Distinct characteristics of social anxiety among youths with childhood sexual abuse: A latent profile analysis.

BACKGROUND: Childhood sexual abuse (CSA) is one type of childhood trauma that has long-term effects on physical and mental health, predisposing to social anxiety. OBJECTIVE: This study attempted to investigate the characteristics of different subgroups of social anxiety among youths with CSA experiences. PARTICIPANTS AND SETTING: 83,219 participants were recruited in a cross-sectional study from 63 colleges and universities in Jilin Province, China. METHODS: The main variables were measured by a series of self-report questionnaires. Latent profile analysis was used to classify different subgroups of social anxiety, and multiple logistic regression was employed to investigate factors influencing transitions between different subgroups. RESULTS: 3022 (3.63 %) youths who suffered from CSA (46.8 % were male, Mage = 19.57, SD = 1.76) could be divided into four subgroups of social anxiety: low-risk social anxiety (16.4 %), medium-risk social anxiety with high public speaking anxiety (30.3 %), medium-risk social anxiety with no prominent characteristics (22.9 %), and high-risk social anxiety (30.4 %). Shy bladder and bowel and virtual life orientation increased the level of social anxiety from low to medium and high risk. Smoking and drinking were more prevalent in the low- and medium-risk subgroups than in the high-risk subgroup. CONCLUSIONS: There was heterogeneity in different subgroups of social anxiety among youths with CSA experiences. Potential targeted prevention and intervention suggestions could be beneficial in mitigating the risk of social anxiety and further preventing the aggravation of risk between subgroups.

Viral replication organelles: the highly complex and programmed replication machinery.

Viral infections usually induce the rearrangement of cellular cytoskeletal proteins and organelle membrane structures, thus creating independent compartments [termed replication organelles (ROs)] to facilitate viral genome replication. Within the ROs, viral replicases, including polymerases, helicases, and ligases, play functional roles during viral replication. These viral replicases are pivotal in the virus life cycle, and numerous studies have demonstrated that the viral replicases could be the potential targets for drugs development. Here, we summarize primarily the key replicases within viral ROs and emphasize the advancements of antiviral drugs targeting crucial viral replicases, providing novel insights into the future development of antiviral strategies.

Molecular prevalence and subtype characteristics of Blastocystis among school children in Hainan, the tropical island province of China.

Blastocystis is one of the most common zoonotic intestinal protozoa with global distribution and can cause gastrointestinal syndrome mainly characterized by diarrhea. School children are the main susceptible population. No epidemiological data on Blastocystis among school children in Hainan, the only tropical island province in China. Between March 2021 and June 2023, 1973 fecal samples were collected from school children across three regions in Hainan province. Blastocystis was examined by amplifying the small subunit ribosomal RNA (SSU rRNA) gene via polymerase chain reaction (PCR), and subtypes were identified through DNA sequencing and phylogenetic analysis. The overall prevalence of Blastocystis was 7.3 % (144/1973). The differences in infection rates across different regions, nationalities, and educational stages are statistically significant (P < 0.001). Five subtypes were identified, of which ST3 was the dominant subtype (60.4 %; 87/144), followed by ST1 (27.8 %; 40/144), ST7 (10.4 %; 15/144), ST6 (0.7 %; 1/144), and ST2 (0.7 %; 1/144). 42 known sequences and 15 novel sequences were identified including eight new variations of the ST1 (ST1-16∼ST1-23) with similarities ranging from 98.3 % to 99.78 % and seven new variations of the ST7 (ST7-7∼ST7-13) with similarities ranging from 97.7 % to 99.79 % by intra-subtype genetic polymorphisms analysis. The results evaluate the public health risks of Blastocystis among school children in Hainan and the sources of infection were discussed, providing important basic data for the effective prevention and control of intestinal parasitic diseases in Hainan.

Revealing Dynamics of Protein Phosphorylation: A Study on the Cashmere Fineness Disparities in Liaoning Cashmere Goats.

