Search

Background: The Nepalese government endorsed and implemented the Package of Essential Non-Communicable Disease Interventions (PEN) by the World Health Organization (WHO) to prevent and manage four major non-communicable diseases (NCDs): cardiovascular disease (CVD), diabetes, cancers, and chronic respiratory diseases. This study explored barriers and facilitators to patient utilization of NCD services at primary healthcare facilities in Nepal., Methodology: We conducted a qualitative study with a 35 purposive sample of patients living with one or more NCDs (hypertension, diabetes, chronic obstructive pulmonary disease (COPD/ asthma) who sought healthcare at primary healthcare facilities in 14 randomly selected districts in seven provinces in Nepal that implemented PEN. Trained qualitative researchers conducted in-depth interviews in-person in a private setting using a semi-structured interview guide developed based on the Health Belief Model in the local language. The interviews were audio-recorded, transcribed verbatim, coded inductively and deductively, and analyzed by a framework approach using Dedoose software., Results: From the perspectives of patients, key facilitators of service utilization encompassed free medicines, low-cost services, geographical and financial accessibility, less waiting time, positive interactions with health service providers, experiencing improvements in their health conditions, and support from family and peers. Barriers to utilizing services included inadequate health services (e.g., lack of medications and equipment), inaccessibility and affordability, inadequate health-related information from health service providers, low knowledge of NCD care, and lack of reminders or follow ups., Conclusion: Enhancing NCD service utilization is potentially attainable through interventions that address patients' knowledge, self-motivation, and misconceptions. Furthermore, strengthening the availability and accessibility of crucial services such as laboratory investigations, medications, equipment, and the patient-provider relationship is crucial for sustainable implementation of PEN.

Optoelectronic devices based on lanthanide-containing materials are an emergent area of research due to imminent interest in a new generation of diode materials, optical and magnetic sensors, and ratiometric thermometers. Tailoring material properties through the employment of photo- or thermochromic moieties is a powerful approach that requires a deep fundamental understanding of possible cooperativity between lanthanide-based metal centers and integrated switchable units. In this work, we probe this concept through the synthesis, structural analysis, and spectroscopic characterization of novel photochromic lanthanide-based metal-organic materials containing noncoordinatively integrated photoresponsive 4,4'-azopyridine between lanthanide-based metal centers. As a result, a photophysical material response tailored on demand through the incorporation of photochromic compounds within a rigid matrix was investigated. The comprehensive analysis of photoresponsive metal-organic materials includes single-crystal X-ray diffraction and diffuse reflectance spectroscopic studies that provide guiding principles necessary for understanding photochromic unit-lanthanide-based metal-organic framework (MOF) cooperativity. Furthermore, steady-state and time-resolved diffuse reflectance spectroscopic studies revealed a rapid rate of photoresponsive moiety attenuation upon its integration within the rigid matrix of lanthanide-based MOFs in comparison with that in solution, highlighting a unique role and synergy that occurred between stimuli-responsive moieties and the lanthanide-based MOF platform, allowing for tunability and control of material photoisomerization kinetics.

In actinide systems, the 5 f electrons experience a uniquely delicate balance of effects and interactions having similar energy scales, which are often difficult to properly disentangle. This interplay of factors such as the dual nature of 5 f -states, strong electronic correlations, and strong spin-orbit coupling results in electronically unusual and intriguing behavior such as multi-k antiferromagnetic ordering, multipolar ordering, Mott-physics, mixed valence configurations, and more. Despite the inherent allure of their exotic properties, the exploratory science of even the more basic, binary systems like the actinide oxides has been limited due to their toxicity, radioactivity, and reactivity. In this article, we provide an overview of the available synthesis techniques for selected binary actinide oxides, including the actinide dioxides, sesquioxides, and a selection of higher oxides. For these oxides, we also review and evaluate the current state of knowledge of their crystal structures and magnetic properties. In many aspects, substantial knowledge gaps exist in the current body of research on actinide oxides related to understanding their electronic ground states. Bridging these gaps is vital for improving not only a fundamental understanding of these systems but also of future nuclear technologies. To this end, we note the experimental techniques and necessary future investigations which may aid in better elucidating the nature of these fascinating systems., (Not subject to copyright in the USA. Contribution of U.S. Department of Energy.)

Biomolecular simulations have become an essential tool in contemporary drug discovery, and molecular mechanics force fields (FFs) constitute its cornerstone. Developing a high quality and broad coverage general FF is a significant undertaking that requires substantial expert knowledge and computing resources, which is beyond the scope of general practitioners. Existing FFs originate from only a limited number of groups and organizations, and they either suffer from limited numbers of training sets, lower than desired quality because of oversimplified representations, or are costly for the molecular modeling community to access. To address these issues, in this work, we developed an AMBER-consistent small molecule FF with extensive chemical space coverage, and we provide Open Access parameters for the entire modeling community. To validate our FF, we carried out benchmarks of quantum mechanics (QM)/molecular mechanics conformer comparison and free energy perturbation calculations on several benchmark data sets. Our FF achieves a higher level of performance at reproducing QM energies and geometries than two popular open-source FFs, OpenFF2 and GAFF2. In relative binding free energy calculations for 31 protein-ligand data sets, comprising 1079 pairs of ligands, the new FF achieves an overall root-mean-square error of 1.19 kcal/mol for ΔΔ G and 0.92 kcal/mol for Δ G on a subset of 463 ligands without bespoke fitting to the data sets. The results are on par with those of the leading commercial series of OPLS FFs.

