Exploring influential factors in the self-assessment of life satisfaction among Chinese elderly: a structural equation modeling analysis.

The aging problem is becoming more and more prominent globally. Attention to the quality of life and related health improvement among the elderly has become an important issue in modern society. This study utilized a tracking survey conducted in 2017-2018, involving 9,327 Chinese older adults, to examine health influencing factors, and applied structural equation modeling to analyze the influencing factors on the self-assessment of life satisfaction among older adults in different regions (cities, counties, and villages) in China. This study revealed that economic status, psychological status, personal situation, life behaviors, and child care are important influences on older people's self- assessed life satisfaction. There is a positive correlation between economic status, psychological status, child care and the results of the self-assessment of life satisfaction of the elderly. Psychological status and child care have a greater impact on the self-assessment of life satisfaction among the elderly in urban areas compared to villages and towns. The influence of economic status on the self-assessment of life satisfaction of the elderly is lower in urban areas than in rural areas. There is a significant difference in the influence of personal situations on the self-assessment of life satisfaction among the elderly. Additionally, older individuals tend to report higher levels of self-assessment of life satisfaction. Furthermore, female elderly individuals tend to report higher levels of satisfaction compared to males. Findings from this study indicate that improving health self-assessment in older adults requires targeted efforts based on different geographic areas of life and the age stages of older adults, and more attention needs to be paid to men who are just entering old age.

Accurate etiological diagnosis of Mycoplasma hominis mediastinitis in immunocompetent patients using metagenomic next-generation sequencing: a case series and literature review.

Background: As a culture-independent method, metagenomic next-generation sequencing (mNGS) is widely used in microbiological diagnosis with advantages in identifying potential pathogens, guiding antibiotic therapy, and improving clinical prognosis, especially in culture-negative cases. Mycoplasma hominis (M. hominis) mediastinitis is a rare and severe disease for which etiological diagnosis is important but challenging. The application of mNGS in the etiological diagnosis of mediastinitis has seldom been studied. Methods: By searching the electronic medical history retrieval system with "Mycoplasma hominis" and "mediastinitis", seven patients diagnosed with M. hominis mediastinitis were reviewed in Zhongshan Hospital, Fudan University, Shanghai from 9 December 2020 to 14 February 2023. Microbiological cultures and mNGS were conducted for blood, abscess, and/or mediastinal fluid. Adjustment of the antibiotic therapy due to mNGS was assessed. A literature review was conducted in the PubMed database beginning in 1970 for M. hominis infection and mediastinitis. Results: For the seven patients, cultures of blood, abscess, and mediastinal fluid were negative whereas mNGS identified M. hominis in serum, abscess, and/or mediastinal fluid and was used to guide specific antibiotic therapy. The stringent mapped reads number of genera (SMRNG), stringent mapped reads number of species (SMRN), and coverage rate of M. hominis detection by mNGS were significantly higher in body fluid (abscess or mediastinal fluid) than in serum. All seven patients had underlying heart diseases and underwent previous cardiac surgery. The most common symptoms were fever and sternal pain. After detection of M. hominis, antibiotics were adjusted to quinolones or doxycycline except for one patient, whose diagnosis was clarified after death. Two patients died. Literature review since 1970 identified 30 cases of extra-genital infection caused by M. hominis. Including our seven new cases, 2 (5.4%) were neonates and 35 (94.6%) were adults. Thirty (81.1%) cases were postoperative infection and 15 (40.5%) had implanted devices. Five patients (13.5%) died. Conclusions: mNGS might be a promising technology in the detection of fastidious pathogens such as M. hominis. Accurate etiological diagnosis by mNGS could guide antibiotic therapy and facilitate clinical management.

Lipoproteins and metabolites in diagnosing and predicting Alzheimer's disease using machine learning.

