CD8 + T-cell marker genes reveal different immune subtypes of oral lichen planus by integrating single-cell RNA-seq and bulk RNA-sequencing.

BACKGROUND: Oral lichen planus (OLP) is a local autoimmune disease induced by T-cell dysfunction that frequently affects middle-aged or elderly people, with a higher prevalence in women. CD8 + T cells, also known as killer T cells, play an important role in the progression and persistence of OLP. In order to identify different OLP subtypes associated with CD8 + T cell pathogenesis, consensus clustering was used. METHODS: In this study, we preprocessed and downscaled the OLP single-cell dataset GSE211630 cohort downloaded from Gene Expression Omnibus (GEO) to finally obtain the marker genes of CD8 + T cells. Based on the expression of marker genes, we classified OLP patients into CMGs subtypes using unsupervised clustering analysis. The gene expression profiles were analyzed by WGCNA using the "WGCNA" R package based on the clinical disease traits and typing results, and 108 CD8 + T-cell related OLP pathogenicity-related genes were obtained from the intersection. Patients were once again classified into gene subtypes based on intersection gene expression using unsupervised clustering analysis. RESULTS: After obtaining the intersecting genes of CD8 + T cells related to pathogenesis, OLP patients can be precisely classified into two different subtypes based on unsupervised clustering analysis, and subtype B has better immune infiltration results, providing clinicians with a reference for personalized treatment. CONCLUSIONS: Classification of OLP into different subtypes improve our current understanding of the underlying pathogenesis of OLP and provides new insights for future studies.

Comparative evaluation of Sensititre YeastOne and VITEK 2 against the Clinical and Laboratory Standards Institute M27-E4 reference broth microdilution method for the antifungal susceptibility testing of Cryptococcus neoformans and Cryptococcus gattii.

The present study collected 280 isolates of Cryptococcus neoformans and 22 isolates of Cryptococcus gattii and evaluated the consistencies between Sensititre YeastOne (SYO), VITEK 2, and the reference broth microdilution (BMD) method for the antifungal susceptibility testing of fluconazole, voriconazole, and flucytosine. For amphotericin B, SYO was replaced with the BIO KONT amphotericin B microbroth dilution kit. The essential agreements (EAs) by SYO and VITEK 2 for C. neoformans var. grubii and C. neoformans var. neoformans were 98.15-99.63% and 88.89-100%, respectively, with fluconazole, voriconazole, and flucytosine. The EA for C. gattii VG â…  against fluconazole was 29.41% by VITEK 2, while the other EAs for C. gattii strains were 100% by SYO and VITEK 2. The categorical agreements (CAs) by SYO and VITEK 2 for C. neoformans and C. gattii were 94.12-100%, while VITEK 2 failed to distinguish 5/6 fluconazole-resistant non-wild-type C. neoformans var. grubii isolates; this finding confirmed the limitation of testing fluconazole against C. neoformans as documented in the manufacturer's package insert. The EAs for amphotericin B were 97.42-100% for C. neoformans and C. gattii, but the CAs were 17.65-60% by BIO KONT and VITEK 2. Thus, SYO can be used for susceptibility testing of C. neoformans and C. gattii against fluconazole, voriconazole, and flucytosine, and VITEK 2 can be used for susceptibility testing of C. neoformans against voriconazole and flucytosine. Further studies using amphotericin B-resistant isolates are required to assess the agreement between VITEK 2, BIO KONT, and BMD. LAY SUMMARY: Sensititre YeastOne showed a good agreement with the CLSI broth microdilution method for C. neoformans and C. gattii against voriconazole and flucytosine. The limitation regarding fluconazole testing against C. neoformans documented in VITEK 2 manufacturer's package insert was confirmed.

Efficient degradation of organic pollutants using peroxydisulfate activated by magnetic carbon nanotube.

