Understory planting of medicinal plants is a new planting mode that connects Chinese herbal medicine(CHM) with forest resources.The complex and variable understory environmental factors will inevitably affect the yield and quality of understory CHM.This research summarized the research progress on understory planting of medicinal plants based on forest types and environmental factors within the forest from the perspectives of understory light, air temperature and humidity, soil characteristics, and the interaction between crops within the forest.The results showed that the complex and variable light, temperature and humidity, and soil factors(such as fertility, acidity and alkalinity, and microorganisms) under the forest could affect the yield and quality of medicinal plants to varying degrees through physiological activities such as photosynthesis and respiration, resulting in a significant increase or decrease in yield and quality compared to open field cultivation.In addition, the competition or mutual benefit between different crops within the forest could lead to differences in the yield and quality of understory medicinal plants compared to open field cultivation.A reasonable combination of planting could achieve resource sharing and complementary advantages.Therefore, conducting systematic research on the effects of understory environmental factors on the yield and content of medicinal plants with different growth and development characteristics can provide theoretical guidance and technical references for formulating comprehensive strategies for understory planting of medicinal plants, such as selecting suitable medicinal plant varieties, optimizing planting density, and conducting reasonable forest management, thus contributing to the sustainable development and ecological protection of CHM.
Plants, Medicinal/growth & development* ; Forests ; Soil/chemistry* ; Environment ; Ecosystem ; Temperature

The natural forest and artificial shed are the main cropping modes of Coptis chinensis. This study is aimed to reveal the rhizosphere soil bacterial community structure difference between under tow C. chinensis cropping modes-natural forest and artificial shed, and to assist us to completely understand soil quality condition,and provide theoretical guidance for soil improvement and C. chinensis planting. The rhizosphere soil samples of 1-5-year-old C. chinensis under tow cropping modes-natural forest and artificial shed were collected. Illumina high-throughput sequencing technology was used to analyze the alpha diversity, community composition, community structure of soil bacteria under the tow cropping modes,and the effects of soil nutriment indices on soil bacterial community structure. Through the analysis of species number, Shannon, Chao1 index and ACE index of bacterial community, it was found that the bacterial diversity of 1-year-old C. chinensis soil under natural forest cropping mode was significantly lower than that under artificial shed cropping mode, and the diversity of bacterial communities in soil of 2-5-years old C. chinensis were not significant different between two cropping modes. A total of 53 phyla,60 classes,140 orders and 266 families were detected in the rhizosphere soil of C. chinensis under the cropping modes of natural forest, respectively. The rhizosphere soil of C. chinensis under the cropping modes of artificial shed included 54 phyla,65 classes,140 orders and 264 families, respectively. Under the two cropping modes, the top 10 dominant species of bacterial community abundance are the same, they are Proteobacteria, Acidobacteria, Actinobacteria,Bacteroidetes, Planctomycetes, Chloroflexi, Verrucomicrobia, Gemmatimonadetes, Firmicutes and Cyanobacteria, but there are differences in the abundance sequence. The top 10 dominant species of bacterial community abundance accounted for 74.36% to 74.30% of the total bacteria, and 3.15% to 3.92% of the bacteria are unclassified. The results of Metastat analysis showed that the abundance of Gemmatimonadetes in the rhizosphere soil of C. chinensis under the cropping modes the artificial shed was significantly higher than that under the natural forest cropping mode(P<0.05). MRPP analysis of community structure differences showed that under tow cropping modes, there were significant differences in the bacterial community structure of 1-4-year-old soil bacteria, among which the difference between 1-year-old soil samples was the largest. With the increase of cropping years, the difference gradually decreases, and there is no significant difference in the bacterial community structure between 5-year-old soil samples. RDA analysis and correlation analysis of bacterial community structure and soil physical and chemical properties showed that the order of environmental factors on the rhizosphere soil bacteria of Coptis chinensis was: pH>available P> total P> total K>bulk density>total N>available N>organic matter. The results are helpful to understand the soil health of C. chinensis and provide scientific basis and theoretical guidance for soil improvement and C. chinensis planting.
Child, Preschool ; Coptis ; Forests ; Humans ; Infant ; Rhizosphere ; Soil ; Soil Microbiology

