Development of the WeChat Public Account I Love Parasitology and its Preliminary Application in the Teaching of Human Parasitology.

OBJECTIVE: To better construct teaching resources, enhance real-time interaction and feedback between teachers and students in and out of class, and improve the teaching quality of parasitology, our team set up a WeChat public account I love Parasitology. METHODS: The data sources were mainly from original pictures and multimedia materials of different parasites collected and produced by our team, as well as related materials collected from traditional publications and digital media. With the instant interactive platform, course schedules and corresponding teaching contents were sent by push notifications, case-based learning was carried out, and 2-way communication between students and teachers was achieved. Teaching effectiveness was assessed using a self-evaluation questionnaire. RESULTS: A WeChat public account suitable for our daily teaching of parasitology was established. The second recursion and implementation of the learning resources allowed students to conduct in-depth reading and get unrestricted access to high-quality resources through the public account. In addition, all contents were in digital forms and made the original resources reborn, which would make up for our current and future shortage of physical teaching specimens. Moreover, the results from the questionnaire indicated that all these actions encouraged students to master theoretical knowledge, improved their abilities of case analysis and communication, and increased their knowledge of academic progress. CONCLUSION: Our WeChat public account can provide excellent learning materials for students and is a good supplement to the routine education of human parasitology.

Variants in BSN gene associated with epilepsy with favourable outcome.

BACKGROUND: BSN gene encodes Bassoon, an essential protein to assemble the cytomatrix at the active zone of neurotransmitter release. This study aims to explore the relationship between BSN variants and epilepsy. METHODS: Whole-exome sequencing was performed in a cohort of 313 cases (trios) with epilepsies of unknown causes. Additional cases with BSN variants were collected from China Epilepsy Gene V.1.0 Matching Platform. The Clinical Validity Framework of ClinGen was used to evaluate the relationship between BSN variants and epilepsy. RESULTS: Four pairs of compound heterozygous variants and one cosegregating heterozygous missense variant in BSN were identified in five unrelated families. These variants presented statistically higher frequency in the case cohort than in controls. Additional two de novo heterozygous nonsense variants and one cosegregating heterozygous missense variant were identified in three unrelated cases from the gene matching platform, which were not present in the Genome Aggregation Database. The missense variants tended to be located in C-terminus, including the two monoallelic missense variants. Protein modelling showed that at least one missense variant in each pair of compound heterozygous variants had hydrogen bond alterations. Clinically, two cases were diagnosed as idiopathic generalised epilepsy, two as focal epilepsy and the remaining four as epilepsy with febrile seizures plus. Seven out of eight probands showed infancy or childhood-onset epilepsy. Eight out of 10 affected individuals had a history of febrile convulsions. All the cases were seizure-free. The cases with monoallelic variants achieved seizure-free without treatment or under monotherapy, while cases with biallelic missense variants mostly required combined therapy. The evidence from ClinGen Framework suggested an association between BSN variants and epilepsy. CONCLUSION: The BSN gene was potentially a novel candidate gene for epilepsy. The phenotypical severity was associated with the genotypes and the molecular subregional effects of the variants.

Intramuscular injection of a mixture of COVID-19 peptide vaccine and tetanus vaccine in horse induced neutralizing antibodies against authentic virus of SARS-CoV-2 Delta variant.

Peptide vaccine is not effective due to its low immunogenicity. To improve the efficacy of peptide vaccine against COVID-19, a novel method was developed by mixing a COVID-19 peptide vaccine with a tetanus vaccine. In this study, intramuscular injection of a mixture of COVID-19 peptide vaccine and tetanus vaccine twice, i.e., first dose on day 0 and second dose on day 21, induced neutralizing antibodies against authentic virus of SARS-CoV-2 Delta variant in a horse. Horse serum of day 35, i.e., two weeks after the second dose, neutralized authentic virus of SARS-CoV-2 Delta variant, equal to half effectiveness of human serum from vaccinees of Moderna COVID-19 vaccine. However, neither horse serum nor human serum neutralized Omicron variant authentic virus. No side effects were observed after each dose. This study indicates intramuscular injection of a mixture of COVID-19 peptide vaccine and tetanus vaccine may work in humans to improve peptide vaccine efficacy against SARS-CoV-2.

CHD4 variants are associated with childhood idiopathic epilepsy with sinus arrhythmia.

