Deciphering the role of HLF in idiopathic orbital inflammation: integrative analysis via bioinformatics and machine learning techniques.

Idiopathic orbital inflammation, formerly known as NSOI (nonspecific orbital inflammation), is characterized as a spectrum disorder distinguished by the polymorphic infiltration of lymphoid tissue, presenting a complex and poorly understood etiology. Recent advancements have shed light on the HLF (Human lactoferrin), proposing its critical involvement in the regulation of hematopoiesis and the maintenance of innate mucosal immunity. This revelation has generated significant interest in exploring HLF's utility as a biomarker for NSOI, despite the existing gaps in our understanding of its biosynthetic pathways and operational mechanisms. Intersecting multi-omic datasets-specifically, common differentially expressed genes between GSE58331 and GSE105149 from the Gene Expression Omnibus and immune-related gene compendiums from the ImmPort database-we employed sophisticated analytical methodologies, including Lasso regression and support vector machine-recursive feature elimination, to identify HLF. Gene set enrichment analysis and gene set variation analysis disclosed significant immune pathway enrichment within gene sets linked to HLF. The intricate relationship between HLF expression and immunological processes was further dissected through the utilization of CIBERSORT and ESTIMATE algorithms, which assess characteristics of the immune microenvironment, highlighting a noteworthy association between increased HLF expression and enhanced immune cell infiltration. The expression levels of HLF were corroborated using data from the GSE58331 dataset, reinforcing the validity of our findings. Analysis of 218 HLF-related differentially expressed genes revealed statistically significant discrepancies. Fifteen hub genes were distilled using LASSO and SVM-RFE algorithms. Biological functions connected with HLF, such as leukocyte migration, ossification, and the negative regulation of immune processes, were illuminated. Immune cell analysis depicted a positive correlation between HLF and various cells, including resting mast cells, activated NK cells, plasma cells, and CD8 T cells. Conversely, a negative association was observed with gamma delta T cells, naive B cells, M0 and M1 macrophages, and activated mast cells. Diagnostic assessments of HLF in distinguishing NSOI showed promising accuracy. Our investigation delineates HLF as intricately associated with NSOI, casting light on novel biomarkers for diagnosis and progression monitoring of this perplexing condition.

Elucidating the pan-oncologic landscape of S100A9: prognostic and therapeutic corollaries from an integrative bioinformatics and Mendelian randomization analysis.

The calcium-binding protein S100A9 has emerged as a pivotal biomolecular actor in oncology, implicated in numerous malignancies. This comprehensive bioinformatics study transcends traditional boundaries, investigating the prognostic and therapeutic potential of S100A9 across diverse neoplastic entities. Leveraging a wide array of bioinformatics tools and publicly available cancer genomics databases, such as TCGA, we systematically examined the S100A9 gene. Our approach included differential expression analysis, mutational burden assessment, protein interaction networks, and survival analysis. This robust computational framework provided a high-resolution view of S100A9's role in cancer biology. The study meticulously explored S100A9's oncogenic facets, incorporating comprehensive analyses of its relationship with prognosis, tumor mutational burden (TMB), microsatellite instability (MSI), DNA methylation, and immune cell infiltration across various tumor types. This study presents a panoramic view of S100A9 expression across a spectrum of human cancers, revealing a heterogeneous expression landscape. Elevated S100A9 expression was detected in malignancies such as BLCA (Bladder Urothelial Carcinoma), CESC (Cervical squamous cell carcinoma and endocervical adenocarcinoma), COAD (Colon adenocarcinoma), ESCA (Esophageal carcinoma), and GBM (Glioblastoma multiforme), while reduced expression was noted in BRCA (Breast invasive carcinoma), HNSC (Head and Neck squamous cell carcinoma), and KICH (Kidney Chromophobe). This disparate expression pattern suggests that S100A9's role in cancer biology is multifaceted and context-dependent. Prognostically, S100A9 expression correlates variably with patient outcomes across different cancer types. Furthermore, its expression is intricately associated with TMB and MSI in nine cancer types. Detailed examination of six selected tumors-BRCA, CESC, KIRC (Kidney renal clear cell carcinoma), LUSC (Lung squamous cell carcinoma), SKCM (Skin Cutaneous Melanoma); STAD (Stomach adenocarcinoma)-revealed a negative correlation of S100A9 expression with the infiltration of most immune cells, but a positive correlation with neutrophils, M1 macrophages, and activated NK cells, highlighting the complex interplay between S100A9 and the tumor immune environment. This bioinformatics synthesis posits S100A9 as a significant player in cancer progression, offering valuable prognostic insights. The data underscore the utility of S100A9 as a prognostic biomarker and its potential as a therapeutic target. The therapeutic implications are profound, suggesting that modulation of S100A9 activity could significantly impact cancer management strategies.

