New Concepts in Immunity to Neisseria Gonorrhoeae: Innate Responses and Suppression of Adaptive Immunity Favor the Pathogen, Not the Host

It is well-known that gonorrhea can be acquired repeatedly with no apparent development of protective immunity arising from previous episodes of infection. Symptomatic infection is characterized by a purulent exudate, but the host response mechanisms are poorly understood. While the remarkable antigenic variability displayed by Neisseria gonorrhoeae and its capacity to inhibit complement activation allow it to evade destruction by the host's immune defenses, we propose that it also has the capacity to avoid inducing specific immune responses. In a mouse model of vaginal gonococcal infection, N. gonorrhoeae elicits Th17-driven inflammatory–immune responses, which recruit innate defense mechanisms including an influx of neutrophils. Concomitantly, N. gonorrhoeae suppresses Th1- and Th2-dependent adaptive immunity, including specific antibody responses, through a mechanism involving TGF-β and regulatory T cells. Blockade of TGF-β alleviates the suppression of specific anti-gonococcal responses and allows Th1 and Th2 responses to emerge with the generation of immune memory and protective immunity. Genital tract tissues are naturally rich in TGF-β, which fosters an immunosuppressive environment that is important in reproduction. In exploiting this niche, N. gonorrhoeae exemplifies a well-adapted pathogen that proactively elicits from its host innate responses that it can survive and concomitantly suppresses adaptive immunity. Comprehension of these mechanisms of gonococcal pathogenesis should allow the development of novel approaches to therapy and facilitate the development of an effective vaccine

Adaptive Activation Network and Functional Regularization for Efficient and Flexible Deep Multi-Task Learning

Multi-task learning (MTL) is a common paradigm that seeks to improve the generalization performance of task learning by training related tasks simultaneously. However, it is still a challenging problem to search the flexible and accurate architecture that can be shared among multiple tasks. In this paper, we propose a novel deep learning model called Task Adaptive Activation Network (TAAN) that can automatically learn the optimal network architecture for MTL. The main principle of TAAN is to derive flexible activation functions for different tasks from the data with other parameters of the network fully shared. We further propose two functional regularization methods that improve the MTL performance of TAAN. The improved performance of both TAAN and the regularization methods is demonstrated by comprehensive experiments.Comment: To appear in AAAI-202

Novi VP2/VP3 rekombinantni senekavirus A izoliran u sjevernoj Kini

Senecavirus A (SVA), previously called the Seneca Valley virus, is the only member of the genus Senecavirus within the family Picornaviridae. This virus was discovered as a serendipitous finding in 2002 and named Seneca Valley virus 001 (SVV-001). SVA is an emerging pathogen that can cause vesicular lesions and epidemic transient neonatal a sharp decline in swine. In this study, an SVA strain was isolated from a pig herd in Shandong Province in China and identified as SVA-CH-SDFX-2022. The full-length genome was 7282 nucleotides (nt) in length and contained a single open reading frame (ORF), excluding the poly (A) tails of the SVA isolates. Phylogenetic analysis showed that the isolate shares its genomic organization, resembling and sharing high nucleotide identities of 90.5% to 99.6%, with other previously reported SVA isolates. The strain was proved by in vitro characterization and the results demonstrate that the virus has robust growth ability in vitro. The recombination event of the SVA-CH-SDFX-2022 isolate was found and occurred between nts 1836 and 2710, which included the region of the VP2 (partial), and VP3 (partial) genes. It shows the importance of faster vaccine development and a better understanding of virus infection and spread because of increased infection rates and huge economic losses. This novel incursion has substantial implications for the regional control of vesicular transboundary diseases, and will be available for further study of the epidemiology of porcine SVA. Our findings provide useful data for studying SVA in pigs.Senekavirus A (SVA), prije nazivan virusom doline Seneca Valley, jedini je pripadnik roda senekavirusa u porodici Picornaviridae. Virus je slučajno otkriven 2002. i nazvan virusom doline Seneca 001 (SVV-001). SVA je novi patogen koji može uzrokovati vezikularne lezije i prolaznu epidemiju novorođene prasadi s naglim gubicima u proizvodnji. U ovom je istraživanju soj SVA izoliran u populaciji svinja iz provincije Shandong u Kini i identificiran kao SVA-CHSDFX-2022. Kompletni genom izolata SVA imao je 7282 nukleotida (nt) u dužini i sadržavao je jedan otvoreni okvir za očitavanje (ORF), bez poli-A repova. Filogenetska je analiza pokazala da izolat u velikoj mjeri sadržava genomsku organizaciju i nukleotidne identitete, od 90,5 % do 99,6 %, s drugim poznatim SVA izolatima. Karakterizacija virusa je pokazala da ima veliku sposobnost rasta in vitro. Pronađena je rekombinacija izolata SVA-CH-SDFX-između nukleotida 1836 i 2710 što je uključilo regiju gena VP2 (parcijalno) i gena VP3 (parcijalno). Zbog visoke stope infektivnosti i golemih ekonomskih gubitaka važan je brži razvoj cjepiva i bolje razumijevanje zaraze. Rezultati ovog istraživanja pružaju korisne podatke za proučavanje SVA virusa, posebno s obzirom na njegovu epidemiologiju u svinja i regionalnu prekograničnu kontrolu vezikularnih bolesti

