BioTechniques

High-phenolic plant genera present a major technical limitation in genomic research. Standard extraction approaches that perform reliably across diverse flora often perform poorly when applied to recalcitrant taxa, producing low DNA yield and integrity incompatible with sequencing requirements. The genus Anigozanthos (Kangaroo paws) from the family Haemodoraceae exemplifies this problem. We identified key physicochemical factors governing extraction failure in this genus and resolved them through targeted modifications to lysis chemistry and contaminant management. The resulting protocol achieved a near threefold improvement in DNA purity, substantially reducing contaminant carry over and consistently yielded high-integrity, long DNA fragments (DIN > 7) across a diverse sample set spanning cultivated and wild material across four diverse genera of Haemodoraceae. We also tested a straightforward purity assessment framework that can be implemented in any standard molecular laboratory, enabling rapid pre-submission quality assessment without the need for specialised equipment. Together these advances open a practical path to genomic characterisation of Anigozanthos that establishes a transferable model for genomic research across Australia ' s chemically complex native flora.

Pancreatic ductal adenocarcinoma (PDAC) harbors a distinct intratumoral microbiome. Yet rigorous characterization of its composition is hampered by pervasive environmental and procedural contamination. Sources of contamination have not been thoroughly explored, and the methods of decontamination have not been sufficiently evaluated in a benchmarking manner. We systematically collected >300 negative control (NCT) samples comprising paraffin from formalin-fixed paraffin-embedded (FFPE) samples, lysis buffer and sterile water over a period of four years processed by different laboratory persons (LP). All samples were sequenced using full-length 16S rRNA gene sequencing with Oxford-Nanopore Technologies. We benchmarked four decontamination methods (restrictive filtering, decontam, SCRuB, and the Nejman et al.-derived (Nj) pipeline) against fresh-frozen tumor samples (FF) from LSL-KrasG12D/+;LSL-Trp53R172H/+;Pdx-1-Cre (KPC) mice, using the abovementioned contamination assessment to calculate a composite score for the assessment. Further, we validated those methods via technical replicates. Microbial profiles of NCT samples were significantly determined by control type, LP, year and season reflecting complex batch effects. The 15 most abundant contaminants spanned well-characterized environmental taxa and human commensals from the oral cavity. The LP processing samples left a significant microbial trace highly contributing to the batch effect. Decontamination benchmarking demonstrated that the Nj method consistently outperformed alternatives in both composite score and inter-replicate concordance. Application of Nj to fresh frozen PDAC samples substantially reduced contaminant burden while preserving putative tumor-associated signals in FF but not FFPE samples. Our results support the adoption of the Nj decontamination approach for future intratumoral microbiome studies in fresh frozen tumor samples.

Botulinum neurotoxins (BoNTs) comprise a highly diverse group of seven serotypes (from A-G) and over 40 subtypes worldwide. Previous primer- and probe-based nucleic acid amplification tests (NAATs) for detection of BoNT encoding genes are challenged by high levels of nucleotide polymorphism both across and within subtypes. In this study, multiple BoNT gene sequences were aligned to identify highly conserved regions for the design of new primers that enable the detection of all seven serotypes under the same conditions. Specific primer sets were designed and validated using in silico, conventional and real-time PCR with constructed plasmids carrying the target fragments and spiked food matrices. The established procedure achieved highly specific and sensitive detection of BoNT serotypes A-G with sensitivity of 10 copies/reaction and a total turnaround time of approximately 1.5 hours. The procedure also eliminated the carryover PCR product by using uracil-N-glycosylase in combination with dUTP in the assay reaction mix. This study provides an alternative NAAT with higher coverage and compliments the traditional mouse bioassays in enhancing global botulism surveillance capabilities.

The binding affinities of a chimeric analog of a riboflavin derivative linked to biotin, (6- (7,8-dimethyl-2,4-dioxo-3,4-dihydrobenzo[g]pteridin-10(2H)-yl)hexyl 5-((3aS,4S,6aR)-2- oxohexahydro-1H-thieno[3,4-d]imidazol-4-yl)pentanoate), referred to as C6-Rf-biotin-tag, to the riboflavin binding retain or streptavidin are in the M range, 1.29 {+/-} 0.277 and 3.00 {+/-} 0.459, respectively. These values suggest that C6-Rf-biotin-tag has potential applications in diagnostic assay and labelling target flavin binding proteins. The C6-Rf-biotin-tag which was characterized with respect to physical and biochemical properties retains UV/Vis spectroscopic and fluorescence behavior similar to riboflavin.

