Production and purification of polyclonal anti-hamster immunoglobulins in rabbits

Polyclonal antibodies are mixtures of monoclonal antibodies that were produced against different epitops. The goal of this project is to know the production, purification and horseradish peroxidase (HRP) conjugation of polyclonal antibodies against hamster immunoglobulins in rabbits. 300 ìg/300 ìl of ten hamster immunoglobulins was mixed with the same volume (300 ìl) of adjuvant and injected into three 6-month-old white New Zealand rabbits. Anti hamster rich rabbits serums were isolated from whole blood and precipitated with ammonium sulfate in the final concentration of 50%. The precipitate was dialysed against phosphate buffered saline (PBS) (pH: 7.4) and applied to ion exchange chromatography (IEC) on diethylaminoethyl (DEAE)-sepharose 6B with tris-phosphate (pH: 8.1), andtris-phosphate contain 50 mM NaCl buffer. The purity of produced antibody was confirmed by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) under reduced condition. Then purifiedimmunoglobulin G (IgG) was conjugated with HRP. For exact measurement of conjugated IgG titer and evaluating of cross reaction, enzyme linked immunosorbent assay (ELISA) test was designed. Since IEC is a more simple and inexpensive method for the purification of IgG, we obtained a protein with approximate purity of 95%. Produced IgG showed high titer and high specificity in the designed ELISA. Purified antibody and its conjugation with HRP are used in research and diagnosis of hamster disease.Key words: Production, purification, hamster immunoglobulins

Commuting varieties of rr-tuples over Lie algebras

Let $G$ be a simple algebraic group defined over an algebraically closed field $k$ of characteristic $p$ and let \g be the Lie algebra of $G$. It is well known that for $p$ large enough the spectrum of the cohomology ring for the $r$-th Frobenius kernel of $G$ is homeomorphic to the commuting variety of $r$-tuples of elements in the nilpotent cone of \g [Suslin-Friedlander-Bendel, J. Amer. Math. Soc, \textbf{10} (1997), 693--728]. In this paper, we study both geometric and algebraic properties including irreducibility, singularity, normality and Cohen-Macaulayness of the commuting varieties C_r(\mathfrak{gl}_2), C_r(\fraksl_2) and $C_r(\N)$ where $\N$ is the nilpotent cone of \fraksl_2. Our calculations lead us to state a conjecture on Cohen-Macaulayness for commuting varieties of $r$-tuples. Furthermore, in the case when \g=\fraksl_2, we obtain interesting results about commuting varieties when adding more restrictions into each tuple. In the case of \fraksl_3, we are able to verify the aforementioned properties for C_r(\fraku). Finally, applying our calculations on the commuting variety C_r(\overline{\calO_{\sub}}) where \overline{\calO_{\sub}} is the closure of the subregular orbit in \fraksl_3, we prove that the nilpotent commuting variety $C_r(\N)$ has singularities of codimension $\ge 2$.Comment: To appear in Journal of Pure and Applied Algebr

Laser-induced breakdown spectroscopy: a tool for real-time, in vitro and in vivo identification of carious teeth

BACKGROUND: Laser Induced Breakdown Spectroscopy (LIBS) can be used to measure trace element concentrations in solids, liquids and gases, with spatial resolution and absolute quantifaction being feasible, down to parts-per-million concentration levels. Some applications of LIBS do not necessarily require exact, quantitative measurements. These include applications in dentistry, which are of a more "identify-and-sort" nature – e.g. identification of teeth affected by caries. METHODS: A one-fibre light delivery / collection assembly for LIBS analysis was used, which in principle lends itself for routine in vitro / in vivo applications in a dental practice. A number of evaluation algorithms for LIBS data can be used to assess the similarity of a spectrum, measured at specific sample locations, with a training set of reference spectra. Here, the description has been restricted to one pattern recognition algorithm, namely the so-called Mahalanobis Distance method. RESULTS: The plasma created when the laser pulse ablates the sample (in vitro / in vivo), was spectrally analysed. We demonstrated that, using the Mahalanobis Distance pattern recognition algorithm, we could unambiguously determine the identity of an "unknown" tooth sample in real time. Based on single spectra obtained from the sample, the transition from caries-affected to healthy tooth material could be distinguished, with high spatial resolution. CONCLUSIONS: The combination of LIBS and pattern recognition algorithms provides a potentially useful tool for dentists for fast material identification problems, such as for example the precise control of the laser drilling / cleaning process

