The miR-302s/367 family has the ability to induce mouse and human somatic cell reprogramming into induced pluripotent stem cells (iPSCs), inhibit the proliferation of several types of cancer cells, ...and even cause cancer cell apoptosis. However, the functions of the miR-302s/367 family in other mammals have not been explored. In the present study, the effects of miR-302s/367 on reprogramming, proliferation, and apoptosis in sheep fetal fibroblasts (SFFs) were evaluated by the delivery of a plasmid vector containing synthetic precursor miRNAs into cells, followed by the induction of mature miR-302s/367 expression. The results showed that miR-302s/367 could not reprogram SFFs into iPSCs; however, they could inhibit both the proliferation and apoptosis of SFFs by targeting
CDK2
,
E
2F
1
,
E
2F
2
, and
PTEN
in the cell cycle and PI3K-Akt pathways. Based on our findings, a novel mechanism was proposed in which the miR-302s/367 family functions in both the proliferation and apoptosis of somatic cells in mammals, suggesting that caution is needed when using miR-302s/367 as therapeutic agent.
Health care delivery in China is in transition from reactive and doctor-centered to preventative and patient-centered. The challenge for the reform is to account for the needs of unique individuals ...and local communities while ensuring efficiency and equity. This Viewpoint presents data-driven integrated care pathways as a potential solution to standardize patient-centered care delivery, highlighting five core aspects of the entire care journey for personalization by using real-time data and digital technology, and identifying three capabilities to support the uptake of data-driven design.
Colorectal cancer (CRC) remains an incurable disease. There are no effective noninvasive techniques that have achieved colorectal cancer (CRC) diagnosis, prognosis, survival and recurrence in clinic. ...To investigate colorectal cancer metabolism, we perform an electronic literature search, from 1998 to January 2016, for studies evaluating the metabolomic profile of patients with CRC regarding the diagnosis, recurrence, prognosis/survival, and systematically review the twenty-three literatures included. QUADOMICS tool was used to assess the quality of them. We highlighted the metabolism perturbations based on metabolites and pathway. Metabolites related to cellular respiration, carbohydrate, lipid, protein and nucleotide metabolism were significantly altered in CRC. Altered metabolites were also related to prognosis, survival and recurrence of CRC. This review could represent the most comprehensive information and summary about CRC metabolism to date. It certificates that metabolomics had great potential on both discovering clinical biomarkers and elucidating previously unknown mechanisms of CRC pathogenesis.
Curcumin, a natural polyphenol antioxidant extracted from the root of turmeric (Curcuma longa), can induce apoptosis and DNA demethylation in several types of cancer cells. However, the mechanism of ...its anticancer potentials and DNA demethylation effects and the potential relationships between these outcomes have not been clearly elucidated. In the present study, the effects of curcumin on the proliferation, colony formation, and migration of human gastric cancer cells (hGCCs) were explored. Reactive oxygen species (ROS) levels, mitochondrial damage, DNA damage, and apoptosis of curcumin-treated hGCCs were analyzed. Changes in the expression of several genes related to DNA damage repair, the p53 pathway, cell cycle, and DNA methylation following curcumin treatment were also evaluated. We observed that curcumin inhibited the proliferation, colony formation, and migration of hGCCs in a dose- and time-dependent fashion. A high concentration of curcumin elevated ROS levels and triggered mitochondrial damage, DNA damage, and apoptosis of hGCCs. Further, curcumin-induced DNA demethylation of hGCCs was mediated by the damaged DNA repair-p53-p21/GADD45A-cyclin/CDK-Rb/E2F-DNMT1 axis. We propose that the anticancer effect of curcumin could largely be attributed to its prooxidative effect at high concentrations and ROS elevation in cancer cells. Moreover, we present a novel mechanism by which curcumin induces DNA demethylation of hGCCs, suggesting the need to further investigate the demethylation mechanisms of other DNA hypomethylating drugs.
Cigarettes smoking and IL-17A contribute to chronic obstructive pulmonary disease (COPD), and have synergistical effect on bronchial epithelial cell proliferation. CCAAT/enhancer-binding protein β ...(C-EBPβ) could be induced by IL-17A and is up-regulated in COPD. We explored the effect of cigarettes and IL-17 on bronchial epithelial-mesenchymal transition (EMT) in COPD mice and potential mechanism involved with C-EBPβ in this study.
COPD model was established with mice by exposing to cigarettes. E-Cadherin, Vimentin, IL-17A and C-EBPβ distributions were detected in lung tissues. Primary bronchial epithelial cells were separated from health mice and cocultured with cigarette smoke extract (CSE) or/and IL-17A. E-Cadherin, Vimentin and IL-17 receptor (IL-17R) expressions in vitro were assessed. When C-EBPβ were silenced by siRNA in cells, E-Cadherin, Vimentin and C-EBPβ expressions were detected.
