Abstract. The portable microAeth® MA200
(MA200) is widely applied for measuring black carbon in human exposure
profiling and mobile air quality monitoring. Due to it being relatively new on
the market, the field lacks a refined assessment of the instrument's
performance under various settings and data post-processing approaches. This
study assessed the mobile real-time performance of the MA200 to determine a
suitable noise reduction algorithm in an urban area, Augsburg, Germany.
Noise reduction and negative value mitigation were explored via different
data post-processing methods (i.e., local polynomial regression (LPR),
optimized noise reduction averaging (ONA), and centred moving average
(CMA)) under common sampling interval times (i.e., 5, 10, and 30 s). After
noise reduction, the treated data were evaluated and compared by (1) the
amount of useful information attributed to retention of microenvironmental
characteristics, (2) the relative number of negative values remaining, (3) the
reduction and retention of peak samples, and (4) the amount of useful signal
retained after correction for local background conditions. Our results
identify CMA as a useful tool for isolating the central trends of raw black
carbon concentration data in real time while reducing nonsensical negative
values and the occurrence and magnitudes of peak samples that affect visual
assessment of the data without substantially affecting bias. Correction for
local background concentrations improved the CMA treatment by bringing
nuanced microenvironmental changes into view. This analysis employs
a number of different post-processing methods for black carbon data,
providing comparative insights for researchers looking for black carbon data
smoothing approaches, specifically in a mobile monitoring framework and data
collected using the microAeth® series of Aethalometer.
Type 2 diabetes mellitus (T2DM) is a multisystemic disease that afflicts more than 415 million people globally-the incidence and prevalence of T2DM continues to rise. It is well-known that T2DM has detrimental effects on bone quality that increase skeletal fragility, which predisposes subjects to an increased risk of fracture and fracture healing that results in non-or malunion. Diabetics have been found to have perturbations in metabolism, hormone production, and calcium homeostasis-particularly PTH expression-that contribute to the increased risk of fracture and decreased fracture healing. Given the perturbations in PTH expression and the establishment of hPTH (1-34) for use in age-related osteoporosis, it was determined logical to attempt to ameliorate the bone phenotype found in T2DM using hPTH (1-34). Therefore, the present study had two aims: (i) to establish a suitable murine model of the skeletal fragility present in T2DM because no current consensus model exists; and (ii) to determine the effects of hPTH (1-34) on bone fractures in T2DM. The results of the present study suggest that the polygenic mouse of T2DM, TALLYHO/JngJ, most accurately recapitulates the diabetic osteoporotic phenotype seen in humans and that the intermittent systemic administration of hPTH (1-34) increases fracture healing in T2DM murine models by increasing the proliferation of mesenchymal stem cells.
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