bluuebunny/crossref_metadata_2025_split huggingface dataset:
Socioeconomic inequalities across life and premature mortality from 1971 to 2016: findings from three British birth cohorts born in 1946, 1958, and 1970
Authors: Fluharty Meg E , Hardy Rebecca , Ploubidis George B. , Pongiglione Benedetta , Bann David 
Published: April 2020

AbstractIntroductionDisadvantaged socioeconomic position (SEP) in early and adult life has been repeatedly associated with premature mortality. However, it is unclear whether these inequalities differ across time, nor if they are consistent across different SEP indicators.MethodsBritish birth cohorts born in 1946, 1958 and 1970 were used, and multiple SEP indicators in early and adult life were examined. Deaths were identified via national statistics or notifications. Cox proportional hazard models were used to estimate associations between SEP indicators and mortality risk—from 26-43 (n=40,784), 26-58 (n=35,431), and 26-70 years (n=5,353).ResultsMore disadvantaged SEP was associated with higher mortality risk—magnitudes of association were similar across cohort and each SEP indicator. For example, hazards ratios (95% CI) between 26-43 years comparing lowest to highest father’s social class were 2.74 (1.02—7.32) in 1946c, 1.66 (1.03—2.69) in 1958c, and 1.94 (1.20—3.15) in 1970c. Childhood social class, adult social class, and housing tenure were each independently associated with mortality risk.ConclusionsSocioeconomic circumstances in early and adult life appear to have had persisting associations with premature mortality from 1971—2016. This reaffirms the need to address socioeconomic factors across life to reduce inequalities in survival to older age.
New approximations, and policy implications, from a delayed dynamic model of a fast pandemic
Authors: Vyasarayani C. P. , Chatterjee Anindya 
Published: April 2020

AbstractWe study an SEIQR (Susceptible-Exposed-Infectious-Quarantined-Recovered) model for an infectious disease, with time delays for latency and an asymptomatic phase. For fast pandemics where nobody has prior immunity and everyone has immunity after recovery, the SEIQR model decouples into two nonlinear delay differential equations (DDEs) with five parameters. One parameter is set to unity by scaling time. The subcase of perfect quarantining and zero self-recovery before quarantine, with two free parameters, is examined first. The method of multiple scales yields a hyperbolic tangent solution; and a long-wave approximation yields a first order ordinary differential equation (ODE). With imperfect quarantining and nonzero self-recovery, the long-wave approximation is a second order ODE. These three approximations each capture the full outbreak, from infinitesimal initiation to final saturation. Low-dimensional dynamics in the DDEs is demonstrated using a six state non-delayed reduced order model obtained by Galerkin projection. Numerical solutions from the reduced order model match the DDE over a range of parameter choices and initial conditions. Finally, stability analysis and numerics show how correctly executed time-varying social distancing, within the present model, can cut the number of affected people by almost half. Alternatively, faster detection followed by near-certain quarantining can potentially be even more effective.
Comparison of different exit scenarios from the lock-down for COVID-19 epidemic in the UK and assessing uncertainty of the predictions
Authors: Zhigljavsky Anatoly , Whitaker Roger , Fesenko Ivan , Kremnizer Kobi , Noonan Jack 
Published: April 2020

