[{"data":1,"prerenderedAt":106},["ShallowReactive",2],{"cases":3},[4,29,49,69,85],{"id":5,"tier":6,"title":7,"description":8,"subject":9,"source":10,"pilot":11,"searchText":12,"shortTitle":13,"task_id":5,"topic":7,"source_publication":14,"doi":15,"background_and_objective":8,"data_and_descriptions":16,"source_data_access":17,"agent_task":18,"input_files":19,"evaluation_directory":28},"FR-0001","frontier","Postprandial glycemic responses and baseline metabolic physiology","Responses to the same food can differ between individuals. Meal composition and baseline metabolic physiology may contribute to this variation. Participants without a prior diabetes diagnosis consumed standardized meals after an overnight fast. Seven base meals each provided approximately 50 g of total carbohydrate. A subset also received fiber, protein or fat before a rice meal. Baseline phenotyping included steady-state plasma glucose (SSPG), an indicator of insulin resistance, and the disposition index (DI), which characterizes beta-cell function relative to insulin sensitivity.\n\nScientific question: In these adults without a prior diabetes diagnosis, do postprandial glycemic responses to standardized meals with equal carbohydrate loads exhibit reproducible differences between individuals, and how are the direction and magnitude of these differences associated with baseline insulin resistance and beta-cell function?","Metabolic physiology","Original research",false,"Responses to the same food can differ between individuals. Meal composition and baseline metabolic physiology may contribute to this variation. Participants without a prior diabetes diagnosis consumed standardized meals after an overnight fast. Seven base meals each provided approximately 50 g of total carbohydrate. A subset also received fiber, protein or fat before a rice meal. Baseline phenotyping included steady-state plasma glucose (SSPG), an indicator of insulin resistance, and the disposition index (DI), which characterizes beta-cell function relative to insulin sensitivity.\n\nScientific question: In these adults without a prior diabetes diagnosis, do postprandial glycemic responses to standardized meals with equal carbohydrate loads exhibit reproducible differences between individuals, and how are the direction and magnitude of these differences associated with baseline insulin resistance and beta-cell function?  ","Glycemic responses & metabolic physiology","Wu, Y. et al. Individual variations in glycemic responses to carbohydrates and underlying metabolic physiology. Nature Medicine 31, 2232–2243 (2025).\n\nDOI: 10.1038\u002Fs41591-025-03719-2","10.1038\u002Fs41591-025-03719-2","cgm_curves.csv contains 23,520 glucose measurements from 588 meal-challenge curves in 38 participants. Each curve contains 40 measurements at 5-minute intervals from −25 to 170 minutes relative to meal intake. participant_metadata.csv contains clinical and metabolic phenotypes for 74 participants, including the 38 with CGM data. meal_nutrients.csv describes the seven base meals. baseline_metabolomics.tsv, baseline_lipidomics.tsv and baseline_olink.csv provide baseline molecular measurements for optional extensions.\n\nTime points are nested within curves, and meal conditions and repeated challenges are nested within participants. Meal coverage, repeat counts and participant coverage across assays are unequal. These inputs represent the publicly shared subset. The molecular measurements are supplementary to the main question. README.md and data_dictionary.csv define file roles, identifiers, units, observed ranges and missing values.","https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41591-025-03719-2","frontier\u002FFR-0001\u002Ftask.md",[20,21,22,23,24,25,26,27],"frontier\u002FFR-0001\u002Fdata\u002Fcgm_curves.csv","frontier\u002FFR-0001\u002Fdata\u002Fbaseline_lipidomics.tsv","frontier\u002FFR-0001\u002Fdata\u002Fparticipant_metadata.csv","frontier\u002FFR-0001\u002Fdata\u002Fmeal_nutrients.csv","frontier\u002FFR-0001\u002Fdata\u002FREADME.md","frontier\u002FFR-0001\u002Fdata\u002Fbaseline_metabolomics.tsv","frontier\u002FFR-0001\u002Fdata\u002Fdata_dictionary.csv","frontier\u002FFR-0001\u002Fdata\u002Fbaseline_olink.csv","frontier\u002FFR-0001\u002Fevaluation",{"id":30,"tier":6,"title":31,"description":32,"subject":33,"source":10,"pilot":11,"searchText":34,"shortTitle":35,"task_id":30,"topic":31,"source_publication":36,"doi":37,"background_and_objective":32,"data_and_descriptions":38,"source_data_access":39,"agent_task":40,"input_files":41,"evaluation_directory":48},"FR-0002","Doxycycline post-exposure prophylaxis and the gut resistome and microbiome","Doxycycline post-exposure prophylaxis (doxy-PEP) reduces some bacterial sexually transmitted infections, but antibiotic exposure may alter commensal communities and select for resistance genes. The source trial randomized participants to doxy-PEP or standard care in a 2:1 ratio and collected rectal swabs at enrollment and month 6. The sequencing subset was selected partly according to sample availability and, in the doxy-PEP arm, higher reported use.