AIMS: CHD4 gene, encoding chromodomain helicase DNA-binding protein 4, is a vital gene for fetal development. In this study, we aimed to explore the association between CHD4 variants and idiopathic epilepsy. METHODS: Trios-based whole-exome sequencing was performed in a cohort of 482 patients with childhood idiopathic epilepsy. The Clinical Validity Framework of ClinGen and an evaluating method from five clinical-genetic aspects were used to determine the association between CHD4 variants and epilepsy. RESULTS: Four novel heterozygous missense mutations in CHD4, including two de novo mutations (c.1597A>G/p.K533E and c.4936G>A/p.E1646K) and two inherited mutations with co-segregation (c.856C>G/p.P286A and c.4977C>G/p.D1659E), were identified in four unrelated families with eight individuals affected. Seven affected individuals had sinus arrhythmia. From the molecular sub-regional point of view, the missense mutations located in the central regions from SNF2-like region to DUF1087 domain were associated with multisystem developmental disorders, while idiopathic epilepsy-related mutations were outside this region. Strong evidence from ClinGen Clinical Validity Framework and evidences from four of the five clinical-genetic aspects suggested an association between CHD4 variants and epilepsy. CONCLUSIONS: CHD4 was potentially a candidate pathogenic gene of childhood idiopathic epilepsy with arrhythmia. The molecular sub-regional effect of CHD4 mutations helped explaining the mechanisms underlying phenotypic variations.

Evaluation of AutoLumo A2000 Chemiluminescent Immunoassay for Detection of Respiratory Syncytial Virus and Adenovirus IgM Antibodies.

BACKGROUND: Respiratory syncytial virus and adenovirus are seasonal diseases that cause an enormous burden on health systems. Previously, our lab uses DHI D3-Ultra DFA for detecting antigen of respiratory syncytial virus (RSV) and adenovirus (ADV). This article will evaluate the performance of AutoLumo RSV-IgM and ADV-IgM assays compared to D3-Ultra DFA method. METHODS: We used quality control specimens to evaluate precision, cross-reactivity specimen to evaluate the specificity, exogenous interferent: Hb (1,000 mg/dL); total bilirubin (50 mg/dL), ANA titer (1:10,000), RF (500 IU/mL) to evaluate interference, and paired, nasopharyngeal swab and sera specimens to evaluate clinical sensitivity and specificity. RESULTS: AutoLumo RSV-IgM and ADV-IgM assay show good precision and no cross-reactivity with other pathogen-specific IgM antibodies; no hook effect; exogenous interferent substance: Hb < 1,000 mg/dL; total bilirubin < 50 mg/dL, ANA titer < 1:10,000, and RF < 500 IU/mL showed no interference to RSV-IgM and ADV-IgM antibodies. The paired comparison test showed that RSV-IgM and ADV-IgM appear partly on the fifth day of the disease and peaked on days six to fourteen. CONCLUSIONS: AutoLumo RSV-IgM and ADV-IgM have good performance, but their sensitivities await further improvements.

Heterozygous PGM3 Variants Are Associated With Idiopathic Focal Epilepsy With Incomplete Penetrance.

INTRODUCTION: Idiopathic focal epilepsy (IFE) is a group of self-limited epilepsies. The etiology for the majority of the patients with IFE remains elusive. We thus screened disease-causing variants in the patients with IFE. METHODS: Whole-exome sequencing was performed in a cohort of 323 patients with IFE. Protein modeling was performed to predict the effects of missense variants. The genotype-phenotype correlation of the newly defined causative gene was analyzed. RESULTS: Four novel heterozygous variants in PGM3, including two de novo variants, were identified in four unrelated individuals with IFE. The variants included one truncating variant (c.1432C > T/p.Q478X) and three missense variants (c.478C > T/p.P160S, c.1239C > G/p.N413K, and c.1659T > A/p.N553K), which had no allele frequency in the gnomAD database. The missense variants were predicted to be damaging and affect hydrogen bonds with surrounding amino acids. Mutations Q478X, P160S, and N413K were associated with benign childhood epilepsy with centrotemporal electroencephalograph (EEG) spikes. P160S and N413K were located in the inner side of the enzyme active center. Mutation N553K was associated with benign occipital epilepsy with incomplete penetrance, located in the C-terminal of Domain 4. Further analysis demonstrated that previously reported biallelic PGM3 mutations were associated with severe immunodeficiency and/or congenital disorder of glycosylation, commonly accompanied by neurodevelopmental abnormalities, while monoallelic mutations were associated with milder symptoms like IFE. CONCLUSION: The genetic and molecular evidence from the present study implies that the PGM3 variants identified in IFE patients lead to defects of the PGM3 gene, suggesting that the PGM3 gene is potentially associated with epilepsy. The genotype-phenotype relationship of PGM3 mutations suggested a quantitative correlation between genetic impairment and phenotypic severity, which helps explain the mild symptoms and incomplete penetrance in individuals with IFE.