Mechanism of drug-pairs Astragalus Mongholicus-Largehead Atractylodes on treating knee osteoarthritis investigated by GEO gene chip with network pharmacology and molecular docking.

Investigations into the therapeutic potential of Astragalus Mongholicus (AM, huáng qí) and Largehead Atractylodes (LA, bái zhú) reveal significant efficacy in mitigating the onset and progression of knee osteoarthritis (KOA), albeit with an elusive mechanistic understanding. This study delineates the primary bioactive constituents and their molecular targets within the AM-LA synergy by harnessing the comprehensive Traditional Chinese Medicine (TCM) network databases, including TCMSP, TCMID, and ETCM. Furthermore, an analysis of 3 gene expression datasets, sourced from the gene expression omnibus database, facilitated the identification of differential genes associated with KOA. Integrating these findings with data from 5 predominant databases yielded a refined list of KOA-associated targets, which were subsequently aligned with the gene signatures corresponding to AM and LA treatment. Through this alignment, specific molecular targets pertinent to the AM-LA therapeutic axis were elucidated. The construction of a protein-protein interaction network, leveraging the shared genetic markers between KOA pathology and AM-LA intervention, enabled the identification of pivotal molecular targets via the topological analysis facilitated by CytoNCA plugins. Subsequent GO and KEGG enrichment analyses fostered the development of a holistic herbal-ingredient-target network and a core target-signal pathway network. Molecular docking techniques were employed to validate the interaction between 5 central molecular targets and their corresponding active compounds within the AM-LA complex. Our findings suggest that the AM-LA combination modulates key biological processes, including cellular activity, reactive oxygen species modification, metabolic regulation, and the activation of systemic immunity. By either augmenting or attenuating crucial signaling pathways, such as MAPK, calcium, and PI3K/AKT pathways, the AM-LA dyad orchestrates a comprehensive regulatory effect on immune-inflammatory responses, cellular proliferation, differentiation, apoptosis, and antioxidant defenses, offering a novel therapeutic avenue for KOA management. This study, underpinned by gene expression omnibus gene chip analyses and network pharmacology, advances our understanding of the molecular underpinnings governing the inhibitory effects of AM and LA on KOA progression, laying the groundwork for future explorations into the active components and mechanistic pathways of TCM in KOA treatment.

Spontaneous Generation of Unconventional Language and Its Link with Grammatical Performance in Chinese Adults With and Without ASD.

This study investigated the generation of unconventional language in the spontaneous speech of Chinese adults with autism spectrum disorder (ASD), and how it was related to their grammatical performance, when compared to neurotypical (NT) controls. Twenty Cantonese-speaking adults with ASD and 20 NT controls completed three interview tasks in the Autism Diagnostic Observation Schedule, Second Edition (ADOS-2), and their spontaneous speech was recorded and transcribed. Utterances containing unconventional language (neologisms, idiosyncratic phrases, and pedantic language), morphosyntactic errors, mean length of utterance (MLU), and mazes were computed. The ASD group produced more neologisms, idiosyncratic phrases, and pedantic language than the NT group and their grammatical difficulties were shown in shorter MLU but not morphosyntactic errors. Mazes were more frequent in the ASD than the NT group. While the use of unconventional language increased with MLU in the NT group, it correlated positively with mazes in the ASD group. Generation of unconventional language, particularly pedantic language, in Cantonese-speaking NT adults is linked to more advanced grammar, while it appears to be a common speech characteristic among autistic speakers regardless of individual grammatical performance.

The shared mechanism and potential diagnostic markers for premature ovarian failure and dry eye disease.

