Environmental sympatry through time: spatio-temporal distribution and conservation status of two sympatric anuran species (Leptodactylidae) in South America / Simpatría ambiental a través del tiempo: distribución espacio-temporal y estado de conservación de dos especies de anuros simpátricos (Leptodactylidae) en América del Sur

Abstract Introduction: Leptodactylus latinasus and Physalaemus cuqui are sympatric anuran species with similar environmental requirements and contrasting reproductive modes. Climatic configuration determines distribution patterns and promotes sympatry of environmental niches, but specificity/selectivity determines the success of reproductive modes. Species distribution models (SDM) are a valuable tool to predict spatio-temporal distributions based on the extrapolation of environmental predictors. Objectives: To determine the spatio-temporal distribution of environmental niches and assess whether the protected areas of the World Database of Protected Areas (WDPA) allow the conservation of these species in the current scenario and future. Methods: We applied different algorithms to predict the distribution and spatio-temporal overlap of environmental niches of L. latinasus and P. cuqui within South America in the last glacial maximum (LGM), middle-Holocene, current and future scenarios. We assess the conservation status of both species with the WDPA conservation units. Results: All applied algorithms showed high performance for both species (TSS = 0.87, AUC = 0.95). The L. latinasus predictions showed wide environmental niches from LGM to the current scenario (49 % stable niches, 37 % gained niches, and 13 % lost niches), suggesting historical fidelity to stable climatic-environmental regions. In the current-future transition, L. latinasus would increase the number of stable (70 %) and lost (20 %) niches, suggesting fidelity to lowland regions and a possible trend toward microendemism. P. cuqui loses environmental niches from the LGM to the current scenario (25 %) and in the current-future transition (63 %), increasing the environmental sympathy between both species; 31 % spatial overlap in the current scenario and 70 % in the future. Conclusion: Extreme drought events and rainfall variations, derived from climate change, suggest the loss of environmental niches for these species that are not currently threatened but are not adequately protected by conservation units. The loss of environmental niches increases spatial sympatry which represents a new challenge for anurans and the conservation of their populations.

Resumen Introducción: Leptodactylus latinasus y Physalaemus cuqui son especies de anuros simpátricos con requerimientos ambientales similares y modos reproductivos contrastantes. La configuración climática determina los patrones de distribución y promueve la simpatría de los nichos ambientales, pero la especificidad/selectividad determina el éxito de los modos reproductivos. Los modelos de distribución de especies (MDE) son una herramienta valiosa para predecir distribuciones espacio-temporales basadas en la extrapolación de predictores ambientales. Objetivos: Determinar la distribución espacio-temporal de los nichos ambientales y evaluar si las áreas protegidas de la base de Datos Mundial de Áreas Protegidas (DMAP) permiten la conservación de estas especies en el escenario actual y futuro. Métodos: Aplicamos diferentes algoritmos para predecir la distribución y superposición espacio-temporal de nichos ambientales de L. latinasus y P. cuqui dentro de América del Sur en el último máximo glacial (UGM), Holoceno medio, actual y futuro. Evaluamos el estado de conservación de ambas especies con las unidades de conservación de la DMAP. Resultados: Todos los algoritmos aplicados mostraron un alto rendimiento para ambas especies (TSS = 0.87, AUC = 0.95). Las predicciones de L. latinasus mostraron amplios nichos ambientales desde LGM hasta el escenario actual (49 % de nichos estables, 37 % de nichos ganados y 13 % de nichos perdidos), sugiriendo fidelidad histórica por regiones climático-ambientales estables. En la transición actual-futura L. latinasus incrementaría la cantidad de nichos estables (70 %) y perdidos (20 %), sugiriendo fidelidad por regiones de tierras bajas y la posible tendencia hacia el microendemismo. P. cuqui pierde nichos ambientales desde el LGM al escenario actual (25 %) y en la transición actual-futura (63 %), incrementando la simpatría ambiental entre ambas especies; 31 % de superposición espacial en el escenario actual y 70 % en el futuro. Conclusión: Los eventos de sequía extrema y las variaciones de precipitaciones, derivados del cambio climático, sugieren la pérdida de nichos ambientales para estas especies, actualmente no se encuentran amenazadas, pero no están adecuadamente protegidas por las unidades de conservación. La pérdida de nichos ambientales aumenta la simpatría espacial que representa un nuevo desafío para estos anuros y la conservación de sus poblaciones.

