Search Results (80,420)

Invasive candidiasis (IC), characterized by the most common clinical manifestation of candidemia, is a fungal infection with a high mortality rate and a significant impact on global public health. It is estimated that each year there are between 227,000 and 250,000 hospitalizations related to IC, with more than 100,000 associated deaths. In Latin America and the Caribbean (LA&C), the absence of a standardized surveillance system has led to multicenter studies documenting incidences ranging from 0.74 to 6.0 cases per 1000 hospital admissions, equivalent to 50,000–60,000 hospitalizations annually, with mortality rates of up to 60% in certain high-risk groups. Armed conflicts and structural violence in LA&C cause forced displacement, the collapse of health systems, and poor living conditions—such as overcrowding, malnutrition, and lack of sanitation—which increase vulnerability to opportunistic infections, such as IC. Insufficient specialized laboratories, diagnostic technology, and trained personnel impede pathogen identification and delay timely initiation of antifungal therapy. Furthermore, the empirical use of broad-spectrum antibiotics and the limited availability of echinocandins and lipid formulations of amphotericin B have promoted the emergence of resistant non-albicans strains, such as Candida tropicalis, Candida parapsilosis, and, in recent outbreaks, Candidozyma auris. Full article

Background: Hip fractures represent a major clinical challenge, particularly in elderly and frail patients, where postoperative pain control must balance effective analgesia with motor preservation to facilitate early mobilization. Various regional anesthesia techniques are used in this setting, including the pericapsular nerve group (PENG) block, fascia iliaca compartment block (FICB), femoral nerve block (FNB), and quadratus lumborum block (QLB), yet optimal strategies remain debated. Objectives: To systematically review the efficacy, safety, and clinical applicability of major regional anesthesia techniques for pain management in hip fractures, including considerations of fracture type, surgical approach, and functional outcomes. Methods: A systematic literature search was conducted following PRISMA 2020 guidelines in PubMed, Scopus, Web of Science, and the virtual library of the Hospital Central de la Defensa “Gómez Ulla” up to March 2025. Inclusion criteria were RCTs, systematic reviews, and meta-analyses evaluating regional anesthesia for hip surgery in adults. Risk of bias in RCTs was assessed using RoB 2.0, and certainty of evidence was evaluated using the GRADE approach. Results: Twenty-nine studies were included, comprising RCTs, systematic reviews, and meta-analyses. PENG block demonstrated superior motor preservation and reduced opioid consumption compared to FICB and FNB, particularly in intracapsular fractures and anterior surgical approaches. FICB and combination strategies (PENG+LFCN or sciatic block) may provide broader analgesic coverage in extracapsular fractures or posterior approaches. The overall risk of bias across RCTs was predominantly low, and certainty of evidence ranged from moderate to high for key outcomes. No significant safety concerns were identified across techniques, although reporting of adverse events was inconsistent. Conclusions: PENG block appears to offer a favorable balance of analgesia and motor preservation in hip fracture surgery, particularly for intracapsular fractures. For extracapsular fractures or posterior approaches, combination strategies may enhance analgesic coverage. Selection of block technique should be tailored to fracture type, surgical approach, and patient-specific functional goals. Full article

Millions of puppies are welcomed into the homes of families around the world each year. However, understanding the ways in which puppies are bred and raised by their breeders, as well as the perspectives and perceptions underpinning these practices, is still in its infancy. The current study administered an online survey to 200 Australian dog breeders to investigate their breeding program characteristics, breeding dog selection, understanding of the importance of early experiences in puppyhood, and the extent and diversity of their puppy rearing and socialisation practices. Results indicated that breeders were motivated by breed improvement and producing dogs for themselves rather than providing companion dogs, despite most of their puppies being placed in companionship roles. The participating breeders also acknowledged the important role they play in shaping puppies’ behaviour and temperament, which was reflected in both their breeding dog selection and in their rearing and socialisation practices. The majority of breeders housed their litters within their residence for the initial weeks of life but the socialisation experiences they provided were variable in type and frequency. Longer-term breeders and those with larger, more intensive programs reported providing human-focused socialisation experiences less frequently, though the correlational nature of these findings require cautious interpretation. Whilst future research should endeavor to explore these results more comprehensively among a more diverse sample, these findings provide valuable insight into the breeding, rearing, and socialisation process undertaken by dog breeders in Australia. Full article

