Cardiac involvement in Chagas disease and African trypanosomiasis.

Trypanosomiases are diseases caused by various species of protozoan parasite in the genus Trypanosoma, each presenting with distinct clinical manifestations and prognoses. Infections can affect multiple organs, with Trypanosoma cruzi predominantly affecting the heart and digestive system, leading to American trypanosomiasis or Chagas disease, and Trypanosoma brucei primarily causing a disease of the central nervous system known as human African trypanosomiasis or sleeping sickness. In this Review, we discuss the effects of these infections on the heart, with particular emphasis on Chagas disease, which continues to be a leading cause of cardiomyopathy in Latin America. The epidemiology of Chagas disease has changed substantially since 1990 owing to the emigration of over 30 million Latin American citizens, primarily to Europe and the USA. This movement of people has led to the global dissemination of individuals infected with T. cruzi. Therefore, cardiologists worldwide must familiarize themselves with Chagas disease and the severe, chronic manifestation - Chagas cardiomyopathy - because of the expanded prevalence of this disease beyond traditional endemic regions.

Artificial intelligence-enhanced electrocardiography derived body mass index as a predictor of future cardiometabolic disease.

The electrocardiogram (ECG) can capture obesity-related cardiac changes. Artificial intelligence-enhanced ECG (AI-ECG) can identify subclinical disease. We trained an AI-ECG model to predict body mass index (BMI) from the ECG alone. Developed from 512,950 12-lead ECGs from the Beth Israel Deaconess Medical Center (BIDMC), a secondary care cohort, and validated on UK Biobank (UKB) (n = 42,386), the model achieved a Pearson correlation coefficient (r) of 0.65 and 0.62, and an R2 of 0.43 and 0.39 in the BIDMC cohort and UK Biobank, respectively for AI-ECG BMI vs. measured BMI. We found delta-BMI, the difference between measured BMI and AI-ECG-predicted BMI (AI-ECG-BMI), to be a biomarker of cardiometabolic health. The top tertile of delta-BMI showed increased risk of future cardiometabolic disease (BIDMC: HR 1.15, p < 0.001; UKB: HR 1.58, p < 0.001) and diabetes mellitus (BIDMC: HR 1.25, p < 0.001; UKB: HR 2.28, p < 0.001) after adjusting for covariates including measured BMI. Significant enhancements in model fit, reclassification and improvements in discriminatory power were observed with the inclusion of delta-BMI in both cohorts. Phenotypic profiling highlighted associations between delta-BMI and cardiometabolic diseases, anthropometric measures of truncal obesity, and pericardial fat mass. Metabolic and proteomic profiling associates delta-BMI positively with valine, lipids in small HDL, syntaxin-3, and carnosine dipeptidase 1, and inversely with glutamine, glycine, colipase, and adiponectin. A genome-wide association study revealed associations with regulators of cardiovascular/metabolic traits, including SCN10A, SCN5A, EXOG and RXRG. In summary, our AI-ECG-BMI model accurately predicts BMI and introduces delta-BMI as a non-invasive biomarker for cardiometabolic risk stratification.

Development of a Microwave-Assisted Bench Reactor for Biomass Pyrolysis Using Hybrid Heating.

Microwave-assisted pyrolysis (MAP) is a cutting-edge technology that converts biomass into fuels, chemicals, and materials. In this study, an Arduino was used to control and automate a MAP system built from a microwave oven with a cordierite chamber filled with silicon carbide. Sugar cane bagasse was pyrolyzed at 250, 350, 450, and 550 °C to validate the MAP system and obtain pyrolytic products with different yields and chemical compositions. Lower temperatures led to high biochar yields, but the highest surface area of 25.14 m2 g-1 was only achieved at 550 °C. By contrast, higher temperatures favored the recovery of pyrolysis liquids. BET and scanning electron microscopy analyses revealed a porous biochar structure, while Fourier transform infrared spectroscopy analysis showed that the availability of functional groups on the biochar surface decreased with an increase in pyrolysis temperature. GC-MS analysis quantified valuable low molecular mass compounds in pyrolysis liquids, including aldehydes, ketones, phenols, and alcohols. With its unprecedented hybrid heating device, the MAP system promoted suitable heating rates (31.9 °C min-1) and precise temperature control (only 19 °C of set point variation), generating pyrolysis products devoid of microwave susceptor interferences. Therefore, MAP provided a rapid, safe, and efficient means of depolymerizing biomass, thus holding promise for biorefinery applications.

