Based on spleen deficiency-phlegm dampness as the core pathogenesis of obesity， and integrating recent advances in modern medicine regarding the key role of immune inflammation in obesity， this paper proposes a multidimensional pathogenic network of "obesity-spleen deficiency-phlegm dampness-immune imbalance". Various traditional Chinese medicine （TCM） herbs that strengthen the spleen， regulate qi， and resolve phlegm and dampness can treat obesity by improving spleen-stomach transport and transformation， promoting water-damp metabolism， and regulating immune homeostasis. This highlights immune inflammation as an important entry point to elucidate the TCM concepts of "spleen deficiency-phlegm dampness" and the therapeutic principle of "strengthening the spleen and eliminating dampness to treat obesity". By systematically analyzing the intrinsic connection between "spleen deficiency generating dampness， internal accumulation of phlegm dampness" and immune dysregulation in obesity， this paper aims to provide theoretical support for TCM treatment of obesity based on dampness.

To summarize the distribution characteristics of human papillomavirus(HPV) infection types in patients with cervical squamous intraepithelial lesion(SIL) and cervical cancer(CC), and to explore the impact of HPV vaccination, HPV infection types, and general clinical data on different grades of cervical lesions.

Objective: To propose an improved method for constructing the internal quality control (IQC) framework for ELISA assays and validate its efficacy by statistically analyzing IQC data from nine blood center laboratories. Methods: 1) IQC data was collected from nine blood centers and analyzed using a domestic HBsAg ELISA detection kit as an example. 2) Differences between IQC values across batches within Blood Center 1 were assessed. 3) Statistical analyses were performed on batch usage, number of batches used, days of use, number of QC points, batch-specific means, and coefficients of variation (CV) across all nine centers. 4) Using the improved construction method for IQC framework, provisional and permanent frames were established for batches within Blood Center 1 and Blood Center 9, followed by outlier determination. Results: 1) Statistically significant differences were observed in IQC data between batches within Blood Center 1 (P<0.01). It is recommended that both the control material/reagents and the control chart framework be replaced simultaneously. 2) There were substantial differences among 9 blood centers regarding the control material/reagent lot numbers used, the number of QC runs per batch, and the QC values for identical lots. Therefore, individual laboratories should establish their own IQC chart frameworks. 3) The improved IQC framework construction method for ELISA assays is as follows: provisional frames are established via frame-shifting, using the pre-experimental mean and cumulative coefficient of variation (CV) from the preceding batch. For batches used >20 days with >20 QC points, permanent frames are constructed by aggregating in-control data accumulated over ≥20 days with ≥20 points to calculate cumulative mean and standard deviation. The provisional and permanent frames constructed by this method identified all 26 extreme outliers across Blood Centers 1 and 9 as out-of-control. Among the 218 general outliers, 10 were classified as normal by the provisional frames, while the remainder were designated as warnings or out-of-control. This method effectively monitors assay stability. Conclusion: Based on the statistical analysis of IQC practices across blood centers of varying scales, combined with the inherent characteristics of ELISA assays and the batch-to-batch instability of reagents/QC materials, it is recommended to reconstruct QC charts upon lot changes. The proposed method—utilizing frame-shifting for provisional frames and establishing permanent frames based on cumulative data—is applicable to blood center laboratories of differing sizes and effectively monitors the stability of the ELISA assay process.

