989 resultados para Synthetic training devices


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A scalable synthetic muscle has been constructed that transducts nanoscale molecular shape changes into macroscopic motion. The working material, which deforms affinely in response to a pH stimulus, is a self-assembled block copolymer comprising nanoscopic hydrophobic domains in a weak polyacid matrix. A device has been assembled where the muscle does work on a cantilever and the force generated has been measured. When coupled to a chemical oscillator this provides a free running chemical motor that generates a peak power of 20 mW kg 1 by the serial addition of 10 nm shape changes that scales over 5 orders of magnitude. It is the nanostructured nature of the gel that gives rise to the affine deformation and results in a robust working material for the construction of scalable muscle devices.

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Eigenmodes and dispersion curves in different configurations of synthetic photonic lattices are studied numerically. Eigenmodes localized on borders between areas with different optical potential are found. Stability of these eigenmodes against potential disturbances of different type is studied.

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Synthetic biological systems promise to combine the spectacular diversity of biological functionality with engineering principles to design new life to address many pressing needs. As these engineered systems advance in sophistication, there is ever-greater need for customizable, situation-specific expression of desired genes. However, existing gene control platforms are generally not modular, or do not display performance requirements required for robust phenotypic responses to input signals. This work expands the capabilities of eukaryotic gene control in two important directions.

For development of greater modularity, we extend the use of synthetic self-cleaving ribozyme switches to detect changes in input protein levels and convey that information into programmed gene expression in eukaryotic cells. We demonstrate both up- and down-regulation of levels of an output transgene by more than 4-fold in response to rising input protein levels, with maximal output gene expression approaching the highest levels observed in yeast. In vitro experiments demonstrate protein-dependent ribozyme activity modulation. We further demonstrate the platform in mammalian cells. Our switch devices do not depend on special input protein activity, and can be tailored to respond to any input protein to which a suitable RNA aptamer can be developed. This platform can potentially be employed to regulate the expression of any transgene or any endogenous gene by 3’ UTR replacement, allowing for more complex cell state-specific reprogramming.

We also address an important concern with ribozyme switches, and riboswitch performance in general, their dynamic range. While riboswitches have generally allowed for versatile and modular regulation, so far their dynamic ranges of output gene modulation have been modest, generally at most 10-fold. We address this shortcoming by developing a modular genetic amplifier for near-digital control of eukaryotic gene expression. We combine ribozyme switch-mediated regulation of a synthetic TF with TF-mediated regulation of an output gene. The amplifier platform allows for as much as 20-fold regulation of output gene expression in response to input signal, with maximal expression approaching the highest levels observed in yeast, yet being tunable to intermediate and lower expression levels. EC50 values are more than 4 times lower than in previously best-performing non-amplifier ribozyme switches. The system design retains the modular-input architecture of the ribozyme switch platform, and the near-digital dynamic ranges of TF-based gene control.

Together, these developments suggest great potential for the wide applicability of these platforms for better-performing eukaryotic gene regulation, and more sophisticated, customizable reprogramming of cellular activity.

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In this paper, a musical learning application for mobile devices is presented. The main objective is to design and develop an application capable of offering exercises to practice and improve a selection of music skills, to users interested in music learning and training. The selected music skills are rhythm, melodic dictation and singing. The application includes an audio signal analysis system implemented making use of the Goertzel algorithm which is employed in singing exercises to check if the user sings the right musical note. This application also includes a graphical interface to represent musical symbols. A set of tests were conducted to check the usefulness of the application as musical learning tool. A group of users with different music knowledge have tested the system and reported to have found it effective, easy and accessible.

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Correctness of information gathered in production environments is an essential part of quality assurance processes in many industries, this task is often performed by human resources who visually take annotations in various steps of the production flow. Depending on the performed task the correlation between where exactly the information is gathered and what it represents is more than often lost in the process. The lack of labeled data places a great boundary on the application of deep neural networks aimed at object detection tasks, moreover supervised training of deep models requires a great amount of data to be available. Reaching an adequate large collection of labeled images through classic techniques of data annotations is an exhausting and costly task to perform, not always suitable for every scenario. A possible solution is to generate synthetic data that replicates the real one and use it to fine-tune a deep neural network trained on one or more source domains to a different target domain. The purpose of this thesis is to show a real case scenario where the provided data were both in great scarcity and missing the required annotations. Sequentially a possible approach is presented where synthetic data has been generated to address those issues while standing as a training base of deep neural networks for object detection, capable of working on images taken in production-like environments. Lastly, it compares performance on different types of synthetic data and convolutional neural networks used as backbones for the model.

