Electrocatalytic Synthesis of Essential Amino Acids from Nitric Oxide Using Atomically Dispersed Fe on N-doped Carbon.

How to transfer industrial exhaust gases of nitrogen oxides into high-values product is significantly important and challenging. Herein, we demonstrate an innovative method for artificial synthesis of essential α-amino acids from nitric oxide (NO) by reacting with α-keto acids through electrocatalytic process with atomically dispersed Fe supported on N-doped carbon matrix (AD-Fe/NC) as the catalyst. A yield of valine with 32.1 µmol mgcat -1 is delivered at -0.6 V vs. reversible hydrogen electrode, corresponding a selectivity of 11.3 %. In situ X-ray absorption fine structure and synchrotron radiation infrared spectroscopy analyses show that NO as nitrogen source converted to hydroxylamine that promptly nucleophilic attacked on the electrophilic carbon center of α-keto acid to form oxime and subsequent reductive hydrogenation occurred on the way to amino acid. Over 6 kinds of α-amino acids have been successfully synthesized and gaseous nitrogen source can be also replaced by liquid nitrogen source (NO3 - ). Our findings not only provide a creative method for converting nitrogen oxides into high-valued products, which is of epoch-making significance towards artificial synthesis of amino acids, but also benefit in deploying near-zero-emission technologies for global environmental and economic development.

Clinical Study of Virtual Reality Augmented Technology Combined with Contrast-Enhanced Ultrasound in the Assessment of Thyroid Cancer.

Thyroid cancer has become the most common malignant tumor in the endocrine system, and its global incidence has been showing an upward trend. The diagnosis methods of thyroid cancer include ultrasound, fine-needle aspiration cytology, and neck CT, but the single ultrasound feature cannot simultaneously take into account the sensitivity and specificity of more than 85% when diagnosing thyroid cancer. The development of virtual technology can significantly improve the diagnosis of the thyroid gland. Based on this, this article proposes a clinical study of virtual reality technology combined with contrast-enhanced ultrasound in the assessment of thyroid cancer. This article uses a variety of methods, such as literature method, mathematical statistics, and experimental research, in-depth study of the theoretical cornerstones of virtual reality augmented technology, the application status of ultrasound contrast technology, and so on. And a fuzzy mean clustering algorithm was proposed to identify ultrasound images. Then, a clinical experiment of virtual reality augmented technology combined with contrast-enhanced ultrasound was designed to evaluate thyroid cancer, which included comparison of contrast-enhanced ultrasound signs, analysis of enhancement results, multifactor logistic analysis, and diagnostic efficacy analysis of ultrasound signs. The combined application of virtual reality augmented technology and contrast-enhanced ultrasound in the study of thyroid cancer has a sensitivity and specificity exceeding 85% as the diagnosis boundary changes, and the accuracy of the combined diagnosis is relatively high.

Systematic Analysis of Metabolic Pathway Distributions of Bacterial Energy Reserves.

Previous bioinformatics studies have linked gain or loss of energy reserves with host-pathogen interactions and bacterial virulence based on a comparatively small number of bacterial genomes or proteomes. Thus, understanding the theoretical distribution patterns of energy reserves across bacterial species could provide a shortcut route to look into bacterial lifestyle and physiology. So far, five major energy reserves have been identified in bacteria due to their capacity to support bacterial persistence under nutrient deprivation conditions. These include polyphosphate (polyP), glycogen, wax ester (WE), triacylglycerol (TAG), and polyhydroxyalkanoates (PHAs). Although the enzymes related with metabolism of energy reserves are well understood, there is a lack of systematic investigations into the distribution of bacterial energy reserves from an evolutionary point of view. In this study, we sourced 8282 manually reviewed bacterial reference proteomes and combined a set of hidden Markov sequence models (HMMs) to search homologs of key enzymes related with the metabolism of energy reserves. Our results revealed that specific pathways like trehalose-related glycogen metabolism and enzymes such as wax ester synthase/acyl-CoA:diacylglycerol acyltransferase (WS/DGAT) are mainly restricted within specific types of bacterial groups, which provides evolutionary insights into the understanding of their origins and functions. In addition, the study also confirms that loss of energy reserves like polyP metabolism absence in Mollicutes is correlated with bacterial genome reduction. Through this analysis, a clearer picture about the metabolism of energy reserves in bacteria is presented, which could serve as a guide for further theoretical and experimental analyses of bacterial energy metabolism.

Assessing the social determinants of health care costs for Medicaid-enrolled adolescents in Washington State using administrative data.

OBJECTIVE: The study used administrative data to identify the social determinants that have the greatest impact on Medicaid expenditures in adolescence. DATA SOURCES: Data were compiled using the Washington State Department of Social and Health Services Integrated Client Databases, which link data from state systems including Medicaid claims and social services receipt. STUDY DESIGN: Medical system and behavioral health service costs of over 180 000 Medicaid-enrolled adolescents aged 12-17 were measured using integrated administrative data from Washington State. Social determinants of health, including child maltreatment and parent risk factors, were also measured. Two-stage regression models were used to identify factors associated with increased health care utilization and costs. PRINCIPAL FINDINGS: Regression models revealed that the factors most predictive of higher health care costs were child abuse, child neglect, and instability in out-of-home placements related to foster care. Other social determinants of health, such as parent risk factors, were not associated with health care costs. Child maltreatment and placement instability impacted health care costs primarily through large increases in behavioral health utilization and costs. CONCLUSIONS: Prevention and early interventions for children and families to decrease child maltreatment and increase foster care placement stability could reduce overall health care costs.

Predicting Homelessness among Emerging Adults Aging Out of Foster Care.

This study examines risk and protective factors associated with experiencing homelessness in the year after "aging out" of foster care. Using a state-level integrated administrative database, we identified 1,202 emerging adults in Washington State who exited foster care between July 2010 and June 2012. Initial bivariate analyses were conducted to assess the association between candidate predictive factors and an indicator of homelessness in a 12-month follow-up period. After deploying a stepwise regression process, the final logistic regression model included 15 predictive factors. Youth who were parents, who had recently experienced housing instability, or who were African American had approximately twice the odds of experiencing homelessness in the year after exiting foster care. In addition, youth who had experienced disrupted adoptions, had multiple foster care placements (especially in congregate care settings), or had been involved with the juvenile justice system were more likely to become homeless. In contrast, youth were less likely to experience homelessness if they had ever been placed with a relative while in foster care or had a high cumulative grade point average relative to their peers.