Bell's palsy is the most common condition involving a rapid and unilateral onset of peripheral paresis/paralysis of the seventh cranial nerve. It affects 11.5-53.3 per 100,000 individuals a year across different populations. Bell's palsy is a health issue causing concern and has an extremely negative effect on both patients and their families. Therefore, diagnosis and prompt cause determination are key for early treatment. However, the etiology of Bell's palsy is unclear, and this affects its treatment. Thus, it is critical to determine the causes of Bell's palsy so that targeted treatment approaches can be developed and employed. This article reviews the literature on the diagnosis of Bell's palsy and examines possible etiologies of the disorder. It also suggests that the diagnosis of idiopathic facial palsy is based on exclusion and is most often made based on five factors including anatomical structure, viral infection, ischemia, inflammation, and cold stimulation responsivity.

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Botanical primary metabolites extensively exist in herbal medicine injections (HMIs), but often were ignored to control. With the limitation of bias towards hydrophilic substances, the primary metabolites with strong polarity, such as saccharides, amino acids and organic acids, are usually difficult to detect by the routinely applied reversed-phase chromatographic fingerprint technology. In this study, a proton nuclear magnetic resonance (1H NMR) profiling method was developed for efficient identification and quantification of small polar molecules, mostly primary metabolites in HMIs. A commonly used medicine, Danhong injection (DHI), was employed as a model. With the developed method, 23 primary metabolites together with 7 polyphenolic acids were simultaneously identified, of which 13 metabolites with fully separated proton signals were quantified and employed for further multivariate quality control assay. The quantitative 1H NMR method was validated with good linearity, precision, repeatability, stability and accuracy. Based on independence principal component analysis (IPCA), the contents of 13 metabolites were characterized and dimensionally reduced into the first two independence principal components (IPCs). IPC1 and IPC2 were then used to calculate the upper control limits (with 99% confidence ellipsoids) of χ2 and Hotelling T2 control charts. Through the constructed upper control limits, the proposed method was successfully applied to 36 batches of DHI to examine the out-of control sample with the perturbed levels of succinate, malonate, glucose, fructose, salvianic acid and protocatechuic aldehyde. The integrated strategy has provided a reliable approach to identify and quantify multiple polar metabolites of DHI in one fingerprinting spectrum, and it has also assisted in the establishment of IPCA models for the multivariate statistical evaluation of HMIs.