biochemical biomarkers
Recently Published Documents


TOTAL DOCUMENTS

159
(FIVE YEARS 46)

H-INDEX

26
(FIVE YEARS 3)

2021 ◽  
Author(s):  
Arjun Chandna ◽  
Raman Mahajan ◽  
Priyanka Gautam ◽  
Lazaro Mwandigha ◽  
Karthik Gunasekaran ◽  
...  

ABSTRACTBackgroundIn locations where few people have received COVID-19 vaccines, health systems remain vulnerable to surges in SARS-CoV-2 infections. Tools to identify patients suitable for community-based management are urgently needed.MethodsWe prospectively recruited adults presenting to two hospitals in India with moderate symptoms of laboratory-confirmed COVID-19 in order to develop and validate a clinical prediction model to rule-out progression to supplemental oxygen requirement. The primary outcome was defined as any of the following: SpO2 < 94%; respiratory rate > 30 bpm; SpO2/FiO2 < 400; or death. We specified a priori that each model would contain three clinical parameters (age, sex and SpO2) and one of seven shortlisted biochemical biomarkers measurable using near-patient tests (CRP, D-dimer, IL-6, NLR, PCT, sTREM-1 or suPAR), to ensure the models would be suitable for resource-limited settings. We evaluated discrimination, calibration and clinical utility of the models in a temporal external validation cohort.Findings426 participants were recruited, of whom 89 (21·0%) met the primary outcome. 257 participants comprised the development cohort and 166 comprised the validation cohort. The three models containing NLR, suPAR or IL-6 demonstrated promising discrimination (c-statistics: 0·72 to 0·74) and calibration (calibration slopes: 1·01 to 1·05) in the validation cohort, and provided greater utility than a model containing the clinical parameters alone.InterpretationWe present three clinical prediction models that could help clinicians identify patients with moderate COVID-19 suitable for community-based management. The models are readily implementable and of particular relevance for locations with limited resources.FundingMédecins Sans Frontières, India.RESEARCH IN CONTEXTEvidence before this studyA living systematic review by Wynants et al. identified 137 COVID-19 prediction models, 47 of which were derived to predict whether patients with COVID-19 will have an adverse outcome. Most lacked external validation, relied on retrospective data, did not focus on patients with moderate disease, were at high risk of bias, and were not practical for use in resource-limited settings. To identify promising biochemical biomarkers which may have been evaluated independently of a prediction model and therefore not captured by this review, we searched PubMed on 1 June 2020 using synonyms of “SARS-CoV-2” AND [“biomarker” OR “prognosis”]. We identified 1,214 studies evaluating biochemical biomarkers of potential value in the prognostication of COVID-19 illness. In consultation with FIND (Geneva, Switzerland) we shortlisted seven candidates for evaluation in this study, all of which are measurable using near-patient tests which are either currently available or in late-stage development.Added value of this studyWe followed the TRIPOD guidelines to develop and validate three promising clinical prediction models to help clinicians identify which patients presenting with moderate COVID-19 can be safely managed in the community. Each model contains three easily ascertained clinical parameters (age, sex, and SpO2) and one biochemical biomarker (NLR, suPAR or IL-6), and would be practical for implementation in high-patient-throughput low resource settings. The models showed promising discrimination and calibration in the validation cohort. The inclusion of a biomarker test improved prognostication compared to a model containing the clinical parameters alone, and extended the range of contexts in which such a tool might provide utility to include situations when bed pressures are less critical, for example at earlier points in a COVID-19 surge.Implications of all the available evidencePrognostic models should be developed for clearly-defined clinical use-cases. We report the development and temporal validation of three clinical prediction models to rule-out progression to supplemental oxygen requirement amongst patients presenting with moderate COVID-19. The models are readily implementable and should prove useful in triage and resource allocation. We provide our full models to enable independent validation.


Author(s):  
Salsabil Trigui ◽  
Davorka K. Hackenberger ◽  
Marija Kovačević ◽  
Nikolina Stjepanović ◽  
Goran Palijan ◽  
...  

