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Abstract Deployment of ultracold atom interferometers (AI) into space will capitalize on quantum advantages and the extended freefall of persistent microgravity to provide high-precision measurement capabilities for gravitational, Earth, and planetary sciences, and to enable searches for subtle forces signifying physics beyond General Relativity and the Standard Model. NASA’s Cold Atom Lab (CAL) operates onboard the International Space Station as a multi-user facility for fundamental studies of ultracold atoms and to mature space-based quantum technologies. We report on pathfinding experiments utilizing ultracold 87Rb atoms in the CAL AI. A three-pulse Mach–Zehnder interferometer was studied to understand the influence of ISS vibrations. Additionally, Ramsey shear-wave interferometry was used to manifest interference patterns in a single run that were observable for over 150 ms free-expansion time. Finally, the CAL AI was used to remotely measure the Bragg laser photon recoil as a demonstration of the first quantum sensor using matter-wave interferometry in space.

We describe an approach to optically trapping small, chemically stable molecules at cryogenic temperatures by buffer-gas loading a deep optical dipole trap. The ∼10K trap depth will be produced by a tightly focused, 1064-nm cavity capable of reaching intensities of hundreds of GW/cm^{2}. Molecules will be directly buffer-gas loaded into the trap using a helium buffer gas at 1.5K. The very far-off-resonant, quasielectrostatic trapping mechanism is insensitive to a molecule's internal state, energy level structure, and its electric and magnetic dipole moment. Here, we theoretically investigate the trapping and loading dynamics, as well as the heating and loss rates, and conclude that 10^{4}–10^{6} molecules are likely to be trapped. Our trap would open new possibilities in molecular spectroscopy, studies of cold chemical reactions, and precision measurement, amongst other fields of physics.

Introduction: Acute kidney injury (AKI) is an important complication in COVID-19, but its precise etiology has not fully been elucidated. Insights into AKI mechanisms may be provided by analyzing the temporal associations of clinical parameters reflecting disease processes and AKI development. Methods: We performed an observational cohort study of 223 consecutive COVID-19 patients treated at 3 sites of a tertiary care referral center to describe the evolvement of severe AKI (Kidney Disease: Improving Global Outcomes stage 3) and identify conditions promoting its development. Descriptive statistics and explanatory multivariable Cox regression modeling with clinical parameters as time-varying covariates were used to identify risk factors of severe AKI. Results: Severe AKI developed in 70 of 223 patients (31%) with COVID-19, of which 95.7% required kidney replacement therapy. Patients with severe AKI were older, predominantly male, had more comorbidities, and displayed excess mortality. Severe AKI occurred exclusively in intensive care unit patients, and 97.3% of the patients developing severe AKI had respiratory failure. Mechanical ventilation, vasopressor therapy, and inflammatory markers (serum procalcitonin levels and leucocyte count) were independent time-varying risk factors of severe AKI. Increasing inflammatory markers displayed a close temporal association with the development of severe AKI. Sensitivity analysis on risk factors of AKI stage 2 and 3 combined confirmed these findings. Conclusion: Severe AKI in COVID-19 was tightly coupled with critical illness and systemic inflammation and was not observed in milder disease courses. These findings suggest that traditional systemic AKI mechanisms rather than kidney-specific processes contribute to severe AKI in COVID-19.

Global healthcare systems are challenged by the COVID-19 pandemic. There is a need to optimize allocation of treatment and resources in intensive care, as clinically established risk assessments such as SOFA and APACHE II scores show only limited performance for predicting the survival of severely ill COVID-19 patients. Additional tools are also needed to monitor treatment, including experimental therapies in clinical trials. Comprehensively capturing human physiology, we speculated that proteomics in combination with new data-driven analysis strategies could produce a new generation of prognostic discriminators. We studied two independent cohorts of patients with severe COVID-19 who required intensive care and invasive mechanical ventilation. SOFA score, Charlson comorbidity index, and APACHE II score showed limited performance in predicting the COVID-19 outcome. Instead, the quantification of 321 plasma protein groups at 349 timepoints in 50 critically ill patients receiving invasive mechanical ventilation revealed 14 proteins that showed trajectories different between survivors and non-survivors. A predictor trained on proteomic measurements obtained at the first time point at maximum treatment level (i.e. WHO grade 7), which was weeks before the outcome, achieved accurate classification of survivors (AUROC 0.81). We tested the established predictor on an independent validation cohort (AUROC 1.0). The majority of proteins with high relevance in the prediction model belong to the coagulation system and complement cascade. Our study demonstrates that plasma proteomics can give rise to prognostic predictors substantially outperforming current prognostic markers in intensive care.

