•Thyme essential oil could suppress growth and aflatoxin B1 production in A. flavus.•Thyme essential oil induced apoptotic-like cell death on A. flavus.•Gene laeA of fungal secondary metabolism was ...down-regulated by thyme essential oil.
Several approaches, including the detection of apoptotic-like cell death, aflatoxin B1 (AFB1) production and gene expression analysis, were carried out to provide insights into the antifungal and anti-aflatoxigenic effects of thyme essential oil (EO) on Aspergillus flavus. At 0.5 µL mL−1, thyme EO completely inhibited A. flavus growth. Furthermore, this antifungal activity triggered significant apoptosis, via nuclear condensation (87.5% of nuclei analyzed) and plasma membrane damage (in 100% of treated hyphae). Further analysis of AFB1 production and gene expression related to secondary metabolism (laeA) and the mechanism of virulence (lipA and meT) of A. flavus in the presence of thyme EO indicated important physiological changes related to its anti-aflatoxigenic property. These results highlight the potent antifungal abilities of thyme EO in controlling A. flavus and AFB1 production, especially the abilities that operate by exerting changes at the molecular level and inducing significant apoptotic-like cell death.
Repurposing hydroxychloroquine (HCQ) and chloroquine (CQ) as antiviral agents is a re-emerging topic with the advent of new viral epidemics.
To summarize evidence from human clinical studies for ...using HCQ or CQ as antiviral agents for any viral infection.
PubMed, EMBASE, Scopus, Web of Science for published studies without time or language restrictions; Cochrane Clinical Trial Registry and Chinese Clinical Trials Registry for trials registered after 2015; MedRxiv for preprints within the last 12 months.
Study eligibility criteria were interventional and prospective observational studies (with or without a control group). Participants were adults and children with a confirmed viral infection. Interventions included the use of CQ or HCQ as antiviral agent in one or more groups of the study. Two authors independently screened abstracts, and all authors agreed on eligible studies. A meta-analysis was planned if studies were available which were similar in terms of participants, intervention, comparator and outcomes. Nineteen studies (including two preprints) were eligible (HIV 8, HCV 2, dengue 2, chikungunya 1, COVID-19 6). Nine and ten studies assessed CQ and HCQ respectively. Benefits of either drug for viral load suppression in HIV are inconsistent. CQ is ineffective in curing dengue (high-certainty evidence) and may have little or no benefit in curing chikungunya (low-certainty evidence). The evidence for COVID-19 infection is rapidly evolving but at this stage we are unsure whether either CQ or HCQ has any benefit in clearing viraemia (very-low-certainty evidence).
Using HCQ or CQ for HIV/HCV infections is now clinically irrelevant as other effective antivirals are available for viral load suppression (HIV) and cure (HCV). There is no benefit of CQ in dengue, and the same conclusion is likely for chikungunya. More evidence is needed to confirm whether either HCQ or CQ is beneficial in COVID-19 infection.
This paper proposes a unified sparsity-aware robust recursive least-squares RLS (S-RRLS) algorithm for the identification of sparse systems under impulsive noise. The proposed algorithm generalizes ...multiple algorithms only by replacing the specified criterion of robustnessand sparsity-aware penalty. Furthermore, by jointly optimizing the forgetting factor and the sparsity penalty parameter, we develop the jointly-optimized S-RRLS (JO-S-RRLS) algorithm, which not only exhibits low misadjustment but also can track well sudden changes of a sparse system. Simulations in impulsive noise scenarios demonstrate that the proposed S-RRLS and JO-S-RRLS algorithms outperform existing techniques.
Space-time adaptive processing (STAP) algorithms with coprime arrays can provide good clutter suppression potential with low cost in airborne radar systems as compared with their uniform linear ...arrays counterparts. However, the performance of these algorithms is limited by the training samples support in practical applications. To address this issue, a robust two-stage reduced dimension (RD) sparsity-aware STAP algorithm is proposed in this work. In the first stage, an RD virtual snapshot is constructed using all spatial channels but only m adjacent Doppler channels around the target Doppler frequency to reduce the slow-time dimension of the signal. In the second stage, an RD sparse measurement modeling is formulated based on the constructed RD virtual snapshot, where the sparsity of clutter and the prior knowledge of the clutter ridge are exploited to formulate an RD overcomplete dictionary. Moreover, an orthogonal matching pursuit (OMP)-like method is proposed to recover the clutter subspace. In order to set the stopping parameter of the OMP-like method, a robust clutter rank estimation approach is developed. Compared with recently developed sparsity-aware STAP algorithms, the size of the proposed sparse representation dictionary is much smaller, resulting in low complexity. Simulation results show that the proposed algorithm is robust to prior knowledge errors and can provide good clutter suppression performance in low sample support.
