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Abstract Renal dysfunction (RD) often characterizes the worse course of patients with advanced heart failure (AHF). Many prognosis assessments are hindered by researcher biases, redundant predictors, and lack of clinical applicability. In this study, we enroll 1736 AHF/RD patients, including data from Henan Province Clinical Research Center for Cardiovascular Diseases (which encompasses 11 hospital subcenters), and Beth Israel Deaconess Medical Center. We developed an AI hybrid modeling framework, assembling 12 learners with different feature selection paradigms to expand modeling schemes. The optimized strategy is identified from 132 potential schemes to establish an explainable survival assessment system: AIHFLevel. The conditional inference survival tree determines a probability threshold for prognostic stratification. The evaluation confirmed the system’s robustness in discrimination, calibration, generalization, and clinical implications. AIHFLevel outperforms existing models, clinical features, and biomarkers. We also launch an open and user-friendly website www.hf-ai-survival.com , empowering healthcare professionals with enhanced tools for continuous risk monitoring and precise risk profiling.

Abstract Parkinson’s disease (PD) is a serious neurodegenerative disorder marked by significant clinical and progression heterogeneity. This study aimed at addressing heterogeneity of PD through integrative analysis of various data modalities. We analyzed clinical progression data (≥5 years) of individuals with de novo PD using machine learning and deep learning, to characterize individuals’ phenotypic progression trajectories for PD subtyping. We discovered three pace subtypes of PD exhibiting distinct progression patterns: the Inching Pace subtype (PD-I) with mild baseline severity and mild progression speed; the Moderate Pace subtype (PD-M) with mild baseline severity but advancing at a moderate progression rate; and the Rapid Pace subtype (PD-R) with the most rapid symptom progression rate. We found cerebrospinal fluid P-tau/α-synuclein ratio and atrophy in certain brain regions as potential markers of these subtypes. Analyses of genetic and transcriptomic profiles with network-based approaches identified molecular modules associated with each subtype. For instance, the PD-R-specific module suggested STAT3, FYN, BECN1, APOA1, NEDD4, and GATA2 as potential driver genes of PD-R. It also suggested neuroinflammation, oxidative stress, metabolism, PI3K/AKT, and angiogenesis pathways as potential drivers for rapid PD progression (i.e., PD-R). Moreover, we identified repurposable drug candidates by targeting these subtype-specific molecular modules using network-based approach and cell line drug-gene signature data. We further estimated their treatment effects using two large-scale real-world patient databases; the real-world evidence we gained highlighted the potential of metformin in ameliorating PD progression. In conclusion, this work helps better understand clinical and pathophysiological complexity of PD progression and accelerate precision medicine.

Abstract In acidic soils, aluminum (Al) toxicity inhibits the growth and development of plant roots and affects nutrient and water absorption, leading to reduced yield and quality. Therefore, it is crucial to investigate and identify candidate genes for Al tolerance and elucidate their physiological and molecular mechanisms under Al stress. In this study, we identified a new gene OsAlR3 regulating Al tolerance, and analyzed its mechanism from physiological, transcriptional and metabolic levels. Compared with the WT, malondialdehyde (MDA) and hydrogen peroxide (H2O2) content were significantly increased, superoxide dismutase (SOD) activity and citric acid (CA) content were significantly decreased in the osalr3 mutant lines when exposed to Al stress. Under Al stress, the osalr3 exhibited decreased expression of antioxidant-related genes and lower organic acid content compared with WT. Integrated transcriptome and metabolome analysis showed the phenylpropanoid biosynthetic pathway plays an important role in OsAlR3-mediated Al tolerance. Exogenous CA and oxalic acid (OA) could increase total root length and enhance the antioxidant capacity in the mutant lines under Al stress. Conclusively, we found a new gene OsAlR3 that positively regulates Al tolerance by promoting the chelation of Al ions through the secretion of organic acids, and increasing the expression of antioxidant genes.

Guided by the intelligent construction of coal mines and integrating the concept of the Cyber-Physical System (CPS), a novel approach to a coal mine information-physical fusion system is proposed. This concept emerges from the advancement of intelligent mines and the growing need for enhanced safety in coal mine operations. From a system safety perspective, this approach aims to effectively evaluate security issues by better integrating the informational and physical layers of intelligent mines. Currently, research in areas such as power grids and water networks has widely adopted concepts of cascade failures and robustness. It is suggested that the CPS framework be adapted to the mining sector. Considering the critical role of coal mines in China's energy security and their vulnerability to cyber attacks, a mine-specific CPS system is designed. This system incorporates a model of mine information-physical fusion, including networks for mine operations, management, and control, tailored to the unique conditions of mine shafts and underground settings. Utilizing Markov process theory, the paper delves into the theoretical study of the cascade failure process under deliberate attack strategies. This analysis is essential to effectively assess the safety issues within the information-physical system, providing vital support for fault prediction and safety analysis. The model of cascading failures in the mine information-physical system is developed, and based on an analysis of resilience and robustness, the study identifies key factors influencing the security of mine information-physical systems. Critical factors affecting the reliability of these systems include the number of system nodes, node coupling, edge count, and the interconnection methods of the dual-layer dependency network. The paper concludes by discussing the challenges in analyzing the security of information-physical systems and suggesting directions for future research.

Abstract This paper introduces two cases of multiple myeloma, COVID-19 infection during autologous stem cell transplantation, the treatment process, and different results of the two patients, which provides a reference for how to carry out ASCT safely during the COVID-19 normalization stage.

Abstract Non-pharmaceutical interventions (NPI) have great potential to improve cognitive function but limited investigation to discover NPI repurposing for Alzheimer's Disease (AD). This is the first study to develop an innovative framework to extract and represent NPI information from biomedical literature in a knowledge graph (KG), and train link prediction models to repurpose novel NPIs for AD prevention. We constructed a comprehensive KG, called ADInt, by extracting NPI information from biomedical literature. We used the previously-created SuppKG and NPI lexicon to identify NPI entities. Four KG embedding models (i.e., TransE, RotatE, DistMult and ComplEX) and two novel graph convolutional network models (i.e., R-GCN and CompGCN) were trained and compared to learn the representation of ADInt. Models were evaluated and compared on two test sets (time slice and clinical trial ground truth) and the best performing model was used to predict novel NPIs for AD. Discovery patterns were applied to generate mechanistic pathways for high scoring candidates. The ADInt has 162,212 nodes and 1,017,284 edges. R-GCN performed best in time slice (MR = 5.2054, Hits@10 = 0.8496) and clinical trial ground truth (MR = 3.4996, Hits@10 = 0.9192) test sets. After evaluation by domain experts, 10 novel dietary supplements and 10 complementary and integrative health were proposed from the score table calculated by R-GCN. Among proposed novel NPIs, we found plausible mechanistic pathways for photodynamic therapy and Choerospondias axillaris to prevent AD, and validated psychotherapy and manual therapy techniques using real-world data analysis. The proposed framework shows potential for discovering new NPIs for AD prevention and understanding their mechanistic pathways.

Abstract Background There is evidence for an association between the gut microbiome and endometriosis. However, their causal relationship and the mediating role of lipid metabolism remain unclear. Methods Using genome-wide association study (GWAS) data, we conducted a bidirectional Mendelian randomization (MR) analysis to investigate the causal relationships between gut microbiome and endometriosis. The inverse variance weighted (IVW) method was used as the primary model, with other MR models used for comparison. Sensitivity analysis based on different statistical assumptions was used to evaluate whether the results were robust. A two-step MR analysis was further conducted to explore the mediating effects of lipids, by integrating univariable MR and the multivariate MR method based on the Bayesian model averaging method (MR-BMA). Results We identified four possible intestinal bacteria genera associated with the risk of endometriosis through the IVW method, including Eubacterium ruminantium group (odds ratio [OR] = 0.881, 95% CI: 0.795–0.976, P = 0.015), Anaerotruncus (OR = 1.252, 95% CI: 1.028–1.525, P = 0.025), Olsenella (OR = 1.110, 95% CI: 1.007–1.223, P = 0.036), and Oscillospira (OR = 1.215, 95% CI: 1.014–1.456, P = 0.035). The further two-step MR analysis identified that the effect of Olsenella on endometriosis was mediated by triglycerides (proportion mediated: 3.3%; 95% CI = 1.5−5.1%). Conclusion This MR study found evidence for specific gut microbiomes associated with the risk of endometriosis, which might partially be mediated by triglycerides.

