FUNCTIONAL PROPERTIES OF PROTEIN ISOLATE EXTRACTED FROM BEEF BONES

Bone protein isolate (BPI) extracted from beef bones with 2% added salt (i) and without salt (ii) has been analysed for functional properties as these properties are of importance when the protein isolate is used in different industries. Water absorption by the bone protein isolate (i) and (ii) was 0.35 and 0.46 H2O/g protein, respectively. The minimum solubility of protein isolate (i) was 65.85% at pH 3 while isolated protein (ii) had a minimum solubility of 52.30% at pH 5. An increase in solubility was observed below and above pH 3 for the protein isolate (i) (83.66% at pH 1 and 87.12% at pH 11) and below and above pH 5 for protein isolate (ii) (83.20% at pH 1 and 89.78% at pH 11). The emulsifying capacity of the BPI is great, being much better than that of many classical proteins (sodium caseinate, soy protein isolate). The emulsifying capacity (ml oil/g protein) progressively decreased with increasing protein concentration. On the other hand, alkaline pH improved the mentioned property more than acidic pH. The maximum emulsifying capacity was 1152.60 and 986.78 ml oil/g protein at pH 9 for protein isolate (i) and (ii) respectively. The best foaming capacity was observed at pH 4 for both protein isolates (i) and (ii) (96% and 89% volume increase, respectively). Foams had also high stability at pH 4, having 145 ml and 138 ml final volume for isolates (i) and (ii), respectively. The stability of foams decreased with increase in pH. Both protein isolates obtained had high solubility (NSI) and dispersibility (PDI); being 97.98%, 86.78% for NSI and 99.94%, 89.06% for PDI in case of isolates (i) and (ii). respectively. Such isolates had a satisfactory protein solubility in the pH range existing in many food products

Dark-Bright Solitons in Inhomogeneous Bose-Einstein Condensates

We investigate dark-bright vector solitary wave solutions to the coupled non-linear Schr\"odinger equations which describe an inhomogeneous two-species Bose-Einstein condensate. While these structures are well known in non-linear fiber optics, we show that spatial inhomogeneity strongly affects their motion, stability, and interaction, and that current technology suffices for their creation and control in ultracold trapped gases. The effects of controllably different interparticle scattering lengths, and stability against three-dimensional deformations, are also examined.Comment: 5 pages, 5 figure

Recombinase polymerase amplification assay for rapid detection of lumpy skin disease virus

Background  Lumpy skin disease virus (LSDV) is aCapripoxvirusinfecting cattle and Buffalos. Lumpy skin disease (LSD) leads to significant economic losses due to hide damage, reduction of milk production, mastitis, infertility and mortalities (10 %). Early detection of the virus is crucial to start appropriate outbreak control measures. Veterinarians rely on the presence of the characteristic clinical signs of LSD. Laboratory diagnostics including virus isolation, sequencing and real-time polymerase chain reaction (PCR) are performed at well-equipped laboratories. In this study, a portable, simple, and rapid recombinase polymerase amplification (RPA) assay for the detection of LSDV-genome for the use on farms was developed.  Results  The LSDV RPA assay was performed at 42 °C and detected down to 179 DNA copies/reaction in a maximum of 15 min. Unspecific amplification was observed with neither LSDV-negative samples (n= 12) nor nucleic acid preparations from orf virus, bovine papular stomatitis virus, cowpoxvirus, Peste des petits ruminants and Blue tongue virus (serotypes 1, 6 and 8). The clinical sensitivity of the LSDV RPA assay matched 100 % (n= 22) to real-time PCR results. In addition, the LSDV RPA assay detected sheep and goat poxviruses.  Conclusion  The LSDV RPA assay is a rapid and sensitive test that could be implemented in field or at quarantine stations for the identification of LSDV infected case

The quassinoid derivative NBT-272 targets both the AKT and ERK signaling pathways in embryonal tumors

The quassinoid analogue NBT-272 has been reported to inhibit MYC, thus warranting a further effort to better understand its preclinical properties in models of embryonal tumors (ET), a family of childhood malignancies sharing relevant biological and genetic features such as deregulated expression of MYC oncogenes. In our study, NBT-272 displayed a strong anti-proliferative activity in vitro that resulted from the combination of diverse biological effects, ranging from G1/S arrest of the cell cycle to apoptosis and autophagy. The compound prevented the full activation of both the eukaryotic initiation factor 4E (eIF4E) and its binding protein 4EBP-1, regulating cap-dependent protein translation. Interestingly, all responses induced by NBT-272 in ET could be attributed to interference with two main pro-proliferative signaling pathways, i.e. the AKT and the MEK/extracellular signal-regulated kinase (ERK) pathways. These findings also suggested that the depleting effect of NBT-272 on MYC protein expression occurred via indirect mechanisms, rather than selective inhibition. Finally, the ability of NBT-272 to arrest tumor growth in a xenograft model of neuroblastoma plays a role in the strong anti-tumor activity of this compound, both in vitro and in vivo, with its potential to target cell-survival pathways that are relevant for the development and progression of ET

In vivo effects of interferon-Γ and anti-interferon-Γ antibody on the experimentally induced lichenoid tissue reaction

We investigated the in vivo effect of recombinant interferon-Γ (IFN-Γ) and tumour necrosis factor Α (TNF-Α) treatment of mice on the development of the delayed-type hypersensitivity (DTH) reaction and lichenoid tissue reaction (LTR) following the local injection of cloned autoreactive T cells. Both the DTH reaction and the LTR were significantly enhanced by pre-treatment with IFN-Γ, but not with TNF-Ã. Induction of class II MHC antigens on keratinocytes was not essential for the enhancement by IFN-Γ. Administration of anti-IFN-Γ antibody reduced the DTH reaction and LTR, although complete inhibition was not observed with our treatment regimen. The ability of IFN-Γ to increase the number of the cloned T cells invading the epidermis in vivo , is in keeping with our previous observation that IFN-Γ treatment of cultured keratinocytes markedly increased the adherence reaction between T cells and keratinocytes in vitro.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74579/1/j.1365-2133.1988.tb03202.x.pd

