Protective effects of tetramethylpyrazine on myocardial ischemia/reperfusion injury involve NLRP3 inflammasome suppression by autophagy activation.

Tetramethylpyrazine (TMP) belongs to the active ingredients of the traditional Chinese medicine Chuanxiong, which has a certain protective effect in myocardial ischemia-reperfusion (I/R) injury. It can improve postoperative cardiac function and alleviate ventricular remodeling in acute myocardial infarction patients. However, its specific protective mechanism is still unclear. In this study, a certain concentration of TMP was introduced into I/R mice or H9C2 cells after oxygen-glucose deprivation/reoxygenation (OGD/R) treatment to observe the effects of TMP on cardiomyocyte activity, cytotoxicity, apoptosis, autophagy, pyroptosis, and NLRP3 inflammasome activation. The results displayed that TMP intervention could reduce OGD/R and I/R-induced cardiomyocyte apoptosis, accelerate cellular activity and autophagy levels, and ameliorate myocardial tissue necrosis in I/R mice in a dose-dependent manner. Further, TMP prevented the formation of NLRP3 inflammasomes to suppress pyroptosis by increasing the level of cardiomyocyte autophagy after I/R and OGD/R modelling, the introduction of chloroquine to suppress autophagic activity in vivo and in vitro was further analyzed to confirm whether TMP inhibits NLRP3 inflammasome activation and pyroptosis by increasing autophagy, and we found the inhibitory effect of TMP on NLRP3 inflammasomes and its protective effect against myocardial injury were blocked when autophagy was inhibited with chloroquine. In conclusion, this experiment demonstrated that TMP unusually attenuated I/R injury in mice, and this protective effect was achieved by inhibiting the activation of NLRP3 inflammasomes through enhancing autophagic activity.

Study of LY9 as a potential biomarker for prognosis and prediction of immunotherapy efficacy in lung adenocarcinoma.

Background: Lymphocyte antigen 9 (LY9) participates in the development of several tumors and diseases but has not been reported yet in lung adenocarcinoma (LUAD). Methods: First, we analyzed the expression and prognostic value of LY9 in pan-cancer, including LUAD. Additionally, we conducted a correlation analysis of LY9 expression in LUAD with immune cell infiltration using the TIMER database and the CIBERSORT algorithm, and with immune checkpoints using the GEPIA database. Also, we constructed a potential ceRNA network for LY9. Furthermore, we explored LY9-related pathways by Gene Set Enrichment Analysis (GSEA). Finally, validation of differential expression at the mRNA level was obtained from the GEO database. We collected LUAD tissues for Quantitative Real-time PCR (qRT-PCR) to verify the expression of LY9, CD8, and CD4 and calculated the correlation between them. We also conducted immunohistochemistry (IHC) to verify the protein expression of LY9. Results: Results showed that LY9 was highly expressed in various tumors, including LUAD. Besides, patients with high LY9 expression presented longer overall survival (OS) and more multiple lymphocyte infiltrations. The expression of LY9 in LUAD strongly and positively correlates with multiple immune cell infiltration and immune checkpoints. The functional enrichment analysis indicated that LY9 was involved in multiple immune-related pathways and non-small cell lung cancer. Moreover, a ceRNA regulatory network of LINC00943-hsa-miR-141-3p-LY9 might be involved. Finally, GSE68465 dataset confirmed differential expression of LY9 mRNA levels in LUAD and the qRT-PCR results verified LY9 had a strong and positive correlation with CD4 and CD8 T cells. Unfortunately, IHC did not detect the expression of LY9 protein level in tumor tissues and WB experiments validated the protein expression of LY9 in the OCI-AML-2 cell line. Conclusions: Therefore, we hypothesized that LY9 could serve as a potential, novel prognostic biomarker for LUAD and could predict immunotherapy efficacy at the mRNA level.

First-Principles Study of the Structural, Mechanical, Electronic, and Thermodynamic Properties of AlCu2M (M = Ti, Cr, Zr, Sc, Hf, Mn, Pa, Lu, Pm) Ternary Intermetallic Compounds.

