Search

The precipitation of solutes is a major cause of irradiation hardening and embrittlement limiting the service life of reactor pressure vessel (RPV) steels. Impurities play a significant role in the formation of precipitation in RPV materials. In this study, the effects of carbon on cluster formation and irradiation hardening were investigated in an RPV alloy Fe-1.35Mn-0.75Ni using C and Fe ions irradiation at 290 °C. Nanoindentation results showed that C ion irradiation led to less hardening below 1.0 dpa, with hardening continuing to increase gradually at higher doses, while it was saturated under Fe ion irradiation. Atom probe tomography revealed a broad size distribution of Ni–Mn clusters under Fe ion irradiation, contrasting a narrower size distribution of small Ni–Mn clusters under C ion irradiation. Further analysis indicated the influence of carbon on the cluster formation, with solute-precipitated defects dominating under C ion irradiation but interstitial clusters dominating under Fe ion irradiation. Simulations suggested that carbon significantly affected solute nucleation, with defect clusters displaying smaller size and higher density as carbon concentration increased. The higher hardening at doses above 1.0 dpa was attributed to a substantial increase in the number density of defect clusters when carbon was present in the matrix.

ABSTRACT Mixotrophy is an important trophic strategy for bacterial survival in the ocean. However, the global relevance and identity of the major mixotrophic taxa remain largely elusive. Here, we combined phylogenetic, metagenomic, and metatranscriptomic analyses to characterize ubiquitous Arcobacteraceae based on our deep-sea in situ incubations and the global data. The phylogenomic tree of Arcobacteraceae is divided into three large clades, among which members of clades A and B are almost all from terrestrial environments, while those of clade C are widely distributed in various marine habitats in addition to some terrestrial origins. All clades harbor genes putatively involved in chitin degradation, sulfide oxidation, hydrogen oxidation, thiosulfate oxidation, denitrification, dissimilatory nitrate reduction to ammonium, microaerophilic respiration, and metal (iron/manganese) reduction. Additionally, in clade C, more unique pathways were retrieved, including thiosulfate disproportionation, ethanol fermentation, methane oxidation, fatty acid oxidation, cobalamin synthesis, and dissimilatory reductions of sulfate, perchlorate, and arsenate. Within this clade, two mixotrophic Candidatus genera represented by UBA6211 and CAIJNA01 harbor genes putatively involved in the reverse tricarboxylic acid pathway for carbon fixation. Moreover, the metatranscriptomic data in deep-sea in situ incubations indicated that the latter genus is a mixotroph that conducts carbon fixation by coupling sulfur oxidation and denitrification and metabolizing organic matter. Furthermore, global metatranscriptomic data confirmed the ubiquitous distribution and global relevance of Arcobacteraceae in the expression of those corresponding genes across all oceanic regions and depths. Overall, these results highlight the contribution of previously unrecognized Arcobacteraceae to carbon, nitrogen, and sulfur cycling in global oceans.IMPORTANCEMarine microorganisms exert a profound influence on global carbon cycling and ecological relationships. Mixotrophy, characterized by the simultaneous utilization of both autotrophic and heterotrophic nutrition, has a significant impact on the global carbon cycling. This report characterizes a group of uncultivated bacteria Arcobacteraceae that thrived on the “hot time” of bulky particulate organic matter and exhibited mixotrophic strategy during the in situ organic mineralization. Compared with clades A and B, more unique metabolic pathways were retrieved in clade C, including the reverse tricarboxylic acid pathway for carbon fixation, thiosulfate disproportionation, methane oxidation, and fatty acid oxidation. Global metatranscriptomic data from the Tara Oceans expeditions confirmed the ubiquitous distribution and extensive transcriptional activity of Arcobacteraceae with the expression of genes putatively involved in carbon fixation, methane oxidation, multiple sulfur compound oxidation, and denitrification across all oceanic regions and depths.

