ZIL: An Energy-Efficient Indoor Localization System Using ZigBee Radio to Detect WiFi Fingerprints

In existing WiFi-based localization methods, smart mobile devices consume quite a lot of power as WiFi interfaces need to be used for frequent AP scanning during the localization process. In this work, we design an energy-efficient indoor localization system called ZigBee assisted indoor localization (ZIL) based on WiFi fingerprints via ZigBee interference signatures. ZIL uses ZigBee interfaces to collect mixed WiFi signals, which include non-periodic WiFi data and periodic beacon signals. However, WiFi APs cannot be identified from these WiFi signals by ZigBee interfaces directly. To address this issue, we propose a method for detecting WiFi APs to form WiFi fingerprints from the signals collected by ZigBee interfaces. We propose a novel fingerprint matching algorithm to align a pair of fingerprints effectively. To improve the localization accuracy, we design the K-nearest neighbor (KNN) method with three different weighted distances and find that the KNN algorithm with the Manhattan distance performs best. Experiments show that ZIL can achieve the localization accuracy of 87%, which is competitive compared to state-of-the-art WiFi fingerprint-based approaches, and save energy by 68% on average compared to the approach based on WiFi interface.

Energy-Aware Rate and Description Allocation Optimized Video Streaming for Mobile D2D Communications

The proliferation problem of video streaming applications and mobile devices has prompted wireless network operators to put more efforts into improving quality of experience (QoE) while saving resources that are needed for high transmission rate and large size of video streaming. To deal with this problem, we propose an energy-aware rate and description allocation optimization method for video streaming in cellular network assisted device-to-device (D2D) communications. In particular, we allocate the optimal bit rate to each layer of video segments and packetize the segments into multiple descriptions with embedded forward error correction (FEC) for realtime streaming without retransmission. Simultaneously, the optimal number of descriptions is allocated to each D2D helper for transmission. The two allocation processes are done according to the access rate of segments, channel state information (CSI) of D2D requester, and remaining energy of helpers, to gain the highest optimization performance. Simulation results demonstrate that our proposed method (named OPT) significantly enhances the performance of video streaming in terms of high QoE and energy saving.

Nestor-Guillermo Progeria Syndrome: a biochemical insight into Barrier-to-Autointegration Factor 1, alanine 12 threonine mutation

Background: Premature aging syndromes recapitulate many aspects of natural aging and provide an insight into this phenomenon at a molecular and cellular level. The progeria syndromes appear to cause rapid aging through disruption of normal nuclear structure. Recently, a coding mutation (c.34G > A [p.A12T]) in the Barrier to Autointegration Factor 1 (BANF1) gene was identified as the genetic basis of Nestor-Guillermo Progeria syndrome (NGPS). This mutation was described to cause instability in the BANF1 protein, causing a disruption of the nuclear envelope structure.

Results: Here we demonstrate that the BANF1 A12T protein is indeed correctly folded, stable and that the observed phenotype, is likely due to the disruption of the DNA binding surface of the A12T mutant. We demonstrate, using biochemical assays, that the BANF1 A12T protein is impaired in its ability to bind DNA while its interaction with nuclear envelope proteins is unperturbed. Consistent with this, we demonstrate that ectopic expression of the mutant protein induces the NGPS cellular phenotype, while the protein localizes normally to the nuclear envelope.

Conclusions: Our study clarifies the role of the A12T mutation in NGPS patients, which will be of importance for understanding the development of the disease.

A role of autophagy in PTP4A3-driven cancer progression

Autophagy, a "self-eating" cellular process, has dual roles in promoting and suppressing tumor growth, depending on cellular context. PTP4A3/PRL-3, a plasma membrane and endosomal phosphatase, promotes multiple oncogenic processes including cell proliferation, invasion, and cancer metastasis. In this study, we demonstrate that PTP4A3 accumulates in autophagosomes upon inhibition of autophagic degradation. Expression of PTP4A3 enhances PIK3C3-BECN1-dependent autophagosome formation and accelerates LC3-I to LC3-II conversion in an ATG5-dependent manner. PTP4A3 overexpression also enhances the degradation of SQSTM1, a key autophagy substrate. These functions of PTP4A3 are dependent on its catalytic activity and prenylation-dependent membrane association. These results suggest that PTP4A3 functions to promote canonical autophagy flux. Unexpectedly, following autophagy activation, PTP4A3 serves as a novel autophagic substrate, thereby establishing a negative feedback-loop that may be required to fine-tune autophagy activity. Functionally, PTP4A3 utilizes the autophagy pathway to promote cell growth, concomitant with the activation of AKT. Clinically, from the largest ovarian cancer data set (GSE 9899, n = 285) available in GEO, high levels of expression of both PTP4A3 and autophagy genes significantly predict poor prognosis of ovarian cancer patients. These studies reveal a critical role of autophagy in PTP4A3-driven cancer progression, suggesting that autophagy could be a potential Achilles heel to block PTP4A3-mediated tumor progression in stratified patients with high expression of both PTP4A3 and autophagy genes.

