bluuebunny/crossref_metadata_2025_split huggingface dataset:
Synergistic interaction of hyposalinity stress with Vibrio infection causes mass mortalities in oysters by inducing host microflora imbalance and immune dysregulation
Authors: Li Xin , Yang Ben , Shi Chenyu , Wang Hebing , Li Qi , Liu Shikai 
Published: September 2021

ABSTRACTA sudden drop in salinity following extreme precipitation events usually causes mass mortalities of oysters exposed to pathogens in ocean environment. While how hyposalinity stress interacts with pathogens to cause mass mortality remains obscure. In this study, we performed an experiment by mimicking hyposalinity stress and pathogen infection with V. alginolyticus to investigate their synergistic effect on the mortality of infected oysters toward understanding of the interaction among environment, host, and pathogen. We showed that hyposalinity stress (10‰, 20‰ versus 30‰) did not significantly affect proliferation and virulence of V. alginolyticus, but significantly altered microbial composition and diversity in infected oysters. Microbial community profiling by 16S rRNA sequencing revealed disrupted homeostasis of digestive bacterial microbiota with increased abundance of several pathogenic bacteria, which may affect the pathogenesis in oysters. Transcriptome profiling of infected oysters revealed that a large number of genes associated with apoptosis and inflammation were significantly induced under hyposalinity, suggesting that hyposalinity stress may have triggered immune dysregulation in infected oysters. This work provides significant information in decoding mechanisms of synergistic interaction among environment factors, host genetics, and digestive microbiota, and how they contribute to pathogenesis.IMPORTANCERevealing the response of oyster host and microbial community to the interference of multiple environmental factors is an important aspect of deciphering the complex pathogenic mechanism in oysters. We evaluated the synergistic effects of hyposalinity stress and Vibrio alginolyticus infection in oysters. Results showed that hyposalinity stress significantly caused mass mortalities of infected oysters by destroying digestive microbial community structure, and triggering excessive immune response in oysters. This work provides valuable information for deciphering the mechanisms of synergistic interaction among environmental factors, host, and pathogens, and how they contribute to pathogenesis.
Quantifying the impact of ecological memory on the dynamics of interacting communities
Authors: Khalighi Moein , Sommeria-Klein Guilhem , Gonze Didier , Faust Karoline , Lahti Leo 
Published: September 2021

AbstractEcological memory refers to the influence of past events on the response of an ecosystem to exogenous or endogenous changes. Memory has been widely recognized as a key contributor to the dynamics of ecosystems and other complex systems, yet quantitative community models often ignore memory and its implications.Recent modeling studies have shown how interactions between community members can lead to the emergence of resilience and multistability under environmental perturbations. We demonstrate how memory can be introduced in such models using the framework of fractional calculus. We study how the outcomes of a well-characterized interaction model are affected by gradual increases in ecological memory under varying initial conditions, perturbations, and stochasticity.Our results highlight the implications of memory on several key aspects of community dynamics. In general, memory introduces inertia into the dynamics. This favors species coexistence under perturbation, enhances system resistance to state shifts, mitigates hysteresis, and can affect system resilience both ways depending on the time scale considered. Memory also promotes long transient dynamics, such as long-standing oscillations and delayed regime shifts, and contributes to the emergence and persistence of alternative stable states. Our study highlights the fundamental role of memory on ecological communities, and provides quantitative tools to introduce it in ecological models and analyse its impact under varying conditions.Author summaryAn ecosystem is said to exhibit ecological memory when its future states do not only depend on its current state but also on its initial state and trajectory. Memory may arise through various mechanisms as organisms adapt to their environment, modify it, and accumulate biotic and abiotic material. It may also emerge from phenotypic heterogeneity at the population level. Despite its commonness in nature, ecological memory and its potential influence on ecosystem dynamics have been so far overlooked in many applied contexts. Here, we use modeling to investigate how memory can influence the dynamics, composition, and stability landscape of ecological communities. We incorporate long-term memory effects into a multi-species model recently introduced to investigate alternative stable states in microbial communities. We assess the impact of memory on key aspects of model behavior and validate our findings using a model parameterized by empirical data from the human gut microbiota. Our approach for modeling memory and studying its implications has the potential to improve our understanding of microbial community dynamics and ultimately our ability to predict, manipulate, and experimentally design microbial ecosystems. It could also be applied more broadly in the study of systems composed of interacting components.
Essentiality, Protein-Protein Interactions and Evolutionary Properties are Key Predictors for Identifying Cancer Genes Using Machine Learning
Authors: Safadi Amro , Lovell Simon C. , Doig Andrew J. 
Published: September 2021