Hybridoma screening in semi-solid medium typically employs antigens labeled with visible fluorophores (e.g., FITC, AF488) to enable single-step identification of antibody-secreting clones. However, conventional chemical conjugation via NHS-esters or isothiocyanate groups frequently modifies lysine residues located within epitopes, potentially abrogating antibody recognition of these critical regions. Here, we describe a SpyTag SpyCatcher-based site-specific labeling strategy that circumvents epitope damage during semi-solid medium screening. A 16-amino-acid SpyTag was genetically fused to the C-terminus of the target antigen, enabling covalent conjugation to an sfGFP SpyCatcher fluorescent probe. In semi-solid medium supplemented with SpyTag-antigen and sfGFPSpyCatcher, positive hybridoma clones were readily identified by distinct fluorescent halos, whereas negative clones showed no detectable signal. Notably, the site-specific method yielded a significantly higher frequency of fluorescence-positive clones compared to the conventional AF488-labeled antigen method, suggesting that epitope preservation enhances screening recovery. Furthermore, this approach did not impair hybridoma growth or final clone positivity, offering a simple, rapid, and epitope-compatible method for monoclonal antibody screening.

The Bacillus cereus group comprises bacteria of biotechnological interest, but also raises health concerns. Some bacteria in this group are opportunistic human pathogens, mainly causing foodborne gastrointestinal infections. As of today, the presence, sequence variability, or expression of genes encoding toxins or other virulence factors are insufficient to predict the potential of a given isolate to cause the diarrheal form of the disease. To address this limitation, we developed a sandwich ELISA to quantify the NheA and Sphingomyelinase (SMase) proteins in culture supernatants to test them as markers of pathogenic potential. Application of the assay to a collection of B. cereus group isolates revealed that strains associated with food poisoning outbreaks produce significantly more NheA and SMase than those isolated from the environment or from commercial products. Statistical analyses show that the combined quantification of NheA and SMase provides robust discrimination between pathogenic and non-pathogenic (environmental and commercial) profiles. These results demonstrate that the quantitative assessment of both NheA and SMase production can serve as a reliable biomarker for distinguishing diarrheic food poisoning isolates from harmless strains.

Amplicon sequencing of the 16S rRNA gene is the most widely used approach for profiling bacterial communities, but its taxonomic resolution is typically limited to the genus level. Many species carry multiple divergent 16S rRNA alleles that overlap across species boundaries, an ambiguity that even full-length, long-read sequencing cannot fully resolve. Shotgun metagenomics achieves species-level resolution but remains costly, particularly when only a single genus is of interest. Amplicon sequencing of rapidly evolving, protein-coding housekeeping genes offers a cost-effective alternative, yet no tool exists to identify suitable primer sets for a given target taxon. Here we present AmPair, a Snakemake pipeline that, given a target genus and one or more candidate housekeeping genes, designs and ranks primer pairs binding conserved regions while flanking a variable region capable of species-level discrimination, and validates them in silico across all available genomes. Using the genus Bacillus and the housekeeping gene tuf as a case study, the primer set recommended by AmPair amplified 99% of 2,392 genomes; only 0.04% carried multiple alleles and none showed inter-species allele overlap, compared with 91.41% and 69.49%, respectively, for the standard 16S rRNA V1-V9 region. Applied to a Bacillus community profiled by Nanopore sequencing, the same primers resolved closely related species. AmPair thus offers a generalizable and accessible route to species-level community profiling.