Metabolic associated fatty liver disease (MAFLD) is fundamentally driven by an imbalance in hepatic fatty-acid flux: the influx of fatty acids exceeds the liver’s capacity for disposal, resulting in excessive hepatic lipid accumulation, predominantly in the form of triglycerides (TGs). The occurrence and progression of MAFLD depend on disordered regulation across multiple metabolic steps, including fatty-acid uptake, de novo lipogenesis (DNL), fatty-acid oxidation (FAO), and very low-density lipoprotein (VLDL) export. Forkhead box protein O1 (FOXO1) is a key transcriptional regulator within the hepatic network coordinating glucose and lipid metabolism. Under metabolic stress and insulin resistance (IR), FOXO1 expression is frequently increased, whereas its inhibitory phosphorylation is reduced. These changes enhance FOXO1 nuclear localization and transcriptional activity, thereby reprogramming the expression of genes related to metabolism in the liver. Because hepatic lipid deposition is the central pathological feature of MAFLD, the functional status of FOXO1 directly influences hepatic lipid homeostasis. Growing evidence suggests that FOXO1 can exert bidirectional, environment-dependent effects on hepatic lipid accumulation; however, the molecular basis for this functional switch remains incompletely understood. This review systematically summarizes the biological functions and regulatory mechanisms of FOXO1 and its roles in hepatic lipid metabolism, with a particular focus on its crosstalk with insulin signaling. FOXO1 expression is shaped by RNA modifications and epigenetic regulation mediated by non-coding RNAs. Its transcriptional output is precisely governed by post-translational modifications—such as phosphorylation and acetylation—as well as by coordinated nucleocytoplasmic shuttling. Notably, these regulatory patterns vary markedly across nutritional states, degrees of insulin resistance, and stages of disease. In the fed state, insulin/IGF-1 signaling activates the PI3K-AKT pathway, promoting the inhibitory phosphorylation of FOXO1 and facilitating additional modifications, including acetylation, methylation, and ubiquitination. Together, these events drive FOXO1 export from the nucleus and dampen its transcriptional activity, suppressing gluconeogenesis and constraining lipogenic programs. Conversely, during fasting or when insulin signaling is weakened, FOXO1 inhibition is relieved. FOXO1 accumulates in the nucleus, binds to DNA, and regulates the transcription of downstream target genes. Mechanistically, FOXO1 can aggravate hepatic lipid accumulation by activating genes involved in TG synthesis while repressing FAO-related pathways, thereby favoring storage over oxidation. However, under specific conditions, FOXO1 may also alleviate the hepatic lipid burden by promoting TG hydrolysis and enhancing VLDL secretion, thereby reducing the net hepatic lipid load. In addition, lipotoxic signals mediated by ceramides and diacylglycerols (Cer/DAG) activate atypical protein kinase C (aPKC), further exacerbating the disruption of the AKT-FOXO1 axis. This vicious cycle ultimately produces a metabolic paradox in which increased hepatic glucose output coexists with persistent, insulin-independent lipogenesis, accelerating MAFLD progression. Importantly, FOXO1 regulation is not uniform: during early metabolic overload, insulin-mediated suppression may remain effective, whereas in advanced insulin resistance, the loss of AKT control permits sustained FOXO1 activity. Such stage-dependent dynamics may help explain why FOXO1 can either promote steatosis or, in certain contexts, support programs that facilitate lipid turnover. Accordingly, interventions should be liver-specific and tuned to the disease stage, aiming to curb maladaptive FOXO1 signaling while preserving its capacity to promote triglyceride hydrolysis and VLDL secretion when advantageous. Overall, this review offers an important perspective on MAFLD pathogenesis, emphasizing FOXO1 as a potential therapeutic target and providing a theoretical basis for developing liver-specific, disease-course-dependent precision interventions.

Objective: To investigate the incidence, characteristics, and influencing factors of resolution discrepancies within the minipool (MP) testing model across Chinese blood station laboratories in 2024. Methods: A nationwide, multicenter, cross-sectional study was conducted, including 334 blood station laboratories that reported nucleic acid reactive data among enzyme immunoassay non-reactive samples. Of these, 296 laboratories adopted the pool resolution model, with a total of 12 536 273 samples tested. Systematic analysis was performed on resolution data, focusing on the MP-NAT reactivity rate, the pool resolution concordance rate, and the resolution discrepancy rate. Subgroup analyses were conducted based on reagent types, viral targets, and Ct values. Potential causes were further explored through laboratory surveys and re-examination of raw amplification curves. Results: In 2024, the national average MP-NAT reactivity rate was 0.15%. The overall pool resolution concordance rate was 57.86%, which showed a gradual decline as Ct values increased across all reagents. The national average resolution discrepancy rate was 0.081‱(102/12 536 273), with 17.91%(53/296) of laboratories reporting at least one discrepancy. Nine reagent types were associated with these events, exhibiting reagent-specific patterns. For Reagent A2, the predominant discrepancy was HBV reactive pools resolving as HIV (36.36%); for Reagent D1, HBV pools frequently resolved as HCV (38.89%); and for Reagent E, the most common pattern was HIV pools resolving as HBV (48.00%). These resolution discrepancies were strongly associated with high Ct values: the median pool Ct for HBV exceeded 38, while those for HCV and HIV both exceeded 40. Investigations across 16 laboratories revealed that most discrepant samples exhibited “tailing” amplification curves, with some cases linked to cross-contamination or reagent batch-specific issues. Conclusion: While the incidence of resolution discrepancies in the MP-NAT model remains low in China, variations exist across different reagents and laboratories. These discrepancies are closely associated with low viral load, reagent performance, and laboratory operational practices.

