bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring heteroaromatic rings as a replacement for the labile amide of antiplasmodial pantothenamides
Authors: Guan Jinming , Spry Christina , Tjhin Erick T. , Yang Penghui , Kittikool Tanakorn , Howieson Vanessa M. , Ling Harriet , Starrs Lora , Burgio Gaetan , Saliba Kevin J. , Auclair Karine 
Published: October 2020

ABSTRACTThePlasmodiumparasites that cause malaria are adept at developing resistance to antimalarial drugs, necessitating the search for new antiplasmodials. Although several amide analogs of pantothenate (pantothenamides) show potent antiplasmodial activity, hydrolysis by pantetheinases (or vanins) present in blood rapidly inactivates them. We report herein the facile synthesis and biological activity of a small library of pantothenamide analogs in which the labile amide group is replaced with a variety of heteroaromatic rings. Several of the new analogs display antiplasmodial activity in the nanomolar range againstP. falciparumand/orP. knowlesiin the presence of pantetheinase. A previously reported triazole and an isoxazole derivative presented here were further characterized and found to possess high selectivity indices, medium or high Caco-2 permeability, and medium or low microsomal clearancein vitro. Although we show here that the two compounds fail to suppress proliferation ofP. berghei in vivo, pharmacokinetic and contact time data presented provide a benchmark for the compound profile required to achieve antiplasmodial activity in mice and should facilitate lead optimization.
Impact of pre-existing T cell immunity to SARS-CoV-2 in uninfected individuals with COVID-19 mortality in different countries
Authors: Glinsky Gennadi V. 
Published: October 2020

AbstractSeveral recent studies identified SARS-CoV-2 reactive T cells in people without exposure to the virus. However, pathophysiological implications of these findings remain unknown. Here, the potential impact of pre-existing T cell reactivity against SARS-CoV-2 in uninfected individuals on markedly different COVID-19 mortality levels in different countries has been investigated. The inverse correlation is documented between the prevalence of pre-existing SARS-CoV-2 reactive T cells in people without exposure to the virus and COVID-19 mortality rates in different countries. In countries with similar levels of pre-existing SARS-CoV-2 cross-reactive T cells in uninfected individuals, differences in COVID-19 mortality appear linked with the extend and consistency of implementations of social measures designed to limit the transmission of SARS-CoV-2 (lockdown; physical distancing; mask wearing). Collectively, these observations support the model that the level of pre-existing SARS-CoV-2 reactive T cells is one of the important determinants of the innate herd immunity against COVID-19. Together with the consistent social measures directed to limit the virus spread, high levels of pre-existing SARS-CoV-2 reactive T cells appear significant determinants diminishing the COVID-19 mortality. Observations reported in this contribution should have significant impact on definitions of the herd immunity threshold required to effectively stop the pandemic in different countries across the globe.
Fractal and inertia moment analysis of SARS CoV-2 proliferation through replication
Authors: Raj Vimal , Sreejyothi S , Swapna M S , Sankararaman S 
Published: October 2020

AbstractThe present work proposes a surrogate method for understanding and analyzing the replication of SARS CoV-2 through fractal and inertia moment (IM) analysis of cell culture images at different stages. The fractal analysis of images of cell culture, calculated by the box-counting and power spectral density methods, reflect the stages of virus infection, leading to the replication of the virus RNA and damaging the host cell. The linear increase of IM value reveals not only the proliferation of SARS CoV-2 by replication but also damage to the host cell with time. Thus, the work shows the possibility of fractal analysis and IM measurement for understanding the dynamics of the virus infection.
The effect of face mask mandates during the COVID-19 pandemic on the rate of mask use in the United States
Authors: Maloney Michael J. 
Published: October 2020

