bluuebunny/crossref_metadata_2025_split huggingface dataset:
Role of sex and high fat diet in metabolic and hypothalamic disturbances in the 3xTg-AD mouse model of Alzheimer’s disease
Authors: Robison Lisa. S. , Gannon Olivia J. , Thomas Melissa A. , Salinero Abigail E. , Abi-Ghanem Charly , Poitelon Yannick , Belin Sophie , Zuloaga Kristen L. 
Published: July 2020

AbstractHypothalamic dysfunction occurs early in the clinical course of Alzheimer’s disease (AD), likely contributing to disturbances in feeding behavior and metabolic function that are often observable years prior to the onset of cognitive symptoms. Late-life weight loss and low BMI are associated with increased risk of dementia and faster progression of disease. However, high fat diet and metabolic disease (e.g. obesity, type 2 diabetes), particularly in mid-life, are associated with increased risk of AD, as well as exacerbated AD pathology and behavioral deficits in animal models. In the current study, we explored possible relationships between hypothalamic function, diet/metabolic status, and AD. Considering the sex bias in AD, with women representing two-thirds of AD patients, we sought to determine whether these relationships vary by sex. WT and 3xTg-AD male and female mice were fed a control (10% fat) or high fat (HF; 60% diet) diet from ~3-7 months of age, then tested for metabolic and hypothalamic disturbances. On control diet, male 3xTg-AD mice displayed decreased body weight, reduced fat mass, hypoleptinemia, and mild systemic inflammation, as well as increased expression of gliosis- and inflammation-related genes in the hypothalamus (Iba1, GFAP, TNF-α, IL-1β). In contrast, female 3xTg-AD mice on control diet displayed metabolic disturbances opposite that of 3xTg-AD males (increased body and fat mass, impaired glucose tolerance). HF diet resulted in expected metabolic alterations across groups (increased body and fat mass; glucose intolerance; increased plasma insulin and leptin, decreased ghrelin; nonalcoholic fatty liver disease-related pathology). HF diet resulted in the greatest weight gain, adiposity, and glucose intolerance in 3xTg-AD females, which were associated with markedly increased hypothalamic expression of GFAP and IL-1β, as well as GFAP labeling in several hypothalamic nuclei that regulate energy balance. In contrast, HF diet increased diabetes markers and systemic inflammation preferentially in AD males but did not exacerbate hypothalamic inflammation in this group. These findings provide further evidence for the roles of hypothalamic and metabolic dysfunction in AD, which in the 3xTg-AD mouse model appears to be dependent on both sex and diet.
Multiple genetic pathways regulating lifespan extension are neuroprotective in a G2019S LRRK2 nematode model of Parkinson’s disease
Authors: Senchuk Megan M. , Van Raamsdonk Jeremy M. , Moore Darren J. 
Published: July 2020

AbstractBackgroundMutations in theleucine-rich repeat kinase 2(LRRK2) gene are the most frequent cause of late-onset, familial Parkinson’s disease (PD), andLRRK2variants are associated with increased risk for sporadic PD. While advanced age represents the strongest risk factor for disease development, it remains unclear how different age-related pathways interact to regulateLRRK2-driven late-onset PD.FindingsIn this study, we employ aC.elegansmodel expressing PD-linked G2019S LRRK2 to examine the interplay between age-related pathways and LRRK2-induced dopaminergic neurodegeneration. We find that multiple genetic pathways that regulate lifespan extension can provide robust neuroprotection against mutant LRRK2. However, the level of neuroprotection does not strictly correlate with the magnitude of lifespan extension, suggesting that lifespan can be experimentally dissociated from neuroprotection. Using tissue-specific RNAi, we demonstrate that lifespan-regulating pathways, including insulin/IGF-1 signaling, TOR, and mitochondrial respiration, can be directly manipulated in neurons to mediate neuroprotection. We extend this finding for AGE-1/PI3K, where pan-neuronal versus dopaminergic neuronal restoration of AGE-1 reveals both cell-autonomous and non-cell-autonomous neuroprotective mechanisms downstream of insulin signaling.ConclusionsOur data demonstrate the importance of distinct lifespan-regulating pathways in the pathogenesis ofLRRK2-linked PD, and suggest that extended longevity is broadly neuroprotective via the actions of these pathways at least in part within neurons. This study further highlights the complex interplay that occurs between cells and tissues during organismal aging and disease manifestation.
Increasing growth temperature alters the within-host competition of viral strains and influences virus genetic variation
Authors: Alcaide Cristina , Sardanyés Josep , Elena Santiago F. , Gómez Pedro 
Published: July 2020

