Search Results (1,701)

Fungi and bacteria associated with bark beetles can facilitate successful tree colonization, and, in some cases, these fungi act as pathogens of trees. The red turpentine beetle (RTB, Dendroctonus valens) is a bark beetle native to North America that colonizes stressed pines, rarely killing healthy trees. The fungal communities associated with RTB adults, larval galleries, and control tree phloem from red pine (Pinus resinosa) and white pine (P. strobus) forests in the Great Lakes region of the United States were characterized using both culture-independent and culture-dependent methods. Similarly, the bacterial communities associated with RTB adults in the same region were characterized using a culture-independent method. There were significant differences between the adult beetle fungal communities and the tree-based fungal communities. Culture-independent sequencing of RTB adults showed high abundances of the fungal order Filobasidiales (red pine: 28.71% relative abundance, white pine: 6.91% relative abundance), as well as the bacterial orders Enterobacterales (red pine: 53.72%, white pine: 22.15%) and Pseudomonadales (red pine: 15.86%, white pine: 12.91%). In contrast, we isolated high amounts of fungi in the orders Pleosporales (red pine: 21.79%, white pine: 15.90%) and Eurotiales (red pine: 15.38%, white pine: 16.51%) from the adult beetles by culturing. Culture-independent sequencing of beetle galleries yielded high abundances of fungi in the orders Helotiales (red pine: 22.23%, white pine: 23.21%), whereas culture-based isolation from the same galleries yielded high amounts of Eurotiales (red pine: 17.91%, white pine: 17.91%), Hypocreales (red pine: 16.42%, white pine: 16.42%), and Ophiostomatales (red pine: 23.39%, white pine: 23.39%). This contrasts with the culture-independent method, where, likely due to limitations in the sequencing method, the Ophiostomatales accounted for only around 2% of the fungi from RTB galleries in both pine species. We observed a high species-level diversity of Ophiostomatales associated with RTB, isolating 14 species from the Great Lakes region. Leptographium terebrantis, a species that has been described in association with RTB throughout the United States, was the most common species (e.g., >35% of the Ophiostomatales relative abundance in red pine environments and >14% of the Ophiostomatales relative abundance in the white pine environment). This study enhances our understanding of RTB-associated fungi and bacteria in the beetle’s native range at both the community and species levels. Full article

Parasitic infections remain a major global health challenge, particularly in resource-limited settings where they are closely tied to poverty and inadequate sanitation. The increasing emergence of drug resistance and the limited accessibility of current therapies highlight the urgent need for novel, safe, and affordable alternatives. Mangifera indica L. (mango), a widely cultivated fruit tree deeply rooted in traditional medicine, has long been used to treat conditions symptomatic of parasitic diseases, including fever, diarrhea, and dysentery. Phytochemical investigations have revealed a rich spectrum of bioactive compounds, notably mangiferin, phenolic compounds and terpenoids, which exhibit antimicrobial, antioxidant, and immunomodulatory activities. This review critically synthesizes evidence on the antiparasitic potential of M. indica against protozoa, such as Plasmodium, Leishmania, Trypanosoma, Toxoplasma gondii, Entamoeba histolytica, and free-living amoebae, as well as helminths. Strongest evidence exists for malaria and helminth infections, where both crude extracts and isolated compounds demonstrated significant activity in vitro and in vivo. Encouraging but limited findings are available for leishmaniasis and trypanosomiasis, while data on toxoplasmosis and amoebiasis remain largely speculative. Variations in efficacy across studies are influenced by plant parts and extraction methods, with ethanolic extracts and mangiferin often showing superior results. Despite promising findings, mechanistic studies, standardized methodologies, toxicological evaluations, and clinical trials are scarce. Future research should focus on elucidating molecular mechanisms, exploring synergistic interactions with existing drugs, and leveraging advanced delivery systems to enhance bioavailability. Full article

