ObjectiveTo analyze the influencing factors for recurrence in successfully treated pulmonary tuberculosis patients with isoniazid-resistant and rifampicin-sensitive in Shaoxing City, Zhejiang Province. MethodsData on general demographic information, treatment information and drug susceptibility test results for pulmonary tuberculosis patients admitted to the designated tuberculosis medical institutions and registered in the tuberculosis information management system was collected in Shaoxing City from January 2011 to August 2024. A total of 428 patients with isoniazid resistance (including isoniazid single resistance and multiple resistance) but who were successfully treated were included in the study. Information for the recurrence after successful treatment of the patients was analyzed. The Cox proportional hazards models were used to analyze the influencing factors of recurrence in patients. ResultsAmong the 428 successfully treated patients included in the study, 31 cases (accounting for 7.24%) had recurrence by the end of the observation period, with a recurrence rate density of 1.31 per 100 person-years and a median recurrence time of 0.99 (0.08, 8.27) years. Among the relapsed population, 51.61% of the patients relapsed within one year after successful treatment. 77.42% of the patients relapsed within two years after successful treatment. Multivariate Cox regression analysis showed that when isoniazid resistance was discovered, the diagnosis classification of relapse (HR=4.115, 95%CI: 1.734‒9.767) and positive 0-month sequence smear (HR=4.457, 95%CI: 1.053‒18.866) were risk factors for recurrence after successful treatment in patients. ConclusionRegular follow-up should be strengthened for at least two years after the successful treatment of isoniazid-resistant pulmonary tuberculosis patients. Special attention should be paid to the treatment effect and regular re-examination and monitoring after the end of the treatment course of isoniazid-resistant pulmonary tuberculosis patients who have been re-treated and were sputum smear positive at baseline, so as to prevent recurrence and disease progression in high-risk populations.

OBJECTIVES: The application of photodynamic therapy in solid tumors has attracted increasing attention in recent years, and the efficiency of photosensitizers is a crucial determinant of therapeutic efficacy. This study aims to evaluate the cytotoxic effects of a novel photosensitizer, PEG-MTPABZ-PyC, in photodynamic therapy against gastric cancer cells. METHODS: Gastric cancer MKN45 cells were treated with PEG-MTPABZ-PyC. A high-content live-cell imaging system was used to assess the cellular uptake kinetics and subcellular localization of the photosensitizer. The cytotoxic effects of PEG-MTPABZ-PyC-mediated photodynamic therapy were examined using the cell counting kit-8 (CCK-8) assay and flow cytometry, while the intrinsic cytotoxicity of the photosensitizer alone was verified by the CCK-8 assay. Intracellular reactive oxygen species (ROS) generation after photodynamic therapy was detected using 2'-7'-dichlorodihydrofluorescein diacetate (DCFH-DA). RESULTS: PEG-MTPABZ-PyC alone exhibited no cytotoxicity toward MKN45 cells, indicating excellent cytocompatibility. The compound efficiently entered cells within 6 hours and localized predominantly in lysosomes. Upon light irradiation, PEG-MTPABZ-PyC-mediated photodynamic therapy induced significant cytotoxicity compared with the control group (P<0.05) and generated abundant intracellular ROS. CONCLUSIONS The novel photosensitizer PEG-MTPABZ-PyC demonstrates potent photodynamic cytotoxicity against gastric cancer cells, showing promising potential for further development in gastric cancer photodynamic therapy.
Humans ; Stomach Neoplasms/drug therapy* ; Photochemotherapy/methods* ; Photosensitizing Agents/pharmacology* ; Cell Line, Tumor ; Polyethylene Glycols/chemistry* ; Reactive Oxygen Species/metabolism* ; Mesoporphyrins/pharmacology*

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/.