Precipitation explains Wood Thrush (Hylocichla mustelina) occupancy patterns in Northern Costa Rica / Patrones de ocurrencia del Zorzal del Bosque (Hylocichla mustelina) explicados por la precipitación en el Norte de Costa Rica

Abstract Introduction: The Wood Thrush is a migratory bird that has experienced dramatic declines in its populations in recent decades. This species overwinters in forest fragments with intermediate levels of habitat modification in Central America. However, more studies detailing the use of remnant forests through time are needed to elucidate the threats this species faces in the wintering grounds. Objective: To understand the effects of environmental and forest structure variables on the occupancy of Wood Thrush in Northern Costa Rica. Methods: The study area was the Área de Conservación Guanacaste (ACG), located in Northern Costa Rica, in December 2016, and during the 2018-2019 migration season. We estimated Wood Thrush occupancy and detection probability in four locations of ACG (dry forest, cloud forest, and two locations in the wet forest) using single-season occupancy models. We also estimated Wood Thrush occupancy and probability of persistence in different months in three vegetation types (open area, secondary forest, and old-growth forest) in the wet forest of ACG using a multi-season occupancy model approach. Results: Wood Thrush occupancy was best described by precipitation in the four locations of the ACG; the probability of occupancy increased with precipitation. The average occupancy of Wood Thrushes varied with vegetation type: open area with shrubs and forest edge (0.69 ± 0.09), secondary forest (0.46 ± 0.1), and old-growth forest (0.61 ± 0.1). Wood Thrush probability of persistence responded partially to changes in precipitation, with an unexpected increase in persistence when the rainfall continued decreasing in the season. Conclusion: Wood Thrush occupancy was best predicted by changes in precipitation considering a larger spatial scale. Its probability of persistence partially varied with precipitation. An increase in persistence closer to Spring migration might be explained by the start of the breeding season of resident birds, potentially reducing territorial conflicts and conserving energy before migration. The long-term protection of wet forests in Northern Costa Rica is of paramount importance for the conservation of Wood Thrushes in their wintering grounds.

Resumen Introducción: El Zorzal del Bosque es un ave migratoria que ha experimentado caídas dramáticas en sus poblaciones en las últimas décadas. Esta especie pasa el invierno en fragmentos de bosque con niveles intermedios de modificación de hábitat en Centroamérica. Sin embargo, se necesitan más estudios que detallen el uso de los bosques remanentes a lo largo del tiempo para dilucidar las amenazas que enfrenta esta especie en las zonas de invernada. Objetivo: Comprender los efectos de variables ambientales y de estructura del bosque en la ocurrencia del Zorzal del Bosque en el Norte de Costa Rica. Métodos: El área de estudio fue el Área de Conservación Guanacaste (ACG), ubicada en el Norte de Costa Rica, en diciembre de 2016, y en la temporada migratoria 2018-2019. Estimamos la ocurrencia y la probabilidad de detección del Zorzal del Bosque en cuatro ubicaciones de ACG (bosque seco, bosque nuboso y dos ubicaciones en el bosque húmedo) utilizando modelos de ocurrencia de una sola temporada. También estimamos la ocurrencia del Zorzal del Bosque y la probabilidad de persistencia en diferentes meses en tres tipos de vegetación (área abierta, bosque secundario y bosque primario) en el bosque húmedo de ACG utilizando un enfoque de modelo de ocurrencia multi-estacional. Resultados: La ocurrencia del Zorzal del Bosque estuvo mejor descrita por la precipitación en las cuatro localidades del ACG; la probabilidad de ocurrencia aumentó con las precipitaciones. La ocurrencia media de zorzales varió con el tipo de vegetación: área abierta con arbustos y borde de bosque (0.69 ± 0.09), bosque secundario (0.46 ± 0.1) y bosque primario (0.61 ± 0.1). La probabilidad de persistencia del zorzal respondió parcialmente a cambios en la precipitación, con un aumento inesperado en la persistencia cuando las precipitaciones continuaron disminuyendo en la temporada. Conclusión: La ocurrecia del Zorzal del Bosque varió con la precipitación considerando una escala espacial mayor. Su probabilidad de persistencia varió parcialmente con la precipitación. Un aumento en la persistencia más cerca de la migración de primavera podría explicarse por el inicio de la temporada de reproducción de las aves residentes, lo que podría reducir los conflictos territoriales y conservar energía antes de la migración. La protección a largo plazo de los bosques húmedos en el norte de Costa Rica es de suma importancia para la conservación de los Zorzales del Bosque en sus zonas de invernada.

Value of interventional radiology and their contributions to modern medical systems.

