Human Plasma Protein Corona of Aβ Amyloid and Its Impact on Islet Amyloid Polypeptide Cross-Seeding

Alzheimer's disease (AD) is the most severe form of neurological disorder, characterized by the presence of extracellular amyloid-β (Aβ) plaques and intracellular tau tangles. For decades, therapeutic strategies against the pathological symptoms of AD have often relied on the delivery of monoclonal antibodies to target specifically Aβ amyloid or oligomers, largely to no avail. Aβ can be traced in the brain as well as in cerebrospinal fluid and the circulation, giving rise to abundant opportunities to interact with their environmental proteins. Using liquid chromatography tandem-mass spectrometry, here we identified for the first time the protein coronae of the two major amyloid forms of Aβ-Aβ1-42 and Aβ1-40-exposed to human blood plasma. Out of the proteins identified in all groups, 58 proteins were unique to the Aβ1-42 samples and 31 proteins unique to the Aβ1-40 samples. Both fibrillar coronae consisted of proteins significant in complement activation, inflammation, and protein metabolic pathways involved in the pathology of AD. Structure-wise, the coronal proteins often possessed multidomains of high flexibility to maximize their association with the amyloid fibrils. The protein corona hindered recognition of Aβ1-42 fibrils by their structurally specific antibodies and accelerated the aggregation but not the β-cell toxicity of human islet amyloid polypeptide, the peptide associated with type 2 diabetes. This study highlights the importance of understanding the structural, functional, and pathological implications of the amyloid protein corona for the development of therapeutics against AD and a range of amyloid diseases.

Prevalence and economic impact of cystic echinococcosis and liver fluke infections in slaughtered sheep and goat in north-central Iran, 2008-2018

Cystic echinococcosis (CE) and liver fluke infections as important zoonotic infections impose a large socioeconomic impact on societies. As an endemic region for these infections, slaughterhouse inspections should be more considered in Iran. This study aimed to analyze the 11-year record of offal condemnation due to CE, fascioliasis, dicrocoeliasis infections in sheep and goat and its economic impact at Alborz slaughterhouse, north-central Iran. The prevalence rate was calculated as the infected organs (as nominator) divided by the slaughtered cases (as the denominator) in each year and month. The annual percent changes was used to determine trends of parasitic diseases over time. The relationship between metrological indexes and the prevalence of parasitic diseases was determined by the linear regression model. Statistical analyses were done using STATA software 14. For an estimate, the economic impact, the total numbers of offal condemnation were calculated. The overall prevalence rate of fascioliasis, dicrocoeliasis, and CE was 0.95%, 2.17%, and 12.74%, respectively. There was a declining trend in the prevalence of fascioliasis and dicrocoeliasis, whereas, the prevalence of CE increased from 7.57% in 2008 to 9.53% in 2018, representing an annual change of + 0.02%. The direct economic impact was estimated at US$ 1,670,977 and US$ 25,148 for liver and lung, respectively. The number of condemned organs due to these infections is noticeable in Alborz Province, north-central, Iran. The high economic impact of these infections showed the necessity of implementing a continuously infected animal's trace-back and disease control in the site of infection.

Graphene quantum dots rescue protein dysregulation of pancreatic β-cells exposed to human islet amyloid polypeptide

The amyloid aggregation of peptides and proteins is a hallmark of neurological disorders and type 2 diabetes. Human islet amyloid polypeptide (IAPP), co-secreted with insulin by pancreatic β-cells, plays dual roles in both glycemic control and the pathology of type 2 diabetes. While IAPP can activate the NLRP3 inflammasome and modulate cellular autophagy, apoptosis and extracellular matrix metabolism, no data is available concerning intracellular protein expression upon exposure to the polypeptide. More surprisingly, how intracellular protein expression is modulated by nanoparticle inhibitors of protein aggregation remains entirely unknown. In this study, we first examined the changing proteomes of βTC6, a pancreatic β-cell line, upon exposure to monomeric, oligomeric and fibrillar IAPP, and detailed cellular protein expression rescued by graphene quantum dots (GQDs), an IAPP inhibitor. We found that 29 proteins were significantly dysregulated by the IAPP species, while majority of these proteins were nucleotide-binding proteins. Collectively, our liquid chromatography tandem-mass spectrometry, fluorescence quenching, helium ion microscopy, cytotoxicity and discreet molecular dynamics simulations data revealed a remarkable capacity of GQDs in regulating aberrant protein expression through H-bonding and hydrophobic interactions, pointing to nanomedicine as a new frontier against human amyloid diseases.

