An active balance board system with real-time control of stiffness and time-delay to assess mechanisms of postural stability

Increased time-delay in the neuromuscular system caused by neurological disorders, concussions, or advancing age is an important factor contributing to balance loss (Chagdes et al., 2013, 2016a,b). We present the design and fabrication of an active balance board system that allows for a systematic study of stiffness and time-delay induced instabilities in standing posture. Although current commercial balance boards allow for variable stiffness, they do not allow for manipulation of time-delay. Having two controllable parameters can more accurately determine the cause of balance deficiencies, and allows us to induce instabilities even in healthy populations. An inverted pendulum model of human posture on such an active balance board predicts that reduced board rotational stiffness destabilizes upright posture through board tipping, and limit cycle oscillations about the upright position emerge as feedback time-delay is increased. We validate these two mechanisms of instability on the designed balance board, showing that rotational stiffness and board time-delay induced the predicted postural instabilities in healthy, young adults. Although current commercial balance boards utilize control of rotational stiffness, real-time control of both stiffness and time-delay on an active balance board is a novel and innovative manipulation to reveal balance deficiencies and potentially improve individualized balance training by targeting multiple dimensions contributing to standing balance.     

Multiomic Metabolic Enrichment Network Analysis Reveals Metabolite–Protein Physical Interaction Subnetworks Altered in Cancer

Metabolism is recognized as an important driver of cancer progression and other complex diseases, but global metabolite profiling remains a challenge. Protein expression profiling is often a poor proxy since existing pathway enrichment models provide an incomplete mapping between the proteome and metabolism. To overcome these gaps, we introduce multiomic metabolic enrichment network analysis (MOMENTA), an integrative multiomic data analysis framework for more accurately deducing metabolic pathway changes from proteomics data alone in a gene set analysis context by leveraging protein interaction networks to extend annotated metabolic models. We apply MOMENTA to proteomic data from diverse cancer cell lines and human tumors to demonstrate its utility at revealing variation in metabolic pathway activity across cancer types, which we verify using independent metabolomics measurements. The novel metabolic networks we uncover in breast cancer and other tumors are linked to clinical outcomes, underscoring the pathophysiological relevance of the findings.     

Impact of High Deductible Health Plans on Diabetes Care Quality and Outcomes: Systematic Review

ObjectiveTo provide a review of the impact of high deductible health plans (HDHPs) on the utilizations of services required for optimal management of diabetes and subsequent health outcomes.MethodsSystematic literature review of studies published between January 1, 2000, and May 7, 2021, was conducted that examined the impact of HDHP on diabetes monitoring (eg, recommended laboratory and surveillance testing), routine care (eg, ambulatory appointments), medication management (eg, medication initiation, adherence), and acute health care utilization (eg, emergency department visits, hospitalizations, incident complications).ResultsOf the 303 reviewed articles, 8 were relevant. These studies demonstrated that HDHPs lower spending at the expense of reduced high-value diabetes monitoring, routine care, and medication adherence, potentially contributing to the observed increases in acute health care utilization. Additionally, patient out-of-pocket costs for recommended screenings doubled, and total health care expenditures increased by 49.4% for HDHP enrollees compared with enrollees in traditional health plans. Reductions in disease monitoring and routine care and increases in acute health care utilization were greatest in lower-income patients. None of the studies examined the impact of HDHPs on access to diabetes self-management education, technology use, or glycemic control.ConclusionAlthough HDHPs reduce some health care utilization and costs, they appear to do so at the expense of limiting high-value care and medication adherence. Policymakers, providers, and payers should be more cognizant of the potential for negative consequences of HDHPs on patients’ health.     

An Extreme Value Analysis of Pollutant Concentrations in Surface Soils Due to Atmospheric Deposition

Risk assessments often rely on deterministic models using long-term averages or “steady-state” values of input variables. Such models do not provide the information needed to estimate acute exposures. This study uses extreme value theory to examine the frequency and magnitude of daily pollutant concentrations in surface soils predicted at six U.S. locations. Concentrations are predicted using a deposition-leaching model and 50 years of historical precipitation data. A stochastic model also is used to generate 1000 years of precipitation data as modeling inputs for each location. The annual maximum concentrations at each site are fitted to a Gumbel type I distribution to estimate occurrence probability. For soluble pollutants, the predicted concentration varied substantially with precipitation, and the maximum daily concentrations exceeded annual averages by 4 to 8 times. Observed and synthetic precipitation data produced similar results at most study locations, though the synthetic data provided a slightly better fit to the Gumbel type I distribution. The precipitation model allows the generation of representative precipitation data that extend limited historical records. The extreme value analysis facilitates the evaluation of maximum pollutant concentrations, return periods, and other statistics that are important in evaluating acute exposures.     

