Miracle-dz/UniFAR-FTUs huggingface dataset:
Control of Penicillium glabrum by Indigenous Antagonistic Yeast from Vineyards

Biocontrol is one of the most promising alternatives to synthetic fungicides for food preservation. Botrytis cinerea, Alternaria alternata, and Aspergillus section Nigri are the most concerning pathogens for grape development. However, frequently, other species, such as Penicillium glabrum in this study, are predominant in spoiled bunches. In this work, 54 native yeasts from vineyards were screened by direct confrontation in potato dextrose agar plates as antagonists against P. glabrum. Isolates of Pichia terricola, Aureobasidium pullulans, and Zygoascus meyerae were selected for their antagonist activity in vitro, plus isolates of Pichia kudriavzevii, Hormonema viticola, and Hanseniaspora uvarum were used as negative controls. However, in vivo, confrontations in wounded grapes showed disagreement with direct confrontation in vitro. P. terricola, P. kudriavzevii, H. viticola, Z. meyerae, and H. uvarum significantly reduced the incidence of P. glabrum on grapes. Nevertheless, P. terricola, H. viticola, and H. uvarum themselves spoiled the wounded grapes. Inhibitions were associated with different mechanisms such as the production of volatile organic compounds (VOCs), lytic enzymes, biofilm formation, and competition for nutrients. The isolates of P. kudriavzevii L18 (a producer of antifungal VOCs which completely inhibited the incidence of P. glabrum) and Z. meyerae L29 (with pectinase, chitinase and β-glucanase activity and biofilm formation which reduced 70% of the incidence of P. glabrum) are proposed as suitable biocontrol agents against P. glabrum.
Modified BET models for modeling water vapor sorption in hydrophilic glassy polymers and systems deviating strongly from ideality

The use of two modified BET models for modeling water vapor sorption in various nonideal systems involving strong interactions (textiles, polyamides, polyimide, vinyl polymers, proteins, and related compounds) has been investigated. Contrary to the original BET model derived for multimolecular adsorption and restricted to low water activities only, the three-parameter BET model, which considers sorption on a limited number of sorption layers, allowed the modeling for activities up to 0.9. This model has been shown to be an important extension of the original model but remains limited, due to the divergence of the model for a → 1. Releasing an other important assumption of the BET model, the GAB model was then investigated and its striking efficiency, in terms of high correlation coefficients and low residual sums of squares, was demonstrated for activities up to 0.95, thus covering all the usual experimental range. © 1998 John Wiley & Sons, Inc. J Appl Polym Sci 67:1415–1430, 1998
Post-Contrast Acute Kidney Injury and Intravenous Prophylactic Hydration: An Update

Abstract Background Despite tremendous improvement in molecular properties over the last century, intravascular injection of iodinated contrast material may still have systemic and hemodynamic consequences. Patients with pre-existing renal insufficiency may be at risk for acute kidney injury, which may be associated with an increased risk of the need for dialysis and mortality in the long term. Many questions as to the physiological pathways, optimal definition, and incidence of contrast-induced acute kidney injury remain open. These uncertainties are reflected in the changing landscape of this field in terms of nomenclature, research, and clinical practice. Methods Clinical practice guidelines for the prevention of post-contrast acute kidney injury all recommend giving prophylaxis in the form of intravenous hydration to high-risk patients. Solid evidence for this strategy is lacking. This article gives an overview of the changing landscape of post-contrast acute kidney injury and prophylactic intravenous hydration, with the aim of supporting informed decision-making in clinical practice. Results Recent data have caused a shift in guideline recommendations: 90 % of patients formerly considered high-risk for contrast-induced acute kidney injury no longer qualify for prophylaxis. The remaining high-risk patients, with severe chronic kidney disease, represent a vulnerable population for whom intravenous hydration may provide some benefits but also carries risk. Conclusion Intravenous hydration may benefit ‘new’ high-risk patients. However, it also confers risk. A dual approach to screening patients will help avoid this risk in clinical practice. Key Points: Intravenous hydration is the cornerstone for preventing contrast-induced acute kidney injury Solid evidence is lacking; recent data caused a shift in guideline recommendations Intravenous hydration may benefit ‘new’ high-risk patients with severe chronic kidney disease; however, it also confers risk A dual approach to screening patients will help avoid this risk in clinical practice Citation Format Nijssen E, Rennenberg R, Nelemans P et al. Post-Contrast Acute Kidney Injury and Intravenous Prophylactic Hydration: An Update. Fortschr Röntgenstr 2021; 193: 151 – 159
Combining randomness and fuzziness

