Search PubMedSearch

SEARCH · Search PubMed

Results for “Semen detection”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

322 records · Page 3Linked to original sources

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

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

Metal-organic frameworks nanozyme-integrated portable microneedle patch for visual bacterial monitoring in meat.

Foodborne microbial contamination is a major global health concern, with conventional methods often being time-consuming and complex. Herein, we developed a novel portable biosensor by integrating microneedle patch technology and a metal-organic framework (Fe/Cu-NBDC MOF) nanozyme, enabling rapid, on-site, visual detection of bacteria in meat. The sensing system works by encapsulating aptamer-functionalized MOF nanozymes within a hydrogel patch, where their catalytic sites are initially blocked by the aptamer. In the presence of Staphylococcus aureus (S. aureus) as the target, the specific aptamer's binding to bacteria exposes numerous catalytic sites, further activating the chromogenic reaction of the tetramethylbenzidine‑hydrogen peroxide (TMB-H₂O₂) system, enabling visual detection of S. aureus. The biosensor demonstrates a detection limit of 82 CFU/mL with excellent specificity to successfully apply to commercial mutton. By integrating sampling, enrichment, and visual detection into a single compact device, this platform offers a practical, efficient solution for rapid on-site screening of foodborne pathogens.

Biosensing Techniques

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

Artificial intelligence-assisted detection and optical differentiation of colorectal lesions in Lynch syndrome surveillance (CADLY2): a multicentre, open-label, randomised controlled superiority trial.

BACKGROUND: Artificial intelligence (AI)-based computer-aided detection (CADe) systems improve adenoma detection in average-risk colorectal cancer screening. Meanwhile, evidence in Lynch syndrome surveillance is sparse and inconsistent. We assessed the effect of CADe on adenoma detection during Lynch syndrome surveillance. Computer-aided optical diagnosis (CADx) performance for optical differentiation of colorectal lesions was evaluated as a secondary aim. METHODS: CADLY2 was an international, multicentre, open-label, randomised controlled superiority trial at nine specialised hereditary cancer surveillance centres in Belgium, Germany, the Netherlands, and Spain. Adults aged 18 years or older with genetically confirmed Lynch syndrome scheduled for surveillance colonoscopy were randomly assigned (1:1) to high-definition white-light (HD-WL) colonoscopy alone or to HD-WL colonoscopy with computer-aided assistance from CAD EYE (Fujifilm, Tokyo, Japan). CAD EYE was used for CADe during withdrawal and for CADx after lesion detection. Randomisation was done centrally through a secure web-based system using Pocock's minimisation algorithm with a stochastic component and was stratified by centre, sex, previous colorectal cancer, underlying pathogenic variant, and interval since previous colonoscopy. Allocation concealment was ensured through the centralised web-based system. Patients were masked to group allocation until the start of withdrawal in procedures with mild sedation, or until completion of the procedure in procedures with propofol-based sedation. Endoscopists were not masked. The primary outcome was adenoma detection rate, defined as the proportion of patients with at least one histopathologically confirmed adenoma, analysed in the full analysis set (defined as all randomly allocated patients with available data for the primary outcome). The diagnostic performance of the CADx system was evaluated as a secondary outcome. The safety analysis set comprised all randomly allocated patients who underwent a study colonoscopy. This study is registered with the German Clinical Trials Register, DRKS00030695, and is completed. FINDINGS: Between May 9, 2023, and Oct 30, 2025, 757 patients were randomly allocated to HD-WL colonoscopy (377 patients) or to AI-assisted colonoscopy (380 patients); 733 patients were included in the full analysis set (369 HD-WL and 364 AI-assisted). The median age was 49 years (IQR 38-59) in the HD-WL group and 50 years (38-59) in the AI-assisted group; 213 (58%) were female and 156 (42%) male in the HD-WL group, and 207 (57%) were female and 157 (43%) male in the AI-assisted group. The adenoma detection rate was 30·9% (114 of 369 patients) with HD-WL versus 33·8% (123 of 364 patients) with CADe assistance (odds ratio 1·14 [95% CI 0·83-1·57], p=0·41). For CADx differentiation of neoplastic versus non-neoplastic lesions in the paired lesion-level analysis, with histopathology as the reference standard and sessile serrated lesions and traditional serrated adenomas classified as non-neoplastic, CADx sensitivity was 85·9% (95% CI 82·0-89·1) and specificity was 91·4% (89·4-93·0). Three adverse events occurred in the AI-assisted group: two mild post-polypectomy bleedings and one serious pulmonary embolism or deep venous thrombosis unrelated to the procedure. No adverse events occurred in the HD-WL group. INTERPRETATION: CADe-assisted colonoscopy did not show the absolute improvement in adenoma detection rate that was assumed in the prespecified sample-size calculation. CADx did not clearly improve lesion differentiation beyond expert optical diagnosis in expert Lynch syndrome surveillance settings. FUNDING: Third-party research funding of the National Center for Hereditary Tumor Syndromes, University Hospital Bonn.

