Use of cannabidiol in the treatment of drug-refractory epilepsy in children and young adults: A systematic review.

Objectives: Epilepsy poses a significant challenge in pediatric and adolescent populations, impacting not only seizures but also psychological and cognitive comorbidities, leading to higher mortality rates than the general population. Drug-refractory epilepsy, resistant to conventional treatments, affects a range of 7-20% of pediatric patients. The search for alternative therapies has led to exploring the therapeutic potential of Cannabis sativa L. compounds, particularly cannabidiol (CBD). Examine the use of CBD for treating drug-refractory epilepsy in children and young adults, summarizing existing evidence on its efficacy. Materials and Methods: A systematic review, following Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines, assessed studies from 2018 to 2023, focusing on CBD's efficacy and safety for treatment-resistant epilepsy in pediatric and juvenile populations. The search spanned seven databases, and the studies underwent rigorous screening and data extraction. Results: Out of 6351 identified articles, eight were selected for review. The included studies reported positive outcomes, with CBD leading to a reduction in seizure frequency ranging from 50% to complete seizure freedom. Adverse effects were mostly mild and reversible, including drowsiness, diarrhea, and loss of appetite. Conclusion: The CBD emerges as a promising tool for refractory epilepsy in pediatric patients, showing efficacy in reducing seizure frequency and improving overall quality of life. Despite mild and reversible adverse effects, CBD's benefits outweigh the risks. However, more research on long-term effects is needed to fully understand its implications.

The global prevalence and associated risk factors of Eimeria infection in domestic chickens: A systematic review and meta-analysis.

BACKGROUND: Eimeria is a protozoan parasite that affects poultry, particularly chickens, causing a disease known as coccidiosis. This disease imposes substantial significant economic challenges to the poultry sector. OBJECTIVES: The current study aimed to estimate the global prevalence and associated risk factors of Eimeria in domestic chickens. METHODS: Multiple databases (Scopus, PubMed, ProQuest, Web of Science and Google Scholar) were searched for articles published until June 2023. The pooled prevalence was estimated using a random-effects model with a 95% confidence interval. The statistical analysis was conducted using meta packages in R version (3.6.1). RESULTS: In total, 41 articles fulfilled the eligibility criteria. The global pooled prevalence was 44.3% (36.9%-51.8%) with Eimeria tenella (38.7%, 30.1%-47.7%) as the most prevalent species. The highest pooled prevalence was related to the Western Pacific Region (80.5%, 72.6%-87.3%) and urban areas (44.4%, 36.5%-52.6%). Moreover, areas with humid subtropical climates represent the highest overall prevalence (75.8%, 46.6%-95.9%). CONCLUSION: The necessity for robust and innovative strategies for preventing and managing this disease cannot be overstated. Addressing Eimeria impact is crucial not only for safeguarding poultry health but also for sustaining the economic viability of the poultry industry.

Asymmetric Synthesis of α-Chloroamides via Photoenzymatic Hydroalkylation of Olefins.

Photoenzymatic intermolecular hydroalkylations of olefins are highly enantioselective for chiral centers formed during radical termination but poorly selective for centers set in the C-C bond-forming event. Here, we report the evolution of a flavin-dependent "ene"-reductase to catalyze the coupling of α,α-dichloroamides with alkenes to afford α-chloroamides in good yield with excellent chemo- and stereoselectivity. These products can serve as linchpins in the synthesis of pharmaceutically valuable motifs. Mechanistic studies indicate that radical formation occurs by exciting a charge-transfer complex templated by the protein. Precise control over the orientation of molecules within the charge-transfer complex potentially accounts for the observed stereoselectivity. The work expands the types of motifs that can be prepared using photoenzymatic catalysis.

Development and Characterization of Electrodes Coated with Plasma-Synthesized Polypyrrole Doped with Iodine, Implanted in the Rat Brain Subthalamic Nucleus.

