First report of leaf blight caused by Nigrospora hainanensis on Euonymus japonicus in China.

Euonymus japonicus Thunb., belonging to the family Celastreace and native to East Asia, is a widely cultivated evergreen ornamental woody plant with important ecological and economic values. In May 2023, serious leaf blight of E. japonicus occurred in the campus green space at Guiyang University, Guizhou Province, China (26°55'85"N, 106°78'04"E). Early symptom appeared as small, circular light brown spots on the edges or tips of the leaves. Then, the spot developed visible necrosis, initially light brown to dark brown halos with clear margins. Subsequently, severely infected leaves appear totally wilt, and significantly decrease their ornamental values. In a 0.07-ha field, the disease incidence reached to 40-55%. To identify the pathogen, ten typical symptomatic E. japonicus leaves were collected. They were initially immersed in 75% ethanol for 3 min, and by sodium hypochlorite (4% NaClO) solution for 45 s, and ultimately rinsed with sterile distilled water (dH2O) five times for not less than 1 min each time, then, placed the leaves on potato dextrose agar (PDA) medium and cultured for 5 days at 25°C in constant temperature incubator. Cultures were purified to yield eight isolates. Early colonies are white and regularly rounded, gradually turning dark brown to black with fluffy mycelium. Conidia were single celled, smooth, black, spherical or ellipsoidal. The conidia size of the representative strain, GY-2 and GY-3, was averagely 12.3-17.3 µm × 10.8-17 µm (n = 50). The conidiogenous cells were monoblastic, hyaline, globose or ampulliform. Morphology-based identification revealed the strain as Nigrospora spp. (Wang et al., 2017). For further confirmation, PCR of GY-2 and GY-3 DNA was performed with the primers ITS1/ITS4 (White et al., 1990), Bt2a-F/Bt2b-R (Glass and Don-aldson 1995), and TEF1-728F/TEF1-986R (Carbone and Kohn 1999). Sequences of the ITS region, TUB and TEF1 genes from the strain GY-2 and GY-3 were deposited in GenBank. (GY-2: OR999377, PP112221 and PP150467; GY-3: PP406871, PP421045 and PP421046, respectively). BLAST analysis showed GY-2 100%, 100%, and 98.36%; GY-3 99.43%, 98.21% and 100% (ITS region, TEF1, and TUB) identity to N. hainanensis sequences (accession numbers. NR_153480.1, KY019415.1, and KY019464.1; KX986094.1, OP611475.1, and KY019597.1). Additionally, tandem sequences of ITS, TUB and TEF1 constructed by MEGA 7.0 confimed the homology through the phylogenetic tree. Pathogenicity tests were conducted on healthy plants grown, each 5 mm diameter of active growing mycelium plug of isolate GY-2 was attached to 15 leaves from five healthy 2-year-old E. japonicu plants. The same number of leaves in the control group were treated with non-inoculated plugs only. All the plants were incubated at 25°C and 75% relative humidity with a 16-h/8-h photoperiod. After 10 days, no symptoms appeared on the leaves of the control group. In contrast, symptomatic blight appeared on all leaves inoculated with GY-2. Pathogenicity tests were performed five times. Pure strains were re-isolated from diseased leaves and, confirmed to be N. hainanensis based on the above methods. Recently, Nigrospora oryzae was reported as causal agent of leaf spots on Euonymus japonicus in China (Xu et al., 2023). To our knowledge, this study is the first report of N. hainanensis causing leaf blight on E. japonicu. Identification of the etiological agent may provide assistance for sustainable management in the future.

Potential of melatonin and Trichoderma harzianum inoculation in ameliorating salt toxicity in watermelon: Insights into antioxidant system, leaf ultrastructure, and gene regulation.