Renal cell carcinoma (RCC) is a common urinary tract tumor that arises from the highly heterogeneous epithelium of the renal tubules. The incidence of kidney cancer is second only to the incidence of bladder cancer, and has shown an upward trend over time. Although surgery is the preferred treatment for localized RCC, treatment decisions should be customized to individual patients considering their overall health status and the risk of developing or worsening chronic kidney disease postoperatively. Anticancer drugs are preferred to prevent perioperative and long-term postoperative complications; however, resistance to chemotherapy remains a considerable problem during the treatment process. To overcome this challenge, nanocarriers have emerged as a promising strategy for targeted drug delivery for cancer treatment. Nanocarriers can transport anticancer agents, achieving several-fold higher cytotoxic concentrations in tumors and minimizing toxicity to the remaining parts of the body. This article reviews the use of nanomaterials, such as liposomes, polymeric nanoparticles, nanocomposites, carbon nanomaterials, nanobubbles, nanomicelles, and mesoporous silica nanoparticles, for RCC treatment, and discusses their advantages and disadvantages.

This work studies the defect features in a dilute FeMnNi alloy by an Object Kinetic Monte Carlo (OKMC) model based on the ''grey-alloy'' method. The dose rate effect is studied at 573 K in a wide range of dose rates from 10−8 to 10−4 displacement per atom (dpa)/s and demonstrates that the density of defect clusters rises while the average size of defect clusters decreases with increasing dose rate. However, the dose-rate effect decreases with increasing irradiation dose. The model considered two realistic mechanisms for producing -type self-interstitial atom (SIA) loops and gave reasonable production ratios compared with experimental results. Our simulation shows that the proportion of -type SIA loops could change obviously with the dose rate, influencing hardening prediction for various dose rates irradiation. We also investigated ways to compensate for the dose rate effect. The simulation results verified that about a 100 K temperature shift at a high dose rate of 1 × 10−4 dpa/s could produce similar irradiation microstructures to a lower dose rate of 1 × 10−7 dpa/s irradiation, including matrix defects and deduced solute migration events. The work brings new insight into the OKMC modeling and the dose rate effect of the Fe-based alloys.

Colonic endoscopy is the gold standard for detecting rectal polyps and rectal cancer. In which polyps are a major predisposing factor for colorectal cancer, the precise diagnosis of polyps within colorectal endoscopy is highly dependent on a physician of professional level. With the development of deep learning, some semantic segmentation methods have recently been applied to polyp detection, but there are problems with insufficient accuracy and segmentation speed. To this end, we propose a precision adaptive global context network (AGCNet) based on real-time colon endoscopy. Firstly, in order to adapt to the problem of large-scale variation of polyps, we designed a multi-scale semantic fusion module (MSFM), which enhances the representation capability by varieties of filters to collect contextual information at different scales, thus adapting to the problem of large variation of polyp size, especially smaller polyps. In addition, modelling long-range dependence by simply using complex spatial pixels tends to introduce more background noise and increase the computational effort. To this end, a context-aware pyramid aggregation module (CPAM) was designed, which internally includes a novel dual attention mechanism whereby the CPAM aggregates feature information across different regions to boost the network’s ability to utilize global context and model long-range dependency through dual attention to further reinforce the features information of important regions and efficiently suppress features in non-important regions. Additionally, the CPAM performs multi-level pooling on the input features to extract multi-scale context information from the image and uses an attention mechanism to selectively highlight informative regions of the image that are most relevant to the segmentation task. The module fuses the multi-level pooled features with the attention map to produce enhanced feature representations that capture both global and local information. Thereby achieving precise polyp segmentation and taking real-time into account. Our proposed AGCNet performed extensive experimental studies on datasets Kvasir-SEG, CVC-ClinicDB, CVC-ColonDB and ETIS-LaribPolypDB. Specifically, AGCNet achieved an IoU of 87.40% and a Dice score of 92.63% on the Kvasir dataset, achieving accurate segmentation results faster than many current state-of-the-art models.

