Heart failure through the spectrum of reduced (HFrEF), mid-range (or mildly reduced or HFmEF), and preserved ejection fraction (HFpEF), continues to plague patients' quality of life through recurrent admissions and high mortality rates. Despite tremendous innovation in medical therapy, patients continue to experience refractory congestive symptoms due to adverse left ventricular remodeling, significant functional mitral regurgitation (FMR), and right-sided failure symptoms due to significant functional tricuspid regurgitation (FTR). As most of these patients are surgically challenging for open cardiac surgery, the past decade has seen the development and evolution of different percutaneous structural interventions targeted at improving FMR and FTR. There is renewed interest in the sphere of left ventricular restorative devices to effect reverse remodeling and thereby improve effective stroke volume and patient outcomes. For patients suffering from HFpEF, there is still a paucity of disease-modifying effective medical therapies, and these patients continue to have recurrent heart failure exacerbations due to impaired left ventricular relaxation and high filling pressures. Structural therapies involving the implantation of inter-atrial shunt devices to decrease left atrial pressure and the development of implantable devices in the pulmonary artery for real-time hemodynamic monitoring would help redefine treatment and outcomes for patients with HFpEF. Lastly, there is pre-clinical data supportive of soft robotic cardiac sleeves that serve to improve cardiac function, can assist contraction as well as relaxation of the heart, and have the potential to be customized for each patient. In this review, we focus on the role of structural interventions in heart failure as it stands in current clinical practice, evaluate the evidence amassed so far, and review promising structural therapies that may transform the future of heart failure management. Despite tremendous advances in medical therapy and revascularization techniques, heart failure continues to be a growing global epidemic– the prevalence of global heart failure doubled from 33.5 million in 1990 to 64.3 million in 2017 . In thisModerate or severe functional or secondary MR accompanies heart failure in about one-third of the patients and is mediated by mal-coaptation of the valve leaflets due to left ventricular remodeling and dysfunction secondary to ischemic and/or non-ischemic etiologies or due to annular dilatation in patients with long-standing atrial fibrillation or “atrial FMR” , 6. MechNot all mitral valve anatomies are ideal for performing a TEER and hence alternative mitral valve repair strategies are needed. One such device is a self-expandable nitinol ring that can be implanted in the coronary sinus through the right jugular vein– the Carillon™ Mitral Contour System– this device relies on the close relationship between the coronary sinus and the mitral valve annulus to effect an indirect annuloplasty . AdvantaAnother device that targets annular dilatation is a minimally invasive, catheter-delivered direct annuloplasty ring– the Cardioband™ valve reconstruction system (Edwards Lifesciences) . This imWhile these Transcatheter Mitral Valve Repair (TMVr) techniques offer promising results for patients with FMR, some patients have unfavorable mitral valve anatomy  for percutaneous repair and may experience complications or failure with significant residual or recurrent MR despite TMVr . TranscaIn 2005, ~1,600,000 patients were identified to have moderate-severe TR, however, only <8,000 of these patients underwent tricuspid repair or replacement . PrimaryTreatment strategies for Transcatheter Tricuspid Repair (TTVr) include TEER using the Triclip™ (Abbott) and PASCAL™ (Edwards Lifesciences) systems, direct annuloplasty with Cardioband™ (Edwards Lifesciences), Tricinch™ (4Tech Cardio Ltd.), Trialign™  and the Mistral™  device which effects a reduction in TR through grasping and inward pulling of the chordae tendineae . Among tIn patients with large coaptation gaps (>6–8 mm), massive/torrential TR, device-related TR, or prior failed repair with single leaflet detachment, TTVr may not be feasible and this has created the niche for Caval Valve Implantation (CAVI) and Transcatheter Tricuspid Valve Replacement (TTVR). CAVI involves placement of a heterotopic valve in the Inferior Vena Cava and possibly the Superior Vena Cava (SVC) to protect the hepatic and renal circulation by redirecting the TR jet and this modality also improves the forward stroke volume ejected through the right ventricle. CAVI is technically easier than other transcatheter tricuspid therapeutic options and can be easily combined with other modalities as the valve or sub-valvular apparatus are intact. While the initial experience with non-dedicated valves showed a high rate of complications related to device thrombosis and dislocation, the novel dedicated bicaval valves are currently undergoing early feasibility studies  66). Fo. Fo66). In patients with severe Aortic Stenosis (AS) and left ventricular dysfunction or in patients with Continuous-Flow Left Ventricular-Assist Devices (CF-LVAD) who develop moderate or higher degrees of Aortic Insufficiency (AI), the role of transcatheter aortic valve interventions has been growing. In the TOPAS-TAVI registry, 293 patients with low-flow, low-gradient aortic stenosis and depressed ejection fraction were included and patients with severely depressed EF (<30%) had greater improvements in LVEF at 1-year follow-up after Transcatheter Aortic Valve Replacement (TAVR) compared to patients with moderately reduced EF (<40%), irrespective of the presence of contractile reserve with dobutamine stress . Aortic de-novo AI following LVAD implantation– noted in ~15–52% of patients at 1-year post-implant , or replacement with a bio-prosthetic valve. Complete valve closure can be fatal in cases of device malfunction and the potential for myocardial recovery should also be weighed in. Surgical Aortic Valve Replacement (SAVR) at the time of VAD surgery would increase the bypass and aortic cross-clamping times and is associated with worse clinical outcomes in patients with INTERMACS 1 and 2 level heart failure . There i-implant . Moderat-implant . In a ca-implant .® Atrial Shunt) vs. a sham control and significant reduction in pulmonary wedge pressure with exercise was noted in patients treated with device therapy at 1-month follow-up  vs. a sham control in a similar heart failure population failed to show any improvement in heart failure events or heart failure symptoms at 12–24 months follow-up  – these devices are implanted through the femoral veins and trans-septal access and aim to lower the left-atrial pressure with activity thereby improving symptoms and outcomes in patients with HFpEF and HFmEF. REDUCE-LAP HF I was a phase-II randomized trial in patients with symptomatic refractory heart failure (wedge pressure ≥25 mm Hg during exercise) with LVEF>40% and a gradient of ≥5 mm Hg between the left and right atria– patients were randomized to treatment with IASD (Corviaollow-up . Furtherollow-up . Howeverollow-up . Patientollow-up . While C-months) . A modifHF trial . AnotherHF trial .Recently, there has been active research in the development of implant-free Inter-Atrial Shunts– the Alleviant System is one such strategy that creates a shunt using radiofrequency energy-based septectomy that has shown safety and clinical efficacy with patency through 12-months follow-up in the first-in-human clinical study (ALLEVIATE HF-1) . The impImplantable micro-electromechanical-based sensors in the Pulmonary Artery (PA) have been developed to assist in real-time monitoring of cardiac filling pressures to tailor medical therapy and pre-empt a heart failure exacerbation. This is particularly important for patients with HFpEF, where patients are threading a narrow line between hypervolemia and heart failure and hypovolemia and underfilling of the ventricle resulting in hypotension. CHAMPION was a single-blinded randomized controlled trial that showed a clinically meaningful and significant reduction in HF admissions in patients with moderately symptomatic heart failure (New York Heart Association (NYHA) class III HF with a recent admission in the past 12 months) with the use of the wireless PA pressure monitoring using the CardioMEMS™ HF system (Abbott) compared to medical therapy alone. HF admissions were consistently reduced in patients with HFpEF and HFrEF with a significant change in diuretic dosing across the two arms; this effect was apparent after about 3 months of diuretic titration in the treatment arm and persisted up to 17 months of follow-up (50% relative reduction for HFpEF and 26% for HFrEF) . CardioM® (Cardiokinetix) is a catheter-based, self-expanding, umbrella-shaped, partitioning device, that was intended to separate the aneurysmal portion of the LV and create a new apex in patients with ischemic cardiomyopathy. While the first-in-human study (PARACHUTE) in patients with HFrEF (EF 15–40% and an akinetic of dyskinetic apex) showed safety and feasibility, at 3-year follow-up, a reduction in stroke volume and LVEF were noted. This device was subsequently tested in a randomized, controlled trial (PARACHUTE IV) that enrolled 331 subjects with NYHA class III-IV ischemic cardiomyopathy and wall motion abnormalities (EF 15–35%) with suitable anatomy for the device, however, the trial was terminated prematurely in 2017 and this device is not in use currently (® (Ancora Heart Inc.) Ventricular Restoration System– a nitinol anchor-based cinching cable positioned in the LV cavity below the mitral valve through a retrograde transventricular approach. This is still being tested in early feasibility trials in patients with HFrEF or moderate or higher degree of FMR with NYHA class III-IV symptoms despite optimal medical therapy (CorCinch)  . BioVentorCinch) . Based oorCinch) .Cardiac sleeves envisage the use of biomimetic implantable robotic devices for ventricular support in heart failure patients. The sleeves have certain benefits compared to current VAD in clinical practice– they can provide bi-ventricular support, no contact with blood reduces the risk for thrombosis, they can be activated to provide support to the heart during systole as well as diastole, and finally, level of support can be weaned as the native function recovers . These rIn summary, in the last decade, there has been tremendous growth in the development of transcatheter interventions to improve heart failure outcomes. Given the multitude of structural therapies available and the clinical complexity involved in decision-making, the role of team-approach with involvement of the advanced heart failure team, multi-modality cardiac imagers, different medical sub-specialties  and the structural heart team cannot be overstated. Finally, early consideration of structural therapies is paramount to ensure good outcomes before end-organ damage has ensued. The ongoing trials for cardiac robotic sleeves, ventricular restorative devices, implant-free inter-atrial shunts, novel transcatheter mitral and tricuspid valve devices would help shape the future of heart failure management.DK and MM were involved in the planning, execution, writing, and critical appraisal of this manuscript. All authors contributed to the article and approved the submitted version.MM: primary investigatory at University of Miami for Clinical Evaluation of the AccuCinch ventricular restoration system in patients who present with symptomatic heart failure with reduced ejection fraction (HFrEF): the CORCINCH-HF study. The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Rural Indians have higher mortality rates than urban Indians. However, the rural-urban gap in under-five mortality has changed is less researched. This paper aims to assess 1) whether the rural-urban gap in under-five mortality has reduced over time 2) Whether rural children are still experiencing a higher likelihood of death after eliminating the role of other socioeconomic factors 3) What factors are responsible for India’s rural-urban gap in under-five mortality.We used all rounds for National Family Health Survey data for understanding the trend of rural-urban gap in under-five mortality. Using NFHS-2019-21 data, we carried out a binary logistic regression analysis to examine the factors associated with under-five mortality. Fairlie’s decomposition technique was applied to understand the relative contribution of different covariates to the rural–urban gap in under-five mortality.India has witnessed a more than 50% reduction in under-five mortality rate between 1992 and 93 and 2019–21. From 1992 to 93 to 2019–21, the annual decrease in rural and urban under-five mortality is 1.6% and 2.7%, respectively. Yet, rural population still contributes a higher proportion of the under-five deaths. The rural-urban