Pistol Packin\u27 Mama

Photograph of Al Dexter holding a guitarhttps://scholarsjunction.msstate.edu/cht-sheet-music/13823/thumbnail.jp

Interim outcomes of mechanical thrombectomy for deep vein thrombosis from the all-comer CLOUT registry

OBJECTIVES: The multicenter, prospective, single arm CLOUT registry assesses the safety and effectiveness of the ClotTriever System (Inari Medical, Irvine, CA) for the treatment of acute and nonacute lower extremity deep vein thrombosis (DVT) in all-comer patients. Reported here are the outcomes of the first 250 patients. METHODS: All-comer patients with lower extremity DVT were enrolled, including those with bilateral DVT, those with previously failed DVT treatment, and regardless of symptom duration. The primary effectiveness end point is complete or near-complete (≥75%) thrombus removal determined by independent core laboratory-adjudicated Marder scores. Safety outcomes include serious adverse events through 30 days and clinical outcomes include post-thrombotic syndrome severity, symptoms, pain, and quality of life through 6 months. RESULTS: The median age was 62 years and 40% of patients had contraindications to thrombolytics. A range of thrombus chronicity (33% acute, 35% subacute, 32% chronic) was observed. No patients received thrombolytics and 99.6% were treated in a single session. The median thrombectomy time was 28 minutes. The primary effectiveness end point was achieved in 86% of limbs. Through 30 days, one device-related serious adverse event occurred. At 6 months, 24% of patients had post-thrombotic syndrome. Significant and sustained improvements were observed in all clinical outcomes, including the Revised Venous Clinical Severity Score, the numeric pain rating scale, and the EuroQol Group 5-Dimension Self-Report Questionnaire. CONCLUSIONS: The 6-month outcomes from the all-comer CLOUT registry with a range of thrombus chronicities demonstrate favorable effectiveness, safety, and sustained clinical improvements

Drill control studies with formulations of Polystream and Sevin for 1963

During 1963 , the Virginia Institute of Marine Science conducted a series of tests on oyster drill control with formulations of Polystream , a chlorinated hydrocarbon and Sevin , an insecticide . The utility of these two compounds had previously been investigated by the U. S. Fish and Wildlife Service in Long Is land Sound, in the laboratory and in field trials on commercial beds. Several of these earlier fie ld studies indicated that the treatment prescribed was effective in drill control. Consequently, application was made to the U. S. Department of Agriculture for an experimental permit. The permit was granted , laying the groundwork for further experimental field trials supervised by state or federal agencies

A State-of-the-Art Vegetation Map for Jordan: A New Tool for Conservation in a Biodiverse Country

In many countries, including Jordan, the updating of vegetation maps is required to aid in formulating development and management plans for agriculture, forest, and rangeland sectors. Remote sensing data contributes widely to vegetation mapping at different scales by providing multispectral information that can separate and identify different vegetation groups at reasonable accuracy and low cost. Here, we implemented state-of-the-art approaches to develop a vegetation map for Jordan, as an example of how such maps can be produced in regions of high vegetation complexity. Specifically, we used a reciprocal illumination technique that combines extensive ground data (640 vegetation inventory plots) and Sentinel-2 satellite images to produce a categorical vegetation map (scale 1:50,000). Supervised classification was used to translate the spectral characteristics into vegetation types, which were first delimited by the clustering analyses of species composition data from the plots. From the satellite image interpretation, two maps were created: an unsupervised land cover/land use map and a supervised map of present-day vegetation types, both consisting of 18 categories. These new maps should inform ecosystem management and conservation planning decisions in Jordan over the coming years

Neuroprotective role for RORA in Parkinson’s disease revealed by analysis of post-mortem brain and a dopaminergic cell line

Parkinson's disease (PD) is almost twice as prevalent in men, which has largely been attributed to neuroprotective effect of oestradiol in women. RORA (retinoic acid receptor-related orphan receptor alpha) regulates the transcription of central aromatase, the enzyme responsible for local oestradiol synthesis, simultaneously, RORA expression is regulated by sex hormones. Moreover, RORA protects neurones against oxidative stress, a key mechanism contributing to the loss of dopaminergic neurones in PD. Therefore, we hypothesized that there would be sex differences in RORA expression in the substantia nigra pars compacta (SNpc), which could contribute to sex differences observed in PD prevalence and pathogenesis. In a case control study, qPCR and western blot analyses were used to quantify gene and protein expression in the SNpc of post-mortem brains (n = 14 late-stage PD and 11 age and sex matched controls). The neuroprotective properties of a RORA agonist were then investigated directly using a cell culture toxin-based model of PD coupled with measures of viability, mitochondrial function and apoptosis. RORA was expressed at significantly higher levels in the SNpc from control females' brains compared to males. In PD, we found a significant increase in SNpc RORA expression in male PD compared to female PD. Treatment with a RORA agonist showed a significant neuroprotection in our cell culture model of PD and revealed significant effects on intracellular factors involved in neuronal survival and demise. This study is the first to demonstrate a sex specific pattern of RORA protein and gene expression in the SNpc of controls post-mortem human brains, and to show that this is differentially altered in male and female PD subjects, thus supporting a role for RORA in sex-specific aspects of PD. Furthermore, our in vitro PD model indicates mechanisms whereby a RORA agonist exerts its neuroprotective effect, thereby highlighting the translational potential for RORA ligands in PD