Dendrobium huoshanense is a precious medicinal plant belonging to Dendrobium of Orchidaceae. It is a special medicinal material and extremely scarce in Huoshan county, Anhui province. At present, D. huoshanense has been greatly protected, which also makes it possible to industrialize relying on tissue culture and artificial cultivation technology. Three main planting methods were utilized for cultivating D. huoshanense including facility cultivation, under forest cultivation and simulative habitat cultivation. Firstly, the three cultivation modes and technical characteristics of D. huoshanense were compared and analyzed, and it was found that the ecological environment of D. huoshanense cultivated in the simulated environment was closer to that of wild D. huoshanense. Secondly, based on comparing the characters and quality of three cultivation modes, the results showed that the shape of D. huoshanense cultivated in simulated environment was more similar to that of "grasshopper thigh" recorded in Bencao Jing Jizhu, and its quality was better than that of facilities and under forest cultivation. The comprehensive benefit comparison of three modes showed that the simulated cultivation had high income, the lowest input-output ratio and significant economic benefit. The quality of cultivated D. huoshanense was further evaluated from four aspects of "excellent environment" "excellent shape" "high quality" "excellent effect", which summarized the comprehensive advantages of simulative habitat cultivation of D. huoshanense as follows: the original habitat and site environment of simulated wild D. huoshanense, the closer shape to the wild, the more content of main medicinal components, and higher economic benefit and better efficacy. The quality of D. huoshanense was improved by the use of simulative habitat cultivation, which has practical significance to guide its large-scale cultivation.
Dendrobium ; Ecosystem ; Forests ; Plants, Medicinal

The ecological environment is closely related to the growth and quality of authentic medicinal materials. Ginseng is very strict with its natural environment and grows mostly in the damp valleys of forests, and the appearance and chemical composition of ginseng under different growth environments are very different. This article reviews the effects of different ecological factors(including light, temperature, altitude, moisture, soil factors, etc.)on the appearance and chemical composition(mainly ginsenosides) of ginseng. Through systematic review, it is found that soil physical factors are the most important ecological factors that affect the appea-rance of ginseng, and soil bulk density plays a key role; temperature affects ginsenosides in ginseng medicinal materials The dominant ecological factors for the accumulation of chemical ingredents; strong light, high altitude, high soil moisture, low soil nutrient and strong acid soil can influence the accumulation of secondary metabolites in ginseng. Environmental stress can also stimulate the formation and accumulation of secondary metabolites in medicinal plants. Appropriate low temperature stress, high or low water stress, acid or alkali stress can also promote the accumulation of ginsenosides. This article systematically reviews the ecological factors that affect the appearance and chemical composition of ginseng, and clarifies the dominant ecological factors and limiting factors for the formation of ginseng's appearance and quality, as well as beneficial environmental stress factors, in order to provide a theoretical basis for ginseng ecological planting and ginseng quality improvement.
Forests ; Ginsenosides ; Panax ; Plants, Medicinal ; Soil

This study is aimed to reveal the rhizosphere soil fungal community structure difference of Coptis chinensis cropping between natural forest and artificial shed modes, and provide theoretical guidance for soil improvement and C. chinensis planting. The rhizosphere soil samples of 1-5-year-old C. chinensis under natural forest and artificial shed modes were collected. Illumina high-throughput sequencing technology was used to analyze the community structure and diversity of soil fungi under the tow cropping modes,and the effects of soil nutriment indices on soil fungal community structure. The results suggested that the abundance and diversity of fungal communities in soil of 2-5-year-old C. chinensis were not significant different in both two cropping modes, but it was significantly higher than that in the 1-year-old C. chinensis. Comparing soil samples from the same year-old C. chinensis under the two cropping modes, it was found that there was no significant difference in the abundance and diversity of fungal communities. The fungal community of the rhizosphere soil was different in composition and abundance between tow cropping modes, and between different planting years. The 17 phyla,59 classes and 155 orders,and 17 phyla,59 classes and 157 orders were detected in the rhizosphere soil of C. chinensis under the cropping modes of natural forest and the artificial shed, respectively. Ascomycota, Basidiomycota and Mortierellomycota were dominant phyla in rhizosphere soil, and the average abundance of the 3 phyla accounted for 74.36% and 74.30% of the total fungi. The results of analysis of similarities showed that there were significant differences in the fungal community structure of 1-year-old and 2-year-old C. chinensis soil fungi, and there was no significant difference in the community structure of 3-5-year-old samples. Under the natural forest cropping mode, there were significant differences among the samples of different years. Under the artificial shed cropping, there were significant differences in fungal community structure between 1-year-old and 3-5-year-old C. chinensis soil, and between 2-year-old and 3-5-year-old C. chinensis soil. The results of canonical correlation analysis showed that soil pH and soil organic matter content were the main factors affecting the soil fungal community structure. Soil organic matter content was positively correlated with Basidiomycota and Cryptomycota, pH was negatively correlated with Basidiomycota and C. ryptomycota. The planting of C. chinensis has promoted the diversity and abundance of rhizosphere fungal community significantly. For the same year-old C. chinensis soil, abundance of fungal community was no significant difference between two cropping modes. There are significant differences in the rhizosphere soil fungal community structure between tow cropping modes in the first two years of planting. Through the interaction between the rhizosphere and the soil and the continuous selection of the rhizosphere to the fungal community, the fungal community structure tended to be the same between the two cropping modes in rhizosphere soil of 3-5-year old C. chinensis. The soil pH and orga-nic matter content were the main factors affecting the change of fungal community structure.
Coptis ; Forests ; Fungi ; Mycobiome ; Plant Roots ; Rhizosphere ; Soil ; Soil Microbiology

