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Understanding the subcellular localization of long non-coding RNAs (lncRNAs) is crucial for unraveling their functional mechanisms. While previous computational methods have made progress in predicting lncRNA subcellular localization, most of them ignore the sequence order information by relying on k-mer frequency features to encode lncRNA sequences. In the study, we develope SGCL-LncLoc, a novel interpretable deep learning model based on supervised graph contrastive learning. SGCL-LncLoc transforms lncRNA sequences into de Bruijn graphs and uses the Word2Vec technique to learn the node representation of the graph. Then, SGCL-LncLoc applies graph convolutional networks to learn the comprehensive graph representation. Additionally, we propose a computational method to map the attention weights of the graph nodes to the weights of nucleotides in the lncRNA sequence, allowing SGCL-LncLoc to serve as an interpretable deep learning model. Furthermore, SGCL-LncLoc employs a supervised contrastive learning strategy, which leverages the relationships between different samples and label information, guiding the model to enhance representation learning for lncRNAs. Extensive experimental results demonstrate that SGCL-LncLoc outperforms both deep learning baseline models and existing predictors, showing its capability for accurate lncRNA subcellular localization prediction. Furthermore, we conduct a motif analysis, revealing that SGCL-LncLoc successfully captures known motifs associated with lncRNA subcellular localization. The SGCL-LncLoc web server is available at http://csuligroup.com:8000/SGCL-LncLoc. The source code can be obtained from https://github.com/CSUBioGroup/SGCL-LncLoc.

Highlights Exploiting single-atom catalytic activation and targeted adsorption properties, Ni single-atom active sites based on N, C coordination are constructed on the surface of two-dimensional MXene nanosheets (Ni–N–C/Ti3C2Tx), enabling highly sensitive and selective NH3 gas detection. The catalytic activation effect of Ni–N–C/Ti3C2Tx effectively reduces the Gibbs free energy of the sensing elemental reaction, while its electronic structure promotes the spill-over effect of reactive oxygen species at the gas–solid interface. An end-sealing passivation strategy utilizing a conjugated hydrogen bond network of the conductive polymer was employed on MXene-based flexible electrodes, effectively mitigating the oxidative degradation of MXene-based gas sensors.

Three new species belonging to Basidiomycota from southwestern China are described based on morphological and molecular data. Campanophyllum microsporum is morphologically characterized by dorsally pseudostipitate, pale orange to brownish orange pileus, excentric to lateral pseudostipe, crowded lamellae, cylindrical-ellipsoid basidiospores 3.0–4.2 × 1.7–2.2 µm, narrowly clavate to clavate basidia 14.5–23.0 × 3.0–4.2 µm, and cylindrical to clavate cheilocystidia 22.0–55.0 × 5.0–10.8 µm. Calocera multiramosa is morphologically characterized by stipitate, yellowish to orange, dendroid, and dichotomously branched basidiomata, cylindrical to clavate basidia 36.5–52.5 × 3.8–6.1 µm, navicular or reniform, 1–5-septate mature basidiospores 10.4–16.7 × 5.2–7.4 µm. Dacrymyces naematelioides is morphologically characterized by stipitate and cerebriform, orange to light brown basidiomata, cylindrical to clavate, smooth or roughened basidia 38.5–79.5 × 6.5–10.6 µm, broadly and elliptic-fusiform, 7-septate mature basidiospores 18.5–28.6 × 8.9–13.8 µm. These three new species are supported by the phylogenetic analyses using maximum likelihood (ML) and Bayesian inference (BI) analyses with combined nuclear ribosomal DNA (rDNA) internal transcribed spacer (ITS) and large ribosomal subunit (LSU) sequences. Full descriptions and photographs of these new species are provided.

Abstract Real-time and accurate biomarker detection is highly desired in point-of-care diagnosis, food freshness monitoring, and hazardous leakage warning. However, achieving such an objective with existing technologies is still challenging. Herein, we demonstrate a wireless inductor-capacitor (LC) chemical sensor based on platinum-doped partially deprotonated-polypyrrole (Pt-PPy+ and PPy0) for real-time and accurate ammonia (NH3) detection. With the chemically wide-range tunability of PPy in conductivity to modulate the impedance, the LC sensor exhibits an up-to-180% improvement in return loss (S11). The Pt-PPy+ and PPy0 shows the p-type semiconductor nature with greatly-manifested adsorption-charge transfer dynamics toward NH3, leading to an unprecedented NH3 sensing range. The S11 and frequency of the Pt-PPy+ and PPy0-based sensor exhibit discriminative response behaviors to humidity and NH3, enabling the without-external-calibration compensation and accurate NH3 detection. A portable system combining the proposed wireless chemical sensor and a handheld instrument is validated, which aids in rationalizing strategies for individuals toward various scenarios.

Colorectal cancer (CRC) is the third most diagnosed cancer and the second deadliest cancer worldwide representing a major public health problem. In recent years, increasing evidence has shown that microRNA (miRNA) can control the expression of targeted human messenger RNA (mRNA) by reducing their abundance or translation, acting as oncogenes or tumor suppressors in various cancers, including CRC. Due to the significant up-regulation of oncogenic miRNAs in CRC, elucidating the underlying mechanism and identifying dysregulated miRNA targets may provide a basis for improving current therapeutic interventions. In this paper, we proposed Gra-CRC-miRTar, a pre-trained nucleotide-to-graph neural network framework, for identifying potential miRNA targets in CRC. Different from previous studies, we constructed two pre-trained models to encode RNA sequences and transformed them into de Bruijn graphs. We employed different graph neural networks to learn the latent representations. The embeddings generated from de Bruijn graphs were then fed into a Multilayer Perceptron (MLP) to perform the prediction tasks. Our extensive experiments show that Gra-CRC-miRTar achieves better performance than other deep learning algorithms and existing predictors. In addition, our analyses also successfully revealed 172 out of 201 functional interactions through experimentally validated miRNA-mRNA pairs in CRC. Collectively, our effort provides an accurate and efficient framework to identify potential miRNA targets in CRC, which can also be used to reveal miRNA target interactions in other malignancies, facilitating the development of novel therapeutics. The Gra-CRC-miRTar web server can be found at: http://gra-crc-mirtar.com/.

Background: The senescence of endothelial cells is of great importance involving in atherosclerosis (AS) development. Recent studies have proved the protective role of mesenchymal stem cell-derived extracellular vesicles in AS, herein, we further desired to unvei their potential regulatory mechanisms in endothelial cell senescence. Methods: Senescence induced by H2O2 in primary mouse aortic endothelial cells (MAECs) was evaluated by SA-β-gal staining. Targeted molecule expression was detected by qRT-PCR and Western blotting. The biological functions of MAECs were determined by CCK-8, flow cytometry, transwell, and tube formation assays. Oxidative injury was assessed by LDH, total and lipid ROS, LPO and MDA levels. The proliferation of adipose-derived mesenchymal stem cell (ADSCs) was analyzed by EdU assay. Effect of ADSCs-derived extracellular vesicles (ADSC-EVs) on AS was investigated in HFD-fed ApoE−/− mice. Results: miR-674-5p was up-regulated, while C1q/TNF-related protein 9 (CTRP9) was down-regulated in H2O2-induced senescent MAECs. CTRP9 was demonstrated as a target gene of miR-674-5p. miR-674-5p inhibition restrained senescence, oxidative stress, promoted proliferation, migration, and angiogenesis of H2O2-stimulated MAECs via enhancing CTRP9 expression. Moreover, treatment with ADSC-EVs inhibited H2O2-induced senescence and dysfunction of MAECs through regulating miR-674-5p/CTRP9 axis. In the in vivo AS mouse model, ADSC-EVs combination with miR-674-5p silencing slowed down AS progression via up-regulation of CTRP9. Conclusion: ADSC-EVs repressed endothelial cell senescence and improved dysfunction via promotion of CTRP9 expression upon miR-674-5p deficiency during AS progression, which might provide vital evidence for ADSC-EVs as a promising therapy for AS.

