Notes

Case statement: The particular body structure of the preventable tragedy -Near dying within a hot spa.
Hypoxia induced by flooding or submergence is a serious abiotic stress affecting crop productivity worldwide. During evolution, plants have developed different metabolism mechanisms to cope with the energy crisis caused by hypoxia stress. Among those, the metabolism of γ-aminobutyric acid (GABA), a non-protein amino acid, is recognized as a crucial component for low-oxygen stress responses because of its link both in carbon and nitrogen metabolism. However, it is largely unknown how to control GABA homeostasis. In this study, we identified a novel glycosyltransferase encoding gene, UGT79B7, which was significantly downregulated by low-oxygen treatment in Arabidopsis. ugt79b7 knockout mutants showed increased resistance to hypoxia, while the overexpression lines showed increased sensitivity. We demonstrated that glycosyltransferase UGT79B7 could catalyze GABA to form GABA glucose conjugate (GABA-Glc) in vitro. The in vivo biochemical function of UGT79B7 in controlling GABA glycosylation was also verified. Moreover, we also demonstrated that UGT79B7 could negatively modulate the accumulation of GABA under hypoxia stress. Our data suggest that the glycosylation of GABA plays an important role in GABA homeostasis and reveal a new way for the regulation of plant hypoxia response through a dynamic balance of GABA and its glycosylation products, GABA-Glc.
It is suggested that dental agenesis affects maxillary protrusion and dental arch relationship in children with unilateral cleft lip and palate (UCLP). In addition, an association between the need for orthognathic surgery and dental agenesis is reported.

The aim was to study the impact of maxillary dental agenesis on craniofacial growth and dental arch relationship in 8-year-old children with UCLP.

The sample consisted of individuals with UCLP from Scandcleft randomized trials. The participants had available data from diagnosis of maxillary dental agenesis as well as cephalometric measurements (n = 399) and GOSLON assessment (n = 408) at 8 years of age.

A statistically significant difference was found for ANB between individuals with agenesis of two or more maxillary teeth (mean 1.52°) in comparison with those with no or only one missing maxillary tooth (mean 3.30° and 2.70°, respectively). Mean NSL/NL was lower among individuals with agenesis of two or more maxillary teeth (mean 9.90°), in comparison with individuals with no or one missing maxillary tooth (mean 11.46° and 11.45°, respectively). The number of individuals with GOSLON score 4-5 was 47.2% in the group with two or more missing maxillary teeth and 26.1% respectively 26.3% in the groups with no or one missing maxillary tooth. No statistically significant difference was found in the comparison between individuals with no agenesis or with agenesis solely of the cleft-side lateral.

Maxillary dental agenesis impacts on craniofacial growth as well as dental arch relationship and should be considered in orthodontic treatment planning.
Maxillary dental agenesis impacts on craniofacial growth as well as dental arch relationship and should be considered in orthodontic treatment planning.
Protein-protein interactions drive wide-ranging molecular processes, and characterizing at the atomic level how proteins interact (beyond just the fact that they interact) can provide key insights into understanding and controlling this machinery. Unfortunately, experimental determination of three-dimensional protein complex structures remains difficult and does not scale to the increasingly large sets of proteins whose interactions are of interest. Computational methods are thus required to meet the demands of large-scale, high-throughput prediction of how proteins interact, but unfortunately both physical modeling and machine learning methods suffer from poor precision and/or recall.

In order to improve performance in predicting protein interaction interfaces, we leverage the best properties of both data- and physics-driven methods to develop a unified Geometric Deep Neural Network, "PInet" (Protein Interface Network). PInet consumes pairs of point clouds encoding the structures of two partner proteins, in order to predict their structural regions mediating interaction. buy BL-918 To make such predictions, PInet learns and utilizes models capturing both geometrical and physicochemical molecular surface complementarity. In application to a set of benchmarks, PInet simultaneously predicts the interface regions on both interacting proteins, achieving performance equivalent to or even much better than the state-of-the-art predictor for each dataset. Furthermore, since PInet is based on joint segmentation of a representation of a protein surfaces, its predictions are meaningful in terms of the underlying physical complementarity driving molecular recognition.

PInet scripts and models are available at https//github.com/FTD007/PInet.

Supplementary data are available at Bioinformatics online.
Supplementary data are available at Bioinformatics online.
Here, we propose Fourier ring correlation-based quality estimation (FRC-QE) as a new metric for automated image quality estimation in 3 D fluorescence microscopy acquisitions of cleared organoids that yields comparable measurements across experimental replicates, clearing protocols and works for different microscopy modalities.

FRC-QE is written in ImgLib2/Java and provided as an easy-to-use and macro-scriptable plugin in Fiji. Code, documentation, sample images and further information can be found under https//github.com/PreibischLab/FRC-QE.

Supplementary data are available at Bioinformatics online.
Supplementary data are available at Bioinformatics online.Damage to the myelin sheath and the neuroaxonal unit is a cardinal feature of multiple sclerosis; however, a detailed characterization of the interaction between myelin and axon damage in vivo remains challenging. We applied myelin water and multi-shell diffusion imaging to quantify the relative damage to myelin and axons (i) among different lesion types; (ii) in normal-appearing tissue; and (iii) across multiple sclerosis clinical subtypes and healthy controls. We also assessed the relation of focal myelin/axon damage with disability and serum neurofilament light chain as a global biological measure of neuroaxonal damage. Ninety-one multiple sclerosis patients (62 relapsing-remitting, 29 progressive) and 72 healthy controls were enrolled in the study. Differences in myelin water fraction and neurite density index were substantial when lesions were compared to healthy controls and normal-appearing MS tissue both white matter and cortical lesions exhibited a decreased myelin water fraction and neurite density index compared with healthy (P less then 0.
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