Search Results (80)

Nocardia spp. are opportunistic pathogens of humans, domestic animals, and wildlife that can cause high levels of morbidity and mortality. Here, we present a unique case of nocardial airsacculitis in a free-ranging mallard (Anas platyrhynchos) from Arizona, USA, and compare it to the hosts, geographic distribution, diagnostic methodology, and infection site of known nocardiosis cases in birds. A gross necropsy, histopathology, and bacterial culture were performed. There were no gross findings associated with the nocardiosis. Histopathology showed multiple granulomas expanding the air sac with intralesional filamentous bacteria that were Grocott’s methenamine silver-positive, Fite–Faraco and Ziehl–Neelsen acid-fast, positive with the Periodic acid–Schiff reaction, and variably Gram-positive. The organism was isolated in culture and identified as Nocardia cyriacigeorgica based on the sequencing of a 463 bp portion of the 16S rRNA gene. While reports of nocardiosis in the class Aves are rare and some are possibly misdiagnosed due to limited diagnostics, cases are reported globally, sometimes resulting in epizootics. More information is needed to understand whether immunosuppression plays a role in disease development in birds. Known to be an emerging pathogen in humans, N. cyriacigeorgica can be considered as a differential diagnosis for pulmonary and potentially cutaneous or disseminated infections in birds. Full article

Background: Canine pyoderma and otitis externa are prevalent bacterial skin infections in veterinary practice, frequently complicated by the emergence of multidrug-resistant (MDR) pathogens. Objectives: To investigate the frequency, antimicrobial resistance (AMR) profiles, and frequency of MDR bacterial isolates from dogs with pyoderma or otitis externa in Hong Kong. Methods: A retrospective study of bacterial isolates from 215 clinical samples collected from dogs presenting with pyoderma (n = 63) or otitis externa (n = 152) at veterinary clinics across Hong Kong between 2018 and 2022. Bacterial isolates were identified and subjected to antimicrobial susceptibility testing against 13 antimicrobial classes. Results: Staphylococcus spp., particularly S. pseudintermedius, were the most commonly isolated species, followed by Pseudomonas spp. and Proteus spp. High resistance rates were observed for orbifloxacin (61.3% in pyoderma; 76.7% in otitis externa), doxycycline (59.3%; 69.2%), clindamycin (62%; 68.9%), and enrofloxacin (50%; 55.5%). Most isolates were sensitive to ofloxacin, ticarcillin–clavulanate, tobramycin, ciprofloxacin, cefpodoxime, cefuroxime, and cefixime. MDR was detected in 67.5% of pyoderma and 66.8% of otitis externa isolates. Gram-negative bacteria exhibited significantly higher MDR rates than Gram-positive isolates. The multiple antibiotic resistance (MAR) index averaged 0.41 for pyoderma and 0.52 for otitis externa isolates. We found no significant associations between MDR and non-modifiable risk factors (i.e., age, sex, breed, and reproductive status). Conclusions: These findings highlight the critical need for prudent antimicrobial use and continuous surveillance of AMR trends in companion animals. A higher focus should be placed on topical antiseptic therapy, with oral antibiotics used only in exceptional cases and after susceptibility testing. From a One Health perspective, the potential transmission of MDR bacteria between companion animals and humans underscores the importance of a coordinated approach to antimicrobial stewardship across both veterinary and human medicine. Full article

