Validity Of Method Research Articles

Comparison of genomic prediction methods for early growth traits of Inner Mongolia cashmere goats based on multi trait models.

Inner Mongolia cashmere goat is an excellent livestock breed formed through long-term natural selection and artificial breeding, and is currently a world-class dual-purpose breed producing cashmere and meat. Multi trait animal model is considered to significantly improve the accuracy of genetic evaluation in livestock and poultry, enabling indirect selection between traits. In this study, the pedigree, genotype, environment, and phenotypic records of early growth traits of Inner Mongolia cashmere goats were used to build multi trait animal model., Then three methods including ABLUP, GBLUP, and ssGBLUP wereused to estimate the genetic parameters and genomic breeding values of early growth traits (birth weight, weaning weight, average daily weight gain before weaning, and yearling weight). The accuracy and reliability of genomic estimated breeding value are further evaluated using the five fold cross validation method. The results showed that the heritability of birth weight estimated by three methods was 0.13-0.15, the heritability of weaning weight was 0.13-0.20, heritability of daily weight gain before weaning was 0.11-0.14, and the heritability of yearling weight was 0.09-0.14, all of which belonged to moderate to low heritability. There is a strong positive genetic correlation between weaning weight and daily weight gain before weaning, daily weight gain before weaning and yearling weight, with correlation coefficients of 0.77-0.79 and 0.56-0.67, respectively. The same pattern was found in phenotype correlation among traits. The accuracy of the estimated breeding values by ABLUP, GBLUP, and ssGBLUP methods for birth weight is 0.5047, 0.6694, and 0.7156, respectively; the weaning weight is 0.6207, 0.6456, and 0.7254, respectively; the daily weight gain before weaning was 0.6110, 0.6855, and 0.7357 respectively; and the yearling weight was 0.6209, 0.7155, and 0.7756, respectively. In summary, the early growth traits of Inner Mongolia cashmere goats belong to moderate to low heritability, and the speed of genetic improvement is relatively slow. The genetic improvement of other growth traits can be achieved through the selection of weaning weight. The ssGBLUP method has the highest accuracy and reliability in estimating genomic breeding value of early growth traits in Inner Mongolia cashmere goats, and is significantly higher than that from ABLUP method, indicating that it is the best method for genomic breeding of early growth weight in Inner Mongolia cashmere goats.

Preparation and characterization of AChE immobilized magnetic bio-nanocomposites (Fe3O4@Cht/Au) for pesticide detection.

Free enzymes cause difficulties in many applications due to their insufficient stability, loss of activity in a short time, and most importantly, although they are costly, they are used only once in reactions, lose their effect and cannot be recovered from the environment. Magnetic nanoparticles coated with biocompatible polymeric material are potential candidates for promising enzyme carriers due to their multifunctional pore surfaces, easy removal from the environment provided by the magnetization, ability to main stability under various harsh conditions. This study prepared a biosensor candidate based on the inhibiting acetylcholinesterase enzyme by organophosphate pesticides from chitosan-coated magnetic nanoparticles doped with gold. Transmission electron microscopy, scanning electron microscopy, X-ray diffraction diffractometry, and Fourier transform infrared spectroscopy analysis confirmed the structure of synthesized nanocomposites. Magnetic characteristics of the nanocomposites were assessed using VSM. Bio-nanocomposite (Fe3O4@Cht/Au/AChE) was used to determine environmental pollutants qualitatively. Remediation of organophosphate-containing wastewater is an essential issue for environmental sustainability. In this work, Dichlorvos and Chlorpyrifos were selected as organic pollutants to assess the enzymatic activity of immobilized Fe3O4@Cht/Au/AChE. Optimum conditions for AChE enzyme were immobilized nanostructures (Fe3O4@Cht/Au/AChE) were determined. The optimum pH for the immobilized enzyme was found to be 8, and the optimum temperature was found to be 60 °C. Retained immobilized enzyme activity is found to be around 50% for the 20th reuse. In the presence of 150 µL pesticide, retained immobilized enzyme activity is found to be around 25%. Method validation was performed for pesticides. When using immobilized AChE, the LOD (limit of detection)-LOQ (limit of quantitation) values for Dichlorovos and Chlorpyrifos was obtained in the range of 0.0087-0.029 nM and 0.0014-0.0046 nM, respectively. The relative standard deviation (RSD%) values, which are indicators of precision, were found to be below 2%.

