lncRNA TMEM161B-AS1 screened the onset of oral squamous cell carcinoma in HPV-infected patients, predicted poor prognosis, and regulated cell progression via modulating the miR-651-5p/BDNF axis.

Oral squamous cell carcinoma (OSCC) has become the most common HPV-related cancer with high invasion and metastasis. Exploring biomarkers for the screening and monitoring of OSCC, especially for the HPV-OSCC, would benefit patients' diagnosis and prognosis. This study evaluated the significance and mechanism of TMEM161B-AS1 and miR-651-5p in HPV-OSCC aiming to provide novel insight into the mechanism of HPV-OSCC development. Expression of TMEM161B-AS1 and miR-561-5p was analyzed in healthy individuals, HPV-infected non-OSCC patients, and HPV-OSCC patients using PCR. Their significance in HPV-OSCC occurrence and prognosis was evaluated by logistic regression, ROC, Kaplan-Meier, and Cox regression analysis. In OSCC cells, CCK8 and Transwell assays were employed for assessing cell growth and metastasis. The luciferase reporter assay and cell transfection were performed to evaluate the regulatory association between TMEM161B-AS1, miR-561-5p, and BDNF. Significant upregulation of TMEM161B-AS1 and downregulation of miR-561-5p were observed in oral HPV-infected patients. Both TMEM161B-AS1 and miR-651-5p served as risk factors for the occurrence of OSCC in oral HPV-infected patients and could distinguish HPV-OSCC patients from HPV-infected non-OSCC patients. Increased TMEM161B-AS1 and reduced miR-561-5p indicated severe development and adverse prognosis of HPV-OSCC patients. In OSCC cells, silencing TMEM161-AS1 suppressed cell proliferation and motility via negatively modulating miR-561-5p. miR-561-5p negatively regulated BDNF, which was considered the underlying mechanism of TMEM161B-AS1. Increasing TMEM161B-AS expression and decreasing miR-561-5p showed the occurrence of OSCC in HPV-infected patients and predicted malignant development and adverse prognosis. TMEME161B-AS1 served as a tumor promoter via regulating the miR-561-5p/BDNF axis.

Mobility in China, 2020: a tale of four phases.

2020 was an unprecedented year, with rapid and drastic changes in human mobility due to the COVID-19 pandemic. To understand the variation in commuting patterns among the Chinese population across stable and unstable periods, we used nationwide mobility data from 318 million mobile phone users in China to examine the extreme fluctuations of population movements in 2020, ranging from the Lunar New Year travel season (chunyun), to the exceptional calm of COVID-19 lockdown, and then to the recovery period. We observed that cross-city movements, which increased substantially in chunyun and then dropped sharply during the lockdown, are primarily dependent on travel distance and the socio-economic development of cities. Following the Lunar New Year holiday, national mobility remained low until mid-February, and COVID-19 interventions delayed more than 72.89 million people returning to large cities. Mobility network analysis revealed clusters of highly connected cities, conforming to the social-economic division of urban agglomerations in China. While the mass migration back to large cities was delayed, smaller cities connected more densely to form new clusters. During the recovery period after travel restrictions were lifted, the netflows of over 55% city pairs reversed in direction compared to before the lockdown. These findings offer the most comprehensive picture of Chinese mobility at fine resolution across various scenarios in China and are of critical importance for decision making regarding future public-health-emergency response, transportation planning and regional economic development, among others.

Resveratrol attenuates dapagliflozin-induced renal gluconeogenesis via activating the PI3K/Akt pathway and suppressing the FoxO1 pathway in type 2 diabetes.

