Integrative machine learning and neural networks for identifying PANoptosis-related lncRNA molecular subtypes and constructing a predictive model for head and neck squamous cell carcinoma.

PURPOSE: PANoptosis is considered a novel type of cell death that plays important roles in tumor progression. In this study, we applied machine learning algorithms to explore the relationships between PANoptosis-related lncRNAs (PRLs) and head and neck squamous cell carcinoma (HNSCC) and established a neural network model for prognostic prediction. METHODS: Information about the HNSCC cohort was downloaded from the TCGA database, and the differentially expressed prognostic PRLs between tumor and normal samples were assessed in patients with different tumor subtypes via nonnegative matrix factorization (NMF) analysis. Subsequently, five kinds of machine-learning algorithms were used to select the core PRLs across the subtypes, and the interactive features were pooled into a neural network model to establish a PRL-related risk score (PLRS) system. Survival differences were compared via Kaplan‒Meier analysis, and the predictive effects were assessed with the areas under the ROCs. Moreover, functional enrichment analysis, immune infiltration, tumor mutation burden (TMB) and clinical therapeutic response were also conducted to further evaluate the novel predictive model. RESULTS: A total of 347 PRLs were identified, 225 of which were differentially expressed between tumor and normal samples. Patients were divided into two clusters via NMF analysis, in which cluster 1 had a better prognosis and more immune cells and functional infiltrates. With the application of five machine learning algorithms, we selected 13 interactive PRLs to construct the predictive model. The AUCs for the ROCs in the entire set were 0.735, 0.740 and 0.723, respectively. Patients in the low-PLRS group exhibited a better prognosis, greater immune cell enrichment, greater immune function activation, lower TMB and greater sensitivity to immunotherapy. CONCLUSION: In this study, we established a novel neural network prognostic model to predict survival and identify tumor subtypes in HNSCC patients. This novel assessment system is useful for prediction, providing ideas for clinical treatment.

Multiomics data analyses to identify SLC25A17 as a novel biomarker to predict the prognosis and immune microenvironment in head and neck squamous cell carcinoma.

OBJECTIVE: This study aims to explore the predictive value of SLC25A17 in the prognosis and tumor microenvironment (TME) of patients with head and neck squamous cell carcinoma (HNSCC) and to provide ideas for individual clinical treatment. METHODS: A pancancer analysis of the differential expression of SLC25A17 among different tumors was first conducted via the TIMER 2.0 database. Subsequently, the expression of SLC25A17 and related clinical information of HNSCC patients were obtained from the TCGA database, and patients were divided into two groups according to the median value of SLC25A17 expression. K‒M survival analysis was conducted to compare the overall survival (OS) and progression-free survival (PFS) between the groups. The Wilcoxon test was used to compare the distribution of SLC25A17 in different clinical characteristics, and univariate Cox and multivariate Cox analyses were performed to analyze independent prognostic factors to establish a predictive nomogram. Calibration curves were generated to verify the reliability of predicting 1-year, 3-year and 5-year survival rates and another cohort (GSE65858) was used for external validation. Gene set enrichment analysis was conducted to compare the enriched pathways, and the immune microenvironment was assessed using the CIBERSORT and estimate packages. Furthermore, the expression levels of SLC25A17 in immune cells were also analyzed with single-cell RNA-seq via the TISCH. Moreover, the immunotherapeutic response and chemotherapy drug sensitivity were compared between the two groups to guide precise treatment. The TIDE database was applied to predict the possibility of immune escape in the TCGA-HNSC cohort. RESULTS: Compared with normal samples, the expression of SLC25A17 was much higher in HNSCC tumor samples. For patients with high SLC25A17 expression, the OS and PFS were shorter than those with low SLC25A17 expression, indicating a worse prognosis. The expression of SLC25A17 varied in different clinical features. Univariate Cox and multivariate COX analyses showed that SLC25A17, age, and lymph node metastasis are independent prognostic risk factors for HNSCC, and the survival prediction model based on these factors had reliable predictive value. Patients in the low-expression group exhibited more immune cell infiltration, higher TME scores, higher IPS scores and lower TIDE scores than those in the high-expression groups, suggesting better immunotherapeutic response with lower SLC25A17 expression. Moreover, patients in the high-expression group were more sensitive to chemotherapy. CONCLUSIONS: SLC25A17 can effectively predict the prognosis of HNSCC patients and could be a precise individual-targeted indicator for the treatment of HNSCC patients.