AbstractThe identification of genes that may be linked to cancer is of great importance for the discovery of new drug targets. The rate at which cancer genes are being found experimentally is slow, however, due to the complexity of the identification and confirmation process, giving a narrow range of therapeutic targets to investigate and develop. One solution to this problem is to use predictive analysis techniques that can accurately identify cancer gene candidates in a timely fashion. Furthermore, the effort in identifying characteristics that are linked to cancer genes is crucial to further our understanding of this disease. These characteristics can be employed in recognising therapeutic drug targets. Here, we investigated whether certain genes’ properties can indicate the likelihood of it to be involved in the initiation or progression of cancer. We found that for cancer, the essentiality scores tend to be higher for cancer genes than for all protein coding human genes. A machine-learning model was developed and we found that essentiality related properties and properties arising from protein-protein interaction networks or evolution are particularly effective in predicting cancer-associated genes. We were also able to identify potential drug targets that have not been previously linked with cancer, but have the characteristics of cancer-related genes.Author SummaryMutations in numerous genes are known to be involved in cancer, yet there are undoubtedly many more to be discovered. We analysed a set of hundreds of cancer genes with the aim of finding out what makes them different from genes not known to be mutated in cancer. In particular, we found that genes that are essential for the survival of an organism are more likely to be involved in cancer. We used the gene properties that we examined to develop an artificial intelligence method that can accurately predict whether a gene is involved in cancer or not. Applying the method gives hundreds of non-cancer genes that resemble cancer genes. New discoveries of cancer genes are likely to be found within this set.
Redistribution of the novelC. difficilespore-adherence receptor, E-cadherin, by TcdA and TcdB increases spore-binding to adherens junctions
Authors: Castro-Córdova Pablo , Otto-Medina Macarena , Montes-Bravo Nicolás , Brito-Silva Christian , Lacy D. Borden , Paredes-Sabja Daniel 
Published: September 2021

ABSTRACTClostridioides difficilecauses antibiotic-associated diseases in humans ranging from mild diarrhea to severe pseudomembranous colitis and death. A major clinical challenge is the prevention of disease recurrence, which affects nearly ∼20 to 30 % of the patients with a primaryC. difficileinfection (CDI). During CDI,C. difficileforms metabolically dormant spores that are essential for recurrence of CDI (R-CDI). In prior studies, we have shown thatC. difficilespores interact with intestinal epithelial cells (IECs), which contributes to R-CDI. However, this interaction remains poorly understood. Here, we provide evidence thatC. difficilespores interact with E-cadherin, contributing to spore-adherence and internalization into IECs.C. difficiletoxins TcdA/TcdB lead to adherens junctions opening and increase spore-adherence to IECs. Confocal micrographs demonstrate thatC. difficilespores associate with accessible E-cadherin; spore-E-cadherin association increases upon TcdA/TcdB intoxication. The presence of anti-E-cadherin antibodies decreased spore adherence and entry into IECs. By ELISA, immunofluorescence, and immunogold labelling, we observed that E-cadherin binds toC. difficilespores, specifically to the hair-like projections of the spore, reducing spore-adherence to IECs. Overall, these results expand our knowledge of howC. difficilespores bind to IECs by providing evidence that E-cadherin acts as a spore-adherence receptor to IECs and by revealing how toxin-mediated damage affects spore interactions with IECs.
Long-term incubation of lake water enables genomic sampling of consortia involving Planctomycetes and Candidate Phyla Radiation bacteria
Authors: Jaffe Alexander L. , Fuster Maxime , Schoelmerich Marie C. , Chen Lin-Xing , Colombet Jonathan , Billard Hermine , Sime-Ngando Télesphore , Banfield Jillian F. 
Published: September 2021

