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The psychological impact of disasters extends beyond directly exposed populations to those indirectly affected through close social networks. Sex is a critical factor of post-trauma outcomes, yet its role in shaping the mental health of indirectly exposed individuals remains underexplored. This study investigates sex-based disparities in psychosocial distress among a cohort remotely exposed to a major earthquake. Approximately 3 months after the 2023 Kahramanmaras earthquakes, 129 Turkish medical students with indirect exposure (e.g. via affected relatives or close social circles) took part in this cross-sectional study, completing a structured anxiety survey and a self-report form. The self-report form assessed academic stress, health behaviors (smoking, alcohol use, exercise, and nutrition status), and lifestyle factors. After Bonferroni correction, no variable remained statistically significant. However, using the Benjamini-Hochberg false discovery rate procedure, peer bullying was associated with sex (χ2(3) = 13.581, p_FDR = .046, Cramer's V = 0.324). All other chi-square tests were nonsignificant under both correction methods. After rigorous correction, sex differences were largely attenuated. Peer bullying showed a possible association under FDR, but not under Bonferroni, suggesting the need for larger confirmatory studies. Main findings: After Benjamini–Hochberg correction (but not Bonferroni), peer bullying was associated with sex among indirectly exposed medical students; all other variables showed no robust sex differences under either correction.Added knowledge: This study demonstrates that indirect disaster exposure through social networks can produce measurable psychological distress, but sex-specific patterns are subtle and largely attenuated after multiplicity adjustment. The most reliable sex-related marker was peer bullying, though this finding did not survive the most stringent (Bonferroni) correction.Global health impact for policy and action: Post-disaster mental health frameworks should extend screening and support to remotely affected healthcare trainees. While sex-sensitive approaches remain important, they should prioritize interpersonal stressors such as peer bullying and be applied cautiously, as many initially observed sex disparities may not be robust; larger confirmatory studies are needed to guide resource allocation and targeted interventions.

This study investigated the quality and comprehensibility of responses generated by four different artificial intelligence (AI)-powered chatbots (ChatGPT, Gemini, DeepSeek, and Grok) when queried about testicular prostheses. A Google search using the keyword "testicular prosthesis" was conducted, and the 50 most frequently asked questions listed in the "People Also Ask" section were identified. These questions were categorized into preoperative, perioperative, and postoperative topics and were posed to four AI chatbots: ChatGPT, Google Gemini, DeepSeek, and Grok. The responses were independently evaluated by four urologists using the Global Quality Scale (GQS), Modified DISCERN, and Patient Education Materials Assessment Tool for Printed Materials (PEMAT-P) scales to assess quality, reliability, and readability. According to the GQS evaluation, the median scores for ChatGPT, Gemini, DeepSeek, and Grok were 4.75, 4.5, 4.75 and 4.875, respectively (p < 0.001). According to the Modified DISCERN scale, the scores were 2.75, 3.0, 3.75 and 3.0, respectively. The PEMAT-P understandability scores were 79.1%, 75.0%, 84.2% and 78.6%, respectively (p < 0.001). Similarly, the PEMAT-P actionability scores were 73.5%, 68.5%, 78.9% and 73.2%, respectively (p < 0.001). While all chatbots provided high-quality responses, their reliability was moderate. DeepSeek demonstrated the best performance across the evaluated metrics. These findings suggest that AI chatbots may serve as useful supplementary tools for patient education regarding testicular prostheses.

Research is embedded into the curriculum of most US medical schools. However, there is a great deal of variety in the curricular approaches to teaching research. Further, some programs choose to focus on teaching the conduct of research while others focus on the application of research findings (i.e. evidence-based practice). This variation may lead to conflation of two independent skill sets. This investigation advances a theory (called CEAR-Core, Evidence Application, Research) that research skills and evidence-application skills are independent from one another. We evaluated the CEAR model using a pre-post design and paired t-tests at a medical school with defined curricula in both research and evidence-based practice. We found that medical student skills were low in CEAR model Core skills (approximately 42% of possible maximum score on the CEAR tool at baseline). Core and Research skills increased at each timepoint, although whether the changes were significant varied by research subdomain. Evidence-application scores improved after evidence-based practice activities within the curriculum (22.8&#x2009;&#xb1;&#x2009;16.4% to 30.2&#x2009;&#xb1;&#x2009;18.4% p&#x2009;<&#x2009;0.001), but did not increase significantly further after the research experience (30.2&#x2009;&#xb1;&#x2009;18.4% to 36.5&#x2009;&#xb1;&#x2009;17.3%, p&#x2009;=&#x2009;0.126). Limitations include the single medical school design and the limited number of students who completed all three data collection timepoints. Overall, we believe CEAR is a valid model for medical educators to use to conceptualize the separation of research and evidence application, the core skills required for both, and the sub-domains, in their development of curricula. Additionally, the CEAR tool may be useful for student assessment and curricular evaluation.

