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Approaches to evaluating the toxicity and carcinogenicity of man-made fibers: summary of a workshop held November 11-13, 1991, Durham, North Carolina.

The Workshop on Approaches to Evaluating the Toxicity and Carcinogenicity of Man-Made Fibers (MMF) was held in Durham, North Carolina, on November 11-13, 1991. The goal of the workshop was to reach a consensus, or to determine the extent to which a consensus existed, in two areas. Participants were asked to identify scientifically sound approaches for evaluating the toxicity and carcinogenicity of man-made fibers based on today's science and to determine research appropriate for study during the next 5 years that can provide an improved scientific basis for future revisions of approaches used to evaluate man-made fiber toxicity and carcinogenicity. During the first day, a series of "state of knowledge" presentations were made to provide all participants with a common data base from which to interact and discuss scientific issues. The workshop participants were assigned to one of four discussion groups, which met separately in three half-day sessions following the first day of presentations. All groups discussed the same topics: exposure assessment, hazard identification, and dose-response information needed to integrate to characterize risk in the first session; approaches to obtaining the needed information in the second session; and recommended approaches and guidelines for evaluating the toxicity and carcinogenicity of MMF and research needs in the third session. The workshop participants reconvened as a whole after each discussion session, and one member from each group reported the group's conclusions. A closure period was also included at the end of the workshop for review and discussion of items that had been considered during the workshop. The primary conclusions reached were the following: -All fiber types capable of depositing in the thorax are not alike in their pathogenic potential. -Only fiber samples with dimensions similar to those to which humans can inhale should be tested. -A complete characterization (i.e., dimensions, fiber number, mass, and aerodynamic diameter) of the fiber aerosol and retained dose is essential. -Appropriate aerosol generation methods must be used for inhalation studies in order to preserve fiber lengths. -A tiered approach to toxicity evaluation is recommended that includes: 1. In vitro screening for durability, surface properties, cytotoxicity, and similar properties, etc; 2. Short-term inhalation or other in vivo studies; 3. That chronic inhalation studies are the "gold standard" (i.e., provide most appropriate data for risk characterization). -The rat is the most appropriate species for inhalation studies. -In chronic inhalation studies, animals should be retained to at least 20% survival after 2-year exposure. -Serial lung burden analyses are an essential component of inhalation studies and are essential for understanding exposure-dose-response relationships. -Studies oriented to understanding mechanisms of toxicity and carcinogenicity are important adjuncts to traditional toxicity studies. -Histopathological analyses of tissues of the respiratory tract represent primary endpoints for evaluating effects of inhaled fibers. Major effects include pulmonary fibrosis, lung tumors, and mesotheliomas. Experimental tissues should be archived for future studies; wherever possible, handling and preservation of tissues should be done in a way that maximizes their future use in mechanistic studies. -Potential human exposures throughout the entire life-cycle of the fiber must be considered and fibrous material for toxicologic studies prepared accordingly. -Intracavity studies are inappropriate for risk characterization but can play a useful screening role in assessing fiber toxicity.(ABSTRACT TRUNCATED AT 400 WORDS)

Animals↗

Changing educational paradigms in transfusion medicine and cellular therapies: development of a profession.

The transfusion medicine profession can be easily compared and contrasted with an early 1900 ironclad ship operating in the rough seas of the 21st century. Without modifying the old ship to today's standards, even the captain and crew will begin to expect the ship to meet its demise. The unfortunate passengers, on the other hand, do not expect that they are on an old obsolete ship and, instead, are innocent victims stuck on a doomed course. The old ironclad ship must change into a sleek cruiser and utilize the latest available technology so that its well-educated and competent captain and crew can safely navigate even the most challenging waters. The transfusion medicine profession must transform itself into a state-of-the-art ship so that it, like the refurbished ironclad ship, can be set on cruise control through the open seas. The question facing our industry is do we have the courage to utilize modern technology and to commit the funds necessary to develop, implement, and maintain our existence? It is difficult to plot a steady course into the future because of existing challenges that stand ready to sink our profession, including economic wrangling over regulation, technologic changes, generation conflict, and political differences that threaten our excellence. The primary purpose of this article is to focus on the educational needs that affect all personnel involved in transfusion medicine. In addition, this article will address potential adverse outcomes and investigate possible resolutions to avoid the "sinking ship." Within the next 5 to 7 years, without a corrective course of action, our profession will be at the bottom of the clinical ladder, remembered more for its demise and tragic ending than for its accomplishments. It is hoped, successful implementation of changes in educational paradigms in transfusion medicine may lead to a renaissance within our workforce-generations working together, each sharing and learning from one another.

