An integrated strategy combining comprehensive two-dimensional gas chromatography with chemometrics was established to characterize Aucklandiae radix (AR, Mu-xiang) and its complex formulations. By employing contour visualization, intelligent deconvolution, and in-silico retention index prediction, the method effectively resolved severe co-elution, separating at least five components from single peak vertices. A total of 55 characteristic compounds were identified in the AR essential oil. Comparative analysis revealed that AR and its substitute, Vladimiriae radix (Chuan-Muxiang), shared 21 components, while the former possessed 12 unique constituents compared to 47 in the latter. Chemical divergence was even more pronounced in other substitutes. Furthermore, although costunolide is a major component in the herb powder, it constitutes only 0.4% of the essential oil; thus, dehydrocostus lactone (or dihydrodehydrocostus lactone) and 1,8,11,14-heptadecatetraene were selected as quality markers. The application of these markers to Xiangsha-Yangwei pills from eight manufacturers yielded similarity values of 0.22-0.76. This quantitative profiling revealed significant quality inconsistencies, including the absence of critical components, demonstrating the method's utility for the comprehensive quality assessment of traditional formulas.

Background Traditional Chinese Medicine (TCM) presents a unique therapeutic paradigm characterized by multi-compound, multi-target interventions, yet this complexity impedes mechanistic understanding and standardization. While artificial intelligence (AI) has been applied to isolated aspects of TCM research, a critical gap remains in integrating these applications across the inherent hierarchical structure of TCM—from the pharmacological effects of single compounds (SC) to the synergistic mechanisms of complex Chinese medicinal materials (CMM) and Chinese medicine formulae (CMF). Aim of review This review aims to introduce a novel, AI-driven framework that unifies the multi-scale target analysis continuum of TCM through a systematic, cross-scale data flow, positioning AI as the central catalyst for a holistic understanding across SC, CMM, and CMF levels. Key scientific concepts of review The proposed framework demonstrates how molecular targets predicted at the SC level serve as foundational inputs to decipher multi-SC synergistic networks within CMM. These modular networks are subsequently integrated to unravel the complex multi-target synergistic mechanisms of CMF, thereby paving the way for intelligent CMF recommendation (CMFR) and precise quantitative dosage prediction. Furthermore, the review critically addresses fundamental challenges such as the “semantic gap” between abstract TCM theories and molecular data, strongly advocating for a “computation-experiment” closed loop to validate in silico predictions. Finally, we propose transformative future directions, including the development of TCM-specific large language models (LLMs), to decode TCM’s pharmacological logic and chart a definitive path towards its scientific validation and global integration.

Sichuan Province is the daodi source of Huangsi-Yujin (HSYJ, Radix Curcuma longa). Despite their similar appearances, traditional and improved HSYJ cultivars coexist, complicating quality standardization. This study explored the significant phenotypic diversity between these cultivars, primarily in aroma and color, and established a marker-guided quality retention strategy. Non-targeted GC×GC-TOFMS volatilomics revealed that even within the same daodi region, improved cultivars exhibited higher germacrone but lower turmerone content than traditional ones. Transcriptomic analysis confirmed that this chemical divergence is driven by genetic factors. Furthermore, HS-SPME-GC/Orbitrap-MS integrated with electronic nose assessments identified variety-specific aromatic signatures. Quantitative LC-MS analysis correlated the superior curcuminoid levels in traditional HSYJ with their intense yellow hue (elevated CIE L*a*b* values). To bridge the gap between chemical identification and industrial application, these identified volatile markers and curcuminoids guided a tailored, sequential processing strategy. Supercritical CO2 extraction was first utilized to capture the authentic aroma fraction, followed by the recovery and stabilization of curcuminoids via microencapsulation. This integrated framework not only elucidates the genetic and chemical basis of HSYJ quality but also demonstrates how marker-guided processing ensures the consistent, modernized production of high-quality daodi herbal products.

