Search

The pandemic of SARS-CoV-2 post a significant threat to public health. Here the authors show, by screening 23 viral proteins, that both structural and non-structural SARS-CoV-2 proteins are capable of modulating host innate immunity and type interferon responses, with this information serves to warrant further studies on SARS-CoV-2 pathogenesis.

SARS-CoV-2 has spread globally. Here, the authors characterize the entry pathway of SARS-CoV-2, show that the SARS-CoV-2 spike protein is less stable than that of SARS-CoV, and show limited cross-neutralization activities between SARS-CoV and SARS-CoV-2 sera.

ABSTRACTTo identify the association between the kinetics of viral load and clinical outcome in severe coronavirus disease 2019 (COVID-19) patients, a retrospective study was performed by involved 188 hospitalized severe COVID-19 patients in the LOTUS China trial. Among the collected 578 paired throat swab (TS) and anal swab (AS) samples, viral RNA was detected in 193 (33.4%) TS and 121 (20.9%) AS. A higher viral RNA load was found in TS than that of AS, with means of 1.0 × 106 and 2.3 × 105 copies/ml, respectively. In non-survivors, the viral RNA in AS was detected earlier than that in survivors (median of 14 days vs 19 days, P = 0.007). The positivity and viral load in AS were higher in non-survivors than that of survivors at week 2 post symptom onset (P = 0.006). A high initial viral load in AS was associated with death (OR 1.368, 95% CI 1.076–1.741, P = 0.011), admission to the intensive care unit (OR 1.237, 95% CI 1.001–1.528, P = 0.049) and need for invasive mechanical ventilation (OR 1.340, 95% CI 1.076–1.669, P = 0.009). Our findings indicated viral replication in extrapulmonary sites should be monitored intensively during antiviral therapy.

As is well known, satellite resources are extremely scarce relative to observation demands. Consequently, the Earth observation satellite (EOS) scheduling becomes a remarkable problem which is of significant importance. As an NP-hard problem, It is difficult to get an optimal solution. Furthermore, real-time scheduling makes it even more challenging for researchers. Unfortunately, although fruitful results have been achieved in the category of EOS scheduling, there still exist a number of obvious limitations and drawbacks. For example, the response speed and stability are always limited in the scheduling of urgent tasks that appeared stochastically. To overcome this obstacle, a reinforcement learning algorithm, which is of the ability to make a fast response for the urgent task scheduling, has been proposed in this paper. In order to improve scheduling stability and reduce computational complexity, hierarchical architecture with two layers has been established for the proposed algorithm. In each hierarchical layer, we adopt an online learning paradigm to explore a scheduling strategy at the learning phase. According to the algorithm, the satellite takes a scheduling action when urgent tasks arrive randomly according to a certain strategy. The environment will feedback to the satellite by the corresponding rewards of the actions taken. After multiple feedback, the satellite will select the action that can obtain the greatest benefit. In practical space applications, the satellite can employ the learned strategy to operate the low orbit satellite selection and observation time window (OTW) assignment for urgent tasks in stochastic scenarios, which realize an immediate schedule and maximize scheduling stability at the same time. Finally, a numerical experiment has been performed. The simulation results demonstrate that, compared to the heuristic m-WSITF algorithm, the proposed algorithm possesses significant advantages in effectiveness and efficiency, especially in response speed and stability.

Abstract Transforming carbon dots (CDs) fluorescent materials into smart materials with complex functions is a topic of great interest to nanoscience. However, designing CDs with regulating fluorescence/phosphorescence that can be visually monitored with the environment changes in real‐time remains a challenge. Here, a very simple strategy, one‐step solvent‐free catalytic assistant strategy, which is low cost, facile, environment‐friendly, and high throughput, is put forward. Hydrogen bond is used to manipulate nanostructure of CDs, and the obtained carbon dots (M‐CDs) show a series of attractive properties including matrix‐free room‐temperature phosphorescence, time‐dependent fluorescence, and near‐infrared emissive characteristics. Different from the traditional aggregation caused quenching or aggregation‐induced emission fluorescent materials, M‐CDs exhibit unprecedented and unique dispersion induced redshift fluorescence phenomenon, promoting the studies of fluorescence from static to dynamic. The causes of this phenomenon are further analyzed in detail. As a kind of intelligent fluorescent materials, this new designed CDs greatly enrich the basic recognition of CDs by illustrating the relationship between redshift fluorescence behaviors and the dispersion states, and may provide with an opportunity for solid‐state fluorescent materials, anti‐counterfeiting, cellular imaging, and hopefully many others.

ABSTRACT The microbiota plays an important role in human health and disease development. The lung microbiota profile in pulmonary tuberculosis (TB) patients and the effects of anti-TB treatment on the profile need to be determined thoroughly and comprehensively. This study primarily aimed to determine the lung microbiota profile associated with pulmonary TB and characterize the longitudinal changes during anti-TB treatment. A total of 53 participants, comprising 8 healthy individuals, 12 untreated pulmonary TB patients, 15 treated pulmonary TB patients, 11 cured pulmonary TB patients, and 7 lung cancer patients, were recruited in the present study. Bronchioalveolar lavage fluid (BALF) samples were collected from the above participants, and throat swabs were taken from healthy individuals. Microbiomes in the samples were examined using metagenomic next-generation sequencing (mNGS). Differences in microbiota profiles were determined through a comparison of the indicated groups. Our findings indicated that the BALF samples displayed decreased richness and diversity of the microbiota compared to those of the throat swab samples, and these two kinds of samples exhibited obvious separation on principal-coordinate analysis (PCoA) plots. Untreated pulmonary TB patients displayed a unique lung microbiota signature distinct from that of healthy individuals and lung cancer patients. Our data first demonstrated that anti-TB treatment with first-line drugs increases alpha diversity and significantly affects the beta diversity of the lung microbiota, while it also induces antibiotic resistance genes (ARGs). IMPORTANCE Characterization of the lung microbiota could lead to a better understanding of the pathogenesis of pulmonary TB. Here, we applied the metagenomic shotgun sequencing instead of 16S rRNA sequencing method to characterize the lung microbiota using the BALF samples instead of sputum. We found that alterations in the lung microbiota are associated with TB infection and that anti-TB treatment significantly affects the alpha and beta diversity of the lung microbiota in pulmonary TB patients. These findings could help us better understand TB pathogenesis.

A strict relationship exists between the Sirex noctilio and the Amylostereum areolatum, which is carried and spread by its partner. The growth and development of this symbiotic fungus is key to complete the life history of the Sirex woodwasp. Real-time quantitative polymerase chain reaction (RT-qPCR) is used to measure gene expression in samples of A. areolatum at different growth stages and explore the key genes and pathways involved in the growth and development of this symbiotic fungus. To obtain accurate RT-qPCR data, target genes need to be normalized by reference genes that are stably expressed under specific experimental conditions. In our study, the stability of 10 candidate reference genes in symbiotic fungal samples at different growth and development stages was evaluated using geNorm, NormFinder, BestKeeper, delta Ct methods, and RefFinder. Meanwhile, laccase1 was used to validate the stability of the selected reference gene. Under the experimental conditions of this study, p450, CYP, and γ-TUB were identified as suitable reference genes. This work is the first to systematically evaluate the reference genes for RT-qPCR results normalization during the growth of this symbiotic fungus, which lays a foundation for further gene expression experiments and understanding the symbiotic relationship and mechanism between S. noctilio and A. areolatum.

