Identification Of Species Research Articles

Prevalence and associated factors for isolated Malassezia species in patients with Dandruff in Mekelle City, Tigrai, Ethiopia

ObjectiveDandruff, a condition caused by lipophilic Malassezia fungi, is an excessive shed of dead skin cells from the scalp. Effective preventive and curative measures of the condition depend on knowledge and understanding of the prevalence of the condition, the common etiologic species, and the associated factors. This study aimed to investigate the prevalence, common etiologic species, and associated factors of Malassezia infection in Mekelle City, Ethiopia.MethodA facility-based cross-sectional study was conducted from February 2019 to June 2020 involving 217 participants who were visiting dermatology clinics to seek treatment for dandruff conditions. Information on the socio-demographic characteristics and hair care behaviors of the participants was obtained. Isolation and identification of Malassezia species from scalp scrapings using cultural and biochemical tests were carried out.ResultsOut of the 217 participants with dandruff, 111 (51.15%) were positive for Malassezia fungi. One hundred forty (140) Malassezia isolates were collected from the 111 positive participants. Further study of the isolates yielded three etiologic species: Malassezia globosa (67.15%), M. furfur (21.70%), and M. restricta (12.15%). Demographic characteristics, namely gender (AOR = 2.605; 95%CI: 1.427 − 4.757) and age (AOR = 2.667; 95%CI: 1.046 − 6.795), as well as hair care behaviors, namely use of hair oil (AOR = 2.964; 95%CI: 1.288 − 6.820), were associated with the presence of Malassezia species. However, the use of anti-dandruff shampoo (AOR = 2.782; 95%CI: 1.301 − 10.993) was negatively associated with the presence of Malassezia species among the participants with dandruff conditions. These findings open opportunities to devise effective prevention, management, and control measures for Malassezia-based dandruff conditions.

First report of Colletotrichum nymphaeae causing anthracnose on Hass avocados in Brazil.

The Hass cultivar is one of the most cultivated and distributed avocado varieties throughout the world, having high productivity, nutritional quality, market acceptance and adaptation to different climatic zones (Dreher and Davenport 2013). Anthracnose affects avocado production in tropical and subtropical regions, causing economic losses, especially post-harvest (Fuentes-Aragón et al. 2020). Correct identification of Colletotrichum species causing anthracnose is essential, as different species vary in important phenotypes such as virulence and sensitivity to fungicides (Chen et al. 2016). Twelve samples from batches of avocados with anthracnose were collected in Minas Gerais State, Brazil, in September 2023. The observed symptoms were brown to black depressed circular spots, ranging from a few millimeters to 3 cm in diameter on the epicarp of the fruits, covered in center by mucilaginous layers of pathogen sporulation. Isolation was performed directly from the spore masses and monoconidial isolates were cultured in PDA at 25°C for 7 days for morphological characterization and preserved in sterile water at 4°C. One of the morphotypes commonly recovered from lesions, represented by isolate UCBV 362 (Culture Collection COAD 3843), formed fast-growing colonies having white aerial mycelium and intense salmon-colored sporulation. The cylindrical conidia were 13 to 17.5 μm long and 4.5 to 7 μm wide (average 14.5 x 5.7 μm, N=100), produced on conidiophores dispersed in the aerial mycelium or aggregated on melanized conidiomata formed on the agar. The partial sequence of the second largest subunit of the RNA polymerase II gene (RPB2) from isolate UCBV 362 (GenBank: PQ034617, 1116 nt) showed 99% of coverage and 99.37% of nucleotide identity with the RPB2 sequence of the ex-epitype strain of Colletotrichum nymphaeae ICMP 17918 (=CBS 515.78) (GenBank: JN985506). In a Maximum Likelihood phylogenetic tree composed with RBP2 sequences from reference strains of the Colletotrichum acutatum species complex, the isolate UCBV 362 formed a highly supported clade with the ex-epitype and other reference strains of Colletotrichum nymphaeae, occupying the Clade 2 of the species complex together with C. scovillae and C. simmondsii (Damm et al. 2012). This result shows the reliability of RPB2 for phylogeny and species delimitation within Colletotrichum. To confirm pathogenicity, 10-mm discs from a 7-day-old colony were inoculated at 3 different points on healthy-looking avocado fruits and incubated at 28°C. Uninoculated fruits served as controls. The first symptoms appeared 5 days after inoculation and were similar to those observed in the original samples, while the fruits in the control group remained asymptomatic. The pathogen was reisolated from the lesions and identified morphologically, fulfilling Koch's postulates. Colletotrichum nymphaeae has been associated with avocado anthracnose in Mexico (Fuentes-Aragón et al. 2020). In Brazil, a study based on molecular phylogeny identified Colletotrichum siamense and C. karsti as etiological agents of this disease (Soares et al. 2021). This report expands the range of species that cause avocado anthracnose in Brazil and provides etiological information for the implementation and monitoring of control methods, especially chemical control.

