bluuebunny/crossref_metadata_2025_split huggingface dataset:
Unveiling the unknown phylogenetic position of the scallop Austrochlamys natans and its implications for marine stewardship in the Magallanes Province
Authors: Rosenfeld Sebastián , Aldea Cristian , López Zambra , Maturana Claudia S. , Ojeda Jaime , Bahamonde Francisco , Detrée Camille , Mansilla Andrés , Poulin Elie , Gérard Karin 
Published: March 2021

AbstractTwo species of scallop, Austrochlamys natans (“Ostión del Sur”) and Zygochlamys patagonica (“Ostión patagonico”) are presently exploited in the southern part of the Magallanes Province (MP). The lack of clarity in taxonomic identification and ecological aspects is generating both erroneous extraction statistics and an unperceived harvesting pressure on A. natans and Z. patagonica. We aim to discriminate these Magallanes scallops accurately, improve our understanding of their complex natural history and discuss possible implications for their management and conservation status, given the current fisheries statistics. To achieve these goals, we present a complete review of the historical identification of the Magallanes scallop and a multi-locus molecular phylogeny which allowed us to recover the phylogenetic position of A. natans. We sampled 54 individuals from five localities across the southern Pacific coast of the MP. We calculated the depth of the byssal notch (BND) and shell height (VH) ratio from morphological characters and conducted phylogenetic reconstructions with mitochondrial (12S and 16S) and nuclear markers (28S) using Bayesian and maximum likelihood analyses. Both morphology and molecular phylogeny identified two distinct entities, Z. patagonica and a distinct, highly divergent lineage that corresponds to A. natans. Our study provides integrative evidence to alert the current fishery management and the need for further conservation studies.
An R package for generic modular response analysis and its application to estrogen and retinoic acid receptor crosstalk
Authors: Jimenez-Dominguez Gabriel , Ravel Patrice , Jalaguier Stéphan , Cavaillès Vincent , Colinge Jacques 
Published: March 2021

AbstractModular response analysis (MRA) is a widely used inference technique developed to uncover directions and strengths of connections in molecular networks under a steady-state condition by means of perturbation experiments. We devised several extensions of this methodology to search genomic data for new associations with a biological network inferred by MRA, to improve the predictive accuracy of MRA-inferred networks, and to estimate confidence intervals of MRA parameters from datasets with low numbers of replicates. The classical MRA computations and their extensions were implemented in a freely available R package called aiMeRA (https://github.com/bioinfo-ircm/aiMeRA/). We illustrated the application of our package by assessing the crosstalk between estrogen and retinoic acid receptors, two nuclear receptors implicated in several hormone-driven cancers, such as breast cancer. Based on new data generated for this study, our analysis revealed potential cross-inhibition mediated by the shared corepressors NRIP1 and LCoR. We designed aiMeRA for non-specialists and to allow biologists to perform their own analyses.
Effect of autogenous crack self-healing on mechanical strength recovery of cement mortar under various environmental exposure
Authors: Suleiman A. R. , Nehdi M. L. 
Published: March 2021

AbstractWhile research on self-healing of cement-based materials has recently gained considerable attention and made sizable progress, there is still ongoing debate and controversy regarding the effect of crack closing induced by autogenous self-healing on mechanical strength recovery. Despite that several techniques have been used to capture and quantify the self-healing of surface cracks, the resulting effect on mechanical strength has not, to date, been explored and quantified in a rigorous and systematic manner. Therefore, in this study, a broad array of multi-scale techniques including non-destructive shear wave velocity, high-resolution X-ray computed tomography (µCT), and 3D image analysis was deployed to examine the effects of autogenous crack self-healing on the mechanical strength recovery in various mortar specimens. The influence of microstructural changes induced by additives such as swelling compounds, silica-based additions, and carbonating minerals on strength recovery under diverse environmental exposures was further explored. The results capture the relationship between the crack closing mechanism imparted by self-healing and mechanical strength recovery, therefore elucidating the discrepancies in mechanical strength recovery results reported in the open literature.
Individual differences in dominance-related traits drive dispersal and settlement in hatchery-reared juvenile brown trout
Authors: Sánchez-González Jorge R. , Nicieza Alfredo G. 
Published: March 2021