Computational cancer biology: education is a natural key to many locks

Background: Oncology is a field that profits tremendously from the genomic data generated by high-throughput technologies, including next-generation sequencing. However, in order to exploit, integrate, visualize and interpret such high-dimensional data efficiently, non-trivial computational and statistical analysis methods are required that need to be developed in a problem-directed manner.

Discussion: For this reason, computational cancer biology aims to fill this gap. Unfortunately, computational cancer biology is not yet fully recognized as a coequal field in oncology, leading to a delay in its maturation and, as an immediate consequence, an under-exploration of high-throughput data for translational research.

Summary: Here we argue that this imbalance, favoring 'wet lab-based activities', will be naturally rectified over time, if the next generation of scientists receives an academic education that provides a fair and competent introduction to computational biology and its manifold capabilities. Furthermore, we discuss a number of local educational provisions that can be implemented on university level to help in facilitating the process of harmonization.

Prognostic significance of minichromosome maintenance proteins in breast cancer

A role for the minichromosome maintenance (MCM) proteins in cancer initiation and progression is slowly emerging. Functioning as a complex to ensure a single chromosomal replication per cell cycle, the six family members have been implicated in several neoplastic disease states, including breast cancer. Our study aim to investigate the prognostic significance of these proteins in breast cancer. We studied the expression of MCMs in various datasets and the associations of the expression with clinicopathological parameters. When considered alone, high level MCM4 overexpression was only weakly associated with shorter survival in the combined breast cancer patient cohort (n = 1441, Hazard Ratio = 1.31; 95% Confidence Interval = 1.11-1.55; p = 0.001). On the other hand, when we studied all six components of the MCM complex, we found that overexpression of all MCMs was strongly associated with shorter survival in the same cohort (n = 1441, Hazard Ratio = 1.75; 95% Confidence Interval = 1.31-2.34; p <0.001), suggesting these MCM proteins may cooperate to promote breast cancer progression. Indeed, their expressions were significantly correlated with each other in these cohorts. In addition, we found that increasing number of overexpressed MCMs was associated with negative ER status as well as treatment response. Together, our findings are reproducible in seven independent breast cancer cohorts, with 1441 patients, and suggest that MCM profiling could potentially be used to predict response to treatment and prognosis in breast cancer patients.

Retrieving Regions of Interest for User Exploration

We consider an application scenario where points of interest (PoIs) each have a web presence and where a web user wants to iden- tify a region that contains relevant PoIs that are relevant to a set of keywords, e.g., in preparation for deciding where to go to conve- niently explore the PoIs. Motivated by this, we propose the length- constrained maximum-sum region (LCMSR) query that returns a spatial-network region that is located within a general region of in- terest, that does not exceed a given size constraint, and that best matches query keywords. Such a query maximizes the total weight of the PoIs in it w.r.t. the query keywords. We show that it is NP- hard to answer this query. We develop an approximation algorithm with a (5 + ǫ) approximation ratio utilizing a technique that scales node weights into integers. We also propose a more efficient heuris- tic algorithm and a greedy algorithm. Empirical studies on real data offer detailed insight into the accuracy of the proposed algorithms and show that the proposed algorithms are capable of computingresults efficiently and effectively.

