Complete mitochondrial genome of Melia azedarach L., reveals two conformations generated by the repeat sequence mediated recombination.

Melia azedarach is a species of enormous value of pharmaceutical industries. Although the chloroplast genome of M. azedarach has been explored, the information of mitochondrial genome (Mt genome) remains surprisingly limited. In this study, we used a hybrid assembly strategy of BGI short-reads and Nanopore long-reads to assemble the Mt genome of M. azedarach. The Mt genome of M. azedarach is characterized by two circular chromosomes with 350,142 bp and 290,387 bp in length, respectively, which encodes 35 protein-coding genes (PCGs), 23 tRNA genes, and 3 rRNA genes. A pair of direct repeats (R1 and R2) were associated with genome recombination, resulting in two conformations based on the Sanger sequencing and Oxford Nanopore sequencing. Comparative analysis identified 19 homologous fragments between Mt and chloroplast genome, with the longest fragment of 12,142 bp. The phylogenetic analysis based on PCGs were consist with the latest classification of the Angiosperm Phylogeny Group. Notably, a total of 356 potential RNA editing sites were predicted based on 35 PCGs, and the editing events lead to the formation of the stop codon in the rps10 gene and the start codons in the nad4L and atp9 genes, which were verified by PCR amplification and Sanger sequencing. Taken together, the exploration of M. azedarach gap-free Mt genome provides a new insight into the evolution research and complex mitogenome architecture.

Highly transparent Ce:Nd:YAG ceramic with good light conversion capacity for solar-pumped solid-state lasers.

Developing a high quality ceramic laser gain medium for solar directly pumped solid state lasers is essential, and yet the light conversion efficiency of the gain media for solar pumping remains a challenge. In this study, Ce and Nd ions, co-doped YAG transparent ceramics with theoretical transmittance and stable Ce3+ valent state were developed, and revealed that the absorbed visible light and light conversion efficiency in Ce,Nd:YAG ceramics were 3.98 times and 1.34 times higher than those in widely reported Cr,Nd:YAG ceramics, respectively. A concentration matching principle between Ce3+ and Nd3+ ions in YAG was established, and a higher Nd3+ ion doping concentration with a relatively low Ce3+ concentration was favorable to improve both the light conversion efficiency and emission intensity at 1064 nm of Ce,Nd:YAG ceramics. Energy transfer efficiency from Ce3+ to Nd3+ of the 0.3 at.%Ce,1.5at.%Nd:YAG ceramic reached as high as 61.71% at room temperature. Surprisingly, it was further promoted to 64.31% at a higher temperature of 473 K. More excited electrons at the upper energy level of Ce3+ ion under the high temperature accounted for this novel phenomenon. This study proposes a new design strategy of gain materials for solar directly pumped solid state lasers.

Selective effect of winter weather on a songbird's morphology depends on individual sex and winter condition.

Knowledge of the effect of harsh weather on the phenotypic traits of organisms is essential for understanding the environmental influence on phenotype evolution and holds implications for predicting how species respond to current climate change. For many birds, harsh weather in winter often imposes a strong selective effect on their survival, and only the individuals with certain phenotypes may survive. However, whether the selective effect on phenotype varies with winter weather conditions has been poorly investigated. Here, we explored the selective effect of winter weather on black-throated tit's (Aegithalos concinnus) morphological traits under winters with and without severe snowstorms. We found that for males, the sizes of their bills, heads and wings significantly affected their overwinter survival, but the effects varied with winter conditions. In relatively benign winters, males with smaller bill depths, smaller bill surface areas, and greater head lengths survived better; whereas, in winters with severe snowstorms, a reverse pattern was found. This phenomenon was likely driven by selection pressures from heat retention and foraging requirements, with their relative importance depending on winter conditions. Additionally, wing length was positively correlated with male survival and the relationship was stronger in harsher winters, which was probably due to longer wings' higher flight efficiency in adverse weather. By contrast, we found no correlation between morphological traits and survival in females. These results suggest a sex-specific and condition-dependent selective effect of environment on bird phenotypes, implying complicated interactions between different selection pressures and phenotype evolution.

DL-PPI: a method on prediction of sequenced protein-protein interaction based on deep learning.