\n\nScientific question: Within the supplied sequencing subset of the DoxyPEP randomized trial, does doxycycline exposure over six months alter the gut antimicrobial resistome and bacterial microbiome measured in rectal samples, and what are the direction and magnitude of any changes?","Microbiome","Doxycycline post-exposure prophylaxis (doxy-PEP) reduces some bacterial sexually transmitted infections, but antibiotic exposure may alter commensal communities and select for resistance genes. The source trial randomized participants to doxy-PEP or standard care in a 2:1 ratio and collected rectal swabs at enrollment and month 6. The sequencing subset was selected partly according to sample availability and, in the doxy-PEP arm, higher reported use.\n\nScientific question: Within the supplied sequencing subset of the DoxyPEP randomized trial, does doxycycline exposure over six months alter the gut antimicrobial resistome and bacterial microbiome measured in rectal samples, and what are the direction and magnitude of any changes?  ","Doxycycline & the gut resistome","Chu, V. T. et al. Impact of doxycycline post-exposure prophylaxis for sexually transmitted infections on the gut microbiome and antimicrobial resistome. Nature Medicine 31, 207–217 (2025). Published online 3 October 2024.\n\nDOI: 10.1038\u002Fs41591-024-03274-2","10.1038\u002Fs41591-024-03274-2","participants.csv describes 99 participants. samples.csv contains 213 sequencing-sample records: 127 DNA and 86 RNA records, with treatment arm, visit, antimicrobial exposure and sequencing information. arg_calls.csv contains resistance-gene measurements. microbiome_genera.csv contains genus-level measurements for DNA and RNA, and microbiome_species.csv contains species-level measurements for DNA. Inputs are processed measurement tables.\n\nVisits occur at enrollment and month 6. Some participants lack a time point or assay, and the DNA and RNA sample sets are not fully matched. participant_id identifies repeated measurements, and sample_id connects each measurement table to its sample record. Inference concerns the supplied sequencing subset, whose selection was affected by exposure and sample availability. README.md defines variables, units, missing values and relationships among the five CSV files.","https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41591-024-03274-2","frontier\u002FFR-0002\u002Ftask.md",[42,43,44,45,46,47],"frontier\u002FFR-0002\u002Fdata\u002Fparticipants.csv","frontier\u002FFR-0002\u002Fdata\u002Fsamples.csv","frontier\u002FFR-0002\u002Fdata\u002FREADME.md","frontier\u002FFR-0002\u002Fdata\u002Fmicrobiome_genera.csv","frontier\u002FFR-0002\u002Fdata\u002Farg_calls.csv","frontier\u002FFR-0002\u002Fdata\u002Fmicrobiome_species.csv","frontier\u002FFR-0002\u002Fevaluation",{"id":50,"tier":6,"title":51,"description":52,"subject":53,"source":10,"pilot":11,"searchText":54,"shortTitle":55,"task_id":50,"topic":51,"source_publication":56,"doi":57,"background_and_objective":52,"data_and_descriptions":58,"source_data_access":59,"agent_task":60,"input_files":61,"evaluation_directory":68},"FR-0003","Felzartamab and molecular phenotypes of kidney transplant rejection","Antibody-mediated rejection (ABMR) can involve immune activity, tissue injury and chronic changes that need not evolve together. Established expression classifiers and transcript sets summarize these processes as continuous molecular scores. Felzartamab is an anti-CD38 monoclonal antibody. The supplied data come from a small randomized, double-blind, placebo-controlled trial with nine infusions over 20 weeks and follow-up to week 52. Earlier clinical findings motivated investigation of the molecular response and its persistence.\n\nScientific question: Among kidney transplant recipients with late active or chronic active ABMR, how does 20 weeks of felzartamab treatment, compared with placebo, affect the evolution of biopsy molecular phenotypes from baseline to weeks 24 and 52, in direction, magnitude and persistence?","Transplant immunology","Antibody-mediated rejection (ABMR) can involve immune activity, tissue injury and chronic changes that need not evolve together. Established expression classifiers and transcript sets summarize these processes as continuous molecular scores. Felzartamab is an anti-CD38 monoclonal antibody. The supplied data come from a small randomized, double-blind, placebo-controlled trial with nine infusions over 20 weeks and follow-up to week 52. Earlier clinical findings motivated investigation of the molecular response and its persistence.