Abstract Objective Idiopathic infantile hypercalcemia (IIH) is a rare disorder of PTH-independent hypercalcemia. CYP24A1 and SLC34A1 gene mutations cause two forms of hereditary IIH. In this study, the clinical manifestations and molecular aspects of six new Chinese patients were investigated. Methods The clinical manifestations and laboratory study of six patients with idiopathic infantile hypercalcemia were analyzed retrospectively. Results Five of the patients were diagnosed with hypercalcemia, hypercalciuria, and bilateral medullary nephrocalcinosis. Their clinical symptoms and biochemical abnormalities improved after treatment. One patient presented at age 11 years old with arterial hypertension, hypercalciuria and nephrocalcinosis, but normal serum calcium. Gene analysis showed that two patients had compound heterozygous mutations of CYP24A1, one patient had a monoallelic CYP24A1 variant, and three patients had a monoallelic SLC34A1 variant. Four novel CYP24A1 variants (c.116G > C, c.287T > A, c.476G > A and c.1349T > C) and three novel SLC34A1 variants (c.1322 A > G, c.1697_1698insT and c.1726T > C) were found in these patients. Conclusions A monoallelic variant of CYP24A1 or SLC34A1 gene contributes to symptomatic hypercalcemia, hypercalciuria and nephrocalcinosis. Manifestations of IIH vary with onset age. Hypercalcemia may not necessarily present after infancy and IIH should be considered in patients with nephrolithiasis either in older children or adults.

Abstract Although adverse environmental exposures are considered a major cause of chronic diseases, current studies provide limited information on real-world chemical exposures and related risks. For this study, we collected serum samples from 5696 healthy people and patients, including those with 12 chronic diseases, in China and completed serum biomonitoring including 267 chemicals via gas and liquid chromatography-tandem mass spectrometry. Seventy-four highly frequently detected exposures were used for exposure characterization and risk analysis. The results show that region is the most critical factor influencing human exposure levels, followed by age. Organochlorine pesticides and perfluoroalkyl substances are associated with multiple chronic diseases, and some of them exceed safe ranges. Multi-exposure models reveal significant risk effects of exposure on hyperlipidemia, metabolic syndrome and hyperuricemia. Overall, this study provides a comprehensive human serum exposome atlas and disease risk information, which can guide subsequent in-depth cause-and-effect studies between environmental exposures and human health.

INTRODUCTION: Children born small for gestational age (SGA) are at a greater risk of developing insulin resistance, type 2 diabetes, and cardiovascular disease in adulthood. Gastrointestinal peptides, some secreted by intestinal L cells, regulate glucose and lipid metabolism and act on the hypothalamus to regulate energy homeostasis. The aim of this study was to explore whether gastrointestinal peptides are involved in metabolic disorders in SGA, which remains unclear. METHODS: The secretion of glucagon-like peptide 1 (GLP-1) and peptide YY (PYY) were investigated in prepubertal children born SGA, the differences between catch-up growth and persistent short stature were compared, and correlation with glucose and lipid metabolism was analyzed. GLP-1, PYY, insulin-like growth factor 1, glucose, insulin, and lipid concentrations were analyzed in prepubertal children aged 4-10 years, stratified into three groups: short-SGA (SGA-s), catch-up growth SGA, and normal growth appropriate for gestational age (AGA). RESULTS: Fasting GLP-1 and PYY concentrations were significantly lower in the SGA group than in the AGA group (p

BackgroundThe objective of this study was to examine whether the combination of elevated levels of C-reactive protein (CRP) and dyslipidemia increased the risk of stroke among middle-aged and older adult individuals in China.MethodsThis study utilized longitudinal data from the China Health and Nutrition Survey (CHNS) collected in 2009, 2015, and 2018. A total of 8,023 participants aged ≥40 years (3,595 males and 4,428 females) were included. The Generalized Estimating Equation (GEE) method was employed to examine the association between inflammation, dyslipidemia, their combined effects, and stroke in the Chinese population.ResultsA total of 174 stroke events occurred during follow-up. Compared with those with normal CRP levels (CRP ≤ 3 mg/L), the adjusted ORs and 95%CI were 2.13 (1.25, 3.64) for the female with elevated CRP level. Compared with those with non-dyslipidemia, the adjusted ORs and 95%CI were 1.56 (1.03, 2.37) for the individuals with high LDL cholesterol, 1.93 (1.12, 3.33) for the male with high LDL cholesterol. Compared with those with normal CRP levels and non-dyslipidemia, the adjusted ORs and 95%CI were 1.74 (1.08, 2.78) for the individuals with elevated CRP levels and dyslipidemia, 2.41 (1.29, 4.49) for the male with elevated CRP levels and dyslipidemia. People with the coexistence of elevated CRP levels and dyslipidemia had the highest risk of stroke among male.ConclusionIn females, higher levels of inflammation are associated with an increased incidence of stroke. In males, individuals with dyslipidemia characterized by high LDL cholesterol levels are more susceptible to stroke. In the general population, the joint effect of inflammation and dyslipidemia predisposes individuals to a higher risk of stroke, particularly among males.

ObjectiveThe cingulate sulcus sign (CSS) has been observed in patients with idiopathic normal pressure hydrocephalus (iNPH), suggesting potential disruptions in cerebrospinal fluid circulation and compromised glymphatic system. Although there are similarities in the underlying mechanisms between cerebral small vessel disease (CSVD) and iNPH, the relationship between CSS and CSVD remains unclear. This study aimed to investigate the prevalence and potential mechanisms of CSS in patients with CSVD.MethodsData from patients diagnosed with CSVD at Shengjing Hospital of China Medical University between January 2020 and October 2022 were retrospectively collected, including general information, global cognitive function [assessed by measuring Mini-Mental State Examination (MMSE)], and four CSVD magnetic resonance imaging (MRI) markers [(white matter hyperintensity (WMH), cerebral microbleeds (CMBs), lacunes, and enlarged perivascular spaces (EPVS)], CSS and the Evan’s index (EI).ResultsA total of 308 patients were included, and CSS was detected in 80 patients (26%). Univariate analysis revealed that MMSE scores in the CSS group were significantly lower compared to the non-CSS group (p < 0.001). Multivariable analysis showed an independent correlation between CSS and the presence of lacunes (odds ratio [OR] 0.358, 95% confidence interval [CI] 0.193–0.663, p = 0.001), presence of lobar dominant CMBs (OR 2.683, 95%CI 1.385–5.195, p = 0.003), periventricular WMH Fazekas score (OR 1.693, 95% CI 1.133–2.529, p = 0.01), and EI (OR 1.276, 95% CI 1.146–1.420, p < 0.001).ConclusionThis preliminary study showed that CSS can be observed in some patients with CSVD. The presence of CSS may represent different mechanisms of CSVD pathogenesis and reflect differences in the degree of cerebrospinal fluid (CSF)/interstitial fluid (ISF) stasis.