Biological treatments involve the application of metallic material coatings to enhance biocompatibility and properties. In invasive therapies, metallic electrodes are utilized, which are implanted in patients. One of these invasive therapeutic procedures is deep brain stimulation (DBS), an effective therapy for addressing the motor disorders observed in patients with Parkinson's disease (PD). This therapy involves the implantation of electrodes (IEs) into the subthalamic nucleus (STN). However, there is still a need for the optimization of these electrodes. Plasma-synthesized polypyrrole doped with iodine (PPPy/I) has been reported as a biocompatible and anti-inflammatory biomaterial that promotes nervous system regeneration. Given this information, the objective of the present study was to develop and characterize a PPPy/I-coated electrode for implantation into the STN. The characterization results indicate a uniform coating along the electrode, and physical-chemical characterization studies were conducted on the polymer. Subsequently, the IEs, both coated and uncoated with PPPy/I, were implanted into the STN of male rats of the Wistar strain to conduct an electrographic recording (EG-R) study. The results demonstrate that the IE coated with PPPy/I exhibited superior power and frequency signals over time compared to the uncoated IE (p < 0.05). Based on these findings, we conclude that an IE coated with PPPy/I has optimized functional performance, with enhanced integrity and superior signal quality compared to an uncoated IE. Therefore, we consider this a promising technological development that could significantly improve functional outcomes for patients undergoing invasive brain therapies.

Biosensor and machine learning-aided engineering of an amaryllidaceae enzyme.

A major challenge to achieving industry-scale biomanufacturing of therapeutic alkaloids is the slow process of biocatalyst engineering. Amaryllidaceae alkaloids, such as the Alzheimer's medication galantamine, are complex plant secondary metabolites with recognized therapeutic value. Due to their difficult synthesis they are regularly sourced by extraction and purification from the low-yielding daffodil Narcissus pseudonarcissus. Here, we propose an efficient biosensor-machine learning technology stack for biocatalyst development, which we apply to engineer an Amaryllidaceae enzyme in Escherichia coli. Directed evolution is used to develop a highly sensitive (EC50 = 20 µM) and specific biosensor for the key Amaryllidaceae alkaloid branchpoint 4'-O-methylnorbelladine. A structure-based residual neural network (MutComputeX) is subsequently developed and used to generate activity-enriched variants of a plant methyltransferase, which are rapidly screened with the biosensor. Functional enzyme variants are identified that yield a 60% improvement in product titer, 2-fold higher catalytic activity, and 3-fold lower off-product regioisomer formation. A solved crystal structure elucidates the mechanism behind key beneficial mutations.

Immunization of cattle with a Rhipicephalus microplus chitinase peptide containing predicted B-cell epitopes reduces tick biological fitness.

Rhipicephalus microplus, the cattle fever tick, is the most important ectoparasite impacting the livestock industry worldwide. Overreliance on chemical treatments for tick control has led to the emergence of acaricide-resistant ticks and environmental contamination. An immunological strategy based on vaccines offers an alternative approach to tick control. To develop novel tick vaccines, it is crucial to identify and evaluate antigens capable of generating protection in cattle. Chitinases are enzymes that degrade older chitin at the time of moulting, therefore allowing interstadial metamorphosis. In this study, 1 R. microplus chitinase was identified and its capacity to reduce fitness in ticks fed on immunized cattle was evaluated. First, the predicted amino acid sequence was determined in 4 isolates and their similarity was analysed by bioinformatics. Four peptides containing predicted B-cell epitopes were designed. The immunogenicity of each peptide was assessed by inoculating 2 cattle, 4 times at 21 days intervals, and the antibody response was verified by indirect ELISA. A challenge experiment was conducted with those peptides that were immunogenic. The chitinase gene was successfully amplified and sequenced, enabling comparison with reference strains. Notably, a 99.32% identity and 99.84% similarity were ascertained among the sequences. Furthermore, native protein recognition was demonstrated through western blot assays. Chitinase peptide 3 reduced the weight and oviposition of engorged ticks, as well as larvae viability, exhibiting a 71% efficacy. Therefore, chitinase 3 emerges as a viable vaccine candidate, holding promise for its integration into a multiantigenic vaccine against R. microplus.

