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.

The key to improving the cultivation quality of socialist core values in medical colleges and universities， enhancing their dissemination efficiency， consolidating the foundation of medical students’ ideals and beliefs， and uniting the spiritual strength of medical students to serve society and dedicate themselves to the people， lies in integrating the red doctor spirit into the cultivation process of medical students’ socialist core values. Faced with the dilemmas encountered in the cultivation of socialist core values in medical colleges and universities， this paper traced the connection between the red doctor spirit and the socialist core values and reflected on the profound value connotations after the integration of the two， thereby providing theoretical references for finding appropriate cultivation methods and approaches in the future.

Objective To predict the lymph node metastasis status of patients with invasive pulmonary adenocarcinoma by constructing machine learning models based on primary tumor radiomics, peritumoral radiomics, and habitat radiomics, and to evaluate the predictive performance and generalization ability of different imaging features. Methods A retrospective analysis was performed on the clinical data of 1 263 patients with invasive pulmonary adenocarcinoma who underwent surgery at the Department of Thoracic Surgery, Jiangsu Province Hospital, from 2016 to 2019. Habitat regions were delineated by applying K-means clustering (average cluster number of 2) to the grayscale values of CT images. The peritumoral region was defined as a uniformly expanded area of 3 mm around the primary tumor. The primary tumor region was automatically segmented using V-net combined with manual correction and annotation. Subsequently, radiomics features were extracted based on these regions, and stacked machine learning models were constructed. Model performance was evaluated on the training, testing, and internal validation sets using the area under the receiver operating characteristic curve (AUC), F1 score, recall, and precision. Results After excluding patients who did not meet the screening criteria, a total of 651 patients were included. The training set consisted of 468 patients (181 males, 287 females) with an average age of (58.39±11.23) years, ranging from 29 to 78 years, the testing set included 140 patients (56 males, 84 females) with an average age of (58.81±10.70) years, ranging from 34 to 82 years, and the internal validation set comprised 43 patients (14 males, 29 females) with an average age of (60.16±10.68) years, ranging from 29 to 78 years. Although the habitat radiomics model did not show the optimal performance in the training set, it exhibited superior performance in the internal validation set, with an AUC of 0.952 [95%CI (0.87, 1.00)], an F1 score of 84.62%, and a precision-recall AUC of 0.892, outperforming the models based on the primary tumor and peritumoral regions. Conclusion The model constructed based on habitat radiomics demonstrated superior performance in the internal validation set, suggesting its potential for better generalization ability and clinical application in predicting lymph node metastasis status in pulmonary adenocarcinoma.

