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by Junyu Zhang, Zhixi Hu, Yuquan Tan, Jiahao Ye
BackgroundHeart Failure (HF) is a widespread condition that affects millions of people, and it is caused by issues with the heart and blood vessels. Even though we know hypertension, coronary artery disease, obesity, diabetes, and genetics can increase the risk of HF and Chronic Kidney Disease (CKD), the exact cause of these conditions remains a mystery. To bridge this gap, we adopted Mendelian Randomization (MR), which relies on genetic variants as proxies.
MethodsWe used data from European populations for our Bidirectional Two-Sample MR Study, which included 930,014 controls and 47,309 cases of HF from the HERMES consortium, as well as 736,396 controls and 51,256 cases of CKD. We also employed several MR variations, including MR-Egger, Inverse Variance Weighted (IVW), and Weighted Median Estimator (WME), to guarantee the results were accurate and comprehensive.).
ResultsIn this study, the MR analysis found that individuals with a genetic predisposition for HF have an elevated risk of CKD. Our study revealed a significant association between the genetic prediction of HF and the risk of CKD, as evidenced by the IVW method [with an odds ratio (OR) of 1.12 (95% CI, 1.03–1.21), p = 0.009] and the WME [with an OR of 1.14 (95% CI, 1.03–1.26), p = 0.008]. This causal relationship remained robust even after conducting MR analysis while adjusting for the effects of diabetes and hypertension, yielding ORs of 1.13 (IVW:95% CI, 1.03–1.23), 1.12 (MR-Egger: 95% CI, 0.85–1.48), and 1.15 (WME:95% CI, 1.04–1.27) (p = 0.008). However, in the reverse analysis aiming to explore CKD and renal function as exposures and HF as the outcome, we did not observe a statistically significant causal link between CKD and HF.
ConclusionOur study demonstrates the significance of HF in CKD progression, thus having meaningful implications for treatment and the potential for discovering new therapies. To better understand the relationship between HF and CKD, we need to conduct research in a variety of populations.
by Guanghao Xin, Jingyan Niu, Qinghua Tian, Yanchi Fu, Lixia Chen, Tingting Yi, Kuo Tian, Xuesong Sun, Na Wang, Jianjian Wang, Huixue Zhang, Lihua Wang
BackgroundParkinson’s disease is the second most common neurodegenerative disease in the world. However, current diagnostic methods are still limited, and available treatments can only mitigate the symptoms of the disease, not reverse it at the root. The immune function has been identified as playing a role in PD, but the exact mechanism is unknown. This study aimed to search for potential immune-related hub genes in Parkinson’s disease, find relevant immune infiltration patterns, and develop a categorical diagnostic model.
MethodsWe downloaded the GSE8397 dataset from the GEO database, which contains gene expression microarray data for 15 healthy human SN samples and 24 PD patient SN samples. Screening for PD-related DEGs using WGCNA and differential expression analysis. These PD-related DEGs were analyzed for GO and KEGG enrichment. Subsequently, hub genes (dld, dlk1, iars and ttd19) were screened by LASSO and mSVM-RFE machine learning algorithms. We used the ssGSEA algorithm to calculate and evaluate the differences in nigrostriatal immune cell types in the GSE8397 dataset. The association between dld, dlk1, iars and ttc19 and 28 immune cells was investigated. Using the GSEA and GSVA algorithms, we analyzed the biological functions associated with immune-related hub genes. Establishment of a ceRNA regulatory network for immune-related hub genes. Finally, a logistic regression model was used to develop a PD classification diagnostic model, and the accuracy of the model was verified in three independent data sets. The three independent datasets are GES49036 (containing 8 healthy human nigrostriatal tissue samples and 15 PD patient nigrostriatal tissue samples), GSE20292 (containing 18 healthy human nigrostriatal tissue samples and 11 PD patient nigrostriatal tissue samples) and GSE7621 (containing 9 healthy human nigrostriatal tissue samples and 16 PD patient nigrostriatal tissue samples).
