Cancer is associated with excess morbidity and mortality from coronavirus disease 2019 (COVID-19) following infection by the novel pandemic coronavirus SARS-CoV-2. Vaccinations against SARS-CoV-2 have been rapidly developed and proved highly effective in reducing the incidence of severe COVID-19 in clinical trials of healthy populations. However, patients with cancer were excluded from pivotal clinical trials. Early data suggest that vaccine response is less robust in patients with immunosuppressive conditions or treatments, while toxicity and acceptability of COVID-19 vaccines in the cancer population is unknown. Unanswered questions remain about the impact of various cancer characteristics  on serological response to and safety of COVID-19 vaccinations. Furthermore, as the virus and disease manifestations evolve, ongoing data is required to address the impact of new variants.SerOzNET is a prospective observational study of adults and children with cancer undergoing routine SARS-CoV-2 vaccination in Australia. Peripheral blood will be collected and processed at five timepoints (one pre-vaccination and four post-vaccination) for analysis of serologic responses to vaccine and exploration of T-cell immune correlates. Cohorts include: solid organ cancer (SOC) or haematological malignancy (HM) patients currently receiving (1) chemotherapy, (2) immune checkpoint inhibitors (3) hormonal or targeted therapy; (4) patients who completed chemotherapy within 6–12 months of vaccination; (5) HM patients with conditions associated with hypogammaglobulinaemia or immunocompromise; (6) SOC or HM patients with allergy to PEG or polysorbate 80. Data from healthy controls already enrolled on several parallel studies with comparable time points will be used for comparison. For children, patients with current or prior cancer who have not received recent systemic therapy will act as controls. Standardised scales for quality-of-life assessment, patient-reported toxicity and vaccine hesitancy will be obtained.The SerOzNET study was commenced in June 2021 to prospectively study immune correlates of vaccination in specific cancer cohorts. The high proportion of the Australian population naïve to COVID-19 infection and vaccination at study commencement has allowed a unique window of opportunity to study vaccine-related immunity. Quality of life and patient-reported adverse events have not yet been reported in detail post-vaccination for cancer patients.Trial registration This trial is registered on the Australia New Zealand Clinical Trials Registry (ANZCTR) ACTRN12621001004853. Submitted for registration 25 June 2021. Registered 30 July 2021 (Retrospectively registered). https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=382281&isReview=trueThe online version contains supplementary material available at 10.1186/s12879-021-07019-1. More than 18 months into the COVID-19 pandemic, major social and economic disruption has occurred worldwide. To date, more than 4.7 million people globally have died from COVID-19 disease and more than 230 million have been infected  have been demonstrated in early-phase trials of leading COVID-19 vaccines , 29. ImpTo date, there are no published data regarding the outcome of COVID-19 vaccination for children with cancer. In the healthy clinical trial population who underwent vaccination with the BNT162b2 vaccine, neutralising antibody titres in children aged 12–15 years were higher than seen in young adults aged 16–25 receiving the same vaccine . It is uPublished data have not shown any increase in toxicity in cancer patients compared with healthy controls. In fact, Monin et al. showed reduced toxicity rates in patients, potentially related to the lower immunogenicity of the vaccines in this cohort . There hThere are some potential safety concerns with vaccination in patients sensitised to polyethylene glycol  and polysorbate 80 (present in ChAdOx1-S). These excipients are found in many common cancer treatments and cancer patients sensitised to these agents with prior allergic reactions may be at higher risk of vaccine-related adverse effects , 35.There is to date no published data on quality of life related to vaccination, which could potentially deteriorate due to adverse effects or improve due to less requirement for social isolation.Since the onset of the COVID-19 pandemic in early 2020, Australia has imposed strict suppression measures to eliminate community transmission of COVID-19 . As a reThere remain significant unknowns regarding the response of cancer patients to the COVID-19 vaccine. In particular, in studies in Europe and the USA with relatively high background rates of COVID-19, the rollout of vaccination has been rapid. This has limited the ability to enrol large cohorts of cancer patients naïve to both COVID-19 infection and vaccination into studies of vaccine safety and immune response. Published studies to date have been in the context of rapid responses to unfolding events with pragmatic eligibility criteria; these studies have therefore included patients with heterogeneous clinical characteristics (related to both diagnosis and treatment) and have lacked the power to dissect contributing factors which might influence vaccine response such as treatment modality. Some have been unable to include a baseline blood sample due to rapid vaccine rollout, and others have had fragmented follow up due to repeated COVID-19 lockdowns and health service disruption.Our study, SerOzNET, seeks to provide a comprehensive, prospective observational cohort of patients with baseline health status and blood tests collected, divided into balanced cohorts on different cancer therapies of interest. SerOzNET will enrol patients from a population with a very low rate of prior COVID-19 infection, and to date a low rate of COVID-19 vaccination. This will better inform clinicians in future regarding immune protection and safety of vaccines against COVID-19 in this vulnerable patient group.The SerOzNET study objective is to characterise the response of patients with cancer, including children, to the currently available COVID-19 vaccinations in Australia. The aims of the study are to evaluate serologic and immunological responses to COVID-19 vaccination in predefined cohorts of patients with cancer in Australia, to evaluate short- and medium-term safety of COVID-19 vaccination in patients with cancer, and to evaluate the effect of COVID-19 vaccination on patient-reported quality of life.SerOzNET is a multi-arm, multi-centre, prospective, observational cohort study of patients with cancer undergoing routine COVID-19 vaccination. Control samples will be provided by healthy controls enrolled on concurrent, separate studies with collaborating investigators, with blood tests taken at harmonised time points for comparison. Time points for sampling have also been harmonised with the publicly shared “SeroNet” protocol template released by the United States National Cancer Institute (NCI) to allow international comparisons . To provThe anamnestic humoral response to COVID-19 vaccine is likely to be blunted in cancer patients due to immunosuppression arising from their disease and/or treatment.The T-lymphocyte-mediated vaccine response may also be modulated due to disease and treatment factors, with the impact of contemporary treatments such as immune checkpoint inhibitors of particular interest.The adverse event profile may differ in cancer patients compared with the non-cancer population and therefore the impact of vaccine administration on quality of life of cancer patients is unknown.Hypotheses:The endpoints of SerOzNET relate to these hypotheses. The core primary endpoint is seroconversion rate following COVID-19 vaccine in each cohort compared with healthy controls at 1 month post second dose. Co-primary endpoints are translational research into immune correlates of COVID-19 vaccine in each of the cancer cohorts compared with healthy controls  and assessment of patient-reported and medically determined adverse effects and quality of life following vaccination. Secondary endpoints include exploratory analysis of further immunologic parameters to characterise vaccine response and investigation of durability and kinetics of response in the months post vaccination.The SerOzNET lead study site is an outer-urban hospital in south-east Melbourne, Victoria with a large oncology department located over several campuses serving a culturally and linguistically diverse population. Patients will be approached during the course of their routine cancer care by a member of their care team ; further study advertisement will be via posters in waiting rooms and day treatment units which can facilitate self-referral. COVID-19 vaccination  will occur at either a state-run site or local general practice according to availability and is not administered as part of the study itself: this approach was chosen so as to not complicate the running of the vaccine clinics or present confusion about responsibility for management of any acute toxicities. Study participants will attend the lead site at several timepoints relative to their COVID-19 vaccine for biospecimen collection. Surveys and scales for patient-reported quality of life and adverse events will be offered to patients preferably via email or SMS to complete remotely or via tablet while on-site, but for those without internet access paper surveys will be given.Healthy controls are enrolled on parallel studies with collaborating investigators. Timepoints for blood collection and planned assays have been harmonised with the healthy control studies to allow direct comparison of outcome.SOC or HM patients currently on cytotoxic chemotherapy.SOC or HM patients currently on immunotherapy (immune checkpoint inhibitors).(3a) SOC patients currently on systemic therapy which is not traditionally considered immunosuppressive .