Understanding the emerging models of adaptive resistance is key to overcoming cancer chemotherapy failure. Using human breast cancer explants, in vitro cell lines, mouse in vivo studies and ...mathematical modelling, here we show that exposure to a taxane induces phenotypic cell state transition towards a favoured transient CD44(Hi)CD24(Hi) chemotherapy-tolerant state. This state is associated with a clustering of CD44 and CD24 in membrane lipid rafts, leading to the activation of Src Family Kinase (SFK)/hemopoietic cell kinase (Hck) and suppression of apoptosis. The use of pharmacological inhibitors of SFK/Hck in combination with taxanes in a temporally constrained manner, where the kinase inhibitor is administered post taxane treatment, but not when co-administered, markedly sensitizes the chemotolerant cells to the chemotherapy. This approach of harnessing chemotherapy-induced phenotypic cell state transition for improving antitumour outcome could emerge as a translational strategy for the management of cancer.
Cancer progresses by evading the immune system. Elucidating diverse immune evasion strategies is a critical step in the search for next-generation immunotherapies for cancer. Here we report that ...cancer cells can hijack the mitochondria from immune cells via physical nanotubes. Mitochondria are essential for metabolism and activation of immune cells. By using field-emission scanning electron microscopy, fluorophore-tagged mitochondrial transfer tracing and metabolic quantification, we demonstrate that the nanotube-mediated transfer of mitochondria from immune cells to cancer cells metabolically empowers the cancer cells and depletes the immune cells. Inhibiting the nanotube assembly machinery significantly reduced mitochondrial transfer and prevented the depletion of immune cells. Combining a farnesyltransferase and geranylgeranyltransferase 1 inhibitor, namely, L-778123, which partially inhibited nanotube formation and mitochondrial transfer, with a programmed cell death protein 1 immune checkpoint inhibitor improved the antitumour outcomes in an aggressive immunocompetent breast cancer model. Nanotube-mediated mitochondrial hijacking can emerge as a novel target for developing next-generation immunotherapy agents for cancer.
It has been an established fact that comminution processes, crushing and grinding, are most energy intensive processes which account for more than half of the total energy consumed in mineral ...industries.Various alternative pre-treatment methods have been tried by experts around the globe. Although these methods yielded positive results in terms of reduction in energy consumption in crushing and particularly, in grinding operations at laboratory scale, their industrial application still remains an unresolved issue and challenge. Present review paper describes each one of these methods along with outcome of earlier studies and issues that need to be addressed through further rigorous experimental investigation.It also suggests the direction in which future studies can be carried out to meet the primary objective of making comminution processes more energy efficient than today they are.
All organisms, including unicellular pathogens, compulsorily possess DNA topoisomerases for successful nucleic acid metabolism. But particular subtypes of topoisomerases exist, in all prokaryotes and ...in some unicellular eukaryotes, that are absent in higher eukaryotes. Moreover, topoisomerases from pathogenic members of a niche possess some unique molecular architecture and functionalities completely distinct from their nonpathogenic colleagues. This review will highlight the unique attributes associated with the structures and functions of topoisomerases from the unicellular pathogens, with special reference to bacteria and protozoan parasites. It will also summarise the progress made in the domain pertaining to the druggability of these topoisomerases, upon which a future platform for therapeutic development can be successfully constructed.
Topoisomerases from pathogenic members of a niche possess significant structural and functional differences from their nonpathogenic colleagues.
Plasmodium and Toxoplasma, despite being apicomplexan parasites, differ from each other significantly in topoisomerase distribution, structure, and function.
Few pathogens compensate the absence of a particular topoisomerase subtype by amplifying another topoisomerase variant.
Kinetoplastid pathogens possess a ‘unique’ bi-subunit topoisomerase IB, completely distinct from all other type IB enzymes.
Particular subtypes of topoisomerases exclusively exist in prokaryotes and in some unicellular eukaryotes. The absence of these enzymes in higher eukaryotes, including human, adds a new dimension in drug development research.
Pathogens from diverse genera show a similar molecular trend in mutating their topoisomerase genes to attain resistance against topo-targeted compounds.
This survey article discusses the revolutions of wireless communication technologies right from the prehistoric man's fire signals to today's space optical communications. A brief description of ...evaluations of communication technologies from the ancient Greece to today's mature telecommunication fields is discussed in this review paper. Principle, significance, demonstration and development of free space optical (FSO) communication technology over different decades are discussed. Major FSO channel limitations, temporal and spatial challenges of FSO communication system and their state-of-art mitigation techniques are presented. Classical quantitative analysis of reliability of FSO communication, developments on radio over FSO (RoFSO) and hybrid FSO/RF systems are also explained. Advanced developments of FSO communication techniques such as optical free space wavelength division multiplexing (WDM), sub-carrier multiplexing (SCM), worldwide interoperability for microwave access (WiMAX), visible light communications (VLC) and vehicular visible light communications (VVLC) are reported. Deep space optical communication systems and next generation FSO wireless terrestrial/global network architecture are summarised. Research challenges of FSO systems for internet of things/everything (IoT/IoE), 5G communication, mobile-network, terahertz spectrum, quantum communication and underwater optical applications are presented. Based on the review, we outlined the challenges that need to be addressed in near-future researches to realize full potential FSO communication systems.
