Accumulating evidence demonstrated that tumor microenvironmental cells played important roles in predicting clinical outcomes and therapeutic efficacy. We aimed to develop a reliable immune-related gene signature for predicting the prognosis of ovarian cancer (OC).Single sample gene-set enrichment analysis (ssGSEA) of immune gene-sets was used to quantify the relative abundance of immune cell infiltration and develop high- and low-abundance immune subtypes of 308 OC samples. The presence of infiltrating stromal/immune cells in OC tissues was calculated as an estimate score. We estimated the correlation coefficients among the immune subtype, clinicopathological feature, immune score, distribution of immune cells, and tumor mutation burden (TMB). The differentially expressed immune-related genes between high- and low-abundance immune subtypes were further used to construct a gene signature of a prognostic model in OC with lasso regression analysis.The ssGSEA analysis divided OC samples into high- and low-abundance immune subtypes based on the abundance of immune cell infiltration, which was significantly related to the estimate score and clinical characteristics. The distribution of immune cells was also significantly different between high- and low-abundance immune subtypes. The correlation analysis showed the close relationship between TMB and the estimate score. The differentially expressed immune-related genes between high- and low-abundance immune subtypes were enriched in multiple immune-related pathways. Some immune checkpoints  were overexpressed in the high-abundance immune subtype. Furthermore, the five-immune-related-gene-signature prognostic model -based high-risk and low-risk groups were significantly related to OC overall survival.Immune-related genes were the promising predictors of prognosis and survival, and the comprehensive landscape of tumor microenvironmental cells of OC has potential for therapeutic schedule monitoring. Ovarian cancer (OC) is one of the most common gynecological tumors worldwide . The OC Accumulating evidence demonstrated that the immune system played an important role in cancer initiation, progression, and therapeutic responses . OC was In this study, 308 OC cases from TCGA database were divided into two immune subtypes—high and low abundance groups of immune cell infiltration based on the mixed cellular gene expression data. These two immune subtypes were systematically correlated with clinical characteristics, ESTIMATE results , and mutation information. These correlation results were used to predict and evaluate the clinical outcomes of OC. Further, lasso regression was used for the identification of the five-immune-related-gene signature model  to improve the predictive accuracy for OC overall survival. This study aimed to quantify the cellular compositions of the immune response and explore its association with the OC prognosis. The immune-based prognostic signature will provide potential value for prognostic prediction and tailored immunotherapy of OC.1. Patients with complete follow-up information and survival status were selected to match with their RNA-seq data. The main outcome of our study was overall survival. Patients without survival information were removed for further evaluation. Following these criteria, 308 OC cases were involved in this study , mutation data, and clinical follow-up data were obtained from the public database TCGAis study . Data wen = 415). The raw data from the microarray datasets generated by Affymetrix and Illumina were downloaded from the Gene Expression Omnibus2, including gene expression data, and survival information.Also, OC gene expression datasets were systematically searched that were publicly available with full clinical annotations. The data from GSE13876 “Survival Related Profile, Pathways and Transcription Factors in Ovarian Cancer” were downloaded to validate the reliability of the built model. GSE13876 developed a gene expression profile associated with overall survival in advanced-stage serous ovarian cancer  was used to quantify the abundance of tumor microenvironment cell infiltration in each sample based on the gene expression data . Briefly3.Tumors with different qualitative microenvironment cell infiltration patterns were grouped with sparse hierarchical clustering based on Euclidean distance and Ward’s linkage. The sparse k-means method was used to establish the optimal number of tumor groups. This method used the genes in each node and metanode. Briefly, classification consistency was tested with random forest. The sparse hierarchical clustering algorithm was used to analyze the data that contained the variables selected by the sparse K-means method, which optimized the classification of samples into two subtypes . This pr4.ESTIMATE  is a tool to predict tumor purity and the presence of infiltrating stromal/immune cells in tumor tissues with gene expression data . The EST5, with the algorithm run using the LM22 signature and 1,000 permutations  considered a minimal representation for each cell type and, based on those values, infers cell type proportions in data from bulk tumor samples with mixed cell types using support vector regression. Gene expression profiles were prepared with standard annotation files, and data were uploaded to the CIBERSORT web portalutations . The corutations .6, and is specially used to visualizethe information in MAF files. The distribution of tumor mutation burden (TMB) was conducted by Maftools R package  based on the corresponding data from CellMiner7.TMB was calculated as mutations per megabase (mut/Mb). Mutational signature analysis was performed for tumors with somatic mutation counts of at least 10. With the development of cancer genomics, mutation annotation format (MAF) was widely accepted and used to store the detected somatic variants. Maftools is an R package that is published in Bioconductor package , which g package . Furthert-tests . The adjusted P-value for multiple testing was calculated with the Benjamini-Hochberg correction. The immunology database and analysis portal (IMMPORT) website8 is funded by the NIH, NIAID, and DAIT in support of the NIH mission to share data with the public. The expression information of immune-related genes of each sample was extracted with ImmPort, and differentially expressed immune-related genes (DEIRGs) were identified, including genes that were directly or indirectly involved in immune responses . DEGs between these two groups were determined with the R package limma package (Bioconductor version 3.0), which implements an empirical Bayesian approach to estimate gene expression changes using moderated t-tests . DEGs amesponses .9. Gene Ontology (GO) terms  < 0.05. The upregulated and downregulated pathways were also identified between two immune subtypes with a gene set enrichment analysis (GSEA) of the adjusted expression data for all transcripts. Gene sets were downloaded from the MSigDB database of Broad Institute10. Enrichment P-values were based on 10,000 permutations and subsequently adjusted with the Benjamini-Hochberg multiple testing to control the FDR. All DEIRGs were mapped in the protein–protein interaction (PPI) network in the STRING11 database O) terms  and KyotO) terms  were idedatabase  to evalup < 0.05 was considered a statistical significance. Further, the overall survival-related DEIRGs were selected to construct lasso regression that examines the relationship between gene signatures and OC risk score. Lasso regression was constructed by the glmnet R package12. The risk scores of OC samples were calculated according to the expression of the selected overall survival-related DEIRGs and were stratified into high- and low-risk score groups based on the median value of the risk scores. The Kaplan-Meier method was used to evaluate the availability of the prognostic model. In addition, the association of clinical characteristics with overall survival was analyzed in OC patients with the univariate and multivariate Cox regression model.The OC samples were divided into two groups according to the mean value of DEIRG expressions. Overall survival was calculated with the Kaplan-Meier method and compared to the log-rank test. The t-tests for normally distributed variables and with Mann-Whitney U-tests  for non-normally distributed variables. The Spearman correlation coefficient was calculated between the TMB score and ESTIMATEScore by Graphpad prism 8. In all cases, p < 0.05 was considered as statistical significance. Benjamini-Hochberg multiple testing and FDR were calculated to correct the p-value in DEGs, GO, and KEGG analysis. The Kaplan-Meier method was used to generate survival curves for the subgroups in each data set, and the Log-rank (Mantel-Cox) test was used to determine the statistical significance of differences. The hazard ratios for univariate analyses were calculated with a univariate Cox proportional hazard regression model.For between-group comparisons, statistical significance was estimated with unpaired Student’s + T cells, checkpoint, cytolytic activity, DCs, HLA, iDCs, inflammation-promoting, macrophages, mast cells, MHC class I, neutrophils, NK cells, parainflammation, pDCs, T cell co-inhibition, T cell co-stimulation, T helper cells, Tfh, Th1 cells, Th2 cells, TIL, type I IFN response, and type II IFN response). The OC samples provided an optimum classification into two subtypes with the sparse hierarchical clustering algorithm based on the data containing immune cell information, which named high- and low-immunity abundance groups of the immune cell infiltration   . The ssGn = 152) . The corn = 152) .The tumor-immune infiltration of the 308 OC samples was summarized . The disThe distribution of tumor mutation was plotted to explore the relationship between immune and mutation statuses of OC . The mutA total of 20,530 genes were analyzed with the limma package to identify the underlying biological characteristics of immune subtypes, and 9712 DEGs were acquired . Next, GThe GO and KEGG analysis showed that DEGs were significantly enriched in the immune system, which prompted IRGs expression changes between immune subtypes. The expression information of IRGs was extracted from each sample according to the list of IRGs curated by the Immunology Database and Analysis Portal (IMMPORT) website, which included genes that were directly or indirectly involved in immune responses. A total of 998 IRGs were curated by the IMMPORT dataset in OC , among wMajor histocompatibility complex (MHC), a group of genes that code proteins, was found on the surfaces of cells that help the immune system recognize foreign substances. MHC proteins were found in all higher vertebrates. In human beings, the complex was also called the human leukocyte antigen (HLA) system. According to the hub molecules obtained from the PPI network, the HLA system and immune checkpoints  were identified. The expression information of the HLA family and immune checkpoints from DEIRGs were shown , which ip < 0.05), including CCL18, CXCL13, HLA-DOB, HLA-DPB2, HLA-DQA2, HLA-DRB6, HLA-J, IFNG, IL18RAP, and TNFRSF17 (p = 0.0248).The K-M plot analysis revealed that 10 out of 118 DEIRGs were significantly associated with OC overall survival  and high-risk score group (n = 208) according to the median risk score based on the immune-based prognostic model. There was a significant difference in the OS rate between the two groups, and the OS rate was significantly lower in the high-risk score group compared to the low-risk score group   . The pre= 0.001) . FurtherIn terms of immune-related pathways, DEGs between immunity-high and -low abundance groups of immune cell infiltration were enriched in multiple immune-related pathways according to GO and KEGG analyses; for example, PD-L1 expression and PD-1 checkpoint pathway in cancer, antigen processing and presentation, Fc gamma R-mediated phagocytosis, T-cell receptor signaling pathway, and natural killer cell-mediated cytotoxicity. The multiple enriched pathways were closely related to tumorigenesis and progress in OC, and some studies tried to use PD-1/PD-L1 pathway inhibitors in cancer. It was reported that the PD-1 receptor and its ligand (PD-L1) were over-expressed in tumor cells and immunology system cells in OC patients. It is possible in the future to apply PD-1/PD-L1 pathway inhibitors in the treatment of ovarian cancer . The previa human NK cells as well as the formation of NK-tumor conjugates. Mice implanted with MUC16-knockdown OVCAR-3 showed a more than twofold increase in terms of survival compared to controls  xenograft tumors, which indicated that Fludelone could be a promising compound for cancer chemotherapy in OC  process. The specific ERK inhibitor PD-98059 efficiently impaired the cisplatin-resistance of ovarian cancer cells and decreased cell proliferation and migratory area by inhibiting the