A CsEIL3-CsARN6.1 module promotes waterlogging-triggered adventitious root formation in cucumber by activating the expression of CsPrx5.

The formation of adventitious roots (ARs) derived from hypocotyl is the most important morphological adaptation to waterlogging stress in Cucumis sativus (cucumber). Our previous study showed that cucumbers with the gene CsARN6.1, encoding an AAA ATPase domain-containing protein, were more tolerant to waterlogging through increased AR formation. However, the apparent function of CsARN6.1 remained unknown. Here, we showed that the CsARN6.1 signal was predominantly observed throughout the cambium of hypocotyls, where de novo AR primordia are formed upon waterlogging treatment. The silencing of CsARN6.1 expression by virus-induced gene silencing and CRISPR/Cas9 technologies adversely affects the formation of ARs under conditions of waterlogging. Waterlogging treatment significantly induced ethylene production, thus upregulating CsEIL3 expression, which encodes a putative transcription factor involved in ethylene signaling. Furthermore, yeast one-hybrid, electrophoretic mobility assay and transient expression analyses showed that CsEIL3 binds directly to the CsARN6.1 promoter to initiate its expression. CsARN6.1 was found to interact with CsPrx5, a waterlogging-responsive class-III peroxidase that enhanced H2 O2 production and increased AR formation. These data provide insights into understanding the molecular mechanisms of AAA ATPase domain-containing protein and uncover a molecular mechanism that links ethylene signaling with the formation of ARs triggered by waterlogging.

XBP1 variant 1 promotes mitosis of cancer cells involving upregulation of the polyglutamylase TTLL6.

XBP1 variant 1 (Xv1) is the most abundant XBP1 variant and is highly enriched across cancer types but nearly none in normal tissues. Its expression is associated with poor patients' survival and is specifically required for survival of malignant cells, but the underlying mechanism is not known. Here we report that Xv1 upregulates the polyglutamylase tubulin tyrosine ligase-like 6 (TTLL6) and promotes mitosis of cancer cells. Like the canonical XBP1, Xv1 mRNA undergoes unconventional splicing by IRE1α under endoplasmic reticulum stress, but it is also constitutively spliced by IRE1ß. The spliced Xv1 mRNA encodes the active form of Xv1 protein (Xv1s). RNA sequencing in HeLa cells revealed that Xv1s overexpression regulates expression of genes that are not involved in the canonical unfolded protein response, including TTLL6 as a highly upregulated gene. Gel shift assay and chromatin immunoprecipitation revealed that Xv1s bind to the TTLL6 promoter region. Knockdown of TTLL6 caused death of cancer cells but not benign and normal cells, similar to the effects of knocking down Xv1. Moreover, overexpression of TTLL6 partially rescued BT474 cells from apoptosis induced by either TTLL6 or Xv1 knockdown, supporting TTLL6 as an essential downstream effector of Xv1 in regulating cancer cell survival. TTLL6 is localized in the mitotic spindle of cancer cells. Xv1 or TTLL6 knockdown resulted in decreased spindle polyglutamylation and interpolar spindle, as well as congression failure, mitotic arrest and cell death. These findings suggest that Xv1 is essential for cancer cell mitosis, which is mediated, at least in part, by increasing TTLL6 expression.

Cucumber abscisic acid 8'-hydroxylase Csyf2 regulates yellow flesh by modulating carotenoid biosynthesis.

Cucumber (Cucumis sativus L.) flesh is typically colorless or pale green. Flesh with yellow or orange pigment, determined mainly by carotenoid content and composition, is mostly found in semi-wild Xishuangbanna cucumber, which has a very narrow genetic background. Here, we identified a spontaneous cucumber mutant with yellow flesh (yf-343), which accumulated more ß-cryptoxanthin and less lutein than regular cultivated European glasshouse-type cucumbers. Genetic analysis revealed that the yellow flesh phenotype was controlled by a single recessive gene. Through fine mapping and gene sequencing, we identified the candidate gene C. sativus yellow flesh 2 (Csyf2), encoding an abscisic acid (ABA) 8'-hydroxylase. Overexpression and RNAi-silencing of Csyf2 in cucumber hairy roots produced lower and higher ABA contents than in non-transgenic controls, respectively. Further, RNA-seq analysis suggested that genes related to ABA signal transduction were differentially expressed in fruit flesh between yf-343 and its wild type, BY, with white flesh. The carotenoid biosynthesis pathway was specifically enriched in fruit flesh at 30 days after pollination when yf-343 fruit flesh turns yellow. Our findings highlight a promising target for gene editing to increase carotenoid content, expanding our genetic resources for pigmented cucumber flesh breeding for improving the nutritional quality of cucumber.

