Protein-spatiotemporal partition releasing gradient porous scaffolds and anti-inflammatory and antioxidant regulation remodel tissue engineered anisotropic meniscus

Meniscus is a wedge-shaped fibrocartilaginous tissue,playing important roles in maintaining joint stability and function.Meniscus injuries are difficult to heal and frequently progress into structural breakdown,which then leads to osteoarthritis.Regeneration of heterogeneous tissue engineering meniscus(TEM)continues to be a scientific and translational challenge.The morphology,tissue architecture,mechanical strength,and functional applications of the cultivated TEMs have not been able to meet clinical needs,which may due to the negligent attention on the importance of microenvironment in vitro and in vivo.Herein,we combined the 3D(three-dimensional)-printed gradient porous scaffolds,spatiotemporal partition release of growth factors,and anti-inflammatory and anti-oxidant microenvironment regulation of Ac2-26 peptide to prepare a versatile meniscus composite scaffold with heterogeneous bionic structures,excellent biomechanical properties and anti-inflammatory and anti-oxidant effects.By observing the results of cell activity and differentiation,and biomechanics under anti-inflammatory and anti-oxidant microenvironments in vitro,we explored the effects of anti-inflammatory and anti-oxidant microenvironments on construction of regional and functional heterogeneous TEM via the growth process regulation,with a view to cultivating a high-quality of TEM from bench to bedside.

Occurrence and health risk assessment of trace heavy metals via groundwater in Shizhuyuan Polymetallic Mine in Chenzhou City, China

The Shizhuyuan Polymetallic Mine in Chenzhou City is an important multi-metal deposit in China. After a dam accident in 1985, there are still a number of mining plants, smelters and tailing ponds in this area. These had the potential to pollute the surrounding groundwater. In this study, groundwater samples were collected from 20 residents＇ wells in this area during both dry and wet seasons. In particular, this study focused on the exposure and the health risk assessment of trace heavy metal in groundwater. Multiple statistical analysis and fuzzy comprehensive method were employed to reveal the distribution characteristics of heavy metal and to assess the groundwater quality. Results indicated that Cr, Fe, Ni, Cu, Zn, As, Cd, Ba, Hg and Pb were widespread with low exposure levels. There were 19 wells with low level exposure and one well with a moderate level exposure in the dry season. All of the wells were in low level exposure during the wet season. As and Mn exhibited potential noncarcinogenic concern, because their maximum hazard quotient （HQ） was higher than 1.0. This may cause adverse health effect on adults in dry season or on children in both seasons. Only As, showed that the maximum carcinogenic risk was more than 10^-4, suggesting a high cancer risk for children in both dry and wet seasons. Therefore, analysis and reduction the concentrations of As and Mn in groundwater are needed in order to protect the health of residents and especially children in the area.

Recent advances in RNA structurome

RNA structures are essential to support RNA functions and regulation in various biological processes. Recently, a range of novel technologies have been developed to decode genome-wide RNA structures and novel modes of functionality across a wide range of species. In this review, we summarize key strategies for probing the RNA structurome and discuss the pros and cons of representative technologies. In particular, these new technologies have been applied to dissect the structural landscape of the SARS-CoV-2 RNA genome. We also summarize the functionalities of RNA structures discovered in different regulatory layers-including RNA processing, transport, localization, and mRNA translation-across viruses, bacteria, animals, and plants. We review many versatile RNA structural elements in the context of different physiological and pathological processes(e.g., cell differentiation, stress response, and viral replication). Finally, we discuss future prospects for RNA structural studies to map the RNA structurome at higher resolution and at the single-molecule and single-cell level, and to decipher novel modes of RNA structures and functions for innovative applications.

Effect of nitrogen/phosphorus concentration on algal organic matter generation of the diatom Nitzschia palea:Total indicators and spectroscopic characterization

Critical algal blooms in great lakes increase the level of algal organic matters（AOMs）,significantly altering the composition of natural organic matters（NOMs） in freshwater of lake.This study examined the AOM＇s characteristics of Nitzschia palea（N.palea）,one kind of the predominant diatom and an important biomarker of water quality in the great lakes of China,to investigate the effect of AOMs on the variation of NOMs in lakes and the process of algal energy.Excitation–emission matrix fluorescence（EEM） spectroscopy,synchronous fluorescence（SF） spectroscopy and deconvolution UV–vis（D-UV） spectroscopy were utilized to characterize AOMs to study the effects of nutrient loading on the composition change of AOMs.From results,it was revealed that the phosphorus is the limiting factor for N.palea＇s growth and the generation of both total organic carbon and amino acids but the nitrogen is more important for the generation of carbohydrates and proteins.EEM spectra revealed differences in the composition of extracellular organic matter and intracellular organic matter.Regardless of the nitrogen and phosphorus concentrations,aromatic proteins and soluble microbial products were the main components,but the nitrogen concentration had a significant impact on their composition.The SF spectra were used to study the AOMs for the first time and identified that the protein-like substances were the major component of AOMs,creating as a result of aromatic group condensation.The D-UV spectra showed carboxylic acid and esters were the main functional groups in the EOMs,with –OCH_3,–SO_2NH_2,–CN,–NH_2,–O– and –COCH_3functional groups substituting into benzene rings.

