Search PubMedSearch

SEARCH · Search PubMed

Results for “Therapy, Computer-Assisted”

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.

768 records · Page 6Linked to original sources

Bioactive peptides for meat quality and preservation: Integrating peptidomics and computational screening.

Bioactive peptides generated from meat proteins, fermented meat products, and slaughter by-products have attracted increasing attention as functional molecules for improving meat quality and preservation. In meat systems, peptides can be produced through endogenous postmortem proteolysis, microbial fermentation, gastrointestinal digestion, or controlled enzymatic hydrolysis of underutilized animal by-products. These peptides are closely associated with key meat science endpoints, including postmortem tenderization, oxidative stability, color retention, flavor development, microbial inhibition, and the valorization of processing by-products. However, although high-resolution peptidomics has greatly expanded the identification of meat-derived peptide sequences, their translation into practical meat applications remains limited by matrix interactions, processing stability, sensory constraints, safety concerns, and insufficient validation in real meat systems. This review synthesizes recent advances in meat-related peptidomics and computational screening, including sequence-based prediction, machine learning, molecular docking, molecular dynamics, stability assessment, and safety-oriented filtering. Particular attention is given to how these approaches can prioritize peptides with antioxidant, antimicrobial, flavor-modulating, and preservation-related functions under meat-specific technological constraints. By integrating peptide generation pathways, mass spectrometry-based identification, in silico prioritization, and meat quality endpoints, this review proposes a stage-gated framework for translating meat-derived bioactive peptides from discovery to application. Future research should strengthen matrix-specific validation, standardized peptidomic reporting, and safety assessment to support the use of bioactive peptides in meat quality improvement, clean-label preservation, and circular utilization of meat industry by-products.

Animals

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

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

Animals

Policy pathways and historical insights: Canada's evolving approach to psychedelic access for end-of-life distress.

Canada's evolving attitudes toward psychedelic interventions in palliative and end-of-life care reflect a departure from historically prohibitionist policies and an emerging recognition of their therapeutic potential for individuals facing end-of-life distress. This shift parallels international regulatory developments in jurisdictions such as the United States, Australia and parts of Europe, where cautious policy liberalization has signaled growing acceptance of psychedelics within clinical contexts. Canada is also a relevant case because of its formative role in the development of modern palliative care, its contemporary frameworks emphasizing holistic approaches to suffering at the end of life, and its experience with medical assistance in dying, all of which have shaped national conversations about suffering, autonomy, and end-of-life care. Additionally, Canada's distinctive historical approach to drug regulation-marked by federal flexibility, mechanisms for compassionate access, and responsiveness to patient advocacy-combined with rising public demand and incremental provincial changes, may uniquely position the country along a transitional pathway toward clinical integration of psychedelics in palliative care. At the same time, Canadian drug policy remains heterogeneous across substances and provinces, underscoring the political contingency of reform. Within this dynamic landscape, Canada's psychedelic drug policy trajectory aligns with broader international trends toward cautious medicalization and regulated access to psychedelic therapies, while also offering an instructive case for how end-of-life frameworks and federal-provincial governance shape policy development.

Humans

Nurse-led titration models of care for heart failure reduced ejection fraction: a systematic narrative review of characteristics, patient outcomes, and healthcare resource utilization.

AIMS: Nurse-led titration (NLT) models of care assist with delivery of guideline directed medical therapy for patients with heart failure with reduced ejection fraction (HFrEF). Effectiveness of NLT is established but there is limited information of characteristics of models, patient outcomes and healthcare resource utilization. To build upon the existing evidence by providing a systematic narrative review of the literature of NLT of medications for patients with HFrEF. This review syntheses characteristics of NLT models of care, patient outcomes and healthcare resource utilization. METHODS AND RESULTS: A systematic narrative literature review with systematic search strategy, identification of results, thematic analysis and narrative synthesis. A search was conducted from 2012 to 2025 in Medline, Cinahl complete, Embase and Cochrane. Sixteen studies of NLT models of care were identified from 1944 screened records. Characteristics of models of care were participation of nurses, multidisciplinary teams, follow-up and common features of service delivery. Patient outcomes of mortality were favourable for those that received NLT. There is some evidence of changes in healthcare resource utilization; studies in which the NLT groups received more HF nurse visits and greater HF medication use also reported reduced rehospitalizations. CONCLUSION: Findings reinforce the published benefits of NLT. Additional studies examining adverse events and quality-of-life outcomes are needed to strengthen the evidence base. Several studies suggest a shift in resource use with NLT, highlighting the need for an economic evaluation to inform a cost-effective model of care.

