Objective To investigate disparities in health levels among populations across different regions of China and analyze the relationship between these disparities and regional, social, and economic factors, and to provide recommendations to promote health equity. Methods Based on the data from the Seventh National Population Census, this study employed spatial autocorrelation analysis and the spatial Durbin model to conduct spatial and temporal analyses of the health status of the national population from 2012 to 2021, focusing on the regional distribution of health levels and related influencing factors. Results 1. Regional disparities: The mortality rate in Gansu Province rose from 6.05‰ in 2012 to 8.26‰ in 2021, whereas the mortality rate in eastern provinces such as Hainan Province was relatively low in 2021 (5.39‰). 2. Spatial clustering: The spatial correlation of mortality rates was weak (Moran's I: 0.134-0.245), and the high mortality clusters showed a shift from southwest to northeast region. 3. Influencing factors: Economic conditions, education quality, urbanization levels, and healthcare resources significantly impacted population mortality rates. Conclusion The present study identifies pronounced regional disparities in population health, providing a scientific basis for formulating targeted healthcare policies. Additionally, this study highlights the critical importance of spatial analysis in understanding and addressing public health issues to advance health equity.

Objective To explore the mediating role of activities of daily living (ADL) in pain and depressive symptoms in the elderly in China. Methods Utilizing the data from 2020 China Health and Retirement Longitudinal Study, 4403 Chinese elderly individuals aged ≥ 60 years old were selected as the research subjects. Depression Scale (CES-D 10) of the Center for Epidemiological Survey and ADL scale were used in the study. The PROCESS4.1 macro was used to test the mediating effect of daily living activities between pain and depressive symptoms, and the Bootstrap method was applied for verification of the mediating variables. Results A total of 2368 cases of depressive symptoms were detected in the elderly in China, with a detection rate of 53.78%. Pain was positively correlated with depressive symptoms (r=0.27, P<0.01), and activities of daily living were negatively correlated with pain and depressive symptoms (r=-0.27, -0.337, P<0.01). The results showed that the total effect value of pain on depressive symptoms was 0.33, the direct effect value was 0.24, and the mediating effect value of daily living activities was 0.09, accounting for 27.27%. Conclusion Pain and activities of daily living are important factors influencing depressive symptoms in the elderly, and activities of daily living play a partial mediating role in the relationship between pain and depressive symptoms in the elderly.

Alzheimer’s disease (AD) is a central neurodegenerative disease characterized by progressive cognitive decline and memory impairment in clinical. Currently, there are no effective treatments for AD. In recent years, a variety of therapeutic approaches from different perspectives have been explored to treat AD. Although the drug therapies targeted at the clearance of amyloid β-protein (Aβ) had made a breakthrough in clinical trials, there were associated with adverse events. Neuroinflammation plays a crucial role in the onset and progression of AD. Continuous neuroinflammatory was considered to be the third major pathological feature of AD, which could promote the formation of extracellular amyloid plaques and intracellular neurofibrillary tangles. At the same time, these toxic substances could accelerate the development of neuroinflammation, form a vicious cycle, and exacerbate disease progression. Reducing neuroinflammation could break the feedback loop pattern between neuroinflammation, Aβ plaque deposition and Tau tangles, which might be an effective therapeutic strategy for treating AD. Traditional Chinese herbs such as Polygonum multiflorum and Curcuma were utilized in the treatment of AD due to their ability to mitigate neuroinflammation. Non-steroidal anti-inflammatory drugs such as ibuprofen and indomethacin had been shown to reduce the level of inflammasomes in the body, and taking these drugs was associated with a low incidence of AD. Biosynthetic nanomaterials loaded with oxytocin were demonstrated to have the capability to anti-inflammatory and penetrate the blood-brain barrier effectively, and they played an anti-inflammatory role via sustained-releasing oxytocin in the brain. Transplantation of mesenchymal stem cells could reduce neuroinflammation and inhibit the activation of microglia. The secretion of mesenchymal stem cells could not only improve neuroinflammation, but also exert a multi-target comprehensive therapeutic effect, making it potentially more suitable for the treatment of AD. Enhancing the level of TREM2 in microglial cells using gene editing technologies, or application of TREM2 antibodies such as Ab-T1, hT2AB could improve microglial cell function and reduce the level of neuroinflammation, which might be a potential treatment for AD. Probiotic therapy, fecal flora transplantation, antibiotic therapy, and dietary intervention could reshape the composition of the gut microbiota and alleviate neuroinflammation through the gut-brain axis. However, the drugs of sodium oligomannose remain controversial. Both exercise intervention and electromagnetic intervention had the potential to attenuate neuroinflammation, thereby delaying AD process. This article focuses on the role of drug therapy, gene therapy, stem cell therapy, gut microbiota therapy, exercise intervention, and brain stimulation in improving neuroinflammation in recent years, aiming to provide a novel insight for the treatment of AD by intervening neuroinflammation in the future.