Childhood obesity and its impact on the characteristics of gait stance phases: a cross-sectional study.

This study aimed to investigate the variations in foot type, laxity, dynamic characteristics of gait, and the characteristics of the stance phase of gait, in relation to body mass index (BMI) and groups of children of different ages. Additionally, it aimed to explore the correlations between BMI and these variables across children groups of different ages. A cross-sectional study was conducted involving 196 infants aged between 5 and 10 years old. The variables assessed included BMI, foot type, laxity, dynamic variables, and characteristics of the stance phase of gait. Significant variations were observed in foot type, laxity, certain dynamic variables, and characteristics of the stance phase of gait between normoweight (NW) and overweight/obese (OW/OB) groups among children aged between 5 and 10 years old (p ranged between 0.019 and 0.050). Moreover, BMI was also positively associated with the initial forefoot contact, heel off, total duration of the step, and forefoot contact phase of children 7 to 10 years of age (p ranged between < 0.010 and 0.040).   Conclusion: Children who are OW/OB had alterations at different stages of gait. Being OW/OB is related to alterations of the phases of gait mainly from 7 to 10 years of age, and spending more time in each of the phases of walking. This could indicate that children who are OW/OB, in addition to walking slower, overload the musculoskeletal system, subjecting their joints and muscles to greater stress. What is Known: • Children who are overweight (OW) and obese (OB) can experience changes in their musculoskeletal systems, posture, and gait due to increased body mass index. • OW and OB children experience additional stress on their musculoskeletal systems, impacting posture, biomechanics, mobility, physical activity, and daily tasks. Excessive plantar loading is linked to foot pain in adults. What is New: • Body mass index was positively associated with initial forefoot contact, heel off, total duration of the step, and forefoot contact phase in children aged 7 to 10 years old. OW/OB children aged 5-6 exhibited less ankle dorsiflexion and smaller relaxed calcaneal stance position (RCSP) as compared to normal-weight children. • Obese children aged 5-6 showed less pronation excursion, suggesting altered frontal plane movement due to RCSP differences. Children aged 7-8 who are OW/OB spent more time in certain gait phases, particularly in the forefoot contact phase. Being OW/OB is linked to altered gait parameters such as initial forefoot, heel off, total step duration, and forefoot contact phase. Being OW/OB was associated with a longer forefoot contact phase, particularly in the right foot.

Insulina colirio en afecciones de la superficie ocular

Cuando se produce una erosión corneal y fracasa la epitelización corneal surgen los defectos epiteliales corneales persistentes, cuyo tratamiento es un desafío para el oftalmólogo. Es muy frecuente el fracaso del tratamiento convencional por lo que se mantiene el interés en la búsqueda de otros factores de crecimiento para la cicatrización epitelial tales como los colirios de insulina. La insulina es un péptido estrechamente relacionado con el factor de crecimiento similar a la insulina 1. Su mecanismo de acción no es bien comprendido, sin embargo se acepta que es capaz de inducir migración y proliferación de las células epiteliales corneales, por lo que promueve y acelera la reepitelización de defectos epiteliales persistentes refractarios a tratamiento. La ausencia de una presentación comercial de colirio de insulina, hace necesario conocer su estabilidad físicoquímica y microbiológica así como la eficacia, efectividad y seguridad del colirio de insulina a diferentes concentraciones. De ahí la motivación para realizar una revisión de la literatura existente sobre el empleo del colirio de insulina en el tratamiento del defecto epitelial corneal persistente. Se realizó la búsqueda en bases de datos electrónicas como PubMed Central, EBSCO, Clinical Trials.gov, MEDLINE OVID, EMBASE OVID con el objeto de identificar artículos relacionados con el tema.

