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Background Past research in population health trends has shown that injuries form a substantial burden of population health loss. Regular updates to injury burden assessments are critical. We report Global Burden of Disease (GBD) 2017 Study estimates on morbidity and mortality for all injuries. Methods We reviewed results for injuries from the GBD 2017 study. GBD 2017 measured injury-specific mortality and years of life lost (YLLs) using the Cause of Death Ensemble model. To measure non-fatal injuries, GBD 2017 modelled injury-specific incidence and converted this to prevalence and years lived with disability (YLDs). YLLs and YLDs were summed to calculate disability-adjusted life years (DALYs). Findings In 1990, there were 4 260 493 (4 085 700 to 4 396 138) injury deaths, which increased to 4 484 722 (4 332 010 to 4 585 554) deaths in 2017, while age-standardised mortality decreased from 1079 (1073 to 1086) to 738 (730 to 745) per 100 000. In 1990, there were 354 064 302 (95% uncertainty interval: 338 174 876 to 371 610 802) new cases of injury globally, which increased to 520 710 288 (493 430 247 to 547 988 635) new cases in 2017. During this time, age-standardised incidence decreased non-significantly from 6824 (6534 to 7147) to 6763 (6412 to 7118) per 100 000. Between 1990 and 2017, age-standardised DALYs decreased from 4947 (4655 to 5233) per 100 000 to 3267 (3058 to 3505). Interpretation Injuries are an important cause of health loss globally, though mortality has declined between 1990 and 2017. Future research in injury burden should focus on prevention in high-burden populations, improving data collection and ensuring access to medical care.

3564 Background: Lethal-7 (let-7) microRNA has been shown to inhibit colon cancer cell proliferation by inducing KRAS downregulation after binding to specific sites in the 3’- UTR. Recent studies identified a KRAS 3’-UTR polymorphism in the let-7 complimentary site (LCS6) that has been shown to weaken let-7 binding and alter KRAS expression. Carriers of the LCS6 G-allele showed worse survival in metastatic colorectal cancer from prior studies of limited sample size. In the current study, we evaluated the LCS6 variant in 2,834 Stage III colon cancer patients and its association with disease-free survival (DFS), KRAS mutation status, and other clinicopathological features. Methods: In the NCCTG phase III trial (N0147), the LCS6 variant was assayed in germline DNA extracted from whole blood using RT-PCR. Extracted tumor DNA was analyzed for KRAS exon 2 mutations. Chi-squared and two-sample t test were used to compare baseline factors and KRAS mutation status between patients defined by LCS6 variant status. Log-rank tests and multivariate Cox models assessed the unadjusted and adjusted associations between LCS6 status and DFS, respectively. Results: We identified 432 (15.2%) patients heterozygous or homozygous for the LCS6 G-allele and 2402 (84.8%) patients homozygous for the LCS6 T-allele. G-allele carriers were significantly more frequent in Caucasians than other races (Chi-Squared Test, p<0.0001). No associations were found between the LCS6 genotype and T stage, positive lymph node number, tumor differentiation, or primary tumor location (all p>0.2). Moreover, the LCS6 genotype was not associated with DFS (hazard ratio = 0.93, p=0.49) even after combining LCS6 genotype with KRAS mutation status. Conclusions: We report the largest association study investigating the LCS6 polymorphism and colon cancer outcome. There is no significant evidence that the germline LCS6 genotype was associated with DFS in stage III colon cancer patients. Additional studies are needed to determine if LCS6 genotype differs between tumor and germline DNA which may further clarify its prognostic value.