Sirex noctilio F. is an invasive woodwasp that causes pine mortality in plantations in China. Sirex nitobei M. is a native woodwasp in large areas of China. In this study, the flight capacity of the two woodwasps was studied and compared using a tethered-flight mill system to find individual factors affecting the flight capacity. After flight bioassays, woodwasps were dissected to determine nematode infestation. Post-eclosion-day (PED) age significantly influenced the flight capacity of S. noctilio females and males; as woodwasps become older, their flight capacity decreased. For S. nitobei, PED age did not significantly affect their flight capacity. In general, the flight capacity of S. noctilio was greater than that of S. nitobei. Females flew further and for longer than males for both Sirex species. The Deladenus spp. parasitism status of the two Sirex species did not significantly affect their flight performance parameters. PED age and body mass were key individual factors significantly affecting the flight capacity of the two Sirex species. In this study, detailed and accurate tethered-flight parameters of S. noctilio and S. nitobei were obtained. Although this is different from natural flight, it also provides us substantial laboratory data on their flight capacity, and facilitates risk analysis of the two woodwasp species.

Using energy plants to repair salinized soils polluted by petroleum is an efficient way to solve the problem of farmland reduction and prevent pollutants from entering the food chain simultaneously. In this study, pot experiments were conducted for the purposes of preliminarily discussing the potential of using an energy plant, sweet sorghum (Sorghum bicolor (L.) Moench), to repair petroleum-polluted salinized soils and obtain associated varieties with excellent remediation performance. The emergence rate, plant height and biomass of different varieties were measured to explore the performance of plants under petroleum pollution, and the removal of petroleum hydrocarbons in soil with candidate varieties was also studied. The results showed that the emergence rate of 24 of the 28 varieties were not reduced by the addition of 1.0 × 104 mg/kg petroleum in soils with a salinity of 0.31%. After a 40-day treatment in salinized soil with petroleum additions of 1.0 × 104 mg/kg, 4 potential well-performed varieties including Zhong Ketian No. 438, Ke Tian No. 24, Ke Tian No. 21 (KT21) and Ke Tian No. 6 with a plant height of >40 cm and dry weight of >4 g were screened. Obvious removal of petroleum hydrocarbons in the salinized soils planted with the four varieties were observed. Compared with the treatment without plants, the residual petroleum hydrocarbon concentrations in soils planted with KT21 decreased by 69.3%, 46.3%, 56.5%, 50.9% and 41.4%, for the additions of 0, 0.5 × 104, 1.0 × 104, 1.5 × 104 and 2.0 × 104 mg/kg, respectively. In general, KT21 had the best performance and application potential to remediate petroleum-polluted salinized soil.

The invasive pest Dendroctonus valens has spread to northeast China, causing serious economic and ecological losses. Early detection and disposal of infested trees is critical to prevent its outbreaks. This study aimed to evaluate the potential of an unmanned aerial vehicle (UAV)-based hyperspectral image for early detection of D. valens infestation at the individual tree level. We compared the spectral characteristics of Pinus tabuliformis in three states (healthy, infested and dead), and established classification models using three groups of features (reflectance, derivatives and spectral vegetation indices) and two algorithms (random forest and convolutional neural network). The spectral features of dead trees were clearly distinct from those of the other two classes, and all models identified them accurately. The spectral changes of infested trees occurred mainly in the visible region, but it was difficult to distinguish infested from healthy trees using random forest classification models based on reflectance and derivatives. The random forest model using spectral vegetation indices and the convolutional neural network model performed better, with an overall accuracy greater than 80% and a recall rate of infested trees reaching 70%. Our results demonstrated the great potential of hyperspectral imaging and deep learning for the early detection of D. valens infestation. The convolutional neural network proposed in this study can provide a reference for the automatic detection of early D. valens infestation using UAV-based multispectral or hyperspectral images in the future.

Pine wilt disease (PWD) has caused huge economic and environmental losses since it invaded China. Although early monitoring is an effective way to control this hazard, the monitoring window for the early stage is hard to identify, and varies in different hosts and environments. We used UAV-based multispectral images of Pinus thunbergii forest in East China to identify the change in the number of infected trees in each month of the growing season. We built classification models to detect different PWD infection stages by testing three machine learning algorithms—random forest, support vector machine, and linear discriminant analysis—and identified the best monitoring period for each infection stage (namely, green attack, early, middle, and late). From the obtained results, the early monitoring window period was determined to be in late July, whereas the monitoring window for middle and late PWD stages ranged from mid-August to early September. We also identified four important vegetation indices to monitor each infection stage. In conclusion, this study demonstrated the effectiveness of using machine learning algorithms to analyze multitemporal multispectral data to establish a window for early monitoring of pine wilt disease infestation. The results could provide a reference for future research and guidance for the control of pine wilt disease.

BackgroundStriking similarities have been found between coronavirus disease 2019 (COVID-19) and anti-melanoma differentiation-associated gene 5 (MDA5) antibody (Ab)-related dermatomyositis, implying a shared autoinflammatory aberrance. Herein, we aim to investigate whether the anti-MDA5 Ab is present in COVID-19 and correlates with the severity and adverse outcome of COVID-19 patients.Methods and FindingsWe retrospectively recruited 274 adult inpatients with COVID-19 in this study, including 48, 164, and 62 cases of deaths, severe, and non-severe patients respectively. The anti-MDA5 Ab was determined by ELISA and verified by Western Blotting, which indicated that the positive rate of anti-MDA5 Ab in COVID-19 patients was 48.2% (132/274). The clinical and laboratory features, as well as outcomes between patients with positive and negative anti-MDA5 Ab were compared and we found that the anti-MDA5 Ab positive patients tended to represent severe disease (88.6% vs 66.9%, P

Background: Shotgun metagenomics has been used clinically for diagnosing infectious diseases. However, most technical assessments have been limited to individual sets of reference standards, experimental workflows, and laboratories. Methods: A reference panel and performance metrics were designed and used to examine the performance of shotgun metagenomics at 17 laboratories in a coordinated collaborative study. We comprehensively assessed the reliability, key performance determinants, reproducibility, and quantitative potential. Findings: Assay performance varied significantly across sites and microbial classes, with a read depth of 20 millions as a generally cost-efficient assay setting. Results of mapped reads by shotgun metagenomics could indicate relative and intra-site (but not absolute or inter-site) microbial abundance. Interpretation: Assay performance was significantly impacted by the microbial type, the host context, and read depth, which emphasizes the importance of these factors when designing reference reagents and benchmarking studies. Across sites, workflows and platforms, false positive reporting and considerable site/library effects were common challenges to the assay's accuracy and quantifiability. Our study also suggested that laboratory-developed shotgun metagenomics tests for pathogen detection should aim to detect microbes at 500 CFU/mL (or copies/mL) in a clinically relevant host context (10^5 human cells/mL) within a 24h turn-around time, and with an efficient read depth of 20M. Funding: This work was supported by National Science and Technology Major Project of China (2018ZX10102001).

SARS-CoV-2 has become a global threat to public health. Infected individuals can be asymptomatic or develop mild to severe symptoms, including pneumonia, respiratory distress, and death. This wide spectrum of clinical presentations of SARS-CoV-2 infection is believed in part due to the polymorphisms of key genetic factors in the population. In this study, we report that the interferon-induced antiviral factor IFITM3 inhibits SARS-CoV-2 infection by preventing SARS-CoV-2 spike-protein-mediated virus entry and cell-to-cell fusion. Analysis of a Chinese COVID-19 patient cohort demonstrates that the rs12252 CC genotype of IFITM3 is associated with SARS-CoV-2 infection risk in the studied cohort. These data suggest that individuals carrying the rs12252 C allele in the IFITM3 gene may be vulnerable to SARS-CoV-2 infection and thus may benefit from early medical intervention.

