Conversació entre el llisensiado Tarrós de Almásera, y Tofol Rosegó de Alboraya [Texto impreso]

Hay un ejemplar encuadernado con: Poesías colocadas en el pórtico del Convento de San Francisco de Valencia (NP849.91/3086)

Sex-biased expression of the TLR7 gene in severe COVID-19 patients: Insights from transcriptomics and epigenomics

This study received support from Instituto de Salud Carlos III (ISCIII): GePEM (PI16/01478/Cofinanciado FEDER; A.S.), DIAVIR (DTS19/00049/Cofinanciado FEDER, A.S.), Resvi-Omics (PI19/01039/Cofinanciado FEDER, A.S.), Agencia Gallega de Innovación (GAIN): Grupos con Potential de Crecimiento (IN607B 2020/08, A.S.); Agencia Gallega para la Gestión del Conocimiento en Salud (ACIS): BI-BACVIR (PRIS-3, A.S.), and CovidPhy (SA 304C, A.S.); ReSVinext (PI16/01569/Cofinanciado FEDER, F.M.T.), Enterogen (PI19/01090/Cofinanciado FEDER, F.M.T.) and consorcio Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CB21/06/00103; F.M.T.); GEN-COVID (IN845D 2020/23, F.M-T.) and Grupos de Referencia Competitiva (IIN607A2021/05, F.M-T). The funders were not involved in the study design, collection, analysis, interpretation of data, the writing of this article or the decision to submit it for publicationThere is abundant epidemiological data indicating that the incidence of severe cases of coronavirus disease (COVID-19) is significantly higher in males than females worldwide. Moreover, genetic variation at the X-chromosome linked TLR7 gene has been associated with COVID-19 severity. It has been suggested that the sex-biased incidence of COVID-19 might be related to the fact that TLR7 escapes X-chromosome inactivation during early embryogenesis in females, thus encoding a doble dose of its gene product compared to males. We analyzed TLR7 expression in two acute phase cohorts of COVID-19 patients that used two different technological platforms, one of them in a multi-tissue context including saliva, nasal, and blood samples, and a third cohort that included different post-infection timepoints of long-COVID-19 patients. We additionally explored methylation patterns of TLR7 using epigenomic data from an independent cohort of COVID-19 patients stratified by severity and sex. In line with genome-wide association studies, we provide supportive evidence indicating that TLR7 has altered CpG methylation patterns and it is consistently downregulated in males compared to females in the most severe cases of COVID-19S

Bacteremia in Children Hospitalized with Respiratory Syncytial Virus Infection

Background The risk of bacteremia is considered low in children with acute bronchiolitis. However the rate of occult bacteremia in infants with RSV infection is not well established. The aim was to determine the actual rate and predictive factors of bacteremia in children admitted to hospital due to confirmed RSV acute respiratory illness (ARI), using both conventional culture and molecular techniques. Methods A prospective multicenter study (GENDRES-network) was conducted between 2011–2013 in children under the age of two admitted to hospital because of an ARI. Among those RSV-positive, bacterial presence in blood was assessed using PCR for Meningococcus, Streptococcus pneumoniae, Haemophilus influenzae, Streptococcus pyogenes, Klebsiella pneumoniae, Pseudomonas aeruginosa, Escherichia coli, and Staphylococcus aureus, in addition to conventional cultures. Results 66 children with positive RSV respiratory illness were included. In 10.6% patients, bacterial presence was detected: H. influenzae (n = 4) and S. pneumoniae (n = 2). In those patients with bacteremia, there was a previous suspicion of bacterial superinfection and had received empirical antibiotic treatment 6 out of 7 (85.7%) patients. There were significant differences in terms of severity between children with positive bacterial PCR and those with negative results: PICU admission (100% vs. 50%, P-value = 0.015); respiratory support necessity (100% vs. 18.6%, P-value < 0.001); Wood-Downes score (mean = 8.7 vs. 4.8 points, P-value < 0.001); GENVIP scale (mean = 17 vs. 10.1, P-value < 0.001); and length of hospitalization (mean = 12.1 vs. 7.5 days, P-value = 0.007). Conclusion Bacteremia is not frequent in infants hospitalized with RSV respiratory infection, however, it should be considered in the most severe casesThis work was supported by the Spanish Government (Research Program Health Research Fund (FIS; PI10/00540 y PI13/02382) National Plan I + D + I and FEDER funds) and Regional Galician funds (Promotion of Research Project 10 PXIB 918 184 PR) (FMT), and Ministerio de Ciencia e Innovación (SAF2011-26983) and the Plan Galego IDT, Xunta de Galicia (EM 2012/045) (AS). MC’s research activities had been supported by grants from Instituto de Investigación Sanitaria de Santiago de Compostela. FMT’s research activities have been supported by grants from Instituto Carlos III (Intensificación de la actividad investigadora). Investigators received funding from the European Union’s Seventh Framework Program under ECGA no. 279185 (EUCLIDS) during the production of this paperS

Does Viral Co-Infection Influence the Severity of Acute Respiratory Infection in Children?

