Circulating miRNAs are acclaimed biomarkers to predict the occurrence and progression of type 2 diabetes mellitus (T2DM). This study is aimed at analyzing the correlation of circulating miR-210 level and obesity-associated T2DM and then investigating the underlying mechanism of circulating miR-210 in T2DM. α (HIF-1α) was measured by western blotting.  Totally, 137 serum samples from patients with T2DM were collected; meanwhile, the demographic, general, and clinical hematological characteristics, disease history, and dietary patterns were recorded. The miR-210 level in exosomes from serum was detected by qRT-PCR. Then, the correlations of BMI or miR-210 level with patients' clinical characteristics were analyzed. Furthermore, the miR-210 level was detected in T2DM related various cells under high glucose condition. Meanwhile, the expression of carbohydrate responsive element binding protein (ChREBP) and hypoxia-inducible factor 1α.  The miR-210 level in exosomes from serum was obviously elevated in the BMI > 24 group compared with the BMI ≤ 24 group. Higher BMI was correlated with abnormal lipid metabolism and impaired liver function as well as higher miR-210 level. Notably, higher miR-210 level was also correlated with abnormal lipid metabolism, disease history, and dietary patterns. In addition, compared with normal cells, high glucose increased the miR-210 level in exosomes from cell culture supernatants as well as cells in HUVEC, VSMC, RAW 264.7, 3 T3-L1, SMC, and Beta-TC-6 cells, while it reduced the expression of ChREBP and HIF-1 Circulating miR-210 level was closely correlated with obesity-associated T2DM. Furthermore, higher miR-210 level might be implicated in the occurrence and development of T2DM and its complications. As a continuous metabolic disease, type 2 diabetes mellitus (T2DM) is caused by the deficiency of insulin secretion and function, accounting for larger than 90% of all DM cases , 2. It iMicroRNAs (miRNAs), consisting of approximately 22 nucleotides, are a large type of noncoding small RNA molecules that suppress the expression of target gene through mRNA degradation mediated by the RNA-induced silencing complex in the posttranscriptional level . MicroRNβ cells under high glucose condition, which might be able to explain the roles of miR-210 in obesity-associated T2DM.In the present study, we first analyzed the correlation of obesity and miR-210 with clinical characteristics of patients with T2DM. Furthermore, we explored the miR-210 level in T2DM related various cells, including endothelial cells, vascular smooth muscle cells (VSMC), macrophages, embryonic fibroblasts (preadipocytes), cardiomyocytes, skeletal muscle cells (SMC), and pancreatic Totally, one hundred and thirty-seven serum samples from patients who newly were diagnosed as type 2 diabetes mellitus (T2DM) without treatments at the 3rd Affiliated Hospital of Shenzhen University from January 2020 to June 2021 were included in this study, consisting of 88 males and 49 females aged 22-74 years. Meanwhile, the demographic and general characteristics of T2DM patients, including gender, age, height, weight, body mass index (BMI), head circumference, neck circumference, waist circumference, hip circumference, visceral fat, and subcutaneous fat, were recorded. In addition, the clinical hematological characteristics were collected, including diagnosis time, fasting blood-glucose (FBG), postprandial blood glucose (PBG), fasting insulin (FINS), postprandial insulin (PINS), fasting and postprandial C-peptide, glycated hemoglobin (HbAlc), hemoglobin (HGB), red blood count (RBC), white blood cell (WBC), hematocrit value, mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean platelet volume (MPV), alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), gamma-glutamyl transpeptidase (GGT), albumin (ALB), blood urea nitrogen (BUN), creatinine (CR), uric acid (UA), triglyceride (TG), total cholesterol (TC), high-density lipoprotein (HDL), and low density lipoprotein (LDL). Moreover, investigations of patient's disease history and dietary patterns were performed. Based on BMI, patients with T2DM were divided into two groups: BMI ≤ 24 and BMI > 24. The differences of serum exosomal miR-210 level, the demographic, general, and clinical characteristics between these two groups were compared. Furthermore, according to the median of serum exosomal miR-210 level, patients were divided into the low miR-210 level group and the high miR-210 level group, and the differences of the demographic, general, and clinical hematological characteristics, disease history, and dietary patterns between the two groups were analyzed. For the serum samples and clinical data used in this study, prior patient consent and approval were obtained from the Ethics Committee of the 3rd Affiliated Hospital of Shenzhen University Hospital.β cells (Beta-TC-6) were purchased and recovered in complete DMEM medium  before use and cultured with 5% carbon dioxide at 37°C. All these cells were cultured in DMEM medium containing exosome-depleted FBS for 24 h, and then stimulated with or without high dose of glucose (30 mM), namely, high glucose group (HG) and normal group for 3 h.Human umbilical vein endothelial cells (HUVEC), VSMC, mouse mononuclear macrophages (RAW 264.7), mouse embryonic fibroblasts , mouse cardiomyocytes (HL-1), mouse SMC, and mouse insulinoma pancreatic Exosomes from serum and cell culture supernatants were isolated by ExoQuick solution  as described in the manufacturer's protocol. In brief, serum or cell culture supernatants were incubated with ExoQuick exosome precipitation reagent overnight at 4°C, and then the exosome pellet was obtained by centrifugation at 1,500 g for 30 and 5 minutes, respectively.The exosomes and treated cells were harvested to obtain total RNA samples by the TAKARA TRIzol Reagent. Then, complementary DNA samples were prepared from the isolated RNA based on the Bestar™ qPCR RT kit (DBI). The following quantitative PCR was finished using the BestarTM qPCR MasterMix (DBI) on fluorescent quantitative PCR instrument . U6 was used as the internal standards for miR-210 quantitation. Sequences of primers were all presented in Table α (HIF-1α) or GAPDH primary antibody  at room temperature for 3 h. Second antibody  was then reacted with the membrane, and the expression of these proteins was observed using enhanced chemiluminescence .The treated cells were lysed using lysis buffer  on ice to extract proteins. Then, protein samples underwent resolving on PAGE gel and transferring to PVDF, followed by blocking the membrane and reacting with carbohydrate responsive element binding protein (ChREBP), hypoxia-inducible factor 1t test. Pearson correlation analysis was used to analyze the correlations of BMI with miR-210 level, the demographic, general, and clinical characteristics as well as the correlations of the miR-210 level with the demographic, general, and clinical characteristics. A P value of <0.05 was set as the threshold.Quantitative data were analyzed using the SPSS 20.0 software. Quantitative and qualitative data were expressed as mean ± standard deviation (SD) or percentage, respectively. Skewness-Kurtosis normality analysis was applied to the study variables. The differences between two groups were evaluated by n = 57) and BMI > 24 (n = 80) groups. The miR-210 level in exosomes from serum was obviously elevated in the BMI > 24 group compared with the BMI ≤ 24 group (P < 0.05, Tables A total of 137 patients with T2DM included in this study, including BMI ≤ 24 (24 group . In addi24 group . Moreove24 group . PearsonP < 0.05, We compared the T2DM patients' characteristics between the low and high miR-210 level groups . The resα which might be transcriptional regulator of miR-210 was decreased in the high glucose-induced various cells in comparison to normal cells (We further detected the miR-210 level in various cells after high glucose exposure. The results found that compared with normal cells, exosomes from cell culture supernatants expressed obviously higher miR-210 level in high glucose-induced HUVEC, VSMC, RAW 264.7, 3 T3-L1, SMC, and Beta-TC-6 cells . Similaral cells .Increasing evidences have demonstrated that circulating miRNAs are acclaimed biomarkers due to high stability and noninvasive property to predict the occurrence and progression of various diseases, including cancers, metabolic diseases, and inflammatory diseases . miR-210Obesity is thought to be a trigger factor for T2DM , 29. It in vivo and in vitro [β cells is the underlying causes of T2DM [α has been proved to be a target gene of miR-210 [α is one of miR-210's transcriptional regulators [β cell dysfunction, thereby resulting in the occurrence of diabetic complications through regulating angiogenesis and apoptosis [α and ChREBP. Therefore, we speculated that the abnormal expression of miR-210 during the occurrence and progression of T2DM and its complications might be regulated by HIF-1 signaling. However, it is widely known that the level of noncoding RNA in serum is dynamically changed. Because the blood samples of patients at different time periods of the day were not collected, it is difficult to observe the dynamic change of miR-210 level in this study. Meanwhile, the lack of cell experiments to verify the role and mechanism of miR-210 in T2DM and its complications is also one of the limitations of this study.miRNAs have been widely reported to exist in exosomes and are involved in various cellular biological processes by regulating the functions of neighboring or distant cells . A previin vitro . Notablyin vitro . Thus, iin vitro , 35. Meain vitro . It has in vitro . In addiin vitro . More im of T2DM . Our res of T2DM , 40, 41. miR-210 , and HIFgulators . During poptosis . In addipoptosis . Consistα and ChREBP.In conclusion, data form our study revealed that circulating high miR-210 level was closely correlated with obesity-associated T2DM. Furthermore, circulating miR-210 might be implicated in the occurrence and development of T2DM and its complications, and the expression of miR-210 might be regulated by HIF-1


