Inapparent primary dengue virus infections reveal hidden serotype-specific epidemiological patterns and spectrum of infection outcome: a cohort study in Nicaragua.

Background: Dengue is the most prevalent mosquito-borne viral disease and a major public health problem worldwide. Most primary infections with the four dengue virus serotypes (DENV1-4) are inapparent; nevertheless, prior research has primarily focused on symptomatic infections, which has limited our understanding of the epidemiological burden and spectrum of disease of each DENV serotype. Our study addresses this bottleneck in dengue research by providing a new method and a detailed examination of primary inapparent infections. Methods: Here we present (1) the evaluation of a multiplex DENV1-4 envelope domain III multiplex microsphere-based assay (EDIII-MMBA) to serotype inapparent primary infections and (2) its application leveraging 17 years of prospective sample collection from the Nicaraguan Pediatric Dengue Cohort Study. After evaluation, we analyzed 46% (N=574) of total inapparent primary DENV infections with the EDIII-MMBA. Remaining infections were inferred using stochastic imputation, taking year and neighborhood of infection into account. Findings: The EDIII-MMBA demonstrated excellent diagnostic accuracy of symptomatic and inapparent primary DENV infections when evaluated against gold-standard serotyping methods. Significant within- and between-year variation in serotype distribution between symptomatic and inapparent infections and circulation of serotypes undetected in symptomatic cases were observed in multiple years. Our findings reveal that a significant majority of primary infections remained inapparent: 76.8% for DENV1, 79.9% for DENV2, and 63.9% for DENV3. DENV3 exhibited the highest likelihood of symptomatic and severe primary infections (Pooled OR compared to DENV1 = 2.13, 95% CI 1.28-3.56, and 6.75, 2.01-22.62, respectively), whereas DENV2 had similar likelihood to DENV1 in both analyses. Interpretation: Our study indicates that case surveillance skews the perceived epidemiological footprint of DENV and reveals a more complex and intricate pattern of serotype distribution in inapparent infections. Further, the significant differences in infection outcomes by serotype emphasizes the need for serotype-informed public health strategies. Funding: NIH/NIAID P01AI106695, U01AI153416. Research in context: Evidence before this study: We conducted a search in PubMed for studies published up to February 2024. Keywords included "dengue virus" and "DENV" in combination with "inapparent infections", "asymptomatic infections", "primary infections by serotype", "FoI by serotype", "force of infection", "force of infection by serotype", and identified a significant gap in the current understanding of dengue epidemiology. Despite acknowledging the high prevalence of inapparent DENV infections in endemic regions, previous research has focused primarily on symptomatic infections, potentially biasing our understanding of the DENV epidemiological landscape and hindering our capacity to determine the complete disease spectrum of the different DENV serotypes. While cross-sectional studies have provided preliminary insights into this gap, there is a need for more comprehensive and detailed serotype-specific insights to evaluate the epidemiological impact of inapparent infections. The lack of comprehensive characterization of inapparent infections reflects methodological challenges, particularly the need for prospective cohort studies designed to capture and accurately serotype these infections. Moreover, the reliance on labor-intensive and low-throughput antibody neutralization assays for serotyping, despite their accuracy, has constrained high-throughput analysis required for large-scale epidemiological studies.Added value of this study: Our study, spanning 17 years of prospective cohort data in Nicaragua, addresses this bottleneck in dengue research by providing a detailed examination of primary inapparent infections. The introduction of a novel envelope domain III (EDIII) multiplex microsphere-based assay for DENV serotyping represents a significant methodological advance, offering an efficient, scalable alternative for large epidemiological studies. A key contribution of our study is the intricate pattern of serotype distribution among inapparent infections. In contrast to the serotype predominance observed in symptomatic infections, inapparent infections exhibit a complex landscape with co-circulation of multiple DENV serotypes, including serotypes undetected in symptomatic surveillance in multiple years. Our systematic documentation of the entire disease spectrum provides unprecedented insights into the serotype-specific disease burden in primary infection, including the proportion of symptomatic versus inapparent infection and its temporal variations, thus providing a more complete picture of DENV epidemiology than has been available to date. Notably, we demonstrate striking differences in disease severity by serotype, with DENV3 infections being significantly more symptomatic and more severe compared to DENV1 and DENV2, the latter displaying the highest rate of inapparent infection.Implications of all the available evidence: Our research challenges prior assumptions by demonstrating that inapparent and symptomatic primary DENV infections present distinct epidemiological profiles, revealing that the epidemiological footprint of DENV is broader and more nuanced than previously recognized through symptomatic cases alone. These findings underscore the utility for continuous and comprehensive surveillance systems that capture both symptomatic and inapparent infections to accurately assess the epidemiological burden of DENV and inform public health interventions. Additionally, they provide critical insight for enhancing the accuracy of predictive DENV transmission modeling. Furthermore, the marked differences in infection outcomes by serotype emphasize the need for serotype-informed public health strategies. This nuanced understanding is pivotal for the crafting of targeted interventions, vaccine development and vaccination strategies, and efficient resource allocation, ultimately contributing to the global effort to mitigate the impact of dengue.

