Obesity and septic patient outcomes: Shaping the puzzle through age and sex perspectives.

BACKGROUND & AIMS: While obesity has been reported as a protective factor in septic patients, little is known about the potential modifying effects of age and sex. The objective of this study is to investigate age and sex-specific associations between obesity and the prognosis of septic patients. METHODS: A retrospective analysis was conducted on a cohort of 15,464 septic patients, categorized by body mass index (BMI) into four groups: underweight (<18.5 kg/m2, n = 483), normal (18.5-24.9 kg/m2, n = 4344), overweight (25-29.9 kg/m2, n = 4949) and obese (≥30 kg/m2, n = 5688). Multivariable logistic regression and inverse probability weighting were employed to robustly confirm the protective effect of a higher BMI on 28-day mortality, with normal weight serving as the reference category. Subgroup analyses based on age (young: 18-39, middle-aged: 40-64 and elderly: ≥65) and sex were performed. RESULTS: The findings demonstrate that high BMI independently confers a protective effect against 28-day mortality in septic patients. However, the relationship between BMI and 28-day mortality exhibits a non-linear trend, with a BMI of 34.5 kg/m2 displaying the lowest odds ratio. Notably, the survival benefits associated with a high BMI were not observed in the young group. Moreover, being underweight emerges as an independent risk factor for middle-aged and elderly female patients, while in males it is only a risk factor in the elderly group. Interestingly, being overweight and obese were identified as independent protective factors in middle-aged and elderly male patients, but not in females. CONCLUSIONS: The effect of BMI on mortality in septic patients varies according to age and sex. Elderly individuals with sepsis may derive more prognostic benefits from obesity.

Carnosine regulation of intracellular pH homeostasis promotes lysosome-dependent tumor immunoevasion.

Tumor cells and surrounding immune cells undergo metabolic reprogramming, leading to an acidic tumor microenvironment. However, it is unclear how tumor cells adapt to this acidic stress during tumor progression. Here we show that carnosine, a mobile buffering metabolite that accumulates under hypoxia in tumor cells, regulates intracellular pH homeostasis and drives lysosome-dependent tumor immune evasion. A previously unrecognized isoform of carnosine synthase, CARNS2, promotes carnosine synthesis under hypoxia. Carnosine maintains intracellular pH (pHi) homeostasis by functioning as a mobile proton carrier to accelerate cytosolic H+ mobility and release, which in turn controls lysosomal subcellular distribution, acidification and activity. Furthermore, by maintaining lysosomal activity, carnosine facilitates nuclear transcription factor X-box binding 1 (NFX1) degradation, triggering galectin-9 and T-cell-mediated immune escape and tumorigenesis. These findings indicate an unconventional mechanism for pHi regulation in cancer cells and demonstrate how lysosome contributes to immune evasion, thus providing a basis for development of combined therapeutic strategies against hepatocellular carcinoma that exploit disrupted pHi homeostasis with immune checkpoint blockade.

OXCT1 functions as a succinyltransferase, contributing to hepatocellular carcinoma via succinylating LACTB.

Metabolic reprogramming is an important feature of cancers that has been closely linked to post-translational protein modification (PTM). Lysine succinylation is a recently identified PTM involved in regulating protein functions, whereas its regulatory mechanism and possible roles in tumor progression remain unclear. Here, we show that OXCT1, an enzyme catalyzing ketone body oxidation, functions as a lysine succinyltransferase to contribute to tumor progression. Mechanistically, we find that OXCT1 functions as a succinyltransferase, with residue G424 essential for this activity. We also identified serine beta-lactamase-like protein (LACTB) as a main target of OXCT1-mediated succinylation. Extensive succinylation of LACTB K284 inhibits its proteolytic activity, resulting in increased mitochondrial membrane potential and respiration, ultimately leading to hepatocellular carcinoma (HCC) progression. In summary, this study establishes lysine succinyltransferase function of OXCT1 and highlights a link between HCC prognosis and LACTB K284 succinylation, suggesting a potentially valuable biomarker and therapeutic target for further development.

Diagnosis Framework for Probable Alzheimer's Disease and Mild Cognitive Impairment Based on Multi-Dimensional Emotion Features.

