OBJECTIVE: Although dietary preferences influence chronic diseases, few studies have linked dietary preferences to mortality risk, particularly in large cohorts. To investigate the relationship between dietary preferences and mortality risk (all-cause, cancer, and cardiovascular disease [CVD]) in a large adult cohort. METHODS: A cohort of 1,160,312 adults (mean age 62.48 ± 9.55) from the Shenzhen Healthcare Big Data Cohort (SHBDC) was analyzed. Hazard ratios ( HRs) for mortality were estimated using the Cox proportional hazards model. RESULTS: The study identified 12,308 all-cause deaths, of which 3,865 (31.4%) were cancer-related and 3,576 (29.1%) were attributed to CVD. Compared with a mixed diet of meat and vegetables, a mainly meat-based diet (hazard ratio [ HR] = 1.13; 95% confidence interval [ CI]: 1.02, 1.27) associated with a higher risk of all-cause mortality, while mainly vegetarian ( HR = 0.87; 95% CI: 0.78, 0.97) was linked to a reduced risk. Furthermore, there was a stronger correlation between mortality risk and dietary preference in the > 65 age range. CONCLUSION A meat-based diet was associated with an increased risk of all-cause mortality, whereas a mainly vegetarian diet was linked to a reduced risk.
Humans ; China/epidemiology* ; Middle Aged ; Male ; Female ; Prospective Studies ; Aged ; Cardiovascular Diseases/mortality* ; Diet/statistics & numerical data* ; Neoplasms/mortality* ; Adult ; Cause of Death ; Food Preferences ; Proportional Hazards Models ; Mortality ; Cohort Studies

OBJECTIVE To evaluate the cost-effectiveness of trastuzumab biosimilars （Hanquyou） versus original drug （Hesaiting） in the treatment of recurrent/metastatic human epidermal growth factor receptor-2 （HER-2） positive breast cancer. METHODS A partitional survival model was constructed based on the NCT03084237 trial data. The simulation period was 3 weeks， and the simulation time was 10 years. Using costs and quality-adjusted life year （QALY） as the output indicator， the cost- utility analysis method was used to evaluate the cost-effectiveness of the two schemes mentioned above. Univariate and probabilistic sensitivity analyses were performed to verify the robustness of the basic analysis. RESULTS The costs of the trastuzumab biosimilars group and original drug group were 111 516.72 yuan and 111 122.30 yuan respectively， with health utility values of 1.52 QALYs and 1.36 QALYs， and ICER of 2 465.12 yuan/QALY， which were less than 3 times China’s per capita gross domestic product （GDP） in 2023 as the threshold for willingness-to-pay （WTP） （268 200 yuan/QALY）. Univariate sensitivity analysis showed that the cost of the trastuzumab biosimilars and original drug had a great impact on the ICER. The probabilistic sensitivity analysis showed that the probability of trastuzumab biosimilars being cost-effective was 100% at WTP threshold of 14 902 yuan/QALY. CONCLUSIONS When WTP threshold is 3 times China’s GDP in 2023 （268 200 yuan/QALY）， compared with original drug， trastuzumab biosimilars have good cost-effectiveness in the treatment of recurrent/metastatic HER-2 positive breast cancer.