Differential Roles of Plasma Protein Corona on Immune Cell Association and Cytokine Secretion of Oligomeric and Fibrillar Beta-Amyloid

Alzheimer's disease (AD) is a primary neurological disease with no effective cure. A hallmark of AD is the presence of intracellular tangles and extracellular plaques derived from the aberrant aggregation of tau- and beta-amyloid (Aβ). Aβ presents in the brain as well as in cerebrospinal fluid and the circulation, and Aβ toxicity has been attributed to amyloidosis and inflammation, among other causes. In this study, the effects of the plasma protein corona have been investigated with regard to the blood cell association and cytokine secretion of oligomeric (Aβo) and fibrillar Aβ_1-42(Aβ_f), two major forms of the peptide aggregates. Aβo displayed little change in membrane association in whole blood or washed blood (i.e., cells in the absence of plasma proteins) at 37 °C, while Aβ_f showed a clear preference for binding with all cell types sans plasma proteins. Immune cells exposed to Aβo, but not to Aβ_f, resulted in significant expression of cytokines IL-6 and TNF measured in real-time by a localized surface plasmon resonance sensor. These observations indicate greater immune cell association and cytokine stimulation of Aβo than Aβ_f and shed new light on the contrasting toxicities of Aβo and Aβ_f resulting from their differential capacities in acquiring a plasma protein corona. These results further implicate a close connection between Aβ amyloidosis and immunopathology in AD.

Single-Molecular Heteroamyloidosis of Human Islet Amyloid Polypeptide

Human amyloids and plaques uncovered post mortem are highly heterogeneous in structure and composition, yet literature concerning the heteroaggregation of amyloid proteins is extremely scarce. This knowledge deficiency is further exacerbated by the fact that peptide delivery is a major therapeutic strategy for targeting their full-length counterparts associated with the pathologies of a range of human diseases, including dementia and type 2 diabetes (T2D). Accordingly, here we examined the coaggregation of full-length human islet amyloid polypeptide (IAPP), a peptide associated with type 2 diabetes, with its primary and secondary amyloidogenic fragments 19-29 S20G and 8-20. Single-molecular aggregation dynamics was obtained by high-speed atomic force microscopy, augmented by transmission electron microscopy, X-ray diffraction, and super-resolution stimulated emission depletion microscopy. The coaggregation significantly prolonged the pause phase of fibril elongation, increasing its dwell time by 3-fold. Surprisingly, unidirectional elongation of mature fibrils, instead of protofilaments, was observed for the coaggregation, indicating a new form of tertiary protein aggregation unknown to existing theoretical models. Further in vivo zebrafish embryonic assay indicated improved survival and hatching, as well as decreased frequency and severity of developmental abnormalities for embryos treated with the heteroaggregates of IAPP with 19-29 S20G, but not with 8-20, compared to the control, indicating the therapeutic potential of 19-29 S20G against T2D.

Amphiphilic surface chemistry of fullerenols is necessary for inhibiting the amyloid aggregation of alpha-synuclein NACore

