Obsessive-compulsive (OC) symptoms are usually associated with obsessive-compulsive disorder but they are also present in the general population. It has been reported that OC symptoms can involve atypical olfactory experiences, but their impact on mental health and wellbeing is poorly understood. We have investigated the prevalence of OC symptoms in a representative sample (n = 996) of the adult Czech population aged 18-50. We investigated to find out whether the severity of OC symptoms is associated with odour awareness, olfactory irritability, disgust sensitivity, and trait anxiety. A total of 12.3% of respondents reported moderate or elevated OC symptoms, with the highest prevalence observed in individuals aged 18-30 years. We also found that trait anxiety and olfactory irritability positively predicted the severity of OC symptoms, but, interestingly, disgust sensitivity was not a significant predictor of the severity of OC symptoms in our sample. Overall, these findings highlight a complex link between OC symptoms and atypical olfactory experiences in a non-clinical adult population.

A work group representing the U.S. Department of Veterans Affairs (VA) and U.S. Department of Defense (DoD) prepared a new VA/DoD clinical practice guideline (CPG) for tobacco use treatment. This article provides a synopsis of the 2026 CPG, which addresses use of commercially available tobacco and nicotine products.

A multidisciplinary work group developed 19 key questions on clinical topics of highest priority for the VA and DoD populations. Published literature from 1 January 2014 to 10 December 2024 was systematically reviewed using the PICOTS (population, intervention, comparator, outcomes, timing of outcomes measurement, and setting) framework. Recommendations were made by consensus and informed by evaluation using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) method, which assesses quality of evidence and balances benefits and harms, patient preferences, and feasibility. The final document incorporated input from peer review by an external group of experts.

The 2026 guideline includes 32 recommendations across 10 topic areas. Key recommendations for increasing abstinence from combustible tobacco include recommending motivational interviewing to increase engagement in treatment of tobacco and nicotine use (strong) and use of U.S. Food and Drug Administration-approved pharmacotherapies (strong), with varenicline recommended over monotherapy with other agents (strong), combination nicotine replacement therapy ([NRT] for example, patch plus lozenge) recommended over NRT monotherapy (single agent) (strong), and extending use of bupropion sustained release beyond 12 weeks (weak). Other key recommendations include varenicline for increasing abstinence from smokeless tobacco (strong) and electronic nicotine delivery systems (weak) and use of NRT or varenicline to increase quit attempts and abstinence in patients not ready to quit in the next 30 days (weak).

Regular physical activity promotes brain health, yet the underlying mechanisms remain incompletely understood. Repetitive activation of neurons results in accumulation of the nuclear transcription factor ΔFOSB, a long-lived splice variant of FOSB. Long-term voluntary wheel running (VWR), a behavioral paradigm that mimics exercise training in humans, altered brain ΔFOSB immunoreactivity signatures and reorganized co-activation networks in Wistar rats. Here, we used a similar approach to determine large-scale ΔFOSB brain signatures following long-term VWR in mice. Young-adult individually-housed male and female C57BL/6J^OlaHsd mice were allowed to run for four weeks on horizontal saucer-like wheels, after which ΔFOSB immunoreactivity was quantified in 46 brain regions associated with stress regulation, cognition- and reward-related behavior. Network analysis was applied to assess VWR-mediated changes in interregional ΔFOSB co-activation patterns and network topology. Male and female mice ran equal distances and VWR blunted body weight gain and terminal gonadal white adipose tissue mass in both sexes. VWR modulated ΔFOSB immunoreactivity across several cortical, striatal, hippocampal and thalamic regions. Network analysis revealed substantial network reorganizations, with reduced overall network density and increased cortical centrality in males, and greater global efficiency (i e, small-worldness) in females. Thus, VWR induced large-scale adaptations in brain (in)activation, reshaping network organization in distinct ways in both sexes. Because ΔFOSB regulates many target genes, impacting e g neuron excitability, our findings suggest that long-term VWR induces widespread transcriptional alterations throughout the mouse brain. Functional and mechanistic follow-up studies are necessary to determine the impact of these alterations on stress regulation, cognition- and reward-related behavior.Significance statement Regular physical activity promotes brain health, but the underlying mechanisms remain incompletely understood. Here, we quantified ΔFOSB, a transcription factor involved in neuroplasticity, in 46 brain regions associated with stress regulation, cognition- and reward-related behavior after four weeks of VWR in individually-housed male and female mice. We show altered ΔFOSB immunoreactivity in a subset of these brain regions in both male and female runners. This was accompanied by specific changes in ΔFOSB co-activation networks. These large-scale mouse brain ΔFOSB signatures following VWR improve our understanding of how VWR impacts brain plasticity in mice and offers a framework for mechanistic and functional studies into ΔFOSB-mediated changes in stress regulation, cognition- and reward-related behavior following VWR.

