Mesenchymal stem cells promote alveolar epithelial cell wound repair in vitro through distinct migratory and paracrine mechanisms.

BACKGROUND: Mesenchymal stem cells (MSC) are in clinical trials for widespread indications including musculoskeletal, neurological, cardiac and haematological disorders. Furthermore, MSC can ameliorate pulmonary fibrosis in animal models although mechanisms of action remain unclear. One emerging concept is that MSCs may have paracrine, rather than a functional, roles in lung injury repair and regeneration. METHODS: To investigate the paracrine role of human MSC (hMSC) on pulmonary epithelial repair, hMSC-conditioned media (CM) and a selected cohort of hMSC-secretory proteins (identified by LC-MS/MS mass spectrometry) were tested on human type II alveolar epithelial cell line A549 cells (AEC) and primary human small airway epithelial cells (SAEC) using an in vitro scratch wound repair model. A 3D direct-contact wound repair model was further developed to assess the migratory properties of hMSC. RESULTS: We demonstrate that MSC-CM facilitates AEC and SAEC wound repair in serum-dependent and -independent manners respectively via stimulation of cell migration. We also show that the hMSC secretome contains an array of proteins including Fibronectin, Lumican, Periostin, and IGFBP-7; each capable of influencing AEC and SAEC migration and wound repair stimulation. In addition, hMSC also show a strong migratory response to AEC injury as, supported by the observation of rapid and effective AEC wound gap closure by hMSC in the 3D model. CONCLUSION: These findings support the notion for clinical application of hMSCs and/or their secretory factors as a pharmacoregenerative modality for the treatment of idiopathic pulmonary fibrosis (IPF) and other fibrotic lung disorders

Homozygosity Mapping and Genetic Analysis of Autosomal Recessive Retinal Dystrophies in 144 Consanguineous Pakistani Families.

PurposeThe Pakistan Punjab population has been a rich source for identifying genes causing or contributing to autosomal recessive retinal degenerations (arRD). This study was carried out to delineate the genetic architecture of arRD in the Pakistani population.MethodsThe genetic origin of arRD in a total of 144 families selected only for having consanguineous marriages and multiple members affected with arRD was examined. Of these, causative mutations had been identified in 62 families while only the locus had been identified for an additional 15. The remaining 67 families were subjected to homozygosity exclusion mapping by screening of closely flanking microsatellite markers at 180 known candidate genes/loci followed by sequencing of the candidate gene for pathogenic changes.ResultsOf these 67 families subjected to homozygosity mapping, 38 showed homozygosity for at least one of the 180 regions, and sequencing of the corresponding genes showed homozygous cosegregating mutations in 27 families. Overall, mutations were detected in approximately 61.8 % (89/144) of arRD families tested, with another 10.4% (15/144) being mapped to a locus but without a gene identified.ConclusionsThese results suggest the involvement of unmapped novel genes in the remaining 27.8% (40/144) of families. In addition, this study demonstrates that homozygosity mapping remains a powerful tool for identifying the genetic defect underlying genetically heterogeneous arRD disorders in consanguineous marriages for both research and clinical applications

Learning Moore Machines from Input-Output Traces

The problem of learning automata from example traces (but no equivalence or membership queries) is fundamental in automata learning theory and practice. In this paper we study this problem for finite state machines with inputs and outputs, and in particular for Moore machines. We develop three algorithms for solving this problem: (1) the PTAP algorithm, which transforms a set of input-output traces into an incomplete Moore machine and then completes the machine with self-loops; (2) the PRPNI algorithm, which uses the well-known RPNI algorithm for automata learning to learn a product of automata encoding a Moore machine; and (3) the MooreMI algorithm, which directly learns a Moore machine using PTAP extended with state merging. We prove that MooreMI has the fundamental identification in the limit property. We also compare the algorithms experimentally in terms of the size of the learned machine and several notions of accuracy, introduced in this paper. Finally, we compare with OSTIA, an algorithm that learns a more general class of transducers, and find that OSTIA generally does not learn a Moore machine, even when fed with a characteristic sample

Design of a Novel High-Efficiency Class-F/E Power Amplifier

This paper introduces a compact Class-F/E power amplifier (PA) that eliminates the need for RF choke LRFC and incorporates a parallel resonant filter. The parallel resonant filter filters out the third harmonic of the switch current, thereby reducing the switch current stress on the PA. Additionally, design equations for calculating the component values are provided. To validate these equations, a prototype circuit was designed and simulated. At a operating frequency of 430 MHz, the simulated output power, drain efficiency, and gain of the prototype PA are 40.9 dBm, 79%, and 10.9 dB, respectively