5-Methylcytosine-related lncRNAs: predicting prognosis and identifying hot and cold tumor subtypes in head and neck squamous cell carcinoma.

BACKGROUND: 5-Methylcytosine (m5C) methylation is recognized as an mRNA modification that participates in biological progression by regulating related lncRNAs. In this research, we explored the relationship between m5C-related lncRNAs (mrlncRNAs) and head and neck squamous cell carcinoma (HNSCC) to establish a predictive model. METHODS: RNA sequencing and related information were obtained from the TCGA database, and patients were divided into two sets to establish and verify the risk model while identifying prognostic mrlncRNAs. Areas under the ROC curves were assessed to evaluate the predictive effectiveness, and a predictive nomogram was constructed for further prediction. Subsequently, the tumor mutation burden (TMB), stemness, functional enrichment analysis, tumor microenvironment, and immunotherapeutic and chemotherapeutic responses were also assessed based on this novel risk model. Moreover, patients were regrouped into subtypes according to the expression of model mrlncRNAs. RESULTS: Assessed by the predictive risk model, patients were distinguished into the low-MLRS and high-MLRS groups, showing satisfactory predictive effects with AUCs of 0.673, 0.712, and 0.681 for the ROCs, respectively. Patients in the low-MLRS groups exhibited better survival status, lower mutated frequency, and lower stemness but were more sensitive to immunotherapeutic response, whereas the high-MLRS group appeared to have higher sensitivity to chemotherapy. Subsequently, patients were regrouped into two clusters: cluster 1 displayed immunosuppressive status, but cluster 2 behaved as a hot tumor with a better immunotherapeutic response. CONCLUSIONS: Referring to the above results, we established a m5C-related lncRNA model to evaluate the prognosis, TME, TMB, and clinical treatments for HNSCC patients. This novel assessment system is able to precisely predict the patients' prognosis and identify hot and cold tumor subtypes clearly for HNSCC patients, providing ideas for clinical treatment.

The Novel-Natural-Killer-Cell-Related Gene Signature Predicts the Prognosis and Immune Status of Patients with Hepatocellular Carcinoma.

The current understanding of the prognostic significance of natural killer (NK) cells and their tumor microenvironment (TME) in hepatocellular carcinoma (HCC) is limited. Thus, we screened for NK-cell-related genes by single-cell transcriptome data analysis and developed an NK-cell-related gene signature (NKRGS) using multi-regression analyses. Patients in the Cancer Genome Atlas cohort were stratified into high- and low-risk groups according to their median NKRGS risk scores. Overall survival between the risk groups was estimated using the Kaplan-Meier method, and a NKRGS-based nomogram was constructed. Immune infiltration profiles were compared between the risk groups. The NKRGS risk model suggests significantly worse prognoses in patients with high NKRGS risk (p < 0.05). The NKRGS-based nomogram showed good prognostic performance. The immune infiltration analysis revealed that the high-NKRGS-risk patients had significantly lower immune cell infiltration levels (p < 0.05) and were more likely to be in an immunosuppressive state. The enrichment analysis revealed that immune-related and tumor metabolism pathways highly correlated with the prognostic gene signature. In this study, a novel NKRGS was developed to stratify the prognosis of HCC patients. An immunosuppressive TME coincided with the high NKRGS risk among the HCC patients. The higher KLRB1 and DUSP10 expression levels correlated with the patients' favorable survival.

Exploration of a predictive model based on genes associated with fatty acid metabolism and clinical treatment for head and neck squamous cell carcinoma.

