TONSL promotes lung adenocarcinoma progression, immune escape and drug sensitivity.

PURPOSE: The tonsoku-like DNA repair protein (TONSL) encoded by the TONSL gene, located on chromosome 8q24.3, is crucial for repairing DNA double-strand breaks through homologous recombination. However, TONSL overexpression in lung adenocarcinoma (LUAD) promotes tumor development, leading to a poor prognosis. METHODS: TONSL was verified as a reliable prognostic marker for LUAD using bioinformatics, and clinical features related to LUAD prognosis were screened from the TCGA database to establish the relationship between risk factors and TONSL expression. In addition, TONSL expression in normal and LUAD tissues was verified using real-time quantitative polymerase chain reaction and immunohistochemistry. To elucidate the possible functions of TONSL, TONSL-related differentially expressed genes were screened, and functional enrichment analysis was performed. Subsequently, siRNA was used to knock down TONSL expression in lung cancer cells for cytobehavioral experiments. The effects of TONSL expression on tumor immune escape were analyzed using the ESTIMATE algorithm and tumor immune-infiltration analysis. In addition, the half-maximal inhibitory concentration of LUAD with varying TONSL expression levels in response to first-line chemotherapeutic drugs and epidermal growth factor receptor-tyrosine kinase inhibitors was analyzed for drug sensitivity. RESULTS: Up-regulation of TONSL in LUAD promotes the proliferation, migration, and invasion of lung cancer cells, thereby contributing to a poor prognosis. Furthermore, TONSL overexpression promotes immune escape and drug sensitivity in LUAD. CONCLUSION: TONSL serves as a reliable prognostic marker for LUAD, and its up-regulation is associated with increased immune escape and drug sensitivity. These findings suggest that TONSL holds potential as a novel therapeutic target for LUAD.

Facile synthesis of a hydrazone-based zinc(ii) complex for ferroptosis-augmented sonodynamic therapy.

Sonodynamic therapy (SDT), as a novel non-invasive cancer treatment modality derived from photodynamic therapy (PDT), has drawn much attention due to its unique advantages for the treatment of deep tumors. Zinc-based complexes have shown great clinical prospect in PDT due to their excellent photodynamic activity and biosafety. However, their application in SDT has lagged seriously behind. Exploring efficient zinc-based complexes as sono-sensitizers remains an appealing but significantly challenging task. Herein, we develop a hydrazone ligand-based zinc complex (ZnAMTC) for SDT of tumors in vitro and in vivo. ZnAMTC was facilely synthesized via a two-step reaction from low-cost raw materials without tedious purification. It shows negligible dark toxicity and can produce singlet oxygen (1O2) under ultrasound (US) irradiation, exhibiting high sono-cytotoxicity to various cancer cells. Mechanism studies show that ZnAMTC can effectively reduce the levels of glutathione (GSH) and glutathione peroxidase 4 (GPX4) under US irradiation and later cause ferroptosis of cancer cells. In vivo studies further demonstrate that ZnAMTC exhibits efficient tumor growth inhibition under US irradiation and has good biosafety. This work provides useful insights into the design of first-row transition metal complexes for SDT application.

MIS18A upregulation promotes cell viability, migration and tumor immune evasion in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) presents a significant global health challenge owing to its poor prognosis and high mortality rates. Despite its involvement in the initiation and progression of a number of cancer types, the understanding of the precise impact of MIS18 kinetochore protein A (MIS18A) on LUAD remains incomplete. In the present study, the role of MIS18A in LUAD was investigated by analyzing the genomic and clinical data from multiple public datasets. The expression of MIS18A was validated using reverse transcription-quantitative polymerase chain reaction, and in vitro experiments involving small interfering RNA-induced downregulation of MIS18A in lung cancer cells were conducted to further explore its impact. These findings revealed that elevated MIS18A expression in LUAD was associated with advanced clinical features and poor prognosis. Functional analysis also revealed the role of MIS18A in regulating the cell cycle and immune-related pathways. Moreover, MIS18A altered the immune microenvironment in LUAD, influencing its response to immunotherapy and drug sensitivity. The results of the in vitro experiments indicated that suppression of MIS18A expression reduced the proliferative and migratory capacities of LUAD cells. In summary, MIS18A possesses potential as a biomarker and may serve as a possible therapeutic target for LUAD, with significant implications for tumor progression by influencing both cell cycle dynamics and immune infiltration.