BACKGROUND: Alzheimer's disease (AD) is a chronic neurodegenerative disorder that poses a substantial economic burden. The Random forest algorithm is effective in predicting AD; however, the key factors influencing AD onset remain unclear. This study aimed to analyze the key lipoprotein and metabolite factors influencing AD onset using machine-learning methods. It provides new insights for researchers and medical personnel to understand AD and provides a reference for the early diagnosis, treatment, and early prevention of AD. METHODS: A total of 603 participants, including controls and patients with AD with complete lipoprotein and metabolite data from the Alzheimer's disease Neuroimaging Initiative (ADNI) database between 2005 and 2016, were enrolled. Random forest, Lasso regression, and CatBoost algorithms were employed to rank and filter 213 lipoprotein and metabolite variables. Variables with consistently high importance rankings from any two methods were incorporated into the models. Finally, the variables selected from the three methods, with the participants' age, sex, and marital status, were used to construct a random forest predictive model. RESULTS: Fourteen lipoprotein and metabolite variables were screened using the three methods, and 17 variables were included in the AD prediction model based on age, sex, and marital status of the participants. The optimal random forest modeling was constructed with "mtry" set to 3 and "ntree" set to 300. The model exhibited an accuracy of 71.01%, a sensitivity of 79.59%, a specificity of 65.28%, and an AUC (95%CI) of 0.724 (0.645-0.804). When Mean Decrease Accuracy and Gini were used to rank the proteins, age, phospholipids to total lipids ratio in intermediate-density lipoproteins (IDL_PL_PCT), and creatinine were among the top five variables. CONCLUSIONS: Age, IDL_PL_PCT, and creatinine levels play crucial roles in AD onset. Regular monitoring of lipoproteins and their metabolites in older individuals is significant for early AD diagnosis and prevention.

Screening of key immune-related gene in Parkinson's disease based on WGCNA and machine learning. / 基于WGCNAå’Œæœºå™¨å­¦ä¹ ç­›é€‰å¸•é‡‘æ£®ç— å ç–«ç›¸å ³å ³é”®åŸºå› .

OBJECTIVES: Abnormal immune system activation and inflammation are crucial in causing Parkinson's disease. However, we still don't fully understand how certain immune-related genes contribute to the disease's development and progression. This study aims to screen key immune-related gene in Parkinson's disease based on weighted gene co-expression network analysis (WGCNA) and machine learning. METHODS: This study downloaded the gene chip data from the Gene Expression Omnibus (GEO) database, and used WGCNA to screen out important gene modules related to Parkinson's disease. Genes from important modules were exported and a Venn diagram of important Parkinson's disease-related genes and immune-related genes was drawn to screen out immune related genes of Parkinson's disease. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to analyze the the functions of immune-related genes and signaling pathways involved. Immune cell infiltration analysis was performed using the CIBERSORT package of R language. Using bioinformatics method and 3 machine learning methods [least absolute shrinkage and selection operator (LASSO) regression, random forest (RF), and support vector machine (SVM)], the immune-related genes of Parkinson's disease were further screened. A Venn diagram of differentially expressed genes screened using the 4 methods was drawn with the intersection gene being hub nodes (hub) gene. The downstream proteins of the Parkinson's disease hub gene was identified through the STRING database and a protein-protein interaction network diagram was drawn. RESULTS: A total of 218 immune genes related to Parkinson's disease were identified, including 45 upregulated genes and 50 downregulated genes. Enrichment analysis showed that the 218 genes were mainly enriched in immune system response to foreign substances and viral infection pathways. The results of immune infiltration analysis showed that the infiltration percentages of CD4+ T cells, NK cells, CD8+ T cells, and B cells were higher in the samples of Parkinson's disease patients, while resting NK cells and resting CD4+ T cells were significantly infiltrated in the samples of Parkinson's disease patients. ANK1 was screened out as the hub gene. The analysis of the protein-protein interaction network showed that the ANK1 translated and expressed 11 proteins which mainly participated in functions such as signal transduction, iron homeostasis regulation, and immune system activation. CONCLUSIONS: This study identifies the Parkinson's disease immune-related key gene ANK1 via WGCNA and machine learning methods, suggesting its potential as a candidate therapeutic target for Parkinson's disease.

Algorithm of automatic identification of diabetic retinopathy foci based on ultra-widefield scanning laser ophthalmoscopy.

