Engineered Enucleated Mesenchymal Stem Cells Regulating Immune Microenvironment and Promoting Wound Healing.

Persistent excessive inflammation caused by neutrophil and macrophage dysfunction in the wound bed leads to refractory response during wound healing. However, previous studies using cytokines or drugs often suffer from short half-lives and limited targeting, resulting in unsatisfactory therapeutic effects. Herein, the enucleated mesenchymal stem cell is engineered by aptamer bioorthogonal chemistry to modify the cell membrane and mRNA loading in the cell cytoplasm as a novel delivery vector (Cargocyte) with accurate targeting and sustained cytokine secretion. Cargocytes can successfully reduce NETosis by targeting the nuclear chromatin protein DEK protein with aptamers and sustaining interleukin (IL)-4 expression to overcome the challenges associated with the high cost and short half-life of IL-4 protein and significantly prevent the transition of macrophages into the M1 phenotype. Therapeutic effects have been demonstrated in murine and porcine wound models and have powerful potential to improve wound immune microenvironments effectively. Overall, the use of engineered enucleated mesenchymal stem cells as a delivery system may be a promising approach for wound healing.

Microtia, Branchial Cleft Fistula, and Tetralogy of Fallot: A Possible Association.

When searching over associations between congenital ear abnormalities, especially microtia and affiliated deformities like cleft lip or palate and congenital heart diseases, some clinical analysis and genetic theories are found. A 10-year-old boy sent to the plastic surgery hospital was puzzled by a congenital anterior auricular fistula with fluid trace for more than 9 years. The preoperative diagnoses were branchial cleft fistula and congenital left ear deformity with postoperation of TOF. By browsing over studies on genetic concerns and clinical performance, it may be attributed to a possible association between microtia, branchial cleft fistula, and tetralogy of Fallot, though whose fundamental mechanisms remain concerned.

Knowledge, attitudes, and practices (KAP) toward seasonal influenza vaccine among college students under the COVID-19 pandemic in South China.

BACKGROUND: The control measures of the coronavirus disease 2019 (COVID-19) pandemic had influenced the activity of the influenza virus, and we were wondering the knowledge, attitudes, and practices (KAP) toward seasonal influenza vaccine among college students were having at the context of the COVID-19 pandemic. METHODS: Online questionnaire survey of the college students was conducted and the data was collected anonymously, cross-sectional study were used to describe the distribution of the KAP. RESULTS: There were 815 respondents in our study. Most participants have a high recognition of the effectiveness and safety of the influenza vaccine. However, a low awareness rate of influenza vaccine knowledge and vaccination rate (18%) against influenza was observed among college students. The education level and major would have a higher weight on the influence of KAP among the college students. Binary logistic regression analysis showed that the sex (OR = 2.163, p < .001), age (OR = 2.242, p < .001), heard of the influenza vaccine (OR = 2.655, p = .014), and "How necessary do you think vaccinating every year is?" (OR = 3.947, p < .001) of the college students were the main factors that affect the KAP on influenza vaccination. CONCLUSIONS: Our study provided an insight into the KAP of influenza vaccine among college students in South China. The vaccination rate and acceptability of influenza vaccine in college students are higher than that in the whole population.

Diagnostic value of BinaxNOW antigen card for Severe Acute Respiratory Syndrome Coronavirus 2.

