Estimating forest plant area index (PAI) with the simultaneous separation of overstory vegetation (OV) and understory vegetation (UV) is essential to study forest carbon and water cycles. Measuring PAI of OV and UV using conventional field surveys within forests is challenging, particularly for subtropical regions of China, where terrain slope can exceed 10°. The effective PAI (PAIe) instead of PAI for UV is usually measured by the conventional method of subtracting PAIe of OV from total PAIe. We find PAIe obtained using this strategy is underestimated by 25%–85%. Thus, we propose an approach to estimate PAIe and PAI of both OV and UV on sloped terrain by using single-station (SS) terrestrial laser scanner (TLS) data. Results are verified by comparing them with multistation (MS) TLS data acquired coincidentally. Then we analyze the effects of horizontal range and slope correction on PAI estimated from SS TLS data. The results show that the correlation between SS and MS PAI (PAIe) is strong, with$R^{2}$of 0.88 (0.81) and 0.52 (0.75) (${p}~\lt 0.01$) for OV and UV, respectively. We recommend imposing a horizontal 20-m radius range for data acquired from SS TLS for PAI estimations. The difference between PAI estimations with and without a slope correction can be neglected. These results demonstrate that SS TLS data can serve as a means for PAI estimations of both OV and UV, which should help facilitate large-scale estimation in the subtropical forests of China.

Exploring the genes associated with rheumatoid arthritis (RA) patients with blood-stasis syndrome may shed light on the pathology studies of RA patients subtyped blood-stasis named in the traditional Chinese medicine (TCM) towards precision and personalized medicine. In this study, GWAS (genome-wide association study) and enrichment analysis were deployed on GSE205962 which is a gene expression data set from whole blood samples of RA patients with blood-stasis syndrome. Together with knowledge accumulated on RA, gene profiling results indicate RA-associated pathways, together with primary immunodeficiency, indicate a highly expressed gene set that is associated with RA patients with blood-stasis syndrome. The genes are AIRE, IFNG, IFNB1, IRF5, IL4, HSP90B2P, IL12B, IFNA1, and FLT1. The genes associated with RA patients with blood-stasis syndrome were validated via raw expression data and evidence collected from the literature.

Exploring the gene expression profile of rheumatoid arthritis (RA) patients with qi-blood-deficiency syndrome may shed light on the pathology of RA patients with qi-blood-deficiency syndrome in traditional Chinese medicine (TCM) towards precision medicine. In this study, GWAS (genome-wide association study), enrichment analysis, and visualizations were deployed on GSE205962 containing samples of RA patients with qi-blood-deficiency syndrome compared with healthy ones. As a result, more than half of differentially expressed genes were weakened/inhibited in RA patients with qi-blood-deficiency syndrome. To be enriched and demonstrated in KEGG RA-associated pathways, these pathways are all weakened and imbalanced with three gene groups: the activated, the inhibited, and the normal group. Besides, enrichment analysis also demonstrated that many signaling pathways are weakened and imbalanced by the development of RA with qi-blood-deficiency syndrome.

Differentially expressed genes (DEGs) shared among different yet associated pathways on rheumatoid arthritis (RA) may shed light on its pathology study. In this study, DEGs of RA subtyped liver-kidney deficiency (a syndrome in traditional Chinese medicine) were collected from the GSE205962 dataset toward the roles they played among RA-associated pathways. GWAS (genome-wide association study) and enrichment analysis demonstrated that the AP-1 transcription factor-associated genes are the top DEGs shared by the RA-associated pathways. As a result, the AP-1 delivers complex regulations on immune responses e.g. activating T cells via up-regulating JUN, FOS, MAPKs, and NFKB1B while inhibiting IKBKB, LCK, NFKB1, CD3D, et al. The protein networks of DEGs shared in the T cell receptor signaling pathway and Th17 cell differentiation, together with the AP-1-centered network, were proposed.

In clinical fights against rheumatoid arthritis (RA), the unique integrated medicine in China involves using biologics of adalimumab, glucocorticoids, and Chinese medicines for better therapeutic effects e.g. anti-inflammation (9.4 days of average hospital stay: 72% reduced C-reactive protein, 71% decreased erythrocyte sedimentation rate) and less side effects e.g. retarded osteoporosis (8.8% RA patients were diagnosed with osteoporosis compared with about 30% onset ratio without Chinese medicines). To uncover the candidate mechanisms of Chinese medicines against RA and osteoporosis, bioinformatics analysis was carried out with hospitalized information, blood tests and microarray data. As a result, three core Chinese medicines identified not only deliver a significant coordinative regulation network against RA inflammation, but also retard osteoporosis with their bioactive compounds, targeted genes/proteins, and genes/proteins involved with RA and osteoporosis.

Insomnia is a sleep disorder affecting 6% of people with substantial impairment in the quality of life with symptoms of low energy, irritability, and depressed mood. Chinese medicines have positive effects against insomnia with various formulae. A core formula of 7 constituents was extracted from 1,494 clinical prescriptions of Duan-Haichen, a national famous Chinese medicinal doctor. To explore the potential regulation networks of the core formula, we collected and integrated experiment-based compound and targeted proteins, directed and functional protein regulations, and differentially expressed genes (DEG) of insomnia. Targeting the up- and down-regulated DEGs, two networks were constructed towards positive- and negative-regulation of the DEGs, respectively. Further enrichment analysis on KEGG pathways revealed that the DEGs are heavily involved with Parkinson’s disease and IL17 signaling pathway.

In China, the integration of traditional Chinese medicine (TCM) and western medicine against rheumatoid arthritis (RA) delivers both low-level inflammation indexes and less side effects. Thus, exploring the mechanism of TCM against RA might help to explore the pathology of RA. As the diagnosis of TCM is based on syndrome differentiation and deficiency of liver and kidney is the leading one, then, explore associated Chinese medicines against RA may shed light on the therapeutic regulation network. In this study, network pharmacology analysis was carried out based on bioactive compounds, targeted proteins and protein interactions towards RA. As a result, the regulation network against RA delivered by the top five Chinese medicines was constructed. Further bioinformatics analysis on participant genes not only elucidate the relationships to RA and immune response, but also the reduced side effects e.g. osteoporosis. Validation of the therapeutic effect on RA patients was done via check indexes on C-reactive protein and erythrocyte sedimentation rate. Potential effects of the delivered regulation network were demonstrated with heatmap on the microarray data of RA synovium tissue.

