Distribution of gene relatedness and network size in the <i>E. coli</i> CLR network.

<p>(A) Probability distribution of relatedness values, , between pairs of genes in <i>E. coli</i> calculated using the CLR algorithm and the full dataset. (B) Size of the largest connected component for relatedness value, . At small values of the network is fully connected but begins to break up into multiple disconnected components at a critical value of approximately .</p

Links connecting operons in the community that enriches for genes involved in ribosome structure.

<p>CLR links are in light blue, RegulonDB links are in black. Small symbols are genes that are not in the community, but are regulators of genes that are in the community and are therefore candidates for mediating indirect interactions between community genes. Symbol shape and color indicate attributes as follows: red, transcription factors; dark blue, ppGpp regulated promoter by direct assay <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002391#pcbi.1002391-Lemke1" target="_blank">[54]</a>; light blue, ppGpp regulated translation related promoter by microarray <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002391#pcbi.1002391-Traxler1" target="_blank">[55]</a>; pink, other; hexagon, promoter; diamond, promoter; square, promoter; circle, unknown sigma factor. Note that very few interactions observed in the CLR network can be explained by the direct interactions annotated in RegulonDB. The high proportion of ppGpp sensitive promoters among operons contained in the community suggests this molecule as a good candidate for regulating the remaining interactions. The network layout was determined by the circular layout option in Cytoscape 2.8.1, no particular significance should be attached to operons being outside the main circle.</p

The 25 most relevant relationships found for without noise.

<p>The “P value” or random probability, calculated with a hypergeometric test with Benjamini-Hochberg correction, of the common occurrence, or overlap, of genes in an inferred community and in a GO term for the 25 most statistically relevant relationships are listed. Also listed are the “GO term num” that distinguishes the GO term and its “Description” in the GO database, the number of genes in the GO term “GO size”, the number of genes in the inferred community “Com size”, and the number of genes they have in common “In common.” The complete set of the 239 relevant relationships found for , as well as the relevant relationships found for , are given in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002391#pcbi.1002391.s007" target="_blank">Dataset S7</a>.</p

The effect of noise on core community structure and GO term enrichment.

<p>(A) Proportion of core community nodes that remain in a core community. (B) The number of significant GO term enrichments as a function of noise level for networks constructed with . If a GO term is enriched by more than one community, each enrichment is counted separately.</p

Change in core community structure as noise is increased from to .

<p>The grey scale value of each element indicates the fraction of times the two genes occurred in the same community over replicate community partitionings. If the element is white (black) the two genes were always (never) found in the same community. At each noise value there are clearly white diagonal blocks indicating sets of genes that are always found in the same community, which we refer to as core communities. Note that, the five core communities at (<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002391#pcbi-1002391-g003" target="_blank">Figure 3A</a>) are in the same order in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002391#pcbi-1002391-g003" target="_blank">Figure 3:B, C, D, and E</a>. Within each of the five core communities of <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002391#pcbi-1002391-g003" target="_blank">Figure 3A</a>, the node order is allowed to change in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002391#pcbi-1002391-g003" target="_blank">Figure 3:B, C, D, and E</a> in order to display the largest subcommunity first. For each panel, he list of of the order of genes and the core community they belong to is given in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002391#pcbi.1002391.s005" target="_blank">Dataset S5</a> and <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002391#pcbi.1002391.s006" target="_blank">Dataset S6</a>, respectively. A full size version with each pixel representing a distinct pair of genes is included in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002391#pcbi.1002391.s012" target="_blank">Figure S3</a>.</p

Image1_The intervention seasons of thoracic endovascular aortic repair impacted the outcomes for patients with type B aortic dissection.tif

PurposeThe objective of this research was to investigate whether seasonal variations influence the outcomes of type B aortic dissection (TBAD) patients with thoracic endovascular aortic repair (TEVAR).Patients and methodsFrom 2003 to 2020, a retrospective cohort study was performed, which included 1,123 TBAD patients who received TEVAR. Medical records were used to gather data on baseline characteristics. Outcomes including all-cause mortality and aortic-related adverse events (ARAEs) were tracked and analyzed.ResultsOf the 1,123 TBAD patients in this study, 308 received TEVAR in spring (27.4%), 240 cases in summer (21.4%), 260 cases in autumn (23.2%), and 315 cases in winter (28.0%). Patients in the autumn group had a significantly lower risk of 1-year mortality than those in the spring group (hazard ratio: 2.66, 95% confidence interval: 1.06–6.67, p = 0.037). Kaplan–Meier curves revealed that patients who underwent TEVAR in autumn had a lower risk of 30-day ARAEs (p = 0.049) and 1-year mortality (p = 0.03) than those in spring.ConclusionThis study confirmed that TEVAR operated in autumn for TBAD was associated with a lower risk of 30-day ARAEs and 1-year mortality than in spring.</p

Image2_The intervention seasons of thoracic endovascular aortic repair impacted the outcomes for patients with type B aortic dissection.tif

