bluuebunny/crossref_metadata_2025_split huggingface dataset:
Use of Metabolomic Profiling to Understand Variability in Adiposity Changes Following an Intentional Weight Loss Intervention in Older Adults
Authors: Quillen Ellen E. , Beavers Daniel P. , Cox Anderson O’Brien , Furdui Cristina M. , Lee Jingyun , Miller Ryan M. , Wu Hanzhi , Beavers Kristen M. 
Published: September 2020

ABSTRACTIntroductionInter-individual response to dietary interventions remains a major challenge to successful weight loss among older adults. This study applied metabolomics technology to identify small molecule signatures associated with loss of fat mass and overall weight in a cohort of older adults on a nutritionally complete, high protein diet.Methods102 unique metabolites were measured using LC-MS for 38 adults aged 65-80 years randomized to dietary intervention and 36 controls. Metabolite values were analyzed in both baseline plasma samples and samples collected following the six-month dietary intervention to consider both metabolites that could predict response to diet and those that changed in response to diet or weight loss.ResultsEight metabolites changed over intervention at a nominally-significant level: D-pantothenic acid, L-methionine, nicotinate, aniline, melatonin, deoxycarnitine, 6-deoxy-L-galactose, and 10-hydroxydecanoate. Within the intervention group, there was broad variation in achieved weight-loss and DXA-defined changes in total fat and visceral adipose tissue (VAT) mass. Change in VAT mass was significantly associated with baseline abundance of α-aminoadipate (p = 0.0007) and an additional mass spectrometry peak that may represent D-fructose, myo-inositol, mannose, α-D-glucose, allose, D-galactose, D-tagatose, or L-sorbose (p = 0.0001).DiscussionThis hypothesis-generating study reflects the potential of metabolomic biomarkers for the development of personalized dietary interventions.
Host-to-Host Airborne Transmission As a Multiphase Flow Problem For Science-Based Social Distance Guidelines
Authors: Balachandar S. , Zaleski S. , Soldati A. , Ahmadi G. , Bourouiba L. 
Published: September 2020

AbstractCOVID-19 pandemic has strikingly demonstrated how important it is to develop fundamental knowledge related to generation, transport and inhalation of pathogen-laden droplets and their subsequent possible fate as airborne particles, or aerosols, in the context of human to human transmission. It is also increasingly clear that airborne transmission is an important contributor to rapid spreading of the disease. In this paper, we discuss the processes of droplet generation by exhalation, their potential transformation into airborne particles by evaporation, transport over long distances by the exhaled puff and by ambient air turbulence, and final inhalation by the receiving host as interconnected multiphase flow processes. A simple model for the time evolution of droplet/aerosol concentration is presented based on a theoretical analysis of the relevant physical processes. The modeling framework along with detailed experiments and simulations can be used to study a wide variety of scenarios involving breathing, talking, coughing and sneezing and in a number of environmental conditions, as humid or dry atmosphere, confined or open environment. Although a number of questions remain open on the physics of evaporation and coupling with persistence of the virus, it is clear that with a more reliable understanding of the underlying flow physics of virus transmission one can set the foundation for an improved methodology in designing case-specific social distancing and infection control guidelines.
Social Determinants Associated with COVID-19 Mortality in the United States
Authors: Debopadhaya Shayom , Sprague Ariella D. , Mou Hongxi , Benavides Tiburon L. , Ahn Sarah M. , Reschke Cole A. , Erickson John S. , Bennett Kristin P. 
Published: September 2020