Featuring small sizes, caged structures, low cytotoxicity and the capability to cross biological barriers, fullerene hydroxy derivatives named fullerenols have been explored as nanomedicinal candidates for amyloid inhibition. Understanding the surface chemistry effect of hydroxylation extents and the corresponding amyloid inhibition mechanisms is necessary for enabling applications of fullerenols and also future designs of nanomedicines in mitigating amyloid aggregation. Here, we investigated effects of C60(OH)n with n = 0-40 on the aggregation of NACore (the amyloidogenic core region of the non-amyloid-β component in α-synuclein), the amyloidogenic core of α-synuclein, by computational simulations, transmission electron microscopy (TEM), Fourier transform infrared (FTIR) spectroscopy, thioflavin-T (ThT) fluorescence kinetics and viability assays. Computationally, NACore assembled into cross-β aggregates via intermediates including β-barrels, which are postulated as toxic oligomers of amyloid aggregation. Hydrophobic C60 preferred to self-assemble, and NACore bound to the surface of C60 nano-clusters formed β-sheet rich aggregates - i.e., having little inhibition effect. Amphiphilic C60(OH)n with n = 4-20 displayed significant inhibition effects on NACore aggregation, where hydrogen bonding between hydroxyls and peptide backbones interrupted the formation of β-sheets between peptides adsorbed onto the surfaces of fullerenols or fullerenol nano-assemblies due to hydrophobic interactions. Thus, both cross-β aggregates and β-barrel intermediates were significantly suppressed. With hydroxyls increased to 40, fullerenols became highly hydrophilic with reduced peptide binding and thus an inhibition effect on amyloid aggregation. ThT, FTIR and TEM characterization of C60(OH)n with n = 0, 24, & 40 confirmed the computational predictions. Our results and others underscore the importance of amphiphilic surface chemistry and the capability of polar groups in forming hydrogen bonds with peptide backbones to render amyloid inhibition, offering a new insight for de-novo design of anti-amyloid inhibitors.

Probing the Aggregation and Immune Response of Human Islet Amyloid Polypeptides with Ligand-Stabilized Gold Nanoparticles

The use of nanomaterials has recently become an emerging strategy against protein amyloidosis associated with a range of metabolic and brain diseases. To facilitate research in this area, here we first demonstrated the use of hyperspectral imaging (HSI) and COMSOL simulations for reporting the aggregation of human islet amyloid polypeptides (IAPPs), a hallmark of type 2 diabetes, as well as the physical interactions between the peptide and gold nanoparticles (AuNPs) grafted with citrate and poly(ethylene glycol) (PEG₄₀₀ and PEG₃₀₀₀). We found a distinct anticorrelation between increased IAPP aggregation and decreased spectral red shifts incurred in the AuNP plasmonic resonance. Moreover, Jurkat cells exposed to IAPP and AuNPs were characterized by quantifying their cytokine secretions with a localized surface plasmon resonance (LSPR) immunoassay, where a peak response was registered for the most toxic IAPP oligomers and most suppressed by citrate-coated AuNPs. This study demonstrated the potential of using HSI and LSPR as two new platforms for the facile examination of protein aggregation and their induced immune response associated with amyloid diseases.

Physical and Toxicological Profiles of Human IAPP Amyloids and Plaques

Although much has been learned about the fibrillization kinetics, structure and toxicity of amyloid proteins, the properties of amyloid fibrils beyond the saturation phase are often perceived as chemically and biologically inert, despite evidence suggesting otherwise. To fill this knowledge gap, we examined the physical and biological characteristics of human islet amyloid polypeptide (IAPP) fibrils that were aged up to two months. Not only did aging decrease the toxicity of IAPP fibrils, but the fibrils also sequestered fresh IAPP and suppressed their toxicity in an embryonic zebrafish model. The mechanical properties of IAPP fibrils in different aging stages were probed by atomic force microscopy and sonication, which displayed comparable stiffness but age-dependent fragmentation, followed by self-assembly of such fragments into the largest lamellar amyloid structures reported to date. The dynamic structural and toxicity profiles of amyloid fibrils and plaques suggest that they play active, long-term roles in cell degeneration and may be a therapeutic target for amyloid diseases.

Mitigating Human IAPP Amyloidogenesis In Vivo with Chiral Silica Nanoribbons

Amyloid fibrils generally display chirality, a feature which has rarely been exploited in the development of therapeutics against amyloid diseases. This study reports, for the first time, the use of mesoscopic chiral silica nanoribbons against the in vivo amyloidogenesis of human islet amyloid polypeptide (IAPP), the peptide whose aggregation is implicated in type 2 diabetes. The thioflavin T assay and transmission electron microscopy show accelerated IAPP fibrillization through elimination of the nucleation phase and shortening of the elongation phase by the nanostructures. Coarse-grained simulations offer complementary molecular insights into the acceleration of amyloid aggregation through their nonspecific binding and directional seeding with the nanostructures. This accelerated IAPP fibrillization translates to reduced toxicity, especially for the right-handed silica nanoribbons, as revealed by cell viability, helium ion microscopy, as well as zebrafish embryo survival, developmental, and behavioral assays. This study has implicated the potential of employing chiral nanotechnologies against the mesoscopic enantioselectivity of amyloid proteins and their associated diseases.