Hyperuricemia has been widely associated with cardiovascular health, but its relationship with incident valvular heart disease (VHD) remains uncertain. This study investigated the association between hyperuricemia and VHD, and further explored the role of weight management within this context. Participants from the UK Biobank cohort were categorized into three groups based on serum uric acid (SUA) level: normal (< 6.0 mg/dL), high (6.0-8.9 mg/dL), and very high (&#x2265; 9.0 mg/dL). The risk of VHD associated with SUA level was assessed in the overall population and across subgroups with differing metabolic profiles. To examine the impact of obesity on VHD development, the relative risk of VHD was analyzed based on body mass index and waist circumference. Among 462,705 participants, 340,793 (73.7%) had normal SUA levels, 118,861 (25.7%) had high levels, and 3,051 (0.7%) had very high levels. Over an average follow-up period of 12.3 years, the adjusted risk of VHD was significantly higher in individuals with very high SUA, followed by those with high and normal SUA (2.31 vs. 1.25 vs. reference, respectively). Stratifying VHD risk by metabolic disorders revealed a dose-response relationship between SUA level and VHD risk. The impact of obesity on VHD development was notable among individuals with SUA below 9.0 mg/dL, but less pronounced in those with SUA exceeding 9.0 mg/dL. This finding suggests a significant association between hyperuricemia and VHD, highlighting the potential relevance of elevated SUA levels in VHD risk stratification.

Residual inflammatory risk after acute myocardial infarction (AMI) remains an important determinant of long-term outcomes despite optimal lipid-lowering therapy. The prognostic significance of serial high-sensitivity C-reactive protein (hs-CRP) measurements beyond the acute phase remains unclear. This study compared baseline and 1-year hs-CRP for predicting 3-year major adverse cardiovascular events in patients with AMI undergoing percutaneous coronary intervention. We analyzed a large prospective AMI registry in which hs-CRP was measured at baseline and 1 year, classifying patients at each time point using a &#x2265; 2 mg/L threshold. The primary endpoint was 3-year MACE, including cardiovascular death, recurrent myocardial infarction, stroke, repeat revascularization, and stent thrombosis. Among 16,371 patients, 9,618 (58.8%) had elevated hs-CRP at baseline. Of the 5,389 patients with 1-year data, 28.9% had elevated hs-CRP. Baseline hs-CRP predicted MACE within the first year (hazard ratio [HR] 1.38, 95% CI 1.21-1.57); however, this association was no longer significant beyond 1 year. One year hs-CRP independently predicted subsequent 2-year MACE (HR 1.33, 95% CI 1.01-1.77). Patients with persistently high hs-CRP (&#x2265; 2 mg/L at both time points) had the highest 3-year MACE risk (HR 1.49, 95% CI 1.08-2.06, p = 0.015 vs. persistently low group) than patients with recovered, worsening, and persistently low hs-CRP. In patients with AMI, hs-CRP measured at 1-year provides stronger long-term prognostic information than that at baseline beyond 1 year. Routine assessment of hs-CRP may improve risk stratification and guide targeted anti-inflammatory strategies in secondary prevention.

