Htm1 protein generates the N-glycan signal for glycoprotein degradation in the endoplasmic reticulum

To maintain protein homeostasis in secretory compartments, eukaryotic cells harbor a quality control system that monitors protein folding and protein complex assembly in the endoplasmic reticulum (ER). Proteins that do not fold properly or integrate into cognate complexes are degraded by ER-associated degradation (ERAD) involving retrotranslocation to the cytoplasm and proteasomal peptide hydrolysis. N-linked glycans are essential in glycoprotein ERAD; the covalent oligosaccharide structure is used as a signal to display the folding status of the host protein. In this study, we define the function of the Htm1 protein as an α1,2-specific exomannosidase that generates the Man7GlcNAc2 oligosaccharide with a terminal α1,6-linked mannosyl residue on degradation substrates. This oligosaccharide signal is decoded by the ER-localized lectin Yos9p that in conjunction with Hrd3p triggers the ubiquitin-proteasome–dependent hydrolysis of these glycoproteins. The Htm1p exomannosidase activity requires processing of the N-glycan by glucosidase I, glucosidase II, and mannosidase I, resulting in a sequential order of specific N-glycan structures that reflect the folding status of the glycoprotein

Effects of commercial apple varieties on human gut microbiota composition and metabolic output using an in vitro colonic model

Apples are a rich source of polyphenols and fiber. A major proportion of apple polyphenols escape absorption in the small intestine and together with non-digestible polysaccharides reach the colon, where they can serve as substrates for bacterial fermentation. Animal studies suggest a synergistic interaction between apple polyphenols and the soluble fiber pectin; however, the effects of whole apples on human gut microbiota are less extensively studied. Three commercial apple varieties-Renetta Canada, Golden Delicious and Pink Lady-were digested and fermented in vitro using a batch culture colonic model (pH 5.5-6.0, 37 °C) inoculated with feces from three healthy donors. Inulin and cellulose were used as a readily and a poorly fermentable plant fiber, respectively. Fecal microbiota composition was measured by 16S rRNA gene Illumina MiSeq sequencing (V3-V4 region) and Fluorescence in Situ Hybridization. Short chain fatty acids (SCFAs) and polyphenol microbial metabolites were determined. The three apple varieties significantly changed bacterial diversity, increased Actinobacteria relative abundance, acetate, propionate and total SCFAs (p < 0.05). Renetta Canada and Golden Delicious significantly decreased Bacteroidetes abundance and increased Proteobacteria proportion and bifidobacteria population (p < 0.05). Renetta Canada also increased Faecalibacterium prausnitzii, butyrate levels and polyphenol microbial metabolites (p < 0.05). Together, these data suggest that apples, particularly Renetta Canada, can induce substantial changes in microbiota composition and metabolic activity in vitro, which could be associated with potential benefits to human health. Human intervention studies are necessary to confirm these data and potential beneficial effects

Multi-task learning for joint weakly-supervised segmentation and aortic arch anomaly classification in fetal cardiac MRI

Congenital Heart Disease (CHD) is a group of cardiac malformations present already during fetal life, representing the prevailing category of birth defects globally. Our aim in this study is to aid 3D fetal vessel topology visualisation in aortic arch anomalies, a group which encompasses a range of conditions with significant anatomical heterogeneity. We present a multi-task framework for automated multi-class fetal vessel segmentation from 3D black blood T2w MRI and anomaly classification. Our training data consists of binary manual segmentation masks of the cardiac vessels' region in individual subjects and fully-labelled anomaly-specific population atlases. Our framework combines deep learning label propagation using VoxelMorph with 3D Attention U-Net segmentation and DenseNet121 anomaly classification. We target 11 cardiac vessels and three distinct aortic arch anomalies, including double aortic arch, right aortic arch, and suspected coarctation of the aorta. We incorporate an anomaly classifier into our segmentation pipeline, delivering a multi-task framework with the primary motivation of correcting topological inaccuracies of the segmentation. The hypothesis is that the multi-task approach will encourage the segmenter network to learn anomaly-specific features. As a secondary motivation, an automated diagnosis tool may have the potential to enhance diagnostic confidence in a decision support setting. Our results showcase that our proposed training strategy significantly outperforms label propagation and a network trained exclusively on propagated labels. Our classifier outperforms a classifier trained exclusively on T2w volume images, with an average balanced accuracy of 0.99 (0.01) after joint training. Adding a classifier improves the anatomical and topological accuracy of all correctly classified double aortic arch subjects.Comment: Accepted for publication at the Journal of Machine Learning for Biomedical Imaging (MELBA) https://melba-journal.org/2023:01

Fetal whole-heart 4D imaging using motion-corrected multi-planar real-time MRI

Purpose: To develop a MRI acquisition and reconstruction framework for volumetric cine visualisation of the fetal heart and great vessels in the presence of maternal and fetal motion. Methods: Four-dimensional depiction was achieved using a highly-accelerated multi-planar real-time balanced steady state free precession acquisition combined with retrospective image-domain techniques for motion correction, cardiac synchronisation and outlier rejection. The framework was evaluated and optimised using a numerical phantom, and evaluated in a study of 20 mid- to late-gestational age human fetal subjects. Reconstructed cine volumes were evaluated by experienced cardiologists and compared with matched ultrasound. A preliminary assessment of flow-sensitive reconstruction using the velocity information encoded in the phase of dynamic images is included. Results: Reconstructed cine volumes could be visualised in any 2D plane without the need for highly-specific scan plane prescription prior to acquisition or for maternal breath hold to minimise motion. Reconstruction was fully automated aside from user-specified masks of the fetal heart and chest. The framework proved robust when applied to fetal data and simulations confirmed that spatial and temporal features could be reliably recovered. Expert evaluation suggested the reconstructed volumes can be used for comprehensive assessment of the fetal heart, either as an adjunct to ultrasound or in combination with other MRI techniques. Conclusion: The proposed methods show promise as a framework for motion-compensated 4D assessment of the fetal heart and great vessels

Tanner-Whitehouse skeletal ages in male youth soccer players : TW2 or TW3?

BACKGROUND: The Tanner-Whitehouse radius-ulna-short bone protocol (TW2 RUS) for the assessment of skeletal age (SA) is widely used to estimate the biological (skeletal) maturity status of children and adolescents. The scale for converting TW RUS ratings to an SA has been revised (TW3 RUS) and has implications for studies of youth athletes in age-group sports. OBJECTIVES: The aim of this study was to compare TW2 and TW3 RUS SAs in an international sample of male youth soccer players and to compare distributions of players by maturity status defined by each SA protocol. METHODS: SA assessments with the TW RUS method were collated for 1831 male soccer players aged 11-17 years from eight countries. RUS scores were converted to TW2 and TW3 SAs using the appropriate tables. SAs were related to chronological age (CA) in individual athletes and compared by CA groups. The difference of SA minus CA with TW2 SA and with TW3 SA was used to classify players as late, average, or early maturing with each method. Concordance of maturity classifications was evaluated with Cohen's Kappa coefficients. RESULTS: For the same RUS score, TW3 SAs were systematically and substantially reduced compared with TW2 SAs; mean differences by CA group ranged from - 0.97 to - 1.16 years. Kappa coefficients indicated at best fair concordance of TW2 and TW3 maturity classifications. Across the age range, 42% of players classified as average with TW2 SA were classified as late with TW3 SA, and 64% of players classified as early with TW2 SA were classified as average with TW3 SA. CONCLUSION: TW3 SAs were systematically lower than corresponding TW2 SAs in male youth soccer players. The differences between scales have major implications for the classification of players by maturity status, which is central to some talent development programs