Incretin-based drugs decrease the incidence of prostate cancer in type 2 diabetics: A pooling-up analysis.

Incretin-based drugs, a class of Antidiabetic medications (ADMs) used in the treatment of type 2 diabetes, may affect the incidence of prostate cancer (PCa). But real-world evidence for this possible effect is lacking. Therefore, the aim of this study is to assess the effect of incretin-based drugs on the incidence of PCa, including glucagon-like peptide-1 (GLP-1) receptor agonists and dipeptidyl peptidase-4 (DPP-4) inhibitors. We searched PubMed, Embase, and Cochrane Library databases for eligible studies through September 2023. Two independent reviewers performed screening and data extraction. We used the Cochrane Handbook for Systematic Reviews and the Newcastle-Ottawa Scale (NOS) to assess the quality of included randomized controlled trials (RCTs) and cohort studies. We did a meta-analysis of available trial data to calculate overall risk ratios (RRs) for PCa. A total of 1238 articles were identified in our search. After screening for eligibility, 7 high-quality studies met the criteria for meta-analysis, including 2 RCTs and 5 cohort studies, with a total of 1165,738 patients. Compared with the control group, we found that incretin-based drugs reduced the relative risk of PCa by 35% (95% confidence interval (CI), 0.17-0.49; P = .0006). In subgroup analysis, the RR values for GLP-1 receptor agonists and DPP-4 inhibitors were 62% (95% CI, 0.45-0.85; P = .003) and 72% (95% CI, 0.46-1.12; P = .14), respectively. Incretin-based drugs are associated with lower incidence of prostate cancer and may have a preventive effect on prostate cancer in patients with type 2 diabetes.

GTADC: A Graph-Based Method for Inferring Cell Spatial Distribution in Cancer Tissues.

The heterogeneity of tumors poses a challenge for understanding cell interactions and constructing complex ecosystems within cancer tissues. Current research strategies integrate spatial transcriptomics (ST) and single-cell sequencing (scRNA-seq) data to thoroughly analyze this intricate system. However, traditional deep learning methods using scRNA-seq data tend to filter differentially expressed genes through statistical methods. In the context of cancer tissues, where cancer cells exhibit significant differences in gene expression compared to normal cells, this heterogeneity renders traditional analysis methods incapable of accurately capturing differences between cell types. Therefore, we propose a graph-based deep learning method, GTADC, which utilizes Silhouette scores to precisely capture genes with significant expression differences within each cell type, enhancing the accuracy of gene selection. Compared to traditional methods, GTADC not only considers the expression similarity of genes within their respective clusters but also comprehensively leverages information from the overall clustering structure. The introduction of graph structure effectively captures spatial relationships and topological structures between the two types of data, enabling GTADC to more accurately and comprehensively resolve the spatial composition of different cell types within tissues. This refinement allows GTADC to intricately reconstruct the cellular spatial composition, offering a precise solution for inferring cell spatial composition. This method allows for early detection of potential cancer cell regions within tissues, assessing their quantity and spatial information in cell populations. We aim to achieve a preliminary estimation of cancer occurrence and development, contributing to a deeper understanding of early-stage cancer and providing potential support for early cancer diagnosis.

Dietary exposure to 2,2',4,4'-tetrabromodiphenyl ether (BDE-47) induces oxidative damage promoting cell apoptosis primarily via mitochondrial pathway in the hepatopancreas of carp, Cyprinus carpio.

To investigate the mechanisms of BDE-47 on hepatotoxicity in fish, this study examined the effects of dietary exposure to BDE-47 (40 and 4000 ng/g) on carp for 42 days. The results showed that BDE-47 significantly increased carp's condition factor and hepatosomatic index. Pathological results revealed unclear hepatic cord structure, hepatocytes swelling, cellular vacuolization, and inflammatory cell infiltration in the hepatopancreas of carp. Further investigation showed that ROS levels significantly increased on days 7, 14, and 42. Moreover, the activities of antioxidant enzymes SOD, GSH, CAT, and GST increased significantly from 1 to 7 days, and the transcription levels of antioxidant enzymes CAT, Cu-Zn SOD, Mn-SOD, GST, and GPX, and antioxidant pathway genes Keap1, Nrf2, and HO-1 changed significantly at multiple time-points during the 42 days. The results of apoptosis pathway genes showed that the mitochondrial pathway genes Bax, Casp3, and Casp9 were significantly upregulated and Bcl2 was significantly downregulated, while the transcription levels of FADD and PERK were significantly enhanced. These results indicate that BDE-47 induced oxidative damage in hepatopancreas, then it promoted cell apoptosis mainly through the mitochondrial pathway. This study provides a foundation for analyzing the mechanism of hepatotoxicity induced by BDE-47 on fish.