Characterization of alternative splicing events and prognostic signatures in gastric cancer.

BACKGROUND: Accumulating evidences indicate that the specific alternative splicing (AS) events are linked to the occurrence and prognosis of gastric cancer (GC). Nevertheless, the impact of AS is still unclear and needed to further elucidation. METHODS: The expression profile of GC and normal samples were downloaded from TCGA. AS events were achieved from SpliceSeq database. Cox regression together with LASSO analysis were employed to identify survival-associated AS events (SASEs) and calculate risk scores. PPI and pathway enrichment analysis were implemented to determine the function and pathways of these genes. Kaplan-Meier (K-M) analysis and Receiver Operating Characteristic Curves were used to evaluate the clinical significance of genes of SASEs. Q-PCR were applied to validate the hub genes on the survival prognosis in 47 GC samples. Drug sensitivity and immune cell infiltration analysis were conducted. RESULTS: In total, 48 140 AS events in 10 610 genes from 361 GC and 31 normal samples were analyzed. Through univariate Cox regression, 855 SASEs in 763 genes were screened out. Further, these SASEs were analyzed by PPI and 17 hub genes were identified. Meanwhile, using Lasso and multivariate Cox regression analysis, 135 SASEs in 132 genes related to 7 AS forms were further screened and a GC prognostic model was constructed. K-M curves indicates that high-risk group has poorer prognosis. And the nomogram analysis on the basis of the multivariate Cox analysis was disclosed the interrelationships between 7 AS forms and clinical parameters in the model. Five key genes were then screened out by PPI analysis and Differential Expression Gene analysis based on TCGA and Combined-dataset, namely STAT3, RAD51B, SOCS2, POLE2 and TSR1. The expression levels of AS in STAT3, RAD51B, SOCS2, POLE2 and TSR1 were all significantly correlated with survival by qPCR verification. Nineteen drugs were sensitized to high-risk patients and eight immune cells showed significantly different infiltration between the STAD and normal groups. CONCLUSIONS: In this research, the prognostic model constructed by SASEs can be applied to predict the prognosis of GC patients and the selected key genes are expected to become new biomarkers and therapeutical targets for GC treatment.

LncRNA RPARP-AS1 promotes the progression of osteosarcoma cells through regulating lipid metabolism.

Osteosarcoma (OS) is a highly malignant tumor, and its dysregulated lipid metabolism is associated with tumorigenesis and unfavorable prognosis. Interestingly, long noncoding RNAs (lncRNAs) have emerged as pivotal regulators of lipid metabolism, exerting notable impacts on tumor proliferation. Nevertheless, the involvement of RPARP-AS1, a novel lipid metabolism-associated lncRNA, remains unexplored in the context of OS. This study aims to identify functionally relevant lncRNAs impacting OS proliferation and lipid metabolism and seeks to shed light on the upstream regulatory mechanisms governing lipogenic enzyme activity. Based on comprehensive bioinformatic analysis and the establishment of a risk model, we identified seven lncRNAs significantly associated with clinical characteristics and lipid metabolism-related genes in patients with OS. Among these, RPARP-AS1 was selected for in-depth investigation regarding its roles in OS proliferation and lipid metabolism. Experimental techniques including RT-qPCR, Western blot, cell viability assay, assessment, and quantification of free fatty acids (FFAs) and triglycerides (TGs) were utilized to elucidate the functional significance of RPARP-AS1 in OS cells and validate its effects on lipid metabolism. Manipulation of RPARP-AS1 expression via ectopic expression or siRNA-mediated knockdown led to alterations in epithelial-mesenchymal transition (EMT) and expression of apoptosis-associated proteins, thereby influencing OS cell proliferation and apoptosis. Mechanistically, RPARP-AS1 was found to augment the expression of key lipogenic enzymes (FABP4, MAGL, and SCD1) and potentially modulate the Akt/mTOR pathway, thereby contributing to lipid metabolism (involving alterations in FFA and TG levels) in OS cells. Collectively, our findings establish RPARP-AS1 as a novel oncogene in OS cells and suggest its role in fostering tumor growth through the enhancement of lipid metabolism.

