Critical COVID-19, Victivallaceae abundance, and celiac disease: A mediation Mendelian randomization study.

Celiac disease exhibits a higher prevalence among patients with coronavirus disease 2019. However, the potential influence of COVID-19 on celiac disease remains uncertain. Considering the significant association between gut microbiota alterations, COVID-19 and celiac disease, the two-step Mendelian randomization method was employed to investigate the genetic causality between COVID-19 and celiac disease, with gut microbiota as the potential mediators. We employed the genome-wide association study to select genetic instrumental variables associated with the exposure. Subsequently, these variables were utilized to evaluate the impact of COVID-19 on the risk of celiac disease and its potential influence on gut microbiota. Employing a two-step Mendelian randomization approach enabled the examination of potential causal relationships, encompassing: 1) the effects of COVID-19 infection, hospitalized COVID-19 and critical COVID-19 on the risk of celiac disease; 2) the influence of gut microbiota on celiac disease; and 3) the mediating impact of the gut microbiota between COVID-19 and the risk of celiac disease. Our findings revealed a significant association between critical COVID-19 and an elevated risk of celiac disease (inverse variance weighted [IVW]: P = 0.035). Furthermore, we observed an inverse correlation between critical COVID-19 and the abundance of Victivallaceae (IVW: P = 0.045). Notably, an increased Victivallaceae abundance exhibits a protective effect against the risk of celiac disease (IVW: P = 0.016). In conclusion, our analysis provides genetic evidence supporting the causal connection between critical COVID-19 and lower Victivallaceae abundance, thereby increasing the risk of celiac disease.

Aberrant expression of thyroidal hormone receptor α exasperating mitochondrial dysfunction induced sarcopenia in aged mice.

Disrupted mitochondrial dynamics and mitophagy contribute to functional deterioration of skeletal muscle (SM) during aging, but the regulatory mechanisms are poorly understood. Our previous study demonstrated that the expression of thyroid hormone receptor α (TRα) decreased significantly in aged mice, suggesting that the alteration of thyroidal elements, especially the decreased TRα, might attenuate local THs action thus to cause the degeneration of SM with aging, while the underlying mechanism remains to be further explored. In this study, decreased expression of myogenic regulators Myf5, MyoD1, mitophagy markers Pink1, LC3II/I, p62, as well as mitochondrial dynamic factors Mfn1 and Opa1, accompanied by increased reactive oxygen species (ROS), showed concomitant changes with reduced TRα expression in aged mice. Further TRα loss- and gain-of-function studies in C2C12 revealed that silencing of TRα not only down-regulated the expression of above-mentioned myogenic regulators, mitophagy markers and mitochondrial dynamic factors, but also led to a significant decrease in mitochondrial activity and maximum respiratory capacity, as well as more mitochondrial ROS and damaged mitochondria. Notedly, overexpression of TRα could up-regulate the expression of those myogenic regulators, mitophagy markers and mitochondrial dynamic factors, meanwhile also led to an increase in mitochondrial activity and number. These results confirmed that TRα could concertedly regulate mitochondrial dynamics, autophagy, and activity, and myogenic regulators rhythmically altered with TRα expression. Summarily, these results suggested that the decline of TRα might cause the degeneration of SM with aging by regulating mitochondrial dynamics, mitophagy and myogenesis.

Flexible statistical methods for estimating and testing effects in genomic studies with multiple conditions.

We introduce mvSuSiE, a multi-trait fine-mapping method for identifying putative causal variants from genetic association data (individual-level or summary data). mvSuSiE learns patterns of shared genetic effects from data, and exploits these patterns to improve power to identify causal SNPs. Comparisons on simulated data show that mvSuSiE is competitive in speed, power and precision with existing multi-trait methods, and uniformly improves on single-trait fine-mapping (SuSiE) in each trait separately. We applied mvSuSiE to jointly fine-map 16 blood cell traits using data from the UK Biobank. By jointly analyzing the traits and modeling heterogeneous effect sharing patterns, we discovered a much larger number of causal SNPs (>3,000) compared with single-trait fine-mapping, and with narrower credible sets. mvSuSiE also more comprehensively characterized the ways in which the genetic variants affect one or more blood cell traits; 68% of causal SNPs showed significant effects in more than one blood cell type.

