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Background: Evidence on how social and school-level contexts shape pediatric vision screening outcomes is limited, particularly in sub-Saharan Africa. We examined the association between individual and contextual factors and vision screening outcomes in a pilot enhanced school-based vision screening program (ESVSP) in Kumasi, Ghana.

Methods: We conducted a cross-sectional study using data from an ESVSP to detect eye disorders in school-children aged 4 to 22 years. Outcomes were the presence of eye disorders and referral adherence. Exposure variables were individual [(age, sex, socioeconomic status (SES)], and contextual [school type (public vs private)] factors. Logistic regression was used to estimate unadjusted (OR) and adjusted (aOR) odds ratios with 95% confidence intervals (CI).

Results: We analyzed data for 1,123 children screened and 299 referred. The average age was 10.2 (±2.6) years. Overall, 34% (n=382) had suspected eye disorders, and 32.8% (n=98) adhered to the referral. After adjusting for key variables, children attending public (32.2%) compared to private (67.8%) schools had 45% lower odds of identified eye disorders (aOR= 0.55; 95% CI 0.37, 0.83). Children with low (13.3%) compared to high (28.6%) SES had 70% lower odds of referral adherence (aOR= 0.30; 95% CI 0.12, 0.80).

Conclusion: In this pilot school-based program, school context and socioeconomic status were associated with suspected pediatric vision and eye disorders, and referral adherence, respectively. These findings highlight equity-relevant gaps in referral adherence and underscore the need for context-specific strategies to strengthen referral pathways in low-resource settings.

Older individuals frequently harbor multiple brain pathologies, including Alzheimer's disease (AD) related amyloid-β (Aβ) and tau alongside α-synucleinopathy and vascular pathology. Proteomic profiling offers a strategy to better understand common as well as unique features of these different brain pathologies. We analyzed cerebrospinal fluid (CSF) (n=1,658) and plasma (n=749) samples from participants in the BioFINDER cohorts using the automated NULISAseq CNS Disease panel of 125 proteins. Differentially abundant proteins (DAPs) related to AD pathology (based on Aβ- and tau-PET positivity), α-synuclein (based on synuclein amplification assay [SAA] positivity) and vascular pathology (based on white matter lesion [WML] load) were identified with linear models simultaneously including a binary measure for the three pathologies. In the BioFINDER-2 subcohorts, DAPs were further evaluated for associations with continuous baseline (n=1,137) and longitudinal (n=656) Aβ-PET, tau-PET, and WML measures in models accounting for all pathologies. Associations with AD-signature cortical atrophy (n=915) and cognitive decline by the MMSE (n=1054) were also examined. We identified 84 CSF DAPs, with largely distinct protein signatures for each pathology (AD, n=66 DAPs; vascular pathology, n=55; α-synuclein pathology, n=16). 10 DAPs (e.g., FABP3, UCHL1, NPTXR, NPTX2) were altered across all three pathologies, reflecting general neurodegeneration. AD-associated DAPs included glial/inflammatory markers (CHIT1, CX3CL1, CD63) linked to Aβ pathology, and synaptic/neuronal injury markers (VSNL1, NRGN, NEFL) and metabolic enzymes (FABP3, MDH1) linked to tau pathology. Aβ-associated proteomic differences were most evident in CU individuals, while tau-associated differences predominated in MCI. More proteins, particularly neurodegeneration and synaptic markers, were associated with tau change than with Aβ change. Vascular pathology exhibited a distinct profile, enriched for inflammatory, angiogenic and extracellular matrix proteins (PGF, POSTN, TREM1, VCAM1). DDC was the main protein associated with α-synucleinopathy. Only a few proteins, including UCHL1, NPTX2, and NEFL, predicted cognitive decline and cortical atrophy after accounting for all brain pathologies. In plasma, although fewer DAPs were identified (n=20), findings included established AD biomarkers. Only plasma VCAM1 and NEFL were associated with α-synuclein and vascular pathology. NULISA identified stage-dependent, disease-specific CSF biomarker signatures with limited overlap, alongside shared neurodegenerative markers, supporting improved biological interpretation and more refined classification of neurodegenerative pathology.

Background: Blood-based biomarkers offer a scalable alternative to cerebrospinal fluid and PET imaging for Alzheimer's disease (AD) detection, yet traditional venipuncture limits participation among rural and socioeconomically disadvantaged populations. Self-collection using the Tasso+ capillary device could reduce access barriers, but its feasibility and validity for AD plasma biomarkers remain uncertain, particularly with real-world delays prior to processing.

Methods: Adults aged 45-90 years from the Wisconsin SHOW cohort who were underrepresented in AD research (Black or Hispanic race/ethnicity, rural residence, or

Results: Tasso+ collection was successful for 96% of participants; 64% rated it very easy and 86% reported comfort/no pain, yet 57% preferred future venipuncture-particularly Black, lower-income, and lower-education participants. Agreement varied markedly by biomarker. GFAP and NfL demonstrated excellent concordance (CCC 0.97-0.98) with minimal bias (-6% to -8%). Aβ40 and Aβ42 showed modest correlations (r=0.40-0.47) and substantial underestimation (-60% to -70%). Aβ42/40 and pTau217 exhibited poor correlation and extreme positive bias for pTau217 (∼+2600%). Hemolysis was more frequent in Tasso+ samples and contributed to disagreement for several markers; processing lag and sample volume were not strong predictors.