Premature ovarian failure (POF), which is often comorbid with dry eye disease (DED) is a key issue affecting female health. Here, we explored the mechanism underlying comorbid POF and DED to further elucidate disease mechanisms and improve treatment. Datasets related to POF (GSE39501) and DED (GSE44101) were identified from the Gene Expression Omnibus (GEO) database and subjected to weighted gene coexpression network (WGCNA) and differentially expressed genes (DEGs) analyses, respectively, with the intersection used to obtain 158 genes comorbid in POF and DED. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses of comorbid genes revealed that identified genes were primarily related to DNA replication and Cell cycle, respectively. Protein-Protein interaction (PPI) network analysis of comorbid genes obtained the 15 hub genes: CDC20, BIRC5, PLK1, TOP2A, MCM5, MCM6, MCM7, MCM2, CENPA, FOXM1, GINS1, TIPIN, MAD2L1, and CDCA3. To validate the analysis results, additional POF- and DED-related datasets (GSE48873 and GSE171043, respectively) were selected. miRNAs-lncRNAs-genes network and machine learning methods were used to further analysis comorbid genes. The DGIdb database identified valdecoxib, amorfrutin A, and kaempferitrin as potential drugs. Herein, the comorbid genes of POF and DED were identified from a bioinformatics perspective, providing a new strategy to explore the comorbidity mechanism, opening up a new direction for the diagnosis and treatment of comorbid POF and DED.

Research on the loading and release kinetics of the vincristine sulfate liposomes and its anti-breast cancer activity.

Vincristine (VCR), as a cytotoxic drug, is used clinically to treat acute lymphatic leukemia and breast cancer, and commonly used clinically as vincristine sulfate (VCRS). However, its clinical use is limited by unpredictable pharmacologic characteristics, a narrow therapeutic index, and neurotoxicity. The pH gradient method was used for active drug loading of VCRS, and the process route mainly includes the preparation of blank liposomes and drug-loaded liposomes. VCRS liposomes had suitable particle size, high encapsulation efficiency and good stability. The loading and release kinetics of VCRS liposomes were explored. By calculating the changes of encapsulation efficiency with time at different temperatures, it was confirmed that the drug-loading process of liposomes exhibited a first-order kinetic feature, and the activation energy required for the reaction was determined as 20.6 kcal/mol. The release behavior at different pH was also investigated, and it was demonstrated that the release behavior conformed to the first-order model, suggesting that the release mechanism of VCRS was simple transmembrane diffusion. VCRS liposomes also enhanced in vitro and in vivo antitumor activity. Thus, VCRS liposomes showed great potential for VCRS delivery, and the loading and release kinetics were well researched to provide a reference for investigating active drug loading liposomes.

Elucidating the multifaceted roles of GPR146 in non-specific orbital inflammation: a concerted analytical approach through the prisms of bioinformatics and machine learning.

Background: Non-specific Orbital Inflammation (NSOI) is a chronic idiopathic condition marked by extensive polymorphic lymphoid infiltration in the orbital area. The integration of metabolic and immune pathways suggests potential therapeutic roles for C-peptide and G protein-coupled receptor 146 (GPR146) in diabetes and its sequelae. However, the specific mechanisms through which GPR146 modulates immune responses remain poorly understood. Furthermore, the utility of GPR146 as a diagnostic or prognostic marker for NSOI has not been conclusively demonstrated. Methods: We adopted a comprehensive analytical strategy, merging differentially expressed genes (DEGs) from the Gene Expression Omnibus (GEO) datasets GSE58331 and GSE105149 with immune-related genes from the ImmPort database. Our methodology combined LASSO regression and support vector machine-recursive feature elimination (SVM-RFE) for feature selection, followed by Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) to explore gene sets co-expressed with GPR146, identifying a significant enrichment in immune-related pathways. The tumor microenvironment's immune composition was quantified using the CIBERSORT algorithm and the ESTIMATE method, which confirmed a positive correlation between GPR146 expression and immune cell infiltration. Validation of GPR146 expression was performed using the GSE58331 dataset. Results: Analysis identified 113 DEGs associated with GPR146, with a significant subset showing distinct expression patterns. Using LASSO and SVM-RFE, we pinpointed 15 key hub genes. Functionally, these genes and GPR146 were predominantly linked to receptor ligand activity, immune receptor activity, and cytokine-mediated signaling. Specific immune cells, such as memory B cells, M2 macrophages, resting mast cells, monocytes, activated NK cells, plasma cells, and CD8+ T cells, were positively associated with GPR146 expression. In contrast, M0 macrophages, naive B cells, M1 macrophages, activated mast cells, activated memory CD4+ T cells, naive CD4+ T cells, and gamma delta T cells showed inverse correlations. Notably, our findings underscore the potential diagnostic relevance of GPR146 in distinguishing NSOI. Conclusion: Our study elucidates the immunological signatures associated with GPR146 in the context of NSOI, highlighting its prognostic and diagnostic potential. These insights pave the way for GPR146 to be a novel biomarker for monitoring the progression of NSOI, providing a foundation for future therapeutic strategies targeting immune-metabolic pathways.

