Effects of industrial pollution and ambient air temperature on larval performance and population dynamics of Eriocrania leafminers (Lepidoptera).

Pollution is an integral part of global environmental change, yet the combined and interactive effects of pollution and climate on terrestrial ecosystems remain inadequately understood. This study aims to explore whether pollution alters the impacts of ambient air temperature on the population dynamics of herbivorous insects. Between 1995 and 2005, we studied populations of two closely related moths, Eriocrania semipurpurella and E. sangii, at eight sites located 1 to 64 km from a large copper­nickel smelter in Monchegorsk, Russia. We found that pollution and temperature influence the performance of Eriocrania larvae mining in the leaves of mountain birch, Betula pubescens var. pumila, through multiple pathways. This is evident from the unconsistent changes observed in larval and frass weight, mine area, and leaf size. We found increases in both leaf quality and larval weight with decreasing pollution levels at both spatial and temporal scales and attributed these to the impact of sulphur dioxide, rather than trace elements (nickel and copper). The quality of birch leaves increased with spring (May) temperatures, enabling Eriocrania larvae to achieve greater weight while consuming less biomass. During the larval growth period (early June to early July), Eriocrania larvae increased their consumption with rising temperatures, presumably to compensate for increased metabolic expenses. Contrary to our expectations, the per capita rate of population change did not correlate with larval weight and did not vary along the pollution gradient. Nevertheless, we detected interactive effects of pollution and climate on the rate of population change. This rate decreased with rising winter temperatures in slightly polluted and unpolluted sites but remained unchanged in heavily polluted sites. We conclude that pollution disrupts mechanisms regulating the natural population dynamics of Eriocrania moths.

Mulberry leaf dataset for image classification task.

This manuscript presents a mulberry leaf dataset collected from five provinces within three regions in Thailand. The dataset contains ten categories of mulberry leaves. We proposed this dataset due to the challenges of classifying leaf images taken in natural environments arising from high inter-class similarity and variations in illumination and background conditions (multiple leaves from a mulberry tree and shadows appearing in the leaf images). We highlight that our research team recorded mulberry leaves independently from various perspectives during our data acquisition using multiple camera types. The mulberry leaf dataset can serve as vital input data passed to computer vision algorithms (conventional deep learning and vision transformer algorithms) for creating image recognition systems. The dataset will allow other researchers to propose novel computer vision techniques to approach mulberry recognition challenges.

Analysis of banana plant health using machine learning techniques.

The Indian economy is greatly influenced by the Banana Industry, necessitating advancements in agricultural farming. Recent research emphasizes the imperative nature of addressing diseases that impact Banana Plants, with a particular focus on early detection to safeguard production. The urgency of early identification is underscored by the fact that diseases predominantly affect banana plant leaves. Automated systems that integrate machine learning and deep learning algorithms have proven to be effective in predicting diseases. This manuscript examines the prediction and detection of diseases in banana leaves, exploring various diseases, machine learning algorithms, and methodologies. The study makes a contribution by proposing two approaches for improved performance and suggesting future research directions. In summary, the objective is to advance understanding and stimulate progress in the prediction and detection of diseases in banana leaves. The need for enhanced disease identification processes is highlighted by the results of the survey. Existing models face a challenge due to their lack of rotation and scale invariance. While algorithms such as random forest and decision trees are less affected, initially convolutional neural networks (CNNs) is considered for disease prediction. Though the Convolutional Neural Network models demonstrated impressive accuracy in many research but it lacks in invariance to scale and rotation. Moreover, it is observed that due its inherent design it cannot be combined with feature extraction methods to identify the banana leaf diseases. Due to this reason two alternative models that combine ANN with scale-invariant Feature transform (SIFT) model or histogram of oriented gradients (HOG) combined with local binary patterns (LBP) model are suggested. The first model ANN with SIFT identify the disease by using the activation functions to process the features extracted by the SIFT by distinguishing the complex patterns. The second integrate the combined features of HOG and LBP to identify the disease thus by representing the local pattern and gradients in an image. This paves a way for the ANN to learn and identify the banana leaf disease. Moving forward, exploring datasets in video formats for disease detection in banana leaves through tailored machine learning algorithms presents a promising avenue for research.

Interplay between drought and plant viruses co-infecting melon plants.