Novel design of simplified ß-hairpin antimicrobial peptide as a potential food preservative based on Trp-pocket backbone.

Food contamination from microbial deterioration requires the development of potent antimicrobial peptides (AMPs). The deployment of approved AMPs as dietary preservatives is limited due to barriers such as instability, toxicity, and high synthetic costs. This exploration utilizes the primary structural elements of the Trp-pocket backbone to engineer a series of ß-hairpin AMPs (XWRWRPGXKXXR-NH2, X representing I, V, F, and/or L). Peptides WpLF, with Phe as X and Leu arranged at the 11th position, demonstrated exceptional selectivity index (SI = 123.08) and sterilization effects both in vitro and in vivo. WpLF consistently exhibited stable bacteriostasis, regardless of physiological salts, serum, and extreme pH. Mechanistic analysis indicated that the peptide penetrates microbial cell membranes, inducing membrane disruption, thereby impeding drug resistance evolution. Conclusively, AMPs engineered by the Trp-pocket skeleton hold substantial potential as innovative biological preservatives in food preservation, providing valuable insights for sustainable and safe peptide-based food preservatives.

Mesothelin-based CAR-T cells exhibit potent antitumor activity against ovarian cancer.

BACKGROUND: Ovarian cancer (OC) is characterized by its rapid growth and spread which, accompanied by a low 5-year survival rate, necessitates the development of improved treatments. In ovarian cancer, the selective overexpression of Mucin-16 (MUC16, CA125) in tumor cells highlights its potential as a promising target for developing anti-tumor therapies. However, the potential effectiveness of CAR-T cell therapy that targets MUC16 in ovarian cancer cells is unknown. METHODS: The expression of MUC16 in viable OC cells was detected using immunofluorescence and flow cytometry techniques. A MSLN-CAR construct, comprising the MUC16-binding polypeptide region of mesothelin (MSLN), a CD8 hinge spacer and transmembrane domain, 4-1BB, and CD3ζ endo-domains; was synthesized and introduced into T cells using lentiviral particles. The cytotoxicity of the resultant CAR-T cells was evaluated in vitro using luciferase assays. Cytokine release by CAR-T cells was measured using enzyme-linked immunosorbent assays. The anti-tumor efficacy of the CAR-T cells was subsequently assessed in mice through both systemic and local administration protocols. RESULTS: MSLN-CAR T cells exhibited potent cytotoxicity towards OVCAR3 cells and their stem-like cells that express high levels of MUC16. Also, MSLN-CAR T cells were inefficient at killing SKOV3 cells that express low levels of MUC16, but were potently cytotoxic to such cells overexpressing MUC16. Moreover, MSLN-CAR T cells delivered via tail vein or peritoneal injection could shrink OVCAR3 xenograft tumors in vivo, with sustained remission observed following peritoneal delivery of MSLN-CAR T cells. CONCLUSIONS: Collectively, these results suggested that MSLN-CAR T cells could potently eliminate MUC16- positive ovarian cancer tumor cells both in vitro and in vivo, thereby providing a promising therapeutic intervention for MUC16-positive patients.

Analysis of modulations of mental fatigue on intra-individual variability from single-trial event related potentials.

BACKGROUND: Intra-individual variability (IIV), a measure of variance within an individual's performance, has been demonstrated as metrics of brain responses for neural functionality. However, how mental fatigue modulates IIV remains unclear. Consequently, the development of robust mental fatigue detection methods at the single-trial level is challenging. NEW METHODS: Based on a long-duration flanker task EEG dataset, the modulations of mental fatigue on IIV were explored in terms of response time (RT) and trial-to-trial latency variations of event-related potentials (ERPs). Specifically, latency variations were quantified using residue iteration decomposition (RIDE) to reconstruct latency-corrected ERPs. We compared reconstructed ERPs with raw ERPs by means of temporal principal component analysis (PCA). Furthermore, a single-trial classification pipeline was developed to detect the changes of mental fatigue levels. RESULTS: We found an increased IIV in the RT metric in the fatigue state compared to the alert state. The same sequence of ERPs (N1, P2, N2, P3a, P3b, and slow wave, or SW) was separated from both raw and reconstructed ERPs using PCA, whereas differences between raw and reconstructed ERPs in explained variances for separated ERPs were found owing to IIV. Particularly, a stronger N2 was detected in the fatigue than alert state after RIDE. The single-trial fatigue detection pipeline yielded an acceptable accuracy of 73.3%. COMPARISON WITH EXISTING METHODS: The IIV has been linked to aging and brain disorders, and as an extension, our finding demonstrates IIV as an efficient indicator of mental fatigue. CONCLUSIONS: This study reveals significant modulations of mental fatigue on IIV at the behavioral and neural levels and establishes a robust mental fatigue detection pipeline.

