A Comparison of Anaerobic Power Tests using Cycle Ergometry and Non-motorized Treadmill Ergometry at Optimized Loads

International Journal of Exercise Science 16(4): 1293-1305, 2023. The purpose of this study was to compare performance markers derived from a 30-second maximal bout on a cycle ergometer (CE) and non-motorized treadmill (NMT) under optimized loads. Recreationally active participants (n = 40) volunteered for the study. Force-velocity tests on the CE and NMT were used to determine optimal resistance for peak power (PP) production. The remaining visits were randomized and counterbalanced, with a single 30-second maximal test on CE or NMT to assess PP, mean power (MP), fatigue index (FI), over the course of the 30-second test, and maximum heart rate (HRmax) and blood lactate (BLa-) taken 1-minute post. Results were that PP and MP were higher (P\u3c0.05) on CE compared to NMT for both sexes. FI did not differ among males (P=0.201) whereas females showed higher FI (P=0.002) on the CE. HRmax and BLa- were higher (P\u3c0.05) after NMT for both sexes. There was no difference for optimal braking force on NMT between males (16.65±4.49%BW) and females (14.30±3.10%BW) (P=0.061). CE optimal torque factor was higher for males (0.78±0.16 Nm/kg) compared to females (0.62±0.14 Nm/kg) (P=0.001). Overall, CE produced higher power output using optimized loads in recreationally active males and females, while NMT test resulted in a higher HRmax andBLa- concentration. These tests for anaerobic power, when performed with optimized loads, produced different results for several variables, therefore these modalities should not be considered interchangeable. Practitioners should consider which modality best mimics the activities of the person being tested when selecting a protocol

Neuronal SIRT3 Deletion Predisposes to Female-Specific Alterations in Cellular Metabolism, Memory, and Network Excitability

Mitochondrial dysfunction is an early event in the pathogenesis of neurologic disorders and aging. Sirtuin 3 (SIRT3) regulates mitochondrial function in response to the cellular environment through the reversible deacetylation of proteins involved in metabolism and reactive oxygen species detoxification. As the primary mitochondrial deacetylase, germline, or peripheral tissue-specific deletion of SIRT3 produces mitochondrial hyperacetylation and the accelerated development of age-related diseases. Given the unique metabolic demands of neurons, the role of SIRT3 in the brain is only beginning to emerge. Using mass spectrometry-based acetylomics, high-resolution respirometry, video-EEG, and cognition testing, we report targeted deletion of SIRT3 from select neurons in the cortex and hippocampus produces altered neuronal excitability and metabolic dysfunction in female mice. Targeted deletion of SIRT3 from neuronal helix-loop-helix 1 (NEX)-expressing neurons resulted in mitochondrial hyperacetylation, female-specific superoxide dismutase-2 (SOD2) modification, increased steady-state superoxide levels, metabolic reprogramming, altered neuronal excitability, and working spatial memory deficits. Inducible neuronal deletion of SIRT3 likewise produced female-specific deficits in spatial working memory. Together, the data demonstrate that deletion of SIRT3 from forebrain neurons selectively predisposes female mice to deficits in mitochondrial and cognitive function. SIGNIFICANCE STATEMENT Mitochondrial SIRT3 is an enzyme shown to regulate energy metabolism and antioxidant function, by direct deacetylation of proteins. In this study, we show that neuronal SIRT3 deficiency renders female mice selectively vulnerable to impairment in redox and metabolic function, spatial memory, and neuronal excitability. The observed sex-specific effects on cognition and neuronal excitability in female SIRT3-deficient mice suggest that mitochondrial dysfunction may be one factor underlying comorbid neuronal diseases, such as Alzheimer\u27s disease and epilepsy. Furthermore, the data suggest that SIRT3 dysfunction may predispose females to age-related metabolic and cognitive impairment

Alterations in the human lung proteome with lipopolysaccharide

<p>Abstract</p> <p>Background</p> <p>Recombinant human activated protein C (rhAPC) is associated with improved survival in high-risk patients with severe sepsis; however, the effects of both lipopolysaccharide (LPS) and rhAPC on the bronchoalveolar lavage fluid (BALF) proteome are unknown.</p> <p>Methods</p> <p>Using differential in gel electrophoresis (DIGE) we identified changes in the BALF proteome from 10 healthy volunteers given intrapulmonary LPS in one lobe and saline in another lobe. Subjects were randomized to pretreatment with saline or rhAPC.</p> <p>Results</p> <p>An average of 255 protein spots were detected in each proteome. We found 31 spots corresponding to 8 proteins that displayed abundance increased or decreased at least 2-fold after LPS. Proteins that decreased after LPS included surfactant protein A, immunoglobulin J chain, fibrinogen-γ, α₁-antitrypsin, immunoglobulin, and α₂-HS-glycoprotein. Haptoglobin increased after LPS-treatment. Treatment with rhAPC was associated with a larger relative decrease in immunoglobulin J chain, fibrinogen-γ, α₁-antitrypsin, and α₂-HS-glycoprotein.</p> <p>Conclusion</p> <p>Intrapulmonary LPS was associated with specific protein changes suggesting that the lung response to LPS is more than just a loss of integrity in the alveolar epithelial barrier; however, pretreatment with rhAPC resulted in minor changes in relative BALF protein abundance consistent with its lack of affect in ALI and milder forms of sepsis.</p

Lung Microbiota and Metabolites Collectively Associate with Clinical Outcomes in Milder Stage Chronic Obstructive Pulmonary Disease.

