Preclinical Practice Research Articles

MO-FG-207B-02: Breast

State-of-the-Art in Radiomics in Radiology and Radiation Oncology Radiomics is the science of converting medical images into mineable data, data that are descriptive of “phenotypes,” which may provide diagnostic, prognostic, or therapeutic information. Genomics is the science of sequencing and analyzing the function and structure of genomes; the complete set of DNA in a single cell of an organism. In turn, imaging genomics (or radiogenomics) is concerned with the correlation between image-based features, as determined by radiomics, and gene expression, as determined by genomics. Imaging genomics arose from decades of work in at least three key areas: 1) sequencing of the human genome, 2) quantitative imaging, computer-aided diagnosis, therapy prognostics, and assessment of therapy response in preclinical and clinical research and practice; and 3) data science, including the burgeoning areas of genomics, preclinical and population-based disease modeling, individualized medicine, and big data. Imaging genomics may answer important questions in medicine by correlating validated, quantitative image phenotypes (through validated imaging biomarkers) with clinical data, histopathologic data, molecular classifications, genomic assays, and treatment outcomes. This approach could address some of the greatest health burdens, including cancer, cardiac disease, and arthritis. Participants will discuss the state-of-the-art of radiomics across multiple disease sites and modalities. Aspects of the presentations will include how to improve the quality of image-based phenotypes of normal and diseased tissue, how to better determine the relationships between these phenotypes and the underlying biology associated with the images, and how to create predictive models using the image-based phenotypes. Topics will also include: 1) creating, archiving, curating and sharing ultra-large datasets (“big data”); 2) standardizing image acquisition and processing methods; 3) standardizing and validating phenotype extraction methods and classifier designs; and 4) using high-throughput, robust, and validated phenotyping systems. H. Aerts, NIH; NCIH. Li, This research was funded in part by the University of Chicago Dean Bridge Fund,and by NCI U24-CA143848-05, P50- CA58223 Breast SPORE program. Hui Li received royalties from Hologic.W. Lu, This work was supported in part by the National Cancer Institute Grants R01CA172638.

MO-FG-207B-01: Thorax/Lung

State-of-the-Art in Radiomics in Radiology and Radiation Oncology Radiomics is the science of converting medical images into mineable data, data that are descriptive of “phenotypes,” which may provide diagnostic, prognostic, or therapeutic information. Genomics is the science of sequencing and analyzing the function and structure of genomes; the complete set of DNA in a single cell of an organism. In turn, imaging genomics (or radiogenomics) is concerned with the correlation between image-based features, as determined by radiomics, and gene expression, as determined by genomics. Imaging genomics arose from decades of work in at least three key areas: 1) sequencing of the human genome, 2) quantitative imaging, computer-aided diagnosis, therapy prognostics, and assessment of therapy response in preclinical and clinical research and practice; and 3) data science, including the burgeoning areas of genomics, preclinical and population-based disease modeling, individualized medicine, and big data. Imaging genomics may answer important questions in medicine by correlating validated, quantitative image phenotypes (through validated imaging biomarkers) with clinical data, histopathologic data, molecular classifications, genomic assays, and treatment outcomes. This approach could address some of the greatest health burdens, including cancer, cardiac disease, and arthritis. Participants will discuss the state-of-the-art of radiomics across multiple disease sites and modalities. Aspects of the presentations will include how to improve the quality of image-based phenotypes of normal and diseased tissue, how to better determine the relationships between these phenotypes and the underlying biology associated with the images, and how to create predictive models using the image-based phenotypes. Topics will also include: 1) creating, archiving, curating and sharing ultra-large datasets (“big data”); 2) standardizing image acquisition and processing methods; 3) standardizing and validating phenotype extraction methods and classifier designs; and 4) using high-throughput, robust, and validated phenotyping systems. H. Aerts, NIH; NCIH. Li, This research was funded in part by the University of Chicago Dean Bridge Fund,and by NCI U24-CA143848-05, P50- CA58223 Breast SPORE program. Hui Li received royalties from Hologic.W. Lu, This work was supported in part by the National Cancer Institute Grants R01CA172638.