With the aging population and the widespread implementation of lung cancer screening programs, an increasing number of elderly patients are undergoing curative lung resection. Due to diminished physiological reserve and complex comorbidities, this demographic exhibits a significantly higher incidence of severe perioperative complications (defined as Clavien-Dindo grade≥Ⅲ), which adversely affects both perioperative safety and long-term prognosis. In recent years, the research paradigm has shifted from univariate analysis toward multidimensional risk integration and the development of predictive models. This article systematically reviews the key risk factors for severe perioperative complications in elderly lung cancer patients, encompassing biological aging processes, frailty and sarcopenia, cardiopulmonary and renal functional reserves, inflammatory-immune and coagulation status, and perioperative interventions. Furthermore, it traces the evolution of risk assessment tools from traditional regression models to machine learning models that integrate multimodal data. The review also discusses common challenges in this field, including the standardization of outcome definitions, external validation, calibration assessment, and clinical translation. Future efforts should prioritize the deep integration of predictive tools with clinical decision support systems to establish a closed-loop care pathway from risk identification to stratified intervention, thereby effectively reducing complication rates and enhancing surgical outcomes for elderly lung cancer patients.

Parkinson's disease(PD) is a neurodegenerative disorder characterized by the progressive degeneration of dopaminergic neurons in the substantia nigra and the accumulation of Lewy bodies. While conventional drugs like levodopa can improve early symptoms, their efficacy diminishes over time, and they may cause severe side effects. Traditional Chinese medicine(TCM), with its multi-target therapeutic approach, has shown unique advantages in PD treatment, particularly in slowing disease progression and improving clinical symptoms. The nuclear factor erythroid 2-related factor 2(Nrf2)/heme oxygenase-1(HO-1) signaling pathway plays a critical role in cellular antioxidation, anti-inflammation, and cellular repair mechanisms, which are crucial for neuroprotection against PD. Studies indicate that TCM regulates the Nrf2/HO-1 pathway to enhance neuronal antioxidative capacity, inhibit neuroinflammation, promote dopaminergic neuron repair and survival, and slow pathological progression. This review explores the neuroprotective role of the Nrf2/HO-1 pathway in PD patients, including alleviating oxidative stress, suppressing neuroinflammation, promoting neuronal repair, and regulating iron metabolism and autophagy. It also discusses the mechanisms by which TCM active ingredients(flavonoids, alkaloids, terpenes, saponins, polyphenols, etc.), single herbs(Cistanche deserticola, Uraria crinite, and Melissa officinalis, etc.), and formulas(Bushen Jianpi Decoction, Didang Decoction, and Gancao Yangyin Decoction, etc.) modulate the Nrf2/HO-1 pathway in PD treatment, providing a theoretical basis for the clinical application and new drug development of TCM in PD prevention and treatment.
Humans ; Parkinson Disease/genetics* ; NF-E2-Related Factor 2/genetics* ; Signal Transduction/drug effects* ; Drugs, Chinese Herbal/pharmacology* ; Animals ; Heme Oxygenase-1/genetics* ; Medicine, Chinese Traditional

PURPOSE: Intertrochanteric fracture (ITF) classification is crucial for surgical decision-making. However, orthopedic trauma surgeons have shown lower accuracy in ITF classification than expected. The objective of this study was to utilize an artificial intelligence (AI) method to improve the accuracy of ITF classification. METHODS: We trained a network called YOLOX-SwinT, which is based on the You Only Look Once X (YOLOX) object detection network with Swin Transformer (SwinT) as the backbone architecture, using 762 radiographic ITF examinations as the training set. Subsequently, we recruited 5 senior orthopedic trauma surgeons (SOTS) and 5 junior orthopedic trauma surgeons (JOTS) to classify the 85 original images in the test set, as well as the images with the prediction results of the network model in sequence. Statistical analysis was performed using the SPSS 20.0 (IBM Corp., Armonk, NY, USA) to compare the differences among the SOTS, JOTS, SOTS + AI, JOTS + AI, SOTS + JOTS, and SOTS + JOTS + AI groups. All images were classified according to the AO/OTA 2018 classification system by 2 experienced trauma surgeons and verified by another expert in this field. Based on the actual clinical needs, after discussion, we integrated 8 subgroups into 5 new subgroups, and the dataset was divided into training, validation, and test sets by the ratio of 8:1:1. RESULTS: The mean average precision at the intersection over union (IoU) of 0.5 (mAP50) for subgroup detection reached 90.29%. The classification accuracy values of SOTS, JOTS, SOTS + AI, and JOTS + AI groups were 56.24% ± 4.02%, 35.29% ± 18.07%, 79.53% ± 7.14%, and 71.53% ± 5.22%, respectively. The paired t-test results showed that the difference between the SOTS and SOTS + AI groups was statistically significant, as well as the difference between the JOTS and JOTS + AI groups, and the SOTS + JOTS and SOTS + JOTS + AI groups. Moreover, the difference between the SOTS + JOTS and SOTS + JOTS + AI groups in each subgroup was statistically significant, with all p < 0.05. The independent samples t-test results showed that the difference between the SOTS and JOTS groups was statistically significant, while the difference between the SOTS + AI and JOTS + AI groups was not statistically significant. With the assistance of AI, the subgroup classification accuracy of both SOTS and JOTS was significantly improved, and JOTS achieved the same level as SOTS. CONCLUSION In conclusion, the YOLOX-SwinT network algorithm enhances the accuracy of AO/OTA subgroups classification of ITF by orthopedic trauma surgeons.
Humans ; Hip Fractures/diagnostic imaging* ; Orthopedic Surgeons ; Algorithms ; Artificial Intelligence

