Flexible regression model for predicting the dissemination of Candidatus Liberibacter asiaticus under variable climatic conditions.

Greening, or Huanglongbing (HLB), poses a severe threat to global citrus cultivation, affecting various citrus species and compromising fruit production. Primarily transmitted by psyllids during phloem feeding, the bacterium Candidatus Liberibacter induces detrimental symptoms, including leaf yellowing and reduced fruit quality. Given the limitations of conventional control strategies, the search for innovative approaches, such as resistant genotypes and early diagnostic methods, becomes essential for the sustainability of citrus cultivation. The development of predictive models, such as the one proposed in this study, is essential as it enables the estimation of the bacterium's concentration and the vulnerability of healthy plants to infection, which will be instrumental in determining the risk of HLB. This study proposes a prediction model utilizing environmental factors, including temperature, humidity, and precipitation, which play a decisive role in greening epidemiology, influencing the complex interaction among the pathogen, vector, and host plant. In the proposed modeling, it addresses non-linear relationships through cubic smoothing splines applications and tackles imbalanced categorical predictor variables, requiring the use of a random-effects regression model, incorporating a random intercept to account for variability across different groups and mitigate the risk of biased predictions. The model's ability to predict HLB incidence under varying climatic conditions provides a significant contribution to disease management, offering a strategic tool for early intervention and potentially reducing the spread of HLB. Using climatological and environmental data, the research aims to develop a predictive model, assessing the influence of these variables on the spread of Candidatus Liberibacter asiaticus, essential for effective disease management. The proposed flexible model demonstrates robust predictions for both training and test data, identifying climatological and environmental predictors influencing the dissemination of Candidatus Liberibacter asiaticus, the vascular bacterium associated with Huanglongbing (HLB) or greening.

Diagnosing Glaucoma Based on the Ocular Hypertension Treatment Study Dataset Using Chat Generative Pre-Trained Transformer as a Large Language Model.

Purpose: To evaluate the capabilities of Chat Generative Pre-Trained Transformer (ChatGPT), as a large language model (LLM), for diagnosing glaucoma using the Ocular Hypertension Treatment Study (OHTS) dataset, and comparing the diagnostic capability of ChatGPT 3.5 and ChatGPT 4.0. Design: Prospective data collection study. Participants: A total of 3170 eyes of 1585 subjects from the OHTS were included in this study. Methods: We selected demographic, clinical, ocular, visual field, optic nerve head photo, and history of disease parameters of each participant and developed case reports by converting tabular data into textual format based on information from both eyes of all subjects. We then developed a procedure using the application programming interface of ChatGPT, a LLM-based chatbot, to automatically input prompts into a chat box. This was followed by querying 2 different generations of ChatGPT (versions 3.5 and 4.0) regarding the underlying diagnosis of each subject. We then evaluated the output responses based on several objective metrics. Main Outcome Measures: Area under the receiver operating characteristic curve (AUC), accuracy, specificity, sensitivity, and F1 score. Results: Chat Generative Pre-Trained Transformer 3.5 achieved AUC of 0.74, accuracy of 66%, specificity of 64%, sensitivity of 85%, and F1 score of 0.72. Chat Generative Pre-Trained Transformer 4.0 obtained AUC of 0.76, accuracy of 87%, specificity of 90%, sensitivity of 61%, and F1 score of 0.92. Conclusions: The accuracy of ChatGPT 4.0 in diagnosing glaucoma based on input data from OHTS was promising. The overall accuracy of ChatGPT 4.0 was higher than ChatGPT 3.5. However, ChatGPT 3.5 was found to be more sensitive than ChatGPT 4.0. In its current forms, ChatGPT may serve as a useful tool in exploring disease status of ocular hypertensive eyes when specific data are available for analysis. In the future, leveraging LLMs with multimodal capabilities, allowing for integration of imaging and diagnostic testing as part of the analyses, could further enhance diagnostic capabilities and enhance diagnostic accuracy. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Analysis of ChatGPT Responses to Ophthalmic Cases: Can ChatGPT Think like an Ophthalmologist?

