Delineation of intracavitary electrograms for the automatic quantification of decrement-evoked potentials in the coronary sinus with deep-learning techniques.

Cardiac arrhythmias cause depolarization waves to conduct unevenly on the myocardial surface, potentially delaying local components with respect to a previous beat when stimulated at faster frequencies. Despite the diagnostic value of localizing the distinct local electrocardiogram (EGM) components for identifying regions with decrement-evoked potentials (DEEPs), current software solutions do not perform automatic signal quantification. Electrophysiologists must manually measure distances on the EGM signals to assess the existence of DEEPs during pacing or extra-stimuli protocols. In this work, we present a deep learning (DL)-based algorithm to identify decrement in atrial components (measured in the coronary sinus) with respect to their ventricular counterparts from EGM signals, for disambiguating between accessory pathways (APs) and atrioventricular re-entrant tachycardias (AVRTs). Several U-Net and W-Net neural networks with different configurations were trained on a private dataset of signals from the coronary sinus (312 EGM recordings from 77 patients who underwent AP or AVRT ablation). A second, separate dataset was annotated for clinical validation, with clinical labels associated to EGM fragments in which decremental conduction was elucidated. To alleviate data scarcity, a synthetic data augmentation method was developed for generating EGM recordings. Moreover, two novel loss functions were developed to minimize false negatives and delineation errors. Finally, the addition of self-attention mechanisms and their effect on model performance was explored. The best performing model was a W-Net model with 6 levels, optimized solely with the Dice loss. The model obtained precisions of 91.28%, 77.78% and of 100.0%, and recalls of 94.86%, 95.25% and 100.0% for localizing local field, far field activations, and extra-stimuli, respectively. The clinical validation model demonstrated good overall agreement with respect to the evaluation of decremental properties. When compared to the criteria of electrophysiologists, the automatic exclusion step reached a sensitivity of 87.06% and a specificity of 97.03%. Out of the non-excluded signals, a sensitivity of 96.77% and a specificity of 95.24% was obtained for classifying them into decremental and non-decremental potentials. Current results show great promise while being, to the best of our knowledge, the first tool in the literature allowing the delineation of all local components present in an EGM recording. This is of capital importance at advancing processing for cardiac electrophysiological procedures and reducing intervention times, as many diagnosis procedures are performed by comparing segments or late potentials in subsequent cardiac cycles.

Cost of SARS-CoV-2 self-test distribution programmes by different modalities: a micro-costing study in five countries (Brazil, Georgia, Malaysia, Ethiopia and the Philippines).

OBJECTIVE: Diagnostic testing is an important tool to combat the COVID-19 pandemic, yet access to and uptake of testing vary widely 3 years into the pandemic. The WHO recommends the use of COVID-19 self-testing as an option to help expand testing access. We aimed to calculate the cost of providing COVID-19 self-testing across countries and distribution modalities. DESIGN: We estimated economic costs from the provider perspective to calculate the total cost and the cost per self-test kit distributed for three scenarios that differed by costing period (pilot, annual), the number of tests distributed (actual, planned, scaled assuming an epidemic peak) and self-test kit costs (pilot purchase price, 50% reduction). SETTING: We used data collected between August and December 2022 in Brazil, Georgia, Malaysia, Ethiopia and the Philippines from pilot implementation studies designed to provide COVID-19 self-tests in a variety of settings-namely, workplace and healthcare facilities. RESULTS: Across all five countries, 173 000 kits were distributed during pilot implementation with the cost/test distributed ranging from $2.44 to $12.78. The cost/self-test kit distributed was lowest in the scenario that assumed implementation over a longer period (year), with higher test demand (peak) and a test kit price reduction of 50% ($1.04-3.07). Across all countries and scenarios, test procurement occupied the greatest proportion of costs: 58-87% for countries with off-site self-testing (outside the workplace, for example, home) and 15-50% for countries with on-site self-testing (at the workplace). Staffing was the next key cost driver, particularly for distribution modalities that had on-site self-testing (29-35%) versus off-site self-testing (7-27%). CONCLUSIONS: Our results indicate that it is likely to cost between $2.44 and $12.78 per test to distribute COVID-19 self-tests across common settings in five heterogeneous countries. Cost-effectiveness analyses using these results will allow policymakers to make informed decisions on optimally scaling up COVID-19 self-test distribution programmes across diverse settings and evolving needs.