Abstract. Cancer is a major global health issue. Effective therapeutic strategies can prolong patients' survival and reduce the costs of treatment. Drug repurposing, which identifies new therapeutic uses for approved drugs, is a promising approach with the advantages of reducing research costs, shortening development time, and increasing efficiency and safety. Disulfiram (DSF), a Food and Drug Administration (FDA)-approved drug used to treat chronic alcoholism, has a great potential as an anticancer drug by targeting diverse human malignancies. Several studies show the antitumor effects of DSF, particularly the combination of DSF and copper (DSF/Cu), on a wide range of cancers such as glioblastoma (GBM), breast cancer, liver cancer, pancreatic cancer, and melanoma. In this review, we summarize the antitumor mechanisms of DSF/Cu, including induction of intracellular reactive oxygen species (ROS) and various cell death signaling pathways, and inhibition of proteasome activity, as well as inhibition of nuclear factor-kappa B (NF-κB) signaling. Furthermore, we highlight the ability of DSF/Cu to target cancer stem cells (CSCs), which provides a new approach to prevent tumor recurrence and metastasis. Strikingly, DSF/Cu inhibits several molecular targets associated with drug resistance, and therefore it is becoming a novel option to increase the sensitivity of chemo-resistant and radio-resistant patients. Studies of DSF/Cu may shed light on its improved application to clinical tumor treatment.

ABSTRACT Background In the era of novel agents, the clinical outcomes of induction treatment and the impact of the number of high‐risk cytogenetic abnormalities (HRA) in newly diagnosed multiple myeloma (NDMM) need to be explored. Objective Through this study, we aim to analyze the effectiveness of different induction treatments and explore the survival outcomes of patients with varying numbers of HRA. Methods A total of 734 patients from seven medical centers were included in our study. Results Patients in the CD38 monoclonal antibody or IMiDs plus proteasome inhibitors (PI) groups had significantly superior overall survival (OS) and progression‐free survival (PFS) compared to those receiving IMiDs or PI alone. Additionally, the CD38 monoclonal antibody conferred a PFS advantage over IMiDs plus PI. Patients with ≥ 2 high‐risk cytogenetic abnormalities (HRA) exhibited an extremely poor prognosis and should be considered ultra‐high‐risk individuals in multiple myeloma (MM). The CD38 monoclonal antibody, transplantation, and achieving minimal residual disease (MRD) negativity only partly mitigated the poor prognosis in patients with HRA. Furthermore, patients with 1q21 gain/amplification (1q21+) only had a significantly worse prognosis compared to patients without HRA, and those with 1q21+ plus del17p or t(4;14) exhibited an inferior prognosis compared to those with 1q21+ alone. Conclusion Our results suggested that double‐hit multiple myeloma was associated with extremely poor survival outcomes, and more effective treatments needed to be explored for this particular subtype of MM.

The widespread presence of micro(nano)plastics (MNPs) has generated public concern. Studies have indicated that MNPs can accumulate in mammalian bones; however, research on the skeletal toxicity and underlying molecular mechanisms of MNPs in aquatic organisms remains limited. We subjected zebrafish embryos to three varying levels (1, 10, 100 μg/mL) of polystyrene nanoplastics (PSNPs) exposure over a period of 7 days in our research. The results revealed that PSNPs significantly reduced the body length and hatching rate of zebrafish, leading to skeletal deformities. mRNA level analysis showed significant upregulation of sp7, sparc, and smad1 genes transcription by PSNPs. Moreover, PSNPs markedly downregulated the mRNA levels associated with runx2a, bmp2a, and bmp4. Further investigations demonstrated that PSNPs dramatically increased ROS levels in zebrafish larvae, with significant downregulation of transcription levels of sod1 and cat genes, resulting in a sharp increase in transcription levels of apoptosis-related regulatory genes bcl-2 and bax. Furthermore, PSNPs led to a marked rise in Caspase 3 activity in zebrafish larvae, suggesting the initiation of apoptosis. PSNPs also notably inhibited alkaline phosphatase (AKP) activity. Compared to a 4-day exposure, a 7-day exposure to PSNPs intensified abnormalities across multiple indicators. In summary, our research indicates that PSNPs cause significant oxidative stress in zebrafish larvae, resulting in apoptosis. Moreover, PSNPs disrupt the transcription of genes related to skeletal development through the bone morphogenetic protein (BMP) pathway, further disrupting skeletal development processes and ultimately resulting in skeletal deformities in zebrafish larvae. This study provides new insights into the skeletal toxicity of MNPs.

In the current study, the CN-CD30V10A battery tester, K-type temperature sensor, and RS485 are utilized to perform charging and discharging tests on the Panasonic 21,700 lithium-ion battery at various rates. The voltage and temperature changes are measured in real-time, with the data transmitted to the computer via RS485. Then a micro-thermal resistance method is proposed to calculate the equivalent thermal resistance of the cell core along the axial positive and negative poles, as well as along the radial outer circumference surface under anisotropic conditions. Based on the experimental results and the equivalent thermal resistance, an electrothermal coupling model is established for battery internal temperature estimation, taking into account anisotropy and temperature effects on heat transfer. Through the integration of the model and externally measured temperature, the internal temperature is accurately estimated. Moreover, the proposed model (Root-Mean-Square Error, RMSE=0.329) exhibits a significant improvement in accuracy compared to equivalent circuit model (RMSE=1.08), extended Kalman filter (RMSE=0.95), network extended Kalman filter (RMSE=0.58), and neural network unscented Kalman filter (RMSE=0.61). Specifically, the model achieves an approximately 76 % to 228 % reduction in RMSE compared to these methods.

Hepatocyte transplantation is an effective treatment for end-stage liver disease. However, due to the limited supply of human hepatocytes, porcine hepatocytes have garnered attention as a potential alternative source. Nonetheless, traditional primary porcine hepatocytes exhibit certain limitations in function maintenance and in vitro proliferation. This study has discovered that by using histone deacetylase inhibitors (HDACi), primary porcine hepatocytes can be successfully reprogrammed into liver progenitor cells with high proliferative potential. This method enables porcine hepatocytes to proliferate over an extended period in vitro and exhibit increased susceptibility in lentivirus-mediated gene modification. These liver progenitor cells can readily differentiate into mature hepatocytes and, upon microencapsulation transplantation into mice with acute liver failure, significantly improve the survival rate. This research provides new possibilities for the application of porcine hepatocytes in the treatment of end-stage liver disease.

Abstract Over the past decade, learning engagement has received increasing attention from researchers. As a critical factor in college students’ academic achievement, learning engagement is significant in students’ long-term future development and social creativity. Present studies show that the overall level of college students’ learning engagement is low, which is highly unfavourable to educational quality and long-term development. There is no doubt about the position of the university library in academic circles. However, the influence of the university library environment on college students’ learning engagement has not been fully explored. The data in this study came from a survey of 45 Chinese universities. This paper investigates the relationship between the university library environment, students’ interaction, and students’ learning engagement. The results showed differences in Chinese college students’ learning engagement in liberal arts and sciences majors. The learning engagement of liberal arts majors is much lower than that of science students. We found that the library environment has an important influence on college students’ learning engagement. And the library environment can affect college students’ learning engagement through the intermediary role of interactive participation among students. In addition, for liberal arts students, the direct effect of the library environment on their learning engagement is more significant. However, for science students, the influence of the library environment on their learning engagement is more strongly intermediated by the students’ interaction. Therefore, future construction and renovation of library environments should cater not only to the diverse needs of different academic disciplines, especially liberal arts students who need special attention but also guide more students to interact friendly through the spatial characteristics of the library so as to improve the overall learning engagement of college students.