gap in under-five mortality has reduced from 44 per thousand live births in 1992–1993 to 30 per thousand in 2004–2005 which further decreased to 14 per thousand in 2019–2021. There is no disadvantage for the rural children due to their place of residence if they belong to economically well-off household or their mothers are educated. It is wealth index rather than place of residence which determines the under-five mortality. Economic (50.82% contribution) and educational differential (28.57% contribution) are the main reasons for rural-urban under-five mortality gaps.The existing rural-urban gap in under-five mortality suggests that the social and health policies need to be need to reach rural children from poor families and uneducated mothers. This call for attention to ensure that the future programme must emphasize mothers from economically and educationally disadvantaged sections. While there should be more emphasis on equal access to health care facilities by the rural population, there should also be an effort to strengthen the rural economy and quality of education.The online version contains supplementary material available at 10.1186/s12889-022-14436-7. Since 1990, child mortality has been reducing substantially. The worldwide under-five mortality rate has dropped by 60%, from 93 deaths (12.6 million) per 1000 live births in 1990 to 37 deaths (5.0 million) per 1000 live births in 2020 . The odds of dying under age 5 is more than first order birth when the birth interval is less than two years . Whereas this is less than first order birth when the birth interval is more than two years .Maternal education and mass media exposure are positively associated with under-five mortality. Now other backward classes  and other forward caste  are less likely to die groups under age five than the scheduled caste. After controlling other variables, Muslim children have significantly lower odds of under-five mortality compared to Hindu children . Children born to mothers with the richest wealth quintile were less likely to die before age five than those born to the poorer mothers .Compared to the Eastern part of India, other regions  have lower likelihood of under five deaths.Table The present study investigated the changing role of place of residence in under-five mortality. Earlier studies found that under-five mortality gap between rural and urban in India is due to rural-urban disparity in socioeconomic and demographic variables . Our stuHowever, regression analysis shows that rural urban status is a significant factor until when we do not control the role of the wealth index of the household. This indicates that there is no disadvantage for the rural children due to their place of residence if they belong to economically well-off household or their mothers are educated. This is contrast to some previous studies which found that rural children experience higher level mortality even after controlling other socioeconomic and demographic variables . The disDecomposition analysis demonstrates that wealth index and educational attainment of the mothers are the most two important factors which contribute 75% of the total gap in under-five mortality by place of residence. Both are associated with better child care practices. The economic condition of the children’s household is linked to better nutrition and access to health care facilities . Wealth Unequal attainment of maternal education also increased the rural-urban gap in under-five mortality , 27. AccUnequal maternal exposure to mass media has also increased the rural-urban gap in under-five mortality. From the media exposure, a mother can know about the different sanitation practices, usefulness of breastfeeding, proper dietary habits for infants and other healthcare utilization programs –35. In rOur study has one limitation. While our focus is to examine rural-urban gap in under-five mortality, we did not investigate the intra-urban mortality variation. Within urban area, there is wide difference in mortality indicators between slum and non-slum dwellers.Though India has witnessed a considerable decline in rural under-five mortality rate from 1992 to 93 and 2019–21, yet the total number of under-five children’s deaths is huge. The rural population still contributes higher proportion of the deaths. The existing rural-urban gap in under-five mortality suggests that the social and health policies should focus more on the rural areas. Our finding shows that economic and education differential is the main reason for under-five mortality in rural area. This call for attention to ensure that the future programme must lay on emphasis on mother from economically and educationally disadvantageous section. While there should be more emphasis on equal access to health care facilities by the rural population, there should be also effort to strengthen rural economy and quality of education. There is need to strengthen health care services in rural areas by improving the availability of trained human resource, physical infrastructure, medicines, and medical equipment..Additional file 1.


The coronavirus 19 disease (COVID-19) pandemic has led to a renewed focus on end-of-life care. The majority of COVID-19 deaths occur in hospital, with patients cared for by generalists and hospital specialist palliative care teams (HSPCTs). This project aims at exploring the potential influences of HSPCTs on end-of-life care in COVID-19.A retrospective observational study was carried out by exploring four end-of-life care themes in a Scottish hospital population who died from COVID-19. Comparison was made between cohorts seen by HSPCTs versus generalist clinicians.p = 0.02), have a cancer diagnosis , die sooner after admission , and be commenced on a syringe driver . Differences detected across four end-of-life care themes comparing HSPCTs with generalist teams were minimal with documentation and prescribing in keeping with available guidance.Analysis of 119 patients across NHS Greater Glasgow and Clyde (NHSGGC) health board demonstrated that COVID-19 patients seen by HSPCTs were more likely to be younger (median 77 vs. 81 years; Consistencies in end-of-life care observed across NHSGGC cohorts draw attention to the potential wider impact of HSPCT roles, including education, guideline development, and mentoring. Understanding such diverse effects is important to support funding and development of HSPCTs. Further research is required to better quantify the impact and heterogenous influences of HSPCTs in general. Coronavirus 19 disease (COVID-19) has led to increased exposure of generalist clinicians to end-of-life care.Hospital specialist palliative care teams (HSPCTs) provide patient care and a supportive role for generalists.End-of-life care in hospital settings may be safely standardized with the support of HSPCT support.Established palliative care practices appear to be transferrable to COVID-19 disease.Further research is required to quantify the impact of hospital palliative care teams on patient outcomes and generalist care.1 There remains a need for more evidence to support the effectiveness and positive impact of HSPCTs for patients, families, and staff.2 In particular, there is a need for more evidence around HSPCT roles in non-malignant conditions.2 The rapidly changing landscape of hospital end-of-life care (EOLC) that occurred with the coronavirus 19 disease (COVID-19) pandemic provided an opportunity to explore differences in EOLC delivered by hospital generalist teams compared with HSPCTs.A significant proportion of patients in Scotland will have access to hospital specialist palliative care team (HSPCT) review at end-of-life as in-patients.With this in mind, we conducted a retrospective comparative cohort study comparing two cohorts of patients who died from COVID-19 disease in the NHS Greater Glasgow and Clyde (NHSGGC) health board area of Scotland: one cohort looked after by generalist health care professionals and one that received HSPCT review. By comparing four areas of EOLC, this study aims at answering the question:“Do hospitalized patients who die from COVID-19 disease receive different end-of- life care if reviewed by the hospital specialist palliative care team?”A retrospective comparative cohort design was selected to ensure that only hospitalized patients who died with a confirmed positive polymerase chain reaction (SARS-CoV-2 PCR) test were included. Cohorts were divided as follows:Cohort 1: patients who died with COVID-19 disease reviewed by an HSPCTCohort 2: patient who died with COVID-19 disease who were managed by generalist teamsThe EOLC data were collected from a sample of 140 NHSGGC hospital patients who died with COVID-19 between April 1 and April 12, 2020. This timeframe was selected, as it represents a crucial period when NHSGGC hospital admissions reached the peak of the pandemic and COVID-19 EOLC guidance in Scotland had recently been introduced.Inclusion criteria were as follows: (1) patients older than the age of 18 who died in hospital; (2) who had a confirmed +ve SARS-CoV-2 PCR test within 28 days of death; (3) who received face-to-face HSPCT or generalist care at ward level and had complete admission notes and medication prescription charts scanned onto the NHSGGC Portal system.Exclusion criteria were as follows: (1) patients with equivocal SARS-CoV-2 PCR testing or X-ray diagnosis only; (2) patients who died in intensive care units (ICU); or (3) patients with incompletely scanned clinical notes on the NHSGGC Portal system.The HSPCT phone advice was not included in this study. This is not always recorded in the patient's notes and can be difficult to differentiate from other specialty reviews if not identified as HSPCT advice. Patients in ICU and psychiatry settings were excluded due to complexities around obtaining complete patient documentation across different IT systems.Data collection occurred on NHSGGC computer systems using the PORTAL digital patient record platform. Encrypted patient community health index (CHI) numbers were supplied and overseen by a Caldicott Guardian. A data collection tool and protocol were developed using Microsoft Excel and distributed to data collectors to standardize data collection and reduce observer bias.3 A selection of common co-morbidities was included for further analysis. Date and time of death was confirmed using the digitally scanned medical certificate of death.Population data, including age, sex, and source of admission, were collected to build study demographics. Admission date, date of first SARS-CoV-2 +ve PCR, and date of death were included as reference point variables to calculate multiple time indices. The EOLC ward setting was broken down into medical, surgical, care of the elderly (COTE), infectious diseases (ID), and high dependency/coronary care units (HDU/CCU). A standardized assessment of the underlying health of the study population was performed using an online Charlson co-morbidity index (CCI) calculator.4 A synopsis of how each section of the GAEL guidelines relates to the four EOLC themes is provided in Table 1Four EOLC themes were selected based on NHSGGC guidance at end of life (GAEL) advice for health care professionals that outlines important aspects of EOLC.1.Advance care discussion (ACD): the term “advance care discussion” was employed to incorporate documented evidence of the following: (1) a discussion with the patient/relative/power of attorney (POA) relating specifically to the diagnosis of COVID-19 disease, including prognostic implications and treatment options; (2) that may also include exploration of preferred place of care/death  or discussion about escalation to higher levels of care (HDU/ICU) and palliative care approaches.2.Do not attempt cardiopulmonary resuscitation (DNACPR) documentation: evidence of DNACPR discussion was confirmed if both of the following were found: (1) a completed DNACPR form scanned onto PORTAL applicable at time of patient death and (2) documented evidence of a discussion between a senior health care professional and patient/relative/POA about the rationale behind decisions to complete a DNACPR form. Pre-admission DNACPR forms were not included unless a review of this decision was evident in the context of a COVID-19 diagnosis.3.Continuous subcutaneous infusion (CSCI) dosage and timing of initiation before death: the maximum titrated dose (in milligrams) of the following medications in each CSCI was recorded: Morphine; Oxycodone; Alfentanil; Midazolam; Levomepromazine; Haloperidol; and Hyoscine butylbromide. Doses were recorded from CSCI prescription sheets. These are the most commonly used medications for end-of-life symptom relief in NHSGGC. The selection is comparable with other EOLC studies of COVID-19 disease. The start date and time of CSCI were recorded to investigate the timing of CSCI use around patient death.4.As required (PRN) end-of-life symptom medication