Objective: To investigate the urban and rural differences in adverse outcomes of pulmonary tuberculosis (PTB) in patients with pulmonary tuberculosis-diabetes mellitus comorbidity (PTB-DM), so as to provide insights into improving the prevention and treatment measures for PTB-DM. Methods: Patients with PTB-DM who were admitted and discharged from 14 designated tuberculosis hospitals in Hangzhou City from 2018 to 2022 were selected. Basic information, and history of diagnosis and treatment were collected through hospital information systems. The adverse outcomes of PTB were defined as endpoints, and the proportions of adverse outcomes of PTB in urban and rural patients with PTB-DM were analyzed. Factors affecting the adverse outcomes of PTB were identified using a multivariable Cox proportional hazards regression model. Results: A total of 823 patients with PTB-DM were enrolled, including 354 (43.01%) urban and 469 (56.99%) rural patients. There were 112 (13.61%) patients with adverse outcomes of PTB. The proportions of adverse outcomes of PTB in urban and rural patients were 14.41% and 13.01%, respectively, with no statistically significant difference (P>0.05). Multivariable Cox proportional hazards regression analysis identified first diagnosed in county-level hospitals or above (HR=2.107, 95%CI: 1.181-3.758) and drug resistance (HR=3.303, 95%CI: 1.653-6.600) as the risk factors for adverse outcomes of PTB in urban patients with PTB-DM, while the treatment/observed management throughout the process (HR=0.470, 95%CI: 0.274-0.803) and fixed-dose combinations throughout the process (HR=0.331, 95%CI: 0.151-0.729) as the protective factors for adverse outcomes in rural patients with PTB-DM. Conclusions There are differences in influencing factors for adverse outcomes of PTB in urban and rural patients with PTB-DM. The adverse outcomes of PTB are associated with first diagnosed hospitals and drug resistance in urban patients, and are associated with the treatment/observed management and fixed-dose combinations throughout the process in rural patients.

OBJECTIVE To provide valuable insights for the adjustment of anti-infectious regimens， identification of adverse reactions， and individualized pharmaceutical care in patients with critically severe scrub typhus. METHODS Clinical pharmacists actively participated in the pharmaceutical care process for a patient with severe scrub typhus leading to mixed shock undergoing continuous renal replacement therapy and extracorporeal membrane oxygenation. Initially， the patient received meropenem （1 g， q12 h， ivdrip）， in combination with doxycycline （0.1 g， q12 h， po）， which was later switched to meropenem （1 g， q8 h， ivdrip） along with omacycline （100 mg， qd， ivdrip） due to impaired gastrointestinal function. However， as the patient’s condition progressively deteriorated and the infection became uncontrolled， the clinical pharmacists recommended that the clinicians adjust the anti-infective regimen to meropenem （2 g， q8 h， ivdrip） combined with tigecycline （100 mg for first dose； 50 mg， q12 h for maintenance； ivdrip）. The clinicians followed the advice of the clinical pharmacists. After treatment， the patient’s symptoms exhibited significant improvement， accompanied by a notable decrease in inflammatory markers， indicating that the infection had been successfully controlled. However， due to continuously increasing bilirubin levels， in order to reduce the risk of drug-induced liver injury， the clinicians changed tigecycline to azithromycin （0.5 g， qd， ivdrip） following the recommendation of the clinical pharmacists. RESULTS Ultimately， metagenomic next-generation sequencing of the bronchoalveolar lavage fluid and blood specimens indicated that Orientia tsutsugamushi had been completely eradicated in the patient. CONCLUSIONS Tigecycline may be a viable therapeutic choice for patients with severe scrub typhus. In the context of critically ill patients with scrub typhus， combining tigecycline with azithromycin might potentially enhance the efficacy in eliminating Orientia tsutsugamushi.

