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We found that LUM cultivated cancer progression by targeting the miR200 family to promote epithelial-to-mesenchymal transition. These findings suggest that LUM is a potential target for inhibiting immune escape and carcinogenic pathways.E3 ubiquitin ligase RING finger protein 168 (RNF168) is one of the key proteins in DNA damage repair. Abnormal expression of RNF168 has recently been found in some tumors. However, the role of RNF168 in the development of esophageal squamous cell carcinoma (ESCC) has not been fully elucidated. Here we report that expression of RNF168 in esophageal squamous cell carcinoma is increased with respect to normal esophageal epithelial tissue. Notably, in ESCC patients, increased RNF168 expression was associated with tumor stage and depth of invasion. Knockdown of the RNF168 gene inhibited proliferation of esophageal cancer cells, promoted cell apoptosis, and interfered with cell movement, ultimately inhibiting tumor xenograft growth. Mechanistic studies showed that RNF168 influenced the malignant behavior of esophageal cancer cells by regulating the Wnt/ β-catenin signaling pathway. In addition, RNF168 expression was positively correlated with wingless-type MMTV integration site family member 3A (WNT3A) expression, and high expression of RNF168 and WNT3A predicted a low survival rate. In conclusion, our findings highlight the important role of RNF168 in ESCC tumorigenesis and provide new biomarkers and therapeutic targets for the treatment of ESCC.Ovarian serous carcinoma (OSC), as a common malignant tumor, poses a serious threat to women's health in that epithelial-mesenchymal transformation (EMT)-related modulation becomes heavily implicated in the invasion and progression of OSC. In this study, two core genes (BUB1B and NDC80) among the 16 hub genes have been identified to be involved in the molecular regulation of EMT and associated with the poor early survival of OSC at stages I+II. Through the Gene Regulatory Networks (GRN) analysis of 15 EMT regulators and core genes, it was revealed that TFAP2A and hsa-miR-655 could elaborately modulate EMT development of OSC. Next genetic variation analysis indicated that EMT regulator ELF3 would also serve as a crucial part in the occurrence and progression of OSC. Eventually, survival investigation suggested that TFAP2A, ELF3 and hsa-miR-655 were significantly associated with the overall survival of progressive OSC patients. Thus, combined with diversified bioinformatic analyses, BUB1B, NDC80, TFAP2A, ELF3 and hsa-miR-655 may act as the key biomarkers for early clinical diagnosis and prognosis evaluation of OSC patients as well as potential therapeutic target-points.

Misdiagnosis, arbitrary charges, annoying queues, and clinic waiting times among others are long-standing phenomena in the medical industry across the world. These factors can contribute to patient anxiety about misdiagnosis by clinicians. However, with the increasing growth in use of big data in biomedical and health care communities, the performance of artificial intelligence (Al) techniques of diagnosis is improving and can help avoid medical practice errors, including under the current circumstance of COVID-19.

This study aims to visualize and measure patients' heterogeneous preferences from various angles of AI diagnosis versus clinicians in the context of the COVID-19 epidemic in China. We also aim to illustrate the different decision-making factors of the latent class of a discrete choice experiment (DCE) and prospects for the application of AI techniques in judgment and management during the pandemic of SARS-CoV-2 and in the future.

A DCE approach was the main analysis method applied in this papbutes are palpable. AI will have a potential market. However, accuracy and diagnosis expenses need to be taken into consideration.

More than 1 in 4 people in the United States aged 65 years and older have type 2 diabetes. For diabetes care, medical nutrition therapy is recommended as a clinically effective intervention. Previous researchers have developed and validated dietary assessment methods using images of food items to improve the accuracy of self-reporting over traditional methods. Nevertheless, little is known about the usability of image-assisted dietary assessment methods for older adults with diabetes.

The aims of this study were (1) to create a food record app for dietary assessments (FRADA) that would support image-assisted dietary assessments, and (2) to evaluate the usability of FRADA for older adults with diabetes.

For the development of FRADA, we identified design principles that address the needs of older adults and implemented three fundamental tasks required for image-assisted dietary assessments capturing, viewing, and transmitting images of food based on the design principles. For the usability assessment of F FRADA, and concerns of older adults with diabetes regarding interactions with FRADA.

This study demonstrates in a lab-based setting not only the usability of FRADA by older adults with diabetes but also potential opportunities using FRADA in real-world settings. The findings suggest implications for creating a smartphone app for an image-assisted dietary assessment. Future work still remains to evaluate the feasibility and validity of FRADA with multiple stakeholders, including older adults with diabetes and dietitians.

This study demonstrates in a lab-based setting not only the usability of FRADA by older adults with diabetes but also potential opportunities using FRADA in real-world settings. The findings suggest implications for creating a smartphone app for an image-assisted dietary assessment. Future work still remains to evaluate the feasibility and validity of FRADA with multiple stakeholders, including older adults with diabetes and dietitians.[This corrects the article DOI 10.2196/23491.].[This corrects the article DOI 10.2196/19151.].

Amid the COVID-19 pandemic, public health policies to curb the spread of SARS-CoV-2 and its associated disease, COVID-19, have resulted in significant alterations to daily routines (eg, work-from-home policies) that may have enabled longer sleep duration among the general population.

We aimed to examine changes in estimated sleep duration in 5 major metropolitan areas before and after the start of the COVID-19 pandemic.

We conducted a prospective observational study using estimated sleep duration data obtained from a smartphone app. this website The data were obtained from regular users of the smartphone app before and after the World Health Organization declared COVID-19 a pandemic in March 2020. We compared within-subject estimated sleep duration before and during the COVID-19 pandemic using generalized linear mixed models.

Among the 2,871,037 observations, 957,022 (33.3%) were from users in London; 549,151 (19.1%) were from users in Los Angeles; 846,527 (29.5%) were from users in New York City; 251,113 (8.7%) were from users in Seoul; and 267,224 (9.