Conclusions: Remote capillary self-collection with a 24-hour delay is suitable for measuring GFAP and NfL but not currently reliable for Aβ or pTau217 without improved handling (e.g., temperature control, hemolysis reduction). Although user experience was favorable, trust and logistical concerns limited preference among underrepresented groups. Community-informed strategies and optimized pre-analytics are essential before deploying Tasso+ in large AD studies.

As cognitive decline progresses, older adults may self-regulate their driving. Avoidance of left turns across traffic is observable in naturalistic driving data but rarely self-reported. We studied 106 older adults using baseline and one-year follow-up neuropsychological assessments. In-vehicle sensors passively recorded driving behavior over 12 weeks. We identified 295,112 turns from vehicle heading changes. We used mixed-effects logistic regression to model the odds of turning left, with cognitive status category change from baseline to one-year follow-up as the predictor. Greater cognitive impairment, represented by movement to a more severe cognitive status category at one-year follow-up, was associated with reduced odds of turning left (odds ratio = 0.984, 95% confidence interval = 0.969-0.999; P value = .037). Left-turn avoidance may be a behavioral marker of early cognitive decline. Passive driving data could help detect functional changes, enabling intervention to preserve mobility and independence. Further research is needed to establish a clinical threshold of concern for decreasing trends in left turn frequency in older drivers.

Purpose: To evaluate the intra- and inter-grader concordance of anterior segment optical coherence tomography (ASOCT) grading for detection of endothelial plaque in microbial keratitis, and to compare endothelial plaque detection via ASOCT grading versus in-person slit lamp examination.

Methods: Diagnostic concordance study of 150 consecutive patients with microbiologically confirmed bacterial or fungal keratitis at a high-volume tertiary eye hospital in India. Two masked ophthalmologist graders independently evaluated ASOCT images for presence of two morphologically distinct endothelial plaque subtypes noted during image review (round and flat plaques). We assessed intra-grader and inter-grader concordance for each endothelial plaque morphology and for presence of either morphology. Diagnostic agreement between ASOCT and in-person slit lamp examination was evaluated using percent agreement, Cohen's kappa, sensitivity, and specificity. Univariable and multivariable logistic regression was used to assess odds of disagreement between ASOCT and slit lamp examination for endothelial plaque detection.

Results: ASOCT detection showed near perfect inter-grader agreement for round endothelial plaques (kappa 0.88, 94.7% agreement), flat endothelial plaques (kappa 0.84, 92.0% agreement), and either plaque (kappa 0.88, 94.0% agreement). Intra-grader agreement was substantial to near perfect for both graders across all plaque types (kappa 0.70-0.86). Ophthalmologist slit lamp examination identified endothelial plaque in 6.0% eyes, while ASOCT detected round plaques in 32.7%, flat plaques in 43.3%, and either plaque in 55.3% of eyes. Using ASOCT as reference, slit lamp examination demonstrated sensitivity of 16.3% for round plaques, 6.2% for flat plaques, and 9.6% for either plaque, with specificity exceeding 94% for all. Poor visual acuity (logMAR ≥1.0) was associated with increased disagreement for round plaques (adjusted OR 5.04), flat plaques (adjusted OR 3.63), and either plaque (adjusted OR 3.98). Bacterial infection was associated with increased disagreement for any endothelial plaque (adjusted OR 4.56).

Conclusion: Slit lamp examination substantially under-detects endothelial plaque compared to ASOCT, while ASOCT enables reproducible detection with excellent intra- and inter-grader agreement. These findings support incorporation of ASOCT imaging into microbial keratitis evaluation protocols. Differences in round and flat endothelial plaque morphologies warrant further investigation.

Child maltreatment is a pervasive problem leading to increased morbidity and mortality across the lifespan, potentially propagated by DNA methylation (DNAm) changes. We conducted an EWAS meta-analysis (n=175, 554,979 Illumina EPICv1/EPICv2 sites) in buccal swabs from three hospital-based studies of young children with traumatic injuries, stratified by study group to include 1) any traumatic injury, 2) fractures, and 3) traumatic brain injuries. Empirical bayes-moderated linear models tested differential DNAm with M-values. We identified abuse-associated pathways with rank-based promoter gene set enrichment analysis. Abuse was associated with methylation at 11 sites (false-discovery q<0.10), including enhancers of neuroblast differentiation-associated AHNAK and the immunomodulators SCGB1A1 and CCL26 as well as exon 5 of LAMP1 , essential for lysosomal function and cytotoxicity. Several of the most enriched biological processes included injury-affected cranial skeletal system and connective tissue development, neural structure and function, immune regulation, gene expression regulation, and metabolism. Our findings suggest that early-life abuse may epigenetically affect both proximal injury responses and longer-lived systemic biological dysregulation.

