Vitamin deficiency is rare in modern industrialised countries; however, it still occurs in patients with specific backgrounds, such as those with extremely unbalanced diets, those with alcoholism and those who have undergone gastrointestinal surgery. Imaging examinations that demonstrate classic findings confirm the clinical diagnosis of vitamin deficiency and help monitor response to treatment. Because vitamin deficiencies are not prevalent, the diagnosis might not be straightforward. Therefore, imaging should be performed in cases of suspected vitamin deficiency. Radiologists should be familiar with characteristic imaging findings of vitamin deficiency and should survey an affected patient’s background and blood vitamin levels. Because symptoms of vitamin deficiency are quickly improved by vitamin replacement, early diagnosis is essential. This pictorial review provides imaging findings for deficiencies in vitamins B1 , B12 (subacute combined degeneration), C (scurvy), D (rickets) and K (bleeding tendency). In modern industrialised countries, vitamin deficiency is rare because the food supply is stable and sufficient. Vitamin deficiency may result from inadequate oral intake or malabsorption. Extreme picky eaters, such as people with autism spectrum disorder or schizophrenia and patients with alcoholism, may develop symptoms of vitamin deficiency. A history of surgery in the gastrointestinal tract is also a risk factor.Physicians might not be familiar with vitamin deficiency because its symptoms are relatively mild; therefore, the diagnosis may be difficult and delayed. Although vitamin deficiency is basically diagnosed through medical interviews and physical examinations, some vitamin deficiencies are characterised by specific imaging findings, which may aid in the diagnosis. The symptoms of vitamin deficiencies are quickly resolved after sufficient vitamin supplementation; therefore, knowledge of imaging findings of vitamin deficiency helps improve patient outcomes. This pictorial essay provides imaging findings of vitamin deficiencies .Vitamin B1 deficiency occurs predominantly in patients who have undergone gastrointestinal surgery and in patients with alcoholism because vitamin B1 (thiamine) is absorbed in the jejunum, and because ethanol inhibits the absorption of vitamin B1. Lesions adjacent to the ventricles are better detected on MRI, fluid-attenuated inversion recovery (FLAIR) sequences and diffusion-weighted imaging (DWI) than on T2 weighted imaging (T2WI). Common locations of lesions are symmetrical in the paraventricular regions of the thalamus, hypothalamus, mammillary bodies, periaqueductal region and floor of the fourth ventricle  originates from animal food and is synthesised by a microorganism. Absorption in the distal ileum depends on intrinsic factor, which is synthesised by the gastric parietal cells; therefore, total gastrectomy is a risk factor for vitamin B12 deficiency. This disorder leads to megaloblastic anaemia, which may result from folate deficiency and subacute combined degeneration. The symptoms of subacute combined degeneration include symmetrical weakness, paraesthesia, sensory ataxia and loss of vibratory sense with subacute onset and progression from distal to proximal. On MRI, a characteristic finding is symmetrical high T2 signal in the posterior and lateral columns, involving the corticospinal and spinocerebellar tracts . The chaVitamin C (ascorbic acid) is obtained from fruits and vegetables and is absorbed in the ileum. It functions as an antioxidant and a cofactor for the hydroxylation of protein and is essential in synthesising collagen. Vitamin C deficiency, known as scurvy, leads to abnormal collagen production. Because collagen is distributed in every part of the body, the various manifestations of scurvy include delayed wound healing, nail change, corkscrew hair, gingival and tooth anomalies and anaemia, which sometimes mimics haematological disease, vasculitis and infection. Blood vessels become fragile as a result of abnormal collagen, and this can lead to a bleeding tendency. In affected children, subperiosteal haemorrhage as a result of bleeding tendency can cause inability to walk and leg pain, especially around the knee. Moreover, diffuse osteopaenia and thin cortices distributed predominantly in the epiphyses are observed on radiographs. On nuclear bone scans, hot spots are observed in femoral, tibial and fibular metaphyses corresponded to a provisional zone calcification (Frankel line). Ultrasonography reveals subperiosteal heterogenous echogenic effusion, suggestive of subperiosteal haemorrhage. MRI can also depict subperiosteal haemorrhage, as well as bone marrow abnormalities, which demonstrate diffuse or patchy abnormal signal intensity; the characteristic findings are symmetrical low intensity on T1 weighted images, high-intensity on fat-suppressed T2 weighted images and contrast enhancement on fat-suppressed T1 weighted images in the bilateral lower extremity metaphyses  with subjacent lines of demineralisation (scurvy line or Trummerfeld zone), a peripheral extension of the zone of calcification that results in beaking (Pelkan spurs) and a sclerotic cortical rim around osteopenic epiphyseal ossification centres (Wimberger ring sign) .9 Moreaphyses . Because Another case report described nonspecific MRI depictions of inflammation, including dermal thickening, subcutaneous and deep fascial oedema and heterogeneous increased T2 weighted signal bilaterally in the quadriceps and gastrocnemius muscles (T2WI are believed to reflect increased capillary permeability as a result of the fragility of the vessel wall. In one report, patchy foci of enhancing marrow oedema in the distal femur and proximal tibia were non-specific and assumed to represent islands of red marrow.Reports of adult scurvy are limited. Multiple small bilateral intramuscular haemorrhages with a branching pattern suggestive of perivascular distribution were reported as a unique presentation of scurvy. muscles . The mecVitamin D is obtained through exposure to sunlight or diet. Activated vitamin D is involved in calcium, phosphorus and bone metabolism; therefore, its deficiency results in rickets, which is the interruption of development and mineralisation of the growth plates, or osteomalacia, which is insufficient or abnormal mineralisation of osteoid in the bone. Rickets occurs only before the growth plate fusion.Patients with rickets may present with pain and exhibit delayed growth and motor skills. On radiographs, the characteristic findings are widening of the growth plate; cupping, splaying and fraying of the metaphyses; and poor mineralisation . Transve In the adult population, vitamin K deficiency is rare because the daily requirement is small. However, an extremely unbalanced diet may cause bleeding tendency, purpura, gastrointestinal bleeding, epistaxis and haematuria.Vitamin K is indispensable for synthesising coagulation factors II, VII, IX and X, which are essential for haemostasis. Vitamin K deficiency is common in breastfed infants because human breast milk contains a low amount of vitamin K; additionally, stores of vitamin K are low at birth. Biliary atresia is associated with vitamin K deficiency because vitamin K is fat-soluble and bile is needed for its absorption. Intracranial haemorrhage is one of the life-threatening manifestations of vitamin K deficiency in infants , althougVitamin deficiencies can develop in patients with an extremely unbalanced diet, those who have undergone gastrointestinal surgery or those with mental disease even in modern industrialised countries. Because physician might be not aware of vitamin deficiencies due to its low prevalence, radiologists should be familiar with characteristic imaging findings of vitamin deficiencies for correct and early diagnosis and treatment.


OBJECTIVES/GOALS: 1) illustrate the varied challenges individuals with a cocaine use disorder experience in daily life, 2) demonstrate techniques for empathizing and building rapport with potential subjects, and 3) identify recruitment obstacles and solutions. METHODS/STUDY POPULATION: Methods: We use a multi-source strategy to recruit our participants and employ practical techniques to enhance protocol adherence. Methods include a welcoming environment, establishing a routine with flexibility, personalized attention, and incentives for participation. Study population: Individuals with a cocaine use disorder. RESULTS/ANTICIPATED RESULTS: Understanding the life of an individual with a cocaine use disorder is paramount to successful recruitment and retention in addiction research studies. Our clinicians have been able to recruit and retain participants successfully by employing empathetic interpersonal skills, personalized attention, and health-related incentives. DISCUSSION/SIGNIFICANCE OF IMPACT: The Centers for Disease Control and Prevention estimated that 69,029 people died of a drug overdose during the period from February 2018 to February 2019, with 23%, due to cocaine. While methadone and buprenorphine-naloxone maintenance treatment allow opioid-dependent individuals achieve a sense of physical and mental stability, there is no pharmaceutical treatment to help a cocaine-dependent individual cope with cravings or the depression and anxiety that typically follow a cocaine binge. The development of a cocaine use disorder is multi-factorial and presents a significant challenge in terms of discovering treatments, identifying efficient recruitment and retention strategies is the first step for effective research.


