Tommaso Melis

Emmanuel Simeu

Etienne Auvray

Paul Armagnat

Analog and mixed-signal circuits simulation for product level EMMI analysis

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

The fault isolation process is fundamental in every failure analysis, to address the physical analysis (PA). This step is becoming increasingly difficult to carry out. The cause is the increasing complexity of devices and applications, which implies a longer time for the fault isolation step. In a standard failure analysis (FA), the global fault isolation step is mainly performed using emission microscopy (EMMI). In general, this procedure takes a long time. In fact, the image comparison between golden and faulty sample is always necessary and time consuming. Furthermore, in safety applications, some activation of defects are not permitted by the device. It must prevent a critical state to be activated when a fail occurs. Consequently, the light emitted will only be the result of the consequences of the defect which cannot produce light. For this reason, the simulation of the circuit can make this step easier. Some solutions have been proposed, focusing mainly on the PICA emission tool [START_REF] Mc Manus | PICA: Backside failure analysis of CMOS circuits using Picosecond Imaging Circuit Analysis[END_REF], [START_REF] Knebel | System and method for VLSI visualization[END_REF]. This tool provides the light emission spot with the timing associated. It is very powerful from the perspective of analysis, especially for digital electronics. Nevertheless, the integration of simulation in this application risks complicating the analysis considerably. In fact, for a modern mixed signal product, the emission activity is high. Inside a real FA case, the study of the timing for each spot would make the analysis longer than recommended. Moreover, each study reported above focused mainly on MOSFET structures. Omitting other types of devices does not allow complete knowledge of the circuit. Consequently, not even emission simulation will be available at product-level. Regarding the emission in static condition, an example of EMMI simulation for MOSFET was studied in [START_REF] Auvray | Use of Analog Simulation in Failure Analysis: Application to Emission Microscopy and Laser Voltage Probing Techniques[END_REF]. In this case, the simulation used the substrate current [START_REF] Boit | Fundamentals of photon emission (PEM) in siliconelectroluminescence for analysis of electronic circuit and device functionality[END_REF] for the transistor in saturation and the density of current in diode configuration. These models have some limitations for those transistors without body pin, such as DMOS and FD-SOI. In these, in fact, the substrate current is inaccessible.

This paper overcomes these problems with a new method for product-level emission simulation. We name this solution Emitting Light Simulator (ELS), handling the EMMI of each device inside the circuit. This tool uses an emission model for MOSFETs without the need to know the substrate current. In this way, it is applicable for the first time to any MOS typology, any analog IP and products. For the other components like diodes and BJT, forward current model is used to simulate the light emitted. The second section presents the model to reproduce the light emission of the devices. The attention is focused on DMOS structure with transistor characterization. The third part is dedicated to the description of the simulation tool. Starting from the basic requirements, we will present the ELS algorithm. The fourth section deals with real-life failure analysis cases, in which the fault isolation phase is done by ELS. Finally, we will draw conclusions and hint future developments.

Emitting device models

This section is dedicated to the derivation of the fundamentals to rebuild the EMMI at product level. The basic models employed to derive the emission of each device are studied. In the first part, the attention is focused on the models used for the MOSFETs, bipolar transistors and diodes. The second describes the characterization and tuning process needed to achieve a correct simulation.

Light emission models

For MOSFET devices a light emission occurs when they operates in the saturation region [START_REF] Boit | Fundamentals of photon emission (PEM) in siliconelectroluminescence for analysis of electronic circuit and device functionality[END_REF]. In these conditions the light emitted is proportional to the substrate current (body pin current). Accordingly, the emission for CMOS transistors has been derived using this current, with satisfactory results [START_REF] Stellari | CMOS circuit testing via time-resolved luminescence measurements and simulations[END_REF]. Nevertheless, this is no longer possible for devices which substrate is not accessible. It is the case for DMOS in analog electronics and FD-SOI and FinFET in digital electronics. For this reason the model presented in [START_REF] Stellari | CMOS circuit testing via time-resolved luminescence measurements and simulations[END_REF] is considered in this work. In fact, it does not directly use the substrate current, instead it expresses the number of photons (Nph) as follows:

= - * (1)
© 2020 published by Elsevier. This manuscript is made available under the CC BY NC user license https://creativecommons.org/licenses/by-nc/4.0/ Version of Record: https://www.sciencedirect.com/science/article/pii/S0026271420304546 where Id is the drain current, VDS and VDSsat are respectively: the drain-source voltage and drain-source saturation voltage.

The factor α is a scale factor, while β is dependent on the fabrication technology and the parameters of the device. The first part of equation ( 1) indicates a linear dependency of the emission on the current flowing on the channel. The rest is the probability of emission of each carrier. The gate-source voltage (VGS) is used to determine the current Id and the VDSsat. The expression used for VDSsat is reported in [START_REF] Chan | A simple method to characterize substrate current in MOSFET's[END_REF]. In the latter, the channel length of the transistor is also considered. All the parameters can be retrieved from the simulation results and netlist information, through the technology models. Concerning the scale factors, α is linear and is easily treated, while β requires particular attention, being the argument of the exponential. An eventual wrong approximation of that may cause an exponential error propagation. For this reason, we planned a characterization to extrapolate the β factor. It is described in the second part of this section, paying particular attention to the DMOS component. From our experience, we also noticed that this type of structure can emit in a particular voltage configuration, called diode configuration [START_REF] Korman | High performance power DMOSFET with integrated Schottky diode[END_REF], [START_REF] Ferreira | Power MOSFETs reverse conduction revisited[END_REF]. In this case, the emission model finds a direct proportionality between the light emitted and the density of current flowing in the channel. An example is reported in the second part of this section.

The other emitting devices inside an integrated circuit are diodes and BJTs. The diodes emit when they are both in forward and reverse bias polarisation. In reverse bias, the emission is present when they are in the avalanche region. It is a common case for the Zener diodes, which work mainly in that state. For the forward bias, the emission occurs when the applied voltage is greater than the knee voltage. In both cases, the emission is derived from the current flowing in the junction. A similar reasoning can be made for BJTs, which are composed of two junctions. In this case, the emission is qualified by the collector current [START_REF] Zanoni | Measurements of avalanche effects and light emission in advanced Si and SiGe bipolar transistors[END_REF].

Devices characterization

For the extrapolation of the β parameter (see Eq. 1), we used the Meridian IV equipment, with an InGaAs camera to perform the acquisition in near-IR range. The measurements have been done in a steady state for the emission, using equal timing exposures of 1 second. We chose this interval so that it would faithfully approximate the measurements we make during a real FA. The equipment offers the possibility to quantify the emission reporting an average of the collected photons, during the acquisition interval. Therefore, the measurement of the number of photons will be on an arbitrary scale. Although this is not the exact number of photons, it is still a relevant indication for our work. The objective is to simulate the image coming from this instrument.

A wafer with single devices in BCD technology has been used for the measurements. This is the technology that we have more frequently for our FA cases. In this wafer all the structures have been studied, paying special attentions to DMOS. In this work are reported only some measurements executed in one of the many DMOS typologies present in the wafer. The considered transistor works at 30 V in nominal conditions, with a length of 500 nm.

