Identifying cell type-specific transcription factor-mediated activity immune modules reveal implications for immunotherapy and molecular classification of pan-cancer.

Systematic investigation of tumor-infiltrating immune (TII) cells is important to the development of immunotherapies, and the clinical response prediction in cancers. There exists complex transcriptional regulation within TII cells, and different immune cell types display specific regulation patterns. To dissect transcriptional regulation in TII cells, we first integrated the gene expression profiles from single-cell datasets, and proposed a computational pipeline to identify TII cell type-specific transcription factor (TF) mediated activity immune modules (TF-AIMs). Our analysis revealed key TFs, such as BACH2 and NFKB1 play important roles in B and NK cells, respectively. We also found some of these TF-AIMs may contribute to tumor pathogenesis. Based on TII cell type-specific TF-AIMs, we identified eight CD8+ T cell subtypes. In particular, we found the PD1 + CD8+ T cell subset and its specific TF-AIMs associated with immunotherapy response. Furthermore, the TII cell type-specific TF-AIMs displayed the potential to be used as predictive markers for immunotherapy response of cancer patients. At the pan-cancer level, we also identified and characterized six molecular subtypes across 9680 samples based on the activation status of TII cell type-specific TF-AIMs. Finally, we constructed a user-friendly web interface CellTF-AIMs (http://bio-bigdata.hrbmu.edu.cn/CellTF-AIMs/) for exploring transcriptional regulatory pattern in various TII cell types. Our study provides valuable implications and a rich resource for understanding the mechanisms involved in cancer microenvironment and immunotherapy.

Circulating 25-hydroxyvitamin D and survival outcomes of colorectal cancer: evidence from population-based prospective cohorts and Mendelian randomisation.

BACKGROUND: To investigate the association between circulating 25-hydroxyvitamin D (25-OHD) and colorectal cancer (CRC) survival outcomes. METHODS: We conducted analyses among the Study of Colorectal Cancer in Scotland (SOCCS) and the UK Biobank (UKBB). Both cancer-specific survival (CSS) and overall survival (OS) outcomes were examined. The 25-OHD levels were categorised into three groups, and multi-variable Cox-proportional hazard models were applied to estimate hazard ratios (HRs). We performed individual-level Mendelian randomisation (MR) through the generated polygenic risk scores (PRS) of 25-OHD and summary-level MR using the inverse-variance weighted (IVW) method. RESULTS: We observed significantly poorer CSS (HR = 0.65,95%CI = 0.55-0.76,P = 1.03 × 10-7) and OS (HR = 0.66,95%CI = 0.58-0.75,P = 8.15 × 10-11) in patients with the lowest compared to those with the highest 25-OHD after adjusting for covariates. These associations remained across patients with varied tumour sites and stages. However, we found no significant association between 25-OHD PRS and either CSS (HR = 0.98,95%CI = 0.80-1.19,P = 0.83) or OS (HR = 1.07,95%CI = 0.91-1.25,P = 0.42). Furthermore, we found no evidence for causal effects by conducting summary-level MR analysis for either CSS (IVW:HR = 1.04,95%CI = 0.85-1.28,P = 0.70) or OS (IVW:HR = 1.10,95%CI = 0.93-1.31,P = 0.25). CONCLUSION: This study supports the observed association between lower circulating 25-OHD and poorer survival outcomes for CRC patients. Whilst the genotype-specific association between better outcomes and higher 25-OHD is intriguing, we found no support for causality using MR approaches.

Novel protein ligase based on dual split intein.

Inteins are unique single-turnover enzymes that can excise themselves from the precursor protein without the aid of any external cofactors or energy. In most cases, inteins are covalently linked with the extein sequences and protein splicing happens spontaneously. In this study, a novel protein ligation system was developed based on two atypical split inteins without cross reaction, in which the large segments of one S1 and one S11 split intein fusion protein acted as a protein ligase, the small segments (only several amino acids long) was fused to the N-extein and C-extein, respectively. The splicing activity was demonstrated in E. coli and in vitro with different extein sequences, which showed ∼15% splicing efficiency in vitro. The protein trans-splicing in vitro was further optimized, and possible reaction explanations were explored. As a proof of concept, we expect this approach to expand the scope of trans-splicing-based protein engineering and provide new clues for intein based protein ligase.

Evaluation of reverse transcription yield of RNA standards and forensic samples based on droplet digital PCR.

