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PubMed2026

Molecular Landscape and Advanced Diagnostic Technologies for BRAF Mutations in Cancer: From Quantitative PCR and ddPCR to CRISPR-Based Platforms.

BRAF mutations are key oncogenic alterations across multiple malignancies, including melanoma, thyroid carcinoma, colorectal cancer, non-small cell lung cancer, glioma, and hairy cell leukemia. The most prevalent variant, BRAF-V600E, induces constitutive activation of the MAPK signaling pathway, promoting tumor progression and influencing therapeutic responsiveness. Accurate detection of BRAF alterations is therefore essential for molecular classification, prognostic assessment, treatment selection, and resistance surveillance. This review summarizes the molecular heterogeneity of BRAF mutations and critically evaluates current diagnostic methodologies. Conventional approaches such as allele-specific PCR and Sanger sequencing are compared with advanced quantitative platforms, including high-resolution melting analysis, droplet digital PCR, and next-generation sequencing, with emphasis on analytical sensitivity, mutation coverage, and clinical applicability. Emerging technologies such as CRISPR-based assays, rolling circle amplification systems, and nanoparticle-based biosensors and point-of-care diagnostic platforms are also discussed for their potential to enhance ultra-sensitive detection, particularly in liquid biopsy settings. These emerging tools are highlighted for their potential to enable ultra-sensitive, rapid, and decentralized mutation detection, particularly in liquid biopsy settings. Key challenges, including intratumoral heterogeneity, low allele-frequency variants, FFPE-associated artifacts, and clonal evolution under therapeutic pressure, are examined within a translational framework. In addition, we examine critical barriers to clinical implementation, including standardization, cost, and global accessibility of molecular diagnostics, and outline potential solutions through scalable technologies and decentralized testing strategies. We propose that optimal BRAF testing requires a mutation subclass-informed and clinically integrated strategy combining comprehensive baseline profiling with longitudinal molecular monitoring. Future diagnostic paradigms will likely integrate multi-omics data and artificial intelligence (AI)-assisted interpretation to refine precision oncology implementation. Looking forward, we propose that optimal BRAF testing will require integration of multi-omics profiling with AI-assisted interpretation, enabling automated variant classification, real-time clinical decision support, and improved prediction of therapeutic response and resistance.

Humans↗

PubMed2026

The landscape of pruning for large language models: A systematic review and unified taxonomy.

Confronting the inherent tension between the exceptional capabilities and the immense computational costs of Large Language Models (LLMs), pruning has become a crucial technique for achieving efficient deployment. However, a systematic analytical framework dedicated specifically to LLM pruning remains absent. In this paper, we aim to bridge this gap. We first elucidate the theoretical foundations that underpin the effectiveness of pruning, namely overparameterization and redundancy, and then propose a multidimensional taxonomy that organizes existing approaches along the axes of granularity, timing, and criteria. Building upon this unified perspective, we further analyze performance recovery mechanisms and the broader evaluation ecosystem, while also exploring forward-looking challenges such as interpretability, automation, and hardware-algorithm co-design. Through this comprehensive synthesis, we seek to provide an integrated and coherent analytical lens for advancing both research and practice in LLM pruning.

Large Language Models↗

PubMed2026

Complication rates of 16- and 18-gauge needles for native kidney biopsies: a systematic review and proportional meta-analysis.

This systematic review and meta-analysis evaluated complication rates and diagnostic yield reported in studies of adult native kidney biopsy using 16-gauge (16 G) or 18-gauge (18 G) needles. We included randomized trials and cohort studies of real-time ultrasound-guided biopsies, including case series. MEDLINE, Embase, and CENTRAL were searched through October 2024. Two reviewers independently performed study selection, data extraction, and risk of bias assessment using Joanna Briggs Institute tools. Random-effects meta-analyses estimated pooled proportions with 95% confidence intervals (CI), and univariable random-effects meta-regression explored study-level associations with major complications, transfusion, or gross hematuria. We screened 4,499 titles and abstracts and reviewed 319 full-text articles; 62 studies comprising 68 biopsy series were included. The pooled major complication rate in studies using 16 G needles was 1.83% (95% CI: 1.20-2.79) and 1.29% (95% CI: 0.78-2.13) in studies using 18 G needles, with no statistically significant difference. Mean glomerular yield was 18.8 with 16 G and 17.5 with 18 G needles. In study-level meta-regression, studies with higher prevalence of acute kidney injury, lower mean estimated glomerular filtration rate, or lower mean hemoglobin reported higher pooled complication rates. Most studies were single-arm cohorts; between-needle differences therefore reflect indirect study-level contrasts. Interpretation is limited by retrospective design and heterogeneity across studies. Overall, studies using both needle sizes reported low complication rates and similar diagnostic yield, although definitions and reporting varied. Direct comparative studies are needed to determine whether meaningful differences exist.

