Influenza viruses, including four major types (A, B, C, and D), can cause mild-to-severe and lethal diseases in humans and animals. Influenza viruses evolve rapidly through antigenic drift (mutation) ...and shift (reassortment of the segmented viral genome). New variants, strains, and subtypes have emerged frequently, causing epidemic, zoonotic, and pandemic infections, despite currently available vaccines and antiviral drugs. In recent years, avian influenza viruses, such as H5 and H7 subtypes, have caused hundreds to thousands of zoonotic infections in humans with high case fatality rates. The likelihood of these animal influenza viruses acquiring airborne transmission in humans through viral evolution poses great concern for the next pandemic. Severe influenza viral disease is caused by both direct viral cytopathic effects and exacerbated host immune response against high viral loads. Studies have identified various mutations in viral genes that increase viral replication and transmission, alter tissue tropism or species specificity, and evade antivirals or pre-existing immunity. Significant progress has also been made in identifying and characterizing the host components that mediate antiviral responses, pro-viral functions, or immunopathogenesis following influenza viral infections. This review summarizes the current knowledge on viral determinants of influenza virulence and pathogenicity, protective and immunopathogenic aspects of host innate and adaptive immune responses, and antiviral and pro-viral roles of host factors and cellular signalling pathways. Understanding the molecular mechanisms of viral virulence factors and virus-host interactions is critical for the development of preventive and therapeutic measures against influenza diseases.
Particles of various sizes can exist around Mars. The orbits of large particles are mainly governed by Martian gravity, while those of small particles could be significantly affected by ...non-gravitational forces. Many of the previous studies of particle dynamics around Mars have focused on relatively small particles (radius of rp≲100μm) for ≲104 years. In this paper, using direct numerical orbital integration and analytical approaches, we consider Martian gravity, Martian J2, the solar radiation pressure (SRP) and the Poynting–Robertson (PR) force to study the giga-year dynamical evolution of particles orbiting near the Martian equatorial plane with radius ranging from micrometer to meter. We also newly study the effect of the planetary shadow upon the particle dynamics. Our results show that small particles (rp≲10μm) initially at ≲8 Martian radii (below the orbit of today’s Deimos) are quickly removed by the SRP due to eccentricity increase, resulting in a collision with Mars at the pericenter distance. The orbits of larger particles (rp>10μm) slowly decay due to the PR forces (timescale of >104 years). The planetary shadow reduces the sunlit area in the orbit and thus the efficiency of the PR drag force is reduced. However, we show that, even including the planetary shadow, particles up to ∼10 cm in radius, initially at ≲8 Martian radii, eventually spiral onto the Martian surface within ∼109 years. Smaller particles require less time to reach Mars, and vice versa. Our results would be important to better understand and constrain the nature of the remaining particle around Mars in a context of giant impact hypothesis for the formation of Phobos and Deimos.
•We studied the giga-year dynamical evolution of particles around Mars under various perturbations.•We investigated the effect of planetary shadow.•Small particles (≲10μm in radius) initially at ≲8 Martian radii are removed by the SRP quickly (within a few years).•Orbits of large particles (>10μm in radius) slowly decay due to the PR forces (timescale of >104 years).•The planetary shadow reduces the sunlit area in orbit, thus the efficiency of the PR drag is reduced.•With planetary shadow, particles up to ∼10 cm initially at ≲8 Martian radii spiral onto the Martian surface within ∼109 years.
Despite the success of vaccination to greatly mitigate or eliminate threat of diseases caused by pathogens, there are still known diseases and emerging pathogens for which the development of ...successful vaccines against them is inherently difficult. In addition, vaccine development for people with compromised immunity and other pre-existing medical conditions has remained a major challenge. Besides the traditional inactivated or live attenuated, virus-vectored and subunit vaccines, emerging non-viral vaccine technologies, such as viral-like particle and nanoparticle vaccines, DNA/RNA vaccines, and rational vaccine design, offer innovative approaches to address existing challenges of vaccine development. They have also significantly advanced our understanding of vaccine immunology and can guide future vaccine development for many diseases, including rapidly emerging infectious diseases, such as COVID-19, and diseases that have not traditionally been addressed by vaccination, such as cancers and substance abuse. This review provides an integrative discussion of new non-viral vaccine development technologies and their use to address the most fundamental and ongoing challenges of vaccine development.
