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Accurate estimation of crown fire potential (CFP) can improve guidance on crown fire control and management. However, robust simulations of crown fire behavior are still challenging, limiting the accuracy of regional-scale CFP mapping. This study aims to incorporate fire spread simulation and machine learning algorithms to improve CFP mapping at a regional scale. First, we built a crown fire dataset using the fire simulations from the FARSITE model, as well as multi-source data, including fuel, weather, and topography variables. Fuel model parameters were optimized with four metaheuristic algorithms for robust fire simulations. Then, the hybrid models of CFP estimation (TBA-ML) were established by coupling with the transfer AdaBoost (TrAdaBoost) algorithm and three machine learning (ML) algorithms, i.e., Bayesian Network (BN), Random Forest (RF), and Support Vector Machine (SVM), to estimate CFP for crown fire danger assessment spatially. Results showed that the TBA-BN model performed best in estimating CFP with higher accuracy (AUC>0.9 and F1 score > 0.8) than the RF- and SVM-based CFP models. The variable importance and causal analysis showed that fuel and topography variables have major contributions to crown fire occurrence. Finally, we mapped monthly average passive and active CFP at regional scales and qualitatively demonstrated that our CFP time-series products successfully captured the dynamic change of crown fire danger. The above results suggest the potential of integrating fire spread simulation and machine learning algorithms to accurately estimate CFP to improve crown fire management.

Objectives To estimate the association between the transition to daylight saving time and the risks of all cause and cause specific mortality in the US.Design Nationwide time series observational study based on weekly data.Setting US state level mortality data from the National Center for Health Statistics, with death counts from 50 US states and the District of Columbia, from the start of 2015 to the end of 2019.Population 13 912 837 reported deaths in the US.Main outcome measures Weekly counts of mortality for any cause, and for Alzheimer's disease, dementia, circulatory diseases, malignant neoplasms, and respiratory diseases.Results During the study period, 13 912 837 deaths were reported. The analysis found no evidence of an association between the transition to spring daylight saving time (when clocks are set forward by one hour on the second Sunday of March) and the risk of all cause mortality during the first eight weeks after the transition (rate ratio 1.003, 95% confidence interval 0.987 to 1.020). Autumn daylight saving time is defined in this study as the time when the clocks are set back by one hour (ie, return to standard time) on the first Sunday of November. Evidence indicating a substantial decrease in the risk of all cause mortality during the first eight weeks after the transition to autumn daylight saving time (0.974, 0.958 to 0.990). Overall, when considering the transition to both spring and autumn daylight saving time, no evidence of any effect of daylight saving time on all cause mortality was found (0.988, 0.972 to 1.005). These patterns of changes in mortality rates associated with transition to daylight saving time were consistent for Alzheimer's disease, dementia, circulatory diseases, malignant neoplasms, and respiratory diseases. The protective effect of the transition to autumn daylight saving time on the risk of mortality was more pronounced in elderly people aged ≥75 years, in the non-Hispanic white population, and in those residing in the eastern time zone.Conclusions In this study, transition to daylight saving time was found to affect mortality patterns in the US, but an association with additional deaths overall was not found. These findings might inform the ongoing debate on the policy of shifting daylight saving time.

Integrin β4 (ITGB4) is a transmembrane protein that functions as a mechanosensor, mediating the bidirectional exchange of information between the intracellular and extracellular matrices. ITGB4 plays a critical role in cell adhesion, migration, and signaling. Numerous studies have implicated ITGB4 as a key facilitator of tumor migration and invasion. This review provides a foundational description of the mechanisms by which ITGB4 regulates tumor migration and invasion through pathways involving focal adhesion kinase (FAK), protein kinase B (AKT), and matrix metalloproteinases (MMPs). These mechanisms encompass epithelial-mesenchymal transition (EMT), phosphorylation, and methylation of associated molecules. Additionally, this review explores the role of ITGB4 in the migration and invasion of prevalent clinical tumors, including those of the digestive system, breast, and prostate.

A novel thermal integration approach is introduced for a biomass-driven gas turbine power plant that generates electricity, coolant, and liquefied hydrogen. The designed scheme encompassed an organic flash cycle, a bi-evaporator ejector refrigeration unit, a high-temperature water electrolyzer for hydrogen production, a multi-effect desalination cycle for supplying water for electrolysis process, and a Claude cycle for hydrogen gas liquefaction. The designed system's importance comes back to using biomass feedstock as the input fuel and utilizing the hydrogen liquefaction method. In addition to the possibility of deploying the system in remote areas, it provides the opportunity for hydrogen storage in a smaller volume for more accessible storage and transportation. On the other hand, using a comparative method for selecting an environmentally friendly fluid for the heat recovery subsystem is another crucial aspect of the present study from the environmental aspect. It is found that R161 is the appropriate choice among the seven studied working fluids. Subsequently, a comprehensive evaluation of the entire system's thermodynamic and environmental aspects is performed using an intelligent process. By considering energy and exergy efficiencies along with CO2 emissions as the objective functions, a thorough sensitivity analysis and a triple-objective optimization are carried out. Hence, artificial neural networks for the objectives are developed and integrated into the NSGA-II optimization method. Employing LINMAP decision-making, the values of objective are attained, exhibiting 39.6 % for energy efficiency, 36.1 % for exergy efficiency, and 631.7 kg/MWh for CO2 emissions. Considering the optimum solution, the proposed system is capable of producing electricity, cooling, and liquefied hydrogen with capacities of 4526 kW, 1875 kW, and 21.22 m3/day, respectively. Additionally, the scenario yields an exergoenvironmental index of 0.579 and an exergetic stability index of 0.61. and a liquefied hydrogen generation rate of 21.22 m3/day.

Abstract Chorus waves are intense electromagnetic emissions critical in modulating electron dynamics. In this study, we perform two‐dimensional particle‐in‐cell simulations to investigate self‐consistent wave‐particle interactions with oblique chorus waves. We first analyze the electron dynamics sampled from cyclotron and Landau resonances with waves, and then quantify the advection and diffusion coefficients through statistical studies. It is found that phase‐trapped cyclotron resonant electrons satisfy the second‐order resonance condition and gain energy from waves. While phase‐bunched cyclotron resonant electrons cannot remain in resonance for long periods. They transfer energy to waves and are scattered to smaller pitch angles. Landau resonant electrons are primarily energized by waves. For both types of resonances, advection coefficients are greater than diffusion coefficients when the wave amplitude is large. Our study highlights the important role of advection in electron dynamics modulation resulting from nonlinear wave‐particle interactions.

The E3 enzyme in the UPS pathway is a crucial factor for inhibiting substrate specificity. In Solanaceae, the U-box E3 ubiquitin ligase has a complex relationship with plant growth and development, and plays a pivotal role in responding to various biotic and abiotic stresses. The analysis of the U-box gene family in Solanaceae and its expression profile under different stresses holds significant implications. A total of 116 tobacco NtU-boxs and 56 eggplant SmU-boxs were identified based on their respective genome sequences. Phylogenetic analysis of U-box genes in tobacco, eggplant, tomato, Arabidopsis, pepper, and potato revealed five distinct subgroups (I-V). Gene structure and protein motifs analysis found a high degree of conservation in both exon/intron organization and protein motifs among tobacco and eggplant U-box genes especially the members within the same subfamily. A total of 15 pairs of segmental duplication and 1 gene pair of tandem duplication were identified in tobacco based on the analysis of gene duplication events, while 10 pairs of segmental duplication in eggplant. It is speculated that segmental duplication events are the primary driver for the expansion of the U-box gene family in both tobacco and eggplant. The promoters of NtU-box and SmU-box genes contained cis-regulatory elements associated with cellular development, phytohormones, environment stress, and photoresponsive elements. Transcriptomic data analysis shows that the expression levels of the tobacco and eggplant U-box genes in different tissues and various abiotic stress conditions. Using cultivar Hongda of tobacco and cultivar Yanzhi of eggplant as materials, qRT-PCR analysis has revealed that 15 selected NtU-box genes and 8 SmU-box may play important roles in response to pathogen Ras invasion both in tobacco and eggplant.

