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Cyclosporin A is a calcineurin inhibitor which has a narrow therapeutic window and high interindividual variability. Various population pharmacokinetic models have been reported; however, professional software and technical personnel were needed and the variables of the models were limited. Therefore, the aim of this study was to establish a model based on machine learning to predict CsA trough concentrations in Chinese allo-HSCT patients. A total of 7874 cases of CsA therapeutic drug monitoring data from 2069 allo-HSCT patients were retrospectively included. Sequential forward selection was used to select variable subsets, and eight different algorithms were applied to establish the prediction model. XGBoost exhibited the highest prediction ability. Except for the variables that were identified by previous studies, some rarely reported variables were found, such as norethindrone, WBC, PAB, and hCRP. The prediction accuracy within ±30% of the actual trough concentration was above 0.80, and the predictive ability of the models was demonstrated to be effective in external validation. In this study, models based on machine learning technology were established to predict CsA levels 3–4 days in advance during the early inpatient phase after HSCT. A new perspective for CsA clinical application is provided.

Location-based Service has become the fastest growing activity related service that people use in their daily life due to the boom of location-aware mobile devices. In edge computing along with the benefits brought by LBS, privacy preservation becomes a more challenging issue because of the nature of the paradigm, in which peers may cooperate with each other to collect and analyze user's location data. To avoid potential information leakage and usage, user's exact location should not be exposed to the edge node. In this paper, we propose a stochastic location privacy protection scheme for edge computing, in which the geographical distribution of surrounding users is obtained by analyzing proposed long-term density map and short-term density map. The cloaking scheme transfers user's exact location to a cloaked location to satisfy predefined probability of having k-users in that area. Our scheme does not reveal any exact location information, thus it is practicable for the real scenario when edge computing is honest but curious. Extensive experimental results are conducted to verify the efficiency and effectiveness of our method. By varying the privacy protection requirements, the corresponding performance have been examined and discussed.

Because of the complexity of gear working condition, there are non-linear relationship between characteristic parameters and fault types. This paper proposes to apply the Support Vector Machine to set up the nonlinear mapping to solve the difficulties of gear fault diagnosis. Taking a certain gearbox fault signal acquisition experimental system for instance, Matlab software and its neural network toolbox are used to model and simulate. The simulation result shows the founded model has preferable learning and generalization capabilities, which performs effectively in the common gear fault diagnosis and it can identify various types of faults stably and accurately.

The objective of this study was to investigate the possible association of the ABCB1 gene C3435 T polymorphism and the CYP3A5 gene A6986G polymorphism with sirolimus (SRL) trough concentration and dose requirements in Chinese stable renal transplant recipients. Blood samples were collected from 105 healthy volunteers and 50 renal transplant patients, whose polymorphisms of the ABCB1 and CYP3A5 genes were determined by polymerase chain reaction (PCR)-restriction fragment length polymorphism (RFLP). Plasma concentrations of SRL were determined with HPLC. The allele frequencies of the ABCB1 mutation in Chinese healthy volunteers and renal transplant recipients were 51.0% and 44.0% (p0.05), while the allele frequencies of the CYP3A5 mutation were 72.9% and 71.0% (p0.05). The SRL concentration/dose ratio (C/D) in patients with CYP3A5 (*)3/(*)3 were significantly higher than that of those with (*)1 allele (p0.05). However, no significant differences were observed between C/D and ABCB1 SNPs (p0.05). These results confirm that when treated with a SRL-based therapy and low-dose steroids, patients carrying the CYP3A5(*)1 allele required significantly more SRL to achieve adequate blood trough concentrations. In patients with SRL-based therapy, genotyping of the CYP3A5 genes may help to optimize the SRL management in renal transplant recipients.