Meaningful exploration of the chemical space of druglike molecules in drug design is a highly challenging task due to a combinatorial explosion of possible modifications of molecules. In this work, we address this problem with transformer models, a type of machine learning (ML) model originally developed for machine translation. By training transformer models on pairs of similar bioactive molecules from the public ChEMBL data set, we enable them to learn medicinal-chemistry-meaningful, context-dependent transformations of molecules, including those absent from the training set. By retrospective analysis on the performance of transformer models on ChEMBL subsets of ligands binding to COX2, DRD2, or HERG protein targets, we demonstrate that the models can generate structures identical or highly similar to most active ligands, despite the models having not seen any ligands active against the corresponding protein target during training. Our work demonstrates that human experts working on hit expansion in drug design can easily and quickly employ transformer models, originally developed to translate texts from one natural language to another, to "translate" from known molecules active against a given protein target to novel molecules active against the same target.

Deep learning, aided by the availability of big data sets, has led to substantial advances across many disciplines. However, many scientific problems of practical interest lack sufficiently large datasets amenable to deep learning. Prediction of antibody viscosity is one such problem where deep learning methods have not yet been explored due to the relative scarcity of relevant training data. In this work, we overcome this limitation using a biophysically meaningful representation that enables us to develop generalizable models even under limited training data. We present, PfAbNet-viscosity, a 3D convolutional neural network architecture, to predict high-concentration viscosity of therapeutic antibodies. We show that with the electrostatic potential surface of the antibody variable region as the only input to the network, the models trained on as few as couple dozen datapoints can generalize with high accuracy. Our feature attribution analysis shows that PfAbNet-viscosity has learned key biophysical drivers of viscosity. The applicability of our approach to other biological systems is discussed., (© 2023. The Author(s).)

The supply chain is a complex network in healthcare that crosses organizational and geographical borders. The inherent complexity of such structures can introduce impurities inclusive of erroneous facts, lack of transparency, and restricted records provenance. In the healthcare business, counterfeit pills are one of the major reasons for the harmful impact on human health and also for financial losses. Thus, pharmaceutical supply chains and end-to-end tracking systems are the recent research in healthcare. In this paper, we propose blockchain based traceability of counterfeited drugs (BBTCD) that implements tracking of counterfeited drugs using smart contracts on the Ethereum blockchain. We propose a solution to fully decentralize the tracking in healthcare by storing BBTCD on IPFS (Inter Planetary File System) to provide transparency, cost-effectiveness., (© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

The experimental realization of magnetic skyrmion crystals in centrosymmetric materials has been driven by theoretical understanding of how a delicate balance of anisotropy and frustration can stabilize topological spin structures in applied magnetic fields. Recently, the centrosymmetric material Gd_{2}PdSi_{3} was shown to host a field-induced skyrmion crystal, but the skyrmion stabilization mechanism remains unclear. Here, we employ neutron-scattering measurements on an isotopically enriched polycrystalline Gd_{2}PdSi_{3} sample to quantify the interactions that drive skyrmion formation. Our analysis reveals spatially extended interactions in triangular planes, and large ferromagnetic interplanar magnetic interactions that are modulated by the Pd/Si superstructure. The skyrmion crystal emerges from a zero-field helical magnetic order with magnetic moments perpendicular to the magnetic propagation vector, indicating that the magnetic dipolar interaction plays a significant role. Our experimental results establish an interaction space that can promote skyrmion formation, facilitating identification and design of centrosymmetric skyrmion materials.

The structural and compositional diversity of the RTX 3 family of materials offers various magnetic and thermodynamic properties such as complex magnetic structure, vibronic bound states, heavy-fermions, valence fluctuations, metamagnetism, spin glass behavior, quantum criticality, and unconventional superconductivity. Here we present an overview of the crystal structures, crystal growth and magnetic properties of RTX 3 compounds as well as a discussion of the relevant physics. The magnetic properties of several compounds of the RTX 3 family still remain unexplored. The compounds with a complex magnetic structure could potentially host exotic topological phases. This review article may help explore exotic magnetic properties such as the vibron state and topological spin textures., (© 2022 IOP Publishing Ltd.)

