Loneliness and wisdom have opposite effects on health and well-being. Loneliness is a serious public health problem associated with increased morbidity and mortality. Wisdom is associated with better health and well-being. We have consistently found a strong negative correlation between loneliness and wisdom. The present study aimed to investigate the association of loneliness and wisdom with the gut microbiome. One hundred eighty-four community-dwelling adults (28–97 years) completed validated self-report-based measures of loneliness, wisdom, compassion, social support, and social engagement. Fecal samples were collected and profiled using 16S rRNA sequencing. Linear regression analyses, controlling for age and body mass index, revealed that lower levels of loneliness and higher levels of wisdom, compassion, social support, and social engagement were associated with greater phylogenetic richness and diversity of the gut microbiome. Partial least squares (PLS) analysis to investigate multivariate relationships extracted two composite variables. Linear regression model predicting alpha-diversity with PLS components revealed that a linear combination of all psychosocial predictors  was significantly associated with alpha-diversity. For beta-diversity, compassion and wisdom accounted for a significant proportion of variance in overall microbial community composition. Findings may have implications for interventions to reduce loneliness and possibly its health-related adverse consequences. Future research should explore whether increasing compassion and wisdom may improve loneliness and overall well-being as well as microbial diversity. Loneliness and social isolation are important public health risks, linked to worse emotional, cognitive, and physical health, functional decline, and premature death , 2. LoneWisdom is a multifaceted human characteristic with affective (or compassionate), reflective, and cognitive dimensions , 10. TheThe ability of gut microbes to communicate with the brain and modulate human behavior has emerged as an exciting concept in health and disease. The “microbiota-gut-brain-axis” involves bi-directional signaling between the gastrointestinal and central nervous systems and is regulated at neural, hormonal, and immunological levels . AlteratThe present study sought to examine the relationship of microbial alpha-diversity and beta-diversity to loneliness and wisdom, as well as related psychosocial factors, in a sample of community-dwelling individuals across the adult lifespan. We hypothesized that higher levels of loneliness and lower levels of wisdom, compassion, social support, and social engagement would be associated with lower microbial diversity.www.ResearchMatch.org, and word-of-mouth. Participants were screened for major neuropsychiatric disorders using the Mini-International Neuropsychiatric Interview (MINI) (The study included 184 community-dwelling adults (28–97 years). Inclusion criteria were age between 21 and 100 years, English fluency, and physical/cognitive ability to complete study assessments. This investigation was part of larger ongoing studies, including the SAGE  study and non-psychiatric comparison subjects from a study of aging and mental illness –40. Partw (MINI) . ExclusiParticipants completed validated scales of loneliness  , wisdom Fecal samples were obtained from participants using at-home self-collection kits  and returned via mail. Samples were immediately frozen and stored at −80°C. DNA extraction and 16S rRNA amplicon sequencing were completed using the Earth Microbiome Project protocols , 49. In Sequencing data were processed using QIIME2 (version 2019.7) , 54. RawA two-sided alpha = 0.05 was used to determine statistical significance. The adaptive control of false discovery rate (FDR) procedure by Benjamini-Hochberg was used for multiple comparisons . UnivariDemographic and clinical characteristics for the sample are presented in F = 3.27, p = 0.041), with lower alpha-diversity among individuals with high loneliness severity, compared to those with no/low (p = 0.015) and moderate (p = 0.042) severity  and wisdom total score , we examined whether associations with microbial diversity were moderated by age . Loneliness significantly interacted with age on alpha-diversity , such that greater loneliness was associated with lower alpha-diversity in older adults  but not in young/middle-aged adults . There was no significant age interaction for wisdom (p = 0.118). Similarly, we examined gender as a potential moderating factor, and did not find any significant interactions between gender and psychosocial predictors on alpha-diversity (ps > 0.183). Finally, we explored other variables that could potentially explain or moderate the relationship between loneliness and alpha-diversity, including depression and physical well-being. Neither depression (p = 0.665) nor physical well-being (p = 0.950) was associated with alpha-diversity.Considering the wide age range of participants and that age was significantly correlated with loneliness , whereas component 2 was not (p = 0.217). Component 1 comprised of a linear combination of all psychosocial predictors  and accounted for 39.6% of the variance of the psychosocial predictors (ps > 0.238).In multivariate analysis, we extracted composite variables from the PLS result and continuously added them into the linear regression model predicting alpha-diversity, examining the contribution of each composite component added by the size of explained variance in the outcome of alpha-diversity . edictors . The effps > 0.055).Beta-diversity was significantly associated with compassion, the cognitive and affective dimensions of wisdom, and wisdom total score . After aTo our knowledge, this is the first study to show that loneliness and wisdom, including its important component of compassion, are related to gut microbial diversity and composition. As hypothesized, higher levels of loneliness and lower levels of compassion, wisdom, social support, and social engagement were associated with decreased phylogenetic richness and diversity of the gut microbiome. We further evaluated the multivariate relationship of alpha-diversity with psychosocial variables, and found that the PLS component comprising of all psychosocial variables were significantly associated with alpha-diversity. Wisdom and compassion were associated with both microbial diversity and microbial community structure and composition.vice versa.Gut microbial diversity and composition have been previously reported to be associated with personality traits and psychosocial constructs –23. IncrThe mechanisms by which loneliness, compassion, and wisdom may be related gut microbial diversity is unknown. It is typically believed that reduced alpha-diversity represents worse physical and mental health, as low microbial diversity has been associated with various diseases, such as obesity, inflammatory bowel disease, and major depressive disorder , 36. TheOn the other hand, social support, compassion, and wisdom may confer protection against loneliness-related instability of the gut microbiome. Prior evidence suggests that perceived social support may buffer the negative effects of chronic stress on pro-inflammatory markers . Those eDifferent dimensions of wisdom were associated with microbiome diversity and composition. Alpha-diversity findings indicate that increased self-reflection, ability to regulate emotions, and pro-social attitudes and behaviors are associated with greater ecological diversity of the gut microbiome within individuals. Beta-diversity findings indicate that compassion and the cognitive dimension of wisdom account for a significant proportion of variance overall microbial community composition differences across individuals.Our findings have potential clinical implications for developing interventions to reduce loneliness and its health-related consequences. Increasing perceived social support, participation in social activities, and wisdom may improve loneliness by engaging overlapping biological targets. We have shown that it is possible to increase wisdom, particularly its affective and pro-social aspects, with behavioral interventions . Prior rvice versa. The bi-directionality of gut-brain communications and cross-sectional nature of this study limit interpretations of causality. Loneliness may lead to changes in the gut microbiome or, reciprocally, alterations of the gut milieu may predispose an individual to become lonely. Despite these limitations, the findings represent a step forward in understanding the relationships between the gut microbiome and psychosocial factors that have important consequences for health and well-being. Future longitudinal studies of diverse samples are needed to examine the relationship of changes in loneliness and wisdom with alterations in the gut microbiome as well as other inflammatory, neuroendocrine, and metabolic biomarkers. Similarly, the effects of psychosocial interventions on the microbiota should be examined as well as effects of probiotic treatments on loneliness and wisdom. This type of research will help improve our understanding of the microbiota-gut-brain-axis.This study had several important limitations. We did not have a measure of social network size or social interaction. It is important to dissociate subjective loneliness from objective social isolation, because more physical contact and interaction with others would provide increased opportunity to recolonize with more microbes. Additionally, as this was an exploratory study, we did not have measures of medical morbidity, diet, or other biological markers to further investigate relationships with health status. The sample size is modest considering the large age range. The effect sizes in this study were small to medium. A wide range of environmental and genetic factors can affect microbiome composition as well as psychological health. It is possible that some of the genetic and environmental effects on psychological well-being are via influence from the microbiome and https://www.ebi.ac.uk/ena/browser/home, PRJEB11419. Sample IDs and EBI accession numbers for individual subjects and additional metadata used in this study are available in https://qiita.ucsd.edu/) under study ID 10317.The datasets presented in this study can be found in online repositories. The name of the repository and accession number can be found below: European Molecular Biology Laboratory's European Bioinformatics Institute (EMBL-EBI) European Nucleotide Archive (ENA), The studies involving human participants were reviewed and approved by UCSD Human Research Protections Program. The patients/participants provided their written informed consent to participate in this study.TN: conceptualization, investigation, data curation, formal analysis, visualization, and writing – original draft. XZ, T-CW, JL, and XT: formal analysis, writing – review, and editing. CL: data curation, writing – review, and editing. RK: methodology, software, resources, supervision, writing – review, and editing. DJ: conceptualization, project administration, resources, funding acquisition, supervision, writing – review, and editing. All authors reviewed and approved the final manuscript.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.