RNA analysis has shown great value in forensic science, such as body fluids and tissue identification, postmortem interval estimation, biological age prediction, etc. Currently, most RNA follow-up experiments involve reverse transcription (RT) procedures. It has been shown that the RT step is variable and has a greater impact on subsequent data analysis, especially for forensic trace samples. However, the pattern of variation between different RNA template inputs and complementary DNA (cDNA) yield is unclear. In this study, a series of 2-fold gradient dilutions of RNA standards (1 µg/µL - 0.24 ng/µL) and forensic samples (including blood samples, saliva samples, bloodstains, and saliva stains) were reverse-transcribed using EasyQuick RT MasterMix. The obtained cDNA was quantified by droplet digital PCR (ddPCR) to assess the RT yield of the ACTB gene. The results showed that the 125 ng RNA template had the highest RT yield in a 10 µL RT reaction system with the selected kit. For all stain samples, the RT yield improved as the amount of RNA template input increased since RNA quantities were below 125 ng. As many commercialized reverse transcription kits using different kinds of enzymes are available for forensic RNA research, we recommend that systematic experiments should be performed in advance to determine the amount of RNA input at the optimum RT yield when using any kit for reverse transcription experiments.

Diet-related diseases mediate the effect of masticatory function on premature death in older adults.

AIM: Although poor oral health has been a potentially modifiable risk for mortality, the precise association between functional tooth units (FTUs) and premature death as well as the underlying mechanisms remains unclear. METHODS: This study used data from the National Health and Nutrition Examination Survey (NHANES) 2009-2018. Mortality details were obtained from the National Death Index (NDI). The number of FTUs was defined as pairs of opposing natural and artificial teeth in the premolar and molar area. Weighted logistic regression models were employed to assess the relationship between FTU and premature death. Demographic characteristics, lifestyle habits, and disease histories were adjusted as confounding factors. The propensity score matching (PSM) was conducted to further assess the association between FTU and premature death. Mediation analyses were conducted to assess the role of diet-related diseases in the association between FTU and premature death. RESULTS: The analysis included 4169 individuals aged between 60 and 74 years. Participants with 0 ≤ FTUs ≤ 3 had a significantly higher odds of premature death compared to the 10 ≤ FTUs ≤ 12 group (OR = 2.142, 95% CI 1.091-4.208). After missing data imputation, 0 ≤ FTUs ≤ 3 was still significantly associated with increased odds of premature death (OR = 2.115, 95% CI 1.125-3.975). The relationship between 0 ≤ FTUs ≤ 3 and reference group persisted (OR = 2.196, 95% CI 1.296-3.721) after PSM analyses. For mechanism, mediation analysis showed that diet-related diseases, including diabetes and hypertension, partially mediated the association between FTU and premature death with proportions of 5.089% and 8.437%, respectively. CONCLUSION: The findings revealed a link between impairment of masticatory function and a heightened odds of premature death among older adults. Notably, 0 ≤ FTUs ≤ 3 is significantly correlated to premature death among this demographic, with diabetes and hypertension partially mediating the effect of FTU on premature death. Further longitudinal studies are required to validate the findings.

Efficacy and safety of anticoagulant for treatment and prophylaxis of VTE patients with renal insufficiency: a systemic review and meta-analysis.

Patients with venous thromboembolism (VTE) comorbid renal insufficiency (RI) are at higher risk of bleeding and thrombosis. Recommendations in guidelines on anticoagulation therapy for those patients remain ambiguous. The goal of this study is to compare the efficacy and safety between different anticoagulant regimens in VTE patients comorbid RI at different stages of treatment and prophylaxis. We performed English-language searches of Pubmed, EMBASE, and Web of Science (inception to Nov 2022). RCTs evaluated anticoagulants for VTE treatment at the acute phase, extension phase, and prophylaxis in patients with RI and reported efficacy and safety outcomes were selected. The methodological quality of the studies was assessed at the outcome level using the risk-of-bias assessment tool developed by the Cochrane Bias Methods Group. A meta-analysis of twenty-five RCTs was conducted, comprising data from twenty-three articles, encompassing a total of 9,680 participants with RI. In the acute phase, the risk of bleeding was increased with novel oral anticoagulants (NOACs) compared to LMWH (RR 1.29, 95% CI 1.04-1.60). For the prophylaxis of VTE, NOACs were associated with an elevated risk of bleeding compared with placebo (RR 1.31, 95%CI 1.02-1.68). In comparison to non-RI patients, both NOACs and vitamin K antagonists (VKA) could increase the risk of bleeding among RI patients (RR 1.45, 95%CI 1.14-1.84 and RR 1.53, 95%CI 1.25-1.88, respectively) during acute phase, while NOACs may increase the incidence of VTE in RI population (RR 1.74, 95%CI 1.29-2.34). RI patients who are under routine anticoagulation have a significantly higher risk of adverse outcomes. LMWH is the most effective and safe option for VTE treatment or prophylaxis in patients with RI.