Objective: To explore the relationship between sleep characteristics, physical activity patterns, with depressive and anxiety symptoms in college students, so as to provide reference for student mental health promotion. Methods: From September to November 2023, a convenience sampling method was used to select 7 954 college students aged 18-22 years from 9 universities in Shanghai, Hubei, and Jiangxi. Assessments were conducted using the International Physical Activity Questionnaire Short-Form (IPAQ-SF), Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder Scale-7 (GAD-7), and Pittsburgh Sleep Quality Index (PSQI) to evaluate physical activity, depressive and anxiety symptoms, and sleep quality, respectively. Logistic regression analysis was employed to explore the impact of sleep characteristics and physical activity patterns on depressive and anxiety symptoms and their comorbidity among college students. Results: The detection rates for depressive symptoms, anxiety symptoms, and comorbid depression and anxiety symptoms were 25.67%, 35.39%, and 23.15%, respectively. Factors such as gender, grade, household registration, parental education level, annual family income, family structure, and dietary habits were all associated with the detection rates of depressive and anxiety symptoms and their comorbidity (χ2=4.41-118.39, P<0.05). Physical activity patterns, sleep duration, sleep quality, and sleepwake characteristics were also associated with the occurrence of depressive and anxiety symptoms and their comorbidity (χ2=9.66-627.70, P<0.05). Logistic regression analysis showed that college students who stayed up late and slept less than 7 had the highest risk of depressive and anxiety symptoms and their comorbidity (OR=1.93, 1.85, 1.88, P<0.05). Compared to regular physical activity patterns, insufficient physical activity patterns were associated with an increased risk of depressive and anxiety symptoms (all OR=1.18, P<0.05). Further stratified analysis results showed that the risk of depression, anxiety and their comorbidity increased in college students who stayed up late and slept less than 7 h, went to bed before midnight and slept less than 7 h, or went to bed before midnight and slept more than 7 h but did not have sufficient physical activity (P<0.05). Conclusions Sleep characteristics and physical activity patterns significantly affect depressive and anxiety symptoms in college students. Universities should strengthen sleep management and implement flexible physical activity interventions to help students establish healthy lifestyles.

Abdominal obesity represents the predominant obesity phenotype in China.Compared to peripheral obesity,individuals with abdominal obesity are more prone to metabolic disorders,cardiovascular diseases,and higher mortality rates.Catgut embedding therapy at acupoints has demonstrated significant clinical efficacy in preventing and treating abdominal obesity.However,standardized clinical guidelines for its application in abdominal obesity management have not yet been established.This review comprehensively summarizes the clinical applications of catgut embedding therapy for simple abdominal obesity and abdominal obesity with various complications,aiming to provide clinical evidence and theoretical guidance for its use in preventing and treating abdominal obesity.

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.Compar-ative 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/.

The diagnosis of osteoporosis is mainly characterized by reduced bone mineral density(BMD).Commonly used BMD examination methods are dual-energy X-ray absorptiometry and quantitative CT,but their distribution is not enough.Routine clinical CT can also be used for BMD assessment,which mainly includes vertebral body CT values and BMD values obtained based on asynchronous calibration and internal calibration technology,which is expected to achieve opportunistic osteoporosis screening and fracture risk prediction.This paper reviews the application of routine clinical CT in assessing BMD of osteoporosis patients,in order to help clinicians and scholars understand the current status and future research directions of opportunistic osteoporosis screening.

Objective To investigate the expression characteristics of poly(rC)-binding protein 1(PCBP1)in gastric cancer tissues and their clinical significances by bioinformatics analysis combined with experimental verification,and to identify its relationship with STIP1 homology and U-Box containing protein 1(STUB1).Specifically,this study aims to verify the expression patterns of PCBP1 and STUB1 in gastric cancer and determine their relationships with clinicopathological features by immunohistochemistry to provide a theoretical framework as well as potential intervention strategies for gastric cancer.Methods Data of PCBP1 expression in gastric cancer and adjacent tissues were obtained from TIMER 2.0 online analysis website.KEGG pathway enrichment analysis was performed using gastric cancer data(STAD)in the TCGA(the Cancer Genome Atlas)database,and its potential mechanism was determined.The main regulatory factor STUB1 was found in the fer-roptosis regulatory pathway.Subsequently,PCBP1 and STUB1 expressions in 33 cases of gastric cancer tissues and corresponding adjacent tissues were detected by immunohistochemistry.The collected cases were grouped according to different degrees of differentiation,age,gender,tumor size,depth of tumor invasion,TNM stage and pathological morphology.The positive expression rates of PCBP1 and STUB1 were observed.The correlation between the two proteins and the correlation between clinical and pathological features were analyzed by c2 test.Finally,the relationship between PCBP1 and STUB1 and malignancy of gastric cancer was further explored.Results Immunohistochemical results showed that the positive expression rate of PCBP1 in cancer tissues was 69.7%,which was significantly higher than that in adjacent tissues(48.5%).The positive expression rate of STUB1 in cancer tissues was 39.4%,which was lower than that in adjacent tissues(54.5%),statistically significant difference(P<0.05).The positive expression rate of PCBP1 was correlated with tumor differentiation,lymph node metastasis and Lauren classification(P<0.05),but not with patient's age,gender,depth of inva-sion,clinical stage,nerve infiltration,and intravascular tumor thrombus(P>0.05).The positive expression rate of STUB1 was correlated with tumor differentiation,depth of invasion,lymph node metastasis and Lauren classification(P<0.05).The Spearman correlation coefficient between PCBP1(cancer)and STUB1(cancer)was-0.413,with P=0.017(P<0.05),indicating that there was a significant negative correlation between them.Conclusion PCBP1 participates in the malignant progression of gastric cancer by regulating the main regulator STUB1 in the ferroptosis pathway.Theoretically,it provides a new insight into molecular mechanism as well as a potential therapeutic strategy for treating gastric cancer.

