Raloxifene Enhances Material-Level Mechanical Properties of Femoral Cortical and Trabecular Bone

We have previously documented that raloxifene enhances the mechanical properties of dog vertebrae independent of changes in bone mass, suggesting a positive effect of raloxifene on material-level mechanical properties. The goal of this study was to determine the separate effects of raloxifene on the material-level mechanical properties of trabecular and cortical bone from the femur of beagle dogs. Skeletally mature female beagles (n = 12 per group) were treated daily for 1 yr with oral doses of vehicle or raloxifene (0.50 mg/kg d). Trabecular bone mechanical properties were measured at the femoral neck using reduced platen compression, a method that allows the trabecular bone to be tested without coring specimens. Cortical bone properties were assessed on prismatic beam specimens machined from the femoral diaphysis using both monotonic and dynamic (cyclic relaxation) four-point bending tests. Trabecular bone from raloxifene-treated animals had significantly higher ultimate stress (+130%), modulus (+89%), and toughness (+152%) compared with vehicle-treated animals. Cortical bone from raloxifene-treated animals had significantly greater toughness (+62%) compared with vehicle, primarily as a function of increased postyield displacement (+100%). There was no significant difference between groups in the percentage of stiffness loss during cortical bone cyclic relaxation tests. These results are consistent with previous data from the vertebrae of these same animals, showing raloxifene has positive effects on biomechanical properties independent of changes in bone volume/density. This may help explain how raloxifene reduces osteoporotic fractures despite modest changes in bone mass.This work was supported by National Institutes of Health Grants AR047838 and AR007581 and a research grant from Lilly Research Laboratories. This investigation used an animal facility constructed with support from Research Facilities Improvement Program Grant Number C06 RR10601-01 from the National Center for Research Resources, National Institutes of Health. Disclosure Summary: M.R.A. has research contracts from Eli Lilly and the Alliance for Better Bone Health. D.B.B. has research contracts from Eli Lilly, the Alliance for Better Bone Health, and Amgen; owns stock in Amgen, Eli Lilly, Pfizer, and Glaxo SmithKline; and is a speaker/consultant for Merck, Eli Lilly, the Alliance for Better Bone Health, and Amgen. A.S.K. and M.C.K. have a family member employed by Eli Lilly. H.A.H. and W.A.H. have nothing to declare

The use of chained two-point clusters for the examination of associations of air pollution with health conditions

Objectives: There are a few accepted and intensively applied statistical methods used to study associations of ambient air pollution with health conditions. Among the most popular methods applied to assess short term air health effects are case-crossover (using events) and time-series methodologies (using counts). A few other techniques for studying counts of events have been proposed, including the Generalized Linear Mixed Models (GLMM). One suggested GLMM technique uses cluster structures based on natural embedded hierarchies: days are nested in the days of a week (dow), which, in turn, are nested in months and months in years (). Material and Methods: In this study the authors considered clusters with hierarchical structures in a form of , where the 14-days hierarchy determines 7 clusters composed of 2 days (the same days) of a week (2 Mondays, 2 Tuesdays, etc.), in 1 year. In this work the authors proposed hierarchical chained clusters in which 2 days of a week are grouped as follows: (first, second), (second, third), (third, fourth) and so on. Such an approach allows determination of an additional series of the slopes on the clusters (second, third), (fourth, fifth), etc., i.e., estimation of the coefficients for other configurations of air pollutant levels. The authors considered a series of 2 point chained clusters covering a year. In such a construction each cluster has one common data point (day) with another one. Results: The authors estimated coefficients (slopes) related to the ambient ozone exposure (mortality) and to 3 selected air pollutants (particulate matter, nitrogen dioxide and ozone) combined into index and considered as health risk exposure (emergency department (ED) visits). The generated results were compared to the estimations obtained from the time-series method and the time-stratified case-crossover method applied to the same data. Conclusions: The proposed statistical method, based on the chained hierarchical clusters (), generated results with shorter confidence intervals than the other methods

Environmental data science: Part 1

Environmental data science is a multi-disciplinary and mature field of research at the interface of statistics, machine learning, information technology, climate and environmental science. The two-part special issue ‘Environmental Data Science’ comprises a set of research articles and opinion pieces led by statisticians who are at the forefront of the field. This editorial identifies and discusses common strands of research that appear in the contributions to Part 1, which largely focus on statistical methodology. These include temporal, spatial and spatio-temporal modeling; statistical computing; machine learning and artificial intelligence; and the critical question of decision-making in the presence of uncertainty. This editorial complements that of Part 2, which largely focuses on applications; see Burr, Newlands, and Zammit-Mangion (2023)

Identifying the Early Post-Mortem VOC Profile from Cadavers in a Morgue Environment Using Comprehensive Two-Dimensional Gas Chromatography

Understanding the VOC profile released during the early post-mortem period is essential for applications in training human remains detection dogs and urban search and rescue operations (USAR) to rapidly locate living and deceased victims. Human cadavers were sampled at the UQTR morgue within a 0–72 h post-mortem interval. VOC samples were collected from the headspace above the cadavers, using Tenax TA/Carbograph 5TD dual sorbent tubes, and analyzed using GC×GC-TOFMS. Multiple data processing steps, including peak table alignment and filtering, were undertaken using LECO ChromaToF and custom scripts in R programming language. This study identified 104 prevalent VOCs, some of which are linked to human decomposition, while others are connected to the persistence of living scent. Principal Component Analysis (PCA) further highlighted that VOC profiles can change dynamically over time, even in a controlled setting. The findings underscore the complexity and variability in VOC profiles during the early post-mortem period. This variability is influenced by multiple factors including the individual’s biological and physiological conditions. Despite the challenges in characterizing these profiles, the identified VOCs could potentially serve as markers in forensic applications. The study also highlights the need for additional research to build a dataset of VOCs for more robust forensic applications

Air Health Trend Indicator: Association between Short-Term Exposure to Ground Ozone and Circulatory Hospitalizations in Canada for 17 Years, 1996–2012

The Air Health Trend Indicator is designed to estimate the public health risk related to short-term exposure to air pollution and to detect trends in the annual health risks. Daily ozone, circulatory hospitalizations and weather data for 24 cities (about 54% of Canadians) for 17 years (1996–2012) were used. This study examined three circulatory causes: ischemic heart disease (IHD, 40% of cases), other heart disease (OHD, 31%) and cerebrovascular disease (CEV, 14%). A Bayesian hierarchical model using a 7-year estimator was employed to find trends in the annual national associations by season, lag of effect, sex and age group (≤65 vs. >65). Warm season 1-day lagged ozone returned higher national risk per 10 ppb: 0.4% (95% credible interval, −0.3–1.1%) for IHD, 0.4% (−0.2–1.0%) for OHD, and 0.2% (−0.8–1.2%) for CEV. Overall mixed trends in annual associations were observed for IHD and CEV, but a decreasing trend for OHD. While little age effect was identified, some sex-specific difference was detected, with males seemingly more vulnerable to ozone for CEV, although this finding needs further investigation. The study findings could reduce a knowledge gap by identifying trends in risk over time as well as sub-populations susceptible to ozone by age and sex

Barley in the Great Plains area : relation of cultural methods to production /

no.222 (1915

Oats in the Great Plains area : relation of cultural methods to production /

no.218 (1915

Crop production in the Great Plains area : relation of cultural methods to yields /

no.268 (1915

Oats in the Great Plains area : relation of cultural methods to production /

no.218 (1915