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Background Fracture risk in men and women with type 1 diabetes (type 1 DM) has not been studied in a large prospective well designed cohort. Objective A systematic review and meta-analysis of observational studies were conducted to assess the association between type 1 DM and fractures. Data source Data were selected from Medline and Embase and abstract from annual scientific meeting of various diabetes and bone and mineral societies. Study selection Published studies reporting fracture risk in subjects with type 1 DM in comparison with subjects without diabetes between 1990 and July, 2014 and abstracts from various annual meeting (2005 onwards) were included for this meta-analysis. Data extraction Data were extracted from text of included publication or abstract of conferences. Data synthesis Fourteen studies that met inclusion criteria reported 2,066 fracture events among 27,300 subjects with type 1 DM (7.6%) and 136,579 fracture events among 4,364,125 subjects without diabetes (3.1%). The pooled relative risk (RR) of any fracture in subjects with type 1 DM was 3.16 (95% CI 1.51–6.63, p=0.002). Women and men with type 1 DM had four and two times higher risk for any fractures, respectively, compared to subjects without diabetes. The pooled RR of hip fractures and spinal fractures were 3.78 (95%CI; 2.05–6.98, p<0.001) and 2.88 (1.71–4.82, p<0.001), respectively, among subjects with type 1 DM. Conclusion Our meta-analysis suggests that both men and women with type 1 DM might have an increased risk for any fractures. A large prospective epidemiological study is needed to confirm our findings.

Femoral neck and lumbar spine BMD were modestly lower in adults with T1D compared to controls. However, this modest reduction in femoral neck and lumbar spine BMD cannot explain much higher observed fracture risk in adults with T1D.

The establishment of a GU MDC improved the quality of care for cancer patients as demonstrated by improved adherence to National Comprehensive Cancer Network guidelines, and a broadening of treatment choices made available.

Relative motion between the brain and skull and brain deformation are biomechanics aspects associated with many types of traumatic brain injury (TBI). Thus far, there is only one experimental endeavor reported brain strain under loading conditions commensurate with levels that were capable of producing injury. Most of the existing finite element (FE) head models are validated against brain-skull relative motion and then used for TBI prediction based on strain metrics. However, the suitability of using a model validated against brain-skull relative motion for strain prediction remains to be determined. To partially address the deficiency of experimental brain deformation data, this study revisits the only existing dynamic experimental brain strain data and updates the original calculations, which reflect incremental strain changes. The brain strain is recomputed by imposing the measured motion of neutral density target (NDT) to the NDT triad model. The revised brain strain and the brain-skull relative motion data are then used to test the hypothesis that an FE head model validated against brainskull relative motion does not guarantee its accuracy in terms of brain strain prediction. To this end, responses of brain strain and brain-skull relative motion of a previously developed FE head model (Kleiven, 2007) are compared with available experimental data. CORrelation and Analysis (CORA) and Normalized Integral Square Error (NISE) are employed to evaluate model validation performance for both brain strain and brain-skull relative motion. Correlation analyses (Pearson coefficient) are conducted between average cluster peak strain and average cluster peak brain-skull relative motion, and also between brain strain validation scores and brain-skull relative motion validation scores. The results show no significant correlations, neither between experimentally acquired peaks nor between computationally determined validation scores. These findings indicate that a head model validated against brain-skull relative motion may not be sufficient to assure its strain prediction accuracy. It is suggested that a FE head model with intended use for strain prediction should be validated against the experimental brain deformation data and not just the brain-skull relative motion.

SummaryContext The safety of vitamin D replacement in subjects with primary hyperparathyroidism (PHPT) and coexistent vitamin D deficiency is not well established. Objective To evaluate the safety of vitamin D replacement in PHPT. Data Source Data were searched from Medline, EMBASE, Cochrane CENTRAL and abstracts form annual scientific meetings of various international bone and mineral societies. Study Selection Studies examining the effect of preoperative vitamin D replacement in patients with PHPT and coexisting vitamin D deficiency, irrespective of year and language of the publication were included in the present meta-analysis. Data Extraction Data were extracted from text of the included publications or abstract of conferences. Data Synthesis Ten studies enrolling 340 subjects with PHPT were analysed in this meta-analysis. After vitamin D replacement, there was significant increase in 25(OH) D levels by 55Á3 nmol/l (95% CI 33Á3-77Á3), reduction in serum parathyroid hormone levels by 3Á5 pmol/l (5Á8 to À1Á2) without change in serum calcium (À0Á08 mmol/l, À0Á2 to +0Á03) and urinary calcium levels (0Á72 mmol/24 h, P = 0Á2) compared to baseline. Conclusion Vitamin D replacement in subjects with PHPT and coexistent vitamin D deficiency increase 25 (OH) D and reduce serum PTH significantly without causing hypercalcaemia and hypercalciuria. The finding of the study needs to be confirmed by a large randomized trial in patient with PHPT and coexistent vitamin D deficiency.

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Background: Many CpGs become hyper or hypo-methylated with age. Multiple methods have been developed by Horvath et al. to estimate DNA methylation (DNAm) age including Pan-tissue, Skin & Blood, PhenoAge, and GrimAge. Pan-tissue and Skin & Blood try to estimate chronological age in the normal population whereas PhenoAge and GrimAge use surrogate markers associated with mortality to estimate biological age and its departure from chronological age. Here, we applied Horvath's four methods to calculate and compare DNAm age in 499 subjects with type 1 diabetes (T1D) from the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) study using DNAm data measured by Illumina EPIC array in the whole blood. Association of the four DNAm ages with development of diabetic complications including cardiovascular diseases (CVD), nephropathy, retinopathy, and neuropathy, and their risk factors were investigated. Results: Pan-tissue and GrimAge were higher whereas Skin & Blood and PhenoAge were lower than chronological age (p < 0.0001). DNAm age was not associated with the risk of CVD or retinopathy over 18-20 years after DNAm measurement. However, higher PhenoAge (β = 0.023, p = 0.007) and GrimAge (β = 0.029, p = 0.002) were associated with higher albumin excretion rate (AER), an indicator of diabetic renal disease, measured over time. GrimAge was also associated with development of both diabetic peripheral neuropathy (OR = 1.07, p = 9.24E−3) and cardiovascular autonomic neuropathy (OR = 1.06, p = 0.011). Both HbA1c (β = 0.38, p = 0.026) and T1D duration (β = 0.01, p = 0.043) were associated with higher PhenoAge. Employment (β = − 1.99, p = 0.045) and leisure time (β = − 0.81, p = 0.022) physical activity were associated with lower Pan-tissue and Skin & Blood, respectively. BMI (β = 0.09, p = 0.048) and current smoking (β = 7.13, p = 9.03E−50) were positively associated with Skin & Blood and GrimAge, respectively. Blood pressure, lipid levels, pulse rate, and alcohol consumption were not associated with DNAm age regardless of the method used. Conclusions: Various methods of measuring DNAm age are sub-optimal in detecting people at higher risk of developing diabetic complications although some work better than the others.