Although the detailed biosynthetic mechanism is still unclear, the unique secondary metabolites of Ginkgo biloba, including ginkgolic acids (GAs) and terpene trilactones, have attracted increasing attention for their potent medicinal, physiological and biochemical properties. In particular, GAs have shown great potential in the fields of antibacterial and insecticidal activities, making it urgent to elucidate their biosynthetic mechanism. In this study, we systematically revealed the landscape of metabolic-transcriptional regulation across continuous growth stages of G. biloba seeds (GBS) based on multi-omics mining and experimental verification, and successfully identified all major types of GAs and terpene trilactones along with more than a thousand kinds of other metabolites. The phenological changes and the essential gene families associated with these unique metabolites were analyzed in detail, and several potential regulatory factors were successfully identified based on co-expression association analysis. In addition, we unexpectedly found the close relationship between large introns and the biosynthesis of these secondary metabolites. These genes with large introns related to the synthesis of secondary metabolites showed higher gene expression and expression stability in different tissues or growth stages. Our results may provide a new perspective for the study of the regulatory mechanism of these unique secondary metabolites in GBS.

Through the synergy of nervous system and the self-regulation of muscle stiffness, living organisms are capable of quickly adjusting movements and actively adapting to dynamic environments. Likewise, the stiffness-changing and self-sensing functionalities are critical to empower soft robots with adjustable load capacity and agile movement. This work presents a paradigm for the design and fabrication of soft actuators with stiffness tunability and intrinsic self-sensing feedback through 4D printing method. The integration of 4D printed conductive composite into soft actuator body allows for stiffness adjustment within three orders of magnitude and ensures real-time stiffness-sensing, bending-sensing and pressure-sensing feedback. By constructing the theoretical deformation models and decoupling the resistance signals by machine learning methods, information on the stiffness, deformation and pressure of the material at different temperatures can be obtained. Cardiac-mimicking actuator and active therapeutic insoles are fabricated as proof-of-concept demonstrations, among which the active therapeutic insoles can perceive plantar pressure changes and conduct pressure-releasing actuation to ease the pain of patient at walk. It demonstrates the potential of this design approach for versatile applications such as medical assistive devices, artificial muscles, soft robotics, etc.

Patients with cholangiocarcinoma (CCA) often have an unfavorable prognosis because of its insidious nature, low resectability rate, and poor response to anticancer drugs and radiotherapy, which makes early detection and treatment difficult. At present, CCA has a five-year overall survival rate (OS) of only 5%, despite advances in therapies. New an increasing number of evidence suggests that nanoplatforms may play a crucial role in enhancing the pharmacological effects and in reducing both short- and long-term side effects of cancer treatment. This document reviews the advantages and shortcomings of nanoparticles such as liposomes, polymeric nanoparticle，inorganic nanoparticle, nano-metals and nano-alloys, carbon dots, nano-micelles, dendrimer, nano-capsule, bio-Nanomaterials in the diagnosis and treatment of CCA and discuss the current challenges in of nanoplatforms for CCA.

Abstract It is well known that the Doppler frequency shift contains the emitter location information. The problem of emitter location based on frequency of arrival (FOA) measurements of multiple moving observers is focussed. In contrast to most relevant works, the newly proposed positioning methods consider the influence of signal frequency deviation due to source instability and present two mathematical models of the frequency deviation. The first model assumes that the frequency offset is a small random parameter. A two‐stage closed‐form location method (called method a) is proposed. In stage 1, a set of pseudo‐linear equations are established according to the geometric relationship between the observers and emitter, so as to obtain an intermediate estimate of source position. Stage 2 returns to the original FOA measurement model and uses the estimation result in stage 1 to construct the second set of pseudo‐linear equations, yielding the final positioning result. The second model assumes that the signal frequency deviation is a large deterministic parameter. We propose an alternative two‐stage localisation method (called method b). In stage 1, a decoupling optimisation algorithm is developed based on the pseudo‐linear equations derived in stage 1 of method a, and intermediate estimates of the source position and frequency deviation are obtained successively. Stage 2 returns to the original FOA measurement model again and forms the second set of pseudo‐linear equations, yielding the final closed‐form solutions of emitter position and frequency offset. Both methods are proved analytically to achieve the Cramér–Rao bound (CRB) under the moderate noise level. Simulation results demonstrate the superior performance of the new methods.