Complete Chloroplast Genomes and Phylogenetic Analysis of Woody Climbing Genus Phanera (Leguminosae).

Phanera Lour., a genus in the subfamily Cercidoideae of the family Leguminosae, is characterized by woody liana habit, tendrils, and distinctive bilobate or bifoliolate leaves. The genus holds important medicinal value and constitutes a complex group characterized by morphological diversity and unstable taxonomic boundaries. However, limited information on the chloroplast genomes of this genus currently available constrains our understanding of its species diversity. Hence, it is necessary to obtain more chloroplast genome information to uncover the genetic characteristics of this genus. We collected and assembled the complete chloroplast genomes of nine representative Phanera plants, including Phanera erythropoda, Phanera vahlii, Phanera aureifolia, Phanera bidentata, Phanera japonica, Phanera saigonensis, Phanera championii, Phanera yunnanensis, and Phanera apertilobata. We then conducted a comparative analysis of these genomes and constructed phylogenetic trees. These species are each characterized by a typical quadripartite structure. A total of 130-135 genes were annotated, and the GC content ranged from 39.25-42.58%. Codon usage analysis indicated that codons encoding alanine were dominant. We found 82-126 simple sequence repeats, along with 5448 dispersed repeats, mostly in the form of forward repeats. Phylogenetic analysis revealed that 16 Phanera species form a well-supported monophyletic group, suggesting a possible monophyletic genus. Furthermore, 10 hypervariable regions were detected for identification and evolutionary studies. We focused on comparing chloroplast genome characteristics among nine Phanera species and conducted phylogenetic analyses, laying the foundation for further phylogenetic research and species identification of Phanera.

Environmental Impact of Digital Technologies and Artificial Intelligence

Very often arguments are put forward that replacing in-person meetings by online events or using digital technologies to do collaborative research will lower the pressure on the environment (Spencer 2023). But is this actually true? The obvious impacts, such as the carbon footprint of using digital technologies, are often overlooked. The electricity (even if green alternatives exist) used to run and cool the ever-growing number of large data centers has been regularly cited (Monteclaro 2023) as the largest contributor to this impact. Recent studies (Bordage 2019), however, tend to show that other actors (mostly the users) in the domain of digital technologies, appear to have an even greater impact. Additionally, ethical considerations and habitat degradation issues resulting from mining for the components to build professional and personal digital devices contribute to the problems. The deployments of networks have also a non-negligible share in the calculation of the actual digital impact on the environement (Bordage 2019). The tremendous increase of generated data, information exchanges, algorithms to run digital applications due to the larger use of AI in all scientific fields, in all sectors of the policy making, industry and civil society will increase the environmental impact of digital technologies even more. However, depending on the purpose of the AI technology, if its usage can demonstrate a reduction of negative environmental impacts, mitigation solutions can be envisaged. For example, if AI allows better land planning or better identification of species, it could balance out the digital environmental impact. In terms of online versus in-person or hybrid meetings, the issue is not as easy as one may think. For in-person meetings, especially in topics like biodiversity information, almost everyone is using devices such as laptops, tablets or smartphones, even encouraged by the organizers and speakers, making live demos, or doing online polls requiring the use of digitial technologies (e.g., Mentimeter). Totally online meetings make heavy use of the networks, dataflows and devices, even if it can be argued that the impact of the flights is removed from the equation. Hybrid meetings combine both the impacts of fully in-person or fully online options, also encouraging local participants to interact with the online participants and potentially demultiplying the environemental impact even more. Mitigation aspects to take into account are the added value of social interactions, learning about localhost's culture and biodiversity, and input to the local economies and infrastructures to welcome business tourism for large conferences. Efforts made to make onsite meetings greener play an important role, by wisely choosing the location and how catering is handled with local products and diminishing the use of one-use-only cups and cutlery. The debate on which meeting options are the best, is far from being closed and will continue into the future. This presentation will show recent analyses conducted, among others, by the European Institutes for Sustainable IT (information technology), to demystify common assumptions on major responsibilities in terms of environmental impact or carbon footprints of digital technologies. Tips and tricks to lower everyone's overall digital impact will be provided as well as encouraging the actors in biodiversity information to sign the Sustainable IT charter or even act further to get the highest Sustainable IT label for their institutions.