Fast and accurate assessment of small-molecule dihedral energetics is crucial for molecular design and optimization in medicinal chemistry. Yet, accurate prediction of torsion energy profiles remains challenging as the current molecular mechanics (MM) methods are limited by insufficient coverage of drug-like chemical space and accurate quantum mechanical (QM) methods are too expensive. To address this limitation, we introduce TorsionNet, a deep neural network (DNN) model specifically developed to predict small-molecule torsion energy profiles with QM-level accuracy. We applied active learning to identify nearly 50k fragments (with elements H, C, N, O, F, S, and Cl) that maximized the coverage of our corporate compound library and leveraged massively parallel cloud computing resources for density functional theory (DFT) torsion scans of these fragments, generating a training data set of 1.2 million DFT energies. After training TorsionNet on this data set, we obtain a model that can rapidly predict the torsion energy profile of typical drug-like fragments with DFT-level accuracy. Importantly, our method also provides an uncertainty estimate for the predicted profiles without any additional calculations. In this report, we show that TorsionNet can accurately identify the preferred dihedral geometries observed in crystal structures. Our TorsionNet-based analysis of a diverse set of protein-ligand complexes with measured binding affinity shows a strong association between high ligand strain and low potency. We also present practical applications of TorsionNet that demonstrate how consideration of DNN-based strain energy leads to substantial improvement in existing lead discovery and design workflows. TorsionNet500, a benchmark data set comprising 500 chemically diverse fragments with DFT torsion profiles (12k MM- and DFT-optimized geometries and energies), has been created and is made publicly available.

The idea behind network caching is to reduce network traffic during peak hours via transmitting frequently-requested content items to end users during off-peak hours. However, due to limited cache sizes and unpredictable access patterns, this might not totally eliminate the need for data transmission during peak hours. Coded caching was introduced to further reduce the peak hour traffic. The idea of coded caching is based on sending coded content which can be decoded in different ways by different users. This allows the server to service multiple requests by transmitting a single content item. Research works regarding coded caching traditionally adopt a simple network topology consisting of a single server, a single hub, a shared link connecting the server to the hub, and private links which connect the users to the hub. Building on the results of Sengupta et al. (IEEE Trans. Inf. Forensics Secur., 2015), we propose and evaluate a yet more complex system model that takes into consideration both throughput and security via combining the mentioned ideas. It is demonstrated that the achievable rates in the proposed model are within a constant multiplicative and additive gap with the minimum secure rates.

Background: Cardiovascular diseases (CVDs) are the leading cause of deaths and disability in Nepal. Health systems can improve CVD health outcomes even in resource-limited settings by directing efforts to meet critical system gaps. This study aimed to identify Nepal's health systems gaps to prevent and manage CVDs., Methods: We formed a task force composed of the government and non-government representatives and assessed health system performance across six building blocks: governance, service delivery, human resources, medical products, information system, and financing in terms of equity, access, coverage, efficiency, quality, safety and sustainability. We reviewed 125 national health policies, plans, strategies, guidelines, reports and websites and conducted 52 key informant interviews. We grouped notes from desk review and transcripts' codes into equity, access, coverage, efficiency, quality, safety and sustainability of the health system., Results: National health insurance covers less than 10% of the population; and more than 50% of the health spending is out of pocket. The efficiency of CVDs prevention and management programs in Nepal is affected by the shortage of human resources, weak monitoring and supervision, and inadequate engagement of stakeholders. There are policies and strategies in place to ensure quality of care, however their implementation and supervision is weak. The total budget on health has been increasing over the past five years. However, the funding on CVDs is negligible., Conclusion: Governments at the federal, provincial and local levels should prioritize CVDs care and partner with non-government organizations to improve preventive and curative CVDs services.

In quantum magnets, magnetic moments fluctuate heavily and are strongly entangled with each other, a fundamental distinction from classical magnetism. Here, with inelastic neutron scattering measurements, we probe the spin correlations of the honeycomb lattice quantum magnet YbCl 3 . A linear spin wave theory with a single Heisenberg interaction on the honeycomb lattice, including both transverse and longitudinal channels of the neutron response, reproduces all of the key features in the spectrum. In particular, we identify a Van Hove singularity, a clearly observable sharp feature within a continuum response. The demonstration of such a Van Hove singularity in a two-magnon continuum is important as a confirmation of broadly held notions of continua in quantum magnetism and additionally because analogous features in two-spinon continua could be used to distinguish quantum spin liquids from merely disordered systems. These results establish YbCl 3 as a benchmark material for quantum magnetism on the honeycomb lattice.

