Anti-Inflammatory and Antioxidant Mechanism of Tangeretin in Activated Microglia

Tangeretin, a flavonoid from citrus fruit peels, has been proven to play an important role in anti-inflammatory responses and neuroprotective effects in several disease models, but further study is necessary for elucidating the detailed mechanisms of these effects. In this study, we examined the anti-inflammatory effect of tangeretin in lipopolysaccharide (LPS)-stimulated microglia. We first observed that tangeretin inhibited LPS-induced production of nitric oxide, tumor necrosis factor alpha, interleukin (IL)-6, and IL-1β, as well as LPS-induced mRNA expression of inducible nitric oxide synthases and cytokines. Additionally, we found that the activities, mRNA levels, and protein levels of matrix metalloproteinase (MMP)-3 and MMP-8 were inhibited, while the expression of tissue inhibitor of metalloproteinase-2 was enhanced by tangeretin in LPS-stimulated microglia. Further mechanistic study showed that tangeretin suppressed LPS-induced phosphorylation of mitogen-activated protein kinases and Akt. Also, tangeretin inhibited nuclear factor-κB by upregulating sirtuin 1 and 5′-adenosine monophosphate-activated protein kinase. We further demonstrated the antioxidant effect of tangeretin by showing that tangeretin inhibited reactive oxygen species production and p47^phox phosphorylation, while enhancing the expression of heme oxygenase-1 and the DNA binding activity of nuclear factor-erythroid 2-related factor 2 to the antioxidant response element in LPS-stimulated microglia. Taken together, the results of the present study demonstrate that tangeretin possesses a potent anti-inflammatory and antioxidant effect in microglia.     

Assessment of DCE–MRI parameters for brain tumors through implementation of physiologically–based pharmacokinetic model approaches for Gd-DOTA

Dynamic-contrast enhanced magnetic resonance imaging (DCE–MRI) is used for detailed characterization of pathology of lesions sites, such as brain tumors, by quantitative analysis of tracer’s data through the use of pharmacokinetic (PK) models. A key component for PK models in DCE–MRI is the estimation of the concentration–time profile of the tracer in a nearby vessel, referred as Arterial Input Function (AIF). The aim of this work was to assess through full body physiologically-based pharmacokinetic (PBPK) model approaches the PK profile of gadoteric acid (Gd-DOTA) and explore potential application for parameter estimation in DCE-MRI based on PBPK-derived AIFs. The PBPK simulations were generated through Simcyp^® platform and the predicted PK parameters for Gd-DOTA were compared with available clinical data regarding healthy volunteers and renal impairment patients. The assessment of DCE-MRI parameters was implemented by utilizing similar virtual profiles based on gender, age and weight to clinical profiles of patients diagnosed with glioblastoma multiforme. The PBPK–derived AIFs were then used to compute DCE-MRI parameters through the Extended Tofts Model and compared with the corresponding ones derived from image-based AIF computation. The comparison involved: (i) image measured AIF of patients vs AIF of in silico profile, and, (ii) population average AIF vs in silico mean AIFs. The results indicate that PBPK–derived AIFs allowed the estimation of comparable imaging biomarkers with those calculated from typical DCE–MRI image analysis. The incorporation of PBPK models and potential utilization of in silico profiles to real patient data, can provide new perspectives in DCE–MRI parameter estimation and data analysis.     

Estimation of phase signal change in neuronal current MRI for evoke response of tactile detection with realistic somatosensory laminar network model

Magnetic field generated by neuronal activity could alter magnetic resonance imaging (MRI) signals but detection of such signal is under debate. Previous researches proposed that magnitude signal change is below current detectable level, but phase signal change (PSC) may be measurable with current MRI systems. Optimal imaging parameters like echo time, voxel size and external field direction, could increase the probability of detection of this small signal change. We simulate a voxel of cortical column to determine effect of such parameters on PSC signal. We extended a laminar network model for somatosensory cortex to find neuronal current in each segment of pyramidal neurons (PN). 60,000 PNs of simulated network were positioned randomly in a voxel. Biot–savart law applied to calculate neuronal magnetic field and additional phase. The procedure repeated for eleven neuronal arrangements in the voxel. PSC signal variation with the echo time and voxel size was assessed. The simulated results show that PSC signal increases with echo time, especially 100/80 ms after stimulus for gradient echo/spin echo sequence. It can be up to 0.1 mrad for echo time = 175 ms and voxel size = 1.48 × 1.48 × 2.18 mm³. With echo time less than 25 ms after stimulus, it was just acquired effects of physiological noise on PSC signal. The absolute value of the signal increased with decrease of voxel size, but its components had complex variation. External field orthogonal to local surface of cortex maximizes the signal. Expected PSC signal for tactile detection in the somatosensory cortex increase with echo time and have no oscillation.     