Crassostrea gigas, have a different function mechanism compared with that in chordates. In this report, we identified the molecular characteristics of CgRAR to further explore the mechanism of RAR in mollusks. RT-qPCR analysis shows that CgRAR has a higher expression level in the hemocytes and gonads, indicating that CgRAR may play roles in the processes of development and metabolism. The mRNA expression level of both CgRAR and CgRXR was analyzed by RT-qPCR after injection with RA. The elevated expression of CgRAR and CgRXR was detected upon all-trans-RA (ATRA) exposure. Finally, according to the results of Yeast Two-Hybrid assay and co-immunoprecipitation analysis, CgRAR and CgRXR can interact with each other through the C-terminal region. Taken together, our results suggest that CgRAR shows a higher expression level in gonads and hemocytes. ATRA exposure up-regulates the expression of CgRAR and CgRXR. Besides, CgRAR can interact with CgRXR to form a heterodimer complex.Retinoic acid (RA) signaling pathways mediated by RA receptors (RARs) are essential for many physiological processes such as organ development, regeneration, and differentiation in animals. Recent studies reveal that RARs identified in several mollusks, including Pacific oyster  Retinoic acid (RA), an important hormone derived from vitamin A, plays crucial roles in regulating many development and differentiation processes, such as axial patterning, tissue formation, nervous system development, and regeneration . It has trans-RA (ATRA), 9-cis-RA (9cRA), and 13-cis-RA. ATRA is the primary ligand sensed by RAR–RXR heterodimers during the development process , with an average shell length of 65 cm. All the oysters were acclimated in aerated seawater at 15–22°C for at least 1 week before experiment. For tissue expression analysis, mantle (Man), gill (Gil), adductor muscle (Amu), hemolymph (Hae), digestive gland (Dgl), gonad (Gon), and labial palps (Lpa) were collected from nine wild oyster individuals. For RA exposure analysis, 48 oysters were divided into two groups randomly. ATRA was dissolved in dimethylsulfoxide (DMSO); oysters in two groups were injected with DMSO and 2 μg/μl of ATRA and given a supplementary injection every 2 days for a total of five injections.TM RT Master Mix (TaKaRa) was performed according to the instructions. RT-qPCR analysis was performed using SYBR Premix Ex Taq II (TaKaRa) and a Bio-Rad CFX Connect PCR instrument. RS18 was used as reference gene for normalization of gene expression. 2–ΔΔCt method was used to calculate the relative expression level. Primers utilized for RT-qPCR are listed in Total RNA was isolated from different oyster tissues or RA-treated oysters using an RNA extraction kit (Tiangen). Briefly, tissue blocks were ground into a homogenate in liquid nitrogen, the cracking buffer was added to the homogenate, the supernatant was obtained by centrifugation, and subsequent operations were performed according to the kit instructions. cDNA synthesis using PrimeScriptpEGFP-N1 plasmid (Clontech) and then transferred into HEK293T cells with Lipofectamine 3000 (Invitrogen) when the confluence of cells reached 60%. Transfected cells were fixed with 4% paraformaldehyde and then incubated with DAPI for 5 min to stain the nuclei 24 h after transfection. Laser-Scanning Confocal Microscopy System FluoView FV1000  was used to observe fluorescent signal. Primers used for fusion vector construction are listed in Full-length coding sequence (CDS) of CgRAR was cloned into CgRAR, and C-terminal of CgRXR were cloned into pGAD T7 and pGBK T7 to generate CgRAR-AD/BD, CgRXR-AD/BD, C-AD/BDCgRAR, and C-AD/BDCgRXR fusion plasmids; fusion plasmids were co-transferred into Y2H Gold yeast strain according to the manufacturer’s instructions (Clontech). Primers used for fusion plasmids construction are listed in The yeast strain Yeast Two-Hybrid (Y2H) Gold (Clontech) was used to assess protein–protein interactions in this study. The CDS fragments of CgRAR, CgRXR, C-terminal of pCMV-Myc and pCMS-flag to generate the fusion vectors. Primers used for fusion vectors construction are listed in The full-length CDSs of CgRAR and CgRXR were constructed into CgRAR was detected in different tissues isolated from healthy adult oysters under normal growing conditions, including the mantle, adductor muscle, gill, digestive gland, gonad, labial palp, and hemocytes. As a result, the CgRAR gene is widely expressed in all the detected tissues, with a higher expression in hemocytes and gonads -tagged CgRAR was transferred into HEK293T cells. GFP plasmid was also transferred into HEK293T as control. As show in C-AD/BD and CgRXRC-AD/BD fusion vectors, respectively (C and CgRXRC can be grown on QDO selection medium without self-activation (To verify the interaction between CgRAR and CgRXR, a Y2H assay was carried out using the full-length CDSs of CgRAR and CgRXR first. Both CgRAR and CgRXR fusion vectors exhibit strong self-activation . Thus, tectively . Yeast stivation , indicattivation . As a retivation . Taken tRetinoic acid is an important hormone playing critical roles in the processes of organogenesis, neuronal differentiation, and embryonic development in vertebrates . The impC. gigas. In chordates, RARs and RXRs form a heterodimer to regulate the expression of target genes in the perception of ATRA (To help predict the possible function of CgRAR, tissue expression pattern was first examined in adult oysters under normal indoor culture environment in this study. A universal distribution of CgRAR gene was detected in different tissues of oyster, with a higher expression in gonads and hemocytes . Since b of ATRA . A recen of ATRA . Thus, ttrans-RA exposure activates the mRNA expression of both CgRAR and CgRAR in Pacific oyster (CgRAR and CgRXR can be respond to ATRA exposure. It is worth noting that activation at the transcriptional level does not mean that CgRAR and CgRXR proteins can sense and bind to ATRA ligands. Whether CgRAR and CgRXR function in this process and what role they play need to be further studied.All-c oyster . This reCgRAR–GFP fusion plasmid was constructed and transferred into HEK293T cells to explore the subcellular location of CgRAR. The results showed that CgRAR was also localized in the nucleus in the human cell line (Both RARs and RXRs belong to the nuclear receptor family and can regulate target gene transcription in the nucleus in vertebrates . A recenell line . TherefoT. clavigera, Patella vulgata, N. lapillus, and C. gigas, lose the ability to bind ligand RA. In addition, the transcriptional activity of these RARs cannot be activated by RA (In vertebrates, RA–RAR–RXR complex targets RARE of downstream genes, activating or repressing gene transcription . Severaled by RA . It is red by RA . In thised by RA . WhetherThe original contributions presented in the study are included in the article/Crassostrea gigas is not an endangered or protected species and is not a vertebrate.Ethical review and approval was not required for the animal study because XW and YL designed the experiment. KJ, QJ, BH, LW, MZ, and YL carried out the experiments. ZC and WG contributed reagents, materials, and analysis tools. YL wrote the manuscript. XW supervised the study and revised the manuscript. All authors reviewed the manuscript. All authors contributed to the article and approved the submitted version.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.


Treatment of multidrug- and rifampin-resistant tuberculosis (MDR/RR-TB) is expensive, labour-intensive, and associated with substantial adverse events and poor outcomes. While most MDR/RR-TB patients do not receive treatment, many who do are treated for 18 months or more. A shorter all-oral regimen is currently recommended for only a sub-set of MDR/RR-TB. Its use is only conditionally recommended because of very low-quality evidence underpinning the recommendation. Novel combinations of newer and repurposed drugs bring hope in the fight against MDR/RR-TB, but their use has not been optimized in all-oral, shorter regimens. This has greatly limited their impact on the burden of disease. There is, therefore, dire need for high-quality evidence on the performance of new, shortened, injectable-sparing regimens for MDR-TB which can be adapted to individual patients and different settings.endTB is a phase III, pragmatic, multi-country, adaptive, randomized, controlled, parallel, open-label clinical trial evaluating the efficacy and safety of shorter treatment regimens containing new drugs for patients with fluoroquinolone-susceptible, rifampin-resistant tuberculosis. Study participants are randomized to either the control arm, based on the current standard of care for MDR/RR-TB, or to one of five 39-week multi-drug regimens containing newly approved and repurposed drugs. Study participation in all arms lasts at least 73 and up to 104 weeks post-randomization. Randomization is response-adapted using interim Bayesian analysis of efficacy endpoints. The primary objective is to assess whether the efficacy of experimental regimens at 73 weeks is non-inferior to that of the control. A sample size of 750 patients across 6 arms affords at least 80% power to detect the non-inferiority of at least 1 (and up to 3) experimental regimens, with a one-sided alpha of 0.025 and a non-inferiority margin of 12%, against the control in both modified intention-to-treat and per protocol populations.The lack of a safe and effective regimen that can be used in all patients is a major obstacle to delivering appropriate treatment to all patients with active MDR/RR-TB. Identifying multiple shorter, safe, and effective regimens has the potential to greatly reduce the burden of this deadly disease worldwide.ClinicalTrials.gov Identifier NCT02754765. Registered on 28 April 2016; the record was last updated for study protocol version 3.3, on 27 August 2019. The order of the items has been modified to group similar items  was designed in 2015 to avail of and optimize exciting, new developments in treatment for drug-resistant tuberculosis (DR-TB). That year, there were an estimated 580,000 new cases of TB caused by organisms resistant to the most potent first-line anti-TB drugs . Only 132,120 cases (22.7%) of MDR/RR-TB were detected and 125,000 (21.5%) received treatment with second-line TB drugs. Roughly half were cured  culture medium where possible); (b) time to culture conversion assessed in MGIT system (and LJ where possible); and (c) change in time to positivity (TTP) in MGIT over 8 weeksSecondary efficacy outcomes are:The definitions used for the primary efficacy outcome are shown in Table Although differences are not expected, the primary efficacy endpoints are also