Existing and Expected Service Quality of Grameenphone Users in Bangladesh

. The Grameenphone (GP) is a market leader in the telecommunication industry in Bangladesh. This study investigates the existing and expected service quality of Grameenphone users in Bangladesh. The Study reveals that there are significant gap between existing and expected perceived service network, 3G, customer care, physical facilities, billing cost, information service, mobile banking and GP offers. The study concludes that customer satisfaction is a dynamic phenomenon. Maintaining desired level of customer satisfaction requires corporate proactive responsiveness in accessing, building & retaining satisfied customers for sustainable competitive advantages in the marketplace

Anti-diabetic potential of Plectranthus lanuginosus in streptozotocin-induced diabetic rats

Purpose: To determine the antidiabetic effect of methanol extract of Plectranthus lanuginosus leaves in streptozotocin-induced hyperglycemic (HGD) rats. Methods: P. lanuginosus leaves were collected from Saad Medhas, Al Baha, Kingdom of Saudi Arabia. After defatting with n-hexane, they were extracted in vacuo at 40 oC with 75 % methanol. Streptozotocin (50 mgkg−1, i.p.) was used to induce hyperglycemia (diabetes) in the rats. The HGD rats received either standard drug (glibenclamide, 10 mgkg−1, p.o.) or Plectranthus lanuginosus leaf methanol leaf extract (PLLM) at doses of 200 and 400 mgkg−1/day, p.o. for 21 consecutive days. Blood samples were taken from the rat tails 2 h after dosing, and at 7-day intervals (i.e., 0, 7th, 14th and 21st days). The blood samples were used for measurement of fasting blood glucose (FBS), using a glucometer. On the 21st day, the rats were sacrificed via cardiac puncture. The activities of liver marker enzymes (SGPT and SGOT), and serum lipid profile (cholesterol, triglycerides, HDL and LDL) were determined using a hemolyzer. Results: Streptozotocin treatment produced significant hyperglycemia in the rats (348.9 ± 5.6) when compared to control (79.2 ± 1.3). However, PLLM (200 and 400 mg kg−1) produced significant and dose-dependent anti-diabetic (166.4 ± 5.6 and 123.86 ± 6.8 respectively) and antihyperlipidemic effects in HGD rats, at levels similar to those produced by the standard drug, glibenclamide (120.6 ± 6.4). Conclusion: P. lanuginosus leaf extract possesses pronounced anti-diabetic and anti-hyperlipidemic properties which may be due to the presence of phenolic and flavonoid constituents in the plant. Therefore, the plant extract can be further developed for the management of diabete

Saturation transfer difference NMR on the integral trimeric membrane transport protein GltPh determines cooperative substrate binding

UID/Multi/04378/2019 Grant no. BB/P010660/1 grant number BB/M011216/1Saturation-transfer difference (STD) NMR spectroscopy is a fast and versatile method which can be applied for drug-screening purposes, allowing the determination of essential ligand binding affinities (KD). Although widely employed to study soluble proteins, its use remains negligible for membrane proteins. Here the use of STD NMR for KD determination is demonstrated for two competing substrates with very different binding affinities (low nanomolar to millimolar) for an integral membrane transport protein in both detergent-solubilised micelles and reconstituted proteoliposomes. GltPh, a homotrimeric aspartate transporter from Pyrococcus horikoshii, is an archaeal homolog of mammalian membrane transport proteins—known as excitatory amino acid transporters (EAATs). They are found within the central nervous system and are responsible for fast uptake of the neurotransmitter glutamate, essential for neuronal function. Differences in both KD’s and cooperativity are observed between detergent micelles and proteoliposomes, the physiological implications of which are discussed.publishersversionpublishe

Transition metal ion FRET uncovers K(+) regulation of a neurotransmitter/sodium symporter

Neurotransmitter/sodium symporters (NSSs) are responsible for Na(+)-dependent reuptake of neurotransmitters and represent key targets for antidepressants and psychostimulants. LeuT, a prokaryotic NSS protein, constitutes a primary structural model for these transporters. Here we show that K(+) inhibits Na(+)-dependent binding of substrate to LeuT, promotes an outward-closed/inward-facing conformation of the transporter and increases uptake. To assess K(+)-induced conformational dynamics we measured fluorescence resonance energy transfer (FRET) between fluorescein site-specifically attached to inserted cysteines and Ni(2+) bound to engineered di-histidine motifs (transition metal ion FRET). The measurements supported K(+)-induced closure of the transporter to the outside, which was counteracted by Na(+) and substrate. Promoting an outward-open conformation of LeuT by mutation abolished the K(+)-effect. The K(+)-effect depended on an intact Na1 site and mutating the Na2 site potentiated K(+) binding by facilitating transition to the inward-facing state. The data reveal an unrecognized ability of K(+) to regulate the LeuT transport cycle

