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Purpose: To determine whether significant changes in best-corrected visual acuity (BCVA) precede or coincide with increases in central retinal thickness (CRT) in diabetic macular edema (DME) during a treat-and-extend (T&E) regimen following initial edema resolution.

Methods: This post-hoc analysis included 60 eyes (60 participants) from the READ-3 clinical trial that achieved CRT <250 µm and were followed until edema recurrence. Following a six-month ranibizumab loading phase, patients were monitored through 24 months with as-needed retreatment. Significant changes were defined as ≥4 Early Treatment Diabetic Retinopathy Study (ETDRS) letters and ≥30 µm on time-domain optical coherence tomography (TD-OCT). The temporal relationship between functional (BCVA) and anatomical (CRT) changes was analyzed.

Results: Median time to edema resolution was 10 months (IQR: 6-16) and to recurrence was 3 months (IQR: 2-3). 52 eyes (86.7%) had functional worsening and 43 (71.7%) had anatomical worsening. In 39 eyes exhibiting both types of deterioration, changes were concurrent in 24 (61.5%). Vision loss preceded anatomical recurrence (BCVA-led) in 23.1% of eyes, with a lead time of 1-4 months. Conversely, anatomical thickening preceded vision loss (OCT-led) in 15.4% of eyes, by a maximum of 2 months.

Conclusions: BCVA fluctuations frequently mirror CRT changes and can precede structural relapse, suggesting that BCVA is a sensitive indicator of DME activity. In resource-limited settings, BCVA may allow for earlier detection of recurrence than OCT alone.

Translational relevance: Functional vision loss can precede structural edema recurrence, supporting the potential for home-based BCVA monitoring as a validated bridge for timely clinical intervention in DME.

To evaluate the impact of sex on acute SARS-CoV-2 infection, 668 participants from the ACTIV-2/A5401 study were followed over a 28-day period. A primary analysis was performed on the 469 participants who had quantifiable viral loads at baseline. Male and female participants had comparable nasal SARS-CoV-2 RNA levels at study entry and throughout follow-up. However, sex-specific differences in viral shedding emerged when stratified by duration of symptoms. In the first three days from symptom onset, female participants exhibited higher nasal SARS-CoV-2 RNA levels than males, but lower viral RNA levels thereafter. The higher viral RNA levels in females during the earliest phase of acute COVID-19 was seen even after adjusting for age, race and region of enrollment. Female participants also tended to have higher symptom scores across days since symptom onset but no significant correlation was observed between nasal SARS-CoV-2 RNA levels and symptom score regardless of sex. These findings highlight the impact of sex on both viral shedding and symptom dynamics and underscore the importance of considering time since symptom onset when evaluating respiratory virus antiviral therapies in clinical trials.

In death certificates Entity Axis reflects reported death causes in their original order, and Record Axis reflects standardized re-classifications processed with expert rules. Additionally, while conventional mortality statistics consider a single underlying cause ignoring multiple contributing conditions, weighting schemes may consider all listed causes. We evaluated the impact of re-classification and weighting schemes across all 56,986,831 US death certificates from 2003-2023. ICD-10 codes were mapped to 14 broad disease categories. We recorded the frequency of changes and concordance in reported underlying cause of death between Entity and Record Axes. We considered weighting schemes for attributing mortality burden with Record Axis data: W1 (50% weight to underlying cause, 50% distributed equally among contributing causes), W2 (equal weighting across all causes) and W2A (equal weighting across all causes at ICD-10 level). Entity and Record Axes agreed on underlying cause category in 84.8% and on specific ICD-10 code in 68.9%. Reclassification from Entity Axis to Record Axis markedly increased COVID-19 (+92%) and Transport (+44%) and markedly decreased deaths from Other External Causes (-54%). Weighting schemes substantially altered death burden attribution: e.g. they reduced COVID-19 (-44-63%) and Falls (-46-66%), and changes tended to be more prominent with W2 and W2A than with W1 weighting. Weighting brought death counts per disease category closer to the Entity Axis. Weighting also restored Respiratory seasonality patterns. Systematic differences between reported and re-classified causes of death and weighting schemes for multiple causes profoundly change some disease burden estimates with major implications for resource allocation and public health priorities.

Significance statement: Standardized re-classification processes using expert rules recast the selected causes of death in many death certificates. Moreover, vital statistics typically isolate a single underlying cause, while for many deaths multiple causes jointly lead to demise. Analysis of ∼57 million deaths in the USA (2003-2023) shows that a large proportion of deaths are re-classified by expert rules to different causes than those filled by original certifiers. Analyses that give weight not only the recorded underlying cause but also the other listed causes lead to markedly different estimates of deaths from several diseases. For example, the footprint of COVID-19 fatalities during the pandemic years decreases by 44-63%. Re-classification and weighting schemes may have profound impact on disease burden estimates and policy decisions.