In clinical fights against rheumatoid arthritis (RA), tofacitinib and glucocorticoids are usually combined with Chinese medicines in China for better therapeutic effects against inflammation (9.6 days of average hospital stay, 73% reduced C-reactive protein, 69% decreased erythrocyte sedimentation rate) with fewer side effects of osteoporosis (16.6% RA patients were diagnosed with osteoporosis compared with around 30% onset ratio without Chinese medicines). To discover the candidate mechanisms of Chinese medicines against RA and osteoporosis, bioinformatics analysis was launched with hospitalized data, blood tests, and microarray. As a result, six top Chinese medicines were identified to deliver significant coordinative regulation networks against RA inflammation while reducing osteoporosis with their bioactive compounds, targeted genes/proteins, and genes/proteins associated with RA and osteoporosis.

Pain in rheumatoid arthritis (RA) joints is the most significant symptom which is a multifactor process that may link to peripheral joint inflammation, disease progression, structural change, and the dysregulation of the central nervous system. In clinical practices, a ternate Chinese medicine (e.g. PAEONIAE RADIX ALBA/ 白芍, CHUANXIONG RHIZOMA/ 川芎, and CORYDALIS RHIZOMA/ 延胡索) can alleviate pain significantly. However, due to the complexity of multi-constituent, multi-compound, multi-target, and multi-regulation, the mechanism is not clear. In this study, targeting the RA pain pathways, bioinformatics and network pharmacology analysis were deployed to explore the pain alleviation mechanism. As a result, this study delivered a candidate mechanism network: 6 bioactive compounds of the ternate Chinese medicines inhibit 24 target proteins (e.g. IL4/6/1B, NFKB1/2, MAPK8, et a1) which also further regulate 14 downstream proteins (e.g., CXCLS, CCL2, TRAF6, et al.). The mechanism network was also validated with the RNA transcript microarray data with samples of a normal control group, joint pain group, and RA group.

In the development of rheumatoid arthritis (RA), hypoxia occurs in the process of synovial proliferation, neovascularization, and leukocyte extravasation. BuYang-HuanWu-Tang (BYHWT), a Chinese medicine formula, can alleviate hypoxia in RA patients with the syndrome of qi stagnation and blood stasis. However, the BYHWT mechanism network against hypoxia is not clear. In this study, bioinformatics analysis was deployed via bio-active compounds, target protein, protein interactions, and RA microarray data for mechanism exploration and validation. As a result, the BYHWT may alleviate hypoxia via down-regulating BNIP3, MAPK8, and the PI3K/AKT pathway. Literature review and microarray data can validate the results. This study may provide insights of BYHWT against hypoxia in RA for alternative therapy.

One interesting question between the Homo Sapiens and other mammal species is their protein sequence similarities. In this study, based on the global alignment algorithm with the substitution matrix of “BLOSUM62”, calculations were carried out on protein sequence similarities within Homo Sapiens and mammal species, protein families and specified proteins across species. As a result, protein sequence similarities among Homo Sapiens and other mammal species are around 19%; protein families share similarities ranges from around 20%-90%.

The onion (Allium cepa L.), is a functional vegetable that is widely cultivated and consumed around the world with its anti-atherosclerosis activity and delicious tastes. Studies reported that quercetin, the main flavones of onion, exhibits anti-atherogenic effects via regulating dozens of proteins and genes. Till now, no mechanism network of onion quercetin against the development of atherosclerosis was constructed. In this study, evidenced items were collected to constructed the mechanism network of quercetin from onion via regulating dozens of proteins/genes to block the atherosclerosis pathways. As a result, proteins and genes participating atherosclerosis pathways were negatively regulated by onion quercetin and they form the candidate mechanism network which were also validated with the microarray evidence on the development of atherosclerosis under the stimulation of cholesterol.

Under the market economy, the moderate fluctuations in the price were normal reaction of the market mechanism. However, excessive fluctuations in the price would also bring adverse effects to corresponding industry. The price change of agricultural products was the great event vital to national well-being and the people's livelihood. Since the price of agricultural products was affected by many factors, it was difficult to predict the price of agricultural products timely and accurately. The emergence of cloud computing, accompanied by massive storage space, huge computing capacity and low cost, provided a new direction for data mining to deal with big data. To realize the short-term agricultural product price forecasting, took service oriented forecasting as the guidance, this paper constructed a agricultural product price forecasting service system based on the DOA architecture. The system could conduct the analysis and prediction for the market price through the combined forecasting method of wavelet transform and BP neural network. Based on the 72 sets of monthly price data from January 2013 to December 2018 of the spinach, cabbage, tomato, pepper and potato, this paper studied the changing trend of agricultural products price. Firstly, in this paper, the price was conducted the db5 three scale decomposition using wavelet transform. Then, the shredded trend part and detail part were predicted by BP neural network model respectively. Finally, the prediction results of each component were combined and reconstructed. On the basis of this combined forecasting method, the agricultural product price forecasting service system with functions of price data service and price forecasting service was designed based on DOA architecture. To verify the prediction accuracy to the price of the 5 kinds of vegetables, the prediction accuracy index was used to evaluate and analyze the price prediction results of the system. The results showed that the minimum mean absolute error of the system was 0.083 yuan/kg, the minimum mean percentage error was 3.95%, the minimum mean square error was 0.102 and the agricultural product price forecasting service system combining wavelet transform and BP neural network had better agricultural product price forecasting performance. At the same time, this also meant that the universality of this system could adapt to the price forecasting of a variety of vegetables and provide technical support for producers, operators, consumers and relevant government departments.

Angelicae Sinensis Radix, also called Dang-Gui in Chinese, is an important and widely used natural product in traditional Chinese medicine (TCM) formulae with therapeutic properties of “menstrual regulation”. However, the underlying mechanisms on the molecular-interaction-level are still under exploration. In this study, based on evidenced bioactive compounds, targeted genes and proteins, different level functional annotations on gene ontology biological processes (GOBP) was deployed and then validated with microarray data. As a result, participating-fold analysis of targeted proteins revealed that the rhythmic process is the top GOBP. Further analysis indicated that the ovulation cycle process is associated with both the rhythmic process and TCM clinical relevance. After that, a kernel candidate regulation network was constructed towards the therapeutic properties of menstrual regulation identified in TCM that is delivered by Dang-Gui.