Abstract Extracellular vesicles (EVs) are emerging as promising carriers for the delivery of therapeutic biologics. Genetic engineering represents a robust strategy for loading proteins of interest into EVs. Identification of EV‐enriched proteins facilitates protein cargo loading efficiency. Many EV‐enriched proteins are sorted into EVs via an endosomal sorting complex required for transport (ESCRT)‐dependent pathway. In parallel, viruses hijack this EV biosynthesis machinery via conserved late domain motifs to promote egress from host cells. Inspired by the similarity of biogenesis between EVs and viruses, we developed a synthetic, Late domain‐based EV scaffold protein that enables the display of a set of single chain variable fragments (scFvs) on the EV surface. We named this scaffold the Late domain‐based exosomal antibody surface display platform (LEAP). We applied the LEAP scaffold to reprogramme HEK293T cell‐derived EVs to elicit T‐cell anti‐tumor immunity by simultaneously displaying αPD‐L1 and αCD3 scFvs on the EV surface (denoted as αPD‐L1×αCD3 bispecific T‐cell engaging exosomes, BiTExos). We demonstrated that αPD‐L1×αCD3 BiTExos actively redirected T cells to bind to PD‐L1+ tumor cells, promoting T‐cell activation, proliferation and tumoricidal cytokine production. Furthermore, the αPD‐L1×αCD3 BiTExos promoted T‐cell infiltration into the tumor microenvironment to mitigate the tumor burden in vivo. Our study suggested that the LEAP scaffold may serve as a platform for EV surface display and could be applied for a broad range of EV‐based biomedical applications.

Abstract Background Airborne pollen is a crucial risk factor in allergic rhinitis (AR). The severity of AR symptoms can vary based on pollen type and concentration. This study aimed to estimate the association between exposure to different pollen types and AR risk. Methods We obtained data from patients admitted to the Beijing Tongren Hospital for AR, and data on pollen concentration, meteorological factors, and fine particulate matter (PM2.5) from 13 districts in Beijing from 2016 to 2019. We used a time‐stratified case‐crossover study design and calculated odds ratios (ORs) related to the risk of AR associated with a 10 grain/1000 mm2 increase in total pollen concentrations for specific pollen types. A stratified analysis was conducted to assess whether the associations were varied by age and sex. Results The OR of AR associated with a 10 grain/1000 mm2 increase in the 7‐day average pollen concentration was 1.014 (95% CI: 1.014, 1.015), 1.076 (95% CI: 1.070, 1.082), 1.024 (95% CI: 1.023, 1.025), 1.042 (95% CI: 1.039, 1.045), 1.142 (95% CI: 1.137, 1.147), 1.092 (95% CI: 1.088, 1.097), 1.046 (95% CI: 1.035, 1.058), and 1.026 (95% CI: 1.024, 1.028) for total pollen, Ulmus, Cupressaceae, Populus, Fraxinus, Pinus, Betula, and Artemisia, respectively. Both tree pollen (Ulmus, Cupressaceae, Populus, Fraxinus, Betula, and Pinus) and weed pollen (Artemisia, Chenopodium, and Humulus) were correlated with an increased risk of AR. These associations remained consistent across distinct subgroups defined by both age and sex. Conclusion Exposure to pollen from trees and weeds might be associated with an increased risk of AR. This research provides valuable scientific support for both clinical practitioners and patients with AR regarding the hazards of pollen exposure.

BackgroundPeroxisome proliferator-activated receptor (PPAR) agonists are recognised as a promising treatment for primary biliary cholangitis (PBC). However, the effects and safety of these agonists on PBC remain unexplored. Our study aimed to investigate the efficacy and safety of PPAR agonists in treating PBC.MethodsWe searched Cochrane Library, and Web of Science, PubMed, and Embase databases from inception to 15 March 2024 for randomised controlled studies (RCTs) that enrolled individuals with PBC treated with PPAR agonists compared with placebo. The primary outcomes were biochemical response and normalization of the alkaline phosphatase (ALP) level.ResultsEight RCTs involving 869 participants in total were included. The meta-analysis revealed that compared to placebo, PPAR agonists increased the rate of biochemical response (RR: 5.53; 95% CI: 3.79, 8.06) and normalization of the ALP level (RR: 17.18; 95% CI: 5.61, 52.61). In addition, PPAR agonists can also reduce alanine aminotransferase (ALT) (MD: −12.69 U/L; 95% CI: −18.03, −7.35), aspartate aminotransferase (AST) (MD: −4.18 U/L; 95% CI: −7.28, −1.08), ALP (MD: −142.95 U/L; 95% CI: −167.29, −118.60), γ-glutamyltransferase (GGT) (MD: −63.03 U/L; 95% CI: −92.08, −33.98), and total cholesterol (TC) levels (SMD: −0.71; 95% CI: −1.38, −0.04), and there was no significant difference in overall adverse reactions (RR: 0.99; 95% CI: 0.92, 1.05), serious adverse reactions (RR: 1.10; 95% CI: 0.70, 1.72) between the two groups.ConclusionPPAR agonists are safe and well-tolerated in patients with PBC and are effective in improving the rate of biochemical response and related biomarkers.

Summary: The ongoing emergence of SARS-CoV-2 variants poses challenges to the immunity induced by infections and vaccination. We conduct a 6-month longitudinal evaluation of antibody binding and neutralization of sera from individuals with six different combinations of vaccination and infection against BA.5, XBB.1.5, EG.5.1, and BA.2.86. We find that most individuals produce spike-binding IgG or neutralizing antibodies against BA.5, XBB.1.5, EG.5.1, and BA.2.86 2 months after infection or vaccination. However, compared to ancestral strain and BA.5 variant, XBB.1.5, EG.5.1, and BA.2.86 exhibit comparable but significant immune evasion. The spike-binding IgG and neutralizing antibody titers decrease in individuals without additional antigen exposure, and

Cadmium, as a typical heavy metal, has the potential to induce soil pollution and threaten human health through the soil-plant-human pathway. The conventional evaluation method based on the total content in soil cannot accurately represent the content migrated from the food chain to plants and the human body. Previous studies focused on the process of plant enrichment of heavy metals in soil, and very few studies directly predicted human exposure or risk through the labile state of Cd in soil. Hence, a relatively accurate and convenient prediction model of Cd release and translocation in the soil-rice-human system was developed. This model utilizes available Cd and soil parameters to predict the bioavailability of Cd in soil, as well as the in vitro bioaccessibility of Cd in cooked rice. The bioavailability of Cd was determined by the Diffusive Gradients in Thin-films technology and BCR sequential extraction procedure, offering in-situ quantification, which presents a significant advantage over traditional monitoring methods and aligns closely with the actual uptake of heavy metals by plants. The experimental results show that the prediction model based on the concentration of heavy metal forms measured by BCR sequential extraction procedure and diffusive gradients in thin-films technique can accurately predict the Cd uptake in rice grains, gastric and gastrointestinal phase (R2=0.712, 0.600 and 0.629). This model accurately predicts Cd bioavailability and bioaccessibility across the soil-rice-human pathway, informing actual human Cd intake, offering scientific support for developing more effective risk assessment methods.