2021 ◽  
Vol 14 (3) ◽  
pp. 1613-1631
Author(s):  
Christina Nilofer ◽  
Arumugam Mohanapriya

The outbreak of COVID-19 and its mutant variants has become a life-threatening and fatal viral disease to mankind. Several studies have been carried out to identify an effective receptor against coronavirus using clinically driven samples distinguished as hematological, immunological and biochemical biomarkers. Simultaneously, protein interfaces are being researched to understand the structural and functional mechanism of action. Therefore, we characterized and examined the interfaces of corona viral proteins using a dataset consisting of 366 homomeric and 199 heteromeric protein interfaces. The interfaces were analyzed using six parameters including interface area, interface size, van der Waal, hydrogen bond, electrostatic and total stabilizing energies. We observed the interfaces of corona viral proteins (homomer and heteromer) to be alike. Therefore, we clustered the interfaces based on the percent contribution of vdW towards total stabilizing energy as vdW energy dominant (≥60%) and vdW energy subdominant (<60%). We found 91% of interfaces to have vdW energy in dominance with large interface size [146±29 (homomer) and 122±29 (heteromer)] and interface area [1690±683 (homomer) and 1306±355 (heteromer)]. However, we also observed 9% of interfaces to have vdW energy in sub-dominance with small interface size [60±12 (homomer) and 41±20 (heteromer)] and interface area [472±174 (homomer) and 310±199 (heteromer)]. We noticed the interface area of large interfaces to be four-fold more when compared to small interfaces in homomer and heteromer. It was interesting to observe that the small interfaces of homomers to be rich in electrostatics (r2=0.50) destitute of hydrogen bond energy (r2=0.04). However, the heteromeric interfaces were equally pronounced with hydrogen bond (r2=0.70) and electrostatic (r2=0.61) energies. Hence, our earlier findings stating that the small protein interfaces are rich in electrostatic energy remaintrue with the homomeric interfaces of corona viral proteins whereas not in heteromeric interfaces.


2021 ◽  
Author(s):  
Wanessa A Ramsdorf ◽  
Eduarda Roberta Bordin ◽  
Renan cesar Munhoz ◽  
Paloma Pucholobek Panicio ◽  
Adriane Martins Freitas

Abstract Herbicide mixture is used as an alternative to obtain different mechanisms of action acting on weeds, resulting in the frequent presence of pesticides in environmental compartments. As they are products used worldwide, this study evaluated effects of environmentally relevant concentrations of the analytical standards and commercial formulations of the herbicides atrazine (2 µg L− 1) and glyphosate (65 µg L− 1), in isolation and also in mixture (2 + 65 µg L− 1) on the microcrustacean Daphnia magna. Through chronic exposure (21 days) of two generations of organisms, effects on survival and reproductive capacity were observed, as well as responses regarding oxidative stress, determined through the analysis of biochemical biomarkers such as catalase and glutathione S-transferase. In the evaluation of the first generation of test organisms, no significant results related to biochemical biomarkers were observed, only effects over sexual maturation of organisms. However, in the second generation of exposed organisms, changes were observed in all parameters evaluated, with the mixture of herbicide active principles being the treatment responsible for more significant responses (p < 0.05). A statistical difference (p < 0.05) was also observed between analytical standards and commercial formulations, indicating that other components present in the formulations can change the toxicity of the products. Given the difficulty of estimating the effects of mixtures and considering that various stressors are found in the environment, our results support the need to carry out studies that address long-term effects and, above all, that verify what the impacts are across generations, so that the toxicity of products is not underestimated.


2021 ◽  
Vol 10 (11) ◽  
pp. e409101119877
Author(s):  
Ana Catia Santos da Silva ◽  
Aline Santos dos Santos ◽  
Theila dos Santos Santana ◽  
Elissandra Ulbricht Winkaler ◽  
Marcos Gonçalves Lhano

Biochemical biomarkers are commonly used in environmental monitoring programs due to their sensitivity to certain pollutants. From this perspective, their responses can be used as indicators of environmental quality. The present study aimed to determine the activity of the catalase (CAT) and glutathione-S-transferase (GST) enzymes in grasshoppers Abracris flavolineata (De Geer, 1773) from two forest remnant areas in Serra da Jiboia (BA) and compare them between males and females. The specimens were collected at two sites in Serra da Jiboia (Bahia, Brasil), named ‘Baixa de Areia’ and ‘Baixa Grande’. The animals were actively collected in the morning using a sweep net and a 2.5 h sampling effort. In total, 160 individuals were collected, with 80 individuals from each sampling site, 50 males and 30 females. After identification, an incision was made in the lateral region of the abdomen to remove the midgut, which was used to extract the CAT and GST enzymes. The results obtained demonstrated that CAT and GST activity did not vary significantly between sampling areas. However, with regard to sex, enzyme activity was significantly higher in males (p<0.005) in both locations. This is a pioneer study on the responses of CAT and GST activity in grasshoppers in Brazil.


Sign in / Sign up

Export Citation Format

Share Document