Techno-Economic Feasibility Study of Investigation of Renewable Energy System for Rural Electrification in South Algeria

This work aims to consider the combination of different technologies regarding energy production and management with four possible configurations. We present an energy management algorithm to detect the best design and the best configuration from the combination of different sources. This combination allows us to produce the necessary electrical energy for supplying habitation without interruption. A comparative study is conducted among the different combinations on the basis of the cost of energy, diesel consumption, diesel price, capital cost, replacement cost, operation, and maintenance cost and greenhouse gas emission. Sensitivity analysis is also performed

Systemic effects of epidural methylprednisolone injection on glucose tolerance in diabetic patients

ABSTRACT: BACKGROUND: Several studies have shown that in diabetic patients, the glycemic profile was disturbed after intra-articular injection of corticosteroids. Little is known about the impact of epidural injection in such patients. The goal of this study was double, at first comparing the glycaemic profile in diabetic patients after a unique injection of 80 mg of acetate methylprednisolone either intra-articular or epidural and secondly to compare the amount of systemic diffusion of the drug after both procedures. METHODS: Seventeen patients were included. Glycemic changes were compared in 9 diabetic patients following intra-articular (4 patients) and epidural injections (5 patients). Epidural injections were performed using the sacral route under fluoroscopic control in patients with lumbar spinal stenosis. Diabetes control had to stable for more than 10 days and the renal function to be preserved. Blood glucose was monitored using a validated continuous measuring device (GMS, Medtronic) the day before and for two days following the injection. Results were expressed in the form of daily glycemic profiles and as by mean, peak and minimal values +/ SD. The urinary excretion of methylprednisolone after the 2 routes of injection was analyzed in 8 patients (4 in each group). Urine samples were cropped one hour before the injections, then 4 times during the first day and 3 times a week for 2 weeks. The measurements included the free and conjugated fraction RESULTS: The glycaemic profile remains unchanged with no significant changes in the group of the 5 diabetic patients receiving epidural injections. On the other end, the average peak and mean values were enhanced up to 3 mmol/l above baseline two days after the infiltration in the groups of the 4 diabetic patients infiltrated intra-articular. The mean urinary excretion of the steroid was about ten times higher in the intra-articular versus epidural group: 7000 ng/ml versus 700 ng/ml. Looking at each individual there were marked differences especially after intra-articular injections. CONCLUSION: This is the first study to show that a single epidural steroid injection of 80 mg depot methylprednisolone had no effect on the glycemic control in diabetic patients. The absence of glycemic control changes correlated well with the very low urinary excretion of the drug after epidural injection. Trial registration NCT01420497

Brain activity underlying negative self- and other-perception in adolescents: The role of attachment-derived self-representations

One of teenagers' key developmental tasks is to engage in new and meaningful relationships with peers and adults outside the family context. Attachment-derived expectations about the self and others in terms of internal attachment working models have the potential to shape such social reorientation processes critically and thereby influence adolescents' social-emotional development and social integration. Because the neural underpinnings of this developmental task remain largely unknown, we sought to investigate them by functional magnetic resonance imaging. We asked n = 44 adolescents (ages 12.01-18.84 years) to evaluate positive and negative adjectives regarding either themselves or a close other during an adapted version of the well-established self-other trait-evaluation task. As measures of attachment, we obtained scores reflecting participants' positive versus negative attachment-derived self- and other-models by means of the Relationship Questionnaire. We controlled for possible confounding factors by also obtaining scores reflecting internalizing/externalizing problems, schizotypy, and borderline symptomatology. Our results revealed that participants with a more negative attachment-derived self-model showed increased brain activity during positive and negative adjective evaluation regarding the self, but decreased brain activity during negative adjective evaluation regarding a close other, in bilateral amygdala/parahippocampus, bilateral anterior temporal pole/anterior superior temporal gyrus, and left dorsolateral prefrontal cortex. These findings suggest that a low positivity of the self-concept characteristic for the attachment anxiety dimension may influence neural information processing, but in opposite directions when it comes to self- versus (close) other-representations. We discuss our results in the framework of attachment theory and regarding their implications especially for adolescent social-emotional development and social integration

Comparison of machine learning and semi-quantification algorithms for (I123)FP-CIT classification: the beginning of the end for semi-quantification?