Using Artificial Intelligence to Predict Heart Failure Risk from Single-lead Electrocardiographic Signals: A Multinational Assessment.

Importance: Despite the availability of disease-modifying therapies, scalable strategies for heart failure (HF) risk stratification remain elusive. Portable devices capable of recording single-lead electrocardiograms (ECGs) can enable large-scale community-based risk assessment. Objective: To evaluate an artificial intelligence (AI) algorithm to predict HF risk from noisy single-lead ECGs. Design: Multicohort study. Setting: Retrospective cohort of individuals with outpatient ECGs in the integrated Yale New Haven Health System (YNHHS) and prospective population-based cohorts of UK Biobank (UKB) and Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). Participants: Individuals without HF at baseline. Exposures: AI-ECG-defined risk of left ventricular systolic dysfunction (LVSD). Main Outcomes and Measures: Among individuals with ECGs, we isolated lead I ECGs and deployed a noise-adapted AI-ECG model trained to identify LVSD. We evaluated the association of the model probability with new-onset HF, defined as the first HF hospitalization. We compared the discrimination of AI-ECG against the pooled cohort equations to prevent HF (PCP-HF) score for new-onset HF using Harrel's C-statistic, integrated discrimination improvement (IDI), and net reclassification improvement (NRI). Results: There were 194,340 YNHHS patients (age 56 years [IQR, 41-69], 112,082 women [58%]), 42,741 UKB participants (65 years [59-71], 21,795 women [52%]), and 13,454 ELSA-Brasil participants (56 years [41-69], 7,348 women [55%]) with baseline ECGs. A total of 3,929 developed HF in YNHHS over 4.5 years (2.6-6.6), 46 in UKB over 3.1 years (2.1-4.5), and 31 in ELSA-Brasil over 4.2 years (3.7-4.5). A positive AI-ECG screen was associated with a 3- to 7-fold higher risk for HF, and each 0.1 increment in the model probability portended a 27-65% higher hazard across cohorts, independent of age, sex, comorbidities, and competing risk of death. AI-ECG's discrimination for new-onset HF was 0.725 in YNHHS, 0.792 in UKB, and 0.833 in ELSA-Brasil. Across cohorts, incorporating AI-ECG predictions in addition to PCP-HF resulted in improved Harrel's C-statistic (Δ=0.112-0.114), with an IDI of 0.078-0.238 and an NRI of 20.1%-48.8% for AI-ECG vs. PCP-HF. Conclusions and Relevance: Across multinational cohorts, a noise-adapted AI model with lead I ECGs as the sole input defined HF risk, representing a scalable portable and wearable device-based HF risk-stratification strategy.

Performance of contemporary cardiovascular risk stratification scores in Brazil: an evaluation in the ELSA-Brasil study.

AIMS: Despite notable population differences in high-income and low- and middle-income countries (LMICs), national guidelines in LMICs often recommend using US-based cardiovascular disease (CVD) risk scores for treatment decisions. We examined the performance of widely used international CVD risk scores within the largest Brazilian community-based cohort study (Brazilian Longitudinal Study of Adult Health, ELSA-Brasil). METHODS: All adults 40-75 years from ELSA-Brasil (2008-2013) without prior CVD who were followed for incident, adjudicated CVD events (fatal and non-fatal MI, stroke, or coronary heart disease death). We evaluated 5 scores-Framingham General Risk (FGR), Pooled Cohort Equations (PCEs), WHO CVD score, Globorisk-LAC and the Systematic Coronary Risk Evaluation 2 score (SCORE-2). We assessed their discrimination using the area under the receiver operating characteristic curve (AUC) and calibration with predicted-to-observed risk (P/O) ratios-overall and by sex/race groups. RESULTS: There were 12 155 individuals (53.0±8.2 years, 55.3% female) who suffered 149 incident CVD events. All scores had a model AUC>0.7 overall and for most age/sex groups, except for white women, where AUC was <0.6 for all scores, with higher overestimation in this subgroup. All risk scores overestimated CVD risk with 32%-170% overestimation across scores. PCE and FGR had the highest overestimation (P/O ratio: 2.74 (95% CI 2.42 to 3.06)) and 2.61 (95% CI 1.79 to 3.43)) and the recalibrated WHO score had the best calibration (P/O ratio: 1.32 (95% CI 1.12 to 1.48)). CONCLUSION: In a large prospective cohort from Brazil, we found that widely accepted CVD risk scores overestimate risk by over twofold, and have poor risk discrimination particularly among Brazilian women. Our work highlights the value of risk stratification strategies tailored to the unique populations and risks of LMICs.