Exploring the landscape of protein phosphorylation, this investigation focuses on skin samples from LCG (Liaoning Cashmere Goats), characterized by different levels of cashmere fineness. Employing LC-MS/MS technology, we meticulously scrutinized FT-LCG (fine-type Liaoning Cashmere Goats) and CT-LCG (coarse-type Liaoning Cashmere Goats). Identifying 512 modified proteins, encompassing 1368 phosphorylated peptide segments and 1376 quantifiable phosphorylation sites, our exploration further revealed consistent phosphorylation sites in both groups. Analysis of phosphorylated peptides unveiled kinase substrates, prominently featuring Protein Kinase C, Protein Kinase B and MAPK3-MAPK1-MAPK7-NLK-group. Differential analysis spotlighted 28 disparate proteins, comprising six upregulated and twenty-two downregulated. Cluster analysis showcased the robust clustering efficacy of the two sample groups. GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analyses underscored the significance of the purine metabolism pathway, suggesting its pivotal role in modulating cashmere fineness in LCG. Notably, through differential protein analysis, two crucial proteins were identified: HSL-X (hormone-sensitive lipase isoform X1) and KPRP (keratinocyte proline-rich protein). Further evidence supports LIPE and KPRP as key genes regulating cashmere fineness, paving the way for promising avenues in further research. These findings not only contribute to a nuanced understanding of protein-level dynamics in cashmere but also provide a theoretical foundation for the selective breeding of superior Liaoning Cashmere Goat strands.

More is not always better: revealing the impact of cumulative risk on health-promoting behaviors among miners and the mediating role of health beliefs.

OBJECTIVE: Health-promoting behaviors carry substantial significance for miners' overall health and well-being. This study aimed to examine the association between cumulative risk (CR) and miners' health-promoting behaviors and test the mediating role of health beliefs in this relationship. METHODS: Data were collected from a sequential survey conducted among 712 frontline miners (Mage=41.7 ± 10.1 years) in China. The survey entailed online questionnaire measurements at three distinct time points, each spaced two weeks apart. This study utilized the conceptual model of health-promoting behaviors, the CR model, and structural equation modeling in the analysis of relationships. RESULTS: CR was negatively related to health-promoting behaviors, with a negative acceleration effect. CR was positively associated with perceived threat in a gradient effect, while negatively associated with perceived benefits in a gradient effect. Furthermore, CR was negatively related to self-efficacy, following a negative acceleration effect. Perceived threat, perceived benefits, and self-efficacy emerged as significant mediators in the relationship between CR and health-promoting behaviors. CONCLUSION: This study highlights the critical role of considering both CR and health beliefs in shaping miners' health-promoting behaviors. Understanding these dynamics is pivotal for developing interventions to enhance miners' health and well-being.

Argonaute-2 autoantibodies: a promising biomarker for predicting mortality in HBV-related acute-on-chronic liver failure patients with cirrhosis.

Background & aims: HBV infection initiates autoimmune responses, leading to autoantibody generation. This research explores the role of autoantibodies in HBV-related Acute-on-Chronic Liver Failure (ACLF), offering novel perspectives for clinical management. Method: We applied immunoprecipitation and iTRAQ techniques to screen for autoantibodies in serum from HBV-related cirrhosis patients and conducted detection with conformation- stabilizing ELISA in a cohort of 238 HBV-infected individuals and 49 health controls. Our results were validated in a retrospective cohort comprising 106 ACLF patients and further assessed through immunohistochemical analysis in liver tissues from an additional 10 ACLF cases. Results: Utilizing iTRAQ, we identified Argonaute1-3 autoantibodies (AGO-Abs) in this research. AGO2-Abs notably increased in cirrhosis, decompensation, and further in ACLF, unlike AGO1-Abs and AGO3-Abs. This reflects disease severity correlation. Logistic regression and COX models confirmed AGO2-Abs as independent prognostic indicators for decompensated liver cirrhosis (DLC) and ACLF. In the ROC analysis, AGO2-Abs showed significant diagnostic value for predicting 28- and 90-day mortality (AUROC = 0.853 and 0.854, respectively). Furthermore, combining AGO2-Abs with the Child-Pugh, MELD, and AARC scores significantly improved their predictive accuracy (P < 0.05). Kaplan-Meier analysis showed poorer survival for AGO2-Abs levels above 99.14µg/ml. These findings were supported by a retrospective validation cohort. Additionally, immunohistochemistry revealed band-like AGO2 expression in periportal liver areas, with AGO2-Abs levels correlating with total bilirubin, indicating a potential role in exacerbating liver damage through periportal functions. Conclusions: AGO2-Abs is a robust biomarker for predicting the mortality of patients with HBV-related ACLF.

