Personality, Defenses, Mentalization, and Epistemic Trust Related to Covid-19 Containment Strategies: A Psychodynamic Perspective

Introduction: The COVID-19 pandemic has considerably influenced all the domains of people's lives worldwide, determining a high increase in overall psychological distress and several clinical conditions. The study attempted to shed light on the relationship between strategies adopted to manage the pandemic, vaccine hesitancy, and distinct features of personality and mental functioning. Method(s): The sample consisted of 367 Italian individuals (68.1% women, 31.9% men;M age=37, SD=12.79) who completed an online survey including an instrument assessing four response styles to the pandemic and lockdown(s) (RSPL;Tanzilli et al., 2021), the Personality Inventory for DSM-5-Brief Form (PID-BF;Krueger et al., 2013), the Defense Mechanisms Rating Scales-Self-Report-30 (DMRS-SR-30;Di Giuseppe et al., 2020, 2014), the Reflective Functioning Questionnaire (RFQ;Fonagy et al., 2016), and the Epistemic Trust, Mistrust, Credulity Questionnaire (ETMCQ;Campbell et al., 2021). Result(s): Maladaptive response patterns to pandemic restrictions were related to dysfunctional personality traits, immature defense mechanisms, poor mentalization, and epistemic mistrust or credulity. Moreover, more severe levels of personality pathology was predictive of an extraverted-maladaptive response style to health emergency through the full mediation of low overall defensive functioning, poor certainty of others' mental states, and high epistemic credulity. Conclusion(s): Recognizing and understanding dysfunctional psychological pathways associated with individuals' difficulties in dealing with the pandemic are crucial for developing tailored mental health interventions and promoting best practices in healthcare services.

A urine-based ELISA with recombinant non-glycosylated SARS-CoV-2 spike protein for detecting anti-SARS-CoV-2 spike antibodies.

Serological assays have been widely used to detect anti-SARS-CoV-2 antibodies, which are generated from previous exposure to the virus or after vaccination. The presence of anti-SARS-CoV-2 Nucleocapsid antibodies was recently reported in patients´ urine using an in-house urine-based ELISA-platform, allowing a non-invasive way to collect clinical samples and assess immune conversion. In the current study, we evaluated and validated another in-house urine-based ELISA for the detection of anti-SARS-CoV-2 Spike antibodies. Three partial recombinant SARS-CoV-2 Spike proteins comprising the Receptor Binding Domain, expressed in eukaryotic or prokaryotic systems, were tested in an ELISA platform against a panel of over 140 urine and paired serum samples collected from 106 patients confirmed positive for SARS-CoV-2 by qRT-PCR. The key findings from our study were that anti-SARS-CoV-2 Spike antibodies could be detected in urine samples and that the prokaryotic expression of the rSARS-CoV-2 Spike protein was not a barrier to obtain relatively high serology efficiency for the urine-based assay. Thus, use of a urine-based ELISA assay with partial rSARS-CoV-2 Spike proteins, expressed in a prokaryotic system, could be considered as a convenient tool for screening for the presence of anti-SARS-CoV-2 Spike antibodies, and overcome the difficulties arising from sample collection and the need for recombinant proteins produced with eukaryotic expression systems.

Heterogeneity of humoral response patterns in mildly symptomatic, non-hospitalized COVID-19 patients: A one-year longitudinal study.

The duration and protectiveness of antibodies against SARS-CoV-2 in infected subjects are still uncertain; nonetheless, anti-S-specific antibodies can contribute to protective immunity against new infections. It has been described that the level of antibodies produced in COVID-19 is related to the severity of symptoms, and the majority of the humoral response studies have been conducted in hospitalized patients who have been, then, followed over time. However, about 80% of SARS-CoV-2 infections in unvaccinated people are mild to asymptomatic, and this percentage reaches more than 95% in vaccinated individuals. Therefore, understanding the long-term dynamics of the antibody responses in this predominant part of the COVID-19-affected population is essential. In this study, we followed a cohort of individuals with mild COVID-19 who did not require hospitalization. We collected blood samples at sequential times after the SARS-CoV-2-positive qRT-PCR result. From 65 recruited patients, 50 had detectable antibodies at screening. Anti-SARS-CoV-2 IgM levels peaked around two weeks post-COVID-19 diagnostics, becoming undetectable after 65 days. IgG levels reached a peak in approximately one month and remained detectable for more than one year. In contrast to the levels of anti-SARS-CoV-2, antibody neutralization potency indexes persisted over time. In this study, humoral responses in mild COVID-19 patients persisted for more than one year. This is an important long-term follow-up study that includes responses from COVID-19 patients before and after vaccination, a scenery that has become increasingly difficult to evaluate due to the growing vaccination of the world human population.

