Safety and immunogenicity of an MF59™-adjuvanted subunit influenza vaccine in elderly Chinese subjects

BACKGROUND: The safety and immunogenicity of an MF59™-adjuvanted subunit influenza vaccine (Sub/MF59™; FLUAD(®), Novartis Vaccines) was evaluated among elderly Chinese subjects (≥ 60 years of age). After a preliminary Phase I, open-label study (n = 25) to assess safety 1–14 days post-vaccination, a comparative observer-blind, randomised, controlled clinical trial (n = 600) was performed to assess safety and immunogenicity versus a non-adjuvanted subunit influenza vaccine (Subunit; Agrippal(®), Novartis Vaccines). Subjects were randomised (2:1) to receive Sub/MF59™ or Subunit. RESULTS: Both vaccines were well tolerated, with no vaccine-related serious adverse events reported during the Phase I trial. During the observer-blind study, local and systemic reactions were generally similar for both vaccines 1–22 days post-vaccination; however, injection-site induration was more frequent among the Subunit group (P < 0.05), and mild pain at the injection site and fever were more frequent among Sub/MF59™ recipients (P ≤ 0.005). Both vaccines induced a significant (P < 0.001) increase in geometric mean titres (GMTs) for the three strains tested, versus baseline; GMTs against A/H1N1, A/H3N2 and B were significantly higher in the Sub/MF59™ group (P = 0.034, P < 0.001 and P = 0.005, respectively). GMT ratios against A/H1N1, A/H3N2 and B were also significantly higher in the Sub/MF59™ group (P = 0.038, P < 0.001 and P = 0.006, respectively). Similarly, the percentage of subjects achieving seroprotection or seroconversion on Day 22 was greater for Sub/MF59™ recipients, reaching significance for A/H3N2 (P < 0.001). CONCLUSION: MF59™-adjuvanted subunit influenza vaccine is well tolerated by elderly Chinese subjects and induces a higher level of immunogenicity than a non-adjuvanted subunit influenza vaccine in this population that is at high risk of influenza-related complications. CLINICAL TRIAL REGISTRY: , NCT0031064

M2HGCL: Multi-Scale Meta-Path Integrated Heterogeneous Graph Contrastive Learning

Inspired by the successful application of contrastive learning on graphs, researchers attempt to impose graph contrastive learning approaches on heterogeneous information networks. Orthogonal to homogeneous graphs, the types of nodes and edges in heterogeneous graphs are diverse so that specialized graph contrastive learning methods are required. Most existing methods for heterogeneous graph contrastive learning are implemented by transforming heterogeneous graphs into homogeneous graphs, which may lead to ramifications that the valuable information carried by non-target nodes is undermined thereby exacerbating the performance of contrastive learning models. Additionally, current heterogeneous graph contrastive learning methods are mainly based on initial meta-paths given by the dataset, yet according to our deep-going exploration, we derive empirical conclusions: only initial meta-paths cannot contain sufficiently discriminative information; and various types of meta-paths can effectively promote the performance of heterogeneous graph contrastive learning methods. To this end, we propose a new multi-scale meta-path integrated heterogeneous graph contrastive learning (M2HGCL) model, which discards the conventional heterogeneity-homogeneity transformation and performs the graph contrastive learning in a joint manner. Specifically, we expand the meta-paths and jointly aggregate the direct neighbor information, the initial meta-path neighbor information and the expanded meta-path neighbor information to sufficiently capture discriminative information. A specific positive sampling strategy is further imposed to remedy the intrinsic deficiency of contrastive learning, i.e., the hard negative sample sampling issue. Through extensive experiments on three real-world datasets, we demonstrate that M2HGCL outperforms the current state-of-the-art baseline models.Comment: Accepted to the conference of ADMA2023 as an Oral presentatio

Reply: Does the polyubiquitination pathway operate inside intact chloroplasts to remove proteins?