Objective: Large language models such as ChatGPT have demonstrated significant potential in question-answering within ophthalmology, but there is a paucity of literature evaluating its ability to generate clinical assessments and discussions. The objectives of this study were to (1) assess the accuracy of assessment and plans generated by ChatGPT and (2) evaluate ophthalmologists' abilities to distinguish between responses generated by clinicians versus ChatGPT. Design: Cross-sectional mixed-methods study. Subjects: Sixteen ophthalmologists from a single academic center, of which 10 were board-eligible and 6 were board-certified, were recruited to participate in this study. Methods: Prompt engineering was used to ensure ChatGPT output discussions in the style of the ophthalmologist author of the Medical College of Wisconsin Ophthalmic Case Studies. Cases where ChatGPT accurately identified the primary diagnoses were included and then paired. Masked human-generated and ChatGPT-generated discussions were sent to participating ophthalmologists to identify the author of the discussions. Response confidence was assessed using a 5-point Likert scale score, and subjective feedback was manually reviewed. Main Outcome Measures: Accuracy of ophthalmologist identification of discussion author, as well as subjective perceptions of human-generated versus ChatGPT-generated discussions. Results: Overall, ChatGPT correctly identified the primary diagnosis in 15 of 17 (88.2%) cases. Two cases were excluded from the paired comparison due to hallucinations or fabrications of nonuser-provided data. Ophthalmologists correctly identified the author in 77.9% ± 26.6% of the 13 included cases, with a mean Likert scale confidence rating of 3.6 ± 1.0. No significant differences in performance or confidence were found between board-certified and board-eligible ophthalmologists. Subjectively, ophthalmologists found that discussions written by ChatGPT tended to have more generic responses, irrelevant information, hallucinated more frequently, and had distinct syntactic patterns (all P < 0.01). Conclusions: Large language models have the potential to synthesize clinical data and generate ophthalmic discussions. While these findings have exciting implications for artificial intelligence-assisted health care delivery, more rigorous real-world evaluation of these models is necessary before clinical deployment. Financial Disclosures: The author(s) have no proprietary or commercial interest in any materials discussed in this article.

Weight of Evidence: Criteria and Applications.

Toxicologists and authorities evaluate substances that in the traditional way refer to data and knowledge on the toxic mechanism. Non-testing methods (NTMs) proved to be a valuable resource for risk assessment of chemical substances. Indeed, they can be particularly useful when the information provided by different sources is integrated to increase confidence in the result. In this chapter, we will address data obtained from NTM, including in silico models and read-across. Typically, these two approaches are used separately, but in this way, we lose some information. The integration of different results can be sometimes difficult because different methods can lead to conflicting results and because a clear guideline for integrating information from different sources was not available in the recent past. In this chapter, we present and discuss the recently published guideline from EFSA for integrating and weighting evidence for scientific assessment, and how to proceed, manually or through novel integrated tool, SWAN. Moreover, practical examples of the application of these integration principles on evidence from different in silico models are shown. These examples represent a demonstration of the suitability and effectiveness of in silico methods for risk assessment, as well as a practical guide to end users to perform similar analyses on likely hazardous chemicals.

Nonlinear mixed models and related approaches in infectious disease modeling: A systematic and critical review.

The level of surveillance and preparedness against epidemics varies across countries, resulting in different responses to outbreaks. When conducting an in-depth analysis of microinfection dynamics, one must account for the substantial heterogeneity across countries. However, many commonly used statistical model specifications lack the flexibility needed for sound and accurate analysis and prediction in such contexts. Nonlinear mixed effects models (NLMMs) constitute a specific statistical tool that can overcome these significant challenges. While compartmental models are well-established in infectious disease modeling and have seen significant advancements, Nonlinear Mixed Models (NLMMs) offer a flexible approach for handling heterogeneous and unbalanced repeated measures data, often with less computational effort than some individual-level compartmental modeling techniques. This study provides an overview of their current use and offers a solid foundation for developing guidelines that may help improve their implementation in real-world situations. Relevant scientific databases in the Research4life Access initiative programs were used to search for papers dealing with key aspects of NLMMs in infectious disease modeling (IDM). From an initial list of 3641 papers, 124 were finally included and used for this systematic and critical review spanning the last two decades, following the PRISMA guidelines. NLMMs have evolved rapidly in the last decade, especially in IDM, with most publications dating from 2017 to 2021 (83.33%). The routine use of normality assumption appeared inappropriate for IDM, leading to a wealth of literature on NLMMs with non-normal errors and random effects under various estimation methods. We noticed that NLMMs have attracted much attention for the latest known epidemics worldwide (COVID-19, Ebola, Dengue and Lassa) with the robustness and reliability of relaxed propositions of the normality assumption. A case study of the application of COVID-19 data helped to highlight NLMMs' performance in modeling infectious diseases. Out of this study, estimation methods, assumptions, and random terms specification in NLMMs are key aspects requiring particular attention for their application in IDM.

