bluuebunny/crossref_metadata_2025 huggingface dataset:
Relationships of Alzheimer’s disease and apolipoprotein E genotypes with small RNA and protein cargo of brain tissue extracellular vesicles
Authors: Huang Yiyao , Driedonks Tom A. P. , Cheng Lesley , Turchinovich Andrey , Rajapaksha Harinda , Arab Tanina , Powell Bonita H. , Pletniková Olga , Redding Javier , Troncoso Juan C. , Vella Laura , Zheng Lei , Hill Andrew F. , Mahairaki Vasiliki , Witwer Kenneth W.
Published: December 2020

Alzheimer’s disease (AD) is a public health crisis that grows as populations age. Hallmarks of this neurodegenerative disease include aggregation of beta-amyloid peptides and hyperphosphorylated tau proteins in the brain. Variants of the APOE gene are the greatest known risk factors for sporadic AD. As emerging players in AD pathophysiology, extracellular vesicles (EVs) contain proteins, lipids, and RNAs and are involved in disposal of cellular toxins and intercellular communication. AD-related changes in the molecular composition of EVs may contribute to pathophysiology and lend insights into disease mechanisms. We recently adapted a method for separation of brain-derived EVs (bdEVs) from post-mortem tissues. Using this method, we isolated bdEVs from AD patients with different APOE genotypes and controls. bdEVs were counted, sized, and subjected to parallel small RNA sequencing, proteomic analysis. Although overall bdEV concentration was not affected by AD, we observed a shift towards smaller particles in AD. Also, numerous bdEV-associated RNAs (including miRNAs and tRNAs) and proteins were found to be correlated with AD pathology and APOE genotype. Some of the identified entities have been implicated previously in important AD-related pathways, including amyloid processing, neurodegeneration, and metabolic functions, etc. Prominently, AD hallmark Tau and Tau phosphorylated at threonine 231 (phosTau) were significantly increased in AD bdEVs, indicating the involvement of bdEVs in spread of Tau pathology. These findings provide further evidence that bdEVs and their molecular cargo modulate development and progression of AD.
Application of concise machine learning to construct accurate and interpretable EHR computable phenotypes
Authors: Cava William La , Lee Paul C , Ajmal Imran , Ding Xiruo , Solanki Priyanka , Cohen Jordana B , Moore Jason H , Herman Daniel S
Published: December 2020

Objective

Electronic health records (EHRs) can improve patient care by enabling systematic identification of patients for targeted decision support. But, this requires scalable learning of computable phenotypes. To this end, we developed the feature engineering automation tool (FEAT) and assessed it in targeting screening for the underdiagnosed, under-treated disease primary aldosteronism.

Materials and Methods

We selected 1,199 subjects receiving longitudinal care in a large health system and classified them for hypertension (N=608), hypertension with unexplained hypokalemia (N=172), and apparent treatment-resistant hypertension (N=176) by chart review. We derived 331 features from EHR encounters, diagnoses, laboratories, medications, vitals, and notes. We modified FEAT to encourage model parsimony and compared its models’ performance and interpretability to those of expert-curated heuristics and conventional machine learning.

Results

FEAT models trained to replicate expert-curated heuristics had higher area under the precision-recall curve (AUPRC) than all other models (p < 0.001) except random forests and were smaller than all other models (p < 1e-6) except decision trees. FEAT models trained to predict chart review phenotypes exhibited similar AUPRC to penalized logistic regression while being simpler than all other models (p < 1e-6). For treatment-resistant hypertension, FEAT learned a six-feature, clinically intuitive model that demonstrated a positive predictive value of 0.70 and sensitivity of 0.62 in held-out testing data.

Discussion

FEAT learns computable phenotypes that approach the performance of expert-curated heuristics and conventional machine learning without sacrificing interpretability.

Conclusion

By constructing accurate and interpretable computable phenotypes at scale, FEAT has the potential to facilitate systematic clinical decision support.
How the COVID-19 pandemic has adversely affected the economics of U.S. emergency care
Authors: Pines Jesse M. , Zocchi Mark S. , Black Bernard S. , Kornas Rebecca , Celedon Pablo , Moghtaderi Ali , Venkat Arvind ,   For the US Acute Care Solutions Research Group
Published: December 2020

Objective

We describe how the coronavirus (COVID-19) pandemic impacted emergency department (ED) economics, acuity, and staffing.

Methods

We conducted an observational study of visits during January to September 2020 compared to 2019 in 136 EDs staffed by a national emergency medicine group. We created ratios of three-week moving averages for 2020 visits, acuity, costs divided by 2019 moving averages, by age and ED size. We tabulated reductions in clinician hours and FTEs compared to early 2020 staffing.

Results

2020-2019 ED visit ratios declined in March nadiring mid-April for both adults (to 0.60) and children (to 0.30) and rose thereafter but remained below 2019 levels through September 2020. The ratio of adult RVUs/visit rose to 1.1 for adults and 1.2 for children in the early pandemic, falling to 1.04 and 1.1 through September. The ratio of direct salary expenses in freestanding (FSED) and small EDs declined less dramatically than in medium and large EDs. Clinical revenues in medium and large EDs declined more sharply and recovered slowly but plateaued well below 2019 levels. By September 2020, expenses were still higher than revenues for small EDs, similar for FSEDs, and somewhat higher for medium and large EDs. During the pandemic, physician hours fell 15% and APP hours 27% during COVID-19 translating to 174 lost physician and 193 lost APP FTEs.

