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Machine learning vs. traditional methods for predicting postoperative cardiac complications after non-cardiac surgery: a systematic review and Bayesian network meta-analysis.

INTRODUCTION: Accurate prediction of peri-operative cardiac complications is critical to optimise pre-operative decision-making. Traditional risk prediction scores, such as the Revised Cardiac Risk Index, show only modest discrimination. Machine learning can model complex, non-linear relationships but their predictive performance compared with traditional scores remains unclear. METHODS: We performed a systematic review and Bayesian network meta-analysis. The primary outcome was postoperative adverse cardiac events following non-cardiac surgery. Prediction models were assessed relative to the Revised Cardiac Risk Index. As many studies evaluated multiple versions of each model type, the highest performing ('best version') and lowest performing ('worst version') results were analysed. Models were ranked using the surface under the cumulative ranking curve (SUCRA). RESULTS: Thirteen studies evaluating 54 models and 927,113 patients were included. Machine learning approaches generally outperformed traditional risk scores. Automated machine learning ranked highest (SUCRA 96.6) showed the greatest improvement in the best version analysis (mean difference (MD) 0.28 (95%CrI 0.16-0.40)) and remained superior in the sensitivity analysis (MD 0.30 (95%CrI 0.14-0.45)). Gradient boosting models showed superior performance over the Revised Cardiac Risk Index across analysis (best version: MD 0.20 (95%CrI 0.14-0.26), worst version: MD 0.18 (95%CrI 0.12-0.25), SUCRA 82.4). The Gupta Perioperative Risk for Myocardial Infarction or Cardiac Arrest score outperformed the Revised Cardiac Risk Index in the best version analysis (MD 0.16 (95%CrI 0.01-0.32)). Between-study heterogeneity was low. None of the included studies externally validated their machine learning models and only six were judged to be at low risk of bias. DISCUSSION: Most machine learning models showed better discrimination than traditional risk scores, with automated machine learning and gradient boosting models ranking highest. However, study quality, calibration reporting and absence of external validation limit immediate clinical adoption. Prospective, multicentre evaluation is required before integration of these models into peri-operative practice.

Humans

Methods for defining equity-stratifying variables: a systematic review of validation studies.

BACKGROUND AND OBJECTIVE: Disease burden is often disproportionally higher among those who are socially disadvantaged by factors defined in the PROGRESS-Plus framework (ie, Place of residence, Race/ethnicity/culture/language, Occupation, Gender/sex, Religion, Education, Socioeconomic status, and Social capital, with "Plus" covering features like age and disability). The accuracy and applicability of case definitions to identify these variables from administrative and clinical health data are unknown. We conducted a systematic review to explore how equity-stratifying variables, as categorized by the PROGRESS-Plus framework, have been defined and validated in epidemiologic studies using administrative health, population-level, or electronic health record (EHR) data. METHODS: Medline, EMBASE, CINAHL, Web of Science, and Google Scholar were searched from the inception of the databases to 2024 for validation studies of equity-stratifying variables in adults using administrative health datasets, health registries, or EHR data. Titles and abstracts, followed by relevant full-text articles, were screened in duplicate by two reviewers for eligibility. The data sources utilized, algorithms employed, and their associated performance measures were extracted and synthesized from included studies. Given substantial heterogeneity in study design, equity-stratifying variable definition, and performance metrics, meta-analysis was not possible. RESULTS: Of the 9099 unique citations screened, 188 full texts were reviewed and 116 were included in this review. Most studies were published between 2019 and 2024 (n = 64, 55%) and were validation studies of race/ethnicity definitions that used race/ethnicity codes or surname list algorithms (n = 66, 57%). No studies examined religion. Regarding the reported performance measure estimates, the race/ethnicity/culture/language equity-stratifying variables category had the largest variability across sensitivity, positive predictive value (PPV), and Cohen's Kappa. Occupation validation studies had the lowest variation in sensitivity and PPV. CONCLUSION: Despite an increasing number of publications reporting on the validation of equity-stratifying variables relevant to the PROGRESS-Plus framework, performance measures varied widely across studies. The significant heterogeneity in equity-stratifying variable definitions and methods used to validate them support the need for further rigorous validation of equity-stratifying variables in administrative and clinical health data. PLAIN LANGUAGE SUMMARY: Disease burden is often higher in people who experience financial hardships, lower level of education, discrimination due to race/ethnicity, and unstable housing. These social factors can be considered health equity factors and are important for understanding health inequalities. Health researchers often use large datasets, such as hospital or electronic health records (EHRs), to study these health equity factors. However, it is not clear how accurately these data sources capture information about people's social circumstances and how these factors are defined. In this study, we reviewed existing research to understand how health equity factors have been defined across health data sources and how accurate they are at measuring aspects of health equity and social disadvantage. Of the more than 9000 studies we identified, we included 116 that met our criteria for this systematic review. Most included studies focused on identifying race and ethnicity, often using codes or surname-based methods. We found that the accuracy of these methods varied widely across studies, meaning results may not always be reliable or comparable. Overall, our findings show that there are inconsistencies in how social factors are defined and measured in health data. This makes it difficult to fully understand and address health inequalities using routinely collected health data. More work is needed to develop and validate better quality and more consistent methods for capturing these important social factors.

