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Abstract Pediatric patients with recurrent and refractory cancers are in most need for new treatments. This study developed patient-derived-xenograft (PDX) models within the European MAPPYACTS cancer precision medicine trial (NCT02613962). To date, 131 PDX models were established following heterotopical and/or orthotopical implantation in immunocompromised mice: 76 sarcomas, 25 other solid tumors, 12 central nervous system tumors, 15 acute leukemias, and 3 lymphomas. PDX establishment rate was 43%. Histology, whole exome and RNA sequencing revealed a high concordance with the primary patient’s tumor profile, human leukocyte-antigen characteristics and specific metabolic pathway signatures. A detailed patient molecular characterization, including specific mutations prioritized in the clinical molecular tumor boards are provided. Ninety models were shared with the IMI2 ITCC Pediatric Preclinical Proof-of-concept Platform (IMI2 ITCC-P4) for further exploitation. This PDX biobank of unique recurrent childhood cancers provides an essential support for basic and translational research and treatments development in advanced pediatric malignancies.

Abstract In the treatment of most newly discovered solid cancerous tumors, surgery remains the first treatment option. An important factor in the success of these operations is the precise identification of oncological safety margins to ensure the complete removal of the tumor without affecting much of the neighboring healthy tissue. Here we report on the possibility of applying femtosecond Laser-Induced Breakdown Spectroscopy (LIBS) combined with Machine Learning algorithms as an alternative discrimination technique to differentiate cancerous tissue. The emission spectra following the ablation on thin fixed liver and breast postoperative samples were recorded with high spatial resolution; adjacent stained sections served as a reference for tissue identification by classical pathological analysis. In a proof of principle test performed on liver tissue, Artificial Neural Networks and Random Forest algorithms were able to differentiate both healthy and tumor tissue with a very high Classification Accuracy of around 0.95. The ability to identify unknown tissue was performed on breast samples from different patients, also providing a high level of discrimination. Our results show that LIBS with femtosecond lasers is a technique with potential to be used in clinical applications for rapid identification of tissue type in the intraoperative surgical field.

NADH provides electrons for aerobic ATP production. In cells deprived of oxygen or with impaired electron transport chain activity, NADH accumulation can be toxic. To minimize such toxicity, elevated NADH inhibits the classical NADH-producing pathways: glucose, glutamine, and fat oxidation. Here, through deuterium-tracing studies in cultured cells and mice, we show that folate-dependent serine catabolism also produces substantial NADH. Strikingly, when respiration is impaired, serine catabolism through methylene tetrahydrofolate dehydrogenase (MTHFD2) becomes a major NADH source. In cells whose respiration is slowed by hypoxia, metformin, or genetic lesions, mitochondrial serine catabolism inhibition partially normalizes NADH levels and facilitates cell growth. In mice with engineered mitochondrial complex I deficiency (NDUSF4-/-), serine's contribution to NADH is elevated, and progression of spasticity is modestly slowed by pharmacological blockade of serine degradation. Thus, when respiration is impaired, serine catabolism contributes to toxic NADH accumulation.

Abstract The application of machine learning models to predict material properties is determined by the availability of high-quality data. We present an expert-curated dataset of lithium ion conductors and associated lithium ion conductivities measured by a.c. impedance spectroscopy. This dataset has 820 entries collected from 214 sources; entries contain a chemical composition, an expert-assigned structural label, and ionic conductivity at a specific temperature (from 5 to 873 °C). There are 403 unique chemical compositions with an associated ionic conductivity near room temperature (15–35 °C). The materials contained in this dataset are placed in the context of compounds reported in the Inorganic Crystal Structure Database with unsupervised machine learning and the Element Movers Distance. This dataset is used to train a CrabNet-based classifier to estimate whether a chemical composition has high or low ionic conductivity. This classifier is a practical tool to aid experimentalists in prioritizing candidates for further investigation as lithium ion conductors.

Mammalian organs continually exchange metabolites via circulation, but systems-level analysis of this shuttling process is lacking. Here, we compared, in fasted pigs, metabolite concentrations in arterial blood versus draining venous blood from 11 organs. Greater than 90% of metabolites showed arterial-venous differences across at least one organ. Surprisingly, the liver and kidneys released not only glucose but also amino acids, both of which were consumed primarily by the intestine and pancreas. The liver and kidneys exhibited additional unexpected activities: liver preferentially burned unsaturated over more atherogenic saturated fatty acids, whereas the kidneys were unique in burning circulating citrate and net oxidizing lactate to pyruvate, thereby contributing to circulating redox homeostasis. Furthermore, we observed more than 700 other cases of tissue-specific metabolite production or consumption, such as release of nucleotides by the spleen and TCA intermediates by pancreas. These data constitute a high-value resource, providing a quantitative atlas of inter-organ metabolite exchange.