Ubiquitin conjugating enzyme E2S (UBE2S), a member of the ubiquitin-conjugating enzyme family, is known to play a pivotal role in tumorigenesis and progression in some tumor types. However, whether UBE2S plays an irreplaceable role in the immune-oncology context of tumorigenesis, prognosis, pathogenesis, immune regulation, and therapeutic response through certain common molecular mechanisms remains to be defined. The present pan-cancer study was intended to decipher the landscape of UBE2S in pathologic, immunological, and therapeutic aspects across various cancers.  Data used for UBE2S analysis were obtained from TCGA database. The pan-cancer analysis was mainly focused on the expression patterns, prognostic values, mutation landscapes, biological pathways, tumor microenvironment remodeling, and therapeutic resistance of UBE2S using multiple databases including cBioPortal, Cancer Cell Line Encyclopedia (CCLE) database, Tumor Immune Estimation Resource (TIMER), and Gene Expression Profiling Interactive Analysis (GEPIA). External experimental validation was conducted to delineate the association of UBE2S with tumor phenotypes through assays of proliferation, colony formation, and migration. Data processing, statistical analysis, and plotting were performed using R software and GraphPad Prism software.  UBE2S was aberrantly expressed in almost all human cancers, and elevated UBE2S expression was unfavorably associated with the clinical pathological stage and prognosis. DNA methylation and RNA modification were significantly correlated with the UBE2S expression level. The results of enrichment analysis revealed that UBE2S positively regulated MYC, G2M cell cycle, and DNA repair pathways and negatively regulated adipogenesis, fatty acid metabolism, and heme metabolism. In addition, UBE2S exhibited a significantly positive correlation with myeloid-derived suppressor cell MDSC and Th2 subsets in almost all tumors analyzed. UBE2S could confer immune evasion via coexpressed immunoinhibitors and T cell exhaustion. Notably, a higher UBE2S expression indicated a higher level of stemness, TMB, MSI, and MMR deficiency and DNA methyltransferases, as well as chemotherapeutic resistance in various cancers. Notably, in vitro functional validation showed that UBE2S knockdown attenuated the phenotypes of proliferation, clonogenicity, and migration in hepatocellular carcinoma cells.  Our study provided meaningful clues to support UBE2S as an immune-oncogenic molecule and shed light on potential applications of UBE2S in cancer detection, prognostic prediction, and therapeutic response assessment. The ubiquitin-proteasome system, mediated by E1 ubiquitin-activating enzymes, E2 ubiquitin-conjugating enzymes (E2s), and E3 ubiquitin ligases, governs key aspects of eukaryotic cell biological processes through a posttranscriptional protein modification mechanism . AccumulIn this study, we intended to conduct a visual analysis by using various bioinformatics algorithms at a systematic pan-cancer level to identify the expression patterns of UBE2S and determine the prognostic value of UBE2S across cancers. In addition, we tried to delineate the key signaling pathways with respect to cancer development and progression and decipher the correlation between UBE2S expression and immune infiltration, immune evasion, genome instability markers, and therapeutic response, hoping that the results could provide novel insights into the essential immune-oncology properties of UBE2S in the field of cancer detection, prognosis, and therapeutic response prediction.http://cancergenome.nih.gov). In addition, the cBiopPortal database  was used to identify mutation landscapes of UBE2S in diverse cancers [The Cancer Genome Atlas (TCGA) database is a landmark cancer genomics project that molecularly characterizes over 20,000 primary cancer and matched normal samples spanning 33 cancer types . In the  cancers . Transcrhttp://cancergenome.nih.gov), and a “box plot” together with a “paired dot plot” was employed for difference visualization. The differential expression of UBE2S across different pathological stages was visualized with violin plots based on the module of “stage plot” of the gene expression profiling interactive analysis, version 2 .Differential UBE2S expression between tumor tissues, para-cancerous tissues, and normal tissues was modeled using high-quality RNA sequencing datasets of 33 cancers from TCGA database  and disease-specific survival (DSS) were analyzed to delineate the prognostic landscapes of UBE2S, with the R packages “survival” and “survminer” for Cox regression analysis. Kaplan-Meier curves and survival maps of UBE2S were drawn using the “Survival Analysis” module of GEPIA2 to further analyze and validate the prognostic value of UBE2S, with OS and DSS as the censored endpoints. A cutoff value of median UBE2S expression was selected to discriminate low- and high-expression cohorts.As mentioned above, the genomic mutation landscapes of UBE2S, including the mutation type, copy number alteration (CNA), and alteration frequency, were generated from the “cancer types summary” module of the cBioPortal database, and the corresponding mutated site of UBE2S protein was explored via the “mutations” module . In addiBased on the guilt-by-association principle, we explored the coexpression of UBE2S with other associated genes extracted from TCGA transcriptome matrix using Pearson's correlation. Sorted by the level of the association index between UBE2S and related genes, those genes at the top of the gene lists were chosen for enrichment analysis to predict the impact of UBE2S expression on biological processes. R package “GSVA” was used for Gene Set Variation Analysis (GSVA), and “clusterprofiler” was employed for Gene Set Enrichment Analysis (GSEA).The immune score and stromal score were introduced to determine the abundance of immune and stromal cells via R package of “ESTIMATE,” with a higher score referring a higher proportion of the respective component in TME . ESTIMATTo further determine the underlying mechanisms of immune evasion, correlations of UBE2S with immunomodulatory and immune checkpoint genes were calculated and presented as heatmaps via packages of “limma,” “reshape2,” and “RColorBrewer.” Analyzed immune checkpoint-related genes included CD276, VEGFB, TGFB1, VEGFA, IDO1, LAG3, PDCD1 (PD1), CD274, IL12A, TIGHT, IL10, HMGB1, CD80, ICOS, IL1, and TNFRSF. T cell exhaustion-related markers, including PDCD1, CTLA4, LAG3, TIGIT, CXCL13, and HAVCR2 genes, were deciphered. Gene expression data were normalized with log2 transformation.Subsequently, genome instability markers of homologous recombination deficiency (HRD), TMB, MSI, and mutational mismatch repair  were evaluated. In addition, DNA methylation methyltransferases (DNMT), including DNMT1, DNMT2, DNMT3A, and DNMT3B, were considered to govern a fundamental role in tumorigenesis and disease progression. Therefore, we explored the landscapes of DNA methyltransferases. All datasets were obtained from TCGA database, and the results were presented based on Pearson's method.https://sites.broadinstitute.org/ccle).The half maximal inhibitory concentration (IC50) was introduced to describe the correlation between CCNA2 expression and specific therapy response in cancer cell lines. Elevation of IC50 denoted that high expression of UBE2S may confer multidrug resistance. The datasets were obtained from Cancer Cell Line Encyclopedia database  according to the manufacturer's instructions. Cells were transiently transfected for 48 h for mRNA and protein assessments. Sequences for siRNAs were as follows: siCtrl sense UUCUCCGAACGUGUCACGUTT, antisense ACGUGACACGUUCGGAGAATT; siUBE2S-1 sense UCAUCCGCCUGGUGUACAATT, antisense UUGUACACCAGGCGGAUGATT; and siUBE2S-2 sense GACACGUACUGCUGACCAUTT, antisense AUGGUCAGCAGUACGUGUCTT.HepG2 cell line, Hep3B cell line, Bel-7404 cell line, and SMMC-7721 cell line were obtained from the National Key Laboratory of Medical Immunology & Institute of Immunology, Navy Medical University. MHCC-97H cell line and QGY-7703 cell line were obtained from Eastern Hepatobiliary Surgery Hospital of Navy Medical University. All cell lines were cultured in DMEM medium supplemented with 10% fetal bovine serum, 1% penicillin, and streptomycin in 5% COβ-actin expression was used as a reference control. The primers were as follows: UBE2S, forward: 5′-ACAAGGAGGTGACGACACTGA-3′ and reverse: 5′-CCACGTTCGGGTGGAAGAT-3′; β-actin, forward: 5′-TGGCACCCAG-CACAATGAA-30 and reverse: 5′-CTAAGTCATAGTCCGCCTAGAAGCA-3′.cDNA was synthesized from the total RNA, using the PrimeScript RT reagent Kit  according to the manufacturer's instructions. qRT-PCR was performed with SYBR Premix ExTaq . The expression of β-actin . After being washed by TBST, the membranes were incubated with corresponding secondary antibody. ECL detection reagent  was used to visualize the protein bands.Proteins extracted from HCC cells were quantified with a BCA protein assay kit . Then, protein samples were fractionated by SDS-PAGE, transferred to PVDF membranes, and incubated with a primary specific antibody for UBE2S  and μl cell suspensions). Cell numbers were assessed every 24 h by CCK-8 assays according to the manufacturer's instructions.MHCC-97H cells with or without UBE2S silencing were seeded into 96-well plates  were