Ginseng is an important herbal medicine in traditional Chinese medicine (TCM) with therapeutic properties of “reinforcing primary qi” and “pulse restoring and blocking depletion” that are mentioned in both TCM textbooks and the Pharmacopoeia of the People's Republic of China. However, the underlying mechanisms are still under exploration. In this study, based on evidenced bioactive compounds and targeted genes/proteins, top-level functional annotation towards gene ontology biological processes was deployed and then validated with transcript microarray data. As a result, a kernel candidate regulation network was constructed towards the therapeutic properties of ginseng identified in TCM. Functional annotation indicated three associated biological processes e.g. (1) cell killing, (2) rhythmic process, and (3) growth. In short, through regulating the three processes, the therapeutic properties of “reinforcing primary qi” and “pulse restoring and blocking depletion” identified in TCM can be roughly elaborated and validated.

Astragali Radix, called Huang-Qi in Chinese, is a widely used traditional Chinese medicine (TCM) with therapeutic effects of “tonifying qi” that is identified in both TCM formulae, textbooks, and the Pharmacopoeia of the People's Republic of China. However, the underlying mechanisms of the bioactive compounds and target proteins are still under exploration. In this study, based on evidenced bioactive compounds and targeted genes/proteins, different level functional annotations towards gene ontology biological processes and KEGG pathways were deployed and validated. As a result, the candidate molecular regulation network was constructed towards the “tonifying qi”. Functional annotation indicated one outstanding biological process called cell killing which is tightly associated with immunoenhancement. In short, the “tonifying qi” effect identified in TCM on Astragali Radix might be associated with immunoenhancement by various modern bio-medical studies.

Dioscoreae Rhizoma, also called Shan-Yao in Chinese, is a tonic food and herbal medicine in traditional Chinese medicine (TCM). Recent biomedical researches on Shan-Yao mainly focused on cancer and immune responses that are scattered in the literature. To build a holistic view of the immunoregulation functions delivered by Shan-Yao, the dispersed experimental knowledge items were collected, integrated, analyzed, and demonstrated. As a result, a candidate regulation network was constructed towards the immunoregulation. This network was composed of Shan-Yao, bioactive compounds, target proteins, protein interactions, pathway enrichment, and functional annotations. Functional annotations demonstrated the cell killing process is tightly associated with immunoregulation scenarios under different conditions via pathway enrichment, all are participated by the same target proteins of Shan-Yao.

Atractylodis Macrocephalae Rhizome (AMR) has been identified in traditional Chinese medicine (TCM) with “spleen tonifying” effect. In TCM clinical practices, AMR has been widely used against “spleen deficiency” syndrome associated diseases e.g., chronic gastritis. However, the underlying mechanisms are still under exploration. In this study, based on evidenced knowledge items of bio-active compounds and targeted proteins, bioinformatics analysis towards underlying mechanisms was deployed. As a result, a key candidate process of regulation on secretion was identified. For all 14 network participating proteins, 8 had been evidenced with regulations on secretion of gastritis acid. Gene expression data of chronic gastritis also provide support evidences. In brief, the positive regulation on protein secretion of gastric acid delivered by AMR might be the underlying mechanism of “spleen tonifying” observed in TCM clinical practices.

Angelicase Pubescentis Radix (APR) has been used in the practices of traditional Chinese medicine (TCM) with anti-rheumatoid arthritis (RA) effects called “wind-dampness-dispelling and cold dispersing”. In TCM prescriptions and patient medicines, APR has been widely adopted against RA. Till now, the anti-rheumatoid mechanisms are still obscure. In this study, bioactive compounds and targeted proteins based on experiment evidences were collected. Then, bioinformatics analysis towards RA was deployed. As a result, five RA associated biological processes were enriched with proteins targeted/regulated by APR e.g. ossification, osteoclast differentiation, positive regulation of lymph activation and regulation of T and B cell. The result can also be validated with bioinformatics tools and RA microarray data. In short, the anti-RA effect of APR recognized in TCM may associated with regulations on bone formation and inflammations.

Carthami Flos (CF), a Traditional Chinese medicine (TCM), has been widely used in TCM prescriptions and Chinese patent medicines against contusion and potential bone fractures and striated muscle damages for its outstanding healing functions. Although intensively studied, its healing mechanisms w.r.t. TCM theory are still not elucidated at protein interaction level. In this study, bioinformatics analysis was deployed based on experiment-evidenced reliable knowledge on bio-active compounds and targeted proteins. Further enrichment analysis revealed three key role healing functions provided by CF e.g., regulation of blood vessel diameter, ossification, and regulation of striated muscle development. Besides, underlying protein interaction networks were also proposed and validated. This study provided a reliable approach to study the therapeutic mechanisms of Chinese medicines.

Carthami Flos (CF), a Traditional Chinese medicine (TCM), has been widely used in TCM prescriptions and Chinese patent medicines against contusion and potential bone fractures and striated muscle damages for its outstanding healing functions. Although intensively studied, its healing mechanisms w.r.t. TCM theory are still not elucidated at protein interaction level. In this study, bioinformatics analysis was deployed based on experiment-evidenced reliable knowledge on bio-active compounds and targeted proteins. Further enrichment analysis revealed three key role healing functions provided by CF e.g., regulation of blood vessel diameter, ossification, and regulation of striated muscle development. Besides, underlying protein interaction networks were also proposed and validated. This study provided a reliable approach to study the therapeutic mechanisms of Chinese medicines.

Persicae Semen (PS), a typical Chinese medicine with blood-activation and stasis-dispelling function identified in traditional Chinese medicine. In clinical practices, PS has been widely used against bruises and accompanied symptoms e.g., bone fractures and striated muscle damages. However, till now, the healing mechanisms at protein interaction level is still not clearly elucidated. In this study, with evidenced knowledge of bioactive compounds and targeted proteins extracted via reviewing experiment-based literatures. Bioinformatics analysis on protein interaction and enrichment were deployed. As a result, two key biological processes were highlighted e.g., wound healing and regulation of blood vessel diameter. Besides, underlying protein interaction networks were also constructed, demonstrated and validated with both wet and dry evidences.