use: the cumulative dose (in milligrams) administered in the last 48 hours of life for each of the following medications was recorded: Oral Morphine equivalent; Oral Oxycodone equivalent; Alfentanil; Midazolam; Levomepromazine; Haloperidol; and Hyoscine Butylbromide. As both morphine and oxycodone can be given as either oral or subcutaneous doses, both were converted to their oral equivalencies. A ratio of subcutaneous/oral equivalency of 2:1 was used for both.n; %). Interval-ratio variables, descriptive statistics were presented for all interval-ratio variables as median and interquartile ranges (IQRs).Univariate analysis was performed on all data. Frequency counts were generated for nominal and ordinal variables (U (MW) testing was used to test for differences between the cohort data in interval-ratio variables. Pearson Chi-square (CHI2) testing was applied to binary/nominal variables. Both tests were analyzed using 0.05 as the cut-off level of significance.Mann–Whitney IBM SPSS  version 26 was used to perform the statistical tests.Complete data were collected for 119 (85%) of the 140 patients in the sample group. Twenty-one (15%) patients were excluded from final collection. This consisted of eight patients who died in the ICU and 13 who died in a psychiatric setting. There were 46 (38.7%) patients in the HSPCT cohort, with 73 (61.3%) in the general care cohort. Demographics and co-morbidities are summarized in p = 0.02 MW). There was a small predominance of male patients in both cohorts, with a male-to-female ratio of 26:20  in the HSPCT cohort and 48:25  in the general care cohort.The median age of HSPCT patients was lower at 77 years compared with an age of 81 years in those receiving general care (p = 0.55 MW).No statistically significant difference was found in the prevalence of pre-existing patient co-morbidities. The CCI scores were similar between both cohorts with an HSPCT median of 5 and a general care median of 5 (p = 0.01 CHI2). The CCI scores were similar between both cohorts with an HSPCT median of 5 and a general care median of 5 (p = 0.55 MW).Only 14 patients had a confirmed cancer diagnosis, and these patients were more likely to have HSPCT review . Every patient had a DNACPR form in place when they died. DNACPR discussions occurred earlier after admission in patients seen by an HSPCT. The median duration was zero days (day of admission) compared with one day in the general care cohort. This did not meet the criteria for statistical significance (p = 0.06 MW). Full analysis is presented in Documented evidence of an ACD was found in 42 (91.3%) of the HSPCT cohort and 68 (93.2%) of those receiving general care (p < 0.01 CHI2). Maximum CSCI doses reached for each of the seven selected EOLC medications were comparable across both cohorts. Results are presented in A CSCI was commenced in 41 (89.1%) of the patients seen by HSPCTs compared with 31 (42.5%) of those receiving general care  than those receiving generalist care but more likely to be male when compared with pre-pandemic HSPCT cohorts.5–7Patients reviewed by HPSCTs were younger than those cared for by generalist teams. The median age of HSPCT referrals was comparable with a previous study from NHSGGC that reported an increased patient median age during the pandemic compared with their pre-COVID HSPCT cohort (73–76 years).7–9 The comparison of six co-morbidities in this study demonstrated no statistically significant difference in prevalence between cohorts. The prevalence of patients with cancer was low across both cohorts; although HSPCTs still saw the majority of these patients, this is consistent with previous reports.10Co-morbidity levels were similar between cohorts. The HSPCT COVID-19 referral CCI scores were lower than those reported in previous studies.10 It has also been reported that CCI scores in patients with COVID-19 referred to HSPCTs have been lower than pre-pandemic levels.7 The fall in cancer referrals to HSPCTs may account for this finding, as points in the CCI are attributed for cancer diagnoses.A fall in referral rates of patients with cancer to HSPCTs during the pandemic has been consistently reported,10–13 These findings coupled with the low proportion of cancer patients, lower CCI scores, and distribution of co-morbidities presented in this study support previously observed changes in HSPCT patient phenotype during the pandemic.The HSPCT patients died sooner after admission than in the generalized cohort, and the time involved with patient care was even shorter than reported in previous studies (1 day vs. 1.4–2.26 days).14It is possible that the fall in cancer-related referrals was due to less patients with cancer attending hospital as a result of concerns that admission could lead to contracting COVID-19. Most patients in both cohorts were admitted from their own home and died in general medical wards. A higher proportion of patients from care home settings were referred to the HSPCT. There is some indication from this study that COTE teams were less likely to refer patients dying from COVID-19 to HSPCTs. This may be due to familiarity with EOLC management or attributable to reported differences in COVID-19 presentations in advanced age and dementia.Documented evidence of ACDs was widely identified across both cohorts. Discussions took place earlier after admission in patients referred for HSPCT input. It is not possible to attribute this directly to HSPCT intervention though, particularly when most of these discussions took place on the day of admission and the median time to HSPCT referral was two days. All study patients had a DNACPR form in place at the time of their death.Documentation of DNACPR discussion was found in around 91% of patients in both cohorts. DNACPR discussions occurred earlier in the HSPCT cohort, but again it is not possible to attribute this to HSPCT interaction. The time between a PCR +ve result and documentation of these themes was short across both cohorts, suggesting that a COVID-19 diagnosis in itself may have acted as a trigger for discussion.15–17 Despite the patient-centered foundations of these approaches in the context of COVID-19, their communication and methods of form completion have been areas of controversy. The concept of “blanket” DNACPR forms along with media reports about patients or relatives being asked to sign DNACPR orders added complexity to what can already be emotive discussions for all involved.18The benefits of early advance care planning along with DNACPR discussion across most disease states have been widely promoted.19–21In this study, it became apparent that such discussions frequently took place close to the patient's death, often on the same day. Although not formally recorded, the data collection team noted a significant proportion of discussions that had taken place via telephone. The evidence of the impact of such changes in practice during the pandemic on patients, families, and health care professionals themselves is still emerging but does appear to demonstrate increased risk of psychological harm, severe acute grief reactions, and prolonged grief disorder.7 Possible reasons for this difference include familiarity of HSPCTs with their use, recognition of efficacy for managing symptoms, and experience accrued day-to-day addressing COVID-19 symptoms. Clinician observational evidence from prior studies suggests that CSCI use can improve symptom burden in COVID-19; however, there is a lack of empirical outcome measurement and qualitative data in this area.22The use of CSCI medication to control symptoms of COVID-19 at end-of-life was more common in patients reviewed by an HSPCT, and this is consistent with previous studies.24The CSCI medication use in the generalist cohort was also common. Maximum titrated medication doses were similar across both cohorts apart from higher midazolam doses in those reviewed by HSPCTs. The reason for this difference may relate to the severity of HSPCT patient symptoms or familiarity of midazolam use within HSPCTs. The CSCI doses were comparable with the existing literature and safely fell within the National Institute of Clinical Excellence (NICE) guidelines and Scottish Palliative Care Guideline (SPCG) recommendations.The timing of CSCI initiation is important to allow adequate symptom control. The median time between CSCI initiation and death in both cohorts was 26 hours, which indicates that any potential benefits of this administration route would generally have been obtained. The 26 hours mean duration of CSCI delivery before death observed across both cohorts suggests that although statistically significant data demonstrated that patients in the HSPCT cohort died sooner after admission, the use of CSCI medications did not appear to hasten death.24 The HSPCT cohort patients were less likely to require PRN morphine for breathlessness, which may be attributable to the higher doses of midazolam administered via CSCI. Alfentanil is used when patients have significant renal failure or have developed opioid toxicity with other opioids.25 The PRN alfentanil was prescribed more often in HSPCT patients and it may be that knowledge of this drug's applications was more prevalent among these teams.The PRN medication requirements were similar across both cohorts. Doses used were comparable with previous studies and conformed with both SPCG and NICE guidance.23There was no clear influence on PRN requirement related to CSCI use identified but without analyzing sequential changes in patient symptom burden there are no conclusions that can be drawn here. The PRN Oxycodone was required more often when a CSCI was in use, but numbers were small. Oxycodone is the second-line opioid choice in NHSGGC when morphine has not been tolerated.26Prescribing practices in this study observed across both cohorts coupled with the effective pharmacological timing and use of dose ranges within recommendations are important and reassuring findings. The early collaboration of generalists and palliative care specialists in Scotland to produce rapid clinical guidelines for managing symptoms of COVID-19 at end-of-life was potentially a significant driver toward standardizing practice.The HSPCT experience was transposed from pre-pandemic EOLC and combined with real-life clinical experience gained in the early days of the pandemic to produce this guidance. Symptom management recommendations from the SPCG pre-pandemic EOLC work combined with their COVID-19 specific guidance provided NHSGGC clinicians with solid foundations of reference during a time of uncertainty. The authors postulate that HSPCT clinicians working in NHSGGC had an influential role on the overall management of patients dying from COVID-19. This was most likely achieved by extrapolating practice based on previous experience, helping develop COVID-19 specific advice, leading by clinical example on the wards, and signposting to guidance resources.This study presents the first known attempt to explore potential differences in EOLC themes for patients with COVID-19 between HSPCT and generalist delivered care.Evidence is presented to support important themes emerging from previous COVID-19 literature. This includes a change in HSPCT patient co-morbidity, referrals closer to time of death, and shorter periods of HSPCT patient contact. New evidence is presented surrounding the timing and documentation of advance care and DNAPCR discussions in COVID-19.The study presents important evidence that supports the safe and appropriate use of medications to manage end-of-life symptoms in COVID-19. Taken in conjunction with existing evidence, this provides further evidence that previously established palliative care end-of-life practices are transferrable to COVID-19 disease.This study does not include patients who survived to discharge or were admitted to ICU, limiting application to patients who died in a ward setting. Critical care and community settings are under-represented in this study, leaving important contributions of HSPCTs unexplored.This study lacks patient-reported outcome measures and qualitative analysis of patient, relative, and staff experiences. Although it gives insight into the temporality of discussions, support and prescribing it fails to expand on the impact of these themes. There is no exploration of non-pharmacological interventions or oxygen therapy, making it difficult to analyze prescribing data in a robust, holistic manner.This study highlights the need for ongoing research into patient and family experiences of HSPCT compared with generalist care across end-of-life care. Themes that could be expanded include the impact of communication approaches, holistic care, and differences in grief outcomes. We suggest employing patient-reported outcome measures and qualitative analysis to better quantify any observable differences and investigate the “bleed down” effects of HSPCT input on EOLC on other clinical teams.