The roles of IRF8 in nonspecific orbital inflammation: an integrated analysis by bioinformatics and machine learning.

BACKGROUND: Nonspecific Orbital Inflammation (NSOI) represents a persistent and idiopathic proliferative inflammatory disorder, characterized by polymorphous lymphoid infiltration within the orbit. The transcription factor Interferon Regulatory Factor 8 (IRF8), integral to the IRF protein family, was initially identified as a pivotal element for the commitment and differentiation of myeloid cell lineage. Serving as a central regulator of innate immune receptor signaling, IRF8 orchestrates a myriad of functions in hematopoietic cell development. However, the intricate mechanisms underlying IRF8 production remain to be elucidated, and its potential role as a biomarker for NSOI is yet to be resolved. METHODS: IRF8 was extracted from the intersection analysis of common DEGs of GSE58331 and GSE105149 from the GEO and immune- related gene lists in the ImmPort database using The Lasso regression and SVM-RFE analysis. We performed GSEA and GSVA with gene sets coexpressed with IRF8, and observed that gene sets positively related to IRF8 were enriched in immune-related pathways. To further explore the correlation between IRF8 and immune-related biological process, the CIBERSORT algorithm and ESTIMATE method were employed to evaluate TME characteristics of each sample and confirmed that high IRF8 expression might give rise to high immune cell infiltration. Finally, the GSE58331 was utilized to confirm the levels of expression of IRF8. RESULTS: Among the 314 differentially expressed genes (DEGs), some DEGs were found to be significantly different. With LASSO and SVM-RFE algorithms, we obtained 15 hub genes. For biological function analysis in IRF8, leukocyte mediated immunity, leukocyte cell-cell adhesion, negative regulation of immune system process were emphasized. B cells naive, Macrophages M0, Macrophages M1, T cells CD4 memory activated, T cells CD4 memory resting, T cells CD4 naive, and T cells gamma delta were shown to be positively associated with IRF8. While, Mast cells resting, Monocytes, NK cells activated, Plasma cells, T cells CD8, and T cells regulatory (Tregs) were shown to be negatively linked with IRF8. The diagnostic ability of the IRF8 in differentiating NSOI exhibited a good value. CONCLUSIONS: This study discovered IRF8 that are linked to NSOI. IRF8 shed light on potential new biomarkers for NSOI and tracking its progression.

In Situ Structural Densification of Hydrogel Network and Its Interface with Electrodes for High-Performance Multimodal Artificial Skin.

The multisensory responsiveness of hydrogels positions them as promising candidates for artificial skin, whereas the mismatch of modulus between soft hydrogels and hard electrodes as well as the poor adhesion and conductance at the interface greatly impairs the stability of electronics devices. Herein, we propose an in situ postprocessing approach utilizing electrochemical reactions between metals (Zn, etc.) and hydrogels to synergistically achieve strong adhesion of the hydrogel-electrode interface, low interfacial impedance, and local strain isolation due to the structural densification of the hydrogel network. The mechanism is that Zn electrochemically oxidizes to Zn2+ and injects into the hydrogel, gradually forming a mechanically interlocked structure, Zn2+-polymer dual-helix structural nodes, and a high-modulus ZnO from the surface to the interior. Compared to untreated samples, the treated sample displays 8.7 times increased interfacial adhesion energy between the hydrogel and electrode (87 J/m2), 95% decreased interfacial impedance (218.8 Ω), and a high-strain isolation efficiency (εtotal/εisolation > 400). Akin to human skin, the prepared sensor demonstrates multimodal sensing capabilities, encompassing highly sensitive strain perception and simultaneous perception of temperature, humidity, and oxygen content unaffected by strain interference. This easy on-chip preparation of hydrogel-based multimodal sensor array shows great potential for health and environment monitoring as artificial skin.

