Interaction Pathways Research Articles

Promoting Sustainability: Collaborative Governance Pathways for Virtual Water Interactions and Environmental Emissions

This study explores the water consumption and greenhouse gas (GHG) emissions in the Yarkand River Basin, focusing on their dynamic interactions across industrial sectors. Utilizing environmental input–output analysis (IOA), the CROPWAT model, and life cycle assessment (LCA), we quantified the historical evolution of physical and virtual water cycles in relation to the water–carbon nexus. Our findings reveal that the planting industry, particularly the production of export-oriented, water-intensive crops like cotton, significantly contributes to both blue and green water consumption, exacerbating regional water scarcity. The persistent external market demand drives this over-extraction, further strained by the basin’s limited water retention capabilities. Although advancements have been made in reducing the per-unit water footprint of crops, total water consumption continues to rise due to agricultural expansion, intensifying pressure on blue water resources. Additionally, agricultural GHG emissions have surged, driven by increased electricity consumption, heavy fertilizer use, and escalating soil N2O emissions. In light of these challenges, our research underscores the critical need for integrated resource management strategies that align with sustainable development goals. By promoting efficient water allocation within the agricultural sector and diversifying crop structures downstream, we can enhance ecosystem resilience and reduce environmental degradation. Furthermore, the advancement of value-added agricultural processing and the implementation of innovative water conservation technologies are essential for fostering economic sustainability. These strategies not only mitigate the environmental impacts associated with agricultural practices but also strengthen the region’s adaptive capacity in the face of climate change and fluctuating market demands. Our findings contribute to the broader discourse on sustainable agricultural practices, emphasizing the interconnectedness of water management, climate resilience, and economic viability in arid regions.

Shrinkage estimation of gene interaction networks in single-cell RNA sequencing data

BackgroundGene interaction networks are graphs in which nodes represent genes and edges represent functional interactions between them. These interactions can be at multiple levels, for instance, gene regulation, protein-protein interaction, or metabolic pathways. To analyse gene interaction networks at a large scale, gene co-expression network analysis is often applied on high-throughput gene expression data such as RNA sequencing data. With the advance in sequencing technology, expression of genes can be measured in individual cells. Single-cell RNA sequencing (scRNAseq) provides insights of cellular development, differentiation and characteristics at the transcriptomic level. High sparsity and high-dimensional data structures pose challenges in scRNAseq data analysis.ResultsIn this study, a sparse inverse covariance matrix estimation framework for scRNAseq data is developed to capture direct functional interactions between genes. Comparative analyses highlight high performance and fast computation of Stein-type shrinkage in high-dimensional data using simulated scRNAseq data. Data transformation approaches also show improvement in performance of shrinkage methods in non-Gaussian distributed data. Zero-inflated modelling of scRNAseq data based on a negative binomial distribution enhances shrinkage performance in zero-inflated data without interference on non zero-inflated count data.ConclusionThe proposed framework broadens application of graphical model in scRNAseq analysis with flexibility in sparsity of count data resulting from dropout events, high performance, and fast computational time. Implementation of the framework is in a reproducible Snakemake workflow https://github.com/calathea24/ZINBGraphicalModel and R package ZINBStein https://github.com/calathea24/ZINBStein.

S100A16 stabilizes the ITGA3‑mediated ECM‑receptor interaction pathway to drive the malignant properties of lung adenocarcinoma cells via binding MOV10.

Lung adenocarcinoma (LUAD) is highly associated with lung cancer‑associated mortality. Notably, S100 calcium‑binding protein A16 (S100A16) has been increasingly considered to have prognostic value in LUAD; however, the underlying mechanism remains unknown. In the present study, S100A16 expression levels in LUAD tissues and cells were respectively analyzed by the UALCAN database and western blotting. Cell Counting Kit‑8 and 5‑ethynyl‑2'‑deoxyuridine assays were used to examine cell proliferation, whereas wound healing, Transwell and tube formation assays were used to assess cell migration, invasion and angiogenesis, respectively. Western blotting was also used to examine the expression levels of proteins associated with metastasis, angiogenesis, focal adhesion and the extracellular matrix (ECM)‑receptor interaction pathways. The relationship between S100A16 and Mov10 RNA helicase (MOV10) was predicted by bioinformatics tools, and was verified using a co‑immunoprecipitation assay. Furthermore, the interaction between MOV10 and integrin α3 (ITGA3) was verified by RNA immunoprecipitation assay, and the actinomycin D assay was used to detect ITGA3 mRNA stability. The results demonstrated that S100A16 expression was increased in LUAD tissues and cell lines, and was associated with unfavorable outcomes. Knocking down S100A16 expression hindered the proliferation, migration, invasion and angiogenesis of LUAD cells. Furthermore, S100A16 was shown to bind to MOV10 and positively modulate MOV10 expression in LUAD cells, while MOV10 overexpression partially reversed the suppressive role of S100A16 knockdown on the aggressive phenotypes of LUAD cells. Furthermore, it was demonstrated that S100A16 regulated the stability of ITGA3 mRNA via MOV10 to mediate ECM‑receptor interactions. In conclusion, S100A16 may bind to MOV10 to stabilize ITGA3 mRNA and regulate ECM‑receptor interactions, hence contributing to the malignant progression of LUAD.

