OBJECTIVE: To establish the reference standard of the median nerve conduction study (NCS) in Korea.
METHODS: A total of 648 median motor and 602 median sensory NCSs from 349 Korean healthy volunteers were tested and analyzed prospectively. Equipment calibration, assessment of intraand inter-rater reliability, and the NCSs per se were conducted according to a predetermined protocol. A reference standard was established from uncertainty components for the following parameters: the onset and peak latencies; the baseline-to-peak and peak-to-peak amplitudes; the area and duration of the negative wave; and the nerve conduction velocity. The effects of sex, age and stimulation intensity were analyzed.
RESULTS: Each measured value of 648 median motor and 602 median sensory nerves were obtained and presented with both mean and expanded uncertainties, as well as mean and standard deviations. The cut-off values with expanded uncertainty were determined for different age and sex groups. After adjusting for anthropometric covariates, all parameters except duration were affected by age, and sex appeared to influence both duration and area. While stimulation intensity significantly affected some parameters including latencies, the effect sizes were negligible.
CONCLUSIONS: We propose the median NCS reference standard using the largest Korean dataset ever available. The use of the traceable and reliable reference standard is anticipated to promote more accurate and dependable diagnosis and appropriate management of median neuropathies in Korea.

Mass spectrometry (MS) is a widely used analytical technique including medical diagnostics, forensic toxicology, food and water analysis. The gold standard for quantifying compounds involves using stable isotope-labeled internal standards (SIL-IS). However, when these standards are not commercially available, are prohibitively expensive, or are extremely difficult to synthesize, alternative external quantification techniques are employed. We hereby present a novel, convenient and cheap quantification approach-quantification via post column infusion (PCI). As a proof of concept, we demonstrated PCI quantification for the immunosuppressant tacrolimus in whole blood using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The validation results met the criteria according to the guideline on bioanalytical method validation of the European Medicine Agency (EMA), achieving imprecisions and inaccuracies with coefficient of variation and relative bias below 15%. Anonymized and leftover whole blood samples from immunosuppressed patients receiving tacrolimus were used for method comparison (PCI quantification vs. conventional internal standard (IS) quantification). Both methods showed strong agreement with a Pearson correlation coefficient of r = 0.9532. This novel PCI quantification technique (using the target analyte itself) expands the quantification options available in MS, providing reliable results, particularly when internal standards are unavailable or unaffordable. With the current paper, we aim to demonstrate that our innovative PCI technique has great potential to overcome practical issues in quantification and to provide guidance on how to incorporate PCI in existing or new LC-MS methods. Moreover, this study demonstrated a more convenient method for correcting matrix effects in comparison to alternative PCI techniques.

Tendons are one of the major load-bearing tissues in the body; subjected to enormous peak stresses, and thus vulnerable to injury. Cellular responses to tendon injury are complex, involving inflammatory and repair components, with the latter employing both resident and recruited exogenous cell populations. Gene expression analyses are valuable tools for investigating tendon injury, allowing assessment of repair processes and pathological responses such as fibrosis, and permitting evaluation of therapeutic pharmacological interventions. Quantitative polymerase chain reaction (qPCR) is a commonly used approach for such studies, but data obtained by this method must be normalised to reference genes: genes known to be stably expressed between the experimental conditions investigated. Establishing suitable tendon injury reference genes is thus essential. Accordingly we investigated mRNA expression stability in a rat model of tendon injury, comparing both injured and uninjured tendons, and the effects of rapamycin treatment, at 1 and 3 weeks post injury. We used 11 candidate genes (18S, ACTB, AP3D1, B2M, CSNK2A2, GAPDH, HPRT1, PAK1IP1, RPL13a, SDHA, UBC) and assessed stability via four complementary algorithms (Bestkeeper, deltaCt, geNorm, Normfinder). Our results suggests that ACTB, CSNK2A2, HPRT1 and PAK1IP1 are all stably expressed in tendon, regardless of injury or drug treatment: any three of these would serve as universally suitable reference gene panel for normalizing qPCR expression data in the rat tendon injury model. We also reveal 18S, UBC, GAPDH, and SDHA as consistently poor scoring candidates (with the latter two exhibiting rapamycin- and injury-associated changes, respectively): these genes should be avoided.