Background Semi-quantification methods are well established in the clinic for assisted reporting of (I123) Ioflupane images. Arguably, these are limited diagnostic tools. Recent research has demonstrated the potential for improved classification performance offered by machine learning algorithms. A direct comparison between methods is required to establish whether a move towards widespread clinical adoption of machine learning algorithms is justified. This study compared three machine learning algorithms with that of a range of semi-quantification methods, using the Parkinson’s Progression Markers Initiative (PPMI) research database and a locally derived clinical database for validation. Machine learning algorithms were based on support vector machine classifiers with three different sets of features: Voxel intensities Principal components of image voxel intensities Striatal binding radios from the putamen and caudate. Semi-quantification methods were based on striatal binding ratios (SBRs) from both putamina, with and without consideration of the caudates. Normal limits for the SBRs were defined through four different methods: Minimum of age-matched controls Mean minus 1/1.5/2 standard deviations from age-matched controls Linear regression of normal patient data against age (minus 1/1.5/2 standard errors) Selection of the optimum operating point on the receiver operator characteristic curve from normal and abnormal training data Each machine learning and semi-quantification technique was evaluated with stratified, nested 10-fold cross-validation, repeated 10 times. Results The mean accuracy of the semi-quantitative methods for classification of local data into Parkinsonian and non-Parkinsonian groups varied from 0.78 to 0.87, contrasting with 0.89 to 0.95 for classifying PPMI data into healthy controls and Parkinson’s disease groups. The machine learning algorithms gave mean accuracies between 0.88 to 0.92 and 0.95 to 0.97 for local and PPMI data respectively. Conclusions Classification performance was lower for the local database than the research database for both semi-quantitative and machine learning algorithms. However, for both databases, the machine learning methods generated equal or higher mean accuracies (with lower variance) than any of the semi-quantification approaches. The gain in performance from using machine learning algorithms as compared to semi-quantification was relatively small and may be insufficient, when considered in isolation, to offer significant advantages in the clinical context

Profiling of steroid metabolites after transdermal and oral administration of testosterone by ultra-high pressure liquid chromatography coupled to quadrupole time-of-flight mass spectrometry.

The screening of testosterone (T) misuse for doping control is based on the urinary steroid profile, including T, its precursors and metabolites. Modifications of individual levels and ratio between those metabolites are indicators of T misuse. In the context of screening analysis, the most discriminant criterion known to date is based on the T glucuronide (TG) to epitestosterone glucuronide (EG) ratio (TG/EG). Following the World Anti-Doping Agency (WADA) recommendations, there is suspicion of T misuse when the ratio reaches 4 or beyond. While this marker remains very sensitive and specific, it suffers from large inter-individual variability, with important influence of enzyme polymorphisms. Moreover, use of low dose or topical administration forms makes the screening of endogenous steroids difficult while the detection window no longer suits the doping habit. As reference limits are estimated on the basis of population studies, which encompass inter-individual and inter-ethnic variability, new strategies including individual threshold monitoring and alternative biomarkers were proposed to detect T misuse. The purpose of this study was to evaluate the potential of ultra-high pressure liquid chromatography (UHPLC) coupled with a new generation high resolution quadrupole time-of-flight mass spectrometer (QTOF-MS) to investigate the steroid metabolism after transdermal and oral T administration. An approach was developed to quantify 12 targeted urinary steroids as direct glucuro- and sulfo-conjugated metabolites, allowing the conservation of the phase II metabolism information, reflecting genetic and environmental influences. The UHPLC-QTOF-MS(E) platform was applied to clinical study samples from 19 healthy male volunteers, having different genotypes for the UGT2B17 enzyme responsible for the glucuroconjugation of T. Based on reference population ranges, none of the traditional markers of T misuse could detect doping after topical administration of T, while the detection window was short after oral TU ingestion. The detection ability of the 12 targeted steroids was thus evaluated by using individual thresholds following both transdermal and oral administration. Other relevant biomarkers and minor metabolites were studied for complementary information to the steroid profile, including sulfoconjugated analytes and hydroxy forms of glucuroconjugated metabolites. While sulfoconjugated steroids may provide helpful screening information for individuals with homozygotous UGT2B17 deletion, hydroxy-glucuroconjugated analytes could enhance the detection window of oral T undecanoate (TU) doping

