Near-infrared reflectance spectroscopy (NIRS) for rapid determination of ginsenoside Rg1 and Re in Chinese patent medicine Naosaitong pill

Machine Learning Approaches in Traditional Chinese Medicine: A Systematic Review

Machine learning (ML), as a branch of artificial intelligence, acquires the potential and meaningful rules from the mass of data via diverse algorithms. Owing to all research of traditional Chinese medicine (TCM) belonging to the digitalization of clinical records or experimental works, a massive and complex amount of data has become an inextricable part of the related studies. It is thus not surprising that ML approaches, as novel and efficient tools to mine the useful knowledge from data, have created inroads in a diversity of scopes of TCM over the past decade of years. However, by browsing lots of literature, we find that not all of the ML approaches perform well in the same field. Upon further consideration, we infer that the specificity may inhere between the ML approaches and their applied fields. This systematic review focuses its attention on the four categories of ML approaches and their eight application scopes in TCM. According to the function, ML approaches are classified into four categories, including classification, regression, clustering, and dimensionality reduction, and into 14 models as follows in more detail: support vector machine, least square-support vector machine, logistic regression, partial least squares regression, k-means clustering, hierarchical cluster analysis, artificial neural network, back propagation neural network, convolutional neural network, decision tree, random forest, principal component analysis, partial least squares-discriminant analysis, and orthogonal partial least squares-discriminant analysis. The eight common applied fields are divided into two parts: one for TCM, such as the diagnosis of diseases, the determination of syndromes, and the analysis of prescription, and the other for the related researches of Chinese herbal medicine, such as the quality control, the identification of geographic origins, the pharmacodynamic material basis, the medicinal properties, and the pharmacokinetics and pharmacodynamics. Additionally, this paper discusses the function and feature difference among ML approaches when they are applied to the corresponding fields via comparing their principles. The specificity of each approach to its applied fields has also been affirmed, whereby laying a foundation for subsequent studies applying ML approaches to TCM.

Advances and challenges in ginseng research from 2011 to 2020: the phytochemistry, quality control, metabolism, and biosynthesis

Covering: 2011 to the end of 2020Panax species (Araliaceae), particularly P. ginseng, P. quinquefolius, and P. notoginseng, have a long history of medicinal use because of their remarkable tonifying effects, and currently serve as crucial sources for various healthcare products, functional foods, and cosmetics, aside from their vast clinical preparations. The huge market demand on a global scale prompts the continuous prosperity in ginseng research concerning the discovery of new compounds, precise quality control, ADME (absorption/disposition/metabolism/excretion), and biosynthesis pathways. Benefitting from the ongoing rapid development of analytical technologies, e.g. multi-dimensional chromatography (MDC), personalized mass spectrometry (MS) scan strategies, and multi-omics, highly recognized progress has been made in driving ginseng analysis towards "systematicness, integrity, personalization, and intelligentization". Herein, we review the advances in the phytochemistry, quality control, metabolism, and biosynthesis pathway of ginseng over the past decade (2011-2020), with 410 citations. Emphasis is placed on the introduction of new compounds isolated (saponins and polysaccharides), and the emerging novel analytical technologies and analytical strategies that favor ginseng's authentic use and global consumption. Perspectives on the challenges and future trends in ginseng analysis are also presented.

Brain functional alterations observed 4-weekly in major depressive disorder following antidepressant treatment

BACKGROUND

Major depressive disorder (MDD) is a heterogeneous condition. Identifying the brain responses to antidepressant treatment is of particular interest as these may represent potential neural networks related to treatment response, forming one aspect of the biological markers of MDD. Near-infrared spectroscopy (NIRS) is suitable for repeated measurements with short intervals because of its noninvasiveness, and can provide detailed time courses of functional alterations in prefrontal regions.

METHODS

We conducted a 12-week longitudinal study to explore prefrontal hemodynamic changes at 4-week intervals following sertraline treatment in 11 medication-naïve participants with MDD using 52-channel NIRS.

RESULTS

While all participants achieved remission after treatment, intra-class correlation coefficient of oxygenated hemoglobin [oxy-Hb] values throughout the 12-week observation was moderate at the spatially and temporally contiguous cluster located in the left inferior frontal and temporal gyri. There was a significant negative correlation between mean [oxy-Hb] values in the significant cluster at 4 weeks and changes in Hamilton Rating Scale for Depression total score from 4 to 8 weeks (r = -0.73, P = 0.011) and from 4 to 12 weeks (r = -0.63, P = 0.039).

LIMITATIONS

Without healthy controls for comparison, we were unable to fully evaluate whether improvement of [oxy-Hb] activations after treatment in MDD reached normal levels or not.