Radiomics features (RFs) serve as quantitative metrics to characterize shape, density/intensity, and texture patterns in radiological images. Despite their promise, RFs exhibit reproducibility challenges across acquisition settings, thus limiting implementation into clinical practice. In this investigation, we evaluate the effects of different CT scanners and CT acquisition protocols (KV, mA, field-of-view, and reconstruction kernel settings) on RFs extracted from lumbar vertebrae of a cadaveric trunk. Employing univariate and multivariate Generalized Linear Models (GLM), we evaluated the impact of each acquisition parameter on RFs. Our findings indicate that variations in mA had negligible effects on RFs, while alterations in kV resulted in exponential changes in several RFs, notably First Order (94.4%), GLCM (87.5%), and NGTDM (100%). Moreover, we demonstrated that a tailored GLM model was superior to the ComBat algorithm in harmonizing CT images. GLM achieved R2 > 0.90 in 21 RFs (19.6%), contrasting ComBat\'s mean R2 above 0.90 in only 1 RF (0.9%). This pioneering study unveils the effects of CT acquisition parameters on bone RFs in cadaveric specimens, highlighting significant variations across parameters and scanner datasets. The proposed GLM model presents a robust solution for mitigating these differences, potentially advancing harmonization efforts in Radiomics-based studies across diverse CT protocols and vendors.

In emergency situations, ensuring standardized cardiopulmonary resuscitation (CPR) actions is crucial. However, current automated external defibrillators (AEDs) lack methods to determine whether CPR actions are performed correctly, leading to inconsistent CPR quality. To address this issue, we introduce a novel method called deep-learning-based CPR action standardization (DLCAS). This method involves three parts. First, it detects correct posture using OpenPose to recognize skeletal points. Second, it identifies a marker wristband with our CPR-Detection algorithm and measures compression depth, count, and frequency using a depth algorithm. Finally, we optimize the algorithm for edge devices to enhance real-time processing speed. Extensive experiments on our custom dataset have shown that the CPR-Detection algorithm achieves a mAP0.5 of 97.04%, while reducing parameters to 0.20 M and FLOPs to 132.15 K. In a complete CPR operation procedure, the depth measurement solution achieves an accuracy of 90% with a margin of error less than 1 cm, while the count and frequency measurements achieve 98% accuracy with a margin of error less than two counts. Our method meets the real-time requirements in medical scenarios, and the processing speed on edge devices has increased from 8 fps to 25 fps.

The liver plays a vital role in lipid synthesis and metabolism in poultry. To study the functional genes more effectively, it is essential to screen of reliable reference genes in the chicken liver, including females, males, embryos, as well as the Leghorn Male Hepatoma (LMH) cell line. Traditional reference gene screening involves selecting commonly used housekeeping genes (HKGs) for RT-qPCR experiments and using different algorithms to identify the most stable ones. However, this approach is limited in selecting the best reference gene from a small pool of HKGs. High-throughput sequencing technology may offer a solution to this limitation. This study aimed to identify the most consistently expressed genes by utilizing multiple published RNA-seq data of chicken liver and LMH cells. Subsequently, the stability of the newly identified reference genes was assessed in comparison to previously validated stable poultry liver expressed reference genes and the commonly employed HKGs using RT-qPCR. The findings indicated that there is a higher degree of similarity in stable expression genes between female and male liver (such as LSM14A and CDC40). In embryonic liver, the optimal new reference genes were SUDS3, TRIM33, and ERAL1. For LMH cells, the optimal new reference genes were ALDH9A1, UGGT1, and C21H1orf174. However, it is noteworthy that most HKGs did not exhibit stable expression across multiple samples, indicating potential instability under diverse conditions. Furthermore, RT-qPCR experiments proved that the stable expression genes identified from RNA-seq data outperformed commonly used HKGs and certain validated reference genes specific to poultry liver. Over all, this study successfully identified new stable reference genes in chicken liver and LMH cells using RNA-seq data, offering researchers a wider range of reference gene options for RT-qPCR in diverse situations.