Association between masticatory function and depression in older adults: Results from NHANES 2009 to 2018.

AIM: Depression is prevalent among older adults. Although the number of missing teeth is considered to be associated with depression, the relationship between masticatory function, which is usually indicated by functional tooth units (FTUs), and depression in older adults remains unclear. MATERIALS AND METHODS: This study used data from the National Health and Nutrition Examination Survey (NHANES) 2009-2018. The number of FTUs was defined as pairs of opposing natural and artificial teeth. Depression was accessed using the Patient Health Questionnaire (PHQ-9), and participants who scored ≥10 on PHQ-9 were diagnosed with depression. Logistic regression analyses, propensity score matching (PSM) analyses and subgroup analyses were conducted to assess the association between FTU and depression. RESULTS: The analysis included 5764 individuals over 60 years. An association between FTU and the risk of depression among older adults was detected (odds ratio [OR] = 0.951, 95% confidence interval [CI] 0.915-0.989), suggesting protective roles of more FTUs. Significant increase in the risk of depression in 0 ≤ FTUs ≤ 3 was observed compared with 10 ≤ FTUs ≤ 12 (OR = 1.819, 95% CI 1.157-2.858). However, no significant increase in the risk of depression in 4 ≤ FTUs ≤ 9 was found. After PSM, significant increase in the risk of depression in 0 ≤ FTUs ≤ 3 was still detected compared with 4 ≤ FTUs ≤ 12 (OR = 1.484, 95% CI 1.030-2.136). Subgroup analyses demonstrated consistent results in all subgroups, except for individuals aged 76-80 and drinking regularly. CONCLUSIONS: The findings suggested the association between impaired masticatory function and the risk of depression among older adults. Longitudinal studies are needed to elucidate the role of masticatory function impairment in the development of depression further.

Leveraging Large Language Models for Improved Patient Access and Self-Management: Assessor-Blinded Comparison Between Expert- and AI-Generated Content.

BACKGROUND: While large language models (LLMs) such as ChatGPT and Google Bard have shown significant promise in various fields, their broader impact on enhancing patient health care access and quality, particularly in specialized domains such as oral health, requires comprehensive evaluation. OBJECTIVE: This study aims to assess the effectiveness of Google Bard, ChatGPT-3.5, and ChatGPT-4 in offering recommendations for common oral health issues, benchmarked against responses from human dental experts. METHODS: This comparative analysis used 40 questions derived from patient surveys on prevalent oral diseases, which were executed in a simulated clinical environment. Responses, obtained from both human experts and LLMs, were subject to a blinded evaluation process by experienced dentists and lay users, focusing on readability, appropriateness, harmlessness, comprehensiveness, intent capture, and helpfulness. Additionally, the stability of artificial intelligence responses was also assessed by submitting each question 3 times under consistent conditions. RESULTS: Google Bard excelled in readability but lagged in appropriateness when compared to human experts (mean 8.51, SD 0.37 vs mean 9.60, SD 0.33; P=.03). ChatGPT-3.5 and ChatGPT-4, however, performed comparably with human experts in terms of appropriateness (mean 8.96, SD 0.35 and mean 9.34, SD 0.47, respectively), with ChatGPT-4 demonstrating the highest stability and reliability. Furthermore, all 3 LLMs received superior harmlessness scores comparable to human experts, with lay users finding minimal differences in helpfulness and intent capture between the artificial intelligence models and human responses. CONCLUSIONS: LLMs, particularly ChatGPT-4, show potential in oral health care, providing patient-centric information for enhancing patient education and clinical care. The observed performance variations underscore the need for ongoing refinement and ethical considerations in health care settings. Future research focuses on developing strategies for the safe integration of LLMs in health care settings.

Risk factors and characteristics analysis of cognitive impairment in patients with cerebral infarction during recovery period.