Interventional radiology (IR) is a unique specialty that incorporates a diverse set of skills ranging from imaging, procedures, consultation, and patient management. Understanding how IR generates value to the healthcare system is important to review from various perspectives. IR specialists need to understand how to meet demands from various stakeholders to expand their practice improving patient care. Thus, this review discusses the domains of value contributed to medical systems and outlines the parameters of success. IR benefits five distinct parties: patients, practitioners, payers, employers, and innovators. Value to patients and providers is delivered through a wide set of diagnostic and therapeutic interventions. Payers and hospital systems financially benefit from the reduced cost in medical management secondary to fast patient recovery, outpatient procedures, fewer complications, and the prestige of offering diverse expertise for complex patients. Lastly, IR is a field of rapid innovation implementing new procedural technology and techniques. Overall, IR must actively advocate for further growth and influence in the medical field as their value continues to expand in multiple domains. Despite being a nascent specialty, IR has become indispensable to modern medical practice.

Methylome-wide analysis in systemic microbial-induced experimental periodontal disease in mice with different susceptibility.

Objective: The study delved into the epigenetic factors associated with periodontal disease in two lineages of mice, namely C57bl/6 and Balb/c. Its primary objective was to elucidate alterations in the methylome of mice with distinct genetic backgrounds following systemic microbial challenge, employing high-throughput DNA methylation analysis as the investigative tool. Methods: Porphyromonas gingivalis (Pg)was orally administered to induce periodontitis in both Balb/c and C57bl/6 lineage. After euthanasia, genomic DNA from both maxilla and blood were subjected to bisulfite conversion, PCR amplification and genome-wide DNA methylation analysis using the Ovation RRBS Methyl-Seq System coupled with the Illumina Infinium Mouse Methylation BeadChip. Results: Of particular significance was the distinct methylation profile observed within the Pg-induced group of the Balb/c lineage, contrasting with both the control and Pg-induced groups of the C57bl/6 lineage. Utilizing rigorous filtering criteria, we successfully identified a substantial number of differentially methylated regions (DMRs) across various tissues and comparison groups, shedding light on the prevailing hypermethylation in non-induced cohorts and hypomethylation in induced groups. The comparison between blood and maxilla samples underscored the unique methylation patterns specific to the jaw tissue. Our comprehensive methylome analysis further unveiled statistically significant disparities, particularly within promoter regions, in several comparison groups. Conclusion: The differential DNA methylation patterns observed between C57bl/6 and Balb/c mouse lines suggest that epigenetic factors contribute to the variations in disease susceptibility. The identified differentially methylated regions associated with immune regulation and inflammatory response provide potential targets for further investigation. These findings emphasize the importance of considering epigenetic mechanisms in the development and progression of periodontitis.

RANDOMIZED EXPERIMENTAL STUDY OF TOPICAL VASODILATORS IN MICROSURGERY WITH COST ANALYSIS.

Objective: Throughout microsurgical anastomosis, many surgeons use topical vasodilators in order to reduce pathological vasospasm. It was carried out an experimental study comparing the effectiveness of topical use of Nitroglycerin, Papaverine, Magnesium sulfate over a control group in the femoral artery and vein of rats, in reducing prolonged vasospasm. Methods: Randomized comparative experimental study in 15 rats, divided into four groups. The external diameter of the vases soaked in the randomized solution was measured. For statistical analysis, it was calculated the percentual increase in the external diameter of the vessels. Results: A statistically significant increase in arterial dilation was observed after 10 minutes of topical application of 10% magnesium sulfate compared to the control group, with p = 0.044 . No other drug showed a vasodilator effect superior to the control group. Magnesium sulfate at 10% is still not used in microsurgery and costs 15 times less than papaverine, the standard drug for topical vasodilation in clinical cases at our service. Conclusion: Magnesium sulfate had better vasodilating effects over the control group after 10 minutes of arterial microanastomosis. None of the tested drugs have presented superior vasodilating effects over each other nor the control group after venous microanastomosis. Level of evidence II, Experimental study, Randomized Trial.