Drought affects crops directly, and indirectly by affecting the activity of insect pests and the transmitted pathogens. Here, we established an experiment with well-watered or water-stressed melon plants, later single infected with either cucumber mosaic virus (CMV: non-persistent), or cucurbit aphid-borne yellow virus (CABYV: persistent), or both CMV and CABYV, and mock-inoculated control. We tested whether i) the relation between CMV and CABYV is additive, and ii) the relationship between water stress and virus infection is antagonistic, i.e., water stress primes plants for enhanced tolerance to virus infection. Water stress increased leaf greenness and temperature, and reduced leaf water potential, shoot biomass, stem dimensions, rate of flowering, CABYV symptom severity, and marketable fruit yield. Virus infection reduced leaf water potential transiently in single infected plants and persistently until harvest in double-infected plants. Double-virus infection caused the largest and synergistic reduction of marketable fruit yield. The relationship between water regime and virus treatment was additive in 12 out of 15 traits at harvest, with interactions for leaf water content, leaf:stem ratio, and fruit set. We conclude that both virus-virus relations in double infection and virus-drought relations cannot be generalized because they vary with virus, trait, and plant ontogeny.

Biocontrol potential and growth-promoting effect of endophytic fungus Talaromyces muroii SD1-4 against potato leaf spot disease caused by Alternaria alternata.

BACKGROUND: Alternaria alternata is the primary pathogen of potato leaf spot disease, resulting in significant potato yield losses globally. Endophytic microorganism-based biological control, especially using microorganisms from host plants, has emerged as a promising and eco-friendly approach for managing plant diseases. Therefore, this study aimed to isolate, identify and characterize the endophytic fungi from healthy potato leaves which had great antifungal activity to the potato leaf spot pathogen of A. alternata in vitro and in vivo. RESULTS: An endophytic fungal strain SD1-4 was isolated from healthy potato leaves and was identified as Talaromyces muroii through morphological and sequencing analysis. The strain SD1-4 exhibited potent antifungal activity against the potato leaf spot pathogen A. alternata Lill, with a hyphal inhibition rate of 69.19%. Microscopic and scanning electron microscope observations revealed that the strain SD1-4 grew parallel to, coiled around, shrunk and deformed the mycelia of A. alternata Lill. Additionally, the enzyme activities of chitinase and ß-1, 3-glucanase significantly increased in the hyphae of A. alternata Lill when co-cultured with the strain SD1-4, indicating severe impairment of the cell wall function of A. alternata Lill. Furthermore, the mycelial growth and conidial germination of A. alternata Lill were significantly suppressed by the aseptic filtrate of the strain SD1-4, with inhibition rates of 79.00% and 80.67%, respectively. Decrease of leaf spot disease index from 78.36 to 37.03 was also observed in potato plants treated with the strain SD1-4, along with the significantly increased plant growth characters including plant height, root length, fresh weight, dry weight, chlorophyll content and photosynthetic rate of potato seedlings. CONCLUSION: The endophyte fungus of T. muroii SD1-4 isolated from healthy potato leaves in the present study showed high biocontrol potential against potato leaf spot disease caused by A. alternata via direct parasitism or antifungal metabolites, and had positive roles in promoting potato plant growth.

Food availability aligns with contrasting demographics in populations of an at-risk songbird.

Golden-winged Warblers (Vermivora chrysoptera) have become rare across much of their historic breeding range and response to conservation efforts is variable. Evidence from several recent studies suggests that breeding output is a primary driver explaining responses to conservation and it is hypothesized that differences in food availability may be driving breeding output disparity between two subpopulations of the warbler's Appalachian breeding range. Herein, we studied two subpopulations: central Pennsylvania ("central subpopulation"), where breeding productivity is relatively low, and eastern Pennsylvania ("eastern subpopulation"), where breeding productivity is relatively high. To test the food-availability hypothesis in this system, we measured density of caterpillars, plasma lipid metabolites (triglycerides [TRIG; fat deposition] and glycerol [GLYC; fat breakdown]), body mass of adults males, and acquired body mass data for fledglings at 38 sites managed for nesting habitat. Consistent with our prediction, leaf-roller caterpillar density, the group upon which Golden-winged Warblers specialize, was 45× lower in the central subpopulation than the eastern subpopulation. TRIG concentrations were highest within the eastern subpopulation during breeding grounds arrival. The change in TRIG concentrations from the breeding-grounds-arrival stage to the nestling-rearing stage was subpopulation dependent: TRIG decreased in the eastern subpopulation and was constant in the central subpopulation, resulting in similar concentrations during the nestling-rearing stage. Furthermore, GLYC concentrations were higher in the eastern subpopulation, which suggests greater energy demands in this region. Despite this, adult male warblers in the eastern subpopulation maintained a higher average body mass. Finally, fledgling body mass was 16% greater in the eastern subpopulation than the central subpopulation before and after fledging. Collectively, our results suggest that poor breeding success of Golden-winged Warblers in the central subpopulation could be driven by lower availability of primary prey during the breeding season (leaf-roller caterpillars), and this, in turn, limits their response to conservation efforts.