Upregulation of POC1A in lung adenocarcinoma promotes tumour progression and predicts poor prognosis.

Lung adenocarcinoma (LUAD) is characterized by a high incidence rate and mortality. Recently, POC1 centriolar protein A (POC1A) has emerged as a potential biomarker for various cancers, contributing to cancer onset and development. However, the association between POC1A and LUAD remains unexplored. We extracted The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) data sets to analyse the differential expression of POC1A and its relationship with clinical stage. Additionally, we performed diagnostic receiver operator characteristic (ROC) curve analysis and Kaplan-Meier (KM) survival analysis to assess the diagnostic and prognostic value of POC1A in LUAD. Furthermore, we investigated the correlation between POC1A expression and immune infiltration, tumour mutation burden (TMB), immune checkpoint expression and drug sensitivity. Finally, we verified POC1A expression using real-time quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC). Cell experiments were conducted to validate the effect of POC1A expression on the proliferation, migration and invasion of lung cancer cells. POC1A exhibited overexpression in most tumour tissues, and its overexpression in LUAD was significantly correlated with late-stage presentation and poor prognosis. The high POC1A expression group showed lower levels of immune infiltration but higher levels of immune checkpoint expression and TMB. Moreover, the high POC1A expression group demonstrated sensitivity to multiple drugs. In vitro experiments confirmed that POC1A knockdown led to decreased proliferation, migration, and invasion of lung cancer cells. Our findings suggest that POC1A may contribute to tumour development by modulating the cell cycle and immune cell infiltration. It also represents a potential therapeutic target and marker for the diagnosis and prognosis of LUAD.

Novel CAR-T cells targeting TRKB for the treatment of solid cancer.

Chimeric antigen receptor (CAR) T-cell therapy is highly effective for treating blood cancers such as B-cell malignancies, however, its effectiveness as an approach to treat solid tumors remains to be further explored. Here, we focused on the development of CAR-T cell therapies targeting tropomyosin-related kinase receptor B (TRKB), a highly expressed protein that is significantly associated with tumor progression, malignancy, and drug resistance in multiple forms of aggressive solid tumors. To achieve this, we screened brain-derived neurotrophic factor (BDNF) and neurotrophin 4 (NTF4) ligand-based CAR-T cells for their efficiency in targeting the TRKB receptor in the context of solid tumors, particularly hepatocellular carcinoma and pancreatic cancer. We demonstrated that TRKB is overexpressed not only in hepatocellular carcinoma and pancreatic carcinoma cell lines but also in cancer stem-like cells (CSCs). Notably, BDNF-CAR T and NTF4-CAR T cells could not only effectively target and kill TRKB-expressing pan-cancer cell lines in a dose-dependent manner but also effectively kill CSCs. We also performed in vivo studies to show that NTF4-CAR T cells have a better potential to inhibit the tumor growth of hepatocellular carcinoma xenografts in mice, compared with BDNF-CAR T cells. Taken together, our findings suggest that CAR-T targeting TRKB may be a promising approach for developing novel therapies to treat solid cancers.

SPLiT: Single Portrait Lighting Estimation via a Tetrad of Face Intrinsics.

This paper proposes a novel pipeline to estimate a non-parametric environment map with high dynamic range from a single human face image. Lighting-independent and -dependent intrinsic images of the face are first estimated separately in a cascaded network. The influence of face geometry on the two lighting-dependent intrinsics, diffuse shading and specular reflection, are further eliminated by distributing the intrinsics pixel-wise onto spherical representations using the surface normal as indices. This results in two representations simulating images of a diffuse sphere and a glossy sphere under the input scene lighting. Taking into account the distinctive nature of light sources and ambient terms, we further introduce a two-stage lighting estimator to predict both accurate and realistic lighting from these two representations. Our model is trained supervisedly on a large-scale and high-quality synthetic face image dataset. We demonstrate that our method allows accurate and detailed lighting estimation and intrinsic decomposition, outperforming state-of-the-art methods both qualitatively and quantitatively on real face images.