(3b) Children with current or previous cancer treated only with radiotherapy, surgery, or surveillance.Patients entering survivorship after having completed a course of cytotoxic chemotherapy between 6 and 12 months ago.Patients with haematological malignancies characterised by hypogammaglobulinaemia or immunocompromise, such as multiple myeloma, CLL and low-grade lymphoma.Patients with prior allergic reactions to PEG or polysorbate-80 containing compounds .Participants are current patients of our health service (or at collaborating cancer services). The cohorts to be enrolled are:Up to 100 participants will be enrolled to each arm.Age 12 years or older.Cancer diagnosis and treatment fitting one of the above study cohorts.Have not yet received a dose of COVID-19 vaccine, and eligible for vaccination as per current Australian government guidelines.Inclusion criteria are deliberately broad to allow enrolment of large representative cohorts:Unfit for serial blood collection .Unable to consent, or parent or guardian unable to consent in the case of a patient < 18 years.Estimated survival less than 12 months.Exclusion criteria:This study is observational and vaccine administration will be carried out through the usual channels  and not as part of the SerOzNET study itself. Participants will receive a standard-of-care COVID-19 vaccination supplied by the Australian government. The currently available products in Australia are the BNT162b2 (Pfizer) vaccine, and the ChAdOx1-S (Astra Zeneca) vaccine. The mRNA-1273 (Moderna) vaccine has recently become available and may also be incorporated into the study. As part of SerOzNET, administrative support is offered to participants to schedule and book their vaccination appointment when required.Detailed demographic information will be collected at baseline. Cancer diagnosis and treatment details will be recorded. The full list of common data elements to be collected is included in Additional file Sample collection for serologic and immunologic analysis will be performed at timepoints shown in Table Vaccine hesitancy will be collected at the time of enrolment using the Oxford COVID-19 Vaccine Confidence and Complacency Scale . QualityApart from patient-reported outcomes, a medical review of records 3 months after the second dose of vaccine will be conducted to capture any serious adverse events as well as adverse events of interest . The database entry fields for this are presented in Additional file Serum and PBMCs will be used for a number of core analyses. Participants will be invited to consent during the SerOzNET participant consent process to the storage of excess biospecimens after these core analyses are complete, for later exploratory analyses to be guided by preliminary results from our study and evolving understanding of COVID-19 immunity worldwide.Core analyses will comprise qualitative and quantitative serologic assays and T-lymphocyte immune cell assessment. Serologic neutralisation assays against clinically relevant variants of COVID-19 and immunochemical testing will be performed to detect the presence and titre of anti-SARS-CoV-2 spike protein as previously published, which is correlated with early post-vaccine protection against symptomatic COVID-19 infection , 46. VarImmune cell assessment of T-lymphocyte function derived from PBMC fraction will comprise phenotypic analyses of peripheral T cell subsets and functional assays to measure cytokine production  and cytThe sample size of 100 per cohort will have over 80% power (β of 0.80) to detect a decrease of 10% seroconversion rate in any cancer cohort (compared with assumed non-cancer population incidence of 95%) with 95% confidence (α of 0.05). T-lymphocyte correlates of vaccine response are less well-defined than the expected seroconversion rate, therefore this analysis has not been subject to formal statistical planning and comparison between groups via t-tests or analysis of variance will be for the purpose of hypothesis generation, with significant results deemed to be p < 0.05. Patient reported and medically reported toxicity will be analysed descriptively. Patient-reported quality of life will be analysed longitudinally.This protocol was submitted to the Monash Health Human Research Ethics Committee (HREC) on 26 May 2021, and the amended final version (2.0) was approved on 22 June 2021. The trial was submitted for registration with the Australian New Zealand Clinical Trials Registry (registration number ACTRN12621001004853) in June 2021 prior to enrolment of first participant, with registration number granted on 30 July 2021. The first patient was enrolled on 25 June 2021. Recruitment is ongoing.There are significant gaps in our understanding of immune response to COVID-19 vaccines in patients with different types and stages of cancer, and on various anti-cancer therapies, leaving uncertainty regarding both efficacy (including longevity of response) and safety. A further notable gap in the current literature relates to COVID-19 vaccine responses in paediatric cancer patients. This Australian study seeks to explore how adults and children with cancer respond to the COVID-19 vaccines both quantitatively  and qualitatively through assessment of patient-reported measures. In addition, it also seeks to understand whether treatments generally thought not to affect the immune system  or to have had transient impact  might influence vaccine efficacy. Furthermore, the study will link patient and physician reported toxicity and quality of life data. All of the findings are likely to influence clinical practice regarding timing and potentially type of vaccinations and booster doses in future.We also seek to provide more detailed safety information regarding COVID-19 vaccination in this vulnerable group, to better inform the cancer patient population and hopefully provide reassurance to those with vaccine hesitancy. Our Australian population has had limited COVID-19 exposure in the community which has led to a perceived lack of risk of future COVID-19 infection, and subsequent reduced acceptance of potential vaccine side effects. More detailed information regarding safety in the cancer population could help address patient anxiety about vaccination while on cancer therapy.An unintended benefit of our study to date has been the ability to facilitate COVID-19 vaccination for our vulnerable cohort, through both access to oncologists in the study team to provide counsel regarding vaccination, and practical assistance with vaccination bookings. We will further explore the rate of participants requiring assistance as we continue to recruit and publish this data to inform service provision in future.Overall, we seek to add to the understanding of COVID-19 vaccination for our patient group, to better inform physicians and patients regarding preventive health care during the ongoing pandemic.Additional file 1: Appendix S1. Common data element collection for SerOzNET.Additional file 2: Appendix S2. Biospecimen handling.Additional file 3: Appendix S3. SerOzNET Patient Reported Outcomes Common Terminology Criteria for Adverse Events: PRO-CTCAE.


Pulmonary fibrosis (PF) is a lung disease that may cause impaired gas exchange and respiratory failure while being difficult to treat. Rapid, sensitive, and accurate detection of lung tissue and cell changes is essential for the effective diagnosis and treatment of PF. Currently, the commonly-used high-resolution computed tomography (HRCT) imaging has been challenging to distinguish early PF from other pathological processes in the lung structure. Magnetic resonance imaging (MRI) using hyperpolarized gases is hampered by the higher cost to become a routine diagnostic tool. As a result, the development of new PF imaging technologies may be a promising solution. Here, we summarize and discuss recent advances in fluorescence imaging as a talented optical technique for the diagnosis and evaluation of PF, including collagen imaging, oxidative stress, inflammation, and PF-related biomarkers. The design strategies of the probes for fluorescence imaging  of PF are briefly described, which can provide new ideas for the future PF-related imaging research. It is hoped that this review will promote the translation of fluorescence imaging into a clinically usable assay in PF. As a chronically progressive disease, pulmonary fibrosis (PF) features activation of myofibroblasts and subsequent deposition of large amounts of extracellular matrix, leading to the impaired gas exchange and the increased risk of respiratory failure . In partCurrently, PF is primarily diagnosed by high-resolution computed tomography (HRCT) imaging . HoweverFluorescence imaging is based on the detection of electromagnetic radiation in the ultraviolet–visible–near-infrared (UV–Vis–NIR) range emitted by fluorophores . Thanks in situ fibrotic changes in frozen sections of lung tissues from bleomycin-treated animal models were observed by fluorescence microscopy. As shown in in vivo. The signals in the central and subpleural areas increased over time, while the number of bright spots in the subpleural area increased more significantly, providing direct evidence for the structural abnormality of collagens in fibrotic tissues.Collagen is the main structural component of the extracellular matrix in mammalian tissues. The deposition of collagen is a common feature of the PF patients . Currentin vivo and in vitro, while micro-CT imaging reflected the pathological and therapeutic status of lung parenchyma. There is no doubt that PF-related multi-modality imaging has great potential and deserves more attention and effort.Compared to single-modality imaging, multi-modality imaging tends to have higher sensitivity and specificity by combining the advantages of various imaging techniques, allowing for a more comprehensive evaluation of PF-related targets . For exaPF patients are susceptible to high levels of oxidative stress because the lung is directly involved in respiration . Oxidati2O2) , 4-(bromomethyl) phenylboronic acid pinacol ester (H2O2 response unit), and triphenylphosphonium cation  in one molecular probe (Mito-Bor). It showed little fluorescence because of photoinduced electron transfer (PET) between azo-BODIPY and 4-(bromomethyl) phenylboronic acid pinacol ester. In the presence of H2O2, the NIR fluorescence (∼730 nm) of Mito-Bor was turned on due to the inhibition of PET. Subsequently, changes in H2O2 concentration during fibrosis were successfully visualized by in vitro and in vivo fluorescence imaging, which indicated the levels of oxidative stress in fibroblasts.Mitochondria are the main source of cellular hydrogen peroxide (H2O2) . Mitocho2O2) . Selecti−) response groups can also be reduced fluorescent dyes that show no or weak fluorescence, but exhibit intense emission after oxidation by ONOO− (−) or ONOO− to form SiO3. The off-on fluorescent switch performed well in fluorescence imaging of HClO/ONOO− in IPF mice. In comparison with single-photon fluorescent probes, two-photon fluorescent probes usually have higher spatial resolution and imaging depth. A new two-photon NIR-fluorescent probe, rTPONOO-1, was obtained through direct condensation of acedan (two-photon fluorescent dye) and an indolium derivative  was constructed. The dioxaborolane group in the probe IRBTP-B was shown to be oxidized by ONOO− and produce a fluorophore with entire conjugation, which revealed a NIR-II fluorescence emission. Tissue phantom study confirmed that reliable signal was obtained at a penetration depth of up to 5 mm.Compared to the emission from the NIR-I (680–900 nm) window, the NIR-II (900–2000 nm) emission has higher penetration depth and less light scattering to facilitate better imaging . For exain situ monitoring of cysteine concentrations in PF mice. Higher cysteine concentrations were found in PF mice than in healthy mice, suggesting that low concentrations of GSH was not caused by low concentrations of cysteine. Further comparing the photoacoustic and fluorescence signals of CCYS in PF, pneumonia, and healthy mice, only PF mice showed a significant response, which provided a potential tool to differentiate PF from pneumonia. On the other hand, glutathione S-transferase (GST) and