Objective:To investigate the incidence of coronary artery tortuosity and its correlation with poor prognosis in patients with septal hypertrophic cardiomyopathy (HCM).Methods:This was a retrospective cohort study. Patients with septal HCM who were hospitalized in Fuwai Central China Cardiovascular Hospital and Zhengzhou University People′s Hospital between December 1, 2017 and June 10, 2021 were selected. Non-HCM patients were matched by gender, age, and hypertension as control group. Septal HCM was divided into two groups based on the presence or absence of coronary artery tortuosity. Clinical baseline data and coronary angiography findings were compared using a multifactorial logistic analysis of the risk factors for coronary artery tortuosity. Patients were followed up until July 1, 2022, with the primary outcome being the composite endpoint of malignant arrhythmia, ischemic stroke and all-cause death. Incidence densities were compared between the coronary artery tortuosity and non-coronary artery tortuosity groups of septal HCM patients. The Cox risk-ratio model was used to analyze risk factors for primary outcomes in septal HCM patients.Results:There were 156 patients in the septal HCM group and 156 patients in the control group, both aged (57.0±11.4) years, and 75 (48.1%) were female. The incidence of coronary artery tortuosity was significantly higher in the septal HCM group than in the control group (63.5% vs. 36.5%, P<0.01), and the coronary artery tortuosity score was also higher in the septal HCM group than in the control group ( P<0.01). Multiple logistic regression analysis showed that septal HCM was a risk factor for coronary artery tortuosity ( OR=3.27, 95% CI: 2.02-5.29, P<0.01). In the septal HCM patients, after (2.5±1.2) years of follow-up, the incidence density of primary outcome was significantly higher in the coronary artery tortuosity group than in the non-coronary artery tortuosity group ( P=0.02), while each on-point in coronary artery tortuosity score increased the risk of primary outcome by 53% for septal HCM patients ( HR=1.53, 95% CI: 1.26-1.86, P<0.01). Conclusions:Patients with septal HCM are more prone to suffer coronary artery tortuosity and suffer from it to a greater extent. Coronary artery tortuosity is an important risk factor for adverse events in patients with septal HCM.

Based on the correlation between brain and kidney, this article discussed the scientific connotation of tonifying kidney therapy in treating diabetes mellitus in the elderly complicated with cognitive impairment. Kidney-related theory originates from the viscera-related theory of TCM. The brain is the sea of marrow, and the marrow is born of essence, which originates from the qi and blood of the five internal organs, and its root lies in the kidney. Kidney stores essence, governs bone and marrow, and connects with brain, and "kidney-essence-marrow-brain" form a system, which is closely related with each other. The kidney is full of essence and the brain is full of marrow, and the brain is full of intelligence, thus exerting the physiological function of "the brain is the house of wisdom". Both of them depend on each other physiologically, give birth to each other, and affect each other pathologically. Based on the theory of kidney and brain, from the physiological characteristics of old patients' weakness, aging and kidney-qi weakness, and the development trend of diabetes-related encephalopathy caused by "thirst-quenching for a long time, forgetfulness and palpitation", the core therapeutic methods of tonifying kidney, replenishing marrow and brain to treat senile diabetes complicated with cognitive impairment were introduced, and then the basis for the treatment of diabetic cognitive impairment by tonifying kidney was provided from the modern microscopic study of brain and kidney.

