ObjectiveTo investigate the effects of Huanglian Jiedutang （HLJDT） on cognitive function in mice with ischemic stroke （IS） and to elucidate whether its neuroprotective effects are mediated by inhibition of the nuclear factor-κB （NF-κB） signaling pathway and subsequent suppression of NF-κB-regulated neuronal apoptosis. MethodsAn IS model was established using middle cerebral artery occlusion （MCAO）. Sixty C57BL/6J mice were randomly assigned to five groups （n =12 per group）， i.e.， sham operation， model， HLJDT low-dose （3.9 g·kg^-1·d^-1）， HLJDT high-dose （7.8 g·kg^-1·d^-1）， and Ginkgo biloba extract （GBE， 31.2 mg·kg^-1·d^-1）. Post-operatively， neurological deficit scores （Longa score）， cerebral infarct volume assessed by 2，3，5-triphenyltetrazolium chloride （TTC） staining， and brain water content were evaluated. Learning and memory were assessed using new object recognition （NOR） and fear conditioning （FC） tests. Hippocampal pathology was examined via hematoxylin and eosin （HE） staining. Immunofluorescence detected expression of glial fibrillary acidic protein （GFAP， astrocyte marker）， cellular oncogene Fos （c-Fos， neuronal activation marker）， and glutamate decarboxylase 65 （GAD65）. Western blot measured nuclear factor-κB inhibitor protein α （IκBα）， phosphorylated IκBα （p-IκBα）， NF-κB p65， phosphorylated NF-κB p65 （p-NF-κB p65）， ionic calcium binding adapter molecule 1 （Iba-1）， tumor necrosis factor （TNF）-α， interleukin （IL）-1β， and apoptosis-related proteins， such as cleaved cysteinyl aspartate-specific protease 3 （Caspase-3）， B-cell lymphoma 2 （Bcl-2）， and Bcl-2-associated X protein （Bax）. Real-time quantitative PCR （Real-time PCR） was used to assess mRNA levels of Iba-1， TNF-α， IL-1β， NF-κB p65， cleaved Caspase-3， Bax， and Bcl-2. ResultsCompared with the sham group， the model group exhibited significantly increased neurological deficit scores， brain water content， and cerebral infarct volume （P<0.01）. Hippocampal CA1 neurons were disorganized， showing nuclear pyknosis and karyolysis. NOR exploration time and FC freezing time were significantly reduced （P<0.01）. GFAP and c-Fos expression were increased， while GAD65 expression was decreased （P<0.01）. Cleaved Caspase-3 and Bax were upregulated， Bcl-2 was downregulated， and the Bax/Bcl-2 ratio was elevated （P<0.01）. Expression levels of p-IκBα， p-NF-κB p65， IL-1β， TNF-α， and Iba-1 were significantly increased （P<0.01）. Compared with the model group， HLJDT high-dose， low-dose， and GBE groups showed significant improvements in all parameters （P<0.01）. Among them， the HLJDT high-dose group showed the most pronounced neuronal structural recovery and superior performance in NOR and FC tests （P<0.01）. In this group， GFAP and c-Fos decreased， GAD65 increased （P<0.01）， apoptosis-related protein expression was reversed， and NF-κB signaling and related inflammatory factor expression were suppressed （P<0.01）. ConclusionHLJDT ameliorates cognitive dysfunction in mice after IS， potentially by inhibiting the NF-κB signaling pathway， thereby reducing neuroinflammation and hippocampal neuronal apoptosis.

