Ewing sarcoma (ES) is the second most common pediatric bone tumor with a high rate of metastasis, high recurrence, and low survival rate. Therefore, the identification of new biomarkers which can improve the prognosis of ES patients is urgently needed.  Here, GSE17679 dataset was downloaded from GEO databases. WGCNA method was used to identify one module associating with OVS  and event. cytoHubba was used to screen out 50 hub genes from the module genes. Then, GSE17679 dataset was randomly divided into train cohort and test cohort. Next, univariate Cox analysis, LASSO regression analysis, and multivariate Cox analysis were conducted on 50 hub genes combined with train cohort data to select pivotal genes. Finally, an optimal 7-gene-based risk assessment model was established, which was verified by test cohort, entire GSE17679, and two independent datasets (GSE63157 and TCGA-SARC). P value < 0.0001, indicating that this model was accurate, which was also verified in the test, entire cohort, and two independent datasets (GSE63157 and TCGA-SARC). Then, we performed a comprehensive analysis  of seven pivotal genes, and found that four genes  plays a more crucial role in the prognosis of ES.  The results of the functional enrichment analysis revealed that the OVS and event-associated module were mainly enriched in the protein transcription, cell proliferation, and cell-cycle control. And the train cohort was divided into high-risk and low-risk subgroups based on the median risk score; the results showed that the survival of the low-risk subgroup was significantly longer than high-risk. ROC analysis revealed that AUC values of 1, 3, and 5-year survival were 0.85, 0.94, and 0.88, and Kaplan-Meier analysis also revealed that  Taken together, this study established an optimal 7-gene-based risk assessment model and identified 4 potential therapeutic targets, to improve the prognosis of ES patients. Ewing sarcoma (ES) is the second most common pediatric bone tumor with a high rate of metastasis, high recurrence, and low survival rate. Although a standard multimodal treatment regimen which includes surgical resection, local radiotherapy, and intensive multiagent chemotherapy has been established , 30-40% Previous study has reported that ES is characterized by FET-ETS gene fusions , 6, and In this study, we downloaded the gene expression profiles and clinical data from GSE17679 dataset and two independent datasets (GSE63157 and TCGA-SARC) for validation. We used the WGCNA method to identify one module associating with OVS and event. Then, univariate Cox regression analysis, LASSO regression analysis, and multivariate Cox regression analysis were used to screen out signature hub genes related to the prognosis of ES patients. Finally, we established an optimal 7-gene-based risk assessment model to evaluate the survival of ES patients. Our study provides a new method to assist the prediction of prognosis in clinical ES patients.https://www.ncbi.nlm.nih.gov/geo/) as dataset GSE17679, which was based on the GPL570 platform ((HGU133 Plus 2) Affymetrix Human Genome U133 Plus 2.0 Array). And probes of the array data were replaced with the corresponding official gene symbols using the hgu133plus2.db (version 3.2.3) package. If multiple probes were mapped to the same gene symbol, duplicates were collapsed randomly. Then, 106 samples of human tissue were recognized by consensus clustering, and outlier samples were removed. Finally, a total of 88 samples were selected for the next analysis.The gene expression profiles and clinical data were downloaded the from the Gene Expression Omnibus (GEO) database (β) in the range of 1 to 30 using pickSoftThreshold function. This β value can get with a balance between scale-independence and mean connectivity in a coexpression network, which was used to transform the correlation matrix into a weighted adjacency matrix. Then, the adjacency matrix was transformed into a topological overlap matrix (TOM). Based on TOM, we can get 1-TOM, which was used as the distance measurement to cluster genes into coexpression modules, and highly correlated modules which Pearson′s correlation ≥ 0.75 were merged in one. Finally, the P values and correlation coefficients between a coexpression module and a clinical feature were calculated and visualized by heatmaps.We use the WGCNA (version 1.70-3) package in R to deal with ES data and construct a weighted coexpression network . InitialModule eigengene  can represent the expression levels of all genes in a module. Gene significance (GS) was defined as the correlation between genes and clinical features in linear regression. Module significance (MS) means the average GS for all the genes in a module. In a word, MS was used to select modules having highly relation with interested clinical feature, and the selected module was used for further analysis.https://string-db.org) contains information about the interactions between proteins, which was used to construct the protein-protein interaction (PPI) network. First, we upload the module genes of interest to build the PPI network using STRING online analysis tool. Next, the PPI network was imported into the software of Cytoscape (version 3.8.2). Finally, top 50 hub genes with high Maximal Clique Centrality (MCC) values were selected using cytoHubba in Cytoscape for subsequent analysis.Retrieval of Interacting genes/Proteins (STRING) database (P < 0.05 [Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes Pathway Enrichment (KEGG) were two important databases to analyze the function of genes. To determine the function of top 50 hub genes, the clusterProfiler R package was used to perform GO and KEGG analyses with threshold P < 0.05 .First, GSE17679 datasets were randomly divided into train cohort and test cohort, with train cohort being used for construction of the risk model and test cohort and entire cohort being used as validation data. To construct a reliable model, three analysis methods were used by step: univariate Cox regression analysis-LASSO (least absolute shrinkage and selection operator) regression analysis-multivariate Cox regression analysis . AccordiFirst, we used boxplot to observe the expression levels of prognostic genes in the final outcome of patients and determine whether they were statistically significant. Then, we do a correlation analysis between the expression levels of the prognostic genes and clinical traits, to select more critical genes in prognosis of ES patients. Finally, the median value of gene expression for selected genes was calculated to group patients with above median value as high expressers and below the median value as low expressers. And, based on the expression group, we do survival analysis to further verify the importance of selected genes in prognosis.At the end of present research, clinical information on ES samples, such as gender, age, metastasis, event and survival time, was incorporated with the risk score for nomogram construction. And calibration plot was drawn to verify the accuracy of nomogram.We downloaded the expression matrix and clinical information of GSE17679 from the GEO database and calculated the scale-independence and the mean connectivity at different thresholds. A suitable soft threshold 6 was chosen, which met the standard which scale − independence > 0.85 and average connectivity < 100 . Under tGene significance (GS) was used to measure the correlation between genes and traits, and an average GS value of all genes included in each coexpression module was used to calculate module significance (ME). The most significant module correlated with prognosis and OVS was selected for further analyzed.r2 = 0.46; P = 8e − 06), OVS , and EFS . Consequently, we focused on turquoise module in our further study.According to the module-trait relationship heatmap , the turBased on the STRING database, the PPI network of 880 genes in the turquoise module was constructed, and the top 50 hub genes in the network were selected using the MCC algorithm of cytoHubba .The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) enrichment analysis were used to further study the function of 50 hub genes. According to the GO analysis , the 50 P value < 0.0001). And the AUC value of 1-, 3-, and 5-year survival was 0.85, 0.94, and 0.88, which indicated a good predictive accuracy of this model  also indicated a good predictive accuracy for this model. Furthermore, the results of the other two cohorts (test and entire GSE17679) and two independent datasets were satisfactory, which also showed this model on a good predictive accuracy, versatility, and practicality.In this study, we identified one module that was associated with OVS and event by using weighted coexpression analysis; then, 50 hub genes were selected by cytoHubba. The functional enrichment analysis revealed that 50 hub genes were enriched in the protein transcription, cell proliferation, and cell-cycle control. The result is consistent to FET/ETS family of biology function , so it iIn the 7 pivotal genes, every gene was clearly correlated with OVS and event, but four genes  may play a more important role in ES prognosis. Therefore, further study of these four genes is warranted. Non-SMC condensing complex subunit G (NCAPG) is a crucial component of the condensing complex, which binds to chromosomes at start of mitotic division and dissociates from them when mitotic division ends. Previous studies have reported that NCAPG is a promising therapeutic target across different tumor types, and it may be associated with development and progression of hepatocellular carcinoma (HCC) , 26, esoKinesin family member 4A (KIF4A) was a new component of the chromosome segregation machinery and acted critical roles in mediating spindle organization and cytokinesis . PreviouNUF2 component of NDC80 kinetochore complex (NUF2) is a component of a conserved protein complex associated with the centromere, and one study had demonstrated that NUF2 upregulation is a common feature of many cancers  . So, theCell division cycle 20 (CDC20) regulates cell division and plays an important role in tumorigenesis and tumor progression. The upregulation of CDC20 is associated with poor prognosis of prostate cancer , breast Finally, a visual nomogram was created for quantitatively assessing the overall survival of ES patients using the risk score and clinical prognostic variables. And the results of the calibration curve suggest that the nomogram was dependable. Because of the rapid advances in genome sequencing, the cost of sequencing now is affordable for most patients. So, this nomogram can become a reliable and practical statistical tool, which can help clinician to evaluate the survival and prognosis of patients with ES.This study established a 7-gene-based risk assessment model and demonstrated its good performance on predicting the prognosis of ES. And this study also found four pivotal genes may be the potential prognostic biomarker of ES. Although, based on three datasets, we detect significantly association between the predicted prognosis and the simulated risk score for ES patients, and this association has not yet been clinically confirmed. Therefore, the verification of this 7-gene risk assessment model and the research on the regulatory mechanism of single genes in model need to be further carried out. Taken together, this study provides a new method for evaluating the survival and prognosis of patients with ES and provides several potential therapeutic targets for ES.