New, fast, and precise method of COVID-19 detection in nasopharyngeal and tracheal aspirate samples combining optical spectroscopy and machine learning.

Fast, precise, and low-cost diagnostic testing to identify persons infected with SARS-CoV-2 virus is pivotal to control the global pandemic of COVID-19 that began in late 2019. The gold standard method of diagnostic recommended is the RT-qPCR test. However, this method is not universally available, and is time-consuming and requires specialized personnel, as well as sophisticated laboratories. Currently, machine learning is a useful predictive tool for biomedical applications, being able to classify data from diverse nature. Relying on the artificial intelligence learning process, spectroscopic data from nasopharyngeal swab and tracheal aspirate samples can be used to leverage characteristic patterns and nuances in healthy and infected body fluids, which allows to identify infection regardless of symptoms or any other clinical or laboratorial tests. Hence, when new measurements are performed on samples of unknown status and the corresponding data is submitted to such an algorithm, it will be possible to predict whether the source individual is infected or not. This work presents a new methodology for rapid and precise label-free diagnosing of SARS-CoV-2 infection in clinical samples, which combines spectroscopic data acquisition and analysis via artificial intelligence algorithms. Our results show an accuracy of 85% for detection of SARS-CoV-2 in nasopharyngeal swab samples collected from asymptomatic patients or with mild symptoms, as well as an accuracy of 97% in tracheal aspirate samples collected from critically ill COVID-19 patients under mechanical ventilation. Moreover, the acquisition and processing of the information is fast, simple, and cheaper than traditional approaches, suggesting this methodology as a promising tool for biomedical diagnosis vis-à-vis the emerging and re-emerging viral SARS-CoV-2 variant threats in the future.

DEVELOPMENT AND VALIDATION OF AN ENZYME-LINKED IMMUNOASSAY KIT FOR DIAGNOSIS AND SURVEILLANCE OF COVID-19.

There is a massive demand to identify alternative methods to detect new cases of COVID-19 as well as to investigate the epidemiology of the disease. In many countries, importation of commercial kits poses a significant impact on their testing capacity and increases the costs for the public health system. We have developed an ELISA to detect IgG antibodies against SARS-CoV-2 using a recombinant viral nucleocapsid (rN) protein expressed in E. coli. Using a total of 894 clinical samples we showed that the rN-ELISA was able to detect IgG antibodies against SARS-CoV-2 with high sensitivity (97.5%) and specificity (96.3%) when compared to a commercial antibody test. After three external validation studies, we showed that the test accuracy was higher than 90%. The rN-ELISA IgG kit constitutes a convenient and specific method for the large-scale determination of SARS-CoV-2 antibodies in human sera with high reliability.

Development and validation of an enzyme-linked immunoassay kit for diagnosis and surveillance of COVID-19.

There is a massive demand to identify alternative methods to detect new cases of COVID-19 as well as to investigate the epidemiology of the disease. In many countries, importation of commercial kits poses a significant impact on their testing capacity and increases the costs for the public health system. We have developed an ELISA to detect IgG antibodies against SARS-CoV-2 using a recombinant viral nucleocapsid (rN) protein expressed in E. coli. Using a total of 894 clinical samples we showed that the rN-ELISA was able to detect IgG antibodies against SARS-CoV-2 with high sensitivity (97.5%) and specificity (96.3%) when compared to a commercial antibody test. After three external validation studies, we showed that the test accuracy was higher than 90%. The rN-ELISA IgG kit constitutes a convenient and specific method for the large-scale determination of SARS-CoV-2 antibodies in human sera with high reliability.

New, fast, and precise method of COVID-19 detection in nasopharyngeal and tracheal aspirate samples combining optical spectroscopy and machine learning (preprint)