The use of extracorporeal life support and indwelling blood-contacting devices in critically ill patients is frequently complicated by device-associated thrombosis, a persistent clinical challenge not fully addressed by current antithrombogenic coatings. This limitation is largely attributable to the profound systemic inflammatory state inherent to critical illness, which drives a hypercoagulable milieu through mechanisms of immunothrombosis that conventional coatings fail to mitigate. To address this dual pathophysiological challenge, we designed a novel composite coating comprising a zwitterionic poly(2-methacryloyloxyethyl phosphorylcholine) (PMPC) coordinated with copper ions (Cu(II)). This dual-functional strategy integrates the passive antifouling properties of the PMPC layer with the active, localized generation of nitric oxide (NO) catalyzed by Cu(II) from endogenous S-nitrosothiols. Systematic evaluation under both static and dynamic conditions, including blood models simulating critical illness inflammation, demonstrated that the PCDA coating synergistically resists protein adsorption and inhibits platelet activation; the coating provides superior protection against thrombus formation and inflammatory activation compared to conventional monofunctional surfaces. These findings suggest a translational advance toward enhancing the hemocompatibility and safety of life-support devices in the high-acuity ICU setting.

Tumor-associated macrophages (TAMs) are key determinants of the immunosuppressive microenvironment in hepatocellular carcinoma (HCC) and critically influence the efficacy of immunotherapy. However, how metabolic regulators shape TAM immunophenotypes and subsequent CD8⁺ T cell dysfunction in HCC remains incompletely understood. Single-cell RNA sequencing data and primary tumor samples from patients with HCC were used to characterize xanthine oxidoreductase (XOR) expression on TAMs, and to clarify the underlying mechanisms mediating the effects of XOR⁺ monocytes/macrophages on CD8⁺ T cells. An in-house small-molecule library was screened to identify compounds capable of modulating XOR activity, followed by mechanistic and therapeutic validation in vivo. We identified a marked downregulation of XOR expression in TAMs within HCC tumors, which was significantly associated with poor clinical outcomes. Mechanistically, loss of XOR disrupted PPARγ signaling and cholesterol homeostasis in macrophages, driving their polarization toward an alternatively activated, immunosuppressive M2 phenotype. XOR-deficient TAMs exhibited an impaired capacity to support CD8⁺ T cell activation through enhancing PD-L1 expression, thereby facilitating tumor progression. Notably, a resveratrol derivative, Res616, directly bound to and stabilized the XOR protein, restoring cholesterol metabolic balance and reversing the immunosuppressive phenotype of TAMs. Therapeutically, targeting XOR with Res616 significantly enhanced intratumoral CD8⁺ T cell responses and synergized with anti-PD-L1 therapy to suppress tumor growth in murine HCC models. Our study identified XOR as a pivotal metabolic checkpoint governing TAM-mediated immunosuppression in HCC. Pharmacological stabilization of XOR to restore macrophage cholesterol homeostasis represented a previously unrecognized strategy to remodel the tumor immune microenvironment and improve the efficacy of immune checkpoint blockade.

Comprehensive Two-Dimensional Gas Chromatography (GC × GC) provides unparalleled resolving power for volatomics profiling. However, existing contour detection methods, when applied to these complex samples, frequently suffer from false negatives due to overlapped contours, severely hindering accurate quantification. Even when optimized, these methods struggle to resolve such ambiguities. This study proposes a hybrid deep learning framework to overcome false negatives caused by overlapped contours in GC × GC analysis by integrating image classification and instance segmentation. The approach involves four key steps: (1) constructing initial contour maps using an improved PeakCET v2 with a Laplacian operator; (2) classifying single and multi-peak contours with ResNet18; (3) segmenting overlapping contours via YOLO 11l; and (4) evaluating the segmentation results to identify singular contours. ResNet18 achieved a classification accuracy of 98.59%, outperforming other models with perfect precision. The YOLO 11l component demonstrated exceptional segmentation capability, attaining a mAP50 exceeding 87% and securing the highest mAP50-95 among tested architectures. Validation against diverse rose oil datasets confirmed the method's generalizability and robustness. By significantly reducing the dependency on manual curation, this ResNet18-YOLO 11l pipeline presents an automated, time-efficient solution for processing complex GC × GC data.

