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Abstract Genetically encoded fluorescent biosensors became indispensable tools for biological research, enabling real-time observation of physiological processes in live cells. Recent protein engineering efforts have resulted in the generation of a large variety of fluorescent biosensors for a wide range of biologically relevant processes, from small ions to enzymatic activity and signaling pathways. However, biosensors for imaging sulfate ions, the fourth most abundant physiological anion, in mammalian cells are still lacking. Here, we report the development and characterization of a green fluorescent biosensor for sulfate named Thyone. Thyone, derived through structure-guided design from bright green fluorescent protein mNeonGreen, exhibited a large negative fluorescence response upon subsecond association with sulfate anion with an affinity of 11 mM in mammalian cells. By integrating mutagenesis analyses with molecular dynamics simulations, we elucidated the molecular mechanism of sulfate binding and revealed key amino acid residues responsible for sulfate sensitivity. High anion selectivity and sensitivity of Thyone allowed for imaging of sulfate anion transients mediated by sulfate transporter heterologously expressed in cultured mammalian cells. We believe that Thyone will find a broad application for assaying the sulfate transport in mammalian cells via anion transporters and exchangers.

Abstract As unmanned vehicle technology advances rapidly, obstacle recognition and target detection are crucial links, which directly affect the driving safety and efficiency of unmanned vehicles. In response to the inaccurate localization of small targets such as pedestrians in current object detection tasks and the problem of losing local features in the PointPillars, this paper proposes a three-dimensional object detection method based on improved PointPillars. Firstly, addressing the issue of lost spatial and local information in the PointPillars, the feature encoding part of the PointPillars is improved, and a new pillar feature enhancement extraction module, CSM-Module, is proposed. Channel encoding and spatial encoding are introduced in the new pillar feature enhancement extraction module, fully considering the spatial information and local detailed geometric information of each pillar, thereby enhancing the feature representation capability of each pillar. Secondly, based on the fusion of CSPDarknet and SENet, a new backbone network CSE-Net is designed in this paper, enabling the extraction of rich contextual semantic information and multi-scale global features, thereby enhancing the feature extraction capability. Our method achieves higher detection accuracy when validated on the KITTI dataset. Compared to the original network, the improved algorithm’s average detection accuracy is increased by 3.42%, it shows that the method is reasonable and valuable.

Abstract Methyltransferase-like protein is a ubiquitous enzyme-like protein in the human body, with binding domains for nucleic acids, proteins and other small molecules, and plays an important role in a variety of biological behaviours in normal organisms and diseases, characterised by the presence of a methyltransferase-like structural domain and a structurally conserved SAM-binding domain formed by the seven-stranded β-fold structure in the center of the protein. With the deepening of research, the METTL protein family has been found to be abnormally expressed in a variety of tumor diseases, and the clarification of its relationship with tumor diseases can be used as a molecular therapeutic target and has an important role in the prognosis of tumors. In this paper, we review the structure, biological process, immunotherapy, drug-targeted therapy, and markers of the METTL protein family to provide new ideas for the diagnosis and treatment of tumors.

Abstract Background Dental caries is still a major disease that affect the oral health of people in China. First permanent molars (FPMs) are the most caries-susceptible teeth among school-aged children. The aim of this study was to investigate the eruption and caries status of first permanent molars in children aged 6–7 years in Shijingshan District, Beijing, China, to provide information for oral health promotion. Methods The study was a cross-sectional survey conducted in 6-7-year-old first grade children from public elementary schools in Shijingshan District, Beijing. Participants were invited to receive a clinical oral examination. The eruption status and caries experience of FPMs were recorded. Questionnaires assessing children’s sociodemographic information and oral health-related behaviors were completed by the children’s parents or guardians. Results A total of 3,176 children, including 1,644 boys (51.8%) and 1,532 girls (48.2%) were included in the oral examination and questionnaire. Eruption status of FPMs was as follows: 37.5% fully erupted, 28.3% partially erupted, 34.2% not erupted. Girls had more erupted FPMs than boys (70.1% VS 61.8%, P

The preparation process of soy hull nanocellulose hydrogel was optimized by Box-Behnken response surface. The structure and properties of soy hull nanocellulose hydrogel were studied. On the basis of single factor experiment, the preparation process of soy hull nanocellulose hydrogel was optimized through response surface with three factors and three levels when the maximum stress was used as the index. The structure and properties of soy hull nanocellulose hydrogel were characterized by Fourier transform infrared spectroscopy, X ray polycrystalline diffractometer, scanning electron microscopy, UV spectrophotometer, etc. The optimal process parameters were as follows: gelling temperature 191 ℃, freezing time 102 h, CaCl2 concentration 7%. Under this condition, the actual maximum stress of soy hull nanocellulose hydrogel was 84.11 kPa, which was close to the predicted value of 83.7 kPa. The nanocellulose of soy hull/sodium alginate/CaCl2 (SCNFs/SA/CaCl2) hydrogel showed uniform 3D network structure, excellent tensile performance (elongation at break was 220%), mechanical strength (83.97 kPa), transmittance (82%), and electrical conductivity (1.58 S/cm). The SCNFs/SA/CaCl2 hydrogel also had excellent mechanical strength and fatigue resistance after five cycles of stretching, so the service life of hydrogel was increased. This study provides a new method for preparing a tough, transparent, conductive and fatigue-resistant nanocellulose hydrogel.

Abstract The regulatory significance of ubiquitin-specific peptidase 32 (USP32) in tumor is significant, nevertheless, the biological roles and regulatory mechanisms of USP32 in non-small cell lung cancer (NSCLC) remain unclear. According to our research, USP32 was strongly expressed in NSCLC cell lines and tissues and was linked to a bad prognosis for NSCLC patients. Interference with USP32 resulted in a significant inhibition of NSCLC cell proliferation, migration potential, and EMT development; on the other hand, USP32 overexpression had the opposite effect. To further elucidate the mechanism of action of USP32 in NSCLC, we screened H1299 cells for interacting proteins and found that USP32 interacts with BAG3 (Bcl2-associated athanogene 3) and deubiquitinates and stabilizes BAG3 in a deubiquitinating activity-dependent manner. Functionally, restoration of BAG3 expression abrogated the antitumor effects of USP32 silencing. Furthermore, USP32 increased the phosphorylation level of the RAF/MEK/ERK signaling pathway in NSCLC cells by stabilizing BAG3. In summary, these findings imply that USP32 is critical to the development of NSCLC and could offer a theoretical framework for the clinical diagnosis and management of NSCLC patients in the future.

