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Effectiveness of STK Spray® for semen stain localization on solid surfaces: A specificity and sensitivity study.

Semen identification is a crucial step in sexual assault cases. The aim of this study was to assess STK Spray®, a presumptive test for semen, under controlled conditions including, simulated crime scene stains detection. Easy to use, it can be sprayed directly onto different surfaces and visualized under UV light. Several tests were performed on five different substrates (ceramic tile, drywall, metal, wood, and faux leather). The spray was able to enhance semen fluorescence, especially in diluted samples, with characteristic "globular" spots. Although it showed good specificity, false positives could be obtained with 10% bleach. The fluorescence signals were quantified using ImageJ™ and showed a statistically significant substrate-dependent variability. Mixture analysis indicated that saliva did not interfere with detection of semen, while urine partially suppressed the signal and blood markedly affected its interpretation. Simulation tests with UV lamp comparisons confirmed the importance of choosing the right detection method and the utility of this presumptive test in combination with additional immunochromatographic tests. A preliminary signal retention test showed stable fluorescence for up to two years when stains were stored appropriately. Finally, complete DNA profiles (100% of alleles) were obtained from all samples (n = 24) after exposure to the reagent and UV light. Because of its ability to enhance semen signal, especially on specific surfaces, and its rapidity of use and detection, STK Spray® may represent a useful aid in the preliminary screening phase.

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 (ρ = 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 ≈ 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 ≈ 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 (≈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

Exploratory proteomic and metabolomic profiling of pleural effusions identifies histone H4 and alanine as promising complementary markers for pleural tuberculosis.

The diagnosis of pleural tuberculosis (Pl-TB) remains challenging. Histopathological analysis and pathogen detection in pleural biopsies are informative but limited. We investigated differentially expressed proteins and metabolites in pleural effusions from patients with Pl-TB, malignancies, and other pathologies. A proteomic analysis of pooled pleural effusions identified 45 proteins exclusively detected or upregulated in Pl-TB samples, many linked to infectious processes. Conversely, 18 proteins were uniquely found or upregulated in malignant pleural effusions, mainly associated with detoxification and hemostasis. To validate these findings, we employed targeted proteomics in individual samples. Eight proteins were validated: S100-A9, histone H4, insulin-like growth factor-binding protein 2, fibrinogen beta chain, ficolin-3, immunoglobulin heavy constant alpha 1, sulfhydryl oxidase 1, and histidine-rich glycoprotein. Additionally, NMR-based metabolomics identified 13 metabolites with differential abundance between Pl-TB and non-TB samples. Notably, N-acetyl-glycoprotein and the branched-chain amino acids, alanine and lysine differed between groups. Proteomic and metabolomic analyses revealed distinct molecular profiles between Pl-TB and non-TB patients, despite intra-group variability. To address this, we applied classification models. Histone H4 and alanine consistently emerged as discriminative features. Overall, this study provides novel insights into the molecular landscape of Pl-TB. The combined quantification of proteins and metabolites may improve differential diagnosis, although should be further validated in larger, independent cohorts before clinical application.

Humans

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 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

Proteomics in environmental pollution research: Advances, challenges, and future directions.

Environmental proteomics has emerged as a powerful approach for elucidating the molecular mechanisms underlying pollutant-induced biological effects. Although this field has developed rapidly, the systematic review of recent proteomics applications in environmental pollution research remains limited. This review explored the emerging roles of toxicoproteomics in biomarker discovery and mechanistic elucidation, as well as ecotoxicoproteomics in ecological risk assessment and bioremediation strategies. Here, we review the field, highlighting recent trends such as the integration of proteomics with genomics, transcriptomics, and metabolomics to provide a comprehensive view of biological responses to environmental stressors. We further discuss the growing application of artificial intelligence in improving proteomics data interpretation and accelerating biomarker discovery. In addition, recent technological advances in environmental proteomics are highlighted, including next-generation tissue microarray proteomics, nanoscale proteomics, single-cell proteomics, and spatial proteomics. Despite its potential, proteomics faces challenges, such as high operational costs, computational complexity in analysis, and technical limitations in low-abundance protein detection. We propose that the convergence of proteomics with artificial intelligence and multi-omics approaches offers promising solutions to these challenges, enhancing the practical application of proteomics in environmental monitoring and risk assessment.

