ObjectiveTo preliminarily explore the active components and target pathways of Angelicae Sinensis Radix-Polygonati Rhizoma （ASR-PR） herb pair in the treatment of simple obesity through network pharmacology and molecular docking， and to verify and investigate its mechanism of action via animal experiments. MethodsThe chemical constituents and targets of ASR and PR were predicted using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform （TCMSP）. Targets related to simple obesity were identified by retrieving the GeneCards， Online Mendelian Inheritance in Man （OMIM）， Pharmacogenomics Knowledgebase （PharmGKB）， and DisGeNET databases. The intersection of drug and disease targets was used to construct an active component-target network using Cytoscape software. This network was imported into the STRING database to construct a protein-protein interaction （PPI） network， and topological analysis was conducted to identify core genes. Gene Ontology （GO） analysis and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analysis and mapping were performed using the DAVID database and the Microbioinformatics platform. AutoDock 1.5.7 software was used to perform molecular docking between the top five active components and core targets. An animal model of simple obesity was established by feeding C57BL/6J mice a high-fat diet. The mice were administered ASR （2.06 g·kg^-1）， PR （2.06 g·kg^-1）， or ASR-PR （4.11 g·kg^-1） for 10 weeks， while the model group received an equal volume of purified water by gavage. After the administration period， the mice were sacrificed to measure body fat weight and serum levels of total cholesterol （TC）， triglycerides （TG）， high-density lipoprotein （HDL）， and low-density lipoprotein （LDL）. Hematoxylin-eosin （HE） staining was used to observe histopathological sections of liver and adipose tissue. Serum levels of leptin， interleukin-6 （IL-6）， and tumor necrosis factor-α （TNF-α） were determined by enzyme-linked immunosorbent assay （ELISA）， and the mRNA expression levels of epidermal growth factor receptor （EGFR） and signal transducer and activator of transcription 3 （STAT3） in liver tissue were detected by real-time quantitative polymerase chain reaction （Real-time PCR）. ResultsNetwork pharmacology and molecular docking results indicated that the treatment of simple obesity by ASR-PR may involve the regulation of protein expression of core targets EGFR and STAT3 by its main components MOL009760 （Siberian glycoside A_qt）， MOL003889 （methyl protodioscin_qt）， MOL009766 （resveratrol）， MOL006331 （4′，5-dihydroxyflavone）， and MOL004941 （baicalin）， thereby modulating the PI3K/Akt and JAK/STAT signaling pathways. The animal experiment results showed that compared with the normal group， the model group had significantly increased body weight， body fat weight， and serum levels of TG， TC， TNF-α， IL-6， and leptin （P<0.01）. EGFR mRNA expression was significantly elevated （P<0.05）， while STAT3 mRNA expression was significantly decreased （P<0.01）. Histological analysis revealed disordered hepatic architecture in the model group， with pronounced lipid vacuoles， cytoplasmic loosening， lipid accumulation， and steatosis. Adipocytes in white adipose tissue （WAT） and brown adipose tissue （BAT） of the model group exhibited markedly increased diameters， reduced cell counts per unit area， and irregular morphology. Compared with the model group， the ASR-PR group significantly reduced body weight， body fat weight， serum TC， IL-6， TNF-α， leptin levels， and EGFR mRNA expression （P<0.01）. TG levels were also significantly decreased （P<0.05）， while STAT3 mRNA expression was significantly increased （P<0.01）. Histopathological improvements included reduced size and number of hepatic lipid vacuoles and restoration of liver cell morphology toward that of the normal group. The diameter of adipocytes significantly decreased， and the number of adipocytes per unit area increased. ConclusionASR-PR may regulate the expression of key target proteins such as EGFR and STAT3 via its core active components， modulate the PI3K/Akt and JAK/STAT signaling pathways， repair damaged liver and adipose tissues， and thereby alleviate the progression of obesity in mice.