ABSTRACT Transfer of animal and plant detritus of both terrestrial and marine origins to the deep sea occurs on a global scale. Microorganisms play an important role in mineralizing them therein, but these are yet to be identified in situ. To observe key bacteria involved, we conducted long-term in situ incubation and found that members of the family Marinifilaceae (MF) occurred as some of the most predominant bacteria thriving on the new inputs of plant and animal biomasses in the deep sea in both marginal and oceanic areas. This taxon is diverse and ubiquitous in marine environments. A total of 11 MAGs belonging to MF were retrieved from metagenomic data and diverged into four subgroups in the phylogenomic tree. Based on metagenomic and metatranscriptomic analyses, we described the metabolic features and in situ metabolizing activities of different subgroups. The MF-2 subgroup, which dominates plant detritus-enriched cultures, specializes in polysaccharide degradation and lignin oxidation and has high transcriptional activities of related genes in situ. Intriguingly, members of this subgroup encode a nitrogen fixation pathway to compensate for the shortage of nitrogen sources inside the plant detritus. In contrast, other subgroups dominating the animal tissue-supported microbiomes are distinguished from MF-2 with regard to carbon and nitrogen metabolism and exhibit high transcriptional activity for proteolysis in situ. Despite these metabolic divergences of MF lineages, they show high in situ transcriptional activities for organic fermentation and anaerobic respiration (reductions of metal and/or dimethyl sulfoxide). These results highlight the role of previously unrecognized Marinifilaceae bacteria in organic matter mineralization in marine environments by coupling carbon and nitrogen cycling with metal and sulfur. IMPORTANCE Microbial mineralization of organic matter has a significant impact on the global biogeochemical cycle. This report confirms the role of Marinifilaceae in organic degradation in the oceans, with a contribution to ocean carbon cycling that has previously been underestimated. It was the dominant taxon thriving on plant and animal biomasses in our in situ incubator, as well as in whale falls and wood falls. At least 9 subgroups were revealed, and they were widely distributed in oceans globally but predominant in organic-matter-rich environments, with an average relative abundance of 8.3%. Different subgroups display a preference for the degradation of different macromolecules (polysaccharides, lignin, and protein) and adapt to their environments via special metabolic mechanisms.

Abstract Background Osteoporosis and cardiovascular disease (CVD) are age-related diseases. It is reported that patients with CVD have a higher risk of bone loss. This retrospective study sought to reveal the association between osteoporosis and CVD in Chinese women. Although epidemiological evidence has indicated a relationship between the two, clinical data in southeast China are lacking. Methods In total, 2873 participants completed the baseline survey from January 2007 to October 2019, and 2039 were included in this retrospective study. We divided all subjects into an osteoporosis group and a non-osteoporosis group based on their bone mineral density (BMD). Dual-energy X-ray absorptiometry (DXA) was used to examine BMD. The general information came from the questionnaire survey. Cardiovascular diseases were defined by asking participants at the first visit and checking relevant medical records if they had suffered from hypertension, coronary heart disease, or cerebral infarction. Results According to the criterion, the osteoporosis group had 678 subjects, and the non-osteoporosis group had 1361 subjects. Subjects in the osteoporosis group had a significantly higher prevalence of hypertension and coronary heart disease. Besides, the proportion of subjects who drank tea and drank milk were relatively higher in the osteoporosis group. The odds ratio (OR) for suffering from osteoporosis was high if the patients had hypertension. Conclusions This study indicated that Chinese postmenopausal women with osteoporosis had a higher prevalence of hypertension. Hypertension was significantly associated with osteoporosis.

Abstract Background Recent research has suggested that cardiotrophin-like cytokine factor 1 (CLCF1) may be an important regulator of bone homeostasis. Furthermore, a whole gene chip analysis suggested that the expression levels of CLCF1 in the peripheral blood mononuclear cells (PBMCs) were downregulated in postmenopausal women with osteoporosis. This study aimed to assess whether the expression levels of CLCF1 in PBMCs can reflect the severity of bone mass loss and the related fracture risk. Methods In all, 360 postmenopausal women, aged 50 to 80 years, were included in the study. A survey to evaluate the participants’ health status, measurement of bone mineral density (BMD), routine blood test, and CLCF1 expression level test were performed. Results Based on the participants’ bone health, 27 (7.5%), 165 (45.83%), and 168 (46.67%) participants were divided into the normal, osteopenia, and osteoporosis groups, respectively. CLCF1 protein levels in the normal and osteopenia groups were higher than those in the osteoporosis group. While the CLCF1 mRNA level was positively associated with the BMD of total femur (r = 0.169, p = 0.011) and lumbar spine (r = 0.176, p = 0.001), the protein level was positively associated with the BMD of the lumbar spine (r = 0.261, p