BACKGROUND: Emotion and cognition are intercorrelated. Impaired emotion is common in populations with Alzheimer's disease (AD) and mild cognitive impairment (MCI), showing promises as an early detection approach. OBJECTIVE: We aim to develop a novel automatic classification tool based on emotion features and machine learning. METHODS: Older adults aged 60 years or over were recruited among residents in the long-term care facilities and the community. Participants included healthy control participants with normal cognition (HC, n = 26), patients with MCI (n = 23), and patients with probable AD (n = 30). Participants watched emotional film clips while multi-dimensional emotion data were collected, including mental features of Self-Assessment Manikin (SAM), physiological features of electrodermal activity (EDA), and facial expressions. Emotional features of EDA and facial expression were abstracted by using continuous decomposition analysis and EomNet, respectively. Bidirectional long short-term memory (Bi-LSTM) was used to train classification model. Hybrid fusion was used, including early feature fusion and late decision fusion. Data from 79 participants were utilized into deep machine learning analysis and hybrid fusion method. RESULTS: By combining multiple emotion features, the model's performance of AUC value was highest in classification between HC and probable AD (AUC = 0.92), intermediate between MCI and probable AD (AUC = 0.88), and lowest between HC and MCI (AUC = 0.82). CONCLUSIONS: Our method demonstrated an excellent predictive power to differentiate HC/MCI/AD by fusion of multiple emotion features. The proposed model provides a cost-effective and automated method that can assist in detecting probable AD and MCI from normal aging.

The combination of DNA nanostructures and materials for highly sensitive electrochemical detection.

Due to the wide range of electrochemical devices available, DNA nanostructures and material-based technologies have been greatly broadened. They have been actively used to create a variety of beautiful nanostructures owing to their unmatched programmability. Currently, a variety of electrochemical devices have been used for rapid sensing of biomolecules and other diagnostic applications. Here, we provide a brief overview of recent advances in DNA-based biomolecular assays. Biosensing platform such as electrochemical biosensor, nanopore biosensor, and field-effect transistor biosensors (FET), which are equipped with aptamer, DNA walker, DNAzyme, DNA origami, and nanomaterials, has been developed for amplification detection. Under the optimal conditions, the proposed biosensor has good amplification detection performance. Further, we discussed the challenges of detection strategies in clinical applications and offered the prospect of this field.

Daily diary study of associations between alcohol, cannabis, co-use and sleep quality in individuals with intentions to use cannabis to cope with anxiety.

INTRODUCTION: Sleep problems and anxiety conditions are common comorbidities and may be influenced by cannabis and alcohol use. This study examined daily within-person variation in subjective sleep quality among individuals with anxiety symptoms after cannabis or alcohol were used alone, and after co-use. METHODS: A total of 347 individuals with intentions to use cannabis to cope with anxiety reported their cannabis and alcohol use in the previous 24 h and their previous nights' sleep quality for 30 consecutive days. Mixed-effects models examined whether the within-person daily variation in use of cannabis and alcohol (alone and co-use) was associated with subjective sleep quality. Models also examined whether daily cannabis and alcohol use associations with sleep were moderated by frequency of cannabis, alcohol and co-use during the study period. RESULTS: Compared to non-use, participants reported better sleep after cannabis-use-only and after co-use, but not after alcohol-use-only. People who more frequently use alcohol and cannabis reported sleeping better after cannabis-use-only days compared to those who use cannabis and alcohol less frequently. DISCUSSION AND CONCLUSIONS: The study's utilisation of naturalistic data among individuals with anxiety symptoms replicated previously reported experimental findings among individuals without sleep and anxiety problems that overall, cannabis is associated with higher subjective sleep quality. The results expand upon other research to suggest that more frequent use of alcohol and cannabis may moderate daily associations of cannabis use and sleep, potentially through pharmacokinetics and cross-sensitisation.

SingleScan: a comprehensive resource for single-cell sequencing data processing and mining.