used to evaluate efficacy across linezolid-dose-reduction strategies.The proportion of patients who died of any causeThe proportion of participants with grade 3 or greater AEs, SAEs, and AESIs of any grade by 73 and 104 weeks  weeks:The endpoint for assessment of safety of the linezolid-dose-reduction strategies is severe linezolid-related toxicity, defined as grade 3 or higher linezolid-related AEs , SAEs, and AEs requiring linezolid discontinuation.The primary analysis will compare the proportions of participants with a favourable outcome at week 73 between each experimental arm and the control arm: for all pairwise comparisons, a two-sided 95% confidence interval of the difference will be estimated. The non-inferiority of an experimental arm compared to the control will be established if the difference in favourable outcome at week 73 is greater than the lower equivalence margin, i.e. if the lower bound of the one-sided 97.5% CI—which corresponds to the lower bound of the 2-sided 95% CI—is greater than or equal to -12%. We present two main reasons for the 12% non-inferiority margin. First, the 70% expected efficacy of the control regimen was already higher than that of the standard of care regimen, mitigating concerns about biocreep. Emerging data has suggested that the control arm, containing new and repurposed drugs, may be even more effective (e.g. 80%) , 45. If The family-wise type I error will be controlled by ordering the non-inferiority comparisons. A fixed sequence approach will be considered: the regimen with the highest proportion of favourable outcomes will be compared to the control. If non-inferiority is concluded, then a comparison between the control and the experimental regimen having the second highest proportion of favourable outcomes will be performed, and so on as long as non-inferiority is concluded. Once non-inferiority is not demonstrated, the comparisons will stop. All the previous comparisons will have been done at the full one-sided alpha level of 2.5%. Adjusted analyses on the primary endpoint will be also performed by controlling for covariates.The main primary efficacy analyses will be performed on both modified intent-to-treat (mITT) and per-protocol (PP) populations for the non-inferiority comparisons. The mITT population contains all randomized participants with culture-positive, FQ-susceptible, and RR-TB. The PP population contains participants from the mITT population who completed the study without any major protocol deviation that impacts the assessment of the primary endpoint. Patients who discontinue the study for reasons other than death or loss to follow-up will be excluded from the PP. Sensitivity analyses will be performed in two other efficacy populations: the assessable population and the mITT plus those with baseline culture-negative tuberculosis.Safety analyses will be performed on the safety population, which includes all enrolled participants who had received at least one dose of study treatment (as treated). A full description of the statistical methods, including handling of missing data and planned analyses, is detailed in the Statistical Analysis Plan.The sample size was estimated through simulations that considered (1) early efficacy responses (at weeks 8 and 39), (2) primary outcome (at week 73) with variations described below, (3) the expected number of non-inferior experimental arms, (4) the type I error (2.5% one-sided), (5) expected reductions in population from ITT to mITT (11%) and mITT to PP (10%), and (6) the non-inferiority margin (12%). Sample size estimates were calculated for 75% favourable outcome at 73 weeks in the non-inferior experimental arms. Favourable outcome frequency in the control arm was assumed to be 70% at 73 weeks. A sample size of 750 randomized participants provides power greater than 80% to demonstrate the non-inferiority of at least 1 (and up to 3) experimental regimens. The expected 75% 73-week response in the experimental arm reflects available data. This includes conventional-regimen treatment with delamanid that resulted in 74.5% favourable treatment outcome  and obseData are collected and entered into an electronic case report form, in a web-based system that is compliant with International Conference on Harmonisation (ICH) Good Clinical Practice (GCP) guidelines. Range checks are programmed into the system. Designated study team members at each participating site perform real-time quality control and periodic quality assurance activities. Checks for consistency are implemented at the data entry level on site and centrally after data entry. Regular data review and data cleaning for quality control are organized in a blinded way and detailed in the Data Monitoring Plan. In addition, external monitoring is performed in accordance with the protocol specific requirements, ICH GCP guidance, and other applicable requirements.Data are managed centrally by Epicentre. Additionally, safety data are also entered in a separate pharmacovigilance database at the centralized MSF Pharmacovigilance Unit. Appropriate medical and research records are maintained for the trial, in compliance with ICH E6 GCP and regulatory and institutional requirements. All study documents are coded with a study identification number. All study records are managed in a secure and confidential fashion.All adverse events that occur during study are documented and followed to resolution or stabilization; in the case of AESIs and SAEs, this follow-up may extend beyond the normal study-reporting period. SAEs are notified, within 24 h of awareness, by the site principal investigator (or designee) to the MSF Pharmacovigilance Unit. All SAEs deemed related to one or more investigational product(s) and considered unexpected with the use of such products are reported to National Regulatory Authorities and national/local IRBs. All other SAEs are reported in an Annual Safety Report prepared by the MSF Pharmacovigilance Unit, and earlier if there are specific local regulations for more frequent reporting. In addition, safety data are reviewed semi-annually by an independent Data Safety Monitoring Board (DSMB), the members of which have expertise in clinical trials, MDR-TB, pharmacology, Bayesian adaptive randomization, and electrophysiology. Their functioning is detailed in the DSMB charter.Figure The results of the trial will be disseminated under the responsibility of the principal investigators of the study. Investigators/study authors will have full access to the final trial dataset. Trial results will be published in peer-reviewed scientific journals and presented at national and international conferences, as appropriate. Results will be shared and discussed with study participants and affected communities. Authorship will be defined according to International Committee of Medical Journal Editors criteria. No professional writers will be involved.M. tuberculosis isolates obtained from sputum samples. A subject may consent to study participation without consenting to future use of stored isolates. Stored isolates may be used only to improve diagnosis (including resistance testing) and treatment of TB. Relevant IRBs will oversee any future research using these specimens.Subjects  are asked to provide written informed consent for storage and future use of The lack of safe, effective, short, simple regimens for treatment of RR-/MDR-TB is a major challenge in TB control. Research shows that inadequately treated drug-resistant TB can undermine the population-level benefits of high rates of success in treatment of drug-susceptible TB . MoreoveIf safe and effective, endTB’s novel regimens have the potential to improve the current treatment options significantly. In the many settings that have not yet adopted all-oral, shorter regimens, endTB regimens could reduce treatment duration by more than 50%, eliminate injections and lessen the pill burden, and potentially increase efficacy without worsening toxicity. Some countries, including South Africa, have adopted routine use of shorter regimens in which bedaquiline has replaced the daily injectable , 53, 54.The endTB trial complements other efforts, recently completed, planned or ongoing, to optimize treatment for drug-resistant TB. In addition, a pharmacokinetic substudy will inform optimized dosing and offer insights into pharmacokinetic and pharmacodynamic drug-drug interactions. endTB focuses on questions, populations, or regimens and/or provides additional  evidence compared to other studies. For example, Opti-Q (NCT01918397) optimized the dose of levofloxacin ; when avN=109); lack of an internal, concurrent control; single-country setting; and the high rate of toxicity with the dose of linezolid examined [A more recent development, the SRA licensure of pretomanid was the first marketing authorization for a novel agent (in the same nitroimidazole class as delamanid) used within a new, shorter regimen. Prospects are promising for this regimen containing pretomanid, bedaquiline, and linezolid (BPaL); currently WHO recommends its use only under research conditions . Additioexamined –60. The examined . This woLike Opti-Q, STREAM, STREAM II, and TB-PRACTECAL, endTB employs the gold standard of the randomized, concurrently, controlled trial. Several other design decisions were made to “future-proof” the trial despite the established lengthy time required to enrol trial participants for DR-TB . These dendTB results will not inform treatment of FQ-resistant TB. endTB ensures the use of FQ in patients who may be able to benefit from it. And, the endTB consortium has embarked on a second, complementary clinical trial, “Evaluating newly approved drugs in combination regimens for multidrug-resistant tuberculosis with fluoroquinolone resistance” , examining fluoroquinolone-sparing regimens only in patients who are not likely to benefit from that drug class. endTB-Q represents, to date, the only randomized, concurrently controlled trial with adequate power to detect treatment effects in patients with fluoroquinolone-resistant TB.Change in policy and practice around treatment of drug-resistant TB has historically been slow. In the absence of randomized, internally, and concurrently controlled trials, the urgent need for improved treatments, however, has understandably driven recent acceptance of evidence from observational and uncontrolled studies. The endTB trial will close a critical gap by providing high-quality evidence around the safety and efficacy of five injectable-sparing, 9-month multidrug regimens for the treatment of MDR/RR TB.endTB recruitment began in the first site in February 2017; with expansion to additional sites, enrolment is expected to be complete by mid-2021.