Validation of a next generation sequencing method for adventitious virus detection: Demonstration of sensitivity in multiple cell lines.

In the past few years NGS has become the technology of choice to replace animal-based virus safety methods and this has been strengthened by the recent revision to the ICHQ5A virus safety chapter. Here we describe the validation of an NGS method using an agnostic analysis to detect and identify RNA virus and actively replicating DNA virus contaminants in cell banks. We report the results of the validation of each step in the sequencing process that established quality criteria to ensure consistent sequencing data. Furthermore, the validation of the analysis algorithm designed to identify virus specific sequences is described along with steps undertaken to ensure the integrity of the sequencing data from generation to analysis. Lastly, the validated sequencing and analysis systems were used to establish a limit of detection (LOD) for model viruses in cells that are commonly used in biomanufacturing. The LOD from these studies ranged from 1E+03 to 1E+04 genome copies and were dependent on the virus type with little variability between the different cell types. Thus, the validation of the NGS method for adventitious agent testing and the establishment of a general LOD for cell-based samples provides a suitable alternative to traditional virus detection methods.

Optimization of ultrasound-assisted extraction using box-Behnken design, method validation, and analysis of phytochemicals from drying treatments in the application of Etlingera elatior inflorescence

Optimization of ultrasound-assisted extraction using box-Behnken design, method validation, and analysis of phytochemicals from drying treatments in the application of Etlingera elatior inflorescence

Nitrofurans in natural waters: optimisation and validation of SPE-based method using UHPLC-HRMS techniques

Nitrofurans in natural waters: optimisation and validation of SPE-based method using UHPLC-HRMS techniques

Direct embryonic biopsy with transcervical embryoscopy is an effective method for karyotyping and morphology assessment in miscarriages.

The main purpose of this study is to compare the validity of transcervical embryoscopy method with standard uterine evacuation method in detecting more accurate karyotypes in miscarriages below tenth week of pregnancy. Additionally, the frequency and distribution of fetal morphological abnormality were evaluated. A prospective study was carried out at the Gazi University Faculty of Medicine, Department of Obstetrics and Gynecology. Patients with missed abortions between sixth and tenth gestational weeks were included in the study group, and fetal morphological examination and direct embryonic biopsy were performed by transcervical embryoscopy. The control group consisted of patients who experienced miscarriage and genetic material obtained from routine uterine evacuation between February and October 2023. A total of 60 patients in the study group and 189 patients in the control group were evaluated. The median ages, previous miscarriage numbers, median gravida numbers, and median gestational weeks were comparable between groups. Chromosomal abnormality was detected in 24 (42.8%) and 52 embryos (29.9%) in the study and control groups, respectively (p = 0.004). Culture failure rates were 6.6% (n = 4) and 7.9% (n = 15) in the study and control groups, respectively. In the study group, 12 embryos had a morphological abnormality in which 6 of them had normal karyotype. Direct embryonic biopsy with transcervical embryoscopy is an effective method to exclude maternal decidual cell contamination and placental mosaicism in miscarriages for karyotype analysis. In addition, detecting anomalies in morphology might contribute our understanding in the process of miscarriages which arises independent from structural/numerical chromosomal abnormalities.

Associations of coping and health-related behaviors with medical students' well-being and performance during objective structured clinical examination.

Objective structured clinical examination (OSCE) is a valid method to evaluate medical students' competencies. The present cross-sectional study aimed at determining how students' coping and health-related behaviors are associated with their psychological well-being and performance on the day of the OSCE. Fourth-year medical students answered a set of standardized questionnaires assessing their coping (BCI) and health-related behaviors before the examination (sleep PSQI, physical activity GPAQ). Immediately before the OSCE, they reported their level of instant psychological well-being on multi-dimensional visual analogue scales. OSCE performance was assessed by examiners blinded to the study. Associations were explored using multivariable linear regression models. A total of 482 students were included. Instant psychological well-being was positively associated with the level of positive thinking and of physical activity. It was negatively associated with the level of avoidance and of sleep disturbance. Furthermore, performance was negatively associated with the level of avoidance. Positive thinking, good sleep quality, and higher level of physical activity were all associated with improved well-being before the OSCE. Conversely, avoidance coping behaviors seem to be detrimental to both well-being and OSCE performance. The recommendation is to pay special attention to students who engage in avoidance and to consider implementing stress management programs.Clinical trial: The study protocol was registered on clinicaltrial.gov NCT05393206, date of registration: 11 June 2022.

