Software Procedures Research Articles

RECEIVER OPERATING CHARACTERISTIC CURVE ANALYSIS IN DIAGNOSTIC RESEARCH: A REVIEW

Optimal dose selection in clinical trials is problematic when efficacious and toxic concentrations are close. A receiver operating characteristic curve is a graphical technique used to identify the optimal cut-off point for a continuous variable. Implementation of ROC analysis is currently possible using various statistical software packages. However, the process is straightforward in the EZR package of R software. This present study aims to provide a tutorial using a simple example and a detailed description of the procedure in EZR software. The information provided can help the researchers perform the analysis independently.

ROLE OF SYMMETRY IN OPTIMIZATION OF FEM SIMULATION CALCULATIONS

At the studying the Mannesmann piercing process, we unify two approaches to the problem solving. Namely, the commercial FEM software procedure and the mathematical model of the process via the mathematical model of the considered FEM-simulation bound by certain unifying symmetries. Such phenomenon seemingly exists only if the FE-mesh is initiated to be physically interpreted. We shortly outline, how to come to the slightly modified Cahn-Hilliard equation as to the mathematical model of the FE-simulation possessing quasi-symmetry given by a lattice of colloidal assembly formed by the chosen FE-mesh. Separation of two cylindrical surfaces of the pierced product together with the inpainting role of the piercing plug are described with respect to the background given by the Navier-Stokes equations related to the flow between the both surfaces. Influence of the involved groups related to the considered quasi-symmetry is illustrated by the convergence/divergence of the Newton-Raphson number in the CPU-time.

Design and Implementation of an Underwater Information Acquisition System Prototype Based on Optical Fiber Communication

Ocean observation plays an important role in many areas, such as marine scientific research, environmental expedition, and resource exploitation. Traditional observation generally acquires periodical marine information and lacks real-time performances. To realize underwater observation of multi-information in real-time, an information acquisition system is designed in this study based on optical fiber communication. A multichannel interface between the diverse sensors and the slave computer is designed. It shields discrepancies of different sensor data and allows collecting information of various types, including conductivity, temperature, depth (CTD), attitudes, and images. At the same time, the full communication link is designed by constructing an optical fiber channel in collaboration with RS485 and USB. It provides a higher-rate link for real-time data transmission from underwater to overwater. Then, software procedures are, respectively, developed for the slave computer and the master computer based on the designed communication protocol. Additionally, a PC-based user interface is designed to realize data receipt, file saving, information display, and image restoration. Finally, an acquisition prototype is developed, and an underwater experiment is conducted to evaluate its performance. The results show that the underwater CTD, attitudes, and images can be collected and transmitted in real time. From its higher transmission rate and lower packet loss rate, the accuracy and the stability of the prototype are verified. The implementation of the acquisition prototype follows the trends of laying and networking submarine optical fiber cables. Therefore, its application can be expanded for ocean observation in information collecting, transmitting, and processing.

Cui Bono: Do Open Source Software Incubator Policies and Procedures Benefit the Projects or the Incubator?

Open source software (OSS), a form of Digital or Knowledge Commons, underlies much of the technology that we use in our daily lives. The existence and continuation of OSS relies on the contribution of private resources – personal time, volunteer energy, and effort of numerous actors (e.g., software developers’ time as a common-pool resource) – to public goods, the benefits of which are enjoyed by everyone. Nonprofit organizations such as the Apache Software Foundation (ASF) attempt to aid this process by providing various collective services to OSS projects, acting as a second-order actor in the production of the public good. To this end, the ASF Incubator has created policies – essentially rules or norms – that serve to protect its interests and, as they say, increase the sustainability of the projects. Each policy requires investment by ASF (in terms of money or the use of volunteer time) or an incubating project (in terms of taking project personnel time), the benefits of which can accrue to either party. Such policies may impose additional costs on incubating projects, leading to a decreased production of the OSS public good. Using the ASF Incubator policy documents, we construct a dataset that records who – ASF or an incubating project – bears the cost and who enjoys the benefit of each policy and procedure. We can code most policy statements as costing one party and benefiting one party. The distribution of costs and benefits according to party indicates whether the second-order actor is contributing to an increase in the public good and if they are doing so sustainably. Through a two-way ANOVA, we characterize the impact of ASF policies on the production of public goods (OSS). Being a part of ASF imposes some costs on projects, but these costs may make projects more sustainable. Our analysis shows that the distribution of costs and benefits is fairly symmetric between the ASF and incubating projects. Thus, the configuration of policies or the “institutional design” of the ASF could aid in producing the OSS public good by providing services that projects require.