The ubiquitin-proteasome system (UPS) is the pre-eminent proteolytic system in eukaryotic cells. Its components are abundant in the cytosol and nucleus, and it selectively targets many proteins in both of these compartments for degradation. However, its functions are not restricted to nucleocytosolic proteins as it is now very well established that the UPS also targets proteins in organelles. For example, endoplasmic reticulum (ER) proteins are commonly degraded by the cytosolic proteasome following their extraction (or retrotranslocation) from the organelle, in a process termed ER-associated protein degradation (ERAD). In recent years, it has emerged that even proteins in endosymbiotic organelles (mitochondria and chloroplasts) are processed by ERAD-analogous systems. Ubiquitin-dependent degradation of chloroplast-resident proteins was initially described as a regulatory mechanism governing the chloroplast protein import machinery. This so called chloroplast-associated protein degradation (CHLORAD) system was assumed to act only at the surface of the organelle owing to the physical barrier presented by the double envelope membrane. However, recent results suggested that the UPS may have a more extensive role in regulating chloroplast proteins, affecting even those located internally. Though somewhat surprising, these results were not entirely unpredictable given that there are numerous historical reports suggesting ubiquitin action in chloroplasts, and there is increasing evidence that the UPS acts on internal mitochondrial proteins. We review the relevant literature, address corresponding criticisms, and present additional data supporting the possibility of UPS action inside chloroplasts

Overexpression of Testes-Specific Protease 50 (TSP50) Predicts Poor Prognosis in Patients with Gastric Cancer

Purpose. To investigate the expression of TSP50 protein in human gastric cancers and its correlation with clinical/prognostic significance. Methods. Immunohistochemistry (IHC) analysis of TSP50 was performed on a tissue microarray (TMA) containing 334 primary gastric cancers. Western blot was carried out to confirm the expression of TSP50 in gastric cancers. Results. IHC analysis revealed high expression of TSP50 in 57.2% human gastric cancer samples (191 out of 334). However, it was poorly expressed in all of the 20 adjacent nontumor tissues. This was confirmed by western blot, which showed significantly higher levels of TSP50 expression in gastric cancer tissues than adjacent nontumor tissues. A significant association was found between high levels of TSP50 and clinicopathological characteristics including junior age at surgery (P=0.001), later TNM stage (P=0.000), and present lymph node metastases (P=0.003). The survival of gastric cancer patients with high expression of TSP50 was significantly shorter than that of the patients with low levels of TSP50 (P=0.021). Multivariate Cox regression analysis indicated that TSP50 overexpression was an independent prognostic factor for gastric cancer patients (P=0.017). Conclusions. Our data demonstrate that elevated TSP50 protein expression could be a potential predictor of poor prognosis in gastric cancer patients

Long-term antibody persistence study (3 years after last dose) of the 7-valent pneumococcal conjugate vaccine in young children in China

AbstractBackgroundIn a previous study, Chinese infants were vaccinated with 7-valent pneumococcal conjugate vaccine (PCV7) ⩾7days before routine diphtheria, tetanus, and acellular pertussis vaccine (DTaP); PCV7 administered concomitantly with DTaP (PCV7+DTaP); or DTaP alone. This study examined antibody persistence at a single time point 3years after the last vaccination.MethodsChildren who participated in the prior PCV7 study were eligible to participate. A single blood sample was drawn at enrollment. Immunoglobulin G (IgG) geometric mean concentrations (GMCs) specific to the PCV7 serotypes and percentages of subjects with IgG ⩾0.35μg/mL were compared for subjects receiving PCV7 versus PCV7+DTaP (concomitant) and for PCV7 or PCV7+DTaP (concomitant) versus DTaP alone. IgG concentrations at 3years after the last vaccination were also compared with those after the infant series and toddler dose.ResultsThree years after the last vaccination with PCV7 or PCV7+DTaP (concomitant), IgG GMCs for most PCV7 serotypes were lower than after the infant series or toddler dose but remained above prevaccination concentrations. IgG GMC were similar between the PCV7 and PCV7+DTaP (concomitant) groups for 5 out of 7 serotypes but serotypes 4 and 19F were significantly lower in the PCV7+DTaP (concomitant) recipients. Three years after the last vaccination, IgG GMCs were significantly higher for 6 of 7 PCV7 serotypes among those receiving PCV7 or PCV7+DTaP (concomitant) compared with recipients of DTaP alone. Among subjects receiving DTaP alone, serotype-specific antibody concentrations were significantly higher for all serotypes 3years after the last vaccination compared with after the infant series.ConclusionThree years after PCV7 vaccination, serotype-specific antibodies were lower than after the primary infant series but higher than prevaccination levels and higher among subjects who received PCV7 compared with those who did not. The immune response was comparable in children who received PCV7 with and without concomitant DTaP.Clinical Trial Registration: NCT0129854