added to the upper chambers in serum-free DMEM medium, and 10% FBS was added to the lower chambers. After 24 h, chambers were fixed with methanol for 15 min and stained with 0.1% crystal violet for 20 min and imaged.Cell migration assays were performed in 24-well plates with polyethylene terephthalate membrane filters separating the lower and upper culture chambers. MHCC-97H cells (2 × 10t-test between the two groups and one-way ANOVA tests for three or more groups. The results were deemed significantly different with two-sided p < 0.05.R software (version 4.1.3) was used for data processing, statistical analysis and plotting. Differences between two groups and multiple groups were analyzed using default Wilcoxon's test and one-way analysis of variance (ANOVA), respectively. Differences in OS and disease-free survival (DFS) between the high- and low-expression groups were calculated by Kaplan-Meier analysis and log-rank test. Hazard ratios (HRs) were determined by univariate and multiple Cox regression analysis. Correlation analysis of clinicopathological stages, immune checkpoint expression, immune infiltration abundance, and genomic mutation with UBE2S was performed using Pearson's correlation test. All experiments were independently repeated at least three times. Data are expressed as the mean ± SEM. All data were analyzed using Graph Prism  and assessed using a p < 0.001), kidney renal papillary cell carcinoma (KIRP) (p < 0.05), and kidney chromophobe (KICH) as well as thyroid carcinoma (THCA) (p < 0.01). Of note, although no controlled tissues were available in the remaining tumor types including adrenocortical carcinoma (ACC), breast invasive carcinoma (BRCA), and glioblastoma multiforme (GBM), elevated expression abundance of UBE2S could still be observed. In the paired sample cohort, a similar pattern of increased UBE2S expression was visible in most tumor tissues compared with the para-cancerous tissues, including BLCA, UCEC, HNSC, KIRP, COAD, LUSC, READ, KIRC, LIHC, BRCA, KICH, LUAD, CHOL, ESCA, and STAD (p < 0.05)  were employed in this study. In the nonpaired sample cohort, the expression abundance of UBE2S in tumor samples was significantly higher than that in the corresponding normal samples , includiand STAD . Beyond  < 0.05) . Given tp < 0.05) (p < 0.05)  . Besides < 0.05) . Taken tThe genetic-alteration profiles of UBE2S across multiple tumors of TCGA datasets were deciphered Figures . UBE2S hTo explore whether UBE2S expression was subject to regulation by DNA methylation and RNA modification, we first determined UBE2S expression patterns under various DNA-methylation loci through different probes. Our results demonstrated that DNA methylation could exert a negative modulation on UBE2S expression in multiple cancers . For insTo gain more insights into the biological function of UBE2S in cancers, we carried out GSVA and GSEA analysis to identify underlying mechanisms and relevant pathways by calculating the enrichment scores of canonical tumor-associated pathways at the pan-caner level Figures . The resThe immune score and stromal score were used to identify the association between tumor immune infiltration and UBE2S expression profiles across 33 cancer types. As shown in To further investigate the UBE2S landscape in TME, quantitative analysis of infiltrating immunoreactive cells of diverse cancers was carried out using algorithms of EPIC, MCPCOUNTER, QUANTISEQ, TIMER, XCELL, and TIDE. The results showed a significant negative relationship between macrophage infiltration and UBE2S expression in THYM, GBM and LUSC Figures . The subFurthermore, we deciphered infiltration changes of myeloid-derived suppressor cells (MDSC) and CD4+ T cells via TIDE and XCELL algorithms. The heatmap depicted that UBE2S exhibited a statistically positive correlation with MDSC and Th2 subsets in almost all analyzed tumors . IntriguAs described above, UBE2S plays a significant role in immune infiltration across diverse cancers. To further discover the in-depth landscape of immune regulation, we investigated the relationship between UBE2S expression and immune genes including immunomodulatory and immune checkpoint genes Figures . USBE2S r > 0.4, p < 0.05) and negatively correlated with them in THYM    .Growing evidence implicates that TMB is a promising biomarker for tumor-specific response to immunotherapy, especially immune checkpoint blockade –20. In oIn addition to TMB analysis noted above, we also analyzed genome instability markers involved in HRD, MSI, and mutational MMR  and founThe variation tendencies of five MMR genes are illustrated in Subsequently, we analyzed the correlation between UBE2S expression and chemical drug sensitivity based on the CCLE database. The results showed that elevated UBE2S expression could give rise to a higher IC50 of chemical drugs . In otheTo further delineate the landscape of UBE2S in tumor proliferation and progression, we carried out experimental validation. First, the protein expression levels of UBE2S were determined in six human HCC cell lines. Results confirmed that UBE2S protein was ubiquitously expressed in HCC cells, and MHCC-97H cells exhibited the highest expression . ConsequUBE2S can catalyze ubiquitin transfer to substrates for protein degradation via either E3-dependent or E3-independent mechanisms . PreviouIn this pan-cancer study, we first delineated the mRNA expression profile of UBE2S and its correlation with the tumor pathological stage. Compared with normal or para-carcinoma tissues, UBE2S expression was found to be distinctly higher in a series of cancers, suggesting that UBE2S may play an oncogenic role across these cancers. Furthermore, the aggressive characteristics of UBE2S were supported by the correlation between the upregulated expression of UBE2S and an advanced clinical stage in KIRP, KIRC, ACC, LIHC, KICH, BRCA, HNSC, and LUAD. With respect to prognostic paradigms, the high expression of UBE2S was linked with worse OS, PFS, DSS, and DFS in multiple cancers. The survival landscape was also validated by employing the GEPIA2 database, and results denoted that UBE2S overexpression was associated with unsatisfactory OS and DFS in LIHC, ACC, KIRC, and LGG. The above results regarding the oncogenic and prognostic paradigms of UBE2S are consistent with the previous experimental studies, confirming that UBE2S plays a vital carcinogenic role independent of the algorithms and databases , 28.Previous works have shown that elevated UBE2S expression promoted the proliferation, invasion, metastasis, and G1/S phase transition of cell cycle in HCC through interacting with TRIM28 , and decTME, composed of an extraordinary range of cellular subsets including tumor cells and immune cell, are thought to dramatically correlate with exacerbated cancer presentation and immunotherapeutic response. However, no convincing conclusion has been drawn on whether and how UBE2S promotes TME remodeling to favor tumor malignant phenotypes and immunotherapeutic resistance . The resImmunotherapy, especially immune checkpoint inhibitors, and targeted therapy have transformed cancer treatment and have emerged as well-established care for various human cancers in that they make complete and even durable responses possible even in patient with advanced cancers. However, only a narrow range of cancerous subpopulations could strikingly benefit from such treatments. Hence, it is essential to discover additional robust indicators for efficacy prediction and therapeutic target potential therapeutic targets. An increasing number of studies have addressed the importance of cancerous stemness and DNA methylation for drug sensitivity and resistance , 30, 31.To further confirm the reliability of the conclusion, we conducted in vitro validation to detect the association between UBE2S and HCC phenotypes. In accordance with aforementioned analyses, UBE2S knockdown attenuated the phenotypes of proliferation, clonogenicity, and migration in MHCC-97H cell, indicating the definite role of UBE2S in tumorigenesis and development.Apart from the aforementioned key findings, there were several limitations in our study. Firstly, as the majority of analyses were performed based on the existing databases, further external experimental validation is warranted. In addition, as the data concerning RNA-sequencing, clinical stage and prognosis, enriched pathways, and drug sensitivity were retrieved from a variety of databases, analytic bias is inevitable.In summary, few studies have described the immune-oncology pattern of UBE2S in human cancers. To the best of our knowledge, this is the first pan-cancer study reporting the association of aberrant UBE2S expression with the clinicopathological characteristics of patients with advanced-stage cancers and poor prognosis. In addition, we described the landscape of mutational features, DNA methylation, and RNA modification of UBE2S at gene and protein levels. Using enrichment analysis, we also summarized the potential pathophysiological functions and mechanisms of cancer development and progression and unveiled the substantial correlations of UBE2S with tumor infiltration of immune cells, immune checkpoint modules, and immunotherapeutic response-related genes, demonstrating that UBE2S played significant roles in immune evasion and could serve as a predictor of response to immunotherapy. All these findings may provide novel insights into the essential immune-oncology properties of UBE2S in the field of cancer research.Taken together, UBE2S is associated with various cancerous phenotypes, including tumor proliferation, migration, prognosis, immune infiltration and evasion, and therapy response, which supports UBE2S as an immune-oncogenic molecule.


