Miracle-dz/UniFAR-FTUs huggingface dataset:
Distribution maps of cetacean and seabird populations in the North‐East Atlantic

1. Distribution maps of cetaceans and seabirds at basin and monthly scales are needed for conservation and marine management. These are usually created from standardized and systematic aerial and vessel surveys, with recorded animal densities interpolated across study areas. However, distribution maps at basin and monthly scales have previously not been possible because individual surveys have restricted spatial and temporal coverage.2. This study develops an alternative approach consisting of: (a) collating diverse survey data to maximize spatial and temporal coverage, (b) using detection functions to estimate variation in the surface area covered (km2) among these surveys, standardizing measurements of effort and animal densities, and (c) developing species distribution models (SDM) that overcome issues with heterogeneous and uneven coverage. 3. 2.68 million km of survey data in the North‐East Atlantic between 1980 and 2018 were collated and standardized. SDM using Generalized Linear Models and General Estimating Equations in a hurdle approach were developed. Distribution maps were then created for 12 cetacean and 12 seabird species at 10 km and monthly resolution. Qualitative and quantitative assessment indicated good model performance.4. Synthesis and applications. This study provides the largest ever collation and standardization of diverse survey data for cetaceans and seabirds, and the most comprehensive distribution maps of these taxa in the North‐East Atlantic. These distribution maps have numerous applications including the identification of important areas needing protection, and the quantification of overlap between vulnerable species and anthropogenic activities. This study demonstrates how the analysis of existing and diverse survey data can meet conservation and marine management needs.
A dormant sub-population expressing interleukin-1 receptor characterises anti-estrogen resistant ALDH+ breast cancer stem cells

Estrogen receptor-positive (ER+) breast tumours are often treated with anti-estrogen (AE) therapies but frequently develop resistance. Cancer Stem Cells (CSCs) with high aldehyde dehydrogenase (ALDH) activity (ALDH+ cells) are reported to be enriched following AE treatment. Here we perform in vitro and in vivo functional CSC assays and gene expression analysis to characterise the ALDH+ population in AE resistant metastatic patient samples and an ER+ cell line. We show that the IL1β signalling pathway is activated in ALDH+ cells and data from single cells reveals that AE treatment selects for IL1R1-expressing ALDH+ cells. Importantly, we demonstrate that increased expression of IL1R1 is observed in the tumours of patients treated with AE therapy and predicts for treatment failure. Single-cell gene expression analysis revealed that at least 2 sub-populations exist within the ALDH+ population, one proliferative and one quiescent. Following AE therapy, the quiescent ALDH+IL1R1+ population is expanded, which suggests CSC dormancy as an adaptive strategy that facilitates treatment resistance. Supporting this, analysis of AE resistant dormant tumours reveals significantly increased expression of ALDH1A1, ALDH1A3 and IL1R1 genes. Thus, we propose that targeting of ALDH+IL1R1+ cells will reverse AE resistance, including in patients with minimal residual disease.
Contribution of fungal microbiome to intestinal physiology, early-life immune development and mucosal inflammation in mice

Gut microbiomes make major contributions to the physiological and immunological development of the host, but the relative importance of their bacterial and fungal components, and how they interact, remain largely unknown. We applied carefully controlled experiments in gnotobiotic mice colonized with defined communities of bacteria, fungi, or both to differentiate the direct role of fungi on microbiome assembly, host development, and susceptibility to colitis and airway inflammation. Our results revealed that fungal colonization alone was insufficient to promote the intestinal anatomic and physiological changes seen in mice colonized by bacteria, and had limited impact on the fecal metabolome. However, fungal colonization promoted major shifts in bacterial microbiome ecology, and had an independent effect on the innate and adaptive immune development in young mice. Fungi further exacerbated some aspects of the inflammatory effects of the bacterial community during OVA-induced airway inflammation by promoting macrophage infiltration in the airway. Our results demonstrate a dominant ecological and physiological role of bacteria in gut microbiomes, but highlight fungi as an ecological factor shaping the assembly of the bacterial community and a direct capacity to impact immune system and modulate disease susceptibility. These findings demonstrate that studies focused on bacteria alone provide an incomplete portrayal on microbiome ecology and functionality, and prompt for the inclusion of fungi in human microbiome studies.
PyVOL: a PyMOL plugin for visualization, comparison, and volume calculation of drug-binding sites