It is well known that gout and hyperuricemia are comorbidity due to the high level of uric acid in the blood and its crystallization. However, the pathological mechanism underlying the comorbidity of gout and hyperuricemia is still obscure. In this study, focused on the genes associated with hyperuricemia and gout, three functional protein networks were constructed. They illustrate the pathological mechanism of comorbidity via directed protein regulations from gout to hyperuricemia, vice versa, and their union. Accordingly, these networks contain 8 proteins associated with gout and hyperuricemia, 11 internal proteins bridging their inter-regulations. Consequently, enrichment analysis reveal that these participant proteins mainly functions in processes of immune responses and purine metabolisms. What's more, these participant proteins were primarily validated with PubMed literature and confirmed by bioinformatics tools.

Ginger is a well-known traditional Chinese medicine which has been identified with positive digestive function regulations e.g. vomit prevention and warming interior. 6-shogaol is one of ginger's major bioactive constituents. In this study, digestive functions regulated by 6-shogaol towards stomach and small intestine were investigated. Started with biomarkers regulated by 6-shogaol reported in PubMed literatures, functional protein-protein interactions (FPPI) from biomarkers to proteins expressed in stomach and small intestine were filtered out. These FPPIs form networks regulated by 6-shogaol. Based on these participant proteins, enrichment analysis mainly focused on metabolic processes e.g. proteolysis, fatty acid, purine, steroid, et al and immune responses. Taken together, through 6-shogaol, ginger can regulate a large variety of metabolic processes to enhance digestive functions so as to prevent vomit and warming interior via these enhanced digestive functions.

Ginger is widely used as a spice and traditional Chinese medicine achieving warming interior for dispelling cold during its long time clinical observations and practices. However, its mechanism is still obscure. In this study, interior is restricted to stomach and small intestine. 6-gingerol, ginger's quality control and main bio-active chemical compound, is chosen to represent ginger. Started with biomarkers reported in literatures. Functional protein-protein interactions (FPPI) from biomarkers to proteins expressed in stomach and small intestine were filtered out. These FPPIs form networks regulated by 6-gingerol targeting interior. Further enrichment analysis highlighted biological processes concentrated on metabolic regulations for more energy generation, metal ion transmembrane transporter activity for better digest, more blood flow volume for nutrient and warmth, and cell cycle regulation to prevent canceration. Taken together, ginger's warming up interior for cold expelling is elaborated via bioinformatics analysis on 6-gingerol.

The scan angle information implicitly contained within the 3-D point cloud data (PCD) generated from light detection and ranging strongly affects the retrieval accuracy of the forest canopy structural parameters. Using information generated from overlapping aerial laser scanning (ALS) flight paths with multiple scan angles over a forest canopy can help to remove the occlusion effects between foliage elements, ultimately creating a relative comprehensive PCD. In this paper, we develop a novel physically based scan angle correction algorithm to retrieve the effective leaf area index (LAIe) of a forest canopy using ALS. Furthermore, we investigate the effects of scan angle and the number of ALS overpass lines from adjacent flight paths over a forest canopy on directional gap fraction (DGF) estimates. Our results suggest that ALS-based LAIe estimates capture 71.35% of the variations in LAIe derived from digital hemispherical photography. A forest canopy point cloud created using PCD from multiple overlapping ALS flight paths was sufficient to quantitatively reveal the anisotropy characteristics of DGF variations. These results suggest that scan angle information should not be neglected in retrieving forest canopy structural parameters, especially when using ALS data collected with a wide scan angle (i.e., -30° to 30° in this paper). Finally, this paper provides a solid foundation to characterize the 3-D spatial distribution of a forest radiation regime using ALS-based forest PCD.

Triptolide is an important active compound derived from Chinese herbal medicine Tripterygium wilfordii Hook f. Despite its positive therapeutic effects, the female reproductive toxicity is still blocking its clinical application with its toxicity mechanism is still obscure. In order to tackle the mechanism of female reproductive toxicity, one intuitive approach is to explore the biological molecule network involving targeted proteins and associated ovary expressed proteins. In this study, triptolide's target proteins and their biological functions were analyzed first. Then, focused on the enriched process of negative regulation of cell cycle, targeted proteins, together with proteins expressed in ovary which are contributed in negative regulation of cell cycle were extracted so as to form the female reproductive toxicity molecule network. Finally, three targeted proteins of CASP3, TP53, and MYC were highlighted as the leading causation of female reproductive toxicity. Further analysis indicated that these 3 target proteins can further regulate 21 ovary expressed proteins which also participate in associated processes. This study provides specified molecule level mechanism the female reproductive toxicity of triptolide which can be used to prevent toxicity while keeping its therapeutic effects.

Traditional Chinese medicine has been using Tripterygium wilfordii Hook f. (TWHF) against systemic lupus erythematosus (SLE) over 200 years. Triptolide is an active compound of TWHF with therapeutic effects for auto-immune disease SLE. However, till now, few associated studies were reported and little is known about the mechanism of triptolide against SLE which blocks the new drug discovery. In this study, focused on the proteins participated in the process of immune respond, an integrated bioinformatics analysis covering targeted proteins, SLE OMIM genes, biological process enrichment, and protein-protein interactions (PPI) was deployed. As a result, the candidate therapeutic network against SLE with negative regulation of immune response was proposed. It contains a PPI network of 7 targeted proteins and 7 SLE OMIM genes further regulated by triptolide. Primary validation of this network indicating that processes of apoptosis and pro-inflammatory processes were involved.

Extracted from Chinese herbal medicine Tripterygium wilfordii Hook f., triptolide is an active compound with positive therapeutic effects on immune-regulated disease of rheumatoid arthritis. However, the male reproductive toxicity blocks its wider clinical applications. With the mechanisms of male toxicity is still obscure, it is difficult to tackle its toxicity. In this study, triptolide's male reproductive toxicity mechanisms were carried out through integrated bioinformatics analysis which covers target proteins, further regulated testis proteins, biological process enrichment, and protein-protein interactions. As a result, (1) MYC was identified as the target protein; (2) testis proteins of CCNB1, EZH2, PEG10, and THBS1 were found participated in spermatogenesis; and (3) 3 new candidate testis proteins of CHKA, GAS1, and RCC1 were proposed which might be connected to the male reproductive toxicity.

