In-situ revealed inhibition of W2C to excessive oxidation of CoOOH for high-efficiency alkaline overall water splitting.

The design of low-cost, efficient, and stable multifunctional basic catalysts to replace the high-cost noble metal catalysts remains a challenge. In this work, we report a dual-component Co-W2C catalytic system which achieves excellent properties of hydrogen evolution reaction (HER, η10 = 63 mV), oxygen evolution reaction (OER, η10 = 259 mV) and overall water splitting (η10 = 1.53 V) by adjusting the interfacial electronic structure of the material. Further density functional theory (DFT) calculations indicate that the efficient electronic modulation at the W2C/Co interface leads to the generation of favorable hydroxyl and hydrogen species energetics on the hybrid surface. The results of the in-situ Raman spectra show that W2C can suppress the excessive oxidation of the active site during the OER process, and the existence of core-shell structure also protects the W2C substrate. The stable and efficient catalytic performance of Co-W2C is attributed to the common advantages of structural and interface manipulation.

Harmine inhibits the proliferation and migration and promotes the apoptosis of colon cancer cells via inhibition of the FAK/AKT and ERK1/2/CREB signaling pathways.

Harmine is present in a variety of medicinal plants, and its effects on colon cancer cells remain unclear. Here, we found that harmine exhibited significant inhibitory effects on the proliferation of colon cancer cells by inhibiting the phosphorylation levels of the FAK/AKT and ERK1/2/CREB. Furthermore, harmine also inhibited the migration of colon cancer cells and suppressed the expression levels of MMP-2, MMP-9, and VEGF. Additionally, harmine-induced apoptosis in colon cancer cells by regulating the expression of Bcl-2 and Bax. In conclusion, our findings suggest that harmine exerts a significant inhibitory effect on the development of colon cancer cells.

scBlood: A comprehensive single-cell accessible chromatin database of blood cells.

The advent of single cell transposase-accessible chromatin sequencing (scATAC-seq) technology enables us to explore the genomic characteristics and chromatin accessibility of blood cells at the single-cell level. To fully make sense of the roles and regulatory complexities of blood cells, it is critical to collect and analyze these rapidly accumulating scATAC-seq datasets at a system level. Here, we present scBlood (https://bio.liclab.net/scBlood/), a comprehensive single-cell accessible chromatin database of blood cells. The current version of scBlood catalogs 770,907 blood cells and 452,247 non-blood cells from ∼400 high-quality scATAC-seq samples covering 30 tissues and 21 disease types. All data hosted on scBlood have undergone preprocessing from raw fastq files and multiple standards of quality control. Furthermore, we conducted comprehensive downstream analyses, including multi-sample integration analysis, cell clustering and annotation, differential chromatin accessibility analysis, functional enrichment analysis, co-accessibility analysis, gene activity score calculation, and transcription factor (TF) enrichment analysis. In summary, scBlood provides a user-friendly interface for searching, browsing, analyzing, visualizing, and downloading scATAC-seq data of interest. This platform facilitates insights into the functions and regulatory mechanisms of blood cells, as well as their involvement in blood-related diseases.

Analysis of Risk Factors for Severe Acute Pancreatitis in the Early Period (<24 h) After Admission.

