Evidence-Based Complementary and Alternative Medicine

Parrotia persica is one of the endemic plants in Iran and belongs to the Hamamelidaceae family. A wide range of biological activities of this plant have been attributed to several phenolic compounds. In this study, the phenolic bioactive compounds extraction from P. persica leaves was performed using conventional and ultrasonic-assisted extraction (UAE) techniques through the response surface methodology (RSM) to optimize the best extraction conditions and reach the maximum amount of phenolic compounds. The central composite design (CCD) was conducted for the optimization of four extraction parameters, including extraction time, alcohol concentration, solvent-to-solid ratio, and temperature. The coding of parameters was performed as an independent variable at five levels. Quantitative and qualitative assessments were achieved by using HPLC, LC-MS, and UV-Vis spectrophotometry. According to the results, UAE was chosen as the best method with the optimal extraction values: 15 min as an extraction time, 40% alcohol portion in solvent, solvent-to-solid ratio equal to 30 : 1, and 25°C for temperature. In this regard, it was found that the similarity of experimental to predicted findings was 98.7% for the phenolic content and 94.9% for the mass extract in the UAE method. The findings showed a good similarity between the experimental and predicted values, and no significant changes were observed between the real and theoretical results. In addition, our finding revealed that the optimum extraction yield was 28.5% for the mass extract in the UAE optimization process. Furthermore, the antioxidant activity by DPPH assay indicates that the extract which was obtained using UAE in optimum condition, proposed remarkable antioxidant activity (IC₅₀ 29.86 μg·ml⁻¹). Moreover, the cytotoxic assay was performed against PC-3 cancer cells, and it was found that the optimized extract using UAE has a promising cytotoxic activity (IC₅₀ 10.4 μg·ml⁻¹) without toxicity toward normal cells. Since there is a possibility to use P. persica as one of the commercial herbal sources, the optimized extraction models could be utilized for scaling up the phenolic compound extraction from P. persica leaf.

Existing research combines acupuncture theory with network science and proposes a new paradigm for the study of acupoint selection patterns—a key acupoint mining algorithm based on acupoint networks. However, the basic idea of this study for finding key acupoints is based on binary acupoint synergy relationships, which ignores the higher-order synergy among multiple acupoints and does not truly reflect the implicit patterns of each acupoint among meridian systems. Moreover, the mining results assessment method, which this new paradigm involves, does not have wide applicability and universality. In this paper, with the introduction of higher-order interactions between multiple acupoints, a high-specificity key acupoint mining algorithm based on 3-node motif is proposed in the acupoint-disease network (ADN). In response to the narrow applicability of the new research paradigm involving the evaluation of algorithms’ measures, new and widely applicable and universal evaluation criteria are introduced in terms of resolution, network loss, and accuracy, respectively. Based on the principles of acupoint selection involved in acupuncture clinics in Chinese medicine, the acupoints involved in the data were divided into a total of 19 regions according to their distribution characteristics. From these 19 regions, we selected the key acupoints that have a large impact on the global network. Finally, we compared this algorithm with five other acupoint importance assessment algorithms in terms of resolution, network loss, and accuracy, respectively. The comprehensive results show that the algorithm identifies key acupoints with an accuracy of 63%, which is 14% to 21% higher than other existing methods. The key acupoints identified by the algorithm have a significant disruptive effect on the connectivity of the network, indicating that the key acupoints are at the core of the acupoint-disease network topology. They have a significant propagation influence on other acupoints, which means that the key acupoints have high-synergistic cooperation with other acupoints. Meanwhile, the stability and specificity of the algorithm ensure the reliability of the key acupoints. We believe that the key acupoints identified by the algorithm can be used as core acupoints from the perspective of network topology and high synergy of other acupoints, respectively, and help researchers explore targeted and high-impact combinations of acupoints to optimize existing acupuncture prescriptions under condition constraints.

