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A 3D-printed metal solid target using additive manufacturing process is a cost-effective production solution to complex and intricate target design. The initial proof-of-concept prototype solid target holder was 3D-printed in cast alloy, Al⁻7Si⁻0.6Mg (A357). However, given the relatively low thermal conductivity for A357 (κmax, 160 W/m·K), replication of the solid target holder in sterling silver (SS925) with higher thermal conductivity (κmax, 361 W/m·K) was investigated. The SS925 target holder enhances the cooling efficiency of the target design, thus achieving higher target current during irradiation. A validation production of 64Cu using the 3D-printed SS925 target holder indicated no loss of enriched 64Ni from proton bombardment above 80 µA, at 11.5 MeV.

Patients attending a routine bone densitometry clinic were scanned on two different densitometers on the same day using a pencil-beam (Hologic QDR1000W) and fan-beam (Hologic QDR4500W) machine. Subjects were scanned at the lumbar spine site and or the proximal femur. The differences in bone mineral density (BMD) between the fan-beam and pencil-beam (QDR4500W-QDR1000W) were determined for all pairs of scans. The mean difference in BMD was also calculated to see if there was a systematic bias between the machines. The mean difference in BMD was -8 mg/cm2 and 25 mg/cm2 at the spine and total hip, respectively. The individual differences in BMD between the two machines were examined to assess if they were signifi- cantly greater than measurement error. The percentage of scans classified as significantly different was calculated for the difference in BMD before and after adjusting for the mean difference in BMD. The percentage of individuals classified as significantly different ranged from 17.1-45.0% before adjustment, at the spine and total hip, respectively, and 16.1-22.6% after adjustment. From a clinical perspective, this degree of misclassification is probably unacceptable. These results suggest that scans obtained from a QDR4500W fan-beam system and QDR1000W pencil-beam system should not be compared, with or without adjustment for systematic bias. [ABSTRACT FROM AUTHOR]

Osteoporosis is a complex disorder and commonly leads to fractures in elderly persons. Genome-wide association studies (GWAS) have become an unbiased approach to identify variations in the genome that potentially affect health. However, the genetic variants identified so far only explain a small proportion of the heritability for complex traits. Due to the modest genetic effect size and inadequate power, true association signals may not be revealed based on a stringent genome-wide significance threshold. Here, we take advantage of SNP and transcript arrays and integrate GWAS and expression signature profiling relevant to the skeletal system in cellular and animal models to prioritize the discovery of novel candidate genes for osteoporosis-related traits, including bone mineral density (BMD) at the lumbar spine (LS) and femoral neck (FN), as well as geometric indices of the hip (femoral neck-shaft angle, NSA; femoral neck length, NL; and narrow-neck width, NW). A two-stage meta-analysis of GWAS from 7,633 Caucasian women and 3,657 men, revealed three novel loci associated with osteoporosis-related traits, including chromosome 1p13.2 (RAP1A, p = 3.6x10(-8)), 2q11.2 (TBC1D8), and 18q11.2 (OSBPL1A), and confirmed a previously reported region near TNFRSF11B/OPG gene. We also prioritized 16 suggestive genome-wide significant candidate genes based on their potential involvement in skeletal metabolism. Among them, 3 candidate genes were associated with BMD in women. Notably, 2 out of these 3 genes (GPR177, p = 2.6x10(-13); SOX6, p = 6.4x10(-10)) associated with BMD in women have been successfully replicated in a large-scale meta-analysis of BMD, but none of the non-prioritized candidates (associated with BMD) did. Our results support the concept of our prioritization strategy. In the absence of direct biological support for identified genes, we highlighted the efficiency of subsequent functional characterization using publicly available expression profiling relevant to the skeletal system in cellular or whole animal models to prioritize candidate genes for further functional validation.