Computational Method for Estimating DNA Copy Numbers in Normal Samples, Cancer Cell Lines, and Solid Tumors Using Array Comparative Genomic Hybridization

Genomic copy number variations are a typical feature of cancer. These variations may influence cancer outcomes as well as effectiveness of treatment. There are many computational methods developed to detect regions with deletions and amplifications without estimating actual copy numbers (CN) in these regions. We have developed a computational method capable of detecting regions with deletions and amplifications as well as estimating actual copy numbers in these regions. The method is based on determining how signal intensity from different probes is related to CN, taking into account changes in the total genome size, and incorporating into analysis contamination of the solid tumors with benign tissue. Hidden Markov Model is used to obtain the most likely CN solution. The method has been implemented for Affymetrix 500K GeneChip arrays and Agilent 244K oligonucleotide arrays. The results of CN analysis for normal cell lines, cancer cell lines, and tumor samples are presented. The method is capable of detecting copy number alterations in tumor samples with up to 80% contamination with benign tissue. Analysis of 178 cancer cell lines reveals multiple regions of common homozygous deletions and strong amplifications encompassing known tumor suppressor genes and oncogenes as well as novel cancer related genes

Inflammatory ER stress responses dictate the immunopathogenic progression of systemic candidiasis

Recognition of pathogen-associated molecular patterns can trigger the inositol-requiring enzyme 1α (IRE1α) arm of the endoplasmic reticulum (ER) stress response in innate immune cells. This process maintains ER homeostasis and also coordinates diverse immunomodulatory programs during bacterial and viral infections. However, the role of innate IRE1α signaling in response to fungal pathogens remains elusive. Here, we report that systemic infection with the human opportunistic fungal pathogen Candida albicans induced proinflammatory IRE1α hyperactivation in myeloid cells that led to fatal kidney immunopathology. Mechanistically, simultaneous activation of the TLR/IL-1R adaptor protein MyD88 and the C-type lectin receptor dectin-1 by C. albicans induced NADPH oxidase-driven generation of ROS, which caused ER stress and IRE1a-dependent overexpression of key inflammatory mediators such as IL-1Β, IL-6, chemokine (C-C motif) ligand 5 (CCL5), prostaglandin E2 (PGE), and TNF-α. Selective ablation of IRE1a in leukocytes, or treatment with an IRE1a pharmacological inhibitor, mitigated kidney inflammation and prolonged the survival of mice with systemic C. albicans infection. Therefore, controlling IRE1α hyperactivation may be useful for impeding the immunopathogenic progression of disseminated candidiasis.This work was supported by NIH T32 5T32AI134632-02 and F31CA257631 training grants (to AE); the Cancer Research Institute–Irvington Institute Postdoctoral Fellowship Award (to CSC and CS); NIH/NCI Cancer Center Support Grant P30 CA008748 (to SFS); and NIH R01 NS114653 and R21 CA248106 (to EARS). This work was also supported by a Junta de Castilla y León/Fondo Social Europeo Fellowship (to JJF); the CSIC’s Global Health Platform (PTI Salud Global, to MSC); Plan Nacional de Salud y Farmacia Grant PID2020-113751RB-I00, funded by MCIN/AEI/ 10.13039/501100011033 (to MSC); Junta de Castilla y León/Fondo Social Europeo Grant VA175P20 (to MSC); NIH grant R01 DK121977 and the Burroughs Wellcome Fund Investigator in the Pathogenesis of Infectious Diseases Award (to IDI); NIH R37 093808, NIH R01 139632, NIH R21 142639, and the Burroughs Wellcome Fund Investigator in the Pathogenesis of Infectious Diseases (to TMH); NIH R01 NS114653, NIH R01 CA271619, NIH R21 CA248106, US Department of Defense OC150431, OC200166, and OC200224, the Mark Foundation for Cancer Research ASPIRE Award, and The Pershing Square Sohn Foundation (to JRCR)

The Anglo-Saxon migration and the formation of the early English gene pool.

The history of the British Isles and Ireland is characterized by multiple periods of major cultural change, including the influential transformation after the end of Roman rule, which precipitated shifts in language, settlement patterns and material culture1. The extent to which migration from continental Europe mediated these transitions is a matter of long-standing debate2-4. Here we study genome-wide ancient DNA from 460 medieval northwestern Europeans-including 278 individuals from England-alongside archaeological data, to infer contemporary population dynamics. We identify a substantial increase of continental northern European ancestry in early medieval England, which is closely related to the early medieval and present-day inhabitants of Germany and Denmark, implying large-scale substantial migration across the North Sea into Britain during the Early Middle Ages. As a result, the individuals who we analysed from eastern England derived up to 76% of their ancestry from the continental North Sea zone, albeit with substantial regional variation and heterogeneity within sites. We show that women with immigrant ancestry were more often furnished with grave goods than women with local ancestry, whereas men with weapons were as likely not to be of immigrant ancestry. A comparison with present-day Britain indicates that subsequent demographic events reduced the fraction of continental northern European ancestry while introducing further ancestry components into the English gene pool, including substantial southwestern European ancestry most closely related to that seen in Iron Age France5,6

Author Correction: The Anglo-Saxon migration and the formation of the early English gene pool.