Clinical trial protocols are the foundation for advancing medical sciences, however, the extraction of accurate and meaningful information from the original clinical trials is very challenging due to the complex and unstructured texts of such documents. Named entity recognition (NER) is a fundamental and necessary step to process and standardize the unstructured text in clinical trials using Natural Language Processing (NLP) techniques.In this study we fine-tuned pre-trained language models to support the NER task on clinical trial eligibility criteria. We systematically investigated four pre-trained contextual embedding models for the biomedical domain  and two models for the open domains (BERT and SpanBERT), for NER tasks using three existing clinical trial eligibility criteria corpora. In addition, we also investigated the feasibility of data augmentation approaches and evaluated their performance.Our evaluation results using tenfold cross-validation show that domain-specific transformer models achieved better performance than the general transformer models, with the best performance obtained by the PubMedBERT model . The data augmentation results show that it is feasible to leverage additional corpora to improve NER performance.Findings from this study not only demonstrate the importance of contextual embeddings trained from domain-specific corpora, but also shed lights on the benefits of leveraging multiple data sources for the challenging NER task in clinical trial eligibility criteria text. Clinical trial protocols define important details about design and execution of clinical trials, which are the foundation for advancing medical sciences. An important section of clinical trials is the eligibility criteria (EC), which is often described in free text and not readily amenable for computer processing . Formal In this study, we proposed to investigate different pre-trained language models  for the NER tasks on EC of clinical trial documents. We systematically compared four biomedical domain-specific pre-trained contextual embedding models , with the goal to promote computerized applications during trial execution . Different methods and tools have been developed for NER tasks that aim to extract key clinical concepts from EC and other sections of clinical trial protocols, including rule-based, machine learning-based, and hybrid methods , 24, 25.In addition, annotated corpora for NER in the EC section of clinical trial protocols have been developed in multiple studies, including 1) EliIE , which c EliIE , The purpose of this study is twofold: (1) we want to systematically examine the performance of different state-of-the-art pre-trained language models  on NER for EC in clinical trial protocols; and (2) we plan to compare NER performance across multiple EC corpora and explore the feasibility of leveraging multiple data sources to improve NER performance in EC.In this study, we included all three corpora listed in Table For Chia, there are two distinct datasets titled With Scopes and Without Scopes describing the inclusion or exclusion of Scope entities. The two datasets differs only in their utilization of Scope entity within the annotation model. We chose the Without Scopes dataset and combined the inclusion and exclusion together for each annotated EC file for our evaluation.This study systematically investigated six state-of-the-art transformer-based language models: two from open domains: BERT and SpanBERT; and four for the biomedical domain: BioBERT, BlueBERT, PubMedBERT, and SciBERT.BERT: A bidirectional deep transformer encoder model pre-trained on general domain corpora using masked language modeling (MLM) and next sentence prediction (NSP). The large model architecture has 24 transformer blocks with a hidden size of 1024 and 16 attention heads. The total number of parameters is 340 million. The model was trained on general English corpus from Wikipedia and BooksCorpus .SpanBERT: A pre-trained transformer model extended BERT by: (1) masking contiguous random spans instead of random tokens, and (2) training the span boundary representations without relying on the individual token representations within it.BioBERT: The first domain-specific BERT based model pre-trained on biomedical corpora. BioBERT was initialized with weights from BERT at first, then pretrained with additional corpus from large biomedical domain (PubMed abstracts and PMC full-text articles). BioBERT utilized WordPiece tokenization  to addreBlueBERT: A pre-trained domain-specific transformer model by continual pretraining of BERT on biomedical and clinical corpora. Similar to BioBERT, BlueBERT was initialized with BERT firstly and then continue to pretrain the model using the large biomedical and clinical domain . The Biomedical Language Understanding Evaluation (BLUE) benchmark evaluated on five tasks with ten corpora shows that the BERT model pre-trained on PubMed abstracts and MIMIC-III clinical notes achieved better performance than most state-of-the-art models.PubMedBERT: A pre-trained domain-specific transformer model by pretraining from scratch on a large biomedical domain. It generated the vocabulary and pre-trained from scratch to extend the uncased BERT Base model over a collection of PubMed abstracts and full PubMed Central articles.SciBERT: A pre-trained domain-specific transformer model by pre-training from scratch on biomedicine and computer science domain. It generated the vocabulary and pre-trained from scratch to extend the cased BERT Base model over a random sample of 1.14 M papers from Semantic Scholar (18% papers from the computer science domain and 82% from PMC).Figure https://huggingface.co/models). All NER models were trained using an NER package developed on the Transformers library implemented by the HuggingFace team [All transformer models were downloaded from the HuggingFace website  was used to train and evaluate the performance of the NER models. Based on the state-of-the-art research in  and our We evaluated the performance of all the transformer-based NER models using both the strict and relaxed micro precision, recall, and F1-score , where sFor the data augmentation experiment, we trained NER models by directly combining additional corpora  with the training set of the Covance corpus and then evaluated their performance on the test set of the Covance corpus.Table Table Table Table In this study, we systematically investigated general and domain-specific pre-trained language models for NER in EC text using three clinical trials corpora. Experimental evaluation shows that the PubMedBERT model achieved the best overall performance in all three corpora among six models. It achieved strict F1-scores of 0.715 and 0.832 on the Covance and EliIE corpora respectively, which were better than previously published results on these corpora . These BERT and SpanBERT were pre-trained using general corpora from English Wikipedia and BooksCorpus. Domain-specific models were built by either continuously fine-tuning on the top of BERT using biomedical corpora  or training language models from scratch using biomedical corpora , thus providing more meaningful and representative word embeddings for downstream domain-specific tasks. As shown in Table A large performance variation was observed among three corpora , and patterns were consistent for all models , which indicates the intrinsic differences among three annotated corpora, including (1) information models ; (2) annotation schemes and guidelines ; (3) sub-domains of samples ; and (4) sample sizes. All models have better performance on the EliIE corpus probably due to that it contains trials from AD only and the types of entities are relatively simple. The low performance of Chia is probably mainly related to its complex and notable non-flat annotation schemes, as it stated that Chia was the first clinical trial corpus with considerable size annotated in a non-flat mode which supported annotations of nesting and disjoint entities . When wep < 0.05, therefore indicating it is worth investigating such data augmentation approaches for NER tasks in clinical trial documents. The reason that adding Chia to Covance did not improve the model performance is probably due to the differences of annotation schemes and guidelines between Covance and Chia. As stated in [Our experiment that directly combined different corpora shows slight improvement when adding EliIE to the training set of Covance, the Wilcoxon rank sum tests show that the improvement is statistically significant with tated in –37.There are limitations in this study. We mainly explored pre-trained language models on the NER tasks only. However, to support downstream applications, modifiers of clinical entities and standard codes of those entities should be identified as well. Therefore, our next step is to explore pre-trained language models on relation extraction tasks  in EC teIn this study, we systematically compared BERT and its variants for NER in clinical trial eligibility criteria text and our results show that the PubMedBERT, which trained domain-specific language models from scratch using PubMed abstracts and full-text articles, achieved the best performance across multiple corpora, although variation among different models is small. However, large performance gaps were observed among different clinical trial corpora, calling for in-depth analysis of variations among different types of clinical trials, so that more generalizable approaches can be developed for all types of trial documents.


