bluuebunny/crossref_metadata_2025_split huggingface dataset:
The relationship between benthic nutrient fluxes and bacterial community in Aquaculture Tail-water Treatment Systems
Authors: Nicholaus Regan , Lukwambe Betina , Yanga Wen , Zhenga Zhongming 
Published: August 2021

ABSTRACTConstructed-wetlands, Biofilms, and sedimentation are potential aquaculture tail-water treatments however their roles on the distribution of benthic microbial community and the way they affect the interaction between microbial community and inorganic nutrient fluxes have not been fully explored. This study applied 16S rRNA high-throughput sequencing technology to investigate the microbial community distribution and their link with nutrient fluxes in an aquaculture tail-water bioremediation system. Results showed that bacterial community compositions were significantly different in constructed-wetland and biofilm treatments (p<0.05) relative to sedimentation. The composition of the 16S rRNA genes among all the treatments was enriched with Proteobacteria, Bacteroidetes, Firmicutes, and Flavobacteria. NMDS analysis showed that the bacterial composition in constructed-wetland and biofilm samples clustered separately compared to those in sedimentation. The Functional-Annotation-of-Prokaryotic-Taxa analysis indicated that the proportions of sediment-microbial-functional groups (aerobic-chemoheterophy, chemoheterotrophy, and nitrate-ammonification combined) in the constructed-wetland treatment were 47%, 32% in biofilm and 13% in sedimentation system. Benthic-nutrient fluxes for phosphate, ammonium, nitrite, nitrate and sediment oxygen consumption differed markedly among the treatments (p<0.05). Canonical correspondence analysis indicated constructed-wetland had the strongest association between biogeochemical contents and the bacterial community relative to other treatments. This study suggests that the microbial community distributions and their interactions nutrient fluxes were most improved in the constructed-wetland followed by the area under biofilm and sedimentation treatment.
Cascading effects of elephant-human interactions in a savanna ecosystem and the implications for ecology and conservation
Authors: Western David , Mose Victor N. 
Published: August 2021

AbstractOur study monitored the changes in elephant numbers, distribution and ecological impact over a fifty-year period as the free-ranging intermingled movements of wildlife and traditional subsistence pastoralists across the Amboseli ecosystem were disrupted by a national park, livestock ranches, farms, settlements and changing lifestyles and economies.Elephants compressed into the national park by poaching and settlement turned woodlands to grassland and shrublands and swamps into short grazing lawns, causing a reduction of plant and herbivore diversity and resilience to extreme events. The results echo the ecological findings of high-density elephant populations in protected areas across eastern and southern Africa. The impact has led to the view of elephants in parks being incompatible with biodiversity and to population control measures.In contrast to Amboseli National Park, we found woody vegetation grew and plant diversity fell in areas abandoned by elephants. We therefore used naturalist and exclosure experiments to determine the density-dependent response of vegetation to elephants. We found plant richness to peak at the park boundary where elephants and livestock jostled spatially, setting up a creative browsing-grazing tension and a patchwork of habitats explaining the plant richness.A review of prehistorical and historical literature lends support to the Amboseli findings that elephants and people, the two dominant keystone species in the savannas, have been intimately entangled prior to the global ivory trade and colonialism. The findings point to the inadequacy of parks for conserving mega herbivores and as ecological baselines.The Amboseli study underlines the significance of space and mobility in expressing the keystone role of elephants, and to community-based conservation as a way to win space and mobility for elephants, alleviate the ecological disruption of compressed populations and minimize population management.
Drug resistance mechanisms create targetable proteostatic vulnerabilities in Her2+ breast cancers
Authors: Singh Navneet , Romick-Rosendale Lindsey , Watanabe-Chailland Miki , Privette Vinnedge Lisa M. , Komurov Kakajan 
Published: August 2021

