Polyphenon E enhances the antitumor immune response in neuroblastoma by inactivating myeloid suppressor cells

This is the author's accepted manuscript. The final published article is available from the link below. Note: In this manuscript as well as in the original published version of this article the word "Polyphenon" was incorrectly spelled in the title as "Polyphenol."Purpose: Neuroblastoma is a rare childhood cancer whose high risk, metastatic form has a dismal outcome in spite of aggressive therapeutic interventions. The toxicity of drug treatments is a major problem in this pediatric setting. In this study, we investigated whether Polyphenon E, a clinical grade mixture of green tea catechins under evaluation in multiple clinical cancer trials run by the National Cancer Institute (Bethesda, MD), has anticancer activity in mouse models of neuroblastoma. Experimental Design: We used three neuroblastoma models: (i) transgenic TH-MYCN mouse developing spontaneous neuroblastomas; (ii) nonobese diabetic/severe combined immunodeficient (NOD/SCID) mice xenotransplanted with human SHSY5Y cells; and (iii) A/J mice transplanted with syngeneic Neuro 2A cells. Mice were randomized in control and Polyphenon E–drinking groups. Blood from patients with neuroblastoma and normal controls was used to assess the phenotype and function of myeloid cells. Results: Polyphenon E reduced the number of tumor-infiltrating myeloid cells, and inhibited the development of spontaneous neuroblastomas in TH-MYCN transgenic mice. In therapeutic models of neuroblastoma in A/J, but not in immunodeficient NOD/SCID mice, Polyphenon E inhibited tumor growth by acting on myeloid-derived suppressor cells (MDSC) and CD8 T cells. In vitro, Polyphenon E impaired the development and motility of MDSCs and promoted differentiation to more neutrophilic forms through the 67 kDa laminin receptor signaling and induction of granulocyte colony-stimulating factor. The proliferation of T cells infiltrating a patient metastasis was reactivated by Polyphenon E. Conclusions: These findings suggest that the neuroblastoma-promoting activity of MDSCs can be manipulated pharmacologically in vivo and that green tea catechins operate, at least in part, through this mechanism.SPARKS, Research in Childhood Cancer, the CGD Research Trust, and the Wellcome Trust

Selection of the scaling solution in a cluster coalescence model

The scaling properties of the cluster size distribution of a system of diffusing clusters is studied in terms of a simple kinetic mean field model. It is shown that a one parameter family of mathematically valid scaling solutions exists. Despite this, the kinetics reaches a unique scaling solution independent of initial conditions. This selected scaling solution is marginally physical; i.e., it is the borderline solution between the unphysical and physical branches of the family of solutions.Comment: 4 pages, 5 figure

Photocatalytic Dehydroformylation of Benzyl Alcohols to Arenes

In the last decades, many C−C bond-forming reactions have been developed, whereas less attention has been paid to the design of strategies involving C−C bond cleavage. We report a photocatalytic dehydroformylation sequence for the conversion of benzyl alcohols to arenes in a one-pot two-step process. Herein, the initial dehydrogenation of the benzyl alcohols to the corresponding benzaldehydes is combined with an additional decarbonylation step yielding arenes. As a result, a broad range of benzyl alcohols can be easily transformed in short times under mild photocatalytic conditions. The conducted mechanistic studies indicate that our cooperative hydrogen atom transfer (HAT)-cobalt system proceeds through the formation of α-alkoxy- and acyl radicals as key intermediates, involving concomitant syngas (CO+H2) generation

The profile of a decaying crystalline cone

The decay of a crystalline cone below the roughening transition is studied. We consider local mass transport through surface diffusion, focusing on the two cases of diffusion limited and attachment-detachment limited step kinetics. In both cases, we describe the decay kinetics in terms of step flow models. Numerical simulations of the models indicate that in the attachment-detachment limited case the system undergoes a step bunching instability if the repulsive interactions between steps are weak. Such an instability does not occur in the diffusion limited case. In stable cases the height profile, h(r,t), is flat at radii r<R(t)\sim t^{1/4}. Outside this flat region the height profile obeys the scaling scenario \partial h/\partial r = {\cal F}(r t^{-1/4}). A scaling ansatz for the time-dependent profile of the cone yields analytical values for the scaling exponents and a differential equation for the scaling function. In the long time limit this equation provides an exact description of the discrete step dynamics. It admits a family of solutions and the mechanism responsible for the selection of a unique scaling function is discussed in detail. Finally we generalize the model and consider permeable steps by allowing direct adatom hops between neighboring terraces. We argue that step permeability does not change the scaling behavior of the system, and its only effect is a renormalization of some of the parameters.Comment: 25 pages, 18 postscript figure

