Public Health Measures and Prevention of Alcohol-Associated Liver Disease.

Hazardous alcohol consumption causes approximately 4% of deaths globally, constituting one of the leading risk factors for the burden of the disease worldwide. Alcohol has several health consequences, such as alcohol-associated liver disease, hepatocellular carcinoma, nonliver neoplasms, physical injury, cardiac disease, and psychiatric disorders. Alcohol misuse significantly affects workforce productivity, with elevated direct and indirect economic costs. Due to the high impact of alcohol consumption on the population, public health has led to the development of a range of strategies to reduce its harmful effects. Regulatory public health policies (PHP) for alcohol can exist at the global, regional, international, national, or subnational levels. Effective strategies incorporate a multilevel, multicomponent approach, targeting multiple determinants of drinking and alcohol-related harms. The World Health Organization categorizes the PHP into eight categories: national plan to fight the harmful consequences of alcohol, national license and production and selling control, taxes control and pricing policies, limiting drinking age, restrictions on alcohol access, driving-related alcohol policies, control over advertising and promotion, and government monitoring systems. These policies are supported by evidence from different populations, demonstrating that determinants of alcohol use depend on several factors such as socioeconomic level, age, sex, ethnicity, production, availability, marketing, and others. Although most policies have a significant individual effect, a higher number of PHP are associated with a lower burden of disease due to alcohol. The excessive consequences of alcohol constitute a call for action, and clinicians should advocate for developing and implementing a new PHP on alcohol consumption.

Liquid chromatography-tandem mass spectrometry method for simultaneous quantification of neurotransmitters in rat brain tissue exposed to 4'-fluoro-α-PHP.

The combination of different advanced analytical techniques makes it possible to determine the concentrations of neurotransmitters in various biological matrices, providing a complex and comprehensive study of the effects of psychoactive substances. The present study aimed to develop and validate a fast and simple analytical method for the determination of acetylcholine, serotonin, γ-aminobutyric acid, glutamate, dopamine and metabolites in rats brain tissue by liquid chromatography coupled to tandem mass spectrometry. The brain was homogenized and aliquots of the sample, dopamine-d4 , and acetone were added to a tube and then vortexed and centrifuged. The supernatant was collected and dried. The residue was reconstituted and injected. The LLOQ ranged from 0.001 to 1 µg/g; the intra-run precision ranged from 0.47 to 11.52%; the inter-run precision ranged from 0.68 to 17.54%; and the bias ranged from 89.10 to 109.60%. As proof of concept, the method was applied to animals exposed to the synthetic cathinone 4'-fuoro-α-pyrrolidinohexanophenone (300 mg/kg). In addition, the workflow proved to be simple, rapid and useful to estimate the concentration of neurotransmitters. This analytical tool can be used to support the investigation of the changes in the neurochemical profile for the characterization of the mechanism of action of psychoactive substances, as well as both neurological and psychiatric diseases.

LAITOR4HPC: A text mining pipeline based on HPC for building interaction networks.

BACKGROUND: The amount of published full-text articles has increased dramatically. Text mining tools configure an essential approach to building biological networks, updating databases and providing annotation for new pathways. PESCADOR is an online web server based on LAITOR and NLProt text mining tools, which retrieves protein-protein co-occurrences in a tabular-based format, adding a network schema. Here we present an HPC-oriented version of PESCADOR's native text mining tool, renamed to LAITOR4HPC, aiming to access an unlimited abstract amount in a short time to enrich available networks, build new ones and possibly highlight whether fields of research have been exhaustively studied. RESULTS: By taking advantage of parallel computing HPC infrastructure, the full collection of MEDLINE abstracts available until June 2017 was analyzed in a shorter period (6 days) when compared to the original online implementation (with an estimated 2 years to run the same data). Additionally, three case studies were presented to illustrate LAITOR4HPC usage possibilities. The first case study targeted soybean and was used to retrieve an overview of published co-occurrences in a single organism, retrieving 15,788 proteins in 7894 co-occurrences. In the second case study, a target gene family was searched in many organisms, by analyzing 15 species under biotic stress. Most co-occurrences regarded Arabidopsis thaliana and Zea mays. The third case study concerned the construction and enrichment of an available pathway. Choosing A. thaliana for further analysis, the defensin pathway was enriched, showing additional signaling and regulation molecules, and how they respond to each other in the modulation of this complex plant defense response. CONCLUSIONS: LAITOR4HPC can be used for an efficient text mining based construction of biological networks derived from big data sources, such as MEDLINE abstracts. Time consumption and data input limitations will depend on the available resources at the HPC facility. LAITOR4HPC enables enough flexibility for different approaches and data amounts targeted to an organism, a subject, or a specific pathway. Additionally, it can deliver comprehensive results where interactions are classified into four types, according to their reliability.

Intragenic Deletions of GNAS in Pseudohypoparathyroidism Type 1A Identify a New Region Affecting Methylation of Exon A/B.

CONTEXT: Pseudohypoparathyroidism type 1A (PHP1A) and pseudopseudohypoparathyroidism (PPHP) are caused by inactivating mutations in the exons of GNAS that encode the alpha-subunit of the stimulatory G protein (Gsα). In some cases abnormal methylation of exon A/B of GNAS, a hallmark of PHP1B, has been reported. OBJECTIVE: To identify the underlying genetic basis for PHP1A/PPHP in patients in whom molecular defects were not detected by GNAS sequencing and microarray-based analysis of copy number variations. METHODS: Whole genome sequencing (WGS) and pyrosequencing of differentially methylated regions (DMRs) of GNAS using genomic deoxyribonucleic acid from affected patients. RESULTS: We identified 2 novel heterozygous GNAS deletions: a 6.4 kb deletion that includes exon 2 of GNAS in the first proband that was associated with normal methylation (57%) of exon A/B DMR, and a 1438 bp deletion in a second PHP1A patient that encompasses the promoter region and 5' untranslated region of Gsα transcripts, which was inherited from his mother with PPHP. This deletion was associated with reduced methylation (32%) of exon A/B DMR. CONCLUSIONS: WGS can detect exonic and intronic mutations, including deletions that are too small to be identified by microarray analysis, and therefore is more sensitive than other techniques for molecular analysis of PHP1A/PPHP. One of the deletions we identified led to reduced methylation of exon A/B DMR, further refining a region needed for normal imprinting of this DMR. We propose that deletion of this region can explain why some PHP1A patients have reduced of methylation of the exon A/B DMR.

Sample Mining and Data Mining: Combined Real-Time and Retrospective Approaches for the Identification of Emerging Novel Psychoactive Substances.

Novel psychoactive substances (NPS) are synthetic drugs that pose serious public health and safety concerns. A multitude of NPS have been identified in the United States, often implicated in forensic investigations. The most common and effective manner for identifying NPS is by use of mass spectrometry and the true utility lies within nontargeted acquisition techniques. During this study, a liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QTOF-MS) assay was developed, validated, and implemented for forensic toxicology testing. A SCIEX TripleTOF™ 5600 + with SWATH® acquisition was used. Resulting data were compared against an extensive library database containing more than 800 compounds. The LC-QTOF-MS assay was applied to the reanalysis of biological sample extracts to discover emergent NPS. More than 3,000 sample extracts were analyzed, and more than 20 emerging NPS were detected for the first time. Among these were isopropyl-U-47700, 3,4-methylenedioxy-U-47700, fluorofuranylfentanyl, N-methyl norfentanyl, 2F-deschloroketamine, 3,4-methylenedioxy-alpha-PHP, eutylone, and N-ethyl hexedrone.