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Push forward LC-MS-based therapeutic drug monitoring and pharmacometabolomics for anti-tuberculosis precision dosing and comprehensive clinical management

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Journal of Pharmaceutical Analysis 2024年第1期14卷 16-38页

作者： nguyen quang Thu nguyen Tran Nam Tien nguyen Thi Hai Yen Thuc-Huy Duong nguyen Phuoc long Huy Truong nguyen Department of Pharmacology and PharmacoGenomics Research Center Inje University College of MedicineBusan47392Republic of Korea Department of Chemistry University of EducationHo Chi Minh City700000Viet Nam Faculty of Pharmacy Ton Duc Thang UniversityHo Chi Minh City700000Viet Nam

The spread of tuberculosis(TB),especially multidrug-resistant TB and extensively drug-resistant TB,has strongly motivated the research and development of new anti-TB *** strategies to facilitate drug combinations,including pharmacokinetics-guided dose optimization and toxicology studies of first-and second-line anti-TB drugs have also been introduced and *** chromatography-mass spectrometry(LC-MS)has arguably become the gold standard in the analysis of both endo-and exo-genous *** technique has been applied successfully not only for therapeutic drug monitoring(TDM)but also for pharmacometabolomics *** improves the effectiveness of treatment,reduces adverse drug reactions,and the likelihood of drug resistance development in TB patients by determining dosage regimens that produce concentrations within the therapeutic target *** on TDM,the dose would be optimized individually to achieve favorable *** is essential in generating and validating hypotheses regarding the metabolism of anti-TB drugs,aiding in the discovery of potential biomarkers for TB diagnostics,treatment monitoring,and outcome *** article highlighted the current progresses in TDM of anti-TB drugs based on LC-MS bioassay in the last two ***,we discussed the advantages and disadvantages of this technique in practical *** pressing need for non-invasive sampling approaches and stability studies of anti-TB drugs was ***,we provided perspectives on the prospects of combining LC-MS-based TDM and pharmacometabolomics with other advanced strategies(pharmacometrics,drug and vaccine developments,machine learning/artificial intelligence,among others)to encapsulate in an all-inclusive approach to improve treatment outcomes of TB patients.

关键词： Tuberculosis Therapeutic drug monitoring LC-MS MIPD Pharmacometabolomics Precision medicine

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GLOBAL BOUND ON THE GRADIENT OF SOLUTIONS TO p-LAPLACE TYPE EQUATIONS WITH MIXED DATA

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Acta Mathematica Scientia 2024年第4期44卷 1394-1414页

作者： Minh-Phuong TRAN The-quang TRAN Thanh-Nhan nguyen Applied Analysis Research Group Faculty of Mathematics and StatisticsTon Duc Thang UniversityHo Chi Minh CityVietnam nguyen Huu Huan High School Thu Duc CityVietnam Group of Analysis and Applied Mathematics Department of MathematicsHo Chi Minh City University of EducationVietnam

In this paper,the study of gradient regularity for solutions of a class of elliptic problems of p-Laplace type is *** particular,we prove a global result concerning Lorentz-Morrey regularity of the non-homogeneous boundary data problem:-div((s^(2)+|▽u|^(2)p-2/2)▽u)=-div(|f|^(p-2)f)+g inΩ,u=h in■Ω,with the(sub-elliptic)degeneracy condition s∈[0,1]and with mixed data f∈L^(p)(Q;R^(n)),g∈Lp/(p-1)(Ω;R^(n))for p∈(1,n).This problem naturally arises in various applications such as dynamics of non-Newtonian fluid theory,electro-rheology,radiation of heat,plastic moulding and many *** on the idea of level-set inequality on fractional maximal distribution functions,it enables us to carry out a global regularity result of the solution via fractional maximal *** to the significance of M_(α)and its relation with Riesz potential,estimates via fractional maximal functions allow us to bound oscillations not only for solution but also its fractional derivatives of orderα.Our approach therefore has its own interest.