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.

p21 (encoded by the CDKN1A gene) is a critical cell cycle regulatory protein endowed with versatile biological functions. In various sex hormone-related cancers, p21 exhibits a paradoxical dual role, capable of both inhibiting tumorigenesis and promoting cancer progression, exerting dual, often opposing, effects on cellular fate that are dictated by the specific context. The clinical targeting of p21 remains elusive, largely due to its functionally pleiotropic and context-dependent nature within intricate regulatory networks. During the initial, hormone-dependent phase of cancers like breast and prostate cancer, p21 expression and activity are largely governed by the transcriptional programs of estrogen or androgen receptor signaling. This hormonal regulation contributes to the control of tumor cell proliferation and underpins the initial efficacy of endocrine therapies. In contrast, as these diseases advance to late stages or evolve into non-hormone-dependent subtypes—exemplified by castration-resistant prostate cancer (CRPC) and specific forms of triple-negative breast cancer (TNBC)—these conventional hormonal control mechanisms often become dysfunctional or are entirely bypassed. This fundamental transition creates a critical therapeutic void, highlighting the urgent need to identify and exploit alternative molecular pathways to effectively target p21’s function. Promising strategies may include the precise modulation of its upstream transcriptional regulators, downstream effector proteins, or the intersecting parallel signaling networks that critically influence its activity. This review provides a systematic synthesis of the intricate and interconnected mechanisms that underpin the dual effects of p21 in sex hormone-related tumors. These mechanisms are categorized into three core, interrelated functional domains. (1) cell cycle regulation: p21 executes its canonical tumor-suppressive role by binding to and inhibiting cyclin-dependent kinases (CDKs) and by directly interacting with proliferating cell nuclear antigen (PCNA), thereby inducing cell cycle arrest, predominantly at the G1/S checkpoint; (2) apoptosis modulation: p21 exerts a highly context-dependent influence on programmed cell death, functioning either as a pro-apoptotic agent under severe genotoxic stress or as a pro-survival factor by inhibiting apoptosis through interactions with proteins like Bcl-2; (3) hormonal and signaling crosstalk: p21 is an integral node within broader cellular networks, engaging in direct physical interactions with hormone receptors(e.g., AR, ER) and participating in complex feedback loops with key oncogenic pathways, including PI3K/AKT, MAPK/ERK, and p53. Critically, the role of p21 is not static but highly dynamic. It can undergo a functional switch from tumor-suppressive to tumor-promoting in response to therapeutic pressures, metabolic alterations, or evolving tumor microenvironment cues. These adaptive shifts are frequently implicated in the development of therapy resistance and disease recurrence, particularly in advanced, hormone-resistant cancers. By synthesizing these insights, this review aims to establish a coherent theoretical framework to guide the future development of novel therapeutic strategies that target the p21 pathway. It underscores the necessity of moving beyond a simplistic, binary view of p21 and emphasizes the forthcoming challenges, such as the discovery of reliable biomarkers to predict its functional state and the rational design of context-specific pharmacological modulators to selectively harness its therapeutic potential.