Black spot is currently one of the most widespread diseases affecting Yanbian Pingguoli pears (Pyrus pyrifolia cv. ‘Pingguoli’), resulting in significant economic losses for fruit farmers. It is mainly caused by infestation by the fungal group of Alternaria species. To date, no research has reported the presence of Alternaria species and the pathogen of black spot disease on Yanbian Pingguoli pears in China. This study isolated, identified, and performed molecular profiling of 124 Alternaria strains collected from 15 major growing areas of Yanbian Pingguoli pear (more than 5000 trees). Moreover, the study evaluated the ability of Artemisia capillaris essential oil (AcEO) to suppress the mycelial expansion of Alternaria pathogens and conducted comprehensive chemical profiling. Overall, 124 pathogenic fungi were identified as Alternaria tenuissima (67 isolates, 54.0%) and A. alternate (57 isolates, 46.0%). AcEO showed a strong inhibitory effect on the two Alternaria species, with a minimal inhibitory concentration (MIC) value equivalent to 5.0 μL/mL. Eucalyptol, 2,2-Dimethyl-3-methylenebicyclo [2.2.1] heptane, (-)-alcanfor, and β-copaene were identified as the predominant bioactive components of AcEO. AcEO demonstrated concentration-dependent inhibition of the mycelial growth of A. tenuissima and A. alternata. These findings position AcEO as a promising candidate for developing sustainable fungicides to combat Alternaria-induced crop losses. Full article

Urinary tract infections (UTIs) are among the most common pathologies, with a high incidence in women and hospitalized patients. Their diagnosis is based on the presence of clinical symptoms and signs in addition to the detection of microorganisms in urine trough urine cultures, a time-consuming and resource-intensive test. The goal was to optimize UTI detection through artificial intelligence (machine learning) using non-microbiological laboratory parameters, thereby reducing unnecessary cultures and expediting diagnosis. A total of 4283 urine cultures from patients with suspected UTIs were analyzed in the Microbiology Laboratory of the University Hospital Virgen de las Nieves (Granada, Spain) between 2016 and 2020. Various machine learning algorithms were applied to predict positive urine cultures and the type of isolated microorganism. Random Forest demonstrated the best performance, achieving an accuracy (percentage of correct positive and negative classifications) of 82.2% and an area under the ROC curve of 87.1%. Moreover, the Tree algorithm successfully predicted the presence of Gram-negative bacilli in urine cultures with an accuracy of 79.0%. Among the most relevant predictive variables were the presence of leukocytes and nitrites in the urine dipstick test, along with elevated white cells count, monocyte count, lymphocyte percentage in blood and creatinine levels. The integration of AI algorithms and non-microbiological parameters within the diagnostic and management pathways of UTI holds considerable promise. However, further validation with clinical data is required for integration into hospital practice. Full article

Glioblastoma multiforme (GBM) is an aggressive brain tumor with limited treatment options and a poor prognosis. Natural phytochemicals from Dendrobium species, particularly bibenzyl derivatives, possess diverse pharmacological activities, yet their potential against GBM remains largely unexplored. Here, we investigated the anticancer activity of 4,5,4′-trihydroxy-3,3′-dimethoxybibenzyl (TDB), a potent antioxidant bibenzyl derivative isolated from Dendrobium pachyglossum. In U87MG cells, TDB reduced viability in a dose- and time-dependent manner, suppressed clonogenic growth, induced apoptosis via Bax upregulation and Bcl-xL/Mcl-1 downregulation, and inhibited both mTORC1 and mTORC2 signaling. TDB also impaired cell migration and downregulated epithelial–mesenchymal transition (EMT)-associated proteins. Notably, TDB enhanced the cytotoxicity of temozolomide (TMZ), the current standard of care for GBM. These TMZ-sensitizing properties were further confirmed in patient-derived xenograft (PDX) Jx22 cells. To assess its potential for central nervous system delivery, blood–brain barrier (BBB) permeability was predicted using four independent in silico platforms—ADMETlab 3.0, LogBB_Pred, LightBBB, and BBB Predictor (Tree2C)—all of which consistently classified TDB as BBB-permeable. This predicted CNS accessibility, together with its potent anticancer profile, underscores TDB’s translational promise. Collectively, our findings identify TDB as a plant-derived antioxidant with multifaceted anti-GBM activity and favorable BBB penetration potential, warranting further in vivo validation and preclinical development as a novel therapeutic candidate for GBM. Full article