The aim in this literature review was (1) to explore the physiologically and psychologically therapeutic benefits of forest bathing on adults suffering from pre-hypertension or hypertension, and (2) to identify the type, duration, and frequency of an effective forest bathing intervention in the management of pre-hypertension and hypertension, so as to provide directions for future interventions or research. The electronic databases PubMed, Cochrane Library, CINAHL, PsyINFO, and the China Academic Journals (CAJ) offered through the Full-text Database (CNKI) were searched for relevant studies published from the inception of the databases to April 2019. Of the 364 articles that were identified, 14 met the criteria for inclusion in this review. The synthesis of the findings in the included studies revealed that forest bathing interventions were effective at reducing blood pressure, lowering pulse rate, increasing the power of heart rate variability (HRV), improving cardiac-pulmonary parameters, and metabolic function, inducing a positive mood, reducing anxiety levels, and improving the quality of life of pre-hypertensive or hypertensive participants. Forest walking and forest therapy programs were the two most effective forest bathing interventions. Studies reported that practicing a single forest walking or forest therapy program can produce short-term physiological and psychological benefits. It is concluded that forest bathing, particularly forest walking and therapy, has physiologically and psychologically relaxing effects on middle-aged and elderly people with pre-hypertension and hypertension.
Adult ; Aged ; Aged, 80 and over ; Female ; Forests ; Humans ; Hypertension ; prevention & control ; Male ; Middle Aged ; Prehypertension ; prevention & control ; Relaxation Therapy ; statistics & numerical data ; Young Adult

To clarify the difference of soil moisture characteristics between mixed broad leaf-conifer forest soil and artificial cultivation of Notopterygium incisum, the HYPROP system and the dew point potential meter were used to determine soil water retention curves(SWRC) for samples of two horizons(i.e. 2-7 cm, 10-15 cm). The basic physical and chemical properties of soil and its water characteristic parameters were also determined. The result showed as fllows:①The bulk density of mixed coniferous-broad leaf forest soil was between 0.33 and 0.52 g·cm~(-3), significantly lower than the corresponding value of field soil(1.01-1.18 g·cm~(-3))(P<0.05), While the organic matter content was significantly higher than the corresponding value of field soil(P<0.05). ②The saturated water content(θ_s), field water holding capacity(θ_(FC)) and Water that can be effectively utilized by plants(θ_(PAC)) of mixed coniferous-broadleaved forest soil were significantly higher than the corresponding value of field soil(P<0.05), while the retained water content(θ_r) value that cannot be effectively utilized by plants was significantly lower than that of field soil(P<0.05). ③The values of structural porosity(0.13-0.24 cm~3·cm~(-3)) and Matrix porosity(0.34-0.44 cm~3·cm~(-3)) of mixed coniferous-broadleaved forest soil were higher than the corresponding values of field soil. Therefore, with low bulk density and high content of organic matter, mixed coniferous-broadleaved forest soil can store more water in soil in the form of effective water to meet the needs of plants for water, thus possibly forming high quality medicinal materials of Notopterygii Rhizoma et Radix. In conclusion, the results of this study can provide theoretical basis guidance for soil structure improvement and water management to form high quality medicinal materials in the artificial cultivation of N. incisum.
Apiaceae ; China ; Forests ; Soil ; Tracheophyta ; Water ; analysis

