[Premenstrual dysphoric disorder (PMDD): Drug and psychotherapeutique management, a literature review]. / Trouble dysphorique prémenstruel : prises en charge médicamenteuses et psychothérapeutiques, une revue de littérature.

INTRODUCTION: Premenstrual Dysphoric Disorder (PMDD) was first recognised in July 2013 in the DSM-5 after a long journey to identify its existence. It was not until 1983 that the US National Institute of Mental Health determined research criteria for the study of PMS. In 1994, the term "premenstrual dysphoric disorder" (PMDD) replaced this term in the 4th edition of the Diagnostic System Manual (DSM). It was listed in the section "Mood Disorder Not Otherwise Specified" and remained under consideration until the DSM-5, in which it appeared in the depressive disorders section. The legitimisation of the psychiatric diagnosis as well as the determination of clear symptomatology criteria in 2013 opened up possibilities for management, development of clinical, pathophysiological, therapeutic and psychotherapeutic studies. This disabling disorder can affect personal, social, family and professional life. In 2019, the ICD-11 in turn introduced the diagnosis of premenstrual dysphoric disorder, which solidifies the recognition of the disorder. OBJECTIVE: (I) to review the existing treatments, both medicinal and psychotherapeutic, and (II) to review their effectiveness. At the end of this work we will formulate recommendations for the management of these patients. METHODOLOGY: A bibliographic search was carried out from 7 June 2021 to 7 July2021 on the databases (bases de données) Psychinfo APA, Scopus, PubMed, as well as the bases de données of the Cochrane organisation and the recommendation documents of the Haute Autorité de la santé. After an initial selection based on keywords, the full text of all articles were read to arrive at the final selection of 32 articles. RESULTS: Antidepressants and Cognitive Behavioural Therapies (CBT) appear to be the most commonly recommended treatments for PMDD. Other research shows the effectiveness of oral contraceptives including drospirenone. Selective serotonin reuptake inhibitors (SSRIs) were identified as an effective treatment for PMDD. These data are consistent with the current etiological hypothesis of PMDD which has a negative impact of natural hormonal fluctuations on certain neurotransmitters. CBT showed positive results in reducing the functional impact of PMDD. DISCUSSION: Selective serotonin reuptake inhibitor (SSRI) antidepressants were reported to be first-line treatments for PMDD (sertraline 50-150 mg/d, fluoxetine 10-20 mg/d, escitalopram 10-20 mg/d, paroxetine 12.5-25 mg/d). Drospirenone (EE 3 mg and EE 20 mg/d 24 days of hormonal pills, 4 days inactive) appears to have been a first or second line treatment depending on the articles. Current results clearly point to the effectiveness of CBT in helping to reduce: functional impairment, depressed mood, feelings of hopelessness, anxiety, mood swings, sensitivity, irritability, insomnia, conflict with others, impact of premenstrual symptoms on daily life, intensity of symptoms experienced, and symptom handicap. CBTs could also become a first-line treatment if there were to be more evidence of their effectiveness. In the future, it would seem useful to offer a psychotherapeutic treatment that can be reproduced and to multiply research with a high level of scientific comparability in order to clarify the place of CBT in the management of PMDD. Research on the etiopathology of the disorder and the optimal drug regimen is still ongoing. There is a need to develop appropriate psychotherapeutic techniques to support and accompany these patients. CONCLUSION: In order to better evaluate treatments for PMDD, there is a need to homogenise studies on the subject at several levels: design, treatment doses, psychotherapeutic techniques, and evaluation measures. At present, some studies include both premenstrual syndrome (PMS) and PMDD patients. PMS and PMDD do not include the same symptoms, nor the same severity and potentially the same aetiology in the patients studied. In order to propose rigorous research that evaluates the effectiveness of treatments for PMDD and to properly support people with both these disorders, it seems essential to distinguish the two conditions. The role of the health practitioner is to be able to identify PMDD by differentiating it from other clinically related disorders. The patient must then be accompanied to make a choice of treatment adapted to her symptoms, their severity, her history, her plans for procreation, contraindications and her preferences. In 2021, the French National Authority for Health did not offer any guidelines or recommendations for the management of premenstrual dysphoric disorder. There is a need to develop research in France.

Review of Neural Network Modeling of Shape Memory Alloys.

Shape memory materials are smart materials that stand out because of several remarkable properties, including their shape memory effect. Shape memory alloys (SMAs) are largely used members of this family and have been innovatively employed in various fields, such as sensors, actuators, robotics, aerospace, civil engineering, and medicine. Many conventional, unconventional, experimental, and numerical methods have been used to study the properties of SMAs, their models, and their different applications. These materials exhibit nonlinear behavior. This fact complicates the use of traditional methods, such as the finite element method, and increases the computing time necessary to adequately model their different possible shapes and usages. Therefore, a promising solution is to develop new methodological approaches based on artificial intelligence (AI) that aims at efficient computation time and accurate results. AI has recently demonstrated some success in efficiently modeling SMA features with machine- and deep-learning methods. Notably, artificial neural networks (ANNs), a subsection of deep learning, have been applied to characterize SMAs. The present review highlights the importance of AI in SMA modeling and introduces the deep connection between ANNs and SMAs in the medical, robotic, engineering, and automation fields. After summarizing the general characteristics of ANNs and SMAs, we analyze various ANN types used for modeling the properties of SMAs according to their shapes, e.g., a wire as an actuator, a wire with a spring bias, wire systems, magnetic and porous materials, bars and rings, and reinforced concrete beams. The description focuses on the techniques used for NN architectures and learning.

