scholarly journals Biomarker candidates for progression and clinical management of COVID-19 associated pneumonia at time of admission

2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Joan Calvet ◽  
Antoni Berenguer-Llergo ◽  
Marina Gay ◽  
Marta Massanella ◽  
Pere Domingo ◽  
...  
Keyword(s):  
Prognostic Factors ◽  
Specific Treatment ◽  
Therapeutic Strategies ◽  
Plasma Samples ◽  
Specific Therapy ◽  
Before And After ◽  
Critical Patients ◽  
Lipids Metabolism ◽  
Time Of Admission ◽  
Potential Biomarkers

AbstractCOVID-19 pathophysiology is currently not fully understood, reliable prognostic factors remain elusive, and few specific therapeutic strategies have been proposed. In this scenario, availability of biomarkers is a priority. MS-based Proteomics techniques were used to profile the proteome of 81 plasma samples extracted in four consecutive days from 23 hospitalized COVID-19 associated pneumonia patients. Samples from 10 subjects that reached a critical condition during their hospital stay and 10 matched non-severe controls were drawn before the administration of any COVID-19 specific treatment and used to identify potential biomarkers of COVID-19 prognosis. Additionally, we compared the proteome of five patients before and after glucocorticoids and tocilizumab treatment, to assess the changes induced by the therapy on our selected candidates. Forty-two proteins were differentially expressed between patients' evolution groups at 10% FDR. Twelve proteins showed lower levels in critical patients (fold-changes 1.20–3.58), of which OAS3 and COG5 found their expression increased after COVID-19 specific therapy. Most of the 30 proteins over-expressed in critical patients (fold-changes 1.17–4.43) were linked to inflammation, coagulation, lipids metabolism, complement or immunoglobulins, and a third of them decreased their expression after treatment. We propose a set of candidate proteins for biomarkers of COVID-19 prognosis at the time of hospital admission. The study design employed is distinctive from previous works and aimed to optimize the chances of the candidates to be validated in confirmatory studies and, eventually, to play a useful role in the clinical practice.

Label-Free Mass Spectrometry-Based Plasma Proteomics Identified LY6D, DSC3, CDSN, SERPINB12, and SLURP1,as Novel Protein Biomarkers For Pulmonary Tuberculosis

2019 ◽  
Vol 17 ◽  
Author(s):  
Xiaoli Yu ◽  
Lu Zhang ◽  
Na Li ◽  
Peng Hu ◽  
Zhaoqin Zhu ◽  
...  
Keyword(s):  
Pulmonary Tuberculosis ◽  
Search Algorithm ◽  
Differentially Expressed ◽  
P Value ◽  
Plasma Samples ◽  
Label Free ◽  
Protein Biomarkers ◽  
Protein Database ◽  
Leave One Out ◽  
Potential Biomarkers

Aim: We aimed to identify new plasma biomarkers for the diagnosis of Pulmonary tuberculosis. Background: Tuberculosis is an ancient infectious disease that remains one of the major global health problems. Until now, effective, convenient, and affordable methods for diagnosis of Pulmonary tuberculosis were still lacked. Objective: This study focused on construct a label-free LC-MS/MS based comparative proteomics between six tuberculosis patients and six healthy controls to identify differentially expressed proteins (DEPs) in plasma. Method: To reduce the influences of high-abundant proteins, albumin and globulin were removed from plasma samples using affinity gels. Then DEPs from the plasma samples were identified using a label-free Quadrupole-Orbitrap LC-MS/MS system. The results were analyzed by the protein database search algorithm SEQUEST-HT to identify mass spectra to peptides. The predictive abilities of combinations of host markers were investigated by general discriminant analysis (GDA), with leave-one-out cross-validation. Results: A total of 572 proteins were identified and 549 proteins were quantified. The threshold for differentially expressed protein was set as adjusted p-value < 0.05 and fold change ≥1.5 or ≤0.6667, 32 DEPs were found. ClusterVis, TBtools, and STRING were used to find new potential biomarkers of PTB. Six proteins, LY6D, DSC3, CDSN, FABP5, SERPINB12, and SLURP1, which performed well in the LOOCV method validation, were termed as potential biomarkers. The percentage of cross-validated grouped cases correctly classified and original grouped cases correctly classified is greater than or equal to 91.7%. Conclusion: We successfully identified five candidate biomarkers for immunodiagnosis of PTB in plasma, LY6D, DSC3, CDSN, SERPINB12, and SLURP1. Our work supported this group of proteins as potential biomarkers for pulmonary tuberculosis, and be worthy of further validation.