Nuclear receptor corepressor 1 deficiency exacerbates asthma by modulating macrophage polarization.

Macrophage polarization plays an important role in asthma. Nuclear receptor corepressor 1 (NCOR1) plays an important role in metabolic and cardiovascular diseases by regulating the function of macrophages. The aim of this research was to examine the role and mechanism of macrophage NCOR1 in the development of asthma. We used ovalbumin (OVA) to induce macrophage NCOR1-deficient mice for asthma formation. Our results revealed that macrophage NCOR1 deficiency markedly enhanced allergic airway inflammation. In addition, NCOR1 deficiency in macrophages was found to enhance M2 polarization. Mechanistic studies suggested that NCOR1 promoted macrophage polarization by interacting with PPARγ, contributing to the pathogenesis of asthma. In conclusion, macrophage NCOR1 deficiency promoted the regulation of M2 programming by enhancing PPARγ expression to exacerbate asthma. Macrophage NCOR1 might be a potential target for the treatment of asthma.

Genotyping, sequencing and analysis of 140,000 adults from Mexico City.

The Mexico City Prospective Study is a prospective cohort of more than 150,000 adults recruited two decades ago from the urban districts of Coyoacán and Iztapalapa in Mexico City1. Here we generated genotype and exome-sequencing data for all individuals and whole-genome sequencing data for 9,950 selected individuals. We describe high levels of relatedness and substantial heterogeneity in ancestry composition across individuals. Most sequenced individuals had admixed Indigenous American, European and African ancestry, with extensive admixture from Indigenous populations in central, southern and southeastern Mexico. Indigenous Mexican segments of the genome had lower levels of coding variation but an excess of homozygous loss-of-function variants compared with segments of African and European origin. We estimated ancestry-specific allele frequencies at 142 million genomic variants, with an effective sample size of 91,856 for Indigenous Mexican ancestry at exome variants, all available through a public browser. Using whole-genome sequencing, we developed an imputation reference panel that outperforms existing panels at common variants in individuals with high proportions of central, southern and southeastern Indigenous Mexican ancestry. Our work illustrates the value of genetic studies in diverse populations and provides foundational imputation and allele frequency resources for future genetic studies in Mexico and in the United States, where the Hispanic/Latino population is predominantly of Mexican descent.

From Topological Nodal-Line Semimetal to Insulator in ABW-Ge4: A New Member of the Germanium Allotrope.

Topological semimetals have attracted much attention because of their excellent properties, such as ultra-high speed, low energy consumption quantum transport, and negative reluctance. Searching materials with topological semimetallic properties has become a new research field for Group-IV materials. Herein, using first-principles calculations and tight-binding modeling, we proposed a topological nodal-line semimetal ABW-Ge4 when spin-orbit coupling (SOC) is ignored, which is composed of pure germanium atoms in a zeolite framework ABW. It holds excellent dynamic and thermal stability. In its electronic band structure, there exists a stable Dirac linear band crossing near the Fermi energy level, which forms a closed ring in the kx = 0 plane of the Brillouin zone (BZ). Our symmetry analysis reveals that the nodal ring is protected by Mx mirror symmetry. Furthermore, by examining the slope index in all possible k paths through the considered Dirac point, we find that the band dispersion near the Dirac point is greatly anisotropic. In some direction, the Fermi velocity is even larger than that of graphene, being promising for the future ultra-high speed device. When spin-orbit coupling is included, the nodal line is gapped and the system becomes a topological insulator with topological invariants Z2 = 1. Our findings not only identify a new Ge allotrope but also establish a promising topological material in Group-IV materials, which may have the desirable compatibility with the traditional semiconductor industry.

TT3, a More Practical Indicator for Evaluating the Relationship Between Sarcopenia and Thyroid Hormone in the Euthyroid Elderly Compared with FT3.