Metabolite profiling and transcriptome analyses reveal defense regulatory network against pink tea mite invasion in tea plant

BackgroundThe tea plant Camellia sinensis (L.) O. Kuntze is a perennial crop, invaded by diversity of insect pest species, and pink tea mite is one of the most devastating pests for sustainable tea production. However, molecular mechanism of defense responses against pink tea mites in tea is still unknown. In this study, metabolomics and transcriptome profiles of susceptible and resistant tea varieties were compared before and after pink tea mite infestation.ResultsMetabolomics analysis revealed that abundance levels of polyphenol-related compounds changed significantly before and after infestation. At the transcript level, nearly 8 GB of clean reads were obtained from each sequenced library, and a comparison of infested plants of resistant and susceptible tea varieties revealed 9402 genes with significant differential expression. An array of genes enriched in plant pathogen interaction and biosynthetic pathways of phenylpropanoids showed significant differential regulation in response to pink tea mite invasion. In particular, the functional network linkage of disease resistant proteins, phenylalanine ammonia lyase, flavanone -3-hydroxylase, hydroxycinnamoyl-CoA shikimate transferase, brassinosteroid-6-oxidase 1, and gibberellin 2 beta-dioxygenase induced dynamic defense signals to suppress prolonged pink tea mite attacks. Further integrated analyses identified a complex network of transcripts and metabolites interlinked with precursors of various flavonoids that are likely modulate resistance against to pink tea mite.ConclusionsOur results characterized the profiles of insect induced metabolic and transcript reprogramming and identified a defense regulatory network that can potentially be used to fend off pink tea mites damage.

Weighted Gene Co-Expression Network Analysis Uncovers Critical Genes and Pathways Involved in Soybean Response to Soybean Mosaic Virus

Background: Soybean mosaic virus (SMV) is a globally prevalent and detrimental virus that belongs to the Potyvirus genus. Pathogenic viruses of this genus are typically linear in shape, with dimensions ranging between 630 and 750 nm, and are composed of single-stranded RNA and proteins. We have developed an SMV-resistant soybean line, Dongnong 93-046, which has no significant changes in disease resistance identification in the adult plants and has neat grains with no obvious brown or black markings. To explore the defense mechanisms of soybean against SMV, we performed comparative transcriptomic sequencing of the leaves between the Dongnong 93-046 inoculated with SMV at 8 h (T) and the non-inoculated control (C) on the HiSeq2000 platform. In addition, we performed non-targeted metabolomic sequencing of leaves from the treatment and control groups. Results: We identified a total of 41,189 differentially expressed genes (DEGs). A total of 9809 differentially expressed genes (DEGs) met the criteria of |Log2FC (Fold Change)| ≥ 1 and adjusted p-value ≤ 0.001. Among the 41,189 DEGs identified, 9196 exhibited FPKM values greater than 10. KEGG pathway enrichment analysis of the 9809 DEGs revealed significant enrichment of genes involved in resistance-related pathways such as plant–pathogen interaction, linoleic acid metabolism, mitogen-activated protein kinase (MAPK) signaling pathway, and plant hormone signaling transduction. Functional analysis using MapMan software identified multiple DEGs that were associated with pathways such as jasmonate synthesis and phenylpropanoid biosynthesis. Weighted gene co-expression network analysis (WGCNA) using the differential metabolites and the 9196 DEGs revealed a strong correlation between gene clusters within the Turquoise module and the content of jasmonate-related metabolites. Further functional enrichment analysis of the 894 genes within the gene clusters showed a significant and repeated enrichment of pathways related to plant–pathogen interaction, linoleic acid metabolism, and plant hormone signaling transduction. Subsequent focused pathway analysis identified key genes involved in plant hormone signaling transduction pathways, such as the jasmonate ZIM domain protein Glyma.16G010000, the gene Glyma.01G235600 encoding the essential diterpene reductase required for jasmonate synthesis in the jasmonate biosynthesis pathway, and the transcription factor Glyma.02G232600 involved in the plant–pathogen interaction pathway, among others. This study provides a theoretical framework for understanding the resistance mechanism of soybean cultivar Dongnong 93-046 against the SMV N1 strain, offers potential gene resources for breeding soybean varieties with resistance to SMV, and paves the way for new strategies to control SMV infection, enhance resistance, and improve crop yield and quality.