Abstract Large national-level electronic health record (EHR) datasets offer new opportunities for disentangling the role of genes and environment through deep phenotype information and approximate pedigree structures. Here we use the approximate geographical locations of patients as a proxy for spatially correlated community-level environmental risk factors. We develop a spatial mixed linear effect (SMILE) model that incorporates both genetics and environmental contribution. We extract EHR and geographical locations from 257,620 nuclear families and compile 1083 disease outcome measurements from the MarketScan dataset. We augment the EHR with publicly available environmental data, including levels of particulate matter 2.5 (PM2.5), nitrogen dioxide (NO2), climate, and sociodemographic data. We refine the estimates of genetic heritability and quantify community-level environmental contributions. We also use wind speed and direction as instrumental variables to assess the causal effects of air pollution. In total, we find PM2.5 or NO2 have statistically significant causal effects on 135 diseases, including respiratory, musculoskeletal, digestive, metabolic, and sleep disorders, where PM2.5 and NO2 tend to affect biologically distinct disease categories. These analyses showcase several robust strategies for jointly modeling genetic and environmental effects on disease risk using large EHR datasets and will benefit upcoming biobank studies in the era of precision medicine.

Ferroptosis, an emerging paradigm of programmed cellular necrosis posited in recent years, manifests across a spectrum of maladies with profound implications for human well-being. Numerous investigations substantiate that modulating ferroptosis, whether through inhibition or augmentation, plays a pivotal role in the etiology and control of numerous age-related afflictions, encompassing neurological, circulatory, respiratory, and other disorders. This paper not only summarizes the regulatory mechanisms of ferroptosis, but also discusses the impact of ferroptosis on the biological processes of aging and its role in age-related diseases. Furthermore, it scrutinizes recent therapeutic strides in addressing aging-related conditions through the modulation of ferroptosis. The paper consolidates the existing knowledge on potential applications of ferroptosis-related pharmacotherapies and envisages the translational prospects of ferroptosis-targeted interventions in clinical paradigms.

SiCf/Ti2AlNb-reinforced Ti17 (SiCf/Ti2AlNb/Ti17) composites were fabricated through hot isostatic pressing. The designed SiCf/Ti2AlNb/Ti17 composites exhibited excellent tensile properties, with tensile strengths of 1657 MPa at room temperature and 1830 MPa at 450 °C. The microstructure, fracture morphology, and longitudinal section of the composites were characterized by X-ray diffraction, scanning electron microscopy, and electron backscatter diffraction techniques. The fracture process of SiCf/Ti2AlNb/Ti17 composites during room-temperature tensile tests was as follows: the SiCf/Ti2AlNb reaction layer first fractured, the crack extended into the Ti2AlNb matrix, the Ti2AlNb matrix crack extended to the adjacent reaction layer and promoted fiber fracture, the crack extended to the Ti2AlNb/Ti17 interface, ultimately the Ti17 capsule fractured. The fracture process of SiCf/Ti2AlNb/Ti17 composites during 450 °C tensile tests was as follows: the SiCf/Ti2AlNb reaction layer first fractured, multiple fiber fractures occurred, and the crack in the reaction layer entered the Ti2AlNb matrix, the crack extended to the Ti2AlNb/Ti17 interface, eventually the Ti17 capsule fractured. The room-temperature tensile fracture was fitted to the LLS model, while the tensile fracture at 450 °C was fitted to the GLS model. The different fracture processes indicated that the SiCf/Ti2AlNb/Ti17 composites were suitable for exploiting fiber strength at 450 °C and therefore exhibited excellent tensile strength.

Microstructure evolution during the hot isostatic pressing (HIP) of continuous silicon carbide fiber-reinforced Ti (SiCf/Ti) composites has not been investigated. In this study, SiCf/Ti60 composites were prepared via the HIP solidification method of Ti60 precursor wires. The evolution of the microstructure of the Ti60 precursor wires and SiCf/Ti60 composites was characterized using electron backscatter diffraction microscopy and transmission electron microscopy techniques. The results showed that the deformation of α-Ti was mainly accomplished by basal dislocations and prismatic dislocations slip during the HIP process. After the completion of HIP, the low-angle grain boundaries (LAGBs) were reduced to 24.6%, and the average grain size of α-Ti was increased to 7.47 μm2. Two fiber textures, //axial direction (AD) and //AD strength, were present in α-Ti, with a 38% increase in //AD strength. The phase contents of 1.0% β-Ti and 0.6% (Ti, Zr)6Si3 precipitated from different locations in the Ti60 matrix and induced changes in misorientation.

Abstract The Tetraspanins (Tspan) protein family, also known as the tetraspanin family, contains 33 family members that interact with other protein molecules such as integrins, adhesion molecules, and T cell receptors by forming dimers or heterodimers. The Tspan protein family regulates cell proliferation, cell cycle, invasion, migration, apoptosis, autophagy, tissue differentiation, and immune response. More and more studies have shown that Tspan proteins are involved in tumorigenesis, epithelial-mesenchymal transition, thrombosis, tumor stem cell, and exosome signaling. Some drugs and microRNAs can inhibit Tspan proteins, thus providing new strategies for tumor therapy. An in-depth understanding of the functions and regulatory mechanisms of the Tspan protein family, which can promote or inhibit tumor development, will provide new strategies for targeted interventions in the future.

Abstract SARS-CoV-2 has spread rapidly worldwide and infected hundreds of millions of people worldwide. With the increasing number of COVID-19 patients discharged from hospitals, the emergence of its associated complications, sequelae, has become a new global health crisis secondary to acute infection. For the time being, such complications and sequelae are collectively called “Post-acute sequelae after SARS-CoV-2 infection (PASC)”, also referred to as “long COVID” syndrome. Similar to the acute infection period of COVID-19, there is also heterogeneity in PASC. This article reviews the various long-term complications and sequelae observed in multiple organ systems caused by COVID-19, pathophysiological mechanisms, diagnosis, and treatment of PASC, aiming to raise awareness of PASC and optimize management strategies.

Abstract Background Sequence variation produced by mutation provides the ultimate source of natural selection for species adaptation. Unlike nonsynonymous mutation, synonymous mutations are generally considered to be selectively neutral but accumulating evidence suggests they also contribute to species adaptation by regulating the flow of genetic information and the development of functional traits. In this study, we analysed sequence characteristics of ATP6, a housekeeping gene from 139 Phytophthora infestans isolates, and compared the fitness components including metabolic rate, temperature sensitivity, aggressiveness, and fungicide tolerance among synonymous mutations. Results We found that the housekeeping gene exhibited low genetic variation and was represented by two major synonymous mutants at similar frequency (0.496 and 0.468, respectively). The two synonymous mutants were generated by a single nucleotide substitution but differed significantly in fitness as well as temperature-mediated spatial distribution and expression. The synonymous mutant ending in AT was more common in cold regions and was more expressed at lower experimental temperature than the synonymous mutant ending in GC and vice versa. Conclusion Our results are consistent with the argument that synonymous mutations can modulate the adaptive evolution of species including pathogens and have important implications for sustainable disease management, especially under climate change.

