Good Correlation Research Articles

Formulation and characterization: Metoprolol succinate controlled release matrix tablets

Metoprolol succinate-controlled release matrix tablets were made utilizing the wet granulation process with various ratio of Hydroxypropyl methyl cellulose (HPMC K4M). Isopropyl alcohol is used as a granulating agent in the Povidone (PVP K30) solution. In addition to being utilised as diluents to raise the weight of the tablets, magnesium stearate and talc were added to enhance the granules' flow ability during tablet compression. The crushed tablets underwent physicochemical characteristics, in-vitro and kinetic tests, and the micromeritic properties of the generated granules were evaluated. In every formulation, results were nearly satisfactory, with M4 being the best among the others. All of the formulations showed good correlation. The drug diffusion kinetics from matrix tablets appeared to be zero order, and the release mechanism was diffusion regulated.

Intraductal papillary mucinous neoplasms of the pancreas: Cytologic-histologic correlation study and evaluation of the cytologic accuracy in identifying high-grade dysplasia/invasive adenocarcinoma.

Intraductal papillary mucinous neoplasms (IPMNs) may be associated with invasive adenocarcinoma, low-grade dysplasia (LGD), or high-grade dysplasia (HGD). We aimed to review the cytologic-histologic correlation of cases with a histologic diagnosis of IPMN. A database search (January 2010-January 2021) was performed for resected IPMNs with preceding endoscopic ultrasound-guided fine-needle aspiration (FNA). Cytology slides were reviewed for the presence of benign, atypical, or malignant cells, and necrosis. Histologically, IPMNs were classified as benign (LGD) or malignant (HGD or adenocarcinoma). There were 41 patients with IPMN; 24 malignant and 17 benign. Sixteen of the 24 malignant IPMNs were accurately classified as malignant on cytology. There were eight false negatives and one false positive. Cytology yielded a sensitivity of 67% and a specificity of 94%. Among the 16 true positives with FNA diagnosis of adenocarcinoma, seven were IPMNs with HGD, and nine had invasive adenocarcinomas on histology. Cellular morphology and absence or presence of necrosis did not help distinguish HGD from adenocarcinoma on cytology (P > 0.5). Sampling errors and interpretative errors resulted in false-negative cases. Cytology yielded diagnoses related to IPMN in 73% of cases (30/41) and lack of identification of mucinous cells/mucinous background resulted in interpretative errors (9). This study shows that there is a good correlation between cytopathology and surgical pathology diagnoses of IPMNs and that cytology is mostly able to recognize IPMN with HGD/adenocarcinoma. However, heterogeneity in areas of IPMN with HGD/adenocarcinoma may result in sampling errors yielding false-negative cases. Mucinous cells/background should raise the suspicion of IPMN on cytology, even when no neoplastic epithelium is present for the evaluation of dysplasia.

Fluorescence-Polarization-Based Assaying of Lysozyme with Chitooligosaccharide Tracers.

Lysozyme is a well-known enzyme found in many biological fluids which plays an important role in the antibacterial protection of humans and animals. Lysozyme assays are used for the diagnosis of a number of diseases and utilized in immunohistochemistry, genetic and cellular engineering studies. The assaying methods are divided into two categories measuring either the concentration of lysozyme as a protein or its activity as an enzyme. While the first category of methods traditionally uses an enzyme-linked immunosorbent assay (ELISA), the methods for the determination of the enzymatic activity of lysozyme use either live bacteria, which is rather inconvenient, or natural peptidoglycans of high heterogeneity and variability, which leads to the low reproducibility of the assay results. In this work, we propose the use of a chemically synthesized substrate of a strictly defined structure to measure in a single experiment both the concentration of lysozyme as a protein and its enzymatic activity by means of the fluorescence polarization (FP) method. Chito-oligosaccharides of different chain lengths were fluorescently labeled and tested leading to the selection of the pentasaccharide as the optimal size tracer and the further optimization of the assay conditions for the accurate (detection limit 0.3 μM) and rapid (<30 min) determination of human lysozyme. The proposed protocol was applied to assay human lysozyme in tear samples and resulted in good correlation with the reference assay. The use of synthetic fluorescently labeled tracer, in contrast to natural peptidoglycan, in FP analysis allows for the development of a reproducible method for the determination of lysozyme activity.

