ObjectiveTo decipher the mechanism by which Zuoguiwan （ZGW） treat hyperthyroidism in rats with kidney-Yin deficiency based on the dopamine receptor D4 （DRD4）/nicotinamide adenine dinucleotide phosphate （NADPH） oxidase 4 （NOX4） signaling pathway. MethodsThe rat model of kidney-Yin deficiency was induced by unilateral intramuscular injection of dexamethasone （0.35 mg·kg^-1）. After successful modeling， the rats were randomized into model， methimazole （positive control， 5 mg·kg^-1）， low-， medium-， and high-dose （1.85， 3.70， 7.40 g·kg^-1， respectively） ZGW， and normal control groups. After 21 days of continuous gavage， the behavioral indexes and body weight changes of rats were evaluated. The pathological changes of the renal tissue were observed by hematoxylin-eosin staining. The serum levels of thyroid hormones ［triiodothyronine （T₃）， thyroxine （T₄）， thyroid-stimulating hormone （TSH）］， renal function indexes ［serum creatine （Scr） and blood urea nitrogen （BUN）］， energy metabolism markers ［cyclic adenosine monophosphate （cAMP） and cyclic guanosine monophosphate （cGMP）］， and oxidative stress-related factors ［superoxide dismutase （SOD）， malondialdehyde （MDA）， and NADPH）］ were measured by enzyme-linked immunosorbent assay （ELISA）. Western blot was employed to analyze the expression of DRD4， NOX4， mitochondrial respiratory chain complex proteins ［NADH：ubiquinone oxidoreductase subunit S4 （NDUFS4） and cytochrome C oxidase subunit 4 （COX4）］， and inflammation-related protein ［tumor necrosis factor-alpha （TNF-α）， interleukin-6 （IL-6）， p38 mitogen-activated protein kinase （MAPK）］ pathway in the renal tissue. ResultsCompared with the normal group， the model group showed mental malaise， body weight decreases （P<0.01）， inflammatory cell infiltration in the renal tissue， a few residual parotid glands in the thyroid， elevations in serum levels of T₃， T₄， Scr， BUN， cAMP， cAMP/cGMP， MDA， and NADPH （P<0.01）， down-regulation in protein levels of TSH， SOD， and DRD4 （P<0.05， P<0.01）， and up-regulation in expression of NOX4， p-p38 MAPK/p38 MAPK， and inflammatory factors （P<0.01）. Compared with the model group， ZGW increased the body weight （P<0.05， P<0.01）， reduced the infiltration of renal interstitial inflammatory cells， restored the thyroid structure and follicle size， lowered the serum levels of T₃， T₄， Scr， BUN， cAMP， cAMP/cGMP， MDA and NADPH （P<0.05， P<0.01）， up-regulated the expression of TSH， SOD and DRD4 （P<0.05， P<0.01）， and down-regulated the expression of NOX4， p-p38 MAPK/p38 MAPK， and inflammatory factors （P<0.05， P<0.01）. Moreover， high-dose ZGW outperformed methimazole （P<0.05）. ConclusionBy activating DRD4， ZGW can inhibit the expression of NOX4 mediated by the p38 MAPK pathway， reduce oxidative stress and inflammatory response， thereby ameliorating the pathological state of hyperthyroidism due to kidney-Yin deficiency. This study provides new molecular mechanism support for the clinical application of ZGW.

With the rapid advancement of artificial intelligence technology, computational pathology has evolved from task-specific models to foundation models capable of supporting multiple organs, diseases, and downstream tasks. However, existing methods remain limited to single-pass inference on images and are unable to fully emulate the complex diagnostic processes encountered in real-world clinical settings. In recent years, large language models have driven the development of agent-based paradigms. By leveraging capabilities such as navigation, reasoning, and tool use, these frameworks offer a novel approach for modeling complex diagnostic workflows. Framed within the context of clinical pathology diagnostic processes, this article systematically reviews the key challenges and advances in computational pathology research across three stages: preliminary overview, diagnostic analysis, and report writing, and discusses the current functional roles and implementation approaches of agent-based technologies at each stage. Although validation scenarios in existing studies remain limited, the core modules and methods required to construct a pathology diagnostic agent system are largely in place. Agent-related technologies are expected to facilitate the development of a clinically deployable intelligent assistance platform for pathology diagnosis.