Exploring the therapeutic potential of Nelumbo nucifera leaf extract against amyloid-beta-induced toxicity in the Caenorhabditis elegans model of Alzheimer's disease.

Introduction: Alzheimer's disease (AD) represents a critical global health challenge with limited therapeutic options, prompting the exploration of alternative strategies. A key pathology in AD involves amyloid beta (Aß) aggregation, and targeting both Aß aggregation and oxidative stress is crucial for effective intervention. Natural compounds from medicinal and food sources have emerged as potential preventive and therapeutic agents, with Nelumbo nucifera leaf extract (NLE) showing promising properties. Methods: In this study, we utilized transgenic Caenorhabditis elegans (C. elegans) models to investigate the potential of NLE in countering AD and to elucidate the underlying mechanisms. Various assays were employed to assess paralysis rates, food-searching capabilities, Aß aggregate accumulation, oxidative stress, lifespan under stress conditions, and the expression of stress-resistance-related proteins. Additionally, autophagy induction was evaluated by measuring P62 levels and the formation of LGG-1+ structures, with RNAi-mediated inhibition of autophagy-related genes to confirm the mechanisms involved. Results: The results demonstrated that NLE significantly reduced paralysis rates in CL4176 and CL2006 worms while enhancing food-searching capabilities in CL2355 worms. NLE also attenuated Aß aggregate accumulation and mitigated Aß-induced oxidative stress in C. elegans. Furthermore, NLE extended the lifespan of worms under oxidative and thermal stress conditions, while concurrently increasing the expression of stress-resistance-related proteins, including SOD-3, GST-4, HSP-4, and HSP-6. Moreover, NLE induced autophagy in C. elegans, as evidenced by reduced P62 levels in BC12921 worms and the formation of LGG-1+ structures in DA2123 worms. The RNAi-mediated inhibition of autophagy-related genes, such as bec-1 and vps-34, negated the protective effects of NLE against Aß-induced paralysis and aggregate accumulation. Discussion: These findings suggest that NLE ameliorates Aß-induced toxicity by activating autophagy in C. elegans. The study underscores the potential of NLE as a promising candidate for further investigation in AD management, offering multifaceted approaches to mitigate AD-related pathology and stress-related challenges.

Pest categorisation of Coniella castaneicola.

The European Commission requested the EFSA Panel on Plant Health to conduct a pest categorisation of Coniella castaneicola (Ellis & Everh) Sutton, following commodity risk assessments of Acer campestre, A. palmatum, A. platanoides, A. pseudoplatanus, Quercus petraea and Q. robur plants from the UK, in which C. castaneicola was identified as a pest of possible concern to the EU. When first described, Coniella castaneicola was a clearly defined fungus of the family Schizoparmaceae, but due to lack of a curated type-derived DNA sequence, current identification based only on DNA sequence is uncertain and taxa previously reported to be this fungus based on molecular identification must be confirmed. The uncertainty on the reported identification of this species translates into uncertainty on all the sections of this categorisation. The fungus has been reported on several plant species associated with leaf spots, leaf blights and fruit rots, and as an endophyte in asymptomatic plants. The species is reported from North and South America, Africa, Asia, non-EU Europe and Oceania. Coniella castaneicola is not known to occur in the EU. However, there is a key uncertainty on its presence and geographical distribution worldwide and in the EU due to its endophytic nature, the lack of systematic surveys and possible misidentifications. Coniella castaneicola is not included in Commission Implementing Regulation (EU) 2019/2072 and there are no interceptions in the EU. Plants for planting, fresh fruits and soil and other growing media associated with infected plant debris are the main pathways for its entry into the EU. Host availability and climate suitability in parts of the EU are favourable for the establishment and spread of the fungus. Based on the scarce information available, the introduction and spread of C. castaneicola in the EU is not expected to cause substantial impacts, with a key uncertainty. Phytosanitary measures are available to prevent its introduction and spread in the EU. Because of lack of documented impacts, Coniella castaneicola does not satisfy all the criteria that are within the remit of EFSA to assess for this species to be regarded as potential Union quarantine pest.

Research on the mechanism of sea buckthorn leaf Fu tea in the treatment of hyperlipidemia.