The forest canopy vertical structure, understory spatial distribution as well as bare soil ground under a forest canopy strongly affect the accuracy of retrieving leaf area index (LAI) using optical remotely sensed data. Combining the reflectance from two different view directions and geometric optical (GO) radiative model, we investigated the effects of background information on retrieving forest canopy LAI using moderate resolution data for temperate forest in Northeastern China. Firstly, the forest background reflectance (BR) was computed using the bidirectional reflectance distribution function (BRDF) product from MODIS data. Then the forest canopy effective leaf area index (LAIe) was retrieved using the four scale geometric optical radiative model after removing the effects of forest background. It was found that the LAIe estimates without considering and with considering forest background contribution can explain 46 % and 36 % variations of field measurement-based LAIe (p<; 0.01, N=28), respectively. The forest canopy LAIe estimation without removing background influence can result in the LAIe overestimation ranging from 20 % to 46 %, thus it is necessary to separate the contribution of forest background to total forest canopy reflectance.

A campaign aimed at airborne multi-angle hyperspectral data collection was designed and implemented in Daxinganling of Northeastern China in the August of 2015. The purpose of this campaign is to investigate the potentials of multi-angle optical data for forest height and biomass estimation. The observation angles of 0°, 20°, 44° and 55° were used with 400-1000 nm spectrum range. To provide comparable information, airborne Lidar data were collected simultaneously. First results showed the collected angular information captured the Bidirectional Reflectance Distribution Function (BRDF) characteristics of forest spectrum. The relationship of lidar derived vertical parameters and multi-angle optical data are under further investigation.

Accurate separation of photosynthetic and nonphotosynthetic components in a forest canopy from 3-D terrestrial laser scanning (TLS) data is a challenging but of key importance to understand the spatial distribution of the radiation regime, photosynthetic processes, and carbon and water exchanges of the forest canopy. The objective of this paper was to improve current methods for separating photosynthetic and nonphotosynthetic components in TLS data of forest canopies by adding two additional filters only based on its geometric information. By comparing the proposed approach with the eigenvalues plus color information-based method, we found that the proposed approach could effectively improve the overall producer's accuracy from 62.12% to 95.45%, and the overall classification producer's accuracy would increase from 84.28% to 97.80% as the forest leaf area index (LAI) decreases from 4.15 to 3.13. In addition, variations in tree species had negligible effects on the final classification accuracy, as shown by the overall producer's accuracy for coniferous (93.09%) and broadleaf (94.96%) trees. To remove quantitatively the effects of the woody materials in a forest canopy for improving TLS-based LAI estimates, we also computed the “woody-to-total area ratio” based on the classified linear class points from an individual tree. Automatic classification of the forest point cloud data set will facilitate the application of TLS on retrieving 3-D forest canopy structural parameters, including LAI and leaf and woody area ratios.

The spatial distribution of the photosynthetic components of a forest canopy plays a key role in ecological related processes such as gas exchange, photosynthesis, and evapotranspiration through affecting radiation regimes of the forest canopy. However, quantitative evaluation of woody materials' contribution to effective leaf area index (LAIe) using 3-D terrestrial laser scanning (TLS) is a challenging work. In this paper, we first identified the differences between directional gap fraction (DGF) and angular gap fraction (AGF) and then developed a local geometric feature-based approach to automatically classify a TLS forest point cloud data (PCD) into three different classes, including nonphotosynthetic canopy components (i.e., stem and branch points), photosynthetic canopy components (i.e., leaf and grass points), and bare ground. In addition, we proposed a new approach named “radial hemispherical point cloud slicing” algorithm to investigate the 3-D spatial distribution of foliage elements and retrieve LAIe from a given forest PCD. Our results showed that nonphotosynthetic canopy components contributed from 19% to 54% to LAIe depending on various forest densities. Moreover, TLS-based LAIe estimates can explain 74.27% variations of digital-hemispherical-photography-based LAIe values with a linear regression statistical model. This paper provides a theoretical foundation for LAI estimation based on the PCD generated using the TLS system and facilitates the application of TLS on retrieving 3-D forest canopy structural biophysical parameters.

With limited researches, there is still lack of pathway networks of Chuan-wu (also called Aconitum carmichaelii) against rheumatoid arthritis which might provide clues for further researches. In this study, started from the chemical compounds, proteins targeted by Chuan-wu were explored. After that, pathway networks enriched with these targeted proteins were analyzed with hypergeometric distribution on threshold ofp-value set to 0.001 for pharmacology mechanism. Meanwhile, pathway networks enriched with OMIM genes of rheumatoid arthritis were also calculated for pathology analysis in the same way. Then, these two pathway networks of pharmacology and pathology were merged into one for validation and further predictions. As a result, six pathway networks were predicted which might be responsible for the therapeutic effect against rheumatoid arthritis. They are: disease, signal transduction, metabolism of proteins, cell cycle, metabolism of proteins, and developmental biology.

It is a long histroy that use of acupuncture treatment coronary heart disease (CHD) which belongs to Xiong Bi in Traditional Chinese Medicine (TCM). In this paper, application of acupuncture on CHD treatment was analyzed by text mining. The study was focused on the fields of meridian, acupoints, acupuncture method and constructed the associated network of them. By analyzing the network, we found that Pericardium Meridian of Hand-Jueyin was the frequently used meridian combined with other meridians and Neiguan was the frequently used acupoint combined with other acupoints for acupuncture treatment on CHD. Electroacupuncture was the common used method and often applied in the meridian of Hand-Jueyin and Hand-Shaoyin. The combinations of meridians, acupoints and methods were demonstrated in network. Results could be helpful for both clinical practice and medical research.

Hypertension becomes a major public health problem due to its serious morbidity and mortality and serious cardiovascular, cerebrovascular and kidney complications. The complementary therapies of Traditional Chinese Medicine (TCM) play important roles in hypertension treatment. Acupuncture, as an important component in TCM, is frequently used in treatment hypertension. In this paper, we mined the data set of literature downloaded from SinoMed on hypertension focused on its treatment with acupuncture technology in TCM common use. The text mining results showed that Shuigou, Zhongshu, Burong, Zusanli, and Taichong were the top 5 acupoints, while Governor Meridian, Bladder Meridian of Foot-Taiyang and Stomach Meridian of Foot-Yangming were the top 3 meridian used for hypertension treatment. The combinations of acupoints were demonstrated in network, which were widely used in the clinical practices of acupuncture. The results provided good references for both clinical practice and medical research.

