Induction of apoptosis by a short-chain neuropeptide analog in small cell lung cancer

Small cell lung cancer (SCLC) cells express a variety of neuropeptides which act as autocrine growth factors. Although several neuropeptide analogs have been reported to antagonize SCLC proliferation, the development of these compounds has been limited by their low potency and the cytostatic nature of their effects. In the present study we evaluated the cytotoxic activity of four short-chain substance P analogs (NY3460, NY3238[-pHOPA], NY3238[Phe1], NY3238[Lys5]) against a panel of five SCLC cell lines. NY3460 was the most potent compound in all five SCLC cell lines (IC50 = 2.8-3.7 microM) as assessed by a MTT growth inhibitory assay. NY3238[Phe1] was also relatively active in all cell lines (IC50 = 3.5-11.2 microM), while NY3238[Lys5] and NY3238[-pHOPA] were substantially less active. NY3460 was the only agent to induce an increase in the percentage of cells with subdiploid DNA content suggestive of apoptosis by flow cytometric DNA content analysis. The induction of apoptosis was confirmed by fluorescent microscopy in NCI-H69, NCI-H82, NCI-H446, and NCI-H510 cells after exposure to 5.0 microM NY3460 for 48 h. These findings suggest that NY3460 is a relatively potent cytotoxic inhibitor of SCLC growth, and that short-chain neuropeptide analogs deserve further evaluation as anti-SCLC agents.     

A finite element analysis of temperature in accelerated cutting

Temperature attained during machining has significant effects on the properties of tool, chip and workpiece. It governs the parameters like shear angle, cutting force, tool wear, surface finish etc. Review of literature reveals that hardly any information is available about the analytical determination of the tool-chip interface temperature and the temperature distribution during the accelerated cutting.

This paper presents the temperature analysis of accelerated cutting (i.e. taper turning and facing) as well as longitudinal turning, using the finite element technique. It has been concluded that the temperature distribution within the tool-chip-work system and the average tool-chip interface temperature for the two classes of machining (viz longitudinal turning and accelerated cutting) are not the same, even though the conditions of machining are identical. Further, the average tool-chip interface temperature is lowest in case of facing and highest in case of longitudinal turning.     

Chemical composition, antioxidant and antibacterial properties of the essential oils of Etlingera elatior and Cinnamomum pubescens Kochummen

BACKGROUND: Plant essential oils are widely used as fragrances and flavours. Therefore, the essential oils from the leaves of Cinnamomum pubescens Kochummen (CP) and the whole plant of Etlingera elatior (EE) were investigated for their antioxidant, antibacterial and phytochemical properties. RESULTS: CP and EE were found to contain appreciable levels of total phenolic contents (50.6 and 33.41 g kg^?1 as gallic acid equivalent) and total flavonoid contents (205.6 and 244.8 g kg^?1 as rutin equivalent), respectively. DPPH free radical scavenging activity of CP is superior to EE (P < 0.05) showing IC₅₀ of 77.2 and 995.1 µg mL^?1, respectively. Methicillin‐resistant Staphylococcus aureus (MRSA), Bacillus subtilis, Pseudomonas aeruginosa and Salmonella choleraesuis were tested against CP and EE. Only MRSA was the most susceptible bacteria to CP. GC/MS studies resulted in the identification of 79 and 73 compounds in CP and EE, respectively. The most abundant components of EE included β‐pinene (24.92%) and 1‐dodecene (24.31%). While the major compound in CP were 1,6‐octadien‐3‐ol,3,7‐dimethyl (11.55%), cinnamaldehyde (56.15%) and 1‐phenyl‐propane‐2,2‐diol diethanoate (11.38%). CONCLUSION: This study suggests that the essential oils from Cinnamomum pubescens Kochummen and Etlingera elatior could be potentially used as a new source of natural antioxidant and antibacterial in the food and pharmaceutical industries. Copyright © 2010 Society of Chemical Industry     

Correction to: Two New Co(II) Complexes of Picolinate: Synthesis,Crystal Structure,Spectral Characterization, α-Glucosidase İnhibition and TD/DFT Study

Journal of Inorganic and Organometallic Polymers and Materials -     

Touch sensor and photovoltaic characteristics of CuSbS2 thin films

Spin-coated chalcostibite CuSbS₂ thin films (≈500 nm thick) were fabricated and the influence of the drying temperature on the structural, morphological, optical and thermoelectric properties of the films was investigated. Crystalline phase-pure chalcostibite has been obtained for the films dried at 180 °C and 210 °C, while below 180 °C these films are partially amorphous. Surprisingly, at drying temperature of 240 °C, a Cu_xS secondary phase appeared. The increase of the drying temperature leads to the increase of the particle size and the decrease of the optical band gap, which is interesting for optoelectronic applications. The highest power factor value was achieved for the film dried at 210 °C, due to the inexistence of secondary phases, which allowed realizing a stable thermoelectric touch sensor with a V_signal/_noise of 5. In addition, this film was tested as a photovoltaic (PV) device and a power conversion efficiency (PCE) of 0.030% with an open-circuit voltage (V_OC) of 0.36 V, a short-circuit current density (J_SC) of 0.278 mAcm^?2 and a fill factor (FF) of 0.27 were obtained. Therefore, this work evidences a pathway toward developing bi-functional devices with simultaneously thermoelectric touch sensor and photovoltaic functions.     