High expression of CNOT6L contributes to the negative development of type 2 diabetes.

Type 2 diabetes (T2D) is a chronic metabolic disorder characterized by reduced responsiveness of body cells to insulin, leading to elevated blood sugar levels. CNOT6L is involved in glucose metabolism, insulin secretion regulation, pancreatic beta-cell proliferation, and apoptosis. These functions may be closely related to the pathogenesis of T2D. However, the exact molecular mechanisms linking CNOT6L to T2D remain unclear. Therefore, this study aims to elucidate the role of CNOT6L in T2D. The T2D datasets GSE163980 and GSE26168 profiles were downloaded from the Gene Expression Omnibusdatabase generated by GPL20115 and GPL6883.The R package limma was used to screen differentially expressed genes (DEGs). A weighted gene co-expression network analysis was performed. Construction and analysis of the protein-protein interaction (PPI) network, functional enrichment analysis, gene set enrichment analysis, and comparative toxicogenomics database (CTD) analysis were performed. Target Scan was used to screen miRNAs that regulate central DEGs. The results were verified by reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR), western blotting (WB), and blood glucose measurements in mice. A total of 1951 DEGs were identified. GO and KEGG enrichment analysis revealed that differentially expressed genes were mainly enriched in the insulin signaling pathway, ECM-receptor interaction, and PPAR signaling pathway. Metascape analysis indicated enrichment primarily in the cAMP signaling pathway and enzyme-linked receptor protein signaling pathway. WGCNA analysis yielded 50 intersecting genes. PPI network construction and algorithm identification identified two core genes (CNOT6L and GRIN2B), among which CNOT6L gene was associated with multiple miRNAs. CTD analysis revealed associations of core genes with type 2 diabetes, diabetic complications, dyslipidemia, hyperglycemia, and inflammation. WB and RT-qPCR results showed that in different pathways, CNOT6L protein and mRNA levels were upregulated in type 2 diabetes. CNOT6L is highly expressed in type 2 diabetes mellitus, and can cause diabetes complications, inflammation and other physiological processes by regulating miRNA, PPAR and other related signaling pathways, with poor prognosis. CNOT6L can be used as a potential therapeutic target for type 2 diabetes.

Auranofin as a Novel Anticancer Drug for Anaplastic Thyroid Cancer.

Background/Objectives: Anaplastic thyroid cancer (ATC) is an aggressive and rare cancer with a poor prognosis, and traditional therapies have limited efficacy. This study investigates drug repositioning, focusing on auranofin, a gold-based drug originally used for rheumatoid arthritis, as a potential treatment for ATC. Methods: Auranofin was identified from an FDA-approved drug library and tested on two thyroid cancer cell lines, 8505C and FRO. Antitumor efficacy was evaluated through gene and protein expression analysis using Western blot, FACS, and mRNA sequencing. In vivo experiments were conducted using subcutaneous injections in nude mice to confirm the anticancer effects of auranofin. Results: Auranofin induced reactive oxygen species (ROS) production and apoptosis, leading to a dose-dependent reduction in cell viability, G1/S phase cell cycle arrest, and altered expression of regulatory proteins. It also inhibited cancer stem cell activity and suppressed epithelial-mesenchymal transition. mRNA sequencing revealed significant changes in the extracellular matrix-receptor interaction pathway, supported by Western blot results. In vivo xenograft models demonstrated strong antitumor activity. Conclusions: Auranofin shows promise as a repurposed therapeutic agent for ATC, effectively inhibiting cell proliferation, reducing metastasis, and promoting apoptosis. These findings suggest that auranofin could play a key role in future ATC treatment strategies.