A moment-based Kalman filtering approach for estimation in ensemble systems.

A persistent challenge in tasks involving large-scale dynamical systems, such as state estimation and error reduction, revolves around processing the collected measurements. Frequently, these data suffer from the curse of dimensionality, leading to increased computational demands in data processing methodologies. Recent scholarly investigations have underscored the utility of delineating collective states and dynamics via moment-based representations. These representations serve as a form of sufficient statistics for encapsulating collective characteristics, while simultaneously permitting the retrieval of individual data points. In this paper, we reshape the Kalman filter methodology, aiming its application in the moment domain of an ensemble system and developing the basis for moment ensemble noise filtering. The moment system is defined with respect to the normalized Legendre polynomials, and it is shown that its orthogonal basis structure introduces unique benefits for the application of Kalman filter for both i.i.d. and universal Gaussian disturbances. The proposed method thrives from the reduction in problem dimension, which is unbounded within the state-space representation, and can achieve significantly smaller values when converted to the truncated moment-space. Furthermore, the robustness of moment data toward outliers and localized inaccuracies is an additional positive aspect of this approach. The methodology is applied for an ensemble of harmonic oscillators and units following aircraft dynamics, with results showcasing a reduction in both cumulative absolute error and covariance with reduced calculation cost due to the realization of operations within the moment framework conceived.

Treatment of the neck in residual/recurrent disease after chemoradiotherapy for advanced primary laryngeal cancer.

Concomitant chemoradiotherapy (CRT) is extensively used as primary organ preservation treatment for selected advanced laryngeal squamous cell carcinomas (LSCC). The oncologic outcomes of such regimens are comparable to those of total laryngectomy followed by adjuvant radiotherapy. However, the management of loco-regional recurrences after CRT remains a challenge, with salvage total laryngectomy being the only curative option. Furthermore, the decision whether to perform an elective neck dissection (END) in patients with rN0 necks, and the extent of the neck dissection in patients with rN + necks is still, a matter of debate. For rN0 patients, meta-analyses have reported occult metastasis rates ranging from 0 to 31 %, but no survival advantage for END. In addition, meta-analyses also showed a higher incidence of complications in patients who received an END. Therefore, END is not routinely recommended in addition to salvage laryngectomy. Although some evidence suggests a potential role of END for supraglottic and locally advanced cases, the decision to perform END should weigh benefits against potential complications. In rN + patients, several studies suggested that selective neck dissection (SND) is oncologically safe for patients with specific conditions: when lymph node metastases are not fixed and are absent at level IV or V. Super-selective neck dissection (SSND) may be an option when nodes are confined to one level. In conclusion, current evidence suggests that in rN0 necks routine END is not necessary and that in rN + necks with limited nodal recurrences SND or a SSND could be sufficient.

Loss of heterozygosity impacts MHC expression on the immune microenvironment in CDK12-mutated prostate cancer.

