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Our objective is to achieve a new good-quality and mechanically durable high-transparency material that, when activated by rare earth ions, can be used as laser sources, scintillators, or phosphors. The best functional transparent ceramics are formed from high-symmetry systems, mainly cubic. Considering hexagonal hydroxyapatite, which shows anisotropy, the particle size of the initial powder is extremely important and should be of the order of several tens of nanometers. In this work, transparent micro-crystalline ceramics of non-cubic Ca10(PO4)6(OH)2 calcium phosphate were fabricated via Spark Plasma Sintering (SPS) from two types of nanopowders i.e., commercially available (COM. HA) and laboratory-made (LAB. HA) via the hydrothermal (HT) protocol. Our study centered on examining how the quality of sintered bodies is affected by the following parameters: the addition of LiF sintering agent, the temperature during the SPS process, and the quality of the starting nanopowders. The phase purity, microstructure, and optical transmittance of the ceramics were investigated to determine suitable sintering conditions. The best optical ceramics were obtained from LAB. HA nanopowder with the addition of 0.25 wt.% of LiF sintered at 1000 °C and 1050 °C.

The phenomenon of discontinuous shear thickening (DST) is observed in suspensions of solid particles with a very high-volume fraction. It is characterized by an abrupt decrease in the shear rate for critical stress during a ramp of stress. This behavior can be reproduced in numerical simulations by introducing a local friction between two particles above a given local force. We present experimental results showing this DST behavior obtained with suspensions of magnetic (iron) and nonmagnetic (calcium carbonate) particles and different amounts of a superplasticizer molecule used in the cement industry. For both types of particles, the same behavior was observed with first an increase in critical stress with the amount of plasticizer followed by a decrease at higher concentrations but with a larger viscosity before critical stress was reached. At a low concentration of plasticizer, the low critical stress is interpreted by the local sliding of plasticizer molecules on the surface of particles. At higher concentrations, when total coverage is achieved, the critical stress is higher since it has to remove the molecules out of the surface. At still higher concentrations, the increase in viscosity is explained by the formation of multilayers of molecules on the surface of the particles. This interpretation is supported by the measurement of the adsorption isotherm of the plasticizer on the surface of the particles.

For a panel data linear regression model with both individual and time effects, empirical studies select the two-way random-effects (TWRE) estimator if the Hausman test based on the contrast between the two-way fixed-effects (TWFE) estimator and the TWRE estimator is not rejected. Alternatively, they select the TWFE estimator in cases where this Hausman test rejects the null hypothesis. Not all the regressors may be correlated with these individual and time effects. The one-way Hausman-Taylor model has been generalized to the two-way error component model and allow some but not all regressors to be correlated with these individual and time effects. This paper proposes a pretest estimator for this two-way error component panel data regression model based on two Hausman tests. The first Hausman test is based upon the contrast between the TWFE and the TWRE estimators. The second Hausman test is based on the contrast between the two-way Hausman and Taylor (TWHT) estimator and the TWFE estimator. The Monte Carlo results show that this pretest estimator is always second best in MSE performance compared to the efficient estimator, whether the model is random-effects, fixed-effects or Hausman and Taylor. This paper generalizes the one-way pretest estimator to the two-way error component model.

Background: The COVID-19 pandemic has affected Madagascar, Cameroon, and the Central African Republic (CAR), with each experiencing multiple waves by mid-2022. This study aimed to evaluate immunity against SARS-CoV-2 strains Wuhan (W) and BA.2 (BA.2) among healthcare workers (HCWs) in these countries, focusing on vaccination and natural infection effects. Methods: HCWs’ serum samples were analyzed for neutralizing antibodies (nAbs) against W and BA.2 variants, with statistical analyses comparing responses between countries and vaccination statuses. Results: Madagascar showed significantly higher nAb titers against both strains compared to CAR and Cameroon. Vaccination notably increased nAb levels against W by 2.6-fold in CAR and 1.8-fold in Madagascar, and against BA.2 by 1.6-fold in Madagascar and 1.5-fold in CAR. However, in Cameroon, there was no significant difference in nAb levels between vaccinated and unvaccinated groups. Conclusion: This study highlights the complex relationship between natural and vaccine-induced immunity, emphasizing the importance of assessing immunity in regions with varied epidemic experiences and low vaccination rates.

