Dispersive Approach to Semileptonic Form-Factors in Heavy-to-Light Meson Decays

We study the semileptonic decays of heavy mesons into light pseudoscalars by making use of dispersion relations. Constraints from heavy quark symmetry, chiral symmetry and perturbative QCD are implemented into a dispersive model for the form-factors. Large deviations from $B^*$-pole dominance are observed in $B\to\pi\ell\nu$. We discuss the model prediction for this mode and its possible impact on the extraction of $|V_{ub}|$.Comment: 30 pages, including 5 Postcript figure

LocTree3 prediction of localization

The prediction of protein sub-cellular localization is an important step toward elucidating protein function. For each query protein sequence, LocTree2 applies machine learning (profile kernel SVM) to predict the native sub-cellular localization in 18 classes for eukaryotes, in six for bacteria and in three for archaea. The method outputs a score that reflects the reliability of each prediction. LocTree2 has performed on par with or better than any other state-of-the-art method. Here, we report the availability of LocTree3 as a public web server. The server includes the machine learning-based LocTree2 and improves over it through the addition of homology-based inference. Assessed on sequence-unique data, LocTree3 reached an 18-state accuracy Q18 = 80 ± 3% for eukaryotes and a six-state accuracy Q6 = 89 ± 4% for bacteria. The server accepts submissions ranging from single protein sequences to entire proteomes. Response time of the unloaded server is about 90 s for a 300-residue eukaryotic protein and a few hours for an entire eukaryotic proteome not considering the generation of the alignments. For over 1000 entirely sequenced organisms, the predictions are directly available as downloads. The web server is available at http://www.rostlab.org/services/loctree3

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Magnetic frequency mixing detection of magnetic nanoparticles for immunoquantification in a microfluidic structure

International audienc

Investigation of magnetic phase transition and magnetocaloric effect of (Ni,Co)-Mn-Al melt-spun ribbons

Magnetic phase transition, magnetocaloric effect and critical parameters of Ni50-xCoxMn50-yAly (x = 5 and 10; y = 17, 18 and 19) rapidly quenched ribbons have been studied. X-ray diffraction patterns exhibit a coexistence of the L21 and 10M crystalline phases of the ribbons. Magnetization measurements show that all the samples behave as soft magnetic materials with a low coercive force less than 60 Oe. The shape of thermomagnetization curves considerably depends on Co and Al concentrations. The Curie temperature (TC) of the alloy ribbons strongly increases with increasing the Co concentration and slightly decreases with increasing the Al concentration. The Ni45Co5Mn31Al19 and Ni40Co10Mn33Al17 ribbons reveal both the positive and negative magnetocaloric effects. Under magnetic field change (ΔGH) of 13.5 kOe, the maximum magnetic entropy change (|ΔSm|max) of the Ni45Co5Mn31Al19 ribbon is about 2 and -1 J·kg−1·K−1 for negative and positive magnetocaloric effects, respectively. Basing on Arrott - Noakes and Kouvel - Fisher methods, critical parameters of the Ni45Co5Mn31Al19 ribbon were determined to be TC ≈ 290 K, β ≈ 0.58, γ ≈ 0.92 and δ ≈ 2.59. The obtained values of the critical exponents indicate that the magnetic order of the alloy ribbon is close to the mean-field model

Phase formation and magnetocaloric effect in (Pr,Nd)-Fe alloys prepared by rapidly quenched method

In this work, Pr2-xNdxFe17 (x = 0 - 2) ribbons with thickness of about 15 μm were prepared by melt-spinning method. The alloy ribbons were then annealed at different temperatures (900 - 1100°C) for various time (0.25 - 2 h). The formation of the (Pr,Nd)2Fe17 (2:17) crystalline phase in the alloys strongly depends on the Pr/Nd ratio and annealing conditions. Annealing time for the completed formation of the 2:17 phase in the rapidly quenched ribbons is greatly reduced in comparison with that of bulk alloys. Curie temperature, TC, of the alloys can be controlled in room temperature region by changing Pr/Nd ratio. Maximum magnetic entropy change (|ΔSm|max) and full width at haft the maximum peak (FWHM) of the magnetic entropy change of the alloys were respectively found to be larger than 1.5 J.kg−1K−1 and 40 K in room temperature region with magetic field change ΔH = 12 kOe

Investigation of magnetic phase transition and magnetocaloric effect of (Ni,Co)-Mn-Al melt-spun ribbons

Magnetic phase transition, magnetocaloric effect and critical parameters of Ni50-xCoxMn50-yAly (x = 5 and 10; y = 17, 18 and 19) rapidly quenched ribbons have been studied. X-ray diffraction patterns exhibit a coexistence of the L21 and 10M crystalline phases of the ribbons. Magnetization measurements show that all the samples behave as soft magnetic materials with a low coercive force less than 60 Oe. The shape of thermomagnetization curves considerably depends on Co and Al concentrations. The Curie temperature (TC) of the alloy ribbons strongly increases with increasing the Co concentration and slightly decreases with increasing the Al concentration. The Ni45Co5Mn31Al19 and Ni40Co10Mn33Al17 ribbons reveal both the positive and negative magnetocaloric effects. Under magnetic field change (ΔGH) of 13.5 kOe, the maximum magnetic entropy change (|ΔSm|max) of the Ni45Co5Mn31Al19 ribbon is about 2 and -1 J·kg−1·K−1 for negative and positive magnetocaloric effects, respectively. Basing on Arrott - Noakes and Kouvel - Fisher methods, critical parameters of the Ni45Co5Mn31Al19 ribbon were determined to be TC ≈ 290 K, β ≈ 0.58, γ ≈ 0.92 and δ ≈ 2.59. The obtained values of the critical exponents indicate that the magnetic order of the alloy ribbon is close to the mean-field model

Phase formation and magnetocaloric effect in (Pr,Nd)-Fe alloys prepared by rapidly quenched method

In this work, Pr2-xNdxFe17 (x = 0 - 2) ribbons with thickness of about 15 μm were prepared by melt-spinning method. The alloy ribbons were then annealed at different temperatures (900 - 1100°C) for various time (0.25 - 2 h). The formation of the (Pr,Nd)2Fe17 (2:17) crystalline phase in the alloys strongly depends on the Pr/Nd ratio and annealing conditions. Annealing time for the completed formation of the 2:17 phase in the rapidly quenched ribbons is greatly reduced in comparison with that of bulk alloys. Curie temperature, TC, of the alloys can be controlled in room temperature region by changing Pr/Nd ratio. Maximum magnetic entropy change (|ΔSm|max) and full width at haft the maximum peak (FWHM) of the magnetic entropy change of the alloys were respectively found to be larger than 1.5 J.kg−1K−1 and 40 K in room temperature region with magetic field change ΔH = 12 kOe