Humans

The Impact of Upper Extremity Rehabilitation on Fatigue in Individuals With Multiple Sclerosis: A Systematic Review.

BACKGROUND: Although numerous interventions have been investigated to alleviate fatigue in people with multiple sclerosis (PwMS), evidence regarding the effects of upper extremity rehabilitation on fatigue remains limited. OBJECTIVE: The objective of this review was to evaluate and synthesize the available evidence on the effects of upper extremity rehabilitation interventions on fatigue in PwMS. METHODS: This review was conducted in accordance with the PRISMA guidelines and was prospectively registered in the PROSPERO database. A systematic search of PubMed, Web of Science, and Scopus was performed up to August 2026. Studies were eligible if they investigated the effects of upper extremity rehabilitation interventions on fatigue in PwMS. The risk of bias of randomized controlled trials was assessed using the Risk of Bias 2 (RoB 2), and the certainty of the evidence was appraised using the GRADE methodology. RESULTS: Nine studies including 250 participants (136 intervention, 114 control) met the inclusion criteria. The included studies evaluated a range of technology-assisted, exercise-based, home-based, and task-oriented upper extremity rehabilitation approaches, with some interventions incorporating more than one therapeutic or technological component. Fatigue outcomes were measured using the Fatigue Severity Scale (FSS) and the Modified Fatigue Impact Scale (MFIS). Risk of bias was low in three randomized controlled trials, with some concerns in two and high in two; among the two crossover studies, one was rated as low risk and one as high risk. GRADE assessment showed low certainty of evidence for studies using the FSS and very low certainty for those using the MFIS, indicating an overall low certainty of the available evidence. CONCLUSIONS: The available evidence is insufficient to draw definitive conclusions regarding the effects of upper extremity rehabilitation on fatigue in PwMS. Further high-quality randomized controlled trials are required.

Humans

Meta-PseU: A meta-classifier for robust prediction of RNA pseudouridine modification sites from long sequences.

BACKGROUND AND OBJECTIVES: Pseudouridine (Ψ) represents one of the most abundant and conserved RNA modifications. Ψ provides an additional hydrogen-bond donor that enhances RNA structural stability and modulates translation. It participates in diverse biological processes, including RNA-protein interactions, splicing, translational control, and stress responses. Aberrant pseudouridylation is implicated in cancer, neurodegenerative disorders, and autoimmune diseases. Despite its biological importance, experimental identification of Ψ sites remains time-consuming and costly, limiting the feasibility of transcriptome-wide profiling. Computational approaches have therefore become essential complements to experimental techniques. However, state-of-the-art machine-learning and deep-learning predictors often suffer from limited generalizability due to small training datasets. To overcome these issues, we aim at constructing new long-sequence datasets and developing a novel Ψ site predictor. METHODS: New long-sequence datasets were constructed as benchmarks for RNA Ψ-site prediction. The Ψ modification sites in RMBase 3.0 were mapped to the reference genomes across three species of human, mouse, and yeast, and the RNA sequences with a length of 201 were generated by extending the upstream and downstream from the mapped, central sites. To eliminate sequence redundancy, the sequences were clustered using CD-HIT with a 70% sequence identity threshold. We developed Meta-PseU, a logistic regression-based meta-classifier that considered 118 machine learning and deep learning classifiers. The datasets and programs are freely accessible at https://github.com/kuratahiroyuki/MetaPseU. RESULTS: By optimizing model configuration, we proposed the Meta-PseU model stacking 32 machine learning and deep learning classifiers out of 118 classifiers. Meta-PseU substantially improved model generalizability, overcoming a key limitation of existing approaches. It greatly outperformed state-of-the-art predictors and achieved increasing accuracy with increasing sequence length. CONCLUSIONS: Long-sequence datasets were newly constructed as benchmarks for RNA Ψ-site prediction. Meta-PseU offers a new framework for robust Ψ-site identification by using long sequences.

Pseudouridine

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. 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 + AI for prediction model studies. 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 + 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. 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

Applications of quantum AI in brain disorder diagnosis: A systematic review.

