bluuebunny/crossref_metadata_2025_split huggingface dataset:
High-fat diet impacts the colon and its transcriptome in a sex-dependent manner that is modifiable by estrogens
Authors: Hases L. , Archer A. , Indukuri R. , Birgersson M. , Savva C. , Korach-André M. , Williams C. 
Published: June 2020

AbstractEpidemiological studies highlight a strong association between obesity and colorectal cancer (CRC), especially in men. Estrogen, on the other hand, is associated with protection against both the metabolic syndrome and CRC. The colon is the first organ to respond to a high-fat diet (HFD), and estrogen receptor beta (ERβ) in the intestine appears to prevent CRC. How estrogen impacts the colon under HFD condition has, however, not been investigated. Estrogen can act through three different receptors (ERα, ERβ, GPER1) which all may impact metabolism. In an effort to dissect this, we fed mice a control diet or a high-fat diet (HFD) for 13 weeks and administered receptor-selective estrogenic ligands for the last three weeks. We recorded corresponding physiological impact on fat distribution, fasting glucose, colon crypt proliferation and immune cell infiltration, and the colon transcriptome response. We identify clear sex-differences at the transcriptome level, both at base line and after HFD and ligand treatments. An unexpected observation was the significant sex-differences and impact by HFD and estrogens on circadian clock gene expression, such asNpas2andArntl (Bmal1), in the colon. Both sexes also exhibited an increased infiltration of F4/80+ macrophages as a result of HFD. In males, but not females, this was accompanied by changes in colonic epithelial cell proliferation. ERα-selective PPT treatment had significant systemic effects, reducing body weight in both sexes, whereas ERβ-selective DPN treatment did not impact body weight, but reduced infiltration of F4/80+ macrophages in colon of both sexes and attenuated HFD-induced proliferation of male colon crypts. Both ERα and ERβ activation contributed to circadian clock gene regulations. We detail for the first time how HFD and estrogens modulate the colon transcriptome and physiology in a sex and ER-specific manner.
Protein structure search to support the development of protein structure prediction methods
Authors: Ayoub Ronald , Lee Yugyung 
Published: June 2020

AbstractProtein structure prediction is a long-standing unsolved problem in molecular biology that has seen renewed interest with the recent success of deep learning with AlphaFold at CASP13. While developing and evaluating protein structure prediction methods, researchers may want to identify the most similar known structures to their predicted structures. These predicted structures often have low sequence and structure similarity to known structures. We show how RUPEE, a purely geometric protein structure search, is able to identify the structures most similar to structure predictions, regardless of how they vary from known structures, something existing protein structure searches struggle with. RUPEE accomplishes this through the use of a novel linear encoding of protein structures as a sequence of residue descriptors. Using a fast Needleman-Wunsch algorithm, RUPEE is able to perform alignments on the sequences of residue descriptors for every available structure. This is followed by a series of increasingly accurate structure alignments from TM-align alignments initialized with the Needleman-Wunsch residue descriptor alignments to standard TM-align alignments of the final results. By using alignment normalization effectively at each stage, RUPEE also can execute containment searches in addition to full-length searches to identify structural motifs within proteins. We compare the results of RUPEE to mTM-align, SSM, CATHEDRAL and VAST using a benchmark derived from the protein structure predictions submitted to CASP13. RUPEE identifies better alignments on average with respect to RMSD and TM-score as well as Q-score and SSAP-score, scores specific to SSM and CATHEDRAL, respectively. Finally, we show a sample of the top-scoring alignments that RUPEE identified that none of the other protein structure searches we compared to were able to identify.The RUPEE protein structure search is available athttps://ayoubresearch.com. Code and data are available athttps://github.com/rayoub/rupee.
ZFP982 confers mouse embryonic stem cell characteristics by regulating expression of Nanog, Zfp42 and Dppa3
Authors: Dehghanian Fariba , Bovio Patrick Piero , Hojati Zohreh , Vogel Tanja 
Published: June 2020

