Characteristics of two different immune infiltrating pyroptosis subtypes in ischemic stroke.

Background: Ischemic stroke (IS) is a serious health hazard and identified as the second leading cause of mortality around the world. However, the role of pyroptosis in the immune microenvironment regulation in IS is still unclear. Here, our study aims to elucidate the effect of pyroptosis on immune microenvironment in IS. Methods: The regulation mode of pyroptosis in IS was systematically evaluated, and its effects on immune microenvironment were explored, including infiltration of immune cells, immune response gene sets, and human leukocyte antigen (HLA) gene. The genes and drugs related to pyroptosis phenotype were also identified. An MCAO rat model was constructed, and the mRNA expression levels in the classifier model were validated by qRT-PCR. Results: The separator is composed of 11 pyroptosis genes, out of which 10 genes could distinguish between ischemic stroke and control samples. CHMP2A, CHMP4A, and NAIP genes are significantly related to immune infiltrating cells, immune response gene sets, and HLA. However, two different pyroptosis subtypes mediated by 10 pyroptosis genes were identified, which were different in immune cell abundance, HLA genes, and immune response gene sets. Furthermore, 199 genes associated with pyroptosis phenotype was identified along with the analysis of biological functions. Conclusion: These findings reveal the potential mechanism of pyroptosis in the immune microenvironment of IS, indicating that pyroptosis functions as a vital component in the complexity and diversity of the immune microenvironment in patients with IS.

The consistently up-regulated expression of NLRP3 in severe asthma patients from mRNA microarray and ovalbumin-induced mouse model of asthma.

Background: Severe asthma (SA) is a chronic lung disease, resistant to current treatments, symbolized by repeated symptoms of reversible airflow obstruction, airway hyper-responsiveness, and inflammation. The aim of this study was to identify genes exhibiting differential expression in individuals without asthma and SA patients. We aimed to pinpoint hub differentially expressed genes (DEGs) by utilizing a mouse model of asthma sensitized to ovalbumin (OVA). Methods: Microarray data for SA were acquired from the Gene Expression Omnibus (GEO) databases. DEGs were identified, and functional enrichment analyses were carried out. STRING and Cytoscape were utilized to design a protein-protein interaction (PPI) network and conduct module analysis. An OVA-induced asthma mice model was established. Lung tissue from the mice was collected for quantitative reverse transcription polymerase chain reaction (qRT-PCR), Western blot, and immunohistochemistry (IHC) to assess the expression of DEGs. Results: A total of 545 DEGs were identified, among which 172 genes were upregulated in SA patients compared to healthy controls. The nucleotide-binding oligomerization domain-like receptor family pyrin domain containing 3 (NLRP3) was significantly up-regulated in SA patients [adjusted P value (Padj) =0.001]. Analysis of lung tissue using qRT-PCR, western blot, and IHC revealed higher expression of NLRP3 in OVA-induced asthma mice compared to the control group. Enrichment analysis suggests the involvement of NLRP3 in pathways related to pyroptosis, c-type lectin receptor signaling, and NOD-like receptor signaling. Conclusions: Through bioinformatics analysis, we identified a multitude of DEGs that could potentially contribute significantly to the development of SA. Notably, our findings highlight NLRP3 as a potential pivotal player in asthma pathogenesis, underscoring its prospective utility as a biomarker for SA.

Bioinformatic analysis of hippocampal histopathology in Alzheimer's disease and the therapeutic effects of active components of traditional Chinese medicine.

Background and aim: Pathological changes in the central nervous system (CNS) begin before the clinical symptoms of Alzheimer's Disease (AD) manifest, with the hippocampus being one of the first affected structures. Current treatments fail to alter AD progression. Traditional Chinese medicine (TCM) has shown potential in improving AD pathology through multi-target mechanisms. This study investigates pathological changes in AD hippocampal tissue and explores TCM active components that may alleviate these changes. Methods: GSE5281 and GSE173955 datasets were downloaded from GEO and normalized to identify differentially expressed genes (DEGs). Key functional modules and hub genes were analyzed using Cytoscape and R. Active TCM components were identified from literature and the Pharmacopoeia of the People's Republic of China. Enrichment analyses were performed on target genes overlapping with DEGs. Result: From the datasets, 76 upregulated and 363 downregulated genes were identified. Hub genes included SLAMF, CD34, ELN (upregulated) and ATP5F1B, VDAC1, VDAC2, HSPA8, ATP5F1C, PDHA1, UBB, SNCA, YWHAZ, PGK1 (downregulated). Literature review identified 33 active components from 23 herbal medicines. Target gene enrichment and analysis were performed for six components: dihydroartemisinin, berberine, naringenin, calycosin, echinacoside, and icariside II. Conclusion: Mitochondrial to synaptic vesicle dysfunction pathways were enriched in downregulated genes. Despite downregulation, UBB and SNCA proteins accumulate in AD brains. TCM studies suggest curcumin and echinacoside may improve hippocampal pathology and cognitive impairment in AD. Further investigation into their mechanisms is needed.