The prognostic significance of PD-L1 in bladder cancer

Immunotherapy is a promising strategy for the treatment of various types of cancer. An antibody that targets programmed death ligand-1 (PD-L1) pathway has been shown to be active towards various types of cancer, including melanoma and lung cancer. MPDL3280A, an anti‑PD-L1 antibody, has shown clear clinical activity in PD-L1-overexpressing bladder cancer with an objective response rate of 40-50%, resulting in a breakthrough therapy designation granted by FDA. These events pronounce the importance of targeting the PD-L1 pathway in the treatment of bladder cancer. In the present study, we investigated the prognostic significance of the expression of three genes in the PD-L1 pathway, including PD-L1, B7.1 and PD-1, in three independent bladder cancer datasets in the Gene Expression Omnibus database. PD-L1, B7.1 and PD-1 were significantly associated with clinicopathological parameters indicative of a more aggressive phenotype of bladder cancer, such as a more advanced stage and a higher tumor grade. In addition, a high level expression of PD-L1 was associated with reduced patient survival. Of note, the combination of PD-L1 and B7.1 expression, but not other combinations of the three genes, were also able to predict patient survival. Our findings support the development of anti-PD-L1, which blocks PD-L1-PD-1 and B7.1-PD-L1 interactions, in treatment of bladder cancer. The observations were consistent in the three independent bladder cancer datasets consisting of a total of 695 human bladder specimens. The datasets were then assessed and it was found that the expression levels of the chemokine CC-motif ligand (CCL), CCL3, CCL8 and CCL18, were correlated with the PD-L1 expression level, while ADAMTS13 was differentially expressed in patients with a different survival status (alive or deceased). Additional investigations are required to elucidate the role of these genes in the PD-L1-mediated immune system suppression and bladder cancer progression. In conclusion, findings of this study suggested that PD-L1 is an important prognostic marker and a therapeutic target for bladder cancer.

The significance of combining VEGFA, FLT1, and KDR expressions in colon cancer patient prognosis and predicting response to bevacizumab

Targeting angiogenesis through inhibition of the vascular endothelial growth factor (VEGF) pathway has been successful in the treatment of late stage colorectal cancer. However, not all patients benefit from inhibition of VEGF. Ras status is a powerful biomarker for response to anti-epidermal growth factor receptor therapy; however, an appropriate biomarker for response to anti-VEGF therapy is yet to be identified. VEGF and its receptors, FLT1 and KDR, play a crucial role in colon cancer progression; individually, these factors have been shown to be prognostic in colon cancer; however, expression of none of these factors alone was predictive of tumor response to anti-VEGF therapy. In the present study, we analyzed the expression levels of VEGFA, FLT1, and KDR in two independent colon cancer datasets and found that high expression levels of all three factors afforded a very poor prognosis. The observation was further confirmed in another independent colon cancer dataset, wherein high levels of expression of this three-gene signature was predictive of poor prognosis in patients with proficient mismatch repair a wild-type KRas status, or mutant p53 status. Most importantly, this signature also predicted tumor response to bevacizumab, an antibody targeting VEGFA, in a cohort of bevacizumab-treated patients. Since bevacizumab has been proven to be an important drug in the treatment of advanced stage colon cancer, our results suggest that the three-gene signature approach is valuable in terms of its prognostic value, and that it should be further evaluated in a prospective clinical trial to investigate its predictive value to anti-VEGF treatment.

Thermodynamically stable amorphous drug dispersions in amorphous hydrophilic polymers engineered by hot melt extrusion.

In this study thermodynamically stable dispersions of amorphous quinine, a model BCS class 2 therapeutic agent, within an amorphous polymeric platform (HPC), termed a solid-in-solid dispersion, were produced using hot melt extrusion. Characterisation of the pre-extrudates and extrudates was performed using hyper-differential scanning calorimetry (DSC), powder X-ray diffraction (PXRD) and Raman spectroscopy. Water uptake by the raw materials was determined using dynamic vapour sorption (DVS) analysis. Furthermore, the presence or absence of crystalline drug following storage at 25 °C/60% relative humidity and 40 °C/75% relative humidity in a sealed glass jar, and at 40 °C/75% relative humidity in an open glass jar for 3 months was determined using PXRD. Amorphous quinine was generated in situ during extrusion from both quinine base (5%, 10%, 20% w/w drug loading) and from quinine hydrochloride (5%, 10% w/w drug loading) and remained thermodynamically stable as a solid-in-solid dispersion within the HPC extrudates. When processed with HPC, quinine hydrochloride (20% w/w) was converted to amorphous quinine hydrochloride. Whilst stable for up to 3 months when stored under sealed conditions, this amorphous form was unstable, resulting in recrystallisation of the hydrochloride salt following storage for 1 month at 40 °C/75% relative humidity in an open glass jar. The behaviour of the amorphous quinine hydrochloride (20% w/w) HPC extrudate was related, at least in part, to the lower stability and the hygroscopic properties of this amorphous form.