AbstractWe here used multi-omics analyses to identify and characterize zinc finger protein 982 (Zfp982) that confers stemness characteristics by regulating expression of Nanog, Zfp42 and Dppa3 in mouse embryonic stem cells (mESC). Network-based expression analyses comparing the transcriptional profiles of mESC and differentiated cells revealed high expression of Zfp982 in stem cells. Moreover, Zfp982 showed transcriptional overlap with Yap1, the major co-activator of the Hippo pathway. Quantitative proteomics and co-immunoprecipitation revealed interaction of ZFP982 with YAP1. ZFP982 used a GCAGAGKC motif to bind to chromatin, for example near the stemness conferring genes Nanog, Zfp42 and Dppa3 as shown by ChIP-seq. Loss-of-function experiments in mESC established that expression of Zfp982 is necessary to maintain stem cell characteristics. Zfp982 expression decreased with progressive differentiation, and knockdown of Zfp982 resulted in neural differentiation of mESC. ZFP982 localized to the nucleus in mESC and translocated to the cytoplasm upon neuronal differentiation. Similarly, YAP1 localized to the cytoplasm upon differentiation, but in mESC YAP1 was present in the nucleus and cytoplasm.Graphical AbstractZFP982 is a regulator of stemness of mouse embryonic stem cells and acts as transcription factor by activating expression of stem cell genes including Nanog, Dppa3 and Zfp42.HighlightsZfp982 is a new mouse stem cell defining marker gene.Zfp982 is co-expressed with Yap1 and stem cell marker genes in mESC.ZFP982 binds to DNA and induces expression of master genes of stemness in mESC.Expression of Zfp982 gene prevents neural differentiation and maintains stem cell characteristics.ZFP982 and YAP1 interact in mESC and translocate to the cytoplasm upon neural differentiation.
Distinct growth stages shaped by an interplay of deterministic and neutral processes are indispensable for functional anammox biofilms
Authors: Niederdorfer Robert , Fragner Lisa , Yuan Ling , Hausherr Damian , Wei Jing , Magyar Paul , Joss Adriano , Ju Feng , Bürgmann Helmut 
Published: June 2020

AbstractComplex microbial biofilms orchestrating mainstream anaerobic ammonium oxidation (anammox) represent one of the most promising energy-efficient mechanisms of fixed nitrogen elimination from anthropogenic waste waters. However, little is known about the ecological processes that are driving microbial community assembly leading to functional anammox biofilms in engineered ecosystems. Here, we use fluorescence in situ hybridization and 16S rRNA sequencing combined with network modelling to elucidate the contribution of stochastic and deterministic processes during anammox biofilm development from first colonization to maturation in a carrier-based anammox reactor. We find that distinct stages of biofilm development emerge naturally in terms of structure and community composition. These stages are characterized by dynamic succession and an interplay of stochastic and deterministic processes. The staged process of biofilm establishment appears to be the prerequisite for the anticipated growth of anammox bacteria and for reaching a biofilm community structure with the desired metabolic capacities. We discuss the relevance of this improved understanding of anammox community ecology and biofilm development concerning its practical application in the start-up and configuration of anammox biofilm reactors.
Analyzing hCov Genome Sequences: Predicting Virulence and Mutation
Authors: Sawmya Shashata , Saha Arpita , Tasnim Sadia , Toufikuzzaman Md. , Anjum Naser , Rafid Ali Haisam Muhammad , Rahman M. Saifur , Rahman M. Sohel 
Published: June 2020