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) is one of the most prevalent malignant tumors of the head and neck and presents high risks of recurrence and poor prognosis postoperatively. The aim of this study was to establish a predictive model based on fatty acid metabolism (FAM) genes to forecast the prognosis of HNSCC patients and the subsequent treatment strategies. METHODS: We accessed the TCGA and GEO databases for HNSCC genes and clinical data. The FAM risk score model was created and validated using a combination of univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) regression analysis. Combining risk scores and clinical characteristics, a nomogram was established and assessed. Subsequently, the function, gene mutation, immune difference, and chemotherapeutic drug sensitivity of the groups with high- and low-risk scores were analyzed. Consequently, the mode's validity was evaluated comprehensively by combining single gene analysis. RESULTS: The FAM risk score model for predicting HNSCC prognosis had certain validity. Patients in the high- and low-risk groups had genetic mutations, and the prognosis was the poorest for the high-risk groups with high genetic mutations. The patients with low-risk scores were suitable for immunotherapy since they had increased infiltration of immune cells. In contrast, the patients in the other groups were more suitable for chemotherapy. CONCLUSION: The results of this study demonstrated that the FAM risk score model may predict the prognosis of HSNCC and has a certain therapeutic guidance value.

Identification of cuproptosis-related subtypes and characterization of the tumor microenvironment landscape in head and neck squamous cell carcinoma.

BACKGROUND: Cuproptosis is considered a novel copper-dependent cell death model. In this study, we established a novel scoring system based on 10 cuproptosis-related genes (CRGs) to predict the prognosis and immune landscape of head and neck squamous cell carcinoma (HNSCC). METHODS: The RNA-seq data of HNSCC patients were downloaded from the GEO and TCGA databases and were merged into a novel HNSCC cohort. Multiomics landscape analyses were conducted, including tumor mutation burden (TMB), copy number variations and the interaction network of CRGs. Patients were then divided into different cuproptosis subtypes based on the expression of 10 CRGs and subsequently regrouped into novel gene clusters referring to differentially expressed genes. A cuproptosis score (CS) system was established using principal component analysis. The CIBERSORT, ssGSEA and ESTIMATE algorithms were used to assess the tumor immune microenvironment. Moreover, the immunotherapeutic and chemotherapeutic responses were assessed. RESULTS: Patients were divided into three cuproptosis subtypes and subsequently regrouped into three gene clusters, reflecting different immune infiltration. Assessed by the CS system, those with higher CSs exhibited worse prognosis and higher TMB frequency. Nevertheless, the immune-related analysis revealed patients in the low-CS group appeared immunosuppressive and easily suffered from immune escape. High CSs possibly show high expression of immune checkpoint genes and enhance chemotherapy sensitivity to cisplatin, docetaxel, and gemcitabine. CONCLUSION: We established a novel scoring system to predict the prognosis and immune landscape of HNSCC patients. This signature exhibits satisfactory predictive effects and the potential to guide comprehensive treatment for patients.

Construction of a necroptosis-related lncRNA signature to predict the prognosis and immune microenvironment of head and neck squamous cell carcinoma.

BACKGROUND: Previous studies have determined that necroptosis-related genes are potential biomarkers in head and neck squamous cell carcinoma (HNSCC). Herein, we established a novel risk model based on necroptosis-related lncRNAs (nrlncRNAs) to predict the prognosis of HNSCC patients. METHODS: Transcriptome and related information were obtained from TCGA database, and an nrlncRNA signature was established based on univariate Cox analysis and least absolute shrinkage and selection operator Cox regression. Kaplan-Meier analysis and time-dependent receiver operating characteristic (ROC) analysis were used to evaluate the model, and a nomogram for survival prediction was established. Gene set enrichment analysis, immune analysis, drug sensitivity analysis, correlation with N6-methylandenosin (m6A), and tumor stemness analysis were performed. Furthermore, the entire set was divided into two clusters for further discussion. RESULTS: A novel signature was established with six nrlncRNAs. The areas under the ROC curves (AUCs) for 1-, 3-, and 5-year overall survival (OS) were 0.699, 0.686, and 0.645, respectively. Patients in low-risk group and cluster 2 had a better prognosis, more immune cell infiltration, higher immune function activity, and higher immune scores; however, patients in high-risk group and cluster 1 were more sensitive to chemotherapy. Moreover, the risk score had negative correlation with m6A-related gene expression and tumor stemness. CONCLUSION: According to this study, we constructed a novel signature with nrlncRNA pairs to predict the survival of HNSCC patients and guide immunotherapy and chemotherapy. This may possibly promote the development of individualized and precise treatment for HNSCC patients.