The magnetic composite of Fe3O4 and carbon nanotube (MCNT) was fabricated in a facile one-pot solvothermal method and employed to activate peroxydisulfate (PDS) for degradation of Rhodamine B (RhB) and other pollutants. The effects of operational factors including MCNT dosage and PDS dosage were studied, and high removal efficiencies of 84.2-99.5% were achieved for these pollutants with 0.3 g/L MCNT and 4 mM PDS. The effects of environmental factors including initial pH, inorganic cations, inorganic anions, humic acid and water matrix were also studied. Reusability test showed that the removal efficiency declined in four consecutive runs, which was attributed to the adsorbed oxidation products on the catalyst surface. Based on quenching experiments, solvent exchange (H2O to D2O), inductively coupled plasma and open circuit potential tests, it was concluded that radicals of ·OH/SO4·- and the non-radical electron-transfer pathway were involved in the MCNT/PDS system, and the contributions of O2·-, 1O2, high-valent iron-oxo species and homogenous activation were insignificant. Moreover, the orbital-weighted Fukui functions of RhB were calculated by density functional theory, and its plausible degradation pathway was proposed based on the calculation results. Finally, toxicity evaluation of the degradation products was performed in the quantitative structure-activity relationship approach.

Single-Molecule Force Spectroscopy Reveals that the Fe-N Bond Enables Multiple Rupture Pathways of the 2Fe2S Cluster in a MitoNEET Monomer.

The mitochondrial outer membrane protein, mitoNEET (mNT), is an iron-sulfur protein containing an Fe2S2(His)1(Cys)3 cluster with a unique single Fe-N bond. Previous studies have shown that this Fe(III)-N(His) bond is essential for metal cluster transfer and protein function. To further understand the effect of this unique Fe-N bond on the metal cluster and protein, we used atomic force microscopy-based single-molecule force spectroscopy (AFM-SMFS) to investigate the mechanical unfolding mechanism of an mNT monomer, focusing on the rupture pathway and kinetic stability of the cluster. We found that the Fe-N bond was the weakest point of the cluster, the rupture of which occurred first, and could be independent of the cluster break. Moreover, this Fe-N bond enabled a dynamic and labile iron-sulfur cluster, as multiple unfolding pathways of mNT with a unique Fe2S2(Cys)3 intermediate were observed accordingly.

Aggregation behavior of aqu/nC60 produced via extended mixing: Influence of sunlight and agitation intensity.

Aggregation of C60, as an important process governing its mobility and toxicity, has been quantitatively investigated. However, effects of sunlight and agitation intensity on the aggregation behavior of aqu/nC60 produced via extended mixing, have not been clarified. Therefore, in the present study, the aggregation behavior of aqu/nC60 produced at 500 and 800 rpm in the absence and presence of sunlight was investigated. Aggregation with increasing concentrations could be accelerated, while changes of Zave and zeta potential were not obvious. Critical coagulation concentrations (CCCs) of aqu/nC60 obtained at 800 rpm in the absence/presence of sunlight and that at 500 rpm under sunlight were 330, 205 and 170 mM NaCl, and 10.0, 2.6 and 3.1 mM CaCl2, respectively. These CCCs indicated that the aqu/nC60 prepared by the extended mixing were more stable than those produced by other methods. Salt-induced aggregation occurred more easily for aqu/nC60 formed under sunlight than that formed in the dark. Extra surface oxidation induced by high agitation intensity remarkably increased the stability of aqu/nC60 in NaCl solutions. In contrast, in CaCl2 solutions, aqu/nC60 formed at high agitation intensity had similar stability or even inadequate stability to that obtained at low agitation intensity due to the charge neutralization and cross-link bridging.

Mdivi-1, a mitochondrial fission inhibitor, modulates T helper cells and suppresses the development of experimental autoimmune encephalomyelitis.