AbstractBackgroundCovid-19 pandemic, caused by the SARS-CoV-2 genome sequence of coronavirus, has affected millions of people all over the world and taken thousands of lives. It is of utmost importance that the character of this deadly virus be studied and its nature be analyzed.MethodsWe present here an analysis pipeline comprising a classification exercise to identify the virulence of the genome sequences and extraction of important features from its genetic material that are used subsequently to predict mutation at those interesting sites using deep learning techniques.ResultsWe have classified the SARS-CoV-2 genome sequences with high accuracy and predicted the mutations in the sites of Interest.ConclusionsIn a nutshell, we have prepared an analysis pipeline for hCov genome sequences leveraging the power of machine intelligence and uncovered what remained apparently shrouded by raw data.
Schizosaccharomyces pombeKAT5 contributes to resection and repair of a DNA double strand break
Authors: Li Tingting , Petreaca Ruben C. , Forsburg Susan L. 
Published: June 2020

AbstractChromatin remodeling is essential for effective repair of a DNA double strand break. KAT5 (S. pombeMst1, human TIP60) is a MYST family histone acetyltransferase conserved from yeast to humans that coordinates various DNA damage response activities at a DNA double strand break (DSB), including histone remodeling and activation of the DNA damage checkpoint. InS. pombe, mutations inmst1+causes sensitivity to DNA damaging drugs. Here we show that Mst1 is recruited to DSBs. Mutation ofmst1+disrupts recruitment of repair proteins and delays resection. These defects are partially rescued by deletion ofpku70, which has been previously shown to antagonize repair by homologous recombination. These phenotypes ofmst1are similar topht1-4KR, a non-acetylatable form of histone variant H2A.Z, which has been proposed to affect resection. Our data suggest that Mst1 functions to direct repair of DSBs towards homologous recombination pathways by modulating resection at the double strand break.
An expanding bacterial colony forms a depletion zone with growing droplets
Authors: Ma H. , Bell J. , Tang J.X. 
Published: June 2020

AbstractMany species of bacteria have developed means to spread on solid surfaces. This study focuses on the expansion ofPseudomonas aeruginosaon an agar gel surface. We report the occurrence and spread of a depletion zone, where the layer of bacteria on the agar becoming thinner. The depletion zone occurs within an expanded colony under conditions of minimal water evaporation. It is colocalized with a higher concentration of rhamnolipids, the biosurfactants that are produced by the bacteria and accumulate in the older region of the colony. With continued growth in bacterial population, dense droplets occur and coalesce in the depletion zone, displaying remarkable fluid dynamic behavior. Whereas expansion of a central depletion zone requires activities of live bacteria, new zones can be seeded by adding rhamnolipids. These depletion zones due to the added surfactants expand quickly, even on plates covered by bacteria that have been killed by ultraviolet light. We propose a model to account for the observed properties, taking into consideration bacterial growth and secretion, osmotic swelling, fluid volume expansion, cell-cell interaction, and interfacial fluid dynamics involving Marangoni flow.SignificanceBacterial growth and pattern formation have strong bearing on their biological functions, such as their spread and accumulation, biofilm growth & its effects on infection and antibiotic resistance. The bacterial species of this study,Pseudomonas aeruginosa, is a human pathogen responsible for frequent infections in wounds, airways, and urinary tract, particularly when involving the use of catheters. The findings of this study and the mechanisms we propose offer new insights on the important behaviors of bacterial collective motility, pattern dynamics, and biofilm growth.
Predicting antibiotic resistance in hospitalized patients by applying machine learning to electronic medical records
Authors: Lewin-Epstein Ohad , Baruch Shoham , Hadany Lilach , Stein Gideon Y , Obolski Uri 
Published: June 2020