Tumor hypoxia in immune infiltration and prognosis of bladder cancer.

Background: Bladder cancer (BC) is the sixth most common cancer and the ninth leading cause of cancer death among men in the world. Previous studies have shown that tumor hypoxia plays an important role in the occurrence and development of BC, but the role of tumor hypoxia in the prognosis and immune infiltration of BC remains unclear. Our aim was to perform a bioinformatics analysis combined with a clinical analysis to explore the roles of hypoxia in BC. Methods: We acquired datasets (GSE13507, GSE5287, and GSE1827) containing mRNA expression information from BC cohorts from the Gene Expression Omnibus (GEO) and measured the Hypoxia score using the Gene Set Variation Analysis (GSVA). Then we used X-tile method and log-rank test and Pearson's correlation test to analyze the relation among the Hypoxia score and the clinicopathological and immunological characteristics of BC and used stepwise Cox regression analysis to establish a Prognostic model. Results: Hypoxia was found to be closely associated with tumor grade, pathological type, invasion, and prognosis of BC in our study. Moreover, we determined that hypoxia was closely related to the infiltration abundance of multiple immune cells through a correlation analysis, and the tumor immune cell infiltration was further found to be significantly associated with the tumor grade and tumor type of BC. Furthermore, we constructed several models based on the Hypoxia score and tumor immune infiltration with C-indexes ranging from 0.703 and 0.888, which showed good performance in predicting the prognosis of BC. Conclusions: Our study showed that hypoxia plays an important role in the progression, prognosis, and tumor immune infiltration of BC. Our models based on hypoxia and tumor immune infiltration play a guiding role in the prognosis and treatment of BC patients.

Two hub genes of bipolar disorder, a bioinformatics study based on the GEO database.

Bipolar disorder is a mood illness that affects many people. It has a high recurrence frequency and will cause significant damage to the patient's social function. At present, the pathogenesis of BD is not clear. The National Center for Biotechnology Information (NCBI) established and maintained the Gene Expression Omnibus (GEO) database, a gene expression database. For bioinformatics analysis, researchers can obtain expression data from the internet. At present, the samples of the dataset used in the research of BD are mostly from brain tissue, and the data containing blood samples are rarely used. GEO databases (GSE46416, GSE5388, and GSE5389) were used to retrieve public data, and utilizing the online tool GEO2R, differentially expressed genes (DEGs) were retrieved. The common DEGs between the samples of patients with BD and the samples of the normal population were screened by Venn diagrams. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to perform functional annotation and pathway enrichment analysis of DEGs. A protein-protein interaction network (PPI) was built to investigate hub genes on this basis. There were 117 up-regulated DEGs and 38 down-regulated DEGs discovered, with two hub genes [SRC, CDKN1A] among the up-regulated DEGs. These two hub genes were also highly enriched in the oxytocin signaling pathway, proteoglycans in cancer and bladder cancer, according to KEGG analysis. The results of the receiver operating characteristic curve (ROC) of SRC and CDKN1A in the three datasets strongly suggested that SRC and CDKN1A were potential diagnostic markers of BD. The results strongly suggest that SRC and CDKN1A are related to the pathogenesis of BD.

Characterization of RNA Processing Genes in Colon Cancer for Predicting Clinical Outcomes.