The electrochemical production of hydrogen peroxide (H2O2) by the two-electron oxygen reduction (2e−-ORR) process has the advantages of high safety, low energy consumption, and environmental friendliness. For 2e−-ORR, the catalyst/electrode is the key component as it strongly affects catalytic performance and cost. Carbon materials have the advantages of high electronic conductivity, good structural stability, easy control of nanostructures, and low cost. Therefore, it has been regarded as a promising catalyst/electrode material for the electrosynthesis of H2O2 via 2e−-ORR. In addition, studies have also considered the optimization of the liquid/gas interface by tuning the electrode surface, electrolyte pH, and reactor configurations for further improving the activity and selectivity of catalysts. In this review, we provide an in-depth discussion of the recent research on the carbon-based electrocatalysts for 2e−-ORR, especially in terms of microenvironment tuning, catalyst/electrode interface engineering, and reactor design for achieving stable and efficient production of H2O2. The challenges that we are still facing and the future development prospects will then be concluded, which we believe should help the future development in this field.

Background: Metabolic imbalance is the common basis of many diseases. As natural isoquinoline alkaloid, berberine (BBR) has shown great promise in regulating glucose and lipids metabolism and treating metabolic disorders. However, the related mechanism still lacks systematic research.Aim: To discuss the role of BBR in the whole body’s systemic metabolic regulation and further explore its therapeutic potential and targets.Method: Based on animal and cell experiments, the mechanism of BBR regulating systemic metabolic processes is reviewed. Potential metabolism-related targets were summarized using Therapeutic Target Database (TTD), DrugBank, GeneCards, and cutting-edge literature. Molecular modeling was applied to explore BBR binding to the potential targets.Results: BBR regulates the whole-body metabolic response including digestive, circulatory, immune, endocrine, and motor systems through adenosine 5’-monophosphate (AMP)-activated protein kinase (AMPK)/mammalian target of rapamycin (mTOR), sirtuin (SIRT)1/forkhead box O (FOXO)1/sterol regulatory element-binding protein (SREBP)2, nuclear factor erythroid 2-related factor (Nrf) 2/heme oxygenase (HO)-1, and other signaling pathways. Through these reactions, BBR exerts hypoglycemic, lipid-regulating, anti-inflammatory, anti-oxidation, and immune regulation. Molecular docking results showed that BBR could regulate metabolism targeting FOXO3, Nrf2, NAD(P)H quinone oxidoreductase 1 (NQO1), glutathione peroxidase (Gpx) 4 and phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA). Evaluating the target clinical effects, we found that BBR has the therapeutic potential of anti-aging, anti-cancer, relieving kidney disease, regulating the nervous system, and alleviating other chronic diseases.Conclusion: This review elucidates the interaction between potential targets and small molecular metabolites by exploring the mechanism of BBR regulating metabolism. That will help pharmacologists to identify new promising metabolites interacting with these targets.

Abstract Chorus subpackets are the wave packets with modulated amplitudes in chorus waves, commonly observed in the magnetospheres of Earth and other planets. Nonlinear wave‐particle interactions have been suggested to play an important role in subpacket formation, yet the corresponding electron dynamics remain not fully understood. In this study, we have investigated the electron trapping through cyclotron resonance with subpackets, using a self‐consistent general curvilinear plasma simulation code simulation model in dipole fields. The electron trapping period has been quantified separately through electron dynamic analysis and theoretical derivation. Both methods indicate that the electron trapping period is shorter than the subpacket period/duration. We have further established the relation between electron trapping period and subpacket period through statistical analysis using simulation and observational data. Our study demonstrates that the nonlinear electron trapping through cyclotron resonance is the dominant mechanism responsible for subpacket formation.

Summary: Scent marking sites served as a primary means of chemical communication for giant pandas, enabling intraspecific communication. We integrated metabolomics and high-throughput sequencing techniques to examine the non-targeted metabolome and microbial community structure of scent marking sites and feces in the field. Integrative analysis revealed a more comprehensive array of chemical compounds compared to previous investigations, including ketones, acids, heterocycles, alcohols, and aldehydes. Notably, specific compounds such as 2-decenal, (E)-, octanal, decanal, L-α-terpineol, vanillin, and nonanal emerged as potential key players in scent signaling. Intriguingly, our study of the microbial domain identified dominant bacterial species from the Actinobacteria, Bacteroidetes, and Proteobacteria phyla, likely orchestrating metabolic processes at scent marking sites. Comparative analyses showed, for the first time, that feces do not share the same functions as scent markers, indicating distinct functional roles. This research deepens scientific understanding of chemical communication in wild pandas.

BackgroundsThe prevalence of cyberbullying has brought about many adverse effects on adolescents’ mental health. Although current studies have shown that perceived chronic social adversity (PCSA) is closely related to cyberbullying perpetration among adolescents, the underlying mechanism of the relationship between the two remains relatively unclear. This study investigated the association of PCSA, rumination, mindfulness, and cyberbullying perpetration among adolescents, building upon the general strain theory, the general aggressive model, and the limited resource of self-control theory.MethodsA sample of 477 Chinese high school students (Mage = 15.84 years, SDage = 0.67, 49.69% female) completed the Perceived Chronic Social Adversity Questionnaire, the Ruminative Responses Scale, the Child and Adolescent Mindfulness Measure, and the cyberbullying subscale of the Revised Cyber Bullying Inventory. The current study constructed a moderated mediation model to examine the relationship between PCSA and cyberbullying perpetration among adolescents and assessed the mediating role of rumination and the moderating role of mindfulness.ResultsThe results revealed a significant positive correlation between PCSA and cyberbullying perpetration. Rumination mediated the relationship between PCSA and cyberbullying perpetration, whereas mindfulness moderated the latter half of the mediation pathway. Specifically, compared to adolescents with higher mindfulness, the association between rumination and cyberbullying perpetration is greater for adolescents with lower mindfulness.ConclusionThe results further deepen our understanding of the mechanisms linking subjective perception of negative life events and cyberbullying perpetration among adolescents from the interaction of multiple factors, thus providing a basis for future interventions to encourage adolescents to properly cope with social adversity and promote positive mental health to reduce the risk of cyberbullying.

