TECHNIQUES TO ENHANCE USER PLANE FUNCTION (UPF) LOAD METRICS TO IMPROVE UPF SELECTION

Mobile network architectures, such as Fifth Generation Core (5GC) architectures are designed to serve a variety of use cases in which each of the use cases can demand very different network resource allocation and traffic treatment. The introduction of the Control and User Plane separation (CUPS) architecture in the Evolved Packet Core (EPC) mobile network architecture, requires the control plane (CP) to select an appropriate User Plane Function (UPF) to serve a service request from a user equipment (UE) with a desired Quality of Service (QoS). This proposal provides techniques through which optimum UPF usage can be determined by considering multiple load factors, which can aid in performing UPF selection for 5GC and CUPS/EPC mobile network architectures

Evaluation of finite difference based asynchronous partial differential equations solver for reacting flows

Next-generation exascale machines with extreme levels of parallelism will provide massive computing resources for large scale numerical simulations of complex physical systems at unprecedented parameter ranges. However, novel numerical methods, scalable algorithms and re-design of current state-of-the art numerical solvers are required for scaling to these machines with minimal overheads. One such approach for partial differential equations based solvers involves computation of spatial derivatives with possibly delayed or asynchronous data using high-order asynchrony-tolerant (AT) schemes to facilitate mitigation of communication and synchronization bottlenecks without affecting the numerical accuracy. In the present study, an effective methodology of implementing temporal discretization using a multi-stage Runge-Kutta method with AT schemes is presented. Together these schemes are used to perform asynchronous simulations of canonical reacting flow problems, demonstrated in one-dimension including auto-ignition of a premixture, premixed flame propagation and non-premixed autoignition. Simulation results show that the AT schemes incur very small numerical errors in all key quantities of interest including stiff intermediate species despite delayed data at processing element (PE) boundaries. For simulations of supersonic flows, the degraded numerical accuracy of well-known shock-resolving WENO (weighted essentially non-oscillatory) schemes when used with relaxed synchronization is also discussed. To overcome this loss of accuracy, high-order AT-WENO schemes are derived and tested on linear and non-linear equations. Finally the novel AT-WENO schemes are demonstrated in the propagation of a detonation wave with delays at PE boundaries

Quantifying the Twitter Influence of Third Party Commercial Entities versus Healthcare Providers in Thirteen Medical Conferences from 2011-2013

Introduction Twitter channels are increasingly popular at medical conferences. Many groups, including healthcare providers and third party entities (e.g., pharmaceutical or medical device companies) use these channels to communicate with one another. These channels are unregulated and can allow third party commercial entities to exert an equal or greater amount of Twitter influence than healthcare providers. Third parties can use this influence to promote their products or services instead of sharing unbiased, evidence-based information. In this investigation we quantified the Twitter influence that third party commercial entities had in 13 major medical conferences. Methods We analyzed tweets contained in the official Twitter hashtags of thirteen medical conferences from 2011 to 2013. We placed tweet authors into one of four categories based on their account profile: healthcare provider, third party commercial entity, none of the above and unknown. We measured Twitter activity by the number of tweet authors per category and the tweet-to-author ratio by category. We measured Twitter influence by the PageRank of tweet authors by category. Results We analyzed 51159 tweets authored by 8778 Twitter account holders in 13 conferences that were sponsored by 5 medical societies. A quarter of all authors identified themselves as healthcare providers, while only 18% could be identified as third party commercial entities. Healthcare providers had a greater tweet-to-author ratio than their third party commercial entity counterparts (8.98 versus 6.93 tweets). Despite having less authors and composing less tweets, third party commercial entities had a statistically similar PageRank as healthcare providers (0.761 versus 0.797). Conclusion The Twitter influence of third party commercial entities (PageRank) is similar to that of healthcare providers. This finding is interesting because the number of tweets and third party commercial entity authors required to achieve this PageRank is far fewer than that needed by healthcare providers. Without safety mechanisms in place, the Twitter channels of medical conferences can devolve into a venue for the spread of biased information rather than evidence-based medical knowledge that is expected at live conferences. Continuing to measure the Twitter influence that third parties exert can help conference organizers develop reasonable guidelines for Twitter channel activity

Self-nano Emulsifying Formulations: An Encouraging Approach for Bioavailability Enhancement and Future Perspective

Currently lipid-based formulations are playing a vital and promising role in improving the oral bioavailability of poorly water-soluble drugs. Lipid based formulations mainly consist of a drug dissolved in lipids such as triglycerides, glycerides, oils and surface active agent. Self nanoemulsifying formulations (SNEF) are isotropic mixtures of lipids/oils, surfactants and co-surfactants. On mild agitation followed by dilution in aqueous media, such as GI fluids, SNEF can form fine oil-in-water (o/w) nanoemulsions. Present chapter summarizes different types of lipid formulations with special emphasis on SNEF, availability of dosage forms, different components with natural surfactants from medicinal plants, mechanism of SNEF, recent advancements in oral drug delivery, solid SNEDDS, patents on SNEF and future prospects. SNEF emerging as powerful technique to improve solubility and commercialization of solid SNEF is the future novel drug delivery to improve bioavailability of poorly water soluble drugs