Large-Area and Low-Cost Force/Tactile Capacitive Sensor for Soft Robotic Applications.

This paper presents a novel design and development of a low-cost and multi-touch sensor based on capacitive variations. This new sensor is very flexible and easy to fabricate, making it an appropriate choice for soft robot applications. Materials (conductive ink, silicone, and control boards) used in this sensor are inexpensive and easily found in the market. The proposed sensor is made of a wafer of different layers, silicone layers with electrically conductive ink, and a pressure-sensitive conductive paper sheet. Previous approaches like e-skin can measure the contact point or pressure of conductive objects like the human body or finger, while the proposed design enables the sensor to detect the object's contact point and the applied force without considering the material conductivity of the object. The sensor can detect five multi-touch points at the same time. A neural network architecture is used to calibrate the applied force with acceptable accuracy in the presence of noise, variation in gains, and non-linearity. The force measured in real time by a commercial precise force sensor (ATI) is mapped with the produced voltage obtained by changing the layers' capacitance between two electrode layers. Finally, the soft robot gripper embedding the suggested tactile sensor is utilized to grasp an object with position and force feedback signals.

A Minireview on Brain Models Simulating Geometrical, Physical, and Biochemical Properties of the Human Brain.

There is a growing body of evidences that brain surrogates will be of great interest for researchers and physicians in the medical field. They are currently mainly used for education and training purposes or to verify the appropriate functionality of medical devices. Depending on the purpose, a variety of materials have been used with specific and accurate mechanical and biophysical properties, More recently they have been used to assess the biocompatibility of implantable devices, but they are still not validated to study the migration of leaching components from devices. This minireview shows the large diversity of approaches and uses of brain phantoms, which converge punctually. All these phantoms are complementary to numeric models, which benefit, reciprocally, of their respective advances. It also suggests avenues of research for the analysis of leaching components from implantable devices.

Early Deformation of Deep Brain Stimulation Electrodes Following Surgical Implantation: Intracranial, Brain, and Electrode Mechanics.

INTRODUCTION: Although deep brain stimulation is nowadays performed worldwide, the biomechanical aspects of electrode implantation received little attention, mainly as physicians focused on the medical aspects, such as the optimal indication of the surgical procedure, the positive and adverse effects, and the long-term follow-up. We aimed to describe electrode deformations and brain shift immediately after implantation, as it may highlight our comprehension of intracranial and intracerebral mechanics. MATERIALS AND METHODS: Sixty electrodes of 30 patients suffering from severe symptoms of Parkinson's disease and essential tremor were studied. They consisted of 30 non-directional electrodes and 30 directional electrodes, implanted 42 times in the subthalamus and 18 times in the ventrolateral thalamus. We computed the x (transversal), y (anteroposterior), z (depth), torsion, and curvature deformations, along the electrodes from the entrance point in the braincase. The electrodes were modelized from the immediate postoperative CT scan using automatic voxel thresholding segmentation, manual subtraction of artifacts, and automatic skeletonization. The deformation parameters were computed from the curve of electrodes using a third-order polynomial regression. We studied these deformations according to the type of electrodes, the clinical parameters, the surgical-related accuracy, the brain shift, the hemisphere and three tissue layers, the gyration layer, the white matter stem layer, and the deep brain layer (type I error set at 5%). RESULTS: We found that the implanted first hemisphere coupled to the brain shift and the stiffness of the type of electrode impacted on the electrode deformations. The deformations were also different according to the tissue layers, to the electrode type, and to the first-hemisphere-brain-shift effect. CONCLUSION: Our findings provide information on the intracranial and brain biomechanics and should help further developments on intracerebral electrode design and surgical issues.

Potential applications of medical and non-medical robots for neurosurgical applications.

The objective of the paper is to review the state-of-the-art in medical robotic systems used for different surgical applications, and to position and evaluate their concepts according to the design requirements of an innovative, robotized neurosurgical system, capable of performing tumor ablation or electrode positioning. A few other non-medical systems, which have interesting concepts, will also be discussed. The overall aim is to determine the robotic concept (structure, actuation, etc.) most applicable to specific tasks in neurosurgery. The first section of the article describes the requirements of the task and each important aspect is expressed by an evaluation criterion. Then, 59 systems are described, according to the fields of medical applications and the robotic concepts. An evaluation of the different systems is conducted, based on the five most significant criteria. However, the main characteristic assessed is the deployment capability of the system i.e. extension and retraction. The final section presents an overview of concepts transferable to neurosurgical applications. Continuum concepts, such as "elephant trunks", seem to be the most adapted solutions, utilizing pneumatic and/or spring and/or cable actuations. Pneumatics offer deployment forces and cables can control and guide the deployment. The design of a new neurosurgical device should take into account these observations as a base.