Humans↗

PubMed2026

Efficacy of dapagliflozin on hepatic steatosis and fibrosis in patients with type 2 diabetes mellitus and metabolic dysfunction-associated steatotic liver disease: a pre-specified single-arm analysis from a randomized controlled trial.

AIM: To evaluate the association of dapagliflozin therapy with changes in hepatic steatosis and non-invasive fibrosis surrogate markers in patients with type 2 diabetes mellitus (T2DM) and Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) over 12 months. METHODS: This is a pre-specified single-arm analysis from a randomised, open-label, parallel-group trial. Of 54 participants randomised to dapagliflozin 10 mg daily, 50 (92.6%) completed the 12-month follow-up and were included in the per-protocol analysis. Assessments at baseline, 3, 6, and 12 months included transient elastography (CAP and LSM), ultrasonography, and biochemical tests. Primary endpoints were changes in hepatic steatosis (CAP) and non-invasive fibrosis surrogates (LSM). RESULTS: Significant reductions were observed in hepatic steatosis (CAP: 316.7 to 245.7 dB/m; mean change - 71.02 dB/m, 95% CI: -63.4 to - 78.6; p < 0.001) and in liver stiffness as a non-invasive fibrosis surrogate (LSM: 8.59 to 7.28 kPa; mean change - 1.31 kPa, 95% CI: -0.92 to - 1.70; p < 0.001). Improvements were also observed in glycaemic control, body weight, lipid profile, liver enzymes, ultrasonographic steatosis grading, and serum fibrosis markers. Genitourinary infections were the most frequently reported adverse events (32%); no serious adverse events were recorded. CONCLUSIONS: Dapagliflozin was associated with significant improvements in hepatic steatosis, non-invasive fibrosis surrogate markers, metabolic parameters, and liver function in T2DM patients with MASLD over 12 months. These findings provide region-specific evidence for an Indian population and support further controlled investigation. However, these findings should be interpreted in light of the pre-specified single-arm design of this analysis, the open-label methodology, relatively small sample size, and the absence of liver biopsy confirmation.

Humans↗

PubMed2026

Machine learning-based prediction of unplanned readmission and construction of an online calculator for elderly patients with mild ischemic stroke.

OBJECTIVE: To screen for independent risk factors for unplanned readmission in elderly patients with mild ischemic stroke, and to construct and validate an online risk prediction calculator based on an interpretable machine learning model, thereby providing a promising practical tool for accurate clinical assessment of 30‑day all‑cause unplanned readmission risk in this population. METHODS: A prospective cohort study was conducted, including 1050 patients aged ≥ 60 years with mild ischemic stroke admitted between August 2023 and September 2024. Participants were randomly divided into a training set (840 cases) and a test set (210 cases) at a ratio of 8:2. Risk factors were screened by univariate analysis and multivariable Logistic regression. Four machine learning models, namely LightGBM, XGBoost, Random Forest, and K‑Nearest Neighbors (KNN), were developed and their performance was evaluated using AUC, accuracy, sensitivity, and specificity as metrics. The SHAP framework was used for interpretability analysis, and an online calculator was subsequently developed based on the optimal model. RESULTS: Univariate analysis showed significant differences (P < 0.05) in 13 factors including age, smoking, AIP, TyG index, HALP score, etc. Multivariable Logistic regression identified age (OR = 9.752), smoking (OR = 5.171), AIP (OR = 6.691), TyG index (OR = 4.393), HALP score (OR = 2.831), and ≥ 2 comorbidities (OR = 3.664) as independent risk factors. All four machine learning models demonstrated good predictive performance. Based on a comprehensive evaluation of multiple metrics and computational efficiency, the LightGBM model exhibited the best predictive performance (AUC = 0.884, accuracy = 0.829, sensitivity = 0.812, specificity = 0.875). SHAP analysis showed that age, AIP, TyG index, smoking, and HALP score were key predictors. An online calculator developed based on this model enables individualized risk predictions. CONCLUSION: Key risk factors associated with 30‑day unplanned readmission in elderly patients with mild ischemic stroke were identified. The LightGBM model demonstrated high predictive accuracy, and together with the interpretability analysis and online calculator, offers a practical tool to support clinical risk assessment. However, this tool requires future external validation.

