Positive school climate and strong school identification as protective factors of adolescent mental health and learning engagement: A longitudinal investigation before and during COVID-19.

The COVID-19 pandemic resulted in significant disruptions for children and youth around the world, especially given school closures and shifts in teaching modes (on-line and hybrid). However, the impact of these disruptions remains unclear given data limitations such as a reliance on cross-sectional and/or short-interval surveys as well as a lack of broad indicators of key outcomes of interest. The current research employs a quasi-experimental design by using an Australian four-year longitudinal survey with student responses from Grade 7 to 10 (aged 12-15 years old) (N = 8,735 from 20 schools) in one education jurisdiction. Responses are available pre-pandemic (2018 and 2019) and during the pandemic (2020 and 2021). Importantly the survey included measures of well-being, mental health and learning engagement as well as potential known school-environment factors that could buffer against adversity: school climate and school identification. The findings were generally in line with key hypotheses; 1) during COVID-19 students' learning engagement and well-being significantly declined and 2) students with more positive school climate or stronger school identification pre-COVID-19 fared better through the disruption of the pandemic. However, these same students suffered from a steeper decline in well-being and engagement which may be explained through the impact of losing meaningful social or group connections. This decline was evident after controlling for gender, academic grade (as a proxy of age), parental education, and socioeconomic status. It is concluded that investing in the social environment of schools is important in crisis preparedness and can facilitate better crisis response among youth.

Application of Multimodal Transformer Model in Intelligent Agricultural Disease Detection and Question-Answering Systems.

In this study, an innovative approach based on multimodal data and the transformer model was proposed to address challenges in agricultural disease detection and question-answering systems. This method effectively integrates image, text, and sensor data, utilizing deep learning technologies to profoundly analyze and process complex agriculture-related issues. The study achieved technical breakthroughs and provides new perspectives and tools for the development of intelligent agriculture. In the task of agricultural disease detection, the proposed method demonstrated outstanding performance, achieving a precision, recall, and accuracy of 0.95, 0.92, and 0.94, respectively, significantly outperforming the other conventional deep learning models. These results indicate the method's effectiveness in identifying and accurately classifying various agricultural diseases, particularly excelling in handling subtle features and complex data. In the task of generating descriptive text from agricultural images, the method also exhibited impressive performance, with a precision, recall, and accuracy of 0.92, 0.88, and 0.91, respectively. This demonstrates that the method can not only deeply understand the content of agricultural images but also generate accurate and rich descriptive texts. The object detection experiment further validated the effectiveness of our approach, where the method achieved a precision, recall, and accuracy of 0.96, 0.91, and 0.94. This achievement highlights the method's capability for accurately locating and identifying agricultural targets, especially in complex environments. Overall, the approach in this study not only demonstrated exceptional performance in multiple tasks such as agricultural disease detection, image captioning, and object detection but also showcased the immense potential of multimodal data and deep learning technologies in the application of intelligent agriculture.

Heterostructured ZnFe2O4@Ni3S2 nanosheet arrays on Ni foam as an efficient oxygen evolution catalyst.

Honeycomb-like ZnFe2O4@Ni3S2 hierarchical nanosheet arrays on Ni foam (NF) were fabricated via a combined hydrothermal and electrodeposition method. The electrode exhibits high oxygen evolution reaction (OER) activity with low overpotentials of 254 mV at 10 mA cm-2 and 290 mV at 50 mA cm-2, a small Tafel slope of 39.29 mV dec-1 and excellent durability in an alkaline electrolyte.

Characterisation of the MLP genes in peach postharvest cold storage and the regulatory role of PpMLP10 in the chilling stress response.

The major latex proteins/ripening-related proteins are a subfamily of the Bet v 1 protein superfamily and are commonly involved in plant development and responses to various stresses. However, the functions of MLPs in the postharvest cold storage of fruits remain uninvestigated. Herein, we identified 30 MLP genes in the peach (Prunus persica) genome that were clustered into three subgroups. Chromosomal location analysis revealed that the PpMLP genes were unevenly distributed on five of the eight peach chromosomes. Synteny analysis of the MLP genes between peach and seven other plant species (five dicotyledons and two monocotyledons) explored their evolutionary characteristics. Furthermore, the PpMLP promoters contained cis-elements for multiple hormones and stress responses. Gene expression analysis revealed that PpMLPs participated in chilling stress responses. Ectopic expression of PpMLP10 in Arabidopsis improved chilling stress tolerance by decreasing membrane damage and maintaining membrane stability. Additional research confirmed that PpWRKY2 participates in PpMLP10-mediated chilling stress by binding to its promoter. Collectively, these results suggest the role of PpMLP10 in enhancing chilling stress tolerance, which is significant for decreasing chilling injury during the postharvest cold storage of peaches.

