bluuebunny/crossref_metadata_2025_split huggingface dataset:
Proteomics study of colorectal cancer and adenomatous polyps identifies TFR1, SAHH, and HV307 as potential biomarkers for screening
Authors: Tang Meifang , Zeng Liuhong , Zeng Zhaolei , Liu Jie , Yuan Jie , Wu Dongjie , Lu Ying , Zi Jin , Ye Mingzhi 
Published: October 2020

AbstractColorectal cancer (CRC) is a malignant tumour with high morbidity and mortality worldwide. Efficient screening strategies for CRC and pre-cancerous lesions will promote early medical intervention and treatment, thus reducing morbidity and mortality. Proteins are generally considered key biomarkers of cancer. Herein, we performed a quantitative, tissue-original proteomics study in a cohort of ninety patients from pre-cancerous to cancerous conditions by liquid chromatography-tandem mass spectrometry. A total of 134,812 peptides, 8,697 proteins, 2,355 (27.08%) union differentially expressed proteins (DEPs), and 409 shared DEPs (compared with adjacent tissues) were identified. The number of DEPs showed a positive correlation with increasing severity of illness. The union and shared DEPs were both enriched in the KEGG pathway of focal adhesion, metabolism of xenobiotics by cytochrome P450, and drug metabolism – cytochrome P450. Among the 2,355 union DEPs, 32 were selected for identification and validation by multiple reaction monitoring from twenty plasma specimens. Of these, three proteins, transferrin receptor protein 1 (TFR1), adenosylhomocysteinase (SAHH), and immunoglobulin heavy variable 3-7 (HV307), were significantly differentially expressed and displayed the same expression pattern in plasma as observed in the tissue data. In conclusion, TFR1, SAHH, and HV307 may be considered as potential biomarkers for screening of CRC.SignificanceCRC is a malignant tumour with high morbidity and mortality worldwide. Efficient screening strategies for CRC and pre-cancerous lesions can play an important role in addressing the issue of high morbidity and mortality. Screening of molecular biomarkers provide a non-invasive, cost-effective and effective approach. Proteins are generally considered key molecular biomarkers of cancer. Our study reports a quantitative proteomics analysis of protein biomarkers for colorectal cancer (CRC) and adenomatous polyps and identifies TFR1, SAHH, and HV307 as potential biomarkers for screening. The research makes a significant contribution to the literature because whereas mass spectrometry-based proteomics research has been widely used for clinical research, its application to clinical translation is lacking as parallel specimens ranging from pre-cancerous to cancerous tissues, according to the degree of disease progression, have not been readily assessed.
Multi-step vs. single-step resistance evolution under different drugs, pharmacokinetics and treatment regimens
Authors: Igler Claudia , Rolff Jens , Regoes Roland R. 
Published: October 2020

AbstractThe success of antimicrobial treatment is threatened by the evolution of drug resistance. Population genetic models are an important tool in mitigating that threat. However, most such models consider resistance emergence via a single mutational step. Here, we assembled experimental evidence that drug resistance evolution follows two patterns: i) a single mutation, which provides a large MIC increase, or ii) multiple mutations, each conferring a small increase, which combine to yield high-level resistance. Using stochastic modeling we then investigated the consequences of these two patterns for treatment failure and population diversity under various treatments. We find that resistance evolution is substantially limited if more than two mutations are required and that the most efficacious drug type depends on the pharmacokinetic profile. Further, we demonstrate that, for resistance evolution in multiple steps, adaptive treatment, which only suppresses the bacterial population, is favored over aggressive treatment, which aims at eradication.
High-throughput phenotyping analysis of maize at the seedling stage using end-to-end segmentation network
Authors: Li Yinglun , Wen Weiliang , Guo Xinyu , Yu Zetao , Gu Shenghao , Yan Haipeng , Zhao Chunjiang 
Published: October 2020