Fuzzy random variable (frv) is one of the most successful mathematical tool for taking an intellectual step towards situations where randomness and fuzziness co-occur. This hybrid concept is discussed in this paper along with an outline of its key features. We also list some applications of fuzzy random variables in solving concrete problems and we provide a numerical example showing how randomness and fuzziness can be combined in an optimization setting. The paper ends with some concluding remarks emphasizing perspectives on potential research directions. Keywords : random variable, fuzzy number, fuzzy random variable, optimization African Journal of Science and Technology Vol. 5(2) 2004: 51-59
Sufficient sampling for kriging prediction of cortical potential in rat, monkey, and human µECoG

Objective. Large channel count surface-based electrophysiology arrays (e.g. µECoG) are high-throughput neural interfaces with good chronic stability. Electrode spacing remains ad hoc due to redundancy and nonstationarity of field dynamics. Here, we establish a criterion for electrode spacing based on the expected accuracy of predicting unsampled field potential from sampled sites. Approach. We applied spatial covariance modeling and field prediction techniques based on geospatial kriging to quantify sufficient sampling for thousands of 500 ms µECoG snapshots in human, monkey, and rat. We calculated a probably approximately correct (PAC) spacing based on kriging that would be required to predict µECoG fields at ≤ 10% error for most cases (95% of observations). Main results. Kriging theory accurately explained the competing effects of electrode density and noise on predicting field potential. Across five frequency bands from 4–7 to 75–300 Hz, PAC spacing was sub-millimeter for auditory cortex in anesthetized and awake rats, and posterior superior temporal gyrus in anesthetized human. At 75–300 Hz, sub-millimeter PAC spacing was required in all species and cortical areas. Significance. PAC spacing accounted for the effect of signal-to-noise on prediction quality and was sensitive to the full distribution of non-stationary covariance states. Our results show that µECoG arrays should sample at sub-millimeter resolution for applications in diverse cortical areas and for noise resilience.
Cerebellar Transcranial Direct Current Stimulation for Motor Learning in People with Chronic Stroke: A Pilot Randomized Controlled Trial

Cerebellar transcranial direct current stimulation (ctDCS) is a non-invasive brain stimulation technique that alters neural plasticity through weak, continuous, direct currents delivered to the cerebellum. This study aimed to evaluate the feasibility of conducting a randomized controlled trial (RCT) delivering three consecutive days of ctDCS during split-belt treadmill training (SBTT) in people with chronic stroke. Using a double-blinded, parallel-group RCT design, eligible participants were randomly allocated to receive either active anodal ctDCS or sham ctDCS combined with SBTT on three consecutive days. Outcomes were assessed at one-week follow-up, using step length symmetry as a measure of motor learning and comfortable over-ground walking speed as a measure of walking capacity. The feasibility of the RCT protocol was evaluated based on recruitment, retention, protocol deviations and data completeness. The feasibility of the intervention was assessed based on safety, adherence and intervention fidelity. Of the 26 potential participants identified over four months, only four were enrolled in the study (active anodal ctDCS n = 1, sham ctDCS n = 3). Both the inclusion criteria and the fidelity of the SBTT relied upon the accurate estimation of step length asymmetry. The method used to determine the side of the step length asymmetry was unreliable and led to deviations in the protocol. The ctDCS intervention was well adhered to, safe, and delivered as per the planned protocol. Motor learning outcomes for individual participants revealed that treadmill step length symmetry remained unchanged for three participants but improved for one participant (sham ctDCS). Comfortable over-ground walking speed improved for two participants (sham ctDCS). The feasibility of the planned protocol and intervention was limited by intra-individual variability in the magnitude and side of the step length asymmetry. This limited the sample and compromised the fidelity of the SBTT intervention. To feasibly conduct a full RCT investigating the effect of ctDCS on locomotor adaptation, a reliable method of identifying and defining step length asymmetry in people with stroke is required. Future ctDCS research should either optimize the methods for SBTT delivery or utilize an alternative motor adaptation task.
Nucleus Accumbens-Associated Protein 1 Binds DNA Directly through the BEN Domain in a Sequence-Specific Manner