CONCLUSION

Our NIRS findings of detailed prefrontal hemodynamic alterations over short interval observations such as 4 weeks may have revealed potential trait marker for MDD and biological maker for predicting clinical response to sertraline treatment in MDD.

Analytical methods and biological activities of Panax notoginseng saponins: Recent trends

ETHNOPHARMACOLOGICAL RELEVANCE

Panax notoginseng (Burk.) F. H. Chen, also called Sanqi, is a widely used traditional Chinese medicine, which has long history used as herbal medicines. It is currently an important medicinal material in China, holding the first place in the sale volume of the whole patent medicines market in China, and the market size of the single species has exceeded 10 billion yuan. In addition, P. notoginseng is an important constituent part of many famous Chinese patent medicines, such as Compound Danshen Dripping Pills and Yunnan Baiyao. P. notoginseng saponins (PNSs), which are the major active components of P. notoginseng, are a kind of chemical mixture containing different dammarane-type saponins. Many studies show that PNSs have been extensively used in medical research or applications, such as atherosclerosis, diabetes, acute lung injury, cancer, and cardiovascular diseases. In addition, various PNS preparations, such as injections and capsules, have been made commercially available and are widely applied in clinical practice.

AIM OF THE REVIEW

Since the safety and efficacy of compounds are related to their qualitative and quantitative analyses, this review briefly summarizes the analytic approaches for PNSs and their biological effects developed in the last decade.

METHODOLOGY

This review conducted a systematic search in electronic databases, such as Pubmed, Google Scholar, SciFinder, ISI Web of Science, and CNKI, since 2009. The information provided in this review is based on peer-reviewed papers and patents in either English or Chinese.

RESULTS

At present, the chromatographic technique remains the most extensively used approach for the identification or quantitation of PNSs, coupled with different detectors, among which the difference mainly lies in their sensitivity and specificity for analyzing various compounds. It is well-known that PNSs have traditionally strong activity on cardiovascular diseases, such as atherosclerosis, intracerebral hemorrhage, or brain injury. The recent studies showed that PNSs also responded to osteoporosis, cancers, diabetes, and drug toxicity. However, some other studies also showed that some PNSs injections and special PNS components might lead to some biological toxicity under certain dosages.

CONCLUSION

This review may be used as a basis for further research in the field of quantitative and qualitative analyses, and is expected to provide updated and valuable insights into the potential medicinal applications of PNSs.

Detection of Cistanches Herba (Rou Cong Rong) Medicinal Products Using Species-Specific Nucleotide Signatures

Cistanches Herba is a medicinal plant that has tonification properties and is commonly used in Asia. Owing to the imbalance between supply and demand, adulterants are frequently added for profit. However, there is no regulatory oversight because quality control tools are not sufficient for identifying heavily processed products. Thus, a novel molecular tool based on nucleotide signatures and species-specific primers was developed. The ITS2 regions from 251 Cistanches Herba and adulterant samples were sequenced. On the basis of SNP sites, four nucleotide signatures within 30~37 bp and six species-specific primers were developed, and they were validated by artificial experimental mixtures consisting of six different species and different ratios. This method was also applied to detect 66 Cistanches Herba products on the market, including extracts and Chinese patent medicines. The results demonstrated the utility of nucleotide signatures in identifying adulterants in mixtures. The market study revealed 36.4% adulteration: 19.7% involved adulteration with Cynomorium songaricum or Cistanche sinensis, and 16.7% involved substitution with Cy. songaricum, Ci. sinensis, or Boschniakia rossica. The results also revealed that Cy. songaricum was the most common adulterant in the market. Thus, we recommend the use of species-specific nucleotide signatures for regulating adulteration and verifying the quality assurance of medicinal product supply chains, especially for processed products whose DNA is degraded.

High-throughput prediction of tablet weight and trimethoprim content of compound sulfamethoxazole tablets for controlling the uniformity of dosage units by NIR

This paper establishes a novel method to simultaneously predict the tablet weight (TW) and trimethoprim (TMP) content of compound sulfamethoxazole tablets (SMZCO) by near infrared (NIR) spectroscopy with partial least squares (PLS) regression for controlling the uniformity of dosage units (UODU). The NIR spectra for 257 samples were measured using the optimized parameter values and pretreated using the optimized chemometric techniques. After the outliers were ignored, two PLS models for predicting TW and TMP content were respectively established by using the selected spectral sub-ranges and the reference values. The TW model reaches the correlation coefficient of calibration (R(c)) 0.9543 and the TMP content model has the R(c) 0.9205. The experimental results indicate that this strategy expands the NIR application in controlling UODU, especially in the high-throughput and rapid analysis of TWs and contents of the compound pharmaceutical tablets, and may be an important complement to the common NIR on-line analytical method for pharmaceutical tablets.