AbstractWe model further development of the COVID-19 epidemic in the UK given the current data and assuming different scenarios of handling the epidemic. In this research, we further extend the stochastic model suggested in [1] and incorporate in it all available to us knowledge about parameters characterising the behaviour of the virus and the illness induced by it. The models we use are flexible, comprehensive, fast to run and allow us to incorporate the following:
time-dependent strategies of handling the epidemic;spatial heterogeneity of the population and heterogeneity of development of epidemic in different areas;special characteristics of particular groups of people, especially people with specific medical pre-histories and elderly.Standard epidemiological models such as SIR and many of its modifications are not flexible enough and hence are not precise enough in the studies that requires the use of the features above. Decision-makers get serious benefits from using better and more flexible models as they can avoid of nuanced lock-downs, better plan the exit strategy based on local population data, different stages of the epidemic in different areas, making specific recommendations to specific groups of people; all this resulting in a lesser impact on economy, improved forecasts of regional demand upon NHS allowing for intelligent resource allocation.In this work, we investigate the sensitivity of the model to all its parameters while considering several realistic scenarios of what is likely to happen with the dynamics of the epidemic after the lock-down, which has started on March 23, is lifted.The main findings from this research are the following
very little gain, in terms of the projected hospital bed occupancy and expected numbers of death, of continuing the lock-down beyond April 13, provided the isolation of older and vulnerable people continues and the public carries on some level of isolation in the next 2-3 months, see Section 3.1;in agreement with [1], isolation of the group of vulnerable people during the next 2-3 months should be one of the main priorities, see Section 3.2;it is of high importance that the whole population carries on some level of isolation in the next 2-3 months, see Section 3.5;the timing of the current lock-down seems to be very sensible in areas like London where the epidemic has started to pick up by March 23; in such areas the second wave of epidemic is not expected, see figures in Sections 2.2 and 3;the epidemic should almost completely finish in July, no global second wave should be expected, except areas where the first wave is almost absent, see Section 3.4.
Between Geography and Demography: Key Interdependencies and Exit Mechanisms for Covid-19
Authors: Scala Antonio , Flori Andrea , Spelta Alessandro , Brugnoli Emanuele , Cinelli Matteo , Quattrociocchi Walter , Pammolli Fabio 
Published: April 2020

AbstractWe develop a minimal compartmental model to analyze policies on mobility restriction in Italy during the Covid-19 outbreak. Our findings show that a premature lockdown barely shifts the epidemic in time: moreover, beyond a critical value of the lockdown strength, an epidemic that seems to be quelled fully recovers after lifting the restrictions. We investigate the effects on lockdown scenarios and exit strategies by introducing heterogeneities in the model. In particular, we consider Italian regions as separate administrative entities in which social interactions through different age classes occur. We find that, due to the sparsity of the mobility matrix, epidemics develop independently in different regions once the outbreak starts. Moreover, after the epidemics ha started, the influence of contacts with other regions becomes soon irrelevant. Sparsity might be responsible for the observed delays among different regions. Analogous arguments apply to the world/countries scenario. We also find that disregarding the structure of social contacts could lead to severe underestimation of the post-lockdown effects. Nevertheless, age class based strategies can help to mitigate rebound effects with milder strategies. Finally, we point out that these results can be generalized beyond this particular model by providing a description of the effects of key parameters on non-medical epidemic mitigation strategies.
Generation of a novel SARS-CoV-2 sub-genomic RNA due to the R203K/G204R variant in nucleocapsid: homologous recombination has potential to change SARS-CoV-2 at both protein and RNA level
Authors: Leary Shay , Gaudieri Silvana , Parker Matthew D. , Chopra Abha , James Ian , Pakala Suman , Alves Eric , John Mina , Lindsey Benjamin B. , Keeley Alexander J , Rowland-Jones Sarah L. , Swanson Maurice S. , Ostrov David A. , Bubenik Jodi L. , Das Suman , Sidney John , Sette Alessandro ,   COVID-19 Genomics UK (COG-UK) consortium, de Silva Thushan I. , Phillips Elizabeth , Mallal Simon 
Published: April 2020

AbstractBackgroundGenetic variations across the SARS-CoV-2 genome may influence transmissibility of the virus and the host’s anti-viral immune response, in turn affecting the frequency of variants over-time. In this study, we examined the adjacent amino acid polymorphisms in the nucleocapsid (R203K/G204R) of SARS-CoV-2 that arose on the background of the spike D614G change and describe how strains harboring these changes became dominant circulating strains globally.MethodsDeep sequencing data of SARS-CoV-2 from public databases and from clinical samples were analyzed to identify and map genetic variants and sub-genomic RNA transcripts across the genome.ResultsSequence analysis suggests that the three adjacent nucleotide changes that result in the K203/R204 variant have arisen by homologous recombination from the core sequence (CS) of the leader transcription-regulating sequence (TRS) rather than by stepwise mutation. The resulting sequence changes generate a novel sub-genomic RNA transcript for the C-terminal dimerization domain of nucleocapsid. Deep sequencing data from 981 clinical samples confirmed the presence of the novel TRS-CS-dimerization domain RNA in individuals with the K203/R204 variant. Quantification of sub-genomic RNA indicates that viruses with the K203/R204 variant may also have increased expression of sub-genomic RNA from other open reading frames.ConclusionsThe finding that homologous recombination from the TRS may have occurred since the introduction of SARS-CoV-2 in humans resulting in both coding changes and novel sub-genomic RNA transcripts suggests this as a mechanism for diversification and adaptation within its new host.
Environmental enrichment alleviates the deleterious effects of stress in experimental autoimmune encephalomyelitis
Authors: Fournier Antoine Philippe , Baudron Erwan , Wagnon Isabelle , Aubert Philippe , Vivien Denis , Neunlist Michel , Bardou Isabelle , Docagne Fabian 
Published: April 2020