Humans↗

PubMed2026

A systematic review of human avoidance learning: Cognition, computation, and methods.

Avoidance behaviour is fundamental for survival but can become maladaptive in clinical conditions. A large body of literature has accumulated on the dynamics of human avoidance learning. However, current theories and overviews do not provide an exhaustive account of this evidence. In this systematic review, we identify N = 116 studies on human avoidance learning. We analyse these studies with the goal of distilling robust empirical phenomena as a basis for theory-building, and examine their diagnostic value in differentiating between competing theories. We find that the evidence is difficult to reconcile with foundational two-factor and classical safety-signal accounts, and most strongly supports expectancy- and inference-based views, in which avoidance responses are selected with respect to represented consequences. At the same time, no current framework provides a complete account of the evidence: several findings point to an additional role for operant valuation, Pavlovian influences, and contextual or latent-state control over the expression of avoidance. Methodologically, we observe that the problem setting in the most common experimental paradigms is radically simpler than real-world avoidance and therefore unlikely to expose the limits of inferential or reflective mechanisms. Consequently, we argue that paradigms with greater computational demands and more realistic action affordances are required to identify the mechanisms underlying avoidance learning. Collectively, these insights provide a foundation for theoretical refinement, computational modelling, and methodological innovation, with implications for advancing interventions targeting maladaptive avoidance.

Humans↗

PubMed2026

Recovery of polysaccharides from marc and pomace through sequential extractions assisted by ultrasound, enzymes and acid maceration.

This study evaluated the pilot-scale recovery of polysaccharides from Vitis vinifera pomace/marc using sequential extraction strategies combining high-power ultrasound (UAE), enzymes (EAE), and acid maceration (AAE). Laboratory-scale trials identified optimal conditions for enzyme dosage and liquid/solid ratio (L/S). Pilot-scale trials demonstrated that the extraction sequence and the processing byproducts influenced extraction efficiency, total soluble polysaccharide in the extract (TSP), and polysaccharide composition. Post-maceration at pH 3.2, with/without the maximum enzyme dose after UAE in a L/S of 1.3/1, improved structural polysaccharide extraction from Viura pomace, while Tempranillo marc showed better recovery of pectic families and TSP with UAE + EAE. Separating grape pomace extract (UAE) from the post-maceration stage at pH 3.2 produced two extracts: E1, with higher yield (19.9%), enriched in structural polysaccharides and oligosaccharides, and E2, enriched in high and medium molecular weight pectic polysaccharides (58.03%), a low degree of esterification (17.1%) and more complex rhamnogalacturan structures.

Polysaccharides↗

PubMed2026

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↗

PubMed2026

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↗

PubMed2026

Effectiveness and usability of artificial intelligence-powered assistive technologies in Supporting daily activities of children with cerebral palsy: a systematic review.

BACKGROUND: Cerebral Palsy (CP) is the main cause of motor disabilities in childhood, necessitating innovative approaches to rehabilitation and assistive technology (AT). Simultaneously, artificial intelligence (AI) is increasingly being integrated into devices to create more adaptive, personalized, and effective AT. This systematic review aimed to evaluate the effectiveness and usability of AI-powered assistive technologies designed to support daily activities and rehabilitation in children with CP. MATERIALS AND METHODS: Five databases, including Scopus, Web of Science, PubMed, Embase, and IEEE Xplore, were systematically searched, and 23 articles were included in the final analysis. Articles were identified, selected, and categorized into emerging thematic areas based on the primary function and application of the technology. RESULTS: Five key thematic topics were identified: 1) AI-driven motor rehabilitation and gait training for functional mobility; 2) intelligent assessment and monitoring systems for clinical decision support; 3) AI-supported communication, social interaction, and intention recognition tools; 4) gamified and virtual reality-based interventions to enhance engagement and usability; and 5) smart assistive systems supporting daily living and independent mobility. The findings demonstrate a strong trend toward the application of AI technologies in personalized, engaging, and data-driven interventions for children with CP. However, the field is predominantly in the proof-of-concept stage, with limitations including small sample sizes, lack of long-term clinical validation, challenges in user-centered design, and usability for children with CP. CONCLUSION: AI-powered assistive technologies hold significant potential for transforming the care of children with CP by enabling highly personalized and engaging interventions. To actualize this potential, future work must realize that practical application remains challenging owing to limited clinical validation, technological integration, and usability barriers for children with CP. Future research must prioritize user-centered design and multidisciplinary collaboration to ensure that AI and robotic advancements improve the usability and quality of life for children with CP.

