Computational and chemical approaches to drug repurposing

Drug repurposing, which entails discovering novel therapeutic applications for already existing drugs, provides numerous benefits compared to conventional drug discovery methods. This strategy can be pursued through two primary approaches: computational and chemical. Computational methods involve the utilization of data mining and bioinformatics techniques to identify potential drug candidates, while chemical approaches involve experimental screens oriented to finding new potential treatments based on existing drugs. Both computational and chemical methods have proven successful in uncovering novel therapeutic uses for established drugs. During my PhD, I participated in several experimental drug repurposing screens based on high-throughput phenotypic approaches. Finally, attracted by the potential of computational drug repurposing pipelines, I decided to contribute and generate a web platform focused on the use of transcriptional signatures to identify potential new treatments for human disease. A summary of these studies follows: In Study I, we utilized the tetracycline repressor (tetR)-regulated mechanism to create a human osteosarcoma cell line (U2OS) with the ability to express TAR DNA-binding protein 43 (TDP-43) upon induction. TDP-43 is a protein known for its association with several neurodegenerative diseases. We implemented a chemical screening with this system as part of our efforts to repurpose approved drugs. While the screening was unsuccessful to identify modulators of TDP-43 toxicity, it revealed compounds capable of inhibiting the doxycyclinedependent TDP-43 expression. Furthermore, a complementary CRISPR/Cas9 screening using the same cell system identified additional regulators of doxycycline-dependent TDP43 expression. This investigation identifies new chemical and genetic modulators of the tetR system and highlights potential limitations of using this system for chemical or genetic screenings in mammalian cells. In Study II, our objective was to reposition compounds that could potentially reduce the toxic effects of a fragment of the Huntingtin (HTT) protein containing a 94 amino acid long glutamine stretch (Htt-Q94), a feature of Huntington's disease (HD). To achieve this, we carried out a high-throughput chemical screening using a varied collection of 1,214 drugs, largely sourced from a drug repurposing library. Through our screening process, we singled out clofazimine, an FDA-approved anti-leprosy drug, as a potential therapeutic candidate. Its effectiveness was validated across several in vitro models as well as a zebrafish model of polyglutamine (polyQ) toxicity. Employing a combination of computational analysis of transcriptional signatures, molecular modeling, and biochemical assays, we deduced that clofazimine is an agonist for the peroxisome proliferator-activated receptor gamma (PPARγ), a receptor previously suggested to be a viable therapeutic target for HD due to its role in promoting mitochondrial biogenesis. Notably, clofazimine was successful in alleviating the mitochondrial dysfunction triggered by the expression of Htt-Q94. These findings lend substantial support to the potential of clofazimine as a viable candidate for drug repurposing in the treatment of polyQ diseases. In Study III, we explored the molecular mechanism of a previously identified repurposing example, the use of diethyldithiocarbamate-copper complex (CuET), a disulfiram metabolite, for cancer treatment. We found CuET effectively inhibits cancer cell growth by targeting the NPL4 adapter of the p97VCP segregase, leading to translational arrest and stress in tumor cells. CuET also activates ribosomal biogenesis and autophagy in cancer cells, and its cytotoxicity can be enhanced by inhibiting these pathways. Thus, CuET shows promise as a cancer treatment, especially in combination therapies. In Study IV, we capitalized on the Molecular Signatures Database (MSigDB), one of the largest signature repositories, and drug transcriptomic profiles from the Connectivity Map (CMap) to construct a comprehensive and interactive drug-repurposing database called the Drug Repurposing Encyclopedia (DRE). Housing over 39.7 million pre-computed drugsignature associations across 20 species, the DRE allows users to conduct real-time drugrepurposing analysis. This can involve comparing user-supplied gene signatures with existing ones in the DRE, carrying out drug-gene set enrichment analyses (drug-GSEA) using submitted drug transcriptomic profiles, or conducting similarity analyses across all database signatures using user-provided gene sets. Overall, the DRE is an exhaustive database aimed at promoting drug repurposing based on transcriptional signatures, offering deep-dive comparisons across molecular signatures and species. Drug repurposing presents a valuable strategy for discovering fresh therapeutic applications for existing drugs, offering numerous benefits compared to conventional drug discovery methods. The studies conducted in this thesis underscore the potential of drug repurposing and highlight the complementary roles of computational and chemical approaches. These studies enhance our understanding of the mechanistic properties of repurposed drugs, such as clofazimine and disulfiram, and reveal novel mechanisms for targeting specific disease pathways. Additionally, the development of the DRE platform provides a comprehensive tool to support researchers in conducting drug-repositioning analyses, further facilitating the advancement of drug repurposing studies

