De novo mutation rates at the single-mutation resolution in a human HBB gene-region associated with adaptation and genetic disease

While it is known that the mutation rate varies across the genome, previous estimates were based on averaging across various numbers of positions. Here we describe a method to measure the origination rates of target mutations at target base positions and apply it to a 6-bp region in the human hemoglobin subunit beta (HBB) gene and to the identical, paralogous hemoglobin subunit delta (HBD) region in sperm cells from both African and European donors. The HBB region of interest (ROI) includes the site of the hemoglobin S (HbS) mutation, which protects against malaria, is common in Africa and has served as a classic example of adaptation by random mutation and natural selection. We found a significant correspondence between de novo mutation rates and past observations of alleles in carriers, showing that mutation rates vary substantially in a mutation-specific manner that contributes to the site frequency spectrum. We also found that the overall point mutation rate is significantly higher in Africans than in Europeans in the HBB region studied. Finally, the rate of the 20A→T mutation, called the 'HbS mutation' when it appears in HBB, is significantly higher than expected from the genome-wide average for this mutation type. Nine instances were observed in the African HBB ROI, where it is of adaptive significance, representing at least three independent originations; no instances were observed elsewhere. Further studies will be needed to examine mutation rates at the single-mutation resolution across these and other loci and organisms and to uncover the molecular mechanisms responsible.

Global Contextual Dependency Network for Object Detection

Current two-stage object detectors extract the local visual features of Regions of Interest (RoIs) for object recognition and bounding-box regression. However, only using local visual features will lose global contextual dependencies, which are helpful to recognize objects with featureless appearances and restrain false detections. To tackle the problem, a simple framework, named Global Contextual Dependency Network (GCDN), is presented to enhance the classification ability of two-stage detectors. Our GCDN mainly consists of two components, Context Representation Module (CRM) and Context Dependency Module (CDM). Specifically, a CRM is proposed to construct multi-scale context representations. With CRM, contextual information can be fully explored at different scales. Moreover, the CDM is designed to capture global contextual dependencies. Our GCDN includes multiple CDMs. Each CDM utilizes local Region of Interest (RoI) features and single-scale context representation to generate single-scale contextual RoI features via the attention mechanism. Finally, the contextual RoI features generated by parallel CDMs independently are combined with the original RoI features to help classification. Experiments on MS-COCO 2017 benchmark dataset show that our approach brings continuous improvements for two-stage detectors.

Reinforced Palmprint Reconstruction Attacks in Biometric Systems

Biometric signals can be acquired with different sensors and recognized in secure identity management systems. However, it is vulnerable to various attacks that compromise the security management in many applications, such as industrial IoT. In a real-world scenario, the target template stored in the database of a biometric system can possibly be leaked, and then used to reconstruct a fake image to fool the biometric system. As such, many reconstruction attacks have been proposed, yet unsatisfactory naturalness, poor visual quality or incompleteness remains as major limitations. Thus, two reinforced palmprint reconstruction attacks are proposed. Any palmprint image, which can be easily obtained, is used as the initial image, and the region of interest is iteratively modified with deep reinforcement strategies to reduce the matching distance. In the first attack, Modification Constraint within Neighborhood (MCwN) limits the modification extent and suppresses the reckless modification. In the second attack, Batch Member Selection (BMS) selects the significant pixels (SPs) to compose the batch, which are simultaneously modified to a slighter extent to reduce the matching number and the visual-quality degradation. The two reinforced attacks can satisfy all the requirements, which cannot be simultaneously satisfied by the existing attacks. The thorough experiments demonstrate that the two attacks have a highly successful attack rate for palmprint systems based on the most state-of-the-art coding-based methods.

