Search Results (398)

Cuscohygrine (CUS) and hygrine (HYG) are pyrrolidine alkaloids proposed as biomarkers of coca leaf consumption, a culturally accepted practice in some Latin American countries. Differentiating legal coca use from illicit cocaine consumption holds forensic importance. While LC-MS/MS is preferred, GC-MS remains widely used in Latin American toxicology labs due to accessibility. This study critically evaluates the analytical limitations of GC-MS for detecting CUS and HYG in biological matrices. Key parameters—injector temperature (180–290 °C), injection mode (split/splitless), solvent, liner condition, and matrix—were systematically studied. GC-MS showed significant limitations: low-abundance, non-specific fragments (m/z 42, 84, 98, 140) failed to meet the identification criteria in SIM mode. Thermal degradation of CUS to HYG and CUS-d6 to HYG-d3 was observed, especially with splitless injection and aged liners. Matrix effects produced signal enhancement ranging from +29% to +316%, meaning that analyte responses in biological samples were significantly higher than in neat standards, likely due to reduced degradation or adsorption. Although deuterated internal standards (CUS-d6) partially corrected signal variability and matrix enhancement, these corrections were not sufficient to overcome the fundamental limitations of GC-MS, including poor ion specificity and compound instability. These findings support the need for LC-MS/MS-based approaches for reliable alkaloid detection and question the suitability of GC-MS for CUS analysis in forensic toxicology contexts. Full article

Background/Objectives: Despite advancements in surgery, esophagectomy remains one of the most challenging and complex gastrointestinal surgical procedures, burdened by significant perioperative morbidity and mortality rates, as well as high financial costs. Recognizing the need for standardized care provided by a multidisciplinary healthcare team, the EUropean PErioperative MEdical Networking (EUPEMEN) initiative developed a dedicated protocol for perioperative care of patients undergoing esophagectomy, aiming to enhance recovery, reduce morbidity, and homogenize care delivery across European healthcare systems. Methods: Developed through a multidisciplinary European collaboration of five partners, the protocol incorporates expert consensus and the latest scientific evidence. It addresses the entire perioperative pathway, from preoperative preparation to hospital discharge and postoperative recovery, emphasizing patient-centered care, risk mitigation, and early functional restoration. Results: The implementation of the EUPEMEN esophagectomy protocol is expected to improve patient outcomes through a day-by-day structured prehabilitation plan, meticulous intraoperative management, and proactive postoperative rehabilitation. The approach promotes reduced postoperative complications, earlier return to oral intake, and shorter hospital stays, while supporting multidisciplinary coordination. Conclusions: The EUPEMEN protocol for esophagectomy provides a comprehensive guideline framework for optimizing perioperative care in esophageal surgery. In addition, it serves as a practical guide for healthcare professionals committed to advancing surgical recovery and standardizing clinical practice across diverse care environments across Europe. Full article

Background: Sex differences in type 2 diabetes (T2D) are a growing area of diabetes research. No data have been reported on sex differences with oral semaglutide (oSEMA) in a real-world setting. Methods: We included people with T2D who started treatment with oSEMA in routine clinical practice between November 2021 and November 2022, with at least one report of clinical follow-up (FU) data at 3 months. We evaluated in women with T2D (WWT2D) the clinical effectiveness of oSEMA and factors associated with clinical response and persistence. We also analyzed differences in baseline characteristics, clinical effectiveness, persistence rates and safety according to biological sex. Results: Of the 1018 subjects [median age: 63 years, body mass index (BMI): 33.8 kg/m², HbA1c: 7.8%], 469 were WWT2D. In WWT2D, oSEMA reduced HbA1c by 0.7% [−0.1 to −1.3] and 0.9% [−0.2 to −1.5] at the 6- and 12-month FU visits, while weight decreased by 4.6% [2.0 to 7.9] and 7.2% [2.5 to 10.9], respectively. Weight loss was >10% in 29.8% of WWT2D (95% CI 25.8 to 34.1); meanwhile, the combined endpoint (HbA1c decrease ≥ 1% + weight reduction ≥ 5%) was achieved in 23.5% (95% CI 19.8 to 27.5%) of WWT2D at the 12-month FU visit. Achievement of glycaemic targets was similar in women and men (59.3% vs. 61.1%). We found no sex differences in weight loss (6.9% vs. 6.8%), oSEMA maintenance dose, persistence rate (76.3% vs. 77.3%), or adverse events. Conclusions: oSEMA was effective and safe in WWT2D in a real-world setting, with nearly one-third of patients reporting weight loss >10% and more than two-thirds achieving HbA1c < 7%. oSEMA showed no sex bias in terms of effectiveness and safety. Full article

