LncRNA BBOX1-AS1 Contributes to Laryngeal Carcinoma Progression by Recruiting SRSF1 to Maintain EFNB2 mRNA Stability.

Laryngeal cancer is a common malignancy of the larynx with a generally poor prognosis. This study systematically assessed the functional role of lncRNA BBOX1-AS1 in laryngeal carcinoma progression and associated molecular regulatory mechanisms. The proliferation, migration, and invasion of laryngeal carcinoma cells were detected by Cell Counting Kit-8, wound healing, clonal formation, and transwell assays. In addition, the interaction between BBOX1-AS1, Serine/Arginine Splicing Factor 1 (SRSF1), and Ephrin-B2 (EFNB2) mRNA was examined employing RNA immunoprecipitation and RNA pull-down experiments. Furthermore, western blotting, and RT-qPCR assays were adopted to detect the expression levels of BBOX1-AS1, SRSF1, and EFNB2. The impact of BBOX1-AS1 and SRSF1 on EFNB2 mRNA stability was examined using the RNA stability assay. BBOX1-AS1 was highly expressed in human laryngeal carcinoma tissues and cell lines. BBOX1-AS1 knockdown suppressed the growth, proliferation, migration, and invasion of laryngeal carcinoma cells. BBOX1-AS1 maintained the stability of EFNB2 mRNA in laryngeal carcinoma cells by recruiting SRSF1. EFNB2 knockdown inhibited the growth and metastatic function of laryngeal carcinoma cells in vitro. EFNB2 overexpression reversed the influence of BBOX1-AS1 knockdown on laryngeal cancer tumorigenesis. BBOX1-AS1 maintained EFNB2 mRNA stability by recruiting SRSF1, thereby aggravating laryngeal carcinoma malignant phenotypes. BBOX1-AS1 might be a new theoretical target for the treatment of laryngeal carcinoma.

Macrophage and fibroblast trajectory inference and crosstalk analysis during myocardial infarction using integrated single-cell transcriptomic datasets.

BACKGROUND: Cardiac fibrosis after myocardial infarction (MI) has been considered an important part of cardiac pathological remodeling. Immune cells, especially macrophages, are thought to be involved in the process of fibrosis and constitute a niche with fibroblasts to promote fibrosis. However, the diversity and variability of fibroblasts and macrophages make it difficult to accurately depict interconnections. METHODS: We collected and reanalyzed scRNA-seq and snRNA-seq datasets from 12 different studies. Differentiation trajectories of these subpopulations after MI injury were analyzed by using scVelo, PAGA and Slingshot. We used CellphoneDB and NicheNet to infer fibroblast-macrophage interactions. Tissue immunofluorescence staining and in vitro experiments were used to validate our findings. RESULTS: We discovered two subsets of ECM-producing fibroblasts, reparative cardiac fibroblasts (RCFs) and matrifibrocytes, which appeared at different times after MI and exhibited different transcriptional profiles. We also observed that CTHRC1+ fibroblasts represent an activated fibroblast in chronic disease states. We identified a macrophage subset expressing the genes signature of SAMs conserved in both human and mouse hearts. Meanwhile, the SPP1hi macrophages were predominantly found in the early stages after MI, and cell communication analysis indicated that SPP1hi macrophage-RCFs interactions are mainly involved in collagen deposition and scar formation. CONCLUSIONS: Overall, this study comprehensively analyzed the dynamics of fibroblast and macrophage subsets after MI and identified specific subsets of fibroblasts and macrophages involved in scar formation and collagen deposition.

Perceived stress and influencing factors for the people at high risk to COVID-19 in centralized quarantine camps in Wenzhou, China.