Rapid laboratory detection is remarkably crucial to diagnosing coronavirus disease 2019 (COVID-19) infection, due to whose outbreak causes to the world pandemic. The BinaxNOW antigen card (BinaxNOW) is a simple, effective, and cheap tool to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The meta-analysis in this study was conducted to evaluate the diagnostic performance of BinaxNOW for SARS-CoV-2. The researchers independently retrieved the related databases (PubMed, Embase, Web of Science, Cochrane Library) before May 1st, 2021, and extracted the relevant data based on the early inclusion/exclusion criterion. Quality Assessment of Diagnostic Accuracy Study-2 was used to evaluate the quality of the enrolled studies. Stata 16.0, Meta-DiSc 1.4, and Review Manager 5.3 were used to generate analytical data for the statistical analysis. 59 sets of data were identified from the seven studies included in this meta-analysis. The combined sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and their 95% confidence intervals were 0.77 (0.76 to 0.79), 0.99 (0.99 to 0.99), 65.72 (48.23 to 89.56), 0.23 (0.19 to 0.28), and 461.10 (281.55 to 755.13), respectively. The area under curve was 0.9910 in the summary receiver operating characteristic curve. BinaxNOW is beneficial for symptomatic patients' onset within 7 days. CT value and testing site may be the heterogeneity source of BinaxNOW accuracy. Moreover, this technology has an efficient performance for diagnosing COVID-19, especially in patients with heavy viral load. BinaxNOW may become a practical tool for large-scale or at-home use for COVID-19 in the post-pandemic era.Highlights● Pooled sensitivity with 0.77 and specificity with 0.99 in the BinaxNOW assay.● CT value and testing site may be the heterogeneity source of BinaxNOW accuracy.● BinaxNOW is beneficial for symptomatic patients' onset within 7 days.● BinaxNOW may become a practical tool for large-scale or at-home use for COVID-19.

A novel autophagy-related long non-coding RNAs prognostic risk score for clear cell renal cell carcinoma.

BACKGROUND: As the main histological subtype of renal cell carcinoma, clear cell renal cell carcinoma (ccRCC) places a heavy burden on health worldwide. Autophagy-related long non-coding RNAs (ARlncRs) have shown tremendous potential as prognostic signatures in several studies, but the relationship between them and ccRCC still has to be demonstrated. METHODS: The RNA-sequencing and clinical characteristics of 483 ccRCC patients were downloaded download from the Cancer Genome Atlas and International Cancer Genome Consortium. ARlncRs were determined by Pearson correlation analysis. Univariate and multivariate Cox regression analyses were applied to establish a risk score model. A nomogram was constructed considering independent prognostic factors. The Harrell concordance index calibration curve and the receiver operating characteristic analysis were utilized to evaluate the nomogram. Furthermore, functional enrichment analysis was used for differentially expressed genes between the two groups of high- and low-risk scores. RESULTS: A total of 9 SARlncRs were established as a risk score model. The Kaplan-Meier survival curve, principal component analysis, and subgroup analysis showed that low overall survival of patients was associated with high-risk scores. Age, M stage, and risk score were identified as independent prognostic factors to establish a nomogram, whose concordance index in the training cohort, internal validation, and external ICGC cohort was 0.793, 0.671, and 0.668 respectively. The area under the curve for 5-year OS prediction in the training cohort, internal validation, and external ICGC cohort was 0.840, 0.706, and 0.708, respectively. GO analysis and KEGG analysis of DEGs demonstrated that immune- and inflammatory-related pathways are likely to be critically involved in the progress of ccRCC. CONCLUSIONS: We established and validated a novel ARlncRs prognostic risk model which is valuable as a potential therapeutic target and prognosis indicator for ccRCC. A nomogram including the risk model is a promising clinical tool for outcomes prediction of ccRCC patients and further formulation of individualized strategy.

A Novel Insight into Paraptosis-Related Classification and Signature in Lower-Grade Gliomas.

Lower-grade gliomas (LGG) are the most common intracranial malignancies that readily evolve to high-grade gliomas and increase drug resistance. Paraptosis is defined as a nonapoptotic form of programmed cell death, which is gradually focused on patients with gliomas to develop treatment options. However, the specific role of paraptosis in LGG and its correlation is still vague. In this study, we first establish the novel paraptosis-based prognostic model for LGG patients. The relevant data of LGG patients were acquired from The Cancer Genome Atlas database, and we found that LGG patients could be divided into three different clusters based on paraptosis via consensus cluster analysis. Through least absolute shrinkage and selection operator regression analysis and multivariate Cox regression analysis, 10-paraptosis-related gene (PRG) signatures (CDK4, TNK2, DSTYK, CDKN3, CCR4, CASP9, HSPA5, RGR, LPAR1, and PDCD6IP) were identified to separate LGG patients into high- and low-risk subgroups successfully. The Kaplan-Meier analysis and time-dependent receiver-operating characteristic showed that the performances of predicting overall survival (OS) were dramatically high. The parallel results were reappeared and verified by using the Chinese Glioma Genome Atlas and Gene Expression Omnibus databases. Independent prognostic analysis and nomogram construction implied that risk scores could be considered the independent factor to predict OS. Enrichment analysis indicated that immune-related biological processes were generally enriched, and different immune statuses were highly infiltrated in high-risk group. We also confirmed the potential relationship of 10-PRG signatures and drug sensitivity of Food and Drug Administration-approved drugs. In summary, our findings provide a novel knowledge of paraptosis status and crucial direction to further explore the role of PRG signatures in LGG.