关键词： gradient estimates p-Laplace quasilinear elliptic equation fractional maximal operators Lorentz-Morrey spaces

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A comparative study on kinetics and dynamics of two dump truck lifting mechanisms using MATLAB simscape

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Theoretical & Applied Mechanics Letters 2024年第2期14卷 146-156页

作者： Thong Duc Hong Minh quang Pham Son Cong Tran Lam quang Tran Truong Thanh nguyen Faculty of Transportation Engineering Ho Chi Minh City University of Technology(HCMUT)Ho Chi Minh City 700000Vietnam Vietnam National University Ho Chi Minh City(VNU-HCM) Ho Chi Minh City 700000Vietnam Industrial Maintenance Training Center Ho Chi Minh City University of Technology(HCMUT)Ho Chi Minh City 700000Vietnam

In this paper,two lifting mechanism models with opposing placements,which use the same hydraulic hoist model and have the same angle of 50°,have been *** mechanical and hydraulic simulation models are established using MATLAB Simscape to analyze their kinetics and dynamics in the lifting and holding *** simulation findings are compared to the analytical calculation results in the steady state,and both methods show good *** the early lifting stage,Model 1 produces greater force and discharges goods in the container faster than Model ***,Model 2 reaches a higher force and ejects goods from the container cleaner than its counterpart at the end lifting *** established simulation models can consider the effects of dynamic loads due to inertial moments and forces generated during the system *** is crucial in studying,designing,and optimizing the structure of hydraulic-mechanical systems.

关键词： Dump truck Lifting mechanism Hydraulic MATLAB Simscape Kinetic dynamic analysis

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An Enhanced Ensemble-Based long Short-Term Memory Approach for Traffic Volume Prediction

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Computers, Materials & Continua 2024年第3期78卷 3585-3602页

作者： Duy quang Tran Huy Q.Tran Minh Van nguyen Faculty of Civil Engineering Nha Trang UniversityNha Trang650000Vietnam Robotics and Mechatronics Research Group Faculty of Engineering and TechnologyNguyen Tat Thanh UniversityHo Chi Minh City700000Vietnam Department of Civil Engineering Ho Chi Minh City University of Technology and EducationHo Chi Minh City700000Vietnam

With the advancement of artificial intelligence,traffic forecasting is gaining more and more interest in optimizing route planning and enhancing service *** volume is an influential parameter for planning and operating traffic *** study proposed an improved ensemble-based deep learning method to solve traffic volume prediction problems.A set of optimal hyperparameters is also applied for the suggested approach to improve the performance of the learning *** fusion of these methodologies aims to harness ensemble empirical mode decomposition’s capacity to discern complex traffic patterns and long short-term memory’s proficiency in learning temporal ***,a dataset for automatic vehicle identification is obtained and utilized in the preprocessing stage of the ensemble empirical mode decomposition *** second aspect involves predicting traffic volume using the long short-term memory ***,the study employs a trial-and-error approach to select a set of optimal hyperparameters,including the lookback window,the number of neurons in the hidden layers,and the gradient descent ***,the fusion of the obtained results leads to a final traffic volume *** experimental results show that the proposed method outperforms other benchmarks regarding various evaluation measures,including mean absolute error,root mean squared error,mean absolute percentage error,and *** achieved R-squared value reaches an impressive 98%,while the other evaluation indices surpass the *** findings highlight the accuracy of traffic pattern ***,this offers promising prospects for enhancing transportation management systems and urban infrastructure planning.

关键词： Ensemble empirical mode decomposition traffic volume prediction long short-term memory optimal hyperparameters deep learning

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Assessment of Radiation Dose Caused by Radioactive Gaseous Effluent Released from Nuclear Power Plant Ninh Thuan 1 under Scenario of Normal Working Conditions

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World Journal of Nuclear Science and Technology 2015年第3期5卷 183-191页

作者： nguyen Tuan Khai Do Xuan Anh Le Dinh Cuong Duong Duc Thang Vuong Thu Bac nguyen Thi Thu Ha nguyen quang long Trinh Van Giap nguyen Hao quang Institute for Nuclear Science and Technology (INST) Hanoi Vietnam Vietnam Atomic Energy Institute (VINATOM) Hanoi Vietnam

Based on guides RG 1.109, RG 1.111 published by United States Nuclear Regulatory Commission (USNRC), our research concentrates in assessing radiation doses caused by radioactive substances released from the nuclear power plant (NPP) Ninh Thuan 1 under the scenario of normal operation using software package NRCDose72 provided by the USNRC. The database including the released radioactive nuclides, meteorology, terrain, population and agricultural production activities have been collected and processed to build the input data for the model calculation. The wind rose distribution obtained from the meteorological data in a five-year period from 2009-2013 showed that the radioactive nuclides released to environment spread in two main wind directions which are North East and South West. The X/Q (s/m3) and D/Q (s/m2) qualities which are, respectively, the ratio of activity concentration to release rate and that of deposition density of radioactive nuclides to release rate were calculated within an area of 80 km radius from the NPP site using XOQDOQ. Population doses were calculated using GASPAR. The XOQDOQ and GASPAR are two specific softwares in NRCDose72 package.