Diatoms are major contributors to marine primary production, yet current approaches for monitoring their abundance and function rely on coarse satellite chlorophyll estimates or sparse cell count and carbon fixation measurements. Molecular markers are a promising approach for high-resolution measurement of both abundance and metabolic activity through analysis of environmental DNA (eDNA) and RNA (eRNA). We present an isothermal quantitative recombinase polymerase amplification (qRPA) assay targeting rbcL gene copies and transcripts of marine diatoms, operating at low temperature and producing results in less than 15 min. We demonstrate specificity and calibration across diverse diatom taxa, then apply the assay to eDNA and eRNA samples from the Mare Chiara Long-Term Ecological Research site in the Bay of Naples, Italy, alongside microscopy, chlorophyll, physicochemical, and carbon-fixation data. Diatom rbcL DNA tracked abundance across five orders of magnitude despite seasonal shifts in community composition. Combining molecular and optical data revealed increased cellular rbcL copies and chlorophyll in low-light winter populations, suggesting enhanced photosynthetic capacity despite lower abundance. Furthermore, rbcL RNA reflected total carbon fixation rates and identified populations with differing carbon fixation activity. These results support rapid, RPA-based rbcL quantification as a robust approach for biomolecular ocean observing.

Genome-wide coexpression analysis of intact tissue samples is a powerful approach for identifying reproducible signatures of cell types and states, since it can survey vast numbers of individuals, cells, and transcripts. However, it can be difficult to optimize gene coexpression network construction and compare results from independent analyses. To address these challenges, we developed OMICON (theomicon.ucsf.edu) for research on human brain gene coexpression networks. OMICON contains gene expression data from >17K normal and neoplastic human brain samples with standardized metadata. Systematic analysis of independent datasets identified >250K gene coexpression modules, which were characterized and compared via enrichment analysis with >40K gene sets. All modules are discoverable via an advanced search engine that can filter by genes, metadata, and enrichment results. Analyses can also be browsed with an interactive workflow visualization tool, and users can communicate within OMICON using @mention functionality to support communal research on human brain gene coexpression networks.

Background & Aims: Fatigue is a central symptom of chronic liver disease (CLD), substantially impacting health-related quality of life (HRQoL). This study aimed to further understand CLD symptomatology, including fatigue, and its impact on HRQoL from a patient perspective. Methods: Abbott Global Assessment of Patients unmet needs (aGAP) was a multinational, cross-sectional survey in adults with compensated CLD in China, India and Mexico, conducted between July and November 2024. Adult participants who self-reported that they had physician-diagnosed CLD and were experiencing fatigue completed a quantitative survey to assess symptom burden and included three HRQoL patient-reported outcome (PRO) questionnaires (Patient-Reported Outcomes Measurement Information System [PROMIS]-29+2, Work Productivity and Activity Impairment - Specific Health Problem version 2.0 [WPAI: SHP], Multidimensional Fatigue Inventory [MFI]). Results: Overall, 505 participants (China: 200; Mexico: 105; India: 200) completed the study. Participants reported that their CLD-related fatigue sometimes, often or always affected their self-esteem/confidence (45.1%) and ability to maintain or acquire new employment (38.6%). Most participants reported moderate (51.3%) or serious (26.9%) fatigue, with 33.5% experiencing fatigue every day or almost every day. Many participants felt their social life was negatively impacted by their fatigue (47.3%) and that there were related financial difficulties (53.9%). Use of validated PRO tools demonstrated severe fatigue (MFI: overall mean [SD] 13.9 [3.4] general fatigue and 13.4 [3.6] physical fatigue) as well as substantial levels of work and activity impairment (WPAI: SHP overall mean [SD] 53.0 [26.4]) and high levels of anxiety, pain interference, depression and sleep interference (PROMIS T-scores [≥]54). Conclusions: Fatigue has a substantial impact on HRQoL among adults with CLD across several countries, highlighting a global unmet need for targeted interventions to effectively identify and manage the condition.