Humans

Pictographs: feasibility and acceptability of a novel method of newborn identification to reduce wrong-patient errors in the NICU.

Wrong-patient errors cause serious harm in newborns. These errors involve ordering and administering tests, procedures, medications, and breast milk to an unintended patient. Newborns receiving care in neonatal intensive care units (NICUs) are at particularly high risk. Although more distinct newborn naming conventions as recommended by the Joint Commission significantly reduce wrong-patient orders, name similarities among multiple-birth infants and truncation of differentiating information in some electronic health record (EHR) systems contribute to this persistent increased risk. Accordingly, novel newborn identifiers are urgently needed. We propose Pictographs - images that are appealing, recognizable, and appropriate - to serve as visual identifiers for newborns in NICUs. Pictographs are selected by caregivers, uploaded into the EHR, and displayed at bedside. As part of a multicenter randomized controlled trial assessing effectiveness of Pictographs to prevent wrong-patient order errors, we initially evaluated feasibility and acceptability of Pictographs at two study sites. Pictographs as novel visual identifiers for newborns in the NICU were generally well received by caregivers and clinicians, and the vast majority of caregivers selected a Pictograph for their infant(s), which was posted at the bedside and uploaded into the EHR. Ordering clinicians - the primary target of the intervention to prevent wrong-patient errors - recognized the potential for Pictographs to provide a visual cue when placing orders, particularly for multiple-birth infants. Here, we describe the rationale, implementation, framework, feasibility, usefulness, and acceptability of Pictographs among key stakeholders. If found effective for preventing wrong-patient errors, Pictographs could be adopted as a patient safety solution in hospitals worldwide.

Female

Measuring Coping Strategies in Daily Life: A Systematic Review of Experience Sampling Methodology and Daily Diary Studies.

Advances in daily diary methods and experience sampling method (ESM) have improved the study of coping strategies in daily life and their role in shaping health and well-being. In this review, we examine study designs, measurement approaches, and analytical practices used to investigate coping in natural contexts. We performed a systematic review of studies published before 5 December 2025 that used daily diary or ESM to measure coping strategies over multiple days or moments. Studies were examined with regard to sampling schemes, assessment frequency and duration, measurement of coping strategies, incorporation of stressor appraisals, and analytic techniques used to model coping processes. Fifty-five studies met the inclusion criteria. Results indicated that 80% employed end-of-day diary designs, generally lasting 1-3 weeks, whereas higher-frequency ESM protocols were less common and ranged 2-14 days. Coping strategies were often assessed using abbreviated or single-item measures, frequently adapted from established questionnaires. Many studies incorporated appraisals such as perceived stressor intensity or controllability, enabling tests of coping flexibility. Multilevel modelling was the dominant analytic approach, allowing researchers to distinguish within-person dynamics from between-person differences. However, analyses were predominantly concurrent, and temporally ordered models remained comparatively rare. Overall, the literature demonstrates substantial progress in capturing coping in everyday contexts, yet heterogeneity in measurement and limited use of temporal modelling constrain cumulative knowledge about the temporal links between coping and psychological and physiological health outcomes. Future research would benefit from greater alignment between theoretical assumptions, assessment strategies, and analytic methods.