Proteomics

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

Health bill beneath the plastic feast: A phthalate contamination alert from takeout food containers.

The rapid growth of takeout food consumption in China has raised concerns regarding exposure to phthalic acid esters (PAEs) from food packaging. This study investigated the presence, source, contribution, and health risk of PAEs in commonly used takeout containers. Widespread contamination was observed, with total PAE concentrations ranging from below the limit of detection to 222,000 ng/g. Diisobutyl phthalate (DIBP), dibutyl phthalate (DBP), and bis(2-ethylhexyl) phthalate (DEHP) were identified as the predominant compounds, accounting for 7.50 %, 14.7 %, and 18.7 % of the total concentration, respectively. These PAEs may originated from additives during manufacturing and potential contamination of raw materials. Human exposure assessment showed that daily exposure doses of DIBP, DBP, and DEHP via container ranged from 0.00 to 2340 ng/(kg&#xb7;day) among frequent takeout consumers, contributing substantially to overall PAE body burdens. To further assess exposure and associated risks, a nationwide online questionnaire survey was conducted across China. Based on this national-scale behavioral dataset, the health risks among Chinese residents were evaluated. Although the modeled non-carcinogenic risks of DIBP, DBP, and DEHP remained within acceptable limits, the simulation suggested that approximately 70 % of participants may experience potential exceedance of the carcinogenic risk threshold for DEHP. The frequency of takeout food consumption was identified as the most important factor affecting PAE exposure. These findings underscore the importance of limiting takeout frequency and reducing reliance on plastic containers to mitigate health risks. This study provides scientific evidence to support the development of safer packaging materials and informs public health strategies.

Phthalic Acids

Cine-derived mitral annular relaxation velocity for detection of preclinical left ventricular diastolic dysfunction.

OBJECTIVES: Imaging diastolic dysfunction in pre-clinical heart failure (HF) is challenging. We evaluated a novel cardiac MRI (CMR) biomarker, CMR e-prime (CMR-MARV), in patients at risk of HF. METHODS: In this substudy of the PARABLE trial (NCT04687111), 236 patients (71.6&#xa0;&#xb1;&#xa0;7.7&#xa0;years, 61.6% male) fulfilling trial-defined ALVDD citeria underwent CMR with measurement of mitral annular relaxation velocity (CMR-MARV) at four mitral annular anchor points. Diastolic strain rates from FT were also assessed. Twenty-five age- and sex-matched controls were included (73.8&#xa0;&#xb1;&#xa0;3.1&#xa0;years, 52% male). Group differences were tested with t-tests, diagnostic accuracy with ROC analysis, and predictors of diastolic dysfunction with adjusted logistic regression. RESULTS: Compared with controls, patients had significantly higher indexed maximal left atrial volume (LAVimax), LV end-diastolic and end-systolic volumes, and LV mass (all p&#xa0;<&#xa0;0.001). Of FT variables, only peak diastolic longitudinal velocity differed between groups (p&#xa0;<&#xa0;0.001). In multivariate models, CMR-MARV correlated with radial, circumferential, and longitudinal diastolic strain rates, radial and longitudinal diastolic velocities (all p&#xa0;<&#xa0;0.001), echocardiographic e' (r&#xa0;=&#xa0;0.20, p&#xa0;=&#xa0;0.007), LV mass (r&#xa0;=&#xa0;-0.18, p&#xa0;=&#xa0;0.008), LAVimax (r&#xa0;=&#xa0;-0.18, p&#xa0;=&#xa0;0.008), and NT-proBNP (r&#xa0;=&#xa0;-0.30, p&#xa0;<&#xa0;0.0001). LAVimax and CMR-MARV were strongly independently associated with ALVDD (AUC 0.89 and 0.76, respectively; p&#xa0;<&#xa0;0.0001). A combined model (LAVimax + CMR-MARV) achieved excellent discrimination (AUC 0.91, 95% CI 0.86-0.97, p&#xa0;<&#xa0;0.0001). Independent predictors included LAVimax, CMR-MARV, and peak diastolic longitudinal velocity (all p&#xa0;<&#xa0;0.001). CONCLUSION: CMR-MARV provides a simple cine-derived measure of longitudinal relaxation that correlates with established structural and biochemical markers of diastolic burden. Within an at-risk population, it offers incremental functional information beyond conventional parameters and may support multiparametric CMR phenotyping of preclinical diastolic dysfunction.