ObjectiveTo preliminarily explore the active components and target pathways of Angelicae Sinensis Radix-Polygonati Rhizoma （ASR-PR） herb pair in the treatment of simple obesity through network pharmacology and molecular docking， and to verify and investigate its mechanism of action via animal experiments. MethodsThe chemical constituents and targets of ASR and PR were predicted using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform （TCMSP）. Targets related to simple obesity were identified by retrieving the GeneCards， Online Mendelian Inheritance in Man （OMIM）， Pharmacogenomics Knowledgebase （PharmGKB）， and DisGeNET databases. The intersection of drug and disease targets was used to construct an active component-target network using Cytoscape software. This network was imported into the STRING database to construct a protein-protein interaction （PPI） network， and topological analysis was conducted to identify core genes. Gene Ontology （GO） analysis and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analysis and mapping were performed using the DAVID database and the Microbioinformatics platform. AutoDock 1.5.7 software was used to perform molecular docking between the top five active components and core targets. An animal model of simple obesity was established by feeding C57BL/6J mice a high-fat diet. The mice were administered ASR （2.06 g·kg^-1）， PR （2.06 g·kg^-1）， or ASR-PR （4.11 g·kg^-1） for 10 weeks， while the model group received an equal volume of purified water by gavage. After the administration period， the mice were sacrificed to measure body fat weight and serum levels of total cholesterol （TC）， triglycerides （TG）， high-density lipoprotein （HDL）， and low-density lipoprotein （LDL）. Hematoxylin-eosin （HE） staining was used to observe histopathological sections of liver and adipose tissue. Serum levels of leptin， interleukin-6 （IL-6）， and tumor necrosis factor-α （TNF-α） were determined by enzyme-linked immunosorbent assay （ELISA）， and the mRNA expression levels of epidermal growth factor receptor （EGFR） and signal transducer and activator of transcription 3 （STAT3） in liver tissue were detected by real-time quantitative polymerase chain reaction （Real-time PCR）. ResultsNetwork pharmacology and molecular docking results indicated that the treatment of simple obesity by ASR-PR may involve the regulation of protein expression of core targets EGFR and STAT3 by its main components MOL009760 （Siberian glycoside A_qt）， MOL003889 （methyl protodioscin_qt）， MOL009766 （resveratrol）， MOL006331 （4′，5-dihydroxyflavone）， and MOL004941 （baicalin）， thereby modulating the PI3K/Akt and JAK/STAT signaling pathways. The animal experiment results showed that compared with the normal group， the model group had significantly increased body weight， body fat weight， and serum levels of TG， TC， TNF-α， IL-6， and leptin （P<0.01）. EGFR mRNA expression was significantly elevated （P<0.05）， while STAT3 mRNA expression was significantly decreased （P<0.01）. Histological analysis revealed disordered hepatic architecture in the model group， with pronounced lipid vacuoles， cytoplasmic loosening， lipid accumulation， and steatosis. Adipocytes in white adipose tissue （WAT） and brown adipose tissue （BAT） of the model group exhibited markedly increased diameters， reduced cell counts per unit area， and irregular morphology. Compared with the model group， the ASR-PR group significantly reduced body weight， body fat weight， serum TC， IL-6， TNF-α， leptin levels， and EGFR mRNA expression （P<0.01）. TG levels were also significantly decreased （P<0.05）， while STAT3 mRNA expression was significantly increased （P<0.01）. Histopathological improvements included reduced size and number of hepatic lipid vacuoles and restoration of liver cell morphology toward that of the normal group. The diameter of adipocytes significantly decreased， and the number of adipocytes per unit area increased. ConclusionASR-PR may regulate the expression of key target proteins such as EGFR and STAT3 via its core active components， modulate the PI3K/Akt and JAK/STAT signaling pathways， repair damaged liver and adipose tissues， and thereby alleviate the progression of obesity in mice.

Purpose: Cancer has become a significant major public health concern, making the discovery of new cancer markers or therapeutic targets exceptionally important. Elevated expression of tumor necrosis factor receptor superfamily member 12A (TNFRSF12A) expression has been observed in certain types of cancer. This project aims to investigate the function of TNFRSF12A in tumors and the underlying mechanisms. Materials and Methods: Various websites were utilized for conducting the bioinformatics analysis. Tumor cell lines with stable knockdown or overexpression of TNFRSF12A were established for cell phenotyping experiments and subcutaneous tumorigenesis in BALB/c mice. RNA-seq was employed to investigate the mechanism of TNFRSF12A. Results: TNFRSF12A was upregulated in the majority of cancers and associated with a poor prognosis. Knockdown TNFRSF12A hindered the colorectal cancer progression, while overexpression facilitated malignancy both in vitro and in vivo. TNFRSF12A overexpression led to increased nuclear factor кB (NF-κB) signaling and significant upregulation of baculoviral IAP repeat containing 3 (BIRC3), a transcription target of the NF-κB member RELA, and it was experimentally confirmed to be a critical downstream factor of TNFRSF12A. Therefore, we speculated the existence of a TNFRSF12A/RELA/BIRC3 regulatory axis in colorectal cancer. Conclusion TNFRSF12A is upregulated in various cancer types and associated with a poor prognosis. In colorectal cancer, elevated TNFRSF12A expression promotes tumor growth, potentially through the TNFRSF12A/RELA/BIRC3 regulatory axis.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Purpose: Cancer has become a significant major public health concern, making the discovery of new cancer markers or therapeutic targets exceptionally important. Elevated expression of tumor necrosis factor receptor superfamily member 12A (TNFRSF12A) expression has been observed in certain types of cancer. This project aims to investigate the function of TNFRSF12A in tumors and the underlying mechanisms. Materials and Methods: Various websites were utilized for conducting the bioinformatics analysis. Tumor cell lines with stable knockdown or overexpression of TNFRSF12A were established for cell phenotyping experiments and subcutaneous tumorigenesis in BALB/c mice. RNA-seq was employed to investigate the mechanism of TNFRSF12A. Results: TNFRSF12A was upregulated in the majority of cancers and associated with a poor prognosis. Knockdown TNFRSF12A hindered the colorectal cancer progression, while overexpression facilitated malignancy both in vitro and in vivo. TNFRSF12A overexpression led to increased nuclear factor кB (NF-κB) signaling and significant upregulation of baculoviral IAP repeat containing 3 (BIRC3), a transcription target of the NF-κB member RELA, and it was experimentally confirmed to be a critical downstream factor of TNFRSF12A. Therefore, we speculated the existence of a TNFRSF12A/RELA/BIRC3 regulatory axis in colorectal cancer. Conclusion TNFRSF12A is upregulated in various cancer types and associated with a poor prognosis. In colorectal cancer, elevated TNFRSF12A expression promotes tumor growth, potentially through the TNFRSF12A/RELA/BIRC3 regulatory axis.