Melatonin (MT) is an extensively studied biomolecule with dual functions, serving as an antioxidant and a signaling molecule. Trichoderma Harzianum (TH) is widely recognized for its effectiveness as a biocontrol agent against many plant pathogens. However, the interplay between seed priming and MT (150 µm) in response to NaCl (100 mM) and its interaction with TH have rarely been investigated. This study aimed to evaluate the potential of MT and TH, alone and in combination, to mitigate salt stress (SS) in watermelon plants. The findings of this study revealed a significant decline in the morphological, physiological, and biochemical indices of watermelon seedlings exposed to SS. However, MT and TH treatments reduced the negative impact of salt stress. The combined application of MT and TH exerted a remarkable positive effect by increasing the growth, photosynthetic and gas exchange parameters, chlorophyll fluorescence indices, and ion balance (decreasing Na+ and enhancing K+). MT and TH effectively alleviated oxidative injury by inhibiting hydrogen peroxide formation in saline and non-saline environments, as established by reduced lipid peroxidation and electrolyte leakage. Moreover, oxidative injury induced by SS on the cells was significantly mitigated by regulation of the antioxidant system, AsA-GSH-related enzymes, the glyoxalase system, augmentation of osmolytes, and activation of several genes involved in the defense system. Additionally, the reduction in oxidative damage was examined by chloroplast integrity via transmission electron microscopy (TEM). Overall, the results of this study provide a promising contribution of MT and TH in safeguarding the watermelon crop from oxidative damage induced by salt stress.

Almond shell-derived biochar decreased toxic metals bioavailability and uptake by tomato and enhanced the antioxidant system and microbial community.

The effectiveness of almond shell-derived biochar (ASB) in immobilizing soil heavy metals (HMs) and its impact on soil microbial activity and diversity have not been sufficiently studied. Hence, a pot study was carried out to investigate the effectiveness of ASB addition at 2, 4, and 6 % (w/w) on soil biochemical characteristics and the bioavailability of Cd, Cu, Pb, and Zn to tomato (Solanum lycopersicum L.) plants, as compared to the control (contaminated soil without ASB addition). The addition of ASB promoted plant growth (up to two-fold) and restored the damage to the ultrastructure of chloroplast organelles. In addition, ASB mitigated the adverse effects of HMs toxicity by decreasing oxidative damage, regulating the antioxidant system, improving soil physicochemical properties, and enhancing enzymatic activities. At the phylum level, ASB addition enhanced the relative abundance of Actinobacteriota, Acidobacteriota, and Firmicutes while decreasing the relative abundance of Proteobacteria and Bacteroidota. Furthermore, ASB application increased the relative abundance of several fungal taxa (Ascomycota and Mortierellomycota) while reducing the relative abundance of Basidiomycota in the soil. The ASB-induced improvement in soil properties, microbial community, and diversity led to a significant decrease in the DTPA-extractable HMs down to 41.0 %, 51.0 %, 52.0 %, and 35.0 % for Cd, Cu, Pb, and Zn, respectively, as compared to the control. The highest doses of ASB (ASB6) significantly reduced the metals content by 26.0 % for Cd, 78.0 % for Cu, 38.0 % for Pb, and 20.0 % for Zn in the roots, and 72.0 % for Cd, 67.0 % for Cu, 46.0 % for Pb, and 35.0 % for Zn in the shoots, as compared to the control. The structural equation model predicts that soil pH and organic matter are driving factors in reducing the availability and uptake of HMs. ASB could be used as a sustainable trial for remediation of HMs polluted soils and reducing metal content in edible plants.

Compound Weakly Supervised Clustering.

Clustering is a fundamental and important step in many image processing tasks, such as face recognition and image segmentation. The performance of clustering can be largely enhanced if relevant weak supervision information is appropriately exploited. To achieve this goal, in this paper, we propose the Compound Weakly Supervised Clustering (CSWC) method. Concretely, CSWC incorporates two types of widely available and easily accessed weak supervision information from the label and feature aspects, respectively. To be specific, at the label level, the pairwise constraints are utilized as a kind of typical weak label supervision information. At the feature level, the partial instances collected from multiple perspectives have internal consistency and they are regarded as weak structure supervision information. To achieve a more confident clustering partition, we learn a unified graph with its similarity matrix to incorporate the above two types of weak supervision. On one hand, this similarity matrix is constructed by self-expression across the partial instances collected from multiple perspectives. On the other hand, the pairwise constraints, i.e., must-links and cannot-links, are considered by formulating a regularizer on the similarity matrix. Finally, the clustering results can be directly obtained according to the learned graph, without performing additional clustering techniques. Besides evaluating CSWC on 7 benchmark datasets, we also apply it to the application of face clustering in video data since it has vast application potentiality. Experimental results demonstrate the effectiveness of our algorithm in both incorporating compound weak supervision and identifying faces in real applications.

Absent Multiview Semisupervised Classification.

