Influence of Maqian essential oil on gut microbiota and immunoresponses in type 1 diabetes: In silico study

Diversity and homeostasis of gut bacterial composition is highly associated with the pathogenesis of insulin dysfunction and type 1 diabetes melittus (T1D), hence emerged in parallel with the activation of autoimmunity. We aimed to study the bioactive potential of essential oil from Zanthoxylum myriacanthum var. pubescens Huang (Maqian) through computational approaches. Twelve chemical constituents derived from Maqian essential oil were docked with selected proteins (i.e., 3pig, 1kho, 7dmq, 4m4d, 2z65, 4glp, and 3fxi) in which are involved in gut microbiota modulation in T1D. Subsequently, the prediction of bioavailability properties of the small molecules were evaluated. Among all chemical constituents, the post-docking interaction analysis demonstrated that α-phellandrene exhibits the strongest binding affinity and induces gut microbiota modulation with β-fructofuranosidase from Bifidobacterium longum. The current result revealed the potential of 3-Carene and α-Pinene in inducing specific changes in gut microbiota downregulating Clostridium perfringens and quenching Leptotrichia shahii respectively. β-Pinene possess exceptionally strong binding affinity that effectively disrupt the interaction between lipopolysaccharide and its cognate receptors, while α-Phellandrene was exhibited the uppermost binding affinity with TLR4/MD2 and could likely target TLR4 stimulating lipopolysaccharide. Our results are the first to report on the gut microbiota modulation effects of α-Phellandrene and β-Phellandrene via actions on LPS binding to CD14 and the TLR4 co-receptor signaling. In conclusion, our findings based on computational approaches, small molecules from Maqian present as promising agents which could regulate inflammatory response and modulate gut microbiota in type 1 diabetes mellitus.

Investigation of Biogenic Amine Levels and Microbiological Activity as Quality Markers in Some Dairy and Fish Products in Food Markets in the Kingdom of Saudi Arabia

This study aimed to verify the presence of biogenic amines (BAs) and evaluate the microbiological activity of some food samples collected from retail stores in the Kingdom of Saudi Arabia. A total of thirty-five dairy and fish products were collected and analyzed for BAs, including putrescine (PUT), cadaverine (CAD), spermidine (SPE), histamine (HIS), spermine (SPR), and tyramine (TYR), as well as for total colony count (TCC), lactic acid bacteria (LAB), Enterobacteriaceae, yeast and mold (Y and M), coliforms, and aerobic sporulation count (ASF). The thin layer chromatography (TLC) method was used in the analytical methodology to identify the BAs. The results showed the presence of BAs in all dairy products, but their concentration did not exceed the maximum permissible limit, which in contrast was established by the Food and Drug Administration (FDA) at 10 mg/100 g. The amounts of BAs in fish products varied significantly. All fish product samples contained levels of BAs below the permissible limit. Results of an independent study also indicated potential toxicity at levels of BAs (>10 mg/100 g) in Egyptian herring. Enterobacteriaceae and the coli group were present in higher concentrations in the Egyptian herring samples, whereas other samples (particularly frozen shrimp) showed increased TCC levels with a higher concentration of histamine-producing bacteria. From a consumer safety perspective, this study also indicated that food samples generally contained acceptable levels of BAs. In conclusion, there is a need to improve and standardize food quality and hygiene practices during production and storage to ensure human safety and prevent HIS formation.

Unveiling the volatile compounds and antibacterial mechanisms of action of Cupressus sempervirens L., against Bacillus subtilis and Pseudomonas aeruginosa

Cupressus sempervirens is a known traditional plant used to manage various ailments, including cancer, inflammatory and infectious diseases. In this investigation, we aimed to explore the chemical profile of Cupressus sempervirens essential oil (CSEO) as well as their antibacterial mode of action. The volatile components were characterized using gas chromatography coupled to a mass spectrometer (GC-MS). The results revealed remarkable antibacterial properties of EO derived from C. sempervirens. GC-MS analysis indicated that C. sempervirens EO characterized by δ-3-carene (47.72%), D-limonene (5.44%), β-pinene (4.36%), β-myrcene (4.02%). The oil exhibited significant inhibitory effects against a range of bacteria, including Staphylococcus aureus ATCC 29213, Bacillus subtilis ATCC 13048, Bacillus cereus (Clinical isolate), Pseudomonas aeruginosa ATCC 27853, and Escherichia coli ATCC 25922. These inhibitory effects surpassed those of conventional antibiotics. Furthermore, the EO demonstrated low minimum inhibitory concentrations (MICs) and minimum bactericidal concentrations (MBCs), indicating its bactericidal nature (MBC/MIC < 4.0). Time-kill kinetics analysis showed that CSEO was particularly effective at 2 × MIC doses, rapidly reduced viable count of B. subtilis and P. aeruginosa within 8 h. This suggests that the oil acts quickly and efficiently. The cell membrane permeability test further demonstrated the impact of CSEO on the relative conductivity of B. subtilis and P. aeruginosa, both at 2 × MIC concentrations. These observations suggest that EO disrupts the bacterial membrane, thereby influencing their growth and viability. Additionally, the cell membrane integrity test indicated that the addition of CSEO to bacterial cultures resulted in the significant release of proteins from the bacterial cells. This suggests that EO affects the structural integrity of the bacterial cells. Furthermore, the anti-biofilm assay confirmed the efficacy of CSEO as a potent anti-biofilm agent. It demonstrated the oil's ability to inhibit quorum sensing, a crucial mechanism for biofilm formation, and its competitive performance compared to the tested antibiotics.