ABSTRACTAs COVID-19 continues to spread throughout the United States, there has been a search for policies to prevent individual infections, to slow the spread of the virus in general, and to mitigate the economic impact of the pandemic. Masks have proven to be a cost-effective measure in all regards, and as such some state governments have begun to mandate their use. However, while the efficacy of masks has been demonstrated, the efficacy of public policies which mandate the use of masks has not been demonstrated. This paper compares the rates of mask use in counties as defined by state policy. It finds that state mandates are strongly correlated with higher rates of mask use, and that mandating use by all individuals in public spaces is more effective than a less comprehensive mandate for mask use by all public facing employees.
Lysophosphatidic acid and lysophosphatidylcholine levels in serum samples of patients with major depressive disorder
Authors: Bari Sumaia , Sultana Sharmin , Daria Sohel , Proma Maliha Afrin , Islam Md. Rabiul , Haque Md. Ahsanul 
Published: October 2020

ABSTRACTMajor depressive disorder (MDD) is a heterogeneous condition featured with a continuous low mood, feeling of sadness, lack of interest to perform daily activities. Many factors including genetic, physiological, biological, social, and environmental are thought to be connected with the pathophysiology of depression. Several previous studies failed to identify the favorable biomarkers for MDD. Lysophosphatidic acid (LPA) and lysophosphatidylcholine (LPC)showed important roles in the regulation of emotion among experimental animals. The current study aimed to measure the serum levels of LPA and LPC in MDD patients and healthy controls (HCs) to explore their roles and relationship with depression. This case-control study enrolled 53 MDD patients and 50 healthy controls (HCs). The patients were recruited from the department of psychiatry, Bangabandhu Sheikh Mujib Medical University whereas the controls was from different locations of Dhaka city. Both the cases and controls were strictly matched by gender, age, and body mass index. A qualified psychiatrist diagnosed patients and evaluated controls based on the diagnostic and statistical manual of mental disorders, 5th edition. The severity of depression in MDD patients was measured by using the Hamilton depression rating scale (Ham-D). Enzyme-linked immunosorbent assay kits were used to measure serum levels LPA and LPC. We found no alterations of these parameters in serum levels of MDD patients compared to HCs. A significant positive correlation was found between serum LPA and LPC levels in MDD patients. Moreover, the present study showed no significant associations between target markers and either diagnosis of depression or Ham-D scores, or management of depression. The present study suggests that LPA and LPC levels probably would not serve as potential biomarkers of MDD. Thus, further studies with large and more homogeneous populations are recommended to explore the exact relationship between targeted serum lipids and major depression.
Higher levels of serum IL-1β and TNF-α are associated with an increased probability of major depressive disorder
Authors: Das Rajesh , Zaman Emon Md. Prova , Shahriar Mohammad , Nahar Zabun , Ashraful Islam Sardar Mohammad , Bhuiyan Mohiuddin Ahmed , Islam Sheikh Nazrul , Islam Md. Rabiul 
Published: October 2020

ABSTRACTMajor depressive disorder (MDD) is a serious psychiatric disorder but there are no reliable risk assessment tools for this condition. The actual reason for affecting depression is still controversial. It is assumed that the dysregulated cytokines are produced due to the hyperactivation of the immune system in depression. We aimed to evaluate the possible alteration and the role of serum interleukin-1β (IL-1β) and tumor necrosis factor-α (TNF-α) in MDD patients. The diagnostic and statistical manual of mental disorders, 5th edition was used to diagnose patients and evaluation of healthy controls (HCs). The severity of depression was measured by the Hamilton depression rating scale (Ham-D). Serum IL-1β and TNF-α levels were quantified by enzyme-linked immunosorbent assay kits. Increased levels of serum IL-1β and TNF-α were observed in MDD patients compared to HCs. These higher levels of peripheral markers were positively correlated with the severity of depression. Moreover, females with higher Ham-D scores showed greater serum IL-1β and TNF-α levels compared to males. Good predictive values were detected for both serum IL-1β and TNF-α levels by receiver operating characteristic analysis. Therefore, the elevated levels of serum IL-1β and TNF-α might be used as risk assessment indicators for MDD.
Rationale and prognosis of repurposed drugs with risk stratification of COVID-19 patients requiring Oxygen supplementation: A systematic review and meta-analysis
Authors: Elangovan Esther Jebarani , Kumar Vanitha Shyamili , Kathiravan Adhithyan , Mallampalli Raghav , Thomas Tiju , Subramaniyam Gnanasambandam 
Published: October 2020

