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1.
Artigo em Inglês | MEDLINE | ID: mdl-34501584

RESUMO

Due to the high effectiveness of cancer screening and therapies, the diagnosis of second primary cancers (SPCs) has increased in women with endometrial cancer (EC). However, previous studies providing adequate evidence to support screening for SPCs in endometrial cancer are lacking. This study aimed to develop effective risk prediction models of second primary endometrial cancer (SPEC) in women with obesity (body mass index (BMI) > 25) and included datasets on the incidence of SPEC and the other risks of SPEC in 4480 primary cancer survivors from a hospital-based cancer registry database. We found that obesity plays a key role in SPEC. We used 10 independent variables as predicting variables, which correlated to obesity, and so should be monitored for the early detection of SPEC in endometrial cancer. Our proposed scheme is promising for SPEC prediction and demonstrates the important influence of obesity and clinical data representation in all cases following primary treatments. Our results suggest that obesity is still a crucial risk factor for SPEC in endometrial cancer.


Assuntos
Neoplasias do Endométrio , Segunda Neoplasia Primária , Índice de Massa Corporal , Neoplasias do Endométrio/epidemiologia , Feminino , Hospitais , Humanos , Obesidade/complicações , Obesidade/epidemiologia , Sistema de Registros , Fatores de Risco
2.
Pharmaceuticals (Basel) ; 14(6)2021 Jun 17.
Artigo em Inglês | MEDLINE | ID: mdl-34204249

RESUMO

The vascular nitric oxide (NO) system has a protective effect in atherosclerosis. NO is generated from the conversion of L-arginine to L-citrulline by the enzymatic action of endothelial NO synthase (eNOS). Compounds with the effect of enhancing eNOS expression are considered to be candidates for the prevention of atherosclerosis. In this study, extracts from the aerial, root, and whole plant of Glossogyne tenuifolia (GT) were obtained with ethanol, n-hexane, ethyl acetate (EA), and methanol extraction, respectively. The effects of these GT extracts on the synthesis of NO and the expression of eNOS in human umbilical vein endothelial cells (HUVECs) were investigated. NO production was determined as nitrite by colorimetry, following the Griess reaction. The treatment of HUVECs with EA extract from the root of GT and n-hexane, methanol, and ethanol extract from the aerial, root, and whole plant of GT increased NO production in a dose-dependent manner. When at a dose of 160 µg/mL, NO production increased from 0.9 to 18.4-fold. Among these extracts, the methanol extract from the root of GT (R/M GTE) exhibited the most potent effect on NO production (increased by 18.4-fold). Furthermore, using Western blot and RT-PCR analysis, treatment of HUVECs with the R/M GTE increased both eNOS protein and mRNA expression. In addition, Western blot analysis revealed that the R/M GTE increased eNOS phosphorylation at serine1177 as early as 15 min after treatment. The chemical composition for the main ingredients was also performed by HPLC analysis. In conclusion, the present study demonstrated that GT extracts increased NO production in HUVECs and that the R/M GTE increased NO production via increasing eNOS expression and activation by phosphorylation of eNOS at serine1177.

3.
Front Immunol ; 12: 626582, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34054800

RESUMO

There is a need to increase the vaccine completion rates in women who have already received human papillomavirus (HPV) vaccines. With vaccines requiring multiple doses, designing a vaccination control program and increasing the proportion of women who complete vaccination are critical and remain as huge challenges. Currently, there are no published reports on the differences in the background characteristics between postpartum women who are vaccinated or unvaccinated against HPV. This study aimed to determine the vaccination rates of the second and third doses of HPV vaccination utilizing an achievable HPV vaccination program in postpartum women. In this retrospective study, 243 postpartum women attending Chiayi Chang Gung Memorial Hospital between March and September 2014 were enrolled. These women were classified into two groups: one group received the HPV vaccine under a practical, controlled postpartum HPV vaccination program, and the other group did not. The rates for the second and third rounds of HPV vaccination in postpartum women were calculated. The differences in the background characteristics between the two groups were determined using the Student's t test, chi-square test or Fisher's exact test, and the multiple logistic models, as appropriate. Under the controlled postpartum HPV vaccination program, the completion rate for the three doses of postpartum HPV vaccination was 97.2%. Significant differences were observed according to maternal age, gender of the newborn, and postpartum Pap smear results between the two groups in our study. In conclusion, the controlled postpartum HPV vaccination program is a reasonable method for achieving an excellent completion rate for the three doses of postpartum HPV vaccination and may be a good model for any multiple-dose vaccination protocol.


