Development of a computational toolbox to analyse first-passage times and diffusion coefficients in heterogeneous soft-matter system

The analysis of first-passage time statistics in soft-matter systems, such as water near amino-acid crystals explored in [1], can be vital in understanding the dynamical complexity of their chemical and geometrical properties. From the first-passage time statistics of water molecules, it was shown in [1, 2] that it is possible to infer space-dependent diffusion coefficients in directions normal to various phase boundaries. The analysis developed in [1, 2] is highly-nontrivial, computationally expensive, and system-dependent. Here, in an interdisciplinary collaboration between statistical physics and atomistic simulations, we aim to develop a generic computational methodology which will allow us to extract and analyse trajectories, obtained from molecular dynamics simulations by programs such as GROMACS or LAMMPS, to determine first passage times and spatially resolved diffusion coefficients. We perform exhaustive high-performance-computing benchmarks of our algorithm in various aqueous systems, and develop a user-friendly interface that we will make available to researchers as an open-source toolbox, working on in-silico studies of natural products

Characterizing qubit channels in the context of quantum teleportation

We consider a scenario where a party, say, Alice prepares a pure two-qubit (either maximally entangled or non-maximally entangled) state and sends one half of this state to another distant party, say, Bob through a qubit (either unital or non-unital) channel. Finally, the shared state is used as a teleportation channel. In this scenario, we focus on characterizing the set of qubit channels with respect to the final state's efficacy as a resource of quantum teleportation (QT) in terms of maximal average fidelity and fidelity deviation (fluctuation in fidelity values over the input states). Importantly, we point out the existence of a subset of qubit channels for which the final state becomes useful for universal QT (having maximal average fidelity strictly greater than the classical bound and having zero fidelity deviation) when the initially prepared state is either useful for universal QT (i.e., for a maximally entangled state) or not useful for universal QT (i.e., for a subset of non-maximally entangled pure states). Interestingly, in the latter case, we show that non-unital channels (dissipative interactions) are more effective than unital channels (non-dissipative interactions) in producing useful states for universal QT from non-maximally entangled pure states

Segmenting Scientific Abstracts into Discourse Categories: A Deep Learning-Based Approach for Sparse Labeled Data

The abstract of a scientific paper distills the contents of the paper into a short paragraph. In the biomedical literature, it is customary to structure an abstract into discourse categories like BACKGROUND, OBJECTIVE, METHOD, RESULT, and CONCLUSION, but this segmentation is uncommon in other fields like computer science. Explicit categories could be helpful for more granular, that is, discourse-level search and recommendation. The sparsity of labeled data makes it challenging to construct supervised machine learning solutions for automatic discourse-level segmentation of abstracts in non-bio domains. In this paper, we address this problem using transfer learning. In particular, we define three discourse categories BACKGROUND, TECHNIQUE, OBSERVATION-for an abstract because these three categories are the most common. We train a deep neural network on structured abstracts from PubMed, then fine-tune it on a small hand-labeled corpus of computer science papers. We observe an accuracy of 75% on the test corpus. We perform an ablation study to highlight the roles of the different parts of the model. Our method appears to be a promising solution to the automatic segmentation of abstracts, where the labeled data is sparse.Comment: to appear in the proceedings of JCDL'202

Notch and VEGF pathways play distinct but complementary roles in tumor angiogenesis

Background: Anti-angiogenesis is a validated strategy to treat cancer, with efficacy in controlling both primary tumor growth and metastasis. The role of the Notch family of proteins in tumor angiogenesis is still emerging, but recent data suggest that Notch signaling may function in the physiologic response to loss of VEGF signaling, and thus participate in tumor adaptation to VEGF inhibitors. Methods: We asked whether combining Notch and VEGF blockade would enhance suppression of tumor angiogenesis and growth, using the NGP neuroblastoma model. NGP tumors were engineered to express a Notch1 decoy construct, which restricts Notch signaling, and then treated with either the anti-VEGF antibody bevacizumab or vehicle. Results: Combining Notch and VEGF blockade led to blood vessel regression, increasing endothelial cell apoptosis and disrupting pericyte coverage of endothelial cells. Combined Notch and VEGF blockade did not affect tumor weight, but did additively reduce tumor viability. Conclusions: Our results indicate that Notch and VEGF pathways play distinct but complementary roles in tumor angiogenesis, and show that concurrent blockade disrupts primary tumor vasculature and viability further than inhibition of either pathway alone

Dynamics of Hot QCD Matter -- Current Status and Developments

The discovery and characterization of hot and dense QCD matter, known as Quark Gluon Plasma (QGP), remains the most international collaborative effort and synergy between theorists and experimentalists in modern nuclear physics to date. The experimentalists around the world not only collect an unprecedented amount of data in heavy-ion collisions, at Relativistic Heavy Ion Collider (RHIC), at Brookhaven National Laboratory (BNL) in New York, USA, and the Large Hadron Collider (LHC), at CERN in Geneva, Switzerland but also analyze these data to unravel the mystery of this new phase of matter that filled a few microseconds old universe, just after the Big Bang. In the meantime, advancements in theoretical works and computing capability extend our wisdom about the hot-dense QCD matter and its dynamics through mathematical equations. The exchange of ideas between experimentalists and theoreticians is crucial for the progress of our knowledge. The motivation of this first conference named "HOT QCD Matter 2022" is to bring the community together to have a discourse on this topic. In this article, there are 36 sections discussing various topics in the field of relativistic heavy-ion collisions and related phenomena that cover a snapshot of the current experimental observations and theoretical progress. This article begins with the theoretical overview of relativistic spin-hydrodynamics in the presence of the external magnetic field, followed by the Lattice QCD results on heavy quarks in QGP, and finally, it ends with an overview of experiment results.Comment: Compilation of the contributions (148 pages) as presented in the `Hot QCD Matter 2022 conference', held from May 12 to 14, 2022, jointly organized by IIT Goa & Goa University, Goa, Indi