OBJECTIVE: To analyze the risk factors and characteristics of cognitive impairment in patients with cerebral infarction during the recovery period. METHODS: This retrospective case-control study included 183 patients with cerebral infarction in the recovery period. According to the MMSE score, they were divided into a cognitive impairment group of 79 cases and a cognitive normal group of 104 cases. Collect clinical data from all patients, including age, gender, body mass index, laboratory test results, past medical history, National Institute of Health Stroke Scale (NIHSS) score, modified Barthel index, Oxfordshire Community Stroke Project (OCSP) classification, and number of infarcted lesions. Multiple logistic regression analysis was used to identify risk factors related to cognitive impairment in patients with cerebral infarction. RESULT: There were significant differences (p < 0.05) between the cognitive impairment group and the cognitive normal group in terms of age, body mass index, low-density lipoprotein level, NIHSS score, modified Barthel index, and number of infarcted lesions. Multivariate logistic regression analysis showed that age ≥ 65 years, stroke, carotid artery plaques, NIHSS score ≥ 5, anterior circulation infarction type, and multiple infarcted lesions were important risk factors for cognitive impairment. CONCLUSION: Elderly age, presence of carotid artery plaques, high NIHSS score, multiple infarct lesions, and specific infarct types are important risk factors for cognitive dysfunction in patients during the recovery period of cerebral infarction.

Assessment of sulfamethoxazole removal by three wetland plant species under hydroponic conditions: uptake, accumulation, and physiological responses.

Plants play a crucial role as a removal pathway in constructed wetlands, demonstrating the ability to absorb and tolerate antibiotics from wastewater. However, the specific contribution of plants in this regard has not yet to be sufficiently established. To gain a more comprehensive insight into the associated processes, we selected three common wetland plant species, Canna indica L. (C. indica), Cyperus alternifolius L. (C. alternifolius), and Thalia dealbata Fraser (T. dealbata), to evaluate their capacity for uptake, accumulation, and physiological response in the removal of sulfamethoxazole (SMX) at varying initial concentrations (10, 30, 100, and 300 µg/L) under hydroponic conditions. The results showed that SMX removal was more efficient at lower concentrations (10 and 30 µg/L) than at higher concentrations (100 and 300 µg/L). Moreover, plant systems were found to consistently outperform unplanted systems in SMX removal. Among the assessed species, C. indica was identified as being relatively effective in the removal of SMX, whereas the performance of C. alternifolius was notably less pronounced. A positive correlation was observed between the concentration of SMX in the plant tissues and that in the external aqueous medium. However, plant tissue residues contributed only a minor fraction to the overall removal of SMX. Wetland plants absorb SMX through their roots, and we accordingly detected significantly higher concentrations in submerged plant tissues. Furthermore, we also detected reductions in net photosynthetic rates indicative of potential phytotoxicity, which is associated with the accumulation of antibiotic in the shoot tissues. Accumulation of SMX in the roots and rhizomes was also found to be associated with the development of shorter roots, with this effect becoming more pronounced with an increase in the concentration of exogenous SMX. However, despite these adverse effects, plants can detoxify antibiotics via the glutathione pathway. Of the assessed plant species, C. indica was identified as the most SMX tolerant, as indicated by Km and Vmax values, with C. alternifolius being the least tolerant. Our findings in this study reveal the potential value of wetland plants in the sequestration of antibiotics and provide evidence for the underlying mechanisms of action. These findings could make an important contribution to the implementation of phytoremediation in antibiotic-contaminated water.

Three wetland plants with fibrous root systems, namely Canna indica, Cyperus alterniflius, and Thalia dealbata, were selected to investigate the removal efficiencies of sulfamethoxazole in the hydroponic system by different emergent plants, quantify the contribution of uptake and accumulation for sulfamethoxazole in plant tissues, and assess the physiological responses of plants and their effect on the removal of sulfamethoxazole. The knowledge obtained from this study shows the potential use of wetland plants for removing antibiotics and the inherent mechanisms, which will be useful for the application of phytoremediation in antibiotic contaminated water.

Populus euphratica CPK21 Interacts with NF-YC3 to Enhance Cadmium Tolerance in Arabidopsis.

