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1.
Nanoscale ; 13(37): 15576-15589, 2021 Oct 01.
Artigo em Inglês | MEDLINE | ID: mdl-34524338

RESUMO

Multifunctional nanoagents integrating multiple therapeutic and imaging functions hold promise in the field of non-invasive and precise tumor therapies. However, the complex preparation process and uncertain drug metabolism of nanoagents loaded with various therapeutic agents or imaging agents greatly hinder its clinical applications. Developing simple and effective nanoagents that integrate multiple therapeutic and imaging functions remain a huge challenge. Therefore, a novel strategy based on in situ hydrogen release is proposed in this work: aminoborane (AB) was loaded onto mesoporous polydopamine nanoparticles (MPDA NPs) as a prodrug for hydrogen production, and then, PEG was modified on the surface of nanoparticles (represented as AB@MPDA-PEG). MPDA NPs not only act as photothermal agents (PTA) with high photothermal conversion efficiency (808 nm, η = 38.72%) but also as the carriers of AB accumulated in the tumor through enhanced permeability and retention (EPR) effect. H2 gas generated by AB in the weak acid conditions of the tumor microenvironment (TME) not only was used to treat tumors via a combination of hydrogen and photothermal therapies but also serves as a US and CT contrast agent, providing accurate guidance for tumor treatment. Finally, in vivo and in vitro investigation suggest that the designed multifunctional nanosystem not only showed excellent properties such as high hydrogen-loading capacity, long-lasting sustained hydrogen release ability and excellent biocompatibility but also achieve selective PTT/hydrogen therapies and US/CT bimodal imaging functions, which can effectively guide antitumor therapies. The proposed hydrogen gas-based strategy for combination therapies and bimodal imaging integration holds promise as an efficient and safe tumor treatment for future clinical translation.


Assuntos
Hipertermia Induzida , Nanopartículas , Neoplasias , Terapia Combinada , Humanos , Hidrogênio , Neoplasias/terapia , Fototerapia , Microambiente Tumoral
2.
J Cancer ; 12(13): 3819-3826, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34093790

RESUMO

Lung cancer is one of the most common malignant tumors in the world, and the mortality rate ranks first among various malignant tumors. GTP-binding proteins (guanosine 5'-triphosphate-binding proteins, GTPBPs) are a type of protein with signal transduction function, have GTP hydrolase activity, and play an important role in cell signal transmission, cytoskeletal regulation, protein synthesis and other activities. GTPBP2 is one of the members of the G protein superfamily. Research on GTPBP2 is currently focused on human genetics, and its research in tumors has not been reported. First, Western blot and quantitative real-time PCR were used to analyze the expression differences of 12 cases of GTPBP2 in human NSCLC fresh cancer tissues and adjacent tissues. Then we selected 112 cases of NSCLC cancer tissues and 65 adjacent tissues for immunohistochemistry experiments to analyze the relationships between the expression of GTPBP2 and clinical pathological parameters and prognosis, we found that GTPBP2 is highly expressed in NSCLC cancer tissues, and the high expression of GTPBP2 is related to pTNM stage and lymph node metastasis. In addition, after GTPBP2 knockdown, GTPBP2 can promote the proliferation and invasion of NSCLC cell lines by up-regulating RhoC and MMP-9, and up-regulate cyclinD1, CDK4 and c-myc, and down-regulate P27 to promote the invasion of NSCLC cell lines. In addition, GTPBP2 negatively regulates Axin to promote ß-catenin expression, thereby activating Wnt/ß-catenin signaling, and promoting the occurrence of NSCLC.

3.
Preprint em Inglês | bioRxiv | ID: ppbiorxiv-434764

RESUMO

The global emergence of SARS-CoV-2 has triggered numerous efforts to develop therapeutic options for COVID-19 pandemic. The main protease of SARS-CoV-2 (Mpro), which is a critical enzyme for transcription and replication of SARS-CoV-2, is a key target for therapeutic development against COVID-19. An organoselenium drug called ebselen has recently been demonstrated to have strong inhibition against Mpro and antiviral activity but its molecular mode of action is unknown preventing further development. We have examined the binding modes of ebselen and its derivative in Mpro via high resolution co-crystallography and investigated their chemical reactivity via mass spectrometry. Stronger Mpro inhibition than ebselen and potent ability to rescue infected cells were observed for a number of ebselen derivatives. A free selenium atom bound with cysteine 145 of Mpro catalytic dyad has been revealed by crystallographic studies of Mpro with ebselen and MR6-31-2 suggesting hydrolysis of the enzyme bound organoselenium covalent adduct, formation of a phenolic by-product is confirmed by mass spectrometry. The target engagement of these compounds with an unprecedented mechanism of SARS-CoV-2 Mpro inhibition suggests wider therapeutic applications of organo-selenium compounds in SARS-CoV-2 and other zoonotic beta-corona viruses.