Objective To mine and analyze cutaneous adverse drug event(ADE)of eight antibody-drug conjugates(ADC),and to ensure the safe clinical use of ADC drugs.Methods The data was obtained from the U.S.Food and Drug Administration Adverse Event Reporting System(FAERS)for the period from the third quarter of 2011 to the fourth quarter of 2023.The cutaneous ADE associated with 8 eight ADC drugs were identified through the process of specification and standardization of nomenclature.The potential ADE signals were detected using the reporting odds ratio and Bayesian confidence propagation neural network methods.Results A total of 124 234 ADE reports were identified with the 8 ADC drugs as the first suspected drugs,including 5 184 reports of cutaneous ADEs adverse reactions,involving 3 225 patients.A total of 72 preferred term signals were detected for the 8 ADC drugs.The highest number of signals were detected for enfortumab vedotin,followed by ado-trastuzumab emtansine and brentuximab vedotin.Except for detrolizumab,the first-day incidence of cutaneous ADEs associated with the remaining 7 ADC drugs was less than 30％.The median time of occurrence for the 7 drugs,excluding brentuximab vedotin,was within one course of treatment(21 d).Conclusion The risks of cutaneous ADEs was variable with ADC drugs,occurs early in treatment and poses a potential life-threatening danger.Therefore,clinical vigilance and close monitoring of skin conditions are essential during ADC drug use.

The compounds were isolated and purified by silica gel, MCI, Sephadex LH-20 and semi-preparative high performance liquid chromatography. The structures of the compounds were determined by NMR and MS spectroscopic data. Twenty monomer compounds were isolated from the ethyl acetate extract of Lindera reflexa root from Hunan province, and identified as: (1″S,3″S,6″R)-2′,4′,6′-trihydroxy-3′-[1″-(3″-hydroxy)-p-menthanyl]-chalcone (1), sumadain D (2), quercetin (3), catechin (4), epicatechin (5), N-cis-feruloyltyramine (6), N-trans-feruloyltyramine (7), N-trans-feruloyl-3-methoxytyramine (8), flavifloramides B (9), northalifoline (10), isolariciresinol (11), syringaresinol (12), pinoresinol (13), medioresinol (14), dehydroconiferyl alcohol (15), 4-methoxyl-denudaquinol (16), miliusanal (17), syringic acid (18), abscisic acid (19), (E)-cinnamyl-(E)-cinnamate (20). Compound 1 is a new compound, and compounds 2‒20 have been isolated from Lindera reflexa for the first time. The results showed that compounds 1, 2, 3 and 16 could significantly reduce the survival ability of MGC-803 cells with IC₅₀ values of 5.58, 23.41, 25.72 and 20.96 μmol·L^-1, respectively. Compounds 5 and 20 can reduce the survival ability of MGC-803 cells with IC₅₀ values of 98.83 and 89.26 μmol·L^-1, respectively.

