Optimized Precoders for Vehicular Massive MIMO RadCom Systems

This paper proposes optimized precoders for dual-functional radar and communication (RadCom) systems to maximize the sum-rate (SR) while satisfying radar target detection and user data rate constraints towards 6G networks. For this purpose, a RadCom precoder scheme that exploits radar interference is utilized with massive multiple-input-multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems. Firstly, the communication capacity and radar detection performance metrics are analytically derived. Then, optimum precoders that utilize these analytical expressions are designed via convex optimization to maximize the SR with modest computational complexity. The analytical results are also verified by simulations. The results show that the optimized precoder can substantially enhance the SR compared to the benchmark methods

A Dual-Function Massive MIMO Uplink OFDM Communication and Radar Architecture

This paper proposes a joint uplink massive multiple-input-multiple-output (MIMO) communication and orthogonal frequency-division multiplexing (OFDM) radar sensing architecture. Specifically, uplink communication and short-range radar sensing are considered, where the user equipments (UEs) transmit data to the base-station (BS), which simultaneously receives radar returns from the targets over the same subcarriers. Hence, the signals received at each BS antenna include radar returns and communication signals to be processed for extracting the sensing and communication data. The separation and detection of such signals are achieved by utilizing the channel diversity between the UEs and the targets. To this end, the UEs' signals are first detected and demodulated, and then subtracted from the received signal to acquire the radar returns. Symbol-based radar processing is then employed, as it provides substantial processing gains, and its detection performance is independent of the transmitted radar waveform. Furthermore, self-interference - due to the simultaneous operation of transmit and receive antennas - is taken into account. The communication rate and normalized error of the radar-target channel estimation are mathematically analyzed, and the trade-off between the achievable rate and radar detection performance is demonstrated in terms of the output power of the communication and radar sub-systems and the signal-to-noise ratio

The somatic autosomal mutation matrix in cancer genomes

DNA damage in somatic cells originates from both environmental and endogenous sources, giving rise to mutations through multiple mechanisms. When these mutations affect the function of critical genes, cancer may ensue. Although identifying genomic subsets of mutated genes may inform therapeutic options, a systematic survey of tumor mutational spectra is required to improve our understanding of the underlying mechanisms of mutagenesis involved in cancer etiology. Recent studies have presented genome-wide sets of somatic mutations as a 96-element vector, a procedure that only captures the immediate neighbors of the mutated nucleotide. Herein, we present a 32 × 12 mutation matrix that captures the nucleotide pattern two nucleotides upstream and downstream of the mutation. A somatic autosomal mutation matrix (SAMM) was constructed from tumor-specific mutations derived from each of 909 individual cancer genomes harboring a total of 10,681,843 single-base substitutions. In addition, mechanistic template mutation matrices (MTMMs) representing oxidative DNA damage, ultraviolet-induced DNA damage, 5mCpG deamination, and APOBEC-mediated cytosine mutation, are presented. MTMMs were mapped to the individual tumor SAMMs to determine the maximum contribution of each mutational mechanism to the overall mutation pattern. A Manhattan distance across all SAMM elements between any two tumor genomes was used to determine their relative distance. Employing this metric, 89.5 % of all tumor genomes were found to have a nearest neighbor from the same tissue of origin. When a distance-dependent 6-nearest neighbor classifier was used, 86.9 % of all SAMMs were assigned to the correct tissue of origin. Thus, although tumors from different tissues may have similar mutation patterns, their SAMMs often display signatures that are characteristic of specific tissues

Identifying allosteric fluctuation transitions between different protein conformational states as applied to Cyclin Dependent Kinase 2

