Identification of novel therapeutics for complex diseases from genome-wide association data

Background: Human genome sequencing has enabled the association of phenotypes with genetic loci, but our ability to effectively translate this data to the clinic has not kept pace. Over the past 60 years, pharmaceutical companies have successfully demonstrated the safety and efficacy of over 1,200 novel therapeutic drugs via costly clinical studies. While this process must continue, better use can be made of the existing valuable data. In silico tools such as candidate gene prediction systems allow rapid identification of disease genes by identifying the most probable candidate genes linked to genetic markers of the disease or phenotype under investigation. Integration of drug-target data with candidate gene prediction systems can identify novel phenotypes which may benefit from current therapeutics. Such a drug repositioning tool can save valuable time and money spent on preclinical studies and phase I clinical trials. Methods. We previously used Gentrepid (http://www.gentrepid.org) as a platform to predict 1,497 candidate genes for the seven complex diseases considered in the Wellcome Trust Case-Control Consortium genome-wide association study; namely Type 2 Diabetes, Bipolar Disorder, Crohn's Disease, Hypertension, Type 1 Diabetes, Coronary Artery Disease and Rheumatoid Arthritis. Here, we adopted a simple approach to integrate drug data from three publicly available drug databases: the Therapeutic Target Database, the Pharmacogenomics Knowledgebase and DrugBank; with candidate gene predictions from Gentrepid at the systems level. Results: Using the publicly available drug databases as sources of drug-target association data, we identified a total of 428 candidate genes as novel therapeutic targets for the seven phenotypes of interest, and 2,130 drugs feasible for repositioning against the predicted novel targets. Conclusions: By integrating genetic, bioinformatic and drug data, we have demonstrated that currently available drugs may be repositioned as novel therapeutics for the seven diseases studied here, quickly taking advantage of prior work in pharmaceutics to translate ground-breaking results in genetics to clinical treatments. © 2014 Grover et al.; licensee BioMed Central Ltd

Novel therapeutics for coronary artery disease from genome-wide association study data

BACKGROUND: Coronary artery disease (CAD), one of the leading causes of death globally, is influenced by both environmental and genetic risk factors. Gene-centric genome-wide association studies (GWAS) involving cases and controls have been remarkably successful in identifying genetic loci contributing to CAD. Modern in silico platforms, such as candidate gene prediction tools, permit a systematic analysis of GWAS data to identify candidate genes for complex diseases like CAD. Subsequent integration of drug-target data from drug databases with the predicted candidate genes can potentially identify novel therapeutics suitable for repositioning towards treatment of CAD. METHODS: Previously, we were able to predict 264 candidate genes and 104 potential therapeutic targets for CAD using Gentrepid (http://www.gentrepid.org), a candidate gene prediction platform with two bioinformatic modules to reanalyze Wellcome Trust Case-Control Consortium GWAS data. In an expanded study, using five bioinformatic modules on the same data, Gentrepid predicted 647 candidate genes and successfully replicated 55% of the candidate genes identified by the more powerful CARDIoGRAMplusC4D consortium meta-analysis. Hence, Gentrepid was capable of enhancing lower quality genotype-phenotype data, using an independent knowledgebase of existing biological data. Here, we used our methodology to integrate drug data from three drug databases: the Therapeutic Target Database, PharmGKB and Drug Bank, with the 647 candidate gene predictions from Gentrepid. We utilized known CAD targets, the scientific literature, existing drug data and the CARDIoGRAMplusC4D meta-analysis study as benchmarks to validate Gentrepid predictions for CAD. RESULTS: Our analysis identified a total of 184 predicted candidate genes as novel therapeutic targets for CAD, and 981 novel therapeutics feasible for repositioning in clinical trials towards treatment of CAD. The benchmarks based on known CAD targets and the scientific literature showed that our results were significant (p < 0.05). CONCLUSIONS: We have demonstrated that available drugs may potentially be repositioned as novel therapeutics for the treatment of CAD. Drug repositioning can save valuable time and money spent on preclinical and phase I clinical studies

A comparative study on process optimization of betalain pigment extraction from Beta vulgaris subsp. vulgaris: RSM, ANN, and hybrid RSM-GA methods