The energetics of rotation around single bonds (torsions) is a key determinant of the three-dimensional shape that druglike molecules adopt in solution, the solid state, and in different biological environments, which in turn defines their unique physical and pharmacological properties. Therefore, accurate characterization of torsion angle preference and energetics is essential for the success of computational drug discovery and design. Here, we analyze torsional strain in crystal structures of druglike molecules in Cambridge structure database (CSD) and bioactive ligand conformations in protein data bank (PDB), expressing the total strain energy as a sum of strain energy from constituent rotatable bonds. We utilized cloud computing to generate torsion scan profiles of a very large collection of chemically diverse neutral fragments at DFT(B3LYP)/6-31G*//6-31G** or DFT(B3LYP)/6-31+G*//6-31+G** (for sulfur-containing molecule). With the data generated from these ab initio calculations, we performed rigorous analysis of strain due to deviation of observed torsion angles relative to their ideal gas-phase geometries. Contrary to the previous studies based on molecular mechanics, we find that in the crystalline state, molecules generally adopt low-strain conformations, with median per-torsion strain energy in CSD and PDB under one-tenth and one-third of a kcal/mol, respectively. However, for a small fraction (<5%) of motifs, external effects such as steric hindrance and hydrogen bonds result in strain penalty exceeding 2.5 kcal/mol. We find that due to poor quality of PDB structures in general, bioactive structures tend to have higher torsional strain compared to small-molecule crystal conformations. However, in the absence of structural fitting artifacts in PDB structures, protein-induced strain in bioactive conformations is quantitatively similar to those due to the packing forces in small-molecule crystal structures. This analysis allows us to establish strain energy thresholds to help identify biologically relevant conformers in a given ensemble. The work presented here is the most comprehensive study to date that demonstrates the utility and feasibility of gas-phase quantum mechanics (QM) calculations to study conformational preference and energetics of drug-size molecules. Potential applications of this study in computational lead discovery and structure-based design are discussed.

Kondo-based semimetals and semiconductors are of extensive current interest as a viable platform for strongly correlated states in the dilute carrier limit. It is thus important to explore the routes to understand such systems. One established pathway is through the Kondo effect in metallic nonmagnetic analogs, in the so called half-filling case of one conduction electron and one 4 f electron per site. Here, we demonstrate that Kondo-based semimetals develop out of conduction electrons with a low-carrier density in the presence of an even number of rare-earth sites. We do so by studying the Kondo material Yb 3 Ir 4 Ge 13 along with its closed-4 f -shell counterpart, Lu 3 Ir 4 Ge 13 . Through magnetotransport, optical conductivity, and thermodynamic measurements, we establish that the correlated semimetallic state of Yb 3 Ir 4 Ge 13 below its Kondo temperature originates from the Kondo effect of a low-carrier conduction-electron background. In addition, it displays fragile magnetism at very low temperatures, which in turn, can be tuned to a Griffiths-phase-like regime through Lu-for-Yb substitution. These findings are connected with recent theoretical studies in simplified models. Our results can pave the way to exploring strong correlation physics in a semimetallic environment.

The discovery of D1 subtype-selective agonists with drug-like properties has been an enduring challenge for the greater part of 40 years. All known D1-selective agonists are catecholamines that bring about receptor desensitization and undergo rapid metabolism, thus limiting their utility as a therapeutic for chronic illness such as schizophrenia and Parkinson's disease. Our high-throughput screening efforts on D1 yielded a single non-catecholamine hit PF-4211 (6) that was developed into a series of potent D1 receptor agonist leads with high oral bioavailability and CNS penetration. An important structural feature of this series is the locked biaryl ring system resulting in atropisomerism. Disclosed herein is a summary of our hit-to-lead efforts on this series of D1 activators culminating in the discovery of atropisomer 31 (PF-06256142), a potent and selective orthosteric agonist of the D1 receptor that has reduced receptor desensitization relative to dopamine and other catechol-containing agonists.

We developed customizable biomolecule functionalized 3D poly-ε-caprolactone (PCL) scaffolds reinforced with carbon nanofibers (CNF) for human meniscal tissue engineering. 3D nanocomposite scaffolds exhibited commendable mechanical integrity and electrical properties with augmented cytocompatibility. Especially, the functionalized 3D (10wt% CNF) scaffolds showed ~363% increase in compressive moduli compared to the pristine PCL. In dynamic mechanical analysis, these scaffolds achieved highest value (~42 MPa at 10 Hz) among all tested scaffolds including pristine PCL and human menisci (33, 41, 56 years). In vitro results were well supported by the outcomes of cell proliferation analysis, microscopic images, Hoechst staining and extracellular-matrix estimation. Further, in vivo rabbit bio toxicity studies revealed scaffold's non-toxicity and its future potential as a meniscus scaffold. This study also indicates that the incorporation of CNF in polymer matrix may be optimized based on mechanical properties of patient meniscus and it may help in developing the customized patient specific 3D constructs with improved multifunctional properties., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Background: The diagnosis of acute coronary syndrome remains challenging, as cardiac troponins and creatine kinase-MB do not detect myocardial ischemia. Ischemia modified albumin is biomarker positive within 6-10 minutes following ischemic onset, where oxygen free radicals leads to reduction in binding capacity of human serum albumin to transitional metal-cobalt. The objective of this study was to compare ischemia modified albumin between acute coronary syndrome patients and healthy controls, and evaluate diagnostic performance of ischemia modified albumin compared to cardiac troponins, creatine kinase-MB and electrocardiogram in acute coronary syndrome patients., Methods: Fifty ACS patients and 50 healthy controls were enrolled in this cross-sectional study. Ischemia modified albumin was measured after addition of known amount of cobalt to human serum albumin, followed by spectrophotometric determination of unbound cobalt fraction at 470 nm using dithiothreitol as coloring agent. Independent student t-test and One-way ANOVA to compare differences of mean between groups; diagnostic sensitivity and specificity of ischemia modified albumin was determined by receiver operating characteristic curve; McNemar-test was used to assess diagnostic performance of entire test parameters, when used alone and in combinations., Results: Ischemia modified albumin was significantly higher in acute coronary syndrome patients compared to controls (0.823±0.191 vs 0.410±0.081)(p<0.001). Receiver operating characteristic curve derived optimal cut-off of 0.475 Absorbance unit had sensitivity and specificity of 92% and 82% respectively (area under curve- 0.96). However, no significant differences in mean ischemia modified albumin values between three categories of acute coronary syndrome were seen. Sensitivity of ischemia modified albumin assay (92%) was significantly higher compared to electrocardiogram (72%), cardiac troponin I (18%), and creatine kinase-MB(42%)., Conclusions: Ischemia modified albumin is elevated in acute coronary syndrome patients with better diagnostic performance compared to electrocardiogram, cardiac troponin I, and creatine kinase-MB for early diagnosis, however, with limited ability to discriminate between ST-elevation myocardial infarction, non-ST-elevation myocardial infarction and unstable angina.

