AN ANALYTICAL SOLUTION FOR THE MODEL OF DRUG DISTRIBUTION AND ABSORPTION IN SMALL INTESTINE

According to the physiological and anatomical characteristics of small intestine,neglecting the effect of its motility on the distribution and absorption of drug and nutrient,Y.Miyamoto et al.proposed a model of two-dimensional laminar flow in a circular porous tube with permeable wall and calculated the concentration profile of drugby numerical analysis.In this paper,we give a steady-state analytical solution of the above model including deactivationterm.The obtained results are in agreement with the results of their numerical analysis. Moreover the analytical solution presented in this paper reveals the relation among the physiological parameters of the model and describes the basic absorption rule of drug and nutrient through the intestinal wall and hence pro- vides a theoretical basis for determining the permeability and reflection coefficient through in situ experiments.

The Impacts of Supplemental Irrigation Based on Soil Moisture Measurement and Nitrogen Use on Winter Wheat Yield and Nitrogen Absorption and Distribution

Based on split plot design method of field test,the impacts of supplemental irrigation based on soil moisture measurement and nitrogen use on winter wheat yield and nitrogen absorption and distribution were studied.Supplemental irrigation had three levels: 60%(W_1),70%(W_2) and 80%(W3) of the targeted relative water content at 0-40 cm of soil layer during jointing period of winter wheat.Nitrogen fertilization had three levels: not using nitrogen(N_0),using pure nitrogen of 195 kg/hm^2(N_(195)) and 255 kg/hm^2(N_(255)).Results showed that:(i)different supplemental irrigation and nitrogen fertilization significantly affected plant height and leaf area of winter wheat during key growth period.Under the same supplemental irrigation treatment,both plant height and leaf area of winter wheat showed as N_(255)> N_(195)> N_0(P <0.05).Plant height in N_(195) and N_(255)treatments was significantly higher than that in N_0 treatment,but there was not significant difference between N_(195) and N_(255)(P >0.05).Under the same nitrogen fertilization,plant height in W_2(569.4 m^3/hm^2) and W3(873.45 m^3/hm^2) treatments was significant higher than that in W_1(265.2 m^3/hm^2),but there was not significant difference between W_2 and W3(P >0.05).It illustrated that excessive nitrogen fertilization and supplemental irrigation did not significantly affect plant height and leaf area of winter wheat.(ii) Under the same nitrogen fertilization level,yield increase effect of winter wheat by supplemental irrigation showed a declining trend with nitrogen application amount increased.It illustrated that nitrogen fertilization and supplemental irrigation had certain critical values on the yield of winter wheat.When surpassing the critical value,the yield declined.When nitrogen fertilization amount was 195 kg/hm^2,and supplemental irrigation amount was 70% of field moisture capacity(569.4 m^3/hm^2),the highest yield 8500 kg/hm^2 could be obtained.(iii) During mature period of winter wheat,nitrogen accumulation amount of plant treated by nitrogen was significantly higher than that not treated by nitrogen(P <0.05).But under the treatments of W_2 and W3,nitrogen accumulation amount in N_(255) significantly declined when compared with N_(195)(P <0.05).Especially under W3(873.45 m^3/hm^2) level,nitrogen accumulation amount in N_(255) was even lower than N_0.Under the treatments of N_0 and N_(195),nitrogen accumulation amount of plant significantly increased with supplemental irrigation increased(P < 0.05).But under N_(255) treatment,there was not significant difference(P > 0.05).It illustrated that moderate supplemental irrigation and nitrogen fertilization could improve nitrogen absorption ability of winter wheat,but excessive supplemental irrigation and nitrogen fertilization were not favorable for plant's nitrogen absorption.(iv) Although the increase of supplemental irrigation during jointing period improved nitrogen absorption ability of winter wheat and promoted winter wheat absorbing more nitrogen,it inhibited nitrogen transferring and distributing to seed.Comprehensively considering growth condition of winter wheat and nitrogen risk condition,it is suggested that nitrogen application amount was 195 kg/hm^2,and supplemental irrigation reached 70% of field moisture capacity(569.4 m^3/hm^2),which could be as the suitable water and fertilizer use amounts in the region.