AbstractThe emergence of viral diseases in plant crops hamper the sustainability of food production, and this may be boosted by global warming. Concurrently, mixed viral infections are becoming common in plants, of which epidemiology are unpredictable due to within-host virus-virus interactions. However, the extent in which the combined effect of variations in the abiotic components of the plant ecological niche (e.g., temperature) and the prevalence of mixed infections (i.e., within-host interactions among viruses) affect the evolutionary dynamics of viral populations is not well understood. Here, we explore the interplay between ecological and evolutionary factors during viral infections, and show that two individual strains of pepino mosaic virus (PepMV) coexisted in a temperature-dependent continuum between neutral and antagonistic interactions in tomato plants. After a long-term infection, the mutational analysis of the evolved viral genomes revealed strain-specific single-nucleotide polymorphisms that were modulated by the interaction between the type of infection and temperature. Mathematical modeling allowed us to asses a thermal reaction norm for both strains, which indicated that viral replication rates were increased along with increasing temperature in mixed infections, with a remarkable strain-dependent effect. These results suggest that the growth temperature is an ecological driver of virus-virus interactions, with an effect on the genetic diversity of individual viruses co-infecting a host. This research provides insights into the effect that climate change will have on the evolutionary dynamics of viral populations.
Novel tunable spatio-temporal patterns from a simple genetic oscillator circuit
Authors: Yáñez Feliú Guillermo , Vidal Gonzalo , Muñoz Silva Macarena , Rudge Timothy J. 
Published: July 2020

AbstractMulticellularity, the coordinated collective behaviour of cell populations, gives rise to the emergence of self-organized phenomena at many different spatio-temporal scales. At the genetic scale, oscillators are ubiquitous in regulation of multicellular systems, including during their development and regeneration. Synthetic biologists have successfully created simple synthetic genetic circuits that produce oscillations in single cells. Studying and engineering synthetic oscillators in a multicellular chassis can therefore give us valuable insights into how simple genetic circuits can encode complex multicellular behaviours at different scales. Here we develop a study of the coupling between the repressilator synthetic genetic ring oscillator and constraints on cell growth in colonies. We show in silico how mechanical constraints generate characteristic patterns of growth rate inhomogeneity in growing cell colonies. Next, we develop a simple one-dimensional model which predicts that coupling the repressilator to this pattern of growth rate via protein dilution generates travelling waves of gene expression. We show that the dynamics of these spatio-temporal patterns are determined by two parameters; the protein degradation and maximum expression rates of the repressors. We derive simple relations between these parameters and the key characteristics of the travelling wave patterns: firstly, wave speed is determined by protein degradation and secondly, wavelength is determined by maximum gene expression rate. Our analytical predictions and numerical results were in close quantitative agreement with detailed individual based simulations of growing cell colonies. Confirming published experimental results we also found that static ring patterns occur when protein stability is high. Our results show that this pattern can be induced simply by growth rate dilution and does not require transition to stationary phase as previously suggested. Our method generalizes easily to other genetic circuit architectures thus providing a framework for multi-scale rational design of spatio-temporal patterns from genetic circuits. We use this method to generate testable predictions for the synthetic biology design-build-test-learn cycle.
The fragile X mental retardation protein promotes adjustments in cocaine self-administration that preserve reinforcement level
Authors: Huebschman Jessica L. , Davis Megan C. , Pensa Catherina Tovar , Guo Yuhong , Smith Laura N. 
Published: July 2020