Accreditation↗

[Issues of research in medicine].

Research in medicine is liable to all rules and standards that apply to research in other natural sciences, since medicine as a science and service fully meets the general definition of science: it is a common, integrated, organized and systematized knowledge of mankind, whereby physician--being more or less aware of doing so-- in his daily activities applies scientific thinking and scientific methods. The procedure of problem solving in scientific work and in medical practice is characterized by many similarities as well as variation. In scientific research, the observation of some phenomenon that cannot be explained by the known facts and theories is followed by making a hypothesis, planning and carrying out experimental investigation resulting in some data. Interpretation of these data then provides evidence to confirm or reject the hypothesis. In medical practice, quite a similar procedure is followed; the initial examination of a patient, when his condition cannot be explained by the data thus obtained, is identical to the observation of a phenomenon which cannot be explained by the known facts; working diagnosis would correspond to making the hypothesis; and experimental investigation would compare to laboratory and other diagnostic studies. The working diagnosis is accepted or rejected depending on these results. Of course, there also are differences in the problem solving procedure between scientific research and daily medical practice. For example, in research a single hypothesis is posed, a single experiment with successive testing and/or repeats is performed, whereas in medical practice several hypotheses are made, multiple studies are concurrently performed to reject current hypotheses and to make new ones. Scientific investigation produces an abundance of systematic data, whereas in medical practice target data are being generated, yet not systematically. Definitive decision making also differs greatly, as in scientific research it only ensues from conclusive evidence, whereas in medical practice definitive decision is made and therapeutic procedures are performed even before reaching final evidence. The general strategy of work and research in medicine can be briefly described by four principles, i.e. good knowledge of one's own work; continuing upgrading of one's own work in collaboration with respective institutions (laboratories, university, and research institutes); implementation of standard, up-to-date and scientific methods most of the time; and publishing work results on a regular basis. This strategy ensures constant progress and treatment quality improvement while allowing due validation and evaluation of the work by the society. Scientific research is based on the pre-existing knowledge of the problem under study, and should be supervised, systematic and planned. Research produces data that may represent some new concepts, or such concepts are developed by further data processing. In research, scientific procedure includes a number of steps that have to be made to reach a new scientific result. This procedure includes (a) thinking about a scientific issue; (b) making a scientific hypothesis, i.e. the main objective of the study; (c) research ethics; (d) determination of sources and mode of data collection; (e) research performance; (f) collection and analysis of all research data; (g) interpretation of results and evidence; and (h) publications. The next section of this chapter brings an example of scientific research in the field of medicine, where the procedures carried out during the research are briefly described; other chapters of this supplement deal with statistical methodology used on processing the data obtained in the study, which is most frequently employed in scientific work in the field of medicine.

Biomedical Research↗

Accurate identification of abnormal ploidy using an artificial intelligence model in preimplantation genetic testing.