glutamyl transpeptidase (GGT) catalyze the nucleophilic addition of GSH to oxidative stress products and are thus potential indicators for monitoring PF progression  is an inducible enzyme closely related to PF . A NIR-fin vivo and in situ diagnosis of PF.Small metabolites are considered as sensitive markers for disease diagnosis . For exain vivo fluorescence imaging to give the distribution information of Spd-AKF-PLGA NPs during the therapy. Through the specific recognition by lung epithelial cells and accumulate in lung tissues, Spd-AKF-PLGA NPs reduced the degree of fibrosis and alveolar destruction in paraquat-induced animal models. Some ROS-sensitive fluorophore, such as nonfluorescent dihydrorhodamine-123, which can be rapidly oxidized by ROS to the strongly fluorescent rhodamine 123, allowed determination of the ROS level using fluorescence changes  is similar to that of the anti-fibrotic drug pirfenidone, which can inhibit the growth of fibroblasts and the synthesis of collagen. Spermidine (Spd)-modified poly (lactic-co-glycolic acid) (PLGA) nanoparticles (NPs) were used as an AKF carrier to improve the anti-fibrosis effect . Coumari changes . When an changes  or ROS s changes  show grein vivo tracking of transplanted stem cells  would be of great help to perform the early diagnosis of PF. The use of specific fluorescent probes to label PF-associated biomarkers allows for real-time detection of fluctuating levels of these biomarkers, providing visual evidence of their abnormal expression in vivo and/or in vitro. Meanwhile, probes with NIR fluorescence emission can reduce background interference and provide high-precision imaging of deep tissues. On the other hand, multimodal imaging that combines fluorescence imaging and other imaging techniques shows great potential for generating more comprehensive information in PF detection and treatment response.On the basis of the pathological process of PF, this review covers the fluorescence imaging studies used in the last years for PF diagnosis and to assess the effect of relevant drug treatments. Currently, there are no other simple, rapid and effective diagnostic tools when HRCT or surgical lung biopsy is not possible, and the identification of biomarkers (in vitro tests to the clinic requires safe fluorophores and standard imaging protocols. A feasible solution is to select a suitable fluorophore among the existing Food and Drug Administration (FDA)-approved medicines as the fluorescent parent and to make reasonable modifications. Current fluorescence imaging systems also need to be further improved in order to be suitable for clinical applications. In addition, multimodal imaging may be able to accelerate the clinical translation of fluorescence imaging by using existing fluorescent probes in conjunction with other FDA-approved imaging agents.Despite some advances in fluorescence imaging for PF diagnosis, there are still some unresolved challenges. For example, ROS levels may be associated with other diseases and corresponding inflammation, causing the results of imaging and measuring ROS to be unspecific to PF disease. The translation of preclinical studies and


There is a need to increase oral health knowledge, attitudes and behaviors in children to improve oral health. This research involves peer-assisted learning to determine if high school students can influence rural middle school students’ oral health. The study sample consisted of middle school students. After completing pre-test, they were assigned to receive 1) didactic peer-assisted learning with professionally supervised and educated high school students ; or, 2) teacher provided handouts/activity sheets. Both groups then completed a post test. The results of the Mann-Whitney U Tests showed that brushing and flossing failed to reach significant improvements between the pre-test and post-test for the handouts/activity sheets group . There was improvement within that group for oral health knowledge (P<.001). Brushing, flossing and oral health knowledge failed to reach significant improvement between the pre-test and post-test for the peer-assisted learning group . In terms of oral health knowledge, there was no difference between the scores of the two groups on the pre-test  nor on the post-test . Near-peer assisted learning for oral hygiene knowledge, attitudes, and behaviors had similar outcomes as teacher provided handouts and activity sheets in a middle school setting. Developing the habit of daily oral infection control through brushing and flossing is important to maintain personal oral health. Nevertheless, in one report, nearly 25% of children were not developing appropriate brushing and flossing habits . It is kSchools are a natural setting for peer-assisted learning . PreviouIt has been also reported to be effective with children 7–13 years in terms of behavior improvement (violence prevention) [This study received West Virginia University Institutional Review Board approval (IRB protocol number 1803018663).The researchers contacted Health Science and Technology Academy (HSTA) high school students to help with the research as near peers for the middle school children. HSTA students are interested in careers to help the medically under-served and they have presented healthcare outreach sessions to adults throughout their rural communities –12. The 245 middle school students from voluntarily enlisted schools in West Virginia were invited to participate in a cross-age mentoring project with HSTA high school student oral health near peers. Middle school students provided assent and parents provided consent for the research.A pre-test was created by the study team with input and review of the HSTA students. It was the baseline assessment of oral health knowledge/attitudes/beliefs and had a self-report of brushing and flossing . Community research associates and classroom teachers discussed the assignment of the schools to either an intervention school or a control school. The criteria for the assignments were that the administration of the program would have the least class time disturbance (a convenience sampling). Therefore, a cluster design was employed. The middle school students in the intervention schools had the HSTA student near-peers intervention. The middle school students in the control schools received oral health handouts.The HSTA students provided the in-person, near-peer education. The topics were: daily oral infection control; oral and systemic effects of tobacco use and vaping; oral health and nutrition; and, trauma and oral injuries. The interventions included inquiry-based activities. The HSTA high school students met with West Virginia University Health Sciences faculty members via four teleconferences to review the objectives and activities of the research prior to the sessions with the middle school students. Each of the sessions with the West Virginia University faculty members and HSTA high school students was approximately one hour in length. The HSTA high school students received additional instruction from their community research associates. The HSTA students and community research associates revised activities to be consistent with students’ existing knowledge and understanding of daily oral infection control. Lesson plans were created to engage middle school students using technology such as Kahoot!,® PowerPoint® slides, as well as with handouts, dental models, and volunteer-led demonstrations.The data for the research were collected and managed with the REDCap (Research Electronic Data Capture) electronic data capture tools hosted at West Virginia University. REDCap is a secure, web-based application that provides 1) a data entry interface; 2) audit trails 3) data exporting; and 4) data importing . Data reThe discrete tools used are presented in The pre-test and post-test had 19 knowledge-based statements to which middle school students were to agree or disagree. The responses on the pre-test and post-test were dichotomized to “correct” and “incorrect“ responses. A neutral response was categorized as incorrect. A score of zero was assigned to incorrect answers and a score of 1 was assigned to correct responses. The number of correct responses, means and standard deviations on each test was determined. Daily oral infection control and other oral health behaviors and attitudes were collected. Results were compiled using descriptive statistics. Mann-Whitney U Tests were used to compare the groups. Data analysis was conducted with IBM SPSS® Version 25 . The P-value was set at <.05.There were 245 middle school students  who participated in the pre-test. Of these students, 94.6% were in seventh grade, and their mean age was 13.20 years . There were 58.5% reporting dental insurance coverage. Seventeen students (7.5%) reported one urgent dental visit within the previous year, and 13 (13.2%) reported more than one urgent visit to his or her dentist within the previous year.There were 28 students (12.7%) reporting no dental visits within the previous year; 39 (17.6%) reporting one dental visit within the previous year; and, 154 (69.7%) reporting two or more dental visits within the previous year. Eighty-three students (38.2%) reported at least one dental restoration; and, 51 (21.9%) reported having teeth that hurt. There were 174 students in schools assigned as controls and 71 students in schools assigned to have HSTA students.Before the study, the control and intervention groups were similar on oral health behaviors, oral health attitudes, and oral health knowledge  and 2. TIn similar studies involving science, technology, electronics, mathematics –18 and rIn a qualitative study evaluating peer-assisted learning , several challenges were noted that may also apply to this current study. Small groups were found to be more conducive to learning than larger groups . Near-peOne criticism of peer-assisted learning is the inadequacy of preparation during peer training and inadequate subsequent monitoring of the accuracy of implementation . A stronStart-up costs are also limitations noted in another research . WithoutIn a meta-analysis of peer-assisted learning with elementary students, there was a positive increase in achievement . HoweverThe results of this research indicate a greater need for oral health education in Middle School curricula. Future research could potentially involve a mixed approach with both dental access to dental healthcare professionals and longer interventions with HSTA students. Many of the techniques used by the near-peers were innovative and engaging. These also should be evaluated in future research to determine the effectiveness of technological features used by near-peers and younger students to teach and learn about oral health.In terms of oral health knowledge, there was no difference between the scores of the two groups on the pre-test  nor on the post-test . Near-peer assisted learning for oral hygiene knowledge, attitudes, and behaviors had similar outcomes as teacher provided handouts and activity sheets in a middle school setting.