Acetylation of PGK1 at lysine 323 promotes glycolysis, cell proliferation, and metastasis in luminal A breast cancer cells.

BACKGROUND: In prior research employing iTRAQ (Isobaric Tags for Relative and Absolute Quantitation) technology, we identified a range of proteins in breast cancer tissues exhibiting high levels of acetylation. Despite this advancement, the specific functions and implications of these acetylated proteins in the context of cancer biology have yet to be elucidated. This study aims to systematically investigate the functional roles of these acetylated proteins with the objective of identifying potential therapeutic targets within breast cancer pathophysiology. METHODS: Acetylated targets were identified through bioinformatics, with their expression and acetylation subsequently confirmed. Proteomic analysis and validation studies identified potential acetyltransferases and deacetylases. We evaluated metabolic functions via assays for catalytic activity, glucose consumption, ATP levels, and lactate production. Cell proliferation and metastasis were assessed through viability, cycle analysis, clonogenic assays, PCNA uptake, wound healing, Transwell assays, and MMP/EMT marker detection. RESULTS: Acetylated proteins in breast cancer were primarily involved in metabolism, significantly impacting glycolysis and the tricarboxylic acid cycle. Notably, PGK1 showed the highest acetylation at lysine 323 and exhibited increased expression and acetylation across breast cancer tissues, particularly in T47D and MCF-7 cells. Notably, 18 varieties acetyltransferases or deacetylases were identified in T47D cells, among which p300 and Sirtuin3 were validated for their interaction with PGK1. Acetylation at 323 K enhanced PGK1's metabolic role by boosting its activity, glucose uptake, ATP production, and lactate output. This modification also promoted cell proliferation, as evidenced by increased viability, S phase ratio, clonality, and PCNA levels. Furthermore, PGK1-323 K acetylation facilitated metastasis, improving wound healing, cell invasion, and upregulating MMP2, MMP9, N-cadherin, and Vimentin while downregulating E-cadherin. CONCLUSION: PGK1-323 K acetylation was significantly elevated in T47D and MCF-7 luminal A breast cancer cells and this acetylation could be regulated by p300 and Sirtuin3. PGK1-323 K acetylation promoted cell glycolysis, proliferation, and metastasis, highlighting novel epigenetic targets for breast cancer therapy.

Characterization of a Novel Monoclonal Antibody with High Affinity and Specificity against Aflatoxins: A Discovery from Rosetta Antibody-Ligand Computational Simulation.

Aflatoxin B1 (AFB1) accumulates in crops, where it poses a threat to human health. To detect AFB1, anti-AFB1 monoclonal antibodies have been developed and are widely used. While the sensitivity and specificity of these antibodies have been extensively studied, information regarding the atomic-level docking of AFB1 (and its derivatives) with these antibodies is limited. Such information is crucial for understanding the key interactions that are required for high affinity and specificity in aflatoxin binding. First, a 3D comparative model of anti-AFB1 antibody (Ab-4B5G6) was predicted from the sequence using RosettaAntibody. We then utilized RosettaLigand to dock AFB1 onto ten homology models, producing a total of 10,000 binding modes. Interestingly, the best-scoring mode predicted strong interactions involving four sites within the heavy chain: ALA33, ASN52, HIS95, and TRP99. Importantly, these strong binding interactions exclusively involve the variable domain of the heavy chain. The best-scoring mode with AFB1 was also obtained through AF multimer combined with RosettaLigand, and two interactions at TRP and HIS were consistent with those found by Rosetta antibody-ligand computational simulation. The role of tryptophan in π interactions in antibodies was confirmed through mutation experiments, and the resulting mutant (W99A) exhibited a >1000-fold reduction in binding affinity for AFB1 and analogs, indicating the effect of tryptophan on the stability of CDR-H3 region. Additionally, we evaluated the binding of two glycolic acid-derived molecular derivatives (with impaired hydrogen bonding potential), and these derivatives (AFB2-GA and AFG2-GA) demonstrated a very weak binding affinity for Ab-4B5G6. The heavy chain was successfully isolated, and its sensitivity and specificity were consistent with those of the intact antibody. The homology models of variable heavy (VH) single-domain antibodies were established by RosettaAntibody, and the docking analysis revealed the same residues, including Ala, His, and Trp. Compared to the potential binding mode of fragment variable (FV) region, the results from a model of VH indicated that there are seven models involved in hydrophobic interaction with TYR32, which is usually referred to as polar amino acid and has both hydrophobic and hydrophilic features depending on the circumstances. Our work encompasses the entire process of Rosetta antibody-ligand computational simulation, highlighting the significance of variable heavy domain structural design in enhancing molecular interactions.