BACKGROUND: Severe acute pancreatitis (SAP) has high mortality. Early identification of high-risk factors that may progress to SAP and active intervention measures may improve the prognosis of SAP patients. OBJECTIVE: Clinical data within 24 h after admission were retrospectively analyzed to provide an evidence for early screening of high-risk factors in patients with SAP. METHODS: A review of clinical data of acute pancreatitis patients from January 1, 2018, to December 31, 2022, was conducted. We compared the clinical data of SAP and non-SAP patients, and a multivariable logistic regression model was used to identify the independent predictors of SAP. The receiver operating characteristic (ROC) curve of SAP was drawn for continuous numerical variables to calculate the optimal clinical cutoff value of each variable, and the predictive value of each variable was compared by the area under the ROC curve. RESULTS: Based on the multivariate logistic regression analysis of Age (odds ratio (OR), 1.032;95% confident interval (CI),1.018-1.046, p < 0.001), body mass index (BMI) (OR, 1.181; 95% CI,1.083-1.288, p < 0.001), Non-HTGAP (nonhypertriglyceridemic acute pancreatitis) (OR, 2.098; 95% CI,1.276-3.45, p = 0.003), white blood cell count (WBC) (OR,1.072; 95% CI,1.034-1.111, p < 0.001), procalcitonin (PCT) (OR, 1.060; 95% CI, 1.027-1.095, p < 0.001), serum calcium (Ca) (OR,0.121; 95% CI, 0.050-0.292, p < 0.001), computed tomography severity index (CTSI) ≥4 (OR,12.942;95% CI,7.267-23.049, p < 0.001) were identified as independent risk factors for SAP. The area under the ROC curve (AUC) and optimal CUT-OFF values of continuous numerical variables for predicting SAP were Age (0.6079,51.5), BMI (0.6,23.25), WBC (0.6701,14.565), PCT (0.7086, 0.5175), Ca (0.7787,1.965), respectively. CONCLUSION: Age, BMI, non-HTGAP, WBC, PCT, serum Ca and CTSI≥4 have good predictive value for SAP.

Selenium represses microRNA-202-5p/MICU1 aixs to attenuate mercuric chloride-induced kidney ferroptosis.

Mercuric chloride (HgCl2) is a nephrotoxic contaminant that is widely present in the environment. Selenium (Se) can effectively antagonize the biological toxicity caused by heavy metals. Here, in vivo and in vitro models of Se antagonism to HgCl2-induced nephrotoxicity in chickens were established, with the aim of exploring the specific mechanism. Morphological observation and kidney function analysis showed that Se alleviated HgCl2-induced kidney tissue injury and cytotoxicity. The results showed that ferroptosis was the primary mechanism for the toxicity of HgCl2, as indicated by iron overload and lipid peroxidation. On the one hand, Se significantly prevented HgCl2-induced iron overload. On the other hand, Se alleviated the intracellular reactive oxygen species (ROS) levels caused by HgCl2. Subsequently, we focused on the sources of ROS during HgCl2-induced ferroptosis. Mechanically, Se reduced ROS overproduction induced by HgCl2 through mitochondrial calcium uniporter (MCU)/mitochondrial calcium uptake 1 (MICU1)-mediated mitochondrial calcium ion (Ca2+) overload. Furthermore, a dual luciferase reporter assay demonstrated that MICU1 was the direct target of miR-202-5p. Overall, Se represses miR-202-5p/MICU1 axis to attenuate HgCl2-induced kidney ferroptosis.

Selenium alleviates pancreatic fibrosis in chickens caused by mercuric chloride: Involvement of the MAPK signaling pathway and selenoproteins.

Mercuric chloride (HgCl2) is a widespread inorganic mercury with digestive toxicity. The pancreas is an important digestive organ in animals, and pancreatic fibrosis (PF) is a major pathological feature of chronic pancreatitis, which can be caused by heavy metals. Selenium (Se) is an essential trace element for the animal organism, performing biological functions in the form of selenoproteins, as well as alleviating the toxicity of heavy metals. In this study, we explored the specific mechanisms underlying the protective effect of Se on HgCl2-induced pancreatic injury in chickens. Morphological observation and serum biochemical analysis showed that Se attenuated HgCl2-caused pancreatic tissue damage and elevated glucose concentration and α-amylase activity. Next, the expression of oxidative stress indicators such as MDA and GSH-Px as well as inflammation-related markers including IL-1ß, IL-6, and TNF-α were detected. Results showed that Se had an inhibitory effect on HgCl2-induced oxidative stress and inflammation. Furthermore, we found that Se alleviated HgCl2-induced PF by detecting the expression of markers related to PF including TGF-ß1, α-SMA, COL1A1, and FN1. Mechanistically, Se attenuated HgCl2-induced PF via the MAPK signaling pathway. Importantly, several selenoproteins, especially those with antioxidant activity, were involved in the protective effect of Se on HgCl2 toxicity. In conclusion, our findings demonstrated that Se inhibited HgCl2-induced oxidative stress and inflammation and alleviated chicken PF through the MAPK signaling pathway, in which some antioxidant selenoproteins were involved.

