46 research outputs found
A comparison of the mechanical behaviour of self-piercing riveted and resistance spot welded aluminium sheets for the automotive industry
The increased application of lightweight materials, such as aluminium has initiated many investigations into new joining techniques for aluminium alloys. The resistance spot welding (RSW) concept for aluminium has always attracted many researchers from different organizations. Self-piercing riveting (SPR) is the major production process used to join aluminium sheet body structures for the automotive industry. The research team at the University of Warwick has investigated these two major joining technologies for aluminium assembly. The paper reported here gives an in depth comparison of the mechanical behaviour for each joint type under different loading conditions. It covers symmetrical and asymmetrical assembly from thin gauge of 1.0 mm to thick gauge of 3.0 mm. The results suggest that generally RSW can provide similar strength performance to SPR with the exception of T-peel; the energy to maximum load needs be considered ‘case to case’ and is dependent largely on loading conditions and the failure mode particularly with respect to SPR. The spread of results for SPR is generally smaller than for RSW, and the performance of SPR joints improves as the thickness increases
Brain size and brain/intracranial volume ratio in major mental illness
<p>Abstract</p> <p>Background</p> <p>This paper summarizes the findings of a long term study addressing the question of how several brain volume measure are related to three major mental illnesses in a Colorado subject group. It reports results obtained from a large N, collected and analyzed by the same laboratory over a multiyear period, with visually guided MRI segmentation being the primary initial analytic tool.</p> <p>Methods</p> <p>Intracerebral volume (ICV), total brain volume (TBV), ventricular volume (VV), ventricular/brain ratio (VBR), and TBV/ICV ratios were calculated from a total of 224 subject MRIs collected over a period of 13 years. Subject groups included controls (C, N = 89), and patients with schizophrenia (SZ, N = 58), bipolar disorder (BD, N = 51), and schizoaffective disorder (SAD, N = 26).</p> <p>Results</p> <p>ICV, TBV, and VV measures compared favorably with values obtained by other research groups, but in this study did not differ significantly between groups. TBV/ICV ratios were significantly decreased, and VBR increased, in the SZ and BD groups compared to the C group. The SAD group did not differ from C on any measure.</p> <p>Conclusions</p> <p>In this study TBV/ICV and VBR ratios separated SZ and BD patients from controls. Of interest however, SAD patients did not differ from controls on these measures. The findings suggest that the gross measure of TBV may not reliably differ in the major mental illnesses to a degree useful in diagnosis, likely due to the intrinsic variability of the measures in question; the differences in VBR appear more robust across studies. Differences in some of these findings compared to earlier reports from several laboratories finding significant differences between groups in VV and TBV may relate to phenomenological drift, differences in analytic techniques, and possibly the "file drawer problem".</p
An Improved PSO Algorithm for Generating Protective SNP Barcodes in Breast Cancer
BACKGROUND: Possible single nucleotide polymorphism (SNP) interactions in breast cancer are usually not investigated in genome-wide association studies. Previously, we proposed a particle swarm optimization (PSO) method to compute these kinds of SNP interactions. However, this PSO does not guarantee to find the best result in every implement, especially when high-dimensional data is investigated for SNP-SNP interactions. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we propose IPSO algorithm to improve the reliability of PSO for the identification of the best protective SNP barcodes (SNP combinations and genotypes with maximum difference between cases and controls) associated with breast cancer. SNP barcodes containing different numbers of SNPs were computed. The top five SNP barcode results are retained for computing the next SNP barcode with a one-SNP-increase for each processing step. Based on the simulated data for 23 SNPs of six steroid hormone metabolisms and signalling-related genes, the performance of our proposed IPSO algorithm is evaluated. Among 23 SNPs, 13 SNPs displayed significant odds ratio (OR) values (1.268 to 0.848; p<0.05) for breast cancer. Based on IPSO algorithm, the jointed effect in terms of SNP barcodes with two to seven SNPs show significantly decreasing OR values (0.84 to 0.57; p<0.05 to 0.001). Using PSO algorithm, two to four SNPs show significantly decreasing OR values (0.84 to 0.77; p<0.05 to 0.001). Based on the results of 20 simulations, medians of the maximum differences for each SNP barcode generated by IPSO are higher than by PSO. The interquartile ranges of the boxplot, as well as the upper and lower hinges for each n-SNP barcode (n = 3∼10) are more narrow in IPSO than in PSO, suggesting that IPSO is highly reliable for SNP barcode identification. CONCLUSIONS/SIGNIFICANCE: Overall, the proposed IPSO algorithm is robust to provide exact identification of the best protective SNP barcodes for breast cancer
Prolactin receptor is a negative prognostic factor in patients with squamous cell carcinoma of the head and neck
Background:
The influence of human prolactin (hPRL) on the development of breast and other types of cancer is well established. Little information, however, exists on the effects of hPRL on squamous cell carcinomas of the head and neck (SCCHNs).
Methods:
In this study, we evaluated prolactin receptor (PRLR) expression in SCCHN cell lines and assessed by immunohistochemistry the expression in 89 patients with SCCHNs. The PRLR expression was correlated with clinicopathological characteristics as well as clinical outcome. The effect of hPRL treatment on tumour cell growth was evaluated in vitro.