OGU: A Toolbox for Better Utilising Organelle Genomic Data.

Organelle genomes serve as crucial datasets for investigating the genetics and evolution of plants and animals, genome diversity, and species identification. To enhance the collection, analysis, and visualisation of such data, we have developed a novel open-source software tool named Organelle Genome Utilities (OGU). The software encompasses three modules designed to streamline the handling of organelle genome data. The data collection module is dedicated to retrieving, validating and organising sequence information. The evaluation module assesses sequence variance using a range of methods, including novel metrics termed stem and terminal phylogenetic diversity. The primer module designs universal primers for downstream applications. Finally, a visualisation pipeline has been developed to present comprehensive insights into organelle genomes across different lineages rather than focusing solely on individual species. The performance, compatibility and stability of OGU have been rigorously evaluated through benchmarking with four datasets, including one million mixed GenBank records, plastid genomic data from the Lamiaceae family, mitochondrial data from rodents, and 308 plastid genomes sourced from various angiosperm families. Based on software capabilities, we identified 30 plastid intergenic spacers. These spacers exhibit a moderate evolutionary rate and offer practical utility comparable to coding regions, highlighting the potential applications of intergenic spacers in organelle genomes. We anticipate that OGU will substantially enhance the efficient utilisation of organelle genomic data and broaden the prospects for related research endeavours.

Comparative analysis of chloroplast genome of Lonicera japonica cv. Damaohua.

Lonicera japonica is a well-known medicinal plant, and the Damaohua cultivar is one of the oldest known honeysuckle cultivars in China. The 155,151 bp chloroplast genome of this cultivar was obtained through Illumina sequencing. The genome includes a pair of inverted repeats (IRa and IRb; 23,789 bp each), a large single-copy region (88,924 bp), and a small single-copy (SSC) region (18,649 bp). In total, 127 unique genes were identified: 80 protein-coding, 39 tRNA, and 8 rRNA genes. Only ycf3 contained two introns. Eighty-nine large repetitive sequences and 54 simple sequence repeats were detected. Fifty potential RNA editing sites were predicted. Adaptive evolution analysis revealed that infA, matK, petB, petD, rbcL, rpl16, rpl2, rps3, ycf1, and ycf2 were positively selected, possibly reflecting the specific environmental adaptations of this cultivar. Sequence alignment and analysis revealed several candidate fragments for Lonicera species identification, such as the intergenic regions rpoB-petN, rbcL-accD, and psaA-ycf3. The IR region boundary and phylogenetic analysis revealed that the L. japonica cv. Damaohua chloroplast genome was most closely related to the L. japonica genome, but there were five distinct differences between the two. There are four sites with high variability between L. japonica and L. japonica cv. Damaohua with nucleotide variability (Pi) greater than 0.002, including rps2-rpoC2, atpB-rbcL, ycf1, and ycf1-trnN GUU. The differences between L. japonica and L. japonica cv. Damaohua were further confirmed by the single nucleotide polymorphism sites between these two species. Therefore, this study revealed that the chloroplast genome can serve as a universal super barcode for plant identification, which can identify differences and help distinguish Lonicera japonica from related species. An understanding of Lonicera japonica cv. Damaohua chloroplast genomics and a comparative analysis of Lonicera species will provide a scientific basis for breeding, species identification, systematic evolution analysis, and chloroplast genetic engineering research on medicinal honeysuckle plants.