This work focuses on the accuracy and stability of high-order nodal discontinuous Galerkin (DG) methods for under-resolved turbulence computations. In particular we consider the inviscid Taylor–Green ...vortex (TGV) flow to analyse the implicit large eddy simulation (iLES) capabilities of DG methods at very high Reynolds numbers. The governing equations are discretised in two ways in order to suppress aliasing errors introduced into the discrete variational forms due to the under-integration of non-linear terms. The first, more straightforward way relies on consistent/over-integration, where quadrature accuracy is improved by using a larger number of integration points, consistent with the degree of the non-linearities. The second strategy, originally applied in the high-order finite difference community, relies on a split (or skew-symmetric) form of the governing equations. Different split forms are available depending on how the variables in the non-linear terms are grouped. The desired split form is then built by averaging conservative and non-conservative forms of the governing equations, although conservativity of the DG scheme is fully preserved. A preliminary analysis based on Burgers' turbulence in one spatial dimension is conducted and shows the potential of split forms in keeping the energy of higher-order polynomial modes close to the expected levels. This indicates that the favourable dealiasing properties observed from split-form approaches in more classical schemes seem to hold for DG. The remainder of the study considers a comprehensive set of (under-resolved) computations of the inviscid TGV flow and compares the accuracy and robustness of consistent/over-integration and split form discretisations based on the local Lax–Friedrichs and Roe-type Riemann solvers. Recent works showed that relevant split forms can stabilize higher-order inviscid TGV test cases otherwise unstable even with consistent integration. Here we show that stable high-order cases achievable with both strategies have comparable accuracy, further supporting the good dealiasing properties of split form DG. The higher-order cases achieved only with split form schemes also displayed all the main features expected from consistent/over-integration. Among test cases with the same number of degrees of freedom, best solution quality is obtained with Roe-type fluxes at moderately high orders (around sixth order). Solutions obtained with very high polynomial orders displayed spurious features attributed to a sharper dissipation in wavenumber space. Accuracy differences between the two dealiasing strategies considered were, however, observed for the low-order cases, which also yielded reduced solution quality compared to high-order results.
CAR T Cell Therapy: A Versatile Living Drug De Marco, Rodrigo C; Monzo, Hector J; Ojala, Päivi M
International journal of molecular sciences,
03/2023, Volume:
24, Issue:
7
Journal Article
Peer reviewed
Open access
After seeing a dramatic increase in the development and use of immunotherapy and precision medicine over the past few decades, oncological care now embraces the start of the adoptive cell therapy ...(ACT) era. This impulse towards a new treatment paradigm has been led by chimeric antigen receptor (CAR) T cells, the only type of ACT medicinal product to be commercialized so far. Brought about by an ever-growing understanding of cellular engineering, CAR T cells are T lymphocytes genetically modified with an appropriate DNA construct, which endows them with expression of a CAR, a fusion protein between a ligand-specific recognition domain, often an antibody-like structure, and the activating signaling domain of the T cell receptor. Through this genetic enhancement, CAR T cells are engineered from a cancer patient's own lymphocytes to better target and kill their cancer cells, and the current amassed data on clinical outcomes point to a stream of bright developments in the near future. Herein, from concept design and present-day manufacturing techniques to pressing hurdles and bright discoveries around the corner, we review and thoroughly describe the state of the art in CAR T cell therapy.
In this work, we present an energy-efficient distributed learning framework using coarsely quantized signals for Internet of Things (IoT) networks. In particular, we develop a distributed ...quantization-aware recursive least-squares (DQA-RLS) algorithm that can learn parameters in an energy-efficient fashion using signals quantized with few bits while requiring a low computational cost. Moreover, we develop a bias compensation strategy to further improve the performance of the proposed DQA-RLS algorithm. We carry out a statistical analysis of the proposed DQA-RLS algorithm and derive analytical expressions for predicting the mean-square deviation. A computational complexity evaluation and a study of the power consumption of the proposed and existing techniques are then presented. Numerical results assess the DQA-RLS algorithm against existing techniques for a distributed parameter estimation task in a scenario where IoT devices operate in peer-to-peer mode.
Binary and multiple stars have long provided an effective empirical method of testing stellar formation and evolution theories. In particular, the existence of wide binary systems (separations ...>20,000 au) is particularly challenging to binary formation models as their physical separations are beyond the typical size of a collapsing cloud core (∼5000-10,000 au). We mined the recently published Gaia-DR2 catalog to identify bright comoving systems in the five-dimensional space (sky position, parallax, and proper motion). We identified 3741 comoving binary and multiple stellar candidate systems, out of which 575 have compatible radial velocities for all the members of the system. The candidate systems have separations between ∼400 and 500,000 au. We used the analysis tools of the Virtual Observatory to characterize the comoving system members and to assess their reliability. The comparison with previous comoving systems catalogs obtained from TGAS showed that these catalogs contain a large number of false systems. In addition, we were not able to confirm the ultra-wide binary population presented in these catalogs. The robustness of our methodology is demonstrated by the identification of well known comoving star clusters and by the low contamination rate for comoving binary systems with projected physical separations <50,000 au. These last constitute a reliable sample for further studies. The catalog is available online at the Spanish Virtual Observatory portal (http://svo2.cab.inta-csic.es/vocats/v2/comovingGaiaDR2/).
The effectiveness of inactivated vaccines (VE) against symptomatic and severe COVID-19 caused by omicron is unknown. We conducted a nationwide, test-negative, case-control study to estimate VE for ...homologous and heterologous (BNT162b2) booster doses in adults who received two doses of CoronaVac in Brazil in the Omicron context. Analyzing 1,386,544 matched-pairs, VE against symptomatic disease was 8.6% (95% CI, 5.6-11.5) and 56.8% (95% CI, 56.3-57.3) in the period 8-59 days after receiving a homologous and heterologous booster, respectively. During the same interval, VE against severe Covid-19 was 73.6% (95% CI, 63.9-80.7) and 86.0% (95% CI, 84.5-87.4) after receiving a homologous and heterologous booster, respectively. Waning against severe Covid-19 after 120 days was only observed after a homologous booster. Heterologous booster might be preferable to individuals with completed primary series inactivated vaccine.
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