4.
Front Psychiatry ; 12: 566241, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33658949

RESUMO

Background: During the coronavirus disease 2019 (COVID-19) pandemic, quarantine as an effective public health measure has been widely used in China and elsewhere to slow down the spread, while high-risk psychological response populations remain under-reported. Objective: The aim of the study is to investigate the depressive and anxiety symptoms among the high-risk individuals quarantined during the COVID-19 pandemic in China. Methods: An online survey was conducted from February 29 to April 10, 2020, among individuals quarantined for at least 2 weeks due to the high-risk exposure. Chinese versions of the nine-item Patient Health Questionnaire (PHQ-9) with a seven-item Generalized Anxiety Disorder (GAD-7) were applied to assess depressive and anxiety symptoms, respectively. Compliance with quarantine and knowledge of COVID-19 was also assessed. An unconditional logistic regression model was performed to identify the correlators. Results: Of the 1,260 participants completing the full survey, 14.0% (95% CI: 12.2-16.1%), 7.1% (95% CI: 5.9-8.7%), and 6.3% (95% CI: 5.1-7.8%) had at least moderate symptoms of depression, anxiety, and a combination of depression and anxiety (CDA), respectively; 14.8% (95% CI: 13.0-16.9%) had at least one condition. Multivariate analysis showed that participants with an undergraduate or above degree were more likely to report depressive (OR = 2.98, 95% CI: 1.56-5.72) and anxiety symptoms (OR = 2.95, 95% CI: 1.14-7.63) than those with middle school education. Those who were unemployed (OR = 0.37, 95% CI: 0.21-0.65 for depression; OR = 0.31, 95% CI: 0.14-0.73 for anxiety), students (OR = 0.14, 95% CI: 0.04-0.48 for depression; OR = 0.11, 95% CI: 0.01-0.85 for anxiety), and more knowledgeable of COVID-19 (OR = 0.84, 95% CI: 0.73-0.96 for depression, OR = 0.82, 95% CI: 0.68-0.98 for anxiety) were less likely to report depressive and anxiety symptoms. Higher quarantine compliance correlated with lower risks of depressive (OR = 0.94, 95% CI: 0.91-0.96) and anxiety symptoms (OR = 0.95, 95% CI: 0.91-0.98). Conclusion: Individuals under quarantine during the COVID-19 pandemic suffered prevalent depressive and anxiety symptoms. Consequently, comprehensive interventional measures, including knowledge dissemination, timely virus tests, and strengthened communication, may minimize quarantine's adverse effects.

5.
Clin Exp Pharmacol Physiol ; 48(2): 279-287, 2021 02.
Artigo em Inglês | MEDLINE | ID: mdl-33030246

RESUMO

Nucleotide metabolism is the driving force of cell proliferation, and thymidylate synthase (TYMS) catalyzes a rate-limiting step in the initial synthesis of nucleotides. Previous studies reported that TYMS activity significantly affected the proliferation of tumour cells. However, the diagnostic and prognostic significance of TYMS expression in breast cancer remains unclear. Here, we used the Breast Cancer Integrative Platform (BCIP) to investigate the relationship between progression and prognosis of breast cancer with TYMS expression, and then verified the database analysis using immunohistochemical staining. Our results indicated TYMS expression was greater in breast cancer than adjacent normal tissues and greater in triple-negative breast cancer (TNBC) than non-TNBC tissues. TYMS expression also had significant positive correlations with histological grade, tumour size, and ER negativity, and PR negativity. The increased copy number of the TYMS gene appears to be the reason for its upregulation in breast cancer. Breast cancer patients with higher TYMS expression had poorer prognosis. Our data suggest that TYMS has potential use as a diagnostic and prognostic marker for breast cancer patients.

6.
Zhongguo Zhong Yao Za Zhi ; 45(20): 4819-4826, 2020 Oct.
Artigo em Chinês | MEDLINE | ID: mdl-33350252

RESUMO

Flavones are widely distributed in terrestrial plants and act as important bioactive compounds in medicinal plants. Baicalein, wogonin and their glycosides baicalin and wogonoside are major active components found in medicinal plant Scutellaria baicalensis. These flavones can induce apoptosis in various cancer cell lines, with such pharmacological activities as anti-oxidation, antivirus and liver protection. In recent years, the biosynthesis pathways of flavones in Scutellaria have been studied thoroughly. In particular, the biosynthesis pathways of baicalein and wogonin in S. baicalensis were interpreted completely. In this review, the biosynthesis of flavones in Scutellaria, the regulation of environmental factors and elicitors on their biosynthesis, and the metabolic engineering of the flavones were discussed.