Objective: The goal of the research is to investigate the link between serum potassium levels and death after 28 days in sepsis patients, utilizing an extensive sample of patients from the multi-center Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Current research on serum potassium levels and 28-day mortality in sepsis patients is questionable. This study adds to the growing body of evidence linking serum potassium levels to the 28-day possibility of death in patients with sepsis. Methods: We collected 349,08 patients with sepsis from the retrospective cohort MIMIC-IV database, using serum potassium level on the first day of admission to the intensive care unit as the exposure variable and mortality at 28 days as the outcome variable. And controlled for confounding characteristics including gender, age, ethnicity, and vital signs during admission. Results: Serum potassium has a U-shaped connection with 28-day mortality in patients suffering from sepsis. The turning point was 4.10 mmol/L (95 % confidence interval: 4.03 to 4.22). Serum potassium and 28-day mortality were negatively linked on the inflection point’s left side (OR: 0.72; 95 % CI: 0.63 to 0.83, P

Small interference RNA (siRNA) is a class of short double-stranded RNA molecules that cause mRNA degradation through an RNA interference mechanism and is a promising therapeutic modality. RBD1016 is a siRNA drug in clinical development for the treatment of chronic Hepatitis B Virus (HBV) infection, which contains a conjugated with N-acetylglucosamine moiety that can facilitate its hepatic delivery. We aimed to construct a semi-mechanistic model of RBD1016 in pre-clinical animals, to elucidate the pharmacokinetic/pharmacodynamic (PK/PD) profiles in mice and PK profiles in monkeys, which can lay the foundation for potential future translation of RBD1016 PK and PD from the pre-clinical stage to the clinic stage. The proposed semi-mechanistic PK/PD model fitted PK and PD data in HBV transgenic mice well and described plasma and liver concentrations in the monkeys well. The simulation results showed that our model has a reasonable predictive ability for Hepatitis B surface antigen (HBsAg) levels after multiple dosing in mice. Further PK and PD data for RBD1016, including clinical data, will assist in refining the model presented here. Our current effort focused on model building for RBD1016, we anticipate that the model could apply to other GalNAc-siRNA drugs.

Summary: Single-cell RNA sequencing (scRNA-seq) has advanced our understanding of cellular heterogeneity by characterizing cell types across tissues and species. While several mouse retinal scRNA-seq datasets exist, each dataset is either limited in cell numbers or focused on specific cell classes, thereby hindering comprehensive gene expression analysis across all retina types. To fill the gap, we generated the largest retinal scRNA-seq dataset to date, comprising approximately 190,000 single cells from C57BL/6J mouse retinas, enriched for rare population cells via antibody-based magnetic cell sorting. Integrating this dataset with public datasets, we constructed the Mouse Retina Cell Atlas (MRCA) for wild-type mice, encompassing over 330,000 cells, characterizing 12 major classes and 138 cell types. The MRCA consolidates existing knowledge, identifies new cell types, and is publicly accessible via CELLxGENE, UCSC Cell Browser, and the Broad Single Cell Portal, providing a user-friendly resource for the mouse retina research community.

The milk proteins from samples of 13 different animals were identified utilizing 4D-Label-Free proteomics technology, leading to the identification of a substantial number of proteins. Among the various samples, Chinese people (CHP) milk proteins exhibited the highest count, with 1149 distinct proteins. Simultaneously, we identified common proteins present in these animal milk. It's notable presence in goat milk contributes to enhancing infant infection resistance, showcasing the beneficial role of lactoperoxidase. Galectin-3 binding protein (Gal-3BP) and tetraspanin in human milk are significantly higher than those in other animals, which determine the prominent antiviral effect of human milk and the important processes related to cell transduction. Furthermore, human milk, camel milk, goat milk and sheep milk proved to be rich sources of milk fat globule membrane (MFGM) proteins. The insights obtained from this study can serve as a foundational framework for exploring the role of different animal milk proteins in disease treatment and the composition of infant formula.

Enzymes, as highly efficient biocatalysts, excel in catalyzing diverse reactions with exceptional activity and selective properties under mild conditions. Nonetheless, their broad applications are hindered by their inherent fragility, including low thermal stability, limited pH tolerance, and sensitivity to organic solvents and denaturants. Encapsulating enzymes within metal–organic frameworks (MOFs) can protect them from denaturation in these harsh environments. However, this often leads to a compromised enzyme activity. In recent years, extensive research efforts have been dedicated to enhancing enzymatic activity within MOFs, leading to the development of new enzyme–MOF composites that not only preserve their catalytic potential but also outperform their free counterparts. This Review provides a comprehensive review on recent developments in enzyme–MOF composites with a specific emphasis on their enhanced enzymatic activity compared to free enzymes.

Abstract Currently deep neural networks have been used to perform the tongue constitution recognition, but they are still challenged, failing to extract nice multi-scale and multi-level features. This paper proposes a novel interpretable tongue constitution recognition method based on the reshaped wavelet attention. It separates multi-scale features through discrete wavelet transform and then uses the attention mechanism to weight them. Subsequently, these features are reshaped to the high-dimensional space where the association knowledge of multi-level features are mined and hierarchized so as to fuse them efficiently. Finally, both are integrated into the framework of convolution neural network to generate the more accurate tongue image attributes, by which the tongue constitution recognition is performed. The proposed method not only obtains the higher performance with small cost, but also nicely interprets them. Experimental results show that the proposed method is effective, efficient, and interpretable.

Abstract Background As a key enzyme in ceramide synthesis, longevity assurance homologue 2 (LASS2) has been indicated to act as a tumour suppressor in a variety of cancers. Ferroptosis is involved in a variety of tumour processes; however, the role of LASS2 in regulating ferroptosis has yet to be explored. This article explores the potential underlying mechanisms involved. Methods Bioinformatics tools and immunohistochemical staining were used to evaluate LASS2 expression, and the results were analysed in relation to overall survival and clinical association in multiple cancers. Coimmunoprecipitation-coupled liquid chromatography-mass spectrometry (co-IP LC-MS) was performed to identify potential LASS2-interacting proteins in thyroid, breast, and liver cancer cell lines. Transcriptomics, proteomics and metabolomics analyses of multiple cancer cell types were performed using MS or LC–MS to further explore the underlying mechanisms involved. Among these tumour cells, the common LASS2 interaction partner transferrin receptor (TFRC) was analysed by protein–protein docking and validated by coimmunoprecipitation western blot, immunofluorescence, and proximity ligation assays. Then, we performed experiments in which tumour cells were treated with Fer-1 or erastin or left untreated, with or without inducing LASS2 overexpression, and assessed the molecular biological and cellular functions by corresponding analyses. Results Low LASS2 expression is correlated with adverse clinical characteristic and poor prognosis in patients with thyroid cancer, breast cancer or HCC. Multiomics analyses revealed significant changes in the ferroptosis signalling pathway, iron ion transport and iron homeostasis. Our in vitro experiments revealed that LASS2 overexpression regulated ferroptosis status in these tumour cells by affecting iron homeostasis, which in turn inhibited tumour migration, invasion and EMT. In addition, LASS2 overexpression reversed the changes in tumour cell metastasis induced by either Fer-1 or erastin. Mechanistically, LASS2 interacts directly with TFRC to regulate iron homeostasis in these tumour cells. Conclusions In summary, our study reveals for the first time that LASS2 can inhibit tumour cell metastasis by interacting with TFRC to regulate iron metabolism and influence ferroptosis status in thyroid, breast, and liver cancer cells, these results suggest potential universal therapeutic targets for the treatment of these cancers.

