Automated lesion detection of breast cancer in [18F] FDG PET/CT using a novel AI-Based workflow

UNLABELLED: Applications based on artificial intelligence (AI) and deep learning (DL) are rapidly being developed to assist in the detection and characterization of lesions on medical images. In this study, we developed and examined an image-processing workflow that incorporates both traditional image processing with AI technology and utilizes a standards-based approach for disease identification and quantitation to segment and classify tissue within a whole-body [ METHODS: One hundred thirty baseline PET/CT studies from two multi-institutional preoperative clinical trials in early-stage breast cancer were semi-automatically segmented using techniques based on PERCIST v1.0 thresholds and the individual segmentations classified as to tissue type by an experienced nuclear medicine physician. These classifications were then used to train a convolutional neural network (CNN) to automatically accomplish the same tasks. RESULTS: Our CNN-based workflow demonstrated Sensitivity at detecting disease (either primary lesion or lymphadenopathy) of 0.96 (95% CI [0.9, 1.0], 99% CI [0.87,1.00]), Specificity of 1.00 (95% CI [1.0,1.0], 99% CI [1.0,1.0]), DICE score of 0.94 (95% CI [0.89, 0.99], 99% CI [0.86, 1.00]), and Jaccard score of 0.89 (95% CI [0.80, 0.98], 99% CI [0.74, 1.00]). CONCLUSION: This pilot work has demonstrated the ability of AI-based workflow using DL-CNNs to specifically identify breast cancer tissue as determined by

Land management explains major trends in forest structure and composition over the last millennium in California's Klamath Mountains

For millennia, forest ecosystems in California have been shaped by fire from both natural processes and Indigenous land management, but the notion of climatic variation as a primary controller of the pre-colonial landscape remains pervasive. Understanding the relative influence of climate and Indigenous burning on the fire regime is key because contemporary forest policy and management are informed by historical baselines. This need is particularly acute in California, where 20th-century fire suppression, coupled with a warming climate, has caused forest densification and increasingly large wildfires that threaten forest ecosystem integrity and management of the forests as part of climate mitigation efforts. We examine climatic versus anthropogenic influence on forest conditions over 3 millennia in the western Klamath Mountains—the ancestral territories of the Karuk and Yurok Tribes—by combining paleoenvironmental data with Western and Indigenous knowledge. A fire regime consisting of tribal burning practices and lightning were associated with long-term stability of forest biomass. Before Euro-American colonization, the long-term median forest biomass was between 104 and 128 Mg/ha, compared to values over 250 Mg/ha today. Indigenous depopulation after AD 1800, coupled with 20th-century fire suppression, likely allowed biomass to increase, culminating in the current landscape: a closed Douglas fir–dominant forest unlike any seen in the preceding 3,000 y. These findings are consistent with precontact forest conditions being influenced by Indigenous land management and suggest large-scale interventions could be needed to return to historic forest biomass levels

Massive migration from the steppe is a source for Indo-European languages in Europe

We generated genome-wide data from 69 Europeans who lived between 8,000-3,000 years ago by enriching ancient DNA libraries for a target set of almost four hundred thousand polymorphisms. Enrichment of these positions decreases the sequencing required for genome-wide ancient DNA analysis by a median of around 250-fold, allowing us to study an order of magnitude more individuals than previous studies and to obtain new insights about the past. We show that the populations of western and far eastern Europe followed opposite trajectories between 8,000-5,000 years ago. At the beginning of the Neolithic period in Europe, ~8,000-7,000 years ago, closely related groups of early farmers appeared in Germany, Hungary, and Spain, different from indigenous hunter-gatherers, whereas Russia was inhabited by a distinctive population of hunter-gatherers with high affinity to a ~24,000 year old Siberian6 . By ~6,000-5,000 years ago, a resurgence of hunter-gatherer ancestry had occurred throughout much of Europe, but in Russia, the Yamnaya steppe herders of this time were descended not only from the preceding eastern European hunter-gatherers, but from a population of Near Eastern ancestry. Western and Eastern Europe came into contact ~4,500 years ago, as the Late Neolithic Corded Ware people from Germany traced ~3/4 of their ancestry to the Yamnaya, documenting a massive migration into the heartland of Europe from its eastern periphery. This steppe ancestry persisted in all sampled central Europeans until at least ~3,000 years ago, and is ubiquitous in present-day Europeans. These results provide support for the theory of a steppe origin of at least some of the Indo-European languages of Europe

