Mechanistic insights into the removal of As(III) and As(V) by iron modified carbon based materials with the aid of machine learning.

The machine learning (ML) technique was used to examine the effects of different microscopic material features on the ability of iron modified carbon-based materials (Fe-CBMs) to remove As(V) and As(III). The findings showed that specific CBMs and Fe-CBMs features (such as surface functionality) from sophisticated microscopic and spectroscopic techniques led to models that were more accurate than those constructed using more basic information, such as bulk elemental composition and surface area (the root-mean-square error fell by 44.7% for As(V) and 56.9% for As(III), respectively). The high non-polar carbon (NPC) content of CBMs and Fe-CBMs had a detrimental influence on As(V) and As(III) removal capability, whereas surface oxygen-containing functional groups (SOFGs) contents on CBMs and Fe-CBMs played an essential role in arsenic removal based on ML approaches. The relative importance of CO was greater by 77.8% and 40.6% than that of C-O on the elimination of As(V) and As(III), respectively. The accurate ML models are helpful for the future design of Fe-CBMs and the relative importance and partial dependence plot analysis can direct the use of Fe-CBMs for arsenic removal in a sensible manner under different application situations.

Novel Fluorescent Probe Based on Rare-Earth Doped Upconversion Nanomaterials and Its Applications in Early Cancer Detection.

In this paper, a novel rare-earth-doped upconverted nanomaterial NaYF4:Yb,Tm fluorescent probe is reported, which can detect cancer-related specific miRNAs in low abundance. The detection is based on an upconversion of nanomaterials NaYF4:Yb,Tm, with emissions at 345, 362, 450, 477, 646, and 802 nm, upon excitation at 980 nm. The optimal Yb3+:Tm3+ doping ratio is 40:1, in which the NaYF4:Yb,Tm nanomaterials have the strongest fluorescence. The NaYF4:Yb, Tm nanoparticles were coated with carboxylation or carboxylated protein, in order to improve their water solubility and biocompatibility. The two commonly expressed proteins, miRNA-155 and miRNA-150, were detected by the designed fluorescent probe. The results showed that the probes can distinguish miRNA-155 well from partial and complete base mismatch miRNA-155, and can effectively distinguish miRNA-155 and miRNA-150. The preliminary results indicate that these upconverted nanomaterials have good potential for protein detection in disease diagnosis, including early cancer detection.

Rhizosphere microbial community composition and survival strategies in oligotrophic and metal(loid) contaminated iron tailings areas.

In this study, the metal(loid) fractions in two alkaline iron tailings areas with similar physico-chemical properties and the enrichment ability of dominant plants in these areas were investigated. Additionally, high-throughput sequencing and metagenome analysis were used to examine the rhizosphere microbial community structures and their strategies and potential for carbon fixation, nitrogen metabolism, and metal(loid) resistance in mining areas. Results showed that Salsola collina, Setaria viridis, and Xanthium sibiricum have strong enrichment capacity for As, and the maximum transport factor for Mn can reach 4.01. The richness and diversity of bacteria were the highest in rhizosphere tailings, and the dominant phyla were Proteobacteria, Actinobacteria, Ascomycota, and Thaumarchaeota. The key taxa present in rhizosphere tailings were generally metal(loid) resistant, especially Sphingomonas, Pseudomonas, Nocardioides, and Microbacterium. The reductive citrate cycle was the main carbon fixation pathway of microorganisms in tailings. Rhizosphere microorganisms have evolved a series of survival strategies and can adapt to oligotrophic and metal(loid) polluted mining environments. The results of this study provide a basis for the potential application of plant-microbial in situ remediation of alkaline tailings.

The exploration of quantum dot-molecular beacon based MoS2 fluorescence probing for myeloma-related Mirnas detection.

Highly sensitive and reliable detection of multiple myeloma remains a major challenge in liquid biopsy. Herein, for the first time, quantum dot-molecular beacon (QD-MB) functionalized MoS2 (QD-MB @MoS2) fluorescent probes were designed for the dual detection of multiple myeloma (MM)-related miRNA-155 and miRNA-150. The results indicate that the two probes can effectively detect miRNA-155 and miRNA-150 simultaneously with satisfactory recovery rates, and the limit of detections (LODs) of miRNA-155 and miRNA-150 in human serum are low to 7.19 fM and 5.84 fM, respectively. These results indicate that our method is the most sensitive detection so far reported and that the designed fluorescent probes with signal amplification strategies can achieve highly sensitive detection of MM-related miRNAs for MM diagnosis.

Label-free discrimination of glioma brain tumors in different stages by surface enhanced Raman scattering.

According to the WHO classification criteria, the most common intracranial tumor gliomas can be divided into four grades based on their symptoms. Among them, Grade Ⅰ and Grade II are low-grade gliomas, and Grade III and Grade IV are high-grade gliomas. Because gliomas have a high lethal rate, they have received widespread attention in the medical field. Based on these circumstances, a rapid and facile surface enhanced Raman scattering (SERS) method using silver nano particle-decorated silver nanorod (AgNPs@AgNR) as substrates were developed for the discrimination of gliomas. Compared with SERS-active silver nanoparticles and silver nanorod substrates, the prepared AgNPs@AgNR substrates showed an outstanding SERS performance with an enhancement factor up to 1.37 × 109. Combined AgNPs@AgNR substrate with principal component analysis (PCA), we achieved rapid discrimination of healthy brain tissue and gliomas at different grades. The spectra obtained from the tissue illustrate prominently spectral differences which can be applied to identify whether it came from a healthy region or from a glioma. The most prominently difference between the SERS spectrum of healthy brain tissue and that of gliomas at different grades is the reduction in quotient of two characteristic peaks at 653 and 724 cm-1. Furthermore, healthy brain tissue and Grade II gliomas as low grade gliomas as well as Grade III and Grade IV as high-grade gliomas can be clearly distinguished by three-dimensional PCA. Preliminary results indicate that the SERS spectra based on AgNPs@AgNR substrates can be applied for a rapid identification owing to its simple preparation of specimen and high-speed spectral acquirement.

Leaching behavior of metals from iron tailings under varying pH and low-molecular-weight organic acids.

The migration of metals (e.g., Fe, Cd, Co, Cr, Cu, Mn, Ni, and Zn) in both of iron tailings under different pH leachates was studied by laboratory static leaching experiments. The results indicated that Fe showed the highest leaching concentration at an initial pH of 2, reaching 16.19 and 51.72 mg L-1 in the Qian'anling (Q0) and Majuanzi (M0) iron tailings, respectively. Metal ions manifested a strong pH dependence. In addition, the leaching behavior of Cd, Cr, Fe, and Cu for the two tailings was also evaluated under leaching by three low-molecular-weight organic acids (LMWOAs). The results indicated the leaching of Cd and Fe followed the order of citric acid > malic acid > oxalic acid and that the leaching order for Cr and Cu was citric acid > oxalic acid > malic acid. The concentration of Fe was low in 5 mM oxalic acid leaching for 20 days because of the hydrolysis precipitation of iron ions and the complexation with organic ligand. The crystal lattice on the tailings was significantly damaged after leaching. The CO32- peak appeared in M0 with different treatments, and the proportion of COO- fitting peak areas increased markedly after leaching with LMWOAs.