Membrane-bound trehalase enhances cadmium tolerance by regulating cell apoptosis in Neocaridina denticulata sinensis.

Trehalase gene is mainly expressed in the digestive circulatory system for regulating energy metabolism and chitin synthesis in insects, but it is significantly expressed in gill for immunomodulation in shrimp. However, its function in regulating immunity, particularly metal resistance in crustaceans has yet to be elucidated. In this study, one Tre2 gene (NdTre2) was isolated from Neocaridina denticulata sinensis. It could bind to Cd2+ and inhibit its toxicity. Spatiotemporal expression analysis showed that the expression of NdTre2 was highest in the gill and significantly reduced at 12 h after Cd2+ stimulation. The transcriptomic analysis of the gill after NdTre2 knockdown showed that the expression of genes synthetizing 20E was up-regulated and the increased 20E could further induce apoptosis by activating the intrinsic mitochondrial pathway, exogenous death receptor-ligand pathway, and MAPK pathway. In vitro, overexpressing NdTre2 enhanced the tolerance of E. coli in Cd2+ environment. In summary, these results indicate that NdTre2 plays an essential role in regulating immunity and chitin metabolism in N. denticulata sinensis.

Comparative transcriptomic analysis primarily explores the molecular mechanism of compound eye formation in Neocaridina denticulata sinensis.

Compound eyes formation in decapod crustaceans occurs after the nauplius stage. However, the key genes and regulatory mechanisms of compound eye development during crustacean embryonic development have not yet been clarified. In this study, RNA-seq was used to investigate the gene expression profiles of Neocaridina denticulata sinensis from nauplius to zoea stage. Based on RNA-seq data analysis, the phototransduction and insect hormone biosynthesis pathways were enriched, and molting-related neuropeptides were highly expressed. There was strong cell proliferation in the embryo prior to compound eye development. The formation of the visual system and the hormonal regulation of hatching were the dominant biological events during compound eye development. The functional analysis of DEGs across all four developmental stages showed that cuticle formation, muscle growth and the establishment of immune system occurred from nauplius to zoea stage. Key genes related to eye development were discovered, including those involved in the determination and differentiation of the eye field, eye-color formation, and visual signal transduction. In conclusion, the results increase the understanding of the molecular mechanism of eye formation in crustacean embryonic stage.

Kv3.1 Interaction with UBR5 Is Required for Chronic Inflammatory Pain.

Chronic inflammatory pain caused by neuronal hyperactivity is a common and refractory disease. Kv3.1, a member of the Kv3 family of voltage-dependent K+ channels, is a major determinant of the ability of neurons to generate high-frequency action potentials. However, little is known about its role in chronic inflammatory pain. Here, we show that although Kv3.1 mRNA expression was unchanged, Kv3.1 protein expression was decreased in the dorsal spinal horn of mice after plantar injection of complete Freund's adjuvant (CFA), a mouse model of inflammatory pain. Upregulating Kv3.1 expression alleviated CFA-induced mechanical allodynia and heat hyperalgesia, whereas downregulating Kv3.1 induced nociception-like behaviors. Additionally, we found that ubiquitin protein ligase E3 component n-recognin 5 (UBR5), a key factor in the initiation of chronic pain, binds directly to Kv3.1 to drive its ubiquitin degradation. Intrathecal injection of the peptide TP-CH-401, a Kv3.1 ubiquitination motif sequence, rescued the decrease in Kv3.1 expression and Kv currents through competitive binding to UBR5, and consequently attenuated mechanical and thermal hypersensitivity. These findings demonstrate a previously unrecognized pathway of Kv3.1 abrogation by UBR5 and indicate that Kv3.1 is critically involved in the regulation of nociceptive behavior. Kv3.1 is thus a promising new target for treating inflammatory pain.

