Results 81 to 90 of about 424,943 (312)

Scalable Univariate and Multivariate Time-Series Classifiers with Deep Learning Methods Exploiting Symbolic Representations

Computers
Time-series classification (TSC) is an important task across sciences. Symbolic representations (especially SFA) are very effective at combating noise. In this paper, we employ symbolic representations to create state-of-the-art time-series classifiers ...
Apostolos Glenis, George Vouros
doaj   +1 more source

Plecstatin inhibits hepatocellular carcinoma tumorigenesis and invasion through cytolinker plectin

Molecular Oncology, EarlyView.
The ruthenium‐based metallodrug plecstatin exerts its anticancer effect in hepatocellular carcinoma (HCC) primarily through selective targeting of plectin. By disrupting plectin‐mediated cytoskeletal organization, plecstatin inhibits anchorage‐dependent growth, cell polarization, and tumor cell dissemination.
Zuzana Outla, Jan Kosla, Magdalena Prechova, Lukas Frick, Patricia Bortel, Yasmin Borutzki, Andrea Bileck, Christopher Gerner, Samuel M. Meier‐Menches, Selma Osmanagic‐Myers, Martin Gregor   +10 more
wiley   +1 more source

MCPL-Based FT-LSTM: Medical Representation Learning-Based Clinical Prediction Model for Time Series Events

IEEE Access, 2019
Large collections of electronic medical records (EMRs) provide us with a vast source of information on medical practice. However, the utilization of these data to support clinical decisions is still limited.
Lutong Wang, Hong Wang, Yongqiang Song, Qian Wang   +3 more
doaj   +1 more source

Therapeutic strategies for MMAE‐resistant bladder cancer through DPP4 inhibition

Molecular Oncology, EarlyView.
We established monomethyl auristatin E (MMAE)‐resistant bladder cancer (BC) cell lines by exposure to progressively increasing concentrations of MMAE in vitro. RNA sequencing showed DPP4 expression was increased in MMAE‐resistant BC cells. Both si‐DPP4 and the DPP4 inhibitor sitagliptin suppressed the viability of MMAE‐resistant BC cells.
Gang Li, Shuichi Tatarano, Hirofumi Yoshino, Saeki Saito, Mitsuhiko Tominaga, Junya Arima, Ikumi Fukuda, Takashi Sakaguchi, Ryosuke Matsushita, Yasutoshi Yamada, Hideki Enokida   +10 more
wiley   +1 more source

Crucial parameters for precise copy number variation detection in formalin‐fixed paraffin‐embedded solid cancer samples

Molecular Oncology, EarlyView.
This study shows that copy number variations (CNVs) can be reliably detected in formalin‐fixed paraffin‐embedded (FFPE) solid cancer samples using ultra‐low‐pass whole‐genome sequencing, provided that key (pre)‐analytical parameters are optimized.
Hanne Goris, Vasiliki Siozopoulou, Léon C van Kempen, Anne Sieben, Ella Roelant, Stig Hellemans, Elyne Backx, Laure Sorber, Koen De Winne, Senada Koljenović, Karen Zwaenepoel   +10 more
wiley   +1 more source

Combining antibody conjugates with cytotoxic and immune‐stimulating payloads maximizes anti‐cancer activity

Molecular Oncology, EarlyView.
Methods to improve antibody–drug conjugate (ADC) treatment durability in cancer therapy are needed. We utilized ADCs and immune‐stimulating antibody conjugates (ISACs), which are made from two non‐competitive antibodies, to enhance the entry of toxic payloads into cancer cells and deliver immunostimulatory agents into immune cells.
Tiexin Wang, Dong Jun Koo, Peter M. Tessier, Greg M. Thurber   +3 more
wiley   +1 more source

Representation learning for clinical time series prediction tasks in electronic health records

BMC Medical Informatics and Decision Making, 2019
Background Electronic health records (EHRs) provide possibilities to improve patient care and facilitate clinical research. However, there are many challenges faced by the applications of EHRs, such as temporality, high dimensionality, sparseness, noise,
Tong Ruan, Liqi Lei, Yangming Zhou, Jie Zhai, Le Zhang, Ping He, Ju Gao   +6 more
doaj   +1 more source

Time-Series Representation Learning in Topology Prediction for Passive Optical Network of Telecom Operators. [PDF]

Sensors (Basel), 2023
Zhao H, Fang Y, Zhao Y, Tian Z, Zhang W, Feng X, Yu L, Li W, Fan H, Mu T.   +9 more
europepmc   +1 more source

TRAIL‐PEG‐Apt‐PLGA nanosystem as an aptamer‐targeted drug delivery system potential for triple‐negative breast cancer therapy using in vivo mouse model

Molecular Oncology, EarlyView.
Aptamers are used both therapeutically and as targeting agents in cancer treatment. We developed an aptamer‐targeted PLGA–TRAIL nanosystem that exhibited superior therapeutic efficacy in NOD/SCID breast cancer models. This nanosystem represents a novel biotechnological drug candidate for suppressing resistance development in breast cancer.
Gulen Melike Demirbolat, Aslihan Kucuk, Omer Erdogan, Samed Ozer, Bensu Kozan, Tugba Cuceli, Erkan Gumus, Evrim Cevik, Ozge Cevik   +8 more
wiley   +1 more source

Correlation of the differential expression of PIK3R1 and its spliced variant, p55α, in pan‐cancer

Molecular Oncology, EarlyView.
PIK3R1 undergoes alternative splicing to generate the isoforms, p85α and p55α. By combining large patient datasets with laboratory experiments, we show that PIK3R1 spliced variants shape cancer behavior. While tumors lose the protective p85α isoform, p55α is overexpressed, changes linked to poorer survival and more pronounced in African American ...
Ishita Gupta, Yang Song, Madeleine Ndahayo, Anirudh Saxena, Theresa Guo, Dylan Z. Kelley, Jessica Gore, Andrew Hennigan, Alexa Anderson, John C. Papadimitriou, Daria A. Gaykalova   +10 more
wiley   +1 more source