Systematic review on rocuronium continuous infusion for deep neuromuscular blockade

(E-pub Abstract Ahead of Print)

Author(s): Mafalda Couto*, J. Guilherme Couto, Catarina S. Nunes, Sérgio Vide, Pedro Amorim, Joaquim G. Mendes.

Journal Name: Current Clinical Pharmacology

Abstract:

Background: Rocuronium is a muscle relaxant with increased use interest due to the binding relation with the reversal agent sugammadex. The purpose of this review entails the investigation of its use for the maintenance of deep neuromuscular block (NMB) via continuous infusion.

Methods: Based on PRISMA systematic search guidelines, databases included PubMed, ISI Web of Science, Cochrane Library and google scholar. This comprehensive search addresses surgical patients under deep muscle relaxation via continuous rocuronium infusion. Main indicators were the rocuronium administration, NMB monitoring approaches and effects in order to maintain the deep level of relaxation, as well as reversal time after standard dose of sugammadex.

Results: Despite the variance in approaches found in the literature, findings show the overall maintenance of deep NMB requires approximately 0.758 mg.kg-1h-1 of rocuronium (according to the PTC target of 0-10, 0-5 and 1-2, mean estimates are 0.445, 0.65 and 0.833 mg.kg-1h-1 respectively), suggesting that a lower range and smaller maximum of PTC response require higher amount of rocuronium for its maintenance. Standard dose of sugammadex (4 mg/kg), administered at the end of the surgery take longer [2.85 (1.17) min] than when administered after moderate NMB recovery [1.68 (0.47) min].

Conclusion: Continuous infusion for deep NMB presents inherent advantages in terms of maintenance and stability of the muscle relaxation. For that purpose, monitoring and rocuronium administration approaches are fundamental and intrinsically connected. Additional efforts should be placed in further studies to better understand the variability and methodological parameters for an improved maintenance of deep NMB.

Keywords: Anesthesia, Neuromuscular blockade, Post-tetanic count, Continuous infusion, Deep NMB, Rocuronium

Rights & PermissionsPrintExport Cite as

Article Details

(E-pub Abstract Ahead of Print)
DOI: 10.2174/1574884714666191120144331
Price: $95



An Updated Overview of The Complex Clinical Spectrum of Tourette Syndrome

(E-pub Abstract Ahead of Print)

Author(s): Natan Gadoth.

Journal Name: Current Drug Therapy

Abstract:

Background: Tourette syndrome is reflectively and quite erroneously associated by many as a syndrome with tics and swearing. However, the syndrome is a complex neuropsychiatric disorder consisting of features known as Tourette syndrome combined with several serious comorbidities justifying the quite recent designation of Tourette Disorder rather than “syndrome”. Unfortunately, the published literature is mostly dedicated to tics, while mentioning only briefly the comorbidities.

Objective: To provide a short description of the “many faces” of Tourette syndrome

Methods: Summary of relevant published literature

Results: The literature review provided indicates that this rare neuropsychiatric clinical picture is a multidisciplinary “disorder” rather than a” syndrome”.

Conclusion: Patients with Tourette Disorder should be evaluated and treated by a multidisciplinary team.

Keywords: Tourette Syndrome, Tics, Coprolalia, Self-Mutilation, ADHD, OCD, Sleep

Rights & PermissionsPrintExport Cite as

Article Details

(E-pub Abstract Ahead of Print)
DOI: 10.2174/1574885514666191120143747
Price: $95


Model with the GBDT for colorectal adenoma risk diagnosis

(E-pub Abstract Ahead of Print)

Author(s): Junbo Gao*, Lifeng Zhang, Gaiqing Yu, Guoqiang Qu, Yanfeng Li, Xuebing Yang.

Journal Name: Current Bioinformatics

Abstract:

Background and objective: Colorectal cancer (CRC) is a common malignant tumor of the digestive system; it is associated with high morbidity and mortality. However, an early prediction of colorectal adenoma (CRA) that is a precancerous disease of most CRC patients provides an opportunity to make an appropriate strategy for prevention, early diagnosis and treatment. We aimed to build a machine learning model to predict CRA that could assist physicians in classifying high-risk patients and make informed choices, prevent CRC.