Latent relation shared learning for endometrial cancer diagnosis with incomplete multi-modality medical images.

Magnetic resonance imaging (MRI), ultrasound (US), and contrast-enhanced ultrasound (CEUS) can provide different image data about uterus, which have been used in the preoperative assessment of endometrial cancer. In practice, not all the patients have complete multi-modality medical images due to the high cost or long examination period. Most of the existing methods need to perform data cleansing or discard samples with missing modalities, which will influence the performance of the model. In this work, we propose an incomplete multi-modality images data fusion method based on latent relation shared to overcome this limitation. The shared space contains the common latent feature representation and modality-specific latent feature representation from the complete and incomplete multi-modality data, which jointly exploits both consistent and complementary information among multiple images. The experimental results show that our method outperforms the current representative approaches in terms of classification accuracy, sensitivity, specificity, and area under curve (AUC). Furthermore, our method performs well under varying imaging missing rates.

Rosiglitazone and trametinib exhibit potent anti-tumor activity in a mouse model of muscle invasive bladder cancer.

Muscle invasive bladder cancers (BCs) can be divided into 2 major subgroups-basal/squamous (BASQ) tumors and luminal tumors. Since Pparg has low or undetectable expression in BASQ tumors, we tested the effects of rosiglitazone, Pparg agonist, in a mouse model of BASQ BC. We find that rosiglitazone reduces proliferation while treatment with rosiglitazone plus trametinib, a MEK inhibitor, induces apoptosis and reduces tumor volume by 91% after 1 month. Rosiglitazone and trametinib also induce a shift from BASQ to luminal differentiation in tumors, which our analysis suggests is mediated by retinoid signaling, a pathway known to drive the luminal differentiation program. Our data suggest that rosiglitazone, trametinib, and retinoids, which are all FDA approved, may be clinically active in BASQ tumors in patients.

An integrated approach for discrimination of Magnoliae officinalis cortex before and after being processed by ginger juice combining LC/MS, GC/MS, intelligent sensors, and chemometrics.

INTRODUCTION: Magnoliae officinalis cortex (MOC) is an important traditional Chinese medicine (TCM), and both raw and stir-fried MOC were commonly used in clinic. OBJECTIVES: This study aimed to discriminate MOC and MOC stir-fried with ginger juice (MOCG) using an integrated approach combining liquid chromatography/mass spectrometry (LC/MS), gas chromatography/mass spectrometry (GC/MS), intelligent sensors, and chemometrics. METHODS: The sensory characters of the samples were digitalized using intelligent sensors, i.e., colorimeter, electronic nose, and electronic tongue. Meanwhile, the chemical profiles of the samples were analyzed using LC/MS and GC/MS methods. Chemometric models were constructed to discriminate samples of MOC and MOCG based on not only the sensory data but also the chemical data. RESULTS: The differential sensory characters (L* and b* from colorimeter, ANS from electronic tongue, W1S and W2S from electronic nose) and the differential chemical compounds (26 and 11 compounds from LC/MS and GC/MS, respectively) were discovered between MOC and MOCG. Furthermore, twelve differential compounds showed good relations with differential sensory characters. Finally, artificial neural network models were established to discriminate samples of MOC and MOCG, in which W1S, W2S, ANS, b*, and 10 differential compounds were among the top 10 important variables, respectively. CONCLUSION: Samples of MOC and MOCG can be discriminated not only by the digitalized data of color, taste, and scent detected by intelligent sensors but also by chemical information obtained from LC/MS and GC/MS using chemometrics. The variations in sensory characters and chemical compounds between MOC and MOCG partially resulted from the Maillard reaction products and the oxidation of some compounds in the stir-frying process.