Plasma checkpoint protein 1 (Chk1) as a potential diagnostic biomarker for opisthorchiasis and cholangiocarcinoma

2021 ◽  
pp. 1-13
Author(s):  
Teva Phanaksri ◽  
Yodying Yingchutrakul ◽  
Sittiruk Roytrakul ◽  
Sattrachai Prasopdee ◽  
Anthicha Kunjantarachot ◽  
...  
Keyword(s):  
Diagnostic Methods ◽  
Protein Network ◽  
Enzyme Linked Immunosorbent Assay ◽  
Plasma Samples ◽  
Diagnostic Biomarker ◽  
Checkpoint Protein ◽  
Venn Diagrams ◽  
Network Prediction ◽  
Candidate Protein ◽  
Potential Biomarkers

BACKGROUND: Patients infected with a parasite often develop opisthorchiasis viverrini, which often progresses into cholangiocarcinoma (CCA) due to the asymptomatic nature of the infection. Currently, there are no effective diagnostic methods for opisthorchiasis or cholangiocarcinoma. OBJECTIVE: The aim of this study was to identify the host-responsive protein that can be developed as a diagnostic biomarker of opisthorchiasis and cholangiocarcinoma. METHODS: Plasma samples were collected from non-OVCCA, OV, and CCA subjects, and the proteomes were investigated by LC-MS/MS. Venn diagrams and protein network prediction by STITCH were used to identify the potential biomarkers. The level of candidate protein, the plasma checkpoint protein 1 (Chk1), was measured by indirect enzyme-linked immunosorbent assay (ELISA). RESULTS: Chk1 was present in the center of the protein network analysis in both the OV and CCA groups. In addition, the plasma Chk1 levels were significantly increased in both groups (P< 0.05). The sensitivity of the opisthorchiasis viverrini and cholangiocarcinoma was 59.38% and 65.62%, respectively, while the specificity of both was 85.71%. CONCLUSION: Chk1 was identified by differential plasma proteomes and was increased in O. viverrini-infected and cholangiocarcinoma-derived plasma samples. Higher levels of plasma Chk1 levels may serve as a potential diagnostic biomarker for opisthorchiasis and cholangiocarcinoma.

scholarly journals Effect of COVID-19 outbreak on emergency department attendances in an Italian academic hospital

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
M Poletto ◽  
G Perri ◽  
F Malacarne ◽  
B Bianchet ◽  
A Doimo ◽  
...  
Keyword(s):  
Emergency Department ◽  
Initial Phase ◽  
Mainland China ◽  
Hospital Setting ◽  
Academic Hospital ◽  
Significant Difference ◽  
Before And After ◽  
Life Threatening ◽  
The Mean ◽  
Critical Patients