Study 2 (n = 39) was a 3-month double-blinded randomized trial comparing placebo to duloxetine, a dual serotonin–noradrenaline reuptake inhibitor. Across two independent studies, we found that patients with chronic pain present alterations in the functional circuit related to the serotonin transporter, when compared with age-matched healthy controls. Placebo responders in Study 1 presented with higher pre-treatment functional connectivity enriched by the dopamine transporter compared to non-responders. Duloxetine responders presented with higher pre-treatment functional connectivity enriched by the serotonin and noradrenaline transporters when compared with non-responders. Neurotransmission-enriched functional connectivity mapping might hold promise as a new mechanistic-informed biomarker for functional brain alterations and prediction of response to pharmacological analgesia in chronic pain.Chronic pain is a world-wide clinical challenge. Response to analgesic treatment is limited and difficult to predict. Functional MRI has been suggested as a potential solution. However, while most analgesics target specific neurotransmission pathways, functional MRI-based biomarkers are not specific for any neurotransmitter system, limiting our understanding of how they might contribute to predict treatment response. Here, we sought to bridge this gap by applying Receptor-Enriched Analysis of Functional Connectivity by Targets to investigate whether neurotransmission-enriched functional connectivity mapping can provide insights into the brain mechanisms underlying chronic pain and inter-individual differences in analgesic response after a placebo or duloxetine. We performed secondary analyses of two openly available resting-state functional MRI data sets of 56 patients with chronic knee osteoarthritis pain who underwent pre-treatment brain scans in two clinical trials. Study 1 ( et al. report that patients with chronic knee osteoarthritis pain show altered connectivity in functional circuits related to the molecular systems underlying pain regulation. The functional mapping of these circuits might hold promise as a new neuroimaging biomarker to predict analgesic response.Martins   Therefore, developing mechanism-based biomarkers that can guide analgesic treatment selection for chronic pain patients based on the prediction of treatment response remains an unmet target and a clinical need.Pain is a world-wide leading cause of disability, constituting one of the primary reasons for people to seek healthcare.12 Currently, it is generally accepted that chronic pain is a multifactorial entity entailing physical, psychological, emotional and social aspects.1 Preclinical studies have offered insights into key central mechanisms that might contribute to chronic pain, including sensitization phenomena in an array of nervous system pathways, imbalances in the facilitatory and inhibitory descending modulation pathways from the brain that regulate the transmission of noxious information in the spinal cord, neuroinflammation and glial dysfunction, among others.13–17 These findings have fuelled substantial interest in developing neuroimaging-based biomarkers that could unravel how chronic pain affects brain functioning and what form of brain pathophysiology in these patients can be targeted by different treatments.19 While a range of preliminary diagnosis, prognosis and treatment response brain biomarkers have been suggested , to date these biomarkers have provided minimal direct clinical application in the management of chronic pain patients.Part of this problem stems from our limited understanding of the neurobiological mechanisms underlying chronic pain and, hence, of the mechanisms through which most of these pharmacological treatments might produce persistent pain relief in chronic pain patients.20 However, neuroimaging-based biomarkers of brain function [i.e. such as those based on measurements of blood oxygenation level dependent (BOLD) signal]21 are not specific for any neurotransmission system, limiting the potential mechanistic understanding of how these biomarkers might contribute to explain treatment response. The same limitation applies to the potential neuroimaging biomarkers in unravelling functional changes in neuromodulatory pathways that could guide drug development or repurposing for patients with chronic pain.12Most pharmacological analgesic treatments target specific neurotransmission pathways. For instance, duloxetine, a dual antidepressant often used to manage pain in chronic pain patients, inhibits the reuptake of both serotonin and noradrenaline, increasing their bioavailability in the synapses.This study aims at advancing our understanding on the pain-induced functional alterations in the brain, exploring their link with the neurobiological processes underlying chronic pain and inter-individual differences in analgesic response to pharmacological treatment. Our main hypotheses are that (i) patients with chronic pain present functional alterations in key neurotransmission-related circuits associated with pain control and regulation, when compared with age-matched healthy controls (HCs) and (ii) pre-treatment inter-individual differences in the functional connectivity (FC) of these neurotransmission-related circuits can predict analgesia in response to placebo and pharmacological intervention.22 using the recently developed Receptor-Enriched Analysis of Functional Connectivity by Targets (REACT) multimodal framework  imaging.24 These data sets included HCs (n = 20) and patients with chronic knee osteoarthritis (OA) pain (n = 56) who underwent pre-treatment brain scans in two clinical trials. Study 1 (n = 17) was a 2-week single-blinded placebo pill trial. Study 2 (n = 39) was a 3-month double-blinded, between-subject, randomized trial comparing placebo (n = 20) to duloxetine (n = 19).To test these hypotheses, we performed secondary analyses of two openly available resting-state functional MRI (rs-fMRI) data setsramework ,23 whichBox 1Receptor-Enriched Analysis of functional Connectivity by TargetsREACT is a multimodal framework specifically developed to enrich the analysis of fMRI data with information on the spatial distribution of selected molecular systems, using molecular templates derived from PET and SPECT imaging. This integrated analysis allows us to identify functional networks associated with specific molecular systems and explain functional alterations in terms of the underlying molecular substrates of the brain.How it works: REACT is based on a two-step multivariate regression analysis performed at the subject level. In the first general linear model (GLM), the molecular templates are used as independent variables to inform the model on the spatial configuration of the neurotransmitters under investigation and estimate the dominant BOLD fluctuations of the functional networks related to each molecular system. Regions with high density of neurotransmitters will have a stronger weight in the estimation of the dominant BOLD fluctuation of the corresponding functional network when compared with the regions with lower molecular density. For example, the SERT, which has a high density in the basal ganglia and thalamic regions, will provide a SERT-related functional circuit where those regions will be key centres of the network. On the contrary, regions with a low distribution density of SERT will have a low contribution in the estimation of the functional circuit associated with this neurotransporter.In the second GLM, the dominant BOLD fluctuations estimated in the previous step are used as independent variables to assess the contribution of each voxel to each dominant BOLD fluctuation associated with the molecular systems under investigation. This analysis will return a set of functional connectivity maps, one for each molecular system being examined.Of note, while in the first GLM, the areas used as reference regions in the kinetic models for the quantification of the PET/SPECT images are discarded from the analysis because target density in those regions cannot be reliably measured, in the second GLM, every area is taken into account as the BOLD signal is reliably measured in every voxel of the brain. The regions excluded from the first GLM analysis can show either positive or negative functional coupling with the overall receptor-enriched functional network, depending on their positive or negative correlation with the dominant BOLD fluctuation.What it means: When the REACT-based functional maps are compared between groups , significant increases or decreases of functional connectivity in brain areas of the functional network related to a specific molecular system can be interpreted as an altered involvement of those areas to the normal functioning of the network. Therefore, this suggests a potential relationship of the functional alterations with the underlying mechanisms involving that molecular system.Template choice: Different types of molecular templates can be used in REACT, according to the specific hypotheses of each study and templates availability. To explore the brain mechanisms underlying a certain disorder, the distribution of neurotransmitter transporters might be more suited to capture the full architecture of a certain system than the distribution of specific receptors, which might not capture the complete picture of neurotransmission related to the specific system. In the case of a drug challenge targeting specific neurotransmitters, the optimal approach would be to use the maps of those specific receptors, if drug binding is known.26 Furthermore, they have also been implicated in placebo analgesia (i.e. dopamine and opioids)27 and correspond to the main molecular targets of duloxetine (i.e. SERT and NET),20 whose treatment response was effectively studied herein.We focused our analyses on the functional circuits related to the serotonin transporter (SERT), noradrenaline transporter (NET) and dopamine transporter (DAT), and the µ-opioid receptor, as general indicators of the regional distribution of the neurotransmission related to the serotonin, noradrenaline, dopamine and opioid systems, respectively. When available, the distribution of neurotransmitter transporters is better suited to capture the full architecture of a certain system than the distribution of specific receptors, which might not capture the full picture. We informed our selection of molecular targets by the fact that these neurotransmitters play pivotal roles in pain regulation, namely in those descendent modulatory pathways controlling the spinal transmission of nociceptive information.22 of patients with chronic knee OA pain who underwent pre-treatment brain scans in two clinical trials. The full details on demographics, inclusion and exclusion criteria have been provided in the original article.22 Here, we will simply present a brief summary to help the reader to contextualize. Study 1 was a 2-week single-blinded placebo pill trial where 17 patients with OA  ingested a lactose placebo pill once a day for 2 weeks. Study 2 was a 3-month double-blinded randomized trial in which 39 patients with OA ingested either placebo pills  or duloxetine  at a dose of 30 mg for the first week and escalated to 60 mg for the rest of the treatment period, except for the last week, when the dose was decreased back to 30 mg. In addition, Study 1 also included 20 age-matched HC subjects . Of note, the authors of this study were not blinded to the treatment arms.For this work, we used two openly available rs-fMRI data setsFor Studies 1 and 2, behavioural and clinical parameters were obtained before and after treatment, while brain scans were collected only before treatment. Patients were asked to discontinue their medications 2 weeks before the beginning of the trial and were provided with acetaminophen as rescue medication. All participants gave written informed consent to procedures approved by the Northwestern University Institutional Review Board Committee (STU00039556).a priori on an individual