Assuntos
Alphapapillomavirus/imunologia , Programas de Imunização , Esquemas de Imunização , Adesão à Medicação , Infecções por Papillomavirus/prevenção & controle , Vacinas contra Papillomavirus/administração & dosagem , Período Pós-Parto , Neoplasias do Colo do Útero/prevenção & controle , Recusa de Vacinação , Adolescente , Adulto , Alphapapillomavirus/patogenicidade , Feminino , Humanos , Pessoa de Meia-Idade , Infecções por Papillomavirus/imunologia , Infecções por Papillomavirus/virologia , Vacinas contra Papillomavirus/efeitos adversos , Gravidez , Estudos Retrospectivos , Fatores de Risco , Fatores de Tempo , Neoplasias do Colo do Útero/imunologia , Neoplasias do Colo do Útero/virologia , Adulto Jovem
4.
J Neurogenet ; 35(1): 29-32, 2021 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-33332175

RESUMO

Spinal muscular atrophy (SMA) is a common autosomal recessive disorder which has been considered as the second common cause of infant death, with an estimated prevalence of 1 in 10,000 live births. The disorder is caused by survival motor neuron 1 gene (SMN1) deficiency leading to limb weakness, difficult swallowing and abnormal breathing. Here, a fast and accurate method for SMA detection has been developed. Genomic DNA sample collected from whole blood, amniotic fluid, or dried blood spots can be analysed by using the Clarity™ Digital PCR (dPCR) System for determining the copy numbers of SMN1 and SMN2 genes. Two hundred and fourteen clinical samples determined by qPCR-based method were enrolled and used to establish the cut-off ranges for unaffected individual, SMA carrier and SMA patient categories. After setting the cut-off range for each group, 12 samples were analyzed by both dPCR-based method and MLPA (multiplex ligation-dependent probe amplification), the current testing golden standard for SMA, and 100% concordant results between the two testing methods were performed. CSB SMA Detection Kit combined with dPCR platform provides a robust and precise approach to distinguish unaffected individuals, SMA carrier and SMA patients. This rapid molecular diagnostic method can be adapted to pre-pregnancy eugenics inspection, prenatal testing as well as newborns screening and help physicians or genetic counselors to improve population SMA incidence.

5.
Molecules ; 25(24)2020 Dec 10.
Artigo em Inglês | MEDLINE | ID: mdl-33321921

RESUMO

The proliferation and migration of vascular smooth muscle cells (VSMCs) are essential in the pathogenesis of various vascular diseases, such as atherosclerosis and restenosis. Among the mediators of VSMC during atherosclerosis development, platelet-derived growth factor (PDGF)-BB is a potent mitogen for VSMCs and greatly contributes to the intimal accumulation of VSMCs. Glossogyne tenuifolia (GT, Xiang-Ru) is a traditional antipyretic and hepatoprotective herb from Penghu Island, Taiwan. This study evaluated the inhibitory effect of GT ethanol extract (GTE) and GT water extract (GTW) on proliferative and migratory activities in PDGF-BB-induced VSMCs. The experimental results demonstrated that GTE significantly inhibited the PDGF-BB-stimulated VSMC proliferation and migration, as shown by MTT, wound healing, and Boyden chamber assays. GTE was found to have a much more potent inhibitory activity than GTW. Based on the Western blot analysis, GTE significantly blocked the PDGF-BB-induced phosphorylation of NF-κB and mitogen-activated protein kinase (MAPK) pathways, including extracellular signal-regulated kinase (ERK), p38, and JNK, in VSMCs. In addition, GTE retarded the PDGF-BB-mediated migration through the suppression of matrix metalloproteinase (MMP)-2 and MMP-9 expression in VSMCs. Three main ingredients of GT-chlorogenic acid, luteolin-7-glucoside, and luteolin-all showed significant anti-proliferative effects on PDGF-BB-induced VSMCs. As a whole, our findings indicated that GTE has the potential to be a therapeutic agent to prevent or treat restenosis or atherosclerosis.