Pine wilt disease (PWD) is a global destructive threat to forests, having caused extreme damage in China. Therefore, the establishment of an effective method to accurately monitor and map the infection stage by PWD is imperative. Unmanned aerial vehicle (UAV)-based hyperspectral imaging (HI) and light detection and ranging (LiDAR) technique is an effective approach for forest health monitoring. However, few previous studies have used airborne HI and LiDAR to detect PWD and compared the capability for predicting PWD infection stage at the tree level. In this paper, PWD infection was divided into five stages (green, early, middle, heavy, and grey), and HI and LiDAR data were integrated to detect PWD. We estimated the power of the hyperspectral method (HI data only), LiDAR (LiDAR data only), and their combination (HI plus LiDAR data) to predict the infection stages of PWD using the random forest (RF) algorithm. We obtained the following results: (1) The classification accuracies of HI (OA: 66.86%, Kappa: 0.57) were higher than those of LiDAR (OA: 45.56%, Kappa: 0.27) for predicting PWD infection stages, and their combination had the best accuracies (OA: 73.96%, Kappa: 0.66); (2) LiDAR data had higher ability for dead tree identification than HI data; and (3) The combined use of HI and LiDAR data for estimation of PWD infection stages showed that LiDAR metrics (e.g., crown volume) were essential in the classification model, although the variables derived from HI data contributed more than those extracted from LiDAR. Therefore, we proposed a new approach combining the merits of HI and LiDAR data to precisely predict PWD infection stages at the tree level, allowing better PWD monitoring and control. The approach could also be employed for mapping and monitoring other forest disturbance issues.

Human parainfluenza viruses (HPIV1–4) cause acute respiratory tract infections, thereby impacting human health worldwide. However, there are no current effective antivirals or licensed vaccines for infection prevention. Moreover, sequence information for human parainfluenza viruses (HPIVs) circulating in China is inadequate. Therefore, to shed light on viral genetic diversity and evolution, we collected samples from patients infected with HPIV1–4 in China from 2012 to 2018 to sequence the viruses. We obtained 24 consensus sequences, comprising 1 for HPIV1, 2 for HPIV2, 19 for HPIV3, and 2 for HPIV4A. Phylogenetic analyses classified the 1 HPIV1 into clade 2, and the 2 HPIV4 sequences into cluster 4A. Based on the hemagglutinin-neuraminidase (HN) gene, a new sub-cluster was identified in one of the HPIV2, namely G1c, and the 19 HPIV3 sequences were classified into the genetic lineages of C3f and C3a. The results indicated that HPIV1–4 were co-circulated in China. Further, the lineages of sub-cluster C3 of HPIV3 were co-circulated in China. A recombination analysis indicated that a putative recombination event may have occurred in the HN gene of HPIV3. In the obtained sequences of HPIV3, we found that two amino acid substitution sites (R73K in the F protein of PUMCH14028/2014 and A281V in the HN protein of PUMCH13961/2014) and a negative selection site (amino acid position 398 in the F protein) corresponded to the previously reported neutralization-related sites. Moreover, amino acid substitution site (K108E) corresponded to the negative selection site (amino acid position 108) in the 10 F proteins of HPIV3. However, no amino acid substitution site corresponded to the glycosylation site in the obtained HPIV3 sequences. These results might help in studying virus evolution, developing vaccines, and monitoring HPIV-related respiratory diseases.

During July 2007–June 2015, we enrolled 4,225 hospitalized children with pneumonia in a study to determine the seasonality of respiratory syncytial virus (RSV) infection in Beijing, China. We defined season as the period during which >10% of total PCRs performed each week were RSV positive. We identified 8 distinctive RSV seasons. On average, the season onset occurred at week 41 (mid-October) and lasted 33 weeks, through week 20 of the next year (mid-May); 97% of all RSV-positive cases occurred during the season. RSV seasons occurred 3–5 weeks earlier and lasted ≈6 weeks longer in RSV subgroup A–dominant years than in RSV subgroup B–dominant years. Our analysis indicates that monitoring such RSV subgroup shifts might provide better estimates for the onset of RSV transmission. PCR-based tests could be a flexible or complementary way of determining RSV seasonality in locations where RSV surveillance is less well-established, such as local hospitals throughout China.

The surveillance and prevention of pathogenic microbiological contamination are the most important tasks of biosafety management in the lab. There is an urgent need to establish an effective and unbiased method to evaluate and monitor such contamination. This study aims to investigate the utility of next generation sequencing (NGS) method to detect possible contamination in the microbiology laboratory. Environmental samples were taken at multiple sites at the lab including the inner site of centrifuge rotor, the bench used for molecular biological tests, the benches of biosafety cabinets used for viral culture, clinical sample pre-treatment and nucleic acids extraction, by scrubbing the sites using sterile flocked swabs. The extracted total nucleic acids were used to construct the libraries for deep sequencing according to the protocol of Ion Torrent platform. At least 1G raw data was obtained for each sample. The reads of viruses and bacteria accounted for 0.01 ± 0.02%, and 77.76 ± 12.53% of total reads respectively. The viral sequences were likely to be derived from gene amplification products, the nucleic acids contaminated in fetal bovine serum. Reads from environmental microorganisms were also identified. Our results suggested that NGS method was capable of monitoring the nucleic acids contaminations from different sources in the lab, demonstrating its promising utility in monitoring and assessing the risk of potential laboratory contamination. The risk of contamination from reagents, remnant DNA and environment should be considered in data analysis and results interpretation.

In a data sharing system, it is a basic requirement for a user, who has an appropriate privilege to perform keyword retrieval for encrypted documents stored in the cloud. Although traditional searchable encryption technology can provide data protection and retrieval characteristic, there are some main issues should also be considered. First, most existing attribute-based searchable encryption schemes only support single-keyword search, which may return abundant irrelevant search results, resulting in a waste of computational and broadband resources. Second, the user often needs to seek some data related to some particular keywords but his attributes may be altered frequently. Third, the cloud server is not completely loyal which sometimes returns a fraction of erroneous search results. Focus on these issues, a practical multi-keyword searchable encryption scheme is proposed for data integrity verification and attribute revocation by combining the ciphertext policy attribute-based encryption (CP-ABE) and auditing ideas. The scheme on one hand supports multi-keyword search which avoids the cloud server yield ample irrelevant documents by narrowing the search scope, and the other hand can implement effectively attribute revocation by entrusting ciphertext updates to the powerful cloud server, thereby preventing access by illegal users. Furthermore, third-party audits use verification algorithms to ensure the correctness of search results and reduce the amount of computing by end users. The most critically, the scheme proved to be resistant to selective plaintext attacks and selective keyword attacks under the general group model. The extensive experimental results demonstrate that the scheme is more expressive, efficient, and feasible in the practical applications.