AbstractImage processing technologies are available for high-throughput acquisition and analysis of phenotypes for crop populations, which is of great significance for crop growth monitoring, evaluation of seedling condition, and cultivation management. However, existing methods rely on empirical segmentation thresholds, thus can have insufficient accuracy of extracted phenotypes. Taking maize as an example crop, we propose a phenotype extraction approach from top-view images at the seedling stage. An end-to-end segmentation network, named PlantU-net, which uses a small amount of training data, was explored to realize automatic segmentation of top-view images of a maize population at the seedling stage. Morphological and color related phenotypes were automatic extracted, including maize shoot coverage, circumscribed radius, aspect ratio, and plant azimuth plane angle. The results show that the approach can segment the shoots at the seedling stage from top-view images, obtained either from the UAV or ground high-throughput phenotyping platform. The average segmentation accuracy, recall rate, and F1 score are 0.96, 0.98, and 0.97, respectively. The extracted phenotypes, including maize shoot coverage, circumscribed radius, aspect ratio, and plant azimuth plane angle, are highly correlated with manual measurements (R2=0.96-0.99). This approach requires less training data and thus has better expansibility. It provides practical means for high-throughput phenotyping analysis of early growth stage crop populations.
Vectorchip: Microfluidic platform for highly parallel bite by bite profiling of mosquito-borne pathogen transmission
Authors: Kumar Shailabh , Hol Felix J. H. , Pujhari Sujit , Ellington Clayton , Narayanan Haripriya Vaidehi , Li Hongquan , Rasgon Jason L. , Prakash Manu 
Published: October 2020

AbstractMosquito bites transmit a number of human pathogens resulting in potentially fatal diseases including malaria, dengue, chikungunya, West Nile encephalitis, and Zika. Although female mosquitoes transmit pathogens via salivary droplets deposited during blood feeding on a host, very little is known about the genomic content of these nanoliter scale droplets, including the transmission dynamics of live pathogens. Here we introduceVectorchip, a low-cost, scalable microfluidic platform for molecular interrogation of individual mosquito bites in a high-throughput fashion. An ultra-thin PDMS membrane coupled to a microfluidic chip acts as a biting interface, through which freely-behaving mosquitoes deposit saliva droplets by biting into isolated arrayed micro-wells enabling molecular interrogation of individual bites. By modulating membrane thickness, the device enables on-chip comparison of biting capacity and provides a mechanical filter allowing selection of a specific mosquito species. UtilizingVectorchip, we show on-chip simultaneous detection of mosquito DNA as well as viral RNA from Zika infectedAedes aegyptimosquitoes – demonstrating multiplexed high-throughput screening of vectors and pathogens. Focus-forming assays performed on-chip quantify number of infectious viral particles transmitted during mosquito bites, enabling assessment of active virus transmission. The platform presents a promising approach for single-bite-resolution laboratory and field characterization of vector pathogen communities, to reveal the intricate dynamics of pathogen transmission, and could serve as powerful early warning artificial “sentinel” for mosquito-borne diseases.
Transcriptomic, proteomic and phosphoproteomic underpinnings of daily exercise performance and Zeitgeber activity of endurance training
Authors: Maier Geraldine , Delezie Julien , Westermark Pål O. , Santos Gesa , Ritz Danilo , Handschin Christoph 
Published: October 2020

AbstractTimed physical activity might potentiate the health benefits of training. The underlying signaling events triggered by exercise at different times of the day are, however, poorly understood. Here, we found that time-dependent variations in maximal treadmill exercise capacity of naïve mice were associated with energy stores, mostly hepatic glycogen levels. Importantly, running at different times of the day resulted in a vastly different activation of signaling pathways, e.g., related to stress response, vesicular trafficking, repair, and regeneration. Second, voluntary wheel running at the opposite phase of the dark, feeding period surprisingly revealed minimal Zeitgeber (i.e., synchronizing) activity of training. This integrated study provides important insights into the circadian regulation of endurance performance and the control of the circadian clock by exercise. These results are of high importance to understand circadian aspects of training design in athletes and the application of chrono-exercise-based interventions in patients.HighlightsMaximal endurance performance is greater in the early morningTimed exercise differentially alters the muscle transcriptome and (phospho)-proteomeMorning exercise triggers energy provisioning and tissue regenerationEvening exercise activates stress-related and catabolic pathwaysTraining exerts poor Zeitgeber activity on the muscle and liver clocks
Resource reallocation in engineeredEscherichia colistrains with reduced genomes
Authors: Nakayasu Ernesto S. , Chazin-Gray Adam M. , Francis Ryan M. , Eaton Arielle M. , Auberry Deanna L. , Muñoz Nathalie , Cottam Joseph A. , Zucker Jeremy D. , Kumar Neeraj , Nicora Carrie D. , Mitchell Hugh D. , Kim Young-Mo , Nelson William C. , Egbert Robert G. 
Published: October 2020

