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Flight delays pose substantial operational and economic challenges for airlines, directly affecting scheduling efficiency, resource allocation, and passenger satisfaction. Accurate prediction of arrival delays is therefore critical for optimizing airline operations and enhancing customer experience. This study systematically evaluates the predictive performance of six machine learning classifiers-Decision Tree, Random Forest, Support Vector Classifier (SVC), Logistic Regression, K-Nearest Neighbors (KNN), and Naive Bayes-on a comprehensive flight dataset, with particular attention to the challenges posed by class imbalance. To mitigate skewed class distributions, resampling techniques including Random Oversampling, Synthetic Minority Oversampling Technique (SMOTE), and Adaptive Synthetic Sampling (ADASYN) were applied to the training data. Model performance was rigorously assessed using stratified 10-fold cross-validation and further validated on a hold-out test set, employing multiple evaluation metrics: Accuracy, F1-score, Matthews Correlation Coefficient (MCC), and ROC-AUC. The results demonstrate that Random Forest combined with Random Oversampling and Decision Tree combined with SMOTE both achieved the highest predictive performance (accuracy 0.90, F1-score 0.90, MCC 0.73, ROC-AUC 0.87. Notably, simpler models such as Naive Bayes exhibited competitive results under balanced conditions, underscoring the continued relevance of probabilistic classifiers in certain operational contexts. These findings highlight the critical role of resampling strategies and rigorous cross-validation in developing reliable, high-performing predictive models for imbalanced flight delay datasets, offering actionable insights for both airline operations and data-driven decision-making.

Fungal primary pathogenicity on vertebrates is here described as a deliberate strategy where the host plays a role in increasing the species’ fitness. Opportunism is defined as the coincidental survival of an individual strain in host tissue using properties that are designed for life in an entirely different habitat. In that case, the host's infection control is largely based on innate immunity, and the etiologic agent is not transmitted after infection, and thus fungal evolution is not possible. Primary pathogens encompass two types, depending on their mode of transmission. Environmental pathogens have a double life cycle, and tend to become enzootic, adapted to a preferred host in a particular habitat. In contrast, pathogens that have a host-to-host transmission pattern are prone to shift to a neighboring, immunologically naive host, potentially leading to epidemics. Beyond these prototypical life cycles, some environmental fungi are able to make large leaps between dissimilar hosts/habitats, probably due to the similarity of key factors enabling survival in an entirely different niche, and thus allowing a change from opportunistic to primary pathogenicity. Mostly, such factors seem to be associated with extremotolerance. The authors conclude that for a primary pathogenic species, the infection is strategic, while ecological strategies of opportunistic pathogens do not include vertebrates, and the infection is detrimental even if the infecting fungus survives.

Fungal diseases are associated with high morbidity and mortality, yet their epidemiology and burden are not well addressed. While deaths probably exceed 1.5 million per year, many cases remain undiagnosed and underreported. Estimating the burden of these diseases is needed for prioritization and implementation of effective control programs. Here we used a model based on population at risk to estimate the burden of serious fungal infections in Sudan. The prevalence of the susceptible population including HIV, TB, cancer, asthma, and COPD was obtained from the literature. Incidence and prevalence of fungal infections were calculated using local data when applicable and if not available then regional or international figures were used. In total, the estimated number of Sudanese suffering from fungal disease is 5 M (10% of the total population). Tinea capitis, recurrent vulvovaginitis and keratitis are estimated to affect 4,127,760, 631,261, and 6,552 patients, respectively. HIV-related mycosis is estimated to affect 5,945 oral candidiasis, 1,921 esophageal candidiasis, 571 Pneumocystis pneumonia, and 462 cryptococcal meningitis cases. Aspergillus infections are estimated as follow: 3,438 invasive aspergillosis, 14,950 chronic pulmonary aspergillosis, 67,860 allergic bronchopulmonary aspergillosis cases, while the prevalence of severe asthma with fungal sensitization and fungal rhinosinusitis was 86,860 and 93,600 cases, respectively. The neglected tropical disease eumycetoma was estimated to affect 16,837 cases with a rate of 36/100,000. Serious fungal infections are quite common in Sudan and require urgent attention to improve diagnosis, promote treatment, and develop surveillance programs.

The genus Madurella comprising four species, M. fahalii, M. mycetomatis, M. pseudomycetomatis, and M. tropicana, represents the prevalent cause of eumycetoma worldwide. The four species are phenotypically similar and cause an invariable clinical picture, but differ markedly in their susceptibility to antifungal drugs, and epidemiological pattern. Therefore, specific identification is required for optimal management of Madurella infection and to reveal proper epidemiology of the species. In this study, a novel multiplex real-time PCR targeting the four Madurella species was developed and standardized. Evaluation of the assay using reference strains of the target and non-target species resulted in 100% specificity, high analytical reproducibility (R2 values >0.99) and a lowest detection limit of 3 pg target DNA. The accuracy of the real-time PCR was further assessed using biopsies from eumycetoma suspected patients. Unlike culture and DNA sequencing as gold standard diagnostic methods, the real-time PCR yielded accurate diagnosis with specific identification of the causative species in three hours compared to one or two weeks required for culture. The novel method reduces turnaround time as well as labor intensity and high costs associated with current reference methods.

