Strict frequency reuse algorithm in random cellular networks

© 2016 IEEE. A Frequency Reuse algorithm which divides the users into two groups called Cell-Center Users (CCUs) and Cell- Edge Users (CEUs) is one of the most effective techniques that can mitigate the InterCell Interference as well as improve the spectrum efficiency in cellular networks. In literature, most of work on Strict Frequency Reuse algorithms in a Spatial Point Poisson network assumed that the reuse factor was 1 and there was either single user or single Resource Block (RB). Hence, the performance either CEU or CCU was discussed. In this paper, the performance of both types of users as well as total throughput of CEUs and CCUs are investigated. The analytical results indicate that most of users in Tier-1 are served as CCUs while the numbers of UEUs and CCUs in Tier-2 are similar

Performance of soft frequency reuse in random cellular networks in Rayleigh-Lognormal fading channels

© 2016 IEEE. Soft Frequency Reuse (Soft FR) is an effective resource allocation technique that can improve the instantaneous received Signal-to-Interference-plus-Noise ratio (SINR) at a typical user and the spectrum efficiency. In this paper, the performance of Soft FR in Random Cellular network, where the locations of Base Stations (BSs) are random variables of Spatial Point Poisson Process (PPP), is investigated. While most of current works considered the network model with either single RB or frequency reuse with factor of 1, this work assume that the Soft FR with factor of Δ is deployed and there are M users and N (Δ > 1, M > 1, N > 1). The analytical and simulation results show that a network system with high frequency reuse factor create more InterCell Interference than that with low frequency reuse factor. Furthermore, in order to design the parameters to optimize Soft FR, the performance of the Cell-Edge and Cell-Center user should be considered together

Red blood cell extracellular vesicles as robust carriers of RNA-based therapeutics

One of the major challenges of RNA-based therapeutics is the method for delivery of RNA molecules. In a recent article (Nat Commun 9(1):2359), we described a novel delivery platform for RNA-based drugs using red blood cell extracellular vesicles which can efficiently deliver both small and large RNAs to solid and liquid tumours. Our RBCEVs platform features exceptional merits over conventional RNA delivery methods in biosafety, biocompatibility, efficiency, accessibility, and cost effectiveness

Regulatory de novo mutations underlying intellectual disability

The genetic aetiology of a major fraction of patients with intellectual disability (ID) remains unknown. De novo mutations (DNMs) in protein-coding genes explain up to 40% of cases, but the potential role of regulatory DNMs is still poorly understood. We sequenced 63 whole genomes from 21 ID probands and their unaffected parents. In addition, we analysed 30 previously sequenced genomes from exome-negative ID probands. We found that regulatory DNMs were selectively enriched in fetal brain-specific enhancers as compared with adult brain enhancers. DNM-containing enhancers were associated with genes that show preferential expression in the prefrontal cortex. Furthermore, we identified recurrently mutated enhancer clusters that regulate genes involved in nervous system development (CSMD1, OLFM1, and POU3F3). Most of the DNMs from ID probands showed allele-specific enhancer activity when tested using luciferase assay. Using CRISPR-mediated mutation and editing of epigenomic marks, we show that DNMs at regulatory elements affect the expression of putative target genes. Our results, therefore, provide new evidence to indicate that DNMs in fetal brain-specific enhancers play an essential role in the aetiology of ID

MDCK Cystogenesis Driven by Cell Stabilization within Computational Analogues

The study of epithelial morphogenesis is fundamental to increasing our understanding of organ function and disease. Great progress has been made through study of culture systems such as Madin-Darby canine kidney (MDCK) cells, but many aspects of even simple morphogenesis remain unclear. For example, are specific cell actions tightly coupled to the characteristics of the cell's environment or are they more often cell state dependent? How does the single lumen, single cell layer cyst consistently emerge from a variety of cell actions? To improve insight, we instantiated in silico analogues that used hypothesized cell behavior mechanisms to mimic MDCK cystogenesis. We tested them through in vitro experimentation and quantitative validation. We observed novel growth patterns, including a cell behavior shift that began around day five of growth. We created agent-oriented analogues that used the cellular Potts model along with an Iterative Refinement protocol. Following several refinements, we achieved a degree of validation for two separate mechanisms. Both survived falsification and achieved prespecified measures of similarity to cell culture properties. In silico components and mechanisms mapped to in vitro counterparts. In silico, the axis of cell division significantly affects lumen number without changing cell number or cyst size. Reducing the amount of in silico luminal cell death had limited effect on cystogenesis. Simulations provide an observable theory for cystogenesis based on hypothesized, cell-level operating principles

Relational grounding facilitates development of scientifically useful multiscale models

