Free thyroxine measurement in clinical practice: how to optimize indications, analytical procedures, and interpretation criteria while waiting for global standardization

Thyroid dysfunctions are among the most common endocrine disorders and accurate biochemical testing is needed to confirm or rule out a diagnosis. Notably, true hyperthyroidism and hypothyroidism in the setting of a normal thyroid-stimulating hormone level are highly unlikely, making the assessment of free thyroxine (FT4) inappropriate in most new cases. However, FT4 measurement is integral in both the diagnosis and management of relevant central dysfunctions (central hypothyroidism and central hyperthyroidism) as well as for monitoring therapy in hyperthyroid patients treated with anti-thyroid drugs or radioiodine. In such settings, accurate FT4 quantification is required. Global standardization will improve the comparability of the results across laboratories and allow the development of common clinical decision limits in evidence-based guidelines. The International Federation of Clinical Chemistry and Laboratory Medicine Committee for Standardization of Thyroid Function Tests has undertaken FT4 immunoassay method comparison and recalibration studies and developed a reference measurement procedure that is currently being validated. However, technical and implementation challenges, including the establishment of different clinical decision limits for distinct patient groups, still remain. Accordingly, different assays and reference values cannot be interchanged. Two-way communication between the laboratory and clinical specialists is pivotal to properly select a reliable FT4 assay, establish reference intervals, investigate discordant results, and monitor the analytical and clinical performance of the method over time

CFD modelling of a spark ignition internal combustion engine fuelled with syngas for a mCHP system

Micro Combined Heat and Power (mCHP) powered with biomass is nowadays a technology attracting increasing interest to develop a local supply chain to produce, process and valorise the available material in territorial areas as much as possible circumscribed, with a considerable reduction also of the CO2 related to transportation. Application for biomass powered mCHP produces environmental benefits by reducing primary energy consumption and associated greenhouse gas emissions and complies with the need for increased decentralization of energy supply. Of particular relevance is mCHP based on biomass gasification due to the negligible particulate matter release with respect to combustion. The present work describes a 3D CFD model of the spark ignition (SI) internal combustion engine (ICE) fuelled with syngas installed in the mCHP pilot system ECO20 manufactured by the Italian company Costruzioni Motori Diesel S.p.A. (CMD). The considered system is made of a gasifier combined with proper syngas cleaning devices, an ICE and a generator to deliver a maximum electrical and thermal power of 20 kW and 40 kW, respectively. For the proper initialisation of the 3D CFD model, the syngas composition is experimentally characterised using a gas-chromatograph on samples collected under real operation. The calculated pressure cycle is verified by comparison with the one calculated through a properly developed 1D ICE model. Main goals of the performed numerical analysis are to study into detail the combustion process and to assess the engine performance characteristics related to the use of syngas

Developing Symptom Lists for People with Cancer Treated with Targeted Therapies

Background: Targeted Therapies (TTs) have revolutionised cancer treatment with their enhanced specificity of action. Compared with conventional therapies, TTs are delivered over a longer period and often have unusual symptom profiles. Patient reported outcome measures such as symptom side-effect lists need to be developed in a time-efficient manner to enable a rapid and full evaluation of new treatments and effective clinical managementObjective: the aim of this study is to develop a set of TT-related symptoms and identify the optimal method for developing symptom lists. Patients and Methods: symptoms from TT treatment in the context of Chronic Myeloid Leukaemia (CML), HER2 positive breast cancer, or Gastrointestinal Stromal Tumours (GIST) were identified through literature reviews, interviews with health care professionals (HCPs) and patients, and patient focus groups. The symptom set was then pilot tested in patients across the three cancer diagnoses: The number of items derived from each source (literature, patients, or HCPs) were compared. Results: a total of 316 patients and 86 HCPs from 16 countries participated. An initial set of 209 symptoms was reduced to 61 covering 12 symptom categories. Patient interviews made the greatest contribution to the item set.Conclusions: symptom lists should be created based on input from patients. The item set described will be applicable to the assessment of new TTs, and in monitoring treatment.<br/

Nile red fluorescence screening facilitating neutral lipid phenotype determination in budding yeast, Saccharomyces cerevisiae, and the fission yeast Schizosaccharomyces pombe.

