946 Standardized transcriptional profiling for optimizing cellular therapies: a multi-center PICI-NanoString collaboration

BackgroundThe field of cellular therapy remains one of the most promising areas for the development of new cancer treatments. To further these improvements, it is imperative to broadly understand cell therapy products at the molecular level and to identify factors that contribute to their efficacy. NanoString and the Parker Institute for Cancer Immunotherapy (PICI) have established a ground-breaking collaboration to characterize up to 1,000 apheresis and cellular therapy infusion products with the primary goal to dissect and study molecular pathways that correlate with optimal cellular therapies.MethodsUsing a large and diverse sample cohort collected from eight PICI network Cell Therapy Centers the team will aim to study gene expression profiles (GEP) that correlate with optimal apheresis and downstream cellular products, identifying biomarkers and signatures for clinical response or toxicity and further explore unique cancer-specific and shared characteristics that make an optimal and effective chimeric antigen receptor (CAR) T cell. As shown here, this first of its kind study will include samples that target dozens of different antigens covering both primary and metastatic hematological and solid tumors. Samples will be characterized using the standardized set of genes included in the nCounter CAR-T Characterization Panel and will measure essential components of CAR-T including: metabolic fitness, phenotype, TCR diversity, toxicity, activation, persistence, exhaustion and cell typing along with individual transgene expression.ResultsPresented here are initial questions that will be asked as part of this study. Meta-analysis will be performed as an aggregated set of data and individual site-specific analysis. Data will further be analyzed across individual cancer types, target types, outcome and manufacturing conditions as examples. We anticipate this information will prove useful across many aspects of the development, manufacturing and clinical applications for cellular therapies and further hypothesize that these findings will promote the understanding of pathways affecting safety and efficacy that may help optimize the therapy.ConclusionsThe project is anticipated to begin Fall of 2021 with work continuing in phases through 2022 with periodic data reports to be shared through scientific conferences. All data and findings will be made publicly available to the scientific community through PICI’s Cancer Data and Evidence Library analysis platform (CANDEL).

Rough estimation of cell numbers in 5G networks using simple mathematical calculations

This paper focuses on the problem of 5G network cell planning. In addition, it presents an example of a rough estimation of the required number of cells or base stations in a certain area for arbitrary number of users who are provided with a certain bandwidth per user within these cells. The cell number estimation is the initial step and the essence of planning and implementation of 5G network in an area. It is helpful for the operators to create and take into the account business plans in order to fully implement the network as a function of number of users which have to be served. Considering that, knowing the rough number of 5G base stations per user is very important for pre-sale activities and eventually necessity for widening of the initial investments. Therefore, the paper presents four scenarios that include different network parameters. Depending on the network parameters, the required number of base stations in a certain area changes. Given scenarios are examples of one 5G network in virtual area per bandwidth per user.

Speeding Up Reachability Queries in Public Transport Networks Using Graph Partitioning

Computing path queries such as the shortest path in public transport networks is challenging because the path costs between nodes change over time. A reachability query from a node at a given start time on such a network retrieves all points of interest (POIs) that are reachable within a given cost budget. Reachability queries are essential building blocks in many applications, for example, group recommendations, ranking spatial queries, or geomarketing. We propose an efficient solution for reachability queries in public transport networks. Currently, there are two options to solve reachability queries. (1) Execute a modified version of Dijkstra’s algorithm that supports time-dependent edge traversal costs; this solution is slow since it must expand edge by edge and does not use an index. (2) Issue a separate path query for each single POI, i.e., a single reachability query requires answering many path queries. None of these solutions scales to large networks with many POIs. We propose a novel and lightweight reachability index. The key idea is to partition the network into cells. Then, in contrast to other approaches, we expand the network cell by cell. Empirical evaluations on synthetic and real-world networks confirm the efficiency and the effectiveness of our index-based reachability query solution.

