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Introduction: Eplerenone is approved for the treatment of hypertension as well as symptomatic heart failure with reduced ejection fraction (HFrEF) following an acute myocardial infarction. However, the adverse events (AEs) have not been systematically analyzed. The aim of this study was to identify adverse drug reactions (ADRs) related to eplerenone using the FDA Adverse Event Reporting System (FAERS) database. By identifying previously unreported AEs, the study could potentially contribute to updating the drug's label. Methods: In order to find significant AEs, four algorithms, including Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN) and Empirical Bayesian Geometric Mean (EBGM), were used to analyze the signal strength of the ADRs connected to eplerenone that were gathered from the FAERS database over the previous 20 years. Results: From 2004Q1 to 2023Q4, a total of 20, 629, 811 reported cases were gathered from the FAERS database for this study. After processing the data and filtering, 1,874 case reports were analyzed. Of these cases, 1,070 AEs were identified, 128 of which were eplerenone-related ADRs. We investigated the occurrence of ADRs induced by eplerenone in 27 organ systems. Our study showed that the AEs listed in the medication's package insert correspond with those listed in the literature, including hyperkalemia and increased creatinine. Additionally, the prescription label for eplerenone does not include all system organ class (SOC) terms, like Vascular disorders, hepatobiliary Disorders, etc. Discussion: The study used multiple algorithms to quantify the signal strength and then identified any previously unrecognized ADRs, further studies are needed to confirm the association of ADRs with eplerenone. The findings of this study may provide important insights into the safety profile of eplerenone, ensure that healthcare providers have up-to-date information about their potential risks and help guide them in the correct use of the drug.
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BACKGROUND: Glioblastoma (GB) is recognized as one of the most aggressive brain tumors, with a median survival of 14.6 months. However, there are still some patients whose survival time was greater than 3 years, and the biological reasons behind this clinical phenomenon arouse our research interests. By conducting proteomic analysis on tumor tissues obtained from GB patients who survived over 3 years compared to those who survived less than 1 year, we identified a significant upregulation of SelK in patients with shorter survival times. Therefore, we hypothesized that SelK may be an important indicator related to the occurrence and progression of GBM. METHODS: Proteomics and immunohistochemistry from GB patients were analyzed to investigate the correlation between SelK and clinical prognosis. Cellular phenotypes were evaluated by cell cycle analysis, cell viability assays, and xenograft models. Immunoblots and co-immunoprecipitation were conducted to verify SelK-mediated ubiquitin-dependent degradation of CDK4. RESULTS: SelK was found to be significantly upregulated in GB samples from short-term survivors (≤ 1 year) compared to those from long-term survivors (≥ 3 years), and its expression levels were negatively correlated with clinical prognosis. Knocking down of SelK expression reduced GB cell viability, induced G0/G1 phase arrest, and impaired the growth of transplanted glioma cells in nude mice. Down-regulation of SelK-induced ER stress leads to a reduction in the expression of SKP2 and an up-regulation of ß-TrCP1 expression. Up-regulation of ß-TrCP1, thereby accelerating the ubiquitin-dependent degradation of CDK4 and ultimately inhibiting the malignant proliferation of the GB cells. CONCLUSION: This study discovered a significant increase in SelK expression in GB patients with poor prognosis, revealing a negative correlation between SelK expression and patient outcomes. Further mechanistic investigations revealed that SelK enhances the proliferation of GB cells by targeting the endoplasmic reticulum stress/SKP2/ß-TrCP1/CDK4 axis.
