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.

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.

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.

Superhydrophobic Co-MOF-based sponge for efficient oil-water separation utilizing photothermal effect.

Effectively addressing crude oil spills remains a global challenge due to its high viscosity and limited flow characteristics. In this study, we successfully prepared a modified sponge (PCP@MS) by embedding the photothermal material of Co-HHTP and coating the melamine sponge (MS) with low-surface-energy polydimethylsiloxane (PDMS). The PCP@MS exhibited outstanding hydrophobicity with WCA of 160.2° and high oil absorption capacity of 59-107 g/g. The PCP@MS showed high separation efficiency of 99.2% for various oil-water mixtures, along with notable self-cleaning properties and mechanical stability. The internal micro-nano hierarchical structure on the sponge surface significantly enhanced light absorption, synergizing with the photo-thermal conversion properties of Co-HHTP, enabled PCP@MS to achieve a surface temperature of 109.2 °C under 1.0 solar light within 300 s. With the aid of solar radiation, PCP@MS is able to heat up quickly and successfully lowering the viscosity of the surrounding crude oil, resulting in an oil recovery rate of 8.76 g/min. Density functional theory (DFT) calculation results revealed that Co-HHTP featured a zero-gap band structure, rendering advantageous electronic properties for full-wavelength light absorption. This in situ solar-heated absorbent design is poised to advance the practical application of viscous oil spill cleanup and recovery.

Progestin and adipoQ receptor 7 (PAQR7) mediate the anti-apoptotic effect of P4 on human granulosa cells and its deficiency reduces ovarian function in female mice.

PURPOSE: PAQR7 plays a key role in cell apoptosis as a progesterone membrane receptor. The physiological mechanism of PAQR7 in ovarian function and its anti-apoptotic action in mammals remain poorly understood. METHODS: We first added 0.2 µM aminoglutethimide (AG), an inhibitor of endogenous progesterone (P4) secretion, and transfected siPAQR7 co-incubated with P4 in human KGN cells to identify granulosa cell apoptosis, respectively. Additionally, we used Paqr7 knockout (PAQR7 KO) mice to assess the role of PAQR7 in the ovary. RESULTS: The PAQR7 deficiency significantly increased apoptosis of KGN cells, and this significant difference disappeared following P4 supplementation. The Paqr7-/- female mice showed a prolonged estrous cycle, reduced follicular growth, increased the number of atresia follicles, and decreased the concentrations of E2 and AMH. The litters, litter sizes, and spontaneous ovulation in the Paqr7-/- mice were significantly decreased compared with the Paqr7+/+ mice. In addition, we also found low expression of PAQR7 in GCs from human follicular fluids of patients diagnosed with decreased ovarian reserve (DOR) and ovaries of mice with a DOR-like phenotype, respectively. CONCLUSIONS: The present study has identified that PAQR7 is involved in mouse ovarian function and fertilization potential. One possible mechanism is mediating the anti-apoptotic effect of P4 on GC apoptosis via the BCL-2/BAX/CASPASE-3 signaling pathway. The mechanism underlying the effect of PAQR7 on ovarian development and aging remains to be identified.

Glutamine metabolism-related genes and immunotherapy in nonspecific orbital inflammation were validated using bioinformatics and machine learning.

BACKGROUND: Nonspecific orbital inflammation (NSOI) is an idiopathic, persistent, and proliferative inflammatory condition affecting the orbit, characterized by polymorphous lymphoid infiltration. Its pathogenesis and progression have been linked to imbalances in tumor metabolic pathways, with glutamine (Gln) metabolism emerging as a critical aspect in cancer. Metabolic reprogramming is known to influence clinical outcomes in various malignancies. However, comprehensive research on glutamine metabolism's significance in NSOI is lacking. METHODS: This study conducted a bioinformatics analysis to identify and validate potential glutamine-related molecules (GlnMgs) associated with NSOI. The discovery of GlnMgs involved the intersection of differential expression analysis with a set of 42 candidate GlnMgs. The biological functions and pathways of the identified GlnMgs were analyzed using GSEA and GSVA. Lasso regression and SVM-RFE methods identified hub genes and assessed the diagnostic efficacy of fourteen GlnMgs in NSOI. The correlation between hub GlnMgs and clinical characteristics was also examined. The expression levels of the fourteen GlnMgs were validated using datasets GSE58331 and GSE105149. RESULTS: Fourteen GlnMgs related to NSOI were identified, including FTCD, CPS1, CTPS1, NAGS, DDAH2, PHGDH, GGT1, GCLM, GLUD1, ART4, AADAT, ASNSD1, SLC38A1, and GFPT2. Biological function analysis indicated their involvement in responses to extracellular stimulus, mitochondrial matrix, and lipid transport. The diagnostic performance of these GlnMgs in distinguishing NSOI showed promising results. CONCLUSIONS: This study successfully identified fourteen GlnMgs associated with NSOI, providing insights into potential novel biomarkers for NSOI and avenues for monitoring disease progression.