ResultsUltimately, we screened for four immune-related Parkinson’s disease hub genes. Among them, the AUC values of dlk1, dld and ttc19 in GSE8397 and three other independent external datasets were all greater than 0.7, indicating that these three genes have a certain level of accuracy. The iars gene had an AUC value greater than 0.7 in GES8397 and one independent external data while the AUC values in the other two independent external data sets ranged between 0.5 and 0.7. These results suggest that iars also has some research value. We successfully constructed a categorical diagnostic model based on these four immune-related Parkinson’s disease hub genes, and the AUC values of the joint diagnostic model were greater than 0.9 in both GSE8397 and three independent external datasets. These results indicate that the categorical diagnostic model has a good ability to distinguish between healthy individuals and Parkinson’s disease patients. In addition, ceRNA networks reveal complex regulatory relationships based on immune-related hub genes.
ConclusionIn this study, four immune-related PD hub genes (dld, dlk1, iars and ttd19) were obtained. A reliable diagnostic model for PD classification was developed. This study provides algorithmic-level support to explore the immune-related mechanisms of PD and the prediction of immune-related drug targets.
by Shuang Xu, Qiongyu Zhang, Jiayan Zhou
The objective of this study was to investigate the direct effects of pain-induced depression and anxiety, as well as the mediating role of psychological resilience, on the psychological distress associated with rheumatoid arthritis. The method involved a sample of 196 patients with rheumatoid arthritis and applied the Hospital Anxiety and Depression Scale, Connor–Davidson Resilience Scale, and visual analog scale for pain. Bivariate and path analyses were performed, and a multiple mediational model was utilized. Results showed that all correlations among study variables were significant (pby Chao Li, Zhong Liu, Justin Anderson, Zhongyu Liu, Liping Tang, Yao Li, Ning Peng, Jianguo Chen, Xueming Liu, Lianwu Fu, Tim M. Townes, Steven M. Rowe, David M. Bedwell, Jennifer Guimbellot, Rui Zhao
A major unmet need in the cystic fibrosis (CF) therapeutic landscape is the lack of effective treatments for nonsense CFTR mutations, which affect approximately 10% of CF patients. Correction of nonsense CFTR mutations via genomic editing represents a promising therapeutic approach. In this study, we tested whether prime editing, a novel CRISPR-based genomic editing method, can be a potential therapeutic modality to correct nonsense CFTR mutations. We generated iPSCs from a CF patient homozygous for the CFTR W1282X mutation. We demonstrated that prime editing corrected one mutant allele in iPSCs, which effectively restored CFTR function in iPSC-derived airway epithelial cells and organoids. We further demonstrated that prime editing may directly repair mutations in iPSC-derived airway epithelial cells when the prime editing machinery is efficiently delivered by helper-dependent adenovirus (HDAd). Together, our data demonstrated that prime editing may potentially be applied to correct CFTR mutations such as W1282X.by Junghyun Kim, Jenny Jiang, Sophie Shen, Soko Setoguchi
ObjectivesTo describe inpatient and outpatient cardiac rehabilitation (CR) utilization patterns over time and by subgroups among patients admitted for acute heart failure (AHF) in Japan.
BackgroundCardiac rehabilitation (CR) is a crucial secondary prevention strategy for patients with heart failure. While the number of older patients with AHF continues to rise, trends in inpatient and outpatient CR participation following AHF in Japan have not been described to date.
MethodsWe conducted a retrospective cohort study of adult patients hospitalized for AHF in Japan between April 2008 and December 2020. Using data from the Medical Data Vision database, we measured trends in inpatient and outpatient CR participation following AHF. Descriptive analyses and summary statistics for AHF patients by CR participation status were reported.
ResultsThe analytic cohort included 88,052 patients. Among these patients, 37,810 (42.9%) participated in inpatient and/or outpatient CR. Of those, 36,431 (96.4%) participated in inpatient CR only and 1,277 (3.4%) participated in both inpatient and outpatient CR. Rates of inpatient CR rose more than 6-fold over the study period, from 9% in 2009 to 55% in 2020, whereas rates of outpatient CR were consistently low.