Dengue severity by serotype in 19 years of pediatric clinical studies in Nicaragua.

Background: Dengue virus, a major global health threat, consists of four serotypes (DENV1-4) that cause a range of clinical manifestations from mild to severe and potentially fatal disease. Methods: This study, based on 19 years of data from the Pediatric Dengue Cohort Study and Pediatric Dengue Hospital-based Study in Managua, Nicaragua, investigates the influence of serotype and immune status on dengue severity. Study participants 6 months to 17 years old were followed during their hospital stay or as ambulatory patients, with dengue cases confirmed by molecular, serological, and/or virological methods. Results: We enrolled a total of 14071 participants, of whom 2954 (21%) were positive for DENV infection. Of 2425 cases with serotype result by RT-PCR, 541 corresponded to DENV1, 996 to DENV2, 718 to DENV3 and 170 to DENV4. Severe disease was more prevalent among secondary DENV2 and DENV4 cases, while similar disease severity was observed in both primary and secondary DENV1 and DENV3 cases. According to the 1997 World Health Organization (WHO) severity classification, both DENV2 and DENV3 had a higher proportion of severe disease compared to other serotypes, whereas DENV3 had the greatest percentage of severity under the WHO-2009 classification. DENV2 was associated with pleural effusion and low platelet count, while DENV3 correlated with both hypotensive and compensated shock. Conclusions: These findings emphasize the critical need for a dengue vaccine with balanced efficacy against all four serotypes, particularly as existing vaccines show variable efficacy by serotype and immune status, posing challenges for comprehensive protection, particularly in dengue-naïve individuals.

Improving Drug-Drug Interaction Extraction with Gaussian Noise.

Drug-Drug Interactions (DDIs) produce essential and valuable insights for healthcare professionals, since they provide data on the impact of concurrent administration of medications to patients during therapy. In that sense, some relevant works, related to the DDIExtraction2013 Challenge, are available in the current technical literature. This study aims to improve previous results, using two models, where a Gaussian noise layer is added to achieve better DDI relationship extraction. (1) A Piecewise Convolutional Neural Network (PW-CNN) model is used to capture relationships among pharmacological entities described in biomedical databases. Additionally, the model incorporates multichannel words to enrich a person's vocabulary and reduce unfamiliar words. (2) The model uses the pre-trained BERT language model to classify relationships, while also integrating data from the target entities. After identifying the target entities, the model transfers the relevant information through the pre-trained architecture and integrates the encoded data for both entities. The results of the experiment show an improved performance, with respect to previous models.

A non-destructive X-ray fluorescence method of analysis of formalin fixed-paraffin embedded biopsied samples for biomarkers for breast and colon cancer.

In this work we present a methodology for the non-destructive elemental determination of formalin-fixed paraffin-embedded (FFPE) human tissue samples based on the Fundamental Parameters method for the quantification of micro Energy Dispersive X Ray Fluorescence (micro-EDXRF) area scans. This methodology intended to overcome two major constraints in the analysis of paraffin embedded tissue samples - retrieval of optimal region of analysis of the tissue within the paraffin block and the determination of the dark matrix composition of the biopsied sample. This way, an image treatment algorithm, based on R® tool to select the regions of the micro-EDXRF area scans was developed. Also, different dark matrix compositions were evaluated using varying combinations of H, C, N and O until the most accurate matrix was found: 8% H, 15% C, 1% N and 60% O for breast FFPE samples and 8% H, 23% C, 2% N and 55% O for colon. The developed methodology was applied to paired normal-tumour samples of breast and colon biopsied tissues in order to gauge potential elemental biomarkers for carcinogenesis in these tissues. The obtained results showed distinctive biomarkers for breast and for colon: there was a significant increase of P, S, K and Fe in both tissues, while a significant increase of Ca an Zn concentrations was also determined for breast tumour samples.