Based on the first principles, the structural stability, mechanical characteristics, electronic structure, and thermodynamic properties of AlCu2M (M = Ti, Cr, Zr, Sc, Hf, Mn, Pa, Lu, Pm) are investigated. The calculated results indicate that the AlCu2Pa crystal structure is more stable and that AlCu2Pa should be easier to form. All of the AlCu2M compounds have structural stability in the ground state. Elastic constants are used to characterize the mechanical stability and elastic modulus, while the B/G values and Poisson ratio demonstrate the brittleness and ductility of AlCu2M compounds. It is demonstrated that all computed AlCu2M compounds are ductile and mechanically stable, with AlCu2Hf having the highest bulk modulus and AlCu2Mn having the highest Young's modulus. AlCu2Mn has the highest intrinsic hardness among AlCu2M compounds, according to calculations of their intrinsic hardness. The electronic densities of states are discussed in detail; it was discovered that all AlCu2M compounds form Al-Cu and Al-M covalent bonds. Additionally, we observe that the Debye temperature and minimum thermal conductivity of AlCu2Mn and AlCu2Sc are both larger than those of others, indicating stronger chemical bonds and higher thermal conductivities, which is consistent with the elastic modulus results.

SHAP based predictive modeling for 1 year all-cause readmission risk in elderly heart failure patients: feature selection and model interpretation.

Heart failure (HF) is a significant global public health concern with a high readmission rate, posing a serious threat to the health of the elderly population. While several studies have used machine learning (ML) to develop all-cause readmission risk prediction models for elderly patients with HF, few have integrated ML-selected features with those chosen by human experts to assess HF patients readmission. A retrospective analysis of 8396 elderly HF patients hospitalized at the Affiliated Hospital of North Sichuan Medical College from January 1, 2018 to December 31, 2021 was conducted. Variables selected by XGBoost, LASSO regression, and random forest constituted the machine group, while the human expert group comprised variables chosen by two experienced cardiovascular professors. The variables selected by both groups were combined to form a human-machine collaboration group. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC). The SHapley Additive exPlanations (SHAP) method was used to elucidate the importance of each predictive feature, explain the impact of individual features on the model, and provide visual representation. A total of 73 features were included for model development. The human-machine collaboration model, utilizing CatBoost, achieved an AUC of 0.83617, an F1-score of 0.73521, and a Brier score of 0.16536 on the validation set. This model demonstrated superior predictive performance compared to those created solely by human experts or machine. The SHAP plot was then used to visually display the feature analysis of the human-machine collaboration model, revealing HGB, NT-proBNP, smoking history, NYHA classification, and LVEF as the 5 most important features. This study indicate that the human-machine collaboration model outperforms those relying solely on human expert selection or machine algorithm at predicting all-cause readmission in elderly HF patients. The application of the SHAP method enhanced the interpretability of the model outcomes, aiding clinicians in accurately pinpointing risk factors associated with HF readmission. This advancement enables the formulation of tailored treatment strategies, offering a more personalized approach to patient care.

Development and validation of a machine learning-based readmission risk prediction model for non-ST elevation myocardial infarction patients after percutaneous coronary intervention.

