Results 161 to 170 of about 59,286 (281)

Machine learning‐driven investigation on liquid–liquid phase separation‐related prognostic signature in diffuse large B‐cell lymphoma

British Journal of Haematology, EarlyView.
Summary Diffuse large B‐cell lymphoma (DLBCL) is the most common aggressive non‐Hodgkin lymphoma and is characterized by substantial heterogeneity. This study aimed to develop a liquid–liquid phase separation (LLPS)‐related prognostic model to improve risk stratification.
Zhen‐Zhong Zhou, Jia‐Chen Lu, Zhao Wang, Rong‐Hui Chen, Hai‐Long Li, Wan‐Ting Chen, Yu‐Ning Deng, Hui‐Juan Zhang, Yu Wang, Xuan‐Ye Zhang, Wei‐Juan Huang, Xiao‐Peng Tian   +11 more
wiley   +1 more source

Chromosomal microarray analysis for the prenatal diagnosis in fetuses with fetal echogenic bowel: a retrospective cohort study. [PDF]

BMC Pregnancy Childbirth
Wu W, Tian M, Liu M, Man D, Wang F.
europepmc   +1 more source

Molecular and clinical features of a Japanese medulloblastoma cohort: Subgroup‐specific prognostic stratification using economical/accessible diagnostic methods

Brain Pathology, EarlyView.
This study characterizes the molecular subgroup–specific features of a nationwide Japanese cohort comprising 242 medulloblastomas (MBs). Furthermore, we introduce SEE‐6‐CNA, a simple, cost‐effective, and FFPE‐compatible molecular test that is applicable to routine pathology samples and serves as a surrogate for risk stratification in non‐WNT/non‐SHH ...
Kohichi Go, Asako Katsuma, Ema Yoshioka, Tomoko Shofuda, Kohei Fukuoka, Koichi Ichimura, Yuko Matsushita, Yohei Mineharu, Yasuhide Makino, Takeshi Kawauchi, Atsushi Sasaki, Junko Hirato, Takeshi Inoue, Yoshinori Kodama, Masayuki Mano, Daisuke Kanematsu, Noriyuki Kijima, Naoki Kagawa, Dai Keino, Akitake Mukasa, Tomonari Suzuki, Koji Yoshimoto, Daisuke Kuga, Keishi Horiguchi, Shigeru Yamaguchi, Masayuki Kanamori, Kai Yamasaki, Kenichi Ishibashi, Takuya Akai, Masayoshi Yamaoka, Ryuji Ishizaki, Atsufumi Kawamura, Shigeo Ohba, Joji Ishida, Ryo Ando, Junya Fukai, Tomoru Miwa, Masazumi Fujii, Ai Muroi, Kuniaki Saito, Atsuko Harada, Yasuhiko Hayashi, Masahiro Nonaka, Young‐Soo Park, Yusuke Kobayashi, Tadashi Higuchi, Yosuke Miyairi, Kazuhisa Yoshifuji, Noriyoshi Takebe, Soichi Oya, Kosuke Nakajo, Mitsutoshi Nakada, Yoshiteru Nakano, Mizuki Kambara, Koji Adachi, Kazuhiro Tanaka, Hideo Nakamura, Yukihiko Sonoda, Ryuta Saito, Takafumi Wataya, Kazuhiko Kurozumi, Michael D. Taylor, Yoshitaka Narita, Soichiro Shibui, Hajime Arai, Hiroaki Sakamoto, Isao Date, Motoo Nagane, Ryo Nishikawa, Yoshiki Arakawa, Yonehiro Kanemura   +70 more
wiley   +1 more source

Clinical significance of regions of homozygosity detection in prenatal chromosomal microarray analysis. [PDF]

HGG Adv
Hao Y, Geng Q, Li X, Yang J, Liu Y, Huang Q, Xu Y, Li P, Xie J, Wu W, Wu B, Liu W.   +11 more
europepmc   +1 more source

Reproductive outcomes in couples with sporadic miscarriage after embryonic chromosomal microarray analysis. [PDF]

Ann Med, 2023
Xia Z, Zhou R, Li Y, Meng L, Huang M, Tan J, Qiao F, Zhu H, Hu P, Zhu Q, Xu Z, Wang Y.   +11 more
europepmc   +1 more source

Chromosomal and immune dysregulation underlying granular mitosis in glioblastoma

Brain Pathology, EarlyView.
Granular mitosis (GM) morphology is linked to PI3K/PTEN pathway alterations, chromosomal disorganization, and impaired innate immunity. Cells exhibiting GM morphology are associated with localized immune responses within their immediate spatial microenvironment.
Rachel Barboza, Xuan Wang, August Lin, Eric Liu, Pramath Kakodkar, Yayuan Zhao, Quinn Le, Christina A. Castellani, Qi Zhang   +8 more
wiley   +1 more source

Prenatal Use of Exome Sequencing and Chromosomal Microarray Analysis: Indications, Interpretation, and Gene Selection Strategies. [PDF]

Diagnostics (Basel)
Rodriguez-Revenga L, Ardiles-Ruesjas V, Borrell A.   +2 more
europepmc   +1 more source

Clinical utility of chromosomal microarray analysis and whole exome sequencing in foetuses with oligohydramnios. [PDF]

Ann Med, 2023
Shi X, Ding H, Li C, Liu L, Yu L, Zhu J, Wu J.   +6 more
europepmc   +1 more source

Nearest‐neighbors assisted unsupervised analysis for methylation array profiling for central nervous system tumors

Brain Pathology, EarlyView.
The NN method identifies the five nearest reference dataset neighbors to a tested sample and provides an objective estimation of the tested sample methylation class cluster rather than relying on subjective visualization using dimensionality reduction methods such as UMAP and t‐SNE.
Mallika Gandham, Surendra Dasari, Cherisse Marcou, Stephanie Smoley, Matthew Isaacson, Caterina Giannini, Aditya Raghunathan, Rachael A. Vaubel, M. Adelita Vizcaino Villalobos, Aivi Nguyen, Jorge A. Trejo‐Lopez, Kenneth Aldape, Cristiane M. Ida   +12 more
wiley   +1 more source

Comprehensive analysis of copy number variations in congenital heart defects Tunisian patients: chromosomal microarray analysis insights. [PDF]

Mol Cytogenet
Khelifi R, Othmane H, Ajmi H, Slimani W, Bennour A, Dardour L, Soyeh N, Benzarti A, Rjiba K, Abdallah HH, Rassass A, Kooli R, Mghirbi O, Kammoun M, Khelifa HB, Bahri F, Hayet M, Ammar A, Ghanmi S, Mathlouthi J, Ben Hamida H, Habboul Z, Kemis T, Kharrat H, Hassine N, Tej A, Bellalah M, Chouikh F, Houssine M, Mahdhaoui A, Kortas C, Guith A, Maatouk F, Naffeti E, Soua H, Gribaa M, Saad A, Mougou-Zerelli S.   +37 more
europepmc   +1 more source