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1.
Exp Parasitol ; 206: 107769, 2019 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-31580876

RESUMO

BACKGROUND: Mansonellosis arises from infections with threadlike filarial nematodes in millions of individuals, especially in sub-Saharan Africa. Since infections present no overt clinical symptoms but attenuate immune responses that might lead to increased susceptibility and worsened disease course of concomitant infections, it is truly a neglected tropical disease. Nevertheless, only few studies focus on identifying suitable safe drugs for its control and little is known about the requirements for in vitro maintenance of the Mansonella perstans transmission stage. This study, therefore, evaluated the survival of M. perstans microfilariae (mf) using in vitro conditions that have been shown to promote survival of Loa loa, a closely related filarial nematode. Furthermore, the in vitro microfilaricidal effect of 15 agents was assessed on this helminth. METHODS: The ability of two basic culture media; Dulbecco's Modified Eagle's Medium (DMEM) and Roswell Park Memorial Institute (RPMI-1640) supplemented with 10% fetal bovine serum (FBS) and a monkey kidney epithelial cell line (LLC-MK2) to support the survival of M. perstans microfilariae was investigated. Subsequently, 6 anti-helminthics, 5 anti-malarials, 1 anti-microbacterial, 2 trypanocidals and 1 anti-cancer agent were tested in vitro against mf. The suitability of the culture media as well as the effect of the anti-infective agents on mf survival was assessed by scoring their motility. RESULTS: FBS supplement and additional LLC-MK2 cells significantly improved the survival of mf in DMEM and RPMI-1640 culture. In detail, RPMI-1640 supplemented with 10% FBS and LLC-MK2 cells sustained the maintenance of mf for at least 20 days (100.00 ±â€¯0.00% survival). In co-cultures with LLC-MK2 cells without serum, M. perstans mf were maintained in DMEM and RPMI-1640 medium with a motility above 99% by day 5. Mefloquine displayed the highest microfilaricidal effect in vitro followed by artesunate. CONCLUSION: Both RPMI and DMEM in the presence of LLC-MK2 cells are suitable for the maintenance of M. perstans mf in vitro. In absence of the feeder cells, the addition of 10% FBS to RPMI-1640 medium improved the parasite survival rate and motility. The microfilaricidal activity of mefloquine and artesunate on M. perstans mf was documented for the first time in this study and can therefore be considered as reference for further screening of agents against this parasite stage.


Assuntos
Artesunato/farmacologia , Filaricidas/farmacologia , Mansonella/efeitos dos fármacos , Mansonella/crescimento & desenvolvimento , Mefloquina/farmacologia , Amodiaquina/farmacologia , Animais , Antimaláricos/farmacologia , Antinematódeos/farmacologia , Área Sob a Curva , Bovinos , Linhagem Celular , Meios de Cultura/química , Haplorrinos , Ivermectina/farmacologia , Mansonella/fisiologia , Microfilárias/efeitos dos fármacos , Microfilárias/crescimento & desenvolvimento , Microfilárias/fisiologia , Movimento/efeitos dos fármacos , Rifampina/farmacologia
2.
Int Heart J ; 60(5): 1061-1069, 2019 Sep 27.
Artigo em Inglês | MEDLINE | ID: mdl-31484870

RESUMO

Plaque erosion (PE) is a significant substrate of acute coronary thrombosis. An improved ability to distinguish plaque phenotype in vivo among patients with ST-segment elevation myocardial infarction (STEMI) is of considerable interest because of the potential to formulate tailored treatment. This study assessed the plaque features and screened the circulating microRNAs (miRNAs) characteristically expressed in patients with PE compared with those with plaque rupture (PR). An miRNA microarray profile was generated in an initial cohort of eight STEMI patients with PE and eight clinically matched subjects with PR to select the circulating miRNAs with significant differences. miRNAs of interest were validated in a prospective cohort, and the plaque characteristics of enrolled patients were assessed by optical coherence tomography (OCT). Thirty culprit lesions were classified as PE (32.6%) and 46 as PR (50%). The main component of PE was fibrotic tissue, whereas the chief component of PR was lipids (P < 0.001). Thirty-four miRNAs were differentially expressed between the two groups; we validated five candidates and found that only the level of circulating miR-3667-3p exhibited significant discriminatory power in predicting the presence of PE (AUC = 0.767; P < 0.001). Our results show that high levels of circulating miR-3667-3p are closely related to PE in STEMI patients, which provides further evidence for PE pathophysiology and potential tailor treatment strategies.


