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Hydrogen refueling stations play a pivotal role in advancing hydrogen fuel cell vehicles. Ensuring the accuracy and reliability of these stations is crucial for their safe and efficient operation. This study proposes a hybrid metrology evaluation system for the comprehensive cross-validation of hydrogen refueling stations. The system combines experimental measurements with computational models to thoroughly assess the stations' performance. The main objectives of this study are to evaluate the precision, accuracy, and reliability of hydrogen refueling stations and to identify potential uncertainties or sources of error in measurements. Six refueling experiments were conducted, varying the refueling pressure from 476 bar to 735 bar and the refueling rate from 0.601486 kg/min to 0.702694 kg/min. The maximum refueling capacity was determined to be approximately 6.3 kg, based on the specifications of the NEXO vehicle.Throughout the experiments, data on critical parameters such as pressure, weight, and flow rate were collected. These data were meticulously analyzed and compared with expected values derived from computational models. The results convincingly demonstrate that the hybrid metrology evaluation system offers a robust and precise evaluation of hydrogen refueling stations. The system adeptly identifies discrepancies between experimental measurements and computational models, facilitating the correction of potential measurement errors.This study contributes significantly to the enhancement of metrological cross-validation techniques for hydrogen refueling stations, ensuring their precision and dependability. The study findings can inform the development of standardized metrological protocols and guidelines for the certification and calibration of hydrogen refueling stations. By establishing accurate and dependable metrological validation methods, the adoption of hydrogen fuel cell vehicles can be expedited, promoting a sustainable and environmentally friendly transportation system.

Background/Aims: The prevalence of Helicobacter pylori-naive status is increasing. Nonetheless, biennial gastroscopy is recommended for all Koreans aged 40 to 75 years. This study aimed to determine whether gastric cancer screening guidelines could be changed according to H. pylori infection status and year of birth. Methods: Koreans who underwent serum assays and gastroscopy for gastric cancer screening between 2010 and 2016 were included if screening tests were followed up for ≥3 times. H. pylori infection was confirmed when invasive tests or 13C-urea breath tests were positive. In the case of negative test findings, eradication history, serologically detected atrophy, and intestinal metaplasia/atrophy were checked for past infection. If all were absent, H. pylori-naive status was confirmed. Results: Two-thousand and two (256 H. pylori-naive, 743 past-infected, and 1,003 infected) Koreans underwent screening tests for 95.5±28.4 months. The mean year of birth in the naive group (1969±7) differed from those of the past-infected (1957±10, p

Influenza A virus causes numerous deaths and infections worldwide annually. Therefore, we have considered nanobodies as a potential treatment for patients with severe cases of influenza. We developed a nanobody that was expected to have protective efficacy against the A/California/04/2009 (CA/04; pandemic 2009 flu strain) and evaluated its therapeutic efficacy against CA/04 in mice experiments. This nanobody was derived from the immunization of the alpaca, and the inactivated CA/04 virus was used as an immunogen. We successfully generated a nanobody library through bio-panning, phage ELISA, and Bio-layer interferometry. Moreover, we confirmed that administering nanobodies after lethal doses of CA/04 reduced viral replication in the lungs and influenza-induced clinical signs in mice. These research findings will help to develop nanobodies as viral therapeutics for CA/04 and other infectious viruses.