MO-FG-207B-00: State-of-the-Art in Radiomics in Radiology and Radiation Oncology

State-of-the-Art in Radiomics in Radiology and Radiation Oncology Radiomics is the science of converting medical images into mineable data, data that are descriptive of “phenotypes,” which may provide diagnostic, prognostic, or therapeutic information. Genomics is the science of sequencing and analyzing the function and structure of genomes; the complete set of DNA in a single cell of an organism. In turn, imaging genomics (or radiogenomics) is concerned with the correlation between image-based features, as determined by radiomics, and gene expression, as determined by genomics. Imaging genomics arose from decades of work in at least three key areas: 1) sequencing of the human genome, 2) quantitative imaging, computer-aided diagnosis, therapy prognostics, and assessment of therapy response in preclinical and clinical research and practice; and 3) data science, including the burgeoning areas of genomics, preclinical and population-based disease modeling, individualized medicine, and big data. Imaging genomics may answer important questions in medicine by correlating validated, quantitative image phenotypes (through validated imaging biomarkers) with clinical data, histopathologic data, molecular classifications, genomic assays, and treatment outcomes. This approach could address some of the greatest health burdens, including cancer, cardiac disease, and arthritis. Participants will discuss the state-of-the-art of radiomics across multiple disease sites and modalities. Aspects of the presentations will include how to improve the quality of image-based phenotypes of normal and diseased tissue, how to better determine the relationships between these phenotypes and the underlying biology associated with the images, and how to create predictive models using the image-based phenotypes. Topics will also include: 1) creating, archiving, curating and sharing ultra-large datasets (“big data”); 2) standardizing image acquisition and processing methods; 3) standardizing and validating phenotype extraction methods and classifier designs; and 4) using high-throughput, robust, and validated phenotyping systems. H. Aerts, NIH; NCIH. Li, This research was funded in part by the University of Chicago Dean Bridge Fund,and by NCI U24-CA143848-05, P50- CA58223 Breast SPORE program. Hui Li received royalties from Hologic.W. Lu, This work was supported in part by the National Cancer Institute Grants R01CA172638.

간호대학생의 취업스트레스에 미치는 영향요인

Abstract The purpose of this study was to analyze the relationship between general characteristics, clinical practice stress, major satisfaction and employment stress, and check the effect on employment stress in order to provide baseline data of reduced amount of stress from nursing undergraduates. Methods: The cross-sectional descriptive study design was used. We selected 388 nursing undergraduate students from nursing college located in Daejeon, Jinju, Naju city by convenience random sampling and analyzed the data using SPSS 22.0 program. Results and Conclusion: Factors that effects on employment stress was clinical practice stress, major satisfaction and family economic status, and the explanatory power was 23.8%. The results show the need for development of pre-clinical practice adaptation education program and applying it for nursing students to reduce the clinical practice stress. Also, development of counseling program is needed, since nursing has higher employment rate compare to other major however it is difficult to get a job at wanted hospital, moreover there are students who are pressured from license examination.KeyWords : Clinical practice stress, Major satisfaction, Employment stress

Influence of Teaching Strategies and its Order of Exposure on Pre-Clinical Teeth Arrangement - A Pilot Study.

Teeth arrangement is a vital skill for the undergraduate dental student. The attainment of skills depends largely on the methodology of teaching. In a dental curriculum, the students are exposed to a wide variety of inputs and teaching methodologies from different sources. The educational unit in dental school must identify the sequence of teaching methods that enhance the learning and practising ability of students. The aim of this study was to evaluate the effectiveness of three different teaching methodologies for teeth arrangement and compare the differences between the orders of exposure to each teaching methodology on the development of teeth arrangement skills. The first year B.D.S students were study participants and were divided into three groups A, B, C. They were exposed to three teaching patterns namely live demonstration with video assisted teaching, group discussion with hand-outs and lectures with power point presentation. After each teaching methodology, their skill was assessed. The groups were exposed to three methodologies in different order for three arrangements. The scores obtained were analysed using Kruskal Wallis rank sum test and Dunn test for statistical significance. Significantly higher scores in the teeth arrangement procedure were obtained by the Group A students who were exposed initially to live demonstration with video-assisted teaching. Difference in the scores was noted among and within the groups. The difference between Group A and Group C was statistically significant after both first and third teeth arrangement (p=0.0031, p=0.0057). The study suggests each pre-clinical practice should begin with a live demonstration to enhance immediate learning absorption followed by lectures with power point presentation and group discussion for retention of knowledge and memory retrieval.

