Reforming Fiscal Institutions in Resource-Rich Arab Economies: Policy Proposals

This paper traces the evolution of fiscal institutions of Resource Rich Arab Economies (RRAEs) over time since their pre-oil days, through the discovery of oil to their build-up of oil exports. It then identifies challenges faced by RRAEs and variations in their severity among the different countries over time. Finally, it articulates specific policy reforms, which, if implemented successfully, could help to overcome these challenges. In some cases, however, these policy proposals may give rise to important trade-offs that will have to be evaluated carefully in individual cases

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

A proposed multi-scale approach with automatic scale selection for image change detection

In this paper a system for multi-scale change detection with automatic scale selection is proposed. The generation of the multi-scale data set is performed based on the fractal net evolution approach (FNEA). The set of scales used by FNEA are optimally selected from the scale domain ensuring that the selected levels present a good enough representation of the scale domain. A pattern search module is used to select good enough set of scales with the least redundancy. The change detection is performed on each scale individually. For each individual object in a specific scale change indicators are extracted for the pixels corresponding to this object in the base-scale images. After extracting the change indicators for each scale, the extracted indicators are thresholded to obtain a per-scale binary change map. To obtain the final change map, a scale-driven fusion of all the extracted change maps is performed. The fusion is based on detecting for each pixel the preferred scale to obtain its change information. The best scale for an object is the scale where the object area keeps static/almost static while moving from one scale to the next scale(s). The proposed system proves advantageous over other change detection systems

Caffeic acid methyl and ethyl esters exert potential antidiabetic effects on glucose and lipid metabolism in cultured murine insulin-sensitive cells through mechanisms implicating activation of AMPK

Context: Caffeic acid methyl (CAME) and ethyl (CAEE) esters stimulate glucose uptake and AMP-activated protein kinase (AMPK) in C2C12 myocytes (ATCC® CRL-1772TM). Objective: Effects of CAME and CAEE were now assessed on myocyte glucose transporter GLUT4 activity and expression, on hepatic gluconeogenesis and on adipogenesis as well as major underlying signaling pathways. Materials and methods: GLUT4 protein translocation was studied in L6 GLUT4myc cells, glucose-6-phospatase (G6Pase) in H4IIE hepatocytes and adipogenesis in 3T3-L1 adipocytes. Key modulators were measured using western immunoblot. Cells were treated for 18 h with either CAME or CAEE at various concentrations (12.5–100 μM). Results: Myocyte glucose uptake rose from 10.1 ± 0.5 to 18.7 ± 0.8 and 21.9 ± 1.0 pmol/min/mg protein in DMSO-, CAME- and CAEE-stimulated cells, respectively, similar to insulin (17.7 ± 1.2 pmol/min/mg protein), while GLUT4myc translocation increased significantly by 1.70 ± 0.18, by 1.73 ± 0.18- and by 1.95 ± 0.30-fold (relative to DMSO), following insulin, CAME and CAEE stimulation, respectively. CAME and CAEE suppressed hepatocyte G6Pase by 62.0 ± 6.9% and 62.7 ± 6.0% with IC50 of 45.93 and 22.64 μM, respectively, comparable to insulin (70.7 ± 2.3% inhibition). Finally, CAME and CAEE almost abrogated adipogenesis (83.3 ± 7.2% and 97.3 ± 3.0% at 100 μM; IC50 of 13.8 and 12.9 μM, respectively). The compounds inhibited adipogenic factors C/EBP-β and PPAR-γ and stimulated AMPK activity in the three cell-lines. Discussion and conclusions: CAME and CAEE exerted antidiabetic activities in insulin-responsive cells through insulin-independent mechanisms involving AMPK and adipogenic factors

The fatty acid-rich fraction of Eruca sativa (rocket salad) leaf extract exerts antidiabetic effects in cultured skeletal muscle, adipocytes and liver cells

