Search

Abstract Background The clinical manifestations of COVID-19 range from asymptomatic, mild to moderate, severe, and critical disease. Host genetic variants were recognized to affect the disease severity. However, the genetic landscape differs among various populations. Therefore, we explored the variants associated with COVID-19 severity in the Guangdong population. Methods A total of 314 subjects were selected, of which the severe and critical COVID-19 patients were defined as “cases”, and the mild and moderate patients were defined as “control”. Twenty-two variants in interferon-related genes and FOXP4 were genotyped using the MassARRAY technology platform. Results IFN signaling gene MX1 rs17000900 CA + AA genotype was correlated with a reduced risk of severe COVID-19 in males (P = 0.001, OR = 0.050, 95%CI = 0.008–0.316). The AT haplotype comprised of MX1 rs17000900 and rs2071430 was more likely to protect against COVID-19 severity (P = 6.3E-03). FOXP4 rs1886814 CC genotype (P = 0.001, OR = 3.747, 95%CI = 1.746–8.043) and rs2894439 GA + AA genotype (P = 0.001, OR = 5.703, 95% CI = 2.045–15.903) were correlated with increased risk of severe COVID-19. Haplotype CA comprised of rs1886814 and rs2894439 was found to be correlated with adverse outcomes (P = 7.0E-04). FOXP4 rs1886814 CC (P = 0.0004) and rs2894439 GA + AA carriers had higher neutralizing antibody titers (P = 0.0018). The CA + AA genotype of MX1 rs17000900 tended to be correlated with lower neutralizing antibody titers than CC genotype (P = 0.0663), but the difference was not statistically significant. Conclusion Our study found a possible association between MX1 and FOXP4 polymorphisms and the severity of COVID-19. Distinguishing high-risk patients who develop severe COVID-19 will provide clues for early intervention and individual treatment strategies.

Interferon-induced transmembrane proteins (IFITMs) are upregulated by interferons. They are not only highly conserved in evolution but also structurally consistent and have almost identical structural domains and functional domains. They are all transmembrane proteins and have multiple heritable variations in genes. The IFITM protein family is closely related to a variety of biological functions, including antiviral immunity, tumor formation, bone metabolism, cell adhesion, differentiation, and intracellular signal transduction. The progress of the research on its structure and related functions, as represented by IFITM3, is reviewed.

The annual co-circulation of two influenza A subtypes, H1N1 and H3N2, viruses in humans poses significant public health threats worldwide. However, the continuous antigenic drift and shift of influenza viruses limited the effectiveness of current seasonal influenza vaccines, necessitating the development of new vaccines against both seasonal and pandemic viruses. One potential solution to this challenge is to improve inactivated vaccines by including multiple T-cell epitopes. In this study, we designed stabilized trimeric recombinant mosaic HA proteins named HAm, which contain the most potential HA T-cell epitopes of seasonal influenza A virus. We further evaluated the antigenicity, hemagglutinin activity, and structural integrity of HAm and compared its immunogenicity and efficacy to a commercial quadrivalent inactivated influenza vaccine (QIV) in mice. Our results demonstrated that the HAm vaccine was able to induce broadly cross-reactive antibodies and T-cell responses against homologous, heterologous, and heterosubtypic influenza-naive mice. Additionally, the HAm antigens outperformed QIV vaccine antigens by eliciting protective antibodies against panels of antigenically drifted influenza vaccine strains from 2009 to 2024 and protecting against ancestral viruses’ lethal challenge. These results suggest that the HAm vaccine is a promising potential candidate for future universal seasonal and pandemic influenza vaccine development.

Abstract The development of a universal influenza vaccine to elicit broad immune responses is essential in reducing disease burden and pandemic impact. In this study, the mosaic vaccine design strategy and genetic algorithms were utilized to optimize the seasonal influenza A virus (H1N1, H3N2) hemagglutinin (HA) and neuraminidase (NA) antigens, which also contain most potential T-cell epitopes. These mosaic immunogens were then expressed as virus-like particles (VLPs) using the baculovirus expression system. The immunogenicity and protection effectiveness of the mosaic VLPs were compared to the commercial quadrivalent inactivated influenza vaccine (QIV) in the mice model. Strong cross-reactive antibody responses were observed in mice following two doses of vaccination with the mosaic VLPs, with HI titers higher than 40 in 15 of 16 tested strains as opposed to limited cross HI antibody levels with QIV vaccination. After a single vaccination, mice also show a stronger level of cross-reactive antibody responses than the QIV. The QIV vaccinations only elicited NI antibodies to a small number of vaccine strains, and not even strong NI antibodies to its corresponding vaccine components. In contrast, the mosaic VLPs caused robust NI antibodies to all tested seasonal influenza virus vaccine strains. Here, we demonstrated the mosaic vaccines induces stronger cross-reactive antibodies and robust more T-cell responses compared to the QIV. The mosaic VLPs also provided protection against challenges with ancestral influenza A viruses of both H1 and H3 subtypes. These findings indicated that the mosaic VLPs were a promising strategy for developing a broad influenza vaccine in future.

