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PubMed2026

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↗

PubMed2026

Selective and sensitive colorimetric sensing of carbosulfan based on BiO2-x/Bi2O2.75 nanosheets with excellent haloperoxidase-like activity.

The development of colorimetric methods based on directly inhibiting nanozyme activity for pesticide detection has attracted considerable attention. In this study, we report a novel colorimetric sensing strategy utilizing BiO2-x/Bi2O2.75 nanosheets (BiO2-x/Bi2O2.75 NSs) with haloperoxidase (HPO)-like activity for the rapid and sensitive detection of carbosulfan (CBS) in foods. Oxygen-vacancy-rich BiO2-x/Bi2O2.75 NSs with HPO-like activity were rationally constructed. Kinetic studies revealed a remarkable Michaelis-Menten constant (Km) of 0.014 mM for I-, indicating a higher affinity for iodide ions than other reported HPO-like nanozymes, as evidenced by its lower Km. Under acidic conditions, CBS tends to be hydrolyzed to produce reductive sulfide species, which directly inhibit the iodoperoxidase-like activity of BiO2-x/Bi2O2.75 NSs, enabling selective detection with a limit of detection (LOD) of 0.18 μg/mL and a linear range of 0.20-100 μg/mL. When the concentration of interfering pesticides and substances was 5 times that of CBS, the sensor remained unaffected, exhibiting excellent stability and specificity. This work contributes to the detection of CBS in complex food matrices, bridging the application gap of HPO-like nanozymes in pesticide detection and providing a promising method for food safety detection.

Colorimetry↗

PubMed2026

A point-of-use SERS assay for rapid detecting difenoconazole and flusilazole residues in fruit juices using Au/COF substrate.

We developed a ready-to-use surface-enhanced Raman scattering (SERS) sensor for rapid, pretreatment-free detection of difenoconazole (DIF) and flusilazole (FLU) in peach and lychee juices. The substrate combines Au nanoparticles (AuNPs) with covalent organic frameworks (COF) and is implemented on a portable 25-well plate, enabling in situ testing. Juices can be directly applied to the SERS-active Au/COF composite, allowing simultaneous adsorption and signal generation. The correlation between SERS intensity and logarithmic concentration yielded R-values between 0.925 and 0.986, meeting the monitoring needs of non-laboratory scenarios. The entire workflow completes within 12 min, offering a faster alternative to conventional methods while maintaining high sensitivity and reproducibility. Detection limits reach 0.96-1.22 ppb for DIF and FLU, both of which are below the regulatory maximum residue limits. Distinct SERS fingerprints enable reliable discrimination of mixed residues across juice matrices, supporting rapid on-site monitoring and cost-effective pesticide surveillance.

Triazoles↗

PubMed2026

A homogeneous immunoassay based on AlphaLICA technology for detecting florfenicol residues in animal-derived foods.

Florfenicol (FF), a broad-spectrum amide antibiotic widely used in livestock, poultry, and aquaculture, poses potential threats to food safety and public health due to its residual accumulation. In this study, a novel homogeneous immunoassay based on Amplified Luminescent Proximity Homogeneous Assay (AlphaLICA) technology was developed for the first time for rapid screening of FF residues in milk and egg matrices. By covalently immobilizing the FF-BSA conjugate and goat anti-mouse IgG onto luminescent and photosensitive microspheres, respectively, the method achieved wash-free, homogeneous quantitative detection through a competitive immunoreaction. Under optimized conditions, the assay exhibited a linear range of 0.2-16.2 ng mL-1, with a limit of detection of 9.7 pg mL-1 and a limit of quantification of 183 pg mL-1. The intra- and inter-batch coefficients of variation ranged from 3.08% to 5.70% and 2.44% to 7.09%, respectively. Spike recovery rates in milk and egg matrices ranged from 93.18% to 107.17% (RSD ≤ 5.57%). Cross-reactivity with 11 other common antibiotics, including chloramphenicol and thiamphenicol, was below 0.1%, demonstrating excellent specificity. Comparative analysis with a commercial ELISA kit showed high consistency (r2 = 0.9332, p < 0.001). With high sensitivity, strong specificity, simple operation, and a detection time of only 10 min, this method provides a reliable technical platform for high-throughput, rapid monitoring of FF residues in milk and egg matrices.

