UNASSIGNED: In December 2019, a novel coronavirus, SARS-CoV-2 caused a series of acute atypical respiratory diseases worldwide. However, there is still a lack of drugs with clear curative effects, and the clinical trial research of vaccines has not been completely finished.
UNASSIGNED: LH capsules are approved TCM patent medicine that are widely used for the treatment of respiratory tract infectious diseases caused by colds and flu. On April 12, 2020, LH capsules and granules were officially repurposed by the China Food and Drug Administration (CFDA) for patients with mild COVID-19 based on their safety and efficacy demonstrated through multicentre, randomized, controlled clinical trials. We hope to conduct a comprehensive review of it through modern pharmacy methods, and try to explain its possible mechanism.
UNASSIGNED: Using the full names of LH capsules Lianhuaqingwen, Lianhua Qingwen andSARS-COV-2, COVID-19 as the keywords of the search terms, systemically search for existing related papers in various databases such as Web of Science and PubMed. And completed the collection of clinical data in ClinicalTrials.gov and Chinese Clinical Trial Registry. Last but not least, we have sorted out the anti-inflammatory and antiviral mechanisms of LH capsules through literature and Selleck.
UNASSIGNED: This review systematically sorted out the active ingredients in LH capsules. Furthermore, the related pharmacological and clinical trials of LH capsule on SARS-CoV-2, IAV and IBV were discussed in detail. Moreover, the present review provides the first summary of the potential molecular mechanism of specific substances in LH capsules involved in resistance to SARS-COV-2 infection and the inhibition of cytokine storm syndrome (CSS) caused by IL-6.
UNASSIGNED: This review summarizes the available reports and evidence that support the use of LH capsules as potential drug candidates for the prevention and treatment of COVID-19. However, TCM exerts its effects through multiple targets and multiple pathways, and LH capsules are not an exception. Therefore, the relevant mechanisms need to be further improved and experimentally verified.

The use of small interfering RNAs (siRNAs) has been under investigation for the treatment of several unmet medical needs, including acute lung injury/acute respiratory distress syndrome (ALI/ARDS) wherein siRNA may be implemented to modify the expression of pro-inflammatory cytokines and chemokines at the mRNA level. The properties such as clear anatomy, accessibility, and relatively low enzyme activity make the lung a good target for local siRNA therapy. However, the translation of siRNA is restricted by the inefficient delivery of siRNA therapeutics to the target cells due to the properties of naked siRNA. Thus, this review will focus on the various delivery systems that can be used and the different barriers that need to be surmounted for the development of stable inhalable siRNA formulations for human use before siRNA therapeutics for ALI/ARDS become available in the clinic.

Severity prediction of COVID-19 remains one of the major clinical challenges for the ongoing pandemic. Here, we have recruited a 144 COVID-19 patient cohort, resulting in a data matrix containing 3,065 readings for 124 types of measurements over 52 days. A machine learning model was established to predict the disease progression based on the cohort consisting of training, validation, and internal test sets. A panel of eleven routine clinical factors constructed a classifier for COVID-19 severity prediction, achieving accuracy of over 98% in the discovery set. Validation of the model in an independent cohort containing 25 patients achieved accuracy of 80%. The overall sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 0.70, 0.99, 0.93, and 0.93, respectively. Our model captured predictive dynamics of lactate dehydrogenase (LDH) and creatine kinase (CK) while their levels were in the normal range. This model is accessible at https://www.guomics.com/covidAI/ for research purpose.

The quality control processes for herbal medicines have been problematic. Flavonoids are the major active components of Huangqin Tang (HQT, a traditional Chinese medicine formula). In this study, we used a combinative method approach consisting of chromatographic fingerprinting (high performance liquid chromatography; HPLC), quantitative methods and a pharmacodynamic evaluation model to analyze the flavonoids of HQT obtained from different sources. Ten batches of HQT were analyzed by the HPLC fingerprinting method and 26 common peaks were detected, of which 23 peaks corresponded with the chemical profile of HQT. In addition, 11 major compounds were identified by LC-MS analysis (liquid chromatography-tandem mass spectrometer; LC-MS (n) ) and quantified by the HPLC quantitative method approach. The studied 10 batches of HQT were found to be homogeneous in their composition with a similarity between 0.990 and 1.000. The distribution of the 11 identified compounds was found to be very similar among the batches. Only slight pharmacodynamic differences were detected between the different batches, confirming the homogeneity of HQT. The results of this study prove that the combination of chromatographic fingerprinting and quantitative analysis can be readily used for comprehensive quality control of herbal medicines.