BACKGROUND: This study was designed to assess stress levels and related factors during the coronavirus disease 2019 (COVID-19) epidemic among individuals in centralized quarantine camps in Wenzhou, China. METHODS: The survey was conducted using a questionnaire. The questionnaire included questions on sociodemographic characteristics, life events related to the COVID-19 and stressful situations, as well as Perceived Stress Scale-14. Participants included close contacts of patients with COVID-19 or at-risk individuals in quarantine camps. Multivariate logistic regression was used to analyze different factors affecting perceived stress. RESULTS: The prevalence of high stress among quarantine camp participants was 37.45%. Of the 881 respondents, 51.99% were concerned about the difficulty of controlling the epidemic, 46.20% were concerned about the health of themselves and their family members and 39.61% were concerned about not being able to leave their homes. Multivariate logistic regression analysis revealed statistically significant differences in the prevalence of stress among different groups for certain variables, including occupation, education level and knowledge of COVID-19 (all P < 0.05). Our study found that at-risk individuals and close contacts experienced high levels of stress in quarantine camps during the COVID-19 pandemic. CONCLUSIONS: These findings suggest that centralized quarantine policies should be adapted and optimized to minimize negative psychological effects on quarantined individuals.

Telehealth With Comprehensive Live-Fed Real-World Data as a Patient Care Platform for Lung Cancer: Implementation and Evaluation Study.

BACKGROUND: Telehealth has emerged as a popular channel for providing outpatient services in many countries. However, the majority of telehealth systems focus on operational functions and offer only a sectional patient journey at most. Experiences with incorporating longitudinal real-world medical record data into telehealth are valuable but have not been widely shared. The feasibility and usability of such a telehealth platform, with comprehensive, real-world data via a live feed, for cancer patient care are yet to be studied. OBJECTIVE: The primary purpose of this study is to understand the feasibility and usability of cancer patient care using a telehealth platform with longitudinal, real-world data via a live feed as a supplement to hospital electronic medical record systems specifically from physician's perspective. METHODS: A telehealth platform was constructed and launched for both physicians and patients. Real-world data were collected and curated using a comprehensive data model. Physician activities on the platform were recorded as system logs and analyzed. In February 2023, a survey was conducted among the platform's registered physicians to assess the specific areas of patient care and to quantify their before and after experiences, including the number of patients managed, time spent, dropout rate, visit rate, and follow-up data. Descriptive and inferential statistical analyses were performed on the data sets. RESULTS: Over a period of 15 months, 16,035 unique users (13,888 patients, 1539 friends and family members, and 174 physician groups with 608 individuals) registered on the platform. More than 382,000 messages including text, reminders, and pictures were generated by physicians when communicating with patients. The survey was completed by 78 group leaders (45% of the 174 physician groups). Of the participants, 84% (65.6/78; SD 8.7) reported a positive experience, with efficient communication, remote supervision, quicker response to questions, adverse event prevention, more complete follow-up data, patient risk reduction, cross-organization collaboration, and a reduction in in-person visits. The majority of the participants (59/78, 76% to 76/78, 97.4%) estimated improvements in time spent, number of patients managed, the drop-off rate, and access to medical history, with the average ranging from 57% to 105%. When compared with prior platforms, responses from physicians indicated better experiences in terms of time spent, the drop-off rate, and medical history, while the number of patients managed did not significantly change. CONCLUSIONS: This study suggests that a telehealth platform, equipped with comprehensive, real-world data via a live feed, is feasible and effective for cancer patient care. It enhances inpatient management by improving time efficiencies, reducing drop-off rates, and providing easy access to medical history. Moreover, it fosters a positive experience in physician-patient interactions.

[Anti-tumor mechanism of total saponins of Paridis Rhizoma on inducing ferroptosis of breast cancer MCF-7 cells].

