Clinical significance and therapeutic value of glutathione peroxidase 3 (GPx3) in hepatocellular carcinoma

AIMS: We aimed to investigate the clinical significance of GPx3 in hepatocellular carcinoma (HCC) and to characterize its tumor suppressive role. METHODS: HCC patients (113) who underwent hepatectomy were recruited to examine the clinical relevance of GPx3. The tumor suppressive role of GPx3 was studied by administration of recombinant GPx3 (rGPx3) or over-expression of GPx3 in HCC cells in vitro and in vivo. The therapeutic value of GPx3 for HCC was further investigated using human induced pluripotent stem cell derived mesenchymal stem cells (hiPSC-MSCs) as its delivery vehicle. RESULTS: Down-regulation of GPx3 significantly correlated with advanced tumor stage (P = 0.024), venous infiltration (P = 0.043) and poor overall survival (P = 0.007) after hepatectomy. Lower plasma GPx3 in HCC patients was significantly associated with larger tumor size (P = 0.011), more tumor nodules (P = 0.032) and higher recurrence (P = 0.016). Over-expression of GPx3 or administration of rGPx3 significantly inhibited proliferation and invasiveness of HCC cells in vitro and in vivo. Tumor suppressive activity of GPx3 was mediated through Erk-NFκB-SIP1 pathway. GPx3 could be delivered by hiPSC-MSCs into the tumor and exhibited tumor suppressive activity in vivo. CONCLUSIONS: GPx3 is a tumor suppressor gene in HCC and may possess prognostic and therapeutic value for HCC patients.published_or_final_versio

Strategy Escalation: An emerging paradigm for safe clinical development of T cell gene therapies

Gene therapy techniques are being applied to modify T cells with chimeric antigen receptors (CARs) for therapeutic ends. The versatility of this platform has spawned multiple options for their application with new permutations in strategies continually being invented, a testimony to the creative energies of many investigators. The field is rapidly expanding with immense potential for impact against diverse cancers. But this rapid expansion, like the Big Bang, comes with a somewhat chaotic evolution of its therapeutic universe that can also be dangerous, as seen by recently publicized deaths. Time-honored methods for new drug testing embodied in Dose Escalation that were suitable for traditional inert agents are now inadequate for these novel "living drugs". In the following, I propose an approach to escalating risk for patient exposures with these new immuno-gene therapy agents, termed Strategy Escalation, that accounts for the molecular and biological features of the modified cells and the methods of their administration. This proposal is offered not as a prescriptive but as a discussion framework that investigators may wish to consider in configuring their intended clinical applications

Graph Learning based Recommender Systems: A Review

Recent years have witnessed the fast development of the emerging topic of Graph Learning based Recommender Systems (GLRS). GLRS employ advanced graph learning approaches to model users' preferences and intentions as well as items' characteristics for recommendations. Differently from other RS approaches, including content-based filtering and collaborative filtering, GLRS are built on graphs where the important objects, e.g., users, items, and attributes, are either explicitly or implicitly connected. With the rapid development of graph learning techniques, exploring and exploiting homogeneous or heterogeneous relations in graphs are a promising direction for building more effective RS. In this paper, we provide a systematic review of GLRS, by discussing how they extract important knowledge from graph-based representations to improve the accuracy, reliability and explainability of the recommendations. First, we characterize and formalize GLRS, and then summarize and categorize the key challenges and main progress in this novel research area

QoS-Aware Energy Management and Node Scheduling Schemes for Sensor Network-Based Surveillance Applications

Recent advances in wireless technologies have led to an increased deployment of Wireless Sensor Networks (WSNs) for a plethora of diverse surveillance applications such as health, military, and environmental. However, sensor nodes in WSNs usually suffer from short device lifetime due to severe energy constraints and therefore, cannot guarantee to meet the Quality of Service (QoS) needs of various applications. This is proving to be a major hindrance to the widespread adoption of WSNs for such applications. Therefore, to extend the lifetime of WSNs, it is critical to optimize the energy usage in sensor nodes that are often deployed in remote and hostile terrains. To this effect, several energy management schemes have been proposed recently. Node scheduling is one such strategy that can prolong the lifetime of WSNs and also helps to balance the workload among the sensor nodes. In this article, we discuss on the energy management techniques of WSN with a particular emphasis on node scheduling and propose an energy management life-cycle model and an energy conservation pyramid to extend the network lifetime of WSNs. We have provided a detailed classification and evaluation of various node scheduling schemes in terms of their ability to fulfill essential QoS requirements, namely coverage, connectivity, fault tolerance, and security. We considered essential design issues such as network type, deployment pattern, sensing model in the classification process. Furthermore, we have discussed the operational characteristics of schemes with their related merits and demerits. We have compared the efficacy of a few well known graph-based scheduling schemes with suitable performance analysis graph. Finally, we study challenges in designing and implementing node scheduling schemes from a QoS perspective and outline open research problems

Large Anomalous Hall effect in a silicon-based magnetic semiconductor

Magnetic semiconductors are attracting high interest because of their potential use for spintronics, a new technology which merges electronics and manipulation of conduction electron spins. (GaMn)As and (GaMn)N have recently emerged as the most popular materials for this new technology. While Curie temperatures are rising towards room temperature, these materials can only be fabricated in thin film form, are heavily defective, and are not obviously compatible with Si. We show here that it is productive to consider transition metal monosilicides as potential alternatives. In particular, we report the discovery that the bulk metallic magnets derived from doping the narrow gap insulator FeSi with Co share the very high anomalous Hall conductance of (GaMn)As, while displaying Curie temperatures as high as 53 K. Our work opens up a new arena for spintronics, involving a bulk material based only on transition metals and Si, and which we have proven to display a variety of large magnetic field effects on easily measured electrical properties.Comment: 19 pages with 5 figure

