Miracle-dz/UniFAR-FTUs huggingface dataset:
Grain Inoculated with Different Growth Stages of the Fungus, Aspergillus flavus, Affect the Close-Range Foraging Behavior by a Primary Stored Product Pest, Sitophilus oryzae (Coleoptera: Curculionidae)

Abstract Although some research has investigated the interactions among stored product insects and microbes, little research has examined how specific fungal life stages affect volatile emissions in grain and linked it to the behavior of Sitophilus oryzae, the cosmopolitan rice weevil. Thus, our goals were to 1) isolate, culture, and identify two fungal life stages of Aspergillus flavus, 2) characterize the volatile emissions from grain inoculated by each fungal morphotype, and 3) understand how microbially-produced volatile organic compounds (MVOCs) from each fungal morphotype affect foraging, attraction, and preference by S. oryzae. We hypothesized that the headspace blends would be unique among our treatments and that this will lead to preferential mobility by S. oryzae among treatments. Using headspace collection coupled with GC-MS, we found the sexual life stage of A. flavus had the most unique emissions of MVOCs compared to the other semiochemical treatments. This translated to a higher interaction with kernels containing grain with the A. flavus sexual life stage, as well as a higher cumulative time spent in those zones by S. oryzae in a video-tracking assay in comparison to the asexual life stage. While fungal cues were important for foraging at close-range, the release-recapture assay indicated that grain volatiles were more important for attraction at longer distances. There was no significant preference between grain and MVOCs in a four-way olfactometer. Overall, this study enhances our understanding of how fungal cues affect the close and longer range foraging ecology of a primarily stored product insect. Graphical Abstract
Anatomo‐comparative study of formaldehyde, alcohol, and saturated salt solution as fixatives in Wistar rat brains

Although formaldehyde is the most widely used and largely available fixative for preserving cadavers through decomposition prevention, it promotes darkening and weight gain, in addition to being considered carcinogenic. Ethyl alcohol has been proven a potential substitute to formaldehyde due to its effectiveness in tissue penetration, thus preventing proliferation of microorganisms; however, it can only be used alone for fixation of small parts. In view of such fixatives limitations, saturated salt solution has been widely employed based on its antimicrobial effect and ability to maintain tissue similar to the original one, in addition to exerting no hazardous effects as there is no evaporation of harmful substances. This research aimed to observe anatomical brain behaviour submitted to formaldehyde, alcohol, and saturated salt solution as fixatives. Fixatives were tested in 15 adult Wistar rats’ brain, submerged in 10 ml of intended solution after removal for 4 weeks. Weight of the brains fixed in saturated salt did not change over the weeks. However, the weight of formaldehyde‐fixed brains increased and the weight in alcohol‐fixed brains decreased; in addition, modifications in all solutions measures were also observed. Alcohol provides a peculiar dehydrating effect as formaldehyde clearly increases the length of the pieces. Thus, since the saturated salt solution showed no important adjustment over the experimental time, it proved an efficient alternative for replacing formaldehyde and alcohol as fixative solutions of anatomical study of the brain.
Test d'ajustement d'une loi bidimensionnelle : Application à des données climatologiques

Si F est la fonction de repartition d'une loi multivariee, de fonctions de repartition marginales F i , i = 1,…, n, il existe une application H, appelee copule ou fonction de dependance, definie sur [0,1] n a valeurs dans [0,1], telle que F(x 1 ,…, x n ) = H(F 1 (x 1 ) F n (x n )). Cette application definit une distribution multivariee de marges uniformes sur [0, 1]. Lorsque les marges sont continues, la fonction F peut etre representee de maniere unique par une copule H, Plusieurs familles de copules ont ete presentees ces dernieres annees. Dans cet article, nous presentons une procedure d'ajustement d'une loi bidimensionnelle par une famille particuliere de copules, dites archimediennes, basee sur un resultat du a Genest et al [9]. Nous verrons que l'ajustement d'une fonction de repartition bidimensionnelle se resume a celui d'une fonction de repartition unidimensionnelle d'une pseudo-variable aleatoire U = F(X 1 , X 2 ) en comparant les versions parametrique et non-parametrique de sa distribution. Pour illustrer cette methode nous presentons une application a des donnees climatologiques.
Resources to Facilitate Use of the Altered Schaedler Flora (ASF) Mouse Model to Study Microbiome Function

