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1.
J Hazard Mater ; 413: 125406, 2021 Feb 11.
Artigo em Inglês | MEDLINE | ID: mdl-33609879

RESUMO

The evolution of brown carbon (BrC) during atmospheric aging, including the changes in optical properties and chemical compositions, is still unclear. Light absorption and fluorescence of BrC fraction extracted from fresh and ozonized propane soot particles by methanol were systematically measured, which showed that (1) the mass absorption efficiencies (MAE) sharply decreased by ozone (O3) aging (e.g., 1.2 ± 0.3-0.8 ± 0.1 m2 g-1 for MAE365), but changed slowly with increased O3 concentration (e.g., from 0.7 ± 0.2-0.8 ± 0.1 m2 g-1 for MAE365); (2) the fluorescence emission peaks were blue shifted, implying a loss of conjugated structures; (3) excitation-emission matrix analysis suggested that humic-like substances, charge transfer complexes, and polycyclic aromatic hydrocarbon (PAH)-like substances were the main chromophores. The PAH loss, accompanied by the decline of surface CË­C content, contributed more to the change of optical properties than the oxygenated PAH formation, thereby leading to the decrease in light absorption and fluorescence with O3 aging. This research reveals the importance of identifying the components responsible for optical properties in investigating the evolution of BrC during atmospheric aging, and is benefit for improving the evaluation of BrC's radiative forcing.

2.
Brief Bioinform ; 2021 Jan 18.
Artigo em Inglês | MEDLINE | ID: mdl-33454744

RESUMO

The interactions between proteins and nucleic acid sequences play many important roles in gene expression and some cellular activities. Accurate prediction of the nucleic acid binding residues in proteins will facilitate the research of the protein functions, gene expression, drug design, etc. In this regard, several computational methods have been proposed to predict the nucleic acid binding residues in proteins. However, these methods cannot satisfactorily measure the global interactions among the residues along protein. Furthermore, these methods are suffering cross-prediction problem, new strategies should be explored to solve this problem. In this study, a new computational method called NCBRPred was proposed to predict the nucleic acid binding residues based on the multilabel sequence labeling model. NCBRPred used the bidirectional Gated Recurrent Units (BiGRUs) to capture the global interactions among the residues, and treats this task as a multilabel learning task. Experimental results on three widely used benchmark datasets and an independent dataset showed that NCBRPred achieved higher predictive results with lower cross-prediction, outperforming 10 existing state-of-the-art predictors. The web-server and a stand-alone package of NCBRPred are freely available at http://bliulab.net/NCBRPred. It is anticipated that NCBRPred will become a very useful tool for identifying nucleic acid binding residues.

3.
Environ Pollut ; 268(Pt A): 115906, 2020 Oct 20.
Artigo em Inglês | MEDLINE | ID: mdl-33120333

RESUMO

Fluorescence spectroscopy is a commonly used technique to analyze dissolved organic matter in aquatic environments. Given the high sensitivity and non-destructive analysis, fluorescence has recently been used to study water-soluble organic carbon (WSOC) in atmospheric aerosols, which have substantial abundance, various sources and play an important role in climate change. Yet, current research on WSOC characterization is rather sparse and limited to a few isolated sites, making it challenging to draw fundamental and mechanistic conclusions. Here we presented a review of the fluorescence properties of atmospheric WSOC reported in various field and laboratory studies, to discuss the current advances and limitations of fluorescence applications. We highlighted that photochemical reactions and relevant aging processes have profound impacts on fluorescence properties of atmospheric WSOC, which were previously unnoticed for organic matter in aquatic environments. Furthermore, we discussed the differences in sources and chemical compositions of fluorescent components between the atmosphere and hydrosphere. We concluded that the commonly used fluorescence characteristics derived from aquatic environments may not be applicable as references for atmospheric WSOC. We emphasized that there is a need for more systematic studies on the fluorescence properties of atmospheric WSOC and to establish a more robust reference and dataset for fluorescence studies in atmosphere based on extensive source-specific experiments.