Assuntos
Músculo Liso Vascular/efeitos dos fármacos , Miócitos de Músculo Liso/efeitos dos fármacos , Extratos Vegetais/química , Extratos Vegetais/farmacologia , Plantas Medicinais/química , Animais , Aorta , Becaplermina/farmacologia , Movimento Celular/efeitos dos fármacos , Proliferação de Células/efeitos dos fármacos , Células Cultivadas , Relação Dose-Resposta a Droga , Proteínas Quinases Ativadas por Mitógeno , NF-kappa B , Extratos Vegetais/isolamento & purificação , Ratos , Transdução de Sinais , Taiwan
6.
Artigo em Inglês | MEDLINE | ID: mdl-32942728

RESUMO

Unlike most daily decisions, medical decision making often has substantial consequences and trade-offs. Recently, big data analytics techniques such as statistical analysis, data mining, machine learning and deep learning can be applied to construct innovative decision models. With complex decision making, it can be difficult to comprehend and compare the benefits and risks of all available options to make a decision. For these reasons, this Special Issue focuses on the use of big data analytics and forms of public health decision making based on the decision model, spanning from theory to practice. A total of 64 submissions were carefully blind peer reviewed by at least two referees and, finally, 23 papers were selected for this Special Issue.


Assuntos
Big Data , Tomada de Decisão Clínica , Mineração de Dados , Saúde Pública , Aprendizado de Máquina
7.
Molecules ; 25(18)2020 Sep 14.
Artigo em Inglês | MEDLINE | ID: mdl-32937928

RESUMO

Antrodia cinnamomea (AC) has been shown to have anti-inflammatory, anti-tumor, and immunomodulation activities. It is estimated that hundreds of metric tons of AC extraction waste (ACEW) are produced per year in Taiwan. This study aims to assess the feasibility of applying ACEW as feed supplement in the aquaculture industry. ACEW significantly inhibited the growth of microorganisms in the water tank, by around 39.4% reduction on the fifth day with feed supplemented of 10% ACEW. The feed conversion efficiency of zebrafish with 10% ACEW supplementation for 30 days was 1.22-fold compared to that of the control. ACEW dramatically improved the tolerances of zebrafish under the heat and cold stresses. When at water temperature extremes of 38 °C or 11 °C, compared to the 100% mortality rate in the control group, the 10% ACEW diet group still had 91.7% and 83.3% survival rates, respectively. In a caudal fin amputation test, the fin recovery of zebrafish was increased from 68.4% to 93% with 10% ACEW diet after 3-week regeneration. ACEW effectively down-regulated the gene expression of TNF-α, IL-1ß, IL-6, and IL-10, and up-regulated the gene expression of IL-4/13A. Additionally, the supplement of ACEW in the feed can maintain and prevent the fish's body weight from dropping too much under enteritis. Taken together, ACEW has beneficial potential in aquaculture.


Assuntos
Aquicultura , Resíduos Industriais , Polyporales/química , Regeneração/efeitos dos fármacos , Amputação , Ração Animal , Animais , Anti-Infecciosos/química , Anti-Inflamatórios/química , Peso Corporal/efeitos dos fármacos , Temperatura Baixa , Suplementos Nutricionais , Feminino , Temperatura Alta , Concentração de Íons de Hidrogênio , Inflamação/tratamento farmacológico , Masculino , Polissacarídeos/química , Triterpenos/química , Água/análise , Peixe-Zebra/fisiologia
8.
Artigo em Inglês | MEDLINE | ID: mdl-32664271