Research progress on nonsteroidal anti-inflammatory drugs in the treatment of pituitary neuroendocrine tumors.

Pituitary neuroendocrine tumor is the third most common primary intracranial tumor. Its main clinical manifestations include abnormal hormone secretion symptoms, symptoms caused by tumor compression of the surrounding pituitary tissue, pituitary stroke, and other anterior pituitary dysfunction. Its pathogenesis is yet to be fully understood. Surgical treatment is still the main treatment. Despite complete resection, 10%-20% of tumors may recur. While dopamine agonists are effective in over 90% of prolactinomas, prolonged use and individual variations can lead to increased drug resistance and a gradual decline in efficacy, which ultimately requires surgical intervention. Nonsteroidal anti-inflammatory drugs reduce the production of inflammatory mediator prostaglandins by inhibiting the activity of cyclooxygenase and exert antipyretic, analgesic, antiplatelet, and anti-inflammatory effects. In recent years, many in-depth studies have confirmed the potential of nonsteroidal anti-inflammatory drugs as a preventive and antitumor agent. It has been extensively utilized in the prevention and treatment of various types of cancer. However, their specific mechanisms of action still need to be fully elucidated. This article summarizes recent research progress on the expression of cyclooxygenase in pituitary neuroendocrine tumors and the treatment of nonsteroidal anti-inflammatory drugs. It provides a feasible theoretical basis for further research on pituitary neuroendocrine tumors and explores potential therapeutic targets.

Evidence of a causal relationship between blood pressure and pathological scars: a bidirectional Mendelian randomization study.

Background: Recent advancements in basic medicine and epidemiology suggest a potential influence of blood pressure on scar formation, yet the specifics of this relationship are not fully understood. This study aims to clarify the causal link between blood pressure and the development of pathological scars using Mendelian randomization (MR). Methods: This study employed genetic variants closely linked to blood pressure as instrumental variables to explore the relationship between blood pressure and pathological scars. The inverse variance weighted (IVW) method was used for analysis. Results: Our analysis identified a notable association where higher blood pressure was correlated with a lower risk of pathological scars. Specifically, an increase in diastolic blood pressure (odds ratio [OR] per standard deviation increase: 0.67 [95% Confidence Interval [CI], 0.49-0.99]), systolic blood pressure (OR per standard deviation increase: 0.66 [95% CI, 0.46-0.93]), and hypertension (pooled OR: 0.39 [95% CI, 0.18-0.85]) were significantly associated with a reduced risk of keloids. Similarly, a genetic predisposition to hypertension (pooled OR: 0.31 [95% CI, 0.11-0.89]) was significantly associated with a reduced risk of hypertrophic scars. Neither reverse MR analysis nor Steiger's test indicated a significant reverse causal relationship between hypertension and either keloids or hypertrophic scars. Conclusion: The findings suggest a protective role of higher blood pressure against the development of pathological scars, including keloids and hypertrophic scars. However, the inconsistency observed across different MR methods warrants cautious interpretation and underscores the need for further investigation to confirm these findings.

Mapping Knowledge Landscapes and Emerging Trends in AI for Dementia Biomarkers: Bibliometric and Visualization Analysis.