In Vivo Mitigation of Amyloidogenesis through Functional-Pathogenic Double-Protein Coronae

Amyloid diseases are global epidemics with no cure available. Herein, we report a first demonstration of in vivo mitigation of amyloidogenesis using biomimetic nanotechnology. Specifically, the amyloid fragments (b_a) of β-lactoglobulin, a whey protein, were deposited onto the surfaces of carbon nanotubes (b_aCNT), which subsequently sequestered human islet amyloid polypeptide (IAPP) through functional-pathogenic double-protein coronae. Conformational changes at the b_a-IAPP interface were studied by Fourier transform infrared, circular dichroism, and X-ray scattering spectroscopies. b_aCNT eliminated the toxic IAPP species from zebrafish embryos, as evidenced by the assays of embryonic development, cell morphology, hatching, and survival as well as suppression of oxidative stress. In addition to IAPP, b_aCNT also displayed high potency against the toxicity of amyloid-β, thereby demonstrating the broad applicability of this biomimetic nanotechnology and the use of an embryonic zebrafish model for the high-throughput screening of a range of amyloidogenesis and their inhibitors in vivo.

Nanoparticle-proteome in vitro and in vivo

The protein corona is a concept central to a range of disciplines exploiting the bio-nano interface. As the literature continues to expand in this field, it is essential to condense and contextualize the in vitro and in vivo proteome databases accumulated over the past decade: a goal which this review intends to achieve for the benefit of nanomedicine and nanobiotechnology. The parameters used for our review are the physicochemical characteristics of the nanoparticles, their surface ligands, the biological matrix from which a corona was formed, methods employed, plus the top-ten enriched corona proteins. In addition, the protein coronal networks and their implications in vivo are highlighted for selected studies.

Profiling the Serum Protein Corona of Fibrillar Human Islet Amyloid Polypeptide

Amyloids may be regarded as native nanomaterials that form in the presence of complex protein mixtures. By drawing an analogy with the physicochemical properties of nanoparticles in biological fluids, we hypothesized that amyloids should form a protein corona in vivo that would imbue the underlying amyloid with a modified biological identity. To explore this hypothesis, we characterized the protein corona of human islet amyloid polypeptide (IAPP) fibrils in fetal bovine serum using two complementary methodologies developed herein: quartz crystal microbalance and "centrifugal capture", coupled with nanoliquid chromatography tandem mass spectroscopy. Clear evidence for a significant protein corona was obtained. No trends were identified for amyloid corona proteins based on their physicochemical properties, whereas strong binding with IAPP fibrils occurred for linear proteins or multidomain proteins with structural plasticity. Proteomic analysis identified amyloid-enriched proteins that are known to play significant roles in mediating cellular machinery and processing, potentially leading to pathological outcomes and therapeutic targets.

In Vitro Analysis of Modified Surfaces of Silicone Breast Implants

Background

Although silicone breast implants are well tolerated, local complications such as capsular contracture occur because of insufficient integration with surrounding tissues. In this study, cell behaviour on hydrophilized silicone breast implant foils was analysed qualitatively and quantitatively under in vitro conditions in order to provoke the desired responses in a defined environment.

Methods

Silicone breast implant foils with different surface modifications were tested after 24 hours, 5 days and 7 days. The following modifications of silicone implant foils were tested: Unmodified silicone, silicone after-graft polymerisation for polyacrylic acid (pAAc), silicone-pAAc-fibronectin adsorptive, silicone-pAAC-fibronectin covalent, positive and negative controls. Experiments were conducted using cell culture with murine mouse fibroblasts L-929. Cytotoxicity assays were carried out in direct and indirect contact with cells grown on the material. For the viability test and qualitative analysis of cell proliferation on different foils, both fluoresceine-diacetate and ethidiumbromide were used and in addition the morphologic description of hemalaun-stained cells were used. Quantitative cell analysis was carried out using XTT after resuspension.