RESUMO

Developing effective risk prediction models is a cost-effective approach to predicting complications of chronic kidney disease (CKD) and mortality rates; however, there is inadequate evidence to support screening for CKD. In this study, four data mining algorithms, including a classification and regression tree, a C4.5 decision tree, a linear discriminant analysis, and an extreme learning machine, are used to predict early CKD. The study includes datasets from 19,270 patients, provided by an adult health examination program from 32 chain clinics and three special physical examination centers, between 2015 and 2019. There were 11 independent variables, and the glomerular filtration rate (GFR) was used as the predictive variable. The C4.5 decision tree algorithm outperformed the three comparison models for predicting early CKD based on accuracy, sensitivity, specificity, and area under the curve metrics. It is, therefore, a promising method for early CKD prediction. The experimental results showed that Urine protein and creatinine ratio (UPCR), Proteinuria (PRO), Red blood cells (RBC), Glucose Fasting (GLU), Triglycerides (TG), Total Cholesterol (T-CHO), age, and gender are important risk factors. CKD care is closely related to primary care level and is recognized as a healthcare priority in national strategy. The proposed risk prediction models can support the important influence of personality and health examination representations in predicting early CKD.


Assuntos
Insuficiência Renal Crônica , Adulto , Creatinina , Feminino , Taxa de Filtração Glomerular , Humanos , Testes de Função Renal , Masculino , Exame Físico , Proteinúria , Insuficiência Renal Crônica/diagnóstico , Insuficiência Renal Crônica/epidemiologia , Fatores de Risco
9.
Biomed Res Int ; 2020: 2654815, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32566676

RESUMO

Information about the expression status of hormone receptors such as estrogen receptor (ER), progesterone receptor (PR), and Her-2 is crucial in the management and prognosis of breast cancer. Therefore, the retrieval and analysis of hormone receptor expression characteristics in metastatic breast cancer may be valuable in breast cancer study. Herein, we report a text mining tool based on word/phrase matching that retrieves hormone receptor expression data of regional or distant metastatic breast cancer from pathology reports. It was tested on pathology reports at the China Medical University Hospital from 2013 to 2018. The tool showed specificities of 91.6% and 63.3% for the detection of regional lymph node metastasis and distant metastasis, respectively. Sensitivity in immunohistochemical study result extraction in these cases was 98.6% for distant metastasis and 78.3% for regional lymph node metastasis. Statistical analysis on these retrieved data showed significant difference s in PR and Her-2 expressions between regional and metastatic breast cancer, which is compatible with previous studies. In conclusion, our study shows that metastatic breast cancer hormone receptor expression characteristics can be retrieved by text mining. The algorithm designed in this study may be useful in future studies about text mining in pathology reports.


Assuntos
Neoplasias da Mama , Mineração de Dados/métodos , Receptor ErbB-2/metabolismo , Receptores de Estrogênio/metabolismo , Receptores de Progesterona/metabolismo , Algoritmos , Neoplasias da Mama/classificação , Neoplasias da Mama/diagnóstico , Neoplasias da Mama/metabolismo , Neoplasias da Mama/patologia , Biologia Computacional , Feminino , Humanos , Metástase Linfática
10.
Stud Health Technol Inform ; 270: 1191-1192, 2020 Jun 16.
Artigo em Inglês | MEDLINE | ID: mdl-32570574

RESUMO

Colorectal cancer (CRC) ranked third among most commonly diagnosed cancers worldwide. The onset of second primary cancer (SPC) is an important indicator in treating CRC. We tried to use the advanced machine learning method in order to find the factors of SPC. Patients with CRC from three medical centers were identified from cancer registries in Taiwan. The classifier of A Library for Support Vector Machines (LIBSVM) and Reduced Error Pruning Tree (REPTree) were applied to analyze the relationship of clinical features with category by constructing the optimized model of every classified issue. Machine learning can be used to rank the factor affecting the secondary primary malignancy. In the clinical practice, physician should be of aware the possibility of cancer recurrence and routine checkups for early second primary malignancy detection is recommended. The accuracy rate of the may need more big data. The machine learning method is feasible in detecting/predicting potential second primary cancer in the future.