AbstractThe fragile X mental retardation protein (FMRP), an RNA-binding protein, regulates cocaine-induced neuronal plasticity and is critical for the normal development of drug-induced locomotor sensitization, as well as reward-related learning in the conditioned place preference assay. However, it is unknown whether FMRP impacts behaviors that are used to more closely model substance use disorders. Utilizing an intravenous cocaine self-administration (IVSA) assay inFmr1knockout (KO) and wild type (WT) littermate mice, we find that, despite normal acquisition and extinction learning,Fmr1KO mice fail to make a normal upward shift in responding during dose-response testing. Later, with access to the original acquisition dose under increasing schedules of reinforcement (FR1, FR3, FR5),Fmr1KO mice earn significantly fewer cocaine infusions than WT mice. Importantly, operant conditioning with a palatable food reinforcer does not show similar deficits, indicating that our results do not stem from broad learning or reward-related deficits inFmr1KO mice. Additionally, we find an FMRP target, the activity-regulated cytoskeleton-associated protein (Arc), to be significantly reduced inFmr1KO mouse synaptic fractions from the nucleus accumbens following cocaine IVSA. Overall, our findings suggest that FMRP facilitates adjustments in drug self-administration behavior that generally serve to preserve reinforcement level, and combined with our similar IVSA findings inArcKO mice, suggest Arc as a target of FMRP to investigate in behavioral shifts that occur when drug availability is altered.
Adherence to Pakistan dietary guidelines – Findings from major cities of Pakistan
Authors: Rafique Ibrar , Muhammad Arif Nadeem Saqib , Murad Nighat , Munir Muhammad Kashif , Khan Aftab , Irshad Rabia , Rahat Tayyaba , Naz Saima 
Published: July 2020

AbstractBackgroundPakistan dietary guidelines for better nutrition were developed to cater the local need and prevent nutritional deficiency by providing information to public about healthy eating practices.AimsTo assess the level of adherence to Pakistan Dietary Guidelines for Better Nutrition (PDGN)MethodsIt was a community based study conducted in five cities with two stage stratified sampling approach. Total of 448 participants were interviewed using Food frequency questionnaire adapted to local context. Five food groups (proteins, cereals, dairy, vegetables and fruits) were taken as per country guidelines. A score point of 1 was given to each food group making a total of 5 scores. Data were analyzed using SPSS.ResultsOverall adherence to PDGN was poor as none of the participants had 05 score while only 1% achieved score 04. However, adherence was more in females (B = 0.45, 95%CI = 0.24; 0.66), graduates (B = 0.45, 95% CI = 0.25; 0.64), unmarried (B = 0.30, 95% CI = 0.18; 0.43), unemployed (B = 0.22, 95% CI = 0.01-0.43) and aged >50 years (B = 0.34, 95% CI = 0.08; 0.60) as compared to others. Among food groups, mean intake of cereals (carbohydrates) was high (3.38±1.39) followed by other items with fruits was least (0.76±0.91). Overall, at least one serving of discretionary food was taken by participants which was more female gender (p= 0.001), graduates (p= 0.003), high socio-economic group (p=0.001) and employed persons (p= 0.04).ConclusionThe adherence to PDGN was poor and there is a need to bring behavior change by information education and communication to the society.
COVID-19-related Fake News in Social Media
Authors: Al-Zaman Md. Sayeed 
Published: July 2020

AbstractThis study analyzes N=125 prominent fake news related to the COVID-19 pandemic spread in social media from 29 January to 11 April 2020. The five parameters of the analysis are themes, content types, sources, coverage, and intentions. First, the six major themes of fake news are health, religiopolitical, political, crime, entertainment, religious, and miscellaneous. Health-related fake news (67.2%) dominates the others. Second, the seven types of fake news contents have four main types: text, photo, audio and video, and three combined types: text & photo; text & video; and text & photo & video. More fake news takes the forms of text & video (47.2%), while the main types of content are less popular. Third, the two main sources of fake news are online media and mainstream media, where online-produced fake news (94.4%) prevails. Fourth, the main two types of coverages are international and national, and more fake news has an international connection (54.4%). Fifth, the intention of fake news has three types: positive, negative, and unknown. Most of the COVID-19-related fake news is negative (63.2%). Although fake news cases are unevenly distributed and repeatedly fluctuates during the period, a slow decrease of daily cases is noticed toward the end.
Does sub-Saharan Africa truly defy the forecasts of the COVID-19 pandemic? Response from population data
Authors: Fokoua-Maxime Dongmo Christophe , Amor-Ndjabo Monique , Ankobil Amandus , Victor-Kiyung Momah , Franck-Metomb Steve , Choukem Simeon Pierre 
Published: July 2020