Rationale: Chronic obstructive pulmonary disease (COPD) is variable in its development. Lung microbiota and metabolites collectively may impact COPD pathophysiology, but relationships to clinical outcomes in milder disease are unclear. Objectives: Identify components of the lung microbiome and metabolome collectively associated with clinical markers in milder stage COPD. Methods: We analyzed paired microbiome and metabolomic data previously characterized from bronchoalveolar lavage fluid in 137 participants in the SPIROMICS (Subpopulations and Intermediate Outcome Measures in COPD Study), or (GOLD [Global Initiative for Chronic Obstructive Lung Disease Stage 0-2). Datasets used included 1) bacterial 16S rRNA gene sequencing; 2) untargeted metabolomics of the hydrophobic fraction, largely comprising lipids; and 3) targeted metabolomics for a panel of hydrophilic compounds previously implicated in mucoinflammation. We applied an integrative approach to select features and model 14 individual clinical variables representative of known associations with COPD trajectory (lung function, symptoms, and exacerbations). Measurements and Main Results: The majority of clinical measures associated with the lung microbiome and metabolome collectively in overall models (classification accuracies, &gt;50%, P &lt; 0.05 vs. chance). Lower lung function, COPD diagnosis, and greater symptoms associated positively with Streptococcus, Neisseria, and Veillonella, together with compounds from several classes (glycosphingolipids, glycerophospholipids, polyamines and xanthine, an adenosine metabolite). In contrast, several Prevotella members, together with adenosine, 5-methylthioadenosine, sialic acid, tyrosine, and glutathione, associated with better lung function, absence of COPD, or less symptoms. Significant correlations were observed between specific metabolites and bacteria (Padj &lt; 0.05). Conclusions: Components of the lung microbiome and metabolome in combination relate to outcome measures in milder COPD, highlighting their potential collaborative roles in disease pathogenesis

B cell activity is impaired in human and mouse obesity and is responsive to an essential fatty acid upon murine influenza infection

Obesity is associated with increased risk for infections and poor responses to vaccinations, which may be due to compromised B cell function. However, there is limited information about the influence of obesity on B cell function and underlying factors that modulate B cell responses. Therefore, we studied B cell cytokine secretion and/or Ab production across obesity models. In obese humans, B cell IL-6 secretion was lowered and IgM levels were elevated upon ex vivo anti-BCR/TLR9 stimulation. In murine obesity induced by a high fat diet, ex vivo IgM and IgG were elevated with unstimulated B cells. Furthermore, the high fat diet lowered bone marrow B cell frequency accompanied by diminished transcripts of early lymphoid commitment markers. Murine B cell responses were subsequently investigated upon influenza A/Puerto Rico/8/34 infection using a Western diet model in the absence or presence of docosahexaenoic acid (DHA). DHA, an essential fatty acid with immunomodulatory properties, was tested because its plasma levels are lowered in obesity. Relative to controls, mice consuming theWestern diet had diminished Ab titers whereas theWestern diet plus DHA improved titers. Mechanistically, DHA did not directly target B cells to elevate Ab levels. Instead, DHA increased the concentration of the downstream specialized proresolving lipid mediators (SPMs) 14-hydroxydocosahexaenoic acid, 17-hydroxydocosahexaenoic acid, and protectin DX. All three SPMs were found to be effective in elevating murine Ab levels upon influenza infection. Collectively, the results demonstrate that B cell responses are impaired across human and mouse obesity models and show that essential fatty acid status is a factor influencing humoral immunity, potentially through an SPM-mediated mechanism

Perspective:Dietary Biomarkers of Intake and Exposure - Exploration with Omics Approaches

While conventional nutrition research has yielded biomarkers such as doubly labeled water for energy metabolism and 24-h urinary nitrogen for protein intake, a critical need exists for additional, equally robust biomarkers that allow for objective assessment of specific food intake and dietary exposure. Recent advances in high-throughput MS combined with improved metabolomics techniques and bioinformatic tools provide new opportunities for dietary biomarker development. In September 2018, the NIH organized a 2-d workshop to engage nutrition and omics researchers and explore the potential of multiomics approaches in nutritional biomarker research. The current Perspective summarizes key gaps and challenges identified, as well as the recommendations from the workshop that could serve as a guide for scientists interested in dietary biomarkers research. Topics addressed included study designs for biomarker development, analytical and bioinformatic considerations, and integration of dietary biomarkers with other omics techniques. Several clear needs were identified, including larger controlled feeding studies, testing a variety of foods and dietary patterns across diverse populations, improved reporting standards to support study replication, more chemical standards covering a broader range of food constituents and human metabolites, standardized approaches for biomarker validation, comprehensive and accessible food composition databases, a common ontology for dietary biomarker literature, and methodologic work on statistical procedures for intake biomarker discovery. Multidisciplinary research teams with appropriate expertise are critical to moving forward the field of dietary biomarkers and producing robust, reproducible biomarkers that can be used in public health and clinical research

