Long Non-Coding RNA ANRIL as a Potential Biomarker of Chemosensitivity and Clinical Outcomes in Osteosarcoma

Simple SummaryOsteosarcoma is a bone cancer with a poor prognosis. This is, in part, due to resistance to current standard-of-care chemotherapeutic treatment. As personalized treatment plans become more widely utilized, the role of patient-specific genome markers may serve to identify individuals with chemo-resistant disease at the outset of diagnosis. ANRIL, a long non-coding RNA, has promise as a predictive biomarker. Utilizing osteosarcoma cell lines, we observed that altering the expression of ANRIL significantly alters the sensitivity to cisplatin and doxorubicin, two agents that are a standard-of-care for treatment. Analysis of clinical data from the TARGET dataset confirmed higher ANRIL expression portending poorer prognosis, as evidenced by association with death and metastases at diagnosis.AbstractOsteosarcoma has a poor prognosis due to chemo-resistance and/or metastases. Increasing evidence shows that long non-coding RNAs (lncRNAs) can play an important role in drug sensitivity and cancer metastasis. Using osteosarcoma cell lines, we identified a positive correlation between the expression of a lncRNA and ANRIL, and resistance to two of the three standard-of-care agents for treating osteosarcoma—cisplatin and doxorubicin. To confirm the potential role of ANRIL in chemosensitivity, we independently inhibited and over-expressed ANRIL in osteosarcoma cell lines followed by treatment with either cisplatin or doxorubicin. Knocking-down ANRIL in SAOS2 resulted in a significant increase in cellular sensitivity to both cisplatin and doxorubicin, while the over-expression of ANRIL in both HOS and U2OS cells led to an increased resistance to both agents. To investigate the clinical significance of ANRIL in osteosarcoma, we assessed ANRIL expression in relation to clinical phenotypes using the osteosarcoma data from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) dataset. Higher ANRIL expression was significantly associated with increased rates of metastases at diagnosis and death and was a significant predictor of reduced overall survival rate. Collectively, our results suggest that the lncRNA ANRIL can be a chemosensitivity and prognosis biomarker in osteosarcoma. Furthermore, reducing ANRIL expression may be a therapeutic strategy to overcome current standard-of-care treatment resistance.     

Facile polyacrylamide graft based on poly (2-chloroaniline) silver nano-composites as antimicrobial

Series of polymers based on the grafting of polyacrylamide with both poly(2-methoxyaniline) P2-MeOANI and poly(2-chloroaniline) P2-ClANI were synthesized by the oxidative chemical grafting copolymerization of individually 2-methoxyaniline (2-MeOANI) and 2-chloroaniline (2-ClANI) onto polyacrylamide (PACM). The grafting was performed in aqueous hydrochloric acid solution (HCl) using ammonium persulfate (APS) as oxidant. The optimum conditions of the grafting based on the yield was achieved. The obtained polymer samples at optimum conditions were assembling on colloidal silver nanoparticles (AgNPs). The obtained polymer samples and their AgNPs were characterized by UV- visible & IR spectroscopy, EM, TEM & TGA to confirm the suggested structure of obtained polymers. The efficiency of the prepared polymeric samples to using as anti-microbial including as sulfate reducing bacteria (SRB) was investigated.     

Thermal properties and formation mechanism of h‐BN nanoneedles synthesized via carbothermic reduction reaction

Hexagonal boron nitride (BN) was synthesized through the carbothermic reduction reaction (CRR) of boric acid using lactose as a carbon source under the nitrogen atmosphere at 1500^°C for 3 hours. The boron/carbon (B/C) molar ratio was controlled during the CRR, and the produced samples were investigated by XRD diffraction pattern, FTIR analysis, and Raman spectra. Boron carbide (B₄C) was formed in samples that have a higher carbon content, in addition to boron nitride. While boron nitride pure sample was produced from lower carbon content samples. Formation of B₄C was found to depend on the B/C molar ratio. The morphology of the produced powder was also investigated by SEM and TEM, which revealed that the samples consist of nanoneedles of BN and hexagonal particles of B₄C. The vapor‐solid (VS) reaction mechanism was processed greatly with increasing boron amount, producing boron nitride nanoneedles, which compete with the liquid‐solid (LS) reaction mechanism. The physicochemical properties of the produced samples were studied by DTA, UV, PL, and AC impedance measurements, and revealed that the samples are promising to many proper applications.     

Composing Specific Domains for Large Scale Systems

DSM （domain-specific modeling） offers many advantages over general purpose modeling, but this type of modeling is effective just in narrow domains. The recent MDE （model driven engineering） approaches seek to provide a technology to compose different specific domains in order to cover large scale systems. In this context, this article proposes a new approach for composing specific domain models. First, we analyze some related works. On the basis of the key findings and conclusions drawn from the analysis, we propose a multidimensional approach based on the composition of crosscutting concerns contained in the source domain models. The approach is illustrated by a composition of service domains.     

Power CoolMOS transistor electrothermal model for PSpice simulation

Analog Integrated Circuits and Signal Processing - Electrothermal modeling and simulation of power electronics semiconductors are crucial for the efficient optimization of power electronics...     