Since SARS-CoV-2 emerged in December 2019 in Wuhan, the resulting pandemic has paralyzed the economic and cultural life of the world. Variants of concern (VOC) strongly increase pressure on public health systems. Rapid, easy-to-use, and cost-effective assays are essential to manage the pandemic. Here we present a bioinformatical approach for the fast and efficient design of two innovative serological Particle Enhanced Turbidimetric Immunoassays (PETIA) to quantify the SARS-CoV-2 immunoresponse. To confirm bioinformatical assumptions, an S-RBD- and a Nucleocapsid-based PETIA were produced. Sensitivity and specificity were compared for 95 patient samples using a BioMajesty™ fully automated analyzer. The S-RBD-based PETIA showed necessary specificity (98%) over the N protein-based PETIA (21%). Further, the reactivity and cross-reactivity of the RBD-based PETIA towards variant-derived antibodies of SARS-CoV-2 were assessed by a quenching inhibition test. The inhibition kinetics of the S-RBD variants Alpha, Beta, Delta, Gamma, Kappa, and Omicron were evaluated. In summary, we showed that specific and robust PETIA immunoassays can be rapidly designed and developed. The quantification of the SARS-CoV-2-related immunoresponse of variants (Alpha to Kappa) is possible using specific RBD assays. In contrast, Omicron revealed lower cross-reactivity (approx. 50%). To ensure the quantification of the Omicron variant, modified immunoassays appear to be necessary.

Background: In face of the Coronavirus Disease (COVID)-19 pandemic, best practice for mechanical ventilation in COVID-19 associated Acute Respiratory Distress Syndrome (ARDS) is intensely debated. Specifically, the rationale for high positive end-expiratory pressure (PEEP) and prone positioning in early COVID-19 ARDS has been questioned. Methods: The first 23 consecutive patients with COVID-19 associated respiratory failure transferred to a single ICU were assessed. Eight were excluded: five were not invasively ventilated and three received veno-venous ECMO support. The remaining 15 were assessed over the first 15 days of mechanical ventilation. Best PEEP was defined by maximal oxygenation and was determined by structured decremental PEEP trials comprising the monitoring of oxygenation, airway pressures and trans-pulmonary pressures. In nine patients the impact of prone positioning on oxygenation was investigated. Additionally, the effects of high PEEP and prone positioning on pulmonary opacities in serial chest x-rays were determined by applying a semiquantitative scoring-system. This investigation is part of the prospective observational PA-COVID-19 study. Findings: Patients responded to initiation of invasive high PEEP ventilation with markedly improved oxygenation, which was accompanied by reduced pulmonary opacities within 6 h of mechanical ventilation. Decremental PEEP trials confirmed the need for high PEEP (17.9 (SD ± 3.9) mbar) for optimal oxygenation, while driving pressures remained low. Prone positioning substantially increased oxygenation (p

Pneumonia is one of the leading causes of death worldwide. The course of the disease is often highly dynamic with unforeseen critical deterioration within hours in a relevant proportion of patients. Besides antibiotic treatment, novel adjunctive therapies are under development. Their additive value needs to be explored in preclinical and clinical studies and corresponding therapy schedules require optimization prior to introduction into clinical practice. Biomathematical modeling of the underlying disease and therapy processes might be a useful aid to support these processes. We here propose a biomathematical model of murine immune response during infection with Streptococcus pneumoniae aiming at predicting the outcome of different treatment schedules. The model consists of a number of non-linear ordinary differential equations describing the dynamics and interactions of the pulmonal pneumococcal population and relevant cells of the innate immune response, namely alveolar- and inflammatory macrophages and neutrophils. The cytokines IL-6 and IL-10 and the chemokines CCL2, CXCL1 and CXCL5 are considered as major mediators of the immune response. We also model the invasion of peripheral blood monocytes, their differentiation into macrophages and bacterial penetration through the epithelial barrier causing blood stream infections. We impose therapy effects on this system by modelling antibiotic therapy and treatment with the novel C5a-inactivator NOX-D19. All equations are derived by translating known biological mechanisms into equations and assuming appropriate response kinetics. Unknown model parameters were determined by fitting the predictions of the model to time series data derived from mice experiments with close-meshed time series of state parameters. Parameter fittings resulted in a good agreement of model and data for the experimental scenarios. The model can be used to predict the performance of alternative schedules of combined antibiotic and NOX-D19 treatment. We conclude that we established a comprehensive biomathematical model of pneumococcal lung infection, immune response and barrier function in mice allowing simulations of new treatment schedules. We aim to validate the model on the basis of further experimental data. We also plan the inclusion of further novel therapy principles and the translation of the model to the human situation in the near future.

If gravitational perturbations are quantized into gravitons in analogy with the electromagnetic field and photons, the resulting graviton interactions should lead to an entangling interaction between massive objects. We suggest a test of this prediction. To do this, we introduce the concept of interactive quantum information sensing. This novel sensing protocol is tailored to provable verification of weak dynamical entanglement generation between a pair of systems. We show that this protocol is highly robust to typical thermal noise sources. Moreover, the sensitivity can be increased both using an initial thermal state and/or an initial phase of entangling via a nongravitational interaction. We outline a concrete implementation testing the ability of the gravitational field to generate entanglement between an atomic interferometer and a mechanical oscillator. Preliminary numerical estimates suggest that near-term devices could feasibly be used to perform the experiment.