Background: Hyperlipidemia (HLP) presents a significant challenge to global public health. Mounting evidence suggests that statins, the recommended first-line lipid-lowering agents, have significant adverse effects. Consequently, the quest for natural and efficacious alternative therapies is steadily emerging as a research priority for HLP prevention and treatment. Consumption of tea, which is rich in diverse biologically active compounds with the capacity to regulate lipid metabolism and combat obesity, has emerged as a promising alternative therapy. Sea buckthorn leaves are rich in a multitude of biologically active substances, have a hypolipidemic effect, and can be used as a raw material for tea because of their unique flavor. There is a suggestion that combining Aspergillus cristatus with tea could modify or boost the lipid-lowering active compounds present in tea, thereby increasing its efficacy in regulating lipid metabolism. Results: Sea Buckthorn Leaf Fu Tea (SBLFT) was obtained by fermentation when sea buckthorn leaves contained 42 % moisture, inoculated with Aspergillus cristatus 0.2 mL/g, and incubated for 8 d at constant temperature. Animal experiments demonstrated that SBLFT significantly inhibited body weight gain in HLP rats and reduced lipid content and serum oxidative stress. In addition, liver tissue sections and functional indices showed that SBLFT can improve liver morphology and function abnormalities. Reverse transcription-polymerase chain reaction results indicated that the expression of Liver kinase B1 (LKB1), adenosine 5'-monophosphate (AMP)-activated protein kinase (AMPK), acetyl CoA carboxylase 1 (ACC1), and sterol-regulatory element binding protein-1 (SREBP1c) gene related to lipid metabolism was altered. Conclusion: SBLFT improved HLP, specifically via promoting the expression of LKB1 in the liver of HLP rats, activating AMPK, and inhibiting ACC1 and SREBP1c expression, resulting in the inhibition of fatty acid and triglyceride synthesis-related enzymes at the transcriptional level.

Bio-pump cadmium phytoextraction efficiency promoted by phytohormones in Festuca arundinacea.

The leaves of Festuca arundinacea can excrete cadmium (Cd) out onto the leaf surface, leading to a bio-pump phytoremediation strategy based on "root uptake-root-to-leaf translocation-leaf excretion". However, the bio-bump efficiency of soil Cd is a limiting factor for the implementation of this novel technology. Bio-bump remediation involves the bioprocess of plant root uptake from soil, root-to-leaf translocation, and leaf hydathode excretion. Here we show the significant effects of phytohormones in regulating the bio-pump phytoextraction efficiency. The results showed that salicylic acid and ethylene enhanced the whole process of Cd root uptake, root-to-leaf translocation, and leaf excretion, promoting the bio-pump phytoextraction efficiency by 63.6% and 73.8%, respectively. Gibberellin also greatly promoted Cd translocation, leaf excretion, and phytoextraction, but did not significantly impact Cd root uptake. Our results indicate that salicylic acid and ethylene could be recommended to promote bio-pump phytoextraction efficiency in F. arundinacea. Gibberellin might be used for a short-term promotion of the leaf Cd excretion.

Traditional and Novel Organophosphate Esters in Plastic Greenhouse: Occurrence, Multimedia Migration, and Exposure Risk via Vegetable Consumption.

The migration and risk of organophosphate esters (OPEs) in agricultural air-soil-plant multimedia systems due to plastic film application remain unclear. This study investigates the multimedia distribution of traditional OPEs (TOPEs), novel OPEs (NOPEs), and their transformation products (POPEs) in plastic and solar greenhouses. The total concentration of OPE-associated contaminants in air and airborne particles ranged from 594 to 1560 pg/m3 and 443 to 15600 ng/g, respectively. Significant correlations between air OPE concentrations and those in polyolefin film (P < 0.01) indicate plastic film as the primary source. Contaminants were also found in soils (96.8-9630 ng/g) and vegetables (197-7540 ng/g). The primary migration pathway for NOPEs was particle dry deposition onto the soil and leaf, followed by plant accumulation. Leaf absorption was the main uptake pathway for TOPEs and POPEs, influenced by vegetable specific leaf surface area. Moreover, total exposure to OPE-associated contaminants via vegetable intake was assessed at 2250 ng/kg bw/day for adults and 2900 ng/kg bw/day for children, with an acceptable hazard index. However, a high ecological risk was identified for NOPE compounds (median risk quotient, 975). This study provides the first evidence of the multimedia distribution and potential threat posed by OPE-associated contaminants in agricultural greenhouses.

Physiological and structural traits contribute to thermotolerance in wild Australian cotton species.