Correlations of Ego Resilience and Self Efficacy in Pre-Clinical Practice of Nursing Students

Correlations of Ego Resilience and Self Efficacy in Pre-Clinical Practice of Nursing Students

EP-1452: A new CT based tissue automatic segmentation method for absorbed dose calculation in preclinical radiation therapy

Tissue segmentation in CT images is a key parameter for accurate dose calculation in external beam radiation therapy. Tissue segmentation methods used in clinical practice cannot be applied to preclinical practice due to both CT energy (40kVp) and treatment beam energy (100- 300kVp). At MV energy range, tissue segmentation is based on the conversion of HU into densities (HU, ρ). At medium energy range, this conversion method does not allow to achieve a satisfactory accuracy. Taking into account tissue heterogeneities requires to define the tissue elemental composition (EC). We developed a new tissue segmentation method (HU, ρ, EC) allowing the automatic assignment of density and elemental composition from HU. The (HU, ρ, EC) method is dedicated to preclinical practice to reach accurate dose distributions in small animals.

Short- and long-term neurological and psychiatric sequelae of developmental exposure to antiepileptic and anesthetic drugs.

Phenobarbital has been in clinical use for over a century; phenytoin for more than three-quarters of a century, and volatile anesthetics, such as isoflurane and halothane for more than half a century. Despite the long history of use of these compounds for the treatment of epilepsy, and for anesthesia, their effects on brain development are still relatively poorly understood. For this reason, the use of neuroactive drugs during gestation and infancy remains one of the thorniest issues in clinical neurology and neonatology. I had the privilege of co-editing this research topic with my mentor, colleague, and friend, Dr. Karen Gale. Dr. Gale passed away in August of 2014. She and I saw this research topic as an opportunity to highlight the state of the field, and in particular, underscore important future research directions. Together, these articles do exactly that. In this research topic, the current state of the field is reviewed from pre-clinical and clinical perspectives by Turski and Ikonomidou (1) and Gedzelman and Meador (2). These reviews highlight converging results from animal and human studies that underscore the profound impact of these drugs can have on the developing brain. Complementing these reviews, Rochelle Caplan’s translational review focuses on the role of antiepileptic drugs in psychopathology seen in pediatric epilepsy (3). From a translational perspective, the review by Khanna and colleagues (4), and the opinion piece by Pressler and Auvin (5) highlight the importance of neuronal chloride homeostasis as a key regulator of neuronal activity during brain development and as a critical mediator of the efficacy of the first-line therapies for neonatal seizures (i.e., phenobarbital). With respect to anesthesia, the review from Jevtovic-Todorovic and colleagues (6) approaches the problem of anesthesia-induced damage to the developing brain from a highly mechanistic perspective. In particular, they highlight the role of sub cellular organelles, such as mitochondia, in the pathophysiology of neonatal anesthesia exposure. Furthermore, the review by Cheng Wang outlines research approaches and models that have been employed in pre-clinical pediatric neurotoxicology experiments (7). Finally, the research article by Murphy and Baxter highlights sex-dependent effects of neonatal anesthesia exposure on long-term cognitive outcomes (8). In the decade and a half since the first characterization of apoptotic neurodegeneration in the developing rat brain after exposure to these drugs (9–11), this field has made considerable advances in understanding mechanisms of toxicity and characterizing the types of lasting injury that occur after early drug exposure. Indeed, the importance of this research was highlighted in the 2014 NINDS Benchmarks for Epilepsy Research, which lists as a goal, “[To] identify the impact of pharmacological treatment of the epilepsies on fetal and neonatal development. Develop strategies to control seizures in pregnancy without causing harm to either the mother or child” (12). There are, however, many questions that remain to be addressed. To what degree do the mechanisms of developmental neurotoxicity overlap and differ between classes of drugs (e.g., anesthesia vs. antiepileptic drugs). How can pre-clinical research influence clinical practice with respect to these drugs? What therapeutic strategies and adjunct treatments can be used to minimize/avoid developmental neurotoxicity? How does sex modulate risk for developmental neurotoxicity? What features and types of toxicity will be revealed by studies in non-human primate models? It is my sincere hope that 10 years from now, we will have made considerable progress in addressing these issues.