Motivation Binding pocket volumes are a simple yet important predictor of small molecule binding; however, generating visualizations of pocket topology and performing meaningful volume comparisons can be difficult with available tools. Current programs for accurate volume determination rely on extensive user input to define bulk solvent boundaries and to partition cavities into subpockets, increasing inter-user variability in measurements as well as time demands. Results We developed PyVOL, a python package with a PyMOL interface and GUI, to visualize, to characterize, and to compare binding pockets. PyVOL’s pocket identification algorithm is designed to maximize reproducibility through minimization of user-provided parameters, avoidance of grid-based methods, and automated subpocket identification. This approach permits efficient, scalable volume calculations. Availability PyVOL is released under the MIT License. Source code and documentation are available through github (https://github.com/schlessingerlab/pyvol/) with distribution through PyPI (bio-pyvol). Contact avner.schlessinger@mssm.edu, arvin.dar@mssm.edu
Development of Rhodotorula mucilaginosa strain via random mutagenesis for improved lipid production

Oleaginous yeasts are widely used for the production of biodiesel feedstocks because of their high lipid content. In this study, strain improvement was performed on the oleaginous yeast Rhodotorula mucilaginosa to generate mutants with higher lipid yields via random mutagenesis using ethyl methane sulfonate (EMS). Twenty-two mutant isolates prescreened with cerulenin were produced and further characterized via M13 PCR fingerprinting to determine their polymorphism and genetic distances. Eight strains, namely R. mucilaginosa M1, R. mucilaginosa M2, R. mucilaginosa M3, R. mucilaginosa M4, R. mucilaginosa M7, R. mucilaginosa M10, R. mucilaginosa M11 and R. mucilaginosa M18, were chosen based on their genetic distances from the parental strain for biomass production. Six mutants (M1, M2, M3, M4, M7 and M18) showing the highest dry cell weights were further selected for evaluation of lipid production in a laboratory-scale bioreactor using glucose as a carbon source. Results indicated that parental strain exhibited lipid content of 1.83±0.06 g/L, while strains M1, M2, M3, M7 and M18 generated 2.37±0.06 g/L, 2.27±0.06 g/L, 2.27±0.06 g/L, 3.10±0.00 g/L and 3.83±0.15 g/L of intracellular lipid, respectively. These five mutants were identified to have significant increase in lipid production compared to the parental strain. For FAME analysis, two selected strains M7 and M18 comprised of mainly C16 and C18 methyl esters, which are suitable for biodiesel production. This work demonstrated enhanced lipid production in R. mucilaginosa by random mutagenesis. The newly generated strains had higher lipid productivity compared to the parental strain. The application of these strains in industry may reduce the overall cost production of biodiesel.
Detecting prodromal Alzheimer’s disease with MRI through deep learning

Deep learning applied to MRI for Alzheimer’s classification is hypothesized to improve if the deep learning model implicates disease’s pathophysiology. The challenge in testing this hypothesis is that large-scale data are required to train this type of model. Here, we overcome this challenge by using a novel data augmentation strategy and show that our MRI-based deep learning model classifies Alzheimer’s dementia with high accuracy. Moreover, a class activation map was found dominated by signal from the hippocampal formation, a site where Alzheimer’s pathophysiology begins. Next, we tested the model’s performance in prodromal Alzheimer’s when patients present with mild cognitive impairment (MCI). We retroactively dichotomized a large cohort of MCI patients who were followed for up to 10 years into those with and without prodromal Alzheimer’s at baseline and used the dementia-derived model to generate individual ‘deep learning MRI’ scores. We compared the two groups on these scores, and on other biomarkers of amyloid pathology, tau pathology, and neurodegeneration. The deep learning MRI scores outperformed nearly all other biomarkers, including—unexpectedly—biomarkers of amyloid or tau pathology, in classifying prodromal disease and in predicting clinical progression. Providing a mechanistic explanation, the deep learning MRI scores were found to be linked to regional tau pathology, through investigations using cross-sectional, longitudinal, premortem and postmortem data. Our findings validate that a disease’s known pathophysiology can improve the design and performance of deep learning models. Moreover, by showing that deep learning can extract useful biomarker information from conventional MRIs, the advantages of this model extend practically, potentially reducing patient burden, risk, and cost.
Genome-scale Model Constrained by Proteomics Reveals Metabolic Rearrangements in the Heterologous Host Streptomyces coelicolor