Association of Cutibacterium acnes with human thyroid cancer

IntroductionThe diverse subtypes of thyroid carcinoma have distinct clinical outcomes despite a comparable spectrum of underlying genetic alterations. Beyond genetic alterations, sparse efforts have been made to characterize the microbes associated with thyroid cancer. In this study, we examine the microbial profile of thyroid cancer.MethodsWe sequenced the whole transcriptome of 70 thyroid cancers (40 papillary and 30 anaplastic). Using Infectious Pathogen Detector IPD 2.0, we analysed the relative abundance of 1060 microbes across 70 tumours from patients with thyroid cancer against 118 tumour samples from patients with breast, cervical, colorectal, and tongue cancer.ResultsOur analysis reveals a significant prevalence of Cutibacterium acnes in 58.6% thyroid cancer samples compared to other cancer types (p=0.00038). Immune cell fraction analysis between thyroid cancer samples with high and low Cutibacterium loads identify enrichment of immunosuppressive cells, including Tregs (p=0.015), and other anti-inflammatory cytokines in the tumour microenvironment, suggesting an immune evasion/immunosuppression milieu is associated with the infection. A higher burden of Cutibacterium acnes was also found to be associated with poor survival defining a distinct sub-group of thyroid cancer.ConclusionCutibacterium acnes is associated with immune suppression and poor prognosis in a subpopulation of thyroid cancer. This study may help design novel therapeutic measures involving appropriate antibiotics to manage the disease better

Role of Drug Repurposing in Cancer Treatment and Liposomal Approach of Drug Targeting

Cancer is the leading cause of death, and incidences are increasing significantly and patients suffering from it desperately need a complete cure from it. The science of using an already-invented drug that has been approved by the FDA for a new application is known as “drug repurposing.” Currently, scientists are drawn to drug repositioning science in order to investigate existing drugs for newer therapeutic uses and cancer treatment. Because of their unique ability to target cancer cells, recently repurposed drugs and the liposomal approach are effective in the treatment of cancer. Liposomes are nanovesicles that are drastically flexible, rapidly penetrate deeper layers of cells, and enhance intracellular uptake. More importantly, liposomes are biocompatible, biodegradable; entrap both hydrophobic and hydrophilic drugs. This chapter summarizes various approaches to drug repurposing, as well as drug repurposing methods, advantages and limitations of drug repurposing, and a liposomal approach to using repurposed drugs in cancer targeting. This chapter also summarizes liposomal structure, drug loading, and the mechanism of liposomes in targeted cancer treatment. The lipid-based liposomal approach is emerging as a powerful technique for improving drug solubility, bioavailability, reducing side effects, and improving the therapeutic efficacy of repurposed drugs for cancer treatment

SARS-CoV-2 B.1.617.2 Delta variant replication and immune evasion

Abstract: The B.1.617.2 (Delta) variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first identified in the state of Maharashtra in late 2020 and spread throughout India, outcompeting pre-existing lineages including B.1.617.1 (Kappa) and B.1.1.7 (Alpha)1. In vitro, B.1.617.2 is sixfold less sensitive to serum neutralizing antibodies from recovered individuals, and eightfold less sensitive to vaccine-elicited antibodies, compared with wild-type Wuhan-1 bearing D614G. Serum neutralizing titres against B.1.617.2 were lower in ChAdOx1 vaccinees than in BNT162b2 vaccinees. B.1.617.2 spike pseudotyped viruses exhibited compromised sensitivity to monoclonal antibodies to the receptor-binding domain and the amino-terminal domain. B.1.617.2 demonstrated higher replication efficiency than B.1.1.7 in both airway organoid and human airway epithelial systems, associated with B.1.617.2 spike being in a predominantly cleaved state compared with B.1.1.7 spike. The B.1.617.2 spike protein was able to mediate highly efficient syncytium formation that was less sensitive to inhibition by neutralizing antibody, compared with that of wild-type spike. We also observed that B.1.617.2 had higher replication and spike-mediated entry than B.1.617.1, potentially explaining the B.1.617.2 dominance. In an analysis of more than 130 SARS-CoV-2-infected health care workers across three centres in India during a period of mixed lineage circulation, we observed reduced ChAdOx1 vaccine effectiveness against B.1.617.2 relative to non-B.1.617.2, with the caveat of possible residual confounding. Compromised vaccine efficacy against the highly fit and immune-evasive B.1.617.2 Delta variant warrants continued infection control measures in the post-vaccination era

Direct Numerical Simulations of Flame Propagation in Stratified Mixtures at Auto-ignitive Conditions Using Accelerated Computing

Direct numerical simulation (DNS) of auto-ignition under turbulent conditions has played a very important role in improving the fundamental understanding and advancement of combustion technologies for practical applications. However, very little is known of the nature of combustion in a reactive fuel/air mixture that is conducive to both spontaneous ignition and premixed deflagration. As such, characterizing the precise nature of combustion and the relevant propagation speed remains a challenge. This study attempts to address these questions by performing fully resolved numerical simulations of preheated fuel/air mixtures at elevated pressures using a newly developed DNS code called KAUST Adaptive Reactive Flows Solver (KARFS). Unlike a periodic box setup that has been used in most of the previous DNS studies, an inflow-outflow configuration representing a statistically stationary reaction front has been employed to understand the unsteady flame dynamics at auto-ignitive conditions.The first part of the dissertation is devoted to a discussion on parametric mapping of propagation speeds of auto-ignitive dimethyl-ether/air as well as dimethyl-ether/methane/air mixtures at elevated pressures under the influence of monochromatic thermal and composition/reactivity stratification using a one-dimensional, statistically stationary configuration. Thereafter, the implementation and effectiveness of Weighted Essentially Non-oscillatory (WENO) schemes in performing DNS of turbulent reacting flows is demonstrated with various non-trivial model problems. In addition, the scalability and performance portability of KARFS is presented on heterogeneous (CPU + GPU) system architectures. Finally, as a more extensive parametric quantification of the effects of thermal and composition stratification on turbulent flame propagation, results from DNS of a turbulent premixed flame in an auto-ignitive dimethyl-ether/air mixture conducted at elevated pressure are presented and discussed. The outcomes of this dissertation are expected to provide a fundamental understanding of the combustion mode transition and relevant propagation speeds in modern engines utilizing mixed-mode combustion