Abstract Background Novel therapeutic targets are urgently needed for treating drug-resistant non-small cell lung cancer (NSCLC) and overcoming drug resistance to molecular-targeted therapies. Regulator of G protein signaling 20 (RGS20) is identified as an upregulated factor in many cancers, yet its specific role and the mechanism through which RGS20 functions in NSCLC remain unclear. Our study aimed to identify the role of RGS20 in NSCLC prognosis and delineate associated cellular and molecular pathways. Methods Immunohistochemistry and lung cancer tissue microarray were used to verify the expression of RGS20 between NSCLC patients. CCK8 and cell cloning were conducted to determine the proliferation ability of H1299 and Anip973 cells in vitro. Furthermore, Transcriptome sequencing was performed to show enrichment genes and pathways. Immunofluorescence was used to detect the translocation changes of YAP to nucleus. Western blotting demonstrated different expressions of autophagy and the Hippo-PKA signal pathway. In vitro and in vivo experiments verified whether overexpression of RGS20 affect the proliferation and autophagy of NSCLC through regulating the Hippo pathway. Results The higher RGS20 expression was found to be significantly correlated with a poorer five-year survival rate. Further, RGS20 accelerated cell proliferation by increasing autophagy. Transcriptomic sequencing suggested the involvement of the Hippo signaling pathway in the action of RGS20 in NSCLC. RGS20 activation reduced YAP phosphorylation and facilitated its nuclear translocation. Remarkably, inhibiting Hippo signaling with GA-017 promoted cell proliferation and activated autophagy in RGS20 knock-down cells. However, forskolin, a GPCR activator, increased YAP phosphorylation and reversed the promoting effect of RGS20 in RGS20-overexpressing cells. Lastly, in vivo experiments further confirmed role of RGS20 in aggravating tumorigenicity, as its overexpression increased NSCLC cell proliferation. Conclusion Our findings indicate that RGS20 drives NSCLC cell proliferation by triggering autophagy via the inhibition of PKA-Hippo signaling. These insights support the role of RGS20 as a promising novel molecular marker and a target for future targeted therapies in lung cancer treatment.

ABSTRACTThe antipsychotic drug pimozide has been demonstrated to inhibit cancer. However, the precise anti-cancer mechanism of pimozide remains unclear. The purpose of this study was to investigate the effects of pimozide on human MCF-7 and MDA-MB-231 breast cancer cell lines, and the potential involvement in the RAF/ERK signaling. The effects of pimozide on cells were examined by 4,5-dimethylthiazol-2-yl-3,5-diphenylformazan, wound healing, colony formation, transwell assays, and caspase activity assay. Flow cytometry and acridine orange and ethidium bromide staining were performed to assess changes in cells. Transmission electron microscopy and monodansylcadaverine staining were used to observe autophagosomes. The cyclic adenosine monophosphate was evaluated using the FRET system. Immunohistochemistry, immunofluorescence, RNA interference, and western blot investigated the expression of proteins. Mechanistically, we focus on the RAF1/ERK signaling. We detected pimozide was docked to RAF1 by Schrodinger software. Pimozide down-regulated the phosphorylation of RAF1, ERK 1/2, Bcl-2, and Bcl-xl, up-regulated Bax, and cleaved caspase-9 to induce apoptosis. Pimozide might promote autophagy by up-regulating cAMP. The enhancement of autophagy increased the conversion of LC3-I to LC3-II and down-regulated p62 expression. But mTOR signaling was not involved in promoting autophagy. The knockdown of RAF1 expression induced autophagy and apoptosis in breast cancer cells, consistent with the results of pimozide or sorafenib alone. Blocked autophagy by chloroquine resulted in the impairment of pimozide-induced apoptosis. These data showed that pimozide inhibits breast cancer by regulating the RAF/ERK signaling pathway and might activate cAMP-induced autophagy to promote apoptosis and it may be a potential drug for breast cancer treatment.

Ovarian cancer (OCa) is a common malignancy in women, and the role of cuproptosis and its related genes in OCa is unclear. Using the GSE14407 dataset, we analyzed the expression and correlation of cuproptosis-related genes (CRGs) between tumor and normal groups. From the TCGA-OV dataset, we identified 20 cuproptosis-related long non-coding RNAs (CuLncs) associated with patient survival through univariate Cox analysis. OCa patients were divided into early-stage and late-stage groups to analyze CuLncs expression. Cluster analysis classified patients into two clusters, with Cluster1 having a poorer prognosis. Significant differences in “Lymphatic Invasion” and “Cancer status” were observed between clusters. Seven CRGs showed significant expression differences, validated using the human protein atlas (HPA) databases. Immune analysis revealed a higher ImmuneScore in Cluster1. GSEA identified associated signaling pathways. LASSO regression included 11 CuLncs to construct and validate a survival prediction model, classifying patients into high-risk and low-risk groups. Correlations between riskScore, Cluster phenotype, ImmuneScore, and immune cell infiltration were explored. Cell experiments showed that knocking down AC023644.1 decreases OCa cell viability. In conclusion, we constructed an accurate prognostic model for OCa based on 11 CuLncs, providing a basis for prognosis assessment and potential immunotherapy targets.

Ferroptosis is a novel form of cell demise characterized primarily by the reduction of trivalent iron to divalent iron, leading to the release of reactive oxygen species (ROS) and consequent induction of intense oxidative stress. In atherosclerosis (AS), highly accumulated lipids are modified by ROS to promote the formation of lipid peroxides, further amplifying cellular oxidative stress damage to influence all stages of atherosclerotic development. Macrophages are regarded as pivotal executors in the progression of AS and the handling of iron, thus targeting macrophage iron metabolism holds significant guiding implications for exploring potential therapeutic strategies against AS. In this comprehensive review, we elucidate the potential interplay among iron overload, inflammation, and lipid dysregulation, summarizing the potential mechanisms underlying the suppression of AS by alleviating iron overload. Furthermore, the application of Traditional Chinese Medicine (TCM) is increasingly widespread. Based on extant research and the pharmacological foundations of active compounds of TCM, we propose alternative therapeutic agents for AS in the context of iron overload, aiming to diversify the therapeutic avenues.

ObjectiveEphedra, widely used in clinical practice as a medicinal herb, belongs to the genus Ephedra in the family Ephedraceae. However, the presence of numerous Ephedra varieties and variants requires differentiation for accurate identification.MethodsIn this study, we employed headspace gas chromatography mass spectrometry (HS-GC-MS), ultra-high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS), and global natural products social molecular networking (GNPS) for chemical component identification. Chemometric analysis was used to analyze the differential components. Metabolic analysis and Kyoto encyclopedia of genes and genomes (KEGG) enrichment were utilized to explore the synthesis pathways of different components.ResultA total of 83 volatile and 79 non-volatile components were identified in Ephedra species. Differential analysis revealed that among the eight Ephedra stems, 18 volatile and 19 non-volatile differential compounds were discovered, whereas Ephedra roots exhibited 21 volatile and 17 non-volatile markers. Volatile compounds were enriched in four synthetic pathways, while non-volatile components were enriched in five pathways among the differentiated components.ConclusionThis study is the first to conduct a comparative analysis of chemical components in different Ephedra species and parts. It provides a foundational reference for authenticating Ephedra herbs, evaluating medicinal resources, and comparing quality in future studies.

