Bis[(m-phenyl­enedimethyl­ene)­diammonium] tetra­deca­borate

The title compound 2C8H14N2 2+·[B14O20(OH)6]4−, contains diprotonated C8H14N2 2+ cations and centrosymmetric tetra­deca­borate anions. The crystal structure is stabilized by O—H⋯O and N—H⋯O hydrogen bonds

The Protective Antibodies Induced by a Novel Epitope of Human TNF-α Could Suppress the Development of Collagen-Induced Arthritis

Tumor necrosis factor alpha (TNF-α) is a major inflammatory mediator that exhibits actions leading to tissue destruction and hampering recovery from damage. At present, two antibodies against human TNF-α (hTNF-α) are available, which are widely used for the clinic treatment of certain inflammatory diseases. This work was undertaken to identify a novel functional epitope of hTNF-α. We performed screening peptide library against anti-hTNF-α antibodies, ELISA and competitive ELISA to obtain the epitope of hTNF-α. The key residues of the epitope were identified by means of combinatorial alanine scanning and site-specific mutagenesis. The N terminus (80–91 aa) of hTNF-α proved to be a novel epitope (YG1). The two amino acids of YG1, proline and valine, were identified as the key residues, which were important for hTNF-α biological function. Furthermore, the function of the epitope was addressed on an animal model of collagen-induced arthritis (CIA). CIA could be suppressed in an animal model by prevaccination with the derivative peptides of YG1. The antibodies of YG1 could also inhibit the cytotoxicity of hTNF-α. These results demonstrate that YG1 is a novel epitope associated with the biological function of hTNF-α and the antibodies against YG1 can inhibit the development of CIA in animal model, so it would be a potential target of new therapeutic antibodies

Assessment of density functional approximations for the hemibonded structure of water dimer radical cation

Due to the severe self-interaction errors associated with some density functional approximations, conventional density functionals often fail to dissociate the hemibonded structure of water dimer radical cation (H2O)2+ into the correct fragments: H2O and H2O+. Consequently, the binding energy of the hemibonded structure (H2O)2+ is not well-defined. For a comprehensive comparison of different functionals for this system, we propose three criteria: (i) The binding energies, (ii) the relative energies between the conformers of the water dimer radical cation, and (iii) the dissociation curves predicted by different functionals. The long-range corrected (LC) double-hybrid functional, omegaB97X-2(LP) [J.-D. Chai and M. Head-Gordon, J. Chem. Phys., 2009, 131, 174105.], is shown to perform reasonably well based on these three criteria. Reasons that LC hybrid functionals generally work better than conventional density functionals for hemibonded systems are also explained in this work.Comment: 10 pages, 5 figures, 4 table

Effects of Scutellarin on MUC5AC Mucin Production Induced by Human Neutrophil Elastase or Interleukin 13 on Airway Epithelial Cells

Scutellarin is a flavonoid extracted from a traditional Chinese herb, Erigeron breviscapus. The present study investigated the effect of scutellarin on MUC5AC mucin production and the possible mechanism. Human bronchial epithelial 16 (HBE16) cells were pretreated with scutellarin for 60 min, and then exposed to human neutrophil elastase (HNE) or interleukin (IL)-13 for 12 hr. RT-PCR and ELISA were performed to measure the amount of MUC5AC mucin production. The results showed that scutellarin inhibited MUC5AC expression both in mRNA and protein level induced by HNE in a concentration-dependent manner. However, scutellarin failed to inhibit MUC5AC mucin production induced by IL-13. To investigate the intracellular mechanisms associated with the effect of scutellarin on MUC5AC mucin production, western blotting was carried out to examine the phosphorylation of protein kinase C (PKC), signal transducer and activator of transcription 6 (STAT6) and extracellular signal-regulated kinase 1/2 (ERK1/2). The phosphorylation of PKC and ERK1/2 was attenuated after treatment with scutellarin, whereas STAT6 was not significantly affected. Therefore, it is suggested that scutellarin down-regulates MUC5AC mucin production on HBE16 cells via ERK-dependent and PKC-dependent pathways

PCDHGB7 hypermethylation-based Cervical cancer Methylation (CerMe) detection for the triage of high-risk human papillomavirus-positive women:a prospective cohort study