ERK pathway and EMT process  with lasso regression, and such model-based high-risk and low-risk groups were significantly related to OC overall survival. Mutations in the tumor genome can cause tumors to express mutant proteins that are tumor-specific and not expressed on normal cells (neoantigens). These neoantigens are an attractive immune target because their selective expression in tumors may minimize immune tolerance as well as the risk of autoimmunity . This prcontrols . CCL18, nt of OC . Furthernt of OC . For exant of OC . A case nt of OC . One stupy in OC . The cis process . Those d+ T cells, naive T cells, and CD8+ T cells but not for granulocytes and monocytes. It might play a role in both humoral and cell-mediated immunity responses. Finally, CCL18 was involved in immune tolerance toward cancer to influence cancer cell activation and migration . The risk score derived from this prognostic signature model could be one of the risk factors for OC alongside age at initial pathological diagnosis, anatomic neoplasm subdivision, cancer status, primary therapy outcome, and residual tumor disease. Those five immune-related genes in the prognostic signature model played important roles in immune and cancer . For exaigration . CXCL13,igration . Recent igration . This geigration , invasivigration , and coligration . Comparap < 0.05; then, these statistically significant results were rationalized in the biological system with a scientific explanation. For example, the five-immune-related-gene prognostic signature model  constructed with lasso regression based on the TCGA ovarian cancer database was verified with a GEO ovarian cancer dataset, and these genes were scientifically rationalized in the biological system of ovarian cancers as described in the section of discussion. Another example, for the mutation study, is that the top mutation gene expressions of OC were statistically significantly associated with drug sensibility, and those mutation genes were thought to be potential targets in OC, such as the drugs dasatinib, zoledronate, epothilone B, pelitrexol, vemurafenib, dabrafenib, PD-98059, tamoxifen, and nelarabine. Some of these drugs have been proven to be effective in OC, as described in the discussion. It clearly demonstrates that the statistically significantly related findings in the current study are also scientifically significant, which is of important scientifical merit in the treatment of OC patients.Scientifical significance is different from statistical significance in terms of the concept aspect, though both have a certain overlapping . When weTumor microenvironment alterations participate in carcinogenesis and development in OCs. Recent studies have revealed that mutation gene distribution and immune-related genes play critical roles in regulating the reprogramming of immune status in cancer cells. In this study, ssGSEA was a useful tool to quantify the relative abundance of immune cell infiltration and recognize immune subtypes. Systematical analysis of the relationships between immune subtype, clinical characteristics, ESTIMATE results, and mutation information could provide new insights into the clinical outcome prediction of OC. Lasso regression identified the five-immune-related gene signature model  to improve the prediction accuracy for overall survival in OC. Further quantitative investigations of cellular immune infiltrations in tumors may contribute to therapeutic advances. Identification of combination roles of multiple key molecules in recognition of heterogeneity and complexity of tumor microenvironment cell infiltration will reveal the potential mechanisms of tumor microenvironment antitumor immune responses and determine more effective immunotherapy strategies.The original contributions presented in the study are included in the article/NL designed the project, analyzed the data, prepared the figures and tables, and wrote the manuscript. BL participated in partial bioinformatics analysis. XZ conceived the concept, supervised the results, critically revised and wrote the manuscript, and was responsible for its financial supports and the corresponding works. All authors approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Hydrogels are polymeric three-dimensional network structures with high water content. Due to their superior biocompatibility and low toxicity, hydrogels play a significant role in the biomedical fields. Hydrogels are categorized by the composition from natural polymers to synthetic polymers. To meet the complicated situation in the biomedical applications, suitable host–guest supramolecular interactions are rationally selected. This review will have an introduction of hydrogel classification based on the formulation molecules, and then a discussion over the rational design of the intelligent hydrogel to the environmental stimuli such as temperature, irradiation, pH, and targeted biomolecules. Further, the applications of rationally designed smart hydrogels in the biomedical field will be presented, such as tissue repair, drug delivery, and cancer therapy. Finally, the perspectives and the challenges of smart hydrogels will be outlined. Hydrogels are cross-linked three-dimensional hydrophilic networks with the ability to maintain large amounts of water with tunable biocompatibility, biodegradability, acute environmental sensing, and mechanical properties .Hydrogels can be designed by the incorporation of natural or synthetic polymers through physical or covalent cross-linking. Their properties can be adjusted to meet the diverse applicable demands by the variation of hydrophilic and hydrophobic proportion or the addition of active recognition motif . HydrogeAs shown in Hydrogels can be divided in two categories by the forming molecule types, natural polymer and synthetic polymer. Commonly, naturally derived hydrogels including cellulose , chitosaChitin, a natural mucopolysaccharide, is one of the most plentiful polysaccharides on earth, ranking second to cellulose . Chitosad-mannuronic acid (M) and 1,4-α-l-guluronic acid (G) which are organized in a block (-M-M-M- or -G-G-G-) or alternating (-M-GM-G-) configuration. Alginate is able to chelate with divalent cations to form physical hydrogels such as Ca2+ and Ba2+ with G block which prompts the generation of ionic bridge between nearby polymer chains  with linear structure and molecular weight ranging from 6,500 to 10,900 kDa is a component of all connective tissue . It is acosamine . HA is acosamine . HA-basecosamine , meshes cosamine , and spocosamine . HA and cosamine , wound dcosamine , drug decosamine , and tiscosamine  due to icosamine . Howevercosamine . To imprcosamine . Variouscosamine . For exa  and semi-IPN . IPN is By far, hydrogels can be formulated with various polymers to endow them diverse functionality in biomedical applications. Based on the responsive stimuli, smart hydrogels could be divided into physical, chemical, and biochemical responsive hydrogels. They are extensively applied in biomedical fields, including therapeutic delivery , contactPrecisely, rational design for smart hydrogel in biomedical application is needed according to the inherent property of hydrogel and the molecular constructure, to meet the detailed and trivial demand of the practical biomedical applications.Generally, physical stimuli such as temperature, light, and electricity can be easily modified, which make it the prioritized option for biomedical applications .Thermosensitive hydrogel is the most extensively evaluated and conventional type of stimuli-responsive gel system. They are defined by their capability to swell or shrink with the surrounding temperature changing . The volThere are diverse applications for thermosensitive hydrogels, including bacterial infected wound healing , tumor tl-lactide)–poly(ethylene glycol)- (PLEL) and polysaccharides, endow hydrogels with a unique feature of thermosensitive. By variation of end groups of NIPAM, the LCST can be tuned in the range of 32.8°C–45.3°C (l-lactide) inside, respectively. The subsequent entanglement of PEG fragment causes the gelation of PLEL solution which in turn enhances the tissue adhesion at physiological temperature. The animals experiment revealed that the thermosensitive hydrogel could effectively close the broken skin and conspicuously facilitate wound healing.LCST based coil-to-globule transition of the crosslinker is the driven force to achieve thermosensitive sol–gel transformation . LCST ofC–45.3°C . Below Lin-situ photopolymerization. The light stimulus, commonly UV or near-infrared light, can be imposed instantly and delivered with space-time accuracy, allowing overall control of the hydrogel formation with tunable properties  prepared a SMH by synergetic integration of 2-phenoxyethyl acrylate (PEA) with acrylamide (AAm). The hydrogel possessed strong mechanical strength and by tuning the gel formation at body temperature, the SMH would be a promising tool for transcatheter arterial embolization. + and i-motif sensitive to H+. When the hydrogel meets its target, K+ or low pH, the transient shape may be disturbed to reverse the eternal shape. Of interest, due to the polymer chains’ entanglement and the related fixed distance between two types of networks, after the addition of factor to clear the target, the shape will again fall into the transient shape.Shape memory hydrogels (SMHs) possess the properties of shape memory transformation from temporary shape to eternal shape upon exposure to the stimuli, which endow them great potential in tissue engineering and drug delivery . The SMH3O4-based magnetic nanocomposite hydrogel system by loading anticancer drug 5-fluorouracil for colon and rectal administration. Through external magnetic field, the magnetic nanocomposite hydrogel could release drug in target sites.As the development of nanoscience, in recent years, hydrogel nanocomposite systems, such as magnetic , electroin-vivo and in-vitro  are incorporated, doped, or chemically modified in the polymer network to form nanocomposite hydrogel which can be used as scaffolds supporting for cell growth both in-vitro . Xu et ain-vitro . Rakhshin vitro and in vivo by the hydrogel. Based on a smart hydrogel system, in vitro and in diabetic mouse models. Glucose is a key biomedical analyte, which plays a crucial role in physiological metabolism. Abnormal glucose levels are associated with diabetes and hypoglycemia. Hence, glucose is closely related to body function, and sustained glucose monitoring promotes the strict control of blood glucose in diabetic . EspeciaLu et al. (2018) designed a pure DNA hydrogel based on triplex DNA structures with protonated cytosine–guanine–cytosine (C-G•C+) and thymine–adenine–thymine (T-A•T) to set the pH transition point to 5.0 and 7.0, respectively. The highly tunable pH responsiveness made it attractive in biomedical applications.One of the most outstanding intelligent hydrogels is the pH-responsive hydrogels due to significant variations of pH at different sites under normal and pathological conditions. Several pH-responsive polymers, including DNA, chitosan, and poly (methacrylic acid) (PMAA), have been extensively recommended and used for local controlled drug delivery system. When pH altered following the disease’s occurrence, the hydrogels can trigger disease-controlled drug release. After triggered by pH changing, hydrogels have a gel–sol conversion which is beneficial for drugs encapsulation at gel status and effective frameworks clearance after hydrogel degradation. Until now, several natural polymers like cellulose, hyaluronic acid, guar gum, and chitosan, owing to the presence of abundant ionic groups in their network, have been employed to synthesize pH-responsive hydrogels. Some functional groups like amide, sulfate, phosphate, and carboxylate could be also introduced to alter the electrochemical properties . FunctioZhao Z. et al. (2020) used an injectable MMPs sensitive hydrogel that payload temozolomide (TMZ) and O6-benzylamine (BG) for the clearance of residual TMZ-resistant gliomas after surgery. When the concentration of MMPs enzymes is high, hydrogels could release the TMZ and BG simultaneously when TMZ kills the residual glioma cell under the guarantee by BG. The result is demonstrated to be good in localized drug codelivery for residual glioma treatment. The hydrogel embedded in the arthritic joint with lots of therapeutic agents and enzyme sensing agents will disassemble when enzyme appears in the inflammatory microenvironments. Instead of providing prolonged drug release, enzyme-sensitive hydrogels are capable to supply drug one time when necessary, thereby improving therapeutic efficacy . MMPs are upregulated in varieties of diseases, attracting attention on the design of MMP-responsive hydrogel for drug delivery . For insefficacy .2−), singlet oxygen (1O2), hydroxyl radical (·OH), peroxynitrite (ONOO−), and hypochlorite (OCl−), play important roles in biological process. However, abnormal metabolism elevates ROS level significantly in many diseases  designed a biodegradable injectable hydrogel composed of PEG, ROS-responsive l-methionine (Me), and dextro-1-methyl tryptophan (D-1MT), loading with anti-programed cell death-ligand 1 (aPD-L1) effectively. The encapsulated aPD-L1 and D-1MT could be released from the intelligent hydrogels slowly according to the trigger of environmental ROS that will result in the reduction of ROS level and enhanced antitumor efficacy.ROS, such as superoxide , but in practical biomedical applications, more work need to be done. We demand a unity to monitor, to sense, and to stimulate with the feedback loop system to smartly control the drug release rate, or even release the reverse drug to terminate the therapy when disease changes. The constructure of such unity can draw experience from cascaded assembly or cascaded enzymatic reaction. Third, as the emerging of a lot of new hydrogels as the development of nanoscience and pharmacy, by incorporation with functional nanomaterial and emerging functional peptide and DNA, the hydrogel will move beyond the present stimuli target, even alter the present hydrogel designed mechanism. As for the high specificity of functional peptide and DNA, we foresee that the hydrogel could be designed specifically to personalized individuals.The unique properties of hydrogels make it a wonderful platform for biomedical applications, although there are still varieties of obstacles to overcome. First, hydrogels composed of different molecules possess merits of their own; the natural polymer is biocompatible with low toxicity but weak, while the synthetic polymer is often cell toxic but strong. How to mingle the advantages together is a hard question. The mechanism of multipolymer network and shape memory hydrogel can provide some suggestions for further advancing. Second, the contemporary hydrogels are mainly designed for a single purpose , Xiamen Youth Innovation Fund Project (3502Z20206064), Education Scientific Research Project for Young and Middle-aged Teachers in Fujian Province (JAT190989).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Although combined antiretroviral therapy has substantially improved the prognosis of people living with HIV (PLHIV), mortality remains higher compared to the general population, mainly due to higher prevalence of non-HIV-related comorbidities, including cardiovascular diseases (CVD). We assessed the prevalence of CVD risk and its contributing factors in adult PLHIV versus general population controls in Greece.Cross-sectional comparison of PLHIV  versus general population controls .All HIV-infected adults with ≥1 measurement of interest  between 2012–2014 and all EMENO participants (2014–2016) were included. Ten-year total CVD risk was estimated using the Framingham (FRS) or the Systematic Coronary Risk Evaluation (SCORE) equations.5839 PLHIV  and 4820 controls  were included. Adjusting for age, sex and origin, PLHIV were more likely to be current smokers (adjusted OR:1.53 [95% CI:1.35–1.74]) and dyslipidemic , less likely to be obese  FRS but with greater odds of high (≥5%) SCORE (aOR:1.55 [1.05–2.30]). Further adjustment for educational level, anti-HCV positivity and BMI showed higher prevalence of hypertension in PLHIV.Despite the relative absence of obesity, PLHIV have higher prevalence of traditional CVD risk factors and higher risk of fatal CVD compared to general population. Regular screening and early management of CVD risk factors in PLHIV should be of high priority for CVD prevention. Mortality among people living with HIV (PLHIV) has decreased substantially since the introduction of combined antiretroviral therapy (cART). Mortality rates, however, remain higher in PLHIV compared to the general population –3. The dSmoking, a modifiable risk factor that is strongly associated with CVD, is highly prevalent among PLHIV ,14; On tThe aim of this study was to estimate i) the prevalence of specific non-AIDS related comorbidities and established CVD risk factors , ii) the total CVD risk estimated using the 10-year Framingham risk score (FRS) or the European Systematic Coronary Risk Evaluation (SCORE) in adult PLHIV in comparison to general population controls in Greece. For this purpose, data from a large ongoing Greek cohort of HIV-infected individuals, were compared cross-sectionally with data from a recent health examination survey in a representative sample of the general adult population in Greece.http://en.uoa.gr/), the HCIDC IRB (http://www.keelpno.gr/en-us/home.aspx) and the National Organization of Medicines (http://www.eof.gr/web/guest/home).Data for the HIV-infected individuals were derived from the “Athens Multicenter AIDS Cohort Study” (AMACS). AMACS is a collaborative, ongoing, population-based cohort study, initiated in 1996.Currently, 14 out of the 18main clinics that follow PLHIV in Greece, participate in the study. Data are provided by the clinics after de-identification. The study has been approved by the Athens University IRB  and the Hellenic Data Protection Authority (www.dpa.gr).Data for the general population were derived from the health examination survey “National Survey of Morbidity and Risk Factors” (EMENO). EMENO is a population-based cross-sectional survey aiming to include 6000 adults aged ≥18 years. The study design has been described in detail elsewhere . BrieflyAll AMACS participants who had at least one measurement of interest  between 2012–2014 and aged ≥18 years at the selected visit, were included in the current study. If more than one visit was available within 2012–2014, the most recent was selected.All EMENO participants who had at least one measurement of interest were included in the current study. HIV positive individuals were excluded from all analyses.Hypertension was defined as systolic blood pressure ≥140 mmHg and/or diastolic blood pressure ≥90 mmHg, or taking antihypertensive medication .Diabetes2 was considered indicative of obesity. AMACS participants were classified as infected with hepatitis C virus (HCV) if they had a positive anti-HCV test or a detectable HCV-RNA in their medical records and as infected with hepatitis B virus (HBV) if they had a positive HBsAg. EMENO participants who provided signed informed consent had been screened using anti-HCV and HBsAg tests.Dyslipidemia was defined as elevated total cholesterol ≥240 mg/dl(6.21 mmol/l), and/or decreased high-density lipoprotein (HDL)-cholesterol ≤35mg/dl(0.91 mmol/l), and/or elevated triglycerides ≥200 mg/dl(5.17 mmol/l), or taking antilipidemic medications . BMI wasThe 10-year total risk of fatal and non-fatal CVD was estimated using the Framingham risk score (FRS)  and the Sampling weights, being the reciprocal of the selection probabilities, multiplied with post-stratification weights based on 2011 census were applied to EMENO data to allow for differences in age and sex distribution between the final sample and the adult Greek population. To adjust for non-response, as a sub-sample of the interviewed individuals participated in the physical examination and provided blood samples, the inverse probability weighting method was applied. Weights were estimated through multivariable logistic regression.10 scale) and diagnoses of hypertension, diabetes or dyslipidemia. Completely observed variables included in the model were age, country of origin (Greek vs. other) and AIDS status. Ten imputed datasets were created using the jomo package . Most participants in both populations were of Greek/Western Europe (WE) origin, although a larger percentage in the AMACS cohort was from other regions. HBV or HCV co-infection was significantly more prevalent among HIV-infected individuals compared to the general population.Based on complete cases data, crude (unadjusted) prevalence of hypertension, diabetes, obesity and high FRS or SCORE were significantly higher in the control group. On the contrary, prevalence of dyslipidemia and current smoking were significantly higher in HIV-infected individuals compared to the general population . HoweverAdjusted for age, sex and origin, HIV-infected patients were more likely to be current smokers, dyslipidemic, and have a high SCORE, and less likely to be obese; there were no significant differences between the two groups in the odds of hypertension, diabetes or high FRS , model 1The predicted marginal prevalence of comorbidities and risk factors adjusted for age, sex and origin are presented in Results from the sensitivity analyses were in line with those of the main analysis although significance levels were different due to the different number of observations contributing in each sensitivity analysis .In this work, we cross-sectionally compared the prevalence of CVD risk factors and the estimated total CVD risk between AMACS and EMENO participants. AMACS includes the majority of the HIV-infected adults living in Greece, and it is representative of the PLHIV on care . EMENO cSmoking constitutes one of the strongest modifiable CVD risk factors. In this study, current smoking was high in both the general  and the HIV-infected population , but still significantly higher in the latter. Most previous studies have reported higher frequency of current smoking in PLHIV ,14 with In line with our results, most previous studies reported lower BMI in PLHIV than in HIV-uninfected counterparts ,12. SeveThe effect of HIV infection or cART on dyslipidemia is well recognized ,22,23. IAs traditional risk factors are quite prevalent in PLHIV, accurate CVD risk stratification is very important. FRS and the European SCORE are two commonly used models for risk stratification. Other models, like the D:A:D (Data Collection on Adverse Events of Anti-HIV Drugs) equations, have also been developed to incorporate HIV-specific variables . HoweverIn this study we estimated and compared FRS and SCORE CVD risk estimation between HIV-infected and the general population, but the results of the two score equations were not compatible. The prevalence of high FRS (≥ 20%) or the 10-year FRS risk score did not differ between the two groups in the basic model adjusted for demographics. On the contrary, the prevalence of high SCORE (≥5%) or10-year SCORE risk was significantly higher in HIV-infected people. Previous studies have reported contradictory results when comparing FRS risk in HIV-infected and uninfected individuals, with some reporting higher , some siOur study has some limitations. In EMENO, standardized equipment and operating procedures were used across the country to evaluate CVD risk factors. In AMACS, data were extracted from patients’ files; some risk factors, anti-hypertensive treatment, diabetes and anti-diabetic treatment, may have been missing or recorded incorrectly. This would make harder to reveal the true differences between the two compared groups, with most probable underestimation of CVD risk factors in PLHIV. In AMACS, hypertension, obesity and to a lesser extent BMI had several missing values . We applied the MI method to impute missing data, but its validity depends on the accuracy of the imputing model. To increase the accuracy, we used many variables (auxiliary ones included) in the imputation model. In addition, a set of sensitivity analyses were carried out and all obtained results were in line with those of the main analysis, albeit with varying significance levels due to the different number of observations contributing in each analysis. AMACS and EMENO participants differed in the age, sex and, to a lesser extent, country of origin distribution. All analyses were adjusted for these factors. We also adjusted for other important variables, such as educational level (an indicator of socio-economic status) and anti-HCV positivity. However, we did not have data on poverty, diet and other behavioural variables. Thus, confounding of other unmeasured variables cannot be excluded in such cross-sectional observational studies.We estimated and compared the prevalence of hypertension, dyslipidemia, diabetes, current smoking, obesity and total CVD risk calculated by FRS or SCORE equations in adult PLHIV and in the general adult population living in Greece. Our results showed that, although PLHIV are less likely to be obese, they are more likely to be dyslipidemic, current smokers and to have high SCORE CVD risk. There is evidence that, for a given BMI, PLHIV are more likely to be hypertensive and, possibly even, diabetics. Health care providers should regularly screen HIV-infected persons for established CVD risk factors, even in the absence of obesity; smoking cessation campaigns are very important in this group. Assessment and management of established CVD risk factors are of high priority for HIV-infected patients’ care, potentially leading to improved health outcomes.