Community-based lung cancer screening by low-dose computed tomography in China:First round results and a meta-analysis

OBJECTIVE: To evaluate the efficiency of low-dose computed tomography (LDCT) screening for lung cancer in China by analyzing the baseline results of a community-based screening study accompanied with a meta-analysis. METHODS: A first round of community-based lung cancer screening with LDCT was conducted in Tianjin, China, and a systematic literature search was performed to identify LDCT screening and registry-based clinical studies for lung cancer in China. Baseline results in the community-based screening study were described by participant risk level and the lung cancer detection rate was compared with the pooled rate among the screening studies. The percentage of patients per stage was compared between the community-based study and screening and clinical studies. RESULTS: In the community-based study, 5523 participants (43.6% men) underwent LDCT. The lung cancer detection rate was 0.5% (high-risk, 1.2%; low-risk, 0.4%), with stage I disease present in 70.0% (high-risk, 50.0%; low-risk, 83.3%), and the adenocarcinoma present in 84.4% (high-risk, 61.5%; low-risk, 100%). Among all screen-detected lung cancer, women accounted for 8.3% and 66.7% in the high- and low-risk group, respectively. In the screening studies from mainland China, the lung cancer detection rate 0.6% (95 %CI: 0.3%-0.9%) for high-risk populations. The proportions with carcinoma in situ and stage I disease in the screening and clinical studies were 76.4% (95 %CI: 66.3%-85.3%) and 15.2% (95 %CI: 11.8%-18.9%), respectively. CONCLUSIONS: The stage shift of lung cancer due to screening suggests a potential effectiveness of LDCT screening in China. Nearly 70% of screen-detected lung cancers in low-risk populations are identified in women

A unified neurocognitive model of semantics language social behaviour and face recognition in semantic dementia

Funder: Chinese Scholarship CouncilFunder: National Key R&D Program of China (2016YFC1306305)Funder: ERC grant (GAP: 670428 - BRAIN2MIND_NEUROCOMP)Abstract: The anterior temporal lobes (ATL) have become a key brain region of interest in cognitive neuroscience founded upon neuropsychological investigations of semantic dementia (SD). The purposes of this investigation are to generate a single unified model that captures the known cognitive-behavioural variations in SD and map these to the patients’ distribution of frontotemporal atrophy. Here we show that the degree of generalised semantic impairment is related to the patients’ total, bilateral ATL atrophy. Verbal production ability is related to total ATL atrophy as well as to the balance of left > right ATL atrophy. Apathy is found to relate positively to the degree of orbitofrontal atrophy. Disinhibition is related to right ATL and orbitofrontal atrophy, and face recognition to right ATL volumes. Rather than positing mutually-exclusive sub-categories, the data-driven model repositions semantics, language, social behaviour and face recognition into a continuous frontotemporal neurocognitive space