The toxic metal cadmium (Cd) poses a serious threat to plant growth and human health. Populus euphratica calcium-dependent protein kinase 21 (CPK21) has previously been shown to attenuate Cd toxicity by reducing Cd accumulation, enhancing antioxidant defense and improving water balance in transgenic Arabidopsis. Here, we confirmed a protein-protein interaction between PeCPK21 and Arabidopsis nuclear transcription factor YC3 (AtNF-YC3) by yeast two-hybrid and bimolecular fluorescence complementation assays. AtNF-YC3 was induced by Cd and strongly expressed in PeCPK21-overexpressed plants. Overexpression of AtNF-YC3 in Arabidopsis reduced the Cd inhibition of root length, fresh weight and membrane stability under Cd stress conditions (100 µM, 7 d), suggesting that AtNF-YC3 appears to contribute to the improvement of Cd stress tolerance. AtNF-YC3 improved Cd tolerance by limiting Cd uptake and accumulation, activating antioxidant enzymes and reducing hydrogen peroxide (H2O2) production under Cd stress. We conclude that PeCPK21 interacts with AtNF-YC3 to limit Cd accumulation and enhance the reactive oxygen species (ROS) scavenging system and thereby positively regulate plant adaptation to Cd environments. This study highlights the interaction between PeCPK21 and AtNF-YC3 under Cd stress conditions, which can be utilized to improve Cd tolerance in higher plants.

JMJD6 Autoantibodies as a Potential Biomarker for Inflammation-Related Diseases.

Inflammation is closely associated with cerebrovascular diseases, cardiovascular diseases, diabetes, and cancers, and it is accompanied by the development of autoantibodies in the early stage of inflammation-related diseases. Hence, it is meaningful to discover novel antibody biomarkers targeting inflammation-related diseases. In this study, Jumonji C-domain-containing 6 (JMJD6) was identified by the serological identification of antigens through recombinant cDNA expression cloning. In particular, JMJD6 is an antigen recognized in serum IgG from patients with unstable angina pectoris (a cardiovascular disease). Then, the serum antibody levels were examined using an amplified luminescent proximity homogeneous assay-linked immunosorbent assay and a purified recombinant JMJD6 protein as an antigen. We observed elevated levels of serum anti-JMJD6 antibodies (s-JMJD6-Abs) in patients with inflammation-related diseases such as ischemic stroke, acute myocardial infarction (AMI), diabetes mellitus (DM), and cancers (including esophageal cancer, EC; gastric cancer; lung cancer; and mammary cancer), compared with the levels in healthy donors. The s-JMJD6-Ab levels were closely associated with some inflammation indicators, such as C-reactive protein and intima-media thickness (an atherosclerosis index). A better postoperative survival status of patients with EC was observed in the JMJD6-Ab-positive group than in the negative group. An immunohistochemical analysis showed that JMJD6 was highly expressed in the inflamed mucosa of esophageal tissues, esophageal carcinoma tissues, and atherosclerotic plaques. Hence, JMJD6 autoantibodies may reflect inflammation, thereby serving as a potential biomarker for diagnosing specific inflammation-related diseases, including stroke, AMI, DM, and cancers, and for prediction of the prognosis in patients with EC.

Impact of periodontitis on type 2 diabetes: a bioinformatic analysis.

BACKGROUND: Periodontitis is strongly associated with type 2 diabetes (T2D) that results in serious complications and mortality. However, the pathogenic role of periodontitis in the development of T2D and the underlain mechanism have not been fully elucidated. METHODS: A Mendelian randomization (MR) was performed to estimate the causality between two diseases. Bioinformatics tools, including gene ontology and pathway enrichment analyses, were employed to analyze the common differentially expressed genes (DEGs) in periodontitis and T2D. MR and colocalization analyses were then utilized to investigate the causal associations between potential pathogenic gene expression and the risk of T2D. Single cell-type expression analysis was further performed to detect the cellular localization of these genes. RESULTS: Genetically predicted periodontitis was associated with a higher risk of T2D (OR, 1.469; 95% CI, 1.117-1.930; P = 0.006) and insulin resistance (OR 1.034; 95%CI 1.001-1.068; P = 0.041). 79 common DEGs associated with periodontitis and T2D were then identified and demonstrated enrichment mainly in CXC receptor chemokine receptor binding and interleutin-17 signaling pathway. The integration of GWAS with the expression quantitative trait locis of these genes from the peripheral blood genetically prioritized 6 candidate genes, including 2 risk genes (RAP2A, MCUR1) and 4 protective genes (WNK1, NFIX, FOS, PANX1) in periodontitis-related T2D. Enriched in natural killer cells, RAP2A (OR 4.909; 95% CI 1.849-13.039; P = 0.001) demonstrated high risk influence on T2D, and exhibited strong genetic evidence of colocalization (coloc.abf-PPH4 = 0.632). CONCLUSIONS: This study used a multi-omics integration method to explore causality between periodontitis and T2D, and revealed molecular mechanisms using bioinformatics tools. Periodontitis was associated with a higher risk of T2D. MCUR1, RAP2A, FOS, PANX1, NFIX and WNK1 may play important roles in the pathogenesis of periodontitis-related T2D, shedding light on the development of potential drug targets.