ObjectiveTo explore the effect of oral sodium butyrate on skeletal muscle atrophy in CT26 tumor mice through the gut microbiota-skeletal muscle axis and its potential mechanism. MethodsSixty SPF BALB/c male mice aged 8 weeks were randomly divided into a normal control group (NC, n=18) and a ABX-depleted group (ABX, n=42). The ABX mice were pretreated with a quadruple antibiotic cocktail via oral gavage (0.2 ml per administration, once daily, 6 d per week, for 2 weeks), whereas NC received an equal volume of sterile water. The quadruple antibiotic cocktail consisted of metronidazole (1 g/L), vancomycin (0.5 g/L), ampicillin (1 g/L), and gentamicin (1 g/L). Following successful pretreatment, six mice from each group were randomly selected for gut microbiota sequencing analysis and designated as the Abx group and the NC0 group, respectively. Theremaining mice in ABX were subcutaneously inoculated in the dorsum with 0.2 ml of CT26 cell suspension (at a cell density of 1×10⁷/ml). Then these mice were randomly allocated into three subgroups: a control tumor bearing model group (0_NaB, n=12), a tumor-bearing model group receiving low-dose oral sodium butyrate (L_NaB, n=12), a tumor-bearing model group receiving high-dose oral sodium butyrate (H_NaB, n=12). And mice in NC were inoculated at the same site with 0.2 ml of normal saline. The administration dose for L_NaB was 0.3 g/(kg·d), that for H_NaB was 0.5 g/(kg·d), while NC and 0_NaB were given the same volume of normal saline (0.2ml per time, once daily, 6 d per week, for 4 weeks). The general condition of mice was monitored, and forelimb grip strength gastrocnemius muscle mass and its muscle fiber cross-sectional area were measured for each group. The structural changes in gut microbiota were assessed by 16S rRNA sequencing of cecal contents. Pathological alterations in the intestinal wall were examined via HE staining. Serum and gastrocnemius muscle levels of TNF‑α, IL-6, IL-1β, and LPS were quantified using ELISA. The protein expression of ZO-1 and occludin in the small intestine, as well as proteins associated with the TLR4/MyD88/NF-κB signaling pathway in the gastrocnemius muscle, were detected by Western blot analysis. Results(1) The alpha-diversity in Abx was significantly lower than that in NC0 (P<0.01), a significant decrease of the mass and muscle fiber cross-sectional area of the gastrocnemius (P<0.01), with the majority of gut microbiota being effectively depleted. (2) Compared with NC, the subcutaneous tumors of mice in 0_NaB were prominent, a significant increase of the mass and muscle fiber cross-sectional area of the gastrocnemius, accompanied by a significant decrease in body weight at the end of the 3th and 4th week (P<0.05), and a significant weakening of the forelimb grasping strength at the 5th and 6th week (P<0.01). Compared with 0_NaB, the tumor mass of mice in L_NaB and H_NaB showed a significant decreasing trend, and the grip strength of the forelimbs significantly increased at the 5th and 6th week (P<0.05, P<0.01). (3) Compared with 0_NaB, the Shannon and Observed species indices in α diversity of L_NaB and H_NaB were significantly increased (P<0.05). At the genus level, compared with 0_NaB, L_NaB exhibited a significant decrease in the relative abundance of Parasutterella (P< 0.01), while H_NaB showed significant reductions in the relative abundances of both Escherichia-Shigella and Parasutterella (P < 0.01). (4) Compared with 0_NaB, the small intestinal tissue structure in L_NaB and H_NaB was more intact, the infiltration of inflammatory cells was significantly reduced, and the capillaries were slightly dilated. The expression levels of ZO-1 and occludin proteins in L_NaB were significantly increased (P<0.01). (5) The LPS concentration in the gastrocnemius muscle and the protein expression levels of TLR4, MyD88, p-IκBα, and p-NF‑κB p65 in L_NaB and H_NaB were significantly lower than those in 0_NaB (P<0.05). The serum TNF‑α concentration in H_NaB and TNF-α concentration in the gastrocnemius muscle of the L_NaB and H_NaB were significantly lower than those in 0_NaB (P<0.05, P<0.01, P<0.01). ConclusionOral administration of NaB can improve gut microbiota α diversity, adjusting its composition, improving intestinal mucosal barrier function, reducing the LPS-induced pro-inflammatory response, and delaying skeletal muscle atrophy. The underlying mechanism may involve down regulation of TLR4/MyD88/NF-κB signaling in skeletal muscle.