Background: Gastrointestinal stromal tumor (GIST) is the most common gastrointestinal mesenchymal tumor, driven by tyrosine-protein kinase KIT and platelet-derived growth factor receptor A (PDGFRA) mutations. Specific variants, such as KIT exon 11 deletions, carry prognostic and therapeutic implications, whereas wild-type (WT) variants derive limited benefit from tyrosine kinase inhibitors (TKIs). Given the limited reproducibility of established clinicopathological risk models, deep learning (DL) applied to whole-slide images (WSIs) emerged as a promising tool for molecular classification and prognostic assessment.

Patients and methods: We analyzed 8398 GIST cases from 21 centers in 7 countries, including 7238 with molecular data and 2638 with clinical follow-up. DL models were trained on WSIs to predict mutations, treatment sensitivity, and recurrence-free survival (RFS).

Results: DL predicted mutational status in GIST from WSIs, with area under the curve (AUC) of 0.87 for KIT , 0.96 for PDGFRA . High performance was observed for subtypes, including KIT exon 11 delinss 557-558 (0.67) and PDGFRA exon 18 D842V (0.93). For therapeutic categories, performance reached 0.84 for avapritinib sensitivity, 0.81 for imatinib sensitivity. DL models predicted RFS, with hazard-ratios (HR) of 8.44 (95%CI 6.14-11.61) in the overall cohort and 4.74 (95%CI 3.34-6.74) in patients receiving adjuvant therapy. Prognostic performance was comparable to pathology-based scores, with highest discrimination in the overall cohort and in patients without adjuvant therapy (9.44, 95%CI (5.87-15.20)).

Conclusion: DL applied to WSIs enables prediction of molecular alterations, treatment sensitivity, and RFS in GIST, performing comparably to established risk scores across international cohorts, providing a baseline for future multimodal predictors.

Highlights: Deep learning on histology predicts KIT and PDGFRA mutations in a large international cohort of GISTs from multiple centers Whole-slide image models stratify recurrence-free survival comparable to pathology-based risk scores Prognostic value of deep learning is preserved in adjuvant therapy subgroups, supporting treatment duration decisions.

The exposome factors, such as diet, lifestyle, microbiome, chemical exposures and social exposome, shapes human health beyond genetic influences, but the mechanisms remain only partially understood. Leveraging the Area Deprivation Index (ADI) of Neighborhood Atlas, a validated measure of the US social exposome, we derive molecular insights on how adverse social exposome (ASE) may impact cardiometabolic and brain health. Using complementary metabolomics platforms, we measured blood metabolome as readouts on net influences of exposome factors. Participants from six Alzheimer's disease research centers (n=449) were studied with generalizability confirmed in the UK Biobank using its harmonizable metric for ASE (n=380,943). Our results suggest that participants living in ASE have metabolic features often shown to predispose individuals to higher risks for cardiovascular diseases and cognitive decline, with impaired mitochondrial energetics, amino acid and lipid metabolism. Diet, microbiome and chemical exposures may contribute to these metabolic features. Molecular insights from metabolic signatures for ASE allows us to map potential modifiable risk factors that can impact and sustain health including brain health.

Aim: We investigated the heterogeneity of treatment effects in transcranial direct current stimulation (tDCS) with mindfulness-based meditation (MBM) and within each individual study group (tDCS alone, MBM alone, and sham) among individuals with symptomatic knee osteoarthritis. We also explored participant characteristics underlying this heterogeneity.

Methods: This secondary analysis drew on a double-blind, randomized, sham-controlled, phase II, parallel-group trial in which 200 participants were assigned to one of four groups: (1) active tDCS + active MBM, (2) active tDCS + sham MBM, (3) sham tDCS + active MBM, or (4) sham tDCS + sham MBM. Participants received ten 20-minute tDCS sessions (active or sham) administered concurrently with MBM (active or sham). Latent class growth analysis was used to identify subgroups with distinct treatment response trajectories (responders vs. non-responders) based on changes in clinical pain (Numeric Rating Scale) from baseline to post-intervention. Generalized linear models were then applied to determine baseline factors associated with participants' response classification, including demographic, clinical, and psychological characteristics; quantitative sensory testing battery; and pain-related cortical hemodynamic activity measured using functional near-infrared spectroscopy (fNIRS) in response to punctate and thermal stimuli.