Study on the precursor characteristics of coal energy spontaneous combustion process using infrasound wave monitoring and warning

The spontaneous combustion of coal energy has seriously threatened energy security, and there is an urgent need for monitoring and warning of coal energy. Therefore, this article innovatively proposes a method of using infrasound waves to monitor coal energy spontaneous combustion, establishes a coal spontaneous combustion(CSC) infrasound wave experimental testing system, and studies the precursor characteristics of coal energy spontaneous combustion process. The results indicate that there is a good positive correlation between the amplitude of the dominant frequency of the infrasound wave generated by CSC and temperature, with a correlation coefficient of R2 > 0.85. The energy proportion of the infrasound signal from 0 to 0.12Hz exceeds 80 %. And as the CSC stage progresses, the energy of infrasound waves in the 0.04–0.08Hz frequency band increases significantly, and the changes in infrasound signals in this frequency band have a good correlation with temperature, with a correlation coefficient above 0.8. This frequency band is the main frequency band of infrasound waves during the CSC process. The research in this article provides a theoretical basis for the application of infrasound wave monitoring and warning of coal energy spontaneous combustion, and it is of great significance to ensure the safe mining of coal energy.

Exploring the potential of drill cuttings for reservoir characterization: A case study from the Volga-Ural basin, Russia

The research objectives are to assess the possibility of using drill cutting analysis to obtain information about the mineralogical and geochemical properties of the reservoir rocks. Drill cutting samples were collected from a vertical well that penetrated the Domanik sediments (Semiluksk Formation) in one of the oil fields in the Volga-Ural petroleum province. Thin sections from drill cuttings were examined using an optical polarizing microscope (Axio Imager A2). X-ray diffraction (XRD) analyses were performed using a Brucker D2 Phaser X-ray powder diffractometer. Thermophysical properties were studied using an STA 449 F3 Jupiter instrument. The pyrolytic studies were performed using the Rock-Eval method. Visual inspection showed that the studied sediments are alternations of carbonates and siliceous-carbonate rocks. Thin section examinations revealed that the carbonates are mainly limestone (mudstone and wackestone) and are characterized by a dense texture and up to 30 % organic residues. The siliceous-carbonate rocks are dominated by siliceous mudstones and are characterized by dark colours, layered structure, and an enrichment in organic matter. XRD analyses showed that the carbonate rocks are mainly composed of calcite, dolomite, quartz, feldspar, and mica, which are minor components. The siliceous-carbonate rocks are dominated by quartz, followed by calcite, although they also contain feldspars, mica, dolomite, and pyrite as impurities. According to the simultaneous thermal analysis, the average total hydrocarbon in the carbonate and siliceous-carbonate rocks is 13.6 % (for the core samples) and 11.5 % (for the drill cutting samples). The content of heavy hydrocarbons in the rocks is higher than the content of light hydrocarbons, indicating the immature nature of organic matter. Kerogen is found sporadically in siliceous-carbonate rocks. According to the pyrolytic studies, average S1 is 4.4 mg/g and average S2 is 19.8 mg/g (for the core samples); average S1 is 2.1 mg/g and average S2 is 17.8 mg/g (for the drill cutting samples), which indicated that the studied sediments have very good to excellent generation potential. The average Tmax of 425.7 °C (for the drill cutting samples) and 427.9 °C (for the core samples) indicate immature organic matter that generated only heavy oils. Comparing the results of the analysed drill cutting samples with the results of the analysed core analysis from the same reservoir interval in the neighbouring wells showed a good correlation, which proves that this technique is a valid tool that provides an alternative, cost-effective method to determine the rock's characteristics from drill cuttings.

Immunity transfer in mule foals fed with good IgG quality colostrum

While the passive transfer of immunity in horse and donkey foals has been extensively studied, there is limited information for mule foals. Immunoglobulin type G (IgG) and serum total protein concentration (TP) were assessed at different sampling times to evaluate the correlation between serum radial immunodiffusion (SRID) with electrophoresis, refractometry, and dry chemistry analyzer (Biuret), and to estimate serum IgG concentrations using serum TP in mule foals. We analyzed a total of 30 samples collected at birth, and at 6, 12, 24, and 48 h of life from 6 mule foals by SRID, electrophoresis TP, biuret TP, and refractometry TP.The SRID IgG concentration significantly increased from birth until T6 (p < 0.001). Serum TP analyzed with refractometry revealed differences between T0 and T12, T24 and T48 (p < 0.05), while a significant difference was observed with the biuret method between T0 and all the other sampling times (p < 0.001).A strong correlation was found between IgG SRID and biuret TP (r = 0.69, p < 0.001), and a good correlation existed between IgG SRID, refractometry TP, and electrophoresis TP (r = 0.44, p < 0.01 and r = 0.39, p < 0.05, respectively).All methods can be used to estimate the passive transfer of immunity in mule foals. TP refractometry and biuret TP values can be used to determine serum IgG concentrations in the blood of mule foals on their first day of life through the application of a specific equation.