[Consistency evaluation of multidimensional quality attributes of Atractylodis Macrocephalae Rhizoma by fusion of multi-source information].

The quality control of Chinese medicinal decoction pieces is one of the key tasks in the traditional Chinese medicine industry. In this study, multi-source information fusion was employed to fuse the data from near-infrared spectroscopy, electronic tongues, and other tests and establish an overall quality consistency evaluation method for Atractylodis Macrocephalae Rhizoma, which provided methodological support for the overall quality evaluation of Atractylodis Macrocephalae Rhizoma. The near-infrared spectroscopy information was measured in both static and dynamic states for 23 batches of Atractylodis Macrocephalae Rhizoma samples from different sources, and the electronic tongue sensory information, moisture content, and leachate content were measured. The overall quality of Atractylodis Macrocephalae Rhizoma was evaluated by multi-source information fusion. The results showed that the near-infrared spectroscopy information of 16122103, 801000509, 801000352, 701003656, HX21L01, and 160956 was different from that of other batches of Atractylodis Macrocephalae Rhizoma powder in the static state, and 701003298, 16122103, 701003656, 701003107, 801000229, and 18090404 were the different batches in the dynamic state. The moisture content showed no significant difference between batches. The leachate content in the batch 801000509 was different from that in other batches. The electronic tongue sensory information of 150721004, 151237, 160703004, HX21M01, HX21K04, HX21K01, and 601003516 was different from that of other batches. Furthermore, data layer fusion was employed to analyze the overall quality of Atractylodis Macrocephalae Rhizoma. Four batches, 150721004, HX21M01, HX21K04, and HX21K01, showed the parameters exceeding the 95% control limits and differed from the other samples in terms of the overall quality. This study integrated the information of moisture, near-infrared spectroscopy, and other sources to evaluate the quality consistency among 23 batches of Atractylodis Macrocephalae Rhizoma samples, which provides a reference for the quality consistency evaluation of Chinese medicinal decoction pieces.

PWSC: a novel clustering method based on polynomial weight-adjusted sparse clustering for sparse biomedical data and its application in cancer subtyping.

BACKGROUND: Clustering analysis is widely used to interpret biomedical data and uncover new knowledge and patterns. However, conventional clustering methods are not effective when dealing with sparse biomedical data. To overcome this limitation, we propose a hierarchical clustering method called polynomial weight-adjusted sparse clustering (PWSC). RESULTS: The PWSC algorithm adjusts feature weights using a polynomial function, redefines the distances between samples, and performs hierarchical clustering analysis based on these adjusted distances. Additionally, we incorporate a consensus clustering approach to determine the optimal number of classifications. This consensus approach utilizes relative change in the cumulative distribution function to identify the best number of clusters, resulting in more stable clustering results. Leveraging the PWSC algorithm, we successfully classified a cohort of gastric cancer patients, enabling categorization of patients carrying different types of altered genes. Further evaluation using Entropy showed a significant improvement (p = 2.905e-05), while using the Calinski-Harabasz index demonstrates a remarkable 100% improvement in the quality of the best classification compared to conventional algorithms. Similarly, significantly increased entropy (p = 0.0336) and comparable CHI, were observed when classifying another colorectal cancer cohort with microbial abundance. The above attempts in cancer subtyping demonstrate that PWSC is highly applicable to different types of biomedical data. To facilitate its application, we have developed a user-friendly tool that implements the PWSC algorithm, which canbe accessed at http://pwsc.aiyimed.com/ . CONCLUSIONS: PWSC addresses the limitations of conventional approaches when clustering sparse biomedical data. By adjusting feature weights and employing consensus clustering, we achieve improved clustering results compared to conventional methods. The PWSC algorithm provides a valuable tool for researchers in the field, enabling more accurate and stable clustering analysis. Its application can enhance our understanding of complex biological systems and contribute to advancements in various biomedical disciplines.

Coronary Artery Calcium Score Improves Risk Assessment of Symptomatic Patients in Low-Risk Group Based on Current Guidelines.