Midpalatal Suture Density CBCT Evaluation, Sex Gender and Growth Pattern Related Variability in 392 Adolescents Treated With Rapid Maxillary Expander Appliance

The aim of this paper was to evaluate the changes in the mean bone density values of the midpalatal suture in 392 young patients treated with the Rapid Palatal Expander appliance according to sex, gender, vertical and sagittal skeletal patterns. Materials and Methods. The evaluations were performed using the low-dose protocol cone-beam computed tomography scans at t0 (preoperatively) and t1 (1 year after the beginning of the therapy). The region of interest was used to calculate bone density in Hounsfield units (HU) in the area between the maxillary incisors. Results. CBCT scan data of 196 females and 196 males (mean age of 11,7 years) showed homogeneous and similar density values of the MPS at T0 (547.59 HU - 565.85 HU) and T1 (542.31 - 554.20 HU). Class III skeletal individuals showed a significant higher BD than the II class group at T0, but not at T1. Females showed significantly higher BD than males at t0 and t1. No significant differences were found between the other groups and between two-time points in terms of bone density values of the MPS. Conclusions. Females and III class groups showed significantly higher bone density values than males and II class, respectively. No statistically significant differences were found from T0 to T1 in any groups, suggesting that a similar rate of suture reorganization occurs after the use of the RPE, following reorganization and bone deposition along with the MPS.

System analysis of the sequencing quality of human whole exome samples on BGI NGS platform

Human exome sequencing is a classical method used in most medical genetic applications. The leaders in the field are the manufacturers of enrichment kits based on hybridization of cRNA or cDNA biotinylated probes specific for a genomic region of interest. Recently, the platforms manufactured by the Chinese company MGI Tech have become widespread in Europe and Asia. The reliability and quality of the obtained data are already beyond any doubt. However, only a few kits compatible with these sequencers can be used for such specific tasks as exome sequencing. We developed our own solution for library pre-capture pooling and exome enrichment with Agilent probes. In this work, using a set of the standard benchmark samples from the Platinum Genome collection, we demonstrate that the qualitative and quantitative parameters of our protocol which we called “RSMU_exome” exceed those of the MGI Tech kit. Our protocol allows for identifying more SNV and indels, generates fewer PCR duplicates, enables pooling of more samples in a single enrichment procedure, and requires less raw data to obtain results comparable with the MGI Tech's protocol. The cost of our protocol is also lower than that of MGI Tech's solution.

Extrastriatal Dopamine D2/3 Receptor Availability in Alcohol Use Disorder and Individuals at High Risk

<b><i>Introduction:</i></b> Reduced striatal dopamine D2/3 receptor availability in alcohol use disorder (AUD) has been demonstrated in recent clinical studies and meta-analyses. However, only a limited number of studies investigated extrastriatal D2/3 availability in AUD or in at-risk populations. In line with a dimensional understanding of addiction, extrastriatal dopaminergic neuroadaptations have been suggested to be relevant from a pathobiological perspective. <b><i>Methods:</i></b> We investigated D2/3 receptor availability via ¹⁸F-fallypride positron emission tomography applying a region of interest (ROI) approach. We selected ROIs for the prefrontal cortex (PFC) and the anterior cingulate cortex (ACC). Our sample included 19 healthy controls (low risk [LR]), 19 individuals at high risk (HR) to develop addiction, and 20 recently detoxified AUD patients. <b><i>Results:</i></b> We found significantly higher D2/3 receptor availability of HR compared to AUD in the left and right rostral ACC (rACC), as well as in the left ventrolateral PFC (vlPFC). We did not observe a significant difference between AUD and LR. After corrections for multiple comparisons none of the ROIs reached significance throughout the group comparison. The D2/3 receptor availability in the left rACC was inversely correlated with symptom severity assessed with the Alcohol Dependency Scale. <b><i>Discussion:</i></b> To our knowledge, the present work is the first study investigating extrastriatal D2/3 receptor availabilities in individuals at HR and patients with AUD. The observation that D2/3 receptor availabilities are highest in HR might suggest that their pathobiology differs from subjects with AUD. Future studies are necessary to clarify the intraindividual course of this biomarker over different disease stages and its possible role as a risk or protective factor.

PD1+ T-cells correlate with Nerve Fiber Density as a prognostic biomarker in patients with resected perihilar cholangiocarcinoma.