Wound,pressure ulcer and burn guidelines – 4: Guidelines for the management of connective tissue disease/vasculitis-associated skin ulcers

The Japanese Dermatological Association prepared guidelines focused on the treatment of skin ulcers associated with connective tissue disease/vasculitis practical in clinical settings of dermatological care. Skin ulcers associated with connective tissue diseases or vasculitis occur on the background of a wide variety of diseases including, typically, systemic sclerosis but also systemic lupus erythematosus (SLE), dermatomyositis, rheumatoid arthritis (RA), various vasculitides and antiphospholipid antibody syndrome (APS). Therefore, in preparing the present guidelines, we considered diagnostic/therapeutic approaches appropriate for each of these disorders to be necessary and developed algorithms and clinical questions for systemic sclerosis, SLE, dermatomyositis, RA, vasculitis and APS.     

Prediction of human pharmacokinetics of typical compounds by a physiologically based method using chimeric mice with humanized liver

1. In this study, total body clearance (CL_t), volume of distribution at steady state (V_ss) and plasma concentration–time profiles in humans of model compounds were predicted using chimeric mice with humanized livers.

2. On the basis of assumption that unbound intrinsic clearance (CL_Uint) per liver weight in chimeric mice was equal to those in humans, CL_t were predicted by substituting human liver blood flow and liver weights in well-stirred model. V_ss were predicted by Rodgers equation using scaling factors of tissue-plasma concentration ratios (SF_Kp) in chimeric mice estimated from a difference between the observed and predicted V_ss. These physiological approaches showed high prediction accuracy for CL_t and V_ss values in humans.

3. We compared the predictability of CL_t and V_ss determined by the physiologically based predictive approach using chimeric mice with those from predictive methods reported by Pharmaceutical Research Manufacturers of America. The physiological approach using chimeric mice indicated the best prediction accuracy in each predictive method.

4. Simulation of human plasma concentration–time profiles were generally successful with physiologically based pharmacokinetic (PBPK) model incorporating CL_Uint and SF_Kp obtained from chimeric mice.

5. Combined application of chimeric mice and PBPK modeling is effective for prediction of human PK in various compounds.

     

Precision Medicine for Tobacco Dependence: Development and Validation of the Nicotine Metabolite Ratio

Quitting smoking significantly reduces the risk of tobacco-related morbidity and mortality, yet there is a high rate of relapse amongst smokers who try to quit. Phenotypic biomarkers have the potential to improve smoking cessation outcomes by identifying the best available treatment for an individual smoker. In this review, we introduce the nicotine metabolite ratio (NMR) as a reliable and stable phenotypic measure of nicotine metabolism that can guide smoking cessation treatment among smokers who wish to quit. We address how the NMR accounts for sources of variation in nicotine metabolism including genotype and other biological and environmental factors such as estrogen levels, alcohol use, body mass index, or menthol exposure. Then, we highlight clinical trials that validate the NMR as a biomarker to predict therapeutic response to different pharmacotherapies for smoking cessation. Current evidence supports the use of nicotine replacement therapy for slow metabolizers, and non-nicotine treatments such as varenicline for normal metabolizers. Finally, we discuss future research directions to elucidate mechanisms underlying NMR associations with treatment response, and facilitate the implementation of the NMR as biomarker in clinical practice to guide smoking cessation.     

Reciprocal Peer Support for Post-partum Patients with Diabetes: A Needs Assessment for the Diabetes Buddy Program

While peer support has been investigated in multiple clinical contexts, its application to the postpartum setting is unknown. The aim was to assess acceptability of a postpartum peer support program for women with diabetes. Observational survey-based needs assessment of forty low-income women with diabetes, receiving care at a major medical institution. Mean age and gravidity were 30.7 years and 3.15 ± 1.67 respectively. 45 % expressed interest in a “buddy.” There was no significant difference between groups desiring and not desiring this program. A majority of respondents desired telephone, text messaging, and in-person contacts (79.2, 72.1, 83.8 %), with 72.5 % of patients desiring diabetes-related activities during clinic waiting time. Many women desire a postpartum diabetes reciprocal peer program for support outside of clinician visits. Patients are receptive to educational services during their wait and outside of clinic time, a potentially valuable opportunity to share important health information.