Objective: Colon cancer is associated with multiple levels of molecular heterogeneity. RNA processing converts primary transcriptional RNA to mature RNA, which drives tumourigenesis and its maintenance. The characterisation of RNA processing genes in colon cancer urgently needs to be elucidated. Methods: In this study, we obtained 1033 relevant samples from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to explore the heterogeneity of RNA processing phenotypes in colon cancer. Firstly, Unsupervised hierarchical cluster analysis detected 4 subtypes with specific clinical outcomes and biological features via analysis of 485 RNA processing genes. Next, we adopted the least absolute shrinkage and selection operator (LASSO) as well as Cox regression model with penalty to characterise RNA processing-related prognostic features. Results: An RNA processing-related prognostic risk model based on 10 genes including FXR1, MFAP1, RBM17, SAGE1, SNRPA1, SRRM4, ADAD1, DDX52, ERI1, and EXOSC7 was identified finally. A composite prognostic nomogram was constructed by combining this feature with the remaining clinical variables including TNM, age, sex, and stage. Genetic variation, pathway activation, and immune heterogeneity with risk signatures were also analysed via bioinformatics methods. The outcomes indicated that the high-risk subgroup was associated with higher genomic instability, increased proliferative and cycle characteristics, decreased tumour killer CD8+ T cells and poorer clinical prognosis than the low-risk group. Conclusion: This prognostic classifier based on RNA-edited genes facilitates stratification of colon cancer into specific subgroups according to TNM and clinical outcomes, genetic variation, pathway activation, and immune heterogeneity. It can be used for diagnosis, classification and targeted treatment strategies comparable to current standards in precision medicine. It provides a rationale for elucidation of the role of RNA editing genes and their clinical significance in colon cancer as prognostic markers.

Identification of Key Genes and Signaling Pathways in Entrectinibresistant Non-small Cell Lung Cancer Using Bioinformatic Analysis and Experimental Verification.

BACKGROUND: Entrectinib, a ROS1 inhibitor, is effective in patients with ROS1-positive non-small-cell lung cancer (NSCLC). However, entrectinib resistance remains a challenge worldwide. The biomarkers of entrectinib resistance and molecular mechanisms have not been clarified based on the Gene Expression Omnibus (GEO) database. OBJECTS: The aim of this study is to identify key genes and signaling pathways involved in the development of entrectinib-resistant NSCLC through bioinformatics analysis and experimental validation. METHODS: Differentially expressed genes (DEGs) were screened between entrectinib resistant and parental human NSCLC cell lines of the GSE214715 dataset, lung adenocarcinoma (LUAD) and non-tumor adjacent tissues of the GSE75037 dataset, and NSCLC and non-tumor adjacent tissues of the GSE18842 dataset. Functional enrichment analyses were performed, including Gene Ontology (GO) term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Overlapped DEGs among those three datasets were identified using the Venn diagram package. The transcriptional levels of key genes were investigated using the University of ALabama at Birmingham CANcer data analysis Portal (UALCAN). The association between transcriptional levels of key genes and survival was analyzed using Kaplan-Meier Plotter (https://www.kmplot.com/analysis/). The correlations between hub genes and immune cell infiltration were investigated using the Tumor Immune Estimation Resource (TIMER) database. Specific signaling pathway enrichment analysis was performed using Gene Set Enrichment Analysis (GSEA) of LinkedOmics. Competitive endogenous RNA (ceRNA) networks, genome-wide association studies (GWAS), and drug sensitivity analyses of key genes were further investigated. The expression of ZEB2 was subsequently confirmed in both parental HCC78 cells and entrectinib-resistant HCC78 cells using real-time quantitative polymerase chain reaction (qRT-PCR). RESULTS: 708 DEGs were identified between entrectinib-resistant CUTO28 (CUTO28-ER) and parental CUTO28 cell lines in the GSE214715 dataset. One thousand three hundred and ninety-five DEGs were identified between entrectinib resistant (CUTO37-ER) and parental CUTO37 cell lines in the GSE214715 dataset. Eight hundred and forty-nine DEGs were identified between LUAD and non-tumor adjacent tissues in the GSE75037 dataset. Seven hundred and sevety-three DEGs were identified between NSCLC and non-tumor adjacent tissues in the GSE18842 dataset. Among these three datasets, seven overlapped DEGs were identified, including ZBED2, CHI3L2, CELF2, SEMA5A, ZEB2, S100A12, and PDK4. Among these seven overlapped DEGs, the expression levels of CHI3L2, ZEB2, and S100A12 were downregulated in those three datasets. The results of analysis using the UALCAN database showed that these three genes were significantly downregulated in LUAD and LUSC patients compared with the normal population. However, only the lower transcriptional level of ZEB2 was linked to worse survival in patients with lung cancer. GSEA analysis revealed that ZEB2 was significantly negatively correlated with nucleotide excision repair (NER) in LUAD, and homologous recombination (HR) and NER in LUSC, which were linked to drug resistance. A ceRNA network of THRB-AS1/ has-miR-1293/ ZEB2 in LUAD was established. CONCLUSION: We have identified core genes associated with non-small cell resistance to entrectinib, including CHI3L2, ZEB2, and S100A12. ZEB2 is a core gene associated with acquired resistance to entetinib in NSCLC.

