Microbiome data from sequencing experiments contain the relative abundance of a large number of microbial taxa with their evolutionary relationships represented by a phylogenetic tree. The ...compositional and high-dimensional nature of the microbiome mediator challenges the validity of standard mediation analyses. We propose a phylogeny-based mediation analysis method called PhyloMed to address this challenge. Unlike existing methods that directly identify individual mediating taxa, PhyloMed discovers mediation signals by analyzing subcompositions defined on the phylogenic tree. PhyloMed produces well-calibrated mediation test p-values and yields substantially higher discovery power than existing methods.
There is heightened interest in using high-throughput sequencing technologies to quantify abundances of microbial taxa and linking the abundance to human diseases and traits. Proper modeling of ...multivariate taxon counts is essential to the power of detecting this association. Existing models are limited in handling excessive zero observations in taxon counts and in flexibly accommodating complex correlation structures and dispersion patterns among taxa. In this article, we develop a new probability distribution, zero-inflated generalized Dirichlet multinomial (ZIGDM), that overcomes these limitations in modeling multivariate taxon counts. Based on this distribution, we propose a ZIGDM regression model to link microbial abundances to covariates (e.g. disease status) and develop a fast expectation-maximization algorithm to efficiently estimate parameters in the model. The derived tests enable us to reveal rich patterns of variation in microbial compositions including differential mean and dispersion. The advantages of the proposed methods are demonstrated through simulation studies and an analysis of a gut microbiome dataset.
Given the successful identification of epidermal growth factor receptor EGFR T790M, the third-generation EGFR tyrosine kinase inhibitor (TKI), osimertinib (OSI, AZD9291), was developed to target EGFR ...T790M mutation. OSI was approved for the treatment of patients with non-small cell lung cancer (NSCLC) harboring EGFR T790M mutation. However, the disease would progress after the patient received OSI treatment for approximately 10 months. Resistance mechanisms to OSI, such as additional mutation of EGFR and alternative kinase activation, were recently identified, and some novel therapeutic strategies were proposed to overcome OSI resistance. In this review, the resistance mechanisms and therapeutic strategies for OSI-resistant NSCLC were summarized to direct further use of OSI and aid in the development of novel drugs or strategies for OSI-resistant NSCLC.
•Both EGFR-dependent and -independent manners contribute to the resistant mechanisms.•Re-biopsy to study the resistance mechanisms at the time of progression is required.•Immunotherapy might be used for treating a sub-set of OSI-resistant NSCLC.•More research is needed for treating NSCLC harboring naive EGFR mutation with OSI.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Summary
Guaranteed‐cost consensus for high‐order nonlinear multiagent networks with switching topologies is investigated. By constructing a time‐varying nonsingular matrix with a specific structure, ...the whole dynamics of multiagent networks is decomposed into the consensus and disagreement parts with nonlinear terms, which is the key challenge to be dealt with. An explicit expression of the consensus dynamics, which contains the nonlinear term, is given and its initial state is determined. Furthermore, by the structure property of the time‐varying nonsingular transformation matrix and the Lipschitz condition, the impacts of the nonlinear term on the disagreement dynamics are linearized, and the gain matrix of the consensus protocol is determined on the basis of the Riccati equation. Moreover, an approach to minimize the guaranteed cost is given in terms of linear matrix inequalities. Finally, the numerical simulation is shown to demonstrate the effectiveness of theoretical results.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
To understand how organisms adapt to their environment, a gene‐environmental association (GEA) analysis is commonly conducted. GEA methods based on mixed models, such as linear latent factor mixed ...models (LFMM) and LFMM2, have grown in popularity for their robust performance in terms of power and computational speed. However, it is unclear how the assumption of a Gaussian distribution for the response variables influences model performance. In this paper, we develop a generalized linear model (GLM) that allows for non‐Gaussian distribution in the genotypic response variables, and treatment of multiallelic nucleotide polymorphisms. Moreover, this multinomial logistic regression model (MLR) is combined with an admixture‐based model or principal components analysis to correct for population structure (MLR‐ADM and MLR‐PC). Using simulations, we evaluate the type 1 error, false discovery rates (FDR), and power to detect selected SNPs, to guide model choice and best practices. With genomic control, MLR‐PC and LFMM2 have similar type 1 error, FDRs, and power when analysing biallelic SNPs, while dramatically outperforming models not accounting for population structure. Differences in performance occur under continuous population structure where MLR‐PC outperforms LFMM/LFMM2, especially when a larger number of clusters or triallelic SNPs are analysed. The Human Genome Diversity Project (HGDP) data set shows that both MLR‐PC and LFMM2 control the inflation of P‐values. Analysis of the 1,000 Genome Project Phase 3 data set illustrates that MLR‐PC and LFMM2 produce consistent results for most significant SNPs, while MLR‐PC discovered additional SNPs corresponding to certain genes, suggesting MLR‐PC may be a useful alternative to GEA inference.