A new GIS model for ecologically suitable distributions of medicinal plants

UHPLC-QTOF-MS-Based Targeted Metabolomics Provides Novel Insights into the Accumulative Mechanism of Soil Types on the Bioactive Components of Salvia miltiorrhiza

The root of Salvia miltiorrhiza Bunge (SMB) has been widely used to treat cardiovascular diseases. However, the contents of secondary metabolites in the roots from different production areas are significantly different, and the impact of soil factors on this accumulation remains unclear. Therefore, this study aimed to elucidate the regularity of variation between the active components and soil factors through targeted metabolomics and chemical dosimetry. Soils were collected from five different cities (A, B, C, D, and E) and transplanted into the study area. The results showed that there were significant differences in the soil fertility characteristics and heavy metal pollution levels in different soils. Ten water- and twelve lipid-soluble metabolites were identified in SMBs grown in all soil types. SMBs from D cities exhibited the highest total tanshinone content (p < 0.05). The salvianolic acid B content in SMBs from E cities was the highest (p < 0.05). Interestingly, correlation analysis revealed a significant negative correlation between the accumulation of lipid-soluble and water-soluble metabolites. Double-matrix correlation analysis demonstrated that available potassium (AK) was significantly negatively correlated with salvianolic acid B (r = -0.80, p = 0.0004) and positively correlated with tanshinone IIA (r = 0.66, p = 0.008). Conversely, cadmium (Cd) and cuprum (Cu) were significantly positively and negatively correlated with salvianolic acid B (r = 0.96, p < 0.0001 and r = 0.72, p = 0.0024) and tanshinone IIA (r = 0.40, p = 0.14 and r = 0.73, p = 0.0018), respectively. Mantel's test indicated that AK (r > 0.52, p < 0.001), Cu (r > 0.60, p < 0.005), and Cd (r > 0.31, p < 0.05) were the primary drivers of the differences in the active components of SMBs. These findings provide a theoretical framework for modulating targeted metabolites of SMB through soil factors, with significant implications for the cultivation and quality control of medicinal plants.

Potential impacts of climate change on the geographic distribution of Achillea eriophora DC., a medicinal species endemic to Iran in southwestern Asia

Climate change is considered to rank among the most important global issues affecting species' geographic distributions and biodiversity. Understanding effects of climate change on species can enhance conservation efficacy. In this study, we applied ecological niche modeling (ENM) using maximum entropy (MaxEnt) approaches to predict the potential geographic distribution of Achillea eriophora DC., a medicinal plant species to Iran in southwestern Asia, under current and future climate scenarios. We evaluated potential distributional areas of the species, under two shared socioeconomic pathways (SSP2-4.5 and SSP5-8.5) for the period 2041-2060. Most current potential suitable areas were identified for A. eriophora in montane regions. Our results anticipated that the potential distribution of A. eriophora will expand geographically toward higher elevations and northward. However, the species is expected to experience relatively high losses of suitability in its actual habitats under future climate scenarios. Consequently, we recommend regional-to-national conservation action plans for A. eriophora in its natural habitats.

Mapping of soil suitability for medicinal plants using machine learning methods

Inadequate conservation of medicinal plants can affect their productivity. Traditional assessments and strategies are often time-consuming and linked with errors. Utilizing herbs has been an integral part of the traditional system of medicine for centuries. However, its sustainability and conservation are critical due to climate change, over-harvesting and habitat loss. The study reveals how machine learning algorithms, geographic information systems (GIS) being a powerful tool for mapping and spatial analysis, and soil information can contribute to a swift decision-making approach for actual forethought and intensify the productivity of vulnerable curative plants of specific regions to promote drug discovery. The data analysis based on machine learning and data mining techniques over the soil, medicinal plants and GIS information can predict quick and effective results on a map to nurture the growth of the herbs. The work incorporates the construction of a novel dataset by using the quantum geographic information system tool and recommends the vulnerable herbs by implementing different supervised algorithms such as extra tree classifier (EXTC), random forest, bagging classifier, extreme gradient boosting and k nearest neighbor. Two unique approaches suggested for the user by using EXTC, firstly, for a given subregion type, its suitable soil classes and secondly, for soil type from the user, its respective subregion labels are revealed, finally, potential medicinal herbs and their conservation status are visualised using the choropleth map for classified soil/subregion. The research concludes on EXTC as it showcases outstanding performance for both soil and subregion classifications compared to other models, with an accuracy rate of 99.01% and 98.76%, respectively. The approach focuses on serving as a comprehensive and swift reference for the general public, bioscience researchers, and conservationists interested in conserving medicinal herbs based on soil availability or specific regions through maps.