Assuntos
Neoplasias Colorretais , Aprendizado de Máquina , Segunda Neoplasia Primária , Humanos , Recidiva Local de Neoplasia , Máquina de Vetores de Suporte , Taiwan
11.
Int J Med Sci ; 17(2): 182-190, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32038102

RESUMO

Background: Fatty acid-binding protein 1 (FABP1) (also known as liver-type fatty acid-binding protein or LFABP) is a protein that is mainly expressed in the liver, and is associated with hepatocyte injury in acute transplant rejection. Reduced levels of FABP1 in mice livers have been shown to be effective against nonalcoholic fatty liver disease (NAFLD). In this study, we investigated the association between plasma FABP1 levels and NAFLD in patients with type 2 diabetes mellitus (T2DM). Methods: We enrolled 267 T2DM patients. Clinical and biochemical parameters were measured. The severity of NAFLD was assessed by ultrasound. FABP1 levels were determined using by enzyme-linked immunosorbent assays. Results: FABP1 levels were higher in patients with overt NAFLD, defined as more than a moderate degree of fatty liver compared to those without NAFLD. Age- and sex-adjusted analysis of FABP1 showed positive associations with body mass index (BMI), waist circumference, homeostasis model assessment estimate of ß-cell function, creatinine, and fatty liver index, but showed negative associations with albumin and estimated glomerular filtration rate (eGFR). The odds ratio (OR) for the risk of overt NAFLD with increasing levels of sex-specific FABP1 was significantly increased (OR 2.63 [95% CI 1.30-5.73] vs. 4.94 [2.25-11.48]). The OR in the second and third tertiles of FABP1 remained significant after adjustments for BMI, triglycerides, high-density lipoprotein cholesterol, HbA1C, homeostasis model assessment estimate of insulin resistance, white blood cell count, hepatic enzymes, and eGFR. Conclusion: Our results indicate that FABP1 may play a role in the pathogenesis of NAFLD in patients with T2DM.


Assuntos
Diabetes Mellitus Tipo 2/sangue , Proteínas de Ligação a Ácido Graxo/sangue , Hepatopatia Gordurosa não Alcoólica/sangue , Idoso , Índice de Massa Corporal , Creatinina/sangue , Ensaio de Imunoadsorção Enzimática , Feminino , Humanos , Insulina/sangue , Masculino , Pessoa de Meia-Idade , Razão de Chances , Circunferência da Cintura/fisiologia
12.
Int Heart J ; 61(1): 29-38, 2020 Jan 31.
Artigo em Inglês | MEDLINE | ID: mdl-31956139

RESUMO

Low-circulating levels of adiponectin (ADPN) are associated with obesity, diabetes mellitus, and coronary artery disease. On the contrary, some studies have demonstrated a link between relatively high levels of plasma ADPN and heart failure, atrial fibrillation, and adverse outcome. However, little is known about the relationship between ADPN level and prolonged QT interval. The aim of this study was to investigate the association between plasma ADPN levels and prolonged QT interval in patients with stable angina.In this retrospective study, because the diverse disease severity and condition of the study population may have affected the results, we chose individuals with stable angina. Plasma ADPN concentrations were measured using enzyme-linked immunosorbent assays. A 12-lead ECG recording was obtained from each patient.We enrolled 479 stable-angina patients. Patients with an abnormal corrected QT (QTc) interval had higher median plasma ADPN levels than those with normal QTc intervals. Age- and sex-adjusted ADPN levels were positively associated with heart rate, QTc interval, left ventricular mass index, and creatinine but negatively associated with left ventricular ejection fraction, waist circumference, current smoking, total cholesterol, triglycerides, low-density lipoprotein cholesterol, albumin, and estimated glomerular filtration rate. A multiple logistic regression analysis revealed ADPN as an independent association factor for abnormal QTc interval. Increasing concentrations of sex-specific ADPN were independently and significantly associated with abnormal QTc interval, even after full adjustment of known biomarkers.Our results indicate that ADPN may play a role in the pathogenesis of abnormal QTc interval in patients with stable angina.


