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Automated Text Message Outreach to Increase Diabetes Screening: A Pragmatic Randomized Trial

Background Despite evidence that early intervention can prevent or delay progression to type 2 diabetes, more than 80% of individuals with prediabetes in the United States remain undiagnosed, underscoring the need for scalable strategies to increase uptake. In this study, we evaluated whether a single text message could increase completion of HbA1c-based diabetes screening in routine clinical practice. Methods We conducted a pragmatic randomized controlled trial within Duke University Health System (DUHS). Patients aged 35 years or older who met American Diabetes Association 2022 screening criteria, had no previous diagnosis of diabetes, had not undergone HbA1c testing within the preceding 3 years, and had opted to receive text messages from DUHS were randomly assigned to receive either a single text message encouraging guideline-based diabetes screening and discussion with a primary care provider (intervention group; n=55,494) or usual care (control group; n=5,748). The primary outcome was HbA1c test completion within 24 weeks following message delivery (or no message for controls), analyzed using a Cox proportional hazards model stratified by wave. Secondary outcomes included piecewise hazard ratios for early (weeks 1-4), mid (weeks 5-12), and late (weeks 13-24) intervals and the between-group difference in cumulative testing rate. Findings Text message outreach significantly increased HbA1c test completion over 24 weeks (HR, 1.18 [95% CI, 1.07-1.03]) with the strongest effect in the first four weeks (HR, 1.48 [95% CI, 1.18-1.86]). By the end of the 24-week observation period, cumulative testing reached 9.14% in the messaged group vs 7.83% in controls (between-group difference, 1.31% [95% CI, 0.59-2.07]), corresponding to one additional HbA1c test per 76 messages delivered ($0.51 in messaging costs per additional HbA1c test performed). Rates of prediabetes and diabetes among those screened were similar between groups, indicating no selection bias of higher-risk patients. One additional dysglycemia case was identified per 213 messages sent ($1.43 per case detected).

Atlas of glomerular disease-specific genetic effects on blood transcriptome

IgA nephropathy (IgAN), IgA vasculitis (IgAV), focal segmental glomerulosclerosis (FSGS), membranous nephropathy (MN), and minimal change disease (MCD) account for the majority of idiopathic glomerulo-nephropathies (GN). These disorders involve immune system dysregulation and have a complex genetic architecture. Currently, there are no adequately powered blood transcriptomic datasets coupled to genetic data from patients with GN that can delineate disease-context specific genetic effects on blood immune cell transcriptome. We performed whole genome sequencing coupled with bulk blood transcriptome sequencing on 1,822 participants from the CureGN study, a prospective cohort of participants with a kidney biopsy diagnosis of primary GN. We generated disease-context specific transcriptome-wide maps of gene expression QTL (eQTL), splicing QTL (sQTL), and double strand RNA-editing QTL (edQTL) for FSGS (N=447), IgAN (N=403), IgAV (N=123), MCD (N=408), and MN (N=441), as well as cross-disease maps for all 1,822 participants. Our QTL mapping identified 16,068 eGenes, 4,644 sGenes and 4,611 edQTLs with an FDR

The clinical utility of functional testing in fibroblasts to diagnose primary mitochondrial disease

Genome sequencing of the heterogeneous primary mitochondrial disorders (PMD) frequently reveals variants of uncertain significance that require functional tests for diagnosis, and does not identify variants in all patients. We analyzed mitochondrial enzyme assays, blue native polyacrylamide gel electrophoresis (BN-PAGE) with in-gel activity staining, complex I assembly blot, and select protein abundances in fibroblasts of a case series of 204 PMD patients divided into functional classes, in comparison to 51 controls and 53 differential diagnostic conditions. Overall, sensitivity and specificity for respiratory chain enzyme assays were 46% and 93% respectively, for BN-PAGE 40% and 98%, for complex I assembly assay 49% and 99%. The overall sensitivity of all tests was 76%, specificity 93%, with positive predictive value 96% and negative predictive value 67%. Categories with high sensitivity were isolated complex deficiencies, nuclear DNA-encoded mitochondrial protein synthesis defects, co-factor defects, and mitochondrial amino-acyl-tRNA synthetase conditions when aided by protein abundance. Mitochondrial DNA mutations and maintenance disorders showed poor sensitivities. Secondary dysfunctions were rare. A complete battery of functional tests showed strong diagnostic clinical utility in fibroblasts.

An Approach to Simultaneous Acquisition of Real-Time MRI Video, EEG, and Surface EMG for Articulatory, Brain, and Muscle Activity During Speech Production

Speech production is a complex process spanning neural planning, motor control, muscle activation, and articulatory kinematics. While the acoustic speech signal is the most accessible product of the speech production act, it does not directly reveal its causal neurophysiological substrates. We present the first simultaneous acquisition of real-time (dynamic) MRI, EEG, and surface EMG, capturing several key aspects of the speech production chain: brain signals, muscle activations, and articulatory movements. This multimodal acquisition paradigm presents substantial technical challenges, including MRI-induced electromagnetic interference and myogenic artifacts. To mitigate these, we introduce an artifact suppression pipeline tailored to this tri-modal setting. Once fully developed, this framework is poised to offer an unprecedented window into speech neuroscience and insights leading to brain-computer interface advances. The source code and data are available.