The effect of mobile phone electromagnetic fields on the human resting state wake EEG and event-related potential: A systematic review and meta-analysis.

The rapid growth of mobile phone usage and its use of radiofrequency electromagnetic fields (RF-EMF) have raised concerns about potential health risks. Researchers have conducted studies to examine the effects of RF-EMF on the brain using electroencephalography (EEG). We conducted a systematic quality assessment and meta-analysis of published research in this field to establish high-quality studies as references for future protocols.

Effects of mobile phone electromagnetic fields on brain waves in healthy volunteers.

The interaction between biological tissue and electromagnetic fields (EMF) is a topic of increasing interest due to the rising prevalence of background EMF in the past decades. Previous studies have attempted to measure the effects of EMF on brainwaves using EEG recordings, but are typically hampered by experimental and environmental factors. In this study, we present a framework for measuring the impact of EMF on EEG while controlling for these factors.

Design of the formalized and integrated Alzheimer's Disease Ontology and its application in retrieving textual data via text mining.

As one of the leading causes for dementia in the population, it is imperative that we discern exactly why Alzheimer's disease (AD) has a strong molecular association with beta-amyloid and tau. Although a clear understanding about etiology and pathogenesis of AD remains unsolved, scientists worldwide have dedicated significant efforts to discovering the molecular interactions linked to the pathological characteristics and potential treatments. Knowledge representations, such as domain ontologies encompassing our current understanding about AD, could greatly assist and contribute to disease research.

Impact of Short-Course Palliative Radiation Therapy on Pancreatic Cancer-Related Pain: Prospective Phase 2 Nonrandomized PAINPANC Trial.

Purpose: Clinical evidence is limited regarding palliative radiation therapy for relieving pancreatic cancer-related pain. We prospectively investigated pain response after short-course palliative radiation therapy in patients with moderate-to-severe pancreatic cancer-related pain.

Methods And Materials: In this prospective phase 2 single center nonrandomized trial, 30 patients with moderate-to-severe pain (5-10, on a 0-10 scale) of pancreatic cancer refractory to pain medication, were treated with a short-course palliative radiation therapy; 24 Gy in 3 weekly fractions (2015-2018).

Automated pose estimation reveals walking characteristics associated with lameness in broilers.

Walking ability of broilers can be improved by selective breeding, but large-scale phenotypic records are required. Currently, gait of individual broilers is scored by trained experts, however, precision phenotyping tools could offer a more objective and high-throughput alternative. We studied whether specific walking characteristics determined through pose estimation are linked to gait in broilers.

The Epilepsy Ontology: a community-based ontology tailored for semantic interoperability and text mining.

Motivation: Epilepsy is a multifaceted complex disorder that requires a precise understanding of the classification, diagnosis, treatment and disease mechanism governing it. Although scattered resources are available on epilepsy, comprehensive and structured knowledge is missing. In contemplation to promote multidisciplinary knowledge exchange and facilitate advancement in clinical management, especially in pre-clinical research, a disease-specific ontology is necessary.

Critical assessment of transformer-based AI models for German clinical notes.

Objective: Healthcare data such as clinical notes are primarily recorded in an unstructured manner. If adequately translated into structured data, they can be utilized for health economics and set the groundwork for better individualized patient care. To structure clinical notes, deep-learning methods, particularly transformer-based models like , have recently received much attention.

Common data model for COVID-19 datasets.

Motivation: A global medical crisis like the coronavirus disease 2019 (COVID-19) pandemic requires interdisciplinary and highly collaborative research from all over the world. One of the key challenges for collaborative research is a lack of interoperability among various heterogeneous data sources. Interoperability, standardization and mapping of datasets are necessary for data analysis and applications in advanced algorithms such as developing personalized risk prediction modeling.

ASAS-NANP Symposium: Mathematical Modeling in Animal Nutrition: Opportunities and challenges of confined and extensive precision livestock production.

Modern animal scientists, industry, and managers have never faced a more complex world. Precision livestock technologies have altered management in confined operations to meet production, environmental, and consumer goals. Applications of precision technologies have been limited in extensive systems such as rangelands due to lack of infrastructure, electrical power, communication, and durability.

A hybrid approach unveils drug repurposing candidates targeting an Alzheimer pathophysiology mechanism.

The high number of failed pre-clinical and clinical studies for compounds targeting Alzheimer disease (AD) has demonstrated that there is a need to reassess existing strategies. Here, we pursue a holistic, mechanism-centric drug repurposing approach combining computational analytics and experimental screening data. Based on this integrative workflow, we identified 77 druggable modifiers of tau phosphorylation (pTau).

ASAS-NANP symposium: mathematical modeling in animal nutrition: limitations and potential next steps for modeling and modelers in the animal sciences.

The field of animal science, and especially animal nutrition, relies heavily on modeling to accomplish its day-to-day objectives. New data streams ("big data") and the exponential increase in computing power have allowed the appearance of "new" modeling methodologies, under the umbrella of artificial intelligence (AI). However, many of these modeling methodologies have been around for decades.

Benchmarking table recognition performance on biomedical literature on neurological disorders.

Motivation: Table recognition systems are widely used to extract and structure quantitative information from the vast amount of documents that are increasingly available from different open sources. While many systems already perform well on tables with a simple layout, tables in the biomedical domain are often much more complex. Benchmark and training data for such tables are however very limited.