BACKGROUND: Unrestrained activation of Th1 and Th17 cells is associated with the pathogenesis of multiple sclerosis and its animal model, experimental autoimmune encephalomyelitis (EAE). While inactivation of dynamin-related protein 1 (Drp1), a GTPase that regulates mitochondrial fission, can reduce EAE severity by protecting myelin from demyelination, its effect on immune responses in EAE has not yet been studied. METHODS: We investigated the effect of Mdivi-1, a small molecule inhibitor of Drp1, on EAE. Clinical scores, inflammation, demyelination and Drp1 activation in the central nervous system (CNS), and T cell responses in both CNS and periphery were determined. RESULTS: Mdivi-1 effectively suppressed EAE severity by reducing demyelination and cellular infiltration in the CNS. Mdivi-1 treatment decreased the phosphorylation of Drp1 (ser616) on CD4+ T cells, reduced the numbers of Th1 and Th17 cells, and increased Foxp3+ regulatory T cells in the CNS. Moreover, Mdivi-1 treatment effectively inhibited IFN-γ+, IL-17+, and GM-CSF+ CD4+ T cells, while it induced CD4+ Foxp3+ regulatory T cells in splenocytes by flow cytometry. CONCLUSIONS: Together, our results demonstrate that Mdivi-1 has therapeutic potential in EAE by modulating the balance between Th1/Th17 and regulatory T cells.

A DNA-Azobenzene Nanopump Fueled by Upconversion Luminescence for Controllable Intracellular Drug Release.

Stimulus-responsive drug release possesses considerable significance in cancer therapy. This work reports an upconversion-luminescence-fueled DNA-azobenzene nanopump for rapid and efficient drug release. The nanopump is constructed by assembling the azobenzene-functionalized DNA strands on upconversion nanoparticles (UCNPs). Doxorubicin (DOX) is loaded in the nanopump by intercalation in the DNA helix. Under NIR light, the UCNPs emit both UV and visible photons to fuel the continuous photoisomerization of azo, which acts as an impeller pump to trigger cyclic DNA hybridization and dehybridization for controllable DOX release. In a relatively short period, this system demonstrates 86.7 % DOX release. By assembling HIV-1 TAT peptide and hyaluronic acid on the system, targeting of the cancer-cell nucleus is achieved for perinuclear aggregation of DOX and enhanced anticancer therapy. This highly effective drug delivery nanopump could contribute to chemotherapy development.

Gemcitabine and Taxane Adjuvant Therapy with Chemoradiation in Resected Pancreatic Cancer: A Novel Strategy for Improved Survival?

BACKGROUND: Gemcitabine-taxane combination chemotherapy has demonstrated a survival benefit clinically in metastatic pancreatic cancer (PC). The authors present their experience with gemcitabine and docetaxel (gem/tax)-based adjuvant treatment (Rx) after surgery with curative intent. METHODS: Patients with de novo resectable PC from January 2010 to December 2015 were identified from the authors' institutional database and registry. The study included only patients who received gem/tax as their initial Rx administered exclusively at the authors' institution with or without chemoradiation (CRTx). Survival analysis was performed using Kaplan-Meier methods, and prognostic factors were investigated by Cox proportional hazard modeling. RESULTS: Of 102 patients identified, 58 met the study criteria. The median age at diagnosis was 65 years, with 55% of the patients undergoing an R1 resection (margin ≤ 1 mm). Tumor characteristics included a median tumor size of 28 mm, a poor differentiation rate of 54%, and a lymph node positivity of 67%. Most of the patients (90%, 52/58) completed 80% or more of the 24 week Rx. Of these patients, 71% received post-gem/tax CRTx Rx. Grade 3 or 4 toxicity was observed in 52% of the patients. The median follow-up period was 51.2 months, and the observed median overall survival (OS) was 52 months [95% confidence interval (CI) 27.4-not reached]. The actuarial 5-year OS was 49% (95% CI 33.7-63.4%). In the multivariate analysis, an R1 resection and American Joint Committee on Cancer (AJCC) stage 2 versus stage 1 disease were negatively associated with OS, whereas administration of CRTx was positively associated with OS. CONCLUSIONS: Adjuvant gem/tax with or without CRTx is feasible, with a favorable OS. Future prospective studies of gem/taxane-based adjuvant Rx for PC are warranted.