Finite element simulation on the reflection and transmission of the lamb waves across a micro defect of plates

This paper presents a theoretical and finite element (FE) investigation of the generation and propagation characteristics of the fundamental Lamb waves symmetrical mode S0 and anti-symmetrical mode A0 after testing with different types of defects in the plates. The reflection and transmission of Lamb waves at a micro symmetry defect and asymmetry defect are analyzed numerically in the two-dimension (2D) model. Mode conversion of Lamb waves can occur upon encountering the asymmetry discontinuities leading to newly-converted modes apart from wave reflection and transmission. When testing the symmetry defects, the reflection and transmission waves have no modal separation phenomenon. To describe the mode conversion and reflection and transmission degree, and evaluate the micro defect severity, a series of defects are simulated to explore the relationships of defect reflection and transmission with the length and depth of a defect in the 2D FE model. In the three-dimension (3D) FE model, the straight-crest Lamb waves and circular-crest Lamb waves are simulated and researched by contrast analysis. Then the straight-crest Lamb waves are motivated to study the scattering laws of Lamb waves interacting with the circle hole defects and rectangular hole defects. S0 mode and SH0 mode are contained in the scattering waves after S0 mode testing the through holes defects. Corresponding mode energy percentages were analyzed at different micro defect severities changed in different ways. Simulation results illustrated that the modal energy percentages varied in a different character and provided support for the analytically determined results of Lamb waves in the non-destructive testing and evaluation

Human Health Indicator Prediction from Gait Video

Body Mass Index (BMI), age, height and weight are important indicators of human health conditions, which can provide useful information for plenty of practical purposes, such as health care, monitoring and re-identification. Most existing methods of health indicator prediction mainly use front-view body or face images. These inputs are hard to be obtained in daily life and often lead to the lack of robustness for the models, considering their strict requirements on view and pose. In this paper, we propose to employ gait videos to predict health indicators, which are more prevalent in surveillance and home monitoring scenarios. However, the study of health indicator prediction from gait videos using deep learning was hindered due to the small amount of open-sourced data. To address this issue, we analyse the similarity and relationship between pose estimation and health indicator prediction tasks, and then propose a paradigm enabling deep learning for small health indicator datasets by pre-training on the pose estimation task. Furthermore, to better suit the health indicator prediction task, we bring forward Global-Local Aware aNd Centrosymmetric Encoder (GLANCE) module. It first extracts local and global features by progressive convolutions and then fuses multi-level features by a centrosymmetric double-path hourglass structure in two different ways. Experiments demonstrate that the proposed paradigm achieves state-of-the-art results for predicting health indicators on MoVi, and that the GLANCE module is also beneficial for pose estimation on 3DPW

The versatile application of cervicofacial and cervicothoracic rotation flaps in head and neck surgery

<p>Abstract</p> <p>Background</p> <p>The large defects resulting from head and neck tumour surgeries present a reconstructive challenge to surgeons. Although numerous methods can be used, they all have their own limitations. In this paper, we present our experience with cervicofacial and cervicothoracic rotation flaps to help expand the awareness and application of this useful system of flaps.</p> <p>Methods</p> <p>Twenty-one consecutive patients who underwent repair of a variety of defects of the head and neck with cervicofacial or cervicothoracic flaps in our hospital from 2006 to 2009 were retrospectively analysed. Statistics pertaining to the patients' clinical factors were gathered.</p> <p>Results</p> <p>Cheek neoplasms are the most common indication for cervicofacial and cervicothoracic rotation flaps, followed by parotid tumours. Among the 12 patients with medical comorbidities, the most common was hypertension. Defects ranging from 1.5 cm × 1.5 cm to 7 cm × 6 cm were reconstructed by cervicofacial flap, and defects from 3 cm × 2 cm to 16 cm × 7 cm were reconstructed by cervicothoracic flap. The two flaps also exhibited versatility in these reconstructions. When combined with the pectoralis major myocutaneous flap, the cervicothoracic flap could repair through-and-through cheek defects, and in combination with a temporalis myofacial flap, the cervicofacial flap was able to cover orbital defects. Additionally, 95% patients were satisfied with their resulting contour results.</p> <p>Conclusions</p> <p>Cervicofacial and cervicothoracic flaps provide a technically simple, reliable, safe, efficient and cosmetic means to reconstruct defects of the head and neck.</p

Outdoor particulate matter exposure affects metabolome in chronic obstructive pulmonary disease: Preliminary study

