Medicinal plants as immune booster in the palliative management of viral diseases: A perspective on coronavirus

Stimulatory effects of Lycium shawii on human melanocyte proliferation, migration, and melanogenesis: In vitro and in silico studies

There is no first-line treatment for vitiligo, a skin disease characterized by a lack of melanin produced by the melanocytes, resulting in an urgent demand for new therapeutic drugs capable of stimulating melanocyte functions, including melanogenesis. In this study, traditional medicinal plant extracts were tested for cultured human melanocyte proliferation, migration, and melanogenesis using MTT, scratch wound-healing assays, transmission electron microscopy, immunofluorescence staining, and Western blot technology. Of the methanolic extracts, Lycium shawii L. (L. shawii) extract increased melanocyte proliferation at low concentrations and modulated melanocyte migration. At the lowest tested concentration (i.e., 7.8 μg/mL), the L. shawii methanolic extract promoted melanosome formation, maturation, and enhanced melanin production, which was associated with the upregulation of microphthalmia-associated transcription factor (MITF), tyrosinase, tyrosinase-related protein (TRP)-1 and TRP-2 melanogenesis-related proteins, and melanogenesis-related proteins. After the chemical analysis and L. shawii extract-derived metabolite identification, the in silico studies revealed the molecular interactions between Metabolite 5, identified as apigenin (4,5,6-trihydroxyflavone), and the copper active site of tyrosinase, predicting enhanced tyrosinase activity and subsequent melanin formation. In conclusion, L. shawii methanolic extract stimulates melanocyte functions, including melanin production, and its derivative Metabolite 5 enhances tyrosinase activity, suggesting further investigation of the L. shawii extract-derived Metabolite 5 as a potential natural drug for vitiligo treatment.

Gut microbiota and transcriptome profiling revealed the protective effect of aqueous extract of Tetrastigma hemsleyanum leaves on ulcerative colitis in mice

Tetrastigma hemsleyanum, a traditional Chinese medicinal plant, possesses various biological activities, including anti-inflammatory and immunomodulatory functions. The purpose of this study was to determine the alleviating effect of the water extract of Tetrastigma hemsleyanum leaves (THLW) on ulcerative colitis (UC) and its relationship with gut microbiota. The administration of THLW significantly decreased the severity of dextran sulfate sodium (DSS)-induced intestinal damage, as demonstrated by the stabilization of body weight and colon length, and decreased disease activity index (DAI) and histological scores. THLW also decreased NF-κB protein expression in colon tissues and reduced the serum levels of IL-6, IL-1β, and TNF-α. Further co-housing experiment confirmed that the anti-UC effect of THLW was possibly by regulating the structure and composition of gut microbiota, including increasing the abundance of Oscillospiraceae, Prevotellaceae and Corynebacterium. Additionally, the expression of genes related to inflammation and immunity was also regulated by THLW treatment as evidenced by transcriptome analysis. These results suggested that the protective effect of THLW on DSS-induced colitis was mediated by alleviating inflammation and modulating the microbiota composition. This work proved the potent protective effects of THLW treatment on colitis and may have potential for UC relief.

Identification of Suitable Drug Combinations for Treating COVID-19 Using a Novel Machine Learning Approach: The RAIN Method

Simple Summary

This study follows an improved approach to systematic reviews, called the Systematic Review and Artificial Intelligence Network Meta-Analysis (RAIN), registered within PROSPERO (CRD42021256797), in which, the PRISMA criterion is still considered. Drugs used in the treatment of COVID-19 were searched in the databases of ScienceDirect, Web of Science (WoS), ProQuest, Embase, Medline (PubMed), and Scopus. In addition, using artificial intelligence and the measurement of the p-value between human genes affected by COVID-19 and drugs that have been suggested by clinical experts, and reported within the identified research papers, suitable drug combinations are proposed for the treatment of COVID-19. During the systematic review process, 39 studies were selected. Our analysis shows that most of the reported drugs, such as azithromycin and hydroxyl-chloroquine on their own, do not have much of an effect on the recovery of COVID-19 patients. Based on the result of the new artificial intelligence, on the other hand, at a significance level of less than 0.05, the combination of the two drugs therapeutic corticosteroid + camostat with a significance level of 0.02, remdesivir + azithromycin with a significance level of 0.03, and interleukin 1 receptor antagonist protein + camostat with a significance level 0.02 are considered far more effective for the treatment of COVID-19 and are therefore recommended.