Technical quality of root canal therapies performed by novice dental students in preclinical practice.

Background:For improving the quality of endodontic performance of practitioners in clinical practice, their basic, preclinical performance and knowledge must be taken into consideration. This study aimed to radiographically evaluate the technical quality of preclinical molar root canal treatments (RCTs) performed by undergraduate dental students at a dental school in Iran. Further, the effect of using Gates-Glidden (GG) drills on the final quality of RCTs was evaluated.Materials and Methods:In this retrospective cross-sectional study, 315 roots of 105 endodontically treated teeth in preclinical practice were evaluated radiographically. The analyzed quality parameters included length, taper and density of fillings, which were scored as S2 (adequate standard), the S1 (slight deviation), or S0 (considerable deviation). For all the parameters, acceptable, moderate and poor fillings received total scores of 6, 3-5 and 0-2, respectively. There were two groups of students: One group had used only K-files, and the other had used K-files along with GG drills. The quality of RCTs between these groups was evaluated using the aforementioned scoring protocol. The results were analyzed using Chi-square, Mann–Whitney and Fisher's exact tests (α = 0.05).Results:Under-fillings (P = 0.001) and under-shapings (P = 0.007) occurred mostly in mandibular root fillings. A lower density was found in maxillary fillings (P < 0.001). No relationship was observed between the technique used (irrespective of GG drills usage) and length (P = 0.499) and taper of fillings (P = 0.238). The roots instrumented with GG drills had a higher filling density (P = 0.004). The quality mean score of RCTs was improved when GG drills were used (P = 0.008).Conclusion:The technical quality of preclinical molar RCTs performed by undergraduate dental students was considered acceptable in 35.6% of the cases. When GG drills were used along with K-files, the technical quality of RCTs was enhanced.

Restoflex--a revolutionary change in preclinical practice for restorative dentistry and endodontics.

Preclinical exercises are very important for the dental students in order to master various dental techniques. The objective of this article is to introduce a new preclinical working model named Restoflex. It is especially designed for the students to carry out various restorative and endodontic procedures in an environment that closely simulate clinical situations. This will help them to provide a smooth transition from preclinical environment to the clinical one. It would also mean an increased confidence level and the efficiency with which the students would deal with their cases.

From Bench to Bedside: Does Preclinical Practice in Translational Oncology Need Some Rebuilding?