The World Health Organization reports that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has impacted a staggering 770 million individuals to date. Despite the widespread nature of this viral infection, its precise effects remain largely elusive. This scientific inquiry aims to shed light on the intricate interplay between SARS-CoV-2 infection and the development of neurodegenerative disorders—an affliction that weighs heavily on millions worldwide and stands as the fourth most prevalent cause of mortality. By comprehensively understanding the repercussions of SARS-CoV-2 on neurodegenerative disorders, we strive to unravel critical insights that can potentially shape our approach to the diagnosis, prevention, and treatment of these debilitating conditions. To achieve this goal, we conducted a comprehensive literature review of the scientific data available to date showing that SARS-CoV-2 infection is associated with increased risk and severity of neurodegenerative disorders, as well as altered expression of key genes and pathways involved in their pathogenesis.

Vaccinia virus (Orthopoxvirus) F17 protein is a major virion structural phosphoprotein having a molecular weight of 11 kDa. Recently, it was shown that F17 synthesised in infected cells interacts with mTOR subunits to evade cell immunity and stimulate late viral protein synthesis. Several years back, we purified an 11 kDa protein that inhibited protein synthesis in reticulocyte lysate from virions, and that possesses all physico-chemical properties of F17 protein. To investigate this discrepancy, we used defective vaccinia virus particles devoid of the F17 protein (designated iF17− particles) to assess their ability to inhibit protein synthesis. To this aim, we purified iF17− particles from cells infected with a vaccinia virus mutant which expresses F17 only in the presence of IPTG. The SDS-PAGE protein profiles of iF17− particles or derived particles, obtained by solubilisation of the viral membrane, were similar to that of infectious iF17 particles. As expected, the profiles of full iF17− particles and those lacking the viral membrane were missing the 11 kDa F17 band. The iF17− particles did attach to cells and injected their viral DNA into the cytoplasm. Co-infection of the non-permissive BSC40 cells with a modified vaccinia Ankara (MVA) virus, expressing an mCherry protein, and iF17− particles, induced a strong mCherry fluorescence. Altogether, these experiments confirmed that the iF17− particles can inject their content into cells. We measured the rate of protein synthesis as a function of the multiplicity of infection (MOI), in the presence of puromycin as a label. We showed that iF17− particles did not inhibit protein synthesis at high MOI, by contrast to the infectious iF17 mutant. Furthermore, the measured efficiency to inhibit protein synthesis by the iF17 mutant virus generated in the presence of IPTG, was threefold to eightfold lower than that of the wild-type WR virus. The iF17 mutant contained about threefold less F17 protein than wild-type WR. Altogether these results strongly suggest that virion-associated F17 protein is essential to mediate a stoichiometric inhibition of protein synthesis, in contrast to the late synthesised F17. It is possible that this discrepancy is due to different phosphorylation states of the free and virion-associated F17 protein.

The first hyperpolarizability of graphene quantum dots (GQDs) suspended in water was determined using the hyper-Rayleigh scattering (HRS) technique. To the best of our knowledge, this is the first application of the HRS technique to characterize GQDs. Two commercial GQDs (Acqua-Cyan and Acqua-Green) with different compositions were studied. The HRS experiments were performed with an excitation laser at 1064 nm. The measured hyperpolarizabilities were (1.0±0.1)×10−27 esu and (0.9±0.1)×10−27 esu for Acqua-Cyan and Acqua-Green, respectively. The results were used to estimate the hyperpolarizability per nanosheet obtained by assuming that each GQD has five nanosheets with 0.3 nm thickness. The two-level model, used to calculate the static hyperpolarizability per nanosheet, provides values of (2.4±0.1)×10−28 esu (Acqua-Cyan) and (0.5±0.1)×10−28 esu (Aqua-Green). The origin of the nonlinearity is discussed on the basis of polarized resolved HRS experiments, and electric quadrupolar behavior with a strong dependence on surface effects. The nontoxic characteristics and order of magnitude indicate that these GQDs may be useful for biological microscopy imaging.

