Association between psychiatric disorders and glioma risk: evidence from Mendelian randomization analysis.

BACKGROUND: Observational studies have explored the association of psychiatric disorders and the risk of brain cancers. However, the causal effect of specific mental illness on glioma remains elusive due to the lack of solid evidence. METHODS: We performed a two-sample bidirectional Mendelian randomization (MR) analysis to explore the causal relationships between 5 common psychiatric disorders (schizophrenia, major depressive disorder, bipolar disorder, autism spectrum disorder, and panic disorder) and glioma. Summary statistics for psychiatric disorders and glioma were extracted from Psychiatric Genomics Consortium (PGC) and 8 genome-wide association study (GWAS) datasets respectively. We calculated the MR estimates for odds ratio of glioma associated with each psychiatric disorder by using inverse-variance weighting (IVW) method. Sensitivity analyses such as weighted median estimator, MR-Egger and MR-PRESSO were leveraged to assess the strength of causal inference. RESULTS: A total of 30,657 participants of European ancestry were included in this study. After correction for multiple testing, we found that genetically predicted schizophrenia was associated with a statistically significant increase in odds of non-glioblastoma multiforme (non-GBM) (OR = 1.13, 95% CI: 1.03-1.23, P = 0.0096). There is little evidence for the causal relationships between the other 4 psychiatric disorders with the risk of glioma. CONCLUSIONS: In this MR analysis, we revealed an increased risk of non-GBM glioma in individuals with schizophrenia, which gives an insight into the etiology of glioma.

P129, a pyrazole ring-containing isolongifolanone-derivate: synthesis and investigation of anti-glioma action mechanism.

BACKGROUND: Cyclin-dependent kinase-2 (CDK-2) is an important regulatory factor in the G1/S phase transition. CDK-2 targeting has been shown to suppress the viability of multiple cancers. However, the exploration and application of a CDK-2 inhibitor in the treatment of glioblastoma are sparse. METHODS: We synthesized P129 based on isolongifolanone, a natural product with anti-tumor activity. Network pharmacology analysis was conducted to predict the structural stability, affinity, and pharmacological and toxicological properties of P129. Binding analysis and CETSA verified the ability of P129 to target CDK-2. The effect of P129 on the biological behavior of glioma cells was analyzed by the cell counting kit-8, colony formation, flow cytometry, and other experiments. Western blotting was used to detect the expression changes of proteins involved in the cell cycle, cell apoptosis, and epithelial-mesenchymal transition. RESULTS: Bioinformatics analysis and CETSA showed that P129 exhibited good intestinal absorption and blood-brain barrier penetrability together with high stability and affinity with CDK-2, with no developmental toxicity. The viability, proliferation, and migration of human glioma cells were significantly inhibited by P129 in a dose- and time-dependent manner. Flow cytometry and western blotting analyses showed G0/G1 arrest and lower CDK-2 expression in cells treated with P129 than in the controls. The apoptotic ratio of glioma cells increased significantly with increasing concentrations of P129 combined with karyopyknosis and karyorrhexis. Apoptosis occurred via the mitochondrial pathway. CONCLUSION: The pyrazole ring-containing isolongifolanone derivate P129 exhibited promising anti-glioma activity by targeting CDK-2 and promoting apoptosis, indicating its potential importance as a new chemotherapeutic option for glioma.

Association between viral infections and glioma risk: a two-sample bidirectional Mendelian randomization analysis.

BACKGROUND: Glioma is one of the leading types of brain tumor, but few etiologic factors of primary glioma have been identified. Previous observational research has shown an association between viral infection and glioma risk. In this study, we used Mendelian randomization (MR) analysis to explore the direction and magnitude of the causal relationship between viral infection and glioma. METHODS: We conducted a two-sample bidirectional MR analysis using genome-wide association study (GWAS) data. Summary statistics data of glioma were collected from the largest meta-analysis GWAS, involving 12,488 cases and 18,169 controls. Single-nucleotide polymorphisms (SNPs) associated with exposures were used as instrumental variables to estimate the causal relationship between glioma and twelve types of viral infections from corresponding GWAS data. In addition, sensitivity analyses were performed. RESULTS: After correcting for multiple tests and sensitivity analysis, we detected that genetically predicted herpes zoster (caused by Varicella zoster virus (VZV) infection) significantly decreased risk of low-grade glioma (LGG) development (OR = 0.85, 95% CI: 0.76-0.96, P = 0.01, FDR = 0.04). No causal effects of the other eleven viral infections on glioma and reverse causality were detected. CONCLUSIONS: This is one of the first and largest studies in this field. We show robust evidence supporting that genetically predicted herpes zoster caused by VZV infection reduces risk of LGG. The findings of our research advance understanding of the etiology of glioma.