Multifaceted roles of lymphatic and blood endothelial cells in the tumor microenvironment of hepatocellular carcinoma: A comprehensive review.

The tumor microenvironment is a complex network of cells, extracellular matrix, and signaling molecules that plays a critical role in tumor progression and metastasis. Lymphatic and blood vessels are major routes for solid tumor metastasis and essential parts of tumor drainage conduits. However, recent studies have shown that lymphatic endothelial cells (LECs) and blood endothelial cells (BECs) also play multifaceted roles in the tumor microenvironment beyond their structural functions, particularly in hepatocellular carcinoma (HCC). This comprehensive review summarizes the diverse roles played by LECs and BECs in HCC, including their involvement in angiogenesis, immune modulation, lymphangiogenesis, and metastasis. By providing a detailed account of the complex interplay between LECs, BECs, and tumor cells, this review aims to shed light on future research directions regarding the immune regulatory function of LECs and potential therapeutic targets for HCC.

Ultrasensitive and Rapid Circulating Tumor DNA Liquid Biopsy Using Surface-Confined Gene Amplification on Dispersible Magnetic Nano-Electrodes.

Circulating tumor DNA (ctDNA) detection has been acknowledged as a promising liquid biopsy approach for cancer diagnosis, with various ctDNA assays used for early detection and treatment monitoring. Dispersible magnetic nanoparticle-based electrochemical detection methods have been proposed as promising candidates for ctDNA detection based on the detection performance and features of the platform material. This study proposes a nanoparticle surface-localized genetic amplification approach by integrating Fe3O4-Au core-shell nanoparticles into polymerase chain reactions (PCR). These highly dispersible and magnetically responsive superparamagnetic nanoparticles act as nano-electrodes that amplify and accumulate target ctDNA in situ on the nanoparticle surface upon PCR amplification. These nanoparticles are subsequently captured and subjected to repetitive electrochemical measurements to induce reconfiguration-mediated signal amplification for ultrasensitive (∼3 aM) and rapid (∼7 min) metastatic breast cancer ctDNA detection in vitro. The detection platform can also detect metastatic biomarkers from in vivo samples, highlighting the potential for clinical applications and further expansion to rapid and ultrasensitive multiplex detection of various cancers.

Hierarchical chiral MOFs with the induced chirality of AIE ligands exhibiting non-reciprocal CPL.

Two pairs of chiral MOFs with hierarchical chiral structures were constructed through assembly of achiral AIE-type multidentate linkers and chiral camphoric acid. Non-reciprocal circularly polarized luminescence (CPL) can be observed on the macroscopic due to the coexistence of optical anisotropic and chiroptical nature. This study provides a new perspective to recognize and construct chiral crystalline materials.

The effect of fine particulate matter (PM2.5) pollution on health inequality: an intergenerational perspective.

Air pollution poses a serious challenge to public health and simultaneously exacerbating regional & intergenerational health inequality. This research introduces PM2.5 pollution into the intergenerational health transmission model, and estimates its impact on health inequality in China using Ordered Logit Regression (OLR) and Multi-scale Geographically Weighted Regression (MGWR) model. The results indicate that PM2.5 pollution exacerbate the intergenerational health inequality, and its impacts show inconsistency across family income levels, parental health insurance status, and area of residence. Specifically, it is more difficult for offspring in low-income families to escape from the influence of unhealthy family to become upwardly mobile. Additionally, this health inequality is more significant in households in which at least one parent does not have health insurance. Moreover, the intergenerational solidification caused by PM2.5 pollution is higher in the east and lower in the west. Both the PM2.5 level and solidification effect are high in Beijing-Tianjin-Hebei region, Yangtze River Delta region and central areas of China, which is the focus of air pollution management. These findings suggest that more emphasis should be placed on family-based health promotion. In areas with high PM2.5 pollution levels, resources, subsidies and air pollution protection should be provided for less healthy families with lower incomes and no health insurance.

Triply Interlocked [2]catenanes: Rational Synthesis, Reversible Conversion Studies and Unprecedented Application in Photothermal Responsive Elastomer.