Objective To explore the mechanism of'homotherapy for heteropathy'Zhigancao Decoction in the treatment of coronary heart disease arrhythmia and pulmonary fibrosis by network pharmacology and molecular docking technology.Methods All the active components of Zhigancao Decoction were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP)and Herbal Compendium(HERB).The SwissTargetPrediction database was used to predict the targets.Cytoscape software was used to construct the drugs-targets network diagram and network topology analysis was performed to obtain the core drug targets.The disease targets of coronary heart disease,arrhythmia and pulmonary fibrosis were obtained in GeneCards and OMIM databases,and the intersection targets of Chinese medicine and disease were obtained by Venny software.The intersection targets were imported into the STRING online database to construct a protein-protein interaction network,and the data were imported into Cytoscape software for visualization and screening of core targets.Gene ontology(GO)function enrichment analysis and kyto encyclo-pedia of genes and genomes(KEGG)pathway enrichment analysis were performed on the intersection targets using the Metascape database.Molecular docking verification and heat map visualization were performed on the core intersection target and the core drug target through the CB-DOCK2 online platform.Results A total of 137 active components of Zhigancao Decoction were screened out,and 848 corresponding drug targets were obtained by removing repeated values.A total of 9 962 targets of coronary heart disease,5 735 targets of arrhythmia and 7 722 targets of pulmonary fibrosis were obtained.A total of 362 drug-disease intersection targets were obtained by Venny platform processing.The potential core targets with higher degree values were GAPDH,IL-6,ALB,STAT3,TNF,MMP-9 and so on by network topology analysis.GO functional enrichment analysis showed that the main biological processes(BP)involved in Zhigancao Decoction'homotherapy for heteropathy'were the response to hormones,the positive regulation of circulatory system process,phosphorus metabolism process,the response to exogenous stimulation,and the response to organic matter,the main cellular components(CC)include lipid rafts,receptor complexes,cytoplasmic perinuclear regions,dendrites,membrane sides,etc.,the main molecular functions(MF)include protein kinase activity,kinase binding,protein homopolymerization activity,nuclear receptor activity,heme binding,etc..KEGG pathway enrichment analysis showed that the main signaling pathways involved in Zhigancao Decoction'homotherapy for heteropathy'were lipid and atherosclerosis,calcium signaling pathway,cAMP signaling pathway,insulin resistance,cGMP-PKG signaling pathway,JAK-STAT signaling pathway,NF-κB signaling pathway,etc..The results of molecular docking suggested that there was a good binding activity between the main active component targets of Zhigancao Decoction and the core targets of'homotherapy for heteropathy'.Conclusion Zhigancao Decoction mainly regulates JAK-STAT,NF-κB,cAMP and other signaling pathways,acts on IL-6,STAT3,TNF,MMP-9 and other gene targets,and exerts the effect of'homotherapy for heteropathy'on coronary heart disease arrhythmia and pulmonary fibrosis.

Endoplasmic reticulum is an important organelle in eukaryotic cells,which is responsible for the folding,processing and transportation of secretory proteins.A variety of stimuli inside and outside cells can lead to the accumulation of misfolded or unfolded proteins in the endoplasmic reticulum,resulting in abnormal structure and function of the endoplasmic reticulum,which is called endoplasmic reticulum stress(ERS).Endoplasmic reticulum autophagy is an important endogenous mechanism to alleviate ERS.It is often considered as a cell protective procedure,which participates in many important physiological processes,such as metabolism,immune response,inflammatory response and cell proliferation.Endoplasmic reticulum autophagy is an important endogenous protective mechanism to alleviate endoplasmic reticulum stress and restore the endoplasmic reticulum homeostasis,through eliminating redundant and disabled endoplasmic reticulum membrane and macromolecular protein complexes,which is critical to cell function and fate.This paper reviews the types of endoplasmic reticulum autophagy,related specific receptors,main regulatory mechanisms,and its role and significance in the related diseases.

Objective: To investigate the ability of radiological parameter canal bone ratio (CBR) to assess bone mineral density and to differentiate between patients with primary and multiple osteoporotic vertebral compression fracture (OVCF). Methods: A retrospective analysis was conducted on OVCF patients treated at our hospital. CBR was measured through full-spine x-rays. Patients were categorized into primary and multiple fracture groups. Receiver operating characteristic curve analysis and area under the curve (AUC) calculation were used to assess the ability of parameters to predict osteoporosis and multiple fractures. Predictors of T values were analyzed by multiple linear regression, and independent risk factors for multiple fractures were determined by multiple logistic regression analysis. Results: CBR showed a moderate negative correlation with dual-energy x-ray absorptiometry T values (r = -0.642, p < 0.01). Higher CBR (odds ratio [OR], -6.483; 95% confidence interval [CI], -8.234 to -4.732; p < 0.01) and lower body mass index (OR, 0.054; 95% CI, 0.023–0.086; p < 0.01) were independent risk factors for osteoporosis. Patients with multiple fractures had lower T values (mean ± standard deviation [SD]: -3.76 ± 0.73 vs. -2.83 ± 0.75, p < 0.01) and higher CBR (mean ± SD: 0.54 ± 0.07 vs. 0.46 ± 0.06, p < 0.01). CBR had an AUC of 0.819 in predicting multiple fractures with a threshold of 0.53. T values prediction had an AUC of 0.816 with a threshold of -3.45. CBR > 0.53 was an independent risk factor for multiple fractures (OR, 14.66; 95% CI, 4.97–43.22; p < 0.01). Conclusion CBR is negatively correlated with bone mineral density (BMD) and can be a novel opportunistic BMD assessment method. It is a simple and effective measurement index for predicting multiple fractures, with predictive performance not inferior to T values.