We review grounding issues that influence the scientific usefulness of any biomedical multiscale model (MSM). Groundings are the collection of units, dimensions, and/or objects to which a variable or model constituent refers. To date, models that primarily use continuous mathematics rely heavily on absolute grounding, whereas those that primarily use discrete software paradigms (e.g., object-oriented, agent-based, actor) typically employ relational grounding. We review grounding issues and identify strategies to address them. We maintain that grounding issues should be addressed at the start of any MSM project and should be reevaluated throughout the model development process. We make the following points. Grounding decisions influence model flexibility, adaptability, and thus reusability. Grounding choices should be influenced by measures, uncertainty, system information, and the nature of available validation data. Absolute grounding complicates the process of combining models to form larger models unless all are grounded absolutely. Relational grounding facilitates referent knowledge embodiment within computational mechanisms but requires separate model-to-referent mappings. Absolute grounding can simplify integration by forcing common units and, hence, a common integration target, but context change may require model reengineering. Relational grounding enables synthesis of large, composite (multi-module) models that can be robust to context changes. Because biological components have varying degrees of autonomy, corresponding components in MSMs need to do the same. Relational grounding facilitates achieving such autonomy. Biomimetic analogues designed to facilitate translational research and development must have long lifecycles. Exploring mechanisms of normal-to-disease transition requires model components that are grounded relationally. Multi-paradigm modeling requires both hyperspatial and relational grounding

Integrated genome and transcriptome sequencing identifies a noncoding mutation in the genome replication factor DONSON as the cause of microcephaly-micromelia syndrome

While next-generation sequencing has accelerated the discovery of human disease genes, progress has been largely limited to the "low hanging fruit" of mutations with obvious exonic coding or canonical splice site impact. In contrast, the lack of high-throughput, unbiased approaches for functional assessment of most noncoding variants has bottlenecked gene discovery. We report the integration of transcriptome sequencing (RNA-seq), which surveys all mRNAs to reveal functional impacts of variants at the transcription level, into the gene discovery framework for a unique human disease, microcephaly-micromelia syndrome (MMS). MMS is an autosomal recessive condition described thus far in only a single First Nations population and causes intrauterine growth restriction, severe microcephaly, craniofacial anomalies, skeletal dysplasia, and neonatal lethality. Linkage analysis of affected families, including a very large pedigree, identified a single locus on Chromosome 21 linked to the disease (LOD > 9). Comprehensive genome sequencing did not reveal any pathogenic coding or canonical splicing mutations within the linkage region but identified several nonconserved noncoding variants. RNA-seq analysis detected aberrant splicing in DONSON due to one of these noncoding variants, showing a causative role for DONSON disruption in MMS. We show that DONSON is expressed in progenitor cells of embryonic human brain and other proliferating tissues, is co-expressed with components of the DNA replication machinery, and that Donson is essential for early embryonic development in mice as well, suggesting an essential conserved role for DONSON in the cell cycle. Our results demonstrate the utility of integrating transcriptomics into the study of human genetic disease when DNA sequencing alone is not sufficient to reveal the underlying pathogenic mutation

Kinetics of the hydrogen abstraction ·C2H5 + alkane → C2H6 + alkyl reaction class: an application of the reaction class transition state theory

This paper presents an application of the reaction class transition state theory (RC-TST) to predict thermal rate constants for hydrogen abstraction reactions at alkane by the C2H5 radical on-the-fly. The linear energy relationship (LER), developed for acyclic alkanes, was also proven to hold for cyclic alkanes. We have derived all RCTST parameters from rate constants of 19 representative reactions, coupling with LER and the barrier height grouping (BHG) approach. Both the RC-TST/LER, where only reaction energy is needed, and the RC-TST/BHG, where no other information is needed, can predict rate constants for any reaction in this reaction class with satisfactory accuracy for combustion modeling. Our analysis indicates that less than 50% systematic errors on the average exist in the predicted rate constants using either the RC-TST/LER or RC-TST/BHG method, while in comparison with explicit rate calculations, the differences are within a factor of 2 on the average. The results also show that the RC-TST method is not sensitive to the choice of density functional theory used

Effect of Virulence Factors on the Photodynamic Inactivation of Cryptococcus neoformans

Opportunistic fungal pathogens may cause an array of superficial infections or serious invasive infections, especially in immunocompromised patients. Cryptococcus neoformans is a pathogen causing cryptococcosis in HIV/AIDS patients, but treatment is limited due to the relative lack of potent antifungal agents. Photodynamic inactivation (PDI) uses the combination of non-toxic dyes called photosensitizers and harmless visible light, which produces singlet oxygen and other reactive oxygen species that produce cell inactivation and death. We report the use of five structurally unrelated photosensitizers (methylene blue, Rose Bengal, selenium derivative of a Nile blue dye, a cationic fullerene and a conjugate between poly-L-lysine and chlorin(e6)) combined with appropriate wavelengths of light to inactivate C. neoformans. Mutants lacking capsule and laccase, and culture conditions that favoured melanin production were used to probe the mechanisms of PDI and the effect of virulence factors. The presence of cell wall, laccase and melanin tended to protect against PDI, but the choice of the appropriate photosensitizers and dosimetry was able to overcome this resistance.Fundação de Amparo à Pesquisa do Estado de São Paulo (2010/13313–9