Abstract Plasma metabolomics profiling is an emerging methodology to identify metabolic pathways underlying cardiovascular health (CVH). The objective of this study was to define metabolomic profiles underlying CVH in a cohort of Black adults, a population that is understudied but suffers from disparate levels of CVD risk factors. The Morehouse-Emory Cardiovascular (MECA) Center for Health Equity study cohort consisted of 375 Black adults (age 53 ± 10, 39% male) without known CVD. CVH was determined by the AHA Life’s Simple 7 (LS7) score, calculated from measured blood pressure, body mass index (BMI), fasting blood glucose and total cholesterol, and self-reported physical activity, diet, and smoking. Plasma metabolites were assessed using untargeted high-resolution metabolomics profiling. A metabolome wide association study (MWAS) identified metabolites associated with LS7 score after adjusting for age and sex. Using Mummichog software, metabolic pathways that were significantly enriched in metabolites associated with LS7 score were identified. Metabolites representative of these pathways were compared across clinical domains of LS7 score and then developed into a metabolomics risk score for prediction of CVH. We identified novel metabolomic signatures and pathways associated with CVH in a cohort of Black adults without known CVD. Representative and highly prevalent metabolites from these pathways included glutamine, glutamate, urate, tyrosine and alanine, the concentrations of which varied with BMI, fasting glucose, and blood pressure levels. When assessed in conjunction, these metabolites were independent predictors of CVH. One SD increase in the novel metabolomics risk score was associated with a 0.88 higher LS7 score, which translates to a 10.4% lower incident CVD risk. We identified novel metabolomic signatures of ideal CVH in a cohort of Black Americans, showing that a core group of metabolites central to nitrogen balance, bioenergetics, gluconeogenesis, and nucleotide synthesis were associated with CVH in this population.

Abstract Peritoneal metastases (PM) in colorectal cancer (CRC) is associated with a dismal prognosis. Identifying and exploiting new biomarkers, signatures, and molecular targets for personalised interventions in the treatment of PM in CRC is imperative. We conducted transcriptomic profiling using RNA-seq data generated from the primary tissues of 19 CRC patients with PM. Using our dataset established in a previous study, we identified 1422 differentially expressed genes compared to non-metastatic CRC. The profiling demonstrated no differential expression in liver and lung metastatic CRC. We selected 12 genes based on stringent criteria and evaluated their expression patterns in a validation cohort of 32 PM patients and 84 without PM using real-time reverse transcription-polymerase chain reaction. We selected cartilage intermediate layer protein 2 (CILP2) because of high mRNA expression in PM patients in our validation cohort and its association with a poor prognosis in The Cancer Genome Atlas. Kaplan–Meier survival analysis in our validation cohort demonstrated that CRC patients with high CILP2 expression had significantly poor survival outcomes. Knockdown of CILP2 significantly reduced the proliferation, colony-forming ability, invasiveness, and migratory capacity and downregulated the expression of molecules related to epithelial-mesenchymal transition in HCT116 cells. In an in vivo peritoneal dissemination mouse knockdown of CILP2 also inhibited CRC growth. Therefore, CILP2 is a promising biomarker for the prediction and treatment of PM in CRC.

In this paper, a nonlinear simulation block for a fish robot was designed using MATLAB Simulink. The simulation block incorporated added masses, hydrodynamic damping forces, restoring forces, and forces and moments due to dorsal fins, pectoral fins, and caudal fins into six-degree-of-freedom equations of motion. To obtain a linearized model, we used three different nominal surge velocities (i.e., 0.2 m/s, 0.4 m/s, and 0.6 m/s). After obtaining output responses by applying pseudo-random binary signal inputs to a nonlinear model, an identification tool was used to obtain approximated linear models between inputs and outputs. Utilizing the obtained linearized models, two-degree-of-freedom proportional, integral, and derivative controllers were designed, and their characteristics were analyzed. For the 0.4 m/s nominal surge velocity models, the gain margins and phase margins of the surge, pitch, and yaw controllers were infinity and 69 degrees, 26.3 dB and 85 degrees, and infinity and 69 degrees, respectively. The bandwidths of surge, pitch, and yaw control loops were determined to be 2.3 rad/s, 0.17 rad/s, and 2.0 rad/s, respectively. Similar characteristics were observed when controllers designed for linear models were applied to the nonlinear model. When step inputs were applied to the nonlinear model, the maximum overshoot and steady-state errors were very small. It was also found that the nonlinear plant with three different nominal surge velocities could be controlled by a single controller designed for a linear model with a nominal surge velocity of 0.4 m/s. Therefore, controllers designed using linear approximation models are expected to work well with an actual nonlinear model.