Methods: We instructed patients who had undergone a colonoscopy to fill out a questionnaire at the Sixth People Hospital of Shanghai in China from July 2018 to November 2018. A classification model with the gradient boosting decision tree (GBDT) was developed to predict CRA. This model was compared with three other models, namely, random forest (RF), support vector machine (SVM), and logistic regression (LR). The area under the receiver operating characteristic curve (AUC) was used to evaluate performance of the models.

Results: Among the 245 included patients, 65 patients had CRA. The area under the receiver operating characteristic (AUCs) of GBDT, RF, SVM ,and LR with 10 fold-cross validation were 0.8131, 0.74, 0.769 and 0.763. We also built an online prediction service, CRA Inference System, to substantialize the proposed solution for patients with CRA.

Conclusion: We developed and compared four classification models for CRA prediction, and the GBDT model showed the highest performance. Implementing a GBDT model for screening can reduce the cost of time and money and help physicians identify high-risk groups for primary prevention.

Keywords: Colorectal adenoma, Colorectal cancer, Gradient boosting decision tree, Prediction, Clinical data, Early prevention

Rights & PermissionsPrintExport Cite as

Article Details

(E-pub Abstract Ahead of Print)
DOI: 10.2174/1574893614666191120142005
Price: $95


An Information Gain-based Method for Evaluating the Classification Power of Features Towards Identifying Enhancers

(E-pub Abstract Ahead of Print)

Author(s): Tianjiao Zhang, Rongjie Wang, Qinghua Jiang*, Yadong Wang.

Journal Name: Current Bioinformatics

Abstract:

Background: Enhancers are cis-regulatory elements that enhance gene expression on DNA sequences and are usually located far from transcription start sites. Like other regulatory elements, the regions around enhancers contain a variety of features.

Objective: The above features are widely used to predict the position of enhancers in existing algorithms. And the accuracies of these methods are significant affected by the selected features. Thus, it is urgent to filter the important features out, which can greatly help for enhancer recognition.

Method: To evaluate the classification power of these features for enhancer recognition, all of the features were divided into three categories: sequence features, transcriptional features, and epigenetic features. Here, we presented two evaluation methods involving information gain and single feature prediction accuracy. The information gain can effectively reflect the entropy change of enhancer recognition using different features. Single feature prediction accuracy can directly reflect the contribution of features for enhancers recognition.

Results: The average information gain of the sequence feature, transcriptional feature and epigenetic feature is 0.068, 0.213, and 0.299, respectively. The average AUC value corresponding to the sequence feature, transcriptional feature, and epigenetic feature is 0.534, 0.605, and 0.647, respectively.

Conclusion: In comparison with sequence features, epigenetic features are more effective for recognizing enhancers.

Keywords: Enhancer, Gene Expression Regulation, Sequence Features, Transcriptional Features, Epigenetic Features, Information Gain.

Rights & PermissionsPrintExport Cite as

Article Details

(E-pub Abstract Ahead of Print)
DOI: 10.2174/1574893614666191120141032
Price: $95


Stinging Insect Allergens

(E-pub Abstract Ahead of Print)

Author(s): Cui Le, Xu Ying-Yang, Wang Xiu-Jie, Guan Kai*.

Journal Name: Current Protein & Peptide Science

Abstract:

Hymenoptera venom allergy is one of the common causes of anaphylaxis. However, when physicians make the diagnosis of Hymenoptera venom allergy, the histories of being stung are not always consistent with the results of venom specific IgE. With the development of component-resolved diagnosis, it is possible to accurately localize an allergic reaction to certain sensitized proteins. This paper reviewed the studies that have addressed the identified allergenicity and cross-reactivity of Hymenoptera venom allergens accepted by the WHO/IUIS Nomenclature Sub-committee, the component-resolved diagnosis of Hymenoptera venom allergy and its predictive values for the efficacy and safety of venom immunotherapy. Also, we paid special attention to the progress of Hymenoptera venom allergy in Asian countries.

