Could bacteriophages isolated from the sewage be the solution to methicillin-resistant Staphylococcus aureus?

Introductions: The emergence of multidrug-resistant bacteria such as Methicillin-Resistant Staphylococcus aureus (MRSA) complicates the treatment of the simplest infection. Although glycopeptides such as vancomycin still proves to be effective in treating MRSA infections, the emergence of vancomycin-resistant strains limits the long term use of this antibiotic. Bacteriophages are ubiquitous bacterial viruses which is capable of infecting and killing bacteria including its antibiotic-resistant strains. Bactericidal bacteriophages use mechanisms that is distinct from antibiotics and is not affected by the antibioticresistant phenotypes. Objectives: The study was undertaken to evaluate the possibility to isolate bacteriolytic bacteriophages against S.aureus from raw sewage water and examine their efficacy as antimicrobial agents in vitro. Methods: Bacteriophages were isolated from the raw sewage using the agar overlay method. Isolated bacteriophages were plaque purified to obtain homogenous bacteriophage isolates. The host range of the bacteriophages was determined using the spot test assay against the 25 MRSA and 36 MSSA isolates obtained from the Sarawak General Hospital. Staphylococcus saprophyticus, Staphylococcus sciuri and Staphylococcus xylosus were included as non-SA controls. The identity of the bacteriophages was identified via Transmission Electron Microscopy and genomic size analysis. Their stability at different pH and temperature were elucidated. Results: A total of 10 lytic bacteriophages infecting S.aureus were isolated and two of them namely ΦNUSA-1 and ΦNUSA-10 from the family of Myoviridae and Siphoviridae respectively exhibited exceptionally broad host range against >80% of MRSA and MSSA tested. Both bacteriophages were specific to S.aureus and stable at both physiologic pH and temperature. Conclusion: This study demonstrated the abundance of S.aureus specific bacteriophages in raw sewage. Their high virulence against both MSSA and MRSA is an excellent antimicrobial characteristic which can be exploited for bacteriophage therapy against MRSA

Evaluation of the efficacy of bacteriophages against Staphylococcus aureus

Staphylococcus aureus (S. aureus) is an opportunistic human pathogen that has the ability to cause both health care-associated and community-acquired infections (Chambers, 2001). The infections were once, easily treated with antibiotics before resistance against beta-lactams (eg. Methicillin) and glycopeptides (eg. Vancomycin) began to emerge over the years and caused an increase in mortality and morbidity rates in patients infected with S. aureus (Boucher & Corey, 2008, Howe et al., 1998). This has led to an increased interest in the exploration of the use of bacteriophages as a way to combat multi-drug resistant organisms because bacteriophages has bacteriolytic mechanism independent from those of any known antibiotics (Matsuzaki et al., 2005)

Could bacteriophages isolated from the sewage be the solution to methicillin-resistant Staphylococcus aureus?

Introductions: The emergence of multidrug-resistant bacteria such as Methicillin-Resistant Staphylococcus aureus (MRSA) complicates the treatment of the simplest infection. Although glycopeptides such as vancomycin still proves to be effective in treating MRSA infections, the emergence of vancomycin-resistant strains limits the long term use of this antibiotic. Bacteriophages are ubiquitous bacterial viruses which is capable of infecting and killing bacteria including its antibiotic-resistant strains. Bactericidal bacteriophages use mechanisms that is distinct from antibiotics and is not affected by the antibioticresistant phenotypes. Objectives: The study was undertaken to evaluate the possibility to isolate bacteriolytic bacteriophages against S.aureus from raw sewage water and examine their efficacy as antimicrobial agents in vitro. Methodology: Bacteriophages were isolated from the raw sewage using the agar overlay method. Isolated bacteriophages were plaque purified to obtain homogenous bacteriophage isolates. The host range of the bacteriophages was determined using the spot test assay against the 25 MRSA and 36 MSSA isolates obtained from the Sarawak General Hospital. Staphylococcus saprophyticus, Staphylococcus sciuri and Staphylococcus xylosus were included as non-SA controls. The identity of the bacteriophages was identified via Transmission Electron Microscopy and genomic size analysis. Their stability at different pH and temperature were elucidated. Results: A total of 10 lytic bacteriophages infecting S.aureus were isolated and two of them namely ΦNUSA-1 and ΦNUSA-10 from the family of Myoviridae and Siphoviridae respectively exhibited exceptionally broad host range against >80% of MRSA and MSSA tested. Both bacteriophages were specific to S.aureus and stable at both physiologic pH and temperature. Conclusion: This study demonstrated the abundance of S.aureus specific bacteriophages in raw sewage. Their high virulence against both MSSA and MRSA is an excellent antimicrobial characteristic which can be exploited for bacteriophage therapy against MRSA

Electroacupuncture activates corticotrophin-releasing hormone-containing neurons in the paraventricular nucleus of the hypothalammus to alleviate edema in a rat model of inflammation

