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The predicted fluxes are tested in vitro resulting in 32- and 42-fold increased product of isobutanol and shikimate, respectively. Moreover, we authenticate the platform by mimicking a bacterial population in the presence of glyphosate, a metabolic pathway inhibitor. Here, we observe a fraction of subsisting persisters despite inhibition, thus affirming the signature of a heterogeneous populace. The platform has multiple uses based on the disposition of the user. In consumptive hypothyroidism associated with infantile hepatic hemangiomas (IHH), elevated reverse triiodothyronine (rT3) is known due to elevated D3. This report shows that rT3 is a new indicator of IHH progression and that three divided doses of LT3 per day were more effective than a single dose. A 23day-old boy was diagnosed with diffuse IHH and severe hypothyroidism with high rT3. Propranolol and LT4 were administered. Hemangiomas gradually diminished and rT3 decreased, but the thyroid-stimulating hormone remained elevated, and free triiodothyronine (fT3) did not normalize after 2weeks of treatment. Liothyronine (LT3) was started as a single dose and then divided into three doses after 1week, which stabilized thyroid function. rT3 levels were less variable and decreased in conjunction with tumor shrinkage; thus, rT3 is an indicator of therapeutic outcomes for IHH. LT3 administered in divided doses aided in managing IHH-associated hypothyroidism.rT3 levels were less variable and decreased in conjunction with tumor shrinkage; thus, rT3 is an indicator of therapeutic outcomes for IHH. LT3 administered in divided doses aided in managing IHH-associated hypothyroidism.A photoreceptor on the retina acts as an optical waveguide to transfer an individual photonic signal to the cell inside, which is determined by the refractive index of internal materials. Under the photoactivation of photoreceptors making conformational and chemical variation in a visual cell, the optical signal modulation is demonstrated using an artificial photoreceptor-based waveguide with a controlling beam refraction. Two types of nanodiscs are made of human photoreceptor proteins, short-wavelength-sensitive opsin and rhodopsin, with spectral sensitivity. The refractive index and nonlinear features of those two photosensitive nanodiscs are investigated as fundamental properties. The photonanodiscs are photoactivated in such a way that allow refractive index tuning over 0.18 according to the biological function of the respective proteins with color-dependent response. Microbiome datasets are often constrained by sequencing limitations. GenBank is the largest collection of publicly available DNA sequences, which is maintained by the National Center of Biotechnology Information (NCBI). The metadata of GenBank records are a largely understudied resource and may be uniquely leveraged to access the sum of prior studies focused on microbiome composition. Here, we developed a computational pipeline to analyze GenBank metadata, containing data on hosts, microorganisms and their place of origin. This work provides the first opportunity to leverage the totality of GenBank to shed light on compositional data practices that shape how microbiome datasets are formed as well as examine host-microbiome relationships. The collected dataset contains multiple kingdoms of microorganisms, consisting of bacteria, viruses, archaea, protozoa, fungi, and invertebrate parasites, and hosts of multiple taxonomical classes, including mammals, birds and fish. A human data subset of this dataset provides insights to gaps in current microbiome data collection, which is biased towards clinically relevant pathogens. Clustering and phylogenic analysis reveals the potential to use these data to model host taxonomy and evolution, revealing groupings formed by host diet, environment and coevolution. GenBank Host-Microbiome Pipeline is available at https//github.com/bcbi/genbank_holobiome. The GenBank loader is available at https//github.com/bcbi/genbank_loader. Supplementary data are available at Bioinformatics online.Supplementary data are available at Bioinformatics online.One emerging paradigm of cellular organization of RNA and RNA-binding proteins is the formation of membraneless organelles. Examples of membraneless organelles include several types of ribonucleoprotein granules that form via phase separation. A variety of intracellular pH changes and posttranslational modifications, as well as extracellular stresses, can stimulate the condensation of proteins into granules. For example, the assembly of stress granules induced by oxidative stress, osmotic stress, and heat stress has been well characterized in a variety of somatic cell types. In the germ line, similar stress-induced condensation of proteins occurs; however, less is known about the role of phase separation during gamete production. Researchers who study phase transitions often make use of fluorescent reporters to study the dynamics of RNA-binding proteins during live cell imaging. In this report, we demonstrate that common conditions of live-imaging Caenorhabditis elegans can cause an inadvertent stress and trigger phase transitions of RNA-binding proteins. We show that this imaging-associated stress stimulates decondensation of multiple germ granule proteins and condensation of several P-body proteins. Proteins within larger ribonucleoprotein granules in meiotically arrested oocytes do not appear to be as sensitive to the stress as proteins in diakinesis oocytes of young hermaphrodites, with the exception of the germ granule protein PGL-1. Our results have important methodological implications for all researchers using live-cell imaging techniques. The data also suggest that the RNA-binding proteins within large ribonucleoprotein granules of arrested oocytes may have distinct phases, which we characterize in our companion article.The application of highly porous and 3D interconnected microcellular polyelectrolyte polyHIPE (PE-PH) monoliths