PROTOCOL: Residential energy efficiency interventions: An effectiveness systematic review

This review aims to identify, appraise and synthesise the evidence available on the effectiveness of energy efficiency measure installations, including those bundled with behavioural interventions. The synthesis will estimate the overall impact of these interventions as well as examine possible causes of variation in impacts. We will also attempt to assess the cost-effectiveness of residential energy efficiency interventions

Dopamine neuronal loss contributes to memory and reward dysfunction in a model of Alzheimer's disease

Alterations of the dopaminergic (DAergic) system are frequently reported in Alzheimer’s disease (AD) patients and are commonly linked to cognitive and non-cognitive symptoms. However, the cause of DAergic system dysfunction in AD remains to be elucidated. We investigated alterations of the midbrain DAergic system in the Tg2576 mouse model of AD, overexpressing a mutated human amyloid precursor protein (APPswe). Here, we found an age-dependent DAergic neuron loss in the ventral tegmental area (VTA) at pre-plaque stages, although substantia nigra pars compacta (SNpc) DAergic neurons were intact. The selective VTA DAergic neuron degeneration results in lower DA outflow in the hippocampus and nucleus accumbens (NAc) shell. The progression of DAergic cell death correlates with impairments in CA1 synaptic plasticity, memory performance and food reward processing. We conclude that in this mouse model of AD, degeneration of VTA DAergic neurons at pre-plaque stages contributes to memory deficits and dysfunction of reward processing

Inflammation subverts hippocampal synaptic plasticity in experimental multiple sclerosis

Abnormal use-dependent synaptic plasticity is universally accepted as the main physiological correlate of memory deficits in neurodegenerative disorders. It is unclear whether synaptic plasticity deficits take place during neuroinflammatory diseases, such as multiple sclerosis (MS) and its mouse model, experimental autoimmune encephalomyelitis (EAE). In EAE mice, we found significant alterations of synaptic plasticity rules in the hippocampus. When compared to control mice, in fact, hippocampal long-term potentiation (LTP) induction was favored over long-term depression (LTD) in EAE, as shown by a significant rightward shift in the frequency-synaptic response function. Notably, LTP induction was also enhanced in hippocampal slices from control mice following interleukin-1β (IL-1β) perfusion, and both EAE and IL-1β inhibited GABAergic spontaneous inhibitory postsynaptic currents (sIPSC) without affecting glutamatergic transmission and AMPA/NMDA ratio. EAE was also associated with selective loss of GABAergic interneurons and with reduced gamma-frequency oscillations in the CA1 region of the hippocampus. Finally, we provided evidence that microglial activation in the EAE hippocampus was associated with IL-1β expression, and hippocampal slices from control mice incubated with activated microglia displayed alterations of GABAergic transmission similar to those seen in EAE brains, through a mechanism dependent on enhanced IL-1β signaling. These data may yield novel insights into the basis of cognitive deficits in EAE and possibly of MS

Late presentation of metastatic smooth muscle neoplasm of the uterus with low malignant potential

A 48-year-old woman underwent total abdominal hysterectomy with conservation of the ovaries and tubes. Histology showed a well-circumscribed smooth muscle tumor with foci of degeneration (including infarct-type necrosis) but no coagulative tumor cell necrosis and only mild focal cytological atypia. She presented, 24 years later with shortness of breath and abdominal distension and underwent bilateral salpingo-oophorectomy, appendectomy, omental biopsy and para-aortic lymph node sampling. Histology showed bilateral ovarian smooth muscle tumors with no coagulative tumor cell necrosis or significant cellular atypia. The cells were mitotically active. The tumors in both ovaries were most likely secondary to the previous uterine smooth muscle neoplasm. To our knowledge, this case is the first in the literature to describe a benign cellular leiomyoma that subsequently behaved as a smooth muscle tumor of uncertain malignant potential, which recurred 24 years after the initial diagnosis

Translational potential of olfactory mucosa for the study of neuropsychiatric illness