AbstractBackgroundThe rising number of trials on repurposed dugs in COVID-19 has led to duplication and a need for curation of available outcomes from treatments that have been followed across the world. We have conducted a systematic review and meta-analysis that focus on evaluating the clinical outcomes of repurposed interventions against COVID-19.MethodsRandom effects model was adopted to estimate overall treatment effect and heterogeneity. Meta- regression was performed to study the correlation between comorbid conditions and non- invasive or invasive ventilation requirement.ResultsTwenty-nine articles met our eligibility criteria. In subgroup analysis, Tocilizumab was highly significant with lower mortality rate (OR 27.50; 95%CI [5.39-140.24]) of severe COVID-19 patients. Hydroxychloroquine and Lopinavir-ritonavir was found to be inefficacious in severe patients (OR 0.64; 95%CI [0.47-0.86] and 1.40 [0.71-2.76]). Dexamethasone had marginal effect on overall mortality rate (OR 1.19; 95%CI [1.05-1.35]). The meta-regression shows a positive correlation between prevalence of patients on Tocilizumab in non invasive support and hypertension condition (P = 0.02), whereas a negative correlation was identified with patients having lung disease (P = 0.03).ConclusionOverall, our study confirmed that tocilizumab may probably reduce the mortality rate (<10%) of severe COVID-19 patients than other interventions. Further, reduce the risk of requiring non- invasive ventilator support in patients with comorbid condition of lung disease. Hydroxychloroquine and Lopinavir-ritonavir has no clinical benefits in severe COVID-19. A high quality evidence is required to evaluate the usage of Serpin + Favipiravir combination in severe or critical COVID-19.
Digital re-classification of equivocal dysplastic urothelial lesions using morphologic and immunohistologic analysis
Authors: Vrabie Camelia D , Gangal Marius 
Published: October 2020

AbstractA precise diagnostic of precursor dysplastic urothelial lesions is critical for patients but it can be a challenge for pathologists. Multiple immunohistologic markers (panel) improve ambiguous diagnostics but results are subjective, with a high degree of observational variability. Our research objective was to evaluate how a classification algorithm may help morphology diagnostic. Data coming from 45 unequivocal cases of flat urothelial lesions (“training set”: 20 carcinomas in situ, 8 dysplastic and 17 reactive lesions) were used as ground truth in training a random tree classification algorithm. 50 “atypia of unknown significance” diagnostics (diagnostic set) were digitally re-classified based on morphological and immunohistochemical features as possible carcinoma in situ (20), dysplastic (17) and reactive atypia cases (13). The main sorting criterium was morphologic (nuclear area). A four-markers panel was used for a precise classification (74% correctly classified, 93% accuracy, 76% precision, averaged ROC=0.828). 3 cases were “false negative”. The performance of the immunohistologic panel was evaluated based on a stain index, calculated for CD20, p53, Ki67 and observed for CD44. Within training set, the immunohistologic performance was high. In the diagnostic set both the percentage of high stain index for each marker and the percentage of cases with 2-3 strong markers were low, explaining the initial high number of equivocal cases. In conclusion, digital analysis of morphologic and immunohistologic features may bring clarification in classification of equivocal urothelial lesions. Computational pathology supports diagnostic process as it can measure features and handle data in a precise, reproducible and objective way. In our proof of concept study, a low number of cases and the (deliberate) absence of clinical data were main limitations. Validation of the method on a high number of cases, use of genomics and clinical data are essential for improving the reliability of machine learning classification
Intra-county modeling of COVID-19 infection with human mobility: assessing spatial heterogeneity with business traffic, age and race
Authors: Hou Xiao , Gao Song , Li Qin , Kang Yuhao , Chen Nan , Chen Kaiping , Rao Jinmeng , Ellenberg Jordan S. , Patz Jonathan A. 
Published: October 2020