Enhancing lung cancer detection through hybrid features and machine learning hyperparameters optimization techniques.

Machine learning offers significant potential for lung cancer detection, enabling early diagnosis and potentially improving patient outcomes. Feature extraction remains a crucial challenge in this domain. Combining the most relevant features can further enhance detection accuracy. This study employed a hybrid feature extraction approach, which integrates both Gray-level co-occurrence matrix (GLCM) with Haralick and autoencoder features with an autoencoder. These features were subsequently fed into supervised machine learning methods. Support Vector Machine (SVM) Radial Base Function (RBF) and SVM Gaussian achieved perfect performance measures, while SVM polynomial produced an accuracy of 99.89% when utilizing GLCM with an autoencoder, Haralick, and autoencoder features. SVM Gaussian achieved an accuracy of 99.56%, while SVM RBF achieved an accuracy of 99.35% when utilizing GLCM with Haralick features. These results demonstrate the potential of the proposed approach for developing improved diagnostic and prognostic lung cancer treatment planning and decision-making systems.

Photo-Reactivity of dissolved black carbon unveiled by combination of optical spectroscopy and FT-ICR MS analysis: Effects of pyrolysis temperature.

Dissolved black carbon (DBC) has high photoactivity, which plays an important role in contaminants photodegradation. However, it is unclear how pyrolysis temperatures would affect the composition and photo-reactivity of DBC at the molecular level. Herein, we combined complementary techniques to study the characteristics of DBC pyrolyzed at 200 - 500 ℃, as well as the photoproduction of reactive species and the photodegradation of tetracycline (TC). Bulk composition characterization found that condensed aromatic carbonyl compounds (ConAC) with narrow molecular weights in DBC experienced an increase from 200 to 500 °C, which enhanced the photoproduction of 3DBC*,1O2, and ·OH. Molecular-level data suggested that 3DBC* and 1O2 were both related to the same DBC compounds. Comparatively, the patterns for ·OH were less pronounced, implying its precursor was not 3DBC* and had more complexity. Plentiful CHOx species of ConAC in DBC400 and DBC500 (DBCT, where T = pyrolysis temperature) accelerated the generation of 3DBC* and 1O2, enhancing the photodegradation of TC, and mainly triplet states of quinones reacted with TC. In contrast, DBC200 and DBC300 exhibited inhibition since massive CHOx species in lignin-like reduced 3TC* to TC. Our data revealed the diverse photochemical behavior mechanisms of DBC pyrolyzed at 200 - 500 ℃ at the molecular level and the implications for aquatic contaminants photochemistry.

GTAD: a graph-based approach for cell spatial composition inference from integrated scRNA-seq and ST-seq data.

With the emergence of spatial transcriptome sequencing (ST-seq), research now heavily relies on the joint analysis of ST-seq and single-cell RNA sequencing (scRNA-seq) data to precisely identify cell spatial composition in tissues. However, common methods for combining these datasets often merge data from multiple cells to generate pseudo-ST data, overlooking topological relationships and failing to represent spatial arrangements accurately. We introduce GTAD, a method utilizing the Graph Attention Network for deconvolution of integrated scRNA-seq and ST-seq data. GTAD effectively captures cell spatial relationships and topological structures within tissues using a graph-based approach, enhancing cell-type identification and our understanding of complex tissue cellular landscapes. By integrating scRNA-seq and ST data into a unified graph structure, GTAD outperforms traditional 'pseudo-ST' methods, providing robust and information-rich results. GTAD performs exceptionally well with synthesized spatial data and accurately identifies cell spatial composition in tissues like the mouse cerebral cortex, cerebellum, developing human heart and pancreatic ductal carcinoma. GTAD holds the potential to enhance our understanding of tissue microenvironments and cellular diversity in complex bio-logical systems. The source code is available at https://github.com/zzhjs/GTAD.