Objective: To investigate the ability of radiological parameter canal bone ratio (CBR) to assess bone mineral density and to differentiate between patients with primary and multiple osteoporotic vertebral compression fracture (OVCF). Methods: A retrospective analysis was conducted on OVCF patients treated at our hospital. CBR was measured through full-spine x-rays. Patients were categorized into primary and multiple fracture groups. Receiver operating characteristic curve analysis and area under the curve (AUC) calculation were used to assess the ability of parameters to predict osteoporosis and multiple fractures. Predictors of T values were analyzed by multiple linear regression, and independent risk factors for multiple fractures were determined by multiple logistic regression analysis. Results: CBR showed a moderate negative correlation with dual-energy x-ray absorptiometry T values (r = -0.642, p < 0.01). Higher CBR (odds ratio [OR], -6.483; 95% confidence interval [CI], -8.234 to -4.732; p < 0.01) and lower body mass index (OR, 0.054; 95% CI, 0.023–0.086; p < 0.01) were independent risk factors for osteoporosis. Patients with multiple fractures had lower T values (mean ± standard deviation [SD]: -3.76 ± 0.73 vs. -2.83 ± 0.75, p < 0.01) and higher CBR (mean ± SD: 0.54 ± 0.07 vs. 0.46 ± 0.06, p < 0.01). CBR had an AUC of 0.819 in predicting multiple fractures with a threshold of 0.53. T values prediction had an AUC of 0.816 with a threshold of -3.45. CBR > 0.53 was an independent risk factor for multiple fractures (OR, 14.66; 95% CI, 4.97–43.22; p < 0.01). Conclusion CBR is negatively correlated with bone mineral density (BMD) and can be a novel opportunistic BMD assessment method. It is a simple and effective measurement index for predicting multiple fractures, with predictive performance not inferior to T values.

Objective: To investigate the ability of radiological parameter canal bone ratio (CBR) to assess bone mineral density and to differentiate between patients with primary and multiple osteoporotic vertebral compression fracture (OVCF). Methods: A retrospective analysis was conducted on OVCF patients treated at our hospital. CBR was measured through full-spine x-rays. Patients were categorized into primary and multiple fracture groups. Receiver operating characteristic curve analysis and area under the curve (AUC) calculation were used to assess the ability of parameters to predict osteoporosis and multiple fractures. Predictors of T values were analyzed by multiple linear regression, and independent risk factors for multiple fractures were determined by multiple logistic regression analysis. Results: CBR showed a moderate negative correlation with dual-energy x-ray absorptiometry T values (r = -0.642, p < 0.01). Higher CBR (odds ratio [OR], -6.483; 95% confidence interval [CI], -8.234 to -4.732; p < 0.01) and lower body mass index (OR, 0.054; 95% CI, 0.023–0.086; p < 0.01) were independent risk factors for osteoporosis. Patients with multiple fractures had lower T values (mean ± standard deviation [SD]: -3.76 ± 0.73 vs. -2.83 ± 0.75, p < 0.01) and higher CBR (mean ± SD: 0.54 ± 0.07 vs. 0.46 ± 0.06, p < 0.01). CBR had an AUC of 0.819 in predicting multiple fractures with a threshold of 0.53. T values prediction had an AUC of 0.816 with a threshold of -3.45. CBR > 0.53 was an independent risk factor for multiple fractures (OR, 14.66; 95% CI, 4.97–43.22; p < 0.01). Conclusion CBR is negatively correlated with bone mineral density (BMD) and can be a novel opportunistic BMD assessment method. It is a simple and effective measurement index for predicting multiple fractures, with predictive performance not inferior to T values.