Non-intrusive load monitoring (NILM) can obtain fine-grained power consumption information for individual appliances within the user without installing additional hardware sensors. With the rapid development of the deep learning model, many methods have been utilized to address NILM problems and have achieved enhanced appliance identification performance. However, supervised learning models require a substantial volume of annotated data to function effectively, which is time-consuming, laborious, and difficult to implement in real scenarios. In this paper, we propose a novel semi-supervised learning method that combines consistency regularization and pseudo-labels to help identification of appliances with limited labeled data and an abundance of unlabeled data. In addition, given the different learning difficulties of various appliance categories, for example, feature learning is more difficult for multi-state appliances than two-state appliances, the thresholds employed for different appliances are adjusted in a flexible way at each time step so that the informative unlabeled data and their pseudo-labels can be delivered. Experiments have been conducted on publicly available datasets, and the results indicate that the proposed method attains superior appliance identification performance compared to cutting-edge methods.

Bilateral facial palsy with paresthesia (FDP) is a rare variant of GBS, characterized by simultaneous bilateral facial palsy and paresthesia of the distal limbs. Mounting evidence indicates that the presence of anti-GT1a IgG has a pathogenic role as an effector molecule in the development of cranial nerve palsies in certain patients with GBS, whereas anti-GT1a antibody is rarely presented positive in FDP. Here, we report the case of a 33-year-old male diagnosed with FDP presented with acute onset of bilateral facial palsy and slight paresthesias at the feet as the only neurological manifestation. An antecedent infection with no identifiable reason for the fever or skin eruptions was noted in the patient. He also exhibited cerebrospinal fluid albuminocytologic dissociation and abnormal nerve conduction studies. Notably, the testing of specific serum anti-gangliosides showed positive anti-GT1a IgG/IgM Ab. The patient responded well to intravenous immunoglobulin therapy. This case brings awareness to a rare variant of GBS, and provides the first indication that anti-GT1a antibodies play a causative role in the development of FDP. The case also suggests that prompt management with IVIG should be implemented if FDP is diagnosed.

Abstract Introduction Currently, the cause of psoriatic arthritis (PsA) is unknown, and the effectiveness of current drug treatments is unsatisfactory. In March 2019, the US Food and Drug Administration (FDA) approved risankizumab, a humanized immunoglobulin G1 (IgG1) monoclonal antibody targeting the p19 subunit of interleukin (IL)-23, for the treatment of PsA in adults. This study aimed to conduct a meta-analysis of double-blind, randomized, placebo-controlled trials to evaluate the effectiveness and safety of risankizumab in moderate-to-severe PsA. Methods We conducted a thorough search of relevant databases from the establishment of the databases to October 1, 2023. We conducted a meta-analysis using Stata 12.0 and utilized I 2 and Egger tests to assess heterogeneity and publication bias among the studies. Bias assessment was performed using the risk bias map and bias risk summary diagram generated by Revman5.4 software. The review protocols were registered on PROSPERO (CRD42023451894) and adhered to the preferred reporting item of system evaluation (PRISMA) guideline. Results Six randomized controlled trials (RCTs) involving 5038 patients with PsA treated with either risankizumab or placebo were included in the analysis. At 24 weeks, the risankizumab group demonstrated a significantly higher American College of Rheumatology-20 (ACR20) response rate compared to the placebo group (RR 1.760, 95% CI 1.568–1.977, P

This study aimed to investigate the impact of different pickling methods on the water retention and protein structure of salted goose raw material. Five pickling methods, namely conventional curing, vacuum tumbling curing, ultrasound curing, ultrasound combined with tumbling curing, and salt and tumbling curing, were employed, with a curing duration of 2 hours. The cured goose meat samples were analyzed for cooking loss, centrifugal loss, microstructure, as well as the carbonyl content, surface hydrophobicity, total sulfhydryl content, and sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) of the myofibrillar proteins. The results indicated that the ultrasound combined with tumbling curing method exhibited superior water-holding capacity, resulting in significant enhancement of the tenderness of goose meat. Additionally, this curing method caused the most notable damage to the microstructure of muscle fibers. The myofibrillar proteins in the ultrasound combined with tumbling cured goose meat exhibited lower surface hydrophobicity (5.17 μg) and carbonyl content (0.92 nmol/mg) compared to the vacuum tumbling, salt and tumbling, and ultrasound curing groups. Conversely, the total sulfhydryl content was highest (87.9 nmol/mg), indicating lower protein oxidation levels. SDS-PAGE analysis revealed prominent diffusion of protein bands at the 43 kDa position and denser bands between 26 and 43 kDa for the ultrasound combined with tumbling cured samples, indicating protein degradation. In conclusion, ultrasound combined with tumbling curing represents the optimum curing method.

Abstract Background With the rapid development of China’s chemical industry, although researchers have developed many methods in the field of chemical safety, the situation of chemical safety in China is still not optimistic. How to prevent accidents has always been the focus of scholars’ attention. Methods Based on the characteristics of chemical enterprises and the Heinrich accident triangle, this paper developed the organizational-level accident triangle, which divides accidents into group-level, unit-level, and workshop-level accidents. Based on 484 accident records of a large chemical enterprise in China, the Spearman correlation coefficient was used to analyze the rationality of accident classification and the occurrence rules of accidents at different levels. In addition, this paper used TF-IDF and K-means algorithms to extract keywords and perform text clustering analysis for accidents at different levels based on accident classification. The risk factors of each accident cluster were further analyzed, and improvement measures were proposed for the sample enterprises. Results The results show that reducing unit-level accidents can prevent group-level accidents. The accidents of the sample enterprises are mainly personal injury accidents, production accidents, environmental pollution accidents, and quality accidents. The leading causes of personal injury accidents are employees’ unsafe behaviors, such as poor safety awareness, non-standard operation, illegal operation, untimely communication, etc. The leading causes of production accidents, environmental pollution accidents, and quality accidents include the unsafe state of materials, such as equipment damage, pipeline leakage, short-circuiting, excessive fluctuation of process parameters, etc. Conclusion Compared with the traditional accident classification method, the accident triangle proposed in this paper based on the organizational level dramatically reduces the differences between accidents, helps enterprises quickly identify risk factors, and prevents accidents. This method can effectively prevent accidents and provide helpful guidance for the safety management of chemical enterprises.

Abstract Cancer immunotherapy has emerged as a promising strategy in the treatment of colorectal cancer, and relapse after tumor immunotherapy has attracted increasing attention. Cancer stem cells (CSCs), a small subset of tumor cells with self-renewal and differentiation capacities, are resistant to traditional therapies such as radiotherapy and chemotherapy. Recently, CSCs have been proven to be the cells driving tumor relapse after immunotherapy. However, the mutual interactions between CSCs and cancer niche immune cells are largely uncharacterized. In this review, we focus on colorectal CSCs, CSC-immune cell interactions and CSC-based immunotherapy. Colorectal CSCs are characterized by robust expression of surface markers such as CD44, CD133 and Lgr5; hyperactivation of stemness-related signaling pathways, such as the Wnt/β-catenin, Hippo/Yap1, Jak/Stat and Notch pathways; and disordered epigenetic modifications, including DNA methylation, histone modification, chromatin remodeling, and noncoding RNA action. Moreover, colorectal CSCs express abnormal levels of immune-related genes such as MHC and immune checkpoint molecules and mutually interact with cancer niche cells in multiple tumorigenesis-related processes, including tumor initiation, maintenance, metastasis and drug resistance. To date, many therapies targeting CSCs have been evaluated, including monoclonal antibodies, antibody‒drug conjugates, bispecific antibodies, tumor vaccines adoptive cell therapy, and small molecule inhibitors. With the development of CSC-/niche-targeting technology, as well as the integration of multidisciplinary studies, novel therapies that eliminate CSCs and reverse their immunosuppressive microenvironment are expected to be developed for the treatment of solid tumors, including colorectal cancer.