The metabolic microenvironment of melanomas: prognostic value of MCT1 and MCT4

BRAF mutations are known drivers of melanoma development and, recently, were also described as players in the Warburg effect, while this reprogramming of energy metabolism has been identified as a possible strategy for treating melanoma patients. Therefore, the aim of this work was to evaluate the expression and prognostic value of a panel of glycolytic metabolism-related proteins in a series of melanomas. The immunohistochemical expression of MCT1, MCT4, GLUT1, and CAIX was evaluated in 356 patients presenting melanoma and 20 patients presenting benign nevi. Samples included 20 benign nevi, 282 primary melanomas, 117 lymph node and 54 distant metastases samples. BRAF mutation was observed in 29/92 (31.5%) melanoma patients and 17/20 (85%) benign nevi samples. NRAS mutation was observed in 4/36 (11.1%) melanoma patients and 1/19 (5.3%) benign nevi samples. MCT4 and GLUT1 expression was significantly increased in metastatic samples, and MCT1, MCT4 and GLUT1 were significantly associated with poor prognostic variables. Importantly, MCT1 and MCT4 were associated with shorter overall survival. In conclusion, the present study brings new insights on metabolic aspects of melanoma, paving the way for the development of new-targeted therapies.This work was supported by FAPESP grant to VLV (2012/04194-1) and CP (2015/25351-6). VMG received a doctoral fellowship (SFRH/BD/51997/2012) from Fundacao para a Ciencia e a Tecnologia (FCT) and ON. 2 SR&TD Integrated Program (NORTE-07-0124-FEDER-000017) co-funded by Programa Operacional Regional do Norte (ON.2- O Novo Norte), Quadro de Referencia Estrategico Nacional (QREN), through Fundo Europeu de Desenvolvimento Regional (FEDER).info:eu-repo/semantics/publishedVersio

Agonist-mediated switching of ion selectivity in TPC2 differentially promotes lysosomal function

Ion selectivity is a defining feature of a given ion channel and is considered immutable. Here we show that ion selectivity of the lysosomal ion channel TPC2, which is hotly debated (Calcraft et al., 2009;Guo et al., 2017;Jha et al., 2014;Ruas et al., 2015;Wang et al., 2012), depends on the activating ligand. A high-throughput screen identified two structurally distinct TPC2 agonists. One of these evoked robust Ca2+-signals and non-selective cation currents, the other weaker Ca2+-signals and Na+-selective currents. These properties were mirrored by the Ca2+ mobilizing messenger, NAADP and the phosphoinositide, PI(3,5)P-2, respectively. Agonist action was differentially inhibited by mutation of a single TPC2 residue and coupled to opposing changes in lysosomal pH and exocytosis. Our findings resolve conflicting reports on the permeability and gating properties of TPC2 and they establish a new paradigm whereby a single ion channel mediates distinct, functionally-relevant ionic signatures on demand

Metabolite ratios as potential biomarkers for type 2 diabetes:a DIRECT study

Aims/hypothesis Circulating metabolites have been shown to reflect metabolic changes during the development of type 2 diabetes. In this study we examined the association of metabolite levels and pairwise metabolite ratios with insulin responses after glucose, glucagon-like peptide-1 (GLP-1) and arginine stimulation. We then investigated if the identified metabolite ratios were associated with measures of OGTT-derived beta cell function and with prevalent and incident type 2 diabetes. Methods We measured the levels of 188 metabolites in plasma samples from 130 healthy members of twin families (from the Netherlands Twin Register) at five time points during a modified 3 h hyperglycaemic clamp with glucose, GLP-1 and arginine stimulation. We validated our results in cohorts with OGTT data (n = 340) and epidemiological case–control studies of prevalent (n = 4925) and incident (n = 4277) diabetes. The data were analysed using regression models with adjustment for potential confounders. Results There were dynamic changes in metabolite levels in response to the different secretagogues. Furthermore, several fasting pairwise metabolite ratios were associated with one or multiple clamp-derived measures of insulin secretion (all p Conclusion/interpretation In this study we have shown that the Val_PC ae C32:2 metabolite ratio is associated with an increased risk of type 2 diabetes and measures of insulin secretion and resistance. The observed effects were stronger than that of the individual metabolites and independent of known risk factors.</p