We report complex metamagnetic transitions in single crystals of the new low carrier Kondo antiferromagnet YbRh 3 Si 7 . Electrical transport, magnetization, and specific heat measurements reveal antiferromagnetic order at T N = 7.5 K . Neutron diffraction measurements show that the magnetic ground state of YbRh 3 Si 7 is a collinear antiferromagnet, where the moments are aligned in the ab plane. With such an ordered state, no metamagnetic transitions are expected when a magnetic field is applied along the c axis. It is therefore surprising that high-field magnetization, torque, and resistivity measurements with H ‖ c reveal two metamagnetic transitions at μ 0 H 1 = 6.7 T and μ 0 H 2 = 21 T . When the field is tilted away from the c axis, towards the ab plane, both metamagnetic transitions are shifted to higher fields. The first metamagnetic transition leads to an abrupt increase in the electrical resistivity, while the second transition is accompanied by a dramatic reduction in the electrical resistivity. Thus, the magnetic and electronic degrees of freedom in YbRh 3 Si 7 are strongly coupled. We discuss the origin of the anomalous metamagnetism and conclude that it is related to competition between crystal electric-field anisotropy and anisotropic exchange interactions.

The first heterobimetallic phosphide thin film containing iron, manganese, and phosphorus, derived from the single-source precursor FeMn(CO) 8 (μ-PH 2 ), has been prepared using a home-built metal-organic chemical vapor deposition apparatus. The thin film contains the same ratio of iron, manganese, and phosphorus as the initial precursor. The film becomes oxidized when deposited on a quartz substrate, whereas the film deposited on an alumina substrate provides a more homogeneous product. Powder X-ray diffraction confirms the formation of a metastable, hexagonal FeMnP phase that was previously only observed at temperatures above 1200 °C. Selected area electron diffraction on single crystals isolated from the films was indexed to the hexagonal phase. The effective moment of the films (μ eff =3.68 μ B ) matches the previously reported theoretical value for the metastable hexagonal phase, whereas the more stable orthorhombic phase is known to be antiferromagnetic. These results not only demonstrate the successful synthesis of a bimetallic, ternary thin film from a single-source precursor, but also the first low temperature approach to the hexagonal phase of FeMnP., (© 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.)

In this study, silk fibroin nanofibrous scaffolds were developed to investigate the attachment and proliferation of primary human meniscal cells. Silk fibroin (SF)-polyvinyl alcohol (PVA) blended electrospun nanofibrous scaffolds with different blend ratios (2:1, 3:1, and 4:1) were prepared. Morphology of the scaffolds was characterized using atomic force microscopy (AFM). The hybrid nanofibrous mats were crosslinked using 25 % (v/v) glutaraldehyde vapor. In degradation study, the crosslinked nanofiber showed slow degradation of 20 % on weight after 35 days of incubation in simulated body fluid (SBF). The scaffolds were characterized with suitable techniques for its functional groups, porosity, and swelling ratio. Among the nanofibers, 3:1 SF:PVA blend showed uniform morphology and fiber diameter. The blended scaffolds had fluid uptake and swelling ratio of 80 % and 458 ± 21 %, respectively. Primary meniscal cells isolated from surgical debris after meniscectomy were subcultured and seeded onto these hybrid nanofibrous scaffolds. Meniscal cell attachment studies confirmed that 3:1 SF:PVA nanofibrous scaffolds supported better cell attachment and growth. The DNA and collagen content increased significantly with 3:1 SF:PVA. These results clearly indicate that a blend of SF:PVA at 3:1 ratio is suitable for meniscus cell proliferation when compared to pure SF-PVA nanofibers.