Electrochemical peptide-based biosensor for the detection of the inflammatory disease biomarker, interleukin-1beta

This paper reports the development of a highly sensitive and selective electrochemical peptide-based biosensor for the detection of the inflammatory disease biomarker, interleukin-1beta (IL-1β). To this end, flower-like Au–Ag@MoS2-rGO nanocomposites were used as the signal amplification platform to achieve a label-free biosensor with a high sensitivity and selectivity. First, a high-affinity peptide for IL-1β was identified through biopanning with M13 random peptide libraries, and was newly designed by incorporating cysteine at the C-terminus. An IL-1β specific binding peptide was used as the bio-receptor, and the interaction between the IL-1β binding peptide and IL-1β was confirmed via enzyme-linked immunosorbent assay and various physicochemical and electrochemical analyses. Under optimal conditions, the biosensor achieved an ultrasensitive and specific IL-1β detection in a wide linear concentration range of 0–250 ng/mL with a picomolar-level detection limit (∼2.4 pM), low binding constant (∼0.62 pM), and a low coefficient of variation (<1.65 %). The biosensor was successfully utilized for IL-1β determination in the serum of Crohn's disease patients with a good correlation coefficient. In addition, the detection performance was comparable to that of commercially available IL-1β ELISA kit. This indicates that the electrochemical peptide-based biosensor may offer a potentially valuable platform for the clinical diagnosis of various inflammatory disease biomarkers.

Single-cell RNA-seq mapping of chicken peripheral blood leukocytes

BackgroundSingle-cell transcriptomics provides means to study cell populations at the level of individual cells. In leukocyte biology this approach could potentially aid the identification of subpopulations and functions without the need to develop species-specific reagents. The present study aimed to evaluate single-cell RNA-seq as a tool for identification of chicken peripheral blood leukocytes. For this purpose, purified and thrombocyte depleted leukocytes from 4 clinically healthy hens were subjected to single-cell 3′ RNA-seq. Bioinformatic analysis of data comprised unsupervised clustering of the cells, and annotation of clusters based on expression profiles. Immunofluorescence phenotyping of the cell preparations used was also performed.ResultsComputational analysis identified 31 initial cell clusters and based on expression of defined marker genes 28 cluster were identified as comprising mainly B-cells, T-cells, monocytes, thrombocytes and red blood cells. Of the remaining clusters, two were putatively identified as basophils and eosinophils, and one as proliferating cells of mixed origin. In depth analysis on gene expression profiles within and between the initial cell clusters allowed further identification of cell identity and possible functions for some of them. For example, analysis of the group of monocyte clusters revealed subclusters comprising heterophils, as well as putative monocyte subtypes. Also, novel aspects of TCRγ/δ + T-cell subpopulations could be inferred such as evidence of at least two subtypes based on e.g., different expression of transcription factors MAF, SOX13 and GATA3. Moreover, a novel subpopulation of chicken peripheral B-cells with high SOX5 expression was identified. An overall good correlation between mRNA and cell surface phenotypic cell identification was shown.ConclusionsTaken together, we were able to identify and infer functional aspects of both previously well known as well as novel chicken leukocyte populations although some cell types. e.g., T-cell subtypes, proved more challenging to decipher. Although this methodology to some extent is limited by incomplete annotation of the chicken genome, it definitively has benefits in chicken immunology by expanding the options to distinguish identity and functions of immune cells also without access to species specific reagents.