Dementia is a neurodegenerative disorder characterized by progressive cognitive impairment that significantly affects daily living. Early detection of Alzheimer’s disease—the most common form of dementia—remains essential for prompt intervention and treatment, yet clinical diagnosis often requires extensive and resource-intensive procedures. This article explores the effectiveness of automated Natural Language Processing (NLP) methods for identifying Alzheimer’s indicators from audio transcriptions of the Cookie Theft picture description task in the PittCorpus dementia database. Five NLP approaches were compared: a classical Tf–Idf statistical representation and embeddings derived from large language models (GloVe, BERT, Gemma-2B, and Linq-Embed-Mistral), each integrated with a logistic regression classifier. Transcriptions were carefully preprocessed to preserve linguistically relevant features such as repetitions, self-corrections, and pauses. To compare the performance of the five approaches, a stratified 5-fold cross-validation was conducted; the best results were obtained with BERT embeddings (84.73% accuracy) closely followed by the simpler Tf–Idf approach (83.73% accuracy) and the state-of-the-art model Linq-Embed-Mistral (83.54% accuracy), while Gemma-2B and GloVe embeddings yielded slightly lower performances (80.91% and 78.11% accuracy, respectively). Contrary to initial expectations—that richer semantic and contextual embeddings would substantially outperform simpler frequency-based methods—the competitive accuracy of Tf–Idf suggests that the choice and frequency of the words used might be more important than semantic or contextual information in Alzheimer’s detection. This work represents an effort toward implementing user-friendly software capable of offering an initial indicator of Alzheimer’s risk, potentially reducing the need for an in-person clinical visit. Full article

Background/Objectives: Patients with immune-mediated inflammatory diseases (IMIDs) treated with disease-modifying antirheumatic drugs (DMARDs) are at increased risk of latent tuberculosis infection (LTBI) reactivation, influenced by DMARD type. This study aimed to determine LTBI prevalence using interferon-gamma release assays (IGRAs) and identify associated risk factors in IMID patients in a middle-high TB burden setting in Mexico. Methods: A cross-sectional study was conducted from July 2024 to April 2025 at an IMID clinic. Patients aged ≥18 years, either receiving DMARDs or prior to initiating treatment, were included. LTBI was diagnosed using the QuantiFERON-TB Gold Plus assay. Bivariate analysis was performed using the chi-square test, and multivariate analysis was conducted. Results: LTBI prevalence was 34.2% (95% CI 29.1–39.7%) according to QFT-Plus and 35.6% (95% CI 29.7–42.0%) according to TSTs (n = 230). Prior TB exposure was the strongest risk factor (aOR 4.20, 95% CI 1.74–10.12, p = 0.001), while rheumatoid arthritis was associated with a lower LTBI likelihood (aOR 0.31, 95% CI 0.16–0.59, p < 0.001). Conclusions: A high prevalence of LTBI was observed in patients with IMIDs treated with DMARDs. Prior tuberculosis exposure was strongly associated with LTBI. These findings highlight the importance of LTBI screening in this population to prevent reactivation. Full article

Indoors, the infection risk of diseases transmitted through the airborne route is estimated from indoor carbon dioxide (CO₂) levels. However, the approaches to assess this risk do not account for the airborne concentration of pathogens, among other limitations. In this study, we analyzed the relationship between airborne SARS-CoV-2 levels and environmental parameters. Bioaerosols were sampled (n = 40) in hospital corridors of two wards differing in the COVID-19 severity of the admitted patients. SARS-CoV-2 levels were quantified using droplet digital PCR. SARS-CoV-2 was detected in 60% of the total air samples. The ward where the mildly ill patients were admitted had a higher occupancy, transit of people in the corridor, and CO₂ levels, but there were no significant differences in SARS-CoV-2 detection between wards. The mean CO₂ concentration in the positive samples was 569 ± 35.6 ppm. Considering all samples, the CO₂ levels in the corridor were positively correlated with patient door openings but inversely correlated with SARS-CoV-2 levels. In conclusion, airborne SARS-CoV-2 can be detected indoors with optimal ventilation, and its levels do not scale with CO₂ concentration in hospital corridors. Therefore, CO₂ assessment should not be interpreted as a surrogate of airborne viral presence in all indoor spaces. Full article