Humans↗

PubMed2026

Modulation of heart rate and heart rate variability during animal-assisted treatment of patients in a minimally conscious state: A randomized controlled crossover study.

BACKGROUND: Animal-assisted treatment (AATx) is a promising and increasingly used approach in neurorehabilitation, yet its psychophysiological effects remain largely unexplored. Patients in a minimally conscious state (MCS) show severely altered consciousness with minimal but definite behavioral signs of awareness. Because behavioral assessment in this population is limited, psychophysiological measures such as heart rate (HR) and heart rate variability (HRV) may offer valuable insights into autonomic regulation during therapy. AIM: The present study investigated whether AATx influences HR and HRV compared to treatment as usual (TAU). METHODS: A randomized controlled crossover design with repeated measures was conducted. HR and HRV data were recorded using an Empatica E4 wristband, and linear mixed-effects models were fitted for each outcome variable. The analytic sample included twenty-one patients with MCS who completed at least one of the four sessions. RESULTS: We found a significant decrease in mean HR (estimate = -12.75, p = .041) and a significant increase in the standard deviation of normal-to-normal intervals (SDNN) (estimate = 15.76, p = .020) during AATx compared to TAU from the pretreatment to the posttreatment phase, indicating enhanced parasympathetic activation and greater autonomic flexibility. Other HRV parameters revealed no significant effects of AATx, though trends were consistent with the hypotheses. CONCLUSIONS: These findings provide preliminary physiological evidence that AATx can modulate autonomic activity in MCS patients. Despite limitations related to sample size and recording quality, the results highlight the potential of AATx as an emotionally engaging intervention in early neurorehabilitation.

Humans↗

PubMed2026

Hysteroscopic platelet-rich plasma and medically assisted reproduction outcomes: a systematic review and SWOT analysis.

BACKGROUND: Platelet-rich plasma (PRP) has been proposed as an adjuvant treatment in reproductive medicine. While most evidence refers to blind intrauterine instillation, subendometrial administration under hysteroscopic guidance allows targeted delivery under direct visualisation. This systematic review aimed to synthesise the available evidence on hysteroscopic PRP administration and its impact on clinical medically assisted reproduction (MAR) outcomes. METHODS: A systematic search was conducted from inception to December 2025 across major databases. Studies were included if they evaluated hysteroscopic PRP administration in women undergoing MAR, comparing reproductive outcomes between treated and control groups. RESULTS: Out of 142 records, 3 studies met the inclusion criteria. Study populations were heterogeneous and included women with refractory thin endometrium and/or a history of implantation failure. Hysteroscopic PRP administration protocols varied in timing, technique, and dosage. In a prospective case-control study, hysteroscopic intraendometrial PRP injection at a depth of 2-3 mm in the four uterine walls, using an ovum aspiration needle, on days 11-13 of the cycle prior to euploid frozen embryo transfer (ET), was associated with higher implantation (IR), clinical pregnancy (CPR), and live birth rates (LBR) compared with standard therapy. Conversely, no significant differences in CPR, miscarriage rate, or LBR were observed in an observational study evaluating a single intraendometrial PRP injection (35-40 mL, 2-3 mm depth), administered via endoscopic needle on days 6-8 of the menstrual cycle preceding frozen ET, alone or after electrical impulse therapy. A randomised controlled trial in women undergoing intrauterine insemination reported a significant improvement in CPR following hysteroscopic subendometrial PRP instillation in the four uterine walls (1.0 mL each). CONCLUSIONS: Current literature on hysteroscopic PRP administration in reproductive medicine is limited, and robust conclusions cannot yet be drawn. Well-designed randomised controlled trials with standardised protocols are needed to clarify its clinical role.