Triply interlocked [2]catenane complexes featuring two identical, mechanically interlocked units are extraordinarily rare chemical compounds, whose properties and applications remain open to detailed studies. Herein, we introduce the rational design of a new ligand precursor, L1, suitable for the synthesis of six triply interlocked [2]catenanes by coordination-driven self-assembly. The interlocked compounds can be reversibly converted into the corresponding simple triangular prism metallacage by addition of H2O or DMF solvents to their CH3OH solutions, thereby demonstrating the importance of π⋅⋅⋅π stacking and hydrogen bonding interactions in the formation of triply interlocked [2]catenanes. Moreover, extensive studies have been conducted to assess the remarkable photothermal conversion performance. Complex 6 a, exhibiting outstanding photothermal conversion performance (conversion efficiency in solution : 31.82 %), is used to prepare novel photoresponsive elastomer in combination with thermally activated liquid crystal elastomer. The resultant material displays robust response to near-infrared (NIR) laser and the capability of completely reforming the shape and reversible actuation, paving the way for the application of half-sandwich organometallic units in photo-responsive smart materials.

Encapsulation engineering of porous crystalline frameworks for delayed luminescence and circularly polarized luminescence.

Delayed luminescence (DF), including phosphorescence and thermally activated delayed fluorescence (TADF), and circularly polarized luminescence (CPL) exhibit common and broad application prospects in optoelectronic displays, biological imaging, and encryption. Thus, the combination of delayed luminescence and circularly polarized luminescence is attracting increasing attention. The encapsulation of guest emitters in various host matrices to form host-guest systems has been demonstrated to be an appealing strategy to further enhance and/or modulate their delayed luminescence and circularly polarized luminescence. Compared with conventional liquid crystals, polymers, and supramolecular matrices, porous crystalline frameworks (PCFs) including metal-organic frameworks (MOFs), covalent-organic frameworks (COFs), zeolites and hydrogen-bonded organic frameworks (HOFs) can not only overcome shortcomings such as flexibility and disorder but also achieve the ordered encapsulation of guests and long-term stability of chiral structures, providing new promising host platforms for the development of DF and CPL. In this review, we provide a comprehensive and critical summary of the recent progress in host-guest photochemistry via the encapsulation engineering of guest emitters in PCFs, particularly focusing on delayed luminescence and circularly polarized luminescence. Initially, the general principle of phosphorescence, TADF and CPL, the combination of DF and CPL, and energy transfer processes between host and guests are introduced. Subsequently, we comprehensively discuss the critical factors affecting the encapsulation engineering of guest emitters in PCFs, such as pore structures, the confinement effect, charge and energy transfer between the host and guest, conformational dynamics, and aggregation model of guest emitters. Thereafter, we summarize the effective methods for the preparation of host-guest systems, especially single-crystal-to-single-crystal (SC-SC) transformation and epitaxial growth, which are distinct from conventional methods based on amorphous materials. Then, the recent advancements in host-guest systems based on PCFs for delayed luminescence and circularly polarized luminescence are highlighted. Finally, we present our personal insights into the challenges and future opportunities in this promising field.

Dichotomous roles of ADAR1 in liver hepatocellular carcinoma and kidney renal cell carcinoma: Unraveling the complex tumor microenvironment and prognostic significance.