Humans

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

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

Penalized Cumulative Probability Model for a Continuous Outcome Subject to Detection Limits.

Mixed-type outcome data occur when the outcome variable's distribution is a mixture of both continuous and discrete ordinal variables. Such mixed-type outcomes are common in biomedical, psychological, and the health sciences, particularly for variables having either a detection or quantitation limit. When interest lies in identifying a combination of genomic features associated with a mixed-type outcome, any method used would require a variable selection strategy for high-dimensional data. Unfortunately, few variable selection methods exist for modeling a mixed-type outcome when the covariate space is high dimensional. This study develops a high-dimensional penalized cumulative probability model (CPM), to allow for the identification of genomic features associated with mixed-type outcome of interest. We demonstrated how such model may be estimated using the iterative penalization procedure-the generalized monotone incremental forward stagewise (GMIFS) algorithm. The Model-X knockoffs procedure was combined with the estimation algorithm to control the false discovery rates (FDR) when performing variable selection. Through extensive simulation studies, our penalized CPM was shown to outperform alternative methods in terms of controlled variable selection performance by achieving high statistical power with the FDR being controlled at the target level. We demonstrate the utility of our method by applying it to predict estimated glomeruli filtration rate (eGFR) in kidney transplant recipients at 24 months post-transplant using baseline gene expression data as predictors. Our CPM model identified five genes associated with this mixed-type outcome which have important links to renal disease, which may provide prognostic guidance for kidney transplantation recipients.

Models, Statistical

Single-slice Functional Lung MRI During Metronome-Paced Tachypnea Detects Changes in Regional Ventilation Dynamics After a Single Dose of Dual Bronchodilator Treatment in COPD.

Dual long-acting bronchodilators are a standard treatment in chronic obstructive pulmonary disease (COPD), aimed at alleviating dyspnea, improving exercise tolerance, and preventing exacerbations. Metronome-paced tachypnea (MPT) offers a feasible alternative to exercise testing for the evaluation of dynamic hyperinflation (DH) in COPD. Because MPT can be performed during MRI, its combination with single-slice phase-resolved functional lung (PREFUL) MRI provides a promising approach to investigate changes in regional ventilation dynamics induced by DH. This approach was evaluated in a randomized, investigator-blinded, placebo-controlled, single-dose (SD) crossover trial with a two-week extension of once daily dual bronchodilator medication, in which patients with stable COPD underwent PREFUL MRI during resting tidal breathing (RTB) and during MPT. During RTB, no significant improvements in MRI-derived parameters were observed after SD treatment compared with placebo. During MPT, however, regional ventilation, flow-volume loop correlation, its defect percentage, and end-expiratory lung area improved significantly after SD treatment compared to the placebo scan (all p&#x2009;<&#x2009;0.02). After multi-dose treatment, five out of six measured parameters improved during MPT, when compared to the baseline scan without bronchodilator treatment (all p&#x2009;<&#x2009;0.03). In contrast to RTB, PREFUL MRI during MPT was able to detect changes in COPD patients already after SD treatment. The combination of MPT and PREFUL MRI represents a promising method to evaluate the effects of dual bronchodilators on regional ventilation dynamics and hyperinflation.

Humans

ReMeDy: A Flexible Statistical Framework for Region-Based Detection of DNA Methylation Dysregulation.

