Functional analysis of BARD1 missense variants in homology-directed repair and damage sensitivity

The BARD1 protein, which heterodimerizes with BRCA1, is encoded by a known breast cancer susceptibility gene. While several BARD1 variants have been identified as pathogenic, many more missense variants exist that do not occur frequently enough to assign a clinical risk. In this paper, whole exome sequencing of over 10,000 cancer samples from 33 cancer types identified from somatic mutations and loss of heterozygosity in tumors 76 potentially cancer-associated BARD1 missense and truncation variants. These variants were tested in a functional assay for homology-directed repair (HDR), as HDR deficiencies have been shown to correlate with clinical pathogenicity for BRCA1 variants. From these 76 variants, 4 in the ankyrin repeat domain and 5 in the BRCT domain were found to be non-functional in HDR. Two known benign variants were found to be functional in HDR, and three known pathogenic variants were non-functional, supporting the notion that the HDR assay can be used to predict the clinical risk of BARD1 variants. The identification of HDR-deficient variants in the ankyrin repeat domain indicates there are DNA repair functions associated with this domain that have not been closely examined. In order to examine whether BARD1-associated loss of HDR function results in DNA damage sensitivity, cells expressing non-functional BARD1 variants were treated with ionizing radiation or cisplatin. These cells were found to be more sensitive to DNA damage, and variations in the residual HDR function of non-functional variants did not correlate with variations in sensitivity. These findings improve the understanding of BARD1 functional domains in DNA repair and support that this functional assay is useful for predicting the cancer association of BARD1 variants.</div

Attention-Enhanced Deep Learning for Device-Free Through-the-Wall Presence Detection Using Indoor WiFi System

Accurate detection of human presence in indoor environments is important for various applications, such as energy management and security. In this paper, we propose a novel system for human presence detection using the channel state information (CSI) of WiFi signals. Our system named attention-enhanced deep learning for presence detection (ALPD) employs an attention mechanism to automatically select informative subcarriers from the CSI data and a bidirectional long short-term memory (LSTM) network to capture temporal dependencies in CSI. Additionally, we utilize a static feature to improve the accuracy of human presence detection in static states. We evaluate the proposed ALPD system by deploying a pair of WiFi access points (APs) for collecting CSI dataset, which is further compared with several benchmarks. The results demonstrate that our ALPD system outperforms the benchmarks in terms of accuracy, especially in the presence of interference. Moreover, bidirectional transmission data is beneficial to training improving stability and accuracy, as well as reducing the costs of data collection for training. Overall, our proposed ALPD system shows promising results for human presence detection using WiFi CSI signals

Effectiveness of influenza vaccination in patients with end-stage renal disease receiving hemodialysis: a population-based study.

BackgroundLittle is known on the effectiveness of influenza vaccine in ESRD patients. This study compared the incidence of hospitalization, morbidity, and mortality in end-stage renal disease (ESRD) patients undergoing hemodialysis (HD) between cohorts with and without influenza vaccination.MethodsWe used the insurance claims data from 1998 to 2009 in Taiwan to determine the incidence of these events within one year after influenza vaccination in the vaccine (N = 831) and the non-vaccine (N = 3187) cohorts. The vaccine cohort to the non-vaccine cohort incidence rate ratio and hazard ratio (HR) of morbidities and mortality were measured.ResultsThe age-specific analysis showed that the elderly in the vaccine cohort had lower hospitalization rate (100.8 vs. 133.9 per 100 person-years), contributing to an overall HR of 0.81 (95% confidence interval (CI) 0.72-0.90). The vaccine cohort also had an adjusted HR of 0.85 [95% CI 0.75-0.96] for heart disease. The corresponding incidence of pneumonia and influenza was 22.4 versus 17.2 per 100 person-years, but with an adjusted HR of 0.80 (95% CI 0.64-1.02). The vaccine cohort had lowered risks than the non-vaccine cohort for intensive care unit (ICU) admission (adjusted HR 0.20, 95% CI 0.12-0.33) and mortality (adjusted HR 0.50, 95% CI 0.41-0.60). The time-dependent Cox model revealed an overall adjusted HR for mortality of 0.30 (95% CI 0.26-0.35) after counting vaccination for multi-years.ConclusionsESRD patients with HD receiving the influenza vaccination could have reduced risks of pneumonia/influenza and other morbidities, ICU stay, hospitalization and death, particularly for the elderly

