Schneiderlohse1951

Inspired by the active site structure of natural horseradish peroxidase having iron as a pivotal element with coordinated histidine residues, we have developed histidine coated magnetic nanoparticles (His@MNPs) with relatively uniform and small sizes (less than 10 nm) through one-pot heat treatment. In comparison to pristine MNPs and other amino acid coated MNPs, His@MNPs exhibited a considerably enhanced peroxidase-imitating activity, approaching 10-fold higher in catalytic reactions. With the high activity, His@MNPs then were exploited to detect the important neurotransmitter acetylcholine. By coupling choline oxidase and acetylcholine esterase with His@MNPs as peroxidase mimics, target choline and acetylcholine were successfully detected via fluorescent mode with high specificity and sensitivity with the limits of detection down to 200 and 100 nM, respectively. The diagnostic capability of the method is demonstrated by analyzing acetylcholine in human blood serum. This study thus demonstrates the potential of utilizing His@MNPs as peroxidase-mimicking nanozymes for detecting important biological and clinical targets with high sensitivity and reliability.Linear nevus sebaceous syndrome (LNSS) is a rare neurocutaneous disorder. It is characterized by the presence of nevus sebaceous, ocular anomalies, neurological deficits, and convulsion. Renal involvement was not commonly reported. We report a 10-year-old girl with LNSS who had concomitant cystic kidney disease and diffuse aortopathy with bilateral renal artery stenosis, leading to hypertension requiring oral anti-hypertensive medications. The girl presented with chorioretinal coloboma and multiple nevus sebaceous at birth. She had aortic coarctation and received surgical repair at one week of life. She had persistent hypertension during her follow-up. Further investigations were performed to look for causes of hypertension apart from possible re-coarctation. Her magnetic resonance angiogram revealed diffuse aortopathy, which extended from the aortic arch to the abdominal aorta. Branches of the aorta, including the celiac trunk, superior mesenteric arteries, and renal arteries, were also narrowed. Multiple renal cysts were also identified in her right kidney. Interventional angioplasty over the renal arteries was not feasible due to diffuse narrowing of the aorta, especially at the origins of renal arteries. The blood pressure was controlled with oral anti-hypertensive medications. Our case illustrated that pediatricians should be aware of the possible renal involvements in LNSS, which impose a significant impact on the management and long-term prognosis of these patients.Genomic variants that cause neurodevelopmental/psychiatric disorders (NPD) are relatively prevalent and highly penetrant. This study aimed to understand adults' immediate responses to receiving NPD-related results to inform inclusion in population-based genomic screening programs. Nine recurrent, pathogenic copy number variants (CNVs) were identified from research exome data, clinically confirmed, and disclosed to adult participants of the Geisinger MyCode Community Health Initiative DiscovEHR cohort by experienced genetic counselors. check details A subset of in-person genetic counseling sessions (n = 27) were audio-recorded, transcribed, and coded using a grounded theory approach. Participant reactions were overwhelmingly positive and indicated that an NPD genetic etiology was highly valuable and personally useful. Participants frequently reported learning disabilities or other NPD that were not documented in their electronic health records and noted difficulties obtaining support for NPD needs. Most intended to share their genetic result with family members and health care providers and were interested in how their result could improve their healthcare. This study indicates that results from population-based NPD genomic screening can provide personal value for adults with NPD, were viewed positively by participants, and could improve clinical outcomes by informing symptom monitoring for NPD and co-morbidities, promoting improved health behaviors, and enhancing psychotherapeutic approaches.(1) Background Public servants are regarded as guardians of the public interest, and their pandemic response played a vital role in controlling the spread of the epidemic. However, there is limited knowledge of the factors that influence public servants' response (PSR) when facing pandemic prevention and control tasks. (2) Methods Based on the theory of planned behavior (TPB), models were constructed and a regression method was employed with Chinese civil servant data to investigate how PSR is influenced by public service motivation (PSM), accountability pressure (AP), and emergency response capacity (ERC). (3) Results and discussion PSM, AP, and ERC all have a positive effect on PSR, with AP having the greatest influence, followed by PSM and ERC. The effects of PSM, AP, and ERC on PSR have group heterogeneity, which had little effect on civil servants with very low levels of PSR and the greatest impact on civil servants with medium-level PSR. Job categories of civil servants also are a factor related to PSR; PSM and AP have the strongest effects on civil servants in professional technology, and ERC has the greatest influence on administrative law enforcement. Moreover, gender, administrative level, and leadership positions also have an impact on PSR. (4) Conclusions Based on the factors of PSR, we found at least three important aspects that governments need to consider in encouraging PSR when facing a pandemic.The economic and personal consequences that a car accident generates for society have been increasing in recent years. One of the causes that can generate a car accident is the stress level the driver has; consequently, the detection of stress events is a highly desirable task. In this article, the efficacy that statistical time features (STFs), such as root mean square, mean, variance, and standard deviation, among others, can reach in detecting stress events using electromyographical signals in drivers is investigated, since they can measure subtle changes that a signal can have. The obtained results show that the variance and standard deviation coupled with a support vector machine classifier with a cubic kernel are effective for detecting stress events where an AUC of 0.97 is reached. In this sense, since SVM has different kernels that can be trained, they are used to find out which one has the best efficacy using the STFs as feature inputs and a training strategy; thus, information about model explain ability can be determined.