1 We used a combination of intragastric, intrajejunal, and intr
2 We used a diverse set of 58 complete P. aeruginosa genomes to
3 In addition,
we used a genome-wide association study to identify loci that
4 In experimental studies,
we used a monoclonal antibody to urokinase plasminogen activa
5 We used a set of 4,764 records of ticks of the genera Amblyom
6 We used a weighted graph analysis of the adjacency matrix bas
7 We used amplicon targeted metagenomics to compare microbial c
8 In this study,
we used an activity-dependent tagging system in mice to deter
9 As
we used an ensemble of state-of-the-art fire models, includin
10 We used biolistic combinatorial co-transformation (up to 20 t
11 nome editing protein Streptococcus pyogenes Cas9 (SpyCas9),
we used both self-targeting CRISPR screening and guilt-by-ass
12 We used cell-specific monoclonal antibodies to eliminate neut
13 We used chi2 statistics and ordinal regression to assess the
14 We used cluster analysis to group patients by the dose, recen
15 To understand the altered mobility of an oncogenic KRAS4b,
we used complementary experimental and molecular dynamics sim
16 We used complementary techniques ranging from electrophysiolo
17 We used data from Kantar Worldpanel, a commercial household p
18 p, which we refer to as an "AI-enabled glaucoma dashboard."
We used density-based clustering and the VF decomposition met
19 In this study,
we used dynamic resting state functional MRI analyses to incr
20 We used four machine learning models to produce flood suscept
21 Here,
we used genetic colocalization analysis to identify loci at w
22 We used HeLa cells and screened 231 FDA-approved oncology and
23 We used HiCorr to compare the high-resolution maps of chromat
24 Here,
we used integrated optical imaging in a rat self-administrati
25 We used linear regression to examine country-level associatio
26 We used Medicare inpatient files to identify index admissions
27 We used mixed-effects linear models to analyze associations o
28 We used multidimensional statistical analyses to characterize
29 We used multivariate pattern analyses to measure reactivation
30 Finding a lack of local connectivity,
we used optogenetic circuit mapping to study the strength of
31 ine the role of peripheral ORs in triggering brain hypoxia,
we used oxygen sensors in freely moving rats to examine how n
32 Herein,
we used photopatterned microtopographies on azobenzene-contai
33 We used principal component analyses to identify eating behav
34 Here,
we used psychoacoustics and electroencephalography (EEG) in m
35 Here,
we used quantitative kinetic approaches to determine the tran
36 We used random coefficient modeling to account for the nestin
37 Here,
we used rER BOLD fMRI in macaque monkeys while viewing real-w
38 We used simultaneously acquired (11) C-PBR28 positron emissio
39 nce our understanding of the etiology of blinding diseases,
we used single-cell RNA-sequencing (scRNA-seq) to analyze the
40 (n = 213), MCI (n = 322), and control (CN, n = 322) groups,
we used structural MRI data and neuropsychological assessment
41 We used survival analysis to estimate the relationship betwee
42 amine the interplay between Pi, autophagy, and alphaKlotho,
we used the BK/BK mouse (homozygous for mutant Becn1(F121A) )
43 Here
we used the method to date the exploitation of dairy and carc
44 First,
we used the same type of test cells for all reporters; second
45 We used the well known hierarchical structure of the visual m
46 To this end,
we used the well-characterized iSLK.219 cell model of KSHV in
47 We used this process to develop a framework that can be appli
48 We used this technology to study differences between healthy
49 an auxiliary site capable of binding a Lewis acid (LA(II));
we used this unique feature to further modulate the electrost
50 In this study,
we used tracking data from six Southern Ground-hornbill group