The objective of this study was to explore the cross-sectional association between albumin-corrected anion gap (ACAG) and the composite outcome of prediabetes or diabetes mellitus (PD-DM) using data from the National Health and Nutrition Examination Survey (NHANES) 2005-2010.

A cross-sectional analysis was conducted, comprising 3937 adult participants aged ≥ 20 years, who were categorized into two groups: those with PD-DM and those without PD-DM. The baseline characteristics were compared using the most appropriate statistical tests. Logistic regression analyses, restricted cubic spline (RCS), subgroup analyses, interaction tests, and sensitivity analyses were performed to investigate the cross-sectional relationship between ACAG and PD-DM. Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were computed to assess whether ACAG offered incremental predictive value for PD-DM.

Participants with PD-DM exhibited higher ACAG levels (15.02 vs. 14.14, p < 0.01). Each unit increase in ACAG was associated with 1.16-fold higher odds of PD-DM after full adjustment (odds ratio [OR] = 1.16, 95% confidence interval [CI]: 1.09-1.23; p < 0.01). RCS showed that ACAG was linearly associated with PD-DM (p for nonlinearity = 0.48). Subgroup analyses revealed a stronger association in females and lower poverty income ratio (PIR) groups (p for interaction < 0.05). NRI and IDI analyses confirmed that incorporating ACAG into the baseline model significantly improved risk discrimination and reclassification for PD-DM (all p < 0.01). Sensitivity analyses confirmed robustness.

This cross-sectional study demonstrated that ACAG is positively associated with PD-DM, especially among females and lower PIR participants. ACAG also showed significant incremental predictive value for PD-DM risk prediction. Because of the cross-sectional design, causal inference cannot be established. Further large-scale prospective studies are still needed to elucidate the role of ACAG in the development of PD-DM.

To systematically compare sodium-glucose linked transporter 2 inhibitors (SGLT2i) and dipeptidyl peptidase 4 inhibitors (DPP4i) in glycemic control, weight reduction and genital infection risk in type 2 diabetic patients, and provide evidence-based support for individualized clinical medication.

A comprehensive search of PubMed, Web of Science, Cochrane Library, and EMBASE was performed for randomized controlled trials (RCTs) from database inception. Data on glycated hemoglobin, body weight, and genital infections were extracted. Risk of bias was assessed with the Cochrane ROB 2.0 tool. Meta-analyses were conducted using RevMan 5.4 and Stata 17.0, with effect sizes pooled by high- and low-dose SGLT2i subgroups. Subgroup analyses, sensitivity analyses, publication bias assessment (funnel plots plus Egger's test), and GRADE evidence quality rating were performed.

10 RCTs were ultimately included. For low-dose SGLT2i, the reduction in glycated hemoglobin was not statistically different from that of DPP4i (mean difference [MD] = 0.01%, 95% confidence interval [CI]: -0.05% to 0.07%, P = 0.75). In contrast, high-dose SGLT2i demonstrated superior glycemic efficacy (MD = -0.15%, 95% CI: -0.27% to -0.03%, P = 0.01). Regardless of dosage, SGLT2i were significantly more effective than DPP4i in reducing body weight (low-dose MD = -1.69, high-dose MD = -1.92; both P < 0.01). Regarding safety, both low- and high-dose SGLT2i were associated with a significantly higher risk of genital infections compared with DPP4i (low-dose odds ratio [OR] = 4.25, high-dose OR = 4.03; both P < 0.01). Subgroup analyses suggested that the glucose-lowering effects might vary among individual SGLT2i agents, but these exploratory findings should be interpreted with caution due to the limited number of studies.

