Enhanced Delivery of Rituximab Into Brain and Lymph Nodes Using Timed-Release Nanocapsules in Non-Human Primates.

Tumor metastasis into the central nervous system (CNS) and lymph nodes (LNs) is a major obstacle for effective therapies. Therapeutic monoclonal antibodies (mAb) have revolutionized tumor treatment; however, their efficacy for treating metastatic tumors-particularly, CNS and LN metastases-is poor due to inefficient penetration into the CNS and LNs following intravenous injection. We recently reported an effective delivery of mAb to the CNS by encapsulating the anti-CD20 mAb rituximab (RTX) within a thin shell of polymer that contains the analogs of choline and acetylcholine receptors. This encapsulated RTX, denoted as n-RTX, eliminated lymphoma cells systemically in a xenografted humanized mouse model using an immunodeficient mouse as a recipient of human hematopoietic stem/progenitor cells and fetal thymus more effectively than native RTX; importantly, n-RTX showed notable anti-tumor effect on CNS metastases which is unable to show by native RTX. As an important step toward future clinical translation of this technology, we further analyzed the properties of n-RTX in immunocompetent animals, rats, and non-human primates (NHPs). Our results show that a single intravenous injection of n-RTX resulted in 10-fold greater levels in the CNS and 2-3-fold greater levels in the LNs of RTX, respectively, than the injection of native RTX in both rats and NHPs. In addition, we demonstrate the enhanced delivery and efficient B-cell depletion in lymphoid organs of NHPs with n-RTX. Moreover, detailed hematological analysis and liver enzyme activity tests indicate n-RTX treatment is safe in NHPs. As this nanocapsule platform can be universally applied to other therapeutic mAbs, it holds great promise for extending mAb therapy to poorly accessible body compartments

Learning to Segment Microscopy Images with Lazy Labels

The need for labour intensive pixel-wise annotation is a major limitation of many fully supervised learning methods for segmenting bioimages that can contain numerous object instances with thin separations. In this paper, we introduce a deep convolutional neural network for microscopy image segmentation. Annotation issues are circumvented by letting the network being trainable on coarse labels combined with only a very small number of images with pixel-wise annotations. We call this new labelling strategy `lazy' labels. Image segmentation is stratified into three connected tasks: rough inner region detection, object separation and pixel-wise segmentation. These tasks are learned in an end-to-end multi-task learning framework. The method is demonstrated on two microscopy datasets, where we show that the model gives accurate segmentation results even if exact boundary labels are missing for a majority of annotated data. It brings more flexibility and efficiency for training deep neural networks that are data hungry and is applicable to biomedical images with poor contrast at the object boundaries or with diverse textures and repeated patterns

Substrate-induced band gap opening in epitaxial graphene

Graphene has shown great application potentials as the host material for next generation electronic devices. However, despite its intriguing properties, one of the biggest hurdles for graphene to be useful as an electronic material is its lacking of an energy gap in the electronic spectra. This, for example, prevents the use of graphene in making transistors. Although several proposals have been made to open a gap in graphene's electronic spectra, they all require complex engineering of the graphene layer. Here we show that when graphene is epitaxially grown on the SiC substrate, a gap of ~ 0.26 is produced. This gap decreases as the sample thickness increases and eventually approaches zero when the number of layers exceeds four. We propose that the origin of this gap is the breaking of sublattice symmetry owing to the graphene-substrate interaction. We believe our results highlight a promising direction for band gap engineering of graphene.Comment: 10 pages, 4 figures; updated reference

Lack of correlation of stem cell markers in breast cancer stem cells

BACKGROUND: Various markers are used to identify the unique sub-population of breast cancer cells with stem cell properties. Whether these markers are expressed in all breast cancers, identify the same population of cells, or equate to therapeutic response is controversial. METHODS: We investigated the expression of multiple cancer stem cell markers in human breast cancer samples and cell lines in vitro and in vivo, comparing across and within samples and relating expression with growth and therapeutic response to doxorubicin, docetaxol and radiotherapy. RESULTS: CD24, CD44, ALDH and SOX2 expression, the ability to form mammospheres and side-population cells are variably present in human cancers and cell lines. Each marker identifies a unique rather than common population of cancer cells. In vivo, cells expressing these markers are not specifically localized to the presumptive stem cell niche at the tumour/stroma interface. Repeated therapy does not consistently enrich cells expressing these markers, although ER-negative cells accumulate. CONCLUSIONS: Commonly employed methods identify different cancer cell sub-populations with no consistent therapeutic implications, rather than a single population of cells. The relationships of breast cancer stem cells to clinical parameters will require identification of specific markers or panels for the individual cancer