Identification of clinical prognostic factors and analysis of ferroptosis-related gene signatures in the bladder cancer immune microenvironment.

BACKGROUND: Bladder cancer (BLCA) is a prevalent malignancy affecting the urinary system and poses a significant burden in terms of both incidence and mortality rates on a global scale. Among all BLCA cases, non-muscle invasive bladder cancer constitutes approximately 75% of the total. In recent years, the concept of ferroptosis, an iron-dependent form of regulated cell death marked by the accumulation of lipid peroxides, has captured the attention of researchers worldwide. Nevertheless, the precise involvement of ferroptosis-related genes (FRGs) in the anti-BLCA response remains inadequately elucidated. METHODS: The integration of BLCA samples from the TCGA and GEO datasets facilitated the quantitative evaluation of FRGs, offering potential insights into their predictive capabilities. Leveraging the wealth of information encompassing mRNAsi, gene mutations, CNV, TMB, and clinical features within these datasets further enriched the analysis, augmenting its robustness and reliability. Through the utilization of Lasso regression, a prediction model was developed, enabling accurate prognostic assessments within the context of BLCA. Additionally, co-expression analysis shed light on the complex relationship between gene expression patterns and FRGs, unraveling their functional relevance and potential implications in BLCA. RESULTS: FRGs exhibited increased expression levels in the high-risk cohort of BLCA patients, even in the absence of other clinical indicators, suggesting their potential as prognostic markers. GSEA revealed enrichment of immunological and tumor-related pathways specifically in the high-risk group. Furthermore, notable differences were observed in immune function and m6a gene expression between the low- and high-risk groups. Several genes, including MYBPH, SOST, SPRR2A, and CRNN, were found to potentially participate in the oncogenic processes underlying BLCA. Additionally, CYP4F8, PDZD3, CRTAC1, and LRTM1 were identified as potential tumor suppressor genes. Significant discrepancies in immunological function and m6a gene expression were observed between the two risk groups, further highlighting the distinct molecular characteristics associated with different prognostic outcomes. Notably, strong correlations were observed among the prognostic model, CNVs, SNPs, and drug sensitivity profiles. CONCLUSIONS: FRGs are associated with the onset and progression of BLCA. A FRGs signature offers a viable alternative to predict BLCA, and these FRGs show a prospective research area for BLCA targeted treatment in the future.

Ghrelin inhibits myocardial pyroptosis in diabetic cardiomyopathy by regulating ERS and NLRP3 inflammasome crosstalk through the PI3K/AKT pathway.

AIMS: Endoplasmic reticulum stress(ERS) can induce inflammation mediated by NLRP3 inflammatory bodies and link inflammation with oxidative stress in myocardial tissue. Ghrelin is an endogenous growth hormone-releasing peptide that has been proven to have multiple effects, such as regulating energy metabolism and inhibiting inflammation. However, the role of ghrelin in myocardial injury in diabetic rats and the mechanism have not been reported. RESULTS: We found that ghrelin could improve endoplasmic reticulum stress and inflammatory pyroptosis in the myocardial tissue of diabetic rats and reduce ERS and NLRP3 inflammasome crosstalk in H9C2 cardiomyocytes. Interestingly, ghrelin could activate the PI3K/AKT signalling pathway, playing a role in inhibiting endoplasmic reticulum stress and reducing the expression of pyroptosis-related proteins. However, these protective effects could be largely eliminated by LY294002. CONCLUSIONS: In summary, we demonstrated that ghrelin inhibited myocardial pyroptosis in diabetic cardiomyopathy by regulating ERS and NLRP3 inflammasome crosstalk through the PI3K/AKT pathway. Our results provide new insights into the mechanism of diabetic myocardial injury induced by high glucose and high palmitic acid and ghrelin-mediated anti-inflammatory protection and provide potential therapeutic targets and strategies for diabetic cardiomyopathy.

