Long-distance multiplexed quantum teleportation from a telecom photon to a solid-state qubit

Quantum teleportation is an essential capability for quantum networks, allowing the transmission of quantum bits (qubits) without a direct exchange of quantum information. Its implementation between distant parties requires teleportation of the quantum information to matter qubits that store it for long enough to allow users to perform further processing. Here we demonstrate long distance quantum teleportation from a photonic qubit at telecom wavelength to a matter qubit, stored as a collective excitation in a solid-state quantum memory. Our system encompasses an active feed-forward scheme, implementing a phase shift on the qubit retrieved from the memory, therefore completing the protocol. Moreover, our approach is time-multiplexed, allowing for an increase in the teleportation rate, and is directly compatible with the deployed telecommunication networks, two key features for its scalability and practical implementation, that will play a pivotal role in the development of long-distance quantum communication

Entanglement between a telecom photon and an on-demand multimode solid-state quantum memory

Entanglement between photons at telecommunication wavelengths and long-lived quantum memories is one of the fundamental requirements of long-distance quantum communication. Quantum memories featuring on-demand read-out and multimode operation are additional precious assets that will benefit the communication rate. In this work we report the first demonstration of entanglement between a telecom photon and a collective spin excitation in a multimode solid-state quantum memory. Photon pairs are generated through widely non-degenerate parametric down-conversion, featuring energy-time entanglement between the telecom-wavelength idler and a visible signal photon. The latter is stored in a Pr$^{3+}$:Y$_2$SiO$_5$ crystal as a spin wave using the full Atomic Frequency Comb scheme. We then recall the stored signal photon and analyze the entanglement using the Franson scheme. We measure conditional fidelities of $92(2)\%$ for excited-state storage, enough to violate a CHSH inequality, and $77(2)\%$ for spin-wave storage. Taking advantage of the on-demand read-out from the spin state, we extend the entanglement storage in the quantum memory for up to 47.7~$\mu$s, which could allow for the distribution of entanglement between quantum nodes separated by distances of up to 10 km

Effect of pneumococcal conjugate vaccines and SARS-CoV-2 on antimicrobial resistance and the emergence of Streptococcus pneumoniae serotypes with reduced susceptibility in Spain, 2004-20: a national surveillance study

Background: Epidemiological studies are necessary to explore the effect of current pneumococcal conjugate vaccines (PCVs) against antibiotic resistance, including the rise of non-vaccine serotypes that are resistant to antibiotics. Hence, epidemiological changes in the antimicrobial pattern of Streptococcus pneumoniae before and during the first year of the COVID-19 pandemic were studied. Methods: In this national surveillance study, we characterised the antimicrobial susceptibility to a panel of antibiotics in 3017 pneumococcal clinical isolates with reduced susceptibility to penicillin during 2004-20 in Spain. This study covered the early and late PCV7 periods; the early, middle, and late PCV13 periods; and the first year of the COVID-19 pandemic, to evaluate the contribution of PCVs and the pandemic to the emergence of non-vaccine serotypes associated with antibiotic resistance. Findings: Serotypes included in PCV7 and PCV13 showed a decline after the introduction of PCVs in Spain. However, an increase in non-PCV13 serotypes (mainly 11A, 24F, and 23B) that were not susceptible to penicillin promptly appeared. A rise in the proportion of pneumococcal strains with reduced susceptibility to β-lactams and erythromycin was observed in 2020, coinciding with the emergence of SARS-CoV-2. Cefditoren was the β-lactam with the lowest minimum inhibitory concentration (MIC)50 or MIC90 values, and had the highest proportion of susceptible strains throughout 2004-20. Interpretation: The increase in non-PCV13 serotypes associated with antibiotic resistance is concerning, especially the increase of penicillin resistance linked to serotypes 11A and 24F. The future use of PCVs with an increasingly broad spectrum (such as PCV20, which includes serotype 11A) could reduce the impact of antibiotic resistance for non-PCV13 serotypes. The use of antibiotics to prevent co-infections in patients with COVID-19 might have affected the increased proportion of pneumococcal-resistant strains. Cefotaxime as a parenteral option, and cefditoren as an oral choice, were the antibiotics with the highest activity against non-PCV20 serotypes.This work was supported by the Spanish Ministry of Science and Innovation (grant PID2020–119298RB-I00), Meiji Pharma Spain (grant MVP 119/20), and internal funding from Instituto de Salud Carlos III.S