Assuntos
Adiponectina/sangue , Angina Estável/fisiopatologia , Biomarcadores/sangue , Síndrome do QT Longo/diagnóstico por imagem , Idoso , Idoso de 80 Anos ou mais , Angina Estável/metabolismo , Eletrocardiografia , Feminino , Humanos , Modelos Logísticos , Síndrome do QT Longo/metabolismo , Masculino , Pessoa de Meia-Idade , Estudos Retrospectivos , Índice de Gravidade de Doença
13.
Front Genet ; 10: 848, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31620166

RESUMO

Due to the high effectiveness of cancer screening and therapies, the diagnosis of second primary cancers (SPCs) has increased in women with breast cancer. The present study was conducted to develop a novel machine learning-based classification scheme for predicting the risk factors of SPCs in breast cancer survivors. The proposed scheme was based on the XGBoost classifier with the following four comparable strategies: transformation, resampling, clustering, and ensemble learning, to improve the training balanced accuracy. Results suggested that the best prediction accuracy for an empirical case is the XGBoost associated with the strategies of resampling and clustering. The experimental results showed that age, sequence of radiotherapy and surgery, surgical margins of the primary site, human epidermal growth factor, high-dose clinical target volume, and estrogen receptors are relatively more important risk factors associated with SPCs in patients with breast cancer. These risk factors should be monitored for the early detection of breast cancer. In conclusion, the proposed scheme can support the important influence of personality and clinical symptom representations in all phases of the primary treatment trajectory. Our results further suggested that adaptive machine learning techniques require the incorporation of significant variables for optimal predictions.

14.
Math Biosci ; 315: 108217, 2019 09.
Artigo em Inglês | MEDLINE | ID: mdl-31220511

RESUMO

Influenza type A, a serious infectious disease of the human respiratory tract, poses an enormous threat to human health worldwide. It leads to high mortality rates in poultry, pigs, and humans. The primary target identity regions for the human immune system are hemagglutinin (HA) and neuraminidase (NA), two surface proteins of the influenza A virus. Research and development of vaccines is highly complex because the influenza A virus evolves rapidly. This study focused on three genetic features of viral surface proteins: ribonucleic acid (RNA) sequence conservation, linear B-cell epitopes, and N-linked glycosylation. On the basis of these three properties, we analyzed 12,832 HA and 9487 NA protein sequences, which we retrieved from the influenza virus database. We classified the viral surface protein sequences into the 18 HA and 11 NA subtypes that have been identified thus far. Using available analytic tools, we searched for the representative strain of each virus subtype. Furthermore, using machine learning methods, we looked for conservation regions with sequences showing linear B-cell epitopes and N-linked glycosylation. Compared to the prediction of the Immune Epitope Database (IEDB) antibody neutralization response (i.e., screening of antibody sequence regions), in this study, the virus sequence coverage was large and accurate and contained N-linked glycosylation sites. The results of this study proved that we can use the machine learning-based prediction method to solve the problem of vaccine invalidation that occurred during the rapid evolution of the influenza A virus and also as a prevaccine assessment. In addition, the screening fragments can be used as a universal influenza vaccine design reference in the future.


Assuntos
Sequência Conservada , Epitopos de Linfócito B , Glicoproteínas de Hemaglutininação de Vírus da Influenza , Vírus da Influenza A , Influenza Humana , Aprendizado de Máquina , Neuraminidase , Proteínas Virais , Bases de Dados de Proteínas , Glicosilação , Humanos , Vírus da Influenza A/classificação
15.
Front Genet ; 10: 33, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-30809242

RESUMO

In this paper, a computational method based on machine learning technique for identifying Alzheimer's disease genes is proposed. Compared with most existing machine learning based methods, existing methods predict Alzheimer's disease genes by using structural magnetic resonance imaging (MRI) technique. Most methods have attained acceptable results, but the cost is expensive and time consuming. Thus, we proposed a computational method for identifying Alzheimer disease genes by use of the sequence information of proteins, and classify the feature vectors by random forest. In the proposed method, the gene protein information is extracted by adaptive k-skip-n-gram features. The proposed method can attain the accuracy to 85.5% on the selected UniProt dataset, which has been demonstrated by the experimental results.