Background: The guidelines for evaluation and diagnosis of stable chest pain (SCP) released by American societies in 2021 (2021 GL) and European Society of Cardiology (ESC) in 2019 both recommended the estimation of pretest probability (PTP) by ESC-PTP model. Further risk assessment for the low-risk group according to 2021 GL (ESC-PTP ≤ 15%) is important but still remains unclear. Thus, the present study intended to comprehensively investigate the diagnostic and prognostic value of coronary artery calcium score (CACS) in these low-risk patients. Methods: From January 2017 to June 2019, we initially enrolled 8265 patients who were referred for CACS and coronary computed tomography angiography (CCTA) for the assessment of SCP. PTP of each patient was estimated by ESC-PTP model. Patients with ESC-PTP ≤ 15% were finally included and followed up for major adverse cardiovascular event (MACE) and utilization of invasive procedures until June 2022. The degree of coronary artery disease (CAD) on CCTA was defined as no CAD (0%), nonobstructive CAD (1-49%) and obstructive CAD ( ≥ 50%). Multivariate Cox proportional hazards and Logistic regression models were used to calculate adjusted hazard ratios (HRs) and odds ratios (ORs) with 95% confidence intervals (CIs), respectively. Results: A total of 5183 patients with ESC-PTP ≤ 15% were identified and 1.6% experienced MACE during the 4-year follow-up. The prevalence of no CAD and obstructive CAD decreased and increased significantly (p < 0.0001) in patients with higher CACS, respectively, and 62% had nonobstructive CAD among those with CACS > 0, resulting in dramatically increasing ORs for any stenosis ≥ 50% and > 0% across CACS strata. Higher CACS was also associated with an elevated risk of MACE (adjusted HR of 3.59, 13.47 and 6.58 when comparing CACS = 0-100, CACS > 100 and CACS > 0 to CACS = 0, respectively) and intensive utilization of invasive procedures. Conclusions: In patients for whom subsequent testing should be deferred according to 2021 GL, high CACS conveyed a significant probability of substantial stenoses and clinical endpoints, respectively. These findings support the potential role of CACS as a further risk assessment tool to improve clinical management in these low-risk patients.

Using Machine Learning to Predict the In-Hospital Mortality in Women with ST-Segment Elevation Myocardial Infarction.

Background: Several studies have shown that women have a higher mortality rate than do men from ST-segment elevation myocardial infarction (STEMI). The present study was aimed at developing a new risk-prediction model for all-cause in-hospital mortality in women with STEMI, using predictors that can be obtained at the time of initial evaluation. Methods: We enrolled 8158 patients who were admitted with STEMI to the Tianjin Chest Hospital and divided them into two groups according to hospital outcomes. The patient data were randomly split into a training set (75%) and a testing set (25%), and the training set was preprocessed by adaptive synthetic (ADASYN) sampling. Four commonly used machine-learning (ML) algorithms were selected for the development of models; the models were optimized by 10-fold cross-validation and grid search. The performance of all-population-derived models and female-specific models in predicting in-hospital mortality in women with STEMI was compared by several metrics, including accuracy, specificity, sensitivity, G-mean, and area under the curve (AUC). Finally, the SHapley Additive exPlanations (SHAP) value was applied to explain the models. Results: The performance of models was significantly improved by ADASYN. In the overall population, the support vector machine (SVM) combined with ADASYN achieved the best performance. However, it performed poorly in women with STEMI. Conversely, the proposed female-specific models performed well in women with STEMI, and the best performing model achieved 72.25% accuracy, 82.14% sensitivity, 71.69% specificity, 76.74% G-mean and 79.26% AUC. The accuracy and G-mean of the female-specific model were greater than the all-population-derived model by 34.64% and 9.07%, respectively. Conclusions: A machine-learning-based female-specific model can conveniently and effectively identify high-risk female STEMI patients who often suffer from an incorrect or delayed management.

Effects of simvastatin on immunoreaction and inflammation in rats with asthma by regulating NOTCH signaling pathway.