ObjectiveTo explore the mechanisms associated with Mahoniae Caulis alkaloids （MA） in ameliorating depression by network pharmacology， molecular docking， and animal experiments. MethodsThe component targets of MA were obtained through Swiss Target Prediction and TCMIP database. The depression targets were collected through TCMIP， Genecards， HPO， DrugBank and OMIM database. The depression targets were collected through TCMIP， Genecards， HPO， DrugBank and OMIM database. Protein-protein interaction （PPI） network was constructed by protein interaction analysis （STRING） database. Gene ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） analyses were performed through Bioinformatics （DAVID） database. The docking of components and targets was performed by AGFR. The mouse model of depression was established by intraperitoneal injection of corticosterone （CORT） once a day for 35 consecutive days. Sixty mice were randomly allocated into control （0.9% normal saline）， model （CORT， 20 mg·kg^-1）， positive control （fluoxetine hydrochloride， 3.6 mg·kg^-1）， and MA （10， 5， and 2.5 mg·kg^-1） groups. Each group was administrated with corresponding medicine or normal saline once a day for 28 consecutive days. The depression-like behavior of mice was observed. The pathological changes of prefrontal cortex in mice were observed by hematoxylin-eosin staining. Terminal deoxynucleotidyl dUTP transferase nick end labeling （TUNEL） was employed to observe the apoptosis of neurons in the prefrontal cortex. Enzyme-linked immunosorbent assay was employed to assess the serum levels of brain-derived neurotrophic factor （BDNF）， dopamine （DA）， 5-hydroxytryptamine （5-HT）， and norepinephrine （NE） in mice. The mRNA levels of cyclic adenosine monophosphate （cAMP） pathway-related factors and inflammatory factors were determined by Real-time PCR. Western blot was employed to determine the expression of cAMP pathway-related factors and connexin 43 （Cx43）. ResultsA total of 434 component targets and 545 depression targets were obtained， including 84 common targets， among which 10 core targets were screened out. GO analysis predicted 34 biological processes， 15 cell components， and 11 molecular functions. The KEGG pathways were mainly related to gap junction and cAMP signaling pathway. The core components had good binding affinity with the core targets. The results of animal experiments showed that compared with the control group， CORT prolonged the immobility time of mice in forced swimming and tail suspension tests （P<0.01）， lowered the serum levels of NE， BDNF， and 5-HT （P<0.05）， up-regulated the mRNA levels of nuclear factor-κB （NF-κB） and interleukin-6 （IL-6） in the brain tissue （P<0.05）， and down-regulated the mRNA levels of cyclic adenosine monophosphate effector binding protein （CREB） and BDNF （P<0.05） and the protein levels of protein kinase （PRKACA）， phosphorylation （p）-CREB/CREB， BDNF， and Cx43 （P<0.05） in the brain tissue. Compared with the model group， high-dose MA reduced the immobility time of mice in forced swimming （P<0.05） and tail suspension （P<0.01） tests， raised the serum levels of NE， BDNF， and 5-HT （P<0.01）， down-regulated the mRNA level of NF-κB （P<0.01）， and up-regulated the mRNA level of BDNF （P<0.01） and protein levels of PRKACA， p-CREB/CREB， BDNF， and Cx43 （P<0.05）. ConclusionMA alleviates the CORT-induced depressive behavior of mice. It may play an antidepressant role by regulating cAMP signaling pathway and gap junction pathway， improving synaptic plasticity and gap junction function， and reducing neuroinflammation.

ObjectiveTo explore the mechanisms associated with Mahoniae Caulis alkaloids （MA） in ameliorating depression by network pharmacology， molecular docking， and animal experiments. MethodsThe component targets of MA were obtained through Swiss Target Prediction and TCMIP database. The depression targets were collected through TCMIP， Genecards， HPO， DrugBank and OMIM database. The depression targets were collected through TCMIP， Genecards， HPO， DrugBank and OMIM database. Protein-protein interaction （PPI） network was constructed by protein interaction analysis （STRING） database. Gene ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） analyses were performed through Bioinformatics （DAVID） database. The docking of components and targets was performed by AGFR. The mouse model of depression was established by intraperitoneal injection of corticosterone （CORT） once a day for 35 consecutive days. Sixty mice were randomly allocated into control （0.9% normal saline）， model （CORT， 20 mg·kg^-1）， positive control （fluoxetine hydrochloride， 3.6 mg·kg^-1）， and MA （10， 5， and 2.5 mg·kg^-1） groups. Each group was administrated with corresponding medicine or normal saline once a day for 28 consecutive days. The depression-like behavior of mice was observed. The pathological changes of prefrontal cortex in mice were observed by hematoxylin-eosin staining. Terminal deoxynucleotidyl dUTP transferase nick end labeling （TUNEL） was employed to observe the apoptosis of neurons in the prefrontal cortex. Enzyme-linked immunosorbent assay was employed to assess the serum levels of brain-derived neurotrophic factor （BDNF）， dopamine （DA）， 5-hydroxytryptamine （5-HT）， and norepinephrine （NE） in mice. The mRNA levels of cyclic adenosine monophosphate （cAMP） pathway-related factors and inflammatory factors were determined by Real-time PCR. Western blot was employed to determine the expression of cAMP pathway-related factors and connexin 43 （Cx43）. ResultsA total of 434 component targets and 545 depression targets were obtained， including 84 common targets， among which 10 core targets were screened out. GO analysis predicted 34 biological processes， 15 cell components， and 11 molecular functions. The KEGG pathways were mainly related to gap junction and cAMP signaling pathway. The core components had good binding affinity with the core targets. The results of animal experiments showed that compared with the control group， CORT prolonged the immobility time of mice in forced swimming and tail suspension tests （P<0.01）， lowered the serum levels of NE， BDNF， and 5-HT （P<0.05）， up-regulated the mRNA levels of nuclear factor-κB （NF-κB） and interleukin-6 （IL-6） in the brain tissue （P<0.05）， and down-regulated the mRNA levels of cyclic adenosine monophosphate effector binding protein （CREB） and BDNF （P<0.05） and the protein levels of protein kinase （PRKACA）， phosphorylation （p）-CREB/CREB， BDNF， and Cx43 （P<0.05） in the brain tissue. Compared with the model group， high-dose MA reduced the immobility time of mice in forced swimming （P<0.05） and tail suspension （P<0.01） tests， raised the serum levels of NE， BDNF， and 5-HT （P<0.01）， down-regulated the mRNA level of NF-κB （P<0.01）， and up-regulated the mRNA level of BDNF （P<0.01） and protein levels of PRKACA， p-CREB/CREB， BDNF， and Cx43 （P<0.05）. ConclusionMA alleviates the CORT-induced depressive behavior of mice. It may play an antidepressant role by regulating cAMP signaling pathway and gap junction pathway， improving synaptic plasticity and gap junction function， and reducing neuroinflammation.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