ChatGPT-Assisted Classification of Postoperative Bleeding Following Microinvasive Glaucoma Surgery Using Electronic Health Record Data.

Purpose: To evaluate the performance of a large language model (LLM) in classifying electronic health record (EHR) text, and to use this classification to evaluate the type and resolution of hemorrhagic events (HEs) after microinvasive glaucoma surgery (MIGS). Design: Retrospective cohort study. Participants: Eyes from the Bascom Palmer Glaucoma Repository. Methods: Eyes that underwent MIGS between July 1, 2014 and February 1, 2022 were analyzed. Chat Generative Pre-trained Transformer (ChatGPT) was used to classify deidentified EHR anterior chamber examination text into HE categories (no hyphema, microhyphema, clot, and hyphema). Agreement between classifications by ChatGPT and a glaucoma specialist was evaluated using Cohen's Kappa and precision-recall (PR) curve. Time to resolution of HEs was assessed using Cox proportional-hazards models. Goniotomy HE resolution was evaluated by degree of angle treatment (90°-179°, 180°-269°, 270°-360°). Logistic regression was used to identify HE risk factors. Main Outcome Measures: Accuracy of ChatGPT HE classification and incidence and resolution of HEs. Results: The study included 434 goniotomy eyes (368 patients) and 528 Schlemm's canal stent (SCS) eyes (390 patients). Chat Generative Pre-trained Transformer facilitated excellent HE classification (Cohen's kappa 0.93, area under PR curve 0.968). Using ChatGPT classifications, at postoperative day 1, HEs occurred in 67.8% of goniotomy and 25.2% of SCS eyes (P < 0.001). The 270° to 360° goniotomy group had the highest HE rate (84.0%, P < 0.001). At postoperative week 1, HEs were observed in 43.4% and 11.3% of goniotomy and SCS eyes, respectively (P < 0.001). By postoperative month 1, HE rates were 13.3% and 1.3% among goniotomy and SCS eyes, respectively (P < 0.001). Time to HE resolution differed between the goniotomy angle groups (log-rank P = 0.034); median time to resolution was 10, 10, and 15 days for the 90° to 179°, 180° to 269°, and 270° to 360° groups, respectively. Risk factor analysis demonstrated greater goniotomy angle was the only significant predictor of HEs (odds ratio for 270°-360°: 4.08, P < 0.001). Conclusions: Large language models can be effectively used to classify longitudinal EHR free-text examination data with high accuracy, highlighting a promising direction for future LLM-assisted research and clinical decision support. Hemorrhagic events are relatively common self-resolving complications that occur more often in goniotomy cases and with larger goniotomy treatments. Time to HE resolution differs significantly between goniotomy groups. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Construction of Coarse-Grained Molecular Dynamics Model of Nuclear Global Chromosomes Dynamics in Mammalian Cells.

Biomolecules contain various heterogeneities in their structures and local chemical properties, and their functions emerge through the dynamics encoded by these heterogeneities. Molecular dynamics model-based studies will greatly contribute to the elucidation of such chemical/mechanical structure-dynamics-function relationships and the mechanisms that generate them. Coarse-grained molecular dynamics models with appropriately designed nonuniform local interactions play an important role in considering the various phenomena caused by large molecular complexes consisting of various proteins and DNA such as nuclear chromosomes. Therefore, in this chapter, we will introduce a method for constructing a coarse-grained molecular dynamics model that simulates the global behavior of each chromosome in the nucleus of a mammalian cell containing many giant chromosomes.

Full-Field Electroretinogram Responses in Rodent Models of Ganglion Cell Injury.