This study was conducted in order to develop and validate an ultrasonic-based radiomics nomogram for diagnosing solid renal masses.n = 204) and malignant renal tumors (n = 396) were divided into a training set (n = 480) and a validation set (n = 120). Radiomics features were extracted from ultrasound (US) images preoperatively and then a radiomics score (RadScore) was calculated. By integrating the RadScore and independent clinical factors, a radiomics nomogram was constructed. The diagnostic performance of junior physician, senior physician, RadScore, and radiomics nomogram in identifying benign from malignant solid renal masses was evaluated based on the area under the receiver operating characteristic curve (ROC) in both the training and validation sets. The clinical usefulness of the nomogram was assessed using decision curve analysis (DCA).Six hundred renal solid masses with benign renal lesions (p = 0.004), and the model also showed significantly higher specificity than the senior and junior physicians (0.93 vs. 0.57 vs. 0.46).The radiomics signature model showed satisfactory discrimination in the training set  and the validation set . The radiomics nomogram also demonstrated good calibration and discrimination in the training set  and the validation set . In addition, the radiomics nomogram model showed higher accuracy in discriminating benign and malignant renal masses compared with the evaluations by junior physician (DeLong The ultrasonic-based radiomics nomogram shows favorable predictive efficacy in differentiating solid renal masses. Although the majority of renal masses are malignant, about 16% to 19% of renal tumors are reported to be benign . ClinicaPercutaneous renal biopsy is an important pretreatment diagnostic procedure in the evaluation of indeterminate renal masses. However, the diagnostic accuracy of percutaneous biopsy ranges from 70% to 90%, and its role in clinical management remains unclear because of the negative predictive value and the possible complications, including bleeding, perirenal hematoma, hematuria, arteriovenous fistula formation, and pneumothorax –7. Thus,Conventional B-mode ultrasound (US) is an easy, safe, and non-invasive procedure. It is currently the first-line imaging modality for detecting renal lesions and discriminating benign from malignant renal tumors. However, the visual interpretation of US images is generally based on the sonographers’ experience. Radiomics features can be computed from grayscale images to reflect the texture and morphology of tumors –11. Basen = 480) and a validation set (n = 120). The distribution of tumors is detailed in We queried our institution’s electronic medical records to derive all surgically confirmed cases of renal masses between January 2013 and January 2018. A total of 1,998 confirmed renal masses were screened in this query: 1,777 malignant renal lesions and 221 benign renal lesions. In order to balance the proportion of malignant and benign renal masses, we randomly selected 442 malignant renal masses according to the hospitalization numbers. The inclusion criteria were as follows: 1) patients who had undergone US examination before treatment and the image quality of US was satisfactory for analysis and 2) patients with complete clinicopathological data. The exclusion criteria were as follows: 1) the pathological result of the surgical specimen was unclear, 2) the patient had undergone preoperative therapy (ablation therapy), and 3) the renal mass was not completely visible in the image. Finally, 597 patients with 600 renal masses were included in this study  and Aplio 500 . The C5-1 probe was used for conventional ultrasound with a central frequency of 3–5 MHz. The gray image of the renal masses was available.The workflow of the radiomics analysis included tumor segmentation, feature extraction, feature selection, and radiomics signature construction and evaluation (https://imagej.nih.gov/ij/). A sonographer with more than 8 years of experience in US imaging of kidney neoplasms semiautomatically corrected the boundary of the lesion in each image of each individual patient. When the boundary is not determined, another experienced sonographer  was consulted for a final opinion.All US images were retrieved from the picture archiving and communication systems (PACS) for image segmentation and analysis in our institution. Lesions were segmented using ImageJ  morphological features, such as area, largest diameter, length to width ratio, and roundness; 2) grayscale statistic (GSS) features calculated from the histogram of tumor voxel intensities, such as variance, skewness, and kurtosis; 3) texture feature, including gray-level co-occurrence matrix (GLCM), gray-level run-length matrix (GLRLM), gray-level size zone matrix (GLSZM), and neighborhood gray-tone difference matrix (NGTDM); and 4) wavelet feature. Details of the procedures for extraction of radiomic features are described in U was used to select features that were highly related to the biomarkers. A significance level of 0.05 (p < 0.05) was set as the threshold. Secondly, an interfeature coefficient (R) between all possible pairs of features was subsequently used to eliminate high-dimensional feature redundancy. R >0.8 was the cutoff for strong relationships, in which one of two features with a lower p-value was excluded. Next, the least absolute shrinkage selection operator (LASSO) method was used to select the most important features with non-zero coefficients, and a RadScore was calculated for each patient. The process of radiomics feature extraction and analysis was performed in MATLAB 2018a  and R software , respectively.Dimension reduction of the features was conducted to minimize overfitting and reduce the bias from radiomics features in the modeling. Firstly, the Mann–Whitney p-value of Delong’s test. The clinical usefulness of the nomogram was assessed using DCA which included two decision curves based on the radiomics signature and radiomics nomogram and could be demonstrated by calculating the net benefits for a range of threshold probabilities.The significant variables of the clinical factors and RadScore were integrated to build the radiomics nomogram model. We performed a calibration curve to graphically investigate the performance characteristics of the nomogram. The performance of each model for differentiating benign from malignant solid renal masses was evaluated based on the area under the ROC, accuracy, specificity, and sensitivity in both the training and validation sets. The difference in the AUC between the training and validation datasets was tested by the The US findings were independently analyzed by two sonographers , including size, location, shape, margin, and echogenicity.x̅ ± s). The categorical data were presented as percentage or ratio. The logistic regression method was used for univariate and multivariate analysis in the training set. Statistical significance was set at p <0.05.The continuous variables were described as the mean ± standard deviation (p < 0.001) and age (p < 0.001) between benign and malignant patients in the training set. Multiple logistic regression analysis showed that sex  remained as an independent predictor.Detailed information on the clinical characteristics is shown in Of the radiomics features, 855 features were reduced to 30 potential predictors on the basis of 480 renal masses in the training set Figure 2p < 0.001). Thus, the radiomics nomogram was developed using sex and radiomics score .The DCAs based on the two models are presented in p = 0.004), but there was no significant difference between the senior physician and the radiomics nomogram (DeLong p = 0.089). However, the specificity of the radiomics nomogram was significantly higher than that of the senior and junior physicians (0.93 vs. 0.57 vs. 0.46).Clinically, for the renal masses that are radiographically suspicious for renal cell carcinoma (RCC) without a pathology diagnosis, nephrectomy or nephron-sparing surgery is a standard management , 17. HowIn clinical practice, many imaging methods are used to distinguish between benign and malignant renal masses. US is currently the first-line imaging modality for renal tumor screening. Contrast-enhanced CT is the most commonly used imaging equipment for the evaluation of a renal tumor that requires further observation. With a superior soft-tissue contrast, MRI is particularly helpful to distinguish solid from cystic lesions. Contrast-enhanced US (CEUS) could be used to show the real-time tumor vascularization. Compared with US, these imaging procedures are more expensive, time-consuming, and less safe due to the use of nephrotoxic iodine contrast agents and ionizing radiation. Some reports have indicated the significance of CT- or MRI-based radiomics model in discriminating benign renal