The effects of cold working on sensitization and intergranular corrosion behavior of AISI 304 stainless steel

The effects of prior cold rolling of up to an 80 pct reduction in thickness on the sensitization-desensitization behavior of Type AISI 304 stainless steel and its susceptibility to intergranular corrosion have been studied by electrochemical potentiokinetic reactivation (EPR) and Strauss-test methods. The results indicate that the prior deformation accelerated the sensitization as compared to the undeformed stainless steel. The deformed Type 304 stainless steel experienced desensitization at higher temperatures and times, and it was found to be enhanced by increased cold deformation. This could be attributed to the increased long-range chromium diffusion, possibly brought on by increasing pipe diffusion and vacancies. The role of the deformation-induced martensite (DIM) and texture, introduced by uniaxial cold rolling, on the sensitization-desensitization kinetics has also been discussed. This study could not reveal any systematic relationship between texture and the degree of sensitization (DOS) obtained. The effect of DIM on DOS seems to be pronounced at 500 °C when the steel retained significant amounts of DIM; however, the retained DIM is insignificant at higher sensitization times and temperatures

Hourly Price-Based Demand Response for Optimal Scheduling of Integrated Gas and Power Networks Considering Compressed Air Energy Storage

Gas-fired plants are becoming an optimal and practical choice for power generation in electricity grids due to high efficiency and less emissions. Such plants with fast start-up capability and high ramp rate are flexible in response to stochastic load variations. Meanwhile, gas system constraints affect the flexibility and participation of such units in the energy market. Compressed air energy storage (CAES) as a flexible source with high ramp rate can be an alternative solution to reduce the impact of gas system constraints on the operation cost of a power system. In addition, demand response (DR) programs are expressed as practical approaches to overcome peak-demand challenges. This study introduces a stochastic unit commitment scheme for coordinated operation of gas and power systems with CAES technology as well as application of an hourly price-based DR. The introduced model is performed on a six-bus system with a six-node gas system to verify the satisfactory performance of the model

Magnetic responsive cell-based strategies for diagnostics and therapeutics

The potential of magnetically assisted strategies within the remit of cell-based therapies is increasing, creating new opportunities for biomedical platforms and in the field of tissue engineering and regenerative medicine. Among the magnetic elements approached for building magnetically responsive strategies, superparamagnetic iron oxide nanoparticles (SPIONs) represent tunable and precise tools whose properties can be modelled for detection, diagnosis, targeting and therapy purposes. The most investigated clinical role of SPIONs is as contrast imaging agents for tracking and monitoring cells and tissues. Nevertheless, magnetic detection also includes biomarker mapping, cell labelling and cell/drug targeting to monitor cell events and anticipate the disruption of homeostatic conditions and the progression of disease. Additionally, the isolation and screening techniques of cell subsets in heterogeneous populations or of proteins of interest have been explored in a magnetic sorting context. More recently, SPION-based technologies have been applied to stimulate cell differentiation and mechanotransduction processes and to transport genetic or drug cargo to study biological mechanisms and contribute to improved therapies. Magnetically based strategies significantly contribute to magnetic tissue engineering (magTE), in which magnetically responsive actuators built from magnetic labelled cells or magnetic functionalized systems can be remotely controlled and spatially manipulated upon the actuation of an external magnetic field for the delivery or target of TE solutions. SPION functionalities combined with magnetic responsiveness in multifactorial magnetically assisted platforms can revolutionize diagnosis and therapeutics, providing new diagnosis and theranostic tools, encouraging regenerative medicine approaches and having potential for more effective therapies. This review will address the contribution of SPION-based technologies as multifunctional tools in boosting magnetically assisted cell-based strategies to explore diagnostics and tracking solutions for the detection and analysis of pathologies, and to generate improved treatments and therapies, envisioning precise and customized answers for the management of numerous diseases.The authors acknowledge the BPD_RL2_DECEMBER_2017fellowship of AIG and the assistant researcher contract (RL1) of MTR from the project ‘Accelerating Tissue Engineering and Personalized Medicine Discoveries by the Integration of Key Enabling Nanotechnologies, Marine-derived Biomaterials and Stem Cells’, supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). The authors also thank the financial support from FCT for the grant of MSM (SFRH/BPD/110868/2015). The authors acknowledge the financial support from the European Union Framework Programme for Research and Innovation HORIZON 2020, under the TEAMING grant agreement no. 739572—the Discoveries CTR.info:eu-repo/semantics/publishedVersio