Region-based epigenome-wide association studies have demonstrated improved statistical power and biological interpretability compared with probe-wise analyses of DNA methylation data. However, most existing region-based methods characterize methylation dysregulation primarily through changes in mean methylation levels associated with a phenotype of interest. Substantial evidence indicates that phenotype-associated methylation alterations may also manifest through changes in methylation variability or through joint shifts in mean and variability. Despite this, no existing statistical framework jointly models mean-variance methylation changes in a region-based manner. We propose ReMeDy, a flexible statistical framework that uses a hierarchical likelihood approach within a generalized linear model setting to identify differentially methylated regions, variably methylated regions, and regions exhibiting joint differential and variable methylation at a genome-wide scale. Unlike existing models, ReMeDy operates directly on biologically defined co-methylated regions, allowing it to naturally capture spatial correlation inherent in DNA methylation array data, while avoiding reliance on heuristic, user-defined tuning parameters such as smoothing spans and kernel bandwidths that can substantially influence results and introduce subjectivity. Through extensive simulation studies and comprehensive benchmarking against popular models, we demonstrate that ReMeDy maintains false discovery and Type-I error rates at nominal levels while achieving consistently higher statistical power across a wide range of realistic scenarios. Application to population-level DNA methylation data further shows that ReMeDy identifies biologically meaningful regions and pathways implicated in complex human diseases that are not captured by conventional mean-based analyses alone. ReMeDy is implemented as an open-source R package and is freely available at https://github.com/SChatLab/ReMeDy.

DNA Methylation

Artificial intelligence-supported double reading in European population breast cancer screening: A systematic review and meta-analysis of prospective programs.

BACKGROUND: Most European population mammography screening programs rely on double reading with arbitration, a model that delivers mortality benefit but is increasingly challenged by radiologist workload, variable specificity, and interval cancers. Artificial intelligence (AI) is being evaluated to support or optimize these established European screening pathways. PURPOSE: To synthesize prospective or program-embedded evaluations of AI conducted within European-style population screening programs and to estimate exploratory program-level absolute risk differences (RDs) per 1000 examinations for cancer detection rate (CDR) and recall. MATERIALS AND METHODS: We performed a prespecified, focused evidence synthesis of three large studies embedded within routine population screening programs operating under European-relevant workflows: MASAI (randomized AI-supported risk triage within a national program), ScreenTrustCAD (prospective paired-reader evaluation with AI as an independent reader in a double-reading framework), and PRAIM (nationwide decision-referral implementation). Outcomes were harmonized as AI-control RDs per 1000 examinations. Random-effects pooling used Hartung-Knapp-Sidik-Jonkman models. For the paired-reader design, sensitivity analyses applied a Kish effective sample-size approach across plausible within-examination correlations (&#x3c1;&#xa0;=&#xa0;0.3-0.8). Positive predictive value (PPV) and workflow/time outcomes were summarized descriptively. RESULTS: Across 597,419 examinations, the pooled CDR RD was +0.9 per 1000 (95% CI -0.0 to +1.8; I2&#xa0;&#x2248;&#xa0;12%), consistent with a modest directional increase with borderline statistical uncertainty. The pooled recall RD was -0.6 per 1000 (95% CI -3.1 to +2.1; I2&#xa0;&#x2248;&#xa0;41-43%), indicating no consistent recall increase across screening programs. Where reported, PPV was higher with AI-supported screening. Efficiency signals included 44.3% fewer total readings in MASAI and shorter reading times for AI-normal examinations in PRAIM; in PRAIM, a program-level safety-net mechanism recovered 204 cancers that would otherwise have been missed. CONCLUSION: In European population screening programs characterized by double reading and arbitration, prospective program-embedded evidence suggests that AI integration may yield a small absolute increase in cancer detection (&#x2248;1/1000) without a consistent increase in recall, alongside improved PPV and efficiency signals. These findings suggestAI primarily as a complementary reader within European screening workflows, with implementation requiring explicit quality assurance and monitoring of interval cancers and stage distribution.