After years of enormous research efforts for the systematic cataloguing of genetic alterations with causative function in cancer, the goal of “personalized medicine” in clinical oncology is now potentially in reach (1). With the overall aim to characterize more than 25,000 genomes from the 50 more relevant cancer types, major international endeavors are ongoing to provide a complete inventory of oncogenic mutations (2). When combined with the massive capacity of modern pharmaceutical companies to screen for inhibitors that target “druggable” mutant gene products, this undertaking will offer unprecedented opportunities to treat cancer through “precision” approaches whereby therapeutic decisions are informed by the genomic makeup of each tumor in each patient. Nevertheless, the ultimate clinical implementation of personalized medicine in oncology is still a major challenge. Indeed, the categorization of molecularly circumscribed tumor subpopulations featuring specific genetic lesions, the validation of such lesions as therapeutic targets, and the definition of biomarkers for accurate prediction of sensitivity to rational treatments face technical, logistic, and ethical limitations in patients. If cancer therapies must be tailored around small, genetically defined patient subgroups, the efforts essential to identify, recruit, and treat a number of patients great enough to validate the therapeutic relevance of new targets must be massive and may hardly justify high-risk drug development strategies. Highly reliable preclinical models for discrimination between “actionable” therapeutic opportunities and those with weak clinical transferability are thus urgently needed to improve the bench-to-bedside pipeline as a means to systematically increase the success rate of rationally based clinical trials. Further pointing to this criticality, the comprehensive and informed review by Lieu and colleagues in this issue of the Journal (3) depicts a different scenario, in which bedside-to-bench approaches have been clearly dominating the drug development scene in the last decade. Most of the genetic biomarkers that are currently used to predict drug efficacy in patients have been originally identified by retrospective clinical studies, and only subsequently mechanistically validated using preclinical models. There are many prototypic examples of this, ranging from the observation that patients with EGFR-mutant or ALK-translocated lung cancer respond to blockade of the corresponding targets, to the demonstration that mutations in the KRAS gene correlate with lack of benefit from anti-EGFR antibodies in colorectal cancer (3). By robustly validating previously identified biomarkers of response and resistance to drugs, a number of studies—both in cell lines (4,5) and patient-derived xenografts (6)—have demonstrated the potential of preclinical models as tools to generate clinically relevant predictions. However, the fact that these approaches have infrequently translated into reliable instruments for definition of successful trial designs reinforces the notion that preclinical methodology should be renewed and adapted to meet the current needs of translational research. This in turn could reinstate preclinical research to play a central role in defining priorities and strategies for the clinical development of drug candidates, hopefully contributing to overcoming the actual hitches in the field. First, a consensus is needed to define unequivocally what should be deemed a successful endpoint at the preclinical level. If we agreed to raise the bar to more stringent criteria for the evaluation of treatment efficacy at the preclinical level, this would probably reduce the attrition of hypotheses during the clinical phases of experimentation. For example, as clearly stated by Lieu et al., there is growing evidence that predictions of drug sensitivity based on tumor regressions in vivo—especially when observed in patientderived xenografts—are indeed more robust indicators of clinical transferability than those based on the more widely used criteria of tumor growth inhibition. However, although it is probably easy to reach a general agreement about these assumptions when targeting the cell-autonomous properties of cancer in vivo (mainly based on the concept of oncogene addiction), the situation is much less obvious when dealing with the tumor microenvironment. Within this context, the artifacts introduced by using nonhuman hosts are certainly more pronounced, and the definition of unquestionable, clinically relevant endpoints is not trivial. Even more complicated, the results of in vitro assays aiming at testing drug sensitivity in cancer cell lines can be barely correlated to direct measures of clinical efficacy. Thus, while remaining an invaluable resource for high-throughput screening approaches, hypothesis generation, and mechanistic investigation, cell lines should be considered mainly to be prioritization tools. In this view, cell line–based screens should be oriented at selecting promising options that deserve independent evaluation through in vivo approaches (ideally patient-derived xenograft based), which, albeit more laborious, are likely more interpretable in terms of translational implications. This will allow for the definition of clear-cut standards of preclinical activity, ideally based on objective endpoints that will demonstrate statistical correlation with clinical efficacy. In turn, consolidated preclinical knowledge will help rationalize risk assessment–based drug development policies for informed go/no-go decisions.

Students’ Perceptions of Materials and Techniques Used at European Dental Schools in the Education of Fixed Prosthodontics

The aim of this study was to explore the materials and procedures used by students in dental schools across Europe for teaching fixed prosthodontics. An online questionnaire, containing twenty-eight dichotomous, multiple-choice, and Likert scale rating questions, was sent to students in forty dental schools. After excluding dental schools in which less than 10 percent of the students responded, 775 questionnaires from ten schools remained for statistical analysis. Among these respondents, acrylic resin teeth were said to be the most commonly used material during preclinical practice (46-96 percent), and use of extracted teeth varied from 8 to 65 percent. At nine of the ten institutions, metal-ceramic was reported to be most commonly used for fixed dental prostheses. There was large variation in the type of finish line for a metal-ceramic fixed dental prosthesis: students at five institutions reported using a shoulder finish line, three a chamfer finish line, and two a shoulder-bevel finish line. A similar variation was observed with regard to the final cementation of metal-ceramic fixed dental prostheses: students at four institutions reporting most frequently using glass ionomer cement, with three using zinc phosphate cement and three using carboxylate cement. The responding European dental students varied considerably in their opinions about whether they were preclinically properly trained for the first preparation on a patient and in their overall rating of their education in fixed prosthodontics. Responding students in the United Kingdom, Sweden, and Nijmegen, The Netherlands, rated their fixed prosthodontics training overall the highest. Overall, this study found a wide variation amongst dental schools with regard to their education in fixed prosthodontics and their rating of this teaching.

