Precision Anti-Cancer Medicines by Oligonucleotide Therapeutics in Clinical Research Targeting Undruggable Proteins and Non-Coding RNAs

Cancer incidence and mortality continue to increase, while the conventional chemotherapeutic drugs confer limited efficacy and relevant toxic side effects. Novel strategies are urgently needed for more effective and safe therapeutics in oncology. However, a large number of proteins are considered undruggable by conventional drugs, such as the small molecules. Moreover, the mRNA itself retains oncological functions, and its targeting offers the double advantage of blocking the tumorigenic activities of the mRNA and the translation into protein. Finally, a large family of non-coding RNAs (ncRNAs) has recently emerged that are also dysregulated in cancer, but they could not be targeted by drugs directed against the proteins. In this context, this review describes how the oligonucleotide therapeutics targeting RNA or DNA sequences, are emerging as a new class of drugs, able to tackle the limitations described above. Numerous clinical trials are evaluating oligonucleotides for tumor treatment, and in the next few years some of them are expected to reach the market. We describe the oligonucleotide therapeutics targeting undruggable proteins (focusing on the most relevant, such as those originating from the MYC and RAS gene families), and for ncRNAs, in particular on those that are under clinical trial evaluation in oncology. We highlight the challenges and solutions for the clinical success of oligonucleotide therapeutics, with particular emphasis on the peculiar challenges that render it arduous to treat tumors, such as heterogeneity and the high mutation rate. In the review are presented these and other advantages offered by the oligonucleotide as an emerging class of biotherapeutics for a new era of precision anti-cancer medicine

Laser induced fluorescence for axion dark matter detection: a feasibility study in YLiF4_4:Er3+^{3+}

We present a detection scheme to search for QCD axion dark matter, that is based on a direct interaction between axions and electrons explicitly predicted by DFSZ axion models. The local axion dark matter field shall drive transitions between Zeeman-split atomic levels separated by the axion rest mass energy $m_a c^2$. Axion-related excitations are then detected with an upconversion scheme involving a pump laser that converts the absorbed axion energy ($\sim$ hundreds of $\mu$eV) to visible or infrared photons, where single photon detection is an established technique. The proposed scheme involves rare-earth ions doped into solid-state crystalline materials, and the optical transitions take place between energy levels of $4f^N$ electron configuration. Beyond discussing theoretical aspects and requirements to achieve a cosmologically relevant sensitivity, especially in terms of spectroscopic material properties, we experimentally investigate backgrounds due to the pump laser at temperatures in the range $1.9-4.2$ K. Our results rule out excitation of the upper Zeeman component of the ground state by laser-related heating effects, and are of some help in optimizing activated material parameters to suppress the multiphonon-assisted Stokes fluorescence.Comment: 8 pages, 5 figure

Particle detection through the quantum counter concept in YAG:Er3+^{3+}

We report about a novel scheme for particle detection based on the infrared quantum counter concept. Its operation consists of a two-step excitation process of a four level system, that can be realized in rare earth-doped crystals when a cw pump laser is tuned to the transition from the second to the fourth level. The incident particle raises the atoms of the active material into a low lying, metastable energy state, triggering the absorption of the pump laser to a higher level. Following a rapid non-radiative decay to a fluorescent level, an optical signal is observed with a conventional detectors. In order to demonstrate the feasibility of such a scheme, we have investigated the emission from the fluorescent level $^4$S$_{3/2}$ (540 nm band) in an Er$^{3+}$-doped YAG crystal pumped by a tunable titanium sapphire laser when it is irradiated with 60 keV electrons delivered by an electron gun. We have obtained a clear signature this excitation increases the $^{4}I_{13/2}$ metastable level population that can efficiently be exploited to generate a detectable optical signal

Simulation and performance of an artificial retina for 40 MHz track reconstruction

We present the results of a detailed simulation of the artificial retina pattern-recognition algorithm, designed to reconstruct events with hundreds of charged-particle tracks in pixel and silicon detectors at LHCb with LHC crossing frequency of $40\,\rm MHz$. Performances of the artificial retina algorithm are assessed using the official Monte Carlo samples of the LHCb experiment. We found performances for the retina pattern-recognition algorithm comparable with the full LHCb reconstruction algorithm.Comment: Final draft of WIT proceedings modified according to JINST referee's comment

The artificial retina for track reconstruction at the LHC crossing rate

We present the results of an R&D study for a specialized processor capable of precisely reconstructing events with hundreds of charged-particle tracks in pixel and silicon strip detectors at $40\,\rm MHz$, thus suitable for processing LHC events at the full crossing frequency. For this purpose we design and test a massively parallel pattern-recognition algorithm, inspired to the current understanding of the mechanisms adopted by the primary visual cortex of mammals in the early stages of visual-information processing. The detailed geometry and charged-particle's activity of a large tracking detector are simulated and used to assess the performance of the artificial retina algorithm. We find that high-quality tracking in large detectors is possible with sub-microsecond latencies when the algorithm is implemented in modern, high-speed, high-bandwidth FPGA devices.Comment: 3 pages, 3 figures, ICHEP14. arXiv admin note: text overlap with arXiv:1409.089