16.
Molecules ; 23(12)2018 Dec 13.
Artigo em Inglês | MEDLINE | ID: mdl-30551590

RESUMO

Bulnesia sarmientoi (BS) has long been used as an analgesic, wound-healing and anti-inflammatory medicinal plant. The aqueous extract of its bark has been demonstrated to have anti-cancer activity. This study investigated the anti-proliferative and anti-metastatic effects of BS supercritical fluid extract (BSE) on the A549 and H661 lung cancer cell lines. The cytotoxicity on cancer cells was assessed by an MTT assay. After 72 h treatment of A549 and H661 cells, the IC50 values were 18.1 and 24.7 µg/mL, respectively. The cytotoxicity on MRC-5 normal cells was relatively lower (IC50 = 61.1 µg/mL). BSE arrested lung cancer cells at the S and G2/M growth phase. Necrosis of A549 and H661 cells was detected by flow cytometry with Annexin V-FITC/PI double staining. Moreover, the cytotoxic effect of BSE on cancer cells was significantly reverted by Nec-1 pretreatment, and BSE induced TNF-α and RIP-1 expression in the absence of caspase-8 activity. These evidences further support that BSE exhibited necroptotic effects on lung cancer cells. By wound healing and Boyden chamber assays, the inhibitory effects of BSE on the migration and invasion of lung cancer cells were elucidated. Furthermore, the chemical composition of BSE was examined by gas chromatography-mass analysis where ten constituents of BSE were identified. α-Guaiene, (-)-guaiol and ß-caryophyllene are responsible for most of the cytotoxic activity of BSE against these two cancer cell lines. Since BSE possesses significant cytotoxicity and anti-metastatic activity on A549 and H661 cells, it may serve as a potential target for the treatment of lung cancer.


Assuntos
Apoptose/efeitos dos fármacos , Cromatografia com Fluido Supercrítico , Neoplasias Pulmonares/patologia , Extratos Vegetais/farmacologia , Zygophyllaceae/química , Ciclo Celular/efeitos dos fármacos , Linhagem Celular Tumoral , Movimento Celular/efeitos dos fármacos , Proliferação de Células/efeitos dos fármacos , Cisplatino/farmacologia , Humanos , Necrose , Invasividade Neoplásica , Metástase Neoplásica , Extratos Vegetais/química , Cicatrização/efeitos dos fármacos
17.
Molecules ; 23(12)2018 Nov 29.
Artigo em Inglês | MEDLINE | ID: mdl-30501121

RESUMO

Alzheimer's disease (AD) is considered to one of 10 key diseases leading to death in humans. AD is considered the main cause of brain degeneration, and will lead to dementia. It is beneficial for affected patients to be diagnosed with the disease at an early stage so that efforts to manage the patient can begin as soon as possible. Most existing protocols diagnose AD by way of magnetic resonance imaging (MRI). However, because the size of the images produced is large, existing techniques that employ MRI technology are expensive and time-consuming to perform. With this in mind, in the current study, AD is predicted instead by the use of a support vector machine (SVM) method based on gene-coding protein sequence information. In our proposed method, the frequency of two consecutive amino acids is used to describe the sequence information. The accuracy of the proposed method for identifying AD is 85.7%, which is demonstrated by the obtained experimental results. The experimental results also show that the sequence information of gene-coding proteins can be used to predict AD.