Humans

Memantine Augmentation for Obsessive-Compulsive Symptoms in Bipolar Disorder: A Randomized, Double-Blind, Placebo-Controlled Trial.

BACKGROUND: Obsessive-compulsive symptoms are frequently observed in patients with bipolar disorder and present a significant therapeutic challenge. This study evaluated the efficacy and safety of memantine as an adjunctive therapy for obsessive-compulsive disorder in patients with bipolar disorder. METHODS: In this randomized, double-blind, placebo-controlled trial, 46 patients with bipolar disorder and obsessive-compulsive disorder, stabilized on quetiapine and lithium, were randomly assigned to receive either memantine (n = 23) or placebo (n = 23) for 6 weeks. RESULTS: The memantine group showed a significant reduction in Yale-Brown Obsessive-Compulsive Scale scores compared with the placebo group (Cohen d = 1.57 vs 0.42, P < 0.001). Nausea was the most common side effect, but overall adverse effects were minimal. CONCLUSION: Memantine appears to be a safe and effective adjunctive treatment for obsessive-compulsive disorder in patients with bipolar disorder, warranting further investigation.

Humans

Teaching Acute Coronary Syndrome High-Risk ECG Interpretation and Clinical Decision-Making Through FOAMed Videos and Podcast Versus Print-Based Materials Among Emergency Care Providers: Randomized Controlled Mixed Methods Trial.

BACKGROUND: Accurate interpretation of high-risk acute coronary syndrome (ACS) electrocardiograms (ECGs) is essential for early diagnosis and timely reperfusion, yet substantial deficits persist across health care professions. Digital self-learning formats such as FOAMed (Free Open Access Medical Education) are widely used, but their effectiveness has rarely been evaluated for complex, high-risk ACS ECG patterns. Existing ECG education studies often focus on students or single professional groups and established ST-segment elevation myocardial infarction (STEMI) criteria, leaving newer guideline-recognized STEMI equivalents, selected emerging occlusion myocardial infarction (OMI)-related patterns, and interprofessional emergency care underrepresented. OBJECTIVE: This study aimed to compare the effectiveness of FOAMed podcast and videos versus traditional print-based materials for teaching high-risk ACS ECG patterns and related clinical decision-making in emergency providers. METHODS: We conducted a prospective, interprofessional, controlled mixed methods trial across 5 training sites in Germany. Paramedics, prehospital emergency physicians, and emergency department clinicians received either a FOAMed multimedia module or print-based materials through concealed allocation; deviations from the intended 1:1 ratio resulted from participant no-shows. The intervention consisted of a 30-minute supervised self-learning session. In total, 103 participants were allocated to FOAMed (n=45) or print-based materials (n=58). Two coprimary outcomes were assessed: ECG interpretation accuracy and text-based ACS clinical decision-making. Secondary outcomes included subjective confidence, learning experience, and exploratory qualitative free-text responses. Outcome assessment was automated and blinded; mixed ANOVA was the primary analysis. The study was not prospectively registered because it assessed educational outcomes in health care professionals rather than patient health outcomes. RESULTS: All 103 participants completed the study. Both groups improved, with greater gains in the FOAMed group: ECG interpretation increased from 55% to 65.5% and text-based ACS clinical decision-making from 45% to 68%, versus 57% to 60% and from 47% to 63%, respectively, in the print-based group. Effect sizes were &#x3b7;&#xb2;=0.055 for ECG interpretation and &#x3b7;&#xb2;=0.044 for clinical decision-making. Exploratory subgroup analyses provided no evidence of differential effects across age, gender, or professional background and were likely underpowered. Qualitative responses (46 and 37 entries) provided contextual insights into perceived clarity, engagement, and practical relevance supporting the quantitative findings. CONCLUSIONS: This study is innovative in directly comparing a curated FOAMed multimedia module with selected print-based materials in an interprofessional emergency care population. It differs from existing research by focusing on subtle, emerging ischemic patterns and evaluating realistic, time-limited self-learning formats. The findings provide evidence that curated FOAMed resources can produce greater short-term improvements in ECG interpretation and text-based ACS clinical decision-making than traditional print-based materials in this setting. Although implications for clinical performance remain hypothetical, concise, high-quality digital modules may represent a practical supplement to structured continuing education in emergency care.