Muscles are capable of modulating the body and adapting to environmental changes with a highly integrated sensing and actuation. Inspired by biological muscles, coiled/twisted fibers are adopted that can convert volume expansion into axial contraction and offer the advantages of flexibility and light weight. However, the sensing-actuation integrated fish line/yarn-based artificial muscles are still barely reported due to the poor actuation-sensing interface with off-the-shelf fibers. We report herein artificial coiled yarn muscles with self-sensing and actuation functions using the commercially available yarns. Via a two-step process, the artificial coiled yarn muscles are proved to obtain enhanced electrical conductivity and durability, which facilitates the long-term application in human-robot interfaces. The resistivity is successfully reduced from 172.39 Ω·cm (first step) to 1.27 Ω·cm (second step). The multimode sense of stretch strain, pressure, and actuation-sensing are analyzed and proved to have good linearity, stability and durability. The muscles could achieve a sensitivity (gauge factor, GF) of the contraction strain perception up to 1.5. We further demonstrate this self-aware artificial coiled yarn muscles could empower non-active objects with actuation and real-time monitoring capabilities without causing damage to the objects. Overall, this work provides a facile and versatile tool in improving the actuation-sensing performances of the artificial coiled yarn muscles and has the potential in building smart and interactive soft actuation systems.

ABSTRACTIntroduction The mRNA vaccine technologies have progressed rapidly in recent years. The COVID-19 pandemic has accelerated the application of mRNA vaccines, with research and development and clinical trials underway for many vaccines. Application of the quality by design (QbD) framework to mRNA vaccine development and establishing standardized quality control protocols for mRNA vaccines are essential for the continued development of high-quality mRNA vaccines.Areas covered mRNA vaccines include linear mRNA, self-amplifying mRNA, and circular RNA vaccines. This article summarizes the progress of research on quality control of these three types of vaccines and presents associated challenges and considerations.Expert opinion Although there has been rapid progress in research on linear mRNA vaccines, their degradation patterns remain unclear. In addition, standardized assays for key impurities, such as residual dsRNA and T7 RNA polymerase, are still lacking. For self-amplifying mRNA vaccines, a key focus should be control of stability in vivo and in vitro. For circular RNA vaccines, standardized assays, and reference standards for determining degree of circularization should be established and optimized.

ABSTRACTIntroduction Following the coronavirus disease pandemic, respiratory mucosal vaccines that elicit both mucosal and systemic immune responses have garnered increasing attention. However, human physiological characteristics pose significant challenges in the evaluation of mucosal immunity, which directly impedes the development and application of respiratory mucosal vaccines.Areas Covered This study summarizes the characteristics of immune responses in the respiratory mucosa and reviews the current status and challenges in evaluating immune response to respiratory mucosal vaccines.Expert Opinion Secretory Immunoglobulin A (S-IgA) is a major effector molecule at mucosal sites and a commonly used indicator for evaluating respiratory mucosal vaccines. However, the unique physiological structure of the respiratory tract pose significant challenges for the clinical collection and detection of S-IgA. Therefore, it is imperative to develop a sampling method with high collection efficiency and acceptance, a sensitive detection method, reference materials for mucosal antibodies, and to establish a threshold for S-IgA that correlates with clinical protection. Sample collection is even more challenging when evaluating mucosal cell immunity. Therefore, a mucosal cell sampling method with high operability and high tolerance should be established. Targets of the circulatory system capable of reflecting mucosal cellular immunity should also be explored.

