BackgroundMiR-301a and miR-301b are 2 oncomiRs involved in multiple types of cancer. In this study, we explored the expression change of miR-301a and miR-301b in prostate cancer cells in hypoxia and studied their regulation of autophagy and radiosensitivity of prostate cancer cells.Material/MethodsQRT-PCR was performed to quantify the expression change of miR-301a and miR-301b in hypoxia. Their effects on autophagy were measured by Western blot analysis, and their effects on radiosensitivity were measured by clonogenic assay and flow cytometry. In addition, the regulation of miR-301a and miR-301b on NDRG2, a tumor-suppressor gene in prostate cancer, was also studied. The effect of miR-301a/b-NDRG2 axis on autophagy and radiosensitivity of prostate cancer cells was further investigated.ResultsMiR-301a and miR-301b are 2 hypoxia responsive miRNAs that are significantly upregulated in hypoxia in prostate cancer cells. Higher level of miR-301a and miR-301b expression results in elevated autophagy and increased radioresistance in LNCaP cells. MiR-301a and miR-301b simultaneously target NDRG2 and decrease its expression. Knockdown of NDRG2 leads to increased autophagy and radioresistance.ConclusionsMiR-301a and miR-301b are 2 hypoxia-responsive miRNAs that decrease autophagy of prostate cancer cells in hypoxia by targeting NDRG2. Through downregulating NDRG2, miR-301a and miR-301b can promote radioresistance of prostate cancer cells.

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The aim of this study was to explore the diagnostic value of magnetic resonance imaging (MRI) for levamisole-induced demyelinating leukoencephalopathy. The clinical features and MRI findings of 15 patients with levamisole-induced demyelinating leukoencephalopathy were retrospectively analyzed. The abnormality rate of the patients was demonstrated to be 100% by MRI, and scattered multiple cerebral foci were observed in all of the patients. The majority of the foci were located at the centrum ovale, peri-lateral cerebral ventricles and basal ganglia, while the remainder were located in the brain stem and cerebellum, as well as in the white matter regions of the temporal, frontal, apical and occipital lobes. In addition, mottling and ring-shaped enhancements were observed. The study demonstrated that MRI effectively displays demyelinating leukoencephalopathy, and that the combination of MRI with the medical history of the patient is of significance for the early diagnosis, differentiation and treatment of demyelinating leukoencephalopathy.

ObjectiveAnalyzing the symptom characteristics of Coronavirus Disease 2019(COVID‐19) to improve control and prevention.MethodsUsing the Baidu Index Platform (http://index.baidu.com) and the website of Chinese Center for Disease Control and Prevention as data resources to obtain the search volume (SV) of keywords for symptoms associated with COVID‐19 from January 1 to February 20 in each year from 2017 to 2020 and the epidemic data in Hubei province and the other top 9 impacted provinces in China. Data of 2020 were compared with those of the previous three years. Data of Hubei province were compared with those of the other 9 provinces. The differences and characteristics of the SV of COVID‐19‐related symptoms, and the correlations between the SV of COVID‐19 and the number of newly confirmed/suspected cases were analyzed. The lag effects were discussed.ResultsComparing the SV from January 1, 2020 to February 20, 2020 with those for the same period of the previous three years, Hubei's SV for cough, fever, diarrhea, chest tightness, dyspnea, and other symptoms were significantly increased. The total SV of lower respiratory symptoms was significantly higher than that of upper respiratory symptoms (P＜0.001). The SV of COVID‐19 in Hubei province was significantly correlated with the number of newly confirmed/suspected cases (rconfirmed = 0.723, rsuspected = 0.863, both p < 0.001). The results of the distributed lag model suggested that the patients who searched relevant symptoms on the Internet may begin to see doctors in 2–3 days later and be confirmed in 3–4 days later.ConclusionThe total SV of lower respiratory symptoms was higher than that of upper respiratory symptoms, and the SV of diarrhea also increased significantly. It warned us to pay attention to not only the symptoms of the lower respiratory tract but also the gastrointestinal symptoms, especially diarrhea in patients with COVID‐19. Internet search behavior had a positive correlation with the number of newly confirmed/suspected cases, suggesting that big data has an important role in the early warning of infectious diseases.