Abstract As the most prevalent epitranscriptomic modification, N6-methyladenosine (m6A) shows important roles in a variety of diseases through regulating the processing, stability and translation of target RNAs. However, the potential contributions of m6A to RNA functions are unclear. Here, we identified a functional and prognosis-related m6A-modified RNA SREBF2-AS1 in hepatocellular carcinoma (HCC). The expression of SREBF2-AS1 and SREBF2 in HCC tissues and cells was measured by RT-qPCR. m6A modification level of SREBF2-AS1 was measured by methylated RNA immunoprecipitation assay. The roles of SREBF2-AS1 in HCC progression and sorafenib resistance were investigated by proliferation, apoptosis, migration, and cell viability assays. The regulatory mechanisms of SREBF2-AS1 on SREBF2 were investigated by Chromatin isolation by RNA purification, RNA immunoprecipitation, CUT&RUN, and bisulfite DNA sequencing assays. Our findings showed that the expression of SREBF2-AS1 was increased in HCC tissues and cells, and positively correlated with poor survival of HCC patients. m6A modification level of SREBF2-AS1 was also increased in HCC and positively correlated with poor prognosis of HCC patients. METTL3 and METTL14-induced m6A modification upregulated SREBF2-AS1 expression through increasing SREBF2-AS1 transcript stability. Functional assays showed that only m6A-modified, but not non-modified SREBF2-AS1 promoted HCC progression and sorafenib resistance. Mechanistic investigations revealed that m6A-modified SREBF2-AS1 bound and recruited m6A reader FXR1 and DNA 5-methylcytosine dioxygenase TET1 to SREBF2 promoter, leading to DNA demethylation at SREBF2 promoter and the upregulation of SREBF2 transcription. Functional rescue assays showed that SREBF2 was the critical mediator of the oncogenic roles of SREBF2-AS1 in HCC. Together, this study showed that m6A-modified SREBF2-AS1 exerted oncogenic roles in HCC through inducing DNA demethylation and transcriptional activation of SREBF2, and suggested m6A-modified SREBF2-AS1 as a prognostic biomarker and therapeutic target for HCC.

The spiral-wound heat exchanger is a key equipment in the liquefied natural gas application, but the flow and heat transfer mechanisms remain unclarified. In this study, a three-dimensional numerical model is created, focusing on exploring the impact of four crucial structural parameters on the flow and heat transfer performance of natural gas, including the external diameter of tubes, the diameter of the core cylinder, the longitudinal pitch of tubes in the same layer, and the radial pitch of tube bundles between the adjacent layer. It was found that the tube diameter, core cylinder diameter, and radial pitch had significant effects on Nu and Δp m. The optimal Nu on the shell side was obtained at medium core cylinder size. The longitudinal pitch had a weak effect on the performance of both sides, and the longitudinal pitch corresponding to the maximum values of Nu and Δp m on both sides increased with the increase in the inlet Reynolds number. Under the effect of centrifugal force, a shifted tendency was shown by the velocity and temperature fields.

Hydrogels, composed of three-dimensional polymer networks, are excellent delivery carriers and have been extensively employed in the biomedical field. Inflammation acts as a protective mechanism to prevent harmful substances from entering living organisms, but chronic, long-lasting inflammation can cause oxidative stress, which damages tissue and organs and adversely affects patients’ quality of life. The aberrant expression of microRNAs (miRNAs) has been found to play a significant part in the etiology and progression of inflammatory diseases, as suggested by growing evidence. Numerous hydrogels that can act as gene carriers for the intracellular delivery of miRNA have been described during ongoing research into innovative hydrogel materials. MiRNA hydrogel delivery systems, which are loaded with exogenous miRNA inhibitors or mimics, enable targeted miRNA intervention in inflammatory diseases and effectively prevent environmental stressors from degrading or inactivating miRNA. In this review, we summarize the classification of miRNA hydrogel delivery systems, the basic strategies and mechanisms for loading miRNAs into hydrogels, highlight the biomedical applications of miRNA hydrogel delivery systems in inflammatory diseases, and share our viewpoints on potential opportunities and challenges in the promising region of miRNA delivery systems. These findings may provide a new theoretical basis for the prevention and treatment of inflammation-related diseases and lay the foundation for clinical translation.

BackgroundThe ongoing global health crisis of COVID-19, and particularly the challenges posed by recurrent infections of the Omicron variant, have significantly strained healthcare systems worldwide. There is a growing body of evidence indicating an increased susceptibility to Omicron infection in patients suffering from Acute Kidney Injury (AKI). However, the intricate molecular interplay between AKI and Omicron variant of COVID-19 remains largely enigmatic.MethodsThis study employed a comprehensive analysis of human RNA sequencing (RNA-seq) and microarray datasets to identify differentially expressed genes (DEGs) associated with Omicron infection in the context of AKI. We engaged in functional enrichment assessments, an examination of Protein-Protein Interaction (PPI) networks, and advanced network analysis to elucidate the cellular signaling pathways involved, identify critical hub genes, and determine the relevant controlling transcription factors and microRNAs. Additionally, we explored protein-drug interactions to highlight potential pharmacological interventions.ResultsOur investigation revealed significant DEGs and cellular signaling pathways implicated in both Omicron infection and AKI. We identified pivotal hub genes, including EIF2AK2, PLSCR1, GBP1, TNFSF10, C1QB, and BST2, and their associated regulatory transcription factors and microRNAs. Notably, in the murine AKI model, there was a marked reduction in EIF2AK2 expression, in contrast to significant elevations in PLSCR1, C1QB, and BST2. EIF2AK2 exhibited an inverse relationship with the primary AKI mediator, Kim-1, whereas PLSCR1 and C1QB demonstrated strong positive correlations with it. Moreover, we identified potential therapeutic agents such as Suloctidil, Apocarotenal, 3′-Azido-3′-deoxythymidine, among others. Our findings also highlighted a correlation between the identified hub genes and diseases like myocardial ischemia, schizophrenia, and liver cirrhosis. To further validate the credibility of our data, we employed an independent validation dataset to verify the hub genes. Notably, the expression patterns of PLSCR1, GBP1, BST2, and C1QB were consistent with our research findings, reaffirming the reliability of our results.ConclusionOur bioinformatics analysis has provided initial insights into the shared genetic landscape between Omicron COVID-19 infections and AKI, identifying potential therapeutic targets and drugs. This preliminary investigation lays the foundation for further research, with the hope of contributing to the development of innovative treatment strategies for these complex medical conditions.

Background: Previous observational studies have indicated associations of physical activity (PA) and air pollution with mortality. A few studies have evaluated air pollution and PA interactions for health. Still, the trade-off between the harmful effects of air pollution exposure and the protective effects of PA remains controversial and unclear. Objective: This study aimed to investigate the joint association of air pollution and PA with mortality risks. Methods: This prospective cohort study included 322,092 participants from 2006 to 2010 and followed up to 2021 in the UK Biobank study. The concentrations of air pollutants (2006–2010), including particulate matter (PM) with diameters

Unilateral Tracheobronchial foreign body (TFB) present a common clinical disease, whereas bilateral TFB is a rare and acute condition associated with high mortality rates. This case study discusses a pediatric patient hospitalized due to respiratory distress following accidental ingestion of peanut kernels. A plain chest CT scan revealed obstructive emphysema in the right main bronchus and a foreign body at the opening of the left main bronchus. Surgical removal of the bilateral TFB under extracorporeal circulation resulted in a successful postoperative recovery, leading to discharge on the 9th day. A comprehensive literature search was conducted across databases including PubMed, Web of Science, EMBASE, Cochrane Library, and CNKI, spanning publications from January 2014 to October 2023, utilizing keywords “bronchial foreign body” and “Peanut”. After deduplication and relevance screening, 9 pertinent literature sources were included. The objective of this study is to enhance clinical practitioners' understanding of TFB management and improve diagnostic and treatment capabilities through analysis of age of onset, clinical manifestations, diagnosis, and treatment approaches in critically ill pediatric patients.