Long-term consumption of high-GI (glycemic index) foods can increase insulin resistance and increase the risk of diabetes. The annual production of okara, which is rich in dietary fiber and regulates postprandial glycemic response, is huge. The reconstituted rice with the addition of okara was prepared using extrusion reconstitution technology. The okara decreased gelatinization and enhanced gel strength, aging of the reconstituted rice. It also promoted water migration, formed V-shaped crystals, and increased the relative crystallinity and short-range orderliness. Within a certain range of addition, okara increased the resistant-starch content of reconstituted rice. It also improves glucose adsorption capacity and hysteresis coefficient, slowing down starch digestion in vitro. The results showed that okara altered the physicochemical properties of reconstituted rice and slowed down its starch digestion in vitro.

Diabetic nephropathy (DN) is one of the most common microvascular complications in diabetic patients, with its incidence continuously increasing in recent years. DN causes renal tissue damage and functional decline, expedites the aging process of the kidneys, and may ultimately progress leading to end-stage renal disease, severely impacting the patient's quality of life and prognosis. Mesenchymal stem cells (MSCs) are highly valued for their multipotent differentiation, paracrine functions, immunomodulatory effects, and capacity for tissue repair. Particularly, exosomes (Exo) derived from MSCs (MSCs-Exo) are rich in bioactive molecules and facilitate intercellular communication, participating in various physiological and pathological processes. MSCs and MSCs-Exo, in particular, have been demonstrated to have therapeutic effects in DN treatment research by encouraging tissue repair, fibrosis inhibition, and inflammation reduction. Research has shown that MSCs and MSCs-Exo have therapeutic effects in DN treatment by promoting tissue repair, inhibiting fibrosis, and reducing inflammation. Recent studies underscore the potential of MSCs and MSCs-Exo, highlighting their broad applicability in DN treatment. This review aims to provide a comprehensive summary of the scientific developments in treating DN using MSCs and MSCs-Exo from diverse sources, while also exploring their future therapeutic possibilities in detail.

Abstract As societal aging intensifies, the incidence of osteoporosis (OP) continually rises. OP is a skeletal disorder characterized by reduced bone mass, deteriorated bone tissue microstructure, and consequently increased bone fragility and fracture susceptibility, typically evaluated using bone mineral density (BMD) and T-score. Not only does OP diminish patients’ quality of life, but it also imposes a substantial economic burden on society. Conventional pharmacological treatments yield limited efficacy and severe adverse reactions. In contemporary academic discourse, mesenchymal stem cells (MSCs) derived extracellular vesicles (EVs) have surfaced as auspicious novel therapeutic modalities for OP. EVs can convey information through the cargo they carry and have been demonstrated to be a crucial medium for intercellular communication, playing a significant role in maintaining the homeostasis of the bone microenvironment. Furthermore, various research findings provide evidence that engineered strategies can enhance the therapeutic effects of EVs in OP treatment. While numerous reviews have explored the progress and potential of EVs in treating degenerative bone diseases, research on using EVs to address OP remains in the early stages of basic experimentation. This paper reviews advancements in utilizing MSCs and their derived EVs for OP treatment. It systematically examines the most extensively researched MSC-derived EVs for treating OP, delving not only into the molecular mechanisms of EV-based OP therapy but also conducting a comparative analysis of the strengths and limitations of EVs sourced from various cell origins. Additionally, the paper emphasizes the technical and engineering strategies necessary for leveraging EVs in OP treatment, offering insights and recommendations for future research endeavors.

Abstract Multidrug resistance (MDR) is one of the main reasons affecting the efficacy of chemotherapy in breast cancer (BC). Our previous studies constructed polymer lipid hybrid nanoparticles encapsulated with Emodin (EMO) (E-PLNs) and proved that they can inhibit epithelial mesenchymal transition (EMT) and reverse MDR in BC. This study aims to explore the mechanisms by which the EMT involved in MDR and the E-PLNs exerted effects. The prepared E-PLNs were characterized by Dynamic light scattering, infrared spectroscopy, X-ray, and differential scanning calorimetry. The effects of drugs or treatments were evaluated by detecting cell viability, apoptosis, invasion, EMT markers, and MDR related proteins in vitro. The results showed that IL-6 could promote proliferation, EMT, invasion and MDR of MCF-7/ADR cells (induced from MCF-7 cells) by activating the JAK2/STAT3 signaling pathway, and these effects could be reversed by AG490 (JAK2 inhibitor) or E-PLNs combined with Doxorubicin (DOX). E-PLNs might be an effective MDR reversal agent for BC.

Abstract Background Intrahepatic cholangiocarcinoma (ICC) accounts for about 15% of primary liver cancer, and the incidence rate has been rising in recent years. Surgical resection is the best treatment for ICC, but the 5-year survival rate is less than 30%. ICC signature genes are crucial for the early diagnosis of ICC, so it is especially important to find its signature genes and therapeutic drug. Here, we studied that bufalin targeting CAMKK2 promotes mitochondrial dysfunction and inhibits the occurrence and metastasis of intrahepatic cholangiocarcinoma through Wnt/β-catenin signal pathway. Methods IC50 of bufalin in ICC cells was determined by CCK8 and invasive and migratory abilities were verified by wound healing, cell cloning, transwell and Western blot. IF and IHC verified the expression of CAMKK2 between ICC patients and normal subjects. BLI and pull-down demonstrated the binding ability of bufalin and CAMKK2. Bioinformatics predicted whether CAMKK2 was related to the Wnt/β-catenin pathway. SKL2001, an activator of β-catenin, verified whether bufalin acted through this pathway. In vitro and in vivo experiments verified whether overexpression of CAMKK2 affects the proliferative and migratory effects of ICC. Transmission electron microscopy verified mitochondrial integrity. Associated Ca2+ levels verified the biological effects of ANXA2 on ICC. Results It was found that bufalin inhibited the proliferation and migration of ICC, and CAMKK2 was highly expressed in ICC, and its high expression was positively correlated with poor prognosis.CAMKK2 is a direct target of bufalin, and is associated with the Wnt/β-catenin signaling pathway, which was dose-dependently decreased after bufalin treatment. In vitro and in vivo experiments verified that CAMKK2 overexpression promoted ICC proliferation and migration, and bufalin reversed this effect. CAMKK2 was associated with Ca2+, and changes in Ca2+ content induced changes in the protein content of ANXA2, which was dose-dependently decreasing in cytoplasmic ANXA2 and dose-dependently increasing in mitochondrial ANXA2 after bufalin treatment. In CAMKK2 overexpressing cells, ANXA2 was knocked down, and we found that reversal of CAMKK2 overexpression-induced enhancement of ICC proliferation and migration after siANXA2. Conclusions Our results suggest that bufalin targeting CAMKK2 promotes mitochondrial dysfunction and inhibits the proliferation and migration of intrahepatic cholangiocarcinoma through Wnt/β-catenin signal pathway. Thus, bufalin, as a drug, may also be used for cancer therapy in ICC in the future.