Objective The purpose of this study was to investigate the bacterial communities of biting midges and ticks collected from three sites in the Poyang Lake area,namely,Qunlu Practice Base,Peach Blossom Garden,and Huangtong Animal Husbandry,and whether vectors carry any bacterial pathogens that may cause diseases to humans,to provide scientific basis for prospective pathogen discovery and disease prevention and control. Methods Using a metataxonomics approach in concert with full-length 16S rRNA gene sequencing and operational phylogenetic unit(OPU)analysis,we characterized the species-level microbial community structure of two important vector species,biting midges and ticks,including 33 arthropod samples comprising 3,885 individuals,collected around Poyang Lake. Results A total of 662 OPUs were classified in biting midges,including 195 known species and 373 potentially new species,and 618 OPUs were classified in ticks,including 217 known species and 326 potentially new species.Surprisingly,OPUs with potentially pathogenicity were detected in both arthropod vectors,with 66 known species of biting midges reported to carry potential pathogens,including Asaia lannensis and Rickettsia bellii,compared to 50 in ticks,such as Acinetobacter lwoffii and Staphylococcus sciuri.We found that Proteobacteria was the most dominant group in both midges and ticks.Furthermore,the outcomes demonstrated that the microbiota of midges and ticks tend to be governed by a few highly abundant bacteria.Pantoea sp7 was predominant in biting midges,while Coxiella sp1 was enriched in ticks.Meanwhile,Coxiella spp.,which may be essential for the survival of Haemaphysalis longicornis Neumann,were detected in all tick samples.The identification of dominant species and pathogens of biting midges and ticks in this study serves to broaden our knowledge associated to microbes of arthropod vectors. Conclusion Biting midges and ticks carry large numbers of known and potentially novel bacteria,and carry a wide range of potentially pathogenic bacteria,which may pose a risk of infection to humans and animals.The microbial communities of midges and ticks tend to be dominated by a few highly abundant bacteria.

Objective:This study aims to explore the predictive value of T2-weighted imaging (T2WI), apparent diffusion coefficient (ADC), and early-delayed phases enhanced magnetic resonance imaging (DCE-MRI) radiomics prediction model in determining human epidermal growth factor receptor 2 status in breast cancer.Methods:A retrospective study was conducted, involving 187 patients with confirmed breast cancer by postsurgical pathology at Zhenjiang First People's Hospital during January 2021 and May 2023. Immunohistochemistry or fluorescence in situ hybridization was used to determine the HER-2 status of these patients, with 48 cases classified as HER-2 positive and 139 cases as HER-2 negative. The training set was used to construct the prediction models and the validation set was used to verify the prediction models. Layers of T2WI, ADC, and early-delayed phase DCE-MRI images were used to delineate the volumeof interest and 960 radiomic features were extracted from each case using Pyradiomic. After screening and dimensionality reduction by intraclass correlation coefficient, Pearson correlation analysis, least absolute shrinkage, and selection operator, the radiomics labels were established. Logistic regression analysis was used to construct the T2WI radiomics model, ADC radiomics model, DCE-2 radiomics model, DCE-6 radiomics model, and the joint sequence radiomics model to predict the HER-2 expression status of breast cancer, respectively. Based on the clinical, pathological, and MRI image characteristics of patients, univariate and multivariate logistic regression analysis wasused to construct a clinicopathological MRI feature model. The radscore of every patient and the clinicopathological MRI features which were statistically significant after screening were used to construct a nomogram model. The receiver operating characteristic (ROC) curve was used to evaluate the predictive performance of each model and the decision curve analysis wasused to evaluate the clinical usefulness.Results:The T2WI, ADC, DCE-2, DCE-6, and joint sequence radiomics models, the clinicopathological MRI feature model, and the nomogram model were successfully constructed to predict the expression status of HER-2 in breast cancer. ROC analysis showed that in the training set and validation set, the areas under the curve (AUC) of the T2WI radiomics model were 0.797 and 0.760, of the ADC radiomics model were 0.776 and 0.634, of the DCE-2 radiomics model were 0.804 and 0.759, of the DCE-6 radiomics model were 0.869 and 0.798, of the combined sequence radiomics model were 0.908 and 0.847, of the clinicopathological MRI feature model were 0.703 and 0.693, and of the nomogram model were 0.938 and 0.859, respectively. In the training set, the combined sequence radiomics model outperformed the clinicopathological features model ( P＜0.001). In the training and validation sets, the nomogram outperformed the clinicopathological features model ( P＜0.05). In addition, the diagnostic performance of the nomogram was better than that of the four single-modality radiomics models in the training cohort ( P＜0.05) and was better than that of DCE-2 and ADC models in the validation cohort ( P＜0.05). Decision curve analysis indicated that the value of individualized prediction models was higher than clinical and pathological prediction models in clinical practice. The calibration curve showed that the multimodal radiomics model had a high consistency with the actual results in predicting HER-2 expression. Conclusions:T2WI, ADC and early-delayed phase DCE-MRI imaging histology models for HER-2 expression status in breast cancer are expected to provide a non-invasive virtual pathological basis for decision-making on preoperative neoadjuvant regimens in breast cancer.