Assuntos
Flavanonas , Flavonas , Plantas Medicinais , Scutellaria , Flavonoides , Glicosídeos , Extratos Vegetais , Raízes de Plantas , Scutellaria baicalensis
7.
Minerva Med ; 2020 Oct 13.
Artigo em Inglês | MEDLINE | ID: mdl-33047939

RESUMO

BACKGROUND: Signal transducer and activator of transcription 3 (STAT3) plays a pivotal role in osteoblastic differentiation. However, the exact role of STAT3 in osteogenic differentiation of the pre-osteoblastic cell line MC3T3-E1 is still controversial. In this study, we demonstrated that eradication of STAT3 signaling by the inhibitors cryptotanshinone (CPT, a STAT3-specific inhibitor) or STAT3 siRNA both suppressed osteogenic differentiation of MC3T3-E1 cells, with a decrease in alkaline phosphatase (ALP) activity, protein expressions of the osteogenic differentiation markers Collagen I (ColI), ALP, and osteocalcin (OCN), and reduced matrix mineralization capacity at the terminal stage of osteogenic differentiation. However, the inhibition of STAT3 by CPT did not affect MC3T3-E1 cell proliferation. METHODS: To further clarify the effect of STAT3 on osteogenic differentiation of MC3T3-E1 cells, we forced STAT3 expression and found that this ameliorated osteogenic differentiation. RESULTS: Thus, our results confirmed that STAT3 is a likely positive regulator of osteogenic differentiation in MC3T3-E1 cells. CONCLUSIONS: These findings may provide a basis for the development of more efficient and controllable protocols for osteoblastic differentiation and facilitate their use in regenerative medicine. In addition, our results provide novel insights into the effect of the STAT3 antagonist CPT on modulation of osteogenesis.

8.
J Cell Mol Med ; 24(22): 12980-12993, 2020 11.
Artigo em Inglês | MEDLINE | ID: mdl-33002329

RESUMO

Epilepsy is a chronic brain disease characterized by recurrent seizures. Circular RNA (circRNA) is a novel family of endogenous non-coding RNAs that have been proposed to regulate gene expression. However, there is a lack of data on the role of circRNA in epilepsy. In this study, the circRNA profiles were evaluated by microarray analysis. In total, 627 circRNAs were up-regulated, whereas 892 were down-regulated in the hippocampus in mice with kainic acid (KA)-induced epileptic seizures compared with control. The expression of circHivep2 was significantly down-regulated in hippocampus tissues of mice with KA-induced epileptic seizures and BV-2 microglia cells upon KA treatment. Bioinformatics analysis predicted that circHivep2 interacts with miR-181a-5p to regulate SOCS2 expression, which was validated using a dual-luciferase reporter assay. Moreover, overexpression of circHivep2 significantly inhibited KA-induced microglial activation and the expression of inflammatory factors in vitro, which was blocked by miR-181a-5p, whereas circHivep2 knockdown further induced microglia cell activation and the release of pro-inflammatory proteins in BV-2 microglia cells after KA treatment. The application of circHivep2+ exosomes derived from adipose-derived stem cells (ADSCs) exerted significant beneficial effects on the behavioural seizure scores of mice with KA-induced epilepsy compared to control exosomes. The circHivep2+ exosomes also inhibited microglial activation, the expression of inflammatory factors, and the miR-181a-5p/SOCS2 axis in vivo. Our results suggest that circHivep2 regulates microglia activation in the progression of epilepsy by interfering with miR-181a-5p to promote SOCS2 expression, indicating that circHivep2 may serve as a therapeutic tool to prevent the development of epilepsy.


Assuntos
Proteínas de Ligação a DNA/genética , Inflamação/tratamento farmacológico , MicroRNAs/metabolismo , Microglia/efeitos dos fármacos , RNA Circular/genética , Convulsões/metabolismo , Proteínas Supressoras da Sinalização de Citocina/metabolismo , Adipócitos/metabolismo , Animais , Biotinilação , Linhagem Celular , Epilepsia/metabolismo , Exossomos/metabolismo , Perfilação da Expressão Gênica , Regulação da Expressão Gênica , Hipocampo/metabolismo , Hibridização in Situ Fluorescente , Ácido Caínico , Masculino , Camundongos , Camundongos Endogâmicos C57BL , Análise de Sequência com Séries de Oligonucleotídeos , RNA Longo não Codificante/genética , Convulsões/induzido quimicamente , Transdução de Sinais
9.
Front Neuroanat ; 14: 36, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32792914