High-dose SGLT2i offer superior glycemic control versus DPP4i; all SGLT2i doses confer significant weight loss benefits but carry a higher genital infection risk. Clinicians should therefore consider individual glycemic targets, weight status, and infection risk when selecting glucose-lowering therapies.

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD420261468619, identifier CRD420261468619.

Diabetic peripheral neuropathy (DPN) is a prevalent and severe microvascular complication of type 2 diabetes mellitus (T2DM). Early risk screening and warning are critical for slowing disease progression. The triglyceride-glucose (TyG) index, a simple and efficient surrogate marker for assessing insulin resistance (IR), has been proven to be closely associated with various diabetic complications. However, existing studies on the association between the TyG index and the risk of DPN have yielded inconsistent findings, and relevant evidence still lacks systematic synthesis.

A systematic review and meta-analysis were conducted. We systematically searched databases including PubMed, Embase, Web of Science, CNKI, Wanfang, and CQVIP to enroll observational studies exploring the association between the TyG index and the risk of DPN in patients with T2DM. Two investigators independently performed literature screening, data extraction, and quality assessment. The random-effects and fixed-effects models were applied to pool effect sizes, and subgroup analyses were carried out to explore potential sources of heterogeneity.

A total of 14 studies involving 32,281 participants were included. The results showed that a higher TyG index was associated with an increased risk of DPN, with a pooled odds ratio (OR) of 2.614 (95% CI: 1.788-3.821, P < 0.0001) and a pooled hazard ratio (HR) of 1.248 (95% CI: 1.003-1.553, P = 0.0471). This positive correlation remained consistent across most subgroups stratified by age, sample size, BMI, and adjustment for confounding factors. However, the association did not reach statistical significance in the non-China subgroup.

Elevated TyG levels are associated with an increased risk of DPN in patients with T2DM. However, the causal relationship requires further validation. These findings may serve as a reference for clinical screening of DPN risk.

https://www.crd.york.ac.uk/prospero, identifier CRD420261373476.

Previous studies have reported Helcococcus kunzii infection in a range of clinical conditions, including infective endocarditis, umbilical abscesses, bacteremia, diabetic foot infections, and prosthetic joint infections. Diabetes mellitus has been identified as a predisposing condition for infections caused by this pathogen. We report the first documented case of spondylodiscitis caused by Helcococcus kunzii.

We describe a case of spondylodiscitis caused by Helcococcus kunzii in a 62-year-old man with long-standing type 1 diabetes mellitus who presented to the emergency department with severe, immobilizing lumbar pain. Clinical diagnosis of spondylodiscitis was established by magnetic resonance imaging (MRI). Helcococcus kunzii was isolated from four separate blood culture sets. During surgical intervention, two swabs and two tissue samples were collected. H. kunzii was identified in all specimens using MALDI-TOF mass spectrometry (MALDI-TOF MS) with log scores ranging from 2.30 to 2.52. The patient received intravenous β-lactam antibiotics for ten days, followed by 13 weeks of oral β-lactam antibiotics. Follow-up MRI performed before discharge showed no further evidence of spondylodiscitis. At the 3-month follow-up visit, the patient demonstrated clinical improvement.

This case demonstrates that H. kunzii should be considered a potential etiological agent of pyogenic spondylodiscitis, particularly in patients with diabetes mellitus and associated comorbidities that may compromise skin barrier integrity. MALDI-TOF MS is essential for accurate identification of this organism and should be considered in cases of atypical spondylodiscitis.