Preclinical studies of optic nerve injury models have led to significant insight into the mechanism underlying retinal ganglion cell neurodegeneration. During the process of ganglion cell injury, morphological changes can occur prior to gross structural changes and cell death. Similarly, following injury, functional changes can occur in the absence of substantive structural changes. These more subtle effects can often be detected using functional tools such as the electroretinogram. Moreover, the electroretinogram is a sensitive and complementary means to quantify treatment efficacy. Here, we describe in vivo electroretinography for assessing ganglion cell injury in rodent models.

Testing Visual Function by Assessment of the Optomotor Reflex in Glaucoma.

Optomotor response/reflex (OMR) is a fast and efficient first-in-line visual screening method, especially for rodents. It has the potential to evaluate both the scotopic and photopic visions of nonrestrained animals through tracking head movement, providing a quantitative estimate of visual functions. In restrained animals, optokinetic response (OKR), compensatory eye movements for visual shifts in the surroundings, is utilized. Both OMR and OKR capitalize on an individual's innate reflex to stabilize images for the purpose of capturing clear vision. The two reflexes have similar reliability when evaluating stimulus luminance, contrast, spatial frequency, and velocity. They have emerged as powerful tools to evaluate the efficacy of pharmacological treatments and phenotypes of subjects undergoing study. With OMR and OKR accurately assessing visual acuity (VA) as well as contrast sensitivity (CS), the gold standards for measuring clinical vision, they provide reliable and easily accessible results that further eye and brain research. These methods of sight evaluation have been used in multiple animal models, particularly mice and zebrafish. Through OMR assays, these animal models have been utilized to investigate retinal degenerative diseases, helping researchers differentiate between worsening stages. Alongside tests such as optical coherence tomography (OCT), OMR provides confirmation of visual status, where increased OMR function often correlates with improved visual status. OMR has continued to be used outside of glaucoma in various retinal diseases, such as retinitis pigmentosa (RP), diabetic retinopathy, and age-related macular degeneration.In this chapter, we will introduce the concept and application of visual stimulus-induced head or eye reflex movement in different animal species and experimental models of eye diseases, such as glaucoma and other neurodegenerative disorders, and in patients with glaucoma.

Type 2 Cytokine-Dependent Skin Barrier Regulation in Personalized 2-Dimensional and 3-Dimensional Skin Models of Atopic Dermatitis: A Pilot Study.

Keratinocytes (KCs) from healthy donors stimulated with type 2 cytokines are often used to experimentally study atopic dermatitis (AD) inflammatory responses. Owing to potential intrinsic alterations, it seems favorable to use KCs from patients with AD. KCs isolated from hair follicles offer a noninvasive approach to investigate AD-derived KCs. To evaluate whether such AD-derived KCs are suitable to mimic AD inflammatory responses, we compared hair follicle-derived KCs from healthy donors with those from patients with AD in a type 2 cytokine environment. Stimulation of AD-derived KCs with IL-4 and IL-13 induced higher expression changes of AD-associated markers than that of healthy KCs. The combination of IL-4 and IL-13 generally induced highest expression changes, but IL-13 alone also induced significant changes of AD-specific markers. Similar to the 2-dimensional cultures, IL-4/IL-13 stimulation of 3-dimensional skin models generated with AD-derived KCs modulated the expression of several AD-relevant factors. Whole-transcriptome analysis revealed that IL-4 and IL-13 acted similarly on these 3-dimensional skin models. Histologically, IL-13 alone and in combination with IL-4 increased epidermal spongiosis, a histological hallmark of AD skin. Taken together, our pilot study suggests that hair follicle-derived KCs from patients with AD represent a useful model system to study AD-related inflammation in a personalized in vitro model.

Understanding the cellular dynamics, engineering perspectives and translation prospects in bioprinting epithelial tissues.

The epithelium is one of the important tissues in the body as it plays a crucial barrier role serving as a gateway into and out of the body. Most organs in the body contain an epithelial tissue component, where the tightly connected, organ-specific epithelial cells organize into cysts, invaginations, or tubules, thereby performing distinct to endocrine or exocrine secretory functions. Despite the significance of epithelium, engineering functional epithelium in vitro has remained a challenge due to it is special architecture, heterotypic composition of epithelial tissues, and most importantly, difficulty in attaining the apico-basal and planar polarity of epithelial cells. Bioprinting has brought a paradigm shift in fabricating such apico-basal polarized tissues. In this review, we provide an overview of epithelial tissues and provide insights on recapitulating their cellular arrangement and polarization to achieve epithelial function. We describe the different bioprinting techniques that have been successful in engineering polarized epithelium, which can serve as in vitro models for understanding homeostasis and studying diseased conditions. We also discuss the different attempts that have been investigated to study these 3D bioprinted engineered epithelium for preclinical use. Finally, we highlight the challenges and the opportunities that need to be addressed for translation of 3D bioprinted epithelial tissues towards paving way for personalized healthcare in the future.