Radixin: Roles in the Nervous System and Beyond.

Radixin is an ERM family protein that includes radixin, moesin, and ezrin. The importance of ERM family proteins has been attracting more attention, and studies on the roles of ERM in biological function and the pathogenesis of some diseases are accumulating. In particular, we have found that radixin is the most dramatically changed ERM protein in elevated glucose-treated Schwann cells. We systemically review the literature on ERM, radixin in focus, and update the roles of radixin in regulating cell morphology, interaction, and cell signaling pathways. The potential of radixin as a therapeutic target in neurodegenerative diseases and cancer was also discussed. Radixin research has focused on its cell functions, activation, and pathogenic roles in some diseases. Radixin and other ERM proteins maintain cell shape, growth, and motility. In the nervous system, radixin has been shown to prevent neurodegeneration and axonal growth. The activation of radixin is through phosphorylation of its conserved threonine residues. Radixin functions in cell signaling pathways by binding to membrane proteins and relaying the cell signals into the cells. Deficiency of radixin has been involved in the pathogenic process of diseases in the central nervous system and diabetic peripheral nerve injury. Moreover, radixin also plays a role in cell growth and drug resistance in multiple cancers. The trials of therapeutic potential through radixin modulation have been accumulating. However, the exact mechanisms underlying the roles of radixin are far from clarification. Radixin plays various roles in cells and is involved in developing neurodegenerative diseases and many types of cancers. Therefore, radixin may be considered a potential target for developing therapeutic strategies for its related diseases. Further elucidation of the function and the cell signaling pathways that are linked to radixin may open the avenue to finding novel therapeutic strategies for diseases in the nervous system and other body systems.

Seasonal environmental fluctuations alter the transcriptome dynamics of oocytes and granulosa cells in beef cows

BackgroundExamining the mechanistic cellular responses to heat stress could aid in addressing the increasing prevalence of decreased fertility due to elevated ambient temperatures. Here, we aimed to study the differential responses of oocytes and granulosa cells to thermal fluctuations due to seasonal differences. Dry beef cows (n = 10) were housed together, synchronized and subjected to a stimulation protocol to induce follicular growth before ovum pick-up (OPU). Two OPU’s were conducted (summer and winter) to collect cumulus-oocyte-complexes (COCs) and granulosa cells. In addition, rectal temperatures and circulating blood samples were collected during OPU. Oocytes were separated from the adherent cumulus cells, and granulosa cells were isolated from the collected OPU fluid. RNA was extracted from pools of oocytes and granulosa cells, followed by library preparation and RNA-sequencing. Blood samples were further processed for the isolation of plasma and leukocytes. The transcript abundance of HSP70 and HSP90 in leukocytes was evaluated using RT-qPCR, and plasma cortisol levels were evaluated by immunoassay. Environmental data were collected daily for three weeks before each OPU session. Data were analyzed using MIXED, Glimmix or GENMOD procedures of SAS, according to each variable distribution.ResultsAir temperatures (27.5 °C vs. 11.5 °C), average max air temperatures (33.7 °C vs. 16.9 °C), and temperature-humidity indexes, THI (79.16 vs. 53.39) were shown to contrast significantly comparing both the summer and winter seasons, respectively. Rectal temperatures (Summer: 39.2 ± 0.2 °C; Winter: 38.8 ± 0.2 °C) and leukocyte HSP70 transcript abundance (Summer: 4.18 ± 0.47 arbitrary units; Winter: 2.69 ± 0.66 arbitrary units) were shown to increase in the summer compared to the winter. No visual differences persisted in HSP90 transcript abundance in leukocytes and plasma cortisol concentrations during seasonal changes. Additionally, during the summer, 446 and 940 transcripts were up and downregulated in oocytes, while 1083 and 1126 transcripts were up and downregulated in the corresponding granulosa cells, respectively (Fold Change ≤ -2 or ≥ 2 and FDR ≤ 0.05). Downregulated transcripts in the oocytes were found to be involved in ECM-receptor interaction and focal adhesion pathways, while the upregulated transcripts were involved in protein digestion and absorption, ABC transporters, and oocyte meiosis pathways. Downregulated transcripts in the granulosa cells were shown to be involved in cell adhesion molecules, chemokine signaling, and cytokine-cytokine receptor interaction pathways, while those upregulated transcripts were involved in protein processing and metabolic pathways.ConclusionIn conclusion, seasonal changes dramatically alter the gene expression profiles of oocytes and granulosa cells in beef cows, which may in part explain the seasonal discrepancies in pregnancy success rates during diverging climatic weather conditions.