Background: Osteoarthritis (OA) is the most common joint disease worldwide, but its cause remains unclear. Oestrogen protects against OA, but its clinical use is limited. G protein-coupled receptor 30 (GPR30) is a receptor that binds oestrogen, and GPR30 treatment has benefitted patients with some degenerative diseases. However, its effects on OA prevention and treatment remain unclear. Moreover, several studies have found that activation of estrogen receptors exerting anti-ferroptosis effects, which plays an important role in chondrocyte survival. Therefore, this study explored the general and ferroptosis-related effects and mechanisms of GPR30 in OA. Methods: Genome-wide RNA sequencing, western blotting, and immunohistochemistry were used to evaluate GPR30 expression and ferroptosis-related indicators in cartilage tissues from clinical patients. Next, we investigated the effects of G1 (a GPR30 receptor agonist) on the function and pathology of OA in an animal model. We also treated chondrocytes with erastin (ferroptosis agonist) plus G1, G15 (GPR30 receptor antagonist), GPR30 short hairpin RNA, or ferrostatin-1 (ferroptosis inhibitor), then measured cell viability and ferroptosis-related indices and performed proteomics analyses. Finally, western blotting and reverse transcription-polymerase chain reaction were used to assess the effects of G1 on yes-associated protein 1 (YAP1) and ferritin heavy chain 1 (FTH1) expression. Results: GPR30 expression was lower in the OA cartilage tissues than in the normal tissues, and G1 treatment significantly improved the locomotor ability of mice. Moreover, chondrocyte cell viability significantly decreased after erastin treatment, but G1 treatment concentration-dependently mitigated this effect. Furthermore, G1 treatment decreased phosphorylated YAP1 expression, increased activated YAP1 expression, and increased FTH1 transcription and protein expression, protecting against ferroptosis. Conclusion: GPR30 activation inhibited ferroptosis in chondrocytes by suppressing YAP1 phosphorylation, which regulates FTH1 expression.The Translational Potential of this Article: These results provide a novel potential target for therapeutic OA interventions.

Objective To evaluate if a machine learning approach can accurately predict antidepressant treatment outcome using electronic health records (EHRs) from patients with depression. Method This study examined 808 patients with depression at a New York City‐based outpatient mental health clinic between June 13, 2016 and June 22, 2020. Antidepressant treatment outcome was defined based on trend in depression symptom severity over time and was categorized as either “Recovering” or “Worsening” (i.e., non‐Recovering), measured by the slope of individual‐level Patient Health Questionnaire‐9 (PHQ‐9) score trajectory spanning 6 months following treatment initiation. A patient was designated as “Recovering” if the slope is less than 0 and as “Worsening” if the slope was no less than 0. Multiple machine learning (ML) models including L2 norm regularized Logistic Regression, Naive Bayes, Random Forest, and Gradient Boosting Decision Tree (GBDT) were used to predict treatment outcome based on additional data from EHRs, including demographics and diagnoses. Shapley Additive Explanations were applied to identify the most important predictors. Results The GBDT achieved the best results of predicting “Recovering” (AUC: 0.7654 ± 0.0227; precision: 0.6002 ± 0.0215; recall: 0.5131 ± 0.0336). When excluding patients with low PHQ‐9 scores (

Abstract Background Chemokine‐like factor 1 (CKLF1) may be involved in the inflammatory response and secondary brain injury after severe traumatic brain injury (sTBI). We determined serum CKLF1 levels of sTBI patients to further investigate the correlation of CKLF1 levels with disease severity, functional prognosis, and 180‐day mortality of sTBI. Methods Serum CKLF1 levels were measured at admission in 119 sTBI patients and at entry into study in 119 healthy controls. Serum CKLF levels of 50 patients were also quantified at days 1–3, 5, and 7 after admission. Glasgow coma scale (GCS) scores and Rotterdam computerized tomography (CT) classification were utilized to assess disease severity. Extended Glasgow outcome scale (GOSE) scores were recorded to evaluate function prognosis at 180 days after sTBI. Relations of serum CKLF1 levels to 180‐day poor prognosis (GOSE scores of 1–4) and 180‐day mortality were analyzed using univariate analysis, followed by multivariate analysis. Receiver‐operating characteristic (ROC) curve was built to investigate prognostic predictive capability. Results Serum CKLF1 levels of sTBI patients increased at admission, peaked at day 2, and then gradually decreased; they were significantly higher during the 7 days after sTBI than in healthy controls. Differences of areas under ROC curve (areas under the curve [AUCs]) were not significant among the six time points. Multivariate analysis showed that serum CKLF1 levels were independently correlated with GCS scores, Rotterdam CT classification, and GOSE scores. Serum CKLF1 levels were significantly higher in non‐survivors than in survivors and in poor prognosis patients than in good prognosis patients. Serum CKLF1 levels independently predicted 180‐day poor prognosis and 180‐day mortality, and had high 180‐day prognosis and mortality predictive abilities, and their AUCs were similar to those of GCS scores and Rotterdam CT classification. Combination model containing serum CKLF1, GCS scores, and Rotterdam CT classification performed more efficiently than any of them alone in predicting mortality and poor prognosis. The models were visually described using nomograms, which were comparatively stable under calibration curve and were relatively of clinical benefit under decision curve. Conclusion Serum CKLF1 levels are significantly associated with disease severity, poor 180‐day prognosis, and 180‐day mortality in sTBI patients. Hence, complement CKLF1 may serve as a potential prognostic biomarker of sTBI.

Abstract The impact of external factors on the human gut microbiota and how gut microbes contribute to human health is an intriguing question. Here, the gut microbiome of 3,224 individuals (496 with serum metabolome) with 109 variables is studied. Multiple analyses reveal that geographic factors explain the greatest variance of the gut microbiome and the similarity of individuals’ gut microbiome is negatively correlated with their geographic distance. Main food components are the most important factors that mediate the impact of host habitats on the gut microbiome. Diet and gut microbes collaboratively contribute to the variation of serum metabolites, and correlate to the increase or decrease of certain clinical indexes. Specifically, systolic blood pressure is lowered by vegetable oil through increasing the abundance of Blautia and reducing the serum level of 1‐palmitoyl‐2‐palmitoleoyl‐GPC (16:0/16:1), but it is reduced by fruit intake through increasing the serum level of Blautia improved threonate. Besides, aging‐related clinical indexes are also closely correlated with the variation of gut microbes and serum metabolites. In this study, the linkages of geographic locations, diet, the gut microbiome, serum metabolites, and physiological indexes in a Chinese population are characterized. It is proved again that gut microbes and their metabolites are important media for external factors to affect human health.

Nickel is deemed as one of the critical metals because it is currently essential in making both stainless steel and lithium-ion batteries. It is therefore critical to evaluate such impacts so that appropriate mitigation measures can be taken. Emergy is an effective evaluation method, which is widely used for environmental accounting. This study applies such an emergy-based method to evaluate nickel production in China so that the holistic environmental performance of nickel production can be examined. Typical products are chosen for different processes by considering both quantity and the development potential. Results show that nickel production is unsustainable and the associated environmental costs are not fully covered in the nickel prices. In addition, we find that environmental loading from nickel recycling is less than that from primary nickel production. Several policy recommendations are then raised based upon these results to facilitate sustainable nickel management in China.

Blunting the tumor's stress-sensing ability is an effective strategy for controlling tumor adaptive survival and metastasis. Here, we have designed a cyclically amplified nano-energy interference device based on lipid nanoparticles (LNP), focused on altering cellular energy metabolism. This innovative nano device efficiently targets and monitors the tumor's status while simultaneously inhibiting mitochondrial respiration, biogenesis and ribosome production. To this end, we first identified azelaic acid (AA), a binary acid capable of disrupting the mitochondrial respiratory chain. Upon encapsulation in LNP and linkage to mitochondrial-targeting molecules, this disruptive effect is further augmented. Consequently, tumors exhibit a substantial upregulation of the glycolytic pathway, intensifying their glucose demand and worsening the tumor's energy-deprived microenvironment. Then, the glucose analog, 2-Deoxy-D-glucose (2-DG), linked to the LNP, efficiently targets tumors and competitively inhibits the tumor's normal glucose uptake. The synergetic results of combining AA with 2-DG induce comprehensive energy deficiency within tumors, blocking the generation of energy-sensitive ribosomes. Ultimately, the disruption of both mitochondria and ribosomes depletes energy supply and new protein-generating capacity, weakening tumor's ability to adapt to environmental stress and thereby inhibiting growth and metastasis. Comprehensively, this nano-energy interference device, by controlling the tumor's stress-sensing ability, provides a novel therapeutic strategy for refractory tumors.