Current practices in lc-ms untargeted metabolomics: a scoping review on the use of pooled quality control samples

Untargeted metabolomics is an analytical approach with numerous applications serving as an effective metabolic phenotyping platform to characterize small molecules within a biological system. Data quality can be challenging to evaluate and demonstrate in metabolomics experiments. This has driven the use of pooled quality control (QC) samples for monitoring and, if necessary, correcting for analytical variance introduced during sample preparation and data acquisition stages. Described herein is a scoping literature review detailing the use of pooled QC samples in published untargeted liquid chromatography-mass spectrometry (LC-MS) based metabolomics studies. A literature query was performed, the list of papers was filtered, and suitable articles were randomly sampled. In total, 109 papers were each reviewed by at least five reviewers, answering predefined questions surrounding the use of pooled quality control samples. The results of the review indicate that use of pooled QC samples has been relatively widely adopted by the metabolomics community and that it is used at a similar frequency across biological taxa and sample types in both small- and large-scale studies. However, while many studies generated and analyzed pooled QC samples, relatively few reported the use of pooled QC samples to improve data quality. This demonstrates a clear opportunity for the field to more frequently utilize pooled QC samples for quality reporting, feature filtering, analytical drift correction, and metabolite annotation. Additionally, our survey approach enabled us to assess the ambiguity in the reporting of the methods used to describe the generation and use of pooled QC samples. This analysis indicates that many details of the QC framework are missing or unclear, limiting the reader's ability to determine which QC steps have been taken. Collectively, these results capture the current state of pooled QC sample usage and highlight existing strengths and deficiencies as they are applied in untargeted LC-MS metabolomics

Trade-Off between Toxicity and Signal Detection Orchestrated by Frequency- and Density-Dependent Genes

Behaviors in insects are partly highly efficient Bayesian processes that fulfill exploratory tasks ending with the colonization of new ecological niches. The foraging (for) gene in Drosophila encodes a cGMP-dependent protein kinase (PKG). It has been extensively described as a frequency-dependent gene and its transcripts are differentially expressed between individuals, reflecting the population density context. Some for transcripts, when expressed in a population at high density for many generations, concomitantly trigger strong dispersive behavior associated with foraging activity. Moreover, genotype-by-environment interaction (GEI) analysis has highlighted a dormant role of for in energetic metabolism in a food deprivation context. In our current report, we show that alleles of for encoding different cGMP-dependent kinase isoforms influence the oxidation of aldehyde groups of aromatic molecules emitted by plants via Aldh-III and a phosphorylatable adaptor. The enhanced efficiency of oxidation of aldehyde odorants into carboxyl groups by the action of for lessens their action and toxicity, which should facilitate exploration and guidance in a complex odor environment. Our present data provide evidence that optimal foraging performance requires the fast metabolism of volatile compounds emitted by plants to avoid neurosensory saturation and that the frequency-dependent genes that trigger dispersion influence these processes

Perspective: Dietary Biomarkers of Intake and Exposure - Exploration with Omics Approaches

While conventional nutrition research has yielded biomarkers such as doubly labeled water for energy metabolism and 24-h urinary nitrogen for protein intake, a critical need exists for additional, equally robust biomarkers that allow for objective assessment of specific food intake and dietary exposure. Recent advances in high-throughput MS combined with improved metabolomics techniques and bioinformatic tools provide new opportunities for dietary biomarker development. In September 2018, the NIH organized a 2-d workshop to engage nutrition and omics researchers and explore the potential of multiomics approaches in nutritional biomarker research. The current Perspective summarizes key gaps and challenges identified, as well as the recommendations from the workshop that could serve as a guide for scientists interested in dietary biomarkers research. Topics addressed included study designs for biomarker development, analytical and bioinformatic considerations, and integration of dietary biomarkers with other omics techniques. Several clear needs were identified, including larger controlled feeding studies, testing a variety of foods and dietary patterns across diverse populations, improved reporting standards to support study replication, more chemical standards covering a broader range of food constituents and human metabolites, standardized approaches for biomarker validation, comprehensive and accessible food composition databases, a common ontology for dietary biomarker literature, and methodologic work on statistical procedures for intake biomarker discovery. Multidisciplinary research teams with appropriate expertise are critical to moving forward the field of dietary biomarkers and producing robust, reproducible biomarkers that can be used in public health and clinical research