Early post-treatment prognostic assessment may facilitate individualized follow-up in patients with differentiated thyroid cancer (DTC) after initial radioactive iodine (RAI) therapy (RAIT).This study aimed to develop and internally validate a dual-mode machine-learning framework integrating clinical information available from the pre-RAI baseline through the early post-RAI assessment period to predict subsequent unfavorable treatment response and persistence/recurrence-free survival (PRFS).

A retrospective cohort of 550 DTC patients who underwent total thyroidectomy followed by initial RAIT was included. Multidimensional clinical metrics, including demographic, pathological, imaging, and serum biochemical data, were collected. Post-therapy imaging and biochemical measurements obtained at the first follow-up approximately 1-3 months after RAIT were treated as early post-RAI predictors, whereas subsequent therapeutic response was evaluated dynamically during longitudinal follow-up according to the 2025 American Thyroid Association (ATA) dynamic risk stratification framework. Patients with excellent response (ER) or indeterminate response (IndR) were classified as having a favorable response, whereas those with biochemical incomplete response (BIR) or structural incomplete response (SIR) were classified as having an unfavorable response. PRFS was defined as the interval from initial RAIT to the first subsequent documentation of BIR or SIR; patients without such an event were censored at their last follow-up. Data were randomly split into training and testing cohorts at a 7:3 ratio. Boruta and Least Absolute Shrinkage and Selection Operator (LASSO) were utilized for feature selection in binary classification, while Random Survival Forest (RSF) feature importance ranking was applied for survival modeling. We developed Decision Tree (DT), Random Forest (RF), Light Gradient Boosting Machine (LightGBM), and Multi-Layer Perceptron (MLP)-based Artificial Neural Network (ANN) models for risk classification, alongside the Cox Proportional Hazards (Cox PH) model, Gradient Boosting Survival Analysis (GBSA), RSF, and Extra Survival Trees (EST) for survival prediction. Model performance was evaluated using the Area Under the ROC Curve (AUC), Concordance Index (C-index), calibration curves, and Decision Curve Analysis (DCA). The Shapley Additive exPlanations (SHAP) framework was employed to interpret the models' decision-making mechanisms.

Among 550 patients, 113 (20.5%) were classified into the unfavorable response group. The ANN classification model demonstrated superior performance on the testing cohort, with an AUC of 0.932 (95% CI: 0.888-0.967), accuracy of 0.879, specificity of 0.947, F1-score of 0.677, and the lowest Brier Score (0.091). Its clinical net benefit, as assessed by DCA, exceeded that of other models. Key predictors in the ANN risk classification model included Extrathyroidal Extension (ETE), T-stage, iodine-avid lymph node status (iodine_LN), RAI Dose, Metastatic Lymph Nodes (MLN), pre-radioiodine therapy stimulated thyroglobulin (pre_sTg), and pre-radioiodine therapy thyroglobulin antibody (pre_TgAb). Regarding PRFS prediction, the RSF model achieved the highest C-index (0.886) and a mean time-dependent AUC of 0.910 (95% CI: 0.867-0.940), outperforming other models. The core prognostic factors for the RSF model included pre_sTg, thyroglobulin at first follow-up (Tg_FU1), Pre-radioiodine Therapy Thyroglobulin/TSH Ratio (Pre_RAI_Tg_TSH_Ratio), MLN, RAI Dose, Thyroid Stimulating Hormone at first follow-up (TSH_FU1), and Thyroglobulin Antibody Reduction Rate (TgAbRR).

In this single-center cohort, the ANN and RSF models demonstrated favorable internal performance for unfavorable-response classification and PRFS prediction, respectively. These findings provide preliminary proof-of-concept evidence for an early post-RAI prognostic assessment framework; however, prospective multicenter external validation is required before its generalizability or clinical utility can be established.

Assessment of cortisol secretion in patients with adrenal incidentalomas remains challenging. We evaluated the guideline-recommended cortisol cut-off value for cortisol suppression (50 nmol/L) following a 1 mg overnight dexamethasone suppression test (DST) against a control-derived threshold and compared patient classification using the two thresholds. Secondary objectives included assessing associations of pre-DST ACTH, post-DST dexamethasone, and comorbidities with post-DST cortisol.