Humans process faces by using a network of face-selective regions distributed across the brain. Neuropsychological patient studies demonstrate that focal damage to nodes in this network can impair face recognition, but such patients are rare. We approximated the effects of damage to the face network in neurologically normal human participants by using theta burst transcranial magnetic stimulation (TBS). Multi-echo functional magnetic resonance imaging (fMRI) resting-state data were collected pre- and post-TBS delivery over the face-selective right superior temporal sulcus (rpSTS), or a control site in the right motor cortex. Results showed that TBS delivered over the rpSTS reduced resting-state connectivity across the extended face processing network. This connectivity reduction was observed not only between the rpSTS and other face-selective areas, but also between nonstimulated face-selective areas across the ventral, medial, and lateral brain surfaces . TBS delivered over the motor cortex did not produce significant changes in resting-state connectivity across the face processing network. These results demonstrate that, even without task-induced fMRI signal changes, disrupting a single node in a brain network can decrease the functional connectivity between nodes in that network that have not been directly stimulated. Human behavior is dependent on brain networks that perform different cognitive functions. We combined theta burst transcranial magnetic stimulation (TBS) with resting-state fMRI to study the face processing network. Disruption of the face-selective right posterior superior temporal sulcus (rpSTS) reduced fMRI connectivity across the face network. This impairment in connectivity was observed not only between the rpSTS and other face-selective areas, but also between nonstimulated face-selective areas on the ventral and medial brain surfaces . Thus, combined TBS/fMRI can be used to approximate and measure the effects of focal brain damage on brain networks, and suggests such an approach may be useful for mapping intrinsic network organization. The ubiquitous presence of faces in our environment makes them a salient stimulus for studying the cognitive functions of the human brain. Functional magnetic resonance imaging studies have identified regions across the brain that exhibit a stronger neural response to faces than to objects  , bilateral FFA, bilateral OFA, and bilateral amygdala. The right posterior superior temporal sulcus (rpSTS) ROIs were face-selective voxels in gray matter that were also within an 18-mm-diameter sphere centered on the stimulation site. This added restriction means the voxels in the rpSTS ROI were likely to have been directly affected by TBS stimulation. The stimulation site was defined using the same functional localizer scan, but collected on a preceding session. The right-hand motor stimulation site was anatomically defined using an anatomical scan from a preceding session. ROIs for the bilateral hand areas were manually drawn following the gray matter anatomy of the hand knob in the precentral sulcus. The locations for the ROIs are shown in Z transformed. Since the ROIs are a priori selected from a network where we expect to see disruption . Also, there is still not a full understanding of all factors that modulate TBS effect size, including how much spatial precision matters, whether different brain regions are more sensitive to TBS than others, and the causes of intersubject variability in TBS sensitivity. Specifically in this study, we note our poststimulation observation of spatial variation between the hand motor ROI and the hand motor stimulation site . This vaIn this study, we could not directly test whether TBS to the rpSTS caused alterations in face processing because we cannot both collect resting-state fMRI and also present face-selective stimuli during the post-TBS time window when the TBS effect is observable. However, in previous studies using face-selective stimulus that evoked BOLD measures and the same TBS stimulation protocol as used here, changes were reported in responses to face stimuli , with no major medical illness, no neurological or psychiatric illness, no serious head injury, no learning disability, no history of drug or alcohol abuse in the past 3 months, no prescription drugs or supplements affecting brain function, no serious vision or hearing problems and with normal, or corrected-to-normal, vision gave informed consent as directed by the National Institutes of Health (NIH) Institutional Review Board . One participant was excluded due to high motion .Seventeen right-handed participants  or the right primary motor cortex hand knob (rMotor). Stimulation site order was balanced across participants. The two TBS sessions were 7–182 days apart (median = 23). All the data presented were collected during these two TBS sessions.Stimulation sites were localized using individual structural and functional images collected during an fMRI localizer task that each participant completed prior to the combined TBS/fMRI sessions. For the independent localizer runs used to identify face-selective ROIs, participants viewed 3-sec video clips of faces, objects, and scrambled objects. There were 60 movie clips for each category in which distinct exemplars appeared multiple times. Movies of faces were filmed on a black background, and framed close-up to reveal only the faces of seven children as they danced or played with toys or adults (who were out of frame). Fifteen different moving objects were selected that minimized any suggestion of animacy of the object itself or of a hidden actor pushing the object . Within each block, stimuli were randomly selected from within the entire set for that stimulus category. This meant that the same actor or object could appear within the same block. These stimuli were used in a previous fMRI study of face perception . In addition, high-resolution MPRAGE anatomical scans  were acquired to anatomically localize functional activations and register functional data between sessions.Before each MRI session, the stimulation site (either rpSTS or rMotor) was located using the Brainsight TMS-MRI coregistration system (Rogue Research), the information was extracted from the subject-specific localizer scans  was used to deliver the TBS via a figure-eight coil with a wing diameter of 70 mm. TBS was delivered at an intensity of 80% of active motor threshold or 30% of machine output (whichever was higher) over each participant’s functionally localized rpSTS or the right motor hand knob. We used a continuous TBS paradigm  was larger for 49 of the second runs versus first runs. The average across runs of median delta motion difference between run pairs was 0.01 larger in the second runs. The average median delta motion was 0.05 so this was a 19% increase in median motion. There was only a 7% difference in median delta motion for the first and third runs, which were used in these analyses. While these are subtle differences, the systematic nature of this difference added a confound that made these data difficult to interpret, so the second runs were excluded from all analyses.Data were processed using AFNI Cox, . For eachttps://github.com/handwerkerd/MEICA_FaceNetworkTMS. We will refer to the output of the full MEICA algorithm as “denoised” data. The denoised data will be used for all analyses in this manuscript.The multi-echo data were then denoised using the MEICA algorithm. MEICA uses the expected properties of signal changes across multiple echo times to identify and remove signal fluctuations that are unlikely to reflect the blood oxygenation differences that are central to fMRI. By doing this, MEICA has been shown to increase the signal-to-noise ratio and remove data artifacts . Censored volumes per 300 volume run were mean = 2, median = 0, and maximum = 22. The motion parameters and their first derivatives were regressed from the time series. In the same step, signals from a cerebral spinal fluid (CSF) ROI and a white matter ROI that excluded voxels within eight voxels of either stimulation site were averaged and regressed from the data. The resting-state data were bandpass filtered (0.01–0.1 Hz) with censoring, and the data were spatially smoothed with a 5-mm full-width-half-maximum Gaussian kernel.The statistical tests visualized in For whole-brain group maps, the within-subject aligned anatomical volumes from each subject were registered to a standard MNI space and then nonlinearly, iteratively warped to each other to make a within-study anatomical template .We thank Nancy Kanwisher for providing face localizer stimuli. We thank Shruti Japee for reviewing functional localizer results and for identifying functional localizer scans from these volunteers that were collected as part of other datasets.https://doi.org/10.1162/netn_a_00145.Supporting Information for this article is available at Daniel A Handwerker: Conceptualization; Data curation; Formal analysis; Investigation; Methodology; Project administration; Software; Supervision; Validation; Visualization; Writing - Original Draft; Writing - Review & Editing. Geena Ianni: Data curation; Formal analysis; Investigation; Writing - Review & Editing; Validation. Benjamin Gutierrez: Data curation; Formal analysis; Investigation; Software. Vinai Roopchansingh: Methodology; Resources; Software. Javier Gonzalez-Castillo: Methodology; Software; Visualization; Writing - Review & Editing. Gang Chen: Formal analysis; Software; Writing - Review & Editing. Peter A Bandettini: Conceptualization; Funding acquisition; Methodology; Project administration; Resources; Supervision; Writing - Review & Editing. Leslie G Ungerleider: Conceptualization; Funding acquisition; Methodology; Project administration; Resources; Supervision; Writing - Review & Editing. David Pitcher: Conceptualization; Investigation; Methodology; Project administration; Resources; Supervision; Writing - Original Draft; Writing - Review & Editing.http://dx.doi.org/10.13039/100000025), Award ID: ZIAMH002783. Leslie G. Ungerleider, National Institute of Mental Health (http://dx.doi.org/org/10.13039/100000025), Award ID: ZIAMH002918. David Pitcher, Biotechnology and Biological Sciences Research Council (http://dx.doi.org/10.13039/501100000268), Award ID: BB/P006981/1.Peter A. Bandettini, National Institute of Mental Health (Click here for additional data file.