ConclusionsThe rate of inpatient CR participation among AHF patients in Japan rose dramatically over a 12-year period, whereas outpatient CR following AHF was vastly underutilized. Further study is needed to assess the clinical effectiveness of inpatient CR and to create infrastructure and incentives to support and encourage outpatient CR.
by Min Xiao, Hongbin Deng, Wenjian Mao, Yang Liu, Qi Yang, Yuxiu Liu, Jiemei Fan, Weiqin Li, Dadong Liu
BackgroundSepsis is characterized by upregulated lipolysis in adipose tissue and a high blood triglyceride (TG) level. It is still debated whether serum TG level is related to mortality in septic patients. The aim of this study is to investigate the association between serum TG level and mortality in septic patients admitted to the intensive care unit (ICU).
MethodsData from adult septic patients (≥18 years) admitted to the ICU for the first time were obtained from the Multiparameter Intelligent Monitoring in Intensive Care IV (MIMIC-IV) database. The patients’ serum TG levels that were measured within the first week after ICU admission were extracted for statistical analysis. The endpoints were 28-day, ICU and in-hospital mortality.
ResultsA total of 2,782 septic patients were included. Univariate analysis indicated that the relationship between serum TG levels and the risk of mortality was significantly nonlinear. Both the Lowess smoothing technique and restricted cubic spline analyses revealed a U-shaped association between serum TG levels and mortality among septic patients. The lowest mortality rate was associated with a serum TG level of 300–500 mg/dL. Using 300∼500 mg/dL as the reference range, we found that both hypo-TG ( Conclusions
There was a U-shaped association between serum TG and mortality in septic ICU patients. The optimal concentration of serum TG levels in septic ICU patients is 300–500 mg/dL.
by Xiaoxuan Zhao, Yijie Hu, Wenjun Xiao, Yiming Ma, Dan Shen, Yuepeng Jiang, Yi Shen, Suxia Wang, Jing Ma
ObjectivesUnexplained recurrent spontaneous abortion (URSA) remains an intractable reproductive dilemma due to the lack of understanding of the pathogenesis. This study aimed to evaluate the preclinical evidence for the mesenchymal stromal cell (MSC) treatment for URSA.
MethodsA meticulous literature search was independently performed by two authors across the Cochrane Library, EMBASE, and PubMed databases from inception to April 9, 2023. Each study incorporated was assessed using the Systematic Review Centre for Laboratory Animal Experimentation (SYRCLE) risk of bias tool. The amalgamated standardized mean difference (SMD) accompanied by 95% confidence interval (CI) were deduced through a fixed-effects or random-effects model analysis.
ResultsA total of ten studies incorporating 140 mice were subjected to data analysis. The MSC treatment yielded a significant reduction in the abortion rate within the URSA model (OR = 0.23, 95%CI [0.17, 0.3], PP = 0.01), IL10 (SMD 1.60, 95% CI [0.58, 2.61], P = 0.002), IFN-γ (SMD -1.66, 95%CI [-2.79, -0.52], P = 0.004), and TNF-α (SMD -1.98, 95% CI [-2.93, -1.04], PPP>0.05).
ConclusionsThe findings underscore the considerable potential of MSCs in URSA therapy. Nonetheless, the demand for enhanced transparency in research design and direct comparisons between various MSC sources and administration routes in URSA is paramount to engendering robust evidence that could pave the way for successful clinical translation.
