Degradation kinetic study of lysine in lysine hydrochloride solutions for injection by determining its main degradation product

AbstractA limited number of researches have been reported to apply the Arrhenius equation to study the relationship between drugs and its degradation products so far. In the present work, the thermal degradation kinetics of lysine hydrochloride solutions for injection, the special solvent for ademetionine 1, 4-butanedisulfonate (SAM) for injection, was investigated at selected temperatures and pH values. The main degradation product of lysine was separated, purified, and confirmed as lysine lactam. A reversed-phase high performance liquid chromatographic (RP-HPLC) method without derivation was developed for the simultaneous determination of lysine and lysine lactam. The results confirmed that both the lysine degradation and lysine lactam generation followed zero-order reaction kinetics. The degradation and generation rate constants increased with increasing temperatures and decreasing pH values. The temperature-dependent degradation and generation reaction could be sufficiently modeled on the Arrhenius equation with the activation energy of 80.14 and 83.22 kJ/mol, respectively. Meanwhile, a linear relationship existed between the amount of lysine degradation and lysine lactam generation since the approximate activation energy. Considering there could be other side effects, we established an upper limit of lysine lactam (500 μg/ml), as the acceptable criteria for stability to estimate the shelf life together with lysine, which made the prediction more accurate and credible. Extrapolation data demonstrated that the lysine hydrochloride solutions for injection could be stable for two years stored at room temperature

Exopolysaccharide dispelled by calcium hydroxide with volatile vehicles related to bactericidal effect for root canal medication

Objective: Enterococcus faecalis is the dominant microbial species responsible for persistent apical periodontitis with ability to deeply penetrate into the dentin. Exopolysaccharides (EPS) contribute to the pathogenicity and antibiotic resistance of E. faecalis. Our aim was to investigate the antimicrobial activity of calcium hydroxide (CH), camphorated parachlorophenol (CMCP), and chlorhexidine (CHX) against E. faecalis in dentinal tubules. Material and Methods: Decoronated single-canal human teeth and semicylindrical dentin blocks were incubated with E. faecalis for 3 weeks. Samples were randomly assigned to six medication groups for 1 week (n=10 per group): CH + 40% glycerin-water solution (1:1, wt/vol); CMCP; 2% CHX; CH + CMCP (1:1, wt/vol); CH + CMCP (2:3, wt/vol); and saline. Bacterial samples were collected and assayed for colony-forming units. After dentin blocks were split longitudinally, confocal laser scanning microscopy was used to assess the proportion of viable bacteria and EPS production in dentin. Results: CMCP exhibited the best antimicrobial activity, while CH was the least sensitive against E. faecalis (p;0.05). CH combined with CMCP inhibited EPS synthesis by E. faecalis, which sensitized biofilms to antibacterial substances. Moreover, increasing concentrations of CMCP decreased EPS matrix formation, which effectively sensitized biofilms to disinfection agents. Conclusion: The EPS matrix dispelled by CH paste with CMCP may be related to its bactericidal effect; the visualization and analysis of EPS formation and microbial colonization in dentin may be a useful approach to verify medicaments for antimicrobial therapy

Research progress on small biomolecule formulations for chemical disinfection of root canals

Successful treatment of endodontic and periapical diseases requires the elimination of bacteria and microbial biofilms from root canals. Currently, the most preferred irrigation method involves the delivery of sodium hypochlorite via the combination of a syringe and ultrasonic activation. Calcium hydroxide is the main choice for intracanal medicament between endodontic appointments and treatment. However, conventional chemical disinfection of root canals is controversial due to drug permeability and drug resistance. New small biomolecule formulations with high penetrability and bioremediatory capacity, including antimicrobial peptides such as M33D and LL-37, antisense RNA ASwalR/ASvicR and nanoparticles such as silver nanoparticles, mesoporous calcium-silicate nanoparticles and chitosan nanoparticles, have effective antibacterial and antibiofilm properties for use in root canal systems and dentinal tubules, thereby promoting the healing of apical lesions. However, the in vivo drug stability, biosafety, and clinical efficacy of small biomolecule formulations need further investigation. Future research will still focus on the improvement and combination of traditional drugs, as new small molecule formulations and ideal disinfectant drugs need to be developed. In the present paper, we reviewed the development of new antibacterial agents and application of small biomolecule formulations for chemical disinfection of infected root canals

