Publications

Surface electromyography (sEMG) can be used to measure the electrical activity of the respiratory muscles. The possible applications of sEMG span from patients suffering from acute respiratory failure to patients receiving chronic home mechanical ventilation, to evaluate muscle function, titrate ventilatory support and guide treatment. However, sEMG is mainly used as a monitoring tool for research and its use in clinical practice is still limited-in part due to a lack of standardization and transparent reporting. During this round table meeting, recommendations on data acquisition, processing, interpretation, and potential clinical applications of respiratory sEMG were discussed. This paper informs the clinical researcher interested in respiratory muscle monitoring about the current state of the art on sEMG, knowledge gaps and potential future applications for patients with respiratory failure.

JTD Keywords: Acute respiratory failure, Artificial ventilation, Breathing muscle, Clinical monitoring, Clinical practice, Clinical research, Consensus development, Data interpretation, Disease exacerbation, Electrode positioning, Electrode removal, Electromyography, Force, Home care, Human, Humans, Information processing, Inspiratory muscle training, Intensive care unit, Knowledge gap, Long term care, Medical procedures, Muscle contraction, Muscle fatigue, Muscle function, Muscle training, Muscle, skeletal, Patient monitoring, Patient-ventilator asynchrony,muscle-activity,noninvasive ventilation,mechanical ventilation,human diaphragm,severe exacerbations,inspiratory muscles,asthmatic-children,electromyography,driv, Physiology, Prognosis, Quality of life, Reporting and data system, Respiratory failure, Respiratory muscles, Review, Signal processing, Skeletal muscle, Standardization, Surface electromyography, Time factor

Acute lymphoblastic leukemia (ALL) is the most common pediatric cancer, with survival rates exceeding 85%. However, 15% of patients will relapse; consequently, their survival rates decrease to below 50%. Therefore, several research and innovation studies are focusing on pediatric relapsed or refractory ALL (R/R ALL). Driven by this context and following the European strategic plan to implement precision medicine equitably, the Relapsed ALL Network (ReALLNet) was launched under the umbrella of SEHOP in 2021, aiming to connect bedside patient care with expert groups in R/R ALL in an interdisciplinary and multicentric network. To achieve this objective, a board consisting of experts in diagnosis, management, preclinical research, and clinical trials has been established. The requirements of treatment centers have been evaluated, and the available oncogenomic and functional study resources have been assessed and organized. A shipping platform has been developed to process samples requiring study derivation, and an integrated diagnostic committee has been established to report results. These biological data, as well as patient outcomes, are collected in a national registry. Additionally, samples from all patients are stored in a biobank. This comprehensive repository of data and samples is expected to foster an environment where preclinical researchers and data scientists can seek to meet the complex needs of this challenging population. This proof of concept aims to demonstrate that a network-based organization, such as that embodied by ReALLNet, provides the ideal niche for the equitable and efficient implementation of "what's next" in the management of children with R/R ALL.© 2023 Velasco, Bautista, Rubio, Aguilar, Rives, Dapena, Pérez, Ramirez, Saiz-Ladera, Izquierdo, Escudero, Camós, Vega-Garcia, Ortega, Hidalgo-Gómez, Palacio, Menéndez, Bueno, Montero, Romecín, Zazo, Alvarez, Parras, Ortega-Sabater, Chulián, Rosa, Cirillo, García, García, Manzano-Muñoz, Minguela and Fuster.

JTD Keywords: artificial intelligence, cancer registry, children, discovery, functional assay, outcomes, precision medicine, risk-factors, Artificial intelligence, B-cell precursor, Cancer registry, Functional assay, Precision medicine, Relapsed acute lymphoblastic leukemia

The etiology of dental caries remains poorly understood. With the advent of next-generation sequencing, a number of studies have focused on the microbial ecology of the disease. However, taxonomic associations with caries have not been consistent. Researchers have also pursued function-centric studies of the caries microbial communities aiming to identify consistently conserved functional pathways. A major question is whether changes in microbiome are a cause or a consequence of the disease. Thus, there is a critical need to define conserved functional signatures at the onset of dental caries.Since it is unethical to induce carious lesions clinically, we developed an innovative longitudinal ex-vivo model integrated with the advanced non-invasive multiphoton second harmonic generation bioimaging to spot the very early signs of dental caries, combined with 16S rRNA short amplicon sequencing and liquid chromatography-mass spectrometry-based targeted metabolomics.For the first time, we induced longitudinally monitored caries lesions validated with the scanning electron microscope. Consequently, we spotted the caries onset and, associated with it, distinguished five differentiating metabolites - Lactate, Pyruvate, Dihydroxyacetone phosphate, Glyceraldehyde 3-phosphate (upregulated) and Fumarate (downregulated). Those metabolites co-occurred with certain bacterial taxa; Streptococcus, Veillonella, Actinomyces, Porphyromonas, Fusobacterium, and Granulicatella, regardless of the abundance of other taxa.These findings are crucial for understanding the etiology and dynamics of dental caries, and devising targeted interventions to prevent disease progression.© 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

JTD Keywords: bacteria, biofilms, children, dental caries, generation, genomics, longitudinal model, metabolism, metabolomics, microscopy, non-invasive bioimaging, oral microbiome, plaque, restorations, signatures, Dental caries, Field-emission sem, Signatures