PURPOSE: Sequenced Protein-Protein Interaction (PPI) prediction represents a pivotal area of study in biology, playing a crucial role in elucidating the mechanistic underpinnings of diseases and facilitating the design of novel therapeutic interventions. Conventional methods for extracting features through experimental processes have proven to be both costly and exceedingly complex. In light of these challenges, the scientific community has turned to computational approaches, particularly those grounded in deep learning methodologies. Despite the progress achieved by current deep learning technologies, their effectiveness diminishes when applied to larger, unfamiliar datasets. RESULTS: In this study, the paper introduces a novel deep learning framework, termed DL-PPI, for predicting PPIs based on sequence data. The proposed framework comprises two key components aimed at improving the accuracy of feature extraction from individual protein sequences and capturing relationships between proteins in unfamiliar datasets. 1. Protein Node Feature Extraction Module: To enhance the accuracy of feature extraction from individual protein sequences and facilitate the understanding of relationships between proteins in unknown datasets, the paper devised a novel protein node feature extraction module utilizing the Inception method. This module efficiently captures relevant patterns and representations within protein sequences, enabling more informative feature extraction. 2. Feature-Relational Reasoning Network (FRN): In the Global Feature Extraction module of our model, the paper developed a novel FRN that leveraged Graph Neural Networks to determine interactions between pairs of input proteins. The FRN effectively captures the underlying relational information between proteins, contributing to improved PPI predictions. DL-PPI framework demonstrates state-of-the-art performance in the realm of sequence-based PPI prediction.

Preparation and performance of solid thermal energy storage materials based on low-grade pyrophyllite minerals.

The new sensible thermal energy storage materials were prepared by the sintering method with low-grade pyrophyllite mineral powders as main raw materials, Suzhou clay as the sintering aid and sulfite liquors as the binder. Further, the performance of sensible thermal energy storage under different size distributions and sintering temperatures was investigated and analyzed. The results show that the optimum particle size distribution is 50:15:35, the bulk density, thermal conductivity, and specific heat capacity are the largest values, which are 1.97 g cm-3, 0.87 W m-1 K-1 and 0.63 kJ kg-1 K-1, respectively. Other properties including porosity, water absorption, flexural and compressive strength and so on are optimal under this size distribution. When the sintering temperature is 1200 °C, the material has a good thermal conductivity of 0.89 W m-1 K-1 and a high bulk density of 2.05 g cm-3. Meanwhile, the sample with the used temperature from 50 to 900 °C has the best thermal energy storage capacity of 306.29 kWh·m-3.

Extraction and characterization of polysaccharides from blackcurrant fruits and its inhibitory effects on acetylcholinesterase.

Microwave assisted aqueous two-phase system (MA-ATPS) was used to simultaneously extract two polysaccharides from blackcurrant. Under the suitable ATPS (ethanol/(NH4)2SO4, 26.75 %/18.98 %) combining with the optimal MA conditions (liquid-to-material ratio 58.5 mL/g, time 9.5 min, temperature 60.5 °C, power 587 W) predicted by response surface methodology, the yields of the top/bottom phase polysaccharides were 13.08 ± 0.37 % and 42.65 ± 0.89 %, respectively. After purification through column chromatography, the top phase polysaccharide (PRTP) and bottom phase polysaccharide (PRBP) were obtained. FT-IR, methylation and NMR analyses confirmed that the repeating unit in the backbone of PRTP was →2, 5)-α-L-Araf-(1 â†’ 3)-α-D-Manp-(1 â†’ 6)-ß-D-Galp-(1 â†’ 6)-α-D-Glcp-(1 â†’ 4)-α-L-Rhap-(1 â†’ 4)-α-D-GalAp-(1→, while the possible unit in PRBP was →4)-α-L-Rhap-(1 â†’ 3)-α-D-Manp-(1 â†’ 6)-ß-D-Galp-(1 â†’ 6)-α-D-Glcp-(1 â†’ 2, 5)-α-L-Araf-(1 â†’ 4)-α-D-GalAp-(1→. PRBP with relatively low molecular weight exhibited better stability, rheological property, free radical scavenging and acetylcholinesterase (AChE) inhibitory activities than PRTP. PRTP and PRBP were reversible mixed-type inhibitors for AChE, and the conformation of AChE was changed after binding with the polysaccharides. Molecular docking, fluorescence and isothermal titration calorimetry assays revealed that PRTP and PRBP quenched the fluorescence through static quenching mechanism, and the van der Waals interactions and hydrogen bonding played key roles in the stability of polysaccharide-enzyme complexes. This study provided a theoretical basis for blackcurrant polysaccharides as AChE inhibitors to treat Alzheimer's disease.