Abstract Background Disease-modifying antirheumatic drugs (DMARDs) are widely used for treating rheumatoid arthritis (RA). However, there are no established biomarkers to predict a patient’s response to these therapies. Prostanoids, encompassing prostaglandins, prostacyclins, and thromboxanes, are potent lipid mediators implicated in RA progression. Nevertheless, the influence of DMARDs on prostanoid biosynthesis in RA patients remains poorly understood. This study aims to assess the impact of various DMARDs on urinary prostanoids levels and to explore whether urinary prostanoid profiles correlate with disease activity or response to therapy. Methods This study included 152 Swedish female patients with early RA, all rheumatoid factor (RF) positive, enrolled in the NORD-STAR trial (registration number: NCT01491815). Participants were randomized into four therapeutic regimes: methotrexate (MTX) combined with (i) prednisolone (arm ACT), (ii) TNF-α blocker certolizumab pegol (arm CZP), (iii) CTLA-4Ig abatacept (arm ABA), or (iv) IL-6R blocker tocilizumab (arm TCZ). Urine samples, collected before start of treatment and at 24 weeks post-treatment, were analyzed for tetranor-prostaglandin E metabolite (tPGEM), tetranor-prostaglandin D metabolite (tPGDM), 2,3-dinor thromboxane B2 (TXBM), 2,3-dinor-6-keto prostaglandin F1a (PGIM), leukotriene E4 (LTE4) and 12-hydroxyeicosatetraenoic acid (12-HETE) using liquid chromatography–mass spectrometry (LC–MS). Generalized estimating equation (GEE) models were used to analyze the change in urinary eicosanoids and their correlations to clinical outcomes. Results Patients receiving MTX combined with CZP or TCZ exhibited significant elevations in urinary tPGEM and TXBM levels after 24 weeks of treatment. Other eicosanoids did not show significant alterations in response to any treatment. Baseline urinary eicosanoid levels did not correlate with baseline clinical disease activity index (CDAI) levels, nor with changes in CDAI from baseline to week 24. Their levels were also similar between patients who achieved CDAI remission and those with active disease at week 24. Conclusions Treatment with anti-TNF or anti-IL6R agents in early RA patients leads to an increased systemic production of proinflammatory and prothrombotic prostanoids. However, urinary eicosanoid levels do not appear to be predictive of the response to DMARDs therapy.

Background: The treatment for cerebral ischemia remains limited, and new therapeutic strategies are urgently needed. Exosome has shown great promise for the treatment of cerebral ischemia. Steroid receptor coactivator-3 (SRC-3) was reported to be involved in neurological performances. In this study, we aimed to investigate the protective effects of mesenchymal stem cell (MSC)-derived exosomes overexpressing SRC-3 on cerebral ischemia in mice. Methods: The mice were treated with an intracerebroventricular injection of GFP-overexpressed exosomes (GFP-exo) and SRC-3-overexpressed exosomes (SRC3-exo) in a middle cerebral artery occlusion (MCAO) model of cerebral ischemia. Results: The results showed that SRC3-exo treatment significantly inhibited lipid peroxidation and ferroptosis of the neurons subjected to oxygen-glucose deprivation. It further suppressed the activation of microglia and astrocytes, and decreased the production of pro-inflammatory cytokines in the brains of MCAO mice. Furthermore, SRC3-exo treatment reduced the water content of brain tissue and infarct size, which alleviated the neurological damage and improved neurological performances in the MCAO mice. Conclusions: Our results suggest that MSC-derived exosomes expressing SRC3 can be a therapeutic strategy for cerebral ischemia by inhibiting ferroptosis.

The parasitic helminth Schistosoma mansoni is a potent inducer of type 2 immune responses by stimulating dendritic cells (DCs) to prime T helper 2 (Th2) responses. We previously found that S. mansoni soluble egg antigens (SEA) promote the synthesis of Prostaglandin E2 (PGE2) by DCs through ERK-dependent signaling via Dectin-1 and Dectin-2 that subsequently induces OX40L expression, licensing them for Th2 priming, yet the ligands present in SEA involved in driving this response and whether specific targeting of PGE2 synthesis by DCs could affect Th2 polarization are unknown. We here show that the ability of SEA to bind Dectin-2 and drive ERK phosphorylation, PGE2 synthesis, OX40L expression, and Th2 polarization is impaired upon cleavage of high-mannose glycans by Endoglycosidase H treatment. This identifies high-mannose glycans present on glycoproteins in SEA as important drivers of this signaling axis. Moreover, we find that OX40L expression and Th2 induction are abrogated when microsomal prostaglandin E synthase-1 (mPGES) is selectively inhibited, but not when a general COX-1/2 inhibitor is used. This shows that the de novo synthesis of PGE2 is vital for the Th2 priming function of SEA-stimulated DCs as well as points to the potential existence of other COX-dependent lipid mediators that antagonize PGE2-driven Th2 polarization. Lastly, specific PGE2 inhibition following immunization with S. mansoni eggs dampened the egg-specific Th cell response. In summary, our findings provide new insights in the molecular mechanisms underpinning Th2 induction by S. mansoni and identify druggable targets for potential control of helminth driven-Th2 responses.