ABSTRACTClinical observations support the hypothesis that stressful events increase relapse occurrence in multiple sclerosis patients, while stress-reduction strategies can modulate this effect. However, a direct cause-effect relationship between stress level and relapse cannot be firmly established from these data. The purpose of this work was to address whether modulation of stress could interfere with symptom relapse in an animal model of multiple sclerosis with relapsing-remitting course. We report that repeated acute stress induced a twofold increase in relapse incidence in experimental autoimmune encephalomyelitis. On the other hand, environmental enrichment reduced relapse incidence and severity, and reversed the effects of repeated acute stress. These data provide the platform for further studies on the biological processes that link stress and multiple sclerosis relapses in a suitable animal model.
Competition for glutamate between NMDA and AMPA receptors prevents runaway synaptic dynamics
Authors: Guo Qingchen 
Published: April 2020

AbstractHomeostatic plasticity is an important guarantee for proper neural function. However, long term potentiation (LTP) was thought of as positive feedback in Hebbian plasticity. In this condition, synapse after potentiation is prone to be further potentiated. This can cause runaway dynamics of synapse and affect the stability of neural network. In order to prevent runaway synaptic dynamics, negative feedback is needed. Upon induction of LTP, the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors was increased in the postsynaptic density (PSD). Due to the competition for glutamate between AMPA receptors and N-Methyl-D-aspartic acid (NMDA) receptors, the number of opened NMDA receptor channels will reduce. Since the induction of LTP is NMDA receptors dependent, reduction of the number of activated NMDA receptors will increase the threshold of LTP induction. So the LTP of synapse itself can form a negative feedback to LTP induction. To test this hypothesis, a synaptic model with NMDA receptors and AMPA receptors coexisted was developed. When the number of AMPA receptors was increased in the PSD, the number of opened NMDA receptors was reduced though the same number of glutamate was released from presynaptic terminal. This will increase the threshold of further LTP induction and stability of synapse and neural network.
Nanovibrational stimulation of mesenchymal stem cells induces therapeutic reactive oxygen species and inflammation for 3D bone tissue engineering
Authors: Orapiriyakul Wich , Tsimbouri Penelope M. , Childs Peter G. , Campsie Paul , Wells Julia , Fernandez-Yague Marc , Burgess Karl , Tanner K. Elizabeth , Tassieri Manlio , Meek R.M. Dominic , Vassalli Massimo , Biggs Manus JP , Salmerón-Sánchez Manuel , Oreffo Richard O.C. , Reid Stuart , Dalby Matthew J 
Published: April 2020

ABSTRACTThere is a pressing clinical need to develop cell-based bone therapies due to a lack of viable, autologous bone grafts and a growing demand for bone grafts in musculoskeletal surgery. Such therapies can be tissue engineered and cellular, such as osteoblasts combined with a material scaffold. Because mesenchymal stem cells (MSCs) are both available and fast growing compared to mature osteoblasts, therapies that utilise these progenitor cells are particularly promising. We have developed a nanovibrational bioreactor that can convert MSCs into bone-forming osteoblasts in 2D and 3D but the mechanisms involved in this osteoinduction process remain unclear. Here, to elucidate this mechanism, we use increasing vibrational amplitude, from 30 nm (N30) to 90 nm (N90) amplitudes at 1000 Hz, and assess MSC metabolite, gene and protein changes. These approaches reveal that dose-dependent changes occur in MSCs’ responses to increased vibrational amplitude, particularly in adhesion and mechanosensitive ion channel expression, and that energetic metabolic pathways are activated, leading to low-level reactive oxygen species (ROS) production and to low-level inflammation, as well as to ROS- and inflammation-balancing pathways. These events are analogous to those that occur in the natural bone-healing processes. We have also developed a tissue engineered MSC-laden scaffold designed using cells’ mechanical memory, driven by the stronger N90 stimulation. These new mechanistic insights and cell-scaffold design are underpinned by a process that is free of inductive chemicals.
Multiobjective Optimization Identifies Cancer-Selective Combination Therapies
Authors: Pulkkinen Otto I. , Gautam Prson , Mustonen Ville , Aittokallio Tero 
Published: April 2020