Task-sharing is a promising strategy to expand mental healthcare in low-resource settings, especially in low- and middle-income countries (LMICs). Research on how to best implement task-sharing mental health interventions, however, is hampered by an incomplete understanding of the barriers and facilitators to their implementation. This review aims to systematically identify implementation barriers and facilitators in evidence-based task-sharing mental health interventions using an implementation science lens, organizing factors across a novel, integrated implementation science framework.PubMed, PsychINFO, CINAHL, and Embase were used to identify English-language, peer-reviewed studies using search terms for three categories: “mental health,” “task-sharing,” and “LMIC.” Articles were included if they: focused on mental disorders as the main outcome(s); included a task-sharing intervention using or based on an evidence-based practice; were implemented in an LMIC setting; and included assessment or data-supported analysis of barriers and facilitators. An initial conceptual model and coding framework derived from the Consolidated Framework for Implementation Research and the Theoretical Domains Framework was developed and iteratively refined to create an integrated conceptual framework, the Barriers and Facilitators in Implementation of Task-Sharing Mental Health Interventions (BeFITS-MH), which specifies 37 constructs across eight domains: (I) client characteristics, (II) provider characteristics, (III) family and community factors, (IV) organizational characteristics, (V) societal factors, (VI) mental health system factors, (VII) intervention characteristics, and (VIII) stigma.Of the 26,935 articles screened (title and abstract), 192 articles underwent full-text review, yielding 37 articles representing 28 unique intervention studies that met the inclusion criteria. The most prevalent facilitators occur in domains that are more amenable to adaptation , while salient barriers occur in domains that are more challenging to modulate or intervene on—these include constructs in the client characteristics as well as the broader societal and structural levels of influence . Other notable trends include constructs in the family and community domains occurring as barriers and as facilitators roughly equally, and stigma constructs acting exclusively as barriers.Using the BeFITS-MH model we developed based on implementation science frameworks, this systematic review provides a comprehensive identification and organization of barriers and facilitators to evidence-based task-sharing mental health interventions in LMICs. These findings have important implications for ongoing and future implementation of this critically needed intervention strategy, including the promise of leveraging task-sharing intervention characteristics as sites of continued innovation, the importance of but relative lack of engagement with constructs in macro-level domains , and the need for more delineation of strategies for task-sharing mental health interventions that researchers and implementers can employ to enhance implementation in and across levels.CRD42020161357PROSPERO The online version contains supplementary material available at 10.1186/s13012-021-01179-z. Contributions to the literatureTask-sharing based on evidence-based practices is a promising strategy to increase the global availability of mental health care, and no literature has systematically compiled barriers and facilitators to implementation of these interventions in low- and middle-income countries.Barriers and facilitators to evidence-based task-sharing mental health interventions are present at multiple levels, and we provide a conceptual framework to organize them into eight domains.Our enumeration and organization of the implementation barriers and facilitators is an important step in helping practitioners and researchers improve the implementation of these interventions, including the development of tools to measure these implementation determinants and the need to select implementation strategies that can specifically leverage the facilitators and target the barriers across multiple levels.As a key part of global mental health efforts to address the mental health treatment gap, increasingly widespread adoption of task-sharing strategies has led to significant expansions of the mental healthcare workforce and improvements in population mental health and well-being globally –3. Task-, defined by Lewis et al.  as “factor[s] that enable or hinder the implementation strategy from eliciting the desired effect” [There is growing interest in further understanding the development, implementation, and outcomes of the task-sharing approach. One element of this growing field of research is the examination of implementation determinants, commonly referred to as barriers and facilitators effect” . For exa effect” , 16. Sim effect” . An impoet al. 20, p. 2 as effect” .While there have been studies and reviews that have discussed barriers and facilitators to task-sharing mental health interventions, they have limited their search and analyses to specific settings, , specifThe purpose of this review is to use an implementation science perspective to identify barriers and facilitators to the implementation of evidence-based task-sharing mental health interventions focusing on LMICs, as task-sharing has been most widely used in these low-resource settings.What are the reported barriers and facilitators in the implementation of evidence-based task-sharing mental health interventions in LMICs?How can implementation science frameworks and constructs be used to guide the understanding of the implementation determinants of task-sharing mental health interventions?How do these barriers and facilitators inform the selection and further study of implementation strategies for task-sharing mental health interventions?The specific research questions and objectives for the review were:The protocol was registered with The National Institute of Health Research’s international prospective register of systematic reviews (PROSPERO CRD42020161357). This systematic review was conducted using the Preferred Reporting Items for Systematic Review (PRISMA) guidelines , and theWe conducted searches using PubMed, PsychINFO, CINAHL, and Embase to identify peer-reviewed studies published before July 1st, 2019. Studies from all years up until July 1st, 2019 were included to be as comprehensive as possible. Terms were compiled for three broad categories: “mental health,” “task-sharing,” and “LMIC.” “Mental health” and “task-sharing” used search terms from previously published systematic reviews of task-sharing mental health interventions , 25, 26 Title and abstract screening was completed in two phases. In the first phase, the lead and senior authors (PTL and LHY), along with a team of masters-level research assistants, collaboratively screened 200 titles and abstracts to finalize screening protocols and ensure consistency in the screening process. In the second phase, the remaining titles and abstracts were each independently screened by two research assistants, with disagreements resolved by the lead authors and reviewed by the team. A similar process was used for the full-text article review: the lead authors and research assistants collaboratively reviewed 100 full-text articles, then full-text screening was conducted, with each article reviewed by two independent research assistants and discrepancies resolved by the lead authors. We used the software Covidence , 29 to mWe then used a two-stage search process to reach our finalized set of articles. Studies were first evaluated against the following inclusion criteria: (1) the major focus of the intervention/study was a mental health condition, defined as common and serious mental health conditions excluding neurological and substance use disorders (2) the intervention/study was implemented in a LMIC; (3) the intervention involved task-sharing/task-shifting; and (4) the research article included direct assessments of barriers and facilitators or analysis and insights drawn from empirical data. Our focus included serious mental health conditions as well as common mental health conditions due to the noted need to expand the evidence base for task-sharing for serious mental health conditions . We did Although many conceptual models and meta-frameworks exist in implementation science  none haOur preliminary conceptual model integrated the domains and constructs specified in the Consolidated Framework for Implementation Research  and theUsing an initial conceptual framework, we developed a preliminary codebook composed of constructs from the CFIR and the TDF. The lead authors trained research assistants to identify and code texts of each included article as belonging to a specific construct and construct grouping , and as a barrier, a facilitator, or both a barrier and facilitator. Each included article was coded by two research assistants. During the first round of analysis, pairs of research assistants independently coded articles by highlighting and commenting on the text in each article that pertained to a particular construct. The domain, construct, and whether the construct was present as a barrier, a facilitator, or both, was included in each comment. After coding, the pairs reviewed these codes for discrepancies. Group discussions were then held with the lead authors and research assistants to discuss how constructs were or were not manifested in the articles, to resolve discrepancies, and to reach a consensus on definitions for each construct. This process of independent coding, pair review, and group discussion was then repeated until the codebook and its definitions were finalized. All included articles were then recoded by the same pairs with the finalized codebook, and coded text from the articles was extracted into a shared document and sorted into the corresponding domain and construct. Any remaining disagreements were discussed by the team and resolved by the lead authors.In the second round of analysis, codes that were conceptually related were combined to form new overarching constructs. We also allowed for open coding and created new codes for constructs that were not captured in the existing codebook . The process of refining and applying the analytical framework was repeated until the research team determined that we had reached the most parsimonious codebook, which formed the final BeFITS-MH framework.Barriers and Facilitators in Implementation of Task-Sharing Mental Health interventions (BeFITS-MH) framework  situate their “innovation” factor level as interacting primarily with client and provider characteristics, we situate our intervention domain at the nexus of all the domains because intervention characteristics can both influence and be influenced by the other factors—a position also supported by the CFIR , 35. ForAll articles were then re-coded with the final codebook. We then entered the results in a matrix grid presenting domains and constructs in columns, and articles in rows. Of note, although the factors in the mental health system level