Smallpox vaccination-elicited antibodies cross-neutralize 2022-Monkeypox virus Clade II.

Since early May 2022, some monkeypox virus (MPXV) infections have been reported from countries where the disease is not endemic. Within 2 months, the number of patients has increased extensively, becoming the most considerable MPXV outbreak described. Smallpox vaccines demonstrated high efficacy against MPXVs in the past and are considered a crucial outbreak control measure. However, viruses isolated during the current outbreak carry distinct genetic variations, and the cross-neutralizing capability of antibodies remains to be assessed. Here we report that serum antibodies elicited by first-generation smallpox vaccines can neutralize the current MPXV more than 40 years after vaccine administration.

The initial interplay between HIV and mucosal innate immunity.

Human Immunodeficiency Virus (HIV) is still one of the major global health issues, and despite significant efforts that have been put into studying the pathogenesis of HIV infection, several aspects need to be clarified, including how innate immunity acts in different anatomical compartments. Given the nature of HIV as a sexually transmitted disease, one of the aspects that demands particular attention is the mucosal innate immune response. Given this scenario, we focused our attention on the interplay between HIV and mucosal innate response: the different mucosae act as a physical barrier, whose integrity can be compromised by the infection, and the virus-cell interaction induces the innate immune response. In addition, we explored the role of the mucosal microbiota in facilitating or preventing HIV infection and highlighted how its changes could influence the development of several opportunistic infections. Although recent progress, a proper characterization of mucosal innate immune response and microbiota is still missing, and further studies are needed to understand how they can be helpful for the formulation of an effective vaccine.

Proper Selection of In Vitro Cell Model Affects the Characterization of the Neutralizing Antibody Response against SARS-CoV-2.

(1) Background: Our aim is the evaluation of the neutralizing activity of BNT162b2 mRNA vaccine-induced antibodies in different in vitro cellular models, as this still represents one of the surrogates of protection against SARS-CoV-2 viral variants. (2) Methods: The entry mechanisms of SARS-CoV-2 in three cell lines (Vero E6, Vero E6/TMPRSS2 and Calu-3) were evaluated with both pseudoviruses and whole virus particles. The neutralizing capability of sera collected from vaccinated subjects was characterized through cytopathic effects and Real-Time RT PCR. (3) Results: In contrast to Vero E6 and Vero E6/TMPRSS2, Calu-3 allowed the evaluation of both viral entry mechanisms, resembling what occurs during natural infection. The choice of an appropriate cellular model can decisively influence the determination of the neutralizing activity of antibodies against SARS-CoV-2 variants. Indeed, the lack of correlation between neutralizing data in Calu-3 and Vero E6 demonstrated that testing the antibody inhibitory activity by using a single cell model possibly results in an inaccurate characterization. (4) Conclusions: Cellular systems allowing only one of the two viral entry pathways may not fully reflect the neutralizing activity of vaccine-induced antibodies moving increasingly further away from possible correlates of protection from SARS-CoV-2 infection.

Estimating dyskinesia severity in Parkinson's disease by using a waist-worn sensor: concurrent validity study.

Our research team previously developed an accelerometry-based device, which can be worn on the waist during daily life activities and detects the occurrence of dyskinesia in patients with Parkinson's disease. The goal of this study was to analyze the magnitude of correlation between the numeric output of the device algorithm and the results of the Unified Dyskinesia Rating Scale (UDysRS), administered by a physician. In this study, 13 Parkinson's patients, who were symptomatic with dyskinesias, were monitored with the device at home, for an average period of 30 minutes, while performing normal daily life activities. Each patient's activity was simultaneously video-recorded. A physician was in charge of reviewing the recorded videos and determining the severity of dyskinesia through the UDysRS for every patient. The sensor device yielded only one value for dyskinesia severity, which was calculated by averaging the recorded device readings. Correlation between the results of physician's assessment and the sensor output was analyzed with the Spearman's correlation coefficient. The correlation coefficient between the sensor output and UDysRS result was 0.70 (CI 95%: 0.33-0.88; p = 0.01). Since the sensor was located on the waist, the correlation between the sensor output and the results of the trunk and legs scale sub-items was calculated: 0.91 (CI 95% 0.76-0.97: p < 0.001). The conclusion is that the magnitude of dyskinesia, as measured by the tested device, presented good correlation with that observed by a physician.

Corrigendum: Analysis of Correlation between an Accelerometer-Based Algorithm for Detecting Parkinsonian Gait and UPDRS Subscales.

[This corrects the article on p. 431 in vol. 8, PMID: 28919877.].

Analysis of Correlation between an Accelerometer-Based Algorithm for Detecting Parkinsonian Gait and UPDRS Subscales.

BACKGROUND: Our group earlier developed a small monitoring device, which uses accelerometer measurements to accurately detect motor fluctuations in patients with Parkinson's (On and Off state) based on an algorithm that characterizes gait through the frequency content of strides. To further validate the algorithm, we studied the correlation of its outputs with the motor section of the Unified Parkinson's Disease Rating Scale part-III (UPDRS-III). METHOD: Seventy-five patients suffering from Parkinson's disease were asked to walk both in the Off and the On state while wearing the inertial sensor on the waist. Additionally, all patients were administered the motor section of the UPDRS in both motor phases. Tests were conducted at the patient's home. Convergence between the algorithm and the scale was evaluated by using the Spearman's correlation coefficient. RESULTS: Correlation with the UPDRS-III was moderate (rho -0.56; p < 0.001). Correlation between the algorithm outputs and the gait item in the UPDRS-III was good (rho -0.73; p < 0.001). The factorial analysis of the UPDRS-III has repeatedly shown that several of its items can be clustered under the so-called Factor 1: "axial function, balance, and gait." The correlation between the algorithm outputs and this factor of the UPDRS-III was -0.67 (p < 0.01). CONCLUSION: The correlation achieved by the algorithm with the UPDRS-III scale suggests that this algorithm might be a useful tool for monitoring patients with Parkinson's disease and motor fluctuations.