Smart Responsive and Controlled-Release Hydrogels for Chronic Wound Treatment.

Chronic wounds are a major health challenge that require new treatment strategies. Hydrogels are promising drug delivery systems for chronic wound healing because of their biocompatibility, hydration, and flexibility. However, conventional hydrogels cannot adapt to the dynamic and complex wound environment, which involves low pH, high levels of reactive oxygen species, and specific enzyme expression. Therefore, smart responsive hydrogels that can sense and respond to these stimuli are needed. Crucially, smart responsive hydrogels can modulate drug release and eliminate pathological factors by changing their properties or structures in response to internal or external stimuli, such as pH, enzymes, light, and electricity. These stimuli can also be used to trigger antibacterial responses, angiogenesis, and cell proliferation to enhance wound healing. In this review, we introduce the synthesis and principles of smart responsive hydrogels, describe their design and applications for chronic wound healing, and discuss their future development directions. We hope that this review will inspire the development of smart responsive hydrogels for chronic wound healing.

Neutrophil Percentage-to-Albumin Ratio and Risk of Mortality in Patients on Peritoneal Dialysis.

Background: Neutrophil percentage-to-albumin ratio (NPAR), a new inflammatory marker, has been shown to be associated with poor prognosis in patients with cardiovascular disease. However, limited evidence is available for its role in peritoneal dialysis (PD) patients. Our study aimed at investigating the prognostic value of NPAR for mortality in PD patients. Patients and Methods: This was a single center retrospective cohort study. A total of 1966 PD patients were enrolled in our study from January 2006 to December 2016 and were followed up until December 2021. Patients were stratified into tertiles according to baseline NPAR levels. The associations between NPAR levels with all-cause and cardiovascular mortality were estimated using Cox proportional hazards models. Receiver operating characteristic (ROC) analysis was performed to compare the mortality predictive values of NPAR and other known biomarkers, such as NLR (neutrophil-to-lymphocyte ratio), PLR (platelet-to-lymphocyte ratio), LHR (low-density lipoprotein cholesterol-to-high-density lipoprotein cholesterol ratio) and MLR (monocyte-to-lymphocyte ratio). Results: During a median follow-up of 48.1 months, 503 (25.6%) patients died, in which cardiovascular disease (CVD) death dominated 50.3%. Multivariate Cox regression analysis revealed that the highest NPAR tertile was significantly associated with a higher risk of all-cause and cardiovascular mortality (HR 1.51, 95% CI 1.14-1.98; HR 1.57, 95% CI 1.07-2.31; respectively) compared with tertile 1. The AUC values of NPAR were 0.62 (95% CI 0.60-0.65, P < 0.001) for all-cause mortality and 0.61 (95% CI 0.57-0.65, P < 0.001) for cardiovascular mortality. Conclusion: Our study showed that higher NPAR levels were independently associated with increased risk of all-cause and cardiovascular mortality in PD patients. Notably, our results demonstrated that NPAR exhibited superior predictive value for mortality compared to NLR, PLR, MLR, and LHR.

COVID-19 hospitalization increases the risk of developing glioblastoma: a bidirectional Mendelian-randomization study.

Background: As a result of the COVID-19 pandemic, patients with glioblastoma (GBM) are considered a highly vulnerable population. Despite this, the extent of the causative relationship between GBM and COVID-19 infection is uncertain. Methods: Genetic instruments for SARS-CoV-2 infection (38,984 cases and 1,644,784 control individuals), COVID-19 hospitalization (8,316 cases and 1,549,095 control individuals), and COVID-19 severity (4,792 cases and 1,054,664 control individuals) were obtained from a genome-wide association study (GWAS) from European populations. A total of 6,183 GBM cases and 18,169 controls from GWAS were enrolled in our study. Their associations were evaluated by applying Mendelian randomization (MR) including IVW meta-analysis, MR-Egger regression, and weighted-median analysis. To make the conclusions more robust and reliable, sensitivity analyses were performed. Results: Our results showed that genetically predicted COVID-19 hospitalization increases the risk of GBM (OR = 1.202, 95% CI = 1.035-1.395, p = 0.016). In addition, no increased risk of SARS-CoV-2 infection, COVID-19 hospitalization and severity were observed in patients with any type of genetically predicted GBM. Conclusion: Our MR study indicated for the first time that genetically predicted COVID-19 hospitalization was demonstrated as a risk factor for the development of GBM.

