Increased serum IL-6 level time-dependently regulates hyperalgesia and spinal mu opioid receptor expression during CFA-induced arthritis

Interleukin (IL)-6 is known to cause pro- and anti-inflammatory effects during different stages of inflammation. Recent therapeutic investigations have focused on treatment of various inflammatory disorders with anti-cytokine substances. As a result, the aim of this study was to further elucidate the influence of IL-6 in hyperalgesia and edema during different stages of Complete Freund’s Adjuvant (CFA)-induced arthritis (AA) in male Wistar rats. AA was induced by a single subcutaneous injection of CFA into the rats’ hindpaw. Anti-IL-6 was administered either daily or weekly during the 21 days of study. Spinal mu opioid receptor (mOR) expression was detected by Western blotting. Daily and weekly treatment with an anti-IL-6 antibody significantly decreased paw edema in the AA group compared to the AA control group. Additionally, daily and weekly anti-IL-6 administration significantly reduced hyperalgesia on day 7 in the AA group compared to the AA control group; however, there were significant increases in hyperalgesia in the antibody-treated group on days 14 and 21 compared to the AA control group. IL-6 antibody-induced increases in hyperalgesia on the 14th and 21st days after CFA injection correlated with a time-dependent, significant reduction in spinal mOR expression during anti-IL-6 treatment. Our study confirmed the important time-dependent relationship between serum IL-6 levels and hyperalgesia during AA. These results suggest that the stages of inflammation in AA must be considered for anti-hyperalgesic and anti-inflammatory interventions via anti-IL-6 antibody treatment

The comparison between two methods of basic life support instruction: Video self-instruction versus traditional method

Introduction: Medical education is changing and evolving. Teachers need to re-evaluate their medical teaching practice to enhance student learning. The data about the ideal training method of Basic Life Support (BLS) is lacking. The goal of this study was to analyse the use and performance of video self-instruction (VSI) method in BLS, in order to develop an efficient BLS training method. Methods: Eighty-one undergraduate medical interns were enrolled in a prospective clinical study in 2011. They were divided into VSI group and traditional group. We provided the first group with a DVD containing a 20-minute training video while the second group took part in a 4-hour training class of BLS. Subjects participated in a pre-test and post-test based on 2010 American Heart Association Resuscitation guideline. Results: The average scores of VSI group and the traditional group before training were 8.85±2.42 and 8.57±2.22 respectively (p=0.592). After training, the average scores of the VSI and the traditional group were 20.24±0.83 and 18.05±1.86 respectively. VSI group achieved slightly better scores compared with the traditional group (p<0.001). Conclusions: Training through VSI achieves more satisfying results than the traditional lecture method. VSI method can be considered a useful technique in undergraduate educational programs. Developing VSI can increase significantly the access to the BLS training. © 2015, Medcom Limited. All rights reserved

Data mining of remotely sensed datasets for ore grade estimation

Estimation of ore grade is a time and cost consuming process that requires laboratory based and exploratory information. Recognition of ore grade distribution in each alteration zone will help to decrease the risk of exploration and plan for further mining activities (Brown et al., 2000; Harris and Grunsky, 2015). Previous remotely sensed alteration mapping methods were merely focused on the spatial distribution of alteration zones (Ranjbar et al., 2011; Honarmand, 2016). However, further information like ore grade distribution and whether the explored area is an economic deposit or not remain as a question. To find out the relationships between ore grade with alteration minerals, quantitative models as a combination of geological knowledge with the mathematical analysis is suggested. The aim of this study is to develop an algorithm as a set of predictive models. The model could be used not for only broad regional exploration of ore deposits but also the estimation of ore grades in the different alteration zones by using remotely sensed datasets. The proposed remotely sensed datasets which will be used in this study include ASTER and Sentinel 2 satellite images, airborne magnetics and radiometrics. The geological setting of the studied Neotethyan Cu-porphyry deposit is the collision of the Arabian and Neotethyan plates, leading to the subduction of the Neotethyan oceanic plate under the central Iranian micro continental plate during the Paleocene to Oligocene (Maghsoudi Moud and Fathianpour, 2016). As a consequence, intensive calk-alkaline magmatic activities occurred and led to the formation of Urumieh-Dokhtar Magmatic Belt (UDMB). This belt is the host of several copper deposits (e.g. Sar Cheshmeh, Darreh Zar, Meiduk) in Iran and known as one of the main Cu-bearing belts in the world. 100-200 samples from the surface (weathered) and depth (drill hole) will be collected from the Dalli deposit within the central part of the UDMB to derive the predictive models. Approximately 30 samples from different alteration zones will be collected from the Kouh Panj area within the southeastern part of the UDMB to test the performance of the models. The study is divided into the following steps. First of all, different laboratory measurements like hyperspectral imaging, point spectroscopy, X-ray powder diffraction (XRD), X-ray fluorescence (XRF), and magnetometry will be applied to the samples of Dalli area. The laboratory measurements demonstrate truth information including ore grade, mineral composition, and mineral assemblages. Then, the relationships between the truth information and remotely sensed dataset will be quantified as a set of equations which make the predictive models. Afterwards, the models will be applied on the datasets to build a remotely sensed estimation of ore grade. The quantified estimates will be integrated together to create an unique map. This map illustrates the common ore grades in each alteration zone between the all datasets. The outcome will be compared to exploratory reports and approved ore reserve to evaluate the uncertainty and accuracy of the models. In the next stage, to assess the operation of the models, it will be applied to remotely sensed datasets of the Kouh Panj area to create an output ore grade map within the different alteration zones. Finally, the outcome will be compared to the analysis results of collected rocks from the Kouh Panj area to determine the uncertainty and accuracy of the model for the prediction of ore grade and alteration mapping. Since Cu porphyry systems of both Dalli and Kouh Panj areas are the same, it is expected that the created model in Dalli area is operative in Kouh Panj area with a derived estimation of uncertainty