BACKGROUND: The mechanisms underlying protein function and associated conformational change are dominated by a series of local entropy fluctuations affecting the global structure yet are mediated by only a few key residues. Transitional Dynamic Analysis (TDA) is a new method to detect these changes in local protein flexibility between different conformations arising from, for example, ligand binding. Additionally, Positional Impact Vertex for Entropy Transfer (PIVET) uses TDA to identify important residue contact changes that have a large impact on global fluctuation. We demonstrate the utility of these methods for Cyclin-dependent kinase 2 (CDK2), a system with crystal structures of this protein in multiple functionally relevant conformations and experimental data revealing the importance of local fluctuation changes for protein function. RESULTS: TDA and PIVET successfully identified select residues that are responsible for conformation specific regional fluctuation in the activation cycle of Cyclin Dependent Kinase 2 (CDK2). The detected local changes in protein flexibility have been experimentally confirmed to be essential for the regulation and function of the kinase. The methodologies also highlighted possible errors in previous molecular dynamic simulations that need to be resolved in order to understand this key player in cell cycle regulation. Finally, the use of entropy compensation as a possible allosteric mechanism for protein function is reported for CDK2. CONCLUSION: The methodologies embodied in TDA and PIVET provide a quick approach to identify local fluctuation change important for protein function and residue contacts that contributes to these changes. Further, these approaches can be used to check for possible errors in protein dynamic simulations and have the potential to facilitate a better understanding of the contribution of entropy to protein allostery and function

Overweight status is associated with extensive signs of microvascular dysfunction and cardiovascular risk

The aim of this present study was to investigate if overweight individuals exhibit signs of vascular dysfunction associated with a high risk for cardiovascular disease (CVD). One hundred lean and 100 overweight participants were recruited for the present study. Retinal microvascular function was assessed using the Dynamic Retinal Vessel Analyser (DVA), and systemic macrovascular function by means of flow-mediated dilation (FMD). Investigations also included body composition, carotid intimal-media thickness (c-IMT), ambulatory blood pressure monitoring (BP), fasting plasma glucose, triglycerides (TG), cholesterol levels (HDL-C and LDL-C), and plasma von Willebrand factor (vWF). Overweight individuals presented with higher right and left c-IMT (p = 0.005 and p = 0.002, respectively), average 24-h BP values (all p <0.001), plasma glucose (p = 0.008), TG (p = 0.003), TG: HDL-C ratio (p = 0.010), and vWF levels (p = 0.004). Moreover, overweight individuals showed lower retinal arterial microvascular dilation (p = 0.039) and baseline-corrected flicker (bFR) responses (p = 0.022), as well as, prolonged dilation reaction time (RT, p = 0.047). These observations emphasise the importance of vascular screening and consideration of preventive interventions to decrease vascular risk in all individuals with adiposity above normal range

Guanine Holes Are Prominent Targets for Mutation in Cancer and Inherited Disease

Albino Bacolla, Guliang Wang, Aklank Jain, Karen M. Vasquez, Division of Pharmacology and Toxicology, The University of Texas at Austin, Dell Pediatric Research Institute, Austin, Texas, United States of AmericaAlbino Bacolla, Nuri A. Temiz, Ming Yi, Joseph Ivanic, Regina Z. Cer, Duncan E. Donohue, Uma S. Mudunuri, Natalia Volfovsky, Brian T. Luke, Robert M., Stephens, Jack R. Collins, Advanced Biomedical Computing Center, SAIC-Frederick, Inc., Frederick National Laboratory for Cancer Research, Frederick, Maryland, United States of AmericaEdward V. Ball, David N. Cooper, Institute of Medical Genetics, School of Medicine, Cardiff University, Cardiff, United KingdomSingle base substitutions constitute the most frequent type of human gene mutation and are a leading cause of cancer and inherited disease. These alterations occur non-randomly in DNA, being strongly influenced by the local nucleotide sequence context. However, the molecular mechanisms underlying such sequence context-dependent mutagenesis are not fully understood. Using bioinformatics, computational and molecular modeling analyses, we have determined the frequencies of mutation at G•C bp in the context of all 64 5′-NGNN-3′ motifs that contain the mutation at the second position. Twenty-four datasets were employed, comprising >530,000 somatic single base substitutions from 21 cancer genomes, >77,000 germline single-base substitutions causing or associated with human inherited disease and 16.7 million benign germline single-nucleotide variants. In several cancer types, the number of mutated motifs correlated both with the free energies of base stacking and the energies required for abstracting an electron from the target guanines (ionization potentials). Similar correlations were also evident for the pathological missense and nonsense germline mutations, but only when the target guanines were located on the non-transcribed DNA strand. Likewise, pathogenic splicing mutations predominantly affected positions in which a purine was located on the non-transcribed DNA strand. Novel candidate driver mutations and tissue-specific mutational patterns were also identified in the cancer datasets. We conclude that electron transfer reactions within the DNA molecule contribute to sequence context-dependent mutagenesis, involving both somatic driver and passenger mutations in cancer, as well as germline alterations causing or associated with inherited disease.This work was supported by grants from the NIH (CA097175 and CA093729) to KMV, NCI/NIH contract HHSN261200800001E to AB and the Frederick National Laboratory for Cancer Research, and CBIIT/caBIG ISRCE yellow task #09-260 to the Frederick National Laboratory for Cancer Research. DNC and EVB received financial support from BIOBASE GmbH through a license agreement (for HGMD) with Cardiff University. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.PharmacyEmail: [email protected]