Summary Background The causes of phenotypic heterogeneity in familial Alzheimer's disease with autosomal dominant inheritance are not well understood. We aimed to characterise clinical phenotypes and ...genetic associations with APP and PSEN1 mutations in symptomatic autosomal dominant familial Alzheimer's disease (ADAD). Methods We retrospectively analysed genotypic and phenotypic data (age at symptom onset, initial cognitive or behavioural symptoms, and presence of myoclonus, seizures, pyramidal signs, extrapyramidal signs, and cerebellar signs) from all individuals with ADAD due to APP or PSEN1 mutations seen at the Dementia Research Centre in London, UK. We examined the frequency of presenting symptoms and additional neurological features, investigated associations with age at symptom onset, APOE genotype, and mutation position, and explored phenotypic differences between APP and PSEN1 mutation carriers. The proportion of individuals presenting with various symptoms was analysed with descriptive statistics, stratified by mutation type. Findings Between July 1, 1987, and Oct 31, 2015, age at onset was recorded for 213 patients (168 with PSEN1 mutations and 45 with APP mutations), with detailed history and neurological examination findings available for 121 (85 with PSEN1 mutations and 36 with APP mutations). We identified 38 different PSEN1 mutations (four novel) and six APP mutations (one novel). Age at onset differed by mutation, with a younger onset for individuals with PSEN1 mutations than for those with APP mutations (mean age 43·6 years SD 7·2 vs 50·4 years SD 5·2, respectively, p<0·0001); within the PSEN1 group, 72% of age at onset variance was explained by the specific mutation. A cluster of five mutations with particularly early onset (mean age at onset <40 years) involving PSEN1's first hydrophilic loop suggests critical functional importance of this region. 71 (84%) individuals with PSEN1 mutations and 35 (97%) with APP mutations presented with amnestic symptoms, making atypical cognitive presentations significantly more common in PSEN1 mutation carriers (n=14; p=0·037). Myoclonus and seizures were the most common additional neurological features; individuals with myoclonus (40 47% with PSEN1 mutations and 12 33% with APP mutations) were significantly more likely to develop seizures (p=0·001 for PSEN1; p=0·036 for APP ), which affected around a quarter of the patients in each group (20 24% and nine 25%, respectively). A number of patients with PSEN1 mutations had pyramidal (21 25%), extrapyramidal (12 14%), or cerebellar (three 4%) signs. Interpretation ADAD phenotypes are heterogeneous, with both age at onset and clinical features being influenced by mutation position as well as causative gene. This highlights the importance of considering genetic testing in young patients with dementia and additional neurological features in order to appropriately diagnose and treat their symptoms, and of examining different mutation types separately in future research. Funding Medical Research Council and National Institute for Health Research.
The Raman spectra of H2O/D2O−Na2SO4 solutions are measured at temperatures (T) up to 573 K. The hydrating structure of SO42− is investigated based on the solute‐correlated (SC) OD/OH stretch bands ...obtained by the multivariate curve resolution method. Remaining a nearly constant wavenumber of the main peak with increasing temperature, the SC OD/OH bands are narrowed first due to the reduced relative intensity of the shoulder at 2395/~3245 cm−1 when T < ~473 K/~513 K but then because the OD/OH bands get sunken around 2610/3580 cm−1 above ~473/~513 K (letting the ~2660/~3635 cm−1 mode be more prominent and even a separate peak). These spectral features incline to support a temperature‐dependent water structure in the SO42− hydration shell balanced by the SO42−···H2O(D2O) and O–H(D)···O hydrogen bonds (those with D are stronger) as well as the electrostatics. Most hydrating water molecules are engaged in hydrogen bonding configurations of single donor (SD) and single hydrogen‐bond water (SHW). As temperature rises, the average number of hydrogen bonds per hydrating water molecule decreases below ~373 K because of the SD → SHW transition and increases afterward owning to the rapid increase of the ion pairs, and SO42− changes its role from structure breaker to structure maker above ~453 K. The temperature‐dependent solubility behavior of Na2SO4 in H2O can be rationalized by the ion pairing effect and temperature‐dependent structure details in SO42− hydration shell.
The Na2SO4‐correlated Raman OD/OH stretch bands from 293 to 573 K suggest a temperature‐dependent water structure in SO42− hydration shell balanced by SO42−···H2O(D2O) and O–H(D)···O hydrogen bonds and electrostatics. Most hydrating water molecules are engaged in hydrogen bonding configurations of single donor (SD) and single hydrogen‐bond water (SHW). As temperature rises, the hydrogen bond number for hydrating water decreases below ~373 K because of the SD → SHW transition and increases afterward owning to the ion pairing.
The COVID-19 pandemic caused by the coronavirus SARS-CoV-2 is continuing to spread globally. SARS-CoV-2 infections of feline and canine species have also been reported. However, it is not entirely ...clear to what extent natural SARS-CoV-2 infection of pet dogs and cats is in households. We have developed enzyme-linked immunosorbent assays (ELISAs) using recombinant SARS-CoV-2 nucleocapsid (N) protein and the receptor-binding-domain (RBD) of the spike protein, and the SARS-CoV-2 spike-pseudotyped vesicular stomatitis virus (VSV)-based neutralization assay to screen serum samples of 239 pet cats and 510 pet dogs in Minnesota in the early phase of the COVID-19 pandemic from mid-April to early June 2020 for evidence of SARS-CoV-2 exposures. A cutoff value was used to identify the seropositive samples in each experiment. The average seroprevalence of N- and RBD-specific antibodies in pet cats were 8% and 3%, respectively. Among nineteen (19) N-seropositive cat sera, fifteen (15) exhibited neutralizing activity and seven (7) were also RBD-seropositive. The N-based ELISA is also specific and does not cross react with antigens of common feline coronaviruses. In contrast, SARS-CoV-2 antibodies were detected at a very low percentage in pet dogs (~ 1%) and were limited to IgG antibodies against SARS-CoV-2 N protein with no neutralizing activities. Our results demonstrate that SARS-CoV-2 seropositive rates are higher in pet cats than in pet dogs in MN early in the pandemic and that SARS-CoV-2 N-specific IgG antibodies can detect SARS-CoV-2 infections in companion animals with higher levels of specificity and sensitivity than RBD-specific IgG antibodies in ELISA-based assays.