PRP-Augmented Scaffolds for Cartilage Regeneration: A Systematic Review

Modern regenerative procedures for articular cartilage defects have proved to provide good replacement of damaged cartilage, although, at present, the properties of a native healthy cartilage are still not achievable by any substitute. Several scaffolds have been tested and clinically used over the years to help the restoration of articular surface, some of them producing a hyaline-like reparative tissue. Concurrently, biological strategies are used more extensively, alone or in combination with scaffolds, to enhance the clinical outcome in patients with chondral disease. Among these innovative methods, one of the widest used is platelet-rich plasma, with the rationale of taking advantage of the huge amount of GFs contained in platelets to promote cartilage regeneration. The aim of the present manuscript is to review systematically the current evidence in preclinical and clinical practice concerning platelet-rich plasma–augmented scaffolds to treat cartilage disorders.

Translating the concept of peptidelabeling with 5-deoxy-5-[18F]fluororibose into preclinical practice: 18F-labeling of Siglec-9 peptide for PET imaging of inflammation

Peptide glycosylation with 5-deoxy-5-[(18)F]fluororibose was translated into preclinical settings. The novel (18)F-labeled Siglec-9 peptide was produced using an automated synthesis procedure. The (18)F-labeled Siglec-9 peptide showed favorable binding in the animal model of inflammation in vivo.

COMPREHENSIVE QUALITY ASSESSMENT METHOD FOR THE TRADITIONAL CHINESE MEDICINE COMPLEX SYSTEM ON THE BASIS OF HOLISM

s. PHYTOPHARM 2012 M 80 Obzory po kliniceskoj farmacologii i lekarstvennoj terapii [Reviews of clinical pharmacology and drug therapy] ТОМ 10/2012/2 COMPREHENSIVE QUALITY ASSESSMENT METHOD FOR THE TRADITIONAL CHINESE MEDICINE COMPLEX SYSTEM ON THE BASIS OF HOLISM © Luo Guo-An, Liang Qiong-lin, Wang Yi-ming Tsinghua University, P. R. China The presentation summarized the recent development and progress of methodologies, techniques and regulations of China, focused on the field of comprehensive quality assessment method for the TCM complex system. five main aspects were addressed: 1) Proposal of the comprehensive quality assessment system for Traditional Chinese Medicine (TCM). A comprehensive quality assessment method based on the combination of macrocosmic characterization and microscopic feature for the TCM complex systems were introduced. 2) introduction of TCM fingerprint. The use of chromatographic fingerprinting combined with quantitation of multi-indicative components for the quality control of TCM and botanicals were described here. Many new fingerprinting techniques, such as multi-dimensional fingerprint, have been applied for the overall characterization of chemical composition of TCM complex systems, such as qingkailing injection, ginseng products, and so on. The development of the software for information processing of TCM fingerprint can be applied for not only the similarity evaluation but also the classification, recognition and identification of the fingerprint based on correlation analysis and discriminant analysis. 3) introduction of quantitative Analysis of Multi-Components by Single-marker. Since the importance of multi-component determination and the difficulty in acquiring the reference standards, a new strategy named as quantitative Analysis of Multi-Components by Single-marker (qAMS) have been proposed and applied in 2010 Chinese pharmacopeia. We took ginseng products, fructus of Gardenia jasminoides Ellis and herba epimedii as example here to be discussed the feasibility and universality of qAMS. 4) bio-Response fingerprint for assessment of efficacy and safety of TCM. how to charecterize and express the quality of TCM complex system corresponding to the efficacy and safety is a critical but difficult target. The roadmap of gene chip technique applied in the quality evaluation of TCM proposed here. Some examples, such as venenum bufonis, were reported here. GENERAL TOXICITY STUDY OF THE NEW MEDICATION BASED ON THE SCHISANDRA CHINENSIS SEEDS © Makarenko I. E., Avdeeva O. I., Makarova M. N., Pozharitskaya O. N., Kryshen K. L. St-Petersburg Institute of Pharmacy, Russia General toxicity study (acute and chronic) is the part of preclinical program for safety evaluation of new pharmaceuticals. in the acute toxicity study toxic, maximum tolerable and lethal doses for rats and mice were determined. The aim of the chronic toxicity study was to determine the safety profile of new medicine based on the oil extract of the Schisandra Chinensis seeds. The experiments were carried out according to Russian legislation of Ministry of health and Social development and international guidelines in the preclinical safety evaluation and Good laboratory Practice (GlP) standarts and approved by local ethical commission. for acute toxicity study the tested drug was administered oral and intraperitoneal in five doses 500, 2000, 5000, 10000 and 15000 mg/kg (of oil extract) to outbred female and male rats and mice in the same doses for each type of animals. Each group consisted of 5 animals of both sexes. in chronic experiment the tested medicine was administered intraperitoneal during 90 days in doses 50, 500 and 1000 mg/kg (of oil extract) to outbred female and male rats (10 animals per group). in acute experiment ld50 was not determined due to the absence of experimental animals lethality. because the maximum dose for oral treatment was 15000 mg/kg the tested pharmaceutical can be attributed to Class Vi relatively harmless compounds according to the classification of hodge and Sterner (1). in chronic experiments on the laboratory rats and mice there was no any toxic effects after 90 days of treatment for tested drug in all doses. Reference: (1) hodge h. C. and Sterner l. h. Tabulation of toxicity classes. Am. industr. hyg. Ass. quart., 1943, 10 (4): 93.