Magnetoplasmonic design rules for active magneto-optics

Light polarization rotators and non-reciprocal optical isolators are essential building blocks in photonics technology. These macroscopic passive devices are commonly based on magneto-optical Faraday and Kerr polarization rotation. Magnetoplasmonics - the combination of magnetism and plasmonics - is a promising route to bring these devices to the nanoscale. We introduce design rules for highly tunable active magnetoplasmonic elements in which we can tailor the amplitude and sign of the Kerr response over a broad spectral range

Computer Aided Autism Diagnosis Using Diffusion Tensor Imaging

© 2013 IEEE. Autism Spectrum Disorder (ASD), commonly known as autism, is a lifelong developmental disorder associated with a broad range of symptoms including difficulties in social interaction, communication skills, and restricted and repetitive behaviors. In autism spectrum disorder, numerous studies suggest abnormal development of neural networks that manifest itself as abnormalities of brain shape, functionality, and/ or connectivity. The aim of this work is to present our automated computer aided diagnostic (CAD) system for accurate identification of autism spectrum disorder based on the connectivity of the white matter (WM) tracts. To achieve this goal, two levels of analysis are provided for local and global scores using diffusion tensor imaging (DTI) data. A local analysis using the Johns Hopkins WM atlas is exploited for DTI atlas-based segmentation. Furthermore, WM integrity is examined by extracting the most notable features representing WM connectivity from DTI. Interactions of WM features between different areas in the brain, demonstrating correlations between WM areas were used, and feature selection among those associations were made. Finally, a leave-one-subject-out classifier is employed to yield a final per-subject decision. The proposed system was tested on a large dataset of 263 subjects from the National Database of Autism Research (NDAR) with their Autism Diagnostic Observation Schedule (ADOS) scores and diagnosis (139 typically developed: 66 males, and 73 females, and 124 autistics: 66 males, and 58 females), with ages ranging from 96 to 215 months, achieving an overall accuracy of 73%. In addition to this achieved global accuracy, diagnostically-important brain areas were identified, allowing for a better understanding of ASD-related brain abnormalities, which is considered as an essential step towards developing early personalized treatment plans for children with autism spectrum disorder

Early assessment of lung function in coronavirus patients using invariant markers from chest X-rays images

The primary goal of this manuscript is to develop a computer assisted diagnostic (CAD) system to assess pulmonary function and risk of mortality in patients with coronavirus disease 2019 (COVID-19). The CAD system processes chest X-ray data and provides accurate, objective imaging markers to assist in the determination of patients with a higher risk of death and thus are more likely to require mechanical ventilation and/or more intensive clinical care.To obtain an accurate stochastic model that has the ability to detect the severity of lung infection, we develop a second-order Markov-Gibbs random field (MGRF) invariant under rigid transformation (translation or rotation of the image) as well as scale (i.e., pixel size). The parameters of the MGRF model are learned automatically, given a training set of X-ray images with affected lung regions labeled. An X-ray input to the system undergoes pre-processing to correct for non-uniformity of illumination and to delimit the boundary of the lung, using either a fully-automated segmentation routine or manual delineation provided by the radiologist, prior to the diagnosis. The steps of the proposed methodology are: (i) estimate the Gibbs energy at several different radii to describe the inhomogeneity in lung infection; (ii) compute the cumulative distribution function (CDF) as a new representation to describe the local inhomogeneity in the infected region of lung; and (iii) input the CDFs to a new neural network-based fusion system to determine whether the severity of lung infection is low or high. This approach is tested on 200 clinical X-rays from 200 COVID-19 positive patients, 100 of whom died and 100 who recovered using multiple training/testing processes including leave-one-subject-out (LOSO), tenfold, fourfold, and twofold cross-validation tests. The Gibbs energy for lung pathology was estimated at three concentric rings of increasing radii. The accuracy and Dice similarity coefficient (DSC) of the system steadily improved as the radius increased. The overall CAD system combined the estimated Gibbs energy information from all radii and achieved a sensitivity, specificity, accuracy, and DSC of 100%, 97% ± 3%, 98% ± 2%, and 98% ± 2%, respectively, by twofold cross validation. Alternative classification algorithms, including support vector machine, random forest, naive Bayes classifier, K-nearest neighbors, and decision trees all produced inferior results compared to the proposed neural network used in this CAD system. The experiments demonstrate the feasibility of the proposed system as a novel tool to objectively assess disease severity and predict mortality in COVID-19 patients. The proposed tool can assist physicians to determine which patients might require more intensive clinical care, such a mechanical respiratory support

Diffraction-limited ultrabroadband terahertz spectroscopy

Diffraction is the ultimate limit at which details of objects can be resolved in conventional optical spectroscopy and imaging systems. In the THz spectral range, spectroscopy systems increasingly rely on ultra-broadband radiation (extending over more 5 octaves) making a great challenge to reach resolution limited by diffraction. Here, we propose an original easy-to-implement wavefront manipulation concept to achieve ultrabroadband THz spectroscopy system with diffraction-limited resolution. Applying this concept to a large-area photoconductive emitter, we demonstrate diffraction-limited ultra-broadband spectroscopy system up to 14.5 THz with a dynamic range of 103. The strong focusing of ultrabroadband THz radiation provided by our approach is essential for investigating single micrometer-scale objects such as graphene flakes or living cells, and besides for achieving intense ultra-broadband THz electric fields