Results

Toxic influence on cell cultures could be excluded for coated and uncoated surfaces in contact with dissolved biomaterials. Unmodified silicone surfaces showed poor cell growth in direct contact. We found a gradual improvement of cell morphology, with the spread and proliferation depending on the type of surface modification. Better results were achieved with covalently coupled fibronectin and GRGDS than with pAAc.

Conclusion

Covalent immobilisation of hydrophobic silicone rubber can improve the initial cellbiomaterial interactions that are required to aid the successful development of tissue-like structures.

High performance micro-flow cytometer based on optical fibres

Flow cytometry is currently the gold standard for analysis of cells in the medical laboratory and biomedical research. Fuelled by the need of point-of-care diagnosis, a significant effort has been made to miniaturize and reduce cost of flow cytometers. However, despite recent advances, current microsystems remain less versatile and much slower than their large-scale counterparts. In this work, an all-silica fibre microflow cytometer is presented that measures fluorescence and scattering from particles and cells. It integrates cell transport in circular capillaries and light delivery by optical fibres. Single-stream cell focusing is performed by Elasto-inertial microfluidics to guarantee accurate and sensitive detection. The capability of this technique is extended to high flow rates (up to 800 µl/min), enabling a throughput of 2500 particles/s. The robust, portable and low-cost system described here could be the basis for a point-of-care flow cytometer with a performance comparable to commercial systems.

Broiler responses to digestible threonine at different ages: a neural networks approach

Three experiments were conducted with broiler chickens to evaluate the effects of digestible threonine (DThr) and crude protein (CP) on their performance at three different phases of age: 1-14, 15-28 and 29-42 days. The measured traits included the following: average daily gain (ADG), feed intake (FI), feed conversion ratio (FCR), carcass crude protein (CCP), body lipid (BL), feather weight gain (FWG), protein deposited in feather (FCP), carcass plus feather protein (CFCP), carcass Thr deposition (CDThr) and nitrogen excretion (NE). A dilution technique was used to create seven diets (with eight replicates) increasing the DThr content from 1.5 to 10 g/kg of diet for phase 1, 1.3-8.9 g/kg of diet for phase 2, and 1.2-8.2 g/kg of diet for phase 3. Data measured were imported into neural networks (NNs) to: (i) predict the measured traits in response to DThr and CP, (ii) rank the importance of DThr and CP on these traits through sensitivity analysis and (iii) find the optimal levels of DThr and CP that lead to the desired (maximum or minimum) responses. For each trait investigated, 50 different random groups of data were generated using a bootstrapping method. These 50 data groups were then used to develop 50 separate NNs which were subsequently combined to construct the final ensemble NN model. In general, accuracy of the models constructed was acceptable, although models of high (ADG, FCR, CFCP, BL, DThr and NE; 0.64 ≤ R(2)  ≤ 0.99) and low (CCP, FWG and FCP; 0.26 ≤ R(2)  ≤ 0.79) accuracy were obtained. All models developed showed the greatest sensitivity to DThr. This may be explained by the dilution technique diet preparation used in these experiments. Optimization results showed decreases in optimal values of DThr and CP with increasing age for all traits. The highest level of DThr was suggested for minimum BL, followed by minimum FCR, maximum ADG, maximum CFCP, minimum NE and maximum CCP respectively. Results showed that the optimal values of DThr for minimum FCR in phases 1-3 were 8.5, 7.4 and 6.4 g/kg of diet, while these values for maximum ADG were 8.2, 7.2 and 6.4 g/kg of diet respectively.