Bovine uterine infections remain a widespread challenge in dairy production systems, contributing to reduced fertility and overall herd performance. Background/Objectives: Postpartum uterine infections significantly affect dairy cattle fertility and productivity. This study aimed to identify aerobic bacterial pathogens associated with clinical endometritis in Romanian dairy cows and evaluate their antimicrobial resistance profiles. Methods: Uterine swab samples (n = 348) were collected from clinically affected cows across multiple farms. Bacteria were isolated and identified using conventional culture methods and MALDI-TOF MS. Antimicrobial susceptibility testing was performed using the VITEK^® 2 system with GN 96 and GP 79 cards. Statistical analysis was conducted using the chi-square (χ²) test. Results: A total of 387 bacterial isolates were recovered, with over half of the samples showing mixed bacterial contamination. Escherichia coli was the most frequently identified pathogen (44.9%), followed by Staphylococcus spp. (17.3%) and Klebsiella spp. (14.5%). Gram-negative isolates showed high resistance to tetracycline and ampicillin, while retaining susceptibility to imipenem and polymyxin B. Among Gram-positive isolates, Streptococcus spp. were highly susceptible to β-lactams, while Staphylococcus spp. showed moderate resistance to penicillin and macrolides. Conclusions: This study highlights the prevalence of key aerobic pathogens and their resistance profiles in Romanian dairy herds. These findings support the need for targeted diagnostics and rational antimicrobial use to improve uterine health and therapeutic outcomes in dairy cattle. Full article

Pseudowords are essential in (psycho)linguistic research, offering a way to study language without meaning interference. Various methods for creating pseudowords exist, but each has its limitations. Traditional approaches modify existing words, risking unintended recognition. Modern algorithmic methods use high-frequency n-grams or syllable deconstruction but often require specialized expertise. Currently, no automatic process for pseudoword generation is designed explicitly for Greek, which is our primary focus. Therefore, we developed SyBig-r-Morph, a novel application that constructs pseudowords using syllables as the main building block, replicating Greek phonotactic patterns. SyBig-r-Morph draws input from word lists and databases that include syllabification, word length, part of speech, and frequency information. It categorizes syllables by position to ensure phonotactic consistency with user-selected morphosyntactic categories and can optionally assign stress to generated words. Additionally, the tool uses multiple lexicons to eliminate phonologically invalid combinations. Its modular architecture allows easy adaptation to other languages. To further evaluate its output, we conducted a manual assessment using a tool that verifies phonotactic well-formedness based on phonological parameters derived from a corpus. Most SyBig-r-Morph words passed the stricter phonotactic criteria, confirming the tool’s sound design and linguistic adequacy. Full article

Aminosteroid derivative RM-581 stands out as an anticancer agent, supported by positive in vitro and in vivo studies on resistant cancers of the breast, prostate, and pancreas. A synthetic route has already been developed to obtain aminosteroid RM-581 in small quantities (scale of milligrams to a few grams). However, this route has significant limitations in view of its transposition to scaling up to larger quantities to support late preclinical and clinical trials. Among the problems are the use of toxic reagents, the moderate overall yield, and the need for multiple purifications through chromatographic columns. The development of a new synthetic route has therefore been explored. Starting from commercially available estrone, 2,4-dibromo-estrone was rapidly formed, followed by the regioselective introduction of a nitro group at the C2 position and by the methylation of phenol at the C3 position. The 4-bromo-2-nitro-3-O-methylestrone was then reduced to 2-amino-3-O-methylestrone and the primary amine was used to form the piperazine ring. Once the cyclization step was carried out, the last two steps were identical to the first synthetic route previously reported, i.e., introducing an ethynyl group at the C-17α position and then adding the quinoline-proline side chain with an N-acylation, assisted by a peptide coupling reagent. Importantly, no purification by chromatography was necessary during the whole sequence of reactions and only a final silica gel filtration, followed by recrystallization, led to RM-581 at a very high level of purity. The structure was also fully characterized by 2D NMR analysis. Full article