Board games are extensively studied in the AI community because of their ability to reflect/represent real-world problems with a high-level of abstraction, and their irreplaceable role as testbeds of state-of-the-art AI algorithms. Modern board games are commonly featured with partially observable state spaces and imperfect information. Despite some recent successes in AI tackling perfect information board games like chess and Go, most imperfect information games are still challenging and have yet to be solved. This paper empirically explores the capabilities of a state-of-the-art Reinforcement Learning (RL) algorithm – Proximal Policy Optimization (PPO) in playing Ticket to Ride, a popular board game with features of imperfect information, large state-action space, and delayed rewards. This paper explores the feasibility of the proposed generalizable modelling and training schemes using a general-purpose RL algorithm with no domain knowledge-based heuristics beyond game rules, game states and scores to tackle this complex imperfect information game. The performance of the proposed methodology is demonstrated in a scaled-down version of Ticket to Ride with a range of RL agents obtained with different training schemes. All RL agents achieve clear advantages over a set of well-designed heuristic agents. The agent constructed through a self-play training scheme outperforms the other RL agents in a Round Robin tournament. The high performance and versality of this self-play agent provide a solid demonstration of the capabilities of this framework.

The shuttling of polyselenide (Li2Se2Sx) was prevented effectively by building a separator in Li-SexSy batteries. Nitrogen atoms are used to coordinate transition metal (TM=Ti, Zr, V) co-doped graphene to restrict the free shuttling of polylithium selenide (Li2Se2Sx, x = 1–6) through physical confinement and chemical adsorption. The nitrogen (N) atom assisted transition metal co-doped graphene surface to build a model of strong adsorption of cations and anions on lithium-sulfur-selenium compounds to inhibit the shuttle phenomenon. Nitrogen atoms are not only coordinately doped with transition metals, but also lithium atoms can easily form bonds to improve the adsorption strength of Li2Se2Sx on the graphene surface. The evolution of the N-type to P-type adsorption model of Li2Se2Sx on the graphene co-doped Ti-N-G surface to the Zr-N-G surface was constructed based on the phenomenon of Fermi level changes strong adsorption capacity and immobilization. The Fermi energy level of the V-N-G weak adsorption catalytic model was located between the valence and conduction bands. The doping of N and TM improves the ionic conductivity of graphene, which adsorbs Li2Se2Sx and causes a high Li diffusion barrier. A coupled physical model of ion transport and polyselenide conversion was built by adjusting the Fermi level of separator.

ObjectiveOsteonecrosis of the femoral head (ONFH) is a disabling and intractable orthopedic disease largely affecting young and middle-aged groups. Current standard of treatment relies on the collapse of femoral head as a predictor for prognosis. However, a wide range of variability in repair potentials is observed in patients with femoral head collapse. Therefore, the present study aimed to evaluate the accuracy of femoral head collapse as a predictor and to propose the necrotic lesion boundary as a novel yet reliable measure for ONFH prognosis.MethodsA retrospective cross-sectional study was conducted at the First Affiliated Hospital of Guangzhou University of Chinese Medicine, 203 hips with ONFH from 134 patients were included. The occurrences and progression of femoral head collapse were recorded. Necrosis lesion boundary was quantified and classified for each case based on anteroposterior view intact ratio (APIR) and the frog-leg view intact ratio (FLIR) as independent variables. Dependent variables were defined as progressive collapse or terminal collapse for Association Research Circulation Osseous (ARCO) stage II and III respectively. Logistic regression analysis, Receiver Operating Characteristic (ROC) curve and Kaplan-Meier (K-M) survival analysis was performed and results were interpreted.ResultsOut of the 106 hips in ARCO stage II, 31 hips collapsed with further progression, while 75 hips had no collapse or collapse with repair of the necrotic areas. Out of the 97 hips in ARCO stage IIIA, the collapse continued to progress in 58 hips while the necrotic areas were repaired in 39 hips. Logistic regression analysis demonstrated that both APIR and FLIR, were independent risk factors. Further ROC curve analysis indicated that the cutoff values of APIR and FLIR could be considered as indications for evaluating the prognosis of ONFH. Contrary to the traditional view of poor prognosis after femoral head collapse, K-M survival analysis demonstrated a high value of APIR and FLIR for ONFH prognosis.ConclusionThe present study found that the occurrence of collapse is an oversimplified predictor for ONFH prognosis. The collapse of the femoral head in ONFH does not predict a poor prognosis. The necrosis lesion boundary has a high value in predicting ONFH prognosis and informing clinical treatment strategies.

