Perinatal mental health problems are linked to poor outcomes for mothers, babies and families. In the context of Low and Middle Income Countries (LMIC), a leading risk factor is gender disparity. Addressing gender disparity, by involving fathers, mothers in law and other family members can significantly improve perinatal and maternal healthcare, including risk factors for poor perinatal mental health such as domestic violence and poor social support. This highlights the need to develop and implement gender-transformative (GT) interventions that seek to engage with men and reduce or overcome gender-based constraints. This scoping review aimed to highlight existing gender transformative interventions from LMIC that specifically aimed to address perinatal mental health  and identify components of the intervention that were found to be useful and acceptable. This review follows the five-stage Arksey and O’Malley framework and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist. Six papers that met the inclusion criteria were included in the review (four from Africa and two from Asia). Common components of gender transformative interventions across studies included couple-based interventions and discussion groups. Gender inequity and related factors are a strong risk for poor perinatal mental health and the dearth of studies highlights the strong need for better evidence of GT interventions in this area. Research and policies related to perinatal mental health have demonstrated how poor mental health both in pregnancy and postpartum is prevalent in the form of anxiety and depression, and may influence pregnancy outcomes and the health of the foetus and infant ,2. UntreSome of the well-established risk factors for poor perinatal mental health, particularly anxiety and depression, are related to gender inequity, especially in LMIC settings. These include partner violence (Intimate partner violence (IPV), Domestic violence (DV) and Gender-based Violence (GBV)), younger age, poor social support, low education and male infant preference ,11,12. OA few interventions for perinatal health in general that have addressed gender-related factors and focused on enhancing support systems for pregnant women or addressing gender inequity in the family have found improvement in rates of postpartum depression as well ,20,21. Wexisting inequalities; however, they are not aimed at role-reversal or changing gender norms  AND male engagement interventions OR family interventions AND LMIC/Low and Middle income countries .The inclusion and exclusion criteria were developed by the authors and are shown in Additionally, systematic reviews of interventions that targeted prevention or reduction of violence against women, girls or mothers were also included in the review. Since maternal and child’s health and wellbeing are strong predictors of mental health ,37, psycBox 1Inclusion criteriaPublished in EnglishPrograms designed and implemented in LMIC countries.a.Improvement in social support or better relationship with partner;b.Decrease in depression, anxiety or any Common Mental Disorder;c.Decrease in Domestic violence or Intimate Partner Violence.Studies having any one of the three mental health outcomes in the perinatal period which includeAny study design—RCTs, Non Randomised Controlled studies, Case Control studies, pre post intervention studies.Publication years 2007–2022.Exclusion criteriaStudy location not in LMIC.Studies not relating to perinatal period.Studies not relating to mental health or risk.Studies not relating to maternal mental health.Data were extracted according to the PRISMA-ScR ,39 checkUsing a narrative approach, these interventions were critically analysed by VS, AR and PC and reported in terms of intervention characteristics, risk of bias/methodological quality, categorisation of outcomes and identification of gaps in evidence as previously noted in scoping reviews that focused on GT interventions . A totalFrom the search process, 16 studies were identified since they met the inclusion criteria. However, 10 studies were excluded because 7 studies focused on gender but not on the gender “transformative” aspect and did not assess mental health outcomes and 3 studies did not assess perinatal mental health conditions. The six finalised studies ranged primarily between 2015–2022, although the study attempted to include studies over a period of 15 years refer to . Only onMost of the identified studies utilised group discussions as the basis to facilitate critical dialogue and awareness regarding gender roles and mental health. In the Bandebereho couples’ intervention, from Rwanda, small groups of critical reflection and dialogues were initiated with couples and men . SimilarThis section reports practical aspects of the interventions  and impoA successful couples’ intervention designed by Doyle et al. , implemeA similar and older study from India targeted young married women, their husbands as well as family members to address and modify gender norms . The stuRaj et al.  conducteAnother intervention that was targeted for women, children and men/fathers/co-parents in Mutasa district, Zimbabwe, used community-based training and discussion groups that addressed services for mothers, HIV transmissions and engaging in problem-solving therapy. Results indicated that addressing gender inequality improved maternal mental health . The intAlong the lines of men’s involvement, the study by Bapolisi et al.  focused A recent study that contributed towards the current limited literature, was Comrie-Thomson et al.’s  trial onHowever, the aforementioned GT interventions particularly focused on prenatal, maternal care and personal empowerment. Alternatively, it is indicative of how programs and interventions should focus more intentionally on postnatal mental health care, particularly gender-intentional postpartum family planning interventions to ensure antenatal and intrapartum care that were earlier provided remained sustainable and effective. By implementing these interventions, it can be inferred that perinatal mental health will significantly improve eventually decreasing mental health concerns such as anxiety and depression. Possible adverse events that have to be considered includes increased tension in parent relationships and familial relationships due to changed expectations and behaviours . TherefoDue to limited studies, the review could not identify major contexts in which GT interventions were designed. However, it was vastly noted that GT interventions had multifold implications with respect to improvement on mental health, maternal mental health, decreased IPV and GBV and improved couples’ relationships and homecare practices. It was previously noted that gender related factors seem to play a strong role in mental health problems in pregnancy and the postpartum especially in the LMIC region . TherefoSimilar to previous reviews and studies, the results in the present paper indicate how main components of interventions to improve maternal mental health consist of quality time with the infant, group sessions with husbands or family members, counselling sessions and psychoeducational sessions ,52. InteIn programs that focused on fatherhood, targeting men, fathers and husbands, interventions mostly focused on educational sessions on gender-roles ,54 indicFurthermore, fatherhood programs when designed from a systemic lens can significantly support and protect women, families and children from violence. In support, a systematic review of male engagement in GT interventions for women in the community highlighted that 11 out of 12 GT interventions revealed a significant change in men’s attitudes towards gender norms, establishing gender equality . This isFurther, the aforementioned studies do not acknowledge the structural norms that influence masculinity and how norms related to masculinity are also changing . MoreoveTo achieve long-term, sustainable change, community-level interventions need to be accompanied by policies that support the changes men undergo through GT interventions. Future recommendations for gender transformative interventions include taking a more relational perspective that attempts to integrate men and boys with efforts to empower women without adapting the attitude of “saving women and families” since it was noted that many men engaging in activism for equality or trials that promote equality are not disconnected from an inherent saviour complex .Studies could also focus on developing strategies that address change at the level of families and communities leading to sustainable changes through involvement of other family members, which also result in sustainable and lasting effects. Additionally, future studies could focus on programmatic efforts on gender barriers that accompany life stages, that range from helping newly married couples with no children to delay in their first pregnancy. Developing GT interventions for specific groups such as those facing perinatal loss and adolescent mothers is needed. GT studies need to provide more information about how men were encouraged to participate in these trials and stay engaged through the course of multiple sessions, which components were preferred by the groups and whether the gender of the facilitators made a difference and if groups should be men only or combined. This information will enable future researchers to help in better planning of future GT intervention studies for perinatal mental health including deciding the “dose” of the intervention in addition to the methods.Moreover, some reports ,56 focusIt is necessary to remain cautious while interpreting the findings of this review because the evidence is limited due to the small number of studies that were identified. Moreover, since the synthesised studies were not methodologically similar, the findings of the current review cannot be generalised. Our findings and recommendations are partially informed by the studies and their limitations, also accounted for, in our analysis. Moreover, given the sensitivity and stigmatised nature of these issues, consideration must be given to the presence of social desirability bias which may have influenced disclosure and involvement of participants in the programs. Future research may examine the dose or the optimum length of the intervention itself and on whether treatment gains are maintained over longer follow-up periods.Our review has highlighted a need for GT interventions that focus on male engagement, family members and community as a whole. Our review also highlights the methodological strengths and deficits in existing interventions, paving the way for future research to address these limitations and mindfully develop programs that yield effective maternal health outcomes. Lastly, by emphasising programs implemented in the LMIC region, our review addresses the need to develop shared goals that address gender-based violence, cultural norms and family dynamics since perinatal and maternal mental health outcomes cannot be improved in isolation.