BACKGROUND: With the rise of artificial intelligence (AI) in the field of dementia biomarker research, exploring its current developmental trends and research focuses has become increasingly important. This study, using literature data mining, analyzes and assesses the key contributions and development scale of AI in dementia biomarker research. OBJECTIVE: The aim of this study was to comprehensively evaluate the current state, hot topics, and future trends of AI in dementia biomarker research globally. METHODS: This study thoroughly analyzed the literature in the application of AI to dementia biomarkers across various dimensions, such as publication volume, authors, institutions, journals, and countries, based on the Web of Science Core Collection. In addition, scales, trends, and potential connections between AI and biomarkers were extracted and deeply analyzed through multiple expert panels. RESULTS: To date, the field includes 1070 publications across 362 journals, involving 74 countries and 1793 major research institutions, with a total of 6455 researchers. Notably, 69.41% (994/1432) of the researchers ceased their studies before 2019. The most prevalent algorithms used are support vector machines, random forests, and neural networks. Current research frequently focuses on biomarkers such as imaging biomarkers, cerebrospinal fluid biomarkers, genetic biomarkers, and blood biomarkers. Recent advances have highlighted significant discoveries in biomarkers related to imaging, genetics, and blood, with growth in studies on digital and ophthalmic biomarkers. CONCLUSIONS: The field is currently in a phase of stable development, receiving widespread attention from numerous countries, institutions, and researchers worldwide. Despite this, stable clusters of collaborative research have yet to be established, and there is a pressing need to enhance interdisciplinary collaboration. Algorithm development has shown prominence, especially the application of support vector machines and neural networks in imaging studies. Looking forward, newly discovered biomarkers are expected to undergo further validation, and new types, such as digital biomarkers, will garner increased research interest and attention.

DEPDC1B: A novel tumor suppressor gene associated with immune infiltration in colon adenocarcinoma.

BACKGROUND: Recent research indicates a positive correlation between DEP structural domain-containing 1B (DEPDC1B) and the cell cycle in various tumors. However, the role of DEPDC1B in the infiltration of the tumor immune microenvironment (TIME) remains unexplored. METHODS: We analyzed the differential expression and prognostic significance of DEPDC1B in colon adenocarcinoma (COAD) using the R package "limma" and the Gene Expression Profiling Interactive Analysis (GEPIA) website. Gene set enrichment analysis (GSEA) was employed to investigate the functions and interactions of DEPDC1B expression in COAD. Cell Counting Kit-8 (CCK-8) assays and colony formation assays were utilized to assess the proliferative function of DEPDC1B. Correlations between DEPDC1B expression and tumor-infiltrating immune cells, immune checkpoints, tumor mutational burden (TMB), and microsatellite instability (MSI) status were examined using Spearman correlation analysis and CIBERSORT. RESULTS: DEPDC1B was highly expressed in COAD. Elevated DEPDC1B expression was associated with lower epithelial-to-mesenchymal transition (EMT) and TNM stages, leading to a favorable prognosis. DEPDC1B mRNA was prominently expressed in COAD cell lines. CCK-8 and colony formation assays demonstrated that DEPDC1B inhibited the proliferation of COAD cells. Analysis using the CIBERSORT database and Spearman correlation revealed that DEPDC1B correlated with four types of tumor-infiltrating immune cells. Furthermore, high DEPDC1B expression was linked to the expression of PD-L1, CTLA4, SIGLEC15, PD-L2, TMB, and MSI-H. High DEPDC1B expression also indicated responsiveness to anti-PD-L1 immunotherapy. CONCLUSIONS: DEPDC1B inhibits the proliferation of COAD cells and positively regulates the cell cycle, showing a positive correlation with CCNB1 and PBK expression. DEPDC1B expression in COAD is associated with tumor-infiltrating immune cells, immune checkpoints, TMB, and MSI-H in the tumor immune microenvironment. This suggests that DEPDC1B may serve as a novel prognostic marker and a potential target for immunotherapy in COAD.

Postoperative facial prediction for mandibular defect based on surface mesh deformation.

OBJECTIVES: This study aims to introduce a novel predictive model for the post-operative facial contours of patients with mandibular defect, addressing limitations in current methodologies that fail to preserve geometric features and lack interpretability. METHODS: Utilizing surface mesh theory and deep learning, our model diverges from traditional point cloud approaches by employing surface triangular mesh grids. We extract latent variables using a Mesh Convolutional Restricted Boltzmann Machines (MCRBM) model to generate a three-dimensional deformation field, aiming to enhance geometric information preservation and interpretability. RESULTS: Experimental evaluations of our model demonstrate a prediction accuracy of 91.2 %, which represents a significant improvement over traditional machine learning-based methods. CONCLUSIONS: The proposed model offers a promising new tool for pre-operative planning in oral and maxillofacial surgery. It significantly enhances the accuracy of post-operative facial contour predictions for mandibular defect reconstructions, providing substantial advancements over previous approaches.