A Cautionary Note on the Hanurav–Vijayan Sampling Algorithm

AbstractWe consider the Hanurav–Vijayan (HV) sampling design, which is the default method programmed in the SURVEYSELECT procedure of the SAS software. We prove that it is equivalent to the Sunter procedure but is capable of handling any set of inclusion probabilities. We prove that the Horvitz–Thompson (HT) estimator is not generally consistent under this sampling design. We propose a conditional HT estimator and prove its consistency under a nonstandard assumption on the first-order inclusion probabilities. Since this assumption seems difficult to control in practice, we recommend not to use the HV sampling design.

Lack of association between 11 gene polymorphisms on weight loss 1 year after Roux-en-y gastric bypass surgery in woman.

Although effective, the impact of bariatric surgery on weight loss is variable, and little is known about the influence of single-nucleotide polymorphisms (SNPs). The present study investigated the association of eleven SNPs related to obesity with weight loss 1 year after Roux-Y gastric bypass (RYGB) surgery in female patients. This prospective study included 351 women with obesity. The genotypes for eleven SNPs (GHRL-rs26802; GHSR-rs572169; LEP-rs7799039; LEPR-rs1137101; 5HT2C-rs3813929; UCP2-rs659366; UCP3-rs1800849; SH2B1-rs7498665; TAS1R2-rs35874116; TAS1R2-rs9701796; FTO-rs9939609) were determined using a real-time polymerase chain reaction and TaqMan assays. Anthropometric measurements were performed before and 1 year after RYGB surgery. To evaluate the factors that influenced the proportion of weight loss 1 year after surgery, beta regression analysis was used. The models were estimated using the GLIMMIX procedure in SAS statistical software. p<0.05 was considered statistically significant. The mean±SD percentage of total body weight loss in 1 year was 64.4 ± 5.8% and the median was 65.0%. When assessing the proportion of weight loss in 1 year after surgery, using univariate analysis (beta regression), no SNPs influenced weight loss. Furthermore, in the multiple analysis, with stepwise process of variable selection, no variable was significant to compose the multiple model. The 11 SNPs investigated did not influence weight loss 1 year after RYGB surgery in female patients. This result indicates that individual behaviours and other factors might better contribute to the magnitude of loss weight loss in a short period after bariatric surgery.

Modelling growth in dairy heifers based on linear body measurements (withers height) using non-linear functions.

This research communication reports a study to model the growth curves for withers height (WH) and body weight (BW) to withers height ratio (BW:WH) using monthly records (from 1 to 24 months of age) for three breeds of dairy heifer (Holstein, Jersey and Brown Swiss). The data sets used were those reported by the Dairy Heifer Evaluation Project of Penn State Extension (USA) between 1991 and 1992. Four growth functions (monomolecular and Michaelis-Menten, both with diminishing returns behaviour, and Schumacher and López, both with asymptotic sigmoidal behaviour) were fitted using the non-linear regression procedure of the SigmaPlot software and the parameters estimated. The models were judged for goodness of fit using adjusted coefficient of determination ($R_{{\rm adj}}^2 $), root mean square error (RMSE), Akaike's information criterion (AIC) and Bayesian information criterion (BIC). Assessing the goodness of fit by $R_{{\rm adj}}^2 $ (>0.99 in all cases) reveals the generally appropriate fit of the models to the data. The non-sigmoidal functions (i.e. Michaelis-Menten and monomolecular) provided the best fits giving the lowest values of RMSE, AIC and BIC. Based on the chosen statistical criteria, the Schumacher and López equations provided acceptable fits to the WH and BW:WH growth curves, but showed points of inflexion at times before birth, indicating that these growth curves are not sigmoidal. In conclusion, evaluation of the different non-linear growth functions used in this study indicated their potential for modelling growth patterns in dairy heifers.