Efficient removal of organic pollutants by activation of peroxydisulfate with the magnetic CoFe2O4/carbon nanotube composite.

A magnetic composite of CoFe2O4 and carbon nanotube (CNT) was prepared using the solvothermal approach and then employed for the activation of peroxydisulfate (PDS) to degrade reactive black 5 (RB5) and other organic pollutants. Characterization results of the composite catalyst revealed the successful loading of spherical CoFe2O4 particles on CNTs, possessing abundant porosity as well as magnetic separation capability. Under the degradation conditions of 0.2 g/L CoFe2O4-CNT dosage and 4 mM PDS dosage, the removal efficiencies of 10 mg/L RB5 and other pollutants were in the range of 94.5 to ~ 100%. The effects of pH, co-existing ions/humic acid, and water matrices as well as the reusability of the catalyst were also investigated in detail. Furthermore, the degradation mechanism and pathway were proposed based on quenching experiments, LC-MS analysis, and density functional theory (DFT) calculations, and the toxicity of the degradation products was evaluated in the quantitative structure-activity relationship approach.

hdWGCNA and Cellular Communication Identify Active NK Cell Subtypes in Alzheimer's Disease and Screen for Diagnostic Markers through Machine Learning.

BACKGROUND: Alzheimer's disease (AD) is a recognized complex and severe neurodegenerative disorder, presenting a significant challenge to global health. Its hallmark pathological features include the deposition of ß-amyloid plaques and the formation of neurofibrillary tangles. Given this context, it becomes imperative to develop an early and accurate biomarker model for AD diagnosis, employing machine learning and bioinformatics analysis. METHODS: In this study, single-cell data analysis was employed to identify cellular subtypes that exhibited significant differences between the diseased and control groups. Following the identification of NK cells, hdWGCNA analysis and cellular communication analysis were conducted to pinpoint NK cell subset with the most robust communication effects. Subsequently, three machine learning algorithms-LASSO, Random Forest, and SVM-RFE-were employed to jointly screen for NK cell subset modular genes highly associated with AD. A logistic regression diagnostic model was then designed based on these characterized genes. Additionally, a protein-protein interaction (PPI) networks of model genes was established. Furthermore, unsupervised cluster analysis was conducted to classify AD subtypes based on the model genes, followed by the analysis of immune infiltration in the different subtypes. Finally, Spearman correlation coefficient analysis was utilized to explore the correlation between model genes and immune cells, as well as inflammatory factors. RESULTS: We have successfully identified three genes (RPLP2, RPSA, and RPL18A) that exhibit a high association with AD. The nomogram based on these genes provides practical assistance in diagnosing and predicting patients' outcomes. The interconnected genes screened through PPI are intricately linked to ribosome metabolism and the COVID-19 pathway. Utilizing the expression of modular genes, unsupervised cluster analysis unveiled three distinct AD subtypes. Particularly noteworthy is subtype C3, characterized by high expression, which correlates with immune cell infiltration and elevated levels of inflammatory factors. Hence, it can be inferred that the establishment of an immune environment in AD patients is closely intertwined with the heightened expression of model genes. CONCLUSION: This study has not only established a valuable diagnostic model for AD patients but has also delved deeply into the pivotal role of model genes in shaping the immune environment of individuals with AD. These findings offer crucial insights into early AD diagnosis and patient management strategies.

Deciphering a Prognostic Signature Based on Soluble Mediators Defines the Immune Landscape and Predicts Prognosis in HNSCC.