Research on a Simulation Method of the Millimeter Wave Radar Virtual Test Environment for Intelligent Driving.

This study addresses the virtual testing of intelligent driving, examines the key problems in modeling and simulating millimeter wave radar environmental clutter, and proposes a modeling and simulation method for the environmental clutter of millimeter wave radar in intelligent driving. First, based on the attributes of intelligent vehicle millimeter wave radar, the classification characteristics of the traffic environment of an intelligent vehicle and the generation mechanism of radar environmental clutter are analyzed. Next, the statistical distribution characteristics of the clutter amplitude, the distribution characteristics of the power spectrum, and the electromagnetic dielectric characteristics are analyzed. The simulation method of radar clutter under environmental conditions such as road surface, rainfall, snowfall, and fog are deduced and designed. Finally, experimental comparison results are utilized to validate the model and simulation method.

Bio-inspired synthesis of xishacorenes A, B, and C, and a new congener from fuscol.

The xishacorene natural products are structurally unique apolar diterpenoids that feature a bicyclo[3.3.1] framework. These secondary metabolites likely arise from the well-studied, structurally related diterpenoid fuscol. In this manuscript, we describe the conversion of fuscol to xishacorenes A, B, and C, as well as a previously unreported congener, which we have named xishacorene D. In addition, we describe immunomodulatory activity studies of the xishacorenes, a structurally related analogue, and fuscol. These studies were aided by an accurate determination of the physical properties (e.g., molar extinction coefficient) of the highly apolar xishacorenes.

A Novel Method to Enable the Awareness Ability of Non-V2V-Equipped Vehicles in Vehicular Networks.

Autonomous vehicles need to have sufficient perception of the surrounding environment to produce appropriate driving behavior. The Vehicle-to-Vehicle (V2V) communication technology can exchange the speed, position, direction, and other information between autonomous vehicles to improve the sensing ability of the traditional on-board sensors. For example, V2V communication technology does not have a blind spot like a conventional on-board sensor, and V2V communication is not easily affected by weather conditions. However, it is almost impossible to make every vehicle a V2V-equipped vehicle in the real environment due to reasons such as policy and user choice. Low penetration of V2V-equipped vehicles greatly reduces the performance of the traditional V2V system. In this paper, however, we propose a novel method that can extend the awareness ability of the traditional V2V system without adding much extra investment. In the traditional V2V system, only a V2V-equipped vehicle can broadcast its own location information. However, the situation is somewhat different in our V2V system. Although non-V2V-equipped vehicles cannot broadcast their own location information, we can let V2V-equipped vehicle with radar and other sensors detect the location information of the surrounding non-V2V-equipped vehicles and then broadcast it out. Therefore, we think that a non-V2V-equipped vehicle can also broadcast its own location information. In this way, we greatly extend the awareness ability of the traditional V2V system. The proposed method is validated by real experiments and simulation experiments.

Anchor Generation Optimization and Region of Interest Assignment for Vehicle Detection.

Region proposal network (RPN) based object detection, such as Faster Regions with CNN (Faster R-CNN), has gained considerable attention due to its high accuracy and fast speed. However, it has room for improvements when used in special application situations, such as the on-board vehicle detection. Original RPN locates multiscale anchors uniformly on each pixel of the last feature map and classifies whether an anchor is part of the foreground or background with one pixel in the last feature map. The receptive field of each pixel in the last feature map is fixed in the original faster R-CNN and does not coincide with the anchor size. Hence, only a certain part can be seen for large vehicles and too much useless information is contained in the feature for small vehicles. This reduces detection accuracy. Furthermore, the perspective projection results in the vehicle bounding box size becoming related to the bounding box position, thereby reducing the effectiveness and accuracy of the uniform anchor generation method. This reduces both detection accuracy and computing speed. After the region proposal stage, many regions of interest (ROI) are generated. The ROI pooling layer projects an ROI to the last feature map and forms a new feature map with a fixed size for final classification and box regression. The number of feature map pixels in the projected region can also influence the detection performance but this is not accurately controlled in former works. In this paper, the original faster R-CNN is optimized, especially for the on-board vehicle detection. This paper tries to solve these above-mentioned problems. The proposed method is tested on the KITTI dataset and the result shows a significant improvement without too many tricky parameter adjustments and training skills. The proposed method can also be used on other objects with obvious foreshortening effects, such as on-board pedestrian detection. The basic idea of the proposed method does not rely on concrete implementation and thus, most deep learning based object detectors with multiscale feature maps can be optimized with it.