Precise traffic prediction is crucial in the domain of intelligent transportation. However, the task of accurately predicting traffic has struggled to keep pace with escalating application demands. One of the main reasons for this difficulty is the neglect of the dependence of surrounding spatial data on traffic information. In this study, we introduce a novel framework that incorporates the surrounding spatial data from the road network into the analysis of existing sensor graphs. We delve into an innovative method for traffic prediction by employing a heterogeneous graph that integrates the surrounding spatial information from the road network. The method is based on the common observation that traffic conditions are closely associated with surrounding spatial information, which can be analyzed utilizing heterogeneous graphs. Consequently, we propose a new framework, the heterogeneous attentive spatial–temporal network (HASTN). This framework constructs a heterogeneous graph that merges road networks with surrounding geographic features and employs attention mechanisms to learn traffic patterns. Our method achieves promising results on public datasets as well as a dataset we proposed. Additionally, we employ spatial information to analyze the impact of road traffic patterns on attention. This research offers a fresh perspective on addressing traffic prediction problems by integrating spatial information.

We report the case of a woman nearing 70 years old who was admitted to the hospital with a complaint of “epigastric distension for 1 month”. Her main signs and symptoms were progressive abdominal distension and occasional abdominal pain. Computed tomography suggested an abdominal mass. She had a surgical history of synovial sarcoma (SS) of the lungs. After admission, she was diagnosed with jejunal SS following a puncture biopsy and laparoscopic surgery. This disease usually occurs in the soft tissues of the limbs, and it is extremely rare for SS to originate in the jejunum. The morphologic heterogeneity of SS overlaps with other tumors and makes the diagnosis particularly difficult. Imaging studies usually lack specificity; however, measuring multiple immunohistochemical markers can greatly assist in the diagnosis and differential diagnosis of SS. This case not only enriches our understanding of SS and describes a rare site of origin, but also emphasizes the importance and challenges of achieving an accurate diagnosis. Immunohistochemical and molecular biological testing have important roles in the definitive diagnosis, highlighting the need for precise and innovative diagnostic and therapeutic approaches in SS.

Aldolase exhibits multiple functions in a variety of organisms, including fungi, unicellular algae and plants, and so on. Furthermore, different isoforms of fructose 1,6-bisphosphate aldolase (FBA) exhibit significantly different characteristics and functions. This review describes the structures, characteristics, and functions of FBAs derived from diverse organisms, including FBA II in pathogen microorganisms, as well as FBA I mainly in unicellular algae and plants. Differences between FBA and FBP aldolase-phosphatase bifunctional enzyme (FBA/P) are also discussed. Finally, we suggest several potential research questions regarding the functions of FBA in higher plants.

Abstract Objective Surgical site infection(SSI)after neurosurgical procedure can be devastating. Delayed hospital stay has been identified as a potentially modifiable driver of SSI in general surgery patients. However, the relationship between preoperative length of stay and SSI has not been quantified previously in neurosurgery. This study aimed to clarify the association. Design A Cohort study based on STROBE checklist. Method This observational study focused on cranial neurosurgery patients at a tertiary referral centers in China. Data collection from hospital information system conducted between 1 January 2016 and 31 December 2016 was used to examine the results of interest (n = 600). Logistic regression analysis explored association between preoperative length of stay and SSI, adjusting for potential confounders. Results Overall SSI prevalence was 10.8% and was significantly higher in the longer preoperative length of stay group. Besides preoperative length of stay, American Society of Anesthesiologists score, type of surgery, gross blood loss also significantly associated with SSI prevalence. Compared with 1 to 2 days, longer preoperative length of stay was associated with increased SSI prevalence after adjustment for confounders (3 to 4 days: odds ratio[OR], 0.975[95%CI, 0.417 to 2.281]; 5 to 6 days: OR, 2.830[95%CI, 1.092 to 7.332]; 7 or more days: OR, 4.039[95%CI, 1.164 to 14.015]; P for trend

Highlights The flower-like δ-MnO2 nanostructures with controlled oxygen vacancies as an extraordinary ZIBs cathode are innovatively developed. The cathode can present large capacity and high-rate zinc-ion storage. DFT analysis substantially unveils the effects of various vacancy concentrations on their electrochemical performances.

The objective of this study was to identify effective agents for the prevention and control of ginseng Sclerotinia root rot disease caused by Sclerotinia nivalis. The inhibitory effects of 16 chemical fungicides and 10 biocontrol agents (strains) on mycelial growth and sclerotium formation in S. nivalis were determined using a plate confrontation essay. The results showed that the best chemical agents for inhibiting the mycelial growth and sclerotium formation of S. nivalis were fluconazole and fludioxonil, while Bacillus amyloliquefaciens FS6 and B. subtilis (Kono) were the best biocontrol agents (strains). The results of field trials in 2022 and 2023 showed that the control effects of fluconazole and fludioxonil on ginseng Sclerotinia root rot disease were 90.60–98.16%, and those of the biocontrol agents B. amyloliquefaciens FS6 and B. subtilis (Kono) were 94.80–97.24%, respectively. Chemical agents produced abnormal and twisted mycelia, while the biocontrol agents increased mycelial branching, dilated the mycelium tip, and revealed an abnormal balloon. All of the fungicides decreased the ergosterol content, changed the cell membrane permeability, and increased the protein and nucleic acid permeability. These results suggest that these are potential agents for controlling ginseng Sclerotinia root rot disease, and their biochemical mechanisms of chemical and biocontrol of this disease were demonstrated.

Abstract Background Vascular system is affected by diseases that can seriously damage plant health by inducing browning and death of branches. This study aimed to identify and analyze the pathogenicity of Fusarium spp. isolates obtained from diseased peach branches in several peach-producing areas of China. Results We obtained and confirmed nine Fusarium isolates based on morphological and molecular characteristics. Phylogenetic relationships using a combination of rDNA-internal transcribed spacer (ITS), elongation factor (EF)-1α, and mitochondrial small subunit (mtSSU) gene sequences were analyzed. GJH-Z1, GJH-6, and GJH-1 were identified as F. avenaceum; HYR-Z3, and ZLZT-6 as F. concentricum, HH-2020-G2, and HYTZ-4 as F. solani, GG-2020-1 as F. asiaticum, SYGZ-1 as F. equiseti. Through acupuncture comparison, the pathogenicity of F. equiseti (SYGZ-1) was highest amongst nine strains. Meanwhile, F. concentricum (HYR-Z3 and ZLZT-6), and F. solaini (HYTZ-4) had a higher level of pathogenicity as revealed by impregnation. Conclusions Our study shed light on the findings that Fusarium spp. can inflict vascular bundle browning of peach plants. Our results will extend the understanding of pathogenic diseases in China’s peach industry.