Abstract Background Tuberculosis (TB) remains a major public health concern on a global scale, especially in developing nations. So far, no formal guidelines are available for the diagnosis and treatment of tuberculosis pleurisy. The diagnosis of TB is worsened by the immense difficulty in differential determination of tuberculosis pleural effusion (TPE) and malignant pleural effusion (MPE). The purpose of this investigation is to assess the differential diagnostic efficiencies of the pleural IFN-γ release assay (IGRA) and widely-used biochemical parameters in the distinction analysis of TPE and MPE. Methods A cohort of 222 patients with pleural effusion was examined, comprising of 143 TPE and 58 MPE patients. The patients were examined with IGRA, and the widely-used biomarkers in the pleural effusion and peripheral blood. Results Our results show that the TPE patients have significantly higher M. tuberculosis (Mtb) antigen-specific IFN-γ responses to ESAT-6 protein and peptide pool in the blood compared to MPE patients. TPE patients were also shown to have enriched Mtb antigen-specific IFN-γ responses in pleural effusion than in peripheral blood. Among the widely-used biomarkers, the adenosine deaminase (ADA) and carcinoembryonic antigen (CEA) in pleural effusion were better biomarkers with high sensitivity and specificity to discriminate TPE and MPE. In addition, pleural IGRA could not be affected by the pleural adhesion, and the applications of the pleural IGRA together with ADA and CEA provide a promising approach for the TPE and MPE differential identification. Conclusions Our study proposes that the integration of pleural IGRA and ADA, CEA detection could add to more effective diagnosis stratagems in the discernment between TPE and MPE.

Glaucocalyxin A (GLA), is a diterpenoid extracted from Hara and has been studied for decades for its diverse bioactivities. However, GLA presents poor solubility in water and low bioavailability through oral administration which has hindered its application in the clinic. So in this study, we prepared the inclusion complex of GLA in SBE-β-CD by ultrasound method and evaluated its antitumor effect and cytotoxic effect on cancer cells. The production of GLA-SBE-β-CD inclusion complex was optimized using Box-Behnken design. The inhibitory effects of GLA and GLA-SBE-β-CD were investigated on the Hela, A549, HepG2, and SiHa cells in vitro by MTT staining assay. Pharmacokinetic studies were conducted on Sprague-Dawley mice via caudal injection to study the distribution, metabolism, and elimination of GLA-SBE-β-CD in vivo. Tumor-bearing nude mice were taken as the model and adopted to evaluate the inhibitory rate of GLA and GLA-SBE-β-CD on the transplanted tumor. A series of physical characterization results confirmed the fact that GLA-SBE-β-CD inclusion complex was successfully prepared. A production of 87.28% was achieved based on the Box-Behnken design. In the cancer cell inhibition studies, GLA and GLA-SBE-β-CD exhibited apparent concentration-dependent inhibitory actions on four kinds of tumor cells and better inhibition was achieved in GLA-SBE-β-CD group. The pharmacokinetic results showed that the duration of GLA in blood was prolonged and enhanced bioavailability was achieved. GLA and GLA-SBE-β-CD both showed an effective inhibition on the transplanted tumor growth, while the anti-tumor effect of GLA-SBE-β-CD (inhibitory rate of 45.80%) was significantly stronger than that of GLA (30.76%) based on the change of tumor weight and tumor volume.

Inclusion complex of catechin (CAT) with β-cyclodextrin (β-CD) was prepared using co-precipitation method to enhance antioxidant stability of CAT and the physicochemical properties of the inclusion complex were studied. The CAT/β-CD inclusion complex was analyzed through phase solubility study, Fourier transform infrared spectroscopy (FT-IR), differential scanning calorimetry (DSC), scanning electron microscopy (SEM) and X-ray diffraction (XRD). Phase solubility study indicated that CAT and β-CD formed 1:1 stoichiometric inclusion complex. Results of FT-IR indicated that CAT was stabilized in β-CD cavity by intra-molecular hydrogen bonds. Results of DSC and SEM proved that CAT/β-CD inclusion complex formed. XRD results showed that the formation of new solid crystalline phases in the CAT/β-CD inclusion complex. CAT was effectively protected through encapsulation into β-CD and the antioxidant stability of CAT was improved after encapsulation. In addition, the release behavior of CAT from the inclusion complex increased with increasing of the temperature.

This article examines the impact of automatic identification system (AIS) data thinning on ship emissions inventory results. AIS data thinning is theoretically proven to lead to a smaller result for a ship’s air pollutant emissions inventory. The AIS dynamic data of six sampled ships for 1 day and for 1 year were thinned at 1 min, 3 min, 10 min, 30 min, and 1 h time intervals, and then CO2, NOX, CH, PM, SO2, and other air pollutant emissions were estimated both with and without AIS data thinning in the different time intervals. The results show that AIS data thinning affects the air pollutant emissions inventory results of the ships, and the impact is greater as the thinning interval increases. When the thinning interval is less than 10 min, the impact is less than 10%, but the impact increases to about 10–15% at a 30 min interval and about 15–20% at a 60 min interval. The impacts of thinning on the emissions of ships with acutely fluctuating speeds are more significant because the constantly changing speed is the main reason why data thinning affects the ship emissions inventory. Therefore, these data suggest that the AIS data can be thinned at intervals of 5 or 10 min when establishing a coastal or national ship air pollutant emissions inventory, the AIS data should be thinned at intervals of less than 3 min when establishing the air pollutant emissions inventory of inland river ships, and data thinning is not recommended when establishing a port or smaller-scale ship air pollutant emissions inventory.

Streltzoviella insularis (Staudinger) (Lepidoptera: Cossidae) is a woodboring insect feeding on Fraxinus pennsylvanica, Sophora japonica, and Ginkgo biloba, as well as many other species used for urban greening and plain afforestation in northern China, including the temperate north. There is also a risk that S. insularis could spread through the transportation of seedlings, thereby increasing urban greening costs. However, how S. insularis increases the cold tolerance then reduces it to survive winter temperature below 0°C remains unclear. In the transcriptomic of S. insularis, we identified three profiles (profile 25, 27, and 13) whose trends related to the cold tolerance. We detected 1,783 differentially expressed genes (in profile 25) and identified 522 genes enriched in the AMPK signaling pathway. The metabolome analysis identified 122 differential metabolites. We identified four co-pathways, among which “Glycerophospholipid metabolism” was the pathway most enriched in differentially expressed genes and differential metabolites. The AMPK signaling and glycerophospholipid metabolism pathways play key roles in the natural overwintering physiological process of S. insularis larvae.

Abstract Grasping and manipulation are fundamental ways for many creatures to interact with their environments. Different morphologies and grasping methods of “grippers” are highly evolved to adapt to harsh survival conditions. For example, human hands and bird feet are composed of rigid frames and soft joints. Compared with human hands, some plants like Drosera do not have rigid frames, so they can bend at arbitrary points of the body to capture their prey. Furthermore, many muscular hydrostat animals and plant tendrils can implement more complex twisting motions in 3D space. Recently, inspired by the flexible grasping methods present in nature, increasingly more bio‐inspired soft grippers have been fabricated with compliant and soft materials. Based on this, the present review focuses on the recent research progress of bio‐inspired soft grippers based on impactive gripping. According to their types of movement and a classification model inspired by biological “grippers”, soft grippers are classified into three types, namely, non‐continuum bending‐type grippers, continuum bending‐type grippers, and continuum twisting‐type grippers. An exhaustive and updated analysis of each type of gripper is provided. Moreover, this review offers an overview of the different stiffness‐controllable strategies developed in recent years.