Sorting and classification

Emitting structures

We first characterized the electrical parameters, by acquiring the drain current in saturation region (Fig. 1), keeping constant VGS and choosing many VDS steps. We then acquired the number of photons using the same conditions. The acquisition time was 1 second, repeated five times for each value of VDS. The average of the five measurements was computed, giving the number of photons for each voltage (Fig. 1). β has been derived from the measured current, using Eq. 1 with a fixed value of α. This value was 21.3 for the considered structure and for the others DMOS it ranged from 20.0 to 25.0. The computed β was then inserted in Eq.1 to calculate the number of photons, using the results of spice simulations. Fig. 1 shows the results of the Nph computation using Eq.1. In particular it is a comparison between the real Nph, the results of the computation of that parameter using the real Id (measured on the device) and Id resulting from the simulation.

The same structure has been characterized also in the diode configuration, described in the previous section. In this case, it was applied VGS = 0 V and VDS negative, sweeping from 0V to -1 V. The results are presented in Fig. 2. The emission is significantly stronger for lower current values than when the device is operating in saturation mode. Moreover, the type of emission in diode configuration is visually recognizable (Fig. 3) if compared with the saturation one. In fact, in saturation the light emitted is localized in the drain area, while if the transistor is in diode configuration it appears diffused on its whole surface.

Product level simulation

Basic Requirements

Some data are required before starting the emission simulation. The design environment to build the whole circuit simulation or the IP level simulation are essentials. The former is less used due to its longer simulation time and complexity. It can be however employed to reproduce the golden devices, with a standard setup. The latter makes use of spice simulations, with a virtual test bench provided by design team with standard database. It reproduces exactly the electrical bench measurements of a golden device. This simulation type is faster, allowing a wider application domain (defect hypothesis validation and golden unit). Standard fault isolation techniques are used to identify the single IP to be simulated. Generally, it can be determined after the automatic test equipment (ATE) results. Scripts has been done to allow FA engineer to easily modify parameters of the simulation and fit the bench application trial. Concerning the digital circuits, this process is facilitated by the availability of the Fastkit tool [START_REF] Auvray | FASTKIT: A software tool for Easy Design Visibility and Diagnostic Enhancement for Failure Analysis[END_REF], [START_REF] Auvray | Evolution of navigation and simulation tools in failure analysis[END_REF]. It is an automated software environment to manage the product database setup. It allows to generate the test sequences for the analysis and spice simulation of the cells.

The layout, netlist and schematics of the entire circuit are desirable. In this work we use Avalon by Synopsys, a software that offers a fully aligned environment for displaying the circuit. This is suitable but not necessary, because we use it for the image creation. We can still have the full accessibility of the ELS results, without this software, but lacking the image generation.

Emitting Light Simulator tool

The ELS software is written with Tool Command Language (TCL) and it is composed by two main scripts. The inputs are the nominal simulation netlist and the parameters file listing the coefficient extrapolated through the procedure described in section 2.2.

The first script is the main part of the program. It manages the input netlist to automatically add all the probes needed to apply the emission models. This step takes advantage of the regular expressions available on each simulator. In this sense, the netlist is managed differently, depending on the simulator for which it is designed (Eldo, Customsim or Spectre). It ensures the minimum number of probes to obtain the smallest possible results database. The simulation is then run and the output database converted into a text file. This is the input of the second script that is executed at this point.

The second script applies the emission models of each instance, reading the text results and the input netlist for the geometrical parameters (length and width). The script has two different working modes in case the simulation is analog or digital. For the analog one, it considers the values of the instances at steady state. Regarding the transistors, it checks if they are in saturation, it applies the model of Eq.1 and assigns to the transistors an emission value (Nph). If they are in diode configuration, it computes the current density reporting the result inside the same parameter for Eq.1 (Nph). For diodes and BJTs collector, the value of the current is measured using current probes added in the test bench through the first script. Concerning the digital simulations, the procedure is the same but performed for each timing step. These values are stored into vectors, quantifying the emission for each instance in all the simulation timing period. Finally, the vectors elements are integrated to assign a unique emission value to each instance.

From here on, the script acts equally in both types of simulation. It reconstructs the top hierarchy for each instance. Subsequently, to each element is assigned a colour (red for transistor in diode configuration, yellow for all the others) and a transparency level. The transparency level will indicate the emission level of the instance in the image. The transparency is a value that varies from 0 (fully visible) to 100 (fully transparent). This parameter is assigned to each emitting element according to an exponential order of the emission value. The sorting is calculated only between instances of the same type and for which the same emission model has been used (e.g. transistor in diode configuration, BJTs, diodes). In the end an Avalon instance file is generated reporting all the information of each instance. The ELS image is then generated. The file is loaded in the layout, creating a visualization of the emission aligned with schematic and netlist. This software (Fig. 4) can be used to reproduce a golden sample or to analyse the consequence of a fault injected in the simulation. An interesting feature is the possibility to perform the ELS in an inner block of the single IP test bench. The aim is to reproduce the use of higher magnification of the lens in EMMI. This gives a narrower view of a part of the IP, varying the intensity of the light spots (due to less interference between spots from distant areas).

A medium analog IP size, of about 2000 devices, can be simulated in 5 minutes, transferring the results into layout immediately and automatically. An example of ELS performed comparing with a golden sample for an analog IP is showed in Fig. 5. The entire process for a standard digital cell can be faster than the analog approach, despite time step integration. This is a consequence of the digital simulation and export of the Spice net list at the cell level [START_REF] Auvray | FASTKIT: A software tool for Easy Design Visibility and Diagnostic Enhancement for Failure Analysis[END_REF]. A digital application example is reported in Fig. 6, where we chose the violet colour for the EMMI reproduction.

Real Case Study

The FA cases that will be shown in this section deal with door zone devices. They are automotive devices with several functionalities to drive car door components. They are mixed signal products, with an analog-centric design.

FA case 1

The case presented here refers to a device with a problem in a voltage output value. In particular, the ATE measured a wrong voltage generation when the output was turned OFF. The electrical bench verification confirmed this behaviour. In the OFF state, the device reported 11V instead of 0V in a golden unit. In contrast to this, the value was equal to a golden unit when the output was driven high (12 V). To make the back-side analysis possible, the package was partially removed to access the silicon die. A laser stimulation inspection was performed, using the OBIRCH technique and monitoring the failing output. With this technique, it has not been possible to observe any single spot given a location of the defect. For this reason, we started the EMMI inspection, comparing the DUT with a golden unit for both output states. As expected, we did not notice any difference in the images acquired in the ON state. This meant that in that state even the internal behavior of the circuit was correct. From the comparison in the OFF state (Fig. 7), some consequences of the fail were observed. However, they were not sufficient to conclude on the defect localization. We identified the EMMI spot of the faulty device (Fig. 7b) within the circuit layout view (see Fig. 8a). Subsequently, using the schematic, we studied the connections of the various spots through their nets. Some commonalities were observed in a transistor that was not emitting. For this reason, we considered this structure as a hypothesis for the defect. A virtual test bench was then prepared, reproducing the real measurements environment. Afterwards, the ELS was performed in nominal conditions, reproducing the golden device image (Fig 9a). This ensured the correct preparation of the simulation. Finally, we injected a failure into the spice simulation in the hypothesized transistor. We performed many simulations sweeping the resistance values from 10 Ohms to 10 kOhms. The resistance value of 100 Ohms matched perfectly the failing signature (measure of the 11V at the output during the OFF state, see Fig 8b). Therefore, the simulation validated the hypothesis, by explaining the differences observed in the device (see Table I and Fig 9b). The physical analysis started focusing on that area. After the step by step de-layering, we revealed the defect at poly-silicon level (Fig. 10) in the area located by the fault isolation step. The defect was the presence of an extra pattern of silicon at active layer (Fig. 10b) causing a short circuit between the gate and the drain of the MOSFET, like our simulation.