Some novel growth functions and their application with reference to growth in ostrich

Four novel growth functions, namely, Pareto, extreme value distribution (EVD), Lomolino, and cumulative β-P distribution (CBP), are derived, and their ability to describe ostrich growth curves is evaluated. The functions were compared with standard growth equations, namely, the monomolecular, Michaelis-Menten (MM), Gompertz, Richards, and generalized MM (gMM). For this purpose, 2 separate comparisons were conducted. In the first, all the functions were fitted to 40 individual growth curves (5 males and 35 females) of ostriches using nonlinear regression. In the second, performance of the functions was assessed when data from 71 individuals were composited (570 data points). This comparison was undertaken using nonlinear mixed models and considering 3 approaches: 1) models with no random effect, 2) random effect incorporated as the intercept, and 3) random effect incorporated into the asymptotic weight parameter (Wf). The results from the first comparison showed that the functions generally gave acceptable values of R2 and residual variance. On the basis of the Akaike information criterion (AIC), CBP gave the best fit, whereas the Gompertz and Lomolino equations were the preferred functions on the basis of corrected AIC (AICc). Bias, accuracy factor, the Durbin-Watson statistic, and the number of runs of sign were used to analyze the residuals. CBP gave the best distribution of residuals but also produced more residual autocorrelation (significant Durbin-Watson statistic). The functions were applied to sample data for a more conventional farm species (2 breeds of cattle) to verify the results of the comparison of fit among functions and their applicability across species. In the second comparison, analysis of mixed models showed that incorporation of a random effect into Wf gave the best fit, resulting in smaller AIC and AIC values compared with those in the other 2 approaches. On the basis of AICc, best fit was achieved with CBP, followed by gMM, Lomolino, and Richards functions, respectively. The exponential, MM, Pareto, and EVD equations produced negative values for initial weight (W0) if left unconstrained. The Gompertz equation, in spite of having a fixed inflection point and therefore being less flexible, gave accurate estimates of both W0 and Wf and an acceptable goodness of fit favored by having fewer parameters than the other sigmoidal functions. Nevertheless, all the sigmoidal functions appeared appropriate in describing the growth trajectory of male and female ostriches to a reasonable level of accuracy.

Complex chiral colloids and surfaces via high-index off-cut silicon

Silicon wafers are commonly etched in potassium hydroxide solutions to form highly symmetric surface structures. These arise when slow-etching {111} atomic planes are exposed on standard low-index surfaces. However, the ability of nonstandard high-index wafers to provide more complex structures by tilting the {111} planes has not been fully appreciated. We demonstrate the power of this approach by creating chiral surface structures and nanoparticles of a specific handedness from gold. When the nanoparticles are dispersed in liquids, gold colloids exhibiting record molar circular dichroism (>5 × 10(9) M(-1) cm(-1)) at red wavelengths are obtained. The nanoparticles also present chiral pockets for binding.

Alternative growth functions for predicting body, carcass, and breast weight in ducks: Lomolino equation and extreme value function

In this study, 2 alternative growth functions, the Lomolino and the extreme value function (EVF), are introduced and their ability to predict body, carcass, and breast weight in ducks evaluated. A comparative study was carried out of these equations with standard growth functions: Gompertz, exponential, Richards, and generalized Michaelis-Menten. Goodness of fit of the functions was evaluated using R(2), mean square error, Akaike information criterion, and Bayesian information criterion, whereas bias factor, accuracy factor, Durbin-Watson statistic, and number of runs of sign were the criteria used for analysis of residuals. Results showed that predictive performance of all functions was acceptable, though the Richards and exponential equations failed to converge in a few cases for both male and female ducks. Based on goodness-of-fit statistics, the Richards, Gompertz, and EVF were the best equations whereas the worst fits to the data were obtained with the exponential. Analysis of residuals indicated that, for the different traits investigated, the least biased and the most accurate equations were the Gompertz, EVF, Richards, and generalized Michaelis-Menten, whereas the exponential was the most biased and least accurate. Based on the Durbin-Watson statistic, all models generally behaved well and only the exponential showed evidence of autocorrelation for all 3 traits investigated. Results showed that with all functions, estimated final weights of males were higher than females for the body, carcass, and breast weight profiles. The alternative functions introduced here have desirable advantages including flexibility and a low number of parameters. However, because this is probably the first study to apply these functions to predict growth patterns in poultry or other animals, further analysis of these new models is suggested.