In this cross-sectional study (NCT07350031), pre- and post-DST plasma samples from patients with adrenal incidentalomas (N = 108) and matched controls (N = 101) were prospectively collected, and cortisol was analysed using immunoassay (Elecsys^®Cort II) and LC-MS/MS. Post-DST dexamethasone ≥3 nmol/L defined appropriate dexamethasone exposure. The 97.5th percentile of LC-MS/MS-measured post-DST cortisol in controls defined the control-derived threshold. Associations between pre-DST ACTH, post-DST dexamethasone, and post-DST cortisol were assessed. The performance of pre-DST ACTH for identifying post-DST cortisol >50 nmol/L was evaluated using receiver operating characteristic analysis. Logistic regression examined associations between post-DST cortisol and diabetes, dyslipidaemia, hypertension, and osteoporosis.

The 97.5^th percentile of post-DST cortisol in controls was 66 nmol/L. The 50 nmol/L threshold corresponded to the 90^th percentile of controls and classified 44% of patients as having hypercortisolism, compared with 26% using the control-derived threshold (66 nmol/L). Pre-DST ACTH showed poor discrimination for post-DST cortisol >50 nmol/L (AUC 0.69). Post-DST cortisol was not associated with dexamethasone concentrations or comorbidities.

The guideline-recommended post-DST cortisol threshold of 50 nmol/L may be too low, suggesting that higher thresholds warrant further evaluation.

Polycystic ovary syndrome is associated with metabolic and hormonal disturbances during pregnancy, but whether these alterations are reflected in the fetal intrauterine exposure environment remains incompletely understood. This study aimed to identify polycystic ovary syndrome-related intrauterine metabolic signatures using late-gestation amniotic fluid.

Untargeted metabolomic profiling was performed on late-gestation amniotic fluid samples from women with polycystic ovary syndrome and controls. Differential metabolite analysis, pathway-level analysis, and multilevel sensitivity analyses were conducted to identify robust metabolic alterations associated with maternal polycystic ovary syndrome. Exploratory placental transcriptomic analysis and targeted RT-qPCR assessment in an independent sample set were further used to examine tissue-level molecular changes related to the lipidomic findings.

Amniotic fluid from pregnancies with polycystic ovary syndrome showed a distinct metabolic profile dominated by lipid remodeling. Differential metabolites were mainly enriched in membrane phospholipids, sphingolipid-related metabolites, polyunsaturated fatty acid-related pathways, and selected steroid hormone-related metabolites. Phospholipid remodeling was characterized by decreased phosphatidylcholine species, increased phosphatidylethanolamine species, a lower phosphatidylcholine/phosphatidylethanolamine ratio, and redistribution of arachidonic acid-containing phospholipids. Alpha-linolenic acid metabolism provided an additional polyunsaturated fatty acid-related signal. Sphingolipid enrichment suggested that lipid alterations extended from membrane structural remodeling to lipid-mediated signaling. Selected steroid hormone-related metabolites were also elevated, consistent with an altered hormonal milieu in pregnancies with polycystic ovary syndrome. These signatures remained largely stable across sensitivity analyses, as did the multivariable-adjusted inverse association between PE(16:0/20:4) and birth weight. Exploratory placental transcriptomic analysis and targeted RT-qPCR assessment in a small independent cohort provided preliminary tissue-level support for phospholipid-related molecular alterations, with the clearest changes involving PLA2-family genes and PCYT1A, suggesting cross-cohort convergence at the pathway level.

These findings identify phospholipid remodeling as a major amniotic-fluid metabolic signature of polycystic ovary syndrome-related intrauterine exposure. PUFA-related metabolism, sphingolipid enrichment, and steroid hormone-related alterations provide additional metabolic context. Complementary placental molecular findings and the inverse association between PE(16:0/20:4) and birth weight further suggest potential links with the maternal-fetal interface and fetal growth. Further studies are needed to clarify the biological relevance of these changes and their potential role in offspring metabolic susceptibility.