Abstract Intelligent vehicles should not only be able to detect various obstacles, but also identify their categories so as to take an appropriate protection and intervention. However, the scenarios of object detection are usually complex and changeable, so how to balance the relationship between accuracy and speed is a difficult task of object detection. This paper proposes a multi-object detection algorithm using DarkNet-53 and dense convolution network (DenseNet) to further ensure maximum information flow between layers. Three 8-layer dense blocks are used to replace the last three downsampling layers in DarkNet-53 structure, so that the network can make full use of multi-layer convolution features before prediction. The loss function of coordinate prediction error in YOLOv3 is further improved to improve the detection accuracy. Extensive experiments are conducted on the public KITTI and Pascal VOC datasets, and the results demonstrate that the proposed algorithm has better robustness, and the network model is more suitable for the traffic scene in the real driving environment and has better adaptability to the objects with long distance, small size and partial occlusion.

Abstract IscU2 is a scaffold protein that is critical for the assembly of iron–sulfur (Fe–S) clusters and the functions of Fe–S-containing mitochondrial proteins. However, the role of IscU2 in tumor development remains unclear. Here, we demonstrated that IscU2 expression is much higher in human pancreatic ductal adenocarcinoma (PDAC) tissues than in adjacent normal pancreatic tissues. In PDAC cells, activated KRAS enhances the c-Myc-mediated IscU2 transcription. The upregulated IscU2 stabilizes Fe–S cluster and regulates the activity of tricarboxylic acid (TCA) cycle enzymes α-ketoglutarate (α-KG) dehydrogenase and aconitase 2, which promote α-KG catabolism through oxidative and reductive TCA cycling, respectively. In addition to promoting mitochondrial functions, activated KRAS-induced and IscU2-dependent acceleration of α-KG catabolism results in reduced α-KG levels in the cytosol and nucleus, leading to an increase in DNA 5mC due to Tet methylcytosine dioxygenase 3 (TET3) inhibition and subsequent expression of genes including DNA polymerase alpha 1 catalytic subunit for PDAC cell proliferation and tumor growth in mice. These findings underscore a critical role of IscU2 in KRAS-promoted α-KG catabolism, 5mC-dependent gene expression, and PDAC growth and highlight the instrumental and integrated regulation of mitochondrial functions and gene expression by IscU2 in PDAC cells.

Abstract Background The impact of sarcopenia on the outcome of patients with left-sided colon and rectal cancer has not been exhaustively investigated. Thus, the present study was performed to evaluate the effect of sarcopenia on the outcome of patients with left-sided colon and rectal cancer. Methods Patients with pathologically diagnosed stage I, II and III left-sided colon or rectal cancer who had undergone curative surgery between January 2008 and December 2014 were retrospectively reviewed. The psoas muscle index (PMI) identified by 3D-image analysis of computed tomographic images was the criterion used to diagnose sarcopenia. The cut-off value recommended by Hamaguchi (PMI value

Objectives: This study aimed to explore the role of inhibin subunit beta A (INHBA) in the progression of cervical cancer (CCa) and investigate its potential as a therapeutic target. Specifically, the objectives were to assess the expression levels of INHBA in CCa, examine its correlation with patient survival, and elucidate its impact on CCa cell proliferation, cell cycle regulation, migration, invasion, and in vivo tumor growth and metastasis. Methods: To achieve the objectives, we conducted a comprehensive set of experimental methods. INHBA expression in CCa was analyzed, and its association with patient survival was assessed using clinical data. In vitro experiments involved the investigation of INHBA's effects on CCa cell proliferation, cell cycle dynamics, migration, and invasion through the epithelial–mesenchymal transition (EMT) process. Additionally, in vivo experiments were performed to evaluate the influence of INHBA on CCa growth and lung metastasis. Results: The results of this study revealed upregulated expression of INHBA in CCa, with a significant association between high INHBA expression and poor patient survival. Functionally, INHBA was found to promote the proliferation of CCa cells, regulate the cell cycle, and enhance migration and invasion through the EMT process in vitro. Moreover, in vivo experiments demonstrated that INHBA facilitated the growth and lung metastasis of CCa. Conclusion: In conclusion, our findings suggest that INHBA plays a crucial role in the progression of cervical cancer. The upregulation of INHBA is associated with poor patient survival, and its involvement in promoting key aspects of cancer progression makes it a potential therapeutic target for CCa treatment. These results provide valuable insights into the molecular mechanisms underlying CCa and offer a foundation for further exploration of targeted therapeutic interventions.

Nattokinase is an alkaline serine protease secreted by natto during fermentation. Despite its good thrombolytic effect, it is intolerant to gastrointestinal conditions and is easily digested and degraded into polypeptides, oligopeptides, and amino acids. However, whether these peptides inhibit fat-digesting enzymes and other biological activities remains unknown. To explore the bioactivity of peptides produced through nattokinase degradation, nattokinase was subjected to simulated digestion in the gastrointestinal tract, and 41 small peptides were obtained through the enzymolysis of gastric enzymes, pancreases, and chymotrypsin. Four pancreatic lipase (PL) inhibitory peptides (SW, ASF, GAY, and PGGTY) were selected based on their activity scores, water solubility, and toxicity predictions. The molecular docking results revealed that hydrogen bonds and electrostatic interactions were the main forces for inhibiting PL activity. The results of enzyme activity verification revealed that all four peptides inhibited PL activity. Among them, GAY exhibited the strongest inhibitory effect, with an inhibitory rate of 10.93 % at a concentration of 1 mg/mL. Molecular dynamics simulations confirmed that the GAY–1ETH complex demonstrated good stability. Natto foods containing nattokinase own the activity of inhibiting fat-digesting enzymes and show antiobesity potentials.

Sugarcane plays a vital role in many global economies, and its efficient cultivation is critical for sustainable development. A central challenge in sugarcane yield prediction and cultivation management is the precise segmentation of sugarcane fields from satellite imagery. This task is complicated by numerous factors, including varying environmental conditions, scale variability, and spectral similarities between crops and non-crop elements. To address these segmentation challenges, we introduce DSCA-PSPNet, a novel deep learning model with a unique architecture that combines a modified ResNet34 backbone, the Pyramid Scene Parsing Network (PSPNet), and newly proposed Dynamic Squeeze-and-Excitation Context (D-scSE) blocks. Our model effectively adapts to discern the importance of both spatial and channel-wise information, providing superior feature representation for sugarcane fields. We have also created a comprehensive high-resolution satellite imagery dataset from Guangxi’s Fusui County, captured on December 17, 2017, which encompasses a broad spectrum of sugarcane field characteristics and environmental conditions. In comparative studies, DSCA-PSPNet outperforms other state-of-the-art models, achieving an Intersection over Union (IoU) of 87.58%, an accuracy of 92.34%, a precision of 93.80%, a recall of 93.21%, and an F1-Score of 92.38%. Application tests on an RTX 3090 GPU, with input image resolutions of 512 × 512, yielded a prediction time of 4.57ms, a parameter size of 22.57MB, GFLOPs of 11.41, and a memory size of 84.47MB. An ablation study emphasized the vital role of the D-scSE module in enhancing DSCA-PSPNet’s performance. Our contributions in dataset generation and model development open new avenues for tackling the complexities of sugarcane field segmentation, thus contributing to advances in precision agriculture. The source code and dataset will be available on the GitHub repository https://github.com/JulioYuan/DSCA-PSPNet/tree/main.