AIM: To propose an algorithm for automatic detection of diabetic retinopathy (DR) lesions based on ultra-widefield scanning laser ophthalmoscopy (SLO). METHODS: The algorithm utilized the FasterRCNN (Faster Regions with CNN features)+ResNet50 (Residua Network 50)+FPN (Feature Pyramid Networks) method for detecting hemorrhagic spots, cotton wool spots, exudates, and microaneurysms in DR ultra-widefield SLO. Subimage segmentation combined with a deeper residual network FasterRCNN+ResNet50 was employed for feature extraction to enhance intelligent learning rate. Feature fusion was carried out by the feature pyramid network FPN, which significantly improved lesion detection rates in SLO fundus images. RESULTS: By analyzing 1076 ultra-widefield SLO images provided by our hospital, with a resolution of 2600×2048 dpi, the accuracy rates for hemorrhagic spots, cotton wool spots, exudates, and microaneurysms were found to be 87.23%, 83.57%, 86.75%, and 54.94%, respectively. CONCLUSION: The proposed algorithm demonstrates intelligent detection of DR lesions in ultra-widefield SLO, providing significant advantages over traditional fundus color imaging intelligent diagnosis algorithms.

FAM20A is a golgi-localized Type II transmembrane protein.

Family with sequence similarity 20, member A (FAM20A) is a pseudo-kinase in the secretory pathway and is essential for enamel formation in humans. Here we examine if FAM20A is a membrane-associated protein. We show that the full-length FAM20A can be purified from HEK293 cells transfected with a FAM20A-expresing construct. Further, it is only found in the membrane fraction, but not in the soluble fraction, of cell lysate. Consistently, it is not secreted out of the expressing cells. Moreover, it is co-localized with GM130, a cis-Golgi network marker, and membrane topology analysis indicates that it has its C-terminus oriented towards the lumen of the organelle. Our results support that FAM20A is a Type II transmembrane protein within the secretory compartments.

Nitric Oxide-Releasing Tubular Polymersomes toward Advanced Gas Therapeutic Carriers.

Nitric oxide (NO) not only plays a vital role in a series of physiological processes but also has great potential for therapeutic applications. One of the existing challenges in using NO as a gas therapeutic is the inconvenience of gaseous NO storage, and thus, it is of importance to develop NO-releasing vehicle platforms. Although a variety of polymer-based NO-releasing nanoparticles have been constructed, a majority of the systems are limited to spherical morphologies. Here we present the preparation of biodegradable NO-releasing amphiphilic block copolymers containing poly(ethylene glycol) (PEG) and poly(trimethylene carbonate-4-nitro-3-(trifluoromethyl)) (PTMC-NF), which can self-assemble into tubular polymersomes. The tubular polymersomes with high aspect ratio structures showed much faster NO-releasing behavior, in contrast to their spherical counterparts under light irradiation. We found that the amount of NO released from tubular polymersomes is 1.5 times that from spherical polymersomes. More importantly, the tubular polymersomes have an enhanced anticancer performance compared to spherical polymersomes, demonstrating that the morphology of the NO-releasing polymersomes has a significant effect on their anticancer ability. In view of the benefits of NO-releasing tubular polymersomes, we expect that they can be used as an efficient NO delivery system for enhanced gas therapy.

Trend analysis and prediction of gonorrhea in mainland China based on a hybrid time series model.

BACKGROUND: Gonorrhea has long been a serious public health problem in mainland China that requires attention, modeling to describe and predict its prevalence patterns can help the government to develop more scientific interventions. METHODS: Time series (TS) data of the gonorrhea incidence in China from January 2004 to August 2022 were collected, with the incidence data from September 2021 to August 2022 as the validation. The seasonal autoregressive integrated moving average (SARIMA) model, long short-term memory network (LSTM) model, and hybrid SARIMA-LSTM model were used to simulate the data respectively, the model performance were evaluated by calculating the mean absolute percentage error (MAPE), root mean square error (RMSE), and mean absolute error (MAE) of the training and validation sets of the models. RESULTS: The Seasonal components after data decomposition showed an approximate bimodal distribution with a period of 12 months. The three models identified were SARIMA(1,1,1) (2,1,2)12, LSTM with 150 hidden units, and SARIMA-LSTM with 150 hidden units, the SARIMA-LSTM model fitted best in the training and validation sets, for the smallest MAPE, RMSE, and MPE. CONCLUSIONS: The overall incidence trend of gonorrhea in mainland China has been on the decline since 2004, with some periods exhibiting an upward trend. The incidence of gonorrhea displays a seasonal distribution, typically peaking in July and December each year. The SARIMA model, LSTM model, and SARIMA-LSTM model can all fit the monthly incidence time series data of gonorrhea in mainland China. However, in terms of predictive performance, the SARIMA-LSTM model outperforms the SARIMA and LSTM models, with the LSTM model surpassing the SARIMA model. This suggests that the SARIMA-LSTM model can serve as a preferred tool for time series analysis, providing evidence for the government to predict trends in gonorrhea incidence. The model's predictions indicate that the incidence of gonorrhea in mainland China will remain at a high level in 2024, necessitating that policymakers implement public health measures in advance to prevent the spread of the disease.