IntroductionThe metabolomic changes caused by airborne fine particulate matter (PM2.5) exposure in patients with chronic obstructive pulmonary disease (COPD) remain unclear. The aim of this study was to determine whether it is possible to predict PM2.5-induced acute exacerbation of COPD (AECOPD) using metabolic markers.MethodsThirty-eight patients with COPD diagnosed by the 2018 Global Initiative for Obstructive Lung Disease were selected and divided into high exposure and low exposure groups. Questionnaire data, clinical data, and peripheral blood data were collected from the patients. Targeted metabolomics using liquid chromatography-tandem mass spectrometry was performed on the plasma samples to investigate the metabolic differences between the two groups and its correlation with the risk of acute exacerbation.ResultsMetabolomic analysis identified 311 metabolites in the plasma of patients with COPD, among which 21 metabolites showed significant changes between the two groups, involving seven pathways, including glycerophospholipid, alanine, aspartate, and glutamate metabolism. Among the 21 metabolites, arginine and glycochenodeoxycholic acid were positively associated with AECOPD during the three months of follow-up, with an area under the curve of 72.50% and 67.14%, respectively.DiscussionPM2.5 exposure can lead to changes in multiple metabolic pathways that contribute to the development of AECOPD, and arginine is a bridge between PM2.5 exposure and AECOPD

Association of gestational hypertriglyceridemia, diabetes with serum ferritin levels in early pregnancy: a retrospective cohort study

AimsPrevious studies showed conflicting results linking body iron stores to the risk of gestational diabetes mellitus (GDM) and dyslipidemia. We aim to investigate the relationship between serum ferritin, and the prevalence of GDM, insulin resistance (IR) and hypertriglyceridemia.MethodsA total of 781 singleton pregnant women of gestation in Shanghai General Hospital took part in the retrospective cohort study conducted. The participants were divided into four groups by quartiles of serum ferritin levels (Q1–4). Binary logistic regressions were used to examine the strength of association between the different traits and the serum ferritin (sFer) quartiles separately, where Q1 (lowest ferritin quartile) was taken as the base reference. One-way ANOVA was adopted to compare the averages of the different variables across Sfer quartiles.ResultsCompared with the lowest serum ferritin quartile (Q1), the ORs for Q3, and Q4 in our population were 1.79 (1.01–2.646), and 2.07 (1.089-2.562) respectively and this trend persisted even after adjusted for age and pre-BMI. Women with higher serum ferritin quartile including Q3 (OR=2.182, 95%CI=1.729-5.527, P=0.003) and Q4(OR=3.137, 95%CI=3.137-8.523, P&lt;0.01)are prone to develop insulin resistance disorders. No significant difference was observed between sFer concentrations and gestational hypertriglyceridemia(GTG) in the comparison among these 4 groups across logistic regressions but TG was found positively correlated with increased ferritin values in the second trimester.ConclusionsIncreased concentrations of plasma ferritin in early pregnancy are significantly and positively associated with insulin resistance and incidence of GDM but not gestational dyslipidemia. Further clinical studies are warranted to determine whether it is necessary to encourage pregnant women to take iron supplement as a part of routine antenatal care

Short-term exposure to fine particulate matter and genome-wide DNA methylation in chronic obstructive pulmonary disease: A panel study conducted in Beijing, China

BackgroundFine particulate matter (PM2.5) is a crucial risk factor for chronic obstructive pulmonary disease (COPD). However, the mechanisms whereby PM2.5 contribute to COPD risk have not been fully elucidated. Accumulating evidence suggests that epigenetics, including DNA methylation, play an important role in this process; however, the association between PM2.5 exposure and genome-wide DNA methylation in patients with COPD has not been studied.ObjectiveTo evaluate the association of personal exposure to PM2.5 and genome-wide DNA methylation changes in the peripheral blood of patients with COPD.MethodsA panel study was conducted in Beijing, China. We repeatedly measured and collected personal PM2.5 data for 72 h. Genome-wide DNA-methylation of peripheral blood was analyzed using the Illumina Infinium Human Methylation BeadChip (850 k). A linear-mixed effect model was used to identify the differentially methylated probe (DMP) associated with PM2.5. Finally, we performed a functional enrichment analysis of the DMPs that were significantly associated with PM2.5.ResultsA total of 24 COPD patients were enrolled and 48 repeated DNA methylation measurements were associated in this study. When the false discovery rate was &lt; 0.05, 19 DMPs were significantly associated with PM2.5 and were annotated to corresponding genes. Functional enrichment analysis of these genes showed that they were related to the response to toxic substances, regulation of tumor necrosis factor superfamily cytokine production, regulation of photosensitivity 3-kinase signaling, and other pathways.ConclusionThis study provided evidence for a significant relationship between personal PM2.5 exposure and DNA methylation in patients with COPD. Our research also revealed a new biological pathway explaining the adverse effects of PM2.5 exposure on COPD risk