Globally, the incidence of diseases such as obesity, fatty liver and hyperlipidaemia has increased drastically in recent years. This study investigated the direct treatment of obesity and its associated metabolic disorders using peanut-natto in a high-fat diet (HFD)–induced mouse model of obesity. After 6 weeks of treatment, peanut-natto significantly reduced the body and abdominal fat weight of mice with obesity, decreased the fat cell area and fat droplet accumulation in the liver and improved the colon structure by regulating the levels of intestinal lipid metabolism-related proteins such as CD36 and FATP4. Compared with the untreated HFD group, peanut-natto significantly reduced the serum levels of LDL-C, TG and T-CHO. Metagenomic analysis revealed that natto can restore the abundance of gut microbiota to a certain extent and increase the Bacteroidetes-to-Firmicutes ratio. Non-targeted metabolomics analysis indicated a metabolism disorder that was obviously improved by peanut-natto treatment via the regulation of α-linolenic acid metabolism, linoleic acid metabolism, unsaturated fatty acid biosynthesis and lipid decomposition in fat cells. These results provide a scientific basis for using peanut-natto as a new food product to prevent obesity, improve metabolic disorders and balance the intestinal microbiota.

This study examined how college students in a medical school in China engaged in learning in asynchronous online learning environments during the COVID-19 health crisis. A quasi-experimental design approach was employed to compare if a class of students had better learning outcomes and developed systems thinking when asynchronous discussion forums incorporated an inquiry-based pedagogical approach in one unit, whereas the other unit followed a traditional instructor-led approach. In sum, 25 junior students participated in this study. Quantitative results show that the students had statistically significant higher assessment scores and improved systems thinking when the unit incorporated the inquiry-based pedagogical approach. Qualitative findings also demonstrated how students engaged in learning and how the instructor scaffolded students’ inquiries and learning. Practical implications for instructors’ teaching online courses are also discussed.

This paper integrates intelligent reflecting surfaces (IRS) with unmanned aerial vehicles (UAV) to enhance the transmission performance of the Internet of Vehicles (IoV) through non-orthogonal multiple access (NOMA). It focuses on strengthening the signals from cell edge vehicles (CEVs) to the base station by optimizing the wireless propagation environment via an IRS-equipped UAV. The primary goal is to maximize the sum data rate of CEVs while satisfying the constraint of the successive interference cancellation (SIC) decoding threshold. The challenge lies in the non-convex nature of jointly considering the power control, subcarrier allocation, and phase shift design, making the problem difficult to optimally solve. To address this, the problem is decomposed into two independent subproblems, which are then solved iteratively. Specifically, the optimal phase shift design is achieved using the deep deterministic policy gradient (DDPG) algorithm. Furthermore, the graph theory is applied to determine the subcarrier allocation policy and derive a closed-form solution for optimal power control. Finally, the simulation results show that the proposed joint phase shift and resource management scheme significantly enhances the sum data rate compared to the state-of-the-art schemes, thereby demonstrating the benefits of integrating the IRS-equipped UAV into NOMA-enhanced IoV.

This study focuses on constructions that are vulnerable to fire hazards during wildfire events, and these constructions are known as ‘exposures’, which are an increasingly significant area of disaster research. A key challenge lies in estimating dynamically and comprehensively the risk that individuals are exposed to during wildfire spread. Here, ‘exposure risk’ denotes the potential threat to exposed constructions from fires within a future timeframe. This paper introduces a novel method that integrates a spatiotemporal knowledge graph with wildfire spread data and an exposure risk analysis model to address this issue. This approach enables the semantic integration of varied and heterogeneous spatiotemporal data, capturing the dynamic nature of wildfire propagation for precise risk analysis. Empirical tests are employed for the study area of Xichang, Sichuan Province, using real-world data to validate the method’s efficacy in merging multiple data sources and enhancing the accuracy of exposure risk analysis. Notably, this approach also reduces the time complexity from O (m×n×p) to O (m×n).

This study attempts to reveal the intelligent recommendation mechanism of online learning resources. The “multimodal data fusion” aspect is adopted, illustrating online learning resource modeling, learning preference modeling, learning preference evolution, and referral engine smart design. Multimodal learning resources are key constituents of multidimensional intelligent recommendation services. The learner model that integrates multimodal preference data is the key to implementing smart recommendations. Learning preference evolution is a key factor in sustaining learner model robustness. The intelligent recommendation engine is the technical guarantee for developing an intelligent recommendation. Providing learning resources is an important part of online learning services, which mediate online learning processes. Intelligent recommendation, as an effective personalized servicing strategy, recommends differentiated, personalized, and precise learning resources to learners, thereby promoting the effectiveness of online learning performance. This study constructs a framework that reveals an intelligent recommendation mechanism for online learning resources.

Abstract Intelligent soft robotics and wearable electronics require flexible, wireless radio frequency (RF) pressure sensors for human‐like tactile perception of their moving parts. Existing devices face two challenges for array extension: the construction of sensitive units over a limited area and the handling of resonant peaks overlapping within the channel width. Herein, a simply adjustable RF‐resonator‐based tactile array (RFTA) is reported, in which the initial frequency of each resonator unit is regulated by doping polydimethylsiloxane (PDMS) dielectric layers with various concentrations of multiwalled carbon nanotubes (MWCNTs). An array is constructed using four sensor units with a frequency interval of 15 MHz and a multi‐layer micropyramid structure is employed to obtain a low detection limit (

BackgroundChinese college students used to eat in student canteens, making dietary consumption outside the cafeterias the main reason for the difference in sodium intake. This study aims to develop and validate a food frequency questionnaire (Sodium-FFQ) targeting dietary sodium intake outside the canteens among undergraduates in China.MethodsThis cross-sectional study included 124 and 81 college students from comprehensive universities in the development and validation stage. A 24 h dietary recall and a food frequency questionnaire were used to develop the Sodium-FFQ. Food items were selected according to the foods that contributed more to the total sodium intake. Test–retest correlation coefficients with an interval of 14 days were employed to evaluate reproducibility. Validity was assessed against a single 24 h urine collection and a 3-day dietary record using correlation coefficients, Bland–Altman analyses, and cross-classification analysis of Kappa coefficients.ResultsThe Sodium-FFQ consists of 12 groups of foods with 48 items. The Spearman correlation coefficient of test–retest on sodium intake was 0.654 (p