AbstractEffective management of exploited populations is based on an understanding of population dynamics and evolutionary processes. In spatially structured populations, dispersal is a central process that ultimately can affect population growth and viability. It can be influenced by environmental conditions, individual phenotypes, and stochastic factors. However, we have a limited knowledge of the relative contribution of these components and its interactions, and which traits can be used as reliable predictors of the dispersal ability. Here, we conducted a longitudinal field experiment aimed to identify traits which can be used as proxy for dispersal in juvenile brown trout (Salmo truttaL.). We measured body size and standard metabolic rates, and estimated body shapes for 212 hatchery-reared juvenile fish that were marked with individual codes and released in a small coastal stream in northwest Spain. We registered fish positions and distances to the releasing point after 19, 41, 60 and 158 days in the stream. We detected a high autocorrelation of dispersal distances, demonstrating that most individuals settle down relatively soon and then hold stable positions over the study period. Body size and fish shape were reliable predictors of dispersal, with bigger and more robust-set individuals being more likely to settle closer to the release site than smaller and more elongated fish. In addition, the analysis of spacing and spatial patterns indicated that the dispersal of introduced fish could affect the distribution of resident conspecifics. All together, these results suggest that stocking programs aimed to the enhancement of overexploited populations at fine spatial scales can be optimized by adjusting the size and shape of the introduced fish to specific management targets and environmental conditions.
Hand rehabilitation with sonification techniques in the subacute stage of stroke
Authors: Raglio Alfredo , Panigazzi Monica , Colombo Roberto , Tramontano Marco , Iosa Marco , Mastrogiacomo Sara , Baiardi Paola , Molteni Daniele , Baldissarro Eleonora , Imbriani Chiara , Imarisio Chiara , Eretti Laura , Hamedani Mehrnaz , Pistarini Caterina , Imbriani Marcello , Mancardi Gian Luigi , Caltagirone Carlo 
Published: March 2021

AbstractAfter a stroke event, most survivors suffer from arm paresis, poor motor control and other disabilities that make activities of daily living difficult, severely affecting quality of life and personal independence. This randomized controlled trial aimed at evaluating the efficacy of a music-based sonification approach on upper limbs motor functions, quality of life and pain perceived during rehabilitation. The study involved 65 subacute stroke individuals during inpatient rehabilitation allocated into 2 groups which underwent usual care dayweek) respectively of standard upper extremity motor rehabilitation or upper extremity treatment with sonification techniques. The Fugl-Meyer Upper Extremity Scale, Box and Block Test and the Modified Ashworth Scale were used to perform motor assessment and the McGill Quality of Life-it and the Numerical Pain Rating Scale to assess quality of life and pain. The assessment was performed at baseline, after 2 weeks, at the end of treatment and at follow-up (1 month after the end of treatment). Total scores of the Fugl-Meyer Upper Extremity Scale (primary outcome measure) and hand and wrist sub scores, manual dexterity scores of the affected and unaffected limb in the Box and Block Test, pain scores of the Numerical Pain Rating Scale (secondary outcomes measures) significantly improved in the sonification group compared to the standard of care group (time*group interaction < 0.05). Our findings suggest that music-based sonification sessions can be considered an effective standardized intervention for the upper limb in subacute stroke rehabilitation.
A primitive type of renin-expressing lymphocyte protects the organism against infections
Authors: Belyea Brian C. , Santiago Araceli E. , Vasconez Wilson A. , Nagalakshmi Vidya K. , Xu Fang , Mehalic Theodore C. , Sequeira-Lopez Maria Luisa S. , Gomez R. Ariel 
Published: March 2021