Humans

Vortex-assisted liquid-liquid microextraction based on natural deep eutectic solvents for the determination of pyrethroid pesticides in urine.

A novel, facile, and environmentally friendly analytical method was developed based on vortex-assisted liquid-liquid microextraction and high-performance liquid chromatography with diode-array detection for detecting pyrethroid pesticides (PPs) in urine. Natural deep eutectic solvents (NADESs) were prepared using plant essential oil-derived monoterpenoids (thymol, carvacrol, and menthol) combined with aromatic primary alcohols (benzyl alcohol, phenethyl alcohol, and phenylpropyl alcohol) as hydrogen bond donors and acceptors. These solvents served as environmentally benign extraction media, thereby avoiding the use of conventional volatile, toxic organic solvents. NADESs are naturally derived, easy to prepare, biodegradable, and environmentally friendly solvents. Hydrophobic and &#x3c0;-&#x3c0; interactions between the NADESs and PPs may contribute to enhancing the affinity of PPs toward the NADESs phase. Vortex technology, accelerating mass transfer between the sample and extractant phases, enables fast extraction of PPs. Under optimized conditions, the method achieved a low detection limit (0.002&#xa0;mg&#xa0;L-1), satisfactory precision with relative standard deviations (0.3%-2.4%), and acceptable recovery (80.7%-86.2%). The method demonstrated excellent performance in urine analysis and was feasible as a facile and green strategy for monitoring the content of PPs in biological matrices and assessing exposure risk.

Liquid Phase Microextraction

Performance of Automated Hematology Analyzer Criteria in Detecting Peripheral Blood Smear Abnormalities: A Systematic Literature Review.

OBJECTIVES: Criteria for visual examination of stained peripheral blood smear (PBS) differ among institutions in the United States and internationally. In an effort to standardize review criteria, the International Consensus Group for Hematology Review (ICGHR) proposed in 2005 a consensus list of rules for CBC findings that should trigger a review of automated cell counter results and potentially lead to further testing or blood smear review. The primary aim of this paper is to report on the published literature in the past 20&#x2009;years regarding PBS review criteria and their ability to identify relevant peripheral blood abnormalities. METHODS: We performed a systematic review of the published literature from 2005 to 2025 to investigate and summarize PBS review criteria and performance in the context of automated hematology analyzers in clinical laboratories. RESULTS: Of 5351 citations, 68 studies met our search criteria. These studies included 22 countries and all major hematology analyzer manufacturers. Marked variability was observed in study populations, analyzer flagging criteria, details of PBS visual review, definitions of a "positive" smear, and approaches to statistical data analysis. Across studies, the blast flag sensitivity ranged from 18% to 100% while the blast flag specificity ranged from 17% to 100%. Wide ranges in sensitivity/specificity were also seen for atypical and/or abnormal lymphocyte flags across studies. For studies analyzing the same patient population, less striking variation was seen across instruments. CONCLUSIONS: This systematic review provides a 20-year overview of the literature, highlighting significant variability in PBS review criteria, dependence on study design and hematology analyzer, and the importance of developing harmonized evidence-based guidelines.

Humans

PCa Detection in PI-RADS 4 and 5 Lesions: Comparison of [68Ga]Ga-PSMA-11 PET/CT-Guided Robot-Assisted Biopsy Versus mpMRI Cognitive-Fusion TRUS-Guided Prostate Biopsy.