Arabidopsis, rice and maize. Here, we presented a preliminary introduction and characterization of the whole 65 LTP genes in maize, and performed a phylogenetic tree and gene ontology analysis of the LTP family members in maize. We compared the research progresses of the reported LTP genes involved in male fertility and other biological processes in Arabidopsis and rice, and thus provided some implications for their maize orthologs, which will provide useful clues for the investigation of LTP transporters in maize. We predicted the functions of LTP genes based on bioinformatic analyses of their spatiotemporal expression patterns by using RNA-seq and qRT-PCR assays. Finally, we discussed the advances and challenges in substrate identification of plant LTPs, and presented the future research directions of LTPs in plants. This study provides a basic framework for functional research and the potential application of LTPs in multiple plants, especially for male sterility research and application in maize.Plant lipid transfer proteins (LTPs) play essential roles in various biological processes, including anther and pollen development, vegetative organ development, seed development and germination, and stress response, but the research progress varies greatly among  Lipid transfer proteins (LTPs), also named non-specific LTPs (nsLTPs), defined by their ability to facilitate transfer of non-specific phospholipids and fatty acids between membranes in vitro, widely exist in all land plants but not in algae and other organisms. Therefore, LTPs are considered as key proteins for plant survival on and colonization of land ,2. LTPs Arabidopsis, respectively [Arabidopsis involved in a wide range of biological functions, including anther cuticle and pollen wall formation [Arabidopsis and rice, and 12 of them were essential for pollen development and male fertility. LTP proteins can function in the tapetum, extracellular space or microspore. For example, type III LTPs are reported to function as exine precursor distributors and exine constituents in Arabidopsis anther tapetum [LTP genes of Arabidopsis, rice, and maize, the functional reports of LTP genes in Arabidopsis and rice will give helpful clues for investigating their homologs in maize. Furthermore, although the in vivo substrates of LTP transporters remain largely unknown, serval binding experiments of LTPs have been reported, such as an isotope labelling experiment in vivo, a protein-lipid overlay assay, or indirect imprecise measurements by using the Gas Chromatography–Mass Spectrometer (GC-MS) system [To date, plant LTPs have been reported to be involved in numerous biological processes, such as anther and pollen development, vegetative organ development, seed development and germination, and biotic and abiotic stress response . A totalectively ,13, and ormation ,14,15,16ormation ,18,19,20ormation ,23,24,25ormation ,28,29,30 tapetum . Further tapetum ,35,36,37) system ,33,38.LTP gene family, and carried out the phylogenetic tree and gene ontology analysis of LTPs in maize, rice, and Arabidopsis. The homologous and bioinformatic analysis methods were used to predict the functions of maize LTP genes, especially in anther development and male fertility. Furthermore, we summarized the progress of the substrate identification of LTPs, and discussed the future research directions and potential applications of LTP proteins in plants.Here, we updated the number and nomenclature of the maize LTP genes have been divided into six types, including type 1, type 2, type C, type D, type G, and a unique type X, while most of their functions remain obscure [www.maizegdb.org, accessed on 25 October 2022) website, we identified 65 ZmLTP genes, which is different from the previous report because of different versions of the maize reference genome. For example, the gene model of ZmLTP1.2 is GRMZM2G010868 and Zm00001d044686 in B73 V3 (B73 RefGen_v3) and B73 V4 (Zm-B73-REFERENCE-GRAMENE-4.0), respectively, but it corresponds to two gene models (Zm00001eb163900 and Zm00001eb163910) in B73 V5, and thus they were named ZmLTP1.2-1 and ZmLTP1.2-2. All the 65 ZmLTP genes are distributed to the ten chromosomes of maize with variable numbers, from ten ZmLTPs on chromosome 1 to two on chromosome 9 , ZmLTPc2 (Zmnthr3), ZmLTPd9, and ZmLTPx1 are specially expressed in tassel, the ZmLTPg20 is specially expressed in anther, ZmLTPx2 is specially expressed in endosperm, and ZmLTPd7 and ZmLTPg12 are specially expressed in roots , genome physical locus, topology, theoretical pI using Expasy , and subcellular localization prediction using Cell-PLoc 2.0 , are listed in Furthermore, the RNA-seq data revealing spatial expression patterns of maize LTP genes are retrieved from MaizeGDB . Notablyin roots , which wArabidopsis were used to construct the phylogenetic tree by using the maximum likelihood method and the MEGA7 program. All the identified LTPs can be divided into three groups (namely group 1 to 3) in the phylogenetic tree  [OsLTPg28 (previously named as OsLTP47) [AtLTPg3, and AtLTPg4 [Arabidopsis, which can be further classified into five clades (Clades 2-1 to 2-5). The largest number of LTPs related to male sterility were reported in group 2, such as AtLTPc3, AtLTPc1 [OsLTPc1 (previously named as OsC4) [ZmLTPc1 (previously named as Zmms44) [ZmLTPc2 (previously named as MZm3-3/athr3) [OsLTPd11 (previously named as OsDIL/OsLTP6) [AtLTP1.7 (previously named as AtLTP12) [AtLTP1.8 (previously named as AtLTP5) [Arabidopsis. ZmLTPx2, ZmLTPg11 [OsLTPg29  [Arabidopsis LTP genes in the clade 3-2  , OsLTPg2OsLTP47) , AtLTPg3 AtLTPg4  were rep AtLTPc1 , and theas OsC4) ,40, ZmLT Zmms44) , and ZmL3/athr3) . In addi/OsLTP6) ,42, AtLTAtLTP12) , and AtL AtLTP5)  were repZmLTPg11 , and theOsEPAD1)  were replade 3-2 , indicatThe Gene Ontology (GO) database has the highest annotation ratio compared with other analysis databases, such as CDD (Conserved Domain Database), KOG (Ortholog Group), or NR (Non-redundant database) . In ordeArabidopsis LTPs will provide important clues for exploring that of maize orthologs. Increasing evidence indicates that plant LTP transporters play important roles in anther and pollen development, vegetative and female organ development, seed development and germination, and biotic and abiotic stress response during plant biological processes  would arise if the lipid metabolism is disrupted during anther and pollen development in plants . Anther eductase ,49, ZmMsnsferase ,51,52,53L lipase , and ZmPsynthase . Then, tsynthase ,56,57, Lsynthase , and othsynthase . Loss fusynthase .Arabidopsis, rice, and maize (AtLTPc1 (At5g07230), and AtLTPc3 (At5g62080) are required for the exine precursors transport from the tapetal ER to the microspore surface, and also act as the part of components of pollen exine [atltpg3 and atltpg4 showed deformed or collapsed pollen grains, indicating the essential roles of AtLTPg3 and AtLTPg4 in pollen development [Zmms44, the ortholog of AtLTPc1 and AtLTPc3, is the only cloned dominant male sterility gene in maize, functions as a signal peptide, and facilitates the secretion of protein from tapetal cells into the locule [OsC4, an ortholog of AtLTPc1 and AtLTPc3 in rice, along with OsC6 are related to tapetal PCD of anther [To date, at least 15 LTP transporters have been reported to be involved in anther and/or pollen development in nd maize A. The tyen exine . The mutelopment . Zmms44,e locule . OsC4, af anther ,39,40, af anther . In tapef anther . Furtherf anther . These dzmltpg11/zmltpx2 double mutant [Another example, OsLTPL94/OsEPAD1, determines pollen exine patterning as a microspore membrane recruiting protein, and OsLTPL94/OsEPAD1 is not only secreted by pollen mother cells (PMCs) but also derived from the tapetum ,15. ZmLTe mutant . These fAtLTP12 determines site proline biosynthesis, which can restore the fertility of proline-deficient microspores [AtLTP5, the homolog of AtLTP12, shows abnormal vegetative and pollen tube growth, and AtLTP5 is mainly expressed in root, shoots, leaves, and pistil of Arabidopsis [Moreover, the function of LTP genes in male fertility might be influenced by abiotic stress. For example, OsDIL/OsLTP6 is related to drought stress tolerance, and OsDIL-overexpressing transgenic plants showed fewer defective anther sacs and less severe tapetal defects when treated with drought at the reproductive stage in rice ,42. AtLTrospores . Howeverbidopsis ,45. MZm3bidopsis . TogetheArabidopsis, rice, and maize [OsGAMYB, an important component of gibberellin (GA) signaling, regulates early anther development [OsC6 and OsC4 [OsTDR and OsPTC1 act downstream of OsGAMYB, and OsPTC1 associates with OsTDR to regulate expression of their downstream genes [OsC6 and OsC4 work at the downstream of OsPTC1, and OsTDR1 directly regulates the expression of OsC6 [AtAMS, the orthologs of OsTDR in Arabidopsis, directly regulates At5g62080 (AtLTPc3), At1g66850 (AtLTP2.5), and At3g51590 (AtLTP1.7) [OsLTPL94, which plays a key role in tapetum and microspore development [Transcriptional regulatory pathways that control male fertility through lipid metabolism have been well studied and reviewed in nd maize ,58. Manyelopment . OsGAMYBand OsC4 . OsTDR aam genes . For exa of OsC6 ,76. AtAMtLTP1.7) . OsEAT1 elopment . Taken tAtLTP1, a regulator of ethylene response and signaling, takes part in the export of lipids to the plant surface [AtLTP2, as the homolog of AtLTP1, plays a major structural role to maintain the adhesion integrating the mainly hydrophobic cuticle and the hydrophilic underlying cell wall [AtLTP1 to AtLTP6 play multifunction roles in plant growth and reproduction [atltpg2 and atltpg1 atltpg2 double mutants, the composition of cuticular wax in the stems and siliques was significantly altered [OsPSD1/OsPTD1, the ortholog of AtLTP6 in rice, regulates cell development, plant height, and sensitivity to temperature conditions [Another important function of LTP transporters is related to vegetative and seed development B, C. Sev surface ,25,59. Aell wall . AtLTP1 oduction . In atlt altered . OsPSD1/nditions ,24.Some homologous or orthologous LTPs may play similar roles in plant vegetative development between monocots and dicots. AtLTPG23 and AtLTPG26 are related to suberin biosynthesis .OsLTPL36, ZmBETL-9 is transcribed in the outer surface of the developing endosperm [AtEND1 is widely expressed in root, leaf, stem, flower, and seed, and plays important roles in gametophytic tissues and developing endosperm in Arabidopsis [Additionally, some LTP genes are involved in seed development or seed germination C. For exndosperm . AtEND1 bidopsis . AtLTPG5bidopsis . In summStress resistance is an important characteristic for crop breeding. However, the mechanism of LTPs in the induction of stress resistance is not fully understood . AccordiOsLTP5 in rice [Zm-LTP, the ortholog of OsLTP5 in maize, binds to calmodulin (CaM) in a Ca2+-independent manner to modulate its lipid-binding ability [atazi1 is hypersensitive to salt stress, while AtAZI1-overexpressing plants are markedly more tolerant [Arabidopsis by enhancing ABA biosynthesis and the atltp3 mutant seeds showed impaired germination under salt and osmotic treatments [atltp3/atltp4 showed that the susceptibility to Pseudomonas is reduced and the ABA biosynthesis genes are down-regulated [Pst DC3000 [Alternaria brassicicola [Pyricularia oryzae spores in vitro, and overexpression of OsLTP110 could bring a substantial resistance to biotic stresses [Abiotic stress factors include hormones, cold, and salt, etc. For example, enhancing abscisic acid (ABA), salicylic acid, and 16-hydroxypalmitic acid could induce the expression of  in rice . Zm-LTP, ability . The muttolerant ,38. OsLTtolerant . ZmLTP3 tolerant . For sigtolerant ,79. For eatments ,66,67. Iegulated ,66. AtDRt DC3000 . AtLTPG1sicicola . OsLTP1,sicicola ,71. OsLTstresses . In summAs the biological functions of genes are related to their spatiotemporal expression patterns, bioinformatics analyses will provide useful information for exploring the function of maize LTP genes. They are a useful way to predict unknown gene function by using transcriptomic analyses based on RNA-seq data ,58,80,81ZmLTPg11 and ZmLTPg4 are orthologous to male-sterile genes OsLTPg29 and AtLTPG4 [ZmLTPc1/Zmms44, ZmLTPc2/Zmanthr3, ZmLTP2.9, ZmLTP1.5, and ZmLTPd9) in subcluster I-2 based on the information in MaizeGDB (www.maizegdb.org), and two of them (ZmLTPc1/Zmms44 and ZmLTPc2/Zmanthr3) have been reported to be essential for pollen development. It is reasonable to predict the other three LTP genes may also be required for anther and pollen development, which should be proved with experimental data in the future.Based on the RNA-seq data, all the maize LTP genes can be classified into two clusters (I and II). The cluster I contains two subclusters (I-1 and I-2). The subcluster I-1 includes eight LTP genes, which are expressed at early development stages (from stage S2) of maize anthers. Among them,  AtLTPG4 ,15,17, sZmLTPg20 is anther-specific expression gene, and ZmLTPg15 is orthologous to the male-sterile gene AtLTPG3 [ZmLTPg26 and ZmLTPg14 are orthologs of male-sterile genes OsLTP47 and AtLTPG4 [ZmLTP2.5 with high expression at stages S7–S9 in B73, Oh43, and Zheng58 anthers, but undetectable expression in W23 anther. This finding indicates that some gene expression might be related to their genetic backgrounds. Notably, five LTP genes  are orthologous to the male-sterile genes OsLTPg29, OsC6, OsLTP6, and AtLTP5/AtLTP12 [ZmLTPx1 is also a tassel-specific expression gene in maize, implying that these LTP genes may be involved in anther development and male fertility. Furthermore, the expression patterns of anther- or tassel-specific expression genes and the orthologs of GMS genes in Arabidopsis and rice are confirmed by qRT-PCR analysis (The cluster II contains four subclusters (II-1 to II-4). Subcluster II-1 includes five genes with high expression at late development stages (from S10 to S13) of maize anthers. Among them,  AtLTPG3 . The sub AtLTPG4 ,31, resp/AtLTP12 ,43,44,45analysis B. These As previously reported, lipid metabolism plays important roles in plant reproductive development, including anther cuticle and pollen wall development , and theThe most effective approach to identify the substrates of LTP transporters is a transport assay by PIP lipid strips and membrane lipid strips or isotope labelling, etc. However, those transport assays must be based on the overexpression of the LTP protein in the proper expression systems, such as the prokaryotic expression system. TaMs1 and its homologous genes OsLTPg29/OsLTPL94/OsEPAD1 and ZmLTPg11 in rice and maize, respectively, were confirmed to transport phospholipids in anthers by protein-lipid overlay assay by PIP lipid strips and membrane lipid strips ,83. AtDIArabidopsis, rice, and maize , EnsemblPlants , and MaizeGDB , respectively. Physical locations including B73 RefGen_v3, Zm-B73-REFERENCE-GRAMENE-4.0, and Zm-B73-REFERENCE-NAM-5.0, and expression patterns for B73 RefGen_v3 of maize LTP genes were acquired on MaizeGDB . To collect information of physical and chemical properties for maize LTP proteins, Expasy  was used to determine molecular weight and theoretical pI, and Cell-PLoc-2.0  was used to predict subcellular localization.Gene IDs of the LTP family in  studies ,13. The Arabidopsis LTP amino acid sequences were performed by ClustalW of MEGA7. Phylogenetic trees were constructed with MEGA7 using the maximum likelihood method, and bootstrap values were based on 500 replicates. The GO analysis was performed by GENE ONTOLOGY .Multiple alignments of maize, rice, and Total RNA of B73 anthers at stages S5 to S13 were isolated by using a Trizol reagent . The reverse transcription (RT) reaction was operated according to the protocol of the RT system .RNA-sequencing (RNA-seq) analysis of maize anthers from stages S2 to S13 for W23, and S5 to S13 for B73, oh43, and Zheng58 were carried out as described by Jiang et al. .-DDCt method; each data point is the mean from three replicates ± SD. ZmUbi2 (Zm00001d05383) were used as the internal controls. The primers of qPCR analysis are shown in For quantitative real time-PCR (qPCR), three technical replicates and three biological replicates were performed on each sample, and data were analyzed by using the 2In conclusion, the findings presented here will shed light on our understanding of the critical roles of maize LTPs involved in various biological processes, including the transport and localization of lipidic precursors for anther development and male fertility, vegetative organ and seed development, and signal transport for biotic and abiotic stress response and resistance. Notably, the predicted biological functions of maize LTPs can be verified by using reverse genetics such as CRISPR/Cas9 or RNAi mutagenesis analysis ,86,87. W


Increased risk of stroke is highly associated with psychiatric disorders. We aimed to conduct the machine learning model based on multi-modal magnetic resonance imaging (MRI) radiomics predicting the prognosis of ischemic stroke.This study retrospectively analyzed 148 patients with acute ischemic stroke due to anterior circulation artery occlusion. Based on the modified Rankin Scale (mRS) score, patients were divided into good (mRS ≤ 2) and poor (mRS > 2) outcome groups. Segmentation of the infarct region was performed by manually outlining a mask of the lesion on diffusion-weighted images (DWI) using MRIcron software. The apparent diffusion coefficient (ADC), fluid decay inversion recoverage (FLAIR), susceptibility weighted imaging (SWI) and T1-weighted (T1w) images were aligned to the DWI images and the radiomic features within the lesion area were extracted for each image modality. The calculations were done using pyradiomics software and a total of 4,744 stroke-related imaging features were automatically calculated. Next, feature selection based on recursive feature elimination was used for each modality and three radiomic features were extracted from each modality plus one feature from the lesion mask, for a total of 16 radiomic features. At last, five machine learning (ML) models were trained and tested to predict stroke prognosis, calculate the received operating characteristic (ROC) curves and other parameters, evaluate the performance of the models and validate their predictive efficacy by five-fold cross-validation.Sixteen radiomic features were selected to construct the ML models for prognostic classification. By five-fold cross-validation, light gradient boosting machine (LightGBM) model-based muti-modal MRI radiomic features performed best in binary prognostic classification with accuracy of 0.831, sensitivity of 0.739, specificity of 0.902, F1-score of 0.788 and an area under the curve (AUC) of 0.902.The ML models based on muti-modal MRI radiomics are of high value for predicting clinical outcomes in acute stroke patients. Psychiatric comorbidities, such as depression , anxietyThe combination of the multi-modal magnetic resonance imaging (MRI) techniques provides a powerful tool for stroke diagnosis. Mitra et al.  used theIn this study, we constructed five machine learning (ML) models that aimed to predict the prognosis of ischemic stroke patients based on muti-modal MRI radiomics. In addition, we assessed predictive value of the models for ischemic stroke treatment decision-making.This study was a retrospective analysis of 180 patients diagnosed with acute ischemic stroke at Liangxiang Hospital  from October 2020 to May 2022, of which 148 were included in analysis . The incDemographic characteristics as well as the clinical and imaging data were collected under the permission of patients. The National Institutes of Health Stroke Scale (NIHSS) score was collected to evaluate the degree of neurological deficit in stroke patients, which represented the level of consciousness, eye movements, integrity of visual fields, facial movements, arm and leg muscle strength, sensation, coordination, language, speech and neglect . ArrangiThe modified Rankin Scale (mRS) score was used as a prognostic judgment index, with good prognosis defined as mRS scores of 0, 1, and 2, and poor prognosis defined as mRS scores of 3, 4, and 5. Of the 148 patients included in the analysis, 83 were in the good prognosis group and 65 were in the poor prognosis group.MRI scans were performed within 3 days of stroke onset, using a Magnetom Skyra 3.0T MRI scanner  with a 20-channel phased-array head coil.All participants underwent the following scans:2 × 196 mm2, thickness = 5 mm. number of layers = 24 layers, and parallel imaging factor = 2.(1) T1-weighted image scan. Scan parameters: T1w sequence, repetition time (TR) = 2,000 ms, inversion time (TI) = 900 ms, echo time (TE) = 8.8 ms, matrix = 209 × 256, field of view (FOV) = 220 mm2 × 196 mm2, thickness = 5 mm, number of layers = 24 layers, and parallel imaging factor = 2.(2) Cerebrospinal fluid suppression image. Scan parameters: T2-FLAIR sequence, TR = 6,000 ms, TI = 2,028 ms, TE = 72 ms, matrix = 320 × 261, FOV = 220 mm2 × 196 mm2, layer thickness = 2.5 mm, number of layers = 44, repetition number = 1, fat suppression on, and parallel imaging factor = 2.