QSAR: Using the Past to Study the Present.

Quantitative structure-activity relationships (QSAR) is a method for predicting the physical and biological properties of small molecules; it is in use in industry and public services. However, as any scientific method, it is challenged by more and more requests, especially considering its possible role in assessing the safety of new chemicals. To answer the question whether QSAR, by exploiting available knowledge, can build new knowledge, the chapter reviews QSAR methods in search of a QSAR epistemology. QSAR stands on tree pillars, i.e., biological data, chemical knowledge, and modeling algorithms. Usually the biological data, resulting from good experimental practice, are taken as a true picture of the world; chemical knowledge has scientific bases; so if a QSAR model is not working, blame modeling. The role of modeling in developing scientific theories, and in producing knowledge, is so analyzed. QSAR is a mature technology and is part of a large body of in silico methods and other computational methods. The active debate about the acceptability of the QSAR models, about the way to communicate them, and the explanation to provide accompanies the development of today QSAR models. An example about predicting possible endocrine-disrupting chemicals (EDC) shows the many faces of modern QSAR methods.

Toxicity Potential of Nutraceuticals.

During the past few decades and especially during and after the COVID-19 pandemic, the use of nutraceuticals has become increasingly popular in both humans and animals due to their easy access, cost-effectiveness, and tolerability with a wide margin of safety. While some nutraceuticals are safe, others have an inherent toxic potential. For a large number of nutraceuticals, no toxicity/safety data are available due to a lack of pharmacological/toxicological studies. The safety of some nutraceuticals can be compromised via contamination with toxic plants, metals, mycotoxins, pesticides, fertilizers, drugs of abuse, etc. Knowledge of pharmacokinetic/toxicokinetic studies and biomarkers of exposure, effect, and susceptibility appears to play a pivotal role in the safety and toxicity assessment of nutraceuticals. Interaction studies are essential to determine efficacy, safety, and toxicity when nutraceuticals and therapeutic drugs are used concomitantly or when polypharmacy is involved. This chapter describes various aspects of nutraceuticals, particularly their toxic potential, and the factors that influence their safety.

Genetic Mouse Models of Lymphomas.

Mouse models are an indispensable tool in lymphoma research. Here, we focus on the utilization of genetically engineered mouse models as preclinical avatars in lymphoma research. We describe lymphoma-relevant alleles and allele combinations, as well as general considerations for model selection. We further illustrate concepts of gene targeting and model design and provide guidelines for breeding strategies and colony maintenance.

Association between the practice of fitness-related exercises and body image dissatisfaction in adolescents from Curitiba (PR), Brazil / Associação entre a prática de exercícios físicos relacionados ao fitness e insatisfação com a imagem corporal em adolescentes de Curitiba (PR), Brasil

ABSTRACT Objective: The aim of this study was to analyze the association between participation in fitness-related exercises (FRE) and body image dissatisfaction (BID) in adolescents and evaluate the interaction between physical exercise and nutritional status in this association. Methods: A cross-sectional study was conducted in 2015 involving 799 adolescents (10-16 years old) from 14 public schools in Curitiba (PR), Brazil. BID was assessed using the Body Shape Questionnaire and the Silhouette Scale. The FRE was classified as "does not practice," "practices ≤300 min/week," and "practices >300 min/week" by the Physical Activity Questionnaire for Adolescents. Poisson and multinomial logistic regressions, adjusted for sex, sexual maturation, and nutritional status analyzed the association of FRE and BID. Results: The BID prevalence was 28.3%; 52.4% of the adolescents wanted to reduce their silhouettes; and 48.7% did not practice FRE. Adolescents who practiced FRE >300 min/week had a 28% higher prevalence for some level of BID (PR 1.28; 95%CI 1.08-1.52) and a 46% lower chance of wanting to reduce silhouettes (OR 0.54; 95%CI 0.35-0.82), compared to nonpractitioners. There was no interaction between FRE and nutritional status in association with BID. Conclusions: The adolescents who practice FRE >300 min/week are likely to have some level of BID and are less likely to report the desire to increase their silhouettes, regardless of their nutritional status.

