Dispersion of vapor from LNG spills: simulation in a meteorological wind tunnel

CER76-77RNM-JEC-DEN-MM57.Under contract to R & D Associates, Marina del Ray (C.A.).Includes bibliographical references (page 35).May 1977

Excitation-based and informational masking of a tonal signal in a four-tone masker

This study examined contributions of peripheral excitation and informational masking to the variability in masking effectiveness observed across samples of multi-tonal maskers. Detection thresholds were measured for a 1000-Hz signal presented simultaneously with each of 25, four-tone masker samples. Using a two-interval, forced-choice adaptive task, thresholds were measured with each sample fixed throughout trial blocks for ten listeners. Average thresholds differed by as much as 26 dB across samples. An excitation-based model of partial loudness [Moore, B. C. J. et al. (1997). J. Audio Eng. Soc. 45, 224–237] was used to predict thresholds. These predictions accounted for a significant portion of variance in the data of several listeners, but no relation between the model and data was observed for many listeners. Moreover, substantial individual differences, on the order of 41 dB, were observed for some maskers. The largest individual differences were found for maskers predicted to produce minimal excitation-based masking. In subsequent conditions, one of five maskers was randomly presented in each interval. The difference in performance for samples with low versus high predicted thresholds was reduced in random compared to fixed conditions. These findings are consistent with a trading relation whereby informational masking is largest for conditions in which excitation-based masking is smallest

The role of endorphins and vasopressin in canine endotoxin shock

Chemical antagonists were used to assess the role of [beta]-endorphin and arginine-vasopressin (AVP) in canine endotoxin shock. Fifteen awake dogs were given Escherichia coli endotoxin IV. Within 5 min, CO decreased to 28%, LV dP/dt to 46%, and MAP to 52% of baseline. Fifteen minutes after endotoxin, five dogs each received naloxone, AVP antagonist, or no treatment. Control (untreated) animals exhibited persistent cardiovascular depression, with CO 49%, LV dP/dt 69%, and MAP 91% of baseline after 45 min. Naloxone improved CO to 69%, LV dP/dt to 94%, and MAP to 91% by 30 min after treatment. AVP blockade improved CO to 105%, LV dP/dt to 10%, and MAP to 95% of baseline by 30 min after treatment, and caused significant tachycardia. Plasma cortisol and AVP increased markedly in all groups after endotoxin administration. AVP antagonist treatment increased mean survival from 1.4 to 4 days. These data suggest that abnormally elevated AVP contributes to cardiovascular depression in canine endotoxin shock and that AVP blockade is therapeutic in the animal model studied.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/25963/1/0000029.pd

Is the prevalence of psychiatric disorders associated with urbanization?

Objectives In many countries, the total rate of psychiatric disorders tends to be higher in urban areas than in rural areas. The relevance of this phenomenon is that it may help in identifying environmental factors that are important in the pathogenesis of mental disorders. Moreover, urban preponderance suggests that the allocation of funds and services should take urbanization levels into account. Method The Netherlands Mental Health Survey and Incidence Study (NEMESIS) used the Composite International Diagnostic Interview (CIDI) to determine the prevalence of DSM-III-R disorders in a sample of 7,076 people aged 18–64. The sample was representative of the population as a whole. The study population was assigned to five urbanization categories defined at the level of municipalities. The association between urbanization and 12-month prevalence rates of psychiatric disorders was studied using logistic regression taking several confounders into account. Results The prevalence of psychiatric disorders gradually increased over five levels of urbanization. This pattern remained after adjustment for a range of confounders. Comorbidity rates also increased with level of urbanization. Conclusion This study confirms that psychiatric disorders are more common and more complex in more urbanized areas. This should be reflected in service allocation and may help in identifying environmental factors of importance for the aetiology of mental disorders. j Key words population survey – psychiatric epidemiology – mental disorders – urbanizatio