With the advent of vast data collection ways, data are often with multiple modalities or coming from multiple sources. Traditional multiview learning often assumes that each example of data appears in all views. However, this assumption is too strict in some real applications such as multisensor surveillance system, where every view suffers from some data absent. In this article, we focus on how to classify such incomplete multiview data in semisupervised scenario and a method called absent multiview semisupervised classification (AMSC) has been proposed. Specifically, partial graph matrices are constructed independently by anchor strategy to measure the relationships among between each pair of present samples on each view. And to obtain unambiguous classification results for all unlabeled data points, AMSC learns view-specific label matrices and a common label matrix simultaneously. AMSC measures the similarity between pair of view-specific label vectors on each view by partial graph matrices, and consider the similarity between view-specific label vectors and class indicator vectors based on the common label matrix. To characterize the contributions of different views, the p th root integration strategy is adopted to incorporate the losses of different views. By further analyzing the relation between the p th root integration strategy and exponential decay integration strategy, we develop an efficient algorithm with proved convergence to solve the proposed nonconvex problem. To validate the effectiveness of AMSC, comparisons are made with some benchmark methods on real-world datasets and in the document classification scenario as well. The experimental results demonstrate the advantages of our proposed approach.

Identification of Colletotrichum aenigma as the new causal agent of leaf blight disease on Aucuba japonica Thunb., and screenings of effective fungicides for its sustainable management.

Aucuba japonica Thunb is an evergreen woody ornamental plant with significant economic and ecological values. It also produces aucubin, showing a variety of biological activities. It is widely planted in the southwest region of China, including karst landscape areas in Guizhou Province. In January 2022, a serious leaf blight disease was observed on the leaves of A. japonica in the outdoor gardens of Guizhou University, Guiyang, Guizhou, China. The causal agent was identified as Colletotrichum aenigma through amplification and sequencing of the internal transcribed spacer (ITS) region, translation of the chitin synthase (CHS) and actin (ACT) genes, and morphological characterizations. Koch's postulates were confirmed by its pathogenicity on healthy leaves, including re-isolation and identification. To our knowledge, this is the first report of C. aenigma causing leaf blight on A. japonica worldwide. To identify pathogen characteristics that could be utilized for future disease management, the effects of temperature and light on mycelial growth, conidia production, and conidial germination, and the effects of humidity on conidial germination were studied. Optimal temperatures for mycelial growth of C. aenigma BY827 were 25-30°C, while 15°C and 35°C were favorable for conidia production. Concurrently, alternating 10-h light and 14-h dark, proved to be beneficial for mycelial growth and conidial germination. Additionally, conidial germination was enhanced at 90% humidity. In vitro screenings of ten chemical pesticides to assess their efficacy in suppressing C. aenigma representative strain BY827. Among them, difenoconazole showed the best inhibition rate, with an EC50 (concentration for 50% of maximal effect) value of 0.0148 µg/ml. Subsequently, field experiment results showed that difenoconazole had the highest control efficiency on A. japonica leaf blight (the decreasing rate of disease incidence and decreasing rate of disease index were 44.60 and 47.75%, respectively). Interestingly, we discovered that C. aenigma BY827 may develop resistance to mancozeb, which is not reported yet among Colletotrichum spp. strains. In conclusion, our study provided new insights into the causal agent of A. japonica leaf blight, and the effective fungicides evaluated provided an important basis and potential resource for the sustainable control of A. japonica leaf blight caused by C. aenigma in the field.

Incomplete Multi-View Learning Under Label Shift.

In image processing, images are usually composed of partial views due to the uncertainty of collection and how to efficiently process these images, which is called incomplete multi-view learning, has attracted widespread attention. The incompleteness and diversity of multi-view data enlarges the difficulty of annotation, resulting in the divergence of label distribution between the training and testing data, named as label shift. However, existing incomplete multi-view methods generally assume that the label distribution is consistent and rarely consider the label shift scenario. To address this new but important challenge, we propose a novel framework termed as Incomplete Multi-view Learning under Label Shift (IMLLS). In this framework, we first give the formal definitions of IMLLS and the bidirectional complete representation which describes the intrinsic and common structure. Then, a multilayer perceptron which combines the reconstruction and classification loss is employed to learn the latent representation, whose existence, consistency and universality are proved with the theoretical satisfaction of label shift assumption. After that, to align the label distribution, the learned representation and trained source classifier are used to estimate the importance weight by designing a new estimation scheme which balances the error generated by finite samples in theory. Finally, the trained classifier reweighted by the estimated weight is fine-tuned to reduce the gap between the source and target representations. Extensive experimental results validate the effectiveness of our algorithm over existing state-of-the-arts methods in various aspects, together with its effectiveness in discriminating schizophrenic patients from healthy controls.