Bootstrapped neural network models for analyzing the responses of broiler chicks to dietary protein and branched chain amino acids

Faridi, A., Golian, A., Heravi Mousavi, A. and France, J. 2014. Bootstrapped neural network models for analyzing the responses of broiler chicks to dietary protein and branched chain amino acids. Can. J. Anim. Sci. 94: 79–85. Reliable prediction of avian responses to dietary nutrients is essential for planning, management, and optimization activities in poultry nutrition. In this study, two bootstrapped neural network (BNN) models, each containing 100 separated neural networks (SNN), were developed for predicting average daily gain (ADG) and feed efficiency (FE) of broiler chicks in response to intake of protein and branched chain amino acids (BCAA) in the starter period. Using a re-sampling method, 100 different batches of data were generated for both the ADG and FE sets. Starting with 270 data lines extracted from eight studies in the literature, SNN models were trained, tested, and validated with 136, 67, and 67 data lines, respectively. All 200 SNN models developed, along with their respective BNN ones, were subjected to optimization (to find the optimum dietary protein and BCAA levels that maximize ADG and FE). Statistical analysis indicated that based on R 2, the BNN models were more accurate in 76 and 56 cases (out of 100) compared with the SNN models developed for ADG and FE, respectively. Optimization of the BNN models showed protein, isoleucine, leucine, and valine requirements for maximum ADG were 231.80, 9.05, 14.03 and 10.90 g kg−1 of diet, respectively. Also, maximum FE was obtained when the diet contained 232.30, 9.07, 14.50, and 11.04 g kg−1 of protein, isoleucine, leucine, and valine, respectively. The results of this study suggest that in meta-analytic modelling, bootstrap re-sampling algorithms should be used to better analyze available data and thereby take full advantage of them. This issue is of importance in the animal sciences as producing reliable data is both expensive and time-consuming.

Biological Matrices and Synthetic Meshes Used in Implant-based Breast Reconstruction - a Review of Products Available in Germany

While autologous breast reconstruction was considered the procedure of choice for immediate breast reconstruction, there has been a shift towards implant-based breast reconstruction (IBBR) in recent years. The proven safety of silicone breast implants and the development of biological matrices and synthetic meshes have contributed to the growing popularity of this approach. Although these different products are widely used, only limited clinical data are available with regard to breast surgery. The aim of this review was to give an overview of available biological matrices and synthetic meshes and discuss their use in clinical practice.

Study of broiler chicken responses to dietary protein and lysine using neural network and response surface models

1. In this study, neural network (NN) and response surface (RS) models were developed to investigate the response [average daily gain (ADG) and feed efficiency (FE)] of young broiler chickens to dietary protein and lysine. For this purpose, data on their responses to dietary protein and lysine were extracted from the literature and separate NN and RS models were constructed. 2. Comparison between the NN and RS models revealed higher accuracy of prediction with the NN models compared to the RS models. In terms of R (2) values, the NN models developed for both ADG (R (2) = 0.923) and FE (R (2) = 0.904) were far superior to the RS models (R (2) for ADG = 0.511; R (2) for FE = 0.67). This suggests that the NN models can serve as an alternative option to conventional regression approaches including use of RS models. 3. Optimisation of the NN models developed for response to protein and lysine showed that diets containing 220.7 (g/kg of diet) protein and 12.85 (g/kg of diet) lysine maximise ADG, whereas maximum FE is achieved with diets containing 241.3 and 13.12 (g/kg) protein and lysine, respectively. Based on the optimisation results, optimal dietary protein and lysine concentrations for maximum FE in broiler chickens during the starting period are higher than for ADG.