StyleTalk++: A Unified Framework for Controlling the Speaking Styles of Talking Heads.

Individuals have unique facial expression and head pose styles that reflect their personalized speaking styles. Existing one-shot talking head methods cannot capture such personalized characteristics and therefore fail to produce diverse speaking styles in the final videos. To address this challenge, we propose a one-shot style-controllable talking face generation method that can obtain speaking styles from reference speaking videos and drive the one-shot portrait to speak with the reference speaking styles and another piece of audio. Our method aims to synthesize the style-controllable coefficients of a 3D Morphable Model (3DMM), including facial expressions and head movements, in a unified framework. Specifically, the proposed framework first leverages a style encoder to extract the desired speaking styles from the reference videos and transform them into style codes. Then, the framework uses a style-aware decoder to synthesize the coefficients of 3DMM from the audio input and style codes. During decoding, our framework adopts a two-branch architecture, which generates the stylized facial expression coefficients and stylized head movement coefficients, respectively. After obtaining the coefficients of 3DMM, an image renderer renders the expression coefficients into a specific person's talking-head video. Extensive experiments demonstrate that our method generates visually authentic talking head videos with diverse speaking styles from only one portrait image and an audio clip.

Associations of polysocial risk score, lifestyle and genetic factors with incident psoriasis: a larger-scale prospective cohort study.

OBJECTIVES: The impact of polysocial risk score (PsRS), a composite measure of multiple social risk factors, on the development of psoriasis remains unclear. Moreover, the potential modifying effects of lifestyle and genetic susceptibility on the relationship between PsRS and psoriasis risk require further exploration. STUDY DESIGN: This was a prospective cohort study conducted among UK Biobank. METHODS: In this study, we analyzed 331,631 participants enrolled in the UK Biobank cohort. To derive the PsRS, we utilized a summative strategy, amalgamating six social determinants of health derived from three domains: socio-economic status, psychosocial factors, and neighborhood and living environment consistently linked to incident psoriasis. Cox proportional hazard models were used to assess the associations between PsRS and psoriasis incidence. Furthermore, we constructed a lifestyle score and a genetic risk score to explore the potential modifying effects of these factors on the relationship between PsRS and psoriasis risk. RESULTS: Compared with individuals with a low PsRS (≤1), those with intermediate PsRS (2-4) and high PsRS (≥5) had 1.20 (95% confidence interval [CI], 1.06-1.36) and 1.53 (95% CI, 1.31-1.78) times higher risks of developing psoriasis, respectively. Our findings revealed an additive interaction between PsRS and genetic susceptibility. Moreover, it was found that individuals with high PsRS and unhealthier lifestyles had a 2.60 times higher risk of developing psoriasis than those with lower PsRS and healthier ones. CONCLUSIONS: Our study results imply that an elevated PsRS is linked to a heightened risk of psoriasis, which is further influenced by genetic factors. Our results also indicate that greater social vulnerability and unhealthier lifestyle may synergistically contribute to the additional risk of psoriasis.

New insights on the interplays between m6A modifications and microRNA or lncRNA in gastrointestinal cancers.