Selection criteria for tomato lines with defined growth habit

Introduction: The selection of genotypes with determinate growth habit in tomato should contemplate adequate selection criteria to increase the efficiency of the breeding program. Objective: The objective of this work was to estimate selection criteria for “chonto” type tomato lines with determined growth habit. Materials and methods: This work was carried out at the Universidad Nacional de Colombia (Palmira Campus), in 2016, with seven lines with determinate growth habit and a control with indeterminate growth. Heritability in a broad sense (h2 g), coefficient of environmental variation, coefficient of genetic variation, selection efficiency and genetic gain were determined in parameters of morphological, phonological, fruit quality, fruit shape and production, using the RELM/BLUP procedure of the SELEGEN software. Results: There were three ranges of h2 g, the first with values of h2 g greater than 0.76, the second between 0.53 and 0.38, and the third with a value less than 0.38. The highest values of h2 g were for final plant height with 0.92, plant height at harvest with 0.88, yield per plant with 0.83, days to flowering with 0.83, number of fruits per plant with 0.82, and days to harvest with 0.82. For genetic gain it was found that the control had the highest values for final plant height, plant height at harvest, internode length, days to harvest, harvest duration, soluble solids content, number of fruits per plant, fruit weight and yield per plant; however, in some parameters such as height and phenology for selection by determined growth habit, the lowest values were better. Conclusion: There was evidence of genetic parameters that could be considered as selection criteria for “chonto” type tomato lines with determinate growth habit.

A New Stopping Criterion for Rasch Trees Based on the Mantel-Haenszel Effect Size Measure for Differential Item Functioning.

To detect differential item functioning (DIF), Rasch trees search for optimal splitpoints in covariates and identify subgroups of respondents in a data-driven way. To determine whether and in which covariate a split should be performed, Rasch trees use statistical significance tests. Consequently, Rasch trees are more likely to label small DIF effects as significant in larger samples. This leads to larger trees, which split the sample into more subgroups. What would be more desirable is an approach that is driven more by effect size rather than sample size. In order to achieve this, we suggest to implement an additional stopping criterion: the popular Educational Testing Service (ETS) classification scheme based on the Mantel-Haenszel odds ratio. This criterion helps us to evaluate whether a split in a Rasch tree is based on a substantial or an ignorable difference in item parameters, and it allows the Rasch tree to stop growing when DIF between the identified subgroups is small. Furthermore, it supports identifying DIF items and quantifying DIF effect sizes in each split. Based on simulation results, we conclude that the Mantel-Haenszel effect size further reduces unnecessary splits in Rasch trees under the null hypothesis, or when the sample size is large but DIF effects are negligible. To make the stopping criterion easy-to-use for applied researchers, we have implemented the procedure in the statistical software R. Finally, we discuss how DIF effects between different nodes in a Rasch tree can be interpreted and emphasize the importance of purification strategies for the Mantel-Haenszel procedure on tree stopping and DIF item classification.

Reported Incidents Involving Non-medical Care Workers and Nursery Teachers in Hospitals in Japan: An Analysis of the Japan Council for Quality Health Care Nationwide Database.