Context: Eruca sativa Mill. (Brassicaceae), commonly known as rocket salad, is a popular leafy-green vegetable with many health benefits. Objective: To evaluate the antidiabetic activities of this plant in major insulin-responsive tissues. Materials and methods: Five E. sativa leaf extracts of varying polarity were prepared (aqueous extract, 70% and 95% ethanol extracts, the n-hexane-soluble fraction of the 95% ethanol extract (ES3) and the defatted 95% ethanol extract). Eruca sativa extracts were investigated through a variety of cell-based in vitro bioassays for antidiabetic activities in C2C12 skeletal muscle cells, H4IIE hepatocytes and 3T3-L1 adipocytes. Guided by the results of these bioassays, ES3 was fractionated into the saponifiable (SM) and the unspaonifiable (USM) fractions. Glucose uptake was measured using [3H]-deoxy-glucose, while the effects on hepatic glucose-6-phosphatase (G6Pase) and adipogenesis were assessed using Wako AutoKit Glucose and AdipoRed assays, respectively. Results: ES3 and its SM fraction significantly stimulated glucose uptake with EC50 values of 8.0 and 5.8 μg/mL, respectively. Both extracts significantly inhibited G6Pase activity (IC50 values of 4.8 and 9.3 μg/mL, respectively). Moreover, ES3 and SM showed significant adipogenic activities with EC50 of 4.3 and 6.1 μg/mL, respectively. Fatty acid content of SM was identified by GC-MS. trans-Vaccenic and palmitoleic acids were the major unsaturated fatty acids, while palmitic and azelaic acids were the main saturated fatty acids. Discussion and conclusion: These findings indicate that ES3 and its fatty acid-rich fraction exhibit antidiabetic activities in insulin-responsive cell lines and may hence prove useful for the treatment of type 2 diabetes

Node classification with graph neural network based centrality measures and feature selection

Graph neural networks (GNNs) are a new topic of research in data science where data structure graphs are used as important components for developing and training neural networks. GNN always learns the weight importance of the neighbour for perform message aggregation in which the feature vectors of all neighbors are aggregated without considering whether the features are useful or not. Using such more informative features positively affect the performance of the GNN model. So, in this paper i) after selecting a subset of features to define important node features, we present new graph features’ explanation methods based on graph centrality measures to capture rich information and determine the most important node in a network. Through our experiments, we find that selecting certain subsets of these features and adding other features based on centrality measure can lead to better performance across a variety of datasets and ii) We introduce a major design strategy for graph neural networks. Specifically, we suggest using batch renormalization as normalization over GNN layers. Combining these techniques, representing features based on centrality measures that passed to multilayer perceptron (MLP) layer which is then passed to adjusted GNN layer, the proposed model achieves greater accuracy than modern GNN models

Anti-apoptotic potential of several antidiabetic medicinal plants of the eastern James Bay Cree pharmacopeia in cultured kidney cells

Abstract Background Our team has identified 17 Boreal forest species from the traditional pharmacopeia of the Eastern James Bay Cree that presented promising in vitro and in vivo biological activities in the context of type 2 diabetes (T2D). We now screened the 17 plants extracts for potential anti-apoptotic activity in cultured kidney cells and investigated the underlying mechanisms. Methods MDCK (Madin-Darnby Canine Kidney) cell damage was induced by hypertonic medium (700 mOsm/L) in the presence or absence of maximal nontoxic concentrations of each of the 17 plant extracts. After 18 h’ treatment, cells were stained with Annexin V (AnnV) and Propidium iodide (PI) and subjected to flow cytometry to assess the cytoprotective (AnnV−/PI−) and anti-apoptotic (AnnV+/PI−) potential of the 17 plant extracts. We then selected a representative subset of species (most cytoprotective, moderately so or neutral) to measure the activity of caspases 3, 8 and 9. Results Gaultheria hispidula and Abies balsamea are amongst the most powerful cytoprotective and anti-apoptotic plants and appear to exert their modulatory effect primarily by inhibiting caspase 9 in the mitochondrial apoptotic signaling pathway. Conclusion We conclude that several Cree antidiabetic plants exert anti-apoptotic activity that may be relevant in the context of diabetic nephropathy (DN) that affects a significant proportion of Cree diabetics