Ovarian cancer (OC) remains the most lethal malignancy within the spectrum of gynecological cancers globally. While protein S-palmitoylation has been extensively implicated in tumor progression, its specific functional contributions and molecular mechanisms in the context of OC pathogenesis remain to be fully elucidated. This article aims to explore the prognostic effect associated with palmitoylation in OC. In this study, palmitoylation-related genes (PRGs) were defined as genes encoding enzymes directly involved in the palmitoylation/depalmitoylation process, as well as genes whose functions, subcellular localization, or signaling are regulated by this modification. Based on this definition, PRGs comprising enzymes and regulated substrates, were identified from public transcriptomic databases. By intersecting ovarian cancer (OC)-associated and palmitoylation-linked differentially expressed genes (DEGs), candidate targets were pinpointed. A prognostic risk model was then constructed using LASSO and Cox regression analyses on the TCGA-OV cohort (N = 378) and validated in the GSE51088 cohort (N = 152). This model was integrated into a predictive nomogram and further characterized through pathway enrichment, immune infiltration, checkpoint analysis, drug screening, and mutation profiling. Finally, identified markers were validated via RT-qPCR in clinical samples. Through intersecting DEGs1 and DEGs2, we obtained 24 candidate biomarkers. Four PRGs (HSPG2, BRD4, RARRES1, and SCGB1D2) were identified to construct a prognostic risk model. The risk score, alongside ethnicity and tumor stage, served as an independent prognostic indicator, integrated into a robust nomogram. Mechanistically, high-risk cohorts were characterized by dysregulated ribosome and translation initiation pathways, altered infiltration of seven immune cell types, and significant variations in seven checkpoints (e.g., CTLA4, CD274). Additionally, the model predicted sensitivities for 131 drugs and captured a high TP53 mutation rate. RT-qPCR validation confirmed the upregulation of HSPG2, SCGB1D2, and BRD4, and the downregulation of RARRES1 in OC tissues, showing high consistency with bioinformatic predictions (P < 0.05). This study identified HSPG2, BRD4, RARRES1, and SCGB1D2, which served as prognostic markers reflecting the palmitoylation-related biological landscape in OC that could lay the foundation for innovative therapeutic strategies.

BACKGROUND AND AIMS:Accurate prediction of hepatitis B surface antigen (HBsAg) seroclearance remains essential for optimising pegylated interferon-α (Peg-IFN-α) therapy in chronic hepatitis B (CHB). While HBsAg is a conventional predictor, HBV RNA and hepatitis B core-related antigen (HBcrAg) have emerged as potential biomarkers. However, whether combining these markers can improve the predictive value of HBsAg seroclearance remains unclear. METHODS:In this study, CHB patients with HBV DNA < 100 IU/mL, HBeAg-negative and HBsAg level ≤ 1500 IU/mL after receiving ≥ 1 year of nucleos(t)ide analogues (NAs) therapy were enrolled and received 48 weeks of Peg-IFN-α add-on therapy. Baseline clinical, biochemical and virological parameters (HBsAg, HBV RNA and HBcrAg) were evaluated for their predictive value of HBsAg seroclearance at week 48. RESULTS:Among 150 patients, 51 (34.0%) achieved HBsAg seroclearance after 48 weeks of Peg-IFN-α add-on therapy. Baseline HBsAg (OR 4.27, p < 0.001), HBV RNA (OR 6.78, p = 0.004) and HBcrAg (OR 2.35, p = 0.044) were independent predictors of HBsAg seroclearance. Combining HBsAg, HBV RNA and HBcrAg improved predictive accuracy over HBsAg alone (AUROC 0.845 vs. 0.785). Patients meeting the criteria of HBsAg < 200 IU/mL, HBV RNA < 130 copies/mL and HBcrAg < 3.5 log10 U/mL had a substantially higher HBsAg seroclearance rate (81.5%) compared with those meeting only one or two criteria (28.1%) or none (7.4%). CONCLUSIONS:Compared to baseline HBsAg alone, the combination of HBsAg, HBV RNA and HBcrAg can better identify NAs-suppressed CHB patients who are likely to achieve HBsAg seroclearance with Peg-IFN-α add-on therapy.