Starvation induces hepatopancreas atrophy in Chinese mitten crab (Eriocheir sinensis) by inhibiting angiogenesis.

BACKGROUND: The hepatopancreas of crustaceans serves as a significant organ for both the synthesis and secretion of digestive enzymes, as well as energy storage. In the event of food shortage, the hepatopancreas can provide energy for survival. To investigate the potential regulatory mechanisms of the hepatopancreas in response to starvation in Eriocheir Sinensis, transcriptome analysis, histological study and qRT-PCR were performed. RESULTS: The results showed that starvation caused a decrease in the hepatopancreas index of E. sinensis, which had certain effects on the tissue structure, metabolism and angiogenesis in the hepatopancreas. In addition, WGCNA and linear regression analysis showed that the genes significantly related to the hepatopancreas index were mainly enriched in the angiogenesis pathway, in which AKT signaling played an important role. Starvation may inhibit AKT signaling pathway by reducing the expression of TGFBI, HSP27, HHEX, and EsPVF1, thereby hindering angiogenesis, promoting apoptosis, and leading to hepatopancreas atrophy. CONCLUSION: These results indicate that AKT plays an important role in the angiogenesis pathway and apoptosis of the starvation induced hepatopancreas index reduction, which is beneficial to further understand the effect of starvation stress on hepatopancreas of Chinese mitten crab.

Single-cell transcriptome analysis indicates fatty acid metabolism-mediated metastasis and immunosuppression in male breast cancer.

Male breast cancer (MBC) is a rare but aggressive malignancy with cellular and immunological characteristics that remain unclear. Here, we perform transcriptomic analysis for 111,038 single cells from tumor tissues of six MBC and thirteen female breast cancer (FBC) patients. We find that that MBC has significantly lower infiltration of T cells relative to FBC. Metastasis-related programs are more active in cancer cells from MBC. The activated fatty acid metabolism involved with FASN is related to cancer cell metastasis and low immune infiltration of MBC. T cells in MBC show activation of p38 MAPK and lipid oxidation pathways, indicating a dysfunctional state. In contrast, T cells in FBC exhibit higher expression of cytotoxic markers and immune activation pathways mediated by immune-modulatory cytokines. Moreover, we identify the inhibitory interactions between cancer cells and T cells in MBC. Our study provides important information for understanding the tumor immunology and metabolism of MBC.

DeepICSH: a complex deep learning framework for identifying cell-specific silencers and their strength from the human genome.

Silencers are noncoding DNA sequence fragments located on the genome that suppress gene expression. The variation of silencers in specific cells is closely related to gene expression and cancer development. Computational approaches that exclusively rely on DNA sequence information for silencer identification fail to account for the cell specificity of silencers, resulting in diminished accuracy. Despite the discovery of several transcription factors and epigenetic modifications associated with silencers on the genome, there is still no definitive biological signal or combination thereof to fully characterize silencers, posing challenges in selecting suitable biological signals for their identification. Therefore, we propose a sophisticated deep learning framework called DeepICSH, which is based on multiple biological data sources. Specifically, DeepICSH leverages a deep convolutional neural network to automatically capture biologically relevant signal combinations strongly associated with silencers, originating from a diverse array of biological signals. Furthermore, the utilization of attention mechanisms facilitates the scoring and visualization of these signal combinations, whereas the employment of skip connections facilitates the fusion of multilevel sequence features and signal combinations, thereby empowering the accurate identification of silencers within specific cells. Extensive experiments on HepG2 and K562 cell line data sets demonstrate that DeepICSH outperforms state-of-the-art methods in silencer identification. Notably, we introduce for the first time a deep learning framework based on multi-omics data for classifying strong and weak silencers, achieving favorable performance. In conclusion, DeepICSH shows great promise for advancing the study and analysis of silencers in complex diseases. The source code is available at https://github.com/lyli1013/DeepICSH.

Transcriptome Revealed the Macrophages Inflammatory Response Mechanism and NOD-like Receptor Characterization in Siberian Sturgeon (Acipenser baerii).