Adherence to a healthy sleep pattern is associated with lower risks of incident falls and fractures during aging

BackgroundAutoimmune diseases are more common among people with unhealthy sleep behaviors, and these conditions have been linked to aging-related bone health. However, there have been few studies that examined the correlation between recently developed sleep patterns based on sleep duration, sleepiness, chronotype, snoring, insomnia, and the incidence of falls and fractures.MethodsWe used a newly developed sleep pattern with components of sleep 7 to 8 h per day, absence of frequent excessive daytime sleepiness, early chronotype, no snoring, and no frequent insomnia as healthy factors to study their relationship with the incidence of falls and fractures. The analysis was conducted among 289,000 participants from the UK Biobank.ResultsThe mean follow-up period was 12.3 years (3.5 million person-years of follow-up), and 12,967 cases of falls and 16,121 cases of all fractures were documented. Compared to participants exhibiting an unfavorable sleep pattern, those adhering to a healthy sleep pattern experienced a 17% and 28% reduction in the risks of incident falls (hazard ratio [HR], 0.83; 95% CI, 0.74–0.93) and all fractures (HR, 0.72; 95% CI, 0.66–0.79) during follow-up. In addition, participants exhibiting a healthy sleep pattern, together with a high genetically determined bone mineral density (BMD), showed the lowest risks of falls and fractures.ConclusionA healthy sleep pattern was significantly linked to decreased risks of incident falls and fractures. The protective association was not modified by genetically determined BMD

TOD typologies for metro stations based on the butterfly model

As a promising planning strategy for urban sustainability, transit-oriented development (TOD) has been widely encouraged and adopted to integrate land use and transport systems. Because of the different applications in form, function and impact, it is necessary to explore context-based TOD typologies to better map the TOD specificities and focus on strategic planning. As the best-known method, the node-place model provides a useful analytical framework to evaluate TOD typologies. However, by using two indexes to aggregate the node and place value, details of some important TOD characteristics are disregarded in this model. Proposing a multi-axial indexes system, the butterfly model can perform a more detailed evaluation of node and place. In this research, we have revised and optimized the butterfly model and taken Tianjin Metro Line 1 as a case study. We find that all stations can be divided into five TOD types with significant spatial variations. TOD principles have already been implemented in Tianjin with good integration between metro system and land use. The method demonstrated in this paper equips urban planners with a useful tool for evaluating TOD performance and adopting more targeted strategies

Classification of coal gangue pile vegetation based on UAV remote sensing

The accurate classification of vegetation species is the basis for the evaluation of vegetation restoration effect of coal gangue pile. In this paper, the visible image of coal gangue pile in different seasons was obtained by UAV remote sensing technology. The color space conversion and texture filtering were used to adequately explore the rich features of color, structure and texture in the visible image. Then, the traditional artificial feature selection method was improved, which could quickly, simply and efficiently screen features information to obtain the optimal classification features, and the optimized results were fused with RGB images to obtain multi-feature fusion images. Finally, based on two stages of RGB images and multi-feature fusion images, the vegetation of coal gangue pile was classified by three supervised classification methods, including support vector machine (SVM), maximum likelihood (ML) and neural network (NN). Meanwhile, the accuracy of classification results was evaluated by confusion matrix and the dynamic changes of vegetation were analyzed. The results showed that the improved artificial feature selection method could screen out the optimal classification features of coal gangue pile vegetation in different seasons. The selected classification features can not only effectively reflect the differences of various ground features, but also reduce the redundancy of feature information to improve the accuracy and efficiency of image classification. The classification result based on Support Vector Machine Classification (SVM) combined with multi-feature fusion image had highest classification accuracy, and the overall classification accuracy could reach 90.60%, and the corresponding Kappa coefficient is 0.8780, which was 9.74% and 0.1265 higher than that of RGB image of the same period, respectively. And, the accuracy of MLC and NNC classification methods was less improved. Compared with the RGB images of the same period, the overall classification accuracy could be improved by 6.95% and 3.93%, respectively, and the corresponding Kappa coefficient could be improved by 0.0845 and 0.0541, respectively. At the same time, based on the result of optimal classification, this paper evaluated the vegetation restoration effect of coal gangue pile in Changcun from the perspectives of vegetation coverage and vegetation allocation pattern. The results showed that a variety of different vegetation allocation patterns were adopted by the coal gangue pile, and the vegetation coverage in autumn and summer is higher than 75%. The overall effect of vegetation restoration was better. This study could provide reference for the identification and classification of coal gangue piles vegetation information based on UAV visible light image, and meanwhile provide opinions or suggestions for the later management and maintenance of coal gangue piles vegetation restoration

