Results 161 to 170 of about 1,138 (212)

Circulating microRNA signatures of cachexia and cancer in Canis familiaris as a comparative oncology model for human disease

Molecular Oncology, EarlyView.
Circulating microRNAs as biomarkers of cachexia and sex‐specific cancer in senior dogs. In 25 client‐owned dogs, four circulating miRNAs (miR‐15a, miR‐15b, miR‐16, miR‐140) were downregulated in cachexia, with miR‐16 the strongest individual biomarker (AUC = 0.899).
Soon‐Seok Park, Kyongman An, Gyeonghwa Kim, Soo‐Nyun Choi, Hong‐Ki Lee, Keun Hur, Kyu‐Shik Jeong   +6 more
wiley   +1 more source

Preoperative circulating tumor cells integrated with imaging analysis for prognostic evaluation in head and neck squamous cell carcinoma

Molecular Oncology, EarlyView.
Detecting circulating tumor cells (CTCs) in blood before surgery may help predict outcomes in patients with head and neck squamous cell carcinoma (HNSCC). Here, we show when combined with tumor size and lymph node involvement from routine imaging, CTC status identifies high‐risk patients with poorer survival—offering a simple, minimally invasive tool ...
Susanne Flach, Gizem Abaci, Tom Huberty, Axel Lechner, Lukas Käsmann, Jens Ricke, Sophia Stöcklein, Martin Canis, Philipp Baumeister, Marianna Alunni‐Fabbroni   +9 more
wiley   +1 more source

Epigenetic silencing of the liver‐specific lncRNA LUNAR promotes liver cancer progression via NOTCH activation

Molecular Oncology, EarlyView.
LUNAR is a liver‐specific long noncoding RNA (lncRNA) that is highly expressed in normal liver but becomes epigenetically silenced in hepatocellular carcinoma through promoter hypermethylation. Loss of LUNAR is associated with NOTCH activation, epithelial–mesenchymal transition, and metastasis, whereas restoring LUNAR restrains metastatic progression ...
Se Ha Jang, Hyung Seok Kim, Geum Ok Baek, Moon Gyeong Yoon, Su In Lee, Jee‐Yeong Jeong, Ji Eun Han, Soon Sun Kim, Jae Youn Cheong, Jung Woo Eun   +9 more
wiley   +1 more source

Translating whole‐genome doubling into precision medicine in cancer

Molecular Oncology, EarlyView.
Whole‐genome doubling creates a WGD‐positive tumor state characterized by persistent chromosomal instability, karyotypic diversification, and cellular stress. These same biological pressures drive aggressive tumor evolution while exposing therapeutic vulnerabilities, providing a rationale for WGD‐informed precision medicine. Whole‐genome doubling (WGD)
Sejung Lee, Junghyeok Lim, Jinhyuk Bhin
wiley   +1 more source

Single‐cell DNA methylation profiling: Technologies, computation, and applications in precision oncology

Molecular Oncology, EarlyView.
Single‐cell DNA methylation (scDNAme) profiling maps epimutational clonal evolution, revealing mechanisms of malignancy and therapeutic resistance across diverse cancer types. By providing a high‐resolution landscape of intratumoral heterogeneity, these technologies empower precise patient stratification, guide the development of enhanced ...
Ik Soo Kim
wiley   +1 more source

Interferon beta drives therapy resistance in a patient‐derived model of high‐grade serous ovarian cancer

Molecular Oncology, EarlyView.
Interferon type 1 (IFN‐1) production and signaling is associated with the acquisition of therapy resistance, following chronic DNA damage, via Interferon‐related DNA damage resistance signature (IRDS) gene expression. An alternative, DNA damage‐independent role of sustained IFN‐1 mediated resistance was identified and characterized by the emergence of ...
Ashlyn Conant, Tise Suzuki, Kiera McGivney, V. S. S. Abhinav Ayyadevara, Sharon Asariah, Jay Deng, Ethan Nyein, Jacqueline Coats, Gary Yu, Yevgeniya J. Ioffe, Christian Hurtz, Juli J. Unternaehrer   +11 more
wiley   +1 more source

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Perfect sampling: a review and applications to signal processing

IEEE Transactions on Signal Processing, 2002
Markov chain Monte Carlo (MCMC) sampling methods have gained much popularity among researchers in signal processing. The Gibbs and the Metropolis-Hastings (1954, 1970) algorithms, which are the two most popular MCMC methods, have already been employed in resolving a wide variety of signal processing problems.
P M Djuric
exaly   +2 more sources

Parallel Graph Signal Processing: Sampling and Reconstruction

IEEE Transactions on Signal and Information Processing Over Networks, 2023
Gonzalo Arce, Daniel Lau, Maria Daniela Dapena Rivero   +2 more
exaly   +2 more sources

Sampling and processing of color signals

IEEE Transactions on Image Processing, 1996
Digital signal processing tools are used to determine the proper sampling of color spectra and the effect of sampling on the accuracy of derived properties such as CIE tristimulus values and color rendering indexes. It is found that 10 nm sampling is adequate for most applications, but not for more exacting textile and paint matching applications ...
H. Joel Trussell, Manish S. Kulkarni
openaire   +2 more sources

Compressed Signal Processing on Nyquist-Sampled Signals

IEEE Transactions on Computers, 2016
Pattern-recognition algorithms from the domain of machine learning play a prominent role in embedded sensing systems, in order to derive inferences from sensor data. Very often, such systems face severe energy constraints. The focus of this work is to mitigate the computational energy by exploiting a form of compression which preserves a similarity ...
Jie Lu, Naveen Verma, Niraj K. Jha
openaire   +1 more source