Ultrasound as a Physical Elicitor to Improve Texture in Blueberry Fruit: Physiological Indicator and Transcriptomic Analysis.

Ultrasound (US) washing has been verified to improve the quality of postharvest blueberry fruit. However, its physiological and molecular mechanisms remain largely unknown. In the present study, an US with a frequency of 25 kHz and a power density of 400 W for 2 min was performed to investigate its role in impacting the quality of blueberries. The results showed that US washing improved the quality of blueberries, with a higher firmness and lignin content (p < 0.05) than the control. Moreover, US washing inhibited the levels of superoxide radical (O2·-) production rate and hydrogen peroxide (H2O2) content while stimulating the superoxide dismutase (SOD) and catalase (CAT) activities of the blueberry fruit. Transcriptomic analysis screened 163 differentially expressed genes (DEGs), and the key DEGs were mainly enriched in phenylpropanoid biosynthesis, flavonoid biosynthesis, and plant-pathogen interaction pathways. Furthermore, the transcription factors and the structural genes associated with lignin biosynthesis were also identified from the DEGs. More importantly, the correlation analysis revealed that firmness and lignin content were positively correlated with the expression of C4H, COMT1, and POD52 in blueberry fruit, indicating that these genes might be involved in the regulation of US-mediated lignin synthesis. The findings provide new insight into the US-enhanced quality of blueberry fruits.

Comparison of Whey N-Glycoproteins in Yak Colostrum and Mature Milk Based on 4D Label-Free Technology.

Whey proteins are N-glycosylated proteins that play important roles in a variety of biological processes including immune defense. However, the N-glycosylation of yak colostrum (YC) and mature milk (YM) whey proteins is unknown. Therefore, this study systematically compared and analyzed YC and YM whey N-glycoproteomes using the 4D label-free technique. We identified 162 glycoproteins, 222 glycosylated peptides, and 234 glycosylation sites in YC and YM, of which 59 glycoproteins were differentially expressed in YC and YM. According to gene ontology annotation and KEGG pathway metabolism analysis, the differentially expressed N-glycoproteins were highly enriched in "cell adhesion", "extracellular region", and "calcium binding", and were mainly involved in the extracellular matrix (ECM)-receptor interaction pathway. The immunity-related N-glycoproteins, such as platelet glycoprotein 4 (CD36) and polymeric immunoglobulin receptor (PIGR), were observed to be different between YC and YM. The results revealed the glycosylation sites, composition, and biological functions of YC and YM whey N-glycoprotein, which supplemented our understanding of the N-glycosylation of yak whey proteins.

Multi-Target Mechanisms of Si-Ni-San on Anxious Insomnia: An Example of Network-pharmacology and Molecular Docking Analysis.