Despite the advent of numerous biologic therapies and small molecular drugs targeting specific immune pathways, at least 40% of PsA patients exhibit poor response.Given the complexity and heterogeneity of signalling pathways resulting in synovio-entheseal disease in PsA; new treatment strategies must be evaluated to induce deep and sustainable clinical responses in all the phenotypic domains.In patients who do not achieve remission in all disease aspects on biologic monotherapy or combination of a biologic therapy with an oral synthetic agent; dual targeted anti-cytokines strategies or combined biologic with a targeted oral small molecule are a possible treatment option.A 40-year-old attended our rheumatology department in 2010 with peripheral synovitis, dactylitis and scalp psoriasis. A clinical diagnosis of PsA was made and she was commenced on combination methotrexate and sulphasalazine.In 2011, therapy was escalated to include etanercept and methotrexate due to persistent active disease clinically and on nuclear medicine bone scan.Between 2011 to 2015, sequential bDMARD switches including certolizumab, infliximab and adalimumab, failed to put the disease in remission.Due to loss of effect, adalimumab was switched to secukinumab in early 2016. A few months later, while on secukinumab, she developed new onset Crohn’s disease and required treatment change to ustekinumab.In August 2018 following a prolonged flare, ustekinumab was stopped and tofacitinib was started. The disease went in LDA until September 2020 when hospital admission for a severe PsA flare was required. She had dactylitis of 3 digits, a left temporomandibular joint effusion on ultrasound and elevated acute phase reactants. A treatment change to abatacept resulted in primary failure and abatacept was replaced with baricitinib.In March 2021, she attended clinic with new nail changes, dactylitis of 3 digits and a large left knee effusion. She underwent a diagnostic arthroscopy of the left knee and wash-out in May 2021 which showed a macroscopic synovitis score and vascularity score of 100% respectively. Synovial histology showed evidence of chronic synovitis with abundant plasma cells.Following the arthroscopy and careful discussion, it was decided to initiate combination therapy with adalimumab biosimilar and tofacitinib in June 2021. The patient was assessed at 2 months following starting combination therapy and a dramatic clinical and biochemical was noted. CRP had improved from 139.9mg/L to 6.3mg/L. She was mobilising without an aid for the first time in years. Both her psoriasis and Crohn’s disease were also well controlled.While the outcomes of patients with psoriasis have dramatically improved with monoclonal antibody therapies targeting IL-23 and IL-17A; achieving a measurable low disease activity state such as minimal disease activity (MDA) for musculoskeletal manifestations of psoriatic disease is infrequent. Due to the heterogeneity of disease in PsA, multiple cellular pathways are involved in the pathogenesis resulting in recalcitrant disease in a subgroup of patients. These patients, like our case, exhibit poor response to the current therapeutic paradigm in PsA.In such patients, treating one disease domain, one type of cell or a single pathway at a time is unlikely to result in meaningful disease control and remission may be unachievable thus subjecting patients to sustained joint inflammation and damage seen in PsA. Very little data exist regarding the safety of dual immunomodulator therapies for concomitant psoriasis and psoriatic arthritis. Safety concerns such as infectious risks are important considerations with such strategies; however, the targeted second-generation anti-cytokine biologics and targeted JAK-I have exhibited improved safety profiles with regards to infections.In this case, following careful discussion with our patient, she felt that the prospect of possible reduction in her musculoskeletal symptoms outweighed the potential safety concerns.Multiple cases are reported in the literature regarding the use combined biologic strategies in psoriatic disease; the most common combination reported being anti-TNF therapy and ustekinumab with varying degrees of response. Prospective, high-quality studies are needed to identify safe and efficacious dual strategies in PsA to pinpoint dosages, sequence and frequency of therapies.This case truly highlights the heterogeneity and complexity that accompanies psoriatic disease and as such, modulating a single pathway may not be sufficient to address all the phenotypic domains .While physicians are often, understandably, hesitant to prescribe combined immunomodulatory therapies due to concerns regarding potential complications, such strategies should be considered in debilitating cases of psoriatic disease who fail to respond to conventional treatment as they have the potential to foster deep and long-lasting remission.Our case highlights that a patient-centred approach with patient involvement in clinical decisions regarding their disease is required. With such strategies, patients and clinicians, both, should balance the potential associated risks particularly infectious risk.Further studies are required to better determine the efficacy and safety profile of combined immunomodulatory therapies in psoriatic disease.


Medication-assisted treatment (MAT) is an evidence-based therapy for opioid use disorder (OUD) that has not been fully implemented in rural areas due to patient, provider, and logistical barriers. Limited information is available on provider perceptions of barriers to MAT in rural Central Appalachia which has very high rates of OUD compared to the rest the United States.Determine perceived barriers for potential prescribers to using MAT, including buprenorphine, as part of treatment for OUD in West Virginia.A 30-question, anonymous survey was sent to physicians, physician assistants and advanced practice registered nurses using an online link. Link was distributed through the WV Medicaid provider list, professional association and institutional contact lists, and social media. Comparisons were made by provider waivered or non-waivered status.Overall, 84% of waivered providers (n = 77) and only 8% of non-waivered providers (n = 341) indicated ever prescribing a form of MAT for OUD; 73% percent of waivered providers were currently prescribing MAT and accepting new patients with OUD. Only 4% of non-waivered providers were currently prescribing MAT and 21% were currently accepting new patients with OUD. Lack of available mental health and psychosocial support services and concerns about diversion or misuse of medication were the top perceived barriers to implementing MAT programs.Implementing strategies to improve access to behavioral health care including telehealth and apps, provider training and addressing stigma around OUD treatment were identified as priorities that would help increase providers’ willingness to prescribe medications for OUD treatment. Higher rates of occupational injuries and chronic pain coupled with declining economic opportunities and a flood of prescription opioids have fueled rising rates of opioid misuse, resulting in rates of opioid use disorder (OUD) in Central Appalachia that are much higher than other parts of the U.S.6Efforts are currently underway in West Virginia (WV) to expand buprenorphine treatment via a hub-and-spoke model.A cross-sectional study using total population sampling was conducted using an online survey link and recruitment script. The survey link embedded within the recruitment script was sent to the email on file to a total of 20,762 individuals on the WV Medicaid provider list at the time of the study. This list included physicians , physician assistants (N=1833) and advanced practice registered nurses (N=3262). Additional requests to complete the survey using the link sent to the e-mail address on file with WV Medicaid were through professional association and institutional contact lists, and social media.Participants completed an anonymous 30-item survey adapted from a national studyResults are presented using descriptive statistics. Data regarding barriers to providing MAT as part of OUD treatment were collected on an ordinal scale and independent samples Mann-Whitney U tests (α=0.05) with Bonferroni corrections to account for multiple comparisons were used to evaluate differences in mean ranks as a function of provider waiver status using SPSS v26. Note that physicians, nurse practitioners, and physician assistants must obtain a waiver from the Drug Enforcement Administration to allow them to prescribe buprenorphine for the treatment of opioid use disorder.The survey received 780 clicks and the final sample size, based on those who accessed the survey, was 431 respondents who completed at least one question on the survey (55.3%). A total of 303 respondents completed the entire survey (38.8%). Respondents’ age ranged from 25 to 77 years .Sample characteristics are summarized in Major themes that emerged from open comments on reasons providers chose to offer MAT in their clinics they listed better outcomes, number of patients presenting with the problem, lack of providers for pregnant women, patient request, effectiveness, and starting practice in a clinic already providing MAT. Open comments indicated that stigma towards individuals with an OUD and providers who use medication to treat OUD, administrative burden, diversion, and lack of training/comfort in prescribing were perceived barriers to implementing MAT programs. Mean rank was higher for non-waivered providers compared to those with waivers on all perceived