Sigma-1 receptor regulates the endoplasmic reticulum stress pathway in the protective mechanism of dexmedetomidine against hyperoxia-induced lung injury.

Perioperative hyperoxia therapy is of great significance to save the lives of patients, but little is known about the possible mechanisms that induce hyperoxia-induced acute lung injury (HALI) and the measures for clinical prevention and treatment. In this experiment, the models were established with a feeding chamber with automatic regulation of oxygen concentration. The results showed that with the increase in inhaled oxygen concentration and the prolongation of exposure time, the severity of lung injury also increases significantly, reaching the diagnostic indication of HALI after 48 h of inhaling 95 % oxygen concentration. Subsequently, according to the dynamic changes of apoptosis in lung specimens, and the expression changes in Sig-1R-regulated ER stress pathway proteins (Sig-1R, GRP78, p-PERK, ATF6, IRE1, Caspase-12, ATF4, CHOP, Caspase-3 and p-JNK), it was confirmed that the Sig-1R-regulated ER stress signaling pathway was involved in the occurrence of HALI. To explore the preventive and therapeutic effects of routine clinical medication on HALI during the perioperative period, our research group selected dexmedetomidine (Dex) with lung protection. The experimental results revealed that Dex partially reversed the changes in the expression levels of Sig-1R-regulated ER stress pathway proteins. These results preliminarily confirmed that Dex may inhibit apoptosis induced by high oxygen concentration through the Sig-1R-regulated ER stress signaling pathway, thus playing a protective role in HALI.

Analysis of Nucleoporin 107 Overexpression and Its Association with Prognosis and Immune Infiltration in Lung Adenocarcinoma by Bioinformatics Methods.

Background: Lung adenocarcinoma (LUAD) has high morbidity and mortality. Current studies indicate nucleoporin 107 (NUP107) is involved in the construction of nuclear pore complex, and NUP107 overexpression contributes to the growth and development in most types of cancers, but its effect in LUAD has not been elucidated. Methods: Differences in NUP107 expression were investigated using the Cancer Genome Atlas (TCGA) and multiple Gene Expression Omnibus (GEO) data sets. Enrichment analysis were implemented to probe the NUP107 function. The association of NUP107 with the degree of immune cell infiltration was investigated by the TIMER database, single-sample gene set enrichment analysis (ssGSEA), and ESTIMATE. The association of NUP107 expression with tumor mutation burden (TMB), TP53, and immune checkpoint was analyzed. Single-cell RNA sequencing data were used to detect NUP107 expression in different cell clusters. Finally, we performed real-time quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC) to prove the difference of NUP107 expression. Results: NUP107 was overexpressed in LUAD and mainly expressed in cancer stem cell (CSC). Overexpression of NUP107 in LUAD suggested a poorer prognosis. Functional enrichment analysis pointed out that NUP107 was mainly linked to the regulation of cell cycle. Both immune cell infiltration and TMB were found to be in connection with NUP107. Cases in the group with high NUP107 expression had poorer immune infiltration, but had higher expression of immune checkpoints, TMB, and proportion of TP53 mutations. Conclusion: NUP107 is a sensitive diagnostic and prognostic factor for LUAD and may be involved in tumor progression through its effects on cell cycle and immune infiltration.

Association of C-reactive protein with mortality in Covid-19 patients: a secondary analysis of a cohort study.

Our study aimed to explore the association between serum C-reactive protein (CRP) and COVID-19 mortality. This is a retrospective cohort study of all patients admitted to 4 hospitals within the Montefiore Health System between March 1 and April 16, 2020, with SARS-CoV-2 infection. All-cause mortality were collected in 7 May 2020. The mortality risk was estimated using Cox proportional hazards models. Of the 3545 patients with a median age of 63.7 years, 918 (25.9%) died within the time of cohort data collection after admission. When the CRP was < 15.6 mg/L, the mortality rate increased with an adjusted HR of 1.57 (95% CI 1.30-1.91, P < 0.0001) for every 10 mg/L increment in the CRP. When the CRP was ≥ 15.6 mg/L, the mortality rate increased with an adjusted HR of 1.11 (95% CI 0.99-1.24, P = 0.0819) for every 10 mg/L increment in the CRP. For patients with COVID-19, the association between the CRP and the mortality risk was curve and had a saturation effect. When the CRP was small, the mortality rate increased significantly with the increase of CRP. When CRP > 15.6 mg/L, with the increase of CRP, the mortality rate increases relatively flat.