Base editing correction of OCRL in Lowe syndrome: ABE-mediated functional rescue in patient-derived fibroblasts.

Lowe syndrome, a rare X-linked multisystem disorder presenting with major abnormalities in the eyes, kidneys, and central nervous system, is caused by mutations in OCRL gene (NG_008638.1). Encoding an inositol polyphosphate 5-phosphatase, OCRL catalyzes the hydrolysis of PI(4,5)P2 into PI4P. There are no effective targeted treatments for Lowe syndrome. Here, we demonstrate a novel gene therapy for Lowe syndrome in patient fibroblasts using an adenine base editor (ABE) that can efficiently correct pathogenic point mutations. We show that ABE8e-NG-based correction of a disease-causing mutation in a Lowe patient-derived fibroblast line containing R844X mutation in OCRL gene, restores OCRL expression at mRNA and protein levels. It also restores cellular abnormalities that are hallmarks of OCRL dysfunction, including defects in ciliogenesis, microtubule anchoring, α-actinin distribution, and F-actin network. The study indicates that ABE-mediated gene therapy is a feasible treatment for Lowe syndrome, laying the foundation for therapeutic application of ABE in the currently incurable disease.

Roll-to-Roll Manufacturing of Breathable Superhydrophobic Membranes.

Self-cleaning and anti-biofouling are both advantages for lotus-leaf-like superhydrophobic surfaces. Methods for creating superhydrophobicity, including chemical bonding low surface energy molecular fragments and constructing surface morphology with protrusions, micropores, and trapped micro airbags by traditional physical strategies, unfortunately, have encountered challenges. They often involve complex synthesis processes, stubborn chemical accumulation, brutal degradation, or infeasible calculation and imprecise modulation in fabricating hierarchical surface roughness. Here, a scalable method to prepare high-quality, breathable superhydrophobic membranes is proposed by developing a successive roll-to-roll laser manufacturing technique, which offers advantages over conventional fabrication approaches in enabling automatically large-scale production and ensuring cost-effectiveness. Nanosecond laser writing and femtosecond laser drilling produce surface microstructures and micropore arrays, respectively, endowing the membrane with superior antiwater capability with hierarchical microstructures forming a barrier and blocking water infiltration. The membrane's breathability is carefully optimized by tailoring micropore arrays to allow for the adequate passage of water vapor while maintaining superhydrophobicity. These membranes combine the benefits of anti-aqueous corrosive liquid behaviors, photothermal effects, thermoplastic properties, and stretchable performances as promising comprehensive materials in diverse scenes.

13C6-Glucose Labeling Associated with LC-MS: Identification of Plant Primary Organs in Secondary Metabolite Synthesis.

This paper presents a novel and efficient method for certifying primary organs involved in secondary metabolite synthesis. As the most important secondary metabolite in Parispolyphylla var. yunnanensis (Franch.) Hand. -Mzt. (PPY), Paris saponin (PS) has a variety of pharmacological activities and PPY is in increasing demand. This study established leaf, rhizome, and stem-vascular-bundle 13C6-Glucose feeding and non-feeding four treatments to precisely certify the primary organs involved in Paris saponins VII (PS VII) synthesis. By combining liquid chromatography-mass spectrometry (LC-MS), the 13C/12C ratios of leaf, rhizome, stem, and root in different treatments were quickly and accurately calculated, and four types of PS isotopic ion peak(M-) ratios were found: (M+1) -/M-, (M+2) -/M-, (M+3) -/M- and (M+4) -/M-. The results showed that the ratio of 13C/12C in the rhizomes of the stem-vascular-bundle and rhizome feeding treatments was significantly higher than that in the non-feeding treatment. Compared to the non-feeding treatment, the ratio of PS VII molecules (M+2) -/M- in the leaves increased significantly under leaf and stem-vascular-bundle feeding treatments. Simultaneously, compared to the non-feeding treatment, the ratio of PS VII molecules (M+2) -/M- in the leaves under rhizome treatment showed no significant difference. Furthermore, the ratio of PS VII molecules (M+2) -/M- in the stem, root, and rhizome showed no differences among the four treatments. Compared to the non-feeding treatment, the ratio of the Paris saponin II (PS II) molecule (M+2) -/M- in leaves under leaf feeding treatment showed no significant difference, and the (M+3) -/M- ratio of PS II molecules in leaves under leaf feeding treatment were lower. The data confirmed that the primary organ for the synthesizing of PS VII is the leaves. It lays the foundation for future identification of the primary organs and pathways involved in the synthesis of secondary metabolites in medicinal plants.