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Proliferação de Células , Quinase 4 Dependente de Ciclina , Glioblastoma , Humanos , Glioblastoma/metabolismo , Glioblastoma/patologia , Glioblastoma/genética , Quinase 4 Dependente de Ciclina/metabolismo , Animais , Camundongos , Masculino , Feminino , Proteínas Contendo Repetições de beta-Transducina/metabolismo , Proteínas Contendo Repetições de beta-Transducina/genética , Ubiquitina/metabolismo , Linhagem Celular Tumoral , Proteólise , Prognóstico , Camundongos Nus , Neoplasias Encefálicas/metabolismo , Neoplasias Encefálicas/patologia , Neoplasias Encefálicas/genética , Pessoa de Meia-Idade , UbiquitinaçãoRESUMO
Superficial temporal artery-middle cerebral artery (STA-MCA) bypass surgery represents the primary treatment for Moyamoya disease (MMD), with its efficacy contingent upon collateral vessel development. This study aimed to develop and validate a machine learning (ML) model for the non-invasive assessment of STA-MCA bypass surgery efficacy in MMD. This study enrolled 118 MMD patients undergoing STA-MCA bypass surgery. Clinical features were screened to construct a clinical model. MRI features were extracted from the middle cerebral artery supply area using 3D Slicer and employed to build five ML models using logistic regression algorithm. The combined model was developed by integrating the radiomics score (Rad-score) with the clinical features. Model performance validation was conducted using ROC curves. Platelet count (PLT) was identified as a significant clinical feature for constructing the clinical model. A total of 3404 features (851 × 4) were extracted, and 15 optimal features were selected from each MRI sequence as predictive factors. Multivariable logistic regression identified PLT and Rad-score as independent parameters used for constructing the combined model. In the testing set, the AUC of the T1WI ML model [0.84 (95% CI, 0.70-0.97)] was higher than that of the clinical model [0.66 (95% CI, 0.46-0.86)] and the combined model [0.80 (95% CI, 0.66-0.95)]. The T1WI ML model can be used to assess the postoperative efficacy of STA-MCA bypass surgery for MMD.
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Methods: Rat models of DN were established using streptozotocin (STZ). The primary metabolic parameters were assessed. The pathological changes of the rat kidney were investigated, and RNA sequencing was performed for each group. Renal tissue apoptosis was detected using the TUNEL assay. In rats and high glucose- (Hg-) induced HK-2 cells, RT-qPCR and western blot were used to analyze the expression of related genes and proteins. Hg medium was used to establish the diabetic kidney environment. The CCK-8 assay and flow cytometry were used to assess cell viability and apoptosis, respectively. Transmission electron microscopy was used to evaluate autophagy in vitro. Results: CRT treatment significantly reduced albuminuria and renal tissue damage in DN rats. Furthermore, CRT administration inhibited apoptosis and promoted autophagy in DN rat kidney tissues. CRT downregulated CD36 expression and activated the adenosine monophosphate-activated protein kinase (AMPK) signaling pathway in DN rat kidney tissues. CRT intervention inhibited Hg-induced apoptosis and reversed autophagy in HK-2 cells. Moreover, overexpression of CD36 suppressed the beneficial effects of CRT. Conclusions: Our study is the first to report that CRT inhibited apoptosis and promoted autophagy in vivo and in vitro, which was achieved by reducing CD36 expression and activating the AMPK pathway. Therefore, CRT may be an effective drug to treat DN.
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Diabetes Mellitus , Nefropatias Diabéticas , Mercúrio , Animais , Ratos , Nefropatias Diabéticas/genética , Proteínas Quinases Ativadas por AMP , Apoptose , Autofagia , Antígenos CD36/genéticaRESUMO
In this study, an efficient ultrasonic-assisted extraction method was used for the extraction and optimization of four wine grape polysaccharides. A three-level, three-factor Box Behnken Design combined with the response surface approach was used to optimize the extraction conditions. Their physicochemical properties, molecular structure, antioxidant activity, immunomodulatory activity and hepatoprotective effects were examined and compared. These findings suggest that the four wine grape polysaccharides share similar basic structural features and monosaccharide composition. Furthermore, four wine grape polysaccharides exhibited antioxidant and immunomodulatory activities in a concentration-dependent manner. Moldova (MD) polysaccharide displayed better antioxidant activity and immunomodulatory ability. Furthermore, MD polysaccharide has a significant therapeutic effect on CCl4-induced rat liver injury by improving the antioxidant defense system and inhibiting oxidative stress, indicating that MD has a hepatoprotective effect. Taken together, the MD wine grape polysaccharide may have potential applications in prevention of liver disease in the functional food and pharmaceutical industries.