Nucleotide-binding and oligomerization domain-like receptors (NOD-like receptors, NLRs) can regulate the inflammatory response to eliminate pathogens and maintain the host's homeostasis. In this study, the head kidney macrophages of Siberian sturgeon were treated with lipopolysaccharide (LPS) to induce inflammation by evaluating the expression of cytokines. The high-throughput sequencing for macrophages after 12 h treatment showed that 1224 differentially expressed genes (DEGs), including 779 upregulated and 445 downregulated, were identified. DEGs mainly focus on pattern recognition receptors (PRRs) and the adaptor proteins, cytokines, and cell adhesion molecules. In the NOD-like receptor signaling pathway, multiple NOD-like receptor family CARD domains containing 3-like (NLRC3-like) were significantly downregulated, and pro-inflammatory cytokines were upregulated. Based on the transcriptome database, 19 NLRs with NACHT structural domains were mined and named in Siberian sturgeon, including 5 NLR-A, 12 NLR-C, and 2 other NLRs. The NLR-C subfamily had the characteristics of expansion of the teleost NLRC3 family and lacked the B30.2 domain compared with other fish. This study revealed the inflammatory response mechanism and NLRs family characterization in Siberian sturgeon by transcriptome and provided basic data for further research on inflammation in teleost.

DeepITEH: a deep learning framework for identifying tissue-specific eRNAs from the human genome.

MOTIVATION: Enhancers are vital cis-regulatory elements that regulate gene expression. Enhancer RNAs (eRNAs), a type of long noncoding RNAs, are transcribed from enhancer regions in the genome. The tissue-specific expression of eRNAs is crucial in the regulation of gene expression and cancer development. The methods that identify eRNAs based solely on genomic sequence data have high error rates because they do not account for tissue specificity. Specific histone modifications associated with eRNAs offer valuable information for their identification. However, identification of eRNAs using histone modification data requires the use of both RNA-seq and histone modification data. Unfortunately, many public datasets contain only one of these components, which impedes the accurate identification of eRNAs. RESULTS: We introduce DeepITEH, a deep learning framework that leverages RNA-seq data and histone modification data from multiple samples of the same tissue to enhance the accuracy of identifying eRNAs. Specifically, deepITEH initially categorizes eRNAs into two classes, namely, regularly expressed eRNAs and accidental eRNAs, using histone modification data from multiple samples of the same tissue. Thereafter, it integrates both sequence and histone modification features to identify eRNAs in specific tissues. To evaluate the performance of DeepITEH, we compared it with four existing state-of-the-art enhancer prediction methods, SeqPose, iEnhancer-RD, LSTMAtt, and FRL, on four normal tissues and four cancer tissues. Remarkably, seven of these tissues demonstrated a substantially improved specific eRNA prediction performance with DeepITEH, when compared with other methods. Our findings suggest that DeepITEH can effectively predict potential eRNAs on the human genome, providing insights for studying the eRNA function in cancer. AVAILABILITY AND IMPLEMENTATION: The source code and dataset of DeepITEH have been uploaded to https://github.com/lyli1013/DeepITEH.

Effect of adsorption on ferrihydrite on the photoreactivity of dissolved black carbon for photodegradation of sulfadiazine.

The selective adsorption of dissolved black carbon (DBC) on inorganic minerals is a widespread geochemical process in the natural environment, which could change the chemical and optical properties of DBC. However, it remains unclear how selective adsorption affects the photoreactivity of DBC for photodegradation of organic pollutants. This paper was the first to investigate the effect of DBC adsorption on ferrihydrite at different Fe/C molar ratios (Fe/C molar ratios of 0, 7.50 and 11.25, and marked as DBC0, DBC7.50 and DBC11.25) on the photoproduction of reactive intermediates generated from DBC and their interaction with sulfadiazine (SD). Results showed that UV absorbance, aromaticity, molecular weight and contents of phenolic antioxidants of DBC were significantly decreased after adsorption on ferrihydrite, and higher decrease was observed at higher Fe/C ratio. Photodegradation kinetics experiments showed that observed photodegradation rate constant of SD (kobs) increased from 3.99 × 10-5 s-1 in DBC0 to 5.69 × 10-5 s-1 in DBC7.50 while decreased to 3.44 × 10-5 s-1 in DBC11.25, in which 3DBC* played an important role and 1O2 played a minor role, while ·OH was not involved in the reaction. Meanwhile, the second-order reaction rate constant between 3DBC* and SD (kSD, 3DBC*) increased from 0.84 × 108 M-1 s-1 for DBC0 to 2.53 × 108 M-1 s-1 for DBC7.50 while decreased to 0.90 × 108 M-1 s-1 for DBC11.25. The above results might be mainly attributed to the fact that the decrease of phenolic antioxidants in DBC weakened the back-reduction of 3DBC* and reactive intermediates of SD as the Fe/C ratio increased, while the decrease of quinones and ketones reduced the photoproduction of 3DBC*. The research revealed adsorption on ferrihydrite affected the photodegradation of SD by changing the reactivity of 3DBC*, which was helpful to understand the dynamic roles of DBC in the photodegradation of organic pollutants.

