METHODS: Participants were recruited in Intensive Care Units (ICUs) from multiple UK hospitals, including fifty-nine patients with abdominal sepsis, eighty-four patients with pulmonary sepsis, forty-two SIRS patients with Out-of-Hospital Cardiac Arrest (OOHCA), sampled at four time points, in addition to thirty healthy control donors. Multiple clinical parameters were measured, including SOFA score, with many differences observed between SIRS and sepsis groups. Differential gene expression analyses were performed using microarray hybridization and data analyzed using a combination of parametric and non-parametric statistical tools.
RESULTS: Nineteen high-performance, differentially expressed mRNA biomarkers were identified between control and combined SIRS/Sepsis groups (FC>20.0, p<0.05), termed 'indicators of inflammation' (I°I), including CD177, FAM20A and OLAH. Best-performing minimal signatures e.g. FAM20A/OLAH showed good accuracy for determination of severe, systemic inflammation (AUC>0.99). Twenty entities, termed 'SIRS or Sepsis' (S°S) biomarkers, were differentially expressed between sepsis and SIRS (FC>2·0, p-value<0.05).
DISCUSSION: The best performing signature for discriminating sepsis from SIRS was CMTM5/CETP/PLA2G7/MIA/MPP3 (AUC=0.9758). The I°I and S°S signatures performed variably in other independent gene expression datasets, this may be due to technical variation in the study/assay platform.
METHODS: FB recordings for six visualised features: secretions (amount and color) and mucosal appearance (erythema, pallor, ridging, oedema) based on pre-determined criteria on a pictorial chart were assessed by two physicians independently, blinded to the clinical history. These features were used to obtain various models of BScoreexp that were plotted against bronchoalveolar lavage (BAL) neutrophil % using a receiver operating characteristic (ROC) curve. Inter- and intra-rater agreement (weighted-kappa, K) were assessed from 30 FBs.
RESULTS: Using BAL neutrophilia of 20% to define inflammation, the highest area under ROC (aROC) of 0.71, 95%CI 0.61-0.82 was obtained by the giving three times weightage to secretion amount and color and adding it to erythema and oedema. Inter-rater K values for secretion amount (K = 0.87, 95%CI 0.73-1.0) and color (K = 0.86, 95%CI 0.69-1.0) were excellent. Respective intra-rater K were 0.95 (0.87-1.0) and 0.68 (0.47-0.89). Other inter-rater K ranged from 0.4 (erythema) to 0.64 (pallor).
CONCLUSION: A repeatable FB-defined bronchitis scoring tool can be derived. However, a prospective study needs to be performed with larger numbers to further evaluate and validate these results.
DATA SYNTHESIS: We searched the following international databases from inception to January 2022: PubMed, Scopus, Web of Science and Embase, and Google Scholar. Our findings of eleven meta-analyses showed that cinnamon consumption can significantly improve total cholesterol (TC) (WMD = -1.01 mg/dL; 95% CI: -2.02, -0.00, p = 0.049), low-density lipoprotein-cholesterol (LDL-C) (WMD = -0.82 mg/dL; 95% CI: -1.57, -0.07, p = 0.032), and high-density lipoprotein-cholesterol (HDL-C) (WMD = 0.47 mg/dL; 95% CI: 0.17, 0.77, p = 0.002) levels but not triglyceride (TG) levels (WMD = -0.13 mg/dL; 95% CI: -0.58, 0.32, p = 0.570). Our results did not show any significant effect of cinnamon on malondialdehyde (MDA) levels (WMD = -0.47; 95% CI: -0.99, 0.05, p = 0.078) and C-reactive protein (CRP) levels (WMD = -1.33; 95% CI: -2.66, 0.00, p = 0.051) but there was enhanced total antioxidant capacity (TAC) in patients with type 2 diabetes (T2DM) and polycystic ovary syndrome (PCOS) (WMD = 0.34; 95% CI: 0.04, 0.64, p = 0.026) and increased levels of interleukin-6 (WMD = -1.48; 95% CI: -2.96, -0.01, p = 0.049).
CONCLUSIONS: Our results support the usefulness of cinnamon intake in modulating an imbalanced lipid profile in some metabolic disorders, particularly PCOS, as well as in improving TAC and interleukin-6. The review protocol was registered on PROSPERO as CRD42022358827.
METHODOLOGY: A cross-sectional study involved 105 apparently healthy adults. Interview questionnaire was used to collect personal information. Participants were excluded if they suffered from acute or chronic inflammatory diseases, or continued using medicines, which might affect the biomedical results.
RESULTS: In association with increased Body Mass Index (BMI), the obese group displayed significant higher markers including: interleukin 6 (IL-6), high sensitivity C reactive protein (hs-CRP), total cholesterol (TC), systolic blood pressure (SBP), and diastolic blood pressure (DBP). Obese group in association with increased waist circumference (WC) was higher significantly in inflammatory markers (IL-6, hs-CRP), lipid profile (TC) and triglyceride (TG), and blood pressure (SBP, DBP). A tertile of a feature of systemic inflammation (hs-CRP) was created, by Ordinal Logistic Regression, after adjusting for the age, gender, smoking habits, physical activity pattern, father and mother's health history; risk factors were the increased BMI [OR: 1.24] (95% CI: 1.005-1.548, P=0.050), IL-6 [OR: 3.35] (95% CI: 1.341-8.398, P=0.010), DBP [OR: 1.19] (95% CI: 1.034-1.367, P=0.015), and reduced Adiponectin [OR: 0.59] (95% CI: 0.435-0.820, P=0.001). Finally, BMI correlated with IL-6 and hs-CRP (r=0.326, P=0.005; r=0.347, P<0.001; respectively), and hs-CRP correlated with IL-6 (r=0.303, P=0.010), and inversely with Adiponectin (r=-0.342, P=0.001).
CONCLUSION: The increased level of IL-6 and reduced Adiponectin, which strongly associated with obesity, indicated that having high BMI is a useful marker in association with IL-6 and further developed systemic inflammation.
METHOD: Blood samples were obtained from 20 healthy blood donors, 30 RA patients who presented with anaemia and 30 patients who had pure iron deficiency anaemia (IDA). The samples were analysed for full blood count, iron, ferritin, transferrin, soluble transferrin receptor and prohepcidin.
RESULTS: The mean prohepcidin level in the control subjects was 256 microg/L. The prohepcidin level was significantly lower in IDA patients (100 microg/L; p < 0.0001) but not significantly different from that of control in RA patients (250 microg/L; p > 0.05). Higher serum soluble transferrin receptor (sTfR) levels were observed in IDA (p < 0.0001) but not in RA compared with that of control (p > 0.05). RA patients were divided into iron depleted and iron repleted subgroups based on the ferritin level. Prohepcidin in the iron depleted group was significantly lower than the iron repleted group and the control (p < 0.0001) and higher levels were observed in the iron repleted group (p < 0.01). sTfR levels in the iron depleted group were significantly higher than the control and the iron repleted patients (p < 0.001). In the iron repleted group, sTfR level was not statistically different from that of control (p > 0.05).
CONCLUSION: Serum prohepcidin is clearly reduced in uncomplicated iron deficiency anaemia. The reduced prohepcidin levels in the iron depleted RA patients suggests that there may be conflicting signals regulating hepcidin production in RA patients. In RA patients who have reduced hepcidin in the iron depleted group (ferritin <60 microg/L) where sTfR levels are increased suggests that these patients are iron deficient. Further studies with a larger cohort of patients are required to substantiate this point.