This study aims to investigate the mechanism of total saponins of Paridis Rhizoma in inducing the ferroptosis of MCF-7 cells and provide a theoretical basis for the clinical treatment of breast cancer with total saponins of Paridis Rhizoma. The methyl thiazolyl tetrazolium(MTT) assay was employed to examine the effects of different concentrations of total saponins of Paridis Rhizoma on the proliferation of MCF-7 cells. A phase contrast inverted microscope was used to observe the morphological changes of MCF-7 cells. The colony formation assay was employed to test the colony formation of MCF-7 cells. The lactate dehydrogenase(LDH) release test was conducted to determine the cell membrane integrity of MCF-7 cells. The cell scratch assay was employed to examine the migration of MCF-7 cells. After that, the level of reactive oxygen species(ROS) in MCF-7 cells was observed by an inverted fluorescence microscope, and the content of Fe~(2+) in MCF-7 cells was detected by the corresponding kit. Transmission electron microscopy was employed to observe the mitochondrial ultrastructure of MCF-7 cells. Western blot was employed to determine the expression of ferroptosis-related proteins, such as p53, solute carrier family 7 member 11(SLC7A11), glutathione peroxidase 4(GPX4), acyl-CoA synthetase long-chain family member 4(ACSL4), and transferrin receptor protein 1(TFR1) in MCF-7 cells. The results showed that 1.5, 3, 4.5, 6, 7.5, and 9 µg·mL~(-1) total saponins of Paridis Rhizoma significantly inhibited the proliferation of MCF-7 cells, with the IC_(50) of 4.12 µg·mL~(-1). Total saponins of Paridis Rhizoma significantly damaged the morphology of MCF-7 cells, leading to the formation of vacuoles and the gradual shrinkage and detachment of cells. Meanwhile, total saponins of Paridis Rhizoma inhibited the colony formation of MCF-7 cells, destroyed the cell membrane(leading to the release of LDH), and shortened the migration distance of MCF-7 cells. Total saponins of Paridis Rhizoma treatment significantly increased the content of ROS, induced oxidative damage, and led to the accumulation of Fe~(2+) in MCF-7 cells. Furthermore, total saponins of Paridis Rhizoma changed the mitochondrial structure, increased the mitochondrial membrane density, led to the decrease or even disappear of ridges, promoted the expression of p53 protein, down-regulated the expression of SLC7A11 and GPX4, and up-regulated the expression of ACSL4 and TFR1. In summary, total saponins of Paridis Rhizoma can significantly inhibit the proliferation and migration of MCF-7 cells and destroy the cell structure by inducing ferroptosis.

Skeletal muscle index based on CT at the 12th thoracic spine level can predict osteoporosis and fracture risk: a propensity score-matched cohort study.

Background: Multiple studies have shown that skeletal muscle index (SMI) measured on abdominal computed tomography (CT) is strongly associated with bone mineral density (BMD) and fracture risk as estimated by the fracture risk assessment tool (FRAX). Although some studies have reported that SMI at the level of the 12th thoracic vertebra (T12) measured on chest CT images can be used to diagnose sarcopenia, it is regrettable that no studies have investigated the relationship between SMI at T12 level and BMD or fracture risk. Therefore, we further investigated the relationship between SMI at T12 level and FRAX-estimated BMD and fracture risk in this study. Methods: A total of 349 subjects were included in this study. After 1∶1 propensity score matching (PSM) on height, weight, hypertension, diabetes, hyperlipidemia, hyperuricemia, body mass index (BMI), age, and gender, 162 subjects were finally included. The SMI, BMD, and FRAX score of the 162 participants were obtained. The correlation between SMI and BMD, as well as SMI and FRAX, was assessed using Spearman rank correlation. Additionally, the effectiveness of each index in predicting osteoporosis was evaluated through the receiver operating characteristic (ROC) curve analysis. Results: The BMD of the lumbar spine (L1-4) demonstrated a strong correlation with SMI (r = 0.416, p < 0.001), while the BMD of the femoral neck (FN) also exhibited a correlation with SMI (r = 0.307, p < 0.001). SMI was significantly correlated with FRAX, both without and with BMD at the FN, for major osteoporotic fractures (r = -0.416, p < 0.001, and r = -0.431, p < 0.001, respectively) and hip fractures (r = -0.357, p < 0.001, and r = -0.311, p < 0.001, respectively). Moreover, the SMI of the non-osteoporosis group was significantly higher than that of the osteoporosis group (p < 0.001). SMI effectively predicts osteoporosis, with an area under the curve of 0.834 (95% confidence interval 0.771-0.897, p < 0.001). Conclusion: SMI based on CT images of the 12th thoracic vertebrae can effectively diagnose osteoporosis and predict fracture risk. Therefore, SMI can make secondary use of chest CT to screen people who are prone to osteoporosis and fracture, and carry out timely medical intervention.