This paper addressed the problem of oil diagnostics lubricants applied to the predictive maintenance of industrial gearboxes, proposing the integration of an artificial intelligence (AI) system into the process analysis. The main objective was to overcome the critical issues of the traditional method, characterized by long analysis times and a marked dependence on the subjective interpretation of operators. The method includes a detailed statistical analysis of the common ways to assess the condition of lubricants, such as optical emission spectroscopy, particle counting, measuring viscosity and density, and Fourier-transform infrared spectroscopy (FT-IR). These methods are then combined with an artificial intelligence model. Tested on commercial gearbox data, the proposed approach demonstrates agreement between IA and expert evaluation. The application has shown that it can effectively support diagnoses, reduce processing time by 60%, and minimize human errors. It also improves knowledge sharing through an increase in the stability and repetitiveness of diagnoses and promotes consistency and clarity in reporting. Full article

Ventricular tachycardia (VT) remains a major cause of morbidity and mortality in patients with structural heart disease. While catheter ablation has become a cornerstone in VT management, recurrence rates remain substantial due to limitations in electroanatomic mapping (EAM), particularly in cases of deep or heterogeneous arrhythmogenic substrates. Cardiac imaging, especially when multimodal and integrated with mapping systems, has emerged as a critical adjunct to enhance procedural efficacy, safety, and individualized strategy. This comprehensive review explores the evolving role of various imaging modalities, including echocardiography, cardiac magnetic resonance (CMR), computed tomography (CT), positron emission tomography (PET), and intracardiac echocardiography (ICE), in the preprocedural and intraprocedural phases of VT ablation. We highlight their respective strengths in substrate identification, anatomical delineation, and real-time guidance. While limitations persist, including costs, availability, artifacts in device carriers, and lack of standardization, future advances are likely to redefine procedural workflows. Full article

Petrological knowledge on weathering processes controlling the mobility of chemical elements is still limited in the dry tropical zone of Cameroon. This study aims to investigate the mobility of major and trace elements during rhyolite weathering and soil formation in Mobono by understanding the mineralogical and elemental vertical variation. The studied soil was classified as Cambisols containing mainly quartz, K-feldspar, plagioclase, smectite, kaolinite, illite, calcite, lepidocrocite, goethite, sepiolite, and interstratified clay minerals. pH values ranging between 6.11 and 8.77 indicated that hydrolysis, superimposed on oxidation and carbonation, is the main process responsible for the formation of secondary minerals, leading to the formation of iron oxides and calcite. The bedrock was mainly constituted of SiO₂, Al₂O₃, Na₂O, Fe₂O₃, Ba, Zr, Sr, Y, Ga, and Rb. Ce and Eu anomalies, and chondrite-normalized La/Yb ratios were 0.98, 0.67, and 2.86, respectively. SiO₂, Al₂O₃, Fe₂O₃, Na₂O, and K₂O were major elements in soil horizons. Trace elements revealed high levels of Ba (385 to 1320 mg kg⁻¹), Zr (158 to 429 mg kg⁻¹), Zn (61 to 151 mg kg⁻¹), Sr (62 to 243 mg kg⁻¹), Y (55 to 81 mg kg⁻¹), Rb (1102 to 58 mg kg⁻¹), and Ga (17.70 to 35 mg kg⁻¹). LREEs were more abundant than HREEs, with LREE/HREE ratio ranging between 2.60 and 6.24. Ce and Eu anomalies ranged from 1.08 to 1.21 and 0.58 to 1.24 respectively. The rhyolite-normalized La/Yb ratios varied between 0.56 and 0.96. Mass balance revealed the depletion of Si, Ca, Na, Mn, Sr, Ta, W, U, La, Ce, Pr, Nd, Sm, Gd and Lu, and the accumulation of Al, Fe, K, Mg, P, Sc, V, Co, Ni, Cu, Zn, Ga, Ge, Rb, Y, Zr, Nb, Cs, Ba, Hf, Pb, Th, Eu, Tb, Dy, Ho, Er, Tm and Yb during weathering along the soil profile. Full article

Portland cement production is a major source of global CO₂ emissions due to its high energy consumption and calcination processes. This study proposes a sustainable alternative through the partial replacement of cement with alkali-activated pumice, a naturally occurring aluminosilicate material with high regional availability. Mixes with 0%, 10%, 20%, and 30% cement replacement were designed for pedestrian slabs exposed to humid tropical conditions. Compressive strength was evaluated using non-destructive testing over a period of 364 days, and carbonation was analyzed at different ages. The results show that mixes with up to 30% pumice maintain adequate strength levels for light-duty applications, although with a more gradual strength development. A significant reduction in carbonation depth was also observed, especially in the mix with the highest replacement level, suggesting greater durability in aggressive environments. These findings support the use of pumice as a viable and sustainable supplementary cementitious material in tropical regions, promoting low-impact construction practices. Full article