In poultry production, antibiotics have been excessively used as growth promoters to support well-being and decrease mortality caused by pathogenic microorganisms. The overuse of antibiotics has led to the emergence of antibiotic-resistant bacteria and the presence of antibiotic residues in poultry products. To counteract this problem, probiotics could be used as adjuncts or as substitutes for preserving a diverse and balanced microflora to prevent the colonization and multiplication of pathogenic bacteria in the GI tract. This study aimed to isolate and characterize the potential probiotic properties of lactic acid bacteria from the small intestine of 23-week-old broiler breeders, with the goal of identifying potential probiotic candidates. Four phenotypically healthy broiler breeders were selected, and intestinal contents were aseptically collected and cultured on MRS agar. From the initial pool of 39 colonies, six isolates were identified based on Gram-positive and catalase-negative characteristics and further classified using 16S rRNA sequencing as Levilactobacillus brevis (n = 3), Pediococcus pentosaceus (n = 2), and Streptococcus salivarius (n = 1). These strains were further evaluated for probiotic properties such as transit resistance to simulated upper gastrointestinal conditions, antagonist activity, haemolytic activity, and cell surface properties such as autoaggregation, co-aggregation and hydrophobicity, in vitro. L. brevis NKFS8 showed good tolerance to pH 3, while P. pentosaceus NKSF10 exhibited good tolerance to pH 4 acidic conditions. All isolates demonstrated good survivability in bile salt concentration of 3% (w/v), with P. pentosaceus NKSF10 exhibiting the highest tolerance. The isolates showed a wide range of antagonistic activity against the test pathogens Pseudomonas aeruginosa (ATCC 27853), Salmonella typhimurium, Salmonella enterica (ATCC 13314), Staphylococcus aureus (ATCC 29213), and Listeria monocytogenes (ATCC 7644). Furthermore, these strains exhibited good auto-aggregation, co-aggregation, and hydrophobicity properties. In conclusion, lactic acid bacteria from the small intestine of broiler breeders present a valuable prospect for the development of effective probiotics. These probiotics can be utilized as a supplementary inclusion in poultry feed, obviating the need for antibiotics as growth promoters. Nevertheless, additional in vivo studies are required to closely monitor and assess the effects of probiotics on the gastrointestinal system of chickens. Full article

During the COVID-19 pandemic, social media platforms emerged as both vital information sources and conduits for the rapid spread of propaganda and misinformation. However, existing studies often rely on single-label classification, lack contextual sensitivity, or use models that struggle to effectively capture nuanced propaganda cues across multiple categories. These limitations hinder the development of robust, generalizable detection systems in dynamic online environments. In this study, we propose a novel deep learning (DL) framework grounded in fine-tuning the RoBERTa model for a multi-label, multi-class (ML-MC) classification task, selecting RoBERTa due to its strong contextual representation capabilities and demonstrated superiority in complex NLP tasks. Our approach is rigorously benchmarked against traditional and neural methods, including, TF-IDF with n-grams, Conditional Random Fields (CRFs), and long short-term memory (LSTM) networks. While LSTM models show strong performance in capturing sequential patterns, our RoBERTa-based model achieves the highest overall accuracy at 88%, outperforming state-of-the-art baselines. Framed within the diffusion of innovations theory, the proposed model offers clear relative advantages—including accuracy, scalability, and contextual adaptability—that support its early adoption by Information Systems researchers and practitioners. This study not only contributes a high-performing detection model but also delivers methodological and theoretical insights for combating propaganda in digital discourse, enhancing resilience in online information ecosystems. Full article

Antimicrobial resistance (AMR) poses a significant global health threat, largely driven by the overuse and misuse of antibiotics. Methicillin-resistant Staphylococcus aureus (MRSA), a multidrug-resistant pathogen, remains a critical target for novel antibiotic development. This study explores the rhizosphere of the wild apple tree (Malus trilobata) in Lebanon as a potential source of antibacterial compounds. A bacterial strain, MR7S4, identified as Streptomyces anulatus, was isolated and characterized. Its crude extracts exhibited potent activity against Gram-positive pathogens, with minimum inhibitory concentration (MIC) values of 2 µg/mL against S. aureus ATCC 29213, S. aureus Newman, and S. aureus N315 (MRSA), and of 1 µg/mL against Enterococcus faecalis ATCC 19433. Bio-guided fractionation and structural analysis identified a novel antibacterial pyrazinone derivative, MR7S4-F3. This compound demonstrated MIC values of 4–16 µg/mL against Bacillus subtilis ATCC 6633, multiple S. aureus strains, E. faecalis ATCC 19433, E. faecium DSM 17050 (VRE), and E. faecium DSM 20478, while exhibiting no activity against Gram-negative bacteria. Whole-genome sequencing of MR7S4 revealed 35 biosynthetic gene clusters, underscoring its potential for natural product discovery. These findings highlight the untapped microbial diversity of the Middle East and North Africa (MENA) region as a valuable reservoir for antibiotic discovery. MR7S4-F3 emerges as a promising bioactive scaffold, addressing the urgent need for new therapeutic options to combat AMR. Full article