Humans↗

PubMed2026

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↗

PubMed2026

Dexamethasone as an adjuvant to continuous erector spinae plane block for postoperative analgesia after video-assisted thoracoscopic surgery for pulmonary nodule surgery: a randomized controlled trial.

BACKGROUND: While dexamethasone is proven to enhance single-shot erector spinae plane block (ESPB), its role as an adjuvant in continuous ESPB catheters is unclear. This randomised controlled trial evaluated whether adding dexamethasone to ropivacaine improves analgesia after video-assisted thoracoscopic surgery (VATS). METHODS: 85 patients undergoing VATS with continuous ESPB were randomised to receive postoperative infusion of either 0.2% ropivacaine(C-ESPB group) or ropivacaine with 10 mg dexamethasone(D + C-ESPB group). The primary outcome was resting pain visual analog scale (VAS)at 12 h postoperatively, while secondary outcomes included QoR-15 scores, tramadol consumption, time to first analgesic requirement, postoperative adverse events, 3-month incidence of chronic pain, catheter-related complications, pain intensity at other times, and hospital stay. RESULTS: The D + C-ESPB group had significantly lower resting pain at 12 h [2.56 (1.03) vs 3.24 (1.21), mean difference -0.680, p = 0.006]; and lower coughing pain at 12 h [4.60 (1.48) vs 5.69 (1.35), mean difference 1.086, p < 0.001], with analgesic superiority sustained through 72 h. Quality of Recovery-15 scores were higher at 12 h [124.70 (12.48) vs 117.26 (12.24); mean difference -7.436, p = 0.007] and 48 h [141.60 (5.51) vs 138.98 (6.64); mean difference -2.628, p = 0.050]; Total tramadol consumption over 72 h was markedly reduce [0 (0,100) vs 100 (75,100), z = -3.807, p < 0.001], and hospital stay was shorter [Mean (SD) 6.09 (1.34) d vs 6.93 (1.55)d, p < 0.001]. The intervention did not, however, alter the 3-month incidence of chronic postsurgical pain (31% vs 34%, p = 0.756). CONCLUSION: Dexamethasone significantly enhances the analgesic efficacy of continuous ESPB, improving early pain control, recovery quality, and opioid-sparing after VATS, but does not reduce the incidence of chronic persistent surgical pain.

Humans↗

PubMed2026

Risk factors and management strategies for needle disengagement from the visual field in pediatric robot-assisted laparoscopic pyeloplasty.

OBJECTIVE: This study aimed to identify risk factors for suture needle disengagement from the visual field during pediatric robot-assisted laparoscopic pyeloplasty (RALP) and propose effective strategies for prevention and management. METHODS: A retrospective cohort study analyzed clinical data from 339 pediatric patients who underwent RALP for ureteropelvic junction obstruction (UPJO) at a single institution between August 2017 and December 2020. Patients were categorized based on the occurrence of needle disengagement from the visual field. Various patient demographics and surgical procedural factors were evaluated. Univariate and multivariate logistic regression, along with LASSO regression, identified independent risk and protective factors. RESULTS: Needle disengagement occurred in 38 (11.21%) of 339 cases. Multivariate logistic regression identified five independent risk factors for needle disengagement: use of a 3-mm auxiliary trocar (OR = 4.69, 95% CI: 1.98-12.53, P < 0.001), non-standard needle holder use (OR = 2.32, 95% CI: 1.04-5.18, P = 0.038), unshaped suture needles (OR = 3.16, 95% CI: 1.44-7.19, P = 0.005), simultaneous use of ≥2 intra-abdominal sutures (OR = 2.46, 95% CI: 1.15-5.48, P = 0.023), and clamping the needle shank during withdrawal (OR = 3.42, 95% CI: 1.40-8.21, P = 0.006). Conversely, sufficient assistant experience (>10 cases) was identified as a protective factor (OR = 0.39, 95% CI: 0.18-0.88, P = 0.021). CONCLUSION: Suture needle disengagement from the visual field during pediatric RALP is associated with specific technical and instrumental factors. Implementing targeted strategies-such as mandating specialized needle holders, preoperative needle shaping, a single-needle workflow, prioritizing clamping the suture thread over the needle shank during withdrawal, and ensuring adequate assistant training-has the potential to significantly reduce significantly mitigate the risk of needle loss and enhance overall surgical safety in pediatric RALP.