Background: Cannabis use by physicians can be detrimental for them and their patients. We conducted a systematic review and meta-analysis on the prevalence of cannabis use by medical doctors (MDs)/students. Method: PubMed, Cochrane, Embase, PsycInfo and ScienceDirect were searched for studies reporting cannabis use in MDs/students. For each frequency of use (lifetime/past year/past month/daily), we stratified a random effect meta-analysis depending on specialties, education level, continents, and periods of time, which were further compared using meta-regressions. Results: We included 54 studies with a total of 42,936 MDs/students: 20,267 MDs, 20,063 medical students, and 1976 residents. Overall, 37% had used cannabis at least once over their lifetime, 14% over the past year, 8% over the past month and 1.1 per thousand (‰) had a daily use. Medical students had a greater cannabis use than MDs over their lifetime (38% vs. 35%, p < 0.001), the past year (24% vs. 5%, p < 0.001), and the past month (10% vs. 2%, p < 0.05), without significance for daily use (0.5% vs. 0.05%, NS). Insufficient data precluded comparisons among medical specialties. MDs/students from Asian countries seemed to have the lowest cannabis use: 16% over their lifetime, 10% in the past year, 1% in the past month, and 0.4% daily. Regarding periods of time, cannabis use seems to follow a U-shape, with a high use before 1990, followed by a decrease between 1990 and 2005, and a rebound after 2005. Younger and male MDs/students had the highest cannabis use. Conclusions: If more than a third of MDs tried cannabis at least once in their lifetime, this means its daily use is low but not uncommon (1.1‰). Medical students are the biggest cannabis users. Despite being common worldwide, cannabis use is predominant in the West, with a rebound since 2005 making salient those public health interventions during the early stage of medical studies.

The chemical investigation of the n-hexane fraction from the methanol extract of the stem bark of Symphonia globulifera Linn f., which displayed good in vitro activity against Leishmania donovani NR-48822 promastigotes (IC50 43.11 µg/mL), led to the isolation of three previously unreported polyprenylated benzophenones, guttiferone U (1), V (2)/W (3), and a new tocotrienol derivative named globuliferanol (4), along with 11 known compounds (5–15). Their structures were elucidated based on their NMR and MS data. Some isolated compounds were assessed for both their antileishmanial and cytotoxic activities against L. donovani and Vero cells, respectively. Guttiferone K (5) exhibited the best potency (IC50 3.30 μg/mL), but with low selectivity to Vero cells. The n-hexane fraction and some compounds were also assessed in vitro for their antibacterial activity against seven bacterial strains. All the samples exhibited moderate to potent antibacterial activity (MICs ≤ 15.6 µg/mL) against at least one of the tested strains.

This paper presents an overview of the emerging trends in the development of electrical generators for large wind turbines. To describe the developments in the design of electrical generators, it is necessary to look at the conversion system as a whole, and then, the structural and mechanical performances of the drive train need to be considered. Many drive train configurations have been proposed for large wind turbines; they should ensure high reliability, long availability and reduced maintainability. Although most installed wind turbines are geared, directly driven wind turbines with permanent magnet generators have attracted growing interest in the last few years, which has been in parallel to the continuous increase of the per unit turbine power. The aim of this work is to present the recent commercial designs of electrical generators in large wind turbines. Both the strengths and weaknesses of the existing systems are discussed. The most emerging technologies in high-power, low-speed electrical generators are investigated. Furthermore, a comparative analysis of different electrical generator concepts is performed, and the generators are assessed upon a list of criteria such as the mass, cost, and mass-to-torque ratio. Within the framework of these criteria, it may help to determine whether the electrical generator is technically feasible and economically viable for high-power wind turbines. Finally, this review could help to determine suitable generators for use in large and ultra-large wind energy systems.

The thermal lens effect is analyzed as a time-resolved Z-scan measurement using cw-single Gaussian beam configuration. The main characteristics of the measurement method are determined. We focus on the evaluation of the measurement error from statistical calculations to also check the linearity of the response and the way to extract the thermo-optical characteristics of absorbing liquids. The results are also applied to demonstrate the feasibility of absorption and scattering efficiencies determination on gold nanoparticles of 5 and 50 nm diameters.