Fast screening and confirmation of doping agents by UHPLC-QTOF-MS/MS

Introduction: The general strategy to perform anti-doping analysis starts with a screening followed by a confirmatory step when a sample is suspected to be positive. The screening step should be fast, generic and able to highlight any sample that may contain a prohibited substance by avoiding false negative and reducing false positive results. The confirmatory step is a dedicated procedure comprising a selective sample preparation and detection mode. Aim: The purpose of the study is to develop rapid screening and selective confirmatory strategies to detect and identify 103 doping agents in urine. Methods: For the screening, urine samples were simply diluted by a factor 2 with ultra-pure water and directly injected ("dilute and shoot") in the ultrahigh- pressure liquid chromatography (UHPLC). The UHPLC separation was performed in two gradients (ESI positive and negative) from 5/95 to 95/5% of MeCN/Water containing 0.1% formic acid. The gradient analysis time is 9 min including 3 min reequilibration. Analytes detection was performed in full scan mode on a quadrupole time-of-flight (QTOF) mass spectrometer by acquiring the exact mass of the protonated (ESI positive) or deprotonated (ESI negative) molecular ion. For the confirmatory analysis, urine samples were extracted on SPE 96-well plate with mixed-mode cation (MCX) for basic and neutral compounds or anion exchange (MAX) sorbents for acidic molecules. The analytes were eluted in 3 min (including 1.5 min reequilibration) with a S1-25 Ann Toxicol Anal. 2009; 21(S1) Abstracts gradient from 5/95 to 95/5% of MeCN/Water containing 0.1% formic acid. Analytes confirmation was performed in MS and MS/MS mode on a QTOF mass spectrometer. Results: In the screening and confirmatory analysis, basic and neutral analytes were analysed in the positive ESI mode, whereas acidic compounds were analysed in the negative mode. The analyte identification was based on retention time (tR) and exact mass measurement. "Dilute and shoot" was used as a generic sample treatment in the screening procedure, but matrix effect (e.g., ion suppression) cannot be avoided. However, the sensitivity was sufficient for all analytes to reach the minimal required performance limit (MRPL) required by the World Anti Doping Agency (WADA). To avoid time-consuming confirmatory analysis of false positive samples, a pre-confirmatory step was added. It consists of the sample re-injection, the acquisition of MS/MS spectra and the comparison to reference material. For the confirmatory analysis, urine samples were extracted by SPE allowing a pre-concentration of the analyte. A fast chromatographic separation was developed as a single analyte has to be confirmed. A dedicated QTOF-MS and MS/MS acquisition was performed to acquire within the same run a parallel scanning of two functions. Low collision energy was applied in the first channel to obtain the protonated molecular ion (QTOF-MS), while dedicated collision energy was set in the second channel to obtain fragmented ions (QTOF-MS/MS). Enough identification points were obtained to compare the spectra with reference material and negative urine sample. Finally, the entire process was validated and matrix effects quantified. Conclusion: Thanks to the coupling of UHPLC with the QTOF mass spectrometer, high tR repeatability, sensitivity, mass accuracy and mass resolution over a broad mass range were obtained. The method was sensitive, robust and reliable enough to detect and identify doping agents in urine. Keywords: screening, confirmatory analysis, UHPLC, QTOF, doping agent