OBJECTIVE To investigate the ameliorative effects and potential mechanism of total secondary ginsenosides （TSG） on hypertrophic changes of primary cardiomyocytes stimulated by angiotensin Ⅱ （Ang Ⅱ）. METHODS Primary cardiomyocytes were isolated from the hearts of neonatal SD rats and divided into the following groups： control group， AngⅡ group （2 µmol/L）， TSG group （7.5 µg/mL）， PFK-015 group [6-phosphofructo-2-kinase/fructose-2， 6-bisphosphatase 3 （PFKFB3） inhibitor， 10 nmol/L]， and TSG+PFK-015 group （TSG 7.5 µg/mL+PFK-015 10 nmol/L）. The surface area， protein synthesis， energy metabolism-related indicators [free fatty acid （FFA）， coenzyme A （CoA）， acetyl coenzyme A （acetyl-CoA）]， and the expressions of glycolysis-related factors [hypoxia-inducible factor 1α （HIF-1α）， glucose transporter protein 4 （GLUT-4）， lactate dehydrogenase A （LDHA）， pyruvate dehydrogenase kinase 1 （PDK1） and PFKFB3] in primary cardiomyocytes of each group were measured. RESULTS Compared with the control group， the surface area of primary cardiomyocytes and protein synthesis were significantly increased， the content of FFA， protein and mRNA expressions of HIF-1α， LDHA， PDK1 and PFKFB3 were significantly increased or up-regulated in the AngⅡ group， while the contents of CoA and acetyl-CoA， the protein and mRNA expressions of GLUT-4 were significantly decreased or down-regulated （P＜0.05）. Compared with the AngⅡ group， both TSG group and PFK-015 group showed significant improvements in these indexes， with the TSG+PFK-015 group generally demonstrating superior effects compared to either treatment alone （P＜0.05）. CONCLUSIONS TSG can reduce the surface area of AngⅡ-induced primary cardiomyocytes， decrease protein synthesis， and inhibit their hypertrophic changes. These effects may be related to improving energy metabolism and the inhibition of glycolysis activity.

Esophagogastric variceal bleeding is a common complication and the leading cause of death in advanced liver cirrhosis， and endoscopic variceal ligation （EVL） and endoscopic cyanoacrylate injection （ECI） are commonly used treatment strategies. Thrombocytopenia is one of the most common hematological complications in liver cirrhosis， and patients with severe thrombocytopenia have the potential risk of bleeding， which may affect treatment decision-making by clinicians and endoscopists. This article reviews the evolution of guidelines and clinical research advances regarding EVL/ECI in China and globally， in order to provide a basis for decision making among clinicians.

Ulcerative colitis(UC) is a recurrent, chronic, nonspecific inflammatory bowel disease. The longer the course of the disease, the higher the risk of cancerization. In recent years, the incidence and mortality rates of colon cancer in China have been increasing year by year, seriously threatening the life and health of patients. Therefore, studying the mechanism of "inflammation cancer transformation" in UC and conducting early intervention is crucial. The "Kenang" theory is an important component of traditional Chinese medicine(TCM) theory of phlegm and blood stasis. It is based on the coexistence of phlegm and blood stasis in the body and deeply explores the pathogenic syndromes and characteristics of phlegm and blood stasis. Kenang is a pathological product formed when long-term Qi stagnation leads to the internal formation of phlegm and blood stasis, which is hidden deep within the body. It is characterized by being hidden, progressive, and difficult to treat. The etiology and pathogenesis of "inflammation cancer transformation" in UC are consistent with the connotation of the "Kenang" theory. The internal condition for the development of UC "inflammation cancer transformation" is the deficiency of healthy Qi, with Qi stagnation being the key pathological mechanism. Phlegm and blood stasis are the main pathogenic factors. Phlegm and blood stasis accumulate in the body over time and can produce cancer toxins. Due to the depletion of healthy Qi and a weakened constitution, the body is unable to limit the proliferation and invasion of cancer toxins, eventually leading to cancer transformation in UC. In clinical treatment, the focus should be on removing phlegm and blood stasis, with syndrome differentiation and treatment based on three basic principles: supporting healthy Qi to strengthen the body's foundation, resolving phlegm and blood stasis to break up the Kenang, and regulating Qi and blood to smooth the flow of energy and resolve stagnation. This approach helps to dismantle the Kenang, delay, block, or even reverse the cancerization process of UC, reduce the risk of "inflammation cancer transformation", improve the patient's quality of life, and provide new perspectives and strategies for early intervention in the development of colon cancer.
Humans ; Colitis, Ulcerative/immunology* ; Medicine, Chinese Traditional ; Drugs, Chinese Herbal/therapeutic use* ; Cell Transformation, Neoplastic