The contemporary nexus of medicines security and bioprospecting: a future perspective for prioritizing the patient

Reacting to the challenges presented by the evolving nexus of environmental change, defossilization, and diversified natural product bioprospecting is vitally important for advancing global healthcare and placing patient benefit as the most important consideration. This overview emphasizes the importance of natural and synthetic medicines security and proposes areas for global research action to enhance the quality, safety, and effectiveness of sustainable natural medicines. Following a discussion of some contemporary factors influencing natural products, a rethinking of the paradigms in natural products research is presented in the interwoven contexts of the Fourth and Fifth Industrial Revolutions and based on the optimization of the valuable assets of Earth. Following COP28, bioprospecting is necessary to seek new classes of bioactive metabolites and enzymes for chemoenzymatic synthesis. Focus is placed on those performance and practice modifications which, in a sustainable manner, establish the patient, and the maintenance of their prophylactic and treatment needs, as the priority. Forty initiatives for natural products in healthcare are offered for the patient and the practitioner promoting global action to address issues of sustainability, environmental change, defossilization, quality control, product consistency, and neglected diseases to assure that quality natural medicinal agents will be accessible for future generations.

Assessment of Carbon Sequestration Capacity of E. ulmoides in Ruyang County and Its Ecological Suitability Zoning Based on Satellite Images of GF-6

Eucommia ulmoides Oliver. (E. ulmoides) is a species of small tree native to China. It is a valuable medicinal herb that can be used to treat Alzheimer's disease, diabetes, hypertension, and other diseases. In addition, E. ulmoides is a source of rubber. It has both medicinal and ecological value. As ecological problems become increasingly prominent, accurate information on the cultivated area of E. ulmoides is important for understanding the carbon sequestration capacity and ecological suitability zoning of E. ulmoides. In previous tree mapping studies, no studies on the spectral characteristics of E. ulmoides and its remote sensing mapping have been seen. We use Ruyang County, Henan Province, China, as the study area. Firstly, using the 2021 Gao Fen-6 (GF-6) Wide Field of View (WFV) time series images covering the different growth stages of E. ulmoides based on the participation of red-edge bands, several band combination schemes were constructed. The optimal time window to identify E. ulmoides was selected by calculating the separability of E. ulmoides from other land cover types for different schemes. Secondly, a random forest algorithm based on several band combination schemes was investigated to map the E. ulmoides planting areas in Ruyang County. Thirdly, the annual NPP values of E. ulmoides were estimated using an improved Carnegie Ames Stanford Approach (CASA) to a light energy utilization model, which, in turn, was used to assess the carbon sequestration capacity. Finally, the ecologically suitable distribution zone of E. ulmoides under near current and future (2041-2060) climatic conditions was predicted using the MaxEnt model. The results showed that the participation of the red-edge band of the GF-6 data in the classification could effectively improve the recognition accuracy of E. ulmoides, making its overall accuracy reach 96.62%; the high NPP value of E. ulmoides was mainly concentrated in the south of Ruyang County, with a total annual carbon sequestration of 540.104835 t CM-2·a-1. The ecological suitability zone of E. ulmoides can be divided into four classes: unsuitable area, low suitable area, medium suitable area, and high suitable area. The method proposed in this paper applies to the real-time monitoring of E. ulmoides, highlighting its potential ecological value and providing theoretical reference and data support for the reasonable layout of E. ulmoides.

A method of motion estimation of segmental ventricular wall with tracking of ultrasonic echocardiogram

BACKGROUND

Ultrasonic echocardiography is commonly used for monitoring myocardial dysfunction. However, it has limitations such as poor quality of echocardiography images and subjective judgment of doctors.

METHODS

In this paper, a calculation model based on optical flow tracking of echocardiogram is proposed for the quantitative estimation motion of the segmental wall. To improve the accuracy of optical flow estimation, a method based on confidence-optimized multiresolution(COM) optical flow model is proposed to reduce the estimation errors caused by the large amplitude of myocardial motion and the presence of "shadows" and other image quality problems. In addition, motion vector decomposition and dynamic tracking of the ventricular region of interest are used to extract information regarding the myocardial segmental motion. The proposed method was validated using simulation images and 50 clinical cases (25 patients and 25 healthy volunteers) for myocardial motion analysis.

RESULTS

The results demonstrated that the proposed method could track the motion information of myocardial segments well and reduce the estimation errors of optical flow caused due to the use of low-quality echocardiogram images.

CONCLUSIONS

The proposed method improves the accuracy of motion estimation for the cardiac ventricular wall.