Effects of Drought Stress Induced by Hypertonic Polyethylene Glycol (PEG-6000) on Passiflora edulis Sims Physiological Properties.

Passion fruit is known to be sensitive to drought, and in order to study the physiological and biochemical changes that occur in passion fruit seedlings under drought stress, a hypertonic polyethylene glycol (PEG) solution (5%, 10%, 15%, and 20%) was used to simulate drought stress in passion fruit seedlings. We explored the physiological changes in passion fruit seedlings under drought stress induced by PEG to elucidate their response to drought stress and provide a theoretical basis for drought-resistant cultivation of passion fruit seedlings. The results show that drought stress induced by PEG had a significant effect on the growth and physiological indices of passion fruit. Drought stress significantly decreased fresh weight, chlorophyll content, and root vitality. Conversely, the contents of soluble protein (SP), proline (Pro), and malondialdehyde (MDA) increased gradually with the increasing PEG concentration and prolonged stress duration. After nine days, the SP, Pro and MDA contents were higher in passion fruit leaves and roots under 20% PEG treatments compared with the control. Additionally, with the increase in drought time, the activities of antioxidant enzymes such as peroxidase (POD), superoxide dismutase (SOD) and catalase (CAT) showed an increasing trend and then a decreasing trend, and they reached the highest value at the sixth day of drought stress. After rehydration, SP, Pro and MDA contents in the leaves and roots of passion fruit seedlings was reduced. Among all the stress treatments, 20% PEG had the most significant effect on passion fruit seedlings. Therefore, our study demonstrated sensitive concentrations of PEG to simulate drought stress on passion fruit and revealed the physiological adaptability of passion fruit to drought stress.

Adaptive Feature Selection With Augmented Attributes.

In many dynamic environment applications, with the evolution of data collection ways, the data attributes are incremental and the samples are stored with accumulated feature spaces gradually. For instance, in the neuroimaging-based diagnosis of neuropsychiatric disorders, with emerging of diverse testing ways, we get more brain image features over time. The accumulation of different types of features will unavoidably bring difficulties in manipulating the high-dimensional data. It is challenging to design an algorithm to select valuable features in this feature incremental scenario. To address this important but rarely studied problem, we propose a novel Adaptive Feature Selection method (AFS). It enables the reusability of the feature selection model trained on previous features and adapts it to fit the feature selection requirements on all features automatically. Besides, an ideal l0-norm sparse constraint for feature selection is imposed with a proposed effective solving strategy. We present the theoretical analyses about the generalization bound and convergence behavior. After tackling this problem in a one-shot case, we extend it to the multi-shot scenario. Plenty of experimental results demonstrate the effectiveness of reusing previous features and the superior of l0-norm constraint in various aspects, together with its effectiveness in discriminating schizophrenic patients from healthy controls.

Plant Growth Promotion and Biocontrol of Leaf Blight Caused by Nigrospora sphaerica on Passion Fruit by Endophytic Bacillus subtilis Strain GUCC4.

Passion fruit (Passiflora edulis Sims) is widely cultivated in tropic and sub-tropic regions for the production of fruit, flowers, cosmetics, and for pharmacological applications. Its high economic, nutritional, and medical values elicit the market demand, and the growing areas are rapidly increasing. Leaf blight caused by Nigrospora sphaerica is a new and emerging disease of passion fruit in Guizhou, in southwest China, where the unique karst mountainous landscape and climate conditions are considered potential areas of expansion for passion fruit production. Bacillus species are the most common biocontrol and plant-growth-promotion bacteria (PGPB) resources in agricultural systems. However, little is known about the endophytic existence of Bacillus spp. in the passion fruit phyllosphere as well as their potential as biocontrol agents and PGPB. In this study, 44 endophytic strains were isolated from 15 healthy passion fruit leaves, obtained from Guangxi province, China. Through purification and molecular identification, 42 of the isolates were ascribed to Bacillus species. Their inhibitory activity against N. sphaerica was tested in vitro. Eleven endophytic Bacillus spp. strains inhibited the pathogen by >65%. All of them produced biocontrol- and plant-growth-promotion-related metabolites, including indole-3-acetic acid (IAA), protease, cellulase, phosphatase, and solubilized phosphate. Furthermore, the plant growth promotion traits of the above 11 endophytic Bacillus strains were tested on passion fruit seedlings. One isolate, coded B. subtilis GUCC4, significantly increased passion fruit stem diameter, plant height, leaf length, leaf surface, fresh weight, and dry weight. In addition, B. subtilis GUCC4 reduced the proline content, which indicated its potential to positively regulate passion fruit biochemical properties and resulted in plant growth promotion effects. Finally, the biocontrol efficiencies of B. subtilis GUCC4 against N. sphaerica were determined in vivo under greenhouse conditions. Similarly to the fungicide mancozeb and to a commercial B. subtilis-based biofungicide, B. subtilis GUCC4 significantly reduced disease severity. These results suggest that B. subtilis GUCC4 has great potential as a biological control agent and as PGPB on passion fruit.

