Short-termed changes in quantitative ultrasound estimated bone density among young men in an 18-weeks follow-up during their basic training for the Swiss Armed Forces

Background Quantitative Ultrasound (QUS) methods have been widely used to assess estimated bone density. This study aimed to assess changes in estimated bone density in association with changes in body composition, physical activity, and anthropometry. Methods We examined changes in anthropometry, body composition, and physical activity associated with changes in estimated bone mineral density (measured using quantitative ultrasound with a heel ultrasound device indicating broadband ultrasound attenuation BUA and speed of sound SOS) in a follow-up sample of n = 73 young men at the beginning and again 18 weeks later at the end of basic military training. Results At the end of the basic training, the subjects were on average significantly heavier (+1.0%), slightly taller (+0.5%) and had a higher fat mass (+6.6%) and grip strength (+8.6%). A significant decrease in mean physical activity (−49.5%) and mean estimated bone density calculated with BUA (−7.5%) was observed in the paired t-test. The results of the multivariable linear regressions (backward selection) show that changes in skeletal muscle mass (delta = 2nd measurement minus 1st measurement) have negative and body weight (delta) have positive association with the speed of sound SOS (delta), while fat mass (delta) and physical activity (delta) had the strongest negative associations with estimated bone mineral density (delta). In particular, we found a negative association between fat mass (delta) and estimated bone mineral density (delta, estimated with BUA). Conclusion Our study suggests that estimated bone density from the calcaneus can change within a few months even in young and mostly healthy individuals, depending upon physical activity levels and other co-factors. Further studies including other troop types as control groups as well as on women should follow in order to investigate this public health relevant topic in more depth. To what extent the estimated bone density measurement with quantitative ultrasound is clinically relevant needs to be investigated in further studies

CT-based radiomic signature predicts distant metastasis in lung adenocarcinoma

BACKGROUND AND PURPOSE: Radiomics provides opportunities to quantify the tumor phenotype non-invasively by applying a large number of quantitative imaging features. This study evaluates computed-tomography (CT) radiomic features for their capability to predict distant metastasis (DM) for lung adenocarcinoma patients. MATERIAL AND METHODS: We included two datasets: 98 patients for discovery and 84 for validation. The phenotype of the primary tumor was quantified on pre-treatment CT-scans using 635 radiomic features. Univariate and multivariate analysis was performed to evaluate radiomics performance using the concordance index (CI). RESULTS: Thirty-five radiomic features were found to be prognostic (CI > 0.60, FDR < 5%) for DM and twelve for survival. It is noteworthy that tumor volume was only moderately prognostic for DM (CI=0.55, p-value=2.77 × 10(−5)) in the discovery cohort. A radiomic-signature had strong power for predicting DM in the independent validation dataset (CI=0.61, p-value=1.79 ×10(−17)). Adding this radiomic-signature to a clinical model resulted in a significant improvement of predicting DM in the validation dataset (p-value=1.56 × 10(−11)). CONCLUSIONS: Although only basic metrics are routinely quantified, this study shows that radiomic features capturing detailed information of the tumor phenotype can be used as a prognostic biomarker for clinically-relevant factors such as DM. Moreover, the radiomic-signature provided additional information to clinical data

CT-based radiomic signature predicts distant metastasis in lung adenocarcinoma

Background and Purpose: Radiomics provides opportunities to quantify the tumor phenotype non-invasively by applying a large number of quantitative imaging features. This study evaluates computed-tomography (CT) radiomic features for their capability to predict distant metastasis (DM) for lung adenocarcinoma patients. Material and Methods: We included two datasets: 98 patients for discovery and 84 for validation. The phenotype of the primary tumor was quantified on pre-treatment CT-scans using 635 radiomic features. Univariate and multivariate analysis was performed to evaluate radiomics performance using the concordance index (CI). Results: Thirty-five radiomic features were found to be prognostic (CI > 0.60, FDR < 5%) for DM and twelve for survival. It is noteworthy that tumor volume was only moderately prognostic for DM (CI=0.55, p-value=2.77 × 10−5) in the discovery cohort. A radiomic-signature had strong power for predicting DM in the independent validation dataset (CI=0.61, p-value=1.79 ×10−17). Adding this radiomic-signature to a clinical model resulted in a significant improvement of predicting DM in the validation dataset (p-value=1.56 × 10−11). Conclusions: Although only basic metrics are routinely quantified, this study shows that radiomic features capturing detailed information of the tumor phenotype can be used as a prognostic biomarker for clinically-relevant factors such as DM. Moreover, the radiomic-signature provided additional information to clinical data