CAR-T Therapy Targets Extra Domain B of Fibronectin Positive Solid Tumor Cells.

BACKGROUND: CAR-T cell immunotherapy has achieved remarkable success in malignant B-cell malignancies, but progress in solid tumors is slow, and one of the key reasons is the lack of ideal targets. Cancer-specific extra domain B of fibronectin (EDB-FN) is widely upregulated in solid tumors and expressed at low levels in normal tissues. Many imaging and targeted cancer therapies based on EDB-FN targets have been developed and tested in clinical trials, making EDB-FN an ideal target for immunotherapy. METHODS: We constructed two EDB-FN-targeted CAR-Ts based on the peptide APT0 and the single-chain antibody CGS2 in a lentiviral infection manner for the first time. Luciferase cytotoxicity assay to assess CAR-T killing of tumor cells. An enzyme-linked immunosorbent assay was used to detect the release of the cytokine IFN-γ. Fluorescence imaging to evaluate the dynamics of CAR-T cell and tumor cell coculture. Knockdown assays were used to validate the target specificity of CAR-T cells. RESULTS: In this research, two CAR-Ts targeting EDB-FN, APT0 CAR-T, and CGS2 CAR-T, were constructed. In vitro, both CAR-T cells produced broad-spectrum killing of multiple EDB-FN-positive solid tumor cell lines and were accompanied by cytokine IFN-γ release. Regarding safety, the two CAR-T cells did not affect T cells' normal growth and proliferation and were not toxic to HEK-293T human embryonic kidney epithelial cells. CONCLUSION: APT0 CAR-T and CGS2 CAR-T cells are two new CAR-Ts targeting EDB-FN. Both CAR-T cells can successfully identify and specifically kill various EDB-FN-positive solid tumor cells with potential clinical applications.

Hepatocyte-specific HDAC3 ablation promotes hepatocellular carcinoma in females by suppressing Foxa1/2.

BACKGROUND: Hepatocellular carcinoma (HCC), the most common primary liver cancer, prevails mainly in males and has long been attributed to androgens and higher circumstantial levels of interleukin-6 (IL-6) produced by resident hepatic macrophages. METHODS: Constitutively hepatocyte-specific histone deacetylase 3 (HDAC3)-deficient (HDAC3LCKO) mice and constitutively hepatocyte-specific HDAC3 knockout and systemic IL-6 simultaneously ablated (HDAC3LCKO& IL-6-/-) mice were used in our study to explore the causes of sex differences in HCC. Additionally, we performed human HCC tissues with an IHC score. Correlation analysis and linear regression plots were constructed to reveal the association between HDAC3 and its candidate genes. To further elucidate that HDAC3 controls the expression of Foxa1/2, we knocked down HDAC3 in HUH7 liver cancer cells. RESULTS: We observed a contrary sex disparity, with an earlier onset and higher incidence of HCC in female mice when HDAC3 was selectively ablated in the liver. Loss of HDAC3 led to constant liver injury and the spontaneous development of HCC. Unlike the significant elevation of IL-6 in male mice at a very early age, female mice exhibit stable IL-6 levels, and IL-6 ablation did not eliminate the sex disparity in hepatocarcinogenesis in HDAC3-deficient mice. Oestrogen often protects the liver when combined with oestrogen receptor alpha (ERα); however, ovariectomy in HDAC3-ablated female mice significantly delayed tumourigenesis. The oestrogen-ERα axis can also play a role in tumour promotion in the absence of Foxa1 and Foxa2 in the receptor complex. Loss of HDAC3 profoundly reduced the expression of both Foxa1 and Foxa2 and impaired the binding between Foxa1/2 and ERα. Furthermore, a more frequent HDAC3 decrease accompanied by the simultaneous Foxa1/2 decline was found in female HCC compared to that in male HCC. CONCLUSION: In summary, we reported that loss of HDAC3 reduces Foxa1/2 and thus promotes HCC development in females in an oestrogen-dependent manner.