were conceptualized as distinct from those in the organizational factors domain in that they describe macro-level characteristics that extend beyond a single implementing organization, sometimes factors were coded both in this domain and in the organizational domain if the macro-level issues also exerted influence at the organizational level . At this stage, we grouped articles derived from the same parent study together before conducting data extraction.The following data were extracted into a spreadsheet and cross-checked by two research team members for accuracy: (1) author and publication year; (2) title; (3) country (or countries) where the study occurred; (4) mental health condition(s) addressed; (5) task-sharing model of evidence-based practice; (6) implementation stage(s) about which the barriers and facilitators were referring within the study ; (7) hon = 19;) were qualitative studies, while the remaining study designs included RCT (n = 8); quasi-experimental ; cohort (n = 2); and analytical cross-sectional studies (n = 2). Some criteria were determined to be unclear for some studies. “NA” was used when the study characteristics rendered certain criteria for the general category of the study design as not applicable, such as the requirement of blinding for a pragmatic trial (for RCTs), or including a reflexivity statement for a process evaluation . Among the qualitative studies, all but one met at least 8 of the 10 appraisal criteria. The criteria most frequently unmet included locating the researcher culturally or theoretically (n = 9) and addressing the influence of the researcher on the research (n = 9). Among the RCTs, none of the included studies had unmet criteria; a few (n = 3) had 2–3 unclear criteria. Among the quasi-experimental studies, all met at least 7 of the 9 appraisal criteria. Among the cohort and cross-sectional studies, none had unmet criteria. Overall, over 80% of the included articles had one or fewer unclear criteria, and 95% of the included articles had one or fewer unmet criteria.All included studies were critically appraised for quality and rigor using the Joanna Briggs Institute’s (JBI’s) critical appraisal tool corresponding to each article’s study type or research design , 45. Of As an additional step, the analysis and insights regarding barriers and facilitators in the discussion section of each article was also critically appraised using the three most relevant questions from the JBI’s “Text and Opinion” critical appraisal tool  . All artA total of 20,081 unique abstracts were identified through database and manual reference searches and underwent title and abstract screening. From this first screening stage, 192 articles received full-text review, with 82 articles (71 unique studies) meeting the initial inclusion criteria. Of the 71 studies initially selected, 28 studies (comprising 37 articles) were determined to use or be based on EBPs using the criteria described above and were selected to comprise the set of studies to be reviewed. See Fig. The 28 included intervention studies (from 37 articles) , 47–81 wThe large majority of studies focused on common mental disorders , with very few studies reporting on serious mental illnesses (SMIs).In the majority of studies, the task-sharing providers were community health workers , followed by primary healthcare providers . Complementary and alternative providers  were less represented. Notably, numerous studies utilized multiple task-sharing provider types.The EBP most commonly used by these studies was mhGAP , followeThe large majority of studies included barriers and facilitators about the implementation stage of the implementation process, with far fewer studies reporting on the preparation, exploration, and sustainment stages. Several studies reported across multiple stages of the implementation process.Table When considering facilitators across the eight domains, intervention characteristics were most frequently reported, and overwhelmingly as facilitators. The six most frequently reported facilitators were all located in the intervention domain: intervention source and rationale; training, supervision, and integration; engagement and reinforcement mechanisms; packaging, adaptability, trialability; task-sharing provider’s role; and cost. The only top facilitator outside of the intervention domain was provider skills and self-efficacy. There was more variation across the domains represented by the top five barriers. Each of the five most frequently reported barriers represented five different domains: client other personal attributes ; sociocultural norms; family/community stigma; clinical resources in the organization; and mental health infrastructure and human resources.Client (other) personal attributes such as demographic factors and experiences of negative life events were identified as the most pervasive barriers in this domain. Among the demographic factors, factors tied to low socio-economic status such as poverty, unemployment, unstable housing and homelessness, and low levels of literacy or language fluency were identified as factors that hindered clients’ participation. Oftentimes, these factors limited access to interventions and the ability to fruitfully engage in programs .Characteristics associated with the task-sharing provider were largely reported as facilitators. In contrast to clients’ other personal attributes, which were largely identified as barriers (above), providers’ other personal attributes were identified as facilitators. This is likely due to an increased acceptability of providers whose personal characteristics such as gender, age, or education align with the local contexts. In some programs, clients expressed preferences for providers who were older adult men, whereas in others, women fluent in the local language were favored. Overall, higher education generally increased acceptability due to perceived authority and mastery. Additionally, providers with higher education were perceived as being more receptive to training . The mosFamily-related factors were sometimes identified as a barrier when family-related obligations  or familial conflict hindered clients’ participation in interventions. On the other hand, providers’ relationships with family members, when successfully developed, could improve both clients’ participation in the intervention and the family’s ability to support their family member with mental illness, which contributed to better outcomes. Community factors such as community support were sometimes reported as facilitators, especially when interventions were held in small, tight-knit communities where collaboration with community members  allowed for implementers to safely identify and engage potential clients, and ensure the community acceptability of the intervention , 67. SucFactors operating at the organizational domain  were identified primarily as barriers. Studies cited several limited clinical resources as impeding implementation. From the clients’ perspective, understaffed clinics had long waiting times and limited scheduling which reduced engagement, particularly for clients whose socioeconomic situation had constrained their availability to attend appointments. From the providers’ perspective, providers in such clinics needed to manage large caseloads which may potentially lead to burnout or decreased quality of care. Physical space constraints in health clinics also posed a major barrier, such as limiting the ease of achieving privacy for private counseling sessions with users. The absence of these resources constrained effective, sustained client participation by limiting the frequency of appointments or by making clients more reluctant to meaningfully disclose concerns or conditions due to a lack of privacy.Implementation climate factors such as collaboration with other entities or healthcare workers on the ground in the delivery of interventions were found to be more successful. For instance, existing networks between providers facilitated referrals from task-sharing workers to specialists and other care providers , but a rBroader, societal factors such as socioeconomic conditions, cultural norms, and historical context were identified as having a largely negative influence on intervention implementation in terms of both intervention access and ongoing engagement and delivery. Particularly, sociocultural norms emerged as the most salient barrier. Several studies emphasized the importance of accounting for cultural norms in intervention design and delivery and identified salient issues such as reluctance to discuss psychological feelings or certain taboo subjects such as death. Gender norms were also identified as factors associated with intervention delivery, as unequal gender relations limited women’s ability to seek treatment, and the gender pairings of counselors and clients often must be considered. The intervention settings’ economic conditions were identified as a challenge; communities’ levels of poverty compounded by other inequalities limited individuals’ capability to utilize services, especially among marginalized groups. Another reported barrier was religion/spirituality; beliefs in traditional healing methods were often mentioned as a deeply ingrained cultural norm that challenged client engagement in interventions. Several studies reported the historical and political context of these interventions  as a barrier. For example, living in contexts with civil unrest or high rates of violence challenged clients’ capacity to prioritize mental health while concerns for safety were paramount. In some instances, clinics experienced a shortage of staffing or even closed due to the political climate. Within communities where gang violence was prevalent, clients feared for their safety traveling to and from intervention sessions and requested that their identities remain anonymous with providers . StrikinActing primarily as barriers, mental health system–level factors included infrastructure-related concerns such as lack of transportation and facilities. In one instance, a general disorganization of the mental health system failed to provide service based on need, resulting in clients with serious mental health conditions receiving inadequate care at the primary care level while a disproportionate number of clients with common mental health conditions receiving specialized care . AdditioIntervention characteristics were identified in all of the studies and were overwhelmingly discussed as facilitators. Notable facilitating factors were intervention source and rationale ; high-quality training, supervision, and integration within the implementing entity, which increased provider confidence and competence; engagement and reinforcements ; packaging, adaptability, and trialability ; and the role of task-sharing providers. Interventions employed a variety of specific roles for task-sharing providers ranging from primary care clinicians being delegated with diagnosis, treatment, and/or referral responsibilities, to community members facilitating group-based therapy, to traditional healers and faith-based leaders being integrated into clients’ care plans. Task-sharing