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Since the inception of the transcranial magnetic stimulation (TMS) technique, it has become imperative to numerically compute the distribution of the electric field induced in the brain. Various models of the coil-brain system have been proposed for this purpose. These models yield a set of formulations and boundary conditions that can be employed to calculate the induced electric field. However, the literature on TMS simulation presents several of these formulations, leading to potential confusion regarding the interpretation and contribution of each source of electric field. The present study undertakes an extensive compilation of widely utilized formulations, boundary value problems and numerical solutions employed in TMS fields simulations, analyzing the advantages and disadvantages associated with each used formulation and numerical method. Additionally, it explores the implementation strategies employed for their numerical computation. Furthermore, this work provides numerical expressions that can be utilized for the numerical computation of TMS fields using the finite difference and finite element methods. Notably, some of these expressions are deduced within the present study. Finally, an overview of some of the most significant results obtained from numerical computation of TMS fields is presented. The aim of this work is to serve as a guide for future research endeavors concerning the numerical simulation of TMS.
RESUMO
STUDY QUESTION: Is it possible to determine the receptivity status of an endometrium by combined quantitative reverse transcription PCR (RT-qPCR) expression analysis of genes involved in endometrial proliferation and immunity? SUMMARY ANSWER: The new ER Map®/ER Grade® test can predict endometrial receptivity status by RT-qPCR using a new panel of genes involved in endometrial proliferation and the maternal immune response associated to embryonic implantation. WHAT IS KNOWN ALREADY: The human endometrium reaches a receptive status adequate for embryonic implantation around Days 19-21 of the menstrual cycle. During this period, known as the window of implantation (WOI), the endometrium shows a specific gene expression profile suitable for endometrial function evaluation. The number of molecular diagnostic tools currently available to characterize this process is very limited. In this study, a new system for human endometrial receptivity evaluation was optimized and presented for the first time. STUDY DESIGN, SIZE, DURATION: ER Map®/ER Grade® validation was achieved on 312 endometrial samples including fertile women and patients undergoing fertility treatment between July 2014 and March 2016. Expression analyses of 184 genes involved in endometrial receptivity and immune response were performed. Samples were additionally tested with an independent endometrial receptivity test. PARTICIPANTS/MATERIALS, SETTING, METHODS: A total of 96 fertile women and 120 assisted reproduction treatment (ART) patients participated in the study. Endometrial biopsy samples were obtained at LH + 2 and LH + 7 days in fertile subjects in a natural cycle and at the window of implantation (WOI) in patients in a hormone-replacement therapy (HRT) cycle. Total RNA was purified, quality-checked and reverse-transcribed. Gene expression was quantified by high-throughput RT-qPCR and statistically analyzed. Informative genes were selected and used to classify samples into four different groups of endometrial receptivity status. MAIN RESULTS AND THE ROLE OF CHANCE: Significantly different gene expression levels were found in 85 out of 184 selected genes when comparing LH + 2 and LH + 7 samples (paired t-test, P < 0.05). Gene ontology analyses revealed that cell division and proliferation, cell signaling and response, extracellular organization and communication, immunological activity, vascular proliferation, blood pressure regulation and embryo implantation are the most over-represented biological terms in this group of genes. Principal component analysis and discriminant functional analysis showed that 40 of the differentially expressed genes allowed accurate classification of samples according to endometrial status (proliferative, pre-receptive, receptive and post-receptive) in both fertile and infertile groups. LARGE SCALE DATA: N/A. LIMITATIONS, REASONS FOR CAUTION: To evaluate the efficacy of this new tool to improve ART outcomes, further investigations such as non-selection studies and randomized controlled trials will also be required. WIDER IMPLICATIONS OF THE FINDINGS: A new comprehensive system for human endometrial receptivity evaluation based on gene expression analysis has been developed. The identification of the optimal time for embryo transfer is essential to maximize the effectiveness of ART. This study is a new step in the field of personalized medicine in human reproduction which may help in the management of endometrial preparation for embryo transfer, increasing the chances of pregnancy for many couples. STUDY FUNDING/COMPETING INTEREST(S): The authors have no potential conflict of interest to declare. No external funding was obtained for this study.