AbstractThe hormone renin plays a crucial role in the regulation of blood pressure and fluid-electrolyte homeostasis. Normally, renin is synthesized by juxtaglomerular (JG) cells, a specialized group of myoepithelial cells located near the entrance to the kidney glomeruli. In response to low blood pressure and/or a decrease in extracellular fluid volume (as it occurs during dehydration, hypotension, or septic shock) JG cells respond by releasing renin to the circulation to reestablish homeostasis. Interestingly, renin-expressing cells also exist outside of the kidney, where their function has remained a mystery. We discovered a unique type of renin-expressing B-1 lymphocyte that may have unrecognized roles in defending the organism against infections. These cells synthesize renin, entrap and phagocyte bacteria and control bacterial growth. The ability of renin-bearing lymphocytes to control infections—which is enhanced by the presence of renin—adds a novel, previously unsuspected dimension to the defense role of renin-expressing cells, linking the endocrine control of circulatory homeostasis with the immune control of infections to ensure survival.
Characterization of new cristamonad species from kalotermitid termites including a novel genus, Runanympha
Authors: Singh Racquel A. , Boscaro Vittorio , James Erick R. , Karnkowska Anna , Kolisko Martin , Gavelis Gregory S. , Okamoto Noriko , del Campo Javier , Fiorito Rebecca , Hehenberger Elisabeth , Irwin Nicholas A. T. , Mathur Varsha , Scheffrahn Rudolf H. , Keeling Patrick J. 
Published: March 2021

AbstractCristamonadea is a large class of parabasalian protists that reside in the hindguts of wood-feeding insects, where they play an essential role in the digestion of lignocellulose. This group of symbionts boasts an impressive array of complex morphological characteristics, many of which have evolved multiple times independently. However, their diversity is understudied and molecular data remain scarce. Here we describe seven new species of cristamonad symbionts from Comatermes, Calcaritermes, and Rugitermes termites from Peru and Ecuador. To classify these new species, we examined cells by light and scanning electron microscopy, sequenced the symbiont small subunit ribosomal RNA (rRNA) genes, and carried out barcoding of the mitochondrial large subunit rRNA gene of the hosts to confirm host identification. Based on these data, five of the symbionts characterized here represent new species within described genera: Devescovina sapara n. sp., Devescovina aymara n. sp., Macrotrichomonas ashaninka n. sp., Macrotrichomonas secoya n. sp., and Macrotrichomonas yanesha n. sp. Additionally, two symbionts with overall morphological characteristics similar to the poorly-studied and probably polyphyletic ‘joeniid’ Parabasalia are classified in a new genus Runanympha n. gen.: Runanympha illapa n. sp., and Runanympha pacha n. sp.
DOT1L inhibitors block abnormal self-renewal induced by cohesin loss
Authors: Heimbruch Katelyn E. , Fisher Joseph B. , Stelloh Cary T. , Phillips Emily , Reimer Michael H. , Wargolet Adam J. , Meyer Alison E. , Pulakanti Kirthi , Viny Aaron D. , Loppnow Jessica J. , Levine Ross L. , Pulikkan John Anto , Zhu Nan , Rao Sridhar 
Published: March 2021

AbstractAcute myeloid leukemia (AML) is a high-risk malignancy characterized by a diverse spectrum of somatic genetic alterations. The mechanisms by which these mutations contribute to leukemia development and how this informs the use of targeted therapies is critical to improving outcomes for patients. Importantly, how to target loss-of-function mutations has been a critical challenge in precision medicine. Heterozygous inactivating mutations in cohesin complex genes contribute to AML in adults by increasing the self-renewal capacity of hematopoietic stem and progenitor cells (HSPCs) by altering PRC2 targeting to induce HOXA9 expression, a key self-renewal transcription factor. Here we sought to delineate the epigenetic mechanism underpinning the enhanced self-renewal conferred by cohesin-haploinsufficiency. First, given the substantial difference in the mutational spectrum between pediatric and adult AML patients, we first sought to identify if HOXA9 was also elevated in children. Next, using primary HSPCs as a model we demonstrate that abnormal self-renewal due to cohesin loss is blocked by DOT1L inhibition. In cohesin-depleted cells, DOT1L inhibition is associated with H3K79me2 depletion and a concomitant increase in H3K27me3. Importantly, we find that there are cohesin-dependent gene expression changes that promote a leukemic profile, including HoxA overexpression, that are preferentially reversed by DOT1L inhibition. Our data further characterize how cohesin mutations contribute to AML development, identifying DOT1L as a potential therapeutic target for adult and pediatric AML patients harboring cohesin mutations.
Towards global flood mapping onboard low cost satellites with machine learning
Authors: Mateo-Garcia Gonzalo , Veitch-Michaelis Joshua , Smith Lewis , Oprea Silviu Vlad , Schumann Guy , Gal Yarin , Baydin Atılım Güneş , Backes Dietmar 
Published: March 2021

