Aptamers Targeting Membrane Proteins for Sensor and Diagnostic Applications.

Many biological processes (physiological or pathological) are relevant to membrane proteins (MPs), which account for almost 30% of the total of human proteins. As such, MPs can serve as predictive molecular biomarkers for disease diagnosis and prognosis. Indeed, cell surface MPs are an important class of attractive targets of the currently prescribed therapeutic drugs and diagnostic molecules used in disease detection. The oligonucleotides known as aptamers can be selected against a particular target with high affinity and selectivity by iterative rounds of in vitro library evolution, known as Systematic Evolution of Ligands by EXponential Enrichment (SELEX). As an alternative to antibodies, aptamers offer unique features like thermal stability, low-cost, reuse, ease of chemical modification, and compatibility with various detection techniques. Particularly, immobilized-aptamer sensing platforms have been under investigation for diagnostics and have demonstrated significant value compared to other analytical techniques. These "aptasensors" can be classified into several types based on their working principle, which are commonly electrochemical, optical, or mass-sensitive. In this review, we review the studies on aptamer-based MP-sensing technologies for diagnostic applications and have included new methodological variations undertaken in recent years.

Incidence of autoantibodies related to systemic autoimmunity in patients with severe COVID-19 admitted to the intensive care unit.

OBJECTIVES: To assess the prevalence of autoantibodies (AAbs) in mechanically ventilated COVID-19 patients and to investigate whether AAbs influence the clinical outcome. METHODS: Serum samples were drawn within the first 48 hours upon admission to the intensive care unit (ICU) from 217 consecutive patients, from January 1st, 2021, to May 10th, 2021, and investigated for the presence of AAbs using conventional techniques. Serum samples (n=117) of age- and sex-matched healthy individuals collected before COVID-19 pandemic were used as controls. RESULTS: COVID-19 patients in the ICU had more commonly AAbs compared to age- and sex-matched controls (174/217, 80.2% vs. 73/117, 62.4%, p<0.001). Patients expressed more frequently ANAs (48.4% vs. 21.4%, p<0.001), anti-dsDNA (5.1% vs. 0%, p=0.01), anti-CCP (8.3% vs. 1.7%, p=0.014) and anti-CL IgM AAbs (21.7% vs. 9.4%, p=0.005) than controls, respectively. Simultaneous reactivity against at least three autoantigens, occurred in 144 out of 174 (82.8%) patients. The two groups did not differ in terms of clinicoepidemiologic characteristics or the mortality ratio within the ICU. Patients who died compared to convalescents were older, had higher ferritin, D-dimers levels, APACHE II score, lower oxygen saturation, higher prevalence of comorbidities and cognitive dysfunction. However, AAbs were not found to correlate with the clinical outcome. CONCLUSIONS: Patients with severe COVID-19 express AAbs more commonly compared to controls. No correlation was found between AAbs and disease outcome.

Visual Analogue Scale for the Evaluation of Olfactory and Gustatory Dysfunction of COVID-19 Patients in Northwestern Greece.

Background The visual analogue scale (VAS) has been used as a diagnostic tool for the evaluation of the severity of olfactory and gustatory dysfunction (OGD) caused by SARS-CoV2 infection. The main objective of the present study was the evaluation of OGD with VAS in COVID-19-positive patients in Northwestern Greece and its possible association with the patients' self-reported symptoms of olfactory and gustatory dysfunction. Methods The presence of olfactory and gustatory symptoms and their severity were assessed by questionnaire along with the use of specific odorants and tastant ingredients, in three time periods: prior to COVID-19, during COVID-19 (initial diagnosis) and post-COVID-19 disease (at four weeks from disease onset). Three hundred COVID-19-positive patients (home-quarantined and hospitalized) tested with RT-PCR test in the University Hospital of Ioannina Greece were included in this study. Statistical analysis was performed on SPSS Statistics 26.0 (IBM Corp., Armonk, NY) Results Out of a total of 300 patients, 146 and 190 patients had mild hyposmia and hypogeusia respectively, followed by patients with severe hyposmia or hypogeusia (118 and 88 respectively), at the time of COVID-19 onset (initial diagnosis). An increase in the number of patients with recovery of symptoms was observed during the follow-up period, during which only eight patients had non-resolving severe symptoms (six patients with hyposmia and two with hypogeusia). On further analysis, a statistically significant association was found between the severity of symptoms (assessed by VAS score) and the self-reported symptoms of sensory dysfunction by the patients. There was a significant association between the groups of patients with mild hyposmia and patients that reported no loss of smell; between the patients with moderate hyposmia and the patients who reported "loss of smell"; and between the patients with severe hyposmia and the group of patients who reported a loss of smell, at the COVID-19 onset period. Similarly, patients with mild hyposmia were associated with those that reported a loss of smell at the same time. The severity of hyposmia was also associated with the reported symptom of "loss of taste" at the time of COVID-19 diagnosis. Similar findings were observed regarding the severity of hypogeusia and the reported symptom of "loss of taste" among the groups of patients. Finally, the severity of hypogeusia was associated with smell loss at the time of initial diagnosis of the infection. Conclusion Similar to the literature data, our findings indicate that hyposmia and hypogeusia are common symptoms of COVID-19 disease with varying severity. In our study, most of the patients exerted a complete recovery of these OGD symptoms. In addition, we found an association between olfactory dysfunction and self-reported sensory of taste as well as gustatory dysfunction and sensory of smell. Finally, we found that the VAS score was a reliable diagnostic tool in the estimation of OGD in this cohort of patients. However, our results need to be confirmed by larger-scale trials.