A method for the rational selection of drug repurposing candidates from multimodal knowledge harmonization.

The SARS-CoV-2 pandemic has challenged researchers at a global scale. The scientific community's massive response has resulted in a flood of experiments, analyses, hypotheses, and publications, especially in the field of drug repurposing. However, many of the proposed therapeutic compounds obtained from SARS-CoV-2 specific assays are not in agreement and thus demonstrate the need for a singular source of COVID-19 related information from which a rational selection of drug repurposing candidates can be made.

Discovery of a Novel Series of Potent and Selective Alkynylthiazole-Derived PI3Kγ Inhibitors.

Phosphoinositide 3-kinases (PI3Ks) are a family of enzymes that control a wide variety of cellular functions such as cell growth, proliferation, differentiation, motility, survival, and intracellular trafficking. PI3Kγ plays a critical role in mediating leukocyte chemotaxis as well as mast cell degranulation, making it a potentially interesting target for autoimmune and inflammatory diseases. We previously disclosed a novel series of PI3Kγ inhibitors derived from a benzothiazole core.

The COVID-19 Ontology.

Motivation: The COVID-19 pandemic has prompted an impressive, worldwide response by the academic community. In order to support text mining approaches as well as data description, linking and harmonization in the context of COVID-19, we have developed an ontology representing major novel coronavirus (SARS-CoV-2) entities. The ontology has a strong scope on chemical entities suited for drug repurposing, as this is a major target of ongoing COVID-19 therapeutic development.

The effect of hydroxychloride trace minerals on the growth performance and carcass quality of grower/finisher pigs: a meta-analysis.

The current study compared the effect of hydroxychloride trace minerals (HTM) with the effect of inorganic trace minerals (ITM) on growth performance and carcass quality in grower-finisher pigs. The results of 6 studies conducted throughout Europe were combined into one meta-analysis. All included studies were performed using pigs from about 19 kg of body weight until slaughter.

Technical note: concentrations of soluble, insoluble, and total dietary fiber in feed ingredients determined using Method AOAC 991.43 are not different from values determined using Method AOAC 2011.43 with the AnkomTDF Dietary Fiber Analyzer.

The primary objective of this experiment was to test the hypothesis that concentrations of soluble (SDF), insoluble (IDF), and total dietary fiber (TDF) in feed ingredients used in diets for pigs and poultry analyzed using Method AOAC 2011.25 are greater than values determined using Method AOAC 991.43.

Intravenous calcium infusion in a calving protocol disrupts calcium homeostasis compared with an oral calcium supplement.

Hypocalcemia is a common postpartum condition in dairy cows, which negatively affects health and production. Intravenous Ca infusions are commonly included in calving protocols to prevent or mitigate the effect of hypocalcemia in multiparous cows. Thus, we sought to contrast the effect of intravenous Ca infusion against voluntary oral Ca intake on Ca metabolism.

ROCK inhibitors 3: Design, synthesis and structure-activity relationships of 7-azaindole-based Rho kinase (ROCK) inhibitors.

Rho kinase (ROCK) inhibitors are potential therapeutic agents for the treatment of a variety of disorders including hypertension, glaucoma and erectile dysfunction. Here we disclose a series of potent and selective ROCK inhibitors based on a substituted 7-azaindole scaffold. Substitution of the 3-position of 7-azaindole led to compounds such as 37, which possess excellent ROCK inhibitory potency and high selectivity against the closely related kinase PKA.

Soft document clustering using a novel graph covering approach.

Background: In text mining, document clustering describes the efforts to assign unstructured documents to clusters, which in turn usually refer to topics. Clustering is widely used in science for data retrieval and organisation.

Results: In this paper we present and discuss a novel graph-theoretical approach for document clustering and its application on a real-world data set.

ROCK inhibitors 2. Improving potency, selectivity and solubility through the application of rationally designed solubilizing groups.

Solubilizing groups have been frequently appended to kinase inhibitor drug molecules when solubility is insufficient for pharmaceutical development. Such groups are usually located at substitution sites that have minimal impact on target activity. In this report we describe the incorporation of solubilizing groups in a class of Rho kinase (ROCK) inhibitors that not only confer improved solubility, but also enhance target potency and selectivity against a closely related kinase, PKA.

Design and Synthesis of a Novel Series of Orally Bioavailable, CNS-Penetrant, Isoform Selective Phosphoinositide 3-Kinase γ (PI3Kγ) Inhibitors with Potential for the Treatment of Multiple Sclerosis (MS).

The lipid kinase phosphoinositide 3-kinase γ (PI3Kγ) has attracted attention as a potential target to treat a variety of autoimmune disorders, including multiple sclerosis, due to its role in immune modulation and microglial activation. By minimizing the number of hydrogen bond donors while targeting a previously uncovered selectivity pocket adjacent to the ATP binding site of PI3Kγ, we discovered a series of azaisoindolinones as selective, brain penetrant inhibitors of PI3Kγ. This ultimately led to the discovery of 16, an orally bioavailable compound that showed efficacy in murine experimental autoimmune encephalomyelitis (EAE), a preclinical model of multiple sclerosis.