Clinical information collected in electronic health records (EHRs) is becoming an essential source to emulate randomized experiments. Since patients do not interact with the healthcare system at random, the longitudinal information in large observational databases must account for irregular visits. Moreover, we need to also account for subject-specific unmeasured confounders which may act as a common cause for treatment assignment mechanism (e.g. glucose-lowering medications) while also influencing the outcome (e.g. Hemoglobin A1c). We used the calibration of longitudinal weights to improve the finite sample properties and to account for subject-specific unmeasured confounders. A Monte Carlo simulation study is conducted to evaluate the performance of calibrated inverse probability estimators using time-dependent treatment assignment and irregular visits with subject-specific unmeasured confounders. The simulation study showed that the longitudinal weights with calibrated restrictions improved the finite sample bias when compared to the stabilized weights. The application of the calibrated weights is demonstrated using the exposure of glucose lowering medications and the longitudinal outcome of Hemoglobin A1c. Our results support the effectiveness of glucose lowering medications in reducing Hemoglobin A1c among type II diabetes patients with elevated glycemic index (The online version contains supplementary material available at 10.1186/s12874-022-01831-2. Prospective randomized experiments are conducted to evaluate the effectiveness of an intervention. However, in the absence of controlled experiments, large data repositories may provide an alternative source to emulate the randomized experiment with the intention to draw causal inference pertaining to the effectiveness of an intervention . LongituPullenayegum and Lim  describeIn the context of longitudinal causal inference, Hernán et al.  considerRegression models may yield biased estimation of longitudinal causal effect of time-varying treatment in the presence of time-varying confounder and treatment-confounder feedback . In partTo our knowledge, the simultaneous existence of treatment-confounder and visit-confounder feedback with unmeasured confounder for each subject in longitudinal settings has not been considered in the causal inference literature. The cumulative-time weights with respect to treatment and visit account for this feedback. Moreover, the treatment weights and visit weights are calibrated to make the non-probability  sample similar to the target population. In this article, we extend the earlier work by Yiu and Su ) in two-n individuals i is denoted as i. In some instances, the index for individual i is suppressed because it is assumed that the random vector for each individual i is drawn independently with respect to other individuals. The cumulative treatment status j. As an example, A framework for longitudinal causal inference is considered for The marginal causal effects of treatment are specified through a parametric marginal structural model with respect to the longitudinal outcome asication) . In the We use the generalized estimating equations with inverse probability weights to obtain an estimate of the marginal treatment effect with respect to time-dependent covariates. We describe the marginal structural model using the score function of weighted generalized estimating equations asThe longitudinal weights with stabilization factor are constructed to account for treatment-confounder and visit-confounder feedback asj given the history Longitudinal causal inference with time-varying treatment use the sequential version of identifiability assumptions: (i) latent sequential exchangeability, (ii) sequential postivity and (iii) sequential consistency. The sequential exchangeability assumption is an extension of conditional exchangeability (or no unmeasured confounding) assumption where the probability of treatment assignment and visit occurrence at We motivate the application of calibrated longitudinal weights to estimate the causal effects of glucose lowering medications on hemoglobin A1c. Calibration has been used in causal inference framework to estimate the average treatment effect when regularizing high-dimensional covariates with lasso penalty , to miniUnder finite longitudinal sample, stabilized inverse probability weights may not remove the associations between time-dependent treatment n errors . The samn errors , while ar columns. The unknown vector of The calibration restrictions are employed on inverse probability weights to make the treatment assignment unassociated with the history of the time-varying covariates at each time interval in the pseudo-population. Yiu and Su  proposedk accumulates over j time intervals. The dependence of treatment In similar spirit to Yiu and Su , the regj. The calibration restrictions are inverted to estimate the values of unknown coefficients In both score Eqs.  and 4),,4), we nThe stabilized inverse probability weights used in the pseudo-likelihood function of marginal structural models tend to satisfy the property of unity mean at each time interval (i.e. jV)=1∀j) . HoweverIn the presence of subject-level unmeasured confounder Kang et al.  assessedWe allow the treatment umptions .Apart from observed dependencies between outcome atisfied . The G-cIn the conditional data generating mechanism, the most recent values for visit feedback , 28. Thementclass2pt{minimThe baseline covariates In the absence of visit (i.e. mentclass2pt{minimScenario 1: absence of irregular visits (i.e. Scenario 2: absence of irregular visits and presence of unmeasured confounder Scenario 3: presence of irregular visits and absence of unmeasured confounder Scenario 4: presence of irregular visits and presence of unmeasured confounder The g-computation formula (in the absence and presence of unmeasured confounder) is used to obtain the true values of marginal treatment effects see  Section.We implemented the constrained optimization of the cumulative-time product weights using the Barzilai-Borwein (BB) method . After tTable The results of the simulation study are presented for the four scenarios in which the presence or absence of irregular visits and time-invariant latent confounder is considered. The results are summarized using the performance metrics of relative bias, MCE, rMSE, coverage probabilities and successful convergence of calibrated weights, as shown in Table We assessed the performance of sIPTW and calibrated IPTW in the absence of irregular visits and unmeasured confounder. An improvement in bias was observed for calibrated IPTW in relation to sIPTW. The MCE and rMSE for calibrated weights was smaller than the stabilized weights, and the coverage probabilities were close to 95% nominal rate. The correlation between stabilized weights and calibrated weights ranged from 0.986 to 0.999. Successful convergence of calibrated weights was observed for all 1,000 replicates.In this scenario, we assessed the performance of sIPTW and calibrated IPTW in the absence of irregular visits, and in the presence of unmeasured confounder. Nominal coverage rates close to 95% were observed for marginal structural models with sIPTW and calibrated IPTW. The calibrated weights had smaller mean bias than stabilized weights. The calibrated weights also had smaller MCE and rMSE than stabilized weights. The correlation between stabilized weights and calibrated weights ranged from 0.929 to 0.999. Successful convergence was observed for 959 out of 1,000 replicates.In this scenario, we assessed the performance of stabilized and calibrated variants of treatment and visit weights in the presence of irregular visits and absence of unmeasured confounder. The coverage probabilities were close to the expected 95% nominal rate for the four estimators: (i) sIPTW, (ii) sIPVW, (iii) joint sIPTW and sIPVW, (iv) and calibrated IPTW and IPVW. Smaller bias was observed for calibrated weights when compared to the stabilized weights. The correlation between stabilized weights and calibrated weights ranged from 0.25 to 0.99, and successful convergence was observed for all 1,000 replicates.In this scenario, we assessed the performance of stabilized and calibrated variants of treatment and visit weights in the presence of irregular visits and unmeasured confounder. The coverage probabilities were close to the expected 95% nominal rate for all estimators. A reduction in bias was observed for calibrated IPTW and IPVW estimators when compared with sIPTW and sIPVW estimators. The correlation between stabilized weights and calibrated weights ranged from 0.24 to 0.99, and successful convergence was recorded for 966 out of 1,000 replicates.Electronic health records (EHRs) can serve as a complete lifetime record of a patient’s longitudinal health trajectory, and they can be collected from different sources including hospitals, specialist clinics, primary care providers, pharmacies, and laboratories. University of Toronto practice based research network (UTOPIAN) collects de-identified patient-level medical information from EHRs of primary care practices across the Greater Toronto region , 31. TheDiabetes is one of the most common chronic conditions in which the body cannot properly use insulin produced by pancreas (Type II). Hemogloblin A1c (HbA1c) is an important glycemic marker to reduce the incidence of diabetes-related complications and mortality . More thWe emulate a randomized experiment using an observational setting, and describe several elements of emulating the target trial in Table We assume the time-varying patient characteristics  as time-dependent confounders. Other glucose lowering medications lsewhere . We incllsewhere .The effectiveness of glucose lowering medications was assessed among diabetes patients who were prescribed SGLT-2i and/or DPP-4i medications during the study period. Longitudinal marginal structural models using generalized estimating equations (AR-1 correlation) with stabilized and calibrated weights were used to generate covariate balance with respect to treatment assignment (i.e. SGLT-2i and DPP-4i medications) and irregular visits. We fitted the following marginal structural model: effects .We describe the effectiveness of glucose lowering medications among diabetes patients with elevated HbA1c  . FurtherIn this article, we proposed calibrated weights to estimate the effect of time-dependent treatment on longitudinal outcomes with irregular visits and with unmeasured confounding. We derived the calibrated restrictions for subject-specific latent confounder which acts as a common cause for treatment and outcome. In our simulation study, the effect of time-varying treatment propagated towards the longitudinal outcome in multiple pathways: (i) direct effect of treatment on outcome, (ii) indirect effect of treatment through the time-varying covariate, (iii) indirect effect of treatment through the irregular visits. The proposed weights created a pseudo-population in which the irregular visits were exogenous (using the visit weights), and in which the treatment groups were exchangeable (using the treatment weights). Marginal structural model with inverse probability weights with respect to treatment accounted for confounding bias in treatment-confounder feedback while the inverse probability weights with respect to irregular visit accounted for selection bias in visit-confounder feedback . An imprSimilar to calibrated weights, Imai and Ratkovic  proposedYoung et al.  discretiIn this article, we made the assumption of sequential positivity with respect to the treatment and irregular visits. Sequential positivity assumption may become implausible in some situations when the clinical profile of a patient precludes them from receiving SGLT-2i or DPP-4i medications, or precludes them from visiting the primary care clinic for some time-intervals. As an extension when the sequential postivity assumption is unrealistic, we may employ doubly robust estimators to reduce bias and imprecision due to large weights. Doubly robust estimators may improve the robustness against model misspecification when either the treatment model or the counterfactual outcome model is misspecified . For exaWe demonstrated the application of calibrated weights to assess the effect of irregular visits and to assess the efficacy of glucose lowering medications (SGLT-2i and DPP-4i) on the longitudinal trajectory of Hemoglobin A1c. The empirical results showed a reduction in mean Hemoglobin A1c with cumulative prescriptions of SGLT-2i and DPP-4i medications using primary care EHRs. These findings support the earlier results from a meta-analysis in which SGLT-2i medications had stronger efficacy than DPP-4i medications . In geneAdditional file 1. Appendix.