MoocRadar: A Fine-grained and Multi-aspect Knowledge Repository for Improving Cognitive Student Modeling in MOOCs

Student modeling, the task of inferring a student's learning characteristics through their interactions with coursework, is a fundamental issue in intelligent education. Although the recent attempts from knowledge tracing and cognitive diagnosis propose several promising directions for improving the usability and effectiveness of current models, the existing public datasets are still insufficient to meet the need for these potential solutions due to their ignorance of complete exercising contexts, fine-grained concepts, and cognitive labels. In this paper, we present MoocRadar, a fine-grained, multi-aspect knowledge repository consisting of 2,513 exercise questions, 5,600 knowledge concepts, and over 12 million behavioral records. Specifically, we propose a framework to guarantee a high-quality and comprehensive annotation of fine-grained concepts and cognitive labels. The statistical and experimental results indicate that our dataset provides the basis for the future improvements of existing methods. Moreover, to support the convenient usage for researchers, we release a set of tools for data querying, model adaption, and even the extension of our repository, which are now available at https://github.com/THU-KEG/MOOC-Radar.Comment: Accepted by SIGIR 202

Distinct hyperuricemia trajectories are associated with different risks of incident diabetes: A prospective cohort study

Background and aim: Conflicting results suggest a link between serum uric acid and diabetes and previous studies ignored the effect of continuous exposure of serum uric acid on diabetes risk. This study aims to characterize hyperuricemia trajectories in middle-aged adults and to examine its potential impact on diabetes risk, considering the role of obesity, dyslipidemia, and hypertension. Methods and results: The cohort included 9192 participants who were free of diabetes before 2013. The hyperuricemia trajectories during 2009–2013 were identified by latent class growth models. Incident diabetes during 2014–2018 was used as the outcome. Modified Poisson regression models were used to assess the association of trajectories with diabetes. Furthermore, marginal structural models were used to estimate the mediating effects of the relationship between hyperuricemia trajectories and diabetes. We identified three discrete hyperuricemia trajectories: high-increasing (n = 5794), moderate-stable (n = 2049), and low-stable (n = 1349). During 5 years of follow-up, we documented 379 incident diabetes cases. Compared with the low-stable pattern, the high-increasing pattern had a higher risk of developing diabetes (RR, 1.42; 95% CI: 1.09–1.84). In addition, the percentages of total effect between the high-increasing hyperuricemia pattern and diabetes mediated by obesity, dyslipidemia, and hypertension were 24.41%, 18.26%, and 6.29%. However, the moderate-stable pattern was not associated with an increased risk of diabetes. Conclusions: These results indicate that the high-increasing hyperuricemia trajectory is significantly associated with an increased risk of diabetes. Furthermore, obesity, dyslipidemia, and hypertension play mediating roles in the relationship between the high-increasing hyperuricemia pattern and increased diabetes risk

Analysis of Characteristic Quality Indexes of Gaoyou Duck Eggs

To explore the quality characteristics of Gaoyou duck eggs, metabolomics was used to analyze the quality indexes, basic nutritional indexes and small molecule metabolites. The results showed that the mass, egg shape index, egg yolk color, Haugh unit, egg white height, egg yolk index and crude protein content of Gaoyou duck eggs were higher than those of the other studied breeds. The contents of total amino acids, umami amino acids, branched-chain amino acids, total fatty acids and unsaturated fatty acids were higher, and the content of saturated fatty acids was lower, indicating that sensory quality parameters, amino acids and fatty acids can characterize the quality of Gaoyou duck eggs. The characteristic components of Gaoyou duck eggs were uncovered by metabolomic fingerprinting, principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and hierarchical cluster analysis (HCA). Totally 252 compounds and 22 differential compounds were identified in egg yolk, and 184 compounds and 40 differential compounds in egg white. Among them, uridine 5’-monophosphate, guanosine 5’-monophosphate, and N-acetyl-D-glucosamine were the main differential nutrients, and arachidonic acid in egg yolk was the unique nutrient of Gaoyou duck eggs, while indole was not detected in the egg white of Gaoyou duck eggs