Area-level measures are often used to approximate socioeconomic status (SES) when individual-level data are not available. However, no national studies have examined the validity of these measures in approximating individual-level SES.Data came from ~ 3,471,000 participants in the Mortality Disparities in American Communities study, which links data from 2008 American Community Survey to National Death Index (through 2015). We calculated correlations, specificity, sensitivity, and odds ratios to summarize the concordance between individual-, census tract-, and county-level SES indicators . We estimated the association between each SES measure and mortality to illustrate the implications of misclassification for estimates of the SES-mortality association.r = 0.232; odds ratio [OR] = 2.284) or counties  whose median household income was above the US median. Across indicators, mortality was higher among low-SES groups . Compared to county-level, census tract-level measures more closely approximated individual-level associations with mortality.Participants with high individual-level SES were more likely than other participants to live in high-SES areas. For example, individuals with high household incomes were more likely to live in census tracts (Moderate agreement emerged among binary indicators of SES across individual, census tract, and county levels, with increased precision for census tract compared to county measures when approximating individual-level values. When area level measures were used as proxies for individual SES, the SES-mortality associations were systematically underestimated. Studies using area-level SES proxies should use caution when selecting, analyzing, and interpreting associations with health outcomes. Socioeconomic status (SES) is an individual’s relative position within a social hierarchy reflecting their ability to consume resources . In publHowever, SES data are sensitive. In many population-based datasets, individual-level SES is not available. Furthermore, when studies request this information, participants may decline to respond or exaggerate their SES , 10. To Area-level SES measures are used in at least two ways in public health research: (1) as proxies for individual-level SES –19  study, which includes data for more than 4.5 million people in the US. We sought to illustrate the impact of misclassification when area-level characteristics are used to estimate health disparities by SES.https://www.census.gov/mdac.html). The construction of MDAC involved linking the data from the 2008 ACS to mortality data obtained through the use of the National Death Index (NDI) and other sources for 2008 to 2015. Only ACS records which have the necessary information available to match to NDI records are maintained in the MDAC study’s official research database. The sampling frame for ACS is derived from the Census Bureau’s Master Address File, a continuously updated file of the addresses of known living quarters (both regular housing units and group quarters) in the US. The sampling scheme for the 2008 ACS is a complex stratified sample of the US population conducted on a yearly basis. When 5 years of ACS data are combined, they allow robust SES attribute estimates at the block, census tract, and county level. These estimates have replaced population estimates that previously came from the Decennial Census long form. Further details about the design of ACS are available in Chapter 4 of the ACS Design and Methodology document (https://www.census.gov/programs-surveys/acs/methodology/design-and-methodology.html).Data were obtained from MDAC, a project by the US Census Bureau, Centers for Disease Control, and National Institutes of Health to facilitate research on mortality disparities by social and economic characteristics  linked to a census tract  or county . The individual-level MDAC records were linked to 5-year estimates of area-level characteristics from ACS . MDAC data came from participants in 3242 US counties and 73,057 census tracts in the USA.For MDAC purposes, ACS weights were reweighted by age, sex, race, Hispanic status, and state to the US population to account for the ACS records in MDAC which were not successfully linked to NDI. For the purposes of this paper, analyses were restricted to persons of age 18 years or older . We used these binary variables of individual- and area-level SES characteristic to examine high- versus low-risk groups for adverse health outcomes.We gathered widely used characteristics of SES , 30, 31 We dichotomized each participant’s individual-level household income compared to the US median household income. In addition, we dichotomized area-level (census tract and county) indicators of median household income compared to US median.We developed individual-level household poverty indicators based on whether each participant’s household was below 100% of the federal poverty level . In addWe developed individual-level educational indicators based on whether each participant (a) had a high school degree, restricted to participants who were 18+ years old, and (b) had a 4-year college degree, restricted to participants 25+ years old. In addition, we dichotomized area-level indicators of percentage of relevant populations that had reached each educational milestone compared to US median.We developed individual-level employment/occupational indicators based on whether each participant was (a) unemployed versus employed, restricted to participants who were in the workforce, and (b) employed in a blue-collar industry   versus oWe developed individual-level indicators of other, less frequently used markers of SES: whether participants owned the home they lived in and whether they were born in a different country. In addition, we dichotomized area-level indicators of the percentage of the population in each category compared to the US median.Individual-level mortality data indicated whether each MDAC participant had died from any cause over the 7-year follow-up .We calculated each SES characteristic’s proportion and standard deviation to describe the distribution across socioecological levels  with mortality.p values in the tables.Analyses were conducted in SAS version 9.3 . Individual-level observations were weighted to account for non-equal probability of selection into ACS/MDAC and to increase generalizability. Below, we present unweighted frequencies and weighted proportions. Models included a control variable for county population (measured in 1000s of population). Because of the exceptionally large sample size, we generally do not present confidence intervals or SD) of SES characteristics for individuals, census tracts, and counties appear in Table The proportion and standard deviation (p < .0001). For example, having an individual-level household income above the median for US households was correlated with living in (1) a census tract that had a median household income above the median for the US census tracts (Spearman’s r = .232) and (2) a county that had a median household income above the median for the US counties (Spearman’s r = .157). The correlations between individual- and census tract-level characteristics ranged from 0.048 (for unemployment) to 0.263 (for foreign born), and the correlations between individual- and county-level characteristics ranged from 0.028 (for unemployment) to 0.245 (for foreign born).Correlations between individual- and area-level SES characteristics were small . For example, participants were more likely to have a household income above the US median if they also lived in a census tract (odds ratio [OR] = 2.284) or county (OR = 1.325) whose median household income was above the US median, compared to participants living in low-income census tracts or counties. For all individual-level SES characteristics, the relationship with the corresponding census tract-level characteristic was stronger than that observed for the corresponding county-level characteristic.Individual-level SES characteristics were closely linked to census tract- and county-level characteristics (Table p < .0001). Across all indicators, the association was stronger for individual-level measures compared to the census tract- or county-level measures. For example, participants with a household income above the US median were less likely to die of any cause over the 7-year follow-up period than were other participants . This protective relationship was also seen but attenuated when comparing people living in high-income versus low-income census tracts  or counties .Mortality was associated with all SES characteristics across all socioecological levels , while employment/occupation indicators  performed worse. Perhaps this reflects the fact that area-level unemployment rates are low (0% to < 20%), but experiencing individual-level unemployment has profound social and economic consequences, making their implications quite different. This finding provides additional guidance for researchers: Using indicators such as household income (perhaps the most common SES indicator) or percent foreign born will more precisely approximate individual-level values than employment/occupation indicators. In addition, we also found that individual- and area-level associations with mortality varied in direction for employment/occupation Table . One preOverall, area-level SES indicators had limitations as proxies for individual-level SES . StudiesStudy strengths include the use of a high-quality dataset with exceptionally large sample size and national geographic scope. Millions of participants were successfully geocoded to census tracts and/or counties, allowing us to examine SES measures across multiple socioecological levels. We analyzed some of the most commonly used indicators of SES related to income, education, and occupation. A limitation was that, for data stability, we used 5-year averages for the area-level SES measures; 1-year indicators may be more relevant for comparisons to individual-level SES. Self-reported measures of SES may also be biased . The indStudies examining associations between SES and health face many challenges, most importantly, the frequent unavailability of individual-level data on SES. While using area-level measures of SES as proxies for individual-level SES may be an attractive solution, the current study shows that the validity of these indicators is suboptimal. Considerable misclassification was seen among individual-, census tract-, and county-level indicators of SES. The magnitude of association with mortality was attenuated with area-level data, and in the case of employment/occupation, the direction of associations was opposite that for individual-level data. For studies that cannot measure individual-level SES, the best options may be use of area-level SES (1) measured at smaller geographic units and (2) based on indicators that perform well across socioecological levels, e.g., household income. Importantly, area-level SES provides useful contextual information relevant to health beyond individual-level SES. Additional research is needed to understand the validity of area-level SES proxies across demographic subgroups and health outcomes, and to parse the role of individual- versus area-level SES in public health.


