Results 111 to 120 of about 549,387 (258)
Pancreatic sensory neurons innervating healthy and PDAC tissue were retrogradely labeled and profiled by single‐cell RNA sequencing. Tumor‐associated innervation showed a dominant neurofilament‐positive subtype, altered mitochondrial gene signatures, and reduced non‐peptidergic neurons.
Elena Genova +14 more
wiley +1 more source
Identifying treatment effects using trimmed means when data are missing not at random. [PDF]
Ocampo A +4 more
europepmc +1 more source
We analyze cisplatin–DNA adducts (CDAs) and double‐strand breaks (DSBs) in a cell‐cycle‐dependent manner. We find that CDAs form similarly across all cell cycle phases. DSBs arise only in S‐phase. CDAs might not directly impair DSB repair, but S‐phase DSB lesions evolve in the presence of CDAs and disrupt repair in G2, also causing radiosensitization ...
Ye Qiu +10 more
wiley +1 more source
Semiparametric Inference for Nonmonotone Missing-Not-at-Random Data: The No Self-Censoring Model. [PDF]
Malinsky D +2 more
europepmc +1 more source
KLK7, a tissue kallikrein‐related peptidase, is elevated in advanced colorectal cancer and associated with shorter survival. High KLK7 levels in ascites correlate with peritoneal metastasis. In mice, KLK7 overexpression increases metastasis. In vitro, KLK7 enhances cancer cell proliferation, migration, adhesion, and spheroid formation, driving ...
Yosr Z. Haffani +6 more
wiley +1 more source
Model-based clustering with missing not at random data. Missing mechanism
Since the 90s, model-based clustering is largely used to classify data. Nowadays, with the increase of available data, missing values are more frequent. We defend the need to embed the missingness mechanism directly within the clustering model-ing step. There exist three types of missing data: missing completely at random (MCAR), missing at random (MAR)
Laporte, Fabien +3 more
openaire +2 more sources
LINEAR REGRESSION WITH DATA MISSING NOT AT RANDOM: BOOTSTRAP APPROACH
OLS regressions have a set of assumption in order to have its point and interval estimates to be unbiased and efficient. Data missing not at random (MNAR) can pose serious estimations issues in the linear regression. In this study we evaluate the performance of OLS confidence interval estimates with MNAR data.
Zarrukh Rakhimov, Nilufar Rahimova
openaire +1 more source
CRISPRI‐mediated gene silencing and phenotypic exploration in nontuberculous mycobacteria. In this Research Protocol, we describe approaches to control, monitor, and quantitatively assess CRISPRI‐mediated gene silencing in M. smegmatis and M. abscessus model organisms.
Vanessa Point +7 more
wiley +1 more source
The inhibition of mitochondrial dihydroorotate dehydrogenase (DHODH) impairs syncytialization and induces cellular senescence via mitochondrial and endoplasmic reticulum stress in human trophoblast stem cells, elevating sFlt1/PlGF levels, a hallmark of placental dysfunction in hypertensive disorders of pregnancy.
Kanoko Yoshida +6 more
wiley +1 more source
Missing not at random in end of life care studies: multiple imputation and sensitivity analysis on data from the ACTION study. [PDF]
Carreras G +10 more
europepmc +1 more source