AbstractA major challenge in synthetic biology is properly balancing evolved and engineered functions without compromising microbial fitness. Many microbial proteins are not required for growth in regular laboratory conditions, but it is unclear what fraction of the proteome can be eliminated to increase bioproduction and maintain fitness. Here, we investigated the effects of massive genome reduction inE. colion the expression level and evolutionary stability of a model biosynthetic pathway to produce the pigment protodeoxyviolacein (PDV). We identified an amino acid metabolism imbalance and compromised growth that were correlated with elimination of genes associated with significant proteome fraction. Proteomic profiling suggested that increased amino acid pools are responsible for an alleviation of fitness defects associated with PDV expression. In addition, all strains with genome reductions that significantly affected the proteome exhibited decreased stability of PDV production compared to the wild-type strain under persistent PDV expression conditions despite the alleviation of fitness defects. These findings exhibit the importance of balancing evolved functions with engineered ones to achieve an optimal balance of fitness and bioproduction.
Suicide Deaths during the Stay-at-Home Advisory in Massachusetts
Authors: Faust Jeremy S. , Shah Sejal B. , Du Chengan , Li Shu-Xia , Lin Zhenqiu , Krumholz Harlan M. 
Published: October 2020

AbstractMany believe that shelter-in-place or stay-at-home policies might cause an increase in so-called deaths of despair. While increases in psychiatric stressors during the COVID-19 pandemic are anticipated, whether suicide rates changed during stay-at-home periods has not been described.This was an observational cohort study that assembled suicide death data for persons aged 10 years or older from the Massachusetts Department of Health Registry of Vital Records and Statistics from January 2015 through May 2020. Using autoregressive integrated moving average (ARIMA) and seasonal ARIMA to analyze suicide deaths in Massachusetts, we compared the observed number of suicide deaths in Massachusetts during the stay-at-home period (March through May, 2020) in Massachusetts to the projected number of expected deaths. To be conservative, we also accounted for the deaths still pending final cause determinationThe incident rate for suicide deaths in Massachusetts was 0.67 per 100,000 person-month (95% CI 0.56-0.79) versus 0.81 per 100,000 person-month (95% CI 0.69-0.94) during the 2019 corresponding period (incident rate ratio of 0.83; 95% CI 0.66-1.03). The addition of the 57 deaths pending cause determination occurring from March through May 2020 and the 33 cases still pending determination from the 2019 corresponding period did not change these findings.The observed number of suicide deaths during the stay-at-home period did not deviate from ARIMA projected expectations using either preliminary data or an alternate scenario in which deaths pending investigation (exceeding the average remaining number of deaths still pending investigation which occurred during the corresponding 2015-2019 period) were ascribed to suicide. Decedent age and sex demographics were unchanged during the pandemic period compared to 2015-2019.The stable rates of suicide deaths during the stay-at-home advisory in Massachusetts parallel findings following ecological disasters. As the pandemic persists, uncertainty about its scope and economic impact may increase. However, our data are reassuring that an increase in suicide deaths in Massachusetts during the stay-at-home advisory period did not occur.
Neural oscillations track natural but not artificial fast speech: Novel insights from speech-brain coupling using MEG
Authors: Casas Ana Sofía Hincapié , Lajnef Tarek , Pascarella Annalisa , Guiraud Hélène , Laaksonen Hannu , Bayle Dimitri , Jerbi Karim , Boulenger Véronique 
Published: October 2020