When corneal erosion occurs and corneal epithelialization fails, persistent corneal epithelial defects arise, whose treatment is a challenge for the ophthalmologist. The failure of conventional treatment is very frequent; therefore, there is still interest in the search for other growth factors for epithelial healing, such as insulin eye drops. Insulin is a peptide closely related to insulin-like growth factor 1. Its mechanism of action is not well understood; however, it is accepted that it is capable of inducing migration and proliferation of corneal epithelial cells, thereby promoting and accelerating reepithelialization of persistent epithelial defects refractory to treatment. The absence of a commercial presentation for insulin eye drops makes it necessary to know its physicochemical and microbiological stability, as well as the efficacy, effectiveness and safety of insulin eye drops at different concentrations; hence the motivation to review the existing literature on the use of insulin eye drops in the treatment of persistent corneal epithelial defects. The search was carried out in electronic databases such as PubMed Central, EBSCO, Clinical Trials.gov, MEDLINE OVID, EMBASE OVID, with the aim of identifying relevant articles related to the topic.

Effects of a laboratory-based aerobic exercise intervention on brain volume and cardiovascular health markers: protocol for a randomised clinical trial.

INTRODUCTION: Physical activity (PA) has beneficial effects on brain health and cardiovascular disease (CVD) risk. Yet, we know little about whether PA-induced changes to physiological mediators of CVD risk influence brain health and whether benefits to brain health may also explain PA-induced improvements to CVD risk. This study combines neurobiological and peripheral physiological methods in the context of a randomised clinical trial to better understand the links between exercise, brain health and CVD risk. METHODS AND ANALYSIS: In this 12-month trial, 130 healthy individuals between the ages of 26 and 58 will be randomly assigned to either: (1) moderate-intensity aerobic PA for 150 min/week or (2) a health information control group. Cardiovascular, neuroimaging and PA measurements will occur for both groups before and after the intervention. Primary outcomes include changes in (1) brain structural areas (ie, hippocampal volume); (2) systolic blood pressure (SBP) responses to functional MRI cognitive stressor tasks and (3) heart rate variability. The main secondary outcomes include changes in (1) brain activity, resting state connectivity, cortical thickness and cortical volume; (2) daily life SBP stress reactivity; (3) negative and positive affect; (4) baroreflex sensitivity; (5) pulse wave velocity; (6) endothelial function and (7) daily life positive and negative affect. Our results are expected to have both mechanistic and public health implications regarding brain-body interactions in the context of cardiovascular health. ETHICS AND DISSEMINATION: Ethical approval has been obtained from the University of Pittsburgh Institutional Review Board (IRB ID: 19020218). This study will comply with the NIH Data Sharing Policy and Policy on the Dissemination of NIH-Funded Clinical Trial Information and the Clinical Trials Registration and Results Information Submission rule. TRIAL REGISTRATION NUMBER: NCT03841669.

Use of Artificial Intelligence in the Identification and Diagnosis of Frailty Syndrome in Older Adults: Scoping Review.

BACKGROUND: Frailty syndrome (FS) is one of the most common noncommunicable diseases, which is associated with lower physical and mental capacities in older adults. FS diagnosis is mostly focused on biological variables; however, it is likely that this diagnosis could fail owing to the high biological variability in this syndrome. Therefore, artificial intelligence (AI) could be a potential strategy to identify and diagnose this complex and multifactorial geriatric syndrome. OBJECTIVE: The objective of this scoping review was to analyze the existing scientific evidence on the use of AI for the identification and diagnosis of FS in older adults, as well as to identify which model provides enhanced accuracy, sensitivity, specificity, and area under the curve (AUC). METHODS: A search was conducted using PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines on various databases: PubMed, Web of Science, Scopus, and Google Scholar. The search strategy followed Population/Problem, Intervention, Comparison, and Outcome (PICO) criteria with the population being older adults; intervention being AI; comparison being compared or not to other diagnostic methods; and outcome being FS with reported sensitivity, specificity, accuracy, or AUC values. The results were synthesized through information extraction and are presented in tables. RESULTS: We identified 26 studies that met the inclusion criteria, 6 of which had a data set over 2000 and 3 with data sets below 100. Machine learning was the most widely used type of AI, employed in 18 studies. Moreover, of the 26 included studies, 9 used clinical data, with clinical histories being the most frequently used data type in this category. The remaining 17 studies used nonclinical data, most frequently involving activity monitoring using an inertial sensor in clinical and nonclinical contexts. Regarding the performance of each AI model, 10 studies achieved a value of precision, sensitivity, specificity, or AUC ≥90. CONCLUSIONS: The findings of this scoping review clarify the overall status of recent studies using AI to identify and diagnose FS. Moreover, the findings show that the combined use of AI using clinical data along with nonclinical information such as the kinematics of inertial sensors that monitor activities in a nonclinical context could be an appropriate tool for the identification and diagnosis of FS. Nevertheless, some possible limitations of the evidence included in the review could be small sample sizes, heterogeneity of study designs, and lack of standardization in the AI models and diagnostic criteria used across studies. Future research is needed to validate AI systems with diverse data sources for diagnosing FS. AI should be used as a decision support tool for identifying FS, with data quality and privacy addressed, and the tool should be regularly monitored for performance after being integrated in clinical practice.

