scholarly journals Leveraging genetic interaction for adverse drug-drug interaction prediction

2019 ◽  
Author(s):  
Sheng Qian ◽  
Siqi Liang ◽  
Haiyuan Yu
Keyword(s):  
Genetic Interaction ◽  
Genetic Interactions ◽  
Gradient Boosting ◽  
Interaction Prediction ◽  
Training Scheme ◽  
Feature Spaces ◽  
Multiple Drugs ◽  
Interaction Approach ◽  
First Time

ABSTRACTIn light of increased co-prescription of multiple drugs, the ability to discern and predict drug-drug interactions (DDI) has become crucial to guarantee the safety of patients undergoing treatment with multiple drugs. However, information on DDI profiles is incomplete and the experimental determination of DDIs is labor-intensive and time-consuming. Although previous studies have explored various feature spaces for in silico screening of interacting drug pairs, no method currently provides reliable predictions outside of their training sets. Here we demonstrate for the first time targets of adversely interacting drug pairs are significantly more likely to have synergistic genetic interactions than non-interacting drug pairs. Leveraging genetic interaction features and a novel training scheme, we construct a gradient boosting-based classifier that achieves robust DDI prediction even for drugs whose interaction profiles are completely unseen during training. We demonstrate that in addition to classification power—including the prediction of 432 novel DDIs—our genetic interaction approach offers interpretability by providing plausible mechanistic insights into the mode of action of DDIs.

scholarly journals Decoding directional genetic dependencies through orthogonal CRISPR/Cas screens

2017 ◽  
Author(s):  
Michael Boettcher ◽  
Ruilin Tian ◽  
James Blau ◽  
Evan Markegard ◽  
David Wu ◽  
...  
Keyword(s):  
Genetic Information ◽  
Genetic Interaction ◽  
Human Cancer ◽  
Genetic Interactions ◽  
Combinatorial Screening ◽  
Human Cancer Cells ◽  
Functional Interactions ◽  
Powerful Approach ◽  
Screening Platform ◽  
Interaction Approach

SummaryGenetic interaction studies are a powerful approach to identify functional interactions between genes. This approach can reveal networks of regulatory hubs and connect uncharacterised genes to well-studied pathways. However, this approach has previously been limited to simple gene inactivation studies. Here, we present an orthogonal CRISPR/Cas-mediated genetic interaction approach that allows the systematic activation of one gene while simultaneously knocking out a second gene in the same cell. We have developed this concept into a quantitative and scalable combinatorial screening platform that allows the parallel interrogation of hundreds of thousands of genetic interactions. We demonstrate that the established platform works robustly to uncover genetic interactions in human cancer cells and to interpret the direction of the flow of genetic information.

Disability as a social phenomenon

2020 ◽  
pp. 22-38
Author(s):  
Natalia Guseva ◽  
Vitaliy Berdutin
Keyword(s):  
Social Protection ◽  
Russian Society ◽  
Stage Model ◽  
High Quality ◽  
Rehabilitation Programs ◽  
Current State ◽  
The Social ◽  
Consistent Solution ◽  
First Time

At present, the problem of establishing disability is a point at issue in Russia. Despite the fact that medical criteria for disability are being developed very actively, high-quality methods for assessing social hallmarks are still lacking. Since disability is a phenomenon inherent in any society, each state forms a social and economic policy for people with disabilities in accordance with its level of development, priorities and opportunities. We have proposed a three-stage model, which includes a system for the consistent solution of the main tasks aimed at studying the causes and consequences of the problems encountered today in the social protection of citizens with health problems. The article shows why the existing approaches to the determination of disability and rehabilitation programs do not correspond to the current state of Russian society and why a decrease in the rate of persons recognized as disabled for the first time does not indicate an improvement in the health of the population. The authors proposed a number of measures with a view to correcting the situation according to the results of the study.