Investigation of yeast neutral lipid accumulation is important for biotechnology and also for modelling aberrant lipid metabolism in human disease. The Nile red (NR) method has been extensively utilised to determine lipid phenotypes of yeast cells via microscopic means. NR assays have been used to differentiate lipid accumulation and relative amounts of lipid in oleaginous species but have not been thoroughly validated for phenotype determination arising from genetic modification. A modified NR assay, first described by Sitepu et al. (J Microbiol Methods 91:321-328, 2012), was able to detect neutral lipid changes in Saccharomyces cerevisiae deletion mutants with sensitivity similar to more advanced methodology. We have also be able to, for the first time, successfully apply the NR assay to the well characterised fission yeast Schizosaccharomyces pombe, an increasingly important organism in biotechnology. The described NR fluorescence assay is suitable for increased throughput and rapid screening of genetically modified strains in both the biotechnology industry and for modelling ectopic lipid production for a variety of human diseases. This ultimately negates the need for labour intensive and time consuming lipid analyses of samples that may not yield a desirable lipid phenotype, whilst genetic modifications impacting significantly on the cellular lipid phenotype can be further promoted for more in depth analyses

Saccharomyces Genome Database: the genomics resource of budding yeast

The Saccharomyces Genome Database (SGD, http://www.yeastgenome.org) is the community resource for the budding yeast Saccharomyces cerevisiae. The SGD project provides the highest-quality manually curated information from peer-reviewed literature. The experimental results reported in the literature are extracted and integrated within a well-developed database. These data are combined with quality high-throughput results and provided through Locus Summary pages, a powerful query engine and rich genome browser. The acquisition, integration and retrieval of these data allow SGD to facilitate experimental design and analysis by providing an encyclopedia of the yeast genome, its chromosomal features, their functions and interactions. Public access to these data is provided to researchers and educators via web pages designed for optimal ease of use

Tyrosine Phosphorylation of the UDP-Glucose Dehydrogenase of Escherichia coli Is at the Crossroads of Colanic Acid Synthesis and Polymyxin Resistance

BACKGROUND:In recent years, an idiosyncratic new class of bacterial enzymes, named BY-kinases, has been shown to catalyze protein-tyrosine phosphorylation. These enzymes share no structural and functional similarities with their eukaryotic counterparts and, to date, only few substrates of BY-kinases have been characterized. BY-kinases have been shown to participate in various physiological processes. Nevertheless, we are at a very early stage of defining their importance in the bacterial cell. In Escherichia coli, two BY-kinases, Wzc and Etk, have been characterized biochemically. Wzc has been shown to phosphorylate the UDP-glucose dehydrogenase Ugd in vitro. Not only is Ugd involved in the biosynthesis of extracellular polysaccharides, but also in the production of UDP-4-amino-4-deoxy-L-arabinose, a compound that renders E. coli resistant to cationic antimicrobial peptides. METHODOLOGY/PRINCIPAL FINDINGS:Here, we studied the role of Ugd phosphorylation. We first confirmed in vivo the phosphorylation of Ugd by Wzc and we demonstrated that Ugd is also phosphorylated by Etk, the other BY-kinase identified in E. coli. Tyrosine 71 (Tyr71) was characterized as the Ugd site phosphorylated by both Wzc and Etk. The regulatory role of Tyr71 phosphorylation on Ugd activity was then assessed and Tyr71 mutation was found to prevent Ugd activation by phosphorylation. Further, Ugd phosphorylation by Wzc or Etk was shown to serve distinct physiological purposes. Phosphorylation of Ugd by Wzc was found to participate in the regulation of the amount of the exopolysaccharide colanic acid, whereas Etk-mediated Ugd phosphorylation appeared to participate in the resistance of E. coli to the antibiotic polymyxin. CONCLUSIONS/SIGNIFICANCE:Ugd phosphorylation seems to be at the junction between two distinct biosynthetic pathways, illustrating the regulatory potential of tyrosine phosphorylation in bacterial physiology

Correlation of cell growth and heterologous protein production by Saccharomyces cerevisiae

