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BackgroundWith urbanization and residential space expansion, ecological environment and human health issues have become hot social topics. Forest health, as a way of seeking health in nature, has begun to receive public attention in the context of the gradually increasing sub-healthy population and various psychological and physical diseases at a young age.ObjectiveTo systematically evaluate the effects of forest therapy on selected physical and mental health indicators.MethodsRelevant research literature was retrieved from domestic and international databases (China National Knowledge Infrastructure, Wanfang Database, China Biomedical Literature Service System, Web of Science, ScienceDirect, PubMed, Embase, and Cochrane Library), with a time range from database establishment to January 31, 2023. Relevant data were extracted for meta-analysis to explore the relationship between forest therapy and selected psychological and physiological indicators.ResultsA total of 85 articles were included, and the meta-analysis results showed that better scores of Profile of Mood States, Positive and Negative Affect Scale, Beck Depression Inventory, and State Trait Anxiety Scale were found in the forest group than those in the urban group (P0.5~3 h group (such as tension SMD=−2.40, 95%CI: −3.21, 1.59), and the reduction effects on systolic blood pressure (SMD=−0.53, 95%CI: −1.03, −0.03) and diastolic blood pressure (SMD=−0.42, 95%CI: −0.88, 0.04) were better in the >3 h group. Seated meditation showed better recovery effects on multiple indicators of Profile of Mood States (such as fatigue SMD=−2.26, 95%CI: −3.07, −1.45), while walking showed better recovery effects on physiological indicators such as blood pressure (systolic blood pressure SMD=−0.57, 95%CI: −1.07, −0.06; diastolic blood pressure SMD=−0.72, 95%CI: −1.36, −0.07) and heart rate (SMD=−1.51, 95%CI: −2.38, -0.64). Except for blood pressure, the health benefits of forest therapy in the younger age group were generally better than those in the middle-aged and elderly group.ConclusionRelaxed and comfortable psychological feeling is reported when practicing forest therapy; it can lower blood pressure and heart rate, regulate the autonomic nervous system; it can also reduce the release of stress hormones and lower serum levels of inflammatory factors, exerting an auxiliary recovery effect on cardiovascular and immune system disorders. At the same time, the therapy duration, form, and age of the subjects have a certain impact on the effects of forest therapy practice.

BackgroundArsenic exposure can lead to liver dysfunction, liver steatosis, hepatitis, liver fibrosis, and other liver injuries, but its mechanism is still unclear and effective treatment methods are lacking.ObjectiveTo investigate the potential intervention effect and associated mechanism of Rosa roxburghii Tratt juice on arsenic-induced liver injury in rats from the perspective of S-adenosylmethionine (SAM) metabolism.MethodsThirty-six Wistar rats were randomly divided into six groups, six rats in each group, half male and half female. The low, medium, and high dose groups of sodium arsenite (NaAsO2) were given 2.5, 5.0, and 10.0 NaAsO2 mg·kg−1 (body weight, thereafter), respectively; the control group was given 10 mL·kg−1 deionized water; the Rosa roxburghii Tratt juice intervention group was given 10 mg·kg−1 NaAsO2 for 4 h and then 10 mL·kg−1 Rosa roxburghii Tratt juice; the Rosa roxburghii Tratt juice control group was given 10 mL·kg−1 Rosa roxburghii Tratt juice by gavage. All rats were gavaged once a day, 6 d per week for 4 months. Histopathological changes of rat liver were observed by hematoxylin-eosin (HE) staining. Total bile acids (TBA) and γ-glutamyl transpeptidase (γ-GT) were detected by enzyme cycle method and rate method, respectively. Ultra-high-performance liquid chromatography tandem mass spectrometry (UPLC-MS) was used to evaluate SAM and S-adenosylhomo cysteine (SAH) in rat liver. Real-time fluorescence quantitative reverse transcriptional PCR (RT-qPCR) was used to detect the mRNA expression levels of the genes of glycine-N-methyltransferase (Gnmt), nicotinamide-N-methyltransferase (Nnmt), and phosphatidylethano-lamine N-mathyltransferase (Pemt).ResultsIn the control group, the liver nuclei were stained clearly, the cytoplasm was stained uniformly, and the liver cords were arranged radially without inflammatory infiltration. In the low, medium, and high dose groups of NaAsO2, hepatic sinusoidal dilation, congestion, and inflammatory infiltration were observed to different degrees. Compared with the control group, TBA in the medium and high dose groups of NaAsO2, and γ-GT in the high dose group of NaAsO2 were significantly increased (P

Registration of unmanned aerial vehicle laser scanning (ULS) and ground light detection and ranging (LiDAR) point clouds in forests is critical to create a detailed representation of a forest structure and an accurate retrieval of forest parameters. However, tree occlusion poses challenges for those registration methods used artificial markers, and some automated registration methods have low time-efficiency due to the process of object (e.g., tree, crown) segmentation. In this study, we propose an automated and time-efficient method to register ULS and ground LiDAR (including terrestrial and backpack laser scanning) forest point clouds. Registration involves coarse alignment and fine registration, where the coarse alignment is divided into vertical and horizontal alignment. The vertical alignment is implemented by rotating grounds to the horizontal plane, and the horizontal alignment is achieved by canopy image matching. During image matching, vegetation points are projected onto the horizontal plane to obtain two binary images, and then, canopy shape feature, which is described by a two-point congruent set and canopy overlap, is used to match the binary images. Finally, we implement coarse alignment of ULS and ground LiDAR datasets by combining the results of ground alignment and image matching and finish fine registration in six plantation forest plots with sizes of 0.03 ha to 0.25 ha. Experimental results show that the ULS and ground LiDAR data in different plots are registered, of which the coarse alignment errors are less than 0.20 m in the horizontal direction, the final registration accuracy is less than 0.15 m, and the average runtime is less than 1 s. Our study demonstrates the effectiveness of the proposed strategy and has able to perform accurate and quick registration of ULS and ground LiDAR data from plantation forests with different attributes.