ObjectiveWith the shortage of medical staff, the birth rate decline, and aging populations in some countries, task shifting from specific medical staff to non-medical care workers in hospitals has been implemented as a short-term solution. Incident reporting reduces preventable patient errors, improves the quality of healthcare services, and contributes to patient safety. However, research focused on the expanding roles of non-medical staff who provide direct care for patients is lacking. The present study aimed to bridge this gap by examining reported incidents involving non-medical care workers and nursery teachers in hospitals in Japan.MethodologyA retrospective mixed-methods study was conducted using data published by the Japan Council for Quality Health Care. A total of 21,876 cases were reported between 2016 and 2020, and 97 out of 21,876 cases were analysed, after excluding incidents involving workers or staff other than care workers/nursery teachers. Descriptive statistics were used to examine the incidents, and textual data included in the incident reports were analysed by two registered nurses.ResultsThe occupations of the people involved were care worker (n=80, 82.5%) and nursery teacher (n=17, 17.5%). There were two reports of worker injuries (n=2, 2.1%), which were excluded. A total of 95 cases were included in the final analysis to examine the effects on patients. Among the remaining 95 cases, there were five severe patient incidents (death, n=2, 2.1%; cerebral hemorrhage, n=3, 3.2%), and the most frequent incident was bone fracture (n=64, 67.4%). Some patients had cognitive impairment (n=29, 30.5%) and osteoporosis (n=25, 26.3%). We divided the factors related to incident occurrence into software (procedures and protocols), environment (wards and theaters), and liveware (people, including care workers, nursery teachers, and patients). Regarding the reasons for the incidents, the percentages for the three factors were as follows: education/training 34.7% (n=33), in software; patient state 4.1% (n=39), in environment; and neglect to observe 45.3% (n=43), in liveware.ConclusionOur study involved a secondary analysis of published data, and the sample size was small. However, incident reports from care workers and nursery teachers working in hospitals included serious errors. The role of non-medical care staff in hospitals is broad and diverse, and has been shifting from direct care for patients with mild illnesses to direct care for patients with severe illnesses. An efficient clinical environment that ensures quality of care and service is lacking. By focusing on patient safety outcomes, policymakers and hospital teams should consider adjusting the working environment.

Measured accuracy of intraoral scanners is highly dependent on methodical factors.

The accuracy of intraoral and model scanners has been widely investigated with heterogeneous results, but the impact of the applied diversity of measurement methods on the outcomes remains unknown. This study aimed to evaluate the influence of methodological factors on the measurement result when comparing full-arch scans. The evaluation referred to a 5M model to analyze whether accuracy measurements are affected by (1) the reference geometry, (2) mesh density of the standard tessellation language (STL) datasets, (3) operator, (4) inspection software, and (5) alignment procedure. STL datasets of full-arch reference models were measured with 29 different combinations of these factors. For each combination, 10 repeated measurements of the intermolar width were performed. Trueness was statistically analyzed with one-way ANOVA and T-tests, repeatability with Levene tests, and reproducibility with interclass correlation coefficients. Measurement method variations affected the intermolar width by up to 186 µm. The alignment algorithm had a significant effect on the measurement outcome (p = 0.001). Likewise, reference geometry influenced trueness and repeatability significantly (p = 0.001), whereas mesh density affected the repeatability only in some cases. The operator had no impact on the measurement result. The inspection software affected the repeatability but not the trueness. The factors reference geometry and alignment algorithm highly affected the measurement outcome, while the operator, inspection software, and mesh density showed no impact on the trueness of the outcome. Cylindrical reference geometries showed fewer differences than bar-shaped ones and best-fit alignments fewer variations than alignments based on boundary parameters.

Applications of Computational Fluid Dynamics in Cardiovascular Disease

Computational fluid dynamics (CFD), alone or coupled with the most advanced imaging tools, allows for the assessment of blood flow patterns in cardiovascular disease to both understand their pathophysiology and anticipate the results of their surgical or interventional repair. CFD is a mathematical technique that characterizes fluid flow using the laws of physics. Through the utilization of specific software and numerical procedures based on virtual simulation and/or patient data from computed tomography, resonance imaging, and 3D/4D ultrasound, models of circulation for most CHDs can be reconstructed. CFD can provide insight into the pathophysiology of coronary artery anomalies, interatrial shunts, coarctation of the aorta and bicuspid aortic valve, tetralogy of Fallot and univentricular heart, valvular heart disease, and aortic disease. In some cases, CFD may be able to simulate different types of surgical or interventional repairs, allowing for the tailoring of treatment accordingly.