Background & Aims: Perihilar cholangiocarcinoma (pCCA) is a hepatobiliary malignancy. Nerve fiber invasion (NFI) shows cancer invading the nerve and is considered an aggressive feature. Nerve fiber density (NFD) consists of small nerve fibers without cancer invasion and is divided into high NFD (high numbers of small nerve fibers) or low NFD (low numbers of small nerve fibers). We aim to explore differences in immune cell populations and survival. Approach & Results: We applied multiplex immunofluorescence (mIF) on 47 pCCA surgically resected patients and investigated immune cell composition in the tumor microenvironment (TME) of nerve fiber phenotypes (NFI, high and low NFD). Group comparison was performed and overall survival (OS) was assessed. The NFI Region of Interest (ROI) was measured with highest CD68+ macrophage levels among 3 ROIs (NFI compared to tumor free p= 0.016 and to tumor p=0.034) and PD1 expression on CD8 and were more abundant in the tumor rather than NFI ROI (p= 0.004 and p= 0.0029 respectively). NFD compared to NFI, demonstrated co-expression of CD8+PD1+ as well as CD68+PD1+ to be significantly higher in high NFD patients (p= 0.027 and p= 0.044, respectively). The high NFD OS was 92 months median OS (95% CI:41-142), for low NFD 20 months ((95% CI: 4-36) and for NFI 19 months (95% CI 7-33). High NFD OS was significantly better compared to low NFD (p= 0.046) and NFI (p= 0.032). Conclusions: PD1+ T-cells correlate with high NFD as a prognostic biomarker, the biological pathway behind this needs to be investigated.

Automated histopathological evaluation of pterygium using artificial intelligence

PurposeThis study aimed to evaluate the efficacy of a new automated method for the evaluation of histopathological images of pterygium using artificial intelligence.MethodsAn in-house software for automated grading of histopathological images was developed. Histopathological images of pterygium (400 images from 40 patients) were analysed using our newly developed software. Manual grading (I–IV), labelled based on an established scoring system, served as the ground truth for training the four-grade classification models. Region of interest segmentation was performed before the classification of grades, which was achieved by the combination of expectation-maximisation and k-nearest neighbours. Fifty-five radiomic features extracted from each image were analysed with feature selection methods to examine the significant features. Five classifiers were evaluated for their ability to predict quantitative grading.ResultsAmong the classifier models applied for automated grading in this study, the bagging tree showed the best performance, with a 75.9% true positive rate (TPR) and 75.8% positive predictive value (PPV) in internal validation. In external validation, the method also demonstrated reproducibility, with an 81.3% TPR and 82.0% PPV for the average of four classification grades.ConclusionsOur newly developed automated method for quantitative grading of histopathological images of pterygium may be a reliable method for quantitative analysis of histopathological evaluation of pterygium.

Calculating earthquake damage building by building: the case of the city of Cologne, Germany

The creation of building exposure models for seismic risk assessment is frequently challenging due to the lack of availability of detailed information on building structures. Different strategies have been developed in recent years to overcome this, including the use of census data, remote sensing imagery and volunteered graphic information (VGI). This paper presents the development of a building-by-building exposure model based exclusively on openly available datasets, including both VGI and census statistics, which are defined at different levels of spatial resolution and for different moments in time. The initial model stemming purely from building-level data is enriched with statistics aggregated at the neighbourhood and city level by means of a Monte Carlo simulation that enables the generation of full realisations of damage estimates when using the exposure model in the context of an earthquake scenario calculation. Though applicable to any other region of interest where analogous datasets are available, the workflow and approach followed are explained by focusing on the case of the German city of Cologne, for which a scenario earthquake is defined and the potential damage is calculated. The resulting exposure model and damage estimates are presented, and it is shown that the latter are broadly consistent with damage data from the 1978 Albstadt earthquake, notwithstanding the differences in the scenario. Through this real-world application we demonstrate the potential of VGI and open data to be used for exposure modelling for natural risk assessment, when combined with suitable knowledge on building fragility and accounting for the inherent uncertainties.