RESUMO

Neuron apoptosis in ischemic penumbra was proved to be involved in ischemic stroke (IS) development and contributed to the poor prognosis of IS. Recent studies showed that aberrant trimethylation of histone H3 lysine 4 (H3K4me3) level was associated with cell apoptosis. This study aimed to explore the underlying mechanism of neuron apoptosis in ischemic penumbra via histone methyltransferase (HMT) mixed lineage leukemia 1 (MLL1) mediated epigenetic pathway. Mouse IS model was established by middle cerebral artery occlusion (MCAO). Mouse primary cortical mixed cells were cultured and treated with oxygen-glucose deprivation (OGD) to simulate IS process. The expressions of apoptosis signal regulating kinase-1 (ASK-1), pASK-1, cleaved caspase-3, ASK-1/serine-threonine kinase receptor-associated protein (STRAP)/14-3-3 complex, ASK-1/tumor necrosis factor-α (TNF-α) complex, and MLL1 in mouse brain tissue and mouse primary cortical mixed cells were analyzed. The function of MLL1 was investigated using small interfering RNA (siRNA) targeting MLL1 and vector overexpressing MLL1. In vivo inhibition of MLL1 was conducted to explore its value as a therapeutic target. The prognostic value of MLL1 was investigated in IS patients. Results showed that the expressions of ASK-1, pASK-1, cleaved caspase-3, ASK-1/TNF-α complex, and MLL1 increased significantly in ischemic penumbra compared to brain tissue from the control group (P < 0.05). MCAO and OGD significantly upregulated the H3K4me3 level in ASK-1 promoter region and promoted the recruitment of MLL1 to this region (P < 0.05). siMLL1 significantly reversed the proapoptosis effects of OGD in primary cortical mixed cells, while MLL1 overexpression induced apoptosis of cells (P < 0.05). In vivo inhibition of MLL1 significantly reduced the infarct volume and the neurological score of MCAO mice (P < 0.05). Serum MLL1 level had a positive association with that in ischemic core and penumbra in mouse model and was positively correlated with the infarct volume and neurological score (P < 0.05). Besides, serum MLL1 level was also significantly correlated with the severity of IS (P < 0.05), and high serum MLL1 level indicated poor prognosis of IS patients (P < 0.05). These results revealed that MLL1 contributed to neuron cell apoptosis in ischemic penumbra after IS onset by promoting the formation of ASK-1/TNF-α complex, and its serum level was associated with poor prognosis of IS.

10.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-20176776

RESUMO

Effectively identifying COVID-19 patients using non-PCR clinical data is critical for the optimal clinical outcomes. Currently, there is a lack of comprehensive understanding of various biomedical features and appropriate technical approaches to accurately detecting COVID-19 patients. In this study, we recruited 214 confirmed COVID-19 patients in non-severe (NS) and 148 in severe (S) clinical type, 198 non-infected healthy (H) participants and 129 non-COVID viral pneumonia (V) patients. The participants clinical information (23 features), lab testing results (10 features), and thoracic CT scans upon admission were acquired as three input feature modalities. To enable late fusion of multimodality data, we developed a deep learning model to extract a 10-feature high-level representation of the CT scans. Exploratory analyses showed substantial differences of all features among the four classes. Three machine learning models (k-nearest neighbor kNN, random forest RF, and support vector machine SVM) were developed based on the 43 features combined from all three modalities to differentiate four classes (NS, S, V, and H) at once. All three models had high accuracy to differentiate the overall four classes (95.4%-97.7%) and each individual class (90.6%-99.9%). Multimodal features provided substantial performance gain from using any single feature modality. Compared to existing binary classification benchmarks often focusing on single feature modality, this study provided a novel and effective breakthrough for clinical applications. Findings and the analytical workflow can be used as clinical decision support for current COVID-19 and other clinical applications with high-dimensional multimodal biomedical features. One sentence summaryWe trained and validated late fusion deep learning-machine learning models to predict non-severe COVID-19, severe COVID-19, non-COVID viral infection, and healthy classes from clinical, lab testing, and CT scan features extracted from convolutional neural network and achieved predictive accuracy of > 96% to differentiate all four classes at once based on a large dataset of 689 participants.