tumor from malignancies –29. HoweIn the present study, among the 855 extracted radiomics features, 30 features including texture and wavelet features were selected as the significant features to build the radiomics signature. The images in the benign group were more homogeneous in texture than the ones in the RCC group, which was consistent with previous reports and the diagnostic experience of the sonographer , 23.Recently, radiomics showed excellent performance in differentiating benign and malignant renal masses –29. HodgWe further analyzed the false diagnosed cases. In general, classic AMLs consist of aberrant blood vessels, smooth muscle, and mature adipose tissue . They arUnexpectedly, in this study, the radiomics nomogram model in combination with the clinical factor did not show better performance compared with the radiomics model alone as shown in the study of Nie et al. . Their nIt is noteworthy to point out the limitations of this study. First, its retrospective nature poses a potential selection bias. The US images used in this study were derived from two different US machines. This may lead to heterogeneity of the US images and further impact the performance of the radiomics score. Second, the samples were derived from a single institute, and the training and validation cohorts were split using a random split method. External validation using a prospectively recruited patient cohort and multicenter studies with a larger sample size to prove the robustness of our results are required. Third, manual region of interest (ROI) segmentation is time-consuming and complicated, especially for tumors without a well-defined boundary. Future studies should focus on the development of an automatic segmentation method for renal tumors with favorable reliability and reproducibility.In conclusion, this study developed an ultrasonic–radiomic nomogram model that showed favorable predictive efficacy in preoperatively distinguishing benign renal masses from malignant tumors. As a non-invasive and quantitative method, the radiomics nomogram model may serve as an effective tool to supplement conventional imaging modalities for the clinical decision-making process.The original contributions presented in the study are included in the article/This study was reviewed and approved by the Ethics Committee of Tianjin Medical University Cancer Institute and Hospital . The Ethics Committee waived the requirement of written informed consent for participation.WM and CL designed the study. CL and GQ wrote the original draft. JL, LQ, and XQW performed the analyses. TZ, XL, and SD collected the data. WM and XW contributed to the discussion and manuscript revision. All authors contributed to the article and approved the submitted version.This study was supported by the scientific research program of Tianjin Education Commission (2020KJ131).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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


This research highlights the prospect of kurugua seed by-product as a nutraceutical and functional food ingredient. Nutritional and bioactive profiling revealed that kurugua is rich in excellent nutritional compounds that can be exploited for human food development or in animal feed formulations. The seed by-product has shown great promise as an effective hepatoprotective agent and could be targeted for drug development.Sicana odorifera) is a native fruit that demonstrates attractive nutritional, coloring, flavoring, and antioxidant properties. The main by-products from the processing and consumption of kurugua fruit are epicarp and seeds. In this work, the properties of the seeds of S. odorifera were evaluated. The nutritional composition of the fruit seeds was determined through AOAC official methods and UHPLC-ESI-MS/MS profiling. The antioxidant activities were determined using in vitro methods, and the acute toxicity and hepatoprotective properties were investigated in Swiss albino mice. Quercetin derivatives and cucurbitacins were the main phytochemicals in the seeds’ methanolic extract and demonstrated some biological activities. GC-MS analysis revealed the essential fatty acids linolenic and linoleic as the main compounds present in seeds oil. The methanolic extract significantly reduced the serum levels of glutamic-pyruvic transaminase (GPT) and glutamic-oxaloacetic transaminase (GOT) in mice with induced hepatotoxicity  at the minor concentration tested (100 mg/kg EMSo). The results suggest that the S. odorifera seeds as by-products show potential use as a source of phytochemicals and in the production of oils with application in food supplements and nutraceuticals. Their integral use could contribute to waste reduction from kurugua fruits processing within the food safety and environmental sustainability framework.The “Kurugua” ( Current global challenges such as food safety, climate change, poverty, and health have a direct impact on the realization of the right to adequate food. Each challenge is negatively affected by food loss and waste, and developing sustainable global consumption and production systems is necessary . Food byThe interest of the food and cosmetic industries for products from medicinal plants has increased, and it is necessary to broaden the investigation of natural sources, including fruit waste such as seeds . The litThe year 2021 has been declared as the International Year of Fruits and Vegetables, encouraging populations to increase their consumption, seeking for the reduction of waste within the framework of Sustainable Food and Food Security, and valuing the potential of by-products, such as the seeds, not used in the industrial processing of fruits . It has Sicana odorifera, or “Kurugua” is from the Cucurbitaceae family, found natively in the Latin American region, where it is widely used in folk medicine for various ailments; however, it is a species that has been hardly studied + ion at m/z 443 and was tentatively assigned as boeticol, while compound II with a pseudomolecular ion of 647 amu was compatible with karounidiol dibenzoate. The assignation of compound I was supported by the intense fragments at m/z 263 and 233, in line with cucurbitane-type triterpenoids [II was supported by the MS/MS fragments at m/z 227, 171, and 105, characteristics of Karounidiol dibenzoate [The analysis in the positive ion mode allowed the detection of two cucurbitacins. Their extracted ion chromatograms are shown in benzoate . The results of the analysis of the fatty acid profile of the seeds have shown that the fatty acids are preferably polyunsaturated .The antioxidant activity was measured as a function of the TPC concentration, monomeric anthocyanins, and vitamin C, in addition to the total antioxidant capacity by inhibition of the radical ABTS, the results of which are shown in S. odorifera seeds did not cause lethality in female mice after 24 h of observation.Oral administration  of the methanolic extract of S. odorifera seeds administered orally up to a dose of 2000 mg/kg was shown to be safe because there was no lethality or symptoms indicative of acute toxicity under the experimental working conditions. After 14 days of observation, the mice were euthanized, and no signs of morpho-anatomical alteration were observed in the internal organs macroscopically evaluated and compared with the organs corresponding to the blank group. The methanolic extract of No relevant effects on the general behavior were observed in mice of both sexes administered orally with different doses  of the extract. The most representative effects on the general behavior of the mice were observed within 4 h after administration and are recorded. The appearance of piloerection and self-cleaning behavior is observed in the group treated with the methanolic extract compared to the group treated with the blank. After this time, the influence on the parameters decreased until the total disappearance of these nonspecific effects, which were of a short duration and because they are the crude extract, are considered irrelevant.S. odorifera seeds’ extract on acetaminophen-induced hepatotoxicity. We have studied the activity of S. odorifera did not show significant effects on the serum levels of alkaline phosphatase, total proteins, and albumin between the different treatments.The influence of the oral administration of the seed extract on the serum levels of Albumin, total protein, and serum alkaline phosphatase of male mice with hepatic damage induced with acetaminophen is depicted in S. odorifera seeds (EMSo) did not produce a significant change in serum albumin, serum total proteins, and serum alkaline phosphatase values. On the other hand, In the present study, it was demonstrated that the administration of acetaminophen, silymarin, and the different doses  of the methanolic extract of