Digital pathology implementation in a private laboratory: The CEDAP experience.

Introduction: The transition to digital pathology has been carried out by several laboratories across the globe, with some cases described in Portugal. In this article, we describe the transition to digital pathology in a high-volume private laboratory, considering the main challenges and opportunities. Material and methods: Our process started in 2020, with laboratory workflow adaptation and we are currently using a high-capacity scanner (Aperio GT450DX) to digitize slides at 20×. The visualization system, Aperio eSlide Manager WebViewer, is integrated into the Laboratory System. The validation process followed the Royal College of Pathologists Guidelines. Results: Regarding validation, the first phase detected an error rate of 6.8%, mostly due to digitization errors. Phase optimization and collaboration with technical services led to improvements in this process. In the second validation phase, most of the slides had the desired quality for evaluation, with only an error rate of 0.6%, corrected with a new scan. The interpathologist correlation had a total agreement rate of 96.87% and 3.13% partial agreement. Conclusion: The implementation and validation of digital pathology was a success, being ready for prime time. The total integration of all laboratory systems and the acquisition of new equipment will maximize their use, especially with the application of artificial intelligence algorithms.

Heart failure in COVID-19: the multicentre, multinational PCHF-COVICAV registry.

AIMS: We assessed the outcome of hospitalized coronavirus disease 2019 (COVID-19) patients with heart failure (HF) compared with patients with other cardiovascular disease and/or risk factors (arterial hypertension, diabetes, or dyslipidaemia). We further wanted to determine the incidence of HF events and its consequences in these patient populations. METHODS AND RESULTS: International retrospective Postgraduate Course in Heart Failure registry for patients hospitalized with COVID-19 and CArdioVascular disease and/or risk factors (arterial hypertension, diabetes, or dyslipidaemia) was performed in 28 centres from 15 countries (PCHF-COVICAV). The primary endpoint was in-hospital mortality. Of 1974 patients hospitalized with COVID-19, 1282 had cardiovascular disease and/or risk factors (median age: 72 [interquartile range: 62-81] years, 58% male), with HF being present in 256 [20%] patients. Overall in-hospital mortality was 25% (n = 323/1282 deaths). In-hospital mortality was higher in patients with a history of HF (36%, n = 92) compared with non-HF patients (23%, n = 231, odds ratio [OR] 1.93 [95% confidence interval: 1.44-2.59], P < 0.001). After adjusting, HF remained associated with in-hospital mortality (OR 1.45 [95% confidence interval: 1.01-2.06], P = 0.041). Importantly, 186 of 1282 [15%] patients had an acute HF event during hospitalization (76 [40%] with de novo HF), which was associated with higher in-hospital mortality (89 [48%] vs. 220 [23%]) than in patients without HF event (OR 3.10 [2.24-4.29], P < 0.001). CONCLUSIONS: Hospitalized COVID-19 patients with HF are at increased risk for in-hospital death. In-hospital worsening of HF or acute HF de novo are common and associated with a further increase in in-hospital mortality.

An experience selecting quality features of apps for people with disabilities using abductive approach to explanatory theory generation.

This study determines one of the most relevant quality factors of apps for people with disabilities utilizing the abductive approach to the generation of an explanatory theory. First, the abductive approach was concerned with the results' description, established by the apps' quality assessment, using the Mobile App Rating Scale (MARS) tool. However, because of the restrictions of MARS outputs, the identification of critical quality factors could not be established, requiring the search for an answer for a new rule. Finally, the explanation of the case (the last component of the abductive approach) to test the rule's new hypothesis. This problem was solved by applying a new quantitative model, compounding data mining techniques, which identified MARS' most relevant quality items. Hence, this research defines a much-needed theoretical and practical tool for academics and also practitioners. Academics can experiment utilizing the abduction reasoning procedure as an alternative to achieve positivism in research. This study is a first attempt to improve the MARS tool, aiming to provide specialists relevant data, reducing noise effects, accomplishing better predictive results to enhance their investigations. Furthermore, it offers a concise quality assessment of disability-related apps.