Development and evaluation of a triplex droplet digital PCR method for differentiation of M. tuberculosis, M. bovis and BCG.

Introduction: Tuberculosis, caused by Mycobacterium tuberculosis complex (MTBC), remains a global health concern in both human and animals. However, the absence of rapid, accurate, and highly sensitive detection methods to differentiate the major pathogens of MTBC, including M. tuberculosis, M. bovis, and BCG, poses a potential challenge. Methods: In this study, we have established a triplex droplet digital polymerase chain reaction (ddPCR) method employing three types of probe fluorophores, with targets M. tuberculosis (targeting CFP-10-ESAT-6 gene of RD1 and Rv0222 genes of RD4), M. bovis (targeting CFP-10-ESATs-6 gene of RD1), and BCG (targeting Rv3871 and Rv3879c genes of ΔRD1), respectively. Results: Based on optimization of annealing temperature, sensitivity and repeatability, this method demonstrates a lower limit of detection (LOD) as 3.08 copies/reaction for M. tuberculosis, 4.47 copies/reaction for M. bovis and 3.59 copies/reaction for BCG, without cross-reaction to Mannheimia haemolytica, Mycoplasma bovis, Haemophilus parasuis, Escherichia coli, Pasteurella multocida, Ochrobactrum anthropi, Salmonella choleraesuis, Brucella melitensis, and Staphylococcus aureus, and showed repeatability with coefficients of variation (CV) lower than 10%. The method exhibits strong milk sample tolerance, the LOD of detecting in spike milk was 5 × 103 CFU/mL, which sensitivity is ten times higher than the triplex qPCR. 60 clinical DNA samples, including 20 milk, 20 tissue and 20 swab samples, were kept in China Animal Health and Epidemiology Center were tested by the triplex ddPCR and triplex qPCR. The triplex ddPCR presented a higher sensitivity (11.67%, 7/60) than that of the triplex qPCR method (8.33%, 5/60). The positive rates of M. tuberculosis, M. bovis, and BCG were 1.67, 10, and 0% by triplex ddPCR, and 1.67, 6.67, and 0% by triplex qPCR, with coincidence rates of 100, 96.7, and 100%, respectively. Discussion: Our data demonstrate that the established triplex ddPCR method is a sensitive, specific and rapid method for differentiation and identification of M. tuberculosis, M. bovis, and BCG.

Molecular Bidents with Two Electrophilic Warheads as a New Pharmacological Modality.

A systematic strategy to develop dual-warhead inhibitors is introduced to circumvent the limitations of conventional covalent inhibitors such as vulnerability to mutations of the corresponding nucleophilic residue. Currently, all FDA-approved covalent small molecules feature one electrophile, leaving open a facile route to acquired resistance. We conducted a systematic analysis of human proteins in the protein data bank to reveal ∼400 unique targets amendable to dual covalent inhibitors, which we term "molecular bidents". We demonstrated this strategy by targeting two kinases: MKK7 and EGFR. The designed compounds, ZNL-8162 and ZNL-0056, are ATP-competitive inhibitors that form two covalent bonds with cysteines and retain potency against single cysteine mutants. Therefore, molecular bidents represent a new pharmacological modality with the potential for improved selectivity, potency, and drug resistance profile.

Rapid and Amplification-free Nucleic Acid Detection with DNA Substrate-Mediated Autocatalysis of CRISPR/Cas12a.