Deep Reinforcement Learning-Based Job Shop Scheduling ofSmartManufacturing

Industry 4.0 production environments and smart manufacturing systems integrate both the physical and decision-making aspects of manufacturing operations into autonomous and decentralized systems. One of the key aspects of these systems is a production planning, specifically, Scheduling operations on the machines. To cope with this problem, this paper proposed a Deep Reinforcement Learning with an Actor-Critic algorithm (DRLAC). We model the Job-Shop Scheduling Problem (JSSP) as a Markov Decision Process (MDP), represent the state of a JSSP as simple Graph Isomorphism Networks (GIN) to extract nodes features during scheduling, and derive the policy of optimal scheduling which guides the included node features to the best next action of schedule. In addition, we adopt the Actor-Critic (AC) network’s training algorithm-based reinforcement learning for achieving the optimal policy of the scheduling. To prove the proposed model’s effectiveness, first, we will present a case study that illustrated a conflict between two job scheduling, secondly, we will apply the proposed model to a known benchmark dataset and compare the results with the traditional scheduling methods and trending approaches. The numerical results indicate that the proposed model can be adaptive with real-time production scheduling, where the average percentage deviation (APD) of our model achieved values between 0.009 and 0.21 compared with heuristic methods and values between 0.014 and 0.18 compared with other trending approaches.     

The Impact of Ni Substitution on the Structural and Magnetic Properties of Mg Nano-Ferrite

Magnesium substituted nickel nano-ferrite Mg_1−xNi_xFe₂O₄ (x = 0.0, 0.1, 0.3, 0.5, 0.7, and 1.0) was synthesized by the citrate-gel auto-combustion method. Synthesized powders were sintered at 600 ^∘C for 4 hours and characterized by X-ray, High Transmission Electron Microscopy, Brunauer-Emmett-Teller, Atomic Force Microscopy and Energy Dispersive X-ray Spectroscopy analyses. The impact of replacing Mg ions by Ni on the structural parameters and magnetic properties of the system was investigated utilizing X-ray diffraction and χ–T magnetic measurements at room and low temperatures. The crystallite sizes were found in the range of 24.6 nm – 27.6 nm. The variation of lattice parameter, the roughness, surface area and the porosity size upon increasing the Ni content were determined and then correlated with the cation distribution and the magnetic behavior. The coercivity (H_c) values vary from 56.4 Oe to 130 Oe. These values make the investigated samples well suited for their use in recording media. Magnetic parameters such as saturation magnetization, and Curie temperature (T_c) assured the existence of a critical concentration at x = 0.3 in which the anomalous character appeared.

     

The effects of oral iron supplementation on cognition in older children and adults: a systematic review and meta-analysis

Background  

In observational studies anaemia and iron deficiency are associated with cognitive deficits, suggesting that iron supplementation may improve cognitive function. However, due to the potential for confounding by socio-economic status in observational studies, this needs to be verified in data from randomised controlled trials (RCTs).     

Odd clipping optical orthogonal frequency division multiplexing for VLC system

The Orthogonal Frequency Division Multiplexing (OFDM) has emerged as one of the promising techniques because of its robustness to multipath fading with high‐speed data transmission. Classical bipolar OFDM cannot be used in intensity modulated with direct detection (IM/DD) optical communication systems, as visible light communication (VLC), so many optical modulation techniques as asymmetrical clipped optical OFDM (ACO‐OFDM) and DC‐Clipped OFDM (DCO‐OFDM) have been investigated. In this paper, we introduce a novel optical modulation scheme that meets the optical communications requirements. The proposed odd clipping optical OFDM technique (OCO‐OFDM) is based on the Fourier transform symmetry properties in which the imaginary and odd signal is converted to odd and real valued signal. As a result of this work, the proposed OCO‐OFDM and its modified version have several benefits over ACO‐OFDM and DCO‐OFDM. By introducing a better bit error rate, with the same spectral efficiency as DCO‐OFDM and the same power efficiency as ACO‐OFDM for real valued modulation technique as Binary Phase‐Shift Keying (BPSK), and with the same spectral efficiency and power efficiency as ACO‐OFDM for complex valued modulation technique as Quadrature Phase‐Shift Keying (QPSK) and Eight Phase‐Shift Keying (8PSK).     

Viscosity decrease by interfacial slippage between immiscible polymers

The rheological behavior under pressure-driven shear flow was studied using binary blends with a sea-island structure. The addition of a low-viscosity dispersion having a high interfacial tension with the continuous phase greatly reduces the shear viscosity, for example, the addition of atactic polystyrene (PS) with a low viscosity to isotactic polypropylene (PP) and the addition of PP with a low viscosity to PS. The interfacial slippage occurs because of the poor adhesive strength with the enlarged interfacial area and is responsible for the viscosity decrease. When the dispersion has a similar viscosity to the continuous phase, the viscosity decrease is barely detected. This is because the deformation of dispersed droplets is restricted, which creates a small interfacial area. The interfacial tension between the continuous and dispersed phases plays a crucial role on the shear viscosity. In the case of PP, the addition of linear low-density polyethylene with a relatively low interfacial tension to PP has almost no impact on the shear viscosity. This is despite the polyethylene having a low viscosity.