Recessive dystrophic epidermolysis bullosa (RDEB) is a severe skin fragility disorder caused by mutations in COL7A1 gene, leading to chronic injury, inflammation, and debilitating sensory symptoms, including pain and itch. While structural defects in the dermo-epidermal junction are well characterized, the mechanisms underlying impaired sensory reinnervation and neuropathic manifestations remain poorly understood. Here, we investigated whether defective reinnervation in RDEB is driven by intrinsic neuronal deficits or by alterations in the cutaneous microenvironment. Using a prospective cohort of RDEB patients with small fiber neuropathy (SFN), combined with high-resolution digital PCR and multiplex cytokine profiling, we analyzed the transcriptional and secretory responses of wounded skin and primary keratinocytes. RDEB tissue exhibited a markedly blunted transcriptional response to injury, with failure to induce key inflammatory, proteolytic, and axonal guidance genes, despite a sustained pro-inflammatory secretome characterized by elevated IL-6, TNF-&#x3b1;, IL-1&#x3b2;, CCL2, and MMP9. Functionally, RDEB blister fluid induced growth cone collapse and impaired neurite outgrowth in sensory neurons. These findings reveal a dissociation between transcriptional activation and extracellular signalling, resulting in a non-permissive niche for nerve regeneration. We propose that this altered microenvironment simultaneously impairs reinnervation and promotes maladaptive nociceptive signalling, providing a mechanistic link between chronic denervation and neuropathic pain in RDEB.

This review systematically evaluates the current research landscape, methodological characteristics, and translational challenges of artificial intelligence (AI) integrated with magnetic resonance imaging (MRI) across the diagnostic and therapeutic pathway of spinal metastases, with the aim of informing clinical practice and future research. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we conducted a systematic search of PubMed, Web of Science, and the Cochrane Library. Original studies investigating AI models, including machine learning, deep learning, and large language models, developed from MRI data for spinal metastases were included. Two reviewers independently screened studies and extracted data. Sixty-one studies were included in the qualitative synthesis. The included studies focused on four core clinical tasks: diagnosis and pathological classification (23 studies), clinical prognosis and risk stratification (17 studies), lesion detection and segmentation (16 studies), and automated clinical scoring and report analysis (5 studies). AI models showed promising performance across these tasks, with the highest area under the curve (AUC) for benign-malignant differentiation reaching 0.98 and the highest Dice similarity coefficient (DSC) for automatic lesion segmentation exceeding 0.85. Nevertheless, important limitations remain. Most studies were single-center retrospective investigations (73%), and the majority addressed isolated tasks rather than integrated clinical workflows. Important gaps also persist in multicenter generalizability, long-term survival prediction, and multimodal data integration. MRI-based AI has substantial potential to improve the diagnosis and management of spinal metastases. Future studies should emphasize large-scale, multi-center prospective validation and integrated intelligent systems supporting screening, decision-making, treatment response assessment, and long-term follow-up.

This study's aim was to bridge the gap between the theoretical effectiveness of clinical diagnostic decision support systems (CDDSs) and their practical implementation in emergency medicine. By focusing on one CDDS, we sought to understand how residents use these systems, and how that affects the diagnostic process. Specifically, we investigated the influence of CDDS use on residents' advice-seeking behavior. This mixed-methods study combined exploratory analyses of data obtained during the Differential Diagnosis Broadening (DDx-BRO) cluster-randomized trial and its accompanying preplanned mixed-methods substudy. The DDx-BRO trial employed a multicenter, outcome assessor, patient-blinded, cluster-randomized, multiperiod crossover design across four Swiss emergency departments. The use of the CDDS in clinical practice was investigated by assessing self-reported use and tracked use, as well as observed workflow indicators such as contact time and advice-seeking behavior. A total of 1,204 patients were included. Observations revealed a significant decrease in consultations with senior physicians in intervention periods, during which 91&#x202f;% of observed physicians reported using the CDDS because the use was mandatory. When asked, users rated the CDDS as supportive for 23&#x202f;% the cases. When this was the case, physicians cited the CDDS broadening their list of differential diagnoses and helping confirm their diagnosis as reasons. Our study offers insights into the multifaceted impact of a CDDS on residents' decision-making processes, highlighting the role of such systems in confirmation-oriented diagnostic approaches and changes in consultation patterns.