To investigate the factors that influence readmissions in patients with acute non-ST elevation myocardial infarction (NSTEMI) after percutaneous coronary intervention (PCI) by using multiple machine learning (ML) methods to establish a predictive model. In this study, 1576 NSTEMI patients who were hospitalized at the Affiliated Hospital of North Sichuan Medical College were selected as the research subjects. They were divided into two groups: the readmitted group and the non-readmitted group. The division was based on whether the patients experienced complications or another incident of myocardial infarction within one year after undergoing PCI. Common variables selected by univariate and multivariate logistic regression, LASSO regression, and random forest were used as independent influencing factors for NSTEMI patients' readmissions after PCI. Six different ML models were constructed using these common variables. The area under the ROC curve, accuracy, sensitivity, and specificity were used to evaluate the performance of the six ML models. Finally, the optimal model was selected, and a nomogram was created to visually represent its clinical effectiveness. Three different methods were used to select seven representative common variables. These variables were then utilized to construct six different ML models, which were subsequently compared. The findings indicated that the LR model exhibited the most optimal performance in terms of AUC, accuracy, sensitivity, and specificity. The outcome, admission mode (walking and non-walking), communication ability, CRP, TC, HDL, and LDL were identified as independent predicators of readmissions in NSTEMI patients after PCI. The prediction model constructed by the LR algorithm was the best. The established column graph model established proved to be effective in identifying high-risk groups with high accuracy and differentiation. It holds a specific predictive value for the occurrence of readmissions after direct PCI in NSTEMI patients.

Metabolic reprogramming-driven homologous recombination and TCA cycle dysregulation contribute to poor prognoses in lung adenocarcinoma.

Increasing evidence has shown that homologous recombination (HR) and metabolic reprogramming are essential for cellular homeostasis. These two processes are independent as well as closely intertwined. Nevertheless, they have rarely been reported in lung adenocarcinoma (LUAD). We analysed the genomic, immune microenvironment and metabolic microenvironment features under different HR activity states. Using cell cycle, EDU and cell invasion assays, we determined the impacts of si-SHFM1 on the LUAD cell cycle, proliferation and invasion. The levels of isocitrate dehydrogenase (IDH) and α-ketoglutarate dehydrogenase (α-KGDH) were determined by ELISA in the NC and si-SHFM1 groups of A549 cells. Finally, cell samples were used to extract metabolites for HPIC-MS/MS to analyse central carbon metabolism. We found that high HR activity was associated with a poor prognosis in LUAD, and HR was an independent prognostic factor for TCGA-LUAD patients. Moreover, LUAD samples with a high HR activity presented low immune infiltration levels, a high degree of genomic instability, a good response status to immune checkpoint blockade therapy and a high degree of drug sensitivity. The si-SHFM1 group presented a significantly higher proportion of cells in the G0/G1 phase, lower levels of DNA replication, and significantly lower levels of cell migration and both TCA enzymes. Our current results indicated that there is a strong correlation between HR and the TCA cycle in LUAD. The TCA cycle can promote SHFM1-mediated HR in LUAD, raising their activities, which can finally result in a poor prognosis and impair immunotherapeutic efficacy.

IBPGNET: lung adenocarcinoma recurrence prediction based on neural network interpretability.

Lung adenocarcinoma (LUAD) is the most common histologic subtype of lung cancer. Early-stage patients have a 30-50% probability of metastatic recurrence after surgical treatment. Here, we propose a new computational framework, Interpretable Biological Pathway Graph Neural Networks (IBPGNET), based on pathway hierarchy relationships to predict LUAD recurrence and explore the internal regulatory mechanisms of LUAD. IBPGNET can integrate different omics data efficiently and provide global interpretability. In addition, our experimental results show that IBPGNET outperforms other classification methods in 5-fold cross-validation. IBPGNET identified PSMC1 and PSMD11 as genes associated with LUAD recurrence, and their expression levels were significantly higher in LUAD cells than in normal cells. The knockdown of PSMC1 and PSMD11 in LUAD cells increased their sensitivity to afatinib and decreased cell migration, invasion and proliferation. In addition, the cells showed significantly lower EGFR expression, indicating that PSMC1 and PSMD11 may mediate therapeutic sensitivity through EGFR expression.

Genotype F of Echovirus 25 with multiple recombination pattern have been persistently and extensively circulating in Chinese mainland.