<p>Abstract</p> <p>Background</p> <p>Studies show that electroacupuncture (EA) has beneficial effects in patients with inflammatory diseases. This study investigated the mechanisms of EA anti-inflammation, using a rat model of complete Freund's adjuvant (CFA)-induced hind paw inflammation and hyperalgesia.</p> <p>Design</p> <p>Four experiments were conducted on male Sprague-Dawley rats (n = 6–7/per group). Inflammation was induced by injecting CFA into the plantar surface of one hind paw. Experiment 1 examined whether EA increases plasma adrenocorticotropic hormone (ACTH) levels. Experiments 2 and 3 studied the effects of the ACTH and corticotropin-releasing hormone (CRH) receptor antagonists, ACTH_(11–24)and astressin, on the EA anti-edema. Experiment 4 determined whether EA activates CRH neurons in the paraventricular nucleus of the hypothalammus. EA treatment, 10 Hz at 3 mA and 0.1 ms pulse width, was given twice for 20 min each, once immediately post and again 2 hr post-CFA. Plasma ACTH levels, paw thickness, and paw withdrawal latency to a noxious thermal stimulus were measured 2 h and 5 h after the CFA.</p> <p>Results</p> <p>EA significantly increased ACTH levels 5 h (2 folds) after CFA compared to sham EA control, but EA alone in naive rats and CFA alone did not induce significant increases in ACTH. ACTH_(11–24)and astressin blocked EA anti-edema but not EA anti-hyperalgesia. EA induced phosphorylation of NR1, an essential subunit of the N-methyl-D-aspartic acid (NMDA) receptor, in CRH-containing neurons of the paraventricular nucleus.</p> <p>Conclusion</p> <p>The data demonstrate that EA activates CRH neurons to significantly increase plasma ACTH levels and suppress edema through CRH and ACTH receptors in a rat model of inflammation.</p

MalSort: Lightweight and Efficient Image-based Malware Classification Using Masked Self-supervised Framework with Swin Transformer

The proliferation of malware has exhibited a substantial surge in both quantity and diversity, posing significant threats to the Internet and indispensable network applications. The accurate and effective classification makes a pivotal role in defending against malware. Numerous approaches employ supervised learning techniques, specifically Convolutional Neural Networks (CNNs), to train feature extractors. However, acquiring a substantial quantity of labled samples incurs significant expenses, and relying solely on CNNs as feature extractors may result in restricted local receptive fields, consequently compromising the preservation of crucial features. In order to address these constraints, we propose an effective malware classification approach, denoted as MalSort, which leverages the masked self-supervised framework with Swin Transformer. Initially, each instance of malware is transformed into a color image. Furthermore, the Swin Transformer self-supervised framework is utilized to extract multi-scale key feature vectors from a randomly masked partial color image, while the prediction module is employed to predict the masked image. Ultimately, the pre-trained encoder is fine-tuned using the malware dataset to effectively carry out a malware classification task. Our MalSort exhibits a reduced reliance on labeled data samples during the training phase, thereby obviating the necessity for extensive amounts of labeled data. Consequently, the MalSort conserves hardware resources and improve its training efficiency. The experimental results indicate that the MalSort outperforms existing models by achieving a classification accuracy of 97.85%, a recall of 97.63%, a precision of 97.85%, and an F1-score of 97.85% on the BIG2015 dataset. Similarly, on the Malimg dataset, the model achieves percentages of 98.28%, 98.18%, 98.19%, and 98.28% for classification accuracy, recall, precision, and F1-score, respectively

Automatically Predicting Material Properties with Microscopic Images: Polymer Miscibility as an Example

Many material properties are manifested in the morphological appearance and characterized using microscopic images, such as scanning electron microscopy (SEM). Polymer miscibility is a key physical quantity of polymer materials and is commonly and intuitively judged using SEM images. However, human observation and judgment of the images is time-consuming, labor-intensive, and hard to be quantified. Computer image recognition with machine learning methods can make up for the defects of artificial judging, giving accurate and quantitative judgment. We achieve automatic miscibility recognition utilizing a convolutional neural network and transfer learning methods, and the model obtains up to 94% accuracy. We also put forward a quantitative criterion for polymer miscibility with this model. The proposed method can be widely applied to the quantitative characterization of the microstructure and properties of various materials

A five-year survey of dematiaceous fungi in a tropical hospital reveals potential opportunistic species.

Dematiaceous fungi (black fungi) are a heterogeneous group of fungi present in diverse environments worldwide. Many species in this group are known to cause allergic reactions and potentially fatal diseases in humans and animals, especially in tropical and subtropical climates. This study represents the first survey of dematiaceous fungi in Malaysia and provides observations on their diversity as well as in vitro response to antifungal drugs. Seventy-five strains isolated from various clinical specimens were identified by morphology as well as an internal transcribed spacer (ITS)-based phylogenetic analysis. The combined molecular and conventional approach enabled the identification of three classes of the Ascomycota phylum and 16 genera, the most common being Cladosporium, Cochliobolus and Neoscytalidium. Several of the species identified have not been associated before with human infections. Among 8 antifungal agents tested, the azoles posaconazole (96%), voriconazole (90.7%), ketoconazole (86.7%) and itraconazole (85.3%) showed in vitro activity (MIC ≤ 1 µg/mL) to the largest number of strains, followed by anidulafungin (89.3%), caspofungin (74.7%) and amphotericin B (70.7%). Fluconazole appeared to be the least effective with only 10.7% of isolates showing in vitro susceptibility. Overall, almost half (45.3%) of the isolates showed reduced susceptibility (MIC >1 µg/mL) to at least one antifungal agent, and three strains (one Pyrenochaeta unguis-hominis and two Nigrospora oryzae) showed potential multidrug resistance