Nucleus accumbens-associated protein 1 (NAC1) is a nuclear protein that harbors an amino-terminal BTB domain and a carboxyl-terminal BEN domain. NAC1 appears to play significant and diverse functions in cancer and stem cell biology. Here we demonstrated that the BEN domain of NAC1 is a sequence-specific DNA-binding domain. We selected the palindromic 6 bp motif ACATGT as a target sequence by using a PCR-assisted random oligonucleotide selection approach. The interaction between NAC1 and target DNA was characterized by gel shift assays, pull-down assays, isothermal titration calorimetry (ITC), chromatin-immunoprecipitation assays, and NMR chemical shifts perturbation (CSP). The solution NMR structure revealed that the BEN domain of human NAC-1 is composed of five conserved α helices and two short β sheets, with an additional hitherto unknown N-terminal α helix. In particular, ITC clarified that there are two sequential events in the titration of the BEN domain of NAC1 into the target DNA. The ITC results were further supported by CSP data and structure analyses. Furthermore, live cell photobleaching analyses revealed that the BEN domain of NAC1 alone was unable to interact with chromatin/other proteins in cells.
A Local–Global Dual-Stream Network for Building Extraction From Very-High-Resolution Remote Sensing Images

Buildings constitute one of the most important landscapes in remote sensing (RS) images and have been broadly analyzed in a wide range of applications from urban planning to other socioeconomic studies. As very-high-resolution (VHR) RS imagery becomes more accessible, the current building extraction methods are confronted with the challenges of the diverse appearances, various scales, and complicated structures of buildings in complex scenes. With the development of context-aware deep learning methods, it has been proven by numerous works that capturing contextual information can offer spatial relation cues for robust recognition and detection of the objects. In this article, we propose a novel local–global dual-stream network (DS-Net) that adaptively captures local and long-range information for the accurate mapping of building rooftops in VHR RS images. The local branch and the global branch of DS-Net work in a complementary manner to each other with different fields of view on the input image. Through a well-defined dual-stream architecture, DS-Net learns hierarchical representations for both the local and global branches, and a deep feature sharing strategy is further developed to enforce more collaborative integration of the two branches. Extensive experiments were carried out to verify the effectiveness of our model on three widely used VHR RS data sets: the Massachusetts buildings data set, the Inria Aerial Image Labeling data set, and the DeepGlobe Building Detection Challenge data set. Empirically, the proposed DS-Net achieves competitive or superior performance compared with the current state-of-the-art methods in terms of quantitative measures and visual evaluations.
Doxycycline Interferes With Tau Aggregation and Reduces Its Neuronal Toxicity