Streptomyces coelicolor M1152 is a widely used host strain for the heterologous production of novel small molecule natural products, genetically engineered for this purpose through e.g. deletion of four of its native biosynthetic gene clusters (BGCs) for improved precursor supply. Regardless of its potential, a systems understanding of its tight regulatory network and the effects of the significant genomic changes in M1152 is missing. In this study, we compare M1152 to its ancestor M145, thereby connecting observed phenotypic differences to changes on transcription and translation. Measured protein levels are connected to predicted metabolic fluxes, facilitated by an enzyme-constrained genome-scale model (GEM), that by itself is a consensus result of a community effort. This approach connects observed differences in growth rate and glucose consumption to changes in central carbon metabolism, accompanied by differential expression of important regulons. Results suggest that precursors supply is not limiting secondary metabolism, informing that alternative strategies will be beneficial for further development of S. coelicolor for heterologous production of novel compounds. Importance This study provides the first systems description of S. coelicolor M1152, an engineered heterologous expression host widely used for the production and discovery of natural products. By combining time-series proteomics and transcriptomics, batch fermentation data and genome-scale modelling we can connect observed phenotypes to known genetic modifications and find extensive metabolic rearrangements in the M1152 strain compared to the wild-type stain M145. We furthermore found that the rational strategy of enhancing precursor supply will surprisingly only have limited impact. Instrumental to this study has been the genome-scale model that has allowed us to contextualize the transcriptional changes. To consolidate recent efforts in this field we reconstructed the consensus model Sco-GEM in an open-science framework. This approach facilitates further development by the research community in an organized manner, including version control, continuous integration and quality control and tracking of individual contributions.
ESTUDO HISTOLÓGICO DE PÓLIPOS MENORES QUE 5mm RESSECADOS POR COLONOSCOPIA

RESUMO: Estudamos 1858 videocolonoscopias realizadas no Servico de Coloproctologia do Hospital Prof. Edmundo Vasconcelos, no periodo de abril/96 a dezembro/99. Destas, 255 (13,72%) apresentavam polipos menores que 5mm, sendo 136 doentes (53,33%) do sexo masculino e 119 (46,66%) do sexo feminino. A media de idade foi de 53,64 anos (17-89 anos) e a maioria dos pacientes (70,98%) encontrava-se entre os 40 e 70 anos de idade. Dos 352 polipos estudados (media de 1,38 polipos/paciente), 39,77% dos casos eram adenomatosos, com distribuicao proporcional em todos os segmentos colorretais. Concluimos pela importância da polipectomia endoscopica, independentemente do tamanho da lesao, visto que aproximadamente 40% sao de origem adenomatosa e que sua localizacao topografica nao e fator preditivo de seu perfil histologico.
Prevalence of mastitis in dairy goat farms in Eastern Algeria

Aim: This study aimed to investigate mastitis in dairy goat farms through the California mastitis test (CMT) and bacteriological examinations Materials and Methods: A total of 845 goats belonging to 18 farms from four regions (Tébessa, Guelma, Souk Ahras, and Skikda) were examined. Results: Clinical examination of the mammary glands showed that 30/845 (3.55%) goats had clinical mastitis and 32 goats had half-teat inflammation. CMT subclinical mastitis (SCM) was detected in 815 goats that were presumed to be healthy. CMT showed 46 (5.64%) CMT-positive goats as well as 47 (2.88%) positive half-udders with a score of ≥2. A total of 79 bacteria were isolated and identified from the 79 bacterial positive samples. Bacteriological analyses showed that Gram-positive staphylococci were largely responsible for clinical and SCM. Coagulase-negative staphylococci, with an isolation frequency of 56.96%, were the most prevalent bacteria from all isolated organisms. The second most prevalent organism was Staphylococcus aureus at 40.50% and streptococci (2.53%) had the smallest percentage of isolation. Conclusion: It is suggested that due to the prevalence of mastitis in this species, farmers should be aware of the problem to plan preventive and control measures to reduce dairy goat losses due to this disease.
Transplante hematopoyetico alogenico con celulas progenitoras extraidas de la sangre periferica