The olfactory mucosa (OM) is a unique source of regenerative neural tissue that is readily obtainable from living human subjects and thus affords opportunities for the study of psychiatric illnesses. OM tissues can be used, either as ex vivo OM tissue or in vitro OM-derived neural cells, to explore parameters that have been difficult to assess in the brain of living individuals with psychiatric illness. As OM tissues are distinct from brain tissues, an understanding of the neurobiology of the OM is needed to relate findings in these tissues to those of the brain as well as to design and interpret ex vivo or in vitro OM studies. To that end, we discuss the molecular, cellular and functional characteristics of cell types within the olfactory mucosa, describe the organization of the OM and highlight its role in the olfactory neurocircuitry. In addition, we discuss various approaches to in vitro culture of OM-derived cells and their characterization, focusing on the extent to which they reflect the in vivo neurobiology of the OM. Finally, we review studies of ex vivo OM tissues and in vitro OM-derived cells from individuals with psychiatric, neurodegenerative and neurodevelopmental disorders. In particular, we discuss the concordance of this work with postmortem brain studies and highlight possible future approaches, which may offer distinct strengths in comparison to in vitro paradigms based on genomic reprogramming

QAPgrid: A Two Level QAP-Based Approach for Large-Scale Data Analysis and Visualization

Background: The visualization of large volumes of data is a computationally challenging task that often promises rewarding new insights. There is great potential in the application of new algorithms and models from combinatorial optimisation. Datasets often contain “hidden regularities” and a combined identification and visualization method should reveal these structures and present them in a way that helps analysis. While several methodologies exist, including those that use non-linear optimization algorithms, severe limitations exist even when working with only a few hundred objects. Methodology/Principal Findings: We present a new data visualization approach (QAPgrid) that reveals patterns of similarities and differences in large datasets of objects for which a similarity measure can be computed. Objects are assigned to positions on an underlying square grid in a two-dimensional space. We use the Quadratic Assignment Problem (QAP) as a mathematical model to provide an objective function for assignment of objects to positions on the grid. We employ a Memetic Algorithm (a powerful metaheuristic) to tackle the large instances of this NP-hard combinatorial optimization problem, and we show its performance on the visualization of real data sets. Conclusions/Significance: Overall, the results show that QAPgrid algorithm is able to produce a layout that represents the relationships between objects in the data set. Furthermore, it also represents the relationships between clusters that are feed into the algorithm. We apply the QAPgrid on the 84 Indo-European languages instance, producing a near-optimal layout. Next, we produce a layout of 470 world universities with an observed high degree of correlation with the score used by the Academic Ranking of World Universities compiled in the The Shanghai Jiao Tong University Academic Ranking of World Universities without the need of an ad hoc weighting of attributes. Finally, our Gene Ontology-based study on Saccharomyces cerevisiae fully demonstrates the scalability and precision of our method as a novel alternative tool for functional genomics

Dopamine neuronal loss contributes to memory and reward dysfunction in a model of Alzheimer's disease

Alterations of the dopaminergic (DAergic) system are frequently reported in Alzheimer's disease (AD) patients and are commonly linked to cognitive and non-cognitive symptoms. However, the cause of DAergic system dysfunction in AD remains to be elucidated. We investigated alterations of the midbrain DAergic system in the Tg2576 mouse model of AD, overexpressing a mutated human amyloid precursor protein (APPswe). Here, we found an age-dependent DAergic neuron loss in the ventral tegmental area (VTA) at pre-plaque stages, although substantia nigra pars compacta (SNpc) DAergic neurons were intact. The selective VTA DAergic neuron degeneration results in lower DA outflow in the hippocampus and nucleus accumbens (NAc) shell. The progression of DAergic cell death correlates with impairments in CA1 synaptic plasticity, memory performance and food reward processing. We conclude that in this mouse model of AD, degeneration of VTA DAergic neurons at pre-plaque stages contributes to memory deficits and dysfunction of reward processing

Analysis of the RLMS Adaptive Beamforming Algorithm Implemented with Finite Precision

This paper studies the influence of the use of finite wordlength on the operation of the RLMS adaptive beamformingalgorithm. The convergence behavior of RLMS, based on the minimum mean square error (MSE), is analyzed for operation with finite precision. Computer simulation results verify that a wordlength of nine bits is sufficient for the RLMS algorithm to achieve performance close to that provided by full precision. The performance measures used include residual MSE, rate of convergence, error vector magnitude (EVM), and beam pattern. Based on all these measures, it is shown that the RLMS algorithm outperforms other earlier algorithms, such as least mean square (LMS), recursive least square (RLS), modified robust variable step size (MRVSS) and constrained stability LMS (CSLMS)