Echovirus 25 (E25), a member of the Enterovirus B (EV-B) species, can cause aseptic meningitis (AM), viral meningitis (VM), and acute flaccid paralysis (AFP). However, systematic studies on the molecular epidemiology of E25, especially those concerning its evolution and recombination, are lacking. In this study, 18 strains of E25, isolated from seven provinces of China between 2009 and 2018, were collected based on the Chinese hand, foot, and mouth disease (HFMD) surveillance network, and 95 sequences downloaded from GenBank were also screened. Based on the phylogenetic analysis of 113 full-length VP1 sequences worldwide, globally occurring E25 strains were classified into 9 genotypes (A-I), and genotype F was the dominant genotype in the Chinese mainland. The average nucleotide substitution rate of E25 was 6.08 × 10-3 substitutions/site/year, and six important transmission routes were identified worldwide. Seventeen recombination patterns were determined, of which genotype F can be divided into 9 recombination patterns. A positive selector site was found in the capsid protein region of genotype F. Recombination analysis and pressure selection analysis for genotype F showed multiple recombination patterns and evolution characteristics, which may be responsible for it being the dominant genotype in the Chinese mainland. This study provides a theoretical basis for the subsequent prevention and control of E25.

Paclitaxel-induced inhibition of NSCLC invasion and migration via RBFOX3-mediated circIGF1R biogenesis.

We previously reported that circIGF1R is significantly downregulated in non-small cell lung cancer (NSCLC) cells and tissues. It inhibits cancer cell invasion and migration, although the underlying molecular mechanisms remain elusive. The invasion and migration of NSCLC cells was analyzed by routine in vivo and in vitro functional assays. Fluorescent in situ hybridization, luciferase reporter assay, RNA pull-down assay and RNA immunoprecipitation (RIP) assay were performed to explore the molecular mechanisms. Mechanism of action of paclitaxel-induced RBFOX3-mediated inhibition of NSCLC invasion and migration was investigated through in vitro and in vivo experiments.Our study reveals that circIGF1R acts as a Competing Endogenous RNA (ceRNA) for miR-1270, thereby regulating Van-Gogh-like 2 (VANGL2) expression and subsequently inhibiting NSCLC cell invasion and migration via the Wnt pathway. We also found that RNA binding protein fox-1 homolog 3 (RBFOX3) enhances circIGF1R biogenesis by binding to IGF1R pre-mRNA, which in turn suppresses migration and invasion in NSCLC cells. Additionally, the chemotherapeutic drug paclitaxel was shown to impede NSCLC invasion and migration by inducing RBFOX3-mediated circIGF1R biogenesis.RBFOX3 inhibits the invasion and migration of NSCLC cells through the circIGF1R/ miR-1270/VANGL2 axis, circIGF1R has the potential to serve as a biomarker and therapeutic target for NSCLC.

The multifaceted roles of COL4A4 in lung adenocarcinoma: An integrated bioinformatics and experimental study.

BACKGROUND: Abnormal expression of collagen IV subunits has been reported in cancers, but the significance is not clear. No study has reported the significance of COL4A4 in lung adenocarcinoma (LUAD). METHODS: COL4A4 expression data, single-cell sequencing data and clinical data were downloaded from public databases. A range of bioinformatics and experimental methods were adopted to analyze the association of COL4A4 expression with clinical parameters, tumor microenvironment (TME), drug resistance and immunotherapy response, and to investigate the roles and underlying mechanism of COL4A4 in LUAD. RESULTS: COL4A4 is differentially expressed in most of cancers analyzed, being associated with prognosis, tumor stemness, immune checkpoint gene expression and TME parameters. In LUAD, COL4A4 expression is down-regulated and associated with various TME parameters, response to immunotherapy and drug resistance. LUAD patients with lower COL4A4 have worse prognosis. Knockdown of COL4A4 significantly inhibited the expression of cell-cycle associated genes, and the expression and activation of signaling pathways including JAK/STAT3, p38, and ERK pathways, and induced quiescence in LUAD cells. Besides, it significantly induced the expression of a range of bioactive molecule genes that have been shown to have critical roles in TME remodeling and immune regulation. CONCLUSIONS: COL4A4 is implicated in the pathogenesis of cancers including LUAD. Its function may be multifaceted. It can modulate the activity of LUAD cells, TME remodeling and tumor stemness, thus affecting the pathological process of LUAD. COL4A4 may be a prognostic molecular marker and a potential therapeutic target.