Pathology diagnosis is the "gold standard" for clinical disease diagnosis and treatment. Intelligent pathology image analysis has significant clinical value in improving diagnostic efficiency and ensuring consistency. This paper systematically reviews the core multiple instance learning paradigm for whole slide image analysis, and elaborates the pretraining system, core functional branches and latest advances of pathology foundation models. Taking clinical usability as the core evaluation dimension, it establishes a multi-dimensional evaluation framework, analyzes the clinical translation potential of different technical routes, and points out the core contradiction of "excellent laboratory performance but insufficient clinical usability" in current pathology foundation models. It further dissects the key clinical translation bottlenecks of pathology foundation models, outlines future application and development directions, and provides a reference for technological research and development as well as clinical translation in computational pathology.

Objective To screen for key genes and important pathways common for different etiologies of acute kidney injury(AKI)by pathway-associated deep neural network and multiple machine learning algorithms.Methods AKI microarray datasets GSE30718,GSE37838,GSE53769,GSE108113,GSE125779,GSE99325,and GSE174020 downloaded from the Gene Expression Omnibus(GEO)database were merged,including 60 kidney samples from AKI patients and 79 kidney samples from healthy controls.They were divided(8∶2)into training sets and test sets,and were used to train and evaluate pathway-associated deep neural network and 4 machine learning algorithms,including least absolute shrinkage and selection operator(LASSO),random forest(RF),support vector machine-recursive feature elimination(SVM-RFE),and extreme gradient boosting(XgBoost),to screen for common key genes and pathways of different etiologies of AKI.The downloaded datasets GSE99340 and GSE1563 were merged,including 43 kidney samples from AKI patients and 36 kidney samples from healthy controls,which were used as external validation sets for LASSO model and nomogram performance test based on the final screened genes.The pathway-associated deep neural network and machine learning algorithms were evaluated using receiver operating characteristic curves,precision,recall,accuracy,and F1-score.The immune cell infiltration characteristics were explored in AKI via cell-type identification by estimating relative subsets of RNA transcripts(CIBERSORT),and Pearson correlation coefficients were used to evaluate the correlation between the final screened common key genes and immune cell infiltration levels.Results The pathway-associated deep neural network trained by 5-fold cross validation produced an area under curve(AUC)of 0.914 5±0.007 0,a precision of 0.750 0±0.044 0,a recall of 0.923 1±0.048 0,an accuracy of 0.838 7±0.016 0,and an F1-score of 0.827 6±0.020 0 in the test set,yielding a robust and highly accurate classification performance for AKI,and identified key pathways and a subset of candidate genes.The 4 machine learning algorithms all achieved high discriminative performance for AKI in the test set with AUC≥0.860,precision≥0.750,recall≥0.800,and F1-score≥0.774,and screened 7 common key genes for AKI with different etiologies,including CD86,C-X-C motif chemokine ligand 10(CXCL10),dynamin 2(DNM2),proto-oncogene FOS,transcription factor 12(TCF12),VGF nerve growth factor inducible(VGF),and A kinase anchoring protein 5(AKAP5).Based on the final screened common key genes,the LASSO model had an AUC of 0.940 4 for the test set and an AUC of 0.944 4 for the external validation,and the model showed a very high discriminatory ability for the AKI,which demonstrated the overall regulatory performance of the genes.The nomogram constructed based on the screened 7 genes demonstrated the highest classification performance with an AUC of 0.928 9,validating the outstanding contribution and overall action performance of the screened individual genes.Immune cell infiltration analysis showed that there were significant differences in B cells na?ve,mast cells activated,monocytes,macrophages M1,B cells memory,and dendritic cells activated between AKI samples and healthy control samples(all P＜0.05).Macrophages M1 and monocytes were positively correlated with CD86 and CXCL10,mast cells activated were positively correlated with FOS,and B cells na?ve were negatively correlated with CD86 and CXCL10(all P＜0.01).Mast cells activated were positively correlated with VGF and negatively correlated with CD86 and TCF12,while memory B cells were positively correlated with CD86(all P＜0.05).Conclusion Strategy combining pathway-associated deep neural network and multiple machine learning classifiers can mine high-value key genes from high-dimensional,complex and heterogeneous transcriptomic data as potential targets for therapeutic interventions in AKI.