Abstract Purpose To investigate the distribution of the incidence and genotypes of human papillomavirus (HPV) among women with cervical cancer (CC) and precancerous cervical lesions in Yueyang City, China, to develop prevention and control strategies for CC. Methods A total of 3674 patients with cervical lesions and cervical cancer who attended 7 hospitals in Yueyang City between September 2019 and September 2022 were included. They included 1910 cervical intraepithelial neoplasia (CIN) I, 718 CIN II, 576 CIN II and 470 CC, respectively. The HPV genotyping of the above patients was detected by Real time-PCR in the laboratory department of each hospital. Results The total HPV prevalence was 74.69% (95% CI 73.28–76.09%) in 3674 patients. The incidence of high- and low-risk HPV was 73.46% and 7.21%, respectively. The prevalence of HPV in CIN I, CIN II, CIN III, and invasive CC (ICC) groups was 66.65% (1273/1910, 95% CI 64.53–68.77%), 80.78% (580/718, 95% CI 77.89–83.67%), 83.88% (483/576, 95% CI 80.84–86.87%), and 86.81% (408/470, 95% CI 83.74–89.88%), respectively. The top three HPV subtypes in ICC are HPV16, HPV52, and HPV58. The prevalence of HPV 16 increased with increasing disease severity, with this genotype being present in 12.57%, 20.89%, 36.98%, and 50.85% of CIN I, CIN II, CIN III, and ICC cases, respectively (p

Abstract N6-methyladenosine (m6A) is the most common RNA modification in eukaryotic RNAs. Although the important roles of m6A in RNA fate have been revealed, the potential contribution of m6A to RNA function in various diseases, including hepatocellular carcinoma (HCC), is still unclear. In this study, we identified a novel m6A-modified RNA AC026356.1. We found that AC026356.1 was increased in HCC tissues and cell lines. High expression of AC026356.1 was correlated with poor survival of HCC patients. m6A modification level of AC026356.1 was also increased in HCC and more significantly correlated with poor survival of HCC patients. Functional assays showed that m6A-modified AC026356.1 promoted HCC cellular proliferation, migration, and liver metastasis. Gene set enrichment analysis showed that AC026356.1 activated IL11/STAT3 signaling. Mechanistic investigation showed that m6A-modified AC026356.1 bound to IGF2BP1. The interaction between m6A-modified AC026356.1 and IGF2BP1 promoted the binding of IL11 mRNA to IGF2BP1, leading to increased IL11 mRNA stability and IL11 secretion. Functional rescue assays showed that depletion of IL11 reversed the oncogenic roles of AC026356.1. These findings revealed the potential influences of m6A modification on RNA biological functions and suggested that targeting m6A modification may be a novel strategy for HCC treatment.

Groundwater quality and availability in coastal aquifers have become a serious concern in recent times due to increased abstraction for domestic, agricultural and industrial purposes. (1) Background: Zhuhai city is selected as a representative coastal aquifer in Southern China to comprehensively evaluate the hydrochemical characteristics, spatial distribution and controlling mechanisms of groundwater. (2) Methods: A detailed study utilizing statistical analyses, a Piper diagram, Gibbs plots, and ion ratios was conducted on 114 surface water samples and 211 groundwater samples. (3) Results: The findings indicate that the pH of most groundwater is from 6.06 to 6.52, indicating a weakly acidic environment. The pH of surface water ranges from 5.35 to 9.86, with most values being weakly alkaline. The acidity in the groundwater may be related to the acidic atmospheric precipitation, an acidic unsaturated zone, oxidation of sulphide minerals and tidal action. The groundwater chemical types are predominantly mixed, followed by Ca-Mg-HCO3 type. Surface water samples are predominantly Na-Cl-SO4 type. The NO3− concentration in groundwater is relatively high, with a mean value of 17.46 mg/L. The NO2− and NH4+ concentrations in groundwater are relatively low, with mean values of 0.46 mg/L and 7.58 mg/L. (4) Conclusions: The spatial distribution of the principal chemical constituents in the groundwater is related to the landform. The chemical characteristics of groundwater in the study area are mainly controlled by the weathering and dissolution of silicate and sulfate minerals, evaporation, seawater mixing and cation exchange. Nitrate in clastic fissure groundwater, granite fissure groundwater and unconfined pore groundwater primarily originates from atmospheric precipitation, agricultural activities of slope farmland and forest land. Nitrate in confined pore groundwater and karst groundwater primarily originates from domestic sewage and mariculture wastewater. Our findings elucidate the processes characterizing the hydrogeology and surface water interactions in Zhuhai City’s coastal system, which are relevant to other catchments with similar geological characteristics.

Underwater methane (CH4) detection technology is of great significance to the leakage monitoring and location of marine natural gas transportation pipelines, the exploration of submarine hydrothermal activity, and the monitoring of submarine volcanic activity. In order to improve the safety of underwater CH4 detection mission, it is necessary to study the effect of hydrogen sulfide (H2S) in leaking CH4 gas on sensor performance and harmful influence, so as to evaluate the health status and life prediction of underwater CH4 sensor arrays. In the process of detecting CH4, the accuracy decreases when H2S is found in the ocean water. In this study, we proposed an explainable sorted-sparse (ESS) transformer model for concentration interval detection under industrial conditions. The time complexity was decreased to O (n logn) using an explainable sorted-sparse block. Additionally, we proposed the Ocean X generative pre-trained transformer (GPT) model to achieve the online monitoring of the health of the sensors. The ESS transformer model was embedded in the Ocean X GPT model. When the program satisfied the special instructions, it would jump between models, and the online-monitoring question-answering session would be completed. The accuracy of the online monitoring of system health is equal to that of the ESS transformer model. This Ocean-X-generated model can provide a lot of expert information about sensor array failures and electronic noses by text and speech alone. This model had an accuracy of 0.99, which was superior to related models, including transformer encoder (0.98) and convolutional neural networks (CNN) + support vector machine (SVM) (0.97). The Ocean X GPT model for offline question-and-answer tasks had a high mean accuracy (0.99), which was superior to the related models, including long short-term memory–auto encoder (LSTM–AE) (0.96) and GPT decoder (0.98).

Abstract Background Intervertebral disc degeneration (IDD) is a significant cause of low back pain and poses a significant public health concern. Genetic factors play a crucial role in IDD, highlighting the need for a better understanding of the underlying mechanisms. Aim The aim of this study was to identify potential IDD‐related biomarkers using a comprehensive bioinformatics approach and validate them in vitro. Materials and Methods In this study, we employed several analytical approaches to identify the key genes involved in IDD. We utilized weighted gene coexpression network analysis (WGCNA), MCODE, LASSO algorithms, and ROC curves to identify the key genes. Additionally, immune infiltrating analysis and a single‐cell sequencing dataset were utilized to further explore the characteristics of the key genes. Finally, we conducted in vitro experiments on human disc tissues to validate the significance of these key genes in IDD. Results we obtained gene expression profiles from the GEO database (GSE23130 and GSE15227) and identified 1015 DEGs associated with IDD. Using WGCNA, we identified the blue module as significantly related to IDD. Among the DEGs, we identified 47 hub genes that overlapped with the genes in the blue module, based on criteria of |logFC| ≥ 2.0 and p.adj

Abstract Polymerization‐induced self‐assembly (PISA) enables the simultaneous growth and self‐assembly of block copolymers in one pot and therefore has developed into a high‐efficiency platform for the preparation of polymer assemblies with high concentration and excellent reproducibility. During the past decade, the driving force of PISA has extended from hydrophobic interactions to other supramolecular interactions, which has greatly innovated the design of PISA, enlarged the monomer/solvent toolkit, and endowed the polymer assemblies with intrinsic dynamicity and responsiveness. To unravel the important role of driving forces in the formation of polymeric assemblies, this review summarized the recent development of PISA from the perspective of driving forces. Motivated by this goal, here we give a brief overview of the basic principles of PISA and systematically discuss the various driving forces in the PISA system, including hydrophobic interactions, hydrogen bonding, electrostatic interactions, and π‐π interactions. Furthermore, PISA systems that are driven and regulated by crystallization or liquid crystalline ordering were also highlighted.