Modulation of Trust in Borderline Personality Disorder by Script-Based Imaginal Exposure to Betrayal.

Interpersonal and trust-related difficulties are central features of borderline personality disorder (BPD). In this study, we applied script-driven betrayal imagery to evoke mistrustful behavior in a social reinforcement learning task. In 21 BPD and 20 healthy control (HC) participants, we compared this approach to the standard confederate paradigm used in research studies. The script-driven imagery evoked a transient increase in negative affect and also decreased trusting behavior to a similar degree in both groups. Across conditions, we also replicated previously reported between-group differences in negative affect (increased in BPD) and task behavior (more sensitive to social cues in BPD). These results support the validity of script-driven imagery as an alternative social task stimulus. This script-driven imagery approach is appealing for clinical research studies on reinforcement learning because it eliminates deception, scales easily, and evokes disorder-specific states of social difficulty.

A Novel Imaging Protocol for Investigating Arabidopsis thaliana Siliques and Seeds Using X-rays.

Understanding silique and seed morphology is essential to developmental biology. Arabidopsis thaliana is one of the best-studied plant models for understanding the genetic determinants of seed count and size. However, the small size of its seeds, and their encasement in a pod known as silique, makes investigating their numbers and morphology both time consuming and tedious. Researchers often report bulk seed weights as an indicator of average seed size, but this overlooks individual seed details. Removal of the seeds and subsequent image analysis is possible, but automated counts are often impossible due to seed pigmentation and shadowing. Traditional ways of analyzing seed count and size, without their removal from the silique, involve lengthy histological processing (24-48 h) and the use of toxic organic solvents. We developed a method that is non-invasive, requires minimal sample processing, and obtains data in a short period of time (1-2 h). This method uses a custom X-ray imaging system to visualize Arabidopsis siliques at different stages of their growth. We show that this process can be successfully used to analyze the overall topology of Arabidopsis siliques and seed size and count. This new method can be easily adapted for other plant models. Key features • No requirement for organic solvents for imaging siliques. • Easy image capture and rapid turnaround time for obtaining data. • Protocol may be easily adapted for other plant models.

Changes in stress pathways as a possible mechanism of aerobic exercise training on brain health: a scoping review of existing studies.

Physical activity (PA) in the form of aerobic exercise (AE) preserves and improves neurocognitive function across the lifespan. However, a mechanistic understanding of the pathways by which aerobic exercise impacts brain health is still lacking, particularly with respect to stress-related pathways. One mechanistic hypothesis is that AE improves neurocognitive health in part by modifying circulating levels of stress-related hormones and signaling factors associated with the hypothalamic-pituitary-adrenal (HPA) axis and autonomic nervous system (ANS), as commonly measured by the biomarkers cortisol (CORT) and salivary α-amylase (sAA). Thus, this hypothesis predicts that changes in stress biomarkers, such as CORT and sAA, are possible explanatory pathways mediating the positive effects of AE on neurocognitive health. In the present review article, we provide a summary of available studies examining the possibility that exercise-induced changes to stress biomarkers could partly account for exercise-related improvements in neurocognitive health. Our review indicates that despite the intuitive appeal of this hypothesis, there is insufficient evidence available to conclude that chronic and habitual AE affects neurocognitive health by altering stress biomarker pathways. The cross-sectional nature of the majority of reviewed studies highlights the need for well-controlled studies to adequately test this hypothesis.

