Low bone mass in juvenile onset sclerosis systemic: the possible role for 25-hydroxyvitamin D insufficiency

Juvenile onset systemic sclerosis (JoSSc) is a rare disease, and there are no studies focusing in bone mineral density and biochemical bone parameters. Ten consecutive patients with JoSSc and 10 controls gender, age, menarche age, and physical activity matched were selected. Clinical data were obtained at the medical visit and chart review. Laboratorial analysis included autoantibodies, 25-hydroxyvitamin D (25OHD), intact parathyroid hormone, calcium, phosphorus, alkaline phosphatase and albumin sera levels. Bone mineral density was analyzed by dual-energy X-ray absorptiometry, and bone mineral apparent density (BMAD) was calculated. A lower BMAD in femoral neck (0.294 +/- A 0.060 vs. 0.395 +/- A 0.048 g/cm(3), P = 0.001) and total femur (0.134 +/- A 0.021 vs. 0.171 +/- A 0.022 g/cm(3), P = 0.002) was observed in JoSSc compared to controls. Likewise, a trend to lower BMAD in lumbar spine (0.117 +/- A 0.013 vs. 0.119 +/- A 0.012 g/cm(3), P = 0.06) was also found in these patients. Serum levels of 25OHD were significantly lower in JoSSc compared to controls (18.1 +/- A 6.4 vs. 25.1 +/- A 6.6 ng/mL, P = 0.04), and all patients had vitamin D insufficiency (< 20 ng/mL) compared to 40% of controls (P = 0.01). All other biochemical parameters were within normal range and alike in both groups. BMAD in femoral neck and total femur was correlated with 25OHD levels in JoSSc (r = 0.82, P = 0.004; r = 0.707, P = 0.02; respectively). We have identified a remarkable high prevalence of 25OHD insufficiency in JoSSc. Its correlation with hip BMAD suggests a causal effect and reinforces the need to incorporate this hormone evaluation in this disease management.

Primary antiphospholipid syndrome in premenopausal women: low vitamin D, high fat mass and maintained bone mineral mass

The aim of this study was to analyze vitamin D levels and their association with bone mineral density and body composition in primary antiphospholipid syndrome. For this cross-sectional study 23 premenopausal women with primary antiphospholipid syndrome (Sapporo criteria) and 23 age- and race-matched healthy controls were enrolled. Demographic, anthropometric, clinical and laboratorial data were collected using clinical interview and chart review. Serum 25-hydroxyvitamin D levels, parathormone, calcium and 24-hour urinary calcium were evaluated in all subjects. Bone mineral density and body composition were studied by dual X-ray absorptiometry. The mean age of patients and controls was 33 years. Weight (75.61 [20.73] vs. 63.14 [7.34] kg, p=0.009), body mass index (29.57 [7.17] vs. 25.35 [3.37] kg, p=0.014) and caloric ingestion (2493 [1005.6] vs. 1990 [384.1] kcal/day, p=0.03) were higher in PAPS than controls. All PAPS were under oral anticoagulant with INR within therapeutic range. Interestingly, biochemical bone parameters revealed lower levels of 25-hydroxyvitamin D [21.64 (11.26) vs. 28.59 (10.67) mg/dl, p=0.039], serum calcium [9.04 (0.46) vs. 9.3 (0.46) mg/dl, p=0.013] and 24-hour urinary calcium [106.55 (83.71) vs. 172.92 (119.05) mg/d, p=0.027] in patients than in controls. Supporting these findings, parathormone levels were higher in primary antiphospholipid syndrome than in controls [64.82 (37.83) vs. 44.53 (19.62) pg/ml, p=0.028]. The analysis of osteoporosis risk factors revealed that the two groups were comparable (p>0.05). Lumbar spine, femoral neck, total femur and whole body bone mineral density were similar in both groups (p>0.05). Higher fat mass [28.51 (12.93) vs. 20.01 (4.68) kg, p=0.005] and higher percentage of fat [36.08 (7.37) vs. 31.23 (4.64)%, p=0.010] were observed in PAPS in comparison with controls; although no difference was seen regarding lean mass. In summary, low vitamin D in primary antiphospholipid syndrome could be secondary to higher weight and fat mass herein observed most likely due to adipocyte sequestration. This weight gain may also justify the maintenance of bone mineral density even with altered biochemical bone parameters. Lupus (2010) 19, 1302-1306.

