ObjectiveTo provide a reference for the rational clinical use of cold Chinese medicines by sorting and analyzing their properties， flavors， meridian tropism， primary therapeutic indications， methods of administration， dosages， and precautions as recorded in the 2020 edition of Pharmacopoeia of the People's Republic of China （Chinese Pharmacopoeia）. MethodsCold Chinese medicines for internal and external use included in the 2020 edition of Chinese Pharmacopoeia were entered one by one， and their efficacy， properties， flavors， meridian tropism， methods of administration， dosages， and usage precautions were statistically classified and summarized to guide clinical medication use. ResultsA total of 259 cold Chinese medicines for internal use were included and categorized into 18 efficacy groups， mainly comprising heat-clearing drugs， water-excreting and dampness-draining drugs， and phlegm-resolving， cough- and asthma-relieving drugs. Their predominant flavors were bitter， sweet， and pungent， and they primarily entered the liver， lung， and stomach meridians. The main methods of administration included decocting first， grinding into powder for oral use， or preparing into pills or powders， with most dosages ranging from 9 to 15 g. A total of 83 cold Chinese medicines for external use were included， involving 16 efficacy categories. Their main flavors were bitter， sweet， and pungent， primarily entering the liver， lung， and large intestine meridians. The main external application methods were grinding into powder for topical use or preparing decoctions for fumigation and washing， with most dosages ranging from 9 to 15 g. Whether for internal or external use， cold Chinese medicines should be used with caution or contraindicated in pregnant women. ConclusionThe cold Chinese medicines included in the 2020 edition of the Chinese Pharmacopoeia are mainly suitable for patients with carbuncles， swellings， and coughs. However， in clinical practice， it is necessary to strictly follow the principles of syndrome differentiation and treatment， pay attention to administration methods and dosages， and use cold medicines rationally and effectively to improve clinical efficacy.

Stroke is one of the leading causes of disability and mortality worldwide. Research into its mechanisms and the development of therapeutic strategies heavily rely on animal models that accurately replicate the pathological features of human disease. An ideal animal model for stroke should not only reproduce the neurological deficits and pathological changes observed in clinical patients but also demonstrate good reproducibility and translational value. This review focuses on the preparation and evaluation methods of ischemic stroke animal models. Firstly, it elaborates on the selection criteria, advantages, and disadvantages of experimental animals, including rodents (rats, mice) and non-rodents (non-human primates, miniature pigs, rabbits, zebrafish). Secondly, it provides a detailed overview of the modeling principles, key procedures, and application scopes for ischemic stroke models and hemorrhagic stroke models. Furthermore, the review summarizes advances in the applications of emerging technologies—including gene editing [e.g., clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) gene editing], multimodal imaging (e.g., two-photon microscopy, photoacoustic imaging), artificial intelligence, optogenetics, 3D bioprinting, organoid models, and multi-omics–in model optimization, precise assessment, and mechanistic investigation. Finally, based on a systematic analysis of relevant domestic and international literature from 2019 to 2024, this review discusses model selection strategies based on research objectives, a multidimensional evaluation system encompassing behavioral, imaging, and molecular pathological assessments, and envisions future directions involving technological integration to achieve model precision and individualization. This article aims to provide a comprehensive methodological reference to help researchers select appropriate animal models of stroke according to specific scientific questions.

Objective To address the need for rapid review of automated organ-at-risk (OAR) contouring for head-and-neck cancer in online adaptive radiotherapy, this study used dosimetric indices as the reference standard to evaluate the suitability of geometric similarity metrics and to develop a rapid screening model that balances the risk of missed errors with review efficiency. Methods This retrospective study included 29 patients with head-and-neck radiotherapy, yielding 243 pairs of OAR contours (auto-generated vs. manual). Geometric similarity metrics, including the Dice similarity coefficient (Dice), the 95th percentile Hausdorff distance (HD95), and the maximum Hausdorff distance (HD100), were computed between the two contour sets. Using the dose distributions from clinical treatment plans, dosimetric differences between the two contour sets were calculated for key indices, including mean dose (D_mean) and maximum dose (D_max). Correlations between geometric metrics and dosimetric differences were analyzed. Dosimetric discrepancy events were defined as Y_3Gy using a threshold of 3 Gy. Within a univariable logistic regression triage framework, each geometric metric was used as an independent variable to estimate the probability of Y_3Gy. Discriminative performance was assessed using receiver operating characteristic (ROC) curves and precision-recall (PR) curves, with the area under the curve (AUC) including ROC-AUC and PR-AUC. Practical operating thresholds were determined via threshold sweeping. Results Geometric similarity metrics showed weak-to-moderate correlations with dosimetric differences; compared with maximum dose, correlations with mean dose differences were more consistent. Among the evaluated metrics, HD95 achieved the best classification performance for Y_3Gy. Threshold sweeping suggested that an HD95 threshold in the range of 4-9 mm can balance the risk of missed discrepancies with the efficiency of automated contour quality assurance (QA). Conclusion Several geometric similarity metrics demonstrated only weak-to-moderate associations with dosimetric differences. For head-and-neck OAR contour QA in this study, HD95 provided the best discriminative performance and can support rapid triage of automated contours, with a practical operating threshold range of 4-9 mm, potentially improving the efficiency of adaptive radiotherapy workflows.