Assuntos
MicroRNA Circulante/sangue , Trombose Coronária/diagnóstico por imagem , Placa Aterosclerótica/complicações , Infarto do Miocárdio com Supradesnível do Segmento ST/sangue , Tomografia de Coerência Óptica/métodos , Idoso , Área Sob a Curva , Estudos de Casos e Controles , China , Angiografia Coronária/métodos , Trombose Coronária/mortalidade , Trombose Coronária/terapia , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Placa Aterosclerótica/patologia , Valor Preditivo dos Testes , Prognóstico , Curva ROC , Estudos Retrospectivos , Medição de Risco , Infarto do Miocárdio com Supradesnível do Segmento ST/diagnóstico por imagem , Infarto do Miocárdio com Supradesnível do Segmento ST/mortalidade , Infarto do Miocárdio com Supradesnível do Segmento ST/terapia , Estatísticas não Paramétricas , Análise de Sobrevida , Resultado do Tratamento
3.
BMC Bioinformatics ; 20(1): 466, 2019 Sep 10.
Artigo em Inglês | MEDLINE | ID: mdl-31500560

RESUMO

BACKGROUND: Although many of the genic features in Mycobacterium abscessus have been fully validated, a comprehensive understanding of the regulatory elements remains lacking. Moreover, there is little understanding of how the organism regulates its transcriptomic profile, enabling cells to survive in hostile environments. Here, to computationally infer the gene regulatory network for Mycobacterium abscessus we propose a novel statistical computational modelling approach: BayesIan gene regulatory Networks inferreD via gene coExpression and compaRative genomics (BINDER). In tandem with derived experimental coexpression data, the property of genomic conservation is exploited to probabilistically infer a gene regulatory network in Mycobacterium abscessus.Inference on regulatory interactions is conducted by combining 'primary' and 'auxiliary' data strata. The data forming the primary and auxiliary strata are derived from RNA-seq experiments and sequence information in the primary organism Mycobacterium abscessus as well as ChIP-seq data extracted from a related proxy organism Mycobacterium tuberculosis. The primary and auxiliary data are combined in a hierarchical Bayesian framework, informing the apposite bivariate likelihood function and prior distributions respectively. The inferred relationships provide insight to regulon groupings in Mycobacterium abscessus. RESULTS: We implement BINDER on data relating to a collection of 167,280 regulator-target pairs resulting in the identification of 54 regulator-target pairs, across 5 transcription factors, for which there is strong probability of regulatory interaction. CONCLUSIONS: The inferred regulatory interactions provide insight to, and a valuable resource for further studies of, transcriptional control in Mycobacterium abscessus, and in the family of Mycobacteriaceae more generally. Further, the developed BINDER framework has broad applicability, useable in settings where computational inference of a gene regulatory network requires integration of data sources derived from both the primary organism of interest and from related proxy organisms.


Assuntos
Biologia Computacional/métodos , Redes Reguladoras de Genes , Mycobacterium abscessus/genética , Software , Área Sob a Curva , Bactérias/genética , Simulação por Computador , Regulação Bacteriana da Expressão Gênica , Curva ROC , Regulon/genética
4.
BMC Bioinformatics ; 20(1): 462, 2019 Sep 09.
Artigo em Inglês | MEDLINE | ID: mdl-31500564

RESUMO

BACKGROUND: Determining the association between tumor sample and the gene is demanding because it requires a high cost for conducting genetic experiments. Thus, the discovered association between tumor sample and gene further requires clinical verification and validation. This entire mechanism is time-consuming and expensive. Due to this issue, predicting the association between tumor samples and genes remain a challenge in biomedicine. RESULTS: Here we present, a computational model based on a heat diffusion algorithm which can predict the association between tumor samples and genes. We proposed a 2-layered graph. In the first layer, we constructed a graph of tumor samples and genes where these two types of nodes are connected by "hasGene" relationship. In the second layer, the gene nodes are connected by "interaction" relationship. We applied the heat diffusion algorithms in nine different variants of genetic interaction networks extracted from STRING and BioGRID database. The heat diffusion algorithm predicted the links between tumor samples and genes with mean AUC-ROC score of 0.84. This score is obtained by using weighted genetic interactions of fusion or co-occurrence channels from the STRING database. For the unweighted genetic interaction from the BioGRID database, the algorithms predict the links with an AUC-ROC score of 0.74. CONCLUSIONS: We demonstrate that the gene-gene interaction scores could improve the predictive power of the heat diffusion model to predict the links between tumor samples and genes. We showed the efficient runtime of the heat diffusion algorithm in various genetic interaction network. We statistically validated our prediction quality of the links between tumor samples and genes.


Assuntos
Algoritmos , Genes Neoplásicos , Neoplasias/genética , Área Sob a Curva , Metilação de DNA/genética , Bases de Dados Factuais , Difusão , Epistasia Genética , Redes Reguladoras de Genes , Humanos , Curva ROC , Reprodutibilidade dos Testes
5.
JAMA ; 322(9): 868-886, 2019 09 03.
Artigo em Inglês | MEDLINE | ID: mdl-31479143