Aged

Phase-resolved functional lung MRI detects single-dose and sustained bronchodilator responses in COPD in a randomized crossover trial.

OBJECTIVES: To evaluate the effects of tiotropium/olodaterol (T/O) on phase-resolved functional lung (PREFUL) MRI parameters in hyperinflated chronic obstructive pulmonary disease (COPD) patients and examine correlations with conventional cardiopulmonary and hyperpolarized 129Xe MRI measures. MATERIALS AND METHODS: Retrospective subanalysis of a prospective, randomized, placebo-controlled, crossover trial with open-label extension. Thirty-two patients with moderate-to-severe COPD (61.5&#x2009;&#xb1;&#x2009;7.7 years; 17 men); 30 completed the MRI extension at 1.5&#x2009;T. PREFUL analysis yielded regional ventilation (RVent), flow-volume loop correlation metric (FVL-CM), normalized perfusion (QN), ventilation defect percentage (VDP), perfusion defect percentage (QDP), V/Q match metrics (VQM), and pulmonary pulse wave velocity (PWV; post-hoc parameter). Linear mixed-effects models tested treatment effects; correlations were evaluated with Spearman's rank and bootstrap 95% confidence intervals (95% CIs). RESULTS: PREFUL parameters improved after T/O single dose (SD) versus placebo, including improvements in FVL-CM by 4.1 percentage points (pp; 95% CI: 1.0 to 7.3 pp) and QN by 0.4 pp (95% CI: 0.2 to 0.6 pp) and reductions in VDP and QDP, with parallel gains in VQM(Non-Defect) (p&#x2009;<&#x2009;0.05). PWV decreased after multiple doses (-0.87&#x2009;m/s, 95% CI: -1.26 to -0.48&#x2009;m/s). PREFUL MRI baseline values showed significant correlations with pulmonary function tests, cardiac, dynamic contrast-enhanced and 129Xe MRI. SD treatment-induced absolute changes in VDP(FVL-CM) correlated with reductions in residual volume (&#x3c1;&#x2009;=&#x2009;0.41, 95% CI: 0.02 to 0.64). Further correlations were observed between PREFUL MRI and &#xb9;&#xb2;&#x2079;Xe-derived VDP, apparent diffusion coefficient, and compartment ratios. CONCLUSION: PREFUL MRI sensitively captured immediate SD T/O-induced improvements in V/Q parameters and dose-dependent PWV responses after sustained bronchodilation. KEY POINTS: Question Can phase-resolved functional lung (PREFUL) MRI sensitively capture immediate single-dose and sustain multi-dose effects of tiotropium/olodaterol on ventilation-perfusion and vascular function in COPD patients? Findings Tiotropium/olodaterol improved PREFUL MRI-derived ventilation, perfusion, and V/Q matching parameters after a single dose, with sustained pulmonary vascular improvements after repeated dosing. Clinical relevance PREFUL MRI detected immediate and sustained functional improvements after tiotropium/olodaterol and showed significant correlations with cardiopulmonary tests and hyperpolarized &#xb9;&#xb2;&#x2079;Xe MRI, supporting its role as a sensitive, radiation-free tool for monitoring COPD treatment response.