Image processing plays a crucial role in maximising diagnostic quality of positron emission tomography (PET) images. Recently, deep learning methods developed across many fields have shown tremendous potential when applied to medical image enhancement, resulting in a rich and rapidly advancing literature surrounding this subject. This review encapsulates methods for integrating deep learning into PET image reconstruction and post-processing for low-dose imaging and resolution enhancement. A brief introduction to conventional image processing techniques in PET is firstly presented. We then review methods which integrate deep learning into the image reconstruction framework as either deep learning-based regularisation or as a fully data-driven mapping from measured signal to images. Deep learning-based post-processing methods for low-dose imaging, temporal resolution enhancement and spatial resolution enhancement are also reviewed. Finally, the challenges associated with applying deep learning to enhance PET images in the clinical setting are discussed and future research directions to address these challenges are presented. Positron emission tomography (PET) is a highly versatile means of measuring physiological processes in vivo as an investigative tool for scientific discovery and a diagnostic tool for clinical patient care. Advancements in PET stem from a diverse range of fields including physics, radio- and biochemistry, materials science, modelling and data science and many medical disciplines, all of which act to cooperatively improve the efficacy of PET. From a data processing standpoint, advancements in PET imaging come from the development of optimal methods for extracting information from measured signals that are pertinent to clinical diagnosis and quantitative accuracy.learned prior information into medical image processing. Cornerstone works in CT and MRI have shown deep learning can produce state-of-the-art performance in areas such as low-dose imaging  trained on clinical data. Whiteley et al. [Zhu et al.  presentey et al.  presenteOther works , 58 whicRegularisation-based deep learning image reconstruction integrates a neural network into the iterative reconstruction framework to constrain the solution with a combination of data consistency and prior information. Retaining the explicit system model helps strengthen the generalisability of the reconstruction algorithm. Recurrent neural networks (RNN)  integrat18F-FDG brain data reconstructed with MR-guided MAP expectation maximisation as ground truth and compared against conventional reconstruction methods and a 3D Unet as post-processing. FBSEM-Net demonstrated comparable performance in enhancing contrast-to-noise ratio, lesion uptake error and normalised RMSE (NRMSE), when trained on synthetic data. Results from FBSEM-Net trained on clinical data 16\docume90Y liver images to minimise the L2 norm between the current iteration estimate and ground truth images, demonstrating better performance than total variation regularisation and non-local means. MAPEM-Net from Gong et al. [18F-FDG PET brain phantoms, producing images with significantly better contrast recovery and noise properties compared to the 3D Unet used for post-processing and standard EM reconstruction with Gaussian blurring. Follow-up work from the original FBSEM-Net [18F-FDG PET brains and compared with deep learning-based post-processing, Tikhonov regularisation, the original FBSEM-Net, and an instance of the block coordinate descent algorithm from Lim et al. [While RNNs conventionally share parameters across all blocks of the network, training parameters unique to each block provides more flexibility in learning an optimal convergence Fig. c. The fig et al.  performsBSEM-Net  implemenm et al.  and demoDeep learning-based low-dose to full-dose image post-processing refers to methods which utilise neural networks to synthesise full-dose images from reconstructed low-dose images as:Deep learning models which require only PET images as an input provide a versatile means to implement low-dose PET post-processing on hybrid or stand-alone PET systems.18F-FDG PET brains to full-dose. They achieved a 200 × dose reduction factor that demonstrated superior PSNR, NRMSE and SSIM as compared to non-local means and 3D block matching. Several subsequent papers further developed the application of neural networks for PET only data. Sanaat et al. [82Rb cardiac PET images. Schaefferkoetter et al. [The first report that demonstrated orders of magnitude of dose reduction with PET only input data by Xu et al.  used a 2t et al.  comparedt et al.  used a Ct et al.  trained 18F-FDG to 68 Ga-DOTATATE and 18F-FMISO demonstrated a reduction in training data required to achieve consistent performance with 68 Ga-DOTATATE and 18F-FMISO networks trained from scratch. Directly applying neural networks trained with FDG images to 18F-Florbetapir images, 18F-FET images and across scanner manufacturers has also demonstrated statistically significant improvements in image quality for dose reduction factors ranging from 2 to 100 [Unsupervised learning and methods which reduce the required number of high-quality training pairs are of interest in data scarce applications and situations where high-quality data is unattainable. The deep image prior (DIP) formulated by Ulyanov et al.  that par2 to 100 . Unsuper18F-FDG scans to full duration scans using data from six sites. Results demonstrated improved lesion quantitation and detectability with radiation dose reductions of 50%. Chaudhari et al. [18F-FDG scans collected across three sites with a dose reduction factor of 4 ×  data, is a critical limiting factor for deep learning-based image processing. In the context of diagnostic imaging, OOD has the potential to produce false readings with potentially dire consequences for patient outcome. Furthermore, as neural networks are often poorly conditioned , it is cNovel methods to improve the generalisability of deep learning models will help facilitate their clinical use. The task-specific nature of deep learning-based methods typically limits their applicability to specific tracers and anatomical regions. Physically justifiable regularisation terms in training, derived from the nature of radiation transport and incorporated into a model of the PET system, may help to ensure physically consistent results for OOD data, without the need for prior assumptions regarding the physiology of a tracer. This approach could lead to the development of deep learning algorithms which generalise beyond a single tracer or anatomical region that would make training and implementation more logistically feasible. Uncertainty estimation methods , 135 canThe availability of high-quality training data is a major limitation in the development of deep learning-based methods. Supervised learning of deep neural networks requires high-quality training data to comprehensively describe the variations in the image features for images drawn from the population to which the network will be applied. In practice, there are several logistical and ethical issues associated with accessing the necessary imaging data and related information. The sensitive nature of medical information poses a problem for collecting comprehensive datasets from many sources for research and commercial development purposes. Anonymised open access medical imaging datasets can help make research feasible for groups without the capabilities to produce data. Researchers are encouraged to make new datasets open access when possible. The risks of shared DICOM metadata being incorrectly anonymised are manageable; however, providing adequate protection against facial recognition software  is more The issue of adequate data availability is more fundamental for applications such as resolution enhancement where the production of high-quality ground truth data is limited by the PET system performance and radiation risks. Unsupervised learning methods may provide a means to utilise deep learning models in such applications. Alternatively, supervised learning with synthetic data may prove useful, with Monte Carlo-based methods capable of accurately modelling the PET acquisition process including physical effects such as scatter and attenuation. Computational power is usually a limiting factor for generating volumetric PET images with Monte Carlo modelling. However, recent work in this field has demonstrated significant gains in computational efficiency , 139 thaAdditional studies to evaluate the performance of deep learning-based methods across multiple sites will be crucial to demonstrate the performance of commercially viable deep learning-based methods. While those works which evaluated performance across sites , 101 shoPositron emission tomography offers a means of measuring physiological processes in vivo and plays an essential and unique role in clinical patient care and scientific research. This review provides an overview of the current state-of-the-art deep learning methods and future research directions in image reconstruction and post-processing for PET image enhancement. The integration of newly developed methods from the field of artificial intelligence into conventional PET image processing will further enhance the breadth of capabilities of PET imaging. Deep learning can be incorporated into image reconstruction as a purely data-driven mapping from raw data to images, or as a regularisation term in combination with conventional data consistency. Post-processing techniques offer a multitude of practical ways to integrate deep learning into image processing frameworks.The ultimate impact of deep learning models on PET image reconstruction and post-processing will depend on whether several key obstacles can be successfully addressed. The generalisability of a neural network to out of distribution data is a critical limiting factor for deep learning-based image processing. Emerging uncertainty estimation methods have the potential to quantify the quality of predictions for OOD data. The lack of high-quality training data is a further major limitation for the development of deep learning-based methods with supervised learning. Unsupervised learning techniques and high-quality synthetic data may help to mitigate this issue. Federated learning offers a means of utilising data across multiple sites without explicit transfer of medical images and the associated risk of loss of patient confidentiality. Although several key challenges exist, it is apparent that deep learning will play a pivotal role in the future of PET imaging.