BACKGROUND AND OBJECTIVE: Brain disorder diagnosis and prediction remain challenging because neuroimaging, electrophysiological, behavioral, and multimodal data are high-dimensional, noisy, heterogeneous, and limited by small clinical cohorts. This systematic review synthesised applications of quantum artificial intelligence (QAI) for brain disorder diagnosis, prediction, detection, and monitoring. METHODS: Following PRISMA guidelines, studies published from 2016 to 13 January 2026 were retrieved from Scopus, Web of Science, and IEEE Xplore. After screening, 36 studies met the eligibility criteria and were qualitatively analysed according to disorder category, data modality, QAI method, implementation setting, validation strategy, and performance. RESULTS: At the broader disease-group level, neurodegenerative disorders were the most frequently investigated, followed by mental health and psychiatric disorders. At the individual level, Parkinson's disease and schizophrenia were the leading applications, followed by depression, anxiety, Alzheimer's disease, and stress-related tasks. MRI-based modalities were the most frequently used data source, followed by multimodal data and EEG. Methodologically, primary QAI approaches were dominated by quantum neural and QDL architectures, followed by quantum-inspired optimization or feature-selection methods and quantum-kernel/conventional QML classifiers. Qiskit/IBM Quantum and PennyLane were the most frequently reported quantum software frameworks. However, most studies relied on simulators, classical quantum-inspired implementations, or unclear implementation settings, with limited real-hardware evaluation. CONCLUSIONS: QAI shows emerging potential for brain disorder analysis, particularly through hybrid quantum-classical learning, quantum neural architectures, quantum-kernel methods, and quantum-inspired optimization. Nevertheless, current evidence remains preliminary and requires larger datasets, subject-level and external validation, fair classical benchmarking, noise-resilient circuits, real quantum hardware evaluation, explainability, and clinical validation.

Humans

Affective reactivity to a remote computer-based Trier Social Stress Test during a planned quit attempt: associations with short-term cigarette smoking lapse risk.

BACKGROUND: The Trier Social Stress Test (TSST) elicits affective responses and has been linked to smoking behavior. However, its remote use during a planned quit attempt-when stress reactivity may influence early lapse-remains understudied. OBJECTIVE: To quantify affective reactivity to a remotely administered TSST on a planned quit date following overnight abstinence and evaluate associations with cigarette use and lapse within 48 h. METHODS: This secondary analysis used data from a randomized controlled trial of adult smokers completing a remotely administered TSST following overnight nicotine abstinence. Urge, anxiety, and stress were assessed using visual analog scales and summarized using area under the curve (AUC) metrics. Smoking outcomes included cigarette count and lapse within 48 h. Associations were estimated using generalized estimating equations. RESULTS: In adjusted models, anxiety reactivity-but not urge or stress-was associated with cigarette count and lapse. Greater anxiety exposure (AUCtot) and change above baseline (AUCab) were associated with higher cigarette count (IRR=1.0004, 95%CI:1.0002-1.001, p=.002; IRR=1.01, 95%CI: 1.002-1.01, p=.002) and increased odds of lapse (OR=1.001, 95%CI: 1.0001-1.002, p=.03; OR=1.02, 95%CI: 1.001-1.03, p=.03). Effect sizes were small. CONCLUSIONS: Anxiety reactivity under nicotine deprivation was associated with increased cigarette use and lapse 48 h post quit attempt, suggesting individual differences in stress-evoked anxiety may serve as a behavioral marker for early lapse. Remote TSST administration appears feasible for eliciting affective responses on a quit date.

Humans

PaNDA: Efficient Optimization of Phylogenetic Diversity in Networks.

