Quantifying Blood Pressure Visit-to-Visit Variability in the Real-World Setting: A Retrospective Cohort Study.

Background: Visit-to-visit variability (VVV) in blood pressure values has been reported in clinical studies. However, little is known about VVV in clinical practice and whether it is associated with patient characteristics in real-world setting.

Methods: We conducted a retrospective cohort study to quantify VVV in systolic blood pressure (SBP) values in a real-world setting.

Zero-preserving imputation of single-cell RNA-seq data.

A key challenge in analyzing single cell RNA-sequencing data is the large number of false zeros, where genes actually expressed in a given cell are incorrectly measured as unexpressed. We present a method based on low-rank matrix approximation which imputes these values while preserving biologically non-expressed genes (true biological zeros) at zero expression levels. We provide theoretical justification for this denoising approach and demonstrate its advantages relative to other methods on simulated and biological datasets.

Improved outcomes using laparoscopy for emergency colectomy after mitigating bias by negative control exposure analysis.

Background: Laparoscopy is superior to open surgery for elective colectomy, but its role in emergency colectomy remains unclear. Previous studies were small and limited by confounding because surgeons may have selected lower-risk patients for laparoscopy. We therefore studied the effect of attempting laparoscopy for emergency colectomies while adjusting for confounding using multiple techniques in a large, nationwide registry.

Increased mortality with resuscitative endovascular balloon occlusion of the aorta only mitigated by strong unmeasured confounding: An expanded analysis using the National Trauma Data Bank.

Background: Resuscitative endovascular balloon occlusion of the aorta (REBOA) is being increasingly adopted to manage noncompressible torso hemorrhage, but a recent analysis of the 2015 to 2016 Trauma Quality Improvement Project (TQIP) data set showed that placement of REBOA was associated with higher rates of death, lower extremity amputation, and acute kidney injury (AKI). We expand this analysis by including the 2017 data set, quantifying the potential role of residual confounding, and distinguishing between traumatic and ischemic lower extremity amputation.

Methods: This retrospective study used the 2015 to 2017 TQIP database and included patients older than 18 years, with signs of life on arrival, who had no aortic injury and were not transferred.

Dimensionality Reduction of Single-Cell RNA-Seq Data.

Dimensionality reduction is a crucial step in essentially every single-cell RNA-sequencing (scRNA-seq) analysis. In this chapter, we describe the typical dimensionality reduction workflow that is used for scRNA-seq datasets, specifically highlighting the roles of principal component analysis, t-distributed stochastic neighborhood embedding, and uniform manifold approximation and projection in this setting. We particularly emphasize efficient computation; the software implementations used in this chapter can scale to datasets with millions of cells.

Heavy-tailed kernels reveal a finer cluster structure in t-SNE visualisations.

T-distributed stochastic neighbour embedding (t-SNE) is a widely used data visualisation technique. It differs from its predecessor SNE by the low-dimensional similarity kernel: the Gaussian kernel was replaced by the heavy-tailed Cauchy kernel, solving the 'crowding problem' of SNE. Here, we develop an efficient implementation of t-SNE for a t-distribution kernel with an arbitrary degree of freedom , with → ∞ corresponding to SNE and = 1 corresponding to the standard t-SNE.

Randomized near-neighbor graphs, giant components and applications in data science.

If we pick random points uniformly in [0, 1] and connect each point to its log -nearest neighbors, where ≥ 2 is the dimension and is a constant depending on the dimension, then it is well known that the graph is connected with high probability. We prove that it suffices to connect every point to log log points chosen randomly among its log -nearest neighbors to ensure a giant component of size - () with high probability. This construction yields a much sparser random graph with ~ log log instead of ~ log edges that has comparable connectivity properties.

Protocol for project recovery after cardiac surgery: a single-center cohort study leveraging digital platform to characterise longitudinal patient-reported postoperative recovery patterns.

Introduction: Improving postoperative patient recovery after cardiac surgery is a priority, but our current understanding of individual variations in recovery and factors associated with poor recovery is limited. We are using a health-information exchange platform to collect patient-reported outcome measures (PROMs) and wearable device data to phenotype recovery patterns in the 30-day period after cardiac surgery hospital discharge, to identify factors associated with these phenotypes and to investigate phenotype associations with clinical outcomes.

Methods And Analysis: We designed a prospective cohort study to enrol 200 patients undergoing valve, coronary artery bypass graft or aortic surgery at a tertiary centre in the USA.

NUMERICAL INTEGRATION ON GRAPHS: WHERE TO SAMPLE AND HOW TO WEIGH.

Let = () be a finite, connected graph with weighted edges. We are interested in the problem of finding a subset ⊂ of vertices and weights such that for functions that are 'smooth' with respect to the geometry of the graph; here ~ indicates that we want the right-hand side to be as close to the left-hand side as possible. The main application are problems where is known to vary smoothly over the underlying graph but is expensive to evaluate on even a single vertex.

Single-cell connectomic analysis of adult mammalian lungs.

Efforts to decipher chronic lung disease and to reconstitute functional lung tissue through regenerative medicine have been hampered by an incomplete understanding of cell-cell interactions governing tissue homeostasis. Because the structure of mammalian lungs is highly conserved at the histologic level, we hypothesized that there are evolutionarily conserved homeostatic mechanisms that keep the fine architecture of the lung in balance. We have leveraged single-cell RNA sequencing techniques to identify conserved patterns of cell-cell cross-talk in adult mammalian lungs, analyzing mouse, rat, pig, and human pulmonary tissues.