Abstract Background IgA nephropathy (IgAN) is one of the most common primary glomerulonephritis, which is a significant cause of renal failure. At present, the classification of IgAN is often limited to pathology, and its molecular mechanism has not been established. Therefore we aim to identify subtypes of IgAN at the molecular level and explore the heterogeneity of subtypes in terms of immune cell infiltration, functional level. Methods Two microarray datasets (GSE116626 and GSE115857) were downloaded from GEO. Differential expression genes (DEGs) for IgAN were screened with limma. Three unsupervised clustering algorithms (hclust, PAM, and ConsensusClusterPlus) were combined to develop a single-sample subtype random forest classifier (SSRC). Functional subtypes of IgAN were defined based on functional analysis and current IgAN findings. Then the correlation between IgAN subtypes and clinical features such as eGFR and proteinuria was evaluated by using Pearson method. Subsequently, subtype heterogeneity was verified by subtype-specific modules identification based on weighted gene co-expression network analysis(WGCNA) and immune cell infiltration analysis based on CIBERSORT algorithm. Results We identified 102 DEGs as marker genes for IgAN and three functional subtypes namely: viral-hormonal, bacterial-immune and mixed type. We screened seventeen genes specific to viral hormonal type (ATF3, JUN and FOS etc.), and seven genes specific to bacterial immune type (LIF, C19orf51 and SLPI etc.). The subtype-specific genes showed significantly high correlation with proteinuria and eGFR. The WGCNA modules were in keeping with functions of the IgAN subtypes where the MEcyan module was specific to the viral-hormonal type and the MElightgreen module was specific to the bacterial-immune type. The results of immune cell infiltration revealed subtype-specific cell heterogeneity which included significant differences in T follicular helper cells, resting NK cells between viral-hormone type and control group; significant differences in eosinophils, monocytes, macrophages, mast cells and other cells between bacterial-immune type and control. Conclusion In this study, we identified three functional subtypes of IgAN for the first time and specific expressed genes for each subtype. Then we constructed a subtype classifier and classify IgAN patients into specific subtypes, which may be benefit for the precise treatment of IgAN patients in future.

To overcome the effect of grid mismatch on the superresolution performance, a sparse Bayesian learning-based multichannel radar forward-looking superresolution imaging scheme is proposed in this article. In the scheme, a coarse imaging grid is initialized first, and local grid refinement is performed based on the preliminary estimation results of the target information. Then, based on the refined grid, an off-grid superresolution model considering grid mismatch is established, and the total least squares method is used to estimate the mismatch error for modifying the steering matrix in superresolution processing. At last, based on the modified steering matrix, sparse Bayesian learning algorithm is iteratively executed to achieve multichannel radar forward-looking superresolution imaging. Simulated and measured data processing results are illustrated to verify the effectiveness of the proposed scheme.

Abstract Background Alcohol dehydrogenases (ADHs) are the crucial enzymes that can convert ethanol into acetaldehyde. In tobacco, members of ADH gene family are involved in various stresses tolerance reactions, lipid metabolism and pathways related to plant development. It will be of great application significance to analyze the ADH gene family and expression profile under various stresses in tobacco. Results A total of 53 ADH genes were identified in tobacco (Nicotiana tabacum L.) genome and were grouped into 6 subfamilies based on phylogenetic analysis. Gene structure (exon/intron) and protein motifs were highly conserved among the NtADH genes, especially the members within the same subfamily. A total of 5 gene pairs of tandem duplication, and 3 gene pairs of segmental duplication were identified based on the analysis of gene duplication events. Cis-regulatory elements of the NtADH promoters participated in cell development, plant hormones, environmental stress, and light responsiveness. The analysis of expression profile showed that NtADH genes were widely expressed in topping stress and leaf senescence. However, the expression patterns of different members appeared to be diverse. The qRT-PCR analysis of 13 NtADH genes displayed their differential expression pattern in response to the bacterial pathogen Ralstonia solanacearum L. infection. Metabolomics analysis revealed that NtADH genes were primarily associated with carbohydrate metabolism, and moreover, four NtADH genes (NtADH20/24/48/51) were notably involved in the pathway of alpha-linolenic acid metabolism which related to the up-regulation of 9-hydroxy-12-oxo-10(E), 15(Z)-octadecadienoic acid and 9-hydroxy-12-oxo-15(Z)-octadecenoic acid. Conclusion The genome-wide identification, evolutionary analysis, expression profiling, and exploration of related metabolites and metabolic pathways associated with NtADH genes have yielded valuable insights into the roles of these genes in response to various stresses. Our results could provide a basis for functional analysis of NtADH gene family under stressful conditions.

Abstract Identifying potential prognostic factors of CSM patients could improve doctors’ clinical decision-making ability. The study retrospectively collected the baseline data of population characteristics, clinical symptoms, physical examination, neurological function and quality of life scores of patients with CSM based on the clinical big data research platform. The modified Japanese Orthopedic Association (mJOA) score and SF-36 score from the short-term follow-up data were entered into the cluster analysis to characterize postoperative residual symptoms and quality of life. Four clusters were yielded representing different patterns of residual symptoms and quality of patients’ life. Patients in cluster 2 (mJOA RR 55.8%) and cluster 4 (mJOA RR 55.8%) were substantially improved and had better quality of life. The influencing factors for the better prognosis of patients in cluster 2 were young age (50.1 ± 11.8), low incidence of disabling claudication (5.0%) and pathological signs (63.0%), and good preoperative SF36-physiological function score (73.1 ± 24.0) and mJOA socre (13.7 ± 2.8); and in cluster 4 the main influencing factor was low incidence of neck and shoulder pain (11.7%). We preliminarily verified the reliability of the clustering results with the long-term follow-up data and identified the preoperative features that were helpful to predict the prognosis of the patients. This study provided reference and research basis for further study with a larger sample data, extracting more patient features, selecting more follow-up nodes, and improving clustering algorithm.

Abstract Background Gastric cancer (GC) is a common malignancy with its morbidity increasing worldwide. Hence, it is imperative to develop effective treatments. Studies have shown that metformin has potential antitumor effects. The objective of this study was to probe the antitumor mechanism of metformin in GC. Methods The expression of ADAMTS12 in GC tissues and its enrichment pathways were analyzed by bioinformatics methods. ADAMTS12 expression in GC cells was assessed by qRT-PCR. Cell viability and proliferation were analyzed by CCK-8 and colony formation assays, respectively. Extracellular acidification rate (ECAR) and oxygen consumption rate (OCR) of GC cells in different treatment groups were analyzed by Seahorse XP 96, and glycolysis metabolites were detected by corresponding kits. Western blot was employed to analyze the level of glycolysis pathway related protein HK-2, and cell functional assays were conducted to verify the functions of metformin on GC cells. A xenograft model was constructed to validate the inhibitory role of metformin in GC. Results ADAMTS12 expression was elevated in GC tissues/cells and concentrated in glycolysis pathway. Cell functional assays found that ADAMTS12 promoted the proliferation and glycolysis of GC cells. Rescue experiments showed that metformin could reduce the promoting effect of ADAMTS12 overexpression on the proliferation and glycolysis of GC cells. In vivo studies confirmed that metformin suppressed the proliferation and glycolysis process via ADAMTS12 in GC cells. Conclusion Metformin can repress the proliferation and glycolysis of GC cells via ADAMTS12. The results suggest the potential of ADAMTS12 being a target for the metformin therapy of GC.