FA case 2

The second application case is a field return not starting. The device generates two reference voltages. One is for the digital circuit (here named V1), the other for analog circuit (V2). When one of the two references is not correct, the device enters into a safe state to avoid safety risks. The ATE measurements found this problem at only one voltage (V1). This was confirmed by the measurements made in the electrical bench. The voltage V1 was measured at 2.8V instead of 3.3V while V2 was correctly measured at 3.3 V (see Fig. 11). Since the device did not start and the internal measurements were not accessible, the probability of success of the FA was low. Looking at the failure mode, we understood that the problem came from the voltage reference circuitry. This allowed us to start the nominal simulation before the sample preparation. The circuit was prepared for backside analysis. The ELS image was then created and the emission analysis started on the failing sample. By comparing ELS image with the failing unit in the area of interest, a lot of differences were found (see Fig. 12). These were only consequences of the failing state, since the device switched to a safe one. For this reason, we performed an analysis of the nets that connected the spots in the failing device (see Fig. 13a). We found a common point in the output transistor of V1 voltage generator block (yellow square in Fig. 13a). This transistor was not emitting as expected in case of defect (light localized at the drain side). Therefore, only a leakage in one of its fingers could explain the defect in this structure. We performed a fault injection between the gate and the source of this transistor. The failing behaviour in V1 was reproduced by a resistance of 2 kOhms. The results in fact had a perfect correlation with the failure mode (V1 2.8V and V2 at the correct voltage) (see Fig. 13b). With the same simulation, we ran the ELS, which returned an image (see Fig. 14) that was matching the failing one (Fig. 12b). This allowed to confirm the hypothesis for the defect, giving the right location. The PA started focusing on this area. The layer by layer inspection has been done. Using the passive voltage contrast technique with the SEM, an abnormal contrast was observed at poly silicon level (see Fig. 15a). This was in the same transistor found during the fault isolation (Fig. 13a). At the same location at the active layer, multiple defects were observed (Fig. 15b). They were traces of a typical gate oxide breakdown, involving only one of the multiple fingers in the transistor. This defect was produced by a leakage and explained why the transistor emitted light in the correct way even if it was damaged. Using the ELS, we found the physical defect at the correct location.

Conclusions

This paper shows how the integration of the simulation of analog and mixed signal devices can support the fault isolation step. The basic elements to build an emission simulation are shown, starting from the models and tools. The simulation tool is validated in two application cases of failure analysis. In both, the benefits of this approach emerged. These cases were difficult to be solved without simulation, not ensuring any success and causing a long cycle time with a low success rate. The ELS solves these problems. In the cases presented, fault isolation is faster and more accurate, finding defects with success. Moreover, this method improves the awareness of the operator in the circuit functionalities. In fact, it permits to make and confirm hypotheses, successfully completing the fault isolation.

This approach is not limited only to analog but can be applied also to digital circuits. With the introduction of an algorithm for the integration of the results, the ELS tool has correctly produced the EMMI of digital circuits. Moreover, the model used for the transistor in saturation has been evaluated also in FinFET technology [START_REF] Stellari | Spontaneous photon emission from 32 nm and 14 nm SOI FETs[END_REF]. Future work will address this topic, with the application of ELS in more technology nodes.

Fig. 1

 1 Fig. 1 Comparison of simulation data and real acquisition for the saturated MOSFET model.

Fig. 2 Fig. 3

 23 Fig. 2 Comparison of source current and number of photons acquired for a DMOS in diode configuration.

Fig. 5

 5 Fig. 5 On the left: a real EMMI on a golden unit; on the right: the EMMI simulation, the EMMI spots are in different yellow intensities.

Fig. 4

 4 Fig. 4 Proposed flow for the simulation for product level EMMI

Fig. 7

 7 Fig. 7 EMMI image acquired during OFF state for: a) the golden sample; b) the failing unit.

Fig. 6 a

 6 Fig. 6 a) real EMMI of a golden unit overlaid into layout on scan test of Flipflop ; b) ELS results in different violet intensities; c) both ELS and EMMI overlaid in layout.

Fig. 9 a

 9 Fig. 9 a) ELS image of the golden sample; b) ELS image in consequence of the fault injection.

Fig. 11 .

 11 Fig. 11 . Electrical measurements of the failing device acquired in the bench. In blue the signal failing signal V1 at 2.8 V.

Fig. 13

 13 Fig. 13 a) Spots analysis. In orange and white the nets linking the spots of the EMMI. The yellow square indicates the failing transistor; b) Simulation results in consequence of the fault injection.

Fig. 14

 14 Fig. 14 ELS image in consequence of the fault injection inside the transistor identified in Fig.13a.

Fig. 15

 15 Fig. 15 a) Passive voltage contrast image at poly silicon layer. The red square indicates the abnormal contrast in the finger of the transistor; b) Greater magnification of the red squared area at active layer.


A Nowodzinski

O Ndjoye-Kogou

V Mourier

G Nonglaton

D Bouchu

B Fain

S Giroud

Capacitive micromachined ultrasonic transducers leak detection by dye penetrant test

Dye penetrant test has been used to detect non hermetic capacitive micromachined ultrasonic transducers (CMUTs). The method has proven its ability to highlight faulty CMUTs membranes among more than hundreds of CMUTs membranes. The fluorescence microscopy image highlights the defective CMUTs with a strong contrast and respecting the shape of the CMUTs, which makes it possible to design robust faulty CMUT automatic identification algorithms. Scanning electron microscopy has been performed in order to check the reliability the detection of the non-hermetic CMUTs. Observations confirmed the reliability of the method.

Introduction

Capacitive micromachined ultrasonic transducers (CMUT) are used in many technical fields, such as health care, where their capabilities are no longer to be demonstrated. CMUTs can be used as an ultrasonic imaging transducer [START_REF] Park | Image-guided handheld HIFU treatment system based on real-time tracking of ultrasound imaging probe and HIFU probe[END_REF] and also provide focus ultrasound (FUS) therapy [START_REF] Cline | MR-guided focused ultrasound surgery[END_REF] Moreover, it is possible to gather in a single probe a transducer for real-time imaging and a transducer dedicated to FUS to heat the region of interest. It is a cheap but efficient alternative to magnetic resonance imaging when FUS therapy is used.

A CMUT element consist mainly of an array of suspended membranes. Each membrane is suspended over a cavity. The membranes may be collectively electrostatically actuated in order to generate an ultrasonic mechanical wave propagating in the medium to be probed. CMUTs are also used as sensors in order to sense the reflected wave and thus build an image by echolocation. Medical use of CMUT requires immersion in liquid to ensure good impedance matching between the body and the transducer. But, introduction of liquid into cavity of CMUTs radically modifies their mechanical behavior. The hermiticity of the CMUTs is then an important parameter to validate this type of component. This article describes the use of the dye penetrant test to highlight non-hermetic CMUTs membrane among an array of several hundred CMUTs.