Background: Consumer use of AI chatbots for health advice is rising, yet triage safety relative to established services remains unclear. Australia's Healthdirect, a government-backed symptom checker with 2.4 million uses in FY2024-25, remains unevaluated against frontier large language models (LLMs), and whether premium subscriptions improve triage safety remains unexplored. This study compared the triage accuracy and safety of Healthdirect against six LLM configurations across ChatGPT, Claude, and Gemini, assessed whether paid subscriptions improve triage safety, and characterised each system's error patterns. Methods: Forty-five clinical vignettes from the Semigran et al. benchmark spanning emergency, non-emergent, and self-care categories (15 each) were evaluated across seven systems. Healthdirect was tested following a seven-rule interaction protocol. LLMs were evaluated using first-person patient-language prompts under free-tier and paid-tier conditions. Outcomes were triage accuracy, emergency sensitivity, under-triage, and critical misses, analysed using Cochran's Q, Bonferroni-corrected McNemar tests, Cohen's kappa, and Wilson intervals. Findings: Triage accuracy differed significantly (Cochran's Q = 36.79, p < 0.001). Healthdirect achieved 48.9% accuracy (95% CI 35.0% to 63.0%; kappa = 0.233) versus 73.3% to 86.7% for LLMs (kappa = 0.600 to 0.800). Healthdirect operated under conservative interactive defaults while LLMs received complete information in a single prompt, which may have disadvantaged Healthdirect. Emergency sensitivity was 46.7% versus 80.0% to 86.7% for LLMs. Healthdirect produced two critical misses; no LLM produced any across 270 evaluations (95% CI 0% to 1.4%). When LLMs undertriaged, they recommended GP care rather than self-care. No tier differences were significant (all p > 0.05), and most systems over-triaged self-care cases. Interpretation: Frontier LLMs demonstrated higher triage accuracy and safer error profiles than Healthdirect. All LLMs avoided critical misses; Healthdirect did not. Premium subscriptions did not significantly improve triage safety. These findings support clinical governance decisions about whether LLMs warrant formal evaluation alongside government-backed symptom checkers.

Artificial intelligence applied to routine electrocardiograms (ECGs) has largely focused on detecting existing disease or predicting individual cardiovascular outcomes. Whether ECGs can support prediction of multiple future diseases across organ systems remains unclear. We developed ECG-RISK, a multitask survival model for 67 incident three-character ICD-10 endpoints using ECG waveforms, demographic characteristics and routinely collected laboratory data from 86,673 MIMIC-IV patients. Discrimination was highest for heart, brain, kidney and lung endpoints, with organ-level C-indices ranging from 0.796 to 0.825, whereas liver and pancreatic endpoints showed lower discrimination. The ECG-only model achieved strong discrimination across most endpoints, whereas the incremental improvement gained by incorporating ECG and laboratory inputs beyond demographic information varied substantially across endpoints. Across the nine exploratory aggregated outcomes, Kaplan Meier curves showed clear separation among model-score tertiles. Discrimination was highest for dementia (C-index, 0.891) and heart failure (C-index, 0.857). These findings support the feasibility of ECG-based longitudinal risk prediction across multiple diseases. External validation and competing-risk analyses are required to assess generalisability and clinical utility.

Objectives To evaluate whether access to a certified large language model (LLM)-based clinical decision support system improves physician diagnostic performance in rheumatology compared with conventional diagnostic resources alone. Methods In this multicentre, open-label, randomised controlled trial, 82 physicians from seven hospitals in two countries were randomised 1:1 to conventional diagnostic resources plus Prof. Valmed or conventional resources alone. Participants assessed three rheumatology vignettes before and after assistance. The primary outcome was top-1 diagnostic accuracy. Secondary outcomes included top-3 accuracy, diagnostic reasoning, confidence, case-processing time and perceived support quality. Results Top-1 accuracy increased from 22.2% to 33.3% in the intervention group and from 23.3% to 35.0% in the control group, with no between-group difference in improvement (adjusted OR 0.99, 95% CI 0.45 to 2.19; p=0.979). Differences in top-3 accuracy, diagnostic reasoning and confidence were also not significant. Assisted case-processing time was substantially shorter with LLM support (94 vs 206 s; adjusted mean difference -112 s, 95% CI -141 to -83; p<0.001). Information timeliness and perceived diagnostic support quality were rated significantly higher in the intervention group. Exploratory analyses showed persistent overconfidence and substantial AI over-reliance. Conclusions Certified LLM-based diagnostic support did not improve diagnostic accuracy compared with conventional resources, but substantially reduced case-processing time and improved perceived support quality. These findings suggest potential workflow benefits while highlighting overconfidence and over-reliance as important safety considerations.