Video evidence that cuckoos farm their hosts by ejecting nestlings.

When host nests are scarce, avian brood parasites would benefit from behaviours that increase the availability of suitable nests. Several studies reported ejection of host nestlings from nests by brood parasites; however, whether brood parasites do so to induce the host to re-nest and thus increase opportunities for future parasitism (i.e. 'farming' behaviour) remains unclear. Here, we report observational evidence of farming behaviour by a common cuckoo Cuculus canorus female in a Daurian redstart Phoenicurus auroreus population: (1) the cuckoo destroyed a host nest by ejecting all nestlings, (2) the host then produced a new nest and (3) the cuckoo successfully parasitized the replacement nest. We suggest that farming behaviour may be more common, but often goes undetected because it requires intense nest monitoring.

Mining software insights: uncovering the frequently occurring issues in low-rating software applications.

In today's digital world, app stores have become an essential part of software distribution, providing customers with a wide range of applications and opportunities for software developers to showcase their work. This study elaborates on the importance of end-user feedback for software evolution. However, in the literature, more emphasis has been given to high-rating & popular software apps while ignoring comparatively low-rating apps. Therefore, the proposed approach focuses on end-user reviews collected from 64 low-rated apps representing 14 categories in the Amazon App Store. We critically analyze feedback from low-rating apps and developed a grounded theory to identify various concepts important for software evolution and improving its quality including user interface (UI) and user experience (UX), functionality and features, compatibility and device-specific, performance and stability, customer support and responsiveness and security and privacy issues. Then, using a grounded theory and content analysis approach, a novel research dataset is curated to evaluate the performance of baseline machine learning (ML), and state-of-the-art deep learning (DL) algorithms in automatically classifying end-user feedback into frequently occurring issues. Various natural language processing and feature engineering techniques are utilized for improving and optimizing the performance of ML and DL classifiers. Also, an experimental study comparing various ML and DL algorithms, including multinomial naive Bayes (MNB), logistic regression (LR), random forest (RF), multi-layer perception (MLP), k-nearest neighbors (KNN), AdaBoost, Voting, convolutional neural network (CNN), long short-term memory (LSTM), bidirectional long short term memory (BiLSTM), gated recurrent unit (GRU), bidirectional gated recurrent unit (BiGRU), and recurrent neural network (RNN) classifiers, achieved satisfactory results in classifying end-user feedback to commonly occurring issues. Whereas, MLP, RF, BiGRU, GRU, CNN, LSTM, and Classifiers achieved average accuracies of 94%, 94%, 92%, 91%, 90%, 89%, and 89%, respectively. We employed the SHAP approach to identify the critical features associated with each issue type to enhance the explainability of the classifiers. This research sheds light on areas needing improvement in low-rated apps and opens up new avenues for developers to improve software quality based on user feedback.

The complete mitochondrial genome of Aglaia odorata, insights into its genomic structure and RNA editing sites.

Aglaia odorata, native to Guangdong, Guangxi, and Hainan provinces in China, has long been utilized as an herbal remedy in ancient China. In this study, we assembled and annotated the complete mitochondrial genome (mitogenome) of A. odorata, which spans a total length of 537,321 bp. Conformation of the A. odorata recombination was verified through PCR experiments and Sanger sequencing. We identified and annotated 35 protein-coding genes (PCGs), 22 tRNA genes, and 3 rRNA genes within the mitogenome. Analysis of repeated elements revealed the presence of 192 SSRs, 29 pairs of tandem repeats, and 333 pairs of dispersed repeats in the A. odorata mitogenome. Additionally, we analyzed codon usage and mitochondrial plastid DNAs (MTPTs). Twelve MTPTs between the plastome and mitogenome of A. odorata were identified, with a combined length of 2,501 bp, accounting for 0.47% of the mitogenome. Furthermore, 359 high-confidence C to U RNA editing sites were predicted on PCGs, and four selected RNA editing sites were specially examined to verify the creation of start and/or stop codons. Extensive genomic rearrangement was observed between A. odorata and related mitogenomes. Phylogenetic analysis based on mitochondrial PCGs were conducted to elucidate the evolutionary relationships between A. odorata and other angiosperms.

Conquer coronary artery perforation with magic hands.