Abstract

COVID-19 affects several human genes, each with its own p-value. The combination of drugs associated with these genes with small p-values may lead to an estimation of the combined p-value between COVID-19 and some drug combinations, thereby increasing the effectiveness of these combinations in defeating the disease. Based on human genes, we introduced a new machine learning method that offers an effective drug combination with low combined p-values between them and COVID-19. This study follows an improved approach to systematic reviews, called the Systematic Review and Artificial Intelligence Network Meta-Analysis (RAIN), registered within PROSPERO (CRD42021256797), in which, the PRISMA criterion is still considered. Drugs used in the treatment of COVID-19 were searched in the databases of ScienceDirect, Web of Science (WoS), ProQuest, Embase, Medline (PubMed), and Scopus. In addition, using artificial intelligence and the measurement of the p-value between human genes affected by COVID-19 and drugs that have been suggested by clinical experts, and reported within the identified research papers, suitable drug combinations are proposed for the treatment of COVID-19. During the systematic review process, 39 studies were selected. Our analysis shows that most of the reported drugs, such as azithromycin and hydroxyl-chloroquine on their own, do not have much of an effect on the recovery of COVID-19 patients. Based on the result of the new artificial intelligence, on the other hand, at a significance level of less than 0.05, the combination of the two drugs therapeutic corticosteroid + camostat with a significance level of 0.02, remdesivir + azithromycin with a significance level of 0.03, and interleukin 1 receptor antagonist protein + camostat with a significance level 0.02 are considered far more effective for the treatment of COVID-19 and are therefore recommended. Additionally, at a significance level of less than 0.01, the combination of interleukin 1 receptor antagonist protein + camostat + azithromycin + tocilizumab + oseltamivir with a significance level of 0.006, and the combination of interleukin 1 receptor antagonist protein + camostat + chloroquine + favipiravir + tocilizumab7 with corticosteroid + camostat + oseltamivir + remdesivir + tocilizumab at a significant level of 0.009 are effective in the treatment of patients with COVID-19 and are also recommended. The results of this study provide sets of effective drug combinations for the treatment of patients with COVID-19. In addition, the new artificial intelligence used in the RAIN method could provide a forward-looking approach to clinical trial studies, which could also be used effectively in the treatment of diseases such as cancer.

A Simple and Reliable Dispersive Liquid-Liquid Microextraction with Smartphone-Based Digital Images for Determination of Carbaryl Residues in Andrographis paniculata Herbal Medicines Using Simple Peroxidase Extract from Senna siamea Lam. Bark

A simple and reliable dispersive liquid-liquid microextraction (DLLME) coupled with smartphone-based digital images using crude peroxidase extracts from cassia bark (Senna siamea Lam.) was proposed to determine carbaryl residues in Andrographis paniculata herbal medicines. The method was based on the reaction of 1-naphthol (hydrolysis of carbaryl) with 4-aminoantipyrine (4-AP) in the presence of hydrogen peroxide, using peroxidase enzyme simple extracts from cassia bark as biocatalysts under pH 6.0. The red product, after preconcentration by DLLME using dichloromethane as extraction solvent, was measured for blue intensity by daily life smartphone-based digital image analysis. Under optimized conditions, good linearity of the calibration graph was found at 0.10–0.50 mg·L⁻¹ (r² = 0.9932). Limits of detection (LOD) (3SD/slope) and quantification (LOQ) (10SD/slope) were 0.03 and 0.09 mg·L⁻¹, respectively, with a precision of less than 5%. Accuracy of the proposed method as percentage recovery gave satisfactory results. The proposed method was successfully applied to analyze carbaryl in Andrographis paniculata herbal medicines. Results agreed well with values obtained from the HPLC-UV method at 95% confidence level. This was simple, convenient, reliable, cost-effective and traceable as an alternative method for the determination of carbaryl.