Education Department of Hunan Province

Alkaline phosphatase (ALP) activity serves as a crucial biomarker for livestock disease diagnosis, nutritional management, and the evaluation of milk pasteurization efficacy, holding significant implications for food safety and food science. In this study, we developed a novel method for detecting ALP activity in food samples, based on ATP hydrolysis coupled with a CRISPR/Cas12a system. The assay employs a DNA molecular recognition lock probe, comprising an ATP-specific aptamer and an activator strand designed to trigger the CRISPR/Cas12a trans-cleavage activity. In the absence of ALP, ATP acts as a trans-hydrolysis substrate to open the lock structure, releasing the activator strand. This subsequently activates the Cas12a protein, leading to the generation of a fluorescent signal. Conversely, when the target ALP is present, it catalyzes the hydrolysis of ATP via a dephosphorylation reaction. This prevents the opening of the "Aptamer-Activator" molecular lock, thereby inhibiting Cas12a activation and resulting in a corresponding decrease in fluorescence intensity. Under optimized conditions, the assay demonstrated a detection limit of 2.52mU/mL for ALP activity, with a linear range of 0-18.75mU/mL. The total detection time was 70min. The method was successfully applied to detect ALP activity in samples from various livestock (chickens, pigs, sheep, cattle) and in milk, achieving recovery rates between 92 and 99%. In conclusion, we have developed a sensitive, cost-effective, and rapid method for ALP detection. This work provides a promising strategy for the development of point-of-care testing (POCT) devices in food safety monitoring.

The MADS-box transcription factor SHORT VEGETATIVE PHASE (SVP) plays a pivotal role in flowering regulation. In this study, we aimed to elucidate the protein interaction network of LfSVP inLilium × formolongi. A high-quality yeast two-hybrid (Y2H) cDNA library was constructed and screened using LfSVP as bait. From an initial pool of 18 candidate interactors, six proteins were confirmed through pairwise Y2H assays. These include known floral regulatorsAPETALA1 (AP1),JASMONATE ZIM-DOMAIN (JAZ),SEUSS (SEU), andE3 ubiquitin-protein ligase ARI8 (ARI8), as well as stress-associated factorsWRKY5andSENSITIVE TO PROTON RHIZOTOXICITY1 (STOP1). Notably, virus-induced gene silencing (VIGS) demonstrated that LfSVP cooperates with LfAP1 to regulate floral organ development. While these findings suggest potential roles for LfSVP in flower development pathway, further functionalvalidation is required in planta to establish the biological relevance of most interactions identified here. This work provides a potentially foundational interaction network for LfSVP and highlights candidates for future functional studies in lily flowering regulation.

This study explores the application of artificial intelligence technology for the quantitative analysis of immunohistochemical markers to differentiate between mantle cell lymphoma and chronic lymphocytic leukaemia/small lymphocytic lymphoma. Utilizing an AI-based platform, the research analysed the expression of CD3, CD5, CD10, CD20, CD23, Cyclin D1, BCL-2, BCL-6 and Ki-67 in 91 samples from 84 patients. The findings demonstrate that, compared to manual interpretation, the AI system provides more objective, reproducible and accurate measurement results. Additionally, this study introduces a virtual dual immunohistochemical labelling technique for simultaneous antigen visualization. Although limited by its single-centre retrospective design, the research establishes a promising AI-assisted framework that enhances the accuracy, standardization and diagnostic efficiency in distinguishing between these two clinically distinct lymphomas.

The rumen microbiota plays a pivotal role in the growth performance of host animals, primarily due to its ability to ferment ingested feed. Hulunbuir sheep exhibited a slow growth rate compared to other local breeds. A deeper comprehension of the development of the rumen bacteria community in Hulunbuir sheep can offer insights into the factors contributing to their slow growth rate. This study utilized metagenomic analysis of rumen content samples from Hulunbuir sheep to investigate the patterns of microbial growth and their relationship with the ADG. The results of the PCoA and enterotype analyses demonstrated that the ruminal bacterial community developed distinct characteristics following weaning. The dominant bacterial phyla in the rumen of Hulunbuir sheep, Bacteroidetes and Firmicutes, exhibited a significant age-related change. At the genus level, while the abundance of dominant bacterial genera changed with the growth of Hulunbuir sheep, Prevotella consistently maintained a high abundance across all age time points. We then examined the effects of age on microbial function by analyzing carbohydrate-metabolizing enzymes and protein-metabolizing peptidases. The abundance of carbohydrate-metabolizing enzymes decreased with growth, while peptidases showed opposite dynamics. Under the current feeding conditions correlation analysis showed that the abundances of Firm-04, CAG-83, and GCA-900,199,385 were negatively correlated with ADG (R<-0.4, p < 0.05), while the abundance of Ga6A1 was positively correlated with ADG (R > 0.5, p < 0.05). In addition, we found 67 MAGs related to ADG, which are capable of secreting carbohydrates-metabolizing enzymes and peptidase. This study uncovers the temporal dynamics of rumen microbiota development during the early to late fattening phase and identifies microbes associated with ADG, which could inform strategies to improve growth and production efficiency.

Findings support tailored interventions for delivery riders, including vehicle checks, rider training, and infrastructure improvements near pedestrian crossings and bus stops.