Combined fluorescence and electrochemical investigation on the binding interaction between organic acid and human serum albumin

Human serum albumin （HSA） is a plasma protein responsible for the binding and transport of fatty acids and a variety of exogenous chemicals such as drugs and environmental pollutants. Such binding plays a crucial role in determining the ADME （absorption, distribution, metabolism, and excretion） and bioavailability of the pollutants. The binding interaction between HSA and acetic acid （C2）, octanoic acid （C8） and dodecanoic acid （C12） has been investigated by the combination of site-specific fluorescent probe, tryptophan intrinsic fluorescence and tyrosine electrochemistry. For the study of the fatty acid interaction with the two drug-binding sites on HSA, two fluorescent probes, dansylamide and dansyl-L-proline were employed in the displacement measurements. Intrinsic fluorescence of tryptophan in HSA was monitored upon addition of the fatty acids into HSA. Electrocatalyzed response of the tyrosine residues in HSA by a redox mediator was used to investigate the binding interaction. Qualitatively, observations from these three approaches were very similar. HSA did not show any change in the fluorescence and electrochemical experiments after mixing with C2, suggesting there is no significant interaction with the short-chain fatty acid. For C8, the measured signal dropped in a single-exponential mode, indicating an independent and non-cooperative binding. The calculated association constant and binding ratio were 3.1 × 10^6 L/mol and 1 with drug binding Site Ⅰ, 1.1 × 107 L/mol and 1 with Site Ⅱ, and 7.0× 0^4 L/mol and 4 with the tryptophan site, respectively. The measurements with C12 displayed multiple phases of fluorescence change, suggesting cooperativity and allosteric effect of the C12 binding. These results correlate well with those obtained by the established methods, and validate the new approach as a viable tool to study the interactions of environmental pollutants with biological molecules.

Permeation properties of CO2 and CH4 in asymmetric polyethersulfone/ polyesterurethane and polyethersulfone/polyetherurethane blend membranes

The transport performances of carbon dioxide and methane were studied in polyethersulfone, polyethersulfone/polyeterurethane(PES–ETPU) and polyethersulfone/polyestherurethane(PES–ESPU) blend membranes separately with different compositions. The variations in the structural characteristics of PES membrane after incorporation of ESPU and ETPU were investigated by different techniques. Additionally, the effect of pressure and composition on the permeance of CO_2, CH_4 and ideal selectivity of CO_2/CH_4 were checked on the membranes.The results revealed that the morphology of the blend membranes was affected by two opposite factors: thermodynamic enhancement and kinetic hindrance. The membranes with denser sponge layers were formed at lower ratio of PU/PES, while more porous structure with enlarged macrovoids membranes were observed at higher PU content. The results indicated that adding PU to PES membrane, caused permeance improvement of the gases with nearly no change and/or reduction in ideal selectivity of CO_2/CH_4. Moreover, PES–ETPU membranes showed higher permeability and less CO_2/CH_4 selectivity in comparison with PES–ESPU samples. For PES–ESPU membrane containing 1.5% ESPU, CO_2 permeance at 10 bar was improved up to 20% with almost no change in CO_2/CH_4 selectivity with respect to PES. Finally, response surface methodology was used to evaluate the effects of the operating parameters on the permeance and ideal selectivity.

Exploring the phytoconstituents targeting TNF-αas potential lead compounds to treat inflammatory diseases:an in-silico approach