The growing complexity and volume of genomic and omics data present critical challenges for storage, transfer, and analysis in edge–cloud platforms. Existing compression techniques often involve trade-offs between efficiency and speed, requiring innovative approaches that ensure scalability and cost-effectiveness. This paper introduces a lossless compression method that integrates Trie-based shared dictionaries within an edge–cloud architecture. It presents a software-centric scientific research process of the design and evaluation of the proposed compression method. By enabling localized preprocessing at the edge, our approach reduces data redundancy before cloud transmission, thereby optimizing both storage and network efficiency. A global shared dictionary is constructed using N-gram analysis to identify and prioritize repeated sequences across multiple files. A lightweight index derived from this dictionary is then pushed to edge nodes, where Trie-based sequence replacement is applied to eliminate redundancy locally. The preprocessed data are subsequently transmitted to the cloud, where advanced compression algorithms, such as Zstd, GZIP, Snappy, and LZ4, further compress them. Evaluation on real patient omics datasets from B-cell Acute Lymphoblastic Leukemia (B-ALL) and Chronic Lymphocytic Leukemia (CLL) demonstrates that edge preprocessing significantly improves compression ratios, reduces upload times, and enhances scalability in hybrid cloud frameworks. Full article

Bacterial strain TSO55 was isolated from a commercial field of wheat (Triticum turgidum L. subsp. durum), under organic amendments, located in the Yaqui Valley, Mexico. Morphological and microscopical characterization showed off-white irregular colonies and Gram-positive bacillus, respectively. The draft genome sequence of this strain revealed a genomic size of 5,489,151 bp, with a G + C content of 35.21%, N50 value of 245,934 bp, L50 value of 8, and 85 contigs. Taxonomic affiliation showed that strain TSO55 belongs to Bacillus paranthracis, reported as an emergent human pathogen. Genome annotation identified 5743 and 5587 coding DNA sequences (CDSs), respectively, highlighting genes associated with indole production, phosphate and potassium solubilization, and iron acquisition. Further in silico analysis indicated the presence of three CDSs related to pathogenicity islands and a high pathogenic potential (77%), as well as the presence of multiple gene clusters related to antibiotic resistance. The in vitro evaluation of plant growth promotion traits was negative for indole production and phosphate and potassium solubilization, and it was positive but low (18%) for siderophore production. The biosynthetic gene cluster for bacillibactin (siderophore) biosynthesis was confirmed. Antifungal bioactivity of strain TSO55 evaluated against wheat pathogenic fungi (Alternaria alternata TF17, Bipolaris sorokiniana TPQ3, and Fusarium incarnatum TF14) showed minimal fungal inhibition. An antibiotic susceptibility assay indicated resistance to three of the six antibiotics evaluated, up to a concentration of 20 µg/mL. The beta hemolysis result on blood agar reinforced TSO55’s pathogenic potential. Inoculation of B. paranthracis TSO55 on wheat seedlings resulted in a significant decrease in root length (−8.4%), total plant height (−4.2%), root dry weight (−18.6%), stem dry weight (−11.1%), and total plant dry weight (−15.2%) compared to the control (uninoculated) treatment. This work highlights the importance of analyzing the microbiological safety of organic amendments before application. Comprehensive genome-based taxonomic affiliation and bioprospecting of microbial species introduced to the soil by organic agricultural practices and any microbial inoculant will prevent the introduction of dangerous species with non-beneficial traits for crops, which affect sustainability and generate potential health risks for plants and humans. Full article

