Investigation of liquid biopsy analytes in peripheral blood of individuals after SARS-CoV-2 infection.

BACKGROUND: Post-acute COVID-19 syndrome (PACS) is linked to severe organ damage. The identification and stratification of at-risk SARS-CoV-2 infected individuals is vital to providing appropriate care. This exploratory study looks for a potential liquid biopsy signal for PACS using both manual and machine learning approaches. METHODS: Using a high definition single cell assay (HDSCA) workflow for liquid biopsy, we analysed 100 Post-COVID patients and 19 pre-pandemic normal donor (ND) controls. Within our patient cohort, 73 had received at least 1 dose of vaccination prior to SARS-CoV-2 infection. We stratified the COVID patients into 25 asymptomatic, 22 symptomatic COVID-19 but not suspected for PACS and 53 PACS suspected. All COVID-19 patients investigated in this study were diagnosed between April 2020 and January 2022 with a median 243 days (range 16-669) from diagnosis to their blood draw. We did a histopathological examination of rare events in the peripheral blood and used a machine learning model to evaluate predictors of PACS. FINDINGS: The manual classification found rare cellular and acellular events consistent with features of endothelial cells and platelet structures in the PACS-suspected cohort. The three categories encompassing the hypothesised events were observed at a significantly higher incidence in the PACS-suspected cohort compared to the ND (p-value < 0.05). The machine learning classifier performed well when separating the NDs from Post-COVID with an accuracy of 90.1%, but poorly when separating the patients suspected and not suspected of PACS with an accuracy of 58.7%. INTERPRETATION: Both the manual and the machine learning model found differences in the Post-COVID cohort and the NDs, suggesting the existence of a liquid biopsy signal after active SARS-CoV-2 infection. More research is needed to stratify PACS and its subsyndromes. FUNDING: This work was funded in whole or in part by Fulgent Genetics, Kathy and Richard Leventhal and Vassiliadis Research Fund. This work was also supported by the National Cancer InstituteU54CA260591.

An Adaptable Framework for Factors Contributing to Medication Adherence: Results from a Systematic Review of 102 Conceptual Frameworks.

OBJECTIVE: To summarize the available conceptual models for factors contributing to medication adherence based on the World Health Organization (WHO)'s five dimensions of medication adherence via a systematic review, identify the patient groups described in available conceptual models, and present an adaptable conceptual model that describes the factors contributing to medication adherence in the identified patient groups. METHODS: We searched PubMed®, Embase®, CINAHL®, and PsycINFO® for English language articles published from inception until 31 March 2020. Full-text original publications in English that presented theoretical or conceptual models for factors contributing to medication adherence were included. Studies that presented statistical models were excluded. Two authors independently extracted the data. RESULTS: We identified 102 conceptual models, and classified the factors contributing to medication adherence using the WHO's five dimensions of medication adherence, namely patient-related, medication-related, condition-related, healthcare system/healthcare provider-related, and socioeconomic factors. Eight patient groups were identified based on age and disease condition. The most universally addressed factors were patient-related factors. Medication-related, condition-related, healthcare system-related, and socioeconomic factors were represented to various extents depending on the patient group. By systematically examining how the WHO's five dimensions of medication adherence were applied differently across the eight different patient groups, we present a conceptual model that can be adapted to summarize the common factors contributing to medication adherence in different patient groups. CONCLUSION: Our conceptual models can be utilized as a guide for clinicians and researchers in identifying the facilitators and barriers to medication adherence and developing future interventions to improve medication adherence. PROTOCOL REGISTRATION: PROSPERO Identifier: CRD42020181316.

Qualitative and quantitative characterization of carbohydrate profiles in three different parts of Poria cocos.