barriers to incorporating MAT into treatment of OUD except financial/reimbursement concerns. Lack of available mental health or psychosocial support services and concerns about diversion or misuse of medication were ranked as first and second for all providers, in opposite order for non-waivered and waivered providers, respectively. Statistically significant differences in mean ranks of perceived barriers dependent upon waiver status included: lack of available mental health or psychosocial support services, concerns about diversion or misuse of medication, concerns about legal liability, lack of specialty backup for complex problems, concerns about attracting drug users to practice, outside scope of practice, lack of confidence in ability to manage patients with OUD, and lack of patient need .The study goal was to identify the perceived barriers, willingness, and ability to treat OUD in WV, and identify potential targets for policy and procedural changes to support MAT as part of OUD treatment. Only 18% of respondents had completed the training requirements and received their waiver to prescribe buprenorphine as part of OUD treatment. More than half of those who did not currently have a waiver to prescribe buprenorphine indicated a willingness to complete the requirements if free training and compensation were provided. More than 80% of waivered providers indicated they had ever prescribed an OUD MAT drug, higher than the national average of 58%.all physicians recommended that providers follow all DEA rules strictly (available on the DEA and SAMHSA websites),keep detailed records, and be prepared for the DEA to visit. Physicians who reported strictly following these rules did not report being concerned about the DEA.17Lack of available mental health or psychosocial support services and drug misuse/diversion were the two most serious concerns for both waivered and non-waivered providers, the same top barriers identified in the national study from which the current survey was adaptedIt is noteworthy that five of the top six concerns were identical for those providers who already held the waiver to prescribe buprenorphine and those who had not yet received the waiver. While there were statistically significant differences between their ratings, as well as differences in rank order, most of the concerns were shared. The very practical concern for financial/payment issues was ranked fourth by those currently waivered but ranked twelfth for those not without a waiver.suboxone is a drug of abuse, I strongly believe there should be a better way, substitutes one addiction for another as well as attracting drug users to practice. The latter comment seemed to be a more serious concern for non-waivered providers.Results indicated stigma around provision of MAT for treating OUD. Respondents were more likely to agree reimbursement should be increased for mental health more generally than for OUD specifically, consistent with previous studies exploring implicit bias.Medication-assisted treatment expansion efforts are being implemented across the state and preliminary findings indicate an increased capacity to address the substance use disorder (SUD)/OUD epidemic, including buprenorphine as part of treatment.The WV State Substance Use Response Plan goals for 2020–2022 include increasing the number of providers obtaining waivers by 20% each year, training current and future health care providers on evidence-based approaches to treatment and increasing the number of in-state clinical providers to meet needs of residents seeking SUD treatment.Limitations include a low response rate and small sample size compared to the number of potential prescribers in WV, limiting generalizability of findings. Two percent of the total population targeted by the survey email responded. Conclusions regarding implicit bias are limited due to the large difference in number of respondents for each question, potential confounds with question order, and less stigmatizing language used in the current study (opioid use disorder) compared to previously published work that used “addiction.”11What is already known on this topic?Medication-assisted treatment (MAT) is an evidence-based therapy for opioid use disorder that has not been fully implemented in rural areas due to patient, provider, and logistical barriers.What is added by this report?The current study identified perceived barriers of potential prescribers to use MAT including buprenorphine as part of treatment for OUD in West Virginia, a mostly rural state entirely within Appalachia.What are the implications for future research?These findings can inform efforts to increase access to SUD treatment in the Appalachian region by prioritizing, implementing, and evaluating activities that address providers’ perceived barriers to implementing MAT as part of OUD treatment.


Motor control, movement impairment, and postural control recovery targeted in rehabilitation could be affected by pain. The main objective of this comprehensive review is to provide a synthesis of the effect of experimental and chronic pain on postural control throughout the available literature. After presenting the neurophysiological pathways of pain, we demonstrated that pain, preferentially localized in the lower back or in the leg induced postural control alteration. Although proprioceptive and cortical excitability seem modified with pain, spinal modulation assessment might provide a new understanding of the pain phenomenon related to postural control. The literature highlights that the motor control of trunk muscles in patient presenting with lower back pain could be dichotomized in two populations, where the first over-activates the trunk muscles, and the second under-activates the trunk muscles; both generate an increase in tissue loading. Taking all these findings into account will help clinician to provide adapted treatment for managing both pain and postural control. Chronic pain is defined by the International Association for Study of Pain (IASP) as “an unpleasant sensory and emotional experience associated with, or resembling that associated with, actual or potential tissue damage”  lasting Postural control, either in static or dynamic conditions, is an essential requirement to perform daily activities . The uprThe main aim of this comprehensive review is to provide a synthesis of the effect of experimental and chronic pain on postural control by combining knowledge from the literature and identifying the potential impact of pain on the sensorimotor mechanisms involved in postural control. This review also summarizes the evidence supporting the importance of including postural control in the clinical assessment of patients suffering from chronic pain. Improving the knowledge of pain interference on postural control could help with developing new and adapted therapeutic approaches for patients presenting chronic pain.The process leading to pain starts with the stimulation of nociceptors . There aThe nociceptive Aδ and C fibers surround the outermost layer of the dorsal horn. They enter the dorsal horn and end in the superficial layers  or extend into the deep layers (Lamina V), probably via interneurons . The lamBecause pain is a complex multifactorial subjective experience, a large brain network is engaged during nociceptive processing. Numerous central nervous system structures  consistently respond to transient nociceptive stimuli causing pain. The activation of this pain matrix or pain signature has been related to perceived pain intensity, both within and between individuals . FollowiExperimental pain has been used to determine the potential impact of pain on balance control. By inducing heat pain on the lower leg muscle (45 °C), Blouin et al.  showed aA systematic review, including 16 studies, reported that lower back pain (LBP) results in COP parameters alteration  ,20. PainSome studies also reported a decrease in proprioceptive acuity, that is, patients with back or neck pain have less accurate positions sense ,59 suggePersistent pain also alters cognitive processes. As cognition contributes to balance control ,68,69, iPain is intimately linked to the activation of a complex cerebral network, as mentioned above, and involves cortical reorganization. Results from studies inducing pain confirmed a causal relationship between pain and cortical changes ,75,76,77Using neuroimaging and neurostimulation, numerous studies showed that patients with chronic pain, such as complex regional pain syndrome (CRPS)  or phantAt a lower anatomical level, spinal control may likewise be affected by pain conditions. To date, experimental pain studies failed to provide strong evidence of a potential inhibitory or facilitatory effect at the spinal level . InvestiThe assessment of motor control in patients presenting with CLBP considers three main classes of motor tasks, evaluating the control of the trunk in a steady-state condition (posture and movement) or challenging by predictable or unpredictable perturbations . RegardiThere is no doubt that pain modifies movement and motor control, illustrated by postural control alteration. This review showed that both experimental and chronic pain lead to postural control impairments. Although cortical modification has been largely investigated with pain localized at the upper limb, cortical and spinal modulation focusing on spine and lower limb muscles have yet to be determined. Finally, different phenotypes of motor control by tight or loose trunk control should be considered to provide adapted treatment for managing both pain and postural control in patients presenting with chronic lower back pain.