Multiple voluntary surveillance platforms were developed across the world in response to the COVID-19 pandemic, providing a real-time understanding of population-based COVID-19 epidemiology. During this time, testing criteria broadened and health-care policies matured. We aimed to test whether there were consistent associations of symptoms with SARS-CoV-2 test status across three surveillance platforms in three countries (two platforms per country), during periods of testing and policy changes.For this observational study, we used data of observations from three volunteer COVID-19 digital surveillance platforms  targeting communities in three countries . The study population included adult respondents (age 18–100 years at baseline) who were not health-care workers. We did logistic regression of self-reported symptoms on self-reported SARS-CoV-2 test status (positive or negative), adjusted for age and sex, in each of the study cohorts. We compared odds ratios (ORs) across platforms and countries, and we did meta-analyses assuming a random effects model. We also evaluated testing policy changes, COVID-19 incidence, and time scales of duration of symptoms and symptom-to-test time.Between April 1 and July 31, 2020, 514 459 tests from over 10 million respondents were recorded in the six surveillance platform datasets. Anosmia–ageusia was the strongest, most consistent symptom associated with a positive COVID-19 test . Fever , shortness of breath , and cough  were also highly associated with test positivity. The association of symptoms with test status varied by duration of illness, timing of the test, and broader test criteria, as well as over time, by country, and by platform.The strong association of anosmia–ageusia with self-reported positive SARS-CoV-2 test was consistently observed, supporting its validity as a reliable COVID-19 signal, regardless of the participatory surveillance platform, country, phase of illness, or testing policy. These findings show that associations between COVID-19 symptoms and test positivity ranked similarly in a wide range of scenarios. Anosmia, fever, and respiratory symptoms consistently had the strongest effect estimates and were the most appropriate empirical signals for symptom-based public health surveillance in areas with insufficient testing or benchmarking capacity. Collaborative syndromic surveillance could enhance real-time epidemiological investigations and public health utility globally.National Institutes of Health, National Institute for Health Research, Alzheimer's Society, Wellcome Trust, and Massachusetts Consortium on Pathogen Readiness. Participatory syndromic surveillance has informed public health for nearly a decade,Real-time, community-based data from these platforms are strongly complementary to the so-called hard outcomes—that is, COVID-19 cases, hospitalisations, and deaths14Evidence before this studyWe searched PubMed for titles and abstracts in English that included the words “COVID” and “symptoms” but excluding “long” or “post” published between Jan 1, 2020, and Oct 31, 2020. This search yielded 99 results. We repeated the search with a focus on surveys by including in addition the words “survey” or “digital platform”, which yielded 75 results. As the COVID-19 pandemic evolved, testing capacity was expanded and governmental guidelines adapted, generally encouraging testing with a broader set of symptoms beyond fever with canonical respiratory symptoms. In parallel, multiple large-scale, participatory, digital surveillance platforms launched to complement knowledge from laboratory and somewhat smaller clinical studies. Symptoms such as loss of smell (anosmia) have been identified as strongly predictive of COVID-19 infection in both clinical and syndromic surveillance analyses and have thus been used to inform these testing policy changes and access expansion.Added value of this studyWe identified symptoms that were or were not consistently associated with a positive SARS-CoV-2 test across various testing conditions by use of six datasets from three COVID-19 surveillance platforms in the USA, the UK, and Israel. These platforms are web-based and smartphone-based, as well as cross-sectional and longitudinal. The study period of 4 months covered varying COVID-19 prevalence during the fall of the first wave and, in some areas, rise of the second wave. Importantly, these collaborative analyses used large-scale surveillance data to track and highlight the value of individual symptoms, specifically anosmia, fever, and respiratory symptoms, to predict SARS-CoV-2 test positivity by region, platform, demographic factors, calendar time, timing of testing, illness duration, exposure and outcome ascertainment, and illness.Implications of all the available evidenceDespite differences in syndromic surveillance methods, access to and timing of SARS-CoV-2 testing, and disease prevalence, anosmia or ageusia were consistently the strongest predictors of COVID-19 infection across all platforms over time. The odds of a positive COVID-19 test was nearly 17 times higher among individuals with anosmia or ageusia than those without these symptoms. Fever and respiratory symptoms (shortness of breath and cough) also ranked highly in their association with test positivity. This large, collaborative analysis showed that anosmia–ageusia, fever, shortness of breath, and cough are suitable empirical signals of ongoing COVID-19 transmission and could be particularly useful in regions where testing data are sparse or delayed. A prospective, iterative, surveillance data-based approach, using multiple datasets such as presented here, is likely to play an important role in other epidemiological contexts.COVID-19 participatory surveillance platforms function in regions that have been variably affected by the pandemic, although no direct comparison of these data has been made to our knowledge. Testing policies,With all of these spatiotemporal changes in policies and access, as well as platform-specific study design features and inherent participation biases, we aimed to identify which symptoms were consistently associated with SARS-CoV-2 test positivity, and thus might represent the most clinically and epidemiologically relevant COVID-19 signals despite possible changes over time and across assessment types of their absolute effect estimates. To achieve this goal, we undertook a comparison of the association of putative CLI symptoms with self-reported SARS-CoV-2 testing results over time, by phase of illness, and in three countries across three citizen-science digital surveillance platforms.We used data from three participatory surveillance platforms in the USA, the UK, and Israel (two platforms per country), spanning a 4-month period of observation early in the pandemic  to estimate odds ratios (ORs) for symptoms on self-reported SARS-CoV-2 test positivity among self-identified non-health-care workers . Mapping of survey questions across platforms and survey language used is provided in the The Carnegie Mellon University  and University of Maryland  Facebook COVID-19 Symptom Survey (CMU/UMD) is one of the three participatory surveillance platforms providing the data used in this study, with respondents from the three study countries . This survey was hosted by CMU's Delphi Research Center and provided web-based surveys to Facebook users,The ZOE COVID Symptom Study App (ZOE) is another of the three participatory surveillance platforms providing the data used in this study, with respondents from the USA and the UK. The app was developed by ZOE Global  with input from physicians and scientists from King's College London , Massachusetts General Hospital , Lund University , and Uppsala University .online survey that included a 1-min, anonymous online questionnaire. The survey was first published on March 14, 2020.The Corona Israel (Israel-Corona) study is the final participatory surveillance platform providing data for this study, with respondents from Israel. Israel-Corona data were collected through a voluntary Data from April 1  up to July 31, 2020, were aggregated into weeks, starting each Monday. The study population was restricted to respondents who self-reported a baseline age between 18 and 100 years (the CMU/UMD survey had decade age categories ranging from ≥18 years to ≥75 years), sex male or female, and non-health-care workers. For regression models, for the CMU/UMD survey age bins, the assigned age was the included decade . Users with missing demographic data were excluded.We reviewed publicly available datavs UK), symptom onset-to-test duration (early [≤3 days] vs late [>3 days]), and periods of varying symptom criteria for testing access (narrow vs broad). We did sensitivity analyses of US-CMU/UMD data to assess the impact of illness duration on effect estimates.We grouped 11 symptoms shared across at least two platforms into meta-symptoms . Tests reported as pending or result unknown were excluded. Testing counts and positive test proportions were tabulated as the number of users (ZOE) or surveys (CMU/UMD and Israel-Corona) and the ratio of test positives to total tests reported with results. Multiple test results could be reported (Israel-Corona and ZOE); if multiple tests were done in a time window smaller than 14 days, only the first test was considered. Users were censored for a 14-day window or after a first positive test. US-CMU/UMD did not survey respondents regarding the timing of the test. CMU/UMD outside the USA specified test results within the duration of the respective illness, up to 14 days, or both, regardless of previous test results.The primary outcome was self-reported result of a SARS-CoV-2 test  on SARS-CoV-2 test status (binary) adjusted for age (continuous) and sex (binary) separately in each cohort. We calculated cross-correlations to assess the relationships between national and platform-specific measurements of tests and cases over time. We did meta-analyses assuming a random effects model . We used robust rank aggregation to aggregate the rank lists of symptom–test positivity ORs. Cross-correlations of time series are reported. Analyses were done with R, version 3.6.3, glm for unweighted ORs, svyglm from the survey library for weighted ORs (CMU/UMD), rma from the metafor library for meta-analysis (random effects model specifying the restricted maximum-likelihood estimator via method=“REML”), aggregateRanks from the RobustRankAggreg library for rank (method=“RRA”) list aggregation, and python statsmodels, version 0.12.0 .The funding sources had no role in study design, data collection, data analysis, data interpretation, or writing or the decision to submit the paper for publication.Between April 1 and July 31, 2020, CMU/UMD registered 6 626 897 (USA), 272 767 (UK), and 98 540 (Israel) anonymous surveys with self-reported age and sex information from individuals who did not work in a health-care setting; ZOE counted 3 360 281 unique adult participants in the UK and 276 146 in the USA; and Israel-Corona registered 131 799 completed surveys from 29 993 unique users in Israel. Individuals participating in these surveillance platforms were more often women and tended to be younger and healthier than in the general population , a trendDuring the study period, SARS-CoV-2 testing capacity was scaled up . MeanwhiTrends in national testing data and proportion of positive tests were generally consistent with platform-specific tests reported , with crSymptom performance, as measured by the age-adjusted and sex-adjusted OR for the primary outcome of positive test versus negative test, showed consistently very elevated ORs for anosmia–ageusia . OverallAlthough CLI symptom signals were positive and similar, gastrointestinal symptoms were less consistently significantly associated. When restricting the analysis to individuals with few symptoms . The OR for anosmia–ageusia, a later onset symptom, rose when up to 4 days of symptoms post-test were included, although this rise was smaller for people tested later in their illness and greater when the UK broadened the symptom criteria for testing. We compare this with CMU/UMD stratified by illness duration  US and UK ZOE symptom score analysis, which have focused on single platforms, countries, or time periods.30Core CLI components of fever, cough, and shortness of breath similarly performed well under a wide range of scenarios evaluated. Importantly, although symptom associations varied across platforms, the top performing symptoms were consistently anosmia–ageusia, fever, and cough and shortness of breath. Other symptoms were inconsistent predictors, or most relevant under specific circumstances. These findings highlight key COVID-19 symptoms as signals for multiregional syndromic surveillance under various surveillance platform designs. Testing is a cornerstone of the pandemic response that has presented substantial challenges globally.These findings show the power of using a digital interface to collect epidemiological data on a multinational scale, tailored to public health needs  over space and time, in the response to a novel pathogen. Although privacy limits the validation of anonymous self-reports against health records, the near-real-time, survey-based outcomes closely mirror national trends and are thus useful for so-called nowcasting and forecasting.Our study has some limitations. These findings should be interpreted with the caveat that, by its nature, real-time participatory syndromic surveillance inherently has potential biases related to, for example, generalisability and selection bias , and measurement bias . We compared each platform with national demographics and outcomes, as well as survey-weighted outcomes (for CMU/UMD). For both UK-ZOE and US-CMU/UMD platforms, respondents were younger and more often women than the general population, which is similar to published online survey participation demographics and echoes research showing possible biases related to use of mobile health devices and solutions in the context of symptom reporting in the COVID-19 era.vs temperature threshold) and account for study design variation . However, we should note that due to the necessary broad encapsulation of symptoms enumerated in each platform, the reporting of all symptoms, including anosmia–ageusia, might reflect subjective interpretations rather than clinical features and might not encompass related symptoms that might be even more highly associated with COVID-19, such as dysgeusia.For this interplatform international comparison of symptom-based COVID-19 prediction, we had to map survey questions  in relation to the users' subjective perception. However, many screening tools in use rely on a person's self-report of symptoms.Despite these limitations, the strength of this study lies in the combination of data from very different digital platforms that vary in terms of their participants' location , assessment design, and their observation over time . All six datasets combined are very large in size (over 10 million respondents), with high numbers of tests done  and the capacity to provide automated, aggregate outcomes in near-real time. We were able to show within and between platform and country the associations of CLI symptoms with COVID-19 test positivity. Lastly, we present here evidence for the use of CLI signals for surveillance of anosmia–ageusia, fever, and respiratory symptoms for surveillance in regions for which real-time COVID-19 case data are inadequate.To our knowledge, this is the first comparison of COVID-19-associated symptoms across multiple countries and surveillance cross-platforms of this scale. We established the strength of fever and respiratory symptoms as good CLI signals, with some variation regarding which respiratory symptom was most associated with COVID-19. Importantly, we showed the generalisability of the unique symptom of anosmia–ageusia as the single strongest predictor of all CLI symptoms considered.This online publication has been corrected. The corrected version first appeared at thelancet.com/digital-health on August 23, 2021https://github.com/hrossman/Covid19-Survey. Data from the ZOE platform used in this study are available to researchers through the UK Health Data Research at https://web.www.healthdatagateway.org/dataset/fddcb382-3051-4394-8436-b92295f14259. Requests for access to the CMU/UMD Facebook COVID-19 Symptom Survey can be done at https://dataforgood.fb.com/docs/covid-19-symptom-survey-request-for-data-access/.Tables of de-identified, aggregated data for the Israel-Corona platform are available at ZOE Global codeveloped the app pro bono for non-commercial purposes. JW, JCP, and SG work for ZOE Global, and TDS is a consultant for ZOE Global. LHN, DAD, and ATC previously participated as investigators on a diet study unrelated to this work, which was supported by ZOE Global. ATC reports personal fees from Pfizer, Bayer Pharma, and Boehringer Ingelheim, outside the submitted work. All other authors declare no competing interests.