Results: Responders in the active tDCS + active MBM and active tDCS + sham MBM groups demonstrated greater improvements in clinical pain from baseline to post-intervention than non-responders ( p < 0.001). In the active tDCS + active MBM group, greater cortical activation in the fNIRS channel S06-D06 of the left somatosensory cortex in response to punctate stimuli, identifying as white, and lower conditioned pain modulation (reflecting less efficient endogenous pain modulation), were significantly associated with being responders ( p < 0.05). In the active tDCS + sham MBM group, younger age and lower heat pain tolerance at the knee were significantly associated with being responders ( p < 0.05). No clear response patterns were observed in the remaining groups.

Conclusion: Factors underlying heterogeneity of treatment effects, including somatosensory cortical activation and pain modulatory profiles, may provide preliminary insights to inform the development of personalized neuromodulation (stimulation) protocols.

There is no readily accessible, scalable cure for HIV infection. Trials of HIV-specific broadly neutralising antibodies (bNAbs) demonstrate inhibition of viral replication and reduction of the reservoir of latently-infected cells, potentially offering new strategies for HIV eradication. Animal and human studies suggest bNAbs have multiple activities, including a direct antiviral action and a secondary induction of T cell responses, the 'vaccinal effect'. The RIO trial assessed HIV-specific cell-mediated immunity after dosing with two long-acting bNAbs (10-1074-LS and 3BNC117-LS) in people treated with antiretroviral therapy (ART) since early stage HIV followed by treatment interruption. BNAbs resulted in sustained viral suppression with 75% of participants controlling off ART after 20 weeks. Here we show that HIV-specific T cell immunity was enhanced for at least 36 weeks after bNAbs in aviraemic participants. Gag-specific T cell immune responses predicted virological outcomes. Baseline CD8+ AIM responses predicted longer times to rebound; baseline CD8+ proliferative responses were additionally protective in participants without baseline bNAb resistance mutations. Baseline ELISpot responses were associated with faster rebound. These data highlight the complex interplay between bNAbs and T cells, identify a post-bNAb protective T cell-driven vaccinal effect, and reinforce the role of immune-based interventions as part of HIV cure strategies.

Background: Guideline-directed medical therapy (GDMT) has been shown to improve mortality and/or symptoms in heart failure with reduced ejection fraction (HFrEF). Medical devices also play an important role in improved quality of life and overall symptom relief for HFrEF patients. Baroreflex Activation Therapy (BAT) increases parasympathetic nervous system activity by stimulating the carotid baroreceptors, thereby reducing symptoms. Herein, we analyzed the effects of BAT on hospitalization, atrial arrhythmia (AA), and ventricular arrhythmia (VA) rates.

Methods: A retrospective cohort study was conducted consisting of HFrEF patients treated with BAT at Keck Hospital of USC between 11/2014 and 11/2022. We compared median pre-BAT hospitalization, AA, and VA rates to post-BAT rates at both 6- and 12-months using Wilcoxon Signed Rank tests.

Results: Among 31 patients on BAT, 38.7% met criteria for receiving all four GDMT classes for at least 12 months prior to BAT. Among these, 91.7% had an implantable cardioverter defibrillator (ICD) implanted for ≥12 months pre- and post-BAT. Average pre- vs. post-BAT all-cause hospitalization rates were significantly different only at 12 months [1.3 ± 1.4 vs 0.3 ± 0.9, respectively (p=0.05)]. Borderline significant pre-post comparisons were noted including decreased VA rate at both 6 and 12 months and increased AA rate at 12-months (p=0.06 for all).

Conclusion: In HFrEF patients on full GDMT, BAT was associated with a significant reduction in hospitalization rates at 12 months. There were no significant changes in AA or VA rates.

Interpreting brain structure at the individual level remains a major challenge in neuroimaging, as population variability across age and sex limits the clinical utility of group-level findings. Here, we develop large-scale normative models of regional cortical and subcortical brain volumes from more than 62,000 healthy individuals across the lifespan and apply them to multiple sclerosis (MS) to enable individualised, reference-based assessments of grey matter morphology. We identify a temporally stable yet heterogeneous morphometric phenotype of MS, expressed as concordant deviations from age- and sex-adjusted reference values. Individual deviation profiles are clinically informative: both the magnitude and cumulative burden of lower-than-reference volumes are associated with disability cross-sectionally and longitudinally. Moreover, the profiles can be translated into interpretable stratification rules linked to disability trajectories and relapse dynamics. This work reframes known structural abnormalities into stable, individual-level deviation profiles, demonstrating how normative modelling can move neuroimaging beyond group averages toward clinically interpretable inference. Together, these findings establish a generalisable framework for translating population-level neuroimaging data into individual-level phenotypes with potential beyond multiple sclerosis.