Construction of 11 metabolic-related lncRNAs to predict the prognosis in lung adenocarcinoma.

OBJECTIVE: To explore the metabolism-related lncRNAs in the tumorigenesis of lung adenocarcinoma. METHODS: The transcriptome data and clinical information about lung adenocarcinoma patients were acquired in TCGA (The Cancer Genome Atlas). Metabolism-related genes were from the GSEA (Gene Set Enrichment Analysis) database. Through differential expression analysis and Pearson correlation analysis, lncRNAs about lung adenocarcinoma metabolism were identified. The samples were separated into the training and validation sets in the proportion of 2:1. The prognostic lncRNAs were determined by univariate Cox regression analysis and LASSO (Least absolute shrinkage and selection operator) regression. A risk model was built using Multivariate Cox regression analysis, evaluated by the internal validation data. The model prediction ability was assessed by subgroup analysis. The Nomogram was constructed by combining clinical indicators with independent prognostic significance and risk scores. C-index, calibration curve, DCA (Decision Curve Analysis) clinical decision and ROC (Receiver Operating Characteristic Curve) curves were obtained to assess the prediction ability of the model. Based on the CIBERSORT analysis, the correlation between lncRNAs and tumor infiltrating lymphocytes was obtained. RESULTS: From 497 lung adenocarcinoma and 54 paracancerous samples, 233 metabolic-related and 11 prognostic-related lncRNAs were further screened. According to the findings of the survival study, the low-risk group had a greater OS (Overall survival) than the high-risk group. ROC analysis indicated AUC (Area Under Curve) value was 0.726. Then, a nomogram with T, N stage and risk ratings was developed according to COX regression analysis. The C-index was 0.743, and the AUC values of 3- and 5-year survival were 0.741 and 0.775, respectively. The above results suggested the nomogram had a good prediction ability. The results based on the CIBERSORT algorithm demonstrated the lncRNAs used to construct the model had a strong correlation with the polarization of immune cells. CONCLUSIONS: The study identified 11 metabolic-related lncRNAs for lung adenocarcinoma prognosis, on which basis a prognostic risk scoring model was created. This model may have a good predictive potential for lung adenocarcinoma.

Synthesis of Large Macrocycles with Chiral Sulfur Centers via Enantiospecific SuFEx and SuPhenEx Click Reactions.

Here we report the first asymmetric synthesis of large chiral macrocycles with chiral sulfur atoms. Building on stereospecific SuFEx and SuPhenEx click chemistries, this approach utilizes disulfonimidoyl fluorides and disulfonimidoyl p-nitrophenolates─which are efficient building blocks with two chiral sulfur centers, and diphenols to efficiently form novel S-O bonds. Characteristic results include the enantiospecific one-step synthesis of rings consisting of 21-58 members and characterization of both enantiomers (R,R and S,S) by e.g. X-ray crystallography.

TAGAP expression influences CD4+ T cell differentiation, immune infiltration, and cytotoxicity in LUAD through the STAT pathway: implications for immunotherapy.

Background: T-cell Activation GTPase Activating Protein (TAGAP) plays a role in immune cell regulation. This study aimed to investigate TAGAP's expression and its potential impact on CD4+ T cell function and prognosis in lung adenocarcinoma (LUAD). Methods: We analyzed TAGAP expression and its correlation with immune infiltration and clinical data in LUAD patients using multiple datasets, including The Cancer Genome Atlas (TCGA-LUAD), Gene Expression Omnibus (GEO), and scRNA-seq datasets. In vitro and in vivo experiments were conducted to explore the role of TAGAP in CD4+ T cell function, chemotaxis, and cytotoxicity. Results: TAGAP expression was significantly lower in LUAD tissues compared to normal tissues, and high TAGAP expression correlated with better prognosis in LUAD patients. TAGAP was positively correlated with immune/stromal/ESTIMATE scores and immune cell infiltration in LUAD. Single-cell RNA sequencing revealed that TAGAP was primarily distributed in CD4+/CD8+ T cells. In vitro experiments showed that TAGAP overexpression enhanced CD4+ T cell cytotoxicity, proliferation, and chemotaxis. Gene Set Enrichment Analysis (GSEA) indicated that TAGAP was enriched in the JAK-STAT signaling pathway. In vivo experiments in a xenograft tumor model demonstrated that TAGAP overexpression suppressed tumor growth and promoted CD4+ T cell cytotoxicity. Conclusions: TAGAP influences CD4+ T cell differentiation and function in LUAD through the STAT pathway, promoting immune infiltration and cytotoxicity. This study provides a scientific basis for developing novel LUAD immunotherapy strategies and exploring new therapeutic targets.

