The authors examined online support group members' reliance on their Internet community and other online and offline health resources as they prepare for a scheduled medical appointment. Adult members of an online support group (N = 505) with an upcoming medical appointment completed an online questionnaire that included measures of illness perceptions, control preference, trust in the physician, and eHealth literacy; a checklist of actions one could take to acquire health information; and demographic questions. A factor analysis identified 4 types of information seeking: reliance on the online support group, use of other online health resources, use of offline health resources, and personal network contacts. Previsit information seeking on the Internet was extensive and typically augmented with offline information. Use of online health resources was highest among those who believed they had control over their illness, who attributed many symptoms and negative emotions to it, and who were more eHealth literate. Reliance on the online support group was highest among those who believed they had personal control over their illness, expected their condition to persist, and attributed negative emotions to it. Trust in the physician and preferences for involvement in decision making were unrelated to online information seeking. Most respondents intended to ask their physician questions and request clinical resources based on online information.

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Background Kidney renal clear cell carcinoma (KIRC) is the most common subtype of renal tumor. However, the molecular mechanisms of KIRC pathogenesis remain little known. The purpose of our study was to identify potential key genes related to the occurrence and prognosis of KIRC, which could serve as novel diagnostic and prognostic biomarkers for KIRC. Methods Three gene expression profiles from gene expression omnibus database were integrated to identify differential expressed genes (DEGs) using limma package. Enrichment analysis and PPI construction for these DEGs were performed by bioinformatics tools. We used Gene Expression Profiling Interactive Analysis (GEPIA) database to further analyze the expression and prognostic values of hub genes. The GEPIA database was used to further validate the bioinformatics results. The Connectivity Map was used to identify candidate small molecules that could reverse the gene expression of KIRC. Results A total of 503 DEGs were obtained. The PPI network with 417 nodes and 1912 interactions was constructed. Go and KEGG pathway analysis revealed that these DEGs were most significantly enriched in excretion and valine, leucine, and isoleucine degradation, respectively. Six DEGs with high degree of connectivity ( ACAA1, ACADSB, ALDH6A1, AUH, HADH, and PCCA ) were selected as hub genes, which significantly associated with worse survival of patients. Finally, we identified the top 20 most significant small molecules and pipemidic acid was the most promising small molecule to reverse the KIRC gene expression. Conclusions This study first uncovered six key genes in KIRC which contributed to improving our understanding of the molecular mechanisms of KIRC pathogenesis. ACAA1, ACADSB, ALDH6A1, AUH, HADH, and PCCA could serve as the promising novel biomarkers for KIRC diagnosis, prognosis, and treatment.

The scaling of pulse duration to seismic moment is estimated for earthquakes along an interplate thrust zone, from digital waveforms recorded by short-period and broad-band instruments of the East Aleutian (Shumagin) Seismic Network. We measure pulse duration using an empirical Green's function technique based on damped time-domain deconvolution. From several thousand events, 22 earthquakes with magnitudes 3.0-7.0 and depths 23-56 km are found to give reliable estimates of pulse duration. Durations are also determined directly from one-parameter nonlinear inversions, for a variety of simple functional forms of source time functions. Symmetric source pulses (boxcar or triangle shapes) fit waveforms better than an asymmetric model [t exp (-2tlD)I for most (62 per cent) of the waveform pairs, while the asymmetric model fits best for only 8 per cent of the data. Pulse duration increases with the size of events, from 0.1 to 10s over the seismic moment (M,,) range of 1014 to 3 X lo1' Nm. When normalized by the cube root of seismic moment, pulse durations show -8 x variation; comparable static stress drop estimates range from 0.2 to 135 MPa. Contrary to predictions of some laboratory and theoretical studies, earthquakes at the deepest part of the thrust zone do not show significantly higher stress drops than do shallower events. Rupture properties, however, show a strong dependence on earthquake size. The three largest events (Mo > 5 X 10l8 Nm) have the three longest normalized durations, on average 3.8 times longer than those for smaller events. The durations require smaller events to have 10-100 X larger static stress drops, or -4 x faster rupture velocities, or some combination of the two. Possibly, the largest events rupture both strong and weak patches while smaller events just rupture strong patches on the fault surface. The characteristic dimension that separates large from small events, 3-15 km, is comparable to characteristic wavelengths of Pacific basin bathymetry and may reflect the influence of the subducted sea-floor upon fault-zone heterogeneity.