Chronic kidney disease (CKD) frequently leads to hyperphosphatemia and hyperparathyroidism, mineral bone disorder (CKD-MBD), ectopic calcifications and cardiovascular mortality. PTH activates the osteoanabolic Gαs/PKA and the Gαq/11/PKC pathways in osteoblasts, the specific impact of the latter in CKD-MBD is unknown. We generated osteoblast specific Gαq/11 knockout (KO) mice and established CKD-MBD by subtotal nephrectomy and dietary phosphate load. Bone morphology was assessed by micro-CT, osteoblast function by bone planar scintigraphy at week 10 and 22 and by histomorphometry. Osteoblasts isolated from Gαq/11 KO mice increased cAMP but not IP3 in response to PTH 1-34, demonstrating the specific KO of the PKC signaling pathway. Osteoblast specific Gαq/11 KO mice exhibited increased serum calcium and reduced bone cortical thickness and mineral density at 24 weeks. CKD Gαq/11 KO mice had similar bone morphology compared to WT, while CKD Gαq/11-KO on high phosphate diet developed decreased metaphyseal and diaphyseal cortical thickness and area, as well as a reduction in trabecular number. Gαq/11-KO increased bone scintigraphic tracer uptake at week 10 and mitigated tracer uptake in CKD mice at week 22. Histological bone parameters indicated similar trends. Gαq/11-KO in osteoblast modulates calcium homeostasis, bone formation rate, bone morphometry, and bone mineral density. In CKD and high dietary phosphate intake, osteoblast Gαq/11/PKC KO further aggravates mineral bone disease.

Due to its dire impacts on marine life, public health, and socio-economic services, oil spills require an immediate response. Effective action starts with good knowledge of the ocean dynamics and circulation, from which Lagrangian methods derive key information on the dispersal pathways present in the contaminated region. However, precise assessments of the capacity of Lagrangian methods in real contamination cases remain rare and limited to large slicks spanning several hundreds of km. Here we address this knowledge gap and consider two medium-scale (tens of km wide) events of oil in contrasting conditions: an offshore case (East China Sea, 2018) and a recent near-coastal one (East Mediterranean, 2021). Our comparison between oil slicks and Lagrangian diagnostics derived from near-real-time velocity fields shows that the calculation of Lagrangian fronts is, in general, more robust to errors in the velocity fields and more informative on the dispersion pathways than the direct advection of a numerical tracer. The inclusion of the effect of wind is also found to be essential, being capable of suddenly breaking Lagrangian transport barriers. Finally, we show that a usually neglected Lagrangian quantity, the Lyapunov vector, can be exploited to predict the front drifting speed, and in turn, its future location over a few days, on the basis of near-real-time information alone. These results may be of special relevance in the context of next-generation altimetry missions that are expected to provide highly resolved and precise near-real-time velocity fields for both open ocean and coastal regions.

A general study of the diffracted far field due to thermal lens heating using Gaussian beams is presented. The numerical simulation considers the whole system, including both the optical and the thermal parameters. It is shown that the existing simplified relations found in the literature and used up to now only give the order of magnitude of the thermo-optical coefficients. More accurate, simplified formulas are derived to measure the induced thermal phase shift when working with Z-scan-based methods. Temperature estimation in absorbing media turn out to be more reliable whether using time-resolved or steady-state techniques. The extension of the calculation to the image formation in a 4f system is also addressed.

In this article, we describe the development and evaluation of a double antigen sandwich enzyme-linked immunosorbent assay (ELISA) able to detect serotype 4-specific antibodies from BTV-4 infected or vaccinated animals using a recombinant BTV-4 VP2 protein. The coding sequence of VP2 was inserted into a pVote plasmid by recombination in the Gateway® cloning system. Vaccinia virus (VacV) was used as a vector for the expression of the recombinant VP2. After production in BSR cells, recombinant VP2 was purified by immunoprecipitation using a FLAG tag and then used both as the coated ELISA antigen and as the HRP-tagged conjugate. The performance of the ELISA was evaluated with 1186 samples collected from BTV negative, infected or vaccinated animals. The specificity and sensitivity of the BTV-4 ELISA were above the expected standards for the detection of anti-BTV-4 VP2 antibodies in animals reared in Europe or in the Mediterranean basin. Cross-reactions were observed with reference sera for serotypes 10 and 20, and to a lesser extent with serotypes 12, 17 and 24, due to their genetic proximity to serotype 4. Nevertheless, these serotypes have never been detected in Europe and the Mediterranean area. This ELISA, which requires only the production of a recombinant protein, can be used to detect BTV serotype 4-specific antibodies and is therefore an attractive alternative diagnostic method to serum neutralization.