BACKGROUND: The study on Head and Neck Squamous Cell Carcinoma (HNSCC), a prevalent and aggressive form of head and neck cancer, focuses on the often-overlooked role of soluble mediators. The objective is to leverage a transcriptome-based risk analysis utilizing soluble mediator-related genes (SMRGs) to provide novel insights into prognosis and immunotherapy efficacy in HNSCC patients. METHODS: We analyzed the expression and prognostic significance of 10,859 SMRGs using 502 HNSCC and 44 normal samples from the TCGA-HNSC cohort in The Cancer Genome Atlas (TCGA). The samples were divided into training and test sets in a 7:3 ratio, with an additional external validation using 40 tumor samples from the International Cancer Genome Consortium (ICGC). Key differentially expressed genes (DEGs) with prognostic significance were identified through univariate and Lasso-Cox regression analyses. A prognostic model based on 20 SMRGs was developed using Lasso and multivariate Cox regression. We assessed the clinical outcomes and immune status in high-risk (HR) and low-risk (LR) HNSCC patients utilizing the BEST databases and single-sample Gene Set Enrichment Analysis (ssGSEA). RESULTS: The 20 SMRGs were crucial in predicting the prognosis of HNSCC, with the SMRG signature emerging as an independent prognostic indicator. Patients classified in the HR group exhibited poorer outcomes compared to those in the LR group. A nomogram, integrating clinical characteristics and risk scores, demonstrated substantial prognostic value. Immunotherapy appeared to be more effective in the LR group, possibly attributed to enhanced immune infiltration and expression of immune checkpoints. CONCLUSIONS: The model based on soluble mediator-associated genes offers a fresh perspective for assessing the pre-immune efficacy and showcases robust predictive capabilities. This innovative approach holds significant promise in advancing the field of precision immuno-oncology research, providing valuable insights for personalized treatment strategies in HNSCC.

Emergence and clonal expansion of Aeromonas hydrophila ST1172 that simultaneously produces MOX-13 and OXA-724.

BACKGROUND: Aeromonas hydrophila infections can cause gastrointestinal symptoms such as diarrhea; however, deep infections are rarely reported. Outbreaks of A. hydrophila are reported more frequently in fish, poultry, and snakes than in humans. This study aimed to track clonal relatedness of deep infections caused by A. hydrophila using whole genome sequencing (WGS). METHODS: We collected three isolates of A. hydrophila in July 19 to August 29, 2019, from patients that underwent spine surgery. Accurate species identification was performed using whole-genome average nucleotide identity (ANI). Antimicrobial susceptibility testing was performed using a VITEK 2 automated AST-N334 Gram-negative susceptibility card system. Antimicrobial resistance and virulence genes were identified using the Comprehensive Antibiotic Resistance Database and Virulence Factor Database VFanalyzer. RESULTS: All three isolates were identified as A. hydrophila based on ANI and multilocus sequence typing analysis revealed that A. hydrophila belonged to a novel sequence type (ST1172). All three isolates were susceptible to amikacin and levofloxacin; however, they were resistant to piperacillin/tazobactam, ceftriaxone, cefuroxime, cefoxitin, and imipenem. Isolate 19W05620 (patient 3) showed increased ceftazidime resistance (minimum inhibitory concentration ≥ 64 µg/mL). All three isolates possessed the same chromosomally encoded ß-lactamases, including blaOXA-724 (ß-lactamase), imiH (metallo-ß-lactamase), and blaMOX-13 (AmpC) in plasmids. CONCLUSIONS: Our study validated the transmission of a novel carbapenem-resistant A. hydrophila sequence type (ST1172) in patients that underwent spine surgery. Control measures should be developed to prevent dissemination of A. hydrophila in the hospital setting.

Corrigendum: Machine learning to construct sphingolipid metabolism genes signature to characterize the immune landscape and prognosis of patients with uveal melanoma.

[This corrects the article DOI: 10.3389/fendo.2022.1056310.].

The impact of neoadjuvant chemoradiotherapy on perioperative outcomes, tumor pathology, and survival in clinical stage II and III esophageal cancer.

