Disulfidptosis-related gene expression reflects the prognosis of drug-resistant cancer patients and inhibition of MYH9 reverses sorafenib resistance.

The onset of drug resistance in advanced cancer patients markedly diminishes their prognosis. Recently, disulfidptosis, a novel form of cell death, has been identified, triggered by excessive disulfide formation leading to cell shrinkage and F-actin contraction. Previous studies have identified 15 essential genes (FLNA, FLNB, MYH9, TLN1, ACTB, MYL6, MYH10, CAPZB, DSTN, IQGAP1, ACTN4, PDLIM1, CD2AP, INF2, SLC7A11) associated with disulfidptosis. This study sourced pan-cancer mRNA expression data from Xena to thoroughly evaluate the molecular and clinical characteristics of disulfidptosis-related genes. Through unsupervised clustering, mRNA expression data identified the expression levels of disulfidptosis-related genes and potential clusters related to this form of cell death. Kaplan-Meier survival curves illustrated the correlation between different clusters and overall survival. The findings reveal that high expression of disulfidptosis-related genes is linked to poor survival in liver cancer. The GDSC database was utilized to analyze the relationship between disulfidptosis-related genes and the AUC of 198 drugs. The results demonstrate that 12 disulfidptosis-related genes influence sorafenib resistance, as revealed by the intersection of differential genes related to sorafenib resistance from the GSE109211 dataset. Among them, the MYH9 gene was found to play a crucial role in both. Finally, experimental evidence confirmed that MYH9 mitigates sorafenib resistance in hepatocellular carcinoma through disulfidptosis-like changes. This study identifies disulfidptosis as a promising avenue for enhancing the sensitivity of tumor cells to drugs, offering new therapeutic perspectives for future research on disulfidptosis and drug resistance in cancer patients.

Advances in clinical trials on perioperative immune checkpoint inhibitors for resectable non-small cell lung cancer: A comprehensive review.

The reduction in lung cancer mortality rates over the past decade can be partially ascribed to advancements in immunotherapy. Immune checkpoint inhibitors (ICIs) have transformed the therapeutic landscape for advanced non-small cell lung cancer (NSCLC) and have recently been evaluated in multiple clinical trials to confirm their safety and efficacy in the neoadjuvant, adjuvant and perioperative settings for patients with resectable NSCLC. The Food and Drug Administration (FDA) has granted approval for adjuvant atezolizumab following platinum-doublet chemotherapy, neoadjuvant nivolumab and platinum-doublet chemotherapy, adjuvant pembrolizumab after platinum-doublet chemotherapy, and neoadjuvant/adjuvant pembrolizumab for resectable NSCLC, with potential forthcoming approvals for additional agents or indications. Novel data, approvals, and emerging research findings are dramatically shifting the accepted standards of care over just a few years. Despite these advances, the optimal application of these treatments is not entirely straightforward. This article summarizes the biological rationale for immunotherapy and the important clinical trials regarding perioperative ICIs. We also further outline the controversies and future directions to better guide the individualized treatment of NSCLC patients.

Predicting the risk of in-hospital mortality in traumatic brain injury patients on invasive mechanical ventilation in the intensive care unit: Construction and validation of an online nomogram.

