Some relations between Lagrangian models and synthetic random velocity fields

We propose an alternative interpretation of Markovian transport models based on the well-mixedness condition, in terms of the properties of a random velocity field with second order structure functions scaling linearly in the space time increments. This interpretation allows direct association of the drift and noise terms entering the model, with the geometry of the turbulent fluctuations. In particular, the well known non-uniqueness problem in the well-mixedness approach is solved in terms of the antisymmetric part of the velocity correlations; its relation with the presence of non-zero mean helicity and other geometrical properties of the flow is elucidated. The well-mixedness condition appears to be a special case of the relation between conditional velocity increments of the random field and the one-point Eulerian velocity distribution, allowing generalization of the approach to the transport of non-tracer quantities. Application to solid particle transport leads to a model satisfying, in the homogeneous isotropic turbulence case, all the conditions on the behaviour of the correlation times for the fluid velocity sampled by the particles. In particular, correlation times in the gravity and in the inertia dominated case, respectively, longer and shorter than in the passive tracer case; in the gravity dominated case, correlation times longer for velocity components along gravity, than for the perpendicular ones. The model produces, in channel flow geometry, particle deposition rates in agreement with experiments.Comment: 54 pages, 8 eps figures included; contains additional material on SO(3) and on turbulent channel flows. Few typos correcte

DeepSig: Deep learning improves signal peptide detection in proteins

Motivation: The identification of signal peptides in protein sequences is an important step toward protein localization and function characterization. Results: Here, we present DeepSig, an improved approach for signal peptide detection and cleavage-site prediction based on deep learning methods. Comparative benchmarks performed on an updated independent dataset of proteins show that DeepSig is the current best performing method, scoring better than other available state-of-the-art approaches on both signal peptide detection and precise cleavage-site identification. Availability and implementation: DeepSig is available as both standalone program and web server at https://deepsig.biocomp.unibo.it. All datasets used in this study can be obtained from the same website

Transport properties of heavy particles in high Reynolds number turbulence

The statistical properties of heavy particle trajectories in high Reynolds numbers turbulent flows are analyzed. Dimensional analysis assuming Kolmogorov scaling is compared with the result of numerical simulation using a synthetic turbulence advecting field. The non-Markovian nature of the fluid velocity statistics along the solid particle trajectories is put into evidence, and its relevance in the derivation of Lagrangian transport models is discussed.Comment: 30 pages, 11 eps figures included. To appear in Physics of Fluid

Observability of Gamma Rays from Dark Matter Neutralino Annihilations in the Milky Way Halo

Recent advances in N-body simulations of cold dark matter halos point to a substantial density enhancement near the center. This means that, e.g., the $\gamma$ ray signals from neutralino dark matter annihilations would be significantly enhanced compared to old estimates based on an isothermal sphere model with large core radius. Another important development concerns new detectors, both space- and ground-based, which will cover the window between 50 and 300 GeV where presently no cosmic $\gamma$-ray data are available. Thirdly, new calculations of the $\gamma$-ray line signal (a sharp spike of $10^{-3}$ relative width) from neutralino annihilations have revealed a hitherto neglected contribution which, for heavy higgsino-like neutralinos, gives an annihilation rate an order of magnitude larger than previously predicted. We make a detailed phenomenological study of the possible detection rates given these three pieces of new information. We show that the proposed upgrade of the Whipple telescope will make it sensitive to a region of parameter space, with substantial improvements possible with the planned new generation of Air Cherenkov Telescope Arrays. We also comment on the potential of the GLAST satellite detector. An evaluation of the continuum $\gamma$-rays produced in neutralino annihilations into the main modes is also done. It is shown that a combination of high-rate models and very peaked halo models are already severely constrained by existing data.Comment: 44 pages, LaTex, eps figures embedded with epsfig and subfigure macro

Large scale production of the active human ASCT2 (SLC1A5) transporter in Pichia pastoris--functional and kinetic asymmetry revealed in proteoliposomes.