Harnessing Artificial Intelligence for Wildlife Conservation

The rapid decline in global biodiversity demands innovative conservation strategies. This paper examines the use of artificial intelligence (AI) in wildlife conservation, focusing on the Conservation AI platform. Leveraging machine learning and computer vision, Conservation AI detects and classifies animals, humans, and poaching-related objects using visual spectrum and thermal infrared cameras. The platform processes these data with convolutional neural networks (CNNs) and transformer architectures to monitor species, including those that are critically endangered. Real-time detection provides the immediate responses required for time-critical situations (e.g., poaching), while non-real-time analysis supports long-term wildlife monitoring and habitat health assessment. Case studies from Europe, North America, Africa, and Southeast Asia highlight the platform’s success in species identification, biodiversity monitoring, and poaching prevention. The paper also discusses challenges related to data quality, model accuracy, and logistical constraints while outlining future directions involving technological advancements, expansion into new geographical regions, and deeper collaboration with local communities and policymakers. Conservation AI represents a significant step forward in addressing the urgent challenges of wildlife conservation, offering a scalable and adaptable solution that can be implemented globally.

Molecular Identification and Genetic Structure of Species of Bemisia1 and Trialeurodes1 in the Agroecosystems of Mexico

Molecular Identification and Genetic Structure of Species of Bemisia1 and Trialeurodes1 in the Agroecosystems of Mexico

Description of Trichophoromyia macrisae, a new phlebotomine sand fly species (Diptera: Psychodidae) from Manu Biosphere Reserve, Peru

Phlebotomine sand flies are a highly diverse group of insects capable of transmitting Leishmania parasites. Therefore, the identification of vector species is important to understand local leishmaniasis dynamics. Among the Neotropical sand fly species, the genus Trichophoromyia is predominantly found in the Amazon. A new species of this genus, Trichophoromyia macrisae sp. nov., is described. Specimens were collected using Katchy light traps in forested areas of Manu Biological Station, located within the Manu Biosphere Reserve, in southern Peru. Morphological description was based on 10 male specimens. The disposition of setae in the gonocoxite and the shape of the paramere allows Th. macrisae sp. nov. to be distinguished from other species of genus that have aedeagal ducts > 4 times the length of the sperm pump. The description of Th. macrisae sp. nov. brings the number of species of Trichophoromyia in the Americas to 47 and in Peru to 15.

Molecular identification of Fusarium species in commercial vanilla and crop wild relatives in Colombia.

Vanilla is an economically important crop for low-lying humid tropical regions, but cultivated plants face serious phytosanitary problems. Fusarium wilt is a devastating disease affecting vanilla crops, caused by the fungal pathogens Fusarium oxysporum f. sp. vanillae (Fov) and F. oxysporum f. sp. radicis-vanillae (Forv), part of the F. oxysporum species complex (FOSC). We characterized 29 fungal isolates from a vanilla crop and crop wild relatives (CWR) using molecular (EF1-α and ITS-rRNA loci) and morphological traits. Fusarium was the predominant genus, followed by Colletotrichum and Clonostachys. Four Fusarium species were identified: F. oxysporum (37.9%), Fusarium solani (20.7%), Fusarium pseudocircinatum (13.8%) and Fusarium concentricum (10.3%). The latter three species were isolated only from CWR and may represent latent pathogens. Fov was isolated from both the crop and CWR, while a Forv-affiliated isolate was also found in a vanilla crop, marking the first report in the neotropical region. The EF1-α locus provided greater genotype resolution, as well as having reference sequences for Forv. However, the fungal barcode ITS locus is widely applied. We recommend the continued use of both loci for Fusarium diagnosis in vanilla to facilitate early detection and the development of effective integrated crop management strategies.