Poly(ADP-ribose) polymerases (PARP) attach poly(ADP-ribose) (PAR) chains to various proteins including themselves and chromatin. Topoisomerase I (Top1) regulates DNA supercoiling and is the target of ...camptothecin and indenoisoquinoline anticancer drugs, as it forms Top1 cleavage complexes (Top1cc) that are trapped by the drugs. Endogenous and carcinogenic DNA lesions can also trap Top1cc. Tyrosyl-DNA phosphodiesterase 1 (TDP1), a key repair enzyme for trapped Top1cc, hydrolyzes the phosphodiester bond between the DNA 3'-end and the Top1 tyrosyl moiety. Alternative repair pathways for Top1cc involve endonuclease cleavage. However, it is unknown what determines the choice between TDP1 and the endonuclease repair pathways. Here we show that PARP1 plays a critical role in this process. By generating TDP1 and PARP1 double-knockout lymphoma chicken DT40 cells, we demonstrate that TDP1 and PARP1 are epistatic for the repair of Top1cc. The N-terminal domain of TDP1 directly binds the C-terminal domain of PARP1, and TDP1 is PARylated by PARP1. PARylation stabilizes TDP1 together with SUMOylation of TDP1. TDP1 PARylation enhances its recruitment to DNA damage sites without interfering with TDP1 catalytic activity. TDP1-PARP1 complexes, in turn recruit X-ray repair cross-complementing protein 1 (XRCC1). This work identifies PARP1 as a key component driving the repair of trapped Top1cc by TDP1.
Prostate cancer remains a major cause of cancer-related mortality. Genetic clues to the molecular pathways driving the most aggressive forms of prostate cancer have been limited. Genetic inactivation ...of PTEN through either gene deletion or point mutation is reasonably common in metastatic prostate cancer and the resulting activation of phosphoinostide 3-kinase, AKT and mTOR provides a major therapeutic opportunity in this disease as mTOR inhibitors, HSP90 inhibitors and PI3K inhibitors begin to enter clinical development.
Obtaining measured synthetic aperture radar (SAR) data for training automatic target recognition (ATR) models can be too expensive (in terms of time and money) and complex of a process in many ...situations. In response, researchers have developed methods for creating synthetic SAR data for targets using electro-magnetic prediction software, which is then used to enrich an existing measured training dataset. However, this approach relies on the availability of some amount of measured data. In this work, we focus on the case of having 100% synthetic training data, while testing on only measured data. We use the SAMPLE dataset public released by AFRL, and find significant challenges to learning generalizable representations from the synthetic data due to distributional differences between the two modalities and extremely limited training sample quantities. Using deep learning-based ATR models, we propose data augmentation, model construction, loss function choices, and ensembling techniques to enhance the representation learned from the synthetic data, and ultimately achieved over 95% accuracy on the SAMPLE dataset. We then analyze the functionality of our ATR models using saliency and feature-space investigations and find them to learn a more cohesive representation of the measured and synthetic data. Finally, we evaluate the out-of-library detection performance of our synthetic-only models and find that they are nearly 10% more effective than baseline methods at identifying measured test samples that do not belong to the training class set. Overall, our techniques and their compositions significantly enhance the feasibility of using ATR models trained exclusively on synthetic data.
Training deep learning-based synthetic aperture radar automatic target recognition (SAR-ATR) systems for use in an "open-world" operating environment has, thus far proven difficult. Most SAR-ATR ...systems are designed to achieve maximum accuracy for a limited set of classes, yet ignore the implications of encountering novel target classes during deployment. Even worse, the standard deep learning training objectives fundamentally inherit a closed-world assumption, and provide no guidance for how to handle out-of-distribution (OOD) data. In this work, we develop a novel training procedure called adversarial outlier exposure (AdvOE) to codesign the ATR system for accuracy and OOD detection. Our method introduces a large, diverse, and unlabeled auxiliary training dataset containing samples from the OOD set. The AdvOE objective encourages a deep neural network to learn robust features of the in-distribution training data, while also promoting maximum entropy predictions for adversarially perturbed versions of the OOD data. We experiment with the recent SAMPLE dataset, and find our method nearly doubles the OOD detection performance over the baseline in key settings, and excels when using only synthetic training data. As compared to several other advanced ATR training techniques, AdvOE also affords significant improvements in both classification and detection statistics. Finally, we conduct extensive experiments that measure the effect of OOD set granularity on detection rates; discuss the implications of using different detection algorithms; and develop a novel analysis technique to validate our findings and interpret the OOD detection problem from a new perspective.
The experimental determination of higher heating value (HHV) of solid fuels is a cost intensive process, as it requires special instrumentation and highly trained analyst to operate it, where as ...proximate analysis data can be obtained relatively easily using an ordinary muffle furnace. Therefore, to simplify the task and to reduce the cost of analysis many correlations were developed for determining HHV from proximate analysis of solid fuels. An attempt has been made in this paper to evaluate the applicability of these correlations with a special focus on Indian coals. It has been observed that the developed correlations are either complex in nature or by-pass the effect of important variables like moisture and ash contents of coals. An effort has, therefore, been made to develop a simple correlation based on proximate analysis data for predicting HHV of coal (as-received basis). The model presented here is developed using analyses of 250 coal samples and its significance lies in involvement of all the major variables affecting the HHV. The developed model appears to be better than the existing models and has the following form:
HHV
=
-
0.03
(
A
)
-
0.11
(
M
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+
0.33
(
V
M
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+
0.35
(
F
C
)
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