Protein Oxidation Biomarkers and Myeloperoxidase Activation in Cerebrospinal Fluid in Childhood Bacterial Meningitis

The immunological response in bacterial meningitis (BM) causes the formation of reactive oxygen and nitrogen species (ROS, RNS) and activates myeloperoxidase (MPO), an inflammatory enzyme. Thus, structural oxidative and nitrosative damage to proteins and DNA occurs. We aimed to asses these events in the cerebrospinal fluid (CSF) of pediatric BM patients. Phenylalanine (Phe), para-tyrosine (p-Tyr), nucleoside 2'-deoxiguanosine (2dG), and biomarkers of ROS/RNS-induced protein and DNA oxidation: ortho-tyrosine (o-Tyr), 3-chlorotyrosine (3Cl-Tyr), 3-nitrotyrosine (3NO(2)-Tyr) and 8-oxo-2'-deoxyguanosine (8OHdG), concentrations were measured by liquid chromatography coupled to tandem mass spectrometry in the initial CSF of 79 children with BM and 10 without BM. All biomarkers, normalized with their corresponding precursors, showed higher median concentrations (p <0.0001) in BM compared with controls, except 8OHdG/2dG. The ratios o-Tyr/Phe, 3Cl-Tyr/p-Tyr and 3NO(2)-Tyr/p-Tyr were 570, 20 and 4.5 times as high, respectively. A significantly higher 3Cl-Tyr/p-Tyr ratio was found in BM caused by Streptococcus pneumoniae, than by Haemophilus influenzae type b, or Neisseria meningitidis (p = 0.002 for both). In conclusion, biomarkers indicating oxidative damage to proteins distinguished BM patients from non-BM, most clearly the o-Tyr/Phe ratio. The high 3Cl-Tyr/p-Tyr ratio in pneumococcal meningitis suggests robust inflammation because 3Cl-Tyr is a marker of MPO activation and, indirectly, of inflammation.Peer reviewe

Grupo español de cirugía torácica asistida por videoimagen: método, auditoría y resultados iniciales de una cohorte nacional prospectiva de pacientes tratados con resecciones anatómicas del pulmón

Introduction: our study sought to know the current implementation of video-assisted thoracoscopic surgery (VATS) for anatomical lung resections in Spain. We present our initial results and describe the auditing systems developed by the Spanish VATS Group (GEVATS). Methods: we conducted a prospective multicentre cohort study that included patients receiving anatomical lung resections between 12/20/2016 and 03/20/2018. The main quality controls consisted of determining the recruitment rate of each centre and the accuracy of the perioperative data collected based on six key variables. The implications of a low recruitment rate were analysed for '90-day mortality' and 'Grade IIIb-V complications'. Results: the series was composed of 3533 cases (1917 VATS; 54.3%) across 33 departments. The centres' median recruitment rate was 99% (25-75th:76-100%), with an overall recruitment rate of 83% and a data accuracy of 98%. We were unable to demonstrate a significant association between the recruitment rate and the risk of morbidity/mortality, but a trend was found in the unadjusted analysis for those centres with recruitment rates lower than 80% (centres with 95-100% rates as reference): grade IIIb-V OR=0.61 (p=0.081), 90-day mortality OR=0.46 (p=0.051). Conclusions: more than half of the anatomical lung resections in Spain are performed via VATS. According to our results, the centre's recruitment rate and its potential implications due to selection bias, should deserve further attention by the main voluntary multicentre studies of our speciality. The high representativeness as well as the reliability of the GEVATS data constitute a fundamental point of departure for this nationwide cohort

Implementation of Recommendations on the Use of Corticosteroids in Severe COVID-19

