Graphical abstract

Craig JC, Broxterman RM, Wilcox SL, Chen C, Barstow TJ. Effect of adipose tissue thickness, muscle site, and sex on near-infrared spectroscopy derived total-[hemoglobin + myoglobin]. J Appl Physiol 123: 1571-1578, 2017. First published September 21, 2017; doi: 10.1152/japplphysiol.00207.2017 .-Adipose tissue thickness (ATT) attenuates signals from near-infrared spectroscopy (NIRS) and diminishes the absolute quantification of underlying tissues by contemporary NIRS devices. Based on the relationship between NIRS-derived total-[hemoglobin + myoglobin] (total-[Hb + Mb]) and ATT, we tested the hypotheses that the correction factor for ATT 1) is muscle site specific; 2) does not differ between men and women; and that 3) exclusion of the shortest source-detector distance from data analysis increases total-[Hb + Mb]. Fourteen healthy subjects (7 men) rested in a neutral body position (supine or prone) while measurements of total-[Hb + Mb] and ATT were taken at four muscles common to resting and exercise studies: vastus lateralis (VL), rectus femoris (RF), gastrocnemius (GS), and flexor digitorum superficialis (FDS). ATT averaged 6.0 ± 0.4 mm across all muscles. Every muscle showed a negative slope ( r: 0.6-0.94; P < 0.01) for total-[Hb + Mb] as a function of ATT: VL (-34 μM/mm), RF (-26 μM/mm), GS (-54 μM/mm), and FDS (-33 μM/mm). The projected total-[Hb + Mb] at 0 mm ATT ( y-intercept) was 452, 372, 620, and 456 μM for VL, RF, GS, and FDS, respectively. No differences were found between the sexes within VL, RF, or FDS, but men had a greater projected total-[Hb + Mb] at 0 mm for GS (688 ± 44 vs. 552 ± 40 μM; P < 0.05). Exclusion of the shortest source-detector distance increased total-[Hb + Mb] by 12 ± 1 μM ( P < 0.05). The present findings demonstrate that total-[Hb + Mb] should be corrected for ATT using muscle site-specific factors which are not sex specific, except in the case of GS. NEW & NOTEWORTHY Near-infrared spectroscopy (NIRS) is an important tool for physiologists and clinicians. However, adipose tissue greatly attenuates the signals from these devices. Correcting for this attenuation has been suggested based on the strength of the relationship between NIRS-derived measurements and the adipose tissue thickness. We show that this relationship is unique to the muscle site of interest but may not be sex specific. Accurate quantification of underlying tissue mandates researchers correct for adipose tissue thickness.

The hallmarks of pediatric acute respiratory failure (ARF) are dysregulated inflammation and surfactant dysfunction. The objective is to study association of surfactant protein (SP) genes’ single nucleotide polymorphisms (SNPs) with ARF and its morbidity: pulmonary dysfunction at discharge (PDAD), employing a single-, two-, and three-SNP interaction model. We enrolled 468 newborn controls and 248 children aged ≤ 24 months with ARF; 86 developed PDAD. Using quantitative genetic principles, we tested the association of SP genes SNPs with ARF and PDAD. We observed a dominant effect of rs4715 of the SFTPC on ARF risk. In a three-SNP model, we found (a) 34 significant interactions among SNPs of SFTPA1, SFTPA2, and SFTPC associated with ARF (p = 0.000000002–0.05); 15 and 19 of those interactions were associated with increased and decreased risk for ARF, respectively; (b) intergenic SNP–SNP interactions of both hydrophobic and hydrophilic SP genes associated with PDAD (p = 0.00002–0.03). The majority of intra- and intergenic interactions associated with ARF involve the SFTPA2 SNPs, whereas most of the intra- and intergenic interactions associated with PDAD are of SFTPA1 SNPs. We also observed a dominant effect of haplotypes GG of SFTPA1 associated with increased and AA of SFTPC associated with decreased ARF risk (p = 0.02). To the best of our knowledge, this is the first study showing an association of complex interactions of SP genes with ARF and PDAD. Our data indicate that SP genes polymorphisms may contribute to ARF pathogenesis and subsequent PDAD and/or may serve as markers for disease susceptibility in healthy children.

Gene regulatory networks (GRNs) have been widely used as a fundamental tool to reveal the genomic mechanisms that underlie the individual’s response to environmental and developmental cues. Standard approaches infer GRNs as holistic graphs of gene co-expression, but such graphs cannot quantify how gene–gene interactions vary among individuals and how they alter structurally across spatiotemporal gradients. Here, we develop a general framework for inferring informative, dynamic, omnidirectional, and personalized networks (idopNetworks) from routine transcriptional experiments. This framework is constructed by a system of quasi-dynamic ordinary differential equations (qdODEs) derived from the combination of ecological and evolutionary theories. We reconstruct idopNetworks using genomic data from a surgical experiment and illustrate how network structure is associated with surgical response to infrainguinal vein bypass grafting and the outcome of grafting. idopNetworks may shed light on genotype–phenotype relationships and provide valuable information for personalized medicine.