OBJECTIVE: To explore mortality risk factors and to construct an online nomogram for predicting in-hospital mortality in traumatic brain injury (TBI) patients receiving invasive mechanical ventilation (IMV) in intensive care unit (ICU). METHODS: We retrospectively analysed TBI patients on IMV in ICU from MIMIC-Ⅳ database and two hospitals. Least Absolute Shrinkage and Selection Operation (LASSO) regression and multiple logistic regression were used to detect predictors of in-hospital mortality and to construct an online nomogram. The predictive performance of nomogram was evaluated using area under the receiver operating characteristic curves (AUC), calibration curves, decision curve analysis (DCA), and clinical impact curves (CIC). RESULTS: 510 from MIMIC-Ⅳ database were enrolled for nomogram construction (80%, n=408) and internal validation (20%, n=102). 185 from two hospitals were enrolled for external validation. LASSO-Logistic regression revealed predictors of in-hospital mortality among TBI patients on IMV in ICU included Glasgow Coma Scale (GCS) after ICU admission, Acute Physiology Score Ⅲ (APS Ⅲ) after ICU admission, neutrophil and lymphocyte ratio after IMV, blood urea nitrogen after IMV, arterial serum lactate after IMV, and in-hospital tracheotomy. The AUC, calibration curves, DCA, and CIC indicated the nomogram had good discrimination, calibration, clinical benefit, and applicability. The multi-model comparisons revealed the nomogram had higher AUC than GCS, APS Ⅲ, and Simplified Acute Physiology Score Ⅱ. CONCLUSION: We constructed and validated an online nomogram based on routinely recorded factors at admission to ICU and at the beginning of IMV to target prediction of in-hospital mortality among TBI patients on IMV in ICU.

Identification of Immune Gene Signature Associated with T Cells and Natural Killer Cells in Type 1 Diabetes.

Purpose: This study aimed to investigate the abnormal infiltration of immune cells in type 1 diabetes mellitus (T1D) and elucidate their regulatory mechanisms. Methods: Public T1D-related gene expression data were obtained from the Gene Expression Omnibus database.The GSE123658 dataset analyzed whole blood RNA-seq data from type 1 diabetic patients and healthy volunteers. The GSE110914 dataset analyzed neutrophils purified from peripheral blood of patients with symptomatic and pre-symptomatic type 1 diabetes (T1D), at risk of T1D, and healthy controls. Immune cell infiltration analysis was performed to identify abnormally infiltrating immune cells. Differentially expressed immune genes (DEIGs) in T1D samples were identified, followed by the construction of an immune gene signature (IGS) using a protein-protein interaction (PPI) network and Least absolute shrinkage and selection operator Cox regression analyses (LASSO Cox regression analyses). The regulatory mechanisms underlying IGS were explored using gene set enrichment analysis. Furthermore, expression validation, diagnostic efficacy evaluation, and upstream miRNA prediction of hub signature genes were performed. We verified the miRNA expression of the key gene colony stimulating factor 1 (CSF1) and microRNA-326 (miR-326) by reverse transcription-quantitative PCR (RT‒qPCR). Results: The proportion of infiltrating T and natural killer (NK) cells differed between the T1D and control samples, and 207 immune genes (IGs) related to these immune cells were extracted. After differential expression, PPI, and LASSO Cox regression analyses, four signature DEIGs were identified for IGS construction: notch receptor 1 (NOTCH1), Janus kinase 3 (JAK3), tumor necrosis factor receptor superfamily member 4(TNFRSF4), and CSF1. Key pathways such as the Toll-like receptor signaling pathway were significantly activated in the high-risk group. Moreover, the upregulation of CSF1 in T1D samples was confirmed using a validation dataset, and CSF1 showed high diagnostic efficacy for T1D. Furthermore, CSF1 was targeted by miR-326.We used validated key genes in T1D patients, several of which were confirmed by RT‒qPCR. Conclusion: In conclusion, the identified key IGs may play an important role in T1D. CSF1 can be developed as a novel diagnostic biomarker for T1D.

Decoding the fish genome opens a new era in important trait research and molecular breeding in China.