Leak tests are well documented in the standards (MIL-STD-883E method 1014.9), or in the literature [START_REF] Greenhouse | Hermeticity of electronic packages[END_REF]. Penetrant dye test is known to be useful for determining the location of leaks. This test usually involves forcing the introduction of a dye by placing the package under pressure for several hours. Once the dye is introduced through the leaks, a UV lamp is used to reveal traces of dye where leaks exist. Most fluorescents emit visible light, what may require disassembly of the component to look inside.

To test the hermiticity of an array of waferbonded CMUTs made at CEA-Leti [START_REF] Gross | Fabrication and characterization of wafer-bonded cMUT arrays dedicated to ultrasound-imageguided FUS[END_REF], a procedure has been developed to introduce the dye in the nonhermetic CMUT without using pressure, what can induce excessive stress on CMUT membranes. We show in this paper that use of vacuum for dye penetrant test is efficient to localize non-hermetic CMUTs. It is an alternative for the introduction of the dye into the CMUT, and fluorescence of rhodamine 6G is sufficient to be detected by a fluorescence microscope without the necessity of disassembling the CMUT. It eases the localization of non-hermitic CMUTs membranes among several hundreds CMUTs.

CMUTs description

The CMUT used in this study are part of a mixed imaging/FUS probe that present different geometries. On one side, the so-called low frequency matrix, later referred to as 'BF', are designed to locally heat the body. On the other side, 'HF1'and imaging purpose.

Membrane dimensions have been designed to resonate at 6 MHz (LF), 20 MHz (HF1) and 25 MHz (HF2) in air. BF, HF1 and HF2 CMUTs are respectively made of 126x44, 112x4 and 127x4 membranes. The thickness of the membrane is 800nm and is made of highly doped boron silicon. Two cavity depths could be achieved: 350 nm for the BF membrane and 150 nm for the HF membrane. On one side, an important depth for BF cavities allow the production of powerful acoustic waves. On the other side, a reduced depth for HF1/HF2 devices that have very stiff membranes while they have to be polarized with voltage close to the collapse voltage allows for reasonable collapse voltages. Here, we focus on the membrane quality and the cavity depth of the tested wafer was set to 300 nm for all cavities, which results in a pull-in voltage around 60-80V for the BF and 300V for the HF1 and HF2.

This process limits the parasitic capacitance between the membrane and the bulk electrode because membranes are based on a thick dielectric layer.

During process or during test of reliability CMUT can be damaged. Membranes are sometimes clearly degraded, but holes in membranes or delaminations are not always easy to detect. Nonhermetic membranes are considered faulty. Because each electrical pad polarizes several hundred CMUTs, it is impossible to give a reliable estimate of the rate of intact membranes by electrical measurements or to localize isolated faulty membranes.

Fig. 3 shows a typical optical microscopy image of CMUTs. CMUT membranes are deformed, but no membranes appear to be pierced. Dye penetrant test is a useful complementary technique to standard MEMS characterization tools such as laser dopler vibrometry or digital holographic microscopy. These instruments are very effective instruments for measuring the resonance of the membranes [START_REF] Shin | Acoustic Doppler velocity measurement system using capacitive micromachined ultrasound transducer array technology[END_REF], [START_REF] Sénégond | Characterization of cMUT by Dynamic Holography Microscopy[END_REF] but hardly usable to detect non hermetic membrane because resonance of membranes depend very slightly on the gas pressure within the cavity.

An other way to highlight perforated membrane would be to introduce liquid in the non-hermetic cavity in order to make a significant change in the resonance frequency of the membrane. Yet, it is difficult to ensure a complete filling of cavities below the non-hermetic membranes and a good contact between the liquid and the membrane, especially when the liquid in the CMUT cavity may evaporate.

Methods

To perform the dye penetrant test, the piece of wafer is immersed in a beaker containing several millimeters of a solution of rhodamine 6G ([989-38-8], Sigma-Aldrich) in ethyl alcohol (5g/L). The maximum of absorption of the rhodamine 6G is at 530nm. The Fig. 4 describes a cycle of primary vacuuming and atmospheric pressure performed in the device containing the beaker with the piece of wafer immersed in rhodamine 6G in order to evacuate all air bubbles from the perforated CMUTs and replace them with the rhodamine 6G solution. A series of 5 cycles can be apply. The once no more bubbles escape, the wafer piece is removed and the excess of rhodamine 6G solution on the surface is simply blown off by a stream of compressed air. The piece of wafer is then ready for observation under a fluorescence microscope. Fluorescence microscopy can be done long after the introduction of dyes into the CMUTs, even if the solution evaporates the dyes remain. The main precaution is to preserve dyes from light (photobleaching [START_REF] Zondervan | Photobleaching of Rhodamine 6G in Poly(vinyl alcohol) at the Ensemble and Single-Molecule Levels[END_REF]) and excessive heat. Fluorescence microscopic observations were made several months apart without any evidence of loss of fluorescence efficiency.

Results

Fig. 5 depicts a fluorescence microscopy image of the same field of view as the optical microscopy image of Fig. 3. The leaky membrane is clearly visible because the rhodamine 6G introduced through the leak illuminates the entire membrane, which is much larger than the leak itself..

A few bright spots can be also noticed, but they are not squared and their size are not consistent with CMUT dimensions. These bright spots are due to dye residue or organic contamination.

Fig. 5 demonstrates that the procedure of introduction of the rhodamine 6G is efficient. It also shows that the fluorescence is sufficient to be detected by the microscope despite the thickness of the membrane which hinders the UV light hence the luminescence excitation of the rhodamine 6G. To check that squared illuminations is well correlated to perforated membranes, a comparison between scanning electron microscopy (SEM) and optical or fluorescent microscopy has been performed. Each time the square illuminations correspond to pierced membranes. Similarly, all nonsquare illuminations correspond either to rhodamine or organic residues. This leak detection method has also been used to try to highlight faulty HF1/FH2 membranes. Fig. 7 illustrates an observation in visible microscopy and fluorescent microscopy. Bright spots do not match the shape of CMUTs and were attributed to residue of rhodamine 6G or organic traces, hence we conclude that no faulty CMUT membranes were detected. The shape of such artifacts being very different than the shape of non-hermetic CMUTs, it would be easy to design an algorithm for automatic recognition and counting of CMUTs membrane that are not hermetic.

Conclusion

Dye penetrant test has been used to detect nonhermetic capacitive micromachined ultrasonic transducers (CMUTs) membranes. The method has proven its ability to highlight faulty membranes among more than one hundreds membranes. The rhodamine 6G has proven its efficiency to highlight the defective membrane without disassembly of the die. The fluorescence microscopy image reveals the defective membranes with a strong contrast that respects the shape of the CMUTs membrane, avoiding any confusion with artefacts. The method has been proven to be efficient several months after the dye introduction. As a result robust faulty CMUT automatic identification algorithms may be built.

Scanning electron microscopy has been performed in order to check the reliability the detection of the non-hermetic CMUTs. Observations confirmed the reliability of the method to detect nonhermetic CMUTs cavity.