Simulating Ising Spin Glasses on a Quantum Computer

A linear-time algorithm is presented for the construction of the Gibbs distribution of configurations in the Ising model, on a quantum computer. The algorithm is designed so that each run provides one configuration with a quantum probability equal to the corresponding thermodynamic weight. The partition function is thus approximated efficiently. The algorithm neither suffers from critical slowing down, nor gets stuck in local minima. The algorithm can be A linear-time algorithm is presented for the construction of the Gibbs distribution of configurations in the Ising model, on a quantum computer. The algorithm is designed so that each run provides one configuration with a quantum probability equal to the corresponding thermodynamic weight. The partition function is thus approximated efficiently. The algorithm neither suffers from critical slowing down, nor gets stuck in local minima. The algorithm can be applied in any dimension, to a class of spin-glass Ising models with a finite portion of frustrated plaquettes, diluted Ising models, and models with a magnetic field. applied in any dimension, to a class of spin-glass Ising models with a finite portion of frustrated plaquettes, diluted Ising models, and models with a magnetic field.Comment: 24 pages, 3 epsf figures, replaced with published and significantly revised version. More info available at http://www.fh.huji.ac.il/~dani/ and http://www.fiz.huji.ac.il/staff/acc/faculty/biha

Nonequilibrium dynamics of random field Ising spin chains: exact results via real space RG

Non-equilibrium dynamics of classical random Ising spin chains are studied using asymptotically exact real space renormalization group. Specifically the random field Ising model with and without an applied field (and the Ising spin glass (SG) in a field), in the universal regime of a large Imry Ma length so that coarsening of domains after a quench occurs over large scales. Two types of domain walls diffuse in opposite Sinai random potentials and mutually annihilate. The domain walls converge rapidly to a set of system-specific time-dependent positions {\it independent of the initial conditions}. We obtain the time dependent energy, magnetization and domain size distribution (statistically independent). The equilibrium limits agree with known exact results. We obtain exact scaling forms for two-point equal time correlation and two-time autocorrelations. We also compute the persistence properties of a single spin, of local magnetization, and of domains. The analogous quantities for the spin glass are obtained. We compute the two-point two-time correlation which can be measured by experiments on spin-glass like systems. Thermal fluctuations are found to be dominated by rare events; all moments of truncated correlations are computed. The response to a small field applied after waiting time $t_w$, as measured in aging experiments, and the fluctuation-dissipation ratio $X(t,t_w)$ are computed. For $(t-t_w) \sim t_w^{\hat{\alpha}}$, $\hat{\alpha} <1$, it equals its equilibrium value X=1, though time translational invariance fails. It exhibits for $t-t_w \sim t_w$ aging regime with non-trivial $X=X(t/t_w) \neq 1$, different from mean field.Comment: 55 pages, 9 figures, revte

Avelumab in paediatric patients with refractory or relapsed solid tumours: dose-escalation results from an open-label, single-arm, phase 1/2 trial

Background: We report dose-escalation results from an open-label, phase 1/2 trial evaluating avelumab (anti-PD-L1) in paediatric patients with refractory/relapsed solid tumours. Methods: In phase 1, patients aged \u3c 18 years with solid (including central nervous system [CNS]) tumours for which standard therapy did not exist or had failed were enrolled in sequential cohorts of 3–6 patients. Patients received avelumab 10 or 20 mg/kg intravenously every 2 weeks. Primary endpoints were dose-limiting toxicities (DLTs) and grade ≥ 3 treatment-emergent adverse events (AEs). Results: At data cut-off (27 July 2021), 21 patients aged 3–17 years had received avelumab 10 mg/kg (n = 6) or 20 mg/kg (n = 15). One patient had three events that were classified as a DLT (fatigue with hemiparesis and muscular weakness associated with pseudoprogression; 20 mg/kg cohort). Grade ≥ 3 AEs occurred in five (83%) and 11 (73%) patients in the 10 and 20 mg/kg cohorts, respectively, and were treatment-related in one patient (7%; grade 3 [DLT]) in the 20 mg/kg cohort. Avelumab exposure in paediatric patients receiving 20 mg/kg dosing, but not 10 mg/kg, was comparable or higher compared with approved adult dosing (10 mg/kg or 800 mg flat dose). No objective responses were observed. Four patients with CNS tumours (20 mg/kg cohort) achieved stable disease, which was ongoing in two patients with astrocytoma at cut-off (for 24.7 and 30.3 months). Conclusion: In paediatric patients with refractory/relapsed solid tumours, avelumab monotherapy showed a safety profile consistent with previous adult studies, but clinical benefits were limited