providers acted not only as community mobilizers for mental health but also as liaisons between the users and the rest of the intervention team. Through building partnerships with other facilities, engaging users’ families, recruiting users via community outreach, and developing community awareness towards mental health issues, task-sharing providers can strengthen community acceptability and sustainability of the intervention . Other fMental illness stigma, which also operates across different levels like the intervention domain, was solely reported as hindering implementation success and when present, hindered implementation substantially. Self-stigma by individuals with mental illness was found to be a barrier to seeking psychological/psychiatric treatment and was likely directly linked to high drop-out rates. Enacted stigma toward mental illness  also discouraged treatment-seeking and intervention access. In some instances, official diagnoses of mental health illness resulted in decreased community perceptions of trustworthiness . TherefoIn this review, we used implementation science frameworks to develop a multi-dimensional conceptual model for the barriers and facilitators of mental health task–sharing interventions  and used it to classify the barriers and facilitators reported in the included studies. This process showed that the most prevalent facilitators occur in domains that are more amenable to adaptation , while salient barriers occur in domains that are challenging to modulate or intervene upon—these include constructs in the client characteristics as well as the broader societal and structural levels of influence . Other notable trends include constructs in the family and community domains occurring as barriers and as facilitators roughly equally, and stigma constructs acting exclusively as barriers. These findings have important implications for ongoing and future implementation of evidence-based task-sharing mental health intervention models, including the promise of leveraging task-sharing intervention characteristics as sites of continued innovation; the importance of but relative lack of engagement with constructs in macro-level domains ; and the need for more delineation of strategies for task-sharing mental health interventions that researchers and implementers can employ to enhance implementation within and across levels.That task-sharing intervention factors were the most reported constructs and mostly acted as facilitators is expected, as intervention factors are more amenable to change compared to structural or personal factors. In particular, defining elements of task-sharing  have been specifically designed to be inherently beneficial and are demonstrated to be a strength of this approach . Given tThe fit of task-sharing providers’ roles can also heavily depend on a key facilitator noted in another domain: the task-sharing provider’s personal characteristics, such as their age, gender, and educational background. Alignment of these provider characteristics with the community in which they work can improve the acceptability of task-sharing interventions , 89, 90.This review also underscored that there are a variety of factors that present as major barriers to the implementation of task-sharing mental health interventions at and across levels, including stigma. Trust between all actors  must be established to promote treatment initiation and maintain engagement , in partIn addition to the importance of developing and applying new and existing implementation strategies to enhance known facilitators , another key takeaway from this review is the need to develop and adopt innovative strategies for addressing macro-level barriers. This need for task-sharing interventions to be more responsive to and resistant against macro-level factors is echoed by emerging research that has highlighted the role that structural forces play in not only impeding implementation in their own right but also perpetuating and reinforcing other barriers  –99. In LHowever, the science of developing implementation strategies that could be used to address barriers or to leverage facilitators of task-sharing mental health interventions across all levels is only in its nascent stages. Despite the frequent recognition of the many barriers and facilitators to evidence-based task-sharing interventions, this review found that few studies clearly specified implementation strategies also see . AlthougFurther, this review suggests that future implementation strategies for task-sharing developed in LMICs should seek to address prevalent and pervasive meso- and macro-level barriers and, whenever possible, prioritize aligning with organizational and mental health system efforts to leverage any existing or emerging meso- and macro-level facilitators . ASeveral limitations should be considered. First, the articles included in this review were peer-reviewed journal articles, meaning the grey literature was not utilized. While limiting our criteria to peer-reviewed articles ensures a baseline study quality and rigor, it also makes the studies included in this review subject to publication bias, wherein studies finding statistically significant results or coming from higher-resourced study teams have a higher likelihood of ultimately being identified for inclusion. Published studies were probably more likely to report on positive intervention characteristics that contributed to the significant results achieved by the study, which might have resulted in an overreporting of intervention characteristics as facilitators. Additionally, all studies included for review were in the English language; this criterion was necessary given our team’s linguistic limitations, but limits our access to studies published in local-language journals which may have been a robust source of additional context-rich research given our global focus. Lastly, inherent to the systematic review study design is the reliance on the post-hoc analyses of the included studies; the findings are subject to the methodological rigor and biases of the primary studies. Although all included articles passed their respective quality assessment criteria, barriers and facilitators may be especially likely to lack rigorous reporting or be absent from results entirely given the lack of measurement tools. Thus, in an attempt to mitigate this concern and be properly inclusive, we also critically appraised the discussion sections of each article to allow inclusion of data-grounded discussion of barriers and facilitators .Task-sharing in mental health services continues to be adopted widely, especially to alleviate the mental health treatment gap in many LMICs. Our results underscore a need for greater focus on under-researched geographic areas , populations , and EBPs. Furthermore, we suggest that future studies examine barriers and facilitators and develop implementation strategies across all phases of implementation—especially in the sustainment phase, which will be essential to understand as task-sharing continues to proliferate and become embedded in mental health systems globally .By applying our multi-dimensional BeFITS-MH conceptual framework, which integrated domains and constructs specified in prominent implementation science frameworks, this review offers a comprehensive analysis of barriers and facilitators identified in evidence-based task-sharing mental health interventions conducted in LMICs. Results point to the need for immediate remedies to address material deficiencies in the mental healthcare system and community clinics as a whole, in addition to more complex solutions to mitigate the detrimental effects of mental health stigma and to navigate sociocultural norms in the context of treatment. Barriers and facilitators  are often situated as key factors that lead to implementation outcomes , 35. ThiFurthermore, the lack of valid and pragmatic assessments for implementation-related factors and outcomes has been noted in the health services and implementation science literature , 111 andAdditional file 1: A. Barriers and facilitators to implementation of evidence-based task-sharing mental health interventions in low- and middle-income countries: A systematic review using implementation science frameworks: PRISMA Checklist. B. Barriers and facilitators to implementation of evidence-based task-sharing mental health interventions in low- and middle-income countries: A systematic review using implementation science frameworks: Search Syntax. C. Barriers and facilitators to implementation of evidence-based task-sharing mental health interventions in low- and middle-income countries: A systematic review using implementation science frameworks: Quality Assessment Information by Study Type.


Theory of mind (ToM) is a social cognitive skill that involves the ability to attribute mental states to self and others (what they think (cognitive ToM) and feel (affective ToM)). We aim to provide an overview of previous knowledge of ToM in Parkinson’s disease (PD). In the last few years more attention has been paid to the study of this construct as a non-motor manifestation of PD. In advanced stages, both components of ToM (cognitive and affective) are commonly impaired, although in early PD results remain controversial. Executive dysfunction correlates with ToM deficits and other cognitive domains such as language and visuospatial function have also been related to ToM. Recent studies have demonstrated that PD patients with mild cognitive impairment show ToM deficits more frequently in comparison with cognitively normal PD patients. In addition to the heterogeneity of ToM tests administered in different studies, depression and dopaminergic medication may also be acting as confounding factors, but there are still insufficient data to support this. Neuroimaging studies conducted to understand the underlying networks of cognitive and affective ToM deficits in PD are lacking. The study of ToM deficit in PD continues to be important, as this may worsen quality of life and favor social stigma. Future studies should be considered, including assessment of the patients’ cognitive state, associated mood disorders, and the role of dopaminergic deficit. Non-motor symptoms are common in Parkinson’s disease (PD) . In thisToM may be defined as the ability to understand and predict other people’s behavior, knowledge, intentions, emotions, and beliefs . This teToM consists of a complex metacognitive skill set that begins to develop during brain maturation in infancy and continues during the growth stage . Althougfaux pas or the ability to identify social gaffes, deception and sarcasm, which are also considered to be part of other advanced mentalist abilities. First order ToM develops between three and four years of age. Second order ToM, faux pas, deception and sarcasm are developed from five to ten years, approximately [Another way to categorize ToM is the first-grade belief or the ability that allows the subject to distinguish his/her own beliefs or emotions from those of others; second-grade belief which allows him/her to know that someone thinks that a third person believes or feels something, and