WT1 siRNA decreases proliferation, pAKT, and Bcl2 expression. by Ayana E. Morales (17756335)

“…<b>C.</b> RT-qPCR of WT1, p<0.05(*), vFLIP(ns), LANA, p<0.0001(****), K8.1, p<0.0001(****), and BCL2 p<0.05(*) in the setting of WT1 knockdown in ISLK BAC-16 with WT1 siRNA in comparison to a control siRNA using two-sided, unpaired student’s t-tests. …”

Nasal mucociliary clearance was decreased in <i>Ttll1</i>^−/− mice. by Toshiyuki Iwata (419270)

“…In the <i>Ttll1</i>^−/− mice, a larger amount of Evans blue persisted in the nasal cavity and a lesser amount was swallowed compared with that in the wild-type (WT) mice (mean ± SEM, n = 5, *P < 0.005 by two-tailed Student's t test).…”

Global Land Use Change Impacts on Soil Nitrogen Availability and Environmental Losses by Jing Wang (6206297)

“…By compiling a global data set of 1,782 paired observations from 185 publications, we show that land use conversion from natural to managed ecosystems significantly reduced NNM by 7.5% (−11.5, −2.8%) and increased NN by 150% (86, 194%), indicating decreasing N availability while increasing potential N loss through denitrification and nitrate leaching. …”

200 WT nts but not WT UTRs at each terminus are sufficient for efficient recovery of replicating virus. by Debarpan Dhar (724473)

Network structures of the deep learning models used for respiration prediction. by Sangwoon Jeong (13977888)

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Average error results in millimeters. by Sangwoon Jeong (13977888)

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Maximum error results in millimeters. by Sangwoon Jeong (13977888)

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Actual and predicted respiratory signals for three different patterns of irregular respiration. by Sangwoon Jeong (13977888)

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Plots of actual (solid line) and predicted respiratory signals (dotted line). by Sangwoon Jeong (13977888)

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Process of learning a respiratory signal prediction model using deep learning. by Sangwoon Jeong (13977888)

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Accuracy evaluation of the LSTM, Bi-LSTM, and Transformer methods using the RMSE and CC. by Sangwoon Jeong (13977888)

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Comparison of the prediction accuracies of LSTM, Bi-LSTM, and the Transformer for different training sequences (T_s) and prediction points (P_t). by Sangwoon Jeong (13977888)

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Respiratory signal prediction accuracies of LSTM, Bi-LSTM, and the Transformer. by Sangwoon Jeong (13977888)

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Expression of AC5 and AC6 in WT and AMPKα2-/- mice. by Anne Garnier (130125)

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A representative dataset of multiphase ALADDIN with different gap sizes (300% and 450% of slice thickness) and different inter-slice delay time (TD) (0 and 500 ms) from one represe... by Ki Hwan Kim (427869)

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The G215S mutation decreases packaging of N and growth in primary differentiated human bronchial cells. by Hannah C. Kubinski (21213168)

Decrease of endogenous WT1 abundance by overexpression of zinc finger domain in breast cancer cells by Youqi Han (84352)

Expression of WT coilin or the OFF coilin mutant decreases cell proliferation in the presence of endogenous coilin. by Zunamys I. Carrero (342815)

“…Errors bars denote the percent standard error based on an n of no fewer than 5. There is a significant decrease (p value <0.05) in cell number upon the doxycycline induction of GFP-coilin WT or OFF mutant.…”

WT1 siRNA increases the basal and decreases GnRH stimulated expression of endogenous LHβ primary transcript. by Debalina Bagchi (686046)

SEM images of the samples (a) virgin sample (b) 0.4 wt. % <i>f-MWCNTs</i> (c) 0.5 wt. % <i>f—MWCNTs</i>. by Shaban Gul (14309526)

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