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Age- and sex-specific normative values of bone mineral density in the adult glenoid

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SIRT7 modulates the stability and activity of the renal K-Cl cotransporter KCC4 through deacetylation

Johan Auwerx, Dongryeol Ryu, Olivier Staub, Lilia Noriega Lopez

SIRT7 is a NAD(+)-dependent deacetylase that controls important aspects of metabolism, cancer, and bone formation. However, the molecular targets and functions of SIRT7 in the kidney are currently unknown. In silico analysis of kidney transcripts of the BX ...

2021

Instrumented 5-Time Sit-To-Stand Test: Parameters Predicting Serious Falls beyond the Duration of the Test

Kamiar Aminian, Anisoara Ionescu, Arash Atrsaei, Yves Henchoz

Background: Falls are a major cause of injuries in older adults. To evaluate the risk of falls in older adults, clinical assessments such as the 5-time sit-to-stand (5xSTS) test can be performed. The development of inertial measurement units (IMUs) has pro ...

2021

Smart Armband with Graphene Textile Electrodes for EMG-based Muscle Fatigue Monitoring

Ata Jedari Golparvar

We report the successful acquisition of surface electromyography (sEMG) signals from an intelligent armband and its application in localized muscle fatigue monitoring with a costume-designed, small-scale front-end readout circuitry. The correlation coeffic ...

IEEE2021

A Study on MoS2 Nanolayer Coated Etched Fiber Bragg Grating Strain Sensor

Suneetha Sebastian

In this paper, we report on the comprehensive study on Molybdenum disulfide (MoS2) nanolayer coated etched Fiber Bragg Grating (eFBG) strain sensor. MoS2 nanolayer is coated using Physical Vapor Deposition (PVD) of Molybdenum (Mo) on eFBGs followed by sulf ...

2021

Utterance Verification-Based Dysarthric Speech Intelligibility Assessment Using Phonetic Posterior Features

Mathew Magimai Doss, Julian David Fritsch

In the literature, the task of dysarthric speech intelligibility assessment has been approached through development of different low-level feature representations, subspace modeling, phone confidence estimation or measurement of automatic speech recognitio ...

IEEE Institute of Electrical and Electronics Engineers2021

Atomistic simulation and electron microscopy to characterize grain boundaries in doped beta-tricalcium phosphate ceramics

Gabrielle Anne Laguisma Sblendorio

The limitations and potential complications correlated with autogenous bone grafts have raised interest in the development of synthetic bone graft substitutes. ß-tricalcium phosphate (ß-TCP) is one of the most promising materials for synthetic bone graft s ...

EPFL2021

Geodesic Distance on Optimally Regularized Functional Connectomes Uncovers Individual Fingerprints

Enrico Amico

Background: Functional connectomes (FCs) have been shown to provide a reproducible individual fingerprint, which has opened the possibility of personalized medicine for neuro/psychiatric disorders. Thus, developing accurate ways to compare FCs is essential ...

MARY ANN LIEBERT, INC2021

A Correlation-Based Electromagnetic Time Reversal Technique to Locate Indoor Transient Radiation Sources

Farhad Rachidi-Haeri, Marcos Rubinstein, Zhaoyang Wang, Qi Li

To overcome the multipath interference in locating transient electromagnetic (EM) radiation sources in an indoor environment, we propose a criterion that calculates the correlation between back-propagated signals from observation points, to be used in EM t ...

Institute of Electrical and Electronics Engineers2021

Estimation of Left Ventricular End-Systolic Elastance From Brachial Pressure Waveform via Deep Learning

Nikolaos Stergiopoulos, Georgios Rovas, Vasiliki Bikia, Stamatia Zoi Pagoulatou, Marija Lazaroska

Determination of left ventricular (LV) end-systolic elastance (E- es ) is of utmost importance for assessing the cardiac systolic function and hemodynamical state in humans. Yet, the clinical use of E- es is not established due to the invasive nature and h ...

FRONTIERS MEDIA SA2021

Deep learning for the rapid automatic quantification and characterization of rotator cuff muscle degeneration from shoulder CT datasets

Alexandre Terrier, Alain Farron, Elham Taghizadeh, Philippe Büchler

Objectives This study aimed at developing a convolutional neural network (CNN) able to automatically quantify and characterize the level of degeneration of rotator cuff (RC) muscles from shoulder CT images including muscle atrophy and fatty infiltration. M ...

SPRINGER2021

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SIRT7 modulates the stability and activity of the renal K-Cl cotransporter KCC4 through deacetylation

Johan Auwerx, Dongryeol Ryu, Olivier Staub, Lilia Noriega Lopez

2021

Smart Armband with Graphene Textile Electrodes for EMG-based Muscle Fatigue Monitoring

Ata Jedari Golparvar

IEEE2021

Atomistic simulation and electron microscopy to characterize grain boundaries in doped beta-tricalcium phosphate ceramics

Gabrielle Anne Laguisma Sblendorio

EPFL2021

Estimation of Left Ventricular End-Systolic Elastance From Brachial Pressure Waveform via Deep Learning

Nikolaos Stergiopoulos, Georgios Rovas, Vasiliki Bikia, Stamatia Zoi Pagoulatou, Marija Lazaroska

FRONTIERS MEDIA SA2021

Deep learning for the rapid automatic quantification and characterization of rotator cuff muscle degeneration from shoulder CT datasets

Alexandre Terrier, Alain Farron, Elham Taghizadeh, Philippe Büchler

SPRINGER2021