Assembly and Analysis of Cell-Scale Membrane Envelopes.

The march toward exascale computing will enable routine molecular simulation of larger and more complex systems, for example, simulation of entire viral particles, on the scale of approximately billions of atoms─a simulation size commensurate with a small bacterial cell. Anticipating the future hardware capabilities that will enable this type of research and paralleling advances in experimental structural biology, efforts are currently underway to develop software tools, procedures, and workflows for constructing cell-scale structures. Herein, we describe our efforts in developing and implementing an efficient and robust workflow for construction of cell-scale membrane envelopes and embedding membrane proteins into them. A new approach for construction of massive membrane structures that are stable during the simulations is built on implementing a subtractive assembly technique coupled with the development of a structure concatenation tool (fastmerge), which eliminates overlapping elements based on volumetric criteria rather than adding successive molecules to the simulation system. Using this approach, we have constructed two "protocells" consisting of MARTINI coarse-grained beads to represent cellular membranes, one the size of a cellular organelle and another the size of a small bacterial cell. The membrane envelopes constructed here remain whole during the molecular dynamics simulations performed and exhibit water flux only through specific proteins, demonstrating the success of our methodology in creating tight cell-like membrane compartments. Extended simulations of these cell-scale structures highlight the propensity for nonspecific interactions between adjacent membrane proteins leading to the formation of protein microclusters on the cell surface, an insight uniquely enabled by the scale of the simulations. We anticipate that the experiences and best practices presented here will form the basis for the next generation of cell-scale models, which will begin to address the addition of soluble proteins, nucleic acids, and small molecules essential to the function of a cell.

Experimental Validation of LiDAR Sensors Used in Vehicular Applications by Using a Mobile Platform for Distance and Speed Measurements.

LiDAR sensors are needed for use in vehicular applications, particularly due to their good behavior in low-light environments, as they represent a possible solution for the safety systems of vehicles that have a long braking distance, such as trams. The testing of long-range LiDAR dynamic responses is very important for vehicle applications because of the presence of difficult operation conditions, such as different weather conditions or fake targets between the sensor and the tracked vehicle. The goal of the authors in this paper was to develop an experimental model for indoor testing, using a scaled vehicle that can measure the distances and the speeds relative to a fixed or a moving obstacle. This model, containing a LiDAR sensor, was developed to operate at variable speeds, at which the software functions were validated by repeated tests. Once the software procedures are validated, they can be applied on the full-scale model. The findings of this research include the validation of the frontal distance and relative speed measurement methodology, in addition to the validation of the independence of the measurements to the color of the obstacle and to the ambient light.

Comparison of software accuracy to estimate the bed grain size distribution from digital images: A test performed along the Rhine River

AbstractThe quantification of the bed grain size distribution (GSD) of river surfaces is primarily conducted through manual approaches in the field. These methods are time consuming and not able to accurately represent the spatial diversity of the grain size distribution of rivers. Recently, several software programs and procedures have been developed using semi‐automatic and automatic methods to estimate bed GSD from digital imagery. The purpose of this study is to compare softwares accuracy between reference GSDs and estimated GSDs using geometric approaches (Basegrain software and a procedure developed on ImageJ), statistical approaches (digital grain size [DGS] and PebbleCounts softwares), and a machine learning framework (SediNet). This study evaluates ten digital images recorded along the Rhine River downstream of the city of Basel. The results showed that all software programs considerably underestimated the manually measured GSDs. Nevertheless, it is possible to significantly improve the estimation of bed GSD by applying calibration laws. Both DGS and Basegrain softwares are reliable to estimate the GSD, while the three others softwares are accurate for percentiles equal and higher than the D50. After linear regression correction, the mean normalized root mean square error of percentile errors did not exceed 13% for DGS and Basegrain software, while the others did not exceed 22% for percentiles coarser than the D50.