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Vitis , Vinho , Ratos , Animais , Antioxidantes/farmacologia , Antioxidantes/química , Estresse Oxidativo , Polissacarídeos/farmacologia , Polissacarídeos/químicaRESUMO
Colorectal cancer (CRC) is one of the most common malignant tumors in the gastrointestinal tract, and has been attracted a great deal attention and extensive investigation due to its high morbidity and mortality rates. The C4orf19 gene encodes a protein with uncharacterized function. Our preliminary exploration of the TCGA database indicated that C4orf19 is markedly downregulated in CRC tissues in comparison to that observed in normal colonic tissues, suggesting its potential association with CRC behaviors. Further studies showed a significant positive correlation between C4orf19 expression levels and CRC patient prognosis. Ectopic expression of C4orf19 inhibited the growth of CRC cells in vitro and tumorigenic ability in vivo. Mechanistic studies showed that C4orf19 binds to Keap1 at near the Lys615, which prevents the ubiquitination of Keap1 by TRIM25, thus protecting the Keap1 protein from degradation. The accumulated Keap1 results in USP17 degradation and in turn leading to the degradation of Elk-1, further attenuates its regulated CDK6 mRNA transcription and protein expression, as well as its mediated proliferation of CRC cells. Collectively, the present studies characterize function of C4orf19 as a tumor suppressor for CRC cell proliferation by targeting Keap1/USP17/Elk-1/CDK6 axis.
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Neoplasias Colorretais , Fator 2 Relacionado a NF-E2 , Humanos , Linhagem Celular Tumoral , Proliferação de Células/genética , Neoplasias Colorretais/patologia , Quinase 6 Dependente de Ciclina/genética , Regulação Neoplásica da Expressão Gênica , Proteína 1 Associada a ECH Semelhante a Kelch/genética , Proteína 1 Associada a ECH Semelhante a Kelch/metabolismo , Fator 2 Relacionado a NF-E2/genética , Fatores de Transcrição/genética , Proteínas com Motivo Tripartido/metabolismo , Ubiquitina-Proteína Ligases/metabolismo , Ubiquitinação , Proteínas de Neoplasias/metabolismoRESUMO
In this study, four wine grape polysaccharides were extracted and optimized by using an efficient ultrasound-assisted extraction. A three-level, three-factor Box Behnken Design (BBD) combining with response surface methodology (RSM) was employed to optimize the extraction conditions including ultrasonic power, ultrasonic time and liquid-to-solid ratio. Furthermore, their physicochemical structures, antioxidant and liver protective activity were investigated and compared. Results revealed that the functional groups and monosaccharide compositions of these grape polysaccharides collected from different varieties were similar. Nevertheless, their molecular weights, molar ratios of monosaccharide compositions and surface morphological features were different. And the antioxidant activities of these polysaccharides were screened by free radical scavenging test. 'Beichun' (BC) and 'Benni fuji' (BF) polysaccharides possessed better antioxidant function. Further, the in vivo evaluation indicated that the polysaccharides of BC and BF have a protective effect against myocardial I/R injury in mice by inhibiting myocardial necroptosis mediated by mitochondrial ROS generation. Therefore, BC and BF grapes have potential applications in the medical and food industries.