Improved experimental systems are needed to advance our understanding of how the gut microbiome influences processes of the mammalian host as well as microbial community structure and function. An approach that is receiving considerable attention is the use of animal models that harbor a stable microbiota of known composition, i.e., defined microbiota, which enables control over an otherwise highly complex and variable feature of mammalian biology. ABSTRACT Animals colonized with a defined microbiota represent useful experimental systems to investigate microbiome function. The altered Schaedler flora (ASF) represents a consortium of eight murine bacterial species that have been used for more than 4 decades where the study of mice with a reduced microbiota is desired. In contrast to germ-free mice, or mice colonized with only one or two species, ASF mice show the normal gut structure and immune system development. To further expand the utility of the ASF, we have developed technical and bioinformatic resources to enable a systems-based analysis of microbiome function using this model. Here, we highlighted four distinct applications of these resources that enable and improve (i) measurements of the abundance of each ASF member by quantitative PCR; (ii) exploration and comparative analysis of ASF genomes and the metabolic pathways they encode that comprise the entire gut microbiome; (iii) global transcriptional profiling to identify genes whose expression responds to environmental changes within the gut; and (iv) discovery of genetic changes resulting from the evolutionary adaptation of the microbiota. These resources were designed to be accessible to a broad community of researchers that, in combination with conventionally-reared mice (i.e., with complex microbiome), should contribute to our understanding of microbiome structure and function. IMPORTANCE Improved experimental systems are needed to advance our understanding of how the gut microbiome influences processes of the mammalian host as well as microbial community structure and function. An approach that is receiving considerable attention is the use of animal models that harbor a stable microbiota of known composition, i.e., defined microbiota, which enables control over an otherwise highly complex and variable feature of mammalian biology. The altered Schaedler flora (ASF) consortium is a well-established defined microbiota model, where mice are stably colonized with 8 distinct murine bacterial species. To take better advantage of the ASF, we established new experimental and bioinformatics resources for researchers to make better use of this model as an experimental system to study microbiome function.
The impact of COVID-19 Epidemic on Teaching and Learning

Recently articles in Newspapers, University News Bulletins and Scientific Literature report about negative aspects of the wellbeing of students caused by COVID-19 epidemic. Half of the students have mental problems and don’t participate in the teaching learning process anymore. In the Netherlands, Universities are surveyed by questionnaires, researching the mental health problems of students. In this paper we focus on students of Delft University of Technology. It proved from surveys, that many students complain about loneliness, fear, sleep deprivation and lack of study motivation. In this paper we report about experiments at the Faculty of Electrical Engineering, Mathematics and Computer Science, how students can be activated, motivated and socialized via study activities presented at the website of one of the Study Societies and via study-buddy groups. Students were personally invited to take part in discussions via a Forum, to enroll in group activities and to visit special lectures. A special COVID-19 didactics has been developed to stimulate students to make assignments in Calculus and Programing via Massive Open Online Courses developed in the framework EdX, an online learning destination and MOOC provider.
Study on the Influence of Risk Information on Risk Perception and Coping Behavior of College Students in the Context of Epidemic Prevention and Control

Objective: This study aims to explore the influence of risk information on college students'coping behavior during the pandemic and the mediating role of risk perception in between. Methods: 553 college students were surveyed by risk information questionnaire, risk perception questionnaire and coping behavior measurement. Results: (1)In risk information, the cure information and the government prevention and control measures could reduce the level of individual's risk perception, while the disease information and the self-related information could cause college students'high-risk perception; (2) The four kinds of risk information significantly correlated with risk perception and coping behavior, and risk perception and coping behavior were significantly correlated; (3) Risk perception played an mediating role between risk information and coping behavior. Conclusion: Risk information and risk perception during the epidemic significantly affected college students'coping behavior.
Using compositionality to understand parts in whole objects

A fundamental question for any visual system is whether its image representation can be understood in terms of its components. Decomposing any image into components is challenging because there are many possible decompositions with no common dictionary, and enumerating the components leads to a combinatorial explosion. Even in perception, many objects are readily seen as containing parts, but there are many exceptions. These exceptions include objects that are not perceived as containing parts, properties like symmetry that cannot be localized to any single part and special categories like words and faces whose perception is widely believed to be holistic.
On-line approximation of control programs for a class of nonlinear free-floating systems

We consider the problem of nonholonomic motion planning. We present an efficient paradigm for planning and stabilization of motion in a class of multivariable nonlinear (nonholonomic) systems, and apply this control paradigm to a planar free-flying manipulator. The controller architecture designed in the paper is based on the radial basis function (RBF) network approximation of an optimal control program for any desired motion and sampled-data feedback stabilization. The proposed RBF-based control technique overcomes certain problems associated with other control approaches recently proposed for nonholonomic systems. The presented simulation results reveal a promising potential of the proposed control paradigm. This paradigm can be extended to a broader class of nonlinear control problems.
Fusarium oxysporum Effector Clustering version 2 (FoEC2): an updated pipeline to infer host range

