Serotonin reuptake inhibitor-cognitive behavioural therapy-second generation antipsychotic combination for severe treatment-resistant obsessive-compulsive disorder. A prospective observational study

Tundo, Antonio; Salvati, Loretta; Cieri, Luca; Balestrini, Viviana; Spigno, Daniela Di; Orazi, Floriana; Iommi, Marica; Necci, Roberta

doi:10.1080/13651501.2022.2054351

Cited by 1 publication

(1 citation statement)

References 23 publications

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“…Dysregulation of the serotonin system is thought to be important in the pathology of psychiatric disorders such as major depressive disorder (MDD) [3] , [4] , [5] , [6] . Selective serotonin reuptake inhibitors (SSRIs) block serotonin reuptake, ostensibly increasing the extracellular levels of serotonin within the CNS and are used extensively clinically for MDD, obsessive–compulsive disorder (OCD) [7] , [8] , anxiety disorders [9] , post-traumatic stress disorder (PTSD) [10] , and borderline personality disorder (BPD) [11] . Furthermore, SSRIs have been used to treat alcohol use disorder (AUD) [12] , nicotine and other substance use disorders [9] , [13] .…”

Section: Introductionmentioning

confidence: 99%

SmartFSCV: An Artificial Intelligence Enabled Miniaturised FSCV Device Targeting Serotonin

Corva,

Doeven,

Parke

et al. 2024

IEEE Open J. Eng. Med. Biol.

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Goal: Dynamically monitoring serotonin in real-time within target brain regions would significantly improve the diagnostic and therapeutic approaches to a variety of neurological and psychiatric disorders. Current systems for measuring serotonin lack immediacy and portability and are bulky and expensive. Methods: We present a new miniaturised device, named SmartFSCV, designed to monitor dynamic changes of serotonin using fast-scan cyclic voltammetry (FSCV). This device outputs a precision voltage potential between −3 to +3 V, and measures current between −1.5 to +1.5 μA with nano-ampere accuracy. The device can output modifiable arbitrary waveforms for various measurements and uses an N-shaped waveform at a scan-rate of 1000 V/s for sensing serotonin. Results: Four experiments were conducted to validate SmartFSCV: static bench test, dynamic serotonin test and two artificial intelligence (AI) algorithm tests. Conclusions: These tests confirmed the ability of SmartFSCV to accurately sense and make informed decisions about the presence of serotonin using AI.

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