BackgroundDiabetic kidney disease (DKD) had been proposed as a contributor in the pathogenesis of coronary artery disease (CAD). However, the relationship of DKD and the long-term adverse outcomes in patients with CAD after percutaneous coronary intervention (PCI) was still undiscovered.MethodsApproximately 892 patients with CAD enrolled from January 2012 to December 2016. The patients were divided into two groups, the DKD group (n = 341) and the None DKD group (n = 551). The primary outcome was major adverse cardiac events (MACE) after PCI. The average follow-up time was 1,897 ± 1,276 days.ResultsBaseline data showed that some factors were significantly different between the two groups, including age, body mass index, gender (female), hypertension, smoking, stroke history, heart failure, duration of diabetic mellitus (DM), low-density lipoprotein cholesterol, urinary protein/creatinine ratio, serum creatinine, hemoglobin, platelet, antiplatelet, beta blocker, statin, antihypertensive drugs, and insulin (all p

Background: Whether and to what extent the impact of exposure to various polychlorinated biphenyls (PCBs) congeners on diabetes, as well as the important contributors, have remained unclear. Objective: We aimed to investigate the association patterns between PCBs mixture and diabetes, identify the critical congeners, and explore the potential modifiers. Methods: The present study included 5900 U.S. adults from the National Health and Nutrition Examination Survey (NHANES) conducted between 2007 and 2016. Weighted logistic regression, restricted cubic spline regression, weighted quantile sum (WQS) regression and Bayesian kernel machine regression (BKMR) were applied to estimate the linear and non-linear associations of single and mixed PCB exposure with diabetes. Subgroup analyses were also conducted to explore potential sex differences. Results: In the weighted logistic regression model, total PCBs were positively associated with diabetes (OR = 1.33, P < 0.025), and significant non-linear associations were observed using RCS analyses. The non-linear positive association between PCBs mixed exposure and diabetes was likewise found in the WQS and BKMR results. PCB180, PCB194, PCB196, and PCB167 were with the highest weights in the WQS, and PCB209 and PCB66 were with the highest posterior inclusion probabilities in the BKMR. Additionally, exposure to total PCBs and most of individual PCB congeners were significantly associated with elevated risk of in females (OR = 1.74; P for trend < 0.001), while fewer significant associations were observed in males. Conclusion: The present study highlighted the importance of the long-term surveillance of PCBs and the need to enhance protective measures against them. Notably, these associations were non-linear, congener-specific, and significantly stronger in females than males, especially at relatively high levels of PCBs exposure. Further prospective and mechanistic studies were warranted to ascertain the causal effects between PCBs mixture and diabetes.

The paper discusses the progress and commercialization of binders for energy storage applications, such as batteries. It explains the role of binders in holding together active materials and current collectors, and highlights the challenges associated with conventional organic solvents in binders. The potential of aqueous binders is introduced as a cost-effective and environmentally friendly alternative. The advantages and limitations of different types of binders are discussed, and the importance of binder selection for optimal battery performance is emphasized. The current state of commercialization of binders is reviewed, and the need for collaboration between researchers, manufacturers, and policymakers to develop and promote environmentally friendly and cost-effective binders is emphasized. The paper concludes by outlining future directions for research and development to further improve the performance and commercialization of binders, while addressing limitations such as lack of standardization, high cost, and long-term stability and reliability.

Abstract The Myodural Bridge (MDB) is a physiological structure that is highly conserved in mammals and many of other tetrapods. It connects the suboccipital muscles to the cervical spinal dura mater (SDM) and transmits the tensile forces generated by the suboccipital muscles to the SDM. Consequently, the MDB has broader physiological potentials than just fixing the SDM. It has been proposed that MDB significantly contributes to the dynamics of cerebrospinal fluid (CSF) movements. Animal models of suboccipital muscle atrophy and hyperplasia were established utilizing local injection of BTX-A and ACE-031. In contrast, animal models with surgical severance of suboccipital muscles, and without any surgical operation were set as two types of negative control groups. CSF secretion and reabsorption rates were then measured for subsequent analysis. Our findings demonstrated a significant increase in CSF secretion rate in rats with the hyperplasia model, while there was a significant decrease in rats with the atrophy and severance groups. We observed an increase in CSF reabsorption rate in both the atrophy and hyperplasia groups, but no significant change was observed in the severance group. Additionally, our immunohistochemistry results revealed no significant change in the protein level of six selected choroid plexus-CSF-related proteins among all these groups. Therefore, it was indicated that alteration of MDB-transmitted tensile force resulted in changes of CSF secretion and reabsorption rates, suggesting the potential role that MDB may play during CSF circulation. This provides a unique research insight into CSF dynamics.

Abstract Background The early life stage is critical for the gut microbiota establishment and development. We aimed to investigate the lifelong impact of famine exposure during early life on the adult gut microbial ecosystem and examine the association of famine-induced disturbance in gut microbiota with type 2 diabetes. Methods We profiled the gut microbial composition among 11,513 adults (18–97 years) from three independent cohorts and examined the association of famine exposure during early life with alterations of adult gut microbial diversity and composition. We performed co-abundance network analyses to identify keystone taxa in the three cohorts and constructed an index with the shared keystone taxa across the three cohorts. Among each cohort, we used linear regression to examine the association of famine exposure during early life with the keystone taxa index and assessed the correlation between the keystone taxa index and type 2 diabetes using logistic regression adjusted for potential confounders. We combined the effect estimates from the three cohorts using random-effects meta-analysis. Results Compared with the no-exposed control group (born during 1962–1964), participants who were exposed to the famine during the first 1000 days of life (born in 1959) had consistently lower gut microbial alpha diversity and alterations in the gut microbial community during adulthood across the three cohorts. Compared with the no-exposed control group, participants who were exposed to famine during the first 1000 days of life were associated with consistently lower levels of keystone taxa index in the three cohorts (pooled beta − 0.29, 95% CI − 0.43, − 0.15). Per 1-standard deviation increment in the keystone taxa index was associated with a 13% lower risk of type 2 diabetes (pooled odds ratio 0.87, 95% CI 0.80, 0.93), with consistent results across three individual cohorts. Conclusions These findings reveal a potential role of the gut microbiota in the developmental origins of health and disease (DOHaD) hypothesis, deepening our understanding about the etiology of type 2 diabetes.

Abstract To establish a nomogram for elderly patients with diffuse large B‐cell lymphoma (DLBCL) based on nutritional and imaging features. The data of 221 elderly pretreatment DLBCL patients were retrospectively analyzed. All cases were randomly separated into the training group and validation group. A nomogram was built based on the results of multivariate analysis. A nomogram was established based on maximum standardized uptake value (SUVmax), geriatric nutritional risk index (GNRI), and lactate dehydrogenase. The concordance index (C‐index) of the nomogram was 0.772 for the training group and 0.729 for the validation group, and similar results were found in the area under the curve (AUC). The calibration curve showed favorable consistency between prediction and real survival. The decision curve analysis (DCA) also showed that the nomogram had favorable clinical effectiveness. The new risk‐stratification model divided patients into three groups with obvious survival. The C‐index and AUCs for the new model were greater than those of IPI and NCCN‐IPI. The DCA curve suggested that the new model had better clinical effectiveness than the IPI and NCCN‐IPI. The nomogram prognostic model based on SUVmax and GNRI performed superior to NCCN‐IPI and equal to IPI for risk stratification of elderly DLBCL patients.