ERIC recommendations for TP53 mutation analysis in chronic lymphocytic leukemia-2024 update.

In chronic lymphocytic leukemia (CLL), analysis of TP53 aberrations (deletion and/or mutation) is a crucial part of treatment decision-making algorithms. Technological and treatment advances have resulted in the need for an update of the last recommendations for TP53 analysis in CLL, published by ERIC, the European Research Initiative on CLL, in 2018. Based on the current knowledge of the relevance of low-burden TP53-mutated clones, a specific variant allele frequency (VAF) cut-off for reporting TP53 mutations is no longer recommended, but instead, the need for thorough method validation by the reporting laboratory is emphasized. The result of TP53 analyses should always be interpreted within the context of available laboratory and clinical information, treatment indication, and therapeutic options. Methodological aspects of introducing next-generation sequencing (NGS) in routine practice are discussed with a focus on reliable detection of low-burden clones. Furthermore, potential interpretation challenges are presented, and a simplified algorithm for the classification of TP53 variants in CLL is provided, representing a consensus based on previously published guidelines. Finally, the reporting requirements are highlighted, including a template for clinical reports of TP53 aberrations. These recommendations are intended to assist diagnosticians in the correct assessment of TP53 mutation status, but also physicians in the appropriate understanding of the lab reports, thus decreasing the risk of misinterpretation and incorrect management of patients in routine practice whilst also leading to improved stratification of patients with CLL in clinical trials.

A Comprehensive Review on Advantages of Ultra Performance Liquid Chromatography (UPLC) for Analytical Method Development, Validation, and Stability Studies

A Comprehensive Review on Advantages of Ultra Performance Liquid Chromatography (UPLC) for Analytical Method Development, Validation, and Stability Studies

Validation of satellite-derived solar irradiance datasets: a case study in Saudi Arabia

A robust dataset of Surface Solar Irradiance is essential for secure competitive financing for solar energy projects. Rating agencies and lenders alike require verification of the solar-resource dataset for utilizing each solar energy project, as this can be translated directly into expected electrical energy and revenues. The accuracy of the dataset and the variability of solar radiation, as recorded by historical solar data, play a significant role in estimating the future performance of the project and its budget. The historical observed solar irradiance datasets by local stations are the best and most reliable for a specific site, but they are not always available for long and continuous periods in any location, especially in arid areas. So, the importance of historical solar radiation datasets derived from satellite-based models arises here. This paper validates the historical modeled datasets of the three most famous satellite-based commercial prediction models (SolarGIS, SUNY, and Solcast) against the observed dataset by six ground stations in Saudi Arabia under different climatic zones. The validation method has been implemented using the standard error metrics: Maximum Absolute Error (MAE) and relative Maximum Bias Error (rMBE). The validation process showed that, in the case of GHI, the discrepancy between observed and predicted values is narrow, while in the case of DNI, the discrepancy is wide. Also, the predicted GHI values are more accurate than predicted DNI values, and -in general- the values predicted by the SUNY model are less accurate than those predicted by SolarGIS and Solcast models for both GHI and DNI. The resultant of this validation process could be accepted not for the six locations under study only but, also for deserts and arid areas across Saudi Arabia and might be extended to similar arid areas around the world.

Development and Validation of 1H Nuclear Magnetic Resonance Quantitative Method for Efavirenz API Quality Control

Development and Validation of 1H Nuclear Magnetic Resonance Quantitative Method for Efavirenz API Quality Control

Fluorescence-Based Calibration Model for In-Situ Measurement of Micro-scaled Lubricant Thickness Distribution at Indentation Interface

This study proposes a model for the measurement of microscale liquid film thickness distribution using fluorescence signals. The interfacial conditions between the tool and the workpiece in mechanical machining are important for understanding these phenomena and mechanisms. In this study, indentation tests with transparent tools were used to observe interfaces; however, it was challenging to obtain the signal from a thin fluorescent liquid film on smooth and steeply inclined surfaces. Therefore, fluorescence-based measurement, such as laser-induced fluorescence, was employed. To measure the absolute thickness of the thin fluorescent film, calibration of the measurement system is necessary. Therefore, a theoretical model was proposed considering the multiple reflections of excitation light and fluorescence at the inclined surface between the indenter and workpiece. By measuring the profile of the surface topography of the indented workpiece and comparing the results with those measured by a surface profiler, the validity of the proposed calibration method and the performance of this measurement system were demonstrated. The measured surface profiles, including scratches of 2–4 µm, were in good agreement, demonstrating the validity of the proposed method.