What’s in Toronto’s drug supply? Results from samples checked by Toronto’s drug checking service October 10, 2019 - March 31, 2020.

On 22 August 2018 amendments to the Northern Territory Liquor Act 1978 (the Act) were passed in the NT Legislative Assembly, introducing a minimum alcohol unit price MUP, commonly referred to as a minimum floor price. On 1 October 2018 the MUP was set at $1.30 per standard drink contained in the alcohol product, where the meaning of 'a standard drink is the volume of a liquor product that contains 10g of ethyl alcohol when measured at 20°C'. The legislative amendment prohibits selling alcohol below the price of$1.30 per standard drink (as compared to the $1.50 recommended by the Riley Review), and imposes the minimum price as an automatic condition of a liquor licence

Evaluation of Non- linear Growth Curves Models for Native Slow-growing Khazak Chickens

Native poultry is a valuable genetic source with high resistance against diseases providing an important subject for breeding programs. The non-linear mathematical modeling of the growth pattern may partly explain the relationship between requirements and body weight to precise feeding that plays a vital role in the animal enterprises. A study was conducted to compare five non-linear models including Gompertz, Richards, Lopez, Logistic, and Von Bertalanffy describing the growth curve of Khazak native chickens. A total of 120 Khazak chickens (male and female) were individually weighed from 0 to 29 weeks under the same condition. The models were fitted on body weight data set and then evaluated by goodness-of-fit criteriaincluding root mean square error (RMSE), Bayesian information criterion (BIC), Akaike information criterion (AIC), and adjusted coefficient of determination (R2Adj). Based on goodness-of-fit criteria, Lopez model was the most suitable one for describing the growth curves in female and male chickens. The effect of sex was significantly important on curve parameters in all models (P< 0.05). The highest and lowest initial weight (W0) parameter was estimated by Logistic and Richards models, respectively, however, the other parameters of the growth curves were higher in Lopez model compared to others. Male chickens had higher values for age (ti), and weight (wi) at inflection point than females. Using an appropriate model to describe the growth curve in native Khazak chickens could increase the accuracy of selection for rapid growth at early stages of age

Clear-cell carcinoma originating from cesarean section scar: two case reports

Background: Clear-cell carcinoma arising from the surgical cesarean section scar is very infrequent. The present study reports two patients with clear-cell carcinoma arising from an abdominal wall scar 20 and 23 years after their last cesarean section. Case presentation: Both Iranian patients had prior cesarean sections nearly 20 years earlier. Patients 1 and 2 had transverse and vertical abdominal incisions, respectively. The initial clinical presentation was a huge lower abdominal mass at the site of the previous cesarean section scar. Both patients underwent abdominal wall mass biopsy. The histological analysis revealed the presence of malignancy. Both patients underwent full-thickness resection of the abdominal wall mass. All surgical margins were tumor-free; however, patient 1 had a very narrow tumor-free margin near the pubic symphysis. As the imaging report of patient 2 revealed the presence of a pelvic mass, the exploration of the intraperitoneal space, simple total abdominal hysterectomy (TAH), bilateral salpingo-oophorectomy (BSO), and the excision of enlarged pelvic lymph nodes were performed during the surgery. Six cycles of paclitaxel and carboplatin every 3 weeks as adjuvant chemotherapy was administered for both patients after the surgery. One of the patients had disease recurrence 5 months after the termination of chemotherapy, and the other is still disease-free. These two patients had similar pathology and received a similar initial adjuvant treatment; however, they were different in terms of the direction of tumor spread, tumor distance from the pubic symphysis, status of tumor margins, and surgical procedures. Conclusions: We encountered distinct prognoses in the clear-cell carcinoma of cesarean section scars presented herein. The researchers can recommend complete surgical excision of the abdominal wall mass with wide tumor-free margins, exploration of the abdominopelvic space, TAH, and BSO during the first surgery. © 2021, The Author(s)

Characterizing and correcting phase biases in short-term, multilooked interferograms