ximately .Due to the complexity of this social process, ToM cannot be attributed from a neuroanatomical point of view to a single structure, but to a network of brain functions . The medIt has also been speculated that the cognitive and affective components of the ToM involve different networks. Based on previous work ,41,42 AbThe dopamine depletion characterizing PD impacts the basal ganglia networks involving not only the motor circuit  but alsoIn this regard, it has been hypothesized that the progressive loss of striatal denervation in PD could initially lead to dysfunction of the associative circuit and therefore of cognitive ToM, associated with other symptoms such as executive dysfunction. In more advanced stages, the limbic circuit dysfunction would affect affective ToM and cause mood disorders ,46,47,48Few neuroimaging studies ,50,51 s using diIn a recent study, affective ToM performance positively correlated with cortical metabolism in the insula and superior temporal gyrus. According to I-123 ioflupane single photon emission computed tomography (123 I-FP-CIT-SPECT), ToM scores did not correlate with basal ganglia and cortical dopaminergic function. This technique was also used as a proxy marker of serotoninergic impairment revealing a negative correlation with thalamic specific binding ratio. Cholinergic function was indirectly measured by quantitative electroencephalography (posterior and anterior Theta/Alpha power ratio as a proxy of cholinergic tone) . These fFinally, a study in PD patients undergoing subthalamic nucleus deep brain stimulation (STN-DBS) showed worsening of affective ToM that correlated with brain hypometabolism (according to Fluorodeoxyglucose-PET) in the bilateral cingulate gyrus, bilateral middle frontal gyrus, left middle frontal gyrus, temporal lobe (fusiform gyrus), bilateral parietal lobe and bilateral occipital lobe. In addition, the ToM impairment correlated with hypermetabolism in the left superior temporal gyrus and bilateral inferior frontal gyrus .Cognitive ToM:A wide variety of tools have been used to evaluate ToM in PD ,14,52. SFalse-belief task [Yoni task [ief task : in whiconi task , a sensiStrange Stories Test [ies Test : a task Advanced Test of ToM (AT) [ToM (AT) : a task ToM stories test [ies test : in whicAffective ToM:Reading the Mind in The Eyes Test (RMET) [t (RMET) : it is oThe Emotion Attribution Task (EAT) [sk (EAT) : this isCognitive and affective ToM:Faux-Pas test [Pas test : this teThe Awareness of Social Inference Test (TASIT) [ (TASIT) : these aToM has been studied in PD for the last 20 years. The first study found worse performance of a ToM task  in 11 non-demented patients in comparison with 8 elderly controls and 9 university-aged control participants . HoweverThe first systematic review about ToM in basal ganglia disorders included ten studies on PD, showing that cognitive and affective ToM were impaired in advanced stages of the disease, whereas results in early stages remained controversial .n = 921) [Roca et al.  were then = 921) .n = 25), a recent study found poor performance in several SC tests, among which affective (with RMET) but not cognitive ToM was also evaluated. Half of this sample showed a moderate to severe motor state [Focused on early-onset medicated PD patients with disease duration less than 5 years  but not in affective ToM (assessed with EAT) . These fMoreover, some studies found that mood disorders such as depression influenced ToM performance in PD , whereasIt has been suggested that SC impairment (and hence ToM impairment) could be either a primary disorder or secondary to another related deficit . Since tSome authors assume that frontostriatal deficits in PD could affect not only EF but also ToM as they could share the same circuitry. In this regard, most studies found an association between EF and cognitive ToM performance ,61,65. POn the other hand, a few studies show an association between ToM and other cognitive domains. One study investigated the relationship between language and ToM in PD  finding With respect to the cognitive state, most studies have included “non-demented” PD patients. This term includes MCI and cognitively normal (CN) patients as a single group, but their cognitive performance is different. However, two recent studies included them as separate groups. The first one observed that PD-MCI patients  score < 26) performed worse than PD-CN and a HC group in affective ToM (measured with RMET). However, cognitive ToM was not evaluated . The secSC and especially ToM are essential processes that allow the correct management of interpersonal relationships . More spSuch is the importance of the evaluation of SC in general, and of ToM in particular, in neurodegenerative disorders, that they are considered a domain that should be taken into account for the diagnosis of MCI and dementia . Non-motIt has been suggested that the anatomical regions involved in ToM are integrated into two functionally dissociated circuits according to a neurobiological model. The cognitive ToM network mainly includes the dorsal ACC, the DMPFC, and the dorsal striatum/caudate. On the other hand, the affective ToM network primarily comprises the VMPFC and OFC, the ventral ACC, the amygdala, and the ventral striatum . These aEarly nigrostriatal degeneration in PD would lead to dysfunction of the associative circuit and therefore EF and cognitive ToM. In more advanced stages mesolimbic impairment would explain the mood and affective ToM problems . The impThe influence of depression disorders on ToM performance is controversial in the general population , and theThe cognitive state also influences ToM outcomes. Only two recent studies differentiated among CN and MCI PD patients ,66 findiAccording to the basal ganglia circuits, it has been suggested that dopamine depletion in PD could explain ToM impairment. However, most studies did not find differences between medicated and non-medicated (with dopaminergic drugs) patients ,60. On tThere are some limitations in our review. Although we added the most relevant publications of ToM in PD, this is not a systematic review, and this prevents us from performing an analysis of paper quantity/quality. Nonetheless, we aimed to report a narrative review including other aspects such as the comprehensive background to the ToM concept, suggested circuitries affected in PD or test descriptions. On the other hand, we did not include the study of facial emotion recognition , but this is not considered a part of the ToM construct as reported previously in the scientific literature ,77,78,79In conclusion, ToM, especially the cognitive subcomponent, is impaired in PD. Whereas in advanced PD, both cognitive and affective ToM are affected, previous findings on early patients are not uniform, likely due to several confounding factors. The study of ToM in PD is important as these deficits worsen patients’ quality of life and could increase the patients´ social isolation. Future investigations should include full neuropsychological batteries allowing for the study of all cognitive domains in CN and MCI patients, as well as the evaluation of depressive patients, and analysis of the interaction between dopaminergic medication and disease severity. More neuroimaging studies that may explain the underlying networks of ToM deficits in PD as well as dopamine and serotonin transporter imaging studies are warranted.


The synthetic lethality (SL) clinical success of PARP inhibitors in homologous recombinant deficient tumors has established a new concept for cancer treatment. For decades, efforts have centered on identifying genetic interactions for determining essential tumoral genes, and more recently, SL interactions to determine combinational treatments against persistent cancer reappearance. Currently, the feasibility of CRISPR screen methodology has emerged as the state of the art for uncovering new SL or viable interactors in the biology and treatment of cancers. We present the up-to-date research of numerous laboratories that take advantage of the genome-wide forward genetic CRISPR screen tools and protocols to identify cancer biomarkers, genetic interactions and novel therapies. Indeed, investigations are nowadays focused on defining innovative combinatorial treatments based on SL interactions. By coupling different drugs, concentration treatments can be lowered and therefore toxicity reduced. CRISPR screen technologies have deeply impacted cancer research to promote a robust advance in combined therapies.Cancer is a complex disease resulting from the accumulation of genetic dysfunctions. Tumor heterogeneity causes the molecular variety that divergently controls responses to chemotherapy, leading to the recurrent problem of cancer reappearance. For many decades, efforts have focused on identifying essential tumoral genes and cancer driver mutations. More recently, prompted by the clinical success of the synthetic lethality (SL)-based therapy of the PARP inhibitors in homologous recombinant deficient tumors, scientists have centered their novel research on SL interactions (SLI). The state of the art to find new genetic interactions are currently large-scale forward genetic CRISPR screens. CRISPR technology has rapidly evolved to be a common tool in the vast majority of laboratories, as tools to implement CRISPR screen protocols are available to all researchers. Taking advantage of SLI, combinatorial therapies have become the ultimate model to treat cancer with lower toxicity, and therefore better efficiency. This review explores the CRISPR screen methodology, integrates the up-to-date published findings on CRISPR screens in the cancer field and proposes future directions to uncover cancer regulation and individual responses to chemotherapy. After advances in genome sequencing, maximum interest has been placed on interpreting the genetic code  and undeCRISPR systems have lately been classified as Class 1, comprehending Type I, III and IV, and Class 2 with Type II, V and VI, reviewed in . InteresEmploying a catalytically inactive Cas9 (dCas9) fused to different functional domains allows competent transcriptional activation or repression . Indeed,loci level, but also at the expression regulation  one. Currently, numerous laboratories have taken the advantage of this methodology’s simplicity to design and analyse screens in order to find innovative leads to treat the most complex disease of all, cancer. Here, we provide a technical overview of the protocol steps to perform genome-wide forward genetic CRISPR screens in cancer cell lines and we review recent approaches using this methodology for cancer. Efforts are focused on unravelling genetic interactions (GI) in vitro and in vivo, to find novel synthetic lethal (SL) or viable interactor genes that potentially result in combinatorial therapeutic targets, synergistically or antagonistically, with known drugs.The continuous expansion of CRISPR/Cas technology enables genetic modifications not only at a genomic locus modification, hence each cell must receive a single sgRNA.CRISPR/Cas9 screens are powerful genomic tools to elucidate the mechanistic aspects of cancer