A computational framework to emulate the human perspective in flow cytometric data analysis

Background: In recent years, intense research efforts have focused on developing methods for automated flow cytometric data analysis. However, while designing such applications, little or no attention has been paid to the human perspective that is absolutely central to the manual gating process of identifying and characterizing cell populations. In particular, the assumption of many common techniques that cell populations could be modeled reliably with pre-specified distributions may not hold true in real-life samples, which can have populations of arbitrary shapes and considerable inter-sample variation. <p/>Results: To address this, we developed a new framework flowScape for emulating certain key aspects of the human perspective in analyzing flow data, which we implemented in multiple steps. First, flowScape begins with creating a mathematically rigorous map of the high-dimensional flow data landscape based on dense and sparse regions defined by relative concentrations of events around modes. In the second step, these modal clusters are connected with a global hierarchical structure. This representation allows flowScape to perform ridgeline analysis for both traversing the landscape and isolating cell populations at different levels of resolution. Finally, we extended manual gating with a new capacity for constructing templates that can identify target populations in terms of their relative parameters, as opposed to the more commonly used absolute or physical parameters. This allows flowScape to apply such templates in batch mode for detecting the corresponding populations in a flexible, sample-specific manner. We also demonstrated different applications of our framework to flow data analysis and show its superiority over other analytical methods. <p/>Conclusions: The human perspective, built on top of intuition and experience, is a very important component of flow cytometric data analysis. By emulating some of its approaches and extending these with automation and rigor, flowScape provides a flexible and robust framework for computational cytomics

Cocoa-flavanols enhance moderate-intensity pulmonary [Formula: see text] kinetics but not exercise tolerance in sedentary middle-aged adults.

INTRODUCTION: Cocoa flavanols (CF) may exert health benefits through their potent vasodilatory effects, which are perpetuated by elevations in nitric oxide (NO) bioavailability. These vasodilatory effects may contribute to improved delivery of blood and oxygen (O2) to exercising muscle. PURPOSE: Therefore, the objective of this study was to examine how CF supplementation impacts pulmonary O2 uptake ([Formula: see text]) kinetics and exercise tolerance in sedentary middle-aged adults. METHODS: We employed a double-blind cross-over, placebo-controlled design whereby 17 participants (11 male, 6 female; mean ± SD, 45 ± 6 years) randomly received either 7 days of daily CF (400 mg) or placebo (PL) supplementation. On day 7, participants completed a series of 'step' moderate- and severe-intensity exercise tests for the determination of [Formula: see text] kinetics. RESULTS: During moderate-intensity exercise, the time constant of the phase II [Formula: see text] kinetics ([Formula: see text]) was decreased by 15% in CF as compared to PL (mean ± SD; PL 40 ± 12 s vs. CF 34 ± 9 s, P = 0.019), with no differences in the amplitude of [Formula: see text] (A[Formula: see text]; PL 0.77 ± 0.32 l min-1 vs. CF 0.79 ± 0.34 l min-1, P = 0.263). However, during severe-intensity exercise, [Formula: see text], the amplitude of the slow component ([Formula: see text]) and exercise tolerance (PL 435 ± 58 s vs. CF 424 ± 47 s, P = 0.480) were unchanged between conditions. CONCLUSION: Our data show that acute CF supplementation enhanced [Formula: see text] kinetics during moderate-, but not severe-intensity exercise in middle-aged participants. These novel effects of CFs, in this demographic, may contribute to improved tolerance of moderate-activity physical activities, which appear commonly present in daily life. TRIAL REGISTRATION: Registered under ClinicalTrials.gov Identifier no. NCT04370353, 30/04/20 retrospectively registered