RNA N6-Methyladenosine Modification in DNA Damage Response and Cancer Radiotherapy.

The N6-methyladenosine (M6A) modification is the most common internal chemical modification of RNA molecules in eukaryotes. This modification can affect mRNA metabolism, regulate RNA transcription, nuclear export, splicing, degradation, and translation, and significantly impact various aspects of physiology and pathobiology. Radiotherapy is the most common method of tumor treatment. Different intrinsic cellular mechanisms affect the response of cells to ionizing radiation (IR) and the effectiveness of cancer radiotherapy. In this review, we summarize and discuss recent advances in understanding the roles and mechanisms of RNA M6A methylation in cellular responses to radiation-induced DNA damage and in determining the outcomes of cancer radiotherapy. Insights into RNA M6A methylation in radiation biology may facilitate the improvement of therapeutic strategies for cancer radiotherapy and radioprotection of normal tissues.

Determination of the oil absorption value of inorganic powder by tracer-assisted headspace gas chromatography.

This paper reports a method for determining the oil absorption value of inorganic powder based on tracer-assisted headspace gas chromatographic (HS-GC) technique. The method was carried out by adding 25 µL droplet of toluene-Dioctyl Phthalate solution onto the surface of 1.0 g inorganic powder, then sealing the headspace vial and shaking it to make the powder spherical. The amount of toluene that not been adsorbed by inorganic powder was quantified using HS-GC with the optimal equilibrium temperature and time conditions of 100 °C and 7 min, respectively. A new mathematical model shows that the oil absorption value can be determined from the signal of toluene. The results show that the employed method has good precision (the relative standard deviation < 3.6 %) and accuracy (R2 = 0.993). This method is simple and accurate, and can be an reliable tool for testing the oil absorption value of inorganic powder sample.

Rational Design of a Niobium Tellurite Crystal Nb2Te3O11 Exhibiting Good Overall Infrared NLO Performance by Structural Genetic Engineering.

Nonlinear optical (NLO) materials have aroused increasing interest owing to their promising applications in optoelectronic technologies. Herein, we present the synthesis of an acentric niobium tellurite crystal, Nb2Te3O11, extracted via a spontaneous crystallization approach. It adopts a unique three-dimensional (3D) structure constructed by the distorted [TeO3], [TeO4], and [NbO6] fundamental building units. The title compound undergoes incongruent melting at approximately 807 °C. Optical characterizations demonstrate that Nb2Te3O11 possesses an extended transparency window beyond 5 µm, along with a large band gap value of 3.1 eV. Moreover, the as-synthesized Nb2Te3O11 displays an appreciable second-harmonic generation (SHG) response of 2 × KDP and a notable birefringence of 0.11 under 1064 nm for achieving phase-matching. In addition, theoretical calculation investigations suggest that the intriguing optical properties are ascribed to the cooperative effect of three types of NLO-active motifs: [TeO3] pyramids, [TeO4] seesaws, and [NbO6] octahedra. These attributes provide new functional insights into Nb2Te3O11 and enrich the family of NLO crystals in the mid-infrared region.

Catalytic asymmetric multicomponent reactions of isocyanide, isothiocyanate and alkylidene malonates.

Several unique chiral 3,4-dihydro-2H-pyrrole-2-thiones were made readily available by carrying out, in each case, a chiral-Mg(OTf)2/N,N'-dioxide-complex-promoted formal [2+1+2] cycloaddition in the presence of tetraethylenediamine. Control experiments revealed that in situ-generated ammonium thiocyanate was crucial for maintaining high enantioselectivity through its inhibition of the HNCS-induced racemization of the products.

Iron-Catalyzed Enantioselective Radical Carboazidation and Diazidation of α,ß-Unsaturated Carbonyl Compounds.

Azidation of alkenes is an efficient protocol to synthesize organic azides which are important structural motifs in organic synthesis. Enantioselective radical azidation, as a useful strategy to install a C-N3 bond, remains challenging due to the inherently instability and unique structure of radicals. Here, we disclose an efficient enantioselective radical carboazidation and diazidation of α,ß-unsaturated ketones and amides catalyzed by chiral N,N'-dioxide/Fe(OTf)2 complexes. An array of substituted alkenes was transformed to the corresponding α-azido carbonyl derivatives in good to excellent enantioselectivities, benefiting the preparation of chiral α-amino ketones, vicinal amino alcohols, and vicinal diamines. Control experiments and mechanistic studies proved the radical pathway in the reaction process. The DFT calculations showed that the azido transferred to the radical intermediate via an intramolecular five-membered transition state with the internal nitrogen of the Fe-N3 species.

Controlling the selective synthesis of [2]- and [3]rotaxanes by intermolecular steric hindrance between the macrocyclic hosts.

Two hydrogen-bonded azo-macrocycles with little disparity of the side chains in steric hindrance exhibited a substantial difference in complexation (slow/fast exchange) towards bipyridinium. Inspired by this finding, these macrocycles were applied to efficiently and selectively construct [2]- and [3]rotaxanes through one-pot synthesis. The origin of the selectivity in this novel approach was elucidated by comparing single crystal structures, DFT calculations and stepwise synthesis.

A Novel Method for Alignment-free DNA Sequence Similarity Analysis Based on the Characterization of Complex Networks.

Determination of sequence similarity is one of the major steps in computational phylogenetic studies. One of the major tasks of computational biologists is to develop novel mathematical descriptors for similarity analysis. DNA clustering is an important technology that automatically identifies inherent relationships among large-scale DNA sequences. The comparison between the DNA sequences of different species helps determine phylogenetic relationships among species. Alignment-free approaches have continuously gained interest in various sequence analysis applications such as phylogenetic inference and metagenomic classification/clustering, particularly for large-scale sequence datasets. Here, we construct a novel and simple mathematical descriptor based on the characterization of cis sequence complex DNA networks. This new approach is based on a code of three cis nucleotides in a gene that could code for an amino acid. In particular, for each DNA sequence, we will set up a cis sequence complex network that will be used to develop a characterization vector for the analysis of mitochondrial DNA sequence phylogenetic relationships among nine species. The resulting phylogenetic relationships among the nine species were determined to be in agreement with the actual situation.

[Development of a model for the diagnosis and risk classification on anthrax through artificial neural network].

OBJECTIVE: Based on data through clinical and epidemiological studies, a model regarding the diagnosis and risk classification on anthrax was developed by artificial neural network (ANN). The model could integrally diagnose anthrax cases, judge the risk tendency in time, and increase the ability of recognizing the anthrax accidents. METHODS: Clinical, laboratory and epidemiological data from anthrax cases was collected and analyzed. The important factors which could greatly influence the results on diagnosis and judgment was chosen and used as the neural units. Through the use of artificial neural network analytic method (back propagation, BP), an intelligent model on the diagnosis and risk classification was developed. RESULTS: Results from the multivariate analysis revealed that: 11 factors including incubation period, chest radiographic and microscopic findings, characteristics on professions etc. were associated with the judgment on the diagnosis and intensity of the epidemics. Through 500 times training on the neural network, the performance error decreased from 6.669 59 to 5.051 19 x 10(-11). The model was then validated. With 100% average correct rate, the predictive value was good. CONCLUSION: It was feasible to use the disease information to develop a diagnosis and risk classification model on anthrax by artificial neural network. With 100% average correct rate, the established model was valuable in practice.