BACKGROUND: In prostate cancer (PCa), well-established biomarkers such as MSI status, TMB high, and PDL1 expression serve as reliable indicators for favorable responses to immunotherapy. Recent studies have suggested a potential association between CDK12 mutations and immunotherapy response; however, the precise mechanisms through which CDK12 mutation may influence immune response remain unclear. A plausible explanation for immune evasion in this subset of CDK12-mutated PCa may be reduced MHC expression. RESULTS: Using genomic data of CDK12-mutated PCa from 48 primary and 10 metastatic public domain samples and a retrospective cohort of 53 low-intermediate risk primary PCa, we investigated how variation in the expression of the MHC genes affected associated downstream pathways. We classified the patients based on gene expression quartiles of MHC-related genes and categorized the tumors into "High" and "Low" expression levels. CDK12-mutated tumors with higher MHC-expressed pathways were associated with the immune system and elevated PD-L1, IDO1, and TIM3 expression. Consistent with an inflamed tumor microenvironment (TME) phenotype, digital cytometric analyses identified increased CD8 + T cells, B cells, γδ T cells, and M1 Macrophages in this group. In contrast, CDK12-mutated tumors with lower MHC expression exhibited features consistent with an immune cold TME phenotype and immunoediting. Significantly, low MHC expression was also associated with chromosome 6 loss of heterozygosity (LOH) affecting the entire HLA gene cluster. These LOH events were observed in both major clonal and minor subclonal populations of tumor cells. In our retrospective study of 53 primary PCa cases from this Institute, we found a 4% (2/53) prevalence of CDK12 mutations, with the confirmation of this defect in one tumor through Sanger sequencing. In keeping with our analysis of public domain data this tumor exhibited low MHC expression at the RNA level. More extensive studies will be required to determine whether reduced HLA expression is generally associated with primary tumors or is a specific feature of CDK12 mutated PCa. CONCLUSIONS: These data show that analysis of CDK12 alteration, in the context of MHC expression levels, and LOH status may offer improved predictive value for outcomes in this potentially actionable genomic subgroup of PCa. In addition, these findings highlight the need to explore novel therapeutic strategies to enhance MHC expression in CDK12-defective PCa to improve immunotherapy responses.

Decoding 2.3 million ECGs: interpretable deep learning for advancing cardiovascular diagnosis and mortality risk stratification.

Aims: Electrocardiogram (ECG) is widely considered the primary test for evaluating cardiovascular diseases. However, the use of artificial intelligence (AI) to advance these medical practices and learn new clinical insights from ECGs remains largely unexplored. We hypothesize that AI models with a specific design can provide fine-grained interpretation of ECGs to advance cardiovascular diagnosis, stratify mortality risks, and identify new clinically useful information. Methods and results: Utilizing a data set of 2 322 513 ECGs collected from 1 558 772 patients with 7 years follow-up, we developed a deep-learning model with state-of-the-art granularity for the interpretable diagnosis of cardiac abnormalities, gender identification, and hypertension screening solely from ECGs, which are then used to stratify the risk of mortality. The model achieved the area under the receiver operating characteristic curve (AUC) scores of 0.998 (95% confidence interval (CI), 0.995-0.999), 0.964 (95% CI, 0.963-0.965), and 0.839 (95% CI, 0.837-0.841) for the three diagnostic tasks separately. Using ECG-predicted results, we find high risks of mortality for subjects with sinus tachycardia (adjusted hazard ratio (HR) of 2.24, 1.96-2.57), and atrial fibrillation (adjusted HR of 2.22, 1.99-2.48). We further use salient morphologies produced by the deep-learning model to identify key ECG leads that achieved similar performance for the three diagnoses, and we find that the V1 ECG lead is important for hypertension screening and mortality risk stratification of hypertensive cohorts, with an AUC of 0.816 (0.814-0.818) and a univariate HR of 1.70 (1.61-1.79) for the two tasks separately. Conclusion: Using ECGs alone, our developed model showed cardiologist-level accuracy in interpretable cardiac diagnosis and the advancement in mortality risk stratification. In addition, it demonstrated the potential to facilitate clinical knowledge discovery for gender and hypertension detection which are not readily available.

Skull base surgery for malignant tumors: The 2nd international collaborative study (1995-2015).