AbstractOncogenic kinase inhibitors show short-lived responses in the clinic due to high rate of acquired resistance. We previously showed that pharmacologically exploiting oncogene-induced proteotoxic stress can be a viable alternative to oncogene-targeted therapy. Here, we performed extensive analyses of the transcriptomic, metabolomic and proteostatic perturbations during the course of treatment of Her2+ breast cancer cells with a Her2 inhibitor covering the drug response, resistance, relapse and drug withdrawal phases. We found that acute Her2 inhibition, in addition to blocking mitogenic signaling, leads to significant decline in the glucose uptake, and shutdown of glycolysis and of global protein synthesis. During prolonged therapy, compensatory overexpression of Her3 allows for the reactivation of mitogenic signaling pathways, but fails to re-engage the glucose uptake and glycolysis, resulting in proteotoxic ER stress, which maintains the protein synthesis block and growth inhibition. Her3-mediated cell proliferation under ER stress during prolonged Her2 inhibition is enabled due to the overexpression of the eIF2 phosphatase GADD34, which uncouples protein synthesis block from the ER stress response to allow for active cell growth. We show that this imbalance in the mitogenic and proteostatic signaling created during the acquired resistance to anti-Her2 therapy imposes a specific vulnerability to the inhibition of the endoplasmic reticulum quality control machinery. The latter is more pronounced in the drug withdrawal phase, where the de-inhibition of Her2 creates an acute surge in the downstream signaling pathways and exacerbates the proteostatic imbalance. Therefore, the acquired resistance mechanisms to oncogenic kinase inhibitors may create secondary vulnerabilities that could be exploited in the clinic.
CREB5 reprograms nuclear interactions to promote resistance to androgen receptor targeting therapies
Authors: Hwang Justin , Arafeh Rand , Seo Ji-Heui , Baca Sylvan C. , Ludwig Megan , Arnoff Taylor E. , Richter Camden , Bergom Hannah E. , McSweeney Sean , Rennhack Jonathan P. , Klingenberg Sarah A. , Cheung Alexander TM. , Kwon Jason , So Jonathan , Kregel Steven , Van Allen Eliezer M. , Drake Justin M. , Freedman Mathew L. , Hahn William C. 
Published: August 2021

AbstractMetastatic castration resistant prostate cancers (mCRPC) are treated with therapies that antagonize the androgen receptor (AR). Nearly all patients develop resistance to AR-targeted therapies (ART). Our previous work identified CREB5 as an upregulated target gene in human mCRPC that promoted resistance to all clinically-approved ART. The mechanisms by which CREB5 promotes progression of mCRPC or other cancers remains elusive. Integrating ChIP-seq and rapid immunoprecipitation and mass spectroscopy of endogenous proteins (RIME), we report that cells overexpressing CREB5 demonstrate extensive reprogramming of nuclear protein-protein interactions in response to the ART agent enzalutamide. Specifically, CREB5 physically interacts with AR, the pioneering actor FOXA1, and other known co-factors of AR and FOXA1 at transcription regulatory elements recently found to be active in mCRPC patients. We identified a subset of CREB5/FOXA1 co-interacting nuclear factors that have critical functions for AR transcription (GRHL2, HOXB13) while others (TBX3, NFIC) regulated cell viability and ART resistance and were amplified or overexpressed in mCRPC. Upon examining the nuclear protein interactions and the impact of CREB5 expression on the mCRPC patient transcriptome, we found CREB5 was associated with TGFβ and Wnt signaling and epithelial to mesenchymal transitions, implicating these pathways in ART resistance. Overall, these observations define the molecular interactions among CREB5, FOXA1, and pathways that promote ART resistance.
Chlamydomonas ATX1 is essential for Cu distribution towards the secretory pathway and maintenance of biomass in conditions demanding cupro-enzyme dependent metabolic pathways
Authors: Pham Keegan L. J. , Schmollinger Stefan , Merchant Sabeeha S. , Strenkert Daniela 
Published: August 2021

