On estimating the effectiveness of resources. A local maximum likelihood frontier approach on care for students [PDF]
To study education as a complex production process in a noisy and heterogeneous setting, this paper suggests to using a stochastic frontier model estimated by a local maximum likelihood approach (LMLSF). The LMLSF smoothly combines the virtues of the non-
De Witte, K., Verschelde, M.
core
This paper shows that size‐exclusion chromatography and sequential centrifugation applied to seminal plasma enrich for different populations of extracellular vesicles. This may significantly affect the detection and analysis of extracellular vesicle‐associated cancer biomarkers.
Elen Telumyan +8 more
wiley +1 more source
Engineering IL‐4 resistant proinflammatory human myeloid cells for cancer immunotherapy
We developed a scalable workflow to generate proinflammatory human myeloid cells. CRISPR/Cas9‐edited CD34+ hematopoietic stem and progenitor cells were expanded and differentiated with M‐CSF. Deletion of STAT6 or STAT6/NFKB1 enhanced macrophage proinflammatory gene expression and cytokine secretion in the presence of IL‐4 while maintaining antibody ...
Theresa Barberi, Alan D. Friedman
wiley +1 more source
Asymptotic Properties of Pseudo Maximum Likelihood Estimates for Multiple Frequency I(1) Processes [PDF]
In this paper we derive (weak) consistency and the asymptotic distribution of pseudo maximum likelihood estimates for multiple frequency I(1) processes.
Martin Wagner, Dietmar Bauer
core
Tumour‐proximal deep serum proteomics identifies biomarkers associated with ovarian cancer
New biomarkers are needed for early ovarian cancer detection. Ovarian (tumour‐proximal) and peripheral vein serum from healthy women and patients with benign or malignant tumours underwent nanoparticle‐enriched deep proteomics. Ovarian serum yielded more protein identifications and revealed tumour‐reflective signatures.
Darren Lau +9 more
wiley +1 more source
Marginal Maximum Likelihood Estimation of Item Response Models in R [PDF]
Item response theory (IRT) models are a class of statistical models used by researchers to describe the response behaviors of individuals to a set of categorically scored items.
Matthew S. Johnson
core
Correcting fast irregular motion in PET: maximum-likelihood motion and activity (MLMA) reconstruction. [PDF]
José Santo R +6 more
europepmc +2 more sources
The impact of leukocyte‐associated RNA retention on platelet RNA‐based cancer detection
Platelets carry RNA signals that may help detect cancer, but platelet samples can also retain RNA from white blood cells. We found that this retained white blood cell signal did not significantly affect machine learning cancer classification, suggesting that the cancer‐related RNA signal in platelets is largely independent of leukocyte‐associated RNA ...
Michał Sieczczyński +12 more
wiley +1 more source
On the Existence of the Maximum Likelihood Estimates for Poisson Regression [PDF]
We note that the existence of the maximum likelihood estimates for Poisson regression depends on the data configuration. Because standard software does not check for this problem, the practitioner may be surprised to find that in some applications ...
J. M. C. Santos Silva, Silvana Tenreyro
core
Single‐molecule DNA flow‐stretch assays for high‐throughput DNA–protein interaction studies
We describe an optimised single‐molecule DNA flow‐stretch assay that visualises DNA–protein interactions in real time. Linear DNA fragments are tethered to a surface and stretched by buffer flow for fluorescence imaging. Using λ and φX174 DNA, this protocol enhances reproducibility and accessibility, providing a versatile approach for studying diverse ...
Ayush Kumar Ganguli +8 more
wiley +1 more source