Advances in Chinese Arctic and subarctic research in marine biology and ecology with emphasis on the Pacific Arctic sector

The Arctic is one of the most sensitive regions that respond through feedback to global climate changes. Climatic, hydrological and ecological changes in the Arctic are clear evidence of global warming. In 2012 and 2014, the 5th and 6th Chinese National Arctic Research Expeditions undertook studies in the Bering Sea, the Arctic Ocean (including the Chukchi Sea), and the Norwegian Sea. These studies provided us with a better understanding of the marine biology and ecology in the Arctic and subarctic regions, particularly in the Pacific Arctic sector. Rapid changes observed in the Arctic environment include the shrinking of cold-water masses in the Bering Sea in the summer, and elevated water temperatures promoting phytoplankton blooms, leading to an increase in phytoplankton transferred to higher trophic levels. As a result, the transfer efficiency of organic matter toward the bottom weakened, leading to a reduction in benthic biomass. This is consistent with expectations that the overall carbon and energy flux will ultimately switch from the dominant mode of sea ice–algae–benthos to one of phytoplankton–zooplankton. Influenced by Pacific water inflow, fluvial runoff and melting sea ice, the Chukchi Sea exhibited different responses to various environmental changes. Interactions between water masses led to other interannual ecological shifts. With the increase in sea ice melt and sunlight in the central region of the Arctic Ocean, the relative abundance of heterotrophic bacteria is expected to increase, and play a vital role in the Arctic microbial loop

OmniForce: On Human-Centered, Large Model Empowered and Cloud-Edge Collaborative AutoML System

Automated machine learning (AutoML) seeks to build ML models with minimal human effort. While considerable research has been conducted in the area of AutoML in general, aiming to take humans out of the loop when building artificial intelligence (AI) applications, scant literature has focused on how AutoML works well in open-environment scenarios such as the process of training and updating large models, industrial supply chains or the industrial metaverse, where people often face open-loop problems during the search process: they must continuously collect data, update data and models, satisfy the requirements of the development and deployment environment, support massive devices, modify evaluation metrics, etc. Addressing the open-environment issue with pure data-driven approaches requires considerable data, computing resources, and effort from dedicated data engineers, making current AutoML systems and platforms inefficient and computationally intractable. Human-computer interaction is a practical and feasible way to tackle the problem of open-environment AI. In this paper, we introduce OmniForce, a human-centered AutoML (HAML) system that yields both human-assisted ML and ML-assisted human techniques, to put an AutoML system into practice and build adaptive AI in open-environment scenarios. Specifically, we present OmniForce in terms of ML version management; pipeline-driven development and deployment collaborations; a flexible search strategy framework; and widely provisioned and crowdsourced application algorithms, including large models. Furthermore, the (large) models constructed by OmniForce can be automatically turned into remote services in a few minutes; this process is dubbed model as a service (MaaS). Experimental results obtained in multiple search spaces and real-world use cases demonstrate the efficacy and efficiency of OmniForce

A new squat lobster species of the genus Munida Leach, 1820 (Crustacea: Anomura: Galatheoidea: Munididae) from hydrothermal vents on the Eastern Pacific Rise

Liu, Xinming, Li, Xinzheng, Lin, Rongcheng (2020): A new squat lobster species of the genus Munida Leach, 1820 (Crustacea: Anomura: Galatheoidea: Munididae) from hydrothermal vents on the Eastern Pacific Rise. Zootaxa 4743 (1): 131-136, DOI: 10.11646/zootaxa.4743.1.1