and to define biomarkers and therapies. Despite being challenging, the design and execution of CRISPR pooled screens have become available to the vast majority of laboratories. Scientists merely need to adjust the appropriate experimental strategy to the biological question to be solved. A schematic overview of the general steps is shown in The type of CRISPR library must adjust to the biological question to be answered: CRISPRko libraries eliminate gene expression for loss-of-function or SL/viable interactions screens, CRISPRa libraries to overexpress genes for gain-of-function screens and CRISPRi libraries to block TSS and investigate gene repression. The number and diversity of gene knockouts (KO) or genomic region modifications depends on the approach to be taken: when aiming to find any GI in the genome, a CRISPR library will contain ~20,000 targeting molecules; alternatively, if the screen focuses on a smaller fraction of genes with related function, for instance: transcription factors , nuclearloci activation or inhibition; in a large-genome scale or as subpools; and by way of plasmids or viral preparations. Additionally, alternative options may be obtained from commercial companies. Remarkably, selected oligonucleotides are designed to be redundant. Distinct molecules target the same genomic sequence to compensate for effects of sgRNA diverse efficiency and off-targets consequences. It is recommended to use at least four independent sgRNAs for each genome sequence targeted [sgRNAs selection for the CRISPR library must be done by cutting efficiency (which varies among sgRNAs and sequence context) and target specificity . Recently, many computational models and resources offer further advances in efficiency and specificity prediction for the design and selection of CRISPR pooled libraries ,33,34,35targeted , additiotargeted . For CRItargeted ,15, to itargeted  and optitargeted ,40. For targeted . In mostloci. Since the efficiency of sequence alterations depends on the targeted number of copies, the CRISPR/Cas system may unevenly engineer each genetic locus in genetically instable cancer cell lines. Accordingly, candidate hits of a polyploid cell line conducted screen will result in worse quality compared to a diploid or haploid cell line [Together with the choice of the library comes the selection of an appropriate cell line. When possible, the best is to perform the screen in multiple cell lines ,38, in oell line ,38.loci by repairing the generated DSBs through non-homologous end joining (NHEJ). This repair pathway will be employed by many cancer cell lines, where the homologous direct repair (HDR) is impaired [CRISPRko screens promote small insertions or deletions in the specific impaired . Neverthimpaired . Moreoveimpaired .Once appropriate cell lines and a library are chosen, the experimental strategy must be designed. At this moment, both biological and technical replicates, together with the number of samples to be collected over time (with the corresponding baseline time points or controls) may be established. Besides, library representation must be set to ensure a sufficient diversity representation of sgRNAs in the cell population, 500–1000 cells per sgRNA are recommended . All thePreceding the actual experiment, several setup steps must be done, as settings may vary depending on each specific cell type. First, the characterization of the cellular model: doubling time, drug concentration or fluorescence activated cell sorting (FACS) threshold selection settings, duration of the screen, etc. Secondly, it must be decided if the endonuclease Cas9 will be delivered together with the sgRNAs, increasing plasmid size at the cost of reducing the transduction efficiency, or if Cas9 will be already stably expressed by the cell population ,45, requBRCA2 background is shown in To prove that the screen settings will work, a proof of principle experiment is recommended. An example targeting genes   that wheIn vitro CRISPR screens with immortalized cell lines have generally no limitation in cell number, thus wide-genome screens using millions of cells are easily feasible, while screens in primary cell lines, organoids or in vivo are commonly limited in cell number, thus more directed screens to particular gene families, biochemical routes or protein types with subpooled libraries are more suitable.Following transduction, cell selection may be done by antibiotic resistance or FACS. Several days of culture are necessary for the sgRNA-Cas9 duplex to alter the genome, cells must be kept in antibiotic selection to screen during 7 to 14 days ,30,38, tAt the end the different collected time points will be compared to the baseline time points. Next, genomic DNA is extracted and the integrated sgRNAs amplified by PCR and sequenced, in order to assess the relative abundance of each targeted gene. Overall, the screens can either readout for negative selection or positive selection. Negative selection screens will sensitize cells to the condition and identify essential genes to survive the selective pressure. Thus, the aim is to find sgRNAs less abundant compared to baselines or controls. Conversely, positive selection screens identify genes whose mutation serves as a positive proliferative advantage over the applied condition, offering resistance to the given drug or used stress, hence the readout are sgRNAs with higher abundance than basal time points.There are two forms of screening process: arrayed and pooled screens. The protocol described above summarizes pooled screens, whereas arrayed screens are performed into multi-well plates and individual reagents must be dispensed into single wells. Phenotypes can be assessed manually, but the readout can be automatized by direct imaging of cells , luminesp-values help to establish a ranked candidate hit list. Alternatively, for arrayed-based screens or read out by FACS studies, candidate hits are found by determining the sgRNAs that produce significant changes in the expression of stained or fluorescent proteins.Genomic DNA is isolated from the biological or technical replicates of harvested samples at different time points. As collected samples are frozen in tens of millions cells, standard procedures must be scaled up. Lentiviral integration of sgRNA cassettes facilitates the analysis by PCR amplification using universal primers that target the common template sequences flanking each specific 20 nt sgRNA. Multiple PCR reactions until expending the sample produce a library of short and highly diverse DNA fragments containing the sgRNA sequences. Every fragment library corresponds to a particular collected time point or replicate and may be used as input for next-generation sequencing (NGS) to obtain sequence reads. Adding diverse sequence barcodes (indexes) to the different libraries/samples allows pooling of many samples for simultaneously sequencing in a NGS equipment. Barcodes are afterwards used to demultiplex information and create individual sample sequence files. Current sequencers are able to provide >10,000 reads per sgRNA . BioinfoPromising gene candidates must be validated by means of transcriptional repression, protein inhibition or KO generation, to avoid false positive results. Commonly, hits are analysed together with members of the same pathway, complex or direct upstream and downstream interactors ,63,64. TMedical research aims to identify essential genes and cancer driver mutations. Computational efforts have integrated 501 RNAi screens in numerous well-characterized and heterogeneous cancer cell lines to produce a cancer dependencies map . The ProNevertheless, with the goal of defining essential genes, Dede et al.  analyzedSynthetic lethal (SL) interactions (SLI) result in reduced cell survival and they occur from the inactivation of certain gene pairs; although when single, each gene loss still allows cell viability . SL therUBB and its paralog UBC often mutated in ovarian and uterine tumors [SLI have been also defined among paralog genes, through the loss of the second functionally redundant paralog gene. shRNA and RNAi screens have already defined tumoral survival dependent on certain paralogs: SMARCA4 and SMARCA2 either of each are catalytic subunits of the SWI/SNF chromatin remodelling complex , or the e tumors . Employie tumors  observede tumors . To probe tumors  screenedCombinatorial treatments are settled as central new therapies to treat tumors, since tumors are context dependent, they may respond differently depending on the tissue affected and the individual health, age, gender or genetic background. Importantly, combinational therapies allow lower doses, hence less toxicity for healthy tissues and patients , currentBRD2, Mediator proteins, AXL and TEAD1 kinase pathways or G1-S transition promoters sensitized parental and resistant cells to JQ1, however depletion of the BAF chromatin remodelling complex or ubiquitination-related genes  increased their resistance. To clarify resistance pathways to PARPi, Dev et al. [On many occasions, CRISPR screen approaches simultaneously search synthetic viability/resistance and lethality mechanisms to chemotherapy. GI screens are acting bidirectionally in order to set candidate hits that render tumor cells more sensitive or more resistance to chemotherapeutical drugs. In order to discover GI that confer resistance to BET bromodomain inhibitors (BBDIs), Shu et al.  used CRIv et al.  screenedv et al.  and concDepending on the purpose of each study, the selected cells and drug concentrations will set the type of experiment to be conducted. Very sensitive cells to the selected drug allow screen stringent conditions, i.e., low treatment concentrations, to find the most essential GI with the therapy. However, a cell line more resistant to the treatment will require higher drug concentrations and will result in increased number of candidate hits, many of which would have minor phenotypes. Moreover, positive selection screens to identify gene hits that confer drug resistances, commonly have a high signal-to noise ratio, since only mutated resistance genes survive; on the contrary, in negative selection screens cells grow for ten or more population doublings to induce sensitization of cells by mutations that confer moderate phenotypical deficiencies . Due to The major obstacle for cancer therapy is cancer recurrence. Combined drugs offer good potential to circumvent not only cancer reappearance, but also lessen the doses and their inherent toxicity. At this aim, drug repurposing is central for the simplicity and promptness that could reach patients, although new therapies are discovered, there is a drug productivity gap . A compeRab34, Pdcl, and Tubd1 and are involved in ciliary functions and negative regulators include Megf8, Mgrn1 and Atthog, which converged on the oncoprotein SMO. They constructed a clonal NIH/3T3 cell line with a GFP driven Hh-responsive promoter element, the fluorescence of which increased in response to the ligand Sonic Hedgehog (SHH) in a dose-dependent manner, thus providing a quantitative readout used for a genome-wide pooled screen based on FACS. They transduced the Brie library [Pooled CRISPR genetic forward screens based on FACS readouts offer an alternative way to conduct pooled CRISPR screens. They focus on protein levels determined by measuring the fluorescence intensity in response to drug, ligand or any regulator treatment. Pusapati et al.  used thi library  into the library  integratFurthermore, Jaitin et al.  propose Multicellular spheroid 3D models have been defined to more closely reproduce in vivo tumor conditions, compared to 2D cultured cells. They have been proven to better resemble cellular growth, cell-to-cell communication, gene expression or signal transduction in vivo, and therefore, they offer a more faithful environment for disease modeling or drug screening, reviewed in . 