High SGO2 predicted poor prognosis and high therapeutic value of lung adenocarcinoma and promoted cell proliferation, migration, invasion, and epithelial-to-mesenchymal transformation.

Background: Shugoshin 2 (SGO2), a component of the cell division cohesion complex, is involved in both mitotic and meiotic processes. Despite being overexpressed in various malignant tumors and is associated with poor prognosis, its exact role in lung adenocarcinoma (LUAD) and its biological effects on lung cancer cells are not well understood. Methods: The transcriptomics data and clinical information for LUAD were obtained from TCGA and GEO, and DEGs associated with prognostic risk factors were screened using Cox regression analysis and chi-square testing. Identify these gene functions using correlation heatmaps, protein interaction networks (PPIs), and KEGG enrichment assays. The expression of SGO2 in tissues was verified by PCR and IHC, and the prognostic value of SGO2 in LUAD was evaluated by survival analysis. In addition, the effects of SGO2 knockdown on lung cancer cell proliferation, migration, invasion, and epithelial-to-mesenchymal transition (EMT) were studied in vitro. After that, the TIMER database and single-sample GSEA (ssGSEA) analysis were used to investigate the correlation between SGO2 and immune infiltration. Finally, the tumor mutational burden (TMB) of different SGO2 clusters and the efficacy of the two clusters in multiple treatments were evaluated. Results: High-risk genes associated with poor prognosis in LUAD are involved in cell cycle regulation and proliferation. Among these genes, SGO2 exhibited high expression in LUAD and corresponded with the TNM stage. Furthermore, the knockdown of SGO2 led to a decrease in the proliferation, migration, invasion, and EMT processes of lung cancer cells. Notably, high SGO2 expression may have poorer anti-tumor immunity and may therefore be more suitable for immunotherapy to re-establish immune function, while its high expression with a higher TMB could enable LUAD to benefit from multiple therapies. Conclusion: Our findings suggest that SGO2 may be a promising prognostic biomarker for LUAD, particularly in regulating the cell cycle and benefiting from multiple therapies.

Ultrashort All-Hydrocarbon Stapled α-Helix Amphiphile as a Potent and Stable Antimicrobial Compound.

The ravaging effect of drug-resistant bacteria has heightened the need for the development of membrane-soluble antimicrobial peptides (AMPs). However, their potential for clinical use is hindered by issues such as poor biocompatibility, salt sensitivity, and proteolytic lability. In this study, a series of ultrashort stapled cyclization heptapeptides were obtained by inserting all-hydrocarbon staples. StRRL with the highest therapeutic index (TI = 36.3) was selected after evaluating its antibacterial and toxic activity. Furthermore, stRRL demonstrated exceptional performance in high-protease and high-salt environments, making it an effective weapon against bacteria like Escherichia coli in a mouse peritonitis-sepsis model. The membrane lytic mechanism of stRRL, which operates from outside to inside, gives it a low drug-resistant tendency. This suggests that stRRL has the potential to replace antibiotics as a powerful candidate in tackling bacterial infection. In conclusion, the ultrashort all-hydrocarbon stapled antimicrobial amphiphiles inaugurated a novel entrance to the advancements of highly stable peptide compounds.

Oncogenic role and drug sensitivity of ETV4 in human tumors: a pan-cancer analysis.

Background: Increasing evidence supports a relationship between E twenty-six variant transcription factor 4 (ETV4) and several cancers, but no pan-cancer analysis has been reported. Methods: The present study surveyed the effects of ETV4 on cancer using RNA sequencing data obtained from The Cancer Genome Atlas and GTEx, and further explored its role in drug sensitivity using data from Cellminer. Differential expression analyses were conducted for multiple cancers using R software. Cox regression and survival analysis were employed to calculate correlations between ETV4 levels and survival outcomes in multiple cancers using the online tool Sangerbox. ETV4 expression was also compared with immunity, heterogeneity, stemness, mismatch repair genes, and DNA methylation among different cancers. Results: ETV4 was found to be significantly upregulated in 28 tumors. Upregulation of ETV4 was associated with poor overall survival, progression free interval, disease-free-interval, and disease specific survival in several cancer types. Expression of ETV4 was also remarkably correlated with immune cell infiltration, tumor heterogeneity, mismatch repair gene expression, DNA methylation, and tumor stemness. Furthermore, ETV4 expression seemed to affect sensitivity to a number of anticancer drugs. Conclusions: These results suggest that ETV4 may be useful as a prognostic factor and therapeutic target.