ABSTRACTMicrobial communities in lakes can profoundly impact biogeochemical processes through their individual activities and collective interactions. However, the complexity of these communities poses challenges, particularly for studying rare members. Laboratory enrichments can select for subsystems of interacting organisms and enable genome recovery for enriched populations. Here, a reactor inoculated with water from Lake Fargette, France, and maintained under dark conditions at 4°C for 31 months enriched for diverse Planctomycetes and Candidate Phyla Radiation (CPR) bacteria. We reconstructed draft genomes and predicted metabolic traits for 12 diverse Planctomycetes and 9 CPR bacteria, some of which are likely representatives of undescribed families or genera. One CPR genome representing the little-studied lineage Peribacter (1.239 Mbp) was curated to completion, and unexpectedly, encodes the full gluconeogenesis pathway. Metatranscriptomic data indicate that some Planctomycetes and CPR bacteria were active under the culture conditions. We also reconstructed genomes and obtained transmission electron microscope images for numerous phages, including one with a >300 kbp genome and several predicted to infect Planctomycetes. Together, our analyses suggest that freshwater Planctomycetes may act as hubs for interaction networks that include symbiotic CPR bacteria and phages.
Pathogenicity effector candidates and accessory genome revealed by pan-genomic analysis of Parastagonospora nodorum
Authors: Jones Darcy A. B. , Rybak Kasia , Bertazzoni Stefania , Tan Kar-Chun , Phan Huyen T. T. , Hane James K. 
Published: September 2021

AbstractThe wheat pathogen Parastagonospora nodorum has emerged as a model necrotrophic fungal species with growing genomic resources. Recent population-level pan-genome studies were leveraged to provide novel insights into pathogen evolution and effector-like gene contents relevant to local crop disease outbreaks. In this study, we examined 156 isolates representing a regional population from the Western Australian (WA) wheat-belt region, and 17 internationally sourced isolates. We observed a highly diverse local population, within which were numerous small and highly similar clusters of isolates from hotter and drier regions. Pan-genome assembly and orthologous gene datasets resulted in 3579 predicted effector candidates, 2291 of which exhibited presence-absence variation (PAV) across the population, and 1362 were specific to WA isolates. There was an abundance of mutations (including repeat-induced point mutation (RIP)), distributed in ‘hot-spots’ within the pan-genomic landscape that were rich in effector candidates. Three characterised effector loci (ToxA, Tox1 and Tox3) were located within sub- telomeric regions of lower diversity, but were nestled within larger high-diversity regions. RIP was widespread across the genome, but non-synonymous RIP-like mutations were strongly selected against. These improved bioinformatic resources for P. nodorum, represent progressive advancements in fungal pan-genomics, with a view towards supporting region- specific surveillance of host-pathogen interactions.
Toward More General Embeddings for Protein Design: Harnessing Joint Representations of Sequence and Structure
Authors: Mansoor Sanaa , Baek Minkyung , Madan Umesh , Horvitz Eric 
Published: September 2021

AbstractProtein embeddings learned from aligned sequences have been leveraged in a wide array of tasks in protein understanding and engineering. The sequence embeddings are generated through semi-supervised training on millions of sequences with deep neural models defined with hundreds of millions of parameters, and they continue to increase in performance on target tasks with increasing complexity. We report a more data-efficient approach to encode protein information through joint training on protein sequence and structure in a semi-supervised manner. We show that the method is able to encode both types of information to form a rich embedding space which can be used for downstream prediction tasks. We show that the incorporation of rich structural information into the context under consideration boosts the performance of the model by predicting the effects of single-mutations. We attribute increases in accuracy to the value of leveraging proximity within the enriched representation to identify sequentially and spatially close residues that would be affected by the mutation, using experimentally validated or predicted structures.
High diversity in Delta variant across countries revealed via genome-wide analysis of SARS-CoV-2 beyond the Spike protein
Authors: Suratekar Rohit , Ghosh Pritha , Niesen Michiel J.M. , Donadio Gregory , Anand Praveen , Soundararajan Venky , Venkatakrishnan A.J. 
Published: September 2021