AbstractSpeech processing is supported by the synchronization of cortical oscillations to its rhythmic components, including syllable rate. This has been shown to be the case for normal rate speech as well as artificially accelerated speech. However, the case of natural speech rate variations, which are among the most ubiquitous sources of variability in speech, has been largely overlooked. Here, we directly compared changes in the properties of cortico-acoustic coupling when speech naturally shifts from normal to fast rate and when it is artificially accelerated. Neuromagnetic brain signals of 24 normal-hearing adults were recorded with magnetoencephalography (MEG) while they listened to natural normal (∼6 syllables/s), natural fast (∼9 syllables/s) and time-compressed (∼9 syllables/s) sentences, as well as to envelope-matched amplitude-modulated noise. We estimated coherence between the envelope of the acoustic input and MEG source time-series at frequencies corresponding to the mean syllable rates of the normal and fast speech stimuli. We found that listening to natural speech at normal and fast rates was associated with coupling between speech signal envelope and neural oscillations in right auditory and (pre)motor cortices. This oscillatory alignment occurred at ∼6.25 Hz for normal rate sentences and shifted up to ∼8.75 Hz for naturally-produced fast speech, mirroring the increase in syllable rate between the two conditions. Unexpectedly, despite being generated at the same rate as naturally-produced fast speech, the time-compressed sentences did not lead to significant cortico-acoustic coupling at ∼8.75 Hz. Interestingly, neural activity in putative right articulatory cortex exhibited stronger tuning to natural fast rather than to artificially accelerated speech, as well as stronger phase-coupling with left temporo-parietal and motor regions. This may reflect enhanced tracking of articulatory features of naturally-produced speech. Altogether, our findings provide new insights into the oscillatory brain signature underlying the perception of natural speech at different rates and highlight the importance of using naturally-produced speech when probing the dynamics of brain-to-speech coupling.
Post-entry growth in scope and scale among Chinese multinational enterprises: a structural embeddedness explanation
Authors: Shi Xuanya , Boadu Francis , Du Yifei 
Published: October 2020

PurposeBoth the scope of postentry growth and the scale of postentry growth are essential for Chinese multinational enterprises' aggressive internationalization. Yet, prior literature has not considered the synergistic approach of postentry growth that seeks the scope of growth and the scale of growth simultaneously. Building upon the embeddedness perspective and the learning view, we address how structural embeddedness directly affects firms' postentry growth in the form of scope and scale and indirectly affects postentry growth via both the scope of growth and the scale of growth. Particularly, we investigate the decreasing mediating effect of the growth's scale on the growth's scope when embeddedness strengthens.Design/methodology/approachWith a survey data set of 206 Chinese multinational firms from manufacturing and service industries, we conduct structural equation modeling (SEM), partial least squares path modeling (PLS-PM), instantaneous indirect effect assessment and hierarchical linear regression model to test our hypotheses.FindingsFirst, Chinese multinational enterprises’ (CMNEs) structural embeddedness is positively related to their scope of postentry growth, while has aU-shaped relationship with their scale of postentry growth. Second, CMNEs' scope of postentry growth mediates the relationship between structural embeddedness and the scale of postentry growth, the mediation effect counts for 33.5% of the over effect. Finally, the indirect effect of structural embeddedness on the scope of postentry growth through the scale of postentry growth is nonlinear. As the structural embeddedness strengthens, the positive indirect effect gradually weakens.Originality/valueWe believe this study further connects core international business research on postentry growth to the fast-growing literature on emerging markets multinational enterprises' internationalization. In addition, we undertake an initial effort in addressing an important gap in the literature: how structural embeddedness matters to firms' postentry growth. Moreover, this study finds important evidence to support the direct and indirect effect of structural embeddedness on postentry growth.
Factors influencing graduate job choice – a systematic literature review
Authors: Purohit Divyang , Jayswal Mitesh , Muduli Ashutosh 
Published: October 2020

Purpose
The purpose of this paper, systematic literature review, is twofold: to identify the factors influencing graduate job choice and to propose a theoretical model that can be useful for future research.

