bluuebunny/crossref_metadata_2025_split huggingface dataset:
Model-based prediction of spatial gene expression via generative linear mapping
Authors: Okochi Yasushi , Sakaguchi Shunta , Nakae Ken , Kondo Takefumi , Naoki Honda 
Published: May 2020

AbstractDecoding spatial transcriptomes from single-cell RNA sequencing (scRNA-seq) data has become a fundamental technique for understanding multicellular systems; however, existing computational methods lack both accuracy and biological interpretability due to their model-free frameworks. Here, we introduced Perler, a model-based method to integrate scRNA-seq data with referencein situhybridization (ISH) data. To calibrate differences between these datasets, we developed a biologically interpretable model that uses generative linear mapping based on a Gaussian-mixture model using the Expectation-Maximization algorithm. Perler accurately predicted the spatial gene expression ofDrosophilaembryos, zebrafish embryos, mammalian liver, and mouse visual cortex from scRNA-seq data. Furthermore, the reconstructed transcriptomes did not over-fit the ISH data and preserved the timing information of the scRNA-seq data. These results demonstrated the generalizability of Perler for dataset integration, thereby providing a biologically interpretable framework for accurate reconstruction of spatial transcriptomes in any multicellular system.
Avoiding COVID-19: Aerosol Guidelines
Authors: Evans Matthew J. 
Published: May 2020

AbstractThe COVID-19 pandemic has brought into sharp focus the need to understand respiratory virus transmission mechanisms. In preparation for an anticipated influenza pandemic, a substantial body of literature has developed over the last few decades showing that the short-range aerosol route is an important, though often neglected transmission path. We develop a simple mathematical model for COVID-19 transmission via aerosols, apply it to known outbreaks, and present quantitative guidelines for ventilation and occupancy in the workplace.
Flattening the COVID 19 curve in susceptible forest indigenous tribes using SIR model
Authors: Adwibowo Andrio 
Published: May 2020

AbstractCOVID 19 is a global threat and globally spreading. The international cooperation involving indigenous peoples and local communities is urgently required in joint prevention to control the epidemic. Currently, many indigenous populations are continuing to face COVID 19. This study is concerned about the dynamic of COVID 19 pandemic among indigenous populations living in the remote Amazon rainforest enclaves. Using the Susceptible Infectious Recovered (SIR) model, the spread of the COVID 19 under 3 intervention scenarios (low, moderate, high) is simulated and predicted in indigenous tribe populations. The SIR model forecasts that without intervention, the epidemic peak may reach within 1020 days. Nonetheless the peak can be reduced with strict interventions. Under low intervention, the COVID 19 cases are reduced to 73% and 56% of the total populations. While, in the scenario of high intervention, the COVID 19 peaks can be reduced to values ranging from 53% to 15%. To conclude, the simulated interventions tested by SIR model have reduced the pandemic peak and flattened the COVID 19 curve in indigenous populations. Nonetheless, it is mandatory to strengthen all mitigation efforts, reduce exposures, and decrease transmission rate as possible for COVID 19 containment.
Effects of Government Mandated Social Distancing Measures on Cumulative Incidence of COVID-19 in the United States and its Most Populated Cities
Authors: Krishnamachari Bhuma , Morris Alexander , Zastrow Diane , Dsida Andrew , Harper Brian , Santella Anthony J. 
Published: May 2020