3D cultThe ex vivo screens are performed in cultured primary cell lines that have been extracted from living animals. Cortez et al.  developeThe in vivo screens consist on transducing cells in vitro and subsequently transplanting them into animals in order to complete the screen. The number of cells to be implanted and the engraftment efficiency may restrict the experiment. Several laboratories have already implemented this approach; a summary is shown in KP mouse model by lentiviral particles inhalation. The authors validated miR30b, miR146a and miR-190b as tumor suppressors.In vivo screens may also be conducted by transduction of tissues in vivo, however, the accessibility and cell number to infect is restricted, and hence screens are limited to subpooled libraries. As an example, Hong et al.  investigcis enhancer-gene pairs.98% of our genomes contains non-coding DNA regions, where many oncogenic mutations may occur and whose biological function is still unknown . Besidesloci in our genome and are involved in different cellular processes like transcriptional regulation, cellular reprogramming or differentiation, and also, they have been implicated in human diseases, such as cancer [trans or in cis. Cis-acting lncRNAs regulate gene expression depending on their own sites of transcription, at diverse distances of gene targets by activating, repressing or modulating their expression, reviewed in [lncGRS-1 as a novel glioma-specific therapeutic target enhancing radiotherapy. In another CRISPRa screen for the responses of melanoma cells to the BRAF inhibitor vemurafenib, Joung et al. [Moreover, long non-coding RNAs (lncRNAs) are transcribed from thousands of s cancer . LncRNAss cancer , which riewed in . Consequiewed in  screenediewed in ) in the g et al.  transducg et al.  developeg et al.  determinAdditionally, microRNAs (miRNAs) regulate gene expression post-transcriptionally and regulate tumorigenesis, metastasis and proliferation . CRISPR CRISPR screen technologies are accelerating cancer research field by illuminating the molecular mechanisms of tumorigenesis and chemotherapeutical investigation. sgRNA delivery, specificity and efficiency depend on genetic context and cellular type, being highly advisable to use more than one cell line for the screen and candidate genes validation. Despite these limitations, recent improvements in library design and analysis tools, together with the multitude of CRISPRko screens successfully completed have generated valued data that have already been integrated computationally in accessible interfaces, with the aim of creating the resources to match the genomics of cancer with a suitable treatment for each individual patient.Moreover, CRISPR/Cas genetic screens are lately expanding to primary cells, 3D cultures (spheroids and organoids) or in vivo. All these cancer models offer a more accurate microenvironment to investigate tumorigenesis, disease progress or drug responses that enable valuable and sensitive novel GI discoveries. Nevertheless, in these cases sgRNA delivery, lentiviral transduction, library representation and coverage or experimental replications may be still challenging.Regarding cancer immunotherapy, significant advances in tumor antigen presentation, tumor-specific T cells activity or tumor immune-induced cytotoxicity sensitization are already achieved by CRISPR screens strategies, reviewed in ,150.Future applications of other endonucleases as Cas12a that enables multiplexing of sgRNAs , and CasInterestingly, CRISPRko screens are limited to less than 2% of our genome, as functional exons are a small part of our entire genome. Therefore, emerging screening analysis with CRISPRi and CRISPRa are recently providing extremely powerful information about differential regulators of essential genes and place the importance of non-coding regions as the new focus of researchers’ attention. These already present CRISPR applications are vastly crucial for novel diagnosis and therapeutical strategies.Finally, CRISPR screens may be combined with scRNA-seq ,137, proThe growing explosion of these methodologies are currently remodeling oncology research by redefining cancer heterogeneity, biomarkers and therapies, thus gradually resolving the existing limitations to become excellent and routine tools in the close future.


Decision-making deficits in obesity and alcohol use disorder (AUD) may contribute to the choice of immediate rewards despite their long-term deleterious consequences.Gambling task functional MRI in Human connectome project (HCP) dataset was used to investigate neural activation differences associated with reward or punishment (a key component of decision-making behavior) in 418 individuals with obesity (high BMI) and without obesity (lean BMI) and either at high (HR) or low (LR) risk of AUD based on their alcohol drinking levels.Interaction between BMI and alcohol drinking was seen in regions of the default mode network (DMN) and those implicated in self-related processing, memory, and salience attribution. ObesityHR relative to obesityLR also recruited DMN along with primary motor and regions implicated in inattention, negative perception, and uncertain choices, which might facilitate impulsive choices in obesityHR. Furthermore, obesityHR compared to leanHR/leanLR also demonstrated heightened activation in DMN and regions implicated in uncertain decisions.These results suggest that BMI is an independent variable from that of alcohol drinking levels in neural processing of gambling tasks. Moreover, leanLR relative to leanHR, showed increased activation in motor regions [precentral and superior frontal gyrus] suggestive of worse executive function from excessive alcohol use. Delayed discounting measures failed to distinguish between obesity and high alcohol drinking levels, which as for gambling task results suggests independent negative effects of obesity and chronic alcohol drinking on decision-making. These findings highlight distinct associations of obesity and high-risk alcohol drinking with two key constituents of decision-making behavior. Heavy drinking is associated with a greater waist-hip ratio in mid-life even when taking other influences into account such as having overweight parents, maternal smoking in pregnancy, and physical inactivity , 2. FurtThe metabolic imbalance due to obesity is associated with chronic low-grade inflammation due to elevated circulating pro-inflammatory cytokines. This chronic inflammation extends beyond the adipose tissues to the central nervous system (CNS). Ingestion of a high saturated fat diet increases the expression of inflammatory cytokines in the hypothalamus, which presumably are regulated by microglia , 15. TheOverlaps in the pathways that lead to excessive eating (leading to obesity) and alcohol dependence have been studied. Both obesity and alcohol use disorders (AUD) have been linked to the brain’s reward system . OverconNeuropsychological studies support the hypothesis of food/alcohol addiction-related alterations in inhibitory control, emotion regulation, and overall executive function for which a core cognitive trait is decision-making . IndividThe published literature suggests that both individuals with obesity and AUD suffer from decision-making deficits; here, we expand this inquiry to investigate differences in neural activation associated with reward or punishment during the gambling task (a key component of decision-making behavior) in individuals with and without obesity (lean) who are either at high or low-risk of AUD. We posited that groups with high BMI and at high AUD risk (obesityHR) would show greater activation to rewards in brain regions critical for inhibitory control, uncertainty, and memory function, compared to the obesity low-AUD risk (obesityLR) group, reflecting greater reward sensitivity. It is also expected that individuals with lean BMI and low AUD risk (leanLR) would exhibit lesser reliance on immediate monetary rewards than high-risk AUD groups (obesityHR and leanHR). Therefore, the results would help us understand the effect of BMI and alcohol drinking on decision-making for low and high reinforcing rewards.For the present study, we obtained permission from the human connectome project (HCP) to use Open and Restricted Access data from the S1200  release of the Young Adult HCP (ages 22–35). Participants reported no significant history of neurological disorder, cardiovascular disease, or Mendelian genetic disease and did not present any MRI contraindications. General HCP information can be found in Van Essen et al. . Particin = 24; 66% males);  and LR group . More details on subjects selection criteria are given in Supplementary Fig. From the list of obesity and lean participants for whom the gambling task fMRI data were available, we included 418 subjects [109 with obesity and 309 lean categorized based on SSAGA_BMICat in HCP dataset]. Subjects were sub-categorized based on their risk status for AUD. Accordingly, high-risk (HR) comprised of both binge (BD) and heavy drinkers (HD), while the low-risk (LR) group included individuals who drink less than 4 drinks on a single day and for less than one day per week in the past 12 months. Furthermore, subjects who met DSM IV criteria for alcohol dependence or abuse were excluded from the LR category. Obesity and leanHR group  and alcohol drinking  on ddisc_AUC measures. However, we did not see an interaction effect of BMI*alcohol drinking .We observed significantly lower ddisc_AUC values in the obesity and HR group as compared to the lean and LR group p = 0.00; 0.04, iIn this study, 22% of obesity and 28% of lean subjects were at high-risk of AUD and while drinking intensity was significantly higher in obesityHR compared to leanHR their frequency of consumption did not differ. High-intensity drinkers (regardless of frequency) reportedly have higher BMI, which is most likely associated with their increased intake of calories from foods and drinks , 44. TheOur fMRI results showed an interaction between BMI and alcohol drinking in PCu and PrG, which are part of the default mode network (DMN) and implicated in self-related processing, memory, and salience attribution –48. The We observed heightened activation of DMN , the primary motor cortex  and of regions that aid in decision-making during uncertain choices (PIns), regions implicated in attentional deficits , and negative perception (STG) in participants with high BMI and high-risk