It's time to 'Build Back Fairer': what can we do to reduce health inequalities in cardiology?

Disparities in cardiovascular morbidity and mortality are among the leading health and social care concerns in the UK. The disruption of the COVID-19 pandemic to health services has further placed cardiovascular care and the respective patient communities at the sharp end, not least in exacerbating existing health inequalities across service interfaces and patients' health outcomes. While the pandemic engenders unprecedented constraints within established cardiology services, it conduces to a unique opportunity to embrace novel transformative approaches within the way we deliver patient care in maintaining best practices during and beyond the crisis. As the first step in navigating toward the 'new norm', a clear recognition of the challenges inherent in cardiovascular health inequalities is critical, primarily in preventing the widening of extant inequalities as cardiology workforces continue to build back fairer. We may consider the challenges through the lens of health services' diverse facets, including the aspects of universality, interconnectivity, adaptability, sustainability, and preventability. This article explores the pertinent challenges and provides a focused narration concerning potential measures to foster equitable and resilient cardiology services that are patient centred in the post-pandemic landscape.

An achromatic colorimetric nanosensor for sensitive multiple pathogen detection by coupling plasmonic nanoparticles with magnetic separation.

Rapid screening of multiple pathogens will greatly improve the efficiency of pandemic prevention and control. Colorimetric methods exhibit the advantages of convenience, portability, low cost, time efficiency, and free of sophisticated instruments, yet usually have difficulties in simultaneous detection and suffer from monotonous color changes with low visual resolution and sensitivity. Hence, coupled three kinds of plasmonic nanoparticles (NPs) with magnetic separation, we developed an achromatic colorimetric nanosensor with highly enhanced visual resolution for simultaneous detection of SARS-CoV-2, Staphylococcus aureus, and Salmonella typhimurium. The achromatic nanosensor was composed of SARS-CoV-2-targeting red gold NPs, S. aureus-targeting yellow silver NPs and S. typhimurium-targeting blue silver triangle NPs mixed as black color. In the detection, three corresponding magnetic probes were added into the above mixture. In the presence of a target pathogen, it would be recognized and combined with corresponding colored reporters and magnetic probes to form sandwich complexes, which were removed by magnetic separation, and the sensor changed from black to a chromatic color (the color of the reporters remained in supernatant). Consequently, different target pathogen induced different color. For example, SARS-CoV-2, S. aureus, and S. typhimurium respectively produced green, purple, and orange. While coexistence of S. aureus and S. typhimurium produced red, and coexistence of S. aureus and SARS-CoV-2 produced blue, etc. Therefore, by observing the color change or measuring the absorption spectra, multiple pathogen detection was achieved conveniently. Compared with most colorimetric sensors, this achromatic nanosensor involved rich color change, thus significantly enhancing visual resolution and inspection sensitivity. Therefore, this sensor opened a promising avenue for efficient monitoring and early warning of food safety and quality.

Ag Nanoparticles with Ultrathin Au Shell-Based Lateral Flow Immunoassay for Colorimetric and SERS Dual-Mode Detection of SARS-CoV-2 IgG.

Immunoglobulin detection is essential for diagnosing progression of SARS-CoV-2 infection, for which SARS-CoV-2 IgG is one of the most important indexes. In this paper, Ag nanoparticles with ultrathin Au shells (∼2 nm) embedded with 4-mercaptobenzoic acid (MBA) (AgMBA@Au) were manufactured via a ligand-assisted epitaxial growth method and integrated into lateral flow immunoassay (LFIA) for colorimetric and SERS dual-mode detection of SARS-CoV-2 IgG. AgMBA@Au possessed not only the surface chemistry advantages of Au but also the superior optical characteristics of Ag. Moreover, the nanogap between the Ag core and the Au shell also greatly enhanced the Raman signal. After being modified with anti-human antibodies, AgMBA@Au recognized and combined with SARS-CoV-2 IgG, which was captured by the SARS-CoV-2 spike protein on the T line. Qualitative analysis was achieved by visually observing the color of the T line, and quantitative analysis was conducted by measuring the SERS signal with a sensitivity four orders of magnitude higher (detection limit: 0.22 pg/mL). The intra-assay and inter-assay variation coefficients were 7.7 and 10.3%, respectively, and other proteins at concentrations of 10 to 20 times higher than those of SARS-CoV-2 IgG could hardly produce distinguishable signals, confirming good reproducibility and specificity. Finally, this method was used to detect 107 clinical serum samples. The results agreed well with those obtained from enzyme-linked immunosorbent assay kits and were significantly better than those of the colloidal gold test strips. Therefore, this dual-mode LFIA has great potential in clinical practical applications and can be used to screen and trace the early immune response of SARS-CoV-2.

The Landscape of Coronavirus Disease 2019 (COVID-19) and Integrated Analysis SARS-CoV-2 Receptors and Potential Inhibitors in Lung Adenocarcinoma Patients.