A Specialized Processor for Track Reconstruction at the LHC Crossing Rate

We present the results of an R&D study of a specialized processor capable of precisely reconstructing events with hundreds of charged-particle tracks in pixel detectors at 40 MHz, thus suitable for processing LHC events at the full crossing frequency. For this purpose we design and test a massively parallel pattern-recognition algorithm, inspired by studies of the processing of visual images by the brain as it happens in nature. We find that high-quality tracking in large detectors is possible with sub-$\mu$s latencies when this algorithm is implemented in modern, high-speed, high-bandwidth FPGA devices. This opens a possibility of making track reconstruction happen transparently as part of the detector readout.Comment: Presented by G.Punzi at the conference on "Instrumentation for Colliding Beam Physics" (INSTR14), 24 Feb to 1 Mar 2014, Novosibirsk, Russia. Submitted to JINST proceeding

The emotional side of software developers in JIRA

Issue tracking systems store valuable data for testing hypotheses concerning maintenance, building statistical prediction models and (recently) investigating developer affectiveness. For the latter, issue tracking systems can be mined to explore developers emotions, sentiments and politeness |affects for short. However, research on affect detection in software artefacts is still in its early stage due to the lack of manually validated data and tools. In this paper, we contribute to the research of affects on software artefacts by providing a labeling of emotions present on issue comments. We manually labeled 2,000 issue comments and 4,000 sentences written by developers with emotions such as love, joy, surprise, anger, sadness and fear. Labeled comments and sentences are linked to software artefacts reported in our previously published dataset (containing more than 1K projects, more than 700K issue reports and more than 2 million issue comments). The enriched dataset presented in this paper allows the investigation of the role of affects in software development

Influence of Anodizing by Electro-Chemical Oxidation on Fatigue and Wear Resistance of the EV31A-T6 Cast Magnesium Alloy

In the last decades, several anodizing processes for Mg alloys have been proposed to achieve a good wear and corrosion resistance combination. In particular, Electro-Chemical Oxidation (ECO) showed an improved dense and compact anodized layer compared to other anodizing processes carried out above the dielectric breakdown voltage, such as Plasma Electrolytic Oxidation (PEO). However, the influence of the ECO treatment on the tribological behavior and cyclic mechanical performance of Mg alloys has not been investigated yet. This paper reports on the influence of ECO on dry sliding behavior (vs. 100Cr6 bearing steel (block-on-ring contact geometry)) and rotating bending fatigue performance of the rare earth (RE)-containing Mg alloy EV31A-T6, comparing it with both untreated EV31A-T6 and PEO-treated EV31A-T6, used as benchmarks. The ECO-treated alloy showed improved tribological behavior (critical load for coating failure one order of magnitude higher and coefficient of friction 40% lower than for PEO) and fatigue strength (no decrease for ECO-treated samples compared to the untreated alloy, while PEO-treated samples induced a 15% decrease) due to the increased compactness and lower defectivity of the anodized layer, induced by the minimization of destructive arc discharges during coating growth. In addition, the ECO treatment significantly improved wear resistance compared to the untreated alloy, avoiding, at the same time, the decrease in fatigue strength, which typically occurs after PEO. Therefore, the ECO process can be applied to improve wear resistance without decreasing the fatigue strength of high-performance components

First prototype of a silicon tracker using an artificial retina for fast track finding

We report on the R\&D for a first prototype of a silicon tracker based on an alternative approach for fast track finding. The working principle is inspired from neurobiology, in particular by the processing of visual images by the brain as it happens in nature. It is based on extensive parallelisation of data distribution and pattern recognition. In this work we present the design of a practical device that consists of a telescope based on single-sided silicon detectors; we describe the data acquisition system and the implementation of the track finding algorithms using available digital logic of commercial FPGA devices. Tracking performance and trigger capabilities of the device are discussed along with perspectives for future applications.Comment: 9 pages, 7 figures, Technology and Instrumentation in Particle Physics 2014 (TIPP 2014), conference proceeding

Clinical signs of pneumonia in children: association with and prediction of diagnosis by fuzzy sets theory

The present study compares the performance of stochastic and fuzzy models for the analysis of the relationship between clinical signs and diagnosis. Data obtained for 153 children concerning diagnosis (pneumonia, other non-pneumonia diseases, absence of disease) and seven clinical signs were divided into two samples, one for analysis and other for validation. The former was used to derive relations by multi-discriminant analysis (MDA) and by fuzzy max-min compositions (fuzzy), and the latter was used to assess the predictions drawn from each type of relation. MDA and fuzzy were closely similar in terms of prediction, with correct allocation of 75.7 to 78.3% of patients in the validation sample, and displaying only a single instance of disagreement: a patient with low level of toxemia was mistaken as not diseased by MDA and correctly taken as somehow ill by fuzzy. Concerning relations, each method provided different information, each revealing different aspects of the relations between clinical signs and diagnoses. Both methods agreed on pointing X-ray, dyspnea, and auscultation as better related with pneumonia, but only fuzzy was able to detect relations of heart rate, body temperature, toxemia and respiratory rate with pneumonia. Moreover, only fuzzy was able to detect a relationship between heart rate and absence of disease, which allowed the detection of six malnourished children whose diagnoses as healthy are, indeed, disputable. The conclusion is that even though fuzzy sets theory might not improve prediction, it certainly does enhance clinical knowledge since it detects relationships not visible to stochastic models.The present study compares the performance of stochastic and fuzzy models for the analysis of the relationship between clinical signs and diagnosis. Data obtained for 153 children concerning diagnosis (pneumonia, other non-pneumonia diseases, absence of d375701709FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO01/04905-