Characteristic Male Urine Microbiomes Associate with Asymptomatic Sexually Transmitted Infection

Article discussing research on characteristic male urine microbiomes associated with asymptomatic sexually transmitted infection

Direct Evidence for Packaging Signal-Mediated Assembly of Bacteriophage MS2

Using cross-linking coupled to matrix-assisted laser desorption/ionization mass spectrometry and CLIP-Seq sequencing, we determined the peptide and oligonucleotide sequences at the interfaces between the capsid proteins and the genomic RNA of bacteriophage MS2. The results suggest that the same coat protein (CP)-RNA and maturation protein (MP)-RNA interfaces are used in every viral particle. The portions of the viral RNA in contact with CP subunits span the genome, consistent with a large number of discrete and similar contacts within each particle. Many of these sites match previous predictions of the locations of multiple, dispersed and degenerate RNA sites with cognate CP affinity termed packaging signals (PSs). Chemical RNA footprinting was used to compare the secondary structures of protein-free genomic fragments and the RNA in the virion. Some PSs are partially present in protein-free RNA but others would need to refold from their dominant solution conformations to form the contacts identified in the virion. The RNA-binding peptides within the MP map to two sections of the N-terminal half of the protein. Comparison of MP sequences from related phages suggests a similar arrangement of RNA-binding sites, although these N-terminal regions have only limited sequence conservation. In contrast, the sequences of the C-termini are highly conserved, consistent with them encompassing pilin-binding domains required for initial contact with host cells. These results provide independent and unambiguous support for the assembly of MS2 virions via a PS-mediated mechanism involving a series of induced-fit viral protein interactions with RNA

Bacterial Communities of the Coronal Sulcus and Distal Urethra of Adolescent Males

Lactobacillus-dominated vaginal microbiotas are associated with reproductive health and STI resistance in women, whereas altered microbiotas are associated with bacterial vaginosis (BV), STI risk and poor reproductive outcomes. Putative vaginal taxa have been observed in male first-catch urine, urethral swab and coronal sulcus (CS) specimens but the significance of these observations is unclear. We used 16 S rRNA sequencing to characterize the microbiota of the CS and urine collected from 18 adolescent men over three consecutive months. CS microbiotas of most participants were more stable than their urine microbiotas and the composition of CS microbiotas were strongly influenced by circumcision. BV-associated taxa, including Atopobium, Megasphaera, Mobiluncus, Prevotella and Gemella, were detected in CS specimens from sexually experienced and inexperienced participants. In contrast, urine primarily contained taxa that were not abundant in CS specimens. Lactobacilllus and Streptococcus were major urine taxa but their abundance was inversely correlated. In contrast, Sneathia, Mycoplasma and Ureaplasma were only found in urine from sexually active participants. Thus, the CS and urine support stable and distinct bacterial communities. Finally, our results suggest that the penis and the urethra can be colonized by a variety of BV-associated taxa and that some of these colonizations result from partnered sexual activity

A Point Cloud Data-Driven Pallet Pose Estimation Method Using an Active Binocular Vision Sensor

Pallet pose estimation is one of the key technologies for automated fork pickup of driverless industrial trucks. Due to the complex working environment and the enormous amount of data, the existing pose estimation approaches cannot meet the working requirements of intelligent logistics equipment in terms of high accuracy and real time. A point cloud data-driven pallet pose estimation method using an active binocular vision sensor is proposed, which consists of point cloud preprocessing, Adaptive Gaussian Weight-based Fast Point Feature Histogram extraction and point cloud registration. The proposed method overcomes the shortcomings of traditional pose estimation methods, such as poor robustness, time consumption and low accuracy, and realizes the efficient and accurate estimation of pallet pose for driverless industrial trucks. Compared with traditional Fast Point Feature Histogram and Signature of Histogram of Orientation, the experimental results show that the proposed approach is superior to the above two methods, improving the accuracy by over 35% and reducing the feature extraction time by over 30%, thereby verifying the effectiveness and superiority of the proposed method

A Novel Pallet Detection Method for Automated Guided Vehicles Based on Point Cloud Data

Automated guided vehicles are widely used in warehousing environments for automated pallet handling, which is one of the fundamental parts to construct intelligent logistics systems. Pallet detection is a critical technology for automated guided vehicles, which directly affects production efficiency. A novel pallet detection method for automated guided vehicles based on point cloud data is proposed, which consists of five modules including point cloud preprocessing, key point extraction, feature description, surface matching and point cloud registration. The proposed method combines the color with the geometric features of the pallet point cloud and constructs a new Adaptive Color Fast Point Feature Histogram (ACFPFH) feature descriptor by selecting the optimal neighborhood adaptively. In addition, a new surface matching method called the Bidirectional Nearest Neighbor Distance Ratio-Approximate Congruent Triangle Neighborhood (BNNDR-ACTN) is proposed. The proposed method overcomes the problems of current methods such as low efficiency, poor robustness, random parameter selection, and being time-consuming. To verify the performance, the proposed method is compared with the traditional and modified Iterative Closest Point (ICP) methods in two real-world cases. The results show that the Root Mean Square Error (RMSE) is reduced to 0.009 and the running time is reduced to 0.989 s, which demonstrates that the proposed method has faster registration speed while maintaining higher registration accuracy

Identification and differentiation of major components in three different “Sheng-ma” crude drug species by UPLC/Q-TOF-MS

Cimicifugae Rhizoma (Sheng ma) is a Ranunculaceae herb belonging to a composite family and well known in China. has been widely used in traditional Chinese medicine. The Pharmacopoeia of the People׳s Republic of China contains three varieties (Cimicifuga dahurica (Turcz.), Cimicifuga foetida L. and Cimicifuga heracleifolia Kom.) which have been used clinically as “Sheng-ma”. However, the chemical constituents of three components of “Sheng-ma” have never been documented. In this study, a rapid method for the analysis of the main components of “Sheng-ma” was developed using ultra-high performance liquid chromatography with quadrupole-time-of-flight mass spectrometry (UPLC/Q-TOF-MS). The present study reveals the major common and distinct chemical constituents of C. dahurica, C. foetida and C. heracleifolia and also reports principal component and statistical analyses of these results. The components were identified by comparing the retention time, accurate mass, mass spectrometric fragmentation characteristic ions and matching empirical molecular formula with that of the published compounds. A total of 32 common components and 8 markers for different “Sheng-ma” components were identified. These findings provide an important basis for the further study and clinical utilities of the three “Sheng-ma” varieties

Extension of the bright high-harmonic photon energy range via nonadiabatic critical phase matching

Extending the photon energy range of bright high-harmonic generation to cover the entire soft X-ray region is important for many applications in science and technology. The concept of critical ionization fraction has been essential, because it dictates the maximum driving laser intensity that can be used while preserving bright harmonic emission. In this work, we reveal a second, nonadiabatic critical ionization fraction that substantially extends the maximum phase-matched high-harmonic photon energy, that arises due to strong reshaping of the intense driving laser field. We validate this understanding through a systematic comparison between experiment and theory, for a wide range of pulse durations and driving laser wavelengths. In particular, high harmonics driven by intense few-cycle pulses experience the most pronounced spectral reshaping, significantly extending the bright photon energy range. We also present an analytical model that predicts the spectral extension that can be achieved for different driving lasers. This reveals an increasing role of nonadiabatic critical phase matching when driven by few-cycle mid-infrared lasers. These findings are important for the development of high-brightness soft X-ray sources for applications in spectroscopy and imaging.Comment: 18 pages, 4 figure