BACKGROUND: The purpose of this study was to evaluate the impact of neoadjuvant chemoradiotherapy (NCR) on perioperative outcomes, tumor pathology, and survival following surgical resection of clinical stage II and III esophageal cancer. METHODS: Patients undergoing esophagectomy for clinical stage II and III cancer were divided into two groups: those who received NCR and those who underwent primary surgery (1991-2011). RESULTS: A total of 173 (50.9%) of 340 stage II/III patients received NCR, 108 (31.8%) patients underwent primary surgery, and 59 (17.4%) underwent neoadjuvant chemotherapy followed by surgery. Patients who received NCR were younger but had a similar Charlson comorbidity index and incidence of adenocarcinoma. There were no differences between groups in the incidence of complications, in-hospital mortality, and ICU stay, but patients who received NCR demonstrated a reduced length of hospital stay. NCR was associated with a reduced the incidence of positive pathological lymph node status and positive resection margin (3.1 vs. 21.1%) in stage III esophageal cancer. No overall survival benefit was seen with use of NCR, although a nonsignificant improvement in survival of 22 months (p = 0.06) was noted in patients with adenocarcinoma. Negative resection margin was associated with an improved survival in both stage II and III patients. CONCLUSIONS: This study highlights the importance of planning operations to optimize the opportunity to provide negative surgical resection margins and to identify patients not responding to NCR to allow them to proceed directly to surgery. Additional assessment of the effect of NCR on patients with adenocarcinoma is warranted.

Uncovering the potential role of oxidative stress in the development of periodontitis and establishing a stable diagnostic model via combining single-cell and machine learning analysis.

Background: The primary pathogenic cause of tooth loss in adults is periodontitis, although few reliable diagnostic methods are available in the early stages. One pathological factor that defines periodontitis pathology has previously been believed to be the equilibrium between inflammatory defense mechanisms and oxidative stress. Therefore, it is necessary to construct a model of oxidative stress-related periodontitis diagnostic markers through machine learning and bioinformatic analysis. Methods: We used LASSO, SVM-RFE, and Random Forest techniques to screen for periodontitis-related oxidative stress variables and construct a diagnostic model by logistic regression, followed by a biological approach to build a Protein-Protein interaction network (PPI) based on modelled genes while using modelled genes. Unsupervised clustering analysis was performed to screen for oxidative stress subtypes of periodontitis. we used WGCNA to explore the pathways correlated with oxidative stress in periodontitis patients. Networks. Finally, we used single-cell data to screen the cellular subpopulations with the highest correlation by scoring oxidative stress genes and performed a proposed temporal analysis of the subpopulations. Results: We discovered 3 periodontitis-associated genes (CASP3, IL-1ß, and TXN). A characteristic line graph based on these genes can be helpful for patients. The primary hub gene screened by the PPI was constructed, where immune-related and cellular metabolism-related pathways were significantly enriched. Consistent clustering analysis found two oxidative stress categories, with the C2 subtype showing higher immune cell infiltration and immune function ratings. Therefore, we hypothesized that the high expression of oxidative stress genes was correlated with the formation of the immune environment in patients with periodontitis. Using the WGCNA approach, we examined the co-expressed gene modules related to the various subtypes of oxidative stress. Finally, we selected monocytes for mimetic time series analysis and analyzed the expression changes of oxidative stress genes with the mimetic time series axis, in which the expression of JUN, TXN, and IL-1ß differed with the change of cell status. Conclusion: This study identifies a diagnostic model of 3-OSRGs from which patients can benefit and explores the importance of oxidative stress genes in building an immune environment in patients with periodontitis.

Circadian rhythm-related genes index: A predictor for HNSCC prognosis, immunotherapy efficacy, and chemosensitivity.