Single-cell sequencing has shed light on previously inaccessible biological questions from different fields of research, including organism development, immune function, and disease progression. The number of single-cell-based studies increased dramatically over the past decade. Several new methods and tools have been continuously developed, making it extremely tricky to navigate this research landscape and develop an up-to-date workflow to analyze single-cell sequencing data, particularly for researchers seeking to enter this field without computational experience. Moreover, choosing appropriate tools and optimal parameters to meet the demands of researchers represents a major challenge in processing single-cell sequencing data. However, a specific resource for easy access to detailed information on single-cell sequencing methods and data processing pipelines is still lacking. In the present study, an online resource called SingleScan was developed to curate all up-to-date single-cell transcriptome/genome analyzing tools and pipelines. All the available tools were categorized according to their main tasks, and several typical workflows for single-cell data analysis were summarized. In addition, spatial transcriptomics, which is a breakthrough molecular analysis method that enables researchers to measure all gene activity in tissue samples and map the site of activity, was included along with a portion of single-cell and spatial analysis solutions. For each processing step, the available tools and specific parameters used in published articles are provided and how these parameters affect the results is shown in the resource. All information used in the resource was manually extracted from related literature. An interactive website was designed for data retrieval, visualization, and download. By analyzing the included tools and literature, users can gain insights into the trends of single-cell studies and easily grasp the specific usage of a specific tool. SingleScan will facilitate the analysis of single-cell sequencing data and promote the development of new tools to meet the growing and diverse needs of the research community. The SingleScan database is publicly accessible via the website at http://cailab.labshare.cn/SingleScan .

The effects of esketamine on the intestinal microenvironment and intestinal microbiota in mice.

OBJECTIVE: This study aimed to investigate the impact of esketamine on the intestinal flora and microenvironment in mice using mRNA transcriptome sequencing and 16S rRNA sequencing. METHODS: Ten female mice were randomly assigned to two groups. One group received daily intramuscular injections of sterile water, while the other group received esketamine. After 24 days, the mice were sacrificed, and their intestinal tissues and contents were collected for 16S rRNA sequencing and mRNA transcriptome sequencing. The intergroup differences in the mouse intestinal flora were analyzed. Differentially expressed genes were utilized to construct ceRNA networks and transcription factor regulatory networks to assess the effects of esketamine on the intestinal flora and intestinal tissue genes. RESULTS: Esketamine significantly altered the abundance of intestinal microbiota, including Adlercreutzia equolifaciens and Akkermansia muciniphila. Differential expression analysis revealed 301 significantly upregulated genes and 106 significantly downregulated genes. The ceRNA regulatory network consisted of 6 lncRNAs, 44 miRNAs, and 113 mRNAs, while the regulatory factor network included 13 transcription factors and 53 target genes. Gene Ontology enrichment analysis indicated that the differentially expressed genes were primarily associated with immunity, including B-cell activation and humoral immune response mediation. The biological processes in the ceRNA regulatory network primarily involved transport, such as organic anion transport and monocarboxylic acid transport. The functional annotation of target genes in the TF network was mainly related to epithelial cells, including epithelial cell proliferation and regulation. CONCLUSION: Esketamine induces changes in gut microbiota and the intestinal microenvironment, impacting the immune environment and transport modes.

How do carbon emissions trading impact the financialization of non-financial companies? Evidence from a quasi-natural experiment in China.

This study examines whether and how carbon trading policy impacts the financialization of non-financial firms, using China emission trading scheme as a quasi-natural experiment. We find that the carbon trading policy exerts a substantial and enduring inhibitory effect on corporate financialization. Our findings are robust to possible result bias and more precise control group. Additionally, we explore potential channels through which carbon trading policy can affect financialization, and find that it curbs financialization by reducing financing constraints. Finally, we demonstrate that the relationship between carbon trading policy and financialization of non-financial companies is moderated by company's ownership, region, and industry competition.

Increased functional connectivity between the midbrain and frontal cortex following bright light therapy in subthreshold depression: A randomized clinical trial.