Phytochemical Constituents of Annona reticulata and their Cytotoxic Activity

2020 ◽  
Vol 17 (3) ◽  
pp. 206-210
Author(s):  
Ty Viet Pham ◽  
Thang Quoc Le ◽  
Anh Tuan Le ◽  
Hung Quoc Vo ◽  
Duc Viet Ho
Keyword(s):  
Cytotoxic Activity ◽  
Cell Lines ◽  
Structural Determination ◽  
Phytochemical Investigation ◽  
Ic50 Values ◽  
Phytochemical Constituents ◽  
First Time ◽  
Annona Reticulata

A phytochemical investigation of the leaves of Annona reticulata led to the isolation and structural determination of β-sitosterol (1), ent-pimara-8(14),15-dien-19-oic acid (2), ent-pimara- 8(14),15-dien-19-ol (3), quercetin (4), quercetin 3-O-α-L-arabinopyranoside (5), and a mixture of quercetin 3-O-β-D-galactopyranoside (6a) and quercetin 3-O-β-D-glucopyranoside (6b). Of these, compounds 2 and 3 were isolated from the genus Annona for the first time. Compound 3 showed strong cytotoxicity against SK-LU-1 and SW626 cell lines with IC50 values of 17.64 ± 1.07 and 19.79 ± 1.41 μg mL-1, respectively.

Development of an HPLC-UV Method for Quantification of Stattic

2019 ◽  
Vol 15 (6) ◽  
pp. 568-573
Author(s):  
Soheil Sedaghat ◽  
Ommoleila Molavi ◽  
Akram Faridi ◽  
Ali Shayanfar ◽  
Mohammad Reza Rashidi
Keyword(s):  
High Performance ◽  
Accurate Method ◽  
Plasma Samples ◽  
Promising Target ◽  
Relative Standard ◽  
Dimerization Inhibitor ◽  
Oncogenic Protein ◽  
First Time ◽  
Transcription 3

Background: Signal transducer and activator of transcription 3 (STAT3), an oncogenic protein found constitutively active in many types of human malignancies, is considered to be a promising target for cancer therapy. Objective: In this study for the first time, a simple and accurate method has been developed for the determination of a STAT3 dimerization inhibitor called stattic in aqueous and plasma samples. Methods: A reverse-phase high-performance liquid chromatography (RP-HPLC) composed of C18 column as stationary phase, and the mixture of acetonitrile (60%) and water (40%) as mobile phase with a UV detection at 215 nm were applied for quantification of stattic. The developed method was validated by Food and Drug Administration (FDA) guideline. Results: The method provided a linear range between 1-40 and 2.5-40 µg mL-1 for aqueous and plasma samples, respectively, with a correlation coefficient of 0.999. The accuracy (as recovery) of the developed method was found to be between 95-105% for aqueous medium and 85-115% for plasma samples. The precision (as relative standard deviation) for aqueous and plasma samples was less than 6% and 15%, respectively. The sensitivity of the developed method based on FDA guideline was 1 µg mL-1 for aqueous and 2.5 µg mL-1 for plasma samples. Conclusion: These results show that the established method is a fast and accurate quantification for stattic in aqueous and plasma samples.

Genetic Interactions Effects of Cardiovascular Disorder Using Computational Models: A Review

2020 ◽  
Vol 9 (3) ◽  
pp. 177-191
Author(s):  
Sridharan Priya ◽  
Radha K. Manavalan
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Cardiovascular Diseases ◽  
Computational Models ◽  
Genetic Interaction ◽  
Association Studies ◽  
Genetic Interactions ◽  
Computational Techniques ◽  
Genome Wide Association Studies ◽  
Artery Disease

Background: The diseases in the heart and blood vessels such as heart attack, Coronary Artery Disease, Myocardial Infarction (MI), High Blood Pressure, and Obesity, are generally referred to as Cardiovascular Diseases (CVD). The risk factors of CVD include gender, age, cholesterol/ LDL, family history, hypertension, smoking, and genetic and environmental factors. Genome- Wide Association Studies (GWAS) focus on identifying the genetic interactions and genetic architectures of CVD. Objective: Genetic interactions or Epistasis infer the interactions between two or more genes where one gene masks the traits of another gene and increases the susceptibility of CVD. To identify the Epistasis relationship through biological or laboratory methods needs an enormous workforce and more cost. Hence, this paper presents the review of various statistical and Machine learning approaches so far proposed to detect genetic interaction effects for the identification of various Cardiovascular diseases such as Coronary Artery Disease (CAD), MI, Hypertension, HDL and Lipid phenotypes data, and Body Mass Index dataset. Conclusion: This study reveals that various computational models identified the candidate genes such as AGT, PAI-1, ACE, PTPN22, MTHR, FAM107B, ZNF107, PON1, PON2, GTF2E1, ADGRB3, and FTO, which play a major role in genetic interactions for the causes of CVDs. The benefits, limitations, and issues of the various computational techniques for the evolution of epistasis responsible for cardiovascular diseases are exhibited.