Menstrual and hormonal alterations in juvenile dermatomyositis

Objective To evaluate age at menarche, menstrual cycles and hormone profile in juvenile dermatomyositis (JDM) patients and controls. Methods Twelve consecutive JDM patients were compared to 24 age-matched healthy subjects. Age at menarche and age of maternal menarche were recorded. Menstrual cycle was evaluated prospectively for 6 consecutive months and the mean cycle length and flow were calculated. The hormone profile was collected on the last menstrual cycle. Demographic data, clinical features, muscle enzymes, JDM scores and treatment were analysed. Results The median of current age of JDM patients and controls was similar (18 vs. 17 years, p=0.99). The median age at menarche of the JDM patients was higher than in the control group (13 vs. 11 years, p=0.02) whereas the median age of maternal menarche was alike in both groups (12 vs. 13 years, p=0.67). Menstrual disturbances were not observed, except for one patient who had longer length of menstrual cycle. The median of follicle stimulating hormone (FSH) was significantly higher in JDM patients compared to controls (4.5 vs. 3.0 IU/L, p=0.02) and none of them had premature ovarian failure (POF). The median of progesterone was significantly lower in JDM patients (0.3 vs. 0.7 ng/mL, p=0.01) with a higher frequency of decreased progesterone compared to controls (75% vs. 29%, p=0.01). Conclusions Our study identifies in JDM patients delayed menarche with normal cycles and low follicular reserve. The decreased progesterone levels may suggest an underlying subclinical corpus luteum dysfunction in this disease.

Association of the MCP-1-2518 A/G Polymorphism and No Association of Its Receptor CCR2-64 V/I Polymorphism with Lupus Nephritis

Objective. To evaluate whether the A/G polymorphism at position 2518 in the regulatory region of the monocyte chemoattractant protein-1 (MCP-1) or the V/I polymorphism at position 64 of the receptor. CCR2, are associated with lupus nephritis (LN) or any clinical characteristics of the disease or with renal survival in a patient population. Methods. We selected 197 patients with lupus nephritis and 220 matched healthy controls for study. MCP-1 and CCR2 genotyping was performed by polymerase chain reaction. Clinical and laboratory data were compiled from patients` charts over followup that ranged from 6 months to 10 years. Results. The GIG genotype of MCP-1 was more common in LN patients (p = 0.019), while the A allele was associated with healthy controls (p = 0.007) as was the V allele of CCR2 (p = 0.046) compared to LN patients. Clinical index measures [SLE Disease Activity Index (SLEDAI)], immunological markers, renal histology, renal function at enrollment, and renal survival were not influenced by these polymorphisms. A less aggressive renal disease, measured by renal SLEDAI index, was associated with the V allele of the CCR2 gene polymorphism. Conclusion. These findings support that MCP-1 2518 GIG is associated with LN but there was no association of this genotype with renal function or renal survival. When studying CCR2 64 V/I polymorphism we showed a positive association of the V allele with healthy controls but no association of the genotype with LN patients. (First Release March 152010; J Rheumatol 2010;37:776-82; doi:10.3899/jrheum.090681)

Breast cancer five-year survival in New South Wales women, 1972 to 1991

This study of breast cancer survival is based on analysis of five-year relative survival of 38 362 cases of invasive breast cancer in New South Wales (NSW) women, incident between 1972 and 1991, with follow-up to 1992, using data from the population-based NSW Central Cancer Registry. Survival was ascertained by matching the registry file of breast cancers against NSW death certificates from 1972 to 1992, mainly by automated probabilistic linkage. Absolute survival of cases was compared with expected survival of age- and period-matched NSW women. Proportional hazard regression analysis was used for examination of the effects on excess mortality of age, period of diagnosis and degree of spread at diagnosis. Relative survival at five years increased from 70 per cent in 1972-1976 to 77 per cent in 1987-1991. Survival improved during the 1970s and in the late 1980s. Regression analysis suggested that part of the improved survival in the late 1980s was due to lesser degree of spread at diagnosis, whereas the improved survival during the 1970s may have been due to treatment. Survival was better for those aged 40-49 years (RR = 0.86) and worse for those aged greater than or equal to 70 years (RR = 1.22) compared with the referent group (60-69 years). Excess mortality was much less for those with invasive localised disease than those with regional spread (RR = 3.1) or metastatic cancer (RR = 15.5) at diagnosis. For the most recent period (1987-1991), relative five-year survival was 90, 70 and 18 per cent, respectively, for the three degree-of-spread categories.