Conclusion

The COVID-19 pandemic reduced ED visits and increased acuity in the first 7 months of the pandemic, leading to a contraction of the ED workforce, and threatening ED economics, more so in small and FSEDs.
Public Preferences for Social Distancing Behaviors to Mitigate the Spread of COVID-19: A Discrete Choice Experiment
Authors: Wilson Ingrid Eshun , Mody Aaloke , McKay Ginger , Hlatshwayo Mati , Bradley Cory , Thompson Vetta , Glidden Dave V , Geng Elvin H
Published: December 2020

Policies to promote social distancing can minimize COVID-19 transmission, but come with substantial social and economic costs. Quantifying relative preferences of the public for such practices can inform policy prioritization and optimize uptake. We used a discrete choice experiment (DCE) to quantify relative “utilities” (preferences) for five COVID-19 pandemic social distances strategies (e.g., closure of restaurants, restriction of large gatherings) against the hypothetical risk of acquiring COVID-19 and anticipated income loss. The survey was distributed in Missouri in May-June, 2020. We applied inverse probability sampling weights to mixed logit and latent class models to generate mean preferences and identify preference classes. Overall (n=2,428), the strongest preference was for the prohibition of large gatherings, followed by preferences to keep outdoor venues, schools, and social and lifestyle venues open, 75% of the population showing probable support for a strategy that prohibited large gatherings and closed lifestyle and social venues. Latent class analysis, however revealed four preference sub-groups in the population - “risk eliminators”, “risk balancers”, “altruistic” and “risk takers”, with men twice as likely as women to belong to the risk-taking group. In this setting, public health policies which as a first phase prohibit large gatherings, as well as close social and lifestyle venues may be acceptable and adhered to by the public. In addition, policy messages that address preference heterogeneity, for example by targeting public health messages at men, could improve adherence to social distancing measures and prevent further COVID-19 transmission prior to vaccine distribution and in the event of future pandemics.

Significance Statement

Preferences drive behavior – DCE’s are a novel tool in public health that allow examination of preferences for a product, service or policy, identifying how the public prioritizes personal risks and cost in relation to health behaviors. Using this method to establish preferences for COVID-19 mitigation strategies, our results suggest that, firstly, a tiered approach to non-essential business closures where large gatherings are prohibited and social and lifestyle venues are closed as a first phase, would be well aligned with population preferences and may be supported by the public, while school and outdoor venue closures may require more consideration prior to a second phase of restrictions. And secondly, that important distinct preference phenotypes - that are not captured by sociodemographic (e.g., age, sex, race) characteristics - exist, and therefore that messaging should be target at such subgroups to enhance adherence to prevention efforts.
Identification of acute exacerbations of chronic obstructive pulmonary disease using simple patient-reported symptoms and cough feature analysis: A diagnostic agreement study
Authors: Claxton Scott , Porter Paul , Brisbane Joanna , Bear Natasha , Wood Javan , Peltonen Vesa , Della Phillip , Smith Claire , Abeyratne Udantha
Published: December 2020

Acute Exacerbations of Chronic Obstructive Pulmonary Disease (AECOPD) are commonly encountered in the primary care setting, though accurate and timely diagnosis is problematic. Using technology like that employed in speech recognition technology, we developed a smartphone-based algorithm for rapid and accurate diagnosis of AECOPD. The algorithm incorporates patient-reported features (age, fever, new cough), audio data from five coughs and can be deployed by novice users. We compared the accuracy of the algorithm to expert clinical assessment. In patients with known COPD, the algorithm correctly identified the presence of AECOPD in 82.6% (95% CI: 72.9-89.9%) of subjects (n=86). The absence of AECOPD was correctly identified in 91.0% (95% CI: 82.4-96.3%) of individuals (n=78). Diagnostic agreement was maintained in milder cases of AECOPD (PPA: 79.2%, 95% CI: 68.0-87.8%), who typically comprise the cohort presenting to primary care. The algorithm may aid early identification of AECOPD and be incorporated in patient self-management plans.
Aerobic fitness is associated with cerebral mu-opioid receptor availability and activation in healthy humans
Authors: Saanijoki Tiina , Kantonen Tatu , Pekkarinen Laura , Kalliokoski Kari , Hirvonen Jussi , Tuominen Lauri , Tuulari Jetro J. , Arponen Eveliina , Nuutila Pirjo , Nummenmaa Lauri
Published: December 2020

Central μ-opioid receptors (MORs) modulate affective responses to physical exercise. Individuals with higher aerobic fitness report greater exercise-induced mood improvements than those with lower fitness, but the link between cardiorespiratory fitness and the MOR system remains unresolved. Here we tested whether maximal oxygen uptake (VO2peak) and physical activity level are associated with cerebral MOR availability, and whether these phenotypes predict endogenous opioid release following aerobic exercise. We studied 64 healthy lean men who performed a maximal incremental cycling test for VO2peak determination, completed a questionnaire assessing moderate-to-vigorous physical activity (MVPA, min/week), and underwent positron emission tomography with [11C]carfentanil, a specific radioligand for MOR. A subset of 24 subjects underwent additional PET scan also after a one-hour session of moderate-intensity exercise. Higher VO2peak and self-reported MVPA level was associated with larger decrease in cerebral MOR binding after aerobic exercise in ventral striatum, orbitofrontal cortex and insula. That is, higher fit and more trained individuals showed greater opioid release acutely following exercise in brain regions especially relevant for reward and cognitive processing. Higher VO2peak also associated with lower baseline BPND in the reward and pain circuits, i.e., in frontal and cingulate cortices as well as in temporal lobes and subcortically in thalamus and putamen. We conclude that higher aerobic fitness and regular exercise training may induce neuroadaptation within the MOR system which might contribute to improved emotional and behavioural responses associated with long-term exercise.
The infection-tolerant mammalian reservoir of Lyme disease and other zoonoses broadly counters the inflammatory effects of endotoxin
Authors: Balderrama-Gutierrez Gabriela , Milovic Ana , Cook Vanessa J. , Islam M. Nurul , Zhang Youwen , Kiaris Hippokratis , Belisle John T. , Mortazavi Ali , Barbour Alan G.
Published: December 2020