The whitefly (Bemisia tabaci) (Hemiptera: Aleyrodidae) is a small phytophagous invertebrate of herbaceous plants, shrubs, trees, wild plants, and crops of economic importance. It generates substantial economic losses due to direct damage caused by sap sucking and virus transmission. This work presents referential images of the morphology of B. tabaci and one of its main biological controllers in southern South America, thus serving as a reference for other researchers. In addition, results are presented of studies carried out to evaluate the pathogenicity of two fungal isolates (previously selected in vitro against Sclerotinia sclerotiorum and Botrytis cinerea and plant growth promoters) identified as Metarhizium taii CEP-722 and Trichoderma afroharzianum CEP-754 in immature stages of B. tabaci in tomato plants (Solanum lycopersicum). The trials were conducted under controlled conditions in controlled chambers, ensuring optimal growth conditions for B. tabaci, after morphological prospection, collection, identification, and mass rearing of adults in entomological cages. The results indicate that M. taii CEP-722 caused approximately 30% mortality in the immature stages of B. tabaci, while T. afroharzianum CEP-754 did not increase mortality under the experimental conditions. This study provides new knowledge on the potential of M. taii as a biological control agent against B. tabaci, offering a promising alternative in integrated pest management strategies. The results with T. afroharzianum suggest that further methodologies or combinations should be explored to improve its efficacy. Full article

Diaphorobacter nitroreducens is a Gram-negative bacterium ubiquitously found in wastewater, recognized for its ecological adaptability and potential applications in environmental, biomedical, and industrial processes. Central to its adaptability is the nfrB gene, which encodes a cyclic di-3′,5′-guanylate (c-di-GMP)-activated glycosyltransferase. This enzyme facilitates the secretion of biofilm-associated extracellular polymeric substances (EPS), essential for its survival and functionality in diverse environments. Using complete EMJH media as a selective medium, D. nitroreducens was successfully isolated from soil and water samples from Estero de Paco, Manila, Philippines, enabling downstream analyses of its nfrB gene. Phylogenetic analyses revealed that the nfrB gene tree deviates significantly from the canonical 16S rRNA gene tree, with D. nitroreducens clustering alongside members of the Enterobacteriaceae family. This deviation suggests the potential influence of horizontal gene transfer, adaptive evolution, or lineage-specific pressures on nfrB evolution. Structural analysis of NfrB through Alphafold 3 prediction demonstrated a conserved N-terminal region across taxa, except for the outgroup Zymomonas mobilis. Conversely, the C-terminal region, housing the catalytic domain, showed considerable diversity, reflecting adaptive modifications across bacterial lineages. Despite this variability, the putative binding site for cyclic di-3′,5′-guanylate remained conserved, indicating a balance between functional conservation and adaptive diversification. These findings not only deepen the existing understanding of bacterial signaling and glycosylation mechanisms but also provide insights into the evolutionary dynamics of glycosyltransferases. Furthermore, the study underscores the potential of NfrB as a target for innovative applications, including the design of novel biocatalysts and the development of informed strategies for bacterial management in environmental, industrial, and biotechnological contexts. Full article