N6-Methyladenosine (m6A) methylation is one of the most extremely examined RNA modifications. M6A modification evidently impacts cancer development by effecting RNA metabolism. Long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) are involved in multiple essential biological processes by regulating gene expression at the transcriptional and post-transcriptional levels. Accumulated evidences indicated that m6A is involved in regulating the cleavage, stability, structure, transcription, and transport of lncRNAs or miRNAs. Additionally, ncRNAs also play significant roles in modulating m6A levels of malignant cells by participating in the regulation of m6A methyltransferases, the m6A demethylases and the m6A binding proteins. In this review, we systematically summarize the new insight on the interactions between m6A and lncRNAs or miRNAs, as well as their impacts on gastrointestinal cancer progression. Although there are still extensive studies on genome-wide screening of crucial lncRNAs or miRNAs involved in regulating m6A levels of mRNAs and disclosing differences on mechanisms of regulating m6A modification of lncRNAs, miRNAs or mRNAs in cancer cells, we believe that targeting m6A-related lncRNAs and miRNAs may provide novel options for gastrointestinal cancer treatments.

Epidemiology of Clinically Significant Aspergillus Species from a Large Tertiary Hospital in Shanghai, China, for the Period of Two Years.

Background: Aspergillus species are becoming a major public health concern worldwide due to the increase in the incidence of aspergillosis and emergence of antifungal resistance. In this study, we surveyed all Aspergillus species isolated from aspergillosis patients in Zhongshan Hospital Fudan University, Shanghai, China, from 2019 to 2021. Methods: We characterized the susceptibility profiles of these Aspergillus species to medical azoles (voriconazole, itraconazole and posaconazole) using YeastOneTM broth microdilution system. To determine the underlying antifungal resistance mechanisms in azole-resistant A. fumigatus (ARAf) isolates, we characterized mutations in the cyp51A gene. Genotypic diversity of sampled A. fumigatus was investigated using CSP-typing. Results: A total of 112 Aspergillus isolates (81 A. fumigatus, 17 A. flavus, 5 A. niger, 2 A. terreus, 2 A. lentulus, 2 A. oryzae, 1 A. nidulans, 1 A. versicolor and 1 A. sydowii) from 105 patients diagnosed with aspergillosis (including proven or probable invasive aspergillosis, chronic pulmonary aspergillosis, allergic bronchopulmonary aspergillosis and cutaneous aspergillosis) were obtained. Eight isolates (7 A. fumigatus and 1 A. niger) from seven patients were either azole non-susceptible or non-wild type. Azole non-susceptible or non-wild type rate was 7.1%/isolate and 6.7%/patient analysed. Four ARAf harbored TR34/L98H mutation, whereas one carried TR46/Y121F/T289A allele. The 81 A. fumigatus isolates were spread across 8 CSP types with t01 to be the predominant type (53.1%). ARAf isolates were distributed over CSP types t01, t02, t04A and t11. Conclusion: Results from this study provided us with an understanding of the antifungal resistance and related characteristics of Aspergillus species in Eastern China. Further comparisons of our results with those in other countries reflect potential clonal expansion of A. fumigatus in our region. Further surveillance study is warranted to guide antifungal therapy and for epidemiological purposes.

Widely targeted metabolomic, transcriptomic, and metagenomic profiling reveal microbe-plant-metabolic reprogramming patterns mediated by Streptomyces pactum Act12 enhance the fruit quality of Capsicum annuum L.

Plant growth-promoting rhizobacteria, such as Streptomyces pactum Act12, promote crop growth and stress resistance, but their contribution to fruit quality is still poorly understood. Herein we conducted a field experiment to ascertain the effects of S. pactum Act12-mediated metabolic reprogramming and underlying mechanisms in pepper (Capsicum annuum L.) fruit based on widely targeted metabolomic and transcriptomic profiling. We additionally performed metagenomic analysis to elucidate the potential relationship between S. pactum Act12-mediated reshaping of rhizosphere microbial communities and pepper fruit quality. Soil inoculation with S. pactum Act12 considerably increased the accumulation of capsaicinoids, carbohydrates, organic acids, flavonoids, anthraquinones, unsaturated fatty acids, vitamins, and phenolic acids in pepper fruit samples. Consequently, fruit flavor, taste, and color were modified, accompanied by elevated contents of nutrients and bioactive compounds. Increased microbial diversity and recruitment of potentially beneficial taxa were observed in inoculated soil samples, with crosstalk between microbial gene functions and pepper fruit metabolism. The reformed structure and function of rhizosphere microbial communities were closely associated with pepper fruit quality. Our findings indicate that S. pactum Act12-mediated interactions between rhizosphere microbial communities and pepper plants are responsible for intricate fruit metabolic reprogramming patterns, which enhance not only overall fruit quality but also consumer acceptability.

