•Hyperspectral reflectances of the needles indicated the infection stages.•The green, red-edge, and short-wave infrared bands were sensitive to PWD.•Chlorophyll and moisture content decreased during ...the infection.•Spectral changes and physiological changes were small at the early stage.
Pine wilt disease (PWD) is a very destructive forest disease that causes the mortality of pine. The infected trees usually die within three months, and the disease spreads fast with the long-horned beetle as the medium if the infected trees are not removed from the forest in time. Therefore, detecting the infected trees at different infection stage, especially the early infection, is crucial for preventing PWD spread. This study aims to exhibit the spectral differences of the pine needles between healthy pines and infected pines at different infection stages and reveal the diagnostic spectral bands for classifying the different infected stage trees. We collected needle samples from healthy, early-, middle-, late-stage infected trees in a Japanese pine (Pinus densiflora) forest and a Korean pine (Pinus koraiensis) forest in northern China to explore the spectral and biochemical properties differences of these four classes, and selected the sensitive bands combining competitive adaptive reweighted sampling (CARS) and successive projections algorithm (SPA). The selected bands were used for the four infection stages classification by linear discriminant analysis (LDA) algorithm. The results show that Chlorophyll a, chlorophyll b, carotenoids, and moisture content decreases with the aggravation of infection. The green (510–530 nm), red-edge (680–760 nm), and short-wave infrared (1400–1420 nm and 1925–1965 nm) bands are the sensitive bands, and the overall accuracy is 77 % and 78 % for the Japanese pine and Korean pine respectively when using these bands for classifying healthy, early-, middle-, late-stage infected trees. The results demonstrate that physiological parameters including Chlorophyll a, chlorophyll b, carotenoids, and moisture content can be used as the diagnostic parameters of PWD, and the selected sensitive spectral bands are feasible for detecting the stress symptoms of the Japanese pine and Korean pine.
Oxidative stress underlies a number of pathological conditions, including cancer, neurodegeneration, and aging. Antioxidant-rich foods help maintain cellular redox homeostasis and mitigate oxidative ...stress, but the underlying mechanisms are not clear. For example, sulforaphane (SFN), an electrophilic compound that is enriched in cruciferous vegetables such as broccoli, is a potent inducer of cellular antioxidant responses. NFE2L2/NRF2 (nuclear factor, erythroid 2 like 2), a transcriptional factor that controls the expression of multiple detoxifying enzymes through antioxidant response elements (AREs), is a proposed target of SFN. NFE2L2/NRF2 is a target gene of TFEB (transcription factor EB), a master regulator of autophagic and lysosomal functions, which we show here to be potently activated by SFN. SFN induces TFEB nuclear translocation via a Ca
2+
-dependent but MTOR (mechanistic target of rapamycin kinase)-independent mechanism through a moderate increase in reactive oxygen species (ROS). Activated TFEB then boosts the expression of genes required for autophagosome and lysosome biogenesis, which are known to facilitate the clearance of damaged mitochondria. Notably, TFEB activity is required for SFN-induced protection against both acute oxidant bursts and chronic oxidative stress. Hence, by simultaneously activating macroautophagy/autophagy and detoxifying pathways, natural compound SFN may trigger a self-defense cellular mechanism that can effectively mitigate oxidative stress commonly associated with many metabolic and age-related diseases.