Locally advanced sinonasal adenoid cystic carcinomas: endoscopic endonasal surgery-centered comprehensive treatment provides benefits.

BACKGROUND: Sinonasal adenoid cystic carcinomas (SNACCs) are aggressive tumors that show massive expansion and are challenging to treat when locally advanced. AIMS: To report our experiences with endoscopic endonasal surgery (EES) - centered comprehensive treatment and discuss the associated outcomes of these patients. MATERIAL AND METHODS: A retrospective review of primary locally advanced SNACCs patients was conducted in a single center. EES combined with postoperative radiotherapy (PORT) was used as a comprehensive surgery-centered approach to treat these patients. RESULTS: The study included 44 patients with Stage III/IV tumors. The median follow-up duration was 43 months (4-161 months). Forty-two patients underwent PORT. The 5-year overall survival (OS) and disease-free survival (DFS) rates were 61.2% and 46%, respectively. Local recurrence occurred in 7 patients, and 19 patients had distant metastasis. No significant relationship was found between OS and postoperative local recurrence. The OS of patients with Stage IV or exhibiting distant postoperative metastases was shorter than that of other patients. CONCLUSIONS AND SIGNIFICANCE: Locally advanced SNACCs are not a contraindication for EES. EES-centered comprehensive treatment can ensure satisfactory survival rates and reasonable local control. Function-preserving surgery using EES and PORT may represent an alternative strategy when vital structures are involved.

Effect of celecoxib plus standard chemotherapy on cancer prognosis: A systematic review and meta-analysis.

BACKGROUND: Inflammation is closely related to cancer prognosis. The effect of celecoxib, a nonsteroidal anti-inflammatory drug, on the prognosis of patients with cancer remains uncertain. To assess the association between celecoxib plus standard chemotherapy and cancer prognosis, we conducted a systematic review and meta-analysis of published studies. METHODS: PubMed, EMBASE, and the Cochrane Library were searched from inception until July 2022 for randomized controlled trials reporting the prognosis of patients with cancer treated with celecoxib plus standard chemotherapy. The primary endpoints were overall survival (OS) and progression-free survival (PFS). Meta-analysis was performed using Review Manager software version 5.4. The following search terms were used in the databases: ((((celecoxib)) AND ((((((((cancer) OR (carcinoma)) OR (sarcoma)) OR (neoplasms)) OR (tumor)) OR (tumour)) OR (tumors)) OR (tumours))) AND ((survival) OR (mortality))) AND (((Clinical Trials, Randomized) OR (Trials, Randomized Clinical)) OR (Controlled Clinical Trials, Randomized)). RESULTS: Overall, 13 randomized controlled trials, including 8957 patients with cancer, were included in the analysis. Compared to conventional chemotherapy alone, 1-year OS and 1-year PFS rates were not significantly improved with celecoxib adjuvant therapy (OS: p = .38; PFS: p = .65). In addition, no differences were observed between the celecoxib and placebo groups in 3-year overall (p = .98), 3-year progression-free (p = .40), 5-year overall (p = .59), or 5-year progression-free (p = .56) survival rates. An increase in the risk ratio of leukopenia (p = .02) and thrombocytopenia (p = .05) was also observed, suggesting that celecoxib promotes hematologic toxicity. No increased risk of cardiovascular (p = .96) and gastrointestinal (p = .10-.91) events was observed. CONCLUSIONS: The addition of celecoxib to standard chemotherapy did not improve OS or PFS rates of patients with cancer. Additionally, celecoxib can increase hematologic toxicity without increasing the risk of gastrointestinal or cardiovascular reactions. Further randomized controlled trials are necessary to clarify its effects and applications.