Integrated Transcriptome and Proteome Analysis Reveals That Cell Wall Activity Affects Phelipanche aegyptiaca Parasitism.

Phelipanche aegyptiaca can infect many crops, causing large agricultural production losses. It is important to study the parasitism mechanism of P. aegyptiaca to control its harm. In this experiment, the P. aegyptiaca HY13M and TE9M from Tacheng Prefecture and Hami City in Xinjiang, respectively, were used to analyze the parasitical mechanism of P. aegyptiaca by means of transcriptome and proteome analyses. The parasitic capacity of TE9M was significantly stronger than that of HY13M in Citrullus lanatus. The results showed that the DEGs and DEPs were prominently enriched in the cell wall metabolism pathways, including "cell wall organization or biogenesis", "cell wall organization", and "cell wall". Moreover, the functions of the pectinesterase enzyme gene (TR138070_c0_g), which is involved in the cell wall metabolism of P. aegyptiaca in its parasitism, were studied by means HIGS. The number and weight of P. aegyptiaca were significantly reduced when TR138070_c0_g1, which encodes a cell-wall-degrading protease, was silenced, indicating that it positively regulates P. aegyptiaca parasitism. Thus, these results suggest that the cell wall metabolism pathway is involved in P. aegyptiaca differentiation of the parasitic ability and that the TR138070_c0_g1 gene plays an important role in P. aegyptiaca's parasitism.

Protein oxidation of fucose environments (POFE) reveals fucose-protein interactions.

Cell membrane glycoproteins are generally highly fucosylated and sialylated, and post-translational modifications play important roles in the proteins' functions of signaling, binding and cellular processing. For these reasons, methods for measuring sialic acid-mediated protein-protein interactions have been developed. However, determining the role of fucose in these interactions has been limited by technological barriers that have thus far hindered the ability to characterize and observe fucose-mediated protein-protein interactions. Herein, we describe a method to metabolically label mammalian cells with modified fucose, which incorporates a bioorthogonal group into cell membrane glycoproteins thereby enabling the characterization of cell-surface fucose interactome. Copper-catalyzed click chemistry was used to conjugate a proximity labeling probe, azido-FeBABE. Following the addition of hydrogen peroxide (H2O2), the fucose-azido-FeBABE catalyzed the formation of hydroxyl radicals, which in turn oxidized the amino acids in the proximity of the labeled fucose residue. The oxidized peptides were identified using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). Variations in degree of protein oxidation were obtained with different H2O2 reaction times yielding the acquisition of spatial information of the fucose-interacting proteins. In addition, specific glycoprotein-protein interactions were constructed for Galectin-3 (LEG3) and Galectin-3-binding protein (LG3BP) illustrating the further utility of the method. This method identifies new fucose binding partners thereby enhancing our understanding of the cell glycocalyx.

Mitophagy mediated by HIF-1α/FUNDC1 signaling in tubular cells protects against renal ischemia/reperfusion injury.

Acute kidney injury (AKI) is associated with a high mortality rate. Pathologically, renal ischemia/reperfusion injury (RIRI) is one of the primary causes of AKI, and hypoxia-inducible factor (HIF)-1α may play a defensive role in RIRI. This study assessed the role of hypoxia-inducible factor 1α (HIF-1α)-mediated mitophagy in protection against RIRI in vitro and in vivo. The human tubular cell line HK-2 was used to assess hypoxia/reoxygenation (H/R)-induced mitophagy through different in vitro assays, including western blotting, immunofluorescence staining, terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling (TUNEL), and reactive oxygen species (ROS) measurement. Additionally, a rat RIRI model was established for evaluation by renal histopathology, renal Doppler ultrasound, and transmission electron microscopy to confirm the in vitro data. The selective HIF-1α inhibitor LW6 reduced H/R-induced mitophagy but increased H/R-induced apoptosis and ROS production. Moreover, H/R treatment enhanced expression of the FUN14 domain-containing 1 (FUNDC1) protein. Additionally, FUNDC1 overexpression reversed the effects of LW6 on the altered expression of light chain 3 (LC3) BII and voltage-dependent anion channels as well as blocked the effects of HIF-1α inhibition in cells. Pretreatment of the rat RIRI model with roxadustat, a novel oral HIF-1α inhibitor, led to decreased renal injury and apoptosis in vivo. In conclusion, the HIF-1α/FUNDC1 signaling pathway mediates H/R-promoted renal tubular cell mitophagy, whereas inhibition of this signaling pathway protects cells from mitophagy, thus aggravating apoptosis, and ROS production. Accordingly, roxadustat may protect against RIRI-related AKI.