ObjectiveThrough multimodal research methods including medication rule mining， network pharmacology， molecular docking and dynamics simulation， and in vivo animal experiments， this study aims to speculate and verify the core composition （Ginseng Radix et Rhizoma Rubra-Salviae Miltiorrhizae Radix et Rhizoma-Notoginseng Radix et Rhizoma） and efficacy （Qi-invigorating and blood-activating） of the drug combination in Yitangkang Compound for improving diabetic cardiomyopathy （DCM）， investigate the interaction relationship and binding strength between core active ingredients of the drug combination and key signaling pathway targets， and further explore the mechanism by which the Qi-invigorating and blood-activating drug combination regulates the calcium signaling pathway to improve cardiac function in DCM rats. MethodsThe Ancient and Modern Medical Cases Cloud Platform was used to construct a DCM prescription database， and the "Analysis Method" module of the platform was applied to mine and summarize medication rules， thereby determining the core composition of the Qi-invigorating and blood-activating drug combination in Yitangkang. Drug-active ingredient-signaling pathway-core target-disease analysis and visualization were conducted by combining network pharmacology with the Traditional Chinese Medicine System Pharmacology Platform （TCMSP） database， SwissTargetPrediction platform， GeneCards database， MetaScape database， CytoScape software， etc. Then， molecular docking was performed via the CB-Dock2 platform， and molecular dynamics simulation of the high-binding-strength docking complexes was carried out by Gromacs software. Finally， in vivo animal experiments were carried out. Twenty-eight Sprague Dawley （SD） rats meeting the research criteria were divided into a normal group， a model group， a drug combination group （3.3 g·kg^-1）， and a Yitangkang group （20 g·kg^-1）. A type 2 diabetes mellitus （T2DM） rat model was established by high-fat diet feeding combined with intraperitoneal injection of streptozotocin （STZ）， followed by continuous feeding for eight weeks until the DCM model was successfully established. During this period， the traditional Chinese medicine （TCM） compound and drug combination were administered for prevention and treatment intervention. Meanwhile， changes in blood glucose， body weight， and heart index of each group were monitored. Cardiac function was assessed by echocardiography， and electrophysiological signals were detected by an electrocardiogram. The heart tissue was observed for pathological changes by hematoxylin-eosin （HE） and Masson staining， and the expression of L-type calcium channel （CACNA1C）， calmodulin （CALM1）， calcium/calmodulin-dependent protein kinase Ⅱδ （CAMK2D）， and neuronal nitric oxide synthase （NOS1） proteins in the calcium signaling pathway of myocardial tissue was detected by Western blot. ResultsIn 62 DCM prescriptions， Ginseng Radix et Rhizoma Rubra， Salviae Miltiorrhizae Radix et Rhizoma， and Notoginseng Radix et Rhizoma were used most frequently. Their meridian tropism mainly involved the spleen， heart， and lung， and their sweet and warm properties were prominent. The drugs for tonifying or blood-activating and stasis-resolving ranked top. In association rule analysis， （Ginseng Radix et Rhizoma Rubra， Salviae Miltiorrhizae Radix et Rhizoma）-Notoginseng Radix et Rhizoma had the highest lift. Network pharmacology obtained 75 active ingredients of the drug combination， 714 drug combination action targets， 2 702 disease targets， and 286 intersection targets. Protein-protein interaction （PPI） network predicted nine interaction component-targets （nine active ingredients and four calcium signaling pathway target genes）. Molecular docking showed the four complexes with the lowest binding energy were 2f3z-ginsenoside Re， 1cll-quercetin， 9blh-（6S）-6-（hydroxymethyl）-1，6-dimethyl-8，9-dihydro-7H-naphtho［8，7-g］benzofuran-10，11-dione， and 5vv0-miltionone Ⅱ. Dynamics simulation showed the CALM1-quercetin complex had the strongest binding affinity. The animal experiment results revealed that compared with the normal group， the model group showed significant changes in blood glucose， body weight， myocardial tissue morphology， heart index， cardiac function， electrophysiological indexes， and the expression levels of CACNA1C， CALM1， CAMK2D， and NOS1 proteins （P<0.05， P<0.01）. Compared with the model group， the Yitangkang group had a certain improvement effect on the above indexes （P<0.05， P<0.01）. Compared with the Yitangkang group， the drug combination group showed no significant difference in improving myocardial tissue morphology， heart index， cardiac function， electrophysiological indexes， and the expression of CACNA1C， CALM1， CAMK2D， and NOS1 proteins， except for blood glucose and body weight. ConclusionGinseng Radix et Rhizoma Rubra， Salviae Miltiorrhizae Radix et Rhizoma， and Notoginseng Radix et Rhizoma are the core Qi-invigorating and blood-activating drug combination in Yitangkang Compound. They have a good preventive and therapeutic effect on STZ-induced DCM in rats， and their mechanism of action may be related to the regulation of the calcium signaling pathway.