Background: Atrial fibrosis is a key contributor to atrial cardiomyopathy and can be assessed invasively using mean left atrial voltage (MLAV) from electroanatomical mapping. However, the invasive nature of this procedure limits its clinical applicability. Machine learning (ML), particularly regression tree-based models, may offer a non-invasive approach for predicting MLAV using clinical and echocardiographic data, improving non-invasive atrial fibrosis characterisation beyond current dichotomous classifications. Methods: We prospectively included and followed 113 patients with paroxysmal or persistent atrial fibrillation (AF) undergoing pulmonary vein isolation (PVI) with ultra-high-density voltage mapping (uHDvM), from whom MLAV was estimated. Standardised two-dimensional transthoracic echocardiography was performed before ablation, and clinical and echocardiographic variables were analysed. A regression tree model was constructed using the Classification and Regression Trees—CART-algorithm to identify key predictors of MLAV. Results: The regression tree model exhibited moderate predictive accuracy (R² = 0.63; 95% CI: 0.55–0.71; root mean squared error = 0.90; 95% CI: 0.82–0.98), with indexed minimum LA volume and passive emptying fraction emerging as the most influential variables. No significant differences in AF recurrence-free survival were found among MLAV tertiles or model-based generated groups (log-rank p = 0.319 and p = 0.126, respectively). Conclusions: We present a novel ML-based regression tree model for non-invasive prediction of MLAV, identifying minimum LA volume and passive emptying fraction as the most significant predictors. This model offers an accessible, non-invasive tool for refining atrial cardiomyopathy characterisation by reflecting the fibrotic substrate as a continuum, a crucial advancement over existing dichotomous approaches to guide tailored therapeutic strategies. Full article

This study presents an algorithm for non-invasive blood pressure (BP) estimation in neonates using photoplethysmography (PPG), suitable for resource-constrained neonatal telecare platforms. Using the Windkessel model, the algorithm processes PPG signals from a MAX 30102 sensor, (Analog Devices (formerly Maxim Integrated), based in San Jose, CA, USA) filtering motion noise and extracting cardiac cycle time and systolic time (ST). These parameters inform a derived blood flow signal, the input for the Windkessel model. Calibration utilizes average parameters based on the newborn’s post-conceptional age, weight, and gestational age. Performance was validated against readings from a standard non-invasive BP cuff at SES Hospital Universitario de Caldas. Two parameter estimation methods were evaluated. The first yielded root mean square errors (RMSEs) of 24.14 mmHg for systolic and 19.13 mmHg for diastolic BP. The second method significantly improved accuracy, achieving RMSEs of 2.31 mmHg and 5.13 mmHg, respectively. The successful adaptation of the Windkessel model to single PPG signals allows for BP calculation alongside other physiological variables within the telecare program. A device analysis was conducted to determine the appropriate device based on computational capacity, availability of programming tools, and ease of integration within an Internet of Things environment. This study paves the way for future research that focuses on parameter variations due to cardiovascular changes in newborns during their first month of life. Full article

This work contextualizes the possibility of deriving a unifying artificial intelligence framework by walking in the footsteps of General, Explainable, and Verified Artificial Intelligence (GEVAI): by considering explainability not only at the level of the results produced by a specification but also considering the explicability of the inference process as well as the one related to the data processing step, we can not only ensure human explainability of the process leading to the ultimate results but also mitigate and minimize machine faults leading to incorrect results. This, on the other hand, requires the adoption of automated verification processes beyond system fine-tuning, which are essentially relevant in a more interconnected world. The challenges related to full automation of a data processing pipeline, mostly requiring human-in-the-loop approaches, forces us to tackle the framework from a different perspective: while proposing a preliminary implementation of GEVAI mainly used as an AI test-bed having different state-of-the-art AI algorithms interconnected, we propose two other data processing pipelines, LaSSI and EMeriTAte+DF, being a specific instantiation of GEVAI for solving specific problems (Natural Language Processing, and Multivariate Time Series Classifications). Preliminary results from our ongoing work strengthen the position of the proposed framework by showcasing it as a viable path to improve current state-of-the-art AI algorithms. Full article

The connection between sugar and ethanol prices is in line with concerns about the connection between oil and food prices. This paper studies the nexus between Colombia’s ethanol and sugar prices and the role that weather shocks play. Data on production and prices from the sugar mills and climate data on precipitation and temperature are used to estimate two ways to capture the relationship between prices and the role of weather shocks. First, a reduced-form estimation is made, where the study finds evidence of the pass-through of the international price to domestic prices and how high precipitation and temperature shocks increase prices. Then, the study addresses potential simultaneity problems between prices and estimates a VEC model with exogenous variables such as weather shocks. Results show that all domestic prices are affected by the international price, and the international price is affected by the white sugar domestic prices. Additionally, sugar prices react to shocks in ethanol prices, but ethanol prices do not react to shocks in sugar prices. Finally, weather shocks affect sugar prices, with daytime temperature shocks being the most damaging. Full article