Humans↗

PubMed2026

Prothrombin complex concentrate (PCC) vs. non-PCC strategies for warfarin reversal in left ventricular assist device recipients: A systematic review and meta-analysis.

BACKGROUND: Left ventricular assist devices (LVADs) prolong survival in end-stage heart failure, and warfarin thromboprophylaxis is recommended to prevent device thrombosis and thromboembolic complications. When bleeding occurs or emergency surgery is required, rapid anticoagulation reversal is critical. Prothrombin complex concentrate (PCC) provides rapid reversal; however, its risk-benefit profile in LVAD recipients remains unclear. We conducted a systematic review and meta-analysis comparing PCC with non-PCC strategies for warfarin reversal in LVAD recipients. METHODS: MEDLINE, Embase, and Scopus were searched through June 2025 for studies of PCC versus non-PCC strategies for warfarin reversal in LVAD recipients. Two reviewers independently extracted data. Random-effects models were used to pool arm-level estimates and to pool head-to-head comparisons using mean differences or risk ratios (RRs). RESULTS: Eighteen studies involving 779 patients were included. Arm-level pooled estimates for PCC versus non-PCC comparators were 24.0% versus 15.8% for mortality, 16.5% versus 12.1% for thrombotic events, and 3.1 versus 5.7 for FFP units. Arm-level time to INR correction was longer with PCC overall (16.5 versus 13.6 h), driven by one elective cohort, but faster within the ICH subgroup (6.0 versus 13.7 h). In head-to-head comparisons, PCC achieved faster INR correction than non-PCC comparators (mean difference - 7.6 h; p = 0.001) and required fewer FFP units (-2.6 units; p = 0.019), with no significant difference in all-cause mortality (RR 1.14; p = 0.490) or thrombotic events (RR 1.43; p = 0.176). CONCLUSIONS: In head-to-head studies, PCC was associated with faster INR correction and lower FFP requirements than non-PCC strategies, whereas mortality and thrombotic events did not differ significantly. Given the observational evidence, wide confidence intervals, and heterogeneity, equivalent safety cannot be established, and prospective studies are needed to define the relative safety and effectiveness of the two approaches. IMPLICATIONS FOR CLINICAL PRACTICE: PCC-based strategies may be considered for urgent warfarin reversal in LVAD recipients, particularly when rapid INR reduction or avoidance of large-volume plasma transfusion is clinically important. Treatment decisions should account for the indication, bleeding severity, and underlying thrombotic risk. TRIAL REGISTRATION: CRD42024573925.

Humans↗

PubMed2026

Immersive virtual reality-assisted anatomy training improves endotracheal intubation performance in simulation: a randomized controlled trial among Chinese non-anesthesiology residents.

INTRODUCTION: This study aimed to compare immersive virtual reality (IVR)-assisted versus conventional anatomy training for teaching endotracheal intubation (ETI) to novice non-anesthesiology residents enrolled in China's Standardized Residency Training program. METHODS: A total of 90 non-anesthesiology residents without prior ETI experience were randomly assigned to either an IVR group receiving IVR-assisted anatomy training (n = 45) or a control group receiving conventional anatomy training (n = 45). All participants underwent a standardized teaching protocol. The primary endpoint was residents' ETI performance on a simulator, assessed using both the Global Rating Scale (GRS) and a task-specific checklist. The secondary endpoints included changes in written multiple-choice question (MCQ) scores and residents' evaluations of the course. RESULTS: In practical ETI assessments on a manikin, the IVR group achieved significantly higher scores on the task-specific checklist than the control group (90.34 ± 2.89 vs. 87.20 ± 3.29; p < 0.001), whereas GRS scores were comparable between groups. Both groups showed significant post-training improvement in knowledge scores (p < 0.001), with the IVR group showing a greater gain in theoretical knowledge (54.0% vs. 36.3%; p < 0.001). Participants in the IVR group also expressed a stronger preference for their training method (80.8%) and reported higher levels of motivation, confidence, and enjoyment (all p < 0.05). CONCLUSION: IVR-assisted anatomy training enhances the effectiveness of ETI training for novice non-anesthesiology residents, offering an interactive, engaging, and reproducible approach within China's Standardized Residency Training framework.

Humans↗

PubMed2026

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 π-π 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 mg 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↗