Animals that are competent natural reservoirs of zoonotic diseases commonly suffer little morbidity from the pathogens they persistently harbor. The mechanisms of this infection tolerance and the trade-off costs are poorly understood. We used exposure to a single dose of lipopolysaccharide (LPS) endotoxin as an experimental model of inflammation to compare the responses of the cricentine rodentPeromyscus leucopus, the white-footed deermouse, to that ofMus musculus, the standard laboratory model for pathogenesis studies. Four hours after injection with either LPS or saline, blood and spleen and liver tissues were collected postmortem and subjected to RNA-seq, untargeted metabolomics, and specific RT-qPCR. This was followed by analysis of differential expression at the gene, pathway, and empirical network levels. The deermice showed the same signs of sickness as the mice with LPS exposure, and in addition demonstrated comparable increases in levels of corticosterone and expression of interleukin (IL)-6, tumor necrosis factor, IL-1β, and acute phase reactants, including C-reactive protein. But whereas theM. musculusresponse to LPS was best-characterized by network analysis as cytokine-associated, theP. leucopusresponse was dominated by pathway terms associated with neutrophil activity. Dichotomies between the species in expression profiles of arginase 1 and nitric oxide synthase 2, as well as the ratios of IL-10 to IL-12, were consistent with a type M1 polarized macrophage response in the mice and a type M2 or alternatively-activated response in the deermice. Analysis of metabolites in the plasma and RNA in the tissues revealed differences between the two species in tryptophan metabolism during response to LPS. Two up-regulated genes in particular signified the difference between the species: Slpi (secretory leukocyte proteinase inhibitor) and Ibsp (integrin-binding protein sialoprotein). The latter was previously unrecognized in the context of inflammation or infection. Key RNA-seq findings inP. leucopuswere replicated in a second LPS experiment with older animals, in a systemic bacterial infection model, and with cultivated fibroblasts. Taken together, the results indicate that the deermouse possesses several adaptive traits to moderate effects of inflammation and oxidative stress ensuing from infection. This seems to be at the cost of infection persistence and that is to the benefit of the pathogen.
Profiling of oral microbiota and cytokines in COVID-19 patients
Authors: Iebba Valerio , Zanotta Nunzia , Campisciano Giuseppina , Zerbato Verena , Di Bella Stefano , Cason Carolina , Morassut Sara , Luzzati Roberto , Confalonieri Marco , Palamara Anna Teresa , Comar Manola
Published: December 2020

SARS-CoV-2 presence has been recently demonstrated in the sputum or saliva, suggesting how the shedding of viral RNA outlasts the end of symptoms. Recent data from transcriptome analysis show that oral cavity mucosa harbors high levels of ACE2 and TMPRSS2, highlighting its role as a double-edged sword for SARS-CoV-2 body entrance or interpersonal transmission. In the present study, for the first time, we demonstrate the oral microbiota structure and inflammatory profile of COVID-19 patients. Hospitalized COVID-19 patients and matched healthy controls underwent naso/oral-pharyngeal and oral swabs. Microbiota structure was analyzed by 16S rRNA V2 automated targeted sequencing, while oral and sera concentrations of 27 cytokines were assessed using magnetic bead-based multiplex immunoassays. A significant diminution in species richness was observed in COVID-19 patients, along with a marked difference in beta-diversity. Species such asPrevotella salivaeandVeillonella infantiumwere distinctive for COVID-19 patients, whileNeisseria perflavaandGranulicatella eleganswere predominant in controls. Interestingly, these two groups of oral species oppositely clustered within the bacterial network, defining two distinct Species Interacting Group (SIGs). Pro-inflammatory cytokines were distinctive for COVID-19 in both oral and serum samples, and we found a specific bacterial consortium able to counteract them, following a novel index called C4 firstly proposed here. We even introduced a new parameter, named CytoCOV, able to predict COVID-19 susceptibility for an unknown subject at 71% of power with an AUC equal to 0.995. This pilot study evidenced a distinctive oral microbiota composition in COVID-19 subjects, with a definite structural network in relation to secreted cytokines. Our results would pave the way for a theranostic approach in fighting COVID-19, trying to enlighten the intimate relationship among microbiota and SARS-CoV-2 infection.
Predicting the Peak and COVID-19 trend in six high incidence countries: A study based on Modified SEIRD model
Authors: Bedi Punam , Dhiman Shivani , Gupta Neha , Jindal Vinita , Gole Pushkar
Published: December 2020