IntroductionThe endothelial activation and stress index (EASIX) has been proposed as a surrogate laboratory index reflecting endothelial activation and stress. This study aimed to evaluate the prognostic value of EASIX in patients with severe acute pancreatitis (SAP).MethodsThis retrospective observational study analyzed 340 SAP patients hospitalized between December 2015 and December 2023. EASIX was calculated as LDH (U/L) × creatinine (mg/dL) / platelet count (109/L). Regression analyses identified mortality predictors, which were incorporated into a prognostic model. Receiver operating characteristic (ROC) analysis compared the predictive performance of EASIX and the developed model.ResultsThe overall mortality rate was 28.82%. Non-survivors exhibited significantly elevated EASIX levels compared to survivors (p < 0.001). Multivariate analysis identified EASIX as an independent predictor of mortality (p = 0.004), along with age, APACHE II score, white blood cell count, and shock. The predictive model incorporating these factors achieved an AUC of 0.77 (sensitivity 0.73, specificity 0.70), outperforming EASIX alone (AUC = 0.70).ConclusionEASIX is a moderately effective prognostic marker in SAP, with performance comparable to APACHE II. The developed predictive model incorporating EASIX shows improved accuracy over EASIX alone for mortality risk stratification, but external validation is needed before clinical application.

G-protein-coupled receptors (GPCRs) play an important role in maintaining systemic glucose homeostasis by regulating insulin secretion, with protein kinase A (PKA) signalling serving as a key downstream effector. Our previous work identified specific expression of type IIB PKA in pancreatic beta cells. Based on these findings, we propose that type IIB PKA is involved in mediating the GPCR signalling in pancreatic beta cells. The glucagon-like peptide-1 (GLP-1) analogue liraglutide was administered to mice 30 min before glucose injection during an IPGTT, whereas the glucose levels and insulin levels were measured in wild-type and RIIβ-knockout mice. The isolated islets were subjected to both perifusion assay and static batch incubations following stimulation with liraglutide, glucagon and follicle-stimulating hormone (FSH). RNA-seq analysis was performed to identify molecular changes in islets with RIIβ ablation. Both western blotting and quantitative PCR were employed to quantify the gene expression. Whole-cell patch-clamp recordings were conducted to measure KATP and Ca2+ currents. Insulin granule morphology and abundance were evaluated by electron microscopy and flow cytometry using EGFP-labelled Syncollin, respectively. RIIβ-knockout mice exhibited impaired glucose tolerance and attenuated insulin secretion in response to liraglutide. Islets isolated from RIIβ-knockout mice showed reduced insulin secretion following liraglutide stimulation. Similarly, RIIβ-ablated islets displayed decreased insulin secretion in response to both glucagon and FSH. Further mechanistic studies revealed that RIIβ deficiency impaired liraglutide-mediated PKA signalling activation. Specifically, RIIβ-ablated beta cells exhibited reduced basal KATP channel activity and lack of liraglutide-mediated channel inhibition. Multiple voltage-gated Ca2+ channel genes were downregulated in RIIβ-ablated islets, leading to a mild reduction in basal Ca2+ current and a significant decrease following liraglutide treatment. RIIβ-knockout beta cells also exhibited reduced insulin granule size, decreased total granule number and fewer granules docked at the plasma membrane. Our results highlight type IIB PKA as a primary mediator of Gs-coupled receptor-potentiated insulin secretion, providing a new molecular framework for metabolic regulation research.