Carbon dots derived from Fusobacterium nucleatum for intracellular determination of Fe3+ and bioimaging both in vitro and in vivo

2021 ◽  
Author(s):  
Lijuan Liu ◽  
Shengting Zhang ◽  
Xiaodan Zheng ◽  
Hongmei Li ◽  
Qi Chen ◽  
...  
Keyword(s):  
Carbon Dots ◽  
Fusobacterium Nucleatum ◽  
Living Cells ◽  
First Time ◽  
Fluorescent Carbon Dots ◽  
Fluorescent Carbon

Fusobacterium nucleatum has been employed for the first time to synthesize fluorescent carbon dots which could be applied for the determination of Fe3+ ions in living cells and bioimaging in vitro and in vivo with excellent biocompatibility.

scholarly journals Experimental investigation to characterize simple versus multi scaling analysis of hydraulic conductivity at a mesoscale

2021 ◽  
Author(s):  
Guglielmo Federico Antonio Brunetti ◽  
Samuele De Bartolo ◽  
Carmine Fallico ◽  
Ferdinando Frega ◽  
Maria Fernanda Rivera Velásquez ◽  
...  
Keyword(s):  
Hydraulic Conductivity ◽  
Spatial Variability ◽  
Hydraulic Properties ◽  
Scaling Laws ◽  
Scaling Analysis ◽  
Field Scale ◽  
Porous Formation ◽  
Proper Design ◽  
First Time

AbstractThe spatial variability of the aquifers' hydraulic properties can be satisfactorily described by means of scaling laws. The latter enable one to relate the small (typically laboratory) scale to the larger (typically formation/regional) ones, therefore leading de facto to an upscaling procedure. In the present study, we are concerned with the spatial variability of the hydraulic conductivity K into a strongly heterogeneous porous formation. A strategy, allowing one to identify correctly the single/multiple scaling of K, is applied for the first time to a large caisson, where the medium was packed. In particular, we show how to identify the various scaling ranges with special emphasis on the determination of the related cut-off limits. Finally, we illustrate how the heterogeneity enhances with the increasing scale of observation, by identifying the proper law accounting for the transition from the laboratory to the field scale. Results of the present study are of paramount utility for the proper design of pumping tests in formations where the degree of spatial variability of the hydraulic conductivity does not allow regarding them as “weakly heterogeneous”, as well as for the study of dispersion mechanisms.

scholarly journals Potentiometric Response of Solid-State Sensors Based on Ferric Phosphate for Iron(III) Determination

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1612
Author(s):  
Andrea Paut ◽  
Ante Prkić ◽  
Ivana Mitar ◽  
Perica Bošković ◽  
Dražan Jozić ◽  
...  
Keyword(s):  
Silver Sulfide ◽  
Potential Change ◽  
Linear Potential ◽  
Response Characteristics ◽  
Potentiometric Response ◽  
Best Response ◽  
Body Design ◽  
Long Lifetime ◽  
First Time

A novel ion-selective electrode with membranes based on iron(III) phosphate and silver sulfide integrated into a completely new electrode body design has been developed for the determination of iron(III) cations. The best response characteristics with linear potential change were found in the iron(III) concentration range from 3.97× 10−5 to 10−2 mol L−1. The detection limit was found to be 2.41× 10−5 mol L−1 with a slope of –20.53 ± 0.63 and regression coefficient of 0.9925, while the quantification limit was 3.97× 10−5 M. The potential change per concentration decade ranged from –13.59 ± 0.54 to –20.53 ± 1.56 for Electrode Body 1 (EB1) and from –17.28 ± 1.04 to –24 ± 1.87 for Electrode Body 2 (EB2), which is presented for the first time in this work. The prepared electrode has a long lifetime and the ability to detect changes in the concentration of iron cations within 20 s. Membrane M1 showed high recoveries in the determination of iron cations in iron(III) standard solutions (98.2–101.2%) as well as in two different pharmaceuticals (98.6–106.5%). This proves that this type of sensor is applicable in the determination of ferric cations in unknown samples, and the fact that all sensor parts are completely manufactured in our laboratory proves the simplicity of the method.