BACKGROUND: The current study presents the effort of a global collaborative group to review the management and outcomes of malignant tumors of the skull base worldwide. PATIENTS AND METHODS: A total of 28 institutions contributed data on 3061 patients. Analysis evaluated clinical variables, survival outcomes, and multivariable factors associated with outcomes. RESULTS: The median age was 56 years (IQR 44-67). The open surgical approach was used in 55% (n = 1680) of cases, endoscopic resection was performed in 36% (n = 1087), and the combined approach in 9.6% (n = 294). With a median follow-up of 7.1 years, the 5-year OS DSS and RFS were 65%, 71.7% and 53%, respectively. On multivariable analysis, older age, comorbidities, histology, dural/intracranial involvement, positive margins, advanced stage, and primary site were independent prognostic factors for OS, DSS, and RFS. Adjuvant RT was a protective prognostic factor. CONCLUSION: The progress across various disciplines may have contributed to improved OS and DSS in this study compared to previous reports.

Experimental study, simulation and technical-economic feasibility of an interesterification plant for hydrocarbons synthesis by using plastics and frying oil waste.

This work presents the experimental assessment of a 20 mL batch reactor's efficacy in converting plastic and oil residues into biofuels. The reactor, designed for ease of use, is heated using a metallic system. The experiments explore plastic solubilization at various temperatures and residence times, employing a mixture of distilled water and ethylene glycol as the solvent. Initial findings reveal that plastic solubilization requires a temperature of 350 °C with an ethylene glycol mole fraction of 0.35, whereas 250 °C suffices with a mole fraction of 0.58. Additionally, the study includes a process simulation of a plant utilizing a double fluidized bed gasifier and an economic evaluation of the interesterification/pyrolysis plant. Simulation results support project feasibility, estimating a total investment cost of approximately $12.99 million and annual operating expenses of around $17.98 million, with a projected payback period of about 5 years.

Recurrent Laryngeal Nerve Intraoperative Neuromonitoring Indications in Non-Thyroid and Non-Parathyroid Surgery.

Introperative nerve monitoring (IONM) of the recurrent laryngeal nerve (RLN) is a well-established technique to aid in thyroid/parathyroid surgery. However, there is little evidence to support its use in non-thyroid or non-parathyroid surgery. The aim of this paper was to review the current evidence regarding the use of IONM in non-thyroid/non-parathyroid surgery in the head and neck and thorax. A literature search was performed from their inception up to January 2024, including the term "recurrent laryngeal nerve monitoring". IONM in non-thyroid/non-parathyroid surgery has mainly been previously described in oesophageal surgery and in tracheal resections. However, there is little published evidence on the role of IONM with other resections in the vicinity of the RLN. Current evidence is low-level for the use of RLN IONM in non-thyroid/non-parathyroid surgery. However, clinicians should consider its use in surgery for pathologies where the RLN is exposed and could be injured.

Essential data variables for a minimum dataset for head and neck cancer trials and clinical research: HNCIG consensus recommendations and database.

The Head and Neck Cancer International Group (HNCIG) has undertaken an international modified Delphi process to reach consensus on the essential data variables to be included in a minimum database for HNC research. Endorsed by 19 research organisations representing 34 countries, these recommendations provide the framework to facilitate and harmonise data collection and sharing for HNC research. These variables have also been incorporated into a ready to use downloadable HNCIG minimum database, available from the HNCIG website.

Primary Management of Operable Locally Advanced Oral Cavity Squamous Cell Carcinoma: Current Concepts and Strategies.

INTRODUCTION: Locally advanced oral cavity carcinoma (LAOCSCC) is primarily treated with surgery followed by radiotherapy with or without chemotherapy. METHODS: A review of literature using PubMED was performed for studies reporting the management of LAOCSCC. Based on the reviewed literature and opinions of experts in the field, recommendations were made. RESULTS: Studies have shown that outcomes following resection of T4a and infranotch (inferior to mandibular notch) T4b are comparable. We discuss the concept of compartmental resection of LAOCSCC and issues concerning the management of the neck. Further, patients who refuse or are unable to undergo surgery can be treated with chemoradiotherapy with uncertain outcomes. The role of neoadjuvant chemotherapy has shown promise for organ (mandibular) preservation in a select subset of patients. CONCLUSION: The management strategy for LAOCSCC should be determined in a multidisciplinary setting with emphasis on tumor control, functional preservation, and quality of life of the patient.

Scalable Risk Stratification for Heart Failure Using Artificial Intelligence applied to 12-lead Electrocardiographic Images: A Multinational Study.