Among the different tools to address the antibiotic resistance crisis, bioprospecting in complex uncharted habitats to detect novel microorganisms putatively producing original antimicrobial compounds can definitely increase the current therapeutic arsenal of antibiotics. Fungi from numerous habitats have been widely screened for their ability to express specific biosynthetic gene clusters (BGCs) involved in the synthesis of antimicrobial compounds. Here, a collection of unique 75 deep oceanic crust fungi was screened to evaluate their biotechnological potential through the prism of their antimicrobial activity using a polyphasic approach. After a first genetic screening to detect specific BGCs, a second step consisted of an antimicrobial screening that tested the most promising isolates against 11 microbial targets. Here, 12 fungal isolates showed at least one antibacterial and/or antifungal activity (static or lytic) against human pathogens. This analysis also revealed that Staphylococcus aureus ATCC 25923 and Enterococcus faecalis CIP A 186 were the most impacted, followed by Pseudomonas aeruginosa ATCC 27853. A specific focus on three fungal isolates allowed us to detect interesting activity of crude extracts against multidrug-resistant Staphylococcus aureus. Finally, complementary mass spectrometry (MS)-based molecular networking analyses were performed to putatively assign the fungal metabolites and raise hypotheses to link them to the observed antimicrobial activities.

Clustering methods unequivocally show considerable influence on many recent algorithms and play an important role in hyperspectral data analysis. Here, we challenge the clustering for mineral identification using two different strategies in hyperspectral long wave infrared (LWIR, 7.7–11.8 μm). For that, we compare two algorithms to perform the mineral identification in a unique dataset. The first algorithm uses spectral comparison techniques for all the pixel-spectra and creates RGB false color composites (FCC). Then, a color based clustering is used to group the regions (called FCC-clustering). The second algorithm clusters all the pixel-spectra to directly group the spectra. Then, the first rank of non-negative matrix factorization (NMF) extracts the representative of each cluster and compares results with the spectral library of JPL/NASA. These techniques give the comparison values as features which convert into RGB-FCC as the results (called clustering rank1-NMF). We applied K-means as clustering approach, which can be modified in any other similar clustering approach. The results of the clustering-rank1-NMF algorithm indicate significant computational efficiency (more than 20 times faster than the previous approach) and promising performance for mineral identification having up to 75.8% and 84.8% average accuracies for FCC-clustering and clustering-rank1 NMF algorithms (using spectral angle mapper (SAM)), respectively. Furthermore, several spectral comparison techniques are used also such as adaptive matched subspace detector (AMSD), orthogonal subspace projection (OSP) algorithm, principal component analysis (PCA), local matched filter (PLMF), SAM, and normalized cross correlation (NCC) for both algorithms and most of them show a similar range in accuracy. However, SAM and NCC are preferred due to their computational simplicity. Our algorithms strive to identify eleven different mineral grains (biotite, diopside, epidote, goethite, kyanite, scheelite, smithsonite, tourmaline, pyrope, olivine, and quartz).

Pressure sensors are good candidates for measuring driver postural information, which is indicative for identifying driver’s intention and seating posture. However, monitoring systems based on pressure sensors must overcome the price barriers in order to be practically feasible. This study, therefore, was dedicated to explore the possibility of using pressure sensors with lower resolution for driver posture monitoring. We proposed pressure features including center of pressure, contact area proportion, and pressure ratios to recognize five typical trunk postures, two typical left foot postures, and three typical right foot postures. The features from lower-resolution mapping were compared with those from high-resolution Xsensor pressure mats on the backrest and seat pan. We applied five different supervised machine-learning techniques to recognize the postures of each body part and used leave-one-out cross-validation to evaluate their performance. A uniform sampling method was used to reduce number of pressure sensors, and five new layouts were tested by using the best classifier. Results showed that the random forest classifier outperformed the other classifiers with an average classification accuracy of 86% using the original pressure mats and 85% when only 8% of the pressure sensors were available. This study demonstrates the feasibility of using fewer pressure sensors for driver posture monitoring and suggests research directions for better sensor designs.