(3) SWI imaging scan sequence. Scan parameters: 3D-GRE sequence, TR = 27 ms, TE = 20 ms, flip angle (FA) = 15°, matrix = 256 × 256, FOV = 220 mm2 × 220 mm2, layer thickness = 5 mm, number of layers = 24, fat suppression on, and parallel imaging factor = 2.(4) DWI imaging scan sequence. Scan parameters: EPI-Resolve sequence, b-value b = 1,000 and 0 scan, TR = 500 ms, TE1 = 63 ms, TE2 = 103 ms, FA = 180°, matrix = 160 × 160, FOV = 220 mm1Image analysis was performed independently by two MR diagnosticians blinded to the groups. The region of interest (ROI) of acute ischemic lesions was manually outlined layer by layer on the DWI images using MRIcron software.2 so that the outlined lesions could be directly used for texture feature extraction in the different modal images  were aligned to the DWI images using SPM12 softwarel images .3 for radiomiscs feature extraction using the recommended settings and steps for MRI data: (1) Images were resampled to 3 mm2 × 3 mm2 × 3 mm. (2) DWI, FLAIR, SWI, and T1w images are weighted images and thus needed to be numerically standardization. A scale of 100 was used and the binwith was set to 5. Since ADC images are quantitative, no numerical standardization was done and binwith was set to 20. The above settings ensured that the total number of bins is between 16 and 128. (3) Texture feature extraction was performed on the original images and filtered images, where the filter consisted of Laplacian of Gaussian filter based on sigma = 3 and 5 mm, edge enhancement filter, and 8 wavelet transforms (combination of high pass and low pass in three dimensions). (4) Finally, the texture features of radiomics were extracted, including 18 first order, 22 glcm, 16 glrlm, 16 glszm, and 14 gldm features. Thus, a total of 946 features were extracted per image. The shape features of 14 lesion regions were also extracted.For each patient, the MRI data of the five modalities was analyzed by pyradiomics software4 was used for feature selection of the MRI data of the five modalities. The recursive feature elimination (RFE) feature extraction method was used and only the three best features were retained for each modality. For lesion shape features, we used the same method to retain the one best feature. Finally, a total of 16 image features were retained and used to train the ML model with the scikit-learn tool. A total of five methods, including Support Vector Machine (SVM) Classifier, Random Forest (RF) Classifier, Light Gradient Boosting Machine (LightGBM) Classifier, Category Boosting (CatBoost) Classifier, and eXtreme Gradient Boosting (XGBoost) Classifier, were used to build the models. Model performance was evaluated by a five-fold stratified cross-validation process. The evaluation metrics included accuracy, precision, recall, F1 score, receiver operating characteristic (ROC) curve, area under the curve (AUC), precision recall curve.The scikit-learn packaget-test was used to compare the measurement data. Results with p < 0.05 were considered to be statistically significant differences.Statistical analysis was performed using SPSS 21.0 software. The independent samples p < 0.05). No significant differences were found between patient groups for other baseline clinical characteristics  had a good prognosis and 65 (43.9%) had a poor prognosis. The training set comprised 104 patients and the remaining 44 were used to test the ML model. For the overall sample, the mean age was 64.29 years and the mean NIHSS score was 5.59. These two variables differed significantly between groups  and one best feature for lesion shape were selected as features in the ML models. The detailed information about the features is presented in The average results obtained for the test set using the different classification models after five-fold cross-validation are as follows: SVM model with 79% accuracy, RF model with 82% accuracy, LightGBM model with 83% accuracy, CatBoost model with 81% accuracy, and XGBoost model with 80% accuracy. The full model evaluation results are shown in Early and accurate determination of disease progression may be important for new stroke patients, allowing timely targeted treatment and effective improvement. To predict the prognosis of AIS early and accurately, this paper investigated five ML models based on multi-modal  MRI radiomic features to predict AIS prognosis. The results showed that LightGBM model performed best in binary prognostic classification with accuracy of 0.831, sensitivity of 0.739, specificity of 0.902, F1-score of 0.788 and an area under the curve (AUC) of 0.902.At present, most studies on the prognosis of ischemic stroke have used retrospective cohort studies to perform traditional statistical analysis of stroke prognosis models using Cox regression and logistic regression –13. PrevThis study has provided new clues for predicting the prognosis of AIS and demonstrated the ability of multi-modal based radiomics to accurately predict the clinical functional outcome of AIS, contributing to the prevention of post-stroke psychiatric diseases. However, this study still has several limitations. First, this was a retrospective study with selection bias. Studies using larger samples are needed to further validate the predictive efficacy of the model. Second, this study did not differentiate the etiology and site of stroke, and manual outlining of ROI was affected by individual subjective factors. These clinical and imaging data should be considered in further study in the next step.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.This study was approved by the Ethics Committee of Liangxiang Hospital . Written informed consent to participate was obtained from all subjects.HY and ZW designed the study and drafted the manuscript. YS, WB, KD, and CS collected the MRI data. YH and JZ analyzed and interpreted the results of the data. ZM and NW revised the manuscript. All authors approved the final manuscript.


Current treatments for lower-grade glioma (LGG) do not effectively improve life expectancy rates, and this is a major global health concern. Improving our knowledge of this disease will ultimately help to improve prevention, accurate prognosis, and treatment strategies. Pyroptosis is an inflammatory form of regulated cell death, which plays an important role in tumor progression and occurrence. There is still a lack of effective markers to evaluate the prognosis of LGG patients. We collected paraffin-embedded tissue samples and prognostic information from 85 patients with low-grade gliomas and fabricated them into a tissue microarray. Combining data from public databases, we explored the relationship between pyroptosis-related genes (PRGs) and the prognoses of patients with LGG and investigated their correlations with the tumor microenvironment (TME) by means of machine learning, single-cell, immunohistochemical, nomogram, GSEA, and Cox regression analyses. We developed a six-gene PRG-based prognostic model, and the results have identified CASP4 as an effective marker for LGG prognosis predictions. Furthermore, the effects on immune cell infiltration may also provide guidance for future immunotherapy strategies. Glioma is a frequently seen brain tumor type and is classified by the WHO into grades 1–4 . LGGs haProgrammed cell death (PCD) represents the basic mode of destroying damaged or abnormal cells . The knoInflammatory factors and associated pathways involved in pyroptosis can be tightly associated with the occurrence and development of tumors and their resistance to chemotherapeutic drugs ,15. AccoParaffin-embedded tissue samples were gathered from 85 patients diagnosed with LGG at Zhongnan Hospital, Wuhan University, between May 2016 and March 2019. Clinicopathological data such as age, gender, grade, 1p/19q codeletion, IDH mutation status, and recurrence, together with the survival status of each patient, were collected until 31 December 2021. The inclusion criteria were as follows: (1) primary tumor tissue; (2) >18 years old; (3) pathological diagnosis of grade 2 or 3; (4) complete clinicopathological information; (5) corresponding tissue wax blocks available; and (6) patients followed-up until 31 December 2021. Patients conforming to the criteria below were excluded: (1) recurrent tumors; (2) <18 years of age; (3) incomplete clinicopathological information; (4) a lack of corresponding tissue blocks; (5) not followed-up to the specified deadline; and (6) patients with multiple simultaneous tumors. Our study protocols gained approval from the Ethics Committee of the Zhongnan Hospital of Wuhan University (ethics No. 2022169K). Additionally, the present study was performed following the Declaration of Helsinki.The expression of CASP4 and CASP9 was detected using IHC in 85 glioma tissue samples. First, we constructed tissue microarrays (TMAs). After dewaxing in xylene, rehydration in alcohol, and the blocking of endogenous peroxidase activity, TMAs were subjected to incubation overnight at 4 °C with specific antibodies against CASP4  or CASP9 . The next day, a sheep anti-rabbit secondary antibody was supplemented, followed by incubation for half an hour at 25 °C. After DAB was added, color development was observed under a microscope. Finally, hematoxylin was added to counter-stain sections, followed by rinsing with water and dehydration with gradient alcohol as well as fixation using neutral gum sealing tablets. Positive cells in ×400 and ×100 microscopic fields were observed, and two pathologists unaware of the corresponding tissue information were responsible for assessing the IHC results.The gene expression levels within the tissues were assessed as follows: (1) This work chose five distinct fields of view (FOVs) at random under 400× magnification and rated positively stained cell scores as 0–4 for ≤5%, 6–25%, 26–50%, 51–75%, and >75%, respectively. (2) Staining intensity score: the immunohistochemistry staining intensities were rated as follows: negative (0 points), weak (1 point), intermediate (2 points), or high (3 points). Finally, the two scores were added: high and low expression of CASP4 and CASP9 were defined as scores of >6 and ≤6, respectively.https://xenabrowser.net/datapages/, accessed on 10 February 2022) using the iGTEx project. The GSE108474 dataset  was obtained from the GEO database . Afterwards, clinical data along with RNA-seq data for additional LGG cases were also downloaded based on the Chinese Glioma Genome Atlas (CGGA) . Batch normalization was applied by using the ‘sva’ and ‘limma’ R packages. The downloaded FPKM data were converted to transcripts per kilobase million (TPM). Data from patients without prognostic and clinical information were