ABSTRACT
The application of new-generation information technologies such as big data, the internet of things(IoT), and cloud computing in the traditional Chinese medicine(TCM)manufacturing industry is gradually deepening, driving the intelligent transformation and upgrading of the TCM industry. At the current stage, there are challenges in understanding the extraction process and its mechanisms in TCM. Online detection technology faces difficulties in making breakthroughs, and data throughout the entire production process is scattered, lacking valuable mining and utilization, which significantly hinders the intelligent upgrading of the TCM industry. Applying data-driven technologies in the process of TCM extraction can enhance the understanding of the extraction process, achieve precise control, and effectively improve the quality of TCM products. This article analyzed the technological bottlenecks in the production process of TCM extraction, summarized commonly used data-driven algorithms in the research and production control of extraction processes, and reviewed the progress in the application of data-driven technologies in the following five aspects: mechanism analysis of the extraction process, process development and optimization, online detection, process control, and production management. This article is expected to provide references for optimizing the extraction process and intelligent production of TCM.
Subject(s)
Medicine, Chinese Traditional , Drugs, Chinese Herbal , Quality Control , Big Data , AlgorithmsABSTRACT
<p><b>BACKGROUND</b>Hyperparathyroidism (HPT) occurs at an early age and has a high disability rate. Unfortunately, confirmed diagnosis in most patients is done at a very late stage, when the patients have shown typical symptoms and signs, and when treatment does not produce any desirable effect. It has become urgent to find a method that would detect early bone diseases in HPT to obtain time for the ideal treatment. This study evaluated the accuracy of high field magnetic resonance imaging (MRI) combined with spiral computed tomography (SCT) scan in detecting early bone diseases in HPT, through imaging techniques and histopathological examinations on an animal model of HPT.</p><p><b>METHODS</b>Eighty adult rabbits were randomly divided into two groups with forty in each. The control group was fed normal diet (Ca:P = 1:0.7); the experimental group was fed high phosphate diet (Ca:P = 1:7) for 3, 4, 5, or 6-month intervals to establish the animal model of HPT. The staging and imaging findings of the early bone diseases in HPT were determined by high field MRI and SCT scan at the 3rd, 4th, 5th and 6th month. Each rabbit was sacrificed after high field MRI and SCT scan, and the parathyroid and bones were removed for pathological examination to evaluate the accuracy of imaging diagnosis.</p><p><b>RESULTS</b>Parathyroid histopathological studies revealed hyperplasia, osteoporosis and early cortical bone resorption. The bone diseases in HPT displayed different levels of low signal intensity on T(1)WI and low to intermediate signal intensity on T(2)WI in bone of stage 0, I, II or III, but showed correspondingly absent, probable, osteoporotic and subperiosteal cortical resorption on SCT scan.</p><p><b>CONCLUSION</b>High field MRI combined with SCT scan not only detects early bone diseases in HPT, but also indicates staging, and might be a reliable method of studying early bone diseases in HPT.</p>