[Traditional Chinese medicine preparations in medical institutions: current situation and inspirations on research and development of new traditional Chinese medicine preparations].

Traditional Chinese medicine(TCM) preparations in medical institutions embody the characteristics of TCM and are the source for the development of new TCM drugs. This study summarizes the current situation, existing problems, and development trends of the TCM preparations in medical institutions in 31 provinces across China. Furthermore, this paper puts forward the development path of new TCM preparations based on the requirements of registration and management regulations of TCM preparations, providing new ideas for promoting the inheritance, innovation, and development of TCM.

Quadrat soil pollen signal reflects plant important values in forests and shrublands from subtropical China.

Pollen analysis, a crucial tool in botany and ecology for examining historical biotic dynamics, has elicited debate owing to its complex link with vegetation. The challenge lies in discerning the ecological significance of pollen data. In this study, we conducted detailed quadrat surveys on Jinhua Mountain, subtropical China, analyzing topsoil pollen to determine whether pollen signals accurately reflect key ecological components in the forests and shrublands. We performed direct comparisons between pollen and plant compositions and calculated pollen percentages and plant Important Values (IVs) for each quadrat. The results indicate greater homogeneity in pollen composition across the study area compared to plant composition, particularly in the high percentage of Pinus pollen. However, distinct plant communities exhibited significantly different pollen compositions, as evidenced by the multi-response permutation test. This divergence aligns with variations in the dominant plant species across different communities. There were significant correlations between pollen percentages and plant IVs, with correlation coefficients of 0.55 (p < 0.001) at the quadrat level and 0.78 (p < 0.001) at the taxon level. These results support the utility of pollen analysis for representing ecologically significant values in subtropical Chinese forests and shrublands. Such correlations might also be extrapolated to pollen-based paleoecological studies.

Analysis of risk factors leading to anxiety and depression in patients with prostate cancer after castration and the construction of a risk prediction model.

BACKGROUND: Cancer patients often suffer from severe stress reactions psychologically, such as anxiety and depression. Prostate cancer (PC) is one of the common cancer types, with most patients diagnosed at advanced stages that cannot be treated by radical surgery and which are accompanied by complications such as bodily pain and bone metastasis. Therefore, attention should be given to the mental health status of PC patients as well as physical adverse events in the course of clinical treatment. AIM: To analyze the risk factors leading to anxiety and depression in PC patients after castration and build a risk prediction model. METHODS: A retrospective analysis was performed on the data of 120 PC cases treated in Xi'an People's Hospital between January 2019 and January 2022. The patient cohort was divided into a training group (n = 84) and a validation group (n = 36) at a ratio of 7:3. The patients' anxiety symptoms and depression levels were assessed 2 wk after surgery with the Self-Rating Anxiety Scale (SAS) and the Self-rating Depression Scale (SDS), respectively. Logistic regression was used to analyze the risk factors affecting negative mood, and a risk prediction model was constructed. RESULTS: In the training group, 35 patients and 37 patients had an SAS score and an SDS score greater than or equal to 50, respectively. Based on the scores, we further subclassified patients into two groups: a bad mood group (n = 35) and an emotional stability group (n = 49). Multivariate logistic regression analysis showed that marital status, castration scheme, and postoperative Visual Analogue Scale (VAS) score were independent risk factors affecting a patient's bad mood (P < 0.05). In the training and validation groups, patients with adverse emotions exhibited significantly higher risk scores than emotionally stable patients (P < 0.0001). The area under the curve (AUC) of the risk prediction model for predicting bad mood in the training group was 0.743, the specificity was 70.96%, and the sensitivity was 66.03%, while in the validation group, the AUC, specificity, and sensitivity were 0.755, 66.67%, and 76.19%, respectively. The Hosmer-Lemeshow test showed a χ2 of 4.2856, a P value of 0.830, and a C-index of 0.773 (0.692-0.854). The calibration curve revealed that the predicted curve was basically consistent with the actual curve, and the calibration curve showed that the prediction model had good discrimination and accuracy. Decision curve analysis showed that the model had a high net profit. CONCLUSION: In PC patients, marital status, castration scheme, and postoperative pain (VAS) score are important factors affecting postoperative anxiety and depression. The logistic regression model can be used to successfully predict the risk of adverse psychological emotions.