AbstractIntroductionSince its identification, the COVID-19 infection has caused substantial mortality and morbidity worldwide, but sub-Saharan Africa seems to defy the predictions. We aimed to verify this hypothesis using strong statistical methods.MethodsWe conducted a cross-sectional study comparing the projected and actual numbers as well as population proportions of COVID-19 cases in the 46 sub-Saharan African countries on May 1st, May 29th (4 weeks later) and June 26th (8 weeks later). The source of the projected number of cases was a publication by scientists from the Center for Mathematical Modeling of Infectious Diseases of the London School of Hygiene & Tropical Medicine, whereas the actual number of cases was obtained from the WHO situation reports. We calculated the percentage difference between the projected and actual numbers of cases per country. Further, “N-1” chi-square tests with Bonferroni correction were used to compare the projected and actual population proportion of COVID-19 cases, along with the 95% confidence interval of the difference between these population proportions. All statistical tests were 2-sided, with 0.05 used as threshold for statistical significance.ResultsOn May 1st, May 29th and June 26th, respectively 40 (86.95%), 45 (97.82%) and 41 (89.13%) of the sub-Saharan African countries reported a number of confirmed cases that was lower than the predicted number of 1000 cases for May 1st and 10000 for both May 29th and June 26th. At these dates, the population proportions of confirmed Covid-19 cases were significantly lower (p-value <0.05) than the projected proportions of cases. Across all these dates, South-Africa always exceeded the predicted number and population proportion of COVID-19 infections.ConclusionSub-Saharan African countries did defy the dire predictions of the COVID-19 burden. Preventive measures should be further enforced to preserve this positive outcome.
Predicting the second wave of COVID-19 in Washtenaw County, MI
Authors: Renardy Marissa , Kirschner Denise 
Published: July 2020

AbstractThe COVID-19 pandemic has highlighted the patchwork nature of disease epidemics, with infection spread dynamics varying wildly across countries and across states within the US. These heterogeneous patterns are also observed within individual states, with patches of concentrated outbreaks. Data is being generated daily at all of these spatial scales, and answers to questions regarded reopening strategies are desperately needed. Mathematical modeling is useful in exactly these cases, and using modeling at a county scale may be valuable to further predict disease dynamics for the purposes of public health interventions. To explore this issue, we study and predict the spread of COVID-19 in Washtenaw County, MI, the home to University of Michigan, Eastern Michigan University, and Google, as well as serving as a sister city to Detroit, MI where there has been a serious outbreak. Here, we apply a discrete and stochastic network-based modeling framework allowing us to track every individual in the county. In this framework, we construct contact networks based on synthetic population datasets specific for Washtenaw County that are derived from US Census datasets. We assign individuals to households, workplaces, schools, and group quarters (such as prisons). In addition, we assign casual contacts to each individual at random. Using this framework, we explicitly simulate Michigan-specific government-mandated workplace and school closures as well as social distancing measures. We also perform sensitivity analyses to identify key model parameters and mechanisms contributing to the observed disease burden in the three months following the first observed cases on COVID-19 in Michigan. We then consider several scenarios for relaxing restrictions and reopening workplaces to predict what actions would be most prudent. In particular, we consider the effects of 1) different timings for reopening, and 2) different levels of workplace vs. casual contact re-engagement. Through simulations and sensitivity analyses, we explore mechanisms driving magnitude and timing of a second wave of infections upon re-opening. This model can be adapted to other US counties using synthetic population databases and data specific to those regions.
Finding Rare Disease Patients in EHR Databases via Lightly-Supervised Learning
Authors: Colbaugh Rich , Glass Kristin 
Published: July 2020

