Biomimetic cell-adhesive ligand-functionalized peptide composite hydrogels maintain stemness of human amniotic mesenchymal stem cells

In vivo,stem cells reside in a three-dimensional(3D)extracellular microenvironment in which complicated biophysical and biochemical factors regulate their behaviors.Biomimicking of the stem cellmatrix interactions is an ideal approach for controlling the stem cell fate.This study investigates the effects of the incorporation of cell-adhesive ligands in 3D self-assembling peptide hydrogels to modulate stem cell survival,proliferation,maintenance of stemness,and osteogenic differentiation.The results show that the composite hydrogels were non-cytotoxic and effective for maintaining human amniotic mesenchymal stem cell(hAMSC)survival,proliferation and phenotypic characterization.The expression levels of pluripotent markers were also upregulated in the composite hydrogels.Under inductive media conditions,mineral deposition and mRNA expression levels of osteogenic genes of hAMSCs were enhanced.The increasing expression of integrin aand b-subunits for hAMSCs indicates that the ligandintegrin interactions may modulate the cell fate for hAMSCs in composite hydrogels.

Effects of mixture ratio on anaerobic co-digestion with fruit and vegetable waste and food waste of China

The biochemical methane potentials for typical fruit and vegetable waste (FVW) and food waste (FW) from a northern China city were investigated,which were 0.30,0.56 m 3 CH 4/kgVS (volatile solids) with biodegradabilities of 59.3% and 83.6%,respectively.Individual anaerobic digestion testes of FVW and FW were conducted at the organic loading rate (OLR) of 3 kg VS/(m 3 ·day) using a lab-scale continuous stirred-tank reactor at 35℃.FVW could be digested stably with the biogas production rate of 2.17 m 3/(m 3 ·day) and methane production yield of 0.42 m 3 CH 4/kg VS.However,anaerobic digestion process for FW was failed due to acids accumulation.The effects of FVW:FW ratio on co-digestion stability and performance were further investigated at the same OLR.At FVW and FW mixing ratios of 2:1 and 1:1,the performance and operation of the digester were maintained stable,with no accumulation of volatile fatty acids (VFA) and ammonia.Changing the feed to a higher FW content in a ratio of FVW to FW 1:2,resulted in an increase in VFAs concentration to 1100-1200mg/L,and the methanogenesis was slightly inhibited.At the optimum mixture ratio 1:1 for co-digestion of FVW with FW,the methane production yield was 0.49 m 3 CH 4/kg VS,and the volatile solids and soluble chemical oxygen demand (sCOD) removal efficiencies were 74.9% and 96.1%,respectively.

Graphene-supported nanoscale zero-valent iron:Removal of phosphorus from aqueous solution and mechanistic study

Excess phosphorus from non-point pollution sources is one of the key factors causing eutrophication in many lakes in China,so finding a cost-effective method to remove phosphorus from non-point pollution sources is very important for the health of the aqueous environment. Graphene was selected to support nanoscale zero-valent iron(nZVI)for phosphorus removal from synthetic rainwater runoff in this article. Compared with nZVI supported on other porous materials,graphene-supported nZVI(G-nZVI) could remove phosphorus more efficiently. The amount of nZVI in G-nZVI was an important factor in the removal of phosphorus by G-nZVI,and G-nZVI with 20 wt.% nZVI(20% G-nZVI)could remove phosphorus most efficiently. The nZVI was very stable and could disperse very well on graphene,as characterized by transmission electron microscopy(TEM) and scanning electron microscopy(SEM). X-ray photoelectron spectroscopy(XPS),Fourier Transform infrared spectroscopy(FT-IR) and Raman spectroscopy were used to elucidate the reaction process,and the results indicated that Fe-O-P was formed after phosphorus was adsorbed by G-nZVI. The results obtained from X-ray diffraction(XRD) indicated that the reaction product between nZVI supported on graphene and phosphorus was Fe3(PO4)2·8H2O(Vivianite). It was confirmed that the specific reaction mechanism for the removal of phosphorus with nZVI or G-nZVI was mainly due to chemical reaction between nZVI and phosphorus.

Zeolite (Na) modified by nano-Fe particles adsorbing phosphate in rainwater runoff

Zeolite (Na) modified by self-synthesized nano-Fe particles was used as infiltration media to adsorb phosphate in rainwater runoff. The adsorption capacities increased up to 75 times that of natural zeolite at a saturated equilibrium phosphate concentration of 0.42 mg/L. The correlation of capacity and material-specific surface area indicated that specific surface area was not the key factor contributing to the capacity improvement. SEM and XRD analysis showed that chemical reaction between Fe and P to form new products like cacoxenite is the main reason for the increased capacity, and that the method of adding metal ions or particles to improve the adsorption capacity for phosphate is feasible.

Diagnosis of sewer pipe defects on image recognition of multi-features and support vector machine in a southern Chinese city

Closed circuit television(CCTV)systems are widely used to inspect sewer pipe conditions.During the diagnosis process,the manual diagnosis of defects is time consuming,labor intensive and error prone.To assist inspectors in diagnosing sewer pipe defects on CCTV inspection images,this paper presents an image recognition algorithm that applies features extraction and machine learning approaches.An algorithm of image recognition techniques,including Hu invariant moment,texture features,lateral Fourier transform and Daubechies(DBn)wavelet transform,was used to describe the features of defects,and support vector machines were used to classify sewer pipe defects.According to the inspection results,seven defects were defined;the diagnostic system was applied to a sewer pipe system in a southern city of China,and 28,760 m of sewer pipes were inspected.The results revealed that the classification accuracies of the different defects ranged from 51.6% to 99.3%.The overall accuracy reached 84.1%.The diagnosing accuracy depended on the number of the training samples,and four fitting curves were applied to fit the data.According to this paper,the logarithmic fitting curve presents the highest coefficient of determination of 0.882,and more than 200 images need to be used for training samples to guarantee the accuracy higher than 85%.