Photocatalytic Reactions over TiO2-Based Interfacial Charge Transfer Complexes

The present review is related to the novel approach for improvement of the optical properties of wide bandgap metal oxides, in particular TiO2, based on the formation of the inorganic–organic hybrids that display absorption in the visible spectral range due to the formation of interfacial charge transfer (ICT) complexes. We outlined the property requirements of TiO2-based ICT complexes for efficient photo-induced catalytic reactions, emphasizing the simplicity of the synthetic procedure, the possibility of the fine-tuning of the optical properties supported by the density functional theory (DFT) calculations, and the formation of a covalent linkage between the inorganic and organic components of hybrids, i.e., the nature of the interface. In addition, this study provides a comprehensive insight into the potential applications of TiO2-based ICT complexes in photo-driven catalytic reactions (water splitting and degradation of organic molecules), including the identification of the reactive species that participate in photocatalytic reactions by the spin-trapping electron paramagnetic resonance (EPR) technique. Considering the practically limitless number of combinations between the inorganic and organic components capable of forming oxide-based ICT complexes and with the knowledge that this research area is unexplored, we are confident it is worth studying, and we emphasized some further perspectives.

Comparison between PCR-RFLP and sequencing techniques in the analysis of Paracoccidioides spp. biodiversity: limitations and insights into species and variant differentiation.

The study of Paracoccidioides spp. faces significant challenges due to limitations inherent in the molecular biology techniques employed. Recently, new species were described whose geographical and genetic distributions were investigated. The phylogenetic studies have revealed that genotypes originally thought to be exclusive in specific regions from South American countries are now being found in other areas of the continent. This finding indicates a broader geographic distribution of these genotypes than previously recognized. To evaluate two molecular biology techniques employed to identify genotypes of Paracoccidioides spp. strains from a Brazilian culture collection previously identified only by mycological methods. DNA samples from 35 Paracoccidioides spp. strains maintained in a Brazilian culture collection were subjected to amplification and enzymatic digestion with PCR-RFLP of tub1 gene, followed by sequencing of gp43 Exon 2 loci. Strains with species identification discrepancies had their tub1 sequences determined to verify possible nucleotide mutations. The genotypic characterization of Paracoccidioides spp. using PCR-RFLP of the tub1 gene identified 22 isolates as P. brasiliensis sensu stricto, two as P. americana, four as P. restrepiensis, and eight as P. lutzii. Sequencing of the gp43 Exon 2 loci revealed discrepancies in the identification of four P. venezuelensis isolates, previously characterized as P. brasiliensis sensu stricto by PCR-RFLP of tub1. The sequencing of tub1 from P. brasiliensis sensu stricto and P. venezuelensis isolates revealed nucleotide differences in the pyrimidine class (C and T) in their sequences, specifically at the position 176bp. These molecular tools were able to establish the genetic diversity within the Paracoccidioides genus, crucial for taxonomy and epidemiology studies. The finding of presence of P. venezuelensis in Brazil, previously thought to be exclusive to Venezuela, highlights genetic connections and evolutionary divergences within the genus. While the PCR-RFLP of tub1technique showed limitations in identifying P. venezuelensis, sequencing of the gp43 Exon 2 loci was able to accurately identify this genotype. Thus, our findings contribute to the understanding of the molecular epidemiology of PCM and emphasize the need for precise species characterization in mycological research.