Automatic and interpretable prediction of the site of origin in outflow tract ventricular arrhythmias: machine learning integrating electrocardiograms and clinical data.

The treatment of outflow tract ventricular arrhythmias (OTVA) through radiofrequency ablation requires the precise identification of the site of origin (SOO). Pinpointing the SOO enhances the likelihood of a successful procedure, reducing intervention times and recurrence rates. Current clinical methods to identify the SOO are based on qualitative analysis of pre-operative electrocardiograms (ECG), heavily relying on physician's expertise. Although computational models and machine learning (ML) approaches have been proposed to assist OTVA procedures, they either consume substantial time, lack interpretability or do not use clinical information. Here, we propose an alternative strategy for automatically predicting the ventricular origin of OTVA patients using ML. Our objective was to classify ventricular (left/right) origin in the outflow tracts (LVOT and RVOT, respectively), integrating ECG and clinical data from each patient. Extending beyond differentiating ventricle origin, we explored specific SOO characterization. Utilizing four databases, we also trained supervised learning models on the QRS complexes of the ECGs, clinical data, and their combinations. The best model achieved an accuracy of 89%, highlighting the significance of precordial leads V1-V4, especially in the R/S transition and initiation of the QRS complex in V2. Unsupervised analysis revealed that some origins tended to group closer than others, e.g., right coronary cusp (RCC) with a less sparse group than the aortic cusp origins, suggesting identifiable patterns for specific SOOs.

Electrophysiological biomarkers in dual pathology.

INTRODUCTION: The co-occurrence of substance use disorder with at least one other mental disorder is called dual pathology, which in turn is characterised by heterogeneous symptoms that are difficult to diagnose and have a poor response to treatment. For this reason, the identification and validation of biomarkers is necessary. Within this group, possible electroencephalographic biomarkers have been reported to be useful in diagnosis, treatment and follow-up, both in neuropsychiatric conditions and in substance use disorders. This article aims to review the existing literature on electroencephalographic biomarkers in dual pathology. METHODS: A narrative review of the literature. A bibliographic search was performed on the PubMed, Science Direct, OVID, BIREME and Scielo databases, with the keywords: electrophysiological biomarker and substance use disorder, electrophysiological biomarker and mental disorders, biomarker and dual pathology, biomarker and substance use disorder, electroencephalography, and substance use disorder or comorbid mental disorder. RESULTS: Given the greater amount of literature found in relation to electroencephalography as a biomarker of mental illness and substance use disorders, and the few articles found on dual pathology, the evidence is organised as a biomarker in psychiatry for the diagnosis and prediction of risk and as a biomarker for dual pathology. CONCLUSIONS: Although the evidence is not conclusive, it suggests the existence of a subset of sites and mechanisms where the effects of psychoactive substances and the neurobiology of some mental disorders could overlap or interact.

Evaluation of a Training Program on Gender Mainstreaming in Health Research Evaluation at the Senegalese National Research Ethics Committee.

Health research must be of high ethical and scientific quality and consider the needs and experiences of women, men, and nonbinary individuals. National Research Ethics Committees (RECs) are in a strategic position to impede sex- and gender-blind research. In 2020 and 2021, training programs on gender mainstreaming and sex and gender approaches in research evaluation were launched in Senegal. They were evaluated through a mixture of qualitative and quantitative methods. Knowledge acquisition was 16.67%, 8.54%, and 28.42% for the trainees of 2021, 2020, and those who attended the training in both years, respectively. Gender mainstreaming was reported as pertinent in research ethics by 74% of participants. This training is expected to catalyze gender-transformative research ethics in West Africa.

Self-Consistent Field Approach for the Variational Quantum Eigensolver: Orbital Optimization Goes Adaptive.