Cinquenta y tres pacientes (ptes) recibieron transplante alogenico con celulas progenitoras extraidas de la sangre periferica (PSP); 25 ptes eran mujeres y 28 varones. La edad media del grupo fue de 20 anos, (rango 2-550. Los diagnosticos fueron leucemia mieloide aguda (LMA) en 16 ptes, leucemia linfoblastica aguda (LLA) en 15, leucemia mieloide cronica (LMC) en primera fase cronica en 12, aplasia medular en 4, sindrome mielodisplasico en 3 y Enfermedad de Hodgkin en recaida luego de trasplante autologo, talasemia mayor y sindrome de Hunter en 1 caso, respectivamente. Los acondicionamientos fueron en 38 ptes radioterapia corporal total 1200 cGy y ciclofosfamida 120 mg/kg EV; en 10 ptes busulfan 16 mg/kg y ciclosfosfamida 120 mg/kg EV, 3 ptes radioterapia linfoide total (RLT) y ciclosfosfamida, 2 ptes con otros agentes quimioterapicos. Los PSP se infundieron a traves de un cateter sin ningun tipo de manipulacion. La profilaxis de injerto vs huesped (EICH) se realizo con ciclosporina y metotrexato. Los donantes fueron familiares con HLA compatibles 6/6 y un caso 5/6 de los antigenos. Previo a la extracion de PSP, recibieron G-DSF (filgrastim) 10 mug/kg/dia sc. Cuatro dias. El quinto dia se realizo la feresis, en los primeros treinta casos se hizo la extraccion adicional de medula osea. Las medias de CD34, CD3, CD4, CD8, CD56, CD19 (cel x 10(6)/kg de peso) 4.12; 4.59; 2.57; 1.9; 0.55 y 0.68 respectivamente. La mediana de recuperacion de nuetrofilos > 500 se obtuvo el dia = 11 y de plaquetas > 20000, + 13. El tiempo de internacion fue de 26 dias (18-39) y la media de dias con antibioticos parenterales fue de 12.2 dias (5-45). La mortalidad relacionada al trasplante fue del 15 por ciento. EICH aguda se observo en el 43.4 por ciento de los ptes, con solo 5 ptes con EICH aguda grado III o IV. En 43 ptes se pudo evaluar la aparicion de EICH cronica con un tiempo medio de seguimiento de 18 meses (4-39). En la presente experiencia el trasplante de PSP alogenicos mantuvo una aceptable incidencia de EICH cronica; dados los recientes informes de aumento de esta complicacion, parece logico desaconsejar el uso de PSP en patologia no maligna en la que no importaria la potencia del efecto injerto versus leucemia. (AU)
Capillary resistance and blood pressure changes associated with pain due to local cooling: cold pressor test

Measurements of capillary resistance and blood pressure were made before and after immersion of the right hand in ice water for 5 minutes. The capillary resistance rose sharply immediately after stress and remained elevated for over 3 hours, returning to normal in 21 hours, while the blood pressure response reached its peak in 90 seconds. A significant negative correlation was found between the maximum changes in capillary resistance and blood pressure. Submitted on March 5, 1959
INFLUENCE OF SOWING DATE ON DEVELOPMENT, HARVEST INDEX AND YIELD COMPONENTS FOR BREAD WHEAT CULTIVARS HAVING DIFFERENT THERMAL RESPONSES IN MIDDLE EGYPT