based on (3-acrylamidopropyl)-trimethylammonium chloride as soilless cultivation substrates for in vitro embryo culture is discussed. The embryo axes isolated from chickpea seeds are inoculated onto the surface of the monoliths and allowed to germinate. Germination study show that the newly disclosed PE-PH substrate performs much better than the conventionally used agar as the germination percentage, shoot and root length, fresh and dry weight as well as the number of leaves are enhanced. The PE-PHs exhibit a higher absorption capacity of the plant growth medium, that is, 36 g·g-1 compared to agar, that is, 20 g·g-1, and also survive autoclaving conditions without failing. The key advantage over standard agar substrates is that they can be reused several times and also without prior sterilization. These results suggest that PE-PHs with exceptional absorption/retention properties and robustness have great potential as soilless substrates for in vitro plant cultivation. Understanding life cannot be accomplished without making full use of biological data, which are scattered across databases of diverse categories in life sciences. To connect such data seamlessly, identifier (ID) conversion plays a key role. However, existing ID conversion services have disadvantages, such as covering only a limited range of biological categories of databases, not keeping up with the updates of the original databases and outputs being hard to interpret in the context of biological relations, especially when converting IDs in multiple steps. TogoID is an ID conversion service implementing unique features with an intuitive web interface and an application programming interface (API) for programmatic access. TogoID currently supports 65 datasets covering various biological categories. TogoID users can perform exploratory multistep conversions to find a path among IDs. To guide the interpretation of biological meanings in the conversions, we crafted an ontology that defines the semantics of the dataset relations. The TogoID service is freely available on the TogoID website (https//togoid.dbcls.jp/) and the API is also provided to allow programmatic access. To encourage developers to add new dataset pairs, the system stores the configurations of pairs at the GitHub repository (https//github.com/togoid/togoid-config) and accepts the request of additional pairs. Supplementary data are available at Bioinformatics online.Supplementary data are available at Bioinformatics online.How sexual selection affects the genome ultimately relies on the strength and type of selection, and the genetic architecture of the involved traits. While associating genotype with phenotype often utilizes standard trait morphology, trait representations in morphospace using geometric morphometric approaches receive less focus in this regard. Here, we identify genetic associations to a sexual ornament, the comb, in the chicken system (Gallus gallus). Our approach combined genome-wide genotype and gene expression data (>30k genes) with different aspects of comb morphology in an advanced intercross line (F8) generated by crossing a wild-type Red Junglefowl with a domestic breed of chicken (White Leghorn). In total, 10 quantitative trait loci were found associated to various aspects of comb shape and size, while 1,184 expression QTL were found associated to gene expression patterns, among which 98 had overlapping confidence intervals with those of quantitative trait loci. Our results highlight both known genomic regions confirming previous records of a large effect quantitative trait loci associated to comb size, and novel quantitative trait loci associated to comb shape. https://www.selleckchem.com/products/cct128930.html Genes were considered candidates affecting comb morphology if they were found within both confidence intervals of the underlying quantitative trait loci and eQTL. Overlaps between quantitative trait loci and genome-wide selective sweeps identified in a previous study revealed that only loci associated to comb size may be experiencing on-going selection under domestication. Identifying drug-target interactions is a crucial step for drug discovery and design. Traditional biochemical experiments are credible to accurately validate drug-target interactions. However, they are also extremely laborious, time-consuming and expensive. With the collection of more validated biomedical data and the advancement of computing technology, the computational methods based on chemogenomics gradually attract more attention, which guide the experimental verifications. In this study, we propose an end-to-end deep learning-based method named IIFDTI to predict drug-target interactions (DTIs) based on independent features of drug-target pairs and interactive features of their substructures. First, the interactive features of substructures between drugs and targets are extracted by the bidirectional encoder-decoder architecture. The independent features of drugs and targets are extracted by the graph neural networks and convolutional neural networks, respectively. Then, all extracted features are fused and inputted into fully connected dense layers in downstream tasks for predicting DTIs. IIFDTI takes into account the independent features of drugs/targets and simulates the interactive features of the substructures from the biological perspective. Multiple experiments show that IIFDTI outperforms the state-of-the-art methods in terms of the area under the receiver operating characteristics curve (AUC), the area under the precision-recall curve (AUPR), precision, and recall on benchmark datasets. In addition, the mapped visualizations of attention weights indicate that IIFDTI has learned the biological knowledge insights, and two case studies illustrate the capabilities of IIFDTI in practical applications. The data and codes underlying this article are available in Github at https//github.com/czjczj/IIFDTI. Supplementary data are available at Bioinformatics online.Supplementary data are available at Bioinformatics online.