To investigate the lipid-lowering activity of PVSO (a natural oil derived from the mature seeds of Prunella vulgaris L.), supercritical CO2 extraction technology was used to extract, and the components were characterized using GC–MS/MS and LC-MS/MS techniques. The lipid-lowering activity of PVSO was evaluated in vitro and in vivo. The results indicated that the supercritical CO2 extraction rate of PVSO was 16.63 %, and the ratio of linolenic acid to linoleic acid was 3:1. In addition, PVSO also contains bioactive components such as phenols, terpenes, flavonoids, and squalene. In vitro experiments showed that PVSO has a strong inhibitory effect on porcine pancreatic lipase, cholesterol esterase, and cholesterol micellization in a significant dose-dependent manner. In vivo experiments showed that PVSO (500 and 800 mg/kg) intervention markedly attenuated body-weight gain, liver weights, hepatic steatosis, oxidative stress biomarkers, and dyslipidemia induced by HFD (p

Let $ \mathbb{D}^{m \times n} = \{A = A_{1}+\varepsilon A_{2}|A_{1}, A_{2}\in \mathbb{R}^{m \times n}\} $ be the set of all $ m\times n $ real dual matrices. In this paper, the following problems are considered. Problem I: Given dual matrices $ A = A_{1}+\varepsilon A_{2}\in \mathbb{D}^{m\times n} $ and $ B = B_{1}+\varepsilon B_{2}\in \mathbb{D}^{n\times n} $, find $ X\in S $ such that the dual matrix equation $ A^\top XA = B $ is satisfied, where $ S = \{X\in \mathbb{D}^{m \times m}|CX = D, C, D\in \mathbb{D}^{p \times m}\} $. Problem II: Given dual matrices $ A = A_{1}+\varepsilon A_{2}\in \mathbb{D}^{m\times n}, B = B_{1}+\varepsilon B_{2}\in \mathbb{D}^{n\times n} $ and $ \tilde{X} = \tilde{X}_{1}+\varepsilon \tilde{X}_{2}\in \mathbb{D}^{m\times m} $, with $ B_{i} = B^\top_{i}, i = 1, 2 $, find $ \hat{X}\in T $ such that $ \|\hat{X}-\tilde{X}\|_{{\rm D}} = \mathop{\min}\limits_{X\in T} \|X-\tilde{X}\|_{{\rm D}} = \mathop{\min}\limits_{X\in T}\sqrt{\Vert X_{1}-\tilde{X}_{1} \Vert^{2}+\Vert X_{2}-\tilde{X}_{2}\Vert^{2}} $, where $ T = \{X = X_{1}+\varepsilon X_{2}\in \mathbb{D}^{m \times m}|A^\top XA = B \ \ \mbox{s. t.} \ X_{i} = X^\top_{i}, i = 1, 2\} $. We derive the solvability conditions and the representation of the general solution of Problem I using the Moore-Penrose inverse. Also, we deduce the solvability conditions and the explicit formula of $ T $ and the unique approximation solution $ \hat{X} $ of Problem II by applying the Moore-Penrose inverse and Kronecker product of matrices. Finally, we give a numerical example to show the correctness of our result.

Abstract Introduction Postoperative delirium (POD) is a common complication, and it has a high incidence in neurosurgery patients. Awake craniotomy (AC) has been widely performed in patients with glioma in eloquent and motor areas. Most of the surgical procedure is frontotemporal craniotomy, and the operation duration has been getting longer. Patients undergoing AC are high-risk populations for POD. Dexmedetomidine (Dex) administration perioperatively might help to reduce the incidence of POD. The purpose of this study is to investigate the effect of Dex on POD in patients undergoing AC. Methods The study is a prospective, single-center, double-blinded, paralleled-group, randomized controlled trial. Patients undergoing elective AC will be randomly assigned to the Dex group and the control group. Ten minutes before urethral catheterization, patients in the Dex group will be administered with a continuous infusion at a rate of 0.2 µg/kg/h until the end of dural closure. In the control group, patients will receive an identical volume of normal saline in the same setting. The primary outcome will be the cumulative incidence and severity of POD. It will be performed by using the confusion assessment method in the first 5 consecutive days after surgery. Secondary outcomes include quality of intraoperative awareness, stimulus intensity of neurological examination, pain severity, quality of recovery and sleep, and safety outcomes. Discussion This study is to investigate whether the application of Dex could prevent POD in patients after undergoing AC and will provide strong evidence-based clinical practice on the impact of intraoperative interventions on preventing POD in AC patients. Trial registration ClinicalTrials.gov, NCT05195034. Registered on January 18, 2022.

Introduction To investigate the expression and treatment of chemokine CXCL12 and its receptor CXCR4/CXCR7. Methods The liver cirrhosis hypersplenism model of rats was made with CCL4, and then was detected by immunohistochemistry, Western blot and qRT-PCR. Results The area of spleen fibrosis in the model group was significantly larger than that in the control group (p < 0.01), and the expression of CXCL12, CXCR4 and CXCR7 in the model group was significantly higher than that in the control group (p < 0.01). Conclusions CXCL12-CXCR4/CXCR7 is abnormally high in splenic fibrosis, and blocking its high expression can slow down the occurrence of hypersplenism.

Abstract Due to increasing morbidity worldwide, fractures are becoming an emerging public health concern. This study aimed to investigate the effect of metformin on the healing of osteoporotic as well as normal fractures. Type H vessels have recently been identified as a bone-specific vascular subtype that supports osteogenesis. Here, we show that metformin accelerated fracture healing in both osteoporotic and normal mice. Moreover, metformin promoted angiogenesis in vitro under hypoxia as well as type H vessel formation throughout fracture healing. Mechanistically, metformin increased the expression of HIF-1α, an important positive regulator of type H vessel formation, by inhibiting the expression of YAP1/TAZ in calluses and hypoxia-cultured human microvascular endothelial cells (HMECs). The results of HIF-1α or YAP1/TAZ interference in hypoxia-cultured HMECs using siRNA further suggested that the enhancement of HIF-1α and its target genes by metformin is primarily through YAP1/TAZ inhibition. Finally, overexpression of YAP1/TAZ partially counteracted the effect of metformin in promoting type H vessel-induced angiogenesis-osteogenesis coupling during fracture repair. In summary, our findings suggest that metformin has the potential to be a therapeutic agent for fractures by promoting type H vessel formation through YAP1/TAZ inhibition.