Abstract Background Coronavirus disease 2019 (COVID-19) is a viral infection caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The disease was discovered during the 2019 outbreak in Mainland China and the first cases were reported in Italy on February 21, 2020. This study evaluates the emergency department (ED) attendances of an academic hospital in northern Italy before and after media reported the news of the first infected patients in Italy. Methods Adult attendances in ED in February 2020 were analysed dividing the period into 4 weeks (days 1-7, 8-14, 15-21, 22-28) compared with the same periods in 2019. The visits were analysed separately according to the Italian colour code of triage: white (non-critical), green (low-critical), yellow (medium critical), red (life-threatening). The mean weekly number of attendances was compared with t-test. Results February 2020 total ED attendances compared with February 2019 were 4865 vs 5029 (-3.3%), of which white codes were 834 vs 762 (+9.4%), green 2450 vs 2580 (-5.0%), yellow 1427 vs 1536 (-7.1%), red 154 vs 151 (+2.0%). February 2020 weekly mean ED attendances compared with February 2019 had statistically significant difference only in the fourth week (days 22-28) for green codes (75 vs 92, p = 0.007) and yellow codes (41 vs 52, p = 0.047), not for white (27 vs 26, p = 0.760) and red codes (5 vs 5, p = 0.817). The first three weeks of February 2020 compared with 2019 showed no statistically significant difference in weekly mean ED attendances. Conclusions There was a significant reduction of green and yellow codes attendances at ED in the fourth week of February 2020, corresponding to the initial phase of Italian COVID-19 outbreak. The fear of contracting SARS-CoV-2 by attending the ED probably acted as a significant deterrent in visits, especially for low and medium critical patients. Additional data are required to better understand the phenomenon, including the behaviour of non-critical attendances. Key messages A reduction of green and yellow codes attendances was reported during initial phase of COVID-19 outbreak in an Italian academic hospital. Fear of contracting COVID-19 infection in a hospital setting could impact on emergency department attendances.

The effect of key DNA methylation in different regions on gene expression in hepatocellular carcinoma

2021 ◽  
Author(s):  
Yu-Xian Liu ◽  
Qian-Zhong Li ◽  
Yan-Ni Cao
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Dna Methylation ◽  
Prognostic Factors ◽  
Potential Biomarkers

Four genes related to DNA methylation were found to be independent prognostic factors and potential biomarkers for hepatocellular carcinoma.

scholarly journals Vasculotoxicity of Chemotherapy: Assessment оf Endothelial Dysfunction Biomarkers’ Levels in Gastric Cancer Patients

Kardiologiia ◽  
2020 ◽  
Vol 60 (5) ◽  
pp. 35-40
Author(s):  
Yu. Yu. Kirichenko ◽  
Yu. N. Belenkov ◽  
E. V. Privalova ◽  
Yu. I. Naymann ◽  
E. P. Gitel ◽  
...  
Keyword(s):  
Endothelial Dysfunction ◽  
Healthy Volunteers ◽  
Stomach Cancer ◽  
Specific Treatment ◽  
Study Groups ◽  
Main Group ◽  
Control Group ◽  
Instrumental Evaluation ◽  
Oncological Patients ◽  
Before And After

Aim To evaluate dynamics of biomarkers for endothelial dysfunction (ED), including endothelin-1 (ET-1) and von Willebrand factor (VWF) in patients with stomach cancer (adenocarcinoma) before and after polychemotherapy (PCT); to compare these results with respective values in healthy volunteers and patients with cardiovascular diseases (CVD); to study correlations of the ED biomarkers with indexes of instrumental evaluation of endothelial dysfunction.Material and methods The study included 75 participants, including 25 healthy volunteers (control group), 25 patients with documented CVDs (arterial hypertension + ischemic heart disease), and 25 patients of the main group with histologically documented stage II-IV stomach cancer (adenocarcinoma) who received different courses of PCT with platinum-based agents (oxaliplatin, cisplatin) and fluoropyrimidines (5 fluorouracil, capecitabin). Laboratory measurement of ED biomarkers, computerized nailfold video capillaroscopy (CNVC), and finger laser photoplethysmography (PPG) (methods for noninvasive evaluation of vascular wall and ED), electrocardiography, 24-h ECG Holter monitoring, and echocardiography (EchoCG) were performed for all patients of the main group prior to PCT and within one months after the last course completion. This evaluation was performed once for healthy volunteers and patients of the CVD group upon inclusion into the study.Results In the main group, ET-1 levels were non-significantly lower than normal and did not change during the courses of antitumor treatment (0.95 [0.6; 1.4] and 0.94 [0.7; 1.4] pg /ml (р<0.9) before and after PCT, respectively). Statistically significant differences were found between the control group and oncological patients after the treatment (р<0.04). Levels of VWF remained within the normal range in all examined participants and did not significantly differ between study groups, including oncological patients before and after the specific treatment (р>0.05 for all comparisons). The correlation analysis detected significant correlations of ET-1 levels with functional disorders of microcirculation, ET-1 with the occlusion index (rs=0.56; p=0.005), ЕТ-1 with percentage of capillary restoration (PCR, rs= –0.72; p=0.018) and with the incidence rate of supraventricular extrasystole (rs=0.48; p=0.032).Conclusion The dynamics of ED biomarkers was studied for the first time in patients with stomach cancer receiving a specific antitumor therapy. Although no significant changes in ЕТ-1 and VWF were observed during the PCT (probably due to exhaustion of the endothelial system and a small patient sample), these indexes can be considered as early vasculotoxicity markers due to the presence of significant correlations with indexes of impaired endothelial function according to the results of instrumental evaluation.