Recent data suggest that vascular endothelial growth factor receptor inhibitor (VEGFRi) can enhance the anti-tumor activity of the anti-programmed cell death-1 (anti-PD-1) antibody in colorectal cancer (CRC) with microsatellite stability (MSS). However, the comparison between this combination and standard third-line VEGFRi treatment is not performed, and reliable biomarkers are still lacking. We retrospectively enrolled MSS CRC patients receiving anti-PD-1 antibody plus VEGFRi (combination group, n=54) or VEGFRi alone (VEGFRi group, n=32), and their efficacy and safety were evaluated. We additionally examined the immune characteristics of the MSS CRC tumor microenvironment (TME) through single-cell and spatial transcriptomic data, and an MSS CRC immune cell-related signature (MCICRS) that can be used to predict the clinical outcomes of MSS CRC patients receiving immunotherapy was developed and validated in our in-house cohort. Compared with VEGFRi alone, the combination of anti-PD-1 antibody and VEGFRi exhibited a prolonged survival benefit (median progression-free survival: 4.4 vs. 2.0 months, P=0.0024; median overall survival: 10.2 vs. 5.2 months, P=0.0038) and a similar adverse event incidence. Through single-cell and spatial transcriptomic analysis, we determined ten MSS CRC-enriched immune cell types and their spatial distribution, including naive CD4⁺ T, regulatory CD4⁺ T, CD4⁺ Th17, exhausted CD8⁺ T, cytotoxic CD8⁺ T, proliferated CD8⁺ T, natural killer (NK) cells, plasma, and classical and intermediate monocytes. Based on a systemic meta-analysis and ten machine learning algorithms, we obtained MCICRS, an independent risk factor for the prognosis of MSS CRC patients. Further analyses demonstrated that the low-MCICRS group presented a higher immune cell infiltration and immune-related pathway activation, and hence a significant relation with the superior efficacy of pan-cancer immunotherapy. More importantly, the predictive value of MCICRS in MSS CRC patients receiving immunotherapy was also validated with an in-house cohort. Anti-PD-1 antibody combined with VEGFRi presented an improved clinical benefit in MSS CRC with manageable toxicity. MCICRS could serve as a robust and promising tool to predict clinical outcomes for individual MSS CRC patients receiving immunotherapy.
Humans ; Colorectal Neoplasms/drug therapy* ; Male ; Female ; Immunotherapy ; Middle Aged ; Aged ; Tumor Microenvironment/immunology* ; Retrospective Studies ; Microsatellite Instability ; Transcriptome ; Single-Cell Analysis ; Programmed Cell Death 1 Receptor/immunology* ; Gene Expression Profiling ; Immune Checkpoint Inhibitors/therapeutic use* ; Adult ; Receptors, Vascular Endothelial Growth Factor/antagonists & inhibitors*

In protein engineering, while computational models are increasingly used to predict mutation effects, their evaluations primarily rely on high-throughput deep mutational scanning (DMS) experiments that use surrogate readouts, which may not adequately capture the complex biochemical properties of interest. Many proteins and their functions cannot be assessed through high-throughput methods due to technical limitations or the nature of the desired properties, and this is particularly true for the real industrial application scenario. Therefore, the desired testing datasets, will be small-size (∼10-100) experimental data for each protein, and involve as many proteins as possible and as many properties as possible, which is, however, lacking. Here, we present VenusMutHub, a comprehensive benchmark study using 905 small-scale experimental datasets curated from published literature and public databases, spanning 527 proteins across diverse functional properties including stability, activity, binding affinity, and selectivity. These datasets feature direct biochemical measurements rather than surrogate readouts, providing a more rigorous assessment of model performance in predicting mutations that affect specific molecular functions. We evaluate 23 computational models across various methodological paradigms, such as sequence-based, structure-informed and evolutionary approaches. This benchmark provides practical guidance for selecting appropriate prediction methods in protein engineering applications where accurate prediction of specific functional properties is crucial.