Background and Aims: Sarcopenia is a common disease in the elderly, and the thyroid hormone (TH) might participate in the pathogenesis of sarcopenia. However, the results of previous studies were not completely consistent. We performed this study to investigate the association between THs and sarcopenia in a Chinese elderly euthyroid population. Subjects and Methods: A total of 309 Chinese elderly euthyroid subjects with an average age of 85.19 ± 7.8 years were enrolled. Participants were divided into four groups (non-sarcopenia, possible sarcopenia, sarcopenia and serve sarcopenia) according to the consensus update of AWGS in 2019. Serum levels of TT3, FT3, TT4, FT4, TSH, rT3 and TBG were measured. Muscle mass was measured by multifrequency bioelectrical impedance analysis, hand grip (HG) was represented by spring-type dynamometer, and gait speed (GS) was determined by 6-metre walk test. The FRAIL scale was used to assess frailty. Results: Compared to the non-sarcopenia group, the sarcopenia group showed a significant increase in age and FRIAL score, while FT3 and TT3 levels decreased significantly. Partial correlation analysis (adjusted by age, gender and the scores of FRIAL scale) indicated that FT3, TT3 and TSH had significant positive correlations with HG, and there also was a significant positive correlation between TT3 and GS. In addition, after adjusting for age, gender, BMI, ALT, sCr, and score on the FRAIL scale, the multivariate linear regression analysis showed that TT3 was positively associated with muscle strength and negatively associated with sarcopenia risk. Conclusion: There is an association between the low TT3 level and sarcopenia. Therefore, maintaining higher T3 concentrations within the normal range appears to be beneficial for sarcopenia in the elderly. In addition, due to the fluctuation of FT3, TT3 is a more stable and practical indicator to evaluate the relationship between sarcopenia and thyroid hormone in the elderly euthyroid population.

Maturation of the gut metabolome during the first year of life in humans.

The gut microbiota is involved in the production of numerous metabolites that maintain host wellbeing. The assembly of the gut microbiome is highly dynamic, and influenced by many postnatal factors, moreover, little is known about the development of the gut metabolome. We showed that geography has an important influence on the microbiome dynamics in the first year of life based on two independent cohorts from China and Sweden. Major compositional differences since birth were the high relative abundance of Bacteroides in the Swedish cohort and Streptococcus in the Chinese cohort. We analyzed the development of the fecal metabolome in the first year of life in the Chinese cohort. Lipid metabolism, especially acylcarnitines and bile acids, was the most abundant metabolic pathway in the newborn gut. Delivery mode and feeding induced particular differences in the gut metabolome since birth. In contrast to C-section newborns, medium- and long-chain acylcarnitines were abundant at newborn age only in vaginally delivered infants, associated by the presence of bacteria such as Bacteroides vulgatus and Parabacteroides merdae. Our data provide a basis for understanding the maturation of the fecal metabolome and the metabolic role of gut microbiota in infancy.

A flexible empirical Bayes approach to multivariate multiple regression, and its improved accuracy in predicting multi-tissue gene expression from genotypes.

Predicting phenotypes from genotypes is a fundamental task in quantitative genetics. With technological advances, it is now possible to measure multiple phenotypes in large samples. Multiple phenotypes can share their genetic component; therefore, modeling these phenotypes jointly may improve prediction accuracy by leveraging effects that are shared across phenotypes. However, effects can be shared across phenotypes in a variety of ways, so computationally efficient statistical methods are needed that can accurately and flexibly capture patterns of effect sharing. Here, we describe new Bayesian multivariate, multiple regression methods that, by using flexible priors, are able to model and adapt to different patterns of effect sharing and specificity across phenotypes. Simulation results show that these new methods are fast and improve prediction accuracy compared with existing methods in a wide range of settings where effects are shared. Further, in settings where effects are not shared, our methods still perform competitively with state-of-the-art methods. In real data analyses of expression data in the Genotype Tissue Expression (GTEx) project, our methods improve prediction performance on average for all tissues, with the greatest gains in tissues where effects are strongly shared, and in the tissues with smaller sample sizes. While we use gene expression prediction to illustrate our methods, the methods are generally applicable to any multi-phenotype applications, including prediction of polygenic scores and breeding values. Thus, our methods have the potential to provide improvements across fields and organisms.

Study on the Stability of Low-Carbon Magnesium Cementitious Materials in Sulfate Erosion Environments.