STUDY QUESTION: Can ultra-low-coverage whole-genome sequencing (ulc-WGS) accurately identify abnormal ploidy during preimplantation genetic testing (PGT)? SUMMARY ANSWER: The artificial intelligence (AI)-based PGT-Plus model demonstrates high accuracy in ploidy detection, offering a cost-effective solution that enhances clinical utility of PGT. WHAT IS KNOWN ALREADY: The predominant PGT for aneuploidy can identify chromosomal aneuploidies but cannot determine ploidy status. Transferring embryos with ploidy abnormalities can result in miscarriage and molar pregnancy. On the other hand, in ART, fertilization is assessed by morphological pronuclear assessment at the zygote stage. However, it has a low specificity in the prediction of abnormal ploidy status and embryos deemed abnormally fertilized can yield healthy pregnancies. Accurately identified abnormal ploidy in PGT-A can resolve current limitations and expand the utility range of PGT-A. Several studies have identified ploidy abnormalities; however, they were mainly based on single-nucleotide polymorphism (SNP) arrays or needed to combine additional targeted-next-generation sequencing (NGS) information. Studies based on ulc-WGS remain scarce. STUDY DESIGN SIZE DURATION: The study consisted of two stages: methodology establishment and validation. An AI model, named PGT-Plus, was developed using 653 samples with known ploidy status, which was further validated using 792 different ploidy status samples. In the clinical application stage, the approach was used to analyse the ploidy status of 19&#x2009;103 normally fertilized PGT blastocysts and 140 single pronucleus (1PN)-derived blastocysts collected between May 2022 and December 2023. All blastocysts were tested using trophectoderm biopsy and NGS. PARTICIPANTS/MATERIALS SETTING METHODS: The methodology is based on the ulc-WGS data. First, based on samples with known ploidy status: the heterozygosity rate of high-frequency biallelic SNPs, the likelihood ratio (LLR) of alleles was calculated under different assumptions ('both parental homologs' [BPH] from a single parent, 'single parental homolog' [SPH] from each parent, disomy, and monosomy) by leveraging allele frequencies and linkage disequilibrium (LD) measured in the 1000 genomes project database. Twenty-three continuous candidate features derived from heterozygosity rates and LLRs of chromosomes or selected windows were included to establish the ploidy prediction AI model. Gini importance analysis and multicollinearity mitigation was performed for feature selection, then the performance of Random Forest (RF), Support Vector Machine (SVM), and Logistic Regression for modelling was compared. Subsequently, the parameter optimization was performed based on the RF model. Ploidy constitution concordance was evaluated in known ploidy status samples. The frequency of abnormal ploidy in normal fertilized PGT blastocysts and 1PN-derived blastocysts (including conventional IVF and ICSI) was evaluated. MAIN RESULTS AND THE ROLE OF CHANCE: Eleven features were collected for model architecture compared to SVM and Logistic Regression; RF achieved superior performance for ploidy detection. The AI model achieved an AUC of 1 for genome-wide-uniparental diploidy (GW-UPD), 1 for triploidy, and 0.99 for diploidy. For the 792 validation samples, 99.5% of samples were successfully detected using the AI model, and the model showed 100% accuracy for ploidy classification. In the clinical application stage, out of 19&#x2009;103 PGT samples, 19&#x2009;069 were successfully analysed using the model, with 110 (0.57%) identified as having abnormal ploidy embryos. Among these, 12.7% (14/110) were identified as GW-UPD, and 87.3% (96/110) were triploid. Among 5563 diploid blastocysts transferred, 3478 clinical pregnancies were achieved. Subsequent ploidy analysis was performed for 217 spontaneous abortion and 935 prenatal diagnostic samples, and no abnormal ploidy was identified. Furthermore, of the 140 1PN embryos tested, 40 (28.6%) exhibited GW-UPD, 3 (2.1%) exhibited triploidy, and 97 (69.3%) were determined to be biparental and normally fertilized. Among the 97 biparental embryos, 46 were diploid, 11 were mosaic, and 40 were aneuploid. In terms of the insemination pattern, the percentage of abnormal ploidy in ICSI was significantly higher than in conventional IVF (P&#x2009;<&#x2009;0.01, 37.1% vs. 2.9%, respectively). With full informed consent, 20 patients without euploidy from normal fertilization chose 1PN-derived biparental and diploid blastocysts to transfer, resulting in 10 clinical pregnancies and 9 ongoing pregnancies. LARGE-SCALE DATA: N/A. LIMITATIONS REASONS FOR CAUTION: Some rare ploidy abnormalities, such as polyploidy with an equal number of identical sets of chromosomes and ploidy mosaicism cannot be accurately identified. Moreover, the origin of abnormal ploidy was not identified due to the unavailability of DNA from both parents. WIDER IMPLICATIONS OF THE FINDINGS: The PGT-Plus AI model provides a ploidy evaluation method based on the conventional PGT-A data and integrates directly into standard PGT-A workflows. Clinical utility results suggest that the model is a valuable tool for identifying embryos with abnormal ploidy in PGT-A and rescuing normal diploid embryos from abnormally fertilized embryos. These findings demonstrate that PGT-Plus significantly enhances the diagnostic accuracy of PGT. STUDY FUNDING/COMPETING INTERESTS: This study was supported by grants from Major Scientific Program of CITIC Group (No. 2023ZXKYB34100, to Ge.L.), Hunan Provincial Grant for Innovative Province Construction (2019SK4012), Hunan Xiangjiang New District (Changsha High-tech Zone) key core technology research project in 2023, and Science Foundation of Hunan Province (Grant 2023JJ30422). All authors declared no conflicts of interest..

artificial intelligence↗