ABSTRACTThe novel coronavirus disease (COVID-19) pandemic is a global threat presenting health, economic and social challenges that continue to escalate. Meta-population epidemic modeling studies in the susceptible-exposed-infectious-removed (SEIR) style have played important roles in informing public health and shaping policy making to mitigate the spread of COVID-19. These models typically rely on a key assumption on the homogeneity of the population. This assumption certainly cannot be expected to hold true in real situations; various geographic, socioeconomic and cultural environments affect the behaviors that drive the spread of COVID-19 in different communities. What’s more, variation of intra-county environments creates spatial heterogeneity of transmission in different sub-regions. To address this issue, we develop a new human mobility flow-augmented stochastic SEIR-style epidemic modeling framework with the ability to distinguish different regions and their corresponding behavior. This new modeling framework is then combined with data assimilation and machine learning techniques to reconstruct the historical growth trajectories of COVID-19 confirmed cases in two counties in Wisconsin. The associations between the spread of COVID-19 and human mobility, business foot-traffic, race & ethnicity, and age-group are then investigated. The results reveal that in a college town (Dane County) the most important heterogeneity is spatial, while in a large city area (Milwaukee County) ethnic heterogeneity becomes more apparent. Scenario studies further indicate a strong response of the spread rate on various reopening policies, which suggests that policymakers may need to take these heterogeneities into account very carefully when designing policies for mitigating the spread of COVID-19 and reopening.
New targets acquired: improving locus recovery from the Angiosperms353 probe set
Authors: McLay Todd G.B. , Birch Joanne L. , Gunn Bee F. , Ning Weixuan , Tate Jennifer A. , Nauheimer Lars , Joyce Elizabeth M. , Simpson Lalita , Weigner Nick , Schmidt-Lebuhn Alexander N. , Baker William J. , Forest Félix , Jackson Chris J. 
Published: October 2020

ABSTRACTUniversal target enrichment kits maximise utility across wide evolutionary breadth while minimising the number of baits required to create a cost-efficient kit. Locus assembly requires a target reference, but the taxonomic breadth of the kit means that target references files can be phylogenetically sparse. The Angiosperms353 kit has been successfully used to capture loci throughout angiosperms but includes sequence information from 6–18 taxa per locus. Consequently, reads sequenced from on-target DNA molecules may fail to map to references, resulting in fewer on-target reads for assembly, reducing locus recovery. We expanded the Angiosperms353 target file, incorporating sequences from 566 transcriptomes to produce a ‘mega353’ target file, with each gene represented by 17–373 taxa. This mega353 file is a drop-in replacement for the original Angiosperms353 file in HybPiper analyses. We provide tools to subsample the file based on user-selected taxon groups, and to incorporate other transcriptome or protein-coding gene datasets. Compared to the default Angiosperms353 file, the mega353 file increased the percentage of on-target reads by an average of 31%, increased loci recovery at 75% length by 61.9%, and increased the total length of the concatenated loci by 30%. The mega353 file and associated scripts are available at:https://github.com/chrisjackson-pellicle/NewTargets
Integrative identification by Hi-C revealed distinct advanced structural variations in Lung Adenocarcinoma tissue
Authors: Zhang Li , Song Tingting , Yao Menglin , Yang Ying , Liu Zhiqiang , Li Weimin 
Published: October 2020

