In this task, you are given a passage which has a question and the context. You have to generate an answer to the question based on the information present in the context.

Context: Multiple intercostal recordings were supposed to get a more comprehensive view of the depolarization vector of the outflow tract ventricular arrhythmia (OT-VA), which may help to identify the OT-VA more accurately. This study was undertaken to develop a more accurate electrocardiogram (ECG) criterion for differentiating between left and right OT-VA origins.', 'We studied OT-VA with a left bundle branch block pattern and inferior axis QRS morphology in 47 patients with successful catheter ablation in the right ventricular OT (RVOT; n = 37) or aortic coronary cusp (ACC; n = 10). Superior and inferior precordial leads were taken together with the routine 12-lead ECG. The ECG during the OT-VA and during sinus beats were analyzed. Transition ratio, transition zone (TZ) index, R/S amplitude ratio, and R-wave duration ratio were measured in the regular, superior, and inferior precordial leads.', 'The combined TZ index, TZ index inferior was significantly smaller, while the V2 inferior transition ratio was significantly larger for ACC origins than RVOT origins (P < 0.05). The area under the curve for the combined TZ index by a receiver operating characteristic analysis was 0.974, which was significantly larger than other parameters. A cutoff value ≤0.25 predicted an ACC origin with 94% sensitivity and 100% specificity. This advantage of the parameter over others also held true for a subanalysis of OT-VAs with a lead V3 precordial transition or TZ index = 0.\Question: Does multiple Intercostal Space Electrocardiogram allow Accurate Localization of Outflow Tract Ventricular Arrhythmia Origin?
The combined TZ index outperformed other ECG criteria to differentiate left from right OT-VA origins.

Context: Population-based studies of associations between subclinical hypercortisolism and risk for disease states, such as type 2 diabetes mellitus, have been difficult to assess because of imprecise measures of glucocorticoid exposure. Alternative measures (salivary cortisol and adrenal gland volume) have not been systematically compared with 24-h urine free cortisol (UFC) in a healthy population.', 'Our objectives were: 1) to determine whether 24-h UFC and total daily salivary cortisol correlated with each other, adrenal gland volume, and salivary cortisol after dexamethasone suppression and 2) to evaluate the association of adrenal gland volume with salivary cortisol after dexamethasone suppression.', 'This was a cross-sectional study of 20 healthy, premenopausal African-American women aged 18-45 yr.', 'Salivary cortisol was assessed at six time points throughout the day simultaneous with 24-h UFC collection. Adrenal gland volume was measured by computed tomography scan. Dexamethasone-suppressed salivary cortisol was measured at 0800 h after administration of 0.5 mg dexamethasone at 2300 h the prior evening.', 'Dexamethasone-suppressed salivary cortisol levels correlated strongly with individual, timed salivary cortisol measurements, total daily salivary cortisol (rs=0.75; P=0.0001; n=20), and adrenal gland volume (rs=0.66; P=0.004; n=17). Total daily salivary cortisol and adrenal gland volume also correlated (rs=0.46; P=0.04; n=19). In contrast, 24-h UFC levels did not correlate with any of the other hypothalamic-pituitary-adrenal axis measures.\Question: Do adrenal gland volume and dexamethasone-suppressed cortisol correlate with total daily salivary cortisol in African-American women?
A dexamethasone suppression test or adrenal gland volume may be alternative measures for characterizing subtle subclinical hypercortisolism in healthy adults.

Context: A lot of high-throughput studies produce protein-protein interaction networks (PPINs) with many errors and missing information. Even for genome-wide approaches, there is often a low overlap between PPINs produced by different studies. Second-level neighbors separated by two protein-protein interactions (PPIs) were previously used for predicting protein function and finding complexes in high-error PPINs. We retrieve second level neighbors in PPINs, and complement these with structural domain-domain interactions (SDDIs) representing binding evidence on proteins, forming PPI-SDDI-PPI triangles.', 'We find low overlap between PPINs, SDDIs and known complexes, all well below 10%. We evaluate the overlap of PPI-SDDI-PPI triangles with known complexes from Munich Information center for Protein Sequences (MIPS). PPI-SDDI-PPI triangles have ~20 times higher overlap with MIPS complexes than using second-level neighbors in PPINs without SDDIs. The biological interpretation for triangles is that a SDDI causes two proteins to be observed with common interaction partners in high-throughput experiments. The relatively few SDDIs overlapping with PPINs are part of highly connected SDDI components, and are more likely to be detected in experimental studies. We demonstrate the utility of PPI-SDDI-PPI triangles by reconstructing myosin-actin processes in the nucleus, cytoplasm, and cytoskeleton, which were not obvious in the original PPIN. Using other complementary datatypes in place of SDDIs to form triangles, such as PubMed co-occurrences or threading information, results in a similar ability to find protein complexes.\Question: Do triangle network motifs predict complexes by complementing high-error interactomes with structural information?

Given high-error PPINs with missing information, triangles of mixed datatypes are a promising direction for finding protein complexes. Integrating PPINs with SDDIs improves finding complexes. Structural SDDIs partially explain the high functional similarity of second-level neighbors in PPINs. We estimate that relatively little structural information would be sufficient for finding complexes involving most of the proteins and interactions in a typical PPIN.