4.
J Mol Biol ; 432(22): 5860-5875, 2020 Nov 06.
Artigo em Inglês | MEDLINE | ID: mdl-32920048

RESUMO

DNA-binding protein (DBP) and RNA-binding protein (RBP) are playing crucial roles in gene expression. Accurate identification of them is of great significance, and accurately computational predictors are highly required. In previous studies, DBP recognition and RBP recognition were treated as two separate tasks. Because the functional and structural similarities between DBPs and RBPs are high, the DBP predictors tend to predict RBPs as DBPs, while the RBP predictors tend to predict the DBPs as the RBPs, leading to high cross-prediction rate and low prediction precision. Here we introduced a multi-label learning model based on the motif-based convolutional neural network, and a sequence-based computational method called iDRBP_MMC was proposed to solve the cross-prediction problem so as to improve the predictive performance of DBPs and RBPs. The results on four test datasets showed that it outperformed other state-of-the-art DBP predictors and RBP predictors. When applied to analyze the tomato genome, the results reveal the ability of iDRBP_MMC for large-scale data analysis. Moreover, iDRBP_MMC can identify the proteins binding to both DNA and RNA, which is beyond the scope of existing DBP predictors or RBP predictors. The web-server of iDRBP_MMC is freely available at http://bliulab.net/iDRBP_MMC.

5.
Biochem Biophys Res Commun ; 530(3): 603-608, 2020 Sep 24.
Artigo em Inglês | MEDLINE | ID: mdl-32747091

RESUMO

Anesthetic sevoflurane could induce neurotoxicity in developing brain and cause adverse neurobehavioral outcomes in mice, including inattention, social interaction deficit, and learning and memory impairment. However, there is less data on the effect of anesthesia plus surgery on social interaction behavior. Therefore, we investigated whether the combination of anesthesia and surgical stimulation could induce behavioral and biochemical changes in mice. Firstly, the six-day-old mice were received either 3% sevoflurane anesthesia or abdominal surgery under sevoflurane anesthesia. Then, these mice were scheduled to social interaction test in three-chambered social paradigm at one-month-old. In addition, the brain tissues of neonatal mice were harvested at 24 h after treatment, for measuring the levels of OXTR and NMDAR1 in Western blot analysis. We found that neonatal anesthesia with sevoflurane in a clinically-relevant dosage could not induce social interaction deficit. Nevertheless, anesthesia plus surgery was able to impair preference for social novelty in mice. Moreover, anesthesia plus surgery decreased the levels of OXTR in hippocampus and cortex of mice, as well as NMDAR1 in hippocampus. Collectively, these results suggested that anesthesia plus surgery could impair social novelty preference, but not sociability in mice, and that social memory might be more vulnerable than social affiliation in biological property. Furthermore, reduction in the levels of cortex OXTR and hippocampus NMDAR1 could be associated with social recognition memory in mice.

6.
JMIR Med Inform ; 8(7): e17958, 2020 Jul 29.
Artigo em Inglês | MEDLINE | ID: mdl-32723719

RESUMO

BACKGROUND: Depression is a serious personal and public mental health problem. Self-reporting is the main method used to diagnose depression and to determine the severity of depression. However, it is not easy to discover patients with depression owing to feelings of shame in disclosing or discussing their mental health conditions with others. Moreover, self-reporting is time-consuming, and usually leads to missing a certain number of cases. Therefore, automatic discovery of patients with depression from other sources such as social media has been attracting increasing attention. Social media, as one of the most important daily communication systems, connects large quantities of people, including individuals with depression, and provides a channel to discover patients with depression. In this study, we investigated deep-learning methods for depression risk prediction using data from Chinese microblogs, which have potential to discover more patients with depression and to trace their mental health conditions. OBJECTIVE: The aim of this study was to explore the potential of state-of-the-art deep-learning methods on depression risk prediction from Chinese microblogs. METHODS: Deep-learning methods with pretrained language representation models, including bidirectional encoder representations from transformers (BERT), robustly optimized BERT pretraining approach (RoBERTa), and generalized autoregressive pretraining for language understanding (XLNET), were investigated for depression risk prediction, and were compared with previous methods on a manually annotated benchmark dataset. Depression risk was assessed at four levels from 0 to 3, where 0, 1, 2, and 3 denote no inclination, and mild, moderate, and severe depression risk, respectively. The dataset was collected from the Chinese microblog Weibo. We also compared different deep-learning methods with pretrained language representation models in two settings: (1) publicly released pretrained language representation models, and (2) language representation models further pretrained on a large-scale unlabeled dataset collected from Weibo. Precision, recall, and F1 scores were used as performance evaluation measures. RESULTS: Among the three deep-learning methods, BERT achieved the best performance with a microaveraged F1 score of 0.856. RoBERTa achieved the best performance with a macroaveraged F1 score of 0.424 on depression risk at levels 1, 2, and 3, which represents a new benchmark result on the dataset. The further pretrained language representation models demonstrated improvement over publicly released prediction models. CONCLUSIONS: We applied deep-learning methods with pretrained language representation models to automatically predict depression risk using data from Chinese microblogs. The experimental results showed that the deep-learning methods performed better than previous methods, and have greater potential to discover patients with depression and to trace their mental health conditions.