We present a self-consistent field (SCF) approach within the adaptive derivative-assembled problem-tailored ansatz variational quantum eigensolver (ADAPT-VQE) framework for efficient quantum simulations of chemical systems on near-term quantum computers. To this end, our ADAPT-VQE-SCF approach combines the idea of generating an ansatz with a small number of parameters, resulting in shallow-depth quantum circuits with a direct minimization of an energy expression that is correct to second order with respect to changes in the molecular orbital basis. Our numerical analysis, including calculations for the transition-metal complex ferrocene [Fe (C5H5)2], indicates that convergence in the self-consistent orbital optimization loop can be reached without a considerable increase in the number of two-qubit gates in the quantum circuit by comparison to a VQE optimization in the initial molecular orbital basis. Moreover, the orbital optimization can be carried out simultaneously within each iteration of the ADAPT-VQE cycle. ADAPT-VQE-SCF thus allows us to implement a routine analogous to the complete active space SCF, a cornerstone of state-of-the-art computational chemistry, in a hardware-efficient manner on near-term quantum computers. Hence, ADAPT-VQE-SCF paves the way toward a paradigm shift for quantitative quantum-chemistry simulations on quantum computers by requiring fewer qubits and opening up for the use of large and flexible atomic orbital basis sets in contrast to earlier methods that are predominantly based on the idea of full active spaces with minimal basis sets.

Implementing a pilot study of COVID-19 self-testing in high-risk populations and remote locations: results and lessons learnt.

BACKGROUND: Rapid antigen-detection tests for SARS-CoV-2 self-testing represent a useful tool for pandemic control and expanding access to community-level case screening. COVID-19 self-tests have been extensively used in high-income countries since 2021; however, their introduction and programmatic implementation in low- and middle-income countries was delayed. We aimed to identify and continuously improve a weekly COVID-19 self-testing model among staff at healthcare facilities and schools. METHODS: This mixed-methods, observational prospective study was conducted in 5 healthcare centres and 24 schools in Georgia, between June and December 2022. The study comprised the integration of COVID-19 self-testing into the national mandatory testing programme for high-risk groups, with primary distribution of self-tests among staff performed weekly, plus secondary distribution to their household members. These use cases were selected because NCDC was seeking to strengthen their already strong weekly testing programme, by investigating self-testing to ease the burden of testing in the healthcare system. Online surveys and semi-structured interviews were used for data collection. RESULTS: In total, 2156 participants were enrolled (1963 female, 72%). At baseline and mid- and end-points, 88%, 97% and 99%, respectively, of participants agreed/strongly agreed they would self-test. Similarly, the majority were willing to report their self-testing results (88%, 98% and 96% at baseline and mid- and end-points, respectively). Weekly reporting of test results to the national COVID-19 database was high during all the implementation. There were 622 COVID-19 positive results reported, and linked to care, from 601 individuals (282 participants and 319 household members). Findings from qualitative interviews showed great satisfaction with self-testing for its convenience, ease of use, trust in the results, no need to travel for diagnostics, and increased perception of safety. CONCLUSIONS: Our findings contribute to the evidence-base regarding self-testing strategies conducted via workplaces and secondary distribution to households. Willingness to perform a COVID-19 self-test increased after implementation. This pilot enhanced pandemic preparedness through expansion of the national self-testing reporting system, development of communications materials, changes in the national legal framework and coordination mechanisms, and improved perceptions around self-care in the community. The lessons learnt can inform operational aspects of the introduction and scale-up of self-care strategies.

User requirements for non-invasive and minimally invasive glucose self-monitoring devices in low-income and middle-income countries: a qualitative study in Kyrgyzstan, Mali, Peru and Tanzania.