Recombinant Listeria promotes tumor rejection by CD8+ T cell-dependent remodeling of the tumor microenvironment.

Agents that remodel the tumor microenvironment (TME), prime functional tumor-specific T cells, and block inhibitory signaling pathways are essential components of effective immunotherapy. We are evaluating live-attenuated, double-deleted Listeria monocytogenes expressing tumor antigens (LADD-Ag) in the clinic. Here we show in numerous mouse models that while treatment with nonrecombinant LADD induced some changes in the TME, no antitumor efficacy was observed, even when combined with immune checkpoint blockade. In contrast, LADD-Ag promoted tumor rejection by priming tumor-specific KLRG1+PD1loCD62L- CD8+ T cells. These IFNγ-producing effector CD8+ T cells infiltrated the tumor and converted the tumor from an immunosuppressive to an inflamed microenvironment that was characterized by a decrease in regulatory T cells (Treg) levels, a proinflammatory cytokine milieu, and the shift of M2 macrophages to an inducible nitric oxide synthase (iNOS)+CD206- M1 phenotype. Remarkably, these LADD-Ag-induced tumor-specific T cells persisted for more than 2 months after primary tumor challenge and rapidly controlled secondary tumor challenge. Our results indicate that the striking antitumor efficacy observed in mice with LADD-based immunotherapy stems from TME remodeling which is a direct consequence of eliciting potent, systemic tumor-specific CD8+ T cells.

The Joint Adaptive Kalman Filter (JAKF) for Vehicle Motion State Estimation.

This paper proposes a multi-sensory Joint Adaptive Kalman Filter (JAKF) through extending innovation-based adaptive estimation (IAE) to estimate the motion state of the moving vehicles ahead. JAKF views Lidar and Radar data as the source of the local filters, which aims to adaptively adjust the measurement noise variance-covariance (V-C) matrix 'R' and the system noise V-C matrix 'Q'. Then, the global filter uses R to calculate the information allocation factor 'ß' for data fusion. Finally, the global filter completes optimal data fusion and feeds back to the local filters to improve the measurement accuracy of the local filters. Extensive simulation and experimental results show that the JAKF has better adaptive ability and fault tolerance. JAKF enables one to bridge the gap of the accuracy difference of various sensors to improve the integral filtering effectivity. If any sensor breaks down, the filtered results of JAKF still can maintain a stable convergence rate. Moreover, the JAKF outperforms the conventional Kalman filter (CKF) and the innovation-based adaptive Kalman filter (IAKF) with respect to the accuracy of displacement, velocity, and acceleration, respectively.

AST: Activity-Security-Trust driven modeling of time varying networks.

Network modeling is a flexible mathematical structure that enables to identify statistical regularities and structural principles hidden in complex systems. The majority of recent driving forces in modeling complex networks are originated from activity, in which an activity potential of a time invariant function is introduced to identify agents' interactions and to construct an activity-driven model. However, the new-emerging network evolutions are already deeply coupled with not only the explicit factors (e.g. activity) but also the implicit considerations (e.g. security and trust), so more intrinsic driving forces behind should be integrated into the modeling of time varying networks. The agents undoubtedly seek to build a time-dependent trade-off among activity, security, and trust in generating a new connection to another. Thus, we reasonably propose the Activity-Security-Trust (AST) driven model through synthetically considering the explicit and implicit driving forces (e.g. activity, security, and trust) underlying the decision process. AST-driven model facilitates to more accurately capture highly dynamical network behaviors and figure out the complex evolution process, allowing a profound understanding of the effects of security and trust in driving network evolution, and improving the biases induced by only involving activity representations in analyzing the dynamical processes.

Interleukin-33 promotes Th2 immune responses in infected mice with Schistosoma japonicum.