Ghrelin improves lipid metabolism but not glucose metabolism in rats with diabetic cardiomyopathy.Ghrelin improves cardiac dysfunction and structure disorder in diabetic cardiomyopathy.Ghrelin inhibits cardiomyocyte pyroptosis in diabetic cardiomyopathy by regulating myocardial endoplasmic reticulum stress and NLRP3 inflammasome activation.The protective effect mediated by ghrelin may be related to the activation of PI3K/AKT signal pathway.

Specific inhibition of TET1 in the spinal dorsal horn alleviates inflammatory pain in mice by regulating synaptic plasticity.

DNA demethylation mediated by ten-eleven translocation 1 (TET1) is a critical epigenetic mechanism in which gene expression is regulated via catalysis of 5-methylcytosine to 5-hydroxymethylcytosine. Previously, we demonstrated that TET1 is associated with the genesis of chronic inflammatory pain. However, how TET1 participates in enhanced nociceptive responses in chronic pain remains poorly understood. Here, we report that conditional knockout of Tet1 in dorsal horn neurons via intrathecal injection of rAAV-hSyn-Cre in Tet1fl/fl mice not only reversed the inflammation-induced upregulation of synapse-associated proteins (post-synaptic density protein 95 (PSD95) and synaptophysin (SYP)) in the dorsal horn but also ameliorated abnormalities in dendritic spine morphology and alleviated pain hypersensitivities. Pharmacological blockade of TET1 by intrathecal injection of a TET1-specific inhibitor-Bobcat 339-produced similar results, as did knockdown of Tet1 by intrathecal injection of siRNA. Thus, our data strongly suggest that increased TET1 expression during inflammatory pain upregulates the expression of multiple synapse-associated proteins and dysregulates synaptic morphology in dorsal horn neurons, suggesting that Tet1 may be a potential target for analgesic strategies.

Ferroptosis-related genes prognostic signature for pancreatic cancer and immune infiltration: potential biomarkers for predicting overall survival.

BACKGROUND: Pancreatic adenocarcinoma (PAAD) constitutes a lethal malignancy, notorious for its elevated mortality rates due to the difficulties in early diagnosis and rapid metastasis. The emerging paradigm of ferroptosis-an iron-catalyzed, regulated cell death distinguished by the accrual of lipid peroxides-has recently garnered scholarly focus. However, the expression landscape of ferroptosis-related genes (FRGs) in PAAD and their prognostic implications remain enigmatic. METHODS: We undertook a rigorous quantification of FRGs in PAAD samples, sourcing data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. These repositories also provided extensive metadata, encompassing mesenchymal stemness index (mRNAsi), genomic mutations, copy number variations (CNV), tumor mutational burden (TMB), and other clinical attributes. A predictive model was constructed utilizing Lasso regression analysis, and a co-expression study was executed to elucidate the complex interconnections between FRGs and other gene sets. RESULTS: Intriguingly, FRGs were substantially upregulated in the high-risk cohort, even in the absence of clinically manifest symptoms, emphasizing their utility as prognostic biomarkers. Gene set enrichment analysis (GSEA) revealed significant enrichment of immune and tumor-related pathways in this high-risk demographic. Striking heterogeneities in immune function and N6-methyladenosine (m6A) RNA modification were observed between the low- and high-risk groups. Our analysis further implicated a cohort of genes-including LINC01559, C11orf86, SERPINB5, DSG3, MSLN, EREG, FAM83A, CXCL5, LY6D, and PSCA-as cardinal mediators in PAAD pathogenesis. A convergence of our predictive model with an analysis of CNVs, single nucleotide polymorphisms (SNPs), and drug sensitivities, revealed an intricate relationship with the FRGs. CONCLUSIONS: Our findings accentuate the salient role of FRGs as critical modulators in the pathogenesis and progression of PAAD. Importantly, our composite prognostic framework offers invaluable insights into PAAD clinical trajectory. Moreover, the complex crosstalk between FRGs and immune cell landscapes in the tumor microenvironment (TME) may elucidate prospective therapeutic strategies. The clinical translational utility of these insights, however, requires further in-depth empirical exploration. Accordingly, the FRG signature introduces a compelling new avenue for risk stratification and targeted therapeutic interventions in this devastating malignancy.