关键词： NPP Radioactive Release Radiation Dose Population Dose X/Q and D/Q

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A Complex Fuzzy LSTM Network for Temporal-Related Forecasting Problems

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Computers, Materials & Continua 2024年第9期80卷 4173-4196页

作者： nguyen Tho Thong nguyen Van Quyet Cu nguyen Giap nguyen long Giang Luong Thi Hong Lan Institute of Information Technology Vietnam Academy of Science and TechnologyHoang Quoc VietCau GiayHanoi100000Vietnam Academic Affairs Department Thai Nguyen University of EducationThai Nguyen250000Vietnam Center of Science and Technology Research and Development Thuongmai UniversityHo Tung MauCau GiayHanoi100000Vietnam Faculty of Information Technology Hanoi University of IndustryBac Tu LiemHanoi100000Vietnam

Time-stamped data is fast and constantly growing and it contains significant information thanks to the quick development ofmanagement platforms and systems based on the Internet and cutting-edge information communication *** the time series data including time series prediction has many practical *** new techniques were developed for use with various types of time series data in the prediction *** those,this work suggests a unique strategy to enhance predicting quality on time-series datasets that the timecycle matters by fusing deep learning methods with fuzzy *** order to increase forecasting accuracy on such type of time-series data,this study proposes integrating deep learning approaches with fuzzy ***,it combines the long short-termmemory network with the complex fuzzy set theory to create an innovative complex fuzzy long short-term memory model(CFLSTM).The proposed model adds a meaningful representation of the time cycle element thanks to a complex fuzzy set to advance the deep learning long short-term memory(LSTM)technique to have greater power for processing time series *** on standard common data sets and real-world data sets published in the UCI Machine Learning Repository demonstrated the proposedmodel’s utility compared to other well-known forecasting *** results of the comparisons supported the applicability of our proposed strategy for forecasting time series data.

关键词： Complex fuzzy set long short-term memory(LSTM) CFLSTM T-CFLSTM

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Photocatalytic degradation of antibiotic sulfamethizole by visible light activated perovskite LaZnO_(3)

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Journal of Environmental Sciences 2024年第10期144卷 212-224页

作者： Bui The Huy XCuong nguyen Vu Khac Hoang Bui nguyen Ngoc Tri Iqra Rabani Nhu Hoa Thi Tran quang Viet Ly Hai Bang Truong Major of Biomedical Engineering Division of Smart HealthcareCollege of Information Technology and ConvergencePukyong National UniversityBusan 48513Korea Center for Advanced Chemistry Institute of Research and DevelopmentDuy Tan UniversityDa Nang 550000Viet Nam Faculty of Environmental and Chemical Engineering Duy Tan UniversityDa Nang 550000Viet Nam Department of Environment and Energy Sejong UniversitySeoul 05006Korea Lab of Computational Chemistry and Modelling Department of ChemistryFaculty of Natural SciencesQuy Nhon UniversityQuy NhonViet Nam Department of Nanotechnology and Advanced Materials Engineering Sejong UniversitySeoul 05006Korea Faculty of Materials Science and Technology University of ScienceHo Chi Minh City 700000Viet Nam Vietnam National University Ho Chi Minh City 700000Viet Nam Department of Environmental Engineering Seoul National University of Science and TechnologySeoul 01811Korea Optical Materials Research Group Science and Technology Advanced InstituteVan Lang UniversityHo Chi Minh CityViet Nam Faculty of Applied Technology School of TechnologyVan Lang UniversityHo Chi Minh CityViet Nam