BackgroundImplementation of high-risk human papillomavirus (hrHPV) screening has greatly reduced the incidence and mortality of cervical cancer. However, a triage strategy that is effective, noninvasive, and independent from the subjective interpretation of pathologists is urgently required to decrease unnecessary colposcopy referrals in hrHPV-positive women.MethodsA total of 3251 hrHPV-positive women aged 30–82 years (median = 41 years) from International Peace Maternity and Child Health Hospital were included in the training set (n = 2116) and the validation set (n = 1135) to establish Cervical cancer Methylation (CerMe) detection. The performance of CerMe as a triage for hrHPV-positive women was evaluated.ResultsCerMe detection efficiently distinguished cervical intraepithelial neoplasia grade 2 or worse (CIN2 +) from cervical intraepithelial neoplasia grade 1 or normal (CIN1 −) women with excellent sensitivity of 82.4% (95% CI = 72.6 ~ 89.8%) and specificity of 91.1% (95% CI = 89.2 ~ 92.7%). Importantly, CerMe showed improved specificity (92.1% vs. 74.9%) in other 12 hrHPV type-positive women as well as superior sensitivity (80.8% vs. 61.5%) and specificity (88.9% vs. 75.3%) in HPV16/18 type-positive women compared with cytology testing. CerMe performed well in the triage of hrHPV-positive women with ASC-US (sensitivity = 74.4%, specificity = 87.5%) or LSIL cytology (sensitivity = 84.4%, specificity = 83.9%).ConclusionsPCDHGB7 hypermethylation-based CerMe detection can be used as a triage strategy for hrHPV-positive women to reduce unnecessary over-referrals.Trial registrationChiCTR2100048972. Registered on 19 July 2021.<br/

Salmonella enterica serovar Paratyphi A-induced immune response in Caenorhabditis elegans depends on MAPK pathways and DAF-16

Salmonella enterica serovar Paratyphi A (S. Paratyphi A) is a pathogen that can cause enteric fever. According to the recent epidemic trends of typhoid fever, S. Paratyphi A has been the major important causative factor in paratyphoid fever. An effective vaccine for S. Paratyphi A has not been developed, which made it a tricky public health concern. Until now, how S. Paratyphi A interacts with organisms remain unknown. Here using lifespan assay, we found that S. Paratyphi A could infect Caenorhabditis elegans (C. elegans) at 25°C, and attenuate thermotolerance. The immune response of C. elegans was mediated by tir-1, nsy-1, sek-1, pmk-1, mpk-1, skn-1, daf-2 and daf-16, suggesting that S. Paratyphi A could regulate the MAPK and insulin pathways. Furthermore, we observed several phenotypical changes when C. elegans were fed S. Paratyphi A, including an accelerated decline in body movement, reduced the reproductive capacity, shortened spawning cycle, strong preference for OP50, arrested pharyngeal pumping and colonization of the intestinal lumen. The virulence of S. Paratyphi A requires living bacteria and is not mediated by secreting toxin. Using hydrogen peroxide analysis and quantitative RT-PCR, we discovered that S. Paratyphi A could increase oxidative stress and regulate the immune response in C. elegans. Our results sheds light on the infection mechanisms of S. Paratyphi A and lays a foundation for drugs and vaccine development

New Nodule Type Found in the Lungs of Pomacea canaliculata, an Intermediate Host of Angiostrongylus cantonensis

Background: Pomacea canaliculata (P.canaliculata) lung nodules, were commonly caused by Angiostrongylus cantonensis infection. Here, we found a new nodule type without any parasites. Methods: Overall, 447 P. canaliculata snails were collected in Ning Bo, Zhe Jiang, China in 2018. In order to exhibit the similarities and differences between two nodules types (2018, Huzhou Zhejiang, China), both types were collected in formalin for tissue pathological sectioning. Besides, to obtain the microbial community of the new nodule, the 18S ribosomal RNA (rRNA) gene of it was amplified and analyzed using the Illumina second-generation sequencing platform. Results: Although two nodules were found in the lungs of P. canaliculata, they were different in shape and pathology. Illumina sequencing indicated Poterioochromonas sp., a species of golden algae, might be the causing agent of the new nodule. Conclusion: We firstly found a new pathological nodule type in the lungs of P. canaliculata, and this nodule might be induced by golden algae infection, however, the direct link between the golden algae and the new nodules, as well as the nodules’ impact on the snails’ physiology and A. cantonensis infection require further study