Design of Novel High-Efficiency Inverse Class-E Power Amplifier

In this study, we provide a theoretical examination of an innovative inverse Class-E power amplifier (PA) incorporating a shunt filter to achieve optimal performance. We derive idealized waveforms and load parameters, verifying these through frequency domain simulations. The findings indicate that the performance of inverse Class-E PA does not consistently increase with higher parasitic output capacitance. The ideal switch voltage and current waveforms suggest the potential for reaching 100% efficiency. We offer design examples using both lumped elements and transmission lines. To validate our theoretical predictions, we conducted measurements on the transmission line inverse Class-E. The simulation and measurement results closely align, showing a maximum drain efficiency of 82%/81% and a power-added efficiency of 75%/74.8%. Furthermore, an output power of 40.5/40.3 dBm and a power gain of 11.0/10.3 dB were achieved in the saturation region

The antioxidant activity of some curcuminoids and chalcones

The antioxidant properties of the synthetic compound (C1)–(C8), which comprised 7 curcuminoids and a chalcone, were evaluated by two complementary assays, DPPH and β-carotene/linoleic acid. It was found that, in general, the free radical scavenging ability of (C1)–(C8) was concentration-dependent. Compounds (C1) and (C4), which contained (4-OH) phenolic groups, were found to be highly potent antioxidants with higher antioxidant values than BHT suggesting that synthetic curcuminoids are more potent antioxidants than standard antioxidants like BHT. Using β-carotene-linoleic acid assay, only the water-soluble 2, 4,6-trihydroxyphenolic chalcone (C5) showed 85.2 % inhibition of the formation of conjugated dienes reflecting on its potent antioxidant activity

Electronic Tuning of Zinc Oxide by Direct Fabrication of Chromium (Cr) incorporated photoanodes for Visible-light driven Water Splitting Applications

This is the final version. Available on open access from Nature Research via the DOI in this recordHerein, we report the synthesis of Cr incorporated ZnO sheets arrays microstructures and construction of photoelectrode through a direct aerosol assisted chemical vapour deposition (AACVD) method. The as-prepared Cr incorporated ZnO microstructures were characterized by transmission electron microscopy, scanning electron microscopy, energy dispersive X-ray spectroscopy, powdered X-ray spectroscopy, X-ray photoelectron spectroscopy and UV-Vis diffused reflectance spectroscopy. The Cr incorporation in ZnO red shifted the optical band gap of as-prepared photoanodes. The 15% Cr incorporation in ZnO has shown enhanced PEC performance. The AACVD method provides an efficient in situ incorporation approach for the manipulation of morphological aspects, phase purity, and band structure of photoelectrodes for an enhanced PEC performance.Higher Education Commission of PakistanUniversity of Mancheste

Regression model for the study of sole and cumulative effect of temperature and solar radiation on wheat yield

The effect of variability in temperature, solar radiation and photothermal quotient were studied under varying planting windows in three wheat genotypes to cope environmental vulnerability. Regression models are regarded as valuable tools for the evaluation of temperature, solar radiation and photothermal quotient effects on wheat yield to bring its resilience to climatic vulnerability. The objective of this study was to evaluate sole and cumulative impact of temperature and solar radiation on spring wheat (Triticum aestivum L.) yield using regression modeling approach. The data collected at maturity for grain number, grain weight and grain yield were regressed against mean temperature, solar radiation and photothermal quotient (PTQ) (temperature plus solar radiation) from emergence to anthesis and maturity, using STATISTICA9 software. Scatter-plot regression model was developed at 95% confidence interval with crop data and climate variables. Results indicate direct relationship of yield with solar radiation, cumulative effect of temperature and solar radiation, whereas yield had an inverse relationship with temperature alone. Direct relationship between PTQ and yield parameters confirmed PTQ as crop-yield determinant, thus, its management needs to be done by choosing a more appropriate sowing time and best suited genotypes as an adapted management strategy for farmers under increased climatic vulnerability.Key words: Photothermal quotient, planting windows, solar radiation, temperature, wheat

Computational Models of Auditory Scene Analysis: A Review

Auditory scene analysis (ASA) refers to the process(es) of parsing the complex acoustic input into auditory perceptual objects representing either physical sources or temporal sound patterns, such as melodies, which contributed to the sound waves reaching the ears. A number of new computational models accounting for some of the perceptual phenomena of ASA have been published recently. Here we provide a theoretically motivated review of these computational models, aiming to relate their guiding principles to the central issues of the theoretical framework of ASA. Specifically, we ask how they achieve the grouping and separation of sound elements and whether they implement some form of competition between alternative interpretations of the sound input. We consider the extent to which they include predictive processes, as important current theories suggest that perception is inherently predictive, and also how they have been evaluated. We conclude that current computational models of ASA are fragmentary in the sense that rather than providing general competing interpretations of ASA, they focus on assessing the utility of specific processes (or algorithms) for finding the causes of the complex acoustic signal. This leaves open the possibility for integrating complementary aspects of the models into a more comprehensive theory of ASA