Speech emotion recognition has become increasingly important in a wide range of applications, driven by the development of large transformer-based natural language processing models. However, the large size of these architectures limits their usability, which has led to a growing interest in smaller models. In this paper, we evaluate nineteen of the most popular small language models for the text and audio modalities for speech emotion recognition on the IEMOCAP dataset. Based on their cross-validation accuracy, the best architectures were selected to create ensemble models to evaluate the effect of combining audio and text, as well as the effect of incorporating contextual information on model performance. The experiments conducted showed a significant increase in accuracy with the inclusion of contextual information and the combination of modalities. The results obtained were highly competitive, outperforming numerous recent approaches. The proposed ensemble model achieved an accuracy of 82.12% on the IEMOCAP dataset, outperforming several recent approaches. These results demonstrate the effectiveness of ensemble methods for improving speech emotion recognition performance, and highlight the feasibility of training multiple small language models on consumer-grade computers. Full article

The presence of Candida spp. in urine has traditionally been considered to be a colonization; however, in certain clinical circumstances, such as in critically ill patients, immunocompromised individuals, or those with chronic diseases, it gains greater relevance due to the possibility of active infection and complications. The aim of this study was to characterize the epidemiology (incidence, species distribution, demographic characteristics, and origin) of Candida spp. isolates in urine through a retrospective cross-sectional analysis of urine culture isolates from clinical samples between January 2016 and December 2023. Out of a total of 111,656 urine cultures, Candida spp. was isolated at 2.72% (n = 3037). The most frequently isolated species was Candida albicans (54.25%; 1646/3037), followed by Nakaseomyces glabrata (22.78%; 692/3037) and Candida tropicalis (10.2%; 311/3037). Advanced age (>70 years), male sex, presence of a urinary catheter, and origin from intensive care units, oncology, or surgical services were variables associated with a higher risk of candiduria, highlighting the relevance of candiduria in the presence of such clinical scenarios. Full article

Habitat fragmentation and loss seriously threaten Ceroxylon palms, a key and vulnerable species in Andean forests. Given the need for efficient tools for their monitoring and conservation, this study aimed to evaluate the effectiveness of deep learning YOLO models for the automatic detection of Ceroxylon individuals in high-resolution UAV images. Three versions of YOLO (v8, v10, and v11) were analyzed, each in nano (“n”), medium (“m”), and extra-high (“x”) configurations, considering both processing time and detection accuracy. Difficulties in orthomosaic reconstruction were addressed by specific adjustments to the photogrammetric software parameters. The nine resulting models were tested in seven study plots, with the YOLOv8-m configuration standing out as the one that best balanced processing speed and accuracy, achieving the following outstanding metrics: F1 = 0.91; mAP50 = 0.98; and mAP50-95 = 0.62. These results demonstrate the practical value of YOLO model automatic detection for the informed management and effective conservation of Ceroxylon in mountain ecosystems. Full article

Uncomplicated hypertension (UH) during pregnancy represents a common condition, worsening maternal and fetal prognosis. However, no single biomarker has proven optimal for determining the risk of UH. We developed an early risk multivariate model for UH, integrating hemodynamics with biochemistry, focusing on the relationship between blood pressure (BP) indices, uric acid (UA), and angiogenesis-related factors (AF). We collected and analyzed data on 24 h ambulatory BP monitoring, demographic, epidemiological, clinical, and laboratory variables from 132 pregnancies. The main predictors were BP indices and serum UA and AF levels. Uncomplicated hypertension, defined as the presence of gestational hypertension or worsening of essential hypertension beyond the 20th week, was the main outcome. The combined second-degree polynomial transformation of UA and the AF (sFlt-1/PIGF) ratio, called the UA-AF Index, consistently showed a positive association with UH. The models incorporating nighttime BP indices combined with the UA-AF Index outperformed the others, with the best-performing model based on the nocturnal systolic BP (SBP). Specifically, in the best-fitting model (nighttime SBP + UA-AF Index as predictors), each 1 mmHg increase in nocturnal SBP was associated with a 10% higher risk of UH, while each one-unit increase in the UA-AF Index raised the likelihood of UH by more than twofold (accuracy: 0.830, AUC 0. 874, SE 0.032, p-value < 0.001, 95%CI 0.811–0.938). The combination of nighttime blood pressure indices, serum uric acid, and angiogenesis-related factors may provide added value in the assessment of uncomplicated hypertension during pregnancy. Full article

