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ABSTRACTWe retrospectively studied antibody immunity in 92 candidemia patients, using sera taken at candidemia diagnosis. All patients showed the presence of IgG antibodies against all tested Candida antigens, namely Als3, Mp65, Hyr1 and Eno1, at levels significantly higher than those of non-candidemia controls. Both correlation and multivariable logistic regression analyses showed that the antibodies against Als3 and-Mp65, two known immunodominant and virulence-related proteins, were significantly associated with lower 30-day patient mortality. In particular, high titers of anti-Als3 antibodies were associated with survival in all subgroups of frail, more critical patients (over-median aged, infected by C. albicans or with septic shock) while high anti-Mp65 IgG levels were associated with survival in younger patients and in those infected by non-albicans Candida species or showing no signs of septic shock. A multivariable logistic model including anti-Als3 or anti-MP65 antibody levels and other variables, such as the serum β-glucan level at candidemia diagnosis, septic shock occurrence, the presence of diabetes, and initial antifungal treatment with fluconazole, was highly predictive of candidemia outcome, with an area under the curve of 0.85–0.86. Overall, the data demonstrate the ability of candidemia patients to mount a sustained memory antibody response to Candida antigens and that some of these responses have a sizeable impact on patient survival. Our data invite consideration of a multicenter, prospective investigation of antibody immunity in candidemia.IMPORTANCECandidemia (bloodstream invasion by Candida species) is a major fungal disease in humans. Despite the recent progress in diagnosis and treatment, therapeutic options are limited and under threat of antimicrobial resistance. The disease mortality remains high (around 40%). In contrast with deep-seated invasive candidiasis, particularly that occurring in patients with hematologic malignancies and organ transplants, patients with candidemia are often not immunocompromised and therefore able to mount memory anticandidal immune responses, perhaps primed by Candida commensalism. We investigated antibody immunity in candidemia patients and report here on the ability of these patients to produce antibodies that react with Candida antigens. In particular, the patients with high titers of IgG reactive with two immunodominant, virulence-associated antigens (Als3 and MP65) had a higher 30-day survival. If confirmed by controlled, prospective clinical studies, our data could inform the development of antibody therapy to better treat a severe fungal infection such as candidiasis.

The ability of recombinant, SARS-CoV-2 Spike (S) protein to modulate the production of two COVID-19 relevant, pro-inflammatory cytokines (IL-6 and IFN-γ) in PBMC cultures of healthy, pre-COVID-19 subjects was investigated. We observed that cytokine production was largely and diversely modulated by the S protein depending on antigen or mitogen stimulation, as well as on the protein source, insect (S-in) or human (S-hu) cells. While both proteins co-stimulated cytokine production by polyclonally CD3-activated T cells, PBMC activation by the mitogenic lectin Concanavalin A (Con A) was up-modulated by S-hu protein and down-modulated by S-in protein. These modulatory effects were likely mediated by the S glycans, as demonstrated by direct Con A-S binding experiments and use of yeast mannan as Con A binder. While being ineffective in modulating memory antigenic T cell responses, the S proteins and mannan were able to induce IL-6 production in unstimulated PBMC cultures and upregulate the expression of the mannose receptor (CD206), a marker of anti-inflammatory M2 macrophage. Our data point to a relevant role of N-glycans, particularly N-mannosidic chains, decorating the S protein in the immunomodulatory effects here reported. These novel biological activities of the S glycan ectodomain may add to the comprehension of COVID-19 pathology and immunity to SARS-CoV-2.

Summary: Background: Among interleukin-6 inhibitors suggested for use in COVID-19, there are few robust evidences for the efficacy of sarilumab. Herein, we evaluated the efficacy and safety of sarilumab in severe COVID-19. Methods: In this phase 3, open-labeled, randomized clinical trial, conducted at 5 Italian hospitals, adults with severe COVID-19 pneumonia (excluding mechanically ventilated) were randomized 2:1 to receive intravenous sarilumab (400 mg, repeatable after 12 h) plus standard of care (SOC) (arm A) or to continue SOC (arm B). Randomization was web-based. As post-hoc analyses, the participants were stratified according to baseline inflammatory parameters. The primary endpoint was analysed on the modified Intention-To-Treat population, including all the randomized patients who received any study treatment (sarilumab or SOC). It was time to clinical improvement of 2 points on a 7-points ordinal scale, from baseline to day 30. We used Kaplan Meier method and log-rank test to compare the primary outcome between two arms, and Cox regression stratified by clinical center and adjusted for severity of illness, to estimate the hazard ratio (HR). The trial was registered with EudraCT (2020-001390-76). Findings: Between May 2020 and May 2021, 191 patients were assessed for eligibility, of whom, excluding nine dropouts, 176 were assigned to arm A (121) and B (55). At day 30, no significant differences in the primary endpoint were found (88% [95% CI 81–94] in arm A vs 85% [74–93], HR 1.07 [0.8–1.5] in arm B; log-rank p = 0.50). After stratifying for inflammatory parameters, arm A showed higher probability of improvement than B without statistical significance in the strata with C reactive protein (CRP)