Association of daily sitting time and coffee consumption with the risk of all-cause and cardiovascular disease mortality among US adults.

BACKGROUND: Sedentary behavior has been demonstrated to be a modifiable factor for several chronic diseases, while coffee consumption is believed to be beneficial for health. However, the joint associations of daily sitting time and coffee consumption with mortality remains poorly understood. This study aimed to evaluate the independent and joint associations of daily sitting time and coffee intakes with mortality from all-cause and cardiovascular disease (CVD) among US adults. METHODS: An analysis of a prospective cohort from the 2007-2018 National Health and Nutrition Examination Survey of US adults (n = 10,639). Data on mortality were compiled from interview and physical examination data until December 31, 2019. Daily sitting time was self-reported. Coffee beverages were from the 24-hour diet recall interview. The main outcomes of the study were all-cause and cardiovascular disease mortality. The adjusted hazard ratios [HRs] and 95% confidence intervals [CI] were imputed by Cox proportional hazards regression. RESULTS: Among 10,639 participants in the study cohort, there were 945 deaths, 284 of whom died of CVD during the follow-up period of up to 13 years. Multivariable models showed that sitting more than 8 h/d was associated with higher risks of all-cause (HR, 1.46; 95% CI, 1.17-1.81) and CVD (HR, 1.79; 95% CI, 1.21-2.66) mortality, compared with those sitting for less than 4 h/d. People with the highest quartile of coffee consumption were observed for the reduced risks of both all-cause (HR, 0.67; 95% CI, 0.54-0.84) and CVD (HR, 0.46; 95% CI, 0.30-0.69) mortality compared with non-coffee consumers. Notably, joint analyses firstly showed that non-coffee drinkers who sat six hours or more per day were 1.58 (95% CI, 1.25-1.99) times more likely to die of all causes than coffee drinkers sitting for less than six hours per day, indicating that the association of sedentary with increased mortality was only observed among adults with no coffee consumption but not among those who had coffee intake. CONCLUSIONS: This study identified that sedentary behavior for more than 6 h/d accompanied with non-coffee consumption, were strongly associated with the increased risk of mortality from all-cause and CVD.

Risk factors and prediction score for new-onset diabetes mellitus after liver transplantation.

AIM: New-onset diabetes mellitus is a frequent and severe complication arising after liver transplantation (LT). We aimed to identify the risk factors for new-onset diabetes mellitus after liver transplantation (NODALT) and to develop a risk prediction score system for relevant risks. METHODS: We collected and analyzed data from all recipients who underwent liver transplantation at the First Affiliated Hospital of Xi'an Jiaotong University. The OR derived from a multiple logistic regression predicting the presence of NODALT was used to calculate the risk prediction score. The performance of the risk prediction score was externally validated in patients who were from the CLTR (China Liver Transplant Registry) database. RESULTS: A total of 468 patients met the outlined criteria and finished the follow-up. Overall, NODALT was diagnosed in 115 (24.6%) patients. Age, preoperative impaired fasting glucose (IFG), postoperative fasting plasma glucose (FPG), and the length of hospital stay were significantly associated with the presence of NODALT. The risk prediction score includes age, preoperative IFG, postoperative FPG, and the length of hospital stay. The risk prediction score of the area under the receiver operating curve was 0.785 (95% CI: 0.724-0.846) in the experimental population and 0.782 (95% CI: 0.708-0.856) in the validation population. CONCLUSIONS: Age at the time of transplantation, preoperative IFG, postoperative FPG, and length of hospital stay were independent predictive factors of NODALT. The use of a simple risk prediction score can identify the patients who have the highest risk of NODALT and interventions may start early.