Development of an MCL-1-related prognostic signature and inhibitors screening for glioblastoma.

Introduction: The effect of the conventional treatment methods of glioblastoma (GBM) is poor and the prognosis of patients is poor. The expression of MCL-1 in GBM is significantly increased, which shows a high application value in targeted therapy. In this study, we predicted the prognosis of glioblastoma patients, and therefore constructed MCL-1 related prognostic signature (MPS) and the development of MCL-1 small molecule inhibitors. Methods: In this study, RNA-seq and clinical data of 168 GBM samples were obtained from the TCGA website, and immunological analysis, differential gene expression analysis and functional enrichment analysis were performed. Subsequently, MCL-1-associated prognostic signature (MPS) was constructed and validated by LASSO Cox analysis, and a nomogram was constructed to predict the prognosis of patients. Finally, the 17931 small molecules downloaded from the ZINC15 database were screened by LibDock, ADME, TOPKAT and CDOCKER modules and molecular dynamics simulation in Discovery Studio2019 software, and two safer and more effective small molecule inhibitors were finally selected. Results: Immunological analysis showed immunosuppression in the MCL1_H group, and treatment with immune checkpoint inhibitors had a positive effect. Differential expression gene analysis identified 449 differentially expressed genes. Build and validate MPS using LASSO Cox analysis. Use the TSHR HIST3H2A, ARGE OSMR, ARHGEF25 build risk score, proved that low risk group of patients prognosis is better. Univariate and multivariate analysis proved that risk could be used as an independent predictor of patient prognosis. Construct a nomogram to predict the survival probability of patients at 1,2,3 years. Using a series of computer-aided techniques, two more reasonable lead compounds ZINC000013374322 and ZINC000001090002 were virtually selected. These compounds have potential inhibitory effects on MCL-1 and provide a basis for the design and further development of MCL-1 specific small molecule inhibitors. Discussion: This study analyzed the effect of MCL-1 on the prognosis of glioblastoma patients from the perspective of immunology, constructed a new prognostic model to evaluate the survival rate of patients, and further screened 2 MCL-1 small molecule inhibitors, which provides new ideas for the treatment and prognosis of glioblastoma.

Inflammatory factors and risk of meningiomas: a bidirectional mendelian-randomization study.

Background: Meningiomas are one of the most common intracranial tumors, and the current understanding of meningioma pathology is still incomplete. Inflammatory factors play an important role in the pathophysiology of meningioma, but the causal relationship between inflammatory factors and meningioma is still unclear. Method: Mendelian randomization (MR) is an effective statistical method for reducing bias based on whole genome sequencing data. It's a simple but powerful framework, that uses genetics to study aspects of human biology. Modern methods of MR make the process more robust by exploiting the many genetic variants that may exist for a given hypothesis. In this paper, MR is applied to understand the causal relationship between exposure and disease outcome. Results: This research presents a comprehensive MR study to study the association of genetic inflammatory cytokines with meningioma. Based on the results of our MR analysis, which examines 41 cytokines in the largest GWAS datasets available, we were able to draw the relatively more reliable conclusion that elevated levels of circulating TNF-ß, CXCL1, and lower levels of IL-9 were suggestive associated with a higher risk of meningioma. Moreover, Meningiomas could cause lower levels of interleukin-16 and higher levels of CXCL10 in the blood. Conclusion: These findings suggest that TNF-ß, CXCL1, and IL-9 play an important role in the development of meningiomas. Meningiomas also affect the expression of cytokines such as IL-16 and CXCL10. Further studies are needed to determine whether these biomarkers can be used to prevent or treat meningiomas.

Cerebrospinal fluid protein levels are elevated 100 times in a Leptomeningeal metastasis patient: a case report and literature review.

Leptomeningeal metastasis (LM) has a high degree of malignancy and high mortality. We describe a patient admitted to hospital with acute lower extremity weakness, dysuria, and high intracranial pressure. Enhanced magnetic resonance imaging (MRI) showed extensive enhancement of the leptomeningeal and spinal meninges with multiple nodular changes and extensive fusion. His cerebrospinal fluid (CSF) was yellow and cloudy, the Pandy test was strongly positive (++++), the protein was 46 g/L (normal range 0.15-0.45 g/L), which attracted our attention. Initially, miliary TB with associated tuberculous meningitis (TBM) was diagnosed, and neurosarcoidosis cannot be ruled out. After poor therapeutic effect of standard antituberculosis (anti-TB) therapy, further inspection found that malignant cells were detected by cerebrospinal fluid (CSF) cytology. PET/CT suggested the diagnosis of LM. The purpose of this paper is to describe the characteristics of atypical diffuse LM. In conclusion, when patient with unexplained high levels of CSF protein, it is necessary to be alert to the diagnosis of LM. Multiple examinations of fresh CSF are helpful to increase the positive detection rate of tumor cells. Early diagnosis and active treatment are conducive to improving survival rate.