Acupoint application therapy is one of the Traditional Chinese medicine (TCM) external therapies, which has been used for coronary heart disease (CHD) treatment for a long time. The prescription of acupoint application therapy includes both Chinese herbal medicines (CHMs) and acupoints. This study aims to reveal the basic rules of acupoint selection in acupoint application therapy on CHD treatment by text mining study. Results showed that on CHD treatment, the most frequently used acupoint was Danzhong (RN17), followed by Xinshu (BL15), Neiguan (PC6), Zusanli (ST36) and Zhiyang (DU9). Acupoints closing to the heart or with specific functions were more frequently used. Moreover, Xinshu, Danzhong and Neiguan were of the top 3 relationships with other acupoints, while Zusanli and Sanyinjiao (SP6) were in the lower grade. The combination of Xinshu-Danzhong-Neiguan could be regard as the basic acupoint prescription of acupoint application therapy on CHD.

Tinnitus is the most common medical symptom that can be debilitating. Chinese herbal medicines (CHMs) play important roles in tinnitus treatment. This study analyzed the most frequently prescribed herbs used to treat tinnitus and the molecular mechanisms of therapeutic effects of these CHMs by text mining and bioinformatics technique. Results showed that pinellia ternate (Banxia) and gastrodin (Tianma) are the most frequently prescribed CHMs for treatment tinnitus. The molecular mechanisms of therapeutic effects of two CHMs were focused on sertoli cell-sertoli cell juntion signaling and NRF2-mediated oxidative stress response signaling. Integrative text mining and bioinformatics analysis may be a promising approach to find new drug and decipher their molecular mechanism intuitively.

Mammary gland hyperplasia (MGH) is a kind of endocrine disorder diseases, which is usually characterized by lump and pain in breast and an increased risk event of breast cancer. The complementary therapies of Traditional Chinese Medicine (TCM) play important roles in MGH treatment. This study analyzed the application of the TCM external therapy and food therapy by text mining. Subsequently, suitable techniques and methods which were frequently used on MGH treatment were explored. Results showed that external application of Chinese herb medicine, acupuncture, massage, catgut embedding, and magnet therapy were the top 5 TCM external therapy techniques, while fritillaria Oyster, alga, trionyx, kelp, arrowhead, pseudo-ginseng, lemon, leonurus, and hawthorn were the top 10 foods used for MGH treatment. The combinations of external therapy techniques were demonstrated in network, so does the combinations of the foods. The results provided good references for both clinical practice and basic research.

As the fifth most common malignancy, liver cancer has a high incidence. Chinese herbal medicine (CHM) has been an integral part of traditional Chinese medicine (TCM) for thousands of years. Many herbal formulae have been used in treating liver cancer and proved to be safe and effective in some degree. Yet the principles of treating liver cancer with CHMs are hard to manage due to the complexity of TCM theory and flexibility of TCM clinical practices. In this study, a practical text mining method was deployed based on a comprehensive collection of literatures in order to explore the treatment principles. Networks of TCM patterns and CHMs which were most frequently used in liver cancer treatment were built-up and analyzed; three major treatment principles were explored from 53,499 records of literature: (1) benefiting qi or replenishing blood; (2) promoting blood circulation for removing blood stasis; (3) clearing heat and promoting diuresis. These provided an accessible way for understanding the treatment principles for liver cancer with CHMs.

Fang-Feng-Tang is a Chinese herbal formula which is designed to treat syndrome Feng-Han-Shi-Bi for rheumatoid arthritis (RA). Although its therapeutic effects are widely accepted, its mechanism is still obscure. In this study, by integrating leading knowledge databases of associated different domains, we explored Fang-Feng-Tang's potential therapeutic agents for RA through targeted pathway hierarchies. The molecule mechanism analysis includes compositional herbal medicine, chemical compound, target protein, and pathways enriched. Target proteins are restricted with RA OMIM genes and FDA approved RA drug targets for partial validation. As a result, 8 target proteins were matched and they are UGT1A9, GNT1, UGT1, JAK3, CCR2/5, and CMKBR2/5. What's more, they are mainly involved in pathways of signal transduction, metabolism, immune system, and disease. This research demonstrates that Feng-Feng-Tang's target proteins may regulate a wide range of different systems. This might indicate that Chinese herbal formula's therapeutic effects can be demonstrated through system-level regulation rather than targeting disease specified genes or proteins.

Major depression (MD) is a major public health problem which has a substantial impact on individuals and society. Although it is usually treated with antidepressant in primary care, these therapies accompanied with serious side effects. In the clinic of Chinese medicine, Xiao-Yao-San is the first option for MD with little side effects. Although with clear therapeutic effects, its therapeutic mechanism is obscure. In this study, by integrating leading biomedical knowledge databases, though bioinformatics analysis, we explored the potential therapeutic mechanism of Xiao-Yao-San for MD. The therapeutic mechanism analysis covers aspects of Chinese herbal medicine, chemical compound, target protein, OMIM genes, and pathways enriched. As a result, Xiao-Yao-San's 4 target proteins e.g., ADRB2R, B2AR, ADRB2, and MC4R can be matched in MD's OMIM genes which are mainly enriched in pathways of signal transduction. This research demonstrates that Xiao-Yao-San's target proteins may regulate a wide range of different pathways associated with MD.

Da-Fang-Feng-Tang is a Chinese herbal formula designed to treat syndrome Feng-Han-Shi-Bi for rheumatoid arthritis (RA). Although it's clinical effect have been accepted through 1000 years' clinical practises, its molecule mechanism is still obscure. In this study, by integrating powerful knowledge databases, though bioinformatics analysis, we explored the potential molecular mechanism of Da-Fang-Feng-Tang for RA. The molecule mechanism analysis includes compositional herbal medicine, chemical compound, target protein, RA OMIM genes, and enriched pathways. As a result, Da-Feng-Feng-Tang's 7 target proteins were matched in RA's OMIM genes. What's more, these 7 genes are mainly involved in three pathway hierarchies e.g., disease, immune system, and signal transduction. This research demonstrates that Da-Feng-Feng-Tang's target proteins can regulate a wide range of systems associated with RA. This might indicate that Chinese herbal formula's therapeutic effects are taken effects through system-level regulation rather than targeting only disease specified genes or proteins.