Development and validation of prognostic index based on purine metabolism genes in patients with bladder cancer.

Background: Bladder cancer (BLCA) is a prevalent malignancy affecting the urinary system and is associated with significant morbidity and mortality worldwide. Dysregulation of tumor metabolic pathways is closely linked to the initiation and proliferation of BLCA. Tumor cells exhibit distinct metabolic activities compared to normal cells, and the purine metabolism pathway, responsible for providing essential components for DNA and RNA synthesis, is believed to play a crucial role. However, the precise involvement of Purine Metabolism Genes (PMGs) in the defense mechanism against BLCA remains elusive. Methods: The integration of BLCA samples from the TCGA and GEO datasets facilitated the quantitative evaluation of PMGs, offering potential insights into their predictive capabilities. Leveraging the wealth of information encompassing mRNAsi, gene mutations, CNV, TMB, and clinical features within these datasets further enriched the analysis, augmenting its robustness and reliability. Through the utilization of Lasso regression, a prediction model was developed, enabling accurate prognostic assessments within the context of BLCA. Additionally, co-expression analysis shed light on the complex relationship between gene expression patterns and PMGs, unraveling their functional relevance and potential implications in BLCA. Results: PMGs exhibited increased expression levels in the high-risk cohort of BLCA patients, even in the absence of other clinical indicators, suggesting their potential as prognostic markers. GSEA revealed enrichment of immunological and tumor-related pathways specifically in the high-risk group. Furthermore, notable differences were observed in immune function and m6a gene expression between the low- and high-risk groups. Several genes, including CLDN6, CES1, SOST, SPRR2A, MYBPH, CGB5, and KRT1, were found to potentially participate in the oncogenic processes underlying BLCA. Additionally, CRTAC1 was identified as potential tumor suppressor genes. Significant discrepancies in immunological function and m6a gene expression were observed between the two risk groups, further highlighting the distinct molecular characteristics associated with different prognostic outcomes. Notably, strong correlations were observed among the prognostic model, CNVs, SNPs, and drug sensitivity profiles. Conclusion: PMGs have been implicated in the etiology and progression of bladder cancer (BLCA). Prognostic models corresponding to this malignancy aid in the accurate prediction of patient outcomes. Notably, exploring the potential therapeutic targets within the tumor microenvironment (TME) such as PMGs and immune cell infiltration holds promise for effective BLCA management, albeit necessitating further research. Moreover, the identification of a gene signature associated with purine Metabolism presents a credible and alternative approach for predicting BLCA, signifying a burgeoning avenue for targeted therapeutic investigations in the field of BLCA.

Bioinformatics and machine learning were used to validate glutamine metabolism-related genes and immunotherapy in osteoporosis patients.

BACKGROUND: Osteoporosis (OP), often referred to as the "silent disease of the twenty-first century," poses a significant public health concern due to its severity, chronic nature, and progressive course, predominantly affecting postmenopausal women and elderly individuals. The pathogenesis and progression of this disease have been associated with dysregulation in tumor metabolic pathways. Notably, the metabolic utilization of glutamine has emerged as a critical player in cancer biology. While metabolic reprogramming has been extensively studied in various malignancies and linked to clinical outcomes, its comprehensive investigation within the context of OP remains lacking. METHODS: This study aimed to identify and validate potential glutamine metabolism genes (GlnMgs) associated with OP through comprehensive bioinformatics analysis. The identification of GlnMgs was achieved by integrating the weighted gene co-expression network analysis and a set of 28 candidate GlnMgs. Subsequently, the putative biological functions and pathways associated with GlnMgs were elucidated using gene set variation analysis. The LASSO method was employed to identify key hub genes, and the diagnostic efficacy of five selected GlnMgs in OP detection was assessed. Additionally, the relationship between hub GlnMgs and clinical characteristics was investigated. Finally, the expression levels of the five GlnMgs were validated using independent datasets (GSE2208, GSE7158, GSE56815, and GSE35956). RESULTS: Five GlnMgs, namely IGKC, TMEM187, RPS11, IGLL3P, and GOLGA8N, were identified in this study. To gain insights into their biological functions, particular emphasis was placed on synaptic transmission GABAergic, inward rectifier potassium channel activity, and the cytoplasmic side of the lysosomal membrane. Furthermore, the diagnostic potential of these five GlnMgs in distinguishing individuals with OP yielded promising results, indicating their efficacy as discriminative markers for OP. CONCLUSIONS: This study discovered five GlnMgs that are linked to OP. They shed light on potential new biomarkers for OP and tracking its progression.