Metal-Ferroelectric-Metal (MFM) devices possessing high remanent polarizations ( $2P_{r}$ ) of 84 and $73~\mu $ C/cm2 are demonstrated with nearly epitaxially grown Hf0.5Zr0.5O2 (HZO) films on (001) n+-Si(3E19/cm $^{3}$ ) and n+-Ge(3E20/cm $^{3}$ ) substrates, respectively, which are higher than MFM devices with HZO films grown on amorphous SiO2 and partially crystallized TiN underlayers/substrates. The HZO superlattice films by sequential ZrO2/HfO2 plasma-enhanced atomic layer deposition (PEALD) process show high crystallinity in TEM images of all devices; however, the measured $2P_{r}$ values are quite different, ranging from 84 to $33\mu $ C/cm2. The high-resolution scanning transmission electron microscopy (HR-STEM) images of HZO films on n+-Si and n+-Ge show the polarization axis of o-phase is well-aligned with the growth direction which is consistent with observed high $2P_{r}$ values. Much lower interfacial energy at o-phase/Si(Ge) interfaces than m-(t-)phase/Si(Ge) by density functional theory (DFT) calculations indicates that o-phase is greatly stabilized in the HZO films on n+-Si(Ge) substrates. Strong $2P_{r}$ of 51 and $47~\mu $ C/cm2 are measured after 1E9 and 1E11 endurance cycles for HZO films on n+-Si and n+-Ge substrates, respectively. This study shows epitaxial ferroelectric HZO films could be achieved by using small misfit substrates with the thermal budget as low as 450°C.

Global warming, driven by excessive carbon emissions, harms nature and society. Governments’ carbon reduction policies are crucial for sustainable industrial growth, integrating eco-friendly practices into production decisions. In addition, sellers often demand upfront payment for goods as a performance guarantee, receive a portion upon delivery, and finalize the transaction on credit. This advance-cash-credit (ACC) payment scheme is becoming increasingly common. Based on the above, this study proposes a production–inventory model with a carbon cap-and-trade policy and an ACC payment scheme and discusses optimal production and replenishment strategies. We also consider deteriorating raw materials, deteriorating finished products, and an imperfect production system. Mathematical methods and numerical examples are discussed to clarify the solution process, and a sensitivity analysis of parameters is performed. We demonstrate that under the two-stage trade credit and ACC scheme, a larger credit payment component enables the production–inventory system to generate higher total profits, and that a lower charged interest, higher earned interest, or later overall payment (for the ACC scheme) leads to lower carbon emissions. Furthermore, changing carbon emission quota does not affect annual carbon emissions but increasing carbon trading price does, thereby encouraging companies to reduce annual carbon emissions under a carbon cap-and-trade policy.

Chitosan can be used as an active antibacterial agent or film-forming substrate in foods, and has become a powerful substitute for synthetic plastic polymers because of its good biodegradability, film-forming capacity and antibacterial activity. However, chitosan films have several limitations such as poor water solubility and weak mechanical properties, which limit its application in antibacterial food packaging materials to a certain degree. The safety of applying the antibacterial activity of chitosan in foods has attracted much attention in recent years. In order to provide new ideas for further development and utilization of chitosan-based antibacterial composite materials, this paper expounds the antibacterial mechanism of chitosan and the methods to improve its antibacterial performance, and summarizes the current status of the application of chitosan-polysaccharide, protein or lipid composite films in food preservation.

Abstract The COVID-19 outbreak has dramatically impacted the economy, particularly consumption behaviors. Studies on how consumption responses to COVID-19 can be a powerful aid for urban consumption recovery. In this paper, based on a high-frequency consumption dataset from January 6, 2020, to April 28, 2020 covering 18 sectors and dataset from the corresponding lunar period in 2021, we look at how COVID-19 changed how people spent their money by looking at patterns of recession and recovery during the pandemic. Specifically, we first explore the recession-recovery pattern of national consumption and the effects of various policies and quantify it using regression methods. Then, recession-recovery patterns across cities are widely studied. We also reveal how consumption structures change during a pandemic and the relationship between patterns of change in citizens’ consumption and the socioeconomic characteristics of cities. And the specific empirical analysis is provided through panel regression models. In general, national consumption represented a Vshaped pattern during the pandemic, experiencing a dramatic decline and a rapid rebound. Consumption is significantly inhibited by lockdown, while it is stimulated positively but gradually by easing policies. Consumption patterns at the city level are associated with socioeconomic characteristics. Cities with high-income groups experience a more significant decline, and cities with a high share of the secondary sector have a higher recovery rate in consumption. The consumption structure redistributes but does not fundamentally change. During the recession and early recovery phase, consumption related to basic living saw a significant rise, whereas leisure-related consumption dropped dramatically and recovered slowly. Our study can assist policymakers in implementing diversified market provisions and targeted lockdown policy adjustments for consumption recovery in cities with different socioeconomic backgrounds.

Abstract Primary open-angle glaucoma (POAG), characterized by retinal ganglion cell death, is a leading cause of irreversible blindness worldwide. However, its molecular and cellular causes are not well understood. Elevated intraocular pressure (IOP) is a major risk factor, but many patients have normal IOP. Colocalization and Mendelian randomization analysis of >240 POAG and IOP genome-wide association study (GWAS) loci and overlapping expression and splicing quantitative trait loci (e/sQTLs) in 49 GTEx tissues and retina prioritizes causal genes for 60% of loci. These genes are enriched in pathways implicated in extracellular matrix organization, cell adhesion, and vascular development. Analysis of single-nucleus RNA-seq of glaucoma-relevant eye tissues reveals that the POAG and IOP colocalizing genes and genome-wide associations are enriched in specific cell types in the aqueous outflow pathways, retina, optic nerve head, peripapillary sclera, and choroid. This study nominates IOP-dependent and independent regulatory mechanisms, genes, and cell types that may contribute to POAG pathogenesis.

Abstract Tumor cells primarily employ the PD-1/PD-L1 pathway to thwart the anti-tumor capabilities of T lymphocytes, inducing immunosuppression. This occurs through the direct interaction of PD-L1 with PD-1 on T lymphocyte surfaces. Recent research focusing on the tumor microenvironment has illuminated the pivotal role of immune cells, particularly tumor-associated macrophages (TAMs), in facilitating PD-L1-mediated immunosuppression. Exosomes, characterized by their ability to convey information and be engulfed by cells, significantly contribute to promoting TAM involvement in establishing PD-L1-mediated immunosuppression within the tumor microenvironment. Exosomes, characterized by their ability to convey information and be engulfed by cells, significantly contribute to promoting TAM involvement in establishing PD-L1-mediated immunosuppression within the tumor microenvironment. In addition to receiving signals from tumor-derived exosomes that promote PD-L1 expression, TAMs also exert control over PD-L1 expression in tumor cells through the release of exosomes. This paper aims to summarize the mechanisms by which exosomes participate in this process, identify crucial factors that influence these mechanisms, and explore innovative strategies for inhibiting or reversing the tumor-promoting effects of TAMs by targeting exosomes.

Cross–modal hashing has gained significant attention due to its efficient computational capabilities and impressive retrieval performance. Most supervised methods rely on the auxiliary learning of a similarity matrix, which incurs computational and storage expenses with a complexity of $O(n^{2})$ . By capturing the adjacency relationships between anchor points and original data, the anchor graph learning strategy effectively reduces the time complexity. However, existing anchor graph hashing methods adopt heuristic sampling strategies like k–means or random sampling to determine anchor points. Unfortunately, this approach separates from the anchor graph construction and fails to accurately capture the fine–grained similarity relationships. To overcome this limitation, we introduce a novel method called supervised consensus anchor graph hashing (SCAGH) for cross–modal retrieval with linear complexity. In SCAGH, the anchor points are automatically selected and consensus anchor graph learning is integrated in an unified framework. Through mutual collaboration, a more fine–grained and discriminative consensus anchor graph can be obtained without extra hyper–parameters. Additionally, we utilize anchor graph matrix to approximate the pairwise similarity matrix so that the high complexity can be avoided and enhance the quality of hash codes. Extensive experiments on four benchmark datasets are conducted to verify the superiority of the proposed SCAGH compared to several state–of–the–art methods.