Background: Current risk stratification strategies for heart failure (HF) risk require either specific blood-based biomarkers or comprehensive clinical evaluation. In this study, we evaluated the use of artificial intelligence (AI) applied to images of electrocardiograms (ECGs) to predict HF risk. Methods: Across multinational longitudinal cohorts in the integrated Yale New Haven Health System (YNHHS) and in population-based UK Biobank (UKB) and Brazilian Longitudinal Study of Adult Health (ELSA-Brasil), we identified individuals without HF at baseline. Incident HF was defined based on the first occurrence of an HF hospitalization. We evaluated an AI-ECG model that defines the cross-sectional probability of left ventricular dysfunction from a single image of a 12-lead ECG and its association with incident HF. We accounted for the competing risk of death using the Fine-Gray subdistribution model and evaluated the discrimination using Harrel's c-statistic. The pooled cohort equations to prevent HF (PCP-HF) were used as a comparator for estimating incident HF risk. Results: Among 231,285 individuals at YNHHS, 4472 had a primary HF hospitalization over 4.5 years (IQR 2.5-6.6) of follow-up. In UKB and ELSA-Brasil, among 42,741 and 13,454 people, 46 and 31 developed HF over a follow-up of 3.1 (2.1-4.5) and 4.2 (3.7-4.5) years, respectively. A positive AI-ECG screen portended a 4-fold higher risk of incident HF among YNHHS patients (age-, sex-adjusted HR [aHR] 3.88 [95% CI, 3.63-4.14]). In UKB and ELSA-Brasil, a positive-screen ECG portended 13- and 24-fold higher hazard of incident HF, respectively (aHR: UKBB, 12.85 [6.87-24.02]; ELSA-Brasil, 23.50 [11.09-49.81]). The association was consistent after accounting for comorbidities and the competing risk of death. Higher model output probabilities were progressively associated with a higher risk for HF. The model's discrimination for incident HF was 0.718 in YNHHS, 0.769 in UKB, and 0.810 in ELSA-Brasil. Across cohorts, incorporating model probability with PCP-HF yielded a significant improvement in discrimination over PCP-HF alone. Conclusions: An AI model applied to images of 12-lead ECGs can identify those at elevated risk of HF across multinational cohorts. As a digital biomarker of HF risk that requires just an ECG image, this AI-ECG approach can enable scalable and efficient screening for HF risk.

Combination of Tele-Cardiology Tools for Cardiovascular Risk Stratification in Primary Care: Data from the PROVAR+ Study. / Combinação de Ferramentas de Telecardiologia para Estratificação de Risco Cardiovascular na Atenção Primária: Dados do Estudo PROVAR.

BACKGROUND: Tele-cardiology tools are valuable strategies to improve risk stratification. OBJECTIVE: We aimed to evaluate the accuracy of tele-electrocardiography (ECG) to predict abnormalities in screening echocardiography (echo) in primary care (PC). METHODS: In 17 months, 6 health providers at 16 PC units were trained on simplified handheld echo protocols. Tele-ECGs were recorded for final diagnosis by a cardiologist. Consented patients with major ECG abnormalities by the Minnesota code, and a 1:5 sample of normal individuals underwent clinical questionnaire and screening echo interpreted remotely. Major heart disease was defined as moderate/severe valve disease, ventricular dysfunction/hypertrophy, pericardial effusion, or wall-motion abnormalities. Association between major ECG and echo abnormalities was assessed by logistic regression as follows: 1) unadjusted model; 2) model 1 adjusted for age/sex; 3) model 2 plus risk factors (hypertension/diabetes); 4) model 3 plus history of cardiovascular disease (Chagas/rheumatic heart disease/ischemic heart disease/stroke/heart failure). P-values < 0.05 were considered significant. RESULTS: A total 1,411 patients underwent echo; 1,149 (81%) had major ECG abnormalities. Median age was 67 (IQR 60 to 74) years, and 51.4% were male. Major ECG abnormalities were associated with a 2.4-fold chance of major heart disease on echo in bivariate analysis (OR = 2.42 [95% CI 1.76 to 3.39]), and remained significant after adjustments in models (p < 0.001) 2 (OR = 2.57 [95% CI 1.84 to 3.65]), model 3 (OR = 2.52 [95% CI 1.80 to3.58]), and model 4 (OR = 2.23 [95%CI 1.59 to 3.19]). Age, male sex, heart failure, and ischemic heart disease were also independent predictors of major heart disease on echo. CONCLUSIONS: Tele-ECG abnormalities increased the likelihood of major heart disease on screening echo, even after adjustments for demographic and clinical variables.