RESUMO

Importance: Medications to reduce risk of breast cancer are effective for women at increased risk but also cause adverse effects. Objective: To update the 2013 US Preventive Services Task Force systematic review on medications to reduce risk of primary (first diagnosis) invasive breast cancer in women. Data Sources: Cochrane Central Register of Controlled Trials and Database of Systematic Reviews, EMBASE, and MEDLINE (January 1, 2013, to February 1, 2019); manual review of reference lists. Study Selection: Discriminatory accuracy studies of breast cancer risk assessment methods; randomized clinical trials of tamoxifen, raloxifene, and aromatase inhibitors for primary breast cancer prevention; studies of medication adverse effects. Data Extraction and Synthesis: Investigators abstracted data on methods, participant characteristics, eligibility criteria, outcome ascertainment, and follow-up. Results of individual trials were combined by using a profile likelihood random-effects model. Main Outcomes and Measures: Probability of breast cancer in individuals (area under the receiver operating characteristic curve [AUC]); incidence of breast cancer, fractures, thromboembolic events, coronary heart disease events, stroke, endometrial cancer, and cataracts; and mortality. Results: A total of 46 studies (82 articles [>5 million participants]) were included. Eighteen risk assessment methods in 25 studies reported low accuracy in predicting the probability of breast cancer in individuals (AUC, 0.55-0.65). In placebo-controlled trials, tamoxifen (risk ratio [RR], 0.69 [95% CI, 0.59-0.84]; 4 trials [n = 28 421]), raloxifene (RR, 0.44 [95% CI, 0.24-0.80]; 2 trials [n = 17 806]), and the aromatase inhibitors exemestane and anastrozole (RR, 0.45 [95% CI, 0.26-0.70]; 2 trials [n = 8424]) were associated with a lower incidence of invasive breast cancer. Risk for invasive breast cancer was higher for raloxifene than tamoxifen in 1 trial after long-term follow-up (RR, 1.24 [95% CI, 1.05-1.47]; n = 19 747). Raloxifene was associated with lower risk for vertebral fractures (RR, 0.61 [95% CI, 0.53-0.73]; 2 trials [n = 16 929]) and tamoxifen was associated with lower risk for nonvertebral fractures (RR, 0.66 [95% CI, 0.45-0.98]; 1 trial [n = 13 388]) compared with placebo. Tamoxifen and raloxifene were associated with increased thromboembolic events compared with placebo; tamoxifen was associated with more events than raloxifene. Tamoxifen was associated with higher risk of endometrial cancer and cataracts compared with placebo. Symptomatic effects (eg, vasomotor, musculoskeletal) varied by medication. Conclusions and Relevance: Tamoxifen, raloxifene, and aromatase inhibitors were associated with lower risk of primary invasive breast cancer in women but also were associated with adverse effects that differed between medications. Risk stratification methods to identify patients with increased breast cancer risk demonstrated low accuracy.


Assuntos
Inibidores da Aromatase/uso terapêutico , Neoplasias da Mama/prevenção & controle , Moduladores Seletivos de Receptor Estrogênico/uso terapêutico , Tamoxifeno/uso terapêutico , Adulto , Área Sob a Curva , Inibidores da Aromatase/efeitos adversos , Neoplasias da Mama/genética , Feminino , Genes BRCA1 , Genes BRCA2 , Humanos , Mutação , Guias de Prática Clínica como Assunto , Cloridrato de Raloxifeno/efeitos adversos , Cloridrato de Raloxifeno/uso terapêutico , Medição de Risco/métodos , Fatores de Risco , Moduladores Seletivos de Receptor Estrogênico/efeitos adversos , Tamoxifeno/efeitos adversos
6.
Nan Fang Yi Ke Da Xue Xue Bao ; 39(8): 972-979, 2019 Aug 30.
Artigo em Chinês | MEDLINE | ID: mdl-31511219

RESUMO

OBJECTIVE: To evaluate rectal toxicity of radiotherapy for prostate cancer using a novel predictive model based on multi-modality and multi-classifier fusion. METHODS: We retrospectively collected the clinical data from 44 prostate cancer patients receiving external beam radiation (EBRT), including the treatment data, clinical parameters, planning CT data and the treatment plans. The clinical parameter features and dosimetric features were extracted as two different modality features, and a subset of features was selected to train the 5 base classifiers (SVM, Decision Tree, K-nearest-neighbor, Random forests and XGBoost). To establish the multi-modality and multi-classifier fusion model, a multi-criteria decision-making based weight assignment algorithm was used to assign weights for each base classifier under the same modality. A repeat 5-fold cross-validation and the 4 indexes including the area under ROC curve (AUC), accuracy, sensitivity and specificity were used to evaluate the proposed model. In addition, the proposed model was compared quantitatively with different feature selection methods, different weight allocation algorithms, the model based on single mode single classifier, and two integrated models using other fusion methods. RESULTS: Repeated (5 times) 5-fold cross validation of the proposed model showed an accuracy of 0.78 for distinguishing toxicity from non-toxicity with an AUC of 0.83, a specificity of 0.79 and a sensitivity of 0.76. CONCLUSIONS: Compared with the models based on a single mode or a single classifier and other fusion models, the proposed model can more accurately predict rectal toxicity of radiotherapy for prostate cancer.