BACKGROUND: Adenosine deaminase acting on RNA 1 (ADAR1) is an RNA-editing enzyme that significantly impacts cancer progression and various biological processes. The expression of ADAR1 mRNA has been examined in multiple cancer types using The Cancer Genome Atlas (TCGA) dataset, revealing distinct patterns in kidney chromophobe (KICH), kidney renal clear cell carcinoma (KIRC), kidney renal papillary cell carcinoma (KIRP), and liver hepatocellular carcinoma (LIHC) compared to normal controls. However, the reasons for these differential expressions remain unclear. METHODS: In this study, we performed RT-PCR and western blotting (WB) to validate ADAR1 expression patterns in clinical tissue samples. Survival analysis and immune microenvironment analysis (including immune score and stromal score) were conducted using TCGA data to determine the specific cell types associated with ADAR1, as well as the key genes in those cell types. The relationship between ADAR1 and specific cell types' key genes was verified by immunohistochemistry (IHC), using clinical liver and kidney cancer samples. RESULTS: Our validation analysis revealed that ADAR1 expression was downregulated in KICH, KIRC, and KIRP, while upregulated in LIHC compared to normal tissues. Notably, a significant correlation was found between ADAR1 mRNA expression and patient prognosis, particularly in KIRC, KIRP, and LIHC. Interestingly, we observed a positive correlation between ADAR1 expression and stromal scores in KIRC, whereas a negative correlation was observed in LIHC. Cell type analysis highlighted distinct relationships between ADAR1 expression and the two stromal cell types, blood endothelial cells (BECs) and lymphatic endothelial cells (LECs), and further determined the signature gene claudin-5 (CLDN5), in KIRC and LIHC. Moreover, ADAR1 was inversely related with CLDN5 in KIRC (n = 26) and LIHC (n = 30) samples, verified via IHC. CONCLUSIONS: ADAR1 plays contrasting roles in LIHC and KIRC, associated with the enrichment of BECs and LECs within tumors. This study sheds light on the significant roles of stromal cells within the complex tumor microenvironment (TME) and provides new insights for future research in tumor immunotherapy and precision medicine.

PV Panel Model Parameter Estimation by Using Particle Swarm Optimization and Artificial Neural Network.

Photovoltaic (PV) panels are one of the popular green energy resources and PV panel parameter estimations are one of the popular research topics in PV panel technology. The PV panel parameters could be used for PV panel health monitoring and fault diagnosis. Recently, a PV panel parameters estimation method based in neural network and numerical current predictor methods has been developed. However, in order to further improve the estimation accuracies, a new approach of PV panel parameter estimation is proposed in this paper. The output current and voltage dynamic responses of a PV panel are measured, and the time series of the I-V vectors will be used as input to an artificial neural network (ANN)-based PV model parameter range classifier (MPRC). The MPRC is trained using an I-V dataset with large variations in PV model parameters. The results of MPRC are used to preset the initial particles' population for a particle swarm optimization (PSO) algorithm. The PSO algorithm is used to estimate the PV panel parameters and the results could be used for PV panel health monitoring and the derivation of maximum power point tracking (MMPT). Simulations results based on an experimental I-V dataset and an I-V dataset generated by simulation show that the proposed algorithms can achieve up to 3.5% accuracy and the speed of convergence was significantly improved as compared to a purely PSO approach.

Role of peritumoral tissue analysis in predicting characteristics of hepatocellular carcinoma using ultrasound-based radiomics.

Predicting the biological characteristics of hepatocellular carcinoma (HCC) is essential for personalized treatment. This study explored the role of ultrasound-based radiomics of peritumoral tissues for predicting HCC features, focusing on differentiation, cytokeratin 7 (CK7) and Ki67 expression, and p53 mutation status. A cohort of 153 patients with HCC underwent ultrasound examinations and radiomics features were extracted from peritumoral tissues. Subgroups were formed based on HCC characteristics. Predictive modeling was carried out using the XGBOOST algorithm in the differentiation subgroup, logistic regression in the CK7 and Ki67 expression subgroups, and support vector machine learning in the p53 mutation status subgroups. The predictive models demonstrated robust performance, with areas under the curves of 0.815 (0.683-0.948) in the differentiation subgroup, 0.922 (0.785-1) in the CK7 subgroup, 0.762 (0.618-0.906) in the Ki67 subgroup, and 0.849 (0.667-1) in the p53 mutation status subgroup. Confusion matrices and waterfall plots highlighted the good performance of the models. Comprehensive evaluation was carried out using SHapley Additive exPlanations plots, which revealed notable contributions from wavelet filter features. This study highlights the potential of ultrasound-based radiomics, specifically the importance of peritumoral tissue analysis, for predicting HCC characteristics. The results warrant further validation of peritumoral tissue radiomics in larger, multicenter studies.

Evaluation of disease severity and prediction of severe cases in children hospitalized with influenza A (H1N1) infection during the post-COVID-19 era: a multicenter retrospective study.