7.
Huan Jing Ke Xue ; 41(6): 2528-2535, 2020 Jun 08.
Artigo em Chinês | MEDLINE | ID: mdl-32608766

RESUMO

To explore the seasonal variations and sources of water-soluble ions, PM2.5 samples were collected from 2017 to 2018. Water-soluble ions including SO42-, NO3-, Cl-, F-, Na+, Mg2+, NH4+, K+, and Ca2+ were determined via ion chromatography. Furthermore, the existing form of NH4+, nitrogen oxidation rate (NOR), sulfur oxidation rate (SOR), and [NO3-]/[SO42-] ratio were explored. The results showed that dust, coal combustion, biomass burning, and secondary aerosols were the dominant contributors to water-soluble ions. Ca2+, SO42-, NH4+, and NO3- were the main water-soluble ions in PM2.5 in Xi'an. Correlation analysis results showed that NH4+ could not completely neutralize SO42- in spring; unneutralized SO42- could be mainly combined with K+ and Ca2+. NH4+ mainly existed in the form of ① NH4HSO4 and (NH4)2SO4 in summer; ② NH4HSO4 and NH4NO3 in autumn; and ③ (NH4)2SO4 and NH4NO3 in winter. The yearly mean values of SOR and NOR were 0.35 and 0.16, respectively, indicating a high secondary aerosol transformation rate during the study period. The [NO3-]/[SO42-] ratio showed Xi'an was mainly affected by stationary sources in spring and summer, while the contribution of mobile sources in autumn and winter was greater than stationary sources.

8.
BMC Med Inform Decis Mak ; 20(Suppl 1): 72, 2020 Apr 30.
Artigo em Inglês | MEDLINE | ID: mdl-32349764

RESUMO

BACKGROUND: Semantic textual similarity (STS) is a fundamental natural language processing (NLP) task which can be widely used in many NLP applications such as Question Answer (QA), Information Retrieval (IR), etc. It is a typical regression problem, and almost all STS systems either use distributed representation or one-hot representation to model sentence pairs. METHODS: In this paper, we proposed a novel framework based on a gated network to fuse distributed representation and one-hot representation of sentence pairs. Some current state-of-the-art distributed representation methods, including Convolutional Neural Network (CNN), Bi-directional Long Short Term Memory networks (Bi-LSTM) and Bidirectional Encoder Representations from Transformers (BERT), were used in our framework, and a system based on this framework was developed for a shared task regarding clinical STS organized by BioCreative/OHNLP in 2018. RESULTS: Compared with the systems only using distributed representation or one-hot representation, our method achieved much higher Pearson correlation. Among all distributed representations, BERT performed best. The highest Person correlation of our system was 0.8541, higher than the best official one of the BioCreative/OHNLP clinical STS shared task in 2018 (0.8328) by 0.0213. CONCLUSIONS: Distributed representation and one-hot representation are complementary to each other and can be fused by gated network.