[Objective]To investigate the effect and mechanism of Shuxuetong and its main component hirudin on the apoptosis of cerebellar granule neurons(CGNs)in Sprague-Dawley(SD)rats.[Methods]CGNs incubated in vitro for 7 days were divided into survival control group or 25 K group(cultured in medium containing 25 mmol/L KCL)and apopto-sis group or 5 K group(cultured in medium containing 5 mmol/L KCL).CGNs were separately treated with proportionally diluted and different concentrations of Shuxuetong(1/50,1/40,1/30,1/20 and 1/10)and the corresponding different con-centrations of hirudin(2,2.5,3.34,5 and 10 U/mL).Hoechst staining was performed to analyze the apoptosis.Western blot was used to detect the expression levels of Cleaved Caspase-3,Bim and VEGF.[Results]Hoechst staining showed that 5 K group had a higher apoptosis rate than 25 K group.In 25 K group,there was no significant change in the apoptosis rate between neurons treated with different concentrations of Shuxuetong and hirudin,but significant changes was found in 5 K group and the higher the concentration,the lower the apoptosis rate.Western blot results revealed that,compared with control neurons in 5 K group,Shuxuetong injection and hirudin treatments resulted in a decrease of Cleaved Caspase-3 and Bim expression,but an increase of VEGF protein.[Conclusions]Shuxuetong and its main component hirudin inhibits the apoptosis of CGNs through suppressing proapoptotic BH3-only protein Bim.

OBJECTIVE To explore the effectiveness, potential mechanism and compatibility characteristics of efficacy groups of Dunhuang medical prescription Daxiefei decoction in preventing and treating pneumonia based on chemical bioinformatics method. METHODS To study the effect of Daxiefei decoction freeze-dried powder solution on the proliferation activity of lung epithelial cells through cell experiments. Daxiefei decoction was divided into three groups: clearing away heat group, resolving phlegm group, and nourishing Yin group according to its efficacy characteristics. The chemical components of Daxiefei decoction were obtained by TCMSP database and literature search, and the targets were predicted in Swiss Target Prediction database. Pneumonia disease targets were obtained by DrugBank, TTD, Genecards and DisGeNET databases. STRING database and Cytoscape were used to construct the intersection target interaction network and "drug-component-target- pathway" network and DAVID database was used for KEGG pathway enrichment analysis. The network was used to analyze the scientific connotation of the compatibility of efficacy groups. Furthermore, molecular docking was used to evaluate the target-compound affinity and molecular dynamics was used to explore the dynamic molecular mechanism. RESULTS Cell experiments showed that Daxiefei decoction can maintain the proliferation of lung epithelial cells, reverse the decrease of mitochondrial activity induced by LPS and reduce apoptosis. Complex network analysis showed that the pathways enriched by the three functional groups contained in Daxiefei decoction were mainly distributed in two modules: inflammation regulation and reducing airway mucus hypersecretion. Each module was connected by a common target gene and had its own focus. The results of molecular docking showed that the components quercetin, baicalein, isorhamnetin etc. might be the effective multi-target components of Daxiefei decoction. SRC, EGFR, PPARA etc. had good affinity with each potential active component, which might be a potential target of Daxiefei decoction for preventing and treating pneumonia. Molecular dynamics simulation showed that the potential active component quercetin formed stable intermolecular interactions with SRC. CONCLUSION This study initially reveal the material basis and molecular mechanism of Daxiefei decoction in the prevention and treatment of pneumonia. It also explores the scientific connotation of Daxiefei decoction in the prevention and treatment of pneumonia with different efficacy groups, and its modern development and clinical application provide chemical bioinformatics basis.