Humans

Reinforcement learning-based dynamic ensemble for missense variant effect prediction and tiered prioritization of VUS.

BACKGROUND: Accurate classification of missense variants remains a challenging task despite major advances in genomics. Numerous computational models have been developed to assist in variant classification, but often require repeated integration and benchmarking efforts. Ensemble methods have been proposed to overcome the limitations of single predictors, but mostly rely on fixed, predefined weights that constrain their ability to capture interactions among predictive signals. METHODS: We present GenixRL, a dynamic ensemble framework that reformulates model fusion as a reinforcement learning optimization problem. GenixRL uses a Q-learning agent to learn a policy that dynamically weights the probabilistic outputs of complementary predictors, including BayesDel (addAF and noAF), ClinPred, and MetaRNN. Replacing static weighting with policy learning allows GenixRL to adaptively identify optimal weightings and substantially improve classification accuracy. RESULTS: In benchmark evaluation against 25 state-of-the-art predictors, GenixRL achieved an AUROC of 0.9644 on an independent ClinVar dataset. On saturation genome editing assays for BRCA1 and BRCA2, GenixRL achieved the best performance and ranked highest on 14 of 17 clinically significant genes in a zero-shot evaluation. Applied to uncertain and conflicting ClinVar variants, GenixRL enabled tiered, evidence-based prioritization of hundreds of thousands of variants as likely pathogenic or pathogenic with high confidence, supported by orthogonal population evidence from gnomAD. CONCLUSION: GenixRL advances pathogenicity prediction for missense variants and provides an adaptive ensemble that sorts variants of uncertain significance into tiered candidates for expert curation and functional validation.

Mutation, Missense

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

Early diagnosis of cholangiocarcinoma (CCA) remains challenging because existing diagnostic approaches often lack sufficient sensitivity for reliable detection of early-stage disease. Circulating tumor cells (CTCs) in blood and exfoliated tumor cells (ETCs) in bile represent valuable targets for liquid biopsy-based detection; however, their low abundance and the complexity of clinical sample analysis pose substantial technical challenges for reliable enrichment and identification. Herein, we present a reproducible workflow for isolating and identifying CCA tumor cells from blood for CTCs and bile for ETCs using synthetic cell-surface heparan sulfate (HS) octasaccharide-functionalized magnetic beads (MBs) on integrated microfluidic systems. The method combined sample pre-processing, magnetic bead-based enrichment, controlled low-shear mixing and immunofluorescence-based identification into a unified workflow compatible with distinct clinical sample types. Key operational parameters, including MB concentration, mixing frequency, and pressure settings, were detailed to facilitate consistent performance. Using this workflow, tumor cell capture rates of approximately 70% in bile (for ETCs) and blood (for CTCs) were achieved, with a total processing time of 60-90&#xa0;min per sample under clinically relevant low-abundance conditions. The platform enables reliable detection of as few as 1 tumor cell per mL of blood or bile. This method provides a practical and adaptable strategy for glycosaminoglycan-mediated liquid biopsy applications and may be extended to other tumor-cell enrichment workflows involving heterogeneous cell-surface interactions.