Assuntos
Neoplasias da Próstata , Reto , Algoritmos , Área Sob a Curva , Humanos , Masculino , Estudos Retrospectivos
7.
Ideggyogy Sz ; 72(7-8): 257-263, 2019 Jul 30.
Artigo em Inglês | MEDLINE | ID: mdl-31517458

RESUMO

Background and purpose: Nonconvulsive status epilepticus (NCSE) is a heterogeneous, severe neurological disorder of different etiologies. In this study, the outcomes of NCSE episodes was assessed in a large series of adult patients. Our objective was to evaluate relationship between Status Epilepticus Severity Score (STESS) and etiology and the role of etiological factors on predicting the outcomes. Methods: In this retrospective study, the medical records of 95 patients over 18 years of age who were diagnosed with NCSE between June 2011 and December 2015 were reviewed. Their treatment and follow-up for NCSE was performed at the Epilepsy Unit in Department of Neurology, Antalya Research and Training Hospital. Etiological factors thought to be responsible for NCSE episodes as well as the prognostic data were retrieved. The etiological factors were classified into three groups as those with a known history of epilepsy (Group 1), primary neurological disorder (Group 2), or systemic/unknown etiology (Group 3). STESS was retrospectively applied to patients. Results: There were 95 participants, 59 of whom were female. Group 1, Group 2, and Group 3 consisted of 11 (7 female), 54 (33 female), and 30 (19 female) patients, respectively. Of the 18 total deaths, 12 occurred in Group 2, and 6 in Group 3. The negative predictive value for a STESS score of ≤ 2 was 93.88% (+LR 2.05 95% CI: 1.44-2.9 and -LR 0.3 95% CI 0.10-0.84 ) in the overall study group. While the corresponding values for Group 1 (patients with epilepsy), Group 2 (patients with primary neurological disorder), and group 3 (patients with systemic or unknown etiology) were 100%, 92.59% (+LR 2.06 95%CI: 1.32-3.21 and -LR 0.28 95% CI 0.08-1.02 ) 83.33% (+LR 1.14 95%CI: 0.59-2.9 and -LR 0.80 95% CI 0.23-2.73). Conclusion: This study included the one of the largest patients series ever reported in whom STESS, a clinical scoring system proposed for use in patients with status epilepticus, has been implemented. Although STESS appeared to be quite useful for predicting a favorable outcome in NCSE patients with epilepsy and primary neurological disorders, its predictive value in patients with systemic or unknown etiology was lower. Further prospective studies including larger NCSE samples are warranted.


Assuntos
Eletroencefalografia/estatística & dados numéricos , Estado Epiléptico/diagnóstico , Estado Epiléptico/etiologia , Adolescente , Adulto , Área Sob a Curva , Epilepsia/diagnóstico , Epilepsia/epidemiologia , Feminino , Humanos , Avaliação de Resultados (Cuidados de Saúde) , Prognóstico , Curva ROC , Estudos Retrospectivos , Índice de Gravidade de Doença , Estado Epiléptico/epidemiologia
8.
Stud Health Technol Inform ; 264: 368-372, 2019 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-31437947

RESUMO

The onset of acute kidney injury (AKI) during an intensive care unit (ICU) admission is associated with increased morbidity and mortality. Developing novel methods to identify early AKI onset is of critical importance in preventing or reducing AKI complications. We built and applied multiple machine learning models to integrate clinical notes and structured physiological measurements and estimate the risk of new AKI onset using the MIMIC-III database. From the clinical notes, we generated clinically meaningful word representations and embeddings. Four supervised learning classifiers and mixed-feature deep learning architecture were used to construct prediction models. The best configurations consistently utilized both structured and unstructured clinical features and yielded competitive AUCs above 0.83. Our work suggests that integrating structured and unstructured clinical features can be effectively applied to assist clinicians in identifying the risk of incident AKI onset in critically-ill patients upon admission to the ICU.


Assuntos
Lesão Renal Aguda , Área Sob a Curva , Cuidados Críticos , Estado Terminal , Humanos , Unidades de Terapia Intensiva
9.
Stud Health Technol Inform ; 264: 482-486, 2019 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-31437970

RESUMO

Recently, the National Institutes of Health (NIH) published a chest X-ray image database named "ChestX-ray8", which contains 108,948 X-ray images that are labeled with eight types of diseases. Identifying the pathologies from the clinical images is a challenging task even for human experts, and to develop computer-aided diagnosis systems to help humans identify the pathologies from images is an urgent need. In this study, we applied the deep learning methods to identify the cardiomegaly from the X-ray images. We tested our algorithms on a dataset containing 600 images, and obtained the best performance with an area under the curve (AUC) of 0.87 using the transfer learning method. This result indicates the feasibility of developing computer-aided diagnosis systems for different pathologies from X-rays using deep learning techniques.