AbstractThis study examines social determinants associated with disparities in COVID-19 mortality rates in the United States. Using county-level data, 42 negative binomial mixed models were used to evaluate the impact of social determinants on COVID-19 outcome. First, to identify proper controls, the effect of 24 high-risk factors on COVID-19 mortality rate was quantified. Then, the high-risk terms found to be significant were controlled for in an association study between 41 social determinants and COVID-19 mortality rates. The results describe that ethnic minorities, immigrants, socioeconomic inequalities, and early exposure to COVID-19 are associated with increased COVID-19 mortality, while the prevalence of asthma, suicide, and excessive drinking is associated with decreased mortality. Overall, we recognize that social inequality places disadvantaged groups at risk, which must be addressed through future policies and programs. Additionally, we reveal possible relationships between lung disease, mental health, and COVID-19 that need to be explored on a clinical level.
Unmasking the conversation on masks: Natural language processing for topical sentiment analysis of COVID-19 Twitter discourse
Authors: Sanders Abraham C. , White Rachael C. , Severson Lauren S. , Ma Rufeng , McQueen Richard , Alcântara Paulo Haniel C. , Zhang Yucheng , Erickson John S. , Bennett Kristin P. 
Published: September 2020

AbstractIn this exploratory study, we scrutinize a database of over one million tweets collected from March to July 2020 to illustrate public attitudes towards mask usage during the COVID-19 pandemic. We employ natural language processing, clustering and sentiment analysis techniques to organize tweets relating to mask-wearing into high-level themes, then relay narratives for each theme using automatic text summarization. In recent months, a body of literature has highlighted the robustness of trends in online activity as proxies for the sociological impact of COVID-19. We find that topic clustering based on mask-related Twitter data offers revealing insights into societal perceptions of COVID-19 and techniques for its prevention. We observe that the volume and polarity of mask-related tweets has greatly increased. Importantly, the analysis pipeline presented may be leveraged by the health community for qualitative assessment of public response to health intervention techniques in real time.
The importance of saturating density dependence for predicting SARS-CoV-2 resurgence
Authors: Nightingale E. S. , Brady O. J. ,   CMMID Covid-19 working group, Yakob L. 
Published: September 2020

AbstractSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) associated mortality data from England show evidence for an increasing trend with population density until a saturating level, after adjusting for local age distribution, deprivation, proportion of ethnic minority population and proportion of key workers among the working population. Projections from a mathematical model that accounts for this observation deviate markedly from the current status quo for SARS-CoV-2 models which either assume linearity between density and transmission (30% of models) or no relationship at all (70%). Respectively, these standard model structures over- and under-estimate the delay in infection resurgence following the release of lockdown. Identifying saturation points for given populations and including transmission terms that account for this feature will improve model accuracy and utility for the current and future pandemics.
The influence of temporal predictability on express visuomotor responses
Authors: Contemori Samuele , Loeb Gerald E. , Corneil Brian D. , Wallis Guy , Carroll Timothy J. 
Published: September 2020

ABSTRACTVolitional visuomotor responses in humans are generally thought to manifest 100ms or more after stimulus onset. Under appropriate conditions, however, much faster target-directed responses can be produced at upper limb and neck muscles. These “express” responses have been termed stimulus-locked responses (SLRs) and are proposed to be modulated by visuomotor transformations performed subcortically via the superior colliculus. Unfortunately, for those interested in studying SLRs, these responses have proven difficult to detect consistently across individuals. The recent report of an effective paradigm for generating SLRs in 100% of participants appears to change this. The task required the interception of a moving target that emerged from behind a barrier at a time consistent with the target velocity. Here we aimed to reproduce the efficacy of this paradigm for eliciting SLRs and to test the hypothesis that its effectiveness derives from the predictability of target onset time as opposed to target motionper se. In one experiment, we recorded surface EMG from shoulder muscles as participants made reaches to intercept temporally predictable or unpredictable targets. Consistent with our hypothesis, predictably timed targets produced more frequent and stronger SLRs than unpredictably timed targets. In a second experiment, we compared different temporally predictable stimuli and observed that transiently presented targets produced larger and earlier SLRs than sustained moving targets. Our results suggest that target motion is not critical for facilitating the expression of an SLR and that timing predictability does not rely on extrapolation of a physically plausible motion trajectory. These findings provide support for a mechanism whereby an internal timer, probably located in cerebral cortex, primes the processing of both visual input and motor output within the superior colliculus to produce SLRs.
CUBIC-Cloud: An Integrative Computational Framework Towards Community-driven Whole-Mouse-Brain Mapping
Authors: Mano Tomoyuki , Murata Ken , Kon Kazuhiro , Shimizu Chika , Ono Hiroaki , Shi Shoi , Yamada Rikuhiro G. , Miyamichi Kazunari , Susaki Etsuo A. , Touhara Kazushige , Ueda Hiroki R. 
Published: September 2020