Phylogenetic diversity (PD) plays an important role in biodiversity, conservation, and evolutionary studies by measuring the diversity of a set of taxa based on their phylogenetic relationships. In phylogenetic trees, a subset of k taxa with maximum PD can be found by a simple and efficient greedy algorithm. However, this algorithmic tractability is lost when considering phylogenetic networks, which incorporate reticulate evolutionary events such as hybridization and horizontal gene transfer. To address this challenge, we introduce PaNDA (Phylogenetic Network Diversity Algorithms), the first software package and interactive graphical user-interface for exploring, visualizing, and maximizing diversity in phylogenetic networks. PaNDA includes a novel algorithm to find a subset of k taxa with maximum diversity, running in polynomial time for networks of bounded scanwidth, a measure of tree-likeness of a network that grows slower than the well-known level measure. This algorithm considers the variant of PD on networks in which the branch lengths of all paths from the root to the selected taxa contribute towards their diversity. We demonstrate the scalability of this algorithm on simulated networks, successfully analyzing level-15 networks with up to 200 taxa in seconds. We also provide a proof-of-concept analysis using a phylogenetic network on Xiphophorus species, illustrating how the tool can support diversity studies based on real genomic data. The software is easily installable and freely available at https://github.com/nholtgrefe/panda. Additionally, we extend the definition of PD to semi-directed phylogenetic networks, which are mixed graphs increasingly used in phylogenetic analysis to model uncertainty of the root location. We prove that finding a subset of k taxa with maximum diversity remains NP-hard on semi-directed networks, but do present a polynomial-time algorithm for networks with bounded level.

network

Effectiveness of high-power laser use in the removal of esthetic restorations: a systematic review.

This systematic review aimed to evaluate the effectiveness of high-power lasers in the removal of esthetic restorations compared with conventional methods. The review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and registered in PROSPERO (registration number: CRD420251055736). A comprehensive electronic search was performed in MEDLINE, Scopus, Embase, Web of Science, and the Cochrane Library. Study selection, data extraction, and methodological quality assessment were independently performed by four reviewers using QUIN tool for in vitro studies. A total of 2.384 records were identified, of which 19 in vitro studies conducted on extracted human permanent teeth met the eligibility criteria and were included in the qualitative synthesis. The included studies evaluated different high-power laser systems, predominantly Er: YAG and Er, Cr: YSGG lasers, as well as CO₂ lasers. Five studies were classified as high quality, whereas the remaining fourteen studies were classified as moderate quality. Available laboratory evidence suggests that laser-assisted techniques may represent a potential alternative approach for removing esthetic restorations, with advantages including conservative tissue removal, reduced damage to underlying tooth structures, and intrapulpal temperature increases within acceptable limits. The Er: YAG laser was the most frequently investigated system, with power settings ranging from 1.5 to 5.9 W, showing particularly favorable laboratorial performance in the removal of lithium disilicate restorations, especially in thinner substrates. Within the limitations of the available evidence, high-power lasers appear to be a promising and minimally invasive alternative to conventional methods for the removal of esthetic restorations. However, the predominance of in vitro studies highlights the need for well-designed clinical trials to confirm these findings and support their clinical application.

Humans

Comparison of Iodinated Contrast Doses Based on Total Body Weight and Lean Body Weight in Pediatric Patients: Impact on Image Quality and Contrast Exposure.

INTRODUCTION: Iodinated contrast dosing in pediatric computed tomography (CT) traditionally relies on total body weight (TBW), which may result in excessive contrast administration, particularly in patients with higher adiposity. Lean body weight (LBW)-based protocols have shown promise in adults but remain underexplored in children. Therefore, the aim of this study was to compare contrast volume requirements and hepatic enhancement quality among three dosing protocols: LBW-based, TBW-based, and the Control Group (CG), based on the institutional standard for pediatric abdominal CT. METHODS: This prospective study enrolled 66 patients (age 0-16 years) undergoing contrast-enhanced abdominal CT between September 2023 and August 2024. Patients were randomly assigned to receive iodinated contrast (iobitridol 350mg I/mL) dosed by: (1) LBW (0.63 g iodine/kg x LBW, calculated using Peters formula; n = 23), (2) TBW (0.46 g iodine/kg x TBW; n = 20), or (3) institutional control protocol (2 mL/kg x TBW, equivalent to 0.7 g iodine/kg; n = 23). Kruskal-Wallis, ANOVA, Two-way ANOVA, ANCOVA, Scheirer-Ray-Hare, and Cohen's Kappa tests with Likert scale were used. RESULTS: The LBW group received lower median contrast volumes (27 mL; IQR, 10-80 mL) compared to the TBW group (34.5 mL; IQR, 18-78 mL) and the CG group (40 mL; IQR, 13-80 mL), although the differences did not reach statistical significance (P > 0.05). Notably, this reduction did not compromise hepatic enhancement, which remained comparable to the CG (552 ± 139 HU; P = 0.107). CONCLUSION: Lean body weight may be a useful parameter for estimating contrast dose in pediatric abdominal CT, potentially reducing administered volumes without compromising diagnostic image quality. IMPLICATIONS FOR PRACTICE: These results provide early evidence that LBW-based dosing may support more individualized contrast administration in pediatric CT, potentially reducing exposure-related risks.