AbstractBackgroundComputerized decision support systems are becoming increasingly prevalent with advances in data collection and machine learning algorithms. However, they are scarcely used for empiric antibiotic therapy. Here we accurately predict the antibiotic resistance profiles of bacterial infections of hospitalized patients using machine learning algorithms applied to patients’ electronic medical records.MethodsThe data included antibiotic resistance results of bacterial cultures from hospitalized patients, alongside their electronic medical records. Five antibiotics were examined: Ceftazidime (n=2942), Gentamicin (n=4360), Imipenem (n=2235), Ofloxacin (n=3117) and Sulfamethoxazole-Trimethoprim (n=3544). We applied lasso logistic regression, neural networks, gradient boosted trees, and an ensemble combining all three algorithms, to predict antibiotic resistance. Variable influence was gauged by permutation tests and Shapely Additive Explanations analysis.ResultsThe ensemble model outperformed the separate models and produced accurate predictions on a test set data. When no knowledge regarding the infecting bacterial species was assumed, the ensemble model yielded area under the receiver-operating-characteristic (auROC) scores of 0.73-0.79, for different antibiotics. Including information regarding the bacterial species improved the auROCs to 0.8-0.88. The effects of different variables on the predictions were assessed and found consistent with previously identified risk factors for antibiotic resistance.ConclusionsOur study demonstrates the potential of machine learning models to accurately predict antibiotic resistance of bacterial infections of hospitalized patients. Moreover, we show that rapid information regarding the infecting bacterial species can improve predictions substantially. The implementation of such systems should be seriously considered by clinicians to aid correct empiric therapy and to potentially reduce antibiotic misuse.40-word summaryMachine learning models were applied to large and diverse datasets of medical records of hospitalized patients, to predict antibiotic resistance profiles of bacterial infections. The models achieved high accuracy predictions and interpretable results regarding the drivers of antibiotic resistance.
Long-term Trend in Infant Mortality in India: A Joinpoint Regression Analysis for 1981-2018
Authors: Chaurasia Aalok Ranjan 
Published: June 2020

AbstractInfant mortality rate (IMR) in India remains high by international standards. India accounts for largest number of global infant deaths. This study analyses the trend in IMR in India over almost four decades beginning 1981 through 2018. The analysis is based on the official estimates of IMR available through sample registration system. Long-term trend in IMR is analysed by using joinpoint regression analysis which reveals that the trend in IMR in India changed four times during the period 1981-2018 and the trend has been different for different states of the country. The annual proportionate decrease in IMR was the most rapid during 1985-92 in the country and in most of its states but slowed down considerably during the period 1992-99. The significant deceleration in the decrease in IMR during 1992-99 appears to be the result of the policy shift in the delivery of maternal and child health services. Had the decrease in IMR not decelerated during 1992-99, the IMR in India would have been decreased to less than 20 by 2018.
Exposure to cough aerosols and development of pulmonary COVID-19
Authors: Driessche Koen Vanden , Nestele Jeremy , Grouwels Jeroen , Duval Els LIM 
Published: June 2020

AbstractHalf a year after the emergence of COVID-19, research is still going on to gain insight in the importance of different SARS-CoV-2 transmission routes and their impact on the clinical picture of COVID-19. Our findings suggest that coughing is not as important for transmission as initially anticipated and we discuss the potentially important role for loud conversation as a driver for transmission.DisclosureNone of the authors have any financial associations or other possible conflicts of interest to declare.
Regional Difference in Seroprevalence of SARS-CoV-2 in Tokyo: Results from the community point-of-care antibody testing
Authors: Takita Morihito , Matsumura Tomoko , Yamamoto Kana , Yamashita Erika , Hosoda Kazutaka , Hamaki Tamae , Kusumi Eiji 
Published: June 2020

AbstractThe serosurvey is an alternative way to know the magnitude of the population infected by coronavirus disease 2019 (COVID-19) since the expansion of capacity of the polymerase chain reaction (PCR) to detect the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was delayed. We herein report seroprevalence of COVID-19 accessed in the two community clinics in Tokyo. The point-of-care immunodiagnostic test was implemented to detect the SARS-CoV-2 specific IgG antibody in the peripheral capillary blood. The overall positive percentage of SARS-CoV-2 IgG antibody is 3.83% (95% confidence interval: 2.76-5.16) for the entire cohort (n =1,071). The central Tokyo of 23 special wards exhibited a significantly higher prevalence compared to the other area of Tokyo (p =0.02, 4.68% [95%CI: 3.08-6.79] versus 1.83 [0.68-3.95] in central and suburban Tokyo, respectively). The seroprevalence of the cohort surveyed in this study is low for herd immunity, which suggests the need for robust disease control and prevention. A community-based approach, rather than state or prefectural levels, is of importance to figure out profiles of the SARS-COV-2 outbreak.
Serum RNA profiling in the 10-year period prior to diagnosis of testicular germ cell tumour
Authors: Burton Joshua , Umu Sinan U. , Langseth Hilde , Grotmol Tom , Grimsrud Tom K. , Haugen Trine B. , Rounge Trine B. 
Published: June 2020