Coronary artery perforation (CAP) poses a significant challenge for interventional cardiologists. Management of CAP depends on the location and severity of the perforation. The conventional method for addressing the perforation of large vessels involves the placement of a covered stent, while the perforation of distal and collateral vessels is typically managed using coils, autologous skin, subcutaneous fat, microspheres, gelatin sponge, thrombin or other substances. However, the above techniques have certain limitations and are not applicable in all scenarios. Our team has developed a range of innovative strategies for effectively managing CAP. This article provides an insightful review of the various tips and tricks for the treatment of CAP.

A Comprehensive Review on Synergy of Multi-Modal Data and AI Technologies in Medical Diagnosis.

Disease diagnosis represents a critical and arduous endeavor within the medical field. Artificial intelligence (AI) techniques, spanning from machine learning and deep learning to large model paradigms, stand poised to significantly augment physicians in rendering more evidence-based decisions, thus presenting a pioneering solution for clinical practice. Traditionally, the amalgamation of diverse medical data modalities (e.g., image, text, speech, genetic data, physiological signals) is imperative to facilitate a comprehensive disease analysis, a topic of burgeoning interest among both researchers and clinicians in recent times. Hence, there exists a pressing need to synthesize the latest strides in multi-modal data and AI technologies in the realm of medical diagnosis. In this paper, we narrow our focus to five specific disorders (Alzheimer's disease, breast cancer, depression, heart disease, epilepsy), elucidating advanced endeavors in their diagnosis and treatment through the lens of artificial intelligence. Our survey not only delineates detailed diagnostic methodologies across varying modalities but also underscores commonly utilized public datasets, the intricacies of feature engineering, prevalent classification models, and envisaged challenges for future endeavors. In essence, our research endeavors to contribute to the advancement of diagnostic methodologies, furnishing invaluable insights for clinical decision making.

The complete mitochondrial genome of Pontederia crassipes: using HiFi reads to investigate genome recombination and gene transfer from chloroplast genome.

Water hyacinth (Pontederia crassipes Mart.) is a monocotyledonous aquatic plant renowned for its rapid growth, extensive proliferation, biological invasiveness, and ecological resilience to variations in pH, nutrients, and temperature. The International Union for Conservation of Nature (IUCN) has listed P. crassipes among the top 100 invasive species. However, comprehensive genomic information, particularly concerning its mitochondrial genome (mitogenome), remains surprisingly limited. In this study, the complete mitogenome of P. crassipes was analyzed using bioinformatics approaches. The mitogenome is 399,263 bp long and contains 38 protein-coding genes (PCGs), 24 tRNA genes, and 3 rRNA genes. Sequence analysis revealed that the complete mitogenome of the species contains 3,289 dispersed repeats, and 765 RNA editing sites in protein-coding genes. The P. crassipes mitogenome possessed un-conserved structures, including extensive sequence transfer between its chloroplasts and mitochondria. Our study on the mitogenome of P. crassipes offers critical insights into its evolutionary patterns and phylogenetic relationships with related taxa. This research enhances our understanding of this invasive species, known for its significant biomass and rapid overgrowth in aquatic environments.

Carrier-free self-assembled nanoparticles based on prochloraz and fenhexamid for reducing toxicity to aquatic organism.

Nanoformulations of pesticides are an effective way to increase utilization efficiency and alleviate the adverse impacts on the environments caused by conventional pesticide formulations. However, the complex preparation process, high cost, and potential environmental risk of nanocarriers severely restricted practical applications of carrier-based pesticide nanoformulations in agriculture. Herein, carrier-free self-assembled nanoparticles (FHA-PRO NPs) based on fenhexamid (FHA) and prochloraz (PRO) were developed by a facile co-assembly strategy to improve utilization efficiency and reduce toxicity to aquatic organism of pesticides. The results showed that noncovalent interactions between negatively charged FHA and positively charged PRO led to core-shell structured nanoparticles arranged in an orderly manner dispersing in aqueous solution with a diameter of 256 nm. The prepared FHA-PRO NPs showed a typical pH-responsive release profile and exhibited excellent physicochemical properties including low surface tension and high max retention. The photostability of FHA-PRO NPs was improved 2.4 times compared with free PRO. The FHA-PRO NPs displayed superior fungicidal activity against Sclerotinia sclerotiorum and Botrytis cinerea and longer duration against Sclerotinia sclerotiorum on potted rapeseed plants. Additionally, the FHA-PRO NPs reduced the acute toxicity of PRO to zebrafish significantly. Therefore, this work provided a promising strategy to develop nanoformulations of pesticides with stimuli-responsive controlled release characteristics for precise pesticide delivery.

