Effects on how corn distiller grains with solubles (DDGS) as a replacement for soybean meal (SBM) in a Boer goat diet can improve profitably for producers by saving $0.17 per lbs. of feed

Forty-eight Boer goats were fed a DDGS diet, to which replaced the common SBM diet through 4 separate treatments (Exp. 1 to 4). The experiment is based on evaluating the efficacy of corn dried distiller grains with solubles (DDGS) as a replacement for soybean meal (SBM) in a Boer goat diet to determine growth performance, diet digestibility, carcass traits, and how these outcomes influence profitability for feed producers. Goats were fed a pelleted concentrated diet at Kansas State University’s Sheep and Goat Unit. These feeds either contained no DDGS in replace of SBM (Exp. 1), 33% DDGS in replace of SBM (Exp. 2), 66% DDGS in replace of SBM (Exp. 3), 100% DDGS in replace of SBM (Exp. 4). The study had 16 pens total dedicated to each treatment, with 4 pens containing 3 goats in each. These goats were fed twice a day along with weighing weekly from 0 d to 47 d; 0 d being the start of the experiment. On d 47, the lowest and highest weighed goats were taken out of each corresponding pen for carcass evaluations (hot carcass weight, carcass yield, loin eye area, loin eye depth, back fat, and body wall thickness). After Boer goats were slaughtered, the GLIMMIX procedure of SAS determined the data regarding growth performance (body weight, average daily gain, average daily feed intake, and gain to fed ratio). Overall, carcass traits, growth performance, and feed efficiency had results of acute change in numbers, indicating DDGS lacked the opportunity to cause unnecessary weight gain or loss in goats. From a marketing standpoint, when balancing Exp. 4’s diet compared to Exp. 1; there is a $56.23/ton saving in formulating the feed; converting to$0.17/lbs. basis. Overall, Exp. 4 with only DDGS affected the absence of goat’s comprehensive hot carcass weight and average daily gain in a sustainable and more profitable way. In conclusion, 100% DDGS in Exp. 4 showed no significant negative differences in the goats compared to the usual soybean meal diet in Exp. 1

Targeted knockdown of Tim3 by short hairpin RNAs improves the function of anti-mesothelin CAR T cells

T-cell immunoglobulin mucin 3 (Tim3) is an immune checkpoint receptor that plays a central role in chimeric antigen receptor (CAR) T cell exhaustion within the tumor microenvironment. This study was aimed to evaluate the effects of targeted-knockdown of Tim3 on the antitumor function of anti-mesothelin (MSLN)-CAR T cells. To knockdown Tim3 expression, three different shRNA sequences specific to different segments of the human Tim3 gene were designed and co-inserted with an anti-MSLN-CAR transgene into lentiviral vectors. To investigate the efficacy of Tim3 targeting in T cells, expression of Tim3 was assessed before and after antigen stimulation. Afterwards, cytotoxic effects, proliferative response and cytokine production of MSLN-CAR T cells and Tim3-targeted MSLN-CAR T cells were analyzed. Our results showed that activation of T cells and MSLN-CAR T cells led to up-regulation of Tim3. Tim3 knockdown significantly decreased its expression in different groups of MSLN-CAR T cells. Tim3 knockdown significantly improved cytotoxic function, cytokine production and proliferation capacity of MSLN-CAR T cells. Our findings indicate that targeted knockdown of Tim3 allows tumor-infiltrating CAR T cells that would otherwise be inactivated to continue to expand and carry out effector functions, thereby altering the tumor microenvironment from immunosuppressive to immunosupportive via mitigated Tim3 signaling

Construction and functional characterization of a fully human anti-CD19 chimeric antigen receptor (huCAR)-expressing primary human TÂ cells