看護・理学療法・作業療法科における模擬患者参加型演習の学生による評価

看護・理学療法・作業療法科における模擬患者参加型演習の学生による評価

Practical interior tomography with radial Hilbert filtering and a priori knowledge in a small round area

Interior tomography problem can be solved using the so-called differentiated backprojection-projection onto convex sets (DBP-POCS) method, which requires a priori knowledge within a small area interior to the region of interest (ROI) to be imaged. In theory, the small area wherein the a priori knowledge is required can be in any shape, but most of the existing implementations carry out the Hilbert filtering either horizontally or vertically, leading to a vertical or horizontal strip that may be across a large area in the object. In this work, we implement a practical DBP-POCS method with radial Hilbert filtering and thus the small area with the a priori knowledge can be roughly round (e.g., a sinus or ventricles among other anatomic cavities in human or animal body). We also conduct an experimental evaluation to verify the performance of this practical implementation. We specifically re-derive the reconstruction formula in the DBP-POCS fashion with radial Hilbert filtering to assure that only a small round area with the a priori knowledge be needed (namely radial DBP-POCS method henceforth). The performance of the practical DBP-POCS method with radial Hilbert filtering and a priori knowledge in a small round area is evaluated with projection data of the standard and modified Shepp-Logan phantoms simulated by computer, followed by a verification using real projection data acquired by a computed tomography (CT) scanner. The preliminary performance study shows that, if a priori knowledge in a small round area is available, the radial DBP-POCS method can solve the interior tomography problem in a more practical way at high accuracy. In comparison to the implementations of DBP-POCS method demanding the a priori knowledge in horizontal or vertical strip, the radial DBP-POCS method requires the a priori knowledge within a small round area only. Such a relaxed requirement on the availability of a priori knowledge can be readily met in practice, because a variety of small round areas (e.g., air-filled sinuses or fluid-filled ventricles among other anatomic cavities) exist in human or animal body. Therefore, the radial DBP-POCS method with a priori knowledge in a small round area is more feasible in clinical and preclinical practice.

Effects of Simulation-based Education on Communication Skill and Clinical Competence in Maternity Nursing Practicum.