Association of age at menarche with valvular heart disease: An analysis based on electronic health record (CREAT2109).

Background: The association between age at menarche and coronary heart disease has been reported, but the association between age at menarche and valvular heart disease (VHD) has not been described. We aimed to examine the association between age at menarche and VHD. Methods: By collecting data from four medical centers of the Affiliated Hospital of Qingdao University (QUAH) from January 1, 2016, to December 31, 2020, we sampled 105,707 inpatients. The main outcome of this study was newly diagnosed VHD, which was diagnosed based on ICD-10 coding, and the exposure factor was age at menarche, which was accessed through the electronic health records. We used logistic regression model to investigate the association between age at menarche and VHD. Results: In this sample (mean age 55.31 ± 13.63 years), the mean age at menarche was 15. Compared with women with age at menarche 14-15 years, the odds ratio of VHD in women with age at menarche ≤13, 16-17, and ≥18 years was 0.68 (95% CI 0.57-0.81), 1.22 (95% CI 1.08-1.38), and 1.31 (95% CI 1.13-1.52), respectively (P for all < 0.001). By restricting cubic splines, we found that later menarche was associated with increased odds of VHD (P < 0.001). Furthermore, in subgroup analysis of different etiologies, the similar trend persisted for non-rheumatic VHD. Conclusions: In this large inpatient sample, later menarche was associated with higher risk of VHD.

Dynamic Community Detection for Brain Functional Networks During Music Listening With Block Component Analysis.

The human brain can be described as a complex network of functional connections between distinct regions, referred to as the brain functional network. Recent studies show that the functional network is a dynamic process and its community structure evolves with time during continuous task performance. Consequently, it is important for the understanding of the human brain to develop dynamic community detection techniques for such time-varying functional networks. Here, we propose a temporal clustering framework based on a set of network generative models and surprisingly it can be linked to Block Component Analysis to detect and track the latent community structure in dynamic functional networks. Specifically, the temporal dynamic networks are represented within a unified three-way tensor framework for simultaneously capturing multiple types of relationships between a set of entities. The multi-linear rank- (Lr, Lr, 1) block term decomposition (BTD) is adopted to fit the network generative model to directly recover underlying community structures with the specific evolution of time from the temporal networks. We apply the proposed method to the study of the reorganization of the dynamic brain networks from electroencephalography (EEG) data recorded during free music listening. We derive several network structures ( Lr communities in each component) with specific temporal patterns (described by BTD components) significantly modulated by musical features, involving subnetworks of frontoparietal, default mode, and sensory-motor networks. The results show that the brain functional network structures are dynamically reorganized and the derived community structures are temporally modulated by the music features. The proposed generative modeling approach can be an effective tool for describing community structures in brain networks that go beyond static methods and detecting the dynamic reconfiguration of modular connectivity elicited by continuously naturalistic tasks.

Unsupervised representation learning of spontaneous MEG data with nonlinear ICA.

Resting-state magnetoencephalography (MEG) data show complex but structured spatiotemporal patterns. However, the neurophysiological basis of these signal patterns is not fully known and the underlying signal sources are mixed in MEG measurements. Here, we developed a method based on the nonlinear independent component analysis (ICA), a generative model trainable with unsupervised learning, to learn representations from resting-state MEG data. After being trained with a large dataset from the Cam-CAN repository, the model has learned to represent and generate patterns of spontaneous cortical activity using latent nonlinear components, which reflects principal cortical patterns with specific spectral modes. When applied to the downstream classification task of audio-visual MEG, the nonlinear ICA model achieves competitive performance with deep neural networks despite limited access to labels. We further validate the generalizability of the model across different datasets by applying it to an independent neurofeedback dataset for decoding the subject's attentional states, providing a real-time feature extraction and decoding mindfulness and thought-inducing tasks with an accuracy of around 70% at the individual level, which is much higher than obtained by linear ICA or other baseline methods. Our results demonstrate that nonlinear ICA is a valuable addition to existing tools, particularly suited for unsupervised representation learning of spontaneous MEG activity which can then be applied to specific goals or tasks when labelled data are scarce.