9.
Sci Total Environ ; 725: 138290, 2020 Jul 10.
Artigo em Inglês | MEDLINE | ID: mdl-32294585

RESUMO

Understanding the characteristics and sources of atmospheric chromophores is essential to assess their impact on climate change and the quality of atmospheric environment. In this work, the fine particulate matter (PM2.5) samples of Xi'an, China in 2017 were analyzed by excitation-emission matrices and parallel factor analysis (EEM-PARAFAC) method to obtain the species, content, sources and seasonal variation characteristics of atmospheric chromophores. The results showed that humic-like (HULIS) chromophores and polycyclic aromatic hydrocarbons-like (PAHs-like) chromophores were the most abundant chromophores in the samples, accounting for 42% and 33%, respectively. With the aggravation of air pollution, the relative content of low-polarity chromophores increased markedly, while the relative content of polar chromophores decreased. The concentrations of atmospheric chromophores exhibited obvious seasonal variation characteristics: high in winter and low in summer. Similarly, the relative contributions of atmospheric chromophores from each source varied with the season. In addition, special weather and human activities had a significant influence on the source of atmospheric chromophores. Dust source was an important source of atmospheric chromophores, which was susceptible to long-range incoming air masses from northwestern regions in spring. However, the chromophores from the dust source were easily removed by wet precipitation, which was the same as the chromophores from the combustion source. The chromophores from the combustion source were susceptible to human activities. The contribution of combustion source to atmospheric chromophores was reduced due to the implementation of air pollution control policies during the Chinese Spring Festival. In summer, the formation of photochemical secondary chromophores was more significant than in other seasons, and the photochemical secondary chromophores increased due to the formation of liquid phase reactions under high relative humidity conditions.

10.
Oxid Med Cell Longev ; 2020: 3908641, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32308802

RESUMO

Background: Heat shock protein 70 (Hsp70) has been shown to exert cardioprotection. Intracellular calcium ([Ca2+]i) overload induced by p38 mitogen-activated protein kinase (p38 MAPK) activation contributes to cardiac ischemia/reperfusion (I/R) injury. However, whether Hsp70 interacts with p38 MAPK signaling is unclear. Therefore, this study investigated the regulation of p38 MAPK by Hsp70 in I/R-induced cardiac injury. Methods: Neonatal rat cardiomyocytes were subjected to oxygen-glucose deprivation for 6 h followed by 2 h reoxygenation (OGD/R), and rats underwent left anterior artery ligation for 30 min followed by 30 min of reperfusion. The p38 MAPK inhibitor (SB203580), Hsp70 inhibitor (Quercetin), and Hsp70 short hairpin RNA (shRNA) were used prior to OGD/R or I/R. Cell viability, lactate dehydrogenase (LDH) release, serum cardiac troponin I (cTnI), [Ca2+]i levels, cell apoptosis, myocardial infarct size, mRNA level of IL-1ß and IL-6, and protein expression of Hsp70, phosphorylated p38 MAPK (p-p38 MAPK), sarcoplasmic/endoplasmic reticulum Ca2+-ATPase2 (SERCA2), phosphorylated signal transducer and activator of transcription3 (p-STAT3), and cleaved caspase3 were assessed. Results: Pretreatment with a p38 MAPK inhibitor, SB203580, significantly attenuated OGD/R-induced cell injury or I/R-induced myocardial injury, as evidenced by improved cell viability and lower LDH release, resulted in lower serum cTnI and myocardial infarct size, alleviation of [Ca2+]i overload and cell apoptosis, inhibition of IL-1ß and IL-6, and modulation of protein expressions of p-p38 MAPK, SERCA2, p-STAT3, and cleaved-caspase3. Knockdown of Hsp70 by shRNA exacerbated OGD/R-induced cell injury, which was effectively abolished by SB203580. Moreover, inhibition of Hsp70 by quercetin enhanced I/R-induced myocardial injury, while SB203580 pretreatment reversed the harmful effects caused by quercetin. Conclusions: Inhibition of Hsp70 aggravates [Ca2+]i overload, inflammation, and apoptosis through regulating p38 MAPK signaling during cardiac I/R injury, which may help provide novel insight into cardioprotective strategies.