The possible mechanism of Hippophae fructus oil applied in tympanic membrane repair identified based on network pharmacology and molecular docking.

OBJECTIVE: This study aimed to explore the mechanisms of Hippophae fructus oil (HFO) in the treatment of tympanic membrane (TM) perforation through network pharmacology-based identification. METHODS: The compounds and related targets of HFO were extracted from the TCMSP database, and disease information was obtained from the OMIM, GeneCards, PharmGkb, TTD, and DrugBank databases. A Venn diagram was generated to show the common targets of HFO and TM, and GO and KEGG analyses were performed to explore the potential biological processes and signaling pathways. The PPI network and core gene subnetwork were constructed using the STRING database and Cytoscape software. A molecular docking analysis was also conducted to simulate the combination of compounds and gene proteins. RESULTS: A total of 33 compounds and their related targets were obtained from the TCMSP database. After screening the 393 TM-related targets, 21 compounds and 22 gene proteins were selected to establish the network diagram. GO and KEGG enrichment analyses revealed that HFO may promote TM healing by influencing cellular oxidative stress and related signaling pathways. A critical subnetwork was obtained by analyzing the PPI network with nine core genes: CASP3, MMP2, IL1B, TP53, EGFR, CXCL8, ESR1, PTGS2, and IL6. In addition, a molecular docking analysis revealed that quercetin strongly binds the core proteins. CONCLUSION: According to the analysis, HFO can be utilized to repair perforations by influencing cellular oxidative stress. Quercetin is one of the active compounds that potentially plays an important role in TM regeneration by influencing 17 gene proteins.

Construction of an m6A-related lncRNA pair prognostic signature and prediction of the immune landscape in head and neck squamous cell carcinoma.

BACKGROUND: Mounting evidence indicates that aberrantly expressed N6-methylandenosine (m6A) modification regulators and long noncoding RNA (lncRNA) influence the development of head and neck squamous cell carcinoma (HNSCC). However, the prognosis of m6A-related lncRNA (mrlncRNA) in HNSCC has not yet been evaluated. METHODS: We retrieved transcriptome, somatic mutation, and clinical information from The Cancer Genome Atlas database and established a differently expressed mrlncRNA (DEmrlncRNA) pair signature based on least absolute shrinkage and selection operator Cox regression and multivariate Cox analyses. Each sample's risk score was computed premised on the signature, which accurately classified patients into low- and high-risk group by the cut-off point. The signature was evaluated from the perspective of survival, clinicopathological characteristics, tumor mutation burden (TMB), immune cell infiltration, efficacy of chemotherapeutics, tumor immune microenvironment, and immune checkpoint inhibitor (ICI)-related genes. RESULTS: 11 DEmrlncRNA pairs were identified and were used to construct the prediction signature. Kaplan-Meier plotter revealed a worse prognosis in high-risk patients over low-risk patients (log rank p < 0.001). According to multivariate Cox regression analysis, the hazard ratio of the risk score and 95% confidence interval of 1.722 and (1.488-1.992) (p < 0.001) were obtained. Furthermore, an increased risk score was associated with aggressive clinicopathological features, specific tumor immune infiltration status, increased expression of ICI-related genes, higher TMB, and higher chemotherapeutics sensitivity (all p < 0.05). CONCLUSION: This research demonstrated that the signature premised on DEmrlncRNA pairs was an efficient independent prognostic indicator and may provide a rationale for research on immunotherapeutic and chemotherapeutics strategies for HNSCC patients.