Duhuo-Jisheng-Tang is a Chinese herbal formula designed to treat rheumatoid arthritis (RA) with syndrome dual deficiency of liver and kidney. Although its therapeutic clinical effect is widely accepted over one thousand years, its therapeutic agents are still obscure. In this study, we explored the potential therapeutic agents of Duhuo-Jisheng-Tang for RA by integrating leading knowledge databases of different biomedical domains. The molecule mechanism includes compositional herbal medicine, chemical compound, target protein, RA OMIM genes, FDA approved RA drug targets, and pathways. As a result, Duhuo-Jisheng-Tang's 11 target proteins can be found in RA's OMIM genes (e.g., UGT1, UGT1A9, GNT1, and JAK3) and FDA approved RA drug targets (e.g., CMKBR2/5, CCR2/5, APRF, and STAT1/3). What's more, these 11 genes/proteins are mainly enriched in pathways of disease, immune system, signal transduction, and metabolism. It demonstrates that Duhuo-Jisheng-Tang may regulate a wide range of different systems associated with RA which might indicate that Chinese herbal formula's therapeutic effects are demonstrated through system-level regulation rather than targeting disease specified genes/proteins.

It is well known that acupuncture treatment has an effect on patients with ischemie cerebrovascular disease. This study was aimed to summarize the basic laws of acupoints of ischemie cerebrovascular disease in acupuncture treatment using text mining techniques. First, we proposed the text-mining-based method to collect related literatures about acupuncture treatment of ischemie cerebrovascular disease from Chinese Biomedicai Literature Database, and then the ACCESS database was constructed. Second, structured query language was applied to data processing as well as data stratification algorithm was adopted to analyze the basic laws of acupoints of ischemie cerebrovascular disease in acupuncture treatment. Final, 62,903 documents were retrieved and the results showed that the higher frequency of single point in the treatment of ischemie cerebrovascular disease were sorted in descending order as the following: Renzhong(570), Burong(205), Fufen(186), Youmen(84), Shuifen(58), Baihui(57), Zusanli(55). Moreover, the higher frequency of paired points in the treatment of ischemie cerebrovascular disease were sorted in descending order as the following: Baihui with Dazhui(21), Neiguan with Zusanli(21), Quchi with Zusanli(21), Baihui with Qubin(10), Neiguan with Renzhong(9), Neiguan with Sanyinjiao(9), Neiguan with Yinjiao(9). These findings suggest that the method of text mining can be used to analyze basic acupoint laws through statistical frequency of acupuncture treatment of ischemie cerebrovascular disease and to provide a reference for clinical acupoints.

Much useful information on Ligusticum wallichii (LW) could be obtained from published literature by text mining technique. In this study, the data set on LW was downloaded from Chinese BioMedical literature database (SinoMed). Then, association rules among diseases, traditional Chinese medicine (TCM) syndromes, formulae and herbs on LW were investigated by text mining technique. These rules include TCM syndromes to diseases, formulae and combinational herbs, respectively. Diseases related with formulae including LW were mined out by executing data slicing algorithm. Finally, the results were visually demonstrated with Cytoscape 2.8 software. The main features from the mining data were: (1) LW was frequently used in treating cerebral infraction; (2) Blood stasis due to Qi deficiency was the main syndrome in TCM clinical practice; (3) Angelica sinensis was the first herb to combine with LW according to co-occurrent frequency; (4) Associated with LW, networks of TCM syndromes-diseases, formulae-diseases, TCM syndromes-formulae, and TCM syndromes-combinational herbs were constructed. These associated networks represented a holistic thinking of Chinese medicinal therapy, which might embody association rules among diseases, syndromes, formulae and herbs on LW.

In traditional Chinese medicine, rules of Li-Fa-Fang-Yao is of critical importance in clinical practices. Li-Fa-Fang-Yao, which means principles, methods, formulae, and Chinese herbal medicines respectively, indicate the four basic steps of diagnosis and treatment: determining the cause, mechanism and location of the disease according to the medical theories and principles, then deciding the treatment principle and method, and finally selecting a formula as well as proper Chinese herbal medicines. In this paper, focused on major depressive disorder, we explored the rules of Li-Fa-Fang-Yao within the framework of traditional Chinese medicine. Through calculation, three clusters of Li-Fa-Fang-Yao on major depressive disorder were found based on the syndrome differentiation. What's more, these three clusters can also be validated by textbooks of traditional Chinese medicine.

Hypertension becomes a major public health problem due to its high prevalence and serious complications. The complementary therapies of Traditional Chinese Medicine (TCM) play important roles in hypertension treatment. This study analyzed the application of the TCM external therapy and food therapy by text mining. Subsequently, suitable techniques and methods which were frequently used on hypertension treatment were explored. The text mining results showed that acupuncture, massage, Tuina, auricular-plaster and external application of Chinese herb medicine(CHM) were the top 5 TCM external therapy techniques, while placenta, lily root, pseudo-ginseng, peanut, sea horse, wine, radix aconiti carmichaeli, lemon, soybean and fructus crataegi were the top 10 foods used for hypertension treatment. The combinations of external therapy techniques were demonstrated in network, so does the combinations of the foods. The results provided good references for both clinical practice and medical research.

Non-alcoholic fatty liver disease (NAFLD) is a kind of prevalence diseases. Traditional Chinese medicine (TCM) has better efficacy on treating NAFLD. But there are also not known about the critical pathogenesis and the corresponding biological factors. Regarding this, we addressed a text mining approach to analyze the pattern profile, rule of medication, and the pathological factors of NAFLD from the opening database (SinoMed and PubMed). Based on canonical data source, we have our data treatment scheduled in 4 steps: (1) data retrieving, (2) data pretreating, (3) data analyzing, and (4) data visualization. And according to the TCM theory of formulae-pattern-disease' correlation, we partly understand the possible TCM pathogenesis of NAFLD which linked biological process of lipid metabolism disorder, inflammation, and metabolic regulation confusion.