Mesenchymal Cell-Derived Juxtacrine Wnt1 Signaling Regulates Osteoblast Activity and Osteoclast Differentiation

Human genetic evidence demonstrates that WNT1 mutations cause osteogenesis imperfecta (OI) and early‐onset osteoporosis, implicating WNT1 as a major regulator of bone metabolism. However, its main cellular source and mechanisms of action in bone remain elusive. We generated global and limb bud mesenchymal cell–targeted deletion of Wnt1 in mice. Heterozygous deletion of Wnt1 resulted in mild trabecular osteopenia due to decreased osteoblast function. Targeted deletion of Wnt1 in mesenchymal progenitors led to spontaneous fractures due to impaired osteoblast function and increased bone resorption, mimicking the severe OI phenotype in humans with homozygous WNT1 mutations. Importantly, we showed for the first time that Wnt1 signals strictly in a juxtacrine manner to induce osteoblast differentiation and to suppress osteoclastogenesis, in part via canonical Wnt signaling. In conclusion, mesenchymal cell‐derived Wnt1, acting in short range, is an essential regulator of bone homeostasis and an intriguing target for therapeutic interventions for bone diseases.</p

Ribbon Crystals

A repetitive crystal-like pattern is spontaneously formed upon the twisting of straight ribbons. The pattern is akin to a tessellation with isosceles triangles, and it can easily be demonstrated with ribbons cut from an overhead transparency. We give a general description of developable ribbons using a ruled procedure where ribbons are uniquely described by two generating functions. This construction defines a differentiable frame, the ribbon frame, which does not have singular points, whereby we avoid the shortcomings of the Frenet-Serret frame. The observed spontaneous pattern is modeled using planar triangles and cylindrical arcs, and the ribbon structure is shown to arise from a maximization of the end-to-end length of the ribbon, i.e. from an optimal use of ribbon length. The phenomenon is discussed in the perspectives of incompatible intrinsic geometries and of the emergence of long-range order

Data mining of high density genomic variant data for prediction of Alzheimer's disease risk

<p>Abstract</p> <p>Background</p> <p>The discovery of genetic associations is an important factor in the understanding of human illness to derive disease pathways. Identifying multiple interacting genetic mutations associated with disease remains challenging in studying the etiology of complex diseases. And although recently new single nucleotide polymorphisms (SNPs) at genes implicated in immune response, cholesterol/lipid metabolism, and cell membrane processes have been confirmed by genome-wide association studies (GWAS) to be associated with late-onset Alzheimer's disease (LOAD), a percentage of AD heritability continues to be unexplained. We try to find other genetic variants that may influence LOAD risk utilizing data mining methods.</p> <p>Methods</p> <p>Two different approaches were devised to select SNPs associated with LOAD in a publicly available GWAS data set consisting of three cohorts. In both approaches, single-locus analysis (logistic regression) was conducted to filter the data with a less conservative p-value than the Bonferroni threshold; this resulted in a subset of SNPs used next in multi-locus analysis (random forest (RF)). In the second approach, we took into account prior biological knowledge, and performed sample stratification and linkage disequilibrium (LD) in addition to logistic regression analysis to preselect loci to input into the RF classifier construction step.</p> <p>Results</p> <p>The first approach gave 199 SNPs mostly associated with genes in calcium signaling, cell adhesion, endocytosis, immune response, and synaptic function. These SNPs together with <it>APOE and GAB2 </it>SNPs formed a predictive subset for LOAD status with an average error of 9.8% using 10-fold cross validation (CV) in RF modeling. Nineteen variants in LD with <it>ST5, TRPC1, ATG10, ANO3, NDUFA12, and NISCH </it>respectively, genes linked directly or indirectly with neurobiology, were identified with the second approach. These variants were part of a model that included <it>APOE </it>and <it>GAB2 </it>SNPs to predict LOAD risk which produced a 10-fold CV average error of 17.5% in the classification modeling.</p> <p>Conclusions</p> <p>With the two proposed approaches, we identified a large subset of SNPs in genes mostly clustered around specific pathways/functions and a smaller set of SNPs, within or in proximity to five genes not previously reported, that may be relevant for the prediction/understanding of AD.</p