Journal Article↗

PubMed2026

Emergence of a Novel, Phenotypically Difficult-to-Detect Vancomycin-Resistant Enterococcus faecium Clone (ST117/CT7799).

A significant increase of vancomycin-resistant Enterococcus faecium (VREfm) infections was observed in South-Eastern Austria since 2024. The prolonged outbreak is caused by a novel vanB-VREfm clone (ST117/CT7799, "VREfmstyr"). This study characterizes the atypical difficult-to-detect resistance phenotype and assesses the genomic relatedness of the isolates. Patient and outbreak characteristics were investigated including whole genome sequencing of the isolates. Sensitivity of broth microdilution (BMD), gradient tests (GT), disk diffusion (DD), and automated susceptibility testing (VITEK2) was compared. The performance of commercial screening media was evaluated. From sporadic detections in early 2024 case numbers began to rise during the year. In 30/31 (97%) of all cases, intra-hospital transmission was considered likely and an association with invasive procedures was identified in most cases. Core genome multilocus sequence typing revealed only six allelic differences between VREfmstyr isolates collected in a 12-month period, all belonging to the E. faecium ST117/CT7799 lineage. BMD detected vancomycin resistance (MIC > 4 mg/L) in no more than 16/31 (52%) of isolates after 24 h incubation, while GT and DD misclassified all isolates. Only prolonged incubation improved the performance of these assays. VITEK2 analysis, however, correctly classified all 31 isolates. Of four commercially available VRE-screening agars, only one was capable of detecting VREfmstyr after 24 h incubation. The emergence and clonal dissemination of VREfm ST117/CT7799 reveals a serious diagnostic gap as commonly used diagnostic algorithms fail to reliably detect this resistance phenotype. Our findings should help to further evaluate the true geographical distribution and clinical significance of this novel VREfm clone.

Enterococcus faecium↗

PubMed2026

Detectable C-Peptide and Diabetic Ketoacidosis Risk in Type 1 Diabetes.

OBJECTIVE: To investigate whether detectable C-peptide levels in type 1 diabetes is associated with a lower risk of diabetic ketoacidosis (DKA). RESEARCH DESIGN AND METHODS: We analyzed the Diabetes Control and Complications Trial publicly available data repository for the association between detectable stimulated C-peptide (>0.2 nmol/mL, measured annually) and DKA incidence over an average 6.5-year follow-up. We used crude and adjusted Andersen-Gill models for recurrent DKA events with time-dependent covariates. RESULTS: Of the 1,441 participants (53% male, median age 27 years), 129 (9%) experienced 180 DKA events. Of these events, 179 (99.44%) occurred after C-peptide was ≤0.2 nmol/L in the prior year and only 1 event occurred with C-peptide >0.2 nmol/L. C-peptide >0.2 nmol/L was associated with a DKA hazard ratio of 0.07 (95% CI 0.01-0.48; P = 0.007), consistent across adjusted models. CONCLUSIONS: Endogenous insulin production was significantly associated with lower DKA risk, suggesting that treatments preserving insulin production could decrease long-term DKA risk.

C-Peptide↗

PubMed2026

A versatile reversed-phase liquid chromatography charged aerosol detection method for streamlined monitoring of QS-21 content and stability in liposomal adjuvant formulations.

Identifying and quantifying an active adjuvant along with its degradants in drug formulations is essential for ensuring the safety and efficacy of the drug product. QS-21 is a potent adjuvant that is being evaluated in several clinical trials and is currently formulated in licensed vaccines that protect against shingles, malaria, and RSV. In aqueous environments, QS-21 is subject to hydrolytic degradation that is influenced by pH and temperature, resulting in the formation of a degradant known as QS-21 Hydrolyzed Product, QS-21 HP, which can occur during manufacturing and/or prolonged storage. The intact QS-21 and QS-21 HP induce distinct immune response profiles, making it critical to monitor the degradation of QS-21 in vaccine adjuvant formulations. To date, there has been a paucity of reliable assays for QS-21, its isomers, and degradant QS-21 HP in liposomal adjuvant formulations available that can be transferred seamlessly in quality control (QC) environments. Herein, we introduce a simple and QC-friendly liquid chromatography coupled to a charged aerosol detector (LC-CAD) enabled by stationary phase screening combined with in silico method development optimization. The method exploits 2.7 μm fused-core phenyl hexyl particles, ensuring its versatility in standard and ultra-high pressure LC systems. This approach demonstrates a high correlation between predicted retention time (RT) and experimental outcomes with overall ∆RT < 4%. In addition, this assay shows great linearity, precision, specificity, and accuracy to advance process development characterization of new vaccine formulations.