Thermal resting pattern and acute skin temperature response to exercise in older adults: Role of cardiorespiratory fitness.

BACKGROUND: Infrared thermography is a growing area of interest in sports science due to the potential of skin temperature (Tsk) measurements to provide valuable information from rest to exercise. However, limited research exists on Tsk in older adults and the impact of factors such as sex and cardiorespiratory fitness (CRF) on Tsk. This study aims to investigate Tsk at rest and after acute exercise in older adults and assess whether sex or CRF influences Tsk. METHODS: Ninety-two participants (41 women, 68.48 ± 3.01 years) were examined with a thermographic camera in a conditioned room (23.02 ± 3.01 °C) at rest and after a graded protocol. The Tsk of 25 regions of interest (ROIs) were extracted and analysed. RESULTS: Men had higher overall Tsk at rest in 76% of ROIs, showing significant differences (p < 0.010) in six specific ROIs, independent of CRF. Both sexes had similar Tsk responses after graded exercise, with increases in distal parts (1.06 ± 0.50 °C), decreases in proximal parts (-0.62 ± 0.42 °C), and stable central Tsk (0.23 ± 0.59 °C). Increases in lower limb Tsk were significantly associated with CRF in men and women (ß = 0.438, p = 0.001, and ß = 0.535, p < 0.001, respectively), explaining 17% and 27% of the variance, respectively. CONCLUSIONS: This study demonstrates a sex-specific effect on resting Tsk in older adults, suggesting that sex-specific Tsk patterns should be considered when analysing Tsk in this population. Additionally, the association between increases in lower limb Tsk and CRF suggests that Tsk could be a promising predictor of CRF in older adults.

Mapping the Initial Stages of a Protective Pathway that Enhances Catalytic Turnover by a Lytic Polysaccharide Monooxygenase.

Oxygenase and peroxygenase enzymes generate intermediates at their active sites which bring about the controlled functionalization of inert C-H bonds in substrates, such as in the enzymatic conversion of methane to methanol. To be viable catalysts, however, these enzymes must also prevent oxidative damage to essential active site residues, which can occur during both coupled and uncoupled turnover. Herein, we use a combination of stopped-flow spectroscopy, targeted mutagenesis, TD-DFT calculations, high-energy resolution fluorescence detection X-ray absorption spectroscopy, and electron paramagnetic resonance spectroscopy to study two transient intermediates that together form a protective pathway built into the active sites of copper-dependent lytic polysaccharide monooxygenases (LPMOs). First, a transient high-valent species is generated at the copper histidine brace active site following treatment of the LPMO with either hydrogen peroxide or peroxyacids in the absence of substrate. This intermediate, which we propose to be a CuII-(histidyl radical), then reacts with a nearby tyrosine residue in an intersystem-crossing reaction to give a ferromagnetically coupled (S = 1) CuII-tyrosyl radical pair, thereby restoring the histidine brace active site to its resting state and allowing it to re-enter the catalytic cycle through reduction. This process gives the enzyme the capacity to minimize damage to the active site histidine residues "on the fly" to increase the total turnover number prior to enzyme deactivation, highlighting how oxidative enzymes are evolved to protect themselves from deleterious side reactions during uncoupled turnover.

Advancements in Nanoparticle Deposition Techniques for Diverse Substrates: A Review.

Nanoparticle deposition on various substrates has gained significant attention due to the potential applications of nanoparticles in various fields. This review paper comprehensively analyzes different nanoparticle deposition techniques on ceramic, polymeric, and metallic substrates. The deposition techniques covered include electron gun evaporation, physical vapor deposition, plasma enriched chemical vapor deposition (PECVD), electrochemical deposition, chemical vapor deposition, electrophoretic deposition, laser metal deposition, and atomic layer deposition (ALD), thermophoretic deposition, supercritical deposition, spin coating, and dip coating. Additionally, the sustainability aspects of these deposition techniques are discussed, along with their potential applications in anti-icing, antibacterial power, and filtration systems. Finally, the review explores the importance of deposition purities in achieving optimal nanomaterial performance. This comprehensive review aims to provide valuable insights into state-of-the-art techniques and applications in the field of nanomaterial deposition.