Background: Head and neck squamous cell carcinoma (HNSCC) is the most common head and neck cancer and is highly aggressive and heterogeneous, leading to variable prognosis and immunotherapy outcomes. Circadian rhythm alterations in tumourigenesis are of equal importance to genetic factors and several biologic clock genes are considered to be prognostic biomarkers for various cancers. The aim of this study was to establish reliable markers based on biologic clock genes, thus providing a new perspective for assessing immunotherapy response and prognosis in patients with HNSCC. Methods: We used 502 HNSCC samples and 44 normal samples from the TCGA-HNSCC dataset as the training set. 97 samples from GSE41613 were used as an external validation set. Prognostic characteristics of circadian rhythm-related genes (CRRGs) were established by Lasso, random forest and stepwise multifactorial Cox. Multivariate analysis revealed that CRRGs characteristics were independent predictors of HNSCC, with patients in the high-risk group having a worse prognosis than those in the low-risk group. The relevance of CRRGs to the immune microenvironment and immunotherapy was assessed by an integrated algorithm. Results: 6-CRRGs were considered to be strongly associated with HNSCC prognosis and a good predictor of HNSCC. The riskscore established by the 6-CRRG was found to be an independent prognostic factor for HNSCC in multifactorial analysis, with patients in the low-risk group having a higher overall survival (OS) than the high-risk group. Nomogram prediction maps constructed from clinical characteristics and riskscore had good prognostic power. Patients in the low-risk group had higher levels of immune infiltration and immune checkpoint expression and were more likely to benefit from immunotherapy. Conclusion: 6-CRRGs play a key predictive role for the prognosis of HNSCC patients and can guide physicians in selecting potential responders to prioritise immunotherapy, which could facilitate further research in precision immuno-oncology.

T-cell exhaustion signatures characterize the immune landscape and predict HCC prognosis via integrating single-cell RNA-seq and bulk RNA-sequencing.

Background: Hepatocellular carcinoma (HCC), the third most prevalent cause of cancer-related death, is a frequent primary liver cancer with a high rate of morbidity and mortality. T-cell depletion (TEX) is a progressive decline in T-cell function due to continuous stimulation of the TCR in the presence of sustained antigen exposure. Numerous studies have shown that TEX plays an essential role in the antitumor immune process and is significantly associated with patient prognosis. Hence, it is important to gain insight into the potential role of T cell depletion in the tumor microenvironment. The purpose of this study was to develop a trustworthy TEX-based signature using single-cell RNA-seq (scRNA-seq) and high-throughput RNA sequencing, opening up new avenues for evaluating the prognosis and immunotherapeutic response of HCC patients. Methods: The International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) databases were used to download RNA-seq information for HCC patients. The 10x scRNA-seq. data of HCC were downloaded from GSE166635, and UMAP was used for clustering descending, and subgroup identification. TEX-related genes were identified by gene set variance analysis (GSVA) and weighted gene correlation network analysis (WGCNA). Afterward, we established a prognostic TEX signature using LASSO-Cox analysis. External validation was performed in the ICGC cohort. Immunotherapy response was assessed by the IMvigor210, GSE78220, GSE79671, and GSE91061cohorts. In addition, differences in mutational landscape and chemotherapy sensitivity between different risk groups were investigated. Finally, the differential expression of TEX genes was verified by qRT-PCR. Result: 11 TEX genes were thought to be highly predictive of the prognosis of HCC and substantially related to HCC prognosis. Patients in the low-risk group had a greater overall survival rate than those in the high-risk group, according to multivariate analysis, which also revealed that the model was an independent predictor of HCC. The predictive efficacy of columnar maps created from clinical features and risk scores was strong. Conclusion: TEX signature and column line plots showed good predictive performance, providing a new perspective for assessing pre-immune efficacy, which will be useful for future precision immuno-oncology studies.

Decoding tumor heterogeneity in uveal melanoma: basement membrane genes as novel biomarkers and therapeutic targets revealed by multi-omics approaches for cancer immunotherapy.