Geo-authentic Tibetan medicine: a traditional pharmacological resource for promoting human health and wellness.

Traditional Tibetan medicine (TTM) is an ancient healing system that has been practiced for more than 2,000 years and involves the use of various medicinal plants for preventing and treating acute mountain sickness, depression, asthma, etc. Geo-authentic medicinal materials, also known as "Daodi herbs" in Chinese, have heightened efficacy and quality relative to their counterparts sourced from alternative geographic locales. In 2024, eight medicinal materials, typified by Cordyceps sinensis Sacc., were listed as geo-authentic Tibetan medicine under the administration of the local government. However, there is no comprehensive review on these geo-authentic TTMs, especially with respect to their pharmacological benefits to human health. This review aims to document the pharmacological properties, phytochemical components, safety, toxicity, and future developments of the geo-authentic TTMs that play essential roles in promoting health and wellness. Plant-derived molecules (i.e., polysaccharides, flavonoids, glycosides, terpenoids, and alkaloids) in the TTMs show therapeutic potentials for the management of both mental and physical health. Finally, the applications and prospects of TTM plants are discussed to support the use of these species in folk medicine for human wellness and to promote public health in modern societies.

Mechanisms Underlying the Therapeutic Effects of Nicotinamide Mononucleotide in Treating High-Fat Diet-induced Hypertrophic Cardiomyopathy based on GEO Datasets, Network Pharmacology, and Molecular Docking.

BACKGROUND: The beneficial effects of nicotinamide mononucleotide (NMN) on heart disease have been reported, but the effects of NMN on high-fat diet-induced hypertrophic cardiomyopathy (HCM) and its mechanisms of action are unclear. In this study, we systematically explored the effects and mechanism of action of NMN in HCM using network pharmacology and molecular docking. METHODS: Active targets of NMN were obtained from SWISS, CNKI, PubMed, DrugBank, BingingDB, and ZINC databases. HCM-related targets were retrieved from GEO datasets combined with GeneCards, OMIM, PharmGKB, and DisGeNET databases. A Protein-Protein Interaction (PPI) network was built to screen the core targets. DAVID was used for GO and KEGG pathway enrichment analyses. The tissue and organ distribution of targets was evaluated. Interactions between potential targets and active compounds were assessed by molecular docking. A molecular dynamics simulation was conducted for the optimal core protein-compound complexes obtained by molecular docking. RESULTS: In total, 265 active targets of NMN and 3918 potential targets of HCM were identified. A topological analysis of the PPI network revealed 10 core targets. GO and KEGG pathway enrichment analyses indicated that the effects of NMN were mediated by genes related to inflammation, apoptosis, and oxidative stress, as well as the FOXO and PI3K-Akt signaling pathways. Molecular docking and molecular dynamics simulations revealed good binding ability between the active compounds and screened targets. CONCLUSION: The possible targets and pathways of NMN in the treatment of HCM have been successfully predicted by this investigation. It provides a novel approach for further investigation into the molecular processes of NMN in HCM treatment.

Assessment of seasonal variations in soil heavy metal concentrations and potential health risks in Gujarat, India.

