Molecular cloning of a novel melanocortin receptor

Using the technique of the polymerase chain reaction primed with oligonucleotides based on the homologous transmembrane regions of seven transmembrane G protein-linked receptors, we isolated three full-length human genes that encode a novel subgroup of this receptor family. Recently, two of these receptors were identified as specific for alpha-melanocyte-stimulating hormone (alpha-MSH) and adrenocorticotropic hormone. We report the molecular cloning and pharmacologic characterization of a third member of this subgroup. The gene for this receptor encodes a protein of 361 amino acids in length. Its pharmacology characterizes it as an MSH receptor specific to the heptapeptide core common to adrenocorticotropic hormone and alpha-, beta-, and gamma-MSH. By Northern blot hybridization and polymerase chain reaction, it is expressed in brain, placental, and gut tissues but not in melanoma cells or in the adrenal gland. These findings may yield insight into the physiology of peptides derived from pro-opiomelanocortin post-translational processing.     

Optical scattering in beef steak to predict tenderness using hyperspectral imaging in the VIS-NIR region

The objective of this research is to develop a non-destructive method for predicting cooked beef tenderness using optical scattering of light on fresh beef muscle tissue. A hyperspectral imaging system (λ = 496–1,036 nm) that consists of a CCD camera and an imaging spectrograph, was used to acquire beef steak images. The hyperspectral image consisted of 120 bands with spectral intervals of 4.54 nm. Sixty-one fresh beef steaks, including 44 strip loin and 17 tenderloin cuts, were collected. After imaging, the steaks were cooked and Warner-Bratzler shear (WBS) force values were collected as tenderness references. The optical scattering profiles were derived from the hyperspectral images and fitted to the modified Lorentzian function. Parameters, such as the peak height, full scattering width at half maximum (FWHM), and the slope around the FWHM were determined at each wavelength. Stepwise regression was used to identify 7 key wavelengths and parameters. The parameters were then used to predict the WBS scores. The model was able to predict WBS scores with an R = 0.67. Optical scattering implemented with hyperspectral imaging shows limited success for predicting current status of tenderness in beef steak.     

A Newly Developed Synbiotic Yogurt Prevents Diabetes by Improving the Microbiome–Intestine–Pancreas Axis

The prevalence of type 2 diabetes mellitus (T2D) is increasing worldwide, and there are no long-term preventive strategies to stop this growth. Emerging research shows that perturbations in the gut microbiome significantly contribute to the development of T2D, while microbiome modulators may be beneficial for T2D prevention. However, microbiome modulators that are effective, safe, affordable, and able to be administered daily are not yet available. Based on our previous pro- and prebiotic studies, we developed a novel synbiotic yogurt comprised of human-origin probiotics and plant-based prebiotics and investigated its impact on diet- and streptozotocin-induced T2D in mice. We compared the effects of our synbiotic yogurt to those of a commercially available yogurt (control yogurt). Interestingly, we found that the feeding of the synbiotic yogurt significantly reduced the development of hyperglycemia (diabetes) in response to high-fat diet feeding and streptozotocin compared to milk-fed controls. Surprisingly, the control yogurt exacerbated diabetes progression. Synbiotic yogurt beneficially modulated the gut microbiota composition compared to milk, while the control yogurt negatively modulated it by significantly increasing the abundance of detrimental bacteria such as Proteobacteria and Enterobacteriaceae. In addition, the synbiotic yogurt protected pancreatic islet morphology compared to the milk control, while the control yogurt demonstrated worse effects on islets. These results suggest that our newly developed synbiotic yogurt protects against diabetes in mice and can be used as a therapeutic to prevent diabetes progression.     

Maternal Exposure to Dibutyl Phthalate (DBP) or Diethylstilbestrol (DES) Leads to Long-Term Changes in Hypothalamic Gene Expression and Sexual Behavior