Prevalence and identification of Bacillus species in cellophane, foil, and disposable plastic containers used for food packaging

Background: Foil, cellophane, and disposable plastic containers are commonly employed in food packaging, namely as coatings on food items. Nevertheless, the existence of microbes on the surface and inside the internal composition of these materials gives rise to concerns, as they have the capacity to multiply under ideal circumstances and spread to food items, thereby jeopardizing the safety and quality of the food. Objective: This study aimed at examining the number of microorganisms and identifying specific bacterial species within frequently used food packaging materials like foil, cellophane, and disposable plastic containers. Methods: samples of foil, cellophane, and disposable plastic containers were collected from various popular brands in Iran. The overall bacterial count wضas determined using defibering, flooding, and smear techniques followed by culturing on Tryptone Glucose Extract Agar (TGEA) medium. To identify the bacterial species, various biochemical tests were performed, including fermentation, motility testing, catalase test, oxidase test, and methyl red-Voges Proskauer (MR-VP) test. Results: Bacterial quantity ranged from 0 CFU/g to 8.3 × 103 CFU/g in analyzed samples. All the samples had primary contaminants mainly Bacillaceae family bacteria that could produce spores. Disposable plastic containers had the lowest bacterial count whereas cellophane showed the highest bacterial contamination level. Among Bacillaceae family members Bacillus licheniformis was dominant. Conclusion: The study's findings emphasize the possibility of microbial contamination in food packaging materials, including cellophane. These results indicate that the food packaging industry should adopt a rigorous approach to hazard evaluation and Important Control Points (HACCP) in order to guarantee the microbiological safety and efficacy of packaging materials.

A Data-Driven Model for Classification of Traditional Chinese Medicine Materials

This paper proposes a data-driven classification model for traditional Chinese medicinal herbs based on mid-infrared spectral data. Addressing the limitations of traditional identification methods when the herbs’ appearance is damaged or incomplete, this study employs machine learning techniques to achieve accurate classification of medicinal herb types through spectral data preprocessing and feature extraction. Firstly, the Savitzky-Golay convolution smoothing method and Standard Normal Variate (SNV) transformation were used for denoising the spectral data. Then, Principal Component Analysis (PCA) was employed to reduce the dimensionality of the high-dimensional spectral data and extract the key features. Finally, the Gaussian Mixture Model (GMM) was applied to cluster the reduced data, categorizing the medicinal herbs into six classes. The results show that this method produces the accurate and stable classification. The constructed model is not only applicable to the classification and origin identification of medicinal herbs but also provides an important reference value for the classification and origin identification of other plant species.

A Rapid, Simple Workflow for Quantification of External Adult Drosophila Structures.

The Drosophila compound eye is a precisely patterned tissue that has revealed molecular mechanisms and biological processes that drive morphogenesis. It is a simple structure of repeating unit eyes, termed ommatidia, that is used to characterize genetic interactions and gene functions. Mutations that affect eye architecture can be easily detected and analyzed; hence, this system is frequently used in under-resourced institutions. Further phenotypic analysis often includes a Scanning Electron Microscope (SEM) to generate high-magnification images suitable for quantitative analysis. However, SEMs are expensive and require costly reagents; sample preparation spans days; and, often, they need full-time staff for sample preparation and instrument maintenance. This limits their utility at under-resourced institutions or during budgetary austerity. In entomology, the use of high-resolution digital imaging technology is a common practice for the identification and characterization of species. This paper describes a method that combines strategies and allows for high-resolution digital imaging of adult Drosophila structures and quantitative analysis using the open software ImageJ. The workflow is a rapid and student-friendly alternative that remedies the limitations of underfunded and under-resourced research facilities with a cost-effective and rapid approach to quantitative phenotypic analysis.

Comparison of Efficient Deep Learning Architectures for Lactobacillus Species Identification

Comparison of Efficient Deep Learning Architectures for Lactobacillus Species Identification

Taxonomic Identification of Ligustrum foliosum Nakai: A Comprehensive Study of Macro- and Micromorphology.