Accurate monitoring of tree species diversity is crucial for understanding the dynamic changes in tree species diversity and its relationships with other services and functions in forest ecosystems. Traditional optical remote sensing data have been widely used for monitoring tree species diversity based on the spectral variation hypothesis (SVH). However, this method cannot capture the three-dimensional structural variations in complex species compositions under different stand conditions. In this study, we modeled tree species diversity in terms of spectral variation and stand structural complexity in a typical natural secondary forest in Northeast China by combining Sentinel-2 data and UAV-borne light detection and ranging (LiDAR) point cloud data. First, species diversity indices (including the Shannon index H' and Simpson index D1) were derived from 60 field-measured plots. Second, recursive feature elimination (RFE) was utilized for feature filtering of ten spectral bands and four vegetation indices extracted from Sentinel-2 data and Rao's Q index, as well as eleven features extracted from LiDAR point clouds reflecting the complexity of the stand structure. Subsequently, the random forest method was utilized to fit and predict the relationship between the remote sensing feature set and tree species diversity. The results showed that the use of multisource remote sensing feature set to estimate tree species diversity had the highest accuracy (R2 = 0.44, RMSE = 0.28 for H') compared to the use of only one data source. Moreover, when using a single remote sensing feature set, the estimation accuracy of the optical remote sensing feature set is higher than that of the LiDAR feature set for H' and D1, and the NIRv is the most influential spectral feature. This study clarified the value of spectral variation and productivity heterogeneity embodied in optical remote sensing features for monitoring tree species diversity, as well as evaluating the shortcomings and possibilities of using LiDAR point cloud features independently, and fully confirmed the positive significance of complementary effects between multisource remote sensing feature sets.

Circular RNA (circRNA) vaccines have attracted increasing attention due to their stable closed-loop structures and persistent protein expression ability. During the synthesis process, nicked circRNAs with similar molecular weights to those of circRNAs are generated. Analytical techniques based on differences in molecular weight, such as capillary electrophoresis, struggle to distinguish between circRNAs and nicked circRNAs. The characteristic degradation products of circRNAs and their biological activities remain unclear. Therefore, developing methods to identify target circRNAs and non-target components and investigating degradation patterns will be beneficial to gaining an in-depth understanding of the properties and quality control of circRNAs vaccines. The reversed-phase HPLC (RP-HPLC) method was established for identification of target circRNAs, product-related substances, and impurities. Subsequently, we investigated the degradation patterns of circRNAs under thermal acceleration conditions and performed biological analysis of degradation products and linear precursors. Here, RP-HPLC method effectively identified circRNAs and nicked circRNAs. With thermal acceleration, circRNAs exhibited a “circular→nicked circRNAs→degradation products” degradation pattern. Biological analysis revealed that the immunogenicity of degradation products significantly decreased, whereas linear precursors did not possess immunogenicity. Thus, our established RP-HPLC method can be used for purity analysis of circRNA vaccines, which contributes to the quality control of circRNA vaccines and promoting the development of circRNA technology.