AIMS: Development of non-invasive and minimally invasive glucose monitoring devices (NI-MI-GMDs) generally takes place in high-income countries (HICs), with HIC's attributes guiding product characteristics. However, people living with diabetes (PLWD) in low-income and middle-income countries (LMICs) encounter different challenges to those in HICs. This study aimed to define requirements for NI-MI-GMDs in LMICs to inform a target product profile to guide development and selection of suitable devices. METHODS: This was a multiple-methods, exploratory, qualitative study conducted in Kyrgyzstan, Mali, Peru and Tanzania. Interviews and group discussions/activities were conducted with healthcare workers (HCWs), adults living with type 1 (PLWD1) or type 2 diabetes (PLWD2), adolescents living with diabetes and caregivers. RESULTS: Among 383 informants (90 HCW, 100 PLWD1, 92 PLWD2, 24 adolescents, 77 caregivers), a range of differing user requirements were reported, including preferences for area of glucose measurement, device attachment, data display, alert type and temperature sensitivity. Willingness to pay varied across countries; common requirements included ease of use, a range of guiding functions, the possibility to attach to a body part of choice and a cost lower than or equal to current glucose self-monitoring. CONCLUSIONS: Ease-of-use and affordability were consistently prioritised, with broad functionality required for alarms, measurements and attachment possibilities. Perspectives of PLWD are crucial in developing a target product profile to inform characteristics of NI-MI-GMDs in LMICs. Stakeholders must consider these requirements to guide development and selection of NI-MI-GMDs at country level, so that devices are fit for purpose and encourage frequent glucose monitoring among PLWD in these settings.

Improved production of the antidiabetic metabolite montbretin A in Nicotiana benthamiana: discovery, characterization, and use of Crocosmia shikimate shunt genes.

The plant-specialized metabolite montbretin A (MbA) is being developed as a new treatment option for type-2 diabetes, which is among the ten leading causes of premature death and disability worldwide. MbA is a complex acylated flavonoid glycoside produced in small amounts in below-ground organs of the perennial plant Montbretia (Crocosmia × crocosmiiflora). The lack of a scalable production system limits the development and potential application of MbA as a pharmaceutical or nutraceutical. Previous efforts to reconstruct montbretin biosynthesis in Nicotiana benthamiana (Nb) resulted in low yields of MbA and higher levels of montbretin B (MbB) and montbretin C (MbC). MbA, MbB, and MbC are nearly identical metabolites differing only in their acyl moieties, derived from caffeoyl-CoA, coumaroyl-CoA, and feruloyl-CoA, respectively. In contrast to MbA, MbB and MbC are not pharmaceutically active. To utilize the montbretia caffeoyl-CoA biosynthesis for improved MbA engineering in Nb, we cloned and characterized enzymes of the shikimate shunt of the general phenylpropanoid pathway, specifically hydroxycinnamoyl-CoA: shikimate hydroxycinnamoyl transferase (CcHCT), p-coumaroylshikimate 3'-hydroxylase (CcC3'H), and caffeoylshikimate esterase (CcCSE). Gene expression patterns suggest that CcCSE enables the predominant formation of MbA, relative to MbB and MbC, in montbretia. This observation is supported by results from in vitro characterization of CcCSE and reconstruction of the shikimate shunt in yeast. Using CcHCT together with montbretin biosynthetic genes in multigene constructs resulted in a 30-fold increase of MbA in Nb. This work advances our understanding of the phenylpropanoid pathway and features a critical step towards improved MbA production in bioengineered Nb.

Loss of sodium current caused by a Brugada syndrome-associated variant is determined by patient-specific genetic background.