An explainable machine learning-driven proposal of pulmonary fibrosis biomarkers.

Pulmonary fibrosing diseases are in the very epicenter of biomedical research both due to their increasing prevalence and their association with SARS-CoV-2 infections. Research of idiopathic pulmonary fibrosis, the most lethal among the interstitial lung diseases, is in need for new biomarkers and potential disease targets, a goal that could be accelerated using machine learning techniques. In this study, we have used Shapley values to explain the decisions made by an ensemble learning model trained to classify samples to an either pulmonary fibrosis or steady state based on the expression values of deregulated genes. This process resulted in a full and a laconic set of features capable of separating phenotypes to an at least equal degree as previously published marker sets. Indicatively, a maximum increase of 6% in specificity and 5% in Mathew's correlation coefficient was achieved. Evaluation with an additional independent dataset showed our feature set having a greater generalization potential than the rest. Ultimately, the proposed gene lists are expected not only to serve as new sets of diagnostic marker elements, but also as a target pool for future research initiatives.

Clinical Symptoms in Hospitalized and Self-Quarantined Patients with SARS-CoV-2 Infection in Northwestern Greece - Association with Olfactory and Gustatory Dysfunction.

Backround: We aimed to assess the relation of chemosensory dysfunction with the reported symptoms in two subgroups of patients in Northwestern Greece: the first one included patients with moderate to severe symptomatology who needed hospitalization and the second one, patients with mild symptoms who recovered at home. Methods:We used a questionnaire to select information about patient demographics, medical history and reported symptoms during infection. Three hundred COVID-19 positive patients who were identified via RT-PCR test in the University Hospital of Ioannina, Greece, were included in the present study, of which 150 recovered at home and the remaining 150 needed hospitalization. Statistical analysis was based on IBM-SPSS Statistics 26.0. Results:The majority of patients had fever during infection, while o minor percentage of those who needed hospitalization (12.67%) suffered from sore throat. There was a statistically significant difference between the loss of smell and clinical symptoms including fatigue, nose congestion, body aches and headache, and loss of taste and reported symptoms including fatigue, body aches, runny nose, headache and sore throat. Conclusion: Fever was the symptom with the highest percentage rate, while sore throat was the symptom with the lowest percentage rate. There are reported clinical symptoms related with olfactory and gustatory dysfunction during COVID-19 infection.

Predicting the need for mechanical ventilation and mortality in hospitalized COVID-19 patients who received heparin.

Although several studies have utilized AI (artificial intelligence)-based solutions to enhance the decision making for mechanical ventilation, as well as, for mortality in COVID-19, the extraction of explainable predictors regarding heparin's effect in intensive care and mortality has been left unresolved. In the present study, we developed an explainable AI (XAI) workflow to shed light into predictors for admission in the intensive care unit (ICU), as well as, for mortality across those hospitalized COVID-19 patients who received heparin. AI empowered classifiers, such as, the hybrid Extreme gradient boosting (HXGBoost) with customized loss functions were trained on time-series curated clinical data to develop robust AI models. Shapley additive explanation analysis (SHAP) was conducted to determine the positive or negative impact of the predictors in the model's output. The HXGBoost predicted the risk for intensive care and mortality with 0.84 and 0.85 accuracy, respectively. SHAP analysis indicated that the low percentage of lymphocytes at day 7 along with increased FiO2 at days 1 and 5, low SatO2 at days 3 and 7 increase the probability for mortality and highlight the positive effect of heparin administration at the early days of hospitalization for reducing mortality.

Healthcare Innovations to Address the Challenges of the COVID-19 Pandemic.