To enable rapid and accurate point-of-care DNA detection, we have developed a single-step, amplification-free nucleic acid detection platform, a DNA substrate-mediated autocatalysis of CRISPR/Cas12a (DSAC). DSAC makes use of the trans-cleavage activity of Cas12a and target template-activated DNA substrate for dual signal amplifications. DSAC employs two distinct DNA substrate types: one that enhances signal amplification and the other that negatively modulates fluorescent signals. The positive inducer utilizes nicked- or loop-based DNA substrates to activate CRISPR/Cas12a, initiating trans-cleavage activity in a positive feedback loop, ultimately amplifying the fluorescent signals. The negative modulator, which involves competitor-based DNA substrates, competes with the probes for trans-cleaving, resulting in a signal decline in the presence of target DNA. These DNA substrate-based DSAC systems were adapted to fluorescence-based and paper-based lateral flow strip detection platforms. Our DSAC system accurately detected African swine fever virus (ASFV) in swine's blood samples at femtomolar sensitivity within 20 min. In contrast to the existing amplification-free CRISPR/Dx platforms, DSAC offers a cost-effective and straightforward detection method, requiring only the addition of a rationally designed DNA oligonucleotide. Notably, a common ASFV sequence-encoded DNA substrate can be directly applied to detect human nucleic acids through a dual crRNA targeting system. Consequently, our single-step DSAC system presents an alternative point-of-care diagnostic tool for the sensitive, accurate, and timely diagnosis of viral infections with potential applicability to human disease detection.

Application of slow-controlled release fertilizer coordinates the carbon flow in carbon-nitrogen metabolism to effect rice quality.

Slow-controlled release fertilizers are experiencing a popularity in rice cultivation due to their effectiveness in yield and quality with low environmental costs. However, the underlying mechanism by which these fertilizers regulate grain quality remains inadequately understood. This study investigated the effects of five fertilizer management practices on rice yield and quality in a two-year field experiment: CK, conventional fertilization, and four applications of slow-controlled release fertilizer (UF, urea formaldehyde; SCU, sulfur-coated urea; PCU, polymer-coated urea; BBF, controlled-release bulk blending fertilizer). In 2020 and 2021, the yields of UF and SCU groups showed significant decreases when compared to conventional fertilization, accompanied by a decline in nutritional quality. Additionally, PCU group exhibited poorer cooking and eating qualities. However, BBF group achieved increases in both yield (10.8 t hm-2 and 11.0 t hm-2) and grain quality reaching the level of CK group. The adequate nitrogen supply in PCU group during the grain-filling stage led to a greater capacity for the accumulation of proteins and amino acids in the PCU group compared to starch accumulation. Intriguingly, BBF group showed better carbon-nitrogen metabolism than that of PCU group. The optimal nitrogen supply present in BBF group suitable boosted the synthesis of amino acids involved in the glycolysis/ tricarboxylic acid cycle, thereby effectively coordinating carbon-nitrogen metabolism. The application of the new slow-controlled release fertilizer, BBF, is advantageous in regulating the carbon flow in the carbon-nitrogen metabolism to enhance rice quality.

Production and evaluation of anti-BP26 monoclonal antibodies for the serological detection of animal brucellosis.

Brucella BP26 proves to be a highly immunogenic antigen with excellent specificity in brucellosis detection. In China, the authorized use of the Bp26-deleted vaccine M5ΔBP26 for preventing small ruminant brucellosis highlights the importance of developing accurate detection methods targeting BP26, particularly for the diagnosis of differentiation between infected and vaccinated animals (DIVA). Using the traditional mouse hybridoma technique, we successfully obtained 12 monoclonal antibodies (mAbs) targeting BP26. The efficacy of these mAbs in detecting various animal brucellosis cases using the competitive ELISA method was evaluated. Among them, only the E10 mAb exhibited significant efficiency, being inhibited by 100, 97.62, and 100% of brucellosis-positive sera from cattle, small ruminants, and canines, respectively. The E10-based competitive enzyme-linked immunosorbent assay (cELISA) outperformed the BP26-based indirect enzyme-linked immunosorbent assay (iELISA) in accuracy, particularly for cattle and small ruminant brucellosis, with cELISA sensitivity reaching 97.62% compared to 64.29% for iELISA for small ruminants. Although cELISA showed slightly lower specificity than iELISA, it still maintained high accuracy in canine brucellosis detection. The epitope of mAb E10 was identified in the amino acid sequence QPIYVYPDDKNNLKEPTITGY, suggesting its potential as a diagnostic antigen for brucellosis. In conclusion, the E10-based cELISA presents an effective means of detecting animal brucellosis, particularly significant for DIVA diagnosis in China, where the BP26-mutant vaccine is widely used.