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Saliva-based RT-LAMP assays support heat shock protein 70 as a promising transcript marker for estrus identification in buffaloes.

Buffaloes do not exhibit overt estrus signs particularly during summer, leading to a significant economic loss to farmers. Previous studies have identified several candidate transcripts (HSP70, TIMP1, TLR4 and HSD17B1), abundant in buffalo saliva during estrus stage. However, there is no widely applicable technology for estrus detection targeting these transcripts. Therefore, the present study aimed to develop reverse transcription loop mediated isothermal amplification (RT-LAMP) assays for these candidate transcripts using buffalo saliva. Saliva samples were collected from 10 cyclic buffaloes and RT-LAMP assays were optimized for salivary RNA as well as direct saliva. Among the four candidate transcripts, HSP70 showed a statistically significant colour change (p-value = 0.0191) at the estrus stage compared to the diestrus stage. This abundance of HSP70 was also supported in large simulated population datasets (10,000 animals) generated using R. Further, the RT-LAMP assays were tested using direct saliva without RNA isolation, and the colour change in the samples during estrus suggested the feasibility of estrus identification using direct saliva, overcoming the tedious step of RNA isolation. The detection of HSP70 using either direct saliva or salivary RNA indicated its potential as a marker for estrus identification. Similarly, TLR4 appeared to be another potential biomarker for RT-LAMP reaction using direct saliva, but it needs further validation in both RNA and direct saliva samples. Overall, the proof-of-concept on RT-LAMP assays optimized for salivary transcripts in the present study would be useful for estrus identification in tropical production systems following further validation on a larger sample size.

Animals

First evaluation of a novel recombinant eCG molecule in ewes reveals a discrepancy between ovulatory response and pregnancy outcome.

This study evaluated the reproductive performance and clinical safety of a novel recombinant eCG (r-eCG) in ewes. Two weeks prior to study onset (Day 0: intravaginal progesterone device insertion), 45 ewes were randomly assigned to negative control (NC; no eCG; n&#x202f;=&#x202f;10), positive control (PC; 400IU commercial non-recombinant eCG; n&#x202f;=&#x202f;20), or treatment group (T; 400IU r-eCG; n&#x202f;=&#x202f;15). Ewes were inseminated with fresh-diluted semen (200&#x202f;&#xd7;&#x202f;106 sperm). Ultrasonography assessed follicle count/diameter (days 11, 13), ovulation (day 13), corpus luteum (CL) number/characteristics (day 20), and pregnancy (day 44). Serum progesterone was measured on day 20; Group T underwent clinical/hematological evaluations (days 0, 20, and 44). Estrus signs were more frequent (P&#x202f;<&#x202f;0.01) in T (100%) than NC (50%), while PC (85%) did not differ. Ovulation rates were similar between T (93%) and PC (95%), but higher than NC (50%; P&#x202f;<&#x202f;0.05). On day 13, largest follicle diameter did not differ (P&#x202f;>&#x202f;0.05) among groups; however, fewer follicles > 2&#x202f;mm occurred in PC than NC and T (P&#x202f;<&#x202f;0.05). CL number was higher in T than PC (2.0&#x202f;&#xb1;&#x202f;0.3 vs. 1.0&#x202f;&#xb1;&#x202f;0.0, P&#x202f;<&#x202f;0.01), while NC did not differ (1.0&#x202f;&#xb1;&#x202f;0.25). Conversely, pregnancy rate was higher (P&#x202f;<&#x202f;0.05) in PC (70%) than T (28.6%) and NC (20%). Among ovulated ewes, progesterone concentration and progesterone/CL ratio did not differ among groups (P&#x202f;=&#x202f;0.92 and P&#x202f;=&#x202f;0.08, respectively). No relevant r-eCG-related clinical or hematological alterations occurred. In conclusion, 400IU r-eCG effectively induces estrus and ovulation without adverse effects; however, the discrepancy between ovulatory response and pregnancy rate underscores the need for further study refinement to improve fertility.