Development of Pd/In2O3 hybrid nanoclusters to optimize ethanol vapor sensing.

In this study, we successfully synthesize palladium-decorated indium trioxide (Pd/In2O3) hybrid nanoclusters (NCs) using an advanced dual-target cluster beam deposition (CBD) method, a significant stride in developing high-performance ethanol sensors. The prepared Pd/In2O3 hybrid NCs exhibit exceptional sensitivity, stability, and selectivity to low concentrations of ethanol vapor, with a maximum response value of 101.2 at an optimal operating temperature of 260 °C for 6 at% Pd loading. The dynamic response of the Pd/In2O3-based sensor shows an increase in response with increasing ethanol vapor concentrations within the range of 50 to 1000 ppm. The limit of detection is as low as 24 ppb. The sensor exhibits a high sensitivity of 28.24 ppm-1/2, with response and recovery times of 2.7 and 4.4 seconds, respectively, for 100 ppm ethanol vapor. Additionally, the sensor demonstrates excellent repeatability and stability, with only a minor decrease in response observed over 30 days and notable selectivity for ethanol compared to other common volatile organic compounds. The study highlights the potential of Pd/In2O3 NCs as promising materials for ethanol gas sensors, leveraging the unique capabilities of CBD for controlled synthesis and the catalytic properties of Pd for enhanced gas-sensing performance.

A genetic variant in the TAPBP gene enhances cervical cancer susceptibility by increasing m6A modification.

Genetic variants can affect gene expression by altering the level of N6-methyladenosine (m6A) modifications. A better understanding of the association of these genetic variants with susceptibility to cervical cancer (CC) can promote advances in disease screening and treatment. Genome-wide identification of m6A-associated functional SNPs for CC was performed using the TCGA and JENGER databases, incorporating the data from RNA-seq and MeRIP-seq. The screened risk-associated SNP rs1059288 (A>G), which is located in the 3' UTR of TAPBP, was further validated in a case-control study involving 921 cases and 1077 controls. The results revealed a significant association between rs1059288 and the risk of CC (OR 1.48, 95% CI 1.13-1.92). Mechanistically, the presence of the risk G allele of rs1059288 was associated with increased m6A modification of TAPBP compared with the A allele. This modification was facilitated by the m6A methyltransferase METTL14 and the reading protein YTHDF2. Immunohistochemical staining of tissue microarrays containing 61 CC and 45 normal tissues showed an overexpression of TAPBP in CC. Furthermore, the upregulation of TAPBP promoted the growth and migration of CC cells as well as tumor-forming ability, inhibited apoptosis, and conferred increased resistance to commonly used chemotherapeutic drugs such as bleomycin, cisplatin, and doxorubicin. Knockdown of TAPBP inhibited the JAK/STAT/MICB signaling pathway in CC cells and upregulated certain immune genes including ISG15, IRF3, PTPN6, and HLA-A. These findings offer insights into the involvement of genetic variations in TAPBP in the development and progression of CC.

Comprehensive Analysis of the SUMO-related Signature: Implication for Diagnosis, Prognosis, and Immune Therapeutic Approaches in Cervical Cancer.

