4 research outputs found
Probabilistic topic models for sequence data
No full textProbabilistic topic models are widely used in different contexts to uncover the hidden structure in large text corpora. One of the main (and perhaps strong) assumption of these models is that generative process follows a bag-of-words assumption, i.e. each token is independent from the previous one. We extend the popular Latent Dirichlet Allocation model by exploiting three different conditional Markovian assumptions: (i) the token generation depends on the current topic and on the previous token; (ii) the topic associated with each observation depends on topic associated with the previous one; (iii) the token generation depends on the current and previous topic. For each of these modeling assumptions we present a Gibbs Sampling procedure for parameter estimation. Experimental evaluation over real-word data shows the performance advantages, in terms of recall and precision, of the sequence-modeling approaches. © 2013 The Author(s)
Cannabinoids for the control of experimental multiple sclerosis
No full textPhDThere have been numerous studies reporting that cannabinoids, both exogenous
and endogenous, have a potential beneficial function during incidences of
neurological damage. Using gene knockout mice and cannabinoid-selective agents,
this study demonstrates the diverse actions of cannabinoids with a particular focus
on experimental autoimmune encephalomyelitis, an animal model of multiple
sclerosis. The results presented here report on the action of stimulators of
cannabinoid receptors in the nervous system (CNS) on; immune function, as a
mechanism of suppressing autoimmune attack of the central nervous system, as
agents to suppress neurodegenerative events leading to disease progression and as
agents that can control signs of disease that occur as the consequences of
autoimmune neurodegeneration such as spasticity. Tetrahydrocannabinol the
psychoactive component in cannabis and the CB1 cannabinoid receptor appears to
be central to many of the therapeutic actions of cannabis but also to the side-effect
potential of cannabinoid drugs. This study reports on methods to avoid
psychoactive side-effects of conventional brain-penetrant CB1 receptor agonists
whilst exploiting the therapeutic potential of the cannabinoid system in order to
control spasticity. This was achieved by targeting mechanisms of endocannabinoid
degradation, particularly using fatty acid amide hydrolase inhibitors. Furthermore,
this study also reports the development of novel cannabinoid compounds that are
excluded from the brain and inhibit spasticity and also demonstrates the
mechanism of exclusion of CNS-excluded cannabinoid CB1 receptor agonists. This
study provides further evidence for the efficacy of cannabinoid compounds during
an ongoing CNS disease and also their efficacy for treating the consequences of
CNS autoimmune disease, which hopefully, will give additional impetus for further
clinical investigations of cannabinoid agents in not only multiple sclerosis but also
other neurodegenerative diseases of the CNS
Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries
No full textBackground: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures. Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge. Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to sideeffects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (β coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and lowand middle-income countries, patient-reported outcomes did not. Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely
