100 research outputs found

    Yield of clinical and radiographic surveillance in patients with resected pancreatic adenocarcinoma following multimodal therapy

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    AbstractBackgroundFollowing potentially curative resection at this centre, patients with pancreatic adenocarcinoma (PAC) are routinely enrolled in a programme of clinical and radiographic surveillance. This study sought to evaluate its diagnostic yield.MethodsAll patients who underwent pancreaticoduodenectomy for PAC at this institution during 1998–2008 were identified. Patients with asymptomatic recurrence were compared with those with symptomatic recurrence. Factors associated with survival following the detection of recurrence were compared.ResultsA total of 216 of 327 (66.1%) resected patients developed recurrence. Asymptomatic recurrence was detected in 118 (54.6%) patients. Symptomatic recurrence was associated with multifocal disease or carcinomatosis, poor performance status and less frequent subsequent therapy. Median time to recurrence did not differ between groups, but survival after detection was shorter in symptomatic patients (5.1months vs. 13.0months; P < 0.001). Treatment was administered more frequently to asymptomatic patients (91.2% vs. 61.4%; P < 0.001). At recurrence, a preserved performance status score of ≤1, further therapy, low CA 19-9, and an isolated site of recurrence were independently associated with longer post-recurrence survival (P < 0.001).ConclusionsOverall, 54.6% of cases of recurrent PAC were detected prior to the onset of symptoms using a standardized clinical and radiographic surveillance strategy. Although this retrospective analysis limits definitive conclusions associating this strategy with survival, these results suggest the need for further studies of postoperative surveillance

    Chronic neuropsychiatric sequelae of SARS‐CoV‐2: Protocol and methods from the Alzheimer's Association Global Consortium

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    Introduction Coronavirus disease 2019 (COVID-19) has caused >3.5 million deaths worldwide and affected >160 million people. At least twice as many have been infected but remained asymptomatic or minimally symptomatic. COVID-19 includes central nervous system manifestations mediated by inflammation and cerebrovascular, anoxic, and/or viral neurotoxicity mechanisms. More than one third of patients with COVID-19 develop neurologic problems during the acute phase of the illness, including loss of sense of smell or taste, seizures, and stroke. Damage or functional changes to the brain may result in chronic sequelae. The risk of incident cognitive and neuropsychiatric complications appears independent from the severity of the original pulmonary illness. It behooves the scientific and medical community to attempt to understand the molecular and/or systemic factors linking COVID-19 to neurologic illness, both short and long term. Methods This article describes what is known so far in terms of links among COVID-19, the brain, neurological symptoms, and Alzheimer's disease (AD) and related dementias. We focus on risk factors and possible molecular, inflammatory, and viral mechanisms underlying neurological injury. We also provide a comprehensive description of the Alzheimer's Association Consortium on Chronic Neuropsychiatric Sequelae of SARS-CoV-2 infection (CNS SC2) harmonized methodology to address these questions using a worldwide network of researchers and institutions. Results Successful harmonization of designs and methods was achieved through a consensus process initially fragmented by specific interest groups (epidemiology, clinical assessments, cognitive evaluation, biomarkers, and neuroimaging). Conclusions from subcommittees were presented to the whole group and discussed extensively. Presently data collection is ongoing at 19 sites in 12 countries representing Asia, Africa, the Americas, and Europe. Discussion The Alzheimer's Association Global Consortium harmonized methodology is proposed as a model to study long-term neurocognitive sequelae of SARS-CoV-2 infection

    A connectome and analysis of the adult Drosophila central brain

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    The neural circuits responsible for animal behavior remain largely unknown. We summarize new methods and present the circuitry of a large fraction of the brain of the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses in, and proofread such large data sets. We define cell types, refine computational compartments, and provide an exhaustive atlas of cell examples and types, many of them novel. We provide detailed circuits consisting of neurons and their chemical synapses for most of the central brain. We make the data public and simplify access, reducing the effort needed to answer circuit questions, and provide procedures linking the neurons defined by our analysis with genetic reagents. Biologically, we examine distributions of connection strengths, neural motifs on different scales, electrical consequences of compartmentalization, and evidence that maximizing packing density is an important criterion in the evolution of the fly’s brain

    Search for supersymmetry in events with photons and low missing transverse energy in pp collisions at √s=7 TeV

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    This is the pre-print version of the Article. The official published version can be accessed from the links below - Copyright @ 2013 Elsevier.Many models of new physics, including versions of supersymmetry (SUSY), predict production of events with low missing transverse energy, electroweak gauge bosons, and many energetic final-state particles. The stealth SUSY model yields this signature while conserving R-parity by means of a new hidden sector in which SUSY is approximately conserved. The results of a general search for new physics, with no requirement on missing transverse energy, in events with two photons and four or more hadronic jets are reported. The study is based on a sample of proton–proton collisions at √s=7 TeV corresponding to 4.96 fb−1 of integrated luminosity collected with the CMS detector in 2011. Based on good agreement between the data and the standard model expectation, the data are used to determine model-independent cross-section limits and a limit on the squark mass in the framework of stealth SUSY. With this first study of its kind, squark masses less than 1430 GeV are excluded at the 95% confidence level.This study is supported by the BMWF and FWF (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC (China); COLCIENCIAS (Colombia); MSES (Croatia); RPF (Cyprus); MEYS (Czech Republic); MoER, SF0690030s09 and ERDF (Estonia); Academy of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); OTKA and NKTH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); NRF and WCU (Korea); LAS (Lithuania); CINVESTAV, CONACYT, SEP, and UASLP-FAI (Mexico); MSI (New Zealand); PAEC (Pakistan); MSHE and NSC (Poland); FCT (Portugal); JINR (Armenia, Belarus, Georgia, Ukraine, Uzbekistan); MON, RosAtom, RAS and RFBR (Russia); MSTD (Serbia); SEIDI and CPAN (Spain); Swiss Funding Agencies (Switzerland); NSC (Taipei); ThEP, IPST and NECTEC (Thailand); TUBITAK and TAEK (Turkey); NASU (Ukraine); STFC (United Kingdom); DOE and NSF (USA)

    A connectome and analysis of the adult Drosophila central brain

    Get PDF
    The neural circuits responsible for animal behavior remain largely unknown. We summarize new methods and present the circuitry of a large fraction of the brain of the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses in, and proofread such large data sets. We define cell types, refine computational compartments, and provide an exhaustive atlas of cell examples and types, many of them novel. We provide detailed circuits consisting of neurons and their chemical synapses for most of the central brain. We make the data public and simplify access, reducing the effort needed to answer circuit questions, and provide procedures linking the neurons defined by our analysis with genetic reagents. Biologically, we examine distributions of connection strengths, neural motifs on different scales, electrical consequences of compartmentalization, and evidence that maximizing packing density is an important criterion in the evolution of the fly's brain
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