A rapid, sensitive, precise and specific method for determination of hematoporphyrin monomethyl ether (HMME), a novel photodynamic therapy (PDT) drug, was developed and validated using high-performance liquid chromatography (HPLC) with fluorescence detection. HMME was isolated from the plasma by a single-step liquid-liquid extraction with ethyl acetate. The analyte and internal standard fluorescein were baseline separated on a Diamonsil C(18) analytical column (4.6 x 150 mm, 5 microm) and analyzed using a fluorescence detector with the excitation and emission wavelengths set at 395 and 613 nm, respectively. The method was linear in the concentration range 0.025-5 microg/mL with a lower limit of quantitation (LLOQ) of 10 ng/mL. The inter- and intra-day accuracies and precisions were all within 10% and the mean recoveries of HMME and fluorescein were 95 +/- 3.7 and 90 +/- 2.3%, respectively. The analyte was stable during all sample storage, preparation and analysis periods. This method was successfully applied to a pharmacokinetic study after a single-dose intravenous administration of HMME (5 mg/kg) to beagle dogs. This method was reproducible and sensitive enough for the pharmacokinetic study of HMME. Based on the results of the pharmacokinetic study, we suggest that a rather long light-avoiding time is essential for patients under HMME therapy.

To develop a HPLC-MS method of determining ginsenoside Rh2 in dog plasma based on solid-phase extraction for pharmacokinetic studies. Six dogs were randomly assigned to two groups, either given 0.1 mg/kg dose intravenously or 1 mg/kg dose through oral gavage. Analysis using high performance liquid chromatography (HPLC) with ODS column, followed by detection with electrospray ionization(ESI) mass spectrometry(MS) in negative ion mode with 500 microM ammonium chloride in the mobile phase. The assays were validated over the concentration range of 2.0-1250.0 ng/ml in dog plasma. The intra- and inter- day precision were less than 10% in terms of RSD. The overall recovery was more than 80%. The validated assay was suitable for pharmacokinetic studies of ginsenoside Rh2 and the observed oral bioavailabilities of Rh2 were 17.6% and 24.8% for male and female dogs respectively.

The uptake and metabolism profiles of ginsenoside Rh2 and its aglycon protopanaxadiol (ppd) were studied in the human epithelial Caco-2 cell line. High-performance liquid chromatography-mass spectrometry was applied to determine Rh2 and its aglycon ppd concentration in the cells at different pH, temperature, concentration levels and in the presence or absence of inhibitors. Rh2 uptake was time and concentration dependent, and its uptake rates were reduced by metabolic inhibitors and influenced by low temperature, thus indicating that the absorption process was energy-dependent. Drug uptake was maximal when the extracellular pH was 7.0 for Rh2 and 8.0 for ppd. Rh2 kinetic analysis showed that a non-saturable component (Kd 0.17 nmol x h(-1) x mg(-1) protein) and an active transport system with a Km of 3.95 micromol x l(-1) and a Vmax of 4.78 nmol x h(-1) x mg(-1)protein were responsible for the drug uptake. Kinetic analysis of ppd showed a non-saturable component (Kd 0.78 nmol x h(-1) x mg(-1) protein). It was suggested that active extrusion of P-glycoprotein and drug degradation in the intestine may influence Rh2 bioavailability.

In this paper, the BP neural network improved by the genetic algorithm (GA) is applied to the problem of human face detection. GA is used to optimize the initial weights of the BP neural network to make full use of its global optimization and local accurate searching of the BP algorithm. Matlab Software and its neural network toolbox are used to simulate and compute. The experiment results show that the GA-BP neural network has a good performance for face detection. Furthermore, compared with the conventional BP algorithm, the GA-BP learning algorithm has more rapid convergence and better assessment accuracy of detecting quality.