Humans

K-wire versus screw fixation in Scarf-Akin osteotomy for hallux valgus: A retrospective cohort study.

BACKGROUND: Retention of metal implants after Scarf-Akin osteotomy (SAO) may cause irritation and psychological discomfort, often necessitating a hardware removal procedure. This study aimed to introduce K-wire fixation, allowing for outpatient removal, and to compare it with screw fixation. METHODS: This retrospective study included 64 patients with hallux valgus, comprising 32 in the K-wire fixation group and 32 in the screw fixation group. Clinical outcomes were assessed using the American Orthopaedic Foot and Ankle Society (AOFAS) score, visual analogue scale (VAS), and patient satisfaction. Radiographic parameters included hallux valgus angle(HVA), intermetatarsal angle(IMA), and distal metatarsal articular angle(DMAA). RESULTS: Both groups showed significant clinical and radiographic improvement (P&#x202f;<&#x202f;0.01). No significant between-group differences were observed in the other clinical or radiographic outcomes (P&#x202f;>&#x202f;0.05). Treatment costs were significantly lower in the K-wire group (P&#x202f;<&#x202f;0.001). CONCLUSIONS: K-wire fixation provides clinical and radiographic outcomes comparable to screw fixation, while avoiding the need for an additional procedure to remove the implant. LEVEL OF EVIDENCE: Level III.

Humans

A phase I clinical study of the safety, tolerability, pharmacokinetics and pharmacodynamics of SHR-2106, an anti-CD40 antibody, following single intravenous or subcutaneous administration in healthy participants.

BACKGROUND: SHR-2106 is a humanized IgG1 monoclonal antibody that blocks CD40-CD40L interactions and has demonstrated immunosuppressive activity and graft-prolonging effects in preclinical studies. This first-in-human Phase I study evaluated the safety, pharmacokinetics, pharmacodynamics, and immunogenicity of single intravenous or subcutaneous doses of SHR-2106 in healthy adults. METHODS: This randomized, double-blind, placebo-controlled Phase I study enrolled healthy participants. Fifty-one participants were enrolled in seven cohorts and received five intravenous doses (50-1200&#x202f;mg) or two subcutaneous doses (300 and 600&#x202f;mg). Safety, serum pharmacokinetics, CD40 occupancy on B cells, and anti-drug antibodies were assessed using standard clinical and bioanalytical methods. RESULTS: SHR-2106 demonstrated a favorable safety and tolerability profile, and most treatment-emergent adverse events were mild to moderate laboratory abnormalities with incidence rates comparable to placebo. SHR-2106 exhibited nonlinear pharmacokinetics consistent with target-mediated drug disposition, with a dose-dependent increase in geometric mean terminal half-life following intravenous administration (1.83-10.7 days). Absolute bioavailability after subcutaneous administration was approximately 60%. CD40 occupancy exceeded 80% within 24&#x202f;h at all doses, with saturation duration increasing from 7 to 70 days across the intravenous dose range and remaining comparable between routes at matched doses. Anti-drug antibody incidence decreased with increasing intravenous dose and did not significantly affect pharmacokinetics or pharmacodynamics. CONCLUSION: SHR-2106 was well tolerated and achieved rapid and sustained CD40 engagement, supporting dose and route selection for Phase II studies.

Humans

A contextual activity score (CAS) for inferring ADAR-associated transcriptional activity across RNA-seq, single-cell, and spatial transcriptomics.