Objetivo: Durante a anastomose microcirúrgica, muitos cirurgiões utilizam vasodilatadores tópicos para reduzir o vasoespasmo prolongado patológico, assim reduzindo o risco de complicações vasculares. Entretanto, ainda faltam dados experimentais para identificação da droga padrão-ouro para vasodilatadores tópicos em microcirurgia e sua avaliação de análise de custo, já que a droga geralmente utilizada para este objetivo é baseada, na maior parte dos casos, na experiência do cirurgião. Métodos: Foi realizado um estudo experimental comparativo randomizado, avaliando a eficácia do uso tópico de Nitroglicerina, Papaverina e Sulfato de Magnésio em relação a um grupo controle, na redução do vasoespasmo na artéria e veia femoral de ratos. Foram avaliados o diâmetro externo dos vasos embebidos em solução randomizada dos fármacos para vasodilatação. Após cálculo do aumento percentual no diâmetro externo dos vasos, foi realizada análise estatística. Resultados: Observou-se aumento estatisticamente significativo da dilatação arterial após 10 minutos de aplicação tópica de sulfato de magnésio a 10% em relação ao grupo controle, com p = 0,044. Nenhuma outra droga apresentou efeito vasodilatador superior ao grupo controle. O sulfato de magnésio a 10% ainda não é utilizado em microcirurgia e apresenta custo até 15 vezes menor quando comparado com a papaverina, droga padrão para vasodilatação tópica em casos clínicos em nosso serviço. Conclusão: O sulfato de magnésio apresentou melhor efeito vasodilatador quando comparado ao grupo controle, após 10 minutos da microanastomose arterial. Nenhum dos fármacos testados apresentou efeito vasodilatador superior após a microanastomose venosa. Nível de Evidência II, Estudo experimental, Ensaio Randomizado.

Preparation of magnetic activated carbon fibers@Fe3O4 by electrostatic self-assembly method and adsorption properties for methylene blue.

Nano-Fe3O4 was loaded onto coconut-based activated carbon fibres (CACF) using an electrostatic self-assembly method. The effects of the mass ratio of CACF to nano-Fe3O4, loading time, pH and temperature on the loading effect were investigated and ideal loading conditions were determined. To study the adsorption performance of MACF@Fe3O4 for methylene blue, the effects of the initial concentration, pH and time on the adsorption were investigated and the working conditions of adsorption were established. MACF@Fe3O4 was systematically characterized. Adsorption kinetics were investigated under ideal conditions. The ideal loading conditions for MACF@Fe3O4 were as follows: mass ratio of 1:1, 20 min, pH 9.36, 22.5°C. The saturation magnetization of MACF@Fe3O4 was 48.2263 emu·g-1, which could be quickly separated under an external magnetic field. When the dosage was 0.010 g, the adsorption rate reached 97.29% and the maximum adsorption capacity was 12.1616 mg·g-1. The adsorption process conformed to pseudo-first-order kinetics during the first 15 min and pseudo-second-order kinetics during 20-120 min. The equations were ln( Q e - Q t )=2.2394-0.0689t and t Q t =0.0774 + 0.5295t , respectively. The isothermal adsorption model showed that MACF@Fe3O4 was more in line with the Langmuir model, indicating that the adsorption process was mainly monolayer adsorption. The thermodynamic analysis results showed that the adsorption process of MB by MACF@Fe3O4 was an endothermic process. In this study, MACF@Fe3O4 with high adsorption capacity and easy separation from coconut palm fibres has good application prospects in the field of adsorption, which can promote the high-value utilization of coconut palms.

Making Metadata Machine-Readable as the First Step to Providing Findable, Accessible, Interoperable, and Reusable Population Health Data: Framework Development and Implementation Study.

BACKGROUND: Metadata describe and provide context for other data, playing a pivotal role in enabling findability, accessibility, interoperability, and reusability (FAIR) data principles. By providing comprehensive and machine-readable descriptions of digital resources, metadata empower both machines and human users to seamlessly discover, access, integrate, and reuse data or content across diverse platforms and applications. However, the limited accessibility and machine-interpretability of existing metadata for population health data hinder effective data discovery and reuse. OBJECTIVE: To address these challenges, we propose a comprehensive framework using standardized formats, vocabularies, and protocols to render population health data machine-readable, significantly enhancing their FAIRness and enabling seamless discovery, access, and integration across diverse platforms and research applications. METHODS: The framework implements a 3-stage approach. The first stage is Data Documentation Initiative (DDI) integration, which involves leveraging the DDI Codebook metadata and documentation of detailed information for data and associated assets, while ensuring transparency and comprehensiveness. The second stage is Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) standardization. In this stage, the data are harmonized and standardized into the OMOP CDM, facilitating unified analysis across heterogeneous data sets. The third stage involves the integration of Schema.org and JavaScript Object Notation for Linked Data (JSON-LD), in which machine-readable metadata are generated using Schema.org entities and embedded within the data using JSON-LD, boosting discoverability and comprehension for both machines and human users. We demonstrated the implementation of these 3 stages using the Integrated Disease Surveillance and Response (IDSR) data from Malawi and Kenya. RESULTS: The implementation of our framework significantly enhanced the FAIRness of population health data, resulting in improved discoverability through seamless integration with platforms such as Google Dataset Search. The adoption of standardized formats and protocols streamlined data accessibility and integration across various research environments, fostering collaboration and knowledge sharing. Additionally, the use of machine-interpretable metadata empowered researchers to efficiently reuse data for targeted analyses and insights, thereby maximizing the overall value of population health resources. The JSON-LD codes are accessible via a GitHub repository and the HTML code integrated with JSON-LD is available on the Implementation Network for Sharing Population Information from Research Entities website. CONCLUSIONS: The adoption of machine-readable metadata standards is essential for ensuring the FAIRness of population health data. By embracing these standards, organizations can enhance diverse resource visibility, accessibility, and utility, leading to a broader impact, particularly in low- and middle-income countries. Machine-readable metadata can accelerate research, improve health care decision-making, and ultimately promote better health outcomes for populations worldwide.