E-Cadherin distribution was less and Vimentin distribution was more in bronchus of COPD mice than controls. IL-17A and C-EBPβ expressions were higher in lung tissues of COPD mice than controls. In vitro, C-EBPβ protein expression was highest in CSE + IL-17A group, followed by CSE and IL-17A groups. E-cadherin expression in vitro was lowest and Vimentin expression was highest in CSE + IL-17A group, followed by CSE or IL-17A group. Those could be inhibited by C-EBPβ silenced.
C-EBPβ mediates in cigarette/IL-17A-induced bronchial EMT in COPD mice. Our findings contribute to a better understanding on the progress from COPD to lung cancers, which will provide novel avenues in preventing tumorigenesis of airway in the context of cigarette smoking.
The gastrointestinal (GI) tract is more vulnerable to effects by the outside environment, and experiences oxidative stress. A wide diversity of GI disorders can be partially attributed to oxidative ...stress. However, the mechanism of oxidative stress-caused GI pathological changes is not clear. In the present study, human gastric epithelial cells (hGECs) were treated with hydrogen peroxide (H2O2), and oxidative stress was determined. The effect of oxidative stress on the levels of some antioxidative enzymes, proliferation, nuclear DNA damage, apoptosis, expression of ten-eleven translocation (TET), and level of DNA methylation was determined in these cells. The results showed that H2O2 treatment caused oxidative stress, increased the levels of superoxide dismutase (SOD), catalase (CAT), and malondialdehyde (MDA), decreased the level of glutathione (GSH), inhibited proliferation, caused nuclear DNA damage and apoptosis, upregulated the expression of TET1 gene, and ultimately led to active DNA demethylation in hGECs. The present study presents a mechanism by which oxidative stress induces active DNA demethylation in hGECs. We propose that TET inhibitors can be used to restore the oxidative stress-induced DNA demethylation, and thus inhibit possible malignant transformation of GI cells.
Influenza outbreaks pose a significant threat to global public health. Traditional surveillance systems and simple algorithms often struggle to predict influenza outbreaks in an accurate and timely ...manner. Big data and modern technology have offered new modalities for disease surveillance and prediction. Influenza-like illness can serve as a valuable surveillance tool for emerging respiratory infectious diseases like influenza and COVID-19, especially when reported case data may not fully reflect the actual epidemic curve. This study aimed to develop a predictive model for influenza outbreaks by combining Baidu search query data with traditional virological surveillance data. The goal was to improve early detection and preparedness for influenza outbreaks in both northern and southern China, providing evidence for supplementing modern intelligence epidemic surveillance methods. We collected virological data from the National Influenza Surveillance Network and Baidu search query data from January 2011 to July 2018, totaling 3,691,865 and 1,563,361 respective samples. Relevant search terms related to influenza were identified and analyzed for their correlation with influenza-positive rates using Pearson correlation analysis. A distributed lag nonlinear model was used to assess the lag correlation of the search terms with influenza activity. Subsequently, a predictive model based on the gated recurrent unit and multiple attention mechanisms was developed to forecast the influenza-positive trend. This study revealed a high correlation between specific Baidu search terms and influenza-positive rates in both northern and southern China, except for 1 term. The search terms were categorized into 4 groups: essential facts on influenza, influenza symptoms, influenza treatment and medicine, and influenza prevention, all of which showed correlation with the influenza-positive rate. The influenza prevention and influenza symptom groups had a lag correlation of 1.4-3.2 and 5.0-8.0 days, respectively. The Baidu search terms could help predict the influenza-positive rate 14-22 days in advance in southern China but interfered with influenza surveillance in northern China. Complementing traditional disease surveillance systems with information from web-based data sources can aid in detecting warning signs of influenza outbreaks earlier. However, supplementation of modern surveillance with search engine information should be approached cautiously. This approach provides valuable insights for digital epidemiology and has the potential for broader application in respiratory infectious disease surveillance. Further research should explore the optimization and customization of search terms for different regions and languages to improve the accuracy of influenza prediction models.
Recent studies have demonstrated that macrophage migration inhibitory factor (MIF) is of importance in asthmatic inflammation. The role of MIF in modulating airway remodeling has not yet been ...thoroughly elucidated to date. In the present study, we hypothesized that MIF promoted airway remodeling by intensifying airway smooth muscle cell (ASMC) autophagy and explored the specific mechanisms.