AbstractThe highly contagious Delta variant of SARS-CoV-2 has emerged as the new dominant global strain, and reports of reduced effectiveness of COVID-19 vaccines against the Delta variant are highly concerning. While there has been extensive focus on understanding the amino acid mutations in the Delta variant ‘s Spike protein, the mutational landscape of the rest of the SARS-CoV-2 proteome (25 proteins) remains poorly understood. To this end, we performed a systematic analysis of mutations in all the SARS-CoV-2 proteins from nearly 2 million SARS-CoV-2 genomes from 176 countries/territories. Six highly-prevalent missense mutations in the viral life cycle-associated Membrane (I82T), Nucleocapsid (R203M, D377Y), NS3 (S26L), and NS7a (V82A, T120I) proteins are almost exclusive to the Delta variant compared to other variants of concern (mean prevalence across genomes: Delta = 99.74%, Alpha = 0.06%, Beta = 0.09%, Gamma = 0.22%). Furthermore, we find that the Delta variant harbors a more diverse repertoire of mutations across countries compared to the previously dominant Alpha variant (cosine similarity: meanAlpha = 0.94, S.D.Alpha = 0.05; meanDelta = 0.86, S.D.Delta = 0.1; Cohen ‘s dAlpha-Delta = 1.17, p-value < 0.001). Overall, our study underscores the high diversity of the Delta variant between countries and identifies a list of targetable amino acid mutations in the Delta variant ‘s proteome for probing the mechanistic basis of pathogenic features such as high viral loads, high transmissibility, and reduced susceptibility against neutralization by vaccines.
Investigation of mixing characteristics of coflow rectangular nozzle of aspect ratio 2 and 3
Authors: Murugesan Vignesh Kumar , Suseela Moorthi Aravindh Kumar , Ramachandran Ganapathy Subramanian L. 
Published: September 2021

Purpose
The purpose of this study is to understand experimentally the mixing characteristics of a two-stream exhaust system with a supersonic Mach 1.5 primary jet that exits the rectangular C-D nozzle surrounded by a sonic secondary jet from a convergent rectangular nozzle by varying the aspect ratio (AR = 2 and 3) similar to those that can be available for future high-speed commercial aircraft.

Design/methodology/approach
This paper focuses on the experimental results of effects of AR at various expansion levels of jets issued/delivered from a central rectangular convergent-divergent nozzle of AR 2 and 3 surrounded by a coflow from a convergent rectangular sonic nozzle. The lip thickness of the primary nozzle is 2.2 mm. various nozzle pressure ratios (NPRs) ranging from 2, 3, 3.69 and 4 were chosen for pressure measurements.

Findings
For all the NPRs, AR 3 had a shorter core than AR 2. Also, AR 3 was found to decay faster in the transition and fully developed zones. The lateral plots show that the AR has an influence on the jet spread.

Originality/value
The structure of waves existing in the potential core of the rectangular coflow jet along with the major and minor axis planes was visualized by the shadowgraph technique.
Once upon an anti-black time: unpacking the counter fairy tales (CFT) model to support culturally responsive literacy instruction for black girls
Authors: Young Jemimah , Butler Bettie Ray , Strong Kellan , Turner Maiya A. 
Published: September 2021