Connexin’s Connection in Breast Cancer Growth and Progression

Gap junctions are cell-to-cell junctions that are located in the basolateral surface of two adjoining cells. A gap junction channel is composed of a family of proteins called connexins. Gap junction channels maintain intercellular communication between two cells through the exchange of ions, small metabolites, and electrical signals. Gap junction channels or connexins are widespread in terms of their expression and function in maintaining the development, differentiation, and homeostasis of vertebrate tissues. Gap junction connexins play a major role in maintaining intercellular communication among different cell types of normal mammary gland for proper development and homeostasis. Connexins have also been implicated in the pathogenesis of breast cancer. Differential expression pattern of connexins and their gap junction dependent or independent functions provide pivotal cross talk of breast tumor cells with the surrounding stromal cell in the microenvironment. Substantial research from the last 20 years has accumulated ample evidences that allow us a better understanding of the roles that connexins play in the tumorigenesis of primary breast tumor and its metastatic progression. This review will summarize the knowledge about the connexins and gap junction activities in breast cancer highlighting the differential expression and functional dynamics of connexins in the pathogenesis of the disease

Investigation of novel functions of a gap junction protein, connexin46

Doctor of PhilosophyDepartment of BiochemistryDolores J. TakemotoConnexin proteins are the principle structural components of gap junction channels that connect the cytoplasm of two cells and maintain direct intercellular communication through the exchange of ions, small molecules and cellular metabolites. Colocalization and tissue-specific expression of diverse connexin molecules are reported to occur in a variety of organs. Impairment of gap junctional intercellular communication, caused by mutations, gain of function or loss of function of connexins, is involved in a number of diseases including the development of cancer. Here the functions of a gap junction protein, connexin46 (Cx46), have been investigated in two hypoxic tissues, lens and breast tumor. We show that human breast cancer cells, MCF-7 and breast tumor tissues express connexin46 (Cx46) and it plays a critical role in protecting cells against hypoxia-induced death. Interestingly, I find that Cx46 is upregulated in MCF-7 breast cancer cells and human breast cancer tumors. Downregulation of Cx46 by siRNA promotes cell death of human lens epithelial cells (HLEC) and MCF-7 cells under hypoxic conditions. Furthermore, direct injection of anti-Cx46 siRNA into xenograft tumors prevents tumor growth in nude mice. Our result suggests that both normal hypoxic tissue (lens) and adaptive hypoxic tissue (breast tumor) utilize the same protein, Cx46, as a protective strategy against hypoxia. In the last part of the dissertation, we show that over expression of Cx46 induces the degradation of another connexin, connexin43, in rabbit lens epithelial NN1003A cells. Over expression of Cx46 increases ubiquitination of Cx43. Moreover, the Cx46-induced Cx43 degradation is counteracted by inhibitors of proteasome. Taken together, these data indicate that the degradation of Cx43, upon Cx46 over expression, is mediated by the ubiquitin-proteasome pathway. I also provide evidence that that C-terminal tail of Cx46 is essential to induce degradation of Cx43. Therefore, our study shows that Cx46 has a novel function in the regulation of Cx43 turnover in addition to its conventional role as a gap junction protein. This may contribute to protection from hypoxia in both the lens and tumors

A random bit generator using Rössler chaotic system

In this paper, a random bit generator is proposed which utilizes the chaotic nature of a Rossler System. The generator is modelled and the generated random sequence is tested using statistical tests like autocorrelation test, runs test and monobit test. The sequence shows a high degree of randomness, besides being simple for real-world implementation.</p

Adding nanotechnology to the metastasis treatment arsenal

Metastasis is a major cause of cancer-related mortality, accounting for 90% of cancer deaths. The explosive growth of cancer biology research has revealed new mechanistic network information and pathways that promote metastasis. Consequently, a large number of antitumor agents have been developed and tested for their antimetastatic efficacy. Despite their exciting cytotoxic effects on tumor cells in vitro and antitumor activities in preclinical studies in vivo, only a few have shown potent antimetastatic activities in clinical trials. In this review, we provide a brief overview of current antimetastatic strategies that show clinical efficacy and review nanotechnology-based approaches that are currently being incorporated into these therapies to mitigate challenges associated with treating cancer metastasis.Funding agencies: EU H2020 Marie Sklodowska-Curie Individual Fellowship [706694]; Wolfson College (University of Cambridge, UK); MIIC Seed Grant from Linkoping University (LiU), Sweden</p