With the increasing demand for biopharmaceutical proteins and industrial enzymes, it is necessary to optimize the production by microbial fermentation or cell cultures. Yeasts are well established for the production of a wide range of recombinant proteins, but there are also some limitations; e.g., metabolic and cellular stresses have a strong impact on recombinant protein production. In this work, we investigated the effect of the specific growth rate on the production of two different recombinant proteins. Our results show that human insulin precursor is produced in a growth-associated manner, whereas alpha-amylase tends to have a higher yield on substrate at low specific growth rates. Based on transcriptional analysis, we found that the difference in the production of the two proteins as function of the specific growth rate is mainly due to differences in endoplasmic reticulum processing, protein turnover, cell cycle, and global stress response. We also found that there is a shift at a specific growth rate of 0.1 h(-1) that influences protein production. Thus, for lower specific growth rates, the alpha-amylase and insulin precursor-producing strains present similar cell responses and phenotypes, whereas for higher specific growth rates, the two strains respond differently to changes in the specific growth rate

Predicting Benefit From Immune Checkpoint Inhibitors in Patients With Non-Small-Cell Lung Cancer by CT-Based Ensemble Deep Learning: A Retrospective Study

BACKGROUND: Only around 20-30% of patients with non-small-cell lung cancer (NCSLC) have durable benefit from immune-checkpoint inhibitors. Although tissue-based biomarkers (eg, PD-L1) are limited by suboptimal performance, tissue availability, and tumour heterogeneity, radiographic images might holistically capture the underlying cancer biology. We aimed to investigate the application of deep learning on chest CT scans to derive an imaging signature of response to immune checkpoint inhibitors and evaluate its added value in the clinical context. METHODS: In this retrospective modelling study, 976 patients with metastatic, EGFR/ALK negative NSCLC treated with immune checkpoint inhibitors at MD Anderson and Stanford were enrolled from Jan 1, 2014, to Feb 29, 2020. We built and tested an ensemble deep learning model on pretreatment CTs (Deep-CT) to predict overall survival and progression-free survival after treatment with immune checkpoint inhibitors. We also evaluated the added predictive value of the Deep-CT model in the context of existing clinicopathological and radiological metrics. FINDINGS: Our Deep-CT model demonstrated robust stratification of patient survival of the MD Anderson testing set, which was validated in the external Stanford set. The performance of the Deep-CT model remained significant on subgroup analyses stratified by PD-L1, histology, age, sex, and race. In univariate analysis, Deep-CT outperformed the conventional risk factors, including histology, smoking status, and PD-L1 expression, and remained an independent predictor after multivariate adjustment. Integrating the Deep-CT model with conventional risk factors demonstrated significantly improved prediction performance, with overall survival C-index increases from 0·70 (clinical model) to 0·75 (composite model) during testing. On the other hand, the deep learning risk scores correlated with some radiomics features, but radiomics alone could not reach the performance level of deep learning, indicating that the deep learning model effectively captured additional imaging patterns beyond known radiomics features. INTERPRETATION: This proof-of-concept study shows that automated profiling of radiographic scans through deep learning can provide orthogonal information independent of existing clinicopathological biomarkers, bringing the goal of precision immunotherapy for patients with NSCLC closer

Guidelines and Recommendations on Yeast Cell Death Nomenclature

Elucidating the biology of yeast in its full complexity has major implications for science, medicine and industry. One of the most critical processes determining yeast life and physiology is cellular demise. However, the investigation of yeast cell death is a relatively young field, and a widely accepted set of concepts and terms is still missing. Here, we propose unified criteria for the definition of accidental, regulated, and programmed forms of cell death in yeast based on a series of morphological and biochemical criteria. Specifically, we provide consensus guidelines on the differential definition of terms including apoptosis, regulated necrosis, and autophagic cell death, as we refer to additional cell death routines that are relevant for the biology of (at least some species of) yeast. As this area of investigation advances rapidly, changes and extensions to this set of recommendations will be implemented in the years to come. Nonetheless, we strongly encourage the authors, reviewers and editors of scientific articles to adopt these collective standards in order to establish an accurate framework for yeast cell death research and, ultimately, to accelerate the progress of this vibrant field of research