Search PubMedSearch

subject

Milk

Milk: explore 2 source-linked works published from 2026 to 2026, with original documents and citations.

This collection is a preview while coverage and quality are evaluated.

Search within this collection

Coverage and selection

Includes records with this source-supplied label or an explicit phrase match in their metadata. Matches indicate a mention, not proof that a paper uses a method or tests a material. Source versions are consolidated by DOI.

Sources: pubmed. Collection updated 2026-09-15. Counts describe this index, not the complete source archives.

From buffalo to human: Klebsiella pneumoniae in high-somatic cell count milk as an overlooked link in the one health chain.

High somatic cell count (SCC) is a critical indicator of udder health and milk quality in buffalo milk production. However, in many low-income regions, SCC monitoring is often underemphasized, allowing a proportion of high-SCC buffalo milk to enter the food chain and potentially compromising food safety and public health. Klebsiella pneumoniae (K. pneumoniae) is a common zoonotic pathogen found in high-SCC milk, yet systematic investigations into the prevalence and characteristics in high-SCC buffalo milk remain limited. In this study, 23 K. pneumoniae strains were screened out from 460 bacterial isolates obtained from high-SCC buffalo milk samples from Guangxi, China, with an isolation rate of 5.0%. These isolates were comprehensively characterized using whole-genome sequencing and comparative genomic analyses. The results revealed that 78.26% (18/23) of the isolates shared high genomic similarity with the human reference strain ATCC 13883, and the ST37 clone exhibited a pronounced potential of cross-species transmission. All isolates harbored core adhesion factors and intrinsic resistance genes. Notably, several strains displayed high-risk features: strain 419 carried the K1 capsular serotype, strain 326 possessed a complete yersiniabactin synthesis gene cluster, and strain 320 exhibited a multidrug-resistant phenotype. Phenotypic assays further demonstrated a positive correlation between biofilm formation capacity and virulence in Galleria mellonella. Metabolic pathway enrichment analyses suggested that K. pneumoniae has undergone substantial adaptation to the nutrient-rich buffalo milk environment. Collectively, these findings confirm that raw high-SCC buffalo milk serves as a significant reservoir for high-risk zoonotic K. pneumoniae. While industrial thermal processing effectively eliminates viable pathogens, the resilient antimicrobial resistance determinants within these isolates pose a persistent risk of horizontal gene dissemination along the food chain, providing critical evidence for enhancing pre-processing milk quality regulations within a One Health framework.

Animals

Artificial neural network data fusion-mediated dual-mode sensor based on Fe3O4@PdIr for Salmonellatyphimurium detection in food.

Salmonella Typhimurium (S. typhimurium) is a major foodborne pathogen that poses a serious threat to public health. In this study, a colorimetric/electrochemical dual-mode biosensor assisted by artificial neural network (ANN) was developed for the sensitive detection of S. typhimurium. Fe3O4@PdIr nanocomposites with enhanced peroxidase-like activity and electrochemical performance were prepared and conjugated with an aptamer specific to S. typhimurium to obtain Fe3O4@PdIr-Apt. Through the sandwich binding of Fe3O4@PdIr-Apt and Apt to the target, the nanocomposites were attached to microplates or Au electrodes, thereby generating colorimetric and electrochemical signals. The ANN model deeply resolved the complex nonlinear relationship between the dual signals, enabling mutual correction and ultimately performing data fusion to output a single detection result, which significantly reduced the mean square error while improving detection sensitivity and reliability. This sensor exhibited a wide linear range of 2.7-2.7 × 108 CFU/mL and a low detection limit of 1.66 CFU/mL. Additionally, this method was successfully applied to the detection of S. typhimurium in pork and milk, with a recovery rate of 95.19% ∼ 104.07%. It indicated that the constructed sensor holds great practical potential for S. typhimurium detection.

Neural Networks, Computer
Compare source metadata on this page

These are bibliographic comparisons, not experimental rankings. Follow the original document for methods and conditions.