\n\nScientific question: Among kidney transplant recipients with late active or chronic active ABMR, how does 20 weeks of felzartamab treatment, compared with placebo, affect the evolution of biopsy molecular phenotypes from baseline to weeks 24 and 52, in direction, magnitude and persistence?  ","Felzartamab & transplant rejection","Diebold, M., Gauthier, P. T. et al. Effect of felzartamab on the molecular phenotype of antibody-mediated rejection in kidney transplant biopsies. Nature Medicine 31, 1668–1676 (2025).\n\nDOI: 10.1038\u002Fs41591-025-03653-3","10.1038\u002Fs41591-025-03653-3","sample_metadata.csv describes 65 biopsies from 22 recipients at two centers, including treatment assignment, visits, baseline characteristics, tissue-composition proxies and histology. molecular_scores.csv provides established molecular classifiers, transcript-set scores and donor-derived cell-free DNA measurements. expression_log2.csv.gz contains normalized log2 expression for 49,495 probe sets across the 65 samples. feature_annotation.csv.gz maps probe sets to gene symbols and names.\n\nRandomization is at the recipient level, with repeated biopsies and incomplete scheduled visits. The target visits are baseline, week 24 and week 52; two additional biopsies were obtained at week 12. Multiple probe sets may map to one gene. README.md and data_dictionary.csv define variables, scales, sample relationships and missing values.","https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41591-025-03653-3","frontier\u002FFR-0003\u002Ftask.md",[62,63,64,65,66,67],"frontier\u002FFR-0003\u002Fdata\u002Fsample_metadata.csv","frontier\u002FFR-0003\u002Fdata\u002Fexpression_log2.csv.gz","frontier\u002FFR-0003\u002Fdata\u002Ffeature_annotation.csv.gz","frontier\u002FFR-0003\u002Fdata\u002FREADME.md","frontier\u002FFR-0003\u002Fdata\u002Fdata_dictionary.csv","frontier\u002FFR-0003\u002Fdata\u002Fmolecular_scores.csv","frontier\u002FFR-0003\u002Fevaluation",{"id":70,"tier":6,"title":71,"description":72,"subject":73,"source":10,"pilot":11,"searchText":74,"shortTitle":75,"task_id":70,"topic":71,"source_publication":76,"doi":77,"background_and_objective":72,"data_and_descriptions":78,"source_data_access":79,"agent_task":80,"input_files":81,"evaluation_directory":84},"FR-0004","Peripheral blood mononuclear cell respiration and glaucoma progression","Some patients with glaucoma continue to lose visual-field function despite treatment to lower intraocular pressure. Previous research has implicated mitochondrial bioenergetics in glaucoma susceptibility. Peripheral blood mononuclear cell respiration can be measured using oxygen consumption rate (OCR), including basal, ATP-linked and maximal respiration and reserve capacity. Visual-field mean deviation (MD) summarizes visual function, with more negative values indicating worse function.\n\nScientific question: Among patients with primary open-angle glaucoma receiving routine pressure-lowering treatment, is peripheral blood mononuclear cell mitochondrial respiratory function associated with long-term changes in visual-field mean deviation, and what are the direction and magnitude of the association?","Cellular bioenergetics","Some patients with glaucoma continue to lose visual-field function despite treatment to lower intraocular pressure. Previous research has implicated mitochondrial bioenergetics in glaucoma susceptibility. Peripheral blood mononuclear cell respiration can be measured using oxygen consumption rate (OCR), including basal, ATP-linked and maximal respiration and reserve capacity. Visual-field mean deviation (MD) summarizes visual function, with more negative values indicating worse function.\n\nScientific question: Among patients with primary open-angle glaucoma receiving routine pressure-lowering treatment, is peripheral blood mononuclear cell mitochondrial respiratory function associated with long-term changes in visual-field mean deviation, and what are the direction and magnitude of the association?  ","PBMC respiration & glaucoma","Petriti, B. et al. Peripheral blood mononuclear cell respiratory function is associated with progressive glaucomatous vision loss. Nature Medicine 30, 2362–2370 (2024).\n\nDOI: 10.1038\u002Fs41591-024-03068-6","10.1038\u002Fs41591-024-03068-6","longitudinal_observations.csv contains 2,310 visual-field visits from 229 eyes of 139 patients. It includes cellular respiration measures, visit-level MD and intraocular pressure, follow-up time, and demographic and clinical information. Each row represents one eye at one visit. data_dictionary.md defines variables, measurement levels, units, missing values and observation timing.