Background: Although diffuse large B cell lymphoma (DLBCL) can be cured using immuno-chemotherapy, 40% of patients experience relapse or refractory disease. Large-scale profiling studies have mainly focused on DLBCL at diagnosis, resolving different outcome groups based on gene expression (e.g. cell-of-origin (COO) or molecular high grade), MYC/BCL2 translocations (double-hit lymphoma) or gene mutations and copy number aberrations (Schmitz et al, NEJM 2018; Chapuy et al, NatureMedicine 2018). In comparison, longitudinal studies have been hindered by the limited availability of sequential biopsy samples. To date, the relapse-specific gene mutations identified are limited and inconsistent across studies. In our study, we have focussed attention on the changes in gene expression profile (GEP) accompanying DLBCL relapse. Methods: We retrospectively collected archival paired diagnostic/relapse formalin fixed paraffin embedded tumor biopsies from 38 de novo DLBCL patients collected from multiple UK sites treated with rituximab-based immuno-chemotherapy, where partial or complete remission was reported following treatment. COO classification was performed by the Lymph2Cx assay on NanoString to distinguish activated B-cell-like (ABC) and germinal center B-cell-like (GCB) subtypes. The Ion AmpliSeq™ Transcriptome Human Gene Expression Kit was used to measure the expression levels of > 20,000 genes on the paired samples. Results: COO remained stable from diagnosis to relapse in 17 ABC-ABC pairs, 11 GCB-GCB pairs and 4 unclassified (UNC)-UNC pairs. Frank COO switching was observed in 6 cases (1 ABC-GCB, 2 ABC-UNC, 2 GCB-UNC, 1 UNC-ABC). Pairs with stable COO were taken forward for further analysis. Gene expression analysis using the limma R package identified 163 and 136 genes as differentially expressed (DE) (p <= 0.01 and absolute log2FC > 1) between the diagnostic and relapse biopsies in ABC and GCB tumors respectively, with only a one gene overlap. Gene Set Enrichment Analysis further suggested that ABC and GCB relapses are mediated via different mechanisms, with tumor growth and proliferation signatures enriched in ABC relapses, whilst adaptive immunity-related signatures accompanied GCB relapses. Next, we aimed to utilise our relapse-specific genes to identify outcome predictors at diagnosis using publicly available GEP datasets. In order to increase our discovery power and accuracy, a larger set of DE genes from the paired differential analysis (796 genes in ABC pairs and 387 from GCB pairs) were selected (p <= 0.05) and subsequently used in a training cohort (GEP from Reddy et al, Cell 2017). The Prediction Analysis for Microarrays R (PAMR) algorithm identified a 30-gene signature within DE genes from ABC pairs (Fig1.A), capable of separating the 249 ABC cases into 136 low and 113 high-risk cases with significantly inferior overall survival (Hazard Ratio (HR)=1.89, log-rank p=0.0017, measure of goodness-of-fit C-index=0.71; Fig1.B). No equivalent signature was found in the GCB cases using this approach. The prognostic significance of this 30-gene discriminator was successfully validated using a linear predictor in two independent GEP datasets: 1) a population-based cohort (Lenz et al, NEJM 2008) with 93 R-CHOP-treated ABC cases identifying 47 low and 46 high-risk cases (HR=1.92, p=0.046, C-index=0.77; Fig1.C) and 2) a clinical trial dataset (REMoDL-B, Davies et al, Lancet Oncol 2019) with 255 ABC cases identifying 110 low and 145 high-risk ABC cases (HR=1.95, p=0.0051, C-index=0.70; Fig1.D). Conclusions: Here we describe a 30-gene discriminator in ABC-DLBCL, derived from genes differentially expressed between diagnosis and relapse, that allowed the definition of clinically distinct high and low risk subgroups in ABC-DLBCLs at diagnosis. The clinical translation of such a tool may be useful to guide therapy for this unfavourable subgroup of ABC-DLBCLs. Validation of this signature is currently underway in additional datasets and further study is required to understand the contribution of these genes in DLBCL pathology. Disclosures Korfi: Roche: Consultancy. Burton:Celgene: Membership on an entity's Board of Directors or advisory committees; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees. Rule:TG Therapeutics: Consultancy, Honoraria; Napp: Consultancy; Kite: Consultancy; Pharmacyclics: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; Sunesis: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Roche: Consultancy, Honoraria, Research Funding; Astra-Zeneca: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. Crosbie:Janssen: Honoraria. Scott:Celgene: Consultancy; Janssen: Consultancy, Research Funding; NanoString: Patents & Royalties: Named inventor on a patent licensed to NanoSting [Institution], Research Funding; Roche/Genentech: Research Funding. Rimsza:NanoSting: Patents & Royalties: Named inventor on a patent licensed to NanoSting [Institution]. Davies:Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Honoraria, Research Funding; Bayer: Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Honoraria, Research Funding; Karyopharma: Membership on an entity's Board of Directors or advisory committees, Research Funding; GSK: Research Funding; Acerta Pharma: Honoraria, Research Funding; ADCT Therapeutics: Honoraria, Research Funding; BioInvent: Research Funding; Kite Pharma: Membership on an entity's Board of Directors or advisory committees; MorphoSys AG: Honoraria, Membership on an entity's Board of Directors or advisory committees. Gribben:Abbvie: Consultancy, Honoraria, Research Funding; Acerta/Astra Zeneca: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding. Okosun:Gilead Sciences: Honoraria, Research Funding. Johnson:Epizyme: Honoraria, Research Funding; Novartis: Honoraria; Kite: Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria; Boehringer Ingelheim: Honoraria; Takeda: Honoraria; Genmab: Honoraria; Celgene: Honoraria; Incyte: Honoraria. Fitzgibbon:Epizyme: Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Speakers Bureau.

