Integration of gene panels in the diagnosis of hereditary breast and ovarian cancer (HBOC) requires a careful evaluation of the risk associated with pathogenic or likely pathogenic variants (PVs) ...detected in each gene. Here we analyzed 34 genes in 5131 suspected HBOC index cases by next-generation sequencing.
Using the Exome Aggregation Consortium data sets plus 571 individuals from the French Exome Project, we simulated the probability that an individual from the Exome Aggregation Consortium carries a PV and compared it to the estimated frequency within the HBOC population.
Odds ratio conferred by PVs within BRCA1, BRCA2, PALB2, RAD51C, RAD51D, ATM, BRIP1, CHEK2, and MSH6 were estimated at 13.22 10.01–17.22, 8.61 6.78–10.82, 8.22 4.91–13.05, 4.54 2.55–7.48, 5.23 1.46–13.17, 3.20 2.14–4.53, 2.49 1.42–3.97, 1.67 1.18–2.27, and 2.50 1.12–4.67, respectively. PVs within RAD51C, RAD51D, and BRIP1 were associated with ovarian cancer family history (OR = 11.36 5.78–19.59, 12.44 2.94–33.30 and 3.82 1.66–7.11). PALB2 PVs were associated with bilateral breast cancer (OR = 16.17 5.48–34.10) and BARD1 PVs with triple-negative breast cancer (OR = 11.27 3.37–25.01). Burden tests performed in both patients and the French Exome Project population confirmed the association of PVs of BRCA1, BRCA2, PALB2, and RAD51C with HBOC.
Our results validate the integration of PALB2, RAD51C, and RAD51D in the diagnosis of HBOC and suggest that the other genes are involved in an oligogenic determinism.
Highlighting tumoral mutations is a key step in oncology for personalizing care. Considering the genetic heterogeneity in a tumor, software used for detecting mutations should clearly distinguish ...real tumor events of interest that could be predictive markers for personalized medicine from false positives. OutLyzer is a new variant-caller designed for the specific and sensitive detection of mutations for research and diagnostic purposes. It is based on statistic and local evaluation of sequencing background noise to highlight potential true positive variants. 130 previously genotyped patients were sequenced after enrichment by capturing the exons of 22 genes. Sequencing data were analyzed by HaplotypeCaller, LofreqStar, Varscan2 and OutLyzer. OutLyzer had the best sensitivity and specificity with a fixed limit of detection for all tools of 1% for SNVs and 2% for Indels. OutLyzer is a useful tool for detecting mutations of interest in tumors including low allele-frequency mutations, and could be adopted in standard practice for delivering targeted therapies in cancer treatment.
This study investigates the possibility of mitigating the demographic biases that affect face recognition technologies through the use of synthetic data. Demographic biases have the potential to ...impact individuals from specific demographic groups, and can be identified by observing disparate performance of face recognition systems across demographic groups. They primarily arise from the unequal representations of demographic groups in the training data. In recent times, synthetic data have emerged as a solution to some problems that affect face recognition systems. In particular, during the generation process it is possible to specify the desired demographic and facial attributes of images, in order to control the demographic distribution of the synthesized dataset, and fairly represent the different demographic groups. We propose to fine-tune with synthetic data existing face recognition systems that present some demographic biases. We use synthetic datasets generated with GANDiffFace, a novel framework able to synthesize datasets for face recognition with controllable demographic distribution and realistic intra-class variations. We consider multiple datasets representing different demographic groups for training and evaluation. Also, we fine-tune different face recognition systems, and evaluate their demographic fairness with different metrics. Our results support the proposed approach and the use of synthetic data to mitigate demographic biases in face recognition.
This study investigates the possibility of mitigating the demographic biases that affect face recognition technologies through the use of synthetic data. Demographic biases have the potential to ...impact individuals from specific demographic groups, and can be identified by observing disparate performance of face recognition systems across demographic groups. They primarily arise from the unequal representations of demographic groups in the training data. In recent times, synthetic data have emerged as a solution to some problems that affect face recognition systems. In particular, during the generation process it is possible to specify the desired demographic and facial attributes of images, in order to control the demographic distribution of the synthesized dataset, and fairly represent the different demographic groups. We propose to fine-tune with synthetic data existing face recognition systems that present some demographic biases. We use synthetic datasets generated with GANDiffFace, a novel framework able to synthesize datasets for face recognition with controllable demographic distribution and realistic intra-class variations. We consider multiple datasets representing different demographic groups for training and evaluation. Also, we fine-tune different face recognition systems, and evaluate their demographic fairness with different metrics. Our results support the proposed approach and the use of synthetic data to mitigate demographic biases in face recognition.
There is still disagreement among studies with respect to the magnitude, location, and direction of sex differences of local gray matter volume (GMV) in the human brain. Here, we applied a ...state-of-the-art technique examining GMV in a well-powered sample (n = 2,838) validating effects in two independent general-population cohorts, age range 21-90 years, measured using the same MRI scanner. More GMV in women than in men was prominent in medial and lateral prefrontal areas, the superior temporal sulcus, the posterior insula, and orbitofrontal cortex. In contrast, more GMV in men than in women was detected in subcortical temporal structures, such as the amygdala, hippocampus, temporal pole, fusiform gyrus, visual primary cortex, and motor areas (premotor cortex, putamen, anterior cerebellum). The findings in this large-scale study may clarify previous inconsistencies and contribute to the understanding of sex-specific differences in cognition and behavior.
Une gravure de poisson manifeste, attribuable au Magdalénien final et découverte en 2010 dans la grotte Margot (Thorigné-en-Charnie, Mayenne), présente des éléments graphiques qui permettent ...d’avancer des pistes de détermination spécifique. Il s’agit de toute évidence d’un poisson d’eau douce, et l’hypothèse que l’on soit en présence d’un Cyprinidé de type tanche paraît la plus recevable, d’autant que la couche 3,1 du site voisin de Rochefort, attribuable au Paléolithique supérieur final, a livré un arc branchial d’un autre Cyprinidé (probablement un chevesne ou une vandoise). Le poisson est une thématique peu répandue dans le corpus de l’art pariétal paléolithique. Il est ici associé à une autre représentation animale gravée, dont l’identification nous apparaît sujette à discussion (phoque ou autre poisson).
An engraved fish that can be attributed to the final Magdalenian period was discovered in 2010 in the Margot cave (Thorigné-en-Charnie, Mayenne, France). It shows graphic details that allow us to propose some clues to taxonomic determination. It must be a freshwater fish; the hypothesis of a Cyprinidae such as a tench is acceptable, considering that the 3.1 layer of the nearby Rochefort cave, attributable to the Final Paleolithic, has yielded a branchial arch of another Cyprinidae (probably a chub or a dace). Fish is not a usual theme in Paleolithic wall art. Here it is associated with another engraved animal figure, which is not fully determinable (seal or other fish).
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