To investigate the effect of simvastatin on the immunoreaction and inflammation in rats with asthma through the NOTCH signaling pathway, a total of 36 Sprague-Dawley (SD) rats were enrolled and randomly divided into the normal group (n=12), model group (n=12) and simvastatin group (n=12). The rats in the normal group were fed normally, those in the model group were prepared into models of asthma, and those in the simvastatin group were prepared into models of asthma and intervened with simvastatin. Next, the morphology of airway tissues was observed via hematoxylin-eosin (HE) staining assay. Besides, immunohistochemistry was employed to determine the expression of interferon-γ (INF-γ), and the relative protein expression levels of NOTCH2 and NOTCH3 were measured by Western blotting (WB). Additionally, enzyme-linked immunosorbent assay (ELISA) and quantitative polymerase chain reaction (qPCR) assay were carried out to detect the content of interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α) and the relative mRNA expression levels of INF-γ, IL-6 and TNF-α, respectively. HE staining results uncovered that the airway tissues displayed normal morphology in the normal group and disordered morphology and obvious inflammatory infiltration in the model group. In comparison with the model group, the simvastatin group exhibited significantly improved morphology of airway tissues. Based on immunohistochemistry, the average optical density of INF-γ positive expression was increased in the model group and simvastatin group compared with that in the normal group (P<0.05), and it was distinctly lower in the simvastatin group than that in the model group (P<0.05). The results of WB showed that compared with those in the normal group, the relative protein expression levels of NOTCH2 and NOTCH3 were elevated in model group and simvastatin group (P<0.05), whereas they were overtly reduced in simvastatin group compared with those in model group (P<0.05). It was found through ELISA that the model group and simvastatin group had raised content of IL-6 and TNF-α in comparison with the normal group (P<0.05), while the simvastatin group exhibited markedly decreased content of IL-6 and TNF-α in comparison with the model group (P<0.05). The results of qPCR revealed that the relative mRNA expression levels of INF-γ, IL-6 and TNF-α were distinctly up-regulated in the model group and simvastatin group compared with those in the normal group, displaying statistically significant differences (P<0.05), whereas they were markedly lowered in simvastatin group compared with those in the model group, showing statistically significant differences (P<0.05). Simvastatin represses the immunoreaction and inflammation in rats with asthma by down-regulating the NOTCH signaling pathway.

Efficient Perovskite Nanograin Light-Emitting Diodes in Green-to-Blue Gamut with Co-Additive Engineering.

Perovskite nanograins exceeding the Bohr exciton diameter show great potential for high-performance light-emitting diodes (LEDs) owing to their bandgap homogeneity, spatial charge confinement, and nonlocal interaction. However, it is challenging to directly synthesize proper nanograins along with reduced crystal defects on functional substrate, and the corresponding high-efficiency perovskite LEDs (PeLEDs) have rarely been reported. In this study, crystallization modulation for perovskites with an effective co-additive system, including lithium bromide, p-fluorophenethylammonium bromide, and 18-crown-6, is performed. Furthermore, it is demonstrated that the proposed co-additive system can synergistically retard perovskite crystallization and reduce crystal defects. Consequently, high-quality perovskite nanograin solids (≈22.8 nm) are obtained with a high photoluminescence quantum yield (≈88%). These superior optical properties contribute to developing efficient green PeLEDs with a champion external quantum efficiency (EQE) of 28.4% and an average EQE of 27.1%. The co-additive system can be universally applied to mixed-halide perovskite nanograin LED, presenting a maximum EQE of 24.4%, 21.6%, 17.5%, and 11.1% for the blue device at 496, 488, 478, and 472 nm, respectively, along with a narrow spectral linewidth (17-14 nm) and stable color. These results supplement the research on high-efficiency perovskite nanograin LEDs for multicolor displays and lighting.

Enhanced anaerobic digestion of human feces by ferrous hydroxyl complex (FHC): Stress factors alleviation and microbial resistance improvement.

Anaerobic digestion (AD) offers a reliable strategy for resource recovery from source-separated human feces (HF), but is limited by a disproportionate carbon/nitrogen (C/N) ratio. Ferrous hydroxyl complex (FHC) was first introduced into the HF-AD system to mediate methanogenesis. Mono-digestion of undiluted HF was inhibited by high levels of volatile fatty acids (VFAs), ammonia, and hydrogen sulfide (H2S). FHC addition at optimum dosage (500-1000 mg/L) increased the cumulative methane (CH4) yield by 22.7%, enhanced the peak value of daily CH4 production by 60.5%, and shortened the lag phase by 24.7%. H2S concentration in biogas was also greatly decreased by FHC via precipitation. FHC mainly facilitated the hydrolysis, acidification, and methanogenesis processes. The production and transformation of VFAs were optimized in the presence of FHC, thus relieving acid stress. FHC elevated the activities of alkaline protease, cellulase, and acetate kinase by 32.3%, 18.2%, and 30.3%, respectively. Microbial analysis revealed that hydrogenotrophic methanogens prevailed in mono-digestion at high HF loading but were weakened after FHC addition. FHC also enriched Methanosarcina, thereby expanding the methanogenesis pathway and improving the resistance to ammonia stress. This work would contribute to improving the methanogenic performance and resource utilization for HF anaerobic digestion.