Background/Objectives: Cognitive impairment in older adults has emerged as a growing public health concern, particularly in relation to COVID-19 infection and its associated neuropsychiatric symptoms. The identification of modifiable risk factors may contribute to the development of targeted preventive strategies. This study aimed to assess predictors of cognitive impairment in older adults with and without recent SARS-CoV-2 infection. Methods: A prospective cohort study was conducted from June 2023 to March 2024 at a tertiary hospital in western Mexico. Adults aged 65 years or older with confirmed SARS-CoV-2 infection within the previous six months, along with uninfected controls, were enrolled. Cognitive function (Mini-Mental State Examination), depression (PHQ-9), anxiety (Geriatric Anxiety Inventory), insomnia (Insomnia Severity Index), functional status (Katz Index and Lawton–Brody Scale), and laboratory markers were evaluated at baseline, three months, and six months. The primary outcome was cognitive impairment at six months. Independent predictors were identified using a multivariable generalized linear mixed-effects model. Results: Among the 111 participants, 20 (18.8%) developed cognitive impairment within six months. Low serum magnesium (adjusted risk ratio [aRR] 2.73; 95% CI 1.04–7.17; p = 0.041) and depression (aRR 5.57; 95% CI 1.88–16.48; p = 0.002) were independently associated with a higher risk. A significant synergistic among COVID-19, depression, and hypomagnesemia was observed (RR 44.30; 95% CI 9.52–206.21; p < 0.001), corresponding to the group with simultaneous presence of all three factors compared to the group with none. Conclusions: Depression and hypomagnesemia appear to be independent predictors of cognitive impairment in older adults with recent COVID-19 infection. These findings suggest potential targets for prevention and support the implementation of routine neuropsychiatric and biochemical assessments in this population. Full article

Background: Drug–drug interactions (DDIs) may occur when two or more drugs are taken together, leading to undesired side effects or potential synergistic effects. Most clinical effects of drug combinations have not been assessed in clinical trials. Therefore, predicting DDIs can provide better patient management, avoid drug combinations that can negatively affect patient care, and exploit potential synergistic combinations to improve current therapies in women’s healthcare. Methods: A DDI prediction model was built to describe relevant drug combinations affecting reproductive treatments. Approved drug features (chemical structure of drugs, side effects, targets, enzymes, carriers and transporters, pathways, protein–protein interactions, and interaction profile fingerprints) were obtained. A unified predictive score revealed unknown DDIs between reproductive and commonly used drugs and their associated clinical effects on reproductive health. The performance of the prediction model was validated using known DDIs. Results: This prediction model accurately predicted known interactions (AUROC = 0.9876) and identified 2991 new DDIs between 192 drugs used in different female reproductive conditions and other drugs used to treat unrelated conditions. These DDIs included 836 between drugs used for in vitro fertilization. Most new DDIs involved estradiol, acetaminophen, bupivacaine, risperidone, and follitropin. Follitropin, bupivacaine, and gonadorelin had the highest discovery rate (42%, 32%, and 25%, respectively). Some were expected to improve current therapies (n = 23), while others would cause harmful effects (n = 11). We also predicted twelve DDIs between oral contraceptives and HIV drugs that could compromise their efficacy. Conclusions: These results show the importance of DDI studies aimed at identifying those that might compromise or improve their efficacy, which could lead to personalizing female reproductive therapies. Full article

Prime editing (PE) has emerged as a transformative genome editing technology, enabling precise base substitutions, insertions, and deletions without inducing double-strand DNA breaks (DSBs). However, its application in zebrafish remains limited by low efficiency. Here, we leveraged PE7, a state-of-the-art PE system, combined with La-accessible prime editing guide RNAs (pegRNAs), to enhance editing efficiency in zebrafish. By co-incubating PE7 protein with La-accessible pegRNAs to form ribonucleoprotein (RNP) complexes and microinjecting these complexes into zebrafish embryos, we achieved up to 15.99% editing efficiency at target loci—an improvement of 6.81- to 11.46-fold over PE2. Additionally, we observed 16.60% 6 bp insertions and 13.18% 10 bp deletions at the adgrf3b locus, representing a 3.13-fold increase over PE2. Finally, we used PE to introduce desired edits at the tyr locus, successfully generating zebrafish with the tyr P302L mutation that exhibited melanin reduction. These findings demonstrate that PE7 significantly enhances prime editing efficiency in fish, providing novel tools for functional gene studies and genetic breeding in aquatic species. Full article