The internet of things (IoT) has gained wide adoption across various industries, driving digitalization and intelligence in industry applications.However, the data collected by IoT devices in some industry applications may be closely linked to user privacy and property security.To ensure the security of such data, a cost-effective, multifunctional hardware architecture design based on the Chinese authenticated encryption algorithm SM4-GCM (Galois/Counter Mode) was proposed, which offered a balanced approach to performance, cost, and hardware-level data confidentiality and integrity assurance, and supported three operation modes: SM4-CTR, SM4-ECB, and SM4-GCM.The implementation results on the field programmable gate array (FPGA) development board demonstrate that the design requires only 1 761 look-up tables and 1 825 registers, occupies only 604 slices, and has a throughput rate of 39.78 Mbit/s@100 MHz.These results suggest that the proposed design can effectively meet the requirements of IoT data security applications.

Abstract Deep foundation pits involving complex soil–water-structure interactions are often at a high risk of failure under heavy rainfall. Predicted deformation is an important index for early risk warning. In the study, an ANN model is proposed based on the Wave Transform (WT), Copula method, Convolutional Neural Network (CNN) and Long Short-Term Memory Neural Network (LSTM). The total deformation was firstly decomposed into low and high frequency components with WT. The CNN and LSTM were then used for prediction of the two components with rolling training and prediction. The input variables of the CNN and LSTM were determined and optimized based on the correlations analysis of Copula method of the two components with different random variables, especially with the rainfall. And finally, the predicted total deformation was obtained by adding the two prediction components. A deep foundation pit in Chengdu, China was taken as a case study, of which the horizontal deformation curves at different measuring points shows three types of developed trend, as unstable, less stable, and stable types. The predictions of the deformations of different development types by the proposed ANN model show high accuracies with a few input variables and can accurately prompt risk warning in advance.

Introduction Electronic cigarettes (e-cigarettes) rapidly evolved from large modifiable (MOD) devices, to small and affordable ‘POD’ devices. Detailed information on user demographics and preferences according to device type, which can inform potential chemical exposure and policy recommendations, is currently limited. The goal of this study is to describe user demographics, use behaviors and preferences, as well as self-reported health outcomes according to the e-cigarette device type used. Methods From April 2019 to March 2020, 91 participants from Maryland (18 MOD users, 26 POD users, 16 dual users (use of both combustible and e-cigarettes), and 31 non-users (never e-cigarette users and never smokers or >6 months former use) were recruited. A comprehensive questionnaire collected sociodemographic characteristics, e-cigarette/tobacco use behaviors, self-reported health outcomes, device characteristics and preferences. Chi-squared tests for categorical variables, ANOVA for continuous variables, qualitative thematic analysis, linear and logistic regressions were used to assess relationships between variables and groups. Results POD users were younger (average 22.5 years) than MOD users (30.8 years) or dual users (34.3 years) (p

Abstract Introduction The purpose of this study was to analyze the current status, the research hot spots and frontiers of cognitive impairment (CI) on old adults from 2012 to 2022 based on Web of Science (WoS) and China National Knowledge Infrastructure (CNKI) via CiteSpace, and provide new in-sights for researchers. Methods The articles regarding the old adults’ CI in the WoS and CNKI were retrieved from 2012 to 2022. CiteSpaceV.6.1.R4 was used to generate network maps. Results Four thousand seven hundred thirteen publications and 304 publications from CNKI were retrieved. Overall, from 2012 to 2022, the trend of articles published in WoS and CNKI were increasing. Data from WoS showed that USA, University of California, Petersen RC were the most influential country, institution and author respectively; Folstein MF, Neurology and a diagnosis guideline of mild CI were the most cited author, journal and reference separately; while the keywords of CI could be summarized in 3 aspects: related disease and symptom, risk factors, manifestations. Data from CNKI illustrated that Peking Union Medical College, Dan Liu were the most influential institution and scholar respectively, while the keywords of CI could be summarized in 3 aspects: related disease and symptoms, risk factors, intervention. Conclusion Articles published on old adults’ CI were drawing an increasing amount of attention from 2012 to 2022 both in WoS and CNKI. Keywords of CI in WoS and CNKI both focused on risk factors, related disease and symptom, yet WoS contributed more to the mechanism and CNKI contributed more to the intervention.

Abstract From childhood to adolescence, the spatiotemporal development pattern of the human brain white matter connectome and its underlying transcriptomic and cellular mechanisms remain largely unknown. With a longitudinal diffusion MRI cohort of 604 participants, we map the developmental trajectory of the white matter connectome from global to regional levels and identify that most brain network properties followed a linear developmental trajectory. Importantly, connectome-transcriptomic analysis reveals that the spatial development pattern of white matter connectome is potentially regulated by the transcriptomic architecture, with positively correlated genes involve in ion transport- and development-related pathways expressed in excitatory and inhibitory neurons, and negatively correlated genes enriches in synapse- and development-related pathways expressed in astrocytes, inhibitory neurons and microglia. Additionally, the macroscale developmental pattern is also associated with myelin content and thicknesses of specific laminas. These findings offer insights into the underlying genetics and neural mechanisms of macroscale white matter connectome development from childhood to adolescence.

Abstract Lipoprotein(a) [Lp(a)] is a risk factor for cardiovascular disease (CVD) and aortic stenosis. However, the data on the relationship between Lp(a) and mildly reduced estimated glomerular filtration rate (eGFR) has been disputed. This study was conducted to assess the relationship between Lp(a) concentrations and mildly reduced eGFR in healthy subjects.This community-based, cross-sectional study enrolled 1,064 volunteers aged ≥ 40 years who lived in Yonghong Community, Zhonglou District, Changzhou, China, between December 2016 and December 2017. A mildly reduced eGFR was defined as eGFR between 60 and 90 mL/min/1.73m2. A standardized questionnaire and biochemical measurements were used to gather information about participants. The serum concentration of Lp(a) was determined using the latex-enhanced immunoturbidimetric test. Of the total study population, 34.8% (n = 370) were men, and the mean age was 66.8 ± 8.5 years. A significant association existed between Lp(a) levels and the risk of mildly reduced eGFR. Individuals with the highest tertile of Lp(a) had higher odds of mildly reduced eGFR after adjusting for various confounders (adjusted odds ratio [OR]: 1.80, 95% confidence interval [CI]: 1.24–2.60, P = 0.0025) compared to those with the lowest tertile of Lp(a). Multivariable logistic regression of studies in which Lp(a) was presented as continuous variables showed consistent results (adjusted OR: 1.23 for 1-SD increment of Ln-Lp(a), 95% CI: 1.05–1.43). Subgroup analyses showed that study characteristics such as age, sex, obesity, diabetes, and hypertension status did not significantly affect the association (P for all interactions > 0.05). These results suggest that higher serum Lp(a) level was an independent risk factor for mildly reduced eGFR.