BACKGROUND AND OBJECTIVE: Adenosine-to-inosine RNA editing, catalyzed by Adenosine Deaminases Acting on RNA (ADARs), is a widespread modification involved in neural function, immune regulation, and cancer. The Alu Editing Index (AEI) is the standard metric to estimate ADAR activity but requires raw sequencing reads and is poorly suited for single-cell and spatial transcriptomic data. This study aimed to develop an alternative framework for inferring ADAR-associated transcriptional activity from gene expression data across diverse transcriptomic technologies. METHODS: We developed the Contextual Activity Score (CAS), a framework based on transcriptional signatures from ADAR perturbation experiments. Context-specific signatures were generated for human neurons, mouse neurons, and cancer models to infer ADAR1 and ADAR2 activity. CAS was computed from normalized gene expression matrices using regulon-based enrichment analysis. Performance was evaluated by comparing with the Alu Editing Index across bulk RNA sequencing datasets, simulated sequencing depths, and library preparation protocols. RESULTS: CAS showed strong concordance with the Alu Editing Index across multiple datasets, while remaining robust to reduced sequencing depth and different library protocols. Unlike the Alu Editing Index, CAS can be applied to single-cell and spatial transcriptomic data and enables the independent assessment of ADAR2 activity. In cancer and neuronal contexts, CAS captured biologically meaningful variations in ADAR-associated transcriptional activity at sample, cell-type, and spatial levels. CONCLUSION: CAS provides a scalable approach applicable across multiple RNA-seq protocols for estimating ADAR-associated transcriptional activity using gene expression data. This method, implemented in an open-source R package for broad adoption, expands the ability to study ADAR-associated transcriptional activity across transcriptomic modalities where direct editing quantification is challenging, such as single-cell and spatial transcriptomics.

Adenosine Deaminase

Multimodal alignment improves generalizability of genomic biomarker prediction in computational pathology.

Computational pathology models that use digitized histopathology whole-slide images have the potential to become a cost-effective and scalable alternative to molecular assays for the prediction of genomic biomarkers, a key task in precision oncology. However, as new genomic biomarkers are discovered or quantified, large, labeled datasets must be prospectively collected to train new models. To address this challenge, we developed multimodal alignment for biomarker learning and generalization (MARBLE), a multimodal contrastive pretraining strategy that integrates structured biomarker knowledge into representation learning of histopathology images. MARBLE aligns histopathology-derived representations with representations of genomic biomarkers generated by a large language model (LLM) and a protein language model (PLM). This biologically informed alignment enables data-efficient generalization to novel, out-of-distribution biomarkers. Using the MSK-IMPACT cohort of over 40,000 patients across multiple biomarker panel versions, we design experiments grounded in real-world data to demonstrate the value of our proposed approach.

CP: computational biology

Improving Patient Comfort of Vibratory Anesthetic Devices With a Dampener: A Pilot Study.

BACKGROUND: Vibratory anesthetic devices (VADs) reduce dermatologic injection pain, but their vibration can feel harsh at sensitive anatomical sites. Simple modifications improving patient comfort may enhance VAD adoption. OBJECTIVE: The authors evaluated whether dampening VAD vibration with a cotton buffer improves patient comfort and characterized tactile features influencing preferences. MATERIALS AND METHODS: In a single-site, participant-blinded pilot study (N = 53), adults received a dampened VAD (D-VAD) and standard VAD (S-VAD) at 5 sites-lateral nasal wall, submalar cheek, ear helix, lateral neck, and dorsal forearm-in randomized, contralateral application. Site-specific preference was analyzed with binomial and Cochran Q tests; demographic associations with univariate analyses. Word2vec and hierarchical clustering analyzed qualitative reasons behind patient preference. RESULTS: D-VAD was preferred at all sites across demographics-lateral nasal wall (88.7%), submalar cheek (84.9%), ear helix (88.7%), lateral neck (77.4%), and dorsal forearm (75.5%) (all p < .001), with strongest preference at face and head/neck (p = .018). Computational semantics analysis of qualitative responses identified 6 themes driving preference: Smoothness, Gentleness, Controlled, Low Frequency, Low Intensity, and Less Bothersome. CONCLUSION: Dampening VAD vibration with a cotton buffer enhances comfort across sensitive sites, with reduced harshness and smoother sensation underlying preference. This simple modification may improve patient experience, encouraging broader VAD adoption.

Humans

Intravenous lidocaine reduces the propofol EC50 for loss of consciousness and intraoperative anesthetic consumption in gynecological laparoscopy: A randomized controlled trial.