basis as at least a 20% decrease in VAS pain from baseline to the end of treatment period; otherwise, subjects were classified as non-responders. This threshold for analgesic response was chosen following the same procedure adopted by the previous study on these data sets.22 While the choice of this threshold is arbitrary, we note that a 20% reduction in VAS ratings of pain is higher than the 15% considered to be minimal clinically important.28 As a further reference, a 30% reduction in VAS ratings of pain is typically considered a clinical important pain diminution.29Patients from both studies completed a general health questionnaire, a Visual Analogue Scale (VAS) on a 0–10 scale for their knee OA pain, the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), the Beck Depression Inventory (BDI) and the Pain Catastrophizing Scale (PCS) (note we could only access the raw VAS and WOMAC data). All questionnaires were administered on the day of brain scanning. In Study 2, to partially compensate for regression to the mean effects, VAS was measured three times over a 2-week period prior to the start of treatment and after cessation of medication use, averaged, and used as baseline. Analgesic response was defined 2*-weighted echo-planar sequence .For all participants in Studies 1 and 2, imaging data were collected with a 3 T Siemens Trio whole-body scanner. A 3D T1-weighted anatomical scan was obtained for each participant using a Magnetization Prepared Rapid Acquisition Gradient Echo acquisition . Functional MRI data were obtained during rest using a multi-slice T30 non-brain tissue removal with the Brain Extraction Tool (BET),31 an initial spatial smoothing with a 6 mm full width at half maximum (FWHM) Gaussian kernel  and de-noising with an independent component analysis (ICA)-based Automatic Removal Of Motion Artifacts (ICA-AROMA).32 Additionally, subject-specific white matter (WM) and CSF masks, obtained from the segmentation of the subjects’ structural images and erosion to minimize the contribution of grey matter partial volume effects, were used to extract and regress out the mean WM and CSF signals from each participant’s pre-processed data set. A high-pass temporal filter with a cut-off frequency of 0.005 Hz was applied, followed by an additional spatial smoothing at FWHM = 6 mm, to obtain a final smoothing of the functional MRI (fMRI) images of ∼8 mm . A study-specific template representing the average T1-weighted anatomical image across subjects was built using the Advanced Normalization Tools (ANTs).33 Each participant’s data set was co-registered to its corresponding structural scan, then normalized to the study-specific template before warping to standard Montreal Neurologic Institute (MNI)152 space. Images were finally resampled at 2 mm3 resolution.The rs-fMRI data sets from Studies 1 and 2 were pre-processed using the FMRIB Software Library (FSL). Pre-processing steps included volume re-alignment with MCFLIRT,123I-Ioflupane SPECT images from 30 HCs without evidence of nigrostriatal degeneration.34 The NET atlas is a publicly available template of the [11C]MRB PET brain parametric maps from 10 HCs .36 The SERT atlas is a publicly available template37 of [11C]DASB PET images of 210 HCs from the Cimbi database.38 The µ-opioid receptor map is a publicly available template of [11C]Carfentanil PET images of 89 HCs (https://identifiers.org/neurovault.image:115126). All molecular atlases were normalized by scaling the image values between 0 and 1, although preserving the original intensity distribution of the images, and masked using a standard grey matter mask. Of note, for each atlas, we masked out the regions that were used as references for quantification of the molecular data in the kinetic models for the radioligands, namely the occipital areas for DAT, NET and µ-opioid receptor, and the cerebellum for SERT. Finally, we resampled the SERT image to have all atlases in standard MNI space with 2 mm3 voxel size.For the analysis with REACT, we used the templates of the molecular density distribution of the DAT, NET, SERT and µ-opioid receptor. The DAT map is a publicly available template of 24 In brief, the functional circuits related to the DAT, NET, SERT and µ-opioid receptor systems were estimated using a two-step multivariate regression analysis40 implemented with the fsl_glm command of FSL. In the first step, the rs-fMRI volumes were masked using a binarized mask derived from the molecular atlases to restrict the analysis to the voxels for which the density information of the neurotransmitter was available in the templates. Then, the molecular templates were used as a set of spatial regressors to weigh the rs-fMRI images and estimate the dominant BOLD fluctuation related to each molecular system at the subject level. Those subject-specific time series were then used as temporal regressors in a second multivariate regression analysis to estimate the subject-specific spatial map associated with each molecular atlas. The output consists of four maps per subject, each one reflecting the molecular-enriched FC associated with a specific neurotransmitter. At this stage, the analysis was conducted on the whole grey matter volume. Both data and the design matrix were demeaned (–demean option); the design matrix columns were also normalized to unit standard deviation with the –des_norm option.39A detailed explanation of the REACT methodology and its applications can be found elsewhere.1) and HC by running exploratory whole-brain two-sample t-tests, for each neurotransmission system separately, after controlling for age and gender. For this and all subsequent whole-brain analyses, we applied cluster-based inference within Randomise,41 using 5000 permutations per test and contrast, considering a cluster significant if PFWE < 0.05, corrected for multiple comparisons using the null distribution of the maximum cluster size across the image. We also applied the Bonferroni correction to correct for multiple comparisons across molecular systems and contrasts investigated. To validate the findings from the exploratory analyses, we then conducted hypothesis-driven analyses comparing patients with OA from Study 2 (OA2) and HC. We extracted the mean neurotransmission-enriched FC values in OA2 and HC from the clusters where we found significant OA1 versus HC differences and compared the two groups. For this and all subsequent hypothesis-driven analyses, we performed frequentist and Bayesian two-sample t-tests in SPSS (version 27), controlling for age and gender. Beyond the case–control group differences, we also investigated whether molecular-enriched FC in these clusters would be able to predict the pain ratings (VAS) at baseline in each of the two groups of patients using both frequentist and Bayesian Pearson’s correlations (bootstrapping 1000 samples) in SPSS.We first compared the FC associated with each neurotransmitter system between patients with OA from study 1  by testing whether FC predicts baseline VAS using frequentist and Bayesian Pearson’s correlations in SPSS.As a further check, we examined whether the molecular-enriched FC differences in OA2 for those systems showing significant FC differences between placebo responders and non-responders in OA1, extracting the mean neurotransmission-enriched FC values in the placebo OA2 sub-set from the significant clusters and performing two-sample t-tests in SPSS.We then performed a hypothesis-driven analysis in the placebo OA2 data, which allowed us to examine FC differences between responders and non-responders to placebo and duloxetine. For each functional circuit, we performed a two-way analysis of covariance (ANCOVA) in Randomise to interrogate an interaction effect between treatment type (duloxetine and placebo) and treatment response (responders and non-responders) on FC, controlling for age and gender. For each significant interaction, we extracted the mean FC values within the significant clusters and ran post hoc tests in SPSS to evaluate the simple main effects of treatment response within each group separately, controlling for age and gender. Levene’s test was also performed to check the homogeneity of variances. We also calculated frequentist and Bayesian Pearson’s correlations between the mean FC and baseline VAS in the placebo and duloxetine groups separately.Finally, we tested whether different patterns of pre-treatment FC related to neurotransmission underlie differences in response to different analgesic treatments. We investigated this question using the OA42: BF < 1/10, strong evidence for an alternative hypothesis; 1/10 < BF < 1/3, moderate evidence for an alternative hypothesis; 1/3 < BF < 1, anecdotal evidence for an alternative hypothesis; BF > 1, anecdotal evidence for the null hypothesis; 3 < BF < 10, moderate evidence for the null hypothesis; BF > 10, strong evidence for the null hypothesis.All Bayesian analyses were implemented in JAMOVI, using the default uninformative priors from the software. An increase in Bayes factor (BF) in our analyses corresponds to an increase in evidence in favour of the null hypothesis. To interpret BF, we used the Lee and Wagenmakers’ classification schemehttps://openneuro.org/datasets/ds000208/versions/1.0.0.43All MRI data of Studies 1 and 2 are available at 44 that can be downloaded from https://github.com/ottaviadipasquale/react-fmri.The code for performing the REACT-based fMRI analyses is now available as a python package22 on sociodemographic and clinical variables that might help to interpret our novel imaging findings. For a detailed description of sociodemographic and clinical variables, we refer the reader to the original article published elsewhere.22Here, we report in detail only the results of our analyses on molecular-enriched FC and summarize below some of the main findings from the original analysesIn Study 1, eight patients met the criteria for placebo response and nine patients were classified as non-responders. Responders and non-responders did not differ in baseline pain ratings, age, disease duration, depressive symptoms, pain catastrophizing or medication use at the entry of the study. In Study 2, from those allocated to placebo, 10 patients met the criteria for responders and the other 10 were classified as non-responders. From those allocated to duloxetine, 8 met the criteria for responders and 11 were classified as non-responders. Patients allocated to placebo did not differ in baseline pain ratings when compared with those randomized to duloxetine. In both groups, responders and non-responders did not differ in baseline pain ratings, age, disease duration, depressive symptoms or medication use at the entry of the study. However, in both groups, non-responders showed higher pain catastrophizing than responders. Both placebo and duloxetine produced significant reductions in pain ratings after 3 months of treatment; however, the extent of pain relief did not differ between those treated with placebo and those treated with duloxetine. The clinical variables of knee pain at baseline and pain relief  as measured with the VAS are reported in 45We used the templates of the molecular density distribution of the DAT, NET, SERT and µ-opioid receptor in the REACT analysis to estimate the corresponding molecular-enriched FC maps of these systems for every subject of the two data sets. In 1 and HC. We found significant differences in NET- and SERT-enriched FC (PFWE < 0.05) between the two groups   =  ], and increased SERT-related FC in four clusters including the superior and middle frontal gyri and precentral gyrus ; the frontal pole and middle frontal gyrus ; the frontal pole, frontal medial cortex and anterior division of the paracingulate gyrus ; the paracingulate and superior frontal gyri . We also found decreased SERT-enriched FC in the OA1 group in one cluster including the superior and middle temporal gyri, supramarginal gyrus and angular gyrus . Of note, only the increase in the SERT-enriched FC survived the Bonferroni correction for multiple