Pyrimidine metabolism regulator-mediated molecular subtypes display tumor microenvironmental hallmarks and assist precision treatment in bladder cancer.

Background: Bladder cancer (BLCA) is a common urinary system malignancy with a significant morbidity and death rate worldwide. Non-muscle invasive BLCA accounts for over 75% of all BLCA cases. The imbalance of tumor metabolic pathways is associated with tumor formation and proliferation. Pyrimidine metabolism (PyM) is a complex enzyme network that incorporates nucleoside salvage, de novo nucleotide synthesis, and catalytic pyrimidine degradation. Metabolic reprogramming is linked to clinical prognosis in several types of cancer. However, the role of pyrimidine metabolism Genes (PyMGs) in the BLCA-fighting process remains poorly understood. Methods: Predictive PyMGs were quantified in BLCA samples from the TCGA and GEO datasets. TCGA and GEO provided information on stemness indices (mRNAsi), gene mutations, CNV, TMB, and corresponding clinical features. The prediction model was built using Lasso regression. Co-expression analysis was conducted to investigate the relationship between gene expression and PyM. Results: PyMGs were overexpressed in the high-risk sample in the absence of other clinical symptoms, demonstrating their predictive potential for BLCA outcome. Immunological and tumor-related pathways were identified in the high-risk group by GSWA. Immune function and m6a gene expression varied significantly between the risk groups. In BLCA patients, DSG1, C6orf15, SOST, SPRR2A, SERPINB7, MYBPH, and KRT1 may participate in the oncology process. Immunological function and m6a gene expression differed significantly between the two groups. The prognostic model, CNVs, single nucleotide polymorphism (SNP), and drug sensitivity all showed significant gene connections. Conclusions: BLCA-associated PyMGs are available to provide guidance in the prognostic and immunological setting and give evidence for the formulation of PyM-related molecularly targeted treatments. PyMGs and their interactions with immune cells in BLCA may serve as therapeutic targets.

Glutamine metabolism genes prognostic signature for stomach adenocarcinoma and immune infiltration: potential biomarkers for predicting overall survival.

Background: Stomach adenocarcinoma (STAD), caused by mutations in stomach cells, is characterized by poor overall survival. Chemotherapy is commonly administered for stomach cancer patients following surgical resection. An imbalance in tumor metabolic pathways is connected to tumor genesis and growth. It has been discovered that glutamine (Gln) metabolism plays a crucial role in cancer. Metabolic reprogramming is associated with clinical prognosis in various cancers. However, the role of glutamine metabolism genes (GlnMgs) in the fight against STAD remains poorly understood. Methods: GlnMgs were determined in STAD samples from the TCGA and GEO datasets. The TCGA and GEO databases provide information on stemness indices (mRNAsi), gene mutations, copy number variations (CNV), tumor mutation burden (TMB), and clinical characteristics. Lasso regression was performed to build the prediction model. The relationship between gene expression and Gln metabolism was investigated using co-expression analysis. Results: GlnMgs, found to be overexpressed in the high-risk group even in the absence of any symptomatology, demonstrated strong predictive potential for STAD outcomes. GSEA highlighted immunological and tumor-related pathways in the high-risk group. Immune function and m6a gene expression differed significantly between the low- and high-risk groups. AFP, CST6, CGB5, and ELANE may be linked to the oncology process in STAD patients. The prognostic model, CNVs, single nucleotide polymorphism (SNP), and medication sensitivity all revealed a strong link to the gene. Conclusion: GlnMgs are connected to the genesis and development of STAD. These corresponding prognostic models aid in predicting the prognosis of STAD GlnMgs and immune cell infiltration in the tumor microenvironment (TME) may be possible therapeutic targets in STAD. Furthermore, the glutamine metabolism gene signature presents a credible alternative for predicting STAD outcomes, suggesting that these GlnMgs could open a new field of study for STAD-focused therapy Additional trials are needed to validate the results of the current study.