Ligustrum foliosum Nakai, a species endemic to South Korea, is a member of the Oleaceae family. This study provides a comprehensive taxonomic identification of L. foliosum based on its macro- and micromorphological characteristics, particularly focusing on the leaf foliar epidermal taxonomy. Scanning electron microscopy (SEM) was used to analyze the leaf structures of L. foliosum collected from various populations on Ulleungdo Island, its primary habitat. Macromorphological assessment revealed that L. foliosum exhibits ovate to elliptical leaves with pointed apices, rounded bases, and entire, smooth margins. The leaves measured 3-10 cm in length and 1.5-4 cm in width, with a pinnate venation pattern and prominent secondary veins. The adaxial surface was dark green and glabrous, while the adaxial surface was lighter green and slightly pubescent. Micromorphological analysis using SEM provided detailed insights into the leaf epidermal characteristics. The epidermal cells were polygonal in shape with straight to slightly curved anticlinal walls. Anomocytic stomata that were not surrounded by specialized cells are the predominant type, with a density ranging from 100 to 150/mm2. Epidermal cells measured approximately 10-20 μm in length and 5-10 μm in width, while the stomata typically measured approximately 20-30 μm in length and 10-15 μm in width. Thick-walled bundle sheath cells were evident around the vascular bundles, with a density of 1-3 bundles/mm. The cuticle was moderately thick, providing protection against desiccation, and trichomes were elongated single cell on the leaf both surface. This study contributes to the understanding of L. foliosum's taxonomic position within the Oleaceae family by providing a detailed description of its macro- and micromorphological characteristics. These findings can aid in the identification and conservation of this endemic species, which is crucial for preserving the unique biodiversity of Ulleungdo Island and South Korea.

Outgrowth of Escherichia is susceptible to aggravation of systemic lupus erythematosus

BackgroundSystemic lupus erythematosus (SLE) is linked to host gut dysbiosis. Here we performed faecal gut microbiome sequencing to investigate SLE-pathogenic gut microbes and their potential mechanisms.MethodsThere were 134 healthy controls (HCs) and 114 SLE cases for 16 S ribosomal RNA (rRNA) sequencing and 97 HCs and 124 SLE cases for shotgun metagenomics. Faecal microbial changes and associations with clinical phenotypes were evaluated, and SLE-associated microbial genera were identified in amplicon analysis. Next, metagenomic sequencing was applied for accurate identification of microbial species and discovery of their metabolic pathways and immunogenic peptides both relevant to SLE. Finally, contribution of specific taxa to disease development was confirmed by oral gavage into lupus-prone MRL/lpr mice.ResultsSLE patients had gut microbiota richness reduction and composition alteration, particularly lupus nephritis and active patients. Proteobacteria/Bacteroidetes (P/B) ratio was remarkably up-regulated, and Escherichia was identified as the dominantly expanded genus in SLE, followed by metagenomics accurately located Escherichia coli and Escherichia unclassified species. Significant associations primarily appeared among Escherichia coli, metabolic pathways of purine nucleotide salvage or peptidoglycan maturation and SLE disease activity index (SLEDAI), and between multiple epitopes from Escherichia coli and disease activity or renal involvement phenotype. Finally, gavage with faecal Escherichia revealed that it upregulated lupus-associated serum traits and aggravated glomerular lesions in MRL/lpr mice.ConclusionWe characterize a novel SLE exacerbating Escherichia outgrowth and suggest its contribution to SLE procession may be partially associated with metabolite changes and cross-reactivity of gut microbiota-associated epitopes and host autoantigens. The findings could provide a deeper insight into gut Escherichia in the procession of SLE.

First Report of Fusarium compactum Causing Fusarium Head Blight of Wheat in China.