\n\nVisits are nested within eyes and eyes within patients. The data include repeated measurements, correlation between fellow eyes, unequal visit intervals and truncated observation windows, including windows ending before glaucoma surgery. OCR was not measured prospectively at baseline and may have been measured near or after the end of the visual-field observation window. The scientific question concerns observational association.","https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41591-024-03068-6","frontier\u002FFR-0004\u002Ftask.md",[82,83],"frontier\u002FFR-0004\u002Fdata\u002Fdata_dictionary.md","frontier\u002FFR-0004\u002Fdata\u002Flongitudinal_observations.csv","frontier\u002FFR-0004\u002Fevaluation",{"id":86,"tier":6,"title":87,"description":88,"subject":89,"source":10,"pilot":11,"searchText":90,"shortTitle":91,"task_id":86,"topic":87,"source_publication":92,"doi":93,"background_and_objective":88,"data_and_descriptions":94,"source_data_access":95,"agent_task":96,"input_files":97,"evaluation_directory":105},"FR-0005","Age-related streptococcal antibodies and infection or carriage events","Repeated exposure to Streptococcus pyogenes in high-burden settings may contribute to naturally acquired immunity, but quantitative antibody correlates remain uncertain. Conserved antigens such as GAC, SLO, SpyAD and SpyCEP are of interest for vaccine research, while DNAseB antibodies are used as markers of prior exposure. Maternal IgG can cross the placenta and subsequently decline during infancy. The supplied data cover mother–infant and household cohorts in The Gambia.\n\nScientific question: In this high-burden setting in The Gambia, what levels and age-related patterns of IgG against conserved S. pyogenes antigens are observed from birth through later age groups? In the household cohort, is antigen-specific IgG associated with subsequent culture-confirmed infection or carriage events, and what are the direction and magnitude of the associations?","Infectious disease","Repeated exposure to Streptococcus pyogenes in high-burden settings may contribute to naturally acquired immunity, but quantitative antibody correlates remain uncertain. Conserved antigens such as GAC, SLO, SpyAD and SpyCEP are of interest for vaccine research, while DNAseB antibodies are used as markers of prior exposure. Maternal IgG can cross the placenta and subsequently decline during infancy. The supplied data cover mother–infant and household cohorts in The Gambia.\n\nScientific question: In this high-burden setting in The Gambia, what levels and age-related patterns of IgG against conserved S. pyogenes antigens are observed from birth through later age groups? In the household cohort, is antigen-specific IgG associated with subsequent culture-confirmed infection or carriage events, and what are the direction and magnitude of the associations?  ","Streptococcal antibodies & infection","Keeley, A. J. et al. Early-life serological profiles and the development of natural protective humoral immunity to Streptococcus pyogenes in a high-burden setting. Nature Medicine 31, 3360–3371 (2025).\n\nDOI: 10.1038\u002Fs41591-025-03868-4","10.1038\u002Fs41591-025-03868-4","Two independent cohorts are provided: 94 mother–infant pairs and 442 participants from 44 households. mother_infant_igg.csv records paired maternal and infant antibody measurements. participants.csv describes household-cohort members. followup_visits.csv records infection or carriage observations. observation_periods.csv specifies continuous observation intervals. igg_measurements.csv records actual antibody measurements, and household_followup.csv records household-size follow-up.\n\nThe data cover five antigens and include repeated visits, household clustering, recurrent events and gaps in observation. The cohorts use separate identifiers. Dates and exact ages were anonymized while within-participant intervals, age groups and household structure were retained. Unmeasured IgG periods are not prefilled. Observation intervals specify follow-up interruptions and right censoring. README.md defines fields, units, missing values and file relationships.","https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41591-025-03868-4","frontier\u002FFR-0005\u002Ftask.md",[98,99,100,101,102,103,104],"frontier\u002FFR-0005\u002Fdata\u002Fhousehold_followup.csv","frontier\u002FFR-0005\u002Fdata\u002Fparticipants.csv","frontier\u002FFR-0005\u002Fdata\u002FREADME.md","frontier\u002FFR-0005\u002Fdata\u002Fmother_infant_igg.csv","frontier\u002FFR-0005\u002Fdata\u002Ffollowup_visits.csv","frontier\u002FFR-0005\u002Fdata\u002Fobservation_periods.csv","frontier\u002FFR-0005\u002Fdata\u002Figg_measurements.csv","frontier\u002FFR-0005\u002Fevaluation",1791659693484]