PurposeThis paper aims to argue that culturally responsive approaches to literacy instruction are necessary not only to celebrate Black girl literacies but to also expose, challenge and disrupt antiblackness in English education. However, without explicit exemplars to guide classroom practice, this type of instruction will remain elusive. The present paper expands upon the original conceptualization of Counter Fairy Tales (CFT) by further explicating the framework and providing recommendations to inform culturally responsive literacy practices to disrupt antiblackness.Design/methodology/approachThe question that drives this study asks how can the CFT model be applied as a form of culturally responsive literacy instruction to best teach Black girls?FindingsThe CFT framework places value on Black girls’ ways of knowing and gives primacy to their voice and unique experiences through culturally responsive literacy instruction.Research limitations/implicationsThe larger implication of this research is for teachers to begin to create culturally responsive literacy instruction that honors the lived experiences of today’s Black adolescent girls, particularly those in young grades. Inclusive and affirming literary practices must be established, an environment in which Black girls can share their voices and visions as they explore themselves through writing.Originality/valueThis conceptual paper is one of few that specifically focuses on how teachers can use CFTs to facilitate the inclusion of Black girls’ experiential and communal ways of knowing to support culturally responsive literacy instruction in younger grades.
Critical factors in capacity building of NGOs in the intellectual disability sector in India: PLS SEM modelling
Authors: Jain Mukesh , Dhir Sanjay 
Published: September 2021

PurposeMost of the services being delivered to persons with disabilities (PwDs) in India are through non-government organizations (NGOs). The quality and effectiveness for the delivery of services to PwDs largely depends on the capacity of the NGOs involved. This study attempts to understand the linkage between various capabilities of non-profits organizations working in the field of intellectual and developmental disabilities and their value creation.Design/methodology/approachUsing a mixed methodology, the study has conducted various interviews with the involved stakeholders and interviews to obtain a complete understanding and overcome the limitations of quantitative or qualitative approach alone.FindingsThe findings of this study exhibit that there is a significant and positive influence of financial capability, human resource capability, stakeholder capability, dynamic capability and collaboration capability on non-profit performance. However, knowledge capability has no effect on non-profit performance.Originality/valueThis study will help in making policies for policymakers in capacity building of NGOs. This research study is the first attempt in exploring the critical factors in capacity building of NGOs in the intellectual disability sector, particularly in India.
Predicting students' engagement from hope and mindfulness
Authors: Azila-Gbettor Edem Maxwell , Mensah Christopher , Atatsi Eli Ayawo , Abiemo Martin Kwasi 
Published: September 2021

PurposeThe study examines a mediated mechanism for enhancing students' engagement i.e. peer, intellectual and academic engagement within a higher education setup via the interaction of hope and mindfulness.Design/methodology/approachData were conveniently collected using self-reported questionnaires from a sample of 542 students. PLSc-SEM was used to test the stated hypotheses.FindingsResults from the analysis showed hope and mindfulness positively predict student academic, peer and intellectual engagements. Furthermore, mindfulness positively mediates the effect of hope on academic, peer and intellectual engagements.Practical implicationsThis study demonstrates that management of higher institutions must develop effective and efficient policies targeted at enhancing students' hope and mindful awareness.Originality/valueThis paper is the first to examine a model involving mindfulness, hope and peer, intellectual and academic engagement.
Supply chain integration, capability and performance – a business-to-business network cooperation
Authors: Liao Shu-Hsien , Hu Da-Chian , Chen Szu-Ting 
Published: September 2021

Purpose
Supply chain integration (SCI) is a critical issue in the study of supply chain management in terms of working with partners on business networks to complete tasks, enhance capability and increase performance in a collaborative supply chain process. Thus, this study aims to investigate the influence of SCI and supply chain capability (SCC) on supply chain performance (SCP) which has a positive effect according to the degree of integration (DI) in a supply chain management process. Furthermore, the DI has a direct or indirect impact on how SCI affects SCP.

Design/methodology/approach
Through a questionnaire-survey, 454 valid responses were collected. This study investigates the relationships between SCI, SCC, SCP and the DI in the Taiwan elevator by using a structured equations model. The DI is considered as a variable for the effect of a moderated mediation in the research model.

Findings
It was found that SCI, directly and indirectly, affected the SCP in a positive way. In addition, the research model is a partial mediation model and that SCC plays a mediator role and DI also existing a moderated mediating effect in the research model. The indirect effect of SCI on SCP through SCC is stronger at higher levels of DI than at lower levels of DI.

Originality/value
This is the first study that suggests and empirically tests the moderated mediating impacts of the integration degree on the relationships between SCI, capability and performance with suppliers of the elevator manufacturing supply chain as the business-to-business network cooperation example in Taiwan.