Assuntos
Algoritmos , Cardiomegalia , Diagnóstico por Computador , Área Sob a Curva , Aprendizado Profundo , Humanos
10.
Stud Health Technol Inform ; 264: 223-227, 2019 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-31437918

RESUMO

We tested the value of adding data from the operating room to models predicting in-hospital death. We assessed model performance using two metrics, the area under the receiver operating characteristic curve (AUROC) and the area under the precision-recall curve (AUPRC), to illustrate the differences in information they convey in the setting of class imbalance. Data was collected on 74,147 patients who underwent major noncardiac surgery and 112 unique features were extracted from electronic health records. Sets of features were incrementally added to models using logistic regression, naïve Bayes, random forest, and gradient boosted machine methods. AUROC increased as more features were added, but changes were small for some modeling approaches. In contrast, AUPRC, which reflects positive predicted value, exhibited improvements across all models. Using AUPRC highlighted the added value of intraoperative data, not seen consistently with AUROC, and that with class imbalance AUPRC may serve as the more clinically relevant criterion.


Assuntos
Registros Eletrônicos de Saúde , Área Sob a Curva , Teorema de Bayes , Humanos , Modelos Logísticos , Curva ROC
11.
Expert Opin Drug Metab Toxicol ; 15(9): 697-703, 2019 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-31382802

RESUMO

Background: D-chiro-inositol (DCI) and glucose transporter inhibitors may inhibit myo-inositol (MI) transporters, and the aim is to clinically evaluate their effect on MI absorption. Research design and methods: Fasting 18 healthy volunteers received orally 6000 mg MI, 6000 mg MI with 1000 mg DCI, and 6000 mg MI with SelectSIEVE® Apple PCQ and Sorbitol, Maltodextrin and Sucralose (PCQ-SMS), in three different phases with a washout period of 7 days. At each phase, blood samples were collected before administration, and every 60 minutes until 540 minutes after administration. MI plasma levels (µmol/L) were quantified by gas chromatography-mass spectrometry; maximum plasma concentration (Cmax), time to reach it (Tmax), and the area under the time-concentration curve of MI (AUC 0-540) were evaluated. Results: The Cmax of MI alone (Tmax = 180min) was 1.29-fold higher than those of MI with DCI (Tmax = 180min) (p < 0.001) and 1.69-fold higher than those of MI with PCQ-SMS (Tmax = 240min) (p < 0.001). The AUC 0-540 was reduced by 19.09% in MI plus DCI (p = 0.0118) and by 31.8% in MI plus PCQ-SMS (p < 0.001) as compared to MI alone. Conclusions: DCI, glucose transporter inhibitors and sugars, such as sorbitol and maltodextrin, seem to inhibit MI absorption, decreasing MI plasma concentration as compared to MI alone.


Assuntos
Proteínas Facilitadoras de Transporte de Glucose/antagonistas & inibidores , Inositol/administração & dosagem , Absorção Intestinal , Adulto , Área Sob a Curva , Transporte Biológico , Interações de Medicamentos , Feminino , Cromatografia Gasosa-Espectrometria de Massas , Humanos , Inositol/farmacocinética , Masculino , Polissacarídeos/administração & dosagem , Polissacarídeos/farmacologia , Sorbitol/administração & dosagem , Sorbitol/farmacologia , Sacarose/administração & dosagem , Sacarose/análogos & derivados , Sacarose/farmacologia , Fatores de Tempo , Adulto Jovem
12.
Expert Opin Drug Metab Toxicol ; 15(9): 735-749, 2019 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-31402708

RESUMO

Introduction: Vancomycin is commonly administered to neonates, while observational data on therapeutic drug monitoring (TDM, trough levels) suggest that vancomycin exposure and dosage remain substandard. Area covered: Data on vancomycin pharmacokinetics (PK) and its covariates are abundant. Consequently, modeling is an obvious tool to improve targeted exposure, with a shift from TDM trough levels to area under the curve (AUC24h) targets, as in adults. Continuous administration appeared as a practice to facilitate AUC24h target attainment, while Bayesian model-supported targeting emerged as a novel tool. However, the AUC24h/MIC (minimal inhibitory concentration) target itself should consider neonate-specific aspects (bloodstream infections, coagulase-negative staphylococci, protein binding, underexplored causes of variability, like assays, preparation and administration inaccuracies, or missing covariates). Expert opinion: To improve targeted exposure in neonates, initial vancomycin prescription should be based on 'a priori model-based individual dosing' using validated dosing regimens, followed by further tailoring by dosing optimization applying Bayesian estimation-assisted TDM. Future research should focus on the feasibility to integrate these tools (individualized dosing, Bayesian models) in clinical practice, and to perform PK/PD studies in the relevant animal models and human neonatal setting (coagulase-negative staphylococci, bloodstream infections).