Data Science Methods for Real-World Evidence Generation in Real-World Data.

In the healthcare landscape, data science (DS) methods have emerged as indispensable tools to harness real-world data (RWD) from various data sources such as electronic health records, claim and registry data, and data gathered from digital health technologies. Real-world evidence (RWE) generated from RWD empowers researchers, clinicians, and policymakers with a more comprehensive understanding of real-world patient outcomes. Nevertheless, persistent challenges in RWD (e.g., messiness, voluminousness, heterogeneity, multimodality) and a growing awareness of the need for trustworthy and reliable RWE demand innovative, robust, and valid DS methods for analyzing RWD. In this article, I review some common current DS methods for extracting RWE and valuable insights from complex and diverse RWD. This article encompasses the entire RWE-generation pipeline, from study design with RWD to data preprocessing, exploratory analysis, methods for analyzing RWD, and trustworthiness and reliability guarantees, along with data ethics considerations and open-source tools. This review, tailored for an audience that may not be experts in DS, aspires to offer a systematic review of DS methods and assists readers in selecting suitable DS methods and enhancing the process of RWE generation for addressing their specific challenges.

Discrimination Between Human and Animal Blood Using Raman Spectroscopy and a Self-Reference Algorithm for Forensic Purposes: Method Expansion and Validation

Determining whether the origin of a bloodstain is human or non-human is important during a forensic investigation. In their pioneering work, Bian et al. introduced a self-reference peak algorithm for the analysis of the Raman spectra of bloodstains and demonstrated the great potential of this approach for differentiating between human and non-human blood. However, this work only used three non-human species in the creation of their original model. The current study expands the capability of a self-referencing algorithm to discriminate between human and 18 non-human species based on the Raman spectra of blood samples. The intensity ratios between the bands at 1003 and 1341 cm−1 of the samples’ Raman spectra were compared between species to determine whether a threshold existed that separates human samples from those of non-humans. The self-referencing algorithm was capable of correctly categorizing spectra averaged from donors of all 18 non-human species. The use of this algorithm is simple and requires little training or knowledge of statistics, which makes it accessible for forensic applications, compared to computationally difficult analysis methods. This technique using Raman spectroscopy is rapid, nondestructive, and highly accurate making it a promising tool for forensic applications.

COF-SiO2@Fe3O4 Composite for Magnetic Solid-Phase Extraction of Pyrethroid Pesticides in Vegetables

Pyrethroid pesticides (PYRs) have found widespread application in agriculture for the protection of fruit and vegetable crops. Nonetheless, excessive usage or improper application may allow the residues to exceed the safe limits and pose a threat to consumer safety. Thus, there is an urgent need to develop efficient technologies for the elimination or trace detection of PYRs from vegetables. Here, a simple and efficient magnetic solid-phase extraction (MSPE) strategy was developed for the simultaneous purification and enrichment of five PYRs in vegetables, employing the magnetic covalent organic framework nanomaterial COF-SiO2@Fe3O4 as an adsorbent. COF-SiO2@Fe3O4 was prepared by a straightforward solvothermal method, using Fe3O4 as a magnetic core and benzidine and 3,3,5,5-tetraaldehyde biphenyl as the two building units. COF-SiO2@Fe3O4 could effectively capture the targeted PYRs by virtue of its abundant π-electron system and hydroxyl groups. The impact of various experimental parameters on the extraction efficiency was investigated to optimize the MSPE conditions, including the adsorbent amount, extraction time, elution solvent type and elution time. Subsequently, method validation was conducted under the optimal conditions in conjunction with gas chromatography–mass spectrometry (GC-MS). Within the range of 5.00–100 μg·kg−1 (1.00–100 μg·kg−1 for bifenthrin and 2.5–100 μg·kg−1 for fenpropathrin), the five PYRs exhibited a strong linear relationship, with determination coefficients ranging from 0.9990 to 0.9997. The limits of detection (LODs) were 0.3–1.5 μg·kg−1, and the limits of quantification (LOQs) were 0.9–4.5 μg·kg−1. The recoveries were 80.2–116.7% with relative standard deviations (RSDs) below 7.0%. Finally, COF-SiO2@Fe3O4, NH2-SiO2@Fe3O4 and Fe3O4 were compared as MSPE adsorbents for PYRs. The results indicated that COF-SiO2@Fe3O4 was an efficient and rapid selective adsorbent for PYRs. This method holds promise for the determination of PYRs in real samples.