The Role of Climate Change and Its Sensitivity on Long-Term Standardized Precipitation Evapotranspiration Index, Vegetation and Drought Changing Trends over East Asia.

Droughts have become more severe and frequent due to global warming. In this context, it is widely accepted that for drought assessments, both water supply (rainfall) and demand (standardized precipitation evapotranspiration index, SPEI) should be considered. Using SPEI, we explored the spatial-temporal patterns of dry and wet annual and seasonal changes in five sub-regions of East Asia during 1902-2018. These factors are linked to excess drought frequency and severity on the regional scale, and their effect on vegetation remains an important topic for climate change studies. Our results show that the SPEI significantly improved extreme drought and mostly affected the SPEI-06 and SPEI-12 growing seasons in East Asia during 1981-2018. The dry and wet annual SPEI trends mostly affect the five sub-regions of East Asia. The annual SPEI had two extremely dry spells during 1936-1947 and 1978-2018. Japan, South Korea, and North Korea are wet in the summer compared to other regions of East Asia, with drought frequency occurring at 51.4%, respectively. The mean drought frequencies in China and Mongolia are 57.4% and 54.6%. China and Mongolia are the driest regions in East Asia due to high drought frequency and duration. The spatial seasonal analysis of solar radiation (SR), water vapor pressure (WVP), wind speed (WS), vegetation condition index (VCI), temperature condition index (TCI), and vegetation health index (VHI) have confirmed that the East Asia region suffered from maximum drought events. The seasonal variation of SPEI shows no clear drying trends during summer and autumn seasons. During the winter and spring seasons, there was a dry trend in East Asia region. During 1902-1990, a seasonal SPEI presented diverse characteristics, with clear wet trends in Japan, Mongolia, and North Korea in four different growing seasons, with dry trends in China and South Korea. During 1991-2018, seasonal SPEI presented clear dry trends in Japan, Mongolia, and North Korea in different growing seasons, while China and South Korea showed a wet trend during the spring, autumn, and winter seasons. This ecological and climatic mechanism provides a good basis for the assessment of vegetation and drought-change variations within East Asia. An understandings of long-term vegetation trends and the effects of rainfall and SPEI on droughts of varying severity is essential for water resource management and climate change adaptation. Based on the results, water resources will increase under global warming, which may alleviate the water scarcity issue in the East Asia region.

Identification and Validation of Hub Genes Related to Neutrophil Extracellular Traps-Mediated Cell Damage During Myocardial Infarction.

Purpose: Studies have shown that neutrophil-mediated formation of neutrophil extracellular traps (NETs) leads to increased inflammatory response and cellular tissue damage during myocardial infarction (MI). We aimed to identify and validate possible hub genes in the process of NETs-mediated cell damage. Methods: We performed an immune cell infiltration analysis of the MI transcriptome dataset based on CIBERSORT and ssGSEA algorithms. Gene expression profiles of NETs formation (GSE178883) were used to analyze the physiological processes of peripheral blood neutrophils after phorbol myristate acetate (PMA) stimulation. Bioinformatics and machine learning algorithms were utilized to find candidate hub genes based on NETs-related genes and transcriptome datasets (GSE66360 and GSE179828). We generated the receiver operating curve (ROC) to evaluate the diagnostic value of hub genes. Next, the correlation between hub genes and immune cells was analyzed using CIBERSORT, ssGSEA and xCell algorithms. Finally, we used quantitative real-time PCR (qRT-PCR) and immunohistochemistry to verify gene expression. Results: Immune cell infiltration analysis revealed that inflammatory cells such as neutrophils were highly expressed in the peripheral blood of patients with MI. Functional analysis of differentially expressed genes (DEGs) in GSE178883 indicated that the potential pathogenesis lies in immune terms. Using weighted gene co-expression network analysis (WGCNA) and machine learning algorithms, we finally identified the seven hub genes (FCAR, IL1B, MMP9, NFIL3, CXCL2, ICAM1, and ZFP36). The qRT-PCR results showed that IL-1B, MMP9, and NFIL3 mRNA expression was up-regulated in the MI group compared to the control. Immunohistochemical results showed high MMP9, IL-1B, and NFIL3 expression in the infarcted area compared to the non-infarcted area and sham-operated groups. Conclusion: We identified seven hub genes associated with NETs-mediated cellular damage during MI. Our results may provide insights into the mechanisms of neutrophil-mediated cell injury during MI.