Fig. 1 Fig. 1 :

 11 Fig. 1: In plane CMUTs dimension. Electrical pads address 128x44 BF CMUTs, 112x4 HF1 CMUTs and 127x4 HF2 CMUTs.Fig.2shows the process flow of the CMUTs manufacturing. The silicon of the membrane and the base wafer are highly doped in order to have a good electrical conductivity and to avoid the use of a metallic top electrode.

Fig. 2 :

 2 Fig. 2: CMUT process flow: a) trenches etching, b) silicon oxide deposition and planarization, c) CMUT cavity formation by reactive ion etching, d) SIO2 and SiN thin film deposition, e) wafer bonding, f) Si grinding and buried oxide (BOX) etching, g) membrane parterning, h) SiN thin film deposition, contact opening, AlSi deposition.

Fig. 3 :

 3 Fig. 3: X10 optical microscopy, the field of view depicts 18x27 BF membranes. Circles can be noticed on most of membranes. These circles are due to deformation of the membranes, probably caused by residual stress in the membrane.

Fig. 4 :

 4 Fig. 4: Cycle used to introduce Rhodamine 6G in a perforated CMUT. a) wafer of CMUT is introduced in vacuum chamber containing a solution of rhodamine 6G. Gas in the perforated CMUT does not evacuate in solution b) Vacuum is made in the chamber, bubbles appear everywhere in the solution and especially above the leaky CMUT, the solution is then introduced in the perforated CMUT. The fluorescence microscopy is performed with a Zeiss Axio Imager 2 A2m reflection optical microscope (Carl Zeiss MicroImaging GmbH, Oberkochen Germany). A XBO 75 xenon arc lamp is used for fluorescence and a HAL 100 halogen lamp for bright light.Fluorescence microscopy can be done long after the introduction of dyes into the CMUTs, even if the

Fig. 5 :

 5 Fig. 5: Fluorescent microscopy at x10 magnification of the same field of view than Fig. 3. The perforated BF membrane is illuminated over its entire surface. The field of view covers 486 CMUTs and the faulty CMUT is easily identify.

Fig. 6 Fig. 6 :

 66 Fig. 6: Comparison between optical, fluorescent and scanning electron microscopy of non-perforated CMUT membranes and perforated CMUT membranes due to a non-standard process.

Fig. 7 :

 7 Fig. 7: Images of non-damaged CMUTs HF1 membranes. a) Optical microscopy, b) fluorescent microscopy, c) zoom on image of fluorescent microscopy, the bright spots are probably due to residue of rhodamine.

Acknowledgements

This work was funded by SOITEC, Agence Nationale de la Recherche (ANR-10-TECS-007) and the Fonds européen de développement régional (FEDER 3431-35438).


Michael Schumacher
email: michael.schumacher@inserm.fr

Philippe Liere

Abdelmoumen Ghoumari

Progesterone and Fetal-Neonatal Neuroprotection

Keywords: Progesterone, allopregnanolone, cerebroprotection, myelin, pregnancy, preterm birth

The role of progesterone goes beyond the maintenance of pregnancy. The hormone indeed protects the developing fetal brain and influences its maturation. Metabolomes analyzed by mass spectrometric methods have revealed the great diversity of steroids in maternal plasma and fetal fluids, but their developmental significance remains to be investigated. Progesterone and its metabolites reach highest levels during the third trimester, when the brain growth spurt occurs: its volume triples, synaptogenesis is particularly active and axons start to be myelinated. This developmental stage coincides with a period of great vulnerability. Studies in sheep have shown that progesterone and its metabolite allopregnanolone protect the vulnerable fetal brain. Work in rats and mice have demonstrated that progesterone plays an important role in myelin formation. These experimental studies are discussed in relation to preterm birth. Influences of progesterone on very early stages of neural development at the beginning of pregnancy await to be explored.

STEROID HORMONE EXPOSURE OF THE DEVELOPING HUMAN BRAIN

The prenatal brain is constantly exposed to elevated levels of progesterone and its metabolites, which progressively increase during pregnancy, reaching highest levels during the last trimester [START_REF] Schock | Hormone concentrations throughout uncomplicated pregnancies: a longitudinal study[END_REF]. In parallel, levels of the a GABAA receptor-active progesterone metabolite allopregnanolone, which plays an important role in protecting the developing brain, are also increased [START_REF] Luisi | Serum allopregnanolone levels in pregnant women: changes during pregnancy, at delivery, and in hypertensive patients[END_REF].

After 7 to 9 weeks post-conception, progesterone is mainly produced by the syncytiotrophoblasts of the placenta. As progesterone is required for the maintenance of pregnancy, it is not further surprising that the regulation of its placental synthesis differs from other steroidogenic tissues. The placenta indeed lacks short-term modulation of progesterone synthesis and does not express the intracellular cholesterol transport protein StAR [START_REF] Strauss | Providing progesterone for pregnancy: control of cholesterol flux to the side-chain cleavage system[END_REF].

However, the mitochondrial cholesterol import protein translocase (TSPO), the former peripheral benzodiazepine receptor, is present in human placenta and is involved in steroid production [START_REF] Lassance | Obesityinduced down-regulation of the mitochondrial translocator protein (TSPO) impairs placental steroid production[END_REF]. Expression of cytochrome P450scc (scc for side-chain cleavage), the mitochondrial enzyme that converts cholesterol to pregnenolone, the immediate precursor of progesterone, is constitutive [START_REF] Tuckey | Progesterone synthesis by the human placenta[END_REF][START_REF] Miller | Steroid hormone synthesis in mitochondria[END_REF]. Congruently, the placental 3β-hydroxysteroid dehydrogenase (3β-HSD), which converts pregnenolone to progesterone, is expressed throughout pregnancy [START_REF] Milewich | Initiation of human parturition. IX. Progesterone metabolism by placentas of early and late human gestation[END_REF]. For researchers using animal models, it is interesting to note that in contrast to humans, the maternal corpus luteum remains functional and produces progesterone throughout gestation in laboratory rodents. This explains why the genetic invalidation of enzymes involved in progesterone biosynthesis does not preclude the completion of pregnancy in mice.

The human fetus is not only exposed to high concentrations of progesterone and its metabolites, but also to abundant estrone, estradiol, estriol and estetrol, which also have cerebroprotective actions. The latter is exclusively synthesized by the fetal liver during human pregnancy. Levels of estetrol steadily increase during pregnancy and reach the maternal circulation via the placenta [START_REF] Bennink | Maternal and fetal estetrol levels during pregnancy[END_REF][START_REF] Visser | Clinical applications for estetrol[END_REF]. Estetrol binds with high selectivity to the intracellular estrogen receptors, preferentially to the alpha isoform, but with lower affinity than estradiol.

Interestingly, estetrol administration has been shown to increase brain allopregnanolone levels [START_REF] Pluchino | Effect of estetrol administration on brain and serum allopregnanolone in intact and ovariectomized rats[END_REF].

The other estrogens are mainly produced by the placental aromatization of androgens.

