Characteristics of patients who decreased their screen time by more than 60 minutes after the challenge. by Annaëlle Le Steunf (19838110)

Boxplot comparing Ct values for HD in flies and clothes. by Philippe Ndzomo (17706039)

S1 Data. Bibliometric analysis. S2 Data. Estrogen level analysis. S3 Data. MicroCT quantification. S4 Data. Markers of bone metabolism. by Yan She (8639796)

Skin marks is the S1 Fig title. by Mercedes Soto-González (20422078)

Data Sheet 1_Secretoneurin plasma levels are decreased after catheter ablation for atrial fibrillation—patients with AF produce lower SN levels than healthy individuals: the SAFE r... by Jiří Plášek (21805048)

“…</p>Conclusion<p>Plasma secretoneurin levels are decreased after catheter ablation for atrial fibrillation; patients with AF produce lower SN levels than healthy individuals. …”

Graphs showing the temporal effects of temperature at the four different positions during a drilling sequence with guide drilling in two steps and final widening drilling (MIPS) an... by Marsel Ganeyev (21453399)

AUC statistics as calculated from simulated time series. Each statistical metric was calculated within sliding windows, throughout the pre-critical interval. We considered five-, fifteen-, and thirty-day sliding windows. Given that the temperature of the system increased to 12°C on day sixty, we also considered three pre-critical intervals: Days 1 to 60, Days 20 to 60, and Days 30 to 60. To evaluate trends in these metrics, we calculated Kendall’s rank correlation coefficient during the pre-critical interval, and compared control (constant temperature, non-epidemic) and warming (warming treatment, epidemic emergence) coefficients across simulations and experimental populations by calculating the area under the curve (AUC) statistic. Values less than 0.5 suggest that a decrease in the statistical metric indicates emergence, while values greater than 0.5 suggest that an increase in the statistical metric indicates emergence, with more extreme values indicating stronger tre by Madeline Jarvis-Cross (22394247)

“…Values less than 0.5 suggest that a decrease in the statistical metric indicates emergence, while values greater than 0.5 suggest that an increase in the statistical metric indicates emergence, with more extreme values indicating stronger tre</p>…”

Flow chart with steps of conducting the study. by Athira Satheesh Kumar (20570553)

“…Our numerical analysis indicates that, over time, the temperature anomaly becomes less affected by the variations in rumor propagation parameters, and having larger groups (having more members) is more efficient in reducing temperature (by efficiently propagating rumors) than having numerous small groups. It is observed that decreasing the number of individual connections does not reduce the size of the rejector population when there are large numbers of messages sent through groups. …”

The introduction of mutualisms into assembled communities increases their connectance and complexity while decreasing their richness. by Gui Araujo (22170819)

“…<p>Using the invasion model, we investigate the effect of switching on and off (black vs grey) invasions with mutualisms halfway through the simulation (i.e. after 500 assembly events). …”

Differences among the classes of CAMs. by Daniel P. Bradley (10306893)

“…To ensure the mechanism of action was fully understood, we defined the effects of RNaseH inhibitors on other steps of HBV replication. …”

Image 7_Exploration of the diagnostic and prognostic roles of decreased autoantibodies in lung cancer.tif by Ying Ye (72583)

“…</p>Methods<p>In this study, we applied the HuProt array and the bioinformatics analysis to assess the diagnostic values of the decreased autoantibodies in lung cancers.…”

Image 6_Exploration of the diagnostic and prognostic roles of decreased autoantibodies in lung cancer.tif by Ying Ye (72583)

“…</p>Methods<p>In this study, we applied the HuProt array and the bioinformatics analysis to assess the diagnostic values of the decreased autoantibodies in lung cancers.…”

Image 3_Exploration of the diagnostic and prognostic roles of decreased autoantibodies in lung cancer.tif by Ying Ye (72583)

“…</p>Methods<p>In this study, we applied the HuProt array and the bioinformatics analysis to assess the diagnostic values of the decreased autoantibodies in lung cancers.…”

Image 1_Exploration of the diagnostic and prognostic roles of decreased autoantibodies in lung cancer.tif by Ying Ye (72583)

“…</p>Methods<p>In this study, we applied the HuProt array and the bioinformatics analysis to assess the diagnostic values of the decreased autoantibodies in lung cancers.…”

Image 2_Exploration of the diagnostic and prognostic roles of decreased autoantibodies in lung cancer.tif by Ying Ye (72583)

“…</p>Methods<p>In this study, we applied the HuProt array and the bioinformatics analysis to assess the diagnostic values of the decreased autoantibodies in lung cancers.…”

Image 4_Exploration of the diagnostic and prognostic roles of decreased autoantibodies in lung cancer.tif by Ying Ye (72583)

“…</p>Methods<p>In this study, we applied the HuProt array and the bioinformatics analysis to assess the diagnostic values of the decreased autoantibodies in lung cancers.…”

Image 5_Exploration of the diagnostic and prognostic roles of decreased autoantibodies in lung cancer.tif by Ying Ye (72583)

“…</p>Methods<p>In this study, we applied the HuProt array and the bioinformatics analysis to assess the diagnostic values of the decreased autoantibodies in lung cancers.…”

Image 8_Exploration of the diagnostic and prognostic roles of decreased autoantibodies in lung cancer.tif by Ying Ye (72583)

“…</p>Methods<p>In this study, we applied the HuProt array and the bioinformatics analysis to assess the diagnostic values of the decreased autoantibodies in lung cancers.…”

The energy model responds more differentially to unexpected stimuli than the control model. by Mingfang Zhang (158391)

“…All differences are computed for the time steps during stimulus presentation (). Across all three metrics, the energy model shows a more drastic response difference between expected and unexpected stimuli than the control model (Supporting Information <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1013112#pcbi.1013112.s002" target="_blank">S1 Table</a>). …”

Correlation between TMscore and Length of the RNAs for RNAs longer than 100 nucleotides. by Akash Bahai (20485919)