Assuntos
Algoritmos , Doença de Alzheimer/genética , Área Sob a Curva , Humanos , Máquina de Vetores de Suporte
18.
Sci Rep ; 8(1): 15512, 2018 10 19.
Artigo em Inglês | MEDLINE | ID: mdl-30341374

RESUMO

Most modern tools used to predict sites of small ubiquitin-like modifier (SUMO) binding (referred to as SUMOylation) use algorithms, chemical features of the protein, and consensus motifs. However, these tools rarely consider the influence of post-translational modification (PTM) information for other sites within the same protein on the accuracy of prediction results. This study applied the Random Forest machine learning method, as well as motif screening models and a feature selection combination mechanism, to develop a SUMOylation prediction system, referred to as SUMOgo. With regard to prediction method, PTM sites were coded as new functional features in addition to structural features, such as sequence-based binary coding, encoded chemical features of proteins, and encoded secondary structure information that is important for PTM. Twenty cycles of prediction were conducted with a 1:1 combination of positive test data and random negative data. Matthew's correlation coefficient of SUMOgo reached 0.511, which is higher than that of current commonly used tools. This study further verified the important role of PTM in SUMOgo and includes a case study on CREB binding protein (CREBBP). The website for the final tool is http://predictor.nchu.edu.tw/SUMOgo .


Assuntos
Algoritmos , Biologia Computacional/métodos , Lisina/metabolismo , Processamento de Proteína Pós-Traducional , Sumoilação , Motivos de Aminoácidos , Sequência Consenso , Bases de Dados de Proteínas , Curva ROC , Proteínas Modificadoras Pequenas Relacionadas à Ubiquitina/química , Proteínas Modificadoras Pequenas Relacionadas à Ubiquitina/metabolismo
19.
Genes (Basel) ; 9(2)2018 Feb 14.
Artigo em Inglês | MEDLINE | ID: mdl-29443925

RESUMO

Protein quaternary structure complex is also known as a multimer, which plays an important role in a cell. The dimer structure of transcription factors is involved in gene regulation, but the trimer structure of virus-infection-associated glycoproteins is related to the human immunodeficiency virus. The classification of the protein quaternary structure complex for the post-genome era of proteomics research will be of great help. Classification systems among protein quaternary structures have not been widely developed. Therefore, we designed the architecture of a two-layer machine learning technique in this study, and developed the classification system PClass. The protein quaternary structure of the complex is divided into five categories, namely, monomer, dimer, trimer, tetramer, and other subunit classes. In the framework of the bootstrap method with a support vector machine, we propose a new model selection method. Each type of complex is classified based on sequences, entropy, and accessible surface area, thereby generating a plurality of feature modules. Subsequently, the optimal model of effectiveness is selected as each kind of complex feature module. In this stage, the optimal performance can reach as high as 70% of Matthews correlation coefficient (MCC). The second layer of construction combines the first-layer module to integrate mechanisms and the use of six machine learning methods to improve the prediction performance. This system can be improved over 10% in MCC. Finally, we analyzed the performance of our classification system using transcription factors in dimer structure and virus-infection-associated glycoprotein in trimer structure. PClass is available via a web interface at http://predictor.nchu.edu.tw/PClass/.

20.
Front Genet ; 9: 707, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-30671085

RESUMO

The MADS-box gene family is an important transcription factor family involved in floral organogenesis. The previously proposed ABCDE model suggests that different floral organ identities are controlled by various combinations of classes of MADS-box genes. The five-class ABCDE model cannot cover all the species of angiosperms, especially the orchid. Thus, we developed a two-stage approach for MADS-box gene classification to advance the study of floral organogenesis of angiosperms. First, eight classes of reference datasets (A, AGL6, B12, B34, BPI, C, D, and E) were curated and clustered by phylogenetic analysis and unsupervised learning, and they were confirmed by the literature. Second, feature selection and multiple prediction models were curated according to sequence similarity and the characteristics of the MADS-box gene domain using support vector machines. Compared with the BindN and COILS features, the local BLAST model yielded the best accuracy. For performance evaluation, the accuracy of Phalaenopsis aphrodite MADS-box gene classification was 93.3%, which is higher than 86.7% of our previous classification prediction tool, iMADS. Phylogenetic tree construction - the most common method for gene classification yields classification errors and is time-consuming for analysis of massive, multi-species, or incomplete sequences. In this regard, our new system can also confirm the classification errors of all the random selection that were incorrectly classified by phylogenetic tree analysis. Our model constitutes a reliable and efficient MADS-box gene classification system for angiosperms.

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