The current investigation focuses on the stability of the magnesium oxide-based cementitious system under the action of sulfate attack and the dry-wet cycle. The phase change in the magnesium oxide-based cementitious system was quantitatively analyzed by X-ray diffraction, combined with thermogravimetry/derivative thermogravimetry and scanning electron microscope, to explore its erosion behavior under an erosion environment. The results revealed that, in the fully reactive magnesium oxide-based cementitious system under the environment of high concentration sulfate erosion, there was only magnesium silicate hydrate gel formation and no other phase; however, the reaction process of the incomplete magnesium oxide-based cementitious system was delayed, but not inhibited, by the environment of high-concentration sulfate, and it tended to turn completely into a magnesium silicate hydrate gel. The magnesium silicate hydrate sample outperformed the cement sample, in terms of stability in a high-concentration sulfate erosion environment, but it tended to degrade considerably more rapidly, and to a greater extent, than Portland cement, in both dry and wet sulfate cycle environments.

First-Principles Study on Mechanical, Electronic, and Magnetic Properties of Room Temperature Ferromagnetic Half-Metal MnNCl Monolayer.

Two-dimensional ferromagnetic (FM) half-metals are highly desirable for the development of multifunctional spintronic nano-devices due to their 100% spin polarization and possible interesting single-spin electronic states. Herein, using first-principles calculations based on density functional theory (DFT) with the Perdew-Burke-Ernzerhof (PBE) functional, we demonstrate that the MnNCl monolayer is a promising FM half-metal for spintronics. Specifically, we systematically investigated its mechanical, magnetic, and electronic properties. The results reveal that the MnNCl monolayer has superb mechanic, dynamic, and thermal (ab initio molecular dynamics (AIMD) simulation at 900 K) stability. More importantly, its intrinsic FM ground state has a large magnetic moment (6.16 µB), a large magnet anisotropy energy (184.5 µeV), an ultra-high Curie temperature (952 K), and a wide direct band gap (3.10 eV) in the spin-down channel. Furthermore, by applying biaxial strain, the MnNCl monolayer can still maintain its half-metallic properties and shows an enhancement of magnetic properties. These findings establish a promising new two-dimensional (2D) magnetic half-metal material, which should expand the library of 2D magnetic materials.

Development and validation of a deep learning-based approach to predict the Mayo endoscopic score of ulcerative colitis.

Background: The ulcerative colitis (UC) Mayo endoscopy score is a useful tool for evaluating the severity of UC in patients in clinical practice. Objectives: We aimed to develop and validate a deep learning-based approach to automatically predict the Mayo endoscopic score using UC endoscopic images. Design: A multicenter, diagnostic retrospective study. Methods: We collected 15120 colonoscopy images of 768 UC patients from two hospitals in China and developed a deep model based on a vision transformer named the UC-former. The performance of the UC-former was compared with that of six endoscopists on the internal test set. Furthermore, multicenter validation from three hospitals was also carried out to evaluate UC-former's generalization performance. Results: On the internal test set, the areas under the curve of Mayo 0, Mayo 1, Mayo 2, and Mayo 3 achieved by the UC-former were 0.998, 0.984, 0.973, and 0.990, respectively. The accuracy (ACC) achieved by the UC-former was 90.8%, which is higher than that achieved by the best senior endoscopist. For three multicenter external validations, the ACC was 82.4%, 85.0%, and 83.6%, respectively. Conclusions: The developed UC-former could achieve high ACC, fidelity, and stability to evaluate the severity of UC, which may provide potential application in clinical practice. Registration: This clinical trial was registered at the ClinicalTrials.gov (trial registration number: NCT05336773).

Why was this study done? The development of an auxiliary diagnostic tool can reduce the workload of endoscopists and achieve rapid assessment of ulcerative colitis (UC) severity. What did the researchers do? We developed and validated a deep learning-based approach to automatically predict the Mayo endoscopic score using UC endoscopic images. What did the researchers find? The model that was developed in this study achieved high accuracy, fidelity, and stability, and demonstrated potential application in clinical practice. What do the findings mean? Deep learning could effectively assist endoscopists in evaluating the severity of UC in patients using endoscopic images.

Test-time bi-directional adaptation between image and model for robust segmentation.