A Sunlight-Driven Self-Cleaning CuCo-MOF Composite Membrane for Highly Efficient Emulsion Separation and Water Purification.

The fouling phenomenon of membranes has hindered the rapid development of separation technology in wastewater treatment. The integration of materials into membranes with both excellent separation performance and self-cleaning properties still pose challenges. Here, a self-assembled composite membrane with solar-driven self-cleaning performance is reported for the treatment of complex oil-water emulsions. The mechanical robustness of the composite membrane is enhanced by the electrostatic attraction between chitosan and metal-organic frameworks (MOF) CuCo-HHTP as well as the crosslinking effect of glutaraldehyde. Molecular dynamics (MD) simulations also revealed the hydrogen bonding interaction between chitosan and CuCo-HHTP. The composite membrane of CuCo-HHTP-5@CS/MPVDF exhibits a high flux ranging from 700.6 to 2350.6 L∙m-2∙h-1∙bar-1 and excellent separation efficiency (>99.0%) for various oil-water emulsions, including crude oil, kerosene, and other light oils. The addition of CuCo-HHTP shows remarkable photothermal effects, thus demonstrating excellent solar-driven self-cleaning capability and antibacterial performance (with an efficiency of ≈100%). Furthermore, CuCo-HHTP-5@CS/MPVDF can activate peroxomonosulfate (PMS) under sunlight, quickly removing oil-fouling and dyes. Density functional theory (DFT) calculations indicate that the bimetallic sites of Cu and Co in CuCo-HHTP effectively promoted the activation of PMS. This study provides distinctive insights into the multifaceted applications of MOFs-derived photothermal anti-fouling composite membranes.

Different machine learning methods based on maxillary sinus in sex estimation for northwestern Chinese Han population.

BACKGROUND & OBJECTIVE: Sex estimation is a critical aspect of forensic expertise. Some special anatomical structures, such as the maxillary sinus, can still maintain integrity in harsh environmental conditions and may be served as a basis for sex estimation. Due to the complex nature of sex estimation, several studies have been conducted using different machine learning algorithms to improve the accuracy of sex prediction from anatomical measurements. MATERIAL & METHODS: In this study, linear data of the maxillary sinus in the population of northwest China by using Cone-Beam Computed Tomography (CBCT) were collected and utilized to develop logistic, K-Nearest Neighbor (KNN), Support Vector Machine (SVM) and random forest (RF) models for sex estimation with R 4.3.1. CBCT images from 477 samples of Han population (75 males and 81 females, aged 5-17 years; 162 males and 159 females, aged 18-72) were used to establish and verify the model. Length (MSL), width (MSW), height (MSH) of both the left and right maxillary sinuses and distance of lateral wall between two maxillary sinuses (distance) were measured. 80% of the data were randomly picked as the training set and others were testing set. Besides, these samples were grouped by age bracket and fitted models as an attempt. RESULTS: Overall, the accuracy of the sex estimation for individuals over 18 years old on the testing set was 77.78%, with a slightly higher accuracy rate for males at 78.12% compared to females at 77.42%. However, accuracy of sex estimation for individuals under 18 was challenging. In comparison to logistic, KNN and SVM, RF exhibited higher accuracy rates. Moreover, incorporating age as a variable improved the accuracy of sex estimation, particularly in the 18-27 age group, where the accuracy rate increased to 88.46%. Meanwhile, all variables showed a linear correlation with age. CONCLUSION: The linear measurements of the maxillary sinus could be a valuable tool for sex estimation in individuals aged 18 and over. A robust RF model has been developed for sex estimation within the Han population residing in the northwestern region of China. The accuracy of sex estimation could be higher when age is used as a predictive variable.

Integration of bioinformatics and machine learning approaches for the validation of pyrimidine metabolism-related genes and their implications in immunotherapy for osteoporosis.