Drought stress constrains the productivity of terrestrial ecosystems and the distribution of plant species. To withstand drought stress, plants have evolved diverse water-use strategies. Despite the critical function of roots in whole-plant water regulation, drought strategies have been primarily studied from an aboveground perspective, and so our knowledge of how fine-root traits are related to aboveground hydraulic traits remains limited. Here, we compiled a dataset of primarily woody species comprising five aboveground plant hydraulic traits associated with water-use strategies and four fine-root traits from the root economics space (RES). We investigated how the global diversity in ecological strategies of the RES traits relates to aboveground hydraulic traits contributing to drought resistance. We found a slight trend towards acquisitive species with higher root nitrogen content and lower root tissue density having lower drought resistance in aboveground tissues. Species with thicker roots displayed a tendency towards slightly higher drought resistance than thin-rooted species. The weakness of these relationships suggests that aboveground drought adaptations are largely independent of classical axes of fine root ecological strategies, pointing to either a decoupling between aboveground and belowground responses or a stronger coordinating role for other root traits such as maximum rooting depth or root cortex fraction in hydraulic adaptation.

Appropriate dietary intake across different training phases is crucial for improving the performance of track and field jumpers. However, few studies have investigated dietary intake based on the training phase and competitive level. The purpose of this study was to evaluate dietary intake in track and field jumpers across different training phases and competitive levels. A total of 28 male collegiate jumpers participated. A food frequency questionnaire assessing 1-month dietary intake was administered four times: transition phase (TP), preparatory phase (PP), early competitive phase (ECP), and late competitive phase (LCP). Participants were divided into the Exceeded Group (EG) and the Nonexceeded Group (NEG) based on competition standards. Of the 28 participants, 20 were included in the final analysis. Energy, protein, fat, vitamin B1, and vitamin B6 intake decreased during the ECP and LCP compared with intake during the TP. Intake of these nutrients was higher in the EG than in the NEG, with the EG significantly showing higher intake during the TP. However, these group differences were not observed during the LCP. These results indicate the necessity of appropriate dietary strategies for each training phase.

A major challenge in Parkinson's disease (PD) research is the identification of non-invasive neurophysiological markers that can distinguish PD patients from healthy controls while providing interpretable information about cortical dysfunction. This study investigates whether aperiodic EEG spectral parameters extracted using Fitting Oscillations and One-Over-F decomposition can serve as candidate indicators for exploratory PD classification and medication-state analysis. Resting-state EEG data from 15 PD patients and 16 healthy controls were analyzed. For PD participants, both medicated and unmedicated recordings were considered. Periodic and aperiodic powers spectral densities were separated out, and channel-wise exponents and offsets were derived. A leakage-free machine-learning pipeline was implemented using stratified subject-grouped tenfold cross-validation, in which normalization and hybrid t-test, MRMR, and ReliefF feature selection were performed strictly within each training fold. The Random Forest classifier achieved the best performance, with an accuracy of 0.843&#x2009;&#xb1;&#x2009;0.188, a pooled out-of-fold accuracy of 0.848, and a pooled AUC of 0.811. Permutation testing indicated that the observed performance exceeded chance-level classification. FDR-corrected statistical analysis showed significant group-level differences in global exponent and offset, with regional effects mainly involving frontal, temporal, and central areas. Medication-state analysis suggested that the global exponent was sensitive to dopaminergic state, whereas offset effects were weaker. Overall, the findings suggest that aperiodic EEG parameters may provide interpretable candidate markers for PD-related cortical alterations. However, due to the limited public dataset size and lack of external validation, the results should be considered exploratory and require confirmation in larger independent cohorts.