Tympanic membrane regeneration using platelet-rich fibrin: a systematic review and meta-analysis.

PURPOSE: Platelet-rich fibrin (PRF) results in satisfactory wound healing. This analysis focuses on assessing the effectiveness of PRF in the treatment of tympanic membrane (TM) perforations. MATERIALS AND METHODS: The literature was searched using PubMed, Embase, Cochrane Library and Web of Science databases from inception to February 28th, 2021. The following healing and hearing outcomes were measured: closure rate, pre-and postoperative auditory results, and incidence of postoperative infections. Data were pooled and expressed as the odds ratio (OR). RESULTS: Ten studies were eligible for qualitative review, and seven of them were included for the final quantitative comparison. The OR for the closure rate of acute perforations was 4.30 (95% CI 1.35-13.70, I2 = 0%), and the OR in the chronic subgroup was 5.42 (95% CI 2.57-11.43, I2 = 0%). The total OR value for the completed closure rate was 5.10 (95% CI 2.72-9.54, I2 = 0%), indicating that the utilization of PRF can enhance the closure of both acute and chronic perforations. The qualitative review did not find improved hearing results with the use of PRF. In addition to promoting closure, PRF can reduce the incidence of infections (OR = 0.14). The sensitivity analysis did not change the final results, and there was no publication bias in this analysis. CONCLUSION: PRF can increase the closure rate of acute perforations, enhance the survival rate of autografts in TM surgeries and reduce the incidence of infections. However, the literature indicates that PRF does not influence the hearing outcomes. This study shows that PRF is an effective agent for TM regeneration.

Dysregulated Expression Levels of Circular RNAs Serve as Prognostic and Clinicopathological Markers in Gastric Cancer: a Meta-Analysis.

BACKGROUND: Circular RNAs (circRNAs) are novel biomarkers that are widely investigated in various cancers. There is increasing evidence that the expression levels of circRNAs are upregulated or downregulated in various cancers, but the overall prognostic efficiency of circRNAs in gastric cancer (GC) remains unclear. Therefore, this meta-analysis studies the relationship between circRNA expression and the prognosis of gastric malignancies. METHODS: A systematic search was conducted in the PubMed, Web of Science (WOS), EMBASE, and Cochrane Library databases. Eligible studies reporting on the associations of circRNAs with the clinicopathological characteristics and prognosis of GC patients were included. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were utilized to assess clinicopathological parameters. Hazard ratios (HRs) and 95% CIs were used to evaluate the prognostic value of circRNAs using RevMan 5.3 and Stata 15.1 software. RESULTS: Fifteen eligible studies, including 13 for clinicopathological features and 15 for prognosis, were included in our study. For clinicopathological parameters, the high expression of oncogenic circRNAs was significantly associated with poor clinicopathological features, and the high expression of tumor-suppressor circRNAs was associ-ated with better clinicopathological features. In terms of prognostic value, oncogenic circRNAs had a negative influence on overall survival (OS: HR = 2.27, 95% CI: 1.93 - 2.69), and the high expression of tumor suppressor circRNAs was related to improved survival outcomes (OS: HR = 0.56, 95% Cl: 0.44 - 0.72). CONCLUSIONS: This meta-analysis revealed that the expression of circRNAs might be a useful prognostic biomarker in gastric cancer.

Cascaded DFG via quasi-phase matching with Cherenkov-type PPLN for highly efficient terahertz generation.

Terahertz (THz) generation in a periodically poled lithium niobate crystal via cascaded difference-frequency generation based on Cherenkov-type quasi-phase matching (QPM) is proposed. Photon conversion efficiency is evaluated based on a promising structure that combines QPM and Cherenkov phase-matching with reduced wave-vector mismatch. Cascading processes contribute to photon conversion efficiency, and THz radiation with maximum photon conversion efficiency of 1154.2% in a 14-order cascaded Stokes process was obtained. Comparing the processes with and without Cherenkov-type radiation, with a 50-MW pump, power was boosted nearly 1.9 times for the former case. These results provide an experimental approach to high-energy THz-wave generation.