Humans

The role of artificial intelligence in the diagnosis and prognosis of traumatic brain injury based on brain CT scans: a systematic review.

Traumatic brain injury (TBI) is a leading cause of emergency department visits and a major contributor to injury-related mortality and long-term neurological disability. Non-contrast computed tomography (CT) is the gold-standard imaging modality for the rapid diagnosis of TBI. Clinical outcomes depend strongly on early detection and prompt acute management. Artificial intelligence (AI)-based models may support faster automated identification of traumatic findings and early prediction of patient prognosis.&#xa0;A systematic literature search was conducted in PubMed/MEDLINE, Scopus, IEEE Xplore, ACM Digital Library, and the Cochrane Library in accordance with PRISMA 2020 guidelines to evaluate AI-based models for automated detection of TBI-related findings on CT and for prediction of clinical outcomes. Risk of bias and applicability were assessed using QUADAS-2 for diagnostic accuracy studies and PROBAST&#x2009;+&#x2009;AI for prediction model studies.&#xa0;Twenty-two studies were included. Sixteen studies evaluated diagnostic tasks and 10 evaluated prognostic outcomes, with four studies contributing to both categories. Diagnostic performance was generally high, with many studies reporting AUC values approaching or exceeding 0.90, particularly for larger lesion volumes.Prognostic performance was more variable, with moderate to high discrimination and substantial heterogeneity. Only 9 studies incorporated independent external validation, and performance was frequently lower in external cohorts. All prognostic model studies were judged to be at high overall risk of bias using PROBAST&#x2009;+&#x2009;AI, and most diagnostic accuracy studies also demonstrated high or unclear risk of bias in at least one QUADAS-2 domain, most frequently in patient selection.&#xa0;AI-based models applied to brain CT demonstrate strong technical performance for both diagnostic and prognostic tasks in TBI. However, most studies relied on retrospective designs and lacked independent external validation which limits models generalizability and raises concern for potential overfitting. Prospective, multicenter studies with standardized methodologies and rigorous external validation are required before widespread clinical implementation.

Humans

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&#x2009;=&#x2009;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

Translating single-cell RNA sequencing into monocyte direct leukocyte subpopulation-transcript abundance assay ratio-based biomarkers (IFI27/PSAP or IFI27/CTSS) for clinical detection of viral infection.

A rapid method for triaging febrile patients by aetiology (e.g., viral or bacterial infection) using gene expression in peripheral blood (PB) is an intensively researched area. However, gene expression in blood represents a composite sum of gene expression of all the component cell types present in the sample. As a result, numerous genes are measured in most proposed signatures. Herein, we propose a simple ratio-based biomarker (RBB) called direct leukocyte subpopulation-transcript abundance assay (DIRECT LS-TA) that recapitulates gene expressions of a single cell type in PB (i.e., monocytes). Based on single-cell RNA sequencing (scRNAseq) data and bulk expression data, IFI27 and SIGLEC1 are found as interferon-stimulated genes (ISGs) predominantly expressed by monocytes. The DIRECT LS-TA method can use a simple ratio of two genes measured in PB as an RBB to represent the target gene expression in monocytes without the need for monocyte purification. Both scRNAseq and bulk RNA sequencing datasets were used to evaluate the correlation between ISG expression in monocytes and PB, with a particular focus on monocyte expression of IFI27. An iceberg plot of bulk transcriptome data was used to identify genes that were predominantly expressed by monocytes in PB. DIRECT LS-TA RBBs of the three genes (IFI27, IFI44L and SIGLEC1) were evaluated by group-wise comparison, receiver operating characteristic and meta-analysis. In addition, the conventional interferon (IFN) score was evaluated for comparison of diagnostic performance. In viral infection datasets, DIRECT LS-TA of IFI27 (IFI27/PSAP or IFI27/CTSS) was most intensely activated (p value by t test <1e-9) and had the best area under the curve (0.94) among the three potential monocyte ISGs analysed. DIRECT LS-TA SIGLEC1 was also another monocyte biomarker but showed a lower activation (p<9e-5). IFI27/PSAP showed better diagnostic performance than the conventional IFN score. On the other hand, IFI44L was not a predominant monocyte expression gene. DIRECT LS-TA of IFI27 (IFI27/PSAP or IFI27/CTSS) measured in PB was the best biomarker of viral infection and IFN activation among ISGs predominantly expressed by monocytes. It performed even better than the conventional IFN score which required quantification of eight genes. The results suggest that DIRECT LS-TA of IFI27 is a monocyte-informative biomarker which is easy to determine in PB without the need for cell sorting.