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Social relationships shape human health and mortality via behavioral, psychosocial, and physiological mechanisms, including inflammatory and immune responses. Though not tested in human studies, ...recent primate studies indicate that the gut microbiome may also be a biological mechanism linking relationships to health. Integrating microbiota data into the 60-year-old Wisconsin Longitudinal Study, we found that socialness with family and friends is associated with differences in the human fecal microbiota. Analysis of spouse (N = 94) and sibling pairs (N = 83) further revealed that spouses have more similar microbiota and more bacterial taxa in common than siblings, with no observed differences between sibling and unrelated pairs. These differences held even after accounting for dietary factors. The differences between unrelated individuals and married couples was driven entirely by couples who reported close relationships; there were no differences in similarity between couples reporting somewhat close relationships and unrelated individuals. Moreover, married individuals harbor microbial communities of greater diversity and richness relative to those living alone, with the greatest diversity among couples reporting close relationships, which is notable given decades of research documenting the health benefits of marriage. These results suggest that human interactions, especially sustained, close marital relationships, influence the gut microbiota.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
There is general consensus that consumption of dietary fermentable fiber improves cardiometabolic health, in part by promoting mutualistic microbes and by increasing production of beneficial ...metabolites in the distal gut. However, human studies have reported variations in the observed benefits among individuals consuming the same fiber. Several factors likely contribute to this variation, including host genetic and gut microbial differences. We hypothesized that gut microbial metabolism of dietary fiber represents an important and differential factor that modulates how dietary fiber impacts the host.
We examined genetically identical gnotobiotic mice harboring two distinct complex gut microbial communities and exposed to four isocaloric diets, each containing different fibers: (i) cellulose, (ii) inulin, (iii) pectin, (iv) a mix of 5 fermentable fibers (assorted fiber). Gut microbiome analysis showed that each transplanted community preserved a core of common taxa across diets that differentiated it from the other community, but there were variations in richness and bacterial taxa abundance within each community among the different diet treatments. Host epigenetic, transcriptional, and metabolomic analyses revealed diet-directed differences between animals colonized with the two communities, including variation in amino acids and lipid pathways that were associated with divergent health outcomes.
This study demonstrates that interindividual variation in the gut microbiome is causally linked to differential effects of dietary fiber on host metabolic phenotypes and suggests that a one-fits-all fiber supplementation approach to promote health is unlikely to elicit consistent effects across individuals. Overall, the presented results underscore the importance of microbe-diet interactions on host metabolism and suggest that gut microbes modulate dietary fiber efficacy. Video abstract.
Chemical doping has been demonstrated to be an effective way to realize new functions of graphene as metal‐free catalyst in energy‐related electrochemical reactions. Although efficient catalysis for ...the oxygen reduction reaction (ORR) has been achieved with doped graphene, its performance in the hydrogen evolution reaction (HER) is rather poor. In this study we report that nitrogen and sulfur co‐doping leads to high catalytic activity of nanoporous graphene in HER at low operating potential, comparable to the best Pt‐free HER catalyst, 2D MoS2. The interplay between the chemical dopants and geometric lattice defects of the nanoporous graphene plays the fundamental role in the superior HER catalysis.
Together they're strong: Nitrogen and sulfur co‐doped nanoporous graphene displays high catalytic activity in the hydrogen evolution reaction (HER) at low operating potential. The interplay between the chemical dopants and geometric lattice defects is crucial for the superior HER performance by minimizing the Gibbs free energy of H* absorption.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Abstract
Delving into the influence of strain on organic reactions in small molecules at the molecular level can unveil valuable insight into developing innovative synthetic strategies and ...structuring molecules with superior properties. Herein, we present a molecular‐strain engineering approach to facilitate the consecutive 1,2‐aryl shift (formal 1,3‐aryl shift) in molecular bows (MBs) that integrate 1,4‐dimethoxy‐2,5‐cyclohexadiene moieties. By introducing ring strain into MBs through tethering the bow limb, we can harness the intrinsic mechanical forces to drive multistep aryl shifts from the
para‐
to the
meta‐
to the
ortho‐
position. Through the use of precise intramolecular strain, the seemingly impractical 1,3‐aryl shift was realized, resulting in the formation of
ortho‐
disubstituted products. The solvent and temperature play a crucial role in the occurrence of the 1,3‐aryl shift. The free energy calculations with inclusion of solvation support a feasible mechanism, which entails multistep carbocation rearrangements, for the formal 1,3‐aryl shift. By exploring the application of molecular strain in synthetic chemistry, this research offers a promising direction for developing new tools and strategies towards precision organic synthesis.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
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