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Antioxidantes , Vitis , Animais , Camundongos , Antioxidantes/farmacologia , Antioxidantes/química , Polissacarídeos/farmacologia , Polissacarídeos/química , Peso Molecular , Monossacarídeos/químicaRESUMO
RATIONALE AND OBJECTIVES: To explore the feasibility of differentiating three predominant metastatic tumor types using lung computed tomography (CT) radiomics features based on supervised machine learning. MATERIALS AND METHODS: This retrospective analysis included 252 lung metastases (LM) (from 78 patients), which were divided into the training (n = 176) and test (n = 76) cohort randomly. The metastases originated from colorectal cancer (n = 97), breast cancer (n = 87), and renal carcinoma (n = 68). An additional 77 LM (from 35 patients) were used for external validation. All radiomics features were extracted from lung CT using an open-source software called 3D slicer. The least absolute shrinkage and selection operator (LASSO) method selected the optimal radiomics features to build the model. Random forest and support vector machine (SVM) were selected to build three-class and two-class models. The performance of the classification model was evaluated with the area under the receiver operating characteristic curve (AUC) by two strategies: one-versus-rest and one-versus-one. RESULTS: Eight hundred and fifty-one quantitative radiomics features were extracted from lung CT. By LASSO, 23 optimal features were extracted in three-class, and 25, 29, and 35 features in two-class for differentiating every two of three LM (colorectal cancer vs. renal carcinoma, colorectal cancer vs. breast cancer, and breast cancer vs. renal carcinoma, respectively). The AUCs of the three-class model were 0.83 for colorectal cancer, 0.79 for breast cancer, and 0.91 for renal carcinoma in the test cohort. In the external validation cohort, the AUCs were 0.77, 0.83, and 0.81, respectively. Swarmplot shows the distribution of radiomics features among three different LM types. In the two-class model, high accuracy and AUC were obtained by SVM. The AUC of discriminating colorectal cancer LM from renal carcinoma LM was 0.84, and breast cancer LM from colorectal cancer LM and renal carcinoma LM were 0.80 and 0.94, respectively. The AUCs were 0.77, 0.78, and 0.84 in the external validation cohort. CONCLUSION: Quantitative radiomics features based on Lung CT exhibited good discriminative performance in LM of primary colorectal cancer, breast cancer, and renal carcinoma.
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Neoplasias da Mama , Carcinoma de Células Renais , Neoplasias Colorretais , Neoplasias Renais , Neoplasias Pulmonares , Humanos , Feminino , Estudos Retrospectivos , Tomografia Computadorizada por Raios X/métodos , Neoplasias Pulmonares/diagnóstico por imagem , Neoplasias da Mama/diagnóstico por imagem , Neoplasias Renais/diagnóstico por imagem , Neoplasias Colorretais/diagnóstico por imagemRESUMO
Colorectal cancer (CRC) is the most common digestive tract malignancy, attributing to approximately 9.4% of global cancer-related deaths. However, the pathogenesis of CRC is poorly understood. The testis-expressed 11 (TEX11) gene is located on the X chromosome and is required for spermatogenesis, and is reported might serve as a biomarker for early onset CRC according to database analysis. However, the role played by TEX11 in cancer progression remains to be investigated. In this study, we show that TEX11 expression is significantly downregulated in CRC cell lines and clinical CRC tissue samples, and TEX11 expression correlates with poor prognosis in CRC patients. We further demonstrate that TEX11 can significantly inhibit the proliferative capacity of CRC cells in vitro and in vivo. Mechanistically, we demonstrate that TEX11 promotes transcription of COP1 by upregulating FOXO3a expression. This enhanced COP1 expression subsequently accelerates the degradation of the negative transcriptional regulator c-Jun, which, in turn, enhances p21 transcription inhibiting CRC cell cycle progression and proliferation. Overall, our findings suggest that TEX11 may be a valuable therapeutic target for the treatment of CRC.
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Neoplasias Colorretais , Testículo , Humanos , Masculino , Regulação para Baixo , Testículo/metabolismo , Neoplasias Colorretais/patologia , Linhagem Celular Tumoral , Proliferação de Células/genética , Regulação Neoplásica da Expressão Gênica , Proteínas de Ciclo Celular/genética , Proteínas de Ciclo Celular/metabolismoRESUMO
Purpose: To develop and validate a clinical-radiomics nomogram based on radiomics features and clinical risk factors for identification of human epidermal growth factor receptor 2 (HER2) status in patients with breast cancer (BC). Methods: Two hundred and thirty-five female patients with BC were enrolled from July 2018 to February 2022 and divided into a training group (from center I, 115 patients), internal validation group (from center I, 49 patients), and external validation group (from centers II and III, 71 patients). The preoperative MRI of all patients was obtained, and radiomics features were extracted by a free open-source software called 3D Slicer. The Least Absolute Shrinkage and Selection Operator regression model was used to identify the most useful features. The radiomics score (Rad-score) was calculated by using the radiomics signature-based formula. A clinical-radiomics nomogram combining clinical factors and Rad-score was developed through multivariate logistic regression analysis. The performance of the nomogram was evaluated using receiver operating characteristic (ROC) curve and decision curve analysis (DCA). Results: A total of 2,553 radiomics features were extracted, and 21 radiomics features were selected as the most useful radiomics features. Multivariate logistic regression analysis indicated that Rad-score, progesterone receptor (PR), and Ki-67 were independent parameters to distinguish HER2 status. The clinical-radiomics nomogram, which comprised Rad-score, PR, and Ki-67, showed a favorable classification capability, with AUC of 0.87 [95% confidence internal (CI), 0.80 to 0.93] in the training group, 0.81 (95% CI, 0.69 to 0.94) in the internal validation group, and 0.84 (95% CI, 0.75 to 0.93) in the external validation group. DCA illustrated that the nomogram was useful in clinical practice. Conclusions: The nomogram combined with Rad-score, PR, and Ki-67 can identify the HER2 status of BC.