Mining novel Streptomyces species from extreme environments provides a valuable strategy for the discovery of new antibiotics. Here, we report a strain of Streptomyces sp. HMX87^T, which exhibits antimicrobial activity and was isolated from desert soil collected in the Tuha Basin, China. Molecular taxonomic analysis revealed that the 16S rRNA gene sequence of strain HMX87^T shares the highest similarity with those of Streptomyces bellus CGMCC 4.1376^T (98.5%) and Streptomyces coerulescens DSM 40146^T (98.43%). In phylogenetic trees, it formed a distinct branch. The average nucleotide identity (ANI) and digital DNA–DNA hybridization (dDDH) values between strain HMX87^T and the above two type strains were below the thresholds of 95% and 70%, respectively, confirming that strain HMX87^T represents a novel species within the genus Streptomyces, for which the name Streptomyces hamibioticus sp. nov. is proposed. Physiologically, the strain HMX87^T grew at temperatures ranging from 25 to 37 °C, tolerated pH values from 5 to 12, and survived in NaCl concentrations of 0% to 8% (w/v). Chemotaxonomic characterization indicated the presence of LL-diaminopimelic acid (LL-DAP) in the cell wall, ribose and galactose as whole-cell hydrolysate sugars, MK-9(H8) (66.3%) as the predominant menaquinone, and iso-C_16:0 (25.94%) and anteiso-C_15:0 (16.98%) as the major fatty acids characteristics that clearly distinguish it from its closest relatives. Whole-genome sequencing of strain HMX87^T revealed an abundance of genes associated with high-temperature tolerance, salt-alkali resistance, and antimicrobial activity. The genomic features and secondary metabolic potential reflect its adaptation to extreme environmental conditions, including high temperature, salinity, alkalinity, strong ultraviolet radiation, and oligotrophic nutrients. The strain HMX87^T has been deposited in the Czech Collection of Microorganisms (CCM 9454^T) and the Guangdong Microbial Culture Collection Center (GDMCC 4.391^T). The 16S rRNA gene and whole-genome sequences have been submitted to GenBank under accession numbers PQ182592 and PRJNA1206124, respectively. Full article

Pythium-like organism species are widespread soilborne oomycetes known to cause root diseases in a wide range of plant hosts. However, their involvement in the decline of woody species in historical and urban gardens has received limited attention. This study reports the isolation and identification of a Pythium-like organism from declining Quercus ilex specimens in a historical garden, where affected trees showed symptoms of root rot and sucker dieback. Integration of morphological observations and molecular analyses of ITS, LSU, and Cox II sequences confirmed the identity of the isolates as Globisporangium glomeratum (formerly Pythium glomeratum). Pathogenicity tests confirmed the aggressiveness of these isolates on Q. ilex seedlings, resulting in significant reductions in plant height and shoot and root biomass. The detection of G. glomeratum in the soil of a historical garden underscores the risk of its unintentional dissemination through nursery stock or soil movement, particularly in urban settings where plant replacement is frequent. This is the first report of G. glomeratum as a pathogen of Q. ilex, emphasizing the importance of phytosanitary monitoring in culturally and ecologically valuable green spaces. Full article

Camphora officinarum Nees constitutes a pivotal tree species within the evergreen broad-leaved forests of East Asia, endowed with significant economic, ornamental, and ecological importance. Nevertheless, previous research has markedly underestimated the genetic diversity of this species, thereby hindering our efforts in conserving resources and enhancing genetic breeding. The current study generated 155 chloroplast genomes from specimens of C. officinarum obtained from six provinces/regions in China. The results reveal the identification of seven distinct clades (I–VII), with Clades II, III, V, and VII exhibiting genome expansions, primarily influenced by lineage-specific elongation of inverted repeats (IRs), whereas Clades I, IV, and VI maintained conserved IR lengths. Despite the structural plasticity, the GC content remained highly conserved. Geographic patterns indicated gene flow between adjacent regions (e.g., Hunan and Hubei with identical IR lengths), but genetic isolation in Fujian. High-polymorphism regions (psba-matK, ycf1, ycf2, and ndhF) were identified as superior phylogenetic markers, enhancing intraspecies-level resolution. Simple sequence repeats (SSRs) varied significantly among clades, dominated by A/T-rich mononucleotide repeats. These repeats, along with divergent repeat types (e.g., absence of reverse repeats in Clades V/VI), serve as robust tools for resource identification and evolutionary trajectory inference. Phylogenetically, samples from Fujian formed a distinct lineage, while samples from other regions, especially Guangdong, were mixed, with this finding probably being a reflection of historical cultivation and anthropogenic translocation. This study offers a framework for the genetic breeding and investigation of the evolutionary history of C. officinarum. Full article