BACKGROUND: Osteoporosis (OP), the "silent epidemic" of our century, poses a significant challenge to public health, predominantly affecting postmenopausal women and the elderly. It evolves from mild symptoms to pronounced severity, stabilizing eventually. Unique among OP's characteristics is the altered metabolic profile of affected cells, particularly in pyrimidine metabolism (PyM), a crucial pathway for nucleotide turnover and pyrimidine decomposition. While metabolic adaptation is acknowledged as a therapeutic target in various diseases, the specific role of PyM genes (PyMGs) in OP's molecular response remains to be clarified. METHODS: In pursuit of elucidating and authenticating PyMGs relevant to OP, we embarked on a comprehensive bioinformatics exploration. This entailed the integration of Weighted Gene Co-expression Network Analysis (WGCNA) with a curated list of 37 candidate PyMGs, followed by the examination of their biological functions and pathways via Gene Set Variation Analysis (GSVA). The Least Absolute Shrinkage and Selection Operator (LASSO) technique was harnessed to identify crucial hub genes. We evaluated the diagnostic prowess of five PyMGs in OP detection and explored their correlation with OP's clinical traits, further validating their expression profiles through independent datasets (GSE2208, GSE7158, GSE56815, and GSE35956). RESULTS: Our analytical rigor unveiled five PyMGs-IGKC, TMEM187, RPS11, IGLL3P, and GOLGA8N-with significant ties to OP. A deeper dive into their biological functions highlighted their roles in estrogen response modulation, cytosolic calcium ion concentration regulation, and GABAergic synaptic transmission. Remarkably, these PyMGs emerged as potent diagnostic biomarkers for OP, distinguishing affected individuals with substantial accuracy. CONCLUSIONS: This investigation brings to light five PyMGs intricately associated with OP, heralding new avenues for biomarker discovery and providing insights into its pathophysiological underpinnings. These findings not only deepen our comprehension of OP's complexity but also herald the advent of more refined diagnostic and therapeutic modalities.

Performance and protein conformation of thermally treated silver carp (Hypophthalmichthys molitrix) and scallop (Argopecten irradians) blended gels.

BACKGROUND: The quality of surimi-based products can be improved by combining the flesh of different aquatic organisms. The present study investigated the effects of incorporating diverse ratios of unwashed silver carp (H) and scallop (A) and using various thermal treatments on the moisture, texture, microstructure, and conformation of the blended gels and myofibrillar protein of surimi. RESULTS: A mixture ratio of A:H = 1:3 yielded the highest gel strength, which was 60.4% higher than that of scallop gel. The cooking losses of high-pressure heating and water-bath microwaving were significantly higher than those of other methods (P < 0.05). Moreover, the two-step water bath and water-bath microwaving samples exhibited a more regular spatial network structure compared to other samples. The mixed samples exhibited a microstructure with a uniform and ordered spatial network, allowing more free water to be trapped by the internal structure, resulting in more favorable gel properties. The thermal treatments comprehensively modified the tertiary and quaternary structures of proteins in unwashed mixed gel promoted protein unfurling, provided more hydrophobic interactions, enhanced protein aggregation and improved the gel performance. CONCLUSION: The findings of the present study improve our understanding of the interactions between proteins from different sources. We propose a new method for modifying surimi's gel properties, facilitating the development of mixed surimi products, as well as enhancing the efficient utilization of aquatic resources. © 2024 Society of Chemical Industry.

Discovery and structural mechanism of DNA endonucleases guided by RAGATH-18-derived RNAs.

CRISPR-Cas systems and IS200/IS605 transposon-associated TnpBs have been utilized for the development of genome editing technologies. Using bioinformatics analysis and biochemical experiments, here we present a new family of RNA-guided DNA endonucleases. Our bioinformatics analysis initially identifies the stable co-occurrence of conserved RAGATH-18-derived RNAs (reRNAs) and their upstream IS607 TnpBs with an average length of 390 amino acids. IS607 TnpBs form programmable DNases through interaction with reRNAs. We discover the robust dsDNA interference activity of IS607 TnpB systems in bacteria and human cells. Further characterization of the Firmicutes bacteria IS607 TnpB system (ISFba1 TnpB) reveals that its dsDNA cleavage activity is remarkably sensitive to single mismatches between the guide and target sequences in human cells. Our findings demonstrate that a length of 20 nt in the guide sequence of reRNA achieves the highest DNA cleavage activity for ISFba1 TnpB. A cryo-EM structure of the ISFba1 TnpB effector protein bound by its cognate RAGATH-18 motif-containing reRNA and a dsDNA target reveals the mechanisms underlying reRNA recognition by ISFba1 TnpB, reRNA-guided dsDNA targeting, and the sensitivity of the ISFba1 TnpB system to base mismatches between the guide and target DNA. Collectively, this study identifies the IS607 TnpB family of compact and specific RNA-guided DNases with great potential for application in gene editing.