Lesions with a Prostate Imaging-Reporting and Data System (PI-RADS) score of 4 or greater on multiparametric MRI (mpMRI) indicate a high likelihood of prostate cancer (PCa), and guidelines recommend a targeted biopsy. We aimed to compare the diagnostic performance of robotic arm-assisted [68Ga]Ga-PSMA-11 PET/CT-guided prostate biopsy (PGPB) with mpMRI-directed cognitive-fusion transrectal ultrasound-guided biopsy (MCFB) in biopsy-na&#xef;ve men with clinical findings suggestive of PCa. Methods: This prospective, single-center, randomized clinical trial (NCT05137561) enrolled biopsy-na&#xef;ve men age 50-90 y with elevated levels of prostate-specific antigen (&#x2265;4 ng/mL) and abnormal digital rectal examination findings. All participants underwent mpMRI, and those with a PI-RADS score of 4 or greater were randomized into 2 arms. In arm 1, participants underwent PGPB for a [68Ga]Ga-PSMA-avid lesion, and participants in arm 2 underwent MCFB. Participants in arm 1 with PET-negative findings subsequently underwent MCFB, and participants with negative biopsy results underwent PET and PGPB. The primary outcome was the detection of PCa. Secondary outcomes included complication rates and participant-reported pain. Result: Of the 267 participants enrolled, 81.3% (217) had lesions with a PI-RADS score of 4 or greater and were randomized to either PGPB (n = 112) or MCFB (n = 105). PCa was detected in 97.1% of participants (101/104) in arm 1 and 81.0% (85/105) in arm 2 (P < 0.05). PGPB showed higher diagnostic accuracy for PI-RADS 5 lesions (100% vs. 95.1%, P = 0.09). Major complications were observed in arm 2 only (n = 5). Arm 1 had significantly fewer complications (10.8% vs. 51.4%, P < 0.01), a lower median visual analog scale score for pain (3 vs. 5), and shorter procedure times. The core positivity rate was higher in arm 1 (60% &#xb1; 20%), despite obtaining fewer cores. Conclusion: [68Ga]Ga-PSMA-11 PGPB demonstrated higher diagnostic performance, fewer complications, and better tolerability compared with MCFB. This approach enables integrated diagnosis and staging, offering a promising alternative for efficient, safe, and accurate evaluation of prostate cancer.

Humans

HPV Testing Versus Cytology for Cervical Cancer Screening&#xa0;Among Women 50&#x2009;Years and Older: Evidence From the HPV FOCAL Randomized Controlled Trial.

Evidence on the comparative effectiveness of HPV testing versus cytology specifically in women aged &#x2265;&#x2009;50&#x2009;years who are approaching screening cessation remains limited. This analysis included 6471 women aged &#x2265;&#x2009;50 at baseline screening in the HPV FOCAL randomized clinical trial. Women were randomly allocated to receive cytology (Control Group, n&#x2009;=&#x2009;3248, 50.19%) or HPV testing (Intervention Group, n&#x2009;=&#x2009;3223, 49.81%) at baseline, with co-testing at 48-month exit. We calculated incidence rates and risk ratios for CIN2+ detection over follow-up and compared missed lesions at exit by screening method. At the 48-month exit, CIN2+ detection was lower among HPV baseline-negative women than among those in the cytology group (1.61/1000 [95% CI, 0.52-3.76] vs. 3.15/1000 [95% CI, 1.51-5.78]; risk ratio, 0.51 [95% CI, 0.11-0.91]), reflecting higher baseline detection with HPV testing and fewer prevalent lesions at exit. Even with cytology re-screening at 2&#x2009;years, 50% of CIN2+ cases were missed compared to 30% with HPV testing. After adjusting for age, education, smoking status, and lifetime sexual partners, the hazard ratio for CIN2+ comparing HPV to cytology was 0.44 (95% CI, 0.22-0.88). Among women aged &#x2265;&#x2009;50&#x2009;years, HPV primary screening was more effective than cytology at detecting CIN2+ lesions and was associated with a continued lower subsequent risk following a negative HPV test, supporting its use in cervical cancer screening programs in this age cohort.

Aged

Antimicrobial resistance in Staphylococcus spp. isolated from sporotrichosis-affected cats in Brazil: Detection of MRSP and MRSA.