RESUMO Objetivo: Analisar a associação entre a participação em exercícios físicos relacionados ao fitness (EFRF) e a insatisfação com a imagem corporal (IIC) em adolescentes e avaliar a interação entre os exercícios físicos e o estado nutricional nesta associação. Métodos: Estudo transversal realizado em 2015 com 799 adolescentes (10 a 16 anos) de 14 escolas públicas de Curitiba (PR), Brasil. A IIC foi avaliada por meio do Body Shape Questionnaire e da Escala de Silhuetas. A participação em EFRF foi avaliada pelo Questionário de Atividade Física para Adolescentes e classificada em "não pratica", "pratica ≤300 minutos/semana" e "pratica >300 minutos/semana". As regressões de Poisson e logística multinomial, ajustadas por sexo, maturação sexual e estado nutricional, analisaram a associação entre EFRF e IIC. Resultados: A prevalência de IIC foi de 28,3%; 52,4% dos adolescentes queriam reduzir a silhueta e 48,7% não praticavam a EFRF. Adolescentes que praticavam EFRF >300 minutos/semana tiveram prevalência 28% maior para algum nível de IIC (razão de prevalência — RP 1,28; intervalo de confiança de 95% — IC95% 1,08-1,52) e chance 46% menor de querer reduzir silhuetas (OR 0,54; 95IC% 0,35-0,82), comparados aos não praticantes. Não houve interação entre os EFRF e o estado nutricional na associação com IIC. Conclusões: Os adolescentes que praticam EFRF >300 minutos/semana estão mais propensos a apresentar algum nível de IIC e têm menores chances de reportar o desejo de aumentar silhuetas, independentemente do estado nutricional.

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.

How accurately do finite element models predict the fall impact response of ex vivo specimens augmented by prophylactic intramedullary nailing?

Hip fracture prevention approaches like prophylactic augmentation devices have been proposed to strengthen the femur and prevent hip fracture in a fall scenario. The aim of this study was to validate the finite element model (FEM) of specimens augmented by prophylactic intramedullary nailing in a simulated sideways fall impact against ex vivo experimental data. A dynamic inertia-driven sideways fall simulator was used to test six cadaveric specimens (3 females, 3 males, age 63-83 years) prophylactically implanted with an intramedullary nailing system used to augment the femur. Impact force measurements, pelvic deformation, effective pelvic stiffness, and fracture outcomes were compared between the ex vivo experiments and the FEMs. The FEMs over-predicted the effective pelvic stiffness for most specimens and showed variability in terms of under- and over-predicting peak impact force and pelvis compression depending on the specimen. A significant correlation was found for time to peak impact force when comparing ex vivo and FEM data. No femoral fractures were found in the ex vivo experiments, but two specimens sustained pelvic fractures. These two pelvis fractures were correctly identified by the FEMs, but the FEMs made three additional false-positive fracture identifications. These validation results highlight current limitations of these sideways fall impact models specific to the inclusion of an orthopaedic implant. These FEMs present a conservative strategy for fracture prediction in future applications. Further evaluation of the modelling approaches used for the bone-implant interface is recommended for modelling augmented specimens, alongside the importance of maintaining well-controlled experimental conditions.

Modeling of Parkinson's Disease in Different Models.

Parkinson's Disease (PD) is a progressive disorder worldwide and its etiology remains unidentified. Over the last few decades, animal models of PD have been extensively utilized to explore the development and mechanisms of this neurodegenerative condition. Toxic and transgenic animal models for PD possess unique characteristics and constraints, necessitating careful consideration when selecting the appropriate model for research purposes. Animal models have played a significant role in uncovering the causes and development of PD, including its cellular and molecular processes. These models suggest that the disorder arises from intricate interplays between genetic predispositions and environmental influences. Every model possesses its unique set of strengths and weaknesses. This review provides a critical examination of animal models for PD and compares them with the features observed in the human manifestation of the disease.