Aquaculture represents the fastest-growing global food production sector, as it has become an essential component of the global food supply. China has the world's largest aquaculture industry in terms of production volume. However, the sustainable development of fish culture is hindered by several concerns, including germplasm degradation and disease outbreaks. The practice of genomic breeding, which relies heavily on genome information and genotypephenotype relationships, has significant potential for increasing the efficiency of aquaculture production. In 2014, the completion of the genome sequencing and annotation of the Chinese tongue sole signified the beginning of the fish genomics era in China. Since then, domestic researchers have made dramatic progress in functional genomic studies. To date, the genomes of more than 60 species of fish in China have been assembled and annotated. Based on these reference genomes, evolutionary, comparative, and functional genomic studies have revolutionized our understanding of a wide range of biologically and economically important traits of fishes, including growth and development, sex determination, disease resistance, metamorphosis, and pigmentation. Furthermore, genomic tools and breeding techniques such as SNP arrays, genomic selection, and genome editing have greatly accelerated genetic improvement through the incorporation of functional genomic information into breeding activities. This review aims to summarize the current status, advances, and perspectives of the genome resources, genomic study of important traits, and genomic breeding techniques of fish in China. The review will provide aquaculture researchers, fish breeders, and farmers with updated information concerning fish genomic research and breeding technology. The summary will help to promote the genetic improvement of production traits and thus will support the sustainable development of fish aquaculture.

A novel M2-like tumor associated macrophages-related gene signature for predicting the prognosis and immunotherapy efficacy in gastric cancer.

BACKGROUND: M2-like tumor-associated macrophages (M2-like TAMs) play key roles in tumor progression and the immune response. However, the clinical significance and prognostic value of M2-like TAMs-associated regulatory genes in gastric cancer (GC) have not been clarified. METHODS: Herein, we identified M2-like TAM-related genes by weighted gene coexpression network analysis of TCGA-STAD and GSE84437 cohort. Lasso-Cox regression analyses were then performed to screen for signature genes, and a novel signature was constructed to quantify the risk score for each patient. Tumor mutation burden (TMB), survival outcomes, immune cells, and immune function were analyzed in the risk groups to further reveal the immune status of GC patients. A gene-drug correlation analysis and sensitivity analysis of anticancer drugs were used to identify potential therapeutic agents. Finally, we verified the mRNA expression of signature genes in patient tissues by qRT-PCR, and analyzed the expression distribution of these genes by IHC. RESULTS: A 4-gene (SERPINE1, MATN3, CD36, and CNTN1) signature was developed and validated, and the risk score was shown to be an independent prognostic factor for GC patients. Further analyses revealed that GC patients in the high-risk group had a worse prognosis than those in the low-risk group, with significant differences in TMB, clinical features, enriched pathways, TIDE score, and tumor microenvironment features. Finally, we used qRT-PCR and IHC analysis to verify mRNA and protein level expression of signature genes. CONCLUSION: These findings highlight the importance of M2-like TAMs, provide a new perspective on individualized immunotherapy for GC patients.

Metabolic dysregulation-triggered neutrophil extracellular traps exacerbate acute liver failure.

Acute liver failure (ALF) is an acute liver disease with a high mortality rate in clinical practice, characterized histologically by extensive hepatocellular necrosis and massive neutrophil infiltration. However, the role of these abnormally infiltrating neutrophils during ALF development is unclear. Here, in an ALF mouse model, metabolites were identified that promote the formation of neutrophil extracellular traps (NETs) in the liver, subsequently influencing macrophage differentiation and disease progression. ALF occurs with abnormalities in hepatic and intestinal metabolites. Abnormal metabolites (LTD4 and glutathione) can directly, or indirectly via reactive oxygen species, promote NET formation of infiltrating neutrophils, which subsequently regulate macrophages in a pro-inflammatory M1-like state, inducing an amplification of the destructive effects of inflammation. Together, this study provides new insights into the role of NETs in the pathogenesis of ALF.

Food from Equids-Commercial Fermented Mare's Milk (Koumiss) Products: Protective Effects against Alcohol Intoxication.

Fermented mare's milk (koumiss), a traditional Central Asian dairy product derived from fermented mare's milk, is renowned for its unique sour taste and texture. It has long been consumed by nomadic tribes for its nutritional and medicinal benefits. This study aimed to comprehensively analyze the protective effects of koumiss against alcohol-induced harm across behavioral, hematological, gastrointestinal, hepatic, and reproductive dimensions using a mouse model. Optimal intoxicating doses of alcohol and koumiss doses were determined, and their effects were explored through sleep tests and blood indicator measurements. Pretreatment with koumiss delayed inebriation, accelerated sobering, and reduced mortality in mice, mitigating alcohol's impact on blood ethanol levels and various physiological parameters. Histopathological and molecular analyses further confirmed koumiss's protective role against alcohol-induced damage in the liver, stomach, small intestine, and reproductive system. Transcriptomic studies on reproductive damage indicated that koumiss exerts its benefits by influencing mitochondrial and ribosomal functions and also shows promise in mitigating alcohol's effects on the reproductive system. In summary, koumiss emerges as a potential natural agent for protection against alcohol-induced harm, opening avenues for future research in this field.