The fungus Fusarium oxysporum is infamous for its devastating effects on economically important crops worldwide. F. oxysporum isolates are grouped into formae speciales based on their ability to cause disease on different hosts. Assigning F. oxysporum strains to formae speciales using non-experimental procedures has proven to be challenging due to their genetic heterogeneity and polyphyletic nature. However, genetically diverse isolates of the same forma specialis encode similar repertoires of effectors, proteins that are secreted by the fungus and contribute to the establishment of compatibility with the host. Based on this observation, we previously designed the F. oxysporum Effector Clustering (FoEC) pipeline which is able to classify F. oxysporum strains by forma specialis based on hierarchical clustering of the presence of predicted putative effector sequences, solely using genome assemblies as input. Here we present the updated FoEC2 pipeline which is more user friendly, customizable and, due to multithreading, has improved scalability. It is designed as a Snakemake pipeline and incorporates a new interactive visualization app. We showcase FoEC2 by clustering 537 publicly available F. oxysporum genomes and further analysis of putative effector families as multiple sequence alignments. We confirm classification of isolates into formae speciales and are able to further identify their subtypes. The pipeline is available on github: https://github.com/pvdam3/FoEC2.
Efficient computation of adjoint sensitivities at steady-state in ODE models of biochemical reaction networks

Dynamical models in the form of systems of ordinary differential equations have become a standard tool in systems biology. Many parameters of such models are usually unknown and have to be inferred from experimental data. Gradient-based optimization has proven to be effective for parameter estimation. However, computing gradients becomes increasingly costly for larger models, which are required for capturing the complex interactions of multiple biochemical pathways. Adjoint sensitivity analysis has been pivotal for working with such large models, but methods tailored for steady-state data are currently not available. We propose a new adjoint method for computing gradients, which is applicable if the experimental data include steady-state measurements. The method is based on a reformulation of the backward integration problem to a system of linear algebraic equations. The evaluation of the proposed method using real-world problems shows a speedup of total simulation time by a factor of up to 4.4. Our results demonstrate that the proposed approach can achieve a substantial improvement in computation time, in particular for large-scale models, where computational efficiency is critical. Author summary Large-scale dynamical models are nowadays widely used for the analysis of complex processes and the integration of large-scale data sets. However, computational cost is often a bottleneck. Here, we propose a new gradient computation method that facilitates the parameterization of large-scale models based on steady-state measurements. The method can be combined with existing gradient computation methods for time-course measurements. Accordingly, it is an essential contribution to the environment of computationally efficient approaches for the study of large-scale screening and omics data, but not tailored to biological applications, and, therefore, also useful beyond the field of computational biology.
Loss of EED in the oocyte causes initial fetal growth restriction followed by placental hyperplasia and offspring overgrowth

Germline epigenetic programming, including genomic imprinting, substantially influences offspring development. Polycomb Repressive Complex 2 (PRC2) plays an important role in Histone 3 Lysine 27 trimethylation (H3K27me3)-dependent imprinting, loss of which leads to placental hyperplasia in mammalian offspring generated by somatic cell nuclear transfer (SCNT). In this study, we show that offspring from mouse oocytes lacking the Polycomb protein Embryonic Ectoderm Development (EED) were initially growth restricted, characterised by low blastocyst cell counts and substantial mid-gestational developmental delay. This initial developmental delay was followed by striking late-gestational placental hyperplasia, fetal catch-up growth and extended gestational length that culminated in offspring overgrowth. This involved remodelling of the placenta, including expansion of fetal and maternal tissues and conspicuous expansion of the glycogen enriched cell population in the junctional zone that was associated with a delay in parturition. Despite this remodelling and offspring catchup growth, fetal/placental weight ratio and fetal blood glucose levels were low indicating low placental efficiency. Genome-wide analyses identified extensive transcriptional dysregulation in affected placentas, including a range of imprinted and non-imprinted genes and increased expression of the H3K27me3-imprinted gene Slc38a4, which regulates transport of essential amino acids in the placenta. Our data provide an explanation for apparently opposing observations of growth restriction and overgrowth of offspring derived from Eed-null oocytes and demonstrate that PRC2-dependent programming in the oocyte regulates fetal and placental growth and developmental outcomes.
Counting is almost all you need