Eumycetoma (mycotic mycetoma) is the fungal form of mycetoma, a subcutaneous infection occurring in individuals living in endemic areas of the disease. The Sudan is hyperendemic for mycetoma, with the highest incidence being reported from Gezira State, Central Sudan. The present study was conducted at the Gezira Mycetoma Center and aimed to determine the cause of black-grain eumycetoma in the state and describe its epidemiology. Black-grain specimens were collected during the surgical operation and direct detection of the causative agent was performed using M. mycetomatis species-specific PCR and ITS PCR followed by sequencing. Black-grain was reported from 93.3% of all confirmed mycetoma cases (n = 111/119), with a prevalence in young males. Of the 91 samples subjected to direct PCR, 90.1% (n = 82) gave positive results. The predominant species (88.2%) was Madurella mycetomatis. One sample was identified as M. fahalii, one as M. tropicana, and one matched the phytopathogenic species Sphaerulina rhododendricola. The highest endemic zones were Southern Gezira (76.6%) and Northern Sinnar (23.4%). The study confirmed that direct molecular detection on grains provides rapid and specific diagnosis of agents of eumycetoma.

Mucormycosis is a devastating disease with high morbidity and mortality in susceptible patients. Accurate diagnosis is required for timely clinical management since antifungal susceptibility differs between species. Irregular hyphal elements are usually taken as the hallmark of mucormycosis, but here, we show that some species may also produce yeast-like cells, potentially being mistaken for Candida or Paracoccidioides . We demonstrate that the dimorphic transition is common in Mucor species and can be driven by many factors. The multi-nucleate yeast-like cells provide an effective parameter to distinguish mucoralean infections from similar yeast-like species in clinical samples.

Accurate identification of mycetoma causative agent is a priority for treatment. However, current identification tools are far from being satisfactory for both reliable diagnosis and epidemiological investigations. A rapid, simple, and highly efficient molecular based method for identification of agents of black grain eumycetoma is introduced, aiming to improve diagnostic in endemic areas. Rolling Circle Amplification (RCA) uses species-specific padlock probes and isothermal DNA amplification. The tests were based on ITS sequences and developed for Falciformispora senegalensis, F. tompkinsii, Madurella fahalii, M. mycetomatis, M. pseudomycetomatis, M. tropicana, Medicopsis romeroi, and Trematosphaeria grisea. With the isothermal RCA assay, 62 isolates were successfully identified with 100% specificity and no cross reactivity or false results. The main advantage of this technique is the low-cost, high specificity, and simplicity. In addition, it is highly reproducible and can be performed within a single day.

The Microsporum canis complex consists of one zoophilic species, M. canis , and two anthropophilic species, M. audouinii and M. ferrugineum . These species are the most widespread zoonotic pathogens causing dermatophytosis in cats and humans worldwide. To clarify the evolutionary relationship between the three species and explore the potential host shift process, this study used phylogenetic analysis, population structure analysis, multispecies coalescent analyses, determination of MAT idiomorph distribution, sexual crosses, and macromorphology and physicochemical features to address the above questions. The complex of Microsporum canis , M. audouinii and M. ferrugineum comprises 12 genotypes. MAT1-1 was present only in M. canis , while the anthropophilic entities contained MAT1-2 . The pseudocleistothecia were yielded by the mating behaviour of M. canis and M. audouinii . Growth rates and lipase, keratinolysis and urea hydrolytic capacities of zoophilic M. canis isolates were all higher than those of anthropophilic strains; DNase activity of M. ferrugineum exceeded that of M. canis . The optimum growth temperature was 28 °C, but 22 °C favoured the development of macroconidia. Molecular data, physicochemical properties and phenotypes suggest the adaptation of zoophilic M. canis to anthropophilic M. ferrugineum, with M. audouinii in an intermediate position.

The family Epibryaceae is one of the early-diverging lineages within the order Chaetothyriales . Available molecular data show that most species are associated with mosses, liverworts, and lichens, typically inhabiting apparently psychrophilic environments. However, genomic information about this family remains scarce. This study presents whole-genome sequencing of six reference strains from the genus Epibryon ( Chaetothyriales , Epibryaceae ), aiming to elucidate their ecological adaptations and evolutionary relationships. Comparative analyses of CAZymes and MEROPS annotations showed that most members of Epibryaceae have a reduced set of enzymes associated with lignin degradation. Additionally, the presence of the CspA protein, linked to freezing tolerance, and the absence of the ClpA/B enzyme, associated with heat stress tolerance, suggest a strong preference for cold environments compared with other Chaetothyriales lineages. Multilocus phylogenetic analyses clarified species boundaries and resulted in the introduction of Epibryon brunneolum comb. nov. within the family. Based on phylogenetic analysis, ecological data regarding the preferred habitat of the family, and the presence of exclusive enzymes associated with extreme cold environments, the results indicate that this family is distinct from other chaetothyrialean fungi.

Cryptococcal meningitis is a high-mortality infection. Adding 5-fluorocytosine (5-FC) to its treatment improves outcomes, but resistance to 5-FC presents a significant challenge. We conducted whole-genome sequencing on seven C. neoformans isolates with varying 5-FC susceptibility, along with proteomic and in silico analyses. Our findings indicate that mutations in genes of the pyrimidine salvage pathway are responsible for 5-FC resistance. Specifically, we identified an E64G missense mutation in the FUR1 gene, a large deletion in the FCY1 gene, and a point mutation in FCY1 leading to a truncated protein. The proteomic data indicated that these mutations resulted in the absence or reduction of crucial enzymes in resistant isolates. Genetic transformations confirmed the association between these mutations and 5-FC resistance. Resistance to 5-FC can develop during treatment and is closely tied to mutations in key metabolic enzymes. Understanding in vivo resistance development is crucial for combating resistance and enhancing patient outcomes.