Fig 1 - by Varun Tiwari (9258130)

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Fig 7 - by Varun Tiwari (9258130)

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Data for Figs 8A–8H, 9A–9K, 10A–10I. by Xiaohua Zhang (350570)

“…In <i>vivo</i> experiments further showed that PRV UL4 (¹³²DVAADAAAEAAAAE¹⁴⁵) mutated strain (PRV-UL4^mut) infection did not lead to a significant decrease in viral titers at 12 h. p. i, but it induced lower levels of IL-1β, IL-18, and GSDMD-NT, which led to an alleviated inflammatory infiltration and pathological damage in the lungs and brains, and a lower death rate compared with wild-type PRV strain infection. …”

Accuracy of the random forest regression model with various input variables (all inputs vs. top 30 inputs). by Varun Tiwari (9258130)

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Random forest top 30 variable importance utilizing all input variables, including the MODIS bands, spectral indices, and land surface temperature. by Varun Tiwari (9258130)

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Indices calculated using MODIS bands (B1-B7) which were used to estimate <i>boro</i> rice yields, where MODIS bands relate to indices as follows: B1 = RED, B2 = NIR1, B3 = BLUE, B4... by Varun Tiwari (9258130)

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EF-24 treatment significantly reduces cell viability in leukemia cell lines. by Ajeet P. Singh (22298432)

a-d. Difference in (a) probing depth; (b) clinical attachment level; (c) bleeding on probing, and (d) plaque index values between baseline and six months after treatment using syst... by Iva Milinkovic (22331710)

Mortality of <i>C. maculatus</i> after 24h exposure to GO and GO-GA NPs. by Huda H. Elbehery (22492996)

(A) Appearance image of psoriasis on the back skin of mouse. by Xiaoqiang Huang (1457860)

Data for Figs 1A–1I, 2A–2J, 3B–3H, 4A–4L, 5A–5C, 6A–6C, 6E, by Xiaohua Zhang (350570)

The PP1/PP2A inhibitor calyculin A increases phosphorylated Ser295 of PSD-95 concomitantly with the activation of JNK1. by Takahiko Chimura (729098)

BMI groups by SES. by Krystal Hunter (6820052)

“…For every increase in BMI, there was a decrease in the probability of PTB (OR = 0.923, 95% CI 0.915–0.931, P < 0.001). …”

BMISES_Data_Part2. by Krystal Hunter (6820052)

“…For every increase in BMI, there was a decrease in the probability of PTB (OR = 0.923, 95% CI 0.915–0.931, P < 0.001). …”

Logistic regression for LSES population. by Krystal Hunter (6820052)

“…For every increase in BMI, there was a decrease in the probability of PTB (OR = 0.923, 95% CI 0.915–0.931, P < 0.001). …”

Logistic regression for HSES population. by Krystal Hunter (6820052)

“…For every increase in BMI, there was a decrease in the probability of PTB (OR = 0.923, 95% CI 0.915–0.931, P < 0.001). …”

Logistic regression for overall population. by Krystal Hunter (6820052)

“…For every increase in BMI, there was a decrease in the probability of PTB (OR = 0.923, 95% CI 0.915–0.931, P < 0.001). …”

BMISES_Data_Part1. by Krystal Hunter (6820052)

“…For every increase in BMI, there was a decrease in the probability of PTB (OR = 0.923, 95% CI 0.915–0.931, P < 0.001). …”

Baseline characteristics of HSES/LSES population. by Krystal Hunter (6820052)

“…For every increase in BMI, there was a decrease in the probability of PTB (OR = 0.923, 95% CI 0.915–0.931, P < 0.001). …”

Baseline characteristics of overall population. by Krystal Hunter (6820052)

“…For every increase in BMI, there was a decrease in the probability of PTB (OR = 0.923, 95% CI 0.915–0.931, P < 0.001). …”