PurposeThe objective of this research was to investigate whether seasonal variations influence the outcomes of type B aortic dissection (TBAD) patients with thoracic endovascular aortic repair (TEVAR).Patients and methodsFrom 2003 to 2020, a retrospective cohort study was performed, which included 1,123 TBAD patients who received TEVAR. Medical records were used to gather data on baseline characteristics. Outcomes including all-cause mortality and aortic-related adverse events (ARAEs) were tracked and analyzed.ResultsOf the 1,123 TBAD patients in this study, 308 received TEVAR in spring (27.4%), 240 cases in summer (21.4%), 260 cases in autumn (23.2%), and 315 cases in winter (28.0%). Patients in the autumn group had a significantly lower risk of 1-year mortality than those in the spring group (hazard ratio: 2.66, 95% confidence interval: 1.06–6.67, p = 0.037). Kaplan–Meier curves revealed that patients who underwent TEVAR in autumn had a lower risk of 30-day ARAEs (p = 0.049) and 1-year mortality (p = 0.03) than those in spring.ConclusionThis study confirmed that TEVAR operated in autumn for TBAD was associated with a lower risk of 30-day ARAEs and 1-year mortality than in spring.</p

Image5_The intervention seasons of thoracic endovascular aortic repair impacted the outcomes for patients with type B aortic dissection.tif

PurposeThe objective of this research was to investigate whether seasonal variations influence the outcomes of type B aortic dissection (TBAD) patients with thoracic endovascular aortic repair (TEVAR).Patients and methodsFrom 2003 to 2020, a retrospective cohort study was performed, which included 1,123 TBAD patients who received TEVAR. Medical records were used to gather data on baseline characteristics. Outcomes including all-cause mortality and aortic-related adverse events (ARAEs) were tracked and analyzed.ResultsOf the 1,123 TBAD patients in this study, 308 received TEVAR in spring (27.4%), 240 cases in summer (21.4%), 260 cases in autumn (23.2%), and 315 cases in winter (28.0%). Patients in the autumn group had a significantly lower risk of 1-year mortality than those in the spring group (hazard ratio: 2.66, 95% confidence interval: 1.06–6.67, p = 0.037). Kaplan–Meier curves revealed that patients who underwent TEVAR in autumn had a lower risk of 30-day ARAEs (p = 0.049) and 1-year mortality (p = 0.03) than those in spring.ConclusionThis study confirmed that TEVAR operated in autumn for TBAD was associated with a lower risk of 30-day ARAEs and 1-year mortality than in spring.</p

Image3_The intervention seasons of thoracic endovascular aortic repair impacted the outcomes for patients with type B aortic dissection.tif

PurposeThe objective of this research was to investigate whether seasonal variations influence the outcomes of type B aortic dissection (TBAD) patients with thoracic endovascular aortic repair (TEVAR).Patients and methodsFrom 2003 to 2020, a retrospective cohort study was performed, which included 1,123 TBAD patients who received TEVAR. Medical records were used to gather data on baseline characteristics. Outcomes including all-cause mortality and aortic-related adverse events (ARAEs) were tracked and analyzed.ResultsOf the 1,123 TBAD patients in this study, 308 received TEVAR in spring (27.4%), 240 cases in summer (21.4%), 260 cases in autumn (23.2%), and 315 cases in winter (28.0%). Patients in the autumn group had a significantly lower risk of 1-year mortality than those in the spring group (hazard ratio: 2.66, 95% confidence interval: 1.06–6.67, p = 0.037). Kaplan–Meier curves revealed that patients who underwent TEVAR in autumn had a lower risk of 30-day ARAEs (p = 0.049) and 1-year mortality (p = 0.03) than those in spring.ConclusionThis study confirmed that TEVAR operated in autumn for TBAD was associated with a lower risk of 30-day ARAEs and 1-year mortality than in spring.</p

Table1_The intervention seasons of thoracic endovascular aortic repair impacted the outcomes for patients with type B aortic dissection.docx

PurposeThe objective of this research was to investigate whether seasonal variations influence the outcomes of type B aortic dissection (TBAD) patients with thoracic endovascular aortic repair (TEVAR).Patients and methodsFrom 2003 to 2020, a retrospective cohort study was performed, which included 1,123 TBAD patients who received TEVAR. Medical records were used to gather data on baseline characteristics. Outcomes including all-cause mortality and aortic-related adverse events (ARAEs) were tracked and analyzed.ResultsOf the 1,123 TBAD patients in this study, 308 received TEVAR in spring (27.4%), 240 cases in summer (21.4%), 260 cases in autumn (23.2%), and 315 cases in winter (28.0%). Patients in the autumn group had a significantly lower risk of 1-year mortality than those in the spring group (hazard ratio: 2.66, 95% confidence interval: 1.06–6.67, p = 0.037). Kaplan–Meier curves revealed that patients who underwent TEVAR in autumn had a lower risk of 30-day ARAEs (p = 0.049) and 1-year mortality (p = 0.03) than those in spring.ConclusionThis study confirmed that TEVAR operated in autumn for TBAD was associated with a lower risk of 30-day ARAEs and 1-year mortality than in spring.</p