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As a consequence of the diffusion of next generation sequencing techniques, metagenomics databases have become one of the most promising repositories of information about features and behavior of microorganisms. One of the subjects that can be studied from those data are bacteria populations. Next generation sequencing techniques allow to study the bacteria population within an environment by sampling genetic material directly from it, without the needing of culturing a similar population in vitro and observing its behavior. As a drawback, it is quite complex to extract information from those data and usually there is more than one way to do that; AMR is no exception. In this study we will discuss how the quantified AMR, which regards the genotype of the bacteria, can be related to the bacteria phenotype and its actual level of resistance against the specific substance. In order to have a quantitative information about bacteria genotype, we will evaluate the resistome from the read libraries, aligning them against CARD database. With those data, we will test various machine learning algorithms for predicting the bacteria phenotype. The samples that we exploit should resemble those that could be obtained from a natural context, but are actually produced by a read libraries simulation tool. In this way we are able to design the populations with bacteria of known genotype, so that we can relay on a secure ground truth for training and testing our algorithms.

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Sexual dysfunction (SD) affects up to 80% of multiple sclerosis (MS) patients and pelvic floor muscles (PFMs) play an important role in the sexual function of these patients. The objective of this paper is to evaluate the impact of a rehabilitation program to treat lower urinary tract symptoms on SD of women with MS. Thirty MS women were randomly allocated to one of three groups: pelvic floor muscle training (PFMT) with electromyographic (EMG) biofeedback and sham neuromuscular electrostimulation (NMES) (Group I), PFMT with EMG biofeedback and intravaginal NMES (Group II), and PFMT with EMG biofeedback and transcutaneous tibial nerve stimulation (TTNS) (Group III). Assessments, before and after the treatment, included: PFM function, PFM tone, flexibility of the vaginal opening and ability to relax the PFMs, and the Female Sexual Function Index (FSFI) questionnaire. After treatment, all groups showed improvements in all domains of the PERFECT scheme. PFM tone and flexibility of the vaginal opening was lower after the intervention only for Group II. All groups improved in arousal, lubrication, satisfaction and total score domains of the FSFI questionnaire. This study indicates that PFMT alone or in combination with intravaginal NMES or TTNS contributes to the improvement of SD.

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The present study investigated the effects of running at 0.8 or 1.2 km/h on inflammatory proteins (i.e., protein levels of TNF- α , IL-1 β , and NF- κ B) and metabolic proteins (i.e., protein levels of SIRT-1 and PGC-1 α , and AMPK phosphorylation) in quadriceps of rats. Male Wistar rats at 3 (young) and 18 months (middle-aged rats) of age were divided into nonexercised (NE) and exercised at 0.8 or 1.2 km/h. The rats were trained on treadmill, 50 min per day, 5 days per week, during 8 weeks. Forty-eight hours after the last training session, muscles were removed, homogenized, and analyzed using biochemical and western blot techniques. Our results showed that: (a) running at 0.8 km/h decreased the inflammatory proteins and increased the metabolic proteins compared with NE rats; (b) these responses were lower for the inflammatory proteins and higher for the metabolic proteins in young rats compared with middle-aged rats; (c) running at 1.2 km/h decreased the inflammatory proteins and increased the metabolic proteins compared with 0.8 km/h; (d) these responses were similar between young and middle-aged rats when trained at 1.2 km. In summary, the age-related increases in inflammatory proteins, and the age-related declines in metabolic proteins can be reversed and largely improved by treadmill training.