Computational study of novel natural inhibitors targeting Kirsten rat sarcoma viral oncogene homolog G12C.

Lung adenocarcinoma is one of the most aggressive and rapidly fatal types of malignant lung tumor. Molecular docking and virtual screening were effectively and systematically used to identify specific targets in malignant tumors and screen potential drugs. Here, we screen perfect leading compounds from a medicate library (ZINC15 database) and analyze their properties (conveyance, absorption, metabolism, excretion, and harmless forecasts) with potential inhibition of Kirsten Rat Sarcoma Viral Oncogene Homolog (KRAS) G12C. Further results demonstrated that ZINC000013817014 and ZINC000004098458 were screened out from the ZINC15 database and were identified to have a much better binding affinity and more favorable interaction vitality binding with KRAS G12C and less rat carcinogenicity, Ames mutagenicity, way better dissolvability in water and noninhibition with cytochrome P-450 2D6. Molecular dynamics simulation analysis indicated that the binding capacity of these two compounds and KRAS G12C, ZINC000013817014-KRAS G12C, and ZINC000004098458-KRAS G12C is stable in the natural environment. Our findings reveal that ZINC000013817014 and ZINC000004098458 were perfect leading compounds to be inhibitors binding with KRAS G12C, which were selected as safe drug candidates and a cornerstone for KRAS G12C-related medicine plan and improvement. What is more, we have conducted a Cell Counting Kit-8 to verify the exactly inhibitory effects of the two selected drugs on Lung adenocarcinoma. This study establishes a solid framework for systematic anticancer medication research and development.

Differential regulation of H3K9/H3K14 acetylation by small molecules drives neuron-fate-induction of glioma cell.

Differentiation therapy using small molecules is a promising strategy for improving the prognosis of glioblastoma (GBM). Histone acetylation plays an important role in cell fate determination. Nevertheless, whether histone acetylation in specific sites determines GBM cells fate remains to be explored. Through screening from a 349 small molecule-library, we identified that histone deacetylase inhibitor (HDACi) MS-275 synergized with 8-CPT-cAMP was able to transdifferentiate U87MG GBM cells into neuron-like cells, which were characterized by cell cycle arrest, rich neuron biomarkers, and typical neuron electrophysiology. Intriguingly, acetylation tags of histone 3 at lysine 9 (H3K9ac) were decreased in the promoter of multiple oncogenes and cell cycle genes, while ones of H3K9ac and histone 3 at lysine 14 (H3K14ac) were increased in the promoter of neuron-specific genes. We then compiled a list of genes controlled by H3K9ac and H3K14ac, and proved that it is a good predictive power for pathologic grading and survival prediction. Moreover, cAMP agonist combined with HDACi also induced glioma stem cells (GSCs) to differentiate into neuron-like cells through the regulation of H3K9ac/K14ac, indicating that combined induction has the potential for recurrence-preventive application. Furthermore, the combination of cAMP activator plus HDACi significantly repressed the tumor growth in a subcutaneous GSC-derived tumor model, and temozolomide cooperated with the differentiation-inducing combination to prolong the survival in an orthotopic GSC-derived tumor model. These findings highlight epigenetic reprogramming through H3K9ac and H3K14ac as a novel approach for driving neuron-fate-induction of GBM cells.

Gene therapy targeting miR­212­3p exerts therapeutic effects on MAFLD similar to those of exercise.