Assuntos
Antibacterianos/administração & dosagem , Modelos Biológicos , Vancomicina/administração & dosagem , Animais , Antibacterianos/farmacocinética , Área Sob a Curva , Teorema de Bayes , Relação Dose-Resposta a Droga , Monitoramento de Medicamentos/métodos , Humanos , Recém-Nascido , Testes de Sensibilidade Microbiana , Vancomicina/farmacocinética
13.
BMC Bioinformatics ; 20(1): 425, 2019 Aug 15.
Artigo em Inglês | MEDLINE | ID: mdl-31416434

RESUMO

BACKGROUND: Literature Based Discovery (LBD) produces more potential hypotheses than can be manually reviewed, making automatically ranking these hypotheses critical. In this paper, we introduce the indirect association measures of Linking Term Association (LTA), Minimum Weight Association (MWA), and Shared B to C Set Association (SBC), and compare them to Linking Set Association (LSA), concept embeddings vector cosine, Linking Term Count (LTC), and direct co-occurrence vector cosine. Our proposed indirect association measures extend traditional association measures to quantify indirect rather than direct associations while preserving valuable statistical properties. RESULTS: We perform a comparison between several different hypothesis ranking methods for LBD, and compare them against our proposed indirect association measures. We intrinsically evaluate each method's performance using its ability to estimate semantic relatedness on standard evaluation datasets. We extrinsically evaluate each method's ability to rank hypotheses in LBD using a time-slicing dataset based on co-occurrence information, and another time-slicing dataset based on SemRep extracted-relationships. Precision and recall curves are generated by ranking term pairs and applying a threshold at each rank. CONCLUSIONS: Results differ depending on the evaluation methods and datasets, but it is unclear if this is a result of biases in the evaluation datasets or if one method is truly better than another. We conclude that LTC and SBC are the best suited methods for hypothesis ranking in LBD, but there is value in having a variety of methods to choose from.


Assuntos
Descoberta Baseada em Literatura , Modelos Teóricos , Área Sob a Curva , Bases de Dados como Assunto , Humanos , Curva ROC , Semântica , Estatísticas não Paramétricas
14.
BMC Bioinformatics ; 20(1): 415, 2019 Aug 06.
Artigo em Inglês | MEDLINE | ID: mdl-31387547

RESUMO

BACKGROUND: Predicting the effect of drug-drug interactions (DDIs) precisely is important for safer and more effective drug co-prescription. Many computational approaches to predict the effect of DDIs have been proposed, with the aim of reducing the effort of identifying these interactions in vivo or in vitro, but room remains for improvement in prediction performance. RESULTS: In this study, we propose a novel deep learning model to predict the effect of DDIs more accurately.. The proposed model uses autoencoders and a deep feed-forward network that are trained using the structural similarity profiles (SSP), Gene Ontology (GO) term similarity profiles (GSP), and target gene similarity profiles (TSP) of known drug pairs to predict the pharmacological effects of DDIs. The results show that GSP and TSP increase the prediction accuracy when using SSP alone, and the autoencoder is more effective than PCA for reducing the dimensions of each profile. Our model showed better performance than the existing methods, and identified a number of novel DDIs that are supported by medical databases or existing research. CONCLUSIONS: We present a novel deep learning model for more accurate prediction of DDIs and their effects, which may assist in future research to discover novel DDIs and their pharmacological effects.


Assuntos
Aprendizado Profundo , Interações de Medicamentos , Modelos Teóricos , Área Sob a Curva , Bases de Dados Factuais , Humanos , Redes Neurais (Computação) , Máquina de Vetores de Suporte
15.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi ; 36(4): 613-618, 2019 Aug 25.
Artigo em Chinês | MEDLINE | ID: mdl-31441262

RESUMO

Study of the mechanical properties of in vivo corneal materials is an important basis for further study of corneal physiological and pathological phenomena by means of finite element method. In this paper, the elastic coefficient ( E) and viscous coefficient ( η) of normal cornea and keratoconus under pulse pressure are calculated by using standard linear solid model with the data provided by corneal visualization scheimpflug technology. The results showed that there was a significant difference of E and η between normal cornea and keratoconus cornea ( P < 0.05). Receiver operating characteristic curve analysis showed that the area under curve (AUC) for E, η and their combined indicators were 0.776, 0.895 and 0.948, respectively, which indicated that keratoconus could be predicted by E and η. The results of this study may provide a reference for the early diagnosis of keratoconus and avoid the occurrence of keratoconus after operation, so it has a certain clinical value.


Assuntos
Córnea/fisiologia , Elasticidade , Ceratocone/patologia , Viscosidade , Área Sob a Curva , Humanos , Curva ROC
16.
BMC Bioinformatics ; 20(1): 421, 2019 Aug 13.
Artigo em Inglês | MEDLINE | ID: mdl-31409274

RESUMO

BACKGROUND: Ultra-fast pseudo-alignment approaches are the tool of choice in transcript-level RNA sequencing (RNA-seq) analyses. Unfortunately, these methods couple the tasks of pseudo-alignment and transcript quantification. This coupling precludes the direct usage of pseudo-alignment to other expression analyses, including alternative splicing or differential gene expression analysis, without including a non-essential transcript quantification step. RESULTS: In this paper, we introduce a transcriptome segmentation approach to decouple these two tasks. We propose an efficient algorithm to generate maximal disjoint segments given a transcriptome reference library on which ultra-fast pseudo-alignment can be used to produce per-sample segment counts. We show how to apply these maximally unambiguous count statistics in two specific expression analyses - alternative splicing and gene differential expression - without the need of a transcript quantification step. Our experiments based on simulated and experimental data showed that the use of segment counts, like other methods that rely on local coverage statistics, provides an advantage over approaches that rely on transcript quantification in detecting and correctly estimating local splicing in the case of incomplete transcript annotations. CONCLUSIONS: The transcriptome segmentation approach implemented in Yanagi exploits the computational and space efficiency of pseudo-alignment approaches. It significantly expands their applicability and interpretability in a variety of RNA-seq analyses by providing the means to model and capture local coverage variation in these analyses.