A Cytochrome P450 TxtE Model System with Mechanistic and Theoretical Evidence for a Heme Peroxynitrite Active Species.

The cytochrome P450 homolog, TxtE, efficiently catalyzes the direct and regioselective aromatic nitration of the indolyl moiety of L-tryptophan to 4-nitro-L-tryptophan, using nitric oxide and dioxygen as co-substrates. Pathways for such direct and selective nitration of heteroaromatic motifs present platforms for engineering new nitration biocatalysts for pharmacologically beneficial targets, among a medley of other pivotal industrial applications. Precise mechanistic details concerning this pathway are only weakly understood, albeit a heme iron(III)-peroxynitrite active species has been postulated. To shed light on this unique reaction landscape, we investigated the indole nitration pathway of a series of biomimetic ferric heme superoxide mimics, [(Por)FeIII(O2-•)], in the presence of NO. Therein, our model systems gave rise to three distinct nitroindole products, including 4-nitroindole, the product analogous to that obtained with TxtE. Moreover, 15N and 18O isotope labeling studies, along with meticulously designed control experiments lend credence to a heme peroxynitrite active nitrating agent, drawing close similarities to the tryptophan nitration mechanism of TxtE. All organic and inorganic reaction components have been fully characterized using spectroscopic methods. Theoretical investigation into several mechanistic possibilities deem a unique indolyl radical based reaction pathway as the most energetically favorable, products of which, are in excellent agreement with experimental findings.

An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study.

BACKGROUND: A coordinated care system helps provide timely access to treatment for suspected acute stroke. In Northwestern Ontario (NWO), Canada, communities are widespread with several hospitals offering various diagnostic equipment and services. Thus, resources are limited, and health care providers must often transfer patients with stroke to different hospital locations to ensure the most appropriate care access within recommended time frames. However, health care providers frequently situated temporarily (locum) in NWO or providing care remotely from other areas of Ontario may lack sufficient information and experience in the region to access care for a patient with a time-sensitive condition. Suboptimal decision-making may lead to multiple transfers before definitive stroke care is obtained, resulting in poor outcomes and additional health care system costs. OBJECTIVE: We aimed to develop a tool to inform and assist NWO health care providers in determining the best transfer options for patients with stroke to provide the most efficient care access. We aimed to develop an app using a comprehensive geomapping navigation and estimation system based on machine learning algorithms. This app uses key stroke-related timelines including the last time the patient was known to be well, patient location, treatment options, and imaging availability at different health care facilities. METHODS: Using historical data (2008-2020), an accurate prediction model using machine learning methods was developed and incorporated into a mobile app. These data contained parameters regarding air (Ornge) and land medical transport (3 services), which were preprocessed and cleaned. For cases in which Ornge air services and land ambulance medical transport were both involved in a patient transport process, data were merged and time intervals of the transport journey were determined. The data were distributed for training (35%), testing (35%), and validation (30%) of the prediction model. RESULTS: In total, 70,623 records were collected in the data set from Ornge and land medical transport services to develop a prediction model. Various learning models were analyzed; all learning models perform better than the simple average of all points in predicting output variables. The decision tree model provided more accurate results than the other models. The decision tree model performed remarkably well, with the values from testing, validation, and the model within a close range. This model was used to develop the "NWO Navigate Stroke" system. The system provides accurate results and demonstrates that a mobile app can be a significant tool for health care providers navigating stroke care in NWO, potentially impacting patient care and outcomes. CONCLUSIONS: The NWO Navigate Stroke system uses a data-driven, reliable, accurate prediction model while considering all variations and is simultaneously linked to all required acute stroke management pathways and tools. It was tested using historical data, and the next step will to involve usability testing with end users.

Design and comparison of computationally efficient uniaxial stress-strain models of the lung parenchyma for real-time applications.

