Structurally diverse oxygen-containing aromatic compounds with anti-inflammatory activity from Aspergillus sp. LY-1-2.

Three isocoumarins, ascoisocoumarin A (1), embeurekol (2), and sclerotinin A (3), and five biosynthetically related derivatives, ascospinols A-C (4, 6, and 7), and talaflavuols C and B (5 and 8), together with twelve polyketides or terpenes (9-20) were isolated from the fungus Aspergillus sp. LY-1-2 inhabited in a sample of Cordyceps sp. Most of them belong to the family of oxygen-containing aromatic compounds and compounds 1, 4, 6, and 7 are previously undescribed compounds. Their planar structures were established by a combined spectroscopic analysis of HRESIMS and NMR, and their stereochemistry was determined by 13C NMR calculations with sorted training set (STS) protocol analysis, and ECD calculations. New compounds 1 and 6 displayed potential anti-inflammatory effects in lipopolysaccharide (LPS)-induced BV2 microglia cells.

Evaluation of the real-time fluorescence loop-mediated isothermal amplification assay for the detection of Ureaplasma urealyticum.

Ureaplasma urealyticum (UU) is commonly present in human reproductive tract, which frequently leads to genital tract infection. Hence, there is an urgent need to develop a rapid detection method for UU. In our study, a real-time fluorescence loop-mediated isothermal amplification (LAMP) assay was developed and evaluated for the detection of UU. Two primers were specifically designed based on the highly conserved regions of ureaseB genes. The reaction was carried out for 60 min in a constant temperature system using Bst DNA polymerase, and the process was monitored by real-time fluorescence signal, while polymerase chain reaction (PCR) was performed simultaneously. In real-time fluorescence LAMP reaction system, positive result was only obtained for UU among 9 bacterial strains, with detection sensitivity of 42 pg/µL (4.2 × 105 CFU/mL), and all 16 clinical samples of UU could be detected. In conclusion, real-time fluorescence LAMP is a simple, sensitive, specific and effective method compared with conventional PCR, which shows great promise in the rapid detection of UU.

Adaptive Sparse Detector for Suppressing Powerline Component in EEG Measurements.

Powerline interference (PLI) is a major source of interference in the acquisition of electroencephalogram (EEG) signal. Digital notch filters (DNFs) have been widely used to remove the PLI such that actual features, which are weak in energy and strongly connected to brain states, can be extracted explicitly. However, DNFs are mathematically implemented via discrete Fourier analysis, the problem of overlapping between spectral counterparts of PLI and those of EEG features is inevitable. In spite of their effectiveness, DNFs usually cause distortions on the extracted EEG features, which may lead to incorrect diagnostic results. To address this problem, we investigate an adaptive sparse detector for reducing PLI. This novel approach is proposed based on sparse representation inspired by self-adaptive machine learning. In the coding phase, an overcomplete dictionary, which consists of redundant harmonic waves with equally spaced frequencies, is employed to represent the corrupted EEG signal. A strategy based on the split augmented Lagrangian shrinkage algorithm is employed to optimize the associated representation coefficients. It is verified that spectral components related to PLI are compressed into a narrow area in the frequency domain, thus reducing overlapping with features of interest. In the decoding phase, eliminating of coefficients within the narrow band area can remove the PLI from the reconstructed signal. The sparsity of the signal in the dictionary domain is determined by the redundancy factor. A selection criteria of the redundancy factor is suggested via numerical simulations. Experiments have shown the proposed approach can ensure less distortions on actual EEG features.

[Distribution Characteristics of Antibiotic Resistance Genes in PM2.5 of a Concentrated Broiler Feeding Operation].

Concentrated poultry feeding operations are an important source of antibiotic resistance genes (ARGs). Little attention has been given to PM2.5 as a mechanism for exposing ARGs to humans. In this study, PM2.5 and fecal samples from inside the broiler feeding operation and PM2.5 samples from outside the broiler feeding operation were collected. All samples were subjected to the determination of class Ⅰ integrin (intI1), total bacterial gene (16S rDNA), and 19 ARGs of six types by quantitative real-time PCR (qPCR). The results indicated that, excluding blaGES-1 and blaSHV-1, the remaining 17 ARGs were detected in all six samples. Sulfonamide resistance genes, tetracycline resistance genes, macrolide resistance genes, and aminoglycoside resistance genes were abundant in the feces, reaching 1.04×109-3.27×1010 copies·g-1, while feces was an important source of antibiotic resistance genes in PM2.5 of the broiler feeding operation. There were high abundances of sulfonamide resistance genes and macrolide resistance genes in PM2.5 from inside the broiler feeding operation, reaching (8.9±1.9)×107 copies·m-3 and (5.6±3.1)×107 copies·m-3, respectively. The abundance of ARGs in the PM2.5 samples from inside the broiler feeding operation was significantly higher compared to the outside PM2.5 samples. There was a significant positive correlation between PM2.5 mass concentration and 16S rDNA, intI1, and ARGs abundance, indicating that PM2.5 was the reservoir and disseminator of airborne bacteria, ARGs, and intI1 in the broiler feeding operation. The abundance of intI1 was higher than ARGs among all samples, and the co-occurring relationship between intI1 and ARGs demonstrates the threat of multi-drug resistance, which is harmful to the surrounding air environment and the health of the breeder and poultry.