This study investigates the prevalence, distribution, and ecological consequences of 21 heavy metals (Ag, Al, As, B, Ba, Ca, Cd, Co, Cr, Cu, Fe, Hg, K, Li, Mg, Mn, Na, Ni, Pb, Sr, and Zn) in the soils between the Mahi and Dhadhar rivers in Gujarat, India. It aims to assess the seasonal variations in soil contamination and the potential human health risk associated with the heavy metal exposure through ingestion, inhalation, and dermal contact pathways. Soil samples were collected from 57 sites across three distinct seasons and analyzed using indices such as the geo-accumulation index, contamination factor, pollution load index, ecological risk factor, and global potential ecological risk. Human health risks were also evaluated for carcinogenic and non-carcinogenic effects. The findings reveal significant soil contamination, especially during the Monsoon and Post-Monsoon seasons, with heavy metals like Ag, Cd, Cr, Cu, Co, Ni, and Pb posing considerable ecological threats. Cr and Ni were identified as presenting the highest carcinogenic risks, while Fe and Cr posed major non-carcinogenic challenges. Seasonal variations significantly influenced heavy metal concentrations and distribution patterns. The study highlights the urgent need for comprehensive policies and sustainable practices to mitigate soil contamination and protect environmental health. It emphasizes the critical role of human activities, such as industrial, agricultural, and mining operations, in soil degradation and calls for increased community awareness and action to address these challenges.

Solar Heat Flux Suppression on Optical Antenna of Geosynchronous Earth Orbit Satellite-Borne Lasercom Sensor.

The objective of this article is to examine potential techniques for suppressing solar heat flow on the optical antenna of a laser communication sensor. Firstly, the characteristics of the geosynchronous Earth orbit's (GEO) space radiation environment are analysed, and a combined passive and active thermal control solution is proposed. Secondly, the temperature distribution of the lasercom sensor under extreme operating conditions is simulated utilising IDEAS-TMG (6.8 NX Series) software, which employs Monte Carlo and radiative heat transfer numerical calculation methods. Finally, a strategy for avoiding direct sunlight around midnight is proposed. The simulation results demonstrated that the thermal control solution and solar avoidance strategy proposed in this paper achieved long-term fine-stable control of the temperature field of the optical antenna, which met the thermal permissible communication hours per daily orbit cycle in excess of 14 h per day.

Comprehensive evaluation of disulfidptosis in intestinal immunity and biologic therapy response in Ulcerative Colitis.

Objective: Ulcerative Colitis (UC) manifests as a chronic inflammatory condition of the intestines, marked by ongoing immune system dysregulation. Disulfidptosis, a newly identified cell death mechanism, is intimately linked to the onset and advancement of inflammation. However, the role of disulfidptosis in UC remains unclear. Methods: We screened differentially expressed genes (DEGs) associated with disulfidptosis in multiple UC datasets, narrowed down the target gene number using lasso regression, and conducted immune infiltration analysis and constructed a clinical diagnostic model. Additionally, we explored the association between disulfidptosis-related key genes and disease remission in UC patients receiving biologic therapy. Finally, we confirmed the expression of key genes in FHC cells and UC tissue samples. Results: In the differential analysis, we identified 20 DEGs associated with disulfidptosis. Immune infiltration results revealed that five genes (PDLIM1, SLC7A11, MYH10, NUBPL, OXSM) exhibited strong correlations with immune cells and pathways. Using GO, KEGG and WGCNA analyses, we discovered that gene modules highly correlated with disulfidptosis-related gene expression were significantly enriched in inflammation-related pathways. Additionally, we developed a nomogram based on these five immune-related disulfidptosis genes for UC diagnosis, showing robust diagnostic capability and clinical efficacy. Kaplan-Meier survival analysis revealed a significant link between changes in the expression levels of these cell genes and disease remission in UC patients receiving biologic therapy. In line with previous studies, similar expression changes of the target gene were seen in both UC cell models and tissue samples. Conclusions: This study utilized bioinformatic analysis and machine learning to identify and analyze features associated with disulfidptosis in multiple UC datasets. This enhances our comprehension of the role disulfidptosis plays in intestinal immunity and inflammation in UC, providing new perspectives for developing innovative treatments for UC.

The prognostic and clinical value of genes associate with immunity and amino acid Metabolism in Lung Adenocarcinoma.