Humans

Could the preoperative urethral curve be used to predict immediate urinary continence following Retzius-sparing robot-assisted radical prostatectomy? A retrospective multi-center study.

PURPOSE: Immediate urinary continence (UC) recovery following Retzius-sparing robot-assisted radical prostatectomy (RS-RARP) remains highly variable, highlighting the need for reliable preoperative prediction. We aimed to develop and validate models to identify patients likely to achieve immediate UC recovery following RS-RARP. MATERIALS AND METHODS: A total of 580 prostate cancer patients who underwent RS-RARP from four medical centers were assigned to a training set (n=348), an internal validation set (n=103) and an external validation set (n=129). Independent predictors were identified through univariate analysis and LASSO regression. A nomogram was constructed using multivariate logistic regression. Its performance was evaluated with receiver operating characteristic (ROC) curve, calibration curves, and decision curve analysis. RESULTS: Immediate UC recovery was observed in 84.5% (294/348) of patients in the training cohort, 80.6% (83/103) in the internal validation cohort, and 81.4% (105/129) in the external validation cohort, respectively. Multivariate analysis identified membranous urethral length (MUL) (OR=1.23, P=0.029) and urethral curvature (OR=2.84, P<0.001) as independent predictors, while prostate volume (PV) (OR=0.84, P <0.001) as a protective factor. The nomogram integrating MUL, PV, and urethral curvature demonstrated superior predictive accuracy, with an AUC of 0.87 (95% CI, 0.83-0.91) in the training cohort. The bootstrap-corrected calibration slope was 0.96, and the Brier score was 0.08.&#xa0;Calibration curves and decision curve analysis confirmed the predictive accuracy and clinical utility of the nomogram. CONCLUSIONS: Our study introduces a novel quantitative method for assessing urethral curvature. The mpMRI-based model, integrating urethral curvature and prostate spatial configuration, offers enhanced predictive accuracy for postoperative immediate UC recovery.

Humans

Effects of testosterone-augmented multimodal exercise intervention in spinal cord injury: a randomized controlled trial.

CONTEXT: Spinal cord injury (SCI) leads to profound muscle atrophy, aerobic deconditioning, and metabolic dysfunction. Exercise-based interventions alone produce modest benefits. Whether testosterone can augment physiologic responses to exercise in this population remains untested. OBJECTIVE: To evaluate efficacy and safety of home-based intervention combining functional electrical stimulation-assisted leg cycling (FES-LC), arm ergometry (AE), and testosterone compared with FES-LC, AE plus placebo in adults with SCI. METHODS: This randomized, placebo-controlled, double-blind trial enrolled 84 adults (76 males and 8 females) aged 19-70 years with SCI (neurologic levels C4-T12; AIS grades A-D). Participants were randomized to multimodality intervention (home-based FES-LC, AE and intramuscular testosterone undecanoate) (n = 38) or control intervention (FES-LC, AE plus placebo) (n = 46) for 16 weeks. The primary outcome was change in aerobic capacity (peak VO2) during AE cardiopulmonary exercise testing. Secondary outcomes included lean mass, hemoglobin, cardiometabolic markers, and safety. RESULTS: Mean (SD) age was 44 (13) years and time since injury was 13.9 (13) years). Between-group changes in peak VO2 were not statistically significant. Within-group improvements were larger in multimodality (&#x223c;19% increase; 0.10 L/min; 95% CI, 0.02-0.18 L/min) compared to controls (&#x223c;6% increase; 0.06 L/min; 95% CI, -0.01-0.13). The multimodality group gained significantly more lean mass (whole-body:1.84 kg, 95% CI: 0.52-3.16, P = .007; lower extremity 0.92 kg, 95% CI: 0.38-1.45, P = .001), and anemia was corrected in a greater proportion of participants. Adverse event rates were similar between groups. CONCLUSION: A home-based multimodality intervention combining FES-LC, AE, and testosterone was safe and associated with greater improvements in lean mass and hemoglobin. Although between-group differences in aerobic capacity were not statistically significant, greater within-group increases were observed in the multimodality group. These findings may inform future studies of testosterone-augmented exercise interventions for individuals living with SCI.