Species of Trichoderma are currently in high demand as eco-friendly and commercial biocontrol agents due to the proliferation of organic farming methods. This study focused on the potential biocontrol agents of Trichoderma against plant-pathogenic fungi. Trichoderma strains were isolated from different sources (soil, grapevine tissues, lemon fruit, and maize seeds), and were characterized morphologically on two culture media, i.e., Potato Dextrose Agar and Malt Extract Agar, and molecularly using two gene regions: translation elongation factor 1 (TEF) and nuclear ribosomal internal transcribed spacer (ITS). Phylogenetic trees were constructed. As a result, two Trichoderma species were identified, i.e., T. afroharzianum and T. longibrachiatum. The biocontrol effects of all isolated strains of Trichoderma on Fusarium plant damping-off and the promotion of plant growth were evaluated. Additionally, the antagonistic efficiency of Trichoderma spp. against F. proliferatum using the dual-culture method was evaluated. Under greenhouse conditions, T. afroharzianum strains AEMCTa3 and AEMCTa6 were used to treat maize plants infected with Fusarium. The application of Trichoderma significantly reduced the disease index to 15.6% and 0%, respectively. Additionally, maize seedlings showed significant improvements in shoot and root lengths and fresh and dry weights and increased photosynthetic pigment contents compared to Fusarium-infected plants and the untreated control. The gas chromatography–mass spectrometry (GC-MS) analysis of T. afroharzianum extracts identified a variety of bioactive compounds. These compounds included antifungal substances like N-ethyl-1,3-dithioisoindoline, as well as plant growth-promoting hormones like 6-pentyl-α-pyrone and gibberellic acid. Interestingly, the analysis also revealed new phenylacetic acid derivatives that may play important roles in both plant health and disease resistance. From a practical perspective, developing diverse application methods for Trichoderma is essential to optimize its role as a biocontrol agent and a plant growth promoter, thereby supporting sustainable agriculture through improved adaptability and effectiveness across different farming systems. Full article

Laboratory buildings represent some of the highest energy-consuming infrastructure due to stringent environmental requirements and the continuous operation of specialized equipment. Ensuring both energy efficiency and indoor air quality (IAQ) in such spaces remains a central challenge for sustainable building design and operation. Recent advances in Internet of Things (IoT) systems allow for real-time monitoring of multivariate environmental parameters, including CO₂, total volatile organic compounds (TVOC), PM_2.5, temperature, humidity, and noise. However, these datasets are often noisy or incomplete, complicating conventional monitoring approaches. Supervised anomaly detection methods are ill-suited to such contexts due to the lack of labeled data. In contrast, unsupervised machine learning (ML) techniques can autonomously detect patterns and deviations without annotations, offering a scalable alternative. The challenge of identifying anomalous environmental conditions and latent operational states in laboratory environments is addressed through the application of unsupervised models to 1808 hourly observations collected over four months. Anomaly detection was conducted using Isolation Forest (300 trees, contamination = 0.05) and One-Class Support Vector Machine (One-Class SVM) (RBF kernel, ν = 0.05, γ auto-scaled). Standardized six-dimensional feature vectors captured key environmental and energy-related variables. K-means clustering (k = 3) revealed three persistent operational states: Empty/Cool (42.6%), Experiment (37.6%), and Crowded (19.8%). Detected anomalies included CO₂ surges above 1800 ppm, TVOC concentrations exceeding 4000 ppb, and compound deviations in noise and temperature. The models demonstrated sensitivity to both abrupt and structural anomalies. Latent states were shown to correspond with occupancy patterns, experimental activities, and inactive system operation, offering interpretable environmental profiles. The methodology supports integration into adaptive heating, ventilation, and air conditioning (HVAC) frameworks, enabling real-time, label-free environmental management. Findings contribute to intelligent infrastructure development, particularly in resource-constrained laboratories, and advance progress toward sustainability targets in energy, health, and automation. Full article