Prescription optimization is a crucial aspect in the study of traditional Chinese medicine （TCM） compounds. In recent years， the introduction of mathematical methods， data mining techniques， and artificial neural networks has provided new tools for elucidating the compatibility rules of TCM compounds. The study of TCM compounds involves numerous variables， including the proportions of different herbs， the specific extraction parts of each ingredient， and the interactions among multiple components. These factors together create a complex nonlinear dose-effect relationship. In this context， it is essential to identify methods that suit the characteristics of TCM compounds and can leverage their advantages for effective application in new drug development. This paper provided a comprehensive review of the cutting-edge optimization experimental design methods applied in recent studies of TCM compound compatibilities. The key technical issues， such as the optimization of source material selection， dosage optimization of compatible herbs， and multi-objective optimization indicators， were discussed. Furthermore， the evaluation methods for component effects were summarized during the optimization process， so as to provide scientific and practical foundations for innovative research in TCM and the development of new drugs based on TCM compounds.

This study investigated the effects and underlying mechanisms of the luteolin-naringenin combination(LN)on liver injury induced by acetaminophen(APAP).Forty-eight Kunming mice were randomly allocated into six groups:a normal control group,an APAP-induced liver injury model group,a positive drug treatment group,and three LN treatment groups with low,medium,and high doses.After the final drug administration,the mice were fasted for 12 hours prior to eu-thanasia for sample collection.Serum transaminase activity,oxidative stress indices,and hematoxy-lin-eosin(HE)staining were assessed to evaluate the effects of LN on APAP-induced hepatic inju-ry.Additionally,Western blot analysis was conducted to examine the expression levels of sphingo-sine kinase 1(SPHK1)and endoplasmic reticulum stress(ERS)-related proteins,thereby elucida-ting the potential mechanisms by which LN mitigates APAP-induced liver injury.The results dem-onstrated that varying concentrations of LN effectively ameliorated serum aminotransferase activi-ty and oxidative stress levels induced by APAP in a dose-dependent manner.Histopathological ex-amination via HE staining revealed significant improvement in APAP-induced liver tissue injury following treatment with different concentrations of LN.Furthermore,Western blot analysis indi-cated that the protein expressions of SPHK1,CHOP,p-IRE1α,ATF6,p-PERK,p-eIF2α,and ATF4 were markedly reduced after administration of various concentrations of LN.The results demonstrate that LN exhibits a significant protective effect against APAP-induced liver injury by inhibiting the SPHK1-mediated aberrant expression of ERS-related molecules.This study high-lights the importance of targeting SPHK1 in the treatment of APAP liver injury and provides a no-vel therapeutic approach through the multi-target and multi-pathway combination of monomers.

Objective To investigate the clinical outcome differences between robotic-assisted intramedullary nailing and traditional manual surgery,and to analyze the advantages and feasibility of robotic-assisted intramedullary nail fixation in the treatment of intertrochanteric fractures in elderly patients.Methods From December 2023 to December 2024,elderly patients with intertrochanteric fractures who underwent surgery at Department of Trauma Orthopedics,Beijing Luhe Hospital,Capital Medical University were included.Patients were divided into two groups based on the surgical method.The robotic-assisted group underwent robotic-assisted intramedullary nail fixation,while the traditional group received manual intramedullary nail fixation.Baseline data and observation indicators were collected and compared between the two groups to assess any differences.Results There were no statistically significant differences in baseline data between the two groups(P>0.05).The intraoperative blood loss in the robotic-assisted group was(94.28±9.43)mL,compared to(143.00±11.11)mL in the traditional group(P<0.001).The operative time in the robotic-assisted group was(53.06±9.89)min,while in the traditional group,it was(66.74±10.18)min(P<0.001).The skin incision length for the main nail in the robotic-assisted group was(3.23±0.64)cm,whereas in the traditional group,it was(4.03±0.79)cm(P<0.01).Postoperative hemoglobin levels in the robotic-assisted group decreased by(12.63±4.27)g/L,compared to(17.29±4.32)g/L in the traditional group(P=0.018).At 6 months postoperatively,the Harris hip scores in the robotic-assisted group showed 30 cases of excellent,10 good,and 3 poor outcomes,while in the traditional group,there were 22 excellent,15 good,and 6 poor cases(P=0.198).Conclusion Robotic-assisted intramedullary nailing for intertrochanteric fractures offers advantages such as minimally invasive and precise procedures,shorter operative times,and reduced blood loss.Compared to traditional surgical methods,it demonstrates certain benefits in reducing postoperative complications in elderly patients.

