Abstract: BACKGROUND: In this study, we focus on building a fine-grained entity annotation corpus with the corresponding annotation guideline of traditional Chinese medicine (TCM) clinical records. Our aim is to provide a basis for the fine-grained corpus construction of TCM clinical records in future. METHODS: We developed a four-step approach that is suitable for the construction of TCM medical records in our corpus. First, we determined the entity types included in this study through sample annotation. Then, we drafted a fine-grained annotation guideline by summarizing the characteristics of the dataset and referring to some existing guidelines. We iteratively updated the guidelines until the inter-annotator agreement (IAA) exceeded a Cohen's kappa value of 0.9. Comprehensive annotations were performed while keeping the IAA value above 0.9. RESULTS: We annotated the 10,197 clinical records in five rounds. Four entity categories involving 13 entity types were employed. The final fine-grained annotated entity corpus consists of 1104 entities and 67,799 tokens. The final IAAs are 0.936 on average (for three annotators), indicating that the fine-grained entity recognition corpus is of high quality. CONCLUSIONS: These results will provide a foundation for future research on corpus construction and named entity recognition tasks in the TCM clinical domain.

Abstract: Natural products (NPs) have been the centre of attention of the scientific community in the last decencies and the interest around them continues to grow incessantly. As a consequence, in the last 20 years, there was a rapid multiplication of various databases and collections as generalistic or thematic resources for NP information. In this review, we establish a complete overview of these resources, and the numbers are overwhelming: over 120 different NP databases and collections were published and re-used since 2000. 98 of them are still somehow accessible and only 50 are open access. The latter include not only databases but also big collections of NPs published as supplementary material in scientific publications and collections that were backed up in the ZINC database for commercially-available compounds. Some databases, even published relatively recently are already not accessible anymore, which leads to a dramatic loss of data on NPs. The data sources are presented in this manuscript, together with the comparison of the content of open ones. With this review, we also compiled the open-access natural compounds in one single dataset a COlleCtion of Open NatUral producTs (COCONUT), which is available on Zenodo and contains structures and sparse annotations for over 400,000 non-redundant NPs, which makes it the biggest open collection of NPs available to this date.

Abstract: BACKGROUND: Multiple sclerosis (MS) is a complex disease in which the immune system attacks the central nervous system. The molecular mechanisms contributing to the etiology of MS remain poorly understood. Genome-wide association studies (GWAS) of MS have identified a small number of genetic loci significant at the genome level, but they are mainly non-coding variants. Network-assisted analysis may help better interpret the functional roles of the variants with association signals and potential translational medicine application. The Dense Module Searching of GWAS tool (dmGWAS version 2.4) developed in our team is applied to 2 MS GWAS datasets (GeneMSA and IMSGC GWAS) using the human protein interactome as the reference network. A dual evaluation strategy is used to generate results with reproducibility. RESULTS: Approximately 7500 significant network modules were identified for each independent GWAS dataset, and 20 significant modules were identified from the dual evaluation. The top modules included GRB2, HDAC1, JAK2, MAPK1, and STAT3 as central genes. Top module genes were enriched with functional terms such as "regulation of glial cell differentiation" (adjusted p-value = 2.58 x 10(- 3)), "T-cell costimulation" (adjusted p-value = 2.11 x 10(- 6)) and "virus receptor activity" (adjusted p-value = 1.67 x 10(- 3)). Interestingly, top gene networks included several MS FDA approved drug target genes HDAC1, IL2RA, KEAP1, and RELA, CONCLUSIONS: Our dmGWAS network analyses highlighted several genes (GRB2, HDAC1, IL2RA, JAK2, KEAP1, MAPK1, RELA and STAT3) in top modules that are promising to interpret GWAS signals and link to MS drug targets. The genes enriched with glial cell differentiation are important for understanding neurodegenerative processes in MS and for remyelination therapy investigation. Importantly, our identified genetic signals enriched in T cell costimulation and viral receptor activity supported the viral infection onset hypothesis for MS.