Light and Heavy Fractions of Soil Organic Matter in Response to Climate Warming and Increased Precipitation in a Temperate Steppe

Soil is one of the most important carbon (C) and nitrogen (N) pools and plays a crucial role in ecosystem C and N cycling. Climate change profoundly affects soil C and N storage via changing C and N inputs and outputs. However, the influences of climate warming and changing precipitation regime on labile and recalcitrant fractions of soil organic C and N remain unclear. Here, we investigated soil labile and recalcitrant C and N under 6 years' treatments of experimental warming and increased precipitation in a temperate steppe in Northern China. We measured soil light fraction C (LFC) and N (LFN), microbial biomass C (MBC) and N (MBN), dissolved organic C (DOC) and heavy fraction C (HFC) and N (HFN). The results showed that increased precipitation significantly stimulated soil LFC and LFN by 16.1% and 18.5%, respectively, and increased LFC∶HFC ratio and LFN∶HFN ratio, suggesting that increased precipitation transferred more soil organic carbon into the quick-decayed carbon pool. Experimental warming reduced soil labile C (LFC, MBC, and DOC). In contrast, soil heavy fraction C and N, and total C and N were not significantly impacted by increased precipitation or warming. Soil labile C significantly correlated with gross ecosystem productivity, ecosystem respiration and soil respiration, but not with soil moisture and temperature, suggesting that biotic processes rather than abiotic factors determine variations in soil labile C. Our results indicate that certain soil carbon fraction is sensitive to climate change in the temperate steppe, which may in turn impact ecosystem carbon fluxes in response and feedback to climate change

A Survey of Kiloparsec-Scale Radio Outflows in Radio-Quiet Active Galactic Nuclei

Seyfert galaxies commonly host compact jets spanning 10-100 pc scales, but larger structures (KSRs) are resolved out in long baseline, aperture synthesis surveys. We report a new, short baseline Very Large Array (VLA) survey of a complete sample of Seyfert and LINER galaxies. Out of all of the surveyed radio-quiet sources, we find that 44% (19 / 43) show extended radio structures at least 1 kpc in total extent that do not match the morphology of the disk or its associated star-forming regions. The KSR Seyferts stand out by deviating significantly from the far-infrared - radio correlation for star-forming galaxies, and they are more likely to have a relatively luminous, compact radio source in the nucleus; these results argue that KSRs are powered by the AGN rather than starburst. KSRs probably originate from jet plasma that has been decelerated by interaction with the nuclear ISM. We demonstrate the jet loses virtually all of its power to the ISM within the inner kiloparsec to form the slow KSRs.Comment: to appear in the Astronomical Journal, Vol 132 (projected

What Stimulates Researchers to Make Their Research Usable? Towards an Openness Approach

Ambiguity surrounding the effect of external engagement on academic research has raised questions about what motivates researchers to collaborate with third parties. We argue that what matters for society is research that can be absorbed by users. We define openness as a willingness by researchers to make research more usable by external partners by responding to external influences in their own research practices. We ask what kinds of characteristics define those researchers who are more open to creating usable knowledge. Our empirical study analyses a sample of 1583 researchers working at the Spanish Council for Scientific Research (CSIC). Results demonstrate that it is personal factors (academic identity and past experience) that determine which researchers have open behaviours. The paper concludes that policies to encourage external engagement should focus on experiences which legitimate and validate knowledge produced through user encounters, both at the academic formation career stage as well as through providing ongoing opportunities to engage with third parties.The data used for this study comes from the IMPACTO project funded by the Spanish Council for Scientific Research - CSIC (Ref. 200410E639). The work also benefited from a mobility grant awarded by Eu-Spri Forum to Julia Olmos Penuela & Paul Benneworth for her visiting research to the Center of Higher Education Policy Studies. Finally, Julia Olmos Penuela also benefited from a post-doctoral grant funded by the Generalitat Valenciana (APOSTD-2014-A-006).Olmos-Peñuela, J.; Benneworth, P.; Castro-Martínez, E. (2015). What Stimulates Researchers to Make Their Research Usable? Towards an Openness Approach. Minerva. 53(4):381-410. https://doi.org/10.1007/s11024-015-9283-4S381410534Abreu, Maria, Vadim Grinevich, Alan Hughes, and Michael Kitson. 2009. Knowledge exchange between academics and the business, public and third sectors. Cambridge: Centre for Business Research and UK-IRC.Aghion, Philippe, Mathias Dewatripont, and Jeremy C. Stein. 2008. Academic freedom, private-sector focus, and the process of innovation. RAND Journal of Economics 39: 617–635.Ajzen, Icek. 2001. Nature and operation of attitudes. Annual Review of Psychology 52(1): 27–58.Alrøe, Hugo Fjelsted, and Erik Steen Kristensen. 2002. Towards a systemic research methodology in agriculture: Rethinking the role of values in science. Agriculture and Human Values 19(1): 3–23.Audretsch, David B., Werner Bönte, and Stefan Krabel. 2010. Why do scientists in public research institutions cooperate with private firms. In DRUID Working Paper, 10–27.Baldini, Nicola, Rosa Grimaldi, and Maurizio Sobrero. 2007. To patent or not to patent? A survey of Italian inventors on motivations, incentives, and obstacles to university patenting. Scientometrics 70(2): 333–354.Bandura, Albert. 1977. Social learning theory. Englewood Cliffs, NJ: Prentice-Hall.Barnett, R. 2009. Knowing and becoming in the higher education curriculum. Studies in Higher Education 34(4): 429–440.Becher, Tony. 1994. The significance of disciplinary differences. Studies in Higher Education 19(2): 151–161.Becher, Tony, and Paul Trowler. 2001. Academic tribes and territories: Intellectual enquiry and the culture of disciplines. McGraw-Hill International.Bekkers, Rudi, and Isabel Maria Bodas Freitas. 2008. Analysing knowledge transfer channels between universities and industry: To what degree do sectors also matter? Research Policy 37(10): 1837–1853.Belderbos, René, Martin Carree, Bert Diederen, Boris Lokshin, and Reinhilde Veugelers. 2004. Heterogeneity in R&D cooperation strategies. International Journal of Industrial Organization 22(8): 1237–1263.Benner, Mats, and Ulf Sandström. 2000. Institutionalizing the triple helix: Research funding and norms in the academic system. Research Policy 29(2): 291–301.Bercovitz, Janet, and Maryann Feldman. 2008. Academic entrepreneurs: Organizational change at the individual level. Organization Science 19(1): 69–89.Berman, Elizabeth Popp. 2011. Creating the market university: How academic science became an economic engine. Princeton University Press.Bleiklie, Ivar, and Roar Høstaker. 2004. Modernizing research training-education and science policy between profession, discipline and academic institution. Higher Education Policy 17(2): 221–236.Bozeman, Barry, Daniel Fay, and Catherine P. Slade. 2013. Research collaboration in universities and academic entrepreneurship: The-state-of-the-art. The Journal of Technology Transfer 38(1): 1–67.Collini, Stefan. 2009. Impact on humanities: Researchers must take a stand now or be judged and rewarded as salesmen. The Times Literary Supplement 5563: 18–19.D’Este, Pablo, and Markus Perkmann. 2011. Why do academics engage with industry? The entrepreneurial university and individual motivations. The Journal of Technology Transfer 36(3): 316–339.D’Este, Pablo, Oscar Llopis, and Alfredo Yegros. 2013. Conducting pro-social research: Cognitive diversity, research excellence and awareness about the social impact of research: INGENIO (CSIC-UPV) Working Paper Series.Deem, Rosemary, and Lisa Lucas. 2007. Research and teaching cultures in two contrasting UK policy contexts: Academic life in education departments in five English and Scottish universities. Higher Education 54(1): 115–133.DiMaggio, Paul J., and Walter W. Powell. 1983. The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields. American Sociological Review 48(2): 147–160.Downing, David B. 2005. The knowledge contract: Politics and paradigms in the academic workplace. Lincoln: Nebraska University of Nebraska Press.Donovan, Claire. 2007. The qualitative future of research evaluation. Science and Public Policy 34(8): 585–597.Durning, Bridget. 2004. Planning academics and planning practitioners: Two tribes or a community of practice? Planning Practice and Research 19(4): 435–446.Edquist, Charles. 1997. System of innovation approaches: Their emergence and characteristics. In Systems of innovation: Technologies, institutions and organizations, ed. C. Edquist, 1–35. London: Pinter.Etzkowitz, Henry, and Loet Leydesdorff. 2000. The dynamics of innovation: from National Systems and “Mode 2” to a Triple Helix of university–industry–government relations. Research Policy 29(2): 109–123.Fromhold-Eisebith, Martina, Claudia Werker, and Marcel Vojnic. 2014. Tracing the social dimension in innovation networks. In The social dynamics of innovation networks, eds. Roel Rutten, Paul Benneworth, Frans Boekema, and Dessy Irawati. London: Routledge (in press).Geuna, Aldo, and Alessandro Muscio. 2009. The governance of university knowledge transfer: A critical review of the literature. Minerva 47(1): 93–114.Gibbons, Michael, Camille Limoges, Helga Nowotny, Simon Schwartzman, Peter Scott, and Martin Trow. 1994. The new production of knowledge: The dynamics of science and research in contemporary societies. London: Sage.Gläser, Jochen. 2012. How does Governance change research content? On the possibility of a sociological middle-range theory linking science policy studies to the sociology of scientific knowledge. Technical University Berlin. Technology Studies Working Papers. http://www.ts.tu-berlin.de/fileadmin/fg226/TUTS/TUTS-WP-1-2012.pdf . Accessed 16 Feb 2015.Goethner, Maximilian, Martin Obschonka, Rainer K. Silbereisen, and Uwe Cantner. 2012. Scientists’ transition to academic entrepreneurship: Economic and psychological determinants. Journal of Economic Psychology 33(3): 628–641.Gulbrandsen, Magnus, and Jens-Christian Smeby. 2005. Industry funding and university professors’ research performance. Research Policy 34(6): 932–950.Haeussler, Carolin, and Jeannette Colyvas. 2011. Breaking the ivory tower: Academic entrepreneurship in the life sciences in UK and Germany. Research Policy 40(1): 41–54.Hessels, Laurens K., Harro van Lente, John Grin, and Ruud E.H.M. Smits. 2011. Changing struggles for relevance in eight fields of natural science. Industry and Higher Education 25(5): 347–357.Hessels, Laurens K., and Harro Van Lente. 2008. Re-thinking new knowledge production: A literature review and a research agenda. Research Policy 37(4): 740–760.Hoye, Kate, and Fred Pries. 2009. ‘Repeat commercializers’, the ‘habitual entrepreneurs’ of university–industry technology transfer. Technovation 29(10): 682–689.Jacobson, Nora, Dale Butterill, and Paula Goering. 2004. Organizational factors that influence university-based researchers’ engagement in knowledge transfer activities. Science Communication 25(3): 246–259.Jain, Sanjay, Gerard George, and Mark Maltarich. 2009. Academics or entrepreneurs? Investigating role identity modification of university scientists involved in commercialization activity. Research Policy 38(6): 922–935.Jasanoff, Sheila, and Sang-Hyun Kim. 2013. Sociotechnical imaginaries and national energy policies. Science as Culture 22(2): 189–196.Jensen, Pablo. 2011. A statistical picture of popularization activities and their evolutions in France. Public Understanding of Science 20(1): 26–36.Kitcher, Philip. 2001. Science, truth, and democracy. Oxford: Oxford University Press.Knorr-Cetina, Karin. 1981. The manufacture of knowledge: An essay on the constructivist and contextual nature of science. Oxford: Pergamon Press.Kronenberg, Kristin, and Marjolein Caniëls. 2014. Professional proximity in research collaborations. In The social dynamics of innovation networks, eds. Roel Rutten, Paul Benneworth, Frans Boekema, and Dessy Irawati. London: Routledge (in press).Krueger, Rob, and David Gibbs. 2010. Competitive global city regions and sustainable development’: An interpretive institutionalist account in the South East of England. Environment and planning A 42: 821–837.Lam, Alice. 2011. What motivates academic scientists to engage in research commercialization: ‘Gold’, ‘ribbon’ or ‘puzzle’? Research Policy 40(10): 1354–1368.Landry, Réjean, Malek Saïhi, Nabil Amara, and Mathieu Ouimet. 2010. Evidence on how academics manage their portfolio of knowledge transfer activities. Research Policy 39(10): 1387–1403.Lee, Alison, and David Boud. 2003. Writing groups, change and academic identity: Research development as local practice. Studies in Higher Education 28(2): 187–200.Lee, Yong S. 1996. ‘Technology transfer’ and the research university: A search for the boundaries of university–industry collaboration. Research Policy 25(6): 843–863.Lee, Yong S. 2000. The sustainability of university–industry research collaboration: An empirical assessment. The Journal of Technology Transfer 25(2): 111–133.Leisyte, Liudvika, Jürgen Enders, and Harry De Boer. 2008. The freedom to set research agendas—illusion and reality of the research units in the Dutch Universities. Higher Education Policy 21(3): 377–391.Louis, Karen Seashore, David Blumenthal, Michael E. Gluck, and Michael A. Stoto. 1989. Entrepreneurs in academe: An exploration of behaviors among life scientists. Administrative Science Quarterly 34(1): 110–131.Lowe, Philip, Jeremy Phillipson, and Katy Wilkinson. 2013. Why social scientists should engage with natural scientists. Contemporary Social Science 8(3): 207–222.Martín-Sempere, María José, Belén Garzón-García, and Jesús Rey-Rocha. 2008. Scientists’ motivation to communicate science and technology to the public: Surveying participants at the Madrid Science Fair. Public Understanding of Science 17(3): 349–367.Martin, Ben. 2003. The changing social contract for science and the evolution of the university. In Science and innovation: Rethinking the rationales for funding and governance, eds. A. Geuna, A.J. Salter, and W.E. Steinmueller, 7–29. Cheltenhan: Edward Elgar.Merton, Robert K. 1973. The sociology of science: Theoretical and empirical investigations. Chicago: University of Chicago Press.Miller, Thaddeus R., and Mark W. Neff. 2013. De-facto science policy in the making: how scientists shape science policy and why it matters (or, why STS and STP scholars should socialize). Minerva 51(3): 295–315.Muthén, Bengt O. 1998–2004. Mplus Technical Appendices. Muthén & Muthén. Los Angeles, CA.: Muthén & Muthén.Nedeva, Maria. 2013. Between the global and the national: Organising European science. Research Policy 42(1): 220–230.Neff, Mark William. 2014. Research prioritization and the potential pitfall of path dependencies in coral reef science. Minerva 52(2): 213–235.Nelson, Richard R. 2001. Observations on the post-Bayh-Dole rise of patenting at American universities. The Journal of Technology Transfer 26(1): 13–19.Nowotny, Helga, Peter Scott, and Michael Gibbons. 2001. Re-thinking science: Knowledge and the public in an age of uncertainty. Cambridge: Polity Press.Olmos-Peñuela, Julia, Paul Benneworth, and Elena Castro-Martínez. 2014a. Are ‘STEM from Mars and SSH from Venus’? Challenging disciplinary stereotypes of research’s social value. Science and Public Policy 41: 384–400.Olmos-Peñuela, Julia, Elena Castro-Martínez, and Manuel Fernández-Esquinas. 2014b. Diferencias entre áreas científicas en las prácticas de divulgación de la investigación: un estudio empírico en el CSIC. Revista Española de Documentación Científica. doi: 10.3989/redc.2014.2.1096 .Ouimet, Mathieu, Nabil Amara, Réjean Landry, and John Lavis. 2007. Direct interactions medical school faculty members have with professionals and managers working in public and private sector organizations: A cross-sectional study. Scientometrics 72(2): 307–323.Perkmann, Markus, Valentina Tartari, Maureen McKelvey, Erkko Autio, Anders Brostrom, Pablo D’Este, Riccardo Fini, et al. 2013. Academic engagement and commercialisation: A review of the literature on university-industry relations. Research Policy 42(2): 423–442.Philpott, Kevin, Lawrence Dooley, Caroline O’Reilly, and Gary Lupton. 2011. The entrepreneurial university: Examining the underlying academic tensions. Technovation 31(4): 161–170.Rutten, Roel, and Frans Boekema. 2012. From learning region to learning in a socio-spatial context. Regional Studies 46(8): 981–992.Sarewitz, Daniel, and Roger A. Pielke. 2007. The neglected heart of science policy: reconciling supply of and demand for science. Environmental Science & Policy 10(1): 5–16.Sauermann, Henry, and Paula Stephan. 2013. Conflicting logics? A multidimensional view of industrial and academic science. Organization Science 24(3): 889–909.Schein, Edgar H. 1985. Organizational culture and leadership: A dynamic view. San Francisco, CA: Jossey-Bass.Shane, Scott. 2000. Prior knowledge and the discovery of entrepreneurial opportunities. Organization Science 11(4): 448–469.Spaapen, Jack, and Leonie van Drooge. 2011. Introducing ‘productive interactions’ in social impact assessment. Research Evaluation 20(3): 211–218.Stokes, Donald E. 1997. Pasteur’s quadrant: Basic science and technological innovation. Washington, DC: Brookings Institution Press.Tartari, Valentina, and Stefano Breschi. 2012. Set them free: scientists’ evaluations of the benefits and costs of university–industry research collaboration. Industrial and Corporate Change 21(5): 1117–1147.Tinker, Tony, and Rob Gray. 2003. Beyond a critique of pure reason: From policy to politics to praxis in environmental and social research. Accounting, Auditing & Accountability Journal 16(5): 727–761.van Rijnsoever, Frank J., Laurens K. Hessels, and Rens L.J. Vandeberg. 2008. A resource-based view on the interactions of university researchers. Research Policy 37(8): 1255–1266.Venkataraman, Sankaran. 1997. The distinctive domain of entrepreneurship research: An editor’s perspective. Advances in Entrepreneurship, Firm Emergence, and Growth 3: 119–138.Verspagen, Bart. 2006. University research, intellectual property rights and European innovation systems. Journal of Economic Surveys 20(4): 607–632.Villanueva-Felez, Africa, Jordi Molas-Gallart, and Alejandro Escribá-Esteve. 2013. Measuring personal networks and their relationship with scientific production. Minerva 51(4): 465–483.Watermeyer, Richard. 2015. Lost in the ‘third space’: the impact of public engagement in higher education on academic identity, research practice and career progression. European Journal of Higher Education (online first, doi: 10.1080/21568235.2015.1044546 ).Weingart, Peter. 2009. Editorial for Issue 47/3. Minerva 47(3): 237–239.Ziman, John. 1996. ‘Postacademic science’: Constructing knowledge with networks and norms. Science Studies 1: 67–80.Zomer, Arend H., Ben W.A. Jongbloed, and Jürgen Enders. 2010. Do spin-offs make the academics’ heads spin? The impacts of spin-off companies on their parent research organisation. Minerva 48(3): 331–353

Small-Animal PET Imaging of Amyloid-Beta Plaques with [11C]PiB and Its Multi-Modal Validation in an APP/PS1 Mouse Model of Alzheimer's Disease

In vivo imaging and quantification of amyloid-β plaque (Aβ) burden in small-animal models of Alzheimer's disease (AD) is a valuable tool for translational research such as developing specific imaging markers and monitoring new therapy approaches. Methodological constraints such as image resolution of positron emission tomography (PET) and lack of suitable AD models have limited the feasibility of PET in mice. In this study, we evaluated a feasible protocol for PET imaging of Aβ in mouse brain with [11C]PiB and specific activities commonly used in human studies. In vivo mouse brain MRI for anatomical reference was acquired with a clinical 1.5 T system. A recently characterized APP/PS1 mouse was employed to measure Aβ at different disease stages in homozygous and hemizygous animals. We performed multi-modal cross-validations for the PET results with ex vivo and in vitro methodologies, including regional brain biodistribution, multi-label digital autoradiography, protein quantification with ELISA, fluorescence microscopy, semi-automated histological quantification and radioligand binding assays. Specific [11C]PiB uptake in individual brain regions with Aβ deposition was demonstrated and validated in all animals of the study cohort including homozygous AD animals as young as nine months. Corresponding to the extent of Aβ pathology, old homozygous AD animals (21 months) showed the highest uptake followed by old hemizygous (23 months) and young homozygous mice (9 months). In all AD age groups the cerebellum was shown to be suitable as an intracerebral reference region. PET results were cross-validated and consistent with all applied ex vivo and in vitro methodologies. The results confirm that the experimental setup for non-invasive [11C]PiB imaging of Aβ in the APP/PS1 mice provides a feasible, reproducible and robust protocol for small-animal Aβ imaging. It allows longitudinal imaging studies with follow-up periods of approximately one and a half years and provides a foundation for translational Alzheimer neuroimaging in transgenic mice

