Verrucous carcinoma of the vulva: patterns of care and treatment outcomes.

Background: Verrucous vulvar carcinoma (VC) is an uncommon and distinct histologic subtype of squamous cell carcinoma (SCC). The available literature on VC is currently limited to case reports and small single institution studies. Aims: The goals of this study were to analyze data from the National Cancer Database (NCDB) to quantitate the incidence of VC and to investigate the effects of patient demographics, tumor characteristics, and treatment regimens on overall survival (OS) in women with verrucous vulvar carcinoma. Methods and results: Patients diagnosed with vulvar SCC or VC between the years of 2004 and 2016 were identified in the NCDB. OS was assessed with Kaplan–Meier curves and the log-rank test. Construction of a Cox model compared survival after controlling for confounding variables. The reported incidence of SCC of the vulva has significantly increased since 2004 (p \u3c .0001). In contrast, the incidence of VC has remained stable (p = .344) since 2004. Compared to SCC, VC was significantly more likely to be diagnosed in older women (p \u3c .0001) and treated with surgery alone (p \u3c .0001). However, on propensity score weighted analysis there was a trend toward improved 5-year OS in women with VC compared to those with SCC (63.4% vs. 57.7%, p = .0794). Multivariable Cox survival analysis showed an improvement in OS in VC patients treated with both primary site and regional lymph node surgery compared to primary site surgery alone (adjusted hazard ratio [aHR] 0.67, 95% confidence interval [CI] 0.46–0.97, p = .0357). Conclusion: Verrucous carcinoma is more likely to present in older women. Regional lymph node surgery in addition to primary site surgery significantly improves OS in VC patients

Persistent homology to analyse 3D faces and assess body weight gain

In this paper, we analyse patterns in face shape variation due to weight gain. We propose the use of persistent homology descriptors to get geometric and topological information about the configuration of anthropometric 3D face landmarks. In this way, evaluating face changes boils down to comparing the descriptors computed on 3D face scans taken at different times. By applying dimensionality reduction techniques to the dissimilarity matrix of descriptors, we get a space in which each face is a point and face shape variations are encoded as trajectories in that space. Our results show that persistent homology is able to identify features which are well related to overweight and may help assessing individual weight trends. The research was carried out in the context of the European project SEMEOTICONS, which developed a multisensory platform which detects and monitors over time facial signs of cardio-metabolic risk

Comparison of geometric morphometric outline methods in the discrimination of age-related differences in feather shape

BACKGROUND: Geometric morphometric methods of capturing information about curves or outlines of organismal structures may be used in conjunction with canonical variates analysis (CVA) to assign specimens to groups or populations based on their shapes. This methodological paper examines approaches to optimizing the classification of specimens based on their outlines. This study examines the performance of four approaches to the mathematical representation of outlines and two different approaches to curve measurement as applied to a collection of feather outlines. A new approach to the dimension reduction necessary to carry out a CVA on this type of outline data with modest sample sizes is also presented, and its performance is compared to two other approaches to dimension reduction. RESULTS: Two semi-landmark-based methods, bending energy alignment and perpendicular projection, are shown to produce roughly equal rates of classification, as do elliptical Fourier methods and the extended eigenshape method of outline measurement. Rates of classification were not highly dependent on the number of points used to represent a curve or the manner in which those points were acquired. The new approach to dimensionality reduction, which utilizes a variable number of principal component (PC) axes, produced higher cross-validation assignment rates than either the standard approach of using a fixed number of PC axes or a partial least squares method. CONCLUSION: Classification of specimens based on feather shape was not highly dependent of the details of the method used to capture shape information. The choice of dimensionality reduction approach was more of a factor, and the cross validation rate of assignment may be optimized using the variable number of PC axes method presented herein

Fine-mapping identifies two additional breast cancer susceptibility loci at 9q31.2.

We recently identified a novel susceptibility variant, rs865686, for estrogen-receptor positive breast cancer at 9q31.2. Here, we report a fine-mapping analysis of the 9q31.2 susceptibility locus using 43 160 cases and 42 600 controls of European ancestry ascertained from 52 studies and a further 5795 cases and 6624 controls of Asian ancestry from nine studies. Single nucleotide polymorphism (SNP) rs676256 was most strongly associated with risk in Europeans (odds ratios [OR] = 0.90 [0.88-0.92]; P-value = 1.58 × 10(-25)). This SNP is one of a cluster of highly correlated variants, including rs865686, that spans ∼14.5 kb. We identified two additional independent association signals demarcated by SNPs rs10816625 (OR = 1.12 [1.08-1.17]; P-value = 7.89 × 10(-09)) and rs13294895 (OR = 1.09 [1.06-1.12]; P-value = 2.97 × 10(-11)). SNP rs10816625, but not rs13294895, was also associated with risk of breast cancer in Asian individuals (OR = 1.12 [1.06-1.18]; P-value = 2.77 × 10(-05)). Functional genomic annotation using data derived from breast cancer cell-line models indicates that these SNPs localise to putative enhancer elements that bind known drivers of hormone-dependent breast cancer, including ER-α, FOXA1 and GATA-3. In vitro analyses indicate that rs10816625 and rs13294895 have allele-specific effects on enhancer activity and suggest chromatin interactions with the KLF4 gene locus. These results demonstrate the power of dense genotyping in large studies to identify independent susceptibility variants. Analysis of associations using subjects with different ancestry, combined with bioinformatic and genomic characterisation, can provide strong evidence for the likely causative alleles and their functional basis