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Graphene oxide (GO) and reduced graphene oxide (rGO) nanoparticles were synthesized using 40 mL of lemon juice extract as a reducing agent. The synthesized nanoparticles were characterized using various analytical techniques, including UV–visible spectroscopy, scanning electron microscopy, energy-dispersive X-ray spectroscopy, Fourier transform infrared spectroscopy, and X-ray diffraction. The results confirmed the successful synthesis of GO and rGO nanoparticles with varied sizes and shapes. The synthesized nanoparticles were tested for their antimicrobial activity against a range of bacterial and fungal strains, including Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, Candida albicans, Fusarium oxysporum, and Aspergillus flavus. Multiple concentrations of GO and rGO nanoparticles were tested, and it was observed that 100 µg·mL−1 of both GO and rGO showed the highest inhibitory effect against bacterial and produced zones of inhibition of 17.66 mm, 18.67 mm, and 17.88 for E. coli, S. aureus, K. pneumoniae and 20.33, 22.45, and 21.34 mm for C. albicans, F. oxysporum, and A. flavus. Comparatively, GO performed well as compared to rGO regarding antimicrobial activity. The synthesized nanoparticles exhibited significant antimicrobial activity against various bacterial and fungal strains and have the potential to be developed as novel antimicrobial agents.

IL-2 is a powerful immune growth factor and it plays important role in sustaining T cell response. The potential of IL-2 in expanding T cells without loss of functionality has led to its early use in cancer immunotherapy. IL-2 has been reported to induce complete and durable regressions in cancer patients but immune related adverse effects have been reported (irAE). The present review discusses the prospects of IL-2 in immunotherapy for cancer.

NK-lysins from chicken, bovine and human are used as antiviral and antibacterial agents. Gram-negative and gram-positive microorganisms, including Streptococcus pyogenes, Streptococcus mutans, Escherichia coli, Pseudomonas aeruginosa, Klebsiella oxytoca, Shigella sonnei, Klebsiella pneumoniae and Salmonella typhimurium, are susceptible to NK-lysin treatment. The presence of dominant TEM-1 gene was noted in all untreated and treated bacteria, while TOHO-1 gene was absent in all bacteria. Importantly, β-lactamase genes CTX-M-1, CTX-M-8, and CTX-M-9 genes were detected in untreated bacterial strains; however, none of these were found in any bacterial strains following treatment with NK-lysin peptides. NK-lysin peptides are also used to test for inhibition of infectivity, which ranged from 50 to 90% depending on NK-lysin species. Chicken, bo vine and human NK-lysin peptides are demonstrated herein to have antibacterial activity and antiviral activity against Rotavirus (strain SA-11). On the basis of the comparison between these peptides, potent antiviral activity of bovine NK-lysin against Rotavirus (strain SA-11) is particularly evident, inhibiting infection by up to 90%. However, growth was also significantly inhibited by chicken and human NK-lysin peptides, restricted by 80 and 50%, respectively. This study provided a novel treatment using NK-lysin peptides to inhibit expression of β-lactamase genes in β-lactam antibiotic-resistant bacterial infections. [ABSTRACT FROM AUTHOR]

Colorectal carcinoma (CRC) is one such dispersed cancer globally and also prominent one in causing cancer-based death. Conventionally, pathologists execute CRC diagnosis through visible scrutinizing under the microscope the resected tissue samples, stained and fixed through Haematoxylin and Eosin (H&E). The advancement of graphical processing systems has resulted in high potentiality for deep learning (DL) techniques in interpretating visual anatomy from high resolution medical images. This study develops a slime mould algorithm with deep transfer learning enabled colorectal cancer detection and classification (SMADTL-CCDC) algorithm. The presented SMADTL-CCDC technique intends to appropriately recognize the occurrence of colorectal cancer. To accomplish this, the SMADTLCCDC model initially undergoes pre-processing to improve the input image quality. In addition, a dense-EfficientNet technique was employed to extract feature vectors from the pre-processed images. Moreover, SMA with Discrete Hopfield neural network (DHNN) method was applied for the recognition and classification of colorectal cancer. The utilization of SMA assists in appropriately selecting the parameters involved in the DHNN approach. A wide range of experiments was implemented on benchmark datasets to assess the classification performance. A comprehensive comparative study highlighted the better performance of the SMADTL-CDC model over the recent approaches. [ABSTRACT FROM AUTHOR]

Background: Acute lymphoblastic leukemia (ALL) is the most common cancer diagnosed in children and represents approximately 25% of cancer diagnoses among those younger than 15 years of age., Aim and Objectives: This study investigated substitutions in the ATP synthase subunit 6 gene of mitochondrial DNA (mtDNA) as a potential diagnostic biomarker for early detection and diagnosis of acute lymphoblastic leukemia. Based on mtDNA from 23 subjects diagnosed with acute lymphoblastic leukemia, approximately 465 bp of the ATP synthase subunit 6 gene were amplified and sequenced., Results: The sequencing revealed thirty-one mutations at 14 locations in ATP synthase subunit 6 of mtDNA in the ALL subjects. All were identified as single nucleotide polymorphisms (SNPs) with a homoplasmic pattern. The mutations were distributed between males and females. Novel haplotypes were identified in this investigation: haplotype (G) was recorded in 34% in diagnosed subjects; the second haplotype was (C) with frequency of 13% in ALL subjects. Neither of these were observed in control samples., Conclusions: These haplotypes were identified for the first time in acute lymphoblastic leukemia patients. Five mutations able to change amino acid synthesis for the ATP synthase subunit 6 were associated with acute lymphoblastic leukemia. This investigation could be used to provide an overview of incidence frequency of acute lyphoblastic leukemia (ALL) in Saudi patients based on molecular events.