Development and validation of clinical implementation methods for patient-reported outcomes in Japanese multi-center palliative care units

BackgroundPatient-Reported Outcomes (PROs) are recommended for use in clinical oncology. However, they are not routinely used in professional palliative care practices in Japan. The reasons include both patient and healthcare provider factors and the implementation of PROs. This study aimed to develop and validate clinical implementation methods for PROs in Japanese palliative care units.MethodsThe Consolidated Framework for Implementation Research (CFIR) was conducted with four palliative care units in Japan. The study was conducted in six steps: unit assessment, development and implementation of a PRO implementation plan, PRO post-implementation survey and analysis of its utilization, a review of the PRO implementation process, creation of a PRO implementation method in a palliative care unit, and use and verification of the implementation method. Steps 1–5 were the development phase, and step 6 was the verification phase.ResultsInterviews were conducted with healthcare providers prior to PRO implementation. Intervention characteristics, patient needs in the palliative care unit, and factors related to the organization were identified as barriers. The implementation plan was developed, and the core members were selected. The implementation procedures were created in the above mentioned steps. PROs were used in the palliative care units. The same was true in the validation phase.ConclusionsThis study guided PROs in specialized palliative care unit in a clinical setting. The method was developed and validated for the implementation of PROs in the palliative care unit. In the PRO implementation process, it was important to assess the unit, address the barriers to implementation, and reduce the burden on healthcare providers. Furthermore, healthcare providers had to be supported by the champion, a person responsible for the implementation of PROs in the palliative care unit.

Effect of light-induced changes in leaf anatomy on intercellular and cellular components of mesophyll resistance for CO2 in Fagus sylvatica.

Mesophyll resistance for CO2 diffusion (rm) is one of the main limitations for photosynthesis and plant growth. Breeding new varieties with lower rm requires knowledge of its distinct components. We tested new method for estimating the relative drawdowns of CO2 concentration (c) across hypostomatous leaves of Fagus sylvatica. This technique yields values of the ratio of the internal CO2 concentrations at the adaxial and abaxial leaf side, cd/cb, the drawdown in the intercellular air space (IAS), and intracellular drawdown between IAS and chloroplast stroma, cc/cbd. The method is based on carbon isotope composition of leaf dry matter and epicuticular wax isolated from upper and lower leaf sides. We investigated leaves from tree-canopy profile to analyse the effects of light and leaf anatomy on the drawdowns and partitioning of rm into its inter- (rIAS) and intracellular (rliq) components. Validity of the new method was tested by independent measurements of rm using conventional isotopic and gas exchange techniques. 73% of investigated leaves had adaxial epicuticular wax enriched in 13C compared to abaxial wax (by 0.50‰ on average), yielding 0.98 and 0.70 for average of cd/cb and cc/cbd, respectively. The rIAS to rliq proportion were 5.5:94.5% in sun-exposed and 14.8:85.2% in shaded leaves. cc dropped to less than half of the atmospheric value in the sunlit and to about two-thirds of it in shaded leaves. This method shows that rIAS is minor but not negligible part of rm and reflects leaf anatomy traits, i.e. leaf mass per area and thickness.

Non-Contact Blood Pressure Estimation from Radar Signals by a Stacked Deformable Convolution Network.