Abbreviations: ANOVA: analyzes of variance; AREs: antioxidant response elements; Baf-A1: bafilomycin A
1
; BHA: butylhydroxyanisole; CAT: catechin hydrate; CCCP: carbonyl cyanide m- chlorophenylhydrazone; CLEAR: coordinated lysosomal expression and regulation; DCFH-DA: 2ʹ,7ʹ-dichlorofluorescin diacetate; FBS: fetal bovine serum; GFP: green fluorescent protein; HMOX1/HO-1: heme oxygenase 1; KD: knockdown; KEAP1: kelch like ECH associated protein 1; KO: knockout; LAMP1: lysosomal associated membrane protein 1; MCOLN1/TRPML1: mucolipin 1; ML-SA1: mucolipin-specific synthetic agonist 1; ML-SI3: mucolipin-specific synthetic inhibitor 3; MTOR: mechanistic target of rapamycin kinase; MTORC1: mechanistic target of rapamycin kinase complex 1; NAC: N-acetylcysteine; NFE2L2/NRF2: nuclear factor: erythroid 2 like 2; NPC: Niemann-Pick type C; PBS: phosphate-buffered saline; PPP2/PP2A: protein phosphatase 2; Q-PCR: real time polymerase chain reaction; ROS: reactive oxygen species; RPS6KB1/S6K1/p70S6K: ribosomal protein S6 kinase B1; SFN: sulforaphane; TFEB: transcription factor EB; WT, wild-type
Accurate forest above-ground biomass (AGB) estimation is important for dynamic monitoring of forest resources and evaluation of forest carbon sequestration capacity. However, it is difficult to ...depict the forest’s vertical structure and its heterogeneity using optical remote sensing when estimating forest AGB, for the reason that electromagnetic waves cannot penetrate the canopy’s surface to obtain low vegetation information, especially in subtropical and tropical forests with complex layer structure and tree species composition. As an active remote sensing technology, an airborne laser scanner (ALS) can penetrate the canopy surface to obtain three-dimensional structure information related to AGB. This paper takes the Jiepai sub-forest farm and the Gaofeng state-owned forest farm in southern China as the experimental area and explores the optimal features from the ALS point cloud data and AGB inversion model in the subtropical forest with complex tree species composition and structure. Firstly, considering tree canopy structure, terrain features, point cloud structure and density features, 63 point cloud features were extracted. In view of the biomass distribution differences of different tree species, the random forest (RF) method was used to select the optimal features of each tree species. Secondly, four modeling methods were used to establish the AGB estimation models of each tree species and verify their accuracy. The results showed that the features related to tree height had a great impact on forest AGB. The top features of Cunninghamia Lanceolata (Chinese fir) and Eucalyptus are all related to height, Pinus (pine tree) is also related to terrain features and other broadleaved trees are also related to point cloud density features. The accuracy of the stepwise regression model is best with the AGB estimation accuracy of 0.19, 0.76, 0.71 and 0.40, respectively, for the Chinese fir, pine tree, eucalyptus and other broadleaved trees. In conclusion, the proposed linear regression AGB estimation model of each tree species combining different features derived from ALS point cloud data has high applicability, which can provide effective support for more accurate forest AGB and carbon stock inventory and monitoring.
Accurate and automatic identification of tree species information at the individual tree scale is of great significance for fine-scale investigation and management of forest resources and scientific ...assessment of forest ecosystems. Despite the fact that numerous studies have been conducted on the delineation of individual tree crown and species classification using drone high-resolution red, green and blue (RGB) images, and Light Detection and Ranging (LiDAR) data, performing the above tasks simultaneously has rarely been explored, especially in complex forest environments. In this study, we improve upon the state of the Mask region-based convolution neural network (Mask R-CNN) with our proposed attention complementary network (ACNet) and edge detection R-CNN (ACE R-CNN) for individual tree species identification in high-density and complex forest environments. First, we propose ACNet as the feature extraction backbone network to fuse the weighted features extracted from RGB images and canopy height model (CHM) data through an attention complementary module, which is able to selectively fuse weighted features extracted from RGB and CHM data at different scales, and enables the network to focus on more effective information. Second, edge loss is added to the loss function to improve the edge accuracy of the segmentation, which is calculated through the edge detection filter introduced in the Mask branch of Mask R-CNN. We demonstrate the performance of ACE R-CNN for individual tree species identification in three experimental areas of different tree species in southern China with precision (P), recall (R), F1-score, and average precision (AP) above 0.9. Our proposed ACNet–the backbone network for feature extraction–has better performance in individual tree species identification compared with the ResNet50-FPN (feature pyramid network). The addition of the edge loss obtained by the Sobel filter further improves the identification accuracy of individual tree species and accelerates the convergence speed of the model training. This work demonstrates the improved performance of ACE R-CNN for individual tree species identification and provides a new solution for tree-level species identification in complex forest environments, which can support carbon stock estimation and biodiversity assessment.