Heatstroke has high mortality, requiring early risk stratification. This study aimed to compare the predictive value of the reverse shock index multiplied by Glasgow Coma Scale score (rSIG) with shock index (SI), GCS, and qSOFA score for mortality in ICU heatstroke patients. The reverse shock index multiplied by Glasgow Coma Scale score (rSIG), calculated as GCS × (SBP / HR) using the first recorded values at ICU admission. This multicenter retrospective study included 671 heatstroke patients from 83 ICUs. Predictive performance was compared using receiver operating characteristic (ROC) curves. Independent risk factors were identified via logistic regression, and a nomogram was developed. Subgroup analysis was conducted to assess the consistency of the predictive value of rSIG. The mortality rate was 17.88%. rSIG demonstrated the highest predictive ability (AUC = 0.739), outperforming SI, GCS, and qSOFA. Prothrombin time, creatinine, lactate, and rSIG were independent predictors. The nomogram integrating these factors achieved an AUC of 0.80. Subgroup analysis confirmed the consistent predictive value of rSIG across various patient subgroups. The rSIG is a simple and effective early screening tool for rapid risk stratification in ICU patients with heatstroke. The predictive model combining rSIG with PT, Cr, and Lac further enhances prognostic accuracy, offering significant clinical utility.

BACKGROUND:Chronic hepatitis B virus (HBV) infection is an urgent public health issue, particularly in endemic regions of Asia and sub-Saharan Africa. Achieving hepatitis B surface antigen (HBsAg) clearance significantly reduces the risk of hepatocellular carcinoma. Pegylated interferon alpha (PegIFNα) is widely recognized as the preferred treatment. However, the efficacy of PegIFNα in different chronic HBV infection populations has not been systematically evaluated. This study aimed to assess the HBsAg clearance rate of PegIFNα in different chronic HBV infection populations and to identify influencing factors. METHODS:A systematic search was conducted in PubMed, EMBASE, the Cochrane Central Register of Controlled Trials, and the Web of Science from inception through September 28, 2022, with an update on December 6, 2023. Demographic characteristics, HBsAg clearance, and seroconversion rates were analyzed in different chronic HBV infection populations. Subgroup analyses and meta-regression were performed to explore factors influencing HBsAg clearance. RESULTS:Of the 4867 studies screened, 115 were included in the meta-analysis. The overall HBsAg clearance rate with PegIFNα-based therapy across different chronic HBV infection populations was 16% (95% confidence interval [CI]: 13-20%). The HBsAg clearance rates at the end of treatment (EOT) were 5% (95% CI: 4-7%) in treatment-naive chronic hepatitis B (CHB) patients, 21% (95% CI: 16-26%) in nucleos(t)ide analogues (NAs)-treated CHB patients, 57% (95% CI: 48-65%) in inactive HBsAg carriers, and 22% (95% CI: 10-37%) in children with CHB. The infection population was identified as a key factor influencing HBsAg clearance and seroconversion. CONCLUSIONS:PegIFNα significantly enhances HBsAg clearance in different chronic HBV infection populations, particularly in NAs-treated patients, inactive HBsAg carriers, and children with CHB, achieving higher rates than observed with spontaneous clearance and long-term NAs therapy. REGISTRATION:PROSPERO; No. CRD2024604070.

OBJECTIVE:To evaluate the feasibility of conducting a trial comparing targeted temperature management (TTM) at 35°C-37°C in intubated heatstroke patients, while collecting preliminary data on safety and clinical outcomes. DESIGN:Pilot multicenter randomized clinical trial (June to December 2024). SETTING:Ten tertiary ICUs in China. PATIENTS:Thirty-five intubated adults (18 yr or older) with heatstroke meeting predefined diagnostic criteria. Key exclusions: nonenvironmental hyperthermia, expected death within 24 hours, or contraindications to temperature management. INTERVENTIONS:Patients were randomly assigned 1:1 to two TTM strategies. The therapeutic hypothermia group received protocolized rapid cooling using a combination of ice packs, precooled blankets, and ice-cold IV saline to achieve the target of 35.0°C within 2 hours, which was then maintained for 48 hours. The controlled normothermia group received conventional cooling measures (ice packs, 32°C blankets) only if body temperature exceeded 38.0°C, with the goal of maintaining core temperature between 36.5°C and 37.5°C. Shivering was managed according to a stepwise protocol, with a "lytic cocktail" (chlorpromazine, promethazine, and meperidine) available as rescue therapy for refractory shivering in both groups. MEASUREMENTS AND MAIN RESULTS:Recruitment rate was 83.7%, retention rate was 97.2%, and protocol adherence exceeded 88%. For clinical outcomes, no significant differences were observed in 28-day poor functional outcome (17.6% vs. 16.7%) or survival (82.4% vs. 83.3%). However, therapeutic hypothermia was associated with significantly higher rates of severe gastrointestinal injury (Acute Gastrointestinal Injury grade 3-4: 52.9% vs. 0%; p < 0.001) and arrhythmias (41.2% vs. 11.1%; p = 0.045). The lytic cocktail was required in 100% of hypothermia-group patients vs. 27.8% in the normothermia group (p < 0.001). CONCLUSIONS:This pilot study confirms the operational feasibility of a large-scale randomized clinical trial. However, therapeutic hypothermia was associated with significantly worse gastrointestinal injury and higher arrhythmia incidence, without evidence of neurologic or survival benefit. The universal requirement for pharmacological shivering control in the hypothermia group raises additional safety considerations. Based on current evidence, this strategy should not be routinely adopted in ICU heatstroke management.