Background Elexacaftor-tezacaftor-ivacaftor (ETI) has been demonstrated to improve lung function in clinical trials; however, evidence describing effects on trajectories and whether long-term improvements are sustained (>1-year) is lacking. We estimated within-person lung clearance index (LCI) trajectories before and after ETI initiation, assessing changes in level and rate of change, alongside acute LCI change, up to three years after ETI initiation. Methods Prospective observational study of children at a tertiary hospital. Children aged 3-17 years with [&ge;]2 LCI testing occasions (i) before and (ii) after starting ETI were used to describe lung function trajectories. Children with [&ge;]1 pre-ETI and [&ge;]1 post-ETI LCI occasion(s) were used to describe acute LCI change after ETI initiation. Age-adjusted LCI trajectories for time periods (i) before and (ii) after ETI initiation were estimated using linear mixed-effects models, and pre- and post-ETI LCIs were compared using paired Wilcoxon tests. Results Mean pre-ETI and post-ETI longitudinal changes in LCI were -0.007 (95% CI: -0.28, 0.27; n=35) and 0.12 (95% CI: -0.17, 0.41; n=20) turnovers per year, respectively. Before ETI initiation, 57% (30/53) of patients had an LCI[&ge;]7.1 turnovers (indicating impaired lung function), compared to 26% (14/53) post-ETI, with a median LCI difference of -0.70 (95% CI -0.84, -0.46; p<0.001) turnovers. Within-individual variability in LCI decreased post-ETI. Conclusions Our real-world data within a unique longitudinal study provide a comprehensive picture of ETI benefit by outlining not only acute improvement in LCI but maintained stability in LCI trajectories and improved LCI stability sustained up to three years post-initiation.

Purpose: To evaluate the safety, procedural performance, sample recovery, and surgeon preference of an ophthalmic needle designed specifically for anterior chamber (AC) paracentesis. Methods: In this multicenter study, AC paracentesis was performed in clinic and operating-room settings using a 32-gauge x 4-mm needle with low dead space. The procedure was evaluated using a standardized physician survey. Prespecified outcomes included procedure-related adverse events (primary outcome), needle entry and handling, aspiration and sample recovery, comparative performance versus a 30-gauge needle, and physician preference for future use. Results: A total of 110 needle uses by eight surgeons were included. No ocular complications occurred, including lens or iris injury, hyphema, AC collapse, wound leak, hypotony, infection, or retinal complication, and no procedure required needle exchange or conversion to another device. Two technical events without ocular sequelae were noted, in which needle entry was partial thickness and did not reach the AC (1.8%; exact 95% CI, 0.2%-6.4%). Physicians rated needle entry, handling and sample recovery as good or excellent. Compared with a 30-gauge needle, the study needle was rated as at least comparable across all assessed domains. All surgeons rated it better or much better for intra-procedural safety and preferred it for future AC taps. Conclusions and Relevance: This short, 32-gauge low-dead-space ophthalmic needle demonstrated a favorable safety profile and was preferred over a 30-gauge needle by all surgeons. As aqueous humor liquid biopsy expands in clinical diagnostics and trials, an ophthalmic-specific needle design may help improve the consistency and safety of aqueous humor collection for molecular analysis and broader clinical use. Keywords: Anterior chamber paracentesis; Aqueous humor; Liquid biopsy; Low dead space; Ophthalmic needle