The underlying mechanisms of bright light therapy (BLT) in the prevention of individuals with subthreshold depression symptoms are yet to be elucidated. The goal of the study was to assess the correlation between midbrain monoamine-producing nuclei treatment-related functional connectivity (FC) changes and depressive symptom improvements in subthreshold depression. This double-blind, randomized, placebo-controlled clinical trial was conducted between March 2020 and June 2022. A total of 74 young adults with subthreshold depression were randomly assigned to receive 8-week BLT (N = 38) or placebo (N = 36). Depression severity was measured using the Hamilton Depression Rating Scale (HDRS). The participants underwent resting-state functional magnetic resonance imaging at baseline and after treatment. The dorsal raphe nucleus (DRN), ventral tegmental area (VTA), and habenula seed-based whole-brain FC were analyzed. A multivariate regression model examined whether baseline brain FC was associated with changes in scores on HDRS during BLT treatment. BLT group displayed significantly decreased HDRS scores from pre- to posttreatment compared to the placebo group. BLT increased the FC between the DRN and medial prefrontal cortex (mPFC) and between the left VTA and right superior frontal gyrus (SFG). Altered VTA-SFG connectivity was associated with HDRS changes in the BLT group. Moreover, the baseline FC between DRN and mPFC could predict HDRS changes in BLT. These results suggested that BLT improves depressive symptoms and increases midbrain monoamine-producing nuclei and frontal cortex connectivity in subthreshold depression, which raises the possibility that pretreatment FC of DRN-mPFC could be used as a biomarker for improved BLT treatment in depression. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Microswimmer-Assisted Dual-Signal Sensor for Multiple Targets in Whole Blood.

Accurate detection of biomarkers in whole blood is an important aspect of diagnostic testing but remains a challenge due to various interferences. However, using a self-calibrating two-signal strategy offers a solution that can overcome interference caused by experimental and environmental factors. Here, we proposed a novel microswimmer {methylene blue (MB)@ZIF-90@aptamer-HER2/3,3',5,5'-tetramethylbenzidine (TMB)@ZIF-90@aptamer-ER}-dual-signal (electrochemical and fluorescence) homogeneous sensor based on functionalized ZIF nanomaterials for one-step simultaneous detection of human epidermal growth factor receptor-2 (HER2) and estrogen receptor (ER) in whole blood. The proposed one-step ZIF-90 synthesis encapsulates TMB and MB with dual-signal properties. HER2 and ER aptamers adsorbed on MB@ZIF-90/TMB@ZIF-90 function as the gate switches. The microswimmer targets the HER2 and ER with adenosine triphosphate (ATP)-driven motion. When targets are present, aptamers dissociate and reduce the microswimmer's surface negative charge. The microswimmer undergoes attack and decomposition by swimming ATP due to the strong coordination force between ATP and Zn2+, leading to the release of MB and TMB. The negative charges on the surface of indium tin oxide enrich MB and TMB with positive charges, thereby increasing the intensities of electrochemical and fluorescence signals. The detection process was completed within 40 min, and the detection limits for ER and HER2 were 8.1 and 5.7 fg/mL respectively, with a linear range of 0.25-20 pg/mL.

ATACAmp: a tool for detecting ecDNA/HSRs from bulk and single-cell ATAC-seq data.

BACKGROUND: High oncogene expression in cancer cells is a major cause of rapid tumor progression and drug resistance. Recent cancer genome research has shown that oncogenes as well as regulatory elements can be amplified in the form of extrachromosomal DNA (ecDNA) or subsequently integrated into chromosomes as homogeneously staining regions (HSRs). These genome-level variants lead to the overexpression of the corresponding oncogenes, resulting in poor prognosis. Most existing detection methods identify ecDNA using whole genome sequencing (WGS) data. However, these techniques usually detect many false positive regions owing to chromosomal DNA interference. RESULTS: In the present study, an algorithm called "ATACAmp" that can identify ecDNA/HSRs in tumor genomes using ATAC-seq data has been described. High chromatin accessibility, one of the characteristics of ecDNA, makes ATAC-seq naturally enriched in ecDNA and reduces chromosomal DNA interference. The algorithm was validated using ATAC-seq data from cell lines that have been experimentally determined to contain ecDNA regions. ATACAmp accurately identified the majority of validated ecDNA regions. AmpliconArchitect, the widely used ecDNA detecting tool, was used to detect ecDNA regions based on the WGS data of the same cell lines. Additionally, the Circle-finder software, another tool that utilizes ATAC-seq data, was assessed. The results showed that ATACAmp exhibited higher accuracy than AmpliconArchitect and Circle-finder. Moreover, ATACAmp supported the analysis of single-cell ATAC-seq data, which linked ecDNA to specific cells. CONCLUSIONS: ATACAmp, written in Python, is freely available on GitHub under the MIT license: https://github.com/chsmiss/ATAC-amp . Using ATAC-seq data, ATACAmp offers a novel analytical approach that is distinct from the conventional use of WGS data. Thus, this method has the potential to reduce the cost and technical complexity associated ecDNA analysis.

