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Potential blood biomarkers that can be used as prognosticators of spontaneous intracerebral hemorrhage: A systematic review and meta-analysis
Background Predicting nontraumatic spontaneous intracerebral hemorrhage (SICH) patient prognosis has been commonly practiced, particularly when providing informed consent and considering surgical treatment. Biomarkers might provide more real-time evaluation of SICH patients’ condition than clinical prognostic scoring systems. This study aimed to evaluate the reliability of blood biomarkers in predicting prognosis in SICH patients by systematic review and meta-analysis. Methods Studies that evaluated the association of blood biomarker(s) with mortality and/or functional outcome in SICH patients up to October 11, 2024, were identified through PubMed, Google Scholars, Scopus databases, and reference lists. Studies that satisfied the inclusion criteria were included in the meta-analyses. Good functional outcome was defined by patient’s Glasgow Outcome Scale (GOS) ≥ 4 or modified Rankin scale mRS ≤ 2. Blood biomarkers were classified into the following categories: angiogenic factors, growth factors, inflammatory biomarkers, coagulation parameters, blood counts, and others. Individual meta-analysis was performed for every evaluation endpoint:7 days, 30 days, 3 months, 6 months, and 1 year. Meta-analyses were performed using Random Effect Mean-Difference with a 95% Confidence Interval for continuous data and visualized as forest plots in RevMan version 5.3 software. Cochrane Tool to Assess Risk of Bias in Cohort Studies was used to assess potential risk of bias of the included studies. GRADE Profiler was used to assess quality of evidence. Results Seventy-seven studies fulfilled the inclusion criteria. Surviving SICH patients have significantly lower C-reactive protein (CRP), D-dimer, copeptin, S100β, white blood cell (WBC), monocyte, and glucose than non-surviving patients. SICH patients with good functional outcome have lower D-dimer, Interleukin 6 (IL-6), tumor necrosis factor α (TNF-α), WBC count, neutrophil count, monocyte count, copeptin and significantly higher lymphocyte counts and calcium levels. Out of all blood biomarkers that were evaluated, only S100β and copeptin had very high effect size and high certainty of evidence. Conclusion It is interesting to notice that many blood biomarkers significantly associated with SICH patients’ outcomes are related to inflammatory responses. This suggests that modulation of inflammation might be essential to improve SICH patients’ prognosis. We confidently concluded that S100β and copeptin are the most reliable blood biomarkers that can be used as prognosticators in SICH patients. On other biomarkers, in addition to heterogeneities and inconsistencies, several factors might affect the conclusions of current meta-analysis; thus, future studies to increase the certainties of evidence and effect size on other biomarkers are crucial.
Chromosomal domain formation by archaeal SMC, a roadblock protein, and DNA structure
Based on PCA and SSA-LightGBM oil-immersed transformer fault diagnosis method
A fault diagnosis method for oil immersed transformers based on principal component analysis and SSA LightGBM is proposed to address the problem of low diagnostic accuracy caused by the complexity of current oil immersed transformer faults. Firstly, data on dissolved gases in oil is collected, and a 17 dimensional fault feature matrix is constructed using the uncoded ratio method. The feature matrix is then standardized to obtain joint features. Secondly, principal component analysis is used for feature fusion to eliminate information redundancy between variables and construct fused features. Finally, a transformer diagnostic model based on SSA-LightGBM was constructed, and the ten fold cross validation method was used to verify the classification ability of the model. The experimental results show that the SSA-LightGBM model proposed in this paper has an average fault diagnosis accuracy of 93.6% after SSA algorithm optimization, which is 3.6% higher than before optimization. At the same time, compared with the GA-LightGBM and GWO-LightGBM fault diagnosis models, SSA-LightGBM has improved the diagnostic accuracy by 8.1% and 5.7% respectively, verifying that this method can effectively improve the fault diagnosis performance of oil immersed transformers and is superior to other similar methods.
Ball-and-chain inactivation of a human large conductance calcium-activated potassium channel
A study on the relationship between personality and motivation in leisure participants
Motivation and personality, which are among the most important effects of human behavior, are important in terms of leisure activities. Therefore, this study aimed to examine the relationship between motivation and personality of individuals who participate in physical activity in their leisure time. In the study, the correlational screening model was used, and 370 (m:28.76±10.37) participants who regularly practiced physical activity participated. The relationship between the data obtained in the research was tested with canonical correlation analysis, and the first two canonical correlation functions between the two variable data sets were interpreted. Self-control and extraversion sub-dimensions in the personality data set and internal regulation and external regulation sub-dimensions in the motivation data set were found to make the highest contribution. It was determined that for the first set of canonical functions, the relationship between self-control and internal regulation had a unidirectional correlation, whereas, for the second set of canonical functions, the relationship between extraversion and external regulation had an inverse correlation. Studies show how valuable intrinsic motivation sources are for individuals, and personality traits such as self-control and extraversion support this situation. It is considered that the personality traits of leisure time participants may be a clue to the types of motivation of the participants.