Abstract The human glutamine/neutral amino acid transporter ASCT2 (hASCT2) was over-expressed in Pichia pastoris and purified by Ni 2 + -chelating and gel filtration chromatography. The purified protein was reconstituted in liposomes by detergent removal with a batch-wise procedure. Time dependent [ 3 H]glutamine/glutamine antiport was measured in proteoliposomes which was active only in the presence of external Na + . Internal Na + slightly stimulated the antiport. Optimal activity was found at pH 7.0. A substantial inhibition of the transport was observed by Cys, Thr, Ser, Ala, Asn and Met (≥ 70%) and by mercurials and methanethiosulfonates (≥ 80%). Heterologous antiport of [ 3 H]glutamine with other neutral amino acids was also studied. The transporter showed asymmetric specificity for amino acids: Ala, Cys, Val, Met were only inwardly transported, while Gln, Ser, Asn, and Thr were transported bi-directionally. From kinetic analysis of [ 3 H]glutamine/glutamine antiport Km values of 0.097 and 1.8 mM were measured on the external and internal sides of proteoliposomes, respectively. The Km for Na + on the external side was 32 mM. The homology structural model of the hASCT2 protein was built using the GltPh of Pyrococcus horikoshii as template. Cys395 was the only Cys residue externally exposed, thus being the potential target of SH reagents inhibition and, hence, potentially involved in the transport mechanism

Highlights From the Annual Meeting of the American Epilepsy Society 2022

With more than 6000 attendees between in-person and virtual offerings, the American Epilepsy Society Meeting 2022 in Nashville, felt as busy as in prepandemic times. An ever-growing number of physicians, scientists, and allied health professionals gathered to learn a variety of topics about epilepsy. The program was carefully tailored to meet the needs of professionals with different interests and career stages. This article summarizes the different symposia presented at the meeting. Basic science lectures addressed the primary elements of seizure generation and pathophysiology of epilepsy in different disease states. Scientists congregated to learn about anti-seizure medications, mechanisms of action, and new tools to treat epilepsy including surgery and neurostimulation. Some symposia were also dedicated to discuss epilepsy comorbidities and practical issues regarding epilepsy care. An increasing number of patient advocates discussing their stories were intertwined within scientific activities. Many smaller group sessions targeted more specific topics to encourage member participation, including Special Interest Groups, Investigator, and Skills Workshops. Special lectures included the renown Hoyer and Lombroso, an ILAE/IBE joint session, a spotlight on the impact of Dobbs v. Jackson on reproductive health in epilepsy, and a joint session with the NAEC on coding and reimbursement policies. The hot topics symposium was focused on traumatic brain injury and post-traumatic epilepsy. A balanced collaboration with the industry allowed presentations of the latest pharmaceutical and engineering advances in satellite symposia

Human schistosomiasis in the post Mass Drug Administration (MDA) era

Summary: Profound changes are occurring in the epidemiology of schistosomiasis, a neglected tropical disease caused by a chronic infection with parasitic helminths of the genus Schistosoma. Schistosomiasis currently affects 240 million people worldwide, mostly in sub-Saharan Africa. The advent and proliferation of mass drug administration (MDA) programmes using the drug praziquantel is resulting in substantial increases in the number of people, mainly children aged 6–14 years, being effectively treated, approaching the point where most people in endemic areas will receive one or more treatments during their lifetimes. Praziquantel treatment not only cures infection but also frees the host from the powerful immunomodulatory action of the parasites. The treatment simultaneously enhances exposure to key parasite antigens, accelerating the development of protective acquired immunity, which would take many years to develop naturally. At a population level, these changes constitute a substantial alteration to schistosome ecology in that the parasites are more likely to be exposed not only to praziquantel directly but also to hosts with altered immune phenotypes. Here, we consider the consequences of this for schistosome biology, immunoepidemiology, and public health. We anticipate that there could be substantial effects on chronic pathology, natural immunity, vaccine development strategies, immune disorders, and drug efficacy. This makes for a complex picture that will only become apparent over decades. We recommend careful monitoring and assessment to accompany the roll-out of MDA programmes to ensure that the considerable health benefits to populations are achieved and sustained