FUNDAMENTO: As ferramentas de telecardiologia são estratégias valiosas para melhorar a estratificação de risco. OBJETIVO: Objetivamos avaliar a acurácia da tele-eletrocardiografia (ECG) para predizer anormalidades no ecocardiograma de rastreamento na atenção primária. MÉTODOS: Em 17 meses, 6 profissionais de saúde em 16 unidades de atenção primária foram treinados em protocolos simplificados de ecocardiografia portátil. Tele-ECGs foram registrados para diagnóstico final por um cardiologista. Pacientes consentidos com anormalidades maiores no ECG pelo código de Minnesota e uma amostra 1:5 de indivíduos normais foram submetidos a um questionário clínico e ecocardiograma de rastreamento interpretado remotamente. A doença cardíaca grave foi definida como doença valvular moderada/grave, disfunção/hipertrofia ventricular, derrame pericárdico ou anormalidade da motilidade. A associação entre alterações maiores do ECG e anormalidades ecocardiográficas foi avaliada por regressão logística da seguinte forma: 1) modelo não ajustado; 2) modelo 1 ajustado por idade/sexo; 3) modelo 2 mais fatores de risco (hipertensão/diabetes); 4) modelo 3 mais história de doença cardiovascular (Chagas/cardiopatia reumática/cardiopatia isquêmica/AVC/insuficiência cardíaca). Foram considerados significativos valores de p < 0,05. RESULTADOS: No total, 1.411 pacientes realizaram ecocardiograma, sendo 1.149 (81%) com anormalidades maiores no ECG. A idade mediana foi de 67 anos (intervalo interquartil de 60 a 74) e 51,4% eram do sexo masculino. As anormalidades maiores no ECG se associaram a uma chance 2,4 vezes maior de doença cardíaca grave no ecocardiograma de rastreamento na análise bivariada (OR = 2,42 [IC 95% 1,76 a 3,39]) e permaneceram significativas (p < 0,001) após ajustes no modelo 2 (OR = 2,57 [IC 95% 1,84 a 3,65]), modelo 3 (OR = 2,52 [IC 95% 1,80 a 3,58]) e modelo 4 (OR = 2,23 [IC 95% 1,59 a 3,19]). Idade, sexo masculino, insuficiência cardíaca e doença cardíaca isquêmica também foram preditores independentes de doença cardíaca grave no ecocardiograma. CONCLUSÕES: As anormalidades do tele-ECG aumentaram a probabilidade de doença cardíaca grave no ecocardiograma de rastreamento, mesmo após ajustes para variáveis demográficas e clínicas.

Diving into the proteomic atlas of SARS-CoV-2 infected cells.

The COVID-19 pandemic was initiated by the rapid spread of a SARS-CoV-2 strain. Though mainly classified as a respiratory disease, SARS-CoV-2 infects multiple tissues throughout the human body, leading to a wide range of symptoms in patients. To better understand how SARS-CoV-2 affects the proteome from cells with different ontologies, this work generated an infectome atlas of 9 cell models, including cells from brain, blood, digestive system, and adipocyte tissue. Our data shows that SARS-CoV-2 infection mainly trigger dysregulations on proteins related to cellular structure and energy metabolism. Despite these pivotal processes, heterogeneity of infection was also observed, highlighting many proteins and pathways uniquely dysregulated in one cell type or ontological group. These data have been made searchable online via a tool that will permit future submissions of proteomic data ( https://reisdeoliveira.shinyapps.io/Infectome_App/ ) to enrich and expand this knowledgebase.

Blood cell alterations in Colossoma macropomum juveniles caused by silver nanoparticles.