Performance Evaluation of Supervised Machine Learning Techniques for Efficient Detection of Emotions from Online Content

Emotion detection from the text is a challenging problem in the text analytics. The opinion mining experts are focusing on the development of emotion detection applications as they have received considerable attention of online community including users and business organization for collecting and interpreting public emotions. However, most of the existing works on emotion detection used less efficient machine learning classifiers with limited datasets, resulting in performance degradation. To overcome this issue, this work aims at the evaluation of the performance of different machine learning classifiers on a benchmark emotion dataset. The experimental results show the performance of different machine learning classifiers in terms of different evaluation metrics like precision, recall ad f-measure. Finally, a classifier with the best performance is recommended for the emotion classification.     

Delayed recognition of Judah Folkman’s hypothesis on tumor angiogenesis: when a Prince awakens a Sleeping Beauty by self-citation

In research evaluation of single researchers, the assessment of paper and journal impact is of interest. High journal impact reflects the ability of researchers to convince strict reviewers, and high paper impact reflects the usefulness of papers for future research. In many bibliometric studies, metrics for journal and paper impact are separately presented. In this paper, we introduce two graph types, which combine both metrics in a single graph. The graphs can be used in research evaluation to visualize the performance of single researchers comprehensively.     

Solving comprehensive dynamic job shop scheduling problem by using a GRASP-based approach

There are many dynamic events like new order arrivals, machine breakdowns, changes in due dates, order cancellations, arrival of urgent orders etc. that makes static scheduling approaches very difficult. A dynamic scheduling strategy should be adopted under such production circumstances. In the present study an event driven dynamic job shop scheduling mechanism under machine capacity constraints is proposed. The proposed method makes use of the greedy randomised adaptive search procedure (GRASP) by also taking into account orders due dates and sequence-dependent set-up times. Moreover, order acceptance/rejection decision and Order Review Release mechanism are integrated with scheduling decision in order to meet customer due date requirements while attempting to execute capacity adjustments. We employed a goal programming-based logic which is used to evaluate four objectives: mean tardiness, schedule unstability, makespan and mean flow time. Benchmark problems including number of orders, number of machines and different dynamic events are generated. In addition to event-driven rescheduling strategy, a periodic rescheduling strategy is also devised and both strategies are compared for different problems. Experimental studies are performed to evaluate effectiveness of the proposed method. Obtained results have proved that the proposed method is a feasible approach for rescheduling problems under dynamic environments.     

Optical and Electron Spin Resonance Studies of Destruction of Porous Structures Formed by Nitrogen–Rare Gas Nanoclusters in Bulk Superfluid Helium

We studied optical and electron spin resonance spectra during destruction of porous structures formed by nitrogen–rare gas (RG) nanoclusters in bulk superfluid helium containing high concentrations of stabilized nitrogen atoms. Samples were created by injecting products of a radio frequency discharge of nitrogen–rare gas–helium gas mixtures into bulk superfluid helium. These samples have a high energy density allowing the study of energy release in chemical processes inside of nanocluster aggregates. The rare gases used in the studies were neon, argon, and krypton. We also studied the effects of changing the relative concentrations between nitrogen and rare gas on thermoluminescence spectra during destruction of the samples. At the beginning of the destructions, \(\alpha \)-group of nitrogen atoms, Vegard–Kaplan bands of \(\hbox {N}_2\) molecules, and \(\beta \)-group of O atoms were observed. The final destruction of the samples were characterized by a series bright flashes. Spectra obtained during these flashes contain M- and \(\beta \)-bands of NO molecules, the intensities of which depend on the concentration of molecular nitrogen in the gas mixture as well as the type of rare gas present in the gas mixture.     

Hybrid Computational Modeling for Web Application Security Assessment

Transformation from conventional business management systems to smart digital systems is a recurrent trend in the current era. This has led to digital revolution, and in this context, the hardwired technologies in the software industry play a significant role However, from the beginning, software security remains a serious issue for all levels of stakeholders. Software vulnerabilities lead to intrusions that cause data breaches and result in disclosure of sensitive data, compromising the organizations’ reputation that translates into, financial losses as well. Most of the data breaches are financially motivated, especially in the healthcare sector. The cyber invaders continuously penetrate the E-Health data because of the high cost of the data on the dark web. Therefore, security assessment of healthcare web-based applications demands immediate intervention mechanisms to weed out the threats of cyber-attacks. The aim of this work is to provide efficient and effective healthcare web application security assessment. The study has worked with the hybrid computational model of Multi-Criteria Decision Making (MCDM) based on Analytical Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal-Solutions (TOPSIS) under the Hesitant Fuzzy (HF) environment. Hesitant fuzzy sets provide effective solutions to address decision making problems where experts counter hesitation to make a decision. The proposed research endeavor will support designers and developers in identifying, selecting and prioritizing the best security attributes for web applications’ development. The empirical analysis concludes that Robustness got highest priority amongst the assessed security attributes set followed by Encryption, Authentication, Limit Access, Revoke Access, Data Validation, and Maintain Audit Trail. The results of this research endeavor depict that this proposed computational procedure would be the most conversant mechanism for determining the web application security. The study also establishes guidelines which the developers can refer for the identification and prioritization of security attributes to build more secure and trustworthy web-based applications.