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Purpose: To build CT perfusion (CTP)-based delta-radiomics models to identify collateral vessel formation after revascularization in patients with moyamoya disease (MMD). Methods: Fifty-three MMD patients who underwent CTP and digital subtraction angiography (DSA) examination were retrospectively enrolled. Patients were divided into good and poor groups based on postoperative DSA. CTP parameters, such as mean transit time (MTT), time to drain (TTD), time to maximal plasma concentration (Tmax), and flow extraction product (FE), were obtained. CTP efficacy in evaluating surgical treatment were compared between the good and poor groups. The changes in the relative CTP parameters (ΔrMTT, ΔrTTD, ΔrTmax, and ΔrFE) were calculated to evaluate the differences between pre- and postoperative CTP values. CTP parameters were selected to build delta-radiomics models for identifying collateral vessel formation. The identification performance of machine learning classifiers was assessed using area under the receiver operating characteristic curve (AUC). Results: Of the 53 patients, 36 (67.9%) and 17 (32.1%) were divided into the good and poor groups, respectively. The postoperative changes of ΔrMTT, ΔrTTD, ΔrTmax, and ΔrFE in the good group were significantly better than the poor group (p < 0.05). Among all CTP parameters in the perfusion improvement evaluation, the ΔrTTD had the largest AUC (0.873). Eleven features were selected from the TTD parameter to build the delta-radiomics model. The classifiers of the support vector machine and k-nearest neighbors showed good diagnostic performance with AUC values of 0.933 and 0.867, respectively. Conclusion: The TTD-based delta-radiomics model has the potential to identify collateral vessel formation after the operation.
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Cocrystallization is a helpful method for explosives design. However, lack of understanding of the cocrystallization mechanism leads to inefficiency in cocrystal preparation. Therefore, studying the effects of solvent on cocrystal is of great importance for the efficient application of 2,4,6,8,10,12-hexanitrohexaazaisowurtzitane (CL-20). In this paper, the effect of solvent on cocrystallization is investigated by the CL-20/HMX cocrystal/solvent cluster model, the CL-20/HMX/solvent mixture model, the CL-20/HMX cocrystal/solvent interface model combined with quantum chemistry and molecular dynamic methods. The authors find that the hydrogen bond between CL-20 and 1,3,5,7-tetranitro-1,3,5,7-tetrazocane (HMX) is the strongest and the binding energy of cocrystal and solvent molecules is the weakest in ethyl acetate (EA) solvent, indicating that CL-20 and HMX tend to be combined together and there is less hindrance by solvent molecules. Analysis of the CL-20/HMX/solvent mixture and mass density distribution studies show that the solvent effect has a great influence on the crystal faces and the cocrystallization rate of CL-20 and HMX is the highest in EA solvent. The XRD and SEM characterization results are consistent with the theoretical calculations. The present work on the effects of solvent on CL-20/HMX cocrystals is beneficial for understanding the mechanism of the growth of energetic cocrystal materials. It is helpful in selecting more suitable theoretical and experimental conditions and makes access to excellent cocrystals more efficient.