Drug development encompasses multiple processes, wherein protein subcellular localization is essential. It promotes target identification, treatment development, and the design of drug delivery systems. In this research, a deep learning framework called LocPro is presented for predicting protein subcellular localization. Specifically, LocPro is unique in (a) combining protein representations from the pre-trained large language model (LLM) ESM2 and the expert-driven tool PROFEAT, (b) implementing a hybrid deep neural network architecture that integrates convolutional neural network (CNN), fully connected (FC) layer, and bidirectional long short-term memory (BiLSTM) blocks, and (c) developing a multi-label framework for predicting protein subcellular localization at multiple granularity levels. Additionally, a dataset was curated and divided using a homology-based strategy for training and validation. Comparative analyses show that LocPro outperforms existing methods in sequence-based multi-label protein subcellular localization prediction. The practical utility of this framework is further demonstrated through case studies on drug target subcellular localization. All in all, LocPro serves as a valuable complement to existing protein localization prediction tools. The web server is freely accessible at https://idrblab.org/LocPro/.

Based on ultra-high performance liquid chromatography-quadrupole-Exactive Orbitrap mass spectrometry(UPLC-Q-Exactive Orbitrap-MS) technology and network pharmacology, this study explored the pharmacodynamic substances and potential mechanisms of Huazhuo Sanjie Chubi Decoction in the treatment of gouty arthritis(GA). UPLC-Q-Exactive Orbitrap-MS technology was used to identify the components in Huazhuo Sanjie Chubi Decoction, and the qualitative analysis of its active ingredients was carried out, with a total of 184 active ingredients identified. A total of 897 active ingredient targets were screened through the PharmMapper database, and 491 GA-related disease targets were obtained from the OMIM, GeneCards, CTD databases. After Venn analysis, 60 intersecting targets were obtained. The component target-GA target network was constructed through the Cytoscape platform, and the STRING database was used to construct a protein-protein interaction network, with 16 core targets screened. The core targets were subjected to Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analyses, and the component-target-pathway network was constructed. It was found that the main active ingredients of the formula for the treatment of GA were phenols, flavonoids, alkaloids, and terpenoids, and the key targets were SRC, MMP3, MMP9, REN, ALB, IGF1R, PPARG, MAPK1, HPRT1, and CASP1. Through GO analysis, it was found that the treatment of GA mainly involved biological processes such as lipid response, bacterial response, and biostimulus response. KEGG analysis showed that the pathways related to the treatment of GA included lipids and atherosclerosis, neutrophil extracellular traps(NETs), IL-17, and so on. In summary, phenols, flavonoids, alkaloids, and terpenoids may be the core pharmacodynamic substances of Huazhuo Sanjie Chubi Decoction in the treatment of GA, and the pharmacodynamic mechanism may be related to SRC, MMP3, MMP9, and other targets, as well as lipids and atherosclerosis, NETs, IL-17, and other pathways.
Drugs, Chinese Herbal/therapeutic use* ; Network Pharmacology ; Arthritis, Gouty/metabolism* ; Chromatography, High Pressure Liquid/methods* ; Humans ; Mass Spectrometry/methods* ; Protein Interaction Maps/drug effects*

Purpose: Cancer has become a significant major public health concern, making the discovery of new cancer markers or therapeutic targets exceptionally important. Elevated expression of tumor necrosis factor receptor superfamily member 12A (TNFRSF12A) expression has been observed in certain types of cancer. This project aims to investigate the function of TNFRSF12A in tumors and the underlying mechanisms. Materials and Methods: Various websites were utilized for conducting the bioinformatics analysis. Tumor cell lines with stable knockdown or overexpression of TNFRSF12A were established for cell phenotyping experiments and subcutaneous tumorigenesis in BALB/c mice. RNA-seq was employed to investigate the mechanism of TNFRSF12A. Results: TNFRSF12A was upregulated in the majority of cancers and associated with a poor prognosis. Knockdown TNFRSF12A hindered the colorectal cancer progression, while overexpression facilitated malignancy both in vitro and in vivo. TNFRSF12A overexpression led to increased nuclear factor кB (NF-κB) signaling and significant upregulation of baculoviral IAP repeat containing 3 (BIRC3), a transcription target of the NF-κB member RELA, and it was experimentally confirmed to be a critical downstream factor of TNFRSF12A. Therefore, we speculated the existence of a TNFRSF12A/RELA/BIRC3 regulatory axis in colorectal cancer. Conclusion TNFRSF12A is upregulated in various cancer types and associated with a poor prognosis. In colorectal cancer, elevated TNFRSF12A expression promotes tumor growth, potentially through the TNFRSF12A/RELA/BIRC3 regulatory axis.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.