Abstract Aims Atherosclerosis is a huge threaten to the human health, C1q/TNF‐related protein 9 (CTRP9) has been previously reported possessing vascular protective functions. Our study is aimed to reveal the mechanism of the regulative effects of CTRP9 on the foam cell formation. Methods and results Primary human macrophages were isolated from human monocytes donated by healthy volunteers. CCK‐8 assay was performed for determining the cell viability. Oil Red O staining was employed for measuring the lipid accumulation. Cholesterol ester and cholesterol concentration were detected by commercial kits for evaluating the intracellular cholesterol. Ubiquitination assay was performed to reveal the ubiquitination level of CD36, cycloheximide assay was applied for determining the half‐life of CD36 protein. Quantitative real‐time PCR and western blot assays were performed for detecting the mRNA and protein expression. Pre‐treatment with CTRP9 in primary human macrophages markedly suppressed the cholesterol accumulation concentration after oxidized low‐density lipoprotein treatment. CD36 was significantly increased after oxidized low‐density lipoprotein exposure while was reduced by CTRP9 treatment. Up‐regulation of CD36 significantly reversed the CTRP9‐mediated protective effects in foam cells. The differential expression levels of several deubiquitinating enzymes preliminarily indicated that USP11 was obviously decreased after CTRP9 treatment. USP11 knockdown decreased the CD36 protein expression and pre‐treatment with 10 μg/mL MG132 significantly maintained the CD36 level from USP11 knock down. Up‐regulation of CD36 reversed the alterations on the cholesterol metabolism caused by CTRP9 or USP11 knockdown. Conclusions CTRP9 regulates the USP11/CD36 axis to protect the macrophages form transforming into foam cells by suppressing intracellular lipid and cholesterol accumulation, which is a potential therapeutic agent for atherosclerosis.

The increasing discovery of underwater methane leakage underscores the importance of monitoring methane emissions for environmental protection. Underwater remote sensing of methane leakage is critical and meaningful to protect the environment. The construction of sensor arrays is recognized as the most effective technique to increase the accuracy and sensitivity of underwater remote sensing of methane leakage. With the aim of improving the reliability of underwater methane remote-sensing sensor arrays, in this work, a deep learning method, specifically an explainable sparse spatio-temporal transformer, is proposed for detecting the failures of the underwater methane remote-sensing sensor arrays. The data input into the explainable sparse block could decrease the time complexity and the computational complexity (O (n)). Spatio-temporal features are extracted on various time scales by a spatio-temporal block automatically. In order to implement the data-driven early warning system, the data-driven warning return mechanism contains a warning threshold that is associated with physically disturbing information. Results show that the explainable sparse spatio-temporal transformer improves the performance of the underwater methane remote-sensing sensor array. A balanced F score (F1 score) of the model is put forward, and the anomaly accuracy is 0.92, which is superior to other reconstructed models such as convolutional_autoencoder (CAE) (0.81) and long-short term memory_autoencoder (LSTM-AE) (0.66).

Flexible ammonia (NH3) gas sensors have gained increasing attention for their potential in medical diagnostics and health monitoring, as they serve as a biomarker for kidney disease. Utilizing the pre-designable and porous properties of covalent organic frameworks (COFs) is an innovative way to address the demand for high-performance NH3 sensing. However, COF particles frequently encounter aggregation, low conductivity, and mechanical rigidity, reducing the effectiveness of portable NH3 detection. To overcome these challenges, we propose a practical approach using polyvinyl alcohol-carrageenan (κPVA) as a template for in the situ growth of two-dimensional COF film and particles to produce a flexible hydrogel gas sensor (COF/κPVA). The synergistic effect of COF and κPVA enhances the gas sensing, water retention, and mechanical properties. The COF/κPVA hydrogel shows a 54.4% response to 1 ppm NH3 with a root mean square error of less than 5% and full recovery compared to the low response and no recovery of bare κPVA. Owing to the dual effects of the COF film and the particles anchoring the water molecules, the COF/κPVA hydrogel remained stable after 70 h in atmospheric conditions, in contrast, the bare κPVA hydrogel was completely dehydrated. Our work might pave the way for highly sensitive hydrogel gas sensors, which have intriguing applications in flexible electronic devices for gas sensing.

The aggregation of graphene oxide (GO) during the hydration process limits its wide application. Polymer superplasticizers have been used to improve the dispersion state of GO due to their adsorption and site-blocking effects, though the formation of a large amount of foam during the mixing process weakens the mechanical properties of cement. A highly dispersed amphoteric polycarboxylate superplasticizer-stabilized graphene oxide (APC/GO) toughening agent was prepared by electrostatic self-assembly. Results demonstrate that the APC/GO composite dispersed well in a cement pore solution due to the steric effect offered by the APC. Additionally, the well-dispersed GO acted as an antifoaming agent in the cement since GO nanosheets can be absorbed at the air–liquid interface of APC foam via electrostatic interactions and eliminate the air-entraining effect. The well-dispersed APC/GO sheets promoted cement hydration and further refined its pore structure owing to the nucleation effect. The flexural and compressive strength of the cement containing the APC/GO composite were enhanced by 21.51% and 18.58%, respectively, after a 7-day hydration process compared with a blank sample. The improved hydration degree, highly polymerized C-S-H gel, and refined pore structure provided enhanced mechanical properties.

The solvability conditions for the dual matrix equation $ AXB = D $ and a pair of dual matrix equations $ AX = C $ and $ XB = D $ are deduced by applying the singular value decomposition, and the expressions of the general solutions to these dual matrix equations are provided. Furthermore, the minimum-norm solutions of these dual matrix equations are provided. Finally, two numerical experiments are given to validate the accuracy of the results obtained.

Abstract Key message Primary remains of Eucalyptus (E. urophylla × E. grandis) plantations following clear-cutting are the stumps and coarse roots. A chrono-sequence approach revealed that the biomass of coarse roots is higher than that of stumps, while they have a smaller rate of biomass loss than stumps. This implies that coarse roots serve as long-term stock for nutrients (carbon, nitrogen, and phosphorus). Context A significant quantity of stumps and coarse roots persist in the forest floor following the clear-cutting of Eucalyptus plantations in China. The decomposition of these stumps and coarse roots is a crucial aspect of the nutrient stocks in plantation ecosystems. Aims We described the stock and decomposition dynamics of stumps and coarse roots on Eucalyptus plantations, as well as the nutrient loss rate associated with them. Methods We used a chrono-sequence of 0–6-year-old clear-cutting stands of Eucalyptus plantations in southern China. The biomass and nutrient stocks of these samples were assessed at different times of decomposition. Results The highest biomass of stump-root system was 33.8 Mg·ha−1, with nutrient stocks were 16.3 Mg·ha−1, and 63.0 kg·ha−1, and 6710.9 g·ha−1, for C, N, and P. The coarse roots accounted for 81–96% of the biomass of the stump-root system. The loss rate of biomass and nutrients from stumps was higher than that of coarse roots. This suggests that the decomposition of coarse roots could serve as a long-term source of nutrients, thereby improving the nutrient status of the plantations. Conclusion Stumps and coarse roots serve as significant nutrient stocks that decay at varying rates. The loss of nutrients must be considered while analyzing the decomposition dynamics following clear-cutting in Eucalyptus plantations.

Abstract Groundwater is an important source of water for human sustenance. The determination of groundwater quality at island sites is an urgent priority in China, but there are lacking systematic reports relating to them. Here, 63 groups of groundwater samples were collected and analyzed of Hainan Island. The groundwater in the study area is weakly alkaline, mainly comprising hard and soft freshwater. The predominant anions and cations are HCO3 −, and Ca2+ and Na+, respectively, and the main water chemistry types are HCO3–Cl–Na and HCO3–Cl–Na–Ca. The chemical evolution of groundwater is mainly affected by water–rock interactions, cation exchange, and human activity. The groundwater is mostly of high quality and, in most areas, is suitable for drinking and irrigation. Contrastingly, the water quality in the west of the island is relatively poor. The spatial distribution of the risk coefficient (HQ) is consistent with the spatial variation in the NO3 − concentrations in the groundwater. Notably, there are unacceptable health risks for different groups of people, with infants having the greatest level of impact, followed by children, teenagers, and adults. This study provides a valuable reference for the development and utilization of groundwater resources, as well as the improvement of aquatic ecological conditions on Hainan Island and other island areas worldwide.