Exercise is the main treatment for patients with metabolic­associated fatty liver disease (MAFLD); however, it may be difficult for some patients to adhere to or tolerate an exercise regime. Thus, finding a treatment alternative to exercise is of particular importance. The authors have previously demonstrated that the high expression of microRNA (miRNA/miR)­212 promotes lipogenesis in vitro. The present study aimed to explore the therapeutic potential, as well as the mechanisms of action of miR­212 in MAFLD. The expression of miR­212­3p, but not that of miR­212­5p, was found to be significantly elevated in MAFLD and to be decreased by exercise. Compared with exercise treatment, the inhibition of miR­212­3p expression in a mouse model fed a high­fat diet exerted beneficial effects on MAFLD similar to those of exercise. Conversely, the overexpression of miR­212­3p abolished the ameliorative effects of exercise on MAFLD. Fibroblast growth factor 21 (FGF21) and chromodomain helicase DNA binding protein 1 (CHD1) were identified as target genes of miR­212­3p in lipid metabolism using bioinformatics analysis. Mechanistically, the inhibition of miR­212­3p mimicked the effects of exercise on lipid metabolism by regulating FGF21, but not CHD1. The exercise­related transcription factor, early growth response 1 (EGR1), was identified upstream of miR­212­3p through promoter motif analysis. EGR1 overexpression inhibited miR­212­3p expression. The overexpression of miR­212­3p abolished the effects of exercise on lipid metabolism by exogenously attenuating the transcriptional repression of EGR1. Moreover, the overexpression of miR­212­3p abolished the regulatory effects of EGR1 on FGF21. On the whole, the present study demonstrates that miR­212­3p plays a key role in the effects of exercise on MAFLD. The findings presented herein suggest a potential therapeutic effect of targeting miR­212­3p in MAFLD.

The Flavonoid Components of Scutellaria baicalensis: Biopharmaceutical Properties and their Improvement using Nanoformulation Techniques.

Scutellaria baicalensis georgi, known as "Huangqin" in its dried root form, is a herb widely used in traditional Chinese medicine for "clearing away heat, removing dampness, purging fire and detoxification". Baicalin, baicalein, wogonin, and wogonoside are the main flavonoid compounds found in Scutellaria baicalensis. Scutellaria baicalensis flavonoid components have the potential to prevent and treat a host of diseases. The components of S. baicalensis have limited clinical application due to their low water solubility, poor permeability, and microbial transformation in vivo. Nanopharmaceutical techniques can improve their biopharmaceutical properties, enhance their absorption in vivo, and improve their bioavailability. However, due to the limited number of clinical trials, doubts remain about their toxicity and improvements in human absorption as a result of nanoformulations. This review summarizes the latest and most comprehensive information regarding the absorption, distribution, metabolism, and excretion of the Scutellaria baicalensis components in vivo. We examined the main advantages of nanodrug delivery systems and collected detailed information on the nanosystem delivery of the Scutellaria baicalensis components, including nanosuspensions and various lipid-based nanosystems. Lipid-based systems including liposomes, solid lipid nanoparticles, nanoemulsions, and self-micro emulsifying drug delivery systems are introduced in detail. In addition, we make recommendations for related and future research directions. Future research should further examine the absorption mechanisms and metabolic pathways of nanoformulations of the components of Scutellaria baicalensis in vivo, and accurately track the in vivo behavior of these drug delivery systems to discover the specific reasons for the enhanced bioavailability of nanoformulations of the scutellaria baicalensis components. The development of targeted oral administration of intact nanoparticles of Scutellaria baicalensis components is an exciting prospect.

Predicting glioblastoma molecular subtypes and prognosis with a multimodal model integrating convolutional neural network, radiomics, and semantics.

OBJECTIVE: The aim of this study was to build a convolutional neural network (CNN)-based prediction model of glioblastoma (GBM) molecular subtype diagnosis and prognosis with multimodal features. METHODS: In total, 222 GBM patients were included in the training set from Sun Yat-sen University Cancer Center (SYSUCC) and 107 GBM patients were included in the validation set from SYSUCC, Xuanwu Hospital Capital Medical University, and the First Hospital of Jilin University. The multimodal model was trained with MR images (pre- and postcontrast T1-weighted images and T2-weighted images), corresponding MRI impression, and clinical patient information. First, the original images were segmented using the Multimodal Brain Tumor Image Segmentation Benchmark toolkit. Convolutional features were extracted using 3D residual deep neural network (ResNet50) and convolutional 3D (C3D). Radiomic features were extracted using pyradiomics. Report texts were converted to word embedding using word2vec. These three types of features were then integrated to train neural networks. Accuracy, precision, recall, and F1-score were used to evaluate the model performance. RESULTS: The C3D-based model yielded the highest accuracy of 91.11% in the prediction of IDH1 mutation status. Importantly, the addition of semantics improved precision by 11.21% and recall in MGMT promoter methylation status prediction by 14.28%. The areas under the receiver operating characteristic curves of the C3D-based model in the IDH1, ATRX, MGMT, and 1-year prognosis groups were 0.976, 0.953, 0.955, and 0.976, respectively. In external validation, the C3D-based model showed significant improvement in accuracy in the IDH1, ATRX, MGMT, and 1-year prognosis groups, which were 88.30%, 76.67%, 85.71%, and 85.71%, respectively (compared with 3D ResNet50: 83.51%, 66.67%, 82.14%, and 70.79%, respectively). CONCLUSIONS: The authors propose a novel multimodal model integrating C3D, radiomics, and semantics, which had a great performance in predicting IDH1, ATRX, and MGMT molecular subtypes and the 1-year prognosis of GBM.