Background: Lung adenocarcinoma (LUAD) is the commonest subtype of primary lung cancer. A comprehensive analysis of the association of immunity with amino acid metabolism in LUAD is critical for understanding the disease. Methods: The present study examined LUAD and noncancerous cases from the TCGA database. Differentially expressed genes (DEGs) between LUAD and noncancerous tissues were detected by analyzing processed expression profiles. We cross-referenced the up-regulated DEGs with Immune and Amino Acid Metabolism-related genes (I&AAMGs), resulting in Immune and Amino Acid Metabolism related differentially expressed genes (IAAAMRDEGs). The STRING database was employed to analyze PPI on IAAAMRDEGs, obtaining excavated hub genes, whose biological processes, molecular functions and cellular components were examined with GO/KEGG. Potential mechanisms related to LUAD were investigated by GSEA and GSVA. A prognostic model was built by LASSO-COX analysis, taking into consideration risk scores and prognostic factors to determine biomarkers affecting LUAD occurrence and prognosis. Results: Totally 377 genes were detected at the intersection of upregulated DEGs and I&AAMGs. Analysis of PPI on these 377 IAAAMRDEGs yielded 17 hub genes. A LASSO regression analysis was utilized to assess the prognostic values of the 17 hub genes. Validation using the combined dataset confirmed 4 genes, e.g., polo-like kinase (PLK1), Ribonucleotide Reductase Subunit M2 (RRM2), Thyroid Hormone Receptor Interactor 13 (TRIP13), and Hyaluronan-Mediated Motility Receptor (HHMR). The model's accuracy was further assessed by ROC curve analysis and the COX model. In addition, immunohistochemical staining obtained from the HPA database, revealed enhanced PLK1 expression in LUAD samples. Conclusion: LUAD pathogenesis is highly associated with immunity and amino acid metabolism. The PLK1, RRM2, TRIP13, and HMMR genes have prognostic values for LUAD. PLK1 upregulation in LUAD might be involved in tumorigenesis by modulating the cell cycle and represents a potential prognostic factor in clinic.

[Identification Priority Source of Heavy Metals in Urban Soils Based on Source-specific Ecological Risk Analysis in a Typical Tourist City].

To understand the pollution status, distribution characteristics, and pollution sources of soil heavy metals in tourist cities in northwest China, the soil content of heavy metals As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn in the main areas of Dunhuang City was collected and analyzed. The soil heavy metal pollution level was quantitatively evaluated by the methods of the geo-accumulation index and improved Nemerow pollution index, and the sources of heavy metal pollution were quantitatively analyzed using cluster analysis and the positive matrix factorization （PMF） model. The contribution rate of each pollution source to ecological risk was determined by combining the PMF model and comprehensive ecological risk index. The results showed that except for the mean contents of As and Ni, the mean contents of Cd, Cr, Cu, Hg, Pb, and Zn were all higher than the background values in Gansu Province. However, the average content of the eight elements was lower than the screening value of construction land in the Standard for Soil Pollution Risk Control of Soil Environmental Quality Construction Land （trial） （GB 36600-2018）. Among them, the enrichment of Cd, Pb, and Hg was more serious, and the exceedance rate was higher than 90%. The results of the geo-accumulation index indicated that urban soils were mainly polluted by Hg in the study area, and Cd, Cr, Cu, Pb, and Zn pollution also existed in different degrees. The improved Nemerow pollution index illustrated that the comprehensive pollution degree of the soil was clean to moderate pollution, and the overall pollution was light pollution. Based on the PMF model, we could conclude that soil heavy metals in the study area were affected by natural sources, industrial deposition sources, industrial sources, traffic sources, and comprehensive sources, and the contribution rates were 29.28%, 25.86%, 20.13%, 16.5%, and 8.23%, respectively. The specific source-integrated ecological risk assessment model found that the industrial deposition source contributed the most to the ecological risk in the study area and could be regarded as the priority control pollution source, and Hg was considered to be the priority control pollution element for ecological risk.

Effects of pesticide exposure on the expression of selected genes in normal and cancer samples: Identification of predictive biomarkers for risk assessment.

Pesticides pivotal in controlling pests, can represent a threat for human health. Regulatory agencies constantly monitor their harmful effects, regulating their use. Several studies support a positive association between long-term exposure to pesticides and chronic pathologies, such as cancer. Geno-toxicological biomonitoring has proven to be valuable to assess genetic risks associated with exposure to pesticides, representing a promising tool to improve preventive measures and identify workers at higher risk. In this study, a differential gene expression analysis of 70 candidate genes deregulated upon pesticide exposure, was performed in 10 GEO human gene expression DataSets. It was found that six genes (PMAIP1, GCLM, CD36, SQSTM1, ABCC3, NR4A2) had significant AUC predictive values. Also, CD36 was upregulated in non-transformed cell samples and healthy workers, but downregulated in cancer cells. Further validation in larger groups of workers will corroborate the importance of the identified candidates as biomarkers of exposure/effect.