We present a method for 3D gravity inversion using ellipsoidal parametrization and Particle Swarm Optimization (PSO), aimed at estimating the geometry, density contrast, and orientation of subsurface bodies from gravity anomaly data. The subsurface is modeled as a set of prolate ellipsoids whose parameters are optimized to minimize the misfit between observed and predicted anomalies. This approach enables efficient forward modeling with closed-form solutions and allows the incorporation of geometric and physical constraints. The algorithm is first validated on synthetic models with Gaussian noise, successfully recovering complex multi-body configurations with acceptable uncertainty. A statistical analysis based on multiple PSO runs provides interquartile ranges (IQRs) to quantify inversion stability. The method is then applied to a real microgravity dataset from the Nirano Salse mud volcanoes (northern Italy) using a field acquisition strategy previously described in the literature. Unlike earlier studies based on commercial software, our inversion uses the ellipsoidal–PSO framework. The best-fitting model includes four ellipsoids (two low- and two high-density), reproducing the main features of the observed Bouguer anomaly with a prediction error of 20–25%. The inferred geometry suggests that fluid migration is controlled by fault-related damage zones rather than shallow reservoirs. This method is robust, interpretable, and applicable to both synthetic and real cases, with potential uses in geotechnical, volcanic, and hydrogeological studies. Full article

This study investigated the chemical, thermal, and mechanical properties of segmented polyurethanes (SPUs) synthesized using less common biodegradable polyester polyols, specifically poly(adipate) (PAD) and poly(sebacate) (PSC), to evaluate their potential as nerve guidance conduits (NGCs) in peripheral nerve regeneration. The synthesis of novel 4,4′ methylene-bis-cyclohexyl diisocyanate (HMDI) SPUs was conducted in a two-step process: prepolymer formation and chain extension with 1,4-butanediol (BO) or 1,4-butanediamine (BA). SPUs were synthesized with two molar ratios—polyol:HMDI:BA/BO at 1:2:1 and 1:3:2 for the PAD:HMDI:BA system—to optimize mechanical properties. 1HRMN analysis verified the expected chemical structure of SPUs, whereas Raman and IR spectroscopy confirmed successful polyurethane synthesis. X-ray diffractograms showed that PAD-based SPUs (SPUPAD) were amorphous while PSC-based SPUs (SPUPSC) exhibited semi-crystalline behavior. SPUPAD showed only one degradation stage by TGA, while DSC showed one thermal event. In contrast, SPUPSC exhibited two degradation stages and three thermal events that confirmed phase separation. The longitudinal tensile properties of an NGC fabricated from SPUA-PAD-2 (PAD:HMDI:BA (1:3:2)) after 30 days of immersion in water (25 °C) showed a lower modulus (4.46 ± 0.5 MPa) than native intact nerves (15.87 ± 2.21 MPa) but a similar modulus to extracted nerves (8.19 ± 7.27 MPa). This system exhibited a longitudinal tensile force of 11.1 ± 1.6 N, which is lower than that of peripheral nerves (19.85 ± 7.21 N) but higher than that of commercial collagen-based nerve guide conduits (6.89 ± 2.6 N). The observed properties suggest that PUA-PAD-2 has potential as a biomaterial for nerve regeneration applications. Full article

