scholarly journals Development of Gram Stain Scoring System Based on Pro-Inflammatory Cytokines in the Sheep Model for Testing Toxicity of Vaginal Products

2021 ◽  
Vol 3 ◽  
Author(s):  
Kathleen L. Vincent ◽  
Aaron L. Miller ◽  
Carrie Maxwell ◽  
Nicola Richardson-Harman ◽  
Cynthia O'Neill ◽  
...  
Keyword(s):  
Epithelial Cells ◽  
Immune Cells ◽  
Scoring System ◽  
Methodological Approach ◽  
Characteristic Curve ◽  
Enzyme Linked Immunosorbent Assay ◽  
Placebo Control ◽  
Vaginal Microbiome ◽  
Gram Stain ◽  
Inflammatory State

Background: Development of safe, effective products to prevent the sexual transmission of HIV remains a priority. Prior to clinical testing, the products must undergo strict safety evaluations to avoid mucosal drug toxicity, inflammation, and vaginal microbiome (VMB) shifts. Based on the Food and Drug Administration (FDA) guidance, we designed a study to measure the inflammatory markers and VMB changes after intravaginal treatment with products that have been associated with toxicity, with the objective to develop a Gram stain slide scoring system, similar to Nugent scoring, correlated with the proinflammatory cytokines in sheep.Methods: Non-pregnant Dorset ewes (n = 34) were randomized to receive 5 ml intravaginal 4% nonoxynol-9 (N9) contraceptive gel, positive control (0.2% benzalkonium chloride), placebo control [hydroxethyl cellulose (HEC)], or no application daily for 10 days, with 11-day post-treatment follow-up. The vaginal swabs were collected for the cytokines, VMB, and Gram-stained slides. An enzyme-linked immunosorbent assay (ELISA) analysis of cytokines interleukin (IL)-1β, IL-8, CXCL10, and tumor necrosis factor-α (TNF-α) was used to determine inflammatory state of the sample. Vaginal microbiome community types (CT) were utilized to create five equivalent slide subsets for iterative development of a Gram-stained slide scoring system with comparisons with inflammatory state based on the cytokine levels.Results: Digital images of the Gram-stained slides were scored based on Gram staining and morphology of bacteria, presence of sheep epithelial cells, and immune cells. The scoring system was modified in an iterative fashion with weighting based on cytokine categorization of inflamed samples, with three of four cytokine values above the mean indicating that the sample was inflamed. The parameters in the final version of the scoring system included mature epithelial cells, Gram-negative rods, and Gram-positive diplococci indicating normal and immune cells indicating inflammation. The area under the receiver operator characteristic curve (ROC AUC) was 0.725 (ROC AUCs range between 0.5 and 1.0) with a greater area indicating higher diagnostic ability of a test with a binary outcome: inflamed or normal.Conclusion: The scoring system, derived from the advanced VMB and cytokine analyses, provides a validated, practical method for quantification of Gram-stained slides that can be performed in most laboratories, increasing the potential for standardization. The training plan can assist laboratories to determine the safety of intravaginal products in their sheep studies or the methodological approach can be applied to other animal models where such data are also needed.

JAK3-inhibition: Suppressing immune cells while preserving epithelial cells

2012 ◽  
Vol 60 (S 01) ◽  
Author(s):  
T Gossler ◽  
F Ricklefs ◽  
T Deuse ◽  
E Masuda ◽  
V Taylor ◽  
...  
Keyword(s):  
Epithelial Cells ◽  
Immune Cells

scholarly journals Development of a practical prediction score for acute renal injury after surgery for Stanford type A aortic dissection

2020 ◽  
Vol 30 (5) ◽  
pp. 746-753
Author(s):  
Ning Dong ◽  
Hulin Piao ◽  
Yu Du ◽  
Bo Li ◽  
Jian Xu ◽  
...  
Keyword(s):  
Aortic Dissection ◽  
Risk Score ◽  
Scoring System ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Kidney Injury ◽  
Type A ◽  
Postoperative Management ◽  
Prediction Score ◽  
Improve Patient