Fault identification in Printed Circuit Board Assembly (PCBA) testing is essential for assuring product quality; nevertheless, conventional methods still have difficulties due to the lack of labeled faulty data and the “black box” nature of advanced models. This study introduces a label-free, interpretable self-supervised framework that uses two pretext tasks: (i) an autoencoder (reconstruction error and two latent features) and (ii) isolation forest (faulty score) to form a four-dimensional representation of each test sequence. A two-component Gaussian Mixture Model is used, and the samples are clustered into normal and fault groups. The decision is explained with cluster mean differences, SHAP (LinearSHAP or LinearExplainer on a logistic-regression surrogate), and a shallow decision tree that generated if–then rules. On real PCBA data, internal indices showed compact and well-separated clusters (Silhouette 0.85, Calinski–Harabasz 50,344.19, Davies–Bouldin 0.39), external metrics were high (ARI 0.72; NMI 0.59; Fowlkes–Mallows 0.98), and the clustered result used as a fault predictor reached 0.98 accuracy, 0.98 precision, and 0.99 recall. Explanations show that the IForest score and reconstruction error drive most decisions, causing simple thresholds that can guide inspection. An ablation without the self-supervised tasks results in degraded clustering quality. The proposed approach offers accurate, label-free fault prediction with transparent reasoning and is suitable for deployment in industrial test lines. Full article

Fig (Ficus carica) orchards in the Salento peninsula (southeastern Apulia region, Italy) are increasingly affected by decline syndromes whose etiology remains poorly resolved. In this paper, we provide a first characterization of a complex disease outbreak, integrating field surveys, fungal isolation, molecular phylogenetics, and pathogenicity assays. Symptomatic trees displayed chlorosis, defoliation, cankers, vascular discoloration, and wilting, frequently associated with bark beetle galleries. Mycological analyses revealed a diverse assemblage of fungi, dominated by Botryosphaeriaceae (including Neofusicoccum algeriense, and Lasiodiplodia theobromae), the Fusarium solani species complex (notably Neocosmospora perseae), and Ceratocystis ficicola. While C. ficicola was isolated with lower frequency, its recovery from adult beetles—including Cryphalus dilutus—supports a role in insect-mediated dissemination in addition to soilborne infection. Pathogenicity tests demonstrated that N. algeriense and N. perseae, together with C. ficicola, caused severe vascular lesions and wilting, confirming their contribution to fig decline. By contrast, other Fusarioid strains showed no pathogenicity, consistent with their role as latent or stress-associated pathogens. This study provides the first evidence that N. algeriense and N. perseae act as pathogenic agents on fig, highlights their interaction with C. ficicola within a multifactorial decline syndrome, and identifies dual epidemiological pathways involving both soil/root infection and insect-facilitated dissemination via beetles such as C. dilutus. These findings redefine fig decline in the Salento peninsula (southern Italy) as a multifactorial disease rather than a single-pathogen outbreak, with significant implications for diagnosis, epidemiology, and integrated management strategies. Full article

Copaifera langsdorffii is a neotropical tree widely distributed in the Brazilian Atlantic Forest and Brazilian Savanna. Population genetic analyses can identify the scale at which tree species are impacted by human activities and provide useful demographic information for management and conservation. Using a Restriction site Associated DNA Sequencing approach, we assessed the genomic variability of six C. langsdorffii population relicts in a transition zone between the Seasonal Atlantic Forest and Savanna biomes in Southeastern Brazil. We identified 2797 high-confidence SNP markers from six remnant populations, with 10 to 29 individuals perpopulation, in a transition zone between the Seasonal Atlantic Forest and Savanna biomes in Southeastern Brazil. Observed heterozygosity values (0.197) were lower than expected heterozygosity (0.264) in all populations, indicating an excess of homozygotes. Differentiation among populations (F_ST) was low (0.023), but significant (0.007–0.044, c.i. 95%). A clear correlation was observed between geographic versus genetic distances, suggesting a pattern of isolation by distance. Bayesian inferences of population structure detected partial structuring due to the transition between the Atlantic Forest and the Brazilian Savanna, also suggested by spatial interpolation of ancestry coefficients. Through the analysis of F_ST outliers, 28 candidates for selection have been identified and may be associated with adaptation to these different phytophysiognomies. We conclude that the genetic variation found in these populations can be exploited in programs for the genetic conservation of the species. Full article