The immune memory repertoire encodes the history of present and past infections and immunological attributes of the individual. As such, multiple methods were proposed to use T-cell receptor (TCR) repertoires to detect disease history. We here show that the counting method outperforms all existing algorithms. We then show that the counting can be further improved using a novel attention model to weight the different TCRs. The attention model is based on the projection of TCRs using a Variational AutoEncoder (VAE). Both counting and attention algorithms predict better than any current algorithm whether the host had CMV and its HLA alleles. As an intermediate solution between the complex attention model and the very simple counting model, we propose a new Graph Convolutional Network approach that obtains the accuracy of the attention model and the simplicity of the counting model. The code for the models used in the paper are provided in: https://github.com/louzounlab/CountingIsAlmostAllYouNeed
Melon pan-genome and multi-parental framework for high-resolution trait dissection

Linking between genotype and phenotype is a fundamental goal in biology and requires robust data for both layers. The prominent increase in plant genome sequencing and comparisons of multiple related individuals, exposed the abundance of structural genomic variation and suggest that a single reference genome cannot represent the complete sequence diversity of a crop species, leading to the expansion of the pan-genome concept. For high-resolution forward genetics, this unprecedented access to genomic variation should be paralleled by availability and phenotypic characterization of genetic diversity, and effective integration between these layers. Here, we describe a multi-parental framework for trait dissection in melon, leveraging a novel pan-genome constructed for this crop. Melon (Cucumis melo L.) is an important crop from the Cucurbitaceae family, which display extensive phenotypic variation available for breeding. A diverse core set of 25 founder lines (MelonCore25) was sequenced using a combination of short and long-read technologies and their genomes were assembled de novo. The construction of a melon pan-genome exposed substantial variation in genome size and structure, including detection of ~300,000 structural variants and ~9 million SNPs. A half-diallel derived set of 300 F2 populations representing all possible MelonCore25 parental combinations was constructed as framework for trait dissection through integration with the pan-genome. We demonstrate the potential of this unified framework for genetic analysis of various melon traits, including rind color and mottling pattern, fruit sugar content and resistance to fungal diseases. We anticipate that utilization of this integrated resource will enhance genetic dissection of important traits and accelerate melon breeding. Significance statement Pan-genomes aim to address the abundance of genome structural variation within species for improved genomic analyses. New pan-genome, constructed from de novo genome assemblies of 25 diverse melon (Cucumis melo L.) accessions is integrated with a half-diallel derived set of 300 F2 populations representing all possible parental combinations. The potential of this unified multi-parental trait dissection framework for melon genetics and breeding is presented.
Evolutionary investigations of the biosynthetic diversity in the skin microbiome using lsaBGC

Bacterial secondary metabolites, synthesized by enzymes encoded in biosynthetic gene clusters (BGCs), can underlie microbiome homeostasis and serve as commercialized products, which have historically been mined from a select group of taxa. While evolutionary approaches have proven beneficial for prioritizing BGCs for experimental characterization efforts to uncover new natural products, dedicated bioinformatics tools designed for comparative and evolutionary analysis of BGCs within focal taxa are limited. We thus developed lineage specific analysis of BGCs (lsaBGC; https://github.com/Kalan-Lab/lsaBGC) to aid exploration of microdiversity and evolutionary trends across homologous groupings of BGCs, gene cluster families (GCFs), in any bacterial taxa of interest. lsaBGC enables rapid and direct identification of GCFs in genomes, calculates evolutionary statistics and conservation for BGC genes, and builds a framework to allow for base resolution mining of novel variants through metagenomic exploration. Through application of the suite to four genera commonly found in skin microbiomes, we uncover new insights into the evolution and diversity of their BGCs. We show that the BGC of the virulence-associated carotenoid staphyloxanthin in Staphylococcus aureus is ubiquitous across the genus Staphylococcus . While one GCF encoding the biosynthesis of staphyloxanthin showcases evidence for plasmid-mediated horizontal gene transfer (HGT) between species, another GCF appears to be transmitted vertically amongst a sub-clade of skin-associated Staphylococcus . Further, the latter GCF, which is well conserved in S. aureus , has been lost in most Staphylococcus epidermidis , which is the most common Staphylococcus species on human skin and is also regarded as a commensal. We also identify thousands of novel single-nucleotide variants (SNVs) within BGCs from the Corynebacterium tuberculostearicum sp. complex, a narrow, multi-species clade that features the most prevalent Corynebacterium in healthy skin microbiomes. Although novel SNVs were approximately 10 times as likely to correspond to synonymous changes when located in the top five percentile of conserved sites, lsaBGC identified SNVs that defied this trend and are predicted to underlie amino acid changes within functionally key enzymatic domains. Ultimately, beyond supporting evolutionary investigations of BGCs, lsaBGC also provides important functionalities to aid efforts for the discovery or directed modification of natural products.