@article{SunOrtegaTanetal.2018,
  author    = {Sun, Ping and Ortega, Gabriela and Tan, Yan and Hua, Qian and Riederer, Peter F. and Deckert, J{\"u}rgen and Schmitt-B{\"o}hrer, Angelika G.},
  title     = {Streptozotocin impairs proliferation and differentiation of adult hippocampal neural stem cells in vitro-correlation with alterations in the expression of proteins associated with the insulin system},
  series = {Frontiers in Aging Neuroscience},
  volume    = {10},
  journal   = {Frontiers in Aging Neuroscience},
  number    = {145},
  doi       = {10.3389/fnagi.2018.00145},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-176741},
  year      = {2018},
  abstract  = {Rats intracerebroventricularily (icv) treated with streptozotocin (STZ), shown to generate an insulin resistant brain state, were used as an animal model for the sporadic form of Alzheimer's disease (sAD). Previously, we showed in an in vivo study that 3 months after STZ icv treatment hippocampal adult neurogenesis (AN) is impaired. In the present study, we examined the effects of STZ on isolated adult hippocampal neural stem cells (NSCs) using an in vitro approach. We revealed that 2.5 mM STZ inhibits the proliferation of NSCs as indicated by reduced number and size of neurospheres as well as by less BrdU-immunoreactive NSCs. Double immunofluorescence stainings of NSCs already being triggered to start with their differentiation showed that STZ primarily impairs the generation of new neurons, but not of astrocytes. For revealing mechanisms possibly involved in mediating STZ effects we analyzed expression levels of insulin/glucose system-related molecules such as the glucose transporter (GLUT) 1 and 3, the insulin receptor (IR) and the insulin-like growth factor (IGF) 1 receptor. Applying quantitative Real time-PCR (qRT-PCR) and immunofluorescence stainings we showed that STZ exerts its strongest effects on GLUT3 expression, as GLUT3 mRNA levels were found to be reduced in NSCs, and less GLUT3-immunoreactive NSCs as well as differentiating cells were detected after STZ treatment. These findings suggest that cultured NSCs are a good model for developing new strategies to treat nerve cell loss in AD and other degenerative disorders.},
  language  = {en}
}
@article{HaberstumpfForsterLeinweberetal.2022,
  author    = {Haberstumpf, Sophia and Forster, Andr{\´e} and Leinweber, Jonas and Rauskolb, Stefanie and Hewig, Johannes and Sendtner, Michael and Lauer, Martin and Polak, Thomas and Deckert, J{\"u}rgen and Herrmann, Martin J.},
  title     = {Measurement invariance testing of longitudinal neuropsychiatric test scores distinguishes pathological from normative cognitive decline and highlights its potential in early detection research},
  series = {Journal of Neuropsychology},
  volume    = {16},
  journal   = {Journal of Neuropsychology},
  number    = {2},
  doi       = {10.1111/jnp.12269},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-318932},
  pages     = {324 -- 352},
  year      = {2022},
  abstract  = {Objective Alzheimer's disease (AD) is a growing challenge worldwide, which is why the search for early-onset predictors must be focused as soon as possible. Longitudinal studies that investigate courses of neuropsychological and other variables screen for such predictors correlated to mild cognitive impairment (MCI). However, one often neglected issue in analyses of such studies is measurement invariance (MI), which is often assumed but not tested for. This study uses the absence of MI (non-MI) and latent factor scores instead of composite variables to assess properties of cognitive domains, compensation mechanisms, and their predictability to establish a method for a more comprehensive understanding of pathological cognitive decline. Methods An exploratory factor analysis (EFA) and a set of increasingly restricted confirmatory factor analyses (CFAs) were conducted to find latent factors, compared them with the composite approach, and to test for longitudinal (partial-)MI in a neuropsychiatric test battery, consisting of 14 test variables. A total of 330 elderly (mean age: 73.78 ± 1.52 years at baseline) were analyzed two times (3 years apart). Results EFA revealed a four-factor model representing declarative memory, attention, working memory, and visual-spatial processing. Based on CFA, an accurate model was estimated across both measurement timepoints. Partial non-MI was found for parameters such as loadings, test- and latent factor intercepts as well as latent factor variances. The latent factor approach was preferable to the composite approach. Conclusion The overall assessment of non-MI latent factors may pose a possible target for this field of research. Hence, the non-MI of variances indicated variables that are especially suited for the prediction of pathological cognitive decline, while non-MI of intercepts indicated general aging-related decline. As a result, the sole assessment of MI may help distinguish pathological from normative aging processes and additionally may reveal compensatory neuropsychological mechanisms.},
  language  = {en}
}