by Naomi Carter, Jialin Li, Miao Xu, Li Li, Shengnan Xu, Xuelan Fan, Shuyan Zhu, Prit Chahal, Kaushik Chattopadhyay
The burden of type 2 diabetes (T2DM) in China is significant and growing, and this is reflected in high rates of T2DM in the city of Ningbo, China. Consequent impacts on morbidity, mortality, healthcare expenditure, and health-related quality of life, make this a problem of the utmost importance to address. One way to improve T2DM outcomes is to address lifestyle behaviours that may affect prognosis and complications, such as physical activity levels, dietary habits, smoking status, and alcohol intake. A cross-sectional survey was undertaken to describe the prevalence of being physically active, having a healthy diet, currently smoking, and currently drinking alcohol among people living with T2DM attending a diabetes clinic in Ningbo, China. Regression analysis was used to determine the factors associated with these lifestyle behaviours. We found a high prevalence of a healthy diet (97.8%, 95% CI 96.5–98.7%). Prevalence of being physically active (83.4%, 95% CI 80.6–85.9%), smoking (21.6%, 95% CI 18.8–24.6%), and alcohol drinking (32.9%. 95% CI 29.6–36.2%) appeared in keeping with those of the general population. Marked associations were demonstrated between male sex and smoking (OR 41.1, 95% CI 16.2–139.0), and male sex and alcohol drinking (OR 4.00, 95% CI 2.62–6.20). Correlation between lifestyle factors was demonstrated including between alcohol drinking and smoking, and between physical activity and reduced smoking. General diabetes self-management education programmes that address multiple lifestyle risk factors simultaneously may be beneficial in this population. Specific interventions targeting smoking cessation and reduction in alcohol drinking may be of benefit to men living with T2DM attending a diabetes clinic in Ningbo.by Jiawei Wu, Peng Ren, Boming Song, Ran Zhang, Chen Zhao, Xiao Zhang
As a novel form of human machine interaction (HMI), hand gesture recognition (HGR) has garnered extensive attention and research. The majority of HGR studies are based on visual systems, inevitably encountering challenges such as depth and occlusion. On the contrary, data gloves can facilitate data collection with minimal interference in complex environments, thus becoming a research focus in fields such as medical simulation and virtual reality. To explore the application of data gloves in dynamic gesture recognition, this paper proposes a data glove-based dynamic gesture recognition model called the Attention-based CNN-BiLSTM Network (A-CBLN). In A-CBLN, the convolutional neural network (CNN) is employed to capture local features, while the bidirectional long short-term memory (BiLSTM) is used to extract contextual temporal features of gesture data. By utilizing attention mechanisms to allocate weights to gesture features, the model enhances its understanding of different gesture meanings, thereby improving recognition accuracy. We selected seven dynamic gestures as research targets and recruited 32 subjects for participation. Experimental results demonstrate that A-CBLN effectively addresses the challenge of dynamic gesture recognition, outperforming existing models and achieving optimal gesture recognition performance, with the accuracy of 95.05% and precision of 95.43% on the test dataset.by Linfei Wu, Li Tang, Linli Zhuang, Wenyi Xie, Min Liu, Jianfang Li
In China, studies have shown nosocomial infections contribute to increased mortality rates, prolonged hospital stays, and added financial burdens for patients. Previous studies have demonstrated that effective infection control training can enhance the quality of infection control practices, particularly in intensive care unit (ICU) settings. However, there is currently no universally accepted training mode or program that adequately addresses the specific needs of ICU medical staff regarding nosocomial infection control. The objective of this study was to develop a standardized training system for preventing and controlling hospital-acquired infections among new medical staff in the internal medicine ICU. Our methodology encompassed an extensive literature review, technical interviews focusing on key events, semi-structured in-depth interviews, and two rounds of Delphi expert correspondence. We employed intentional sampling to select 16 experts for the Delphi expert consultation. Indicators were chosen based on an average importance score of >3.5 and a coefficient of variation ofby Chuan Bo Liang, Bin Cui, Fu Rong Wang, Jing Peng, Jian Ying Ma, Mei Yin Xu, Jun Ke, Yi Tian, Zi Qi Cui