Based on comprehensive network-pharmacology and molecular docking analysis, this study was intended to unveil the multiple mechanisms of Si-Ni-San (SNS) in treating anxious insomnia. The compounds of SNS were meticulously analyzed, selected and standardized with references to their pharmacological attributes. The components included chaihu (Bupleurum chinense DC.), baishao (Paeonia lactiflora Pall.), zhishi (Citrus aurantium L.) and gancao (Glycyrrhiza uralensis Fisch. ex DC.). We used the Traditional Chinese Medicine System Pharmacology (TCMSP) Database, Traditional Chinese Medicines Integrated Database (TCMID), GeneCards database, therapeutic target database (TTD) and comparative toxicogenomic database (CTD) to construct the components-compounds-targets networks and used Cytoscape 3.9.1 software to visualize the outcome. Afterwards, the STRING database and Cytoscape 3.9.1 software were utilized to construct and visualize the protein-protein interaction (PPI) network analysis. In addition, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were also conducted through the Database for Annotation, Visualization, and Integrated Discovery (DAVID). The molecular docking program was carried out using AutoDock 4.2 software to understand interactions between target receptors and compound ligands selected for study. We thoroughly sorted and filtered 31 pharmacologically active compounds from SNS. Subsequently, several potential target genes were predicted, of which there were 59 target genes distinctly associated with anxious insomnia. The PPI analysis indicated that the core target proteins included AKT1, IL6, TNF, SLC6A4, MAOA and GABRA2. The results of our study indicated that SNS potentially remediates anxious insomnia by reducing inflammation, neurodegeneration, and cell apoptosis of neurons. In addition, GO and KEGG enrichment analysis results indicated that SNS could modulate multiple aspects of anxious insomnia through mechanisms related to pathways of neuroactive ligand-receptor interaction. These pathways include various kinds of synaptic transmission pathways, and anti-inflammatory activity associated with response pathways. When we compared the components-compounds-targets networks and the compounds-targets-synaptic pathways networks, the five active compounds, including beta-Sitosterol, Kaempferol, Tetramethoxyluteolin, Isorhamnetin and Shinpterocarpin, were selected to conduct molecular docking experiments. Eleven target proteins, (AKT1, SLC6A4, ADRB2, MAOA, ACHE, ESR1, CYP3A4, CHRNA7, GABRA2, HTR2A and NOS3), which also play significant roles in regulating serotonergic, cholinergic, dopaminergic and GABAergic systems in the PPI network, were selected to act as receptors in molecular docking trials. The results showed that docking pairs isorhamnetin-AKT1, isorhamnetin-SLC6A4, β-sitosterol-MAOA, β- sitosterol-ACHE, isorhamnetin-CHRNA7 and shinpterocarpin-GABRA2 provided the most stable conformations of ligand-receptor binding between key compounds and core target proteins in the SNS. In the study, we offer a computational result, revealing that SNS may alleviate sleep disorders associated with anxiety through a "multi-compounds, multi-targets, and multi-pathways" mechanism. The network-pharmacology and molecular docking outcomes could theoretically confirm the anti-anxiety and anti-insomnia effects of SNS. Although this research is purely statistical and systematic without empirical validation, it serves as a stepping stone and cornerstone for subsequent experimental investigations.

The long non-coding RNA GAS5 contributes to the suppression of inflammatory responses by inhibiting NF-κB activity.

Nuclear factor kappa B (NF-κB) is a key regulator of immune and inflammatory responses. Glucocorticoid drugs (GC) act through the glucocorticoid receptor (GR) as immunosuppressant also in pediatric patients inhibiting NF-κB activity. The long non-coding RNA GAS5 interacts with the GR, influencing GC activity. No data on the role of GAS5 on GR-dependent inhibition of NF-κB activity have been published. This study investigated the impact of GAS5 on NF-κB activity in HeLa cells overexpressing GAS5, both under basal conditions and during GC treatment. The study used EMSA, RNA-immunoprecipitation (RIP), Western blotting, and bioinformatic analyses to assess NF-κB DNA binding, GAS5-p65 interaction, and NF-κB signaling pathway modulation. GAS5 overexpression increased NF-κB DNA binding activity in untreated cells. RNA-IP confirmed a direct interaction between GAS5 and the NF-κB subunit p65, suggesting a potential regulatory mechanism. GAS5 overexpression led to downregulation of NF-κB target genes, TNF-α, and NR3C1. GC treatment reduced NF-κB DNA binding activity in GAS5-overexpressing cells, indicating a potential synergistic effect. Furthermore, GAS5 overexpression increased IκB levels and reduced p-p65/pan-p65 levels during GC treatment. GAS5 appears to modulate NF-κB activity in a complex manner, influencing both basal and GC-induced signaling. The interaction between GAS5, GCs, and NF-κB is multi-faceted, and further research is needed to fully elucidate the underlying mechanisms. These findings suggest that GAS5 could be a potential target for personalized therapy, particularly in pediatric patients with inflammatory conditions.

Differential expression and significance of cytokines in cerebrospinal fluid of patients with viral encephalitis