excluded, resulting in a total of 811 LGG cases  being included in the subsequent analyses. Details of the patients with LGG are presented in The present work acquired clinical information together with gene expression profiles  of 523 LGG cases based on the TCGA database. Meanwhile, 1152 non-carcinoma brain tissues were obtained at the University of California Santa Cruz (UCSC) Xena website  integrates DNA methylation data, mRNA and microRNA profiles, non-synonymous mutations, protein expression levels, and DNA copy numbers from the TCGA, ICGC, GEO, and other databases. Using the cbioportal online website, we summarized the copy number and somatic mutation genetic variation of 33 PRGs in LGG. Mutations in the top 15 genes were mapped as an oncoplot.The cBio Cancer Genomics Portal   Cox regression analysis [For evaluating whether PRGs could be adopted for predicting the prognosis of patients with LGG, a univariate regression was used to examine the relationship of PRGs with TCGA-patient prognosis. We chose 19 survival-related genes with analysis . TCGA-LG(n = 24) in LGG tissues were examined using an ssGSEA approach [http://www.biocondutor.org/package/release/bioc/html/GSVA.html, accessed on 20 March 2022). In line with the signature genes reported for those 24 TIICs, we analyzed the TIIC enrichment levels of every gene in every tumor tissue based on the gene expression data. In addition, we conducted a Spearman’s correlation to identify the relations of the prognosis gene with every TIIC.The TIIC levels n =  in LGG tWe obtained the single-cell RNA-seq dataset GSE182109 in the GEO database. Using <20% mitochondrial transcripts or 200 expressed genes as the threshold, we eliminated low-quality sequencing data. Seurat V4.0 , along wp < 0.05 (two-sided) were considered statistically significant.With the purpose of determining the 1-, 3-, and 5-year survival of individual patients, this work built a nomogram according to combined univariate and multivariate analysis results. A Cox proportional hazard (PH) test was conducted before constructing the nomogram . To be sp < 0.05 were considered statistically significant.To better understand PRG-related functions and pathways, this study utilized the R package “cluster Profiler” for a GO/KEGG analysis. Typically, GO terms can be categorized into biological process (BP) and molecular functions (MF), together with cellular component (CC) terms. KEGG has been developed as the database that integrates data on the genome, systemic functions, and chemistry. Adjusted values of https://www.gsea-msigdb.org/gsea/msigdb, accessed on 10 February 2022) was adopted for downloading c2.cp.v7.2. symbols.gmt, the functional annotation dataset, as a control. GSEA enrichment was estimated using the normalized enrichment score (NES). In addition, the significance of the enrichment was evaluated at FDR < 0.25 and p < 0.05.The CASP4-expression-related pathways within LGG were predicted by a gene set enrichment analysis (GSEA)   survival curves, while “survminer” was used to compare different subgroups with log-rank tests. “pROC” in R was utilized to obtain ROC curves, sensitivity, and specificity. Using SPSS22.0, this work evaluated the proportional hazard test within Cox models with Schoenfeld’s test, a KM analysis, and a log-log cumulative survival graph. This work analyzed the levels of 33 PRGs within LGG and non-carcinoma brain samples. Gene levels in LGG were collected in the TCGA database, and normal tissue expression data were obtained from the GTEx database. The SVA package was adopted to remove batch effects. Altogether, 32 PRGs showed upregulation or downregulation within LGG, whereas there was no difference in the expression of PJVK .More specifically, the expression of NLRP1, NLRP3, NLRP6, NLRC4, CASP1, CASP3, CASP4, CASP5, CASP6, CASP8, CASP9, GSDMA, GSDMC, GSDMD, GSDME, PYCARD, PRKACA, AIM2, NOD1, NOD2, GPX4, TIRAP, SCAF11, PLCG1, TNF, IL1B, and IL18 was increased in LGG relative to non-carcinoma samples, whereas the expression of NLRP2, NLRP7, GSDMB, ELANE, and IL6 was decreased .https://www.cbioportal.org/, accessed on 5 March 2022), the copy number and somatic mutation genetic variations were summarized for the 33 PRGs in LGG. Of the 283 samples, 101 (36%) showed genetic mutations. The five most significant genes in terms of mutation frequency included GSDMD, GSDMC, NLRP2, NLRP7, and NLRP6  and GSE108474 (Grade II: 64 and Grade III: 57) datasets for prognosis prediction model validation. The risk scores of all cases were determined. Later, cases were divided into low- or high-risk subgroups according to the median score and compared using the ROC and KM curves of different groups. In the GSE108474 and CGGA datasets, the KM analysis suggested that survival rates notably declined in high-risk subgroups relative to low-risk subgroups  independently predicted LGG patient prognostic outcomes , ≥40 years (p < 0.001), grade 2 (p = 0.05), grade 3 (p < 0.001), astrocytoma (p < 0.001), oligoastrocytoma (p < 0.001), 1p/19q non-codeletion (p < 0.001), and IDH mutant (p < 0.001) subgroups  development. According to our analysis, the PRGs related to prognosis  were correlated with TIICs within LGG.p < 0.001), and a negative relation to regulatory T-cell abundance (p < 0.001). CASP9 expression was positively related to the T gamma delta infiltration level and negatively related to the NK cell infiltration level (p < 0.001). The PLCG1 level was positively related to the T-helper cell level (p < 0.001).As a result, CASP4, CASP5, and IL18 expression showed positive relations to the abundances of macrophages, neutrophils, and eosinophils , CASP4 (p = 0.005), and IDH mutation (p < 0.001) independently predicted LGG patient prognosis . According to the ROC curves, CASP4 was effective in predicting prognosis in the TCGA , GSE108474 , and CGGA  databases  and GC ,37, wherRecent research has revealed functional crossovers between pyroptosis, apoptosis, and necroptosis . GSDME cThe KM and ROC curve analyses of our prognostic model showed good prediction results in the TCGA, GSE108474, and CGGA databases. As revealed by a multivariate regression, the risk score can independently predict LGG patient prognosis. Subsequently, to further evaluate the LGG patient survival time, this study combined our prognostic model with clinicopathological factors to construct a nomogram, and the results showed that our nomogram model performed well in predicting OS rates for LGG cases at 1, 3, and 5 years.Upon univariate/multivariate regression with clinicopathological factors and model genes, CASP4, CASP9, and PLCG1 could act as independent prognostic factors for LGG. Since PLCG1 was already known to be associated with LGG patient prognostic outcomes , we furtCancer immunotherapy based on immune checkpoint inhibitors (ICIs) has shown significant clinical success in recent years , despiteHowever, this study has certain limitations. First, we only adopted online databases for analysis, and the prognostic model was not verified by additional experiments. Second, the number of clinical specimens was not large, and limited by the experimental conditions, we could only verify the prognostic effects of CASP4 by IHC; consequently, further investigations will be required to understand its mechanism of action.The present work establishes a PRG-based prognostic model that can predict LGG patient prognosis and offers a certain reference for clinical decision making. A study on the PRGs included in our prognostic model was also conducted. As a result, LGG cases with high CASP4 expression showed reduced survival time. This indicates that CASP4 can independently predict LGG patient prognosis. Its effect on immune cell infiltration may thus offer more guidance for immunotherapy.


Endocrine-disrupting substances (EDS) are common and pervasive in our environment and pose a serious risk to both human and animal health. Endocrine-disrupting compounds (EDCs) have been associated with a variety of detrimental human health effects, including respiratory issues, as a result of their ability to disrupt cell physiology. Vinclozolin ((RS)-3--5-methyl-5-vinyloxazolidine-2,4-dione) is a common dicarboximide fungicide used to treat plant diseases. Several studies have analyzed the effects of vinclozolin exposure on the reproductive system, but less is known about its effect on other organs such as the lung. Mice were exposed for 28 days to orally administered vinclozolin at a dose of 100 mg/kg. Vinclozolin exposure induced histological alterations and collagen depositions in the lung. Additionally, vinclozolin induced inflammation and oxidative stress that led to lung apoptosis. Our study demonstrates for the first time that the toxicological effects of vinclozolin are not limited to the reproductive system but also involve other organs such as the lung. In vineyards and on fruits and vegetables such as raspberries, lettuce, kiwifruit, snap beans, and onions, vinclozolin ((RS)-3--5-methyl-5-vinyloxazolidine-2,4-dione), a popular dicarboximide fungicide, is used to treat diseases such as blights, rots, and molds. Additionally, it is applied to golf course turf. Vinclozolin, which was first registered in 1981, is widely utilized, but its total application has decreased. Vinclozolin is subject to Environmental Protection Agency (EPA) regulation as a pesticide in the United States (U.S. EPA) ,7. MoreoWe decided to explore the histological damage to the lungs due to exposure to vinclozolin. To assess pulmonary fibrosis in lung tissue, Masson’s trichrome staining was used. When compared to the sham group, vinclozolin administration caused fibrotic lesions in which the alveolar walls presented an increased amount of blue-stained fibrous connective tissue  production C, as wel2O2 D and rea2O2 E. We fouAdditionally, numerous interleukins (ILs), which cause problems with cellular communication, are released when endocrine disruptors (EDs) are present, according to numerous independent investigations . Using EWhen exposed to oxidative injury, organisms have evolved defensive mechanisms that include Nrf-2-HO-1 pathway activation and antioxidant enzymes such as superoxide dismutase (SOD), glutathione peroxidase (GPx), and catalase (CAT). By Western blotting, we found a significant decrease in Nrf-2 C, GPx FD, and CAExposure to endocrine disruptors has been linked to epigenetic alterations in a variety of tissues and organisms ,15. We iTo further investigate the effects of vinclozolin exposure on the lung, we conducted a Western blot analysis of Bax and Bcl-2. We found that animals subject to vinclozolin exposure showed a significant