BACKGROUND: The rebound of influenza A (H1N1) infection in post-COVID-19 era recently attracted enormous attention due the rapidly increased number of pediatric hospitalizations and the changed characteristics compared to classical H1N1 infection in pre-COVID-19 era. This study aimed to evaluate the clinical characteristics and severity of children hospitalized with H1N1 infection during post-COVID-19 period, and to construct a novel prediction model for severe H1N1 infection. METHODS: A total of 757 pediatric H1N1 inpatients from nine tertiary public hospitals in Yunnan and Shanghai, China, were retrospectively included, of which 431 patients diagnosed between February 2023 and July 2023 were divided into post-COVID-19 group, while the remaining 326 patients diagnosed between November 2018 and April 2019 were divided into pre-COVID-19 group. A 1:1 propensity-score matching (PSM) was adopted to balance demographic differences between pre- and post-COVID-19 groups, and then compared the severity across these two groups based on clinical and laboratory indicators. Additionally, a subgroup analysis in the original post-COVID-19 group (without PSM) was performed to investigate the independent risk factors for severe H1N1 infection in post-COIVD-19 era. Specifically, Least Absolute Shrinkage and Selection Operator (LASSO) regression was applied to select candidate predictors, and logistic regression was used to further identify independent risk factors, thus establishing a prediction model. Receiver operating characteristic (ROC) curve and calibration curve were utilized to assess discriminative capability and accuracy of the model, while decision curve analysis (DCA) was used to determine the clinical usefulness of the model. RESULTS: After PSM, the post-COVID-19 group showed longer fever duration, higher fever peak, more frequent cough and seizures, as well as higher levels of C-reactive protein (CRP), interleukin 6 (IL-6), IL-10, creatine kinase-MB (CK-MB) and fibrinogen, higher mechanical ventilation rate, longer length of hospital stay (LOS), as well as higher proportion of severe H1N1 infection (all P < 0.05), compared to the pre-COVID-19 group. Moreover, age, BMI, fever duration, leucocyte count, lymphocyte proportion, proportion of CD3+ T cells, tumor necrosis factor α (TNF-α), and IL-10 were confirmed to be independently associated with severe H1N1 infection in post-COVID-19 era. A prediction model integrating these above eight variables was established, and this model had good discrimination, accuracy, and clinical practicability. CONCLUSIONS: Pediatric H1N1 infection during post-COVID-19 era showed a higher overall disease severity than the classical H1N1 infection in pre-COVID-19 period. Meanwhile, cough and seizures were more prominent in children with H1N1 infection during post-COVID-19 era. Clinicians should be aware of these changes in such patients in clinical work. Furthermore, a simple and practical prediction model was constructed and internally validated here, which showed a good performance for predicting severe H1N1 infection in post-COVID-19 era.

Naturally Crosslinked Biocompatible Carbonaceous Liquid Metal Aqueous Ink Printing Wearable Electronics for Multi-Sensing and Energy Harvesting.

Achieving flexible electronics with comfort and durability comparable to traditional textiles is one of the ultimate pursuits of smart wearables. Ink printing is desirable for e-textile development using a simple and inexpensive process. However, fabricating high-performance atop textiles with good dispersity, stability, biocompatibility, and wearability for high-resolution, large-scale manufacturing, and practical applications has remained challenging. Here, water-based multi-walled carbon nanotubes (MWCNTs)-decorated liquid metal (LM) inks are proposed with carbonaceous gallium-indium micro-nanostructure. With the assistance of biopolymers, the sodium alginate-encapsulated LM droplets contain high carboxyl groups which non-covalently crosslink with silk sericin-mediated MWCNTs. E-textile can be prepared subsequently via printing technique and natural waterproof triboelectric coating, enabling good flexibility, hydrophilicity, breathability, wearability, biocompatibility, conductivity, stability, and excellent versatility, without any artificial chemicals. The obtained e-textile can be used in various applications with designable patterns and circuits. Multi-sensing applications of recognizing complex human motions, breathing, phonation, and pressure distribution are demonstrated with repeatable and reliable signals. Self-powered and energy-harvesting capabilities are also presented by driving electronic devices and lighting LEDs. As proof of concept, this work provides new opportunities in a scalable and sustainable way to develop novel wearable electronics and smart clothing for future commercial applications.