Liposomes↗

PubMed2026

Comparative Efficacy of Different AI Systems for Polyp Detection by Size During Colonoscopy: Systematic Review and Network Meta-Analysis.

BACKGROUND: Colorectal cancer remains a leading cause of death despite being largely preventable through polypectomy. AI systems designed to enhance polyp detection during colonoscopy have shown promise, but the extent to which they improve detection of different-sized polyps remains unclear. OBJECTIVE: This study compared the size-stratified efficacy of AI-assisted colonoscopy vs standard colonoscopy using the Hartung-Knapp-Sidik-Jonkman (HKSJ) method, and generated exploratory rankings while acknowledging all cross-platform comparisons are indirect. METHODS: This systematic review and network meta-analysis (NMA) searched PubMed, Embase, Cochrane CENTRAL, and Web of Science from inception to July 25, 2026, supplemented by citation searching. We included randomized controlled trials (RCTs) comparing AI-assisted vs standard colonoscopy in adults (≥18 years of age), reporting mean polyp detection counts stratified by size (≤5 mm, 6-9 mm, and ≥10 mm). Two reviewers screened studies, extracted data, and assessed risk of bias using the Cochrane Risk of Bias 2.0. We conducted frequentist NMA using the HKSJ method with restricted maximum likelihood estimation, calculated 95% prediction intervals (PIs), and assessed heterogeneity using I2 and τ2. Certainty of evidence was rated using the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) framework. RESULTS: A total of 13 RCTs (4156 participants) compared 8 AI systems to standard colonoscopy, forming a network without direct AI comparisons. For diminutive polyps (≤5 mm), AI showed a modest advantage (standardized mean difference [SMD] 0.21, 95% CI 0.07 to 0.35, 95% PI -1.12 to 1.54), but substantial heterogeneity (I2=86.6%) and wide PI crossing the null indicated high uncertainty. EndoScreener showed the most consistent evidence (SMD 0.36, 95% CI 0.18-0.54). For small and large polyps, effects were minimal (SMD 0.02, 95% CI -0.02 to 0.06, 95% PI -0.03 to 0.07; SMD 0.01, 95% CI 0.00-0.02, 95% PI -0.01 to 0.03). GRADE certainty was very low for diminutive polyps and low for small and large polyps. Sensitivity analysis excluding Tianjin YuJin did not materially change findings. CONCLUSIONS: AI may modestly enhance diminutive polyp detection, but effects on small and large polyps are minimal, with no platform superiority. Given very low to low certainty, findings are hypothesis-generating. This exploratory NMA provides size-stratified comparisons that can inform future head-to-head trial design. Unlike prior reviews aggregating all polyp sizes, we show the overall AI benefit is driven by diminutive polyp detection, providing a framework for targeted deployment-prioritizing AI for diminutive polyp screening, with limited value for larger lesions. Head-to-head trials are urgently needed. TRIAL REGISTRATION: PROSPERO International Prospective Register of Systematic Reviews CRD420251266932; https://www.crd.york.ac.uk/PROSPERO/view/CRD420251266932.

Colonoscopy↗

PubMed2025

Enhanced fracture detection on radiographs with AI assistance for clinicians: a systematic review and meta-analysis.

