AML-DECODER: Advanced Machine Learning for HD-sEMG Signal Classification-Decoding Lateral Epicondylitis in Forearm Muscles.

Background: Innovative algorithms for wearable devices and garments are critical for diagnosing and monitoring disease (such as lateral epicondylitis (LE)) progression. LE affects individuals across various professions and causes daily problems.

Methods: We analyzed signals from the forearm muscles of 14 healthy controls and 14 LE patients using high-density surface electromyography.

BioMOF@cellulose Glycerogel Scaffold with Multifold Bioactivity: Perspective in Bone Tissue Repair.

The development of new biomaterials for musculoskeletal tissue repair is currently an important branch in biomedicine research. The approach presented here is centered around the development of a prototypic synthetic glycerogel scaffold for bone regeneration, which simultaneously features therapeutic activity. The main novelty of this work lies in the combination of an open meso and macroporous nanocrystalline cellulose (NCC)-based glycerogel with a fully biocompatible microporous bioMOF system (CaSyr-1) composed of calcium ions and syringic acid.

Antibacterial and cytocompatible silver coating for titanium Boston Keratoprosthesis.

The Boston Keratoprosthesis (BKPro) serves as a medical solution for restoring vision in complex cases of corneal blindness. Comprising a front plate made of polymethylmethacrylate (PMMA) and a back plate of titanium (Ti), this device utilizes the beneficial biomaterial properties of Ti. While BKPro demonstrates promising retention rates, infection emerges as a significant concern that impacts its long-term efficacy.

Unlocking high-value football fans: unsupervised machine learning for customer segmentation and lifetime value.

Introduction: In the modern competitive landscape of football, clubs are increasingly leveraging data-driven decision-making to strengthen their commercial positions, particularly against rival clubs. The strategic allocation of resources to attract and retain profitable fans who exhibit long-term loyalty is crucial for advancing a club's marketing efforts. While the Recency, Frequency, and Monetary (RFM) customer segmentation technique has seen widespread application in various industries for predicting customer behavior, its adoption within the football industry remains underexplored.

Use of Beacon v2 for Improving Genomics Based Research in a Clinical Setting.

GA4GH has proposed the Beacon architecture as an interface to retrieve genomic information which also protects the privacy of the individuals. In this paper, we propose to adapt the Beacon Reference Implementation to the use case of a study comparing the susceptibility to the carcinogenic effects of tobacco. This analysis compares the germline of heavy smokers who have either never developed lung cancer or, on the contrary, have developed it at a young age.

Machine learning allows robust classification of visceral fat in women with obesity using common laboratory metrics.

The excessive accumulation and malfunctioning of visceral adipose tissue (VAT) is a major determinant of increased risk of obesity-related comorbidities. Thus, risk stratification of people living with obesity according to their amount of VAT is of clinical interest. Currently, the most common VAT measurement methods include mathematical formulae based on anthropometric dimensions, often biased by human measurement errors, bio-impedance, and image techniques such as X-ray absorptiometry (DXA) analysis, which requires specialized equipment.

Methodological biases in observational hospital studies of COVID-19 treatment effectiveness: pitfalls and potential.

Introduction: This study aims to discuss and assess the impact of three prevalent methodological biases: competing risks, immortal-time bias, and confounding bias in real-world observational studies evaluating treatment effectiveness. We use a demonstrative observational data example of COVID-19 patients to assess the impact of these biases and propose potential solutions.

Methods: We describe competing risks, immortal-time bias, and time-fixed confounding bias by evaluating treatment effectiveness in hospitalized patients with COVID-19.

Effect of Functionalization of Texturized Polypropylene Surface by Silanization and HBII-RGD Attachment on Response of Primary Abdominal and Vaginal Fibroblasts.

Soft tissue defects, such as incisional hernia or pelvic organ prolapse, are prevalent pathologies characterized by a tissue microenvironment rich in fragile and dysfunctional fibroblasts. Precision medicine could improve their surgical repair, currently based on polymeric materials. Nonetheless, biomaterial-triggered interventions need first a better understanding of the cell-material interfaces that truly consider the patients' biology.

Mechanical Properties of Bio-Based Sandwich Composites Containing Recycled Polymer Textiles.

In this paper, sandwich composites were produced by compression moulding techniques, and they consisted of regenerated cellulose fabric (rayon) and bio-based polypropylene (PP) to form facings, while virgin and recycled polyamide (PA) textiles were used as core materials. To compare the mechanical performance between sandwich composites and typical composite designs, a control composite was produced to deliver the same weight and fiber mass fraction from rayon and PP. To evaluate the influence of recycled textile on the mechanical properties of the composites, a series of flexural, low velocity impact (LVI) and tensile tests were performed.

Target trial emulation with multi-state model analysis to assess treatment effectiveness using clinical COVID-19 data.

Background: Real-world observational data are an important source of evidence on the treatment effectiveness for patients hospitalized with coronavirus disease 2019 (COVID-19). However, observational studies evaluating treatment effectiveness based on longitudinal data are often prone to methodological biases such as immortal time bias, confounding bias, and competing risks.

Methods: For exemplary target trial emulation, we used a cohort of patients hospitalized with COVID-19 (n = 501) in a single centre.

Target Trial Emulation Using Hospital-Based Observational Data: Demonstration and Application in COVID-19.

Methodological biases are common in observational studies evaluating treatment effectiveness. The objective of this study is to emulate a target trial in a competing risks setting using hospital-based observational data. We extend established methodology accounting for immortal time bias and time-fixed confounding biases to a setting where no survival information beyond hospital discharge is available: a condition common to coronavirus disease 2019 (COVID-19) research data.