scholarly journals Stress Mediating Genes in Aging, Health, and Longevity Traits: Effects of Multiple Interactions

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 286-286
Author(s):  
Anatoliy Yashin ◽  
Dequing Wu ◽  
Konstantin Arbeev ◽  
Arseniy Yashkin ◽  
Galina Gorbunova ◽  
...  
Keyword(s):  
Strong Interaction ◽  
Genetic Interaction ◽  
Interaction Effects ◽  
Genetic Interactions ◽  
Risk Scores ◽  
Data Sets ◽  
Interaction Patterns ◽  
Polygenic Risk ◽  
Drug Candidates ◽  
Aging Health

Abstract Persistent stress of external or internal origin accelerates aging, increases risk of aging related health disorders, and shortens lifespan. Stressors activate stress response genes, and their products collectively influence traits. The variability of stressors and responses to them contribute to trait heterogeneity, which may cause the failure of clinical trials for drug candidates. The objectives of this paper are: to address the heterogeneity issue; to evaluate collective interaction effects of genetic factors on Alzheimer’s disease (AD) and longevity using HRS data; to identify differences and similarities in patterns of genetic interactions within two genders; and to compare AD related genetic interaction patterns in HRS and LOADFS data. To reach these objectives we: selected candidate genes from stress related pathways affecting AD/longevity; implemented logistic regression model with interaction term to evaluate effects of SNP-pairs on these traits for males and females; constructed the novel interaction polygenic risk scores for SNPs, which showed strong interaction potential, and evaluated effects of these scores on AD/longevity; and compared patterns of genetic interactions within the two genders and within two datasets. We found there were many genes involved in highly significant interactions that were the same and that were different within the two genders. The effects of interaction polygenic risk scores on AD were strong and highly statistically significant. These conclusions were confirmed in analyses of interaction effects on longevity trait using HRS data. Comparison of HRS to LOADFS data showed that many genes had strong interaction effects on AD in both data sets.

scholarly journals Determination of Flavonoids Compounds of Three Species and Different Harvesting Periods in Crataegi folium Based on LC-MS/MS

Molecules ◽  
2021 ◽  
Vol 26 (6) ◽  
pp. 1602
Author(s):  
Ya-Ping Guo ◽  
Hong Yang ◽  
Ya-Li Wang ◽  
Xiao-Xiang Chen ◽  
Ke Zhang ◽  
...  
Keyword(s):  
Quantitative Analysis ◽  
Qualitative Analysis ◽  
Quantitative Method ◽  
Total Content ◽  
Qualitative And Quantitative Analysis ◽  
Pharmacological Activities ◽  
Time Saving ◽  
Qualitative And Quantitative ◽  
First Time

Crataegi folium have been used as medicinal and food materials worldwide due to its pharmacological activities. Although the leaves of Crataegus songorica (CS), Crataegus altaica (CA) and Crataegus kansuensis (CK) have rich resources in Xinjiang, China, they can not provide insights into edible and medicinal aspects. Few reports are available on the qualitative and quantitative analysis of flavonoids compounds of their leaves. Therefore, it is necessary to develop efficient methods to determine qualitative and quantitative flavonoids compounds in leaves of CS, CA and CK. In the study, 28 unique compounds were identified in CS versus CK by qualitative analysis. The validated quantitative method was employed to determine the content of eight flavonoids of the leaves of CS, CA and CK within 6 min. The total content of eight flavonoids was 7.8–15.1 mg/g, 0.1–9.1 mg/g and 4.8–10.7 mg/g in the leaves of CS, CA and CK respectively. Besides, the best harvesting periods of the three species were from 17th to 26th September for CS, from 30th September to 15th October for CA and CK. The validated and time-saving method was successfully implemented for the analysis of the content of eight flavonoids compounds in CS, CA and CK for the first time.

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