Choosing appropriate reference genes or internal controls to normalize RT-qPCR data is mandatory for the interexperimental reproducibility of gene expression data obtained by RT-qPCR in most studies, including those on endometriosis. Particularly for miRNAs, the choice for reference genes is challenging because of their physicochemical and biological characteristics. Moreover, the retrograde menstruation theory, mesenchymal stem cells in menstrual blood (MenSCs), and changes in post-transcriptional regulatory processes through miRNAs have gained prominence in the scientific community as important players in endometriosis. Therefore, we originally explored the stability of 10 miRNAs expressions as internal control candidates in conditions involving the two-dimensional culture of MenSCs from healthy women and patients with endometriosis. Here, we applied multiple algorithms (geNorm, NormFinder, Bestkeeper, and delta Ct) to screen reference genes and assessed the comprehensive stability classification of miRNAs using RefFinder. Pairwise variation calculated using geNorm identified three miRNAs as a sufficient number of reference genes for accurate normalization. MiR-191-5p, miR-24-3p, and miR-103a-3p were the best combination for suitable gene expression normalization. This study will benefit similar research, but is also attractive for regenerative medicine and clinics that use MenSCs, miRNA expression, and RT-qPCR.

In vivo studies offer a detailed understanding of organism functioning, surpassing the insights provided by in vitro studies. These experiments are crucial for comprehending disease emergence, progression, and associated mechanisms in humans, as well as for developing treatments. When choosing experimental models, factors such as genomic similarity, physiological relevance, ethical appropriateness, and economic feasibility must be considered. Standardized protocols enhance the reliability, and reproducibility of scientific methods, promoting the assessment of research in the scientific literature. Researchers conducting embryo studies should establish and document standardized protocols for increased data comparability. Standardization is vital for scientific validity, reproducibility, and comparability in both in vivo and in vitro studies, ensuring the accuracy and reliability of experimental results and advancing scientific knowledge.

Accurate measurement of serum glycocholic acid (GCA) is crucial for evaluating the activity of chronic hepatitis. Moreover, GCA is a novel identified biomarker for hepatocellular carcinoma. Although some laboratories have used the liquid chromatography-tandem mass spectrometry (LC-MS/MS) method to measure GCA in recent years, the problem of potential interference of GCA analogues has not been solved well yet. Neither reference measurement procedures nor reference materials for GCA have been listed in the Joint Committee for Traceability in Laboratory Medicine (JCTLM) database. For standardization of GCA, it is urgent to establish a candidate measurement procedure for GCA. In this study, a candidate reference measurement procedure for the quantification of GCA in human serum based on isotope dilution liquid chromatography-tandem mass spectrometry (ID-LC-MS/MS) by a two-step sample pretreatment of protein precipitation and MAX solid-phase extraction was developed and validated. GCA can be completely separated from its structural analogues with gradient elution in 9 min compared with short time gradients published in previous literature by Huang\'s group. Method validation indicated perfect quantitation precision with intra-day and inter-day values that were ≤1.30% and ≤1.80%, respectively. The method showed excellent linearity with high regression coefficients (R2 > 0.999) over a range of 0.92 ng/g-38.38 μg/g and perfect recoveries at three spiked levels (99.87-100.43%). No interference, matrix effect, and carryover were observed. Moreover, the cRMP was successfully applied to measure GCA in serum samples and compared with two immunoassays in a clinical laboratory. As a candidate reference method, this method can promote a GCA standardization program.

Translating RNA-seq into clinical diagnostics requires ensuring the reliability and cross-laboratory consistency of detecting clinically relevant subtle differential expressions, such as those between different disease subtypes or stages. As part of the Quartet project, we present an RNA-seq benchmarking study across 45 laboratories using the Quartet and MAQC reference samples spiked with ERCC controls. Based on multiple types of \'ground truth\', we systematically assess the real-world RNA-seq performance and investigate the influencing factors involved in 26 experimental processes and 140 bioinformatics pipelines. Here we show greater inter-laboratory variations in detecting subtle differential expressions among the Quartet samples. Experimental factors including mRNA enrichment and strandedness, and each bioinformatics step, emerge as primary sources of variations in gene expression. We underscore the profound influence of experimental execution, and provide best practice recommendations for experimental designs, strategies for filtering low-expression genes, and the optimal gene annotation and analysis pipelines. In summary, this study lays the foundation for developing and quality control of RNA-seq for clinical diagnostic purposes.