Identification of Small Molecule Inhibitors of Human Cytomegalovirus pUL89 Endonuclease Using Integrated Computational Approaches

Replication of Human Cytomegalovirus (HCMV) requires the presence of a metal-dependent endonuclease at the C-terminus of pUL89, in order to properly pack and cleave the viral genome. Therefore, pUL89 is an attractive target to design anti-CMV intervention. Herein, we used integrated structure-based and ligand-based virtual screening approaches in combination with MD simulation for the identification of potential metal binding small molecule antagonist of pUL89. In this regard, the essential chemical features needed for the inhibition of pUL89 endonuclease domain were defined and used as a 3D query to search chemical compounds from ZINC and ChEMBL database. Thereafter, the molecular docking and ligand-based shape screening were used to narrow down the compounds based on previously identified pUL89 antagonists. The selected virtual hits were further subjected to MD simulation to determine the intrinsic and ligand-induced flexibility of pUL89. The predicted binding modes showed that the compounds reside well in the binding site of endonuclease domain by chelating with the metal ions and crucial residues. Taken in concert, the in silico investigation led to the identification of potential pUL89 antagonists. This study provided promising starting point for further in vitro and in vivo studies.

A Review of Modern Methods for the Detection of Foodborne Pathogens

Despite the recent advances in food preservation techniques and food safety, significant disease outbreaks linked to foodborne pathogens such as bacteria, fungi, and viruses still occur worldwide indicating that these pathogens still constitute significant risks to public health. Although extensive reviews of methods for foodborne pathogens detection exist, most are skewed towards bacteria despite the increasing relevance of other pathogens such as viruses. Therefore, this review of foodborne pathogen detection methods is holistic, focusing on pathogenic bacteria, fungi, and viruses. This review has shown that culture-based methods allied with new approaches are beneficial for the detection of foodborne pathogens. The current application of immunoassay methods, especially for bacterial and fungal toxins detection in foods, are reviewed. The use and benefits of nucleic acid-based PCR methods and next-generation sequencing-based methods for bacterial, fungal, and viral pathogens' detection and their toxins in foods are also reviewed. This review has, therefore, shown that different modern methods exist for the detection of current and emerging foodborne bacterial, fungal, and viral pathogens. It provides further evidence that the full utilization of these tools can lead to early detection and control of foodborne diseases, enhancing public health and reducing the frequency of disease outbreaks.

Dihydropyrimidone Derivatives as Thymidine Phosphorylase Inhibitors: Inhibition Kinetics, Cytotoxicity, and Molecular Docking

Overexpression of the thymidine phosphorylase (TP) enzyme induces angiogenesis, which eventually leads to metastasis and tumor growth. The crucial role of TP in cancer development makes it an important target for anticancer drug discovery. Currently, there is only one US-FDA-approved drug, i.e., Lonsurf, a combination of trifluridine and tipiracil, for the treatment of metastatic colorectal cancer. Unfortunately, numerous adverse effects are associated with its use, such as myelosuppression, anemia, and neutropenia. Since the last few decades, the discovery of new, safe, and effective TP inhibitory agents has been rigorously pursued. In the present study, we evaluated a series of previously synthesized dihydropyrimidone derivatives 1-40 for their TP inhibitory potential. Compounds 1, 12, and 33 showed a good activity with IC₅₀ = 314.0 ± 0.90, 303.5 ± 0.40, and 322.6 ± 1.60 µM, respectively. The results of mechanistic studies revealed that compounds 1, 12, and 33 were the non-competitive inhibitors. These compounds were also evaluated for cytotoxicity against 3T3 (mouse fibroblast) cells and were found to be non-cytotoxic. Finally, the molecular docking suggested the plausible mechanism of non-competitive inhibition of TP. The current study thus identifies some dihydropyrimidone derivatives as potential inhibitors of TP, which can be further optimized as leads for cancer treatment.

An Efficient Pest Detection Framework with a Medium-Scale Benchmark to Increase the Agricultural Productivity

Insect pests and crop diseases are considered the major problems for agricultural production, due to the severity and extent of their occurrence causing significant crop losses. To increase agricultural production, it is significant to protect the crop from harmful pests which is possible via soft computing techniques. The soft computing techniques are based on traditional machine and deep learning-based approaches. However, in the traditional methods, the selection of manual feature extraction mechanisms is ineffective, inefficient, and time-consuming, while deep learning techniques are computationally expensive and require a large amount of training data. In this paper, we propose an efficient pest detection method that accurately localized the pests and classify them according to their desired class label. In the proposed work, we modify the YOLOv5s model in several ways such as extending the cross stage partial network (CSP) module, improving the select kernel (SK) in the attention module, and modifying the multiscale feature extraction mechanism, which plays a significant role in the detection and classification of small and large sizes of pest in an image. To validate the model performance, we develop a medium-scale pest detection dataset that includes the five most harmful pests for agriculture products that are ants, grasshopper, palm weevils, shield bugs, and wasps. To check the model's effectiveness, we compare the results of the proposed model with several variations of the YOLOv5 model, where the proposed model achieved the best results in the experiments. Thus, the proposed model has the potential to be applied in real-world applications and further motivate research on pest detection to increase agriculture production.