BACKGROUND: Emergency radiographic interpretation for fractures is prone to missed or misdiagnoses. Artificial intelligence (AI) is expected to become a powerful tool to assist clinicians in fracture detection. PURPOSE: A systematic review and meta-analysis was performed to assess whether AI improves clinicians' ability to detect fractures on radiographs. MATERIALS AND METHODS: A literature search was conducted in PubMed, Web of Science, and Cochrane Library for studies published between January 1, 2010, and October 10, 2025. A meta-analysis of diagnostic accuracy studies was performed using a Summary Receiver Operating Characteristic (SROC) curve. The quality of included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool. Subgroup analysis and meta-regression were conducted to explore potential sources of heterogeneity. RESULTS: A total of 26 studies were included . The pooled sensitivity of clinicians increased from 77% (95% CI: 72-81) to 87% (95% CI: 83-90) with AI assistance, while the pooled specificity improved from 88% (95% CI: 85-90) to 92% (95% CI: 89-94). The corresponding AUC values were 0.90 (95% CI: 0.87-0.92) before and 0.95 (95% CI: 0.93-0.97) after AI assistance. Eight studies were rated as high risk of bias. Subgroup analysis and meta-regression identified potential sources of heterogeneity, including fracture location, AI model type, high risk of bias, and reference standards. CONCLUSION: AI assistance significantly improves clinicians' diagnostic performance in detecting fractures on radiographs for extremity and trunk fractures.

Humans↗

PubMed2026

Development and Crossover Evaluation of an Artificial Intelligence-Assisted System for Solid Pancreatic Lesion Detection and Pancreatic Parenchyma Recognition in Endoscopic Ultrasonography (With Video).

BACKGROUND AND STUDY AIMS: Pancreatobiliary endoscopic ultrasonography (EUS) is technically demanding, and supervised training opportunities are limited. We developed an artificial intelligence (AI) overlay system for detecting solid pancreatic lesions (SPL) and recognizing pancreatic parenchyma (PP) and evaluated its effect on reader performance. PATIENTS AND METHODS: Across six centers, two deep learning-based models were trained using expert-annotated EUS frames. We then conducted a randomized, two-sequence, two-period crossover reader study in which eight endosonographers (five novices and three experts) interpreted image sets with and without AI assistance. The primary endpoint was superiority of sensitivity for SPL detection among novices; key secondary endpoints included specificity and PP recognition. RESULTS: From 118 patients, 120 SPL-positive/negative image sets and 160 PP-positive/negative image sets were constructed. Among novices, AI assistance improved SPL detection sensitivity (88.7% vs. 76.8%, p < 0.001) and accuracy (86.4% vs. 78.7%), while specificity met the predefined noninferiority criterion (84.2% vs. 80.5%, p < 0.001). For PP recognition, sensitivity increased numerically (86.3% vs. 83.3%) but did not meet the predefined superiority criterion (p = 0.095); specificity met the noninferiority criterion (87.8% vs. 81.0%), and accuracy increased from 82.1% to 87.0%. Among experts, sensitivity was maintained for both tasks, whereas specificity increased with AI assistance. CONCLUSIONS: AI assistance improved SPL detection among novice endosonographers. For PP recognition, sensitivity increased without reaching statistical superiority, whereas specificity met the predefined noninferiority criterion. These findings support a potential adjunctive role for AI in EUS interpretation.

Humans↗

PubMed2026

Ultrasound protocols used to detect vascular gas emboli in divers: a systematic review.

INTRODUCTION: Venous gas emboli (VGE) detected via ultrasound can be used as a surrogate marker for decompression stress. While Doppler ultrasound is the historical gold standard, two-dimensional (2D) ultrasonography offers advantages for on-site monitoring, including a wider field of view and reduced dependence on noise-free environments. This systematic review evaluates 2D ultrasonography protocols used in decompression research since the 2015 International Meeting on Ultrasound for Diving Research, identifying methodological similarities, differences, and adherence to consensus recommendations. METHODS: A search of PubMed and Scopus identified studies using 2D ultrasound to detect VGE in divers. Inclusion criteria were: (1) use of 2D ultrasound, (2) detection of VGE or monitoring of decompression stress, (3) inclusion of a diver cohort, and (4) publication after 2015. Data extraction focused on VGE scoring systems, ultrasound hardware, measurement protocols, and operator experience. Risk of bias was assessed using ROBINS-I-V2, and compliance with the 2015 consensus recommendations was evaluated. RESULTS: Twenty studies were included. The Eftedal-Brubakk scale was most commonly used (n = 15), with cardiac ultrasound as the primary imaging modality; one study assessed a peripheral vessel. Common shortcomings included post-dive measurements lasting less than two hours, underreporting of operator experience and hardware specifications, limited individual-level data, and inappropriate use of parametric statistics for ordinal bubble grade data. No study fully complied with all consensus recommendations. CONCLUSIONS: This review demonstrates that, although two-dimensional ultrasound is widely used for post-dive VGE assessment, methodological heterogeneity with multiple shortcomings remain. Furthermore, nearly all studies restricted imaging to the heart, thus leaving peripheral vessel assessment largely unexplored.