Distribution Patterns of Gymnosperm Species along Elevations on the Qinghai-Tibet Plateau: Effects of Climatic Seasonality, Energy-Water, and Physical Tolerance Variables.

Climate change is one of the most prominent factors influencing the spatial distribution of plants in China, including gymnosperms. Climatic factors influence gymnosperm distribution along elevational gradients on the Qinghai-Xizang (Tibet) Plateau (QTP), and understanding how species adapt to these factors is important for identifying the impacts of global climate change. For the first time, we examined the county-level distribution of gymnosperm species on QTP using data from field surveys, published works, monographs, and internet sources. We used simulated distribution data of gymnosperms (N = 79) along the elevational gradients to investigate the overall impact of environmental variables in explaining the richness pattern of gymnosperms. Eighteen environmental variables were classified into three key variable sets (climatic seasonality, energy-water, and physical tolerance). We employed principal component analysis and generalized linear models to assess the impact of climatic variables on the gymnosperm's richness pattern. Gymnosperm species are unevenly distributed across the plateau and decline gradually from the southeast to the northwest. The altitudinal gradients have a unimodal relationship with the richness of gymnosperms, with the maximum species richness at an elevation of 3200 m. The joint effects of physical tolerance and energy-water predictors have explained the highest diversity of gymnosperms at mid-elevation. Because the richness peak correlates significantly with the wettest month's precipitation and moisture index, this confirms the significance of moisture on gymnosperm distributions due to increased precipitation during the wet season. Furthermore, our results provide evidence that climatic seasonality factors are involved in the decline of gymnosperm richness at high elevations. A total of 37% of gymnosperm species on QTP are listed as vulnerable, nearly threatened, or endangered, with elevations ranging from 600 m to 5300 m. As a result, we conclude that gymnosperms are at high risk of extinction because of the current climate fluctuations caused by global climate change. Our research offers fundamental data for the study and protection of gymnosperm species along the steepest elevation gradients.

MaxEnt model strategies to studying current and future potential land suitability dynamics of wheat, soybean and rice cultivation under climatic change scenarios in East Asia.

Climate change and variability are projected to alter the geographic suitability of lands for crops cultivation. Accurately predicting changes in the potential current and future land suitability distribution dynamics of wheat (Triticum aestivum), soybean (Glycine max) and rice (Oryza sativa) crops due to climate change scenarios is critical to adapting and mitigating the impacts of bioclimatic changes, and plays a significant role in securing food security in East Asia region. This study compiled large datasets of wheat, soybean and rice occurrence locations from GBIF and 19 bioclimatic variables obtained from the WorldClim database that affect crops growth. We recognized potential future suitable distribution regions for crops under the one socioeconomic pathway, (SSP585) for 2021-2040 and 2041-2060, using the MaxEnt model. The accuracy of the MaxEnt was highly significant with mean AUC values ranging from 0.833 to 0.882 for all models evaluated. The jackknife test revealed that for wheat, Bio4 and Bio12 contributed 17.6% and 12.6%, for soybean Bio10 and Bio12 contributed 15.6% and 49.5%, while for rice Bio12 and Bio14 contributed 12.9% and 36.0% to the MaxEnt model. In addition, cultivation aptitude for wheat, soybean, and rice increased in southeast China, North Korea, South Korea, and Japan, while decreasing in Mongolia and northwest China. Climate change is expected to increase the high land suitability for wheat, soybean, and rice in East Asia. Simulation results indicate an average decrease of unsuitable areas of -98.5%, -41.2% and -36.3% for wheat, soybean and rice from 2060 than that of current land suitability. In contrast, the high land suitable for wheat, soybean and rice cultivation is projected to increase by 75.1%, 68.5% and 81.9% from 2060 as compared with current. The findings of this study are of utmost importance in the East Asia region as they present an opportunity for policy makers to develop appropriate adaptation and mitigation strategies required to sustain crops distribution under future climates. Although the risks of wheat, soybean and rice cultivation may be significantly higher in the future because of high temperatures, heat waves, and droughts caused by climate change.