Background: Early low-level alcohol use predicts subsequent alcohol use and problems. Impulsivity and poor inhibitory control also predict later problematic alcohol use. However, few studies prospectively examine early sipping in combination with modeling impulsivity and inhibitory control change over time as predictors of adolescent alcohol use.

Methods: Data Release 6.0 from the Adolescent Brain Cognitive Development (ABCD) Study was used (n=11,866; 48% Female). A series of linear mixed-effect models examined trajectories of non-religious sipping at baseline (ages 9-10) and self-reported impulsivity (UPPS-P) and task-based inhibitory control (Flanker task) over time as predictors of past year drinks and problematic alcohol use by ages 15-16. Predictors were run as separate models and a full model with all predictors together. Models were nested within the participant and study site. Interactions with age (to measure change over time from Baseline to Year 6) were included. Corrections for multiple comparisons were employed.

Results: In individual models, four impulsivity interactions were significant: (1) negative urgency*age (β=.04, FDR- p <.001), (2) positive urgency*age (β=.04, FDR- p <.001), (3) lack of planning*age (β=.04, FDR- p <.001), and (4) sensation seeking*age (β=.04, FDR- p <.001), suggesting that as age increases, the relationship between impulsivity and alcohol use strengthens. Sipping*age (β=.02, FDR- p <.001) interactions also predicted standard drinks. Regarding problematic use, there was a significant interaction in the full model: negative urgency*age (β=-.07, p =.05), indicating that this relationship is more pronounced at earlier ages.

Conclusions: Trait impulsivity and sipping in late childhood relate to future alcohol use, and the relationship strengthens with age. Our results found a negative interaction between negative urgency and age on problematic use, potentially indicating negative urgency as a phenotype of vulnerability to experiencing alcohol related problems at younger ages. Findings indicate the importance of understanding facets of impulsivity in the context of adolescent alcohol use for prevention and intervention efforts.

Plant-based dietary strategies may offer a tractable approach to mitigating microbiome disruption and improving outcomes in patients undergoing autologous hematopoietic cell transplantation (auto-HCT) for multiple myeloma, a population in whom intestinal dysbiosis has been linked to infectious complications and inferior survival. We conducted a single-arm study to test the feasibility and biological activity of a high-fiber, plant-based, whole-food meal delivery intervention during the peri-transplant period. Adults with multiple myeloma (n = 22) received fully prepared, plant-based meals for 5 weeks spanning conditioning, neutropenia, and early recovery, with the goal of supporting consumption of nutrient-dense, high-fiber foods despite transplant-related symptoms that often limit oral intake. The primary endpoints were feasibility and tolerability, defined by successful enrollment, adherence to study procedures, and patient-reported intake of study meals; diet was quantified using prospective food diaries and 24-hour dietary recall surveys. Secondary endpoints included changes in gut microbiome composition and function assessed by shotgun metagenomic sequencing and stool short-chain fatty acid (SCFA) measurements. The intervention was feasible and generally well tolerated, with all participants consuming at least some proportion of delivered meals and with adherence sufficient to support planned dietary and correlative analyses. Greater intake of study meals was associated with more pronounced shifts in gut microbial communities, including enrichment of SCFA-producing taxa and compositional changes consistent with a fiber-responsive microbiome. Stool SCFA concentrations increased from baseline to the end of the intervention, suggesting a functional impact of the dietary strategy on microbial metabolite production during the peri-transplant period. These findings demonstrate that a plant-based meal delivery intervention is implementable during auto-HCT and suggest dose-dependent modulation of the gut microbiome and its metabolic output. Larger randomized trials are warranted to determine whether microbiome-targeted nutrition can reduce transplant-related toxicities, enhance immune recovery, and improve disease control in multiple myeloma. The trial is registered at ClinicalTrials.gov ( NCT06559709 ).

Chronic kidney disease (CKD) affects nearly 850 million individuals globally; the prevalence of undiagnosed CKD is 60%. Taking advantage of the relationship between CKD and cardiovascular disease, we developed a deep learning (DL) model to detect CKD from parasternal long-axis (PLAX) videos using 325,377 PLAX videos from 62,818 patients at Cedars-Sinai Medical Center (CSMC). We externally validated our model in two independent cohorts of 2,224 patients at Stanford Healthcare (SHC) and 41,611 patients at Kaiser-Permanente Northern California (KPNC). In a held-out test cohort at CSMC, our model detected any stage of CKD with an area under the curve (AUC) of 0.756 [95% confidence interval 0.749 - 0.763], with consistently strong performance in KPNC (AUC 0.718 [0.714 - 0.723]) and SHC (AUC 0.719 [0.704 - 0.735]). Our DL echo model detected CKD with robust performance at two external clinical sites, offering an avenue for noninvasive screening and improved detection rates.