In thiswork,the perovskite LaZnO_(3) was synthesized via sol-gel method and applied for photocatalytic treatment of sulfamethizole(SMZ)antibiotics under visible light *** was almost completely degraded(99.2%±0.3%)within 4 hr by photocatalyst LaZnO3 at the optimal dosage of 1.1 g/L,with amineralization proportion of 58.7%±0.4%.The efficient performance of LaZnO_(3) can be attributed to itswide-range light absorption and the appropriate energy band edge levels,which facilitate the formation of active agents such as·O_(2)^(−),h^(+),and·*** integration of RP-HPLC/Q-TOF-MS and DFT-based computational techniques revealed three degradation pathways of SMZ,which were initiated by the deamination reaction at the aniline ring,the breakdown of the sulfonamidemoieties,and a process known as Smile-type rearrangement and SO2 *** toxicity of SMZ and the intermediateswere analyzed by quantitative structure activity relationship(QSAR),indicating the effectiveness of LaZnO_(3)-based photocatalysis in preventing secondary pollution of the intermediates to the ecosystem during the degradation *** visible-light-activated photocatalyst LaZnO_(3) exhibited efficient performance in the occurrence of inorganic anions and maintained high durability across multiple recycling tests,making it a promising candidate for practical antibiotic treatment.

关键词： Perovskite Antibiotics Photocatalysis Density functional theory Toxicity

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Comparative Chemical Research in Essential Oils from Six Apiaceae Species Growing in the Northern Region of Vietnam

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Phyton-International Journal of Experimental Botany 2024年第7期93卷 1677-1687页

作者： nguyen quang Hung nguyen Thanh Tung nguyen Phuong Hanh Chu Thi Thu Ha nguyen Thi Nhung nguyen Thai An Vu Xuan Giang Luong Van Hao Oleh Koshovyi Ain Raal Institute of Ecology and Biological Resources Vietnam Academy of Science and Technology(VAST)Cau GiayHa Noi100000Viet Nam Graduate University of Science and Technology Vietnam Academy of Science and Technology(VAST)Cau GiayHa Noi100000Viet Nam Department of Pharmacognosy Faculty of Pharmacognosy and Traditional MedicineHanoi University of PharmacyHoan KiemHa Noi100000Viet Nam Sa Pa Research Center of Medicinal Materials National Institute of Medicinal MaterialsDien Bien PhuSa PaLao Cai330000Viet Nam Institute of Pharmacy Faculty of MedicineUniversity of TartuTartu50411Estonia

Our study aimed to compare the essential oil(EO)concentration and composition of several Apiaceae species growing in the Northern region of *** yields of EOs from materials ranged from 0.03%(root EO of Angelica acutiloba and aerial parts EO of Heracleum bivittatum)-0.27%(leaf EO of Xyloselinum vietnamense).Gas chromatography-mass spectrometry(GC-MS)allowed the identiﬁcation of 74 components in the EOs of six Apiaceae species,making up 94.4%–100.0%of the *** EO from Angelica acutiloba,(Z)-ligustilide accounted for an extremely large proportion(94.9%).EO of Angelica pubescens was dominated by six character-istic components includingα-pinene(21.5%),β-phellandrene(18.1%),p-cymene(12.2%),3-methylnonane(8.7%),o-cymene(8.1%),and D-sylvestrene(6.2%).The EO from Cryptotaenia japonica was characterized by high amounts ofα-selinene(48.7%),β-selinene(23.7%),and trans-β-farnesene(5.4%).The EOs from leaves and stems of Xyloselinum vietnamense were characterized by high concentrations of sabinene(69.8%and 33.8%),4-terpineol(8.7%and 7.4%)andβ-pinene(4.0%and 6.5%)while EOs from aerial parts and root of Xylo-selinum leonidii comprise four characteristic monoterpenes includingα-pinene(28.2%and 52.8%),β-pinene(7.9%and 10.3%),β-phellandrene(7.6%and 15.3%),and sabinene(3.0%and 4.1%).Additionally,cryptone is also one of the major components in the EO of Xyloselinum leonidii(13.2%in the aerial parts oil and 2.8%in the root oil).In the EOs isolated from the aerial parts and root of Heracleum bivittatum,α-pinene(22.5%and 70.2%)andβ-pinene(43.2%and 20.0%)were the predominant *** appeared in the EO from aerial parts of Heracleum bivittatum with a relatively high concentration(13.5%)while bornyl acetate(5.1%)was also one of the main components in the EO from its aerial parts but was not detected in other Apiaceae species in the present *** databases help identify and control the quality of plant material studied from the family Apiaceae growing in Vietnam.