comparisons across maps and contrasts. We did not find any group differences in the DAT- and µ-opioid-enriched FC.We investigated our first main research question by comparing the FC associated with each neurotransmitter system between OAo groups . Specifi2 and HC. The two-sample t-tests showed significant differences in SERT-enriched FC , which were similar in direction and magnitude to those observed when we compared OA1 and HC. This analysis identified a similar pattern of alterations in SERT-enriched FC across the two cohorts of patients with OA , but 0.0254 and 0.0557 times more likely in the contrasts HC > OA2 and HC < OA2 in the SERT-enriched FC , respectively.The results from the Bayesian analysis of the same data showed that the null hypothesis of a group difference in the NET-enriched FC between HC and OAOf note, we did not find a consistent pattern of association between NET- and SERT-enriched FC and pain intensity .1 differ in pre-treatment FC associated with any of the neurotransmitter systems we explored. We found that placebo responders, when compared with non-responders, showed significant increases in DAT-enriched FC in the central and parietal opercular cortex, Heschl’s gyrus, anterior division of the superior temporal gyrus, planum polare and planum temporale  and SERT-enriched FC raclopride to D2/D3 dopamine receptors in the basal ganglia, possibly reflecting increases in the release of dopamine in these regions.27 The same study also reported placebo-induced decreases in [11C]carfentanil binding to the µ-opioid receptors, pointing to engagement of the endogenous opioid system during placebo-induced analgesia. However, changes in [11C]raclopride binding in the nucleus accumbens emerged as the strongest predictor of placebo-induced analgesia, accounting for 25% of the variance alone. Another study has shown that individual differences in reward response can explain placebo-induced effects and expectations.72 The differences in DAT-enriched FC between patients who responded versus those who did not respond to administration of placebo reported here are broadly compatible with this idea. Assuming that higher DAT-enriched FC might be driven by strongest dopamine-related neurotransmission within the dopaminergic circuits (which we index here through DAT density distribution in the brain), then it is plausible that those patients with strongest dopamine-related neurotransmission might benefit the most from expectancy effects, which rely on dopamine release and are at the core of the placebo effect.Our second main finding was the observation that patients experiencing analgesia in response to a course of 2 weeks of placebo administration (Study 1) present higher pre-treatment DAT-enriched FC  than patients who did not respond. DAT-enriched FC was not related to disease burden prior to the start of placebo treatment in Study 1, diminishing the possibility that the measure is related to regression to the mean rather than a true placebo response. Furthermore, this difference is also unlikely to be confounded by differences between responders and non-responders in disease duration, depressive symptoms, pain catastrophizing or medication use since the groups did not significantly differ in any of these variables .74 Hence, it is possible that while inter-individual differences in DAT-enriched FC are particularly relevant to explain differences in short-term response to placebo, other mechanisms might be involved in the long term. Until further larger studies will revisit these findings, we urge for some caution when interpreting this association between pre-treatment DAT-enriched FC and placebo response. We also note the lack of differences between placebo responders and non-responders on µ-opioid-enriched FC, despite previous evidence that the endogenous opioid system is recruited during placebo-induced analgesia.27 However, as explained above, whether that might reflect the fact that FC was measured at rest or that some carry-over effects of previous analgesic treatments biased this result is unclear.This finding was nevertheless not replicated in the hypothesis-driven analysis on data from Study 2, where placebo responders and non-responders did not differ in pre-treatment DAT-enriched FC. The lack of between-group differences was supported by the Bayesian analysis, where the null hypothesis was 2.46 times more likely than the alternative hypothesis. We should highlight though that there is at least one important methodological difference between Studies 1 and 2 that could potentially account for this discrepancy. In Study 1, placebo response was evaluated after 2 weeks of placebo administration, while in Study 2, the placebo protocol lasted for 3 months. Studies have shown that the duration of administration is a determinant of placebo response.22 Altogether, these findings suggest that pre-treatment NET- and SERT-related FC at rest might hold promise as a biomarker for duloxetine analgesia response in patients with chronic OA pain.Our third key finding was the observation that patients who responded to duloxetine showed higher pre-treatment NET- and SERT-enriched FC (but not DAT- or µ-opioid-enriched FC) than those who did not respond, while in those patients allocated to placebo, we observed the opposite trend—i.e. lower pre-treatment NET- and SERT-related FC. NET-enriched FC was not related to disease burden prior to the start of placebo or duloxetine treatment, diminishing the possibility that the measure is related to regression to the mean rather than a true response. SERT-enriched FC was also not related to baseline pain ratings in the duloxetine group. Furthermore, these differences are unlikely to be driven by differences between responders and non-responders within each group in disease duration, depressive symptoms or medication use, since the groups did not significantly differ in any of these variables .20 The main mechanisms suggested to underlie the analgesic effect observed under duloxetine include enhancement of descending inhibitory pain pathways from the brain through potentiation of serotoninergic and noradrenergic transmission, with consequent inhibition of ascendant transmission of nociceptive inputs from the spinal cord20 .75 This mechanism has received indirect support from a previous study linking response to duloxetine in painful diabetic neuropathy to the integrity of the descending pain inhibitory pathways, as assessed by conditioned pain modulation.76 Therefore, the fact that only pre-treatment differences in SERT- and NET-enriched FC exist between duloxetine responders and non-responders matches the pharmacodynamics of the drug and aligns with the basic drug mechanisms through which most likely it induces analgesia. Based on this observation, we suggest that target-enriched FC mapping might open a new avenue in neuroimaging biomarkers of pharmacological treatment response in chronic pain, bringing the advantage of allowing to establish a clearer mechanistic link between the measured neuroimaging biomarker and the neurotransmission-related mechanisms through which a pharmacological treatment targeting a specific neurochemical system might induce analgesia. For instance, since duloxetine acts by inhibiting the reuptake of serotonin and noradrenaline, it is conceivable that its ability to enhance serotoninergic or noradrenergic transmission is moderated by the availability of these neurotransmitters in the synapses, promoting lower accumulation of serotonin/noradrenaline in those where synthesis capacity and tonic release is reduced. Following this line of thought, patients with lower bioavailability of serotonin/noradrenaline, which for this reason might show lower SERT- and NET-related FC connectivity, might not benefit from duloxetine treatment. We should highlight though that at this point any relationship between bioavailability of specific neurotransmitters and target-enriched FC remains speculative and will require validation in further studies.Duloxetine is a non-selective inhibitor of the reuptake of serotonin and noradrenaline, which enhances their bioavailability at the synaptic level.77 This superiority is thought to be linked to the fact that antidepressants which also increase the levels of noradrenaline by inhibiting NET might block the spinal transmission of nociceptive input directly through acting on spinal α2 receptors.20This empirical observation matches the clinical evidence that non-selective inhibitors of the reuptake of serotonin and noradrenaline might be superior to selective inhibitors of the reuptake of serotonin in promoting analgesia in patients with chronic pain.Our study has some limitations worth mentioning. First, although REACT improves the specificity of FC analysis, the approach remains relatively indirect and relies on molecular templates estimated in independent cohorts of healthy individuals. Therefore, further specification from intra-regional variation across patients is not possible using the current data set as it would require PET data for each ligand and patient. In any case, it should be noted that although the use of molecular templates of healthy subjects on clinical populations could be seen as a sub-optimal strategy, there would be at least two main disadvantages in using patient-specific templates. First, if the molecular data set used to create the template is not from the same patient cohort, changes in target density for that template might not overlap with the one of the data set under investigation due to factors that might differentially affect the molecular layer . Second, the functional networks estimated from such templates might not properly weight the contribution of the core regions of the molecular systems being examined, eventually resulting in a network that does not reflect the specific features of the molecular system. For these reasons, templates of healthy populations should be adopted in this kind of analyses.79 However, from the findings we gathered in this study, we suggest that future studies expanding this approach to other chronic pain populations and drug classes are worth investing and might be fruitful.The second limitation of our study is the relatively small sample size of both cohorts. This was in part mitigated by the fact that we attempted to replicate some of our findings in Study 1 using a second cohort of patients from Study 2. However, the issue of small sample sizes was even more prominent in the comparisons between responders and non-responders to placebo and duloxetine. Therefore, while our study provides an important proof-of-concept, future larger studies attempting to replicate our findings will be pivotal. Finally, our findings are restricted to patients with OA and to the prediction of placebo and duloxetine response in this group of chronic pain patients; hence, direct extrapolation to other chronic pain conditions or other pharmacological analgesics should be avoided. Indeed, chronic pain manifests in a range of clinical phenotypes; and even within the boundaries of a specific chronic pain syndrome such as OA, it is likely that different pathophysiological mechanisms are in play in different patients.80In conclusion, while further clinical validation in larger cohorts is warranted, this study shed light on the functional brain alterations induced by chronic pain and inter-individual differences in brain function that might underlie variability in the response to pharmacological analgesia. The mechanistic insights provided by the molecular-enriched FC mapping might help characterize chronic pain mechanisms, enabling rational and individualized treatment choice. Ultimately, these informed decisions might contribute to decrease unnecessary exposures of patients to ineffective therapies and undesirable side-effects, facilitate treatment adherence and accelerate pain control without long periods of treatment trial-and-error, decreasing the chance that the pain becomes intractable.fcab302_Supplementary_DataClick here for additional data file.


