Average Structures of a Single Knotted Ring Polymer

Two types of average structures of a single knotted ring polymer are studied by Brownian dynamics simulations. For a ring polymer with N segments, its structure is represented by a 3N -dimensional conformation vector consisting of the Cartesian coordinates of the segment positions relative to the center of mass of the ring polymer. The average structure is given by the average conformation vector, which is self-consistently defined as the average of the conformation vectors obtained from a simulation each of which is rotated to minimize its distance from the average conformation vector. From each conformation vector sampled in a simulation, 2N conformation vectors are generated by changing the numbering of the segments. Among the 2N conformation vectors, the one closest to the average conformation vector is used for one type of the average structure. The other type of the averages structure uses all the conformation vectors generated from those sampled in a simulation. In thecase of the former average structure, the knotted part of the average structure is delocalized for small N and becomes localized as N is increased. In the case of the latter average structure, the average structure changes from a double loop structure for small N to a single loop structure for large N, which indicates the localization-delocalization transition of the knotted part.Comment: 15 pages, 19 figures, uses jpsj2.cl

On fractional order models for Hepatitis C

In this paper we present a fractional order generalization of Perelson et al. basic hepatitis C virus (HCV) model including an immune response term. We argue that fractional order equations are more suitable than integer order ones in modeling complex systems which include biological systems. The model is presented and discussed. Also we argue that the added immune response term represents some basic properties of the immune system and that it should be included to study longer term behavior of the disease

GPT models in construction industry: Opportunities, limitations, and a use case validation

Large Language Models (LLMs) trained on large data sets came into prominence in 2018 after Google introduced BERT. Subsequently, different LLMs such as GPT models from OpenAI have been released. These models perform well on diverse tasks and have been gaining widespread applications in fields such as business and education. However, little is known about the opportunities and challenges of using LLMs in the construction industry. Thus, this study aims to assess GPT models in the construction industry. A critical review, expert discussion and case study validation are employed to achieve the study's objectives. The findings revealed opportunities for GPT models throughout the project lifecycle. The challenges of leveraging GPT models are highlighted and a use case prototype is developed for materials selection and optimization. The findings of the study would be of benefit to researchers, practitioners and stakeholders, as it presents research vistas for LLMs in the construction industry

IRG and GBP host resistance factors target aberrant, ‘‘Non-self’’ vacuoles characterized by the missing of ‘‘Self’’ IRGM proteins

Interferon-inducible GTPases of the Immunity Related GTPase (IRG) and Guanylate Binding Protein (GBP) families provide resistance to intracellular pathogenic microbes. IRGs and GBPs stably associate with pathogen-containing vacuoles (PVs) and elicit immune pathways directed at the targeted vacuoles. Targeting of Interferon-inducible GTPases to PVs requires the formation of higher-order protein oligomers, a process negatively regulated by a subclass of IRG proteins called IRGMs. We found that the paralogous IRGM proteins Irgm1 and Irgm3 fail to robustly associate with ‘‘non-self’’ PVs containing either the bacterial pathogen Chlamydia trachomatis or the protozoan pathogen Toxoplasma gondii. Instead, Irgm1 and Irgm3 reside on ‘‘self’’ organelles including lipid droplets (LDs). Whereas IRGM-positive LDs are guarded against the stable association with other IRGs and GBPs, we demonstrate that IRGM-stripped LDs become high affinity binding substrates for IRG and GBP proteins. These data reveal that intracellular immune recognition of organelle-like structures by IRG and GBP proteins is partly dictated by the missing of ‘‘self’’ IRGM proteins from these structures.Fil: Haldar, Arun K.. University Of Duke; Estados UnidosFil: Saka, Hector Alex. University Of Duke; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Córdoba. Centro de Investigaciones en Bioquímica Clínica e Inmunología; ArgentinaFil: Piro, Anthony S.. University Of Duke; Estados UnidosFil: Dunn, Joe Dan. University Of Duke; Estados UnidosFil: Henry, Stanley C.. University Of Duke; Estados Unidos. Veteran Affairs Medical Center; Estados UnidosFil: Taylor, Gregory A.. University Of Duke; Estados Unidos. Veteran Affairs Medical Center; Estados UnidosFil: Frickel, Eva M.. National Institute for Medical Research; Reino UnidoFil: Valdivia, Raphael H.. University Of Duke; Estados UnidosFil: Coers, Jörn. University Of Duke; Estados Unido

N=1/2 Supersymmetric gauge theory in noncommutative space

A formulation of (non-anticommutative) N=1/2 supersymmetric U(N) gauge theory in noncommutative space is studied. We show that at one loop UV/IR mixing occurs. A generalization of Seiberg-Witten map to noncommutative and non-anticommutative superspace is employed to obtain an action in terms of commuting fields at first order in the noncommutativity parameter tetha. This leads to abelian and non-abelian gauge theories whose supersymmetry transformations are local and non-local, respectively.Comment: One reference added, published versio

Overlapping variants in the blood, tissues and cell lines for patients with intracranial meningiomas are predominant in stem cell-related genes

Objective: Bulk tissue genomic analysis of meningiomas identified common somatic mutations, however, it often excluded blood-related variants. In contrast, genomic characterisation of primary cell lines that can provide critical information regarding growth and proliferation, have been rare. In our work, we identified the variants that are present in the blood, tissues and corresponding cell lines that are likely to be predictive, tumorigenic and progressive. Method: Whole-exome sequencing was used to identify variants and distinguish related pathways that exist in 42 blood, tissues and corresponding cell lines (BTCs) samples for patients with intracranial meningiomas. Conventional sequencing was used for the confirmation of variants. Integrative analysis of the gene expression for the corresponding samples was utilised for further interpretations. Results: In total, 926 BTC variants were detected, implicating 845 genes. A pathway analysis of all BTC genes with damaging variants indicated the 'cell morphogenesis involved in differentiation' stem cell-related pathway to be the most frequently affected pathway. Concordantly, five stem cell-related genes, GPRIN2, ALDH3B2, ASPN, THSD7A and SIGLEC6, showed BTC variants in at least five of the patients. Variants that were heterozygous in the blood and homozygous in the tissues or the corresponding cell lines were rare (average: 1.3 +/- 0.3%), and included variants in the RUNX2 and CCDC114 genes. An analysis comparing the variants detected only in tumours with aggressive features indicated a total of 240 BTC genes, implicating the 'homophilic cell adhesion via plasma membrane adhesion molecules' pathway, and identifying the stem cell-related transcription coactivator NCOA3/AIB1/SRC3 as the most frequent BTC gene. Further analysis of the possible impact of the poly-Q mutation present in the NCOA3 gene indicated associated deregulation of 15 genes, including the up-regulation of the stem cell related SEMA3D gene and the angiogenesis related VEGFA gene. Conclusion: Stem cell-related pathways and genes showed high prevalence in the BTC variants, and novel variants in stem cell-related genes were identified for meningioma. These variants can potentially be used as predictive, tumorigenic and progressive biomarkers for meningioma

N=2 Instanton Effective Action in Omega-background and D3/D(-1)-brane System in R-R Background

We study the relation between the ADHM construction of instantons in the Omega-background and the fractional D3/D(-1)-branes at the orbifold singularity of C \times C^2/Z_2 in Ramond-Ramond (R-R) 3-form field strength background. We calculate disk amplitudes of open strings connecting the D3/D(-1)-branes in certain R-R background to obtain the D(-1)-brane effective action deformed by the R-R background. We show that the deformed D(-1)-brane effective action agrees with the instanton effective action in the Omega-background.Comment: 35 pages, no figures, references adde