Bioinformatic validation and machine learning-based exploration of purine metabolism-related gene signatures in the context of immunotherapeutic strategies for nonspecific orbital inflammation.

Background: Nonspecific orbital inflammation (NSOI) represents a perplexing and persistent proliferative inflammatory disorder of idiopathic nature, characterized by a heterogeneous lymphoid infiltration within the orbital region. This condition, marked by the aberrant metabolic activities of its cellular constituents, starkly contrasts with the metabolic equilibrium found in healthy cells. Among the myriad pathways integral to cellular metabolism, purine metabolism emerges as a critical player, providing the building blocks for nucleic acid synthesis, such as DNA and RNA. Despite its significance, the contribution of Purine Metabolism Genes (PMGs) to the pathophysiological landscape of NSOI remains a mystery, highlighting a critical gap in our understanding of the disease's molecular underpinnings. Methods: To bridge this knowledge gap, our study embarked on an exploratory journey to identify and validate PMGs implicated in NSOI, employing a comprehensive bioinformatics strategy. By intersecting differential gene expression analyses with a curated list of 92 known PMGs, we aimed to pinpoint those with potential roles in NSOI. Advanced methodologies, including Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA), facilitated a deep dive into the biological functions and pathways associated with these PMGs. Further refinement through Lasso regression and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) enabled the identification of key hub genes and the evaluation of their diagnostic prowess for NSOI. Additionally, the relationship between these hub PMGs and relevant clinical parameters was thoroughly investigated. To corroborate our findings, we analyzed expression data from datasets GSE58331 and GSE105149, focusing on the seven PMGs identified as potentially crucial to NSOI pathology. Results: Our investigation unveiled seven PMGs (ENTPD1, POLR2K, NPR2, PDE6D, PDE6H, PDE4B, and ALLC) as intimately connected to NSOI. Functional analyses shed light on their involvement in processes such as peroxisome targeting sequence binding, seminiferous tubule development, and ciliary transition zone organization. Importantly, the diagnostic capabilities of these PMGs demonstrated promising efficacy in distinguishing NSOI from non-affected states. Conclusions: Through rigorous bioinformatics analyses, this study unveils seven PMGs as novel biomarker candidates for NSOI, elucidating their potential roles in the disease's pathogenesis. These discoveries not only enhance our understanding of NSOI at the molecular level but also pave the way for innovative approaches to monitor and study its progression, offering a beacon of hope for individuals afflicted by this enigmatic condition.

Cellulose nanocrystals intercalated clay biocomposite for rapid Cr(VI) removal.

The application of bentonite (Bt) as an adsorbent for heavy metals has been limited due to its hydrophobicity and insufficient surface area. Herein, we present cellulose nanocrystal (CNC) modified Bt composite (CNC@Bt) with enhanced efficiency for Cr(VI) removal. CNC@Bt exhibited an increased specific surface area and a porous structure, while maintaining the original crystal structure of Bt. This was achieved through a synergistic function of ion exchange, hydrogen bonding, electrostatic interactions, and steric hindrance. The adsorption of Cr(VI) by CNC@Bt followed the pseudo-second-order kinetic and Langmuir isotherm adsorption model. Moreover, the process was endothermic and spontaneous. At an initial Cr(VI) concentration of 20 mg/L and pH = 4.0, 10 g/L CNC@Bt achieved a removal rate of 92.7%, and the adsorption capacity was 1.85 mg/g, significantly higher than bare Bt (37.9% and 0.76 mg/g). The removal efficiency remained consistently above 80% over a wide pH range, indicating the potential practical applicability of CNC@Bt. With its fast adsorption rate, pH adaptability, and stable performance, CNC@Bt presents promising prospects for the rapid treatment of Cr-contaminated wastewater.