Climate change impacts on optimal habitat of Stachys inflata medicinal plant in central Iran

Stachys inflata Benth. is a perennial shrub plant, with powerful natural antioxidant agents, which is recognized as a famous medicinal plant that is widely applied to treat Infection, Asthma, and Rheumatism. Iran is renowned as a center of diversity for Stachys, however, the ideal habitats of S. inflata in this nation remain unknown. The potential and future distribution of suitable habitats for S. inflata were projected using an ensembles ecological niche model in Isfahan province, Iran. We used occurrence data (using GPS), bioclimatic and topographic variables from the Chelsa and WorldClim databases to model the current and future potential distribution of this valuable species. The results showed that: (i) S. inflata is mainly distributed in the south, southwest, center, and west of the Isfahan province, and the excellent habitats of S. inflata accounted for 14.34% of the 107,000 km² study area; (ii) mean annual temperature, mean daily temperature of wettest quarter, annual precipitation, and elevation were the four most important variables that affect the distribution of S. inflata, with a cumulative contribution of 56.55%; and (iii) about the half (- 42.36%) of the currently excellent habitats of S. inflata show a tendency to decrease from now to the 2080s, while often the area of other S. inflata habitats increases (the area of unsuitable habitat: 5.83%, the area of low habitat suitability: 24.68%, the area of moderate habitat suitability: 2.66%, and the area of high habitat suitability: 2.88%). The increase in the area of other S. inflata habitats is different and they are less favorable than the excellent habitat. The results help establishing a framework for long-term in-situ and ex-situ conservation and management practices in habitats of S. inflata in rangeland and agricultural ecosystems.

The biology of medicinal resource substitution in Salvia

BACKGROUND

The decrease of wild reserves and the sharp increase of market demand have led to resource substitution, but it is still not clear how to discover medicinal alternative resources. Here we reveal the biology of medicinal resource substitution in the case of Salvia.

METHODS

A hypothesis was put forward that phylogeny and ecology were the main factors which determined alternative species selection. Phylogenetic analysis was performed based on chloroplast genomes. Spatial climatic pattern was assessed through three mathematical models.

RESULTS

Salvia miltiorrhiza and alternative species were mainly located in Clade 3 in topology, and their growth environment was clustered into an independent group 3 inferred from principal component analysis. Correlation and Maxent major climate factor analyses showed that the ecological variations within each lineage were significantly smaller than the overall divergent between any two lineages. Mantel test reconfirmed the inalienability between phylogeny and ecology (P = 0.002). Only the species that are genetically and ecologically related to S. miltiorrhiza can form a cluster with it.

CONCLUSIONS

Phylogenetic relationship and geographical climate work together to determine which species has the potential to be selected as substitutes. Other medicinal plants can learn from this biology towards developing alternative resources.

A geospatial database management system for the collection of medicinal plants

Medicinal plants are increasingly used, both for medical applications and personal healthcare. However, existing herbal database systems for plant retrieval offer only basic information and do not support real-time analysis of the spatial aspects of plantations and distribution sites. Moreover, data records are usually static and not publicly available as they rely on costly proprietary software packages. To address these shortcomings, including limiting the time needed for collection and data processing, a novel medicinal plants geospatial database management system is proposed. The system allows localization of plant sites and data presentation on an interactive heat map displaying spatial information of plants selected by the user within a specific radius from the user's location, including automatic presentation of an itinerary giving the optimal route between user location and plant destinations selected. The approach relies on dynamic and role-based data management, an interactive map that includes graphics and integrated geospatial analyses thanks to cross-platform, geographical a JavaScript library and Google API. Both spatial data and attributes are available in real time. The system would support effective collaboration, among herb farmers, government agencies, private investors, healthcare professionals and the general public with regard to various aspects of medicinal plants and their applications.

Prediction of the globally ecological suitability of Panax quinquefolius by the geographic information system for global medicinal plants (GMPGIS)

American ginseng (Panax quinquefolius L.) is a well-known Asian traditional herbal medicine with a large market demand. The plant is native to eastern North America, and its main producing areas worldwide are decreasing due to continuous cropping obstacles and environmental changes. Therefore, the identification of maximum similarities of new ecological distribution of P. quinquefolius, and prediction of its response to climate change in the future are necessary for plant introduction and cultivation. In this study, the areas with potential ecological suitability for P. quinquefolius were predicted using the geographic information system for global medicinal plants (GMPGIS) based on 476 occurrence points and 19 bioclimatic variables. The results indicate that the new ecologically suitable areas for P. quinquefolius are East Asia and the mid-eastern Europe, which are mainly distributed in China, Russia, Japan, Ukraine, Belarus, North Korean, South Korea, andRomania. Under global climate change scenarios, the suitable planting areas for P. quinquefolius would be increased by 9.16%-30.97%, and expandingnorth and west over the current ecologically suitable areas by 2070. The potential increased areas that are ecologically suitable include northern Canada, Eastern Europe, and the Lesser Khingan Mountains of China, and reduced regions are mainly in central China, the southern U.S., and southern Europe. Jackknife tests indicate that the precipitation of the warmest quarter was the important climatic factor controlling the distribution of P. quinquefolius. Our findings can be used as auseful guide for P. quinquefolius introduction and cultivation in ecologically suitable areas.