Leucemia promielocítica aguda M3. Reporte de un caso clínico / Acute promyelocytic leukemia M3. Report of a clinical case

La leucemia es una neoplásica hemática que contiene múltiples subtipos, entre ellos la leucemia promielocítica aguda, caracterizada por la multiplicación clonal del linaje mieloide y eritroide. El presente caso pertenece a un paciente masculino de 20 años, sin antecedentes de importancia y con un cuadro evolutivo de 20 días con sangrado del dedo anular de la mano derecha, y con ausencia de proceso cicatricial. A partir de los exámenes de laboratorio se identifica bicitopénia eritroide y plaquetaria, con evidencia de un 93% de promielocitos. El tratamiento con ATO, ATRA y Antraciclinas logró una leve mejoría. Durante su estadía hospitalaria desarrolló síndrome de diferenciación, lo que ocasionó su fallecimiento.

Leukemia is a hematic neoplastic that contains multiple subtypes, including acute promyelocytic leukemia, characterized by the clonal multiplication of the myeloid and erythroid lineage. The present case belongs to a 20-year-old male patient without health history of importance and with a 20-day evolutionary picture with bleeding from the ring finger of his right hand, and without scarring process. Erythroid and platelet bicytopenia is identified from laboratory tests with evidence of 93% promyelocytes. The treatment including ATO, ATRA and Anthracyclines achieved a slight improvement. He developed differentiation syndrome during hospitalization, which caused his death.

Evaluación de registros Holter durante 19 horas en el contexto de la teoría de la probabilidad / Evaluation of 19-hour Holter recordings in the context of probability theory

Resumen Introducción: Previamente se desarrolló una nueva metodología de ayuda diagnóstica para los registros Holter fundamentada en los sistemas dinámicos y la teoría de probabilidad, a partir de la información registrada en 21 horas. Objetivo: Evaluar la capacidad diagnóstica de esta metodología durante 19 horas, comparándola con los resultados convencionales del Holter y con los resultados del método matemático aplicado en 21 horas. Materiales y Métodos: fueron evaluados 80 casos de pacientes mayores a 20 años, 10 con registro Holter normal y 70 diagnosticados de forma convencional con diferentes patologías cardíacas. Se establecieron los rangos para las frecuencias cardíacas y de número de latidos por hora en 21 y 19 horas; luego, se calculó la probabilidad de ocurrencia de estos, lo que permitió diferenciar estados de normalidad y enfermedad aguda a partir de tres parámetros. Se comparó el diagnóstico físico-matemático con el diagnóstico convencional, tomado como Gold Standard. Resultados: De los casos normales, dos presentaron probabilidad menor o igual a 0,217 y ocho probabilidades mayores o igual a 0,304; ningún caso de enfermedad aguda presentó valores con probabilidad menor o igual a 0,217, mientras que todos presentaron valores mayores o iguales a 0,304, tanto para los registros Holter evaluados en 21 como en 19 horas. Conclusiones: Se confirmó la utilidad clínica de la metodología ante una reducción del tiempo de evaluación a 19 horas, obteniendo diagnósticos objetivos con base en la auto-organización matemática del fenómeno.

Abstract Background: a new method to help evaluate 21-hour holter recordings based on dynamic systems and the theory of probability was previously developed Aim: to evaluate the diagnostic value of this methodology in the analysis of 19 hr compared to conventional holter analysis over a 21-hr recording. Methods: the holter recordings of 80 subjects aged over 20 years old were analyzed. Ten subjects had a normal holter and 70 conventionally diagnosed as abnormal. Ranges for heart rate and number of beats in 21 or 19 hours were determined. The probability of their occurrence was calculated using 3 parameters. The mathematically derived diagnosis was compared to the clinical diagnosis, considered a gold standard. Results: Among normal cases the calculated probability was ≤ 0.217 in 2 cases and ≥0.304 in 8. No case with acute disease presented probability values ≤0.217; all had probability values ≥0.304, both in 21 and 19 hour recordings. Conclusion: the mathematical methodology described was clinically useful allowing a reduction in recording time from 21 to 19 hr. Clinical diagnosis may be inferred from the mathematical organization of a holter recording.