In this review, we examine this previously overlooked mechanism by summarizing recent advances in the understanding of protein–protein crowding and its prevalence in cellular membrane-shaping processes.Continuous reshaping of the plasma membrane into pleomorphic shapes is critical for a plethora of cellular functions. How the cell carries out this enigmatic control of membrane remodeling has remained an active research field for decades and several molecular and biophysical mechanisms have shown to be involved in overcoming the energy barrier associated with membrane bending. The reported mechanisms behind membrane bending have been largely concerned with structural protein features, however, in the last decade, reports on the ability of densely packed proteins to bend membranes by protein–protein crowding, have challenged prevailing mechanistic views. Crowding has now been shown to generate spontaneous vesicle formation and tubular morphologies on cell- and model membranes, demonstrating crowding as a relevant player involved in the bending of membranes. Still, current research is largely based on unnatural overexpression of proteins in non-native domains, and together with efforts in modeling, this has led to questioning the  The conventional textbook presentation of a plasma membrane, containing individual proteins floating in a lipid bilayer, does not provide a realistic picture of the membrane system: a heterogeneous and dynamic environment comprising domains, protein clusters and a high degree of protein coverage. Historically, the plasma membrane was viewed as a fluid-mosaic bilayer with few proteins in a vast sea of lipids . This siThe plasma membrane is the site of action for an abundance of cellular processes, many of which require membrane shape remodeling. Membrane bending is what allows for the uptake of nutrients, waste disposal, cell migration and much intra- and extracellular communication . CentralDespite a large body of research highlighting conserved structural features as the driver for membrane bending, in the last decade an overlooked and highly disputed entropic mechanism, driving membrane bending via simple protein–protein crowding, has emerged, challenging prevailing views on how membranes adopt their shapes. Crowding drives curvature generation via lateral pressure created from stochastic collisions at one side of a membrane surface if that pressure is not counteracted on the opposing side of the membrane. This entropic mechanism is emerging as a relevant player in the dynamics of membrane-shaping machinery in cells including the generation of various cell surface morphologies, sorting of cargo in clathrin coated pits and potentially virus envelope budding Figure  24–28]..24–28].In this review, we summarize recent literature to evaluate the impact of the crowding mechanism and its interplay with other structural mechanisms, e.g. wedge insertions and scaffolding. We comment on the biological relevance of crowding by examining the ability of the cell membrane to form crowded domains, and finally suggest directions for future quantitative experimental and modeling efforts needed to further our understanding of the role that protein–protein crowding plays in membrane remodeling.Various membrane-bound proteins continuously diffuse within the plasma membrane in a stochastic manner with frequent lateral collisions of their hydrophilic ectodomains in a narrow region above the membrane. The volume of this narrow region is controlled by the surface curvature and hence the translational entropy of the bound proteins will increase upon membrane bending. This gain of entropy will increase as the number of bound proteins increases, eventually overcoming the elastic energy penalty associated with bending. In other words, membrane bending increases the effective distance between the protein ectodomains Figure A and conWith the heterogeneous complexity of the plasma membrane in mind, combined with estimated protein coverage of around 30–50% on the membrane surface , 33, it Accumulated experimental results over the past decade have shown various protein domains are capable of inducing bending through crowding at certain threshold concentrations. Especially, attention has been on experiments concluding that proteins, generally not associated with membrane bending processes, can induce membrane curvature at high area coverage. An interesting example is GFP, a commonly used fluorescent protein, not containing any structural features associated with crowding, which has been shown to both induce spontaneous tubulation in GUVs and reduce vesicle size diameter in vesiculation experiments , 38. In The wide variety of structures and proteins associated with membranes and curvature-inducing events indicates that crowding is a mechanism with potential to influence a huge number of budding and fission processes in the cell. For example, viral budding of corona viruses or influenza viruses could partly be driven by protein crowding of various spike proteins containing large outer domains  Figure C. In thi∼10 nm) . Yet, suWhether the crowding mechanism is biologically relevant, and underlying or assisting other bending mechanisms is still being debated. Especially the bending effect from helix insertion versus crowding has attracted significant attention, and although both mechanisms have been shown to induce curvature, disagreement still exists on the biological relevance and relative impact of each, since they can often be expected to work synergistically in the same process Figure . Proteinic helix , 25. Thiic helix  on ENTH ic helix . In ref.ic helix , howeveric helix  comparedCellular processes are unlikely to employ single mechanisms for curvature generation, but rather harness multiple of these mechanisms to remodel membrane shape. Literature highlights the difficulty in separating out single mechanisms for membrane bending due to the fact that curvature-generating proteins embody a multitude of features that are associated with membrane remodeling. For example, Amphiphysin1 contains intrinsic curvature and an IDP domain, both of which are thought to effectively crowd membranes, likewise Epsin 1 could drive curvature through insertion of its amphipathic helix and via its IDP domain . CertainRelatively high protein coverage is needed for proteins to generate steric pressure in the 2D plane of the membrane sufficient to induce shape transitions . HoweverIn cells, diffusion barriers consisting of membrane domains  or cortiIn addition, as pointed out by Kozlov et al. , if upcoDespite the evidence that crowding can act as a driver for membrane bending, both in cells and model membranes, the effect of crowding, and in which biological processes it plays a part, is still far from being fully elucidated. In the field, the focus has been on demonstrating crowding as a general mechanism, characterized by the spontaneous generation of membrane tubes, vesicles, pearls and similar structures , 24, 26.Designing experiments to identify the underlying bending mechanisms and provide quantitative evidence for crowding is difficult, thus modeling has been a key factor when discussing biologically relevant systems. However, disagreement on the significance of the modeled crowding effect still exists in published papers , 67, thuIf crowding plays a significant role in driving membrane reshaping, this potential ‘bending’ force should be measurable with highly sensitive force detection like e.g. optical tweezers which are routinely used for extracting membrane tethers from cells , 69, GPMCurrent knowledge obtained from multiple approaches including advanced experimental techniques and modeling has made it clear that crowding is indeed an important factor in shaping membranes at nanoscale. Looking forward, the focus must naturally shift towards identifying the processes in which crowding plays a role and characterize the relative, effective contribution of various biophysical membrane-shaping mechanisms. Advanced experimental techniques and rapid progresses in multiscale computer simulations now provide a fantastic opportunity to make a synergetic effort for decoupling and quantifying these contribution. In particular, the combination of highly sensitive force measuring tools like optical tweezers and quantitative imaging could reveal interesting details on how crowding differs for various proteins with different domain sizes and stalk lengths represented in cells. Future endeavors using a palette of experimental techniques together with modeling will undoubtedly give a more nuanced picture of the role of crowding in biology.The plasma membrane of cells is a highly crowded environment containing numerous types of proteins which give rise to phenomena such as entropic pressure, excluded volume effects and steric repulsion among the proteins. Evidence is now emerging that these physical phenomena are responsible for bending membranes and hence could be critical factors in a plethora of essential cellular functions involving membrane remodeling. In combination with molecular engineering and model systems the crowding effect can be tuned to harness effective control over membrane shapes useful for biological reconstitution and for nanotechnology applications like drug delivery.Current thinking explains membrane shape modulations as driven by motors or by specific protein properties like amphiphilic helix insertion or scaffolding, but is challenged by the identification of protein–protein crowding as a driver of curvature.An increased focus on coherent modeling and experimental design to disentangle and quantify the contribution from crowding in membrane curvature generation is needed to fully validate the importance of this interesting physical effect.


When a patient presents to the ED, clinicians often turn to medical imaging to better understand their condition. Traditionally, imaging is collected from the patient and interpreted by a radiologist remotely. However, scanning devices are increasingly equipped with analytical software that can provide quantitative assessments at the patient’s bedside. These assessments often rely on machine learning algorithms as a means of interpreting medical images.A machine learning (ML) algorithm is able to utilize presented data to adapt and learn without following explicit instructions. ML is a branch of artificial intelligence (AI) and has garnered a great deal of attention over the past decade, due in large part to substantial advancements in data processing and improvements in model performance. ML has proven to be a powerful method for interpreting complex data. Clinicians may understand all the information necessary to classify a patient’s condition, but seldom can they derive an equation that communicates precisely what information is relevant and irrelevant. ML excels at this task and permits scientists to develop solutions without knowing how to explicitly code the answer. In the most common form of ML, called supervised learning, scientists provide data inputs  and corresponding class labels. The machine learning algorithm then determines what input features are relevant to predict the class labels, thus generating a model that can take in novel features and provide a predicted class label as output.One of the most successful methods for solving medical imaging problems is a subfield of machine learning called deep learning (DL). Deep learning was inspired by the complex neural architecture of the human brain, which is organized into interconnected layers of neurons and can solve incredibly complex problems. In the primate visual cortex, simple photoreceptor input is passed through convolutional layers in the ventral visual stream of the brain. Each successive layer produces increasingly complex representations of the photoreceptor input, which permits humans to classify the objects and interpret the scenes they see. Similarly, deep learning algorithms simulate the ventral visual stream by passing image information through multiple layers of a convolutional neural network (CNN). These networks process simple pixel information, form new complex representations, and pass those representations on to subsequent layers for eventual image classification To train a CNN to classify images, pixel values are passed into the initial layer of neurons which are activated by the information . The activations are then fed forward into additional hidden layers which further process the data. The features generated by this process are fed through a final activation function, which provides a classification label in the output layer. To improve model accuracy, algorithm predictions are compared to provided labels. A cost function assesses the difference between model predictions and actual values, awarding a proportional penalty to the model. The goal of the training process is to minimize the cost or penalty awarded to the model. Using an optimization technique called gradient descent, the response weight of each individual neuron in the network is iteratively tuned such that the final classifications better match the expected output, thus reducing the penalty assessed by the cost function. After training on a corpus of images, a novel image can be fed into the algorithm and a predicted classification will be output.Over the past several years there have been huge advances in the use of ML and DL algorithms to address a number of challenges clinically. DL