Zinc oxide nanoparticles were prepared from Zn5(CO3)2(OH)6 precursor, capped with poly(vinylpyrrolidone) (PVP), and annealed at 600 °C. The obtained powders were characterized by a powder X-ray diffraction (PXD), transmission electron microscopy (TEM), scanning electron microscopy (SEM), UV–visible spectroscopy (UV–vis), Raman spectroscopy, infrared spectroscopy (IR), thermal analysis (TGA/DTA), and third-order nonlinear (NL) optical measurement. Morphological evaluation by TEM and SEM measurements indicated that the precursor micro-particles are ball-shaped structures composed of plates with a thickness of approximately 10 nm. ZnO thin films, as well as ZnO/polymer multilayer layouts, were obtained by wet chemical methods (spin- and dip-coating). Surface topography and morphology of the obtained films were studied by SEM and AFM microscopy. Films with uniformly distributed ZnO plates, due to the erosion of primary micro-particles were formed. The fabricated specimens were also analyzed using a spectroscopic ellipsometry in order to calculate dielectric function and film thickness.

The aim of this paper is to present the design and modeling of a machine that possesses some advantageous characteristics for wind energy conversion applications. The studied machine is a double stator inner rotor axial airgap flux switching permanent magnet machine (AFSPM). The paper will start by presenting this type of machine and its points of interest. Then, it will continue by introducing the constructed prototype and its specifications and structure. This prototype has been designed based on a reference specification used at GREAH to develop different prototypes and compare their performances. The second part will introduce the reluctance network model specifically constructed for this type of machine. The constructed model was validated by comparing its results to the results from the finite element method model. Finally, the experimental results will be presented and compared to the reluctance network (RN) model results where satisfying agreement between both results was obtained.

Recent remote sensing studies have suggested exploiting vegetation optical properties for assessing oil contamination, especially total petroleum hydrocarbons (TPH) in vegetated areas. Methods based on the tracking of alterations in leaf biochemistry have been proposed for detecting and quantifying TPH under controlled and field conditions. In this study, we expand their use to airborne imagery, in order to monitor oil contamination at a larger scale. Airborne hyperspectral images with very high spatial and spectral resolutions were acquired over an industrial site with oil-contamination (mud pits) and control sites both colonized by Rubus fruticosus L. The method of oil detection exploiting 14 vegetation indices succeeded in classifying the sites in the case of high TPH contamination (overall accuracy ≥ 91.8%). Two methods, based on either the PROSAIL (PROSPECT + SAIL) radiative transfer model or elastic net multiple regression, were also developed for quantifying TPH. Both methods were tested on reflectance measurements in the field, at leaf and canopy scales, and on the image, and achieved accurate predictions of TPH concentrations (RMSE ≤ 3.28 g/kg−1 and RPD ≥ 1.90). The methods were validated on additional sites and open up promising perspectives of operational application for oil and gas companies, with the emergence of new hyperspectral satellite sensors.

The evolving global threat of antimicrobial resistance requires a deep renewal of the antibiotic arsenal including the isolation and characterization of new drugs. Underexplored marine ecosystems may represent an untapped reservoir of novel bioactive molecules. Deep-sea fungi isolated from a record-depth sediment core of almost 2000 m below the seafloor were investigated for antimicrobial activities. This antimicrobial screening, using 16 microbial targets, revealed 33% of filamentous fungi synthesizing bioactive compounds with activities against pathogenic bacteria and fungi. Interestingly, occurrence of antimicrobial producing isolates was well correlated with the complexity of the habitat (in term of microbial richness), as higher antimicrobial activities were obtained at specific layers of the sediment core. It clearly highlights complex deep-sea habitats as chemical battlefields where synthesis of numerous bioactive compounds appears critical for microbial competition. The six most promising deep subseafloor fungal isolates were selected for the production and extraction of bioactive compounds. Depending on the fungal isolates, antimicrobial compounds were only biosynthesized in semi-liquid or solid-state conditions as no antimicrobial activities were ever detected using liquid fermentation. An exception was made for one fungal isolate, and the extraction procedure designed to extract amphipathic compounds was successful and highlighted the amphiphilic profile of the bioactive metabolites.

