450 research outputs found
Flexible availability-aware differentiated protection in software-defined elastic optical networks
No full textMinority Groups In Northern Laos
No full textA report on the minority groups in Northern Laos, with a focus on the Yao.A condensation of the article that originally appeared in Shilin. No . 1 , 196
Courtesans and soldier's wives: an analysis of three cases in the Qingming ji 清明集
No full textIn this article the author discusses three lawsuits in the Ming gong shu pan qingming ji 名公書判清明集 (“Collection of Enlightened Judgements”) which concern the punishment of women, either by registration as a government-courtesan or by being forced to become a soldier’s wife
Reply to: "A global survey of alternative splicing of HBV transcriptome using long-read sequencing" (Letter)
No full textWe read with delight and great interest the latest work by Professors Chen, Lu and their colleagues that confirmed some of the major findings reported in our recently published article, in which multiomics approaches were applied to study HBV-host interactions.1,2 Specifically, through the use of a third-generation sequencing (Iso-seq) technique that enabled the direct sequencing of long transcripts, the authors not only identified known HBV transcripts, but also discovered many previously under-characterized splicing products of HBV RNAs. Among them, of particular interest were the isoforms that resulted from RNA splicing events, A2,446T2,447/G489 and A2,446T2,447/T2,902, which were found to account for 7.3% and 3.5%, respectively, of all the spliced HBV RNA transcripts. These newly obtained data1,3,4 had thus directly substantiated the existence of the major RNA splicing events and products, based on which we showed that the translated products, HBxZ and HpZ, restricted HBV gene expression and replication, and likely contributed to the self-restrictive nature of HBV infection.2 While highlighting the fruitfulness of embracing and applying more novel techniques to investigate HBV-host interactions, these discoveries have unequivocally proven the extra coding potential of the HBV genome, which was under-appreciated.No Full Tex
Abstract 4375: Complex interactions between genomic and epigenomic alterations in esophageal adenocarcinomas
No full textAbstract
Background: The incidence of Barrett’s-related esophageal adenocarcinoma (EAC) is rapidly rising in the USA and the Western countries. However, the interaction between genomic and epigenomic alterations in regulating gene expression networks in EAC is poorly understood.
Results and Discussion: We carried out an integrative analytical approach to identify DNA copy number, promoter DNA methylation and gene expression in a panel of esophageal adenocarcinomas, using chip-based technologies. Our analysis displayed significant differences between EAC and normal samples in DNA copy numbers, gene expression, and DNA methylation profiles. Our results identified remarkable incidence of DNA copy number (CN) alterations showing that 90% of probes had a copy number aberration (gain or loss) in at least one tumor, suggesting a vast chromosomal instability in EAC. Integrative analysis indicated that altered expression of 1755 genes was associated with changes in CN or methylation. We found that expression alterations in 84 genes (56 overexpressed and 28 down regulated) were associated with changes in both CN and methylation. These data suggest a strong interaction between genetic and epigenetic events to modulate gene expression in EAC. Of note, we detected a prominent K-RAS signature in EAC. Network analysis predicted activation of several important transcription factor networks in EAC, including β-catenin, MYB, TWIST1, SOX7, GATA3 and GATA6. 56 genes were overexpressed in EAC with simultaneous promoter hypomethylation and gene amplification, including CDH17 and GATA6. Notably, several genes associated with inflammation such as COX2, IL8 and IL23R were overexpressed and hypomethylated in EAC, a reaffirmation of the underlying inflammatory process in Barrett’s tumorigenesis and a suggestion of an epigenetic regulation of these genes.
Conclusions: In summary, our integrative analysis of genetic and epigenetic alterations in EAC demonstrates a complex interaction between molecular mechanisms in EAC and provides several novel insights for future studies.
