Fluoxetine: a case history of its discovery and preclinical development

Introduction: Depression is a multifactorial mood disorder with a high prevalence worldwide. Until now, treatments for depression have focused on the inhibition of monoaminergic reuptake sites, which augment the bioavailability of monoamines in the CNS. Advances in drug discovery have widened the therapeutic options with the synthesis of so-called selective serotonin reuptake inhibitors (SSRIs), such as fluoxetine. Areas covered: The aim of this case history is to describe and discuss the pharmacokinetic and pharmacodynamic profiles of fluoxetine, including its acute effects and the adaptive changes induced after long-term treatment. Furthermore, the authors review the effect of fluoxetine on neuroplasticity and adult neurogenesis. In addition, the article summarises the preclinical behavioural data available on fluoxetine’s effects on depressive-like behaviour, anxiety and cognition as well as its effects on other diseases. Finally, the article describes the seminal studies validating the antidepressant effects of fluoxetine. Expert opinion: Fluoxetine is the first selective SSRI that has a recognised clinical efficacy and safety profile. Since its discovery, other molecules that mimic its mechanism of action have been developed, commencing a new age in the treatment of depression. Fluoxetine has also demonstrated utility in the treatment of other disorders for which its prescription has now been approved

Capacity building for dementia care in community care services: a mixed methods approach

Background The prevalence of dementia is surging that results in huge service demand in the community care services. Dementia care competence of staff working in these settings is fundamental of the care quality. This project aims to examine the effects of staff training on their competence for the anticipated challenges in dementia care and explore how the training influence their care practices. Methods This study adopted a mixed methods triangulation design, including a prospective multi-center study with pre-test post-test evaluations and a narrative analysis of the participants’ reflective essays. Seventeen experienced health and social care professionals were trained as trainers at the Dementia Services Development Centre of the University of Stirling, UK. The trainers provided local facilitator training to staff members by using training materials that were culturally adapted to the local context. The facilitators were required to deliver 12 two-hour in-service training sessions for 6 months to their colleagues in a small group format in their respective workplace. Eventually a total of 1347 staff members from community care centers, day care centers, outreach teams and care homes of 70 non-government organizations in Hong Kong participated in the study between April 2017 and December 2018. Validated instruments were used to measure knowledge, attitude, sense of competence in dementia care and job satisfaction at the baseline and at 12-month follow-up. All participants were required to write a reflective essay to describe their experiences in dementia care by the end of the training. Results A total of 1264 participants, including 195 facilitators and 1069 learners, completed all assessment were included for analysis. Significant improvements were observed in all outcomes at the 12-month follow-up assessment (Ps ≤ .001). The magnitude of improvements in attitudes was the largest. The findings also showed that the effects of the training program significantly varied across different groups of learners in terms of age, occupation, work and training experience. Conclusions This community-wide large-scale project provided evidence that the train-the-trainer model and reflective learning are effective means to facilitate situated learning that promote awareness and understanding of dementia, and consequently enhance sustainability of changes in care practices

Weakly non-ergodic Statistical Physics

We find a general formula for the distribution of time averaged observables for weakly non-ergodic systems. Such type of ergodicity breaking is known to describe certain systems which exhibit anomalous fluctuations, e.g. blinking quantum dots and the sub-diffusive continuous time random walk model. When the fluctuations become normal we recover usual ergodic statistical mechanics. Examples of a particle undergoing fractional dynamics in a binding force field are worked out in detail. We briefly discuss possible physical applications in single particle experiments

Single particle tracking in systems showing anomalous diffusion: the role of weak ergodicity breaking

Anomalous diffusion has been widely observed by single particle tracking microscopy in complex systems such as biological cells. The resulting time series are usually evaluated in terms of time averages. Often anomalous diffusion is connected with non-ergodic behaviour. In such cases the time averages remain random variables and hence irreproducible. Here we present a detailed analysis of the time averaged mean squared displacement for systems governed by anomalous diffusion, considering both unconfined and restricted (corralled) motion. We discuss the behaviour of the time averaged mean squared displacement for two prominent stochastic processes, namely, continuous time random walks and fractional Brownian motion. We also study the distribution of the time averaged mean squared displacement around its ensemble mean, and show that this distribution preserves typical process characteristic even for short time series. Recently, velocity correlation functions were suggested to distinguish between these processes. We here present analytucal expressions for the velocity correlation functions. Knowledge of the results presented here are expected to be relevant for the correct interpretation of single particle trajectory data in complex systems.Comment: 15 pages, 15 figures; References adde