Pseudothrombocytopenia is an artefactual reduction in platelet count that occurs during laboratory testing, most commonly because ethylenediaminetetraacetic acid (EDTA) induces in vitro platelet aggregation. Although clinically benign, it may lead to unnecessary investigations, treatment, transfusion, referral, procedural delay, and patient anxiety when not recognised. Advances in hematology analyzers, including impedance, optical, fluorescence, digital morphology, and artificial intelligence (AI)-assisted technologies, offer opportunities to improve recognition of platelet aggregation and reduce reporting of artefactual thrombocytopenia. This narrative review summarises literature relating to pseudothrombocytopenia, automated platelet counting, digital morphology systems, and AI applications in hematology. Current evidence indicates that analyzer flags and platelet histograms provide useful screening signals but should not replace peripheral blood smear review. Optical and fluorescence platelet channels can improve platelet counting in selected EDTA-dependent samples, while digital morphology systems facilitate documentation of platelet aggregates and support platelet estimation. Emerging AI-assisted workflows are best understood as workflow-support tools that integrate analyzer data, sample timing, channel discordance, digital images, and expert review; they should not be treated as autonomous diagnostic systems. The strongest practical model combines automated platelet channels, digital morphology, AI-supported triage, clear report communication, and expert clinical oversight. Evidence remains heterogeneous, largely platform-specific, and limited by the lack of direct AI-versus-conventional workflow comparisons. Future research should validate integrated systems across diverse laboratory environments and assess clinically relevant outcomes, including diagnostic accuracy, false-positive and false-negative consequences, workflow efficiency, cost, and patient management.

Prepregnancy counselling is recommended for women with chronic kidney disease (CKD) to discuss potential adverse outcomes; however, no tools exist to estimate individual risk. We aimed to develop and externally validate 2 prediction models for outcomes prioritized by people with CKD and health care professionals: The primary outcome was the probability of &#x2265;25% reduction in estimated glomerular filtration rate (eGFR) or kidney replacement therapy (KRT) within 12 months postpartum. The secondary outcome was the probability of small-for-gestational-age (SGA) (< 3rd percentile) infant and/or preterm delivery (< 34 weeks). The development cohort used linked data from the National Registry of Rare Kidney Disease (RaDar), UK Renal Registry (UKRR) and NHS Hospital Episode Statistics (HES). Individuals with eGFR < 90 ml/min per 1.73 m2 within 24 months preconception and deliveries between 1997 and 2021 were included. Validation cohorts were as follows: (i) Ontario Pregnancy Cohort (2007-2022) and (ii) 3 UK pregnancy-CKD studies (2010-2018). Candidate predictors were selected from known risk factors. Clinically relevant cut-points were determined with people with CKD. The development cohort included 746 women (median prepregnancy eGFR: 58 ml/min per 1.73 m2); validation cohorts included 6974 and 380 women. Optimal cut-points of 0.15 (sensitivity: 90%, negative predictive value (NPV): 85%) and 0.10 (sensitivity: 90%, NPV: 80%) were selected for the primary and secondary outcomes. External validations demonstrated high sensitivity and NPV for the primary outcome. Although comparability is limited by differing end points, Kidney Failure Risk Equation (KFRE) predictions (2-year) were lower than our PREDICT model (1-year) (median risk 1.4% vs. 48%). We developed high performing models for individuals with CKD to predict coselected adverse kidney and neonatal outcomes from contemporaneous cohorts. Individualized pregnancy risk assessment tools could support future parents and health care professionals to make informed choices.

Active participation of medical students in research activities enables their understanding of research methods and the benefits that research can provide them as both researchers and clinicians. Differing expectations on the part of the student and supervisor regarding their relative roles and expected contribution can influence the achievement of learning outcomes and quality of the research project. Here we explore the expectations of medical students and supervisors regarding the roles and responsibilities of both parties during the completion of an undergraduate medical research project. Employing a mixed methods design, the CREDIT URE tool, which defines, and measures roles performed by undergraduate students working in research placements, was completed by 226 medical students and their project supervisors. Q-methodology was then used to examine perspectives of students and supervisors on their relative responsibilities. Q-set data were analysed using a by-person factor analysis to group participants with shared viewpoints. Using the CREDIT URE tool, students and their project supervisors rated writing of the original draft article, visualisation, data curation, formal analysis, and investigation as the most common roles and those with the highest level of student responsibility. In the Q methodology study, a five-factor solution (i.e. profiles) provided the best fit for the data collected from 25 participants (16 student, 9 supervisors), explaining 55% of the variance. Each profile describes a shared viewpoint on project roles. We characterized the profiles as 'student-driven', 'supervisor as guide and overseer', 'self-motivated student', 'supervisor involved only as needed - skills development' and 'supervisor as editor'. Medical schools increasingly emphasise research competencies as part of undergraduate education. These data are expected to lead to the development of clear supervision frameworks and role descriptions, and by extension may inform the design of undergraduate medical research modules or project guidelines. The online version contains supplementary material available at 10.1007/s40670-026-02656-0.