Rolling Bearing Fault Diagnosis Based on SABO-VMD and WMH-KNN.

To improve the performance of roller bearing fault diagnosis, this paper proposes an algorithm based on subtraction average-based optimizer (SABO), variational mode decomposition (VMD), and weighted Manhattan-K nearest neighbor (WMH-KNN). Initially, the SABO algorithm uses a composite objective function, including permutation entropy and mutual information entropy, to optimize the input parameters of VMD. Subsequently, the optimized VMD is used to decompose the signal to obtain the optimal decomposition characteristics and the corresponding intrinsic mode function (IMF). Finally, the weighted Manhattan function (WMH) is used to enhance the classification distance of the KNN algorithm, and WMH-KNN is used for fault diagnosis based on the optimized IMF features. The performance of the SABO-VMD and WMH-KNN models is verified through two experimental cases and compared with traditional methods. The results show that the accuracy of motor-bearing fault diagnosis is significantly improved, reaching 97.22% in Dataset 1, 98.33% in Dataset 2, and 99.2% in Dataset 3. Compared with traditional methods, the proposed method significantly reduces the false positive rate.

A comparison of the large-scale gene expression patterns in summer and fall migratory Pantala flavescens (Fabricius) in northern China.

Pantala flavescens (Fabricius) is the most well-known seasonal migratory insect. This research focused on the molecular response of P. flavescens migration in summer and fall. A total of 17,810 assembled unigenes were obtained and 624 differentially expressed genes (DEGs) were identified in summer migration compared to fall migration. A number of DEGs, including cpr49Ae, itm2b, chitinase, cpr11B, laccase2, nd5, vtg2 and so on, had previously been reported to be involved in cold- and high-temperature resistance. Functional enrichment analysis showed three pathways 'that antibacterial humoral response, response to bacterial, and lipid transporter activity' were significantly enriched in summer migration while that six pathways 'structural constituent of cuticle, chitin binding, mitochondrion, propanoate metabolism, citrate cycle, hypertrophic cardiomyopathy' were significantly enriched in fall migration. These results will provide a valuable baseline for further understanding of the molecular mechanisms of insect adaptation to different climate migrations.

Optimal approach to ultrasound-guided quadratus lumborum blocks for postoperative analgesia in elective caesarean section: protocol for systematic review and meta-analysis.

INTRODUCTION: Ultrasound-guided quadratus lumborum blocks are commonly used for postoperative analgesia during caesarean section. Ultrasound-guided quadratus lumborum blocks can be performed through four approaches, including lateral, posterior, anterior, and intramuscular quadratus lumborum blocks. This systematic review and meta-analysis aims to determine the optimal approach to ultrasound-guided quadratus lumborum blocks for postoperative analgesia in elective caesarean section. METHODS AND ANALYSIS: The PubMed, EMBASE, Cochrane Library and Web of Science databases will be systematically searched from their inception to 30 July 2024. Randomised controlled trials that compared the analgesic effects of different ultrasound-guided quadratus lumborum block approaches in elective caesarean section will be included. Only publications in English will be eligible for inclusion. The total postoperative analgesic consumption over 24 hours will be the primary outcome. The time to first analgesic request, postoperative pain scores at rest and during movement, and incidence of adverse effects will be secondary outcomes. RevMan V.5.4 will be used for the statistical analysis. Network meta-analysis will be used for indirect comparisons between different approaches across studies. The Grading of Recommendations Assessment, Development and Evaluation approach will be used to assess the quality of evidence for each outcome. ETHICS AND DISSEMINATION: Ethical approval was not required. The results of this study will be submitted to peer-reviewed journals. PROSPERO REGISTRATION NUMBER: CRD42024503694.