Defining a Radiomic Response Phenotype: A Pilot Study using targeted therapy in NSCLC

Medical imaging plays a fundamental role in oncology and drug development, by providing a non-invasive method to visualize tumor phenotype. Radiomics can quantify this phenotype comprehensively by applying image-characterization algorithms, and may provide important information beyond tumor size or burden. In this study, we investigated if radiomics can identify a gefitinib response-phenotype, studying high-resolution computed-tomography (CT) imaging of forty-seven patients with early-stage non-small cell lung cancer before and after three weeks of therapy. On the baseline-scan, radiomic-feature Laws-Energy was significantly predictive for EGFR-mutation status (AUC = 0.67, p = 0.03), while volume (AUC = 0.59, p = 0.27) and diameter (AUC = 0.56, p = 0.46) were not. Although no features were predictive on the post-treatment scan (p > 0.08), the change in features between the two scans was strongly predictive (significant feature AUC-range = 0.74–0.91). A technical validation revealed that the associated features were also highly stable for test-retest (mean ± std: ICC = 0.96 ± 0.06). This pilot study shows that radiomic data before treatment is able to predict mutation status and associated gefitinib response non-invasively, demonstrating the potential of radiomics-based phenotyping to improve the stratification and response assessment between tyrosine kinase inhibitors (TKIs) sensitive and resistant patient populations

Forest Elephant Crisis in the Congo Basin

Debate over repealing the ivory trade ban dominates conferences of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). Resolving this controversy requires accurate estimates of elephant population trends and rates of illegal killing. Most African savannah elephant populations are well known; however, the status of forest elephants, perhaps a distinct species, in the vast Congo Basin is unclear. We assessed population status and incidence of poaching from line-transect and reconnaissance surveys conducted on foot in sites throughout the Congo Basin. Results indicate that the abundance and range of forest elephants are threatened from poaching that is most intense close to roads. The probability of elephant presence increased with distance to roads, whereas that of human signs declined. At all distances from roads, the probability of elephant occurrence was always higher inside, compared to outside, protected areas, whereas that of humans was always lower. Inside protected areas, forest elephant density was correlated with the size of remote forest core, but not with size of protected area. Forest elephants must be prioritised in elephant management planning at the continental scale

COMBO-FISH Enables High Precision Localization Microscopy as a Prerequisite for Nanostructure Analysis of Genome Loci

With the completeness of genome databases, it has become possible to develop a novel FISH (Fluorescence in Situ Hybridization) technique called COMBO-FISH (COMBinatorial Oligo FISH). In contrast to other FISH techniques, COMBO-FISH makes use of a bioinformatics approach for probe set design. By means of computer genome database searching, several oligonucleotide stretches of typical lengths of 15–30 nucleotides are selected in such a way that all uniquely colocalize at the given genome target. The probes applied here were Peptide Nucleic Acids (PNAs)—synthetic DNA analogues with a neutral backbone—which were synthesized under high purity conditions. For a probe repetitively highlighted in centromere 9, PNAs labeled with different dyes were tested, among which Alexa 488® showed reversible photobleaching (blinking between dark and bright state) a prerequisite for the application of SPDM (Spectral Precision Distance/Position Determination Microscopy) a novel technique of high resolution fluorescence localization microscopy. Although COMBO-FISH labeled cell nuclei under SPDM conditions sometimes revealed fluorescent background, the specific locus was clearly discriminated by the signal intensity and the resulting localization accuracy in the range of 10–20 nm for a detected oligonucleotide stretch. The results indicate that COMBO-FISH probes with blinking dyes are well suited for SPDM, which will open new perspectives on molecular nanostructural analysis of the genome