ABATRACT OBJECTIVE To utilize the pharmacophore model-molecular docking combined with the virtual screening strategy of free energy calculation and the chemical bioinformatics method of traditional Chinese medicine in cell biology experiments to investigate the components of Guiqi Baizhu prescription that target phosphatidylinositol 3-kinase(PI3K) and inhibit the proliferation of uveal melanoma(UM) cells. METHODS The pharmacophore model of PI3K inhibitor was constructed, and the compounds of Guiqi Baizhu prescription were virtual screened. The components that fit the pharmacophore model were calculated by molecular docking and binding free energy, and the potential inhibitory components were selected for biological experimental evaluation. The effects of potential inhibitory components on UM cell proliferation were detected by CCK-8 and clonal formation assay. Flow cytometry was used to detect the cell cycle and apoptosis of UM cells. The mitochondrial membrane potential of UM cells was detected using JC-10 staining. The expressions of PI3K and downstream pathway proteins were detected by Western blotting.RESULTS The pharmacophore model included 2 hydrogen bond receptors, 2 aromatic ring centers, and exclusion volumes. The results of the CCK-8 experiment showed that quercetin, tangerine, and nobiletin at concentrations of 10, 20, 40, 80 μmol·L−1, and cyrtin at concentrations of 20, 40, 80 μmol·L−1, were able to inhibit the proliferation of UM cells. The clonal formation experiment showed that quercetin, tangerine, nobiletin, and morusin, at different concentrations, could significantly inhibit the clonal proliferation of UM cells. Flow cytometry showed that UM cells were arrested in the G0/G1 phase by tangeretin and quercetin, while UM cells were arrested in the G2/M phase by nobiletin and morusin. The results of JC-10 staining showed that quercetin, nobiletin, tangeretin, and morusin could reduce the mitochondrial membrane potential of UM cells. Western blotting results showed that 4 compounds could target PI3K, but their downstream pathways were different.CONCLUSION Based on the method of chemical bioinformatics in traditional Chinese medicine, this study explores the material basis for the inhibition of UM cell proliferation by the Guiqi Baizhu prescription. It also provides insights for the modern development of traditional Chinese medicine prescription.

Objective To explore the feasibility of second-generation dual-layer detector spectral CT ab-dominal virtual non-contrast(VNC) for diagnosing fatty liver.Methods The imaging data of 128 patients with second-generation dual-layer detector spectral CT abdominal enhanced CT in West China Hospital of Si-chuan University from June 2022 to December 2022 were retrospectively analyzed.The CT values of the left lobe,right anterior lobe,right posterior lobe and spleen of all patients were measured on TNC,arterial stage VNC (A-VNC) and venous stage VNC (V-VNC) images.The difference value (L-S) and ratio value (L/S) between the CT value of liver and CT value of spleen were calculated.According to the threshold value of TNC image diagnosis of fatty liver in previous studies,the included cases were divided into two groups:fatty liver group and non-fatty liver group.The Mann-Whitney U test was used to compare the difference of quanti-tative parameters between the fatty liver group and non-fatty liver group.The efficiency of VNC in the diagno-sis of fatty liver was evaluated by the receiver operating characteristic (ROC) curve,and the difference be-tween ROC curves was compared with DeLong's test.The intra-group and inter-group correlation coefficient (ICC) values were used to evaluate the consistency of data measurement.Results The ICC values of intra-group and inter-group consistency of data ranged (0.835-0.986) and (0.810-0.978),respectively (P<0.05).The mean value of left lobe,right anterior lobe,right posterior lobe and triple lobe of liver and CT val-ue of spleen in A-VNC and V-VNC images were lower than those of TNC images,and the differences were statistically significant (P<0.05).The CT values of TNC,A-VNC,V-VNC,(L-S) values and (L/S) values of the non-fatty liver group were higher than those of the fatty liver group,and the differences were statistical-ly significant (P<0.05).The CT value,(L-S) value and (L/S) value of TNC,A-VNC and V-VNC images in the non-fatty liver group were higher than those in the fatty liver group,and the differences were statistically significant (P<0.05).The area under the curve (AUC) of CT values of A-VNC and V-VNC for the diagnosis of fatty liver all were 0.997,and their efficiencies for diagnosing fatty liver had no statistical difference (Z=0.407,P=0.684).AUC of A-VNC (L-S) and V-VNC (L-S) in the diagnosis of fatty liver was 1.000 and 0.981,respectively,and their efficiencies for diagnosing fatty liver had no statistical difference (Z=1.790,P=0.074).AUC of A-VNC (L/S) and V-VNC (L/S) in the diagnosis of fatty liver was 0.992 and 0.987,respec-tively,and their efficiencies for diagnosing fatty liver also had no statistical difference (Z=0.665,P=0.506). Conclusion The CT values of liver and spleen in VNC images reconstructed by second-generation dual-layer detector spectral CT are lower than TNC,but it is still feasible to diagnose fatty liver based on VNC images.