Beta vulgaris subsp. vulgaris (red Swiss chard) leaf stalks offer a rich source of betalains, natural pigments with promising applications in the food industry. This study employed response surface methodology (RSM) in conjunction with a 3-level Box-Behnken design to optimize independent extraction variables, including temperature, extraction time, and solid-to-liquid ratio, for maximizing betalain extraction from red Swiss chard. Betacyanins and betaxanthins, the key natural pigments, were targeted as response variables. Statistical analysis revealed the optimal conditions for extraction: 21.14 min of extraction time, 52.98°C temperature, and a solid-to-liquid ratio of 21.61 mg/mL, resulting in the maximum extraction of betacyanins (15.53 mg/100g) and betaxanthins (9.5 mg/100g). To enhance prediction accuracy, an artificial neural network (ANN) model was employed, outperforming RSM predictions. Moreover, incorporating a genetic algorithm (GA) into the RSM regression equation predicted even higher betalain contents, with betacyanins reaching 16.53 mg/100g and betaxanthins 10.52 mg/100g. Confirmation experiments conducted under RSM-GA predicted optimum conditions demonstrated mean betacyanin and betaxanthin contents of 16.54 mg/100g and 10.49 mg/100g, respectively. The superior predictive capabilities of the ANN model and the synergistic integration of GA with RSM highlight innovative approaches for enhancing extraction efficiency. Furthermore, the characterized extract exhibit attributes such as aggregated morphology, amorphous nature, and high thermal stability

Use of varenicline for smoking cessation treatment in UK primary care: an association rule mining analysis

BACKGROUND: Varenicline is probably the most effective smoking cessation pharmacotherapy, but is less widely used than nicotine replacement therapy. We therefore set out to identify the characteristics of numerically important groups of patients who typically do, or do not, receive varenicline in the UK. METHODS: We used association rule mining to analyse data on prescribing of smoking cessation pharmacotherapy in relation to age, sex, comorbidity and other variables from 477,620 people aged 16 years and over, registered as patients throughout 2011 with one of 559 UK general practices in The Health Improvement Network (THIN) database, and recorded to be current smokers. RESULTS: 46,685 participants (9.8% of all current smokers) were prescribed any smoking cessation treatment during 2011, and 19,316 of these (4% of current smokers, 41% of those who received any therapy) were prescribed varenicline. Prescription of varenicline was most common among heavy smokers aged 31–60, and in those with a diagnosis of COPD. Varenicline was rarely used among smokers who were otherwise in good health, or were aged over 60, were lighter smokers, or had psychotic disorders or dementia. CONCLUSIONS: Varenicline is being underused in healthy smokers, or in older smokers, and in those with psychotic disorders or dementia. Since varenicline is probably the most effective available single cessation therapy, this study identifies under-treatment of substantial public health significance

Digital health and mobile health: a bibliometric analysis of the 100 most cited papers and their contributing authors

Aim: This study aimed to identify and analyze the top 100 most cited digital health and mobile health (m-health) publications. It could aid researchers in the identification of promising new research avenues, additionally supporting the establishment of international scientific collaboration between interdisciplinary research groups with demonstrated achievements in the area of interest. Methods: On 30th August, 2023, the Web of Science Core Collection (WOSCC) electronic database was queried to identify the top 100 most cited digital health papers with a comprehensive search string. From the initial search, 106 papers were identified. After screening for relevance, six papers were excluded, resulting in the final list of the top 100 papers. The basic bibliographic data was directly extracted from WOSCC using its “Analyze” and “Create Citation Report” functions. The complete records of the top 100 papers were downloaded and imported into a bibliometric software called VOSviewer (version 1.6.19) to generate an author keyword map and author collaboration map. Results: The top 100 papers on digital health received a total of 49,653 citations. Over half of them (n = 55) were published during 2013–2017. Among these 100 papers, 59 were original articles, 36 were reviews, 4 were editorial materials, and 1 was a proceeding paper. All papers were written in English. The University of London and the University of California system were the most represented affiliations. The USA and the UK were the most represented countries. The Journal of Medical Internet Research was the most represented journal. Several diseases and health conditions were identified as a focus of these works, including anxiety, depression, diabetes mellitus, cardiovascular diseases, and coronavirus disease 2019 (COVID-19). Conclusions: The findings underscore key areas of focus in the field and prominent contributors, providing a roadmap for future research in digital and m-health

Biology of the parasitic wasp Stilbum cyanurum var. splendeus Fabr. (Chrysididae: Hymenoptera)