BACKGROUND AND OBJECTIVE: Deep learning models often suffer from performance degradations when deployed in real clinical environments due to appearance shifts between training and testing images. Most extant methods use training-time adaptation, which almost require target domain samples in the training phase. However, these solutions are limited by the training process and cannot guarantee the accurate prediction of test samples with unforeseen appearance shifts. Further, it is impractical to collect target samples in advance. In this paper, we provide a general method of making existing segmentation models robust to samples with unknown appearance shifts when deployed in daily clinical practice. METHODS: Our proposed test-time bi-directional adaptation framework combines two complementary strategies. First, our image-to-model (I2M) adaptation strategy adapts appearance-agnostic test images to the learned segmentation model using a novel plug-and-play statistical alignment style transfer module during testing. Second, our model-to-image (M2I) adaptation strategy adapts the learned segmentation model to test images with unknown appearance shifts. This strategy applies an augmented self-supervised learning module to fine-tune the learned model with proxy labels that it generates. This innovative procedure can be adaptively constrained using our novel proxy consistency criterion. This complementary I2M and M2I framework demonstrably achieves robust segmentation against unknown appearance shifts using existing deep-learning models. RESULTS: Extensive experiments on 10 datasets containing fetal ultrasound, chest X-ray, and retinal fundus images demonstrate that our proposed method achieves promising robustness and efficiency in segmenting images with unknown appearance shifts. CONCLUSIONS: To address the appearance shift problem in clinically acquired medical images, we provide robust segmentation by using two complementary strategies. Our solution is general and amenable for deployment in clinical settings.

Peer Support and Exercise Adherence in Adolescents: The Chain-Mediated Effects of Self-Efficacy and Self-Regulation.

In the context of exercise psychology, the mediating relationship between peer support, self-efficacy and self-regulation, and adolescents' exercise adherence was to be explored. METHODS: A questionnaire was distributed among 2200 teenagers from twelve middle schools in Shanghai. The "process" program in SPSS and the bootstrap method were applied to construct and analyze the direct and indirect effects of peer support on adolescents' exercise adherence. RESULTS: Peer support directly affected adolescents' exercise adherence (ß = 0.135, p < 0.001, effect size of 59%) and self-efficacy (ß = 0.493, p < 0.001, effect size accounted for 42%), and self-regulation (ß = -0.184, p < 0.001, effect size of 11%) influenced exercise adherence indirectly. In addition, self-efficacy and self-regulation could impose a chain-mediated effect on peer support and exercise adherence (effect size of 6%). CONCLUSION: Peer support could promote adolescents' exercise adherence. Self-efficacy and self-regulation are mediating factors of peer support on exercise adherence in teenagers, self-regulation as well as self-efficacy-imposed chain-mediating effects on peer support and adolescents' exercise adherence.

Effect of Breastmilk Microbiota and Sialylated Oligosaccharides on the Colonization of Infant Gut Microbial Community and Fecal Metabolome.

The complex microbiota and sialylated oligosaccharides in breastmilk are important bioactive components that affect the gut microbiota. However, the effect of breastmilk microbiota and sialylated oligosaccharides on the gut microbiota during the neonatal period has been largely overlooked. Here, 16S rRNA gene sequencing and metabolomics analysis were applied to the breastmilk and feces of 69 newborns to clarify the link between breastmilk components and the newborn gut. Results showed that Staphylococcus, Enterococcus, and Bacteroides were commonly shared and positively correlated between breastmilk and the neonatal intestine and they were the main bacteria of breastmilk that interacted with the newborn fecal metabolome. Breastmilk Staphylococcus mainly interacted with amino acids, whereas Bacteroides was involved in the tryptophan, nucleotide, and vitamin metabolism. Breastmilk sialylated oligosaccharides were related to Bacteroides and amino acids of the newborn fecal metabolites. Moreover, Bacteroides was related to the interaction between breastmilk 3'-sialyllactose and newborn fecal metabolites in the mediation effect models. Finally, we pointed out that breastmilk Bacteroides was important in the milk-gut interaction, and it was negatively associated with waist circumference in infants aged 1 year. Our study provides a scientific basis for understanding the role of breastmilk in the development of newborn gut microbiota and metabolome.

Common and rare variant associations with clonal haematopoiesis phenotypes.