The Proximal Humeral Ossification System Improves Assessment of Maturity in Patients with Scoliosis.

Background: We recently developed a classification system to assess skeletal maturity by scoring proximal humeral ossification in a similar way to the canonical Risser sign. The purpose of the present study was to determine whether our system can be used to reliably assess radiographs of the spine for modern patients with idiopathic scoliosis, whether it can be used in combination with the Sanders hand system, and whether the consideration of patient factors such as age, sex, and standing height improves the accuracy of predictions.

Methods: We retrospectively reviewed 414 randomized radiographs from 216 modern patients with scoliosis and measured reliability with use of the intraclass correlation coefficient (ICC).

Fast interpolation-based t-SNE for improved visualization of single-cell RNA-seq data.

t-distributed stochastic neighbor embedding (t-SNE) is widely used for visualizing single-cell RNA-sequencing (scRNA-seq) data, but it scales poorly to large datasets. We dramatically accelerate t-SNE, obviating the need for data downsampling, and hence allowing visualization of rare cell populations. Furthermore, we implement a heatmap-style visualization for scRNA-seq based on one-dimensional t-SNE for simultaneously visualizing the expression patterns of thousands of genes.

Association of Body Mass Index With Blood Pressure Among 1.7 Million Chinese Adults.

Importance: Body mass index (BMI) is positively associated with blood pressure (BP); this association has critical implications for countries like China, where hypertension is highly prevalent and obesity is increasing. A greater understanding of the association between BMI and BP is required to determine its effect and develop strategies to mitigate it.

Objective: To assess the heterogeneity in the association between BMI and BP across a wide variety of subgroups of the Chinese population.

Clustering with t-SNE, provably.

t-distributed Stochastic Neighborhood Embedding (t-SNE), a clustering and visualization method proposed by van der Maaten & Hinton in 2008, has rapidly become a standard tool in a number of natural sciences. Despite its overwhelming success, there is a distinct lack of mathematical foundations and the inner workings of the algorithm are not well understood. The purpose of this paper is to prove that t-SNE is able to recover well-separated clusters; more precisely, we prove that t-SNE in the 'early exaggeration' phase, an optimization technique proposed by van der Maaten & Hinton (2008) and van der Maaten (2014), can be rigorously analyzed.

Single-Cell Analysis Reveals a Hair Follicle Dermal Niche Molecular Differentiation Trajectory that Begins Prior to Morphogenesis.

Delineating molecular and cellular events that precede appendage morphogenesis has been challenging due to the inability to distinguish quantitative molecular differences between cells that lack histological distinction. The hair follicle (HF) dermal condensate (DC) is a cluster of cells critical for HF development and regeneration. Events that presage emergence of this distinctive population are poorly understood.

Prevalence, awareness, treatment, and control of hypertension in China: data from 1·7 million adults in a population-based screening study (China PEACE Million Persons Project).

Background: Hypertension is common in China and its prevalence is rising, yet it remains inadequately controlled. Few studies have the capacity to characterise the epidemiology and management of hypertension across many heterogeneous subgroups. We did a study of the prevalence, awareness, treatment, and control of hypertension in China and assessed their variations across many subpopulations.

Algorithm 971: An Implementation of a Randomized Algorithm for Principal Component Analysis.

Recent years have witnessed intense development of randomized methods for low-rank approximation. These methods target principal component analysis and the calculation of truncated singular value decompositions. The present article presents an essentially black-box, foolproof implementation for Mathworks' MATLAB, a popular software platform for numerical computation.

3-D Stent Detection in Intravascular OCT Using a Bayesian Network and Graph Search.

Worldwide, many hundreds of thousands of stents are implanted each year to revascularize occlusions in coronary arteries. Intravascular optical coherence tomography is an important emerging imaging technique, which has the resolution and contrast necessary to quantitatively analyze stent deployment and tissue coverage following stent implantation. Automation is needed, as current, it takes up to 16 h to manually analyze hundreds of images and thousands of stent struts from a single pullback.

MAGNET: MicroArray Gene expression and Network Evaluation Toolkit.

MicroArray Gene expression and Network Evaluation Toolkit (MAGNET) is a web-based application that provides tools to generate and score both protein-protein interaction networks and coexpression networks. MAGNET integrates user-provided experimental measurements with high-throughput proteomic datasets, generating weighted gene-gene and protein-protein interaction networks. MAGNET allows users to weight edges of protein-protein interaction networks using a logistic regression model integrating tissue-specific gene expression data, sub-cellular localization data, co-clustering of interacting proteins and the number of observations of the interaction.

BiC: a web server for calculating bimodality of coexpression between gene and protein networks.

Unlabelled: Bimodal patterns of expression have recently been shown to be useful not only in prioritizing genes that distinguish phenotypes, but also in prioritizing network models that correlate with proteomic evidence. In particular, subgroups of strongly coexpressed gene pairs result in an increased variance of the correlation distribution. This variance, a measure of association between sets of genes (or proteins), can be summarized as the bimodality of coexpression (BiC).