The standard immunosuppressive treatments in heart transplantation are calcineurin inhibitors, corticosteroids, and antimetabolite agents or inhibitors of the mammalian target of rapamycin. Pharmacogenetic studies show the impact on clinical course of genetic variability in genes that encode transporters, metabolizers, or molecular targets of immunosuppressants. The aim of this systematic review is to elucidate the role that pharmacogenetics of immunosuppressant drugs plays in clinical outcomes upon heart transplantation. PubMed, EMBASE, the Cochrane Central Register, and the Database of Abstracts of Reviews of Effects were searched without restrictions. The 64 studies analyzed followed these criteria: (1) were based on clinical data on heart transplantation patients; (2) analyzed the associations between polymorphisms and clinical response; (3) analyzed the impact of polymorphisms on immunosuppressant safety. CYP3A4/5 variants were associated with higher doses of tacrolimus, whereas POR*28 variants with lower doses—ABCB1, ABCC2, SLCO1B1, and SLC13A1—contribute to interindividual variability in drug absorption, distribution, and toxicity. An ABCC2 polymorphism (rs717620) was related to higher risk of graft rejection in pediatrics. Variations in HLA-G, TNF-α and TGF-β genes influence transplant rejection risk and immune response. Implementing pharmacogenetic screening of polymorphisms could enhance therapeutic outcomes by improving drug efficacy, reducing toxicity, and ultimately increasing heart graft survival rates. Strong evidence supports genotyping for CYP3A5 and TPMT, but further research is required for transporter genes and cytokine polymorphisms. Full article

Background/Objectives: Muscle tissues are a common source of symptoms related to low back pain (LBP), with myofascial trigger points (MTrPs) being a significant contributor. Since previous meta-analyses support interventions targeting MTrPs for reducing pain and improving functional disability in patients with LBP, this review aimed to synthesize current knowledge on the prevalence of MTrPs in LBP patients. Methods: To conduct this systematic review, data were collected from PubMed, Cochrane, and Web of Science. Published articles at any time up to February 2025 that comprised descriptive, observational, or experimental studies in English/Spanish language reporting the prevalence of active or latent MTrPs in patients with LBP were eligible. After assessing the methodological quality, a structured and qualitative synthesis was conducted using a standardized form that captured participant characteristics, evaluated muscles, the number or percentage of active and latent MTrPs in each group, clinical features, summarized results, and conclusions. Results: Nine articles with acceptable methodological quality were included. The prevalence of active MTrPs in patients with LBP was quadratus lumborum (ranging from 30% to 55%), gluteus medius (from 34% to 45%), piriformis (42%), psoas (from 5% to 10%), and lumbar iliocostalis (from 33% to 38%). Latent MTrPs were most common in the gluteus medius (74%) and quadratus lumborum (14–17%), with the piriformis, psoas, and lumbar iliocostalis also affected. Conclusions: Active and latent MTrPs are common in muscles such as the quadratus lumborum, gluteus medius, and iliocostalis in individuals with LBP, with prevalence varying by pain chronicity and etiology. MTrPs in the gluteal region are more frequent in lumbosacral radiculopathy, suggesting a neurogenic-like component. Since the subjectivity of manual palpation and study heterogeneity limit generalizability of the results, future research should standardize diagnostic criteria of MTrPs to ensure the consistency of results. Full article

Backgroud: Ovarian cancer is the deadliest gynecologic malignancy, with most patients presenting with peritoneal dissemination at diagnosis. Complete cytoreduction and sensitivity to platinum-based systemic chemotherapy remain the most significant prognostic factors. However, even after optimal first-line management, over half of patients relapse due to residual microscopic disease. Intraperitoneal chemotherapy aims to target this component, with normothermic intraperitoneal chemotherapy long-term (NIPEC-LT) and hyperthermic intraperitoneal chemotherapy (HIPEC) being the most studied approaches. While NIPEC-LT has demonstrated improved survival in select trials, concerns regarding toxicity and catheter-related complications have limited its adoption as standard care. Conversely, HIPEC has shown survival benefits, particularly in patients undergoing interval cytoreductive surgery (iCRS) after neoadjuvant chemotherapy, leading to its inclusion in clinical guidelines. However, HIPEC is administered as a single intraoperative treatment, limiting its prolonged effect. Objectives and Method: This study investigates the combination of HIPEC and postoperative NIPEC-LT in the BICOV-1 trial, a prospective, non-randomized phase I study evaluating the feasibility, safety, and oncologic outcomes. The primary objective is to assess the treatment completion rates and morbidity. The secondary endpoints include disease-free survival (DFS), overall survival (OS), and quality-of-life measures. Combining HIPEC and NIPEC-LT is a rational approach, as both have shown independent benefits and do not overlap in toxicity. HIPEC-induced biological changes may enhance the effectiveness of subsequent intraperitoneal chemotherapy. This trial will provide essential data for future phase II/III studies assessing the role of intensified intraperitoneal treatment in ovarian cancer management. Full article