Seagrass colonization changes the chemistry and biogeochemical cycles mediated by microbes in coastal sediments. In this study, we molecularly characterized the diazotrophic assemblages and entire ...bacterial community in surface sediments of a Zostera marina-colonized coastal lagoon in northern China. Higher nitrogenase gene (nifH) copy numbers were detected in the sediments from the vegetated region than in the sediments from the unvegetated region nearby. The nifH phylotypes detected were mostly affiliated with the Geobacteraceae, Desulfobulbus, Desulfocapsa, and Pseudomonas. Redundancy analysis based on terminal restriction fragment length polymorphism analysis showed that the distribution of nifH genotypes was mostly shaped by the ratio of total organic carbon to total organic nitrogen, the concentration of cadmium in the sediments, and the pH of the overlying water. High-throughput sequencing and phylogenetic analyses of bacterial 16S rRNA genes also indicated the presence of Geobacteraceae and Desulfobulbaceae phylotypes in these samples. A comparison of these results with those of previous studies suggests the prevalence and predominance of iron(III)-reducing Geobacteraceae and sulfate-reducing Desulfobulbaceae diazotrophs in coastal sedimentary environments. Although the entire bacterial community structure was not significantly different between these two niches, Desulfococcus (Deltaproteobacteria) and Anaerolineae (Chloroflexi) presented with much higher proportions in the vegetated sediments, and Flavobacteriaceae (Bacteroidetes) occurred more frequently in the bare sediments. These data suggest that the high bioavailability of organic matter (indicated by relatively lower carbon-to-nitrogen ratios) and the less-reducing anaerobic condition in vegetated sediments may favor Desulfococcus and Anaerolineae lineages, which are potentially important populations in benthic carbon and sulfur cycling in the highly productive seagrass ecosystem.
Abstract
The ongoing and forthcoming surveys will result in an unprecedented increase in the number of observed galaxies. As a result, data-driven techniques are now the primary methods for analyzing ...and interpreting this vast amount of information. While deep learning using computer vision has been the most effective for galaxy morphology recognition, there are still challenges in efficiently representing spatial and multi-scale geometric features in practical survey images. In this paper, we incorporate layer attention and deformable convolution into a convolutional neural network (CNN) to bolster its spatial feature and geometric transformation modeling capabilities. Our method was trained and tested on seven classifications of a data set from Galaxy Zoo DECaLS, achieving a classification accuracy of 94.5%, precision of 94.4%, recall of 94.2%, and an F1 score of 94.3% using macroscopic averaging. Our model outperforms traditional CNNs, offering slightly better results while substantially reducing the number of parameters and training time. We applied our method to Data Release 9 of the Legacy Surveys and present a galaxy morphological classification catalog including approximately 71 million galaxies and the probability of each galaxy to be categorized as Round, In-between, Cigar-shaped, Edge-on, Spiral, Irregular, and Error. The code detailing our proposed model and the catalog are publicly available in doi:
10.5281/zenodo.10018255
and GitHub (
https://github.com/kustcn/legacy_galaxy
).
Plant height (PH) is an important agronomic trait and is closely related to yield in soybean Glycine max (L.) Merr.. Previous studies have identified many QTLs for PH. Due to the complex genetic ...background of PH in soybean, there are few reports on its fine mapping.
In this study, we used a mapping population derived from a cross between a chromosome segment substitution line CSSL3228 (donor N24852 (G. Soja), a receptor NN1138-2 (G. max)) and NN1138-2 to fine map a wild soybean allele of greater PH by QTL-seq and linkage mapping. We identified a QTL for PH in a 1.73 Mb region on soybean chromosome 13 through QTL-seq, which was confirmed by SSR marker-based classical QTL mapping in the mapping population. The linkage analysis showed that the QTLs of PH were located between the SSR markers BARCSOYSSR_13_1417 and BARCSOYSSR_13_1421 on chromosome 13, and the physical distance was 69.3 kb. RT-PCR and sequence analysis of possible candidate genes showed that Glyma.13 g249400 revealed significantly higher expression in higher PH genotypes, and the gene existed 6 differences in the amino acids encoding between the two parents.
Data presented here provide support for Glyma.13 g249400 as a possible candidate genes for higher PH in wild soybean line N24852.