The present study investigates the impact of biomolecules (biotin, glucose, chondroitin sulphate, proline) as supplement, (individual and in combination) on primary human meniscus cell proliferation. Primary human meniscus cells isolated from patients undergoing meniscectomy were maintained in Dulbecco's Modified Eagle's Medium (DMEM). The isolated cells were treated with above mentioned biomolecules as individual (0-100 µg/ml) and in combinations, as a supplement to DMEM. Based on the individual biomolecule study, a unique combination of biomolecules (UCM) was finalized using one way ANOVA analysis. With the addition of UCM as supplement to DMEM, meniscal cells reached 100 % confluency within 4 days in 60 mm culture plate; whereas the cells in medium devoid of UCM, required 36 days for reaching confluency. The impact of UCM on cell viability, doubling time, histology, gene expression, biomarkers expression, extra cellular matrix synthesis, meniscus cell proliferation with respect to passages and donor's age were investigated. The gene expression studies for E-cadherin and peroxisome proliferator-activated receptor (PPAR∆) using RT-qPCR and immunohistochemical analysis for Ki67, CD34 and Vimentin confirmed that UCM has significant impact on cell proliferation. The extracellular collagen and glycosaminoglycan secretion in cells supplemented with UCM were found to increase by 31 and 37 fold respectively, when compared to control on the 4th day. The cell doubling time was reduced significantly when supplemented with UCM. The addition of UCM showed positive influence on different passages and age groups. Hence, this optimized UCM can be used as an effective supplement for meniscal tissue engineering., Competing Interests: None of the authors have a conflict of interests including direct or indirect financial relations with any of the trademarks and companies mentioned in this paper.

Objectives: Nepal is a least developed country, with limited healthcare resources. An 18 month Fellowship in Emergency Medicine has contributed some improvements to care. This study assessed time to first analgesia in higher and lower acuity patients., Methods: A prospective observational study of 101 patients in each of the Australasian Triage Scale (ATS) 2, 3 and 100 in ATS 4 was undertaken at B.P. Koirala Institute of Health Sciences. Convenience sampling was used coinciding with researcher's duty hours. Pain scores and time to analgesia were recorded., Results: A total of 302 patients were included. The doctors identified pain in 274 (90%, 95% confidence interval [CI] 86.74-93.65), severity recorded in 92 (30.5%, 95% CI 25-36). Median time from triage to analgesia was 30 min (interquartile range [IQR] 15-60) for ATS 2 patients, 60 min (IQR 40-70) for ATS 3 and 69 min (IQR 45-116) for ATS 4. Tramadol was the analgesic used most commonly (33%), followed by diclofenac (25%), morphine (16%), paracetamol (14%) and ketamine (2%). Analgesia was provided to 212 (70%, 95% CI 64.6-75.2), 65 (30.66%, 95% CI 24.5-37.3) with ATS 2, 85 (40%, 95% CI 33.4-47) with ATS 3 and 62 (29.2%, 95% CI 23.2-35.8) with ATS 4. A total of 44 patients (20.7%, 95% CI 15.5-26.8) with mild, 101 (47.6%, 95% CI 40.7-54.6) with moderate and 60 (28.3%, 95% CI 22.3-34.8) with severe pain received analgesics., Conclusion: Time to analgesia for triage score 2 is lower compared to higher triage score. However, a large proportion of patients still do not receive analgesia. This is likely addressed by using a combination of strategies., (© 2016 Australasian College for Emergency Medicine and Australasian Society for Emergency Medicine.)

Introduction: Self-prescription of medicines are common especially in low income countries.Paracetamol is a common medicine that is self-prescribed also among university students. Incorrect use of paracetamol can lead to ill effects on health including liver failure. There is scarce evidence of the use of paracetamol by self-medication in Nepal. The objective of this study is to evaluate the paracetamol use by self-prescription among the undergraduate students of BPKIHS., Methods: A cross-sectional study was conducted among 570 undergraduate students of BPKIHS from February 2016 till July 2016. Pretested semi-structured, self-administered questionnaire was used to collect information regarding socio-demographic characteristics, paracetamol use and perception regarding paracetamol use. Systematic random sampling was done from a list of all medical dental and nursing students to select the study sample., Results: Most (86%) students are in the category of 20-24 years. Female students are slightly more than male. Majority of the students are from Nepal. More than half of the students are from medical stream. Self-prescription of paracetamol is seen among 90.1% of the students in our study. Correct dose of paracetamol was mentioned by less than half (49.3%) of the students. Self-prescription of paracetamol is considered beneficial by all participants of this study., Conclusions: Self-prescription of paracetamol by health sciences students of B P Koirala Institute of Health Sciences is high, while the knowledge of correct dose of paracetamol for adults is low. There is a need to further explore this gap and possibly conduct further studies for other medicines as well.

Pure phase exchange-coupled nanocomposites of hard-soft magnetic oxides, (hard) SrFe10Al2O19(-) (soft) Ni0.75Zn0.25Fe2O4 were prepared via autocombution method. Magnetic properties of the nanocomposites were assessed as a function of soft-phase content in the nanocomposite. A 40% increase in M(s) value was observed for nanocomposite with 30 Wt.% of the soft phase. A linear increase in M(r)/M(s) with soft-phase content indicates the presence of enhanced exchange-coupling between hard and soft phases of the nanocomposite. The highest M(r)/M(s) ratio of 0.68 was obtained for nanocomposite containing 30 Wt.% of the soft-phase. The observed reduction in coercieve field values of the nanocomposite with increase in soft-phase content is explained on the basis of competition between exchange and dipolar interaction between hard-soft and soft-soft phases of the nanocomposite.