11.
Chemosphere ; 252: 126425, 2020 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-32197172

RESUMO

Environmentally persistent free radicals (EPFRs) are a novel class of hazardous substances that can exist stably in airborne particles for a period ranging from days to weeks and are potentially toxic to human health. Electron paramagnetic resonance spectroscopy (EPR) was used to characterize particulate EPFRs in Wanzhou in the Three Gorges Reservoir area in 2017. During the whole of 2017, the average concentration of particulate EPFRs was 7.0 × 1013 ± 1.7 × 1013 spins/m3. The seasonal concentration of EPFRs in PM2.5 showed a trend of autumn > winter > spring > summer. The maxima and minima of EPFRs occurred in spring with concentrations of 2.1 × 1014 spins/m3 and 9.4 × 1012 spins/m3 respectively. The EPFRs in PM2.5 were mainly carbon-centered radicals with adjacent oxygen atoms. Significant positive correlations were found between EPFRs and SO42-, NO3- and NH4+ (r > 0.55, n = 111), indicating that EPFRs are associated with secondary sources. The atmospheric processing of particles from coal combustion, traffic, and agriculture were important sources of EPFRs. They were also particularly well correlated with K+ and Cl- in winter, suggesting that EPFRs may also be derived from wintertime biomass burning emissions. The amount of inhalable EPFRs in Wanzhou was equivalent to the range of 2.3-6.8 cigarettes per capita per day. This study provides evidence of the potential health risks of EPFRs in PM2.5, and references for air pollution control in the Three Gorges Reservoir area.


Assuntos
Poluentes Atmosféricos/análise , Exposição Ambiental/estatística & dados numéricos , Material Particulado/análise , Biomassa , Carbono , China , Carvão Mineral/análise , Poeira/análise , Monitoramento Ambiental , Radicais Livres/análise , Humanos , Estações do Ano
12.
Environ Int ; 136: 105515, 2020 03.
Artigo em Inglês | MEDLINE | ID: mdl-32006763

RESUMO

Reactive oxygen species (ROS) are a class of substances that are of general concern in terms of human health and are used to represent the oxidation potential (OP) of the atmosphere. In this study, the ROS levels in 116 daily fine particulate matter (PM2.5) samples taken over Xi'an in 2017 were measured with the dithiothreitol (DTT) method. The sources of DTTv (volume-based DTT consumption) in PM2.5 as well as their contributions were identified by both positive matrix factorization (PMF) and multiple linear regression (MLR) based on the measured chemical species in particulate matter (PM). The results showed that the yearly average DTTv over Xi'an was 0.53 nmol/min/m3 (0.19-1.10 nmol/min/m3). The highest DTTv level occurred in winter, followed by spring, summer and autumn. DTTv was the most strongly correlated with the water-soluble organic carbon (WSOC; r = 0.85), but the effects of WSOC on DTTv were very limited. SO2, NO2, CO, elemental carbon (EC) and K+ (r > 0.64) had moderate correlations with DTTv and were moderately related to environmentally persistent free radicals (EPFRs) (r = 0.56). The linear mixed-effects model showed that pollutants originating from incomplete combustion had greater effects on DTTv than those from complete combustion. Source apportionment results from PMF showed that motor vehicle emissions (27.4%), secondary sulfates (21.6%) and coal combustion sources (18.8%) were more important contributors to the DTTv in PM2.5 than dust sources (8.4%), metal processing (4.9%), industrial emissions (11.3%) and secondary nitrates (7.5%). The PMF results for the DTTv were consistent with the MLR results, which verified that both PMF and MLR are feasible methods for source apportionment of PM2.5 as well as specific species such as ROS and EPFRs. Backward trajectory clusters showed that the dominant cluster groups were local and regional transport, while the OP of the PM2.5 over Xi'an was affected more by long-range transport than by local transport. As stated above, the improvement of atmospheric oxidation potential require not only regional efforts but also large-scale joint cooperation. Furthermore, this study on the OP of PM as well as the specific source information provides important guidance for health effect research.


Assuntos
Poluentes Atmosféricos , Material Particulado , Poluentes Atmosféricos/química , China , Monitoramento Ambiental , Humanos , Estações do Ano , Emissões de Veículos , Água
13.
Sci Total Environ ; 718: 137322, 2020 May 20.
Artigo em Inglês | MEDLINE | ID: mdl-32092515

RESUMO

It is essential to fully understand the physicochemical properties and sources of atmospheric chromophores to evaluate their impacts on environmental quality and global climate. Three-dimensional excitation-emission matrix (EEM) fluorescence spectroscopy is an important method for directly characterizing the occurrences, origins, and chemical behaviors of atmospheric chromophores. However, there is still a lack of adequate information on the sources and chemical structures of EEM-defined chromophores. This situation limits the extensive application of the EEM method in the study of atmospheric chromophores. Under these adverse conditions, this work uses the analysis of EEM data by the parallel factor (PARAFAC) analysis model and a comprehensive comparison of the types and abundances of different chromophores in different aerosol samples (combustion source samples, secondary organic aerosols, and ambient aerosols) to demonstrate that the EEM method can distinguish among different chromophore types and aerosol sources. Indeed, approximately half of all fluorescent substances can be attributed to specific chemicals and sources. These findings provide an important basis for the study of the sources and chemical processes of atmospheric chromophores by the EEM approach.