Erratum to "Phillyrin Mitigates Apoptosis and Oxidative Stress in Hydrogen Peroxide-Treated RPE Cells through Activation of the Nrf2 Signaling Pathway".

[This corrects the article DOI: 10.1155/2020/2684672.].

Iridoid glycosides from Morinda officinalis induce lysosomal biogenesis and promote autophagic flux to attenuate oxidative stress.

Morinda officinalis is a traditional Chinese tonic herb, and have been used in the treatment of multiple diseases. Here, three iridoid glycosides isolated from M. officinalis were evaluated for their roles in the autophagy-lysosomal pathway. All three iridoid glycosides could induce TFEB/TFE3-mediated lysosomal biogenesis and trigger autophagy. Interestingly, they promoted the nuclear import of TFEB/TFE3 without affecting their nuclear export, suggesting their role in the maintenance of lysosomal homeostasis. The results from this study shed light on the identification of autophagy activators from M. officinalis and provide a basis for developing them in the treatment of oxidative stress-involved diseases.

U-shaped association between plasma C-peptide and sarcopenia: A cross-sectional study of elderly Chinese patients with diabetes mellitus.

Limited research exists regarding the relationship between fasting plasma C-peptide levels and sarcopenia. As a result, our study aimed to examine this association in elderly Chinese diabetic patients. This cross-sectional study included 288 elderly patients with diabetes mellitus from the Fourth People's Hospital in Guiyang who were enrolled prospectively between March 2020 and February 2023. The independent variable of interest was fasting plasma C-peptide, while the dependent variable was sarcopenia. Data on several covariates, including demographic factors, lifestyle habits, co-morbidities, anthropometric indicators, and laboratory indicators, were also collected. Of the 288 participants, 27.43% (79/288) had sarcopenia. After adjusting for potential confounding variables, we found a U-shaped association between fasting plasma C-peptide levels and sarcopenia, with inflection points identified at approximately 774 pmol/L and 939 mmol/L. Within the range of 50-744 pmol/L, each 100 pmol/L increase in CysC was associated with a 37% decrease in the odds of sarcopenia (odds ratio [OR], 0.63; 95% confidence interval [CI], 0.49 to 0.83; P < 0.001). Additionally, within the range of 939-1694 pmol/L, each 100 pmol/L increase in fasting plasma C-peptide was associated with a 76% increase in the odds of sarcopenia (odds ratio [OR], 1.76; 95% confidence interval [CI], 1.11 to 2.81; P = 0.017). Our study revealed a U-shaped association between fasting plasma C-peptide levels and the likelihood of sarcopenia, with lower risk in the range of 774-939 pmol/L. These findings may assist in the development of more effective prevention and treatment strategies for sarcopenia in elderly diabetic patients.

Artificial intelligence in theranostics of gastric cancer, a review.

Gastric cancer (GC) is one of the commonest cancers with high morbidity and mortality in the world. How to realize precise diagnosis and therapy of GC owns great clinical requirement. In recent years, artificial intelligence (AI) has been actively explored to apply to early diagnosis and treatment and prognosis of gastric carcinoma. Herein, we review recent advance of AI in early screening, diagnosis, therapy and prognosis of stomach carcinoma. Especially AI combined with breath screening early GC system improved 97.4 % of early GC diagnosis ratio, AI model on stomach cancer diagnosis system of saliva biomarkers obtained an overall accuracy of 97.18 %, specificity of 97.44 %, and sensitivity of 96.88 %. We also discuss concept, issues, approaches and challenges of AI applied in stomach cancer. This review provides a comprehensive view and roadmap for readers working in this field, with the aim of pushing application of AI in theranostics of stomach cancer to increase the early discovery ratio and curative ratio of GC patients.