The Environment Shapes the Inner Vestibule of LeuT

Human neurotransmitter transporters are found in the nervous system terminating synaptic signals by rapid removal of neurotransmitter molecules from the synaptic cleft. The homologous transporter LeuT, found in Aquifex aeolicus, was crystallized in different conformations. Here, we investigated the inward-open state of LeuT. We compared LeuT in membranes and micelles using molecular dynamics simulations and lanthanide-based resonance energy transfer (LRET). Simulations of micelle-solubilized LeuT revealed a stable and widely open inward-facing conformation. However, this conformation was unstable in a membrane environment. The helix dipole and the charged amino acid of the first transmembrane helix (TM1A) partitioned out of the hydrophobic membrane core. Free energy calculations showed that movement of TM1A by 0.30 nm was driven by a free energy difference of similar to 15 kJ/mol. Distance measurements by LRET showed TM1A movements, consistent with the simulations, confirming a substantially different inward-open conformation in lipid bilayer from that inferred from the crystal structure

Deep Learning Assisted Automated Assessment of Thalassaemia from Haemoglobin Electrophoresis Images

Haemoglobin (Hb) electrophoresis is a method of blood testing used to detect thalassaemia. However, the interpretation of the result of the electrophoresis test itself is a complex task. Expert haematologists, specifically in developing countries, are relatively few in number and are usually overburdened. To assist them with their workload, in this paper we present a novel method for the automated assessment of thalassaemia using Hb electrophoresis images. Moreover, in this study we compile a large Hb electrophoresis image dataset, consisting of 103 strips containing 524 electrophoresis images with a clear consensus on the quality of electrophoresis obtained from 824 subjects. The proposed methodology is split into two parts: (1) single-patient electrophoresis image segmentation by means of the lane extraction technique, and (2) binary classification (normal or abnormal) of the electrophoresis images using state-of-the-art deep convolutional neural networks (CNNs) and using the concept of transfer learning. Image processing techniques including filtering and morphological operations are applied for object detection and lane extraction to automatically separate the lanes and classify them using CNN models. Seven different CNN models (ResNet18, ResNet50, ResNet101, InceptionV3, DenseNet201, SqueezeNet and MobileNetV2) were investigated in this study. InceptionV3 outperformed the other CNNs in detecting thalassaemia using Hb electrophoresis images. The accuracy, precision, recall, f1-score, and specificity in the detection of thalassaemia obtained with the InceptionV3 model were 95.8%, 95.84%, 95.8%, 95.8% and 95.8%, respectively. MobileNetV2 demonstrated an accuracy, precision, recall, f1-score, and specificity of 95.72%, 95.73%, 95.72%, 95.7% and 95.72% respectively. Its performance was comparable with the best performing model, InceptionV3. Since it is a very shallow network, MobileNetV2 also provides the least latency in processing a single-patient image and it can be suitably used for mobile applications. The proposed approach, which has shown very high classification accuracy, will assist in the rapid and robust detection of thalassaemia using Hb electrophoresis images. 2022 by the authors.A part of the research was funded by the Higher Education Commission of Pakistan through its funded project of Artificial Intelligence in Healthcare, Intelligent Information Processing Lab, National Center of Artificial Intelligence.Scopu

Identification and prioritization of critical success factors in faith-based and non-faith-based organizations’ humanitarian supply chain

In the last few decades, an exponential increase in the number of disasters, and their complexity has been reported, which ultimately put much pressure on relief organizations. These organizations cannot usually respond to the disaster on their own, and therefore, all actors involved in relief efforts should have end-to-end synchronization in order to provide relief effectively and efficiently. Consequently, to smoothen the flow of relief operation, a shared understanding of critical success factors in humanitarian supply chain serves as a pre-requisite for successful relief operation. Therefore, any member of the humanitarian supply chain might disrupt this synchronization by neglecting one or several of these critical success factors. However, in this study, we try to investigate how faith-based and non-faith-based relief organizations treat these critical success factors. Moreover, we also try to identify any differences between Islamic and Christian relief organizations in identifying and prioritizing these factors. To achieve the objective of this study, we used a two-stage approach; in the first stage, we collected the critical success factors from existing humanitarian literature. Whereas, in the second stage, using an online questionnaire, we collected data on the importance of selected factors from humanitarian relief organizations from around the world in collaboration with World Association of Non-Governmental Organizations (WANGO). Later, responses were analyzed to answer the research questions using non-parametric Binomial and Wilcoxon Rank-Sum tests. Test results indicate that for RQ1, two but all factors are significant for successful relief operation. For RQ2, we found significant differences for some CSF among faith-based and non-faith-based relief organizations. Similarly for RQ3, we found significant differences for some CSF among Islamic and Christian relief organizations