Human Performance Assessments in Cadet Populations

This study assessed potential physiological differences between the Ranger Challenge (RC) Competition team and junior year cadets in an Army Reserve Officer Training Corps (ROTC) program. The method included: RC (m = 11, f = 2) and junior year cadets (m = 7, f = 3) were assessed in the following areas: 1) quickness and agility (5-10-5 shuttle run), 2) total-body power (standing broad jump), and 3) grip strength (hand grip dynamometry) assessed. The 5-10-5 shuttle run was performed twice (opening once to the left and once to the right). The standing broad jump required that cadets stand with their toes behind a line, perform a maximum of three preparatory movements, triple extend their knees, hips, and ankles while using their upper body to propel them as far forward as possible. After the jump the distanced reached was measured from the line to the heel of the nearest foot. Hand grip dynamometry was performed once on each hand. The cadet held the dynamometer out to his or her side and squeezed it as they lowered it to their hip. The results were that there were no significant differences between groups for the 5-10-5 shuttle run (p = 0.91), standing broad jump (p = 0.49), or grip strength (p = 0.31). RC did not outperform

Interleukin-6, age, and corpus callosum integrity.

The contribution of inflammation to deleterious aging outcomes is increasingly recognized; however, little is known about the complex relationship between interleukin-6 (IL-6) and brain structure, or how this association might change with increasing age. We examined the association between IL-6, white matter integrity, and cognition in 151 community dwelling older adults, and tested whether age moderated these associations. Blood levels of IL-6 and vascular risk (e.g., homocysteine), as well as health history information, were collected. Processing speed assessments were administered to assess cognitive functioning, and we employed tract-based spatial statistics to examine whole brain white matter and regions of interest. Given the association between inflammation, vascular risk, and corpus callosum (CC) integrity, fractional anisotropy (FA) of the genu, body, and splenium represented our primary dependent variables. Whole brain analysis revealed an inverse association between IL-6 and CC fractional anisotropy. Subsequent ROI linear regression and ridge regression analyses indicated that the magnitude of this effect increased with age; thus, older individuals with higher IL-6 levels displayed lower white matter integrity. Finally, higher IL-6 levels were related to worse processing speed; this association was moderated by age, and was not fully accounted for by CC volume. This study highlights that at older ages, the association between higher IL-6 levels and lower white matter integrity is more pronounced; furthermore, it underscores the important, albeit burgeoning role of inflammatory processes in cognitive aging trajectories

An Exploration of Trust in Community Leadership Contexts

This qualitative exploratory study of effective community engagement process examines community leader’s perceptions of their experiences and the role fostering and building trust plays in producing sustainable change in a Midwestern regional context. The purpose of this study was to explore how trust interacts with asset-based thinking and social learning experiences, including trauma-informed awareness, meaning-making, and empathy, to support community engagement efforts. The research team interviewed 26 individuals who were selected via purposive sampling. Study participants were active in their communities and practitioners in their respective professions. The study identified five overarching themes that emerged from participant interviews, including themes related to community leadership and engagement; community leaders fostering trust by extending trust; the influences of trauma, meaning-making, and empathy; and the use of social learning experiences to build trust and enhance shared vision; and innovative strategies to foster community engagement. Community leaders demonstrated numerous forms of caregiving behavior and cultivated an empathetic approach to humanity. Similar to Barnes & Schmitz (2016), we conclude that effective community engagement is a profoundly transformational process that incorporates a bottom-up approach instead of a top-down approach. Our community engagement model shows a continual cycle of learning through trauma-informed practice, meaning-making, and the cultivation of empathy. When community leaders apply this learning to asset-based approaches, social behavioral change can be facilitated within community contexts. Our research suggests that each community member can be empowered with a voice, a voice that builds trust, a voice that is strengthened through community engagement

Large-scale polymorphism discovery in macaque G-protein coupled receptors

Background: G-protein coupled receptors (GPCRs) play an inordinately large role in human health. Variation in the genes that encode these receptors is associated with numerous disorders across the entire spectrum of disease. GPCRs also represent the single largest class of drug targets and associated pharmacogenetic effects are modulated, in part, by polymorphisms. Recently, non-human primate models have been developed focusing on naturally-occurring, functionally-parallel polymorphisms in candidate genes. This work aims to extend those studies broadly across the roughly 377 non-olfactory GPCRs. Initial efforts include resequencing 44 Indian-origin rhesus macaques (Macaca mulatta), 20 Chinese-origin rhesus macaques, and 32 cynomolgus macaques (M. fascicularis). Results: Using the Agilent target enrichment system, capture baits were designed for GPCRs off the human and rhesus exonic sequence. Using next generation sequencing technologies, nearly 25,000 SNPs were identified in coding sequences including over 14,000 non-synonymous and more than 9,500 synonymous protein-coding SNPs. As expected, regions showing the least evolutionary constraint show greater rates of polymorphism and greater numbers of higher frequency polymorphisms. While the vast majority of these SNPs are singletons, roughly 1,750 non-synonymous and 2,900 synonymous SNPs were found in multiple individuals. Conclusions: In all three populations, polymorphism and divergence is highly concentrated in N-terminal and C-terminal domains and the third intracellular loop region of GPCRs, regions critical to ligand-binding and signaling. SNP frequencies in macaques follow a similar pattern of divergence from humans and new polymorphisms in primates have been identified that may parallel those seen in humans, helping to establish better non-human primate models of disease

Extracellular Vesticles in Acute Respiratory Distress Syndrome: Understanding Protective and Harmful Signaling for the Development of New Therapeutics

Acute respiratory distress syndrome (ARDS) is a severe respiratory condition characterized by increased lung permeability, hyper-inflammatory state, and fluid leak into the alveolar spaces. ARDS is a heterogeneous disease, with multiple direct and indirect causes that result in a mortality of up to 40%. Due to the ongoing Covid-19 pandemic, its incidence has increased up to ten-fold. Extracellular vesicles (EVs) are small liposome-like particles that mediate intercellular communication and play a major role in ARDS pathophysiology. Indeed, they participate in endothelial barrier dysfunction and permeability, neutrophil, and macrophage activation, and also in the development of a hypercoagulable state. A more thorough understanding of the variegated and cell-specific functions of EVs may lead to the development of safe and effective therapeutics. In this review, we have collected evidence of EVs role in ARDS, revise the main mechanisms of production and internalization and summarize the current therapeutical approaches that have shown the ability to modulate EV signaling

Manufacturing Assembly Time Estimation Using Structural Complexity Metric Trained Artificial Neural Networks

Assembly time estimation is traditionally a time-intensive manual process that requires detailed geometric and process information, which is often subjective and qualitative in nature. As a result, assembly time estimation is rarely applied during early design iterations. In this paper, the authors explore the possibility of automating the assembly time estimation process while reducing the level of design detail required. In this approach, they train artificial neural networks (ANNs) to estimate the assembly times of vehicle subassemblies using either assembly connectivity or liaison graph properties, respectively, as input data. The effectiveness of estimation is evaluated based on the distribution of estimates provided by a population of ANNs trained on the same input data using varying initial conditions. Results indicate that this method can provide time estimates of an assembly process with ±15% error while relying exclusively on the geometric part information rather than process instructions