Unveiling the gastric microbiota: implications for gastric carcinogenesis, immune responses, and clinical prospects.

High-throughput sequencing has ushered in a paradigm shift in gastric microbiota, breaking the stereotype that the stomach is hostile to microorganisms beyond H. pylori. Recent attention directed toward the composition and functionality of this 'community' has shed light on its potential relevance in cancer. The microbial composition in the stomach of health displays host specificity which changes throughout a person's lifespan and is subject to both external and internal factors. Distinctive alterations in gastric microbiome signature are discernible at different stages of gastric precancerous lesions and malignancy. The robust microbes that dominate in gastric malignant tissue are intricately implicated in gastric cancer susceptibility, carcinogenesis, and the modulation of immunosurveillance and immune escape. These revelations offer fresh avenues for utilizing gastric microbiota as predictive biomarkers in clinical settings. Furthermore, inter-individual microbiota variations partially account for differential responses to cancer immunotherapy. In this review, we summarize current literature on the influence of the gastric microbiota on gastric carcinogenesis, anti-tumor immunity and immunotherapy, providing insights into potential clinical applications.

Synthesis and biological evaluation of novel benzothiazole derivatives as potential anticancer and antiinflammatory agents.

Introduction: Cancer, a significant global health concern, necessitates innovative treatments. The pivotal role of chronic inflammation in cancer development underscores the urgency for novel therapeutic strategies. Benzothiazole derivatives exhibit promise due to their distinctive structures and broad spectrum of biological effects. This study aims to explore new anti-tumor small molecule drugs that simultaneously anti-inflammatory and anticancer based on the advantages of benzothiazole frameworks. Methods: The compounds were characterized by nuclear magnetic resonance (NMR), liquid chromatograph-mass spectrometer (LC-MS) and high performance liquid chromatography (HPLC) for structure as well as purity and other related physicochemical properties. The effects of the compounds on the proliferation of human epidermoid carcinoma cell line (A431) and human non-small cell lung cancer cell lines (A549, H1299) were evaluated by MTT method. The effect of compounds on the expression levels of inflammatory factors IL-6 and TNF-α in mouse monocyte macrophages (RAW264.7) was assessed using enzyme-linked immunosorbent assay (ELISA). The effect of compounds on apoptosis and cell cycle of A431 and A549 cells was evaluated by flow cytometry. The effect of compounds on A431 and A549 cell migration was evaluated by scratch wound healing assay. The effect of compounds on protein expression levels in A431 and A549 cells was assessed by Western Blot assay. The physicochemical parameters, pharmacokinetic properties, toxicity and drug similarity of the active compound were predicted using Swiss ADME and admetSAR web servers. Results: Twenty-five novel benzothiazole compounds were designed and synthesized, with their structures confirmed through spectrogram verification. The active compound 6-chloro-N-(4-nitrobenzyl) benzo[d] thiazol-2-amine (compound B7) was screened through a series of bioactivity assessments, which significantly inhibited the proliferation of A431, A549 and H1299 cancer cells, decreased the activity of IL-6 and TNF-α, and hindered cell migration. In addition, at concentrations of 1, 2, and 4 µM, B7 exhibited apoptosis-promoting and cell cycle-arresting effects similar to those of the lead compound 7-chloro-N-(2, 6-dichlorophenyl) benzo[d] thiazole-2-amine (compound 4i). Western blot analysis confirmed that B7 inhibited both AKT and ERK signaling pathways in A431 and A549 cells. The prediction results of ADMET indicated that B7 had good drug properties. Discussion: This study has innovatively developed a series of benzothiazole derivatives, with a focus on compound B7 due to its notable dual anticancer and anti-inflammatory activities. B7 stands out for its ability to significantly reduce cancer cell proliferation in A431, A549, and H1299 cell lines and lower the levels of inflammatory cytokines IL-6 and TNF-α. These results position B7B7 as a promising candidate for dual-action cancer therapy. The study's mechanistic exploration, highlighting B7's simultaneous inhibition of the AKT and ERK pathways, offers a novel strategy for addressing both the survival mechanisms of tumor cells and the inflammatory milieu facilitating cancer progression.

Efficient Delivery of Lomitapide using Hybrid Membrane-Coated Tetrahedral DNA Nanostructures for Glioblastoma Therapy.