This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

Objective To evaluate the safety and efficacy of a self-developed micro-normothermic machine perfusion (NMP) system (micro-perfusion device) for preserving isolated porcine limbs. Methods Five healthy Landrace pigs were selected, and their left and right forelimbs were randomly divided into the NMP group and static cold storage (SCS) group. The NMP group was perfused with the self-developed micro-perfusion device and polymerized hemoglobin perfusate for 32 hours at normothermia, while the SCS group was preserved at 4 ℃. Hemodynamic parameters such as perfusion pressure and flow were monitored. The pH value, partial pressure of oxygen (PO₂), lactic acid (Lac), creatine kinase (CK) and lactate dehydrogenase (LDH) in the perfusate were measured. Hematoxylin-eosin staining was used to assess the muscle tissue structure, terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling was employed to evaluate muscle cell apoptosis, and immunohistochemistry staining was applied to detect the expressions of tumor necrosis factor (TNF)-α and interleukin (IL)-6. A mixed-effects model was used to analyze the effects of time and treatment methods on tissue structure, cell apoptosis and inflammatory factors. Results The device could stably maintain a perfusion pressure of (69±15) mmHg and a flow rate of (117±42) mL/min. The pH value and electrolytes of the perfusate were generally stable, with PO₂ maintained at a high level. Lac was maintained at 5.38(3.81, 6.45) mmol/L, while CK and LDH increased over time. After 32 hours of perfusion in the NMP group, both the myocyte spacing and apoptosis rate were better than those in the SCS group. Mixed-effects model analysis showed that there were statistically significant differences in the effects of NMP treatment and SCS treatment on myocyte spacing and apoptosis rate per unit time (both P < 0.05). There were no statistically significant differences in TNF-α and IL-6 between the two groups, and mixed-effects model analysis showed no statistically significant differences in the effects of NMP treatment and SCS treatment on TNF-α and IL-6 per unit time (both P > 0.05). Conclusions The micro-perfusion device used in this study may achieve 32-hour normothermic preservation in a porcine limb amputation model, maintain basic metabolism and ionic homeostasis, reduce muscle structural damage and cell apoptosis without inducing additional inflammatory responses. This technology is expected to significantly extend the time window for replantation of amputated limbs in disaster rescue and long-distance transportation, providing an important technical basis for clinical translation and subsequent replantation research.

This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

Objective To investigate the therapeutic effect of Huangkui capsules on targeted drug-related proteinuria in patients with hepatocellular carcinoma (HCC). Methods A retrospective analysis was conducted on clinical data of HCC patients with targeted drug-related proteinuria from June 2023 to December 2024 at Zhongshan Hospital, Fudan University. According to the treatment plan, patients were divided into the conventional treatment group and the Huangkui combination treatment group (Huangkui capsules combined with conventional treatment), and the clinical efficacy between the two groups was compared. The logistic regression analysis was used to identify the main factors affecting treatment efficacy. Results The Huangkui combination treatment group (n＝29) showed a significantly higher overall effective rate (79.3% vs 42.3%, P＝0.005), and an earlier proteinuria improvement (median time: 3 months vs 6 months, P＝0.008) than the conventional treatment group (n＝26) . The multivariate logistic regression analysis showed angiotensin-converting enzyme inhibitor (ACEI) or angiotensin Ⅱ receptor blocker (ARB) using (OR＝0.190, 95%CI 0.045-0.808, P＝0.025), targeted drug adjustment (OR＝0.132, 95%CI 0.030-0.581, P＝0.007), and Huangkui capsules using (OR＝0.168, 95%CI 0.039-0.730, P＝0.017) were protective factors for treatment efficacy of targeted drug-related proteinuria. Conclusions On the basis of conventional treatment, additive treatment with Huangkui capsules can alleviate targeted drug-related proteinuria faster and more effectively in HCC patients.