Dysregulation of the innate immune system drives lung injury and its systemic sequelae due to breakdown of vascular barrier function, harmful hyperinflammation and microcirculatory failure, which contribute to the unfavourable outcome of patients with severe pneumonia. A variety of promising therapeutic targets have been identified and numerous innovative therapeutic approaches demonstrated to improve lung injury in experimental preclinical studies. However, at present specific preventive or curative strategies for the treatment of lung failure in pneumonia in addition to antibiotics are still missing. The aim of this mini-review is to give a short overview of some, but not all, adjuvant therapeutic strategies for pneumonia and its most important complications, sepsis and acute respiratory distress syndrome, and briefly discuss future perspectives.

Self-extracellular RNA (eRNA), released from stressed or injured cells upon various pathological situations such as ischemia-reperfusion-injury, has been shown to act as an alarmin by inducing procoagulatory and proinflammatory responses. In particular, M1-polarization of macrophages by eRNA resulted in the expression and release of a variety of cytokines, including tumor necrosis factor (TNF)-α or interleukin-6 (IL-6). The present study now investigates in which way self-eRNA may influence the response of macrophages towards various Toll-like receptor (TLR)-agonists. Isolated agonists of TLR2 (Pam2CSK4), TLR3 (PolyIC), TLR4 (LPS), or TLR7 (R848) induced the release of TNF-α in a concentration-dependent manner in murine macrophages, differentiated from bone marrow-derived stem cells by mouse colony stimulating factor. Here, the presence of eRNA shifted the dose-response curve for Pam2CSK4 (Pam) considerably to the left, indicating that eRNA synergistically enhanced the cytokine liberation from macrophages even at very low Pam-levels. The synergistic activation of TLR2 by eRNA/Pam was duplicated by other TLR2-agonists such as FSL-1 or Pam3CSK4. In contrast, for TLR4-agonists such as LPS a synergistic effect of eRNA was much weaker, and was not existent for TLR3-, or TLR7-agonists. The synergistic eRNA/Pam action was dependent on the NFκB-signaling pathway as well as on p38MAP- and MEK1/ERK-kinases and was prevented by predigestion of eRNA with RNase1 or by antibodies against TLR2. Thus, the presence of self-eRNA as alarming molecule sensitizes innate immune responses towards pathogen-associated molecular patterns (PAMPs) in a synergistic way and may thereby contribute to the differentiated outcome of inflammatory responses.

We propose and demonstrate a test of Lorentz symmetry based on new, compact, and reliable quartz oscillator technology. Violations of Lorentz invariance in the matter and photon sector of the standard model extension generate anisotropies in particles’ inertial masses and the elastic constants of solids, giving rise to measurable anisotropies in the resonance frequencies of acoustic modes in solids. A first realization of such a “phonon-sector” test of Lorentz symmetry using room-temperature stress-compensated-cut crystals yields 120 h of data at a frequency resolution of 2.4×10^{−15} and a limit of c[over ˜]_{Q}^{n}=(−1.8±2.2)×10^{−14} GeV on the most weakly constrained neutron-sector c coefficient of the standard model extension. Future experiments with cryogenic oscillators promise significant improvements in accuracy, opening up the potential for improved limits on Lorentz violation in the neutron, proton, electron, and photon sector.

We describe the Quantum Test of the Equivalence principle and Space Time (QTEST), a concept for an atom interferometry mission on the International Space Station (ISS). The primary science objective of the mission is a test of Einstein’s equivalence principle with two rubidium isotope gases at a precision of better than 10 ^−15 , a 100-fold improvement over the current limit on equivalence principle violations, and over 1,000,000 fold improvement over similar quantum experiments demonstrated in laboratories. Distinct from the classical tests is the use of quantum wave packets and their expected large spatial separation in the QTEST experiment. This dual species atom interferometer experiment will also be sensitive to time-dependent equivalence principle violations that would be signatures for ultralight dark-matter particles. In addition, QTEST will be able to perform photon recoil measurements to better than 10 ^−11 precision. This improves upon terrestrial experiments by a factor of 100, enabling an accurate test of the standard model of particle physics and contributing to mass measurement, in the proposed new international system of units (SI), with significantly improved precision. The predicted high measurement precision of QTEST comes from the microgravity environment on ISS, offering extended free fall times in a well-controlled environment. QTEST plans to use high-flux, dual-species atom sources, and advanced cooling schemes, for N > 10 ^6 non-condensed atoms of each species at temperatures below 1 nK. Suppression of systematic errors by use of symmetric interferometer configurations and rejection of common-mode errors drives the QTEST design. It uses Bragg interferometry with a single laser beam at the ‘magic’ wavelength, where the two isotopes have the same polarizability, for mitigating sensitivities to vibrations and laser noise, imaging detection for correcting cloud initial conditions and maintaining contrast, modulation of the atomic hyperfine states for reduced sensitivity to magnetic field gradients, two source-regions for simultaneous time reversal measurements and redundancy, and modulation of the gravity vector using a rotating platform to reduce otherwise difficult systematics to below 10 ^−16 .