Background: Antipsychotic medications provide limited long-term benefit to ~30% of schizophrenia patients. Multimodal magnetic resonance imaging (MRI) data have been used to investigate brain features between responders and nonresponders to antipsychotic treatment; however, these analytical techniques are unable to weigh the interrelationships between modalities. Here, we used multiset canonical correlation and joint independent component analysis (mCCA + jICA) to fuse MRI data to examine the shared and specific multimodal features between the patients and healthy controls (HCs) and between the responders and non-responders.Method: Resting-state functional and structural MRI data were collected from 55 patients with drug-naïve first-episode schizophrenia (FES) and demographically matched HCs. Based on the decrease in Positive and Negative Syndrome Scale scores from baseline to the 1-year follow-up, FES patients were divided into a responder group (RG) and a non-responder group (NRG). Gray matter volume (GMV), fractional amplitude of low-frequency fluctuation (fALFF), and regional homogeneity (ReHo) maps were used as features in mCCA + jICA.Results: Between FES patients and HCs, there were three modality-specific discriminative independent components (ICs) showing the difference in mixing coefficients . The fusion analysis indicated one modality-shared IC (GMV-IC2 and ReHo-IC2) and three modality-specific ICs  between the RG and NRG. The right postcentral gyrus showed a significant difference in GMV features between FES patients and HCs and modality-shared features (GMV and ReHo) between responders and nonresponders. The modality-shared component findings were highlighted by GMV, mainly in the bilateral temporal gyrus and the right cerebellum associated with ReHo in the right postcentral gyrus.Conclusions: This study suggests that joint anatomical and functional features of the cortices may reflect an early pathophysiological mechanism that is related to a 1-year treatment response. Antipsychotic medications provide limited long-term therapeutic benefits to only 30% of patients with schizophrenia , 2. In pNeuroimaging has been used to investigate brain features between responders and non-responders to antipsychotic treatment and their longitudinal changes in schizophrenia patients –11. MagnTo fuse MRI data across modalities, a model of multiset canonical correlation and joint independent component analysis (mCCA + jICA) has been developed . SpecifiThe present study aimed to investigate the differences in multimodal MRI features  between patients with drug-naïve FES schizophrenia and healthy controls (HCs) and between treatment responders and non-responders. We hypothesized that patients with poorer clinical outcomes would differ from those with favorable outcomes in pretreatment joint anatomical and functional brain features that were identified with mCCA + jICA.The study was approved by the local research ethics committee. Written informed consent was obtained from all participants. In all, 55 patients with drug-naïve FES were recruited from the Mental Health Center of our hospital, and 55 HCs were recruited from local communities. The sample size was determined by referring to a similar study using the same methods, in which 19 patients and 21 HCs were included  of patients had received a single antipsychotic drug, and the others had received multiple drugs. Meanwhile, 14.5% (8/55) received a single serotonin reuptake inhibitor. Antipsychotic and the additional drugs used are shown in n = 40) and the non-responder group (NRG) (n = 15).A cutoff of at least 50% reduction was considered the criterion of a treatment response . AccordiThe participants underwent brain scans at baseline using a 3T MRI system  with an 8-channel phased-array head coil. High-spatial resolution T1-weighted images were acquired with a three-dimensional spoiled gradient-recalled sequence . An acquisition matrix comprising 256 readings of 128 phase-encoding steps yielded 156 contiguous coronal slices with 1-mm slice thickness. The final matrix was automatically interpolated in-plane to produce an in-plane resolution of 0.47 mm × 0.47 mm. Resting-state functional MRI was obtained with a gradient-echo echo-planar imaging sequence . Each brain volume comprised 30 axial slices, and each functional run contained 200 image volumes.http://rfmri.org/DPARSF). This is a “pipeline” data analysis toolbox based on Statistical Parametric Mapping (SPM) and Resting-State fMRI Data Analysis Toolkit (REST). Compared with SPM, the procedures and methods applied to DPARSF are similar but easier to be operated in a pipeline manner. High-spatial resolution T1-weighted images were segmented into gray matter maps, which were then normalized to the Montreal Neurological Institute (MNI) space. To suppress noise and effects due to residual differences in anatomy during inter-subject averaging, Gaussian kernel smoothing was conducted with the full width at half maximum (FWHM) of 4 mm × 4 mm × 4 mm by using the Diffeomorphic Anatomical Registration Through Exponentiated Lie Algebra (DARTEL) algorithm (Image data were preprocessed with Data Processing Assistant for Resting-State fMRI (DPARSF) software  was used to integrate imaging features from the three modalities. This algorithm runs in a synergistic scheme. Briefly, mCCA extracts mixing brain matrices to generate flexible correlations across modalities, assisting jICA in determining independent components (ICs) simply and precisely to the greatest extent. Here, the correlations between modalities are considered and weighted extensively, no matter whether they are strong or weak, or whether they share or differ completely. This ensures maximum independence between modalities. Complementarily, jICA improves source separation to decompose the mixing matrix into ICs. This fusion model is thus capable of examining full correspondence of the N-way brain datasets and optimizing for both flexibility in intermodal linkages and high capability of source separation  were reshaped for each participant and normalized with the same average sum-of-squares to ensure equal ranges across maps. Second, normalized maps were input into an mCCA + jICA model. Here, three-dimensional maps were reconstructed into a one-dimensional vector and superimposed to form a theme, which was composed of a voxel matrix . Third, t-tests were performed on mixing coefficients to identify group differences in ICs. P-values below 0.05 were considered statistically significant. If ICs were significantly different between groups in two or more modalities, they were defined as modality-shared discriminative ICs. Notably, the terminology “discriminative” denotes statistically significant differences between groups but does not refer to differential diagnosis. Otherwise, those significantly different in only one modality were called modality-specific discriminative ICs. For ICs with significant differences, the MNI coordinates of voxels (Z > |3.5| and cluster size ≥70) were extracted by using xjView  and labeled on the AAL template.The mixing coefficient of an IC was extracted within each modality. A higher mixing coefficient indicated that the corresponding IC was expressed more in the experimental group than in the control group. The outliers were removed, defined as the values more than twice the interquartile range. Two-sample During the analysis between the FES patients and HCs, feature matrices were normalized so that all features had the same mean sum-of-squares. The relative scaling  was preserved within each modality, i.e., 0.27, 0.52, and 0.64 for GMV, fALFF, and ReHo, respectively. The number of ICs was estimated for each feature and set to 8, according to the minimum description length criteria  and conspost hoc analyses, we investigated the correlations of mixing coefficients of the identified significant ICs with the percentage PANSS reduction by SPSS . The Curve Estimation procedure was applied to curve estimation regression statistics. In addition, t-test was used to compare treatment response (the PANSS reduction) between patients with a single drug and those with multiple drugs. Pearson correlations were performed to evaluate the impacts of both illness duration on symptom severity (the PANSS score) and treatment response and CPZ equivalents on treatment response.In p = 0.01). No intergroup differences were found in age, sex, or education years between the FES patients and HCs or in age, sex, illness duration, baseline PANSS scores, or daily dosage of antipsychotics between the RG and NRG. No differences were found in the PANSS reduction between patients with a single drug and those with multiple drugs . No correlations were observed between illness duration and the baseline PANSS scores (p = 0.71) or PANSS reduction (p = 0.11). CPZ equivalents did not correlate with the PANSS reduction (p = 0.33).The demographic and clinical characteristics of the participants were shown in t-tests showed that mixing coefficients differed between the FES patients and HCs for three modality-specific discriminative ICs, namely, GMV-IC7, GMV-IC8, and fALFF-IC5  but slightly lower mixing coefficients for GMV-IC8  than HCs. Brain regions with differences included the bilateral inferior temporal gyri, middle temporal gyri, calcarine, middle frontal gyri, right postcentral gyrus, and left parietal lobe , involving the bilateral paracentral lobules and supplementary motor areas and the right precentral and postcentral gyri  but higher for ReHo-IC2  in the RG than in the NRG. The involved brain regions were predominantly in the right postcentral gyrus for ReHo-IC2 and in the bilateral temporal gyri and in the right cerebellum for GMV-IC2 , GMV-IC3 , and GMV-IC6  in the RG relative to the NRG. The related brain regions mainly included the bilateral middle and inferior temporal gyri, right fusiform gyrus, left precentral gyrus, and right angular gyrus , GMV-IC6 , and ReHo-IC2  in the FES patients. A linear model was identified to provide the best curve fitting of their correlations (p < 0.05). As shown in Pearson correlation analyses showed that PANSS reductions were correlated with mixing coefficients for GMV-IC1  for patient identification and modality-shared features (GMV and ReHo) for responder discrimination. The percentage reduction in PANSS scores was negatively correlated with mixing coefficients for GMV-IC1 and GMV-IC6 but positively correlated with those for ReHo-IC2. These findings indicated that joint anatomical and functional features of the cortices may reflect an early pathophysiological mechanism that is related to a 1-year treatment response.When comparing patients with controls and responders with non-responders, there were differences identified using a structural mode and a functional mode in the right postcentral gyrus, indicating a common brain region for the diagnosis of schizophrenia and explanation of treatment effect. As part of the parietal lobe, the postcentral gyrus is called the “somatosensory cortex,” is the main receptive area of tactile and kinesthetic sensations, and plays an important role in the sensorimotor network (SMN). The SMN is