ABSTRACTRecent advancements in tissue clearing technologies have offered unparalleled opportunities for researchers to explore the whole mouse brain at cellular resolution. With the expansion of this experimental technique, however, a scalable and easy-to-use computational tool is in demand to effectively analyze and integrate whole-brain mapping datasets. To that end, here we present CUBIC-Cloud, a cloud-based framework to quantify, visualize and integrate whole mouse brain data. CUBIC-Cloud is a fully automated system where users can upload their whole-brain data, run analysis and publish the results. We demonstrate the generality of CUBIC-Cloud by a variety of applications. First, we investigated brain-wide distribution of PV, Sst, ChAT, Th and Iba1 expressing cells. Second, Aβ plaque deposition in AD model mouse brains were quantified. Third, we reconstructed neuronal activity profile under LPS-induced inflammation by c-Fos immunostaining. Last, we show brain-wide connectivity mapping by pseudo-typed Rabies virus. Together, CUBIC-Cloud provides an integrative platform to advance scalable and collaborative whole-brain mapping.
Combinatorial Intracellular Delivery Screening (CIDS) of Anticancer Drugs
Authors: Sola-Barrado Belén , Leite Diana Moreira , Scarpa Edoardo , Duro-Castano Aroa , Battaglia Giuseppe 
Published: September 2020

AbstractConventional drug solubilisation strategies limit the understanding of the full potential of poorly water-soluble drugs during drug screening. Here, we propose a screening approach in which poorly water-soluble drugs are entrapped in poly (2-(methacryloyloxyethyl phosphorylcholine)-poly(2-(diisopropylaminoethyl methacryate) (PMPC-PDPA) polymersomes (POs) to enhance drug solubility and facilitate intracellular delivery. By using a human paediatric glioma cell model, we demonstrated that PMPC-PDPA POs mediated intracellular delivery of cytotoxic and epigenetic drugs by receptor-mediated endocytosis. Additionally, when delivered in combination, drug-loaded PMPC-PDPA POs triggered both an enhanced drug efficacy and synergy compared to that of a conventional combinatorial screening. Hence, our comprehensive synergy analysis illustrates that our screening methodology, in which PMPC-PDPA POs are used for intracellular co-delivery of drugs, allows us to identify potent synergistic profiles of anticancer drugs.
Innate immune signaling and sex differences contribute to neurocognitive impairment, neuroinflammation, and mitochondrial rewiring in a mouse model of Gulf War illness
Authors: Bryant Joshua D. , Kodali Maheedhar , Shuai Bing , Menissy Saeed S. , Graves Paige J. , Shetty Ashok K. , West Laura Ciaccia , West A. Phillip 
Published: September 2020

AbstractGulf War Illness (GWI) is a chronic, multi-symptom disorder affecting approximately 30 percent of the nearly 700,000 veterans of the 1991 Persian Gulf War. Recent studies have revealed that GWI-related chemical (GWIC) exposure promotes immune activation and metabolic rewiring, which correlate with neurocognitive impairments and other symptoms of GWI. However, the molecular mechanisms and signaling pathways linking GWIC to inflammation, metabolic alterations, and neurological symptoms remain unclear. Mitochondrial dysfunction has been documented in veterans with GWI and rodent models, and because mitochondria are key immune regulators, we hypothesized that alterations to mitochondria-immune crosstalk could contribute to the development of GWI-related symptoms. Here we show that acute exposure of murine macrophages to GWIC alters mitochondrial respiration and potentiates innate immune signaling and inflammatory cytokine secretion. Using an established mouse model of GWI, we report that neurobehavioral changes, neuroinflammation, and mitochondrial protein rewiring are attenuated in mice lacking the cyclic GMP-AMP synthase (cGAS)-Stimulator of Interferon Genes (STING) and NOD-, LRR- or pyrin domain-containing protein 3 (NLRP3) innate immune pathways. Finally, we report sex differences in response to GWIC, with female mice showing more pronounced cognitive impairment, neuroinflammation, and mitochondrial protein alterations in the brain compared to male mice. Our results provide novel information on sex differences in this model and suggest that STING and NLRP3 are key mediators of the cognitive impairment, inflammation, and mitochondrial dysfunction observed in GWI.
Inter-subject pattern analysis for multivariate group analysis of functional neuroimaging. A unifying formalization
Authors: Wang Qi , Artières Thierry , Takerkart Sylvain 
Published: September 2020