The controllable manipulation of polar topological structures (e.g. skyrmion bubble) in ferroelectric materials have been considered as a cornerstone for future programmable nano-electronics. Here, we present the effective creation and erasure of polar bubble states PbTiO3 (PTO) multilayers trigged by mechanical stress and light illumination, respectively. It was found that applying atomic force microscope (AFM) tip force can induced formation of nanoscale bubble domains from the initial monodomain state. Moreover, the created bubble domain can be eliminated by exposure to ultraviolet or infrared light illumination. The above results can be understood by modulation of depolarization screening charges and bias fields, as reflected by scanning Kelvin potential microscopic (SKPM) observations, whereby the flexoelectric effect from the tip force tends to remove the screening charges on top surface and modulate the bias field that favors the formation of bubble state while light illumination tends to recover the screen charges and favor the monodomain state. The results provide a good example for multi-field manipulation of polar topologies, which might create a new avenue towards the immerging new concept electronic devices.

Abstract Reservoir computing (RC) offers efficient temporal information processing with low training cost. All-ferroelectric implementation of RC is appealing because it can fully exploit the merits of ferroelectric memristors (e.g., good controllability); however, this has been undemonstrated due to the challenge of developing ferroelectric memristors with distinctly different switching characteristics specific to the reservoir and readout network. Here, we experimentally demonstrate an all-ferroelectric RC system whose reservoir and readout network are implemented with volatile and nonvolatile ferroelectric diodes (FDs), respectively. The volatile and nonvolatile FDs are derived from the same Pt/BiFeO3/SrRuO3 structure via the manipulation of an imprint field (E imp). It is shown that the volatile FD with E imp exhibits short-term memory and nonlinearity while the nonvolatile FD with negligible E imp displays long-term potentiation/depression, fulfilling the functional requirements of the reservoir and readout network, respectively. Hence, the all-ferroelectric RC system is competent for handling various temporal tasks. In particular, it achieves an ultralow normalized root mean square error of 0.017 in the Hénon map time-series prediction. Besides, both the volatile and nonvolatile FDs demonstrate long-term stability in ambient air, high endurance, and low power consumption, promising the all-ferroelectric RC system as a reliable and low-power neuromorphic hardware for temporal information processing.

Highlights Imine groups in covalent organic framework (COF) films act as dual-active sites for humidity sensing, inducing an intrinsic enhanced mechanism of reversible protonated tautomerism via water molecule-induced hydrogen bonding. The cis-ketoimine reciprocal isomerization induces a stretching vibration effect for the ordered conjugated conductive frame of COF films, realizing fast response, wide range, and high sensitivity characteristics for humidity detection. Resistance changes of COF film-based sensors keep a strong linear relationship with low-range relative humidity, reflecting the quantitative sensing mechanism at the molecular level.

IntroductionIt is unclear how tranexamic acid (TXA) affects blood loss and seizures in meningioma resections. We performed a systematic review and meta-analysis and tried to evaluate the effectiveness and safety of TXA use for patients undergoing meningioma resections.MethodsRegards to this systematic review and meta-analysis (registered with CRD42023416693), we searched PubMed, Embase (Ovid), EBSCO, and Cochrane central library up to and including Oct 2023. Patients undergoing meningioma resections treated with TXA and placebo or no treatment were eligible for this study. This would allow delineation of the impact of TXA on blood loss, postoperative seizure, and other complication incidences.ResultsFour prospective cohort studies with 781 patients (390 patients in the TXA group and 391 patients in the control group) were conducted via a systematic review and meta-analysis. The results suggested that the application of TXA for patients undergoing meningioma resections reduced mean blood loss of 252 mL with 95% confidence interval (CI) -469.26 to -34.67 (P = 0.02) and I2 of 94% but did not increase postoperative seizure (risk ratio: 1.08; 95%CI: 0.54 to 2.15; P = 0.84) and other complication rates.ConclusionsThis systematic review and meta-analysis suggests that the administration of TXA could reduce blood loss in patients undergoing intracerebral meningioma resection.Registry informationThe systematic review protocol has been registered at PROSPERO (Registration No. CRD42023416693) on April 23, 2023.

IntroductionDiabetic nephropathy (DN), distinguished by detrimental changes in the renal glomeruli, is regarded as the leading cause of death from end-stage renal disease among diabetics. Cellular senescence plays a paramount role, profoundly affecting the onset and progression of chronic kidney disease (CKD) and acute kidney injuries. This study was designed to delve deeply into the pathological mechanisms between glomerulus-associated DN and cellular senescence.MethodsGlomerulus-associated DN datasets and cellular senescence-related genes were acquired from the Gene Expression Omnibus (GEO) and CellAge database respectively. By integrating bioinformatics and machine learning methodologies including the LASSO regression analysis and Random Forest, we screened out four signature genes. The receiver operating characteristic (ROC) curve was performed to evaluate the diagnostic performance of the selected genes. Rigorous experimental validations were subsequently conducted in the mouse model to corroborate the identification of three signature genes, namely LOX, FOXD1 and GJA1. Molecular docking with chlorogenic acids (CGA) was further established not only to validate LOX, FOXD1 and GJA1 as diagnostic markers but also reveal their potential therapeutic effects.Results and discussionIn conclusion, our findings pinpointed three diagnostic markers of glomerulus-associated DN on the basis of cellular senescence. These markers could not only predict an increased risk of DN progression but also present promising therapeutic targets, potentially ushering in innovative treatments for DN in the elderly population.

ATG7, one of the core proteins of autophagy, plays an important role in various biological processes, including the regulation of autophagy. While clear that autophagy drives angiogenesis, the role of ATG7 in angiogenesis remains less defined. Several studies have linked ATG7 with angiogenesis, which has long been underappreciated. The knockdown of ATG7 gene in cerebrovascular development leads to angiogenesis defects. In addition, specific knockout of ATG7 in endothelial cells results in abnormal development of neovascularization. Notably, the autophagy pathway is not necessary for ATG7 regulation of angiogenesis, while the ATG7-dependent non-autophagic pathway plays a critical role in the regulation of neovascularization. In order to gain a better understanding of the non-autophagic pathway-mediated biological functions of the autophagy-associated protein ATG7 and to bring attention to this expanding but understudied research area, this article reviews recent developments in the ATG7-dependent non-autophagic pathways regulating angiogenesis.

Memristive neural networks have extensively been investigated for their capability in handling various artificial intelligence tasks. The training performance of memristive neural networks depends on the pulse scheme applied to the constituent memristors. However, the design of the pulse scheme in most previous studies was approached in an empirical manner or through a trial-and-error method. Here, we choose ferroelectric tunnel junction (FTJ) as a model memristor and demonstrate a physics-based predictive model for the pulse design to achieve high training performance. This predictive model comprises a physical model for FTJ that can adequately describe the polarization switching and memristive switching behaviors of the FTJ and an FTJ-based neural network that uses the long-term potentiation (LTP)/long-term depression (LTD) characteristics of the FTJ for the weight update. Simulation results based on the predictive model demonstrate that the LTP/LTD characteristics with a good trade-off between ON/OFF ratio, nonlinearity, and asymmetry can lead to high training accuracies for the FTJ-based neural network. Moreover, it is revealed that an amplitude-increasing pulse scheme may be the most favorable pulse scheme as it offers the widest ranges of pulse amplitudes and widths for achieving high accuracies. This study may provide useful guidance for the pulse design in the experimental development of high-performance memristive neural networks.