Mapping of Spatio-Temporal Changes of Surface Water Using Sentinel-1 SAR Images

Exploration of surface water bodies and their spatial definition has great importance in water resources management and helps understand hydrological processes in the country. Fast, regular, and effective ways of mapping watercourses and their surroundings through remote sensing methods are crucial tools for capturing change and predicting hazards. The last decades have brought new data products, open-source software, and evaluation procedures that allow low-cost mapping of surface water objects. A widespread and sought-after option for this type of mapping is the use of SAR (Synthetic Aperture Radar) image products. Just through SAR technology that it is possible to identify changes in water in a relatively short time and at the same time under any meteorological conditions thanks to backscattered microwave radiation. This paper presents the possibilities of using SAR technology and its data for long-term temporal mapping of meteorological-hydrological changes in surface water using satellite images of Sentinel-1 product level GRD. As regards surface water extraction, this process is performing by segmenting the threshold values according to the Otsu principle. The water surfaces are then interpreted into the form of water masks of objects by the binarization of the final image. These values are subsequently compared with the supervised classification RFC (Random Forest Classifier) method results. Suitable processing and evaluation procedures conclude that the more suitable polarization configuration for mapping water bodies is VV (vertical-vertical) polarization. As for speckle filter tools to eliminate radar noise, the most suitable option seems to be using a Lee filter. To achieve more accurate results of the extracted water bodies, it is then appropriate to implement quantitative statistical indicators of accuracy and their numerical interpretation of the reliability of results. This paper aims to demonstrate the advantages of using satellite SAR images for spatiotemporal mapping of surface water in the landscape to observe hydrological processes due to inundation, ecological and meteorological changes, and anthropogenic activity.

Comparative efficiency of five mathematical functions in modelling the first lactation milk yield of Kankrej cattle

Modelling of first lactation milk yield of Kankrej cattle was done using five different non-linear mathematical functions viz., exponential decline function (EDF), gamma function (GF), inverse polynomial function (IPF), mixed log function (MLF) and parabolic exponential function (PEF). We compared their efficiency in describing variations in first lactation milk yield of animals maintained under field conditions. A total of 3994 fortnightly daily milk records of 203 Kankrej cattle calved during the years between 2011 and 2017 at farmers? herds in the Banaskantha region of Gujarat State, India were utilized for the study. The PROC NLIN procedure of Statistical Analysis Software (SAS) using Newton method of iteration was applied to generate the model parameters and corresponding standard errors. Different parameters like adjusted R2 -value, root mean square error (RMSE), Durbin?Watson (DW) statistic, Akaike information criterion (AIC) and Bayesian information criterion (BIC) were used to compare the efficiency of different models. Results inferred that mixed log function was the best non-linear mathematical function for explaining variations in the first lactation milk yield of Kankrej cattle followed by gamma function and parabolic exponential function. The exponential decline function was the least efficient in fitting the lactation curve in Kankrej cattle, followed by inverse polynomial function.

The effects of lactic acid bacteria and yeasts as probiotics on the growth performance, relative organ weight, blood parameters, and immune responses of broiler: A meta-analysis.

Introduction: The number of publications in Scopus on this topic increased from less than 50 in 1995 to more than 250 in 2015. In other hand, inconsistency in results about the correlation between yeast and lactic acid bacteria as probiotics has been evident since the early publications on use in broilers. Methods: A meta-analysis was conducted to determine relationship between lactic acid bacteria and yeast as probiotics to broiler diets on the growth performance, relative organ weight, blood parameters, and immune response of the broiler. A database was designed based on published data that reported the use of probiotics on the broiler. The method used for selecting articles was based on the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) method. Articles selected were taken from PubMed, Web of science, Scopus, Google Scholar, and Science direct databases as well as individual. Results: The final database consists of 49 in vivo articles, 93 studies, and 225 treatments. The analysis statement in the system was a PROC MIXED procedure of SAS software. The level of probiotic increased (p <0.001) body weight, body weight gain, and feed intake of broiler. There was a reduction (p <0.01) on feed conversion ratio and mortality on the level probiotic given to broiler. Supplementation of probiotics in broiler diet increased (p <0.001) the weight of liver, spleen, gizzard, bursa of fabricius and carcass yield, while reduced (p<0.001) abdominal fat weight. The probiotic given increased the total of red and white blood cells (both at p < 0.001) but did not affect lymphocyte. Discussion: It can be concluded the yeast act as supporting agent that serves lactic acid bacteria as probiotic increases the growth performance, relative organ weight, blood parameters, and immune response of the broiler.