Comparable analysis of six immunoassays for carcinoembryonic antigen detection

ObjectiveThis study aimed to assess the current status of carcinoembryonic antigen (CEA) detection. We evaluated the correlation, consistency, and comparability of CEA results among six automated immunoassays, and combined with the results of CEA trueness verification of the Beijing Center for Clinical Laboratories (BCCL) for further analysis. MethodsAbbott Architect i2000, Beckman DxI800, Roche Cobas E601, Diasorin Liaison XL, Maccura IS1200, and Autolumo A2000 were used to detect 40 individual serum CEA samples. Taking the optimal analytical quality specifications calculated from data on biological variation as the evaluation criterion. Passing-Bablok regression and Bland-Altman analysis were performed between each assay and all-assays median values to evaluate the correlation and relative difference. The concordance correlation coefficient (CCC) was used for consistency analysis. Additionally, the trueness verification program used samples at three concentration levels to assess the bias, coefficient of variation (CV), and total error (TE) between the average measured values and the target value. ResultsThe Spearman's rank correlation coefficient (rs) was ≥0.996 and the CCC ranged between 0.9448 and 0.9990 for each assay vs. all-assays median. Considering the all-assays median value of each sample as a reference, there were proportional and systematic differences according to the Passing-bablok regression analysis. The relative difference of the four assays (Abbott Architect i2000, Autolumo A2000, Diasorin Liaison XL, and Maccura IS1200) met the optimal analytical quality specifications. On the other hand, Beckman DxI800 (13.2 %) and Roche Cobas E601 (−9.0 %) were only able to fulfill the desirable analytical quality specifications. The average pass rates for bias, CV, and TE of the trueness verification program were 80 %, 98 %, and 96 %, respectively. ConclusionsThe six automated immunoassays vs. all-assays median have a good correlation in CEA detection. However, there is a lack of comparability of CEA results. Further improvements are needed in harmonization among CEA detections.

Establishment of an indirect competitive immunoassay for the detection of dicamba based on a highly specific nanobody

Dicamba, a traditional highly effective and low toxicity herbicide, has gained new life with the development of dicamba-tolerant transgenic crops in recent years. However, dicamba is highly volatile and therefore easy to cause drift damage to sensitive crops. The development of efficient and sensitive detection methods is essential for monitoring of trace dicamba in the environment. Nanobody-based immunoassay plays an important role in on-site detection of pesticides. However, now rapid and sensitive immunoassay methods based on nanobody for dicamba detection were lacking. In this study, the nanobodies specifically recognizing dicamba were successfully obtained by immunising camels and phage display library construction, and then an indirect competitive immunoassay based on Nb-242 was constructed with IC50 of 0.93 μg/mL and a linear range of 0.11–8.01 μg/mL. Nb-242 had good specificity with no cross-reactivities against the dicamba analogs other than 2,3,6-trichlorobenzoic acid and the developed immnoassay had a good correlation with the standard HPLC in the spike-recovery studies. Finally, the key amino acid Ala 123, Tyr 55, Tyr 59 and Arg 72 of Nb-242 that specifically recognizing and binding with dicamba were identified by homologous modeling and molecular docking, laying an important foundation for further structural modification of Nb-242. This study has important guiding significance for constructing immunoassay method of dicamba based on nanobody and provides a sensitive, specific, and reliable detection method that is suitable for the detection of dicamba in the environment.

Efficient and Accurate Analog Voltage Measurement Using a Direct Sensor-to-Digital Port Interface for Microcontrollers and Field-Programmable Gate Arrays

Portable sensor systems are usually based on microcontrollers and/or Field-Programmable Gate Arrays (FPGAs) that are interfaced with sensors by means of an Analog-to-Digital converter (ADC), either integrated in the computing device or external. An alternative solution is based on the direct connection of the sensors to the digital input port of the microcontroller or FPGA. This solution is particularly interesting in the case of devices not integrating an internal ADC or featuring a small number of ADC channels. In this paper, a technique is presented to directly interface sensors with analog voltage output to the digital input port of a microcontroller or FPGA. The proposed method requires only a few passive components and is based on the measurements of the duty cycle of a digital square-wave signal. This technique was investigated by means of circuit simulations using LTSpice and was implemented in a commercial low-cost FPGA device (Gowin GW1NR-9). The duty cycle of the square-wave signal features a good linear correlation with the analog voltage to be measured. Thus, a look-up table to map the analog voltage values to the measured duty cycle is not required with benefits in terms of memory occupation. The experimental results on the FPGA device have shown that the analog voltage can be measured with a maximum accuracy of 1.09 mV and a sampling rate of 9.75 Hz. The sampling rate can be increased to 31.35 Hz and 128.31 Hz with an accuracy of 1.61 mV and 2.68 mV, respectively.