Results:
Immunoreactivity for PRLR was observed in 85 out of 89 (95%) tumours. Multivariate COX regression analysis confirmed high levels of PRLR expression (>25% of tumour cells) to be an independent prognostic factor with respect to overall survival (HR=3.70, 95% CI: 1.14–12.01; P=0.029) and disease-free survival (P=0.017). Growth of PRLR-positive cancer cells increased in response to hPRL treatment.
Conclusion:
Our data indicate that hPRL is an important growth factor for SCCHN. Because of PRLR expression in a vast majority of tumour specimens and its negative impact on overall survival, the receptor represents a novel prognosticator and a promising drug target for patients with SCCHNs
Screening of whole genome sequences identified high-impact variants for stallion fertility
Prolactin-induced mouse mammary carcinomas model estrogen resistant luminal breast cancer.
INTRODUCTION: Tumors that express estrogen receptor alpha (ERα+) comprise 75% of breast cancers in women. While treatments directed against this receptor have successfully lowered mortality rates, many primary tumors initially or later exhibit resistance. The paucity of murine models of this luminal tumor subtype has hindered studies of factors that promote their pathogenesis and modulate responsiveness to estrogen-directed therapeutics. Since epidemiologic studies closely link prolactin and the development of ERα+ tumors in women, we examined characteristics of the aggressive ERα+ and ERα- carcinomas which develop in response to mammary prolactin in a murine transgenic model (neu-related lipocalin- prolactin (NRL-PRL)). To evaluate their relationship to clinical tumors, we determined phenotypic relationships among these carcinomas, other murine models of breast cancer, and features of luminal tumors in women.
METHODS: We examined a panel of prolactin-induced tumors for characteristics relevant to clinical tumors: histotype, ERα/progesterone receptor (PR) expression and estrogen responsiveness, Activating Protein 1 (AP-1) components, and phosphorylation of signal transducer and activator of transcription 5 (Stat5), extracellular signal regulated kinase (ERK) 1/2 and AKT. We compared levels of transcripts in the ERα-associated luminal signature that defines this subtype of tumors in women and transcripts enriched in various mammary epithelial lineages to other well-studied genetically modified murine models of breast cancer. Finally, we used microarray analyses to compare prolactin-induced ERα+ and ERα- tumors, and examined responsiveness to estrogen and the anti-estrogen, Faslodex, in vivo.
RESULTS: Prolactin-induced carcinomas were markedly diverse with respect to histotype, ERα/PR expression, and activated signaling cascades. They constituted a heterogeneous, but distinct group of murine mammary tumors, with molecular features of the luminal subtype of human breast cancer. In contrast to morphologically normal and hyperplastic structures in NRL-PRL females, carcinomas were insensitive to ERα-mediated signals. These tumors were distinct from mouse mammary tumor virus (MMTV)-neu tumors, and contained elevated transcripts for factors associated with luminal/alveolar expansion and differentiation, suggesting that they arose from physiologic targets of prolactin. These features were shared by ERα+ and ERα- tumors, suggesting a common origin, although the former exhibited transcript profiles reflecting greater differentiation.
CONCLUSIONS: Our studies demonstrate that prolactin can promote diverse carcinomas in mice, many of which resemble luminal breast cancers, providing a novel experimental model to examine the pathogenesis, progression and treatment responsiveness of this tumor subtype
Prolactin-induced mouse mammary carcinomas model estrogen resistant luminal breast cancer
Deficiency of the Transcriptional Repressor B Cell Lymphoma 6 (Bcl6) Is Accompanied by Dysregulated Lipid Metabolism
<div><p>The transcriptional repressor B-cell Lymphoma 6 (Bcl6) was recently identified in a profile of genes regulated in adipocytes, suggesting a relationship between Bcl6 and metabolic regulation. As a representative target gene repressed by Bcl6, Suppressor of Cytokine Signaling (Socs) 2 expression was elevated in Bcl6 deficient (KO) mice, including metabolic tissues liver, adipose tissue and muscle, as well as in spleen and thymus. Bcl6 occupied the Socs2 promoter in wild-type, but not Bcl6 KO mice, suggesting direct regulation of Socs2 by Bcl6 <i>in vivo</i>. Mice deficient in Bcl6 were found to exhibit multiple features of dysregulated lipid metabolism. Adipose tissue mass was dramatically reduced or absent in Bcl6 KO mice. Further, hepatic and serum triglycerides were low. Bcl6 deficiency was accompanied by decreased hepatic expression of Stearoyl-CoA desaturase 1 (Scd1) and Fatty acid synthase (Fasn) genes which encode lipogenic enzymes. Expression of the gene for the transcription factor Carbohydrate-Responsive Element Binding Protein (Chrebp), which regulates expression of lipogenic genes, was also reduced in liver of Bcl6 KO mice. Bcl6 deficiency disrupted fasting-induced increases in hepatic triglyceride deposition, but not decreases in lipogenic gene expression. Taken together, these findings suggest that in addition to its well-recognized roles in immune regulation, Bcl6 plays a role in regulatory events of lipid metabolism, and that in the absence of Bcl6, lipid metabolism in liver and adipose tissue is dysregulated.</p></div