Objective: To investigate the ability of radiological parameter canal bone ratio (CBR) to assess bone mineral density and to differentiate between patients with primary and multiple osteoporotic vertebral compression fracture (OVCF). Methods: A retrospective analysis was conducted on OVCF patients treated at our hospital. CBR was measured through full-spine x-rays. Patients were categorized into primary and multiple fracture groups. Receiver operating characteristic curve analysis and area under the curve (AUC) calculation were used to assess the ability of parameters to predict osteoporosis and multiple fractures. Predictors of T values were analyzed by multiple linear regression, and independent risk factors for multiple fractures were determined by multiple logistic regression analysis. Results: CBR showed a moderate negative correlation with dual-energy x-ray absorptiometry T values (r = -0.642, p < 0.01). Higher CBR (odds ratio [OR], -6.483; 95% confidence interval [CI], -8.234 to -4.732; p < 0.01) and lower body mass index (OR, 0.054; 95% CI, 0.023–0.086; p < 0.01) were independent risk factors for osteoporosis. Patients with multiple fractures had lower T values (mean ± standard deviation [SD]: -3.76 ± 0.73 vs. -2.83 ± 0.75, p < 0.01) and higher CBR (mean ± SD: 0.54 ± 0.07 vs. 0.46 ± 0.06, p < 0.01). CBR had an AUC of 0.819 in predicting multiple fractures with a threshold of 0.53. T values prediction had an AUC of 0.816 with a threshold of -3.45. CBR > 0.53 was an independent risk factor for multiple fractures (OR, 14.66; 95% CI, 4.97–43.22; p < 0.01). Conclusion CBR is negatively correlated with bone mineral density (BMD) and can be a novel opportunistic BMD assessment method. It is a simple and effective measurement index for predicting multiple fractures, with predictive performance not inferior to T values.

Objective: To investigate the ability of radiological parameter canal bone ratio (CBR) to assess bone mineral density and to differentiate between patients with primary and multiple osteoporotic vertebral compression fracture (OVCF). Methods: A retrospective analysis was conducted on OVCF patients treated at our hospital. CBR was measured through full-spine x-rays. Patients were categorized into primary and multiple fracture groups. Receiver operating characteristic curve analysis and area under the curve (AUC) calculation were used to assess the ability of parameters to predict osteoporosis and multiple fractures. Predictors of T values were analyzed by multiple linear regression, and independent risk factors for multiple fractures were determined by multiple logistic regression analysis. Results: CBR showed a moderate negative correlation with dual-energy x-ray absorptiometry T values (r = -0.642, p < 0.01). Higher CBR (odds ratio [OR], -6.483; 95% confidence interval [CI], -8.234 to -4.732; p < 0.01) and lower body mass index (OR, 0.054; 95% CI, 0.023–0.086; p < 0.01) were independent risk factors for osteoporosis. Patients with multiple fractures had lower T values (mean ± standard deviation [SD]: -3.76 ± 0.73 vs. -2.83 ± 0.75, p < 0.01) and higher CBR (mean ± SD: 0.54 ± 0.07 vs. 0.46 ± 0.06, p < 0.01). CBR had an AUC of 0.819 in predicting multiple fractures with a threshold of 0.53. T values prediction had an AUC of 0.816 with a threshold of -3.45. CBR > 0.53 was an independent risk factor for multiple fractures (OR, 14.66; 95% CI, 4.97–43.22; p < 0.01). Conclusion CBR is negatively correlated with bone mineral density (BMD) and can be a novel opportunistic BMD assessment method. It is a simple and effective measurement index for predicting multiple fractures, with predictive performance not inferior to T values.