MIF knockdown in the lung tissues of C57BL/6 mice was conducted by instilling intratracheally adeno-associated virus (AAV) vectors (MIF-mutant AAV9) into mouse lung tissues. Mice genetically deficient in the autophagy marker ATG5 (ATG5
) was used to detect the role of autophagy in ovalbumin (OVA)-asthmatic murine models. Moreover, to block the expression of MIF and CD74
models, inhibitors, antibodies and lentivirus transfection techniques were employed.
First, MIF knockdown in the lung tissues of mice showed markedly reduced airway remodeling in OVA murine mice models. Secondly, ASMC autophagy was increased in the OVA-challenged models. Mice genetically deficient in the autophagy marker ATG5 (ATG5
) that were primed and challenged with OVA showed lower airway remodeling than genetically wild-type asthmatic mice. Thirdly, MIF can induce ASMC autophagy
. Moreover, the cellular source of MIF which promoted ASMC autophagy was macrophages. Finally, MIF promoted ASMC autophagy in a CD74-dependent manner.
MIF can increase asthmatic airway remodeling by enhancing ASMC autophagy. Macrophage-derived MIF can promote ASMC autophagy by targeting CD74.
In megacities, there is an urgent need to establish more sensitive forecasting and early warning methods for acute respiratory infectious diseases. Existing prediction and early warning models for ...influenza and other acute respiratory infectious diseases have limitations and therefore there is room for improvement.
The aim of this study was to explore a new and better-performing deep-learning model to predict influenza trends from multisource heterogeneous data in a megacity.
We collected multisource heterogeneous data from the 26th week of 2012 to the 25th week of 2019, including influenza-like illness (ILI) cases and virological surveillance, data of climate and demography, and search engines data. To avoid collinearity, we selected the best predictor according to the weight and correlation of each factor. We established a new multiattention-long short-term memory (LSTM) deep-learning model (MAL model), which was used to predict the percentage of ILI (ILI%) cases and the product of ILI% and the influenza-positive rate (ILI%×positive%), respectively. We also combined the data in different forms and added several machine-learning and deep-learning models commonly used in the past to predict influenza trends for comparison. The R
value, explained variance scores, mean absolute error, and mean square error were used to evaluate the quality of the models.
The highest correlation coefficients were found for the Baidu search data for ILI% and for air quality for ILI%×positive%. We first used the MAL model to calculate the ILI%, and then combined ILI% with climate, demographic, and Baidu data in different forms. The ILI%+climate+demography+Baidu model had the best prediction effect, with the explained variance score reaching 0.78, R
reaching 0.76, mean absolute error of 0.08, and mean squared error of 0.01. Similarly, we used the MAL model to calculate the ILI%×positive% and combined this prediction with different data forms. The ILI%×positive%+climate+demography+Baidu model had the best prediction effect, with an explained variance score reaching 0.74, R
reaching 0.70, mean absolute error of 0.02, and mean squared error of 0.02. Comparisons with random forest, extreme gradient boosting, LSTM, and gated current unit models showed that the MAL model had the best prediction effect.
The newly established MAL model outperformed existing models. Natural factors and search engine query data were more helpful in forecasting ILI patterns in megacities. With more timely and effective prediction of influenza and other respiratory infectious diseases and the epidemic intensity, early and better preparedness can be achieved to reduce the health damage to the population.
This study aimed to investigate the changes in the willingness of guardians to administer the COVID-19 vaccine to their children, allow the coadministration of other vaccines, and administer the ...COVID-19 vaccine booster dose. This was a follow-up study conducted 6 months after a similar previous study. The self-administered questionnaire was distributed through the "Xiao Dou Miao" app and 9424 guardians with access to this app participated in the survey that was conducted from September 15 to October 8, 2021. Of all the participating guardians, 86.68% were willing to vaccinate their children with the COVID-19 vaccine, which was approximately 16% more than those in our previous study. Guardians aged ≥40 years, healthcare workers, and those with children aged ≥3 years were more willing to vaccinate their children. Approximately 77% of the guardians were willing toward the coadministration of COVID-19 and influenza vaccines. Approximately 64% of the guardians were willing toward the coadministration of other nonimmunization program vaccines with the COVID-19 vaccine for their children. The primary reasons for reluctance toward the coadministration of vaccines were concerns about vaccine safety and effectiveness. If necessary, 92% of the guardians were willing to receive a COVID-19 vaccine booster and 82% were willing to vaccinate their children with a COVID-19 vaccine booster. We hope that this research will facilitate the formulation of successful strategies for the implementation of COVID-19 vaccinations, covaccinations, and COVID-19 booster doses, particularly for children aged <6 years.
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