A novel Alzheimer's disease prognostic signature: identification and analysis of glutamine metabolism genes in immunogenicity and immunotherapy efficacy.

Alzheimer's disease (AD) is characterized as a distinct onset and progression of cognitive and functional decline associated with age, as well as a specific neuropathology. It has been discovered that glutamine (Gln) metabolism plays a crucial role in cancer. However, a full investigation of its role in Alzheimer's disease is still missing. This study intended to find and confirm potential Gln-related genes associated with AD using bioinformatics analysis. The discovery of GlnMgs was made possible by the intersection of the WGCNA test and 26 Gln-metabolism genes (GlnMgs). GlnMgs' putative biological functions and pathways were identified using GSVA. The LASSO method was then used to identify the hub genes as well as the diagnostic efficiency of the four GlnMgs in identifying AD. The association between hub GlnMgs and clinical characteristics was also studied. Finally, the GSE63060 was utilized to confirm the levels of expression of the four GlnMgs. Four GlnMgs were discovered (ATP5H, NDUFAB1, PFN2, and SPHKAP). For biological function analysis, cell fate specification, atrioventricular canal development, and neuron fate specification were emphasized. The diagnostic ability of the four GlnMgs in differentiating AD exhibited a good value. This study discovered four GlnMgs that are linked to AD. They shed light on potential new biomarkers for AD and tracking its progression.

Constructing and Validating a Pyroptosis-Related Genes Prognostic Signature for Stomach Adenocarcinoma and Immune Infiltration: Potential Biomarkers for Predicting the Overall Survival.

Background: Stomach adenocarcinoma (STAD) is a kind of cancer that begins in the stomach cells and has a poor overall survival rate. Following resection surgery, chemotherapy has been suggested as a curative method for stomach cancer. However, it is ineffective. Pyroptosis, a kind of inflammatory programmed cell death, has been shown to play a significant role in the development and progression of STAD. However, whether pyroptosis-related genes (PRGs) can be utilized to predict the diagnosis and prognosis of gastric cancer remains unknown. Method: The research measured at predictive PRGs in STAD samples from TCGA and GEO. Lasso regression was used to build the prediction model. Coexpression analysis revealed that gene expression was linked to pyroptosis. PRGs were found to be overexpressed in high-risk individuals, implying that they could be used in a model to predict STAD prognosis. Result: Immunological and tumor-related pathways were discovered using GSEA. In STAD patients, the genes GPX3, PDGFRL, RGS2, and SERPINE1 may be connected to the cancer process. The levels of expression also differed between the two risk groups. Conclusion: The purpose of this study is to identify and verify STAD-associated PRGs that can effectively guide prognosis and the immunological milieu in STAD patients as well as offer evidence for the development of pyroptosis-related molecularly targeted therapeutics. Therefore, PRGs and the link between immunological and PRGs in STAD may be therapeutic targets.

Potential biomarkers for predicting the overall survival outcome of kidney renal papillary cell carcinoma: an analysis of ferroptosis-related LNCRNAs.