scholarly journals Modeling glioblastoma invasion using human brain organoids and single-cell transcriptomics

2019 ◽  
Author(s):  
Teresa G Krieger ◽  
Stephan M Tirier ◽  
Jeongbin Park ◽  
Tanja Eisemann ◽  
Heike Peterziel ◽  
...  
Keyword(s):  
Single Cell ◽  
Specific Treatment ◽  
Cellular Heterogeneity ◽  
Patient Specific ◽  
Before And After ◽  
Invasive Capacity ◽  
Transcriptional Changes ◽  
Potential Interactions

AbstractGlioblastoma multiforme (GBM) are devastating neoplasms with high invasive capacity. GBM has been difficult to study in vitro. Therapeutic progress is also limited by cellular heterogeneity within and between tumors. To address these challenges, we present an experimental model using human cerebral organoids as a scaffold for patient-derived glioblastoma cell invasion. By tissue clearing and confocal microscopy, we show that tumor cells within organoids extend a network of long microtubes, recapitulating the in vivo behavior of GBM. Single-cell RNA-seq of GBM cells before and after co-culture with organoid cells reveals transcriptional changes implicated in the invasion process that are coherent across patient samples, indicating that GBM cells reactively upregulate genes required for their dispersion. Functional therapeutic targets are identified by an in silico receptor-ligand pairing screen detecting potential interactions between GBM and organoid cells. Taken together, our model has proven useful for studying GBM invasion and transcriptional heterogeneity in vitro, with applications for both pharmacological screens and patient-specific treatment selection at a time scale amenable to clinical practice.

Predictors of treatment effect

2019 ◽  
pp. 188-207
Author(s):  
Richard D Riley ◽  
Aroon Hingorani ◽  
Karel GM Moons
Keyword(s):  
Prognostic Factors ◽  
Treatment Effect ◽  
Interaction Effect ◽  
Specific Treatment ◽  
Health Condition ◽  
Effect Modification ◽  
Sign Test ◽  
Stratified Care ◽  
Multiple Trials ◽  
Using Data

A predictor of treatment effect is any factor or combination of factors (such as a patient characteristic, symptom, sign, test, or biomarker result) associated with the effect (benefit or harm) of a specific treatment in persons with a particular disease or health condition. Various terms are used across disciplines to refer to prediction of treatment effect, including treatment-predictor (treatment-covariate) interaction, effect modification, predictive (as opposed to prognostic) factors (in oncology), or moderation analysis. This chapter reviews principles of the design of studies of treatment effect predictors, such as exploration of treatment-predictor interactions in randomized trials and the importance of replication of such estimates using data from multiple trials. The application of predictors of treatment effect in practice for matching individuals or subgroups to specific treatments is introduced as one type of stratified care, and the need for impact studies to investigate whether stratified care leads to better outcomes and improved efficiency of healthcare is highlighted.

scholarly journals 991: Prognostic factors for successful VBAC in women with PROM at the time of admission

2019 ◽  
Vol 220 (1) ◽  
pp. S638
Author(s):  
Yaniv Zipori ◽  
Chen Ben-David ◽  
Roy Lauterbach ◽  
Amir Weissman ◽  
Ron Beloosesky ◽  
...  
Keyword(s):  
Prognostic Factors ◽  
Time Of Admission
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