Animals

A MIL-88@Ru-based molecularly imprinted electrochemiluminescence sensor for highly selective and sensitive detection of enrofloxacin residues in animal-derived foods.

Using a metal-organic framework (MOF) - supported Ru(bpy)32+ (MIL-88@Ru) composite luminescent material, this study innovatively adopted electropolymerization to fabricate a molecularly imprinted polymer-based electrochemiluminescent (MIP-ECL) sensor for enrofloxacin (ENR) detection in animal-derived foods. Systematic investigation of the ECL luminescence and ENR's quenching mechanism confirmed that the sensor integrates ECL's high sensitivity and MIP's high specificity, enabling rapid and accurate recognition of ENR. Experimental results show a good linear response in the range of 1&#xa0;nmol/L-20&#xa0;&#x3bc;mol/L (R2&#xa0;=&#xa0;0.99), a limit of detection (LOD) as low as 0.28&#xa0;nmol/L, as well as excellent selectivity and stability. Recoveries of ENR in all investigated matrices ranged from 97.7% to 106.4%, confirming the reliability of the established method. This ECL-MIP coupling strategy provides a new technical approach and application references for the efficient detection of trace pollutants in food safety and environmental monitoring fields.

Enrofloxacin

An RPA-assisted homogeneous electrochemical DNA sensor for on-site eDNA detection toward early warning of crown-of-thorns starfish outbreaks.

Crown-of-thorns starfish (COTS) outbreaks seriously threaten coral reef ecosystems, while conventional monitoring approaches are time-consuming and often lack sufficient sensitivity for early warning. Existing electrochemical DNA sensors usually require complex electrode-surface immobilization procedures, which can lead to uneven probe distribution, significant steric hindrance, and poor stability. Meanwhile, the low concentration of environmental DNA (eDNA) in marine environments further complicates detection. To overcome these challenges, this study developed a homogeneous electrochemical DNA sensor assisted by recombinase polymerase amplification (RPA) for COTS eDNA detection. Target DNA was first amplified by RPA, and the amplification products were then hybridized in solution with capture probe (CP)-modified magnetic beads (MB) and biotin-labeled signal probe (SP) to form sandwich-structured MB complexes. These complexes were subsequently magnetically enriched and immobilized on the electrode surface for electrochemical signal readout. Under optimized conditions, the sensor displayed a linear response to COTS genomic DNA from 3.77&#xa0;fg/&#x3bc;L to 1&#xa0;ng/&#x3bc;L, with an LOD of 2.02&#xa0;fg/&#x3bc;L and an LOQ of 3.77&#xa0;fg/&#x3bc;L. The sensor was applied to Xisha Islands samples, and the results agreed with droplet digital PCR (ddPCR) (P&#xa0;>&#xa0;0.05), demonstrating its potential for sensitive and reliable on-site COTS eDNA detection.

Animals

PdIr bimetallic nanozyme engineered metal-organic frameworks integrated dual-mode sensor toward Stx2 detection in food.

Shiga toxin II (Stx2) has attracted extensive attention due to its toxicity and pathogenicity, making the development of sensitive detection methods urgent. This study constructed a dual-mode sensing platform for the sensitive detection of Stx2 in food. Composite material UIO-66@PdIr with peroxidase-like activity and fluorescent properties was synthesized and combined with cDNA as the signal probe, while aptamer-modified magnetic beads served as the capture probe. Specific binding of Stx2 to the aptamer triggered the release of the signal probe, enabling colorimetric and fluorescence signal readout. The colorimetric mode showed a linear range of 0.05-100&#xa0;ng/mL with an LOD of 0.039&#xa0;ng/mL, and the fluorescence mode exhibited 0.01-1000&#xa0;ng/mL with an LOD of 0.0097&#xa0;ng/mL. Additionally, this method was successfully applied to the detection of Stx2 in food, and the recovery rates were 94.33%&#xa0;&#x223c;&#xa0;102.20%. It indicated that the constructed sensor holds great practical potential for Stx2 detection.