Glioblastoma (GBM) is the most aggressive and prevalent primary malignant tumor of the central nervous system. Traditional chemotherapy has poor therapeutic effects and significant side effects due to drug resistance, the natural blood-brain barrier (BBB), and nonspecific distribution, leading to a lack of clinically effective therapeutic drugs. Here, 1430 small molecule compounds are screened based on a high-throughput drug screening platform and a novel anti-GBM drug, lomitapide (LMP) is obtained. Furthermore, a bionic nanodrug delivery system (RFA NPs) actively targeting GBM is constructed, which mainly consists of tetrahedral DNA nanocages (tFNA NPs) loaded with LMP as the core and a folate-modified erythrocyte-cancer cell-macrophage hybrid membrane (FRUR) as the shell. FRUR camouflage conferred unique features on tFNA NPs, including excellent biocompatibility, improved pharmacokinetic profile, efficient BBB permeability, and tumor targeting ability. The results show that the LMP RFA NPs exhibited superior and specific anti-GBM activities, reduced off-target drug delivery, prolonged lifespan, and has negligible side effects in tumor-bearing mice. This study combines high-throughput drug screening with biomimetic nanodrug delivery system technology to provide a theoretical and practical basis for drug development and the optimization of clinical treatment strategies for GBM treatment.

Wet canopy photosynthesis in a temperate Japanese cypress forest.

This study aimed to reveal the mechanism and significance of wet canopy photosynthesis during and after rainfall in temperate coniferous ecosystems by evaluating the influence of abaxial leaf interception on wet canopy photosynthesis. We used the eddy covariance (EC) method in conjunction with an enclosed-path gas analyser to conduct continuous ecosystem CO2 flux observations in a Japanese cypress forest within the temperate Asian monsoon area over three years. The observation shows that wet-canopy CO2 uptake predominantly occurred during the post-rainfall canopy-wet period rather than the during-rainfall period. Then, the measured canopy-wet net ecosystem exchange (NEE) was compared with the soil-vegetation-atmosphere transfer multilayer model simulations under different parameter settings of the abaxial (lower) leaf surface wet area ratio. The multilayer model predicted NEE most accurately when it assumed the wet area ratio of the abaxial surface was 50% both during and after rainfall. For the wet canopy both during and after rainfall, the model overestimated CO2 uptake when it assumed no abaxial interception in the simulation, but underestimated CO2 uptake when it assumed that the entire abaxial leaf surface was wet. These results suggest that the abaxial surface of the Japanese cypress leaf is only partly wet to maintain stomatal openness and a low level of photosynthesis. These results allow for an evaluation of the effect of rainfall on forest carbon circulation under a changing climate, facilitating an improvement of ecosystem carbon exchange models.

Hierarchical superstructure aerogels for in situ biofluid metabolomics.

High-throughput biofluid metabolomics analysis for screening life-threatening diseases is urgently needed. However, the high salt content of biofluid samples, which introduces severe interference, can greatly limit the analysis throughput. Here, a new 3-D interconnected hierarchical superstructure, namely a "plasmonic gold-on-silica (Au/SiO2) double-layered aerogel", integrating distinctive features of an upper plasmonic gold aerogel with a lower inert silica aerogel was successfully developed to achieve in situ separation and storage of inorganic salts in the silica aerogel, parallel enrichment of metabolites on the surface of the functionalized gold aerogel, and direct desorption/ionization of enriched metabolites by the photo-excited gold aerogel for rapid, sensitive, and comprehensive metabolomics analysis of human serum/urine samples. By integrating all these unique advantages into the hierarchical aerogel, multifunctional properties were introduced in the SALDI substrate to enable its effective utilization in clinical metabolomics for the discovery of reliable metabolic biomarkers to achieve unambiguous differentiation of early and advanced-stage lung cancer patients from healthy individuals. This study provides insight into the design and application of superstructured nanomaterials for in situ separation, storage, and photoexcitation of multi-components in complex biofluid samples for sensitive analysis.

Barley yellow dwarf virus-GAV 17K protein disrupts thiamine biosynthesis to facilitate viral infection in plants.