AbstractAlthough testicular germ cell tumour (TGCT) overall is highly curable, patients may experience late effects after treatment. An increased understanding of the mechanisms behind the development of TGCT may pave the way for better outcome for patients. To elucidate molecular changes prior to TGCT diagnosis we sequenced small RNAs in serum from 69 patients who were later diagnosed with TGCT and 111 matched controls. The deep RNA profiles, with on average 18 million sequences per sample, comprised of nine classes of RNA, including microRNA. We found that circulating RNA signals differed significantly between cases and controls regardless of time to diagnosis. Different levels of TSIX related to X-chromosome inactivation and TEX101 involved in spermatozoa production are among the interesting findings. The RNA signals differed between seminoma and nonseminoma TGCT subtypes, with seminoma cases showing lower levels of RNAs and nonseminoma cases showing higher levels of RNAs, compared with controls. The differentially expressed RNAs were typically associated with cancer related pathways. Our results indicate that circulating RNA profiles change during TGCT development according to histology and may be useful for early detection of this tumour type.
A historical comparative analysis of the community transformation of Tin Hau temples in Sai Kung and Shaukiwan
Authors: Hung Chung Fun Steven 
Published: June 2020

PurposeThis article investigates social history in Hong Kong and compares their community transformation with two Tin Hau temples in Hong Kong, namely the Sai Kung Tin Hau and Hip Tin Temple and Shaukiwan Tin Hau Old Temple.Design/methodology/approachThe paper is conducts a historical comparison to evaluate the vitality of traditional regions in Hong Kong with particular attention to the extent and intensity of its religious practice.FindingsThe paper fills a gap in the literature by comprehensively investigating Chinese temple related societies and communities. Most previous studies of Chinese temples and their rituals have treated them in isolation from their political contexts, emphasizing topics such as iconography over details of temple communities and their relationships with other elements of the social structure.Originality/valueThe research works from the point of view how the religious situation reflects important social characteristics and transformation of Shaukiwan and Sai Kung which were contemporary urban communities.
Residential satisfaction among low-income single-mother households: the case of residential welfare facilities in South Korea
Authors: Cho Minjung 
Published: June 2020

PurposeThis paper examines residential satisfaction in welfare housing facilities exclusively built for low-income single-mother households in South Korea. The main objective is to identify predictors from among various domains such as sociodemographic and psychological characteristics of residents, as well as objective and subjective characteristics of their residential environment.Design/methodology/approachA mixed-method field study evaluates data obtained via structured questionnaires administered to 233 low-income single mothers in 23 residential welfare facilities across South Korea, supplemented by facility observations and interviews with housing staff from 16 facilities.FindingsResidential satisfaction was found to be a multidimensional construct predicted by a number of variables, with psychological characteristics being dominant. Significant predictors were also identified among physical and sociospatial environmental characteristics, such as plan type, management and service and personal space.Practical implicationsThe results of this study highlight the significance of the human aspects of management and the sociospatial quality of housing unit spaces to provide a sense of protection and privacy for the residents, which emphasizes the importance of management, design and policy improvements to increase satisfaction in welfare facility residents.Originality/valueCurrently, data for special housing conditions of female-headed households in unstable housing affordability are relatively few and outdated. A critical examination of the physical and sociospatial quality of short-term subsidized public housing for low-income single-mother households in South Korea expands the current knowledge in this field to various sociodemographic and cultural contexts.