AbstractBackground and objectiveIn medical imaging, population studies have to overcome the differences that exist between individuals to identify invariant image features that can be used for diagnosis purposes. In functional neuroimaging, an appealing solution to identify neural coding principles that hold at the population level is inter-subject pattern analysis, i.e. to learn a predictive model on data from multiple subjects and evaluate its generalization performance on new subjects. Although it has gained popularity in recent years, its widespread adoption is still hampered by the blatant lack of a formal definition in the literature. In this paper, we precisely introduce the first principled formalization of inter-subject pattern analysis targeted at multivariate group analysis of functional neuroimaging.MethodsWe propose to frame inter-subject pattern analysis as a multi-source transductive transfer question, thus grounding it within several well defined machine learning settings and broadening the spectrum of usable algorithms. We describe two sets of inter-subject brain decoding experiments that use several open datasets: a magnetoencephalography study with 16 subjects and a functional magnetic resonance imaging paradigm with 100 subjects. We assess the relevance of our framework by performing model comparisons, where one brain decoding model exploits our formalization while others do not.ResultsThe first set of experiments demonstrates the superiority of a brain decoder that uses subject-by-subject standardization compared to state of the art models that use other standardization schemes, making the case for the interest of the transductive and the multi-source components of our formalization The second set of experiments quantitatively shows that, even after such transformation, it is more difficult for a brain decoder to generalize to new participants rather than to new data from participants available in the training phase, thus highlighting the transfer gap that needs to be overcome.ConclusionThis paper describes the first formalization of inter-subject pattern analysis as a multi-source transductive transfer learning problem. We demonstrate the added value of this formalization using proof-of-concept experiments on several complementary functional neuroimaging datasets. This work should contribute to popularize inter-subject pattern analysis for functional neuroimaging population studies and pave the road for future methodological innovations.
X-ray mediated scintillation increases synaptic activity via Cerium-doped LSO and Channelrhodopsin-2
Authors: Bartley Aundrea F. , Fischer Máté , Bagley Micah E. , Barnes Justin A. , Burdette Mary K. , Cannon Kelli E. , Bolding Mark S. , Foulger Stephen H. , McMahon Lori L. , Weick Jason P. , Dobrunz Lynn E. 
Published: September 2020