Poria cocos (Schw.) Wolf has been widely used in traditional Chinese medicine (TCM) for centuries. Its three medicinal parts are Poria Cutis, the epidermis or fulingpi in Chinese; White Poria, the middle part or baifuling; and Poria cum Radix Pini, the sclerotium with some part of host pine root or fushen. The hostwood in fushen is the inner part, known as fushenmu. The epidermis, middle part and middle-plus-inner part have different clinical applications, but the differences in their chemistry have not been well determined. Previous studies only concentrated on the differences in secondary metabolites in different parts of P. cocos; however, in this study, we focused on the carbohydrates, another major type of bioactive chemicals in P. cocos, which is also different from most of the other TCM researches. The carbohydrates (polysaccharides, oligosaccharides and monosaccharides) in three parts (epidermis, middle and inner part) of P. cocos were qualitatively and quantitatively characterized by high performance gel permeation chromatography coupled with charged aerosol detector (HPGPC-CAD) and ultra-performance liquid chromatography coupled with triple quadrupole mass spectrometry (UHPLC-QqQ-MS/MS). The obtained data were further processed by principal component analysis (PCA) and supervised orthogonal partial least squared discriminant analysis (OPLS-DA). The results showed that the epidermis contained more polysaccharides with larger molecular weight and higher amount of glucose residue than that of the middle and inner parts, indicating the epidermis as the key site of accumulation of P. cocos polysaccharides. When compared with the epidermis and inner part, the middle part contained the highest glucose molar ratio greater than 92 % in the three types of carbohydrates, whereas the inner part possessed the greatest molar ratio of mannose, xylose, arabinose, rhamnose, glucuronic acid, and galacturonic acid in all kinds of carbohydrates. Furthermore, PCA and OPLS-DA clearly demonstrated that arabinose, glucose, galacturonic acid, and ribose played key roles in the clusters between the epidermis, middle and inner parts. The observed differences in the chemical components in the three parts could provide some explanation for the discriminative clinical applications of Poria Cutis, White Poria, and Poria cum Radix Pini. These findings also provided a chemical basis for quality assessment of P. cocos.

Comparative quality of the forms of decoction pieces evaluated by multidimensional chemical analysis and chemometrics: Poria cocos, a pilot study.

Many Chinese medicinal materials (CMMs) are parts of plants or fungi that have been processed into different physical forms, termed decoction pieces, that are typically boiled in water for consumption. One CMM may have several decoction pieces forms, e.g., slices, small cubes (dice), or grains. The specifications that have different morphological parameters (shape, size and thickness) for these various decoction pieces have been developed over, in some cases, centuries of practice. Nevertheless, whether and how the form of decoction pieces affects the extraction (decoction) dynamics, and quality stability during storage has not been studied. Here, we investigated Poria cocos (PC) as a pilot study; we explore how the form of PC decoction pieces affects its chemistry using multidimensional chemical evaluation such as ultra-performance liquid chromatography-photodiode array-quadrupole time-of-flight mass spectrometry (UHPLC-PDA-QTOF-MS/MS), ultra-performance liquid chromatography-triple quadrupole mass spectrometry (UHPLC-QqQ-MS/MS) and high performance gel permeation chromatography coupled with charged aerosol detector (HPGPC-CAD), combined with analysis of variance (ANOVA), principal component analysis (PCA), factor analysis (FA) and hierarchical cluster analysis (HCA). The results indicated that different specifications had significant differences, and these specifications could be divided into four groups. The comprehensive results of the chemical analyses undertaken here indicate that the highest potentially available quality of PC decoction pieces was in the forms of curl, ultra-small grains and small grains, followed by thin slices. This information not only is conducive to promoting the standardization of the specification/form of PC decoction pieces and maximizing the benefits from its utilization, but also provide a promising strategy for assessing other CMM decoction pieces in different forms.

Coupling Reactions of Alkynyl Indoles and CO2 by Bicyclic Guanidine: Origin of Catalytic Activity?

Density functional theory calculations were used to investigate the three possible modes of activation for the coupling of CO2 with alkynyl indoles in the presence of a guanidine base. The first of these mechanisms, involving electrophilic activation, was originally proposed by Skrydstrup et al. (Angew. Chem. Int. Ed. 2015, 54, 6682). The second mechanism involves the nucleophilic activation of CO2 . Both of these electrophilic and nucleophilic activation processes involve the formation of a guanidine-CO2 zwitterion adduct. We have proposed a third mechanism involving the bifunctional activation of the bicyclic guanidine catalyst, allowing for the simultaneous activation of the indole and CO2 by the catalyst. We demonstrated that a second molecule of catalyst is required to facilitate the final cyclization step. Based on the calculated turnover frequencies, our newly proposed bifunctional activation mechanism is the most plausible pathway for this reaction under these experimental conditions. Furthermore, we have shown that this bifunctional mode of activation is consistent with the experimental results. Thus, this guanidine-catalyzed reaction favors a specific-base catalyzed mechanism rather than the CO2 activation mechanism. We therefore believe that this bifunctional mechanism for the activation of bicyclic guanidine is typical of most CO2 coupling reactions.