Interferometric Synthetic Aperture Radar (InSAR) is widely used to measure deformation of the Earth's surface over large areas and long time periods. A common strategy to overcome coherence loss in long-term interferograms is to use multiple multilooked shorter interferograms, which can cover the same time period but maintain coherence. However, it has recently been shown that using this strategy can introduce a bias (also referred to as a “fading signal”) in the interferometric phase. We isolate the signature of the phase bias by constructing “daisy chain” sums of short-term interferograms of different length covering identical 1-year time intervals. This shows that the shorter interferograms are more affected by this phenomenon and the degree of the effect depends on ground cover types; cropland and forested pixels have significantly larger bias than urban pixels and the bias for cropland mimics subsidence throughout the year, whereas forests mimics subsidence in the spring and heave in the autumn. We, propose a method for correcting the phase bias, based on the assumption, borne out by our observations, that the bias in an interferogram is linearly related to the sum of the bias in shorter interferograms spanning the same time. We tested the algorithm over a study area in western Turkey by comparing average velocities against results from a phase linking approach, which estimates the single primary phases from all the interferometric pairs, and has been shown to be almost insensitive to the phase bias. Our corrected velocities agree well with those from a phase linking approach. Our approach can be applied to global compilations of short-term interferograms and provides accurate long-term velocity estimation without a requirement for coherence in long-term interferograms

Strategies for improving the communication of satellite-derived InSAR data for geohazards through the analysis of Twitter and online data portals

Satellite-based earth observation sensors are increasingly able to monitor geophysical signals related to natural hazards, and many groups are working on rapid data acquisition, processing, and dissemination to data users with a wide range of expertise and goals. A particular challenge in the meaningful dissemination of Interferometric Synthetic Aperture Radar (InSAR) data to non-expert users is its unique differential data structure and sometimes low signal-to-noise ratio. In this study, we evaluate the online dissemination of ground deformation measurements from InSAR through Twitter, alongside the provision of open-access InSAR data from the Centre for Observation and Modelling of Earthquakes, Volcanoes and Tectonics (COMET) Looking Into Continents from Space with Synthetic Aperture Radar (LiCSAR) processing system. Our aim is to evaluate (1) who interacts with disseminated InSAR data, (2) how the data are used, and (3) to discuss strategies for meaningful communication and dissemination of open InSAR data. We found that the InSAR Twitter community was primarily composed of non-scientists (62 %), although this grouping included earth observation experts in applications such as commercial industries. Twitter activity was primarily associated with natural hazard response, specifically following earthquakes and volcanic activity, where users disseminated InSAR measurements of ground deformation, often using wrapped and unwrapped interferograms. For earthquake events, Sentinel-1 data were acquired, processed, and tweeted within 4.7±2.8 d (the shortest was 1 d). Open-access Sentinel-1 data dominated the InSAR tweets and were applied to volcanic and earthquake events in the most engaged-with (retweeted) content. Open-access InSAR data provided by LiCSAR were widely accessed, including automatically processed and tweeted interferograms and interactive event pages revealing ground deformation following earthquake events. The further work required to integrate dissemination of InSAR data into longer-term disaster risk-reduction strategies is highly specific, to both hazard type and international community of practice, as well as to local political setting and civil protection mandates. Notably, communication of uncertainties and processing methodologies are still lacking. We conclude by outlining the future direction of COMET LiCSAR products to maximize their useability.</p

Milk and dairy products: good or bad for human health? An assessment of the totality of scientific evidence

Background: There is scepticism about health effects of dairy products in the public, which is reflected in an increasing intake of plant-based drinks, for example, from soy, rice, almond, or oat. Objective: This review aimed to assess the scientific evidence mainly from meta-analyses of observational studies and randomised controlled trials, on dairy intake and risk of obesity, type 2 diabetes, cardiovascular disease, osteoporosis, cancer, and all-cause mortality. Results: The most recent evidence suggested that intake of milk and dairy products was associated with reduced risk of childhood obesity. In adults, intake of dairy products was shown to improve body composition and facilitate weight loss during energy restriction. In addition, intake of milk and dairy products was associated with a neutral or reduced risk of type 2 diabetes and a reduced risk of cardiovascular disease, particularly stroke. Furthermore, the evidence suggested a beneficial effect of milk and dairy intake on bone mineral density but no association with risk of bone fracture. Among cancers, milk and dairy intake was inversely associated with colorectal cancer, bladder cancer, gastric cancer, and breast cancer, and not associated with risk of pancreatic cancer, ovarian cancer, or lung cancer,while the evidence for prostate cancer risk was inconsistent.Finally,consumption of milk and dairy products was not associated with all-cause mortality. Calcium-fortified plant-based drinks have been included as an alternative to dairy products in the nutrition recommendations in several countries. However, nutritionally, cow’s milk and plant-based drinks are completely different foods,and an evidence-based conclusion on the health value of the plant-based drinks requires more studies in humans. Conclusion: The totality of available scientific evidence supports that intake of milk and dairy products contribute to meet nutrient recommendations, and may protect against the most prevalent chronic diseases, whereas very few adverse effects have been reported