BACKGROUND AND AIMS: Five species of cotton (Gossypium) were exposed to 38°C days during early vegetative development. Commercial cotton (Gossypium hirsutum) was contrasted with four wild cotton species (G. australe, G. bickii, G. robinsonii and G. sturtianum) that are endemic to central and northern Australia. METHODS: Plants were grown at daytime maxima of 30°C or 38°C for 25 d, commencing at the four-leaf stage. Leaf areas and shoot biomass were used to calculate relative rates of growth and specific leaf areas. Leaf gas exchange measurements revealed assimilation and transpiration rates, as well as electron transport rates (ETR) and carboxylation efficiency (CE) in steady-state conditions. Finally, leaf morphological traits (mean leaf area and leaf shape were quantified), along with leaf surface decorations, imaged using scanning electron microscopy. KEY RESULTS: Shoot morphology was differentially affected by heat, with three of the four wild species growing faster at 38°C than at 30°C, whereas early growth in G. hirsutum was severely inhibited by heat. Areas of individual leaves and leaf numbers both contributed to these contrasting growth responses, with fewer, smaller leaves at 38°C in G. hirsutum. CO2 assimilation and transpiration rates of G. hirsutum were also dramatically reduced by heat. Cultivated cotton failed to achieve evaporative cooling, contrasting with the transpiration-driven cooling in the wild species. Heat substantially reduced ETR and CE in G. hirsutum, with much smaller effects in the wild species. We speculate that leaf shape, as assessed by invaginations of leaf margins, and leaf size contributed to heat dispersal differentially among the five species. Similarly, reflectance of light radiation was also highly distinctive for each species. CONCLUSIONS: These four wild Australian relatives of cotton have adapted to hot days that are inhibitory to commercial cotton, deploying a range of physiological and structural adaptations to achieve accelerated growth at 38°C.

First report of Pseudopithomyces palmicola causing leaf spot on tobacco in China.

In July 2023, a new leaf spot disease emerged on tobacco leaves in Meitan County, Guizhou Province, China (27°20'18" - 28°12'30"N, 107°15'36" - 107°41'08"E, average altitude 972 meters). Initially, the symptoms showed raised yellow-brown spots; subsequently, the lesions expanded and became broken and perforated, leading to a significant loss of economic value, the prevalence rate exceeded 30%. For isolation, two tissue fragments (0.2 × 0.2 cm) of symptomatic leaves were sterilized in 75% ethanol for 30 s, 3% NaClO for 2 min, and were washed 3 times in sterilized distilled water, and were subsequently inoculated on potato dextrose agar (PDA), and incubated at 28°C for 9 days in the dark. The two strains CW16 and CW28 were isolated using the single hyphae method (Nouri et al. 2023). Both strains formed pale to yellow white colonies on PDA. Conidia had three constricted transverse septa and 1 to 2 longitudinal septa in the central cells, with thick and hyaline conidiophores and mostly globose, pale brown conidia with slightly constricted septa, their average size were measured as 13.4-22.4×8.358-13.347 µm (n = 50). Genomic DNA was extracted from the isolated strains CW16 and CW28. The internal transcribed spacer regions 1 and 2 as well as 5.8S nuclear ribosomal RNA (ITS), large subunit nrRNA (LSU), and partial DNA-directed RNA polymerase II second largest subunit (RPB2) genes were amplified using primers (Cui et al. 2023). The sequences had been deposited in GenBank under accession numbers ITS: PP024201, PP024205; LSU: PP024207, PP024209; RPB2: PP060480, PP060481. The sequences analysis revealed a high similarity of 99.74 to 100% between strains CW16 and CW28 with P. palmicola isolate KM42 (ITS OQ875842, LSU OQ875844, RPB2 OQ883943) in GenBank. Using BLAST for homology matching, two isolates (CW16, CW28) and with the sequences of the ten type isolates from GenBank, phylogenetic analysis was conducted using the Maximum Likelihood method in MEGA (11.0) software based on ITS, LSU and RPB2 sequences, which showed that strains CW16, CW28 clustered in the same score as the Pseudopithomyces palmicola, confirming the morphological and molecular characteristics identification. The pathogenicity tests were conducted on healthy tobacco plants with 4-5 leaves (Fig. S1B), the isolated strains, CW16 and CW28, were used to inoculate the healthy tobacco leaves, while blank PDA was used as a control. All plants were maintained in a greenhouse at 28°C with a relative humidity of 90%. After 9 days, necrotic spots were observed on all tobacco leaves inoculated with CW16 and CW28 fungal plugs, while the blank PDA-inoculated tobacco leaves showed no symptoms. Based on morphological and molecular characteristics, the same pathogen P. palmicola was identified from the inoculated leaves, fulfilling Koch's postulates. This study represents the first reported of tobacco leaf spot caused by P. palmicola in China and provides a theoretical basis for future prevention and control measures.

Streamlined screening of extracellularly expressed PETase libraries for improved polyethylene terephthalate degradation.