A small signaling domain controls PPIP5K phosphatase activity in phosphate homeostasis
Abstract Inositol pyrophosphates (PP-InsPs) are eukaryotic nutrient messengers. The N-terminal kinase domain of diphosphoinositol pentakisphosphate kinase (PPIP5K) generates the messenger 1,5-InsP 8 , the C-terminal phosphatase domain catalyzes PP-InsP breakdown. The balance between kinase and phosphatase activities regulates 1,5-InsP 8 levels. Here, we present crystal structures of the apo and substrate-bound PPIP5K phosphatase domain from S. cerevisiae (ScVip1 PD ). ScVip1 PD is a phytase-like inositol 1-pyrophosphate histidine phosphatase with two conserved catalytic motifs. The enzyme has a strong preference for 1,5-InsP 8 and is inhibited by inorganic phosphate. It contains an α-helical insertion domain stabilized by a structural Zn 2+ binding site, and a unique GAF domain that channels the substrate to the active site. Mutations that alter the active site, restrict the movement of the GAF domain, or change the substrate channel’s charge inhibit the enzyme activity in vitro, and Arabidopsis VIH2 in planta . Our work reveals the structure, enzymatic mechanism and regulation of eukaryotic PPIP5K phosphatases.
Research on key factors influencing Chinese designers’ use of AIGC: An extension based on TAM and TRI
With the rapid development of AI intelligent technology, AIGC can bring an innovative revolution to art creation, providing designers with unlimited possibilities but also challenges. These challenges affect the willingness to adopt and constrain the sustainable development of AIGC. The purpose of this study is to analyse the factors of designers’ adoption intention behaviours. This study reconstructed the research model by combining the factors of AIGC technology characteristics and interactivity, technology acceptance model, technology readiness model, etc. The empirical study was conducted from the dual perspectives of AIGC application characteristics and designers’ psychology, in order to predict the factors that predict designers’ behavioural intentions to use AIGC. In this study, a questionnaire survey was conducted among designers in China and 462 valuable responses were received. Through structural equation modelling (SEM) analysis, the study found that: (1) AIGC’s technical features and interactivity positively affect perceived ease of use, and perceived usefulness, but the interactive features do not directly affect perceived usefulness; perceived ease of use and perceived usefulness positively affect designers’ intention to adopt AIGC applications; (2) optimism and innovation positively affect technical features and designers’ intention to adopt; Insecurity negatively affects designers’ willingness to adopt, and insecurity does not affect technical features; discomfort does not affect designers’ technical features and willingness to adopt. This study further extends the theoretical models of TAM(Technology Acceptance Model) and TRI(Technology Readiness Model), provides a theoretical basis for studying designers’ adoption behaviour of AIGC, and enriches the application groups and domains of the theoretical models of TAM and TRI. The results of this study provide inspiration for the development, design, and marketing of AIGC applications, contributing to the realisation and further adoption of AIGC applications, as well as to the professional development of designers.
Benefits of equilibrium between microbiota- and host-derived ligands of the aryl hydrocarbon receptor after stroke in aged male mice
Educational constraints on marital sorting and income mobility
This paper examines the effect of educational assortative mating on overall income mobility in terms of both inter- and intragenerational mobility. In recent years, educational assortative mating has become a trend in China, and this marital sorting pattern not only contributes to marriage stability but is also related to increased income mobility. Educational assortative mating affects the distribution of educational resources among families with diffferent educational qualifications. Families with higher educational qualifications have more educational resources, thus obtaining a more solid income status. Educational assortative mating has the most significant influence on the income mobility of the low-income group, as high-quality educational resources are the key to enabling this group to raise its income status. This paper argues that, in the future, income mobility should be promoted by evenly distributing social education resources and reducing the resource constraints on the upward mobility of the low-income group.