A mutational signature and significantly mutated driver genes associated with immune checkpoint inhibitor response across multiple cancers.

Immune checkpoint inhibitor (ICI) treatments dramatically prolong the survival outcomes of several advanced cancers. However, as multiple studies reported, only a subset of patients could benefit from the ICI treatment. In this study, we aim to uncover novel molecular biomarkers predictive of immunotherapy efficacy across multiple cancers. Pre-treatment somatic mutational profiles and immunotherapy clinical information were obtained from 1097 samples of multiple cancers, including melanoma, non-small cell lung cancer (NSCLC), clear cell renal cell carcinoma (ccRCC), bladder carcinoma (BLCA), and head and neck squamous cell carcinoma (HNSCC). Mutational signatures, molecular subtypes, and significantly mutated genes (SMGs) were determined, and their connections with ICI response and outcome were also evaluated. We extracted a total of six mutational signatures across all samples. Among, a mutational signature featured by T > C substitutions was identified to associate with an ICI resistance. A molecular subtype determined based on mutational activities was connected with a significantly improved ICI response rate and outcome. Totaling 50 SMGs were identified, and we observed that patients with COL11A1 or COL4A6 mutations exhibited a superior ICI treatment efficacy than those without such mutations. In this study, we uncovered several novel molecular determinants of cancer immunotherapy response under a multiple-cancer setting, which provides clues for enrolling patients to receive immunotherapy and customizing personalized treatment strategies.

Bioinformatic analysis identifies the immunological profile of turner syndrome with different X chromosome origins.

Introduction: Turner syndrome (TS) is a chromosomal disorder that affects phenotypic females who have one intact X chromosome and complete or partial absence of the second sex chromosome in association with one or more clinical manifestations. However, the immunological profile of TS with different X chromosome origins is incompletely understood. Methods: In this study, transcriptomic expression profiles of 26 TS (45,X) samples and 10 normal karyotype (46,XX) samples derived from GSE46687 cohort were employed. Differentially expressed immune-related genes (DEIRGs) between monosomy X TS patients with different X chromosome origins and normal females were investigated respectively. Subsequently, functional annotation, protein-protein interaction (PPI) network analysis, immunocyte infiltration evaluation, tissue-specific gene expression and Weighted gene co expression network analysis (WGCNA) were performed to explore the immunological characteristic in TS with different X chromosome origins. Results: 34 and 52 DEIRGs were respectively identified in 45,Xm and 45,Xp patients compared with normal individuals. The identified DEIRGs in Xm group were significantly enriched in pathways associated with cancer. In Xp TS patients, the most enriched signals were immune response-related. A majority of genes involved in the above pathways were downregulated. PPI analysis identified 4 (FLT3, IL3RA, CSF2RA, PIK3R3) and 6 (PDGFRB, CSF2, IL5, PRL, CCL17 and IL2)hub genes for Xm and Xp groups, respectively. CIBERSORT results showed that the proportion of Tregs in the Xm group and the naive B cells and resting NK cells in the Xp group significantly increased, respectively. Tissue-specific expression results indicated that BDCA4+_dentritic cells and CD19+ B cells were the prominent specific expressed tissues in Xp patients. Results of WGCNA support the above analysis. Conclusions: This study aims at studying the immunological characteristics of TS with different X chromosome origins. Pathways in cancer in Xm group and immune response in Xp group were suppressed. 4 and 6 hub IRGs were identified as biomarkers for Xm and Xp patients, respectively. B cells played important roles in Xp patients. Further studies are needed to draw more attention to the functional validation of these hub genes and the roles of B cells.