AbstractCopper (Cu) chaperones, of which yeast ATX1 is a prototype, are small proteins with a Cu(I) binding Mx-CxxC motif, and are responsible for directing intracellular Cu towards specific client protein targets that use Cu as a cofactor. The Chlamydomonas reinhardtii ATX1 (CrATX1) was identified because of its high sequence similarity with yeast ATX1. Like the yeast homologue, CrATX1 accumulates in iron-deficient cells (but is not impacted by other metal-deficiencies), and YFP-ATX1 is distributed in the cytoplasm. Reverse genetic analysis using artificial microRNA (amiRNA) to generate lines with reduced CrATX1 abundance and CRISPR/CPF1 to generate ATX1 knock out lines validated a function for ATX1 in iron-poor cells, most likely because of an impact on metalation of the multicopper oxidase FOX1, which is an important component in high-affinity iron uptake. A more general impact on the secretory pathway is indicated by reduced growth of ATX1 mutant lines on guanine as a sole nitrogen source, which we attribute to loss of function of UOX1, a urate oxidase involved in guanine assimilation. The block of Cu trafficking towards the secretory pathway in ATX1 mutants is strikingly evident by a reduced amount of intracellular Cu in all conditions probed in this work.
Impact of Human Serum Proteins on Susceptibility ofAcinetobacter baumanniito Cefiderocol: role of iron transport
Authors: Le Casin , Pimentel Camila , Pasteran Fernando , Tuttobene Marisel R. , Subils Tomas , Escalante Jenny , Nishimura Brent , Arriaga Susana , Carranza Aimee , Vila Alejandro J. , Corso Alejandra , Actis Luis A. , Tolmasky Marcelo E. , Bonomo Robert A. , Ramírez María Soledad 
Published: August 2021

AbstractCefiderocol is a siderophore antibiotic that co-opts iron transporters to facilitate cell entry. We show that genes related to iron uptake systems and resistance to β-lactams inAcinetobacter baumanniihave altered expression levels in the presence of human serum, human serum albumin, or human pleural fluid. Cefiderocol MICs are also raised in the presence of the mentioned fluids. Clinical response inA. baumanniiinfections may be related to the interplay of these human factors.
The evolution of fluoroquinolone resistance in Salmonella under exposure to sub-inhibitory concentration of enrofloxacin
Authors: Gu Yufeng , Huang Lulu , Wu Cuirong , Huang Junhong , Hao Haihong , Yuan Zonghui , Cheng Guyue 
Published: August 2021

AbstractThe evolution of resistance in Salmonella to fluoroquinolones (FQs) under a broad range of sub-inhibitory concentrations (sub-MICs) has not been systematically studied. This study investigated the mechanism of resistance development in Salmonella enterica serovar Enteritidis (S. Enteritidis) under sub-MICs of 1/128×MIC to 1/2×MIC of enrofloxacin (ENR), a widely used veterinary FQ. It was shown that the resistance rate and resistance level of S. Enteritidis varied with the increase of ENR concentration and duration of selection. qRT-PCR results demonstrated that the expression of outer membrane porin (OMP) genes, ompF, ompC and ompD, were down-regulated first to rapidly adapt and develop resistance of ≤ 4×MIC, and as the resistance level increased (≥8×MIC), the up-regulated expression of efflux pump genes, acrB, emrB amd mdfA, along with mutations in quinolone resistance-determining region (QRDR) gradually played a decisive role. Cytohubba analysis based on transcriptomic profiles demonstrated that purB, purC, purD, purF, purH, purK, purL, purM, purN and purT were the hub genes for the FQs resistance. ‘de novo’ IMP biosynthetic process, purine ribonucleoside monophosphate biosynthetic process and purine ribonucleotide biosynthetic process were the top three biological processes screened by MCODE. This study first described the dynamics of FQ resistance evolution in Salmonella under a long-term selection of sub-MICs of ENR in vitro. In addition, this work offers greater insight into the transcriptome changes of S. Enteritidis under the selection of ENR and provides a framework for FQs resistance of Salmonella for further studies.
Deep learning-based algorithm for predicting the live birth potential of mouse embryos
Authors: Tokuoka Yuta , Yamada Takahiro G. , Mashiko Daisuke , Ikeda Zenki , Kobayashi Tetsuya J. , Yamagata Kazuo , Funahashi Akira 
Published: August 2021