The novel Coronavirus (COVID-19) has claimed the lives of almost a million people across the globe and this trend continues to rise rapidly day by day. The fear of getting infected by Corona virus is affecting the people emotionally, psychologically and mentally. They are not able to work to their full capacity and are also worried about the well beings of their near and dear ones. The National governments have taken up several measures like lockdowns, closing of educational institutions, and work from home for employees of companies wherever feasible. Governments are also advising people to take precautions like not to go out if not necessary, use of mask and keep a distance of appx. 6 ft. if you need to go out as the virus spreads from human to human in close proximity. These measures have helped to limit the spread of this virus in the past few months. However, due to rapid increase in the daily confirmed cases, it is becoming tougher for the governments to provide facilities like testing kits, hospitalization facilities, oxygen cylinders etc. to the infected persons. Thus, there is an urgent need to accurately estimate the number of cases in coming future that can help governments in acquiring the required resources. Further, to handle the economic distress caused by this virus, long-term planning is equally important. Focusing on these two aspects, this paper proposes to use the Modified SEIRD (Susceptible-Exposed-Infected-Recovered-Deceased) model to predict the peak and spread trend of COVID-19 in six countries namely USA, India, Brazil, Russia, Peru and Colombia having the highest number of confirmed cases. As in COVID-19, even infected asymptomatic persons can spread the infection, the chosen model is well suited as exposed compartment of SEIRD model includes asymptomatic exposed individuals which are infectious. Epidemiological data till 9th September 2020 has been utilised to perform short-term predictions till 31st December 2020. Long-term predictions have been computed till 31st December 2023, to estimate the end of the virus in the above-mentioned six nations. Small values of MAPE (Mean Absolute Percentage Error) have been obtained for the models fitted to reported data for all the countries. Student t-test has been used for accepting the predictions of the Modified SEIRD model based on the reported data.
Transition from growth to decay of an epidemic due to lockdown
Authors: Khataee H. , Kibble J. , Scheuring I. , Czirok A. , Neufeld Z.
Published: December 2020

We study the transition of an epidemic from growth phase to decay of the active infections in a population when lockdown measures are introduced to reduce the probability of disease transmission. While in the case of uniform lockdown a simple compartmental model would indicate instantaneous transition to decay of the epidemic, this is not the case when partially isolated active clusters remain with the potential to create a series of small outbreaks. We model this using a connected set of stochastic susceptible-infected-removed/recovered (SIR) models representing the locked-down majority population (where the reproduction number is less than one) weakly coupled to a large set of small clusters where the infection may propagate. We find that the presence of such active clusters can lead to slower than expected decay of the epidemic and significantly delayed onset of the decay phase. We study the relative contributions of these changes to the additional total infections caused by the active clusters within the locked-down population. We also demonstrate that limiting the size of the inevitable active clusters can be efficient in reducing their impact on the overall size of the epidemic outbreak.

Statement of Significance

Restricting movement and interaction of individuals has been widely used in trying to limit the spread of COVID-19, however, there is limited understanding of the efficiency of these measures as it is difficult to predict how and when they lead to the decay of an epidemic. In this article, we develop a mathematical framework to investigate the transition to the decay phase of the epidemic taking into account that after lockdown a large number of active groups remain with the potential to produce localised outbreaks affecting the overall decay of infections in the population. Better understanding of the mechanism of transition to the decay of the epidemic can contribute to improving the implementation of public health control strategies.
Transfer Learning for COVID-19 Pneumonia Detection and Classification in Chest X-ray Images
Authors: Katsamenis Iason , Protopapadakis Eftychios , Voulodimos Athanasios , Doulamis Anastasios , Doulamis Nikolaos
Published: December 2020

We introduce a deep learning framework that can detect COVID-19 pneumonia in thoracic radiographs, as well as differentiate it from bacterial pneumonia infection. Deep classification models, such as convolutional neural networks (CNNs), require large-scale datasets in order to be trained and perform properly. Since the number of X-ray samples related to COVID-19 is limited, transfer learning (TL) appears as the go-to method to alleviate the demand for training data and develop accurate automated diagnosis models. In this context, networks are able to gain knowledge from pretrained networks on large-scale image datasets or alternative data-rich sources (i.e. bacterial and viral pneumonia radiographs). The experimental results indicate that the TL approach outperforms the performance obtained without TL, for the COVID-19 classification task in chest X-ray images.
Genome-wide analysis in 756,646 individuals provides first genetic evidence that ACE2 expression influences COVID-19 risk and yields genetic risk scores predictive of severe disease
Authors: Horowitz J. E. , Kosmicki J. A. , Damask A. , Sharma D. , Roberts G. H. L. , Justice A. E. , Banerjee N. , Coignet M. V. , Yadav A. , Leader J. B. , Marcketta A. , Park D. S. , Lanche R. , Maxwell E. , Knight S. C. , Bai X. , Guturu H. , Sun D. , Baltzell A. , Kury F. S. P. , Backman J. D. , Girshick A. R. , O’Dushlaine C. , McCurdy S. R. , Partha R. , Mansfield A. J. , Turissini D. A. , Li A. H. , Zhang M. , Mbatchou J. , Watanabe K. , Gurski L. , McCarthy S. E. , Kang H. M. , Dobbyn L. , Stahl E. , Verma A. , Sirugo G. ,   Regeneron Genetics Center, Ritchie M. D. , Jones M. , Balasubramanian S. , Siminovitch K. , Salerno W. J. , Shuldiner A. R. , Rader D. J. , Mirshahi T. , Locke A. E. , Marchini J. , Overton J. D. , Carey D. J. , Habegger L. , Cantor M. N. , Rand K. A. , Hong E. L. , Reid J. G. , Ball C. A. , Baras A. , Abecasis G. R. , Ferreira M. A.
Published: December 2020