Sarcopenia, a disease recognized by the World Health Organization, has posed a great challenge to the world in the current aging society. The vital role of the gut microbiome through the gut-muscle axis in sarcopenia is increasingly recognized. However, the working mechanisms by which the gut microbiota functions have not been fully explored in the multi-omics field. Here, we designed a cross-sectional study that recruited patients (n = 32) with sarcopenia and healthy old adults (n = 31). Diagnosis of sarcopenia was based on the Asian Working Group for Sarcopenia (AWGS) in 2019 criteria. Muscle mass was represented by appendicular skeletal muscle mass measured by using direct segmental multi-frequency bioelectrical impedance and muscle strength was evaluated using the handgrip strength. The Short Physical Performance Battery, the 5-time Chair Stand Test, and the 4-metre Walk Test were used to assess physical performance. Shotgun metagenomic sequencing was used to profile the gut microbiome in order to identify its construction and function. Metabolome based on untargeted metabolomics was applied to describe the features and structure of fecal metabolites. In clinical indexes including triglycerides and high-density lipoprotein cholesterol, we noted a significant decrease in triglycerides (TG) and a significant increase in high-density lipoprotein cholesterol (HDL-C) in patients with sarcopenia. Appendicular skeletal muscle mass of patients with sarcopenia was lower than the health group. Based on intestinal metagenomic and fecal metabolomic profiles, we found that the gut microbiome and metabolome were disturbed in patients with sarcopenia, with significant decreases in bacteria such as Bifidobacterium longum, Bifidobacterium pseudocatenulatum, and Bifidobacterium adolescentis, as well as metabolites such as shikimic acid. Also, we plotted supervised classification models at the species level of gut bacteria (AUC = 70.83–88.33) and metabolites (AUC = 92.23–98.33) based on machine learning, respectively. Based on the gut-muscle axis network, a potential mechanism is proposed along the gut microbiome - key metabolites - clinical index, that Phascolarctobacterium faecium affects appendicular skeletal muscle mass, calf circumference, handgrip strength, and BMI via Shikimic acid metabolites. This study elucidates the potential mechanisms by which the gut microbiome influences the progress of sarcopenia through metabolites and provides a meaningful theoretical foundation for reference in the diagnosis and treatment of sarcopenia.

AbstractIntroduction Dysmagnesemia has been demonstrated to be involved in the pathophysiology of kidney diseases and is common in cardiac surgical patients. It remains unknown whether changes of serum magnesium after cardiac surgery affect AKI. We aimed to investigate the association of early postoperative magnesium with cardiac surgery-associated AKI in adults.Methods We conducted a multicenter retrospective cohort study involving patients who underwent cardiac surgery in the eICU Collaborative Research Database between 2014 and 2015. AKI within 7 days after surgery was defined using both serum creatinine and urine output criteria of Kidney Disease Improving Global Outcomes definition. Postoperative AKI was analyzed using multivariable logistic regression with early postoperative serum magnesium measured within the first 24 h after surgery as a continuous variable and categorically by quartiles.Results Postoperative AKI was identified in 3498 of 6124 (57.1%) patients receiving cardiac surgery. The median (25th–75th percentiles) early postoperative serum magnesium level of the study population was 2.3 (2.0–2.7) mg/dL. Higher serum magnesium level was associated with a higher risk of developing postoperative AKI (adjusted odds ratio (OR), 1.46 per 1 mg/dL increase; 95% confidence interval (CI), 1.31–1.62; p

Abstract Congenital heart disease (CHD) is a prevalent birth defect and a significant contributor to childhood mortality. The major characteristics of CHD include cardiovascular malformations and hemodynamical disorders. However, the impact of CHD extends beyond the circulatory system. Evidence has identified dysbiosis of the gut microbiome in patients with CHD. Chronic hypoxia and inflammation associated with CHD affect the gut microbiome, leading to alterations in its number, abundance, and composition. The gut microbiome, aside from providing essential nutrients, engages in direct interactions with the host immune system and indirect interactions via metabolites. The abnormal gut microbiome or its products can translocate into the bloodstream through an impaired gut barrier, leading to an inflammatory state. Metabolites of the gut microbiome, such as short‐chain fatty acids and trimethylamine N‐oxide, also play important roles in the development, treatment, and prognosis of CHD. This review discusses the role of the gut microbiome in immunity, gut barrier, neurodevelopment, and perioperative period in CHD. By fostering a better understanding of the cross‐talk between CHD and the gut microbiome, this review aims to contribute to improve clinical management and outcomes for CHD patients.

The lattice Boltzmann method is employed in the current study to simulate the heat transfer characteristics of sinusoidal-temperature-distributed heat sources at the bottom of a square cavity under various conditions, including different amplitudes, phase angles, initial positions, and angular velocities. Additionally, a machine learning-based model is developed to accurately predict the Nusselt number in such a sinusoidal temperature distribution of heat source at the bottom of a square cavity. The results indicate that (1) in the phase angle range from 0 to π, Nu basically shows a decreasing trend with an increase in phase angle. The decline in Nu at an accelerated rate is consistently observed when the phase angle reaches 4π/16. The corresponding Nu decreases as the amplitude increases at the same phase angle. (2) The initial position of the sinusoidal-temperature-distributed heat source Lc significantly impacts the convective heat transfer in the cavity. Moreover, the decline in Nu was further exacerbated when Lc reached 7/16. (3) The optimal overall heat transfer effect was achieved when the angular velocity of the non-uniform heat source reached π. As the angular velocity increases, the local Nu in the square cavity exhibits a gradual and oscillatory decline. Notably, it is observed that Nu at odd multiples of π surpasses that at even multiples of π. Furthermore, the current work integrates LBM with machine learning, enabling the development of a precise and efficient prediction model for simulating Nu under specific operational conditions. This research provides valuable insights into the application of machine learning in the field of heat transfer.

Carbon nanotubes (CNTs) are considered ideal nanoscale reinforcement for the development of high-performance metal matrix composites due to their unique structure and excellent mechanical properties. However, CNTs are easy to agglomerate and have poor wettability with the aluminum matrix, resulting in unsatisfactory effects when added to the aluminum melt. In this study, Cu-coated carbon nanotubes (Cu@CNTs)-reinforced aluminum matrix composites were fabricated by high-energy ultrasonic-assisted casting. Moreover, the effects of different Cu@CNTs content on the microstructure and mechanical properties of aluminum matrix composites were explored. Meanwhile, Fluent 19.0 software was used to further explore the function of ultrasonic vibration in the melt. The results demonstrated that the mechanical properties of composite with 1.2 wt% Cu@CNTs are optimal. Compared with the matrix, the composite with 1.2 wt% Cu@CNTs displayed a 39.3% increase in yield strength, 53.5% increase in ultimate tensile strength, and 5.7% increase in elongation. The simulation results showed that the uniform dispersion of Cu@CNTs and grain refinement can be attributed to the acoustic streaming effect and cavitation effect of high-energy ultrasound. The improvement of the properties of the composites can be attributed to the grain refinement and the load-bearing effect of CNTs.

Realizing robust magnetoelectric (ME) coupling effect near room temperature is still a long-standing challenge for the application of multiferroic materials in next-generation low-power spintronic and memory devices. Here we report a systematic study on the magnetic, dielectric, and ME coupling properties of Y-type hexaferrite Ba0.5Sr1.5Co2Fe12–xAlxO22 (x = 0.0, 0.5, 1.0) single crystals. The Al doping can induce the shifting of the alternating longitudinal conical (ALC)-proper screw (PS) magnetic phase transition temperature from 200 K for x = 0–365 K for x = 1.0. The most interesting feature is that the Ba0.5Sr1.5Co2Fe11AlO22 single crystal displays a direct and converse ME coupling coefficient with αH ∼3,100 ps/m and αE ∼3,900 ps/m at 250 K, respectively, due to the Al-doped enhanced stability of ALC phase. Moreover, the exchange bias also verifies the strong coupling of electric and magnetic orders. These results provide a valuable insight on the modulation of ALC structure and the mechanism of ME effect in Y-type hexaferrites.