Expanded tracking of a Beijing Mycobacterium tuberculosis strain involved in an outbreak in France

14 páginas, 3 figuras, 1 tablaAdvanced epidemiological surveillance supported on genomic epidemiology were necessary to fully describe a Mycobacterium tuberculosis Beijing strain (ARA, Auvergne-Rhône-Alpes region) outbreak in France. The index case was a migrant from Cape Verde with a two-year history of tuberculosis, high bacillary load, and frequent trips within France and to Portugal. We designed an ARA-specific PCR to complete the tracking of this outbreak strain. The ARA-specific PCR was applied on 160 Beijing isolates from independent cases from the Auvergne-Rhône-Alpes region and on 25 cases from Cape Verde migrants in the Île-de-France region. No more cases were found, indicating that the previous surveillance had been exhaustive enough to capture the whole dimension of the outbreak in France. Next, we performed a cross-border surveillance, applying the PCR on 38 Beijing isolates in Portuthe gal. In all four cases (all migrants from Cape Verde) the ARA strain was identified. Whole genome sequences analysis of all ARA isolates representatives indicated a diversification of the strain into two variants present one in France and one in PortugalThis work was supported by ERANet-LAC [ELAC2015/T08-0664] and Instituto de Salud Carlos III [AC16/00057, FIS15/01554, FIS13/ 01207, CP15/00075, PI16/01449, 1PI19/00331] and cofounded by European Regional Development Funds from the European Commission: “A way of making Europe”. Miguel Servet Contract CP15/00075 and CPII20/00001) to LPL. JP [CEECIND/00394/2017] is supported by FCT through Estímulo Individual ao Emprego Cientifico.Peer reviewe

Prognostic implications of comorbidity patterns in critically ill COVID-19 patients: A multicenter, observational study

Background The clinical heterogeneity of COVID-19 suggests the existence of different phenotypes with prognostic implications. We aimed to analyze comorbidity patterns in critically ill COVID-19 patients and assess their impact on in-hospital outcomes, response to treatment and sequelae. Methods Multicenter prospective/retrospective observational study in intensive care units of 55 Spanish hospitals. 5866 PCR-confirmed COVID-19 patients had comorbidities recorded at hospital admission; clinical and biological parameters, in-hospital procedures and complications throughout the stay; and, clinical complications, persistent symptoms and sequelae at 3 and 6 months. Findings Latent class analysis identified 3 phenotypes using training and test subcohorts: low-morbidity (n=3385; 58%), younger and with few comorbidities; high-morbidity (n=2074; 35%), with high comorbid burden; and renal-morbidity (n=407; 7%), with chronic kidney disease (CKD), high comorbidity burden and the worst oxygenation profile. Renal-morbidity and high-morbidity had more in-hospital complications and higher mortality risk than low-morbidity (adjusted HR (95% CI): 1.57 (1.34-1.84) and 1.16 (1.05-1.28), respectively). Corticosteroids, but not tocilizumab, were associated with lower mortality risk (HR (95% CI) 0.76 (0.63-0.93)), especially in renal-morbidity and high-morbidity. Renal-morbidity and high-morbidity showed the worst lung function throughout the follow-up, with renal-morbidity having the highest risk of infectious complications (6%), emergency visits (29%) or hospital readmissions (14%) at 6 months (p<0.01). Interpretation Comorbidity-based phenotypes were identified and associated with different expression of in-hospital complications, mortality, treatment response, and sequelae, with CKD playing a major role. This could help clinicians in day-to-day decision making including the management of post-discharge COVID-19 sequelae. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd

The evolution of the ventilatory ratio is a prognostic factor in mechanically ventilated COVID-19 ARDS patients

Background: Mortality due to COVID-19 is high, especially in patients requiring mechanical ventilation. The purpose of the study is to investigate associations between mortality and variables measured during the first three days of mechanical ventilation in patients with COVID-19 intubated at ICU admission. Methods: Multicenter, observational, cohort study includes consecutive patients with COVID-19 admitted to 44 Spanish ICUs between February 25 and July 31, 2020, who required intubation at ICU admission and mechanical ventilation for more than three days. We collected demographic and clinical data prior to admission; information about clinical evolution at days 1 and 3 of mechanical ventilation; and outcomes. Results: Of the 2,095 patients with COVID-19 admitted to the ICU, 1,118 (53.3%) were intubated at day 1 and remained under mechanical ventilation at day three. From days 1 to 3, PaO2/FiO2 increased from 115.6 [80.0-171.2] to 180.0 [135.4-227.9] mmHg and the ventilatory ratio from 1.73 [1.33-2.25] to 1.96 [1.61-2.40]. In-hospital mortality was 38.7%. A higher increase between ICU admission and day 3 in the ventilatory ratio (OR 1.04 [CI 1.01-1.07], p = 0.030) and creatinine levels (OR 1.05 [CI 1.01-1.09], p = 0.005) and a lower increase in platelet counts (OR 0.96 [CI 0.93-1.00], p = 0.037) were independently associated with a higher risk of death. No association between mortality and the PaO2/FiO2 variation was observed (OR 0.99 [CI 0.95 to 1.02], p = 0.47). Conclusions: Higher ventilatory ratio and its increase at day 3 is associated with mortality in patients with COVID-19 receiving mechanical ventilation at ICU admission. No association was found in the PaO2/FiO2 variation

Clustering COVID-19 ARDS patients through the first days of ICU admission. An analysis of the CIBERESUCICOVID Cohort

Background Acute respiratory distress syndrome (ARDS) can be classified into sub-phenotypes according to different inflammatory/clinical status. Prognostic enrichment was achieved by grouping patients into hypoinflammatory or hyperinflammatory sub-phenotypes, even though the time of analysis may change the classification according to treatment response or disease evolution. We aimed to evaluate when patients can be clustered in more than 1 group, and how they may change the clustering of patients using data of baseline or day 3, and the prognosis of patients according to their evolution by changing or not the cluster.Methods Multicenter, observational prospective, and retrospective study of patients admitted due to ARDS related to COVID-19 infection in Spain. Patients were grouped according to a clustering mixed-type data algorithm (k-prototypes) using continuous and categorical readily available variables at baseline and day 3.Results Of 6205 patients, 3743 (60%) were included in the study. According to silhouette analysis, patients were grouped in two clusters. At baseline, 1402 (37%) patients were included in cluster 1 and 2341(63%) in cluster 2. On day 3, 1557(42%) patients were included in cluster 1 and 2086 (57%) in cluster 2. The patients included in cluster 2 were older and more frequently hypertensive and had a higher prevalence of shock, organ dysfunction, inflammatory biomarkers, and worst respiratory indexes at both time points. The 90-day mortality was higher in cluster 2 at both clustering processes (43.8% [n = 1025] versus 27.3% [n = 383] at baseline, and 49% [n = 1023] versus 20.6% [n = 321] on day 3). Four hundred and fifty-eight (33%) patients clustered in the first group were clustered in the second group on day 3. In contrast, 638 (27%) patients clustered in the second group were clustered in the first group on day 3.Conclusions During the first days, patients can be clustered into two groups and the process of clustering patients may change as they continue to evolve. This means that despite a vast majority of patients remaining in the same cluster, a minority reaching 33% of patients analyzed may be re-categorized into different clusters based on their progress. Such changes can significantly impact their prognosis

Modeling misretrieval and feature substitution in agreement attraction: A computational evaluation

This project contains the data, analysis code, and materials for the above-named pape