BACKGROUND: Intravenous lidocaine reduces propofol requirements and procedure-related adverse events. OBJECTIVES: The study aimed to test whether intravenous lidocaine would reduce the effect-site concentration of propofol required to achieve loss of consciousness and decrease propofol consumption during total intravenous anesthesia in gynecological laparoscopy. METHODS: This was a prospective, randomized, double-blind, placebo-controlled trial. Sixty patients were randomly allocated to receive either intravenous lidocaine (1.5 mg&#xb7;kg-&#xb9; bolus) followed by continuous infusion or an equal volume of saline. Propofol was administered via target-controlled infusion starting at an effect-site concentration of 3.5 &#x3bc;g/mL. The concentration was then adjusted in steps of 0.5 &#x3bc;g/mLaccording to Dixon's up-and-down sequential method: decreased if loss of consciousness was achieved, or increased if not. Loss of consciousness was defined as loss of response to verbal commands. The median effective concentration (EC50) of propofol for inducing loss of consciousness was calculated using the Dixon's up-and-down method. General anesthesia was maintained with propofol and remifentanil, guided by state entropy (target 40-60) and surgical pleth index (target 20-50). Drug consumption was normalized to anesthesia duration and body weight. RESULTS: The estimated EC50 of propofol for inducing loss of consciousness was significantly lower in the lidocaine group than in the saline group (3.32 &#x3bc;g/mL, 95% Confidence Interval (CI): 3.04-3.59 vs. 3.89 &#x3bc;g/mL, 95% CI: 3.50-4.28). Under the study protocol, the lidocaine group also required less propofol (8.62 mg&#xb7;kg-1&#xb7;h-1, 95% CI: 8.10-9.15 vs. 9.89 mg&#xb7;kg-1&#xb7;h-1, 95% CI: 9.05-10.73) and less remifentanil (0.23 &#x3bc;g&#xb7;kg-1&#xb7;min-1, 95% CI: 0.21-0.24 vs. 0.27 &#x3bc;g&#xb7;kg-1&#xb7;min-1, 95% CI: 0.24-0.30) compared with the saline group. CONCLUSION: Intravenous lidocaine reduced the propofol EC50 for Loss of Consciousness (LOC) and decreased intraoperative propofol and remifentanil consumptions in patients undergoing gynecological laparoscopy. These findings suggest a propofol- and opioid-sparing effect of intravenous lidocaine in this setting, although confirmation in larger multicenter trials is needed.

Humans

Autologous Fibrin Glue in Pterygium Surgery as an Alternative to Commercial Fibrin Glue.

PURPOSE: The aim of this study was to evaluate the efficacy and safety of autologous fibrin glue in pterygium surgery, comparing it with commercial fibrin glue in terms of postoperative complications, graft stability, and recurrence rate. METHODS: A prospective, randomized, double-blind study was conducted, involving 42 patients with primary pterygium who underwent autologous conjunctival-limbal transplantation. The graft was fixed using autologous fibrin glue (Group 1, G1) or commercial fibrin glue (Group 2, G2). All patients underwent surgery performed by the same surgeon and were reevaluated on postoperative days 7, 30, 90, and 180 by an independent observer, assessing clinical parameters in the preoperative, intraoperative, and postoperative periods. RESULTS: No cases of severe adverse events were reported. Complete graft dehiscence occurred in 1 patient from G1. The G2 group had more cases of subconjunctival hemorrhage ( P = 0.0355). Pyogenic granuloma was observed in 1 patient from G2 and 2 patients from G1. There was no significant difference in recurrence rates between the groups (15% in G1 vs. 5% in G2; P = 0.2918). In both groups, graft dimensions tended to decrease slightly in the early postoperative period, followed by stabilization. CONCLUSIONS: Autologous fibrin glue demonstrated efficacy and safety comparable to commercial fibrin glue, making it a viable alternative to conjunctival graft fixation in primary pterygium surgery.

Humans

Transcranial Photobiomodulation Variables Assessment Battery: Development and Validation.