AbstractCOVID-19, caused by the SARS-CoV-2 virus, has quickly spread throughout the world, necessitating assessment of the most effective containment methods. Very little research exists on the effects of social distancing measures on this pandemic. The purpose of this study was to examine the effects of government implemented social distancing measures on the cumulative incidence rates of COVID-19 in the United States on a state level, and in the 25 most populated cities, while adjusting for socio-demographic risk factors. The social distancing variables assessed in this study were: days to closing of non-essential business; days to stay home orders; days to restrictions on gathering, days to restaurant closings and days to school closing. Using negative binomial regression, adjusted rate ratios and 95% confidence intervals were calculated comparing two levels of a binary variable: “above median value,” and “median value and below” for days to implementing a social distancing measure. For city level data, the effects of these social distancing variables were also assessed in high (above median value) vs low (median value and below) population density cities. For the state level analysis, days to school closing was associated with cumulative incidence, with an adjusted rate ratio of 1.59 (95% CI:1.03,2.44), p=0.04 at 35 days. Some results were counterintuitive, including inverse associations between cumulative incidence and days to closure of non-essential business and restrictions on gatherings. This finding is likely due to reverse causality, where locations with slower growth rates initially chose not to implement measures, and later implemented measures when they absolutely needed to respond to increasing rates of infection. Effects of social distancing measures seemed to vary by population density in cities. Our results suggest that the effect of social distancing measures may differ between states and cities and between locations with different population densities. States and cities need individual approaches to containment of an epidemic, with an awareness of their own structure in terms of crowding and socio-economic variables. In an effort to reduce infection rates, cities may want to implement social distancing in advance of state mandates.
Rate Estimation and Identification of COVID-19 Infections: Towards Rational Policy Making During Early and Late Stages of Epidemics
Authors: Beigel Richard , Kasif Simon 
Published: May 2020

AbstractPandemics have a profound impact on our world, causing loss of life, affecting our culture and historically shaping our genetics. The response to a pandemic requires both resilience and imagination. It has been clearly documented that obtaining an accurate estimate and trends of the actual infection rate and mortality risk are very important for policy makers and medical professionals. One cannot estimate mortality rates without an accurate assessment of the number of infected individuals in the population. This need is also aligned with identifying the infected individuals so they can be properly treated, monitored and tracked. However, accurate estimation of the infection rate, locally, geographically and nationally is important independently. These infection rate estimates can guide policy makers at both state, national or world level to achieve a better management of risk to society. The decisions facing policy makers are very different during early stages of an emerging epidemic where the infection rate is low, middle stages where the rate is rapidly climbing, and later stages where the epidemic curve has flattened to a low and relatively sustainable rate. In this paper we provide relatively efficient pooling methods to both estimate infection rates and identify infected individuals for populations with low infection rates. These estimates may provide significant cost reductions for testing in rural communities, third world countries and other situations where the cost of testing is expensive or testing is not widely available. As we prepare for the second wave of the pandemic this line of work may provide new solutions for both the biomedical community and policy makers at all levels.
An intriguing characteristic of enhancer-promoter interactions
Authors: Talukder Amlan , Hu Haiyan , Li Xiaoman 
Published: May 2020

ABSTRACTIt is still challenging to predict interacting enhancer-promoter pairs (IEPs), partially because of our limited understanding of their characteristics. To understand IEPs better, here we studied the IEPs in nine cell lines and nine primary cell types. We observed that one enhancer is likely to interact with either none or all of the target genes of another enhancer. This observation implies that enhancers form clusters, and every enhancer in the same cluster synchronously interact with almost every member of a set of genes and only this set of genes. We perceived that an enhancer can be up to two mega base pairs away from other enhancers in the same cluster. We also noticed that although a fraction of these clusters of enhancers do overlap with super-enhancers, the majority of the enhancer clusters are different from the known super-enhancers. Our study showed a new characteristic of IEPs, which may shed new light on distal gene regulation and the identification of IEPs.
Coupling between slow-waves and sharp-wave ripples organizes distributed neural activity during sleep in humans
Authors: Skelin Ivan , Zhang Haoxin , Zheng Jie , Ma Shiting , Mander Bryce A. , Mcmanus Olivia Kim , Vadera Sumeet , Knight Robert T. , McNaughton Bruce L. , Lin Jack J. 
Published: May 2020