CBPH assay for the highest sensitive detection of SARS-COV-2 in the semen.

BACKGROUND: Great concerns have been raised on SARS-CoV-2 impact on men's andrological well-being, and many studies have attempted to determine whether SARS-CoV-2 is present in the semen and till now the data are unclear and somehow ambiguous. However, these studies used quantitative real-time (qRT) PCR, which is not sufficiently sensitive to detect nucleic acids in clinical samples with a low viral load. METHODS: The clinical performance of various nucleic acid detection methods (qRT-PCR, OSN-qRT-PCR, cd-PCR, and CBPH) was assessed for SARS-CoV-2 using 236 clinical samples from laboratory-confirmed COVID-19 cases. Then, the presence of SARS-CoV-2 in the semen of 12 recovering patients was investigated using qRT-PCR, OSN-qRT-PCR, cd-PCR, and CBPH in parallel using 24 paired semen, blood, throat swab, and urine samples. RESULTS: The sensitivity and specificity along with AUC of CBPH was markedly higher than the other 3methods. Although qRT-PCR, OSN-qRT-PCR and cdPCR detected no SARS-CoV-2 RNA in throat swab, blood, urine, and semen samples of the 12 patients, CBPH detected the presence of SARS-CoV-2 genome fragments in semen samples, but not in paired urine samples, of 3 of 12 patients. The existing SARS-CoV-2 genome fragments were metabolized over time. CONCLUSIONS: Both OSN-qRT-PCR and cdPCR had better performance than qRT-PCR, and CBPH had the highest diagnostic performance in detecting SARS-CoV-2, which contributed the most improvement to the determination of the critical value in gray area samples with low vrial load, which then provides a rational screening strategy for studying the clearance of coronavirus in the semen over time in patients recovering from COVID-19. Although the presence of SARS-CoV-2 fragments in the semen was demonstrated by CBPH, COVID-19 is unlikely to be sexually transmitted from male partners for at least 3 months after hospital discharge.

The pathological significance and potential mechanism of ARHGEF6 in lung adenocarcinoma.

BACKGROUND: Emerging evidences suggest that ARHGEF6 is involved in cancers but the exact significance and underlying mechanism are unclear. This study aimed to elucidate the pathological significance and potential mechanism of ARHGEF6 in lung adenocarcinoma (LUAD). METHODS: Bioinformatics and experimental methods were used to analyze the expression, the clinical significance, the cellular function and potential mechanisms of ARHGEF6 in LUAD. RESULTS: ARHGEF6 was downregulated in LUAD tumor tissues and correlated negatively with poor prognosis and tumor stemness, positively with the Stromal score, the Immune score and the ESTIMATE score. The expression level of ARHGEF6 was also associated with drug sensitivity, the abundance of immune cells, the expression levels of Immune checkpoint genes and immunotherapy response. Mast cells, T cells and NK cells were the first three cells with the highest expression of ARHGEF6 in LUAD tissues. Overexpression of ARHGEF6 reduced proliferation and migration of LUAD cells and the growth of xenografted tumors, which could be reversed by re-knockdown of ARHGEF6. Results of RNA sequencing revealed that ARHGEF6 overexpression induced significant changes in the expression profile of LUAD cells, and genes encoding uridine 5'-diphosphate-glucuronic acid transferases (UGTs) and extracellular matrix (ECM) components were downregulated. CONCLUSIONS: ARHGEF6 functions as a tumor suppressor in LUAD and may serve as a new prognostic marker and potential therapeutic target. Regulating tumor microenvironment and immunity, inhibiting the expression of UGTs and ECM components in the cancer cells, and decreasing the stemness of the tumors may among the mechanisms underlying the function of ARHGEF6 in LUAD.