Neurodegenerative diseases including Alzheimer's disease and Parkinson's disease are aging-associated diseases with irreversible damage of brain tissue. Oxidative stress is commonly detected in neurodegenerative diseases and related to neuronal injury and pathological progress. Exosome, one of the extracellular vesicles, is demonstrated to carry microRNAs (miRNAs) and build up a cell-cell communication in neurons. Recent research has found that exosomal miRNAs regulate the activity of multiple physiological pathways, including the oxidative stress response, in neurodegenerative diseases. Here, we review the role of exosomal miRNAs and oxidative stress in neurodegenerative diseases. Firstly, we explore the relationship between oxidative stress and neurodegenerative diseases. Secondly, we introduce the characteristics of exosomes and roles of exosome-related miRNAs. Thirdly, we summarized the crosstalk between exosomal miRNAs and oxidative stress in neurodegenerative diseases. Fourthly, we discuss the potential of exosomes to be a biomarker in neurodegenerative diseases. Finally, we summarize the advantages of exosome-based delivery and present situation of research on exosome-based delivery of therapeutic miRNA. Our work is aimed at probing and reinforcing the recognition of the pathomechanism of neurodegenerative diseases and providing the basis for novel strategies of clinical diagnosis and treatment. The incidence of neurodegenerative diseases, which include Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), and amyotrophic lateral sclerosis (ALS), has been shooting up due to the extended lifespan and environment pollution. Neurodegenerative diseases are a group of refractory diseases and have loaded a huge medical, social, and economic burden to the world. Despite the massive efforts into the pathological mechanisms and therapeutic strategies of neurodegenerative diseases, few sufficiently effective treatments have been generated thus far . Most neExosomes are extracellular vesicles (EVs) secreted by a variety of cells and carry cargos including protein, lipid, and noncoding RNA (ncRNA) . Following the release, exosomes will transfer to specific targets such as immune cells or the central nervous system (CNS) to exert pleiotropic effects , 9. In tin vivo. In a normal situation, the proper ROS level is thought to be necessary to maintain the activation of certain signaling pathways , stimulate the cell proliferation, and regulate the cell metabolism. However, when the production of ROS seriously exceeds the scavenging capacity, the ROS will accumulate and have an effect on cells, leading to DNA [nuclear and mitochondria DNA (mtDNA)] damage, protein misfolding, and chromosome instability, among others , 6717, 6RN7SL1 RNA in stromal-derived exosomes can stimulate a tumor-promoting pathway within a subset of breast cancer cells, which are primarily basal/triple-negative breast cancers [How exosomes are recognized and endocytosed by specific cells is an important aspect to be investigated. Although there is still no consensus concerning the main pathway by which EVs or a given EV subtype deliver content in the cytosol of specific acceptor cells, researchers have indeed found some evidence to support the specificity of exosome uptake. For example, exosomes released by cortical neurons upon synaptic activation bind exclusively to other neurons, not to glial cells . Moreove cancers . The molRecently, miRNAs have been identified in exosomes, which can be taken up by neighboring or distant cells and subsequently modulate recipient cells. miRNAs are a class of 17–24 nt small, noncodingRNAs, which mediate posttranscriptional gene silencing by binding to the 30-untranslated region (UTR) or open reading frame (ORF) region of target mRNAs . There i(1) Potential New Method for Gene Therapy. Exosome is capable to transport functional miRNAs, and this endogenic carrier inspired people to replace virus-based gene therapy [ therapy . Compare therapy . Moreove therapy . miRNA e therapy , 91. Int(2) New Way of Intercellular Communication. The most well-known intercellular communication mechanisms are chemical receptor-mediated event [ed event . Exosomeed event . For insed event . In addied event . In ligh(3) Biomarker for Diagnosis. In neurodegenerative diseases, pathological changes occur several years before the onset of symptoms; thus, predictor for detection of diseases in early stage is always important but challenging. Concerning that exosomes have been recognized as nature carriers of miRNAs, its capability to cross the blood-brain barrier and miRNA expression altered in different neurodegenerative diseases; it is reasonable to infer exosomal miRNAs in peripheral blood change in different diseases. Exosomal miRNAs from blood sample of PD and AD patients were analyzed [analyzed , 97. Preanalyzed , 99. In As mentioned above, both oxidative stress and exosome-derived miRNAs are closely involved in neurodegenerative diseases. Intriguingly, oxidative stress can affect the expression levels of numerous miRNAs, and conversely, miRNAs are able to regulate manifold genes involved in the oxidative stress response as well . AccordimiR-34a, a tumor suppressor transcript, is highly expressed in autopsied brain tissue of AD patients and has a strong pertinence to the pathogenesis of a cognitive disorder. During AD pathogenesis, miR-34a facilitates the amyloid precursor protein (APP) amyloidogenic processing, while miR-34a knockdown can inversely mitigate the APP accumulation in brain tissue , 101. OnmiR-141-3p, a potential serum plasma biomarker for Alzheimer's disease, has been reported to be observed with low concentrations in the plasma exosomes of Alzheimer's disease patients . Howeverβ-induced oxidative stress. This effect is probably due to downregulation of the expression of beta-site amyloid precursor protein cleaving enzyme 1 (BACE1) [miR-125b-5p is one of the most abundant microRNAs in the brain  and is p (BACE1) . Another (BACE1) . The aboStudies in recent years have found that miR-34a appears to act in the neurotoxic pathways of PD-associated neurotoxins such as paraquat, rotenone, and 6-hydroxydopamine (6-OHDA). The mood stabilizing drug lithium chloride protects SH-SY5Y cells from paraquat-induced neurotoxicity by activating the antioxidant protein expression regulator nuclear factor 2-related factor 2 (NRF2) and miR-34a inhibition , 113. SiMiR-137 is a highly conserved miRNA. It is enriched in Drosophila's brain and is reported upregulated in early PD flies . Similarα-synuclein protein, thereby alleviating disease progression in PD [Let-7 is a series of miRNAs which was first discovered in C. elegans and highly conserved across animal species. Disorders of Let-7 can lead to many diseases including neurodegenerative diseases, diabetes, and cancer . Let-7 won in PD .Compared to AD and PD, relatively few studies have targeted the interaction between microRNAs and oxidative stress in ALS and HD. Downregulation of miR-124 expression is observed in both mouse models of HD and in the brains of human HD sufferers . Cyclin Rizzuti et al. observed miR-34a expression downregulated in vitro model of ALS and confirmed the significant role of miR-34a in neurodegeneration and ALS . SirtuinmiR-142-5p is a member of miR-142 family microRNAs. The decreased regulation of miR-142-5p in the CSF of ALS patients was reported . Wang etin vitro [Cell-derived active substances that can steadily be detected in cells, body fluids, or tissues are called molecular markers. Exosomal miRNAs in the body fluids of subjects can exist stably due to the fact that they are free from the degradation by ribonuclease (RNase), and further, they can be stably stored for 48 h at 4°C in vitro . These cin vitro , 138–147Liu et al. identified a lower expression of exosomal miR-193b in the blood and cerebrospinal fluid (CSF) of AD patients compared with controls, indicating the potential of exosomal miR-193b as a unique and noninvasive biomarker for AD . MoreoveGui et al. discovered that in the early stages of PD, there were 27 exosomal miRNAs derived from CSF of patients presenting with abnormal expression, among which miR-153, miR-409-3p, miR-10a-5p, and Let-7g-3p were significantly increased, while miR-1 and miR-19b-3p were significantly decreased, indicating their potential values as biomarkers for early diagnosis of PD . In addiHD is a hereditary and slow-progressing neurodegenerative diseases. Diagnosis mainly relies on family genetic history and genetic testing. Although HD is an untreatable disease, biomarkers remain important to patients by providing early diagnostic clues or reflecting disease progression. Related researches found elevated levels of miR-100-5p and decreased levels of miR-330-3p and miR-641 correlate with total functional capacity in HD patients . GaughwiALS is the most common and severe form of motor neuron disease in adults. The mechanism by which ALS occurs is currently unknown, and the lack of specific biomarkers makes clinical diagnosis difficult. Increasing evidence suggests that RNA metabolism including miRNAs may play an important role in the pathophysiological process of ALS. A global downregulation of miRNAs is a frequent molecular denominator for multiple forms of human ALS . De FeliClinicalTrials.gov Identifier: NCT04202770). Transcranial focused ultrasound administered immediately prior to exosome treatment is in an attempt to enhance the deployment of exosomes to the hippocampus of patients.The BBB has always been an impregnable obstacle to the therapeutic development of CNS disorders, hindering the clinical application of many promising agents . As mentPTEN to hinder its function, which activates Akt and Bcl-2 and suppresses Bad, Bax, and caspase-3, ultimately inhibiting cell apoptosis [Exosome-based delivery of therapeutic miRNA for CNS diseases has become a hot research topic. Experimental studies have indicated that MSC-derived exosomes transferring functional miRNAs  to neurons can promote neural plasticity and functional recovery after stroke –162. Respoptosis . Similarpoptosis .To date, a few preclinical studies have been carried out on the use of exosomal miRNA in the treatment of neurodegenerative disease. Lee et al.  transfecNotably, although exosomes hold great promise as rational vehicles for RNA delivery, in particular miRNAs and/or siRNAs, the loading efficiency is limited. Recently, Li et al.  inventedIn the future, more clinical studies verifying the clinical efficacy of exosome-based drug delivery systems as well as oxidative stress-associated exosomal miRNAs for neurodegenerative diseases and more preclinical studies exploring better methods for loading therapeutic miRNAs into exosomes are warranted.In the past decades since exosomes and miRNAs were found in neurons, researchers have tried to explain cell-cell communication in CNS with an exosome cargo system. And through the cell-cell communication system, exosomes and miRNAs seem to have enormous potential in neurodegenerative diseases especially as we have found that exosomes have a cell specificity. Currently, the value of exosomes and exosome-derived miRNAs in neurodegenerative diseases have been extensively studied, such as early diagnosis of diseases through blood/CSF-based specific miRNA detection, and targeted therapy through exosomes carrying agents across the BBB. Notably, as an irreversible disease, preventive measures or ways to slow the progression of neurodegeneration tend to be more achievable. In this context, the oxidative stress response is one of the crucial targets. Some antioxidants have been used to treat neurodegenerative diseases and appear to have an impressive effect , 167. In