Food Contamination

Dual signal-enhanced immunochromatographic test strip based on Au@PtNPs: From sensitive detection of thiamethoxam to multiplex pesticide screening in vegetables.

Immunochromatographic test strip (ICTS) is a rapid analytical technique widely used in environmental and food detection owing to its merits of simple operation and short analysis time. Herein, three-dimensional nanoflower-structured gold&#x2011;platinum nanoparticles (Au@PtNPs) were synthesized via a seed-growth method. Compared with conventional gold nanoparticles (AuNPs), Au@PtNPs exhibited stronger signal intensity, excellent catalytic performance, and efficient antibody binding efficiency. Colorimetric Au@PtNPs-ICTS and catalytic colorimetric Au@PtNPs-ICTS were developed for the sensitive detection of thiamethoxam (THI) in vegetables. The limits of detection (LODs) for colorimetric Au@PtNPs-ICTS and catalytic colorimetric Au@PtNPs-ICTS quantitative analysis were 0.18&#xa0;ng/mL and 0.093&#xa0;ng/mL, respectively, representing approximately 3-fold and 6-fold improvement compared to AuNPs-ICTS (0.56&#xa0;ng/mL). Furthermore, highly sensitive detection of multiple pesticide residues (chlorpyrifos, acetamiprid, and imidacloprid) was achieved by replacing the corresponding target antigens and antibodies, which further verified the universality of this immunochromatographic strategy.

Thiamethoxam

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&#xa0;&#xd7;&#xa0;108&#xa0;CFU/mL and a low detection limit of 1.66&#xa0;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%&#xa0;&#x223c;&#xa0;104.07%. It indicated that the constructed sensor holds great practical potential for S. typhimurium detection.

Neural Networks, Computer

Peptide molecular lock-engineered nanobodies enable an oriented dual-modal immunoassay for reliable detection of Cronobacter sakazakii.

Conventional nanobody ELISAs for trace Cronobacter sakazakii in powdered infant formula suffer from random orientation and low signal output. We developed an oriented dual-modal immunoassay that combines site-specific biotinylation via a C-terminal AviTag and a peptide molecular lock, enabling controlled surface orientation while preserving nanobody structural integrity. This strategy was further integrated with phage-displayed nanobodies for multivalent amplification and both fluorescent and colorimetric readouts. The assay exhibited a broad linear range of 103-106&#xa0;CFU/mL, with limits of detection (LODs) of 6.70&#xa0;&#xd7;&#xa0;102&#xa0;CFU/mL for fluorescence and 1.55&#xa0;&#xd7;&#xa0;103&#xa0;CFU/mL for colorimetry, showing improved sensitivity compared with the conventional passive adsorption-based Nb-ELISA evaluated in this study. XGBoost-based multimodal fusion improved quantitative accuracy, and SHAP analysis elucidated modality contributions. In spiked powdered infant formula samples, recoveries ranged from 92.1% to 118% with coefficients of variation below 5.98%, confirming acceptable matrix tolerance and analytical reliability.

Cronobacter sakazakii

Assessing the threat of Bacillus cereus: From toxin characterization to modern detection strategies.

Bacillus cereus is a spore-forming pathogen responsible for both diarrheal and emetic foodborne illnesses worldwide. Its significance in food safety has received growing attention. Recent advances, including the discovery of novel virulence factors and the development of emerging detection technologies, have provided new insights into its pathogenic mechanisms and surveillance strategies. This review critically examines the global burden of B. cereus infections, and molecular mechanisms of its major virulence factors, and the performance characteristics of current detection knowledge gaps such as the viable-but-non-culturable state and regulatory blind spots for emetic toxins, and discuss unresolved challenges in clinical management. By integrating epidemiological, microbiological, and technological perspectives with critical lens, this review aims to provide a valuable reference for future research and food safety practices.

Bacillus cereus

Spatially confined electrochemical strategy with DNA-assembled nanogaps for SNP detection.