Fast, precise, and low-cost diagnostic testing to identify persons infected with SARS-CoV-2 virus is pivotal to control the global pandemic of COVID-19 that began in late 2019. The gold standard method of diagnostic recommended is the RT-qPCR test. However, this method is not universally available, and is time-consuming and requires specialized personnel, as well as sophisticated laboratories. Currently, machine learning is a useful predictive tool for biomedical applications, being able to classify data from diverse nature. Relying on the artificial intelligence learning process, spectroscopic data from nasopharyngeal swab and tracheal aspirate samples can be used to leverage characteristic patterns and nuances in healthy and infected body fluids, which allows to identify infection regardless of symptoms or any other clinical or laboratorial tests. Hence, when new measurements are performed on samples of unknown status and the corresponding data is submitted to such an algorithm, it will be possible to predict whether the source individual is infected or not. This work presents a new methodology for rapid and precise label-free diagnosing of SARS-CoV-2 infection in clinical samples, which combines spectroscopic data acquisition and analysis via artificial intelligence algorithms. Our results show an accuracy of 85% for detection of SARS-CoV-2 in nasopharyngeal swab samples collected from asymptomatic patients or with mild symptoms, as well as an accuracy of 97% in tracheal aspirate samples collected from critically ill COVID-19 patients under mechanical ventilation. Moreover, the acquisition and processing of the information is fast, simple, and cheaper than traditional approaches, suggesting this methodology as a promising tool for biomedical diagnosis vis-a-vis the emerging and re-emerging viral SARS-CoV-2 variant threats in the future.

Detecting anti-SARS-CoV-2 antibodies in urine samples: A noninvasive and sensitive way to assay COVID-19 immune conversion.

Serum-based ELISA (enzyme-linked immunosorbent assay) has been widely used to detect anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies. However, to date, no study has investigated patient urine as a biological sample to detect SARS-CoV-2 virus-specific antibodies. An in-house urine-based ELISA was developed using recombinant SARS-CoV-2 nucleocapsid protein. The presence of SARS-CoV-2 antibodies in urine was established, with 94% sensitivity and 100% specificity for the detection of anti-SARS-CoV-2 antibodies with the urine-based ELISA and 88% sensitivity and 100% specificity with a paired serum-based ELISA. The urine-based ELISA that detects anti-SARS-CoV-2 antibodies is a noninvasive method with potential application as a facile COVID-19 immunodiagnostic platform, which can be used to report the extent of exposure at the population level and/or to assess the risk of infection at the individual level.

Previous Infection with SARS-CoV-2 Correlates with Increased Protective Humoral Responses after a Single Dose of an Inactivated COVID-19 Vaccine.

Previous studies have indicated that antibody responses can be robustly induced after the vaccination in individuals previously infected by SARS-CoV-2. To evaluate anti-SARS-CoV-2 humoral responses in vaccinated individuals with or without a previous history of COVID-19, we compared levels of anti-SARS-CoV-2 antibodies in the sera from 21 vaccinees, including COVID-19-recovered or -naïve individuals in different times, before and after immunization with an inactivated COVID-19 vaccine. Anti-SARS-CoV-2-specific antibodies elicited after COVID-19 and/or immunization with an inactivated vaccine were measured by ELISA and Plaque Reduction Neutralizing assays. Antibody kinetics were consistently different between the two vaccine doses for naïve individuals, contrasting with the SARS-CoV-2-recovered subjects in which we observed no additional increase in antibody levels following the second dose. Sera from SARS-CoV2-naïve individuals had no detectable neutralizing activity against lineage B.1 SARS-CoV-2 or Gamma variant five months after the second vaccine dose. Contrarily, SARS-CoV-2-recovered subjects retained considerable neutralizing activity against both viruses. We conclude that a single inactivated SARS-CoV-2 vaccine dose may be sufficient to induce protective antibody responses in individuals with previous history of SARS-CoV-2 infection.

DEVELOPMENT AND VALIDATION OF AN ENZYME-LINKED IMMUNOASSAY KIT FOR DIAGNOSIS AND SURVEILLANCE OF COVID-19 (preprint)

There is a massive demand to identify alternative methods to detect new cases of COVID-19 as well as to investigate the epidemiology of the disease. In many countries, importation of commercial kits poses a significant impact on their testing capacity and increases the costs for the public health system. We have developed an ELISA to detect IgG antibodies against SARS-CoV-2 using a recombinant viral nucleocapsid (rN) protein expressed in E. coli. Using a total of 894 clinical samples we showed that the rN-ELISA was able to detect IgG antibodies against SARS-CoV-2 with high sensitivity (97.5%) and specificity (96.3%) when compared to a commercial antibody test. After three external validation studies, we showed that the test accuracy was higher than 90%. The rN-ELISA IgG kit constitutes a convenient and specific method for the large-scale determination of SARS-Cov-2 antibodies in human sera with high reliability.

The use of denaturing solution as collection and transport media to improve SARS-CoV-2 RNA detection and reduce infection of laboratory personnel.

