This paper describes the development of a biosensor based on label-free immunosensing for the detection of the C-terminal telopeptide bone turnover marker from type-1 collagen. A self-assembled monolayer (SAM) of dithiodipropionic acid was deposited on a gold electrode. Then streptavidin and biotinylated anti-human C-terminal telopeptide antibody were successively conjugated on the self-assembled monolayer. Electrochemical impedance measurements were made to characterize each step of the SAM/streptavidin/biotinylated antibody binding. Subsequently, electrochemical impedance was measured with different concentrations of C-teminal telopeptide. A detection limit of 50 ng/mL and a dynamic range up to 3 μg/mL were achieved. To our knowledge, this is the first attempt to develop a label-free immunosensor based on electrochemical impedance with DC bias for detection of bone-related degradation and rebuilding products. The electronic biosensor might eventually be used for quantitative point-of-care screening of bone health. It is hoped that analysis of bone turnover markers can indicate the beginning of bone diseases such as osteoarthritis and osteoporosis so that treatment might start early when it is most effective.

Background: The effect of dopaminergic therapy on balance in Parkinson’s disease (PD) remains unclear, including previous studies that excluded the effect of dyskinesias or other involuntary movements on postural sway. Additionally, medication’s effects may differ between fallers and non-fallers. In this study, the authors quantify the effect of dopaminergic medication on postural balance (sway) in advanced PD, with and without dyskinesias, and consider the patient’s history of falls. Methods: In 24 patients with advanced idiopathic PD, postural balance was measured using a strain-gauge force platform. Before and after taking dopaminergic medication, the patient’s postural sway was measured at 30-second intervals to determine sway length (SL) and sway area (SA). Data analysis included the presence of dyskinesias during "ON" medication condition and history of previous falls. Results: No significant changes occurred in SL or SA with dopaminergic treatment for fallers without dyskinesias or non-fallers with dyskinesias. However, after dopaminergic treatment, SL and SA were 37.8% and 45% lower, respectively, in non-fallers without dyskinesias (indicating better balance) and were 87.4% and 162.8% higher, respectively, in fallers with dyskinesias (indicating poorer balance). In the ON medication condition, SL and SA were larger in patients with dyskinesias when compared with patients without dyskinesias; SL was larger in fallers than non-fallers in both groups with or without dyskinesias. Conclusions: Dopaminergic medication effects on postural sway could be a predictive factor for fall risk in PD patients with and without dyskinesias: specifically, decreased sway could indicate minimal fall risk whereas no change or increased postural sway could indicate a high risk.

Global fire activities, which are getting worse due to climate change, cause both environmental and human health hazards. Firefighters, being the first responders, are frequently exposed to heat which may impact their immune system and overall health. However, the nature of the impact of chronic heat exposure on immune function has not been studied in-depth in firefighters. In this study, 22 firefighters exposed to “heavy-smoke fires (structural fires)”, categorized as the “high-exposure group” (>0.15 structural fires/week) and “low-exposure group” (<0.15 structural fires/week), were sampled. Peripheral blood was examined for immune cell profile based on total and differential cell counts, immune function based on the transcriptional expression of drivers of innate and adaptive immunity and key inflammation mediators, and heat stress marker HSP70. The white blood cell (WBC) count, mean corpuscular volume, mean corpuscular hemoglobin, and absolute and segmented neutrophil counts decreased below the normal range in both exposure groups. The gene transcript levels for toll-like receptors (TLR2, TLR4, but not TLR7) and their adaptor protein MYD88 were lower whereas those for T-cell transcription factors (RORC/RORγ, FoxP3) and inflammatory mediators (TNF-α, Granzyme-B) were higher in the “high-exposure group”, indicating mixed response; however, the ratios between pro-inflammatory and anti-inflammatory transcription factors of adaptive immunity, namely T-bet/FoxP3 (Th1/Treg) and RORC/FoxP3 (Th17/Treg), were lower. Collectively, decreased immune cell landscape, downregulated key innate immunity receptors, and Tregs’ dominance suggested that chronic heat exposure in firefighters dysregulated innate and adaptive immunity, skewed towards an overall immunosuppressive condition with inflammation.

The purpose of this study was to explore data-driven models, based on decision trees, to develop practical and easy to use predictive models for early identification of firefighters who are likely to cross the threshold of hyperthermia during live-fire training. Predictive models were created for three consecutive live-fire training scenarios. The final predicted outcome was a categorical variable: will a firefighter cross the upper threshold of hyperthermia – Yes/No. Two tiers of models were built, one with and one without taking into account the outcome (whether a firefighter crossed hyperthermia or not) from the previous training scenario. First tier of models included age, baseline heart rate and core body temperature, body mass index, and duration of training scenario as predictors. The second tier of models included the outcome of the previous scenario in the prediction space, in addition to all the predictors from the first tier of models. Classification and regression trees were used independently for prediction. The response variable for the regression tree was the quantitative variable: core body temperature at the end of each scenario. The predicted quantitative variable from regression trees was compared to the upper threshold of hyperthermia (38°C) to predict whether a firefighter would enter hyperthermia. The performance of classification and regression tree models was satisfactory for the second (success rate = 79%) and third (success rate = 89%) training scenarios but not for the first (success rate = 43%). Data-driven models based on decision trees can be a useful tool for predicting physiological response without modeling the underlying physiological systems. Early prediction of heat stress coupled with proactive interventions, such as pre-cooling, can help reduce heat stress in firefighters.

Background: Post-stroke walking impairment is a significant cause of chronic disability worldwide and often leads to loss of life roles for survivors and their caregivers. Walking impairment is traditionally classified into mild (>0.8 m/s), moderate (0.41–0.8 m/s), and severe (≤0.4 m/s), and those categorized as “severe” are more likely to be homebound and at greater risk of falls, fractures, and rehospitalization. In addition, there are minimal effective walking rehabilitation strategies currently available for this subgroup. Backward locomotor treadmill training (BLTT) is a novel and promising training approach that has been demonstrated to be safe and feasible across all levels of impairment; however, its benefits across baseline walking impairment levels (severe (≤0.4 m/s) vs. mild–moderate (>0.4 m/s)) have not been examined. Methods: Thirty-nine adults (>6 months post-stroke) underwent 6 days of BLTT (3×/week) over 2 weeks. Baseline and PRE to POST changes were measured during treadmill training and overground walking. Results: Individuals with baseline severe walking impairment were at a more significant functional disadvantage across all spatiotemporal walking measures at baseline and demonstrated fewer overall gains post-training. However, contrary to our working hypothesis, both groups experienced comparable increases in cadence, bilateral percent single support times, and step lengths. Conclusion: BLTT is well tolerated and beneficial across all walking impairment levels, and baseline walking speed (≤0.4 m/s) should serve as a covariate in the design of future walking rehabilitation trials.