Considering virus-related and drug-induced immunocompromised status of critically ill COVID-19 patients, we hypothesize that these patients would more frequently develop ventilator-associated pneumonia (VAP) than patients with ARDS from other viral causes. We conducted a retrospective observational study in two intensive care units (ICUs) from France, between 2017 and 2020. We compared bacterial co-infection at ICU admission and throughout the disease course of two retrospective longitudinally sampled groups of critically ill patients, who were admitted to ICU for either H1N1 or SARS-CoV-2 respiratory infection and depicted moderate-to-severe ARDS criteria upon admission. Sixty patients in the H1N1 group and 65 in the COVID-19 group were included in the study. Bacterial co-infection at the endotracheal intubation time was diagnosed in 33% of H1N1 and 16% COVID-19 patients (p = 0.08). The VAP incidence per 100 days of mechanical ventilation was 3.4 (2.2−5.2) in the H1N1 group and 7.2 (5.3−9.6) in the COVID-19 group (p < 0.004). The HR to develop VAP was of 2.33 (1.34−4.04) higher in the COVID-19 group (p = 0.002). Ten percent of H1N1 patients and 30% of the COVID-19 patients had a second episode of VAP (p = 0.013). COVID-19 patients have fewer bacterial co-infections upon admission, but the incidence of secondary infections increased faster in this group compared to H1N1 patients.

The coronavirus disease 2019 (COVID-19) pandemic has highlighted the urgent need for effective prophylactic vaccination to prevent the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Intranasal vaccination is an attractive strategy to prevent COVID-19 as the nasal mucosa represents the first-line barrier to SARS-CoV-2 entry. The current intramuscular vaccines elicit systemic immunity but not necessarily high-level mucosal immunity. Here, we tested a single intranasal dose of our candidate adenovirus type 5-vectored vaccine encoding the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein (AdCOVID) in inbred, outbred, and transgenic mice. A single intranasal vaccination with AdCOVID elicited a strong and focused immune response against RBD through the induction of mucosal IgA in the respiratory tract, serum neutralizing antibodies, and CD4 + and CD8 + T cells with a T h 1-like cytokine expression profile. A single AdCOVID dose resulted in immunity that was sustained for over six months. Moreover, a single intranasal dose completely protected K18-hACE2 mice from lethal SARS-CoV-2 challenge, preventing weight loss and mortality. These data show that AdCOVID promotes concomitant systemic and mucosal immunity and represents a promising vaccine candidate.

Annual influenza vaccination greatly reduces morbidity and mortality, but effectiveness remains sub-optimal. Weaknesses of current vaccines include low effectiveness against mismatched strains, lack of mucosal and other effective tissue-resident immune responses, weak cellular immune responses, and insufficiently durable immune responses. The safety and immunogenicity of NasoVAX, a monovalent intranasal influenza vaccine based on a replication-deficient adenovirus type 5 platform, were evaluated in a placebo-controlled single ascending-dose study. Sixty healthy adults (18-49 years) received a single intranasal dose of 1×10 9 viral particles (vp), 1 × 10 10 vp, or 1 × 10 11 vp of NasoVAX or placebo. NasoVAX was well-tolerated and elicited robust influenza-specific systemic and mucosal immune responses. The highest NasoVAX dose and the approved Fluzone ® influenza vaccine elicited comparable hemagglutination inhibition (HAI) geometric mean titers (152.8 vs. 293.4) and microneutralization (MN) geometric mean titers (142.5 vs. 162.8), with NasoVAX HAI titers maintained more than 1-year on average following a single dose. Hemagglutinin-specific T cells responses were also documented in peripheral mononuclear cell (PBMC) preparations. Consistent with the intranasal route of administration, NasoVAX elicited antigen-specific mucosal IgA responses in the nasopharyngeal cavity with an increase of approximately 2-fold over baseline GMT at the mid- and high-doses. In summary, NasoVAX appeared safe and elicited a broad immune response, including humoral, cellular, and mucosal immunity, with no impact of baseline anti-adenovirus antibody at the most immunogenic dose.