11.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-20163402

RESUMO

BackgroundThe outbreak of coronavirus disease 2019 (COVID-19) has become a global pandemic acute infectious disease, especially with the features of possible asymptomatic carriers and high contagiousness. It causes acute respiratory distress syndrome and results in a high mortality rate if pneumonia is involved. Currently, it is difficult to quickly identify asymptomatic cases or COVID-19 patients with pneumonia due to limited access to reverse transcription-polymerase chain reaction (RT-PCR) nucleic acid tests and CT scans, which facilitates the spread of the disease at the community level, and contributes to the overwhelming of medical resources in intensive care units. GoalThis study aimed to develop a scientific and rigorous clinical diagnostic tool for the rapid prediction of COVID-19 cases based on a COVID-19 clinical case database in China, and to assist global frontline doctors to efficiently and precisely diagnose asymptomatic COVID-19 patients and cases who had a false-negative RT-PCR test result. MethodsWith online consent, and the approval of the ethics committee of Zhongshan Hospital Fudan Unversity (approval number B2020-032R) to ensure that patient privacy is protected, clinical information has been uploaded in real-time through the New Coronavirus Intelligent Auto-diagnostic Assistant Application of cloud plus terminal (nCapp) by doctors from different cities (Wuhan, Shanghai, Harbin, Dalian, Wuxi, Qingdao, Rizhao, and Bengbu) during the COVID-19 outbreak in China. By quality control and data anonymization on the platform, a total of 3,249 cases from COVID-19 high-risk groups were collected. These patients had SARS-CoV-2 RT-PCR test results and chest CT scans, both of which were used as the gold standard for the diagnosis of COVID-19 and COVID-19 pneumonia. In particular, the dataset included 137 indeterminate cases who initially did not have RT-PCR tests and subsequently had positive RT-PCR results, 62 suspected cases who initially had false-negative RT-PCR test results and subsequently had positive RT-PCR results, and 122 asymptomatic cases who had positive RT-PCR test results, amongst whom 31 cases were diagnosed. We also integrated the function of a survey in nCapp to collect user feedback from frontline doctors. FindingsWe applied the statistical method of a multi-factor regression model to the training dataset (1,624 cases) and developed a prediction model for COVID-19 with 9 clinical indicators that are fast and accessible: Residing or visiting history in epidemic regions, Exposure history to COVID-19 patient, Dry cough, Fatigue, Breathlessness, No body temperature decrease after antibiotic treatment, Fingertip blood oxygen saturation [≤]93%, Lymphopenia, and C-reactive protein (CRP) increased. The area under the receiver operating characteristic (ROC) curve (AUC) for the model was 0.88 (95% CI: 0.86, 0.89) in the training dataset and 0.84 (95% CI: 0.82, 0.86) in the validation dataset (1,625 cases). To ensure the sensitivity of the model, we used a cutoff value of 0.09. The sensitivity and specificity of the model were 98.0% (95% CI: 96.9%, 99.1%) and 17.3% (95% CI: 15.0%, 19.6%), respectively, in the training dataset, and 96.5% (95% CI: 95.1%, 98.0%) and 18.8% (95% CI: 16.4%, 21.2%), respectively, in the validation dataset. In the subset of the 137 indeterminate cases who initially did not have RT-PCR tests and subsequently had positive RT-PCR results, the model predicted 132 cases, accounting for 96.4% (95% CI: 91.7%, 98.8%) of the cases. In the subset of the 62 suspected cases who initially had false-negative RT-PCR test results and subsequently had positive RT-PCR results, the model predicted 59 cases, accounting for 95.2% (95% CI: 86.5%, 99.0%) of the cases. Considering the specificity of the model, we used a cutoff value of 0.32. The sensitivity and specificity of the model were 83.5% (95% CI: 80.5%, 86.4%) and 83.2% (95% CI: 80.9%, 85.5%), respectively, in the training dataset, and 79.6% (95% CI: 76.4%, 82.8%) and 81.3% (95% CI: 78.9%, 83.7%), respectively, in the validation dataset, which is very close to the published AI model. The results of the online survey Questionnaire Star showed that 90.9% of nCapp users in WeChat mini programs were satisfied or very satisfied with the tool. The WeChat mini program received a significantly higher satisfaction rate than other platforms, especially for availability and sharing convenience of the App and fast speed of log-in and data entry. DiscussionWith the assistance of nCapp, a mobile-based diagnostic tool developed from a large database that we collected from COVID-19 high-risk groups in China, frontline doctors can rapidly identify asymptomatic patients and avoid misdiagnoses of cases with false-negative RT-PCR results. These patients require timely isolation or close medical supervision. By applying the model, medical resources can be allocated more reasonably, and missed diagnoses can be reduced. In addition, further education and interaction among medical professionals can improve the diagnostic efficiency for COVID-19, thus avoiding the transmission of the disease from asymptomatic patients at the community level.