Background: Complete rectal prolapse is characterized by protrusion of full thickness rectal wall through the anal orifice. Despite its rarity more than 100 surgical procedures have been described and there are no good evidence based recommendations for selection of a surgical procedure. This study was conducted to evaluate the clinical outcomes of commonly used procedures for rectal prolapse at our hospital., Materials and Methods: Twenty seven patients presenting with complete rectal prolapse between May 2011 to May 2013 were included in this prospective study. Patients underwent either Abdominal rectopexy or Delorme's procedure after evaluation, based on clinical judgment of experienced surgeons. Patient characteristics, complications, post-operative length of hospitalization and clinical outcomes were assessed. Patients were followed up for a mean duration of 14 months., Results: Seventeen patients underwent Abdominal rectopexy (Posterior mesh rectopexy), ten patients underwent Delorme's procedure. No postoperative mortalities or major complications were noted. Post operative morbidity (minor) was 17% in Abdominal rectopexy group and 10% in Delormes group 0%. Incontinence improved in all six patients (100%) in rectopexy group, four patients (80%) in Delorme's procedure group. Two patients (11%) in rectopexy group reported increase in constipation post operatively. There was one recurrence in Delorme's procedure group with no recurrences in Abdominal rectopexy group., Conclusion: The treatment of rectal prolapse should be individualized to achieve best results. Abdominal rectopexy can be safely applied in most of patients with minimal post operative increase in constipation and recurrence by using posterior mesh rectopexy technique. Delorme's procedure can be performed with minimal morbidity and shorter hospital stay and good functional results with acceptable recurrence rate. Delorme's can be considered as an alternative to rectopexy not only in patients unfit for laparotomy but also in individuals with a short prolpase, avoiding a laparotomy.

We introduce a class of partial atomic charge assignment method that provides ab initio quality description of the electrostatics of bioorganic molecules. The method uses a set of models that neither have a fixed functional form nor require a fixed set of parameters, and therefore are capable of capturing the complexities of the charge distribution in great detail. Random Forest regression is used to build separate charge models for elements H, C, N, O, F, S, and Cl, using training data consisting of partial charges along with a description of their surrounding chemical environments; training set charges are generated by fitting to the b3lyp/6-31G* electrostatic potential (ESP) and are subsequently refined to improve consistency and transferability of the charge assignments. Using a set of 210 neutral, small organic molecules, the absolute hydration free energy calculated using these charges in conjunction with Generalized Born solvation model shows a low mean unsigned error, close to 1 kcal/mol, from the experimental data. Using another large and independent test set of chemically diverse organic molecules, the method is shown to accurately reproduce charge-dependent observables--ESP and dipole moment--from ab initio calculations. The method presented here automatically provides an estimate of potential errors in the charge assignment, enabling systematic improvement of these models using additional data. This work has implications not only for the future development of charge models but also in developing methods to describe many other chemical properties that require accurate representation of the electronic structure of the system., (Copyright © 2013 Wiley Periodicals, Inc.)

Novel near infrared-absorbing iron oxide-gold core-shell nanoparticles in pin shapes were synthesized. The nanopins are superparamagnetic, with 35-fold better surface enhanced Raman scattering activities than the conventional core-shell nanospheres and 50-fold greater photothermal properties than solid gold nanorods. The nanoparticles will have important impact on medical imaging, molecular diagnostics and disease treatment.

Silver nanoparticles-polymer nanocomposites, Ag-(1 - x)PVP-(x)PEG, were synthesized by wet chemical method in the presence of polyvinylpyrrolidone (PVP) and polyethylene glycol (PEG). A mixture of two stabilizing agent PVP and PEG is found to play a crucial role in controlling the morphology of nanocrystalline silver particles in the composite. This is inferred based on the shape and size study of nanocrystalline silver using the X-ray diffraction, transmission electron microscopy, Uv-vis spectroscopy, FTIR, and surface enhance Raman studies. These results suggest asymmetrical growth of silver nanocrystalline particles in the presence of both PVP and PEG. Comparison of the thermal properties of the Ag-polymer nanocomposites with pure polymers, PVP and PEG, showed that the thermal stability of the nanocomposite deteriorates by as much as 75 degrees C in the presence of low PEG concentration (x < or = 0.6) and improves by around 45 degrees C at higher PEG concentration (x > 0.6). The study highlight the fact that the morphology of nanocrystalline silver can be altered just by varying the polymer weight ratios rather than any processing parameters, thus offering a novel, simple, and controlled synthesis engineering route to the formation of nanocrystalline silver in polymer matrix.