Wavelength and polarization are two fundamental properties of light within which information can be encoded and (de)multiplexed. While wavelength-selective systems have widely proliferated, polarization-addressable active photonics has not seen notable progress, primarily because tunable and polarization-selective nanostructures have been elusive. Here, we introduce hybridized-active-dielectric (HAD) nanowires to achieve polarization-selective tunability. We then demonstrate the ability to use polarization as a parameter to selectively modulate the conductance of individual nanowires within a multi-nanowire system. By using polarization as the tunable vector, we show matrix-vector multiplication in a nanowire device configuration. While our HAD nanowires use phase-change materials as the active material, this concept is readily generalized to other active materials hybridized with dielectrics and thus has the potential in a broad range of applications from photonic memories and routing to polarization-multiplexed computing. Hybridized-active-dielectric (HAD) nanowires can selectively switch based on polarization of light. Polarization, one of the fundamental properties of electromagnetic waves, provides extra physical dimensions for multiplexing optical information, enabling applications such as multidimensional spectroscopy (Reconfiguration in phase-change photonic devices is commonly achieved by controlling the intensity (2Sb2Te5 (GST), and silicon (Si) acts, for the purposes of this work, as our dielectric. Our active material undergoes reversible switching, and by using the hybridized resonant structure, we can tune the absorption of this active layer based on the polarization. Our prototype devices are composed of thin films of Si/GST as shown in Here, we demonstrate polarization-selective switching in hybridized-active-dielectric (HAD) nanowires, wherein the optical absorption in the nanowires is tuned on the basis of the polarization of input optical pulses. The active material that we use is the phase-change material, GeThe schematics and operational principles are illustrated in The choice of Si and GST arises from the requirement of implementing high-index, low-loss resonators (Si) in close contact with a thin switchable absorber (GST). Incoming free-space electromagnetic waves are coupled to high-index dielectric nanowires to induce polarization-dependent photonic resonances .We proceed to experimentally evaluate the switching characteristics of our devices by monitoring the conductance state of an initially crystalline nanowire electrically. We apply a 1-V bias between the ends of the nanowire and monitor the resulting current through the nanowire using a source meter unit while simultaneously sending nanosecond-polarized optical pulses at 638 nm onto the device through a 0.28–numerical aperture (NA) objective .Tg; ~493 K) and its melting point , while p-polarized illumination  is not able to switch the crystalline states.Two-dimensional (2D) finite element method (FEM) simulation (COMSOL Multiphysics) is used to determine the optimized conditions for pulse illumination. Details are in the Supplementary Materials (figs. S4 and S5) and I) under s-polarized pulses is observed to be several orders larger than for the case of p-polarized pulses, thereby demonstrating the ability to selectively modulate the electrical characteristics of the nanowire based on the polarization of incident light pulses.Time-trace electrical measurements are shown in We then investigate the ability to tune the conductance of the nanowires between multiple levels by a combination of light intensity modulation (figs. S7 and S8) and polarization selection. A half–wave plate (HWP) is used to control the direction of linearly polarized light, and the power calibration curves used as a function of HWP angles are shown in fig. S9. Five pulses (0° to 90°) are sent for four distinct powers (12 to 7 mW) in I∣) as a function of incident power and polarizations. The change of readout current becomes saturated at the top left corner when either laser power or polarization is above the threshold. Below the saturation, the conductance state reached varies as a function of both laser power  and polarization , respectively. These multilevel conductivities can be attributed to the fractional volume of the GST that is switched along the nanowire  process. The above features enable freely accessible multilevels. As shown in On the other hand, we observe linearly accessible levels when the power of the laser is modulated (8.5 to 12 mW) at a fixed polarization . At 45° We now extend the concept of polarization-selective switching to demonstrating multichannel measurements of multiple HAD nanowires. This is done on a device that consists of two nanowires aligned orthogonally to each other  of each nanowire. As shown in We then verify the reconfigurability of polarization demultiplexing by independently encoding distinct weighting coefficients to both nanowires at the same time . We firsNote that, from the above results, our design exhibits active accessibility of micron-scale polarization-division multilevels with decoupled parameters, while the current state-of-the-art metasurface-based polarization-division (de)multiplexing operates in a passive or volatile manner (IT) through nanowire C is the sum of the inputs to nanowires A and B modulated by their relative weighting. In other words, each nanowire is subject to scalar multiplication between electrical input (VA or VB) and the conductivity of the respective nanowire, which behaves as synaptic weights (wA or wB). I′T. We are able to carry out multiple MAC operations by updating the weights deterministically, as shown in I″T and I″′T. These operations can be continued until either the entire active region of GST becomes crystallized or a reset pulse is applied. Although the weights are monotonically increased here, we can use double-step pulses  with input polarization as the tunable vector element. Our results unlock an additional degree of freedom in phase-change photonics and pave the path for a breadth of applications that fully exploit multifaceted properties of light.2 layer to fabricate the patterns for metal electrodes. Cr and Au of 5 and 50 nm thickness were sequentially deposited onto the patterned substrate via thermal evaporation, and a subsequent lift-off process was carried out. A second step of EBL was performed to define the nanowires with widths of ~180 nm and the contacts with sizes of ~10 μm × 15 μm between the prefabricated metal electrodes. The patterned substrate was subjected to another lift-off process, sequentially followed by deposition of GST and Si layers of 15 and 65 nm thickness, respectively, via radio frequency (RF) sputtering system (Nordiko). Both layers of EBLs were done on a positive photoresist (CSAR62). Prior to the measurement, the fabricated devices were placed on a hot plate  to fully crystallize the GST and improve the contact resistances.A first run of standard electron beam lithography (EBL) was performed on doped 525-μm Si wafers with a 330-nm SiOThe electrical and optical measurement of electro-optic cells was acquired using a customized microscope setup with electrical probes, as shown in 2 and Si from substrates are obtained from Palik  to calculate absorption/reflection spectra, electrical field, and absorbed power distribution of hybrid nanowires for a 2D model with a plane wave source. The spectral response of a single-element nanowire was obtained by considering it with excessively large periods . We also perform 2D FEM thermal simulations (COMSOL Multiphysics) to explore the electromagnetic heating of hybrid nanowires under plane-wave illumination by varying polarization directions, laser powers, or pulse duration. The dielectric function for GST and Si from hybrid nanowires was measured from ellipsometry results on a thin film prepared by RF sputtering. Those of SiO


To develop a simple and secure technological solution to incorporate electronic patient-reported outcomes (ePROs) into routine clinical care.A novel ePRO questionnaire delivery system was developed by Software for Specialists (S4S) in partnership with OPAL Rheumatology Australia. Validated questionnaires were sent from the electronic medical record (EMR) (Audit4) of patients with rheumatoid arthritis (RA), psoriatic arthritis (PsA), ankylosing spondylitis (AS), lupus or giant cell arteritis (GCA) and delivered to the patient's email address or completed in the clinic waiting room using a smart device (in-practice). Completed questionnaires were encrypted and returned to the patient's Audit4. Deidentified clinical data was extracted and aggregated across all sites. Data collected between April 2016-Dec 2020 were analysed descriptively.via email and 15% in-practice. Overall, 85% of patients completed at least one questionnaire, and of all questionnaires sent, 73% were completed. Females were more likely to engage with the questionnaires than males (87% vs. 81%), and older patients were slightly more likely to complete all questionnaires delivered.Between April 2016 to Dec 2020, 221,352 Functional Assessment of Chronic Illness Therapy Fatigue (FACIT-F), Patient Health Questionnaire-2 (PHQ-2) and/or HealthCare Resource Utilization (HCRU) questionnaires were sent from 39 of 42 contributing clinics (93%). 85% of questionnaires were delivered The novel Audit4 ePRO delivery system is an effective tool for incorporating PROs into routine clinical care. The data generated provides a unique opportunity to understand the full burden of disease for patients in the real-world setting and the impact of interventions. Reducing clinical disease activity to very low levels or remission for inflammatory arthropathies such as rheumatoid arthritis (RA), psoriatic arthritis (PsA) and ankylosing spondylitis (AS) is now possible with the availability of highly effective biologic and targeted synthetic disease modifying anti-rheumatic drugs (b/tsDMARDs) –3. DespiRegistry studies and clinical trials are increasingly incorporating PROs to measure the full burden of disease and better understand the effectiveness and value of medicines , 6. The Further compounding these challenges, 80% of rheumatologists in Australia are practising in small independent community clinics without an overarching administrative structure so there is limited capacity for clinicians to develop and implement innovative clinical tools to enhance care at a scale that is economical. In 2009, the Optimising Patient outcomes in Australian rheumatology (OPAL)-Quality Use of Medicines Initiative (QUMI) was established to collate clinical data from rheumatologists distributed around Australia to allow large scale outcomes research to be conducted within the unique Australian rheumatology setting. A bespoke electronic medical record  was customised for rheumatologists contributing to OPAL in partnership with software company Software4Specialists Pty Ltd (S4S) to capture comprehensive clinical data at the point-of-care which could be regularly deidentified, extracted and aggregated across all sites to create the OPAL Dataset. This EMR is now used by 111 rheumatologists (approximately 1 in 3) around Australia, predominately in private clinics .In 2015, OPAL and S4S developed technology to seamlessly integrate electronic PROs (ePRO) into the routine consultation by delivering questionnaires to the patient through the EMR, and completed questionnaires are returned securely to the patient's EMR for review at the next consultation. This paper briefly describes real-world patient engagement with this technology by assessing the demographics and completion rates of Functional assessment of Chronic illness Therapy Fatigue (FACIT-F), Patient Health Questionnaire-2 (PHQ-2), and Health Care Resource Utilization (HCRU) questionnaires delivered using this technology as part of routine clinical care.A novel ePRO questionnaire delivery system was developed by Software4Specialists Pty Ltd (S4S) in partnership with OPAL Rheumatology. Validated PRO questionnaires were sent from the patient's EMR  and delivered to the patient's email address at time intervals specified by the rheumatologist (defaults to quarterly) or completed in the clinic waiting room prior to the consultation using a tablet or the patient's smart phone (in-practice). Both options of delivery (email or in-practice) were available, and the rheumatologists could choose the delivery method most suitable for them and their patient. Completed questionnaires were encrypted and returned directly to the patient's Audit4 EMR held on the clinician's server for review at the next clinical consultation . The linSending of ePRO questionnaires was at the discretion of the treating rheumatologist in consultation with the patient and completion of the questionnaire by the patient was voluntary. All adult patients with a physician diagnosis of RA, AS, PsA lupus or GCA were included in the analysis if they were sent at least one FACIT-F, HCRU or PHQ-2 questionnaire between April 2016–December 2020. Patient demographics  and diagnosis were analysed descriptively against the status  of each questionnaire activated.https://www.facit.org/measures/FACIT-Fatigue.This study focused on describing the demographics and completion rates of three questionnaires, the FACIT-F, PHQ-2 and the HCRU. The FACIT-fatigue is a validated, commonly used, 13-item measure of fatigue. Questions are scored on a 0–4 response scale, ranging from “Not at all” to “Very much so”. The over-all fatigue score can range between 0 and 52 with higher scores representing less fatigue , 16. TheThe PHQ-2 is a brief, two-question questionnaire adapted from the PHQ-9. It is a validated measure, intended to be used as an initial screening for major depression. The PHQ-2 asks the patient about the frequency of depressed mood and anhedonia over the past two weeks and identifies individuals who require additional evaluation. It does not determine whether a patient meets the criteria for a depressive order –19. The The HCRU questionnaire asked about medical events and treatments experienced by the patient in the 3 months prior. The questions focused on visits to doctors or nurses, emergency department visits, hospitalisations, outpatient procedures, visits to allied health practitioners and alternative health practitioners  Human Research Ethics Committee (HREC), based on a patient opt-out arrangement (HC17799). All analyses were performed using R version 4.0.2.Between April 2016-Dec 2020, 221,352 questionnaires  were sent from 39 of 42 contributing clinics (93%) to patients with a physician diagnosis of RA, AS, PsA, lupus or giant cell arteritis (GCA) . The genvia email and 15% were completed in-practice. Overall, 85% of patients completed at least one FACIT-F, PHQ-2 or HCRU questionnaire (via email (The majority (85%) of FACIT-F, HCRU and PHQ-2 questionnaires were delivered to the patient ionnaire . 73% of ia email . Importaia email .The longitudinal completion pattern for patients in each PRO dataset is shown in When the completion method for patients in each PRO dataset was assessed longitudinally, most age groups (80 years and under) were found to be more likely to complete all FACIT-F, PHQ-2 or HCRU questionnaires that were sent by email, although individuals 80 years and older, were more likely to complete all in practice. No meaningful differences in the completion methods were seen between males and females .The data presented here reflects the real-world use of ePROs in routine clinical practice. The results demonstrate high engagement and completion rates of ePROs by patients with common rheumatological diagnoses across all age categories. Importantly, this high completion rate was also sustained over time and many patients had completed multiple ePRO questionnaires. This is important as it allows the treating rheumatologist to track their patient's PRO measures longitudinally and monitor improvement. The high engagement rates reported here are not surprising considering the positive effect PROs reportedly have on the patient-clinician relationship. In a qualitative study investigating perspectives of patients with RA on PRO data collection, patients expressed their interest in PRO measures and desire for greater involvement in the management of their disease . In addiThe development of an ePRO system that can be emailed to the patient for them to complete at home in their own time is a major advantage of the Audit4 software. A study that investigated patients preference for PRO collection found that patients prefer entering ePRO data at home . This reThe rise of technology to facilitate healthcare holds great potential to improve patient outcomes in an efficient and patient-centered manner. Despite the shift towards digital health, ePROs have not been widely implemented in routine clinical care. In a recent study conducted in Germany, the main reasons cited by rheumatologists for not implementing ePROs was the absence of suitable software, and the difficulties and high costs associated with implementing innovative software solutions . As suchThe decision to utilise the ePRO technology, and which patients they were sent to, was at the discretion of the rheumatologist resulting in possible selection bias which was not addressed in the current study. In addition, self -reported questionnaires are at risk of misinterpretation and bias due to inaccurate recall and social desirability which may impact the validity of results . For thiDue to the successful integration and real-world utilisation of the Audit4 ePRO system, important patient reported quality of life data is being captured within the OPAL dataset and available for future research questions. A follow-on study would be to describe the levels of fatigue, mood disturbance and healthcare resource utilisation in our cohort of RA, AS, PsA GCA and lupus patients. The relationship between PRO measures and the traditional clinical disease activity measures as well as investigating the impact ePROs have on patient outcomes are also questions needing further investigation.