Objective To investigate the expression characteristics of poly(rC)-binding protein 1(PCBP1)in gastric cancer tissues and their clinical significances by bioinformatics analysis combined with experimental verification,and to identify its relationship with STIP1 homology and U-Box containing protein 1(STUB1).Specifically,this study aims to verify the expression patterns of PCBP1 and STUB1 in gastric cancer and determine their relationships with clinicopathological features by immunohistochemistry to provide a theoretical framework as well as potential intervention strategies for gastric cancer.Methods Data of PCBP1 expression in gastric cancer and adjacent tissues were obtained from TIMER 2.0 online analysis website.KEGG pathway enrichment analysis was performed using gastric cancer data(STAD)in the TCGA(the Cancer Genome Atlas)database,and its potential mechanism was determined.The main regulatory factor STUB1 was found in the fer-roptosis regulatory pathway.Subsequently,PCBP1 and STUB1 expressions in 33 cases of gastric cancer tissues and corresponding adjacent tissues were detected by immunohistochemistry.The collected cases were grouped according to different degrees of differentiation,age,gender,tumor size,depth of tumor invasion,TNM stage and pathological morphology.The positive expression rates of PCBP1 and STUB1 were observed.The correlation between the two proteins and the correlation between clinical and pathological features were analyzed by c2 test.Finally,the relationship between PCBP1 and STUB1 and malignancy of gastric cancer was further explored.Results Immunohistochemical results showed that the positive expression rate of PCBP1 in cancer tissues was 69.7%,which was significantly higher than that in adjacent tissues(48.5%).The positive expression rate of STUB1 in cancer tissues was 39.4%,which was lower than that in adjacent tissues(54.5%),statistically significant difference(P<0.05).The positive expression rate of PCBP1 was correlated with tumor differentiation,lymph node metastasis and Lauren classification(P<0.05),but not with patient's age,gender,depth of inva-sion,clinical stage,nerve infiltration,and intravascular tumor thrombus(P>0.05).The positive expression rate of STUB1 was correlated with tumor differentiation,depth of invasion,lymph node metastasis and Lauren classification(P<0.05).The Spearman correlation coefficient between PCBP1(cancer)and STUB1(cancer)was-0.413,with P=0.017(P<0.05),indicating that there was a significant negative correlation between them.Conclusion PCBP1 participates in the malignant progression of gastric cancer by regulating the main regulator STUB1 in the ferroptosis pathway.Theoretically,it provides a new insight into molecular mechanism as well as a potential therapeutic strategy for treating gastric cancer.

The diagnosis of osteoporosis is mainly characterized by reduced bone mineral density(BMD).Commonly used BMD examination methods are dual-energy X-ray absorptiometry and quantitative CT,but their distribution is not enough.Routine clinical CT can also be used for BMD assessment,which mainly includes vertebral body CT values and BMD values obtained based on asynchronous calibration and internal calibration technology,which is expected to achieve opportunistic osteoporosis screening and fracture risk prediction.This paper reviews the application of routine clinical CT in assessing BMD of osteoporosis patients,in order to help clinicians and scholars understand the current status and future research directions of opportunistic osteoporosis screening.