Embolism, Air↗

PubMed2026

Liquid biopsy-based detection of circulating and exfoliated cholangiocarcinoma tumor cells from blood and bile using heparan sulfate octasaccharides on integrated microfluidic systems.

Early diagnosis of cholangiocarcinoma (CCA) remains challenging because existing diagnostic approaches often lack sufficient sensitivity for reliable detection of early-stage disease. Circulating tumor cells (CTCs) in blood and exfoliated tumor cells (ETCs) in bile represent valuable targets for liquid biopsy-based detection; however, their low abundance and the complexity of clinical sample analysis pose substantial technical challenges for reliable enrichment and identification. Herein, we present a reproducible workflow for isolating and identifying CCA tumor cells from blood for CTCs and bile for ETCs using synthetic cell-surface heparan sulfate (HS) octasaccharide-functionalized magnetic beads (MBs) on integrated microfluidic systems. The method combined sample pre-processing, magnetic bead-based enrichment, controlled low-shear mixing and immunofluorescence-based identification into a unified workflow compatible with distinct clinical sample types. Key operational parameters, including MB concentration, mixing frequency, and pressure settings, were detailed to facilitate consistent performance. Using this workflow, tumor cell capture rates of approximately 70% in bile (for ETCs) and blood (for CTCs) were achieved, with a total processing time of 60-90 min per sample under clinically relevant low-abundance conditions. The platform enables reliable detection of as few as 1 tumor cell per mL of blood or bile. This method provides a practical and adaptable strategy for glycosaminoglycan-mediated liquid biopsy applications and may be extended to other tumor-cell enrichment workflows involving heterogeneous cell-surface interactions.

Humans↗

PubMed2026

Linked-color imaging with computer-aided detection and the proximal adenoma miss rate: a randomized tandem trial.

BACKGROUND AND AIMS: Linked-color imaging (LCI) aids the detection and characterization of lesions. Computer-aided detection (CADe) systems have been introduced to improve lesion detection during colonoscopy. Although several studies have been reported regarding LCI, few have investigated the combination of LCI and CADe. This study aimed to evaluate the efficacy of LCI with CADe colonoscopy compared to conventional white-light colonoscopy. METHODS: A single-center, randomized tandem trial was conducted. Participants referred for first-time colonoscopy after fecal immunochemical test (FIT)-positive, asymptomatic screening, or surveillance colonoscopy were randomized (1:1) to undergo CADe-assisted colonoscopy of LCI or white-light imaging (WLI) in the right side of the colon. The primary outcome was adenoma miss rate (AMR) in the right side of the colon. Secondary outcomes included polyp miss rate (PMR), diminutive adenoma miss rate (dAMR), sessile serrated lesion miss rate (SSLMR), advanced adenoma miss rate, advanced neoplasia miss rate, flat-type lesion miss rate (FMR), and the differences in miss rates based on expertise. RESULTS: Among 232 randomized participants, 209 were analyzed (LCI/CADe: 102; WLI: 107). AMR (WLI: 39% vs LCI/CADe: 20%; P = .001), PMR (42% vs 18%; P < .001), and dAMR (42% vs 21%; P = .003) were significantly lower in the LCI/CADe arm, particularly among experts. SSLMR (46% vs 0%), advanced AMR (30% vs 0%), advanced neoplasia miss rate (25% vs 0%), and FMR (27% vs 5.6%) were lower in LCI/CADe, although without statistical significance. CONCLUSIONS: Compared to conventional colonoscopy, LCI with CADe colonoscopy resulted in a statistically significant decrease, especially in AMR. (UMIN 000050685).

Humans↗

PubMed2026

Artificial intelligence for dental caries detection: An umbrella review.