14.
IEEE Trans Neural Netw Learn Syst ; 31(11): 4637-4648, 2020 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-31905151

RESUMO

We propose a novel model, called stroke sequence-dependent deep convolutional neural network (SSDCNN), which uses the stroke sequence information and eight-directional features of Chinese characters for online handwritten Chinese character recognition (OLHCCR). SSDCNN learns the representation of OLHCCs by incorporating the natural sequence information of the strokes. Furthermore, it naturally incorporates the eight-directional features. First, SSDCNN inputs the stroke sequence and transforms it into stacks of feature maps following the writing order of the strokes. Second, the fixed-length, stroke sequence-dependent representations of OLHCC are derived through convolutional, residual, and max-pooling operations. Third, the stroke sequence-dependent representation is combined with the eight-directional features via a number of fully connected neural network layers. Finally, the Chinese characters are recognized using a softmax classifier. The SSDCNN is trained in two stages: 1) the whole architecture is pretrained using the training data until the performance converges to an acceptable degree. 2) The stroke sequence-dependent representation is combined with the eight-directional features by a fully connected neural network and a softmax layer for further training. The model was experimentally evaluated on the OLHCCR competition tasks of International Conference on Document Analysis and Recognition (ICDAR) 2013. The recognition error was a maximum 58.28% lower in SSDCNN than in a model using the eight-directional features alone (5.13% versus 2.14%). Owing to its high accuracy (97.86%), the proposed SSDCNN reduced the recognition error by approximately 18.0% as compared with that of the winning system in the ICDAR 2013 competition. SSDCNN integrated with an adaptation mechanism, called the SSDCNN+Adapt model, and reached a new state-of-the-art (SOTA) standard with an accuracy of 97.94%. The SSDCNN exploits the stroke sequence information to learn high-quality OLHCC representations. Moreover, the learned representation and the classical eight-directional features complement each other within the SSDCNN architecture.

15.
BMC Med Inform Decis Mak ; 19(Suppl 10): 277, 2019 12 27.
Artigo em Inglês | MEDLINE | ID: mdl-31881967

RESUMO

BACKGROUND: Family history (FH) information, including family members, side of family of family members (i.e., maternal or paternal), living status of family members, observations (diseases) of family members, etc., is very important in the decision-making process of disorder diagnosis and treatment. However FH information cannot be used directly by computers as it is always embedded in unstructured text in electronic health records (EHRs). In order to extract FH information form clinical text, there is a need of natural language processing (NLP). In the BioCreative/OHNLP2018 challenge, there is a task regarding FH extraction (i.e., task1), including two subtasks: (1) entity identification, identifying family members and their observations (diseases) mentioned in clinical text; (2) family history extraction, extracting side of family of family members, living status of family members, and observations of family members. For this task, we propose a system based on deep joint learning methods to extract FH information. Our system achieves the highest F1- scores of 0.8901 on subtask1 and 0.6359 on subtask2, respectively.


Assuntos
Aprendizado Profundo , Registros Eletrônicos de Saúde , Armazenamento e Recuperação da Informação/métodos , Anamnese , Processamento de Linguagem Natural , Algoritmos , Tomada de Decisão Clínica , Biologia Computacional , Humanos
16.
Artigo em Inglês | MEDLINE | ID: mdl-31722485

RESUMO

DNA-binding proteins (DBPs) and RNA-binding proteins (RBPs) are two kinds of crucial proteins, which are associated with various cellule activities and some important diseases. Accurate identification of DBPs and RBPs facilitate both theoretical research and real world application. Existing sequence-based DBP predictors can accurately identify DBPs but incorrectly predict many RBPs as DBPs, and vice versa, resulting in low prediction precision. Moreover, some proteins (DRBPs) interacting with both DNA and RNA play important roles in gene expression and cannot be identified by existing computational methods. In this study, a two-level predictor named DeepDRBP-2L was proposed by combining Convolutional Neural Network (CNN) and the Long Short-Term Memory (LSTM). It is the first computational method that is able to identify DBPs, RBPs and DRBPs. Rigorous cross-validations and independent tests showed that DeepDRBP-2L is able to overcome the shortcoming of the existing methods and can go one further step to identify DRBPs. Application of DeepDRBP-2L to tomato genome further demonstrated its performance. The webserver of DeepDRBP-2L is freely available at http://bliulab.net/DeepDRBP-2L.