Dispersal patterns of Reeves's pheasant based on genetic and behavioral evidence.

Dispersal is an important life history trait that plays a crucial role in avoiding inbreeding. Uncovering the dispersal pattern of a threatened species facilitates conservation efforts. Most species of Galliformes are forest-dwelling terrestrial birds with a weak dispersal ability and high conservation priorities. However, little is known about the dispersal behavior and dispersal pattern of Galliformes species such as Reeves's pheasant Syrmaticus reevesii, a globally vulnerable species endemic to China. Here, we integrated behavioral and genetic analyses to investigate the dispersal pattern of Reeves's pheasant. Our results revealed that both females and males would disperse, although the overall dispersal pattern was more likely to be male-biased. Reeves's pheasant population had a low level of genetic diversity and a mild level of inbreeding. Speculation low genetic diversity was resulted from fragmented habitat, and male-biased dispersal may reduce the opportunity of inbreeding. Our research indicated that sex-biased dispersal patterns may be a behavioral mechanism adopted by wildlife to avoid inbreeding in a fragmented habitat.

Bridging papermaking and hydrogel production: Nanoparticle-loaded cellulosic hollow fibers with pitted walls as skeleton materials for multifunctional electromagnetic hydrogels.

Electromagnetic hydrogels have attracted significant attention due to their vast potential in soft robotics, biomedical engineering, and energy harvesting. To facilitate future commercialization via large-scale industrial processes, we present a facile concept that utilizes the specialized knowledge of papermaking to fabricate hydrogels with multifunctional electromagnetic properties. The principles of papermaking wet end chemistry, which involves the handling of interactions among cellulosic fibers, fines, polymeric additives, and other components in aqueous systems, serves as a key foundation for this concept. Notably, based on these principles, the versatile use of chemical additives in combination with cellulosic materials enables the tailored design of various products. Our methodology exploits the unique hierarchically pitted and hollow tube-like structures of papermaking grade cellulosic fibers with discernible pits, enabling the incorporation of magnetite nanoparticles through lumen loading. By combining microscale softwood-derived cellulosic fibers with additives, we achieve dynamic covalent interactions that transform the cellulosic fiber slurry into an impressive hydrogel. The cellulosic fibers act as a skeleton, providing structural support within the hydrogel framework and facilitating the dispersion of nanoparticles. In accordance with our concept, the typical hydrogel exhibits combined attributes, including electrical conductivity, self-healing properties, pH responsiveness, and dynamic rheologic behavior. Our approach not only yields hydrogels with interesting properties but also aligns with the forefront of advanced cellulosic material applications. These materials hold the promise in remote strain sensing devices, electromagnetic navigation systems, contactless toys, and flexible electronic devices. The concept and findings of the current work may shed light on materials innovation based on traditional pulp and paper processes. Furthermore, the facile processes involved in hydrogel formation can serve as valuable tools for chemistry and materials education, providing easy demonstrations of principles for university students at different levels.

Olive (Olea europaea L.) Seed as New Source of Cholesterol-Lowering Bioactive Peptides: Elucidation of Their Mechanism of Action in HepG2 Cells and Their Trans-Epithelial Transport in Differentiated Caco-2 Cells.

The production of olive oil has important economic repercussions in Mediterranean countries but also a considerable impact on the environment. This production generates enormous quantities of waste and by-products, which can be exploited as new raw materials to obtain innovative ingredients and therefore make the olive production more sustainable. In a previous study, we decided to foster olive seeds by generating two protein hydrolysates using food-grade enzymes, alcalase (AH) and papain (PH). These hydrolysates have shown, both in vitro and at the cellular level, antioxidant and antidiabetic activities, being able to inhibit the activity of the DPP-IV enzyme and modulate the secretion of GLP-1. Given the multifunctional behavior of peptides, both hydrolysates displayed dual hypocholesterolemic activity, inhibiting the activity of HMGCoAR and impairing the PPI of PCSK9/LDLR, with an IC50 equal to 0.61 mg/mL and 0.31 mg/mL for AH and PH, respectively. Furthermore, both samples restored LDLR protein levels on the membrane of human hepatic HepG2 cells, increasing the uptake of LDL from the extracellular environment. Since intestinal bioavailability is a key component of bioactive peptides, the second objective of this work is to evaluate the capacity of AH and PH peptides to be transported by differentiated human intestinal Caco-2 cells. The peptides transported by intestinal cells have been analyzed using mass spectrometry analysis, identifying a mixture of stable peptides that may represent new ingredients with multifunctional qualities for the development of nutraceuticals and functional foods to delay the onset of metabolic syndrome, promoting the principles of environmental sustainability.