BACKGROUND: Brugada syndrome (BrS) is an inherited cardiac arrhythmogenic disease that predisposes patients to sudden cardiac death. It is associated with mutations in SCN5A, which encodes the cardiac sodium channel alpha subunit (NaV1.5). BrS-related mutations have incomplete penetrance and variable expressivity within families. OBJECTIVE: The purpose of this study was to determine the role of patient-specific genetic background on the cellular and clinical phenotype among carriers of NaV1.5_p.V1525M. METHODS: We studied sodium currents from patient-specific human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) and heterologously transfected human embryonic kidney (HEK) tsA201 cells using the whole-cell patch-clamp technique. We determined gene and protein expression by quantitative polymerase chain reaction, RNA sequencing, and western blot and performed a genetic panel for arrhythmogenic diseases. RESULTS: Our results showed a large reduction in INa density in hiPSC-CM derived from 2 V1525M single nucleotide variant (SNV) carriers compared with hiPSC-CM derived from a noncarrier, suggesting a dominant-negative effect of the NaV1.5_p.V1525M channel. INa was not affected in hiPSC-CMs derived from a V1525M SNV carrier who also carries the NaV1.5_p.H558R polymorphism. Heterozygous expression of V1525M in HEK-293T cells produced a loss of INa function, not observed when this variant was expressed together with H558R. In addition, the antiarrhythmic drug mexiletine rescued INa function in hiPSC-CM. SCN5A expression was increased in the V1525M carrier who also expresses NaV1.5_p.H558R. CONCLUSION: Our results in patient-specific hiPSC-CM point to a dominant-negative effect of NaV1.5_p.V1525M, which can be reverted by the presence of NaV1.5_p.H558R. Overall, our data points to a role of patient-specific genetic background as a determinant for incomplete penetrance in BrS.

Exploring novel organocatalytic-acetylated pea starch blends in the development of hot-pressed bioplastics.

Acetylated starch shows enhanced thermal stability and moisture resistance, but its compatibilization with other more hydrophilic polysaccharides remains poor or unknown. In this study, the feasibility of thermomechanically compounding organocatalytically acetylated pea starch (APS), produced at two different degrees of substitution with alkanoyl groups (DSacyl, 0.39 and 1.00), with native pea starch (NPS), high (HMP) and low methoxyl (LMP) citrus pectin, and sugar beet pectin (SBP, a naturally acetylated pectin) for developing hot-pressed bioplastics was studied. Generally, APS decreased hydrogen bonding (ATR-FTIR) and crystallinity (XRD) of NPS films at different levels, depending on its DSacyl. The poor compatibility between APS and NPS or HMP was confirmed by ATR-FTIR imaging. Contrariwise, APS with DSacyl 1 was effectively thermomechanically mixed with the acetylated SBP matrix, maintaining homogeneous distribution within it (ATR-FTIR imaging). APS (any DSacyl) significantly increased the visible/UV light opacity of NPS-based films and decreased their water vapor transmission rate (WVTR, by ca. 11 %) and surface water wettability (by ca. 3 times). In comparison to NPS-APS films, pectin-APS showed higher visible/UV light absorption, tensile strength (ca.2.9-4.4 vs ca.2.4 MPa), and Young's modulus (ca.96-116 vs ca.60-70 MPa), with SBP-APS presenting significantly lower water wettability than the rest of the films.

Generation of the induced pluripotent stem cell line ESi108-A from a familial atrial fibrillation patient.

Tissue-specific cells differentiated from patient-derived human induced pluripotent stem cells (hiPSC) are a relevant cellular model to study several diseases. We obtained a hiPSC line from skin fibroblasts of a patient affected by familial atrial fibrillation by nucleofection of non-integrating episomal vectors. The resulting hiPSC line displays a normal karyotype, expresses pluripotency surface markers and pluripotency genes, and differentiates into cells of the 3 germ layers. Therefore, it represents a reliable model to study the disease in a physiologically relevant cellular environment.

Immune cell kinetics and antibody response in COVID-19 patients with low-count monoclonal B-cell lymphocytosis.