17.
Drug Des Devel Ther ; 13: 3137-3149, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31564830

RESUMO

Purpose: Intracellular calcium ([Ca2+]i) overload is a major cause of cell injury during myocardial ischemia/reperfusion (I/R). Dexmedetomidine (DEX) has been shown to exert anti-inflammatory and organ protective effects. This study aimed to investigate whether pretreatment with DEX could protect H9c2 cardiomyocytes against oxygen-glucose deprivation/reoxygenation (OGD/R) injury through regulating the Ca2+ signaling. Methods: H9c2 cardiomyocytes were subjected to OGD for 12 h, followed by 3 h of reoxygenation. DEX was administered 1 h prior to OGD/R. Cell viability, lactate dehydrogenase (LDH) release, level of [Ca2+]i, cell apoptosis, and the expression of 12.6-kd FK506-binding protein/ryanodine receptor 2 (FKBP12.6/RyR2) and caspase-3 were assessed. Results: Cells exposed to OGD/R had decreased cell viability, increased LDH release, elevated [Ca2+]i level and apoptosis rate, down-regulated expression of FKBP12.6, and up-regulated expression of phosphorylated-Ser2814-RyR2 and cleaved caspase-3. Pretreatment with DEX significantly blocked the above-mentioned changes, alleviating the OGD/R-induced injury in H9c2 cells. Moreover, knockdown of FKBP12.6 by small interfering RNA abolished the protective effects of DEX. Conclusion: This study indicates that DEX pretreatment protects the cardiomyocytes against OGD/R-induced injury by inhibiting [Ca2+]i overload and cell apoptosis via regulating the FKBP12.6/RyR2 signaling. DEX may be used for preventing cardiac I/R injury in the clinical settings.


Assuntos
Agonistas de Receptores Adrenérgicos alfa 2/farmacologia , Apoptose/efeitos dos fármacos , Cálcio/metabolismo , Dexmedetomidina/farmacologia , Miócitos Cardíacos/efeitos dos fármacos , Oxigênio/metabolismo , Canal de Liberação de Cálcio do Receptor de Rianodina/metabolismo , Proteínas de Ligação a Tacrolimo/antagonistas & inibidores , Cálcio/administração & dosagem , Cálcio/análise , Sobrevivência Celular/efeitos dos fármacos , Células Cultivadas , Relação Dose-Resposta a Droga , Glucose/metabolismo , Humanos , Miócitos Cardíacos/metabolismo , Canal de Liberação de Cálcio do Receptor de Rianodina/genética , Transdução de Sinais/efeitos dos fármacos , Relação Estrutura-Atividade , Proteínas de Ligação a Tacrolimo/genética , Proteínas de Ligação a Tacrolimo/metabolismo
18.
Aging (Albany NY) ; 11(19): 8386-8417, 2019 10 03.
Artigo em Inglês | MEDLINE | ID: mdl-31582589

RESUMO

Children with repeated inhalational anesthesia may develop cognitive disorders. This study aimed to investigate the transcriptome-wide response of hippocampus in young mice that had been exposed to multiple sevoflurane in the neonatal period. Mice received 3% sevoflurane for 2 h on postnatal day (PND) 6, 8, and 10, followed by arterial blood gas test on PND 10, behavioral experiments on PND 31-36, and RNA sequencing (RNA-seq) of hippocampus on PND 37. Functional annotation and protein-protein interaction analyses of differentially expressed genes (DEGs) and quantitative reverse transcription polymerase chain reaction (qPCR) were performed. Neonatal sevoflurane exposures induced cognitive and social behavior disorders in young mice. RNA-seq identified a total of 314 DEGs. Several enriched biological processes (ion channels, brain development, learning, and memory) and signaling pathways (oxytocin signaling pathway and glutamatergic, cholinergic, and GABAergic synapses) were highlighted. As hub-proteins, Pten was involved in nervous system development, synapse assembly, learning, memory, and behaviors, Nos3 and Pik3cd in oxytocin signaling pathway, and Cdk16 in exocytosis and phosphorylation. Some top DEGs were validated by qPCR. This study revealed a transcriptome-wide profile in mice hippocampus after multiple neonatal exposures to sevoflurane, promoting better understanding of underlying mechanisms and investigation of preventive strategies.


