MYC sensitises cells to apoptosis by driving energetic demand

The MYC oncogene is a potent driver of growth and proliferation but also sensitises cells to apoptosis, which limits its oncogenic potential. MYC induces several biosynthetic programmes and primary cells overexpressing MYC are highly sensitive to glutamine withdrawal suggesting that MYC-induced sensitisation to apoptosis may be due to imbalance of metabolic/energetic supply and demand. Here we show that MYC elevates global transcription and translation, even in the absence of glutamine, revealing metabolic demand without corresponding supply. Glutamine withdrawal from MRC-5 fibroblasts depletes key tricarboxylic acid (TCA) cycle metabolites and, in combination with MYC activation, leads to AMP accumulation and nucleotide catabolism indicative of energetic stress. Further analyses reveal that glutamine supports viability through TCA cycle energetics rather than asparagine biosynthesis and that TCA cycle inhibition confers tumour suppression on MYC-driven lymphoma in vivo. In summary, glutamine supports the viability of MYC-overexpressing cells through an energetic rather than a biosynthetic mechanism

Uridine-derived ribose fuels glucose-restricted pancreatic cancer

Pancreatic ductal adenocarcinoma (PDA) is a lethal disease notoriously resistant to therap

Novel therapeutical approaches to managing atherosclerotic risk

Atherosclerosis is a multifactorial vascular disease that leads to inflammation and stiff-ening of the arteries and decreases their elasticity due to the accumulation of calcium, small dense Low Density Lipoproteins (sdLDL), inflammatory cells, and fibrotic material. A review of studies pertaining to cardiometabolic risk factors, lipids alterations, hypolipidemic agents, nutraceuticals, hypoglycaemic drugs, atherosclerosis, endothelial dysfunction, and inflammation was performed. There are several therapeutic strategies including Proprotein Convertase Subtilisin/Kexin 9 (PCSK9) inhibitors, inclisiran, bempedoic acid, Glucagon-Like Peptide-1 Receptor agonists (GLP-1 RAs), and nutraceuticals that promise improvement in the atheromatous plaque from a molecular point of view, because have actions on the exposure of the LDL-Receptor (LDL-R), on endothelial dysfunction, activation of macrophages, on lipid oxidation, formations on foam cells, and deposition extracellular lipids. Atheroma plaque reduction both as a result of LDL-Cholesterol (LDL-C) intensive lowering and reducing inflammation and other residual risk factors is an integral part of the management of atherosclerotic disease, and the use of valid therapeutic alternatives appear to be appealing avenues to solving the problem

Fibrin glue for pilonidal sinus disease

Background Pilonidal sinus disease is a common condition that mainly affects young adults. This condition can cause significant pain and impairment of normal activities. No consensus currently exists on the optimum treatment for pilonidal sinus and current therapies have various advantages and disadvantages. Fibrin glue has emerged as a potential treatment as both monotherapy and an adjunct to surgery. Objectives To assess the effects of fibrin glue alone or in combination with surgery compared with surgery alone in the treatment of pilonidal sinus disease. Search methods In December 2016 we searched: the Cochrane Wounds Specialised Register; CENTRAL; MEDLINE; Embase and CINAHL Plus. We also searched clinical trials registries and conference proceedings for ongoing and unpublished studies and scanned reference lists to identify additional studies. There were no restrictions with respect to language, date of publication or study setting. Selection criteria We included randomised controlled trials (RCTs) only. We included studies involving participants of all ages and studies conducted in any setting. We considered studies involving people with both new and recurrent pilonidal sinus. We included studies which evaluated fibrin glue monotherapy or as an adjunct to surgery. Data collection and analysis Two study authors independently extracted data and assessed risk of bias. We used standard methods expected by Cochrane. Main results We included four RCTs with 253 participants, all were at risk of bias. One unpublished study evaluated fibrin glue monotherapy compared with Bascom's procedure, two studies evaluated fibrin glue as an adjunct to Limberg flap and one study evaluated fibrin glue as an adjunct to Karydakis flap. For fibrin glue monotherapy compared with Bascom's procedure, there were no data available for the primary outcomes of time to healing and adverse events. There was low-quality evidence of less pain on day one after the procedure with fibrin glue monotherapy compared with Bascom's procedure (mean difference (MD) -2.50, 95% confidence interval (CI) -4.03 to -0.97) (evidence downgraded twice for risk of performance and detection bias). Fibrin glue may reduce the time taken to return to normal activities compared with Bascom's procedure (mean time 42 days with surgery and 7 days with glue, MD -34.80 days, 95% CI -66.82 days to -2.78 days) (very low-quality evidence, downgraded as above and for imprecision). Fibrin glue as an adjunct to the Limberg flap may reduce the healing time from 22 to 8 days compared with the Limberg flap alone (MD -13.95 days, 95% CI -16.76 days to -11.14 days) (very low-quality evidence, downgraded twice for risk of selection, performance and detection bias and imprecision). It is uncertain whether use of fibrin glue affects the incidence of postoperative seroma (an adverse event) (risk ratio (RR) 0.27, 95% CI 0.05 to 1.61; very low-quality evidence, downgraded twice for risk of selection, performance and detection bias and imprecision). There was low-quality evidence that fibrin glue, as an adjunct to Limberg flap, may reduce postoperative pain (median 2 versus 4; P < 0.001) and time to return to normal activities (median 8 days versus 17 days; P < 0.001). The addition of fibrin glue to the Limberg flap may reduce the length of hospital stay (MD -1.69 days, 95% CI -2.08 days to -1.29 days) (very low-quality evidence, downgraded twice for risk of selection, performance and detection bias and for unexplained heterogeneity). A single RCT evaluating fibrin glue as an adjunct to the Karydakis flap did not report data for the primary outcome of time to healing. It is uncertain whether fibrin glue with the Karydakis flap affects the incidence of postoperative seroma (adverse event) (RR 3.00, 95% CI 0.67 to 13.46) (very low-quality evidence, downgraded twice for risk of selection, performance and detection bias and for imprecision). Fibrin glue as an adjunct to Karydakis flap may reduce length of stay but this is highly uncertain (mean 2 days versus 3.7 days; P < 0.001, low-quality evidence downgraded twice for risk of selection, performance and detection bias). Authors' conclusions Current evidence is uncertain regarding any benefits associated with fibrin glue either as monotherapy or as an adjunct to surgery for people with pilonidal sinus disease. We identified only four RCTs and each was small and at risk of bias resulting in very low-quality evidence for the primary outcomes of time to healing and adverse events. Future studies should enrol many more participants, ensure adequate randomisation and blinding, whilst measuring clinically relevant outcomes