12.
Preprint em Inglês | bioRxiv | ID: ppbiorxiv-195008

RESUMO

BackgroundLittle is known about the SARS-CoV-2 contamination of environmental surfaces and air in non-health care settings among COVID-19 cases. Methods and findingsWe explored the SARS-CoV-2 contamination of environmental surfaces and air by collecting air and swabbing environmental surfaces among 39 COVID-19 cases in Guangzhou, China. The specimens were tested by RT-PCR testing. The information collected for COVID-19 cases included basic demographic, clinical severity, onset of symptoms, radiological testing, laboratory testing and hospital admission. A total of 641 environmental surfaces and air specimens were collected among 39 COVID-19 cases before disinfection. Among them, 20 specimens (20/641, 3.1%) were tested positive from 9 COVID-19 cases (9/39, 23.1%), with 5 (5/101, 5.0%) positive specimens from 3 asymptomatic cases, 5 (5/220, 2.3%) from 3 mild cases, and 10 (10/374, 2.7%) from 3 moderate cases. All positive specimens were collected within 3 days after diagnosis, and 10 (10/42, 23.8%) were found in toilet (5 on toilet bowl, 4 on sink/faucet/shower, 1 on floor drain), 4 (4/21, 19.0%) in anteroom (2 on water dispenser/cup/bottle, 1 on chair/table, 1 on TV remote), 1 (1/8, 12.5%) in kitchen (1 on dining-table), 1 (1/18, 5.6%) in bedroom (1 on bed/sheet pillow/bedside table), 1 (1/5, 20.0%) in car (1 on steering wheel/seat/handlebar) and 3 (3/20, 21.4%) on door knobs. Air specimens in room (0/10, 0.0%) and car (0/1, 0.0%) were all negative. ConclusionsSARS-CoV-2 was found on environmental surfaces especially in toilet, and could survive for several days. We provided evidence of potential for SARS-CoV-2 transmission through contamination of environmental surfaces.

13.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-20136531

RESUMO

BACKGROUNDRemdesivir, an inhibitor of viral RNA-dependent RNA polymerases, has been identified as a candidate for COVID-19 treatment. However, the therapeutic effect of remdesivir is controversial. METHODSWe searched PubMed, Embase, and the Cochrane Central Register of Controlled Trials, from inception to June 11, 2020 for randomized controlled trials on the clinical efficacy of remdesivir. The main outcomes were discharge rate, mortality, and adverse events. This study is registered at INPLASY (INPLASY202060046). RESULTSData of 1075 subjects showed that remdesivir significantly increased the discharge rate of patients with COVID-19 compared with the placebo (50.4% vs. 45.29%; relative risk [RR] 1.19 [95% confidence interval [CI], 1.05-1.34], I2 = 0.0%, P = 0.754). It also significantly decreased mortality (8.18% vs. 12.70%; RR 0.64 [95% CI, 0.44-0.92], I2 = 45.7%, P = 0.175) compared to the placebo. Data of 1296 subjects showed that remdesivir significantly decreased the occurrence of serious adverse events (RR 0.77 [95% CI, 0.63-0.94], I2 = 0.0%, P = 0.716). CONCLUSIONRemdesivir is efficacious and safe for the treatment of COVID-19. TRIAL REGISTRATION NUMBERThis study is registered at the International Platform of Registered Systematic Review and Meta-analysis Protocols (INPLASY202060046).

14.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-20105841

RESUMO

Effectively and efficiently diagnosing COVID-19 patients with accurate clinical type is essential to achieve optimal outcomes for the patients as well as reducing the risk of overloading the healthcare system. Currently, severe and non-severe COVID-19 types are differentiated by only a few clinical features, which do not comprehensively characterize complicated pathological, physiological, and immunological responses to SARS-CoV-2 invasion in different types. In this study, we recruited 214 confirmed COVID-19 patients in non-severe and 148 in severe type, from Wuhan, China. The patients comorbidity and symptoms (26 features), and blood biochemistry (26 features) upon admission were acquired as two input modalities. Exploratory analyses demonstrated that these features differed substantially between two clinical types. Machine learning random forest (RF) models using features in each modality were developed and validated to classify COVID-19 clinical types. Using comorbidity/symptom and biochemistry as input independently, RF models achieved >90% and >95% predictive accuracy, respectively. Input features importance based on Gini impurity were further evaluated and top five features from each modality were identified (age, hypertension, cardiovascular disease, gender, diabetes; D-Dimer, hsTNI, neutrophil, IL-6, and LDH). Combining top 10 multimodal features, RF model achieved >99% predictive accuracy. These findings shed light on how the human body reacts to SARS-CoV-2 invasion as a unity and provide insights on effectively evaluating COVID-19 patients severity and developing treatment plans accordingly. We suggest that symptoms and comorbidities can be used as an initial screening tool for triaging, while biochemistry and features combined are applied when accuracy is the priority. One Sentence SummaryWe trained and validated machine learning random forest (RF) models to predict COVID-19 severity based on 26 comorbidity/symptom features and 26 biochemistry features from a cohort of 214 non-severe and 148 severe type COVID-19 patients, identified top features from both feature modalities to differentiate clinical types, and achieved predictive accuracy of >90%, >95%, and >99% when comorbidity/symptom, biochemistry, and combined top features were used as input, respectively.