Pediatric medial malleolus stress fracture is a rare pathology and has limited data on management. The authors present a case of bilateral medial malleolus stress fracture treated with operative fixation followed by a course of immobilization and protected weight-bearing. A medial malleolus stress fracture (MMSF) is a rare injury comprising only 4% of all stress fractures . These iSurgical intervention is often necessary to prevent long-term complications  ,4,7. SurBilateral MMSFs are exceedingly rare, and management is challenging due to a lack of consensus treatment algorithms in these patients. The authors present a case of a 16-year-old male athlete with bilateral medial malleolus stress fractures managed successfully with surgical fixation followed by a period of immobilization and protected weight-bearing.A 16-year-old male high school athlete presented with the chief complaint of atraumatic left ankle pain and swelling one day after competing in a high-school varsity level football game. The patient reported mild, left medial-sided ankle pain for one month prior to presentation. The patient’s symptoms acutely worsened during competition, but he did not stop participating in the same game. Physical exam of a neurovascularly intact left foot and ankle revealed no postural abnormalities. There was swelling and tenderness localized to the medial malleolus, and pain with an external rotation stress test. Range of motion of the ankle, midfoot, and hindfoot was without restriction. Physical exam of a neurovascularly intact right foot and ankle revealed no postural abnormalities. There was no swelling, but palpable tenderness at the medial malleolus, and pain with external rotation stress. Bilateral standing anteroposterior (AP) ankle radiographs demonstrated a complete non-displaced medial malleolus stress fracture on the left and an incomplete medial malleolus stress fracture on the right  scan demonstrated no evidence of osteoporosis or osteopenia Table . The cliPost-operatively, range of motion exercises of the ankle were started with physical therapy. The left lower extremity was kept non-weight bearing in a controlled ankle motion-boot for six weeks. After six weeks, the patient was transitioned to weight-bearing as tolerated on the left lower extremity. The right lower extremity was non-weight-bearing in the two weeks immediately following surgery, and was transitioned to weight-bearing as tolerated at two weeks. Bilateral ankle range of motion exercises were recommended in the two-week post-operative period and physical therapy with ankle fracture protocol was prescribed at two weeks post-operative follow-up. Three months post-operatively, follow-up radiographs demonstrated a completely healed right medial malleolus and near-complete healing on the left Figure . The patAt six months post-operative follow-up, radiographs demonstrated completely healed bilateral medial malleolus stress fractures with intact hardware. The patient reported no pain bilaterally at the medial ankle and hindfoot. The patient's physical therapy course was completed, and he had returned to full sprinting activities. Ten months post-operatively, the patient was participating in sports without restriction and the American Orthopedic Foot and Ankle Society (AOFAS) hindfoot score calculated by chart review was 100/100 at 10 months.Medial malleolus stress fractures are seen most frequently in athletes and military recruits due to abnormal weight transmission and torsional forces . PatientMost stress fractures can be managed non-operatively with a boot or cast immobilization and protected weight-bearing for six to eight weeks . HoweverNguyen et al. recommend immobilization in a boot for six weeks for complete medial malleolus fractures after open reduction and internal fixation (ORIF) with early post-operative range of motion (ROM) exercises starting after two weeks . PatientDue to the unprecedented presentation of bilateral MMSF in a young athlete, laboratory evaluation for metabolic etiologies was necessary. Some studies have reported an association between low levels of 25-hydroxy vitamin D and stress fractures . While oA medial malleolus stress fracture is a rare but well-documented injury in running and jumping athletes. A bilateral medial malleolus stress fracture is a rare clinical entity that has only been described in the literature on a case-report basis. The possibility of metabolic bone abnormality warrants referral to a bone health specialist. The patient was successfully treated with surgical fixation, demonstrated routine radiographic healing of the fractures post-operatively at six months, and reported no limitations impacting the quality of life by 10 months.


Previous work highlights the importance of sociobehavioral interventions to address dementia caregiving health and wellbeing outcomes. By empowering caregivers to become objective managers of their loved one’s illness, and own self-care, they are less likely to exhibit negative outcomes. We are conducting a mixed-method, randomized trial to test manualized, multi-family psychoeducational group interventions: Savvy Caregiver Express, and Savvy Caregiver Program. This poster describes the qualitative findings of four focus group interviews recently conducted to elucidate the study participation experiences of family caregivers enrolled in the parent study. Twenty-five racially and ethnically diverse participants  caring for a family member with cognitive decline participated in focus group interviews conducted via videoconferencing methods. We captured more nuanced experiences from the perspective of study participants with regards to the caregiver interventions and their research participation. Interviews were conducted by trained research personnel, lasted 60-75 minutes, and followed an open-ended questioning route. Based on thematic analyses, we identified the following themes: 1) Changing one’s mindset: Seeing life through their shoes; 2) Getting information in one place; 3) Expanding the personal experience; 4) Fears and vulnerability; 5) Time constraints vs. wanting more; 6) Not everyone is at the same place; 7) Technology: It’s going to be part of our lives; and 8) Research: Not always in sync. Our findings indicate high satisfaction with most components of the program while specific recommendations were offered to improve the intervention and study experience such as tailoring materials to stage-specific needs.


Alcohol consumption reduces but pain rises over the life course. Thus, we hypothesized that developmental variability in the bidirectional association between alcohol consumption and pain would vary as a function of age. This hypothesis was tested across three age groups – younger (<29), middle (29-65), and older (>65) using NESARC wave 1 and 2 data . The effect of pain interference at baseline on alcohol consumption at follow-up was non-significant across the age groups, indicating that self-medication theory was unsupported. The effect of alcohol consumption at baseline on pain interference at follow-up was significant among the middle  and older  groups, but non-significant among the younger group. This latter effect differed significantly between the younger and older groups (p =.005) and the middle and older groups (p=.041). Results show that alcohol consumption reduces pain interference, especially later in life.