Enzyme-mediated polyethylene terephthalate (PET) depolymerization has recently emerged as a sustainable solution for PET recycling. Towards an industrial-scale implementation of this technology, various strategies are being explored to enhance PET depolymerization (PETase) activity and improve enzyme stability, expression, and purification processes. Recently, rational engineering of a known PET hydrolase (LCC-leaf compost cutinase) has resulted in the isolation of a variant harboring four-point mutations (LCC-ICCG), presenting increased PETase activity and thermal stability. Here, we revealed the enzyme's natural extracellular expression and used it to efficiently screen error-prone genetic libraries based on LCC-ICCG for enhanced activity toward consumer-grade PET. Following multiple rounds of mutagenesis and screening, we successfully isolated variants that exhibited up to a 60% increase in PETase activity. Among other mutations, the improved variants showed a histidine to tyrosine substitution at position 218, a residue known to be involved in substrate binding and stabilization. Introducing H218Y mutation on the background of LCC-ICCG (named here LCC-ICCG/H218Y) resulted in a similar level of activity improvement. Analysis of the solved structure of LCC-ICCG/H218Y compared to other known PETases featuring different amino acids at the equivalent position suggests that H218Y substitution promotes enhanced PETase activity. The expression and screening processes developed in this study can be further used to optimize additional enzymatic parameters crucial for efficient enzymatic degradation of consumer-grade PET.

SEM-EDS-based rapid measurement and size-fractionated speciation of airborne particulate matter and associated metals utilizing plant leaves.

This study was conducted to assess particulate matter pollution and the accumulation of airborne toxic metals by studying the foliar deposition pattern in an urban environment. To this end, two commonly growing plants (Senna siamea (Lam.) H.S.Irwin & Barneby and Alstonia scholaris (L.) R.Br.) from the busiest traffic squares of the city (Nehru Chowk) in Bilaspur, India, were selected for detailed study. For this purpose, plant leaf samples of both plant species were collected from pollution-affected areas and a reference site (unpolluted) in the city and examined by scanning electron microscopy and energy dispersive X-ray spectroscopy (SEM-EDS) to estimate the accumulation of PM-bound toxic metals at the leaf surfaces. The results of this study showed that the leaves of both plants accumulate PM in different size ranges. Although both plant leaves showed accumulation of PM from respirable suspended particulate matter (RSPM) to ultra-fine particles (UFPs: < 0.1: less than 100 nm) range along with toxic metals, S. siamea retained a higher level of PM than A. scholaris due to better micro-morphological properties on both leaf surfaces. The size of some PM was found to be smaller than the stoma openings. The EDS study proved the presence of harmful airborne toxic metals (Pb, Cd, Cu, Zr, Al, Co, etc.) in these PMs of ambient air. This indicates that toxic metals can enter the leaves through stomatal openings. The results of this study recommended that both plants can be used as a tool to minimise PM pollution.

Deep migration learning-based recognition of diseases and insect pests in Yunnan tea under complex environments.

BACKGROUND: The occurrence, development, and outbreak of tea diseases and pests pose a significant challenge to the quality and yield of tea, necessitating prompt identification and control measures. Given the vast array of tea diseases and pests, coupled with the intricacies of the tea planting environment, accurate and rapid diagnosis remains elusive. In addressing this issue, the present study investigates the utilization of transfer learning convolution neural networks for the identification of tea diseases and pests. Our objective is to facilitate the accurate and expeditious detection of diseases and pests affecting the Yunnan Big leaf kind of tea within its complex ecological niche. RESULTS: Initially, we gathered 1878 image data encompassing 10 prevalent types of tea diseases and pests from complex environments within tea plantations, compiling a comprehensive dataset. Additionally, we employed data augmentation techniques to enrich the sample diversity. Leveraging the ImageNet pre-trained model, we conducted a comprehensive evaluation and identified the Xception architecture as the most effective model. Notably, the integration of an attention mechanism within the Xeption model did not yield improvements in recognition performance. Subsequently, through transfer learning and the freezing core strategy, we achieved a test accuracy rate of 98.58% and a verification accuracy rate of 98.2310%. CONCLUSIONS: These outcomes signify a significant stride towards accurate and timely detection, holding promise for enhancing the sustainability and productivity of Yunnan tea. Our findings provide a theoretical foundation and technical guidance for the development of online detection technologies for tea diseases and pests in Yunnan.

Comparison of Efficacy of Topical Carica papaya Leaf Extract and Hemocoagulase in Postoperative Wound Healing After Therapeutic Orthodontic Premolar Extractions: a Split Mouth Study.