The allometric relationship between carbon emission and economic development in Yangtze River Delta: fusion of multi-source remote sensing nighttime light data.

Exploring the allometric relationship between carbon emission and economic development can provide guidance for policy-makers who hope to accelerate carbon emission reduction and achieve high-quality development. First, based on the established DMSP/OLS and NPP/VIIRS nighttime light datasets, this study simulated the carbon emissions of the Yangtze River Delta from 2000 to 2020. Second, our research analyzed the spatiotemporal evolution characteristics of carbon emissions. Third, adopting allometric growth model, we explored the allometric relationship between economic development and carbon emissions in Yangtze River Delta. The main conclusions are as follows. First, four prediction models, namely, linear fitting, support vector machine, random forest, and CNN-BiLSTM deep learning, were compared to simulate the accuracy of carbon emissions. Consequently, the CNN-BiLSTM deep learning estimation model presented the best accuracy. Second, both the carbon emissions in YRD as a whole showed an increasing trend, with the largest growth rate appearing in Shanghai and the smallest growth rate occurring in Lishui. Moreover, the high-carbon emission areas were mainly distributed in the core city cluster, which are enclosed by Shanghai, Nanjing, and Hangzhou. Finally, the allometric relationship between economic development and carbon emissions was dominated by one-level negative during the sample period, and the relative growth rate of carbon emissions is lower than that of the economic development, which made the YRD at a basic coordinate stage of weak expansion of economy.

Comprehensive single-cell analysis reveals novel anergic antigen-presenting cell subtypes in human sepsis.

Background: Sepsis is a life-threatening condition with high mortality. A few studies have emerged utilizing single-cell RNA sequencing (scRNA-seq) to analyze gene expression at the single-cell resolution in sepsis, but a comprehensive high-resolution analysis of blood antigen-presenting cells has not been conducted. Methods: All published human scRNA-seq data were downloaded from the single cell portal database. After manually curating the dataset, we extracted all antigen-presenting cells, including dendritic cells (DCs) and monocytes, for identification of cell subpopulations and their gene profiling and intercellular interactions between septic patients and healthy controls. Finally, we further validated the findings by performing deconvolution analysis on bulk RNA sequencing (RNA-seq) data and flow cytometry. Results: Within the traditional DC populations, we discovered novel anergic DC subtypes characterized by low major histocompatibility complex class II expression. Notably, these anergic DC subtypes showed a significant increase in septic patients. Additionally, we found that a previously reported immunosuppressive monocyte subtype, Mono1, exhibited a similar gene expression profile to these anergic DCs. The consistency of our findings was confirmed through validation using bulk RNA-seq and flow cytometry, ensuring accurate identification of cell subtypes and gene expression patterns. Conclusions: This study represents the first comprehensive single-cell analysis of antigen-presenting cells in human sepsis, revealing novel disease-associated anergic DC subtypes. These findings provide new insights into the cellular mechanisms of immune dysregulation in bacterial sepsis.

Diamond nitrogen-vacancy color-centered thermometer for integrated circuit application.

With the advancement of the chip industry, accurate temperature measurement and thermal management have become crucial. Traditional infrared temperature imaging has limitations in terms of resolution and accuracy. ln recent years, quantum diamond nitrogen-vacancy centers have emerged as a promising option for temperature sensing, but separating temperature from magnetic field effects remains a challenge. This paper presents a numerical approach to decouple temperature and magnetic fields using an ensemble Hamiltonian in high-current density Integrated Circuit (IC) applications. The proposed method demonstrates a temperature sensitivity of 22.9 mK/Hz1/2 and the ability to perform scanning temperature imaging with a spatial resolution of 20 µm on a typical IC.

Evaluation of trabecular meshwork-specific promoters in vitro and in vivo using scAAV2 vectors expressing C3 transferase.