Evaluating the egg production of broiler breeder hens in response to dietary nutrient intake from 31 to 60 weeks of age through neural network models

Faridi, A., Golian, A. and France, J. 2012. Evaluating the egg production of broiler breeder hens in response to dietary nutrient intake from 31 to 60 weeks of age through neural network models. Can. J. Anim. Sci. 92: 473–481. The aim of this study was to evaluate the response of broiler breeder hens in terms of egg production to dietary nutrient intake. Using neural network (NN) models and breaking down the collected data from 98 commercial broiler breeder houses into 3-wk intervals, 10 NN-based models were developed from 31 to 60 wk of age. The data lines were divided into two random subsets of training (n=64) and testing (n=34) sets. The variables of interest for developing the models were metabolizable energy (ME; kcal bird−1 d−1), and crude protein (CP), total sulphur amino acids (TSAA), lysine (Lys), calcium (Ca) and available phosphorus (AP), all in g bird−1 d−1. The random optimization algorithm was applied to the constructed models to find the optimal level of the input variables which maximized egg production during the different intervals. The high R 2 values in all the developed models for both the training and testing sets indicate the accuracy of NN-based models in estimating egg production. The optimization results revealed that breeder hens consuming 485, 473, 471, 466, 460, 452, 448, 442, 437 and 445 kcal of ME bird−1 d−1 showed the highest egg production during the 10 consecutive 3-wk intervals from 31 to 60 wk of age, respectively. Moreover, the optimal performance of hens required the following average intakes from 31 to 60 wk of age (g bird−1 d−1): CP: 23.7; TSAA: 1.05; Lys: 1.07; Ca: 4.91; and AP: 0.58. The results show that energy (kcal bird−1 d−1) and other nutrient requirements (g bird−1 d−1) of broiler breeder hens from 31 to 60 wk of age do not change in consort together with age; therefore using different diets with different dietary nutrient levels during the production cycle may help the nutritionists better meet the requirements of broiler breeder hens. Based on the present study, it appears that company guideline recommendations may underestimate the nutrient requirements of hens during these weeks when egg production is declining gradually.

Predicting caloric and feed efficiency in turkeys using the group method of data handling-type neural networks

Neural networks (NN) are a relatively new option to model growth in animal production systems. One self-organizing submodel of artificial NN is the group method of data handling (GMDH)-type NN. The use of such self-organizing networks has led to successful application of the GMDH algorithm over a broad range of areas in engineering, science, and economics. The present study aimed to apply the GMDH-type NN to predict caloric efficiency (CE, g of gain/kcal of caloric intake) and feed efficiency (FE, kg of gain/kg of feed intake) in tom and hen turkeys fed diets containing different energy and amino acid levels. Involved effective input parameters in prediction of CE and FE were age, dietary ME, CP, Met, and Lys. Quantitative examination of the goodness of fit for the predictive models was made using R2 and error measurement indices commonly used to evaluate forecasting models. Statistical performance of the developed GMDH-type NN models revealed close agreement between observed and predicted values of CE and FE. In conclusion, using such powerful models can enhance our ability to predict economic traits, make precise prediction of nutrition requirements, and achieve optimal performance in poultry production.

Analysis of local complications following explantation of silicone breast implants

A study was undertaken to analyse local complications in patients with breast implants and the total number of implant-related interventions when silicone breast implants were explanted. We studied 53 patients who had received breast implants for cosmetic augmentation or breast reconstruction following surgery for breast cancer at the time of explantation. The clinical records of all these patients were analysed, and clinical information on reason for implantation, implant properties, number and kind of implant-related interventions and reason for explantation was elicited. A complication was defined as a surgical procedure performed for any of the following reasons: capsular contracture, loss of implant integrity, haematoma or seroma, infection of the implant site, extrusion or wound dehiscence, and dissatisfaction with the result. The mean numbers of implant-related operations were 3.1 in patients who had undergone breast reconstruction and 2.3 in patients who had cosmetic augmentation (P < 0.03). We found a total of 35 complications in 28 patients, 21 patients (75%) each had one complication, five patients (18%) had two and two patients (7%) had three complications. A significantly higher incidence of early complications in patients who had undergone breast reconstruction (P < 0.03) marks the difference from complications in the cosmetic group, most of which arose after a longer time (P < 0.02). A complication analysis is presented. At the time of explantation, 78% of the patients decided to have a new implant, while 12% requested permanent removal of the implant without replacement. In the present study we saw no patients with connective tissue or other autoimmune disorders. When breast reconstruction or augmentation with silicone devices is considered, patients must be informed of the possible complications and of the potential choices in later implant-related revision surgery.