Observation of interlayer phonon modes in van der Waals heterostructures

We have investigated the vibrational properties of van der Waals heterostructures of monolayer transition metal dichalcogenides (TMDs), specifically MoS2/WSe2 and MoSe2/MoS2 heterobilayers as well as twisted MoS2 bilayers, by means of ultralow-frequency Raman spectroscopy. We discovered Raman features (at 30 ~ 40 cm-1) that arise from the layer-breathing mode (LBM) vibrations between the two incommensurate TMD monolayers in these structures. The LBM Raman intensity correlates strongly with the suppression of photoluminescence that arises from interlayer charge transfer. The LBM is generated only in bilayer areas with direct layer-layer contact and atomically clean interface. Its frequency also evolves systematically with the relative orientation between of the two layers. Our research demonstrates that LBM can serve as a sensitive probe to the interface environment and interlayer interactions in van der Waals materials

Contextual Label Projection for Cross-Lingual Structure Extraction

Translating training data into target languages has proven beneficial for cross-lingual transfer. However, for structure extraction tasks, translating data requires a label projection step, which translates input text and obtains translated labels in the translated text jointly. Previous research in label projection mostly compromises translation quality by either facilitating easy identification of translated labels from translated text or using word-level alignment between translation pairs to assemble translated phrase-level labels from the aligned words. In this paper, we introduce CLAP, which first translates text to the target language and performs contextual translation on the labels using the translated text as the context, ensuring better accuracy for the translated labels. We leverage instruction-tuned language models with multilingual capabilities as our contextual translator, imposing the constraint of the presence of translated labels in the translated text via instructions. We compare CLAP with other label projection techniques for creating pseudo-training data in target languages on event argument extraction, a representative structure extraction task. Results show that CLAP improves by 2-2.5 F1-score over other methods on the Chinese and Arabic ACE05 datasets.Comment: Work in Progres

Updated Perspectives on the Role of Biomechanics in COPD: Considerations for the Clinician

Patients with chronic obstructive pulmonary disease (COPD) demonstrate extra-pulmonary functional decline such as an increased prevalence of falls. Biomechanics offers insight into functional decline by examining mechanics of abnormal movement patterns. This review discusses biomechanics of functional outcomes, muscle mechanics, and breathing mechanics in patients with COPD as well as future directions and clinical perspectives. Patients with COPD demonstrate changes in their postural sway during quiet standing compared to controls, and these deficits are exacerbated when sensory information (eg, eyes closed) is manipulated. If standing balance is disrupted with a perturbation, patients with COPD are slower to return to baseline and their muscle activity is differential from controls. When walking, patients with COPD appear to adopt a gait pattern that may increase stability (eg, shorter and wider steps, decreased gait speed) in addition to altered gait variability. Biomechanical muscle mechanics (ie, tension, extensibility, elasticity, and irritability) alterations with COPD are not well documented, with relatively few articles investigating these properties. On the other hand, dyssynchronous motion of the abdomen and rib cage while breathing is well documented in patients with COPD. Newer biomechanical technologies have allowed for estimation of regional, compartmental, lung volumes during activity such as exercise, as well as respiratory muscle activation during breathing. Future directions of biomechanical analyses in COPD are trending toward wearable sensors, big data, and cloud computing. Each of these offers unique opportunities as well as challenges. Advanced analytics of sensor data can offer insight into the health of a system by quantifying complexity or fluctuations in patterns of movement, as healthy systems demonstrate flexibility and are thus adaptable to changing conditions. Biomechanics may offer clinical utility in prediction of 30-day readmissions, identifying disease severity, and patient monitoring. Biomechanics is complementary to other assessments, capturing what patients do, as well as their capability