Breast cancer five-year survival, by New South Wales regions, 1980 to 1991

Breast cancer five-year relative survival was calculated for 16 urban and rural regions in New South Wales (NSW) for cases incident in 1980-1991. Survival analysis employed cancer registry data linked with the death register, and age- and period-matched regional mortality of NSW women, Proportional hazard regression analysis was used to compare excess mortality in breast cancer cases in each region. The effect of region was significant (P < 0.05) in the analysis, after age and the follow-up variable (and their intel action) were adjusted for, although no region was significantly different from the referent group (chosen because of average relative five-year survival). When degree of spread and its interactions were entered into che model, the effect of region became nonsignificant. A significant linear trend (P < 0.05) in the adjusted relative risk for excess mortality in breast cancer cases was noted when regions were divided into quartiles based on socioeconomic status, with higher relative risk in low-socioeconomic-status groups; this effect also disappeared with adjustment for degree of spread at diagnosis. There was no general effect of rurality versus capital city or other metropolitan centres. This study demonstrates a small effect of region of residence and implied socioeconomic status on breast cancer survival in NSW women, but this becomes nonsignificant when the data are adjusted for degree of spread at diagnosis, This suggests that earlier diagnosis would he of benefit in reducing minor inequalities in breast cancer survival in NSW women.

Wavelet correlation between subjects: A time-scale data driven analysis for brain mapping using fMRI

Functional magnetic resonance imaging (fMRI) based on BOLD signal has been used to indirectly measure the local neural activity induced by cognitive tasks or stimulation. Most fMRI data analysis is carried out using the general linear model (GLM), a statistical approach which predicts the changes in the observed BOLD response based on an expected hemodynamic response function (HRF). In cases when the task is cognitively complex or in cases of diseases, variations in shape and/or delay may reduce the reliability of results. A novel exploratory method using fMRI data, which attempts to discriminate between neurophysiological signals induced by the stimulation protocol from artifacts or other confounding factors, is introduced in this paper. This new method is based on the fusion between correlation analysis and the discrete wavelet transform, to identify similarities in the time course of the BOLD signal in a group of volunteers. We illustrate the usefulness of this approach by analyzing fMRI data from normal subjects presented with standardized human face pictures expressing different degrees of sadness. The results show that the proposed wavelet correlation analysis has greater statistical power than conventional GLM or time domain intersubject correlation analysis. (C) 2010 Elsevier B.V. All rights reserved.

Analyzing the connectivity between regions of interest: An approach based on cluster Granger causality for NRI data analysis

The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.

Cortical Thickness Reduction of Normal Appearing Cortex in Patients with Polymicrogyria

OBJECTIVE To examine cortical thickness and volumetric changes in the cortex of patients with polymicrogyria, using an automated image analysis algorithm. METHODS Cortical thickness of patients with polymicrogyria was measured using magnetic resonance imaging (MRI) cortical surface-based analysis and compared with age-and sex-matched healthy subjects. We studied 3 patients with disorder of cortical development (DCD), classified as polymicrogyria, and 15 controls. Two experienced neuroradiologists performed a conventional visual assessment of the MRIs. The same data were analyzed using an automated algorithm for tissue segmentation and classification. Group and individual average maps of cortical thickness differences were produced by cortical surface-based statistical analysis. RESULTS Patients with polymicrogyria showed increased thickness of the cortex in the same areas identified as abnormal by radiologists. We also identified a reduction in the volume and thickness of cortex within additional areas of apparently normal cortex relative to controls. CONCLUSIONS Our findings indicate that there may be regions of reduced cortical thickness, which appear normal from radiological analysis, in the cortex of patients with polymicrogyria. This finding suggests that alterations in neuronal migration may have an impact in the cortical formation of the cortical areas that are visually normal. These areas are associated or occur concurrently with polymicrogyria.

Depression in Parkinson`s disease: Convergence from voxel-based morphometry and functional magnetic resonance imaging in the limbic thalamus

Depression is the most frequent psychiatric disorder in Parkinson`s disease (PD). Although evidence Suggests that depression in PD is related to the degenerative process that underlies the disease, further studies are necessary to better understand the neural basis of depression in this population of patients. In order to investigate neuronal alterations underlying the depression in PD, we studied thirty-six patients with idiopathic PD. Twenty of these patients had the diagnosis of major depression disorder and sixteen did not. The two groups were matched for PD motor severity according to Unified Parkinson Disease Rating Scale (UPDRS). First we conducted a functional magnetic resonance imaging (fMRI) using an event-related parametric emotional perception paradigm with test retest design. Our results showed decreased activation in the left mediodorsal (MD) thalamus and in medial prefrontall cortex in PD patients with depression compared to those without depression. Based upon these results and the increased neuron count in MD thalamus found in previous studies, we conducted a region of interest (ROI) guided voxel-based morphometry (VBM) study comparing the thalamic volume. Our results showed an increased volume in mediodorsal thalamic nuclei bilaterally. Converging morphological changes and functional emotional processing in mediodorsal thalamus highlight the importance of limbic thalamus in PD depression. In addition this data supports the link between neurodegenerative alterations and mood regulation. (C) 2009 Elsevier Inc. All rights reserved.

