Journal of Pharmaceutical and Biomedical Analysis

This contains the raw data for the study.

Dataset for the article titled 'Electrospun nanofiber-based niflumic acid capsules with superior physicochemical properties'

Original of the study.

This data set includes the data for calibration, testing and validation of a model developed at a research laboratory and used to establish blending specifications at a development continuous manufacturing plant. This information would be later on implemented in a continuous manufacturing plant.

Raw LC-MS/MS results obtained from optimization experiments

Neomycin, an aminoglycoside antibiotic widely used in animal breeding industry, is difficult to detect due to its lack of significant UV absorbance or fluorophore. In this paper, a selective fluorescent sensor was developed to detect neomycin in complex biological samples. Fluorescent molecularly imprinted polymers (fMIPs) containing both imprinted cavity and boronate affinity site were synthesized on the surface of silica modified quantum dots (QDs). The achieved fMIPs exhibited high selectivity to neomycin by having two binding sites for neomycin. The existence of neomycin analogues (competing for the imprinted cavity) and D-glucose (competing for the boronate affinity site) did not affect the selective binding of neomycin to the fMIPs. A selective fluorescent sensor was developed by combining the fMIPs with a fluorescent microplate reader. The sensor could quantify neomycin in a linear range of 2-1000 μg/L with a detection limit of detection as 0.16 μg/L. Trace neomycin in complex biological samples after simple (one step) sample pretreatment, which were not suitable for HPLC-FLD analysis due to the presence of large amounts of interferences, could be quantified accurately by the fMIP sensor. The developed fMIP sensor provides a selective, sensitive, accurate and high through-put solution to detect neomycin in complex biological samples. As far as we known, this is the first report to utilize QDs-based fMIPs with doubly selective binding sites to realize rapid and high through-put neomycin monitoring in complex biological samples.

Sample preparation for NMR Previously stored O. sinensis and C. militaris were divided into two groups and used for 1H NMR sample preparation. Prior to NMR analysis, O. sinensis and C. militaris were thawed to room temperature. For the 50% water:ethanol (H2O:EtOH) group, 5 mL of the 50% water:ethanol mixture was added to 500 mg O. sinensis or C. militaris and vortexed for 60 s. The mixtures were maintained for 360 days at 25oC. For the water (H2O) group, 5 mL of distilled water was added to 500 mg of O. sinensis or C. militaris. The mixtures were placed in boiling water and heated to 100oC for 30 mins. The extracts were centrifuged (15 min, 13,000 rpm) at 4oC and 3 mL of supernatant was collected. The supernatant was frozen at -80oC and then dried using a vacuum centrifugal evaporator (CHRiST, Alpha 2-4/LSC, Germany). The dried residues were separately dissolved in 3 mL of distilled water. A 600 µL extract was filtered (Millipore Amicon® ULTRA 3 kDa) and filtrates were collected. 3-(Trimethylsilyl) propanesulfonic acid (50 µL) pre-dissolved in D2O (an internal standard) was subsequently added to 450 µL of the filtrates. Finally, aliquots (480 µL) of each extract were transferred to a 5 mm NMR tube (Norell, Morganton, NC, USA) for NMR analysis. The 1H NMR spectra were recorded as detailed below. NMR analysis and data preprocessing All of the 1H NMR spectra were acquired at 298 K on a Bruker AV III 600 MHz NMR spectrometer (Bruker Analytische GmbH, Rheinstetten, Germany) equipped with an inverse cryoprobe operating at a proton NMR frequency of 600.13 MHz. For each sample, other used acquisition parameters were as follows: number of scans = 32, spectral width (SW) = 8,000 Hz, pulse width (PW) = 10 s, and relaxation delay = 1.0 s. A Noesygppr1d pulse sequence was applied to suppress the residual water signal. All of the free induction decay NMR spectra were phased and baseline-correction was performed using Chenomx NMR Suite v.7.7 (Chenomx Inc., Edmonton, Canada). The metabolites were identified by matching spectral signals to the Chenomx 600 MHz Library comprising 330 metabolites. A reference compound DSS-d6 was used as an internal standard for the chemical shifts (set to 0 ppm) and a reference signal for the quantification. Data quantification was performed by comparing the integration of a known reference signal (DSS-d6) with the signals derived from a library of compounds containing chemical shifts and peak multiplicities for all of the resonances of the constituents. The results were exported as an Excel file for further analysis.

We provide the NMR spectra of RS4/5/8,the MS data of CoA and RSs, the plaisible fragmentaton mechanism of RSs and the raw data of method validation.

Arsenic trioxide (ATO, arsenite (AsIII) in solution) has been applied successfully for treating acute promyelocytic leukemia (APL). Arsenic speciation analysis of urine is critical to reveal metabolic mechanism and the relationship between arsenic species and clinical response. The aim of the present study was to characterize arsenic species in APL urine and explore the metabolism and toxicity of arsenic in patients with APL undergoing As2O3 treatment.A simple and robust HPLC-HG-AFS method was developed and validated to quantify the levels of arsenic species (AsIII and its metabolites, monomethylarsonic acid (MMAV), dimethylarsinic acid (DMAV) and arsenate (AsV)) in urine samples from 66 APL patients. Patients received ATO at 0.16 mg/kg daily with the protocols of continuous slow-rate infusion or conventional infusion. Urine samples were collected at steady state before ATO application. AsIII and DMAV were the highest among all arsenic species in urine (p<0.0001). AsV was the lowest arsenic species in all urine samples. The relative proportions in urine were AsIII 33.00% (IQR: 24.34 to 46.82 %), DMAV 36.42 % (IQR: 25.82 to 51.98 %), MMAV 23.89 % (IQR: 19.52 % to 27.19 %) and AsV 2.22 % (IQR: 1.293 to 3.665%). Good positive correlations were found between arsenic species levels in urine and those in plasma. The AsV% treated with continuous slow-rate infusion was significantly higher than those with conventional infusion (p<0.05). Un-metabolized AsIII and DMAV were dominant arsenic compounds excreted from urine of APL patient treated ATO. MMAV and DMAV are the end products of arsenic metabolism. The levels and proportions of arsenic species possess wide variability among individual patients. Urinary arsenic can reflect the levels of arsenic in plasma. Urinary arsenic is critical as biomarker to evaluate the metabolism and toxicity of arsenic in the clinical use of ATO.

This excel file is the data used for testing CMM. The compounds here presented were found in Plasma samples and they were identified with the use of available standards.