| 1. |
- Lin, HY, et al.
(author)
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KLK3 SNP-SNP interactions for prediction of prostate cancer aggressiveness
- 2021
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In: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 11:1, s. 9264-
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Journal article (peer-reviewed)abstract
- Risk classification for prostate cancer (PCa) aggressiveness and underlying mechanisms remain inadequate. Interactions between single nucleotide polymorphisms (SNPs) may provide a solution to fill these gaps. To identify SNP–SNP interactions in the four pathways (the angiogenesis-, mitochondria-, miRNA-, and androgen metabolism-related pathways) associated with PCa aggressiveness, we tested 8587 SNPs for 20,729 cases from the PCa consortium. We identified 3 KLK3 SNPs, and 1083 (P < 3.5 × 10–9) and 3145 (P < 1 × 10–5) SNP–SNP interaction pairs significantly associated with PCa aggressiveness. These SNP pairs associated with PCa aggressiveness were more significant than each of their constituent SNP individual effects. The majority (98.6%) of the 3145 pairs involved KLK3. The 3 most common gene–gene interactions were KLK3-COL4A1:COL4A2, KLK3-CDH13, and KLK3-TGFBR3. Predictions from the SNP interaction-based polygenic risk score based on 24 SNP pairs are promising. The prevalence of PCa aggressiveness was 49.8%, 21.9%, and 7.0% for the PCa cases from our cohort with the top 1%, middle 50%, and bottom 1% risk profiles. Potential biological functions of the identified KLK3 SNP–SNP interactions were supported by gene expression and protein–protein interaction results. Our findings suggest KLK3 SNP interactions may play an important role in PCa aggressiveness.
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| 2. |
- Mankar, Praful D., et al.
(author)
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A Spatio-temporal Analysis of Cellular-based IoT Networks under Heterogeneous Traffic
- 2021
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In: 2021 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM). - : IEEE. - 9781728181042
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Conference paper (peer-reviewed)abstract
- In this paper, we consider a cellular-based Internet of things (IoT) network consisting of IoT devices that can communicate directly with each other in a device-to-device (D2D) fashion as well as send real-time status updates about some underlying physical processes observed by them. We assume that such real-time applications are supported by cellular networks where cellular base stations (BSs) collect status updates over time from a subset of the IoT devices in their vicinity. We characterize two performance metrics: i) the network throughput which quantifies the performance of D2D communications, and ii) the Age of Information which quantifies the performance of the real-time IoT-enabled applications. Concrete analytical results are derived using stochastic geometry by modeling the locations of IoT devices as a bipolar Poisson Point Process (PPP) and that of the BSs as another Independent PPP. Our results provide useful design guidelines on the efficient deployment of future IoT networks that will jointly support D2D communications and several cellular network-enabled real-time applications.
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| 3. |
- Mankar, Praful D., et al.
(author)
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Throughput and Age of Information in a Cellular-Based IoT Network
- 2021
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In: IEEE Transactions on Wireless Communications. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 1536-1276 .- 1558-2248. ; 20:12, s. 8248-8263
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Journal article (peer-reviewed)abstract
- This paper studies the interplay between device-to-device (D2D) communications and real-time monitoring systems in a cellular-based Internet of Things (IoT) network. In particular, besides the possibility that the IoT devices communicate directly with each other in a D2D fashion, we consider that they frequently send time-sensitive information/status updates (about some underlying physical processes observed by them) to their nearest cellular base stations (BSs). Specifically, we model the locations of the IoT devices as a bipolar Poisson Point Process (PPP) and that of the BSs as another independent PPP. For this setup, we characterize the performance of D2D communications using the average network throughput metric whereas the performance of the real-time applications is quantified by the Age of Information (AoI) metric. The IoT devices are considered to employ a distance-proportional fractional power control scheme while sending status updates to their serving BSs. Hence, depending upon the maximum transmission power available, the IoT devices located within a certain distance from the BSs can only send status updates. This association strategy, in turn, forms the Johnson-Mehl (JM) tessellation, such that the IoT devices located in the JM cells are allowed to send status updates. The average network throughput is obtained by deriving the mean success probability for the D2D links. On the other hand, the temporal mean AoI of a given status update link can be treated as a random variable over space since its success delivery rate is a function of the interference field seen from its receiver. Thus, in order to capture the spatial disparity in the AoI performance, we characterize the spatial moments of the temporal mean AoI. In particular, we obtain these spatial moments by deriving the moments of both the conditional success probability and the conditional scheduling probability for status update links. Our results provide useful design guidelines on the efficient deployment of future massive IoT networks that will jointly support D2D communications and several cellular network-enabled real-time applications.
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| 4. |
- Paice, J. A., et al.
(author)
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The evolution of rapid optical/X-ray timing correlations in the initial hard state of MAXIJ1820+070
- 2021
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In: Monthly notices of the Royal Astronomical Society. - : Oxford University Press (OUP). - 0035-8711 .- 1365-2966. ; 505:3, s. 3452-3469
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Journal article (peer-reviewed)abstract
- We report on a multiepoch campaign of rapid optical/X-ray timing observations of the superbright 2018 outburst of MAXIJ1820+070, a black hole low-mass X-ray binary system. The observations spanned 80 d in the initial hard state and were taken with NTT/ULTRACAM and GTC/HiPERCAM in the optical (u(s)g(s)r(s)i(s)z(s) filters at time resolutions of 8-300Hz) and with ISS/NICER in X-rays. We find (i) a growing anticorrelation between the optical and X-ray light curves, (ii) a steady, positive correlation at an optical lag of similar to 0.2s (with a longer lag at longer wavelengths) present in all epochs, and (iii) a curious positive correlation at negative optical lags in the last, X-ray softest epoch, with longer wavelengths showing a greater correlation and a more negative lag. To explain these, we postulate the possible existence of two synchrotron-emitting components - a compact jet and a hot flow. In our model, the significance of the jet decreases over the outburst, while the hot flow remains static (thus, relatively, increasing in significance). We also discuss a previously discovered quasi-periodic oscillation and note how it creates coherent optical time lags, stronger at longer wavelengths, during at least two epochs.
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