A comparative study on roles of natural killer T cells in two diet-induced non-alcoholic steatohepatitis-related fibrosis in mice.

BACKGROUND: Immune responses are important in the progression of non-alcoholic fatty liver disease (NAFLD). Natural killer T (NKT) cells are main components of the innate immune system that modulate immunity. However, the role of NKT cells in NAFLD remains controversial. OBJECTIVE: We aimed to investigate the role of NKT cells in non-alcoholic steatohepatitis (NASH)-related fibrosis in fast food diet (FFD)- and methionine choline-deficient (MCD) diet-induced mouse models. METHODS: Hepatic NKT cells were analysed in wild-type (WT) and CD1d-/- mice fed FFD or MCD diets. Hepatic pathology, cytokine profiles and liver fibrosis were evaluated. Furthermore, the effect of chronic administration of α-galactosylceramide (α-GalCer) on liver fibrosis was investigated in both FFD- and MCD-treated mice. RESULTS: FFD induced a significant depletion of hepatic NKT cells, thus leading to mild to moderate NASH and early-stage fibrosis, while mice fed MCD diets developed severe liver inflammation and progressive fibrosis without a significant change in hepatic NKT cell abundance. FFD induced a similar liver fibrogenic response in CD1d-/- and WT mice, while MCD induced a higher hepatic mRNA expression of Col1α1 and TIMP1 as well as relative fibrosis density in CD1d-/- mice than WT mice (31.8 vs. 16.3, p = .039; 40.0 vs. 22.6, p = .019; 2.24 vs. 1.59, p = .036). Chronic administration of α-GalCer induced a higher hepatic mRNA expression of TIMP1 in MCD-treated mice than controls (36.7 vs. 14.9, p = .005). CONCLUSION: NKT cells have protective roles in NAFLD as the disease progresses. During diet-induced steatosis, mild to moderate NASH and the early stage of fibrosis, hepatic NKT cells are relatively depleted, leading to a proinflammatory status. In severe NASH and the advanced stage of liver fibrosis, NKT cells play a role in inhibiting the NASH-related fibrogenic response. Chronic administration of α-GalCer induces NKT cell anergy and tolerance, which may play a role in promoting the liver fibrogenic response.

ELOVLs Predict Distinct Prognosis Value and Immunotherapy Efficacy In Patients With Hepatocellular Carcinoma.

Background: Hepatocellular carcinoma (HCC) is a primary malignancy of the liver with high prevalence worldwide and poor prognosis. It has been verified that elongation of very-long-chain fatty acids gene family (ELOVLs), a group of genes that responsible for elongation of saturated and polyunsaturated fatty acids, participate in the pathogenesis and development of multiplex disease including cancers. However, the functions and prognosis of ELOVLs in HCC are still indistinguishable. Methods: First, we searched the mRNA expression and survival data of ELOVLs in patients with HCC via the data of The Cancer Genome Atlas (TCGA). The prognosis value of ELOVLs on HCC was assessed by Kaplan-Meier plotter and Cox regression analysis. reverse transcription quantitative- polymerase chain reaction (RT-qPCR), Western blot (WB), and immunohistochemistry were applied to assess the specific mRNA and protein expression of ELOVLs in HCC clinical specimens of our cohort. Then, the functional enrichment of ELOVL1 especially the pathways relating to the immune was conducted utilizing the Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA) analysis. Additionally, TIMER, CIBERSOR, and tumor immune dysfunction and exclusion (TIDE) were employed to evaluate the relationship between ELOVL1 and immune responses. Last, the correlation of ELOVL1 with genome heterogeneity [microsatellite instability (MSI), tumor mutational burden (TMB), mutant-allele tumor heterogeneity (MATH), homologous recombination deficiency (HRD), purity, ploidy, loss of heterozygosity (LOH), and neoantigens] and mutational landscape were also evaluated basing on the date in TCGA. Results: Significant expression alteration was observed in ELOVLs family at the pan-cancer level. In liver cancer, ELOVL1 and ELOVL3 were strongly associated with poor prognosis of HCC by survival analysis and differential expression analysis. Immunohistochemistry microarray, WB, and RT-qPCR confirmed that ELOVL1 but not ELOVL3 played an important role in HCC. Mechanistically, functional network analysis revealed that ELOVL1 might be involved in the immune response. ELOVL1 could affect immune cell infiltration and immune checkpoint markers such as PD-1 and CTLA4 in HCC. Meanwhile, high expression of ELOVL1 would be insensitive to immunotherapy. Correlation analysis of immunotherapy markers showed that ELOVL1 has been associated with MSI, TMB, and oncogene mutations such as TP53. Conclusion: ELOVLs play distinct prognostic value in HCC. ELOVL1 could predict the poor prognosis and might be a potential indicator of immunotherapy efficacy in HCC patients.