AbstractHippocampal-dependent memory consolidation during sleep is hypothesized to depend on the synchronization of distributed neuronal ensembles, organized by the hippocampal sharp-wave ripples (SWRs, 80-150 Hz) and subcortical/cortical slow-waves (0.5-4 Hz). However, the precise role of SWR-slow-wave interactions in synchronizing subcortical/cortical neuronal activity is unclear. Here, we leverage intracranial electrophysiological recordings from the human hippocampus, amygdala, temporal and frontal cortices, to examine activity modulation and cross-regional coordination during SWRs. Hippocampal SWRs are associated with widespread modulation of high frequency activity (HFA; 70-200 Hz) a measure of local neuronal activation. This peri-SWR HFA modulation is predicted by the coupling between hippocampal SWRs and local subcortical/cortical slow-waves. Finally, local cortical slow-wave phase offsets during SWRs predicted functional connectivity between the frontal and temporal cortex. These findings suggest a selection mechanism wherein hippocampal SWR and cortical slow-wave synchronization governs the transient engagement of distributed neuronal populations supporting hippocampal-dependent memory consolidation.
Joint (Ad)ventures—Family firms' international entry mode choices for emerging markets
Authors: Loehde Ann Sophie K. , Calabrò Andrea , Torchia Mariateresa , Kraus Sascha 
Published: May 2020

PurposeThe aim of this study is to advance knowledge on family firms' entry mode choices by examining the linkage between target market context, especially in the emerging economies of China and India, and the dominant family firm logic of keeping ownership and control in the family.Design/methodology/approachWe use an exploratory multiple case study analysis approach based on nine German family firms' internationalization endeavors. We use both primary and secondary data.FindingsTraditionally, extant research concludes that family principals prefer foreign direct investments (FDIs) in order to exert maximum control when entering international markets. In contrast, our study finds a clear preference for international joint ventures (IJVs) as an initial entry mode of choice into unfamiliar markets. Our findings propose this decision to be rooted in cultural unfamiliarity and the complexity of the target markets' legal environment. The effect of these two factors is amplified by prior IJVs experiences.Originality/valueThis article offers several original insights. First, we identify the triggers of the paradoxical IJVs’ entry mode choice among family firms and thus explain the motivation for breaking with the dominant family firm logic of maximizing control. Second, we account for factors in China's and India's particular emerging market environments. In the light of family control, the unfamiliarity with these markets triggers the decision to compensate for the high level of uncertainty by engaging in an IJV partnership. Third, our study shows that family firms are indeed willing to share control if it serves the long-term survival of the firm.
Maintenance downtime evaluation in a process bottling plant
Authors: Inyiama Gerald Kenechukwu , Oke Sunday Ayoola 
Published: May 2020

PurposeDowntime is a process parameter that substantially impacts on the operating hours and results in production losses, thus motivating maintenance engineers to control process plants. Notwithstanding, the impacting nature of process equipment failure on the operating hours in bottling plants remains inadequately examined. In this paper, the cause-and-effect analysis was used to establish the root cause of the downtime problem and Pareto analysis employed to justify the greatest opportunities for improvement in reducing downtime and increasing reliability levels. Weibull analysis is then conducted on the industrial setting. Novel aspect ratios are proposed.Design/methodology/approachUsing the Weibull failure function of machines as a principal facilitator to produce failure predictions, the downtime behaviour of a process plant was modelled and tested with practical data from a bottling process plant. This research was conducted in a Nigerian process bottling plant where historical data were examined.FindingsThe analysis of the results shows the following principal outcome: First, the machines with the highest and least downtime values are 2 and 5, respectively, with correspondingly mean values of 22.83 and 4.39 h monthly. Second, the total downtime 92.05 and 142.14 h for the observed and target downtime, with a coefficient of determination of 0.5848 was recorded. Third, as month 1 was taken as the base period (target), all the machines, except M5 had accepted performance, indicating proper preventive maintenance plan execution for the bottling process plant. Availability shows a direct relationship between the failure and uptime of the machines and the downtime impacts on production. Two machines had random failure pattern and five machines exhibited a wear-out failure pattern and probably due to old age and wear of components in the machines.Originality/valueThe major contribution of the paper is the Weibull modelling in a unique application to a bottling plant to avoid current practices that use reliability software that is not easily accessible.
Longevity, body dimension and reproductive mode drive differences in aquatic versus terrestrial life‐history strategies
Authors: Capdevila Pol , Beger Maria , Blomberg Simone P. , Hereu Bernat , Linares Cristina , Salguero‐Gómez Roberto 
Published: May 2020

Abstract

Aquatic and terrestrial environments display stark differences in key environmental factors and phylogenetic composition but their consequences for the evolution of species' life‐history strategies remain poorly understood.