Data on disease burden are often used for assessing population health, evaluating the effectiveness of interventions, formulating health policies, and planning future resource allocation. We investigated whether Internet usage and social media data, specifically the search volume on Google, page view count on Wikipedia, and disease mentioning frequency on Twitter, correlated with the disease burden, measured by prevalence and treatment cost, for 1633 diseases over an 11-year period. We also applied least absolute shrinkage and selection operator to predict the burden of diseases. We found that Google search volume is relatively strongly correlated with the burdens for 39 of 1633 diseases, including viral hepatitis, diabetes mellitus, multiple sclerosis, and hemorrhoids. Wikipedia and Twitter data strongly correlated with the burdens of 15 and 7 diseases, respectively. However, an accurate analysis must consider each condition’s characteristics, including acute/chronic nature, severity, familiarity to the public, and the presence of stigma.

In mammalian peripheral sympathetic ganglia GABA acts presynaptically to facilitate cholinergic transmission and postsynaptically to depolarize membrane potential. The GABA effect on parasympathetic pancreatic ganglia is unknown. We aimed to determine the effect of locally applied GABA on cat pancreatic ganglion neurons. Ganglia with attached nerve trunks were isolated from cat pancreata. Conventional intracellular recording techniques were used to record electrical responses from ganglion neurons. GABA pressure microejection depolarized membrane potential with an amplitude of 17.4 ± 0.7 mV. Electrically evoked fast excitatory postsynaptic potentials were significantly inhibited (5.4 ± 0.3 to 2.9 ± 0.2 mV) after GABA application. GABA-evoked depolarizations were mimicked by the GABAAreceptor agonist muscimol and abolished by the GABAAreceptor antagonist bicuculline and the Cl−channel blocker picrotoxin. GABA was taken up and stored in ganglia during preincubation with 1 mM GABA; β-aminobutyric acid application after GABA loading significantly ( P < 0.05) increased depolarizing response to GABA (15.6 ± 1.0 vs. 7.8 ± 0.8 mV without GABA preincubation). Immunolabeling with antibodies to GABA, glial cell fibrillary acidic protein, protein gene product 9.5, and glutamic acid decarboxylase (GAD) immunoreactivity showed that GABA was present in glial cells, but not in neurons, and that glial cells did not contain GAD, whereas islet cells did. The data suggest that endogenous GABA released from ganglionic glial cells acts on pancreatic ganglion neurons through GABAAreceptors.

