Network pharmacology: towards the artificial intelligence-based precision traditional Chinese medicine.

Network pharmacology (NP) provides a new methodological perspective for understanding traditional medicine from a holistic perspective, giving rise to frontiers such as traditional Chinese medicine network pharmacology (TCM-NP). With the development of artificial intelligence (AI) technology, it is key for NP to develop network-based AI methods to reveal the treatment mechanism of complex diseases from massive omics data. In this review, focusing on the TCM-NP, we summarize involved AI methods into three categories: network relationship mining, network target positioning and network target navigating, and present the typical application of TCM-NP in uncovering biological basis and clinical value of Cold/Hot syndromes. Collectively, our review provides researchers with an innovative overview of the methodological progress of NP and its application in TCM from the AI perspective.

The Development of a New IFOG-Based 3C Rotational Seismometer.

For many years, seismological research mainly focuses on translational ground motions due to the lack of appropriate sensors. However, because of the development of devices based on Sagnac effect, measuring rotational waves directly comes available. In this work, a portable three-component broadband rotational seismometer named RotSensor3C based on open loop interferometric fiber optic gyroscope (IFOG) is designed and demonstrated. Laboratory tests and results are illustrated in detail. The self-noise ranging from 0.005 Hz to 125 Hz is about 1.2×10-7rads-1/Hz, and with the harmonics compensation the scale factor variation over ±250∘/s is lower than 10 ppm (parts per million). The misalignment matrix method is adopted to revise the output rotation rate. In a special near field experiment using the explosive source, the back-azimuths and phase velocity are estimated by the recorded acceleration and rotation rate. All the results prove the practicability of this new rotational sensor.

Assessing life-cycle GHG emissions of recycled paper products under imported solid waste ban in China: A case study.

Changes of raw materials in China's recycled paper industry after the imported solid waste ban affect products' life-cycle greenhouse gas (GHG) emissions as well. This paper presented a case study of newsprint production with prior- and post-ban scenarios with life cycle assessment, including using imported waste paper (P0) and its three substitutions, i.e., virgin pulp (P1), domestic waste paper (P2), and imported recycled pulp (P3). The function unit is 1 ton of newsprint produced in China, and the study is conducted from cradle to grave which consists pulping and papermaking process, from raw material acquisition to manufacturing, with associated energy production and wastewater treatment, transport, and chemicals production. Our results showed that P1 holds the highest life-cycle GHG emission of 2724.91, followed by 2400.88 from P3. P2 has the lowest emission of 1619.27, only slightly lower than 1742.39 before the ban using route P0 (unit: kgCO2e/ton paper). Scenario analysis showed that current average life-cycle GHG emission for one ton of newsprint is 2049.33 kgCO2e, increased by 17.62 % due to the ban, while this number could be reduced to 12.22 % or even -0.79 % if switching from P1 to P3 and P2. Our study highlighted the importance of domestic waste paper as a promising way to reduce GHG emissions, which still has great potential to increase if with an enhanced waste paper recycling system in China.

Uncovering the mechanisms of Yi Qi Tong Qiao Pill in the treatment of allergic rhinitis based on Network target analysis.

OBJECTIVE: The purpose of this study is to reveal the mechanism of action of Yi Qi Tong Qiao Pill (YQTQP) in the treatment of allergic rhinitis (AR), as well as establish a paradigm for the researches on traditional Chinese medicine (TCM) from systematic perspective. METHODS: Based on the data collected from TCM-related and disease-related databases, target profiles of compounds in YQTQP were calculated through network-based algorithms and holistic targets of TQTQP was constructed. Network target analysis was performed to explore the potential mechanisms of YQTQP in the treatment of AR and the mechanisms were classified into different modules according to their biological functions. Besides, animal and clinical experiments were conducted to validate our findings inferred from Network target analysis. RESULTS: Network target analysis showed that YQTQP targeted 12 main pathways or biological processes related to AR, represented by those related to IL-4, IFN-γ, TNF-α and IL-13. These results could be classified into 3 biological modules, including regulation of immune and inflammation, epithelial barrier disorder and cell adhesion. Finally, a series of experiments composed of animal and clinical experiments, proved our findings and confirmed that YQTQP could improve related symptoms of AR, like permeability of nasal mucosa epithelium. CONCLUSION: A combination of Network target analysis and the experimental validation indicated that YQTQP was effective in the treatment of AR and might provide a new insight on revealing the mechanism of TCM against diseases. Trial registration Name of the registry: Chinese Clinical Trial Registry: Trial registration number: ChiCTR-TRC-13,003,137: Date of registration: Registered 29 March 2013 - Retrospectively registered: URL of trial registry record: https://www.chictr.org.cn/showproj.html?proj=6422 .