To assess the contribution of vitamin K epoxide reductase complex 1 (VKORC1) and cytochrome P450 2C9 (CYP2C9) genotype, age, body size, height, and weight to warfarin dose requirement.Blood samples were collected from 191 patients receiving warfarin therapy. Patients's age, gender, height, and weight were registered. PCR-RFLP method was used for the detection of VKORC1-1639GA and CYP2C9 genotype.VKORC1-1639GA genotyping showed that 159 patients were homozygous AA, 31 were heterozygous GA, and 1 was homozygous GG genotype. CYP2C9 genotyping showed that 176 patients were *1/*1, 15 patients were heterozygous *1/*3. Patients with VKORC1-1639 (GA) GG + GA genotype required a significantly higher warfarin dose than those with AA genotype [(3.36 +/- 0.97) mg/d vs. (1.75 +/- 0.56) mg/d, P0.01], and patients with CYP2C9*1/*1 genotype also required a higher warfarin dose than those with CYP2C9*1/*3 genotype [(2.06 +/- 0.83) mg/d vs. (1.55 +/- 1.32) mg/d, P0.05]. The multiple linear regression model for warfarin dose indicated age, weight and VKORC1 genotype could explain the inter-individual variation in dose requirement of 9.3%, 7.4%, 51.9% patients, respectively; age, weight, CYP2C9 and VKORC1 genotype together could explain the inter-individual variation in dose requirement of 64.1% patients.This study showed that age, weight and VKORC1 and CYP2C9 polymorphism had significant influences on warfarin dose requirements and should be considered on dosing regimens modification to improve the safety of warfarin therapy.

The intestinal absorptive characteristics of ginkgolide B were investigated. The Caco-2 cells and the in situ closed loop were used as models of the intestinal mucosa to assess transepithelial transport of ginkgolide B. The determination of ginkgolide B was performed by HPLC-MS. In the Caco-2 cells, the absorptive transepithelial transport of ginkgolide B was pH dependent and the transport was enhanced at weakly acidic pH on the apical side. No concentration dependence and saturation were observed for the absorptive transport of ginkgolide B at concentrations up to 50 microM. In the in situ closed loop, the absorption of ginkgolide B was intestinal segment-selective. The results indicate that the intestinal absorption of ginkgolide B in the upper intestine was significantly higher than that in the lower intestine.

The purpose of this study was to investigate the transport characteristics and mechanisms for discovering the possible causes of the low bioavailability of astragaloside IV and to develop an absorption enhancement strategy. Caco-2 cells used as the in vitro model. Results showed a low permeability coefficient (3.7 x 10(-8)cm/s for transport from the AP to BL direction), which remained unchanged throughout the concentration range studied, indicating that the transport of astragaloside IV was predominantly via a passive route. The AP to BL transport of astragaloside IV was found to be highly sensitive to the extracellular Ca2+ concentration, which suggested that its transport may be via a paracellular route. Both chitosan and sodium deoxycholate can increase the permeation efficiency of astragaloside IV. This study indicated that astragaloside IV having a low fraction dose absorbed in humans mainly due to its poor intestinal permeability, high molecular weight, low lipophilicity as well as its paracelluar transport may directly result in the low permeability through its passive transport. Meanwhile, chitosan and sodium deoxycholate can be used as absorption enhancers based on its transport mechanism.

Astragaloside-IV (3-O-beta-d-xylopyranosyl-6-O-beta-d-glucopyranosyl-cycloastragenol) is the major active constituent contained in Radix Astragali. This paper describes a rapid, sensitive and specific assay for quantitative determination of astragaloside-IV in rat plasma. After a liquid/liquid extraction (LLE) with n-butanol and high-performance liquid chromatography (HPLC) gradient separation with acetonitrile-NH4Cl solution (0.5 micromol/L) as the mobile phase, the anions adduct [M + Cl]- at m/z 819.4 of astragaloside-IV, and [M + Cl]- at m/z 815.35 of internal standard (IS) digoxin were analyzed by electrospray ionisation-mass spectrometry (LC-ESI-MS) in selected ion monitoring (SIM) mode. Chromatographic separation was achieved in less than 9 min and calibration curve was linear over a concentration range of 2-200 ng/ml. The described assay method was successfully applied to the preclinical pharmacokinetic study of astragaloside-IV. After intragastric administration of astragaloside-IV to rats, Cmax and Tmax of astragaloside-IV were 134.73 +/- 39.86 ng/ml and 1.5 h, respectively, and the elimination half-life (t1/2) was 5.45 +/- 0.39 h.