To extensively identify cerebrospinal fluid (CSF) cytokine profiles related to the occurrence, development and prognosis of viral encephalitis (VE) patients by using a high-throughput proteomic approach.We measured 80 cytokines in the CSF of acute-phase VE patients (n = 11) using high-throughput protein chip technology, comparing them to controls (n = 6). ELISA validated these findings and assessed additional cytokines from prior literature in a larger cohort (15 VE patients, 15 controls). Correlations between biomarkers and clinical characteristics were also examined.In the initial stage, we identified two differentially expressed cytokines: cathepsin-L (CTSL), which was up-regulated, and Fractalkine, which was down-regulated. Functional enrichment analysis revealed that these proteins are linked to inflammation, apoptosis, autophagy, and blood-brain barrier disruption. In stage2, the elevations of cathepsin-L (CTSL), fractalkine, interleukin-6 (IL-6), IL-1β, macrophage migration inhibitory factor (MIF), tumor necrosis factor-α (TNF-α), insulin-like growth factor Ⅱ (IGF-2) and CXC chemokine ligand 10 (CXCL10) in VE were validated by ELISA. The results of linear regression indicated that these cytokines was positively correlated with CSF reactive lesions (p < 0.05).In this study, some biomarkers related with CSF level changes and prognosis were obtained. Although these cytokines are not specific, they may be related to the occurrence and development of VE. CTSL, MIF, IL-1β, TNF-α and CXCL10 can be used as VE potential biomarkers. These cytokines may participate in the pathogenesis of VE through inflammatory response, cell apoptosis, autophagy, blood-brain barrier disruption and cytokine-cytokine receptor interaction pathway.

Self-organizing maps of unbiased ligand-target binding pathways and kinetics.

The interpretation of ligand-target interactions at atomistic resolution is central to most efforts in computational drug discovery and optimization. However, the highly dynamic nature of protein targets, as well as possible induced fit effects, makes difficult to sample many interactions effectively with docking studies or even with large-scale molecular dynamics (MD) simulations. We propose a novel application of Self-Organizing Maps (SOMs) to address the sampling and dynamic mapping tasks, particularly in cases involving ligand flexibility and induced fit. The SOM approach offers a data-driven strategy to create a map of the interaction process and pathways based on unbiased MD. Furthermore, we show how the preliminary SOM mapping is complementary to kinetic analysis, with the employment of both network-based approaches and Markov state models. We demonstrate the method by comprehensively mapping a large dataset of 640 μs of unbiased trajectories sampling the recognition process between the phosphorylated YEEI peptide and its high-specificity target lck-SH2. The integration of SOM into unbiased simulation protocols significantly advances our understanding of the ligand binding mechanism. This approach serves as a potent tool for mapping intricate ligand-target interactions with unprecedented detail, thereby enhancing the characterization of kinetic properties crucial to drug design.

Identification of novel hub genes and immune infiltration in atopic dermatitis using integrated bioinformatics analysis

The aim of this study was to identify key genes and investigate the immunological mechanisms of atopic dermatitis (AD) at the molecular level via bioinformatics analysis. Gene expression profiles (GSE32924, GSE107361, GSE121212, and GSE230200) were obtained for screening common differentially expressed genes (co-DEGs) from the gene expression omnibus database. Functional enrichment analysis, protein–protein interaction network and module construction, and identification of common hub genes were performed. Hub genes were validated using receiver operating characteristic curve analysis based on GSE130588 and GSE16161. NetworkAnalyst was used to detect microRNAs (miRNAs) and transcription factors (TFs) associated with the hub genes. The immune cell infiltration was analyzed using the CIBERSORT algorithm to further analyze the correlation between hub genes and immune cells. A total of 146 co-DEGs were obtained, showing significant enrichment in cytokine–cytokine receptor interaction and JAK-STAT signaling pathway. Seven hub genes were identified by Cytoscape and validated with external datasets. Subsequent prediction of miRNAs and TFs targeting these hub genes revealed their regulatory roles. Analysis of immune cell infiltration and correlation revealed a significant positive correlation between CCL22 expression and the number of dendritic cells activated. The identified hub genes represent potential diagnostic and therapeutic targets in the immunological pathogenesis of AD.

The relationship between COMT, proline, and negative symptoms in clinical high risk and recent psychosis onset