BackgroundBeta-elemene has potent anti-tumor effect, but its anti-tumor mechanism remains unclear. Chromosome 3 open reading frame 21 (C3orf21) acts as a tumor suppressor. This study tested whether the anti-tumor effect of beta-elemene was associated with modulating C3orf21 expression in non-small cell lung cancer (NSCLC).Materials and MethodsThe impact of beta-elemene on C3orf21 expression in NSCLC cells was quantified. The stable C3orf21 silencing A549 and over-expressing PC-9 cells were established and their effects on the beta-elemene-attenuated proliferation, wound healing and invasion of NSCLC cells as well as the expression of key regulators and signal events were determined.ResultsBeta-elemene significantly up-regulated C3orf21 expression in NSCLC cells. Beta-elemene treatment significantly attenuated the proliferation, wound healing and invasion of NSCLC cells, which were significantly mitigated by C3orf21 silencing, but enhanced by C3orf21 over-expression. Similar patterns of beta-elemene-modulated cyclinD1, c-Myc, COX2, MMP2, MMP9, VEGF, PTEN and Notch1 expression were detected in NSCLC cells.ConclusionsSuch data indicated that beta-elemene treatment attenuated the malignancy of NSCLC cells by up-regulating C3orf21 expression. Our findings may provide new mechanisms underlying the pharmacological action of beta-elemene.

The European woodwasp, Sirex noctilio Fabricius, is a major invasive quarantine pest that attacks and kills pine trees outside of its native range. Insect gut structure and gut microbiota play crucial roles in various life activities. Despite a few reports in nutrition and survival, an extensive study on the S. noctilio larval gut microbiome is lacking. We studied the gut structure using a stereo microscope and used high throughput sequencing of the bacterial 16S rRNA genes and fungal internal transcribed spacer 2 (ITS2) regions to investigate gut microbiota in different developmental stages of S. noctilio, including larvae, adults, and larval frass. We used PICRUSt2 to predict the functional profiles. The larval gut was thin and thread-like from the oral cavity to the anus, carrying few xylem particles in the crop. Pseudomonas, Ralstonia, and Burkholderia s.l were the dominant bacteria in the guts of larvae, adults, and frass, respectively. Even though Pseudomonas was the most abundant among all bacteria, Zoogloea, Ruminobacter, and Nitrosospira, which might be involved in degrading organic matter and fixing nitrogen occurred exclusively in the larval gut indicating their possible role in the growth and development of larvae in pine tree xylem. Fungal communities did not change significantly across different developmental stages or the frass. Amylostereum was dominant in the woodwasp’s larval gut. Functional prediction of bacterial and fungal communities revealed that they may encod enzymes involved in degrading lignocellulose and fixing nitrogen. Ours is the first study that compares gut microbial communities present in S. noctilio larvae, adults, and frass. This study could provide an understanding of larval nutrient acquisition in nutrient-deficient host xylem to some extent. Our study may unlock novel strategies for the development of pest management approaches based on interfering with the gut microbiota and restricting their role in larval survival and development.

Adoptive cell therapy using TCR-engineered T cells (TCR-T cells) represents a promising strategy for treating relapsed and metastatic cancers. We previously established methods to identify neoantigen-specific TCRs based on patients’ PBMCs. However, in clinical practice isolation of PBMCs from advanced-stage cancer patients proves to be difficult. In this study, we substituted blood-derived T cells for tumor-infiltrating lymphocytes (TILs) and used an HLA-matched cell line of antigen-presenting cells (APCs) to replace autologous dendritic cells. Somatic mutations were determined in head and neck squamous cell carcinoma resected from two patients. HLA-A*02:01-restricted neoantigen libraries were constructed and transferred into HLA-matched APCs for stimulation of patient TILs. TCRs were isolated from reactive TIL cultures and functionality was tested using TCR- T cells in vitro and in vivo. To exemplify the screening approach, we identified the targeted neoantigen leading to recognition of the minigene construct that stimulated the strongest TIL response. Neoantigen peptides were used to load MHC-tetramers for T cell isolation and a TCR was identified targeting the KIAA1429D1358E mutation. TCR-T cells were activated, exhibited cytotoxicity, and secreted cytokines in a dose-dependent manner, and only when stimulated with the mutant peptide. Furthermore, comparable to a neoantigen-specific TCR that was isolated from the patient’s PBMCs, KIAA1429D1358E-specific TCR T cells destroyed human tumors in mice. The established protocol provides the required flexibility to methods striving to identify neoantigen-specific TCRs. By using an MHC-matched APC cell line and neoantigen-encoding minigene libraries, autologous TILs can be stimulated and screened when patient PBMCs and/or tumor material are not available anymore. Abbreviations: Head and neck squamous cell carcinoma (HNSCC); adoptive T cell therapy (ACT); T cell receptor (TCR); tumor-infiltrating lymphocytes (TIL); cytotoxic T lymphocyte (CTL); peripheral blood mononuclear cell (PBMC); dendritic cell (DC); antigen-presenting cells (APC)

The larvae of some trunk-boring beetles barely leave traces on the outside of trunks when feeding within, rendering the detection of them rather difficult. One approach to solving this problem involves the use of a probe to pick up boring vibrations inside the trunk and distinguish larvae activity according to the vibrations. Clean boring vibration signals without noise are critical for accurate judgement. Unfortunately, these environments are filled with natural or artificial noise. To address this issue, we constructed a boring vibration enhancement model named VibDenoiser, which makes a significant contribution to this rarely studied domain. This model is built using the technology of deep learning-based speech enhancement. It consists of convolutional encoder and decoder layers with skip connections, and two layers of SRU++ for sequence modeling. The dataset constructed for study is made up of boring vibrations of Agrilus planipennis Fairmaire, 1888 (Coleoptera: Buprestidae) and environmental noise. Our VibDenoiser achieves an improvement of 18.57 in SNR, and it runs in real-time on a laptop CPU. The accuracy of the four classification models increased by a large margin using vibration clips enhanced by our model. The results demonstrate the great enhancement performance of our model, and the contribution of our work to better boring vibration detection.

Pine needle gall midge (T. japonensis), native to Japan, has become a serious invasive pest in South Korea and, more recently in 2006, in China. It was first discovered in Qingdao, Shandong Province, and has caused serious damage to local Pinus thunbergii. The insect’s small size makes morphological-based identification difficult; therefore, molecular detection techniques are urgently needed for monitoring and preventing its further spread. At present, there is no simple and accurate field molecular identification tool. To solve this problem, a LAMP-based molecular diagnosis technology of T. japonensis was developed. Four LAMP primers were designed to specifically amplify T. japonensis DNA. Positive LAMP reactions usually produce amplification in one hour. The optimal incubation conditions for LAMP detection were determined with 4 LAMP primers for 60 min at 61 °C. The LAMP detection range of gDNA concentrations is wide, with a minimum detectable gDNA concentration of 300 fg. A non-destructive DNA-releasing procedure, HotSHOT “HS6”, which could extract “crude DNA” for LAMP assay in 10 min, was used for larval and adult samples. Therefore, we established a LAMP-based rapid molecular identification method that can be applied in the monitoring and management of T. japonensis.