Abstract In the framework of the chiral quark model (ChQM), we systematically investigate the strange hidden-charm tetraquark systems $$cs{\bar{c}}{\bar{u}}$$ c s c ¯ u ¯ with two structures: $$q{\bar{q}}-q{\bar{q}}$$ q q ¯ - q q ¯ and $$qq-{\bar{q}}{\bar{q}}$$ q q - q ¯ q ¯ . The bound-state calculation shows that there is no any bound state in present work, which excludes the molecular state explanation ( $$D^{0}D_{s}^{*-}/D^{*0}D_{s}^{-}/D^{*0}D_{s}^{*-}$$ D 0 D s ∗ - / D ∗ 0 D s - / D ∗ 0 D s ∗ - ) of the reported $$Z_{cs}(3985)^{-}$$ Z cs ( 3985 ) - or $$Z_{cs}(4000)^{+}$$ Z cs ( 4000 ) + . However, the effective potentials for the $$cs-{\bar{c}}{\bar{u}}$$ c s - c ¯ u ¯ systems show the possibility of some resonance states. By applying a stabilization calculation and coupling all channels of both two structures, two new resonance states are obtained, which are the $$IJ^{P}=\frac{1}{2} 0^{+}$$ I J P = 1 2 0 + state with the energy around 4111–4116 MeV and the $$IJ^{P} =\frac{1}{2} 1^{+}$$ I J P = 1 2 1 + state with energy around 4113–4119 MeV, respectively. Both of them are worthy of search in future experiments. Our results show that the coupling calculation between the bound channels and open channels is indispensable to provide the necessary information for experiments to search for exotic hadron states.

Abstract Inspired by the recent observation of $$\chi _{c0}(3930)$$ χ c 0 ( 3930 ) , X(4685) and X(4630) by the LHCb Collaboration and some exotic resonances such as X(4350), X(4500), etc. by several experiment collaborations, the $$cs{\bar{c}}{\bar{s}}$$ c s c ¯ s ¯ tetraquark systems with $$J^{PC}=0^{++}$$ J PC = 0 + + , $$1^{++}$$ 1 + + , $$1^{+-}$$ 1 + - and $$2^{++}$$ 2 + + are systematically investigated in the framework of the quark delocalization color screening model(QDCSM). Two structures, the meson–meson and diquark–antidiquark structures, as well as the channel-coupling of all channels of these two configurations are considered in this work. The numerical results indicate that the molecular bound state $$D^{-}_{s}D_{s}^{+}$$ D s - D s + with $$J^{PC}=00^{++}$$ J PC = 00 + + can be supposed to explain the $$\chi _{c0}(3930)$$ χ c 0 ( 3930 ) . Besides, by using the stabilization method, several resonant states are obtained. Among these states, X(4350), X(4500) and X(4700) can be explained as the compact tetraquark states with $$J^{PC}=00^{++}$$ J PC = 00 + + , and the X(4274) is possible to be a candidate of the compact tetraquark state with $$J^{PC}=1^{++}$$ J PC = 1 + + . Apart from that, the $$J^{PC}=0^{++}$$ J PC = 0 + + resonance state with energy range 4028–4033 MeV, the two $$J^{PC}=2^{++}$$ J PC = 2 + + resonance states with energy range of 4394–4448 MeV and 4526–4536 MeV are possible to be new exotic states, which are indeed worthy of attention. More experimental tests are expected to check the existence of all these possible resonance states.

Vaccination is the most effective means of protecting people from influenza virus infection. The effectiveness of existing vaccines is very limited due to antigenic drift of the influenza virus. Therefore, there is a requirement to develop a universal vaccine that provides broad and long-lasting protection against influenza. CD8+ T-cell response played a vital role in controlling influenza virus infection, reducing viral load, and less clinical syndrome. In this study, we optimized the HA sequences of human seasonal influenza viruses (H1N1, H3N2, Victoria, and Yamagata) by designing multivalent vaccine antigen sets using a mosaic vaccine design strategy and genetic algorithms, and designed an HA mosaic cocktail containing the most potential CTL epitopes of seasonal influenza viruses. We then tested the recombinant mosaic antigen, which has a significant number of potential T-cell epitopes. Results from genetic evolutionary analyses and 3D structural simulations demonstrated its potential to be an effective immunogen. In addition, we have modified an existing neutralizing antibody-based seasonal influenza virus vaccine to include a component that activates cross-protective T cells, which would provide an attractive strategy for improving human protection against seasonal influenza virus drift and mutation and provide an idea for the development of a rationally designed influenza vaccine targeting T lymphocyte immunity.