Artificial intelligence (AI) has been proposed as a tool to improve dental caries detection across imaging modalities; however, its clinical value remains uncertain. This umbrella review aimed to synthesize and critically appraise systematic reviews evaluating AI for caries detection and diagnosis. An umbrella review was conducted following PRIOR guidance (PROSPERO CRD420261340728). Searches were performed in MEDLINE, Embase, Scopus, Web of Science, and Google Scholar up to 15 March 2026. Methodological quality was assessed using AMSTAR 2, and overlap of primary studies was quantified using the corrected covered area (CCA). Seventeen systematic reviews were included, of which five reported diagnostic test accuracy meta-analyses using bivariate or HSROC models. Across these meta-analyses, pooled sensitivity ranged from 0.76 to 0.94 and specificity from 0.85 to 0.91. Most systems were based on deep learning models applied to bitewing radiographs and intraoral photographs. However, substantial heterogeneity was observed in imaging modalities, lesion thresholds, analytical tasks, and evaluation metrics. In addition, a high degree of overlap across reviews and recurrent methodological limitations, including reliance on retrospective datasets, limited external validation, and inconsistent reporting, substantially weaken the reliability of the evidence. Although AI models demonstrate high diagnostic performance under experimental conditions, current evidence does not support their use as stand-alone diagnostic tools. Their clinical applicability remains limited, and implementation should be restricted to decision-support contexts until robust prospective validation demonstrates meaningful impact on clinical decision-making and patient outcomes.

Dental Caries↗

PubMed2026

RR-interval-based atrial fibrillation detection and burden estimation: cross-dataset validation and calibration-aware probability analysis.

Objective.Atrial fibrillation (AF) burden has become an increasingly important endpoint in long-duration rhythm monitoring, but reliable burden estimation requires more than accurate AF detection alone. In particular, when burden is derived by aggregating predicted AF probabilities over time, probability calibration may directly affect burden validity under external dataset shift.Approach.This study developed an interpretable-interval feature model for AF detection and evaluated it using record-wise cross-validation on a development cohort and independent cross-dataset external validation on public Holter electrocardiographic databases. Window-level performance was assessed using the area under the receiver operating characteristic curve (ROC-AUC), area under the precision-recall curve (PR-AUC), Brier score, expected calibration error (ECE), and calibration intercept and calibration slope. Recording-level AF burden was estimated using both probability-based and hard-label aggregation and evaluated using mean absolute error (MAE) and agreement analyses.Main results.The model showed high discrimination in both development and external evaluation, with external ROC-AUC ofand PR-AUC of. However, external calibration deteriorated despite preserved ranking performance, with Brier score of, ECE(15) of, calibration intercept of, and calibration slope of. In the external cohort, probability-based burden estimation preserved strong association with reference burden but showed weaker raw agreement than hard-label aggregation, with MAE ofversus, consistent with systematic probability underprediction. Repeated external recalibration across record-level splits substantially improved probability quality and probability-based burden estimation. Median probability-burden MAE decreased fromwithout recalibration toafter Platt recalibration andafter isotonic recalibration, while median ECE(15) decreased fromtoand, respectively.Significance.These findings indicate that-interval-based AF detection maintained strong ranking performance in the tested external cohort, but probability calibration should be evaluated explicitly when predicted probabilities are aggregated into AF-burden estimates.

Atrial Fibrillation↗

PubMed2026

In Situ Hybridization and RT-PCR Detection of Nervous Necrosis Virus in Fourfinger Threadfin, Eleutheronema tetradactylum, in Taiwan.

Between April and July 2020, suspected outbreaks of nervous necrosis virus (NNV) infection were observed in fourfinger threadfin (Eleutheronema tetradactylum) fingerling hatcheries in Pingtung County, southern Taiwan. Affected fish exhibited spiral swimming behaviour and abdominal distension, resulting in mortality rates between 50% and 100%. Histopathological examination showed severe vacuolation in the brain and ocular tissues, with large oval and/or irregular basophilic cytoplasmic inclusion bodies in the brain. Phylogenetic analysis of the viral replicase (RNA1) and capsid protein (RNA2) genes revealed high nucleotide sequence identities among the isolates in this study, with sequence similarity rates of 96.9%-99% for RNA1 and 98.2%-99.0% for RNA2 compared to RGNNV reference strains available in the NCBI GenBank database. This is the first detection of betanodavirus in fourfinger threadfin in Taiwan, using RT-PCR and ISH. A positive correlation between elevated water temperatures and disease severity indicates the need for year-round surveillance and genomic analysis to clarify the epidemiology of FTNNV. The data suggest that infected eggs may facilitate the vertical transmission of Betanodavirus. Crucially, utilising virus-free broodstock, alongside routine health screening and environmental control, is essential for mitigating NNV risks in fourfinger threadfin aquaculture.