Objective To explore the molecular mechanism of miR-16-5p promoting apoptosis and inflammatory response by targeting GPR30 expression in an in vitro ischemic stroke microglia model(BV-2).Methods An ischemic stroke cell model was established by subjecting BV-2 cells to oxygen-glucose deprivation(OGD).qRT-PCR was utilized to assess the levels of miR-16-5p and GPR30 mRNA in OGD cells.A miR-16-5p inhibitor was transfected into OGD cells to silence miR-16-5p expression,and alterations in inflammatory response and apoptosis were measured using ELISA kits and Annexin V-FITC/PI staining.Starbase was employed to predict interactions,and dual-luciferase reporter gene assays were conducted to confirm that miR-16-5p targets the 3'-untranslated region(UTR)sequence of GPR30.Changes in cellular inflammatory response and apoptosis were evaluated by knocking down miR-16-5p and/or GPR30 in OGD cells.Results miR-16-5p expression was significantly elevated(P<0.01),while GPR30 expression was notably decreased(P<0.01)in OGD-induced cells.Knockdown of miR-16-5p reduced the expression levels of inflammatory factors and the cell apoptosis ratio(P<0.01).Inhibition of miR-16-5p expression led to an upregulation of GPR30 mRNA and protein levels(P<0.01).Simultaneous silencing of both miR-16-5p and GPR30 partially enhanced inflammatory factor expression levels and the cell apoptosis ratio compared to cells transfected solely with the miR-16-5p inhibitor(P<0.05).Conclusion In the microglia OGD model,miR-16-5p triggers inflammatory responses and enhances apoptosis by inhibiting GPR30 expression.

Objective To investigate the clinical outcome differences between robotic-assisted intramedullary nailing and traditional manual surgery,and to analyze the advantages and feasibility of robotic-assisted intramedullary nail fixation in the treatment of intertrochanteric fractures in elderly patients.Methods From December 2023 to December 2024,elderly patients with intertrochanteric fractures who underwent surgery at Department of Trauma Orthopedics,Beijing Luhe Hospital,Capital Medical University were included.Patients were divided into two groups based on the surgical method.The robotic-assisted group underwent robotic-assisted intramedullary nail fixation,while the traditional group received manual intramedullary nail fixation.Baseline data and observation indicators were collected and compared between the two groups to assess any differences.Results There were no statistically significant differences in baseline data between the two groups(P>0.05).The intraoperative blood loss in the robotic-assisted group was(94.28±9.43)mL,compared to(143.00±11.11)mL in the traditional group(P<0.001).The operative time in the robotic-assisted group was(53.06±9.89)min,while in the traditional group,it was(66.74±10.18)min(P<0.001).The skin incision length for the main nail in the robotic-assisted group was(3.23±0.64)cm,whereas in the traditional group,it was(4.03±0.79)cm(P<0.01).Postoperative hemoglobin levels in the robotic-assisted group decreased by(12.63±4.27)g/L,compared to(17.29±4.32)g/L in the traditional group(P=0.018).At 6 months postoperatively,the Harris hip scores in the robotic-assisted group showed 30 cases of excellent,10 good,and 3 poor outcomes,while in the traditional group,there were 22 excellent,15 good,and 6 poor cases(P=0.198).Conclusion Robotic-assisted intramedullary nailing for intertrochanteric fractures offers advantages such as minimally invasive and precise procedures,shorter operative times,and reduced blood loss.Compared to traditional surgical methods,it demonstrates certain benefits in reducing postoperative complications in elderly patients.