Clonal haematopoiesis involves the expansion of certain blood cell lineages and has been associated with ageing and adverse health outcomes1-5. Here we use exome sequence data on 628,388 individuals to identify 40,208 carriers of clonal haematopoiesis of indeterminate potential (CHIP). Using genome-wide and exome-wide association analyses, we identify 24 loci (21 of which are novel) where germline genetic variation influences predisposition to CHIP, including missense variants in the lymphocytic antigen coding gene LY75, which are associated with reduced incidence of CHIP. We also identify novel rare variant associations with clonal haematopoiesis and telomere length. Analysis of 5,041 health traits from the UK Biobank (UKB) found relationships between CHIP and severe COVID-19 outcomes, cardiovascular disease, haematologic traits, malignancy, smoking, obesity, infection and all-cause mortality. Longitudinal and Mendelian randomization analyses revealed that CHIP is associated with solid cancers, including non-melanoma skin cancer and lung cancer, and that CHIP linked to DNMT3A is associated with the subsequent development of myeloid but not lymphoid leukaemias. Additionally, contrary to previous findings from the initial 50,000 UKB exomes6, our results in the full sample do not support a role for IL-6 inhibition in reducing the risk of cardiovascular disease among CHIP carriers. Our findings demonstrate that CHIP represents a complex set of heterogeneous phenotypes with shared and unique germline genetic causes and varied clinical implications.

Fine-mapping from summary data with the "Sum of Single Effects" model.

In recent work, Wang et al introduced the "Sum of Single Effects" (SuSiE) model, and showed that it provides a simple and efficient approach to fine-mapping genetic variants from individual-level data. Here we present new methods for fitting the SuSiE model to summary data, for example to single-SNP z-scores from an association study and linkage disequilibrium (LD) values estimated from a suitable reference panel. To develop these new methods, we first describe a simple, generic strategy for extending any individual-level data method to deal with summary data. The key idea is to replace the usual regression likelihood with an analogous likelihood based on summary data. We show that existing fine-mapping methods such as FINEMAP and CAVIAR also (implicitly) use this strategy, but in different ways, and so this provides a common framework for understanding different methods for fine-mapping. We investigate other common practical issues in fine-mapping with summary data, including problems caused by inconsistencies between the z-scores and LD estimates, and we develop diagnostics to identify these inconsistencies. We also present a new refinement procedure that improves model fits in some data sets, and hence improves overall reliability of the SuSiE fine-mapping results. Detailed evaluations of fine-mapping methods in a range of simulated data sets show that SuSiE applied to summary data is competitive, in both speed and accuracy, with the best available fine-mapping methods for summary data.

2,3',4,4',5-Pentachlorobiphenyl attenuated fast-twitch fibers and fiber size of skeletal muscle via disturbing thyroid hormone signaling and mitochondrial dynamics.

Polychlorinated biphenyls (PCBs) affect multiple organs, and some of the effects are mediated by interfering with thyroid hormone (TH) signaling that regulates physiological processes in mammals. It remains unclear how PCBs affect skeletal muscle (SM). In our study, wistar rats were injected 2,3',4,4',5-pentachlorobiphenyl (PCB118) intraperitoneally at 0, 10, 100, and 1000 µg/kg/day for 13 weeks, and C2C12 myoblasts were treated PCB118 (0, 0.25, 25, and 50 nM) for 24 h or 48 h. We found that myocyte cross-sectional area (MCSA) was reduced, MyHC IIa and MyHC IIb mRNA levels significantly decreased, and muscle strength was weakened in PCB118-exposed rats. TH receptor α (TRα) and iodothyronine deiodinase type 2 (DIO2) were upregulated after PCB118 exposure both in vivo and in vitro. Transmission electron microscopy showed significant mitochondrial abnormalities in PCB118-treated rats, and the expression of mitochondrial regulators such as PTEN-induced kinase 1 (PINK1) and GTPase dynamin-related protein 1 (DRP1) were altered after PCB118 exposure. These results suggest that PCB118 could weaken muscle strength and attenuate fast-twitch fibers and fiber size of SM in rats. TH signaling, mitochondrial dynamics and mitophagy were also disturbed by PCB118, which may contribute to the alternations of SM structure and function.