Blind UAV Images Deblurring Based on Discriminative Networks.

Unmanned aerial vehicles (UAVs) have become an important technology for acquiring high-resolution remote sensing images. Because most space optical imaging systems of UAVs work in environments affected by vibrations, the optical axis motion and image plane jitter caused by these vibrations easily result in blurring of UAV images. In the paper; we propose an advanced UAV image deblurring method based on a discriminative model comprising a classifier for blurred and sharp UAV images which is embedded into the maximum a posteriori framework as a regularization term that constantly optimizes ill-posed problem of blind image deblurring to obtain sharper UAV images. Compared with other methods, the results show that in image deblurring experiments using both simulated and real UAV images the proposed method delivers sharper images of various ground objects.

Development of Chromatin Regulator-related Molecular Subtypes and a Signature to Predict Prognosis and Immunotherapeutic Response in Head and Neck Squamous Cell Carcinoma.

BACKGROUND: Chromatin regulators (CRs) serve as indispensable factors in tumor biological processes by influencing tumorigenesis and the immune microenvironment and have been identified in head and neck squamous cell carcinoma (HNSCC). Hence, CR-related genes (CRRGs) are considered potential biomarkers for predicting prognosis and immune infiltration in HNSCC. In this study, we established a novel signature for predicting the prognosis and immunotherapeutic response of HSNCC. METHODS: A total of 870 CRRGs were obtained according to previous studies. Subsequently, patients in the TCGA-HNSC cohort were divided into different clusters based on the expression of prognostic CRRGs. Kaplan‒Meier (K‒M) survival analysis was conducted to compare the prognosis in clusters, and the CIBERSORT and ssGSEA methods assessed the immune infiltration status. In addition, the differences in immunotherapeutic responses were determined based on the TICA database. Furthermore, the differentially expressed CRRGs between clusters were identified, and the predictive signature was established according to the results of univariate Cox, least absolute shrinkage and selection operator regression analysis, and multivariate Cox. The predictive effects of the risk model were evaluated according to the area under the receiver operating characteristic (ROC) curve (AUC) in both the training and external test cohorts. A nomogram was established, and survival comparisons, functional enrichment analyses, and immune infiltration status and clinical treatment assessments were performed. In addition, the hub gene network and related analysis were conducted with the Cytohubba application. RESULTS: Based on the expression of prognostic CRRGs, patients were divided into two clusters, in which Cluster 1 exhibited a better prognosis, more enriched immune infiltration, and a better immunotherapeutic response but exhibited chemotherapy sensitivity. The AUC values of the 1-, 3- and 5- year ROC curves for the risk model were 0.673, 0.732, and 0.692, respectively, as well as 0.645, 0.608, and 0.623 for the test set. In addition, patients in the low-risk group exhibited more immune cell enrichment and immune function activation, as well as a better immunotherapy response. The hub gene network indicated ACTN2 as the core gene differentially expressed between the two risk groups. CONCLUSIONS: We identified molecular subtypes and established a novel predictive signature based on CRRGs. This effective CRRS system can possibly provide a novel research direction for exploring the correlation between CRs and HNSCC and requires further experimental validation.

Identification of an anoikis-related gene signature and characterization of immune infiltration in skin cutaneous melanoma.

Anoikis is considered strongly associated with a biological procession of tumors. Herein, we utilized anoikis-related genes (ARGs) to predict the prognosis and immunotherapeutic efficacy for skin cutaneous melanoma (SKCM). RNA-seq data were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. After dividing patients into novel subtypes based on the expression of prognostic ARGs, K-M survival was conducted to compare the survival status. Subsequently, differentially expressed ARGs were identified and the predictive model was established. The predictive effects were validated using the areas under the curve about the receiver operating characteristic. Moreover, tumor mutation burden, the enriched functional pathway, immune cells and functions, and the immunotherapeutic response were also analyzed and compared. The distribution of model genes at cell level was visualized by the single-cell seq with tumor immune single-cell hub database. Patients of The Cancer Genome Atlas-SKCM cohort were divided into 2 clusters, the cluster 1 performed a better prognosis. Cluster 2 was more enriched in metabolism-related pathways whereas cluster 1 was more associated with immune pathways. A predictive risk model was established with 6 ARGs, showing the areas under the curves of 1-year, 3-year, and 5-year ROC were 0.715, 0,720, and 0.731, respectively. Moreover, risk score was negatively associated with tumor mutation burden and immune-related pathways enrichment. In addition, patients with high-risk scores performed immunosuppressive status but the decreasing scores enhanced immune cell infiltration, immune function activation, and immunotherapeutic response. In this study, we established a novel signature in predicting prognosis and immunotherapy. It can be considered reliable to formulate the complex treatment for SKCM patients.