Drug repurposing for Alzheimer’s disease and other neurodegenerative disorders
The impact of digital industry development on regional economic resilience: Evidence from China
With the outbreak of the global public health crisis in 2019, enhancing the resilience of regional economies has become the current focal point. Existing studies have mostly focused on the region itself, lacking exploration of regional economic resilience from the aspects of dynamics, multiple perspectives, and multidimensional integration. At the same time, the digital industry, as an emerging sector, should not only consider its impact on economic development itself, but also focus on whether it can continuously and effectively enhance the level of regional economic resilience, in order to cope with crises that may arise at any time. Therefore, through empirical methods, we conducted a detailed study of the spatial correlation and internal driving factors between the digital industry and regional economic resilience, aiming to build a more valuable theoretical framework based on existing research findings and explore a regional resilience development strategy centered around the digital industry. This paper, combining conclusions and methods from existing literature, attempts to expand the definition of regional economic resilience, evaluation index system, and the relationship with the digital industry from the perspective of evolutionary economic geography. This article empirically examines data from 30 provinces in China from 2014 to 2022 (excluding Tibet, Hong Kong, Macau, and Taiwan due to lack of data). Firstly, this paper employs a two-way fixed effects model to examine the direct relationship between digital industry development and regional economic resilience. The research results indicate that the development of the digital industry can effectively enhance regional economic resilience. Secondly, the role of spatial location, as an important aspect of evolutionary economic geography, is also considered in this paper. The spatial Durbin model is used to discover spatial spillover effects of digital industry development on regional economic resilience under different spatial location relationships. Finally, this paper considers environmental regulations as a threshold variable to study the impact of the digital industry on regional economic resilience under different levels of environmental regulation. The results indicate that when the degree of environmental regulation is less than 0.0011, the digital industry can more effectively empower the enhancement of regional economic resilience levels. In conclusion, this paper finds that while emphasizing the role of the digital industry in the resilient development of regional economies, it is also essential to promote regional cooperation for mutual benefit and win-win results. This will accelerate the transformation of digital enterprises, optimize industrial structures, and achieve green development.
Axin formation inhibitor 1 aggravates hepatic ischemia‒reperfusion injury by promoting the ubiquitination and degradation of PPARβ
The impact of top management team tenure heterogeneity on innovation efficiency of declining firms
Most firms will experience a decline in their development process. The contraction in demand and the impact of COVID-19 have exacerbated a firm’s performance. Under the dilemma of resources reduction and recovery, the declining firm pays more attention to the efficient utilization of the diminishing innovation resources. Based on upper echelon theory and principal-agent theory, this study investigates the impacts of top management team (TMT) tenure heterogeneity and ownership concentration on innovation efficiency. The sample consists of 534 firm observations after PSM nearest-neighbour matching, sourced from A-share listed manufacturing firms in Shanghai and Shenzhen from 2015 to 2019. Innovation efficiency of declining firms is measured using the Malmquist Index method. The fixed-effects (FE) model, PSM-DID model, and stepwise regression are employed to test our hypotheses. The main findings conclude that TMT tenure heterogeneity improves innovation efficiency, and the effect in declining firms is stronger compared to normal firm. Moreover, the concentrated ownership structure inhibits this positive effect because of the excessive tight control over TMT, and this inhibitory effect is stronger in declining firms than normal firms. The robustness checks of alternative variables and alternative regression model, and the addressing of endogenous problem, further support these findings. Efficiency improvement is crucial for the recovery of declining firm. The introduction of an efficiency perspective bridges the gaps in the existing literature. This study contributes to the literature on upper echelon theory and principal-agent theory by integrating them into the context of declining firms. The continuous interaction between the replacement TMT members and ownership restructuring shapes the dynamic capability of declining firms, contributing to the dynamic capability literature. The findings also provide practical guidelines for declining firms, such as replacing top management members and diluting equity, to achieve recovery. It is noted that an excessive focus on efficiency can also lead to neglecting thorough strategic change.
Human skeletal muscle fiber heterogeneity beyond myosin heavy chains
A statistical insight to exploration of medicinal wastewater as a source of thermostable lipase-producing microorganisms
Bacteria are ubiquitous and capable of thriving in diverse environments, including industrial effluents, which often present harsh physical and chemical conditions. These microorganisms produce various intracellular and extracellular biomolecules that enable adaptation, tolerance, and utilization of such extreme environments. Recognizing the growing industrial demand for thermostable lipases, this study focuses on the isolation, characterization, and optimization of lipase-producing bacteria from medicinal wastewater collected from a factory in North 24 Parganas, Kolkata, West Bengal, India. Nineteen lipase-producing bacterial isolates were obtained from nutrient agar plates and screened using tributyrin agar (TBA) plates. Extracellular lipolytic activity was confirmed via the cup-plate method with Tween 20/80 agar and methyl red as the indicator. The isolates were characterized morphologically and through biochemical tests. Extracellular lipase activity was quantified spectrophotometrically using para-nitrophenyl palmitate (pNPP) as a substrate in 50 mM Tris-HCl buffer, with absorbance measured at 410 nm after incubation at 65°C for 20 minutes to assess thermostability. Of the 19 isolates, 11 produced thermolabile lipases, while 8 exhibited thermostable lipase activity. Among these, three isolates (MWS14, MWS6, and MWS18) demonstrated high thermostable lipase production, with MWS18 being the most productive. Ribotyping and BLAST analysis revealed that these isolates shared 99% sequence similarity with Enterococcus, Bacillus, and Serratia species, respectively. Statistical analysis using the Kruskal-Wallis H-test confirmed significant differences in lipase production among the three groups of isolates. The study also predicts greater lipase production potential in Gram-negative bacterial strains compared to Gram-positive isolates. These findings highlight the industrial relevance of medicinal wastewater as a source of thermostable lipase-producing bacteria.