Arenaviruses can cause fatal human haemorrhagic fever (HF) diseases for which vaccines and therapies are extremely limited. Both the New World (NW) and Old World (OW) groups of arenaviruses contain ...HF-causing pathogens. Although these two groups share many similarities, important differences with regard to pathogenicity and molecular mechanisms of virus infection exist. These closely related pathogens share many characteristics, including genome structure, viral assembly, natural host selection and the ability to interfere with innate immune signalling. However, members of the NW and OW viruses appear to use different receptors for cellular entry, as well as different mechanisms of virus internalization. General differences in disease signs and symptoms and pathological lesions in patients infected with either NW or OW arenaviruses are also noted and discussed herein. Whilst both the OW Lassa virus (LASV) and the NW Junin virus (JUNV) can cause disruption of the vascular endothelium, which is an important pathological feature of HF, the immune responses to these related pathogens seem to be quite distinct. Whereas LASV infection results in an overall generalized immune suppression, patients infected with JUNV seem to develop a cytokine storm. Additionally, the type of immune response required for recovery and clearance of the virus is different between NW and OW infections. These differences may be important to allow the viruses to evade host immune detection. Understanding these differences will aid the development of new vaccines and treatment strategies against deadly HF viral infections.
Wind power is one of the most efficient renewable resources without emissions. Nonetheless, it is difficult to exactly forecast wind power generation given historical power and wind speed ...information, the failure of which may cost the risk of large-scale outages. This article takes a close look at the artificial recurrent neural network framework in the application of wind power forecasting. More intelligent mechanisms using attention to capture spatial-temporal patterns within historical data are emphasized in this work and are shown to be state-of-the-art for short-term wind power forecasting. Our experiments at a wind farm in southeast Australia using only the historical wind power generation and wind speed records from ambient weather stations show that, e.g., 7.4750% in mean absolute error (MAE) and 0.3345 in the coefficient of variation in the root mean squared error (CV-RMSE) for half-hour-ahead prediction. To interpret how the three models under consideration-the long- and short-term time-series network (LSTNet), the temporal pattern attention-based long short-term memory (TPA-LSTM) and the dual-stage attention-based recurrent neural network (DA-RNN)-work, we visualize and analyze the details of the models so that further improvement can be made by combining the advantageous components of the models.
•Systematically evaluated the effects of GLCM parameters on rubber AGB estimation.•The combination of spectral and textural information improved predictive accuracy.•Support vector regression ...performed the best in AGB estimation with small samples.•Providing new insight on biophysical parameters estimation with a low-cost UAV system.
Aboveground biomass (AGB), as a crucial indicator of forest growth and quality, plays an important role in monitoring the global carbon cycle and forest health. Rapid, accurate, and non-destructive assessment of AGB in rubber plantations is beneficial not only for predicting rubber yield but also for understanding the carbon storage potential in tropical areas. Previous studies have employed spectral information and texture features derived from unmanned aerial vehicle data to estimate the AGB of mangroves. However, few studies systematically assessed the effects of grey level co-occurrence matrix parameters for extracting texture features on AGB estimation in rubber plantations. Whether the combination of spectral information and texture features with suitable grey level co-occurrence matrix parameters selection derived from a low-cost unmanned aerial vehicle system can improve the AGB estimation accuracy remains unclear. To this end, this study evaluated the performance of spectral information and texture features derived from UAV-based high-resolution RGB imagery with different textural parameter settings. Three types of machine learning algorithms (support vector regression; random forest; extreme gradient boosting regressor) and stepwise multiple linear regression were used to compare and analyze their performance for AGB estimation of rubber plantations. The results indicated that appropriate textural parameter selection significantly improved the AGB estimation accuracy when using texture features alone. Among four regression techniques, stepwise multiple linear regression exhibited poor performance, while support vector regression performed the best. The best estimation accuracy (R2 = 0.752, RMSE = 28.72 t/ha) was obtained by support vector regression when using the combination of spectral information and texture features with the textural parameters of the orientation of 135°, displacement of 2 pixels, and moving window size parameter of 7 × 7 pixels. The findings suggested that the AGB estimation accuracy can be further improved by the integration of spectral information and texture features when considering appropriate textural parameters.
Animal models that can replicate clinical and pathologic features of severe human coronavirus infections have been instrumental in the development of novel vaccines and therapeutics. The goal of this ...review is to summarize our current understanding of the pathogenesis of coronavirus disease 2019 (COVID-19) and the pathologic features that can be observed in several currently available animal models. Knowledge gained from studying these animal models of SARS-CoV-2 infection can help inform appropriate model selection for disease modelling as well as for vaccine and therapeutic developments.
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