Control tissue in studies of various orthopedic pathologies is difficult to obtain and presumably equivalent biopsies from other anatomic sites have been utilized in its place. However, for growth plates, different anatomic regions are subject to dissimilar mechanical forces and produce disproportionate longitudinal growth. The purpose of this study was to compare gene expression and structure in normal physes from different anatomic regions within a single animal species to determine whether such physes were equivalent. Thirteen female New Zealand white rabbits (five 15-week-old and eight 19-week-old animals) were euthanized and physes harvested from their proximal and distal femurs and proximal tibiae. Harvested physes were divided into groups for histological, immunohistochemical (IHC), and reverse transcription-quantitative polymerase chain reaction analyses. All physes analyzed demonstrated no apparent differences in morphology or proteoglycan staining intensity on histological examination or in type II collagen presence determined by IHC study. Histomorphometric measures of physeal height as well as gene expression of type II collagen and aggrecan were found to be statistically significantly equivalent (p

Elevations in branched-chain amino acids (BCAAs) associate with numerous systemic diseases, including cancer, diabetes, and heart failure. However, an integrated understanding of whole-body BCAA metabolism remains lacking. Here, we employ in vivo isotopic tracing to systemically quantify BCAA oxidation in healthy and insulin-resistant mice. We find that most tissues rapidly oxidize BCAAs into the tricarboxylic acid (TCA) cycle, with the greatest quantity occurring in muscle, brown fat, liver, kidneys, and heart. Notably, pancreas supplies 20% of its TCA carbons from BCAAs. Genetic and pharmacologic suppression of branched-chain alpha-ketoacid dehydrogenase kinase, a clinically targeted regulatory kinase, induces BCAA oxidation primarily in skeletal muscle of healthy mice. While insulin acutely increases BCAA oxidation in cardiac and skeletal muscle, chronically insulin-resistant mice show blunted BCAA oxidation in adipose tissues and liver, shifting BCAA oxidation toward muscle. Together, this work provides a quantitative framework for understanding systemic BCAA oxidation in health and insulin resistance.

Ceramic matrix composites (CMCs) on one level are excellent materials for acoustic emission (AE) analysis. They are excellent waveguides for AE waveform transmission due to the high modulus to density ratio. CMC inelastic behavior is due to micro‐ and macrocrack formation from matrix crack interaction with the fibers via a relatively weak fiber/matrix interface which create ideal stress waves. Because of this, AE is an excellent detector of microcracks in general, and most importantly in the case of CMCs, the initial or lowest stress crack formation. This property can be related to long time stressed‐oxidation degradation of nonoxide composites, in particular. In addition, AE has been used to effectively determine the stress distribution for matrix cracks which cause the nonlinear stress–strain behavior. However, a key to quantitatively correlating AE with sources is first and foremost to locate where the AE originated. For a tensile test, most AE comes from the near‐grip region and the radius region outside the gage area of interest. Outside the gage region AE would not be considered useful data pertaining to stress/strain behavior and must be sorted out from the AE dataset. Location is determined by the difference in time of arrivals (TOAs) of waveforms received on each sensor from a given AE source. Automated TOA techniques such as threshold voltage crossing or Akaike information criteria (AIC) have limitations in overall accuracy of differences in TOA (Δt) of two different sensors required for location analysis. This study has incorporated several signal filter and enhancement techniques and an approach toward increasing the accuracy of the classic TOA techniques. First TOA was determined for the two sensors of the AE tests "manually" based on first extensional peak of the waveform, this served as the "exact" difference in TOA. Δt's were then determined for the various filter/TOA techniques and compared to those from the manual determined Δt. The best filter/TOA techniques resulted in more than two times better accuracy (defined as percentage of events within 0.1 µs of the exact Δt) than the conventional threshold crossing or AIC technique. [ABSTRACT FROM AUTHOR]

More than 35,000 children are diagnosed with cancer and treated in Europe each year. With the 1st SIOP Europe Course in Paediatric Oncology, the European Society for Paediatric Oncology (SIOP Europe) aimed to equip aspiring physicians to become leaders within a pan-European network and ensure state-of-the-art treatment for children across Europe. Fifty participants from 24 countries and 37 centres were enrolled on the course. With a virtual and a face-to-face meeting complete, we herewith report on the course concept, application process and first meetings of this 3-year educational program.

Excessive consumption of sweets is a risk factor for metabolic syndrome. A major chemical feature of sweets is fructose. Despite strong ties between fructose and disease, the metabolic fate of fructose in mammals remains incompletely understood. Here we use isotope tracing and mass spectrometry to track the fate of glucose and fructose carbons in vivo, finding that dietary fructose is cleared by the small intestine. Clearance requires the fructose-phosphorylating enzyme ketohexokinase. Low doses of fructose are ∼90% cleared by the intestine, with only trace fructose but extensive fructose-derived glucose, lactate, and glycerate found in the portal blood. High doses of fructose (≥1 g/kg) overwhelm intestinal fructose absorption and clearance, resulting in fructose reaching both the liver and colonic microbiota. Intestinal fructose clearance is augmented both by prior exposure to fructose and by feeding. We propose that the small intestine shields the liver from otherwise toxic fructose exposure.