Accurate detection of low-abundance single nucleotide polymorphisms (SNPs) against a large excess of homologous wild-type sequences requires both selective molecular recognition and effective transduction of small sequence differences into measurable signals. Here, we report a spatially confined electrochemical strategy that couples sequence-selective recognition with size-dependent mass-transport gating. DNA-hybridization-driven self-assembly of gold nanoparticles (AuNPs) forms a three-dimensional self-assembled electrode (3D-SAE) with a DNA-defined interparticle architecture. Competitive probes (SP/WP) convert single-base recognition into distinct molecular-size states: the SNP-associated pathway preferentially triggers a hybridization chain reaction (HCR), generating bulky AuNP-anchored HCR/methylene blue complexes (Au@HCR/MB) with reduced electrochemical accessibility through the porous 3D-SAE, whereas the wild-type pathway does not trigger HCR and maintains a high-current response from more readily accessible MB-containing species. Thus, sequence recognition is translated into a molecular-size difference and subsequently into an electrochemical signal through differential mass transport. Under buffer conditions, the platform achieved a statistically estimated detection limit of &#x223c;0.47&#x202f;fM and a quantitative range of 1&#x202f;fM-100 pM. It discriminated a 0.1% mutant abundance in a fragmented genomic-DNA background. The downstream signal-transduction chemistry is enzyme-free and isothermal. This work establishes a mechanistical recognition-size-conversion-mass-transport-gating architecture for electrochemical nucleic acid analysis.

Polymorphism, Single Nucleotide

Machine learning-assisted Mn-N-C nanozyme colorimetric sensor array for trace-level detection of biogenic amines in meat.

Accurate detection of biogenic amines (BAs) in meat remains challenging due to their high structural similarity and co-occurrence. Herein, an Mn-N-C nanozyme was synthesized via a metal-organic framework confined pyrolysis strategy, possessing excellent oxidase (OXD)- and peroxidase (POD)-like activities. The dual enzyme-like activity showed Km values of 0.1584&#xa0;mM (OXD) and 0.1498&#xa0;mM (POD), respectively, in detection system. Leveraging these properties, a colorimetric sensor array was constructed, enabling the detection of four representative BAs within a concentration range of 2-10&#xa0;ppm with 100% classification accuracy. In addition, a concentration independent recognition model based on an artificial neural network was developed to address signal nonlinearity interference in meat. The integrated system achieved accurate trace-level identification of BAs in perishable fish, pork, and chicken, demonstrating its applicability for early-stage BAs monitoring and quality deterioration warning during storage and transportation.

Biogenic Amines

Viral surveillance beyond detection: JMTV and the need for ensemble approaches in emerging virus discovery.

The recent report by T. Murillo, L. E. Enrique Chaves-Gonz&#xe1;lez, S. Temmam, S. Berm&#xfa;dez, et al. (Microbiol Spectr 14:e04078-25, 2026, https://doi.org/10.1128/spectrum.04078-25) expands the known geographic and ecological range of Jingmen tick virus (JMTV) by detecting the virus in Amblyomma mixtum ticks collected from horses in Costa Rica. This is an important finding because A. mixtum can feed on wildlife, domestic animals, and humans, creating a possible interface for virus movement across various hosts. The study also places the Costa Rican virus in a wider phylogenetic context, linking it to JMTV diversity reported from other regions. However, the detection of viral RNA in ticks should not be interpreted as proof of local disease, human infection, or active transmission, especially in the absence of supporting results. Instead, it reflects an important signal for careful viral surveillance. Here, I discuss how JMTV illustrates the need for ensemble approaches that combine field sampling, phylogeny, segment-level genome analysis, serology, experimental validation, and data-driven virus discovery tools.

emerging viruses

Simultaneous determination of imiquimod and terbinafine in skin permeation studies: Validation of a liquid chromatography method with fluorescence detection.