Here, we examine whether and how life‐history strategies vary between terrestrial and aquatic species. We use demographic information for 685 terrestrial and 122 aquatic animal and plant species to estimate key life‐history traits. We then use phylogenetically corrected least squares regression to explore potential differences in trade‐offs between life‐history traits between both environments. We contrast life‐history strategies of aquatic versus terrestrial species in a principal component analysis while accounting for body dimensions and phylogenetic relationships.

Our results show that the same trade‐offs structure terrestrial and aquatic life histories, resulting in two dominant axes of variation that describe species' pace of life and reproductive strategies. Terrestrial plants display a large diversity of strategies, including the longest‐lived species in this study. Aquatic animals exhibit higher reproductive frequency than terrestrial animals. When correcting for body size, mobile and sessile terrestrial organisms show slower paces of life than aquatic ones.

Aquatic and terrestrial species are ruled by the same life‐history trade‐offs, but have evolved different strategies, likely due to distinct environmental selective pressures. Such contrasting life‐history strategies have important consequences for the conservation and management of aquatic and terrestrial species.

A free Plain Language Summary can be found within the Supporting Information of this article.
An improved recombinase polymerase amplification assay for visual detection of Vibrio parahaemolyticus with lateral flow strips
Authors: Yang Xiaohan , Zhao Panpan , Dong Yu , Shen Xin , Shen Hui , Li Juan , Jiang Ge , Wang Weiling , Dai Hong , Dong Jingquan , Gao Song , Si Xinxin 
Published: May 2020

AbstractVibrio parahaemolyticus is an important pathogenic bacterium in both food safety management and mariculture. Rapid and accurate detection technologies are critical for effective control of its outbreak and spreading. Conventional technologies and polymerase chain reaction (PCR)‐based approaches have limited usage because of the requirement of laboratory instruments and trained personnel. Using the isothermal recombinase polymerase amplification (RPA) technology, several detection assays have been developed with added convenience. Combining the lateral flow strip (LFS) test with RPA can further simplify the detection. In this study, an improved RPA assay using LFS for visual detection of V. parahaemolyticus was developed. Primers were designed targeting the virulence genes and screened for amplification efficiency, nonspecific amplification, and primer–dimer formation. Probes were designed for the best primer pairs, and the weakness of LFS tests, being easily affected by primer‐dependent artifacts, was overcome by sequence modifications on primers and probe. The RPA–LFS assay took 25 min at 35 to 45 °C, and showed excellent specificity. It detected as low as one colony forming unit (CFU) of V. parahaemolyticus per reaction without DNA purification, or 10 CFU/10 g spiked food samples with 2 hr of enrichment. The detection limit was better than the currently available RPA‐based detection methods. Application of the RPA–LFS assay for simulated samples or real clinical samples showed accurate and consistent detection results compared to bioassay and quantitative PCR. The RPA–LFS assay provided a rapid, accurate, and convenient V. parahaemolyticus detection method suitable for on‐site detection in resource‐limited conditions.Practical ApplicationThis research developed a rapid and visual detection technology for Vibrio parahaemolyticus that is not dependent on complicated equipment. The detection process takes 25 min and the result is read with the naked eye. A detection kit can be developed based on this technology for on‐site detection of V. parahaemolyticus in resource‐limited regions for food safety management and mariculture.
Effect on the ensilage performance and microbial community of adding Neolamarckia cadamba leaves to corn stalks
Authors: Wang Yi , Zhou Wei , Wang Cheng , Yang Fuyu , Chen Xiaoyang , Zhang Qing 
Published: May 2020