Accurate testing to detect SARS-CoV-2 RNA is key to counteract the virus spread. Nonetheless, the number of diagnostic laboratories able to perform qPCR tests is limited, particularly in developing countries. We describe the use of a virus-inactivating, denaturing solution (DS) to decrease virus infectivity in clinical specimens without affecting RNA integrity. Swab samples were collected from infected patients and from laboratory personnel using a commercially available viral transport solution and the in-house DS. Samples were tested by RT-qPCR, and exposure to infective viruses was also accessed by ELISA. The DS used did not interfere with viral genome detection and was able to maintain RNA integrity for up to 16 days at room temperature. Furthermore, virus loaded onto DS were inactivated, as attested by attempts to grow SARS-CoV-2 in cell monolayers after DS desalt filtration to remove toxic residues. The DS described here provides a strategy to maintain diagnostic accuracy and protects diagnostic laboratory personnel from accidental infection, as it has helped to protect our lab crew.

Evaluation of the efficacy and safety of icatibant and C1 esterase/kallikrein inhibitor in severe COVID-19: study protocol for a three-armed randomized controlled trial.

BACKGROUND: SARS-CoV-2, the virus that causes COVID-19, enters the cells through a mechanism dependent on its binding to angiotensin-converting enzyme 2 (ACE2), a protein highly expressed in the lungs. The putative viral-induced inhibition of ACE2 could result in the defective degradation of bradykinin, a potent inflammatory substance. We hypothesize that increased bradykinin in the lungs is an important mechanism driving the development of pneumonia and respiratory failure in COVID-19. METHODS: This is a phase II, single-center, three-armed parallel-group, open-label, active control superiority randomized clinical trial. One hundred eighty eligible patients will be randomly assigned in a 1:1:1 ratio to receive either the inhibitor of C1e/kallikrein 20 U/kg intravenously on day 1 and day 4 plus standard care; or icatibant 30 mg subcutaneously, three doses/day for 4 days plus standard care; or standard care alone, as recommended in the clinical trials published to date, which includes supplemental oxygen, non-invasive and invasive ventilation, antibiotic agents, anti-inflammatory agents, prophylactic antithrombotic therapy, vasopressor support, and renal replacement therapy. DISCUSSION: Accumulation of bradykinin in the lungs is a common side effect of ACE inhibitors leading to cough. In animal models, the inactivation of ACE2 leads to severe acute pneumonitis in response to lipopolysaccharide (LPS), and the inhibition of bradykinin almost completely restores the lung structure. We believe that inhibition of bradykinin in severe COVID-19 patients could reduce the lung inflammatory response, impacting positively on the severity of disease and mortality rates. TRIAL REGISTRATION: Brazilian Clinical Trials Registry Universal Trial Number (UTN) U1111-1250-1843. Registered on May/5/2020.

THE USE OF DENATURING SOLUTION AS COLLECTION AND TRANSPORT MEDIA TO IMPROVE SARS-COV-2 RNA DETECTION AND REDUCE INFECTION OF LABORATORY PERSONNEL (preprint)

Background Since the emergence of the COVID-19, health officials have struggled to devise strategies to counteract the speed of the pandemic's spread across the globe. It became imperative to implement accurate diagnostic tests for the detection of SARS-CoV-2 RNA on respiratory samples. In many places, however, besides the limited availability of test reagents, laboratory personnel face the challenge of adapting their working routines to manipulate highly infective clinical samples. Here, we proposed the use of a virus-inactivating solution as part of a sample collection kit to decrease the infectious potential of the collected material without affecting the integrity of RNA samples used in diagnostic tests based on RT-qPCR. Methods Nasopharyngeal and oropharyngeal swab samples were collected from SARS-CoV-2-infected patients and from laboratory personnel using a commercially available viral transport solution (VTM) and the denaturing solution (DS) described here. RNA extracted from all samples was tested by RT-qPCR using probes for viral and human genes. Exposure of laboratory personnel to infective viruses was also accessed using ELISA tests. Findings The use of the DS did not interfere with the detection of viral genome or the endogenous human mRNA, since similar results were obtained from samples collected with VTM or DS. In addition, all tests of laboratory personnel for the presence of viral RNA and IgG antibodies against SARS-CoV-2 were negative. Interpretation The methodology described here provides a strategy that allow high diagnostic accuracy as well as safe manipulation of clinical samples by those involved with diagnostic procedures. Funding: CAPES, FAPEMIG, CNPq, MCTIC, FIOCRUZ and the UK Global Challenges Research Fund (GCRF).