Chromoblastomycosis is a chronic, neglected subcutaneous mycosis posing significant therapeutic challenges. A topical strategy combining terbinafine (TBF), an antifungal, with imiquimod (IMQ), a TLR-7/8 agonist immunomodulator, has emerged a promising alternative. However, no validated analytical method is currently available to simultaneously quantify both drugs in skin, which is crucial for novel formulation development. This study reports the development and validation of a simple HPLC method with fluorescence detection (excitation 236&#xa0;nm, emission 340&#xa0;nm) for the simultaneous determination of TBF and IMQ extracted from porcine skin. Separation was achieved on a C8 reversed-phase column (125&#xa0;&#xd7;&#xa0;4.0&#xa0;mm, 5&#xa0;&#x3bc;m) using a mobile phase of methanol and water (60,40, v/v), both containing 0.1% formic acid at a flow rate of 0.8&#xa0;mL/min. The method showed excellent linearity (r&#xa0;>&#xa0;0.999) over 0.01-1.0&#xa0;&#x3bc;g/mL for IMQ and 0.1-2.0&#xa0;&#x3bc;g/mL for TBF. Intra- and inter-day precision demonstrated coefficients of variation below 5%, and recovery rates from skin (79-105%) confirmed accuracy. Limits of detection were 0.001&#xa0;&#x3bc;g/mL for IMQ and 0.004&#xa0;&#x3bc;g/mL for TBF, with quantification limits of 0.02&#xa0;&#x3bc;g/mL and 0.16&#xa0;&#x3bc;g/mL, respectively. This selective, sensitive, and reproducible method represents a valuable analytical tool for supporting the development and quality control of topical formulations for chromoblastomycosis and other fungal skin diseases.

Animals

A Meta-learning-driven strategy for adulteration detection in sweet potato starch and vermicelli using Raman spectroscopy.

To address the widespread adulteration of sweet potato starch and its vermicelli with cheaper starches and overcome conventional supervised learning's dependency on large labeled datasets, this study developed a few-shot discrimination method integrating Raman spectroscopy with meta-learning. We constructed a meta-learning framework using cassava- and wheat-adulterated sweet potato starch as the source domain for training, with potato-adulterated sweet potato starch and cassava-adulterated sweet potato vermicelli as two target domains for testing. Raman spectra showed high consistency between sweet potato vermicelli and its raw starch, laying the foundation for cross-domain detection. Testing yielded comprehensive classification accuracies of 95.33% and 98.00% for the two target domains, significantly outperforming SVM, RF, and CNN (max. 85.24%). This approach effectively identifies subtle starch variety differences in complex adulteration, providing novel food quality inspection solutions and verifying the feasibility of raw material-to-finished product cross-domain detection.

Ipomoea batatas

Interfacial engineering of cobalt tungstate-halloysite nanotube nanocomposite for electrochemical detection of synthetic vanillin in food matrices.

In processed foods and medicine, synthetic vanillin is widely used, although excessive intake poses toxicological risks. Due to the rising usage of synthetic vanillin in food products and associated health hazards, quick, sensitive, and reliable analytical methods are needed to precisely measure vanillin in complex food matrices. This work introduces a CoWO4@F-HNT/GCE nanocomposite as an efficient electrocatalytic modifier for glassy carbon electrodes aimed at trace-level synthetic vanillin detection. Structural and microscopic analyses confirmed phase-pure monoclinic CoWO4, preservation of the tubular aluminosilicate framework, and homogeneous nanoparticle anchoring on F-HNT. Differential pulse voltammetry provided a broad linear range from 0.01 to 372.14&#xa0;&#x3bc;M and a low detection limit of 4.3&#xa0;nM, together with excellent selectivity against common interferents, good cycling stability, and high inter-electrode reproducibility. These characteristics position the CoWO4@F-HNT-modified electrode as a cost-effective and reliable platform for on-site quality control of synthetic vanillin in complex food matrices.

Benzaldehydes

Influence of soil types with different soil-forming process on the qualitative and quantitative detection of microplastics by near-infrared spectroscopy.