An air-sea interaction field campaign was conducted in September of 2017 within the warm and cold eddy region of the western Northwest Pacific (WNP) (17.5˚-20.5˚N, 127.5˚E-133.5˚E). Both near-surface oceanic and atmospheric conditions in addition to ocean heat content (OHC) were examined to better understand the mechanisms governing high heat flux magnitudes responsible for rapidly intensifying tropical cyclones. Observations from this experiment indicate that the latent heat flux (LHF) under modest wind conditions reached 400 W m-2 within the vicinity of a warm eddy, with OHC higher than 100 kJ cm-2 of warm eddy region being 2~3 times as large as that of cold eddy region. These high OHC and a resultant high LHF in the warm eddy, comparable to the magnitude of LHF in the North Equatorial Current, may explain the mechanism of why tropical cyclones over a warm eddy in eddy-rich zones often rapidly intensify in the WNP. A month later typhoon Lan rapidly intensified into a super typhoon, while passing over the boundary region of warm and cold eddies during the observation period. Results from this study illustrate that both the wind-normalized LHF and the difference (Qs-Qa) between the specific humidity at air (Qa) and at the sea surface (Qs), closely correlate with OHC patterns, which suggests that the ocean looks likely to control the spatial pattern of LHF. Overall, both the ocean and weather conditions govern the pattern of specific humidity difference between the air-sea interface, with large OHC over the warm eddy controlling higher Qs and the pattern of Qa depending on the pattern of wind direction. Qa as a factor impacting LHF magnitude is strongly linked to wind direction in the experimental area, that is, the drier northwesterly flow and southeasterly moist wind, resulting in the enhanced contrast of specific humidity at cold eddy region.

Abstract Three‐dimensional (3D) printing has the potential to revolutionize the way energy storage devices are designed and manufactured. In this paper, we explore the use of 3D printing in the design and production of energy storage devices, especially zinc‐ion batteries (ZIBs) and examine its potential advantages over traditional manufacturing methods. 3D printing could significantly improve the customization of ZIBs, making it a promising strategy for the future of energy storage. In particular, 3D printing allows for the creation of complex, customized geometries, and designs that can optimize the energy density, power density, and overall performance of batteries. Simultaneously, we discuss and compare the impact of 3D printing design strategies based on different configurations of film, interdigitation, and framework on energy storage devices with a focus on ZIBs. Additionally, 3D printing enables the rapid prototyping and production of batteries, reducing leading times and costs compared with traditional manufacturing methods. However, there are also challenges and limitations to consider, such as the need for further development of suitable 3D printing materials and processes for energy storage applications.

Abdominal aortic aneurysm (AAA) is a severe cardiovascular disease with a high mortality rate. Several screening and diagnostic methods have been developed for AAA early diagnosis. Open surgery and endovascular aortic repair (EVAR) are clinically available for patients who meet the indications for surgery. However, for non-surgical patients, limited drugs exist to inhibit or reverse the progression of aneurysms due to the complex pathogenesis and biological structure of AAA, failing to accumulate precisely on the lesion to achieve sufficient concentrations. The recently developed nanotechnology offers a new strategy to address this problem by developing drug-carrying nanoparticles with enhanced water solubility and targeting capacity, prolonged duration, and reduced side effects. Despite the rising popularity, limited literature is available to highlight the progression of the field. Herein, in this review, we first discuss the pathogenesis of AAA, the methods of diagnosis and treatment that have been applied clinically, followed by the review of research progressions of constructing different drug-loaded nanoparticles for AAA treatment using engineered nanoparticles. In addition, the feasibility of extracellular vesicles (EVs) and EVs-based nanotechnology for AAA treatment in recent years are highlighted, together with the future perspective. We hope this review will provide a clear picture for the scientists and clinicians to find a new solution for AAA clinical management.

ABSTRACTVaccination plays a key role in preventing morbidity and mortality caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We aimed to evaluate the safety and immunogenicity of a SARS-CoV-2 messenger ribonucleic acid (mRNA) vaccine SYS6006. In the two randomized, observer-blinded, placebo-controlled phase 1 trials, 40 adult participants aged 18–59 years and 40 elderly participants aged 60 years or more were randomized to receive two doses of SYS6006 or placebo (saline). Adverse events (AEs) were collected through 30 days post the second vaccination. Immunogenicity was assessed by live-virus neutralizing antibody (Nab), spike protein (S1) binding antibody (S1-IgG), and cellular immunity. The result showed that 7/15, 9/15 and 4/10 adult participants, and 9/15, 8/15 and 4/10 elderly participants reported at least one AE in the 20-µg, 30-µg and placebo groups, respectively. Most AEs were grade 1. Injection-site pain was the most common AE. Two adults and one elder reported fever. No vaccination-related serious AE was reported. SYS6006 elicited wild-type Nab response with a peak geometric mean titer of 232.1 and 130.6 (adults), and 48.7 and 66.7 (elders), in the 20-µg and 30-µg groups, respectively. SYS6006 induced moderate-to-robust Nab response against Delta, and slight Nab response against Omicron BA.2 and BA.5. Robust IgG response against wild type and BA.2 was observed. Cellular immune response was induced. In conclusion, two-dose primary vaccination with SYS6006 demonstrated good safety and immunogenicity during a follow-up period of 51 days in immunologically naive population aged 18 years or more. (Trial registry: Chictr.org.cn ChiCTR2200059103 and ChiCTR2200059104)

Hepatocellular carcinoma (HCC) is a common malignant tumor of the digestive system with a low early diagnosis rate. Owing to the side effects, tolerance, and patient contraindications of existing therapies, effective drug treatments for HCC remain a major clinical challenge. However, using approved or investigational drugs not initially intended for cancer therapy is a promising strategy for resolving this problem because their safety have been tested in clinic. Therefore, this study evaluated differentially expressed genes between liver cancer and normal tissues in a cohort of patients with HCC from The Cancer Genome Atlas and applied them to query a connectivity map to identify candidate anti-HCC drugs. As a result, fluphenazine was identified as a candidate for anti-HCC therapy in vitro and in vivo. Fluphenazine suppressed HCC cell proliferation and migration and induced cell cycle arrest and apoptosis, possibly owing to disrupted lysosomal function, blocking autophagy flux. Additionally, in vivo studies demonstrated that fluphenazine suppresses HCC subcutaneous xenografts growth without causing severe side effects. Strikingly, fluphenazine could be used as an analgesic to alleviate oxaliplatin-induced pain as well as pain related anxiety-like behavior. Therefore, fluphenazine could be a novel liver cancer treatment candidate.

CAR-T cell therapy, a novel therapeutic approach that has attracted much attention in the field of cancer treatment at present, has become the subject of many studies and has shown great potential in the treatment of hematological malignancies, such as leukemia and lymphoma. This study aims to analyze the characteristics of articles published on CAR-T cell therapy in the lymphoma field and explore the existing hotspots and frontiers. The relevant articles published from 2013 to 2022 were retrieved from the Web of Science Core Collection. CiteSpace, VOSviewer, Bibliometric online analysis platform, Microsoft Excel, and R software were used for bibliometric analysis and visualization. The number of publications related to the research has been increasing year by year, including 1023 articles and 760 reviews from 62 countries and regions, 2092 institutions, 1040 journals, and 8727 authors. The United States, China, and Germany are the main publishing countries in this research field. The top 10 institutions are all from the United States, the journal with the highest impact factor is BLOOD, the author with the most publications is Frederick L Locke, and the most influential author is Carl H June. The top three keywords are “Lymphoma,” “Immunotherapy,” and “Therapy.” “Maude (2014)” is the most cited and strongest burstiness reference over the past decade. This study provides a comprehensive bibliometric analysis of CAR-T cell therapy in lymphoma, which can help researchers understand the current research hotspots in this field, explore potential research directions, and identify future development trends.