Vertical Distribution Characteristics and Ecological Risk Assessment of Mercury and Arsenic in Ice, Water, and Sediment at a Cold-Arid Lake.

Mercury and arsenic are two highly toxic pollutants, and many researchers have explored the effects of the two substances on the environment. However, the research content of toxic substances in frozen periods is relatively small. To explore the spatial and vertical distribution of mercury and arsenic in the ice, water, and sediments of Wuliangsuhai Lake under ice conditions, and to assess the harm degree of the two toxic substances to human beings. We collected the ice, water, and sediments of the lake in December 2020, and tested the contents of Hg and As. The single-factor pollution index method, the local cumulative index method, and the ecological risk coding method were used to assess the pollution status in these three environmental media, and the Monte Carlo simulation combined with the quantitative model recommended by USEPA was used to assess the population health risk. The results showed that (1) The average single-factor pollution values of Hg and As in water were 0.367 and 0.114, both pollutants were at clean levels during the frozen period. (2) The mean Igeo values of Hg and As were 0.657 and -0.948. The bioavailability of Hg in the sediments of Wuliangsuhai Lake during the frozen period was high, and its average value was 7.8%, which belonged to the low-risk grade. The bioavailability of As ranged from 0.2% to 3.7%, with an average value of 1.3%. (3) Monte Carlo simulation results indicate acceptable levels of health risks in both water and ice. This study preliminarily investigated the distribution characteristics of toxic substances and their potential effects on human health in lakes in cold and arid regions during the frozen period. It not only clarified the pollution characteristics of lakes in cold and arid regions during the frozen period, but also provided beneficial supplements for the ecological protection of lake basins. This study lays a foundation for further environmental science research in the region in the future.

Unique Coexistence of Two Resistive Switching Modes in a Memristor Device Enables Multifunctional Neuromorphic Computing Properties.

We report on hybrid memristor devices consisting of germanium dioxide nanoparticles (GeO2 NP) embedded within a poly(methyl methacrylate) (PMMA) thin film. Besides exhibiting forming-free resistive switching and an uncommon "ON" state in pristine conditions, the hybrid (nanocomposite) devices demonstrate a unique form of mixed-mode switching. The observed stopping voltage-dependent switching enables state-of-the-art bifunctional synaptic behavior with short-term (volatile/temporal) and long-term (nonvolatile/nontemporal) modes that are switchable depending on the stopping voltage applied. The short-term memory mode device is demonstrated to further emulate important synaptic functions such as short-term potentiation (STP), short-term depression (STD), paired-pulse facilitation (PPF), post-tetanic potentiation (PTP), spike-voltage-dependent plasticity (SVDP), spike-duration-dependent plasticity (SDDP), and, more importantly, the "learning-forgetting-rehearsal" behavior. The long-term memory mode gives additional long-term potentiation (LTP) and long-term depression (LTD) characteristics for long-term plasticity applications. The work shows a unique coexistence of the two resistive switching modes, providing greater flexibility in device design for future adaptive and reconfigurable neuromorphic computing systems at the hardware level.

Accumulated temperature dictates the regional structural variation of prokaryotic periphyton at soil-water interface in paddy fields.

As a pervasive microbial aggregate found at the water-soil interface in paddy fields, periphyton plays crucial roles in modulating nutrient biogeochemical cycling. Consequently, it effectively mitigates non-point source pollution due to its diverse composition. Despite its significance, the mechanisms governing periphyton diversity across different rice planting regions remain poorly understood. To bridge this gap, we investigated periphyton grown in 200 paddy fields spanning 25° of latitude. Initially, we analyzed local diversity and latitudinal variations in prokaryotic communities within paddy field periphyton, identifying 7 abundant taxa, 42 moderate taxa, and 39 rare taxa as the fundamental prokaryotic framework. Subsequently, to elucidate the mechanisms governing periphyton diversity across large scales, we constructed interaction models illustrating triangular relationships among local richness, assembly, and regional variation of prokaryotic subcommunities. Our findings suggest that accumulated temperature-driven environmental filtering partially influences the assembly process of prokaryotes, thereby impacting local species richness and ultimately governing regional structural variations in periphyton. Furthermore, we determined that a latitude of 39° represents the critical threshold maximizing local species richness of periphyton in paddy fields. This study advances our understanding of the factors shaping periphyton geo-imprints and provides valuable insights into predicting their responses to environmental changes, potentially influencing rice production outcomes.