Objective To address the need for rapid review of automated organ-at-risk (OAR) contouring for head-and-neck cancer in online adaptive radiotherapy, this study used dosimetric indices as the reference standard to evaluate the suitability of geometric similarity metrics and to develop a rapid screening model that balances the risk of missed errors with review efficiency. Methods This retrospective study included 29 patients with head-and-neck radiotherapy, yielding 243 pairs of OAR contours (auto-generated vs. manual). Geometric similarity metrics, including the Dice similarity coefficient (Dice), the 95th percentile Hausdorff distance (HD95), and the maximum Hausdorff distance (HD100), were computed between the two contour sets. Using the dose distributions from clinical treatment plans, dosimetric differences between the two contour sets were calculated for key indices, including mean dose (D_mean) and maximum dose (D_max). Correlations between geometric metrics and dosimetric differences were analyzed. Dosimetric discrepancy events were defined as Y_3Gy using a threshold of 3 Gy. Within a univariable logistic regression triage framework, each geometric metric was used as an independent variable to estimate the probability of Y_3Gy. Discriminative performance was assessed using receiver operating characteristic (ROC) curves and precision-recall (PR) curves, with the area under the curve (AUC) including ROC-AUC and PR-AUC. Practical operating thresholds were determined via threshold sweeping. Results Geometric similarity metrics showed weak-to-moderate correlations with dosimetric differences; compared with maximum dose, correlations with mean dose differences were more consistent. Among the evaluated metrics, HD95 achieved the best classification performance for Y_3Gy. Threshold sweeping suggested that an HD95 threshold in the range of 4-9 mm can balance the risk of missed discrepancies with the efficiency of automated contour quality assurance (QA). Conclusion Several geometric similarity metrics demonstrated only weak-to-moderate associations with dosimetric differences. For head-and-neck OAR contour QA in this study, HD95 provided the best discriminative performance and can support rapid triage of automated contours, with a practical operating threshold range of 4-9 mm, potentially improving the efficiency of adaptive radiotherapy workflows.

Objective To address the need for rapid review of automated organ-at-risk (OAR) contouring for head-and-neck cancer in online adaptive radiotherapy, this study used dosimetric indices as the reference standard to evaluate the suitability of geometric similarity metrics and to develop a rapid screening model that balances the risk of missed errors with review efficiency. Methods This retrospective study included 29 patients with head-and-neck radiotherapy, yielding 243 pairs of OAR contours (auto-generated vs. manual). Geometric similarity metrics, including the Dice similarity coefficient (Dice), the 95th percentile Hausdorff distance (HD95), and the maximum Hausdorff distance (HD100), were computed between the two contour sets. Using the dose distributions from clinical treatment plans, dosimetric differences between the two contour sets were calculated for key indices, including mean dose (D_mean) and maximum dose (D_max). Correlations between geometric metrics and dosimetric differences were analyzed. Dosimetric discrepancy events were defined as Y_3Gy using a threshold of 3 Gy. Within a univariable logistic regression triage framework, each geometric metric was used as an independent variable to estimate the probability of Y_3Gy. Discriminative performance was assessed using receiver operating characteristic (ROC) curves and precision-recall (PR) curves, with the area under the curve (AUC) including ROC-AUC and PR-AUC. Practical operating thresholds were determined via threshold sweeping. Results Geometric similarity metrics showed weak-to-moderate correlations with dosimetric differences; compared with maximum dose, correlations with mean dose differences were more consistent. Among the evaluated metrics, HD95 achieved the best classification performance for Y_3Gy. Threshold sweeping suggested that an HD95 threshold in the range of 4-9 mm can balance the risk of missed discrepancies with the efficiency of automated contour quality assurance (QA). Conclusion Several geometric similarity metrics demonstrated only weak-to-moderate associations with dosimetric differences. For head-and-neck OAR contour QA in this study, HD95 provided the best discriminative performance and can support rapid triage of automated contours, with a practical operating threshold range of 4-9 mm, potentially improving the efficiency of adaptive radiotherapy workflows.

The prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) is higher among individuals with inflammatory bowel disease (IBD) than in the general population. Emerging evidence indicates that the development of MASLD in patients with IBD may occur independently of traditional metabolic risk factors, suggesting a unique pathophysiological mechanism distinct from conventional MASLD pathways. Bile acids (BAs), which act as critical signaling molecules in enterohepatic circulation, play an essential role in maintaining gastrointestinal homeostasis through bidirectional gut–liver axis communication. These molecules are increasingly recognized as pivotal regulators in the progression of both MASLD and IBD. While previous studies have characterized the dynamics of BA in blood or fecal samples under both conditions, a comprehensive understanding of their metabolic profiles and the associated interactions within the gut–liver axis is still lacking. This review synthesizes current evidence from studies employing BA metabolomics to investigate IBD and MASLD. By focusing on BA signatures, we summarize conserved alterations between these two conditions and their potential mechanisms of disease progression. Our review advances understanding of BA-mediated pathways in IBD and MASLD, providing a foundation for assessing their roles in contributing to the pathogenesis of MASLD in patients with IBD.

OBJECTIVE To investigate the antidepressant effect and underlying mechanism of total triterpenes from Poriae Cutis （PCTT）. METHODS UPLC-Q-TOF-MS technology was adopted to analyze the chemical constituents of PCTT. Network pharmacology was applied to screen the antidepressant active ingredients， key targets and signaling pathways of PCTT， and molecular docking was performed to verify the binding capacity between potential active ingredients and core targets. In animal experiment， mice were intragastrically administered PCTT at doses of 80， 160 and 320 mg/kg for 14 consecutive days. Lipopolysaccharide was used to establish an acute depression mouse model. Subsequently， behavioral assays were conducted. The levels of serum inflammatory factors， hippocampal neurotransmitters and brain-derived neurotrophic factor （BDNF） were detected. Western blot and qPCR assays were adopted to validate the antidepressant mechanism of PCTT. RESULTS A total of 101 chemical constituents were identified in PCTT. Network pharmacology screened out 10 potential active ingredients （including poriacosone B， poriacosone A， pachymic acid， etc.）， six core targets [including tumor necrosis factor （TNF）， peroxisome proliferator-activated receptor， caspase-3， etc.]， as well as multiple signaling pathways including TNF and interleukin-17 （IL-17）. All 10 potential active ingredients exhibited strong binding affinity to the six core targets. Animal experimental results demonstrated that 320 mg/kg PCTT markedly increased the movement distance and movement speed of depression model mice （P＜0.05）， and shortened immobility time in tail suspension test and forced swimming test （P＜0.05）. PCTT reduced serum levels of IL-6， IL-1β and TNF-α， decreased hippocampal glutamate level； it also downregulated the relative mRNA expression of TNF-α， tumor necrosis factor receptor-2 （TNFR2）， phosphoinositide 3-kinase （PI3K） and protein kinase B （AKT）， as well as TNFR2 protein expression and the ratios of phosphorylated-PI3K/PI3K，phosphorylated-AKT/AKT in the prefrontal cortex. Meanwhile， PCTT elevated the levels of 5- hydroxytryptamine， dopamine and BDNF in the hippocampus. CONCLUSIONS PCTT exerts antidepressant effects possibly by regulating the TNF-α/PI3K/AKT signaling pathway to downregulate the expression of pro-inflammatory factors， thereby modulating the release of neurotransmitters and BDNF.

Objective To investigate the expression characteristics of c-MET protein in colorectal cancer (CRC) and its associations with clinicopathological parameters, MET gene amplification status, and prognosis, and to evaluate the concordance between immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH) detection strategies, thereby providing evidence for patient selection for MET-targeted therapy. Methods A total of 193 formalin-fixed paraffin-embedded (FFPE) tissue samples from CRC patients were collected. Immunohistochemistry (IHC) was used to detect c-MET protein expression, and fluorescence in situ hybridization (FISH) was performed to evaluate MET gene amplification status. The associations between c-MET protein expression and clinicopathological characteristics, including KRAS, NRAS, and BRAF mutation status, as well as progression-free survival (PFS), were analyzed. The concordance between IHC and FISH detection results was also evaluated. Results c-MET protein expression was significantly higher in tumor tissues than in adjacent normal tissues (P<0.05). Significant differences in c-MET expression were observed between primary tumors and liver or peritoneal/pelvic metastatic lesions (P<0.05). The proportion of high c-MET expression was significantly higher in KRAS-mutant patients than in KRAS wild-type patients (41.38% vs. 16.92%, P<0.05). The MET gene amplification rate was 8.29% (16/193), including clustered or diffuse amplification in 1.55% (3/193) and heterogeneous amplification in 6.74% (13/193). No MET exon 14 skipping mutation or amplification was detected by next-generation sequencing (NGS). Using an IHC H-Score≥150 as the threshold, the positive percent agreement (PPA) between IHC-detected c-MET protein expression and FISH-detected MET gene amplification was 100%. All clustered MET amplification regions exhibited diffuse strong c-MET expression (IHC 3+). No statistically significant association was observed between c-MET expression level and PFS (P>0.05). Conclusion High c-MET expression may represent a potential therapeutic target for KRAS-mutant CRC patients. An H-Score ≥150 is recommended as the initial screening threshold to rapidly identify patients suitable for MET-targeted therapy, with FISH testing when necessary. Diffuse strong c-MET expression (IHC 3+) shows high concordance with clustered MET gene amplification.

