NK cells are activated, proliferating and decreased in frequency in peripheral blood of HFRS patients. by Marina García (694440)

Data from: Colony losses of stingless bees increase in agricultural areas, but decrease in forested areas by Malena Sibaja Leyton (18400983)

Importance of facilitating dispersal for mammals with 2°C warming. by Rhosanna L. M. Jenkins (11167230)

Importance of facilitating dispersal for birds with 2°C warming. by Rhosanna L. M. Jenkins (11167230)

Silencing of <i>NbNBR1</i> decreases the accumulation of βC1. by Tingting Zhou (163678)

Odds ratios (95% CI) for acute exacerbation of IBD per 1 °C daily average temperature <i>decrease</i> at the first quartile. by Yeong Chan Lee (8809223)

Supplementary Material for: Real-World Experience with Artificial Intelligence-Based Triage in Transferred Large Vessel Occlusion Stroke Patients by Morey J.R. (10592381)

“…We hypothesize that the Viz application will decrease time-to-treatment, leading to improved clinical outcomes. …”

Radiation can decrease the expression of the SCFAs in colon contents. by Liying Zhang (102453)

Importance of facilitating dispersal for mammals with 4.5°C warming. by Rhosanna L. M. Jenkins (11167230)

Importance of facilitating dispersal for birds with 4.5°C warming. by Rhosanna L. M. Jenkins (11167230)

Deletion of TAL does not decrease GNG flux. by Julie Kovářová (4114573)

Decreased deaminase activity in A12-infected cells despite a high level of A3B protein. by Noémie Lejeune (9243785)

Comparison of the MLTD and MDD scores of text before and after hypernym substitution using the GPT-J-6B, Programmatic+AI, and T5 approaches. by Karl Swanson (3580583)

Studies with large effect sizes tend to have low samples sizes. by Jeff C. Clements (9161831)

Mice decreased water intake when OJS was added to the water bottle. by Patrice Cunningham (12914917)

miR-200c induction decreases migration of MDA-MB-231 cells as shown in the 1D migration assay. by Bojan Ljepoja (4921255)

Table 3_Exploring common circulating diagnostic biomarkers for sleep disorders and stroke based on machine learning.xlsx by Hanlin Yu (17776399)

“…Co-expression modules were then identified in the SD and stroke datasets by weighted gene co-expression network analysis (WGCNA), respectively, and machine learning algorithms (RandomForest, LASSO, and XGBoost) were performed to identify ARL2 as a key diagnostic biomarker with high predictive value (AUC = 0.91). …”

Table 1_Exploring common circulating diagnostic biomarkers for sleep disorders and stroke based on machine learning.xlsx by Hanlin Yu (17776399)

“…Co-expression modules were then identified in the SD and stroke datasets by weighted gene co-expression network analysis (WGCNA), respectively, and machine learning algorithms (RandomForest, LASSO, and XGBoost) were performed to identify ARL2 as a key diagnostic biomarker with high predictive value (AUC = 0.91). …”

Table 4_Exploring common circulating diagnostic biomarkers for sleep disorders and stroke based on machine learning.xlsx by Hanlin Yu (17776399)

“…Co-expression modules were then identified in the SD and stroke datasets by weighted gene co-expression network analysis (WGCNA), respectively, and machine learning algorithms (RandomForest, LASSO, and XGBoost) were performed to identify ARL2 as a key diagnostic biomarker with high predictive value (AUC = 0.91). …”

Table 2_Exploring common circulating diagnostic biomarkers for sleep disorders and stroke based on machine learning.xlsx by Hanlin Yu (17776399)

“…Co-expression modules were then identified in the SD and stroke datasets by weighted gene co-expression network analysis (WGCNA), respectively, and machine learning algorithms (RandomForest, LASSO, and XGBoost) were performed to identify ARL2 as a key diagnostic biomarker with high predictive value (AUC = 0.91). …”