SARS-CoV-2 enters host cells by binding angiotensin-converting enzyme 2 (ACE2). Through a genome-wide association study, we show that a rare variant (MAF = 0.3%, odds ratio 0.60, P=4.5x10-13) that down-regulates ACE2 expression reduces risk of COVID-19 disease, providing human genetics support for the hypothesis that ACE2 levels influence COVID-19 risk. Further, we show that common genetic variants define a risk score that predicts severe disease among COVID-19 cases.
Rapid processing of SARS-CoV-2 containing specimens for direct RT-PCR
Authors: Chomczynski Piotr
Published: December 2020

Widespread diagnostic testing is needed to reduce transmission of COVID-19 and manage the pandemic. Effective mass screening requires robust and sensitive tests that reliably detect the SARS-CoV-2 virus, including asymptomatic and pre-symptomatic infections with a low viral count. Currently, the most accurate tests are based on detection of viral RNA by RT-PCR. We developed a method to process COVID-19 specimens that simplifies and increases the sensitivity of viral RNA detection by direct RT-qPCR, performed without RNA purification. In the method, termed Alkaline-Glycol Processing (AG processing), a SARS-CoV-2-containing biological specimen, such as saliva or a swab-collected suspension, is processed at pH 12.2 to 12.8 for 5 min at room temperature. An aliquot of the AG-processed specimen is used for detection of SARS-CoV-2 RNA by direct RT-qPCR. AG processing effectively lyses viruses and reduces the effect of inhibitors of RT-PCR that are present in biological specimens. The sensitivity of detecting viral RNA using AG processing is on par with methods that include a viral RNA purification step. One copy of SARS-CoV-2 virus per reaction, equivalent to 300 copies per ml of saliva, is detectable in the AG-processed saliva. The LOD calculated following U.S. FDA guidelines is 600 viral copies per ml of initial saliva specimen. AG processing works with saliva specimens or swab specimens collected into Universal Transport Medium (UTM), is compatible with heat treatment, and was confirmed to work with a range of CDC-approved RT-qPCR products and kits. Detection of SARS-CoV-2 RNA using AG processing with direct RT-qPCR provides a reliable and scalable diagnostic test for COVID-19 that can be integrated into a range of workflows, including automated settings.
Massively parallel transposon mutagenesis identifies temporally essential genes for biofilm formation inEscherichia coli
Authors: Holden Emma R , Yasir Muhammad , Turner A Keith , Wain John , Charles Ian G. , Webber Mark A
Published: December 2020

Biofilms complete a life cycle where cells aggregate, grow and produce a structured community before dispersing to seed biofilms in new environments. Progression through this life cycle requires temporally controlled gene expression to maximise fitness at each stage. Previous studies have largely focused on the essential genome for the formation of a mature biofilm, but here we present an insight into the genes involved at different stages of biofilm formation. We used TraDIS-Xpress; a massively parallel transposon mutagenesis approach using transposon-located promoters to assay the impact of disruption or altered expression of all genes in the genome on biofilm formation. We determined temporal differences in the importance of genes inE. coligrowing as a biofilm on glass beads after 12, 24 and 48 hours. A selection of genes identified as important were then validated independently by assaying biofilm biomass, aggregation, curli production and adhesion ability of defined mutants. We identified 48 genes that affected biofilm fitness including genes with known roles and those not previously implicated in biofilm formation. Regulation of type 1 fimbriae and motility were important at all time points. Adhesion and motility were important for the early biofilm, whereas matrix production and purine biosynthesis were only important as the biofilm matured. We found strong temporal contributions to biofilm fitness for some genes including some where expression changed between being beneficial or detrimental depending on the stage at which they are expressed, includingdksAanddsbA. Novel genes implicated in biofilm formation includedzapEandtruAinvolved in cell division,maoPin DNA housekeeping andyigZandykgJof unknown function. This work provides new insights into the requirements for successful biofilm formation through the biofilm life cycle and demonstrates the importance of understanding expression and fitness through time.
Targeting Scavenger Receptor Type B-1 (SR-B1) and Cholesterol Inhibits Entry of SARS-CoV-2 Pseudovirus in Cell Culture
Authors: Henrich Stephen E. , McMahon Kaylin M. , Palacio Nicole , Bhalla Pankaj , Penaloza-MacMaster Pablo , Thaxton C. Shad
Published: December 2020

The novel human coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged in Wuhan, China in late 2019 and has now caused a global pandemic. The disease caused by SARS-CoV-2 is known as COVID-19. To date, few treatments for COVID-19 have proven effective, and the current standard of care is primarily supportive. As a result, novel therapeutic strategies are in high demand. Viral entry into target cells is frequently sensitive to cell membrane lipid composition and membrane organization. Evidence suggests that cell entry of SARS-CoV-2 is most efficient when the target cell plasma membrane is replete with cholesterol; and recent data implicate cholesterol flux through the high-affinity receptor for cholesterol-rich high-density lipoprotein (HDL), called scavenger receptor type B-1 (SR-B1), as critical for SARS-CoV-2 entry. Here, we demonstrate that a cholesterol-poor synthetic biologic high-density lipoprotein (HDL NP) targets SR-B1 and inhibits cell entry of a SARS-CoV-2 spike protein pseudovirus. Human cells expressing SR-B1 are susceptible to SARS-CoV-2 infection, and viral entry can be inhibited by 50-80% using HDL NPs in an SR-B1-dependent manner. These results indicate that HDL NP targeting of SR-B1 is a powerful potential therapy to combat COVID-19 and other viral diseases.
Frequency matters: Up- and Down-Regulation of Dopamine Tone Induces Similar Frequency Shifts in Cortico-Basal Ganglia Beta Oscillations
Authors: Iskhakova L. , Rappel P. , Fonar G. , Marmor O. , Paz R. , Israel Z. , Eitan R. , Bergman H.
Published: December 2020