Fabrication and Evaluation of Hyaluronidase-Responsive Scaffolds by Electrospinning with Antibacterial Properties for Tympanic Membrane Repair.

Tympanic membrane perforation (TMP) is prevalent in clinical settings. Patients with TMPs often suffer from infections caused by Staphylococcus aureus and Pseudomonas aeruginosa, leading to middle ear and external ear canal infections, which hinder eardrum healing. The objective of this study is to fabricate an enzyme-responsive antibacterial electrospun scaffold using poly(lactic-co-glycolic acid) and hyaluronic acid for the treatment of infected TMPs. The properties of the scaffold were characterized, including morphology, wettability, mechanical properties, degradation properties, antimicrobial properties, and biocompatibility. The results indicated that the fabricated scaffold had a core-shell structure and exhibited excellent mechanical properties, hydrophobicity, degradability, and cytocompatibility. Furthermore, in vitro bacterial tests and ex vivo investigations on eardrum infections suggested that this scaffold possesses hyaluronidase-responsive antibacterial properties. It may rapidly release antibiotics when exposed to the enzyme released by S. aureus and P. aeruginosa. These findings suggest that the scaffold has great potential for repairing TMPs with infections.

Integrating single-cell and bulk RNA sequencing reveals CK19 + cancer stem cells and their specific SPP1 + tumor-associated macrophage niche in HBV-related hepatocellular carcinoma.

PURPOSE: Cytokeratin 19-positive cancer stem cells (CK19 + CSCs) and their tumor-associated macrophages (TAMs) have not been fully explored yet in the hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC). EXPERIMENTAL DESIGN: Single-cell RNA sequencing was performed on the viable cells obtained from 11 treatment-naïve HBV-associated HCC patients, including 8 CK19 + patients, to elucidate their transcriptomic landscape, CK19 + CSC heterogeneity, and immune microenvironment. Two in-house primary HCC cohorts (96 cases-related HBV and 89 cases with recurrence), TCGA external cohort, and in vitro and in vivo experiments were used to validate the results. RESULTS: A total of 64,581 single cells derived from the human HCC and adjacent normal tissues were sequenced, and 11 cell types were identified. The result showed that CK19 + CSCs were phenotypically and transcriptionally heterogeneous, co-expressed multiple hepatics CSC markers, and were positively correlated with worse prognosis. Moreover, the SPP1 + TAMs (TAM_SPP1) with strong M2-like features and worse prognosis were specifically enriched in the CK19 + HCC and promoted tumor invasion and metastasis by activating angiogenesis. Importantly, matrix metalloproteinase 9 (MMP9) derived from TAM_SPP1, as the hub gene of CK19 + HCC, was activated by the VEGFA signal. CONCLUSIONS: This study revealed the heterogeneity and stemness characteristics of CK19 + CSCs and specific immunosuppressive TAM_SPP1 in CK19 + HCC. The VEGFA signal can activate TAM_SPP1-derived MMP9 to promote the invasion and metastasis of CK19 + HCC tumors. This might provide novel insights into the clinical treatment of HCC patients.

Butterfly Cartilage Tympanoplasty as an Alternative to Conventional Surgery for Tympanic Membrane Perforations: A Systematic Review and Meta-Analysis.

