Objective To analyze the status of thyroid nodules in elderly patients with type 2 diabetes mellitus (T2DM) and its relationship with insulin resistance. Methods A total of 324 elderly patients with T2DM admitted to West China Hospital of Sichuan University from January 2018 to December 2023 were selected as the study subjects. The detection status of thyroid nodules was analyzed. According to the presence of thyroid nodules, the patients were classified into thyroid nodule group and non-thyroid nodule group. The insulin resistance index (HOMA-IR) of the study subjects was measured. Spearman correlation analysis was applied to analyze the correlation between concurrent thyroid nodules and HOMA-IR. ROC curve was drawn to analyze the value of HOMA-IR in assessing the risk of thyroid nodules in elderly patients with T2DM. Results Among the 324 elderly T2DM patients, 211 cases of thyroid nodules were detected, with a detection rate of 65.12%. The detection ratio of thyroid nodules in males and females was 1:1.24. The thyroid nodule detection rate was different among patients with different levels of insulin resistance, and the detection rate of thyroid nodules in patients with HOMA-IR>2.0 was higher than that in patients with HOMA-IR≤2.0 (P<0.05). Correlation analysis indicated that HOMA-IR was positively correlated with thyroid nodule in elderly T2DM patients (r=0.650, P<0.05). ROC curve revealed that the area under the curve (AUC), sensitivity, and specificity of HOMA-IR in evaluating thyroid nodules were 0.911, 81.99%, and 96.46%, respectively. Conclusion The risk of thyroid nodules is high in elderly patients with T2DM, and the detection rate in women is higher than that in men, which is closely related to insulin resistance level. HOMA-IR values can provide a reference for the early evaluation of thyroid nodules in elderly T2DM patients.

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.

In recent years， diabetic nephropathy （DN） has become an increasingly serious health challenge worldwide， and its morbidity and mortality rates are rapidly increasing. The patients suffering from the disease tend to be younger. DN is not only accompanied by a wide range of renal pathological changes， such as renal hypertrophy， inflammatory cell infiltration， expansion of the tethered membrane stroma， and thickening of the basement membrane but is also the main cause of end-stage renal disease and death in patients with diabetes mellitus. Therefore， it is particularly urgent to explore new strategies for the prevention and treatment of DN. The pathogenesis of DN is intricate and complex， with current research focusing on multifactorial interactions between metabolic and hemodynamic factors， such as hypoxia， inflammatory responses， and fibrotic processes. Notably， hypoxia plays a pivotal role in the initiation and progression of DN. Hypoxia-inducible factor （HIF-1α）， as a key regulatory protein commonly found in hypoxic cells， has a profound impact on various physiological and pathological processes， such as cell metabolism， vascular neogenesis， oxidative stress， and apoptosis. With its unique theoretical system and therapeutic approach， traditional Chinese medicine has demonstrated significant advantages in coping with hypoxic diseases and can slow down the progression of DN by regulating the expression level of HIF-1α and its downstream signaling molecules and exerting anti-inflammatory， antioxidant， and antifibrotic effects， which has positive clinical significance for drug development and early prevention and treatment of DN.

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.