Background Multiple viruses are often detected in children with respiratory infection but the significance of co-infection in pathogenesis, severity and outcome is unclear. Objectives To correlate the presence of viral co-infection with clinical phenotype in children admitted with acute respiratory infections (ARI). Methods We collected detailed clinical information on severity for children admitted with ARI as part of a Spanish prospective multicenter study (GENDRES network) between 2011–2013. A nested polymerase chain reaction (PCR) approach was used to detect respiratory viruses in respiratory secretions. Findings were compared to an independent cohort collected in the UK. Results 204 children were recruited in the main cohort and 97 in the replication cohort. The number of detected viruses did not correlate with any markers of severity. However, bacterial superinfection was associated with increased severity (OR: 4.356; P-value = 0.005), PICU admission (OR: 3.342; P-value = 0.006), higher clinical score (1.988; P-value = 0.002) respiratory support requirement (OR: 7.484; P-value < 0.001) and longer hospital length of stay (OR: 1.468; P-value < 0.001). In addition, pneumococcal vaccination was found to be a protective factor in terms of degree of respiratory distress (OR: 2.917; P-value = 0.035), PICU admission (OR: 0.301; P-value = 0.011), lower clinical score (-1.499; P-value = 0.021) respiratory support requirement (OR: 0.324; P-value = 0.016) and oxygen necessity (OR: 0.328; P-value = 0.001). All these findings were replicated in the UK cohort. Conclusion The presence of more than one virus in hospitalized children with ARI is very frequent but it does not seem to have a major clinical impact in terms of severity. However bacterial superinfection increases the severity of the disease course. On the contrary, pneumococcal vaccination plays a protective roleThis work was supported by the Spanish Government (Research Program Health Research Fund (FIS; PI10/00540) National Plan I + D + I and FEDER funds), by Regional Galician funds (Promotion of Research Project 10 PXIB 918 184PR) (FMT), by Ministerio de Ciencia e Innovación (SAF2011-26983), and by the Plan Galego IDT, Xunta de Galicia (EM 2012/045) (AS). A grant was received from the Sistema Universitario Gallego -Modalidad REDES (2014-PG139) from the Xunta de Galicia (to AS and FMT). MCL research activities have been supported by grants from Instituto de Investigación Sanitaria de Santiago de Compostela. FMT research activities have been supported by grants from Instituto Carlos III (Intensificación de la actividad investigadora). Investigators received funding from the European Union’s seventh Framework program under ECGA no. 279185 (EUCLIDS) during the production of this paper. JH was supported by the Imperial College Comprehensive Biomedical Research Centre and the Wellcome Trust Centre for Respiratory Infection at Imperial College (DMPED P26077 to JH). Micropathology Ltd. provided support in the form of salaries for authors ES and CF, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ sectionS

Diagnosis of childhood febrile illness using a multi-class blood RNA molecular signature

BACKGROUND: Appropriate treatment and management of children presenting with fever depend on accurate and timely diagnosis, but current diagnostic tests lack sensitivity and specificity and are frequently too slow to inform initial treatment. As an alternative to pathogen detection, host gene expression signatures in blood have shown promise in discriminating several infectious and inflammatory diseases in a dichotomous manner. However, differential diagnosis requires simultaneous consideration of multiple diseases. Here, we show that diverse infectious and inflammatory diseases can be discriminated by the expression levels of a single panel of genes in blood. METHODS: A multi-class supervised machine-learning approach, incorporating clinical consequence of misdiagnosis as a "cost" weighting, was applied to a whole-blood transcriptomic microarray dataset, incorporating 12 publicly available datasets, including 1,212 children with 18 infectious or inflammatory diseases. The transcriptional panel identified was further validated in a new RNA sequencing dataset comprising 411 febrile children. FINDINGS: We identified 161 transcripts that classified patients into 18 disease categories, reflecting individual causative pathogen and specific disease, as well as reliable prediction of broad classes comprising bacterial infection, viral infection, malaria, tuberculosis, or inflammatory disease. The transcriptional panel was validated in an independent cohort and benchmarked against existing dichotomous RNA signatures. CONCLUSIONS: Our data suggest that classification of febrile illness can be achieved with a single blood sample and opens the way for a new approach for clinical diagnosis. FUNDING: European Union's Seventh Framework no. 279185; Horizon2020 no. 668303 PERFORM; Wellcome Trust (206508/Z/17/Z); Medical Research Foundation (MRF-160-0008-ELP-KAFO-C0801); NIHR Imperial BRC