Real-time clinical applications such as robotic lung surgery, tumor localization, atelectasis diagnosis, tumor motion prediction for radiation therapy of lung cancer, or surgery training are in need of biomechanical models of lungs, not necessarily highly accurate, but with good computational properties. These properties can include one or several of the following: low computation time, low memory resource requirement, a low number of parameters, and ease of parameter identification in real-time. Among the numerous existing models of lung parenchyma, some may be well suited for real-time applications; however, they should be extensively assessed against both accuracy and computational efficiency criteria to make an informed choice depending on the requirements of the application. After demonstrating how to derive a real-time compliant force-indentation model from a unixial stress-strain model with rational expression, the core purpose of this paper is to propose such an evaluation of selected models in fitting human lung parenchyma experimental and synthetic data of uniaxial tension. Furthermore, new uniaxial stress-strain models are developed based on an empirical observation of the volumetric behavior of the lungs along with an emphasis on computational performance. These new proposed models are competitive with existing one in terms of computational efficiency and compliance with experimental and synthetic data. One of them reduces the prediction error by 2 compared to other investigated models while maintaining an excellent adjusted coefficient of determination between 0.999 and 1 across various datasets. It exhibits excellent real-time capabilities with an explicit rational expression, only 3 parameters and linear numerator and denominator in the parameters. It is computed with only 20 floating point operations (flops) while another proposed model even requires as few as 2 flops.

Multi-dimensional predictors of first drinking initiation and regular drinking onset in adolescence: A prospective longitudinal study.

Early adolescent drinking onset is linked to myriad negative consequences. Using the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) baseline to year 8 data, this study (1) leveraged best subsets selection and Cox Proportional Hazards regressions to identify the most robust predictors of adolescent first and regular drinking onset, and (2) examined the clinical utility of drinking onset in forecasting later binge drinking and withdrawal effects. Baseline predictors included youth psychodevelopmental characteristics, cognition, brain structure, family, peer, and neighborhood domains. Participants (N=538) were alcohol-naïve at baseline. The strongest predictors of first and regular drinking onset were positive alcohol expectancies (Hazard Ratios [HRs]=1.67-1.87), easy home alcohol access (HRs=1.62-1.67), more parental solicitation (e.g., inquiring about activities; HRs=1.72-1.76), and less parental control and knowledge (HRs=.72-.73). Robust linear regressions showed earlier first and regular drinking onset predicted earlier transition into binge and regular binge drinking (ßs=0.57-0.95). Zero-inflated Poisson regressions revealed that delayed first and regular drinking increased the likelihood (Incidence Rate Ratios [IRR]=1.62 and IRR=1.29, respectively) of never experiencing withdrawal. Findings identified behavioral and environmental factors predicting temporal paths to youthful drinking, dissociated first from regular drinking initiation, and revealed adverse sequelae of younger drinking initiation, supporting efforts to delay drinking onset.

Design of the distribution of iron oxide (Fe3O4) nano-particle drug in realistic cholangiocarcinoma model and the simulation of temperature increase during magnetic induction hyperthermia.

The prognosis for Cholangiocarcinoma (CCA) is unfavorable, necessitating the development of new therapeutic approach such as magnetic hyperthermia therapy (MHT) which is induced by magnetic nano-particle (MNPs) drug to bridge the treatment gap. Given the deep location of CCA within the abdominal cavity and proximity to vital organs, accurately predict the individualized treatment effects and safety brought by the distribution of MNPs in tumor will be crucial for the advancement of MHT in CCA. The Mimics software was used in this study to conduct three-dimensional reconstruction of abdominal computed tomography (CT) and magnetic reso-nance imaging images from clinical patients, resulting in the generation of a realistic digital geometric model representing the human biliary tract and its adjacent structures. Subsequently, The COMSOL Multiphysics software was utilized for modeling CCA and calculating the heat transfer law resulting from the multi-regional distribution of MNPs in CCA. The temperature within the central region of irregular CCA measured approximately 46°C, and most areas within the tumor displayed temperatures surpassing 41°C. The temperature of the inner edge of CCA is only 39 ~ 41℃, however, it can be ameliorated by adjusting the local drug concentration through simulation system. For CCA with diverse morphologies and anatomical locations, the multi-regional distribution patterns of intratumoral MNPs and a slight overlap of drug distribution areas synergistically enhance intratumoral temperature while ensuring treatment safety. The present study highlights the practicality and imperative of incorporating personalized intratumoral MNPs distribution strategy into clinical practice for MHT, which can be achieved through the development of an integrated simulation system which incorporates medical image data and numerical calculations.

Animal models of temporomandibular joint heterotopic ossification: a scoping review.