Abstract OBJECTIVES Acute kidney injury (AKI) is a common complication of cardiovascular surgery that is associated with increased mortality, especially after surgeries involving the aorta. Early detection and prevention of AKI in patients with aortic dissection may help improve outcomes. The objective of this study was to develop a practical prediction score for AKI after surgery for Stanford type A acute aortic dissection (TAAAD). METHODS This was a retrospective cohort study that included 2 independent hospitals. A larger cohort of 326 patients from The Second Hospital of Jilin University was used to identify the risk factors for AKI and to develop a risk score. The derived risk score was externally validated in a separate cohort of 102 patients from the other hospital. RESULTS The scoring system included the following variables: (i) age >45 years; (ii) body mass index >25 kg/m2; (iii) white blood cell count >13.5 × 109/l; and (iv) lowest perioperative haemoglobin <100 g/l, cardiopulmonary bypass duration >150 min and renal malperfusion. On receiver operating characteristic curve analysis, the score predicted AKI with fair accuracy in both the derivation [area under the curve 0.778, 95% confidence interval (CI) 0.726–0.83] and the validation (area under the curve 0.747, 95% CI 0.657–0.838) cohorts. CONCLUSIONS We developed a convenient scoring system to identify patients at high risk of developing AKI after surgery for TAAAD. This scoring system may help identify patients who require more intensive postoperative management and facilitate appropriate interventions to prevent AKI and improve patient outcomes.

scholarly journals Development and Verification of a Deep Learning Algorithm to Evaluate Small-Bowel Preparation Quality

Diagnostics ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1127
Author(s):  
Ji Hyung Nam ◽  
Dong Jun Oh ◽  
Sumin Lee ◽  
Hyun Joo Song ◽  
Yun Jeong Lim
Keyword(s):  
Deep Learning ◽  
Small Bowel ◽  
Scoring System ◽  
Operating Characteristic ◽  
Clinical Evidence ◽  
Learning Algorithm ◽  
Characteristic Curve ◽  
External Validation ◽  
Test Results ◽  
Deep Learning Algorithm

Capsule endoscopy (CE) quality control requires an objective scoring system to evaluate the preparation of the small bowel (SB). We propose a deep learning algorithm to calculate SB cleansing scores and verify the algorithm’s performance. A 5-point scoring system based on clarity of mucosal visualization was used to develop the deep learning algorithm (400,000 frames; 280,000 for training and 120,000 for testing). External validation was performed using additional CE cases (n = 50), and average cleansing scores (1.0 to 5.0) calculated using the algorithm were compared to clinical grades (A to C) assigned by clinicians. Test results obtained using 120,000 frames exhibited 93% accuracy. The separate CE case exhibited substantial agreement between the deep learning algorithm scores and clinicians’ assessments (Cohen’s kappa: 0.672). In the external validation, the cleansing score decreased with worsening clinical grade (scores of 3.9, 3.2, and 2.5 for grades A, B, and C, respectively, p < 0.001). Receiver operating characteristic curve analysis revealed that a cleansing score cut-off of 2.95 indicated clinically adequate preparation. This algorithm provides an objective and automated cleansing score for evaluating SB preparation for CE. The results of this study will serve as clinical evidence supporting the practical use of deep learning algorithms for evaluating SB preparation quality.

Prevention of Dextran Sulfate Sodium-induced Mouse Colitis by a Fungal Protein Ling Zhi-8 via Promoting the Barrier Function of Intestinal Epithelial Cells

2021 ◽  
Author(s):  
Yu-Huan Chen ◽  
Jenn-Yeu Shin ◽  
Hsiu-Mei Wei ◽  
Chi-Chen Lin ◽  
Linda Chia-Hui Yu ◽  
...  
Keyword(s):  
Epithelial Cells ◽  
Immune Cells ◽  
Ganoderma Lucidum ◽  
Dextran Sulfate ◽  
Dextran Sulfate Sodium ◽  
Intestinal Epithelial Cells ◽  
Intestinal Epithelial ◽  
Fungal Protein ◽  
Fungal Immunomodulatory Protein

A fungal immunomodulatory protein Ling Zhi-8 (LZ-8) isolated from Ganoderma lucidum (GL) regulates immune cells and inhibits tumor growth; however, the role of LZ-8 in intestinal epithelial cells (IECs) is...

scholarly journals Plasma interleukin-17 and alpha-fetoprotein combination effectively predicts imminent hepatocellular carcinoma occurrence in liver cirrhotic patients

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Kung-Hao Liang ◽  
Ming-Wei Lai ◽  
Yang-Hsiang Lin ◽  
Yu-De Chu ◽  
Chih-Lang Lin ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Characteristic Curve ◽  
Alpha Fetoprotein ◽  
Enzyme Linked Immunosorbent Assay ◽  
Interleukin 17 ◽  
Medical Need ◽  
Tumor Tissues ◽  
Resected Tumor ◽  
Cirrhotic Patients ◽  
A Prospective Study