A 5-transcript signature for discriminating viral and bacterial etiology in pediatric pneumonia

\ua9 2025 The Author(s)Pneumonia stands as the primary cause of death among children under five, yet current diagnosis methods often result in inadequate or unnecessary treatments. Our research seeks to address this gap by identifying host transcriptomic biomarkers in the blood of children with definitive viral and bacterial pneumonia. We performed RNA sequencing on 192 prospectively collected whole blood samples, including 38 controls and 154 pneumonia cases, uncovering a 5-transcript signature (genes FAM20A, BAG3, TDRD9, MXRA7, and KLF14) that effectively distinguishes bacterial from viral pneumonia (area under the curve (AUC): 0.95 [0.88–1.00]). Initial validation using combined definitive and probable cases yielded an AUC of 0.87 [0.77–0.97], while full validation in a new prospective cohort of 32 patients achieved an AUC of 0.92 [0.83–1.00]. This robust signature holds significant potential to enhance diagnostics accuracy for pediatric pneumonia, reducing diagnostic delays and unnecessary treatments and potentially transforming clinical practice

Diagnosis of childhood febrile illness using a multi-class blood RNA molecular signature.

BackgroundAppropriate treatment and management of children presenting with fever depend on accurate and timely diagnosis, but current diagnostic tests lack sensitivity and specificity and are frequently too slow to inform initial treatment. As an alternative to pathogen detection, host gene expression signatures in blood have shown promise in discriminating several infectious and inflammatory diseases in a dichotomous manner. However, differential diagnosis requires simultaneous consideration of multiple diseases. Here, we show that diverse infectious and inflammatory diseases can be discriminated by the expression levels of a single panel of genes in blood.MethodsA multi-class supervised machine-learning approach, incorporating clinical consequence of misdiagnosis as a "cost" weighting, was applied to a whole-blood transcriptomic microarray dataset, incorporating 12 publicly available datasets, including 1,212 children with 18 infectious or inflammatory diseases. The transcriptional panel identified was further validated in a new RNA sequencing dataset comprising 411 febrile children.FindingsWe identified 161 transcripts that classified patients into 18 disease categories, reflecting individual causative pathogen and specific disease, as well as reliable prediction of broad classes comprising bacterial infection, viral infection, malaria, tuberculosis, or inflammatory disease. The transcriptional panel was validated in an independent cohort and benchmarked against existing dichotomous RNA signatures.ConclusionsOur data suggest that classification of febrile illness can be achieved with a single blood sample and opens the way for a new approach for clinical diagnosis.FundingEuropean Union's Seventh Framework no. 279185; Horizon2020 no. 668303 PERFORM; Wellcome Trust (206508/Z/17/Z); Medical Research Foundation (MRF-160-0008-ELP-KAFO-C0801); NIHR Imperial BRC

A 5-transcript signature for discriminating viral and bacterial etiology in pediatric pneumonia

Pneumonia stands as the primary cause of death among children under five, yet current diagnosis methods often result in inadequate or unnecessary treatments. Our research seeks to address this gap by identifying host transcriptomic biomarkers in the blood of children with definitive viral and bacterial pneumonia. We performed RNA sequencing on 192 prospectively collected whole blood samples, including 38 controls and 154 pneumonia cases, uncovering a 5-transcript signature (genes FAM20A, BAG3, TDRD9, MXRA7, and KLF14) that effectively distinguishes bacterial from viral pneumonia (area under the curve (AUC): 0.95 [0.88–1.00]). Initial validation using combined definitive and probable cases yielded an AUC of 0.87 [0.77–0.97], while full validation in a new prospective cohort of 32 patients achieved an AUC of 0.92 [0.83–1.00]. This robust signature holds significant potential to enhance diagnostics accuracy for pediatric pneumonia, reducing diagnostic delays and unnecessary treatments and potentially transforming clinical practice

Bueno va esto!

Ornamentació tipText a 1 colSign.: [ ]