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Four N,N-dimethylaminomethylferrocene polynitrogen catalysts were applied to the thermal decomposition of FOX-12, and their catalytic effect on FOX-12 was investigated by TG-DSC. The kinetic parameters and kinetic model of the mixed system were revealed by the Kissinger method, Freidman method, and combined kinetic analysis. The results showed that MAFcTAZ is the catalyst with the strongest effect on FOX-12, the decomposition peak temperature of FOX-12 is reduced, and the decomposition weight loss is higher than those for other catalysts, which prove that the decomposition of FOX-12 is more thorough under the catalysis of MAFcTAZ. The introduction of the four catalysts reduced the thermal decomposition peak temperature of FOX-12. MAFcTAZ was the most active catalyst for the decomposition of FOX-12, and the maximum heat release of catalyzing the decomposition of FOX-12 can reach 1236.76 J·g-1. The activation energy (E a) of FOX-12 decomposition decreased from 217.91 to 128.19, 137.85, 157.65, and 151.91 kJ·mol-1 under the effect of MAFcNO3, MAFcPA, MAFcNTO, and MAFcTAZ. The Freidman analysis illustrated that MAFcTAZ reduced the activation energy during the entire decomposition process of FOX-12. The physical model of the decomposition reaction of FOX-12 transformed from the random nucleation and two-dimensional growth of nuclei model (A2) to the random scission model (L2) in the presence of MAFcNO3 and two-dimensional diffusion (D2) under the effect of MAFcPA, MAFcNTO, and MAFcTAZ. By analyzing the molecular structures, MAFcTAZ has a higher iron content and nitrogen content, which are the essence of its excellent catalytic performance. From the perspective of interaction energy, the strong catalytic effect of MAFcTAZ is attributed to its large interaction energy with FOX-12 by energy decomposition analysis.
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Objective: This paper used meta-regression to analyze the heterogenous factors contributing to the prevalence rate of mental health symptoms of the general and frontline healthcare workers (HCWs) in China under the COVID-19 crisis. Method: We systematically searched PubMed, Embase, Web of Science, and Medrxiv and pooled data using random-effects meta-analyses to estimate the prevalence rates, and ran meta-regression to tease out the key sources of the heterogeneity. Results: The meta-regression results uncovered several predictors of the heterogeneity in prevalence rates among published studies, including severity (e.g., above severe vs. above moderate, p < 0.01; above moderate vs. above mild, p < 0.01), type of mental symptoms (PTSD vs. anxiety, p = 0.04), population (frontline vs. general HCWs, p < 0.01), sampling location (Wuhan vs. Non-Wuhan, p = 0.04), and study quality (p = 0.04). Conclusion: The meta-regression findings provide evidence on the factors contributing to the prevalence rate of mental health symptoms of the general and frontline healthcare workers (HCWs) to guide future research and evidence-based medicine in several specific directions. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=220592, identifier: CRD42020220592.
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[This corrects the article DOI: 10.1007/s11469-020-00418-6.].
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Healthcare workers are under such a tremendous amount of pressure during the COVID-19 pandemic that many have become concerned about their jobs and even intend to leave them. It is paramount for healthcare workers to feel satisfied with their jobs and lives during a pandemic. This study aims to examine the predictors of job satisfaction, life satisfaction, and turnover intention of healthcare workers during the COVID-19 pandemic. Between 10 and 30 April 2020, 240 healthcare workers in Bolivia completed a cross-sectional online survey, which assessed their job satisfaction, life satisfaction, and turnover intention in the ongoing COVID-19 pandemic. The results revealed that their number of office days predicted job satisfaction, life satisfaction, and turnover intention, but the relationships varied by their age. For example, healthcare workers' office days negatively predicted job satisfaction for the young (e.g., at 25 years old: b = - 0.21; 95% CI: - 0.36 to - 0.60) but positively predicted job satisfaction for the old (e.g., at 65 years old: b = 0.25; 95% CI: 0.06 to 0.44). These findings provide evidence to enable healthcare organizations to identify staff concerned about job satisfaction, life satisfaction, and turnover intention to enable early actions so that these staffs can remain motivated to fight the prolonged COVID-19 pandemic.
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Nano-graphene-based energetic materials, as a new type of composite energetic materials such as desensitizer and combustion catalyst, have attracted extensive attention from energetic researchers. In this paper, the preparation of nano-graphene-based energetic materials, the desensitization effect of nano-graphene-based on energetic compounds, the thermal decomposition and combustion behavior of the materials are reviewed. Meanwhile, the existing problems and future development of nano-graphene-based energetic compounds are discussed.
