Anti-D in a D-positive renal transplant patient

PURPOSE: We report a case of postoperative reparalysis in the recovery room, following nebulized epinephrine. The patient was pharmacologically reversed with edrophonium after paralysis with rocuronium. CLINICAL FINDINGS: A 12-yr-old girl developed postoperative reparalysis following the intraoperative administration of rocuronium. A total of 0.92 mg.kg-1 rocuronium was administered. After surgery, pharmacological reversal was achieved with 20 mg edrophonium with 0.15 mg atropine sulfate iv 35 min after the last administration of rocuronium. Muscular relaxation was monitored using an ulnar peripheral nerve stimulator (PNS). After reversal, a full train-of-four and sustained tetanus at 50 Hz were present. In the recovery room, following nebulized epinephrine, the patient became apneic. The patient was paralyzed and an ulnar PNS demonstrated only one faint twitch. The paralysis was reversed with 1.5 mg neostigmine with 0.3 mg glycopyrrolate. CONCLUSION: Postoperative reparalysis following rocuronium may be a cause of postoperative respiratory distress. The definitive diagnosis is made using PNS and observing the response to pharmacological reversal. Nebulized epinephrine may have a previously undescribed role in the development of postoperative reparalysis.     

Composing RESTful Services and Collaborative Workflows: A Lightweight Approach

The use of RESTful Web services has gained momentum in the development of distributed applications based on traditional Web standards such as HTTP. In particular, these services can integrate easily into various applications, such as mashups. Composing RESTful services into Web-scale workflows requires a lightweight composition language that's capable of describing both the control and data flow that constitute a workflow. The authors address these issues with Bite, a lightweight and extensible composition language that enables the creation of Web-scale workflows and uses RESTful services as its main composable entities.     

The pharmacokinetics and pharmacodynamics of the oral iron chelator deferiprone (L1) in relation to hemoglobin levels

Recently, we demonstrated that administration of the orally active iron chelating agent deferiprone (1,2-dimethyl-3-hydroxypyrid-4-one (L1)) at 6-hour intervals results in significantly greater urinary iron excretion than that induced during administration of the drug at 12-hour intervals. That study was conducted in thalassemia patients, all of whom had received a packed red cell transfusion of 15 cc/kg. 72 hours prior to evaluation of urinary iron excretion, at a time when endogenous erythropoiesis would be expected to be at its lowest. In clinical practice however, thalassemia patients, suppression of endogenous erythropoiesis is not sustained between transfusions. We set out to determine the influence that administration of deferiprone has on urinary iron excretion at lower hemoglobin concentrations, immediately prior to transfusion. We hypothesized that hemoglobin levels will affect the ability of deferiprone to chelate iron. Ten regularly transfused patients with homozygous beta-thalassemia (HBT) aged mean +/- SD, 20.9 +/- 4.7, range 13 - 27 years, receiving long-term therapy with deferiprone, were treated with deferiprone 75 mg/kg/day, administered every 6 hours (or every 12 hours) for 72 hours immediately prior to a blood transfusion in the first month. One month later each patient received the other of the 2 dosing regimens for 72 hours immediately prior to transfusion. The deferiprone-induced 24-hour urinary iron excretion was similar during both dosing regimens; 0.56 +/- 0.45 mg/kg when L1 was given every 6 hours and 0.48 +/- 0.52 mg/kg when L1 was administered every 12 hours (p = 0.79). However, the calculated 24-hour area under the plasma concentration-time curve (AUC0-24) of deferiprone was significantly lower when deferiprone was administered at 6-hour intervals (6,762.8 +/- 1,601.6 mg*min/l), than that observed when deferiprone was administered every 12 hours (8,250.1 +/- 1,235.7 mg*min/l) (p = 0.04). The pharmacokinetics of deferiprone when administered immediately prior to transfusions are different from those following transfusions. More studies assessing total body iron excretion are needed to determine the contribution of the fecal route in iron excretion.     

The effect of growth hormone replacement on cortisol metabolism and glucocorticoid sensitivity in hypopituitary adults