The Effect of Single, Binary and Ternary Anions of Chloride, Carbonate and Phosphate on the Release of 2,4-Dichlorophenoxyacetate Intercalated into the Zn–Al-layered Double Hydroxide Nanohybrid

Intercalation of beneficial anion into inorganic host has lead to an opportunity to synthesize various combinations of new organic–inorganic nanohybrids with various potential applications; especially, for the controlled release formulation and storage purposes. Investigation on the release behavior of 2,4-dichlorophenoxyacetate (2,4-D) intercalated into the interlayer of Zn–Al-layered double hydroxide (ZAN) have been carried out using single, binary and ternary aqueous systems of chloride, carbonate and phosphate. The release behavior of the active agent 2,4-D from its double-layered hydroxide nanohybrid ZANDI was found to be of controlled manner governed by pseudo-second order kinetics. It was found that carbonate medium yielded the highest accumulated release of 2,4-D, while phosphate in combination with carbonate and/or nitrate speeds up the release rate of 2,4-D. These results indicate that it is possible to design and develop new delivery system of latex stimulant compound with controlled release property based on 2,4-D that is known as a substance to increase latex production of rubber tree,Hevea brasiliensis

Colocalization of connexin 36 and corticotropin-releasing hormone in the mouse brain

<p>Abstract</p> <p>Background</p> <p>Gap junction proteins, connexins, are expressed in most endocrine and exocrine glands in the body and are at least in some glands crucial for the hormonal secretion. To what extent connexins are expressed in neurons releasing hormones or neuropeptides from or within the central nervous system is, however, unknown. Previous studies provide indirect evidence for gap junction coupling between subsets of neuropeptide-containing neurons in the paraventricular nucleus (PVN) of the hypothalamus. Here we employ double labeling and retrograde tracing methods to investigate to what extent neuroendocrine and neuropeptide-containing neurons of the hypothalamus and brainstem express the neuronal gap junction protein connexin 36.</p> <p>Results</p> <p>Western blot analysis showed that connexin 36 is expressed in the PVN. In bacterial artificial chromosome transgenic mice, which specifically express the reporter gene Enhanced Green Fluorescent Protein (EGFP) under the control of the connexin 36 gene promoter, EGFP expression was detected in magnocellular (neuroendocrine) and in parvocellular neurons of the PVN. Although no EGFP/connexin36 expression was seen in neurons containing oxytocin or vasopressin, EGFP/connexin36 was found in subsets of PVN neurons containing corticotropin-releasing hormone (CRH), and in somatostatin neurons located along the third ventricle. Moreover, CRH neurons in brainstem areas, including the lateral parabrachial nucleus, also expressed EGFP/connexin 36.</p> <p>Conclusion</p> <p>Our data indicate that connexin 36 is expressed in subsets of neuroendocrine and CRH neurons in specific nuclei of the hypothalamus and brainstem.</p

Determination of intrinsic switching field distributions in perpendicular recording media: numerical study of the ΔH(M,ΔM)\Delta H(M, \Delta M) method

We present a numerical study of the $\Delta H(M,\Delta M)$ method and its ability to accurately determine intrinsic switching field distributions in interacting granular magnetic materials such as perpendicular recording media. In particular, we study how this methodology fails for large ferromagnetic inter-granular interactions, at which point the associated strongly correlated magnetization reversal cannot be properly represented by the mean-field approximation, upon which the $\Delta H(M,\Delta M)$ method is based. In this study, we use a 2-dimensional array of symmetric hysterons that have an intrinsic switching field distribution of standard deviation $\sigma$ and ferromagnetic nearest-neighbor interactions $J$. We find the $\Delta H(M,\Delta M)$ method to be very accurate for small $J/\sigma$ values, while substantial errors develop once the effective exchange field becomes comparable with $\sigma$, corroborating earlier results from micromagnetic simulations. We furthermore demonstrate that this failure is correlated with deviations from data set redundancy, which is a key property of the mean-field approximation. Thus, the $\Delta H(M,\Delta M)$ method fails in a well defined and quantifiable manner that can be easily assessed from the data sets alone.Comment: 13 pages, 9 figure

Overexpression and Small Molecule-Triggered Downregulation of CIP2A in Lung Cancer

Lung cancer is the leading cause of cancer deaths worldwide, with a five-year overall survival rate of only 15%. Cancerous inhibitor of PP2A (CIP2A) is a human oncoprotein inhibiting PP2A in many human malignancies. However, whether CIP2A can be a new drug target for lung cancer is largely unclear.Normal and malignant lung tissues were derived from 60 lung cancer patients from southern China. RT-PCR, Western blotting and immunohistochemistry were used to evaluate the expression of CIP2A. We found that among the 60 patients, CIP2A was undetectable or very low in paratumor normal tissues, but was dramatically elevated in tumor samples in 38 (63.3%) patients. CIP2A overexpression was associated with cigarette smoking. Silencing CIP2A by siRNA inhibited the proliferation and clonogenic activity of lung cancer cells. Intriguingly, we found a natural compound, rabdocoetsin B which is extracted from a Traditional Chinese Medicinal herb Rabdosia coetsa, could induce down-regulation of CIP2A and inactivation of Akt pathway, and inhibit proliferation and induce apoptosis in a variety of lung cancer cells.Our findings strongly indicate that CIP2A could be an effective target for lung cancer drug development, and the therapeutic potentials of CIP2A-targeting agents warrant further investigation