ABSTRACTCombinatorial therapies are required to treat patients with advanced cancers that have become resistant to monotherapies through rewiring of redundant pathways. Due to a massive number of potential drug combinations, there is a need for systematic approaches to identify safe and effective combinations for each patient, using cost-effective methods. Here, we developed an exact multiobjective optimization method for identifying pairwise or higher-order combinations that show maximal cancer-selectivity. The prioritization of patient-specific combinations is based on Pareto-optimization in the search space spanned by the therapeutic and nonselective effects of combinations. We demonstrate the performance of the method in the context of BRAF-V600E melanoma treatment, where the optimal solutions predicted a number of co-inhibition partners for vemurafenib, a selective BRAF-V600E inhibitor, approved for advanced melanoma. We experimentally validated many of the predictions in BRAF-V600E melanoma cell line, and the results suggest that one can improve selective inhibition of BRAF-V600E melanoma cells by combinatorial targeting of MAPK/ERK and other compensatory pathways using pairwise and third-order drug combinations. Our mechanism-agnostic optimization method is widely applicable to various cancer types, and it takes as input only measurements of a subset of pairwise drug combinations, without requiring target information or genomic profiles. Such data-driven approaches may become useful for functional precision oncology applications that go beyond the cancer genetic dependency paradigm to optimize cancer-selective combinatorial treatments.
Traumatic Joint Injury Induces Acute Catabolic Bone Turnover Concurrent with Articular Cartilage Damage in a Rat Model of Post-Traumatic Osteoarthritis
Authors: Maerz Tristan , Newton Michael D. , Fleischer Mackenzie , Hartner Samantha E. , Gawronski Karissa , Junginger Lucas , Baker Kevin C. 
Published: April 2020

ABSTRACTObjectiveAssess acute alterations in bone turnover, microstructure, and histomorphometry following noninvasive anterior cruciate ligament rupture (ACLR).MethodsTwelve female Lewis rats were randomized to receive noninvasive ACLR or Sham loading (n=6/group). In vivoμCT was performed at 3, 7, 10, and 14 days post-injury to quantify compartment-dependent subchondral (SCB) and epiphyseal trabecular bone remodeling. Near-infrared (NIR) molecular imaging was used to measurein vivobone anabolism (800 CW BoneTag) and catabolism (Cat K 680 FAST). Metaphyseal bone remodeling and articular cartilage morphology was quantified usingex vivoμCT and contrast-enhanced µCT, respectively. Calcein-based dynamic histomorphometry was used to quantify bone formation. OARSI scoring was used to assess joint degeneration, and osteoclast number was quantified on TRAP stained-sections.ResultsACLR induced acute catabolic bone remodeling in subchondral, epiphyseal, and metaphyseal compartments. Thinning of medial femoral condyle (MFC) SCB was observed as early as 7 days post-injury, while lateral femoral condyles (LFC) exhibited SCB gains. Trabecular thinning was observed in MFC epiphyseal bone, with minimal changes to LFC. NIR imaging demonstrated immediate and sustained reduction of bone anabolism (∼15-20%), and a ∼32% increase in bone catabolism at 14 days, compared to contralateral limbs. These findings were corroborated by reduced bone formation rate and increased osteoclast numbers, observed histologically. ACLR-injured femora had significantly elevated OARSI score, cartilage thickness, and cartilage surface deviation.ConclusionACL rupture induces immediate and sustained reduction of bone anabolism and overactivation of bone catabolism, with mild-to-moderate articular cartilage damage at 14 days post-injury.
Discovery of pharmaceutically-targetable pathways and prediction of survivorship for pneumonia and sepsis patients from the view point of ensemble gene noise
Authors: de Jong Tristan , Guryev Victor , Moshkin Yury M. 
Published: April 2020