Phagocytosis of Glioma Cells Enhances the Immunosuppressive Phenotype of Bone Marrow-Derived Macrophages.

Tumor-associated macrophages (TAM) play a crucial role in immunosuppression. However, how TAMs are transformed into immunosuppressive phenotypes and influence the tumor microenvironment (TME) is not fully understood. Here, we utilized single-cell RNA sequencing and whole-exome sequencing data of glioblastoma (GBM) tissues and identified a subset of TAMs dually expressing macrophage and tumor signatures, which were termed double-positive TAMs. Double-positive TAMs tended to be bone marrow-derived macrophages (BMDM) and were characterized by immunosuppressive phenotypes. Phagocytosis of glioma cells by BMDMs in vitro generated double-positive TAMs with similar immunosuppressive phenotypes to double-positive TAMs in the GBM TME of patients. The double-positive TAMs were transformed into M2-like macrophages and drove immunosuppression by expressing immune-checkpoint proteins CD276, PD-L1, and PD-L2 and suppressing the proliferation of activated T cells. Together, glioma cell phagocytosis by BMDMs in the TME leads to the formation of double-positive TAMs with enhanced immunosuppressive phenotypes, shedding light on the processes driving TAM-mediated immunosuppression in GBM. SIGNIFICANCE: Bone marrow-derived macrophages phagocytose glioblastoma cells to form double-positive cells, dually expressing macrophage and tumor signatures that are transformed into M2-like macrophages and drive immunosuppression.

Single-cell analysis reveals the chemotherapy-induced cellular reprogramming and novel therapeutic targets in relapsed/refractory acute myeloid leukemia.

Chemoresistance and relapse are the leading cause of AML-related deaths. Utilizing single-cell RNA sequencing (scRNA-seq), we dissected the cellular states of bone marrow samples from primary refractory or short-term relapsed AML patients and defined the transcriptional intratumoral heterogeneity. We found that compared to proliferating stem/progenitor-like cells (PSPs), a subpopulation of quiescent stem-like cells (QSCs) were involved in the chemoresistance and poor outcomes of AML. By performing longitudinal scRNA-seq analyses, we demonstrated that PSPs were reprogrammed to obtain a QSC-like expression pattern during chemotherapy in refractory AML patients, characterized by the upregulation of CD52 and LGALS1 expression. Flow cytometric analysis further confirmed that the preexisting CD99+CD49d+CD52+Galectin-1+ (QSCs) cells at diagnosis were associated with chemoresistance, and these cells were further enriched in the residual AML cells of refractory patients. Interaction of CD52-SIGLEC10 between QSCs and monocytes may contribute to immune evading and poor outcomes. Furthermore, we identified that LGALS1 was a promising target for chemoresistant AML, and LGALS1 inhibitor could help eliminate QSCs and enhance the chemotherapy in patient-derived primary AML cells, cell lines, and AML xenograft models. Our results will facilitate a better understanding of the AML chemoresistance mechanism and the development of novel therapeutic strategies for relapsed/refractory AML patients.

Natural Coevolution of Tumor and Immunoenvironment in Glioblastoma.

Isocitrate dehydrogenase (IDH) wild-type glioblastoma (GBM) has a dismal prognosis. A better understanding of tumor evolution holds the key to developing more effective treatment. Here we study GBM's natural evolutionary trajectory by using rare multifocal samples. We sequenced 61,062 single cells from eight multifocal IDH wild-type primary GBMs and defined a natural evolution signature (NES) of the tumor. We show that the NES significantly associates with the activation of transcription factors that regulate brain development, including MYBL2 and FOSL2. Hypoxia is involved in inducing NES transition potentially via activation of the HIF1A-FOSL2 axis. High-NES tumor cells could recruit and polarize bone marrow-derived macrophages through activation of the FOSL2-ANXA1-FPR1/3 axis. These polarized macrophages can efficiently suppress T-cell activity and accelerate NES transition in tumor cells. Moreover, the polarized macrophages could upregulate CCL2 to induce tumor cell migration. SIGNIFICANCE: GBM progression could be induced by hypoxia via the HIF1A-FOSL2 axis. Tumor-derived ANXA1 is associated with recruitment and polarization of bone marrow-derived macrophages to suppress the immunoenvironment. The polarized macrophages promote tumor cell NES transition and migration. This article is highlighted in the In This Issue feature, p. 2711.