Two experiments were conducted in 2010/2011, 2011/2012 at Malawi Agric. Res. Sta. , ARC to investigate the effect of sowing date according to the thermal time on developmental traits, yield and its component of four bread wheat cultivars (Triticum aestivum L) i.e. Giza168, Sids-1, Sids-12 and Shanwel-1 (Hexaploid) in three sowing dates i.e. 21 st November, 10 th December and 30 th December . The results showed that mean of all the sowing dates and cultivars arrived to anthesis at 88.6 DAS (881.4 ̊c) and to maturity 141.3 DAS (1671.2 ̊c) in season 1, however they arrived to anthesis at 98.5 DAS (973.0 ̊c) and to maturity 152.6 DAS (1986.5 ̊c) in season 2. Heading date and anthesis were significantly affected by cultivars and sowing dates in both two growing seasons, also the interaction in the second season. Days to maturity were significantly affected by sowing date in two growing seasons and the interaction in the first season. Plant height was differed significantly by cultivars in two growing seasons and by sowing date and their interaction in the second season. No. spikes/m2 was significantly affected by sowing dates in both growing seasons and cultivars in the second season and their interaction in the first season. No. kernels/spike was significantly affected by cultivars, sowing dates and their interaction in the second season only. The weight of 1000-kernels was significantly affected by sowing date in two growing seasons and by cultivars and their interaction in the second season only. Grain filling period was significantly affected by sowing dates in two growing seasons and the interaction between cultivars × sowing date in the second season. Grain yield / plot (kg) was significantly affected by cultivars and sowing dates in two growing seasons. Harvest index was significantly affected by cultivars in first season and by sowing date and their interaction in the second season. Mean H.I. of Sids12 was slightly higher than other cultivars. Mean H.I. in sowing dates of optimum was higher than other dates in two growing seasons and their interaction in the second season. Conclusions: The obtained results revealed that: 1The tested wheat genotypes were differed significantly among them in accordance to temperature and photoperiod requirements. 2This study must be continuously arranged with all new released wheat genotypes for determining appropriate planting time for high yield.
Parallel Factor Analysis for multidimensional decomposition of fNIRS data

Significance Current techniques for data analysis in functional near-infrared spectroscopy (fNIRS), such as artifact correction, do not allow to integrate the information originating from both wavelengths, considering only temporal and spatial dimensions of the signal’s structure. Parallel factor analysis (PARAFAC) has previously been validated as a multidimensional decomposition technique in other neuroimaging fields. Aim We aimed to introduce and validate the use of PARAFAC for the analysis of fNIRS data, which is inherently multidimensional (time, space, wavelength). Approach We used data acquired in 17 healthy adults during a verbal fluency task to compare the efficacy of PARAFAC for motion artifact correction to traditional 2D decomposition techniques, i.e. target principal (tPCA) and independent component analysis (ICA). Correction performance was further evaluated under controlled conditions with simulated artifacts and hemodynamic response functions. Results PARAFAC achieved significantly higher improvement in data quality as compared to tPCA and ICA. Correction in several simulated signals further validated its use and promoted it as a robust method independent of the artifact’s characteristics. Conclusions This study describes the first implementation of PARAFAC in fNIRS and provides validation for its use to correct artifacts. PARAFAC is a promising data-driven alternative for multidimensional data analyses in fNIRS and this study paves the way for further applications.
A chemical perspective on high pressure crystal structures and properties

Abstract The general availability of third generation synchrotron sources has ushered in a new era of high pressure research. The crystal structure of materials under compression can now be determined by X-ray diffraction using powder samples and, more recently, from multi-nano single crystal diffraction. Concurrently, these experimental advancements are accompanied by a rapid increase in computational capacity and capability, enabling the application of sophisticated quantum calculations to explore a variety of material properties. One of the early surprises is the finding that simple metallic elements do not conform to the general expectation of adopting 3D close-pack structures at high pressure. Instead, many novel open structures have been identified with no known analogues at ambient pressure. The occurrence of these structural types appears to be random with no rules governing their formation. The adoption of an open structure at high pressure suggested the presence of directional bonds. Therefore, a localized atomic hybrid orbital description of the chemical bonding may be appropriate. Here, the theoretical foundation and experimental evidence supporting this approach to the elucidation of the high pressure crystal structures of group I and II elements and polyhydrides are reviewed. It is desirable and advantageous to extend and apply established chemical principles to the study of the chemistry and chemical bonding of materials at high pressure.
Avaliação da Replicação e Tolerância a Falhas nos Sistemas Cassandra e MongoDB

Cada vez mais bancos nao relacionais (NoSQL) sao utilizados, suprindo a necessidade de alta disponibilidade, armazenamento e manipulacao de grande volume de dados nao estruturados. Existem varios artigos que fazem avaliacao de sistemas NoSQL, porem nao abrangem caracteristicas de tolerâncias a falhas, que normalmente sao empregadas em varias computadores. Este trabalho visa executar o teste de replicacao e tolerância a falhas nos principais sistemas NoSQL, o Cassandra e MongoDB. Os testes seguem uma metodologia proposta e os resultados mostram baixa taxa de erros em relacaoa disponibilidade das informacoes durante a execucao das cargas de trabalhos e injecao de falhas.