Background: Decreased bone mineral density (BMD) was associated with poorer cognitive function and increased risk of Alzheimer’s disease (AD). However, objective evidence for the relationship between osteoporosis and AD in humans has not been extensively described.Objectives: We aimed to evaluate the relationships between BMD and the cortical volumes of brain regions vulnerable to AD; hippocampus, parahippocampal gyrus, precuneus, posterior cingulate, and angular gyrus, using voxel-based morphometry (VBM), to investigate the association between bone loss and AD.Methods: A cohort of 149 consecutive elderly participants who complained of memory disturbance underwent high-resolution structural brain magnetic resonance imaging (MRI) and dual-energy X-ray absorptiometry (DXA). We used SPM12 software to conduct a voxel-based multiple regression analysis to examine the association between femoral neck BMD values and regional gray matter volume (rGMV) on structural T1-weighted MRI.Results: After adjusting for subject age, gender, total brain volume (TBV), and mini-mental state examination (MMSE) scores, the multiple regression analysis showed significant correlations between BMD loss and rGMV decline in the left precuneus, which is an important neural network hub vulnerable to AD.Conclusion: These data suggest that the bone and brain communicate with each other, as in “bone-brain crosstalk,” and that control of BMD factors could contribute to cognitive function and help prevent AD. Both osteoporosis and Alzheimer’s disease (AD) are global problems, especially in developed countries where the proportion of the elderly population is growing. Both osteoporosis and AD increase proportionally with age and shorten life expectancy , magnetic resonance imaging (MRI), and single-photon emission tomography (SPECT) appears in specific areas of the brain. These findings are important objective biomarkers for the diagnosis of patients with AD  and increased rates of bone loss are associated with cognitive decline and a higher risk of AD  of an individual and the average BMD [expressed in standard deviation (SD) units] of a young adult in a reference population  is the standard and most precise technique for BMD measurement, and BMD is the standard measure for the diagnosis of osteoporosis. In 1994, the World Health Organization (WHO) first proposed diagnostic criteria for osteoporosis, with the diagnosis of osteoporosis being based on T-score, which is the difference between the BMD value  structural MRI combined with spatial-normalization methods enable us to analyze the precise quantitative topological features of brain structure. Voxel-based morphometry , years of education, mini-mental state examination score  who visited the outpatient department of the Department of Geriatric Medicine and Neuroimaging at Tohoku University Hospital for a complaint of memory disturbance between February 1, 2015, and July 31, 2018. All but one male participant was right-handed. Eligible patients had brain MRI and DXA scans completed at the initial investigation. The patients’ age, body mass index  were measured from a single protocol on a whole-body DXA machine  and a 32-element head coil were used to acquire a 3D T1-weighted magnetization-prepared rapid acquisition gradient echo (MPRAGE) structural image .Pre-processing of the structural images was performed using Statistical Parametric Mapping software  implemented in MATLAB  as described  was calculated by combining the gray matter images with the white matter images generated during the SPM segmentation process. Intracranial volume (ICV) was calculated by adding the segmented cerebrospinal fluid space to TBV.The brain parenchymal ratio of TBV over ICV (TBV/ICV) was calculated for normalization by body size. As a partial correlation analysis, Pearson correlation coefficients with adjustment for age and MMSE scores were separately calculated to evaluate the relationship between brain parenchymal ratio and BMD.P-value was lower than 0.05, with this correcting for multiple comparisons across the whole brain using random field theory. In addition to the whole-brain analysis, anatomical masks were created for small volume correction (SVC) with a voxel-level significance of 0.05 corrected for multiple comparisons. Regions were selected for which an a priori hypothesis existed concerning AD: hippocampus, parahippocampal gyrus, posterior cingulate cortex, precuneus, and angular gyrus  against the whole brain. Consequently, the voxels/regions which have a statistically significant correlation with the clinical data  can be demonstrated on the whole brain map. The subjects’ age, gender, TBV, and MMSE score were entered as covariates of no interest in these analyses. All continuous variables were mean-centered before analysis. The initial voxel threshold was set to 0.001 uncorrected. Results were considered significant only if the voxel-level family-wise-error (FWE)-rate-corrected Matsuda, . All regMatsuda,  includedMatsuda, .P < 0.001), SMI (P < 0.001), and education (P < 0.05), but a worse score on the MMSE (P < 0.05). All other demographic variables were similar between the two groups.This cross-sectional study involved 57 males and 92 females participants with an age range of 65–89 years and a mean age of 79.4 ± 5.8 (SD) years. The patients’ demographic data are presented in r = −0.109, P = 0.094; with MMSE adjustment: r = −0.125, P = 0.066).In the partial correlation analysis, the brain parenchymal ratio did not significantly correlate with BMD after adjusting for age or MMSE score . Except for the left precuneus, no other regions including the right precuneus showed statistically significant correlations between BMD and rGMV with even non-corrected VBM  in male subjects, but no significant association between BMD and rGMV was found in any region in the female subjects . The medial prefrontal cortex, PCC, precuneus, anterior cingulate cortex, parietal cortex, and hippocampus show synchronized activation during the resting state, and together form the DMN. AD was reported to disrupt the DMN because the DMN structures are vulnerable to atrophy, deposition of amyloid and tau protein, and reduced glucose metabolism due to AD pathology  adopted for the SPECT study were rather coarse compared with the MRI-VBM method used in this study. The significantly associated area in this VBM study was near the posterior cingulate cortex and medial and inferior clusters within the left precuneus, which included in the left PCC-ROI mask in the previous SPECT study. We, therefore, posit that the two results from the different imaging modalities could be consistent.Other studies have reported whole-brain volume loss in association with BMD loss  or Tartrate-resistant Acid Phosphatase 5b: bone resorption marker (TRACP-5b) which could directly reflect bone metabolism in this study. We presumed that such bone-related biomarkers might also attribute to brain function and morphology. We plan to investigate bone-related serum biomarkers as a role of bone-brain crosstalk in our further study.In conclusion, the present study demonstrated that lower BMD was associated with lower rGMV in the left precuneus in an elderly population, suggesting that bone loss may influence an important hub of a neural network affected by AD. The use of imaging modalities to visualize the evidence for bone-brain crosstalk has only just begun. Given these insights, the establishment of new treatments and preventive strategies for AD by controlling for risk factors affecting osteoporosis and cognitive function could be of great clinical importance.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation, to any qualified researcher.The studies involving human participants were reviewed and approved by the Clinical Research Ethics Committee of Tohoku University Graduate School of Medicine (2018-1-298). Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements. The trial was registered in the University hospital Medical Information Network Clinical Trials Registry .YTak, YTat, and TM co-designed the study. TN and HO were responsible for scanning the subjects and supported the imaging technology. YTak, YTat, NM, IM, and BT analyzed the data. YTak, YTat, and TM wrote the first draft of the manuscript. YTak, YTat, and SY were responsible for the subject’s characterization and sample collection. All authors contributed to and have approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Over the last decade, immune checkpoint inhibitors (ICIs) have revolutionized the treatment of several cancer types. ICIs work through the blockage of immune inhibitory signals, while increasing the T-cell specific immune antitumoral response. However, due to the fact that ICIs’ mechanism of action is not tissue antigen-specific and not limited to the tumor microenvironment, the use of cancer immunotherapy can produce a broad range of immune-related adverse events (irAEs). Neurological immune-related adverse events (NirAEs) are rare , and these adverse events mainly concern the peripheral nervous system, rather than the central nervous system. Due to their potential severity, which could cause interruptions to cancer treatment, NirAEs are of particular clinical importance. Currently, the pathogenesis of these complications is not completely understood, although T-cells seem to play a principal role. Nevertheless, the development of NirAEs is likely to be a multifactorial and complex process. This conclusion can be extracted from the wide range of neurological auto-inflammatory and autoimmune disorders triggered or exacerbated by ICIs, and the extensive variability of the limited histological findings reported. The aim of this review is to summarize the potential immune-driven pathological mechanisms of NirAEs. Over the last decade, the blockade of the immune checkpoints with monoclonal antibodies (ΜAb) has significantly improved clinical outcomes in various malignancies. T-lymphocyte-associated protein 4 (CTLA-4) and programmed cell death protein 1 (PD-1) are receptors that, under physiological conditions, can help to maintain immune tolerance [Anti-CTLA-4 treatment enhances naive T-cells mostly at early stages in the lymphoid organs, whereas anti-PD-1 antibodies induce antigen-mediated T-effector cells’ activation mainly in the peripheral tissues . T-cell https://www.orpha.net/consor/cgi-bin/index.php) [The most common irAEs involve the skin, gastrointestinal tract, endocrine system and liver and can occur in up to 65% of ICI-exposed patients . NirAEs dex.php) .The reasons behind the low incidence of immune-related toxicity in the nervous system compared to other organs remain largely unknown. Typically, the CNS and the peripheral nervous system (PNS) have been considered as immune-privileged systems due to the presence of anatomical barriers such as the blood–brain or the blood–nerve barrier ,12, as wICIs can both attack the peripheral and central nervous system (CNS), although neuromuscular involvement is more frequently disclosed than CNS involvement  . The mosOn the other hand, myositis appears to be the most common neuromuscular syndrome, with diffuse myalgias in back and proximal limbs being clinically evident in up to 2.95% of patients exposed to anti-PD-1 and PD-L1 . Data frConversely, about 1% of patients exposed to therapy with PD-1/PD-L1 inhibitors will manifest any grade of peripheral nerve damage in the form of axonal sensory peripheral neuropathy. The incidence of peripheral neuropathy is comparable after therapy with anti PD-1/PD-L1 or CLTA4 drugs . Treatment-emergent grade 3 neurotoxicity is much less likely to occur with PD-1/PDL-1 therapy than with conventional chemotherapy agents ,15.Several mechanisms have been proposed to be implicated in