There are few animal models for heterotopic ossification of the temporomandibular joint (TMJ-HO). This scoping review provides an overview of current knowledge on the induction methods and specific conditions required to produce TMJ-HO in various animal models. Two independent reviewers selected papers from the PubMed, Web of Science, and Cochrane Library databases. The inclusion criteria were articles in English, in vivo studies, and a TMJ-HO induction method. Observational, in vitro, human studies, reviews, and book chapters were excluded. Twenty-four publications were included. HO was surgically, genetically, or chemically induced through single or combined defects in the condyle, articular disc, and temporal bone in animal models (sheep=9 studies, mouse=5, rat=4, rabbit=2, pig=2, goat=1, dog=1, monkey=1) specific for traumatic TMJ-HO (n=4), ankylosis (n=9), osteoarthritis (n=8), experimental disc perforation (n=1), status post-TMJ replacement (n=1), and status post bilateral sagittal split osteotomy (n=1). TMJ-HO remains challenging to study due to its multifactorial etiology and largely unknown pathogenesis, which varies between species. There is a need for more accurate, reproducible animal models that can be extrapolated to human TMJ-HO and a consolidated clinical classification system to allow for meaningful future research.

A model study on the effect of human's height variability in particle deposition and retained dose in the respiratory tract.

The objective of the current study was to investigate the impact of human's height variability to the deposition percentage, the deposited and the retained dose of particulate matter in the respiratory tract. In addition, the dose to the oesophagus, blood and lymph nodes was evaluated after particle clearance. A methodology which correlates anatomical and physiological parameters with height was adopted into an existing particle dosimetry model (Exposure Dose Model 2, ExDoM2). Model results showed that deposition of particles with aerodynamic diameter (dae) ranging from 0.001 to 10 µm depends on the competition between anatomical/physiological parameters, with the maximum effect induced from height variability to be observed for particles in the size range of 0.30 µm

Enhancing flood mapping through ensemble machine learning in the Gamasyab watershed, Western Iran.

Floods are among the natural hazards that have seen a rapid increase in frequency in recent decades. The damage caused by floods, including human and financial losses, poses a serious threat to human life. This study evaluates two machine learning (ML) techniques for flood susceptibility mapping (FSM) in the Gamasyab watershed in Iran. We utilized random forest (RF), support vector machine (SVM), ensemble models, and a geographic information system (GIS) to predict FSM. The application of these models involved 10 effective factors in flooding, as well as 82 flood locations integrated into the GIS. The SVM and RF models were trained and tested, followed by the implementation of resampling techniques (RT) using bootstrap and subsampling methods in three repetitions. The results highlighted the importance of elevation, slope, and precipitation as primary factors influencing flood occurrence. Additionally, the ensemble model outperformed both the RF and SVM models, achieving an area under the curve (AUC) of 0.9, a correlation coefficient (COR) of 0.79, a true skill statistic (TSS) of 0.83, and a standard deviation (SD) of 0.71 in the test phase. The tested models were adapted to available input data to map the FSM across the study watershed. These findings underscore the potential of integrating an ensemble model with GIS as an effective tool for flood susceptibility mapping.

Assessment of Probiotics' Impact on Neurodevelopmental and Behavioral Responses in Zebrafish Models: Implications for Autism Spectrum Disorder Therapy.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder; the prevalence of which has been on the rise with unknown causes. Alterations in the gut-brain axis have been widely recognized in ASD patients, and probiotics are considered to potentially benefit the rescuing of autism-like behaviors. However, the effectiveness and mechanisms of multiple probiotics on zebrafish models are still not clearly revealed. This study aims to use the germ-free (GF) and conventionally raised (CR) AB wild-type zebrafish and the mutant Tbr1b-/- and Katnal2-/- lines as human-linked ASD animal models to evaluate the effects of multiple probiotics on mitigating developmental and behavioral defects. Results showed that the addition of probiotics increased the basic important developmental indexes, such as body length, weight, and survival rate of treated zebrafish. Moreover, the Lactobacillus plantarum and Lactobacillus rhamnosus affected the behavior of CR zebrafish by increasing their mobility, lowering the GF zebrafish manic, and mitigating transgenic zebrafish abnormal behavior. Moreover, the expression levels of key genes related to gamma-aminobutyric acid (GABA), dopamine (DA), and serotonin (5-HT) as important neuropathways to influence the appearance and development of autism-related disorders, including gad1b, tph1a, htr3a, th, and slc6a3, were significantly activated by some of the probiotics' treatment at some extent. Taken together, this study indicates the beneficial effects of different probiotics, which may provide a novel understanding of probiotic function in related diseases' therapy.

Explainable AI and transformer models: Unraveling the nutritional influences on Alzheimer's disease mortality.