A novel molecular subtypes and risk model based on inflammatory response-related lncrnas for bladder cancer.

BACKGROUND: Inflammation and long noncoding RNAs (lncRNAs) are gradually becoming important in the development of bladder cancer (BC). Nevertheless, the potential of inflammatory response-related lncRNAs (IRRlncRNAs) as a prognostic signature remains unexplored in BC. METHODS: The Cancer Genome Atlas (TCGA) provided RNA expression profiles and clinical information of BC samples, and GSEA Molecular Signatures database provided 1171 inflammation-related genes. IRRlncRNAs were identified using Pearson correlation analysis. After that, consensus clustering was performed to form molecular subtypes. After performing least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses, a risk model constructed based on the prognostic IRRlncRNAs was validated in an independent cohort. Kaplan-Meier (KM) analysis, univariate and multivariate Cox regression, clinical stratification analysis, and time-dependent receiver operating characteristic (ROC) curves were utilized to assess clinical effectiveness and accuracy of the risk model. In clusters and risk model, functional enrichment was investigated using GSEA and GSVA, and immune cell infiltration analysis was demonstrated by ESTIMATE and CIBERSORT analysis. RESULTS: A total of 174 prognostic IRRlncRNAs were confirmed, and 406 samples were divided into 2 clusters, with cluster 2 having a significantly inferior prognosis. Moreover, cluster 2 exhibited a higher ESTIMATE score, immune infiltration, and PD-L1 expression, with close relationships with the inflammatory response. Further, 12 IRRlncRNAs were identified and applied to construct the risk model and divide BC samples into low-risk and high-risk groups successfully. KM, ROC, and clinical stratification analysis demonstrated that the risk model performed well in predicting prognosis. The risk score was identified as an independently significant indicator, enriched in immune, cell cycle, and apoptosis-related pathways, and correlated with 9 immune cells. CONCLUSION: We developed an inflammatory response-related subtypes and steady prognostic risk model based on 12 IRRlncRNAs, which was valuable for individual prognostic prediction and stratification and outfitted new insight into inflammatory response in BC.

Construction of A Novel Ferroptosis-related Prognostic Risk Signature for Survival Prediction in Clear Cell Renal Cell Carcinoma Patients.

PURPOSE: Targeted ferroptosis is a reliable therapy to inhibit tumor growth and enhance immunotherapy. This study generated a novel prognostic risk signature based on ferroptosis-related genes (FRGs), and explored the ability in clinic for clear cell renal cell carcinoma (ccRCC). MATERIALS AND METHODS: The expression profile of mRNA and FRGs for ccRCC patients were exacted from The Cancer Genome Atlas (TCGA) database. A ferroptosis-related prognostic risk signature was constructed based on univariable and multivariable Cox-regression analysis. Kaplan-Meier (KM) survival curves and receiver operating characteristic (ROC) curves were performed to access prognostic value of riskscore. A nomogram integrating riskscore and clinical features was established to predict overall survival (OS). Based on differentially expressed genes between high- and low-OS groups with 5-year OS, function enrichment analyses and single-sample gene set enrichment analysis (ssGSEA) were investigated to immune status. RESULTS: A 9-FRGs prognostic risk signature was constructed based on 37 differentially expressed FRGs. ROC and KM curves showed that riskscore has excellent reliability and predictive ability; Cox regression disclosed the riskscore as an independent prognosis for ccRCC patients. Then, the C-index and calibration curve demonstrated the good performance of nomogram in training and validation cohort, and its predictive ability better than other features. Immune-related biological processes were enriched by function enrichment analysis, and the immune-related cells and functions were differential by ssGSEA between high- and low-OS groups. CONCLUSION: Our study identified and verified a novel 9-FRGs prognostic signature and nomogram to predict OS, providing a novel sight to explore targeted therapy of ferroptosis for ccRCC.