Background: Uveal melanoma (UVM) is a primary intraocular malignancy that poses a significant threat to patients' visual function and life. The basement membrane (BM) is critical for establishing and maintaining cell polarity, adult function, embryonic and organ morphogenesis, and many other biological processes. Some basement membrane protein genes have been proven to be prognostic biomarkers for various cancers. This research aimed to develop a novel risk assessment system based on BMRGs that would serve as a theoretical foundation for tailored and accurate treatment. Methods: We used gene expression profiles and clinical data from the TCGA-UVM cohort of 80 UVM patients as a training set. 56 UVM patients from the combined cohort of GSE84976 and GSE22138 were employed as an external validation dataset. Prognostic characteristics of basement membrane protein-related genes (BMRGs) were characterized by Lasso, stepwise multifactorial Cox. Multivariate analysis revealed BMRGs to be independent predictors of UVM. The TISCH database probes the crosstalk of BMEGs in the tumor microenvironment at the single-cell level. Finally, we investigated the function of ITGA5 in UVM using multiple experimental techniques, including CCK8, transwell, wound healing assay, and colony formation assay. Results: There are three genes in the prognostic risk model (ADAMTS10, ADAMTS14, and ITGA5). After validation, we determined that the model is quite reliable and accurately forecasts the prognosis of UVM patients. Immunotherapy is more likely to be beneficial for UVM patients in the high-risk group, whereas the survival advantage may be greater for UVM patients in the low-risk group. Knockdown of ITGA5 expression was shown to inhibit the proliferation, migration, and invasive ability of UVM cells in vitro experiments. Conclusion: The 3-BMRGs feature model we constructed has excellent predictive performance which plays a key role in the prognosis, informing the individualized treatment of UVM patients. It also provides a new perspective for assessing pre-immune efficacy.

Metabolic orchestration of cell death by AMPK-mediated phosphorylation of RIPK1.

Adenosine monophosphate-activated protein kinase (AMPK) activity is stimulated to promote metabolic adaptation upon energy stress. However, sustained metabolic stress may cause cell death. The mechanisms by which AMPK dictates cell death are not fully understood. We report that metabolic stress promoted receptor-interacting protein kinase 1 (RIPK1) activation mediated by TRAIL receptors, whereas AMPK inhibited RIPK1 by phosphorylation at Ser415 to suppress energy stress-induced cell death. Inhibiting pS415-RIPK1 by Ampk deficiency or RIPK1 S415A mutation promoted RIPK1 activation. Furthermore, genetic inactivation of RIPK1 protected against ischemic injury in myeloid Ampkα1-deficient mice. Our studies reveal that AMPK phosphorylation of RIPK1 represents a crucial metabolic checkpoint, which dictates cell fate response to metabolic stress, and highlight a previously unappreciated role for the AMPK-RIPK1 axis in integrating metabolism, cell death, and inflammation.

Single-Molecule Force Spectroscopy Reveals Stability of mitoNEET and its [2Fe2Se] Cluster in Weakly Acidic and Basic Solutions.

The outer mitochondrial membrane protein mitoNEET (mNT) is a recently identified iron-sulfur protein containing a unique Fe2 S2 (His)1 (Cys)3 metal cluster with a single Fe-N(His87) coordinating bond. This labile Fe-N bond led to multiple unfolding/rupture pathways of mNT and its cluster by atomic force microscopy-based single-molecule force spectroscopy (AFM-SMFS), one of most common tools for characterizing the molecular mechanics. Although previous ensemble studies showed that this labile Fe-N(His) bond is essential for protein function, they also indicated that the protein and its [2Fe2S] cluster are stable under acidic conditions. Thus, we applied AFM-SMFS to measure the stability of mNT and its cluster at pH values of 6, 7, and 8. Indeed, all previous multiple unfolding pathways of mNT were still observed. Moreover, single-molecule measurements revealed that the stabilities of the protein and the [2Fe2S] cluster are consistent at these pH values with only ≈20 pN force differences. Thus, we found that the behavior of the protein is consistent in both weakly acidic and basic solutions despite a labile Fe-N bond.