PURPOSE: This study was conducted to obtain data for the development of an effective fall risk assessment tool for pediatric inpatients through a systematic review and meta-analysis of the diagnostic test accuracy of existing scales. METHODS: A literature search using Medline, Science Direct, CINAHL, EMBASE, and the Cochrane Library was performed between March 1 and 31, 2018. Of 890 identified papers, 10 were selected for review. Nine were used in the meta-analysis. Stata version 14.0 was used to create forest plots of sensitivity and specificity. A summary receiver operating characteristic curve was used to compare all diagnostic test accuracies. RESULTS: Four studies used the Humpty Dumpty Falls Scale. The most common items included the patient's diagnoses, use of sedative medications, and mobility. The pooled sensitivity and specificity of the nine studies were .79 and .36, respectively. CONCLUSION: Considering the low specificity of the pediatric fall risk assessment scales currently available, there is a need to subdivide scoring categories and to minimize items that are evaluated using nurses' subjective judgment alone. Fall risk assessment scales should be incorporated into the electronic medical record system and an automated scoring system should be developed.
Accidental Falls ; Diagnosis ; Diagnostic Tests, Routine* ; Electronic Health Records ; Forests ; Humans ; Inpatients* ; Judgment ; Pediatrics ; Risk Assessment* ; ROC Curve ; Sensitivity and Specificity ; Weights and Measures*

BACKGROUND AND OBJECTIVES: Screening and early diagnosis for heart failure (HF) are critical. However, conventional screening diagnostic methods have limitations, and electrocardiography (ECG)-based HF identification may be helpful. This study aimed to develop and validate a deep-learning algorithm for ECG-based HF identification (DEHF). METHODS: The study involved 2 hospitals and 55,163 ECGs of 22,765 patients who performed echocardiography within 4 weeks were study subjects. ECGs were divided into derivation and validation data. Demographic and ECG features were used as predictive variables. The primary endpoint was detection of HF with reduced ejection fraction (HFrEF; ejection fraction [EF]≤40%), and the secondary endpoint was HF with mid-range to reduced EF (≤50%). We developed the DEHF using derivation data and the algorithm representing the risk of HF between 0 and 1. We confirmed accuracy and compared logistic regression (LR) and random forest (RF) analyses using validation data. RESULTS: The area under the receiver operating characteristic curves (AUROCs) of DEHF for identification of HFrEF were 0.843 (95% confidence interval, 0.840–0.845) and 0.889 (0.887–0.891) for internal and external validation, respectively, and these results significantly outperformed those of LR (0.800 [0.797–0.803], 0.847 [0.844–0.850]) and RF (0.807 [0.804–0.810], 0.853 [0.850–0.855]) analyses. The AUROCs of deep learning for identification of the secondary endpoint was 0.821 (0.819–0.823) and 0.850 (0.848–0.852) for internal and external validation, respectively, and these results significantly outperformed those of LR and RF. CONCLUSIONS: The deep-learning algorithm accurately identified HF using ECG features and outperformed other machine-learning methods.
Artificial Intelligence ; Early Diagnosis ; Echocardiography ; Electrocardiography ; Forests ; Heart Failure ; Heart ; Humans ; Learning ; Logistic Models ; Machine Learning ; Mass Screening ; ROC Curve

We reviewed past studies on the identification of familial relationships using 22 short tandem repeat markers. As a result, we can obtain a high discrimination power and a relatively accurate cut-off value in parent-child and full sibling relationships. However, in the case of pairs of uncle-nephew or cousin, we found a limit of low discrimination power of the likelihood ratio (LR) method. Therefore, we compare the LR ranking method and data mining techniques (e.g., logistic regression, linear discriminant analysis, diagonal linear discriminant analysis, diagonal quadratic discriminant analysis, K-nearest neighbor, classification and regression trees, support vector machines, random forest [RF], and penalized multivariate analysis) that can be applied to identify familial relationships, and provide a guideline for choosing the most appropriate model under a given situation. RF, one of the data mining techniques, was found to be more accurate than other methods. The accuracy of RF is 99.99% for parent-child, 99.44% for full siblings, 90.34% for uncle-nephew, and 79.69% for first cousins.
Classification ; Data Mining ; Discrimination (Psychology) ; Forests ; Humans ; Logistic Models ; Methods ; Microsatellite Repeats ; Siblings ; Support Vector Machine ; Trees