Probiotic bacteria are normal inhabitants of a healthy human gut, conferring multiple beneficial effects on the gut and beyond. Under various disease states, the abundance and diversity of beneficial bacteria are significantly decreased, a process called dysbiosis. Among the intra- and extracellular components of probiotics, the extracellular vesicles (EVs) secreted by them have recently garnered significant attention as potential mediators of probiotics’ effects on host health. Further, these nanosized particles that encapsulate a wide range of bioactive molecules (proteins, lipids, RNA, and DNA) are standing out as key factors that could mediate gut microbiota–host communication and confer ameliorating effects in experimental inflammatory, metabolic, and cardiovascular disease models. However, a standard protocol of EV isolation from probiotic bacteria, not varying from lab to lab, must be established to achieve consistency in the experimental results in these pre-clinical models. Our current study compared two commonly used methods for EV isolation from biological samples, ultracentrifugation and precipitation, to develop a standard protocol for isolating EVs from the probiotics Lactobacillus acidophilus (LA), a Gram-positive bacterium, and Escherichia coli Nissle (EcN), a Gram-negative bacterium. The ultracentrifugation method gave ~1.5-fold higher EV yield for both LA and EcN compared to the precipitation method. Further, EcN released a higher level of EVs compared to LA. EVs were quantified and characterized by nanoparticle-tracking analysis (NTA) and by measuring the specific surface biomarkers using Western blot. Here, we describe our standardized step-by-step protocol for isolating EVs from probiotic bacteria and their characterization. Full article

The amphibian skin secretions are excellent sources of bioactive peptides, some of which and their derivatives exhibit multiple properties, including antibacterial and antagonism against bradykinin. A novel peptide Senegalin-2 was isolated from the skin secretions of Kassina senegalensis frog. Senegalin-2 relaxed rat bladder smooth muscle (EC₅₀ 17.94 nM) and ileum smooth muscle (EC₅₀ 135 nM), inhibited S. aureus and MRSA at 2 μM, and exhibited low hemolytic activity with no cytotoxicity. To design effective bradykinin antagonists, Senegalin-2 was conjugated with bradykinin to synthesize Senegalin-2BK. This modification retained potent activity against Gram-positive bacteria. Compared to Senegalin-2, Senegalin-2BK significantly reduced hemolysis and exhibited a more than threefold increase in the selectivity index. Furthermore, Senegalin-2BK contracted the bladder (EC₅₀ 2.83 μM) and ileum (EC₅₀ 56.64 nM)’s smooth muscle. The pretreatment with 10⁻⁷ M Senegalin-2BK reduced the 10⁻⁶ M bradykinin contraction on the bladder by over 70%. In conclusion, Senegalin-2 has dual functionalities as an antibacterial agent and muscle relaxant, positioning it as a potential therapeutic candidate for managing overactive bladder. As a synthetically derived bradykinin antagonist and myotropic peptide with antibacterial properties, Senegalin-2BK shows promise in effective therapies for relieving pain, inflammation, and addressing muscular disorders such as urinary retention, constipation, and infections. Full article

Word segmentation is a critical task in natural language processing for southeast Asian Abugida languages, including Thai, Burmese, and Khmer. Existing approaches demonstrate that models using fixed-length windowed context inputs can achieve high segmentation accuracy; however, they often rely on low-level character features or language-specific preprocessing. Character-based methods can limit feature learning, while language-specific features add complexity due to specialized preprocessing requirements. This paper introduces UnifiedCut, which is a neural model that leverages multiple n-grams within a windowed multi-head attention mechanism. This design captures segmentation features from local contexts and multi-perspective n-gram inputs, enhancing generalization and recall, particularly for out-of-vocabulary words. Compared to CNN- and RNN-based approaches, UnifiedCut’s multi-head attention enables finer-grained feature extraction and greater parallelism, resulting in a faster, more scalable solution. Comprehensive experiments on public datasets for Thai, Burmese, and Khmer show that UnifiedCutachieves state-of-the-art performance in word segmentation. Full article