Importance: Research diversity and representativeness are paramount in building trust, generating valid biomedical knowledge, and possibly in implementing clinical guidelines. Objectives: To compare variations over time and across World Health Organization (WHO) geographic regions of corticosteroid use for treatment of severe COVID-19; secondary objectives were to evaluate the association between the timing of publication of the RECOVERY (Randomised Evaluation of COVID-19 Therapy) trial (June 2020) and the WHO guidelines for corticosteroids (September 2020) and the temporal trends observed in corticosteroid use by region and to describe the geographic distribution of the recruitment in clinical trials that informed the WHO recommendation. Design, setting, and participants: This prospective cohort study of 434 851 patients was conducted between January 31, 2020, and September 2, 2022, in 63 countries worldwide. The data were collected under the auspices of the International Severe Acute Respiratory and Emerging Infections Consortium (ISARIC)-WHO Clinical Characterisation Protocol for Severe Emerging Infections. Analyses were restricted to patients hospitalized for severe COVID-19 (a subset of the ISARIC data set). Exposure: Corticosteroid use as reported to the ISARIC-WHO Clinical Characterisation Protocol for Severe Emerging Infections. Main outcomes and measures: Number and percentage of patients hospitalized with severe COVID-19 who received corticosteroids by time period and by WHO geographic region. Results: Among 434 851 patients with confirmed severe or critical COVID-19 for whom receipt of corticosteroids could be ascertained (median [IQR] age, 61.0 [48.0-74.0] years; 53.0% male), 174 307 (40.1%) received corticosteroids during the study period. Of the participants in clinical trials that informed the guideline, 91.6% were recruited from the United Kingdom. In all regions, corticosteroid use for severe COVID-19 increased, but this increase corresponded to the timing of the RECOVERY trial (time-interruption coefficient 1.0 [95% CI, 0.9-1.2]) and WHO guideline (time-interruption coefficient 1.9 [95% CI, 1.7-2.0]) publications only in Europe. At the end of the study period, corticosteroid use for treatment of severe COVID-19 was highest in the Americas (5421 of 6095 [88.9%]; 95% CI, 87.7-90.2) and lowest in Africa (31 588 of 185 191 [17.1%]; 95% CI, 16.8-17.3). Conclusions and relevance: The results of this cohort study showed that implementation of the guidelines for use of corticosteroids in the treatment of severe COVID-19 varied geographically. Uptake of corticosteroid treatment was lower in regions with limited clinical trial involvement. Improving research diversity and representativeness may facilitate timely knowledge uptake and guideline implementation

Characteristics and outcomes of COVID-19 patients admitted to hospital with and without respiratory symptoms

Background: COVID-19 is primarily known as a respiratory illness; however, many patients present to hospital without respiratory symptoms. The association between non-respiratory presentations of COVID-19 and outcomes remains unclear. We investigated risk factors and clinical outcomes in patients with no respiratory symptoms (NRS) and respiratory symptoms (RS) at hospital admission. Methods: This study describes clinical features, physiological parameters, and outcomes of hospitalised COVID-19 patients, stratified by the presence or absence of respiratory symptoms at hospital admission. RS patients had one or more of: cough, shortness of breath, sore throat, runny nose or wheezing; while NRS patients did not. Results: Of 178,640 patients in the study, 86.4&nbsp;% presented with RS, while 13.6&nbsp;% had NRS. NRS patients were older (median age: NRS: 74 vs RS: 65) and less likely to be admitted to the ICU (NRS: 36.7&nbsp;% vs RS: 37.5&nbsp;%). NRS patients had a higher crude in-hospital case-fatality ratio (NRS 41.1&nbsp;% vs. RS 32.0&nbsp;%), but a lower risk of death after adjusting for confounders (HR 0.88 [0.83-0.93]). Conclusion: Approximately one in seven COVID-19 patients presented at hospital admission without respiratory symptoms. These patients were older, had lower ICU admission rates, and had a lower risk of in-hospital mortality after adjusting for confounders

At-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods

By September 2022, more than 600 million cases of SARS-CoV-2 infection have been reported globally, resulting in over 6.5 million deaths. COVID-19 mortality risk estimators are often, however, developed with small unrepresentative samples and with methodological limitations. It is highly important to develop predictive tools for pulmonary embolism (PE) in COVID-19 patients as one of the most severe preventable complications of COVID-19. Early recognition can help provide life-saving targeted anti-coagulation therapy right at admission. Using a dataset of more than 800,000 COVID-19 patients from an international cohort, we propose a cost-sensitive gradient-boosted machine learning model that predicts occurrence of PE and death at admission. Logistic regression, Cox proportional hazards models, and Shapley values were used to identify key predictors for PE and death. Our prediction model had a test AUROC of 75.9% and 74.2%, and sensitivities of 67.5% and 72.7% for PE and all-cause mortality respectively on a highly diverse and held-out test set. The PE prediction model was also evaluated on patients in UK and Spain separately with test results of 74.5% AUROC, 63.5% sensitivity and 78.9% AUROC, 95.7% sensitivity. Age, sex, region of admission, comorbidities (chronic cardiac and pulmonary disease, dementia, diabetes, hypertension, cancer, obesity, smoking), and symptoms (any, confusion, chest pain, fatigue, headache, fever, muscle or joint pain, shortness of breath) were the most important clinical predictors at admission. Age, overall presence of symptoms, shortness of breath, and hypertension were found to be key predictors for PE using our extreme gradient boosted model. This analysis based on the, until now, largest global dataset for this set of problems can inform hospital prioritisation policy and guide long term clinical research and decision-making for COVID-19 patients globally. Our machine learning model developed from an international cohort can serve to better regulate hospital risk prioritisation of at-risk patients

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field

Erratum to: Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition) (Autophagy, 12, 1, 1-222, 10.1080/15548627.2015.1100356

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