OBJECTIVE: Growth hormone (GH) replacement therapy in hypopituitary adults is associated with sodium and water retention. The underlying mechanisms are incompletely understood and a possible contribution of altered cortisol metabolism or action has not been evaluated. We have investigated the effect of GH replacement therapy on cortisol metabolism, cortisol binding globulin and in-vitro glucocorticoid sensitivity in a group of adult hypopituitary patients. DESIGN AND PATIENTS: We studied 19 adult hypopituitary patients (18 adult onset, M:F, 6:13), who were receiving conventional hydrocortisone (16 patients), thyroxine (14 patients), triiodothyronine (1 patient), sex steroid (9 patients), human chorionic gonadotrophin (1 patient) or desmopressin (6 patients) replacement during a 6-month, double blind controlled trial of GH therapy (active:placebo, 8:11) followed by a 6-month open phase of GH (mean dose: 0.2 IU/kg/week, range 0.051-0.27) and after a 6-week washout phase following discontinuation of GH therapy. MEASUREMENTS: Twenty-four-hour urine free cortisol, cortisol metabolites (CoM), ratio 11-hydroxy/11-oxo CoM (F/E) and ratio 5 alpha/beta tetrahydrocortisol were measured at 6 months, 12 months and after the 6 week washout phase. Serum cortisol binding globulin was measured basally, at 6 months, 12 months and after washout. Glucocorticoid sensitivity was determined in lymphocyte preparations from 8 patients, during GH therapy and after washout, using an in-vitro technique dependent on dexamethasone suppression of phytohaemagglutinin-stimulated thymidine incorporation into DNA. Plasma renin activity and aldosterone were measured after 6-12 months GH therapy and after washout. RESULTS: After 6 months of GH, in patients on hydrocortisone (n = 9), there were significant decreases in CoM (mean decrement 21%, P < 0.01), F/E (mean decreased from 1.27 to 1.0, P = 0.04; reference range 0.33-1.29) and 5 alpha/5 beta tetrahydrocortisol (mean decreased from 0.67 to 0.48, P = 0.01) and a subsequent increase after washout. Patients not on hydrocortisone (n = 2) demonstrated a normal basal F/E falling by 25% on GH therapy but no change in CoM. During 12 months of GH therapy, patients on hydrocortisone (n = 7) demonstrated a further trend to decrement in CoM (P = 0.09) which reversed after washout (P = 0.04). Urine free cortisol tended to fall during GH therapy and increased significantly following washout after 12 months treatment (P < 0.02). Serum cortisol binding globulin decreased by 20% (P < 0.05) during 12 months GH treatment but remained within the reference range. In-vitro studies demonstrated a trend to reduced glucocorticoid sensitivity on GH therapy; the maximum inhibition of phytohaemagglutinin by dexamethasone tended to be less on GH therapy (P = 0.052) and was also lower than in 29 normal volunteers (P < 0.05). There were no significant changes in plasma renin but there was a small increment in aldosterone in recumbent patients (P = 0.04) during the open phase of GH therapy in the placebo arm. CONCLUSIONS: GH therapy in hypopituitary adults is associated with an apparent reduction in availability of administered hydrocortisone as measured by urine cortisol metabolites and urine free cortisol. This effect is unlikely to be clinically significant except possibly in ACTH deficient subjects on suboptimal hydrocortisone replacement. The changes in F/E suggest that GH may directly or indirectly modulate the activity of 11 beta-hydroxysteroid dehydrogenase. The apparent decrease in glucocorticoid sensitivity during GH therapy, demonstrated in vitro, merits further investigation.     

Visual tracking using convolutional features with sparse coding

Artificial Intelligence Review - Visual object tracking has become one of the most active research topics in computer vision, and it&nbsp;has been applied in several&nbsp;commercial...     

Optimal Artificial Intelligence Based Automated Skin Lesion Detection and Classification Model

Skin lesions have become a critical illness worldwide, and the earlier identification of skin lesions using dermoscopic images can raise the survival rate. Classification of the skin lesion from those dermoscopic images will be a tedious task. The accuracy of the classification of skin lesions is improved by the use of deep learning models. Recently, convolutional neural networks (CNN) have been established in this domain, and their techniques are extremely established for feature extraction, leading to enhanced classification. With this motivation, this study focuses on the design of artificial intelligence (AI) based solutions, particularly deep learning (DL) algorithms, to distinguish malignant skin lesions from benign lesions in dermoscopic images. This study presents an automated skin lesion detection and classification technique utilizing optimized stacked sparse autoencoder (OSSAE) based feature extractor with backpropagation neural network (BPNN), named the OSSAE-BPNN technique. The proposed technique contains a multi-level thresholding based segmentation technique for detecting the affected lesion region. In addition, the OSSAE based feature extractor and BPNN based classifier are employed for skin lesion diagnosis. Moreover, the parameter tuning of the SSAE model is carried out by the use of sea gull optimization (SGO) algorithm. To showcase the enhanced outcomes of the OSSAE-BPNN model, a comprehensive experimental analysis is performed on the benchmark dataset. The experimental findings demonstrated that the OSSAE-BPNN approach outperformed other current strategies in terms of several assessment metrics.     

Detection of Abnormal Activities from Various Signals Based on Statistical Analysis

We perceive big data with massive datasets of complex and variegated structures in the modern era. Such attributes formulate hindrances while analyzing and storing the data to generate apt aftermaths. Privacy and security are the colossal perturb in the domain space of extensive data analysis. In this paper, our foremost priority is the computing technologies that focus on big data, IoT (Internet of Things), Cloud Computing, Blockchain, and fog computing. Among these, Cloud Computing follows the role of providing on-demand services to their customers by optimizing the cost factor. AWS, Azure, Google Cloud are the major cloud providers today. Fog computing offers new insights into the extension of cloud computing systems by procuring services to the edges of the network. In collaboration with multiple technologies, the Internet of Things takes this into effect, which solves the labyrinth of dealing with advanced services considering its significance in varied application domains. The Blockchain is a dataset that entertains many applications ranging from the fields of crypto-currency to smart contracts. The prospect of this research paper is to present the critical analysis and review it under the umbrella of existing extensive data systems. In this paper, we attend to critics' reviews and address the existing threats to the security of extensive data systems. Moreover, we scrutinize the security attacks on computing systems based upon Cloud, Blockchain, IoT, and fog. This paper lucidly illustrates the different threat behaviour and their impacts on complementary computational technologies. The authors have mooted a precise analysis of cloud-based technologies and discussed their defense mechanism and the security issues of mobile healthcare.