In this paper, we describe a lead transformation tool, NEAT (Novel and Electronically equivalent Aromatic Template), which can help identify novel aromatic rings that are estimated to have similar electrostatic potentials, dipoles, and hydrogen bonding capabilities to a query template; hence, they may offer similar bioactivity profiles. In this work, we built a comprehensive heteroaryl database, and precalculated high-level quantum mechanical (QM) properties, including electrostatic potential charges, hydrogen bonding ability, dipole moments, chemical reactivity, and othe properties. NEAT bioisosteric similarities are based on the electrostatic potential surface calculated by Brood, using the precalculated QM ESP charges and other QM properties. Compared with existing commercial lead transformation software, (1) NEAT is the only one that covers the comprehensive heteroaryl chemical space, and (2) NEAT offers a better characterization of novel aryl cores by using high-evel QM properties that are relevant to molecular interactions. NEAT provides unique value to medicinal chemists quickly exploring the largely uncharted aromatic chemical space, and one successful example of its application is discussed herein.

A target is druggable if it can be modulated in vivo by a drug-like molecule. The general properties of oral drugs are summarized by the 'rule of 5' which specifies parameters related to size and lipophilicity. Structure-based target druggability assessment consists of predicting ligand-binding sites on the protein that are complementary to these drug-like properties. Automated identification of ligand-binding sites can use geometrical considerations alone or include specific physicochemical properties of the protein surface. Features of a pocket's size and shape, together with measures of its hydrophobicity, are most informative in identifying suitable drug-binding pockets. The recent availability of several validation sets of druggable versus undruggable targets has helped fuel the development of more elaborate methods., (Copyright © 2011 Elsevier Ltd. All rights reserved.)

Introduction: Bacterial infections account for a huge proportion of neonatal deaths worldwide. The problem of antibiotic resistance among common bacterial pathogens mainly the gram negative bacteria is emerging globally which is of more serious concern in developing countries like Nepal., Methods: A one year retrospective hospital based study was carried out to analyze the results of neonatal blood, cerebrospinal fluid, urine, stool and surface cultures and to look into the sensitivity pattern of the commonly used antibiotics., Results: The positive yield of blood, urine, eye swab and CSF cultures were 19.56%, 38.5%, 60% and 0.36% respectively. The most common isolates in the blood culture were coagulase negative Staphylococcus, Acinetobacter, Enterobacter and non-haemolytic Streptococcus. A significant percent of the isolates were resistant to the first line antibiotics. Among the gram negative isolates more than 30% are resistant to cefotaxime and more than 50% are resistant to gentamicin. During the one year period we had Nursery outbreaks of methicillin resistant Staphylococcus aureus and Salmonella infections. With the help of environmental cultures we were able to trace the source and intervene appropriately., Conclusions: Continuous surveillance for antibiotic susceptibility, rational use of antibiotics and the strategy of antibiotic cycling can provide some answers to the emerging problem of antibiotic resistance.

G Protein-Coupled Receptors (GPCRs) are integral membrane proteins that play important role in regulating key physiological functions, and are targets of about 50% of all recently launched drugs. High-resolution experimental structures are available only for very few GPCRs. As a result, structure-based drug design efforts for GPCRs continue to rely on in silico modeling, which is considered to be an extremely difficult task especially for these receptors. Here, we describe Gmodel, a novel approach for building 3D atomic models of GPCRs using a normal mode-based refinement of homology models. Gmodel uses a small set of relevant low-frequency vibrational modes derived from Random Elastic Network model to efficiently sample the large-scale receptor conformation changes and generate an ensemble of alternative models. These are used to assemble receptor-ligand complexes by docking a known active into each of the alternative models. Each of these is next filtered using restraints derived from known mutation and binding affinity data and is refined in the presence of the active ligand. In this study, Gmodel was applied to generate models of the antagonist form of histamine 3 (H3) receptor. The validity of this novel modeling approach is demonstrated by performing virtual screening (using the refined models) that consistently produces highly enriched hit lists. The models are further validated by analyzing the available SAR related to classical H3 antagonists, and are found to be in good agreement with the available experimental data, thus providing novel insights into the receptor-ligand interactions., ((c) 2009 Wiley-Liss, Inc.)

Molecular docking programs are widely used modeling tools for predicting ligand binding modes and structure based virtual screening. In this study, six molecular docking programs (DOCK, FlexX, GLIDE, ICM, PhDOCK, and Surflex) were evaluated using metrics intended to assess docking pose and virtual screening accuracy. Cognate ligand docking to 68 diverse, high-resolution X-ray complexes revealed that ICM, GLIDE, and Surflex generated ligand poses close to the X-ray conformation more often than the other docking programs. GLIDE and Surflex also outperformed the other docking programs when used for virtual screening, based on mean ROC AUC and ROC enrichment values obtained for the 40 protein targets in the Directory of Useful Decoys (DUD). Further analysis uncovered general trends in accuracy that are specific for particular protein families. Modifying basic parameters in the software was shown to have a significant effect on docking and virtual screening results, suggesting that expert knowledge is critical for optimizing the accuracy of these methods.