Volume: 95Start Page: 134End Page: 13

Wdrożenie narzędzi „Lean Management” w przemyśle odzieżowym

Garment Manufacturing is one of the oldest in the world, compromising a high number of critical operations. The main issues in the garment industry are the lead time, production rate, very poor line balancing and fabric wastes. Productivity improvement is carried out by implementing the various lean tools in the industry, such as 5S, Value Stream Mapping (VSM) and line balancing in the sewing section. After the implementation of lean tools in the garment industry, the outcomes observed are a reduction in work-in-progress inventory, increases in the production process and increased line efficiency. Similarly the before and after implementation of 5S, which shows space utilisation in the sewing section, is increased. In this research, an implementation study was conducted in only one organisation. Hence the results extracted by the conduct of this implementation study are achievable and adaptable in similar organisations.Główne problemy w przemyśle odzieżowym to czas realizacji, tempo produkcji, bardzo niska równowaga linii i marnotrawstwo tkanin. Celem pracy było uzyskanie poprawy produktywności poprzez wdrożenie różnych narzędzi „Lean Management” w branży, takich jak 5S, Mapowanie Strumienia Wartości (VSM) i równoważenie linii w dziale szycia. Po wdrożeniu narzędzi „Lean Management” w przemyśle odzieżowym na podstawie uzyskanych rezultatów zaobserwowano zmniejszenie zapasów w toku prac, zwiększenie procesu produkcji i zwiększenie wydajności linii. Przedstawione w pracy wyniki dotyczą badania wdrożeniowego przeprowadzonego w jednej organizacji. W związku z tym wyniki uzyskane w ramach tego badania są możliwe do osiągnięcia i dostosowania w podobnych organizacjach

Modeling heat transfer of the electrothermal reactor for magnesium production

Thermal analysis of high temperature electrothermal reactor for magnesium production was carried out in full 3D configuration using computational fluid dynamics (CFD). As the temperature inside the reactor reaches to 1200-1500 K, it becomes difficult to understand and control the heat transfer inside the reactor as the thermocouples were embedded in the insulating layers, much away from the core. The present analysis provides a useful tool to correlate the core temperature with experimental thermocouple readings. The transient state CFD simulation is carried out for the actual pilot scale design of the reactor, considering all the modes of heat transfer-conduction, convection and radiation and actual temperature dependent physical properties of the insulating materials. The heat flux and the spatial temperature profile of the various interfaces of insulation layers were also quantified. (C) 2015 Elsevier Masson SAS. All rights reserved

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Not AvailableThe Lymantria obfuscata Walker (Lyob) multiple (M) nucleopolyhedrovirus (NPV) (LyobMNPV) has been isolated and successfully applied for the management of the Indian gypsy moth, L. obfuscata in Jammu and Kashmir (J&K), India. The present work aimed to investigate the variability of LyobMNPV isolates from six localities of J&K through molecular [amplification of the polyhedrin (polh), late expression factor - 8 (lef - 8) and late expression factor - 9 (lef - 9) genes] and biological (bioassays) characterization. To identify the position of LyobMNPV in the phylogenetic tree of baculoviruses, partial sequences of the polh, lef - 8 and lef - 9 genes were determined by using the DNA sequences within their coding regions by optimizing the polymerase chain reaction with degenerate primers. The sequence alignment revealed that LyobMNPV isolates exhibited seven, five and eleven single nucleotide polymorphic sites in the case of polh, lef - 8 and lef - 9, respectively. The phylogenetic analyses supported placing LyobMNPV with the Lymantria dispar L. MNPV (LdMNPV) isolates from different countries, and showed that it was more closely related to LdMNPV than to Lymantria xylina Swinhoe NPV and Lymantria monacha L. NPV. The contaminated diet plug bioassays using 2nd instar larvae indicated that the median lethal dose (LD50) and median survival time (ST50) of different isolates of LyobMNPV against L. obfuscata were lower than those of LdMNPV against L. dispar. LyobMNPV was more closely related to LdMNPV but its LD50 and ST50 were lower than those of LdMNPV. The study provides novel information on the position of LyobMNPV in the phylogenetic tree of baculoviruses and about biological and genetic variation of Lymantria species’ NPV isolates from different parts of the world.Not Availabl

Trends and Non-Stationarity in Groundwater Level Changes in Rapidly Developing Indian Cities

In most of the Indian cities, around half of the urban water requirement is fulfilled by groundwater. Recently, seasonal urban droughts have been frequently witnessed globally, which adds more stress to groundwater systems. Excessive pumping and increasing demands in several Indian cities impose a high risk of running out of groundwater storage, which could potentially affect millions of lives in the future. In this paper, groundwater level changes have been comprehensively assessed for seven densely populated and rapidly growing secondary cities across India. Several statistical analyses were performed to detect the trends and non-stationarity in the groundwater level (GWL). Also, the influence of rainfall and land use/land cover changes (LULC) on the GWL was explored. The results suggest that overall, the groundwater level was found to vary between &plusmn;10 cm/year in the majority of the wells. Further, the non-stationarity analysis revealed a high impact of rainfall and LULC due to climate variability and anthropogenic activities respectively on the GWL change dynamics. Statistical correlation analysis showed evidence supporting that climate variability could potentially be a major component affecting the rainfall and groundwater recharge relationship. Additionally, from the LULC analysis, a decrease in the green cover area (R = 0.93) was found to have a higher correlation with decreasing groundwater level than that of urban area growth across seven rapidly developing cities