Identification and quantitative detection of illegal additives in wheat flour based on near-infrared spectroscopy combined with chemometrics.

As a common food raw material in daily life, the quality and safety of wheat flour are directly related to people's health. In this study, a model was developed for the rapid identification and detection of three illegal additives in flour, namely azodicarbonamide (ADA), talcum powder, and gypsum powder. This model utilized a combination of near-infrared spectroscopy with chemometric methods. A one-dimensional convolutional neural network was used to reduce data dimensionality, while a support vector machine was applied for non-linear classification to identify illegal additives in flour. The model achieved a calibration set F1 score of 99.38% and accuracy of 99.63%, with a validation set F1 score of 98.81% and accuracy of 98.89%. Two cascaded wavelength selection methods were introduced: The first method involved backward interval partial least squares (BiPLS) combined with an improved binary particle swarm optimization algorithm (IBPSO). The second method utilized the CARS-IBPSO algorithm, which integrated competitive adaptive reweighted sampling (CARS) with IBPSO. The two cascade wavelength selection methods were used to select feature wavelengths associated with additives and construct partial least squares quantitative detection models. The models constructed using CARS-IBPSO selected feature wavelengths for detecting ADA, talcum powder, and gypsum powder exhibited the highest overall performance. The model achieved validation set determination coefficients of 0.9786, 0.9102, and 0.9226, with corresponding to root mean square errors of 0.0024%, 1.3693%, and 1.6506% and residual predictive deviations of 6.8368, 3.5852, and 3.9253, respectively. Near-infrared spectroscopy in combination with convolutional neural network dimensionality reduction and support vector machine classification enabled rapid identification of various illegal additives. The combination of CARS-IBPSO feature wavelength selection and partial least squares regression models facilitated rapid quantitative detection of these additives. This study introduces a new approach for rapidly and accurately identifying and detecting illegal additives in flour.

Melatonin targets the paraventricular thalamus to promote non-rapid eye movement sleep in C3H/HeJ mice.

Melatonin (MLT) is an important circadian signal for sleep regulation, but the neural circuitries underlying the sleep-promoting effects of MLT are poorly understood. The paraventricular thalamus (PVT) is a critical thalamic area for wakefulness control and expresses MLT receptors, raising a possibility that PVT neurons may mediate the sleep-promoting effects of MLT. Here, we found that MLT receptors were densely expressed on PVT neurons and exhibited circadian-dependent variations in C3H/HeJ mice. Application of exogenous MLT decreased the excitability of PVT neurons, resulting in hyperpolarization of membrane potential and reduction of action potential firing. MLT also inhibited the spontaneous activity of PVT neurons at both population and single-neuron levels in freely behaving mice. Furthermore, pharmacological manipulations revealed that local infusion of exogeneous MLT into the PVT promoted non-rapid eye movement (NREM) sleep and increased NREM sleep duration, whereas MLT receptor antagonists decreased NREM sleep. Moreover, we found that selectively knocking down endogenous MLT receptors in the PVT decreased NREM sleep and correspondingly increased wakefulness, with particular changes shortly after the onset of the dark or light phase. Taken together, these results demonstrate that PVT is an important target of MLT for promoting NREM sleep.

Discovery of 2,4,6-trisubstituted pyrimidine derivatives as novel potent HIV-1 NNRTIs by exploiting the tolerant region II of the NNIBP.