This study was conducted to examine the effects of simulation-based education on communication skill and clinical competence in maternity nursing practicum. This study used a non-equivalent control pretest-posttest design. The simulation-based education in maternity nursing practicum consisted of two clinical situation scenarios pertaining to patients with normal and high-risk deliveries. The control group consisted of 35 students in 2010 and the experimental group consisted of 35 students in 2009. The experimental group was given the simulation-based education using a high-fidelity patient simulator over 3 sessions, whereas the control group was given a conventional pre-clinical practice orientation before maternity nursing clinical practicum. Data were collected using a questionnaire, which included questions to assess communication skill and clinical competence. Data were analyzed using SPSS/WIN 18.0. Members of the experimental group, who received the simulation-based education, showed significantly higher communication skill and clinical competence scores than the control group (t=-2.39, p = .020; t=-2.71, p = .009). The simulation-based education in maternity nursing practicum is effective in promoting communication skill and clinical competence. With application of diverse clinical situation scenarios, it is recommended to develop and apply simulation-based education using a high-fidelity simulator in the area of maternity nursing.

Selecting a single model or combining multiple models for microarray-based classifier development? – A comparative analysis based on large and diverse datasets generated from the MAQC-II project

BackgroundGenomic biomarkers play an increasing role in both preclinical and clinical application. Development of genomic biomarkers with microarrays is an area of intensive investigation. However, despite sustained and continuing effort, developing microarray-based predictive models (i.e., genomics biomarkers) capable of reliable prediction for an observed or measured outcome (i.e., endpoint) of unknown samples in preclinical and clinical practice remains a considerable challenge. No straightforward guidelines exist for selecting a single model that will perform best when presented with unknown samples. In the second phase of the MicroArray Quality Control (MAQC-II) project, 36 analysis teams produced a large number of models for 13 preclinical and clinical endpoints. Before external validation was performed, each team nominated one model per endpoint (referred to here as 'nominated models') from which MAQC-II experts selected 13 'candidate models' to represent the best model for each endpoint. Both the nominated and candidate models from MAQC-II provide benchmarks to assess other methodologies for developing microarray-based predictive models.MethodsWe developed a simple ensemble method by taking a number of the top performing models from cross-validation and developing an ensemble model for each of the MAQC-II endpoints. We compared the ensemble models with both nominated and candidate models from MAQC-II using blinded external validation.ResultsFor 10 of the 13 MAQC-II endpoints originally analyzed by the MAQC-II data analysis team from the National Center for Toxicological Research (NCTR), the ensemble models achieved equal or better predictive performance than the NCTR nominated models. Additionally, the ensemble models had performance comparable to the MAQC-II candidate models. Most ensemble models also had better performance than the nominated models generated by five other MAQC-II data analysis teams that analyzed all 13 endpoints.ConclusionsOur findings suggest that an ensemble method can often attain a higher average predictive performance in an external validation set than a corresponding “optimized” model method. Using an ensemble method to determine a final model is a potentially important supplement to the good modeling practices recommended by the MAQC-II project for developing microarray-based genomic biomarkers.

Optimization of a partially segmented block detector for MR-compatible small animal PET

Abstract In recent years, there has been an increasing interest in the magnetic resonance (MR)-compatible positron emission tomography (PET) scanners for both clinical and preclinical practice. The aim of this study was to design a novel PET detector module using a segmented block crystal readout with an array of multi-pixel photon counters (MPPCs). A 16.5×16.5×10.0 mm3 LSO block was segmented into an 11×11 array, and reflective material was used to fill in the cuts to optically isolate the elements. The block was attached to a 4×4 MPPC array (Hamamatsu S11064) of 3.0×3.0 mm2 detectors to give a total effective area of 144 mm2. To visualize all the individual detector elements in this 11×11 detector module, the depth of the cuts was optimized by DETECT2000 simulations. The depth of the cuts determines the spread of scintillation light onto the MPPC array. The accuracy of positioning was evaluated by varying the depth of the cuts from 0.0 to 10.0 mm in steps of 0.5 mm. A spatial resolution of 1.5 mm was achieved using the optimized partially segmented block detector. The simulation results of this study can be used effectively as a guide for parameter optimization for the development of a partially segmented block detector for high-resolution MR-compatible PET scanners.