Introduction: Polyendocrine metabolic ovarian syndrome (PMOS), formerly known as polycystic ovary syndrome (PCOS), is a common endocrine disorder affecting women of reproductive age. Besides reproductive and metabolic disturbances, PMOS negatively impacts psychological well-being and quality of life. Despite available treatment options, there remains a need for safe and effective therapies that improve both clinical symptoms and fertility outcomes. Aim: To compare the efficacy of VAMHA and MYRHA tablet combination therapy with standard non-hormonal therapy in restoring regular menstruation. Secondary objectives included assessment of ovulation, menstrual symptoms, polycystic ovarian morphology, hormonal and metabolic parameters, anthropometric measures, and skin manifestations. Study Design: Open-label, randomized, multicentre, prospective comparative clinical study. Methods: Seventy-one women with PMOS were randomized to Group A (n=37) or Group B (n=34). Group A received VAMHA and MYRHA tablets (2 tablets each), while Group B received Metformin 500 mg plus Myoinositol 600 mg (1 tablet), twice daily for 180 days. Data were recorded in Case Report Forms. Statistical Analysis: Continuous variables were summarized using mean and standard deviation, while categorical variables were expressed as frequencies and percentages. Appropriate statistical tests, including Chi-square, were used. A p-value [&le;]0.05 was considered significant. Results: Significantly more participants in Group A achieved regular menstrual cycles than Group B (31 vs. 22; p<0.05). Ovulation occurred in 16 participants in Group A compared with 6 in Group B (p<0.05). Both groups showed significant improvement in menstrual irregularity and related symptoms. Significant reductions in Anti-Mullerian Hormone (AMH), fasting insulin, and body mass index (BMI) were observed in both groups (p<0.05). Resolution of polycystic ovarian morphology occurred in 13 participants (38.23%) in Group A and 10 (33.33%) in Group B. Both treatments were well tolerated with no major safety concerns. Conclusions: VAMHA and MYRHA combination therapy was superior to standard non-hormonal therapy in improving menstrual regularity and ovulation. It also produced favourable metabolic, hormonal, and ultrasonographic outcomes, suggesting its potential as a safe and effective option for comprehensive PMOS management and fertility enhancement.

Objective: The Brief-cope questionnaire explore coping behavior. However, the underlying factor structure remains a subject of ongoing debate. Exploratory factor analyses (EFA) conducted across different populations have identified factor solutions ranging from two to fourteen factors. As of yet, the underlying factor structure of the Brief-cope has not been investigated in patients with seropositive rheumatoid arthritis (RA). Therefore, the aim of this study was to explore the underlying factor structure of the Brief-cope in a German population of seropositive RA. Methods: 216 outpatients with seropositive RA completed the Brief-cope. An EFA with principal axis factoring and Promax rotation was conducted. Results: EFA indicated a five-factor solution. The five-factor solution explained 51.95% of variance. The identified factors were: (1) problem-focused coping (Cronbach's = .851), (2) emotion-focused coping ( = .754), (3) maladaptive coping ( = .747), (4) religious coping ( = .851), and (5) substance-use coping ( = .869). Conclusion: A five-factor solution provided the most appropriate representation of the underlying factor structure of the Brief-cope in patients with seropositive RA. This factor structure may serve as a suitable basis for future analyses of Brief-cope data in comparable RA populations.

Background: Current understanding of acute kidney injury (AKI) risk factors remains largely descriptive, offering limited precision into how specific biomarker values or physiologic thresholds influence susceptibility. We aimed to synthesize knowledge from machine learning models trained across multiple health systems to identify generalizable, value-specific risk drivers and biomarker interactions contributing to AKI risk. Methods: We analyzed electronic health records (EHRs) from 785,497 adult inpatients between 2010 and 2019 across nine U.S. academic medical centers within PCORnet. Interpretable gradient boosting machine models were independently developed at each health system to quantify predictor-outcome associations. Meta-regression was applied to integrate these site-level results, characterize nonlinear value-risk relationships, and identify bivariate interactions between predictors. Results: Meta-analysis revealed consistent, value-specific risk drivers across health systems. An increase in glucose from 100 mg/dL to 140 mg/dL was associated with a 1.46-fold higher risk of AKI. Chloride and anion gap also demonstrated elevated AKI risk with risk increases overlapping portions of their reference ranges, with anion gap showing a 1.14-fold increase across 4-12 mmol/L and chloride a 1.28-fold increase across 96-100 mEq/L. Electrolytes including potassium, calcium, and sodium showed quadratic associations with AKI risk. Bivariate meta-regression identified interactions between key predictors, highlighting pathways that jointly modulate AKI risk. Conclusion: This cross-system meta-analysis synthesizes machine learning-derived evidence into clinically interpretable knowledge, revealing how specific biomarker ranges and interactions modulate AKI risk. By moving beyond surface-level associations to quantitative, generalizable physiologic thresholds, these findings provide actionable insights to enhance risk stratification and personalized prevention in hospital care.