S. odorifera have the potential for their use as a food ingredient in other prepared foods or for the extraction of oil from the seeds, whose lipid content is high (35.5%). Considering the RDI of manganese for healthy adults, which is 2.3 mg/day , 76.67% of the RDI for Cu (RDI = 0.9 mg/day), and more than 15% of the RDI of Fe (RDI = 14 mg/day); these results show that S. odorifera seeds can represent a good source of minerals. However, the mineral content and consequently the bioaccessible fraction may differ when it is released in the intestinal lumen after gastrointestinal digestion to be available for absorption, and further studies were suggested regarding the bioavailability of minerals from S. odorifera seeds [According to the results, and other bio-residues, the seeds of 3 mg/day , nutritira seeds ,47,48. S. odorifera is higher than that reported for the pulp (4.39 μM TEAC/g FW) and skin (0.201 μM T/g FW) [The values of Vitamin C and TPC were lower than those reported in seeds of the same species, from fruits harvested in Colombia (16.0 ± 0.00 mg/100 g). However, the antioxidant activity values by the ABTS method in the seeds were higher than those reported (13.9 ± 2.87 µM TEAC/g) in the seeds of the ripe fruit, by the same authors . In our S. odorifera seeds presented a fatty acid profile, in which the main components were alpha linolenic acid (ALA) (omega 3) and linoleic acid (omega 6) (LA), followed by oleic monounsaturated fatty acid (omega9). ALA is an essential fatty acid for humans, which, when consumed in significant quantities, can be stored, β-oxidized, and metabolized into its bioactive derivatives, mainly DHA [S. odorifera seeds, the presence of alfa linolenic acid (ALA) essential fatty acid omega 3 (C18:3) in 2.93 ± 0.01 mg per 100 g  seed oil [Citrullus colocynthus) seeds’ extract [Cucumis melo) seeds’ extract, and the latter was also found in spiney gourd (Momordica dioica) seeds [Prunus domestica) and has been described for the first time in S. odorifera seeds [S. odorifera seeds, in agreement with our results [Regarding the UHPLC-MS analysis of the seeds, eleven compounds were detected under our experimental conditions. In a preview study of our group, twelve main compounds were tentatively identified, including five anthocyanin derivatives, five flavonols derivatives, two flavonol aglycones, and two unidentified compounds in ra peels . In thise family ,59,60. I extract . Regardira seeds , in agrera seeds ,17,18 anseed oil  and bitt extract . Regardia) seeds . Finallyra seeds ,62. The  results . In addi results ,63, repo results ,64. The p < 0.05; GOT p <0.001); with 100 mg/kg EMSo ; with 300 mg/kg EMSo  and with 500 mg/kg EMSo (GOT p < 0.001) compared to the APAP group . In this work, in the mice treated with SM, used as a hepatoprotective control, the levels of GPT and GOT were significantly attenuated (p < 0.001) compared to the pathological group (APAP). It has been described that the protective effect of SM is associated with several possible mechanisms for antioxidant protection in the body, directly and indirectly; that is, these mechanisms directly involve the elimination of superoxide and prevention of radical oxygen species (ROS) formation on liver cells, but also indirectly the LM maintains an optimal redox balance by activating enzymatic and non-enzymatic antioxidants, and decreases inflammatory responses by inhibiting NF-kB pathways. Consequently, SM would reduce inflammation, necrosis, and transaminase levels. This leads us to think that a flavonoid such as SM that presents hepatoprotective effects could have mechanisms similar to those of the administered extract, considering that we have observed the presence of flavonoid compounds, mostly quercetin derivatives and luteolin aglycon [Hypericum japonicum, offers protection against CCl4-induced hepatotoxicity; this shows that the hepatoprotective effects of Q7R may be related to its antioxidant activity [Momordica charantia (Cucurbitaceae), which showed cytoprotective effects against t-BHP-induced injury on hepatic cells, and cucurbitacin B isolated from the juice of Ecballium elaterium (Cucurbitaceae), which showed both preventive and curative effects against CCl4-induced hepatotoxicity by decreasing the abnormally increased GPT levels of mice [In this work, the increase in transaminase levels induced by paracetamol is significantly reduced by the oral administration of EMSo (GOT < 0.001). Animals treated with 10 mg/kg EMSo presented significantly reduced levels of transaminases . This demonstrates the hepatotoxic effect of 300 mg/kg APAP as a positive control for hepatotoxicity under the test conditions. In silymarin-treated mice (group SM), GOT and GPT were significantly attenuated (p < 0.001) when compared to the pathological group (APAP). It is difficult to predict which of the compounds observed in the methanolic extract profile contributed to the observed hepatoprotective effect. However, the content of polyphenols, specifically luteolin, quercetin, and four of their conjugated derivatives, may have some implications. In general, cucurbitacins, saponins, carotenoids, phytosterols, and polyphenols are the most important phytochemicals present in the cucurbits, and are bioactive phytoconstituents responsible for pharmacological effects such as antioxidant, antitumor, antidiabetic, hepatoprotective, antimicrobial, antiobesity, diuretic, and antigenotoxic activity [S. odorifera. Quercetin, a bioactive secondary metabolite observed in methanolic extract, is incredibly important in terms of bioactivities as antioxidants, which has been proven by in vivo and in vitro studies. These properties of quercetin have been attributed primarily to their antioxidant capacity and free radical scavenging ability [Cucurbita pepo showed hepatoprotective properties and caused a significant increase in the enzyme’s antioxidants, including CAT, SOD, and GPx, as well as glucose-6-phosphatase [The activities of serum enzymes GPT and GOT are sensitive indicators of liver cell injury that may help recognize hepatic diseases. In this work, the results indicated  that admactivity . This stactivity . In this ability . Howeversphatase .APAP is biotransformed to NAPQI, which conjugates with GSH and depletes it, then NAPQI binds to various enzymes, causing mitochondrial dysfunction and oxidative stress . In thisS. odorifera.APAP induces hepatocyte damage by different pathways, one of which is the increase in reactive oxygen species (ROS), which is the final result of a chain failure of the defense system from the oxidative stress of the hepatocytes. Some enzymes regulate this oxidative stress, such as glutamate-cysteine ligase (GCLC) and heme oxygenase-1 (HO-1), whose expression is regulated by the transcription factor Nrf-2, which is normally found in the cytosol, bound to its Keap-1 inhibitor protein. It has been shown that in the presence of APAP, the expression of Keap-1 increases, which is why it intervenes in this ROS regulation system . One of S. odorifera and their oil could be a valid alternative to be used in the production of natural new ingredients and bioactive compounds [According to the current trend on the exploration of health-beneficial components from new resources, including by-products, the seeds of ompounds . Despiteompounds . NeverthThe nutritional characterization, chemical composition, and hepatoprotective activity of the kurugua seeds were studied. In general, they are oleaginous with 35% lipids and a high content of dietary fiber (34%). The oil is rich in polyunsaturated fatty acids, as the essential fatty acid linolenic (C18:3 ω3) is the major component.S. odorifera seeds.The antioxidant capacity and phenolic content were comparable to other parts of the fruit. A total of eleven compounds were tentatively identified, including flavonoids; mostly, quercetin derivatives and luteolin aglycon were observed. Phenolic acids caffeoyl hexoside and vanillic acid, and flavonoids quercetin hexoside rhamnoside, luteolin, quercetin dimethyl ether, quercetin pentoside rhamnoside and quercetin rhamnoside, are described for the first time in S. odorifera. The seeds of this fruit contain bioactive molecules that are known for their beneficial effect on health and could contribute to the antioxidant and hepatoprotective activities observed. This work opens a path to follow in terms of possible applications of these seeds, a new source of healthy food with potential nutraceutical properties, and which currently constitute waste, in order to make full use of the fruit. Furthermore, a hepatoprotective effect has been observed in the mouse model used in the methanolic extract of the seeds of