AbstractSpaceborne Earth observation is a key technology for flood response, offering valuable information to decision makers on the ground. Very large constellations of small, nano satellites— ’CubeSats’ are a promising solution to reduce revisit time in disaster areas from days to hours. However, data transmission to ground receivers is limited by constraints on power and bandwidth of CubeSats. Onboard processing offers a solution to decrease the amount of data to transmit by reducing large sensor images to smaller data products. The ESA’s recent PhiSat-1 mission aims to facilitate the demonstration of this concept, providing the hardware capability to perform onboard processing by including a power-constrained machine learning accelerator and the software to run custom applications. This work demonstrates a flood segmentation algorithm that produces flood masks to be transmitted instead of the raw images, while running efficiently on the accelerator aboard the PhiSat-1. Our models are trained on WorldFloods: a newly compiled dataset of 119 globally verified flooding events from disaster response organizations, which we make available in a common format. We test the system on independent locations, demonstrating that it produces fast and accurate segmentation masks on the hardware accelerator, acting as a proof of concept for this approach.
3D-printed micro bubble column reactor with integrated microsensors for biotechnological applications: From design to evaluation
Authors: Frey Lasse Jannis , Vorländer David , Ostsieker Hendrik , Rasch Detlev , Lohse Jan-Luca , Breitfeld Maximilian , Grosch Jan-Hendrik , Wehinger Gregor D. , Bahnemann Janina , Krull Rainer 
Published: March 2021

AbstractWith the technological advances in 3D printing technology, which are associated with ever-increasing printing resolution, additive manufacturing is now increasingly being used for rapid manufacturing of complex devices including microsystems development for laboratory applications. Personalized experimental devices or entire bioreactors of high complexity can be manufactured within few hours from start to finish. This study presents a customized 3D-printed micro bubble column reactor (3D-µBCR), which can be used for the cultivation of microorganisms (e.g., Saccharomyces cerevisiae) and allows online-monitoring of process parameters through integrated microsensor technology. The modular 3D-µBCR achieves rapid homogenization in less than 1 s and high oxygen transfer with kLa values up to 788 h−1 and is able to monitor biomass, pH, and DOT in the fluid phase, as well as CO2 and O2 in the gas phase. By extensive comparison of different reactor designs, the influence of the geometry on the resulting hydrodynamics was investigated. In order to quantify local flow patterns in the fluid, a three-dimensional and transient multiphase Computational Fluid Dynamics model was successfully developed and applied. The presented 3D-µBCR shows enormous potential for experimental parallelization and enables a high level of flexibility in reactor design, which can support versatile process development.
Differential reprogramming of breast cancer subtypes in 3D cultures and implications for sensitivity to targeted therapy
Authors: Koedoot Esmee , Wolters Liesanne , Smid Marcel , Stoilov Peter , Burger Gerhard A. , Herpers Bram , Yan Kuan , Price Leo S. , Martens John W. M. , Le Dévédec Sylvia E. , van de Water Bob 
Published: March 2021

AbstractScreening for effective candidate drugs for breast cancer has shifted from two-dimensional (2D) to three-dimensional (3D) cultures. Here we systematically compared the transcriptomes of these different culture conditions by RNAseq of 14 BC cell lines cultured in both 2D and 3D conditions. All 3D BC cell cultures demonstrated increased mitochondrial metabolism and downregulated cell cycle programs. Luminal BC cells in 3D demonstrated overall limited reprogramming. 3D basal B BC cells showed increased expression of extracellular matrix (ECM) interaction genes, which coincides with an invasive phenotype not observed in other BC cells. Genes downregulated in 3D were associated with metastatic disease progression in BC patients, including cyclin dependent kinases and aurora kinases. Furthermore, the overall correlation of the cell line transcriptome to the BC patient transcriptome was increased in 3D cultures for all TNBC cell lines. To define the most optimal culture conditions to study the oncogenic pathway of interest, an open source bioinformatics strategy was established.
Identifying unknown Indian wolves by their distinctive howls: its potential as a non-invasive survey method
Authors: Sadhukhan Sougata , Root-Gutteridge Holly , Habib Bilal 
Published: March 2021