Rheumatoid arthritis (RA) is an autoimmune disease that results in a chronic, systemic inflammatory disorder that may affect many tissues and organs, but principally attacks flexible (synovial) joints. Traditional Chinese medicine (TCM) treats RA with herbal formulae according to different syndrome/pattern classification. One important syndrome/pattern in RA is Feng-Han-Shi-Bi. Targeting this syndrome, Juan-Bi-Tang is the basic herbal formula adopted in clinical practises with reliable therapeutic effect. However, the mechanism of Juan-Bi-Tang is still not clear. In this study, we explored the molecular mechanism of Juan-Bi-Tang with in silico analysis on its 11 herbal medicines' chemical compounds, target proteins, protein-protein interaction, and pathway. As a result, the molecular mechanism of Juan-Bi-Tang for Feng-Han-Shi-Bi syndrome in RA covers a variety of biological processes including immune system, signal transduction, metabolism, disease etc. Most of them are relevant to RA which indicate actual therapeutic effect of TCM clinical practises.

It is a still a world-wide challenge that hypertensive patients maintain a satisfactory blood pressure control. In TCM practice, traditional physical therapy has shown beneficial to blood pressure (BP) controlling. As the amount of bio medical data in leading databases (i.e. SinoMed, etc.) is growing at an exponential rate, it might be possible to get something meaningful through the techniques developed in data mining. In this paper, focused on hypertension, we proposed an algorithm named two dimensions data slicing to mine rules of Chinese medicinal physical therapies (massage, cupping and so on). The process of mining was done in two dimensions. The one-dimension analyzes the frequencies. The two-dimension analyzes the frequencies of co-existed keyword pairs. By examining the results of these two dimensions, although some noises existed, most regular knowledge of this disease is mined out. This algorithm might be useful in mining rules in the literature of traditional Chinese medicine.

Through several thousands years of clinical research and theoretical thoughts, traditional Chinese medicine (TCM) has accumulated rich experience on hypertension. However, the usage of Chinese herbal medicines (CHMs) in formulae is flexible in TCM clinical practice according to pattern differentiation. So, it is important to get the composition rules of Chinese herbal medicines through literatures. Based on the keyword list of Chinese herbal medicine, through the keyword filtering skill, we got the lists of Chinese herbal medicines. However, for Chinese herbal medicine, they are not only mentioned in the plain format of herb names, but also densely described in the form of formulae. As formulae are composed by Chinese herbal medicines according the theory of traditional Chinese medicine, so it is necessary to filtering them out and de-compose them back into specified Chinese herbal medicines. In this study, take hypertension for example, we explored the composition-rules of Chinese herbal medicines and the network of TCM pattern with them. Networks of TCM patterns and CHMs which are most frequently used in hypertension treatment are built-up and analyzed, some regularities are obtained in treating hypertension from 175011 records of literature. And this method could provide useful help for TCM clinical application and Chinese medicine research.

Terrestrial laser scanner (TLS)-based leaf area index (LAI) retrieval is an appealing concept, due to the ability to capture structural information of canopies as 3-D point cloud data (PCD). TLS-based LAI estimation methods promise a nondestructive tool for spatially explicit calibration of LAI estimated by aerial or satellite remote sensing techniques. These methods also overcome the sky condition restrictions of on-ground optical instruments such as hemispherical photography frequently used for LAI estimation. This paper presents a new method for estimating the effective LAI (LAIe) directly from PCD generated by TLS in heterogeneous forests. We converted the 3-D PCD into 2-D raster images, similar to hemispherical photographs, using two geometrical projection techniques in order to estimate gap fraction and LAIe using a linear least squares method. Our results indicated that the TLS-based algorithm was able to capture the variability in LAIe of forest stands with a range of densities. The TLS-based LAIe estimation method explained 89.1% (rmse= 0.01 ;p<; 0.001) of the variation in results from digital hemispherical photographs taken of the same stands and used for validation. The Breusch-Pagan test score confirmed that the stereographic-projection-based TLS LAIe model was more robust compared to the Lambert azimuthal equal-area projection TLS LAIe model. Finally, we explore and show significant relationships between airborne-laser-scanner (ALS)-based and TLS-based LAIe estimates, showing promise for further exploration of utilizing TLS as a calibration tool for ALS.

Quantifying the 3-D forest canopy structure and leaf area index of an individual tree or a forest stand is challenging. The canopy structural information implicitly contained within point cloud data (PCD) generated from terrestrial laser scanning (TLS) makes it possible to characterize directly the spatial distribution of foliage elements. In this paper, a new voxel-based method titled “point cloud slicing” is presented to retrieve the biophysical characteristics of the forest canopy including extinction coefficient, gap fraction, overlapping effect, and effective leaf area (ELA) from PCD. These extractions were performed not only from the whole canopy but also from layers of the canopy to depict the distribution patterns of foliage elements within the canopy. The results showed that the TLS-based ELA estimation method could explain 88.7% (rmse= 0.007,pn= 30) variation of the destructive-sample-based leaf area measurement results. It was found that the sampling resolution was a key parameter in defining the dimension of a single voxel. Furthermore, the TLS-based method can also serve as a calibration tool for airborne laser scanning application with ground sampling.

Tree leaf orientation, including the distribution of the inclinational and azimuthal angles in the canopy, is an important attribute of forest canopy architecture and is critical in determining the within and below canopy solar radiation regimes. Characterizing leaf orientation is a key step to the retrieval of leaf area index (LAI) based on remotely sensed data, particularly discrete point data such as that provided by light detection and ranging. In this paper, we present a new method that indirectly and nondestructively retrieves foliage elements' orientation and distribution from point cloud data (PCD) obtained using a terrestrial laser scanning (TLS) approach. An artificial tree was used to develop the method using total least square fitting techniques to reconstruct the normal vectors from the PCD. The method was further validated on live tree crowns. An equation with a single parameter for characterizing the leaf angular distribution of crowns was developed. The TLS-based algorithm captures 97.4% (RMSE = 1.094 degrees, p <; 0.001) variation of the leaf inclination angle compared to manual measurements for an artificial tree. When applied to a live tree seedling and a mature tree crown, the TLS-based algorithm predicts 78.51% (RMSE = 1.225 degrees, p <; 0.001) and 57.28% (RMSE = 4.412 degrees, p <; 0.001) of the angular variability, respectively. Our results indicate that occlusion and noisy points affect the accuracy of normal vector estimation. Most importantly, this work provides a theoretical foundation for retrieving LAI from PCD obtained with a TLS.