Low-count monoclonal B-cell lymphocytosis (MBLlo ) has been associated with an underlying immunodeficiency and has recently emerged as a new risk factor for severe COVID-19. Here, we investigated the kinetics of immune cell and antibody responses in blood during COVID-19 of MBLlo versus non-MBL patients. For this study, we analyzed the kinetics of immune cells in blood of 336 COVID-19 patients (74 MBLlo and 262 non-MBL), who had not been vaccinated against SARS-CoV-2, over a period of 43 weeks since the onset of infection, using high-sensitivity flow cytometry. Plasma levels of anti-SARS-CoV-2 antibodies were measured in parallel by ELISA. Overall, early after the onset of symptoms, MBLlo COVID-19 patients showed increased neutrophil, monocyte, and particularly, plasma cell (PC) counts, whereas eosinophil, dendritic cell, basophil, and lymphocyte counts were markedly decreased in blood of a variable percentage of samples, and with a tendency toward normal levels from week +5 of infection onward. Compared with non-MBL patients, MBLlo COVID-19 patients presented higher neutrophil counts, together with decreased pre-GC B-cell, dendritic cell, and innate-like T-cell counts. Higher PC levels, together with a delayed PC peak and greater plasma levels of anti-SARS-CoV-2-specific antibodies (at week +2 to week +4) were also observed in MBLlo patients. In summary, MBLlo COVID-19 patients share immune profiles previously described for patients with severe SARS-CoV-2 infection, associated with a delayed but more pronounced PC and antibody humoral response once compared with non-MBL patients.

Quasi-Diamond Platelet-Shaped Zinc Oxide Nanostructures Display Enhanced Antibacterial Activity.

The current study compares the antibacterial activity of zinc oxide nanostructures (neZnO). For this purpose, two bacterial strains, Escherichia coli (ATCC 4157) and Staphylococcus aureus (ATCC 29213) were challenged in room light conditions with the aforementioned materials. Colloidal and hydrothermal methods were used to obtain the quasi-round and quasi-diamond platelet-shape nanostructures. Thus, the oxygen vacancy (VO ) effects on the surface of neZnO are also considered to assess its effects on antibacterial activity. The neZnO characterization was achieved by X-ray diffraction (XRD), a selected area electron diffraction (SAED) and Raman spectroscopy. The microstructural effects were monitored by scanning electron microscopy (SEM) and transmission electron microscopy (TEM). Furthermore, optical absorption ultraviolet visible spectrophotometry (UV-Vis) and X-ray photoelectron spectroscopy (XPS) analyses complement the physical characterization of these nanostructures; neZnO caused 50 % inhibition (IC50 ) at concentrations from 0.064 to 0.072 mg/mL for S. aureus and from 0.083 to 0.104 mg/mL for E. coli, indicating an increase in activity against S. aureus compared to E. coli. Consequently, quasi-diamond platelet-shaped nanostructures (average particle size of 377.6±10 nm) showed enhanced antibacterial activity compared to quasi-round agglomerated particles (average size of 442.8±12 nm), regardless of Vo presence or absence.

Real-life evidence about the use of intravenous brivaracetam in urgent seizures: The BRIV-IV study.

PURPOSE: Urgent seizures are a medical emergency for which new therapies are still needed. This study evaluated the use of intravenous brivaracetam (IV-BRV) in an emergency setting in clinical practice. METHODS: BRIV-IV was a retrospective, multicenter, observational study. It included patients ≥18 years old who were diagnosed with urgent seizures (including status epilepticus (SE), acute repetitive seizures, and high-risk seizures) and who were treated with IV-BRV according to clinical practice in 14 hospital centers. Information was extracted from clinical charts and included in an electronic database. Primary effectiveness endpoints included the rate of IV-BRV responder patients, the rate of patients with a sustained response without seizure relapse in 12 h, and the time between IV-BRV administration and clinical response. Primary safety endpoints were comprised the percentage of patients with adverse events and those with adverse events leading to discontinuation. RESULTS: A total of 156 patients were included in this study. The mean age was 57.7 ± 21.5 years old with a prior diagnosis of epilepsy for 57.1% of patients. The most frequent etiologies were brain tumor-related (18.1%) and vascular (11.2%) epilepsy. SE was diagnosed in 55.3% of patients. The median time from urgent seizure onset to IV treatment administration was 60.0 min (range: 15.0-360.0), and the median time from IV treatment to IV-BRV was 90.0 min (range: 30.0-2400.0). Regarding dosage, the mean bolus infusion was 163.0 ± 73.0 mg and the mean daily dosage was 195.0 ± 87.0 mg. A total of 77.6% of patients responded to IV-BRV (66.3% with SE vs. 91% other urgent seizures) with a median response time of 30.0 min (range: 10.0-60.0). A sustained response was achieved in 62.8% of patients. However, adverse events were reported in 14.7%, which were predominantly somnolence and fatigue, with 4.5% leading to discontinuation. Eighty-six percent of patients were discharged with oral brivaracetam. CONCLUSION: IV-BRV in emergency settings was effective, and tolerability was good for most patients. However, a larger series is needed to confirm the outcomes.

