Age-dependent changes in CXC chemokine ligand 10 serum levels in euthyroid subjects.

Circulating levels of cytokines are deeply influenced by aging, and few data about serum chemokines are available. The aim of this study was to evaluate the influence of aging on circulating CXCL10. One hundred forty healthy subjects (70 males and 70 females), 10-79 years of age, underwent fasting plasma glucose, total cholesterol, high-density lipoprotein (HDL), low-density lipoprotein (LDL), triglyceride, and CXCL8 serum assay. Thyroid hormone testing for thyroid-stimulating hormone (TSH), antithyroglobulin (AbTg), and antithyroperoxidase (AbTPO) autoantibodies and thyroid ultrasonography were performed in all subjects to exclude the presence of clinical or subclinical thyroid disease. Serum CXCL10 levels were assayed in all subjects and found to be increased in 14 of 70 females (20%) and in 4 of 70 males (5.7%) (p = 0.01). In a multiple linear regression model including age, body mass index (BMI), systolic and diastolic blood pressure, glycemia, total cholesterol, HDL, LDL, triglycerides, TSH, AbTPO, AbTg, and CXCL8, only age was significantly related to CXCL10 [C.R. 1.30 (0.28-2.33), p = 0.001]. No relationship was present between CXCL8 serum levels and age, suggesting a specificity of CXCL10 elevation as a function of age. Results of this study, performed in healthy subjects on an age gradient, demonstrate an increase in serum CXCL10 with advancing age overall in females, supporting the hypothesis of enhanced Th1 immune responses in aging.     

Age-related differences in the response of the brain to dietary melatonin

The aged brain is prone to excessive levels of immune activity, not initiated by an acute response to an extrinsic agent. While dietary melatonin is reported to attenuate the extent of expression of proinflammatory genes, little is known about the extent to which these changes can be translated into altered levels of corresponding proteins. The baseline levels of the proinflammatory cytokines, tumor necrosis factor alpha (TNF-α) and interleukin-1 alpha, were greater in older (~29 months old) compared to younger (~7 months old) mouse brains. Acute (3 h) exposure to lipopolysaccharide (LPS) induced activation of nuclear factor kappa B (NF-κB), but not inflammatory cytokines in the brain. The serum level of TNF-α was increased after LPS injection, indicating a systemic immune response to the bacterial cell wall component. Dietary melatonin (40 ppm for 9.3 weeks) did not prevent LPS-induced changes in younger animals but caused an increased systemic TNF-α response in older mice. Melatonin did reduce markers of carbonyl formation in brain proteins of young animals and nitrosylative damage to peptide-bound amino acid residues, in the brains of older animals. Acute LPS challenge did not significantly affect these oxidative markers. Thus, despite lack of clear evidence of attenuation of the NF-κB–cytokine inflammatory trajectory within the CNS by melatonin, this agent did show a protective effect against free radical-initiated injury to amino acid residues within proteins. The results illustrate that previously reported changes in gene expression following melatonin treatment need not be closely paralleled by corresponding changes in protein content.     

Early goal-directed therapy reduces mortality in adult patients with severe sepsis and septic shock: Systematic review and meta-analysis

Introduction:

Survival sepsis campaign guidelines have promoted early goal-directed therapy (EGDT) as a means for reduction of mortality. On the other hand, there were conflicting results coming out of recently published meta-analyses on mortality benefits of EGDT in patients with severe sepsis and septic shock. On top of that, the findings of three recently done randomized clinical trials (RCTs) showed no survival benefit by employing EGDT compared to usual care. Therefore, we aimed to do a meta-analysis to evaluate the effect of EGDT on mortality in severe sepsis and septic shock patients.

Methodology:

We included RCTs that compared EGDT with usual care in our meta-analysis. We searched in Hinari, PubMed, EMBASE, and Cochrane central register of controlled trials electronic databases and other articles manually from lists of references of extracted articles. Our primary end point was overall mortality.

Results:

A total of nine trails comprising 4783 patients included in our analysis. We found that EGDT significantly reduced mortality in a random-effect model (RR, 0.86; 95% confidence interval [CI], 0.72–0.94; P = 0.008;   I² =50%). We also did subgroup analysis stratifying the studies by the socioeconomic status of the country where studies were conducted, risk of bias, the number of sites where the trials were conducted, setting of trials, publication year, and sample size. Accordingly, trials carried out in low to middle economic income countries (RR, 0.078; 95% CI, 0.67–0.91; P = 0.002; I² = 34%) significantly reduced mortality compared to those in higher income countries (RR, 0.93; 95% CI, 0.33–1.06; P = 0.28; I² = 29%). On the other hand, patients receiving EGDT had longer length of hospital stay compared to the usual care (mean difference, 0.49; 95% CI, –0.04–1.02; P = 0.07; I² = 0%).

Conclusion:

The result of our study showed that EGDT significantly reduced mortality in patients with severe sepsis and septic shock. Paradoxically, EGDT increased the length of hospital stay compared to usual routine care.     

Posterior sub-tenon’s bevacizumab injection in diabetic macular edema; a pilot study

Purpose

To evaluate the short-term results of sub-tenon’s injection of bevacizumab in patients with clinically significant macular edema (CSME).

Methods

In this prospective non-comparative interventional case series, sub-tenon’s injection of 2.5 mg/0.1 ml bevacizumab was performed for eyes with CSME. Macular thickness and best corrected visual acuity measurements were performed before and one month after injections.

Results

Nineteen eyes of twelve patients with a mean age of 59.8 ± 5.7 years were evaluated. Thirteen eyes (68.4%) had center-involving macular edema. No significant difference was observed between pre- and post-injection central subfield retinal thickness measurements (P = 0.3). Central subfield thickness measurements improved or remained unchanged in 13 eyes (68.4%). Baseline BCVA of 0.48 ± 0.35 LogMAR improved to 0.36 ± 0.26 LogMAR after injection (P = 0.01). Improvement of >2 lines in BCVA was found in 5 eyes (26.3%), and no eye lost >2 lines of BCVA. No complication associated with sub-tenon’s injection was observed.

Conclusion

Sub-tenon’s injection of bevacizumab resulted in significant short-term visual improvement in eyes with CSME. Retinal thickness changes were not significant.     

Dynamic functional connectivity in temporal lobe epilepsy: a graph theoretical and machine learning approach

Purpose

Functional magnetic resonance imaging (fMRI) in resting state can be used to evaluate the functional organization of the human brain in the absence of any task or stimulus. The functional connectivity (FC) has non-stationary nature and consented to be varying over time. By considering the dynamic characteristics of the FC and using graph theoretical analysis and a machine learning approach, we aim to identify the laterality in cases of temporal lobe epilepsy (TLE).

Methods

Six global graph measures are extracted from static and dynamic functional connectivity matrices using fMRI data of 35 unilateral TLE subjects. Alterations in the time trend of the graph measures are quantified. The random forest (RF) method is used for the determination of feature importance and selection of dynamic graph features including mean, variance, skewness, kurtosis, and Shannon entropy. The selected features are used in the support vector machine (SVM) classifier to identify the left and right epileptogenic sides in patients with TLE.

Results

Our results for the performance of SVM demonstrate that the utility of dynamic features improves the classification outcome in terms of accuracy (88.5% for dynamic features compared with 82% for static features). Selecting the best dynamic features also elevates the accuracy to 91.5%.

Conclusion

Accounting for the non-stationary characteristics of functional connectivity, dynamic connectivity analysis of graph measures along with machine learning approach can identify the temporal trend of some specific network features. These network features may be used as potential imaging markers in determining the epileptogenic hemisphere in patients with TLE.