<b><i>Introduction:</i></b> Compared with the placebo, biologics are beneficial in reducing nasal polyp mass and safe in patients with chronic rhinosinusitis with nasal polyps (CRSwNP). However, there lacks a head-to-head randomized trial comparing biologics. We aimed to determine the best biologic for CRSwNP. <b><i>Methods:</i></b> We performed a systematic review and network meta-analysis (NMA), which was registered with PROSPERO (No. CRD42021226766). A comprehensive search was performed in PubMed, Embase, Web of Science, and the Cochrane Library on December 29, 2020. Only randomized controlled trials (RCTs) assessing biologics in adult patients for CRSwNP were included. <b><i>Results:</i></b> Nine RCTs with 1,190 patients comparing 3 different biologics (dupilumab, omalizumab, and mepolizumab) and the placebo were included. Dupilumab had the best efficacy in terms of nasal polyp score (NPS), Sino-Nasal Outcome Test-22 (SNOT-22) score, University of Pennsylvania Smell Identification Test (UPSIT) score, and nasal congestion score (NCS) for surface under the cumulative ranking curve (SUCRA) values of 0.900, 0.916, 1.000, and 0.807, respectively. Omalizumab ranked second in efficacy in terms of SNOT-22, UPSIT, and NCS for SUCRA values of 0.606, 0.500, and 0.693, respectively. Mepolizumab ranked second in efficacy in terms of NPS for SUCRA values of 0.563 and had the highest risk of adverse events (AEs) for SUCRA values of 0.746. <b><i>Conclusion:</i></b> This is the first NMA that compared different biologics in patients with CRSwNP. Based on the efficacy (NPS) and safety (AEs), dupilumab is the best choice and omalizumab is the second best option for CRSwNP. Although mepolizumab ranked second in efficacy, it had the highest risk of AEs.

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Background artificial intelligence (AI) for cellular phenotyping diagnosis of nasal polyps by whole-slide imaging (WSI) is lacking. We aim to establish an AI chronic rhinosinusitis evaluation platform 2.0 (AICEP 2.0) to obtain the proportion of inflammatory cells for cellular phenotyping diagnosis of nasal polyps and to explore the clinical significance of different phenotypes of nasal polyps on the WSI. Methods a total of 453 patients were enrolled in our study. For the development of AICEP 2.0, 179 patients (WSIs) were obtained from the Third Affiliated Hospital of Sun Yat-Sen University (3HSYSU) from January 2008 to December 2018. A total of 24,625 patches were automatically extracted from the regions of interest under a 400× HPF by Openslide and the number of inflammatory cells in these patches was counted by two pathologists. For the application of AICEP 2.0 in a prospective cohort, 158 patients aged 14–70 years old with chronic rhinosinusitis with nasal polyps (CRSwNP) who had undergone endoscopic sinus surgery at 3HSYSU from June 2020 to December 2020 were included for preoperative demographic characteristics. For the application of AICEP 2.0 in a retrospective cohort, 116 patients with CRSwNP who had undergone endoscopic sinus surgery from May 2016 to June 2017 were enrolled for the recurrence rate. The proportion of inflammatory cells of these patients on WSI was calculated by our AICEP 2.0. Findings for AICEP 2.0, the mean absolute errors of the ratios of eosinophils, lymphocytes, neutrophils, and plasma cells were 1.64%, 2.13%, 1.06%, and 1.22%, respectively. The four phenotypes of nasal polyps were significantly different in clinical characteristics (including asthma, itching, sneezing, total IgE, peripheral eosinophils%, tissue eosinophils%, tissue neutrophils%, tissue lymphocytes%, tissue plasma cells%, and recurrence rate; P <0.05), but there were no significant differences in age distribution, onset time, total VAS score, Lund-Kennedy score, or Lund-Mackay score. The percentage of peripheral eosinophils was positively correlated with the percentage of tissue eosinophils ( r = 0.560, P <0.001) and negatively correlated with tissue lymphocytes% ( r = -0.489, P <0.001), tissue neutrophils% ( r = -0.225, P = 0.005), and tissue plasma cells% ( r = -0.266, P = 0.001) in WSIs.