AbstractAdvanced three-dimensional structure variations of chromatin in large genome fragments, such as conversion of A/B compartment, topologically associated domains (TADs) and chromatin loops are related closely to occurrence of malignant tumors. However, the structural characteristics of lung cancer still remain uncovered. In this study, we used high-throughput chromosome (HiC) confirmation capture to detect 2 non-smoking female lung adenocarcinoma (LUAD) tumor and paired normal tissues. The results indicated that significant chromatin variations were detected in tumor tissues compared with normal tissues. At compartment scale, the main conversion type of compartment is A→B in tumor tissues, which concentrated mainly on chromosome 3 (33.6%). Total of 216 tumor-specific TADs were identified in tumor tissues, which distributed mainly in chr1 (19), chr2 (15) and chr3(17). Finally we observed 41 distinct enhancer-promoter loops in tumor tissue, which associated closely to tumor-related pathways including MAPK, PI3K-AKT, Ras, Wnt and Ras1. The most important observation in this study was that we identified 5 important genes (SYT16, NCEH1, NXPE3, MB21D2, andDZIP1L), which were detected in both A→B compartment, TADs and chromatin loops. Four of these genes (NCEH1, NXPE3, MB21D2, andDZIP1L) located on q arm of chromosome 3, which also revealed the importance of chr3 in occurrence of structural variations in LUAD.
Harnessing machine learning to unravel protein degradation inEscherichia coli
Authors: Nagar Natan , Ecker Noa , Loewenthal Gil , Avram Oren , Ben-Meir Daniella , Biran Dvora , Ron Eliora , Pupko Tal 
Published: October 2020

AbstractDegradation of intracellular proteins in Gram-negative bacteria regulates various cellular processes and serves as a quality control mechanism by eliminating damaged proteins. To understand what causes the proteolytic machinery of the cell to degrade some proteins while sparing others, we employed a quantitative pulsed-SILAC (Stable Isotope Labeling with Amino acids in Cell culture) method followed by mass spectrometry analysis to determine the half-lives for the proteome of exponentially growingEscherichia coli, under standard conditions. We developed a likelihood-based statistical test to find actively degraded proteins, and identified dozens of novel proteins that are fast-degrading. Finally, we used structural, physicochemical and protein-protein interaction network descriptors to train a machine-learning classifier to discriminate fast-degrading proteins from the rest of the proteome. Our combined computational-experimental approach provides means for proteomic-based discovery of fast degrading proteins in bacteria and the elucidation of the factors determining protein half-lives and have implications for protein engineering. Moreover, as rapidly degraded proteins may play an important role in pathogenesis, our findings could identify new potential antibacterial drug targets.
The impact of the COVID-19 pandemic on families in Germany
Authors: Brandstetter Susanne , Poulain Tanja , Vogel Mandy , Meigen Christof , Melter Michael , Seelbach-Göbel Birgit , Apfelbacher Christian , Kiess Wieland , Kabesch Michael , Körner Antje ,   the KUNO Kids study group
Published: October 2020

ABSTRACTObjectiveTo assess the impact of the COVID-19 pandemic on families with young children in two population-based childhood cohorts with a low and moderate COVID-19 prevalence, respectively.MethodsA cross-sectional study using online questionnaires in families from LIFE Child (n=306, Leipzig) and KUNO Kids (n=612, Regensburg) was performed at the end of the German lock-down period. Outcomes were parent-reported impact of the COVID-19 pandemic on family life, concerns and trust in political measures.ResultsMost families were concerned about the COVID-19 pandemic and lock-down measures, with major concerns directed towards the economic situation (>70%), the health of close-ones (37%), but less towards their own health (<10%). Many concerns, seeking information and approval of federal measures were more pronounced in the more affected region. Approval of lockdown measures and concerns about economic recession were related to regional differences and not significantly dependent on educational status or being personally affected by the disease.ConclusionRegional differences in approval of lockdown measures were observed and thus, measures to specifically support families according to the regional impact of the COVID-19 pandemic are needed.