Lipogenic enzyme FASN promotes mutant p53 accumulation and gain-of-function through palmitoylation
Abstract The tumor-suppressive function of p53 is frequently disrupted by mutations in cancers. Missense mutant p53 (mutp53) protein often stabilizes and accumulates to high levels in cancers to promote tumorigenesis through the gain-of-function (GOF) mechanism. Currently, the mechanism of mutp53 accumulation and GOF is incompletely understood. Here, we identify the lipogenic enzyme FASN as an important regulator of mutp53 accumulation and GOF. FASN interacts with mutp53 to enhance mutp53 palmitoylation, which inhibits mutp53 ubiquitination to promote mutp53 accumulation and GOF. Blocking FASN genetically or by small-molecule inhibitors suppresses mutp53 palmitoylation to inhibit mutp53 accumulation, which in turn inhibits the growth of mutp53 tumors in orthotopic and subcutaneous xenograft tumor models and transgenic mice, as well as the growth of human tumor organoids carrying mutp53. Our results reveal that mutp53 palmitoylation is an important mechanism underlying mutp53 accumulation and GOF, and targeting FASN is a potential therapeutic strategy for cancers carrying mutp53.
State-trace analysis meets personality measurement: Why the Big Five tests are not based on five latent dimensions and how to fix them
Unidimensionality is a fundamental yet often overlooked prerequisite for measurement. In the context of psychological measurement, the central question is whether a set of items can be logically reduced to a single latent factor. This study advocates for the application of state-trace analysis, an underutilized method from mathematical psychology, as a decisive tool to address this question. State-trace analysis provides a simple, general, and rigorous criterion for unidimensionality: monotonicity between item pairs. Identifying items within a factor that violate this criterion is straightforward, offering a practical approach to evaluating unidimensionality. This paper demonstrates the utility of state-trace analysis through exemplary applications within the framework of the five-factor model, analyzing data from the International Personality Item Pool-NEO-120 (N = 618, 000) and the NEO Personality Inventory–Revised (N1 = 857, N2 = 500). The findings reveal that maintaining the five-factor model requires significant revisions to numerous items, highlighting the potential of state-trace analysis to enhance personality measurement beyond existing methodologies. The paper concludes by discussing strategies to promote broader adoption of this method and how future designs in personality research can be tailored to effectively incorporate state-trace analysis.
Time-resolved oxidative signal convergence across the algae–embryophyte divide
Abstract The earliest land plants faced a significant challenge in adapting to environmental stressors. Stress on land is unique in its dynamics, entailing swift and drastic changes in light and temperature. While we know that land plants share with their closest streptophyte algal relatives key components of the genetic makeup for dynamic stress responses, their concerted action is little understood. Here, we combine time-course stress profiling using photophysiology, transcriptomics on 2.7 Tbp of data, and metabolite profiling analyses on 270 distinct samples, to study stress kinetics across three 600-million-year-divergent streptophytes. Through co-expression analysis and Granger causal inference we predict a gene regulatory network that retraces a web of ancient signal convergences at ethylene signaling components, osmosensors, and chains of major kinases. These kinase hubs already integrated diverse environmental inputs since before the dawn of plants on land.
Fundus autofluorescence features specific for EYS-associated retinitis pigmentosa
Purpose To assess the utility of fundus autofluorescence (FAF) patterns for predicting the EYS genotype in retinitis pigmentosa (RP) patients. Methods This retrospective, multi-institutional study analyzed FAF images from 200 RP patients (74 with EYS and 126 without EYS) from Singapore and Japan. Seven FAF patterns including the infinity sign and a broad banded hyper-autofluorescent leading edge were evaluated for their association with the EYS genotype. Results The infinity sign and broad banded hyperautofluorescent leading edge occurred more frequently in EYS eyes (p = 0.0014 and p = 0.036 respectively). Logistic regression analysis showed that the infinity sign was predictive of EYS (p = 0.003). The combined FAF parameters predicted EYS with a specificity of 95.20%, sensitivity of 25.68% and accuracy of 69.50%, with a cut-off value 0.5 based on the probability of seven FAF parameters. Conclusions In this multinational cohort study of patients with RP, we demonstrated that specific FAF patterns, particularly the infinity sign, have clinical utility in identifying patients with EYS-associated disease. These findings may be useful for clinicians and geneticists when genotyping patients with RP, and may also enhance our understanding of underlying pathophysiology of EYS-associated RP, which is a prevalent cause of RP in Asia and elsewhere.