Pancreatic Cancer Risk Stratification based on Patient Family History

poster abstractBackground: Pancreatic cancer is the fourth leading cause of cancer-related deaths in the US with an annual death rate approximating the incidence (38,460 and 45,220 respectively according to 2013 American Cancer Society). Due to delayed diagnosis, only 8% of patients are amenable to surgical resection, resulting in a 5-year survival rate of less than 6%. Screening the general population for pancreatic cancer is not feasible because of its low incidence (12.1 per 100,000 per year) and the lack of accurate screening tools. However, patients with an inherited predisposition to pancreatic cancer would benefit from selective screening. Methods: Clinical notes of patients from Indiana University (IU) Hospitals were used in this study. A Natural Language Processing (NLP) system based on the Unstructured Information Management Architecture framework was developed to process the family history data and extract pancreatic cancer information. This was performed through a series of NLP processes including report separation, section separation, sentence detection and keyword extraction. The family members and their corresponding diseases were extracted using regular expressions. The Stanford dependency parser was used to accurately link the family member and their diseases. Negation analysis was done using the NegEx algorithm. PancPro risk-prediction software was used to assess the lifetime risk scores of pancreatic cancer for each patient according to his/her family history. A decision tree was constructed based on these scores. Results: A corpus of 2000 reports of patients at IU Hospitals from 1990 to 2012 was collected. The family history section was present in 249 of these reports containing 463 sentences. The system was able to identify 222 reports (accuracy 87.5%) and 458 sentences (accuracy 91.36%). Conclusion: The family history risk score will be used for patients’ pancreatic cancer risk stratification, thus contributing to selective screening

Pancreatic Cysts Identification Using Unstructured Information Management Architecture

poster abstractPancreatic cancer is one of the deadliest cancers, mostly diagnosed at late stages. Patients with pancreatic cysts are at higher risk of developing cancer and surveillance of these patients can help with early diagnosis. Much information about pancreatic cysts can be found in free text format in various medical narratives. In this retrospective study, a corpus of 1064 records from 44 patients at Indiana University Hospital from 1990 to 2012 was collected. A natural language processing system was developed and used to identify patients with pancreatic cysts. The input goes through series of tasks within the Unstructured Information Management Architecture (UIMA) framework consisting of report separation, metadata detection, sentence detection, concept annotation and writing into the database. Metadata such as medical record number (MRN), report id, report name, report date, report body were extracted from each report. Sentences were detected and concepts within each sentence were extracted using regular expression. Regular expression is a pattern of characters matching specific string of text. Our medical team assembled concepts that are used to identify pancreatic cysts in medical reports and additional keywords were added by searching through literature and Unified Medical Language System (UMLS) knowledge base. The Negex Algorithm was used to find out negation status of concepts. The 1064 reports were divided into sets of train and test sets. Two pancreatic-cyst surgeons created the gold standard data (Inter annotator agreement K=88%). The training set was analyzed to modify the regular expression. The concept identification using the NegEx algorithm resulted in precision and recall of 98.9% and 89% respectively. In order to improve the performance of negation detection, Stanford Dependency parser (SDP) was used. SDP finds out how words are related to each other in a sentence. SDP based negation algorithm improved the recall to 95.7%

Compositional response of Amazon forests to climate change

Most of the planet\u27s diversity is concentrated in the tropics, which includes many regions undergoing rapid climate change. Yet, while climate-induced biodiversity changes are widely documented elsewhere, few studies have addressed this issue for lowland tropical ecosystems. Here we investigate whether the floristic and functional composition of intact lowland Amazonian forests have been changing by evaluating records from 106 long-term inventory plots spanning 30 years. We analyse three traits that have been hypothesized to respond to different environmental drivers (increase in moisture stress and atmospheric CO 2 concentrations): maximum tree size, biogeographic water-deficit affiliation and wood density. Tree communities have become increasingly dominated by large-statured taxa, but to date there has been no detectable change in mean wood density or water deficit affiliation at the community level, despite most forest plots having experienced an intensification of the dry season. However, among newly recruited trees, dry-affiliated genera have become more abundant, while the mortality of wet-affiliated genera has increased in those plots where the dry season has intensified most. Thus, a slow shift to a more dry-affiliated Amazonia is underway, with changes in compositional dynamics (recruits and mortality) consistent with climate-change drivers, but yet to significantly impact whole-community composition. The Amazon observational record suggests that the increase in atmospheric CO 2 is driving a shift within tree communities to large-statured species and that climate changes to date will impact forest composition, but long generation times of tropical trees mean that biodiversity change is lagging behind climate change

Ocean temperature controls kelp decomposition and carbon sink potential

Compelling new evidence shows that kelp production contributes an important and underappreciated flux of carbon in the ocean. Major questions remain, however, about the controls on the cycling of this organic carbon in the coastal zone, and their implications for future carbon sequestration. Here we used field experiments distributed across 28° latitude, and the entire range of two dominant kelps in the northern hemisphere, to measure decomposition rates of kelp detritus on the seafloor in relation to environmental factors. Ocean temperature was the strongest control on detritus decomposition in both species, and it was positively related to decomposition. This suggests that decomposition could accelerate with ocean warming under climate change, increasing remineralization and reducing overall kelp carbon sequestration. However, we also demonstrate the potential for high kelp-carbon storage in cooler (northern) regions, which could be targeted by climate mitigation strategies to expand blue carbon sinks