The rapid emergence of drug resistance severely reduces the clinical response of human immunodeficiency virus-1 (HIV-1) to non-nucleoside reverse transcriptase inhibitors (NNRTIs). Herein, a series of 2,4,6-trisubstituted pyrimidine derivatives was designed and synthesized, with the aim to identify novel anti-HIV-1 agents with improved drug resistance profiles. The antiviral activity results demonstrated that all compounds showed excellent potency to wild-type (WT) HIV-1 strain (EC50 = 3.61-15.5 nM). Moreover, 13c was proved to be the most potent inhibitor against the whole tested viral panel, with EC50 ranging from 4.68 to 229 nM. In addition, 13c yielded moderate HIV-1 RT inhibition with IC50 value of 0.231 µM, which demonstrated it was a classical NNRTI. Molecular docking was further conducted to illustrate its binding mode with HIV-1 RT. These encouraging results indicated that 13c can be used as a lead compound for further study.

Inequities in medicaid home- and community-based services waiver enrollment among people with intellectual and/or developmental disabilities: A nationwide claims-based analysis.

BACKGROUND: States use Medicaid 1915(c) waiver programs to enable access to home- and community-based services for people with intellectual and/or developmental disabilities (I/DD). However, enrollment rates and potential inequities are not well documented, impeding efforts to improve care access and quality for waiver program enrollees, especially for racially minoritized beneficiaries experiencing compounded barriers to services and supports. OBJECTIVE: To characterize year-by-year 1915(c) waiver program enrollment among Medicaid-enrolled adults with I/DD from 2016 to 2019 and to analyze population-level inequities by type of I/DD and racial/ethnic group. METHODS: Our data source was 2016-2019 Medicaid Transformed Medicaid Statistical Information System Analytic Files Demographic and Eligibility files for beneficiaries with Down syndrome, autism, and intellectual disability. We used generalized estimating equation linear models to estimate the associations of type of I/DD and racial/ethnic group with the probability of 1915(c) waiver program enrollment and reported (1) unadjusted estimates and (2) estimates adjusted for demographics with state and year fixed effects. RESULTS: From 2016 to 2019, across all types of I/DD and racial/ethnic groups, unadjusted 1915(c) waiver program enrollment rates ranged from 40 to 60 % nationwide. We found modest growth in 1915(c) I/DD waiver program enrollment but persistent inequities over time. Compared to beneficiaries with intellectual disabilities, beneficiaries with autism were less likely to enroll while beneficiaries with Down syndrome were more likely. While some racial/ethnic groups had higher unadjusted mean enrollment, after adjustment, racially minoritized beneficiaries were 3.66-12.0 percentage points less likely to enroll compared to white non-Hispanic beneficiaries. CONCLUSIONS: Given extensive waiting lists for 1915(c) waiver programs, Medicaid programs should evaluate existing enrollment and authorization processes and consider alternative HCBS program authorities.

Using machine learning to classify the immunosuppressive activity of per- and polyfluoroalkyl substances.

Per- and polyfluoroalkyl substances (PFASs), one of the persistent organic pollutants, have immunosuppressive effects. The evaluation of this effect has been the focus of regulatory toxicology. In this investigation, 146 PFASs (immunosuppressive or nonimmunosuppressive) and corresponding concentration gradients were collected from literature, and their structures were characterized by using Dragon descriptors. Feature importance analysis and stepwise feature elimination are used for feature selection. Three machine learning (ML) methods, namely Random Forest (RF), Extreme Gradient Boosting Machine (XGB), and Categorical Boosting Machine (CB), were utilized for model development. The model interpretability was explored by feature importance analysis and correlation analysis. The findings indicated that the three models developed have exhibited excellent performance. Among them, the best-performing RF model has an average AUC score of 0.9720 for the testing set. The results of the feature importance analysis demonstrated that concentration, SpPosA_X, IVDE, R2s, and SIC2 were the crucial molecular features. Applicability domain analysis was also performed to determine reliable prediction boundaries for the model. In conclusion, this study is the first application of ML models to investigate the immunosuppressive activity of PFASs. The variables used in the models can help understand the mechanism of the immunosuppressive activity of PFASs, allow researchers to more effectively assess the immunosuppressive potential of a large number of PFASs, and thus better guide environmental and health risk assessment efforts.

The impact of homocysteine on patients with diabetic nephropathy: a mendelian randomization study.