Beta oscillatory activity (13-30Hz) is pervasive within the cortico-basal ganglia (CBG) network. Studies in Parkinson’s disease (PD) patients and animal models suggested that beta-power increases with dopamine depletion. However, the exact relationship between oscillatory power, frequency and dopamine-tone remains unclear. We recorded neural activity in the CBG network of non-human-primates (NHP) while acutely up- and down-modulating dopamine levels. Further, we assessed changes in beta oscillations of PD patients following acute and chronic changes in dopamine-tone. Beta oscillation frequency was strongly coupled with dopamine-tone in both NHPs and human patients. In contrast, power, coherence between single-units and LFP, and spike-LFP phase-locking were not systematically regulated by dopamine levels. These results demonstrate via causal manipulations that frequency, rather than other properties, is the key property of pathological oscillations in the CBG networks. These insights can lead to improvements in understanding of CBG physiology, PD progression tracking and patient care.
PomX, a ParA/MinD ATPase activating protein, is a triple regulator of cell division inMyxococcus xanthus
Authors: Schumacher Dominik , Harms Andrea , Bergeler Silke , Frey Erwin , Søgaard-Andersen Lotte
Published: December 2020

Cell division is precisely regulated to generate daughter cells of correct size and shape. In the social bacteriumMyxococcus xanthus, the tripartite PomX/Y/Z complex directly stimulates positioning of the cytokinetic FtsZ-ring at midcell to mark the division site. The ∼15 MDa PomX/Y/Z complex associates with the nucleoid in a PomZ-dependent manner, translocates to midcell to stimulate FtsZ-ring formation, and undergoes fission during division. We demonstrate that PomX consists of two functionally distinct domains and has three functions. The N-terminal domain interacts with the ParA/MinD ATPase PomZ and stimulates PomZ ATPase activity. The C-terminal domain mediates PomX self-interaction, interaction to PomY, and serves as a scaffold for PomX/Y/Z complex formation. Moreover, the PomX/PomZ interaction is important for fission. These observations together with previous work support that the architecturally diverse ATPase activating proteins of ParA/MinD ATPases are highly modular and use the same mechanism to activate their cognate ATPase via a short positively charged N-terminal extension.
Multiple Temporal and Semantic Processes During Verbal Fluency Tasks in English-Russian Bilinguals
Authors: Lerner Alan J. , Crough Michelle , Lenio Steven , Woyczynski Wojbor , Lissemore Frances M.
Published: December 2020

Category fluency test (CFT) performance is sensitive to cognitive processes of executive control and memory storage and access, and widely used to measure cognitive performance especially in early Alzheimer’s Disease. Analytical variables have included the number of items named, and various methods to identify and quantify clusters of semantically related words and cluster switches. Also encoded in the response sequence are temporal patterns as shown by “bursts” of responses and pauses between items, that have not been received attention in determining cluster characteristics.

We studied a group of 51 adult Russian-English bilinguals and compared CFT responses based on two clustering methodologies: the semantic-based method (SEM) and a novel method based on the time interval between words (TEMP) with 8 different intercall time thresholds from 0.25 sec-15 sec. Each participant performed the task in both languages. Total number of words and cluster count was greater in Russian than English for both scoring methods, but cluster size did not differ between languages. We also studied stochastic modeling characteristics based on detrending of the “exponential exhaustion” effect seen with CFT, with most notable that total recall capacity (N∞) was greater in Russian than English (P<.05). Multiple demographic variables, and recent and lifetime usage of each language, affected both cognitive performance as measured by the Montreal Cognitive Assessment (MOCA; given in English only). Differential performance is driven by differences in demographics, more words stored in memory, and semantic and timing recall strategies.
Pre-departure psychological distress and associated factors among migrant workers of Nepal
Authors: Poudel Om Prakash , Thapa Bijay , Bhandary Shital
Published: December 2020

Introduction

Foreign employment is the most significant motivation for international migration in Nepal. However, migrant workers are vulnerable to many exploitations that lead to psychological distress during the pre-departure phase and at the destination. The study aimed to identify the prevalence and associated factors for psychological distress among migrant workers during the pre-departure phase.

Methods

This was a cross-sectional study based on the representative sample of 445 migrant workers. A 21-item Depression Anxiety Stress Scale (DASS-21) and Pre-Departure Risk Factors Perception Scale (PD-RFPS) at the workplace were self-administered to migrant workers selected randomly attending the pre-departure orientation program. Bivariate and multivariate logistic regression was performed to identify the associated factors.

Results

Prevalence of psychological distress (Depression, Anxiety and Stress) was identified as 20.9% and female (AOR=2.02, p-value=0.041) and perception of bad working conditions (AOR=2.44, p-value=0.046) were found significantly associated with pre-departure psychological distress.