However, as the human placenta lacks the cytochrome P450 enzyme CYP17, placental estrogen synthesis is dependent on the supply of the androgen precursor dehydroepiandrosterone sulfate (DHEAS) by the adrenal fetal zone and maternal adrenal glands. The sulfate moiety is then removed from DHEAS by the placental sulfatase, and the unconjugated DHEA is converted by 3β-and 17β-hydroxysteroid dehydrogenases to androstenedione and testosterone, the respective precursors of estrone and estradiol [START_REF] Ishimoto | Development and function of the human fetal adrenal cortex: a key component in the feto-placental unit[END_REF]. The fetal zone, described for the first time in 1910, is a compartment of the fetal adrenal cortex only present in humans and higher primates, which produces large amounts of DHEAS [START_REF] Ishimoto | Development and function of the human fetal adrenal cortex: a key component in the feto-placental unit[END_REF][START_REF] Malendowicz | 100th anniversary of the discovery of the human adrenal fetal zone by Stella Starkel and Leslaw Wegrzynowski: How far have we come?[END_REF]. It becomes well differentiated by 9 to 12 weeks of gestation. As fetal zone DHEAS is used as a precursor for estrogen synthesis by the placenta, the term "feto-placental unit" has been coined [START_REF] Ishimoto | Development and function of the human fetal adrenal cortex: a key component in the feto-placental unit[END_REF].

THE CONTRIBUTION OF ANALYTICAL MASS SPECTROMETRIC METHODS

The majority of studies on pregnancy steroids are based on immunological methods. Their lack of specificity and inability to simultaneously analyze multiple steroid metabolites have always represent major limitations. Currently, gas or liquid chromatography (GC or LC) coupled to mass spectrometry (MS) or tandem mass spectrometry (MS/MS), combined with carefully validated sample preparation, have become reference methods for accurate and sensitive steroid analysis [START_REF] Stanczyk | Advantages and challenges of mass spectrometry assays for steroid hormones[END_REF][START_REF] Schumacher | Analytical challenges for measuring steroid responses to stress, neurodegeneration and injury in the central nervous system[END_REF]. Moreover, these technologies offer powerful tools for extensive steroid profiling in tissue samples. Steroid profiling by mass spectrometry has revealed the complexity and large number of steroids to which the fetus is exposed [START_REF] Hertig | Steroid profiling in preeclamptic women: evidence for aromatase deficiency[END_REF][START_REF] Hill | Steroid metabolome in fetal and maternal body fluids in human late pregnancy[END_REF].

They have also provided important informations concerning changes in placental steroids during pregnancy-related disorders such as preeclampsia [START_REF] Berkane | From pregnancy to preeclampsia: a key role for estrogens[END_REF].

Particular interesting are recently reported steroid metabolomic profiles in human fetal body fluids obtained by gas chromatography/mass spectrometry (GC/MS), as they provide insights into the functioning of the feto-placental unit [START_REF] Hill | Steroid metabolome in fetal and maternal body fluids in human late pregnancy[END_REF]. Levels of 37 unconjugated steroids and 30 steroid polar conjugates have been separately measured in blood of he umbilical artery, supplying deoxygenated blood from the fetus to the placenta, and of the umbilical vein, providing oxygenated blood from the placenta to the fetus. Samples were taken from 80 women giving birth within weeks 28 to 42 of gestation [START_REF] Paskova | Steroid metabolome in the umbilical cord: is it necessary to differentiate between arterial and venous blood ?[END_REF]. Differences or similarities in the levels of steroids between placental arterial and venous blood provided clues for their origins. Thus, progesterone is mainly of placental origin, whereas its metabolites 5αdihydroprogesterone (5α-DHP) and allopregnanolone (3α,5α-tetrahydroprogesterone, 3α,5α-THP) did not significantly differ between the umbilical artery and vein, suggesting that they may be formed in both placenta and fetus. In contrast, 20α-dihydroprogesterone (20α-DHP) and its 5α-reduced metabolites as well as isopregnanolone (3β,5α-tetrahydroprogesterone, 3β,5α-THP) and the androgens androstenedione and testosterone are mainly produced by the fetus. Similarly, pregnenolone sulfate (PREGS) and DHEAS are also mainly of fetal origin, and their levels increase towards the normal term of pregnancy, reflecting the increasing activity of the adrenal fetal zone [START_REF] Paskova | Steroid metabolome in the umbilical cord: is it necessary to differentiate between arterial and venous blood ?[END_REF].

NEUROACTIVE STEROIDS ARE SYNTHESIZED WITHIN THE BRAIN

In addition to the steroidogenic endocrine glands, progesterone is also synthesized by neurons and glial cells within the brain. To refer to their site of synthesis, steroids formed in the nervous system have been named "neurosteroids" [START_REF] Baulieu | Neurosteroids: beginning of the story[END_REF]. In addition to their de novo synthesis from cholesterol, progesterone and its metabolites can be synthesized within the nervous system from circulating precursors: progesterone can be formed from circulating pregnenolone, 5α-DHP can be derived from circulating progesterone, and allopregnanolone from circulating progesterone or 5α-DHP. A variety of enzymes are expressed in the fetal brain, in particular the aromatase that converts androgens to estrogens [START_REF] Stoffel-Wagner | Neurosteroid metabolism in the human brain[END_REF][START_REF] Pezzi | Profiling transcript levels for steroidogenic enzymes in fetal tissues[END_REF][START_REF] Arevalo | The neuroprotective actions of oestradiol and oestrogen receptors[END_REF]. This implies that the synthesis of progesterone, allopregnanolone, estradiol and other steroids with protective and trophic actions not exclusively relies on the placenta. This has to be taken into account when discussing consequences of changes in circulating hormones, as for example the case of preterm birth, when the feto-placental unit is disrupted.

NATURAL PROGESTERONE AND SYNTHETIC PROGESTINS

Progesterone designates the hormone produced within the body, qualifying as natural or bioidentical. The term progestin is used here to refer to the synthetic compounds whereas "progestogen" (or progestagen) refers to steroids that possess progestational activity. The ovaries are the main source of circulating progesterone. Its levels are low during the follicular phase of the menstrual cycle (1-3 nM) and are markedly increased during the luteal phase (20-40 nM) [START_REF] Havlikova | Serum profiles of free and conjugated neuroactive pregnanolone isomers in nonpregnant women of fertile age[END_REF]. The luteo-placental shift occurs between 7 and 9 weeks of pregnancy and progesterone levels reach highest levels (200-400 nM) by the end of gestation [START_REF] Parizek | Neuroactive pregnanolone isomers during pregnancy[END_REF].

There are two major differences between progesterone and progestins. The first concerns their metabolism. Thus, progesterone is converted to a variety of reduced metabolites, in particular to allopregnanolone, which is a potent positive modulator of GABAA receptors and plays an important role in the developing brain. In contrast, little is known concerning the metabolism of the synthetic progestins, which are most likely not converted to neuroactive metabolites in the brain [START_REF] Schumacher | Revisiting the roles of progesterone and allopregnanolone in the nervous system: resurgence of the progesterone receptors[END_REF]. This is for example the case of the 19-norprogestatif Nestorone (segesterone acetate), which is not converted to a GABAA receptor-active metabolite and exerts is neuroprotective and promyelinating effects only via intracellular progesterone receptors (PR) [START_REF] Kumar | Nestorone as a novel progestin for nonoral contraception: structure-activity relationships and brain metabolism studies[END_REF].