关键词： Apiaceae essential oil terpenoids gaschromatography-mass spectrometry

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Generating highly active oxide-phosphide heterostructure through interfacial engineering to break the energy scaling relation toward urea-assisted natural seawater electrolysis

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Journal of Energy Chemistry 2024年第10期97卷 687-699页

作者： Ngoc quang Tran Nam Hoang Vu Jianmin Yu Khanh Vy Pham nguyen Thuy Tien nguyen Tran Thuy-Kieu Truong Lishan Peng Thi Anh Le Yoshiyuki Kawazoe Center for Innovative Materials and Architectures Vietnam National University Faculty of Materials Science and Technology University of Science Key Laboratory of Rare Earths Ganjiang Innovation Academy Chinese Academy of Sciences Department of Mechanical Engineering Hanbat National University (HBNU) School of Chemical Engineering-Hanoi University of Science and Technology New Industry Creation Hatchery Center Tohoku University

Urea-assisted natural seawater electrolysis is an emerging technology that is effective for grid-scale carbon-neutral hydrogen mass production yet *** scaling relations is an effective strategy to break through the bottleneck of natural seawater ***,by DFT calculation,we demonstrated that the interface boundaries between Ni2P and MoO2play an essential role in the selfrelaxation of the Ni-O interfacial bond,effectively modulating a coordination number of intermediates to control independently their adsorption-free energy,thus circumventing the adsorption-energy scaling *** this conceptual model,a well-defined 3D F-doped Ni2P-MoO2heterostructure microrod array was rationally designed via an interfacial engineering strategy toward urea-assisted natural seawater *** a result,the F-Ni2P-MoO2exhibits eminently active and durable bifunctional catalysts for both HER and OER in acid,alkaline,and alkaline sea water-based *** in-situ analysis,we found that a thin amorphous layer of NiOOH,which is evolved from the Ni2P during anodic reaction,is real catalytic active sites for the OER and UOR ***,such electrode-assembled urea-assisted natural seawater electrolyzer requires low voltages of 1.29 and 1.75 V to drive 10 and600 mA cm-2and demonstrates superior durability by operating continuously for 100 h at 100 mA cm-2,beyond commercial Pt/C || RuO2and most previous reports.

关键词： Break scaling relationships Doping Interfacial engineering Natural seawater splitting Urea electrolysis

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Machine learning based models for predicting compressive strength of geopolymer concrete

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Frontiers of Structural and Civil Engineering 2024年第7期18卷 1028-1049页

作者： quang-Huy LE Duy-Hung nguyen Thanh SANG-TO Samir KHATIR Hoang LE-MINH Amir H.GANDOMI Thanh CUONG-LE Center for Engineering Application and Technology Solutions Ho Chi Minh City Open UniversityHo Chi Minh 700000Vietnam Institute of Civil Engineering Ho Chi Minh City University of TransportHo Chi Minh 700000Vietnam Faculty of Engineering&Information Technology University of Technology SydneyUltimoNSW 2007Australia

Recently,great attention has been paid to geopolymer concrete due to its advantageous mechanical and environmentally friendly *** effort has been made in experimental studies to advance the understanding of geopolymer concrete,in which compressive strength is one of the most important *** facilitate engineering work on the material,an efficient predicting model is *** this study,three machine learning(ML)-based models,namely deep neural network(DNN),K-nearest neighbors(KNN),and support vector machines(SVM),are developed for forecasting the compressive strength of the geopolymer concrete.A total of 375 experimental samples are collected from the literature to build a database for the development of the predicting models.A careful procedure for data preprocessing is implemented,by which outliers are examined and removed from the database and input variables are standardized before feeding to the fitting *** standard K-fold cross-validation approach is applied for evaluating the performance of the models so that overfitting status is well managed,thus the generalizability of the models is *** effectiveness of the models is assessed via statistical metrics including root mean squared error(RMSE),mean absolute error(MAE),correlation coefficient(R),and the recently proposed performance index(PI).The basic mean square error(MSE)is used as the loss function to be minimized during the model fitting *** three ML-based models are successfully developed for estimating the compressive strength,for which good correlations between the predicted and the true values are obtained for DNN,KNN,and *** numerical results suggest that the DNN model generally outperforms the other two models.

关键词： geopolymer concrete compressive strength prediction machine-learning based model deep neural network K-nearest neighbor support vector machines

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