Introduction. Osteoporosis (OP) is a common polygenic disorder in the aging population, and several single nucleotide polymorphisms (SNPs) in the alpha-L-iduronidase (IDUA) gene and patched homolog 1 (PTCH1) gene regulate bone metabolism and affect bone mass. The study aimed at investigating the relationships of rs3755955 and rs6831280 in the IDUA gene and rs28377268 in the PTCH1 gene with bone mineral density (BMD), bone turnover markers (BTMs), and fractures in the elderly Chinese subjects with OP. Materials and Methods. A cohort of 328 unrelated senile osteoporosis (SOP) patients with or without osteoporotic fractures was recruited. rs3755955, rs6831280, and rs28377268 polymorphisms were identified using SNaPshot technology. BTM levels were determined by electrochemiluminescence (ECL). Bone mineral densities (BMDs) at the lumbar spine (LS) and proximal femur sites were measured by dual-energy X-ray absorptiometry (DEXA) in all subjects. The Hardy-Weinberg equilibrium (HWE) test was performed. HWE P values and comparisons of genotype frequencies were estimated using the chi-square test. Analysis of covariance (ANCOVA) adjusted for confounding factors was performed to investigate associations of SNPs with BMDs and BTMs in subgroups. Results. The chi-square test indicated that genotype distributions in the control group conformed to HWE (P>0.05). The distributions of allele and genotype frequencies of rs6831280 between fracture and osteoporotic participants were significantly different (P-allele=0.002 and P-genotype=0.012, respectively). Concerning rs6831280, ANCOVA found BMDs at LS 2-4 (L2-4) and total hip (TH) among the study subjects suffering from SOP with GA genotype were lower than in those carrying GG or AA (P-L2-4=0.004 and P-TH=0.027, respectively). Conclusions. IDUA rs6831280 is associated with BMDs at L2-4 and TH in the elderly Chinese population with SOP and may serve as a marker for the genetic susceptibility to osteoporotic fractures.

In this study, we investigated whether the measurement of patellar tracking can be used as a diagnostic parameter of patellofemoral joint disease. Patellar tracking is defined as the movement of the patella in relation to the femorotibial joint within the full range of flexion and extension of the knee joint. The PubMed, EMBASE, Medline, PsychINFO, and AMED databases were used to find relevant articles. Analyzed were the patellar tracking coordinate system and the measurement objects, precision, methods used in those studies, as well as the results obtained. Origin points for coordinate systems varied across the studies. The research object and methods of patellar tracking varied in the studies. Most studies focused on a static description of the internal and external displacement and the internal and external inclination. The in vivo , noninvasive, and six degrees of freedom evaluation of patellar tracking reflect patellar motion more comprehensively, though each of these methods does so in different ways. Dynamic and quantitative evaluation of patellar tracking is still lacking in clinical work. Accurate and quantitative patellar tracking measurement could provide clinicians with a comprehensive evaluation of the stability of the knee joint.

This study compares the longitudinal histological characteristics of proximal humeral implants with different spatial structures in rabbits. Thirty skeletally-mature male rabbits were divided into a trabecular structure group and regular hexahedron structure group according to the different spatial structures of a biological titanium alloy screw inserted into the greater tuberosity of the proximal humerus. Samples were collected 3, 6, and 12 weeks after the implantation surgery. Histological results showed that the amount of bone in-growth in the porous cavity of the screw implant increased over time. Quantitative analysis showed there was significantly more bone in-growth in the trabecular structure group than the classic structure group 3 weeks (25.4% ± 6.9% vs 19.6% ± 3.7%, P < 0.05) and 6 weeks (31.2% ± 1.7% vs 26.9% ± 5.3, P < 0.05) after the implantation surgery. No significant difference was detected between the two groups 12 weeks after the surgery (41.7% ± 2.5% vs 39% ± 4.1%, P > 0.05). Our data found that bone in-growth significantly differed among the three time points ( P < 0.05) in both groups, but not between the implants with different spatial structures 12 weeks after the surgery.