Improving inceptionV4 model based on fractional-order snow leopard optimization algorithm for diagnosing of ACL tears.

In the current research study, a new method is presented to diagnose Anterior Cruciate Ligament (ACL) tears by introducing an optimized version of the InceptionV4 model. Our proposed methodology utilizes a custom-made variant of the Snow Leopard Optimization Algorithm, known as the Fractional-order Snow Leopard Optimization Algorithm (FO-LOA), to extract essential features from knee magnetic resonance imaging (MRI) images. This results in a substantial improvement in the accuracy of ACL tear detection. By effectively extracting critical features from knee MRI images, our proposed methodology significantly enhances diagnostic accuracy, potentially reducing false negatives and false positives. The enhanced model based on FO-LOA underwent thorough testing using the MRNet dataset, demonstrating exceptional performance metrics including an accuracy rate of 98.00%, sensitivity of 98.00%, precision of 97.00%, specificity of 98.00%, F1-score of 98.00%, and Matthews Correlation Coefficient (MCC) of 88.00%. These findings surpass current methodologies like Convolutional Neural Network (CNN), Inception-v3, Deep Belief Networks and Improved Honey Badger Algorithm (DBN/IHBA), integration of the CNN with an Amended Cooking Training-based Optimizer version (CNN/ACTO), Self-Supervised Representation Learning (SSRL), signifying a significant breakthrough in ACL injury diagnosis. Using FO-SLO to optimize the InceptionV4 framework shows promise in improving the accuracy of ACL tear identification, enabling prompt and efficient treatment interventions.

Target lipidomics approach to reveal the resolution of inflammation induced by Chinese medicine combination in Liu-Shen-Wan against realgar overexposure to rats.

ETHNOPHARMACOLOGICAL RELEVANCE: Liu-Shen-Wan (LSW) is one of the popular over-the-counter drugs in Asia, which contains realgar (As4S4), used for the treatment of upper respiratory tract inflammation and skin infections. However, the safety and potential risk of this arsenic remain unknown. AIM OF THE STUDY: The aim of this study was to determine total arsenic in tissue and investigate effects of regular dose and overdose LSW exposure on rat liver. MATERIALS AND METHODS: We used a target lipidomics approach to quantify inflammatory eicosanoids and employed ICP-MS to determine total arsenic in tissue. RESULTS: The results showed that oral administration of 8 and 40 mg/kg LSW (1 and 5 fold human-equivalent dose) induced light changes of liver lipidomic profile in rats, which was associated with anti-inflammatory function of LSW. In our recent report, we observed that 41 and 134 mg/kg realgar (40 and 132 fold human-equivalent dose) stimulated rat liver inflammation through up-regulation of pro-inflammatory LOX-derived, CYP-derived HETEs and COX-derived PGs. However, we found that LSW in the form of drug combination, containing 41 and 134 mg/kg realger, could not stimulate these similar inflammatory responses in rats, although the liver total arsenic levels of the realger and LSW groups were same. CONCLUSION: The downregulation of pro-inflammatory response showed that the LSW containing realger is safer than realger alone administrated to rats. These results suggested that Chinese medicines combination could reduce realgar-derived arsenic toxicity in rats.

High Resolution Mass Profile of Bufadienolides and Peptides Combing with Anti-Tumor Cell Screening and Multivariate Analysis for the Quality Evaluation of Bufonis Venenum.

In order to evaluate the quality of Bufonis Venenum commercial herbs, a three-step qualitative and quantitative research study was performed. Firstly, we tried to identify small molecules and peptides in Bufonis Venenum using pre-fractionation chromatography and high-resolution mass spectrometry. The database search of the small molecules and peptides of Bufonis Venenum revealed that the dried venom consisted of free/conjugated-type bufadienolides and peptides with a mass range of 0.4-2 kDa. Secondly, we used partial least squares (PLS) multivariate statistical analysis to screen bufadienolides markers (VIP > 1.5) responsible for the anti-tumor cell activity of Bufonis Venenum, including 21 identified bufadienolides and 7 unknown compounds. It is noticeable that these bufadienolide markers could not be recognized by traditional HPLC-UV based spectrum-effect relationship analysis (correlation coefficient ranging from -0.24 to 0.40). Finally, we proposed a weight coefficient-based corrected total contents of 9 bufadienolides as a quality evaluation indicator, which had good correlation with inhibitory effects on tumor cells of commercial Bufonis Venenum. The correlation coefficient increased from 0.4 to 0.6. Thus, our pre-fractionation chromatography and mass spectrometry strategy had significant advancement over the traditional spectrum-effect relationship method for chemical marker identification. These results could be crucial and helpful in the development of a quality evaluation method that could reflect the pharmacological activity of Bufonis Venenum.

Lipidomic profiling of subchronic As4S4 exposure identifies inflammatory mediators as sensitive biomarkers in rats.

Arsenic sulfide compounds provide nearly all of the world's supply of arsenic. However, the risk of arsenic trisulfide exposure is still not fully investigated. Here, we systemically assessed the toxicology of As4S4 in rats by combining arsenic metabolite detection, routine testing and lipidomic profiling. It was revealed that the oral administration of As4S4 for two months increased the total arsenic content in the liver reaching a saturation level. Further analysis by anion exchange chromatography coupled with inductively coupled plasma mass spectrometry (ICP-MS) technology showed no trace of inorganic arsenic, but there was significant presence of dimethylarsinic acid (DMA), in the livers of rats. This arsenic metabolite was less toxic to rats and did not induce overt liver pathology and functional injury. In contrast, lipidomic profiling provided a comprehensive map of lipids and uncovered a more complex inflammatory response, exhibiting more sensitive change to arsenic exposure. We observed that metabolites of cyclooxygenase, including PGF2α, dhk PGF2α, 15k PGF2α, 8-iso-PGF2a, PGE2, dhk PGE2, PGD2, 15d-PGD2, and PGJ2, were significantly elevated. But mediators from lipoxygenase, cytochrome P450, docosahexaenoic acid, and eicosapentaenoic acid pathways were not markedly affected. In summary, we identified DMA as the predominant arsenic species in the livers of rats, and found cyclooxygenase-derived lipids as the inflammatory mediators before the development of overt liver injury for subchronic As4S4 exposure. These mediators could translate into potential metabolic biomarkers in early arsenic risk assessment and as targets for therapeutic intervention.