The Role of Methylation in the Intrinsic Dynamics of B- and Z-DNA

Methylation of cytosine at the 5-carbon position (5mC) is observed in both prokaryotes and eukaryotes. In humans, DNA methylation at CpG sites plays an important role in gene regulation and has been implicated in development, gene silencing, and cancer. In addition, the CpG dinucleotide is a known hot spot for pathologic mutations genome-wide. CpG tracts may adopt left-handed Z-DNA conformations, which have also been implicated in gene regulation and genomic instability. Methylation facilitates this B-Z transition but the underlying mechanism remains unclear. Herein, four structural models of the dinucleotide d(GC)5 repeat sequence in B-, methylated B-, Z-, and methylated Z-DNA forms were constructed and an aggregate 100 nanoseconds of molecular dynamics simulations in explicit solvent under physiological conditions was performed for each model. Both unmethylated and methylated B-DNA were found to be more flexible than Z-DNA. However, methylation significantly destabilized the BII, relative to the BI, state through the Gp5mC steps. In addition, methylation decreased the free energy difference between B- and Z-DNA. Comparisons of α/γ backbone torsional angles showed that torsional states changed marginally upon methylation for B-DNA, and Z-DNA. Methylation-induced conformational changes and lower energy differences may contribute to the transition to Z-DNA by methylated, over unmethylated, B-DNA and may be a contributing factor to biological function

The Polyamine Inhibitor Alpha-Difluoromethylornithine Modulates Hippocampus-Dependent Function after Single and Combined Injuries

Exposure to uncontrolled irradiation in a radiologic terrorism scenario, a natural disaster or a nuclear battlefield, will likely be concomitantly superimposed on other types of injury, such as trauma. In the central nervous system, radiation combined injury (RCI) involving irradiation and traumatic brain injury may have a multifaceted character. This may entail cellular and molecular changes that are associated with cognitive performance, including changes in neurogenesis and the expression of the plasticity-related immediate early gene Arc. Because traumatic stimuli initiate a characteristic early increase in polyamine metabolism, we hypothesized that treatment with the polyamine inhibitor alpha-difluoromethylornithine (DFMO) would reduce the adverse effects of single or combined injury on hippocampus structure and function. Hippocampal dependent cognitive impairments were quantified with the Morris water maze and showed that DFMO effectively reversed cognitive impairments after all injuries, particularly traumatic brain injury. Similar results were seen with respect to the expression of Arc protein, but not neurogenesis. Given that polyamines have been found to modulate inflammatory responses in the brain we also assessed the numbers of total and newly born activated microglia, and found reduced numbers of newly born cells. While the mechanisms responsible for the improvement in cognition after DFMO treatment are not yet clear, the present study provides new and compelling data regarding the potential use of DFMO as a potential countermeasure against the adverse effects of single or combined injury