A multistage multimodal deep learning model for disease severity assessment and early warnings of high-risk patients of COVID-19.

The outbreak of coronavirus disease 2019 (COVID-19) has caused massive infections and large death tolls worldwide. Despite many studies on the clinical characteristics and the treatment plans of COVID-19, they rarely conduct in-depth prognostic research on leveraging consecutive rounds of multimodal clinical examination and laboratory test data to facilitate clinical decision-making for the treatment of COVID-19. To address this issue, we propose a multistage multimodal deep learning (MMDL) model to (1) first assess the patient's current condition (i.e., the mild and severe symptoms), then (2) give early warnings to patients with mild symptoms who are at high risk to develop severe illness. In MMDL, we build a sequential stage-wise learning architecture whose design philosophy embodies the model's predicted outcome and does not only depend on the current situation but also the history. Concretely, we meticulously combine the latest round of multimodal clinical data and the decayed past information to make assessments and predictions. In each round (stage), we design a two-layer multimodal feature extractor to extract the latent feature representation across different modalities of clinical data, including patient demographics, clinical manifestation, and 11 modalities of laboratory test results. We conduct experiments on a clinical dataset consisting of 216 COVID-19 patients that have passed the ethical review of the medical ethics committee. Experimental results validate our assumption that sequential stage-wise learning outperforms single-stage learning, but history long ago has little influence on the learning outcome. Also, comparison tests show the advantage of multimodal learning. MMDL with multimodal inputs can beat any reduced model with single-modal inputs only. In addition, we have deployed the prototype of MMDL in a hospital for clinical comparison tests and to assist doctors in clinical diagnosis.

In-Situ Assembly of MoS2 Nanostructures on EHD-Printed Microscale PVDF Fibrous Films for Potential Energy Storage Applications.

Three-dimensional (3D) printing has been widely utilized to fabricate free-standing electrodes in energy-related fields. In terms of fabrication, the two most challenging limitations of 3D printed electrodes are the poor printing resolution and simple structural dimension. Here we proposed a novel process to fabricate molybdenum disulfide-polyvinylidene fluoride (MoS2-PVDF) hierarchical electrodes for energy storage applications. The 20-layer microscale PVDF films with a stable fiber width of 8.3 ± 1.2 µm were fabricated by using electrohydrodynamic (EHD) printing. MoS2 nanostructures were synthesized and assembled on the microscale PVDF fibers by using hydrothermal crystal growth. The structural and material investigations were conducted to demonstrate the geometrical morphology and materials component of the composite structure. The electrochemical measurements indicated that the MoS2-PVDF electrodes exhibited the typical charge-discharge performance with a mass specific capacitance of 60.2 ± 4.5 F/g. The proposed method offers a facile and scalable approach for the fabrication of high-resolution electrodes, which might be further developed with enhanced specific capacitance in energy storage fields.

Electrohydrodynamic printing of submicron-microscale hybrid scaffolds with improved cellular adhesion and proliferation behaviors.