AbstractThere is considerable interest in developing computational models capable of detecting rare disease patients in population-scale databases such as electronic health records (EHRs). Deriving these models is challenging for several reasons, perhaps the most daunting being the limited number of already-diagnosed, ‘labeled’ patients from which to learn. We overcome this obstacle with a novel lightly-supervised algorithm that leverages unlabeled and/or unreliably-labeled patient data – which is typically plentiful – to facilitate model induction. Importantly, we prove the algorithm issafe:adding unlabeled/unreliably-labeled data to the learning procedure produces models which are usually more accurate, and guaranteed never to be less accurate, than models learned from reliably-labeled data alone. The proposed method is shown to substantially outperform state-of-the-art models in patient-finding experiments involving two different rare diseases and a country-scale EHR database. Additionally, we demonstrate feasibility of transforming high-performance models generated through light supervision into simpler models which, while still accurate, are readily-interpretable by non-experts.
Impact of Congestive Heart Failure and Role of Cardiac Biomarkers in COVID-19 patients: A Systematic Review and Meta-Analysis
Authors: Dalia Tarun , Lahan Shubham , Ranka Sagar , Acharya Prakash , Gautam Archana , Mastoris Ioannis , Sauer Andrew , Shah Zubair 
Published: July 2020

AbstractImportanceCoronavirus disease 2019 (COVID-19) has been reported to cause worse outcomes in patients with underlying cardiovascular disease, especially in patients with acute cardiac injury, which is determined by elevated levels of high-sensitivity troponin. There is paucity of data on the impact of congestive heart failure (CHF) on outcomes in COVID-19 patients.ObjectiveTo evaluate the occurrence of acute cardiac injury and arrhythmias and to assess the impact of pre-existing CHF and hypertension (HTN) in COVID-19 patients.Data SourcesWe conducted a literature search of PubMed/Medline, EMBASE, and Google Scholar databases from 11/1/2019 till 06/07/2020. databases using following search terms or keywords: “(COVID) AND (Clinical); ((heart) OR (myocard*)) AND (COVID); (COVID) AND (Troponin); (Coronavirus) AND (Heart).”Study SelectionWe identified all relevant studies reporting cardiovascular comorbidities, cardiac biomarkers, disease severity, and survival in COVID-19 patients.Data Extraction and SynthesisWe followed preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines for abstracting data. Pooled data was meta-analyzed using random-effects model and between-study heterogeneity was calculated with Higgins I2 statistic.Main outcome and measuresTo assess the impact of HTN and CHF and to evaluate different cardiac biomarkers in COVID-19 patients based on their disease severity.ResultsWe collected pooled data on 5,967 COVID-19 patients from 20 individual studies. We found that both non-survivors and those with severe disease had an increased risk of acute cardiac injury and cardiac arrhythmias, our pooled relative risk (RR) was — 8.52 (95% CI 3.63– 19.98) (p<0.001); and 3.61 (95% CI 2.03–6.43) (p=0.001), respectively. Mean difference in the levels of Troponin-I, CK-MB, and NT-proBNP was higher in deceased and severely infected patients. The RR of in-hospital mortality was 2.35 (95% CI 1.18–4.70) (p=0.022) and 1.52 (95% CI 1.12–2.05) (p=0.008) among patients who had pre-existing CHF and hypertension, respectively.Conclusion and RelevanceCardiac involvement in COVID-19 infection appears to significantly adversely impact patient prognosis and survival. Pre-existence of CHF, and high cardiac biomarkers like NT-pro BNP and CK-MB levels in COVID-19 patients correlates with worse outcomes.
Modelling interventions to control COVID-19 outbreaks in a refugee camp
Authors: Gilman R. Tucker , Mahroof-Shaffi Siyana , Harkensee Christian , Chamberlain Andrew T. 
Published: July 2020

AbstractRefugee camp populations are expected to be vulnerable to COVID-19 due to overcrowding, unsanitary conditions, and inadequate medical facilities. Because there has been no COVID-19 outbreak in a refugee camp to date, the potential for nonpharmaceutical interventions to slow the spread of COVID-19 in refugee camps remains untested. We used an agent-based model to simulate COVID-19 outbreaks in the Moria refugee camp, and we studied the effects of feasible interventions. Subdividing the camp (’sectoring’) “flattened the curve,” reducing peak infection by up to 70% and delaying peak infection by up to several months. The use of face masks coupled with efficient isolation of infected individuals reduced the overall incidence of infection and sometimes averted epidemics altogether. These interventions must be implemented quickly to be effective. Lockdowns had little effect on COVID-19 dynamics. Our findings provide an evidence base for camp managers planning intervention strategies against COVID-19 or future epidemics.