Comparative meta-analysis of broiler and piglet response to dietary valine taking into account isoleucine and leucine interactions

The aim of this study was to quantify the response of broilers and piglets to dietary valine (Val) level and the impact of the 2 other branched-chain amino acids (BCAA), leucine (Leu) and isoleucine (Ile), on this response through a meta-analysis approach. The databases were composed of 23 articles published between 1999 and 2018 and included 44 experiments and 229 treatments for broilers and 16 articles published between 2001 and 2018 and including 23 experiments and 126 treatments for piglets. Multiple regression models were fitted with the MIXED procedure of Minitab software with the random effect of the experiment. The Y variables were average daily gain (ADG), average daily feed intake (ADFI) and feed conversion ratio (FCR). The main X variable was dietary standardized ileal digestible Val (SID Val) and the other ones were dietary standardized ileal digestible Leu (SID Leu) and dietary standardized ileal digestible Ile (SID Ile). The response for ADG and ADFI to SID Val was positive linear and quadratic for broilers and piglets (broilers, ADG: P < 0.001, R2 = 0.66; ADFI: P < 0.001, R2 = 0.50; piglets, ADG: P < 0.001, R2 = 0.93; ADFI: P < 0.001, R2 = 0.97). The FCR was reduced linearly (P < 0.001) and quadratically (P < 0.001) with increasing SID Val for broilers (P < 0.001, R2 = 0.80) and piglets (P < 0.001, R2 = 0.93). Increasing dietary SID Leu reduced ADG and ADFI in broilers and piglets (ADG and ADFI, P < 0.05), with only an effect on FCR for broilers (P < 0.05). Results also showed that the response to SID Val was stronger with the highest SID Leu diets for both species (Interaction SID Val×SID Leu: Broilers, ADG and ADFI, P < 0.001; Piglets: ADG and ADFI, P < 0.05). In broilers, increasing SID Ile, resulted in a negative effect on ADG (P < 0.05), on FCR (P < 0.001) and a tendency to negatively affected ADFI (P = 0.08). For both species, the response of ADG, ADFI and FCR to SID Val was not modified by SID Ile (No interaction). The current study showed that ADG and ADFI increases with increasing SID Val and this effect was modulated by Leu except for FCR.

Isolation and Purification of Self-Renewable Human Neural Stem Cells from iPSCs for Cell Therapy in Experimental Model of Ischemic Stroke.

Neural stem cell therapy has been galvanized by the discovery of pluripotent stem cells. The possibility to generate specialized central nervous system-specific differentiated cells using human somatic cells engineered to become induced pluripotent stem cells (iPSCs) was a game changer. This technology has broad applications in the field of regenerative medicine, in vitro disease modeling, targeted drug discovery, and precision medicine. Currently, iPSCs are one of the most promising cell sources amenable for commercialization and off-the-shelf neural stem cell therapy products. iPSCs exhibit a strong self-renewable ability that supports the development of a virtually unlimited source of neural cells for structural repair in neurological disorders. However, along with this strong proliferative capacity of iPSCs comes the tumorigenic potential of these cells after transplantation. Thus, the isolation and purification of a homogeneous population of human neural stem cells (hNSCs) are of paramount importance to ensure consistency in the composition of the cellular product and to avoid tumor formation in the host brain. This chapter describes the isolation, neuralization, and long-term perpetuation of hNSCs derived from iPSCs through the use of specific growth medium and the preparation of hNSCs for transplantation in an experimental model of stroke. Additionally, we will describe methods to analyze the ischemic stroke and size of grafts using magnetic resonance imaging and OsiriX software and neuroanatomical tracing procedures to study axonal remodeling after ischemic stroke and cell transplantation.