Basic science232. Certolizumab pegol prevents pro-inflammatory alterations in endothelial cell function

Background: Cardiovascular disease is a major comorbidity of rheumatoid arthritis (RA) and a leading cause of death. Chronic systemic inflammation involving tumour necrosis factor alpha (TNF) could contribute to endothelial activation and atherogenesis. A number of anti-TNF therapies are in current use for the treatment of RA, including certolizumab pegol (CZP), (Cimzia ®; UCB, Belgium). Anti-TNF therapy has been associated with reduced clinical cardiovascular disease risk and ameliorated vascular function in RA patients. However, the specific effects of TNF inhibitors on endothelial cell function are largely unknown. Our aim was to investigate the mechanisms underpinning CZP effects on TNF-activated human endothelial cells. Methods: Human aortic endothelial cells (HAoECs) were cultured in vitro and exposed to a) TNF alone, b) TNF plus CZP, or c) neither agent. Microarray analysis was used to examine the transcriptional profile of cells treated for 6 hrs and quantitative polymerase chain reaction (qPCR) analysed gene expression at 1, 3, 6 and 24 hrs. NF-κB localization and IκB degradation were investigated using immunocytochemistry, high content analysis and western blotting. Flow cytometry was conducted to detect microparticle release from HAoECs. Results: Transcriptional profiling revealed that while TNF alone had strong effects on endothelial gene expression, TNF and CZP in combination produced a global gene expression pattern similar to untreated control. The two most highly up-regulated genes in response to TNF treatment were adhesion molecules E-selectin and VCAM-1 (q 0.2 compared to control; p > 0.05 compared to TNF alone). The NF-κB pathway was confirmed as a downstream target of TNF-induced HAoEC activation, via nuclear translocation of NF-κB and degradation of IκB, effects which were abolished by treatment with CZP. In addition, flow cytometry detected an increased production of endothelial microparticles in TNF-activated HAoECs, which was prevented by treatment with CZP. Conclusions: We have found at a cellular level that a clinically available TNF inhibitor, CZP reduces the expression of adhesion molecule expression, and prevents TNF-induced activation of the NF-κB pathway. Furthermore, CZP prevents the production of microparticles by activated endothelial cells. This could be central to the prevention of inflammatory environments underlying these conditions and measurement of microparticles has potential as a novel prognostic marker for future cardiovascular events in this patient group. Disclosure statement: Y.A. received a research grant from UCB. I.B. received a research grant from UCB. S.H. received a research grant from UCB. All other authors have declared no conflicts of interes

Rituximab versus tocilizumab in rheumatoid arthritis: synovial biopsy-based biomarker analysis of the phase 4 r4ra randomized trial

Patients with rheumatoid arthritis (RA) receive highly targeted biologic therapies without previous knowledge of target expression levels in the diseased tissue. Approximately 40% of patients do not respond to individual biologic therapies and 5–20% are refractory to all. In a biopsy-based, precision-medicine, randomized clinical trial in RA (R4RA; n = 164), patients with low/absent synovial B cell molecular signature had a lower response to rituximab (anti-CD20 monoclonal antibody) compared with that to tocilizumab (anti-IL6R monoclonal antibody) although the exact mechanisms of response/nonresponse remain to be established. Here, in-depth histological/molecular analyses of R4RA synovial biopsies identify humoral immune response gene signatures associated with response to rituximab and tocilizumab, and a stromal/fibroblast signature in patients refractory to all medications. Post-treatment changes in synovial gene expression and cell infiltration highlighted divergent effects of rituximab and tocilizumab relating to differing response/nonresponse mechanisms. Using ten-by-tenfold nested cross-validation, we developed machine learning algorithms predictive of response to rituximab (area under the curve (AUC) = 0.74), tocilizumab (AUC = 0.68) and, notably, multidrug resistance (AUC = 0.69). This study supports the notion that disease endotypes, driven by diverse molecular pathology pathways in the diseased tissue, determine diverse clinical and treatment–response phenotypes. It also highlights the importance of integration of molecular pathology signatures into clinical algorithms to optimize the future use of existing medications and inform the development of new drugs for refractory patients