SUMOylation, an important post-translational protein modification, plays a critical role in cancer development and immune processes. This study aimed to construct diagnostic and prognostic models for cervical cancer (CC) using SUMOylation-related genes (SRGs) and explore their implications for novel clinical therapies. We analyzed the expression profiles of SRGs in CC patients and identified 15 SRGs associated with CC occurrence. After the subsequent qPCR verification of 20 cases of cancer and adjacent tissues, 13 of the 15 SRGs were differentially expressed in cancer tissues. Additionally, we identified molecular markers associated with the prognosis and recurrence of CC patients, based on SRGs. Next, a SUMOScore, based on SRG expression patterns, was generated to stratify patients into different subgroups. The SUMOScore showed significant associations with the tumor microenvironment, immune function features, immune checkpoint expression, and immune evasion score in CC patients, highlighting the strong connection between SUMOylation factors and immune processes. In terms of immune therapy, our analysis identified specific chemotherapy drugs with higher sensitivity in the subgroups characterized by high and low SUMOScore, indicating potential treatment options. Furthermore, we conducted drug sensitivity analysis to evaluate the response of different patient subgroups to conventional chemotherapy drugs. Our findings revealed enrichment of immune-related pathways in the low-risk subgroup identified by the prognostic model. In conclusion, this study presents diagnostic and prognostic models based on SRGs, accompanied by a comprehensive index derived from SRGs expression patterns. These findings offer valuable insights for CC diagnosis, prognosis, treatment, and immune-related analysis.

Surviving a Double-Edged Sword: Response of Horticultural Crops to Multiple Abiotic Stressors.

Climate change-induced weather events, such as extreme temperatures, prolonged drought spells, or flooding, pose an enormous risk to crop productivity. Studies on the implications of multiple stresses may vary from those on a single stress. Usually, these stresses coincide, amplifying the extent of collateral damage and contributing to significant financial losses. The breadth of investigations focusing on the response of horticultural crops to a single abiotic stress is immense. However, the tolerance mechanisms of horticultural crops to multiple abiotic stresses remain poorly understood. In this review, we described the most prevalent types of abiotic stresses that occur simultaneously and discussed them in in-depth detail regarding the physiological and molecular responses of horticultural crops. In particular, we discussed the transcriptional, posttranscriptional, and metabolic responses of horticultural crops to multiple abiotic stresses. Strategies to breed multi-stress-resilient lines have been presented. Our manuscript presents an interesting amount of proposed knowledge that could be valuable in generating resilient genotypes for multiple stressors.

Construction of Nanofibrillar Networked Wood Aerogels Derived from Typical Softwood and Hardwood: A Comparative Study on the In Situ Formation Mechanism of Nanofibrillar Networks.

The construction of networks within natural wood (NW) lumens to produce porous wood aerogels (WAs) with fascinating characteristics of being lightweight, flexible, and porous is significant for the high value-added utilization of wood. Nonetheless, how wood species affect the structure and properties of WAs has not been comprehensively investigated. Herein, typical softwood of fir and hardwoods of poplar and balsa are employed to fabricate WAs with abundant nanofibrillar networks using the method of lignin removal and nanofibril's in situ regeneration. Benefiting from the avoidance of xylem ray restriction and the exposure of the cellulose framework, hardwood has a stronger tendency to form nanofibrillar networks compared to softwood. Specifically, a larger and more evenly distributed network structure is displayed in the lumens of balsa WAs (WA-3) with a low density (59 kg m-3), a high porosity (96%), and high compressive properties (strain = 40%; maximum stress = 0.42 MPa; height retention = 100%) because of the unique structure and properties of WA-3. Comparatively, the specific surface area (SSA) exhibits 25-, 27-, and 34-fold increments in the cases of fir WAs (WA-1), poplar WAs (WA-2), and WA-3. The formation of nanofibrillar networks depends on the low-density and thin cell walls of hardwood. This work offers a foundation for investigating the formation mechanisms of nanonetworks and for expanding the potential applications of WAs.

Construction of a hypoxia-immune-related prognostic model and targeted therapeutic strategies for cervical cancer.

Emerging evidence indicates that hypoxia and immunity play important roles in tumorigenesis and development. However, the hypoxia-immune-related prognostic risk model has not been established in cervical cancer (CC). We aimed to construct a hypoxia-immune-related prognostic risk model, which has potential application in predicting the prognosis of CC patients and the response to targeted therapy. The RNA-seq data and corresponding clinical information were retrieved from The Cancer Genome Atlas (TCGA) database. The hypoxia status and immune status of CC patients were evaluated using the Consensus Clustering method and single-sample gene set enrichment analysis (ssGSEA), respectively. The univariate Cox regression, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression were applied to establish the prognostic risk model of CC. The chemotherapy response for six chemotherapeutic agents of each CC patient was calculated according to the Genomics of Drug Sensitivity in Cancer (GDSC). And the Connectivity Map (CMap) database was performed to screen candidate small-molecule drugs. In this study, we identified seven gene signatures (P4HA2, MSMO1, EGLN1, ZNF316, IKZF3, ISCU and MYO1B) with prognostic values. And the survival time of patients with low risk was significantly longer than those with high risk. Meanwhile, CC patients in the high-risk group yielded higher sensitivity to five chemotherapeutic agents. And we listed 10 candidate small-molecule drugs that exhibited a high correlation with the prognosis of CC. Thus, the prognostic model can accurately predict the prognosis of patients with CC and may be helpful for the development of new hypoxia-immune prognostic markers and therapeutic strategies for CC.

Immune-Related Genes' Prognostic, Therapeutic and Diagnostic Value in Ovarian Cancer Immune-Related Gene Biomarker in Ovarian Cancer.

OBJECTIVES: The abnormal expression of immune-related genes (IRGs) plays an important role in the occurrence and progression of ovarian cancer (OC), which is the main cause of mortality among gynecological cancer patients. This study aims to establish a prognostic risk model and comprehensively analyze the relationship between OC risk score and prognosis, immune cell infiltration (ICI) and therapeutic sensitivity in OC. METHODS: We retrospectively evaluated the clinicopathological characteristics of consecutive OC patients in the Cancer Genome Atlas (TCGA) database. First, the prognostic risk model was constructed by bioinformatics methods. And then, we systematically assessed model robustness, and correlations between risk score and prognosis, and immune cell infiltration. The ICGC cohort was used to verify the prognostic risk model. Finally, we evaluated their value in the treatment of OC immunotherapy and chemotherapy. RESULTS: A total of 10 IRGs were identified to construct the prognostic risk model. Survival analysis revealed that patients in the low-risk group had a better prognosis (P < .01), and the risk score might be considered an independent predictor for predicting the prognosis. In addition, risk scores and patient clinical information were used to construct clinical nomograms, improving the prediction's precision. We also explored the relationship between the risk score and ICI, immunotherapy and drug sensitivity. CONCLUSIONS: Collectively, we identified a novel ten IRGs signature that may be applied as a prognostic predictor of OC, thereby benefiting clinical decision-making and personalized treatment of patients.

Applicability analysis of immunotherapy for lung cancer patients based on deep learning.

According to global and Chinese cancer statistics, lung cancer is the second most common cancer globally with the highest mortality rate and a severe threat to human life and health. In recent years, immunotherapy has made significant breakthroughs in the treatment of cancer patients. However, only 30% of patients are applicable and may have immune-related adverse events. The traditional immunological inspection methods have limitations and often can not obtain the expected benefits. Deep learning is a typical representation learning method that can spontaneously mine the hidden feature of effective classification from seas of data. In order to alleviate medical resources and reduce costs, this paper proposes a deep learning-based method to predict patients best suited for immune checkpoint blocking therapy from patients CT images. The deep immunotherapy analysis method proposed in this paper is divided into three steps:(1) Using LUNA16 public dataset to develop a deep learning model for nodule detection. (2) Nodule detection was performed on the Anti-PD-1_Lung dataset, and the effectiveness of immunotherapy was determined by comparing the detection results of nodules before and after immunotherapy. (3) After the data set was processed, the deep learning method trained and analyzed the Lung images. According to the experimental results and comparative analysis, the proposed deep immunotherapy analysis method has a good performance in the detection of nodules. It works for the predictions for the applicability of immunotherapy for lung cancer.1.

The relationship between body dissatisfaction, lifestyle, and nutritional status among university students in Southern China.