To investigate the diagnostic performance of deep transfer learning (DTL) to detect liver cirrhosis from clinical MRI.th-year resident, board-certified radiologist). Segmentation was performed using a U-Net architecture built on a pre-trained ResNet34 encoder. Differences in classification accuracy were assessed by the χ2-test.The dataset for this retrospective analysis consisted of 713  patients who underwent liver MRI between 2017 and 2019. In total, 553 of these subjects had a confirmed diagnosis of liver cirrhosis, while the remainder had no history of liver disease. T2-weighted MRI slices at the level of the caudate lobe were manually exported for DTL analysis. Data were randomly split into training, validation, and test sets (70%/15%/15%). A ResNet50 convolutional neural network (CNN) pre-trained on the ImageNet archive was used for cirrhosis detection with and without upstream liver segmentation. Classification performance for detection of liver cirrhosis was compared to two radiologists with different levels of experience  and to the board-certified radiologist .Dice coefficients for automatic segmentation were above 0.98 for both validation and test data. The classification accuracy of liver cirrhosis on validation (vACC) and test (tACC) data for the DTL pipeline with upstream liver segmentation  was significantly higher compared to the resident  pre-trained on an extensive natural image database (ImageNet archive) enables detection of liver cirrhosis on standard T2-weighted MRI.• High classification accuracy can be achieved even without altering the pre-trained parameters of the convolutional neural networks.• Other abdominal structures apart from the liver were relevant for detection when the network was trained on unsegmented images.The online version contains supplementary material available at 10.1007/s00330-021-07858-1. Liver cirrhosis is the end stage of chronic liver disease and a major global health condition, especially due to its variety of severe complications caused by portal hypertension such as variceal bleeding, ascites, and hepatic encephalopathy . AlthougTo assume a diagnosis of liver cirrhosis, different morphological criteria have been described for standard imaging modalities . HoweverA method that could objectively assess relevant features automatically within radiological images could support the radiologist in diagnosing liver cirrhosis, leading to greater accuracy and less variation in reading performance. Since 2012, when a deep learning technique has shown superior performance in the prominent ImageNet challenge for the first time, especially CNNs have become the gold standard for image classification and segmentation . Deep leHowever, a disadvantage of CNNs is the requirement of a large number of pre-classified images, which serve as training data. Instead of training a neural network from scratch with a small data set, it has proven advantageous to use a technique called transfer learning . The basThe aim of this study was to investigate the capabilities of deep transfer learning (DTL) to identify liver cirrhosis in standard T2-weighted MRI and to evaluate the diagnostic performance against radiologists with different levels of experience.i.Patients with known liver cirrhosis of any stage: Inclusion criterion was the presence of histologically or clinically defined liver cirrhosis of any clinical disease severity. Exclusion criteria were the presence of focal liver lesions at the level of portal vein bifurcation or a past medical history of hepatic surgery Fig. .ii.Patients without known liver disease: From the same period, a randomly selected control group was recruited, which consisted of patients without known liver disease. Exclusion criteria for the control group were the same as those applied for the cirrhosis group.This retrospective study was approved by the institutional review board with a waiver of written informed consent. Patients who underwent liver MRI at our institution for standard diagnostic purposes between 2017 and 2019 were included. Two groups of patients were identified and included in the final study cohort:Patient characteristics were retrieved from the clinical information management system of the referring institution. An overview of the MRI indications for the two groups is provided in Supplement As this study aimed to determine the diagnostic utility of DTL to detect liver cirrhosis based on morphological hallmarks of liver cirrhosis, T2-weighted imaging was used for analysis. In detail, images of a standard T2-weighted respiratory triggered multi-slice turbo spin echo sequence with non-Cartesian k-space filling with radial rectangular blades (Multi Vane XD) were used. For each patient, a single-slice image at the level of the caudate lobe was exported for DTL analysis . All examinations were performed on clinical whole-body MRI systems . Detailed imaging parameters are listed in Supplement Image data were randomly divided into training data (70%), validation data (15%), and test data (15%) using a custom Matlab script (MathWorks). Details of the preprocessing prior to training are listed in Supplement Images were analyzed using two different processing pipelines. In the first pipeline, an image segmentation network was applied prior to the classification task. In the second pipeline, the classification was performed directly on the unsegmented images.For segmentation, a CNN following the principle architecture of a U-net model was implemented . Its desResNet50 as a well-established CNN with 50 trainable layers and residual connections was used for the classification task in both pipelines. The model was pre-trained on the ImageNet archive and implemented in pytorch’s torchvision package . DetaileThe DTL methods developed in this work were trained in two phases. First, only non-pretrained layers were trained and all pre-trained parameters of the convolutional layers were kept constant. To further investigate whether varying the pre-trained parameters may improve the reading performance of the CNN, the parameters of the pre-trained convolutional layers were made variable in a second phase. The one cycle learning rate policy was applied for fine-tuning of the pre-trained models for liver segmentation and classification of liver cirrhosis . All expTo compare the performance of the DTL analyses to the performance of healthcare professionals at different experience levels, validation and test data were also classified independently by a radiology resident (A.F.) with 4 years of experience in abdominal imaging and a board-certified radiologist (J.A.L.) with 8 years of experience in abdominal imaging.χ2-test was performed to test for significant differences in accuracy between the DTL-based classification and the readers in SPSS Statistics 24 (IBM). For the test set, calculations of balanced accuracy, receiver operating characteristic, and precision-recall analyses were performed with scikit-learn 0.23.2 [The 95% confidence interval of the DTL-based classification accuracy was determined by the Clopper-Pearson method and a n 0.23.2 –24.In order to assess the classification performance of the entire first pipeline (including prior segmentation), the segmentations of the CNN  were used for the validation and test set of the classification network. In addition to evaluating the method by its performance on the validation and test data set, gradient-weighted class activation maps (Grad-CAMs) were generated . This teA total of 713 patients  were included. Of those, examinations of 572 patients were acquired at a field strength of 1.5 T. The remainder were examined on 3.0 T. A total of 553 patients  with a confirmed diagnosis of liver cirrhosis based on clinical or histopathological criteria were included  as well as the board-certified radiologist   of 0.99  for validation data (vACC) and 0.96 (0.90–0.99) for test data (tACC) was achieved. For the classification on unsegmented images, vACC was 0.97 0.92–0.99) and tACC was 0.95 (0.89–0.98). The accuracy of the DTL pipeline for classification of cirrhosis with prior segmentation of the organ was significantly higher compared to the resident  achieved high accuracy. However, the accuracy for the detection of liver cirrhosis was slightly higher for the DTL pipeline with prior segmentation. This result may be attributed to the following advantages of upstream segmentation:For both methods, image areas relevant for the CNN’s decision were investigated applying the Grad-CAM method . The resFuture work should also address whether a multi-task-learning architecture, which would simultaneously optimize segmentation and classification performance, has advantages over the presented pipeline. In addition, the method could be extended by an automated selection of the 2D slice at the level of the caudate lobe to allow fully automated prediction of cirrhosis based on T2-weighted imaging.Our study has several limitations. First, the DTL model has been trained for the identification of liver cirrhosis only and does not support the detection of very early signs of tissue fibrosis, which might be present in early hepatopathy. However, this was not the aim of this proof-of-principle study, but to investigate the hypothesis that ImageNet pre-trained models are generalizable to T2-weighted MRI imaging and allow the assessment of imaging features of liver cirrhosis. The investigation of an automated classification of early signs of tissue fibrosis and different stages of fibrosis will be the next step in the evaluation of deep transfer learning–based approaches based on standard T2-weighted MRI imaging.Our study collective included a broad range of cirrhosis severities (according to the Child-Pugh score) and different etiologies of cirrhosis. To account for the difference in the number of patients with liver cirrhosis and patients without liver disease, additional performance measures were assessed. According to the balanced accuracy, the method trained on segmented images performs at expert level. However, the DTL method shows a higher sensitivity and a lower specificity compared to the board-certified radiologist, which may be a result of the class imbalance of the dataset. An expert level classification performance of the DTL method trained on segmented images is furthermore underlined by the precision-recall analysis.Another limitation is that the classification was based solely on T2-weighted images. In contrast to that, additional pieces of information such as different MRI sequences as well as clinical and laboratory parameters are typically available for diagnosis in clinical routine. However, in our study, high diagnostic accuracy was shown for both the classifier and clinical experts, even if the diagnosis was based on only one anatomical sequence. Future studies may evaluate whether a multi-parametric approach or the inclusion of clinical parameters can further improve diagnostic performance.This proof-of-principle study demonstrates the potential of DTL for the detection of cirrhosis based on standard T2-weighted MRI. The DTL pipeline for the image-based diagnosis of liver cirrhosis demonstrated classification accuracy at expert level. An application of the pipeline could support radiologists in the diagnosis of liver cirrhosis and has the potential to improve consistency of reading performance.ESM 1(DOCX 42 kb)


Exposure of an activated SABRE sample  to 10 mg of the most promising scavenger (5S) resulted in <1 ppm of iridium being detectable by ICP-OES after 2 min of exposure. We propose that combining the approach described herein with other recently reported approaches, such as catalyst separated-SABRE (CASH-SABRE), would enable the rapid preparation of a biocompatible SABRE hyperpolarized bolus.In recent years the NMR hyperpolarisation method signal amplification by reversible exchange (SABRE) has been applied to multiple substrates of potential interest for in vivo investigation. Unfortunately, SABRE commonly requires an iridium-containing catalyst that is unsuitable for biomedical applications. This report utilizes inductively coupled plasma-optical emission spectroscopy (ICP-OES) to investigate the potential use of metal scavengers to remove the iridium catalytic species from the solution. The most sensitive iridium emission line at 224.268 nm was used in the analysis. We report the effects of varying functionality, chain length, and scavenger support identity on iridium scavenging efficiency. The impact of varying the quantity of scavenger utilized is reported for the three scavengers with the highest iridium removed from initial investigations: 3-aminopropyl ( Of particular interest was a systematic assessment of the impact of chain length, differing nitrogen-containing functional groups and the identity of the solid support employed. This work represents an important step towards the future in vivo application of SABRE, where high concentrations of cytotoxic iridium complexes may need to be rapidly removed in order to prepare a biologically compatible hyperpolarized bolus  was observed through monitoring the T1 values associated with pyridine, before and after the addition of ethylenediamine or diethylenetriamine as shown in The displacement of pyridine from the activated species [Ir(IMes)(pyridine)T1 of pyridine in samples A and B is significantly reduced when in the presence of [Ir(IMes)(pyridine)3(H)2], shown in samples C–E, due to interactions with the extended spin system surrounding the iridium  in which the hydride resonance is present at −23.61  from solution by scavenging may be a timely solution as recent work has demonstrated this iridium species is cytotoxic ,34. [Ir to background levels of iridium present within the hyperpolarized T1 of a suitable substrate [SH-SABRE , enable SH-SABRE . Therefoubstrate ,60.