Spatio-temporal characteristics and multi-scenario simulation analysis of ecosystem service value in coastal wetland: A case study of the coastal zone of Hainan Island, China.

Coastal wetland ecosystems harbor rich biodiversity and possess significant ecosystem service value (ESV). Therefore, it offers a range of crucial ecosystem services (ES) for human well-being and socio-economic development. Taking the Hainan Island coastal zone (HICZ) as a case study, the spatio-temporal characteristics of land use and land cover change (LULCC), and its associated ESV in wetland landscapes were analyzed over three time points (2000, 2010 and 2020). We explored the spatio-temporal evolution trajectory of ESV on the basis of geo-information tupu. Then, future land use simulation (FLUS) was employed to predict wetland patterns and ESV under three different scenarios: business as usual (BAU), ecological conservation first (ECF), and economic development first (EDF). The results showed that over the past two decades, a significant proportion (exceeding 80%) of the overall wetland region was comprised of offshore and coastal wetlands (OCW) as well as constructed wetlands (CW); these formed the matrix of the landscape. The area of building land (BL) continued to exhibit a consistent upward trend. Expanding by 2.18 times, it represented the most significant increase in the rate of dynamic changes in BL. The main ES in the HICZ corresponded to the regulation services (53.57%) and the support services (27.58%). The ESV of wetland losses accounted for 45.17% (43.08 × 108 yuan) of the total loss. The spatial differentiation of ESV in the HICZ was larger in the southwest and the northeast regions, while it was comparatively lower in the north. The transformation in the area of early and late change types accounted for 236.46 km2 and 356.69 km2, respectively. The scenario ECF was achieved with an optimal development of ESV (1807.72 × 108 yuan), which was coordinated with the high-level of development of regional ES functions and the economy. These findings provide valuable information for the sustainable development as well as the protection of ecology and environment of the coastal zone under the background of the construction of Hainan pilot free trade zone in the future.

Quantitative analysis of soil quality around brick kilns using pollution indices and ANOVA in Jammu district of Jammu and Kashmir, India.

The study investigated soil quality around brick kilns in the Jammu district of Jammu and Kashmir, analyzing 200 samples from 50 sites for selected parameters such as pH, electrical conductiv1ity, soil temperature, organic carbon content, organic matter, macronutrients, and heavy metals. The findings revealed that soil electrical conductivity ranged from 0.33 to 0.63 dS/m, with significant differences observed at varying distances from the kilns. Copper concentrations were highest at 5.32 mg/kg near the kilns, while iron and lead levels also varied significantly, indicating potential contamination. The mean soil temperature was recorded to be 27.69°C.The pH values ranged from 6.5 to 7.8, and the average pH of 8.22 indicated the slightly alkaline nature of the soil around the brick kilns. The organic carbon ranged from 0.34% to 1.02%.Soil temperature and electrical conductivity decreased with increasing distance from the kilns, with temperature showing positive correlations with organic carbon, organic matter, nitrogen, potassium, manganese, and iron and negative correlations with pH, phosphorus, zinc, copper, lead, and cadmium. A perfect positive correlation was noted among nitrogen, organic carbon, and organic matter. Heavy metals, except for zinc and manganese, showed positive correlations with each other. The average Zn, Cu, Mn, Fe, Pb and Cd concentration was recorded as 1.07, 1.03, 6.71, 10.30, 37.04 and 1.91 ppm, respectively. The contamination factor indicated moderate contamination with lead and cadmium, while the geo-accumulation index also suggested moderate contamination. The pollution load index reflected unpolluted soil and enrichment factor values for heavy metals ranked as Cd > Pb > Cu > Zn > Mn > Fe.ANOVA results revealed significant variations in electrical conductivity, copper, iron, and lead, underscoring the potential environmental impacts at different distances from the kilns. However, no significant differences were found between agricultural and non-agricultural sites in other physicochemical parameters. These variations highlight the considerable impact of brick kilns on soil health, emphasizing the need for enhanced environmental management and further research to mitigate these effects.