Microplastics (MPs) have become a pressing global environmental threat, with soils-acting as sinks for MPs from multiple sources-gaining increasing attention. Near-infrared (NIR) spectroscopy offers a promising tool for MPs detection due to its rapid, non-destructive, and field-applicable features. Although previous studies have focused on the effects of individual soil components on the NIR detection performance of MPs, there is still a lack of systematic research on how the complex background-formed by the coupling of multiple physicochemical properties in natural soils-affects detection performance. This study focuses on soil types with different soil-forming processes, selected five representative agricultural soils to systematically evaluate how the combinations of physicochemical properties they represented affect the performance of NIR-based qualitative and quantitative analysis of MPs in soils. The results demonstrated that soil type significantly affected both the spectral response and detection performance of MPs. Brown Pedocals and Brown Earth exhibited clearer characteristic absorption and stronger linear responses, achieving higher identification accuracy under low (<1.5 %) or zero MPs concentrations and the best quantitative performance (R2 &#x2265; 0.988, prediction set root mean square error (RMSEP) &#x2264; 0.110 %). In contrast, Phaeozem and Red Soil were more prone to misclassification at low concentrations, while Fluvo-aquic Soil showed the poorest quantitative performance. This study is the first to reveal, at a holistic level, the critical constraints posed by natural soil complexity on the NIR detection of MPs, offering targeted empirical evidence to support the application of NIR technology in real-world soil environments.

Soil

Portable metagenomics for preventive surveillance and outbreak control in livestock and poultry: Pathogen detection, resistome profiling, and antimicrobial stewardship.

Conventional diagnostics for livestock and poultry outbreaks commonly rely on culture or targeted PCR panels, which may be too slow or too narrow to guide early control decisions. Portable metagenomics, particularly real-time nanopore sequencing, offers a route to broad pathogen detection, antimicrobial-resistance gene profiling, and outbreak investigation within an integrated workflow. This implementation-focused review evaluates how near-point-of-care metagenomics may support preventive veterinary medicine through earlier detection, surveillance, cohorting, biosecurity decisions, and antimicrobial stewardship. We synthesize sample-to-answer workflows for enteric and respiratory disease in food-producing animals, including sampling, nucleic-acid extraction, host depletion or target enrichment, library preparation, sequencing, bioinformatics, quality control, and interpretation. Applications in calf diarrhea, bovine respiratory disease, poultry outbreaks, mastitis, and resistome monitoring are considered alongside the central limitation that detection alone does not establish causation. Pathogen and resistance-gene signals must therefore be interpreted with clinical signs, lesions, epidemiology, controls, and confirmatory testing. We also propose a minimum reporting checklist, intended as a practical framework rather than a validated consensus standard. Portable metagenomics is not a replacement for conventional diagnostics, but appropriately validated workflows can reduce uncertainty during time-sensitive outbreaks and support more judicious antimicrobial use.

Animals

Recent advances in electrode materials for electrochemical detection of zearalenone.

Zearalenone (ZEN) is an estrogenic mycotoxin commonly found in cereals, animal feed, and processed foods, making it an important concern for food safety and public health. Conventional chromatographic and immunological methods can detect ZEN; however, they often require expensive instruments, lengthy sample preparation, and skilled personnel, which restrict their use for rapid and on-site testing. Electrochemical sensors have attracted enormous interest of the scientific community because of their high sensitivity, rapid response, low cost, miniaturization potential, and compatibility with portable systems. The analytical performance of the electrochemical sensors is strongly influenced by electrode materials, morphology, conductivity, porosity, surface functionality, and the efficiency of bioreceptor immobilization. Despite several reviews on mycotoxin detection, a systematic assessment connecting electrode-material design, modification strategies, sensing mechanisms, and electroanalytical performance specifically for ZEN sensing remain limited. This review critically evaluates recent advances in metal oxides, carbon-based materials, metal-organic- and covalent organic frameworks, MXenes, polymers, and hybrid composites for electrochemical ZEN detection. Particular attention has been given to their roles in electron transfer, analyte enrichment, selectivity, and real-sample analysis. The review also compares the major limitations of current sensing systems, including complex fabrication, matrix interference, insufficient long-term stability, poor inter-electrode reproducibility, and limited scalability. Finally, future directions for developing robust, cost-effective, portable, and commercially viable ZEN sensors are discussed.

Journal Article