Outbreaks of pine shoot beetles (Tomicus spp.) have caused widespread tree mortality in Southwest China. However, the understanding of the role of climatic drivers in pine shoot beetle outbreaks is limited. This study aimed to characterize the relationships between climate variables and pine shoot beetle outbreaks in the forests of Yunnan pine (Pinus yunnanensis Franch) in Southwest China. The pine shoot beetle-infested total area from 2000 to 2017 was extracted from multi-data Landsat images and obtained from field survey plots. A temporal prediction model was developed by partial least squares regression. The results indicated that multi consecutive year droughts was the strongest predictor, as such a condition greatly reduced the tree resistance to the beetles. The beetle-infested total area increased with spring temperature, associated with a higher success rate of trunk colonization and accelerated larval development. Warmer temperatures and longer solar radiation duration promoted flight activity during the trunk transfer to the shoot period and allowed the completion of sister broods. Multi consecutive year droughts combined with the warmer temperatures and higher solar radiation duration could provide favorable conditions for shoot beetle outbreaks. Generally, identifying the climate variables that drive pine shoot beetle outbreaks could help improve current strategies for outbreak control.

Auricularia cornea var. Li. polysaccharide (ACP) has many important biological activities and has potential application value in food engineering, pharmaceutical science, and health care. The results were as follows: the extraction rate of ACP was 28.18% ± 1.41% and the purity of ACP was 86.92% ± 2.80%. ACP contains mannitol 32.41%, glucuronic acid 6.96%, rhamnose 0.32%, glucose 42.35%, galactose 0.77%, xylose 16.83%, and fucose 0.36%, without galacturonic acid and arabinose. In addition, the results of an animal test of diabetes mellitus II (DM II) with ACP showed that the total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), and fasting blood glucose and water in the serum of mice with ACP were significantly lower than those in the model group; the serum SOD, hepatic glycogen, and insulin of mice added with ACP were significantly higher than those in the model group. More importantly, ACP had no significant adverse effects on organ index and liver and kidney tissue morphology in mice. These results suggest that ACP can be used as a potential functional food component for the prevention or treatment of diabetes.

Beijing’s One Million Mu Plain Afforestation Project involves planting large areas with the exotic North American tree species Fraxinus pennsylvanica Marsh (ash). As an exotic tree species, ash is very vulnerable to infestations by the emerald ash borer (EAB), a native Chinese wood borer pest. In the early stage of an EAB infestation, attacked trees show no obvious sign. Once the stand has reached the late damage stage, death occurs rapidly. Therefore, there is a need for efficient early detection methods of EAB stress over large areas. The combination of unmanned aerial vehicle (UAV)-based hyperspectral imaging (HI) with light detection and ranging (LiDAR) is a promising practical approach for monitoring insect disturbance. In this study, we identified the most useful narrow-band spectral HI data and 3D LiDAR data for the early detection of EAB stress in ash. UAV-HI data of different infested stages (healthy, light, moderate and severe) of EAB in the 400–1000 nm range were collected from ash canopies and were processed by Partial Least Squares–Variable Importance in Projection (PLS-VIP) to identify the maximally sensitive bands. Band R678 nm had the highest PLS-VIP scores and the most robust classification ability. We combined this band with band R776 nm to develop an innovative normalized difference vegetation index (NDVI(776,678)) to estimate EAB stress. LiDAR data were used to segment individual trees and supplement the HI data. The new NDVI(776,678) identified different stages of EAB stress, with a producer’s accuracy of 90% for healthy trees, 76.25% for light infestation, 58.33% for moderate infestation, and 100% for severe infestation, with an overall accuracy of 82.90% when combined with UAV-HI and LiDAR.

Acoustic detection technology is a new method for early monitoring of wood-boring pests, and the effective denoising methods are the premise of acoustic detection in forests. This paper used sensors to record Semanotus bifasciatus larval feeding sounds and various environmental noises, and two kinds of sounds were mixed to obtain the noisy feeding sounds with controllable noise intensity. Then, the time domain denoising models and frequency domain denoising models were designed, and the denoising effects were compared using the metrics of a signal-to-noise ratio (SNR), a segment signal-noise ratio (SegSNR), and log spectral distance (LSD). In the experiments, the average SNR increment could achieve 17.53 dB and 11.10 dB using the in the test data using the time domain features and frequency domain features, respectively. The average SegSNR increment achieved 18.59 dB and 12.04 dB, respectively, and the average LSD between pure feeding sounds and denoised feeding sounds were 0.85 dB and 0.84 dB, respectively. The experimental results demonstrated that the denoising models based on artificial intelligence were effective methods for S. bifasciatus larval feeding sounds, and the overall denoising effect was more significant, especially at low SNRs. In view of that, the denoising models using time domain features were more suitable for the forest area and quarantine environment with complex noise types and large noise interference.

Currently, the robustness of pest recognition algorithms based on sample augmentation with two-dimensional images is negatively affected by moth pests with different postures. Obtaining three-dimensional (3D) posture information of pests can provide information for 3D model deformation and generate training samples for deep learning models. In this study, an algorithm of the 3D posture information extraction method for Hyphantria cunea (Drury) based on monocular vision is proposed. Four images of every collected sample of H. cunea were taken at 90° intervals. The 3D pose information of the wings was extracted using boundary tracking, edge fitting, precise positioning and matching, and calculation. The 3D posture information of the torso was obtained by edge extraction and curve fitting. Finally, the 3D posture information of the wings and abdomen obtained by this method was compared with that obtained by Metrology-grade 3D scanner measurement. The results showed that the relative error of the wing angle was between 0.32% and 3.03%, the root mean square error was 1.9363, and the average relative error of the torso was 2.77%. The 3D posture information of H. cunea can provide important data support for sample augmentation and species identification of moth pests.

COVID-19 pandemic has infected millions of people with mortality exceeding >1 million. There is an urgent need to find therapeutic agents that can help clear the virus to prevent severe disease and death. Identifying effective and safer drugs can provide more options to treat COVID-19 infections either alone or in combination. Here, we performed a high throughput screening of approximately 1,700 US FDA-approved compounds to identify novel therapeutic agents that can effectively inhibit replication of coronaviruses including SARS-CoV-2. Our two-step screen first used a human coronavirus strain OC43 to identify compounds with anti-coronaviral activities. The effective compounds were then screened for their effectiveness in inhibiting SARS-CoV-2. These screens have identified 20 anti-SARS-CoV-2 drugs including previously reported compounds such as hydroxychloroquine, amlodipine besylate, arbidol hydrochloride, tilorone 2HCl, dronedarone hydrochloride, mefloquine, and thioridazine hydrochloride. Five of the newly identified drugs had a safety index (cytotoxic/effective concentration) of >600, indicating a wide therapeutic window compared to hydroxychloroquine which had a safety index of 22 in similar experiments. Mechanistically, five of the effective compounds (fendiline HCl, monensin sodium salt, vortioxetine, sertraline HCl, and salifungin) were found to block SARS-CoV-2 S protein-mediated cell fusion. These FDA-approved compounds can provide much needed therapeutic options that we urgently need during the midst of the pandemic.

The recent outbreak of human infections caused by SARS-CoV-2, the third zoonotic coronavirus has raised great public health concern globally. Rapid and accurate diagnosis of this novel pathogen posts great challenges not only clinically but also technologically. Metagenomic next-generation sequencing (mNGS) and reverse-transcription PCR (RT-PCR) have been the most commonly used molecular methodologies. However, each has their own limitations. In this study, we developed an isothermal, CRISPR-based diagnostic for COVID-19 with near single-copy sensitivity. The diagnostic performances of all three technology platforms were also compared. Our study aimed to provide more insights into the molecular detection of SARS-CoV-2, and also to present a novel diagnostic option for this new emerging virus.