We have been faced with an unprecedented challenge in combating the COVID-19/SARS-CoV2 outbreak that is threatening the fabric of our civilization, causing catastrophic human losses and a tremendous economic burden globally. During this difficult time, there has been an urgent need for biomedical engineers, clinicians, and healthcare industry leaders to work together to develop novel diagnostics and treatments to fight the pandemic including the development of portable, rapidly deployable, and affordable diagnostic testing kits, personal protective equipment, mechanical ventilators, vaccines, and data analysis and modeling tools. In this position paper, we address the urgent need to bring these inventions into clinical practices. This paper highlights and summarizes the discussions and new technologies in COVID-19 healthcare, screening, tracing, and treatment-related presentations made at the IEEE EMBS Public Forum on COVID-19. The paper also provides recent studies, statistics and data and new perspectives on ongoing and future challenges pertaining to the COVID-19 pandemic.

The Impact of Age and Gender and Their Association with Chemosensory Dysfunction, in Hospitalized and Self-Quarantine Patients with Covid-19 Infection, in Epirus, Greece

Objective:Olfactory and gustatory dysfunction that relates with the infection from severe acute respiratory syndrome-related coronavirus (SARS-CoV-2) has already improved. The relation between chemosensory dysfunction and age and gender in covid-19 positive patients is the main objective of the present study. Methods:We used a questionnaire to select information about medical history, patient demographics and reported symptoms during infection. Three hundred covid-19 positive patients, who underwent a RT-PCR test in the University Hospital of Ioannina, Grecce, were included in this study;150 of them recovered at home and the remaining 150 were admitted to hospital. Statistical analysis based on ÉBM-SPSS Statistics 26.0 was done. Results:The total sample included 300 patients, of which 106 females and 194 males. There was a statistically significant difference between the subgroup of patients aged 21-25, 61-65 and 71-75 with loss of smell, that of hospitalized patients aged 41-45 with loss of smell and the subgroup of those aged 31-35 and 71-75 with loss of taste. Conclusion:There is a significant association between chemosensory dysfunction and younger age groups. Olfactory and gustatory dysfunction appears more frequently in women than men. Male gender relates with disease severity.

Health Technology Assessment for In Silico Medicine: Social, Ethical and Legal Aspects.

The application of in silico medicine is constantly growing in the prevention, diagnosis, and treatment of diseases. These technologies allow us to support medical decisions and self-management and reduce, refine, and partially replace real studies of medical technologies. In silico medicine may challenge some key principles: transparency and fairness of data usage; data privacy and protection across platforms and systems; data availability and quality; data integration and interoperability; intellectual property; data sharing; equal accessibility for persons and populations. Several social, ethical, and legal issues may consequently arise from its adoption. In this work, we provide an overview of these issues along with some practical suggestions for their assessment from a health technology assessment perspective. We performed a narrative review with a search on MEDLINE/Pubmed, ISI Web of Knowledge, Scopus, and Google Scholar. The following key aspects emerge as general reflections with an impact on the operational level: cultural resistance, level of expertise of users, degree of patient involvement, infrastructural requirements, risks for health, respect of several patients' rights, potential discriminations for access and use of the technology, and intellectual property of innovations. Our analysis shows that several challenges still need to be debated to allow in silico medicine to express all its potential in healthcare processes.

A Multimodal Approach for the Risk Prediction of Intensive Care and Mortality in Patients with COVID-19.

BACKGROUND: Although several studies have been launched towards the prediction of risk factors for mortality and admission in the intensive care unit (ICU) in COVID-19, none of them focuses on the development of explainable AI models to define an ICU scoring index using dynamically associated biological markers. METHODS: We propose a multimodal approach which combines explainable AI models with dynamic modeling methods to shed light into the clinical features of COVID-19. Dynamic Bayesian networks were used to seek associations among cytokines across four time intervals after hospitalization. Explainable gradient boosting trees were trained to predict the risk for ICU admission and mortality towards the development of an ICU scoring index. RESULTS: Our results highlight LDH, IL-6, IL-8, Cr, number of monocytes, lymphocyte count, TNF as risk predictors for ICU admission and survival along with LDH, age, CRP, Cr, WBC, lymphocyte count for mortality in the ICU, with prediction accuracy 0.79 and 0.81, respectively. These risk factors were combined with dynamically associated biological markers to develop an ICU scoring index with accuracy 0.9. CONCLUSIONS: to our knowledge, this is the first multimodal and explainable AI model which quantifies the risk of intensive care with accuracy up to 0.9 across multiple timepoints.

A prospective multicenter study assessing humoral immunogenicity and safety of the mRNA SARS-CoV-2 vaccines in Greek patients with systemic autoimmune and autoinflammatory rheumatic diseases.