Energy-efficient removal of carbamazepine in solution by electrocoagulation-electrofenton using a novel P-rGO cathode

In this study,carbamazepine(CBZ)decay in solution has been studied by coupling electro-coagulation with electro-Fenton(EC-EF)with a novel P-rGO/carbon felt(CF)cathode,aiming to accelerate the in-situ generation of·OH,instead of adding Fe2+and H2O2.Firstly,the fabri-cated P-rGO and its derived cathode were characterized by XRD,SEM,AFM,XPS and electro-chemical test(EIS,CV and LSV).Secondly,it was confirmed that the performance in removal efficiency and electric energy consumption(EEC)by EC-EF(kobs=0.124 min^(-1),EEC=43.98 kWh/kg CBZ)was better than EF(kobs=0.069 min^(-1),EEC=61.04 kWh/kg CBZ).Then,P-rGO/CF(kobs=0.248 min^(-1),EEC=29.47 kWh/kg CBZ,CE=61.04%)showed the best performance in EC-EF,among all studied heteroatom-doped graphene/CF.This superior performance may be associated with its largest layer spacing and richest C=C,which can promote the electron transfer rate and conductivity of the cathode.Thus,more H2O2 and·OH could be produced to degrade CBZ,and almost 100%CBZ was removed with kobs being 0.337 min^(-1) and the EEC was only 24.18 kWh/kg CBZ,under the optimal conditions(P-rGO loading was 6.0 mg/cm^(2),the current density was 10.0 mA/cm^(2),the gap between electrode was 2.0 cm).Additionally,no matter the influent is acidic,neutral or alkaline,no additional pH adjustment is required for the effluent of EC-EF.At last,an inconsecutive empirical kinetic model was firstly estab-lished to predict the effect of operating parameters on CBZ removal.

Togni-ⅡReagent Mediated Selective Hydrotrifluoromethylation and Hydrothiolation of Alkenes

Based on the redox reactions of Togni-Ⅱreagent and thiols,a thiol-tuned selective functionalization of unactivated olefins was disclosed.In combination with aryl thiols,stoichiometric amount of Togni-Ⅱreagent prompted a hydrotrifluoromethylation of alkenes,in which,aryl thiols played as reductant and hydrogen source;while by utilization of alkyl thiols,catalytic amount of Togni-Ⅱreagent initiated thiol-ene and thiol-yne reactions.The reported applications are characterized by their operational simplicity and wide functional group tolerance.

Factors influencing the photodegradation of Nnitrosodimethylamine in drinking water

In order to provide basic data for practical application,photodegradation experiment of Nnitrosodimethylamine(NDMA)in aqueous solution was carried out with a low-pressure Hg lamp.Effects of the initial concentration of NDMA,solution pH,dissolved oxygen,and the presence of humic acid on NDMA photodegradation were investigated.NDMA at various initial concentrations selected in this study was almost completely photodegraded by UV irradiation within 20 min,except that at 1.07 mmol/L,NDMA could be photodegraded almost completely in the acidic and neutral solutions,while the removal efficiency decreased remarkably in the alkaline solution.Dissolved oxygen enhanced the NDMA photodegradation,and the presence of humic acid inhibited the degradation of NDMA.Depending on the initial concentration of NDMA,NDMA photodegradation by UV obeyed the pseudo-first-order kinetics.Dimethylamine,nitrite,and nitrate were detected as the photodegradation products of NDMA.^(1)O_(2) was found to be the reactive oxygen species present in the NDMA photodegradation process by UV,based on the inhibiting experiments using tert-butanol and sodium azide.

User Profiling for CSDN:Keyphrase Extraction,User Tagging and User Growth Value Prediction

The Chinese Software Developer Network(CSDN)is one of the largest information technology communities and service platforms in China.This paper describes the user profiling for CSDN,an evaluation track of SMP Cup 2017.It contains three tasks:(1)user document keyphrase extraction,(2)user tagging and(3)user growth value prediction.In the first task,we treat keyphrase extraction as a classification problem and train a Gradient-Boosting-Decision-Tree model with comprehensive features.In the second task,to deal with class imbalance and capture the interdependency between classes,we propose a two-stage framework:(1)for each class,we train a binary classifier to model each class against all of the other classes independently;(2)we feed the output of the trained classifiers into a softmax classifier,tagging each user with multiple labels.In the third task,we propose a comprehensive architecture to predict user growth value.Our contributions in this paper are summarized as follows:(1)we extract various types of features to identify the key factors in user value growth;(2)we use the semi-supervised method and the stacking technique to extend labeled data sets and increase the generality of the trained model,resulting in an impressive performance in our experiments.In the competition,we achieved the first place out of 329 teams.