A second difference concerns the targets of progesterone and progestins. Natural progesterone not only acts directly on the classical intracellular PR, but on a a variety of targets, including membrane receptors, to which progestins do not necessarily bind [START_REF] Thomas | Steroid and G protein binding characteristics of the seatrout and human progestin membrane receptor alpha subtypes and their evolutionary origins[END_REF][START_REF] Guennoun | Progesterone and allopregnanolone in the central nervous system: response to injury and implication for neuroprotection[END_REF]. In contrast, synthetic progestins have been designed to target PR. However, they belong to different classes with very different pharmacological profiles and modes of action, some of them interacting with multiple steroid receptor signaling pathways [START_REF] Schumacher | Progesterone and progestins: neuroprotection and myelin repair[END_REF][START_REF] Stanczyk | Progestogens used in postmenopausal hormone therapy: differences in their pharmacological properties, intracellular actions, and clinical effects[END_REF].

EFFECTS OF NATURAL PROGESTERONE AND SYNTHETIC PROGESTINS ON THE DEVELOPING BRAIN

$ Despite of the common use of progesterone and synthetic progestins in pregnant women, little is known about their role in early brain development. Studies in rodents have shown that PR are present in numerous regions of the developing brain. Of note, PR expression is transient in brain regions such as the cerebral cortex and cerebellum, pointing to a role of the receptor in neural and cognitive development [START_REF] Quadros | Distribution of progesterone receptor immunoreactivity in the fetal and neonatal rat forebrain[END_REF][START_REF] Quadros | Distribution of progesterone receptor immunoreactivity in the midbrain and hindbrain of postnatal rats[END_REF]. Thus, PR activation promotes the differentiation of developing cerebellar Purkinje neurons [START_REF] Sakamoto | Effects of progesterone synthesized de novo in the developing Purkinje cell on its dendritic growth and synaptogenesis[END_REF].

Synthetic progestins designed to target PR are expected to exert their developmental actions via PR signaling. On the other hand, the developmental effects of natural progesterone are not solely mediated by PR, as its metabolite allopregnanolone is a positive modulator of GABAA receptors. Main effects of progesterone on neural development may indeed involve GABAA receptors, which play a crucial role in the formation of neuronal connections and the maturation of neuronal networks [START_REF] Belelli | Endogenous neurosteroids influence synaptic GABA(A) receptors during postnatal development[END_REF]. Whereas GABAA receptor activation usually inhibits neuronal excitability in the adult brain, it results in neuronal depolarization during early development as a result of relatively high intracellular Cl -concentrations [START_REF] Ben-Ari | Excitatory actions of gaba during development: the nature of the nurture[END_REF]. The depolarizing nature of the early GABAergic signals plays a pivotal role in the neurodevelopmental actions of allopregnanolone [START_REF] Grobin | Perinatal allopregnanolone influences prefrontal cortex structure, connectivity and behavior in adult rats[END_REF].

PROGESTERONE TREATMENT AT THE BEGINNING OF PREGNANCY

Many fetuses are exposed to hormonal contraceptives well into the first trimester. Moreover, progesterone and progestins are nowadays frequently prescribed during early pregnancy for luteal phase dysfunction in conjunction with ovulation stimulating drugs. Early pregnancyrelated intake of progestins has been associated with increased risk in the deviation of normal genitalia masculinization or the development of neurocognitive disorders [START_REF] Wagner | The many faces of progesterone: a role in adult and developing male brain[END_REF][START_REF] Gore | Implications of prenatal steroid perturbations for neurodevelopment, behavior, and autism[END_REF]. However, these studies show great variability regarding types of progestogens, their timing, dosing and durations, making it difficult to draw conclusions. Synthetic progestins which interfere with the signaling of multiple steroid receptors, and in particular progestins with androgenic properties, may have side-effects that do not directly relate to PR signaling.

Whether progesterone treatment during early pregnancy affects neural development remains to be investigated. At these very early stages of embryonic development, neural progenitor cells are born, proliferate, migrate and differentiate into neurons and glial cells. The formation of synaptic connections starts during the second trimester [START_REF] Schepanski | Prenatal immune and endocrine modulators of offspring's brain development and cognitive functions later in life[END_REF]. Although systematic experimental studies concerning possible effects of steroids on neural cells at very early stages of brain development are missing, their actions on embryonic neural stem cells or neural progenitor cells isolated from neurogenic regions of the adult rat brain have been reported.

Thus, sex steroids have been shown to stimulate the proliferation and to influence the differentiation of embryonic neural stem cells [START_REF] Bramble | Sex steroid hormone modulation of neural stem cells: a critical review[END_REF]. During their commitment to dopaminergic neurons, PR expression is upregulated in embryonic neural stem cells [START_REF] Díaz | Changes in the content of estrogen alpha and progesterone receptors during differentiation of mouse embryonic stem cells to dopamine neurons[END_REF]. Progesterone also promotes their differentiation into other types of neurons [START_REF] Diaz | Progesterone increases dopamine neurone number in differentiating mouse embryonic stem cells[END_REF][START_REF] López-González | Progesterone and 17β-estradiol increase differentiation of mouse embryonic stem cells to motor neurons[END_REF]. Of note, the progesterone biosynthetic pathway was found to be upregulated in a human embryonic neuronal progenitor cell line during their differentiation into post-mitotic neurons [START_REF] Pistritto | Differentiation-dependent progesterone synthesis and metabolism in NT2-N human neurons[END_REF].

Allopregnanolone upregulates intracellular calcium concentrations in rat embryonic hippocampal neurons by mechanisms involving GABAA receptors and L-type calcium channels [START_REF] Wang | Allopregnanolone-induced rise in intracellular calcium in embryonic hippocampal neurons parallels their proliferative potential[END_REF]. In mice, progesterone protect neurogenesis in the embryonic brain against inflammation-induced alterations [START_REF] Tronnes | Effects of lipopolysaccharide and progesterone exposures on embryonic cerebral cortex development in mice[END_REF]. Progesterone and a series of contraceptive progestins (Nestorone, norgestimate, norethynodrel, norethindrone, levonorgestrel) stimulated rat adult neural progenitor cell proliferation [START_REF] Liu | Clinically relevant progestins regulate neurogenic and neuroprotective responses in vitro and in vivo[END_REF]. In contrast, medroxyprogesterone acetate (MPA) had an inhibitory effect. Although experimental studies remain limited, results of the available ones, mainly conducted in vitro, strongly suggest that exposure to steroid hormones including progesterone, may influence very early stages of neural development.

VULNERABILITY OF THE FETAL BRAIN DURING THE THIRD TRIMESTER

The last trimester of gestation, when the fetus is exposed to highest levels of progesterone, corresponds to a particularly important stage of human brain development. During this brain growth spurt period, the volume of the brain triples, intense synaptogenesis takes place and axons start to be surrounded and isolated by myelin sheaths. This neurodevelopmental stage also corresponds to a period of great vulnerability. Indeed, preterm infants born before the 30 th week of pregnancy are at high risk of brain damage, commonly caused by ischemic insult or ascending intrauterine infection. Typical lesions include intraventricular hemorrhages and periventricular leukomalacia (PVL), leading to cerebral palsy and motor skill dysfunction [START_REF] Berger | Neuroprotection in preterm infants[END_REF].