Conclusion

Data suggests the presence of symptoms of psychological distress among migrant workers during the pre-departure phase and perception of risk factors at the workplace were found significantly associated with pre-departure psychological distress. Concern bodies should provide in-depth orientation on possible risk factors at the destination and coping skills for psychological distress during the pre-departure orientation program.
Dataset-specific thresholds significantly improve detection of low transcribed regulatory genes in polysome profiling experiments
Authors: Deyneko Igor V. , Mustafaev Orkhan N. , А. Tyurin Alexander , Zhukova Ksenya V. , Goldenkova-Pavlova Irina V.
Published: December 2020

Motivation

Polysome profiling is novel, and yet has proved to be an effective approach to detect mRNAs with differential ribosomal load and explore the regulatory mechanisms driving efficient translation. Genes encoding regulatory proteins, having a great influence of the organism, usually reveal moderate to low transcriptional levels, compared, for example, to genes of house-keeping machinery. This complicates the reliable detection of such genes in the presence of technical and/or biological noise.

Results

In this work we investigate how cleaning of polysome profiling data onArabidopsis thalianainfluences the ability to detect genes with low level of total mRNA, but with a highly differential ribosomal load, i.e. genes translationally active. Suggested data modelling approach to identify a background level of mRNA counts individually for each dataset, shows higher power in detection of low transcribed genes, compared to the use of thresholds for the minimal required mRNA counts or the use of raw data. The significant increase in detected number of regulation–related genes was demonstrated. The described approach is applicable to a wide variety of RNA-seq data. All identified and classified mRNAs with high and low translation status are made available in supplementary material.
Proteomic characterization of pilot scale hot-water extracts from the industrial carrageenan red seaweedEucheuma denticulatum
Authors: Gregersen Simon , Pertseva Margarita , Marcatili Paolo , Holdt Susan Løvstad , Jacobsen Charlotte , García-Moreno Pedro J. , Hansen Egon Bech , Overgaard Michael Toft
Published: December 2020

Seaweeds have a long history as a resource for polysaccharides/hydrocolloids extraction for use in the food industry due to their functionality as stabilizing agents. In addition to the carbohydrate content, seaweeds also contains a significant amount of protein, which may find application in food and feed. Here, we present a novel combination of transcriptomics, proteomics, and bioinformatics to determine the protein composition in two pilot-scale extracts fromEucheuma denticilatum(Spinosum) obtained via hot-water extraction. The extracts were characterized by qualitative and quantitative proteomics using LC-MS/MS and ade-novotranscriptome assembly for construction of a novel proteome. Using label-free, relative quantification, we were able to identify the most abundant proteins in the extracts and determined that the majority of quantified protein in the extracts (>75%) is constituted by merely three previously uncharacterized proteins. Putative subcellular localization for the quantified proteins was determined by bioinformatic prediction, and by correlating with the expected copy number from the transcriptome analysis, we determined that the extracts were highly enriched in extracellular proteins. This implies that the method predominantly extracts extracellular proteins, and thus appear ineffective for cellular disruption and subsequent release of intracellular proteins. Ultimately, this study highlight the power of quantitative proteomics as a novel tool for characterization of alternative protein sources intended for use in foods. Additionally, the study showcases the potential of proteomics for evaluation of protein extraction methods and as powerful tool in the development of an efficient extraction process.
Antibiotics modulate attractive interactions in bacterial colonies affecting survivability under combined treatment
Authors: Cronenberg Tom , Hennes Marc , Wielert Isabelle , Maier Berenike
Published: December 2020

Biofilm formation protects bacteria from antibiotics. Very little is known about the response of biofilm-dwelling bacteria to antibiotics at the single cell level. Here, we developed a cell-tracking approach to investigate how antibiotics affect structure and dynamics of colonies formed by the human pathogenNeisseria gonorrhoeae. Antibiotics targeting different cellular functions enlarge the cell volumes and modulate within-colony motility. Focusing on azithromycin and ceftriaxone, we identify changes in type 4 pilus (T4P) mediated cell-to-cell attraction as the molecular mechanism for different effects on motility. By using strongly attractive mutant strains, we reveal that the survivability under ceftriaxone treatment depends on motility. Combining our results, we find that sequential treatment with azithromycin and ceftriaxone is synergistic. Taken together, we demonstrate that antibiotics modulate T4P-mediated attractions and hence cell motility and colony fluidity.

Author Summary

Aggregation into colonies and biofilms can enhance bacterial survivability under antibiotic treatment. Aggregation requires modulation of attractive forces between neighboring bacteria, yet the link between attraction and survivability is poorly characterized. Here, we quantify these attractive interactions and show that different antibiotics enhance or inhibit them. Live-cell tracking of single cells in spherical colonies enables us to correlate attractive interactions with single cell motility and colony fluidity. Even moderate changes in cell-to-cell attraction caused by antibiotics strongly impact on within-colony motility. Vice versa, we reveal that motility correlates with survivability under antibiotic treatment. In summary, we demonstrate a link between cellular attraction, colony fluidity, and survivability with the potential to optimize the treatment strategy of commonly used drug combinations.
Data-independent Acquisition-based Proteome and Phosphoproteome Profiling across Six Melanoma Cell Lines Reveals Determinants of Proteotypes
Authors: Gao Erli , Li Wenxue , Wu Chongde , Shao Wenguang , Di Yi , Liu Yansheng
Published: December 2020

