Human mesenchymal stem cells reduce the severity of acute lung injury in a sheep model of bacterial pneumonia

Background Human bone marrow-derived mesenchymal stem (stromal) cells (hMSCs) improve survival in mouse models of acute respiratory distress syndrome (ARDS) and reduce pulmonary oedema in a perfused human lung preparation injured with Escherichia coli bacteria. We hypothesised that clinical grade hMSCs would reduce the severity of acute lung injury (ALI) and would be safe in a sheep model of ARDS.

Methods Adult sheep (30–40 kg) were surgically prepared. After 5 days of recovery, ALI was induced with cotton smoke insufflation, followed by instillation of live Pseudomonas aeruginosa (2.5×10¹¹ CFU) into both lungs under isoflurane anaesthesia. Following the injury, sheep were ventilated, resuscitated with lactated Ringer's solution and studied for 24 h. The sheep were randomly allocated to receive one of the following treatments intravenously over 1 h in one of the following groups: (1) control, PlasmaLyte A, n=8; (2) lower dose hMSCs, 5×10⁶ hMSCs/kg, n=7; and (3) higher-dose hMSCs, 10×10⁶ hMSCs/kg, n=4.

Results By 24 h, the PaO₂/FiO₂ ratio was significantly improved in both hMSC treatment groups compared with the control group (control group: PaO₂/FiO₂ of 97±15 mm Hg; lower dose: 288±55 mm Hg (p=0.003); higher dose: 327±2 mm Hg (p=0.003)). The median lung water content was lower in the higher-dose hMSC-treated group compared with the control group (higher dose: 5.0 g wet/g dry [IQR 4.9–5.8] vs control: 6.7 g wet/g dry [IQR 6.4–7.5] (p=0.01)). The hMSCs had no adverse effects.

Conclusions Human MSCs were well tolerated and improved oxygenation and decreased pulmonary oedema in a sheep model of severe ARDS.

Building Trust in a Post-Conflict Society: An Integrative Model of Intergroup Contact and Intergroup Emotions.

Across one longitudinal and two cross-sectional surveys in Northern Ireland, we tested a model of intergroup relations in which out-group attitudes and behavioral tendencies are predicted by cross-group friendship and positive intergroup appraisals, mediated by intergroup emotions and out-group trust. In study 1, out-group friendship at time 1 predicted out-group trust at time 2 (one year later), controlling for prior out-group trust. In study 2, positive and negative intergroup emotions mediated the effects of friendship on positive and negative behavioral tendencies and attitudes. In study 3, a confirmatory factor analysis indicated that trust and emotions are distinct constructs with unique predictive contributions. We then tested a model in which cross-group friendship predicted intergroup emotions and trust through intimate self-disclosure in out-group friendships. Our findings support an integration of an intergroup emotions framework with research highlighting the importance of cross-group friendship in fostering positive intergroup outcomes.

Analytical model of interwoven spiral arrays

Interweaving planar spiral conductors in doubly periodic arrays enable substantially sub-wavelength resonant response along with broadening fractional bandwidth. A self-contained analytical model is proposed to accurately predict the characteristics of the intertwined quadrifilar spiral array near the fundamental resonance. The model, based upon a multiconductor transmission line (MTL) approach, provides physical insight into the unique properties of the distributed interactions between the interleaved counter-wound spiral arms extended beyond a single unit cell and elucidates the mechanisms underlying the array performance at normal and oblique incidence of TE and TM polarised waves. The developed MTL model is instrumental in the design of the artificial surfaces with the specified response.

Effects of thyroxine treatment on histology and behavior using the methimazole model of congenital hypothyroidism in the rat

The timing of thyroxine (T4) replacement treatment in congenital hypothyroidism (CH) has been suggested to be important for optimizing cognitive recovery in humans; however this has not been fully established using modern animal models of CH. Consequently, the current studies investigated the ameliorating effects of postnatal T4 treatment on neuropathology and behavior in CH rats. Rat dams were administered methimazole to produce CH offspring, then brain tissue from male CH pups was analyzed to determine the effects of postnatal (P3, P7, P14 and P21) T4 treatment on hippocampal dendritic branching and the expression of nerve growth factor (NGF). Two operant behavioral procedures were employed to confirm and extend previous findings obtained using this model, and to investigate timelines for instigating T4 treatment on improved behavioral outcomes. T4 treatment initiated at P14 was protective of a reduction in dendritic branching in the hippocampus, and initiated at P7 was protective of a reduction of NGF expression in the fimbria of the hippocampus. Induction of CH did not affect the acquisition of simple operant response rules but had a significant effect on the acquisition of complex operant rules subsequently imposed. Furthermore, T4 treatment initiated at P3 protected learning deficits seen following the imposition of complex operant response rules. These findings indicate T4 treatment initiated at P7 is sufficient for the protection of hippocampal NGF expression and dendritic branching but for the protection of complex behavioral abilities T4 treatment is necessary prior to or approximating P3.

Interpretable semantic vectors from a joint model of brain-and text-based meaning

Vector space models (VSMs) represent word meanings as points in a high dimensional space. VSMs are typically created using a large text corpora, and so represent word semantics as observed in text. We present a new algorithm (JNNSE) that can incorporate a measure of semantics not previously used to create VSMs: brain activation data recorded while people read words. The resulting model takes advantage of the complementary strengths and weaknesses of corpus and brain activation data to give a more complete representation of semantics. Evaluations show that the model 1) matches a behavioral measure of semantics more closely, 2) can be used to predict corpus data for unseen words and 3) has predictive power that generalizes across brain imaging technologies and across subjects. We believe that the model is thus a more faithful representation of mental vocabularies.