Transcranial photobiomodulation (tPBM) response variability is partly driven by biophysical characteristics such as skin tone and hair properties that attenuate photon penetration, and by lifestyle factors including sleep quality, alcohol use, and nicotine consumption that disrupt the mitochondrial and vascular pathways on which tPBM acts. To date, no validated self-report tool exists to capture these moderators systematically. To address this gap, the tPBM Variables Assessment Battery was developed and psychometrically evaluated. It integrates adapted versions of established measures (Brief Pittsburgh Sleep Quality Index, E-cigarette Dependence Scale, Hair Scale Assessment PRO, Monk Skin Tone Scale, and Heaviness of Smoking Index), validated wellbeing evaluators (Ryff's Psychological Wellbeing), and custom measures (Hairstyle Classification, Hair Color Classification). Face and content validity met recommended expert thresholds, internal consistency was acceptable across adapted subscales, and criterion validity analyses confirmed meaningful associations between the lifestyle components and PROMIS-10 global health outcomes. The battery is low-burden, digitally deployable, and psychometrically defensible, offering a practical tool for characterizing the variables most likely to moderate tPBM response in home-use studies.

Humans

Furanic compounds in different coffee extraction systems: Analysis of the main influencing factors and correlation with acrylamide.

This study investigates how different coffee types representative of distinct roast profiles and brewing methods jointly affect the occurrence of furanic compounds and acrylamide in brewed coffee. Coffees were prepared using eight extraction methods (AeroPress, Clever, Chemex, French Press, Moka, Pure Brew, Turkish and V60). Five furanic compounds (furfural, furfuryl acetate, 5-methylfurfural, furfuryl alcohol and 5-hydroxymethylfurfural) were quantified in coffee powders and brews by HS-SPME-GC-MS, while acrylamide was determined by UHPLC-MS/MS. Moka and Turkish brews consistently exhibited the highest concentrations of furanic compounds, whereas paper-filtered pour-over methods (V60 and Chemex) showed the lowest levels. Pearson correlation analysis revealed coffee-dependent relationships between furanic compounds, acrylamide and extraction parameters with the strongest associations observed in dark-roasted coffee, reflecting advanced Maillard reaction chemistry. Overall, these results demonstrate that contaminant levels arise from the combined effects of intrinsic coffee chemistry and brewing mechanics and support targeted mitigation strategies: such as roast selection and brewing method optimization.

Acrylamide

Quantifying the aromatic amino acid metabolome: UPLC-MS/MS analysis of aromatic amino acids and their host and co-metabolites in plasma.

Aromatic amino acids (AAAs), tryptophan, phenylalanine, and tyrosine along with their pathway metabolites have been implicated in the pathogenesis of diseases ranging from cardiovascular, neurological, inflammatory, and cancer diseases, among others. As such, the measurement of the primary AAAs, their host pathway metabolites, and microbiome derived co-metabolites in blood can provide a sensitive reflection of systemic health. The aim of the study was to develop a method for the quantification of 17 metabolites, the three AAAs and various of their metabolites in plasma using a high-throughput ultra performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) method. The method demonstrated a dynamic range (1 to 16,700&#xa0;ng/mL), with detection limits (LOD) as low as 0.05&#xa0;ng/mL. Quantification limits ranged from 3 to 5019&#xa0;ng/mL (LLOQ) and up to 16,700&#xa0;ng/mL (ULOQ). Recovery at LQC, MQC, and HQC was satisfactory and consistent across most metabolites, with significant matrix effects observed only for 4-ethylphenol sulfate. Furthermore, intra and inter-day accuracy and precision met all acceptance criteria at all quality control concentrations for most of the metabolites. Measurement of NIST SRM 1950 showcased the method's accuracy for most of the metabolites. Finally, the method was applied on the analysis of plasma samples from 55 individuals (13 males and 42 females) providing information on AAAs and their pathway metabolites relevant concentrations in human plasma.

Amino Acids, Aromatic