Human cancer cell lines are widely used in pharmacological and systems biological studies. The rapid documentation of the steady-state gene expression landscape of the cells used in a particular experiment may help to improve the reproducibility of scientific research. Here we applied a data-independent acquisition mass spectrometry (DIA-MS) method, coupled with a peptide spectral-library free data analysis workflow, to measure both proteome and phosphoproteome of a melanoma cell line panel with different metastatic properties. For each cell line, the single-shot DIA-MS detected 8,100 proteins and almost 40,000 phosphopeptides in the respective measurement of two hours. Benchmarking the DIA-MS data towards the RNA-seq data and tandem mass tag (TMT)-MS results from the same set of cell lines demonstrated comparable qualitative coverage and quantitative reproducibility. Our data confirmed the high but complex mRNA~protein and protein~phospsite correlations. The results successfully established DIA-MS as a strong and competitive proteotyping approach for cell lines. The data further showed that all subunits of Glycosylphosphatidylinositol (GPI)-anchor transamidase complex were overexpressed in metastatic melanoma cells and identified altered phosphoprotein modules such as BAF complex and mRNA splicing between metastatic and primary cells. This study provides a high-quality resource for calibrating DIA-MS performance, benchmarking DIA bioinformatic algorithms, and exploring the metastatic proteotypes in melanoma cells.
Stable QTL for malate levels in ripe fruit and their transferability acrossVitisspecies
Authors: Reshef Noam , Karn Avinash , Manns David C. , Mansfield Anna Katharine , Cadle-Davidson Lance , Reisch Bruce , Sacks Gavin L.
Published: December 2020

Malate is a major contributor to the sourness of grape berries (Vitisspp.) and their products, such as wine. Excessive malate at maturity, commonly observed in wildVitisgrapes, is detrimental to grape and wine quality and complicates the introgression of valuable disease resistance and cold hardy genes through breeding. This study investigated an interspecificVitisfamily that exhibited strong and stable variation in malate at ripeness for five years and tested the separate contribution of accumulation, degradation, and dilution to malate concentration in ripe fruit in the last year of study. Genotyping was performed using transferable rhAmpSeq haplotype markers, based on theVitiscollinear core genome. Three significant QTL for ripe fruit malate on chromosomes 1, 7, and 17, accounted for over two-fold and 6.9 g/L differences in ripe fruit malate, and explained 40.6% of the phenotypic variation. QTL on chromosomes 7 and 17 were stable in all and in three out of five years, respectively. Variation in pre-veraison malate was the major contributor to variation in ripe fruit malate (39%) and their associated QTL overlapped on chromosome 7, indicating a common genetic basis. However, use of transferable markers on a closely relatedVitisfamily did not yield a common QTL across families. This suggests that diverse physiological mechanisms regulate the levels of this key metabolite in theVitisgenus, a conclusion supported by a review of over a dozen publications from the past decade, showing malate-associated genetic loci on all 19 chromosomes.
Mono-ubiquitination of Rabphilin 3A by UBE3A serves a non-degradative function
Authors: Trezza Rossella Avagliano , Punt A. Mattijs , Mientjes Edwin , van den Berg Marlene , Zampeta F. Isabella , de Graaf Ilona J. , van der Weegen Yana , Demmers Jeroen A. A. , Elgersma Ype , Distel Ben
Published: December 2020

Angelman syndrome (AS) is a severe neurodevelopmental disorder caused by brain-specific loss of UBE3A, an E3 ubiquitin protein ligase. A substantial number of possible ubiquitination targets of UBE3A have been identified, although evidence of being direct UBE3A substrates is often lacking. Here we identified the synaptic protein Rabphilin-3a (RPH3A), an effector of the RAB3A small GTPase involved in axonal vesicle priming and docking, as a ubiquitination target of UBE3A. We found that the UBE3A and RAB3A binding sites on RPH3A partially overlap, and that RAB3A binding to RPH3A interferes with UBE3A binding. We confirmed previous observations that RPH3A levels are critically dependent on RAB3A binding but, rather surprisingly, we found that the reduced RPH3A levels in the absence of RAB3A are not mediated by UBE3A. Indeed, while we found that RPH3A is ubiquitinated in a UBE3A-dependent manner in mouse brain, UBE3A mono-ubiquitinates RPH3A and does not facilitate RPH3A degradation. Moreover, we found that an AS-linked UBE3A missense mutation in the UBE3A region that interacts with RPH3A, abrogates the interaction with RPH3A. In conclusion, our results identify RPH3A as a novel target of UBE3A and suggest that UBE3A-dependent ubiquitination of RPH3A serves a non-degradative function.
Remdesivir is a delayed translocation inhibitor of SARS CoV-2 replication in vitro
Authors: Bravo Jack P. K. , Dangerfield Tyler L. , Taylor David W. , Johnson Kenneth A.
Published: December 2020

Remdesivir is a nucleoside analog approved by the FDA for treatment of COVID-19. Here, we present a 3.9-Å-resolution cryoEM reconstruction of a remdesivir-stalled RNA-dependent RNA polymerase complex, revealing full incorporation of three copies of remdesivir monophosphate (RMP) and a partially incorporated fourth RMP in the active site. The structure reveals that RMP blocks RNA translocation after incorporation of three bases following RMP, resulting in delayed chain termination, which can guide the rational design of improved antiviral drugs.