Ammonia-oxidizing bacteria (AOB) catalyze the first and rate-limiting step of nitrification. They are essential for nitrogen cycling in engineered and natural environments, yet little is known about their viruses or the consequences of phage infection for host physiology. Here, we report the isolation and characterization of a novel lytic bacteriophage, vB_NeuP-Nir1 (DSM 111086), infecting the model AOB Nitrosomonas europaea. Phage Nir1 ceased ammonia oxidation within hours, and caused complete lysis of host populations even at multiplicities of infection as low as 10-6. Electron microscopy revealed drastic host cell remodeling during infection, including pronounced cell bloating and large-scale disintegration of intracytoplasmic membranes. Integrated transcriptomic and metabolomic analyses showed that loss of these ATP and reducing equivalent generating membrane systems was accompanied by signatures of compromised lipid homeostasis and collapse of autotrophic CO&#x2082; fixation. In parallel, Nir1 infection induced metabolic rewiring of the host, including upregulation of uptake systems for nucleic acids, amino acids, and small organic compounds, increased expression of iron acquisition and putative iron-dependent respiratory components, as well as accumulation of metabolites associated with membrane breakdown and stabilization of viral DNA. Together, these results provide the first detailed mechanistic insight into phage-induced host modulation in a chemolithoautotrophic nitrifier. Our study establishes the Nir1-N. europaea system as a model for investigating virus-host interactions in AOB and lays the foundation for assessing the role of phages in shaping nitrification and nitrogen cycling in engineered and natural ecosystems.

Addition of the long-acting muscarinic antagonist umeclidinium (UMEC) to the inhaled corticosteroid/long-acting &#x3b2;2-agonist (ICS/LABA) combination fluticasone furoate/vilanterol (FF/VI) improved lung function in adults with uncontrolled moderate to severe asthma in the CAPTAIN (Clinical study of Asthma Patients receiving Triple therapy through A single INhaler) study; however, the impact on symptoms requires further investigation. We sought to evaluate the effect of adding UMEC to FF/VI on asthma symptoms. The CAPTAIN study was a phase IIIA, randomized, controlled, 24- to 52-week study of patients with uncontrolled moderate to severe asthma despite ICS/LABA receiving once-daily single-inhaler FF/VI (100/25 or 200/25 &#x3bc;g) or FF/UMEC/VI (100/31.25/25, 100/62.5/25, 200/31.25/25, or 200/62.5/25 &#x3bc;g). Here, we compare the effect of pooled FF/UMEC 62.5/VI (100/62.5/25 and 200/62.5/25 &#x3bc;g) versus FF/VI (100/25 and 200/25 &#x3bc;g) on symptom control using prespecified analyses of change from baseline in Evaluating Respiratory Symptoms in Asthma (E-RS: Asthma) total and domain scores, and proportion of patients meeting an E-RS: Asthma total score responder threshold. We also performed post hoc analyses assessing the impact of baseline type 2 inflammation status on treatment response. Least-squares mean (95% CI) reductions from baseline in E-RS: Asthma total score exceeded the minimum clinically important difference (-2.0 units) and were numerically greater with FF/UMEC 62.5/VI (-2.89 [-3.15 to -2.64]; n = 814) versus FF/VI (-2.47 [-2.73 to -2.22]; n = 813). The proportion of responders (45% [n = 360] vs 41% [n = 327]) and odds of response (odds ratio, 1.18 [95% CI, 0.96 to 1.45]) were numerically greater with FF/UMEC 62.5/VI versus FF/VI. Similar trends were observed irrespective of type 2 status. Patients with symptomatic asthma may benefit from optimized treatment interventions, such as adding a long-acting muscarinic antagonist to ICS/LABA.