An order-specific monoclonal antibody to Diptera reveals the impact of alternative prey on spider feeding behavior in a complex food web

Generalist predators have the capacity to restrict pest population growth, especially early in the season before densities increase. However, their polyphagous feeding habits sometimes translate into reduced pest consumption when they target alternative prey. An order-specific monoclonal antibody was developed to examine the strength of trophic connections between Diptera, a major category of non-pest prey, and linyphiid spiders in alfalfa. We report the development and characterization of a monoclonal antibody with order-level specificity to Diptera. This antibody elicited strong absorbance to 22 Diptera from 13 families, no false-positive reactivity to non-dipteran invertebrates, and antigen detection periods following prey consumption that were comparable between spiders. Over 900 field-collected females of the linyphiid spiders Erigone autumnalis and Bathyphantes pallidus were screened for Diptera antigen. Significantly more B. pallidus screened positive for Diptera (40%) compared to E. autumnalis (16%), indicating differential reliance on these prey. In parallel with the collection of spiders for gut-content analysis, prey availability was estimated at web sites. The two spiders exhibited different feeding responses to prey availability. Consumption of Diptera by B. pallidus was strongly correlated with Diptera abundance whilst the availability of other potential prey did not influence predation rates. Conversely, E. autumnalis did not prey upon Diptera in proportion to availability, but increased Collembola activity-density reduced dipteran consumption. Integration of molecular gut-content analysis with precise sampling of prey demonstrated how two closely related linyphiid spiders exhibit different feeding responses to the availability of prey under natural field conditions. Elucidating the feeding preferences of natural enemies is critical to effective incorporation of biological control by generalist predators in the management of agricultural pests.     

ATM regulates Cdt1 stability during the unperturbed S phase to prevent re-replication

Ataxia-telangiectasia mutated (ATM) plays crucial roles in DNA damage responses, especially with regard to DNA double-strand breaks (DSBs). However, it appears that ATM can be activated not only by DSB, but also by some changes in chromatin architecture, suggesting potential ATM function in cell cycle control. Here, we found that ATM is involved in timely degradation of Cdt1, a critical replication licensing factor, during the unperturbed S phase. At least in certain cell types, degradation of p27^Kip1 was also impaired by ATM inhibition. The novel ATM function for Cdt1 regulation was dependent on its kinase activity and NBS1. Indeed, we found that ATM is moderately phosphorylated at Ser1981 during the S phase. ATM silencing induced partial reduction in levels of Skp2, a component of SCF^Skp2 ubiquitin ligase that controls Cdt1 degradation. Furthermore, Skp2 silencing resulted in Cdt1 stabilization like ATM inhibition. In addition, as reported previously, ATM silencing partially prevented Akt phosphorylation at Ser473, indicative of its activation, and Akt inhibition led to modest stabilization of Cdt1. Therefore, the ATM-Akt-SCF^Skp2 pathway may partly contribute to the novel ATM function. Finally, ATM inhibition rendered cells hypersensitive to induction of re-replication, indicating importance for maintenance of genome stability.     

Flood Risk Analysis Based on Information Diffusion Theory

Due to the fact that the flood data series of small drainage basins is relatively short, available data are often not sufficient for flood risk analysis. This presents the problem of risk analysis using very small data samples. One method that can be applied is to regard the available small samples as fuzzy information and optimize them using information diffusion technology to yield analytical results with greater reliability. In this article a risk analysis method based on information diffusion theory is applied to create a new flood risk analysis model. Application of the model is illustrated taking the Jinhuajiang and Qujiang drainage basins as examples. This is a new attempt at applying information diffusion theory in flood risk analysis. Computations based on this analytical flood risk model can yield an estimated flood damage value that is relatively accurate. This study indicates that the aforementioned model exhibits fairly stable analytical results, even when using a small set of sample data. The results also indicate that information diffusion technology is highly capable of extracting useful information and therefore improves system recognition accuracy. This method can be easily applied and the analytical results produced are easy to understand. Results are accurate enough to act as a guide in disaster situations.     

In Pursuit of Safety: One-Hundred Years of Toxicological Risk Assessment

The publication in 1962 of Rachel Carson's Silent Spring marks the mid-point in a century that saw, in its first half, the emergence of public health concerns related to human exposures to chemicals, and, in its second half, the emergence of public policies to deal with those concerns. Those policies made it imperative that the scientific community come to grips with the problem of identifying exposure levels not likely to cause harm. This problem was not significantly discussed within the scientific community until the 1950s, and well-described methods for practical solutions to it did not appear until the 1970s. An important report from the National Academy of Sciences, published in 1983 (Risk Assessment in the Federal Government), provided an analysis of these emerging methods, and recommended a useful framework for the assessment and management of risk. This framework remains central to public health and regulatory decision-making. A high-level perspective is offered on events leading to and following the 1983 report. The article describes early thinking about chemical toxicity and the scientific path that thinking followed through the 20th century, and to the present.     

Predator detection and avoidance by starlings under differing scenarios of predation risk

Practically all animals must find food while avoiding predators.An individual's perception of predation risk may depend on manyfactors, such as distance to refuge and group size, but it isunclear whether individuals respond to different factors ina similar manner. We tested whether flocks of foraging starlingsresponded in the same way to an increased perception of predationrisk by assessing three factors: (1) neighbor distances, (2)habitat obstruction, and (3) recent exposure to a predator.We found that in all three scenarios of increased risk, starlingsreduced their interscan intervals (food-searching bouts), whichincreased the frequency of their vigilance periods. We thenexamined how one of these factors, habitat obstruction, affectedescape speed by simulating an attack with a model predator.Starlings were slower to respond in visually obstructed habitats(long grass swards) and slower when they had their head downin obstructed habitats than when they had their head down inopen habitats. In addition, reaction times were quicker whenstarlings could employ their peripheral fields of vision. Ourresults demonstrate that different sources of increased riskcan generate similar behavioral responses within a species.The degree of visibility in the physical and social environmentaffects both the actual and perceived risk of predation.