algorithms have been extensively used within the field of radiology where they are used to perform numerous tasks, including segmentation of anatomical structures or local lesions, detection of probable tumors, and classification of lung and breast nodules The example above demonstrates the potential of ML systems to improve clinical care for patients as well as assist radiologists with their clinical workload. However, despite rapid advancements in many medical imaging modalities, similar applications of ML algorithms to point of care ultrasound (POCUS) have been slower to arrive. This discrepancy is present for a number of reasons. First, unlike POCUS imaging modalities such as chest X-ray, CT, and MRI, have standardized imaging protocols. Hospital image archiving infrastructure was designed to store and save imaging data for later use. As a result of the persistent imaging infrastructure for these modalities large, organized imaging datasets have been developed that can be more readily interrogated by DL algorithms. In contrast, images and video acquired at the bedside using POCUS are often used for immediate physician support and not always permanently archived for later analysis. Additionally, the point of care setting inherently introduces variability in data quality even when collected by the same sonographer. Variation in sonographer skill level, image acquisition order, and technique further complicates ultrasound datasets. Even in well-performed scans, imaging distortion and artifacts are often an inescapable reality for POCUS. This results in ultrasound images containing a great deal of “noise” or randomness in the data. Variability is further compounded when combining images from different scanner manufacturers or academic centers into a single dataset. Additionally, ultrasound images often lack global reference structures, making it difficult to determine exactly where on a patient’s body an image was collected. Finally, as an imaging modality, POCUS is relatively new compared to chest X-ray, CT, and MRI, only achieving widespread use in hospitals in the 1990s Nonetheless, the last few years have seen an explosion of novel DL applications within POCUS. DL is uniquely suited for analysis of POCUS because it is able to generate high-level abstractions from a wide array of raw imaging data of varying quality. This ability to “cut through the noise” and draw abstractions and note otherwise missed patterns has been one factor leading to greater use of DL within POCUS. Increased interest in DL has come in part due to unique computational approaches to address the obstacles previously mentioned. Both traditional machine learning techniques  and deep learning methods , auto-encoders), have been employed on ultrasound datasets with good success. Additionally, researchers have utilized innovative techniques such as transfer learning to circumvent some issues related to limited and inconsistent datasets. Transfer learning is the process of initializing a DL model with weights derived from another training task and fine-tuning the model to perform a new task with the goal of reducing the number of trials necessary to learn a similar task DL algorithms have the potential to further increase the utility and adoption of POCUS. Many important uses of ML applied to POCUS are outside the scope of this review, but also include DL algorithms applied to enable novice sonographers in acquiring the best imageHere we will briefly highlight some of the clinical ML algorithms that have been developed for POCUS. To date, there are relatively few real-time ML algorithms available in POCUS (Table 1). With the exception of a few commercially available models, the majority of ML algorithms were developed for US applications using datasets captured from retrospective studies. One barrier to greater adoption of ML models within POCUS is the need to implement software in real-time on the ultrasound device hardware itself. Adoption of ML in POCUS is challenging not only because software and hardware must be integrated to enable real time applications, but also because most recently developed ML models lack sufficient clinical validation and FDA approval to be used in the clinical setting. While this regulatory milestone may seem distant, it has already been achieved for similar medical imaging applications. In 2018 the FDA approved a retinal imaging device with onboard artificial intelligence that could make diagnostic decisions, a first of its kind innovation As mentioned before, the majority of new ML algorithms within US have been applied using DL architectures. Some of the most significant advances in DL applied to POCUS have taken place within echocardiography. Here, a number of models have been developed for a wide number of classification, segmentation, and detection tasks. A frequently used DL application involving both segmentation and biometric measurements has been the rapid determination of cardiac ejection fraction (EF). In order to accurately determine EF using echocardiography, determination of cardiac cycles–namely, end-diastole and end-systole–is necessary. Some groups such as Dezaki et al. have successfully used ML models to accurately determine cardiac cyclesThere has also been significant interest in applying ML algorithms to lung ultrasound. Lung ultrasound has gained increased use in the POC setting due to the wide number of clinically useful assessments it provides A number of groups, including our own, have developed DL models using CNN to automatically quantify B-line scores from POC lung ultrasound video clips. Recently, B. Christiana et al. developed a supervised CNN trained on 400 lung ultrasound clips to calculate total BLS in emergency department patients. They achieved a binary classification (B-lines present versus absent) sensitivity and specificity of 93% and 96% compared to an expert interpreter. In multiclass classification of B-line severity their DL model achieved a linear weighted kappa of 0.65 vs an interrater reliability of 0.87 Point of care lung ultrasound has also shown great promise in the accurate diagnosing of community acquired pneumonia (CAP). It has demonstrated excellent diagnostic capabilities when performed by a trained sonographer compared to both clinical assessment and chest X-ray, while also avoiding unnecessary radiation exposure in vulnerable patients such as pediatric populations More recently, amidst the 2020 COVID-19 pandemic, there has been increased attention paid to increasing the diagnostic ability of clinicians to detect the presence of the novel coronavirus in patients. To this end, Born et al. developed a deep CNN trained on over 1100 COVID-19 confirmed lung ultrasound images to achieve a detection sensitivity of 0.96 and specificity of 0.79 and F1-score of 0.92 in a 5-fold cross validation Use of POCUS within nephrology has also increased in use over the past several years. In patients with chronic kidney disease (CKD), volume overload plays an important role in the disease pathology by complicating cardiovascular pathophysiology leading to increased cardiovascular morbidity and overall mortality Fetal measurement is another widely used application in POCUS. In the emergency room, rapid and accurate assessment of fetal parameters such as crown-rump length and classification of the abdominal standard plane, are important to avoid misdiagnosis and guide appropriate interventions The final clinical application of ML for POCUS discussed here is deep-venous thrombosis (DVT) screening. POCUS is an important tool for physicians treating potential DVT patients within the emergency room as well as in the inpatient setting. POCUS can guide clinical decision-making for patients at risk for, or suspected of having, a pulmonary embolism Other models such as that by Tanno et al. have aimed to increase classification accuracy of DVT scans by automatically detecting the extent of vein compressibility in DVT scans Of note, companies such as Mindray and GE have utilized ML and DL based algorithms in commercially available echocardiography products to perform automated tasks such as automated EF calculation, LV border identification, and chamber length calculations . Newer devices entering the market are now often branded with “AI enabled” capabilities, such as left ventricular outflow tract (LVOT) plane identification and Doppler placement (see: GE Venue and Mindray). These tools are beginning to make their way into newer POCUS devices as well. Companies like Butterfly Network, Bay Labs, and Clarius have released POCUS probes that contain AI-enabled cardiac algorithms for automated EF estimation as well as cardiac chamber segmentation (i.e. Butterfly Network’s IQ probe). There is also commercial interest and new adoption of automated B-line counting algorithms within POCUS. Notably, GE has incorporated an auto B-line counter within their new suite of GE Venue Go POCUS devices. Their model uses computer vision and DL approaches, including a proprietary CNN, to automatically detect and count B-lines in lung ultrasound scans. A study by J. Short et al. found that automatic counting of lung B-lines was consistent with visual counting, as performed by experts in the field and both systems showed a high intra- and interobserver reliability Interestingly, the clinical ML software market has grown to now support firms whose business models almost entirely center around developing novel algorithms for clinical use intended for device manufacturers. DiA Imaging Analysis Ltd. is one notable firm in this category. They partner with ultrasound device manufacturers and large academic medical centers to develop AI-enabled solutions for ultrasound. Currently, as mentioned previously, much of the development for these solutions has focused on POC echocardiography, but additional interest has been shown in the development of AI-enabled abdominal algorithms as well. The company has additionally partnered with GE to offer the first AI-based solution for automated EF analysis on handheld ultrasound through the “LVivo EF” on GE’s Vscan Extend, which has been shown to yield similar EF values as 3D echocardiography The dynamic and real-time nature of POCUS provides a major advantage over other imaging modalities such as CT and MRI. Yet, this also represents a major challenge for researchers developing ML algorithms for POCUS. A trained sonographer will rarely examine a single image frame to make a clinical assessment of a patient; rather, data from multiple frames are assessed simultaneously together to inform the clinician of a proper course of action. Within the broader context of deep learning, a known issue is that most state-of-the-art architectures are optimized for single image classification and that impressive performance does not necessarily generalize to video-type data, such as POCUS. A variety of methods have been applied to try to generalize methods used for image classification to video classification. Perhaps the most direct implementation of this has been the use of 3D CNNs (as opposed to the 2D ones used for single image classification). For example, Hara et al. extended the state-of-the-art ResNet architecture to 3D by adjusting the original 3x3 kernels to 3x3x3 . Another approach, first proposed by Simonyan et al., involves processing video data as two separate streams: a spatial and temporal stream A major area of interest in our group and others has been the application of attention-gated networks to DL ultrasound. Attention mechanisms attempt to better mimic human perception by using surrounding local information in the data to contextualize a specific target. Attention models have been heavily used for natural language processing (NLP) tasks, where integrating information from potentially distant parts of a sentence is necessary to accurately translate a given word Additionally, researchers have developed alternative approaches to identifying optimal network architectures through neural architecture search. Generally, network architectures are designed by data scientists using some a priori hypothesis of underlying data structure. This time-consuming task leaves the entirety of alternative network architectures largely unexplored. To address this issue, scientists and Google’s AI division developed a neural architecture search, where machine learning techniques are used to optimize the network architecture while training the network itselfIn conclusion, we have introduced the concepts of machine learning and deep learning, reviewed current applications of these powerful tools in POCUS, discussed available commercial products utilizing machine learning, and explored promising future directions for machine learning on POCUS research. The utility of POCUS is largely derived from its capability for real-time inference and portability. While these factors present initial hurdles to the early adoption of machine learning in POCUS, they may also serve as the modalities greatest assets. Machine learning demands increasingly large datasets, sometimes needing millions of training images. POCUS is uniquely positioned to provide large datasets of video frames that could potentially be used for real-time algorithm training. Additionally, the portability of POCUS has the potential to provide a platform for rolling out machine learning applications in medical imaging to the entire world.The authors have no conflicts of interest to declare.


