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Abstract Several studies have documented the significant impact of methodological choices in microbiome analyses. The myriad of methodological options available complicate the replication of results and generally limit the comparability of findings between independent studies that use differing techniques and measurement pipelines. Here we describe the Mosaic Standards Challenge (MSC), an international interlaboratory study designed to assess the impact of methodological variables on the results. The MSC did not prescribe methods but rather asked participating labs to analyze 7 shared reference samples (5 × human stool samples and 2 × mock communities) using their standard laboratory methods. To capture the array of methodological variables, each participating lab completed a metadata reporting sheet that included 100 different questions regarding the details of their protocol. The goal of this study was to survey the methodological landscape for microbiome metagenomic sequencing (MGS) analyses and the impact of methodological decisions on metagenomic sequencing results. A total of 44 labs participated in the MSC by submitting results (16S or WGS) along with accompanying metadata; thirty 16S rRNA gene amplicon datasets and 14 WGS datasets were collected. The inclusion of two types of reference materials (human stool and mock communities) enabled analysis of both MGS measurement variability between different protocols using the biologically-relevant stool samples, and MGS bias with respect to ground truth values using the DNA mixtures. Owing to the compositional nature of MGS measurements, analyses were conducted on the ratio of Firmicutes: Bacteroidetes allowing us to directly apply common statistical methods. The resulting analysis demonstrated that protocol choices have significant effects, including both bias of the MGS measurement associated with a particular methodological choices, as well as effects on measurement robustness as observed through the spread of results between labs making similar methodological choices. In the analysis of the DNA mock communities, MGS measurement bias was observed even when there was general consensus among the participating laboratories. This study was the result of a collaborative effort that included academic, commercial, and government labs. In addition to highlighting the impact of different methodological decisions on MGS result comparability, this work also provides insights for consideration in future microbiome measurement study design.

While the prognostic impact of QRS axis deviation has been assessed, it has never been investigated in patients without conduction block. Thus, we evaluated the prognostic impact of QRS-axis deviation in patients without conduction block. We retrospectively analyzed 3353 patients who had undergone both scheduled transthoracic echocardiography and electrocardiography in 2013 in a hospital-based population, after excluding patients with a QRS duration of ≥ 110 ms, pacemaker placement, and an QRS-axis - 90° to - 180° (northwest axis). The study population was categorized into three groups depending on the mean frontal plane QRS axis as follows: patients with left axis deviation (N = 171), those with right axis deviation (N = 94), and those with normal axis (N = 3088). The primary outcome was a composite of all-cause death and major adverse cardiovascular events. The cumulative 3-year incidence of the primary outcome measure was significantly higher in the left axis deviation group (26.4% in the left axis deviation, 22.7% in the right axis deviation, and 18.4% in the normal axis groups, log-rank P = 0.004). After adjusting for confounders, the excess risk of primary outcome measure remained significant in the left axis deviation group (hazard ratio [HR] 1.44; 95% confidence interval [CI] 1.07-1.95; P = 0.02), while the excess risk of primary outcome measure was not significant in the right axis deviation group (HR 1.22; 95% CI 0.76-1.96; P = 0.41). Left axis deviation was associated with a higher risk of a composite of all-cause death and major adverse cardiovascular events in hospital-based patients without conduction block in Japan.

We propose a growing network model that can generate dense scale-free networks with an almost neutral degree-degree correlation and a negative scaling of local clustering coefficient. The model is obtained by modifying an existing model in the literature that can also generate dense scale-free networks but with a different higher-order network structure. The modification is mediated by category theory. Category theory can identify a duality structure hidden in the previous model. The proposed model is built so that the identified duality is preserved. This work is a novel application of category theory for designing a network model focusing on a universal algebraic structure.

Networks are useful representations for analyzing and modeling real-world complex systems. They are often both scale-free and dense: their degree distribution follows a power-law and their average degree grows over time. So far, it has been argued that producing such networks is difficult without externally imposing a suitable cutoff for the scale-free regime. Here, we propose a new growing network model that produces dense scale-free networks with dynamically generated cutoffs. The link formation rule is based on a weak form of preferential attachment depending only on order relations between the degrees of nodes. By this mechanism, our model yields scale-free networks whose scaling exponents can take arbitrary values greater than 1. In particular, the resulting networks are dense when scaling exponents are 2 or less. We analytically study network properties such as the degree distribution, the degree correlation function, and the local clustering coefficient. All analytical calculations are in good agreement with numerical simulations. These results show that both sparse and dense scale-free networks can emerge through the same self-organizing process.

We previously reported that chronic rhinosinusitis with nasal polyps (CRSwNP) was subdivided into four chronic rhinosinusitis (CRS) subtypes using the JESREC scoring system. We sought to identify the gene expression profile and biomarkers related with CRSwNP by RNA-sequence. RNA-sequencing was performed to identify differentially expressed genes between nasal polyps (NPs) and inferior turbinate mucosa from 6 patients with CRSwNP, and subsequently, quantitative real-time PCR was performed to verify the results. ELISA was performed to identify possible biomarkers for postoperative recurrence. In the RNA-sequencing results, periostin (POSTN) expression was the highest in NP. We focused on POSTN and investigated the protein level of POSTN by immunohistochemistry and ELISA. POSTN was diffusely expressed in moderate and severe eosinophilic CRS using immunohistochemistry, and its staining pattern was associated with the severity of the phenotype of the CRSwNP (P < 0.05). There was a significant difference between the POSTN high/low groups for postoperative recurrence when the cutoff point was set at 115.5 ng/ml (P = 0.0072). Our data suggests that the protein expression level of POSTN was associated with the severity of CRSwNP, and serum POSTN can be a novel biomarker for postoperative recurrence of CRSwNP.

This study investigated the relationship between atrial fibrillation (AF) and left ventricular (LV) geometric patterns in a hospital-based population in Japan. We retrospectively analyzed 4444 patients who had undergone simultaneous scheduled transthoracic echocardiography (TTE) and electrocardiography during 2013. A total of 430 patients who had findings of previous myocardial infarctions (n = 419) and without the data on body surface area (n = 11) were excluded from the study. We calculated the LV mass index (LVMI) and relative wall (RWT) and categorized 4014 patients into four groups as follows: normal geometry (n = 3046); concentric remodeling (normal LVMI and high RWT, n = 437); concentric hypertrophy (high LVMI and high RWT, n = 149); and eccentric remodeling (high LVMI and normal RWT, n = 382). The mean left atrial volume indices (LAVI) were 22.5, 23.8, 33.3, and 37.0 mm/m 2 in patients with normal geometry, concentric remodeling, concentric hypertrophy, and eccentric hypertrophy, respectively. The mean LV ejection fractions (LVEF) were 62.7, 62.6, 60.8, and 53.8%, respectively, whereas the prevalence of AF was 10.4%, 10.5%, 14.8%, and 16.8% in patients with normal geometry, concentric remodeling, concentric hypertrophy, and eccentric hypertrophy, respectively. In conclusion, the prevalence of AF was increasing according to LV geometric remodeling patterns in association with LA size and LVEF.