Humans

Performance of Photon-counting CT for Assessing Pretreatment Breast Cancer: Comparison with Mammography, MRI, and 18F-FDG PET/CT.

Background Photon-counting CT (PCCT) offers improved spatial resolution, contrast to noise ratio, and dose efficiency, but its clinical utility remains incompletely defined for breast cancer. Purpose To evaluate the feasibility of PCCT for pretreatment breast cancer assessment through comparisons with MRI, full-field digital mammography (FFDM), and fluorine 18 (18F) fluorodeoxyglucose (FDG) PET/CT. Materials and Methods In this prospective study (March-May 2025), female participants with breast lesions categorized as Breast Imaging Reporting and Data System 4C or higher at US or FFDM underwent breast MRI and multiphasic contrast-enhanced PCCT. 18F-FDG PET/CT was performed in a subset with locally advanced disease. Four radiologists independently evaluated lesion morphologic characteristics, additional findings, and clinical TNM stage. Agreement was analyzed using intraclass correlation coefficients (ICCs) and &#x3ba; statistics. The diagnostic performance for additional lesions and nodal metastasis was compared with the reference standard (pathologic examination). Results Among 126 participants (mean age, 58.1 years &#xb1; 12.3 [SD]), interreader agreement across PCCT, MRI, and FFDM was good to excellent. PCCT agreed with MRI for lesion characterization (&#x3ba; = 0.57-0.96) and clinical T categorization (&#x3ba; = 0.86-0.88), with highest agreement with pathologic size (ICC, 0.70-0.81). For 46 pathologically confirmed additional lesions, PCCT was more sensitive than FFDM (difference, 44% [95% CI: 19, 66]) and similar to MRI (difference, 7% [95% CI: -5, 21]). Additionally, 44% (95% CI: 27, 52) of microcalcifications were missed at PCCT versus FFDM. For pathologically confirmed nodal metastasis, PCCT was more sensitive (difference, 10% [95% CI: 1, 20]) and accurate (difference, 6% [95% CI: 1, 11]) than MRI. For clinical N category, PCCT agreed with PET/CT (&#x3ba; = 0.82 [95% CI: 0.62, 0.96]; n = 19). Two distant metastases identified at PCCT were consistent with 18F-FDG PET/CT and pathologic findings. Conclusion PCCT demonstrated similar performance to MRI for lesion characterization and detection of additional lesions, with better performance for nodal metastasis evaluation; however, detection of microcalcifications was limited. &#xa9; RSNA, 2026 Supplemental material is available for this article.

Humans

CT-Derived pelvic morphometry for preoperative risk assessment of recurrent unilateral inguinal hernia.

BACKGROUND: Recurrent inguinal hernia remains a significant challenge in abdominal wall surgery despite advances in mesh-based repair techniques and minimally invasive approaches. Although pelvic skeletal morphology has been implicated in inguinal hernia development, its association with recurrent disease remains incompletely understood. This study aimed to evaluate computed tomography (CT)-derived pelvic morphometric parameters and investigate their potential value in preoperative recurrence risk assessment. METHODS: This retrospective study included 251 male patients with preoperative abdominal CT examinations and complete clinical records who underwent elective inguinal hernia repair at a tertiary referral center. After applying the predefined eligibility criteria, 188 patients with unilateral inguinal hernias constituted the primary study cohort, including 162 primary and 26 recurrent unilateral hernias. The Radoievitch angle and Ami's line were measured independently by two blinded radiology residents using a standardized CT-based pelvic morphometric measurement protocol, and the mean values were used for analysis. Multivariable logistic regression and receiver operating characteristic (ROC) curve analyses were performed to evaluate the association between pelvic morphometric parameters and recurrent inguinal hernia. RESULTS: Patients with recurrent unilateral inguinal hernias demonstrated significantly greater affected-side Ami's line measurements (8.27&#x2009;&#xb1;&#x2009;0.63 vs. 7.90&#x2009;&#xb1;&#x2009;0.71&#xa0;cm, p&#x2009;=&#x2009;0.014) and larger Radoievitch angles (40.68&#x2009;&#xb1;&#x2009;4.02&#xb0; vs. 38.80&#x2009;&#xb1;&#x2009;3.68&#xb0;, p&#x2009;=&#x2009;0.018) than patients with primary unilateral hernias. Both the Radoievitch angle (OR 1.14, 95% CI 1.01-1.28, p&#x2009;=&#x2009;0.033) and Ami's line (OR 2.26, 95% CI 1.14-4.49, p&#x2009;=&#x2009;0.020) remained independently associated with recurrent inguinal hernia after adjustment for age and body mass index. ROC analysis demonstrated modest discriminatory performance (AUC 0.634 for the Radoievitch angle and 0.633 for Ami's line), while the multivariable model incorporating age, body mass index, and Ami's line showed slightly improved discrimination (AUC 0.655). CONCLUSION: CT-derived pelvic morphometric parameters were independently associated with recurrent unilateral inguinal hernia. Although their individual discriminatory performance was modest, standardized CT-based pelvimetry may serve as an objective adjunctive tool for individualized preoperative recurrence risk assessment in patients who already undergo CT imaging for unrelated clinical indications. Prospective multicenter studies are warranted to validate these findings and determine their clinical applicability.