OBJECTIVES: To investigate humoral responses and safety of mRNA SARS-CoV-2 vaccines in systemic autoimmune and autoinflammatory rheumatic disease (SAARD) patients subjected or not to treatment modifications during vaccination. METHODS: A nationwide, multicenter study, including 605 SAARD patients and 116 controls, prospectively evaluated serum anti-SARS-CoV-2 S1-protein IgG antibody titers, side-effects, and disease activity, one month after complete vaccination, in terms of distinct treatment modification strategies (none, partial and extended modifications). Independent risk factors associated with hampered humoral responses were identified by data-driven multivariable logistic regression analysis. RESULTS: Patients with extended treatment modifications responded to vaccines similarly to controls as well as SAARD patients without immunosuppressive therapy (97.56% vs 100%, p = 0.2468 and 97.56% vs 97.46%, p > 0.9999, respectively). In contrast, patients with partial or without therapeutic modifications responded in 87.50% and 84.50%, respectively. Furthermore, SAARD patients with extended treatment modifications developed higher anti-SARS-CoV-2 antibody levels compared to those without or with partial modifications (median:7.90 vs 7.06 vs 7.1, p = 0.0003 and p = 0.0195, respectively). Mycophenolate mofetil (MMF), rituximab (RTX) and methotrexate (MTX) negatively affected anti-SARS-CoV-2 humoral responses. In 10.5% of vaccinated patients, mild clinical deterioration was noted; however, no differences in the incidence of deterioration were observed among the distinct treatment modification SAARD subgroups. Side-effects were generally comparable between SAARD patients and controls. CONCLUSIONS: In SAARD patients, mRNA SARS-CoV-2 vaccines are effective and safe, both in terms of side-effects and disease flares. Treatment with MMF, RTX and/or MTX compromises anti-SARS-CoV-2 antibody responses, which are restored upon extended treatment modifications without affecting disease activity.

Accurate Monitoring of Parkinson's Disease Symptoms With a Wearable Device During COVID-19 Pandemic.

BACKGROUND: Accurate assessment of symptoms in Parkinson's disease (PD) is essential for optimal treatment decisions. During the past few years, different monitoring modalities have started to be used in the everyday clinical practice, mainly for the evaluation of motor symptoms. However, monitoring technologies for PD have not yet gained wide acceptance among physicians, patients, and caregivers. The COVID-19 pandemic disrupted the patients' access to healthcare, bringing to the forefront the need for wearable sensors, which provide effective remote symptoms' evaluation and follow-up. CASE REPORT: We report two cases with PD, whose symptoms were monitored with a new wearable CE-marked system (PDMonitor®), enabling appropriate treatment modifications. CONCLUSION: Objective assessment of the patient's motor symptoms in his daily home environment is essential for an accurate monitoring in PD and enhances treatment decisions.

Recommendation to Use Wearable-Based mHealth in Closed-Loop Management of Acute Cardiovascular Disease Patients During the COVID-19 Pandemic.

Because of the rapid and serious nature of acute cardiovascular disease (CVD) especially ST segment elevation myocardial infarction (STEMI), a leading cause of death worldwide, prompt diagnosis and treatment is of crucial importance to reduce both mortality and morbidity. During a pandemic such as coronavirus disease-2019 (COVID-19), it is critical to balance cardiovascular emergencies with infectious risk. In this work, we recommend using wearable device based mobile health (mHealth) as an early screening and real-time monitoring tool to address this balance and facilitate remote monitoring to tackle this unprecedented challenge. This recommendation may help to improve the efficiency and effectiveness of acute CVD patient management while reducing infection risk.

Structures and dynamics of the novel S1/S2 protease cleavage site loop of the SARS-CoV-2 spike glycoprotein.

At the end of 2019, a new highly virulent coronavirus known under the name SARS-CoV-2 emerged as a human pathogen. One key feature of SARS-CoV-2 is the presence of an enigmatic insertion in the spike glycoprotein gene representing a novel multibasic S1/S2 protease cleavage site. The proteolytic cleavage of the spike at this site is essential for viral entry into host cells. However, it has been systematically abrogated in structural studies in order to stabilize the spike in the prefusion state. In this study, multi-microsecond molecular dynamics simulations and ab initio modeling were leveraged to gain insights into the structures and dynamics of the loop containing the S1/S2 protease cleavage site. They unveiled distinct conformations, formations of short helices and interactions of the loop with neighboring glycans that could potentially regulate the accessibility of the cleavage site to proteases and its processing. In most conformations, this loop protrudes from the spike, thus representing an attractive SARS-CoV-2 specific therapeutic target.