23 research outputs found

    Lurasidone for the treatment of bipolar depression: an evidence-based review

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    Rachel Franklin,1 Sam Zorowitz,1 Andrew K Corse,1 Alik S Widge,2 Thilo Deckersbach1 1Division of Neurotherapeutics, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Charlestown, 2Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA Abstract: Bipolar disorder (BD) is a debilitating and difficult-to-treat psychiatric disease that presents a serious burden to patients’ lives as well as health care systems around the world. The essential diagnostic criterion for BD is episodes of mania or hypomania; however, the patients report that the majority of their time is spent in a depressive phase. Current treatment options for this component of BD have yet to achieve satisfactory remission rates. Lurasidone is a drug in the benzisothiazole class approved by the US Food and Drug Administration in June 2013 for the acute treatment of bipolar depression. Its pharmacological profile features high-affinity antagonism at D2, 5-HT2A, and 5-HT7 receptors; moderate-affinity antagonism at α2C-adrenergic receptors; low- to very low-affinity antagonism at α1A-adrenergic, α2A-adrenergic, H1, M1, and 5-HT2C receptors; and high-affinity partial agonism at 5-HT1A. Preliminary findings from two recent double-blinded clinical trials suggest that lurasidone is efficacious in treating bipolar I depression, with clinical effects manifesting as early as the first 2–3 weeks of treatment (as measured by the Montgomery–Åsberg Depression Rating Scale and Clinical Global Impressions Scale for use in bipolar illness). Its therapeutic benefit appears to be comparable to the current US Food and Drug Administration-indicated treatments: quetiapine and olanzapine–fluoxetine, according to a measure of effect size known as number needed to treat. These studies reported relatively limited extrapyramidal and metabolic side effects as a result of treatment with lurasidone, with the most common side effect being nausea. Safety data drawn from these studies, as well as a more extensive body of schizophrenia research, indicate that in comparison with other atypical antipsychotics, treatment with lurasidone is less likely to result in metabolic side effects such as weight gain or disturbances of serum glucose or lipid levels. Lurasidone holds clinical potential as a novel, efficacious pharmacological treatment for bipolar depression. However, current data on its use for the treatment of BD are limited, and more extensive research, both longer in duration as well as independently conducted, is needed. Keywords: lurasidone, bipolar depression, bipolar disorder, atypical antipsychoti

    Physiologically informed neuromodulation

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    The rapid evolution of neuromodulation techniques includes an increasing amount of research into stimulation paradigms that are guided by patients' neurophysiology, to increase efficacy and responder rates. Treatment personalisation and target engagement have shown to be effective in fields such as Parkinson's disease, and closed-loop paradigms have been successfully implemented in cardiac defibrillators. Promising avenues are being explored for physiologically informed neuromodulation in psychiatry. Matching the stimulation frequency to individual brain rhythms has shown some promise in transcranial magnetic stimulation (TMS). Matching the phase of those rhythms may further enhance neuroplasticity, for instance when combining TMS with electroencephalographic (EEG) recordings. Resting-state EEG and event-related potentials may be useful to demonstrate connectivity between stimulation sites and connected areas. These techniques are available today to the psychiatrist to diagnose underlying sleep disorders, epilepsy, or lesions as contributing factors to the cause of depression. These technologies may also be useful in assessing the patient's brain network status prior to deciding on treatment options. Ongoing research using invasive recordings may allow for future identification of mood biomarkers and network structure. A core limitation is that biomarker research may currently be limited by the internal heterogeneity of psychiatric disorders according to the current DSM-based classifications. New approaches are being developed and may soon be validated. Finally, care must be taken when incorporating closed-loop capabilities into neuromodulation systems, by ensuring the safe operation of the system and understanding the physiological dynamics. Neurophysiological tools are rapidly evolving and will likely define the next generation of neuromodulation therapies

    Separating neuroethics from neurohype

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    Neutralizing antibody levels are highly predictive of immune protection from symptomatic SARS-CoV-2 infection

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    Predictive models of immune protection from COVID-19 are urgently needed to identify correlates of protection to assist in the future deployment of vaccines. To address this, we analyzed the relationship between in vitro neutralization levels and the observed protection from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection using data from seven current vaccines and from convalescent cohorts. We estimated the neutralization level for 50% protection against detectable SARS-CoV-2 infection to be 20.2% of the mean convalescent level (95% confidence interval (CI) = 14.4-28.4%). The estimated neutralization level required for 50% protection from severe infection was significantly lower (3% of the mean convalescent level; 95% CI = 0.7-13%, P = 0.0004). Modeling of the decay of the neutralization titer over the first 250 d after immunization predicts that a significant loss in protection from SARS-CoV-2 infection will occur, although protection from severe disease should be largely retained. Neutralization titers against some SARS-CoV-2 variants of concern are reduced compared with the vaccine strain, and our model predicts the relationship between neutralization and efficacy against viral variants. Here, we show that neutralization level is highly predictive of immune protection, and provide an evidence-based model of SARS-CoV-2 immune protection that will assist in developing vaccine strategies to control the future trajectory of the pandemic
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