New Findings What is the central question of this study? The aim was to investigate the roles of extracellular chloride in electrical slow waves and resting membrane potential of mouse jejunal smooth muscle by replacing chloride with the impermeant anions gluconate and isethionate. What is the main finding and its importance? The main finding was that in smooth muscle cells, the resting Cl− conductance is low, whereas transmembrane Cl− movement in interstitial cells of Cajal (ICCs) is a major contributor to the shape of electrical slow waves. Furthermore, the data confirm that ICCs set the smooth muscle membrane potential and that altering Cl− homeostasis in ICCs can alter the smooth muscle membrane potential. Intracellular Cl− homeostasis is regulated by anion‐permeable channels and transporters and contributes to excitability of many cell types, including smooth muscle and interstitial cells of Cajal (ICCs). Our aims were to investigate the effects on electrical activity in mouse jejunal muscle strips of replacing extracellular Cl− (Cl−o) with the impermeant anions gluconate and isethionate. On reducing Cl−o, effects were observed on electrical slow waves, with small effects on smooth muscle membrane voltage (Em). Restoration of Cl− hyperpolarized smooth muscle Em proportional to the change in Cl−o concentration. Replacement of 90% of Cl−o with gluconate reversibly abolished slow waves in five of nine preparations. Slow waves were maintained in isethionate. Gluconate and isethionate substitution had similar concentration‐dependent effects on peak amplitude, frequency, width at half peak amplitude, rise time and decay time of residual slow waves. Gluconate reduced free ionized Ca2+ in Krebs solutions to 0.13 mm. In Krebs solutions containing normal Cl− and 0.13 mm free Ca2+, slow wave frequency was lower, width at half peak amplitude was smaller, and decay time was faster. The transient hyperpolarization following restoration of Cl−o was not observed in W/Wv mice, which lack pacemaker ICCs in the small intestine. We conclude that in smooth muscle cells, the resting Cl− conductance is low, whereas transmembrane Cl− movement in ICCs plays a major role in generation or propagation of slow waves. Furthermore, these data support a role for ICCs in setting smooth muscle Em and that altering Cl− homeostasis in ICCs can alter smooth muscle Em.

Functional FOXA1 targeting is mostly unique to each of the four human cancer cell lines HepG2, LNCaP, MCF7, and T47D.

AbstractBackgroundThe SCN5A‐encoded voltage‐gated sodium channel NaV1.5 is expressed in human jejunum and colon. Mutations in NaV1.5 are associated with gastrointestinal motility disorders. The rat gastrointestinal tract expresses voltage‐gated sodium channels, but their molecular identity and role in rat gastrointestinal electrophysiology are unknown.MethodsThe presence and distribution of Scn5a‐encoded NaV1.5 was examined by PCR, Western blotting and immunohistochemistry in rat jejunum. Freshly dissociated smooth muscle cells were examined by whole cell electrophysiology. Zinc finger nuclease was used to target Scn5a in rats. Lentiviral‐mediated transduction with shRNA was used to target Scn5a in rat jejunum smooth muscle organotypic cultures. Organotypic cultures were examined by sharp electrode electrophysiology and RT‐PCR.Key ResultsWe found NaV1.5 in rat jejunum and colon smooth muscle by Western blot. Immunohistochemistry using two other antibodies of different portions of NaV1.5 revealed the presence of the ion channel in rat jejunum. Whole cell voltage‐clamp in dissociated smooth muscle cells from rat jejunum showed fast activating and inactivating voltage‐dependent inward current that was eliminated by Na+ replacement by NMDG+. Constitutive rat Scn5a knockout resulted in death in utero. NaV1.5 shRNA delivered by lentivirus into rat jejunum smooth muscle organotypic culture resulted in 57% loss of Scn5a mRNA and several significant changes in slow waves, namely 40% decrease in peak amplitude, 30% decrease in half‐width, and 7 mV hyperpolarization of the membrane potential at peak amplitude.Conclusions & InferencesScn5a‐encoded NaV1.5 is expressed in rat gastrointestinal smooth muscle and it contributes to smooth muscle electrophysiology.