According to the classification of the quark model, the hadrons going beyond three-quark baryon and quark-antiquark meson pictures are called exotic hadrons. Many new hadrons have been observed since 2003, some of which exhibit exotic behaviors. There are a lot of excellent review articles on exotic hadrons available so far; the present article tries to focus on the recent experimental and theoretical progress on the exotic states from the perspective of the quark model. Although lattice quantum chromodynamics may give the final answer of the problem, the phenomenological models are still powerful tools to explore the exotic states and to provide insight on the phenomenology of hadrons. The spatial and color structures of multiquark states and the channel coupling calculation are emphasized through reviewing some bound states, molecular and color structure resonances. Finally, the unquench effects of some exotic states are reviewed. With the accumulation of experimental data on multiquark states and inspiration of underlying theory developments, more reasonable phenomenological models incorporating multi-body interactions and high Fock components to unify the description of normal hadrons and exotic hadrons are expectable.

Objective The contamination rate and gene groups of Norovirus(NoV) in oyster collected from harvesting farm in Fujian Province was investigated, and the contamination concentration was quantitatively analyzed, so as to provide data support for surveillance and risk assessment of Norovirus in food. Methods 244 oyster samples from oyster culture bed in Fujian Province were collected from August 2017 to September 2018. Norovirus nucleic acid was detected by realtime fluorescent quantitative polymerase chain reaction(PCR) to monitor Norovirus contamination in oyster production farm. Results The positive rate of Norovirus in 211 valid samples was 30.33%(64/211). Norovirus was detected in both GI and GII groups. 16.59%(35/211) of the samples were GI positive, 24.17%(51/211) of the samples were GII positive, and 10.43%(22/211) of the samples were both GI and GII positive. The range of the quantity of Norovirus in positive samples was from 1.05×102 -1.68×104 gene copies/g(digestive gland). Conclusion ected from commercial harvesting farm in Fujian Province were partly contaminated by Norovirus. A marked winter seasonality of contamination by both prevalence and quantity was observed. It is necessary to take more targeted risk management interventions in winter to reduce the risk of human illness resulting from Norovirus contamination of oysters.

Abstract Background As one of the most common gynaecological malignant tumors, cervical cancer (CC) has become an important public health issue. Emerging evidence has revealed long non-coding RNAs (lncRNAs) are crucial regulators of biological functions in cancers, including CC. And the oncogenic role of LINC00441 has been verified in hepatocellular carcinoma (HCC). But the molecular mechanism and biological functions of LINC00441 in CC remain unknown. Methods qRT-PCR analysis detected the expression of genes in CC tissues or cells. CCK-8, colony formation, flow cytometry, transwell, western blot assays as well as animal studies were conducted to analyze the function of LINC00441 in CC. Luciferase reporter, RIP and RNA pull down assays were applied to verify the binding relations among the indicated genes. Results LINC00441 was upregulated in CC tissues and cells. Further, LINC00441 depletion repressed cell proliferation and motility in vitro as well as tumor growth in vivo. LINC00441 could sponge miR-450b-5p to upregulate RAB10 expression. Finally, miR-450b-5p inhibitor or RAB10 upregulation counteracted LINC00441 knockdown-mediated function on the development of CC. Conclusions LINC00441 drives CC progression by targeting miR-450b-5p/RAB10 axis, which might provide new idea for researching CC-related molecular mechanism.

Aspect-based sentiment analysis (ABSA) is a fine-grained task of sentiment analysis that presents great benefits to real-word applications. Recently, the methods utilizing graph neural networks over dependency trees are popular, but most of them merely considered if there exist dependencies between words, ignoring the types of these dependencies, which carry important information, as dependencies with different types have different effects. In addition, they neglected the correlations between dependency types and part-of-speech (POS) labels, which are helpful for utilizing dependency imformation. To address such limitations and the deficiency of insufficient syntactic and semantic feature mining, we propose a novel model containing three modules, which aims to leverage dependency trees more reasonably by distinguishing different dependencies and extracting beneficial syntactic and semantic features to further enhance model performance. To enrich word embeddings, we design a syntactic feature encoder (SynFE). In particular, we design Dependency-POS Weighted Graph Convolutional Network (DPGCN) to weight different dependencies by a graph attention mechanism we proposed. Additionally, to capture aspect-oriented semantic information, we design a semantic feature extractor (SemFE). Extensive experiments on five popular benchmark databases validate that our model can better employ dependency information and effectively extract favorable syntactic and semantic features to achieve new state-of-the-art performance.