IL-33, a new member of the IL-1 cytokine family, is associated with many infectious diseases. IL-33 not only is crucial for induction of Th2 polarized responses, but also is involved in induction of inflammation as a proinflammatory cytokine. Whether IL-33 leads to beneficial or worsening outcomes depends on the immune mechanism underlying the pathogensis of each disease condition. This study was to elucidate the role of IL-33 in schistosomiasis japonica in a mouse model. Our results demonstrated that serum levels of IL-33 from infected mice with Schistosoma japonicum began to rise at 1 week postinfection (pi) and reached a peak in 7 weeks pi, and then remained a plateau for 2 weeks, after which its level gradually decreased until 12 weeks pi. Compared with the infection control, exogenous IL-33 administration could increase a Th2 polarized immune response (evidenced by higher levels of IL-5, IL-10, and IL-13, along with lower level of IFN-γ) at 6 weeks pi. Meanwhile, this Th2 polarization was associated with higher infection intensity and liver immunopathology in infected mice, whereas injection of anti-IL-33 mAb into infected mice induced adverse effects on these above immune parameters and immunopathology. These data suggest that IL-33 might act as an inducer of Th2 polarization and plays a crucial role in immunopathology in murine schistosomiasis japonica.

Antitumor immunity. A shed NKG2D ligand that promotes natural killer cell activation and tumor rejection.

Immune cells, including natural killer (NK) cells, recognize transformed cells and eliminate them in a process termed immunosurveillance. It is thought that tumor cells evade immunosurveillance by shedding membrane ligands that bind to the NKG2D-activating receptor on NK cells and/or T cells, and desensitize these cells. In contrast, we show that in mice, a shed form of MULT1, a high-affinity NKG2D ligand, causes NK cell activation and tumor rejection. Recombinant soluble MULT1 stimulated tumor rejection in mice. Soluble MULT1 functions, at least in part, by competitively reversing a global desensitization of NK cells imposed by engagement of membrane NKG2D ligands on tumor-associated cells, such as myeloid cells. The results overturn conventional wisdom that soluble ligands are always inhibitory and suggest a new approach for cancer immunotherapy.

Cytokine therapy reverses NK cell anergy in MHC-deficient tumors.

Various cytokines have been evaluated as potential anticancer drugs; however, most cytokine trials have shown relatively low efficacy. Here, we found that treatments with IL-12 and IL-18 or with a mutant form of IL-2 (the "superkine" called H9) provided substantial therapeutic benefit for mice specifically bearing MHC class I-deficient tumors, but these treatments were ineffective for mice with matched MHC class I+ tumors. Cytokine efficacy was linked to the reversal of the anergic state of NK cells that specifically occurred in MHC class I-deficient tumors, but not MHC class I+ tumors. NK cell anergy was accompanied by impaired early signal transduction and was locally imparted by the presence of MHC class I-deficient tumor cells, even when such cells were a minor population in a tumor mixture. These results demonstrate that MHC class I-deficient tumor cells can escape from the immune response by functionally inactivating NK cells, and suggest cytokine-based immunotherapy as a potential strategy for MHC class I-deficient tumors. These results suggest that such cytokine therapies would be optimized by stratification of patients. Moreover, our results suggest that such treatments may be highly beneficial in the context of therapies to enhance NK cell functions in cancer patients.

Recognition of tumors by the innate immune system and natural killer cells.

In recent years, roles of the immune system in immune surveillance of cancer have been explored using a variety of approaches. The roles of the adaptive immune system have been a major emphasis, but increasing evidence supports a role for innate immune effector cells such as natural killer (NK) cells in tumor surveillance. Here, we discuss some of the evidence for roles in tumor surveillance of innate immune cells. In particular, we focus on NK cells and other immune cells that express germline-encoded receptors, often labeled NK receptors. The impact of these receptors and the cells that express them on tumor suppression is summarized. We discuss in detail some of the pathways and events in tumor cells that induce or upregulate cell-surface expression of the ligands for these receptors, and the logic of how those pathways serve to identify malignant, or potentially malignant cells. How tumors often evade tumor suppression mediated by innate killer cells is another major subject of the review. We end with a discussion on some of the implications of the various findings with respect to possible therapeutic approaches.

Regulation of ligands for the NKG2D activating receptor.

NKG2D is an activating receptor expressed by all NK cells and subsets of T cells. It serves as a major recognition receptor for detection and elimination of transformed and infected cells and participates in the genesis of several inflammatory diseases. The ligands for NKG2D are self-proteins that are induced by pathways that are active in certain pathophysiological states. NKG2D ligands are regulated transcriptionally, at the level of mRNA and protein stability, and by cleavage from the cell surface. In some cases, ligand induction can be attributed to pathways that are activated specifically in cancer cells or infected cells. We review the numerous pathways that have been implicated in the regulation of NKG2D ligands, discuss the pathologic states in which those pathways are likely to act, and attempt to synthesize the findings into general schemes of NKG2D ligand regulation in NK cell responses to cancer and infection.