A state-rate model for the transient wall slip effects in ply-ply friction of UD C/PAEK tapes in melt

Ply-ply slippage is one of the key deformation mechanisms occurring during hot press-forming of thermoplastic composite laminates. Advanced forming simulations, required for defect-free manufacturing, rely on accurate constitutive models for these deformation mechanisms. In this work, we propose a relative simple, yet accurate, transient model to describe the start-up friction response of UD C/PAEK tapes. The model combines a White–Metzner viscoelastic fluid with a state-rate model for the evolution of wall slip near the fiber–matrix interface, describing the disentanglement of surface polymer chains followed by the settlement of these chains in a new equilibrium state. This allows prediction of the stress growth at start-up and the transition from peak to steady-state friction, from smooth to sharp with increasing sliding rate, as well as the magnitude of the peak and steady-state friction. We obtained a good correlation between the modeled and measured friction response for different sliding rates.

On the importance of fundamental computational fluid dynamics toward a robust and reliable model of left atrial flows.

Computational fluid dynamics (CFD) studies of left atrial flows have reached a sophisticated level, for example, revealing plausible relationships between hemodynamics and stresses with atrial fibrillation. However, little focus has been on fundamental fluid modeling of LA flows. The purpose of this study was to investigate the spatiotemporal convergence, along with the differences between high- (HR) versus normal-resolution/accuracy (NR) solution strategies, respectively. Rigid wall CFD simulations were conducted on 12 patient-specific left atrial geometries obtained from computed tomography scans, utilizing a second-order accurate and space/time-centered solver. The convergence studies showed an average variability of around 30% and 55% for time averaged wall shear stress (WSS), oscillatory shear index (OSI), relative residence time (RRT), and endothelial cell activation potential (ECAP), even between intermediate spatial and temporal resolutions, in the left atrium (LA) and left atrial appendage (LAA), respectively. The comparison between HR and NR simulations showed good correlation in the LA for WSS, RRT, and ECAP ( ), but not for OSI ( ). However, there were poor correlations in the LAA especially for OSI, RRT, and ECAP ( .55, .63, and .61, respectively), except for WSS ( ). The errors are comparable to differences previously reported with disease correlations. To robustly predict atrial hemodynamics and stresses, numerical resolutions of 10 M elements (i.e., .5 mm) and 10 k time-steps per cycle seem necessary (i.e., one order of magnitude higher than normally used in both space and time). In conclusion, attention to fundamental numerical aspects is essential toward establishing a plausible, robust, and reliable model of LA flows.

Intercomparison of leaf area index observed by destructive sampling, plant canopy analyzer and tracing radiation and architecture of canopies in paddy fields

ABSTRACT Leaf area index (LAI) is a canopy structure parameter used to characterize vegetation growth. It is increasingly important to obtain continuous and accurate ground LAI measurement data for the validation of remote-sensing products. In this study, direct destructive sampling method and indirect optical measurement including LAI-2200 plant canopy analyser (PCA) and Tracing Radiation and Architecture of Canopies (TRAC) were used for long-term continuous observation of paddy fields in southern China, to explore the variation of LAI during the growth period of paddy, and to quantitatively analyse the errors of indirect optical measurement. The results show that (1) LAI and Plant area index (PAI) increased first and then decreased in the growing period. The proportion of green leaf area gradually decreased at reproductive growth stage (less than 50%). There was a linear relationship between the proportion of green leaf area and PAI at this stage, with a good correlation (R2 = 0.73). This linear relationship can be used to convert PAI into LAI more conveniently. (2) Effective PAI (PAIe) calculated by the two methods (2000 method and Lang method) from PCA showed good consistency between each other in the growing season (the maximum value of R2 is 0.99). With the increase of zenith angle, the consistency between 2000 method and Lang method decreases (R2 = 0.83). Multiple scattering has an effect on PCA measurement, and this effect is more obvious at high zenith angle. Lang method is more sensitive to the change of zenith angle. (3) Compared to the destructive values, both 2000 method and Lang method are able to compute accurate LAI using four ring sensors (4 R), while TRAC underestimates the LAI and PAI from destructive sampling method. This study provided a new idea for reducing the impact of ground reference data errors on LAI product validation.