Since the beginning of the pandemic, the generation of new variants periodically recurs. The XBB.1.5 SARS-CoV-2 variant is one of the most recent. This research was aimed at verifying the potential hazard of this new subvariant. To achieve this objective, we performed a genome-based integrative approach, integrating results from genetic variability/phylodynamics with structural and immunoinformatic analyses to obtain as comprehensive a viewpoint as possible. The Bayesian Skyline Plot (BSP) shows that the viral population size reached the plateau phase on 24 November 2022, and the number of lineages peaked at the same time. The evolutionary rate is relatively low, amounting to 6.9 × 10−4 subs/sites/years. The NTD domain is identical for XBB.1 and XBB.1.5 whereas their RBDs only differ for the mutations at position 486, where the Phe (in the original Wuhan) is replaced by a Ser in XBB and XBB.1, and by a Pro in XBB.1.5. The variant XBB.1.5 seems to spread more slowly than sub-variants that have caused concerns in 2022. The multidisciplinary molecular in-depth analyses on XBB.1.5 performed here does not provide evidence for a particularly high risk of viral expansion. Results indicate that XBB.1.5 does not possess features to become a new, global, public health threat. As of now, in its current molecular make-up, XBB.1.5 does not represent the most dangerous variant.

The BQ.1 SARS-CoV-2 variant, also known as Cerberus, is one of the most recent Omicron descendant lineages. Compared to its direct progenitor BA.5, BQ.1 has some additional spike mutations in some key antigenic sites, which confer further immune escape ability over other circulating lineages. In such a context, here, we perform a genome-based survey aimed at obtaining a complete-as-possible nuance of this rapidly evolving Omicron subvariant. Genetic data suggest that BQ.1 represents an evolutionary blind background, lacking the rapid diversification that is typical of a dangerous lineage. Indeed, the evolutionary rate of BQ.1 is very similar to that of BA.5 (7.6 × 10−4 and 7 × 10−4 subs/site/year, respectively), which has been circulating for several months. The Bayesian Skyline Plot reconstruction indicates a low level of genetic variability, suggesting that the peak was reached around 3 September 2022. Concerning the affinity for ACE2, structure analyses (also performed by comparing the properties of BQ.1 and BA.5 RBD) indicate that the impact of the BQ.1 mutations may be modest. Likewise, immunoinformatic analyses showed moderate differences between the BQ.1 and BA5 potential B-cell epitopes. In conclusion, genetic and structural analyses on SARS-CoV-2 BQ.1 suggest no evidence of a particularly dangerous or high expansion capability. Genome-based monitoring must continue uninterrupted for a better understanding of its descendants and all other lineages.

An analysis of the structural effect of the mutations of the B.1.640.2 (IHU) Spike Receptor Binding Domain (RBD) and N-terminal Domain (NTD) is reported along with a comparison with the sister lineage B.1.640.1. and a selection of variants of concern. The effect of the mutations on the RBD–ACE2 interaction was also assessed. The structural analysis applied computational methods that are able to carry out in silico mutagenesis to calculate energy minimization and the folding energy variation consequent to residue mutations. Tools for electrostatic calculation were applied to quantify and display the protein surface electrostatic potential. Interactions at the RBD–ACE2 interface were scrutinized using computational tools that identify the interactions and predict the contribution of each interface residue to the stability of the complex. The comparison among the RBDs shows that the most evident differences between the variants is in the distribution of the surface electrostatic potential: that of B.1.640.1 is as that of the Alpha RBD, while B.1.640.2 appears to have an intermediate surface potential pattern with characteristics between those of the Alpha and Delta variants. Moreover, the B.1.640.2 Spike includes the mutation E484K that in other variants has been suggested to be involved in immune evasion. These properties may hint at the possibility that B.1.640.2 emerged with a potentially increased infectivity with respect to the sister B.1.640.1 variant, but significantly lower than that of the Delta and Omicron variants. However, the analysis of their NTD domains highlights deletions, destabilizing mutations and charge alterations that can limit the ability of the B.1.640.1 and B.1.640.2 variants to interact with cellular components, such as cell surface receptors.

The health emergency linked to the SARS-CoV-2 pandemic has highlighted problems in the health management of chronic patients due to their risk of infection, suggesting the need of new methods to monitor patients. People living with HIV/AIDS (PLWHA) represent a paradigm of chronic patients where an e-health-based remote monitoring could have a significant impact in maintaining an adequate standard of care. The key objective of the study is to provide both an efficient operating model to “follow” the patient, capture the evolution of their disease, and establish proximity and relief through a remote collaborative model. These dimensions are collected through a dedicated mobile application that triggers questionnaires on the basis of decision-making algorithms, tagging patients and sending alerts to staff in order to tailor interventions. All outcomes and alerts are monitored and processed through an innovative e-Clinical platform. The processing of the collected data aims into learning and evaluating predictive models for the possible upcoming alerts on the basis of past data, using machine learning algorithms. The models will be clinically validated as the study collects more data, and, if successful, the resulting multidimensional vector of past attributes will act as a digital composite biomarker capable of predicting HIV-related alerts. Design: All PLWH > 18 sears old and stable disease followed at the outpatient services of a university hospital (n = 1500) will be enrolled in the interventional study. The study is ongoing, and patients are currently being recruited. Preliminary results are yielding monthly data to facilitate learning of predictive models for the alerts of interest. Such models are learnt for one or two months of history of the questionnaire data. In this manuscript, the protocol—including the rationale, detailed technical aspects underlying the study, and some preliminary results—are described. Conclusions: The management of HIV-infected patients in the pandemic era represents a challenge for future patient management beyond the pandemic period. The application of artificial intelligence and machine learning systems as described in this study could enable remote patient management that takes into account the real needs of the patient and the monitoring of the most relevant aspects of PLWH management today.