This pioneering study introduces the use of transformer-based machine learning models and explainable AI approaches to explore the impact of nutrition on Alzheimer's disease (AD) mortality. Using data from the Third National Health and Nutrition Examination Survey (Nhanes iii 1988 to 1994) and the NHANES III Mortality-Linked File (2019) databases, we investigate the intricate relationship between various nutritional factors and AD mortality. Our approach features a novel application of transformer models, which are then benchmarked against established methods like random forests and support vector machines. This comparison not only underscores the strengths of transformer models in handling complex medical datasets but also highlights their potential for providing deeper insights into disease progression. Key findings, such as the significant roles of Platelet distribution width in AD mortality in transformer and Serum Vitamin B12 in random forest, are enhanced by the use of Explainable Artificial Intelligence (XAI), particularly the Shapley Additive Explanations (SHAP) and the integrated gradient methods. This study serves as a vital step forward in applying advanced AI techniques to medical research, offering new perspectives in understanding and combating Alzheimer's Disease.

Large Language Models and OpenLogos: An Educational Case Scenario.

Large Language Models (LLMs) offer advanced text generation capabilities, sometimes surpassing human abilities. However, their use without proper expertise poses significant challenges, particularly in educational contexts. This article explores different facets of natural language generation (NLG) within the educational realm, assessing its advantages and disadvantages, particularly concerning LLMs. It addresses concerns regarding the opacity of LLMs and the potential bias in their generated content, advocating for transparent solutions. Therefore, it examines the feasibility of integrating OpenLogos expert-crafted resources into language generation tools used for paraphrasing and translation. In the context of the Multi3Generation COST Action (CA18231), we have been emphasizing the significance of incorporating OpenLogos into language generation processes, and the need for clear guidelines and ethical standards in generative models involving multilingual, multimodal, and multitasking capabilities. The Multi3Generation initiative strives to progress NLG research for societal welfare, including its educational applications. It promotes inclusive models inspired by the Logos Model, prioritizing transparency, human control, preservation of language principles and meaning, and acknowledgment of the expertise of resource creators. We envision a scenario where OpenLogos can contribute significantly to inclusive AI-supported education. Ethical considerations and limitations related to AI implementation in education are explored, highlighting the importance of maintaining a balanced approach consistent with traditional educational principles. Ultimately, the article advocates for educators to adopt innovative tools and methodologies to foster dynamic learning environments that facilitate linguistic development and growth.

Large Language Models boast advanced text generation quality and capabilities, often surpassing those of humans. However, they also pose significant challenges when used without proper expertise or care. In an educational context, the examination of language generation tools and their use by students is vital for establishing guidelines and a shared understanding of their ethical usage. This article explores several aspects of language generation within an educational context, and showcases the potential use of OpenLogos resources, provided within the framework of the Multi3Generation COST Action (CA18231) in language study and their integration into language learning tools, such as paraphrasing (monolingual) and translation (bilingual or multilingual). This article emphasizes the importance of leveraging OpenLogos in education, especially in language learning or language enhancement contexts. By embracing innovative tools and methodologies, educators can nurture a dynamic and enriching learning environment conducive to linguistic growth and development.

Mathematical models of TCR initial triggering.

T cell receptors (TCRs) play crucial roles in regulating T cell response by rapidly and accurately recognizing foreign and non-self antigens. The process involves multiple molecules and regulatory mechanisms, forming a complex network to achieve effective antigen recognition. Mathematical modeling techniques can help unravel the intricate network of TCR signaling and identify key regulators that govern it. In this review, we introduce and briefly discuss relevant mathematical models of TCR initial triggering, with a focus on kinetic proofreading (KPR) models with different modified structures. We compare the topology structures, biological hypotheses, parameter choices, and simulation performance of each model, and summarize the advantages and limitations of them. Further studies on TCR modeling design, aiming for an optimized balance of specificity and sensitivity, are expected to contribute to the development of new therapeutic strategies.

Preclinical models for the study of pediatric solid tumors: focus on bone sarcomas.

Sarcomas comprise between 10-15% of all pediatric malignancies. Osteosarcoma and Ewing sarcoma are the two most common pediatric bone tumors diagnosed in children and young adults. These tumors are commonly treated with surgery and/or radiation therapy and combination chemotherapy. However, there is a strong need for the development and utilization of targeted therapeutic methods to improve patient outcomes. Towards accomplishing this goal, pre-clinical models for these unique malignancies are of particular importance to design and test experimental therapeutic strategies prior to being introduced to patients due to their origination site and propensity to metastasize. Pre-clinical models offer several advantages for the study of pediatric sarcomas with unique benefits and shortcomings dependent on the type of model. This review addresses the types of pre-clinical models available for the study of pediatric solid tumors, with special attention to the bone sarcomas osteosarcoma and Ewing sarcoma.