Network Throughput and Outage Analysis in a Poisson and Matérn Cluster based LTE-Advanced Small Cell Networks

<div>In LTE-A (LTE-Advanced), the access network cell formation is an integrated form of outdoor unit and indoor unit. With the indoor unit extension the access network becomes heterogeneous (HetNet). HetNet is a straightforward way to provide quality of service (QoS) in terms better network coverage and high data rate. Although, due to uncoordinated, densely deployed small cells large interference may occur, particularly in case of operating small cells within the spectrum of macro base stations (MBS). This paper probes the impact of small cell on the outage probability and the average network throughput enhancement. The positions of the small cells are retained random and modelled with homogeneous Poisson Point Process (PPP) and Matérn Cluster process (MCP). The paper provides an analytic form which permits to compute the outage probability, including the mostly applied fast fading channel types. Furthermore, simulations are evaluated in order to calculate the average network throughput for both random processes. Simulation results highlights that the network throughput remarkably grows due to small cell deployment.</div>

Network Throughput and Outage Analysis in a Poisson and Matérn Cluster based LTE-Advanced Small Cell Networks

<div>In LTE-A (LTE-Advanced), the access network cell formation is an integrated form of outdoor unit and indoor unit. With the indoor unit extension the access network becomes heterogeneous (HetNet). HetNet is a straightforward way to provide quality of service (QoS) in terms better network coverage and high data rate. Although, due to uncoordinated, densely deployed small cells large interference may occur, particularly in case of operating small cells within the spectrum of macro base stations (MBS). This paper probes the impact of small cell on the outage probability and the average network throughput enhancement. The positions of the small cells are retained random and modelled with homogeneous Poisson Point Process (PPP) and Matérn Cluster process (MCP). The paper provides an analytic form which permits to compute the outage probability, including the mostly applied fast fading channel types. Furthermore, simulations are evaluated in order to calculate the average network throughput for both random processes. Simulation results highlights that the network throughput remarkably grows due to small cell deployment.</div>

ANALYSIS OF MOBILE TELECOMMUNICATION PATH LOSS IN RURAL COMMUNITIES

: In this work, a cheaper alternative method of determining path loss using Network cell info lite software is proposed. Hata-Okumura model is used in the determination of path loss and signal strength of mobile communication devices within Ibogun and Ifo, a suburban community in Ogun state, Nigeria. Additionally, this paper is also aimed at determining the path loss under transmission line to ensure proper network planning in areas covered by transmission lines. Result obtained shows that areas with pylons have greater path loss compared to areas with no pylons. It is recommended that the power levels of base station operating in this area should be increased.

4G LTE Network Coverage Optimization Using Metaheuristic Approach

The main focus of this paper is to optimize the coverage of each 4G LTE network cell within the service area. There are many algorithms can be implemented to determine the optimal 4G LTE coverage area including the deterministic and heuristic approaches. The deterministic approach could solve accurately the optimization problem but need more resources and time consuming to determine the convergence parameters. Therefore, the heuristic approaches were introduced to improve the deterministic approach drawback. The methods used are the Differential Evolution Algorithm (DEA) and Adaptive Mutation Genetic Algorithm (AMGA), which are categorized as metaheuristic approach. The DEA and AMGA algorithms have been widely used to solve combinatorial problems, including for solving the network optimizations. In the network optimization, coverage is strongly related to 2 objectives, which are reducing the black spot area and decreasing the overlapping coverage areas. Coverage overlap is a condition when some cell sites in an area overlap. It implies in the occurrence of hand off and an inefficient network management. This research aims to obtain an optimal 4G LTE network coverage and reduce the overlapping coverage areas based on effective e-Node B arrangements by using the DEA and AMGA algorithms. The simulations results showed that the DEA algorithm’s coverage effectiveness was 23,4%, and the AMGA Algorithm’s was 16,32%.

Development of Radio Propagation Path Loss Model for Kaduna Town, Nigeria Using GMDH Algorithm

Radio propagation measurement were acquired at the 900 MHz and 1800 MHz frequency bands from six (6) live base stations (BS1 to BS6) in Kaduna town, Nigeria using an Asus Zenfone enhanced with a network monitoring software (Network Cell Info Lite). The receive signal strength (RSS) measurements were taken from the BSs at a distances of 200 m apart (in dB) until the signal faded out and the measurements were taken for twelve (12) calendar months which covered all seasons of the year, the corresponding path loss were calculated which were subsequently used to develop a propagation path loss prediction model with the Group Method of Data Handling (GMDH) algorithm. However, the results obtained shows very small variations between the model fit (which was the best fit curve from the measured data) and the predictions (which is the forecast). Hence, since the variations between the model fit and the predictions are not wide, with sometime the values of prediction being better than that model fit, the GMDH model is showing good prediction for Kaduna metropolis.