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We describe herein a general method for the controlled Heck arylation of allylated malonates. Both electron-rich and electron-poor aryldiazonium salts were readily employed as the aryl-transfer agents in good yields and in high chemo-, regio-, and stereoselectivity without formation of decarboxylated byproducts. Reaction monitoring via ESI-MS was used to support the formation of chelated Pd species through the catalytic cycle. Additionally, some Heck adducts were successfully used in the total synthesis of pharmacologically active γ-lactones.

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To investigate the effects of a specific protocol of undulatory physical resistance training on maximal strength gains in elderly type 2 diabetics. The study included 48 subjects, aged between 60 and 85 years, of both genders. They were divided into two groups: Untrained Diabetic Elderly (n=19) with those who were not subjected to physical training and Trained Diabetic Elderly (n=29), with those who were subjected to undulatory physical resistance training. The participants were evaluated with several types of resistance training's equipment before and after training protocol, by test of one maximal repetition. The subjects were trained on undulatory resistance three times per week for a period of 16 weeks. The overload used in undulatory resistance training was equivalent to 50% of one maximal repetition and 70% of one maximal repetition, alternating weekly. Statistical analysis revealed significant differences (p<0.05) between pre-test and post-test over a period of 16 weeks. The average gains in strength were 43.20% (knee extension), 65.00% (knee flexion), 27.80% (supine sitting machine), 31.00% (rowing sitting), 43.90% (biceps pulley), and 21.10% (triceps pulley). Undulatory resistance training used with weekly different overloads was effective to provide significant gains in maximum strength in elderly type 2 diabetic individuals.

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Paper has become increasingly recognized as a very interesting substrate for the construction of microfluidic devices, with potential application in a variety of areas, including health diagnosis, environmental monitoring, immunoassays and food safety. The aim of this review is to present a short history of analytical systems constructed from paper, summarize the main advantages and disadvantages of fabrication techniques, exploit alternative methods of detection such as colorimetric, electrochemical, photoelectrochemical, chemiluminescence and electrochemiluminescence, as well as to take a closer look at the novel achievements in the field of bioanalysis published during the last 2 years. Finally, the future trends for production of such devices are discussed.

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In the work, the in vitro antiproliferative activity of a series of synthetic fatty acid amides were investigated in seven cancer cell lines. The study revealed that most of the compounds showed antiproliferative activity against tested tumor cell lines, mainly on human glioma cells (U251) and human ovarian cancer cells with a multiple drug-resistant phenotype (NCI-ADR/RES). In addition, the fatty methyl benzylamide derived from ricinoleic acid (with the fatty acid obtained from castor oil, a renewable resource) showed a high selectivity with potent growth inhibition and cell death for the glioma cell line-the most aggressive CNS cancer.

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Endurance exercise training as well as leucine supplementation modulates glucose homeostasis and protein turnover in mammals. Here, we analyze whether leucine supplementation alters the effects of endurance exercise on these parameters in healthy mice. Mice were distributed into sedentary (C) and exercise (T) groups. The exercise group performed a 12-week swimming protocol. Half of the C and T mice, designated as the CL and TL groups, were supplemented with leucine (1.5 % dissolved in the drinking water) throughout the experiment. As well known, endurance exercise training reduced body weight and the retroperitoneal fat pad, increased soleus mass, increased VO2max, decreased muscle proteolysis, and ameliorated peripheral insulin sensitivity. Leucine supplementation had no effect on any of these parameters and worsened glucose tolerance in both CL and TL mice. In the soleus muscle of the T group, AS-160(Thr-642) (AKT substrate of 160 kDa) and AMPK(Thr-172) (AMP-Activated Protein Kinase) phosphorylation was increased by exercise in both basal and insulin-stimulated conditions, but it was reduced in TL mice with insulin stimulation compared with the T group. Akt phosphorylation was not affected by exercise but was lower in the CL group compared with the other groups. Leucine supplementation increased mTOR phosphorylation at basal conditions, whereas exercise reduced it in the presence of insulin, despite no alterations in protein synthesis. In trained groups, the total FoxO3a protein content and the mRNA for the specific isoforms E2 and E3 ligases were reduced. In conclusion, leucine supplementation did not potentiate the effects of endurance training on protein turnover, and it also reduced its positive effects on glucose homeostasis.