for AUD relative to their low-risk counter group. Recently, greater BOLD activation in DMN regions, including the ventromedial prefrontal cortex (vmPFC), PCC, and right PrG was reported in subjects with obesity while performing the N-back task . SimilarIncreased activation in DMN and in regions implicated in uncertain decisions in obesityHR as compared to leanHR and leanLR groups is consistent with prior findings of increased DMN activation in obesity compared to lean individuals, which was interpreted to reflect increased attention to internal states like appetite or gut signals . The comFurther, we also observed increased activation in the motor  regions of leanLR individuals compared to leanHR. PFC is mainly concerned with executive control, and metabolic activity in this region has been demonstrated to negatively correlate with BMI and alcoholism , 76. PFCWe also compared the delayed discounting task measures between these groups, which complements the gambling task by assessing preference for small immediate rewards versus large delayed rewards, another key component of decision-making. In agreement with prior findings, we observed significant behavioral differences between obesity and lean groups. The obesity group showed stronger discounting of future monetary rewards than the lean group. This may relate to the preference of obesity individuals for highly rewarding unhealthy foods despite their long-term detrimental effects as compared to lean individuals. We also observed that the delayed discounting measure differed in HR and LR both in obesity and lean individuals. Although these differences were also apparent between the sub-groups with obesityHR and obesityLR having lower measures compared to the leanLR group, the interaction between BMI and alcohol drinking was not significant. The delayed discounting measure did not distinguish between obesity and high alcohol drinking levels, which as for the gambling task fMRI results, suggests that obesity and chronic alcohol drinking have independent negative effects on decision-making.There are certain limitations to the present study. Firstly, the HCP data lacks a measure of reward anticipation, which is another key dimension of decision-making behavior. Secondly, we used only the gambling task-fMRI. Functional connectivity studies using rs-fMRI might provide better information on how intrinsic network function supports decision-making behavior. Thirdly, this explorative study, which solely relies on BMI as a measure of obesity, needs to be extended with precise adiposity measures, other anthropometrics, or metabolic functioning. Moreover, a more detailed analysis of the type of alcohol consumed would give more insights into these findings considering the differential impact of alcohol types on weight changes reported across studies. The fourth limitation is that participants were predominantly of European ancestry and individuals from other ethnicities may carry a higher risk of obesity and have a higher burden for its deleterious consequences . Thus thThe current study documents differences in the neural activation patterns during the gambling task in obesity and lean participants at high and low-risk of AUD. The findings demonstrate a significant impact of BMI and alcohol consumption, and interaction of the two, on interoceptive regions including posterior DMN and parietal operculum during the gambling task. However, we found significant heterogeneity in the discounting measures within and across groups. Moreover, delay discounting was seen to independently predict BMI and alcohol drinking. Together, these findings highlight distinct associations of obesity and high-risk alcohol drinking with two key constituents of decision-making behavior.Supplementary Figure legendsSupplementary Fig S1Supplementary Fig S2Supplementary Fig S3Supplementary Fig S4Supplementary Fig S5


Nephrotoxicity is a major cause of intrinsic acute kidney injury (AKI). Because renal tissue damage may occur independently of a reduction in glomerular filtration rate and of elevations in plasma creatinine concentration, so-called injury biomarkers have been proposed to form part of diagnostic criteria as reflective of tubular damage independently of renal function status. We studied whether the urinary level of NGAL, KIM-1, GM2AP, t-gelsolin, and REGIIIb informed on the extent of tubular damage in rat models of nephrotoxicity, regardless of the etiology, moment of observation, and underlying pathophysiology. At a time of overt AKI, urinary biomarkers were measured by Western blot or ELISA, and tubular necrosis was scored from histological specimens stained with hematoxylin and eosin. Correlation and regression studies revealed that only weak relations existed between biomarkers and tubular damage. Due to high interindividual variability in the extent of damage for any given biomarker level, urinary injury biomarkers did not necessarily reflect the extent of the underlying tissue injury in individual rats. We contended, in this work, that further pathophysiological contextualization is necessary to understand the diagnostic significance of injury biomarkers before they can be used for renal tubular damage severity stratification in the context of nephrotoxic and, in general, intrinsic AKI. Acute kidney injury (AKI) is a syndrome characterized by abrupt decline in renal excretory function derived from reduction of the glomerular filtration rate (GFR), causing azotemia, alterations in diuresis , or both, with important sanitary and economic consequences . AccountThe typical and most common injury pattern of renal AKI is termed acute tubular injury (ATI) , comprisp) or reductions in urinary output [p is a poor and late surrogate of GFR and is practically useless for AKI diagnosis in clinical circumstances until over 60% of renal excretory function is lost [p is also highly unspecific at informing on the underlying pathophysiological mechanisms, and the extent or absence of tissue injury. For instance, Crp may increase with (as in ATI) or without  underlying tissue damage. Similarly, extensive renal damage may occur without concomitant elevations in Crp [p increase [p [International criteria for AKI definition and diagnosis  rely on increments in plasma creatinine concentration , and patient prognosis ,31,32. WThe renal insults used to induce AKI in the animals of this study generated different degrees of acute tubular injury affecting mostly cortical or outer medullary nephron segments, depending on the drug or drug combination. p-values) but weak  Spearman correlations of some biomarkers with cortical and total damage. Linear regression studies provided very low fitting  in all cases. This indicated that, although some tendencies might exist between the levels of some of these biomarkers and the extent of renal cortical damage, the high variability weakend their potential use as renal damage intensity probes. As expected from the definition of AKI itself, Crp showed a very weak and non-significant relation with renal damage , increased filtration from the bloodstream (overwhelming the tubular reuptake capacity), higher tubular secretion, decreased tubular reabsorption, and combinations thereof a. IncreaIn a classical view, renal tissue injury is thought to contribute to increasing shedding of injury-related biomarkers from renal (mostly tubular) cells and to reduce reabsorption (or both). However, biomarker shedding and handicapped reabsorption, leading to increased biomarker urinary excretion, may also result, for instance, from sublethal alterations not distorting renal tissue architecture, i.e., not causing tissue injury. This situation is exemplified by several models wherein defective reabsorption occurs without concomitant tissue injury. These include the maleate model and the megalin knock-out model. Acute administration of sodium maleate uncouples proximal transmembrane transport and inhibits proximal reabsorption ,35,36, lOn the contrary, cases of extensive tissue injury with low  urinary biomarker levels remain unexplained. Hypothetically, very damaged nephrons may become obliterated by luminal tissue debris accumulation. Obliterated nephrons would not contribute to the overall urine and would thus not communicate pathological status information through urinary biomarkers. However, this did not seem to be the case in our models, because rats showing severe renal tissue injury and low urinary biomarker levels varied from one biomarker to another. This observation pointed at a distinct behavior of each biomarker as a function of tissue injury, which needs to be further investigated.p, and thus was not directly proportional to the filtration function   and urinary biomarkers, but merely that this relationship is not directly proportional. In fact, damage was related to both urinary biomarkers and GFR (and Crp), but additional factors decoupled these relationships. Thus, more biomarkers are not synonymous with more tubular damage, nor vice versa (The level of urinary biomarkers was not linked to Cr of GFR) b. In turce versa b. This dUnless otherwise indicated, all reagents were purchased from Sigma-Aldrich .p-formaldehyde for histological studies. In all cases, injury biomarkers were measured by Western blot or ELISA . Tubular injury was blindly determined by means of an injury score, which was calculated semi-quantitatively, as previously described . In totaPlasma creatinine concentration was determined with a commercial colorimetric kit , according to the manufacturer’s instructions.A volume of urine (21 μL) from each animal corresponding to the same fraction of their 24-h urinary output was separated by acrylamide electrophoresis. Proteins were transferred to an Immobilon-P Transfer Membrane  and incubated with antibodies against KIM-1 , t-gelsolin , RegIIIB , GM2AP ), followed by horseradish peroxidase-conjugated secondary antibodies and chemiluminiscent detection  with photographic films . Bands were quantified by densitometric analysis with the Scion Image software . A positive control was used in all experiments to normalize biomarker levels, and all biomarkers were expressed as arbitrary units . Bands were quantified and normalized to the intensity of the positive control. The positive control was urine from a highly proteinuric rat urine which tested positive for the studied biomarkers in pilot studies.A commercial ELISA was used to measure NGAL  according to the manufacturer’s instructions.p values < 0.05 were considered non-normal). Because data displayed non-normal distributions, the Spearman’s correlation analysis was performed to evaluate the strength of relationship between two quantitative variables. GraphPad Prism 7.0  and IBM SPSS Statistics 25 software  were used for the statistical analysis.Data were expressed as mean ± SEM. Linear regression analysis was used to study the relation of biomarker levels to the extent of renal damage or plasma creatinine concentration. The Kolmogorov–Smirnov test and visual inspection of histograms were used to evaluate data distribution  and biomarker pleiotropy associated with comorbidities potentially present in patients , which w