Influencing factors of depressive symptoms among rural elderly patients with chronic diseases / 预防医学

Objective@#To investigate the influencing factors of depressive symptoms among rural elderly patients with chronic diseases in China, so as to provide insights into depression prevention and control among the rural elderly patients with chronic diseases.@*Methods@#The basic demographics, health status, and lifestyle of rural residents at ages of 65 years and older who had at least one chronic disease were retrieved from The Chinese Longitudinal Healthy Longevity Survey (CLHLS) database in 2018, and participants' depressive symptoms were assessed with The Center for Epidemiological Studies Depression-10 (CES-D-10) scale. Factors affecting the depressive symptoms were identified with a multivariable logistic regression model. @*Results@#Totally 5 146 rural elderly patients with chronic diseases were enrolled, including 2 373 men (46.11%) and 2 773 women (53.89%). The prevalence of depressive symptoms was 27.13%. Multivariable logistic regression analysis identified having two and more children (OR=0.614, 95%CI: 0.387-0.975), living alone (OR=1.450, 95%CI: 1.192-1.764), life satisfaction (general, OR=1.933, 95%CI: 1.651-2.264; low, OR=5.366, 95%CI: 3.488-8.254), self-assessed health status (general, OR=2.697, 95%CI: 2.284-3.185; poor, OR=5.338, 95%CI: 4.262-6.685), disability in instrumental activities of daily living (OR=1.592, 95%CI: 1.328-1.908), sleep duration (normal, OR=0.502, 95%CI: 0.429-0.586; too long, OR=0.494, 95%CI: 0.405-0.603), exercise (OR=0.721, 95%CI: 0.607-0.856), watching TV (OR=0.787, 95%CI: 0.664-0.933), and gardening activities (OR=0.781, 95%CI: 0.626-0.975) as factors affecting depressive symptoms among rural elderly patients with chronic diseases.@*Conclusions@#The prevalence of depressive symptoms was 27.13% among rural elderly patients with chronic diseases. Number of children, living style, life satisfaction, health status, sleep duration, exercise, watching TV, and gardening activities are associated with the development of depressive symptoms among rural elderly patients with chronic diseases.

Constitutive expression of spliced X-box binding protein 1 inhibits dentin formation in mice.

Upon endoplasmic reticulum (ER) stress, inositol-requiring enzyme 1 (IRE1) is activated, which subsequently converts an unspliced X-box binding protein 1 (XBP1U) mRNA to a spliced mRNA that encodes a potent XBP1S transcription factor. XBP1S is essential for relieving ER stress and secretory cell differentiation. We previously established Twist2-Cre;Xbp1 CS/+ mice that constitutively expressed XBP1S in the Twist2-expressing cells as well as in the cells derived from the Twist2-expressing cells. In this study, we analyzed the dental phenotype of Twist2-Cre;Xbp1 CS/+ mice. We first generated a mutant Xbp1s minigene that corresponds to the recombinant Xbp1 Δ26 allele (the Xbp1 CS allele that has undergone Cre-mediated recombination) and confirmed that the Xbp1s minigene expressed XBP1S that does not require IRE1α activation in vitro. Consistently, immunohistochemistry showed that XBP1S was constitutively expressed in the odontoblasts and other dental pulp cells in Twist2-Cre;Xbp1 CS/+ mice. Plain X-ray radiography and µCT analysis revealed that constitutive expression of XBP1S altered the dental pulp chamber roof- and floor-dentin formation, resulting in a significant reduction in dentin/cementum formation in Twist2-Cre;Xbp1 CS/+ mice, compared to age-matched Xbp1 CS/+ control mice. However, there is no significant difference in the density of dentin/cementum between these two groups of mice. Histologically, persistent expression of XBP1S caused a morphological change in odontoblasts in Twist2-Cre;Xbp1 CS/+ mice. Nevertheless, in situ hybridization and immunohistochemistry analyses showed that continuous expression of XBP1S had no apparent effects on the expression of the Dspp and Dmp1 genes. In conclusion, these results support that sustained production of XBP1S adversely affected odontoblast function and dentin formation.

Identification and Validation of RELN Mutation as a Response Indicator for Immune Checkpoint Inhibitor Therapy in Melanoma and Non-Small Cell Lung Cancer.