BACKGROUND/AIMS: Homocysteine (Hcy) has been associated with an increased risk of diabetic nephropathy (DN) in patients, but there is still controversy. This study aims to investigate the causal relationship between plasma Hcy and DN. METHODS: A Mendelian randomization (MR) study using data from 2 samples was employed to infer causal relationships. The aggregated genetic data associated with Hcy was derived from the largest genome-wide association study (GWAS) to date, involving 44,147 individuals of European ancestry.Data on SNP-diabetic nephropathy, creatinine, and urea nitrogen were obtained from the IEU GWAS database. The analysis method employed a fixed-effect or random-effect inverse variance-weighted approach to estimate effects.Additional analysis methods were used to assess stability and sensitivity. The potential for pleiotropy was evaluated using the MR-Egger intercept test. RESULTS: Using 12 SNPs as instrumental variables, two-sample MR analysis revealed no evidence of a causal relationship between genetically predicted plasma Hcy levels and diabetic nephropathy, as well as creatinine and blood urea nitrogen levels. This finding is consistent with the results obtained from other testing methods. CONCLUSIONS: Two-sample Mendelian Randomization analysis found no evidence of a causal relationship between plasma homocysteine levels and diabetic nephropathy, creatinine, or urea.

Development of a Novel CD8+ T Cell-Associated Signature for Prognostic Assessment in Hepatocellular Carcinoma.

OBJECTIVE: The aim of this study was to analyze the clinical significance and prognostic value of CD8+ T cell-related regulatory genes in hepatocellular carcinoma (HCC). METHODS: This was a retrospective study. We combined TCGA-LIHC and single-cell RNA sequencing data for Lasso-Cox regression analysis to screen for CD8+ T cell-associated genes to construct a novel signature. The expression of the signature genes was detected at cellular and tissue levels using qRT-PCR, immunohistochemistry, and tissue microarrays. The CIBERSORT algorithm was then used to assess the immune microenvironmental differences between the different risk groups and a drug sensitivity analysis was performed to screen for potential HCC therapeutic agents. RESULTS: An 8-gene CD8 + T cell-associated signature (FABP5, GZMH, ANXA2, KLRB1, CD7, IL7R, BATF, and RGS2) was constructed. Survival analysis showed that high-risk patients had a poorer prognosis in all cohorts. Tumor immune microenvironment analysis revealed 22 immune cell types that differed significantly between patients in different risk groups, with patients in the low-risk group having an immune system that was more active in terms of immune function. Patients in the high-risk group were more prone to immune escape and had a poorer response to immunotherapy, and AZD7762 was screened as the most sensitive drug in the high-risk group. Finally, preliminary experiments have shown that BATF has a promoting effect on the proliferation, migration and invasion of HuH-7 cells. CONCLUSIONS: The CD8+ T-cell-associated signature is expected to be a tool for optimizing individual patient decision-making and monitoring protocols, and to provide new ideas for treatment and prognostic assessment of HCC.

Unveiling the Factors Influencing Different Nucleation Pathways and Liquid-Liquid Phase Separation.

Exploring nucleation pathways has been a research hot spot in the fields of crystal engineering. In this work, vanillin as a model compound was utilized to explore the factors influencing different nucleation pathways with or without liquid-liquid phase separation (LLPS). A thermodynamic phase diagram of vanillin in the mixed solvent system of water and acetone from 10 to 55 °C was determined. It was found that the occurrence of LLPS might be related to different nucleation pathways. Under the guidance of a thermodynamic phase diagram, Raman spectroscopy and molecular simulation were applied to investigate the influencing factors of different nucleation paths. It was found that the degree of solvation is a key factor determining the nucleation path, and strong solvation could lead to LLPS. Additionally, the molecular self-assembly evolution during the crystallization process was further investigated by using small-angle X-ray scattering (SAXS) and dynamic light scattering (DLS). The findings indicate that larger clusters with a diffuse transition layer may lead to LLPS during the nucleation process.