Individuals at clinical high-risk (CHR) of developing psychosis, as well as patients with recent psychosis onset (RO), experience significant negative symptoms that detrimentally impact daily-life functioning and are associated with poor outcomes, even in those who do not convert to psychosis. Targeting negative symptoms may thus hold promise for the treatment of CHR and RO patients. Building from previous findings we examined whether the catechol-O-methyltransferase (COMT) Val158Met functional polymorphism and fasting peripheral proline concentration predicts the severity of negative symptoms experienced by adolescents and young adults at CHR or those with RO. As hypothesized, the interaction between fasting plasma proline and COMT predicted negative symptoms, as measured via the Scale for the Assessment of Negative Symptoms (SANS) total (n = 50, β = 0.066, adjusted p = 0.007) and global severity scores (n = 50, coefficient = 0.026, adjusted p = 0.003): Higher proline was beneficial for Val/Val subjects, but detrimental to those with the Met allele. In a secondary analysis, the COMT x proline interaction also predicted symptoms measured via the Clinical Assessment Interview for Negative Symptoms (CAINS) total scores (n = 50, β-coefficient = 0.035, adjusted p = 0.044), although this result did not reach the Benjamini-Hochberg’s threshold for significance. Further, there was a trend towards significance for an association with social and interpersonal function (Global Functioning-Social, coefficient = −0.005, adjusted p = 0.055). Negative symptoms are intractable and largely unaddressed by current medications. This study further supports a relationship between peripheral proline and COMT influencing negative symptoms such as anhedonia, in young CHR individuals and those with RO. That higher proline has converse effects on symptoms by COMT may have implications for the development of therapeutics to intervene early and specifically target the interaction pathway.

LDH nanoparticles-doped cellulose nanofiber scaffolds with aligned microchannels direct high-efficiency neural regeneration and organized neural circuit remodeling through RhoA/Rock/Myosin II pathway

Spinal cord injury (SCI) triggers interconnected malignant pathological cascades culminating in structural abnormalities and composition changes of neural tissues and impairs spinal cord tissue function. Cellulose nanofibers (CNF) have considerable potential in mimicking tissue microstructure for nerve regeneration, but the effectiveness of CNF in repairing SCI remains poorly understood. In this study, we designed a Mg–Fe layered double hydroxide (LDH)-doped cellulose nanofiber (CNF) scaffold with aligned intact microchannels and homogeneously distributed pores (CNF-LDH), loaded with retinoic acid and sonic hedgehog (CNF-LDH-RS) for neuroregeneration. The aligned microchannel structure and chemical cues in the scaffold were designed further to enhance the differentiation of neural stem cells towards neurons and promote axon growth while inhibiting differentiation to astrocytes. Transplanting the scaffolds into a completely transected SCI mice model dramatically improved behavioral and electrophysiological outcomes underpinned by robust neuronal regeneration, significant axonal growth and orderly neural circuit remodeling. RNA-seq analysis revealed the pivotal roles of the RhoA/Rock/Myosin II pathway and neuroactive ligand-receptor interaction pathway in SCI repair by CNF-LDH-RS. Particularly, Myosin II emerged as a key gene for functional recovery, and its effect on negative regulation of axon growth was suppressed by the scaffolds, resulting in a distinctly oriented growth of the axons along the microchannel structure. The results indicate that CNF-LDH scaffolds rationally combined with physical and biochemical cues create promising tissue-engineered substrates to facilitate the repair of spinal cord injury.

Ultrafast four-wave-mixing spectroscopy with two vacuum fields and coincidence-double-heterodyne detection

In classical macroscopic ultrafast optical four-wave mixing signals, phase matching selects three classes of light–matter interaction pathways: double quantum coherence; non-rephasing; and photon-echo. Multiple pathways contribute to each of these signals. We show that a coincidence-double-heterodyne detection scheme that employs two classical and two vacuum fields can isolate a single pathway contribution to each of these signals. We further demonstrate the advantage of the proposed technique by comparing it with the classical photon-echo signal for a model Frenkel-exciton dimer.

Female-specific mechanisms of meiotic initiation and progression in mammalian oocyte development.

Meiosis is regulated in sexually dimorphic manners in mammals. In females, the commitment to and entry into meiosis are coordinated with the developmental program of oocytes. Female germ cells initiate meiosis within a short time window during the fetal period and then undergo meiotic arrest until puberty. However, the genetic mechanisms underlying the orchestration of oocyte development and meiosis to maximize the reproductive lifespan of mammalian females remain largely elusive. While meiotic initiation is regulated by a sexually common mechanism, where meiosis initiator and Stimulated by Retinoic Acid Gene 8 (STRA8) activate the meiotic genes, the female-specific mode of meiotic initiation is mediated by the interaction between retinoblastoma (RB) and STRA8. This review highlights the female-specific mechanisms of meiotic initiation and meiotic prophase progression in the context of oocyte development. Furthermore, the downstream pathway of the RB-STRA8 interaction that may regulate meiotic arrest will be discussed in the context of oocyte development, highlighting a potential genetic link between the female-specific mode of meiotic entry and meiotic arrest.