An Antithrombin-Heparin Complex Increases the Anticoagulant Activity of Fibrin Clots

Clotting blood contains fibrin-bound thrombin, which is a major source of procoagulant activity leading to clot extension and further activation of coagulation. When bound to fibrin, thrombin is protected from inhibition by antithrombin (AT) + heparin but is neutralized when AT and heparin are covalently linked (ATH). Here, we report the surprising observation that, rather than yielding an inert complex, thrombin-ATH formation converts clots into anticoagulant surfaces that effectively catalyze inhibition of thrombin in the surrounding environment

Multiplex ligation-dependent probe amplification (MLPA) analysis is an effective tool for the detection of novel intragenic PLA2G6 mutations: Implications for molecular diagnosis

Phospholipase associated neurodegeneration (PLAN) comprises a heterogeneous group of autosomal recessive neurological disorders caused by mutations in the PLA2G6 gene. Direct gene sequencing detects 85% mutations in infantile neuroaxonal dystrophy. We report the novel use of multiplex ligation-dependent probe amplification (MLPA) analysis to detect novel PLA2G6 duplications and deletions. The identification of such copy number variants (CNVs) expands the PLAN mutation spectrum and may account for up to 12.5% of PLA2G6 mutations. MLPA should thus be employed to detect CNVs of PLA2G6 in patients who show clinical features of PLAN but in whom both disease-causing mutations cannot be identified on routine sequencin

NASA's High-Resolution GEOS Forecasting and Reanalysis Products: Support for TOLNet

Stratospheric intrusions (SIs) the introduction of ozone-rich stratospheric air into the troposphere have been the interest of decades of research for their link with surface ozone air quality exceedances, especially at the high elevations in the western USA in springtime; however, the impact of SIs in the remaining seasons and over the rest of the USA is less clear. We can expect MERRA-2 to realistically represent both atmospheric dynamics and composition. The operational GEOS weather forecasting system, GEOS-FP, has a similar ozone observing system to MERRA-2, while NASA's new global high-resolution air quality forecast system, GEOS-CF, combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 12), simulating a wide range of additional air pollutants and tracers which strengthens this detailed analysis of the intrusions and the sources for the high ozone concentrations. Using a multitude of observational datasets, including lidar, air craft, ozonesondes and air quality monitoring surface sites, in combination with the GEOS forecast and reanalysis products, we aim to provide the public with tools which are available in near-real time to enhance their capability to identify the impact of stratospheric air on surface ozone concentrations separate from anthropogenic sources. In particular, improved understanding of the connections between large-scale climate variability and local-scale dynamically-driven air quality events may support improved seasonal prediction of SI events

Pain and analgesic use associated with skeletal-related events in patients with advanced cancer and bone metastases

PURPOSE: Bone metastases secondary to solid tumors increase the risk of skeletal-related events (SREs), including the occurrence of pathological fracture (PF), radiation to bone (RB), surgery to bone (SB), and spinal cord compression (SCC). The aim of this study was to evaluate the impact of SREs on patients' pain, analgesic use, and pain interference with daily functioning. METHODS: Data were combined from patients with solid tumors and bone metastases who received denosumab or zoledronic acid across three identically designed phase 3 trials (N = 5543). Pain severity (worst pain) and pain interference were assessed using the Brief Pain Inventory at baseline and each monthly visit. Analgesic use was quantified using the Analgesic Quantification Algorithm. RESULTS: The proportion of patients with moderate/severe pain and strong opioid use generally increased in the 6 months preceding an SRE and remained elevated, while they remained relatively consistent over time in patients without an SRE. Regression analysis indicated that all SRE types were significantly associated with an increased risk of progression to moderate/severe pain and strong opioid use. PF, RB, and SCC were associated with significantly greater risk of pain interference overall. Results were similar for pain interference with emotional well-being. All SRE types were associated with significantly greater risk of pain interference with physical function. CONCLUSIONS: SREs are associated with increased pain and analgesic use in patients with bone metastases. Treatments that prevent SREs may decrease pain and the need for opioid analgesics and reduce the impact of pain on daily functioning

Pain and analgesic use associated with skeletal-related events in patients with advanced cancer and bone metastases

PURPOSE: Bone metastases secondary to solid tumors increase the risk of skeletal-related events (SREs), including the occurrence of pathological fracture (PF), radiation to bone (RB), surgery to bone (SB), and spinal cord compression (SCC). The aim of this study was to evaluate the impact of SREs on patients' pain, analgesic use, and pain interference with daily functioning. METHODS: Data were combined from patients with solid tumors and bone metastases who received denosumab or zoledronic acid across three identically designed phase 3 trials (N = 5543). Pain severity (worst pain) and pain interference were assessed using the Brief Pain Inventory at baseline and each monthly visit. Analgesic use was quantified using the Analgesic Quantification Algorithm. RESULTS: The proportion of patients with moderate/severe pain and strong opioid use generally increased in the 6 months preceding an SRE and remained elevated, while they remained relatively consistent over time in patients without an SRE. Regression analysis indicated that all SRE types were significantly associated with an increased risk of progression to moderate/severe pain and strong opioid use. PF, RB, and SCC were associated with significantly greater risk of pain interference overall. Results were similar for pain interference with emotional well-being. All SRE types were associated with significantly greater risk of pain interference with physical function. CONCLUSIONS: SREs are associated with increased pain and analgesic use in patients with bone metastases. Treatments that prevent SREs may decrease pain and the need for opioid analgesics and reduce the impact of pain on daily functioning