Machine learning has the potential to significantly speed-up the discovery of new materials in synthetic materials chemistry. Here the authors combine unsupervised machine learning and crystal structure prediction to predict a novel quaternary lithium solid electrolyte that is then synthesized.

Mammalian tissues are fuelled by circulating nutrients, including glucose, amino acids, and various intermediary metabolites. Under aerobic conditions, glucose is generally assumed to be burned fully by tissues via the tricarboxylic acid cycle (TCA cycle) to carbon dioxide. Alternatively, glucose can be catabolized anaerobically via glycolysis to lactate, which is itself also a potential nutrient for tissues and tumours. The quantitative relevance of circulating lactate or other metabolic intermediates as fuels remains unclear. Here we systematically examine the fluxes of circulating metabolites in mice, and find that lactate can be a primary source of carbon for the TCA cycle and thus of energy. Intravenous infusions of 13C-labelled nutrients reveal that, on a molar basis, the circulatory turnover flux of lactate is the highest of all metabolites and exceeds that of glucose by 1.1-fold in fed mice and 2.5-fold in fasting mice; lactate is made primarily from glucose but also from other sources. In both fed and fasted mice, 13C-lactate extensively labels TCA cycle intermediates in all tissues. Quantitative analysis reveals that during the fasted state, the contribution of glucose to tissue TCA metabolism is primarily indirect (via circulating lactate) in all tissues except the brain. In genetically engineered lung and pancreatic cancer tumours in fasted mice, the contribution of circulating lactate to TCA cycle intermediates exceeds that of glucose, with glutamine making a larger contribution than lactate in pancreatic cancer. Thus, glycolysis and the TCA cycle are uncoupled at the level of lactate, which is a primary circulating TCA substrate in most tissues and tumours.

Combining optoacoustic (OA) imaging with ultrasound (US) enables visualisation of functional blood vasculature in breast lesions by OA to be overlaid with the morphological information of US. Here, we develop a simple OA feature set to differentiate benign and malignant breast lesions. 94 female patients with benign, indeterminate or suspicious lesions were recruited and underwent OA-US. An OA-US imaging feature set was developed using images from the first 38 patients, which contained 14 malignant and 8 benign solid lesions. Two independent radiologists blindly scored the OA-US images of a further 56 patients, which included 31 malignant and 13 benign solid lesions, with a sensitivity of 96.8% and specificity of 84.6%. Our findings indicate that OA-US can reveal vascular patterns of breast lesions that indicate malignancy using a simple feature set based on single wavelength OA data, which is therefore amenable to application in low resource settings for breast cancer management.

Titanium alloys are key materials for aerospace and turbine industries. Direct energy deposition (DED) is one additive manufacturing method of interest for titanium alloy repair technology. One notable feature of directed energy deposition (DED) technique is the anisotropy of the microstructure due to the build directions and local heating during layer-by-layer formations. To explore the anisotropy in fatigue crack growth (FCG) properties, single-notched, compact specimens were cut and machined from thin “repaired coupon”, i.e., half AM and half wrought Ti–6Al–4V coupon, perpendicular and parallel to the build layers; the geometry was smaller than that required by standard crack growth testing procedures. Using these small coupons, fracture properties were attained for crack growth in either parallel or perpendicular directions with respect to the build layers. Direct current potential drop (DCPD) was utilized to monitor and measured crack length during fatigue. Optical and scanning electron microscopy was performed to investigate the failure mechanisms and microstructural morphology of polished cross-section and fractured surfaces, respectively. The results show that the crack growth direction parallel to the build layer (perpendicular to the build direction) had lower FCG resistance compared to crack growth direction perpendicular to the build layer (parallel to the build direction). The difference in the FCG rate is attributed to the microstructural features and the materials growth directions. Therefore, these clearly findings show that microstructure characteristics have strong influence on fatigue crack growth behavior in both directions of growth as observed in this study.

Photoacoustic imaging (PAI) is an emerging modality that has shown promise for improving patient management in a range of applications. Unfortunately, the current lack of uniformity in PAI data formats compromises inter-user data exchange and comparison, which impedes: technological progress; effective research collaboration; and efforts to deliver multi-centre clinical trials. To overcome this challenge, the International Photoacoustic Standardisation Consortium (IPASC) has established a data format with a defined consensus metadata structure and developed an open-source software application programming interface (API) to enable conversion from proprietary file formats into the IPASC format. The format is based on Hierarchical Data Format 5 (HDF5) and designed to store photoacoustic raw time series data. Internal quality control mechanisms are included to ensure completeness and consistency of the converted data. By unifying the variety of proprietary data and metadata definitions into a consensus format, IPASC hopes to facilitate the exchange and comparison of PAI data.