Humans

Non-destructive prediction of lead content in oilseed rape leaves by fluorescence hyperspectral technology based on neural network.

Based on fluorescence hyperspectral imaging (FHSI), this study targeted rapid, non-destructive quantification of lead (Pb) content in oilseed rape leaves treated with varying silicon (Si) concentrations, acquiring fluorescence spectra over the 484.43-1001.61&#xa0;nm wavelength range. To optimize spectral data quality, preprocessing methods (Savitzky-Golay smoothing, first derivative, detrending) were comprehensively compared. Characteristic wavelengths were then selected via interval variable iterative shrinkage, which effectively compressed data dimensionality and reduced computational load. A hybrid SE-CL1DA model, fusing a 1D convolutional neural network, a long short-term memory network and SE attention mechanism was constructed, with Bayesian optimization tuning hyperparameters to boost stability. The BO-SE-CL1DA outperformed both traditional machine learning and insufficiently optimized deep learning model (Rp2=0.9609, RMSE&#xa0;=&#xa0;0.0377&#xa0;mg/kg, RPD&#xa0;=&#xa0;5.1736), thus enabling accurate Pb estimation, supporting Si-regulated heavy metal stress management and facilitating agricultural contamination monitoring.

Plant Leaves

Discovery of NAT-6-321056 as a novel modulator of VEGFR2 signaling to suppress tumor angiogenesis.

Vascular endothelial growth factor receptor 2 (VEGFR2) is a master regulator of angiogenesis and cancer progression. However, current VEGFR2 modulators face significant challenges, including off-target toxicity and acquired resistance, underscoring the urgent need for novel therapeutic agents with improved efficacy and safety profiles. Here, we reported that virtual screening of 39,442 natural products from the ZINC natural products-derived library, coupled with molecular docking and molecular dynamics (MD) simulations to evaluate the binding stability of candidate compounds, identified NAT-6-321056 as a highly promising modulator of VEGFR2 signaling. Biological evaluations demonstrated that NAT-6-321056 exerted potent inhibition on the growth of a broad spectrum of cancer cells, including both solid tumors and hematological malignancies. In EA.hy 926 endothelial cells and SK-N-DZ neuroblast cells, the compound significantly suppressed proliferation, migration, and invasion. Microscale thermophoresis (MST) confirmed direct binding of NAT-6-321056 to VEGFR2 with favorable affinity. Kinase profiling against a panel of 33 kinases indicated that NAT-6-321056 exhibited a multi-kinase modulation profile. Mechanistic studies revealed that NAT-6-321056 suppressed the expression of hypoxia-inducible factor 1-alpha (HIF-1&#x3b1;) and was associated with reduced VEGFR2 phosphorylation and attenuation of the downstream ERK/JNK/AKT signaling pathways. Moreover, NAT-6-321056 exhibited robust in vivo anti-angiogenic effects in both the chick chorioallantoic membrane (CAM) assay and transgenic zebrafish vascular fluorescence imaging models. Computational absorption, distribution, metabolism, excretion, and toxicity (ADMET) prediction suggested acceptable drug-like properties. Collectively, these findings demonstrated that NAT-6-321056 is a promising modulator of VEGFR2 signaling with potent anti-angiogenic activity and represents a viable candidate for cancer therapy.

Vascular Endothelial Growth Factor Receptor-2