Although remarkable results have been attained by adoptively transferring T cells expressing fully murine and/or humanized anti-CD19 chimeric antigen receptors (CARs) to treat B cell malignancies, evidence of human anti-mouse immune responses against CARs provides a rationale for the development of less immunogenic CARs. By developing a fully human CAR (huCAR), these human anti-mouse immune responses are likely eliminated. This, perhaps, not only increases the persistence of anti-CD19 CAR T cells�thereby reducing the risk of tumor relapse�but also facilitates administration of multiple, temporally separated doses of CAR T cells to the same recipient. To these ends, we have designed and constructed a second-generation fully human anti-CD19 CAR (or huCAR19) containing a fully human single-chain variable fragment (ScFv) fused with a CD8a hinge, a 4-1BB transmembrane domain and intracellular T cell signaling domains of 4-1BB and CD3z. T cells expressing this CAR specifically recognized and lysed CD19 + target cells produced cytokines and proliferated in vitro. Moreover, cell volume data revealed that our huCAR construct cannot induce antigen-independent tonic signaling in the absence of cognate antigen. Considering our results, our anti-CD19 huCAR may overcome issues of transgene immunogenicity that plague trials utilizing CARs containing mouse-derived ScFvs. These results suggest that this huCAR19 be safely and effectively applied for adaptive T cell immunotherapy in clinical practice. © 2018 Wiley Periodicals, Inc

Construction and Functional Characterization of a Fully Human Anti-mesothelin Chimeric Antigen Receptor (CAR) Expressing T Cell

Chimeric antigen receptor (CAR) T cell therapy is considered as an encouraging approach for the treatment of hematological malignancies. However, its efficacy in solid tumors has not been satisfying, mainly in the immunosuppressive network of the tumor microenvironment and paucity of appropriate target antigens. Mesothelin (MSLN) is a tumor-associated antigen (TAA) expressed in numerous types of solid tumors such as gastrointestinal, ovarian, and pancreatic tumors. Owing to high expression in tumor cells and low expression in normal tissues, MSLN-targeted therapies like monoclonal antibodies have been previously developed. In the present study, a CAR T cell harboring the second-generation of a fully human anti-MSLN-CAR construct containing CD3 zeta and 4-1BB signaling domains was produced and it was functionally evaluated against an MSLN-expressing cell line. The findings showed potent, specific proliferation, cytotoxic activity, and interleukin (IL)-2, Tumor necrosis factor-(TNF) alpha, and Interferon-(IFN) gamma production in an antigen-dependent manner. Cytotoxic activity was shown in effector-to-target ratio from 1:1 to 20:1, but the most adequate efficacy was observed in the ratio of 10:1. Non-specific activity against MSLN negative cell line was not observed. Our data demonstrated that primary human T cells expressing fully human MSLN-CAR construct are effective against MSLN-expressing cell lines in vitro, suggesting this MSLN-CAR construct as a potential therapeutic tool in a clinical setting

Construction and Functional Characterization of a Fully Human Anti-mesothelin Chimeric Antigen Receptor (CAR) Expressing T Cell

Chimeric antigen receptor (CAR) T cell therapy is considered as an encouraging approach for the treatment of hematological malignancies. However, its efficacy in solid tumors has not been satisfying, mainly in the immunosuppressive network of the tumor microenvironment and paucity of appropriate target antigens. Mesothelin (MSLN) is a tumor-associated antigen (TAA) expressed in numerous types of solid tumors such as gastrointestinal, ovarian, and pancreatic tumors. Owing to high expression in tumor cells and low expression in normal tissues, MSLN-targeted therapies like monoclonal antibodies have been previously developed. In the present study, a CAR T cell harboring the second-generation of a fully human anti-MSLN-CAR construct containing CD3ζ and 4-1BB signaling domains was produced and it was functionally evaluated against an MSLN-expressing cell line. The findings showed potent, specific proliferation, cytotoxic activity, and interleukin (IL)-2, Tumor necrosis factor-(TNF) α, and Interferon-(IFN) γ production in an antigen-dependent manner. Cytotoxic activity was shown in effector-to-target ratio from 1:1 to 20:1, but the most adequate efficacy was observed in the ratio of 10:1. Non-specific activity against MSLN negative cell line was not observed. Our data demonstrated that primary human T cells expressing fully human MSLN-CAR construct are effective against MSLN-expressing cell lines in vitro, suggesting this MSLN-CAR construct as a potential therapeutic tool in a clinical setting

A multilevel inverter topology using diode half-bridge circuit with reduced power component

This paper presents a new multilevel converter with a reduced number of power components for medium voltage applications. Both symmetric and asymmetric structures of the presented multilevel converter are proposed. The symmetric topology requires equal dc source values, whereas the asymmetric topology uses minimum switch count. However, both structures suffer from high blocking voltage across the switches. To reduce the blocking voltage on switches, an optimal topology is presented and analyzed for the selection of the minimum number of switches and dc sources, while maintaining a low blocking voltage across the switches. A comparative analysis with recently published topologies was performed. The simulation results, as well as the comparative analysis, validated the robustness and effectiveness of the proposed topology in terms of the reduced power loss, lowered number of components, and cost. Furthermore, in addition to the simulation results, the performance of the proposed topology was verified using experimental results of 9, 17, and 25 evels.