Humans

Colorimetric gold nanosensors for monitoring protein aggregation: implications for Alzheimer's disease.

Alzheimer's disease (AD) is the leading cause of dementia worldwide. It remains a major public health challenge due to the lack of early diagnostic tools and effective disease-modifying therapies. Molecularly, AD is characterized by extracellular amyloid-&#x3b2; (A&#x3b2;) plaques and intracellular Tau tangles, as well as soluble oligomers that are likely the neurotoxic species. However, the transient and heterogeneous nature of these oligomers makes them difficult to detect using conventional biosensing approaches. Nanomaterial-based colorimetric biosensors have emerged as promising platforms for detecting protein aggregates and discovering aggregation inhibitors. Specifically, the localized surface plasmon resonance properties of metallic nanomaterials can enable rapid, label-free, and visually detectable colorimetric sensing of molecular interactions. These features can be leveraged to monitor protein aggregation processes in real time and achieve high-throughput screening of aggregation inhibitors, which may collectively enable early detection and timely intervention of AD progression. This Review Article presents the design and engineering of gold-nanomaterial-based colorimetric biosensors for monitoring protein aggregation and highlights the current challenges and emerging opportunities for applying these nanosensors to combat AD.

Journal Article

Stage shift, histological differentiation, and survival patterns of lung squamous cell carcinoma versus adenocarcinoma in low-dose CT screening.

BACKGROUND: Whether LDCT-associated stage shift translates into similar survival patterns across lung cancer histologies remains uncertain. We compared stage shift, histological differentiation, tumor characteristics, and survival between lung squamous cell carcinoma (LUSC) and adenocarcinoma (LUAD) in the National Lung Screening Trial. METHODS: Among participants diagnosed with LUSC or LUAD, stage distribution and histological differentiation were compared between LDCT and chest X-ray (CXR) arms. Survival among diagnosed cases was measured from randomization. Multivariable models tested screening arm-by-histology interactions. Screen-detected LDCT tumors were compared by histology. RESULTS: During 6.5 years of median follow-up, 498 LUAD and 249 LUSC cases were diagnosed in the LDCT arm, and 374 and 212, respectively, were diagnosed in the CXR arm. LDCT was associated with higher odds of stage I disease for LUAD (adjusted odds ratio [aOR], 2.48; 95% CI 1.88-3.28) and LUSC (aOR, 1.71; 95% CI 1.17-2.48), without significant interaction (P&#x202f;=&#x202f;0.116). LDCT was associated with lower hazard of lung cancer-specific death among diagnosed LUAD cases (adjusted hazard ratio [aHR], 0.54; 95% CI 0.43-0.66), but not among diagnosed LUSC cases (aHR, 1.04; 95% CI 0.78-1.39; P for interaction<0.001). LUSC had lower screening sensitivity, more frequent detection in annual screening rounds, greater prediagnostic tumor size increase, and fewer well-differentiated stage I tumors than LUAD. CONCLUSION: LDCT was associated with stage shift for both subtypes, but favorable survival patterns among diagnosed cases were mainly observed for LUAD. Lower screening sensitivity, greater prediagnostic tumor size increase, and poorer histological differentiation may help explain why stage shift did not translate into similar survival patterns for LUSC. TRIAL REGISTRATION: ClinicalTrials.gov, NCT00047385.

Humans