Wilson Lines and a Canonical Basis of SU(4) Heterotic Standard Models

The spontaneous breaking of SU(4) heterotic standard models by Z_3 x Z_3 Wilson lines to the MSSM with three right-handed neutrino supermultiplets and gauge group SU(3)_C x SU(2)_L x U(1) x U(1) is explored. The two-dimensional subspace of the Spin(10) Lie algebra that commutes with su(3)_C + su(2)_L is analyzed. It is shown that there is a unique basis for which the initial soft supersymmetry breaking parameters are uncorrelated and for which the U(1) x U(1) field strengths have no kinetic mixing at any scale. If the Wilson lines "turn on" at different scales, there is an intermediate regime with either a left-right or a Pati-Salam type model. We compute their spectra directly from string theory, and adjust the associated mass parameter so that all gauge parameters exactly unify. A detailed analysis of the running gauge couplings and soft gaugino masses is presented.Comment: 59 pages, 9 figure

Rare coding SNP in DZIP1 gene associated with late-onset sporadic Parkinson's disease

We present the first application of the hypothesis-rich mathematical theory to genome-wide association data. The Hamza et al. late-onset sporadic Parkinson's disease genome-wide association study dataset was analyzed. We found a rare, coding, non-synonymous SNP variant in the gene DZIP1 that confers increased susceptibility to Parkinson's disease. The association of DZIP1 with Parkinson's disease is consistent with a Parkinson's disease stem-cell ageing theory.Comment: 14 page

F-theory on Genus-One Fibrations

We argue that M-theory compactified on an arbitrary genus-one fibration, that is, an elliptic fibration which need not have a section, always has an F-theory limit when the area of the genus-one fiber approaches zero. Such genus-one fibrations can be easily constructed as toric hypersurfaces, and various $SU(5)\times U(1)^n$ and $E_6$ models are presented as examples. To each genus-one fibration one can associate a $\tau$-function on the base as well as an $SL(2,\mathbb{Z})$ representation which together define the IIB axio-dilaton and 7-brane content of the theory. The set of genus-one fibrations with the same $\tau$-function and $SL(2,\mathbb{Z})$ representation, known as the Tate-Shafarevich group, supplies an important degree of freedom in the corresponding F-theory model which has not been studied carefully until now. Six-dimensional anomaly cancellation as well as Witten's zero-mode count on wrapped branes both imply corrections to the usual F-theory dictionary for some of these models. In particular, neutral hypermultiplets which are localized at codimension-two fibers can arise. (All previous known examples of localized hypermultiplets were charged under the gauge group of the theory.) Finally, in the absence of a section some novel monodromies of Kodaira fibers are allowed which lead to new breaking patterns of non-Abelian gauge groups.Comment: 53 pages, 9 figures, 6 tables. v2: references adde

Single to Double Hump Transition in the Equilibrium Distribution Function of Relativistic Particles

We unveil a transition from single peaked to bimodal velocity distribution in a relativistic fluid under increasing temperature, in contrast with a non-relativistic gas, where only a monotonic broadening of the bell-shaped distribution is observed. Such transition results from the interplay between the raise in thermal energy and the constraint of maximum velocity imposed by the speed of light. We study the Bose-Einstein, the Fermi-Dirac, and the Maxwell-J\"uttner distributions, all exhibiting the same qualitative behavior. We characterize the nature of the transition in the framework of critical phenomena and show that it is either continuous or discontinuous, depending on the group velocity. We analyze the transition in one, two, and three dimensions, with special emphasis on two-dimensions, for which a possible experiment in graphene, based on the measurement of the Johnson-Nyquist noise, is proposed.Comment: 5 pages, 5 figure