Thiamine functions as a crucial activator modulating plant health and broad-spectrum stress tolerances. However, the role of thiamine in regulating plant virus infection is largely unknown. Here, we report that the multifunctional 17K protein encoded by barley yellow dwarf virus-GAV (BYDV-GAV) interacted with barley pyrimidine synthase (HvTHIC), a key enzyme in thiamine biosynthesis. HvTHIC was found to be localized in chloroplast via an N-terminal 74-amino acid domain. However, the 17K-HvTHIC interaction restricted HvTHIC targeting to chloroplasts and triggered autophagy-mediated HvTHIC degradation. Upon BYDV-GAV infection, the expression of the HvTHIC gene was significantly induced, and this was accompanied by accumulation of thiamine and salicylic acid. Silencing of HvTHIC expression promoted BYDV-GAV accumulation. Transcriptomic analysis of HvTHIC silenced and non-silenced barley plants showed that the differentially expressed genes were mainly involved in plant-pathogen interaction, plant hormone signal induction, phenylpropanoid biosynthesis, starch and sucrose metabolism, photosynthesis-antenna protein, and MAPK signaling pathway. Thiamine treatment enhanced barley resistance to BYDV-GAV. Taken together, our findings reveal a molecular mechanism underlying how BYDV impedes thiamine biosynthesis to uphold viral infection in plants.

Development and application of GlycanDIA workflow for glycomic analysis.

Glycans modify protein, lipid, and even RNA molecules to form the regulatory outer coat on cells called the glycocalyx. The changes in glycosylation have been linked to the initiation and progression of many diseases. Thus, while the significance of glycosylation is well established, a lack of accessible methods to characterize glycans has hindered the ability to understand their biological functions. Mass spectrometry (MS)-based methods have generally been at the core of most glycan profiling efforts; however, modern data-independent acquisition (DIA), which could increase sensitivity and simplify workflows, has not been benchmarked for analyzing glycans. Herein, we developed a DIA-based glycomic workflow, termed GlycanDIA, to identify and quantify glycans with high sensitivity and accuracy. The GlycanDIA workflow combined higher energy collisional dissociation (HCD)-MS/MS and staggered windows for glycomic analysis, which facilitates the sensitivity in identification and the accuracy in quantification compared to conventional data-dependent acquisition (DDA)-based glycomics. To facilitate its use, we also developed a generic search engine, GlycanDIA Finder, incorporating an iterative decoy searching for confident glycan identification and quantification from DIA data. The results showed that GlycanDIA can distinguish glycan composition and isomers from N-glycans, O-glycans, and human milk oligosaccharides (HMOs), while it also reveals information on low-abundant modified glycans. With the improved sensitivity, we performed experiments to profile N-glycans from RNA samples, which have been underrepresented due to their low abundance. Using this integrative workflow to unravel the N-glycan profile in cellular and tissue glycoRNA samples, we found that RNA-glycans have specific forms as compared to protein-glycans and are also tissue-specific differences, suggesting distinct functions in biological processes. Overall, GlycanDIA can provide comprehensive information for glycan identification and quantification, enabling researchers to obtain in-depth and refined details on the biological roles of glycosylation.

Clinical metabolomics characteristics of diabetic kidney disease: A meta-analysis of 1875 cases with diabetic kidney disease and 4503 controls.

AIMS: Diabetic Kidney Disease (DKD), one of the major complications of diabetes, is also a major cause of end-stage renal disease. Metabolomics can provide a unique metabolic profile of the disease and thus predict or diagnose the development of the disease. Therefore, this study summarises a more comprehensive set of clinical biomarkers related to DKD to identify functional metabolites significantly associated with the development of DKD and reveal their driving mechanisms for DKD. MATERIALS AND METHODS: We searched PubMed, Embase, the Cochrane Library and Web of Science databases through October 2022. A meta-analysis was conducted on untargeted or targeted metabolomics research data based on the strategy of standardized mean differences and the process of ratio of means as the effect size, respectively. We compared the changes in metabolite levels between the DKD patients and the controls and explored the source of heterogeneity through subgroup analyses, sensitivity analysis and meta-regression analysis. RESULTS: The 34 clinical-based metabolomics studies clarified the differential metabolites between DKD and controls, containing 4503 control subjects and 1875 patients with DKD. The results showed that a total of 60 common differential metabolites were found in both meta-analyses, of which 5 metabolites (p < 0.05) were identified as essential metabolites. Compared with the control group, metabolites glycine, aconitic acid, glycolic acid and uracil decreased significantly in DKD patients; cysteine was significantly higher. This indicates that amino acid metabolism, lipid metabolism and pyrimidine metabolism in DKD patients are disordered. CONCLUSIONS: We have identified 5 metabolites and metabolic pathways related to DKD which can serve as biomarkers or targets for disease prevention and drug therapy.