AbstractIn assisted reproductive technology (ART), embryos produced by in vitro fertilization (IVF) are graded according to their live birth potential, and high-grade embryos are preferentially transplanted. However, the rate of live birth following clinical ART remains low worldwide, suggesting that grading is inaccurate. One explanation is that grading is classically based on the characteristic shape of embryos at a limited number of developmental stages and does not consider the shape of embryos and intracellular structures, e.g., nuclei, at various stages important for normal embryogenesis. Therefore, here we developed a Normalized Multi-View Attention Network (NVAN) that directly predicts live birth potential from nuclear structural features in live-cell fluorescence images taken of mouse embryos across a wide range of stages. The classification accuracy of our method was 83.87%, which greatly exceeded that of existing machine-learning methods and that of visual inspection by embryo culture specialists. By visualizing the features that contributed most to the prediction of live birth potential, we found that the size and shape of the cell nucleus at the morula stage and at the time of cell division were important for live birth prediction. We anticipate that our method will help ART and developmental engineering as a new basic technology for IVF embryo selection.
Optimized detection of allelic imbalances specific for homologous recombination deficiency improves the prediction of clinical outcomes in cancer
Authors: Perez-Villatoro Fernando , Oikkonen Jaana , Casado Julia , Chernenko Anastasiya , Gulhan Doga C. , Tumiati Manuela , Li Yilin , Lavikka Kari , Hietanen Sakari , Hynninen Johanna , Haltia Ulla-Maija , Tyrmi Jaakko S. , Laivuori Hannele , Konstantinopoulos Panagiotis A. , Hautaniemi Sampsa , Kauppi Liisa , Färkkilä Anniina 
Published: August 2021

ABSTRACTHomologous recombination DNA-repair deficiency (HRD) is a common driver of genomic instability and confers a therapeutic vulnerability in cancer. The accurate detection of somatic allelic imbalances (AIs) has been limited by methods focused onBRCA1/2mutations and using mixtures of cancer types. Using pan-cancer data, we revealed distinct patterns of AIs in high-grade serous ovarian cancer (HGSC). We used machine learning and statistics to generate improved criteria to identify HRD in HGSC (ovaHRDscar). ovaHRDscar significantly predicted clinical outcomes in three independent patient cohorts with higher precision than previous methods. Characterization of 98 spatiotemporally distinct metastatic samples revealed low intra-patient variation and indicated the primary tumor as the preferred site for clinical sampling in HGSC. Further, our approach improved the prediction of clinical outcomes in triple-negative breast cancer (tnbcHRDscar), validated in two independent patient cohorts. In conclusion, our tumor-specific, systematic approach has the potential to improve patient selection for HR-targeted therapies.
Uncovering non-random binary patterns within sequences of intrinsically disordered proteins
Authors: Cohan Megan C. , Shinn Min Kyung , Lalmansingh Jared M. , Pappu Rohit V. 
Published: August 2021

AbstractSequence-ensemble relationships of intrinsically disordered proteins (IDPs) are governed by binary patterns such as the linear clustering or mixing of specific residues or residue types with respect to one another. To enable the discovery of potentially important, shared patterns across sequence families, we describe a computational method referred to as NARDINI for Non-random Arrangement of Residues in Disordered Regions Inferred using Numerical Intermixing. This work was partially motivated by the observation that parameters that are currently in use for describing different binary patterns are not interoperable across IDPs of different amino acid compositions and lengths. In NARDINI, we generate an ensemble of scrambled sequences to set up a composition-specific null model for the patterning parameters of interest. We then compute a series of pattern-specific z-scores to quantify how each pattern deviates from a null model for the IDP of interest. The z-scores help in identifying putative non-random linear sequence patterns within an IDP. We demonstrate the use of NARDINI derived z-scores by identifying sequence patterns in three well-studied IDP systems. We also demonstrate how NARDINI can be deployed to study archetypal IDPs across homologs and orthologs. Overall, NARDINI is likely to aid in designing novel IDPs with a view toward engineering new sequence-function relationships or uncovering cryptic ones. We further propose that the z-scores introduced here are likely to be useful for theoretical and computational descriptions of sequence-ensemble relationships across IDPs of different compositions and lengths.
An experiential learning-integrated framework to improve problem-solving skills of engineering graduates
Authors: Sangwan Kuldip Singh , Singh Rajni 
Published: August 2021