Nevus lipomatosus superficialis (NLS) is a rare cutaneous hamartoma characterized by ectopic adipose tissue in the dermis. Its genetic basis remains largely unknown. We conducted a comprehensive clinical, histopathological, and genetic investigation of a 17-year-old female with an exceptionally extensive distribution of lesions (involving trunk, buttocks, lower extremities, and vulva) that was atypical due to the presence of significant pain and recurrent infections. Whole exome sequencing (WES) was performed on the proband and both parents (trio-WES), and whole genome sequencing (WGS) was performed on fresh lesional tissue. Low-level mosaicism or regulatory mechanisms may remain undetected. Physical examination revealed widespread hyperpigmented plaques. Histopathology confirmed mature adipocytes within the superficial to mid-dermis, consistent with NLS. Under our detection thresholds, we did not identify any pathogenic or likely pathogenic variants from WES or WGS. WES revealed 24 variants of uncertain significance, none of which were compelling for phenotype/pathway relevance. WGS did not identify pathogenic coding or non-coding variants, structural variations, copy number variations, or mitochondrial mutations. No pathogenic mutation was detected, suggesting alternative genetic mechanisms may be involved. This case represents a rare presentation of extensive NLS with associated pain. Comprehensive genetic analysis did not identify pathogenic variants under our detection thresholds, while suggesting possible somatic mosaicism, recessive inheritance, or non-coding region variations.

This study investigated the effects of pullulanase and amyloglucosidase modification on the in vitro digestibility, multi-scale structure, and processing characteristics of hulless barley starch. Both enzymatic treatments reduced the rapidly digestible starch (RDS) content and increased the total content of slowly digestible starch (SDS) and resistant starch (RS). Pullulanase showed superior performance to amyloglucosidase. Treatment at 60&#xa0;&#xb0;C enhanced anti-digestibility, with the B-pullulanase-50 sample achieving the highest SDS&#xa0;+&#xa0;RS content (31.95%). Amylose content increased with enzyme concentration. XRD analysis showed a transition from A-type to B-type crystal structure. FTIR and Raman spectroscopy revealed enhanced short-range order and increased helical structures. Particle size and SEM results indicated granule aggregation and morphological changes, including surface erosion and swelling. DSC analysis showed elevated gelatinization temperatures. Rheological tests demonstrated pseudoplastic behavior with reduced consistency and enhanced elastic character post-modification. These results suggested enzyme modification can effectively tailor the digestibility and physicochemical properties of hulless barley starch.

Type 2 diabetes (T2DM) is clinically heterogeneous. A subgroup with markedly reduced C-peptide has poorer glycemic stability and different therapeutic needs, but the associated peripheral immune features and practical non-invasive markers are not well defined. We investigated whether T2DM with low C-peptide (T2DM-LowC) is associated with a distinct peripheral immune profile. In this single-center, cross-sectional study, patients with T2DM were propensity score-matched 1:1 by disease duration into low C-peptide (T2DM-LowC, n=109) and preserved C-peptide (T2DM-PresC, n=109) groups. Clinical and metabolic variables were compared. In an exploratory sub-cohort (n=21; HC=7, PresC=7, LowC=7), transcriptomic profiling of peripheral blood mononuclear cells (PBMCs) was analyzed using differential expression analysis, weighted gene co-expression network analysis, and CIBERSORTx deconvolution. Candidate genes were validated in an independent cohort (n=40) by RT-qPCR. Compared with T2DM-PresC, the T2DM-LowC subgroup had lower BMI and triglycerides, higher alkaline phosphatase, and a higher systemic inflammation response index (SIRI; neutrophils &#xd7; monocytes/lymphocytes). Higher SIRI remained associated with low C-peptide status after adjustment (OR = 2.38, p = 0.007). Exploratory PBMC transcriptomic analyses identified lower mast-cell-related signatures, higher resting NK-cell and resting CD4 memory T-cell signatures, and a shift toward memory B cells. CSF2RB, NIBAN1, and TLR1 were consistently downregulated in T2DM-LowC, and the three-gene panel discriminated the two T2DM subgroups in the validation cohort (AUC = 0.903; sensitivity 75.0%; specificity 90.0%). In this cross-sectional dataset, low C-peptide T2DM was associated with a distinct clinical and peripheral immune profile. Integrating SIRI with a three-gene PBMC signature may provide a non-invasive adjunct for identifying this subgroup. These deconvolution-derived immune-cell findings require validation in larger and functionally characterized cohorts.