High-performance plastic-derived metal-free catalysts for organic pollutants degradation via Fenton-like reaction.

The preparation of waste plastics-derived catalysts is an effective strategy for the waste reclamation. However, plastic-derived material is unsuitable for wastewater purification due to its small specific surface area (SSA) and inadequate active sites (such as N/O sites). Herein, we synthesized graphene-like nanosheets using g-C3N4 as the self-sacrificing soft template and plastic as the carbon precursor. Consequently, this strategy greatly promoted the efficiencies of the emerging organic pollutants degradation with the SSA and N content of the plastic-derived biochar increasing up to 1043.4 m2/g and 17.53 at.%, respectively. In detail, 100 % sulfadiazine (SD) removal could be achieved in 180 s via the activation of peroxymonosulfate (PMS) and the catalytic activity is far higher than previous research. Mechanism experiments corroborated that such a striking performance was attributed to the generation of SO4•-, O2•- and 1O2. Meanwhile, kinds of plastic precursors, even medical waste (i.e., masks, gauze, operating caps and degreasing cotton) were also applicable. And the practical application of the plastic-derived catalyst was further demonstrated by treating pollutants in a continuous flow mode with in situ fabricated membrane. This work provides valuable insights into waste plastics processing and water pollutants removal.

OMGMed: Advanced System for Ocular Myasthenia Gravis Diagnosis via Eye Image Segmentation.

This paper presents an eye image segmentation-based computer-aided system for automatic diagnosis of ocular myasthenia gravis (OMG), called OMGMed. It provides great potential to effectively liberate the diagnostic efficiency of expert doctors (the scarce resources) and reduces the cost of healthcare treatment for diagnosed patients, making it possible to disseminate high-quality myasthenia gravis healthcare to under-developed areas. The system is composed of data pre-processing, indicator calculation, and automatic OMG scoring. Building upon this framework, an empirical study on the eye segmentation algorithm is conducted. It further optimizes the algorithm from the perspectives of "network structure" and "loss function", and experimentally verifies the effectiveness of the hybrid loss function. The results show that the combination of "nnUNet" network structure and "Cross-Entropy + Iou + Boundary" hybrid loss function can achieve the best segmentation performance, and its MIOU on the public and private myasthenia gravis datasets reaches 82.1% and 83.7%, respectively. The research has been used in expert centers. The pilot study demonstrates that our research on eye image segmentation for OMG diagnosis is very helpful in improving the healthcare quality of expert doctors. We believe that this work can serve as an important reference for the development of a similar auxiliary diagnosis system and contribute to the healthy development of proactive healthcare services.

Identification and Pathogenicity of Pestalotioid Species on Alpinia oxyphylla in Hainan Province, China.

Alpinia oxyphylla is a traditional Chinese medicinal plant with a medicinal history of more than 1700 years. Ring leaf blight (RLB) disease, caused by pestalotioid species, is an important disease of A. oxyphylla, seriously affecting the yield and quality of its fruits. The causal agent of RLB disease has not been systematically identified or characterized yet. In this study, thirty-six pestalotioid strains were isolated from the leaves and stems of A. oxyphylla that was collected from six cities of Hainan province, China. Based on the multi-locus phylogeny (ITS, tef-1α and tub2) and morphological characteristic analyses, seventeen species belonging to three genera (Neopestalotiopsis, Pestalotiopsis and Pseudopestalotiopsis) were identified, and six new species (N. baotingensis, N. oblatespora, N. olivaceous, N. oxyphylla, N. wuzhishanensis and N. yongxunensis) were described. Pathogenicity tests revealed that strains of Neopestalotiopsis species caused more severe ring leaf blight on A. oxyphylla than strains of Pestalotiopsis and Pseudopestalotiopsis under wounded inoculation conditions.