A real-time and convex model for the estimation of muscle force from surface electromyographic signals in the upper and lower limbs.

Surface electromyography (sEMG) is a signal consisting of different motor unit action potential trains and records from the surface of the muscles. One of the applications of sEMG is the estimation of muscle force. We proposed a new real-time convex and interpretable model for solving the sEMG-force estimation.

Transcutaneous Cervical Spinal Cord Stimulation Combined with Robotic Exoskeleton Rehabilitation for the Upper Limbs in Subjects with Cervical SCI: Clinical Trial.

(1) Background: Restoring arm and hand function is a priority for individuals with cervical spinal cord injury (cSCI) for independence and quality of life. Transcutaneous spinal cord stimulation (tSCS) promotes the upper extremity (UE) motor function when applied at the cervical region. The aim of the study was to determine the effects of cervical tSCS, combined with an exoskeleton, on motor strength and functionality of UE in subjects with cSCI.

Kernel Density Estimation of Electromyographic Signals and Ensemble Learning for Highly Accurate Classification of a Large Set of Hand/Wrist Motions.

The performance of myoelectric control highly depends on the features extracted from surface electromyographic (sEMG) signals. We propose three new sEMG features based on the kernel density estimation. The trimmed mean of density (TMD), the entropy of density, and the trimmed mean absolute value of derivative density were computed for each sEMG channel.

Modeling of the Influence of Input AM Parameters on Dimensional Error and Form Errors in PLA Parts Printed with FFF Technology.

As is widely known, additive manufacturing (AM) allows very complex parts to be manufactured with porous structures at a relatively low cost and in relatively low manufacturing times. However, it is necessary to determine in a precise way the input values that allow better results to be obtained in terms of microgeometry, form errors, and dimensional error. In an earlier work, the influence of the process parameters on surface roughness obtained in fused filament fabrication (FFF) processes was analyzed.

Automatic Classification Between COVID-19 and Non-COVID-19 Pneumonia Using Symptoms, Comorbidities, and Laboratory Findings: The Khorshid COVID Cohort Study.

Coronavirus disease-2019, also known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was a disaster in 2020. Accurate and early diagnosis of coronavirus disease-2019 (COVID-19) is still essential for health policymaking. Reverse transcriptase-polymerase chain reaction (RT-PCR) has been performed as the operational gold standard for COVID-19 diagnosis.

Kinetics of the Thermal Degradation of Poly(lactic acid) and Polyamide Bioblends.

Poly(lactic acid) (PLA) and biosourced polyamide (PA) bioblends, with a variable PA weight content of 10-50%, were prepared by melt blending in order to overcome the high brittleness of PLA. During processing, the properties of the melt were stabilized and enhanced by the addition of a styrene-acrylic multi-functional-epoxide oligomeric reactive agent (SAmfE). The general analytical equation (GAE) was used to evaluate the kinetic parameters of the thermal degradation of PLA within bioblends.

To what extent the traffic restriction policies applied in Barcelona city can improve its air quality?

Barcelona city (Spain) is applying a series of traffic restriction measures that aim at renewing and reducing the amount of circulating vehicles to improve air quality. The measures include changes in the built environment to reduce private vehicle space in specific areas through the so-called "superblocks" and tactical urban planning actions, along with the implementation of a city-wide Low Emission Zone (LEZ) that restricts the entry of the most polluting vehicles to the city. Our study quantifies the impact of these measures in the greater area of Barcelona combining a coupled macroscopic traffic and pollutant emission model with a multi-scale air quality model.

Impact of the solvent composition on the structural and mechanical properties of customizable electrospun poly(vinylpyrrolidone) fiber mats.

The performance of fibrous membrane composites fabricated electrospinning is strongly influenced by the solution's properties, process variables and ambient conditions, although a precise mechanism for controlling the properties of the resulting composite has remained elusive. In this work, we focus on the fabrication of electrospun poly(vinylpyrrolidone) (PVP) fibers, by varying both the polymer concentration and the mixture of ethanol (EtOH) and dimethylformamide (DMF) used as solvent. The impact of the solvent composition on the structural properties is assessed by a combined experimental and theoretical approach, employing scanning electron microscopy (SEM), differential scanning calorimetry (DSC), rheology, Fourier-transform infrared spectroscopy (FTIR) and stress-strain curves obtained from tensile tests to characterize the fibrous membranes produced, and density functional theory (DFT) calculations to explain the solvent's affect on PVP crystallization.

Classification of psychiatric symptoms using deep interaction networks: the CASPIAN-IV study.

Identifying the possible factors of psychiatric symptoms among children can reduce the risk of adverse psychosocial outcomes in adulthood. We designed a classification tool to examine the association between modifiable risk factors and psychiatric symptoms, defined based on the Persian version of the WHO-GSHS questionnaire in a developing country. Ten thousand three hundred fifty students, aged 6-18 years from all Iran provinces, participated in this study.

Quantitative evaluation of trunk function and the StartReact effect during reaching in patients with cervical and thoracic spinal cord injury.

Impaired trunk stability is frequent in spinal cord injury (SCI), but there is a lack of quantitative measures for assessing trunk function. Our objectives were to: (a) evaluate trunk muscle activity and movement patterns during a reaching task in SCI patients, (b) compare the impact of cervical (cSCI) and thoracic (tSCI) injuries in trunk function, and (c) investigate the effects of a startling acoustic stimulus (SAS) in these patients.Electromyographic (EMG) and smartphone accelerometer data were recorded from 15 cSCI patients, nine tSCI patients, and 24 healthy controls, during a reaching task requiring trunk tilting.