Relationships among neurocognition, symptoms and functioning in patients with schizophrenia: a path-analytic approach for associations at baseline and following 24 weeks of antipsychotic drug therapy

<p>Abstract</p> <p>Background</p> <p>Neurocognitive impairment and psychiatric symptoms have been associated with deficits in psychosocial and occupational functioning in patients with schizophrenia. This post-hoc analysis evaluates the relationships among cognition, psychopathology, and psychosocial functioning in patients with schizophrenia at baseline and following sustained treatment with antipsychotic drugs.</p> <p>Methods</p> <p>Data were obtained from a clinical trial assessing the cognitive effects of selected antipsychotic drugs in patients with schizophrenia. Patients were randomly assigned to 24 weeks of treatment with olanzapine (n = 159), risperidone (n = 158), or haloperidol (n = 97). Psychosocial functioning was assessed with the Heinrichs-Carpenter Quality of Life Scale [QLS], cognition with a standard battery of neurocognitive tests; and psychiatric symptoms with the Positive and Negative Syndrome Scale [PANSS]. A path-analytic approach was used to evaluate the effects of changes in cognitive functioning on subdomains of quality of life, and to determine whether such effects were direct or mediated via changes in psychiatric symptoms.</p> <p>Results</p> <p>At baseline, processing speed affected functioning mainly indirectly via negative symptoms. Positive symptoms also affected functioning at baseline although independent of cognition. At 24 weeks, changes in processing speed affected changes in functioning both directly and indirectly via PANSS negative subscale scores. Positive symptoms no longer contributed to the path-analytic models. Although a consistent relationship was observed between processing speed and the 3 functional domains, variation existed as to whether the paths were direct and/or indirect. Working memory and verbal memory did not significantly contribute to any of the path-analytic models studied.</p> <p>Conclusion</p> <p>Processing speed demonstrated direct and indirect effects via negative symptoms on three domains of functioning as measured by the QLS at baseline and following 24 weeks of antipsychotic treatment.</p

Autocrine Activation of the MET Receptor Tyrosine Kinase in Acute Myeloid Leukemia

Although the treatment of acute myeloid leukemia (AML) has improved significantly, more than half of all patients develop disease that is refractory to intensive chemotherapy. Functional genomics approaches offer a means to discover specific molecules mediating aberrant growth and survival of cancer cells. Thus, using a loss-of-function RNA interference genomic screen, we identified aberrant expression of the hepatocyte growth factor (HGF) as a critical factor in AML pathogenesis. We found HGF expression leading to autocrine activation of its receptor tyrosine kinase, MET, in nearly half of the AML cell lines and clinical samples studied. Genetic depletion of HGF or MET potently inhibited the growth and survival of HGF-expressing AML cells. However, leukemic cells treated with the specific MET kinase inhibitor crizotinib developed resistance due to compensatory upregulation of HGF expression, leading to restoration of MET signaling. In cases of AML where MET is coactivated with other tyrosine kinases, such as fibroblast growth factor receptor 1 (FGFR1), concomitant inhibition of FGFR1 and MET blocked compensatory HGF upregulation, resulting in sustained logarithmic cell kill both in vitro and in xenograft models in vivo. Our results demonstrate widespread dependence of AML cells on autocrine activation of MET, as well as the importance of compensatory upregulation of HGF expression in maintaining leukemogenic signaling by this receptor. We anticipate that these findings will lead to the design of additional strategies to block adaptive cellular responses that drive compensatory ligand expression as an essential component of the targeted inhibition of oncogenic receptors in human cancers

The 5-Choice Continuous Performance Test: Evidence for a Translational Test of Vigilance for Mice

Attentional dysfunction is related to functional disability in patients with neuropsychiatric disorders such as schizophrenia, bipolar disorder, and Alzheimer's disease. Indeed, sustained attention/vigilance is among the leading targets for new medications designed to improve cognition in schizophrenia. Although vigilance is assessed frequently using the continuous performance test (CPT) in humans, few tests specifically assess vigilance in rodents.We describe the 5-choice CPT (5C-CPT), an elaboration of the 5-choice serial reaction (5CSR) task that includes non-signal trials, thus mimicking task parameters of human CPTs that use signal and non-signal events to assess vigilance. The performances of C57BL/6J and DBA/2J mice were assessed in the 5C-CPT to determine whether this task could differentiate between strains. C57BL/6J mice were also trained in the 5CSR task and a simple reaction-time (RT) task involving only one choice (1CRT task). We hypothesized that: 1) C57BL/6J performance would be superior to DBA/2J mice in the 5C-CPT as measured by the sensitivity index measure from signal detection theory; 2) a vigilance decrement would be observed in both strains; and 3) RTs would increase across tasks with increased attentional load (1CRT task<5CSR task<5C-CPT).C57BL/6J mice exhibited superior SI levels compared to DBA/2J mice, but with no difference in accuracy. A vigilance decrement was observed in both strains, which was more pronounced in DBA/2J mice and unaffected by response bias. Finally, we observed increased RTs with increased attentional load, such that 1CRT task<5CSR task<5C-CPT, consistent with human performance in simple RT, choice RT, and CPT tasks. Thus we have demonstrated construct validity for the 5C-CPT as a measure of vigilance that is analogous to human CPT studies