involved in motor selection and execution, form perception, color processing, stereo-orientation, and depth perception . DeficitIn addition, there were several relatively large regions  from the GMV features that were significant in different therapeutic effect groups, including the bilateral supplementary motor areas, the bilateral thalami, the left insula, the left superior occipital gyrus, the left postcentral gyrus, the right superior temporal gyrus, and particular regions of the cerebellum. The significant correlations between the GMV-IC1, GMV-IC6, and ReHo-IC2 mixing coefficients and the PANSS reduction percentages may represent the role of the GMV mainly in the parietal, frontal, and temporal lobes and brain activity in the postcentral gyrus in the treatment response in patients with schizophrenia. A previous systematic review of 19 studies also showed the same robust results: RG patients had more extensive GMV reductions than NRG patients . There wThe abnormalities in modality-shared IC indicated that these significantly different brain regions across the two corresponding modalities were potentially correlated. ReHo-IC2 showed that the intrinsic activity of the right postcentral gyrus in the RG was lower than that in the NRG, and GMV-IC2 showed a decrease in extensive range of brain regions, mainly distributed in the default-mode network (DMN). Our previous study found that changes in GMV in patients with schizophrenia can disrupt brain functional connectivity . Our resOur study has some limitations. First, the drug selection and medication dosage were not controlled in the study. It is mainly attributed to the heterogeneity in antipsychotic drugs and small sample size of our study, which impeded further stratification analyses. While controlling for these factors is extremely difficult during 1-year follow-ups, this may nevertheless have complicated the interpretation of our results. Second, due to the small sample size of this study, to include as many subjects as possible, there was a significant difference in the years of education, and the number of subjects was not balanced between the RG and NRG. The small sample size and unequal number between the responders and non-responders would reduce the statistical power of our study. Therefore, the results of this study merit replication in future studies with larger sample size and stratification analysis.In summary, by combining structural and functional MRI in drug-naïve FES patients, our study revealed that structural and functional deficits in multiple regions of the brain at baseline were related to a poorer response to antipsychotic treatment at the 1-year follow-up and thus may serve as a potential biomarker for long-term treatment outcomes. In addition, there were interactions between some significantly different brain regions in anatomical and functional modalities. Our findings deepen the understanding of brain mechanisms underlying heterogeneity in treatment outcomes in schizophrenia and provide evidence for the utility of combining structural and functional imaging in differentiating 1-year treatment responses in drug-naïve FES patients.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by West China Hospitals research Ethics Committee. The patients/participants provided their written informed consent to participate in this study.Conception and design by CY, NH, HC, QG, and SL. Administrative support by CY, NH, WZ, QG, and SL. Provision of study materials or patients by CY, NH, BT, WZ, YX, and SL. Collection and assembly of data by CY, NH, BT, WZ, YZ, and YX. Data analysis and interpretation by CY, NH, HC, BT, WZ, YZ, and YX. All authors contributed to the article and approved the submitted version.This study was supported by the National Natural Science Foundation of China , Sichuan Science and Technology Program , Science and Technology Project of the Health Commission of Sichuan Province (Project No. 20PJ010), Fundamental Research Funds for the Central Universities (Project No. 2020SCU12053), Postdoctoral Interdisciplinary Research Project of Sichuan University (Project No. 0040204153248), 1.3.5 Project for Disciplines of Excellence, West China Hospital, Sichuan University (Project Nos. ZYYC08001 and ZYJC18020), Post-Doctor Research Project, West China Hospital, Sichuan University (Project No. 2020HXBH005), and the University of Cincinnati Schizophrenia Research Fund. SL acknowledges the support from the Humboldt Foundation Friedrich Wilhelm Bessel Research Award.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.


Established in July 2012, Enroll-HD is both an integrated clinical research platform and a worldwide observational study designed to meet the clinical research requirements necessary to develop therapeutics for Huntington's disease (HD). The platform offers participants a low-burden entry into HD research, providing a large, well-characterized, research-engaged cohort with associated clinical data and biosamples that facilitates recruitment into interventional trials and other research studies. Additional studies that use Enroll-HD data and/or biosamples are built into the platform to further research on biomarkers and outcome measures. Enroll-HD is now operating worldwide in 21 countries at 159 clinical sites across four continents—Europe, North America, Latin America, and Australasia—and has recruited almost 25,000 participants, generating a large, rich clinical database with associated biosamples to expedite HD research; any researcher at a verifiable research organization can access the clinical datasets and biosamples from Enroll-HD and nested studies. Important operational features of Enroll-HD include a strong emphasis on standardization, data quality, and protecting participant identity, a single worldwide study protocol, a flexible EDC system capable of integrating multiple studies, a comprehensive monitoring infrastructure, an online portal to train and certify site personnel, and standardized study documents including informed consent forms and contractual agreements. Enroll-HD is a worldwide integrated clinical research platform that has, at its core, an observational study that has recruited almost 25,000 participants. In concert, the platform and study are designed to meet the clinical research requirements necessary to successfully develop and evaluate therapeutics for Huntington's disease (HD) . Enroll-huntingtin (HTT) gene that encodes the mutant huntingtin (HTT) protein , a prospective longitudinal observational study that collects natural history data in HD gene-expansion carriers (HDGECs) and non-HDGEC controls. Established in July 2012, the Enroll-HD study has generated a large and rich clinical database with associated biosamples to support research, including developing disease-progression and prognostic biomarkers, identifying clinically relevant phenotypic characteristics, and establishing endpoints for interventional trials. As of January 1, 2021, Enroll-HD is operating worldwide in 21 countries at 159 sites across four continents—Europe, North America, South America, and Australasia—and has recruited 24,854 participants, 20,159 of whom are still currently enrolled, and 19,311 are currently active.Two HD observational studies, REGISTRY and COHORT, were precursors to Enroll-HD. REGISTRY, a longitudinal observational cohort study conducted in Europe between 2004 and 2017 with >14,000 participants, was the result of strong collaboration and trusted partnership among preclinical and clinical investigators, patients and families in forming the European Huntington's Disease Network (EHDN). Enroll-HD has recruited 6,247 participants from REGISTRY who reconsented to continue participation and transfer their data.Currently there is an emphasis on recruiting premanifest HDGEC participants into Enroll-HD, especially younger adults, to identify early biological and clinical characteristics with a view to designing clinical trials earlier in the disease course. Planning is now ongoing for a digital study, SelfEnroll, that will allow remote data collection and encourage younger participants to join.Participants are recruited at specialized HD clinics following a written informed consent that includes research genotyping. Donating biosamples (venous blood) for banking purposes, pedigree charting and family history, linking of data collected across other studies, and willingness to be contacted to consider participation in future trials/studies are additional optional components that require specific participant consent.The study population comprises HDGECs  classified as:Manifest HD: HDGECs age 18 or older who are deemed to have diagnostic HD clinical features in the opinion of the site investigator (and confirmed at each subsequent visit).Premanifest HD: HDGECs age 18 or older who are deemed not to have diagnostic clinical features of HD.Juvenile HDGECs: HDGECs under the age of 18 years who are clinically diagnosed with juvenile HD.HTT gene expansion  and includes three categories:The control population comprises individuals who do not carry the Genotype negative: first- or second-degree relative of an HDGEC, who has undergone predictive testing and does not have the CAG expansion.Family control: family member or other individual not genetically related to an Enroll-HD HDGEC participant .Community control: individual not genetically related to an HDGEC, who did not grow up in an HD-affected family and does not have a concurrent neurological disorder.HTT CAG expansion but do not wish to know their genetic status can enter the study as “genotype unknown” (see below).Individuals from known HD families who are at risk of inheriting the At their annual study visit, each participant is required to complete a core battery of assessments; extended and optional assessments are completed at the discretion of the PI and participant, respectively . Visits via a secure system; no personally identifying information is stored in the EDC system, and a participant's data from another study can be linked using their HDID. Additionally, all participants are assigned both a lab ID and a research ID for use by the biorepository and other service providers (such as travel reimbursement), respectively, to avoid widespread sharing of their HDID. Similarly, a recoded participant ID, not the HDID, is used in publicly available dataset releases to further reduce risk of identification.Identity is protected by assigning an HDID code to each participant, generated https://enroll-hd.org/for-researchers/technical-support/ contain a complete list of variables.Research CAG genotyping is conducted at a central laboratory in Italy for every participant following their baseline visit, including those designated as “genotype unknown.” The CAG-repeat length defined in this research genotyping is used for all data analysis but is not reported back to the site investigator or participant. Participants who enroll as “genotype unknown” are reassigned to the appropriate HDGEC or genotype negative category at the time of data release under the recoded participant ID; the genetic status of these participants is not linked to their HDID as an extra