PurposeProblem solving skills (PSS), an important component of learning outcomes, is one of the desirable skills in engineering graduates as stated by many employers, researchers and government bodies in India for a strong foothold in professional world. There is a need to develop comprehensive understanding and integration of theory (concept) and practice (process) of PSS in the context of experiential learning (EL).Design/methodology/approachThe present study is qualitative in nature using a conceptual research design focussing on synthesis and model building framework. The key elements of the study are PSS, EL and their integration. The study seeks to develop conceptual integration of PSS across multiple theories and perspectives. It offers an enhanced view of a concept of PSS by summarising and integrating extant knowledge. It presents the complete and comprehensive meaning/definition of PSS. Subsequently, it also explores EL and synthesises the different variants of EL that can be used to develop PSS. Finally, the study builds a theoretical framework that proposes integration and interplay between PSS and EL.FindingsProblem-solving operates at three levels: problem concept (nature and context), process (stages with strategies) and solution (open-ended). EL can be used as a tool to develop PSS in an integrated manner. It is found that EL and problem-solving interplay with each other as both are cyclic in nature and have commonalities strengthening each other.Practical implicationsThe proposed framework can be adopted in engineering education for making the engineering graduates job ready.Originality/valueThe study proposes a framework based on integration of EL and problem-solving focusing on specific aims and goals of the course, learning approaches, learning strategies and authentic learning (learning environment). This integration would bridge the gap between engineering education and industry requirements. EL integrated problem-solving focus on pedagogical knowledge (knowing how to facilitate discussion among learners and curricular knowledge) and instructional knowledge (knowing how to introduce, organise different methods and assess).
Numerical study of the propulsive performance of two-dimensional pitching foils at very high frequencies: scaling laws and turbulence effects
Authors: Sanmiguel-Rojas Enrique , Fernandez-Feria Ramon 
Published: August 2021

Purpose
This paper aims to analyze the propulsive performance of small-amplitude pitching foils at very high frequencies with double objectives: to find out scaling laws for the time-averaged thrust and propulsive efficiency at very high frequencies; and to characterize the Strouhal number above which the effect of turbulence on the mean values cannot be neglected.

Design/methodology/approach
The thrust force and propulsive efficiency of a pitching NACA0012 foil at high reduced frequencies (k) and a Reynolds number Re = 16 000 are analyzed using accurate numerical simulations, both assuming laminar flow and using a transition turbulence model. The time-averaged results are validated with available experimental data for k up to about 12 (Strouhal number, St, up to 0.6). This study also compares the present numerical results with the predictions of theoretical models and existing numerical results. For a foil pitching about its quarter chord with amplitude α0 = 8o, the reduced frequency is varied here up to k = 30 (St up to 2), much higher than in any previous numerical or experimental work.

Findings
For this pitch amplitude, turbulence effects are found negligible for St ≲ 0.8, and affecting less than 10% to the time-averaged thrust coefficient

CT¯ for larger St Linear potential theory fails for very large k, even for the small pitch amplitude considered, particularly for the power coefficient, and therefore for the propulsive efficiency. It is found that

CT¯ ∼ St2 for large St, in agreement with recent models, and the propulsive efficiency decays as 1/k, in disagreement with the linear potential theory.

Originality/value
Pitching foils are increasingly studied as efficient propellers and energy harvesting devices. Their performance at very high reduced frequencies has not been sufficiently analyzed before. The authors provide accurate numerical simulations to discern when turbulence is relevant for the computation of the time-averaged thrust and efficiency and how their scaling with the reduced frequency is affected in relation to the laminar-flow predictions. This is relevant because some small-amplitude theoretical models predict high propulsive efficiency of pitching foils at very high frequencies over certain ranges of the structural parameters, and only very accurate numerical simulations may decide on these predictions.
Numerical modelling of convection-diffusion problems with first-order chemical reaction using the dual reciprocity boundary element method
Authors: Al-Bayati Salam Adel , Wrobel Luiz C. 
Published: August 2021

Purpose
The purpose of this paper is to describe an extension of the boundary element method (BEM) and the dual reciprocity boundary element method (DRBEM) formulations developed for one- and two-dimensional steady-state problems, to analyse transient convection–diffusion problems associated with first-order chemical reaction.

Design/methodology/approach
The mathematical modelling has used a dual reciprocity approximation to transform the domain integrals arising in the transient equation into equivalent boundary integrals. The integral representation formula for the corresponding problem is obtained from the Green’s second identity, using the fundamental solution of the corresponding steady-state equation with constant coefficients. The finite difference method is used to simulate the time evolution procedure for solving the resulting system of equations. Three different radial basis functions have been successfully implemented to increase the accuracy of the solution and improving the rate of convergence.

Findings
The numerical results obtained demonstrate the excellent agreement with the analytical solutions to establish the validity of the proposed approach and to confirm its efficiency.

Originality/value
Finally, the proposed BEM and DRBEM numerical solutions have not displayed any artificial diffusion, oscillatory behaviour or damping of the wave front, as appears in other different numerical methods.