OBJECTIVE To establish the UPLC fingerprint and the method for multi-component content determination in Jingangteng capsules， and to evaluate its quality by combining chemical pattern recognition analysis. METHODS An UPLC method was established. Separation was performed on a Zorbax SB-C 18 Rapid Resolution HD column， with acetonitrile-0.1% formic acid as the mobile phase for gradient elution.Using the Similarity Evaluation System for Chromatographic Fingerprints of Traditional Chinese Medicines （2012 edition）， UPLC fi ngerprints were established for 10 batches of Jingangteng capsules， and similarity was evaluated. SPSS 22.0 and SIMCA 14.1 software were used to perform hierarchial-cluster analysis and orthogonal partial least squares discriminant analysis （OPLS-DA）， respectively. The same UPLC method was employed to determine the contents of chlorogenic acid， 3，5-dihydroxy-2-methylbenzoic acid-3- O -glucoside （M1）， caffeic acid， astilbin， oxyresveratrol， quercitrin and resveratrol in the 10 batches of samples. RESULTS A total of 17 common peaks were identified in UPLC fingerprints of the 10 batches of samples， of which 7 were identified as chlorogenic acid， M1， caffeic acid， astilbin， oxyresveratrol， quercitrin， and resveratrol. The similarities of 10 batches of samples ranged from 0.820 to 0.985. The results of hierarchial-cluster analysis showed that 10 batches of samples were grouped into four categories： S1-S4 formed one group， S5 and S6 formed another， S7， S8 and S10 formed a third， and S9 formed a fourth， consistent with the OPLS-DA results； the variable importance projection values for peaks 7， 10， 2， 16 （resveratrol）， 13 （oxyresveratrol）， 11， 6 （caffeic acid）， 5 （M1） and 15 （quercitrin） were ＞1. Quantitative analysis results showed that the contents of chlorogenic acid， M1， caffeic acid， astilbin， oxyresveratrol， quercitrin， and resveratrol were 1.650 8-4.213 7， 0.636 2-2.161 7， 0.031 0-0.086 5， 0.239 1-1.069 3， 0.211 9-1.104 0， 0.488 8-2.399 2， and 0.164 0-0.699 8 mg/g， respectively. CONCLUSIONS UPLC fingerprint and content determination methods established in this study are simple to operate， accurate， reliable and reproducible； when combined with chemical pattern recognition analysis， they can be used to evaluate the quality of Jingangteng capsules. Nine components， such as resveratrol， oxyresveratrol， caffeic acid， M1 and quercitrin， may serve as markers of quality variation.

Diabetic nephropathy （DN） is one of the most common and serious microvascular complications of diabetes mellitus and represents a major cause of chronic kidney disease progression and end-stage kidney disease， thereby constituting a major public health problem that adversely affects the prognosis and quality of life of patients with diabetes mellitus. The pathogenesis and progression of DN are complex and involve multiple pathological processes， including insulin resistance， inflammation， oxidative stress， lipid deposition， podocyte injury， and renal fibrosis. Although current clinical therapies can delay the progression of DN to some extent， their effectiveness remains limited by marked interindividual variability in therapeutic response and the difficulty of fully reversing renal injury. Therefore， further elucidation of the key molecular mechanisms underlying DN and the exploration of effective therapeutic strategies are of considerable importance. In recent years， with advances in the understanding of DN pathogenesis， peroxisome proliferator-activated receptor γ （PPARγ）， an important nuclear receptor transcription factor involved in the regulation of insulin resistance， inflammation， oxidative stress， and fibrotic processes， has attracted increasing attention for its role in the development and progression of DN. Traditional Chinese medicine （TCM）， characterized by multi-component， multi-target， and multi-pathway synergistic regulation， may ameliorate pathological processes including metabolic abnormalities， inflammation， oxidative stress， lipid deposition， and renal fibrosis in DN by targeting PPARγ and its associated signaling networks. This review systematically summarizes the mechanisms by which PPARγ and its related signaling pathways regulate DN and reviews recent advances in TCM interventions targeting the PPARγ signaling pathway in DN. Such TCM interventions encompass single herbs such as Coptidis Rhizoma， active constituents such as quercetin， astragaloside Ⅳ， and trigonelline， extracts of herbs such as Plantaginis Herba and Dendrobii Nobilis Caulis， and formulas such as Huangkui capsules， Shenshuaining granules， and Mudan granules. This review aims to provide a theoretical basis for the prevention and treatment of DN with TCM.