Abstract: Non-targeted and suspect analyses with liquid chromatography/electrospray/high-resolution mass spectrometry (LC/ESI/HRMS) are gaining importance as they enable identification of hundreds or even thousands of compounds in a single sample. Here, we present an approach to address the challenge to quantify compounds identified from LC/HRMS data without authentic standards. The approach uses random forest regression to predict the response of the compounds in ESI/HRMS with a mean error of 2.2 and 2.0 times for ESI positive and negative mode, respectively. We observe that the predicted responses can be transferred between different instruments via a regression approach. Furthermore, we applied the predicted responses to estimate the concentration of the compounds without the standard substances. The approach was validated by quantifying pesticides and mycotoxins in six different cereal samples. For applicability, the accuracy of the concentration prediction needs to be compatible with the effect (e.g. toxicology) predictions. We achieved the average quantification error of 5.4 times, which is well compatible with the accuracy of the toxicology predictions.

Abstract: The recent epidemic outbreak of a novel human coronavirus called SARS-CoV-2 causing the respiratory tract disease COVID-19 has reached worldwide resonance and a global effort is being undertaken to characterize the molecular features and evolutionary origins of this virus. In this paper, we set out to shed light on the SARS-CoV-2/host receptor recognition, a crucial factor for successful virus infection. Based on the current knowledge of the interactome between SARS-CoV-2 and host cell proteins, we performed Master Regulator Analysis to detect which parts of the human interactome are most affected by the infection. We detected, amongst others, affected apoptotic and mitochondrial mechanisms, and a downregulation of the ACE2 protein receptor, notions that can be used to develop specific therapies against this new virus.

Abstract: Natural products (NPs) are a significant source of inspiration towards the discovery of new bioactive compounds based on novel molecular scaffolds. However, there are currently only a small number of guiding synthetic strategies available to generate novel NP-inspired scaffolds, limiting both the number and types of compounds accessible. In this Perspective, we discuss a design approach for the preparation of biologically relevant small-molecule libraries, harnessing the unprecedented combination of NP-derived fragments as an overarching strategy for the synthesis of new bioactive compounds. These novel 'pseudo-natural product' classes retain the biological relevance of NPs, yet exhibit structures and bioactivities not accessible to nature or through the use of existing design strategies. We also analyse selected pseudo-NP libraries using chemoinformatic tools, to assess their molecular shape diversity and properties. To facilitate the exploration of biologically relevant chemical space, we identify design principles and connectivity patterns that would provide access to unprecedented pseudo-NP classes, offering new opportunities for bioactive small-molecule discovery.

Abstract: The presence of drugs in the environment is an emerging issue in the scientific community. It has been shown that these substances are active chemicals that consequently affect aquatic organisms and, finally, humans as end users. To evaluate the toxicity of these compounds and how they affect the environment, it is important to perform systematic ecotoxicological and physicochemical studies. The best way to address this problem is to conduct studies on different aquatic trophic levels. In this work, an ecotoxicological study of six drugs (anhydrous caffeine, diphenhydramine hydrochloride, gentamicin sulphate, lidocaine hydrochloride, tobramycin sulphate and enalapril maleate) that used three aquatic biological models (Raphidocelis subcapitata, Aliivibrio fischeri and Daphnia magna) was performed. Additionally, the concentration of chlorophyll in the algae R. subcapitata was measured. Furthermore, EC50 values were analysed using the Passino and Smith classification (PSC) method, which categorized the compounds as toxic or relatively toxic. All of the studied drugs showed clear concentration-dependent toxic effects. The toxicity of the chemicals depended on the biological model studied, with Raphidocelis subcapitata being the most sensitive species and Aliivibrio fischeri being the least sensitive. The results indicate that the most toxic compound, for all the studied biological models, was diphenhydramine hydrochloride. Graphical abstract.