decrease in Bax expression  were acquired from Envigo  and kept in a controlled environment. All animal experiments complied with the new Italian regulations (D. Lgs 2014/26), EU regulations (EU Directive 2010/63), and ARRIVE guidelines.Sham: animals that were untreated (shown only in the histology);Sham+vehicle: animals that were orally administered with corn oil;Vinclozolin: animals that were orally administered 100 mg of vinclozolin daily for 28 days.Mice were arbitrarily divided into three groups:At the end of experiment, mice were sacrificed, and lung tissue and blood samples were collected for histology and biochemical analysis as previously described ,38. The g for 10 min at 4 °C. Following this, supernatants representing the cytosolic fraction and pellets containing enriched nuclei were re-suspended in Buffer B containing 1% Triton X-100, 150 mM NaCl, 10 mM Tris-HCl, pH 7.4, 1 mM EGTA, 1 mM EDTA, 0.2 mM PMSF, 20 μM leupeptin, and 0.2 mM sodium orthovanadate, as previously mentioned [Extracts from the cytosol and nucleus were prepared firstly with Buffer A containing 0.2 mM PMSF, 0·15 μM pepstatin A, 20 μM leupeptin, and 1 μM sodium orthovanadate, homogenized at the highest setting for 2 min, and centrifuged at 1000× entioned ,40. The entioned ,46,47,48Lungs were stained with hematoxylin/eosin (H/E) or Masson Trichrome and analyzed using a LeicaDM6 light microscope connected to an imaging system (LasX Navigator); they were blindly scored by two investigators without knowledge of the experimental groups. The severity of lung damage and fibrosis was assessed according to the method of Ashcroft et al. ,49. BrieLung sections were incubated with anti-PARP antibody , as previously described by Cordaro et al. . At the Malonaldehyde (MDA) levels were assessed, as previously described for lung tissue, at the end of the experiments. Briefly, after homogenization, MDA absorbance was measured at 650 nm using a spectrophotometer and expressed in mill-units per 100 milligram weight (mU/100 mg) of wet tissue ,54.2O2) consumed per min per mg of protein [SOD activity assay was performed following the method described by Marklund and Marklund at 420 nm ,10,55,56 protein ,58,59. T protein ,61,62,63ELISA kits were used to investigate IL-1β, IL-18, IL-6, IL-10, and IL-4 in bronchoalveolar lavage fluid (BALF) at the end of experiment, as previously described ,65,66,67TUNEL staining for apoptotic cell nuclei and DAPI staining for all cell nuclei were performed in lung sections as described previously ,69,70,71The levels of relative genes from lung tissues were measured by real-time quantitative polymerase chain reaction analysis (RT qPCR) using kits according to the manufacturer’s protocol . The following primers were used: IL1β (F) ATGAAAGACGGCACACCCAC (R) AAGGCAGAGTCTTCGGTGAG; IL-6 (F) CAACCAAGAGGTGAGTGCTTC (R) GGTGTCCTCTTTCCCACACTG; IL-18 (F) GGAAGACCAGAGACATCCACTG (R) ACACTAGACCAAAGGGCTTG; IL-4 (F) CTGTAGGGCTTCCAAGGTGC (R) CTCTCATTGTGCCAGGTCACT; IL-10 (F) GCCAGTTAGAAAGCCACCAC (R) GGTTCAGCCTGTTTCCCAAC; ACTIN (F) GGCTGTATTCCCCTCCATCG (R) CCAGTTGGTAACAATGCCATGT. The expression levels of target mRNA were normalized to that of actin .Vinclozolin (Lot #BCBZ5052) was obtained from Sigma-Aldrich INC. P.O. . Unless otherwise stated, all compounds were purchased from Sigma-Aldrich . All solutions were prepared using nonpyrogenic saline .In this study, all data are expressed as the average ± SEM and represent at least 3 experiments carried out on different days. For in vivo studies, N represents the number of animals used. The number of animals used for in vivo studies was determined using G*Power 3.1 software . In all statistical studies, GraphPad Prism 8 software  was used. The results were analyzed by t-test, and a p-value less than 0.05 was considered significant.In conclusion, in our study, we demonstrated for the first time that exposure to the fungicide vinclozolin, especially when chronic, induces serious alteration to the respiratory system, with an increase in inflammation, oxidative stress, and apoptosis. This is the first study to consider vinclozolin not only as an endocrine disruptor with androgenic activity but also as a toxin that will require a series of tests and regulations in order to evaluate its risks and hazards on the environment and animals.


Their relative tissue- and organelle-selective distribution, together with agonist-selective ion permeabilities provides a rich palette from which extracellular stimuli can choose. TPCs are emerging as mediators of immunity, cancer, metabolism, viral infectivity and neurodegeneration as this short review attests.In recent years, our understanding of the structure, mechanisms and functions of the endo-lysosomal TPC (two-pore channel) family have grown apace. Gated by the second messengers, NAADP and PIP That is, in addition to their roles of trafficking cargo, repairing membranes, degrading macromolecules and nutrient sensing, acidic vesicles generate Ca2+ signals. The purpose of this article is to update our previous overview [2+-permeable channels found on such acidic vesicles — the TPCs (two-pore channels) — and we confine our remarks to the mammalian channels.These Hoverview  with mor2+] within endosomes is tens of micromolar, whereas in lysosomes it is ∼300–600 µM  is ∼12 mM, the lysosomal luminal [Na+] is reported from 21 mM  and TPC2-A1-P [PIP2 mimetic]), and are selective for TPC2 over TPC1 and TRPMLs [Historically, activation of TPCs in intact-cell populations has been limited to NAADP delivery via liposomes ,72 or ce of TPC2 . Each mid TRPMLs . TPC2-A1d TRPMLs   [Interestingly, photo-release of another lipid, sphingosine, acutely evoked Caot TPC2) ; is thisot TPC2) , but the2+ transients in myocytes [2 [2 [Of broad interest, the mTOR inhibitor, rapamycin, evokes TPC2-dependent Camyocytes  and promcytes [2 . Likewises [2 [2 ,78. Whiles [2 [2 ,76,79.Other signalling inputs may interact with TPCs including protein kinases such as LRKK , JNK/p382 [2+ [+ (ΔΨ) [In the global population, TPC2 naturally occurs with a spectrum of different polymorphisms  and some2 ,76,83 or2 . However2 [2+ , Na+ (ΔΨ [+ (ΔΨ) ,83 and p [+ (ΔΨ) ,56,83 ha2+ signals converted (decoded) into downstream responses? A common theme is that TPCs affect vesicle formation, trafficking, maturation and movement, many of which are sensitive to Ca2+ and lysosomal membrane potential. Being small Ca2+ stores, endo-lysosomes are designed to generate local rather than global Ca2+ signals, and TPCs couple to downstream physiology via local Ca2+ signals for which other Ca2+ sources cannot substitute, as exemplified by phagocytosis [2+-decoders include Ca2+-dependent channels, protein kinases/phosphatases and membrane-fusion machinery.How are TPC-dependent Caocytosis ,42, exococytosis , membranocytosis , receptoocytosis ,87, deveocytosis , vesiculocytosis ,89. Ca2+2+ release, TPCs trans-activate Ca2+-regulated ion channels on other membranes that are closely apposed, probably at MCSs. Via Ca2+-induced Ca2+ release (CICR), IP3Rs or RyRs on the ER can amplify the small Ca2+ release from endo-lysosomal TPCs to evoke global Ca2+ signals [2+-sensitive channels  depolargnalling  under thgnalling . Althougtivation .2+ signals are otherwise decoded is underexplored. Privileged TPC-coupling to downstream processes implies that Ca2+-sensitive decoding proteins are intimately associated with TPCs and sense these high Ca2+ nanodomains. Several TPC interactomes have been published . Phagocytosis is uniquely driven by local Ca2+ from TPCs  [2+-dependent phosphatase, calcineurin, may be the Ca2+ decoder [How local TPC Caiewed in ), but susignals) , where t decoder .2+-binding decoders are growing, and the GTPase, dynamin, has been linked to the NAADP/TPC axis during ‘inward’ trafficking at phagocytosis [2+-binding proteins. In neuronal cells, the NAADP/TPC axis activates AMPK during autophagy [The molecular switches downstream of the immediate Caocytosis  and endoocytosis . Regardiocytosis , althougutophagy . In melautophagy . Affirmiutophagy .Our appreciation of the importance of TPCs is expanding, but the following, recent examples incidentally reinforce that the precise molecular details of the circuitry are often lacking and we do not know the messenger, permeant ion or the decoders. Our understanding of the roles of TPCs is still in its infancy.2+ signals [TPCs contribute to neuronal homeostasis . The neu signals  which in signals . TPCs ar signals ,101, neu signals  and axon signals ,102. AbeIn the vasculature, the role of TPCs is growing and, in particular, at vasculogenesis. The proliferation of endothelial precursors cells is dependent upon NAADP and TPC1 ,103, andMetabolically, the nutrient-sensing kinase complex of mTOR inhibits TPC2 which thereby responds to nutrient status . Recipro2+ circuitry to regulate vesicular trafficking events in an immune context [TPCs are abundantly expressed in immune cells and are involved in often complex Ca context . Extrace context  and macr context  in macro context , of cyto context  and the  context . Thus, TGiven their physiological roles — particularly of membrane and protein trafficking — TPCs are implicated in a wide range of diseases that are a significant health burden . For neu2+ signals at MCSs [2+ release [TPCs contribute to cardiovascular complications. In blood vessels, TPCs exacerbate hypoxia-induced hypertension ,118 or m at MCSs , and TPC at MCSs . Similar release  that mig release ; therefo release ,122.Pathogens deliver toxins and/or enter the host cells to replicate, often gaining access via the endocytic pathway where they traffic through the endo-lysosomal system by co-opting host pathways. Since TPCs regulate vesicular uptake pathways  ,42,123 aAn increasing field is that of TPCs in cancer  where, rIn this brief overview, we have highlighted the diversity of both the ionic nature of the TPC signals and the breadth of the (patho)physiological processes in which TPCs play an important role, and this is only set to grow. A common theme is the involvement of TPCs in vesicular trafficking. With still so many unknowns, and the likely intersection with hitherto unsuspected pathways, the field of endo-lysosomal ionic signalling will continue to be a rich source to mine.2+-permeable channels that are emerging as important signal transducers across biology and phyla.TPCs are endo-lysosomal CaUnusually, their ion conductances depend on the stimulus: they are plastic channels.2+, electrical, lysosomal pH).Different conductances confer the ability of TPCs to signal in different modalities (e.g. CaNew TPC protein regulators have recently emerged.