Summary: Biomedical knowledge graphs (BKGs) provide a new paradigm for managing abundant biomedical knowledge efficiently. Today’s artificial intelligence techniques enable mining BKGs to discover new knowledge. Here, we present a protocol for implementing a computational pipeline for biomedical knowledge discovery (BKD) based on a BKG. We describe steps of the pipeline including data processing, implementing BKD based on knowledge graph embeddings, and prediction result interpretation. We detail how our pipeline can be used for drug repurposing hypothesis generation for Parkinson’s disease.For complete details on the use and execution of this protocol, please refer to Su et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

No proprietary starter cultures for crafting Chinese bacon. This study aimed to isolate Coagulase-negative Staphylococci (CNS) from Chinese bacon, identify their species, and evaluate their ability to produce biogenic amines (BAs), peptides, free amino acids (FAAs), and degrade proteins. Twenty-one isolates were deficient in hemolysis, DNase, and coagulase activities, and exhibited low amino acid decarboxylase activity. Further characterization revealed 11 CNS species showing protease, lipase, or nitrate reductase activities. Specifically, S. cohnii WX-M8 was able to degrade both sarcoplasmic and myofibrillar proteins, while S. saprophyticus MY-A10 was found to only degrade myofibrillar proteins. Both were able to reduce the BAs and increase the content of peptides around day 3. The meat fermented by these two CNS contained FAAs that are more conducive to taste formation, such as Glu and Asp, and reduced the content of bitter FAAs. These findings will provide insights into the use of CNS for Chinese bacon.

AbstractObjective This study aimed to compare the efficacy and safety of focused ultrasound (FU) at different focal depths in treating vulvar lichen sclerosus (VLS).Methods A retrospective study was conducted on 84 patients with VLS. Among them, 43 cases were treated with FU at a focal depth of 2.5 mm and 41 cases at a focal depth of 4.0 mm. Therapeutic time, treatment energy, postoperative efficacy, complications and recurrence rates were compared.Results No statistically substantially differences in age, disease course, history of immune system diseases, lesion size and severity of symptoms were found between the two groups. All patients successfully received FU therapy. No significant difference in curative rate was observed between the two groups at 3, 6 and 12 months after FU therapy. At 12 months after FU therapy, the recurrence rate of the experimental group (FU treatment at 2.5 mm focal depth) was lower than the control group (FU treatment at 4.0 mm focal depth) (7.0% vs 24.4%, p = 0.027). The experimental group was treated for a shorter period of time [22.69 ± 0.64 (min) vs 24.93 ± 0.72(min), p = 0.022] and at a lower dose[5,026.05 ± 148.00(J) vs 5,484.26 ± 160.60(J) p = 0.039].Conclusion Compared with that at the routine focal depth (4.0 mm), FU therapy at a low treatment depth (2.5 mm) can achieve a similar therapeutic effect but lower recurrence rate, therapeutic time and treatment energy. This work provides insight into the optimization of clinical protocols.

AbstractObjective To use logistic regression to analyze the attributes underlying patients’ treatment options for low-grade squamous intraepithelial lesion (LSIL) complicated with high-risk human papillomavirus (HR-HPV) infection, and identify the best benefit group of different treatment options.Methods Clinical data of 197 LSIL patients with HR-HPV infection between June 2009 and February 2022 were collected. According to the treatment options chosen by the patients, they were divided into the interferon, photodynamic therapy, follow-up observation, and focused ultrasound (FUS) treatment groups. One-way analysis of variance (ANOVA) and multivariate logistic regression analysis were used to analyze the influencing factors, including age, occupation, education level, maternity history, reason for encounter, route of consultation, annual personal and household income, screening for related risk factors, and identifying the best benefit group of different treatment options.Results One-way ANOVA revealed a statistically significant difference in age, education level, maternity history, reason for encounter, and annual household income (p

Abstract The advancement of single cell RNA-sequencing (scRNA-seq) technology has enabled the direct inference of co-expressions in specific cell types, facilitating our understanding of cell-type-specific biological functions. For this task, the high sequencing depth variations and measurement errors in scRNA-seq data present two significant challenges, and they have not been adequately addressed by existing methods. We propose a statistical approach, CS-CORE, for estimating and testing cell-type-specific co-expressions, that explicitly models sequencing depth variations and measurement errors in scRNA-seq data. Systematic evaluations show that most existing methods suffered from inflated false positives as well as biased co-expression estimates and clustering analysis, whereas CS-CORE gave accurate estimates in these experiments. When applied to scRNA-seq data from postmortem brain samples from Alzheimer’s disease patients/controls and blood samples from COVID-19 patients/controls, CS-CORE identified cell-type-specific co-expressions and differential co-expressions that were more reproducible and/or more enriched for relevant biological pathways than those inferred from existing methods.

Abstract Candida albicans is a benign member of gut microbiota, but also causes life-threatening disseminated infections, suggesting that this fungus commensalism has evolved with retention of virulence traits. Here we reveal that N-acetylglucosamine (GlcNAc) enables C. albicans to balance between commensalism and pathogenesis. Although GlcNAc catabolism is beneficial for commensal growth of C. albicans, deleting GlcNAc sensor-transducer Ngs1 confers enhanced fitness, indicating that GlcNAc signaling is detrimental to commensalism. Interestingly, addition of GlcNAc attenuates commensal fitness of gut-evolved C. albicans but retains its disease-causing potential. We further demonstrate that GlcNAc is a major inducer of hypha-associated transcription in the gut, which represents the key determinant for commensal-pathogenic equilibrium. In addition to yeast-to-hypha morphogenesis, we also identify other factors, including Sod5 and Ofi1, that contribute to the balance. Thus, C. albicans uses GlcNAc to build up a tradeoff between fungal programs supporting commensalism and virulence, which may explain its success as a commensal and pathogen.

Background: Petrochemical products are flammable, explosive, and toxic, petrochemical accidents are generally extremely destructive. Therefore, disaster analysis and prediction and real-time simulation have become important means to control and reduce accident hazards. Methods: In this study, a complete real-time simulation solution of gas diffusion with coordinate data and concentration data is proposed, which is mainly aimed at the simulation of the types of harmful gas leakage and diffusion accidents in the petrochemical industry. The rendering effect is more continuous and accurate through grid homogenization and trilinear interpolation. A data processing and rendering parallelization process is presented to improve simulation efficiency. Combines gas concentration and fragment transparency to synthesize transparent pixels in a scene. To ensure the approximate accuracy of the rendering effect, improve the efficiency of real-time rendering, and meet the requirement of intuitive perception using concentration data, a weighted blended order-independent transparency with enhanced alpha weight is presented, which can provide a more intuitive perception of hierarchical information of concentration data while preserving depth information. In this study, three order-independent transparency algorithms, depth peeling algorithm, weighted blended order-independent transparency and weighted blended order-independent transparency with enhanced alpha weight, are compared and analyzed for rendering image quality, rendering time, required memory, hierarchical information and so on. Results: Using weighted blended order-independent transparency with enhanced alpha weight technique, the rendering time is shortened by 53.2% compared with the depth peeling algorithm, and the texture memory required is much smaller than the depth peeling algorithm. The rendering results of weighted blended order-independent transparency with enhanced alpha weight are approximately accurate compared with the depth peeling algorithm as ground truth, and there is no popping when surfaces pass through one another. At the same time, compared with weighted blended order-independent transparency, weighted blended OIT with enhanced alpha weight achieves an intuitive perception of hierarchical information of concentration data.