Fake news is one of the biggest challenging issues in today’s technological world and has a huge impact on the population’s decision-making and way of thinking. Disinformation can be classified as a subdivision of fake news, the main purpose of which is to manipulate and generate confusion among people in order to influence their opinion and obtain certain advantages in multiple domains (politics, economics, etc.). Propaganda, rumors, and conspiracy theories are just a few examples of common disinformation. Therefore, there is an urgent need to understand this phenomenon and offer the scientific community a paper that provides a comprehensive examination of the existing literature, lay the foundation for future research areas, and contribute to the fight against disinformation. The present manuscript provides a detailed bibliometric analysis of the articles oriented towards disinformation detection, involving high-performance machine learning and deep learning algorithms. The dataset has been collected from the popular Web of Science database, through the use of specific keywords such as “disinformation”, “machine learning”, or “deep learning”, followed by a manual check of the papers included in the dataset. The documents were examined using the popular R tool, Biblioshiny 4.2.0; the bibliometric analysis included multiple perspectives and various facets: dataset overview, sources, authors, papers, n-gram analysis, and mixed analysis. The results highlight an increased interest from the scientific community on disinformation topics in the context of machine learning and deep learning, supported by an annual growth rate of 96.1%. The insights gained from the research bring to light surprising details, while the study provides a solid basis for both future research in this area, as well for the development of new strategies addressing this complex issue of disinformation and ensuring a trustworthy and safe online environment. Full article

Background: Obesity is considered a health issue associated with increased morbidity and a risk factor for multiple conditions, such as type 2 diabetes, cardiovascular diseases and infections. It may affect the pharmacokinetics and pharmacodynamics of many drugs, including antimicrobials like ciprofloxacin. Regrettably, data on ciprofloxacin’s efficacy in obese patients remain scarce. This study aims to evaluate the impact of obesity on the efficacy of ciprofloxacin in treating Gram-negative bacterial infections. Methods: A retrospective multicenter cohort study was conducted in two tertiary hospitals in Saudi Arabia. Adult patients (≥18 years) treated with ciprofloxacin for confirmed Gram-negative infection between January 2017 and April 2023 were included. Patients were excluded if they received ciprofloxacin empirically, had inadequate source control within 72 h, or had missing weight and height information at ciprofloxacin initiation. The primary outcome was clinical cure, defined as the resolution of the clinical infection manifestations without additional therapeutic management by the end of treatment. Other secondary and safety outcomes were also assessed. Results: A total of 99 patients were included, divided into obese (n = 42) and non-obese (n = 57) groups. The obese group had a significantly lower median age (50 years) compared to the non-obese group (64 years) (p = 0.002). The obese group had fewer male patients (38.10% vs. 68.42%; p = 0.004), higher body weight (90 (81–97) vs. 63 (55–70) days; p < 0.001), and lower height (158 (155–165) vs. 165 (158–172) days; p = 0.008) compared to non-obese. Urinary tract infection was the most common type, with Escherichia coli being the most common isolate. The median hospital length of stay was shorter in the obese group than in the non-obese group (1 vs. 3 days, p = 0.007). There were no significant differences in clinical cure rates between obese (85.71%) and non-obese (85.96%) patients (p = 1). No significant differences were observed in terms of in-hospital mortality, 30-day mortality, or 60-day infection recurrence rates between the two groups. Microbiological eradication was not achieved in the obese group, whereas a 10.53% eradication rate was observed in the non-obese group (p = 0.037). However, the majority of the patients had indeterminate eradication. The incidence of adverse drug reactions (ADRs) was lower in the obese group (4.76%) compared to the non-obese group (17.54%, p = 0.066). Conclusions: Treatment with ciprofloxacin in obese patients has similar efficacy and safety outcomes compared to non-obese patients with infections due to Gram-negative pathogens. Full article