Apigenin (AP), as an anticancer agent, has been widely explored. However, the molecular targets of apigenin on tumor metabolism are unclear. Herein, we found that AP could block cellular glycolysis ...through restraining the tumor-specific pyruvate kinase M2 (PKM2) activity and expression and further significantly induce anti-colon cancer effects. The IC50 values of AP against HCT116, HT29, and DLD1 cells were 27.9 ± 2.45, 48.2 ± 3.01 and 89.5 ± 4.89 μM, respectively. Fluorescence spectra and solid-phase AP extraction assays proved that AP could directly bind to PKM2 and markedly inhibit PKM2 activity in vitro and in HCT116 cells. Interestingly, in the presence of d-fructose-1,6-diphosphate (FBP), the inhibitory effect of AP on PKM2 was not reversed, which suggests that AP is a new allosteric inhibitor of PKM2. RT-PCR and Western blot assays showed that AP could ensure a low PKM2/PKM1 ratio in HCT116 cells via blocking the β-catenin/c-Myc/PTBP1 signal pathway. Hence, PKM2 represents a novel potential target of AP against colon cancer.
Tumour subtype has a significant effect on bone metastasis in breast cancer, but population-based estimates of the prognosis of patients with bone metastases at breast cancer diagnosis are lacking. ...The aim of this study was to analyse the influence of tumour subtype and other factors on the prognosis and survival of patients with bone metastases of breast cancer.
Using the Surveillance, Epidemiology, and End Results (SEER) Program data from 2012 to 2016, a retrospective cohort study was conducted to investigate stage IV breast cancer patients with bone metastases. Stage IV patient characteristics according to subtype were compared using chi-square tests. Overall survival (OS) and prognostic factors were compared using the Kaplan-Meier method and the Cox proportional hazards model, respectively.
A total of 3384 stage IV patients were included in this study; 63.42% were HR+/HER2-, 19.86% were HR+/HER2+, 9.34% were HR-/HER2-, and 7.39% were HR-/HER2+. The median OS for the whole population was 38 months, and 33.9% of the patients were alive at 5 years. The median OS and five-year survival rate were significantly different among stage IV breast cancer patients with different molecular subtypes (p < 0.05). Multivariate Cox regression analysis showed that age of 55-59 (HR = 1.270), black race (HR = 1.317), grade III or IV (HR = 1.960), HR-/HER2- (HR = 2.808), lung metastases (HR = 1.378), liver metastases (HR = 2.085), and brain metastases (HR = 1.903) were independent risk factors for prognosis; married status (HR = 0.819), HR+/HER2+ (HR = 0.631), HR-/HER2+ (HR = 0.716), insurance (HR = 0.587) and surgery (HR = 0.504) were independent protection factors of prognosis. There was an interaction between the HR+/HER2+ subtype and other metastases (except bone metastases, HR = 0.694, 95% CI: 0.485-0.992), but the interaction between race and subtype did not reach significance for prognosis.
There were substantial differences in OS according to tumour subtype. In addition to tumour subtype, other independent predictors of OS were age at diagnosis, race, marital status, insurance, grade, surgery and visceral metastases. There was an interaction between the HR+/HER2+ subtype and other metastases (except bone metastases) for prognosis. Tumour subtype, as a significant prognostic factor, warrants further investigation.
Objective To evaluate the reporting quality of randomized controlled trials (RCTs) regarding patients with COVID-19 and analyse the influence factors. Methods PubMed, Embase, Web of Science and the ...Cochrane Library databases were searched to collect RCTs regarding patients with COVID-19. The retrieval time was from the inception to December 1, 2020. The CONSORT 2010 statement was used to evaluate the overall reporting quality of these RCTs. Results 53 RCTs were included. The study showed that the average reporting rate for 37 items in CONSORT checklist was 53.85% with mean overall adherence score of 13.02±3.546 (ranged: 7 to 22). The multivariate linear regression analysis showed the overall adherence score to the CONSORT guideline was associated with journal impact factor (P = 0.006), and endorsement of CONSORT statement (P = 0.014). Conclusion Although many RCTs of COVID-19 have been published in different journals, the overall reporting quality of these articles was suboptimal, it can not provide valid evidence for clinical decision-making and systematic reviews. Therefore, more journals should endorse the CONSORT statement, authors should strictly follow the relevant provisions of the CONSORT guideline when reporting articles. Future RCTs should particularly focus on improvement of detailed reporting in allocation concealment, blinding and estimation of sample size.
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