BACKGROUND: In recent years, obesity in early adulthood has become an urgent global public health concern. Body dissatisfaction may have adverse effects on lifestyle habits, leading to obesity. However, research on nutritional status and body dissatisfaction among Chinese young adults is still insufficient. Therefore, this study aimed to analyze the relationship between body dissatisfaction, dietary habits, physical activity, and nutritional status among university students. In addition, we explored the feasibility of improving university students' nutritional status by improving the levels of body dissatisfaction. METHODS: This study was conducted in Ganzhou City, Jiangxi Province, China, at a randomly selected university. All 1900 undergraduate students volunteered to participate and signed the consent form. Students were required to completed anthropometric measurements and three questionnaires, which included the Physical Activity Rating Scale-3 (PARS-3), Chinese version of the Dutch Dietary Behavior Questionnaire (C-DEBQ), and Body Dissatisfaction. Of these, 1714 students (age: 18-24 years; men: 933, women: 781) with complete and valid data were included. RESULTS: Higher obesity levels were observed in men compared to women (p<0.01). Meanwhile, body dissatisfaction was higher in women compared to men (p<0.01). Overeating and insufficient physical activity were more problematic in women compared to in men (p<0.01). Multiple regression analyses were conducted separately, with BMI and body dissatisfaction as the dependent variables. Body dissatisfaction (ß=0.72, p<0.01), muscle mass (ß=0.33, p<0.01), emotional eating score (ß=0.05, p<0.01), sex (ß=-0.05, p<0.05) and physical activity (ß=-0.04, p<0.05) score were significant predictors of obesity. Furthermore, Muscle mass (ß=0.61, p<0.01), sex (ß=0.54, p<0.01), restrained eating score (ß=0.25, p<0.01), physical activity score (ß=-0.20, p<0.01) and emotional eating score (ß=0.08, p<0.01) were significant predictors of body dissatisfaction. CONCLUSION: The data presented in this study highlight the impact of university students' body dissatisfaction in China on physical activity deficiency and overeating, discovering that reducing body dissatisfaction has great potential for preventing obesity.

Coherent Phononics of van der Waals Layers on Nanogratings.

Strain engineering can be used to control the physical properties of two-dimensional van der Waals (2D-vdW) crystals. Coherent phonons, which carry dynamical strain, could push strain engineering to control classical and quantum phenomena in the unexplored picosecond temporal and nanometer spatial regimes. This intriguing approach requires the use of coherent GHz and sub-THz 2D phonons. Here, we report on nanostructures that combine nanometer thick vdW layers and nanogratings. Using an ultrafast pump-probe technique, we generate and detect in-plane coherent phonons with frequency up to 40 GHz and hybrid flexural phonons with frequency up to 10 GHz. The latter arises from the periodic modulation of the elastic coupling of the vdW layer at the grooves and ridges of the nanograting. This creates a new type of a tailorable 2D periodic phononic nanoobject, a flexural phononic crystal, offering exciting prospects for the ultrafast manipulation of states in 2D materials in emerging quantum technologies.

Weakened Contractile Performance and Mitochondrial Respiratory Complex Activity in Skeletal Muscle Improve during Interbout Arousal in Hibernating Daurian Ground Squirrel, Spermophilus dauricus.

Mammalian hibernation is composed of multiple episodes of torpor bout, separated by phases of interbout arousal. During torpor, the skeletal muscles of mammals are undoubtedly inactive, but it has been proven to mitigate disuse atrophy. While interbout arousal has been implicated in the prevention of muscle atrophy, the underlying mechanisms sustaining muscle contraction remain to be explored. In the present study, Daurian ground squirrels (Spermophilus dauricus) were divided into four groups: pre-hibernation (PRE), torpor (TOR), interbout arousal (IBA), and post-hibernation (POST). The contractile performance of slow-twitch soleus muscle (SOL) and fast-twitch extensor digitorum longus muscle (EDL) was detected both in situ and in vitro. Concurrently, mitochondrial respiratory chain complex activity in these muscles was quantified. Our findings revealed that in situ contractile properties of both muscles, including force, power output, time duration, and force development/relaxation rates of twitch contraction, and force and power output of tetanic contraction declined in the TOR group compared to the PRE group, but improved in the IBA and POST groups. Fatigue resistance of muscles, determined by the power output of repetitive tetanic contractions in situ, decreased in the TOR group but recovered in the IBA and POST groups. In vitro studies demonstrated that tetanic contraction power output in isolated muscles increased with muscle temperature in both TOR and IBA groups. However, at the same temperature, power output was consistently lower in the TOR group compared to the IBA group. Moreover, the activity of the mitochondrial respiratory chain complex, especially Complexes I and II, decreased in the TOR group but showed recovery in the IBA and POST groups. These findings suggest that both the contractile performance and fatigue resistance of mammalian skeletal muscle are compromised during torpor but can be improved during interbout arousal and post-hibernation. The rebound in body temperature and rise in mitochondrial respiratory chain complex activity in skeletal muscle are involved in enhancing contractile performance and fatigue resistance. This study suggests that interbout arousal functions as a vital temporal interval during which skeletal muscles can transition from the inactivity induced by torpor to a state of restored contractile functionality. Thus, interbout arousal serves as a behavioral safeguard against disuse-induced damage to skeletal muscles during hibernation.