Magnaporthe oryzae, the pathogen responsible for rice blast disease, utilizes specialized infection structures known as appressoria to breach the leaf cuticle and establish intracellular, infectious hyphae. Our study demonstrates that the peroxin MoPex22 is crucial for appressorium function, specifically for the development of primary penetration hyphae. The ∆Mopex22 mutant exhibited slow growth, reduced aerial hyphae, and almost complete loss of virulence. Specifically, despite the mutant’s capability to form appressoria, it showed abnormalities during appressorium development, including reduced turgor, increased permeability of the appressorium wall, failure to form septin rings, and significantly decreased ability to penetrate host cells. Additionally, there was a delay in the degradation of lipid droplets during conidial germination and appressorium development. Consistent with these findings, the ΔMopex22 mutant showed an inefficient utilization of long-chain fatty acids and defects in cell wall integrity. Moreover, our findings indicate that MoPex22 acts as an anchor for MoPex4, facilitating the localization of MoPex4 to peroxisomes. Together with MoPex4, it affects the function of MoPex5, thus regulating the import of peroxisomal matrix proteins. Overall, these results highlight the essential role of MoPex22 in regulating the transport of peroxisomal matrix proteins, which affect fatty acid metabolism, glycerol accumulation, cell wall integrity, growth, appressorium development, and the pathogenicity of M. oryzae. This study provides valuable insights into the significance of peroxin functions in fungal biology and appressorium-mediated plant infection.

Metabolic product accumulation exhibited variations among mulberry (Morus alba L.) leaves (MLs) at distinct growth stages, and this assessment was conducted using a combination of analytical techniques including high-performance liquid chromatography (HPLC), gas chromatography–mass spectrometry (GC-MS), and liquid chromatography–mass spectrometry (LC-MS). Multivariate analysis was applied to the data, and the findings were correlated with antioxidant activity and α-glucosidase inhibitory effects in vitro. Statistical analyses divided the 27 batches of MLs at different growth stages into three distinct groups. In vitro assays for antioxidant activity and α-glucosidase inhibition revealed that IC50 values were highest at the Y23 stage, which corresponds to the ‘Frost Descends’ solar term. In summary, the results of this study indicate that MLs at different growth stages throughout the year can be categorized into three primary growth stages using traditional Chinese solar terms as reference points, based on the observed variations in metabolite content.

The increasing frequency and magnitude of landslides underscore the growing importance of landslide prediction in light of factors like climate change. Traditional methods, including physics-based methods and empirical methods, are beset by high costs and a reliance on expert knowledge. With the advancement of remote sensing and machine learning, data-driven methods have emerged as the mainstream in landslide prediction. Despite their strong generalization capabilities and efficiency, data-driven methods suffer from the loss of semantic information during training due to their reliance on a ‘sequence’ modeling method for landslide scenarios, which impacts their predictive accuracy. An innovative method for landslide prediction is proposed in this paper. In this paper, we propose an innovative landslide prediction method. This method designs the NADE ontology as the schema layer and constructs the data layer of the knowledge graph, utilizing tile lists, landslide inventory, and environmental data to enhance the representation of complex landslide scenarios. Furthermore, the transformation of the landslide prediction task into a link prediction task is carried out, and a knowledge graph embedding model is trained to achieve landslide predictions. Experimental results demonstrate that the method improves the F1 score by 5% in scenarios with complete datasets and 17% in scenarios with sparse datasets compared to data-driven methods. Additionally, the application of the knowledge graph embedding model is utilized to generate susceptibility maps, and an analysis of the effectiveness of entity embeddings is conducted, highlighting the potential of knowledge graph embeddings in disaster management.

Abstract Background Amino acid property-aware phylogenetic analysis (APPA) refers to the phylogenetic analysis method based on amino acid property encoding, which is used for understanding and inferring evolutionary relationships between species from the molecular perspective. Fast Fourier transform (FFT) and Higuchi’s fractal dimension (HFD) have excellent performance in describing sequences’ structural and complexity information for APPA. However, with the exponential growth of protein sequence data, it is very important to develop a reliable APPA method for protein sequence analysis. Results Consequently, we propose a new method named FFP, it joints FFT and HFD. Firstly, FFP is used to encode protein sequences on the basis of the important physicochemical properties of amino acids, the dissociation constant, which determines acidity and basicity of protein molecules. Secondly, FFT and HFD are used to generate the feature vectors of encoded sequences, whereafter, the distance matrix is calculated from the cosine function, which describes the degree of similarity between species. The smaller the distance between them, the more similar they are. Finally, the phylogenetic tree is constructed. When FFP is tested for phylogenetic analysis on four groups of protein sequences, the results are obviously better than other comparisons, with the highest accuracy up to more than 97%. Conclusion FFP has higher accuracy in APPA and multi-sequence alignment. It also can measure the protein sequence similarity effectively. And it is hoped to play a role in APPA’s related research.

Abstract Since December 2019, the coronavirus (COVID-19) pandemic has imposed huge burdens to the whole world, seriously affecting global economic growth, and threatening people’s lives and health. At present, some therapeutic regimens are available for treatment of COVID-19 pneumonia, including antiviral therapy, immunity therapy, anticoagulant therapy, and others. Among them, injection of mesenchymal stem cells (MSCs) is currently a promising therapy. The preclinical studies and clinical trials using MSCs and small extracellular vesicles derived from MSCs (MSC-sEVs) in treating COVID-19 were summarized. Then, the molecular mechanism, feasibility, and safety of treating COVID-19 with MSCs and MSC-sEVs were also discussed.

Abstract. Background:. The risk for chronic kidney disease (CKD) is influenced by genetic predisposition, sex, and lifestyle. Previous research indicates that coffee is a potentially protective factor in CKD. The current study aims to investigate whether sex disparity exists in the coffee–CKD association, and whether genetic risk of CKD or genetic polymorphisms of caffeine metabolism affect this association. Methods:. A total of 359,906 participants from the UK Biobank who were enrolled between 2006 and 2010 were included in this prospective cohort study, which aimed to estimate the hazard ratios for coffee intake and incident CKD using a Cox proportional hazard model. Allele scores of CKD and caffeine metabolism were additionally adjusted for in a subsample with qualified genetic data (n = 255,343). Analyses stratified by genetic predisposition, comorbidities, and sex hormones were performed. Tests based on Bayesian model averaging were conducted to ascertain the robustness of the results. Results:. Coffee was inversely associated with CKD in a dose-dependent manner. The effects of coffee did not differ across different strata of genetic risk for CKD, but were more evident among slower genetically predicted caffeine metabolizers. Significant sex disparity was observed (P value for interaction = 0.013), in that coffee drinking was only associated with the risk reduction of CKD in females. Subgroup analysis revealed that testosterone and sex hormone-binding globulin (SHBG), but not estradiol, modified the coffee–CKD association. Conclusions:. In addition to the overall inverse coffee–CKD association that was observed in the general population, we could also establish that a sex disparity existed, in that females were more likely to experience the benefit of the association. Testosterone and SHBG may partly account for the sex disparity.