Huanglongbing (HLB) is a severe citrus disease worldwide. Wild Australian limes like Citrus australasica, C. inodora, and C. glauca possess beneficial HLB resistance traits. Individual trees of the three taxa were extensively used in a breeding program for over a decade to introgress resistance traits into commercial-quality citrus germplasm. We generated high-quality, phased, de novo genome assemblies of the three Australian limes using PacBio long-read sequencing. The genome assembly sizes of the primary and alternate haplotypes were determined for C. australasica (337 Mb/335 Mb), C. inodora (304 Mb/299 Mb), and C. glauca (376 Mb/379 Mb). The nine chromosome-scale scaffolds included 86–91% of the genome sequences generated. The integrity and completeness of the assembled genomes were estimated to be at 97.2–98.8%. Gene annotation studies identified 25,461 genes in C. australasica, 27,665 in C. inodora, and 30,067 in C. glauca. Genes belonging to 118 orthogroups were specific to Australian lime genomes compared to other citrus genomes analyzed. Significantly fewer canonical resistance (R) genes were found in C. inodora and C. glauca (319 and 449, respectively) compared to C. australasica (576), C. clementina (579), and C. sinensis (651). Similar patterns were observed for other gene families associated with potential HLB resistance, including Phloem protein 2 (PP2) and Callose synthase (CalS) genes predicted in the Australian lime genomes. The genomic information on Australian limes developed in the present study will help understand the genetic basis of HLB resistance.

Recent growth in unmanned aerial vehicle (UAV) technology have promoted the detailed mapping of individual tree species. However, the in-depth mining and comprehending of the significance of features derived from high-resolution UAV data for tree species discrimination remains a difficult task. In this study, a state-of-the-art approach combining UAV-borne light detection and ranging (LiDAR) and hyperspectral was used to classify 11 common tree species in a typical natural secondary forest in Northeast China. First, comprehensive relevant structural and spectral features were extracted. Then, the most valuable feature sets were selected by using a hybrid approach combining correlation-based feature selection with the optimized recursive feature elimination algorithm. The random forest algorithm was used to assess feature importance and perform the classification. Finally, the robustness of features derived from point clouds with different structures and hyperspectral images with different spatial resolutions was tested. Our results showed that the best classification accuracy was obtained by combining LiDAR and hyperspectral data (75.7%) compared to that based on LiDAR (60.0%) and hyperspectral (64.8%) data alone. The mean intensity of single returns and the visible atmospherically resistant index for red-edge band were the most influential LiDAR and hyperspectral derived features, respectively. The selected features were robust in point clouds with a density not lower than 5% (~5 pts/m2) and a resolution not lower than 0.3 m in hyperspectral data. Although canopy surface features were slightly different from original LiDAR features, canopy surface information was also important for tree species classification. This study proved the capabilities of UAV-borne LiDAR and hyperspectral data in natural secondary forest tree species discrimination and the potential for this approach to be transferable to other study areas.

ABSTRACTOver one billion people have received 2–3 dosages of an inactivated COVID-19 vaccine for basic immunization. Whether a booster dose should be delivered to protect against the Omicron variant and its sub-lineages, remains controversial. Here, we tested different vaccine platforms targeting the ancestral or Omicron strain as a secondary booster of the ancestral inactivated vaccine in mice. We found that the Omicron-adapted inactivated viral vaccine promoted a neutralizing antibody response against Omicron in mice. Furthermore, heterologous immunization with COVID-19 vaccines based on different platforms remarkably elevated the levels of cross- neutralizing antibody against Omicron and its sub-lineages. Omicron-adapted vaccines based on heterologous platforms should be prioritized in future vaccination strategies to control COVID-19.

Cancer vaccines drive the activation and proliferation of tumor-reactive immune cells, thereby eliciting tumor-specific immunity that kills tumor cells. Accordingly, they possess immense potential in cancer treatment. However, such vaccines are also faced with challenges related to their design and considerable differences among individual tumors. The success of messenger RNA (mRNA) vaccines against coronavirus disease 2019 has prompted the application of mRNA vaccine technology platforms to the field of oncotherapy. These platforms include linear, circular, and amplifying mRNA vaccines. In particular, amplifying mRNA vaccines are characterized by high-level and prolonged antigen gene expression at low doses. They can also stimulate specific cellular immunity, making them highly promising in cancer vaccine research. In this review, we summarize the research progress in amplifying mRNA vaccines and provide an outlook of their prospects and future directions in oncotherapy.