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BackgroundIn February 2020, the Chinese government imposed a complete lockdown of Wuhan and other cities in Hubei Province to contain a spike of COVID-19 cases. Although such measures are effective in preventing the spread of the virus, medical professionals strongly voiced a caveat concerning the pandemic emotional burnout at the individual level. Although the lockdown limited individuals’ interpersonal communication with people in their social networks, it is common that individuals turn to social media to seek and share health information, exchange social support, and express pandemic-generated feelings. ObjectiveBased on a holistic and multilevel perspective, this study examines how pandemic-related emotional exhaustion enacts intrapersonal, interpersonal, and hyperpersonal emotional regulation strategies, and then evaluates the effectiveness of these strategies, with a particular interest in understanding the role of hyperpersonal-level regulation or social media–based regulation. MethodsUsing an online panel, this study sampled 538 Chinese internet users from Hubei Province, the epicenter of the COVID-19 outbreak in China. Survey data collection lasted for 12 days from February 7-18, 2020, two weeks after Hubei Province was placed under quarantine. The sample had an average age of 35 (SD 10.65, range 18-78) years, and a majority were married (n=369, 68.6%). ResultsUsing structural equation modeling, this study found that intrapersonal-level (B=0.22; β=.24; P

BackgroundExisting health education and communication research routinely measures online channel use as a whole by, for example, evaluating how frequently people use the internet to search for health information. This approach fails to capture the complexity and diversity of online channel use in health information seeking. The measurement of generic online channel use may cause too much error, and it lends no support to media planning in public health promotion campaigns or scholarly research involving online channel use. ObjectiveThis study intends to present a thorough picture of patterns of online health information channel use and classify the use of various types of online health information channels, including WeChat, microblogs, web portals, search engines, mobile apps, and online forums. Under the framework of the risk information seeking and processing model, this study also analyzes the differences in individuals’ motivations for channel selection to offer further evidence to validate the classification scheme. MethodsThis study sampled 542 Chinese internet users in Beijing. The average age of the respondents was 33 years, female respondents accounted for 52.0% (282/542) of the sample, and the average monthly income ranged from US $900 to $1200. The study surveyed the use of 13 commonly used online health information channels and various sociopsychological factors associated with online health information seeking. ResultsThis study derived 3 categories of online health information channels: searching, browsing, and scanning channels. It was found that the use of online searching channels was affect driven (B=0.11; β=0.10; P=.02) and characterized by a stronger need for health knowledge (B=0.09; β=0.01; P

BackgroundSince the rise of the internet, online health information seeking has become a worldwide phenomenon. However, health and health communication are inherently culture bound. A data-driven cross-country comparison enables us to better understand how cultural factors moderate the association between individual-level determinants and online health information seeking. ObjectiveThe objective of the study was to examine similarities and differences in determinants of internet cancer information seeking between the US and Chinese general public (excluding cancer patients and survivors) under the framework of a behavioral model of health services use. MethodsThis study used Health Information National Trends Survey (HINTS) 2017 (US data) and HINTS-China 2017 data to answer the research question. It focused on people with no cancer history and with internet access. For the HINTS 2017, the sample size was 2153; for the HINTS-China 2017, the sample size was 2358. To compare China and the United States, the researchers selected the same set of study variables for each dataset. Under the framework of the behavioral model of health services use, these predictors were predisposing factors, enabling factors, and need factors. ResultsIn terms of the predisposing factors, a higher age, college degree or above, being currently unemployed, and having a family history of cancer were associated with internet cancer information seeking for the Chinese respondents; none of these factors were related to information seeking for the US respondents, although a lower age was associated with information seeking. Regarding the enabling conditions, lower trust in family members and friends as reliable information sources was the only factor associated with information seeking for the Chinese respondents, while no enabling factor was related to information seeking for the US respondents. Regarding the need factors, perceived health status was not related to information seeking for the Chinese respondents, while perception of poorer health condition was related to information seeking for the US respondents. Higher cancer fear was related to information seeking for both groups, but the magnitude of association was smaller for the Chinese respondents than for the US respondents. ConclusionsOverall, under the framework of the behavioral model of health services use, the results based on multivariate logistic regression reveal clear patterns of cross-country/cultural differences in the factors associated with internet cancer information seeking behaviors: predisposing characteristics and enabling conditions are more important in China, while perceived needs are more significant in the US. Such differences might reflect possible US-China differences in job environment (eg, job pressure) and culture (individualism vs collectivism and family structure).

C21H21MnN6O6S, monoclinic, P21/c (no. 14), a = 13.093(3) Å, b = 23.810(5) Å, c = 7.9852(17) Å, β = 106.882(4)°, V = 2,382.1(9) Å3, Z = 4, Rgt(F) = 0.0498, wRref(F2) = 0.1299, T = 296(2) K.

Recent clinical development of KRAS inhibitors has heightened interest in the genomic landscape of KRAS-altered cancers. We performed a pan-cancer analysis of KRAS-altered samples from 426,706 adult patients with solid or hematologic malignancies using comprehensive genomic profiling; additional analyses included 62,369 liquid biopsy and 7241 pediatric samples. 23% of adult pan-cancer samples had KRAS alterations; 88% were mutations, most commonly G12D/G12V/G12C/G13D/G12R, and prevalence was similar in liquid biopsies. Co-alteration landscapes were largely similar across KRAS mutations but distinct from KRAS wild-type, though differences were observed in some tumor types for tumor mutational burden, PD-L1 expression, microsatellite instability, and other mutational signatures. Prognosis of KRAS-mutant versus other genomic cohorts of lung, pancreatic, and colorectal cancer were assessed using a real-world clinicogenomic database. As specific KRAS inhibitors and combination therapeutic strategies are being developed, genomic profiling to understand co-alterations and other biomarkers that may modulate response to targeted or immunotherapies will be imperative.

The main component of O-glycoproteins, mucin, is known to play important roles in physiological conditions and oncogenic processes, particularly correlated with poor prognosis in different carcinomas. Diffuse-type gastric cancer (DGC) has long been associated with genomic stability and unfavorable clinical outcomes. To investigate further, we obtained clinical information and the RNA-seq data of the TCGA-STAD cohort. Through the use of unsupervised clustering methods and GSEA, we identified two distinct clusters, characterized by higher and lower expression of MUC2 and MUC20, denoted as cluster 1 and cluster 2, respectively. Subsequently, employing CIBERSORT, it was determined that cluster 2 exhibited a higher tumor mutation burden (TMB) and a greater abundance of CD8+ T cells and activated CD4+ memory T cells, in addition to immune checkpoints (ICPs). On the other hand, cluster 1 showed a lower TIDE score estimation, indicating a higher probability of tumor immune escape. Furthermore, overexpression of MUC15 and MUC20 was confirmed through qPCR and Western blotting, and their specific roles in mediating the epithelial-mesenchymal transition (EMT) process of GC cells (SNU484 and Hs746t) were validated via CCK-8 assay and wound healing assay in vitro. These findings highlight the potential prognostic value of MUC20 and offer insights into the prospects of immunotherapy for DGC by targeting MUC20.