The use of medicinal plants as complementary and alternative medicine (CAM) has been widely increasing worldwide . AccordiThe use of medicinal plants or their metabolites has not only significantly increased worldwide: research by scientific groups has also expanded, demonstrating their effectiveness in treating diseases with minimal or no adverse effects. People are convinced that natural products are less harmful than synthetic drugs because they are of natural origin, i.e., “if they are not good, they are not bad either.” However, herbal medications and supplements contain chemical compounds whose interactions might produce the same benefits or risks as those of other pharmacologically active compounds, whether natural or synthetic . TherefoIn this way, researchers have increased their efforts to demonstrate both the efficacy of medicinal plants and/or their metabolites for the treatment of various diseases and their safety, either on their own or in combination with other drugs.Preclinical studies have grown in recent decades to demonstrate that interactions between conventional drugs and extracts of medicinal plants and/or their metabolites can be considered a good therapeutic strategy, according to the research about combined therapies. The purpose of those interactions is to improve treatments’ efficacy while reducing potential adverse effects. Nevertheless, clinical studies evaluating these interactions are still limited or inconclusive. However, although such benefits can become a reality in several interactions, negative results might also be possible. Therefore, research should be encouraged to reveal the frequency and nature of these interactions.As previously mentioned, extracts of medicinal plants contain more than one possible bioactive metabolite responsible for therapeutic activity. In this respect, administering herbal medicine alone or combined with conventional drugs can modify the intensity of an active compound’s effects depending on its chemical nature and how it works. This could influence the outcome of treatment in at least three cases: additive, supra-additive (synergistic), or infra-additive (antagonistic) effects .in vitro results, which are a useful tool for warning about potential deleterious effects, but the in vivo experiments that support them are minimal for some plants or still missing for others that are already therapeutically used in traditional or folk medicine.Although there has been an increase in the number of papers on the subject, little is still known about herb-drug or herb-herb interactions, in part, because i) pharmacovigilance is weak regarding herbal medicine use; ii) adverse/unexpected effects are usually not notified, since patients do not tell their doctor they are using herbal medicine in combination with other drugs; or iii) most of the available papers on the subject refer to Therefore, this Frontiers Research Topic, “Pharmacological Interaction Between Drugs and Medicinal Plants,” contributes, as a collection of eight articles written by 62 authors . Four of these publications are original research articles and four are reviews, and they describe or integrate preclinical scientific knowledge focusing on medicinal plants and drug interactions.Hossain et al.). The second review refers to the evidence available in electronic databases and focuses on the combined use of natural products and tamoxifen in breast cancer, identifying the current gaps and suggesting possible future studies for improving treatment strategies. Additionally, this review considers information on some metabolites that can interact with tamoxifen, improving its pharmacokinetic parameters .First, an interesting review describes the strong antioxidant activity of propolis, which could strengthen the therapeutic effect of some drugs such as antimicrobials, hyperglycemics, and those used to improve cognition and movement. In the case of chemotherapy, propolis improved not only antitumoral activity but also attenuated multiorgan toxicity . The fourth and final review in this collection shows that the use of warfarin with some traditional Chinese medicine (TCM) products plays an important role in herb interactions. Warfarin has a long pharmacokinetic half-life in a therapeutic window, and interactions with drugs, herbs, or food can cause severe adverse events. The complex composition of CHM may cause dual effects such as potentiating and attenuating the anticoagulant effect of warfarin, so patients should exercise caution when using warfarin and herbal remedies concurrently .The third review presents interesting information about probiotics combined with Chinese herbal medicines (CHM) for treating ulcerative colitis. Probiotics are bioactive microorganisms that positively impact the body’s health when consumed in adequate doses and combined with CHM. This therapy generates a therapeutic synergism by inhibiting the abnormal inflammatory response, protecting the intestinal barrier, and restoring the intestinal microbiota imbalance  system in preparations based on traditional Latin American and European herbs usually integrated into the Brazilian Unified Health System (SUS). Continuous research on these herbal preparations is important because it allows the mapping of potential ADME effects in different populations .Regarding pharmacological interactions of medicinal plants, including some pharmacokinetic phases, there is currently not much information on the metabolic and transporter targets due to the complexity of medicine based on medicinal plant extracts. An original study in the present collection analyzes, Salix cortex extracts, at high concentrations, interact with CYP3A4, one of the CYP450 isoforms most used by many drugs for their hepatic metabolism. The authors showed the importance of considering that due to polypharmacy, people are at risk of inducing adverse effects when they use more concentrated or long-term herbal preparations that can interact with some cytochromes, leading to changes in their metabolism . Due to the potential interaction with many herbs, it is important to investigate the inherent population at risk and the long-term use of Salix cortex extracts.The second manuscript provides evidence about the importance of studies to identify the kind of drug-herb interactions that occur during some pharmacokinetic phases. Coriolus versicolor products and drugs against cancer, such as tamoxifen, can improve their therapeutic effect. The extract stabilizes the biochemical changes of long-term therapy with tamoxifen, benefiting patients with compromised immune systems. The results also showed that C. versicolor products do not inhibit tamoxifen metabolism in vitro; however, clinical studies to confirm preclinical results will always be needed . The last original research of this collection describes the hepatoprotective effects of a polysaccharide obtained from Smilax china L, a well-known medicinal plant with a variety of pharmacological properties. This study emphasized the importance of protection against acetaminophen-induced hepatotoxicity produced by N-acetyl-L-cysteine (NAC), an approved treatment .Regarding the effects of positive drug interactions, it has been shown that the concomitant use of There is little information available globally about how frequently medicinal plants are used as a form of treatment in patients with a variety of conditions or whether the plants are used as the only treatment or as a complement to the drugs prescribed by clinicians. In many cases, medicinal plants are used as CAM and as traditional and local medicine in aqueous preparations such as infusions (tea) or decoctions. For example, 67.4% of patients with generalized anxiety disorders used medicinal plants, as recorded in a public hospital in Mexico (IMSS). However, in this study, the authors did not report whether patients used the medicinal plants to complement their conventional treatment or alone .Since there is a lack of information about scientific studies on interactions between drugs and medicinal plants around the world, this collection, which includes eight manuscripts on the topic “Pharmacological Interaction Between Drugs and Medicinal Plants,” represents an example of the importance of gathering evidence about the pharmacological interactions between drugs for clinical use and medicinal plants. This will help to identify their potential in producing maximum efficacy with fewer adverse effects, contributing to an optimal alternative in the treatment of several conditions. Ongoing work on the subject is necessary to ensure that herbal medicines are both effective and safe, encouraging rational use of this therapeutic option.