Physiological Correlates of Volunteering

We review research on physiological correlates of volunteering, a neglected but promising research field. Some of these correlates seem to be causal factors influencing volunteering. Volunteers tend to have better physical health, both self-reported and expert-assessed, better mental health, and perform better on cognitive tasks. Research thus far has rarely examined neurological, neurochemical, hormonal, and genetic correlates of volunteering to any significant extent, especially controlling for other factors as potential confounds. Evolutionary theory and behavioral genetic research suggest the importance of such physiological factors in humans. Basically, many aspects of social relationships and social activities have effects on health (e.g., Newman and Roberts 2013; Uchino 2004), as the widely used biopsychosocial (BPS) model suggests (Institute of Medicine 2001). Studies of formal volunteering (FV), charitable giving, and altruistic behavior suggest that physiological characteristics are related to volunteering, including specific genes (such as oxytocin receptor [OXTR] genes, Arginine vasopressin receptor [AVPR] genes, dopamine D4 receptor [DRD4] genes, and 5-HTTLPR). We recommend that future research on physiological factors be extended to non-Western populations, focusing specifically on volunteering, and differentiating between different forms and types of volunteering and civic participation

The science of scale for violence prevention: a new agenda for family strengthening in low- and middle-income countries

Ending all violence against children by 2030 is a core part of Sustainable Development Goals 5 and 16. A number of promising violence reduction strategies have been identified in research studies. However, we lack an understanding of the implementation and impact of these programs in respect to their delivery at a large scale or within existing service systems, particularly in low- and middle-income countries (LMICs). We advocate for greater collaboration between researchers, policymakers, donors, governments, non-governmental organizations, and program managers and staff to study how violence prevention programs operate on a large scale. We describe a new initiative aiming to foster such collaborations in the field of family strengthening programs

Profile of cortisol, glycaemia, and blood parameters of American Bullfrog tadpoles Lithobates catesbeianus exposed to density and hypoxia stressors

The aim of this study was to evaluate alterations to the physiological profile (cortisol, glycaemia, and blood parameters) of Lithobates catesbeianus caused by the stressors density and hypoxia. The organisms were in the prometamorphosis stage and exposed to different tadpole densities: 1 tadpole/L (T1), 5 tadpoles/L (T2), and 10 tadpoles/L (T3) for 12 days. The blood was collected through the rupture of the caudal blood vessel and collected under normoxia (immediate collection) and hypoxia (after 15 minutes of air exposure) conditions. Cortisol levels rose on the fourth and eighth days of treatment and returned to basal levels by the end of the experiment. The stressor mechanisms tested did not affect glycaemia. White blood cells (total number of lymphocytes, neutrophils, and eosinophils) showed a significant difference at the twelfth day of the experiment when compared with the start of the experiment. We concluded that, under controlled conditions, a density of up to 10 tadpoles/L and air exposure for 15 minutes did not cause harmful physiological alterations during the experimental period. The answer to these stressors maybe was in another hormonal level (corticosterone)

Neuropsychosocial profiles of current and future adolescent alcohol misusers

A comprehensive account of the causes of alcohol misuse must accommodate individual differences in biology, psychology and environment, and must disentangle cause and effect. Animal models1 can demonstrate the effects of neurotoxic substances; however, they provide limited insight into the psycho-social and higher cognitive factors involved in the initiation of substance use and progression to misuse. One can search for pre-existing risk factors by testing for endophenotypic biomarkers2 in non-using relatives; however, these relatives may have personality or neural resilience factors that protect them from developing dependence3. A longitudinal study has potential to identify predictors of adolescent substance misuse, particularly if it can incorporate a wide range of potential causal factors, both proximal and distal, and their influence on numerous social, psychological and biological mechanisms4. Here we apply machine learning to a wide range of data from a large sample of adolescents (n = 692) to generate models of current and future adolescent alcohol misuse that incorporate brain structure and function, individual personality and cognitive differences, environmental factors (including gestational cigarette and alcohol exposure), life experiences, and candidate genes. These models were accurate and generalized to novel data, and point to life experiences, neurobiological differences and personality as important antecedents of binge drinking. By identifying the vulnerability factors underlying individual differences in alcohol misuse, these models shed light on the aetiology of alcohol misuse and suggest targets for prevention

Terrain classification of LADAR data over Haitian urban environments using a lower envelope follower and adaptive gradient operator

In response to the 2010 Haiti earthquake, the ALIRT ladar system was tasked with collecting surveys to support disaster relief efforts. Standard methodologies to classify the ladar data as ground, vegetation, or man-made features failed to produce an accurate representation of the underlying terrain surface. The majority of these methods rely primarily on gradient- based operations that often perform well for areas with low topographic relief, but often fail in areas of high topographic relief or dense urban environments. An alternative approach based on a adaptive lower envelope follower (ALEF) with an adaptive gradient operation for accommodating local slope and roughness was investigated for recovering the ground surface from the ladar data. This technique was successful for classifying terrain in the urban and rural areas of Haiti over which the ALIRT data had been acquired