Traditional Chinese medicine Pingchan granule for motor symptoms and functions in Parkinson's disease: A multicenter, randomized, double-blind, placebo-controlled study.

BACKGROUND: Pingchan granule (PCG) is a traditional Chinese medicine for Parkinson's disease (PD). HYPOTHESIS/PURPOSE: This was the first study aiming to evaluate the efficacy and safety of PCG for motor symptoms, gait impairments and quality of life in PD. STUDY DESIGN AND METHODS: In this multicenter, randomized, double-blind, placebo-controlled trial, 292 participants were included and followed for 9 months, randomly assigned at a 1:1 ratio to receive PCG or placebo. The primary outcome was the severity of motor symptoms assessed by Movement Disorder Society Unified Parkinson's Rating Scale III (MDS-UPDRS-III) motor score. Secondary outcomes included timed up and go test (TUG), functional gait assessment (FGA), freezing of gait (FOG), and quality of life assessed by Parkinson's disease questionnaire (PDQ-39). Assessments were done at baseline (T0), 3 months (T1), 6 months (T2) and 9 months (T3). TRIAL REGISTRATION: Chinese Clinical Trial Register, ChiCTR-INR-1,701,194. RESULTS: Generalized estimating equation analyses revealed that PCG group had significantly better improvement in MDS-UPDRS-III motor score than placebo group, as well as its domain scores of axial symptoms, bradykinesia, rigidity, and tremor. Improvements of TUG time, FGA, FOG questionnaire (FOGQ), and PDQ39 scores were also observed. CONCLUSION: PCG had a long-lasting efficacy for motor symptoms and function in PD with good tolerance, supporting that PCG might be a viable alternative in the management of PD.

Insights into insecticide-resistance mechanisms in invasive species: Challenges and control strategies.

Threatening the global community is a wide variety of potential threats, most notably invasive pest species. Invasive pest species are non-native organisms that humans have either accidentally or intentionally spread to new regions. One of the most effective and first lines of control strategies for controlling pests is the application of insecticides. These toxic chemicals are employed to get rid of pests, but they pose great risks to people, animals, and plants. Pesticides are heavily used in managing invasive pests in the current era. Due to the overuse of synthetic chemicals, numerous invasive species have already developed resistance. The resistance development is the main reason for the failure to manage the invasive species. Developing pesticide resistance management techniques necessitates a thorough understanding of the mechanisms through which insects acquire insecticide resistance. Insects use a variety of behavioral, biochemical, physiological, genetic, and metabolic methods to deal with toxic chemicals, which can lead to resistance through continuous overexpression of detoxifying enzymes. An overabundance of enzymes causes metabolic resistance, detoxifying pesticides and rendering them ineffective against pests. A key factor in the development of metabolic resistance is the amplification of certain metabolic enzymes, specifically esterases, Glutathione S-transferase, Cytochromes p450 monooxygenase, and hydrolyses. Additionally, insect guts offer unique habitats for microbial colonization, and gut bacteria may serve their hosts a variety of useful services. Most importantly, the detoxification of insecticides leads to resistance development. The complete knowledge of invasive pest species and their mechanisms of resistance development could be very helpful in coping with the challenges and effectively developing effective strategies for the control of invasive species. Integrated Pest Management is particularly effective at lowering the risk of chemical and environmental contaminants and the resulting health issues, and it may also offer the most effective ways to control insect pests.