BACKGROUND: Kidney renal papillary cell carcinoma (KIRP) is a dangerous cancer, which accounts for 15-20% of all kidney malignancies. Ferroptosis is a rare kind of cell death that overcomes medication resistance. Ferroptosis-related long non-coding RNAs (LNCRNAs) in KIRP, remain unknown. METHOD: We wanted to express how ferroptosis-related LNCRNAs interact with immune cell infiltration in KIRP. Gene set enrichment analysis in the GO and KEGG databases were used to explore gene expression enrichment. The prognostic model was constructed using Lasso regression. In addition, we also analyzed the modifications in the tumor microenvironment (TME) and immunological association. RESULT: The expression of LNCRNA was closely connected to the ferroptosis, according to co-expression analyses. CASC19, AC090197.1, AC099850.3, AL033397.2, LINC00462, and B3GALT1-AS1 were found to be significantly increased in the high-risk group, indicating that all of these markers implicates the malignancy processes for KIRP patients and may be cancer-promoting variables. LNCTAM34A and AC024022.1 were shown to be significantly elevated in the low-risk group; these might represent as the KIRP tumor suppressor genes. According to the TCGA, CCR, and inflammation-promoting genes were considered to be significantly different between the low-risk and high-risk groups. The expression of CD160, TNFSF4, CD80, BTLA, and TNFRSF9 was different in the two risk groups. CONCLUSION: LNCRNAs associated with ferroptosis were linked to the occurrence and progression of KIRP. Ferroptosis-related LNCRNAs and immune cell infiltration in the TME may be potential biomarkers in KIRP that should be further investigated.

Long-term glycemic variability and risk of adverse health outcomes in patients with diabetes: A systematic review and meta-analysis of cohort studies.

AIMS: To quantify associations of different metrics of long-term glycemic variability (GV) with multiple adverse diabetes-related outcomes. METHODS: We searched PubMed and Embase from database inception to 23 August 2021. GV was based on measurements of HbA1c or fasting plasma glucose (FPG) and calculated by standard deviation (SD), coefficient of variance (CV) or other metrics. Outcomes included mortality, cardiovascular disease (CVD), renal disease, peripheral neuropathy, retinopathy, dementia and cancer. Random-effects meta-analyses were adopted to pool the relative risks (RRs). RESULTS: Seventy-five articles with 2,051,701 participants were included. When comparing top with bottom quartiles, HbA1c variabilities were associated with all-cause mortality (RRCV = 1.63, 95 % CI 1.37-1.92; RRSD = 1.87, 1.55-2.26), CVD (RRCV = 1.38, 1.07-1.78; RRSD = 1.34, 1.12-1.59), renal disease (RRCV = 1.43, 1.18-1.74; RRSD = 1.44, 1.24-1.67), and peripheral neuropathy (RRCV = 1.84, 1.40-2.43; RRSD = 1.98, 1.51-2.61), but not retinopathy. FPG variabilities were associated with all-cause mortality (RRCV = 1.59, 1.43-1.78; RRSD = 1.67, 1.26-2.20), renal disease (RRCV = 1.77, 1.32-2.38), and retinopathy (RRCV = 1.92, 1.10-3.35), but not CVD and peripheral neuropathy. Associations of GV with Alzheimer's disease (RRHbA1c-CV = 1.38, 1.13-1.70; RRFPG-CV = 1.32, 1.07-1.63) and cancer (RRHbA1c-SD = 2.19, 1.52-3.17; RRFPG-CV = 3.64, 2.21-5.98) were each found significant in one study. CONCLUSIONS: Long-term GV was associated with multiple adverse diabetes-related outcomes, while the strength of associations varied. The findings support the use of long-term GV for diabetes management in clinical practice.

Ovarian transcriptome and metabolic responses of RNAi-mediated farnesyl pyrophosphate synthase knockdown in Neocaridina denticulata sinensis.

Methyl farnesoate (MF) is considered the equivalent of JH in crustaceans and plays an essential role in many crucial physiological processes. It is believed that farnesyl pyrophosphate synthase (FPPS) plays an essential role in the biosynthesis of mevalonate, which is a branch of the JH/MF pathway. The full-length cDNA of FPPS (NdFPPS) from Neocaridina denticulata sinensis was isolated and characterized, and the deduced amino acid of NdFPPS contained a polyprenyl_synt domain. In addition to its ubiquitous tissue expression, NdFPPS was significantly expressed in the ovary. In vivo gene silencing with dsRNA interference was performed to further investigate the function of NdFPPS. An ovarian transcriptomic analysis of dsNdFPPS experimental and control groups was used to compare, annotate, and classify differentially expressed genes (DEGs). A total of 9230 DEGs were identified in the experimental and control groups based on FPKM values, of which 5082 were up-regulated genes and 4148 were down-regulated genes. 761 GO terms and 102 KEGG pathways were enriched for the DEGs. Our results suggest that NdFPPS might play an important role in ovarian development, however, further functional study is needed to elucidate physiological role of NdFPPS in reproduction.