Keywords: Allergens, Cross Reactions, Hymenoptera, Hypersensitivity, Immunoglobulin E, Immunotherapy, Venoms

Rights & PermissionsPrintExport Cite as

Article Details

(E-pub Abstract Ahead of Print)
DOI: 10.2174/1389203720666191120130209
Price: $95



Natural Fused Heterocyclic Flavonoids: Potent Candidates As Anti-Inflammatory And Anti-Allergic Agents In The Treatment Of Asthma

(E-pub Abstract Ahead of Print)

Author(s): Rajwinder Kaur*, Kirandeep Kaur, Rashmi Arora, Balraj Saini, Sandeep Arora.

Journal Name: Current Bioactive Compounds

Abstract:

In the last two decades, the flavanoids containing fused heterocyclic nucleus in their chemical structure have emerged to display a variety of pharmacological effects including anti-allergic and anti-inflammatory the most recent to the list. These polyphenolic compounds exert their pharmacological effect by various mechanisms including inhibition of human neutrophil elastase, cytokines (Interleukins- IL-3 and IL-4) and mast cells. Quercetin, Pycnogenol, Rutin and Kampferol are the few bio-flavonols out of hundreds of other compounds still under clinical trials that have been studied most. These flavonoids have been also reported to the other pharmacological effects like anti-cancer, anti-oxidants, anti-hypertensive, anti-viral, anti-ulcerogenic, anti-platelet, anti-hypotensive and anti-hepatotoxic. With all these versatile properties heterocyclic containing flavonoids may be a powerful candidate for the discovery of their utilization in other ailments like asthma.

Keywords: Flavonoids, Asthma, Lawsonia, Thuja orientaliFlavonoids, Thuja orientalis, candidate

Rights & PermissionsPrintExport Cite as

Article Details

(E-pub Abstract Ahead of Print)
DOI: 10.2174/1573407215666191120125608
Price: $95


Acknowledgements to Reviewers

Author(s): .

Journal Name: Current Green Chemistry

Volume 6 , Issue 3 , 2019

Rights & PermissionsPrintExport Cite as

Article Details

VOLUME: 6
ISSUE: 3
Year: 2019
Page: [255 - 255]
Pages: 1
DOI: 10.2174/221334610603191120125514


Estimation of calorific values of some of Turkish Lignites by artificial neural network and multiple regression

(E-pub Abstract Ahead of Print)

Author(s): Engin Özdemir*, Didem Eren Sarici.

Journal Name: Current Physical Chemistry

Abstract:

Background: The calorific value is the most important and effective factors of lignites in terms of energy resources. Humidity, ash content, volatile matter and sulfur content are the main factors affecting lignite's calorific values.

Objective: Determination of calorific value is a process that takes time and cost for businesses. Therefore, estimating the calorific value from the developed models by using other parameters will benefit enterprises in term of time, cost and labor

Method: In this study calorific values were estimated by using artificial neural network and multiple regression models by using lignite data of 30 different regions. As input parameters, humidity, ash content and volatile matter values are used. In addition, the mean absolute percentage error and the significance coefficient values were determined.

Results: Mean absolute percentage error values were found to be below 10%. There is a strong relationship between calorific values and other properties (R2> 90).

Conclusion: As a result, artificial neural network and multiple regression models proposed in this study was shown to successfully estimate the calorific value of lignites without performing laboratory analyses.

Keywords: Energy, multiple artificial neural network, calorific value regression, Turkish lignite

Rights & PermissionsPrintExport Cite as

Article Details

(E-pub Abstract Ahead of Print)
DOI: 10.2174/1877946809666191120125450
Price: $95


EDITORIAL: Organic Transformations by Following Green Credentials- Part 1 (A)

Author(s): Bubun Banerjee.

Journal Name: Current Green Chemistry

Volume 6 , Issue 3 , 2019

Rights & PermissionsPrintExport Cite as

Article Details

VOLUME: 6
ISSUE: 3
Year: 2019
Page: [154 - 154]
Pages: 1
DOI: 10.2174/221334610603191120125019