Abstract: BACKGROUND: Acute respiratory distress syndrome (ARDS) is a lung inflammatory process caused mainly by sepsis. Most previous studies that identified genetic risks for ARDS focused on candidates with biological relevance. We aimed to identify novel genetic variants associated with ARDS susceptibility and to provide complementary functional evidence of their effect in gene regulation. METHODS: We did a case-control genome-wide association study (GWAS) of 1935 European individuals, using patients with sepsis-associated ARDS as cases and patients with sepsis without ARDS as controls. The discovery stage included 672 patients admitted into a network of Spanish intensive care units between January, 2002, and January, 2017. The replication stage comprised 1345 individuals from two independent datasets from the MESSI cohort study (Sep 22, 2008-Nov 30, 2017; USA) and the VISEP (April 1, 2003-June 30, 2005) and MAXSEP (Oct 1, 2007-March 31, 2010) trials of the SepNet study (Germany). Results from discovery and replication stages were meta-analysed to identify association signals. We then used RNA sequencing data from lung biopsies, in-silico analyses, and luciferase reporter assays to assess the functionallity of associated variants. FINDINGS: We identified a novel genome-wide significant association with sepsis-associated ARDS susceptibility (rs9508032, odds ratio [OR] 0.61, 95% CI 0.41-0.91, p=5.18 x 10(-8)) located within the Fms-related tyrosine kinase 1 (FLT1) gene, which encodes vascular endothelial growth factor receptor 1 (VEGFR-1). The region containing the sentinel variant and its best proxies acted as a silencer for the FLT1 promoter, and alleles with protective effects in ARDS further reduced promoter activity (p=0.0047). A literature mining of all previously described ARDS genes validated the association of vascular endothelial growth factor A (VEGFA; OR 0.55, 95% CI 0.41-0.73; p=4.69 x 10(-5)). INTERPRETATION: A common variant within the FLT1 gene is associated with sepsis-associated ARDS. Our findings support a role for the vascular endothelial growth factor signalling pathway in ARDS pathogenesis and identify VEGFR-1 as a potential therapeutic target. FUNDING: Instituto de Salud Carlos III, European Regional Development Funds, Instituto Tecnologico y de Energias Renovables.

Abstract: Infection with avian influenza A H5N1 virus results in acute lung injury (ALI) and has a high mortality rate (52.79%) because there are limited therapies available for treatment. Drug repositioning is an economical approach to drug discovery. We developed a method for drug repositioning based on high-throughput RNA sequencing and identified several drugs as potential treatments for avian influenza A H5N1 virus. Using high-throughput RNA sequencing, we identified a total of 1,233 genes differentially expressed in A549 cells upon H5N1 virus infection. Among these candidate genes, 79 drug targets (corresponding to 59 approved drugs) overlapped with the DrugBank target database. Twenty-two of the 41 commercially available small-molecule drugs reduced H5N1-mediated cell death in cultured A549 cells, and fifteen drugs that protected A549 cells when administered both pre- and post-infection were tested in an H5N1-infection mouse model. The results showed significant alleviation of acute lung injury by amitriptyline HCl (an antidepressant drug), flavin adenine dinucleotide (FAD; an ophthalmic agent for vitamin B2 deficiency), azacitidine (an anti-neoplastic drug) and calcitriol (an active form of vitamin D). All four agents significantly reduced the infiltrating cell count and decreased the lung injury score in H5N1 virus-infected mice based on lung histopathology, significantly improved mouse lung edema by reducing the wet-to-dry weight ratio of lung tissue and significantly improved the survival of H5N1 virus-infected mice. This study not only identifies novel potential therapies for influenza H5N1 virus-induced lung injury but also provides a highly effective and economical screening method for repurposing drugs that may be generalizable for the prevention and therapy of other diseases.

Abstract: Drug compounds that augment the production and activity of the cystic fibrosis (CF) transmembrane regulator (CFTR) have revolutionised CF care. Many adults and some children with CF suffer advanced and severe lung disease or await lung transplantation. While the hope is that these drug compounds will prevent lung damage when started early in life, there is an ongoing need to care for people with advanced lung disease. The focus of this review is the accumulating data from clinical trials and case series regarding the benefits of CFTR modulator therapy in people with advanced pulmonary disease. We address the impact of treatment with ivacaftor, lumacaftor/ivacaftor, tezacaftor/ivacaftor and elexacaftor/tezacaftor/ivacaftor on lung function, pulmonary exacerbations, nutrition and quality of life. Adverse events of the different CFTR modulators, as well as the potential for drug-drug interactions, are discussed.