Assuntos
Algoritmos , Transcriptoma , Processamento Alternativo , Animais , Área Sob a Curva , Drosophila/genética , Humanos , RNA/química , RNA/metabolismo , Curva ROC , Análise de Sequência de RNA
17.
Medicine (Baltimore) ; 98(34): e16930, 2019 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-31441881

RESUMO

Few studies have demonstrated the prognostic potential of neutrophil gelatinase-associated lipocalin (NGAL) in post-cardiac arrest patients. This study evaluated the usefulness of plasma NGAL in predicting neurologic outcome and mortality in out-of-hospital cardiac arrest (OHCA) patients treated with targeted temperature management (TTM). A prospective observational study was conducted between October 2013 and April 2016 at a single tertiary hospital. We enrolled 75 patients treated with TTM and collected their demographic data, cardiopulmonary resuscitation-related information, data on plasma NGAL concentration, and prognostic test results. Plasma NGAL was measured at 4 hours after return of spontaneous circulation (ROSC). The primary endpoint was the neurologic outcome at discharge and the secondary outcome was 28-day mortality. Neurologic outcomes were analyzed using a stepwise multivariate logistic regression while 28-day mortality was analyzed using a stepwise Cox regression. The predictive performance of plasma NGAL for neurologic outcome was measured by the area under the receiver operating characteristic curve and the predictability of 28-day mortality was measured using Harrell C-index. We also compared the predictive performance of plasma NGAL to that of other traditional prognostic modalities for outcome variables. Thirty patients (40%) had good neurologic outcomes and 53 (70.7%) survived for more than 28 days. Plasma NGAL in patients with good neurologic outcomes was 122.7 ±â€Š146.7 ng/ml, which was significantly lower than that in the poor neurologic outcome group (307.5 ±â€Š269.6 ng/ml; P < .001). The probability of a poor neurologic outcome was more than 3.3-fold in the NGAL >124.3 ng/ml group (odds ratio, 3.321; 95% confidence interval [CI], 1.265-8.721]). Plasma NGAL in the survived group was significantly lower than that in the non-survived group (172.7 ±â€Š191.6 vs 379.9 ±â€Š297.8 ng/ml; P = .005). Plasma NGAL was significantly correlated with 28-day mortality (hazard ratio 1.003, 95% CI 1.001-1.004; P < .001). The predictive performance of plasma NGAL was not inferior to that of other prognostic modalities except electroencephalography. Plasma NGAL is valuable for predicting the neurologic outcome and 28-day mortality of patients with OHCA at an early stage after ROSC.This study was registered at ClinicalTrials.gov on November 19, 2013 (Identifier: NCT01987466).


Assuntos
Hipotermia Induzida/estatística & dados numéricos , Lipocalina-2/sangue , Parada Cardíaca Extra-Hospitalar/sangue , Adulto , Idoso , Área Sob a Curva , Biomarcadores/sangue , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Parada Cardíaca Extra-Hospitalar/mortalidade , Parada Cardíaca Extra-Hospitalar/terapia , Valor Preditivo dos Testes , Modelos de Riscos Proporcionais , Estudos Prospectivos
18.
Medicine (Baltimore) ; 98(34): e16962, 2019 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-31441900

RESUMO

The emergency department (ED) serves as the first point of hospital contact for most septic patients. Early mortality risk stratification using a quick and accurate triage tool would have great value in guiding management. The mortality in emergency department sepsis (MEDS) score was developed to risk stratify patients presenting to the ED with suspected sepsis, and its performance in the literature has been promising. We report in this study the first utilization of the MEDS score in a Singaporean cohort.In this retrospective observational cohort study, adult patients presenting to the ED with suspected sepsis and fulfilling systemic inflammatory response syndrome (SIRS) criteria were recruited. Primary outcome was 30-day in-hospital mortality (IHM) and secondary outcome was 72-hour mortality. MEDS, acute physiology and chronic health evaluation II (APACHE II), and sequential organ failure assessment (SOFA) scores were compared for prediction of primary and secondary outcomes. Receiver operating characteristic (ROC) analysis was conducted to compare predictive performance.Of the 249 patients included in the study, 46 patients (18.5%) met 30-day IHM. MEDS score achieved an area under the ROC curve (AUC) of 0.87 (95% confidence interval [CI], 0.82-0.93), outperforming the APACHE II score (0.77, 95% CI 0.69-0.85) and SOFA score (0.78, 95% CI 0.71-0.85). On secondary analysis, MEDS score was superior to both APACHE II and SOFA scores in predicting 72-hour mortality, with AUC of 0.88 (95% CI 0.82-0.95), 0.81 (95% CI 0.72-0.89), and 0.79 (95% CI 0.71-0.87), respectively. In predicting 30-day IHM, MEDS score ≥12, APACHE II score ≥23, and SOFA score ≥5 performed at sensitivities of 76.1%, 67.4%, and 76.1%, and specificities of 83.3%, 73.9%, and 65.0%, respectively.The MEDS score performed well in its ability for mortality risk stratification in a Singaporean ED cohort.