protection. Data on reportable events—suicide attempts, completed suicide, mental health events requiring hospitalization, death from any other cause—are also captured. Most participants consent to donate biosamples; family history (pedigree) may also be recorded, subject to participant consent. The Data Dictionary and annotated eCRF at N = 14,737) and ad hoc sources such as unscheduled visits (N = 970). Participant sociodemographic distribution and disease characteristics . This dataset contains data on 21,116 Enroll-HD participants  from 71,682 visits (baseline and follow-up visits); 55,975 of these were Enroll-HD visits, with the remainder from REGISTRY  and that involve additional assessments are referred to as nested studies; currently, these studies are investigating biomarkers and clinical or patient-reported outcomes. These arrangements reduce participant burden while allowing biomarker and outcome-related data to be linked. Ongoing and proposed supported and nested studies included below.HDClarity (NCT02855476) began in 2016 as a prospective nested annual CSF and blood (serum and plasma) collection initiative recruiting HDGECs and control participants from Enroll-HD. The large longitudinal cohort and the comprehensive phenotypic data linked to each CSF biosample are advantageous in validating potential biofluid biomarkers that were previously assessed in cross-sectional or longitudinal studies , 19, andImageClarity is a proposed nested study that will recruit eligible HDClarity participants to undergo an annual multisequence structural and functional modality brain magnetic resonance imaging (MRI). The goal is to expedite identification of biomarkers relevant across the full spectrum of pathological events, especially those occurring in very early stage HD, to evaluate disease progression in interventional trials.11C]CHDI-180R and its suitability to measure aggregated mutant HTT in the brain, especially the basal ganglia, of HDGECs compared to non-HDGEC controls. This is an adaptive study that includes five go/no-go decision points dependent on the radioligand's promise that is being conducted at three sites in Belgium and the Netherlands.iMagemHTT (11C) (NCT03810898) is an ongoing nested PET-imaging study evaluating the binding and kinetic properties of the radioligand [18F-labeled, next-generation mutant HTT-targeting PET tracers. This first-in-human study will be conducted at a single site at Johns Hopkins University.iMagemHTT (F-18) is a proposed nested study currently in late-stage preclinical development that will comparatively evaluate multiple HTT CAG-repeat instability and identify genetic modifiers of intergenerational CAG instability. Semen and blood biosamples from at least 1,000 male HDGECs will be collected at a single visit at around 40–50 sites.Origin-HD is a proposed nested cross-sectional, multi-site, observational study to investigate differences in germline and somatic LSA is a nested study developing two assessments to measure critical milestones during advanced HD when travel is especially burdensome to participants; importantly, these assessments need to be conducted with the assistance of a participant companion, either in-person or remotely. The two-part study will evaluate the internal consistency, reliability, validity and clinimetric properties of the two assessments in development, initially at four sites and subsequently at 20 sites in the US and UK.The proposed FOCUS-HD nested study aims to longitudinally validate FuRST 2.0—a patient reported outcome assessment sensitive to early functional changes in premanifest HDGECs—and HD-CAB—the only available fit-for-purpose HD cognitive assessment battery —to definPACE-HD  is an ongoing interventional supported study conducted in about 120 HDGEC participants  that useTo accelerate HD therapeutic research and development, the platform provides any verified researcher access to the high-quality datasets and biosamples from Enroll-HD and nested studies. Enroll-HD clinical data are shared with the research community through periodic datasets (PDS) and specified datasets (SPS). PDSs are prepared from the Enroll-HD study database every 1–2 years and include a large majority of the collected variables. Prior to release each PDS undergoes stringent QC and coding procedures during which certain variables are transformed, aggregated, or suppressed (excluded) to protect participant identity. Access to non-transformed, non-aggregated, or suppressed data may be obtained through SPS request, subject to approval by the Scientific Review Committee (SRC) that weighs the scientific merit of the proposed project against the increased risk for participant identification. Renewable biosamples  can be obtained without review but non-renewable biosamples from Enroll-HD  or HDClarity  require merit review by the SRC.https://enroll-hd.org/for-researchers/access-data/.Any researcher employed by a recognized research organization can open an Enroll-HD access account to obtain data and biosamples from Enroll-HD (or nested studies that make such resources available), subject to the researcher's employer/institution signing the appropriate data/biosample use agreement(s). Datasets with online click-through agreements, such as PDSs, are accessible immediately, whereas SPS and non-renewable biosample requests require SRC approval. All biosample requests require completion of a material transfer agreement (MTA) with wet ink signature. More detailed access information is available at https://enroll-hd.org/for-researchers/current-enroll-hd-data-projects/, and a list of the publications using Enroll-HD data and/or biosamples is at https://enroll-hd.org/for-researchers/scientific-publications/. A series of articles providing useful advice on Enroll-HD data analysis is at https://enroll-hd.org/analysis-tools/.Enroll-HD datasets and biosamples have been used by researchers in academia, industry, and healthcare around the world to advance HD research. Enroll-HD PDSs have been downloaded 632 times and 124 SPS requests fulfilled. Further details on data users and their projects can be found at FAN1 and MLH1 genes  were found that affect motor onset. Drug development programs investigating genes involved in DNA mismatch repair are now underway.Genome-wide association studies (GWAS) have already been conducted using biosamples from over 9,000  HDGEC participants, most of them from Enroll-HD as well as other HD clinical studies , 23. UsiPredictive and causal modeling for predictors of HD progression has also been undertaken using Enroll-HD data. Given the large number of healthy controls it was possible to establish cognitive and motor norms to determine the effects of natural aging and contrast these with HD progression. Normative curves by age, sex, and education have been estimated for the 0.05, 0.25, 0.50, 0.75, and 0.95 quantiles from the distribution of observed cognitive, motor and functional scores. Extreme quantile estimates for each measure can be considered as boundaries for natural aging, outside which can be attributed to HD pathology . PropensScientific and operational support services are available to industrial and academic sponsors of HD interventional clinical trials and research studies. The Clinical Trial Committee (CTC) provides sponsors an opportunity to consult with highly experienced HD clinicians and researchers through all stages of protocol development regarding study design, endpoint strategy, and study population. CTC members review the study design, including the proposed assessments and endpoints, and ensure that participant interests are protected. Provided the protocol is rational and reasonable, the CTC issues a letter of acceptance that the sponsor can present to IRBs/ERBs.The CTC also manages the HD Clinical Trial Site Certification program that uses an industry-standard framework to determine whether sites have the appropriate infrastructure to support clinical trials. Sites that are not part of Enroll-HD can apply for site certification to enable participation in other HD-related studies.The Enroll-HD operational infrastructure also offers trial/study start-up and conduct to sponsors, with site feasibility assessment, country and site selection, eligible participant availability (in silico feasibility assessment), and liaison with local IRB/ERBs if requested.Enroll-HD operates under a single study protocol worldwide and is supported by a comprehensive operational and oversight management infrastructure. Data quality and integrity is fundamental, and quality control and assurance measures designed to maximize data consistency, completeness, and accuracy are implemented and monitored at the participant, site, and study level. Enroll-HD's governance structure includes the CTC and SRC (see above), the Scientific Oversight Committee—which provides overall scientific strategy, ensures adherence to study and platform goals, and reviews non-interventional study protocols—and the Data Safety Monitoring Committee that reviews reportable events and addresses safety concerns. Together these committees ensure effective oversight of the platform and guidance to study site investigators and staff, regulatory authorities, researchers, and trial/study sponsors.Enroll-HD uses a centralized multi-study electronic data capture (EDC) system that hosts Enroll-HD and supported/nested study data, providing a common data collection and reporting framework for every study site. This ensures the format and definitions of data entered are consistent on an intra- and inter-site level, cross-sectionally and longitudinally, in turn facilitating the application of centralized data QC procedures. System prompts, guidance documents, automated data validity checks, and automated field completion built into the EDC help ensure that accurate information is entered.Remote centralized statistical monitoring (CSM) of data is conducted at the participant and site level by the data monitoring team. Participant-level data are subject to remote QC that checks cross-sectionally and longitudinally for consistency, completeness, and plausibility. Site-level CSM of compliance, performance, and data quality involves outlier analyses targeting site-specific operational performance metrics and clinical data, which may result in follow-up action (communication and training) with sites. All Enroll-HD sites are routinely monitored to review source data and ensure compliance with the study protocol, Good Clinical Practice (GCP), and other applicable regulations.Sites also receive quarterly bulletins, semi-annual site metrics cards, and other communications. Tailored feedback and support are provided to improve underperforming sites and corrective action plans implemented when appropriate.ad hoc training (in response to site-specific training needs), and self-study of online training materials. Onsite monitors also undergo standardized training to ensure consistency.Investigators undergo standardized site-initiation training regarding the protocol, data entry and informed consent. To ensure consistency and accuracy in data collection, assessment-specific rater training and online certification is