In mammals, the cerebellum plays an important role in movement control. Cellular research reveals that the cerebellum involves a variety of sub-cell types, including Golgi, granule, interneuron, and unipolar brush cells. The functional characteristics of cerebellar cells exhibit considerable differences among diverse mammalian species, reflecting a potential development and evolution of nervous system. In this study, we aimed to recognize the transcriptional differences between human and mouse cerebellum in four cerebellar sub-cell types by using single-cell sequencing data and machine learning methods. A total of 321,387 single-cell sequencing data were used. The 321,387 cells included 4 cell types, i.e., Golgi , granule , interneuron , and unipolar brush  cells. Our results showed that by using gene expression profiles as features, the optimal classification model could achieve very high even perfect performance for Golgi, granule, interneuron, and unipolar brush cells, respectively, suggesting a remarkable difference between the genomic profiles of human and mouse. Furthermore, a group of related genes and rules contributing to the classification was identified, which might provide helpful information for deepening the understanding of cerebellar cell heterogeneity and evolution. The cerebellum is like a big regulator and works by affecting the functions of brain, brainstem, and spinal cord at different levels . The cerThe cerebellum is thought to consist of Golgi cells, granule cells (GCs), interneuron cells, and unipolar brush cells (UBC). Cerebellar Golgi cells can receive dual excitatory signals, one of which comes from the mossy fibers of basal dendrites, and the other comes from the parallel fibers of apical dendrites. Golgi cells are inhibitory, and studies showed that the granular layer organization relies on feedforward and feedback inhibition cycles . The anahttps://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE165371), we use new computational methods to screen for characteristically expressed and important genes between human and mouse cerebellar cells that may affect the development and evolution of the central nervous system. We classified cerebellar cells into four different subtypes including Golgi cell, GC, interneuron cell and UBC. We have built and verified some classifiers that can identify key genes related to species-specific expression pattern and the potential evolutional trend in each cerebellar cell type. We use minimum redundancy and maximum relevance (mRMR) (On the basis of existing human and mouse cerebellar cortex single-cell transcriptomic data set (e (mRMR)  combinede (mRMR) , decisioe (mRMR) , random e (mRMR) , and Syne (mRMR)  approache (mRMR) . At the Our research is divided into four parts: 1. data collection, 2. feature analysis, 3. incremental feature selection and model building, and 4. feature interpretation. The process is shown in https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE165371). The total numbers of samples and features in the dataset are 321,387 and 74,593, respectively, which are composed of four different cell sample datasets, corresponding to four sell types: Golgi cell, GC, interneuron cell, and UBC. The breakdown of each dataset, including number of mouse cells, number of human cells, total number of cells and number of gene features, is provided in Single-cell profiling datasets are downloaded from the transcriptomic atlas of human and mice   is used In additional, we also employ other measurements, including sensitivity (SN) , specificity (SP), prediction accuracy (ACC), precision and F1-measure. They can be computed byThese measurements are provided for reference.In our study, 321,387 cerebellum cell samples were collected. These single-cell samples could be divided into four categories, i.e., Golgi cell , GC , interneuron cell , and UBC . In the original cell sample data, each cell sample was represented by expressions on lots of genes, which were quite difficult for machine learning analysis due to the dimensionality curse. Therefore, the Boruta filtering method was first used to do the optimal compression of features  for each of 4 cell datasets. After compression, each Golgi cell, GC, interneuron cell, and UBC was represented as a compressed vector of 1,276, 1,271, 1924, and 1,252 features, respectively. The gene ID corresponding to the feature in the sample vector could be found in Remaining features were analyzed by the mRMR method. An mRMR feature list was obtained for each dataset. Four feature lists are also provided in Performance Evaluation section. To clearly show the performance of DT and RF on different feature subsets, an IFS curve was plotted for each classification algorithm, as shown in x-axis represents the number of features in the subset and y-axis stands for the main measurement, MCC. The key information extracted from these IFS curves is listed in For each dataset, an mRMR feature list was obtained. Afterward, RF and DT classification algorithms were used to construct the classification models in the IFS method with a step size of one on the basis of such list. Each classification model was evaluated by ten-fold cross-validation. The predicted results were counted as measurements listed in When RF was used in the IFS method, it achieved perfect performance with MCC = 1.00000 when proper feature subsets were adopted. In detail, for Golgi cell, 518 top features in the mRMR feature list were used, whereas this number was 2, 100 and 28 for other three types of cells, respectively. These features constituted the optimal features for each dataset. Accordingly, an optimal RF classifier was built on each dataset using corresponding optimal features. Their detailed performance, including SN, SP, ACC, precision and F1-measure, is illustrated in Although the optimal RF classifiers yielded perfect performance, they cannot provide useful clues to uncover essential differences between mouse and human cerebellum cells because RF is a black-box algorithm. In view of this, DT was employed in this study, which can provide more clear insights to study mouse and human cerebellum cells. It can be observed from The optimal DT/RF classifiers constructed above shown good even perfect performance. This section elaborated that these results were not incidental. To this end, for each optimal classifier, we did the following test. According to the number of features in the optimal classifier, i.e., the number of optimal features, we randomly selected same number of features from all features. These selected features were used to represent mouse and human cerebellum cells. A classifier with DT or RF was built on such representation. Ten-fold cross-validation was employed to evaluate its performance. To give a full test, above procedures were conducted twenty times. Obtained MCC values were shown in a box plot, as illustrated Analysis of Significant Single-Genes section.Important genes for distinguishing human and mouse cerebellar cells based on the mRMR ranking are presented in Analysis of Combined-Gene Rules section, we would discuss these rules.Furthermore, we adopted the rule learning algorithm DT to generate combined-gene rules, interpret the classification rules of features. According to the optimal DT classifier on each dataset, a tree was learnt on all cell samples, which were represented by the optimal features of this DT classifier. Such tree was represented by some rules, which are listed in In this project, we used machine learning methods to explore the single-cell expression profile data of human and mouse cerebellar cells. Important single-genes and combined-gene rules of each cerebellar cell type for distinguishing these two mammalian species are created and shown in According to features used in the optimal RF classifiers, we identified 648 (518+2+100+28) considerable features with the mRMR method to distinguish human and mouse cerebellum cells. Next, we further introduced research evidence related to the most important features in each cerebellar cell type to confirm the reliability of previous forecasts.LINGO2) is identified as a member of the leucine-rich repeats (LRR) gene family. The expression of the LINGO2 gene in the hypothalamus and cerebral cortex hypothalamus is higher than that in other regions. The Lingo2 is in the top relevant feature with the mRMR method and has been linked with essential tremor (ET) and Parkinson’s syndrome  (LINGO2 mutant may be an important indicator of neurodegenerative diseases.The protein encoded by leucine-rich repeat and immunoglobulin (Ig) domain containing 2 (syndrome . ET is tdiseases . Studies < 0.05) . Our resUBE3A encodes the E3 ubiquitin protein ligase, which can bind to the ubiquitin of the E2-binding enzyme in the form of a thioester and then transfer ubiquitin to E2-binding enzyme substrate  receptors in synapses. Therefore, researchers inferred that AMPA dysregulation may be related to Angelman