Simple Method of 9,10-Anthraquinone Assay in Eleutherine americana (Aubl.) Merr. ex K. Heyne using High-Performance Liquid Chromatography

Eleutherine americana (E. americana) is a medicinal plant commonly found on the island of Borneo, Indonesia. This plant is known to have several biological activities. However, anthraquinone residues are generally present as contaminants. This study was aimed to develop a method of determining the levels of 9,10-anthraquinone in plant extracts and fractions using High Performance Liquid Chromatography (HPLC). The research aims to optimize the mobile phase, the system suitability test, and the system validation. The optimal mobile phase was acetonitrile:distilled water 1:1 v/v with a flow rate of 1.25 mL/min. The validation result shows that the linearity was obtained with a correlation coefficient (r) of 0.9995 and an r2 coefficient of 0.9991. The estimated limits for detection and quantification values were 0.178 and 0.594 µg/mL, respectively. In the intraday and inter-day accuracy test, the coefficient of variance for reference was 0.627 and 0.774, while the results for the sample were 2.966 and 2.658. The percentage recovery rate for reference was between 98.976–101.452%, and for the sample, the result was 89.191–94.667%. The average 9,10-anthraquinone content in the acetate fraction of E. americana plant was 9.799 µg/g ± 5.243.

Commercial PV Inverter IEEE 1547.1 Ride-Through Assessments Using an Automated PHIL Test Platform

As more countries seek solutions to their de-carbonization targets using renewable energy (RE) technologies, interconnection standards and national grid codes for distributed energy resources (DER) are being updated to support higher penetrations of RE and improve grid stability. Common grid-code revisions mandate DER devices, such as solar inverters and energy storage systems, ride-through (RT) voltage and frequency disturbances. This is necessary because as the percentage of generation from DER increases, there is a greater risk power system faults will cause many or all DER to trip, triggering a substantial load-generation imbalance and possible cascading blackout. This paper demonstrates for the first time a methodology to verify commercial DER devices are compliant to new voltage, frequency, and rate of change of frequency (ROCOF) RT requirements established in IEEE Std. 1547-2018. The methodology incorporates a software automation tool, called the SunSpec System Validation Platform (SVP), in combination with a hardware-in-the-loop (HIL) system to execute the IEEE Std. 1547.1-2020 RT test protocols. In this paper, the approach is validated with two commercial photovoltaic inverters, the test results are analyzed for compliance, and improvements to the test procedure are suggested.

Glioblastoma Surgery Imaging–Reporting and Data System: Validation and Performance of the Automated Segmentation Task

For patients with presumed glioblastoma, essential tumor characteristics are determined from preoperative MR images to optimize the treatment strategy. This procedure is time-consuming and subjective, if performed by crude eyeballing or manually. The standardized GSI-RADS aims to provide neurosurgeons with automatic tumor segmentations to extract tumor features rapidly and objectively. In this study, we improved automatic tumor segmentation and compared the agreement with manual raters, describe the technical details of the different components of GSI-RADS, and determined their speed. Two recent neural network architectures were considered for the segmentation task: nnU-Net and AGU-Net. Two preprocessing schemes were introduced to investigate the tradeoff between performance and processing speed. A summarized description of the tumor feature extraction and standardized reporting process is included. The trained architectures for automatic segmentation and the code for computing the standardized report are distributed as open-source and as open-access software. Validation studies were performed on a dataset of 1594 gadolinium-enhanced T1-weighted MRI volumes from 13 hospitals and 293 T1-weighted MRI volumes from the BraTS challenge. The glioblastoma tumor core segmentation reached a Dice score slightly below 90%, a patientwise F1-score close to 99%, and a 95th percentile Hausdorff distance slightly below 4.0 mm on average with either architecture and the heavy preprocessing scheme. A patient MRI volume can be segmented in less than one minute, and a standardized report can be generated in up to five minutes. The proposed GSI-RADS software showed robust performance on a large collection of MRI volumes from various hospitals and generated results within a reasonable runtime.

A Novel Tool for Gait Analysis: Validation Study of the Smart Insole PODOSmart®

The new smart insole PODOSmart®, is introduced as a new tool for gait analysis against high cost laboratory based equipment. PODOSmart® system measures walking profile and gait variables in real life conditions. PODOSmart® insoles consists of wireless sensors, can be fitted into any shoe and offer the ability to measure spatial, temporal, and kinematic gait parameters. The intelligent insoles feature several sensors that detect and capture foot movements and a microprocessor that calculates gait related biomechanical data. Gait analysis results are presented in PODOSmart® platform. This study aims to present the characteristics of this tool and to validate it comparing with a stereophotogrammetry-based system. Validation was performed by gait analysis for eleven healthy individuals on a six-meters walkway using both PODOSmart® and Vicon system. Intraclass correlation coefficients (ICC) were calculated for gait parameters. ICC for the validation ranged from 0.313 to 0.990 in gait parameters. The highest ICC was observed in cadence, circumduction, walking speed, stride length and stride duration. PODOSmart® is a valid tool for gait analysis compared to the gold standard Vicon. As PODOSmart®, is a portable gait analysis tool with an affordable cost it can be a useful novel tool for gait analysis in healthy and pathological population.

Implementation of Good Computer System Validation Practices In Pharmaceutical Industry- A Review

Computer Systems Validation is a method used to ensure information is generated by a computer-based system that satisfies a set of specified requirements. Compliance with computerized systems is becoming increasingly relevant in the pharmaceutical industry as computer system validations have many benefits, such as enhancing quality control, reducing other validation costs and time, improving compliance with GMP 21 CFR Part 11 Regulation which affects the quality, health, identification or effectiveness of products subject to the GMP Regulations. Both the European Medicines Agency of Europe along with the Food & Drug Administration of the USA has developed CSV practice guidelines. An overview of relevant documents which fulfil the computer system validation along with its best practices implemented is presented below. Official requirements and standards of the USA, Europe, and Switzerland are taken as the main focus. The taken basic GMP guidelines' like Gamp, AVP and PDA implies the same principles and theories. They explain majorly about what to do view point of validation, whereas GAMP describes how to do validation. We strive to define the computer device validation needs of equipment conducted from a pharmaceutical industry perspective. The categorization of a computer system into various frameworks or categories gives the flexible approach for the validation of complex as well as simple computerized systems. The present review article discusses the implementation and various good practices of the pharmaceutical industry to maintain computer system validation. Implementing various good computer system validation activities reduces the re-work and always maintains the quality standards as per the user requirements; as a result of which the future trends will notice merging of various new implemented terminology and techniques as a common practice in mixed sectors.