Cough Diagnosis: Present and Future

Chronic cough is a common symptom of numerous diseases occurring in about 10% of general population. The number of cough impulses over a period of time is an objective marker of cough severity. Cough frequency is now considered the primary endpoint in studies of the effectiveness of cough suppressants, as a factor contributing to the spread of tuberculosis, and as one of the indicators of patient stabilization during exacerbations of chronic obstructive pulmonary disease. The review discusses data from 60 literature sources on the principles of automatic cough impulses counting, methods used for objective cough assessment, and forecasts for future development in this field.

Comparison between methods for measuring fecal egg count and estimating genetic parameters for gastrointestinal parasite resistance traits in sheep

Fecal egg count (FEC) is an indicative measurement for parasite infection in sheep. Different FEC methods may show inconsistent results. Not accounting for inconsistencies can be problematic when integrating measurements from different FEC methods for genetic evaluation. The objectives of this study were to evaluate the difference in means and variances between two fecal egg counting methods used in sheep, the Modified McMaster (LMMR) and the Triple Chamber McMaster (LTCM); to estimate variance components for the two FEC methods, treating them as two different traits; and to integrate FEC data from the two different methods and estimate genetic parameters for FEC and other gastrointestinal parasite resistance traits. Fecal samples were collected from a commercial Rideau-Arcott sheep farm in Ontario. Fecal egg counting was performed using both Modified McMaster and the Triple Chamber McMaster methods. Other parasite resistance trait records were collected from the same farm including eye score (FAMACHA ©), body condition score (BCS), and body weight (WT). The two FEC methods were highly genetically (0.94) and phenotypically (0.88) correlated. However, the mean and variance between the two FEC methods were significantly different (P < 0.0001). Therefore, re-scaling is required prior to integrating data from the different methods. For the multiple trait analysis, data from the two fecal egg counting methods were integrated (LFEC) by using records for the LMMR when available and replacing missing records with re-standardized LTCM records converted to the same mean and variance of LMMR. Heritability estimates were 0.12 ± 0.04, 0.07 ± 0.05 , 0.17 ± 0.06, and 0.24 ± 0.07 for LFEC egg count, FAMACHA ©, BCS, and WT, respectively. The estimated genetic correlations between fecal egg count and the other parasite resistance traits were low and not significant (P>0.05) for FAMACHA © (r= 0.24 ± 0.32) and WT (r= 0.22 ± 0.19), and essentially zero for BCS (r= -0.03 ± 0.25), suggesting little to no benefit of using such traits as indicators for LFEC.

A new look at old numbers, and what it reveals about numeration

In this study, the archaic counting systems of Mesopotamia as understood through the Neolithic tokens, numerical impressions, and proto-cuneiform notations were compared to the traditional number-words and counting methods of Polynesia as understood through contemporary and historical descriptions of vocabulary and behaviors. The comparison and associated analyses capitalized on the ability to understand well-known characteristics of Uruk-period numbers like object-specific counting, polyvalence, and context-dependence through historical observations of Polynesian counting methods and numerical language, evidence unavailable for ancient numbers. Similarities between the two number systems were then used to argue that archaic Mesopotamian numbers, like those of Polynesia, were highly elaborated and would have served as cognitively efficient tools for mental calculation. Their differences also show the importance of material technologies like tokens, impressions, and notations to developing mathematics.

Classic genome-wide association methods are unlikely to identify causal variants in strongly clonal microbial populations.

Since the advent of genome-wide association studies (GWAS) in human genomes, an increasing sophistication of methods has been developed for more robust association detection. Currently, the backbone of human GWAS approaches is allele-counting-based methods where the signal of association is derived from alleles that are identical-by-state. Borrowing this approach from human GWAS, allele-counting-based methods have been popularized in microbial GWAS, notably the generalized linear model using either dimension reduction for fixed covariates and/or a genetic relationship matrix as a random effect in a mixed model to control for population stratification. In this work, we show how the effects of linkage disequilibrium (LD) can potentially obscure true-positive genotype-phenotype associations (i.e., genetic variants causally associated with the phenotype of interest) and also lead to unacceptably high rates of false-positive associations when applying these classical approaches to GWAS in weakly recombining microbial genomes. We developed a GWAS method called POUTINE (https://github.com/Peter-Two-Point-O/POUTINE), which relies on homoplastic mutation to both clarify the source of putative causal variants and reduce likely false-positive associations compared to traditional allele counting methods. Using datasets of M. tuberculosis genomes and antibiotic-resistance phenotypes, we show that LD can in fact render all association signals from allele counting methods to be fully indistinguishable from hundreds to thousands of sites scattered across an entire genome. These classic GWAS methods thus fail to pinpoint likely causal genotype-phenotype associations and separate them from background noise, even after applying methods to correct for population structure. We therefore urge caution when utilizing classical approaches, particularly in populations that are strongly clonal.

Counting methods introduced into the bibliometric research literature 1970 – 2018: A review

This review investigates 1) the number of unique counting methods, 2) to what extent counting methods can be categorized according to selected characteristics, 3) methods and elements to assess the internal validity of counting methods, and 4) to what extent and with which characteristics counting methods are used in research evaluations. The review identifies 32 counting methods introduced 1981 – 2018. Two frameworks categorize these counting methods. Framework 1 describes selected mathematical properties, and Framework 2 describes arguments for choosing a counting method. Twenty of the 32 counting methods are rank-dependent, fractionalized, and introduced to measure contribution, participation, etc. of an object of study. Next, three criteria for internal validity are used to identify five methods that test the adequacy, two elements that test the sensitivity, and three elements that test the homogeneity of counting methods. Finally, a literature search finds that only three of the 32 counting methods are used by four research evaluations or more. Two counting methods are used with the same characteristics as defined in the studies that introduced the counting methods. The review provides a detailed foundation for working with counting methods, and many of the findings provide bases for future investigations of counting methods. Peer Review https://publons.com/publon/10.1162/qss_a_00141

New insights into the standard method of assessing bacterial filtration efficiency of medical face masks

Based on the current knowledge of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) transmission, wearing a mask has been recommended during the COVID-19 pandemic. Bacterial filtration efficiency (BFE) measurements enable designing and regulating medical masks to prevent bioaerosol dissemination; however, despite the simplicity of these measurements, several scientific questions remain unanswered regarding BFE tests. Here, we investigated (1) the impact of substituting 100-mm Petri dishes with 90-mm disposable Petri dishes, (2) the impact of colony-counting methods on the bioaerosol aerodynamic size, and (3) the impact of colony-counting methods on the total viable particle counts. We demonstrated that disposable 90-mm Petri dishes can be used to replace the 100-mm dishes. We also showed that an automatic high-resolution colony counter can be used to directly count viable particles on collection substrates and to measure the bioaerosol size parameters. Our results enable possible modernization of the outdated testing methods recommended in the US and European standards for BFE measurements. Specifically, use of a modernized colony counter should be clearly regulated and permitted to avoid the counting of positive holes. The median aerodynamic diameter appears to be the most relevant parameter for characterizing bioaerosol size.