syndrome or other cognitive disorders  is a protein-coding gene, and its translation product is a member of the neuron cell surface protein family. The NLGN1 family can be used as specific ligands for β-neuroproteins, which may be related to the formation and remodeling of synapses. The NLGN1 protein interacts with neuroproteins to promote synaptic transmission signals and recruits and accumulates other synaptic proteins. Studies showed that NLGN1 can promote the de novo formation of synaptic structures in vitro and may participate in the regulation of excitatory synapses. The protein encoded by NLGN1 has hydrolase and protein dimerization activities and plays an important role in protein–protein interaction at the synapse and signal transmission process across the synapse. NLGN1 variants may result in autism and Asperger’s syndrome. We speculated that the differential expression pattern of NLGN1 in Golgi cells between human and mouse cerebellum may imply a potential functional evolution.Neuroligin 1  is identified as an important characteristic gene by the mRMR, and its encoded RNA binding protein affects embryonic development  family. Members of this family can promote cell mitosis and are closely related to other biological processes. The mutation of this gene is related to autosomal dominant-inherited brain ataxia  protein in hippocampal neurons  family, which can act as a cell adhesion molecule in the process of synaptogenesis and intercellular signaling. and fear . Researcucidated . NRXN3 ediseases . The chrficiency . A study smoking . CombiniANK2) belongs to the ankyrin family and connects integral membrane proteins with the cytoskeleton. Ankyrin is involved in cell proliferation and movement and the maintenance of special domains. ANK2 can promote the localization of ion transporters and channels and maintain the stability of cell membranes. For example, in cardiomyocytes, ANK2 can coordinate the assembly of ion exchangers to maintain and promote the targeting and stability of ion exchangers. In addition, in neonatal cardiomyocytes, ANK2 is indispensable for regulating the contraction rate. In the skeletal muscle, ANK2 is involved in the correct positioning of DMD and DCTN4 and in the formation and/or stabilization of microtubule subsets related to the ribs and neuromuscular junctions. In the rod-shaped photoreceptor, ANK2 participates in the coordinated expression of Na/K atpase, Na/Ca exchanger, and β-2-spectrin. In addition, ANK2 is involved in important life processes, such as endocytosis and intracellular protein transport. ANK2 variants can cause long QT syndrome four and arrhythmia syndrome  and/or guanine (cGMP) 3′,5′-cyclic phosphate in the 3′-cyclic phosphate bond. PDE1A can regulate the concentration of cyclic nucleotides in the cell and influence signal transduction. The cyclic nucleotide PDE has dual specificity for cAMP and cGMP and is involved in the regulation of some important physiological processes. PDE1A can bind calmodulin and cGMP, has higher affinity for cGMP than for cAMP, and occupies an important position in the GPCR and calcium signaling pathway. Current studies found that PDE1A9 is highly expressed in the brain tissue, but its expression may lead to functional changes depending on age. Studies showed that compared with young controls, the phosphorylation level of the transmembrane regulatory protein in the hippocampus of aged rats is significantly reduced (The phosphodiesterase (PDE) 1A gene encodes a Ca reduced , which mRGS6 may cause Hirschsprung’s disease 1, night blindness and congenital quiescence. RGS6-related pathways include GPCR signal transmission and protein metabolism. When the G protein surface receptor is activated, the G protein initiates a signal cascade in the host cell. The RGS protein inactivates the G protein and turns off this signaling cascade. RGS6 belongs to the R7 subfamily and regulates the G protein function, which is essential for the transmission of a variety of neurotransmitters and neuronal responses. Genetic variations in RGS6 may disrupt normal GPCR signals, leading to disease or subtle features. For example, studies reported that RGS6 abnormalities may be related to diseases, such as alcohol dependence, Parkinson’s syndrome, and neurological or affective disorders  belongs to the G protein signal transduction regulator protein family. The RGS6 protein is characterized by DEP and GGL domains. The latter is the G beta 5 interaction domain, and these proteins can activate the gtpase activity. Many alternatively spliced transcripts of this gene have long or short N-terminal domains, complete or incomplete GGL domains, and isotypes of different C-terminal domains. The RGS protein may regulate G protein-mediated signal transduction through negative feedback, thereby affecting the activity of neurons, cardiovascular system, and lymphocytes and may even increase the risk of cancer. Mutations in isorders . In humaisorders . RGS6 haisorders . ExistinWe built total 23 combined-gene rules through the DT method. A total of 8, 2, 2 and 11 decision rules are observed for distinguishing human from mouse cerebellum in Golgi cell, GC, interneuron cell, and UBC, respectively. Given the biological significance of these traits, how do we determine the stage of evolution and development on the basis of the expression of these traits? Here are some studies to introduce their experimental evidence.LINGO2 is one of the four important families related to the nervous system (LINGO1–4)  . This geult mice . The LINdiseases . When thThsd7b is another important gene involved in the decision rules by our analysis. The thrombospondin type 1 domain containing 7B (Thsd7b) is a protein-coding gene. Thsd7b is enriched in human brain regions especially the pons and medulla. Thsd7b is closely related to O-linked glycosylation, glycosylation diseases, and Ehlers–Danlos syndrome. Researchers found a correlation between Thsd7b and the formation of cisplatin resistance. A large number of studies on pancreatic cancer in Japan showed that the Thsd7b gene is significantly associated with the risk of pancreatic cancer. In addition, this gene is related to the prognosis of non-small cell lung cancer with chemotherapy intervention . At presThe RNA coding gene Malat1 belongs to the long noncoding RNA (lncRNA) category. lncRNA is closely related to diseases, such as stroke  and ischA relatively higher expression of Ccdc85a in UBCs was required to indicate human cerebellum in decision rules. The protein-coding gene coiled-coil domain containing 85A (Ccdc85a) is expressed in various brain regions especially in the cerebral cortex. Diseases associated with Ccdc85a include hydrocephalus. Studies confirmed that the Ccdc85a protein is required in the AppNL-F interaction group. The results of colocalization analysis indicate that the Ccdc85a protein may endogenously regulate the function of the amyloid β-protein. In the early stage of Alzheimer’s disease, the upregulation of Ccdc85a expression may be a compensation for the increase in amyloid β-protein and the elimination of amyloid β-protein metabolism. These findings suggest that Ccdc85a may play an important role in nervous system development and evolution, and become a new target and biomarker for clinical intervention in neurological dysfunction diseases .We use the mRMR feature screening method to conduct an in-depth analysis of the existing single-cell transcriptome data set and select the key and characteristically expressed genes. Subsequently, we use DT and SMOTE tools to determine the expression rules of characteristic genes. In the end, we obtain key genes that may be related to evolution and neurodevelopment and confirm the decision-making rules which reflect the heterogeneity between species in different cerebellar cell types. Our analysis results are consistent with many existing research conclusions, but the specific pathogenic molecular mechanism of each characteristic gene needs further verification. Overall, this research has obtained representative species evolution genes and their expression differences in various cerebellar cells. The remarkable potential of these features and rules in studying species evolution and are highlighted and provide insights into new key genes. The excellent performance of our classifiers can be attributed to the strong specificity of gene expression at species and tissue levels, which can significantly distinguish human and mouse. In addition, our research methods and strategies have a good guiding role in exploring genetic evolution. Therefore, the characteristic genes we have identified can be used to identify specific cell groups and the evolutionary level of species and can be regarded as biological indicators to provide research directions for disease-related molecular mechanisms.