Toward the use of novel alternative methods in epilepsy modeling and drug discovery.

Epilepsy is a chronic brain disease and, considering the amount of people affected of all ages worldwide, one of the most common neurological disorders. Over 20 novel antiseizure medications (ASMs) have been released since 1993, yet despite substantial advancements in our understanding of the molecular mechanisms behind epileptogenesis, over one-third of patients continue to be resistant to available therapies. This is partially explained by the fact that the majority of existing medicines only address seizure suppression rather than underlying processes. Understanding the origin of this neurological illness requires conducting human neurological and genetic studies. However, the limitation of sample sizes, ethical concerns, and the requirement for appropriate controls (many patients have already had anti-epileptic medication exposure) in human clinical trials underscore the requirement for supplemental models. So far, mammalian models of epilepsy have helped to shed light on the underlying causes of the condition, but the high costs related to breeding of the animals, low throughput, and regulatory restrictions on their research limit their usefulness in drug screening. Here, we present an overview of the state of art in epilepsy modeling describing gold standard animal models used up to date and review the possible alternatives for this research field. Our focus will be mainly on ex vivo, in vitro, and in vivo larval zebrafish models contributing to the 3R in epilepsy modeling and drug screening. We provide a description of pharmacological and genetic methods currently available but also on the possibilities offered by the continued development in gene editing methodologies, especially CRISPR/Cas9-based, for high-throughput disease modeling and anti-epileptic drugs testing.

Mathematical Modeling for the Assessment of Public Policies in the Cancer Health-Care System Implemented for the Colombian Case.

The incidence of cancer has been constantly growing worldwide, placing pressure on health systems and increasing the costs associated with the treatment of cancer. In particular, low- and middle-income countries are expected to face serious challenges related to caring for the majority of the world's new cancer cases in the next 10 years. In this study, we propose a mathematical model that allows for the simulation of different strategies focused on public policies by combining spending and epidemiological indicators. In this way, strategies aimed at efficient spending management with better epidemiological indicators can be determined. For validation and calibration of the model, we use data from Colombia-which, according to the World Bank, is an upper-middle-income country. The results of the simulations using the proposed model, calibrated and validated for Colombia, indicate that the most effective strategy for reducing mortality and financial burden consists of a combination of early detection and greater efficiency of treatment in the early stages of cancer. This approach is found to present a 38% reduction in mortality rate and a 20% reduction in costs (% GDP) when compared to the baseline scenario. Hence, Colombia should prioritize comprehensive care models that focus on patient-centered care, prevention, and early detection.

Two sequence- and two structure-based ML models have learned different aspects of protein biochemistry.

Deep learning models are seeing increased use as methods to predict mutational effects or allowed mutations in proteins. The models commonly used for these purposes include large language models (LLMs) and 3D Convolutional Neural Networks (CNNs). These two model types have very different architectures and are commonly trained on different representations of proteins. LLMs make use of the transformer architecture and are trained purely on protein sequences whereas 3D CNNs are trained on voxelized representations of local protein structure. While comparable overall prediction accuracies have been reported for both types of models, it is not known to what extent these models make comparable specific predictions and/or generalize protein biochemistry in similar ways. Here, we perform a systematic comparison of two LLMs and two structure-based models (CNNs) and show that the different model types have distinct strengths and weaknesses. The overall prediction accuracies are largely uncorrelated between the sequence- and structure-based models. Overall, the two structure-based models are better at predicting buried aliphatic and hydrophobic residues whereas the two LLMs are better at predicting solvent-exposed polar and charged amino acids. Finally, we find that a combined model that takes the individual model predictions as input can leverage these individual model strengths and results in significantly improved overall prediction accuracy.