Abstract Purpose To examine the diagnostic advantages and clinical application value of the cinematic volume rendering technique (cVRT) when evaluating the relationship between the brachial plexus, peripheral tumor lesions, and blood vessels. Materials and methods Seventy-nine patients with brachial plexus tumors between November 2012 and July 2022 were enrolled in our study. All patients underwent T1WI, T2WI, three-dimensional short recovery time reversal recovery fast spin-echo imaging (3D-STIR-SPACE), and the T1WI enhancement sequence. In addition, cVRT was used to render and obtain a three-dimensional model that clearly showed the location and tissue structure of the brachial plexus nerves and the tumor in all directions. Results Seventy-one patients (mean age, 47.1 years; 33 males, 38 females) with tumors around the brachial plexus were included in the study. The brachial plexus nerve, surrounding tumor lesions, and vascular anatomy of all patients were well displayed with cVRT. The tumors of 37 patients manifested as unilateral or bilateral growths along the brachial plexus nerve and were fusiform, spherical, or multiple beaded; seven patients' tumors pushed against the brachial plexus nerve and were circular, lobular, or irregular; sixteen patients' tumors encircled the brachial plexus nerve and were spherical; and eleven patients' tumors infiltrated the brachial plexus nerve and had irregular morphology. The mass has a moderately uniform or uneven signal on T1WI and a high or mixed signal on T2WI. After enhancement, the signal was evenly or unevenly strengthened. Conclusions cVRT clearly showed the origin of tumors associated with the brachial plexus and their relationship with the nerves and peripheral blood vessels, providing reliable information for clinical diagnosis and treatment.

ABSTRACTGenetically modified (GM) soybeans provide a huge amount of food for human consumption and animal feed. However, the possibility of unexpected effects of transgenesis has increased food safety concerns. High-throughput sequencing profiling provides a potential approach to directly evaluate unintended effects caused by foreign genes. In this study, we performed transcriptomic analyses to evaluate differentially expressed genes (DEGs) in individual soybean tissues, including cotyledon (C), germ (G), hypocotyl (H), and radicle (R), instead of using the whole seed, from four GM and three non-GM soybean lines. A total of 3,351 DEGs were identified among the three non-GM soybean lines. When the GM lines were compared with their non-GM parents, 1,836 to 4,551 DEGs were identified. Furthermore, Gene Ontology (GO) analysis of the DEGs showed more abundant categories of GO items (199) among non-GM lines than between GM lines and the non-GM natural varieties (166). Results of Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that most KEGG pathways were the same for the two types of comparisons. The study successfully employed RNA sequencing to assess the differences in gene expression among four tissues of seven soybean varieties, and the results suggest that transgenes do not induce massive transcriptomic alterations in transgenic soybeans compared with those that exist among natural varieties. This work offers empirical evidence to investigate the genomic-level disparities induced by genetic modification in soybeans, specifically focusing on seed tissues.

In order to address the problem of a high miss-seeding rate in mechanized potato planting work, a novel reseeding device is designed and analyzed. Based on dynamic and kinematic principles, the seed potato’s motion analysis model in the seed preparation process was constructed. The analysis results indicate that the seed preparation performance is positively related to the seed preparation opening length l1 and inclination angle of the seed-returning pipe θ. Then, the potato’s motion analysis model in the reseeding process was constructed. The analysis showed that the displacement of seeding potatoes in the horizontal direction ds is influenced by the initial seeding potato’s speed v0t, dropping height hs, and the angle between the seeding pipe and the horizontal ground βs. The horizontal moving distance xr of the reseeding potatoes is influenced by the angle between the bottom of the reseeding pipe and horizontal ground βs2, the distance from its centroid to the reseeding door d, and the dropping height of the potato hr. The analysis results indicated that the reseeding potato can be effectively discharged into the furrow. Then, a prototype of a reseeding control system was constructed based on the STM32 microcontroller, electric pushers, and through-beam laser sensors. The simulation analysis was conducted to verify the theoretical analysis by using EDEM2020 software. The simulation results indicated that with the increase in the seeding chain speed, the seed preparation success rate initially increased slowly and then decreased gradually. The seed preparation performance can be increased by increasing the seed preparation opening length or decreasing the seed-returning pipe inclination angle. The impact on the successful seed preparation rate is ranked by significance as follows: seed preparation opening length > seed-returning pipe inclination angle > chain speed. Then, the prototype reseeding device and the corresponding seed metering device were manufactured and a series of bench tests and field tests were conducted. The bench test results showed an average successful seed preparation rate of 93.6%. The average qualified-seeding rate, miss-seeding rate, and multi-seeding rate in the field test were 89.6%, 2.46%, and 7.94%, respectively. This study can provide a theoretical reference for the design of potato reseeding devices.

To address the limitations of traditional footstep vibration signal localization algorithms, such as limited accuracy, single feature extraction, and cumbersome parameter adjustment, a motion target localization method for step vibration signals based on deep learning is proposed. Velocity vectors are used to describe human motion and adapt it to the nonlinear motion and complex interactions of moving targets. In the feature extraction stage, a one-dimensional residual convolutional neural network is constructed to extract the time–frequency domain features of the signals, and a channel attention mechanism is introduced to enhance the model’s focus on different vibration sensor signal features. Furthermore, a bidirectional long short-term memory network is built to learn the temporal relationships between the extracted signal features of the convolution operation. Finally, regression operations are performed through fully connected layers to estimate the position and velocity vectors of the moving target. The dataset consists of footstep vibration signal data from six experimental subjects walking on four different paths and the actual motion trajectories of the moving targets obtained using a visual tracking system. Experimental results show that compared to WT-TDOA and SAE-BPNN, the positioning accuracy of our method has been improved by 37.9% and 24.8%, respectively, with a system average positioning error reduced to 0.376 m.

Antibiotic-resistant genes (ARGs) pose a significant threat to the global food transformation system. The increasing prevalence of ARGs in food has elicited apprehension about public health safety. The widespread dissemination of ARGs in food products, driven by the inappropriate use of antibiotics, presents significant adversity for the safety of emerging future food sources such as edible insects. As the world faces increasing challenges related to food security, climate change, and antibiotic resistance, edible insects offer a sustainable and resilient food source. The intriguing possibility of edible insects serving as a less conducive environment for ARGs compared to livestock warrants further exploration and investigation. In this recent work, we listed ARGs from edible insects detected so far by in vitro approaches and aimed to construct a fair comparison with ARGs from livestock based on relevant genes. We also presented our argument by analyzing the factors that might be responsible for ARG abundance in livestock vs. edible insects. Livestock and edible insects have diverse gut microbiota, and their diets differ with antibiotics. Consequently, their ARG abundance may vary as well. In addition, processed edible insects have lower levels of ARGs than raw ones. We hypothesize that edible insects could potentially contain a lower abundance of ARGs and exhibit a diminished ability to disseminate ARGs relative to livestock. A regulatory framework could help intercept the increasing prevalence of ARGs. Due diligence should also be taken when marketing edible insects for consumption.

The detection and quantitative analysis of shale components are of great significance for comprehensively understanding the properties of shale, assessing its resource potential and promoting efficient development and utilization of resources. The low-field NMR T1-T2 two-dimensional spectrum can detect shale components non-destructively and effectively. Unfortunately, due to its complexity, the two-dimensional spectral results of low-field NMR are mainly analyzed using manual qualitative analysis, and accurate results of the composition cannot be obtained. Since the information contained in its two-dimensional map is determined by the morphological texture and the position in the map, commonly used image analysis networks cannot adapt. In order to solve these problems, this paper improves a novel Faster Region-based Convolutional Neural Network (Faster-RCNN). Compared with previous models, the improved Faster-RCNN has better image classification and visual key point estimation capabilities. The results show that compared with traditional methods, the deep learning method using this model can directly obtain key information such as kerogen and movable oil and gas content in rocks. The information provided in this study can help complement and improve the development of analytical methods for low-field 2D NMR spectra.