OBJECTIVE: To investigate possible associations between physical function assessment scales, such as Short Physical Performance Battery (SPPB) and Berg Balance Scale (BBS), with all-cause mortality in acute decompensated heart failure (ADHF) patients. METHODS: A total of 108 ADHF patients were analyzed from October 2020 to October 2022, and followed up to May 2023. The association between baseline clinical characteristics and all-cause mortality was analyzed by univariate Cox regression analysis, while for SPPB and BBS, univariate Cox regression analysis was followed by receiver operating characteristic curves, in which the area under the curve represented their predictive accuracy for all-cause mortality. Incremental predictive values for both physical function assessments were measured by calculating net reclassification index and integrated discrimination improvement scores. Optimal cut-off value for BBS was then identified using restricted cubic spline plots, and survival differences below and above that cut-off were compared using Kaplan-Meier survival curves and the log-rank test. The clinical utility of BBS was measured using decision curve analysis. RESULTS: For baseline characteristics, age, female, blood urea nitrogen, as well as statins, angiotensin-converting enzyme inhibitors, angiotensin II receptor blockers, or angiotensin receptor-neprilysin inhibitors, were predictive for all-cause mortality for ADHF patients. With respect to SPPB and BBS, higher scores were associated with lower all-cause mortality rates for both assessments; similar area under the curves were measured for both (0.774 for SPPB and 0.776 for BBS). Furthermore, BBS ≤ 36.5 was associated with significantly higher mortality, which was still applicable even adjusting for confounding factors; BBS was also found to have great clinical utility under decision curve analysis. CONCLUSIONS BBS or SPPB could be used as tools to assess physical function in ageing ADHF patients, as well as prognosticate on all-cause mortality. Moreover, prioritizing the improvement of balance capabilities of ADHF patients in cardiac rehabilitation regimens could aid in lowering mortality risk.

Objective To investigate the sputum metabolic profiles of patients with occupational coal workers' pneumoconiosis (CWP) by an untargeted metabolomics method, and to identify relevant differential metabolic pathways and potential biomarkers. Methods A total of 12 male patients with stage Ⅰ CWP were selected as the CWP group, and 16 healthy male individuals were selected as the control group, using a judgmental sampling method. Sputum metabolites of individuals in both groups were detected to perform non-targeted metabolomic analysis using the ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. Differential metabolites (DMs) and their pathways were screened using principal component analysis, partial least squares discriminant analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Potential biomarkers were analyzed and identified via the receiver operating characteristic curve (ROC). Results There were apparent metabolic alterations observed in sputum of CWP patients compared with healthy controls. In the positive ion mode, a total of 42 DMs were identified in sputum from CWP patients, including 19 downregulated and 23 upregulated metabolites. In the negative ion mode, a total of 25 DMs were identified in sputum from CWP patients, including 16 downregulated and 9 upregulated metabolites. KEGG enrichment analysis of sputum from CWP patients showed that seven DMs pathways were enriched in ABC transporters, histidine metabolism, phenylalanine metabolism, arachidonic acid metabolism, linoleic acid metabolism, purine metabolism, and oxidative phosphorylation, involving 26 DMs. ROC analysis indicated that 16(R)-hydroxyarachidonic acid, pyrophosphate, and 2-hydroxyphenylacetate of these 26 DMs may serve as potential biomarkers for CWP. Conclusion Sputum metabolomic profiles were altered in CWP patients compared with healthy controls. The potential biomarkers of CWP prevention and treatment are 16(R)-hydroxyarachidonic acid, pyrophosphate, and 2-hydroxyphenylacetate.