Recently, Brazil has experienced a zoonotic emergence of sporotrichosis. The associated cutaneous lesions are often extensive and slow to heal, thereby providing a gateway for opportunistic bacteria belonging to the normal skin microbiota. Among these, Staphylococcus spp. are of particular concern due to their high prevalence and notable levels of antimicrobial resistance. The objective of this study was to identify and characterize Staphylococcus spp. isolated from the cutaneous wounds of domestic cats undergoing treatment for sporotrichosis and exhibiting clinical signs of secondary bacterial infection. A total of 233 samples from 203 cats were analyzed. Staphylococcus spp. was isolated from 156 samples (67%), with S. aureus (42.3%) and S. felis (25.6%) being the most prevalent. Antimicrobial susceptibility testing revealed high levels of resistance to penicillin (51.9%), erythromycin (28.8%), and clindamycin (19.2%). In contrast, most isolates were susceptible to chloramphenicol (98%), ciprofloxacin (96.7%), and nitrofurantoin (93%). Multidrug-resistant strains were identified in 24% (38/156) of the isolates. Overall, 12 isolates (7.7%) were classified as methicillin-resistant staphylococci, including four methicillin-resistant S. pseudintermedius (MRSP) and one methicillin-resistant S. aureus (MRSA). To investigate the genetic profiles and epidemiological relationships of these isolates, all the MRSP and MRSA strains were subjected to whole-genome sequencing. Among the MRSP isolates, four sequence types (STs) were identified, including ST551, the founder of clonal complex (CC)551, which is commonly associated with infection in dogs. The MRSA isolate belonged to ST1176, a member of CC5, which is a globally prevalent lineage and is frequently associated with nosocomial infections in humans. This study demonstrates that Staphylococcus species, including methicillin-resistant isolates, are frequently present in the wounds of sporotrichosis-infected cats exhibiting clinical signs of secondary bacterial infection. The detection of MRSA and MRSP in a cat highlights an additional public health concern associated with feline sporotrichosis and further reinforces the growing concern regarding antimicrobial resistance in companion animals.

Animals

Artificial Intelligence in Diagnosing Depression Through Behavioural Cues: A Diagnostic Accuracy Systematic Review and Meta-Analysis.

AIM: To synthesise existing evidence concerning the application of AI methods in detecting depression through behavioural cues among adults in healthcare and community settings. DESIGN: This is a diagnostic accuracy systematic review. METHODS: This review included studies examining different AI methods in detecting depression among adults. Two independent reviewers screened, appraised and extracted data. Data were analysed by meta-analysis, narrative synthesis and subgroup analysis. DATA SOURCES: Published studies and grey literature were sought in 11 electronic databases. Hand search was conducted on reference lists and two journals. RESULTS: In total, 30 studies were included in this review. Twenty of which demonstrated that AI models had the potential to detect depression. Speech and facial expression showed better sensitivity, reflecting the ability to detect people with depression. Text and movement had better specificity, indicating the ability to rule out non-depressed individuals. Heterogeneity was initially high. Less heterogeneity was observed within each modality subgroup. CONCLUSIONS: This is the first systematic review examining AI models in detecting depression using all four behavioural cues: speech, texts, movement and facial expressions. IMPLICATIONS: A collaborative effort among healthcare professionals can be initiated to develop an AI-assisted depression detection system in general healthcare or community settings. IMPACT: It is challenging for general healthcare professionals to detect depressive symptoms among people in non-psychiatric settings. Our findings suggested the need for objective screening tools, such as an AI-assisted system, for screening depression. Therefore, people could receive accurate diagnosis and proper treatments for depression. REPORTING METHOD: This review followed the PRISMA checklist. PATIENTS OR PUBLIC CONTRIBUTION: No patients or public contribution.

Humans

Mining Stored-Specimen Studies for Information about Cancer Natural History.

The advent of new multicancer early detection tests and publication of early diagnostic results have generated expectations of clinical benefit from multicancer screening. The clinical benefit of a cancer screening test depends critically on disease natural history, which is typically learned from prospective screening studies. Retrospective studies of stored blood specimens are important in learning about a test's preclinical diagnostic performance but have rarely been used to infer natural history. The extent to which these studies might be harnessed to also learn natural history is discussed in the context of an article in this issue that infers the combined natural history of a range of cancers targeted by a multicancer early detection test using a case-control subsample of specimens from a large cohort study. The critical question concerns the identifiability of key transition rates in multistate models of natural history alongside state-specific sensitivities. The article suggests that these parameters are estimable within a Bayesian framework that leverages prior information about test sensitivity from diagnostic studies. We offer a heuristic discussion of identifiability in this setting and encourage formal study to determine the extent to which models with varying degrees of complexity may be learned from stored-specimen studies. See related article by Dai et al., p. 1535.

Humans