AbstractOptogenetics is a widely used tool for studying neural circuits. However, non-invasive methods for light delivery in the brain are needed to avoid physical damage typically caused by intracranial insertion of light guides. An innovative strategy could employ X-ray activation of radioluminescent particles (RLPs) to emit localized light. We previously reported that RLPs composed of cerium doped lutetium oxyorthosilicate (LSO:Ce), an inorganic scintillator that emits blue light, are biocompatible with neuronal function and synaptic transmission. However, little is known about the consequences of acute X-ray exposure on synaptic function and long-term plasticity. Furthermore, modulation of neuronal or synaptic function by X-ray induced radioluminescence from RLPs has not yet been demonstrated. Here we show that 30 minutes of X-ray exposure at a rate of 0.042 Gy/second caused no change in the strength of basal glutamatergic transmission during extracellular dendritic field recordings in mouse hippocampal slices. Additionally, long-term potentiation (LTP), a robust measure of synaptic integrity, was able to be induced after X-ray exposure and expressed at a magnitude not different from control conditions (absence of X-rays). This is important as synaptic plasticity is critical to learning and memory. Next, we used molecular and electrophysiological approaches to determine if X-ray dependent radioluminescence emitted from RLPs can activate light sensitive proteins. We found that X-ray stimulation of RLPs elevated cAMP levels in HEK293T cells expressing OptoXR, a chimeric opsin receptor that combines the extracellular light-sensitive domain of channelrhodopsin-2 (ChR2) with an intracellular second messenger signaling cascade. This demonstrates that X-ray radioluminescence from LSO:Ce particles can activate OptoXR. Next, we tested whether X-ray activation of the RLPs can enhance synaptic activity in whole-cell recordings from hippocampal neurons expressing ChR2, both in cell culture and acute hippocampal slices. Importantly, X-ray radioluminescence caused an increase in the frequency of spontaneous excitatory postsynaptic currents (sEPSCs) in both systems, indicating activation of ChR2 and excitation of neurons. Together, our results show that X-ray activation of LSO:Ce particles can heighten cellular and synaptic function. The combination of LSO:Ce inorganic scintillators and X-rays is therefore a viable method for optogenetics as an alternative to more invasive light delivery methods.
cFos ensembles in the dentate gyrus rapidly segregate over time and do not form a stable map of space
Authors: Lamothe-Molina Paul J. , Franzelin Andreas , Beck Lennart , Li Dong , Auksutat Lea , Fieblinger Tim , Laprell Laura , Alhbeck Joachim , Gee Christine E. , Kneussel Matthias , Engel Andreas K. , Hilgetag Claus C. , Morellini Fabio , Oertner Thomas G. 
Published: September 2020

AbstractTransgenic cFos reporter mice are used to identify and manipulate neurons that store contextual information during fear learning. It is not clear, however, how spatial information acquired over several training days is integrated in the hippocampus. Using a water maze task, we observed that cFos expression patterns in the dentate gyrus are temporally unstable and shift daily. Surprisingly, cFos patterns did not get more stable with increasing spatial memory precision. Despite the fact that cFos was no longer expressed, optogenetic inhibition of neurons that expressed cFos on the first training day affected performance days later. Triggered by training, ΔFosB accumulates and provides a negative feedback mechanism that makes the cFos ensemble in the dentate gyrus dependent on the history of activity. Shifting cFos expression to a different set of granule cells every day may aid the formation of episodic memories.
Pseudouridine synthases modify human pre-mRNA co-transcriptionally and affect splicing
Authors: Martinez Nicole M. , Su Amanda , Nussbacher Julia K. , Burns Margaret C. , Schaening Cassandra , Sathe Shashank , Yeo Gene W. , Gilbert Wendy V. 
Published: September 2020

AbstractEukaryotic messenger RNAs are extensively decorated with modified nucleotides and the resulting epitranscriptome plays important regulatory roles in cells1. Pseudouridine (Ψ) is a modified nucleotide that is prevalent in human mRNAs and can be dynamically regulated2–5. However, it is unclear when in their life cycle RNAs become pseudouridylated and what the endogenous functions of mRNA pseudouridylation are. To determine if pseudouridine is added co-transcriptionally, we conducted pseudouridine profiling2on chromatin-associated RNA to reveal thousands of intronic pseudouridines in nascent pre-mRNA at locations that are significantly associated with alternatively spliced exons, enriched near splice sites, and overlap hundreds of binding sites for regulatory RNA binding proteins. Multiple distinct pseudouridine synthases with tissue-specific expression pseudouridylate pre-mRNA sites, and genetic manipulation of the predominant pre-mRNA modifying pseudouridine synthases PUS1, PUS7 and RPUSD4 induced widespread changes in alternative splicing in cells, supporting a role for pre-mRNA pseudouridylation in alternative splicing regulation. Consistently, we find that individual pseudouridines identified in cells are sufficient to directly affect splicingin vitro. Together with previously observed effects of artificial pseudouridylation on RNA-RNA6–8and RNA-protein9–11interactions that are relevant for splicing, our results demonstrate widespread co-transcriptional pre-mRNA pseudouridylation and establish the enormous potential for this RNA modification to control human gene expression.