Animals↗

PubMed2026

Natural deep eutectic solvent in situ formation-based extraction method coupled to high-performance anion-exchange chromatography with pulsed amperometric detection for multiclass carbohydrates in hot pot bases.

A novel method was developed for the simultaneous extraction of fourteen multiclass carbohydrates from high-fat foods via the in situ formation of deep eutectic adducts from analytes and acetate ions. Different natural deep eutectic solvents (NADESs) composed of fructose and organic acids were tested as extraction solvents. A model NADES formulated with sodium acetate and fructose was characterized using Fourier transform infrared (FTIR) spectroscopy and hydrogen nuclear magnetic resonance (1H-NMR) spectroscopy. The critical extraction parameters were systematically optimized using multi-response surface methodology (MRSM) with a central composite design (CCD). The extract was analyzed using high-performance anion-exchange chromatography coupled with pulsed amperometric detection (HPAEC-PAD) using a sodium hydroxide-sodium acetate eluent, which did not require organic solvents. This approach exhibited good linearity over the concentration range of 0.02-10 mg L-1, with correlation coefficients (r) ranging from 0.9994 to 0.9999. The limits of detection and quantification were in the ranges of 0.06-0.42 mg kg-1 and 0.19-1.3 mg kg-1, respectively, which were significantly lower than those of liquid chromatography (LC). The protocol was successfully applied to the determination of fourteen carbohydrates in forty-five hotpot seasoning samples. The recoveries ranged from 86.3% to 104.1%, with relative standard deviations (RSDs) of 0.9-7.1%. By integrating multiple techniques, this strategy simplifies operations, shortens extraction time, and achieves baseline separation of three carbohydrate classes that exhibit poor resolution using a conventional LC method. This study describes an efficient procedure for the simultaneous determination of multiple trace-level carbohydrates in complex samples using HPAEC-PAD.

Journal Article↗

PubMed2026

Enhancing Hemoglobin Bart's hydrops fetalis syndrome prevention: a single-tube multiplex real-time PCR assay for the comprehensive detection of four significant α0-thalassemia deletions (--SEA, --THAI, --CR, and --SA) found in Thailand.

BACKGROUND: Hemoglobin (Hb) Bart's hydrops fetalis is a major public health concern in Southeast Asia, particularly in Thailand. Current screening strategies target the two most common α0 -thalassemia deletions (--SEA and --THAI). METHOD: In this study, we developed a single-tube multiplex real-time PCR assay for the simultaneous detection of four clinically relevant α0-thalassemia deletions (--SEA, --THAI, --CR, and --SA). The assay was validated using 538 clinical samples with diverse thalassemia genotypes and compared against conventional gap-PCR as the reference method. Analytical performance, including sensitivity, specificity, and limit of detection (LOD), was evaluated. In addition, clinical utility was assessed in 22 prenatal diagnosis cases at risk of Hb Bart's hydrops fetalis. RESULTS: The study cohort demonstrated substantial genetic heterogeneity, comprising 43 distinct genotypes. The developed assay achieved 100% sensitivity and specificity for all targeted deletions, with complete concordance with gap-PCR results. No cross-reactivity was observed with α+-thalassemia. The assay demonstrated a high analytical sensitivity with a LOD of 9.76 × 10-3 ng per reaction. Whereas in prenatal diagnosis, all 22 fetal genotypes were accurately identified, including five cases of homozygous --SEA and one rare compound heterozygous --SEA/--CR fetus. CONCLUSIONS: This study presents a rapid, accurate, and cost-effective multiplex real-time PCR assay capable of detecting both common and rare α0-thalassemia deletions in a single reaction. The assay demonstrates strong potential for implementation in routine clinical laboratories and large-scale population screening, contributing to improved prevention and control of severe thalassemia syndromes in high-prevalence regions.

Humans↗