AIM: To evaluate the potential of two trabecular meshwork (TM)-specific promoters, Chitinase 3-like 1 (Ch3L1) and matrix gla protein (MGP), for improving specificity and safety in glaucoma gene therapy based on self-complementary AAV2 (scAAV2) vector technologies. METHODS: An scAAV2 vector with C3 transferase (C3) as the reporter gene (scAAV2-C3) was selected. The scAAV2-C3 vectors were driven by Ch3L1 (scAAV2-Ch3L1-C3), MGP (scAAV2-MGP-C3), enhanced MGP (scAAV2-eMGP-C3) and cytomegalovirus (scAAV2-CMV-C3), respectively. The cultured primary human TM cells were treated with each vector at different multiplicities of infections. Changes in cell morphology were observed by phase contrast microscopy. Actin stress fibers and Rho GTPases/Rho-associated protein kinase pathway-related molecules were assessed by immunofluorescence staining, real-time quantitative polymerase chain reaction and Western blot. Each vector was injected intracamerally into the one eye of each rat at low and high doses respectively. In vivo green fluorescence was visualized by a Micron III Retinal Imaging Microscope. Intraocular pressure (IOP) was monitored using a rebound tonometer. Ocular responses were evaluated by slit-lamp microscopy. Ocular histopathology analysis was examined by hematoxylin and eosin staining. RESULTS: In TM cell culture studies, the vector-mediated C3 expression induced morphologic changes, disruption of actin cytoskeleton and reduction of fibronectin expression in TM cells by inhibiting the Rho GTPases/Rho-associated protein kinase signaling pathway. At the same dose, these changes were significant in TM cells treated with scAAV2-CMV-C3 or scAAV2-Ch3L1-C3, but not in cells treated with scAAV2-eMGP-C3 or scAAV2-MGP-C3. At low-injected dose, the IOP was significantly decreased in the scAAV2-Ch3L1-C3-injected eyes but not in scAAV2-MGP-C3-injected and scAAV2-eMGP-C3-injected eyes. At high-injected dose, significant IOP reduction was observed in the scAAV2-eMGP-C3-injected eyes but not in scAAV2-MGP-C3-injected eyes. Similar to scAAV2-CMV-C3, scAAV2-Ch3L1-C3 vector showed efficient transduction both in the TM and corneal endothelium. In anterior segment tissues of scAAV2-eMGP-C3-injected eyes, no obvious morphological changes were found except for the TM. Inflammation was absent. CONCLUSION: In scAAV2-transduced TM cells, the promoter-driven efficiency of Ch3L1 is close to that of cytomegalovirus, but obviously higher than that of MGP. In the anterior chamber of rat eye, the transgene expression pattern of scAAV2 vector is presumably affected by MGP promoter, but not by Ch3L1 promoter. These findings would provide a useful reference for improvement of specificity and safety in glaucoma gene therapy using scAAV2 vector.

ENO1 promotes liver carcinogenesis through YAP1-dependent arachidonic acid metabolism.

Enolase 1 (ENO1) is a glycolytic enzyme that plays essential roles in various pathological activities including cancer development. However, the mechanisms underlying ENO1-contributed tumorigenesis are not well explained. Here, we uncover that ENO1, as an RNA-binding protein, binds to the cytosine-uracil-guanine-rich elements of YAP1 messenger RNA to promote its translation. ENO1 and YAP1 positively regulate alternative arachidonic acid (AA) metabolism by inverse regulation of PLCB1 and HPGD (15-hydroxyprostaglandin dehydrogenase). The YAP1/PLCB1/HPGD axis-mediated activation of AA metabolism and subsequent accumulation of prostaglandin E2 (PGE2) are responsible for ENO1-mediated cancer progression, which can be retarded by aspirin. Finally, aberrant activation of ENO1/YAP1/PLCB1 and decreased HPGD expression in clinical hepatocellular carcinoma samples indicate a potential correlation between ENO1-regulated AA metabolism and cancer development. These findings underline a new function of ENO1 in regulating AA metabolism and tumorigenesis, suggesting a therapeutic potential for aspirin in patients with liver cancer with aberrant expression of ENO1 or YAP1.

Identification of mitochondrial-related genes as potential biomarkers for the subtyping and prediction of Alzheimer's disease.

Introduction: Alzheimer's disease (AD) is a progressive and debilitating neurodegenerative disorder prevalent among older adults. Although AD symptoms can be managed through certain treatments, advancing the understanding of underlying disease mechanisms and developing effective therapies is critical. Methods: In this study, we systematically analyzed transcriptome data from temporal lobes of healthy individuals and patients with AD to investigate the relationship between AD and mitochondrial autophagy. Machine learning algorithms were used to identify six genes-FUNDC1, MAP1LC3A, CSNK2A1, VDAC1, CSNK2B, and ATG5-for the construction of an AD prediction model. Furthermore, AD was categorized into three subtypes through consensus clustering analysis. Results: The identified genes are closely linked to the onset and progression of AD and can serve as reliable biomarkers. The differences in gene expression, clinical features, immune infiltration, and pathway enrichment were examined among the three AD subtypes. Potential drugs for the treatment of each subtype were also identified. Discussion: The findings observed in the present study can help to deepen the understanding of the underlying disease mechanisms of AD and enable the development of precision medicine and personalized treatment approaches.