AbstractFinding novel biomarkers for human pathologies and predicting clinical outcomes for patients is rather challenging. This stems from the heterogenous response of individuals to disease which is also reflected in the inter-individual variability of gene expression responses. This in turn obscures differential gene expression analysis (DGE). In the midst of the COVID-19 pandemic, we wondered whether an alternative to DGE approaches could be applied to dissect the molecular nature of a host-response to infection exemplified here by an analysis of H1N1 influenza, community/hospital acquired pneumonia (CAP) and sepsis. To this end, we turned to the analysis of ensemble gene noise. Ensemble gene noise, as we defined it here, represents a variance within an individual for a collection of genes encoding for either members of known biological pathways or subunits of annotated protein complexes. From the law of total variance, ensemble gene noise depends on the stoichiometry of the ensemble genes’ expression and on their average noise (variance). Thus, rather than focusing on specific genes, ensemble gene noise allows for the holistic identification and interpretation of gene expression disbalance on the level of gene networks and systems. Comparing H1N1, CAP and sepsis patients we spotted common disturbances in a number of pathways/protein complexes relevant to the sepsis pathology which lead to an increase in the ensemble gene noise. Among others, these include mitochondrial respiratory chain complex I and peroxisomes which could be readily targeted for adjuvant treatment by methylene blue and 4-phenylbutyrate respectively. Finally, we showed that ensemble gene noise could be successfully applied for the prediction of clinical outcome, namely mortality, of CAP and sepsis patients. Thus, we conclude that ensemble gene noise represents a promising approach for the investigation of molecular mechanisms of a pathology through a prism of alterations in coherent expression of gene circuits.
Short-chain fatty acid production by gut microbiota from children with obesity is linked to bacterial community composition and prebiotic choice
Authors: Holmes Zachary C. , Silverman Justin D. , Dressman Holly K. , Wei Zhengzheng , Dallow Eric P. , Armstrong Sarah C. , Seed Patrick C. , Rawls John F. , David Lawrence A. 
Published: April 2020

AbstractPediatric obesity remains a public health burden and continues to increase in prevalence. The gut microbiota plays a causal role in obesity and is a promising therapeutic target. Specifically, the microbial production of short-chain fatty acids (SCFA) from the fermentation of otherwise indigestible dietary carbohydrates may protect against pediatric obesity and metabolic syndrome. Still, it has not been demonstrated that therapies involving microbiota-targeting carbohydrates, known as prebiotics, will enhance gut bacterial SCFA production in children and adolescents with obesity (age 10-18). Here, we used an in vitro system to examine the SCFA production by fecal microbiota from 17 children with obesity when exposed to five different commercially available over-the-counter (OTC) prebiotic supplements. We found microbiota from all 17 patients actively metabolized most prebiotics. Still, supplements varied in their acidogenic potential. Significant inter-donor variation also existed in SCFA production, which 16S rRNA sequencing supported as being associated with differences in the host microbiota composition. Last, we found that neither fecal SCFA concentration, microbiota SCFA production capacity, nor markers of obesity positively correlated with one another. Together, these in vitro findings suggest the hypothesis that OTC prebiotic supplements may be unequal in their ability to stimulate SCFA production in children and adolescents with obesity, and that the most acidogenic prebiotic may differ across individuals.IMPORTANCEPediatric obesity remains a major public health problem in the US, where 17% of children and adolescents are obese, and rates of pediatric ‘severe obesity’ are increasing. Children and adolescents with obesity face higher health risks, and non-invasive therapies for pediatric obesity often have limited success. The human gut microbiome has been implicated in adult obesity, and microbiota-directed therapies can aid weight loss in adults with obesity. However, less is known about the microbiome in pediatric obesity, and microbiota-directed therapies are understudied in children and adolescents. Our research has two important findings: 1) dietary prebiotics (fiber) cause the microbiota from adolescents with obesity to produce more SCFA, and 2) the effectiveness of each prebiotic is donor-dependent. Together, these findings suggest that prebiotic supplements could help children and adolescents with obesity, but that these therapies may not be one-size-fits-all.