Introduction Postoperative wound healing is the most important factor in the outcome of any surgical procedure. Wound healing is a dynamic process involving inflammation, neovascularization, granulation, fibroblast proliferation, re-epithelization, and remodeling. It repairs tissue integrity, restoring the body's natural defense barrier. A hastened wound healing will help in the quicker re-establishment of the body's homeostasis. Carica papaya includes vital nutrients and bioactive substances such as minerals, vitamins, and antioxidants. Its primary active ingredient papain causes the enzymatic debridement of wounds. Hemocoagulase is a thrombin-like serine protease that is mostly employed for its procoagulant and wound-healing characteristics. It is derived from the venom of Bothrops species of snakes. This study aims to compare the wound-healing properties of topical Carica papaya leaf extract and Hemocoagulase after dental extractions. Materials & Methods For 48 patients requiring bilateral therapeutic dental extraction for orthodontic intervention, Carica papaya leaf extract (Caripill 275mg/5ml) was topically applied to the extraction socket on one side, and Hemocoagulase 0.2 CU solution (Botroclot) was applied to the extraction socket on the other side. The bilateral premolars were extracted for orthodontic treatment under local anesthesia. Patients were asked to apply the solution topically twice daily for seven days and were called for review on the seventh day. The assessment of the efficacy of both solutions in post-operative wound healing was the objective of the study. Healing was assessed by using a blinded single observer for all patients using Landry's healing index. Results A total of 48 subjects with 96 sites completed the study, with a mean age of 15.4 years. The study population consisted of 24 males and 24 females, which were evenly distributed among the two study groups. On comparison of wound healing index (WHI) scores between the two groups using the Wilcoxon signed rank test, Group A had a significantly higher mean rank than Group B with regards to the wound healing index score, and the results were statistically significant (p = 0.037). Conclusion It can be concluded from the study that Carica papaya leaf extract showed better wound healing in post-extraction sockets compared to Hemocoagulase. This study presents the promising use of natural extracts such as Carica papaya in wound healing because they are easily accessible to patients, more economical, and have no adverse reactions. More studies that focus on natural extracts to promote wound healing are required in the future.

Plant leaf disease recognition based on improved SinGAN and improved ResNet34.

The identification of plant leaf diseases is crucial in precision agriculture, playing a pivotal role in advancing the modernization of agriculture. Timely detection and diagnosis of leaf diseases for preventive measures significantly contribute to enhancing both the quantity and quality of agricultural products, thereby fostering the in-depth development of precision agriculture. However, despite the rapid development of research on plant leaf disease identification, it still faces challenges such as insufficient agricultural datasets and the problem of deep learning-based disease identification models having numerous training parameters and insufficient accuracy. This paper proposes a plant leaf disease identification method based on improved SinGAN and improved ResNet34 to address the aforementioned issues. Firstly, an improved SinGAN called Reconstruction-Based Single Image Generation Network (ReSinGN) is proposed for image enhancement. This network accelerates model training speed by using an autoencoder to replace the GAN in the SinGAN and incorporates a Convolutional Block Attention Module (CBAM) into the autoencoder to more accurately capture important features and structural information in the images. Random pixel Shuffling are introduced in ReSinGN to enable the model to learn richer data representations, further enhancing the quality of generated images. Secondly, an improved ResNet34 is proposed for plant leaf disease identification. This involves adding CBAM modules to the ResNet34 to alleviate the limitations of parameter sharing, replacing the ReLU activation function with LeakyReLU activation function to address the problem of neuron death, and utilizing transfer learning-based training methods to accelerate network training speed. This paper takes tomato leaf diseases as the experimental subject, and the experimental results demonstrate that: (1) ReSinGN generates high-quality images at least 44.6 times faster in training speed compared to SinGAN. (2) The Tenengrad score of images generated by the ReSinGN model is 67.3, which is improved by 30.2 compared to the SinGAN, resulting in clearer images. (3) ReSinGN model with random pixel Shuffling outperforms SinGAN in both image clarity and distortion, achieving the optimal balance between image clarity and distortion. (4) The improved ResNet34 achieved an average recognition accuracy, recognition precision, recognition accuracy (redundant as it's similar to precision), recall, and F1 score of 98.57, 96.57, 98.68, 97.7, and 98.17%, respectively, for tomato leaf disease identification. Compared to the original ResNet34, this represents enhancements of 3.65, 4.66, 0.88, 4.1, and 2.47%, respectively.

Surface and composition effects on the biphasic cytotoxicity of nanocomposites synthesized using leaf extracts.