Dapagliflozin alleviates hyperglycemia by increasing glycosuria, but it induces renal gluconeogenesis, thus neutralizing its efficacy. Resveratrol (Rsv), a natural polyphenolic chemical, improves insulin sensitivity in type 2 diabetes (T2D). Here, we investigated the regulatory effects and underlying mechanisms of Rsv on dapagliflozin-induced renal gluconeogenesis. Male ob/ob mice were given the vehicle (HF), dapagliflozin (1 mg kg-1), Rsv (10 mg kg-1), or dapagliflozin and Rsv combination for 10 weeks. Glucose metabolism was evaluated by glucose and pyruvate tolerance tests. HK-2 cells (human renal proximal tubule cells) were treated with dapagliflozin (1 µmol L-1) for 2 h and further incubated with Rsv (10 µmol L-1) for 12 h. The effects of Rsv on gluconeogenesis and insulin signaling were assessed. Dapagliflozin treatment increased glucose production in HK-2 cells and lowered blood glucose and induced gluconeogenesis in ob/ob mice. After Rsv treatment, the enhanced glucose production and gluconeogenesis were alleviated. The upregulated mRNA and protein expression of phosphoenolpyruvate carboxykinase (PEPCK) and glucose-6-phosphatase (G6Pase) and the activation of the forkhead transcription factor O1 (FoxO1) protein in the dapagliflozin group were attenuated by Rsv administration. Rsv also improved renal insulin signaling by increasing PI3K and Akt phosphorylation. The PI3K inhibitor LY294002 dramatically decreased the p-Akt expression and activated FoxO1 by dephosphorylation, thus diminishing the inhibitory effects of Rsv on dapagliflozin-induced PEPCK and G6Pase expression. The data showed the mechanisms of Rsv in attenuating dapagliflozin-induced renal gluconeogenesis via activating the PI3K/Akt pathway and further suppressing FoxO1 activation, suggesting a potential intervention to achieve better glucose-lowering effects for SGLT2 inhibitors in T2D therapy.

Mobile Phone-Based Population Flow Data for the COVID-19 Outbreak in Mainland China.

Background: Human migration is one of the driving forces for amplifying localized infectious disease outbreaks into widespread epidemics. During the outbreak of COVID-19 in China, the travels of the population from Wuhan have furthered the spread of the virus as the period coincided with the world's largest population movement to celebrate the Chinese New Year. Methods: We have collected and made public an anonymous and aggregated mobility dataset extracted from mobile phones at the national level, describing the outflows of population travel from Wuhan. We evaluated the correlation between population movements and the virus spread by the dates when the number of diagnosed cases was documented. Results: From Jan 1 to Jan 22 of 2020, a total of 20.2 million movements of at-risk population occurred from Wuhan to other regions in China. A large proportion of these movements occurred within Hubei province (84.5%), and a substantial increase of travels was observed even before the beginning of the official Chinese Spring Festival Travel. The outbound flows from Wuhan before the lockdown were found strongly correlated with the number of diagnosed cases in the destination cities (log-transformed). Conclusions: The regions with the highest volume of receiving at-risk populations were identified. The movements of the at-risk population were strongly associated with the virus spread. These results together with province-by-province reports have been provided to governmental authorities to aid policy decisions at both the state and provincial levels. We believe that the effort in making this data available is extremely important for COVID-19 modelling and prediction.

Location inference for hidden population with online text analysis.

BACKGROUND: Understanding the geographic distribution of hidden population, such as men who have sex with men (MSM), sex workers, or injecting drug users, are of great importance for the adequate deployment of intervention strategies and public health decision making. However, due to the hard-to-access properties, e.g., lack of a sampling frame, sensitivity issue, reporting error, etc., traditional survey methods are largely limited when studying such populations. With data extracted from the very active online community of MSM in China, in this study we adopt and develop location inferring methods to achieve a high-resolution mapping of users in this community at national level. METHODS: We collect a comprehensive dataset from the largest sub-community related to MSM topics in Baidu Tieba, covering 628,360 MSM-related users. Based on users' publicly available posts, we evaluate and compare the performances of mainstream location inference algorithms on the online locating problem of Chinese MSM population. To improve the inference accuracy, other approaches in natural language processing are introduced into the location extraction, such as context analysis and pattern recognition. In addition, we develop a hybrid voting algorithm (HVA-LI) by allowing different approaches to vote to determine the best inference results, which guarantees a more effective way on location inference for hidden population. RESULTS: By comparing the performances of popular inference algorithms, we find that the classic gazetteer-based algorithm has achieved better results. And in the HVA-LI algorithms, the hybrid algorithm consisting of the simple gazetteer-based method and named entity recognition (NER) is proven to be the best to deal with inferring users' locations disclosed in short texts on online communities, improving the inferring accuracy from 50.3 to 71.3% on the MSM-related dataset. CONCLUSIONS: In this study, we have explored the possibility of location inferring by analyzing textual content posted by online users. A more effective hybrid algorithm, i.e., the Gazetteer & NER algorithm is proposed, which is conducive to overcoming the sparse location labeling problem in user profiles, and can be extended to the inference of geo-statistics for other hidden populations.