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Wearing a face mask has been a key approach to contain or slow down the spread of COVID-19 in the ongoing pandemic. However, there is huge heterogeneity among individuals in their willingness to wear face masks during an epidemic. This research aims to investigate the individual heterogeneity to wear face masks and its associated predictors during the COVID-19 pandemic when mask-wearing was not mandatory. Based on a survey of 708 Malaysian adults and a multivariate least-squares fitting analysis, the results reveal a significant variance among individuals in wearing masks, as 34% of the individual adults did not always wear masks in public places. Female individuals, individuals who wash their hands more frequently, and those who reported more availability of personal protective equipment were more likely to practice mask-wearing. The identification of less-compliant groups of mask wearing has critical implications by enabling more specific health communication campaigns.
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COVID-19/epidemiologia , COVID-19/prevenção & controle , Controle de Doenças Transmissíveis/métodos , Máscaras , SARS-CoV-2 , Adulto , Coleta de Dados , Feminino , Promoção da Saúde , Humanos , Malásia/epidemiologia , Masculino , Pessoa de Meia-Idade , Fatores Sexuais , Adulto JovemRESUMO
The COVID-19 pandemic in Brazil is extremely severe, and Brazil has the third-highest number of cases in the world. The goal of the study is to identify the prevalence rates and several predictors of depression and anxiety in Brazil during the initial outbreak of COVID-19. We surveyed 482 adults in 23 Brazilian states online on 9-22 May 2020, and found that 70.3% of the adults (n = 339) had depressive symptoms and 67.2% (n = 320) had anxiety symptoms. The results of multi-class logistic regression models revealed that females, younger adults, and those with fewer children had a higher likelihood of depression and anxiety symptoms; adults who worked as employees were more likely to have anxiety symptoms than those who were self-employed or unemployed; adults who spent more time browsing COVID-19 information online were more likely to have depression and anxiety symptoms. Our results provide preliminary evidence and early warning for psychiatrists and healthcare organizations to better identify and focus on the more vulnerable sub-populations in Brazil during the ongoing COVID-19 pandemic.
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COVID-19 , Depressão , Adulto , Ansiedade/epidemiologia , Brasil/epidemiologia , Criança , Estudos Transversais , Depressão/epidemiologia , Feminino , Humanos , Pandemias , SARS-CoV-2RESUMO
OBJECTIVE: The high morbidity, complex seasonality, and recurring risk of hand-foot-and-mouth disease (HFMD) exert a major burden in China. Forecasting its epidemic trends is greatly instrumental in informing vaccine and targeted interventions. This study sets out to investigate the usefulness of an advanced exponential smoothing state space framework by combining Box-Cox transformations, Fourier representations with time-varying coefficients and autoregressive moving average (ARMA) error correction (TBATS) method to assess the temporal trends of HFMD in China. METHODS: Data from January 2009 to December 2019 were drawn, and then they were split into two segments comprising the in-sample training data and out-of-sample testing data to develop and validate the TBATS model, and its fitting and forecasting abilities were compared with the most frequently used seasonal autoregressive integrated moving average (SARIMA) method. RESULTS: Following the modelling procedures of the SARIMA and TBATS methods, the SARIMA (1,0,1)(0,1,1)12 and TBATS (0.024, {1,1}, 0.855, {<12,4>}) specifications were recognized as being the optimal models, respectively, for the 12-step ahead forecasting, along with the SARIMA (1,0,1)(0,1,1)12 and TBATS (0.062, {1,3}, 0.86, {<12,4>}) models as being the optimal models, respectively, for the 24-step ahead forecasting. Among them, the optimal TBATS models produced lower error rates in both 12-step and 24-step ahead forecasting aspects compared to the preferred SARIMA models. Descriptive analysis of the data showed a significantly high level and a marked dual seasonal pattern in the HFMD morbidity. CONCLUSION: The TBATS model has the capacity to outperform the most frequently used SARIMA model in forecasting the HFMD incidence in China, and it can be recommended as a flexible and useful tool in the decision-making process of HFMD prevention and control in China.