This study evaluated the median lethal concentration of silver nanoparticles and their effects in fish tambaqui Colossoma macropomum. Therefore, an acute toxicity assay was carried out in completely randomized design evaluating six different concentrations of silver nanoparticles on blood parameters of tambaqui. The silver nanoparticles were produced by chemical reduction with polyvinyl alcohol (AgNP-PVA). The lethal concentration 50% (LC50) was estimated using probit regression. The blood was collected, analyzed and the data were submitted to T-test (dying x surviving fish) and Tukey test (surviving fish). An increase in glucose, hematocrit, total plasma protein, hemoglobin, erythrocytes, leukocytes, monocytes, and neutrophils as well as reduced MCV (mean corpuscular volume) in dying fish compared to surviving fish were observed. Survived fish exposed to 187.5 µg/L showed an increase in hematocrit, MCV, and MCH and a reduction in erythrocytes, total numbers of leukocyte, thrombocyte, lymphocyte, and neutrophil. The fish exposed to concentrations below 125 µg/L, had returned the blood parameter to baselines compared to control. The estimated LC50 was 165.09 µg/L and was classified as highly toxic for the fish tambaqui. In higher concentrations, it causes an acute respiratory toxicity, but in concentrations below 125 µg/L, the fish can adapt to the stressing agent.

Poorly differentiated thyroid carcinomas: conceptual controversy and clinical impact.

Poorly differentiated thyroid carcinomas (PDTC) are rare diseases; nevertheless, they account for the majority of deaths from non-anaplastic follicular cell-derived thyroid carcinomas. Establishing the diagnosis and treatment of PDTC is challenging given the low incidence and the lack of standardization of diagnostic criteria. These limitations hamper the ability to compare therapeutic modalities and outcomes between recent and older studies. Recently, the 5th edition of the classification of endocrine tumors has been published, which includes changes in nomenclature and the addition of the disease entity of "differentiated high-grade follicular cell-derived carcinomas". On the other hand, the recently witnessed advances in molecular diagnostics have enriched therapeutic options and improved prognosis for patients. We herein review the various historical variations and evolution in the diagnostic criteria for PDTC. This systematic review attempts to clarify the evolution of the histological and molecular characteristics of this disease, its prognosis, as well as its treatment options.

Agreement between Handheld and Standard Echocardiography for Diagnosis of Latent Rheumatic Heart Disease in Brazilian Schoolchildren from High-Prevalence Settings (Agreement between Screening and Standard Echo for RHD).

Introduction: Handheld echocardiography (echo) is the tool of choice for rheumatic heart disease (RHD) screening. We aimed to assess the agreement between screening and standard echo for latent RHD diagnosis in schoolchildren from an endemic setting. Methods: Over 14 months, 3 nonphysicians used handheld machines and the 2012 WHF Criteria to determine RHD prevalence in consented schoolchildren from Brazilian low-income public schools. Studies were interpreted by telemedicine by 3 experts (Brazil, US). RHD-positive children (borderline/definite) and those with congenital heart disease (CHD) were referred for standard echo, acquired and interpreted by a cardiologist. Agreement between screening and standard echo, by WHF subgroups, was assessed. Results: 1390 students were screened in 6 schools, with 110 (7.9%, 95% CI 6.5-9.5) being screen positive (14 ± 2 years, 72% women). Among 16 cases initially diagnosed as definite RHD, 11 (69%) were confirmed, 4 (25%) reclassified to borderline, and 1 to normal. Among 79 cases flagged as borderline RHD, 19 (24%) were confirmed, 50 (63%) reclassified to normal, 8 (10%) reclassified as definite RHD, and 2 had mild CHD. Considering the 4 diagnostic categories, kappa was 0.18. In patients with borderline RHD reclassified to non-RHD, the most frequent WHF criterion was B (isolated mitral regurgitation, 64%), followed by A (2 mitral valve morphological features, 31%). In 1 patient with definite RHD reclassified to normal, the WHF criterion was D (borderline RHD in aortic and mitral valves). After standard echo, RHD prevalence was 3.2% (95% CI 2.3-4.2). Conclusions: Although practical, RHD screening with handheld devices tends to overestimate prevalence.