SummaryTo comprehensively evaluate the fermentation performance and microbial community of corn stalks (CS) silage mixed with Neolamarckia cadamba leaves (NCL), CS were ensiled with four levels (0%, 10%, 30% and 50% of fresh weight) of NCL for 1, 7, 14, 30, 60 days in two trials. The results showed that all silages were well preserved with low pH (3.60–3.88) and ammonia nitrogen content (0.08–0.19% DM). The silage samples with NCL displayed lower (P < 0.05) acetic acid, propionic acid and ammonia nitrogen contents and lactic acid bacteria population during ensiling than control silages (100% CS). The addition of NCL also influenced the distribution of bacterial and fungal communities. Fungal diversity (Shannon’s indices were 5.15–5.48 and 2.85–4.27 in trial 1 and trial 2 respectively) increased while the relative abundances of Lactobacillus, Leuconostocs, Acetobacter and two moulds (Aspergillus and Fusarium) decreased after added NCL. In summary, mixing NCL is a promising effective approach to preserve protein of CS silage and inhibit the growth of undesirable bacteria and mould, thus to improve the forage quality to some extent.
Identifying productivity when it is a factor of production
Authors: Flynn Zach 
Published: May 2020

AbstractEconomists typically model a plant's productivity as an exogenous characteristic, but the people who run and work at manufacturing plants make choices, at a cost, that affect plant productivity. I develop a method to partially identify the productivity distribution when such choices determine productivity. The method uses a monotone comparative static result I prove in a general economic model. It does not require instruments or timing assumptions. I use the method to study the effect of implementing market‐based pricing on productivity in the electricity generation industry.
Markets for ideas: prize structure, entry limits, and the design of ideation contests
Authors: Kireyev Pavel 
Published: May 2020

AbstractI develop an empirical model of idea generation contests with heterogeneous participants and endogenous entry, fit the model to data from a platform used by major advertisers, and simulate counterfactual contest designs. The empirical model resolves ambiguous predictions yielded by contest theory about the effects of different prize structures on contest outcomes. Simulations reveal the impact of strategies that hold fixed total award and balance competition by handicapping advantaged participants. Increasing the number of prizes while restricting the number of prizes per participant can improve outcomes for the platform. The results provide guidance for the design of large contests.
Real‐world tyrosine kinase inhibitor treatment pathways, monitoring patterns and responses in patients with chronic myeloid leukaemia in the United Kingdom: the UK TARGET CML study
Authors: Milojkovic Dragana , Cross Nicholas C. P. , Ali Sahra , Byrne Jenny , Campbell Gavin , Dignan Fiona L. , Drummond Mark , Huntly Brian , Marshall Scott , McMullin Mary Frances , Neelakantan Pratap , Raghavan Manoj , Sivakumaran Muttuswamy , Tighe Jane , Wandroo Farooq , Willis Fenella , Glen Fiona , Fildes Louise , Collington Sarah J. , Ryan Jacqueline , Clark Richard E. , Mead Adam J. 
Published: May 2020

SummaryManagement of chronic myeloid leukaemia (CML) has recently undergone dramatic changes, prompting the European LeukemiaNet (ELN) to issue recommendations in 2013; however, it remains unclear whether real‐world CML management is consistent with these goals. We report results of UK TARGET CML, a retrospective observational study of 257 patients with chronic‐phase CML who had been prescribed a first‐line TKI between 2013 and 2017, most of whom received first‐line imatinib (n = 203). Although 44% of patients required ≥1 change of TKI, these real‐world data revealed that molecular assessments were frequently missed, 23% of patients with ELN‐defined treatment failure did not switch TKI, and kinase domain mutation analysis was performed in only 49% of patients who switched TKI for resistance. Major molecular response (MMR; BCR‐ABL1IS ≤0·1%) and deep molecular response (DMR; BCR‐ABL1IS ≤0·01%) were observed in 50% and 29%, respectively, of patients treated with first‐line imatinib, and 63% and 54%, respectively, receiving a second‐generation TKI first line. MMR and DMR were also observed in 77% and 44% of evaluable patients with ≥13 months follow‐up, receiving a second‐generation TKI second line. We found little evidence that cardiovascular risk factors were considered during TKI management. These findings highlight key areas for improvement in providing optimal care to patients with CML.