Background: Stress research in nursing education has largely focused on distress, stressors, and negative outcomes, although challenging experiences may also support motivation, confidence, learning, and growth when appraised positively. Objective: To develop and evaluate the psychometric properties of the Nursing Student Positive Stress Scale (NSPSS). Design: A methodological instrument development and psychometric evaluation study. Methods: The NSPSS was developed using a deductive, theory-driven approach informed by the transactional theory of stress and coping and positive psychology perspectives. Content validity was assessed by an international nursing expert panel. Psychometric evaluation used national survey data from nursing students in New Zealand. Of 539 responses, 507 were analysed. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were conducted using separate subsamples. Internal consistency was assessed using Cronbach's alpha and McDonald's omega, and convergent validity through correlation with Perceived Stress Scale-10 scores. Results: Content validity was strong (I-CVI = .88-1.00; S-CVI/Ave = .975; S-CVI/UA = .800). EFA identified a dominant factor explaining 41.38% of variance (loadings = .528-.735). CFA supported a two-context Academic and Clinical Positive Stress model with correlated residuals between five parallel item pairs, chi-square(29) = 60.49, CFI = .970, TLI = .954, RMSEA = .063, SRMR = .065. Internal consistency was good (alpha = .839; omega = .843). NSPSS scores correlated negatively with PSS-10 scores (r = -.298, p < .001). Conclusion: The NSPSS demonstrated strong content validity, preliminary evidence of structural and convergent validity, and good internal consistency reliability for assessing positive stress appraisal among nursing students. Further validation in independent samples is warranted.

Importance: Evidence on GLP-1/GIP therapies is largely derived from trials enrolling selected populations or medical records that miss utilization outside healthcare channels. No nationally representative cohort has characterized real-world uptake, indications, and access. Objective: To characterize GLP-1/GIP prevalence, indication, clinical profile, and access. Design: Prospective cohort study with three GLP-1/GIP surveillance waves (March 2024, December 2024, October 2025). Setting: The Understanding America Study, an address-based, nationally representative panel of approximately 15,000 US adults aged 18+ years initiated in 2014. Participants: UAS participants responding to at least one surveillance wave (n=9150). Exposures: GLP-1/GIP use status (never vs any use, comprising current and former use), self-reported primary indication (diabetes, weight loss, or other), and access pathway (traditional vs non-traditional). Main Outcomes and Measures: Survey-weighted prevalence of GLP-1/GIP use, overall and by indication and access pathway; sociodemographic, cardiometabolic, treatment, and access characteristics; and smartwatch-derived resting heart rate, heart rate variability, maximum activity heart rate, step count, and sleep duration and variability. Results: Among n=9150 adults (1274 with any use; 60.9% female; median age 53 years), weighted prevalence increased 46%, from 8.2% (March 2024) to 12.0% (October 2025) representing 32 million. Weight-loss indications grew, reaching nearly half of use (4.1% to 5.6%); diabetes-indicated use was stable (5.3% to 5.4%). Users carried high cardiometabolic burden (obesity, 68.2%; diabetes, 53.6%) but diverged by indication: diabetes-indicated users were older (median, 59 vs 49 years), whereas weight-loss-indicated users were more often female (69.9% vs 51.3%) and healthier. One in three users (~9 million) had non-traditional access, especially in weight-loss-indicated users, of whom 33% had no conventional prescription; 41% used compounding, online, or foreign pharmacies; and, 43% lacked coverage. Non-traditional users were five times as likely to report an unlisted, likely compounded formulation (19.8% vs 4.1%). All p<0.05. Conclusions and Relevance: Real-world GLP-1/GIP use has grown rapidly and diversified substantially in indication, access, and population profile. One in 3 users obtained treatment through nontraditional channels largely invisible to claims data, raising long-term safety, efficacy, and coverage questions. GLIMMER provides a public, nationally representative longitudinal evidence base for future payer and provider decisions.