In the present study, the diversity of medicinal plants and associated traditional medicinal knowledge of the rural community in the Ameya district in Ethiopia was assessed and documented. A survey was conducted through semistructured interviews, guided field walks, focus group discussions, and field observations. The snowball and purposeful sampling techniques were employed to select general and knowledgeable informants, respectively. Accordingly, a total of 210 respondents, 156 (74.3%) males and 54 (25.7%) females, were participated in this study. The informants were selected from seven kebeles (the lowest administrative units) following the recommendations of the local community for the availability of traditional medicinal plant use practice. Descriptive statistics, preference ranking, fidelity level, informant consensus factor, and direct matrix ranking were used to analyze and present the data. A total of 78 medicinal plants represented in 70 genera and 40 families were identified. Croton macrostachyus and Dodonaea viscosa were the most preferred species used to treat wounds, whereas Cucumis ficifolius and Phragmanthera macrosolen were the most popular species applied to treat stomachache. Leaves (38%) and roots (20%) were the most predominantly used plant parts for remedial preparation to treat 42 human ailments. The informant consensus factor (ICF) value ranged between 0.45 and 0.81, with the respiratory diseases category scoring the highest ICF value. The fidelity level (FL) value for the medicinal plants ranged from 24 to 95%. Considerable proportions (55.5%) of the medicinal plants were collected from wild habitats. Higher ICF (0.81) and FL (>90%) scores indicate the presence of rich traditional knowledge in the community. This knowledge can be used to select medicinal plants (such as Croton macrostachyus, Cucumis ficifolius, Dodonaea viscosa, and Phragmanthera macrosolen) for further pharmacological and phytochemical studies.

Since Bulgarian rose damascena oil is known for its anti-inflammatory, antioxidant, and antimicrobial properties, we investigated its antifungal activity against the species of Candida, which are among the most common opportunistic fungal pathogens. Our disk-diffusion assay revealed that Bulgarian rose damascena oil effectively inhibited the growth of Candida albicans along with various bacteria. The minimum inhibitory and fungicidal concentrations against Candida albicans and Candida glabrata were all 0.25%. Under our experimental conditions, Bulgarian rose damascena oil showed better inhibitory effects on Candida glabrata and Candida albicans than several popular essential oils reported to have antifungal activity other than Origanum vulgare oil. Interestingly, Bulgarian rose damascena oil showed better antifungal activity against Candida species at acidic pH and induced cell death of Candida species in the culture medium, with cell death seen in 25–35% of the cells exposed to 0.05% Bulgarian rose damascena oil. Furthermore, Bulgarian rose damascena oil inhibited the hyphal growth of Candida albicans cultured in the RPMI medium with fetal bovine serum. These findings collectively suggest that Bulgarian rose damascena oil has antifungal activity against Candida species and thus could potentially be developed in novel therapies for vaginitis-causing pathogenic fungi.

Doxorubicin-induced cardiomyopathy (DICM) is associated with a poor prognosis, and effective therapeutic drug candidates have yet to be identified. Furthermore, whether basic animal models reflect the clinical pathogenesis of DICM should be carefully examined. Although the exact mechanisms underlying the development of DICM are complex and remain unclear, oxidative stress is strongly implicated as a contributing factor. Therefore, we investigated the effects of ginseng (the root of Panax ginseng: Gin), an inexpensive and safe drug with antioxidant properties. We previously conducted a meta-analysis that yielded results suggesting its efficacy in humans. However, this study did not examine the efficacy of ginseng in detail. Therefore, this study investigated the efficacy of red ginseng (steamed and dried ginseng cultivated for over six years; RGin) in a mouse model of chronic DICM to elucidate its potential therapeutic benefits. RGin prevented the decrease in left ventricular ejection fraction associated with doxorubicin (DXR) administration and prolonged survival in DBA/2 mice. In addition, RGin reduced DXR-induced cardiomyocyte damage. These findings highlight its potential as a therapeutic option for the treatment of DICM.

Background. Diarrheal illness is the second-most common cause of death in under-five children. Worldwide, it results in about 1.7 billion illnesses and 525,000 deaths among under-five children annually. It is the leading cause of malnutrition among under-five children. Different people use medicinal plants to treat diarrhea. The present study aimed to review the medicinal plants used to treat diarrhea by the people in the Amhara region and to diagnose whether the antidiarrheal activities of the medicinal plants have been confirmed by studies using animal models. Methods. The author searched 21 articles from worldwide databases up to December 2022 using Boolean operators (“AND” and “OR”) and the terms “ethnobotanical studies,” “ethnobiology,” “traditional medicine,” “ethnobotanical knowledge,” and “Amhara region.” Results. From the 21 studies reviewed, 50 plant species grouped into 28 families were reported to treat diarrhea by the people in the Amhara region. The top most used families were Lamiaceae (12%), Fabaceae (8%), Asteraceae, Cucurbitaceae, Euphorbiaceae, and Poaceae (6% each). The modes of administration of the plant parts were orally 98.88% and topically 1.12%. The different extracts of 18 (or 36%) of the medicinal plants traditionally used to treat diarrhea by the people in the Amhara region have been proven experimentally in animal models. Conclusions. The people in the Amhara region use different medicinal plants to treat diarrhea. Most of them take the medicinal plants orally. The traditional claim that 60% of medicinal plants are antidiarrheal has been confirmed in in vitro studies.