As a major by-product of juice processing, pomegranate peel holds significant valorization potential in sustainable food industries. However, conventional complete carbonization for adsorbent production destroys its bioactivity. This study proposes an innovative strategy based on controlled thermal processing to convert pomegranate peel into a novel solid food ingredient with integrated antioxidant functionality. Effects of different temperatures and durations on the phenolic composition, in vitro antioxidant activity, and safety (benzo[a]pyrene content) of the processed material were systematically investigated. The results showed that processing at 200 °C for 10 min yielded the optimal antioxidant activity, strongly linked to punicalagin enrichment. Subsequently, delayed luminescence was introduced as a process analytical tool. The key parameter Y0 (representing initial photon intensity) exhibited strong correlations with both punicalagin content and antioxidant activity, indicating its potential as a rapid, non-destructive indicator to monitor the evolution of key functional components during thermal processing. This work establishes a scientific foundation for intelligently converting pomegranate peel into a value-added food ingredient via a synergistic approach including controlled heating, targeted phytochemical regulation, and exploration of a physical signal indicator. Subject to independent validation, this exploratory indicator holds promise for supporting quality assessment in similar thermal processing applications.

OBJECTIVE:To investigate the outcomes of abnormal glucose metabolism and its clinical characteristics in patients with Cushing's disease (CD) who achieved biochemical remission after surgery. METHODS:Patients diagnosed with CD who achieved biochemical remission and underwent regular follow-up after surgery were enrolled. Pre- and postoperative clinical datawere collected and analyzed. RESULT:151CD patients were included, of whom 80 (53 %) had preoperative abnormal glucose metabolism, including 56 with diabetes mellitus (DM) and 24 with impaired glucose regulation (IGR). At one year after surgery, 57 patients exhibited improved glucose metabolism, accompanied by a significant reduction in the homeostasis model assessment of insulin resistance (HOMA-IR). Improvements were mainly observed at 3 and 6 months after surgery. At one-year after surgery, there were 20 patients with diabetes and 16 with IGR. Compared to those with NGT, these individuals exhibited a higher prevalence of hypertension, hyperlipidemia, fatty liver, and abnormal bone metabolism. CONCLUSION:CD patients demonstrated a high incidence of abnormal glucose metabolism. Notably, approximately two-thirds demonstrated improved glucose metabolism one year after curative surgery, with the greatest improvements observed at 3- to 6-month postoperative follow-up.