BACKGROUND:Rapid and accurate segmentation of brain tissue in medical images is of great significance for three-dimensional biomechanical modeling and diagnosis of craniocerebral injuries.Currently,artificial intelligence(AI)-based baseline models exhibit excellent generalization capabilities on large-scale datasets.However,due to the specificity and complexity of craniocerebral tissues,these models have certain limitations in their application to craniocerebral tissue segmentation.Additionally,the scarcity of craniocerebral tissue samples makes it difficult for baseline models to achieve precise segmentation results through fine-tuning.OBJECTIVE:To construct a craniocerebral tissue segmentation model based on texture feature retrieval enhancement to improve segmentation accuracy under a small number of samples.METHODS:Segment Anything in Medical Images(MedSAM)model was selected as the basic framework,and texture features were combined with deep learning to build a brain tissue segmentation model based on texture feature retrieval enhancement(DP-MedSAM).Dice Coefficient and mean intersection over union(MIoU)were selected to evaluate the efficiency of image segmentation results.In comparison with the original MedSAM model,the ablation experiment systematically evaluated the influence of key components on the model performance.The sensitivities of MedSAM,the Segment Anything Model(SAM)for medical image segmentation(SAM-Med2D)and DP-MedSAM in the mandible,left optic nerve,and left parotid gland were compared.RESULTS AND CONCLUSION:(1)By verifying the impact of the number of point prompts on segmentation results on the HaN-Seg dataset,the experimental results indicated that the optimal Dice score was achieved with the addition of three points.(2)DP-MedSAM demonstrated performance improvements compared with MedSAM and SAM-Med2D on two datasets(HaN and Public Domain Database for Computational Anatomy).Especially on the Public Domain Database for Computational Anatomy dataset,in terms of the MIoU metric,DP-MedSAM outperformed MedSAM by 6.59％and SAM-Med2D by 37.35％;in terms of the Dice metric,DP-MedSAM outperformed MedSAM and SAM-Med2D by 4.34％and 25.32％,respectively.(3)The ablation experiment results showed that removing the texture feature extraction module in the DP-MedSAM model,relying solely on original image features,led to a significant decrease in results on the test set.Furthermore,removing the vector cache database and its retrieval enhancement function from the model,which deprived the ability of the model to perform similarity retrieval using an external knowledge base,further reduced model performance.(4)Under conditions of limited data resources,the DP-MedSAM model outperformed the other two models in all evaluation metrics.The DP-MedSAM model performed excellently when processing simple and moderately difficult samples,demonstrating a clear advantage over the other two models and indicating good generalization ability.Processing the fine structures of difficult samples placed higher demands on the model's segmentation capabilities.Although the performance of the DP-MedSAM model declined slightly,it still outperformed the other two models.(5)This study proposes an innovative craniocerebral tissue segmentation model,DP-MedSAM,which improves the baseline model's performance in capturing local details and global structural information in medical images by introducing target region texture feature extraction.Through vector similarity retrieval technology,DP-MedSAM can retrieve the feature vector most similar to the current target region from a pre-constructed vector database,providing more precise guiding information for the segmentation process.

Objective To evaluate the predictive value of different machine learning models constructed in a multicenter environment for potential organ donors and verify their clinical application feasibility. Methods The study included 2 000 inpatients admitted to five domestic tertiary hospitals from January 2020 to December 2023, who met the criteria for potential organ donation assessment. They were randomly divided into a training set and an internal validation set (7∶3). Another 300 similar patients admitted to the First Affiliated Hospital of Harbin Medical University from January 2024 to April 2025 were included as an external validation set. The area under the curve (AUC), sensitivity, specificity, accuracy and F1-score of three models were compared, and the consistency of the potential organ donor determination process was tested. Multivariate logistic regression analysis was used to identify predictive factors of potential organ donors. Decision curve analysis (DCA) was employed to verify the resource efficiency of each model, and the threshold interval and intervention balance point were assessed. Results Apart from age, there were no significant differences in other basic characteristics among the centers (all P>0.05). The consistency of the potential organ donor determination process among researchers in each center was good [all 95% confidence interval (CI) lower limits >0]. In the internal validation set, the XGBoost model had the best predictive performance (AUC=0.92, 95% CI 0.89-0.94) and the best calibration (P=0.441, Brier score 0.099). In the external validation set, the XGBoost model also had the best predictive performance (AUC=0.91, 95% CI 0.88-0.94), outperforming logistic regression and random forest models. Multivariate logistic regression showed that mechanical ventilation had the greatest impact (odds ratio=2.06, 95% CI 1.54-2.76, P<0.001). DCA indicated that the XGBoost model had the highest net benefit in the threshold interval of 0.2-0.6. The “treat all” strategy only had a slight advantage at extremely low thresholds. The recommended threshold interval, which balances intervention costs and clinical benefits, considers ≥50% positive predictive value (PPV) and ≤50 referrals per 100 high-risk patients. Conclusions The XGBoost model established in a multicenter environment is accurate and well-calibrated in predicting potential organ donors. Combined with DCA, it may effectively guide the timing of clinical interventions and resource allocation, providing new ideas for the assessment and management of organ donation after brain death.