Assuntos
Transtornos Cognitivos , Hipocampo , Sevoflurano , Transdução de Sinais/efeitos dos fármacos , Anestésicos Inalatórios/administração & dosagem , Anestésicos Inalatórios/efeitos adversos , Animais , Comportamento Animal/fisiologia , Classe I de Fosfatidilinositol 3-Quinases/metabolismo , Transtornos Cognitivos/induzido quimicamente , Transtornos Cognitivos/metabolismo , Quinases Ciclina-Dependentes/metabolismo , Hipocampo/efeitos dos fármacos , Hipocampo/metabolismo , Camundongos , Óxido Nítrico Sintase Tipo III/metabolismo , Sevoflurano/administração & dosagem , Sevoflurano/efeitos adversos , Comportamento Social , Transcriptoma/efeitos dos fármacos
19.
J Am Med Inform Assoc ; 26(12): 1584-1591, 2019 12 01.
Artigo em Inglês | MEDLINE | ID: mdl-31550346

RESUMO

OBJECTIVE: Extracting clinical entities and their attributes is a fundamental task of natural language processing (NLP) in the medical domain. This task is typically recognized as 2 sequential subtasks in a pipeline, clinical entity or attribute recognition followed by entity-attribute relation extraction. One problem of pipeline methods is that errors from entity recognition are unavoidably passed to relation extraction. We propose a novel joint deep learning method to recognize clinical entities or attributes and extract entity-attribute relations simultaneously. MATERIALS AND METHODS: The proposed method integrates 2 state-of-the-art methods for named entity recognition and relation extraction, namely bidirectional long short-term memory with conditional random field and bidirectional long short-term memory, into a unified framework. In this method, relation constraints between clinical entities and attributes and weights of the 2 subtasks are also considered simultaneously. We compare the method with other related methods (ie, pipeline methods and other joint deep learning methods) on an existing English corpus from SemEval-2015 and a newly developed Chinese corpus. RESULTS: Our proposed method achieves the best F1 of 74.46% on entity recognition and the best F1 of 50.21% on relation extraction on the English corpus, and 89.32% and 88.13% on the Chinese corpora, respectively, which outperform the other methods on both tasks. CONCLUSIONS: The joint deep learning-based method could improve both entity recognition and relation extraction from clinical text in both English and Chinese, indicating that the approach is promising.

20.
Environ Sci Technol ; 53(17): 10053-10061, 2019 Sep 03.
Artigo em Inglês | MEDLINE | ID: mdl-31389239

RESUMO

A secondary process may be an important source of environmentally persistent free radicals (EPFRs) in atmospheric particulates; yet, this process remains to be elucidated. This study demonstrated that secondary EPFRs could be generated by visible-light illumination of atmospheric particulate matter (PM), and their lifetimes were only 30 min to 1 day, which were much shorter than the lifetimes of the original EPFRs in PM. The yields of secondary EPFRs produced by PM could reach 15-60% of those of the original EPFRs. The extractable organic matter contributed to the formation of secondary EPFRs (∼55%), and a humic-like substance was the main precursor of the secondary EPFRs and was also the most productive precursor compared to the other aerosol components. The results of simulation experiments showed that the secondary EPFRs generated by the extractable and nonextractable PM components were similar to those produced by phenolic compounds and polycyclic aromatic hydrocarbons, respectively. We have found that oxygen molecules play an important role in the photochemical generation and decay of EPFRs. The reactive oxygen capture experiments showed that the original EPFRs may contribute to singlet oxygen generation, while the secondary EPFRs generated by photoexcitation may not produce singlet oxygen or hydroxyl radicals.


Assuntos
Iluminação , Material Particulado , Carvão Mineral , Poeira , Radicais Livres
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