Salmonella Typhimurium collected from various hosts  and were exposed to antimicrobial drugs—ampicillin, chloramphenicol, streptomycin, sulfisoxazole, and tetracycline—as one set of the experiment. The same isolates were also cultured with no drug exposure as a comparison. There are certain pathways of metabolite expression that are impacted by drug exposure when compared to no drug exposure, meaning that the expressed metabolites could be potential targets for drug companies for the treatment of antimicrobial-resistant pathogens.The global threat that is imposed by the resistance the pathogens develop to antimicrobial drugs is escalating. Tools to detect the resistance (with evidence on molecular and cellular outcomes) would reveal intricate mechanisms through which novel drugs could be developed. Approaches such as metabolomics, which involve metabolite detection, provide scientific evidence of metabolite expression of antimicrobial-resistant pathogens. The current study involved metabolomics of antimicrobial-resistant Salmonella Typhimurium from various hosts. This research aimed to evaluate the metabolomic profiles of S. Typhimurium associated with AMR and it compares profiles across various hosts. Three samples, each from bovine, porcine, and humans , were selectively chosen from an existing library to compare these nine isolates cultured under no drug exposure to the same isolates cultured in the presence of the antimicrobial drug panel ACSSuT . This was followed by metabolomic profiling using UPLC and GC–mass spectrometry. The results indicated that the metabolite regulation was affected by antibiotic exposure, irrespective of the host species. When exposed to antibiotics, 59.69% and 40.31% of metabolites had increased and decreased expressions, respectively. The most significantly regulated metabolic pathway was aminoacyl-tRNA biosynthesis, which demonstrated increased expressions of serine, aspartate, alanine, and citric acid. Metabolites that showed decreased expressions included glutamate and pyruvate. This pathway and associated metabolites have known AMR associations and could be targeted for new drug discoveries and diagnostic methods.Antimicrobial resistance (AMR) is a global public health threat, yet tools for detecting resistance patterns are limited and require advanced molecular methods. Metabolomic approaches produce metabolite profiles and help provide scientific evidence of differences in metabolite expressions between  Antimicrobial resistance (AMR) in bacteria isolated from animal hosts is a major global public health threat. The Centers for Disease Control and Prevention have determined that AMR is “one of the greatest public health challenges of our time” . One of Metabolomics is a relatively new tool that can be used to construct metabolite profiles and these metabolite patterns provide evidence of metabolite regulation at the cellular level. When bacteria are exposed to antibiotics, this exposure can trigger cellular changes within the bacterial cell that results in specific metabolic patterns that can help predict antimicrobial drug resistance profiles. Such predictability can have an immediate impact on human and animal health by leading to advancements in drug discoveries by targeting the expression of certain metabolites, as well as diagnostic tools to screen large numbers of samples for AMR. Identifying possible new drug targets would help pharmaceutical companies develop more specific and effective antibiotics to combat AMR bacterial infections .Recent studies have shown that bacteria produce specific metabolic fingerprints when exposed to different classes of antibiotics. These fingerprints can help predict the mode of action used by antibiotics  to help Salmonella is a rod-shaped, Gram-negative bacillus that belongs to the Enterobacteriaceae family. This organism is of high public health importance due to its ability to cause several syndromes in both animals and humans. Enteritis, septicemia, abortion, and asymptomatic miscarriages are the major syndromes that present in animals. Enteric fever, gastroenteritis, septicemia, and focal infections are the major syndromes that present in humans infected with Salmonella bacteria  fouAn established resistance mechanism against β-lactams, such as ampicillin, includes the production of metallo-β-lactamases, which inactivate the drug through a cleavage process. The metallo-β-lactamases are especially threatening due to their ability to inactivate multiple β-lactams and their insensitivity to β-lactamase inhibitors that target the acyl serine transferases. This resistance mechanism has been identified in extended-spectrum β-lactamases where two amino acid substitutions are critical, a serine-for-arginine and a lysine-for-glutamate . This suPerhaps one of the largest resistance mechanisms is through decreasing TCA cycle flux. Previous studies have shown that exogenous alanine and/or glucose increase susceptibility to antibiotic treatment by increasing TCA flux and thereby increasing drug uptake by the cell . TherefoThese data from our study suggest that another resistance mechanism utilized by these AMR isolates may be initiated from the aminoacyl-tRNA pathway. Aminoacyl-tRNA biosynthesis is responsible for changing cell membrane properties and increasing a pathogen’s resistance. It has previously been identified as an attractive drug target . This paAlanine is a required component of cell wall peptidoglycan and it has been demonstrated that inhibition of alanine transport results in increased susceptibility to drugs . IncreasSalmonella aureus is exposed to cold temperatures, as well as upregulated cell division proteins [S. Typhimurium depends on this metabolite to maintain intracellular Ca++ concentrations and increases the rate of cell division. An increased rate of cell division would also increase the chances of DNA mutation occurring and antibiotic resistance developing. Further examining the role of citrate in bacterial survival and AMR is warranted.In our study, citrate (citric acid) has the highest fold change of any of the metabolites matched to a significant pathway, but its possible role in antimicrobial resistance is less clear. Citrate has previously been described as having a role in the regulation of cell division and gene expression and is known to be a chelator, which may allow bacteria to manage intracellular concentrations of cations. Previous research has shown an increase in citrate concentrations when proteins . TherefoIn future research, exposing isolates to only one antibiotic or one class of antibiotics would allow for a more specific interpretation of the expressed metabolites and potentially provide more robust evidence on resistance mechanisms. Interpretation of these data is limited due to the multiple mechanisms by which the ACSSuT panel targets bacteria. Resistance mechanisms against one class of antibiotics differ from those against another class, hence why bacteria resistant to one class may be susceptible to a different one . This exSalmonella Typhimurium to an ACSSuT panel significantly alters metabolic pathways and, thus, metabolite expression by the bacteria. This research supports the continuation of using metabolomics to study AMR and identify resistance mechanisms, which could become future drug or testing targets. However, further studies are necessary to identify specific resistance mechanisms for different classes of antibiotics.The findings of this study suggest that exposing AMR


Emerging evidence has highlighted the important role of local contexts for integration trajectories of asylum seekers and refugees. Germany's policy of randomly allocating asylum seekers across Germany may advantage some and disadvantage others in terms of opportunities for equal participation in society. This study explores the question whether asylum seekers that have been allocated to rural areas experience disadvantages in terms of language acquisition compared to those allocated to urban areas. We derive testable assumptions using a Directed Acyclic Graph (DAG) which are then tested using large-N survey data (IAB-BAMF-SOEP refugee survey). We find that living in a rural area has no negative total effect on language skills. Further the findings suggest that the “null effect” is the result of two processes which offset each other: while asylum seekers in rural areas have slightly lower access for formal, federally organized language courses, they have more regular exposure to German speakers. Once asylum seekers arrive in Germany, they are distributed geographically across the German regions. The number of asylum seekers that each region receives is based on a quota system considering tax returns and population size in each region (Königstein key). The allocation of individuals across those defined regions occurs randomly. This policy is subject to much debate. The system resembles a lottery that may produce winners and losers. An emerging body of research suggests that the initial placement of asylum seekers shapes their further integration trajectories into society , we first test whether there is, indeed, a rural penalty in language acquisition of asylum seekers. Second, we explore whether potential urban-rural disparities are related to differences in social networks  and learning opportunities (access to language courses). Research has shown that contacts with natives  there is no overall rural penalty in refugees' language acquisition in Germany, (2) both contact with Germans and participation in different forms of language courses proof to be highly effective in increasing refugees' language acquisition and (3) intergroup contact with Germans is significantly more likely in rural areas while official course participation is somewhat less likely. Overall, it can be concluded that language learning in rural areas runs to a greater extent via contacts with Germans, while in urban areas institutional services are a more relevant factor.In addition to advancing understanding of how local contexts shape integration of refugees, these results have implications for policy. The federal government is responsible for the allocation of refugees across regions and regional authorities are responsible for allocation of refugees to districts. The findings reject the claim that refugees are disadvantaged in rural areas in terms of language acquisition, partly because higher exposure to German speakers offsets marginally lower access to formal language courses. The results also suggest that further investment in courses in rural areas and more opportunities for interactions with Germans in urban areas could accelerate language acquisition of refugees and thus maximize integration benefits for refugees and society.Efficiency captures factors that facilitate individual language learning such as prior education attainment, young age, and cognitive skills. Incentives reflect the motivation of the language learner and are