Large-Scale Phenotyping of an Accurate Genetic Mouse Model of JNCL Identifies Novel Early Pathology Outside the Central Nervous System

Cln3Δex7/8 mice harbor the most common genetic defect causing juvenile neuronal ceroid lipofuscinosis (JNCL), an autosomal recessive disease involving seizures, visual, motor and cognitive decline, and premature death. Here, to more thoroughly investigate the manifestations of the common JNCL mutation, we performed a broad phenotyping study of Cln3Δex7/8 mice. Homozygous Cln3Δex7/8 mice, congenic on a C57BL/6N background, displayed subtle deficits in sensory and motor tasks at 10–14 weeks of age. Homozygous Cln3Δex7/8 mice also displayed electroretinographic changes reflecting cone function deficits past 5 months of age and a progressive decline of retinal post-receptoral function. Metabolic analysis revealed increases in rectal body temperature and minimum oxygen consumption in 12–13 week old homozygous Cln3Δex7/8mice, which were also seen to a lesser extent in heterozygous Cln3Δex7/8 mice. Heart weight was slightly increased at 20 weeks of age, but no significant differences were observed in cardiac function in young adults. In a comprehensive blood analysis at 15–16 weeks of age, serum ferritin concentrations, mean corpuscular volume of red blood cells (MCV), and reticulocyte counts were reproducibly increased in homozygous Cln3Δex7/8 mice, and male homozygotes had a relative T-cell deficiency, suggesting alterations in hematopoiesis. Finally, consistent with findings in JNCL patients, vacuolated peripheral blood lymphocytes were observed in homozygous Cln3Δex7/8 neonates, and to a greater extent in older animals. Early onset, severe vacuolation in clear cells of the epididymis of male homozygous Cln3Δex7/8 mice was also observed. These data highlight additional organ systems in which to study CLN3 function, and early phenotypes have been established in homozygous Cln3Δex7/8 mice that merit further study for JNCL biomarker development