Solubility parameter based screening methods for early stage formulation development of itraconazole amorphous solid dispersions

Objectives: This article uses conventional and newly extended solubility parameter (δ) methods to identify polymeric materials capable of forming amorphous dispersions with itraconazole (itz). Methods: Combinations of itz and Soluplus, Eudragit E PO (EPO), Kollidon 17PF (17PF) or Kollidon VA64 (VA64) were prepared as amorphous solid dispersions using quench cooling and hot melt extrusion. Storage stability was evaluated under a range of conditions using differential scanning calorimetry and powder X-ray diffraction. Key findings: The rank order of itz miscibility with polymers using both conventional and novel δ-based approaches was 17PF > VA64 > Soluplus > EPO, and the application of the Flory–Huggins lattice model to itz–excipient binary systems corroborated the findings. The solid-state characterisation analyses of the formulations manufactured by melt extrusion correlated well with pre-formulation screening. Long-term storage studies showed that the physical stability of 17PF/vitamin E TPGS–itz was poor compared with Soluplus and VA64 formulations, and for EPO/itz systems variation in stability may be observed depending on the preparation method. Conclusion: Results have demonstrated that although δ-based screening may be useful in predicting the initial state of amorphous solid dispersions, assessment of the physical behaviour of the formulations at relevant temperatures may be more appropriate for the successful development of commercially acceptable amorphous drug products.

Optimising drug solubilisation in amorphous polymer dispersions: rational selection of hot-melt extrusion processing parameters

The aim of this article was to construct a T–ϕ phase diagram for a model drug (FD) and amorphous polymer (Eudragit® EPO) and to use this information to understand the impact of how temperature–composition coordinates influenced the final properties of the extrudate. Defining process boundaries and understanding drug solubility in polymeric carriers is of utmost importance and will help in the successful manufacture of new delivery platforms for BCS class II drugs. Physically mixed felodipine (FD)–Eudragit® EPO (EPO) binary mixtures with pre-determined weight fractions were analysed using DSC to measure the endset of melting and glass transition temperature. Extrudates of 10 wt% FD–EPO were processed using temperatures (110°C, 126°C, 140°C and 150°C) selected from the temperature–composition (T–ϕ) phase diagrams and processing screw speed of 20, 100 and 200rpm. Extrudates were characterised using powder X-ray diffraction (PXRD), optical, polarised light and Raman microscopy. To ensure formation of a binary amorphous drug dispersion (ADD) at a specific composition, HME processing temperatures should at least be equal to, or exceed, the corresponding temperature value on the liquid–solid curve in a F–H T–ϕ phase diagram. If extruded between the spinodal and liquid–solid curve, the lack of thermodynamic forces to attain complete drug amorphisation may be compensated for through the use of an increased screw speed. Constructing F–H T–ϕ phase diagrams are valuable not only in the understanding drug–polymer miscibility behaviour but also in rationalising the selection of important processing parameters for HME to ensure miscibility of drug and polymer.

A Reliability Assessment Approach For Integrated Transportation and Electrical Power Systems Incorporating Electric Vehicles

With the increasing utilization of electric vehicles (EVs), transportation systems and electrical power systems are becoming increasingly coupled. However, the interaction between these two kinds of systems are not well captured, especially from the perspective of transportation systems. This paper studies the reliability of integrated transportation and electrical power system (ITES). A bidirectional EV charging control strategy is first demonstrated to model the interaction between the two systems. Thereafter, a simplified transportation system model is developed, whose high efficiency makes the reliability assessment of the ITES realizable with an acceptable accuracy. Novel transportation system reliability indices are then defined from the view point of EV’s driver. Based on the charging control model and the transportation simulation method, a daily periodic quasi sequential reliability assessment method is proposed for the ITES system. Case studies based on RBTS system demonstrate that bidirectional charging controls of EVs will benefit the reliability of power systems, while decrease the reliability of EVs travelling. Also, the optimal control strategy can be obtained based on the proposed method. Finally, case studies are performed based on a large scale test system to verify the practicability of the proposed method.