Fusarium head blight (FHB), a devastating wheat disease caused by several species of Fusarium, threatens global wheat yield and quality (Erenstein et al. 2022). In August 2023, wheat spikes exhibiting clear FHB symptoms were observed in fields in Yunnan, China (24°16'46″ N, 102°29'46″ E), with an incidence rate of approximately 10%. Diseased wheat spikes exhibited a bleached, wilted appearance, with abundant orange sporodochia on the glumes, similar to previous reports (Osborne et al. 2007). Twenty-four symptomatic spikes were collected from a single field, and sporodochia were washed with sterile water to prepare a spore suspension of 1 × 10³ spores/ml, which was inoculated onto potato dextrose agar (PDA) to obtain monosporic cultures. Four reference strains (KUNCC 3418 to KUNCC 3420, and KUNCC 3431) were deposited at the Kunming Institute of Botany Culture Collection, Chinese Academy of Sciences (KUNCC). For species identification, four strains were cultured on PDA and carnation leaf agar (CLA) at 25°C, with incubation under a 12-hour near-UV light/dark cycle on CLA and in complete darkness for 24 hours on PDA. Colonies on PDA grew rapidly, appearing white and loosely flocculent. Abundant pale orange, translucent sporodochia formed on CLA. Sporodochial conidiogenous cells were monophialidic or polyphialidic, subulate to subcylindrical, 9.5-12 μm × 3-3.5 μm. Sporodochial macroconidia were naviculate to fusiform, with an elongate, tapering apical cell and a foot-shaped basal cell, 3-6-septate, 33-67.5 μm × 3.5-5.5 μm. The ITS, tef1-α, rpb1, rpb2, and cam regions were amplified and sequenced using primers ITS1/ITS4, EF-1/EF-2, rpb1-F7/G2R, rpb2-5F2/11aR, and CL1/CL2A, respectively (White et al. 1990; O'Donnell et al. 2000; O'Donnell et al. 2010; Reeb et al. 2004; O'Donnell et al. 1998). These sequences were deposited in GenBank for cam (PP951603 to PP951606), ITS (PP946846 to PP946849), tef-1α (PP719217, PP731572 to PP731574), rpb1 (PP719219, PP737839 to PP737841), and rpb2 (PP719218, PP951607 to PP951609). BLASTn analyses of these sequences showed an identity range of 99.7% to 100% with the epitype strain NRRL 36323 of F. compactum (GenBank: cam = GQ505560, ITS = MH855177, tef-1α = GQ505648, and rpb2 = GQ505826), with base pair matches of 663/665 bp for cam, 488/488 bp for ITS, 641/641 bp for tef-1α, and 892/892 bp for rpb2. Both morphological and BLASTn analyses confirmed these isolates as F. compactum (Leslie & Summerell 2006; Han et al. 2023). Pathogenicity tests were performed by spraying 1 ml of spore suspension (1 × 108 spores/ml) of F. compactum strains onto spikes of the wheat cultivar Yunmai 126 at the flowering stage (n = 9). Controls (n = 9) were treated only with sterile water. Following treatment, the wheat spikes were covered with plastic bags and incubated at 25°C for 10 days. After 14 days, the inoculated spikes turned bleached and dry, showing FHB symptoms, while the wheat spikes in the control treatment remained asymptomatic. The pathogenic fungus re-isolated from all diseased samples was confirmed as F. compactum. It has been frequently reported in association with crown and root rot of wheat, particularly in regions such as Turkey and Iran (Tunali et al. 2008; Besharati et al. 2017). To our knowledge, this is the first report of F. compactum on diseased wheat spikes in China. This finding provides valuable insights into the spread of F. compactum.

Enhancing mosquito classification through self-supervised learning

Traditional mosquito identification methods, relied on microscopic observation and morphological characteristics, often require significant expertise and experience, which can limit their effectiveness. This study introduces a self-supervised learning-based image classification model using the Bootstrap Your Own Latent (BYOL) algorithm, designed to enhance mosquito species identification efficiently. The BYOL algorithm offers a key advantage by eliminating the need for labeled data during pretraining, as it autonomously learns important features. During fine-tuning, the model requires only a small fraction of labeled data to achieve accurate results. Our approach demonstrates impressive performance, achieving over 96.77% accuracy in mosquito image analysis, with minimized both false positives and false negatives. Additionally, the model’s overall accuracy, measured by the area under the ROC curve, surpasses 99.55%, highlighting its robustness and reliability. A notable finding is that fine-tuning with just 10% of labeled data produces results comparable to using the full dataset. This is particularly valuable for resource-limited settings with limited access to advanced equipment and expertise. Our model provides a practical solution for mosquito identification, overcoming the challenges of traditional microscopic methods, such as the time-consuming process and reliance on specialized knowledge in healthcare services. Overall, this model supports personnel in resource-constrained environments by facilitating mosquito vector density analysis and paving the way for future mosquito species identification methodologies.