Citation Format: Dunfa Peng, Yan Guo, Heidi Chen, Shilin Zhao, Kay Washington, Tianling Hu, Yu Shyr, Wael El-Rafai. Complex interactions between genomic and epigenomic alterations in esophageal adenocarcinomas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4375. doi:10.1158/1538-7445.AM2017-4375</jats:p
Y-chromosome O3 Haplogroup diversity in Sino-Tibetan populations reveals two migration routes into the Eastern Himalayas
No full textChristina J. Adler, Alan Cooper, Clio S.I. Der Sarkissian and Wolfgang Haak are contributors to the Genographic ConsortiumThe eastern Himalayas are located near the southern entrance through which early modern humans expanded into East Asia. The genetic structure in this region is therefore of great importance in the study of East Asian origins. However, few genetic studies have been performed on the Sino-Tibetan populations (Luoba and Deng) in this region. Here, we analyzed the Y-chromosome diversity of the two populations. The Luoba possessed haplogroups D, N, O, J, Q, and R, indicating gene flow from Tibetans, as well as the western and northern Eurasians. The Deng exhibited haplogroups O, D, N, and C, similar to most Sino-Tibetan populations in the east. Short tandem repeat (STR) diversity within the dominant haplogroup O3 in Sino-Tibetan populations showed that the Luoba are genetically close to Tibetans and the Deng are close to the Qiang. The Qiang had the greatest diversity of Sino-Tibetan populations, supporting the view of this population being the oldest in the family. The lowest diversity occurred in the eastern Himalayas, suggesting that this area was an endpoint for the expansion of Sino-Tibetan people. Thus, we have shown that populations with haplogroup O3 moved into the eastern Himalayas through at least two routes.Longli Kang, Yan Lu, Chuanchao Wang, Kang Hu, Feng Chen, Kai Liu, Shilin Li, Li Jin, Hui Li and The Genographic Consortiu
Deep learning-based super-resolution US radiomics to differentiate testicular seminoma and non-seminoma: an international multicenter study
No full textObjectives: Subvariants of testicular germ cell tumor (TGCT) significantly affect therapeutic strategies and patient prognosis. However, preoperatively distinguishing seminoma (SE) from non-seminoma (n-SE) remains a challenge. This study aimed to evaluate the performance of a deep learning-based super-resolution (SR) US radiomics model for SE/n-SE differentiation. Materials and methods: This international multicenter retrospective study recruited patients with confirmed TGCT between 2015 and 2023. A pre-trained SR reconstruction algorithm was applied to enhance native resolution (NR) images. NR and SR radiomics models were constructed, and the superior model was then integrated with clinical features to construct clinical-radiomics models. Diagnostic performance was evaluated by ROC analysis (AUC) and compared with radiologists’ assessments using the DeLong test. Results: A total of 486 male patients were enrolled for training (n = 338), domestic (n = 92), and international (n = 59) validation sets. The SR radiomics model achieved AUCs of 0.90, 0.82, and 0.91, respectively, in the training, domestic, and international validation sets, significantly surpassing the NR model (p < 0.001, p = 0.031, and p = 0.001, respectively). The clinical-radiomics model exhibited a significantly higher across both domestic and international validation sets compared to the SR radiomics model alone (0.95 vs 0.82, p = 0.004; 0.97 vs 0.91, p = 0.031). Moreover, the clinical-radiomics model surpassed the performance of experienced radiologists in both domestic (AUC, 0.95 vs 0.85, p = 0.012) and international (AUC, 0.97 vs 0.77, p < 0.001) validation cohorts. Conclusions: The SR-based clinical-radiomics model can effectively differentiate between SE and n-SE. Critical relevance statement: This international multicenter study demonstrated that a radiomics model of deep learning-based SR reconstructed US images enabled effective differentiation between SE and n-SE. Key Points: Clinical parameters and radiologists’ assessments exhibit limited diagnostic accuracy for SE/n-SE differentiation in TGCT. Based on scrotal US images of TGCT, the SR radiomics models performed better than the NR radiomics models. The SR-based clinical-radiomics model outperforms both the radiomics model and radiologists’ assessment, enabling accurate, non-invasive preoperative differentiation between SE and n-SE
Quantitative identification of different strong-field ionization channels in the transition regime
No full textWe make a quantitative investigation on the tunneling and multi-photon channels in the transition regime from Keldysh parameter. gamma < 1 to gamma > 1 by numerically solving the time-dependent Schrodinger equation (TDSE). A method is proposed to separate the contributions of those ionization channels based on the characteristics of the current. By analysing the dependence of the ionization rate on the Keldysh parameter., we identify a field independent transition point at gamma approximate to 2, which is different from the well-accepted consensus of gamma approximate to 1, from adiabatic to nonadiabatic regime. (C) 2016 Optical Society of AmericaNational Key program for ST Research and Development [2016YFA0401100]; National Basic Research Program of China Grant [2013CB922201]; National Natural Science Foundation (NSFC) [11274050, 11334009, 11425414, 11374197, 11447114, 11504215]SCI(E)[email protected]
EdgeTuner: Fast Scheduling Algorithm Tuning for Dynamic Edge-Cloud Workloads and Resources
No full textEdge-cloud jobs are rapidly prevailing in many application domains, posing the challenge of using both resource-strenuous edge devices and elastic cloud resources. Efficient resource allocation on such jobs via scheduling algorithms is essential to guarantee their performance, e.g. latency. Deep reinforcement learning (DRL) is increasingly adopted to make scheduling decisions but faces the conundrum of achieving high rewards at a low training overhead. It is unknown if such a DRL can be applied to timely tune the scheduling algorithms that are adopted in response to fast changing workloads and resources. In this paper, we propose EdgeTuner to effectively leverage DRL to select scheduling algorithms online for edge-cloud jobs. The enabling features of EdgeTuner are sophisticated DRL model that captures complex dynamics of Edge-Cloud jobs/tasks and an effective simulator to emulate the response times of short-running jobs in accordance to dynamically changing scheduling algorithms. EdgeTuner trains DRL agents offline by directly interacting with the simulator. We implement EdgeTuner on Kubernetes scheduler and extensively evaluate it on Kubernetes cluster testbed driven by the production traces. Our results show that EdgeTuner outperforms prevailing scheduling algorithms by achieving significant lower job response time while accelerating DRL training speed by more than 180x.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Data-Intensive System
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