driven by expected economic  and non-economic  returns. The incentive dimension incorporates costs associated with language learning such as fees for instruction, material costs or opportunity costs associated with delayed transition to gainful employment. Incentives are commonly modeled as a  cost-benefit calculation by the individual migrant.According to the Chiswick-Miller language learning model, host-country language acquisition is a function of efficiency, incentives and exposure  and access to formal language courses mediate potential effects of location on language learning.In the following, we put forward our theoretical arguments formalized by the means of Directed Acyclic Graphs (DAGs). DAGs are a tool to illustrate the causal model, make assumptions transparent and derive formal rules for selecting control variables Elwert, .The main interest of this study is the total causal effect of location  on language acquisition (in the form of skills) (path 1 in language course participation (path 2). First, rural communities often provide less assistance in language learning. Rural communities have fewer resources to fund language learning opportunities  compared to asylum seekers living in urban settings. First, the opportunity to interact with other co-ethnics is likely smaller because the concentration of migrant groups is historically lower in rural areas compared to cities . Based on these theoretical reflections, we consider the following potential effects of rural area on language acquisition:Rural penalty: Asylum seekers and refugees in rural areas are disadvantaged in terms of language acquisition because negative mediation outweighs positive mediation. According to theory, in this scenario, effects from reduced access to language courses cannot be sufficiently compensated by increased contact with Germans.Rural premium: Asylum seekers and refugees in rural areas are advantaged in terms of language acquisition because positive mediation outweighs negative mediation. According to theory, in this scenario, effects from reduced access to language courses are successfully overcompensated by increased contact with Germans.Compensation effect: Being assigned to a rural location has no overall effect on language acquisition because positive and negative mediation offset each other, i.e., reduced access to language courses is equally compensated by increased contact with Germans.Z1). For example, younger and more educated migrants may sort themselves into urban contexts to seek better employment and more attractive lifestyle opportunities. Parents with children may prefer rural areas with lower living costs and cheaper rents while parents, particularly women, have less availability to participate in language courses  characteristics may be more likely to live in rural areas . In Germany, asylum seekers are randomly allocated to a particular region and then quasi-randomly distributed further to counties. No information about the individual asylum seekers is considered when assigning a location. This is an ideal situation for causal identification resembling a natural experiment. In addition, according to a new policy, the residence of recent asylum seekers is limited to their place of first assignment. This mobility limitation assures that the composition of asylum seekers is similar across localities which – in theory – should also render the population assigned to rural and urban areas non-selective. For any potential imperfections of this random assignment that may occur in practice, we take several measures further described in the following sections. Furthermore, we conduct additional analyses in sub-samples in which we control for factors that reflect the intention and experience of living in the countryside, thus ruling out further potentially endogenous variation .The IAB-BAMF-SOEP Refugee Survey is a longitudinal household survey of asylum seekers and refugees in Germany and was launched in 2016 . Regional centers have a supraregional significance and are usually characterized by a higher level of facilities in various areas, such as culture and education, health, transport connections or administration and authorities . Likewise, we define centers in very peripheral areas as rural, since there likely is no equivalent supply of social facilities and infrastructure present as compared to urban areas.Our central independent variable captures whether refugees live in  Küpper, . For this Einig, . In prinhow often respondents spend time with German people  we include a variable indicating the official (BAMF) course visit and (3) one variable indicating the report of “other” course visits which were not administered by the BAMF. The latter could therefore include locally organized efforts to promote the language acquisition of refugees and are therefore of particular importance.Participation in language courses is measured based on several SOEP survey items regarding participation in various different types of courses. This includes the general official language course, organized by the Federal Office for Migration and Refugeessex, age and educational levels, migration-specific factors country of origin, years since immigration and legal status, as well as indications on partnerships, number of children and moves since the last survey.As discussed above, the random spatial distribution of refugees may be imperfect in practice. Furthermore, even if randomly allocated, asylum seekers and refugees may sort themselves into courses or intergroup contact, depending on various individual characteristics. To isolate the effect pathways from such possible confounders, we therefore include a set of control variables. Thus, we include information on socio-demographic factors Each of the paths in the overall model  is estimTo estimate the treatment effects of all five hypothesized paths, we use Stata's effect command using the regression adjustment (RA) estimator , less likely to be highly-educated  or from Syria .Regarding our main theoretical variables, there is no significant difference in German language skills between rural and urban locations. Frequent contact to Germans is significantly more likely in rural areas and at the same time, any language course participation and specifically official course participation is less likely for respondents in rural areas while unofficial course visits are slightly more likely.p < 0.05) while course participation in other non-BAMF courses tends to be more likely in rural areas by 2.3 percentage points (ns). This may suggest that local communities offer their own language course support, perhaps partly because centrally organized courses are less accessible in rural areas.For path 2 going from rural location to course participation, the picture is heterogeneous: considering all courses combined, there is a very small insignificant effect suggesting that refugees in rural areas do not have lower access to language courses compared to more urban areas. However, when we disaggregate the type of course, a different picture emerges. Living in a rural location reduces access to formal federally-organized (BAMF) courses by about 3.2 percentage points : frequent intergroup interactions  4.6 percentage points more likely compared to refugees' living in urban areas. This may demonstrate altered opportunity structures with regards to intergroup contact across regions. Furthermore, the presence of contact has strong effects on refugees' language skills (path 4): refugees reporting more contact with Germans show a significant increase of 0.097 scale-points in language evaluation as compared to refugees who do not report it. Last, the participation in language courses has significant and strong positive effects on language skills for all forms of courses. The strongest effects are present for the combined specification of course participations with +0.085 scale points in language skills (0–1), followed by official courses (+0.069) and unofficial courses (+0.043).While the main analyses distinguished between different types of courses, it is also conceivable that contact with Germans differs in frequency and effect on language acquisition depending on whether the contact takes place at work, among friends, or in the neighborhood. Thus, some forms of contact may occur relatively frequently, but the intensity of interaction and the depth of possible topics of conversation may remain relatively superficial. The refugee sample does not distinguish between contact with Germans in different spheres of life until the start of the second wave. Self-assessments of language skills are controversial with regards to their strengths in reflecting objective language skills  and course visits (M2) is theoretically plausible in both directions see . IndividAnother robustness check addresses issues of reverse causality. Our argument hinges on the assumption that both contacts to Germans and participation in courses have positive effects on language acquisition (paths 4 and 5). Our results confirm this assumption empirically. However, it is possible that better language skills lead to more contacts to Germans and better access to courses rather than vice versa. To assess this possibility, we run separate models , taking As a final step, we check whether effect directions are sensible toward our chosen estimation approach for obtaining ATE's. Therefore, as alternative to “regression adjustment,” we also provide estimates using two more approaches: inverse-probability-weighting (IPW) and inverse-probability-weighting regression adjustment (IPWRA). A side-by-side comparison is provided in This study explored the potential disadvantage that asylum seekers and refugees may face in terms of language acquisition when being allocated to rural areas after arriving in Germany . We propose a causal model based on DAGs and established language learning models and test our hypotheses using large survey data from Germany  and the degree to which it produces winners and losers in terms of integration. We find that rural areas do not necessarily disadvantage migrants in terms of language acquisition. This finding is important as allocation of migrants to rural areas has been discussed in the context of reviving areas suffering from demographic decline. The results also suggest that policymakers can further promote language acquisition of asylum seekers and refugees by improving access to formal language courses in rural areas and by facilitating interaction with Germans in urban areas. Especially the latter informal mechanism via social contacts is often neglected in the political debate, with an overly rigid focus on language courses instead. Yet intergroup contacts can also achieve other socially desirable effects in addition to migrants' language acquisition, such as reducing xenophobic attitudes within majority groups  – Projektnummer 491466077.The authors declare 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.