conducted through the Enroll-HD Clinical Training Portal (UHDRS motor certification and GCP), interactive webinar training (PBA-s), Recoded participant-level data and biosamples from Enroll-HD are made available to the research community under three stipulations: data and biosamples are shared subject to participants' informed consent and in accordance with GDPR (EU) and HIPAA (US) laws; a data use agreement (DUA) and/or material transfer agreement (MTA) must be signed and adhered to by any requester; and the risk of identification from their clinical data is assessed for all participants before data release and remedial steps taken for those above a predetermined risk threshold.Participant identification recoding uses two data safety methods: the safe harbor method that removes 18 variables that may directly identify individuals , and the expert determination method where statisticians assess all individuals' risk of identification.Enroll!, the Enroll-HD newsletter, features articles about ongoing HD research and clinical trials/studies, including Enroll-HD platform studies, as well as human interest stories from various stakeholders, and is translated into all the languages within Enroll-HD. The Enroll-HD platform also functions as a hub that enables collaborative projects with patient advocacy organizations.Enroll-HD works closely with HD patient advocacy organizations to engage their constituents in ongoing clinical research and provide updates on new developments in Enroll-HD. Since its launch 9 years ago, Enroll-HD has developed into a multi-faceted clinical research platform that can support various clinical studies and interventional trials and has recruited almost 25,000 participants into the core worldwide longitudinal observational study, amassing a rich clinical database that is made available to any researcher. Enroll-HD has successfully incorporated all the required functionalities and provides a dynamic environment that supports clinical research to identify and develop biomarkers and clinically-relevant endpoints, validate novel patient-reported outcome measures, facilitate clinical trial recruitment and site feasibility, and provide expert scientific input on trial/study protocols. Enroll-HD is meeting its remit to better enable the clinical research needs required to develop HD therapeutics.In addition to being a clinical research platform and observational study, Enroll-HD is also a patient registry, defined as “an organized system that uses observational study methods to collect uniform data  to evaluate specified outcomes for a population defined by a particular disease, condition or exposure, and that serves a predetermined scientific, clinical or policy purpose” . Such reIn recent years there has been a drive to recruit more premanifest individuals, particularly young ones, into Enroll-HD to further understand this phase of the disease in preparation for clinical trials in, and subsequent treatment of, such individuals as early as possible. CHDI is now actively planning a companion study, SelfEnroll, that will remotely monitor premanifest participants' disease continuously rather than once a year.Despite the demonstrated commitment of academic researchers, funding agencies, pharmaceutical companies, and patient advocacy groups, drug development for rare disorders has been hindered by sequestered research with insufficient collaboration  that oftSS and CS initially developed the manuscript concept and outline. SS wrote the first draft. JW, JL, and EN wrote sections of the manuscript. SN edited the manuscript throughout and added some further sections. All authors contributed to manuscript revision and have read and approved the submitted version.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.


Advanced age causes skeletal muscle to undergo deleterious changes including muscle atrophy, fast-to-slow muscle fiber transition, and an increase in collagenous material that culminates in the age-dependent muscle wasting disease known as sarcopenia. Advanced glycation end-products (AGEs) non-enzymatically accumulate on the muscular collagens in old age via the Maillard reaction, potentiating the accumulation of intramuscular collagen and stiffening the microenvironment through collagen cross-linking. This review contextualizes known aspects of skeletal muscle extracellular matrix (ECM) aging, especially the role of collagens and AGE cross-linking, and underpins the motor nerve’s role in this aging process. Specific directions for future research are also discussed, with the understudied role of AGEs in skeletal muscle aging highlighted. Despite more than a half century of research, the role that intramuscular collagen aggregation and cross-linking plays in sarcopenia is well accepted yet not well integrated with current knowledge of AGE’s effects on muscle physiology. Furthermore, the possible impact that motor nerve aging has on intramuscular cross-linking and muscular AGE levels is posited. Musculoskeletal injury increases due to falls and other accidental injuries in old age, and age-dependent alterations to skeletal muscle structure and function are the primary causal factors of such incidents . The etiSkeletal muscle ECM is highly structured and regulated to maintain its force-bearing properties and spatial-temporal regulation of muscle-specific stem cells, muscle fibers, and a host of other cell types including fibroblasts, endothelial cells, and nerve fibers ,22,23,24Oxidative muscle fibers (types 1 and 2a) have a rich vascular supply, and as such have higher amounts of collagen in their endomysium, especially type IV, compared to glycolytic fibers (type 2b) . In addiAdult myogenesis is a series of highly coordinated events that follow a defined transcriptional template . Adult mThe receptor for advanced-glycation end-products (RAGE) is a pattern-recognition receptor expressed in activated satellite cells and myoblasts, and was originally discovered in bovine lung homogenate due to its ability to bind AGEs ,48. RAGE14C bomb-pulse technique) [Collagen is the most abundant structural protein found in mammals, and is highly conserved between species ,63,64. Achnique) ,76. Intechnique) . Altogetchnique) . Furtherchnique) ,80. In achnique) . FurtherAGEs are non-enzymatic post-translational modifications to proteins in the body. AGE formation follows the stochastic browning, or Maillard, reaction where a monosaccharide  in its open-ring conformation interacts with a protein to form an unstable Amadori product . Over thAge-dependent changes to the basal laminae alter muscle health, impact force production, and change how muscle stem cells respond to injury . Many agAs mentioned previously, muscle ECM composition is highly dependent on the muscle fiber type. As such, muscles that are predominantly fast-twitch will age differently than muscles that are primarily slow-twitch. Thus, aging is dependent on the location of the muscle in the body, with the hind-limb muscles aging at a faster rate than the forelimb . Fast-twThe neuromuscular junction (NMJ) is a highly regulated microenvironment maintained by cross-talk between glial, motor nerve, and skeletal muscle. The NMJ is comprised of three major segments, the pre-synaptic, post-synaptic, and synaptic extracellular space. Vesicle packaged acetylcholine is localized in the pre-synaptic space inside the peripheral nerve terminal. Following membrane depolarization, acetylcholine is released into the synaptic cleft binding to the acetylcholine receptor, activating sodium ion channels, which results in skeletal muscle contraction.While development of the NMJ is not completely understood, pre-patterning of acetylcholine receptors on the muscle membrane occurs before the motor nerve reaches the immature site . MoreoveLaminins play major roles in motor neuron pathfinding and are known to be critical in synaptogenesis. Peripheral motor neurons traverse the body through their basal laminar tube comprised of laminin α2β1γ1 and α5β1γ1 . MyelinaEndplate fragmentation is a multi-stage disassociation of the NMJ typically seen during aging. This process is marked by a dispersal of clustered AChRs, AChR type switching, and increased turnover rates of the receptor ,119. As There is mounting evidence that the atrophy observed during aging is caused more by signaling disruptions than disuse. The disruption of cross-talk between the muscle and nerve can trigger downstream activation of atrogenes Murf-1 and Fbxo32 via TNF-α activation . In moreDiabetes may support an early onset aging phenotype ,123. ComHyperglycemic conditions in diabetes mellitus causes global AGE formation in the body, leading to diabetic neuropathy and a host of other complications . SensorySevere deficits in motor neurons are not seen until late in diabetic pathology where severe force deficits and motor neuron loss is observed . HoweverThe research covered in this review reveals multiple gaps in our current knowledge regarding AGEs, atrophy, and denervation. Measuring AGEs is particularly difficult since most of the AGE cross-links reside in the irreducible matrix. Methods to measure AGEs need to be standardized, and incorporating ECM normalization factors such as hydroxyproline in homogenization schemas could take into account the insoluble AGEs . There iMuscle and nerve signaling and their relation to the ECM has been particularly difficult to study due to the plastic sensitivity of innervation and inability to study it ex vivo. To date, the current standard for studying muscle-nerve interactions and endplate remodeling is in animal models. There is currently no in vitro model that accurately re-creates muscle innervation. Development of such a model would greatly improve reproducibility while reducing the noise, expense, and animal sacrifice currently required. Further, while there has been increased interest in understanding the specialized endplate ECM, few papers have been published on the non-myelinating Schwann cells that cover each endplate and are known to protectively regulate the intra-synaptic ECM. It is unknown if AGEs cross-link within the synaptic cleft or how cross-linking this specialized ECM effects acetylcholine transmission. Hence, this area of research is relatively unexplored, leaving a possible future topic in ECM modifications and muscle to nerve signaling during aging and other diseases that increase AGE cross-links. In addition, whether modifications to laminin change neural pathfinding and synapse formation is still unclear and interrogating these types of questions might lead to new discoveries in endplate development, motor nerve pathfinding, and endplate stability in the neuromuscular junction.Skeletal muscle aging is a process influenced by deterministic and stochastic processes, and is characterized by muscle wasting, fast-to-slow muscle fiber transition, and an increase in the skeletal muscle collagens. AGE collagen cross-linking clearly plays a role in sarcopenia; however, much study is warranted in further elucidating the impact of AGEs in skeletal muscle. Furthermore, age-related changes to motor nerves drive much of sarcopenia, and may involve AGE cross-linking.