Design/methodology/approach
Thematic analysis of the literature available till June 2020 has been reviewed using electronic databases such as ABI/INFORM Complete, EBSCO, Emerald Insight, ProQuest, SAGE Journals, Science Direct (Elsevier), Scopus, Springer Link, Taylor and Francis Online, Wiley Online Library.

Findings
Out of more than 5,000 studies, 14 studies were found addressing the issue of career choice among graduating students. The thematic analysis result explored five themes such as internal factors, external factors, interpersonal factors, institutional factors and socio-demographic factors that can be considered critical for graduates’ career choice decision. Details of the subthemes are also identified.

Research limitations/implications
Implications for practitioners have been suggested from the internal factors, external factors, interpersonal factors, institutional factors and socio-demographic factors’ perspectives. The study result can be useful for conducting future research using quantitative data on graduate job choice.

Originality/value
This is the first attempt to present a comprehensive picture of past studies on graduate job choice and exploring the factors influencing graduate job choice.
Manager-as-coach: stimulating engagement via learning orientation
Authors: Lyons Paul , Bandura Randall P. 
Published: October 2020

Purpose
The purpose of this paper is to use recent empirical research and theory to help explain how a manager may assume a coaching role to assist employee learning and growth. In the coaching role, performance appraisal and other information may be carefully used as feedback to reinforce growth mindset learning in the service of employee development and engagement in work tasks and in the organization.

Design/methodology/approach
Aided by search devices (Psych Articles, Google Scholar, etc.), this study explored several distinct areas of information to include: manager-as-coach, performance management/appraisal, engagement with work, mindsets – fixed and growth, feedback and self-regulation of learning. Across these domains, this study searched for linkages useful in guiding managers to assist employees to learn and change.

Findings
Coaching employees to embrace a growth mindset and one’s self-regulation of learning has been expressed as a means to improve performance, resiliency, persistence, ability to cope with change and motivation.

Practical implications
Explicit, grounded recommendations are offered to assist managers to guide employees to embrace a growth mindset and take charge of their own learning and development.

Originality/value
Through examination and coordination of streams of research and theory, the study are able to make reasonably clear some avenues for a manager to attempt to positively influence employee confidence, learning, success and growth.
Research and application of novel Euler polynomial-driven grey model for short-term PM10 forecasting
Authors: Xiang Xiwang , Ma Xin , Ma Minda , Wu Wenqing , Yu Lang 
Published: October 2020

PurposePM10 is one of the most dangerous air pollutants which is harmful to the ecological system and human health. Accurate forecasting of PM10 concentration makes it easier for the government to make efficient decisions and policies. However, the PM10 concentration, particularly, the emerging short-term concentration has high uncertainties as it is often impacted by many factors and also time varying. Above all, a new methodology which can overcome such difficulties is needed.Design/methodology/approachThe grey system theory is used to build the short-term PM10 forecasting model. The Euler polynomial is used as a driving term of the proposed grey model, and then the convolutional solution is applied to make the new model computationally feasible. The grey wolf optimizer is used to select the optimal nonlinear parameters of the proposed model.FindingsThe introduction of the Euler polynomial makes the new model more flexible and more general as it can yield several other conventional grey models under certain conditions. The new model presents significantly higher performance, is more accurate and also more stable, than the six existing grey models in three real-world cases and the case of short-term PM10 forecasting in Tianjin China.Practical implicationsWith high performance in the real-world case in Tianjin China, the proposed model appears to have high potential to accurately forecast the PM10 concentration in big cities of China. Therefore, it can be considered as a decision-making support tool in the near future.Originality/valueThis is the first work introducing the Euler polynomial to the grey system models, and a more general formulation of existing grey models is also obtained. The modelling pattern used in this paper can be used as an example for building other similar nonlinear grey models. The practical example of short-term PM10 forecasting in Tianjin China is also presented for the first time.