AIM: To compare the efficacy of 25-gauge(25G)vitrectomy combined with intraocular lens transciliary sulcus scleral suture fixation and sutureless scleral tunnel interlamellar fixation in the treatment of complete lens dislocation.METHODS: Retrospective case-control study. A total of 40 patients(40 eyes)diagnosed with complete lens luxation in the vitreous cavity in our hospital from May 2015 to September 2021 were selected, among which 21 eyes(suture group)underwent 25G vitrectomy combined with intraocular lens fixation via ciliary sulci scleral suture, and 19 eyes(sutureless group)underwent 25G vitrectomy combined with interlamellar scleral tunnel fixation of intraocular lens. The patients in both groups were followed up until 3mo after surgery to observe the operative time, best corrected visual acuity(BCVA), corneal endothelial cell count(CECC), central corneal thickness(CCT)and postoperative complications.RESULTS: The operation time was significantly shorter in the sutureless group than in the suture group(31.79±6.01min vs. 45.38±8.04min, P0.05).CONCLUSION: 25G vitrectomy combined with intraocular lens sutureless scleral tunnel interlamellar fixation in the treatment of complete lens luxation has shorter operation time, faster postoperative visual acuity improvement and fewer postoperative complications.

Phospholipase D (PLD) is an essential biocatalyst for the biological production of phosphatidylserine and phospholipid modification. However, the efficient heterologous expression of PLD is limited by its cell toxicity. In this study, a PLD was secretory expressed efficiently in Bacillus subtilis with an activity around 100 U/mL. A secretory expression system containing the signal peptide SPEstA and the dual-promoter PHpaII-SrfA was established, and the extracellular PLD activity further reached 119.22 U/mL through scale-up fermentation, 191.30-fold higher than that of the control. Under optimum reaction conditions, a 61.61% conversion ratio and 21.07 g/L of phosphatidylserine production were achieved. Finally, the synthesis system of PL derivates was established, which could efficiently synthesis novel PL derivates. The results highlight that the secretory expression system constructed in this study provides a promising PLD producing strain in industrial application, and laid the foundation for the biosynthesis of phosphatidylserine and other PL derivates. As far as we know, this work reports the highest level of extracellular PLD expression to date and the enzymatic production of several PL derivates for the first time.

Mine fire accidents frequently constitute a major threat to mining safety, and their potential consequences are extremely severe, which highlights the urgency of fire prevention and control research. In this study, the CiteSpace software was used to conduct a metrological analysis of 717 relevant studies in the field of mine fire prevention and control (MFPC), aiming to reveal the research trends and trends in this field. This analysis found that the annual number of MFPC articles showed a significant upward trend, indicating that it is in rapid development during the active period. China, the United States, and Australia are the main contributors in this field, and the institutional contribution of China University of Mining and Technology is particularly outstanding, reflecting the regional concentration of research activities. The analysis of cooperation networks reveals the close cross-regional collaboration among European countries. The inhibition effect and evaluation criteria and the inhibition technology under different coal characteristics have become the focus of research. Activation energy, release, and quantum chemistry have become recent hot spots, reflecting the research on the mechanism of forward physicochemical synergistic inhibition and the in-depth exploration of the molecular level. It indicates that future research will focus on the development of temperature-responsive retardant materials, the application of quantum chemistry theory, and the exploration of the microscopic mechanism of coal spontaneous combustion through molecular simulation technology to further optimize the fire prevention strategy. In summary, the findings of this study not only provide a comprehensive picture of current research activities in the MFPC field but also indicate potential directions for future research and have important guiding significance for promoting the development of this field.

Nowadays, the demand for more personalized healthy food recipes is increasing over time, but traditional personalized recipe recommendation systems often tend to overlook the differences that exist in different users’ health conditions. This paper aims to address the issue by proposing an innovative personalized health recipe recommendation framework. This framework is based on different health needs, aiming to address users with different health conditions. More explicitly, the hybrid recommendation algorithm based on facial health recognition is designed to recommend the most suitable recipes for the user by taking into account the user’s health status and preferences. In addition, the fitness factor will adjust the recommendation results to best meet the user’s taste preferences and health goals. Experimental results and user research results show that the recommendation results of this framework are more accurate compared to existing systems, and therefore, users are more satisfied.

Ensuring safety is crucial for promoting the sustainable growth of the construction industry. Assessing safety efficiency is of significant importance for optimizing safety management processes and improving the safety environment. However, the current mainstream methods for evaluating safety efficiency have limitations such as ignoring non-desired outputs and slack variables, the efficiency values being limited to the (0, 1) range, and a narrow perspective. To address these shortcomings, this study focuses on the characteristics of the construction industry and introduces the Super-SBM model and Malmquist index into the assessment of safety efficiency in the construction industry. The study analyzes the evolution characteristics of safety efficiency from both static and dynamic perspectives. Furthermore, using panel quantile regression models, the study identifies the factors influencing safety efficiency and analyzes their heterogeneity. Analyzing panel data from 30 provinces in China from 2015 to 2021, the results show that the overall safety efficiency of the construction industry in China is relatively low, with noticeable spatial clustering characteristics. Provinces in the eastern and central regions exhibit higher levels of construction safety efficiency. The Malmquist index demonstrates a declining trend, with technical efficiency being the primary factor limiting the improvement of safety efficiency in construction. Factors such as per capita GDP, urbanization rate, committed contract amounts, and the number of professionals engaged in survey and design, as well as engineering supervision, have an impact on construction safety efficiency, and the effects of these variables vary across different quantile levels of safety efficiency. This research can assist decision-makers in gaining a better understanding of the safety conditions in different regions of the construction industry. It can also assist in developing customized policies to enhance the health and safety environment, thereby promoting the stable development of the construction industry.

BackgroundPhenolic compounds may adversely affect human health, but the current relevant studies are mostly limited to the impact of single phenolic compound exposure on human health, and there is still a lack of studies on the population-based association between combined exposure to multiple common phenolic compounds and dyslipidemia. ObjectiveTo explore the association of phenolic compound combined exposure and dyslipidemia based on principal component analysis-random forest (PCA-RF) strategy. MethodsThe data were from the National Health and Nutrition Examination Survey (2013–2016). A total of 1301 adult residents aged ≥ 20 years with complete information on demographics and lifestyle, urine phenol concentrations (bisphenol A, bisphenol F, bisphenol S, triclocarban, benzophenone, and triclosan), and serum concentrations of total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) were included in this study. The concentrations of six urinary phenolic compounds were determined by solid phase extraction coupled with high performance liquid chromatography and tandem mass spectrometry, and the lipid indicators were determined by enzymatic methods. Principal component analysis combined with random forest model was used for model construction. First, principal component analysis was performed on 18 original variables including 6 phenolic compounds and 12 basic characteristic indicators, and then random forest model was established with dyslipidemia and its four evaluation indicators as dependent variables and the extracted principal components as independent variables, respectively. ResultsThe PCA-RF analysis showed that bisphenol A, bisphenol F, and benzophenone may be important factors for dyslipidemia in the study subjects; bisphenol A, bisphenol F, and triclosan may be important factors for TC level in the study subjects; bisphenol A, bisphenol F, triclocarban, and benzophenone may be important factors for TG level in the study subjects; bisphenol A may be an important factor for LDL-C level in the study subjects; bisphenol F and benzophenone may be important factors for HDL-C level in the study subjects. ConclusionPhenolic compound exposure may be an important risk factor for the development of dyslipidemia. PCA-RF strategy can be effectively used to explore the association between phenolic compound exposure and dyslipidemia in the population.

Abstract Background Understanding nutritional status among women of childbearing age (WCA) is of increasing concern, as nutrient intakes may affect the health of WCA and well-being of their offspring. This study aimed to investigate secular trends of dietary energy and macronutrients intakes and access longitudinally the urban-rural and geographic disparities among Chinese WCA. Methods A total of 10,219 participants were involved in three rounds of the Chinese Health and Nutrition Survey (CHNS:1991, 2004, and 2015). Average macronutrients intakes were compared against the Chinese Dietary Reference Intakes Standard (DRIs) to better assess adequacy. Mixed effect models were used to estimate the secular trends of dietary intake. Results A total of 10,219 participants were involved. Dietary fat, the percentage of energy (%E) from fat, and the proportion with more than 30% of energy from fat and less than 50% from carbohydrates increased notably over time (p