Electrohydrodynamic (EHD) printing has been considered as a mature strategy to mimic the hierarchical microarchitectures in native extracellular matrix (ECM). Most of the EHD-printed scaffolds possess single-dimensional fibrous structures, which cannot mimic the multi-dimensional architectures for enhanced cellular behaviors. Here we developed a two-nozzle EHD printing system to fabricate hybrid scaffolds involving submicron and microscale features. The polyethylene oxide- polycaprolactone (PEO-PCL) submicron fibers were fabricated via solution-based EHD printing with a width of 527 ± 56 nm. The PCL microscale fibers were fabricated via melt-based EHD printing with a width of 11.2 ± 2.3µm. The hybrid scaffolds were fabricated by printing the submicron and microscale fibers in a layer-by-layer manner. The microscale scaffolds were utilized as a control group. Rat myocardial cells (H9C2 cells) were cultured on the two kinds of scaffolds for the culturing period of 1, 3 and 5 d. Biological results indicated that H9C2 cells showed enhanced adhesion and proliferation behaviors on the hybrid scaffold than those on the pure microscale scaffold. This work offers a facile and scalable strategy to fabricate multiscale synthetic scaffolds, which might be further explored to regulate cellular behaviors in the fields of tissue regeneration and biomedical engineering.

Molecular Characteristics and Genetic Evolution of Echovirus 33 in Mainland of China.

Echovirus, a member of the Enterovirus B (EV-B) family, has led to numerous outbreaks and pandemics, causing a broad spectrum of diseases. Based on the national hand, foot, and mouth disease (HFMD) surveillance system, seven strains of echovirus 33 (E33) were isolated from Mainland of China between 2010 and 2018. The whole genomes of these strains were isolated and sequenced, and phylogenetic trees were constructed based on the gene sequences in different regions of the EV-B prototype strains. It was found that E33 may be recombined in the P2 and P3 regions. Five genotypes (A-E) were defined based on the entire VP1 region of E33, of which the C gene subtype was the dominant gene subtype at present. Recombinant analysis showed that genotype C strains likely recombined with EV-B80, EV-B85, E13, and CVA9 in the P2 and P3 regions, while genotype E had the possibility of recombination with CVB3, E3, E6, and E4. Results of Bayesian analysis indicated that E33 may have appeared around 1955 (95% confidence interval: 1945-1959), with a high evolutionary rate of 1.11 × 10-2 substitution/site/year (95% highest posterior density (HPD): 8.17 × 10-3 to 1.4 × 10-2 substitution/site/year). According to spatial transmission route analysis, two significant transmission routes were identified: from Australia to India and from Oman to Thailand, which the E33 strain in Mainland of China likely introduced from Mexico and India. In conclusion, our study fills the gaps in the evolutionary analysis of E33 and can provide important data for enterovirus surveillance.

A novel gene signature derived from the CXC subfamily of chemokine receptors predicts the prognosis and immune infiltration of patients with lung adenocarcinoma.

The highly malignant nature of lung adenocarcinoma (LUAD) makes its early diagnosis and prognostic assessment particularly important. However, whether the CXC subfamily of chemokine receptors (CXCR) is involved in the development and prognosis of LUAD remains unclear. Here, differentially expressed genes (DEGs) associated with overall survival (OS) were selected from the cancer genome atlas (TCGA) dataset using univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) regression analysis. Then, a prognostic gene signature was constructed, which was evaluated using Kaplan-Meier curves, receiver operating characteristics curves, nomogram curves, and an external gene expression omnibus (GEO) dataset. Finally, we verified the functions of the genes comprising the signature using the gene expression profiling interactive analysis (GEPIA) and the immune system interaction database (TISIDB) web portals. We constructed a 7-gene signature (SHC1, PRKCD, VEGFC, RPS6KA1, CAT, CDC25C, and GPI) that stratified patients into high- and low-risk categories. Notably, the risk score of the signature was a separate and effective predictor for OS (P < .001). Patients in the low-risk category had a better prognosis than those in the high-risk category. The receiver operating characteristics and nomogram curves verified the predictive power of the signature. Moreover, in both categories, biological processes and pathways associated with cell migration were enriched. Immune infiltration statuses differed between the 2 risk categories. Critically, the results from the GEPIA and TISIDB web portals indicated that the expression of the 7-gene signature was associated with survival, clinical stage, and immune subtypes of LUAD patients. We identified a CXCR-related gene signature that could assess prognosis and provide a reference for the diagnosis and treatment of LUAD.