Identification and validation of immune related core transcription factors GTF2I in NAFLD.

Background: Nonalcoholic fatty liver disease (NAFLD) is the most common liver disease worldwide that endangers human health. Transcription factors (TFs) have gradually become hot spots for drug development in NAFLD for their impacts on metabolism. However, the specific TFs that regulate immune response in the development of NAFLD is not clear. This study aimed to investigate the TFs involved in the immune response of NAFLD and provide novel targets for drug development. Methods: Microarray data were obtained from liver samples from 26 normal volunteers and 109 NAFLD patients using the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were analyzed by limma package. Differentially expressed transcription factors (DETFs) were obtained on DEGs combined with Cistrome Cancer database. Immune signatures and pathways hallmark were identified by ssGSSEA and GSVA. The co-regulation network was constructed by the above results. Further, quantitative Real-time Polymerase Chain Reaction (qRT-PCR), Western blot (WB) and Immunohistochemistry (IHC) were used to validate the relationship between GTF2I and NAFLD. CIBERSORT analysis was performed to identify cell types to explore the relationship between differential expression of GTF2I and immune cell surface markers. Results: A total of 617 DEGs and six DETFs (ESR1, CHD2, GTF2I, EGR1, HCFC1, SP2) were obtained by differential analysis. Immune signatures and pathway hallmarks were identified by ssGSSEA and GSVA. GTF2I and CHD2 were screened through the co-regulatory networks of DEGs, DETFs, immune signatures and pathway hallmarks. Furthermore, qRT-PCR, WB and IHC indicated that GTF2I but not CHD2 was significantly upregulated in NAFLD. Finally, in silico, our data confirmed that GTF2I has a wide impact on the immune profile by negatively regulating the expression of the chemokine receptor family (227/261, count of significance). Conclusion: GTF2I plays a role in NAFLD by negatively regulating the chemokine receptor family, which affects the immune profile. This study may provide a potential target for the diagnosis or therapy of NAFLD.

Case Report: A Case of Adult Methylmalonic Acidemia With Bilateral Cerebellar Lesions Caused by a New Mutation in MMACHC Gene.

Methylmalonic acidemia is a severe heterogeneous disorder of methylmalonate and cobalamin (Cbl; vitamin B12) metabolism with poor prognosis. Around 90% of reported patients with methylmalonic acidemia (MMA) are severe infantile early onset, while cases with late-onset MMA have been rarely reported. Few reported late-onset MMA patients presented with atypical clinical symptoms, therefore, often misdiagnosed if without family history. Herein, we report a 29-year-old female who was admitted to our hospital due to symptoms manifested as encephalitis. The brain MRI showed symmetrical bilateral cerebellar lesions with Gd enhancement. Laboratory tests showed significantly elevated levels of homocysteine and methylmalonic acid. A genetic analysis identified a novel homozygous mutation (c.484G>A; p.Gly162 Arg) in the MMACHC gene. The patient was diagnosed with MMA, and her symptoms improved dramatically with intramuscular adenosine cobalamin treatment. In conclusion, for patients with symmetrical lesions in the brain, the possibility of metabolic diseases should be considered, detailed medical and family history should be collected, and metabolic screening tests as well as gene tests are necessary for correct diagnosis. The mutation diversity in MMACHC gene is an important factor leading to the heterogeneity of clinical manifestations of patients with MMA.

Identification of novel natural inhibitors targeting AKT Serine/Threonine Kinase 1 (AKT1) by computational study.