With the emergence and rapid spread of new pandemic variants, especially variants of concern (VOCs), the development of next-generation vaccines with broad-spectrum neutralizing activities is of great importance. In this study, SCTV01C, a clinical stage bivalent vaccine based on trimeric spike extracellular domain (S-ECD) of SARS-CoV-2 variants Alpha (B.1.1.7) and Beta (B.1.351) with a squalene-based oil-in-water adjuvant was evaluated in comparison to its two corresponding (Alpha and Beta) monovalent vaccines in mouse immunogenicity studies. The two monovalent vaccines induced potent neutralizing antibody responses against the antigen-matched variants, but drastic reductions in neutralizing antibody titers against antigen-mismatched variants were observed. In comparison, the bivalent vaccine SCTV01C induced relatively higher and broad-spectrum cross-neutralizing activities against various SARS-CoV-2 variants, including the D614G variant, VOCs (B.1.1.7, B.1.351, P.1, B.1.617.2, B.1.1.529), variants of interest (VOIs) (C.37, B.1.621), variants under monitoring (VUMs) (B.1.526, B.1.617.1, B.1.429, C.36.3) and other variants (B.1.618, 20I/484Q). All three vaccines elicited potent Th1-biased T-cell immune responses. These results provide direct evidence that variant-based multivalent vaccines could play important roles in addressing the critical issue of reduced protective efficacy against the existing and emerging SARS-CoV-2 variants.

Motivated by the very recent observations of hidden charm pentaquarks Pc(4312)+, Pc(4440)+ and Pc(4457)+ of the LHCb Collaboration, we systematically study the spectra of the doubly-heavy (with or without charm/bottom numbers) pentaquarks and tetraquarks in non-relativistic constituent quark model. The model independent variational method is employed to solve the Schrödinger equation, where the test radial functions adopted are symmetric for the light quarks. In our study, the Pc(4312)+ may be assigned as the ground state with spin-parity 12− or 32−, while the Pc(4440)+ and Pc(4457)+ may be assigned as the excited states with 12−, which might all belong to the sextet with scc¯=1 and sℓ=32. It is notable that our working framework is quite similar to that of Hydrogen molecule, but with different potential structure. We also classify these pentaquarks and tetraquarks in light of the heavy quark symmetry and their decay properties are analyzed. Several promising channels for the observation of doubly-heavy pentaquarks and doubly-heavy tetraquarks in experiment are proposed.

On the basis of the first-principles method, this paper discusses a new type of diamond PrV color center by using Vienna Ab-initio Simulation Package software and optimizes the possible configurations of the PrV defect. Theoretically, a stable structure of the diamond PrV color center is one where Pr is located at the center of the double vacancy. The electronic structure of the diamond color center is calculated by using this stable structure, and its energy band and energy level structures are obtained. A zero-phonon line (ZPL) of 1.0185 eV and emission wavelength of 1217.5 nm are predicted for the PrV color center. Calculation of the effects of co-doping of the diamond PrV color center with N or B atoms reveals improvements in energy band and energy level structures and provides a theoretical basis for the experimental preparation of PrV color centers.

Since head-related transfer functions (HRTFs) represent the interactions between sounds and physiological structures of listeners, anthropometric parameters represent a straightforward way to customize (or predict) individualized HRTFs. This paper proposes a hybrid algorithm for predicting median-plane individualized HRTFs using anthropometric parameters. The proposed hybrid algorithm consists of three parts: decomposition of HRTFs; selection of key anthropometric parameters; and establishing a prediction formula. Firstly, an independent component analysis (ICA) is applied to median-plane HRTFs from multiple subjects to obtain independent components and subject-dependent weight coefficients. Then, a factor analysis is used to select key anthropometric parameters relevant to HRTFs. Finally, a regression formula that connects ICA weight coefficients to key anthropometric parameters is established by a multiple linear regression. Further, the effectiveness of the proposed hybrid algorithm is verified by an objective evaluation via spectral distortion and a subjective localization experiment. The results show that, when compared with generic Knowles Electronics Manikin for Acoustic Research (KEMAR) HRTFs, the spectral characteristics of the predicted HRTFs are closer to those of the individualized HRTFs. Moreover, the predicted HRTFs can alleviate front−back and up−down confusion and improve the accuracy of localization for most subjects.