Context: Gut dysbiosis has been proposed as one of pathologies in patients with Alzheimer’s disease (AD) spectrum. Despite such enthusiasm, the relevant results remain substantially controversial.Objective: A systematic review and meta-analysis were performed to investigate the differences of gut microbiota (GM) between patients with AD spectrum (including mild cognitive impairment [MCI] and AD) and healthy controls (HC).Data sources: PubMed, MEDLINE, Scopus, and Cochrane Library from January 2000 to August 2021.Eligibility criteria for study selection: Observational trials and pre-intervention data of intervention trials that investigated the abundance of GM in patients with AD spectrum and HC.Data extraction and synthesis: Two reviewers independently identified articles, extracted data, and evaluated the risk of bias. The effect sizes were performed by a random-effect, inverse-variance weighted model. The effects of different countries and of clinical stages on GM abundance were also examined.Proteobacteria, Bifidobacterium and Phascolarctobacterium, but less abundance of Firmicutes, Clostridiaceae, Lachnospiraceae and Rikenellaceae in patients with AD spectrum as compared with HC. The profiles of abundance of Alistipes and Bacteroides in HC and AD spectrum were differentially affected by countries. Finally, when considering clinical stage as a moderator, the comparisons of abundance in Clostridiaceae and Phascolarctobacterium showed large effect sizes, with gradient changes from MCI to AD stage.Results: 11 studies consisting of 378 HC and 427 patients with AD spectrum were included in the meta-analysis. Patients with AD, but not MCI, showed significantly reduced GM diversity as compared to HC. We also found more abundance of Limitations: The inclusion of studies originating only from China and the U.S. was a possible limitation.Conclusions: Patients with AD spectrum demonstrated altered GM abundance, which was differentially mediated by countries and clinical stages. Previous studies have suggested that amyloid-beta (Aβ) peptide deposition in the brain is an early neural change in patients with Alzheimer’s disease (AD) , 2. HoweThere are thousands of microbes residing in the human gut, which involves crucial functions for individual physiology and development . MoreoveMore recently, the changes in diversity and equilibrium of GM have attracted much attention in many neurological and psychiatric disorders. When the intestinal ecosystem is abnormally altered, the composition of GM becomes imbalanced . This dysbiotic pattern prompts the host to establish a disease-related microbial community, leading to leaky intestine and BBB, as well as bacterial translocation . Animal Bacteroidetes and reduced Actinobacteria in the phylum level [Bacteroidetes and increased Actinobacteria) [It is interesting to note that the composition of GM is distinct from country to country. For instance, a previous study from U.S. showed an alteration of GM in patients with AD, comprising increased um level . In contacteria) . In addiacteria) , 26, 29.acteria) . Thus, iTo the best of our knowledge, no statistical review of GM structure in patients with AD spectrum has been performed. Therefore, the purpose of this study was two-fold. First, we aimed to determine the differences of GM diversity and abundance between the patients with AD spectrum and healthy controls (HC). Second, we further examined the potential effects of different countries and clinical stages on GM abundance.This meta-analysis followed the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines . We condp values, median, maximum, minimum, etc.) to estimate effect sizes. Studies of case reports, systematic reviews and animal research were excluded.Two authors (CCH and CHC) independently screened and identified the full texts that met the following inclusion criteria: (1) they were peer-reviewed articles written in English; (2) GM diversity and abundance was compared between patients with AD spectrum and HC; (3) GM was derived from stool samples; (4) only pre-intervention data were collected from the intervention studies; (5) the GM strains were investigated by at least three studies; (6) adequate statistical data  and differences of GM abundance between the patients with AD spectrum and HC. The secondary outcomes consisted of the effects of different countries and clinical stages on GM abundance.The necessary data of each study regarding the number of participants, age, body mass index, diabetes mellitus, dietary assessments, diversity and abundance of GM, etc. were extracted by CCH and checked by CHC. Median, minimum, maximum, or 95% confidence interval (CI) from 5 studies were estimated from the bar graphs –28, 35. Two authors (CCH and CHC) independently assessed the risk of bias in each included study using the Risk of Bias Assessment Tool for Nonrandomized Studies (RoBANS) , which e2. Additionally, the inclusion of outliers may result in bias and significantly influence the pooled effect sizes [The Comprehensive Meta-Analysis Version 3 software  was applied to calculate the effect sizes with a random-effect, inverse-variance weighted model. Postulating that departures from Gaussian distributions were not serious, we used previously reported conversion equations  to estimct sizes , 39. We p < 0.05.Potential publication bias of each GM abundance was quantitatively assessed by Begg and Mazumdar rank correlation  and EggeData available on request from the corresponding authors.By the comprehensive literature search, 164 relevant articles were yielded when duplications were excluded. After the review of the titles and abstracts, 14 studies were potentially eligible for our meta-analysis. After carefully examining the full texts, three additional studies were removed: two did not provide sufficient data , 43 and p = 0.030; n = 5) and Simpson index .Among the indices of α diversity, Shannon index and Simpson index were most frequently measured in our included articles. There were no significant differences of α diversity between HC and AD spectrum . HoweverAmong all the included articles except for three studies , 35, 47,Proteobacteria  in AD spectrum versus HC. No significant difference was observed for Firmicutes between AD spectrum and HC . After the exclusion of two outliers [Firmicutes  was observed in AD spectrum versus HC. The abundance of Bacteroidetes and Actinobacteria did not show obvious difference between AD spectrum and HC.In terms of the phylum level , the resoutliers , a signiBacteroidia, Clostridia, and Gammaproteobacteria did not show significant differences between AD spectrum and HC.In terms of the class level , the abuBacteroidales, Clostridiales, and Enterobacteriale were not significant in patients with AD spectrum as compared with HC.In terms of the order level , the difp < 0.001, n = 4) for the Clostridiaceae, suggesting a less abundant level of this GM strain in AD spectrum versus HC. The difference of the abundance in Lachnospiraceae was not significant between AD spectrum and HC . After the exclusion of two outliers [Lachnospiraceae  in AD spectrum versus HC. The abundance of Rikenellaceae did not show obvious differences between these two groups . After the exclusion of one outlier [p = 0.002; n = 3), suggesting less abundant of this GM strain in AD spectrum versus HC. No obvious differences were found for Bacteroidaceae, Enterobacteriaceae, and Ruminococcaceae between these two groups.In terms of the family level , the Hedoutliers , we disc outlier , the pooPhascolarctobacterium  was found in AD spectrum versus HC. The abundance of Bifidobacterium did not show obvious differences between AD spectrum and HC . After the exclusion of one outlier [Bifidobacterium  was detected in AD spectrum versus HC. The abundance of Alistipes, Bacteroides, and Blautia did not show significant differences between these two groups.In terms of the genus level , a more  outlier , a signiBacteroides was not significant in the comparison between HC and AD spectrum (n = 2) and for China (n = 6) were −0.781  and 0.027 , respectively. In brief, compared with HC, the American patients with AD spectrum showed more abundance of Bacteroides, but such as pattern was not found for the Chinese patients , suggesting more abundant of this GM strain for American patients with AD spectrum. However, the overall effect size for China was 0.792 , suggesting less abundant of this GM strain for Chinese patients with AD spectrum , but not in the comparison between HC and MCI . Similar trend of abundance was found in the Phascolarctobacterium, revealing that the abundance of this GM was significantly increased in patients with MCI versus HC   .Clostridiaceae in the patients with MCI , which was more pronounced in the patients with AD   .The quality of the included studies is summarized in Firmicutes, Gammaproteobacteria, Bacteroidales, and Enterobacteriale , and the abundance of Proteobacteria increased along with worse memory dysfunction [Proteobacteria was supported by previous literature.The bacteria . Of noteytokines . It has function , 52. TakFirmicutes serves a connection with inflammatory effects, the modulation of metabolic function and the production of SCFAs [Firmicutes was associated with the development of obesity and type 2 diabetes [Firmicutes was positively associated with the performance of executive function, suggesting that it is a kind of beneficial GM strain for the humans [The phylum of SCFAs , 54. Sevdiabetes , 56. It diabetes , 58. Fure humans , 59.Clostridiaceae performs a vital function on producing SCFAs, which can offer fuel sources for the host and protective effects on permeability of gut and BBB [Clostridiaceae was the producers of indole-3-propionic acid, which could prevent oxidative injuries of primary neurons from Aβ [Clostridiaceae may impair cognitive function and intrinsic brain activities as evident by the results of resting-state functional magnetic resonance imaging [Lachnospiraceae is the producer of butyrate, which participates in anti-inflammatory reactions, and in turn maintains the gut barrier [Lachnospiraceae would result in insulin resistance, disruptions of homeostasis within the CNS and exacerbation of AD neuropathology [Lachnospiraceae was considered as an advantageous GM strain.The family  and BBB . Moreove from Aβ . Decreas imaging . Corresp barrier , 63. A nathology , 64. HenBifidobacterium is involved in the production of acetate and γ-aminobutyric