Sex differences in brain tumor glutamine metabolism reveal sex-specific vulnerabilities to treatment

BACKGROUND: Brain cancer incidence and mortality rates are greater in males. Understanding the molecular mechanisms that underlie those sex differences could improve treatment strategies. Although sex differences in normal metabolism are well described, it is currently unknown whether they persist in cancerous tissue. METHODS: Using positron emission tomography (PET) imaging and mass spectrometry, we assessed sex differences in glioma metabolism in samples from affected individuals. We assessed the role of glutamine metabolism in male and female murine transformed astrocytes using isotope labeling, metabolic rescue experiments, and pharmacological and genetic perturbations to modulate pathway activity. FINDINGS: We found that male glioblastoma surgical specimens are enriched for amino acid metabolites, including glutamine. Fluoroglutamine PET imaging analyses showed that gliomas in affected male individuals exhibit significantly higher glutamine uptake. These sex differences were well modeled in murine transformed astrocytes, in which male cells imported and metabolized more glutamine and were more sensitive to glutaminase 1 (GLS1) inhibition. The sensitivity to GLS1 inhibition in males was driven by their dependence on glutamine-derived glutamate for α-ketoglutarate synthesis and tricarboxylic acid (TCA) cycle replenishment. Females were resistant to GLS1 inhibition through greater pyruvate carboxylase (PC)-mediated TCA cycle replenishment, and knockdown of PC sensitized females to GLS1 inhibition. CONCLUSION: Our results show that clinically important sex differences exist in targetable elements of metabolism. Recognition of sex-biased metabolism may improve treatments through further laboratory and clinical research. FUNDING: This work was supported by NIH grants, Joshua\u27s Great Things, the Siteman Investment Program, and the Barnard Research Fund

Identifying metabolites by integrating metabolome databases with mass spectrometry cheminformatics.

Novel metabolites distinct from canonical pathways can be identified through the integration of three cheminformatics tools: BinVestigate, which queries the BinBase gas chromatography-mass spectrometry (GC-MS) metabolome database to match unknowns with biological metadata across over 110,000 samples; MS-DIAL 2.0, a software tool for chromatographic deconvolution of high-resolution GC-MS or liquid chromatography-mass spectrometry (LC-MS); and MS-FINDER 2.0, a structure-elucidation program that uses a combination of 14 metabolome databases in addition to an enzyme promiscuity library. We showcase our workflow by annotating N-methyl-uridine monophosphate (UMP), lysomonogalactosyl-monopalmitin, N-methylalanine, and two propofol derivatives

Keeping Data Science Broad: Negotiating the Digital and Data Divide Among Higher Education Institutions