The outbreak of novel coronavirus disease 2019 (COVID-19) has become the largest health threat worldwide, with more than 34.40 million positive cases and over 1.02 million deaths confirmed. In this study, we confirmed that significantly differentially expressed genes in COVID-19 patients were mainly involved in the regulation of immune and inflammation-related signaling pathways. It is worth noting that many infected COVID-19 patients have malignant tumors, and their prognosis is poor. To explore the susceptibility factors of cancer patients, we assessed the expression of ACE2, TMPRSS2, and the endocytic regulator AAK1 in lung adenocarcinoma (LUAD) patients and explored their effects on immune infiltration. We found that the expression of ACE2 and TMPRSS2 in LUAD patients was significantly increased, which may explain why LUAD patients are susceptible to SARS-CoV-2, and the patients with high-expression genes presented increased infiltration of immune cells such as B cells and CD4 T cells. In addition, we also identified miR-432-5p as a potential targeted molecule and bexarotene as a potential targeted drug of the three genes through bioinformatic analysis and further verified the anti-inflammatory effect of bexarotene, providing new ideas for the treatment of COVID-19.

Immune dysfunction following COVID-19, especially in severe patients.

The coronavirus disease 2019 (COVID-19) has been spreading worldwide. Severe cases quickly progressed with unfavorable outcomes. We aim to investigate the clinical features of COVID-19 and identify the risk factors associated with its progression. Data of confirmed SARS-CoV-2-infected patients and healthy participants were collected. Thirty-seven healthy people and 79 confirmed patients, which include 48 severe patients and 31 mild patients, were recruited. COVID-19 patients presented with dysregulated immune response (decreased T, B, and NK cells and increased inflammatory cytokines). Also, they were found to have increased levels of white blood cell, neutrophil count, and D-dimer in severe cases. Moreover, lymphocyte, CD4+ T cell, CD8+ T cell, NK cell, and B cell counts were lower in the severe group. Multivariate logistic regression analysis showed that CD4+ cell count, neutrophil-to-lymphocyte ratio (NLR) and D-dimer were risk factors for severe cases. Both CT score and clinical pulmonary infection score (CPIS) were associated with disease severity. The receiver operating characteristic (ROC) curve analysis has shown that all these parameters and scores had quite a high predictive value. Immune dysfunction plays critical roles in disease progression. Early and constant surveillance of complete blood cell count, T lymphocyte subsets, coagulation function, CT scan and CPIS was recommended for early screening of severe cases.

Challenges and potential for improving the druggability of podophyllotoxin-derived drugs in cancer chemotherapy.

Covering: up to 2020As a main bioactive component of the Chinese, Indian, and American Podophyllum species, the herbal medicine, podophyllotoxin (PTOX) exhibits broad spectrum pharmacological activity, such as superior antitumor activity and against multiple viruses. PTOX derivatives (PTOXs) could arrest the cell cycle, block the transitorily generated DNA/RNA breaks, and blunt the growth-stimulation by targeting topoisomerase II, tubulin, or insulin-like growth factor 1 receptor. Since 1983, etoposide (VP-16) is being used in frontline cancer therapy against various cancer types, such as small cell lung cancer and testicular cancer. Surprisingly, VP-16 (ClinicalTrials NTC04356690) was also redeveloped to treat the cytokine storm in coronavirus disease 2019 (COVID-19) in phase II in April 2020. The treatment aims at dampening the cytokine storm and is based on etoposide in the case of central nervous system. However, the initial version of PTOX was far from perfect. Almost all podophyllotoxin derivatives, including the FDA-approved drugs VP-16 and teniposide, were seriously limited in clinical therapy due to systemic toxicity, drug resistance, and low bioavailability. To meet this challenge, scientists have devoted continuous efforts to discover new candidate drugs and have developed drug strategies. This review focuses on the current clinical treatment of PTOXs and the prospective analysis for improving druggability in the rational design of new generation PTOX-derived drugs.

COVID-19 early warning score: a multi-parameter screening tool to identify highly suspected patients (preprint)

BACKGROUND Corona Virus Disease 2019 (COVID-19) is spreading worldwide. Effective screening for patients is important to limit the epidemic. However, some defects make the currently applied diagnosis methods are still not very ideal for early warning of patients. We aimed to develop a diagnostic model that allows for the quick screening of highly suspected patients using easy-to-get variables. METHODS A total of 1,311 patients receiving severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleicacid detection were included, whom with a positive result were classified into COVID-19 group. Multivariate logistic regression analyses were performed to construct the diagnostic model. Receiver operating characteristic (ROC) curve analysis were used for model validation. RESULTS After analysis, signs of pneumonia on CT, history of close contact, fever, neutrophil-to-lymphocyte ratio (NLR), Tmax and sex were included in the diagnostic model. Age and meaningful respiratory symptoms were enrolled into COVID-19 early warning score (COVID-19 EWS). The areas under the ROC curve (AUROC) indicated that both of the diagnostic model (training dataset 0.956 [95%CI 0.935-0.977, P < 0.001]; validation dataset 0.960 [95%CI 0.919-1.0, P < 0.001] ) and COVID-19 EWS (training dataset 0.956 [95%CI 0.934-0.978, P < 0.001] ; validate dataset 0.966 [95%CI 0.929-1, P < 0.001]) had good discrimination capacity. In addition, we also obtained the cut-off values of disease severity predictors, such as CT score, CD8+ T cell count, CD4+ T cell count, and so on. CONCLUSIONS The new developed COVID-19 EWS was a considerable tool for early and relatively accurately warning of SARS-CoV-2 infected patients.