Abstract Background Predicting imminent hepatocellular carcinoma (HCC) in liver cirrhotic patients is an unmet medical need. We aimed to investigate circulatory biomarkers and their optimum combinations in a prospective study. Methods We investigated plasma interleukin 17 (IL-17) concentrations, quantified using enzyme-linked immunosorbent assay (ELISA), for the prediction of HCC in a large cohort of 404 HCC-naïve liver cirrhotic patients regularly followed after recruitment. Additionally, IL-17 in surgically resected tumor tissues were evaluated using immunohistochemistry staining. Results IL-17 was detected in HCC tissues. The IL-17 concentrations in the peripheral blood do not have correlation with an extensive list of 31 common demographic, metabolic and liver function variables in the cohort of liver cirrhotic patients. Furthermore, patients stratified by IL-17 and alpha-fetoprotein (AFP) showed distinctive cumulative incidence of HCC. Imminent HCC, defined here as HCC occurrence within 1 year, can be predicted by IL-17 alone with an area under the receiver operating characteristic curve [AUC] of 0.762 (P = 0.002). An multivariate analysis showed that age, hepatitis C viral infection, AFP and IL-17 were four independent factors associated with imminent HCC (adjusted P = 0.03, 0.041, 0.024 and 0.008 respectively). An explicit risk score (R) combining the concentrations of two plasma biomarkers, AFP and IL-17, achieved a high AUC of 0.933 (95% confidence interval 0.893–0.972, P < 0.001) in predicting imminent HCC, with 100% sensitivity and 79.9% specificity at the optimum cutoff. The score is defined as: $${\text{R}} = (2.6914)*{\text{IL-17}} + (0.3909)*{\text{AFP}} - (0.80812875)*{\text{IL-17}}^{2} + (0.10288876884)*{\text{IL-17}}^{2} *{\text{AFP}}.$$ R = ( 2.6914 ) ∗ IL-17 + ( 0.3909 ) ∗ AFP - ( 0.80812875 ) ∗ IL-17 2 + ( 0.10288876884 ) ∗ IL-17 2 ∗ AFP . Conclusions The circulatory IL-17 concentration is a predictor of subsequent HCC occurrence in liver cirrhotic patients. The combination of AFP and IL-17 is highly effective in predicting imminent HCC within 1 year.

Urine β-2-glycoprotein 1 as a biomarker for diagnosis of systemic lupus erythematosus

Lupus ◽  
2021 ◽  
pp. 096120332110142
Author(s):  
Jung Sun Lee ◽  
Eun-Ju Lee ◽  
Jeonghun Yeom ◽  
Ji Seon Oh ◽  
Seokchan Hong ◽  
...  
Keyword(s):  
Systemic Lupus Erythematosus ◽  
Lupus Erythematosus ◽  
Medical Center ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Diagnostic Value ◽  
Urine Samples ◽  
Enzyme Linked Immunosorbent Assay ◽  
Systemic Lupus ◽  
Asan Medical

Objective The need for a biomarker with robust sensitivity and specificity in diagnosing systemic lupus erythematosus (SLE) remains unmet. Compared with blood samples, urine samples are more easily collected; thus, we aimed to identify such a biomarker based on urinary proteomics which could distinguish patients with SLE from healthy controls (HCs). Methods Urine samples were collected from 76 SLE patients who visited rheumatology clinic in 2019 at Asan medical center and from 25 HCs. Urine proteins were analyzed using sequential windowed acquisition of all theoretical fragment ion spectra-mass spectrometry, and the candidate marker was confirmed by enzyme-linked immunosorbent assay (ELISA). Receiver operating characteristic curve analysis was used to determine the diagnostic value of the candidate biomarker. Results Of 1157 proteins quantified, 153 were differentially expressed in urine samples from HCs. Among them were previously known markers including α-1-acid glycoprotein 1, α-2-HS-glycoprotein, ceruloplasmin, and prostaglandin-H2 D-isomerase. Moreover, the amount of β-2 glycoprotein (APOH) was increased in the urine of patients with SLE. The ELISA results also showed the level of urine APOH was higher in patients with SLE than in HCs and patients with rheumatoid arthritis. Moreover, the level was not different between SLE patients with and without nephritis. The urine APOH had an area under the curve value of 0.946 at a cut-off value of 228.53 ng/mg (sensitivity 91.5%, specificity 92.0%) for the diagnosis of SLE. Conclusion The results indicate that the urine APOH level can be an appropriate screening tool in a clinical setting when SLE is suspected.

scholarly journals Rabeprazole inhibits inflammatory reaction by inhibition of cell pyroptosis in gastric epithelial cells