OBJECTIVE: To compare the effectiveness of butterfly cartilage tympanoplasty (BCT) with that of conventional surgical approaches in the treatment of tympanic membrane perforations. METHODS: A systematic search was performed by screening the PubMed, Embase, and Cochrane Library databases up to October 31, 2020. Two coauthors independently identified studies in accordance with the selection criteria. Data were pooled and analyzed via Review Manager version 5.3 and Stata version 12.0 software. The postoperative outcomes were measured and expressed as odds ratios (ORs) and standardized mean differences (SMDs). Additionally, heterogeneity was assessed through the I2 statistic. RESULTS: A total of 15 articles were eligible for final inclusion. The OR values for the graft uptake rate, compared to conventional tympanoplasty, were 1.12 (95%CI: 0.56-2.22, I2 = 52%, P = .75) and 1.22 (95%CI: 0.58-2.59, I2 = 0%, P = .60), and the OR compared to fat plug myringoplasty was 3.02 (95%CI: 1.04-8.77, I2 = 0%, P = .04). The qualitative analysis of the hearing results reflected significant postoperative auditory gains with no significant differences between the BCT and control groups, indicating satisfactory and similar postoperative hearing improvement. Moreover, the operation time was shortened (SMD = -2.19, 95%CI: -2.79 to -1.59, I2 = 82%, P < .05), and the postoperative pain was less with the BCT approach. CONCLUSION: Butterfly cartilage tympanoplasty has satisfactory efficacy in terms of anatomical and functional results in small to medium perforations. It reduces operation time and postoperative pain. However, the effectiveness on large perforation requires further assessment by well-designed studies.

Decoding flat bands from compact localized states.

The flat band system is an ideal quantum platform to investigate the kaleidoscope created by the electron-electron correlation effects. The central ingredient of realizing a flat band is to find its compact localized states. In this work, we develop a systematic way to generate compact localized states by designing destructive interference patterns from 1-dimensional chains. A variety of 2-dimensional new flat band systems are constructed with this method. Furthermore, we show that the method can be extended to generate the compact localized states in multi-orbital systems by carefully designing the block hopping scheme, as well as in quasicrystal and disorder systems.

Pancancer analysis reveals the role of disulfidptosis in predicting prognosis, immune infiltration and immunotherapy response in tumors.

Disulfidptosis has been reported as a novel cell death process, suggesting a therapeutic strategy for cancer treatment. Herein, we constructed a multiomics data analysis to reveal the effects of disulfidptosis in tumors. Data for 33 kinds of tumors were downloaded from UCSC Xene, and disulfidptosis-related genes (DRGs) were selected from a previous study. After finishing processing data by the R packages, the expression and coexpression of DRGs in different tumors were assessed as well as copy number variations. The interaction network was drawn by STRING, and the activity of disulfidptosis was compared to the single-sample gene set enrichment analysis algorithm. Subsequently, the differences in DRGs for prognosis and clinicopathological features were evaluated, and the tumor immune microenvironment was assessed by the TIMER and TISCH databases. Tumor mutation burden, stem cell features and microsatellite instability were applied to predict drug resistance, and the expression of checkpoints was identified for the prediction of immunotherapy. Moreover, the TCIA, CellMiner and Enrichr databases were also utilized for selecting potential agents. Ten DRGs were differentially expressed in tumors, and the plots of coexpression and interaction revealed their correlation. Survival analysis suggested SLC7A11 as the most prognosis-related DRG with the most significant results. Additionally, the comparison also reflected the differences in DRGs in the status of pathologic lymph node metastasis for 5 types of tumors. The tumor immune microenvironment showed commonality among tumors based on immune infiltration and single-cell sequencing, and the analysis of tumor mutation burden, stemness and microsatellite instability showed a mostly positive correlation with DRGs. Moreover, referring to the prediction about clinical treatment, most DRGs can enhance sensitivity to chemotherapeutic agents but decrease the response to immune inhibitors with increasing expression. In this study, a primarily synthetic landscape of disulfidptosis in tumors was established and provided guidance for further exploration and investigation.