See original record

The Anglo-Saxon migration and the formation of the early English gene pool

The history of the British Isles and Ireland is characterized by multiple periods of major cultural change, including the influential transformation after the end of Roman rule, which precipitated shifts in language, settlement patterns and material culture1. The extent to which migration from continental Europe mediated these transitions is a matter of long-standing debate2,3,4. Here we study genome-wide ancient DNA from 460 medieval northwestern Europeans—including 278 individuals from England—alongside archaeological data, to infer contemporary population dynamics. We identify a substantial increase of continental northern European ancestry in early medieval England, which is closely related to the early medieval and present-day inhabitants of Germany and Denmark, implying large-scale substantial migration across the North Sea into Britain during the Early Middle Ages. As a result, the individuals who we analysed from eastern England derived up to 76% of their ancestry from the continental North Sea zone, albeit with substantial regional variation and heterogeneity within sites. We show that women with immigrant ancestry were more often furnished with grave goods than women with local ancestry, whereas men with weapons were as likely not to be of immigrant ancestry. A comparison with present-day Britain indicates that subsequent demographic events reduced the fraction of continental northern European ancestry while introducing further ancestry components into the English gene pool, including substantial southwestern European ancestry most closely related to that seen in Iron Age France5,6

The Gulf of Mexico in trouble: Big data solutions to climate change science

The latest technological advancements in the development and production of sensors have led to their increased usage in marine science, thus expanding data volume and rates within the field. The extensive data collection efforts to monitor and maintain the health of marine environments supports the efforts in data driven learning, which can help policy makers in making effective decisions. Machine learning techniques show a lot of promise for improving the quality and scope of marine research by detecting implicit patterns and hidden trends, especially in big datasets that are difficult to analyze with traditional methods. Machine learning is extensively used on marine science data collected in various regions, but it has not been applied in a significant way to data generated in the Gulf of Mexico (GOM). Machine learning methods using ocean science data are showing encouraging results and thus are drawing interest from data science researchers and marine scientists to further the research. The purpose of this paper is to review the existing approaches in studying GOM data, the state of the art in machine learning techniques as applied to the GOM, and propose solutions to GOM data problems. We review several issues faced by marine environments in GOM in addition to climate change and its effects. We also present machine learning techniques and methods used elsewhere to address similar problems and propose applications to problems in the GOM. We find that Harmful Algal Blooms (HABs), hypoxia, and sea-level rises have not received as much attention as other climate change problems and within the machine learning literature, the impacts on estuaries and coastal systems, as well as oyster mortality (also major problems for the GOM) have been understudied – we identify those as important areas for improvement. We anticipate this manuscript will act as a baseline for data science researchers and marine scientists to solve problems in the GOM collaboratively and/or independently

A novel method for calculating greenhouse gas emissions from the combustion of energy fuels

An analysis of the methods used in Bulgaria for estimating CO2, SO2 and dust emissions has been conducted. The first methodology, which is officially used by all energy auditors at the Agency for Sustainable Energy Development targets the energy efficiency of combustion devices installed mainly at industrial enterprises. The second methodology, used by the Ministry of Environment and Water, is more comprehensive and can be applied to thermal power plants, small combustion plants as well as industrial systems. In recent years, many projects related to energy efficiency and renewable energy projects, including hydrogen technologies, which require an assessment of reduced greenhouse gas emissions, have been implemented as a priority. The use of reliable and accurate methods is essential in the assessment of greenhouse emissions. A novel methodology, based on stoichiometric equations of the combustion process for solid, liquid and gaseous fuels has been proposed and comprised. This novel methodology is characterized by higher precision compared to the methods currently in place and this is achieved through calculating emissions from the combustion of energy fuels accounting for the full elemental composition of the fuel and its heating value, whereas the current commonly applied methods use only the fuel type and the carbon content. A further benefit of the proposed methodology is the ability to estimate emissions of fuels for which there is no alternative method for calculating CO2, SO2 and dust. Results of emission calculations according to the analysed methods are presented. Finally, a comparative analysis between the presented methodologies including an assessment of their accuracy and universal applicability has been made

Effect of Extracts of Bilberries (Vaccinium myrtillus L.) on Amyloglucosidase and α-Glucosidase Activity

Background:Vaccinium myrtillus L. is a species belonging to the genus Vaccinium of the family Ericaceae. Bilberries have drawn attention due to the multiple benefits for the human health, including antioxidant, anti-inflammatory, anticancer, anti-neurodegenerative, and cardioprotective effects. Recently, bilberries were shown to inhibit the activity of carbohydrate-hydrolysing enzymes that can help reduce the intensity of the metabolic syndrome and prevent type 2 diabetes

Enzymatic Hydrolysis of Water Extractable Polysaccharides from Leaves of Plantago major L.

Background:Plantago major L. leaves have been used for centuries by the traditional medicine in the treatment of infectious disorders of the respiratory, urinary and digestive tracts. Researchers have reported that hot water extracts of Plantago major possess a broad-spectrum of anticancer, antioxidant and antiviral activities, as well as activities which modulate cell-mediated immunity. Their beneficial properties may be due to the significant content of polysaccharides. The polysaccharides that have been isolated from the leaves of Plantago major L. have different structures – pectic substances, galactans, arabinogalactans, glucomannans