Cooking methods can change the composition of foods and have important effects on human health. The Chinese people have developed many distinct and unique cooking methods. However, the daily cooking patterns of Chinese people and the characteristics and evolution of trends in cooking patterns commonly used by Chinese consumers remain unclear. The objective of this study was to identify the major cooking patterns and discuss their effects on human health, as well as to identify the cooking pattern consumer clusters and the evolution of trends in Chinese consumer cooking patterns. From March to June 2021, this study interviewed 4,710 residents in Eastern China regarding the consumption frequency of each cooking method when food is prepared at home or when eating out. Exploratory factor analysis, K-Means cluster analysis, Chi-square test, pairwise comparisons of multiple sample rates, and multivariate linear regression were used to identify the cooking patterns and cooking pattern consumer clusters, to assess differences in consumption preferences between consumer clusters, and to examine the relationship between demographic characteristic variables and different cooking patterns. Results revealed three major cooking patterns, namely traditional Chinese (cooking methods with native Chinese characteristics), bland, and high-temperature cooking patterns, as well as seven cooking pattern consumer clusters and their demographic characteristics in the Eastern Chinese population. With increases in age, education level, and income, consumers tended to choose the healthy “Bland” cooking pattern. Further, there was a higher proportion of people aged 36–65 years in the C3 cluster, which is characterized by the “Bland” cooking pattern. However, participants who were male and younger made fewer healthy choices in their cooking patterns. Specifically, a higher proportion of participants aged 21–35 years were found in the C5 cluster, which is characterized by the unhealthy “High-temperature” cooking pattern. Therefore, culinary health education should focus on individuals who are male and young. Specifically, the shift in cooking patterns among people aged 21–35 years should receive special attention.by Yong Zhou, Chao Sun, Yingxu Ma, Yunyin Huang, Keke Wu, Shengyuan Huang, Qiuzhen Lin, Jiayi Zhu, Zuodong Ning, Ningyuan Liu, Tao Tu, Qiming Liu
Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia in the clinic. Aging plays an essential role in the occurrence and development of AF. Herein, we aimed to identify the aging-related genes associated with AF using bioinformatics analysis. Transcriptome profiles of AF were obtained from the GEO database. Differential expression analysis was performed to identify AF-specific aging-related genes. GO and KEGG enrichment analyses were performed. Subsequently, the LASSO, SVM-RFE, and MCC algorithms were applied to screen aging-related genes. The mRNA expression of the screened genes was validated in the left atrial samples of aged rapid atrial pacing-induced AF canine models and their counterparts. The ROC curves of them were drawn to evaluate their diagnostic potential. Moreover, CIBERSORT was used to estimate immune infiltration. A correlation analysis between screened aging-related genes and infiltrating immune cells was performed. A total of 24 aging-related genes were identified, which were found to be mainly involved in the FoxO signaling pathway, PI3K-Akt signaling pathway, longevity regulating pathway, and peroxisome according to functional enrichment analysis. LASSO, SVM-RFE, and MCC algorithms identified three genes (HSPA9, SOD2, TXN). Furthermore, the expression levels of HSPA9 and SOD2 were validated in aged rapid atrial pacing-induced AF canine models. HSPA9 and SOD2 could be potential diagnostic biomarkers for AF, as evidenced by the ROC curves. Immune infiltration and correlation analysis revealed that HSPA9 and SOD2 were related to immune cell infiltrates. Collectively, these findings provide novel insights into the potential aging-related genes associated with AF. HSPA9 and SOD2 may play a significant role in the occurrence and development of AF.by Xiaojun Fan, Ying Wang, Changsheng Tang, Xiaolin Zhang, Jianyu He, Isabella Buttino, Xiaojun Yan, Zhi Liao
Mytilus coruscus is an economically important marine bivalve mollusk found in the Yangtze River estuary, which experiences dramatic pH fluctuations due to seasonal freshwater input and suffer from shell fracture or injury in the natural environment. In this study, we used intact-shell and damaged-shell M. coruscus and performed metabolomic analysis, free amino acids analysis, calcium-positive staining, and intracellular calcium level tests in the mantle to investigate whether the mantle-specific metabolites can be induced by acute sea-water acidification and understand how the mantle responds to acute acidification during the shell repair process. We observed that both shell damage and acute acidification induced alterations in phospholipids, amino acids, nucleotides, organic acids, benzenoids, and their analogs and derivatives. Glycylproline, spicamycin, and 2-aminoheptanoic acid (2-AHA) are explicitly induced by shell damage. Betaine, aspartate, and oxidized glutathione are specifically induced by acute acidification. Our results show different metabolic patterns in the mussel mantle in response to different stressors, which can help elucidate the shell repair process under ocean acidification. furthermore, metabolic processes related to energy supply, cell function, signal transduction, and amino acid synthesis are disturbed by shell damage and/or acute acidification, indicating that both shell damage and acute acidification increased energy consumption, and disturb phospholipid synthesis, osmotic regulation, and redox balance. Free amino acid analysis and enzymatic activity assays partially confirmed our findings, highlighting the adaptation of M. coruscus to dramatic pH fluctuations in the Yangtze River estuary.
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