Integrative analyses identify modulators of response to neoadjuvant aromatase inhibitors in patients with early breast cancer

Introduction Aromatase inhibitors (AIs) are a vital component of estrogen receptor positive (ER+) breast cancer treatment. De novo and acquired resistance, however, is common. The aims of this study were to relate patterns of copy number aberrations to molecular and proliferative response to AIs, to study differences in the patterns of copy number aberrations between breast cancer samples pre- and post-AI neoadjuvant therapy, and to identify putative biomarkers for resistance to neoadjuvant AI therapy using an integrative analysis approach. Methods Samples from 84 patients derived from two neoadjuvant AI therapy trials were subjected to copy number profiling by microarray-based comparative genomic hybridisation (aCGH, n = 84), gene expression profiling (n = 47), matched pre- and post-AI aCGH (n = 19 pairs) and Ki67-based AI-response analysis (n = 39). Results Integrative analysis of these datasets identified a set of nine genes that, when amplified, were associated with a poor response to AIs, and were significantly overexpressed when amplified, including CHKA, LRP5 and SAPS3. Functional validation in vitro, using cell lines with and without amplification of these genes (SUM44, MDA-MB134-VI, T47D and MCF7) and a model of acquired AI-resistance (MCF7-LTED) identified CHKA as a gene that when amplified modulates estrogen receptor (ER)-driven proliferation, ER/estrogen response element (ERE) transactivation, expression of ER-regulated genes and phosphorylation of V-AKT murine thymoma viral oncogene homolog 1 (AKT1). Conclusions These data provide a rationale for investigation of the role of CHKA in further models of de novo and acquired resistance to AIs, and provide proof of concept that integrative genomic analyses can identify biologically relevant modulators of AI response

Targeting tumour re-wiring by triple blockade of mTORC1, epidermal growth factor, and oestrogen receptor signalling pathways in endocrine-resistant breast cancer

Background Endocrine therapies are the mainstay of treatment for oestrogen receptor (ER)-positive (ER+) breast cancer (BC). However, resistance remains problematic largely due to enhanced cross-talk between ER and growth factor pathways, circumventing the need for steroid hormones. Previously, we reported the anti-proliferative effect of everolimus (RAD001-mTORC1 inhibitor) with endocrine therapy in resistance models; however, potential routes of escape from treatment via ERBB2/3 signalling were observed. We hypothesised that combined targeting of three cellular nodes (ER, ERBB, and mTORC1) may provide enhanced long-term clinical utility. Methods A panel of ER+ BC cell lines adapted to long-term oestrogen deprivation (LTED) and expressing ESR1wt or ESR1Y537S, modelling acquired resistance to an aromatase-inhibitor (AI), were treated in vitro with a combination of RAD001 and neratinib (pan-ERBB inhibitor) in the presence or absence of oestradiol (E2), tamoxifen (4-OHT), or fulvestrant (ICI182780). End points included proliferation, cell signalling, cell cycle, and effect on ER-mediated transactivation. An in-vivo model of AI resistance was treated with monotherapies and combinations to assess the efficacy in delaying tumour progression. RNA-seq analysis was performed to identify changes in global gene expression as a result of the indicated therapies. Results Here, we show RAD001 and neratinib (pan-ERBB inhibitor) caused a concentration-dependent decrease in proliferation, irrespective of the ESR1 mutation status. The combination of either agent with endocrine therapy further reduced proliferation but the maximum effect was observed with a triple combination of RAD001, neratinib, and endocrine therapy. In the absence of oestrogen, RAD001 caused a reduction in ER-mediated transcription in the majority of the cell lines, which associated with a decrease in recruitment of ER to an oestrogen-response element on the TFF1 promoter. Contrastingly, neratinib increased both ER-mediated transactivation and ER recruitment, an effect reduced by the addition of RAD001. In-vivo analysis of an LTED model showed the triple combination of RAD001, neratinib, and fulvestrant was most effective at reducing tumour volume. Gene set enrichment analysis revealed that the addition of neratinib negated the epidermal growth factor (EGF)/EGF receptor feedback loops associated with RAD001. Conclusions Our data support the combination of therapies targeting ERBB2/3 and mTORC1 signalling, together with fulvestrant, in patients who relapse on endocrine therapy and retain a functional ER

Quantifying diet-induced metabolic changes of the human gut microbiome

The human gut microbiome is known to be associated with various human disorders, but a major challenge is to go beyond association studies and elucidate causalities. Mathematical modeling of the human gut microbiome at a genome-scale is a useful tool to decipher microbe-microbe, diet-microbe and microbe-host interactions. Here, we describe the CASINO (Community and Systems-level Interactive Optimization) toolbox, a comprehensive computational platform for analysis of microbial communities through metabolic modeling. We first validated the toolbox by simulating and testing the performance of single bacteria and whole communities in in vitro. Focusing on metabolic interactions between the diet, gut microbiota and host metabolism, we demonstrated the predictive power of the toolbox in a diet-intervention study of 45 obese and overweight individuals, and validated our predictions by fecal and blood metabolomics data. Thus, modeling could quantitatively describe altered fecal and serum amino acid levels in response to diet intervention