There is growing evidence highlighting the pivotal role of cellular metabolic adaptation in governing diverse immune responses, as well as the capacity of immune cells to alter metabolic preferences. In both scenarios, the prospect of leveraging bioactive compounds to induce metabolic reprogramming emerges as a novel adjuvant strategy for clinical immunotherapy. Rg1, a major active ginsenoside found in ginseng roots, has the potential to function as a glucocorticoid receptor agonist. Unraveling the intricate relationship between anti-inflammatory functions and the metabolic effects of ginsenosides and glucocorticoids may contribute to the identification of metabolic biomarkers associated with anti-inflammation. This research aims to determine endogenous metabolic response differences evoked by Rg1 and glucocorticoids underlying in vivo anti-inflammatory responses. The metabolic impact, particularly on primary metabolites, was assessed in zebrafish embryos using gas chromatography-mass spectrometry (GC-MS) in conjunction with metabolic pathways analysis via the KEGG pathway database. Our results indicated that Rg1 possesses a similar effect in alleviating inflammation in treating injured zebrafish as beclomethasone. The anti-inflammatory effects of Rg1 are achieved by inhibiting the neutrophils and macrophages toward the amputated edges and upregulating gene expression associated with pro-inflammatory cytokines. The anti-inflammatory effects of Rg1 also include changes in fatty-acid metabolism and downstream aromatic amino acids in the TCA cycle. Therefore, Rg1 may be a promising drug candidate for treating inflammatory responses and a valuable supplement for enhancing immune regulation.

BACKGROUND:Overactive bladder (OAB) is a common disorder, particularly in women, and its symptoms, including urgency, frequency, and nocturia, can significantly affect quality of life. The cardiometabolic index (CMI) is a novel metabolic risk indicator that has been receiving more attention lately. This study investigated the association between CMI and OAB in adult women. METHODS:A cross-sectional analysis was performed using data from the National Health and Nutrition Examination Survey (NHANES) covering the years 2007 to 2018, including 6323 female participants. CMI was calculated based on waist-to-height ratio, triglyceride, and HDL cholesterol levels, while OAB was assessed using the overactive bladder symptom score (OABSS). The association between CMI and OAB was evaluated through multivariate logistic regression, generalized additive models (GAM), smoothing curve fitting, and subgroup analysis. We finally included male participants for sensitivity analysis. RESULTS:A significant positive association was found between female CMI and OAB prevalence (OR = 1.46, 95% CI: 1.29-1.65). When compared to the lowest CMI quartile (Q1), women in the highest CMI quartile were 70% more likely to have OAB (OR = 1.70, 95% CI: 1.42-2.04). Smoothed curve fitting analysis showed a linear association between CMI and OAB. Subgroup analysis revealed that the association between CMI and OAB was stronger in women aged 20-50 years as well as in women without hypertension. Sensitivity analysis confirmed the robustness of our result. CONCLUSION:CMI was significantly and positively associated with the prevalence of OAB, especially in women aged 20-50 years without hypertension. This finding provides a new perspective on metabolic risk management and may contribute to the early prevention and improvement of bladder function in women.

To develop new tools integrating host immune response and viral activity to predict Peg-IFNα therapy efficiency in nucleos(t)ide analogs (NUCs)-treated chronic hepatitis B (CHB) patients. This post-hoc study analyzed data from 758 NUCs-experienced, HBeAg-negative CHB patients with baseline HBsAg < 1500 IU/mL and undetectable serum HBV DNA who completed 48 weeks of Peg-IFNα add-on therapy in a prospective study. Clinical and biochemical data were collected every 12 weeks and evaluated for their predictive value of HBsAg seroclearance and seroconversion. Age, qHBsAg, and ALT levels at Week 12 were associated with both HBsAg seroclearance and seroconversion. The ASAP-12 score (ALT/[qHBsAg × Age] at Week 12), demonstrated strong discrimination for both endpoints (AUROCs: 0.802 [cut-off 0.07] and 0.787 [cut-off 0.12], respectively; p < 0.05). Patients with scores above the respective cut-offs had significantly higher cumulative probabilities of HBsAg seroclearance (63.4% vs. 17.8%, Log-rank test p < 0.001) and seroconversion (47.3% vs. 11.0%, Log-rank test p < 0.001). Higher ASAP-12 scores (β = 0.206, p = 0.006) independently correlated with elevated Week 48 HBsAb levels. The ASAP-12 score may serve as a useful tool to predict both HBsAg seroclearance and seroconversion at Week 48 of Peg-IFNα add-on therapy in NUCs-experienced CHB patients, supporting individualized therapeutic decisions.