15.
Cancer Biol Med ; 17(1): 76-87, 2020 02 15.
Artigo em Inglês | MEDLINE | ID: mdl-32296577

RESUMO

Objective: Oncogenes have been shown to be drivers of non-small cell lung cancer (NSCLC), yet the tumor suppressing genes involved in lung carcinogenesis remain to be systematically investigated. This study aimed to identify tumor suppressing ubiquitin pathway genes (UPGs) that were critical to lung tumorigenesis. Methods: The 696 UPGs were silenced by an siRNA screening in NSCLC cells; the potential tumor suppressing UPGs were analyzed, and their clinical significance was investigated. Results: We reported that silencing of 11 UPGs resulted in enhanced proliferation of NSCLC cells, and four UPGs (UBL3, TRIM22, UBE2G2, and MARCH1) were significantly downregulated in tumor samples compared to that in normal lung tissues and their expression levels were positively associated with overall survival (OS) of NSCLC patients. Among these genes, UBL3 was the most significant one. UBL3 expression was decreased in tumor samples compared to that in paired normal lung tissues in 59/86 (68.6%) NSCLCs, was correlated with TNM stage and sex of NSCLC patients, and was significantly higher in non-smoking patients than in smoking patients. Silencing UBL3 accelerated cell proliferation and ectopic expression of UBL3 suppressed NSCLC in vitro and in vivo. Conclusions: These results showed that UBL3 represented a tumor suppressor in NSCLC and may have potential for use in therapeutics and for the prediction of clinical outcome of patients.


Assuntos
Biomarcadores Tumorais/genética , Carcinogênese/genética , Carcinoma Pulmonar de Células não Pequenas/genética , Neoplasias Pulmonares/genética , Ubiquitinas/genética , Idoso , Biomarcadores Tumorais/análise , Carcinoma Pulmonar de Células não Pequenas/mortalidade , Carcinoma Pulmonar de Células não Pequenas/patologia , Carcinoma Pulmonar de Células não Pequenas/cirurgia , Linhagem Celular Tumoral , Proliferação de Células/genética , Regulação para Baixo , Feminino , Regulação Neoplásica da Expressão Gênica , Inativação Gênica , Genes Supressores de Tumor , Humanos , Estimativa de Kaplan-Meier , Pulmão/patologia , Pulmão/cirurgia , Neoplasias Pulmonares/mortalidade , Neoplasias Pulmonares/patologia , Neoplasias Pulmonares/cirurgia , Masculino , Pessoa de Meia-Idade , Pneumonectomia , Prognóstico , Ubiquitinas/análise
16.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-20033118

RESUMO

BackgroundsSince December 2019, a novel coronavirus epidemic has emerged in Wuhan city, China and then rapidly spread to other areas. As of 20 Feb 2020, a total of 2,055 medical staff confirmed with coronavirus disease 2019 (COVID-19) caused by SARS-Cov-2 in China had been reported. We sought to explore the epidemiological, clinical characteristics and prognosis of novel coronavirus-infected medical staff. MethodsIn this retrospective study, 64 confirmed cases of novel coronavirus-infected medical staff admitted to Union Hospital, Wuhan between 16 Jan, 2020 to 15 Feb, 2020 were included. Two groups concerned were extracted from the subjects based on duration of symptoms: group 1 ([≤]10 days) and group 2 (>10 days). Epidemiological and clinical data were analyzed and compared across groups. The Kaplan-Meier plot was used to inspect the change in hospital discharge rate. The Cox regression model was utilized to identify factors associated with hospital discharge. FindingsThe median age of medical staff included was 35 years old. 64% were female and 67% were nurses. None had an exposure to Huanan seafood wholesale market or wildlife. A small proportion of the cohort had contact with specimens (5%) as well as patients in fever clinics (8%) and isolation wards (5%). Fever (67%) was the most common symptom, followed by cough (47%) and fatigue (34%). The median time interval between symptoms onset and admission was 8.5 days. On admission, 80% of medical staff showed abnormal IL-6 levels and 34% had lymphocytopenia. Chest CT mainly manifested as bilateral (61%), septal/subpleural (80%) and ground-glass (52%) opacities. During the study period, no patients was transferred to intensive care unit or died, and 34 (53%) had been discharged. Higher body mass index (BMI) ([≥] 24 kg/m2) (HR 0.14; 95% CI 0.03-0.73), fever (HR 0.24; 95% CI 0.09-0.60) and higher levels of IL-6 on admission (HR 0.31; 95% CI 0.11-0.87) were unfavorable factors for discharge. InterpretationIn this study, medical staff infected with COVID-19 have relatively milder symptoms and favorable clinical course, which may be partly due to their medical expertise, younger age and less underlying diseases. Smaller BMI, absence of fever symptoms and normal IL-6 levels on admission are favorable for discharge for medical staff. Further studies should be devoted to identifying the exact patterns of SARS-CoV-2 infection among medical staff.