Assuntos
Serviço Hospitalar de Emergência/estatística & dados numéricos , Sepse/mortalidade , Triagem/métodos , Área Sob a Curva , Mortalidade Hospitalar , Humanos , Medição de Risco , Índice de Gravidade de Doença , Singapura/epidemiologia
19.
Medicine (Baltimore) ; 98(31): e16511, 2019 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-31374012

RESUMO

Blood-based biomarkers, such as carcinoembryonic antigen (CEA), and saliva-based biomarkers, such as mRNA, have emerged as potential liquid biopsies for non-invasive detection of many cancers. However, current tests typically use single type of biomarkers, and their sensitivity and specificity is often unsatisfactory.In this study, we developed a novel biomarker panel that measures both CEA level in blood and GREB1 and FRS2 levels in saliva to achieve high sensitivity and high specificity in detecting Non-Small Cell Lung Cancer (NSCLC).In the discovery phase, we achieved sensitivity of 96.67% and specificity of 93.33% for 30 NSCLC patients and 30 healthy controls. To further evaluate the prediction performance of our biomarker panel, we applied it to an independent set of 15 NSCLC cancer patients and 25 healthy controls. The sensitivity and specificity of our test reached 93.33% and 80.00% respectively.Our study discovered that the combined analysis of CEA and mRNA can be a novel liquid-biopsy technology for non-invasive detection of NSCLC.


Assuntos
Biomarcadores Tumorais/análise , Antígeno Carcinoembrionário/análise , Carcinoma Pulmonar de Células não Pequenas/diagnóstico , Proteínas Adaptadoras de Transdução de Sinal/análise , Idoso , Área Sob a Curva , Antígeno Carcinoembrionário/sangue , Carcinoma Pulmonar de Células não Pequenas/enzimologia , Feminino , Humanos , Masculino , Proteínas de Membrana/análise , Pessoa de Meia-Idade , Proteínas de Neoplasias/análise , Curva ROC , Saliva/enzimologia
20.
BMC Infect Dis ; 19(1): 639, 2019 Jul 19.
Artigo em Inglês | MEDLINE | ID: mdl-31324224

RESUMO

BACKGROUND: Systemic Inflammatory Response Syndrome (SIRS) criteria are often used to evaluate the risk of sepsis and to identify in-hospital mortality among patients with suspected infection. However, utilization of the SIRS criteria in mortality prediction among geriatric patients with influenza in the emergency department (ED) remains unclear. Therefore, we conducted a research to delineate this issue. METHODS: This is a retrospective case-control study including geriatric patients (age ≥ 65 years) with influenza, who presented to the ED of a medical center between January 1, 2010 and December 31, 2015. Vital signs, past history, subtype of influenza, demographic data, and outcomes were collected from all patients and analyzed. We calculated the accuracy for predicting 30-days mortality using the SIRS criteria. We also performed covariate adjustment of the area under the receiver operating characteristic curve (AUROC) via regression modeling. RESULTS: We recruited a total of 409 geriatric patients in the ED, with mean age 79.5 years and an equal sex ratio. The mean SIRS criteria score was 1.9 ± 1.1. The result of a Hosmer-Lemeshow goodness-of-fit test was 0.34 for SIRS criteria. SIRS criteria score ≥ 3 showed better mortality prediction, with odds ratio (OR) 3.37 (95% confidence interval (CI), 1.05-10.73); SIRS score ≥ 2 showed no statistical significance, with p = 0.85 (OR, 1.15; 95% CI, 0.28-4.69). SIRS score ≥ 3 had acceptable 30-days mortality discrimination, with AUROC 0.77 (95% CI, 0.68-0.87) after adjustment. SIRS score ≥ 3 also had a notable negative predictive value of 0.97 (95% CI, 0.94-0.99). CONCLUSION: The presence of a higher number of SIRS criteria (≥ 3) showed greater accuracy for predicting mortality among geriatric patients with influenza.


Assuntos
Influenza Humana/mortalidade , Síndrome de Resposta Inflamatória Sistêmica/diagnóstico , Idoso , Idoso de 80 Anos ou mais , Área Sob a Curva , Estudos de Casos e Controles , Serviço Hospitalar de Emergência/estatística & dados numéricos , Feminino , Mortalidade Hospitalar , Humanos , Masculino , Prognóstico , Curva ROC , Estudos Retrospectivos , Taiwan/epidemiologia
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