The Malus sylvestris L. (LE1), Pinus sylvestris L. (LE2), and Sorbus aucuparia L. (LE3) leaves` extracts were used for the synthesis of silver (Ag) nanocomposites containing different amounts of silver chloride (AgCl), silver metal (Agmet), and silver phosphate (Ag3PO4). These nanocomposites were capped with the organic functional groups in the leaf extract. Notably, the nanocomposites caused biphasic cytotoxic response on cells; first attributed to the inhibition of cell growth and second to cell death. The nanocomposites were biocompatible with normal embryonic kidney (HEK293) cells in the cytotoxic range for cancer cells. LE2Ag1 [25(±1) °C synthesis] nanocomposites exhibited the highest cytotoxicity towards HeLa (lethal concentration- LC50 value of 11.4 µg mL-1) and A549 (LC50 value of 14.7 µg mL-1) after 24-h incubation and its efficiency was shown also for the more resistant MCF-7 and MDA-MB-231, however, their respective LC50 values were larger. For the HeLa cell line, this designed LE2Ag1 nanocomposite exhibited an LC50 value similar to the effective concentration (EC50) value of Cisplatin and about 3 times larger than Doxorubicin. LE2Ag1 nanocomposite contained Ag3PO4 in the composite and P on the surface, higher AgCl content, smaller crystallite size of all nanoparticle phases, and carbon-rich oxygen-deficient surface compared to all other nanocomposites.

First Report of Nigrospora oryzae Causing Leaf Spot Disease on Amorphophallus albus in Shaanxi Province of China.

Amorphophallus albus P. Y. Liu & J. F. Chen is a typical cash crop widely planted in southwest China (Gao et al., 2022). In early August of 2021, a peculiar leaf spot disease was first detected on A. albus in Ankang Academy of Agricultural Sciences manufacturing base (32°69'N, 109°02'E), Shaanxi, China. Small irregular yellow-brown spots (1 to 2 mm) were observed on the surface of A. albus leaf. Following infection of the leaf, it expanded (3 to 5 mm) and became necrotic. Nine planting bases were investigated, and approximately 75% of plants were symptomatic during the rapid expansion period of bulb growth in Hanyin, Langao and Hanbin counties, Ankang City, Shaanxi, China. Higher disease incidence was observed at temperatures above 30℃ and humidity above 80%. Twenty-seven symptomatic tissues of infected leaves were first surface sterilized by immersion in 75% ethanol for 1 minute, followed by rinsing three times in sterile distilled water. The tissues were then cut into 4-5 mm pieces, plated on 1.5% potato dextrose agar (PDA), and incubated at 28±2°C. The hyphal tip from the growing edge of colonies cultured for three days at 28±2℃ was transferred to PDA to obtain pure cultures. Fungal colonies were white, then grey to black with an unevenly distributed, fast-growing aerial mycelium covering the petri dish within five days at 28±2℃. The colony turned dark brown when maintained in the dark at 28±2℃ after seven days, then grayish brown upon sporulation after 15 days (Fig.1f-g). Conidia were brown or black, smooth, spherical to sub-spherical, single-celled (8-12 µm × 10-13µm, average 9-11.5 µm in diameter, n=5µm). The nutritional hyphae exhibited septa, and a portion of the aerial hyphae formed a long, rough conidium, giving rise to a nearly spherical apical sac (Fig.1h). The surface gave rise to several small peduncles bearing clusters of surfaced spherical conidia (Fig.1i). Surfaced spherical conidia were generated on the surface of the small peduncle (Fig.1j). These morphological features were consistent with Nigrospora oryzae (Li et al., 2017). Genomic DNA was extracted from mycelia of the pathogen using an Ezup column fungal genomic DNA extraction kit (Sangon Biotech, Shanghai, China). To confirm the identity of the pathogen, the genomic fragments for the internal transcribed spacer (ITS), LSU (28S) and BenA gene of the isolate were amplified by PCR (Wang et al., 2017) and sent for sequencing. The resultant sequence (GeneBank ID of gene ITS, LSU, BenA are OR723825, OR775345, OR277316, respectively) were compared with the voucher specimens. BLAST results showed >99% identity with those of N.oryzae (GeneBank ID of N.oryzae strain LC2707 ITS, LSU, BenA are KX985954, KY806242, KY019481, respectively). A neighbor joining phylogenetic tree with the concatenated sequences of these genes showed that A-pb169 had the closest match with N. oryzae (Fig. 2). For pathogenicity testing, fifty plants in a period of rapid expansion of bulb growth were selected. Four leaves per plant were inoculated by sprayed till runoff with a conidial suspension of the pathogen (50 µL, 1×106 conidia/ml sterile water), and incubated at 30±2℃ and 80 ± 5% humidity. Control plants received sterile water. On the third day after inoculation, a yellow-brown spot appeared on leave surfaces, the spot gradually expanded; the infection rate was 90 to 95%. Fifteen days after inoculation, infected leaves showed symptoms like those observed in the field, whereas 100 control leaves sprayed with sterile water remained symptomless (Fig.1 a-e). The pathogen was reisolated from infected leaves and confirmed as N. oryzae by morphology and molecular identification. To our knowledge, this is the first report of leaf spot disease of A. albus caused by N. oryzae in China. Since its one of the major cash crops of the southeastern China, further work is necessary to determine its spread and economic impact as well as developing sustainable disease management options.