18.
Environ Sci Pollut Res Int ; 27(7): 7105-7119, 2020 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-31883080

RESUMO

China launched the One Belt & One Road (OBOR) initiative to minimize the energy resource shortage. The China's nearby countries are rich in energy resources especially Middle East and North Africa (MENA) and Asian countries which make them ideal locations to cooperate with China in terms of energy resources, as 42.8% of world energy consumption belongs to OBOR countries. The present study elaborates the spatial distribution pattern of energy consumption disparities and its impact on environment. To do this, an entropy approach is utilized to compute the energy consumption inequalities in OBOR and its regions. The spatial and Pareto analysis show that MENA, East, and Southeast Asian economies have the highest degree of energy consumption inequalities, while European and Central Asian economies show the lowest energy consumption inequalities in OBOR region. The long-run estimates indicate that energy consumption inequalities enhance the CO2 emission in OBOR and its region except South and Southeast Asia. Financial development also has a significantly positive impact on CO2 emission in all models for OBOR and its regions except East Asia. Based on findings, the spatial distribution analysis is applicable to maintain balance in regional energy consumption inequality within OBOR and its regions.


Assuntos
Conservação de Recursos Energéticos/economia , Entropia , África do Norte , Ásia , Ásia Sudeste , China , Conservação de Recursos Energéticos/estatística & dados numéricos , Extremo Oriente , Oriente Médio
19.
Prog Biophys Mol Biol ; 151: 40-53, 2020 03.
Artigo em Inglês | MEDLINE | ID: mdl-31761352

RESUMO

Breast cancer (BC) is a serious worldwide disease that threatens women's health. Particularly, the morbidity of triple-negative breast cancer (TNBC) is higher than that of other BC types due to its high molecular heterogeneity, metastatic potential and poor prognosis. TNBC lacks of estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2), so there are still no effective treatment methods for TNBC. Here, we reviewed the classification of TNBC, its molecular mechanisms of pathogenesis, treatment methods and prognosis. Finding effective targets is critical for the treatment of TNBC. Also, refining the classification of TNBC is benefited to choose the treatment of TNBC, because the sensitivity of chemotherapy is different in different TNBC. Some new treatment methods have been proposed in recent years, such as nutritional therapy and noncoding RNA treatment methods. There are some disadvantages, such as the side effect on normal cells after nutrient deprivation, low specificity and instability of noncoding RNA. More studies are necessary to improve the treatment of TNBC.


Assuntos
Neoplasias de Mama Triplo Negativas/terapia , Humanos , Metástase Neoplásica , Prognóstico , Transdução de Sinais/efeitos dos fármacos , Transdução de Sinais/imunologia , Transdução de Sinais/efeitos da radiação , Neoplasias de Mama Triplo Negativas/metabolismo , Neoplasias de Mama Triplo Negativas/patologia
20.
Case Rep Neurol ; 11(2): 167-172, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31543798

RESUMO

Minamata disease (MD) is a form of intoxication involving the central nervous system and is caused by ingesting seafood from methylmercury-contaminated areas in Japan. In MD, cerebellar ataxia is a cardinal feature observed in approximately 80% of MD patients. Although cerebellar transcranial magnetic stimulation (TMS) has recently been used for treating cerebellar ataxia, the optimal stimulation conditions remain unclear. Here, we report the first case of cerebellar ataxia in an MD patient that was significantly improved after high-frequency cerebellar TMS. To determine the optimal stimulation conditions, we examined the excitability of the primary motor cortex (M1) using resting-state functional magnetic resonance imaging (rs-fMRI). rs-fMRI revealed M1 hyperconnectivity, which was indicative of activation of the dentato-thalamo-cortical (DTC) pathway. Thus, high-frequency cerebellar TMS was applied to inhibit the DTC pathway. Improvement of cerebellar ataxia was only observed after real TMS, not sham stimulation. As this effect was consistent with inhibition of hyperconnectivity of M1, the effectiveness of high-frequency cerebellar TMS for cerebellar ataxia was thought to be caused by inhibition of the DTC pathway. Therefore, we suggest that the evaluation of M1 excitability using rs-fMRI can be effective for determining the optimal TMS stimulation conditions for cerebellar ataxia.

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