Objective:This study aims to explore the predictive value of T2-weighted imaging (T2WI), apparent diffusion coefficient (ADC), and early-delayed phases enhanced magnetic resonance imaging (DCE-MRI) radiomics prediction model in determining human epidermal growth factor receptor 2 status in breast cancer.Methods:A retrospective study was conducted, involving 187 patients with confirmed breast cancer by postsurgical pathology at Zhenjiang First People's Hospital during January 2021 and May 2023. Immunohistochemistry or fluorescence in situ hybridization was used to determine the HER-2 status of these patients, with 48 cases classified as HER-2 positive and 139 cases as HER-2 negative. The training set was used to construct the prediction models and the validation set was used to verify the prediction models. Layers of T2WI, ADC, and early-delayed phase DCE-MRI images were used to delineate the volumeof interest and 960 radiomic features were extracted from each case using Pyradiomic. After screening and dimensionality reduction by intraclass correlation coefficient, Pearson correlation analysis, least absolute shrinkage, and selection operator, the radiomics labels were established. Logistic regression analysis was used to construct the T2WI radiomics model, ADC radiomics model, DCE-2 radiomics model, DCE-6 radiomics model, and the joint sequence radiomics model to predict the HER-2 expression status of breast cancer, respectively. Based on the clinical, pathological, and MRI image characteristics of patients, univariate and multivariate logistic regression analysis wasused to construct a clinicopathological MRI feature model. The radscore of every patient and the clinicopathological MRI features which were statistically significant after screening were used to construct a nomogram model. The receiver operating characteristic (ROC) curve was used to evaluate the predictive performance of each model and the decision curve analysis wasused to evaluate the clinical usefulness.Results:The T2WI, ADC, DCE-2, DCE-6, and joint sequence radiomics models, the clinicopathological MRI feature model, and the nomogram model were successfully constructed to predict the expression status of HER-2 in breast cancer. ROC analysis showed that in the training set and validation set, the areas under the curve (AUC) of the T2WI radiomics model were 0.797 and 0.760, of the ADC radiomics model were 0.776 and 0.634, of the DCE-2 radiomics model were 0.804 and 0.759, of the DCE-6 radiomics model were 0.869 and 0.798, of the combined sequence radiomics model were 0.908 and 0.847, of the clinicopathological MRI feature model were 0.703 and 0.693, and of the nomogram model were 0.938 and 0.859, respectively. In the training set, the combined sequence radiomics model outperformed the clinicopathological features model ( P＜0.001). In the training and validation sets, the nomogram outperformed the clinicopathological features model ( P＜0.05). In addition, the diagnostic performance of the nomogram was better than that of the four single-modality radiomics models in the training cohort ( P＜0.05) and was better than that of DCE-2 and ADC models in the validation cohort ( P＜0.05). Decision curve analysis indicated that the value of individualized prediction models was higher than clinical and pathological prediction models in clinical practice. The calibration curve showed that the multimodal radiomics model had a high consistency with the actual results in predicting HER-2 expression. Conclusions:T2WI, ADC and early-delayed phase DCE-MRI imaging histology models for HER-2 expression status in breast cancer are expected to provide a non-invasive virtual pathological basis for decision-making on preoperative neoadjuvant regimens in breast cancer.