Objective To explore the anti-inflammatory phytoconstituents from various plant sources as tumour necrosis factor-α(TNF-α)-inhibitor,a mediator involved in the inflammatory disorder,by in silico molecular docking.Methods Based on previous findings,we performed the in silico assessment of anti-inflammatory phytoconstituents from different medicinal plants to understand their binding patterns against TNF-α(PDB ID:6OP0)using AutoDock Vina.Molecular docking was performed by setting a grid box(25×25×25)Åcentered at[-12.817×(-1.618)×19.009]A with 0.375A of grid spacing.Furthermore,Discovery Studio Client 2020 program was utilized to assess two-and three-dimensional(2D and 3D)hydrogen-bond interactions concerning an amino acid of target and ligand.Physicochemical properties were reported using the Lipinski’s rule and SwissADME database to support the in silico findings.Results From the selected medicinal plants,more than 200 phytocompounds were screened against TNF-α protein with binding scores in the range of -12.3 to -2.5 kcal/mol.Amongst them,emodin,aloe-emodin,pongamol,purpuritenin,semiglabrin,ellagic acid,imperatorin,α-tocopherol,and octanorcucurbitacin A showed good binding affinity as -10.6,-10.0,-10.5,-10.1,-11.2,-10.3,-10.1,-10.1,and -10.0 kcal/mol,respectively.Also,the absorption,distribution,metabolism,excretion,and toxicology(ADMET)profiles were well within acceptable limits.Conclusion Based on our preliminary findings,we conclude that the selected phytoconstituents have the potential to be good anti-inflammatory candidates by inhibiting the TNF-α target.These compounds can be further optimized and validated as new therapeutic components to develop more effective and safe anti-inflammatory drugs.

Machine Learning-Based Quantitative Structure-Activity Relationship and ADMET Prediction Models for ERα Activity of Anti-Breast Cancer Drug Candidates

Breast cancer is presently one of the most common malignancies worldwide,with a higher fatality rate.In this study,a quantitative structure-activity relationship(QSAR)model of compound biological activity and ADMET(Absorption,Distribution,Metabolism,Excretion,Toxicity)properties prediction model were performed using estrogen receptor alpha(ERα)antagonist information collected from compound samples.We first utilized grey relation analysis(GRA)in conjunction with the random forest(RF)algorithm to identify the top 20 molecular descriptor variables that have the greatest influence on biological activity,and then we used Spearman correlation analysis to identify 16 independent variables.Second,a QSAR model of the compound were developed based on BP neural network(BPNN),genetic algorithm optimized BP neural network(GA-BPNN),and support vector regression(SVR).The BPNN,the SVR,and the logistic regression(LR)models were then used to identify and predict the ADMET properties of substances,with the prediction impacts of each model compared and assessed.The results reveal that a SVR model was used in QSAR quantitative prediction,and in the classification prediction of ADMET properties:the SVR model predicts the Caco-2 and hERG(human Ether-a-go-go Related Gene)properties,the LR model predicts the cytochrome P450 enzyme 3A4 subtype(CYP3A4)and Micronucleus(MN)properties,and the BPNN model predicts the Human Oral Bioavailability(HOB)properties.Finally,information entropy theory is used to validate the rationality of variable screening,and sensitivity analysis of the model demonstrates that the constructed model has high accuracy and stability,which can be used as a reference for screening probable active compounds and drug discovery.

Study of Aldo-keto Reductase 1C3 Inhibitor with Novel Framework for Treating Leukaemia Based on Virtual Screening and In vitro Biological Activity Testing

Aldo-keto reductase 1C3(AKR1C3)is a potential target for the treatment of acute myeloid leukaemia and T-cell acute lymphoblastic leukaemia.In this study,pharmacophore models,molecular docking and virtual screening of target prediction were used to find a potential AKR1C3 inhibitor.Firstly,eight bacteriocin derivatives(Z1-Z8)were selected as training sets to construct 20 pharmacophore models.The best pharmacophore model MODEL_016 was obtained by Decoy test(the enrichment degree was 21.5117,and the fitting optimisation degree was 0.9668).Secondly,MODEL_016 was used for the virtual screening of ZINC database.Thirdly,the hit 83256 molecules were docked into the AKR1C3 protein.Compared to the total scores and interactions between compounds and protein,16532 candidate compounds with higher docking scores and interactions with important residues PHE306 and TRP227 were screened.Lastly,eight compounds(A1-A8)that had good absorption,distribution,metabolism,excretion and toxicity(ADMET)properties were obtained by target prediction.Compounds A3 and A7 with high total score and good target prediction results were selected for in vitro biological activity test,whose IC_(50) values were 268.3 and 88.94µmol/L,respectively.The results provide an important foundation for the discovery of novel AKR1C3 inhibitors.The research methods used in this study can also provide important references for the research and development of new drugs.