Degradation of deoxynivalenol in wheat by double dielectric barrier discharge cold plasma: identification and pathway of degradation products.

BACKGROUND: Deoxynivalenol (DON) produced during the onset of fusarium head blight not only affects the quality and safety of wheat but also causes serious harm to human and livestock health. However, due to the high stability of DON, it is difficult to eliminate it or reduce it naturally after it has been produced. Cold plasma technology is a non-thermophysical processing technology that has been widely used for microbial inactivation and mycotoxin degradation. In this study, the degradation efficiency of double dielectric barrier discharge (DDBD) cold plasma on DON in aqueous solution and wheat was studied; the structures of degradation products of DON and its pathway were clarified, and the effect of DDBD plasma on wheat quality was evaluated. RESULTS: Double dielectric barrier discharge cold plasma was used for efficient degradation of DON (0.5 ~ 5 µgmL^-1) solution and achieved a degradation rate of 98.94% within 25 min under the optimal conditions (voltage 100 V, frequency 200 Hz, duty cycle 80%). Furthermore, 10 degradation products (C15 H24 O5 , C15 H22 O6 , C15 H22 O9 , C16 H22 O7 , C15 H20 O7 , C15 H20 O9 , C15 H18 O8 , C15 H22 O5 , C16 H24 O5 , and C15 H18 O9 ) were identified by ultra-performance liquid chromatography-time of flight-mass spectrometry (UPLC-TOF-MS/MS) combined with Metabolitepilot and Peakview software. The degradation pathway of DON was obtained based on the chemical structures and accurate mass of these products. The DON degradation rate of 61% in wheat was achieved after treatment for 15 min, which slightly affects the moisture content, proteins, and wheat starch. CONCLUSION: Applying DDBD to wheat could effectively reduce the level of DON contamination, which provides a theoretical basis for applying cold plasma to the degradation of DON in wheat. © 2022 Society of Chemical Industry.

De novo assisted AFB1-Specific monoclonal antibody sequence assembly and comprehensive molecular characterization.

Despite their widely used and access as biological reagents in analytical methods, the detailed structural features for most of the antibodies were rarely known. Here, a new antibody for AFB1 with high specificity in constructing ELISA was studied in detail. The molecular structure and modification were elucidated mainly by nano-electrospray ionization mass spectrometry. The mass experiments, including MALDI-TOF MS, revealed complete and specific fragments, including antibody molecular weight, peptides, glycopeptide, and N-glycoform. By proteolytic treatment of pepsin and trypsin and high-resolution tandem-MS, the primary structure of the newly developed anti-AFB1 antibody was assembled by several rounds of Database search process assisted with the de novo results. The antibody CDR annotation and constraint-based multiple alignment tool were used to differentiate and align the sequences. The method uses only two proteases to generate numerous peptides for de novo sequencing. This artificial assembled AFB1-specific monoclonal antibody sequence was validated by comparison with the sequencing results of the immunoglobulin gene. The results showed that this method achieves full sequence coverage of anti-AFB1 monoclonal antibody, with an accuracy of 100% in the CDR regions of light chain and four amino acid mismatch in heavy chain. This simple and low-cost method was confirmed by treating a public dataset. The secondary structure information of intact antibody was also elucidated from the results of circular dichroism spectrum.