ABSTRACT Amylostereum areolatum is the symbiotic fungus of the Eurasian woodwasp, Sirex noctilio, a globally invasive species. The mutualistic symbiont is associated with the woodwasp, assisting the damage process and providing nutrition for its insect partners. Colonization and growth of A. areolatum have essential impacts on the development and spread of S. noctilio, though the mechanism of interaction between the two has been poorly described. In this study, the first genome of this symbiotic fungus was sequenced, assembled, and annotated. The assembled A. areolatum genome was 57.5 Mb (54.51% GC content) with 15,611 protein-coding genes. We identified 580 carbohydrate-active enzymes (CAZymes), 661 genes associated with pathogen-host interactions, and 318 genes encoding transport proteins in total. The genome annotation revealed 10 terpene/phytoene synthases responsible for terpenoid biosynthesis, which could be classified into three clades. Terpene synthase gene clusters in clade II were conserved well across Russulales. In this cluster, genes encoding mevalonate kinase (MK), EGR12 (COG1557), and nonplant terpene cyclases (cd00687) were the known biosynthesis and regulatory genes. Genome sequence analysis of this fungus would prove the possibility of A. areolatum volatiles affecting the host selection of S. noctilio on a molecular basis. We further clarified that A. areolatum was a strict obligate symbiotic fungus. The wasps might protect the fungus before it was introduced into a suitable host substrate by oviposition, while the fungus would provide S. noctilio with a suitable environment and nutrients for the larval growth. These results would lay a foundation for our understanding of the mechanism of this entomogenous symbiosis. IMPORTANCE Sirex noctilio (F.), together with Amylostereum areolatum, a wood-decaying symbiotic fungus, causes severe damage to Pinus species worldwide. In China, it causes extensive death of Mongolian pine (Pinus sylvestris var. mongolica). There is an obligate dependency mutualism between the woodwasp and its fungus. Studies have suggested that the fungal growth rate affected the size of the wasps: larger adults emerged from sites with a higher fungus growth rate. This genome is the first reported genome sequence of a woodwasp symbiotic fungus. Genome sequence analysis of this fungus would prove the possibility of A. areolatum volatiles affecting the host selection of S. noctilio on a molecular basis. We further clarified that A. areolatum was a strict obligate symbiotic fungus and that it would provide S. noctilio with a suitable environment and with nutrients for the larval growth. These results would lay a foundation for our understanding of the mechanism of this entomogenous symbiosis.

Securinega suffruticosa (Pall.) Rehd is an excellent natural secondary shrub in the Shell Islands of Yellow River Delta. The roots of S. suffruticosa have high medicinal value and are used to treat diseases, such as neurasthenia and infant malnutrition. Any organism that is isolated from this species is of immense interest due to its potential novel bioactive compounds. In this research, the distribution and diversity of culturable endophytic fungi in S. suffruticosa were studied, and the endophytic fungi with antimicrobial activity were screened. A total of 420 endophytic fungi isolates were obtained from the S. suffruticosa grown in Shell Islands, from which 20 genera and 35 species were identified through morphological and internal transcribed spacer (ITS) sequence analyses. Chaetomium, Fusarium, Cladosporium, and Ceratobasidium were the dominant genera. The high species richness S (42), Margalef index D' (5.6289), Shannon-Wiener index H' (3.1000), Simpson diversity index Ds (0.9459), PIE index (0.8670), and evenness Pielou index J (0.8719) and a low dominant index λ (0.0541) indicated the high diversity of endophytic fungi in S. suffruticosa, the various species of endophytic fungi with obvious tissue specificity. The inhibition percentages of the 12 species of such endophytic fungi against Colletotrichum siamense were 3.6%-26.3%. C. globosum, Fusarium sp.3, and C. ramotenellum had a high antibacterial activity against Enterococcus faecalis, Escherichia coli, Pseudomonas aeruginosa, and Staphylococcus aureus. The Minimum Inhibitory Concentration (MIC) and the Minimum Bactericidal Concentration (MBC) were between 0.5 mg/mL and 2 mg/mL. Alkaloid content detection indicated that endophytic fungi had a high alkaloid content, whereas the alkaloid contents of C. globosum and Fusarium sp.3 reached 0.231% and 0.170%, respectively. Members belonging to the endophytic fungal community in the S. suffruticosa of Shell Islands that may be used as antagonists and antibacterial agents for future biotechnology applications were identified for the first time.

In the medical system, the verification, preservation and synchronization of electronic medical records has always been a difficult problem, and the random dissemination of patient records will bring various risks to patient privacy. Therefore, how to achieve secure data sharing on the basis of ensuring users' personal privacy becomes the key. In recent years, blockchain has been proposed to be a promising solution to achieve data sharing with security and privacy preservation due to its advantages of immutability. So, a distributed electronic medical records searchable scheme was proposed by leveraging blockchain and smart contract technology. Firstly, we perform a hash calculation on the electronic medical data and store the corresponding value on the blockchain to ensure its integrity and authenticity. Then, we encrypt the electronic medical data and store it in the interplanetary file system which is a distributed storage protocol. These operations not only can solve centralized data store of servers of several medical institutions, but also be good at lowering stress from data store and high-frequency access to blockchain. Secondly, the encrypted keyword index information of electronic medical records was stored on the Ethereum blockchain, meanwhile a smart contract deployed in the Ethereum blockchain is used to realize keyword search instead of depending on a centralized third party. Furthermore, we use attribute-based encryption scheme to ensure that only the attributes meeting the access policy can decrypt the encrypted electronic medical records. Finally, our performance analysis and security analysis show that the scheme is secure and efficient.

Forests are increasingly threatened worldwide by the establishment of non-native species arriving from other continents with globalization of trade and international travels. We compiled comprehensive lists of non-native insects associated to woody plants in Europe and China to compare their invasive patterns between these two regions. By 2019, a total of 449 species have colonized forest, ornamental and fruits trees and shrubs in Europe whereas only 77 species were reported in China, a likely underestimated number because studies concentrated on economically-important species. Approximately 6.1 new species have been detected per year since 2000 in Europe vs. only 1.9 in China. Europe and China also exhibited distinct patterns in the invasion sources. Most non-native species recorded in Europe originated from Asia (37.2%), and more especially from China (22.9%) whereas Europe was only a minor source for the insect invasions in China (9.1%), which predominantly originated from other parts of Asia (40.3%). These different patterns likely reflect the dissimilar trends of the trade in ornamental plants. Taxonomic and guild composition of non-native insects in both regions confirmed that ornamental trade of plants for planting including fruit trees played a larger role than timber and wood trade in shaping the non-native entomofaunas associated to woody plants. Hemiptera, and subsequently sap suckers, largely dominated the non-native entomofauna in both regions. However, there were striking differences in the range of hosts these species colonized. Although fruit trees, and especially Citrus, are the most important hosts in both regions, tropical trees including palms were also highly colonized in China whereas deciduous trees, shrubs and conifers were proportionally more affected in Europe. Quite a half of the non-native insect species did not switch from their original, non-native host to natives ones in Europe whereas only a minority of these insect invaders still sticked to their original, non-native host in China. It may be due to the more important presence in China of native woody plants taxonomically close to the original host.