Tauopathies are neurodegenerative disorders with increasing incidence and still without cure. The extensive time required for development and approval of novel therapeutics highlights the need for testing and repurposing known safe molecules. Since doxycycline impacts α-synuclein aggregation and toxicity, herein we tested its effect on tau. We found that doxycycline reduces amyloid aggregation of the 2N4R and K18 isoforms of tau protein in a dose-dependent manner. Furthermore, in a cell free system doxycycline also prevents tau seeding and in cell culture reduces toxicity of tau aggregates. Overall, our results expand the spectrum of action of doxycycline against aggregation-prone proteins, opening novel perspectives for its repurposing as a disease-modifying drug for tauopathies.
IRRISENS: An IoT Platform Based on Microservices Applied in Commercial-Scale Crops Working in a Multi-Cloud Environment

Research has shown the multitude of applications that Internet of Things (IoT), cloud computing, and forecast technologies present in every sector. In agriculture, one application is the monitoring of factors that influence crop development to assist in making crop management decisions. Research on the application of such technologies in agriculture has been mainly conducted at small experimental sites or under controlled conditions. This research has provided relevant insights and guidelines for the use of different types of sensors, application of a multitude of algorithms to forecast relevant parameters as well as architectural approaches of IoT platforms. However, research on the implementation of IoT platforms at the commercial scale is needed to identify platform requirements to properly function under such conditions. This article evaluates an IoT platform (IRRISENS) based on fully replicable microservices used to sense soil, crop, and atmosphere parameters, interact with third-party cloud services for scheduling irrigation and, potentially, control irrigation automatically. The proposed IoT platform was evaluated during one growing season at four commercial-scale farms on two broadacre irrigated crops with very different water management requirements (rice and cotton). Five main requirements for IoT platforms to be used in agriculture at commercial scale were identified from implementing IRRISENS as an irrigation support tool for rice and cotton production: scalability, flexibility, heterogeneity, robustness to failure, and security. The platform addressed all these requirements. The results showed that the microservice-based approach used is robust against both intermittent and critical failures in the field that could occur in any of the monitored sites. Further, processing or storage overload caused by datalogger malfunctioning or other reasons at one farm did not affect the platform’s performance. The platform was able to deal with different types of data heterogeneity. Since there are no shared microservices among farms, the IoT platform proposed here also provides data isolation, maintaining data confidentiality for each user, which is relevant in a commercial farm scenario.
Molecules of map plasticity in the somatosensory cortex

Sensory maps are representations of the sensory epithelia in the brain. Despite the intuitive explanatory power behind sensory maps as being neuronal precursors to sensory perception, and sensory cortical plasticity as a neural correlate of perceptual learning, molecular mechanisms that regulate map plasticity are not well understood. Here we perform a meta-analysis of transcriptional and translational changes during altered whisker use to nominate the major molecular correlates of experience-dependent map plasticity in the barrel cortex. We argue that brain plasticity is a systems level response, involving all cell classes, from neuron and glia to non-neuronal cells including endothelia. Using molecular pathway analysis, we further propose a gene regulatory network that could couple activity dependent changes in neurons to adaptive changes in neurovasculature, and finally we show that transcriptional regulations observed in major brain disorders target genes that are modulated by altered sensory experience. Thus understanding the molecular mechanisms of experience-dependent plasticity of sensory maps might help to unravel the cellular events that shape brain plasticity in health and disease. representations of the ipsilateral eye in the monocular region, a select tonal frequency and a whisker under normal conditions. ( D ) Upon sustained manipulation of sensory input (i.e. monocular deprivation (Gordon and Stryker, 1996), exposure to select tonal frequency (de Villers-Sidani et al., 2007) or whisker deprivation (Fox, 2002)) the sensory maps are reorganized. Independent from the sensory modality, increased use of a sensory organ, or exposure to a specific stimulus, results in expansion of cortical representations in an experience-dependent manner. plasticity.
The kinetics of pre-mRNA splicing in the Drosophila genome: influence of gene architecture