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Jing Xie ◽  
Long Fan ◽  
Liya Xiong ◽  
Peiyu Chen ◽  
Hongli Wang ◽  
...  
Keyword(s):  
Epithelial Cells ◽  
Clinical Sample ◽  
Critical Role ◽  
Enzyme Linked Immunosorbent Assay ◽  
Inflammasome Activation ◽  
Peptic Ulcers ◽  
Gastric Epithelial Cells ◽  
Caspase 1 ◽  
H Pylori

Abstract Background Helicobacter pylori (H. pylori) is a common pathogen in development of peptic ulcers with pyroptosis. Rabeprazole, a critical component of standard triple therapy, has been widely used as the first-line regimen for H. pylori infectious treatment. The aim of this study to explore the function of Rabeprazole on cell pyroptosis in vitro. Methods The clinical sample from patients diagnosed with or without H. pylori-infection were collected to analyze by Immunohistochemistry (IHC). Real-time quantitative PCR (qPCR), western blot (WB) and enzyme linked immunosorbent assay (Elisa) were performed to analyze the effect of Rabeprazole on cell pyroptosis, including LDH, IL-1β and IL-18. Results In this study, we showed that Rabeprazole regulated a phenomenon of cell pyroptosis as confirmed by lactate dehydrogenase (LDH) assay. Further results showed that Rabeprazole inhibited cell pyroptosis in gastric epithelial cells by alleviating GSDMD-executed pyroptosis, leading to decrease IL-1β and IL-18 mature and secretion, which is attributed to NLRP3 inflammasome activation inhibition. Further analysis showed that ASC, NLRP3 and Caspase-1, was significantly repressed in response to Rabeprazole stimulation, resulting in decreasing cleaved-caspase-1 expression. Most important, NLRP3 and GSDMD is significantly increased in gastric tissue of patients with H. pylori infection. Conclusion These findings revealed a critical role of Rabeprazole in cell pyroptosis in patients with H. pylori infection, suggesting that targeting cell pyroptosis is an alternative strategy in improving H. pylori treatment.

scholarly journals Accuracy of conventional and novel scoring systems in predicting severity and outcomes of acute pancreatitis: a retrospective study

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Qing Wu ◽  
Jie Wang ◽  
Mengbin Qin ◽  
Huiying Yang ◽  
Zhihai Liang ◽  
...  
Keyword(s):  
Acute Pancreatitis ◽  
Organ Failure ◽  
Scoring System ◽  
Characteristic Curve ◽  
Failure Prediction ◽  
Scoring Systems ◽  
Mortality Prediction ◽  
Severity Prediction ◽  
Index Of Severity ◽  
Glasgow Score

Abstract Background Recently, several novel scoring systems have been developed to evaluate the severity and outcomes of acute pancreatitis. This study aimed to compare the effectiveness of novel and conventional scoring systems in predicting the severity and outcomes of acute pancreatitis. Methods Patients treated between January 2003 and August 2020 were reviewed. The Ranson score (RS), Glasgow score (GS), bedside index of severity in acute pancreatitis (BISAP), pancreatic activity scoring system (PASS), and Chinese simple scoring system (CSSS) were determined within 48 h after admission. Multivariate logistic regression was used for severity, mortality, and organ failure prediction. Optimum cutoffs were identified using receiver operating characteristic curve analysis. Results A total of 1848 patients were included. The areas under the curve (AUCs) of RS, GS, BISAP, PASS, and CSSS for severity prediction were 0.861, 0.865, 0.829, 0.778, and 0.816, respectively. The corresponding AUCs for mortality prediction were 0.693, 0.736, 0.789, 0.858, and 0.759. The corresponding AUCs for acute respiratory distress syndrome prediction were 0.745, 0.784, 0.834, 0.936, and 0.820. Finally, the corresponding AUCs for acute renal failure prediction were 0.707, 0.734, 0.781, 0.868, and 0.816. Conclusions RS and GS predicted severity better than they predicted mortality and organ failure, while PASS predicted mortality and organ failure better. BISAP and CSSS performed equally well in severity and outcome predictions.

Preparation of Single Cell Suspension from Human Lung Tissue v1

2021 ◽  
Author(s):  
Steven B. Wells ◽  
Peter A. Szabo ◽  
Basak Ural ◽  
Maya M.L. Poon
Keyword(s):  
Epithelial Cells ◽  
Cell Suspension ◽  
Single Cell ◽  
Lung Tissue ◽  
Immune Cells ◽  
Human Lung ◽  
Dilution Factor ◽  
Single Cell Suspension ◽  
Human Lung Tissue ◽  
Defined Media

This protocol describes a method for the isolation of the immune cells, structural and epithelial cells, and progenitors from human lung sections of about two grams. By providing defined media formulations, volumes at each step, and a defined dilution factor for density centrifugation, it yields consistent single-cell suspensions across samples.

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