Single Image Super-Resolution Using Multi-Scale Deep Encoder-Decoder with Phase Congruency Edge Map Guidance

This paper presents an end-to-end multi-scale deep encoder (convolution) and decoder (deconvolution) network for single image super-resolution (SISR) guided by phase congruency (PC) edge map. Our system starts by a single scale symmetrical encoder-decoder structure for SISR, which is extended to a multi-scale model by integrating wavelet multi-resolution analysis into our network. The new multi-scale deep learning system allows the low resolution (LR) input and its PC edge map to be combined so as to precisely predict the multi-scale super-resolved edge details with the guidance of the high-resolution (HR) PC edge map. In this way, the proposed deep model takes both the reconstruction of image pixels’ intensities and the recovery of multi-scale edge details into consideration under the same framework. We evaluate the proposed model on benchmark datasets of different data scenarios, such as Set14 and BSD100 - natural images, Middlebury and New Tsukuba - depth images. The evaluations based on both PSNR and visual perception reveal that the proposed model is superior to the state-of-the-art methods

Identifying patients with atrioventricular septal defect in down syndrome populations by using self-normalizing neural networks and feature selection

Atrioventricular septal defect (AVSD) is a clinically significant subtype of congenital heart disease (CHD) that severely influences the health of babies during birth and is associated with Down syndrome (DS). Thus, exploring the differences in functional genes in DS samples with and without AVSD is a critical way to investigate the complex association between AVSD and DS. In this study, we present a computational method to distinguish DS patients with AVSD from those without AVSD using the newly proposed self-normalizing neural network (SNN). First, each patient was encoded by using the copy number of probes on chromosome 21. The encoded features were ranked by the reliable Monte Carlo feature selection (MCFS) method to obtain a ranked feature list. Based on this feature list, we used a two-stage incremental feature selection to construct two series of feature subsets and applied SNNs to build classifiers to identify optimal features. Results show that 2737 optimal features were obtained, and the corresponding optimal SNN classifier constructed on optimal features yielded a Matthew’s correlation coefficient (MCC) value of 0.748. For comparison, random forest was also used to build classifiers and uncover optimal features. This method received an optimal MCC value of 0.582 when top 132 features were utilized. Finally, we analyzed some key features derived from the optimal features in SNNs found in literature support to further reveal their essential roles

A Refined Study of FCRL Genes from a Genome-Wide Association Study for Graves’ Disease

To pinpoint the exact location of the etiological variant/s present at 1q21.1 harboring FCRL1-5 and CD5L genes, we carried out a refined association study in the entire FCRL region in 1,536 patients with Graves’ disease (GD) and 1,516 sex-matched controls by imputation analysis, logistic regression, and cis-eQTL analysis. Among 516 SNPs with P<0.05 in the initial GWAS scan, the strongest signals associated with GD and correlated to FCRL3 expression were located at a cluster of SNPs including rs7528684 and rs3761959. And the allele-specific effects for rs3761959 and rs7528684 on FCRL3 expression level revealed that the risk alleles A of rs3761959 and C of rs7528684 were correlated with the elevated expression level of FCRL3 whether in PBMCs or its subsets, especially in $CD19^+$ B cells and $CD8^+$ T subsets. Next, the combined analysis with 5,300 GD cases and 4,916 control individuals confirmed FCRL3 was a susceptibility gene of GD in Chinese Han populations, and rs3761959 and rs7528684 met the genome-wide association significance level ($P_{combined}$ = 2.27×$10^{−12}$ and 7.11×$10^{−13}$, respectively). Moreover, the haplotypes with the risk allele A of rs3761959 and risk allele C of rs7528684 were associated with GD risk. Finally, our epigenetic analysis suggested the disease-associated C allele of rs7528684 increased affinity for NF-KB transcription factor. Above data indicated that FCRL3 gene and its proxy SNP rs7528684 may be involved in the pathogenesis of GD by excessive inhibiting B cell receptor signaling and the impairment of suppressing function of Tregs