Preparation and characterization of self-standing biofilms from compatible pectin/starch blends: Effect of pectin structure.

Pectin structure-miscibility-functionality relationships in starch films remain unknown. In this study, five citrus pectins (CPs) with 17 to 63 % of degree of methyl esterification (DM) and sugar beet pectin (SBP, rich in acetyl moieties and rhamnogalacturonan-I domains) were investigated for composition and structure and, further, blended with pea starch (3:1 starch-pectin weight ratio) to fabricate self-standing films. The incorporation of pectin resulted in a two- to three-fold increase in tensile strength and Young's modulus (up to 52.2 and 1837 MPa, respectively, using CP with low DM) without compromising elongation at break. Starch-SBP films presented the lowest strength among pectin films. Lower film moisture and water vapor permeability were attained with CP of high DM, or with SBP, whereas surface wettability was explained by counteracting factors affecting film compositional heterogeneity. Films made with high methoxyl CP, or with SBP, showed lower overall H-bonding (FTIR) and starch crystallinity (XRD). A DM above 57 % negatively affected the mixing and interfacial adhesion of pectin with starch, as shown by Attenuated Total Reflection-FTIR imaging. Pectins with the lowest purity, presumably with the greatest content in xyloglucan, as suggested by HPAEC, presented ~20 % higher elongation at break than the other films.

Artificial intelligence for detection of ventricular oversensing: Machine learning approaches for noise detection within nonsustained ventricular tachycardia episodes remotely transmitted by pacemakers and implantable cardioverter-defibrillators.

BACKGROUND: Pacemakers (PMs) and implantable cardioverter-defibrillators (ICDs) increasingly automatically record and remotely transmit nonsustained ventricular tachycardia (NSVT) episodes, which may reveal ventricular oversensing. OBJECTIVES: We aimed to develop and validate a machine learning algorithm that accurately classifies NSVT episodes transmitted by PMs and ICDs in order to lighten health care workload burden and improve patient safety. METHODS: PMs or ICDs (Boston Scientific, St Paul, MN) from 4 French hospitals with ≥1 transmitted NSVT episode were split into 3 subgroups: training set, validation set, and test set. Each NSVT episode was labeled as either physiological or nonphysiological. Four machine learning algorithms-2DTF-CNN, 2D-DenseNet, 2DTF-VGG, and 1D-AgResNet-were developed using training and validation data sets. Accuracies of the classifiers were compared with an analysis of the remote monitoring team of the Bordeaux University Hospital using F2 scores (favoring sensitivity over predictive positive value) using an independent test set. RESULTS: A total of 807 devices transmitted 10,471 NSVT recordings (82% ICD; 18% PM), of which 87 devices (10.8%) transmitted 544 NSVT recordings with nonphysiological signals. The classification by the remote monitoring team resulted in an F2 score of 0.932 (sensitivity 95%; specificity 99%) The 4 machine learning algorithms showed high and comparable F2 scores (2DTF-CNN: 0.914; 2D-DenseNet: 0.906; 2DTF-VGG: 0.863; 1D-AgResNet: 0.791), and only 1D-AgResNet had significantly different labeling from that of the remote monitoring team. CONCLUSION: Machine learning algorithms were accurate in detecting nonphysiological signals within electrograms transmitted by PMs and ICDs. An artificial intelligence approach may render remote monitoring less resourceful and improve patient safety.

SARS-CoV-2 self-testing in Peru: a cross-sectional survey of values and attitudes of the general population.