PeRL:A circum-Arctic Permafrost Region Pond and Lake database

Ponds and lakes are abundant in Arctic permafrost lowlands. They play an important role in Arctic wetland ecosystems by regulating carbon, water, and energy fluxes and providing freshwater habitats. However, ponds, i.e., waterbodies with surface areas smaller than 1. 0 × 104ĝ€m2, have not been inventoried on global and regional scales. The Permafrost Region Pond and Lake (PeRL) database presents the results of a circum-Arctic effort to map ponds and lakes from modern (2002-2013) high-resolution aerial and satellite imagery with a resolution of 5ĝ€m or better. The database also includes historical imagery from 1948 to 1965 with a resolution of 6ĝ€m or better. PeRL includes 69 maps covering a wide range of environmental conditions from tundra to boreal regions and from continuous to discontinuous permafrost zones. Waterbody maps are linked to regional permafrost landscape maps which provide information on permafrost extent, ground ice volume, geology, and lithology. This paper describes waterbody classification and accuracy, and presents statistics of waterbody distribution for each site. Maps of permafrost landscapes in Alaska, Canada, and Russia are used to extrapolate waterbody statistics from the site level to regional landscape units. PeRL presents pond and lake estimates for a total area of 1. 4 × 106ĝ€km2 across the Arctic, about 17ĝ€% of the Arctic lowland ( &lt; ĝ€300ĝ€mĝ€a.s.l.) land surface area. PeRL waterbodies with sizes of 1. 0 × 106ĝ€m2 down to 1. 0 × 102ĝ€m2 contributed up to 21ĝ€% to the total water fraction. Waterbody density ranged from 1. 0 × 10 to 9. 4 × 101ĝ€kmĝ'2. Ponds are the dominant waterbody type by number in all landscapes representing 45-99ĝ€% of the total waterbody number. The implementation of PeRL size distributions in land surface models will greatly improve the investigation and projection of surface inundation and carbon fluxes in permafrost lowlands. Waterbody maps, study area boundaries, and maps of regional permafrost landscapes including detailed metadata are available at https://doi.pangaea.de/10.1594/PANGAEA.868349

Gene prediction in metagenomic fragments: A large scale machine learning approach

<p>Abstract</p> <p>Background</p> <p>Metagenomics is an approach to the characterization of microbial genomes via the direct isolation of genomic sequences from the environment without prior cultivation. The amount of metagenomic sequence data is growing fast while computational methods for metagenome analysis are still in their infancy. In contrast to genomic sequences of single species, which can usually be assembled and analyzed by many available methods, a large proportion of metagenome data remains as unassembled anonymous sequencing reads. One of the aims of all metagenomic sequencing projects is the identification of novel genes. Short length, for example, Sanger sequencing yields on average 700 bp fragments, and unknown phylogenetic origin of most fragments require approaches to gene prediction that are different from the currently available methods for genomes of single species. In particular, the large size of metagenomic samples requires fast and accurate methods with small numbers of false positive predictions.</p> <p>Results</p> <p>We introduce a novel gene prediction algorithm for metagenomic fragments based on a two-stage machine learning approach. In the first stage, we use linear discriminants for monocodon usage, dicodon usage and translation initiation sites to extract features from DNA sequences. In the second stage, an artificial neural network combines these features with open reading frame length and fragment GC-content to compute the probability that this open reading frame encodes a protein. This probability is used for the classification and scoring of gene candidates. With large scale training, our method provides fast single fragment predictions with good sensitivity and specificity on artificially fragmented genomic DNA. Additionally, this method is able to predict translation initiation sites accurately and distinguishes complete from incomplete genes with high reliability.</p> <p>Conclusion</p> <p>Large scale machine learning methods are well-suited for gene prediction in metagenomic DNA fragments. In particular, the combination of linear discriminants and neural networks is promising and should be considered for integration into metagenomic analysis pipelines. The data sets can be downloaded from the URL provided (see Availability and requirements section).</p

Multimodel assessment of the factors driving stratospheric ozone evolution over the 21st century

The evolution of stratospheric ozone from 1960 to 2100 is examined in simulations from 14 chemistry‐climate models, driven by prescribed levels of halogens and greenhouse gases. There is general agreement among the models that total column ozone reached a minimum around year 2000 at all latitudes, projected to be followed by an increase over the first half of the 21st century. In the second half of the 21st century, ozone is projected to continue increasing, level off, or even decrease depending on the latitude. Separation into partial columns above and below 20 hPa reveals that these latitudinal differences are almost completely caused by differences in the model projections of ozone in the lower stratosphere. At all latitudes, upper stratospheric ozone increases throughout the 21st century and is projected to return to 1960 levels well before the end of the century, although there is a spread among models in the dates that ozone returns to specific historical values. We find decreasing halogens and declining upper atmospheric temperatures, driven by increasing greenhouse gases, contribute almost equally to increases in upper stratospheric ozone. In the tropical lower stratosphere, an increase in upwelling causes a steady decrease in ozone through the 21st century, and total column ozone does not return to 1960 levels in most of the models. In contrast, lower stratospheric and total column ozone in middle and high latitudes increases during the 21st century, returning to 1960 levels well before the end of the century in most models