Gene expression changes reveal the impact of the space environment on the skin of International Space Station astronauts.

BACKGROUND: The various types of ionizing radiation and altered gravity in the space environment present a risk to humans during space missions. Changes in the space environment lead to skin diseases, affecting the status of the aviators to fly. Therefore, it is important to explore the molecular-level changes in the skin during space missions. OBJECTIVES: Bioinformatics analysis of gene arrays from hair follicle tissue of 10 astronauts was performed to explore changes in gene expression before, during and after space missions. METHODS: First, STEM (Short Time-series Expression Miner) software was used to identify the expression patterns of hair follicle genes of astronauts pre-, in- and postflight. Gene Ontology Enrichment Analysis was then performed to explore the gene functions within the module. Protein-protein interaction network analysis was performed on skin-related genes. The transcriptional regulatory network within the module was constructed using the TRRUST database. The circadian rhythm-related genes within the module were screened using the MSigDB (Molecular Signatures Database). RESULTS: Based on differential expression analysis between the two groups, there were 327 differentially expressed genes after the astronauts entered space compared with preflight, and only 54 differentially expressed genes after returning to Earth. This outcome suggests that the expression of most genes can be recovered on return to the ground, but there are a small number of genes whose expression cannot be recovered in a short period of time. Based on time series analysis, 311 genes showed increased expression on entry into space and decreased expression on return to Earth. The genes of this expression pattern were associated with skin development, keratinocyte differentiation and cornification. Ten hub genes were identified as skin-related genes within the module, as well as nine transcription factors and three circadian genes. One hundred and seventy-nine genes decreased in expression after entry into space and increased on return to Earth. By reviewing the literature, we found that four of the genes, CSCD2, HP, CXCR1 and SSTR4, are associated with skin diseases. CONCLUSIONS: Through bioinformatics analysis, we found that the space environment affects skin keratinocyte differentiation, leading to skin barrier damage and inflammatory responses, and that this effect was decreased after return to Earth.

Interaction mechanism of egg derived peptides RVPSL and QIGLF with dipalmitoyl phosphatidylcholine membrane: microcalorimetric and molecular dynamics simulation studies.

BACKGROUND: Egg-derived peptides are becoming increasingly popular due to their biological activity and non-toxic effects. The egg-derived peptides Arg-Val-Pro-Ser-Leu (RVPSL) and Gln-Ile-Gly-Leu-Phe (QIGLF) display strong angiotensin-converting enzyme inhibitory activity and they can be taken up by intestinal epithelial cells. The interaction of the egg-derived peptides RVPSL and QIGLF with the membrane remains unclear. RESULTS: The position and structure of the peptides in the membrane were calculated. The maximum density values of RVPSL and QIGLF were 2.27 and 1.22 nm from the center of the 1,2-dipalmitoyl-sn-glycero-3-phosphatidylcholine (DPPC) membrane, respectively, indicating that peptides penetrated the membrane-water interface and were embedded in the membrane. The interaction of RVPSL and QIGLF with the DPPC membrane did not affect the average area per lipid or the lipid sequence parameters. The thermodynamic parameters ΔH, ΔG, and ΔS of the interaction between the peptide RVPSL with the DPPC membrane were 17.91 kJ mol-1 , -17.63 kJ mol-1 , 187.5 J mol-1 ·k-1 , respectively. The thermodynamic parameters ΔH, ΔG, and ΔS of the interaction between peptide QIGLF with DPPC membrane were 17.10 kJ mol-1 , -17.12 kJ mol-1 , 114.8 J mol-1 ·k-1 , respectively. CONCLUSION: The results indicated that the binding of peptides RVPSL and QIGLF to DPPC is an endothermic, spontaneous, and entropy-driven reaction. The results of the study are relevant to the problem of the low bioavailability of bioactive peptides (BP). © 2023 Society of Chemical Industry.