OBJECTIVES: To assess the values of and attitudes towards the use of rapid SARS-CoV-2 antigen-detection tests for self-testing in a rural and an urban area in Peru. DESIGN: Cross-sectional, street-based population survey. SETTING: A series of over 400 randomly selected street points in Valle del Mantaro and in Lima. PARTICIPANTS: 438 respondents (203 female) participated. They were all older than 17 years and provided informed consent for participation. INTERVENTION: All respondents answered on the spot, a 35-item questionnaire developed in KoboToolbox. PRIMARY AND SECONDARY OUTCOME MEASURES: Primary outcomes of interest were: likelihood to use a SARS-CoV-2 self-test; willingness to pay for a SARS-CoV-2 self-test and likelihood to comply with recommended actions following a positive SARS-CoV-2 self-test result. Bivariate analyses and Poisson regression (PR) analyses were performed to identify significant associations between dependent variables and independent variables pertaining to respondents' characteristics, risk perception and previous experiences with conventional COVID-19 testing. RESULTS: Of the 438 respondents, 51.49% had previous experience with conventional COVID-19 testing; 20.37% had COVID-19 disease; 86.96% accepted the idea of SARS-CoV-2 self-testing; and, 78.95% would be likely to use it if needed. Almost all (94.75%) would pay for a self-testing device (mean acceptable payment: US$10.4) if it was not provided free of charge by health authorities. Overall, 93.12%, 86.93% and 85.32% would self-isolate, report the results and warn their contacts, respectively. Being a female (adjusted PR 1.05, 95% CI 1.00 to 1.09, p<0.018), having completed secondary education (adjusted PR 1.18, 95% CI 1.02 to 1.37, p<0.024) and expressing likelihood to use self-testing (adjusted PR 1.08, 95% CI 1.01 to 1.16, p<0.0.24) could be predictors of willingness to pay for a self-test. CONCLUSIONS: Self-testing is perceived as an acceptable approach. Health authorities in Peru should facilitate access to this approach to complement healthcare facilities-led testing efforts for COVID-19. Future research is necessary to understand the impact of self-testing in case detection and pandemic control.

iPSC-Based Modeling of Variable Clinical Presentation in Hypertrophic Cardiomyopathy.

BACKGROUND: Hypertrophic cardiomyopathy (HCM) is the most common inherited cardiac disease and a frequent cause of heart failure and sudden cardiac death. Our understanding of the genetic bases and pathogenic mechanisms underlying HCM has improved significantly in the recent past, but the combined effect of various pathogenic gene variants and the influence of genetic modifiers in disease manifestation are very poorly understood. Here, we set out to investigate genotype-phenotype relationships in 2 siblings with an extensive family history of HCM, both carrying a pathogenic truncating variant in the MYBPC3 gene (p.Lys600Asnfs*2), but who exhibited highly divergent clinical manifestations. METHODS: We used a combination of induced pluripotent stem cell (iPSC)-based disease modeling and CRISPR (clustered regularly interspersed short palindromic repeats)/Cas9 (CRISPR-associated protein 9)-mediated genome editing to generate patient-specific cardiomyocytes (iPSC-CMs) and isogenic controls lacking the pathogenic MYBPC3 variant. RESULTS: Mutant iPSC-CMs developed impaired mitochondrial bioenergetics, which was dependent on the presence of the mutation. Moreover, we could detect altered excitation-contraction coupling in iPSC-CMs from the severely affected individual. The pathogenic MYBPC3 variant was found to be necessary, but not sufficient, to induce iPSC-CM hyperexcitability, suggesting the presence of additional genetic modifiers. Whole-exome sequencing of the mutant carriers identified a variant of unknown significance in the MYH7 gene (p.Ile1927Phe) uniquely present in the individual with severe HCM. We finally assessed the pathogenicity of this variant of unknown significance by functionally evaluating iPSC-CMs after editing the variant. CONCLUSIONS: Our results indicate that the p.Ile1927Phe variant of unknown significance in MYH7 can be considered as a modifier of HCM expressivity when found in combination with truncating variants in MYBPC3. Overall, our studies show that iPSC-based modeling of clinically discordant subjects provides a unique platform to functionally assess the effect of genetic modifiers.