Predictive uncertainty in deep learning-based MR image reconstruction using deep ensembles: Evaluation on the fastMRI data set.

To estimate pixel-wise predictive uncertainty for deep learning-based MR image reconstruction and to examine the impact of domain shifts and architecture robustness. Uncertainty prediction could provide a measure for robustness of deep learning (DL)-based MR image reconstruction from undersampled data. DL methods bear the risk of inducing reconstruction errors like in-painting of unrealistic structures or missing pathologies. These errors may be obscured by visual realism of DL reconstruction and thus remain undiscovered. Furthermore, most methods are task-agnostic and not well calibrated to domain shifts. We propose a strategy that estimates aleatoric (data) and epistemic (model) uncertainty, which entails training a deep ensemble (epistemic) with nonnegative log-likelihood (aleatoric) loss in addition to the conventional applied losses terms. The proposed procedure can be paired with any DL reconstruction, enabling investigations of their predictive uncertainties on a pixel level. Five different architectures were investigated on the fastMRI database. The impact on the examined uncertainty of in-distributional and out-of-distributional data with changes to undersampling pattern, imaging contrast, imaging orientation, anatomy, and pathology were explored. Predictive uncertainty could be captured and showed good correlation to normalized mean squared error. Uncertainty was primarily focused along the aliased anatomies and on hyperintense and hypointense regions. The proposed uncertainty measure was able to detect disease prevalence shifts. Distinct predictive uncertainty patterns were observed for changing network architectures. The proposed approach enables aleatoric and epistemic uncertainty prediction for DL-based MR reconstruction with an interpretable examination on a pixel level.

General and Specific Cytotoxicity of Chimeric Antisense Oligonucleotides in Bacterial Cells and Human Cell Lines.

In the last two decades, antisense oligonucleotide technology has emerged as a promising approach to tackling various healthcare issues and diseases, such as antimicrobial resistance, cancer, and neurodegenerative diseases. Despite the numerous improvements in the structure and modifications of the antisense oligonucleotides (ASOs), there are still specific problems with their clinical efficacy and preclinical cytotoxicity results. To better understand the effects of the ASOs in this paper, we conducted many MTT assays to assess the general and specific cytotoxicity of four new chimeric ASOs in bacterial cells and human cell lines. We demonstrate the absence of inhibitory activity in the human pathogenic bacteria Staphylococcus aureus by non-specific ASOs. The pVEC-ASO1 and pVEC-ASO2 are designed to have no specific targets in S. aureus. They have only partial hybridization to the guanylate kinase mRNA. The pVEC-ASO3 targets UBA2 mRNA, a hallmark cancer pathology in MYC-driven cancer, while pVEC-ASO4 has no complementary sequences. We discovered some cytotoxicity of the non-specific ASOs in healthy and cancer human cell lines. The results are compared with two other ASOs, targeting specific mRNA in cancer cells. All ASOs are delivered into the cell via the cell-penetrating oligopeptide pVEC, which is attached to them. We draw a good correlation between the thermodynamic stability of ASO/target RNA and the toxicity effect in human cell lines. The data obtained signify the importance of thorough bioinformatic analysis and high specificity in designing and developing novel ASOs for safer therapeutic agents in clinical practice.

3D Back Contour Metrics in Predicting Idiopathic Scoliosis Progression: Retrospective Cohort Analysis, Case Series Report and Proof of Concept.

Adolescent Idiopathic Scoliosis is a 3D spinal deformity commonly characterized by serial radiographs. Patients with AIS may have increased average radiation exposure compared to unaffected patients and thus may be implicated with a modest increase in cancer risk. To minimize lifetime radiation exposure, alternative imaging modalities such as surface topography are being explored. Surface topography (ST) uses a camera to map anatomic landmarks of the spine and contours of the back to create software-generated spine models. ST has previously shown good correlation to radiographic measures. In this study, we sought to use ST in the creation of a risk stratification model. A total of 38 patients met the inclusion criteria for curve progression prediction. Scoliotic curves were classified as progressing, stabilized, or improving, and a predictive model was created using the proportional odds logistic modeling. The results showed that surface topography was able to moderately appraise scoliosis curvatures when compared to radiographs. The predictive model, using demographic and surface topography measurements, was able to account for 86.9% of the variability in the future Cobb angle. Additionally, attempts at classification of curve progression, stabilization, or improvement were accurately predicted 27/38 times, 71%. These results provide a basis for the creation of a clinical tool in the tracking and prediction of scoliosis progression in order to reduce the number of X-rays required.