A method for incorporating organ motion due to breathing into 3D dose calculations

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134856/1/mp8577.pd

Repeatability of IVIM biomarkers from diffusion-weighted MRI in head and neck:Bayesian probability versus neural network

Purpose: The intravoxel incoherent motion (IVIM) model for DWI might provide useful biomarkers for disease management in head and neck cancer. This study compared the repeatability of three IVIM fitting methods to the conventional nonlinear least-squares regression: Bayesian probability estimation, a recently introduced neural network approach, IVIM-NET, and a version of the neural network modified to increase consistency, IVIM-NETmod. Methods: Ten healthy volunteers underwent two imaging sessions of the neck, two weeks apart, with two DWI acquisitions per session. Model parameters (ADC, diffusion coefficient (Formula presented.), perfusion fraction (Formula presented.), and pseudo-diffusion coefficient (Formula presented.)) from each fit method were determined in the tonsils and in the pterygoid muscles. Within-subject coefficients of variation (wCV) were calculated to assess repeatability. Training of the neural network was repeated 100 times with random initialization to investigate consistency, quantified by the coefficient of variance. Results: The Bayesian and neural network approaches outperformed nonlinear regression in terms of wCV. Intersession wCV of (Formula presented.) in the tonsils was 23.4% for nonlinear regression, 9.7% for Bayesian estimation, 9.4% for IVIM-NET, and 11.2% for IVIM-NETmod. However, results from repeated training of the neural network on the same data set showed differences in parameter estimates: The coefficient of variances over the 100 repetitions for IVIM-NET were 15% for both (Formula presented.) and (Formula presented.), and 94% for (Formula presented.); for IVIM-NETmod, these values improved to 5%, 9%, and 62%, respectively. Conclusion: Repeatabilities from the Bayesian and neural network approaches are superior to that of nonlinear regression for estimating IVIM parameters in the head and neck

MAXI J1659-152: The shortest orbital period black-hole transient in outburst

MAXI J1659-152 is a bright X-ray transient black-hole candidate binary system discovered in September 2010. We report here on MAXI, RXTE, Swift, and XMM-Newton observations during its 2010/2011 outburst. We find that during the first one and a half week of the outburst the X-ray light curves display drops in intensity at regular intervals, which we interpret as absorption dips. About three weeks into the outbursts, again drops in intensity are seen. These dips have, however, a spectral behaviour opposite to that of the absorption dips, and are related to fast spectral state changes (hence referred to as transition dips). The absorption dips recur with a period of 2.414+/-0.005 hrs, which we interpret as the orbital period of the system. This implies that MAXI J1659-152 is the shortest period black-hole candidate binary known to date. The inclination of the accretion disk with respect to the line of sight is estimated to be 65-80 degrees. We propose the companion to the black-hole candidate to be close to an M5 dwarf star, with a mass and radius of about 0.15-0.25 M_sun and 0.2-0.25 R_sun, respectively. We derive that the companion had an initial mass of about 1.5 M_sun, which evolved to its current mass in about 5-6 billion years. The system is rather compact (orbital separation of larger than ~1.33 R_sun), and is located at a distance of 8.6+/-3.7 kpc, with a height above the Galactic plane of 2.4+/-1.0 kpc. The characteristics of short orbital period and high Galactic scale height are shared with two other transient black-hole candidate X-ray binaries, i.e., XTE J1118+480 and Swift J1735.5-0127. We suggest that all three are kicked out of the Galactic plane into the halo, rather than being formed in a globular cluster.Comment: 20 pages, 14 figures, accepted for publication in A&

Towards integrative neuromonitoring of the surgical newborn: A systematic review

BACKGROUND: The altered neurodevelopment of children operated on during the neonatal period might be due to peri-operative changes in the homeostasis of brain perfusion. Monitoring of vital signs is a standard of care, but it does not usually include monitoring of the br