Despite great progress, the current cancer treatments often have obvious toxicity and side effects. and a poor prognosis (some patients). One of the reasons for the poor prognosis is that certain enzymes prevent anticancer drugs from killing tumor cells. AKT1 is involved in regulating PI3K/AKT/mTOR, a tumor-generating pathway. Ipatasertib, a highly selective inhibitor of AKT1, is widely used in the treatment of tumors. In this study, many structural and biochemical methodswere used to find better AKT1(Threonine Kinase 1) inhibitors, which laid a foundation for the further development of AKT1 inhibitors and provided new drugs for the treatment of tumors. ZINC15 database and Discovery Studio 4.5, a computer-aided drug screening software with many modules (LibDock for virtual screening, ADME (Absorption, Distribution, Metabolism, Excretion) and TOPKAT (toxicity prediction module) for the toxicity and properties analysis, and MD simulation for stability prediction), were employed. CCK8 assay, ELISA assay genicity and higher tolerance to cytochrome P4502D6. MD simulations indicated they could bind with AKT1 stably in the natural environment. The cell experiment and specific assay for AKT1 inhibition showed they could inhibit the proliferation and AKT1 expression of MG63 cells (Osteosarcoma cells). Moreover, these novel compounds with structural modifications can be potential contributors that lead to further rational drug design for targeting AKT1.AbbreviationAKT1, AKT Serine/Threonine Kinase 1; ADME, absorption, distribution, metabolism, excretion; TOPKAT, toxicity prediction by Computer assisted technology; CCK8, Cell Counting Kit 8; ELISA, Enzyme-linked immunosorbent assay; CYP2D6, cytochrome P4502D6 inhibition; GBM, Glioblastoma; AGC kinase, protein kinase A, G, and C families (PKA, PKC, PKG); PKB, protein kinase B; PAM pathway, PI3K/AKT/mTOR pathway; OS, overall survival; PFS, progression-free survival; LD50, lethal dose half in rats; LOAEL, lowest observed adverse effect level; NPT, normal pressure and temperature; PME, particle mesh Ewald; LINCS, linear constraint solver; RMSD, root-mean-square deviation; BBB, blood-brain barrier; DS, Discovery Studio; DTP, Developmental toxicity potential; PPB, Plasma protein binding; MTD, Maximum Tolerated Dosage; AB, Aerobic Biodegradability; NTP, US. National Toxicology Program; DTP, developmental toxicity potential.

A clinical and laboratory-based nomogram for predicting nonalcoholic fatty liver disease in non-diabetic adults: a cross-sectional study.

BACKGROUND: Although the close relationship between nonalcoholic fatty liver disease (NAFLD) and insulin resistance has been clarified and there is a five-fold higher prevalence of NAFLD in patients with diabetes compared to that in patients without diabetes, this is not a reason to focus only on the incidence of NAFLD in people with diabetes because people who are insulin resistant are not necessarily diagnosed with diabetes, which leads to the overlook of NAFLD in non-diabetic population. Actually, we are obligated to pay more attention to the non-diabetic population for early detection and intervention of NAFLD. There is a lack of a convenient tool for predicting NAFLD in non-diabetic adults, and thus we aim to develop and validate a novel clinical nomogram to predict NAFLD among non-diabetic population to save more medical resources and make less missed diagnosis. METHODS: Researchers initially enrolled 20,944 patients and excluded those with history of drinking, known medication usage, viral hepatitis, known liver disease, missing covariant data, age <18 years, and impaired fasting blood glucose, leaving 14,251 adults participating in the baseline analysis, who were randomly divided in a ratio of 3:1 into a training dataset with 10,689 participants and a validation dataset with 3,562 participants, using the classification and regression training (caret) package in R software v. 4.0.3. Variables for prediction were selected by multivariable logistic regression analysis, the LASSO method, and clinical experience. Based on these, we constructed a prediction model. Performance of this model was validated by the area under the receiver operator characteristic curve, calibration curve, and decision curve analysis. RESULTS: We used 6 variables to construct the prediction model: body mass index (BMI), aspartate aminotransferase (AST), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), hemoglobin A1c (HbA1c), and diastolic blood pressure (DBP). In the training and validation datasets, the AUROC value of this prediction was 0.891 [95% confidence interval (CI): 0.884 to 0.899] and 0.902 (95% CI: 0.890 to 0.914), respectively. The calibration plots and the decision curve analysis (DCA) demonstrated that the accuracy of this model was good, with high clinical practicability. CONCLUSIONS: The nomogram could screen non-diabetic adults for NAFLD and may aid clinical decision-making.