Electrochemical Behavior of Nanoporous Gold/Polypyrrole Supercapacitor under Deformation.

Due to the high demand of wearable electronics, flexible supercapacitors have been extensively developed in recent years. Yet, the effect of deformation in the interior electrode material suffered in practical applications on the performance received less attention. Here, we study the electrochemical behavior of macroscopic nanoporous gold/polypyrrole (NPG/PPy) in situ under compression deformation. Dealloying-driven NPG, a network constructed by bi-continuous nano-scaled ligaments and pores, can serve as a compression-tolerant substrate for PPy supercapacitor material. The electrochemical capacitance of NPG/PPy subjected to compression deformation is revealed to decrease at the scan rates and discharge current densities applied in this work. At the same time, the charge transfer resistance of NPG/PPy is found to increase. This electrochemical behavior is due to the locally reduced mass transport of electrolyte caused by the formation of new connections between the neighboring ligaments under the application of compression loads. The fundamental understanding of the effect of deformation on the performance of energy storage materials revealed in this study paves the way for their practical application in wearable devices.

Phase-transition tailored nanoporous zinc metal electrodes for rechargeable alkaline zinc-nickel oxide hydroxide and zinc-air batteries.

Secondary alkaline Zn batteries are cost-effective, safe, and energy-dense devices, but they are limited in rechargeability. Their short cycle life is caused by the transition between metallic Zn and ZnO, whose differences in electronic conductivity, chemical reactivity, and morphology undermine uniform electrochemical reactions and electrode structural stability. To circumvent these issues, here we propose an electrode design with bi-continuous metallic zinc nanoporous structures capable of stabilizing the electrochemical transition between metallic Zn and ZnO. In particular, via in situ optical microscopy and electrochemical impedance measurements, we demonstrate the kinetics-controlled structural evolution of Zn and ZnO. We also tested the electrochemical energy storage performance of the nanoporous zinc electrodes in alkaline zinc-nickel oxide hydroxide (NiOOH) and zinc-air (using Pt/C/IrO2-based air-electrodes) coin cell configurations. The Zn | |NiOOH cell delivers an areal capacity of 30 mAh/cm2 at 60% depth of discharging for 160 cycles, and the Zn | |Pt/C/IrO2 air cell demonstrates 80-hour stable operation in lean electrolyte condition.

High Expression of ACE2 and TMPRSS2 at the Resection Margin Makes Lung Cancer Survivors Susceptible to SARS-CoV-2 With Unfavorable Prognosis.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has rapidly spread worldwide. Systematic analysis of lung cancer survivors at molecular and clinical levels is warranted to understand the disease course and clinical characteristics. METHODS: A single-center, retrospective cohort study was conducted in 65 patients with COVID-19 from Wuhan Huoshenshan Hospital, of which 13 patients were diagnosed with lung cancer. The study was conducted from February 4 to April 11, 2020. RESULTS: During the course of treatment, lung cancer survivors infected with severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) had shorter median time from symptom onset to hospitalization (P = 0.016) and longer clinical symptom remission time (P = 0.020) than non-cancer individuals. No differences were observed among indicators such as time from symptom onset to hospitalization and symptom remission time between medium-term and short-term survivors. The expression of ACE2 (P = 0.013) and TMPRSS2 (P <0.001) was elevated in lung cancer survivors as compared with that in non-cancer individuals. CONCLUSIONS: ACE2 and TMPRSS2 levels were higher at resection margins of lung cancer survivors than those in normal tissues of non-cancerous individuals and may serve as factors responsible for the high susceptibility to COVID-19 among lung cancer survivors. Lung cancer patients diagnosed with COVID-19, including medium-term survivors, have worse outcomes than the general population.