the development of irAEs, such as T-reg down-regulation, the cross-presentation of neoantigens, epitope spreading, genetic predisposition and microbiome alteration, yet the pathogenesis behind ICI-related toxicities remains largely unknown ,19. The The mechanism of ICIs’ action is not tissue antigen-specific, and their targets, the immune checkpoint receptors , are not only expressed on T-cells. Other immune cells and tissues might also be affected by ICI blockade. Regulatory T-cells (Tregs) express most of the checkpoint molecules, including CTLA-4 and PD-1, and represent a direct target of ICI immunotherapy. Tregs are key players in maintaining peripheral tolerance by actively suppressing effector T-cells  and by ip = 0.12), but no NirAEs were reported, despite the high odds ratio observed. The wide range of the CI due to the small number of patients with positive autoantibodies (n = 19) most probably accounts for the latter insignificant association [On the other hand, CTLA-4 and PD-1 are also key players in the activation, proliferation and regulatory function of B-cells ,25. A clociation .In addition, immune homeostasis is orchestrated by the interactions between immune cells and the cytokine environment. Pro-inflammatory cytokines cause the destruction of target tissues and a break of tolerance, whereas anti-inflammatory cytokines maintain immune tolerance. Tregs are highly regulated by a vast and intricate milieu of cytokine signals, such as IL-2 or TGF-β, which ultimately might modulate immune tolerance . ICIs haFurther investigation and research are needed to elucidate the exact mechanisms behind the occurrence of NirAEs. The blockade of different subtypes of immune cells—i.e., T-cells, B-cells or Tregs—together with systemic changes in cytokines leading to the loss of immune system homeostasis can trigger an innate immune response and the activation of self-reactive immune cells. Host factors, such as genetic predisposition  or the microbiome composition (microbiome-derived products), can further augment this immune response overactivation. The latter theory might explain the reasons behind potential differences in the spectrum and frequency of irAEs.The concept of molecular mimicry refers to the similarity between a host antigen and an antigen from a microorganism, environmental agent or even a tumor cell. This molecular likeness might induce a T-cell or autoantibody cross-reactive autoimmune response wrongly directed against the host antigen rather than the pathogenic antigen. However, this a complex process in which host genetic and environmental factors, as well as issues related to the mechanisms associated with a positive/negative selection of T- and B-cells, are also involved. In patients treated with ICIs, there is increasing evidence that a phenomenon of the cross-presentation of neo-antigens or shared antigens  might induce a loss of tolerance and subsequent autoimmune reaction. The self-antigens might be released when tumor or non-tumor tissues, distributed in and around the tumor environment, are damaged collaterally, by immune cells directed against the tumor ,33.A classic and well-known example of a cross-reactive immune response against a self-antigen is paraneoplastic syndrome (PNS) ,35. SomeGRIN2A gene, which encodes the NMDAR subunit GluN2A, is highly mutated in melanoma patients. This case may represent a molecular mimicry phenomenon in which antibodies against NMDAR attack both melanoma and CNS cells [Likewise, a case of anti-N-methyl-D-aspartate receptor (NMDAR) autoimmune encephalitis was reported in one patient with melanoma. The presence of NMDAR antibodies in the blood and cerebrospinal fluid supports immune-related pathogenesis. NMDAR is expressed on melanocytes, and NS cells ,39.This mechanism of molecular mimicry has also been suggested for some melanoma patients who developed ICI-related demyelinating polyneuropathy, since melanocytes and Schwann cells originate from the neural crest and share many epitopes for humoral and cellular immune responses . In furtOverall, ICIs may unmask or accelerate pre-existing autoimmune reactions against neuronal antigens, leading to the development of NirAEs. Therefore, patients with cancer types that are frequently associated with PNS neurotoxicity, such as melanoma and small cell lung cancer, might be at an increased risk of developing neuromuscular NirAEs when treated with ICIs. In line with the latter view, a retrospective study reported a significant increase in the frequency of anti-Ma2 encephalitis following the implementation of ICIs . SurprisIn contrast to primary neurological autoimmune diseases, in almost all of the ICI-related inflammatory demyelinating neuropathies reported, antiganglioside antibodies were not found and excellent responses to steroid therapy were observed . MoreoveSome authors have suggested that irAEs may be caused by immunotherapy-induced epitope spreading (ES) . Tissue Certain chemotherapeutic drugs or radiotherapy can lead to immunogenic cell death through tumor-antigen processing and presentation to the immune system . RecentlIrAEs can also be derived from the “off-target” effects of ICIs on non-hematopoietic cell lines bearing the target immune checkpoint ligand. In support of this mechanism, it was identified that CTLA-4 protein expression on pituitary endocrine cells might be directly targeted by the anti-CTLA4 MAb . Catureghttps://www.proteinatlas.org/). Temporal as well as spatial differences in immune checkpoint expression may contribute to distinct immune-regulatory functions and differences in toxicities, but further studies are needed.Immune checkpoint receptors such as CTLA-4, as mentioned above, are distinctly expressed in different tissue microenvironments, providing a means for selective roles in tissue tolerance. PD-1 and its ligands can also be expressed on a wide variety of non-hematopoietic cell types, including vascular endothelial cells, fibroblastic reticular cells, epithelial cells, pancreatic islet cells, astrocytes and neurons ,36. SpecBlocking the interaction between PD-1/PD-L1 or CTLA-4 on lymphocytes resident in or infiltrating the nervous system could increase local inflammation or reveal latent central or peripheral inflammation. This mechanism might be responsible for the exacerbation of multiple sclerosis, autoimmune encephalitis, inflammatory demyelinating neuropathies or PNSs, as shown, for example, in some experimental models of CNS inflammation ,53,54.ICIs might augment pre-existing immune responses directed against the nervous system. Several case reports have described the exacerbation of neurological autoimmune diseases during or after ICI therapy. A transition from radiologically isolated syndrome to clinically definite multiple sclerosis in a patient with metastatic melanoma after ipilimumab treatment has been reported. Using TCR gene sequencing analysis, the authors compared the TCR repertoire of T-cells present in the primary melanoma with the TCR repertoire in two consecutive cerebrospinal fluid samples. The analysis revealed two distinct oligoclonal CD4+ and CD8+ T-cell repertoires induced by ipilimumab: an immune response against the tumor and one against neural antigens, which resulted in severe multiple sclerosis disease activity .In addition, the exacerbation of peripheral neurological autoimmune diseases such as pre-existing myasthenia gravis in patients under ICI blockade has also been highlighted in some clinical reports ,57. HoweThe reason accounting for why some patients develop irAEs while others do not remains unclear. Currently, a relationship between some genetic factors and the risk of irAEs has not been established. For example, in terms of genetic associations, CTLA-4 polymorphisms have been linked to an increased risk of autoimmune diseases, such as type 1 diabetes, and preclinical models have shown that anti-CTLA-4 can increase the risk of autoimmune diabetes . HoweverBacteroidetes phylum was correlated with resistance to the development of immune-related colitis [In addition to genetic factors, another relevant question concerns whether the microbiological composition of a patient’s gastrointestinal flora is related to the development of irAEs. In fact, the most common irAEs involve organs that are rich in commensal organisms, such as the skin, colon and lungs . In a st colitis .However, further research with prospective studies is needed to determine whether genetic or microbiome compositions are augmenting or reducing the risk of irAEs. To our knowledge, there is not any evidence correlating genetic or microbiome-related factors, specifically when it comes to the development of NirAEs.The molecular pathogenesis of NirAEs remains largely unknown. As a result, the optimal management of NirAEs has not yet been established. The treatment of these adverse events involves the prompt discontinuation of ICI therapy upon clinical suspicion of NirAE evidence and the initiation of immunosuppressive therapy. As for the other irAEs, their optimal management requires the initial exclusion of tumor-related pathology  and the involvement of experienced multidisciplinary teams to guide appropriate investigations and tailor treatment strategies. Currently, administering corticosteroids represents the cornerstone of NirAEs’ management. Intravenous immunoglobulin, plasma exchange and other immune-modulating treatments should be considered in more severe cases . HoweverDue to the key role of ICIs priming specific antitumor T-cell responses and the predominance of T-cell infiltration within histological samples of irAEs case reports, T-cells are believed to play a pivotal role in ICI-mediated toxicity. However, based on the wide range of neurological auto-inflammatory and autoimmune disorders observed in patients undergoing ICI treatment, other potential players are most likely involved in this process. A unique clinical picture, such as encephalitis, may be yielded by different mechanisms , and, at the same time, extrapolations made from the pathological mechanisms behind primary autoimmune diseases may not be representative of irAEs. Moreover, the functional roles of cytokines and innate immunity are yet to be extensively explored, while in the few clinical cases reported, their involvement in the development of irAEs can be highly suspected.Unfortunately, the role of the primary tumor histology and the potential correlations with the type of ICI used are not well controlled for in large clinical trials and meta-analyses published with regard to the development of NirAEs, which could undoubtedly provide essential information on the underlying mechanisms of immune-related toxicities. Similarly, the concurrence of other irAEs in addition to NirAEs might also be a useful tool, in order to improve our knowledge about the mechanisms involved in the development of these adverse events and the role of host tissues.Overall, as derived from the immune-driven hypothesis and clinical clues available to date, it is suggested that NirAEs might develop as a result of different mechanisms, while the stochastic emergence suggests potential genetic and microbiome-related factors additionally modulating these mechanisms. Such complexity highlights the need to increase our efforts to obtain clinical data, tissue samples and more detailed histological and molecular analysis, in order to enhance our depth of knowledge regarding the molecular pathogenesis of NirAEs. Reliable biomarkers are urgently needed, in order to identify patients that are at higher risk of developing toxicities and in order to improve the therapeutic management of and the clinical approach against irAEs, ensuring the least possible interference with the antitumoral effects of ICIs.