Remarkable clinical benefits in several advanced cancers are observed under the treatment of immune checkpoint inhibitor (ICI) agents. However, only a smaller proportion of patients respond to the treatments. Reelin (RELN) is frequently mutated in the cancer genome. In this study, the RELN mutation association with ICI treatment efficacy in melanoma and non-small cell lung cancer (NSCLC) was elucidated. Data from 631 melanoma and 109 NSCLC patients with both ICI treatment data and pre-treatment mutational profiles were collected. In addition, from the Cancer Genome Atlas (TCGA) project, we also obtained both tumors to explore the immunologic features behind RELN mutations. Melanoma patients with RELN mutations exhibited a favorable ICI survival benefit when compared with wild-type patients (HR: 0.66, 95% CI: 0.51-0.87, p = 0.003). A higher response rate was also noticed in RELN-mutated patients (38.9% vs. 28.3%, p = 0.017). The association of RELN mutations with a preferable immunotherapy outcome and response was further confirmed in NSCLC. Further exploration demonstrated that favorable immunocyte infiltration and immune response signaling pathways were found in patients with RELN mutations. In this study, RELN mutations were identified to connect with a better immune microenvironment and an improved ICI efficacy in melanoma and NSCLC, which provides a potential biomarker for immunological feature evaluation and immunotherapeutic outcome prediction at the molecular level.

HSPG2 Mutation Association with Immune Checkpoint Inhibitor Outcome in Melanoma and Non-Small Cell Lung Cancer.

Immune checkpoint inhibitors (ICIs) markedly promote the survival outcome of advanced melanoma and non-small cell lung cancer (NSCLC). Clinically, favorable ICI treatment efficacy is noticed only in a smaller proportion of patients. Heparan sulfate proteoglycan 2 (HSPG2) frequently mutates in both tumors. Herein, we aim to investigate the immunotherapeutic and immunological roles of HSPG2 mutations in melanoma and NSCLC. A total of 631 melanoma samples and 109 NSCLC samples with both somatic mutational profiles and clinical immunotherapy data were curated. In addition, by using The Cancer Genome Atlas data, genomic and immunological traits behind HSPG2 mutations were elucidated. Melanoma patients with HSPG2 mutations had a markedly extended ICI outcome than other patients. An association between HSPG2 mutations and the improved outcome was further confirmed in NSCLC. In addition, an elevated ICI response rate was presented in HSPG2-mutated NSCLC patients (81.8% vs. 29.7%, p = 0.002). Subsequent analyses revealed that HSPG2-mutated patients had a favorable abundance of response immunocytes, an inferior abundance of suppression immunocytes, enhanced mutational burden, and interferon response-relevant signaling pathways. We uncovered that HSPG2 mutations were predictive of a better ICI response and associated with preferable immunogenicity, which may be considered as a genomic determinant to customize biotherapy strategies.

Favorable immune checkpoint inhibitor outcome of patients with melanoma and NSCLC harboring FAT1 mutations.

Immune checkpoint inhibitors (ICIs) are most commonly used for melanoma and non-small cell lung cancer (NSCLC) patients. FAT atypical cadherin 1 (FAT1), which frequently mutates in melanoma and NSCLC. In this study, we aim to investigate the association of FAT1 mutations with ICI response and outcome. We collected somatic mutation profiles and clinical information from ICI-treated 631 melanoma and 109 NSCLC samples, respectively. For validation, a pan-cancer cohort with 1661 patients in an immunotherapy setting was also used. Melanoma and NSCLC samples from the Cancer Genome Atlas were used to evaluate the potential immunologic mechanisms of FAT1 mutations. In melanoma, patients with FAT1 mutations had a significantly improved survival outcome than those wild-type patients (HR: 0.67, 95% CI: 0.46-0.97, P = 0.033). An elevated ICI response rate also appeared in FAT1-mutated patients (43.2% vs. 29.2%, P = 0.032). Associations of FAT1 mutations with improved prognosis and ICI response were confirmed in NSCLC patients. In the pan-cancer cohort, the association between FAT1 mutations and favorable ICI outcome was further validated (HR: 0.74, 95% CI: 0.58-0.96, P = 0.022). Genomic and immunologic analysis showed that a high mutational burden, increased infiltration of immune-response cells, decreased infiltration of immune-suppressive cells, interferon and cell cycle-related pathways were enriched in patients with FAT1 mutations. Our study revealed that FAT1 mutations were associated with better immunogenicity and ICI efficacy, which may be considered as a biomarker for selecting patients to receive immunotherapy.