The impact of functional connectivity changes on support vector machines mapping of fMRI data

Functional magnetic resonance imaging (fMRI) is currently one of the most widely used methods for studying human brain function in vivo. Although many different approaches to fMRI analysis are available, the most widely used methods employ so called ""mass-univariate"" modeling of responses in a voxel-by-voxel fashion to construct activation maps. However, it is well known that many brain processes involve networks of interacting regions and for this reason multivariate analyses might seem to be attractive alternatives to univariate approaches. The current paper focuses on one multivariate application of statistical learning theory: the statistical discrimination maps (SDM) based on support vector machine, and seeks to establish some possible interpretations when the results differ from univariate `approaches. In fact, when there are changes not only on the activation level of two conditions but also on functional connectivity, SDM seems more informative. We addressed this question using both simulations and applications to real data. We have shown that the combined use of univariate approaches and SDM yields significant new insights into brain activations not available using univariate methods alone. In the application to a visual working memory fMRI data, we demonstrated that the interaction among brain regions play a role in SDM`s power to detect discriminative voxels. (C) 2008 Elsevier B.V. All rights reserved.

Estimating correlations from epidemiological data in the presence of measurement error

Analysis of a major multi-site epidemiologic study of heart disease has required estimation of the pairwise correlation of several measurements across sub-populations. Because the measurements from each sub-population were subject to sampling variability, the Pearson product moment estimator of these correlations produces biased estimates. This paper proposes a model that takes into account within and between sub-population variation, provides algorithms for obtaining maximum likelihood estimates of these correlations and discusses several approaches for obtaining interval estimates. (C) 1997 by John Wiley & Sons, Ltd.

Value congruence in leader-member exchange

In this study, hypotheses were tested that the quality of leader-member exchanges (LMX) depends on congruity of values between leader and member. Data on negotiating latitude and personal values were gathered from 160 members of 30 work groups in Australian organizations. Factor analysis revealed 5 value dimensions: Freedom, Achievement, Mateship, Obedience, and Coping. Analyses of variance supported the hypothesis that LMX quality is higher when leaders and members share achievement and obedience values. Subsequent exploratory analysis, however, indicated that a more complex model based on compatibility of leader authority and member affiliation values may provide a more complete representation.

Surgical Outcomes after Preceptored Laparoscopic Colorectal Surgery: Results of a Brazilian Preceptorship Program

Background/Aims: Safety of laparoscopic colectomy education methods remains unknown. This study aimed at comparing the outcomes of patients undergoing preceptored laparoscopic colectomy with patients operated on by the same preceptor. Methodology: A prospective analysis of 30 preceptored operations performed by nine surgeons (PD group) between 2006 and 2008 was conducted. Data of 30 operations matched for diagnosis and surgery type conducted by the same preceptor (P group) were evaluated. Results: Median age was 56.2 (26-80) and 55.2 (22-81) respectively in P and PD group (p=0.804). Eleven (36.7%) were male in P group, 16 (53.3%) in PD group (p=0.194). Preceptored operations were not significantly longer than operations performed by the preceptor (198 vs. 156 min) - p=0.072. Length of hospital stay did not differ [4 days (3-12) in P group, and 5 (3-15) in PD group, p=0.296]. Conversion occurred in 4 cases in PD and in 2 in P group (p=0.389). Morbidity was similar (23.3% in P and 26.7% in PD group). One patient from P and two from PD group needed re-operation. No deaths occurred. Conclusions: Laparoscopic colorectal surgery preceptorship programs in surgeon learner`s place are safe. Surgeons` introduction through basic and hands-on courses is required for skills acquisition needed to minimize adverse outcomes.

The GHEP-EMPOP collaboration on mtDNA population data-A new resource for forensic casework

Mitochondrial DNA (mtDNA) population data for forensic purposes are still scarce for some populations, which may limit the evaluation of forensic evidence especially when the rarity of a haplotype needs to be determined in a database search. In order to improve the collection of mtDNA lineages from the Iberian and South American subcontinents, we here report the results of a collaborative study involving nine laboratories from the Spanish and Portuguese Speaking Working Group of the International Society for Forensic Genetics (GHEP-ISFG) and EMPOP. The individual laboratories contributed population data that were generated throughout the past 10 years, but in the majority of cases have not been made available to the scientific community. A total of 1019 haplotypes from Iberia (Basque Country, 2 general Spanish populations, 2 North and 1 Central Portugal populations), and Latin America (3 populations from Sao Paulo) were collected, reviewed and harmonized according to defined EMPOP criteria. The majority of data ambiguities that were found during the reviewing process (41 in total) were transcription errors confirming that the documentation process is still the most error-prone stage in reporting mtDNA population data, especially when performed manually. This GHEP-EMPOP collaboration has significantly improved the quality of the individual mtDNA datasets and adds mtDNA population data as valuable resource to the EMPOP database (www.empop.org). (C) 2010 Elsevier Ireland Ltd. All rights reserved.