AbstractPrevious studies have posited the use of acoustics-based surveys to monitor population size and estimate their density. However, decreasing the bias in population estimations, such as by using Capture–Mark–Recapture, requires the identification of individuals using supervised classification methods, especially for sparsely populated species like the wolf which may otherwise be counted repeatedly. The cryptic behaviour of Indian wolf (Canis lupus pallipes) poses serious challenges to survey efforts, and thus, there is no reliable estimate of their population despite a prominent role in the ecosystem. Like other wolves, Indian wolves produce howls that can be detected over distances of more than 6 km, making them ideal candidates for acoustic surveys. Here, we explore the use of a supervised classifier to identify unknown individuals. We trained a supervised Agglomerative Nesting hierarchical clustering (AGNES) model using 49 howls from five Indian wolves and achieved 98% individual identification accuracy. We tested our model’s predictive power using 20 novel howls from a further four individuals (test dataset) and resulted in 75% accuracy in classifying howls to individuals. The model can reduce bias in population estimations using Capture-Mark-Recapture and track individual wolves non-invasively by their howls. This has potential for studies of wolves’ territory use, pack composition, and reproductive behaviour. Our method can potentially be adapted for other species with individually distinctive vocalisations, representing an advanced tool for individual-level monitoring.
Prediction of response of methotrexate in patients with rheumatoid arthritis using serum lipidomics
Authors: Maciejewski Mateusz , Sands Caroline , Nair Nisha , Ling Stephanie , Verstappen Suzanne , Hyrich Kimme , Barton Anne , Ziemek Daniel , Lewis Matthew R. , Plant Darren 
Published: March 2021

AbstractMethotrexate (MTX) is a common first-line treatment for new-onset rheumatoid arthritis (RA). However, MTX is ineffective for 30–40% of patients and there is no way to know which patients might benefit. Here, we built statistical models based on serum lipid levels measured at two time-points (pre-treatment and following 4 weeks on-drug) to investigate if MTX response (by 6 months) could be predicted. Patients about to commence MTX treatment for the first time were selected from the Rheumatoid Arthritis Medication Study (RAMS). Patients were categorised as good or non-responders following 6 months on-drug using EULAR response criteria. Serum lipids were measured using ultra‐performance liquid chromatography–mass spectrometry and supervised machine learning methods (including regularized regression, support vector machine and random forest) were used to predict EULAR response. Models including lipid levels were compared to models including clinical covariates alone. The best performing classifier including lipid levels (assessed at 4 weeks) was constructed using regularized regression (ROC AUC 0.61 ± 0.02). However, the clinical covariate based model outperformed the classifier including lipid levels when either pre- or on-treatment time-points were investigated (ROC AUC 0.68 ± 0.02). Pre- or early-treatment serum lipid profiles are unlikely to inform classification of MTX response by 6 months with performance adequate for use in RA clinical management.
Predicting mortality risk for preterm infants using random forest
Authors: Lee Jennifer , Cai Jinjin , Li Fuhai , Vesoulis Zachary A. 
Published: March 2021

AbstractMortality is an unfortunately common outcome of extremely and very preterm birth. Existing clinical prediction models capture mortality risk at birth but fail to account for the remainder of the hospital course. Infants born < 32 weeks gestation with complete physiologic and clinical data were included in this retrospective study. Mortality risk was quantified by conventional means (clinical factors) using the CRIB-II score and the optimal logistic regression model. A random forest (RF) model was trained using a subset of the cohort, labeling data within 6 h of death as “worry.” The model was then tested using the remaining infants. A total of 275 infants were included in the study with a mean gestational age of 27 weeks, mean birth weight of 929 g, 49% female, and a mortality rate of 21%. The CRIB-II and logistic regression models had acceptable performance with sensitivities of 71% and 80% AUC scores of 0.78 and 0.84, respectively. The RF model had superior performance with a sensitivity of 88% and an AUC of 0.93. A random forest model which incorporates fixed clinical factors with the influence of aberrancies in subsequent physiology has superior performance for mortality prediction compared to conventional models.