A proposed de-identification framework for a cohort of children presenting at a health facility in Uganda.

Data sharing has enormous potential to accelerate and improve the accuracy of research, strengthen collaborations, and restore trust in the clinical research enterprise. Nevertheless, there remains reluctancy to openly share raw data sets, in part due to concerns regarding research participant confidentiality and privacy. Statistical data de-identification is an approach that can be used to preserve privacy and facilitate open data sharing. We have proposed a standardized framework for the de-identification of data generated from cohort studies in children in a low-and-middle income country. We applied a standardized de-identification framework to a data sets comprised of 241 health related variables collected from a cohort of 1750 children with acute infections from Jinja Regional Referral Hospital in Eastern Uganda. Variables were labeled as direct and quasi-identifiers based on conditions of replicability, distinguishability, and knowability with consensus from two independent evaluators. Direct identifiers were removed from the data sets, while a statistical risk-based de-identification approach using the k-anonymity model was applied to quasi-identifiers. Qualitative assessment of the level of privacy invasion associated with data set disclosure was used to determine an acceptable re-identification risk threshold, and corresponding k-anonymity requirement. A de-identification model using generalization, followed by suppression was applied using a logical stepwise approach to achieve k-anonymity. The utility of the de-identified data was demonstrated using a typical clinical regression example. The de-identified data sets was published on the Pediatric Sepsis Data CoLaboratory Dataverse which provides moderated data access. Researchers are faced with many challenges when providing access to clinical data. We provide a standardized de-identification framework that can be adapted and refined based on specific context and risks. This process will be combined with moderated access to foster coordination and collaboration in the clinical research community

A proposed de-identification framework for a cohort of children presenting at a health facility in Uganda

Data sharing has enormous potential to accelerate and improve the accuracy of research, strengthen collaborations, and restore trust in the clinical research enterprise. Nevertheless, there remains reluctancy to openly share raw data sets, in part due to concerns regarding research participant confidentiality and privacy. Statistical data de-identification is an approach that can be used to preserve privacy and facilitate open data sharing. We have proposed a standardized framework for the de-identification of data generated from cohort studies in children in a low-and-middle income country. We applied a standardized de-identification framework to a data sets comprised of 241 health related variables collected from a cohort of 1750 children with acute infections from Jinja Regional Referral Hospital in Eastern Uganda. Variables were labeled as direct and quasi-identifiers based on conditions of replicability, distinguishability, and knowability with consensus from two independent evaluators. Direct identifiers were removed from the data sets, while a statistical risk-based de-identification approach using the k-anonymity model was applied to quasi-identifiers. Qualitative assessment of the level of privacy invasion associated with data set disclosure was used to determine an acceptable re-identification risk threshold, and corresponding k-anonymity requirement. A de-identification model using generalization, followed by suppression was applied using a logical stepwise approach to achieve k-anonymity. The utility of the de-identified data was demonstrated using a typical clinical regression example. The de-identified data sets was published on the Pediatric Sepsis Data CoLaboratory Dataverse which provides moderated data access. Researchers are faced with many challenges when providing access to clinical data. We provide a standardized de-identification framework that can be adapted and refined based on specific context and risks. This process will be combined with moderated access to foster coordination and collaboration in the clinical research community. Author summary Open Data is data that anyone can access, use, and share. Open Data has the potential to facilitate collaboration, enrich research, and advance the analytic capacity to inform decisions. Importantly, Open Data plays a role in fulfilling obligations to research participants and honoring the nature of medical research as a public good. Leaders in industry, academia, and regulatory agencies recognize the value in increased transparency and are focusing on how to openly share data while minimizing the safety risks to research participants. For example, making data open can pose a privacy risk to research participants who have shared personal health information. This risk can be mitigated using data de-identification, a process of removing personal information from a data sets so that an individual’s identity is no longer apparent or cannot be reasonably ascertained from the data. We introduce a simple, statistical risk-based framework for de-identification of clinical data that can be followed by any researcher. This framework will guide open data sharing while improving the protection of research participants