Favorable impact of a novel endoscopic auxiliary system (NEAS) on fluoroscopy-guided lithotripsy for difficult bile duct stones: A pilot study.

OBJECTIVES: Laser lithotripsy under fluoroscopic guidance is difficult to perform and risky due to its invisibility. In this study we aimed to investigate the efficacy and safety of a novel endoscopic auxiliary system (NEAS)-assisted lithotripsy under fluoroscopy for treating difficult common bile duct (CBD) stones. METHODS: Patients with difficult CBD stones who were treated with NEAS-assisted laser lithotripsy (NEAS group) or conventional mechanical lithotripsy (ML) under fluoroscopy (ML group) were retrospectively evaluated. The primary outcome was the complete stone clearance rate and the secondary outcomes included operation time, complications, and medical cost. RESULTS: Seventeen patients were treated with NEAS-assisted laser lithotripsy and 144 patients underwent ML. Using the propensity score matching analysis, 17 pairs of cases treated with NEAS-assisted lithotripsy and ML were included. Patients in the NEAS group showed a higher stone clearance rate than the ML group (94.1% vs 58.8%, P = 0.039), as well as shorter operation time (41.9 min vs 49.4 min, P < 0.001) and lower medical cost (USD 4607 vs USD 5014, P < 0.001). There was no significant difference in the complication rate between the two groups (5.9% vs 17.6%, P = 0.601). CONCLUSION: NEAS-assisted fluoroscopy-guided laser lithotripsy is feasible and safe, which may be a promising technique in fluoroscopy-guided laser lithotripsy for difficult CBD stones.

The diagnosis interval influences risk factors of mortality in patients with co-existent active tuberculosis and lung cancer: a retrospective study.

BACKGROUND: Previous studies reported that tuberculosis (TB) is associated with an increased risk of lung cancer or the survival and mortality of lung cancer. However, the impact of coexisting TB on the survival of lung cancer patients was controversial. We aimed to identify risk factors on the survival rate of patients with co-existent active TB and lung cancer. METHODS: One hundred seventy-three patients diagnosed with active TB and lung cancer from January 2016 to August 2021 in Shanghai pulmonary hospital were selected and divided into two groups (≤ 6 months, > 6 months) according to the diagnosis interval between active TB and lung cancer (the order of diagnosis is not considered). The clinical characteristics and survival were analyzed. Univariate and multivariate logistic regression analyses were used to identify the risk factors for overall survival (OS). RESULTS: One hundred seventy-three patients were diagnosed with lung cancer and active TB. The study population exhibited a median age of 64 years, with a majority of 81.5% being male, 58.0% of patients had a history of smoking. Among those involved, 93.6% had pulmonary TB, 91.9% were diagnosed with non-small cell lung cancer (NSCLC), 76.9% were Eastern Cooperative Oncology Group (ECOG) 0-2 and 12.7% were ECOG 3-4. We observed better survival in the > 6 months group compared with the ≤ 6 months group (hazard ratio [HR] 0.456, 95% confidence interval [CI]:0.234-0.889, P = 0.017). The 1-, 3-, and 5- year OS rates were 94.2%, 80.3%, and 77.6%, respectively, in the > 6 months group and 88.3%, 63.8%, and 58.5%, respectively, in the ≤ 6 months group. Surgery (HR 0.193, [95% CI, 0.038-0.097]; P = 0.046) and ECOG Performance Status (HR 12.866, [95% CI, 2.730-60.638]; P = 0.001) were independent prognostic factors in the > 6 months group. CONCLUSIONS: Patients diagnosed with lung cancer and active TB for more than half a year have a significantly better prognosis than those diagnosed within half a year. ECOG Performance Status and surgery might possibly affect the outcomes of patients with co-existent active TB and lung cancer.