Production of most eukaryotic mRNAs requires splicing of introns from pre-mRNA. The splicing reaction requires definition of splice sites, which are initially recognized in either intron-spanning (“intron definition”) or exon-spanning (“exon definition”) pairs. To understand how exon and intron length and splice site recognition mode impact splicing, we measured splicing rates genome-wide in Drosophila, using metabolic labeling/RNA sequencing and new mathematical models to estimate rates. We found that the modal intron length range of 60-70 nt represents a local maximum of splicing rates, but that much longer exon-defined introns are spliced even faster and more accurately. Surprisingly, we observed low variation in splicing rates across introns in the same gene, suggesting the presence of gene-level influences, and we identified multiple gene level variables associated with splicing rate. Together our data suggest that developmental and stress response genes may have preferentially evolved exon definition in order to enhance rates of splicing.
Interactions and collider bias in case-only gene-environment data

Background Case-only design for gene-environment interaction (CODGEI) relies on the rare disease assumption. A negative association due to collider bias appears between gene and environment when this assumption is not respected. Genetic risk estimation can quantify part of the predisposition of an individual to a disease. Methods We introduce Disease As Collider (DAC), a new case-only methodology to discover environmental factors using genetic risk estimation: a negative correlation between genetic risk and environment in cases provides a signature of a genuine environmental risk marker. Simulation of disease occurrence in a source population allows to estimate the statistical power of DAC and the influence of collider bias in CODGEI. We illustrate DAC in 831 type 1 diabetes (T1D) patients. Results: The power of DAC increases with sample size, prevalence and accuracy of genetic risk estimation. For a prevalence of 1% and a realistic genetic risk estimation, power of 80% is reached for a sample size under 3000. Collider bias offers an alternative interpretation to the results of CODGEI in a published study on breast cancer. Conclusion DAC could provide a new line of evidence for discovering which environmental factors play a role in complex diseases or confirming results obtained in case-control studies. We discuss the circumstances needed for DAC to participate in the dissection of environmental determinants of disease. We provide guidance on the use of CODGEI regarding the rare disease assumption. Key messages A complex disease is a collider between genetic determinants and environmental factors; it is a consequence of both. Collider bias can affect the results of the case-only design for gene-environment interactions when the disease is common. Using genetic risk estimation, collider bias can be used to discover or confirm the association between a disease and an environmental factor in a case-only setting. Statistical power of this approach is small when the disease is rare. Power increases with sample size, prevalence and genetic risk prediction accuracy.
Mechanistic causes of constrained phenotypic variation revealed by synthetic gene regulatory networks

Phenotypic variation is the raw material of adaptive Darwinian evolution. The phenotypic variation brought forth by organismal development is biased towards specific phenotypes, but the molecular mechanisms behind such biases are still poorly understood. Here we study these biases in two synthetic gene regulatory networks expressed in E. coli that produce a gene expression stripe, which is a pivotal pattern in embryonic development. The two gene regulatory networks display the same phenotype, but create it through different regulatory mechanisms. Because these regulatory mechanisms are well understood, we can use a combination of experimental measurements, mathematical modelling and DNA sequencing to understand why mutations bring forth only some but not other novel gene expression phenotypes. Our observations emphasize the interactions between genes in a regulatory network as a mechanistic cause of biased phenotype production.
The functional impact of alternative splicing in cancer

Alternative splicing changes are frequently observed in cancer and are starting to be recognized as important signatures for tumor progression and therapy. However, their functional impact and relevance to tumorigenesis remains mostly unknown. We carried out a systematic analysis to characterize the potential functional consequences of alternative splicing changes in thousands of tumor samples. This analysis revealed that a subset of alternative splicing changes affect protein domain families that are frequently mutated in tumors and potentially disrupt protein protein interactions in cancer-related pathways. Moreover, there was a negative correlation between the number of these alternative splicing changes in a sample and the number of somatic mutations in drivers. We propose that a subset of the alternative splicing changes observed in tumors may represent independent oncogenic processes that could be relevant to explain the functional transformations in cancer and some of them could potentially be considered alternative splicing drivers (AS-drivers).