Sirex noctilio is a major international quarantine pest that recently emerged in northeast China to specifically invade conifers. During female oviposition, venom is injected into the host together with its symbiotic fungus to alter the normal Pinus physiology and weaken or even kill the tree. In China, the Mongolian pine (Pinus sylvestris var. mongolica), an important wind-proof and sand-fixing species, is the unique host of S. noctilio. To explore the interplay between S. noctilio venom and Mongolian pine, we performed a transcriptome comparative analysis of a 10-year-old Mongolian pine after wounding and inoculation with S. noctilio venom. The analysis was performed at 12 h, 24 h and 72 h. PacBio ISO-seq was used and integrated with RNA-seq to construct an accurate full-length transcriptomic database. We obtained 52,963 high-precision unigenes, consisting of 48,654 (91.86%) unigenes that were BLASTed to known sequences in the public database and 4309 unigenes without any annotation information, which were presumed to be new genes. The number of differentially expressed genes (DEGs) increased with the treatment time, and the DEGs were most abundant at 72 h. A total of 706 inoculation-specific DEGs (475 upregulated and 231 downregulated) and 387 wounding-specific DEGs (183 upregulated and 204 downregulated) were identified compared with the control. Under venom stress, we identified 6 DEGs associated with reactive oxygen species (ROS) and 20 resistance genes in Mongolian pine. Overall, 52 transcription factors (TFs) were found under venom stress, 45 of which belonged to the AP2/ERF TF family and were upregulated. A total of 13 genes related to the photosystem, 3 genes related photo-regulation, and 9 TFs were identified under wounding stress. In conclusion, several novel putative genes were found in Mongolian pine by PacBio ISO seq. Meanwhile, we also identified various genes that were resistant to S. noctilio venom, such as GAPDH, GPX, CAT, FL2, CERK1, and HSP83A, etc.

Quantitative reverse transcription polymerase chain reaction (qRT-PCR) is a powerful technique for studying gene expression. The key to quantitative accuracy depends on the stability of the reference genes used for data normalization under different experimental conditions. Pine wood nematode (PWN, Bursaphelenchus xylophilus) is the causal agent of the devastating pine wilt disease (PWD). Extensive and prompt research is needed to understand the molecular mechanism of PWD, but identification of the reference PWN genes for standardized qRT-PCR has not been reported yet. We have analyzed eight candidate reference genes of PWN across different temperature conditions and developmental stages. Delta Ct method, GeNorm, NormFinder, BestKeeper, and RefFinder algorithms were used to evaluate the stability of expression of these genes. Finally, we use heat shock protein 90 (HSP90) in different temperatures and arginine kinase gene (AK) in different developmental stages to confirm the stability of these genes. UBCE and EF1γ were most stable across different temperature treatments, whereas EF1γ and Actin were most stable across different developmental stages. In general, these results indicate that EF1γ is the most stable gene for qRT-PCR under different conditions. The systematic analysis of qRT-PCR reference gene selection will be helpful for future functional analysis and exploration of B. xylophilus genetic resources.

The red turpentine beetle (Dendroctonus valens LeConte) has caused severe ecological and economic losses since its invasion into China. It gradually spreads northeast, resulting in many Chinese pine (Pinus tabuliformis Carr.) deaths. Early detection of D. valens infestation (i.e., at the green attack stage) is the basis of control measures to prevent its outbreak and spread. This study examined the changes in spectral reflectance after initial attacking of D. valens. We also explored the possibility of detecting early D. valens infestation based on spectral vegetation indices and machine learning algorithms. The spectral reflectance of infested trees was significantly different from healthy trees (p < 0.05), and there was an obvious decrease in the near-infrared region (760–1386 nm; p < 0.01). Spectral vegetation indices were input into three machine learning classifiers; the classification accuracy was 72.5–80%, while the sensitivity was 65–85%. Several spectral vegetation indices (DID, CUR, TBSI, DDn2, D735, SR1, NSMI, RNIR•CRI550 and RVSI) were sensitive indicators for the early detection of D. valens damage. Our results demonstrate that remote sensing technology could be successfully applied to early detect D. valens infestation and clarify the sensitive spectral regions and vegetation indices, which has important implications for early detection based on unmanned airborne vehicle and satellite data.

Abstract Background Transcription factor forkhead box M1 (FOXM1) is a crucial regulator in colorectal cancer (CRC) progression. However, the regulatory mechanisms causing dysregulation of FOXM1 in CRC remain unclear. Methods Dual-luciferase reporter assay was conducted to determine FOXM1 as miR-6868-5p target. The function of miR-6868-5p and FOXM1 in CRC angiogenesis was verified in vitro. Intratumoral injection model was constructed to explore the effect of miR-6868-5p on angiogenesis in vivo. Chromatin immunoprecipitation assays were used to assess direct binding of H3K27me3 to the miR-6868 promoter. Results Through integrated analysis, we identified miR-6868-5p as the potent regulator of FOXM1. Overexpression of miR-6868-5p in CRC cells inhibited the angiogenic properties of co-cultured endothelial cells, whereas silencing of miR-6868-5p had opposite effects. In vivo delivery of miR-6868-5p blocked tumor angiogenesis in nude mice, resulting in tumor growth inhibition. Rescue of FOXM1 reversed the effect of miR-6868-5p on tumor angiogenesis. Further mechanistic study revealed that FOXM1 promoted the production of IL-8, which was responsible for the miR-6868-5p/FOXM1 axis-regulated angiogenesis. Reciprocally, FOXM1 inhibited miR-6868-5p expression through EZH2-mediated H3K27me3 on miR-6868-5p promoter, thus forming a feedback circuit. Clinically, the level of miR-6868-5p was downregulated in CRC tissues and inversely correlated with microvessel density as well as levels of FOXM1 and IL-8 in tumor specimens. Conclusions Together, these data identify miR-6868-5p as a novel determinant of FOXM1 expression and establish a miR-6868-5p/FOXM1 regulatory circuit for CRC angiogenesis, providing potential target for CRC treatment.

Alteration of protein O-glycosylation in various human cancers including breast cancer is well known, but molecular roles of their aberrant glycosylations on cancer have not been fully understood. We previously reported critical roles of polypeptide N-acetylgalactosaminyltransferase 6 (GALNT6 or GalNAc-T6) that was upregulated in a great majority of breast cancer tissues. Here we further report O-glycosylation of estrogen receptor alpha (ER-α) by GALNT6 and the significant role of its nuclear localization in breast cancer cells. Knockdown of GALNT6 expression in two breast cancer cell lines, T47D and MCF7, in which both ER-α and GALNT6 were highly expressed, by small interfering RNA could significantly attenuate expression of ER-α. Immunocytochemical analysis clearly demonstrated the drastic decrease of ER-α protein in the nucleus of these cancer cells. Accordingly, the downstream genes of the ER-α pathway such as MYC, CCND1, and CTSD were significantly downregulated. We confirmed GALNT6-dependent ER-α O-glycosylation and identified O-glycosylation of S573 in an F domain of ER-α by GALNT6 through LC-MS/MS analysis. We also obtained evidences showing that the glycosylation of ER-α at S573 by GALNT6 is essential for protein stability and nuclear localization of ER-α in breast cancer cells. Furthermore, we designed cell membrane–permeable peptides including the O-glycosylation site and found a significant decrease of the cell viability of breast cancer cells by treatment of these peptides in a GALNT6 expression–dependent manner. Our study suggests that targeting the GALNT6 enzymatic activity as well as the GALNT6/ER-α interaction could be a promising therapeutic approach to ER-α–positive breast cancer patients.

Cohesin is a multimeric nuclear protein complex which includes STAG2 and is associated with vital roles during cell division. Here in a genome-wide CRISPR-Cas9 screen, the authors identify a novel role of STAG2 as a crucial component of the innate immune response to rotavirus.