Xenobiotic exposure during pregnancy and lactation has been linked to perinatal changes in male reproductive outcomes and other endocrine parameters. This pilot study wished to assess whether brief maternal exposure of rats to xenobiotics dibutyl phthalate (DBP) or diethylstilbestrol (DES) might also cause long-term changes in hypothalamic gene expression or in reproductive behavior of the resulting offspring. Time-mated female Sprague Dawley rats were given either DBP (500 mg/kg body weight, every second day from GD14.5 to PND6), DES (125 µg/kg body weight at GD14.5 and GD16.5 only), or vehicle (n = 8–12 per group) and mild endocrine disruption was confirmed by monitoring postnatal anogenital distance. Hypothalamic RNA from male and female offspring at PND10, PND24 and PND90 was analyzed by qRT-PCR for expression of aromatase, oxytocin, vasopressin, ER-alpha, ER-beta, kisspeptin, and GnRH genes. Reproductive behavior was monitored in male and female offspring from PND60 to PND90. Particularly, DES treatment led to significant changes in hypothalamic gene expression, which for the oxytocin gene was still evident at PND90, as well as in sexual behavior. In conclusion, maternal xenobiotic exposure may not only alter endocrine systems in offspring but, by impacting on brain development at a critical time, can have long-term effects on male or female sexual behavior.     

A facile antistatic modification of polyester fiber based on ion-exchange reaction of sulfonate-modified polyester and various cationic surfactants

A new technique for imparting antistatic properties to poly(ethylene terephthalate) (PET) fiber has been developed. In this technique, blend polyester fibers containing poly(ethylene terephthalate/5-sulfoisophthalate) (SIP-PET) were prepared by blend spinning and then treated with various cationic surfactants in the process of dyeing. The surfactants could effectively be immobilized on the fiber as the counter cations of the sulfonate groups of the 5-sulfoisophthalate (SIP) units and aid the release of static electrons formed in the fiber. Thus, the half-life time (t_1/2) of leakage of static charge and the surface resistivity (Rs) of the blend PET fibers became much lower after treating. The best result was obtained with a methylated quaternary ammonium salt of a stearylamine-ethylene oxide (EO) adduct or hydrochloride of a laurylamine-EO adduct as the surfactant of which the number of EO units was around ten. Even after five washing cycles the t_1/2 value of the fibers treated with these surfactants was kept lower than 30 s with the Rs value maintained in the order of 10¹³ Ω cm^-2. Therefore, the present technique could be useful for practical production of polyester fibers with “semi-permanent” antistatic properties which can be recovered by re-treatment even if they were lost.     

Uncertainty propagation in puff-based dispersion models using polynomial chaos

Atmospheric dispersion is a complex nonlinear physical process with numerous uncertainties in model parameters, inputs, source parameters, initial and boundary conditions. Accurate propagation of these uncertainties through the dispersion models is crucial for a reliable prediction of the probability distribution of the states and assessment of risk. A simple three-dimensional Gaussian puff-based dispersion model is used as a test case to study the effect of uncertainties in the model parameters and initial conditions on the output concentration. A polynomial chaos based approach is used to numerically investigate the evolution of the model output uncertainties due to initial condition and parametric uncertainties. The polynomial chaos solution is found to be an accurate approximation to ground truth, established by Monte Carlo simulation, while offering an efficient computational approach for large nonlinear systems with a relatively small number of uncertainties.     

DeepKnuckle: revealing the human identity

Multimedia Tools and Applications - Identification and authentication are ubiquitous questions which pan across various systems. In certain domains, they are of paramount importance. Like, security...     

Linear stochastic approximation driven by slowly varying Markov chains

We study a linear stochastic approximation algorithm that arises in the context of reinforcement learning. The algorithm employs a decreasing step-size, and is driven by Markov noise with time-varying statistics. We show that under suitable conditions, the algorithm can track the changes in the statistics of the Markov noise, as long as these changes are slower than the rate at which the step-size of the algorithm goes to zero.     

Quantitative analysis of microstructure refinement in ultrafine-grained strips of Al6063 fabricated using large strain extrusion machining

Abstract

In present research work, ultrafine-grained strips of Al-6063 alloy were fabricated using hybrid extrusion machining technique known as “large strain extrusion machining (LSEM).” Fabrication of strips was done using the customized HSS tools of different rake angles varying from 0° to 10° under different machining conditions. Microstructural and mechanical characterizations of these strips were done to ascertain the effect of different parameters on their properties. From the results of hardness measurement of strips, it was concluded that hardness of the strips increased by 34–97% of the base material as of the refinement of grain size occurred. Surface lay was improved by 30% with higher cutting velocity and rake angle. Crystallite size was found to decrease with increase in the rate of strain. The shear strain was increased as chip compression ratio increased and rake angle decreased. Fabrication ability of strips increased due to increase in strain hardening exponent and it may result in the large scope of their applications. Nano-hardness of the strips was found to be more than bulk alloy. These above said results showed that ultrafine strips fabricated using LSEM process can become a good choice for future material fabrication.