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influence on the velocity of tissue formation and tissue composition. The spheroids show properties that make them interesting candidates for cellular cartilage regeneration approaches in trauma and OA therapy.Unambiguous quantum state discrimination is a strategy where the conclusive result can always be trusted. This strategy is very important, since it can be used for various quantum information protocols, including quantum key distribution. However, in the view of quantumness, it is not clear what is going on in performing unambiguous quantum state discrimination. To answer the question, we investigate coherence distribution when unambiguous discrimination is performed by generalized measurement. Specially, we study coherence distribution in three cases, which consist of unambiguous quantum state discrimination, sequential quantum state discrimination, and assisted optimal discrimination, which are considered to be a family of unambiguous quantum state discrimination. In this investigation, we show that the structure of generalized measurements performing various types of unambiguous quantum state discrimination can be understood in terms of coherence distribution. Our result is not limited to the discrimination of two pure quantum states, but it is extended to the discrimination of two mixed states.Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) is a key glycolytic enzyme, which is crucial for the breakdown of glucose to provide cellular energy. Over the past decade, GAPDH has been reported to be one of the most prominent cellular targets of post-translational modifications (PTMs), which divert GAPDH toward different non-glycolytic functions. Hence, it is termed a moonlighting protein. During metabolic and oxidative stress, GAPDH is a target of different oxidative PTMs (oxPTM), e.g., sulfenylation, S-thiolation, nitrosylation, and sulfhydration. These modifications alter the enzyme's conformation, subcellular localization, and regulatory interactions with downstream partners, which impact its glycolytic and non-glycolytic functions. In this review, we discuss the redox regulation of GAPDH by different redox writers, which introduce the oxPTM code on GAPDH to instruct a redox response; the GAPDH readers, which decipher the oxPTM code through regulatory interactions and coordinate cellular response via the formation of multi-enzyme signaling complexes; and the redox erasers, which are the reducing systems that regenerate the GAPDH catalytic activity. Human pathologies associated with the oxidation-induced dysregulation of GAPDH are also discussed, featuring the importance of the redox regulation of GAPDH in neurodegeneration and metabolic disorders.Brain magnetic resonance imaging (MRI) is useful for predicting the outcome of patients with acute ischemic stroke (AIS). Although deep learning (DL) using brain MRI with certain image biomarkers has shown satisfactory results in predicting poor outcomes, no study has assessed the usefulness of natural language processing (NLP)-based machine learning (ML) algorithms using brain MRI free-text reports of AIS patients. Therefore, we aimed to assess whether NLP-based ML algorithms using brain MRI text reports could predict poor outcomes in AIS patients. This study included only English text reports of brain MRIs examined during admission of AIS patients. Poor outcome was defined as a modified Rankin Scale score of 3-6, and the data were captured by trained nurses and physicians. We only included MRI text report of the first MRI scan during the admission. learn more The text dataset was randomly divided into a training and test dataset with a 73 ratio. Text was vectorized to word, sentence, and document levels. In the word lti-CNN algorithm demonstrated the best classification performance (0.805), followed by the CNN (0.799) algorithm. When predicting future clinical outcomes using NLP-based ML of radiology free-text reports of brain MRI, DL algorithms showed superior performance over the other ML algorithms. In particular, the prediction of poor outcomes in document-level NLP DL was improved more by multi-CNN and CNN than by recurrent neural network-based algorithms. NLP-based DL algorithms can be used as an important digital marker for unstructured electronic health record data DL prediction.In this study, a high-density polyethylene (HDPE)-based carbon fiber-reinforced thermoplastic (CFRTP) was irradiated by an electron-beam. To assess the absorbed dose rate influence on its mechanical properties, the beam energy and absorbed dose were fixed, while the absorbed dose rates were varied. The tensile strength (TS) and Young's modulus (YM) were evaluated. The irradiated CFRTP TS increased at absorbed dose rates of up to 6.8 kGy/s and decreased at higher rates. YM showed no meaningful differences. For CFRTPs constituents, the carbon fiber (CF) TS gradually increased, while the HDPE TS decreased slightly as the absorbed dose rates increased. The OH intermolecular bond was strongly developed in irradiated CFRTP at low absorbed dose rates and gradually declined when increasing those rates. X-ray photoelectron spectroscopy analysis revealed that the oxygen content of irradiated CFRTPs decreased with increasing absorbed dose rate due to the shorter irradiation time at higher dose rates. In conclusion, from the TS viewpoint, opposite effects occurred when increasing the absorbed dose rate a favorable increase in CF TS and adverse decline of attractive hydrogen bonding interactions between HDPE and CF for CFRTPs TS. Therefore, the irradiated CFRTP TS was maximized at an optimum absorbed dose rate of 6.8 kGy/s.Whole-school physical activity (PA) promotion programmes are recommended to increase youth PA. Evaluation of programmes is essential to ensure practice is guided by evidence. This paper evaluates the Active School Flag (ASF), a whole-school PA promotion programme in Ireland, using the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. ASF was evaluated across three levels-(1) administration, (2) application, (3) outcomes-using a mi✗ed-methods case study design. E✗isting data sources were reviewed, the programme coordinator was interviewed, and a pilot study was conducted to investigate impact on 3rd and 5th class students (3 schools, n = 126 students, age range 8-12 years). In-school Moderate to Vigorous Physical Activity (MVPA; by accelerometery), motivation for PA (BREQ), PA self-efficacy (PASES), school affect and peer social support (Kidscreen27) were measured pre-programme (0 months), post-programme (8 months), and at retention (12 months). Teacher perceptions of classroom behaviour (CBAST) were also measured pre- and post-programme.