The goal of the “Keeping Data Science Broad” series of webinars and workshops was to garner community input into pathways for keeping data science education broadly inclusive across sectors, institutions, and populations. Input was collected from data science programs across the nation, either traditional or alternative, and from a range of institution types including community colleges, minority-led and minority-serving institutions, liberal arts colleges, tribal colleges, universities, and industry partners. The series consisted of two webinars (August 2017 and September 2017) leading up to a workshop (November 2017) exploring the future of data science education and workforce at institutions of higher learning that are primarily teaching-focused. A third follow-up webinar was held after the workshop (January 2018) to report on outcomes and next steps. Program committee members were chosen to represent a broad spectrum of communities with a diversity of geography (West, Northeast, Midwest, and South), discipline (Computer Science, Math, Statistics, and Domains), as well as institution type (Historically Black Colleges and Universities (HBCU’s), Hispanic-Serving Institutions (HSI’s), other Minority-Serving Institutions (MSI\u27s), Community College\u27s (CC’s), 4-year colleges, Tribal Colleges, R1 Universities, Government and Industry Partners)

Keeping Data Science Broad: Negotiating the Digital and Data Divide Among Higher Education Institutions

The goal of the “Keeping Data Science Broad” series of webinars and workshops was to garner community input into pathways for keeping data science education broadly inclusive across sectors, institutions, and populations. Input was collected from data science programs across the nation, either traditional or alternative, and from a range of institution types including community colleges, minority-led and minority-serving institutions, liberal arts colleges, tribal colleges, universities, and industry partners. The series consisted of two webinars (August 2017 and September 2017) leading up to a workshop (November 2017) exploring the future of data science education and workforce at institutions of higher learning that are primarily teaching-focused. A third follow-up webinar was held after the workshop (January 2018) to report on outcomes and next steps. Program committee members were chosen to represent a broad spectrum of communities with a diversity of geography (West, Northeast, Midwest, and South), discipline (Computer Science, Math, Statistics, and Domains), as well as institution type (Historically Black Colleges and Universities (HBCU’s), Hispanic-Serving Institutions (HSI’s), other Minority-Serving Institutions (MSI\u27s), Community College\u27s (CC’s), 4-year colleges, Tribal Colleges, R1 Universities, Government and Industry Partners)

A multi-analysis approach for estimating regional health impacts from the 2017 Northern California wildfires

Smoke impacts from large wildfires are mounting, and the projection is for more such events in the future as the one experienced October 2017 in Northern California, and subsequently in 2018 and 2020. Further, the evidence is growing about the health impacts from these events which are also difficult to simulate. Therefore, we simulated air quality conditions using a suite of remotely-sensed data, surface observational data, chemical transport modeling with WRF-CMAQ, one data fusion, and three machine learning methods to arrive at datasets useful to air quality and health impact analyses. To demonstrate these analyses, we estimated the health impacts from smoke impacts during wildfires in October 8–20, 2017, in Northern California, when over 7 million people were exposed to Unhealthy to Very Unhealthy air quality conditions. We investigated using the 5-min available GOES-16 fire detection data to simulate timing of fire activity to allocate emissions hourly for the WRF-CMAQ system. Interestingly, this approach did not necessarily improve overall results, however it was key to simulating the initial 12-hr explosive fire activity and smoke impacts. To improve these results, we applied one data fusion and three machine learning algorithms. We also had a unique opportunity to evaluate results with temporary monitors deployed specifically for wildfires, and performance was markedly different. For example, at the permanent monitoring locations, the WRF-CMAQ simulations had a Pearson correlation of 0.65, and the data fusion approach improved this (Pearson correlation = 0.95), while at the temporary monitor locations across all cases, the best Pearson correlation was 0.5. Overall, WRF-CMAQ simulations were biased high and the geostatistical methods were biased low. Finally, we applied the optimized PM2.5 exposure estimate in an exposure-response function. Estimated mortality attributable to PM2.5 exposure during the smoke episode was 83 (95% CI: 0, 196) with 47% attributable to wildland fire smoke. Implications: Large wildfires in the United States and in particular California are becoming increasingly common. Associated with these large wildfires are air quality and health impact to millions of people from the smoke. We simulated air quality conditions using a suite of remotely-sensed data, surface observational data, chemical transport modeling, one data fusion, and three machine learning methods to arrive at datasets useful to air quality and health impact analyses from the October 2017 Northern California wildfires. Temporary monitors deployed for the wildfires provided an important model evaluation dataset. Total estimated regional mortality attributable to PM2.5 exposure during the smoke episode was 83 (95% confidence interval: 0, 196) with 47% of these deaths attributable to the wildland fire smoke. This illustrates the profound effect that even a 12-day exposure to wildland fire smoke can have on human health