Natural products continue to be a major inspiration and untapped resource for bioactive drug leads/probes. Natural products (NPs) or biologically inspired NPs account for approximately 24% of currently approved drugs . ConcernStreptomyces sp. isolate B1848. The chemical structures of these compounds were elucidated by NMR , HRMS, comparison with related compounds and computer-assisted methods. The cytotoxic activity of the isolated mansouramycins has been evaluated in a panel of up to 36 tumor cell lines, indicating significant cytotoxicity and good tumor selectivity for the new isolated compound mansouramycin F [Shaaban et al. reported the isolation and structural identification of three new isoquinolinequinone derivatives (mansouramycins E–G) in addition to the previously reported known compounds mansouramycins A and D from the ethyl acetate extract of the marine-derived  NMR 1D, D, HRMS, Penicillium sp. KFD28. The structures of the new compounds were elucidated extensively by NMR, HRMS data analyses and ECD calculations. Penerpene N represents the second example of paxilline-type indole diterpene bearing a 1,3-dioxepane ring. Three compounds  were found to be cytotoxic to cancer cell lines, of which the known compound, epipaxilline, was the most active and showed cytotoxic activity against the human liver cancer cell line BeL-7402 with an IC50 value of 5.3 μM. Moreover, six compounds, namely paxilline, 7-hydroxyl-13-dehydroxypaxilline, 7-hydroxypaxilline-13-ene, 4a-demethylpaspaline-4a-carboxylic acid, PC-M6 and emindole SB, showed antibacterial activities against Staphylococcus aureus ATCC 6538 and Bacillus subtilis ATCC 6633 [Four new cytotoxic indole-diterpenoids (penerpenes K-N), along with twelve other known compounds, have been discovered by Dai et al. from the fermentation broth produced by adding L-tryptophan to the culture medium of Penicillium griseofulvum. The structure of viridicatol was established by NMR and X-ray diffraction analysis. In the in vivo biological investigation of allergic reaction treatments in a mouse model study, viridicatol was found to amilorate the inflammatory mediator, stabalized the mast cell elivation of anaphylaxis and repaired the intestinal barrier in mice by suppressing mast cell activation [Shu et al. discovered viridicatol as a lead derivative for allergic diseases treatments. Viridicatol is a new quinoline alkaloid derivative purified from the deep-sea-derived fungus tivation .A. baumannii. Two Streptomyces strains (M22 and H37) were rapidly prioritized for producing potentially new compounds. The scale-up fermentation of Streptomyces sp. M22 afforded two new trioxacarcins with keto-reduced trioxacarcinose B, gutingimycin B and trioxacarcin G, together with the known gutingimycin [The study by Lu et al. explored an example of how new strategies could accelerate the discovery of new antibiotics from highly productive natural sources. This article focused on an integrated strategy of combining phylogenetic data and bioactivity tests with a metabolomics-based dereplication approach to fast track the selection process of Mangrove actinomycetia for the discovery of novel biologically active natural products. Metabolomics technologies have been utilized to considerably aid traditional antibiotic discovery approaches in strain prioritization, resulting in increased efficiency in the discovery of new antibiotics from these highly productive and diverse ecosystems. It is a great example of using non-traditional bioactivity and/or taxonomy-based dereplication methods for the selection of new microbial strains for future natural product discoveries. In this study, a total of 521 actinomycetial strains affiliated to 40 genera in 23 families were isolated from 13 different mangrove soil samples by a culture-dependent method. A total of 179 strains affiliated to 40 different genera with unique colony morphology were selected to evaluate antibacterial activity against 12 indicator bacteria. Out of the 179 tested isolates, 47 showed activity against at least one of the tested pathogens. An analysis of 23 out of 47 active isolates using UPLC-HRMS-PCA revealed 6 outliers. Further analysis using the OPLS-DA model identified five compounds from two outliers contributing to bioactivities against drug-sensitive SARS-CoV-2 (severe acute respiratory syndrome coronavirus-2) is a novel coronavirus strain that emerged at the end of 2019 and has resulted in millions of deaths so far. Marine sulfated polysaccharides (MSPs) are a group of natural products that have been reported from a variety of marine sources. They have recently gained significant attention and are widely examined against a variety of viral diseases. Salih et al. presented a comprehensive report and modeling analysis on marine sulfated polysaccharides from different marine sources as potential antiviral medicines, with an emphasis on SARS CoV-2. They aimed to compile a thorough report on MSPs and their antiviral activities against diverse virus species based on studies published over the last 25 years. The reported MSPs were subjected to molecular docking and dynamic simulation experiments, and it was found that nine of the investigated MSPs candidates exhibited promising results, taking into consideration the newly emerged SARS CoV-2 variants, of which five were not previously reported to exert antiviral activity against SARS CoV-2, including sulfated galactofucan, sulfated polymannuroguluronate (SPMG), sulfated mannan, sulfated heterorhamnan and chondroitin sulfate E (CS-E). These promising results shed light on the importance of sulfated polysaccharides as potential SARS-CoV-2 inhibitors .Chlorella vulagaris lipases with different cellular localizations has been reported in the current study. Membrane-associated lipases were also detected and described in the article for the first time in this species. The 14 lipases display an acyl hydrolase motif (GXSXG) and belong to the α/β hydrolase lipase 3 family and the GX class. These putative lipases could be potential candidates for metabolic engineering to improve microalgae lipid productivity. Finally, the authors of this manuscript have also reported, for the first time, a putative lysosomal acid lipase produced by a green microalgae [An original article by Ben Hlima et al. focused on the discovery of new-lipolytic enzymes of biotechnological interest from microalgae with the aid of genomic mining by combining bioinformatics analysis and functional screening to find novel lipases biocatalysts. The in silico characterization of 14 putative croalgae .Lei Chen et al. provided a comprehensive review of natural products from microorganisms associated with sea cucumbers. Sea cucumbers are a class of marine invertebrates that are extensively used as a source of food in Asian cuisines and have reported pharmacological activities. Numerous microorganisms have been associated with sea cucumbers. Seventy-eight genera of bacteria belonging to forty-seven families in four phyla and twenty-nine genera of fungi belonging to twenty four families in the phylum Ascomycota have been cultured from sea cucumbers. Sea-cucumber-associated microorganisms produce diverse secondary metabolites with various biological activities, including cytotoxic, antimicrobial, enzyme-inhibiting and antiangiogenic activities. In this review, the authors have summarized the list of 145 natural products isolated from microorganisms associated with sea cucumbers between 2000 and 2021, which include polyketides, alkaloids and terpenoids as well as their reported biological activities .Co-cultivation is one of the strategies used for drug discovery and has been known as an effective approach for the enhancement of the production of natural products from microorganisms. Jianwei Chen at al. provided a comprehensive review on the structural diversity of marine microbial metabolites based on the co-culture strategy. As reported by the authors, co-culturing of two or more marine microorganisms together in a solid or liquid medium in a certain environment can activate silent biosynthetic genes to produce cryptic natural products that do not exist in monocultures of the partner microbes based on either their competition or synergetic relationship. This review article by Chen et al. focuses on the significant and excellent examples covering sources, types, structures and the bioactivities of secondary metabolites based on the co-cultures of marine-derived microorganisms from 2009 to 2019. They have summarized 154 phytomolecules reported to be produced by the marine microorganism co-culture with examples of novel and bioactive natural products. They have also provided a detailed discussion on the prospects and current challenges in the field of co-culture approaches [In summary, the research articles on the topic presented in this Special Issue reveal the potential of marine microorganisms and microalgae as the treasure house of new drug development in the future. The research articles illustrate the diversity of marine microbial natural products and their biological activities and highlight the importance of developing new methods to encourage the discovery of new compounds.