This study introduces a contactless blood pressure monitoring approach that combines conventional radar signal processing with novel deep learning architectures. During the preprocessing phase, datasets suitable for synchronization are created by integrating Kalman filtering, multiscale bandpass filters, and a periodic extraction method in the time domain. These data comprise data on chest micro variations, encapsulating a complex array of physiological and biomedical information reflective of cardiac micromotions. The Radar-based Stacked Deformable convolution Network (RSD-Net) integrates channel and spatial self attention mechanisms within a deformable convolutional framework to enhance feature extraction from radar signals. The network architecture systematically employs deformable convolutions for initial deep feature extraction from individual signals. Subsequently, continuous blood pressure estimation is conducted using self attention mechanisms on feature map from single source coupled with multi-feature map channel attention. The performance of model is corroborated via the open-source dataset procured using a non-invasive 24GHz six-port continuous wave radar system. The dataset, encompassing readings from 30 healthy individuals subjected to diverse conditions including rest, the Valsalva maneuver, apnea, and tilt-table examinations. It serves to substantiate the validity and resilience of the proposed method in the non-contact assessment of continuous blood pressure. Evaluation metrics reveal Pearson correlation coefficients of 0.838 for systolic and 0.797 for diastolic blood pressure predictions. The Mean Error (ME) and Standard Deviation (SD) for systolic and diastolic blood pressure measurements are -0.32 ±6.14mmHg and -0.20 ±5.50mmHg, respectively. The ablation study assesses the contribution of different structural components of the RSD-Net, validating their significance in the overall of model performance.

Development and Validation of a RP-HPLC Method for the Simultaneous Determination of Silver Sulfadiazine and Sodium Hyaluronate in the Presence of Methyl and Propyl Paraben in a Pharmaceutical Cream for Burns.

A direct and precise isocratic RP-HPLC method for simultaneous determination of silver sulfadiazine (SSD) and sodium hyaluronate (SH) in the presence of methyl (MP) and propyl parabens (PP) was developed and validated. Agilent chromatograph with X-Select C18 column (250 × 4.6mm2, 5μm) was used. Chromatographic separation was achieved using a mobile phase consisting of acetonitrile and 0.05M phosphate buffer (pH5.0 to which added triethyl amine 0.5ml/L), at a ratio 35: 65v/v. Elution was used at flow rate of 1.0mL/min at ambient temperature with UV detection at 205nm. The retention times for SH, SSD, MP and PP were 1.49, 3.3, 6.7 and 19.5min, respectively. The presented chromatographic method was fully validated in accordance with ICH requirements, it was valid over linearity ranges of (0.80-100.00μg/mL) and (3.20-100.00μg/mL) for SSD and SH, respectively. Acceptable precision and accuracy were obtained for concentrations over the standard curve ranges and the sensitivity of the method, as the limits of detection and quantification for each active ingredient was also determined. The validated method was successfully applied for the quantification of SSD and SH in pharmaceutical cream formulation and the mean recovery %±SD were 100.93 ± 0.985 and 100.05 ± 0.668 for SSD and SH; respectively, indicating satisfactory accuracy of the method.

Measurement Guidance in Diffusion Models: Insight from Medical Image Synthesis.

In the field of healthcare, the acquisition of sample is usually restricted by multiple considerations, including cost, labor- intensive annotation, privacy concerns, and radiation hazards, therefore, synthesizing images-of-interest is an important tool to data augmentation. Diffusion models have recently attained state-of-the-art results in various synthesis tasks, and embedding energy functions has been proved that can effectively guide the pre-trained model to synthesize target samples. However, we notice that current method development and validation are still limited to improving indicators, such as Fréchet Inception Distance score (FID) and Inception Score (IS), and have not provided deeper investigations on downstream tasks, like disease grading and diagnosis. Moreover, existing classifier guidance which can be regarded as a special case of energy function can only has a singular effect on altering the distribution of the synthetic dataset. This may contribute to in-distribution synthetic sample that has limited help to downstream model optimization. All these limitations remind that we still have a long way to go to achieve controllable generation. In this work, we first conducted an analysis on previous guidance as well as its contributions on further applications from the perspective of data distribution. To synthesize samples which can help downstream applications, we then introduce uncertainty guidance in each sampling step and design an uncertainty-guided diffusion models. Extensive experiments on four medical datasets, with ten classic networks trained on the augmented sample sets provided a comprehensive evaluation on the practical contributions of our methodology. Furthermore, we provide a theoretical guarantee for general gradient guidance in diffusion models, which would benefit future research on investigating other forms of measurement guidance for specific generative tasks. Codes and models are available at: https://github.com/yangqy1110/MGDM.