Validation of an Ion-Pair Reverse Phase High-Performance Liquid Chromatography Method for the Detection of Major Components and Related Substances in Diquafosol Sodium Eye Drops.

A simple, feasible, isocratic elution, and stable reversed-phase high performance liquid chromatography method was established and verified. The chromatographic conditions are as follows: EF-C18H, 4.6 × 250 mm, 5 μm column; column temperature 30 °C; for the mobile phase 27.2 g of KH2PO4 and 8.5 g of tetrabutylammonium hydrogen sulfate were taken, 2500 mL of water was added to dissolve, and the pH was adjusted to 6.7 with phosphoric acid:methanol solution with a ratio of 84:16 (V:V). The flow rate was 1.0 mL/min; the injection volume was 10 μL; and the wavelength was 262 nm. According to the current ICH guidelines, the developed method was verified, and the system suitability, specificity, LOD, LOQ, linearity, range, accuracy, repeatability, durability, and solution stability of the proposed method were verified. The validation results demonstrated that the LOQ for the method was 0.05% and the LOD was 0.02%. The content was detected within the concentration range of 300 to 900 μg/mL. The relationship between concentration and measurement was linear, with an r2 of >0.999. The concentration of impurities ranged from 0.3 to 4.5 μg/mL. A good linear correlation was observed within the range of g/mL, with a coefficient of determination r2 greater than 0.999. The accuracy and repeatability met the specified criteria.

Rapid Assessment of Extractability of Macronutrients from Yerba Mate (Illex paraguariensis) Leaves Based on Laser-Induced Breakdown Spectroscopy

Leaves of yerba mate plant (Ilex paraguariensis) have a wealth of nutrients, ingested by people who drink them in the hot water infusion popularly known as mate. In the present work, the laser-induced breakdown spectroscopy (LIBS) technique was applied for the first time to analysis of the extractability of macronutrients, including Mg, Ca, Na, and K, in commercial samples of yerba mate. Powdered samples from leaves’ material were used to simulate the infusion process in the laboratory. To carry out LIBS analysis, the emission spectra were measured before and after the infusion from the samples prepared in pellets. The spectral data were processed and analyzed by a specially designed algorithm. A coefficient of extractability was calculated for each of the investigated macronutrients in the range 34–76%, showing a good correlation with the corresponding elemental concentrations leached into the water infusion, determined by Atomic Absorption Spectroscopy. The obtained results demonstrated the feasibility of our approach for the rapid analysis of extractable macronutrients present in yerba mate leaves.

Application of a new MDCKII-MDR1 cell model to measure the extent of drug distribution in vitro at equilibrium for prediction of in vivo unbound brain-to-plasma drug distribution

Intro: Reliable estimates of drug uptake from blood to brain parenchyma are crucial in CNS drug discovery and development. While in vivo Kp,uu,brain estimates are the gold standard for investigating brain drug disposition, animal usage is a limitation to high throughput application. This study investigates an in vitro model using P-gp expressing MDCKII-MDR1 cells for predicting in vivo brain drug penetration. Methods: In vitro equilibrium distribution studies were conducted in apical and basolateral solutions with high protein content to estimate Kp,brain and Kp,uu,brain values. The correlation between in vitro and in vivo Kp,brain values for a set of compounds was examined. Results: We observed a good correlation between in vitro and in vivo Kp,brain values (R2 = 0.69, Slope: 1.6), indicating that the in vitro model could predict in vivo drug brain penetration. The ‘unilateral (Uni-L)’ in vitro setup correctly classified 5 out of 5 unrestricted compounds and 3 out of 5 restricted compounds. Possible reasons for the observed disparities for some compounds have been discussed, such as difference in transport areas between in vitro and in vivo settings and effect of pH changes. Conclusion: The in vitro assay setup developed in this study holds promise for predicting in vivo drug brain penetration in CNS drug discovery. The correlation between in vitro and in vivo Kp,brain values, underscores that the model may have potential for early-stage screening. With minor refinements, this in vitro approach could reduce the reliance on in vivo experiments, accelerating the pace of CNS drug discovery and promoting a more ethical research approach.