acid, which has neuroprotective effects on the hosts [Bifidobacterium members have been associated with anti-inflammatory effects and reduced permeability of gut [Bifidobacterium obviously alleviated the development of AD pathologies [Bifidobacterium ameliorated cognitive impairments in patients with AD [Bifidobacterium was found in subjects with AD spectrum. This finding might imply the potential gut-brain self-preventative mechanism to rebuild intestinal homeostasis [The genus he hosts , 66. It y of gut . In addihologies . It has  with AD . Howevereostasis . NeverthBacteroides and Alistipes in AD spectrum did not show obvious differences as compared with HC. These non-significant results were potentially owing to large heterogeneities among the included studies. When considering the country  as a moderator, our meta-analysis demonstrated an overgrowth of Bacteroides and Alistipes in American patients; however, this pattern was not observed in Chinese patients. A previous meta-analysis study has found that Chinese patients with IBS did not show obvious changes of abundance in Bacteroides compared to HC; inversely, enriched abundance of Bacteroides was observed in patients with IBS from other areas such as U.S. and Finland [Bacteroidetes (genus Bacteroides) members might be a possible signature for AD spectrum since certain members of this phylum are opportunistic pathogens, especially Bacteroides fragilis (B. fragilis) [B. fragilis can be divided into two strains: non-toxigenic B. fragilis (NTBF) and enterotoxigenic B. fragilis (ETBF). NTBF participates in suppression of colitis and strengthening gut barrier; in contrast, ETBF secretes B. fragilis toxins and is highly associated with inflammatory bowel disease [Alistipes abundance in patients with AD spectrum. It will be a valuable issue for future studies to validate our meta-analysis finding.The composition and abundance of GM may be influenced by many factors such as age, geographical areas, dietary pattern, and chronic stress. In general, the random-effect sizes for  Finland . It has ragilis) . Interes disease , 72. Up Proteobacteria, and Phascolarctobacterium were gradually enhanced from MCI to AD stage. The pro-inflammatory Proteobacteria has been suggested as a predictor for AD pathogenesis [Clostridiaceae was found to be progressively reduced from MCI to AD patients. The abundance of beneficial Clostridiaceae has been reported to be significantly decreased in patients with AD, suggesting that it is a distinctive biomarker in predicting the development of AD. In addition, the results of some GM strains in the comparisons of HC versus MCI and HC versus AD did not show gradient changes. The abundance of Enterobacteriales was significantly increased in patients with AD, but a little decreased in patients with MCI. This non-gradient pattern from HC to AD was in line with a previous study [Rikenellaceae was significantly reduced in patients with MCI, but a little enhanced in AD patients, suggesting that the association between Rikenellaceae and AD pathogenesis needs further exploration.We considered the clinical stage as another moderator in the present study. Compared to HC, ogenesis , 35. In us study , 35. TheIn spite of these interesting findings, our study was not without limitations. First, the generalization of these results to other populations is questionable because the vast majority of included studies originated from just two countries. Second, many of the studies suffer from significant sources of bias. There were obvious statistical heterogeneities among the included studies, which could be attributed to differences in dietary pattern, geographical background, center settings, and inclusion criteria of AD spectrum including various regimens, medication doses, illness duration, etc. For example, only three studies , 46, 47 Proteobacteria, Bifidobacterium and Phascolarctobacterium were significantly higher abundant in patients with AD spectrum, whereas Firmicutes, Clostridiaceae, Lachnospiraceae and Rikenellaceae were significantly lower in patients with AD spectrum compared to HC. Moreover, the dysbiosis of these GM can be viewed as an environmental factor of the AD initiation and progression. In the future, a larger cohort study is needed to further examine the differences of GM in AD spectrum.In conclusion, we demonstrated that Supplementary Tables


Stroke incidence is decreasing in most developing countries. However, worrisome trends of an increase in the younger population have been described.To investigate sex differences and longitudinal changes in ischemic stroke regarding incidence, cardiovascular risk factors, and outcome, in the young.This is an observational study based on the data from the Swedish national stroke registry, Riksstroke. Patients, 18–54 years of age, having ischemic stroke between 2005 and 2018 were included, resulting in a study population of 16,210 patients.P < 0.001). After an initial increase, the incidence stabilized and then decreased, resulting in a similar level in 2018 as in 2005. Atrial fibrillation, diabetes, and usage of anti-hypertensives at stroke onset were more common among men and did not change over time. Smoking was common and slightly more so in women, but with a reduced prevalence in both men and women during the study period. Dependency in Activities of Daily Living (ADL) and case fatality showed no clear trends or sex differences.The incidence was higher in men than in women (30.6 vs. 19.1 per 100,000, The results show that there are sex differences in ischemic stroke in the younger age group regarding incidence and vascular risk factors, particularly smoking. Temporal trends in stroke incidence are difficult to interpret as fluctuations are substantial, largely due to stroke being quite uncommon in the younger population. Age and sex are important non-modifiable risk factors for stroke. Women are older at the time of stroke onset but have a longer life expectancy . Thus, tA trend of increasing incidence of stroke in the younger age group in Sweden has previously been described. One such report by Rosengren et al. in 2013 based on Swedish Hospital Discharge and Cause of Death (CDR) registries researched cases of ischemic stroke from 1987 to 2010. The study showed that there was a continuous increase in the incidence of ischemic stroke for both men and women in the age group 18 to 44 years, although slightly larger among women   , previous history of stroke (yes or no), smoking, and atrial fibrillation are recorded in Riksstroke. Smoking is defined as the consumption of one cigarette or more per day, or if the patient had quit during the 3 months leading up to the stroke attack. The date of death was retrieved from the Cause of Death Register , giving statistics of 90 days-CF. Dependency in ADL was based on the patient's reported outcome  3 months after stroke.Age (years) was non-normally distributed and described with medians and quartiles (Q1 and Q3). Binary variables were presented by proportions with approximately 95% CIs. Group comparisons were made with the Mann-Whitney test for age and Pearson's chi-squared test for categorical variables.2. In addition, the sex-by-year interaction was included to test if the time trend differed between men and women.The stroke incidence was analyzed by Poisson regression, with an offset equal to the natural logarithm of the size of the general population . The model included the independent variables year, sex, and sex-by-year interaction. Risk factors and outcomes were analyzed by binary logistic regression. The models included the independent variables sex, year of stroke, age, and agep < 0.05 was considered statistically significant. Statistical analysis was performed using IBM SPSS® statistics version 26.0 for Windows , and SAS software, Version 9.4 of the SAS System for Windows .A This study was approved by the Swedish Ethical Review Authority (reference no. 2018-02777). In accordance with the Personal Data Act (Swedish law No. SFS 1998:204), no informed consent is needed to collect data from medical charts and inpatient records for quality registers but there is information and an opt-out possibility.P < 0.001, P < 0.001) similarly in men and women (P for sex-by-year interaction = 0.278). There was a slight increase between 2005 and 2010 the trend levels off after this, and in 2018 the incidence rates for both men and women were almost at the same level as in 2005.In all, 16,210 persons were included . Throughout 2005–2018, the estimated stroke incidence was higher in men than in women , from 38.3% in 2005 to 25.8% in 2018 (P = 0.018).Smoking decreased during the study period  was 28/100, 000 in adults 20–44 years of age . A recenP < 0.001) , it has more than halved, from 10 to 4% . In many–29 years< 0.001) . Smoking< 0.001) . In a 27< 0.001) . The dif< 0.001) .Stroke is uncommon in younger people and thus small changes in the number of events can lead to large fluctuations in incidence. However, it shows that the worrisome rapidly increasing stroke trend particularly in young women described by Rosengren et al. in 2013 has not continued . In contA study based on insurance claims data 2001-2014 from the US showed an incidence rate ratio of 0.7 for men aged 25–44 years compared with women . This maPrevious reports have overall shown varying results regarding sex differences in fatality in stroke. A large meta-analysis from 2013 found an overall hazard risk of 1.13 for women compared with men but was unable to analyze age-adjusted differences due to limited data . A studyn = 16,210) of the unselected cohort and high coverage of cases during the entire study period. There was also a very low number of missing values. As in all observational studies, it is difficult to establish causation between measures and outcomes, and there may be unmeasured confounding not corrected for.The strengths of this study are firstly the large sample size . Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.KN, ME, and MvE contributed to conception and design of the study. ME organized the database. KN performed the statistical analysis with support of ME and MvE. KN wrote the first draft of the manuscript under supervision of MvE. All authors contributed to manuscript revision, read, and approved the submitted version.Örebro University funded open access publication fees.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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.