Intraventricular hemorrhage is caused by fluctuations of the cerebral blood flow in the vascular bed of the germinal matrix, where the developing vascular system is prominent. In this area, blood vessels are thin-walled and particularly fragile between 24 th and 32 nd weeks of gestation. They easily break, causing periventricular hemorrhagic infarction. Moreover, vascular cells are metabolically very activity and rely on sufficient oxygenation. From the 32 nd week onwards, there is a significant development of the cerebral vasculature and the germinal matrix is no longer apparent. PVL corresponds to the principal form of brain injury in the premature infant and the predominant pathologic finding underlying cerebral palsy. It mainly involves axons and immature oligodendrocytes in proximity of the lateral cerebral ventricles, with irreversible damage to the periventricular white matter. In the preterm brain, between 23 and 32 weeks of gestation, the white matter is particularly vulnerable to ischemic-hypoxic conditions [START_REF] Alix | The pathophysiology of ischemic injury to developing white matter[END_REF][START_REF] Raybaud | The premature brain: developmental and lesional anatomy[END_REF].

During this developmental period, the subcortical white matter is predominantly populated by immature premyelinating oligodendrocytes, which are much more vulnerable than mature oligodendrocytes [START_REF] Billiards | Myelin abnormalities without oligodendrocyte loss in periventricular leukomalacia[END_REF]. Injury results in an arrest of pre-oligodendrocyte maturation, leading to myelination failure, chronic white matter damage and persistent neurological problems [START_REF] Back | Selective vulnerability of late oligodendrocyte progenitors to hypoxia-ischemia[END_REF].

The permanent damage to the developing periventricular white matter might seem surprising and raises interesting fundamental questions, as myelin normally has the capacity to regenerate via a process involving the proliferation and maturation of oligodendrocyte progenitor cells (OPC), which are largely distributed throughout the brain, even in adults [START_REF] Crawford | Oligodendrocyte progenitors: adult stem cells of the central nervous system?[END_REF].

The great vulnerability immature oligodendrocytes and growing axons may both contribute to developmental white matter pathology [START_REF] Alix | Central axons preparing to myelinate are highly sensitivity to ischemic injury[END_REF].

The process of axon myelination starts relatively late in human embryonic development, around the 32 nd week of gestation, when the period of great white matter vulnerability comes to an end. At this stage, mature myelinating oligodendrocytes display greater resistance to cell death from hypoxia, oxidative stress or excitotoxicity, explaining why the sensitivity to damage of preterm white matter is highest before this age [START_REF] Back | Pathophysiology of glia in perinatal white matter injury[END_REF].

FETAL CEREBROPROTECTION: ANIMAL MODELS

The choice of animal models and the appreciation of their respective advantages and limitations are crucial for obtaining experimental results of translational significance for human pregnancy. Mammalian species are characterized by a transient period of rapid brain growth, which has been qualified as "brain growth spurt". It also often corresponds to a period of enhanced vulnerability. In prenatal and perinatal brain developers, including humans, sheep and guinea pigs, the rapid brain growth takes place before birth, whereas in rats and mice, the most commonly used laboratory animals, the brain rapidly matures after birth [START_REF] Dobbing | Comparative aspects of the brain growth spurt[END_REF].

In sheep, the average period of gestation is 147 days. This species offers an excellent model to answer questions about fetal health and informations derived from studies of sheep pregnancy have been successfully translated to human perinatal care [START_REF] Morrison | Improving pregnancy outcomes in humans through studies in sheep[END_REF]. The prenatal timing of brain development makes the sheep valuable for studies of brain development. Moreover, there are similarities between stages of brain development in sheep and humans. The process of myelination is more advanced at birth in sheep than humans, and the sheep fetus at about 95 days gestation is at a structural and functional stage of brain development similar to that of the 24-to 28-week-old human fetus [START_REF] Back | The instrumented fetal sheep as a model of cerebral white matter injury in the premature infant[END_REF]. It is interesting to mention here that the guinea pig, with its relatively long period of gestation, may become a valuable translational animal model to study the effects of preterm birth on brain development [START_REF] Hirst | Birth and neonatal transition in the guinea pig: experimental approaches to prevent preterm birth and protect the premature fetus[END_REF][START_REF] Shaw | Long-term effects of preterm birth on behavior and neurosteroid sensitivity in the guinea pig[END_REF].

Rats and mice are the most commonly used species in the laboratory because of practical reasons. Dams have large litters that are easy to care for. They are born after a short gestation (rat: 22 days; mice: 19 days). Mice are for the moment the most amenable to genetic manipulations. In these species, rapid brain development and myelination occur after birth. It is estimated that the rat and mouse brains at postnatal days 1-10 equate the third trimester in humans [START_REF] Clancy | Extrapolating brain development from experimental species to humans[END_REF]. A database-driven website has been created allowing to compare the timing of more than 100 neurodevelopmental events between 10 mammalian species, including humans, rhesus monkeys, guinea pigs, rats and mice [START_REF] Clancy | Web-based method for translating neurodevelopment from laboratory species to humans[END_REF].

FETAL CEREBROPROTECTION BY PROGESTERONE: ANIMAL STUDIES

Work in sheep has demonstrated that elevated levels of progesterone and allopregnanolone towards the end of pregnancy play an important role in cerebroprotection. In response to acute hypoxic stress caused by umbilical cord occlusion during 10 minutes at 135 days of gestation, brain levels of allopregnanolone and expression of the 5α-reductase are markedly and transiently upregulated [START_REF] Hirst | Stress in pregnancy activates neurosteroid production in the fetal brain[END_REF]. This increase in brain allopregnanolone corresponds to a neuroprotective response against hypoxia-induced cell death. Indeed, administration of the 5α-reductase inhibitor finasteride reduced the brain allopregnanolone content and increased neural cell death [START_REF] Yawno | Inhibition of neurosteroid synthesis increases asphyxia-induced brain injury in the late gestation fetal sheep[END_REF].

A remarkable protective effect of allopregnanolone during brain development has been demonstrated in a mouse model of Niemann-Pick type C (NP-C) disease. This fatal childhood neurodegenerative disease is caused by mutations in the genes encoding either NPC1 or NPC2 proteins, which are involved in the intracellular transport of cholesterol and its release from the late endosomes. The NP-C mouse recapitulates cholesterol and sphingolipid storage problems, neurological deficits, Purkinje cell loss, demyelination and early death typical of the most severe form of human NP-C [START_REF] Griffin | Niemann-Pick type C disease involves disrupted neurosteroidogenesis and responds to allopregnanolone[END_REF]. Activities of enzymes involved in allopregnanolone synthesis are significantly reduced in the brain of NP-C mice. Remarkably, replacement therapy with allopregnanolone slowed down the process of neurodegeneration [START_REF] Griffin | Niemann-Pick type C disease involves disrupted neurosteroidogenesis and responds to allopregnanolone[END_REF].

THE ROLE OF PROGESTERONE IN MYELINATION AND MYELIN REPAIR

The lipid-rich and insulating myelin sheaths, which surround axons in the vertebrate nervous system, are required for the rapid saltatory conduction of nerve impulses [START_REF] Baumann | Biology of oligodendrocyte and myelin in the mammalian central nervous system[END_REF]. In addition to its role in rapid nerve conduction, myelin also provides trophic support to axons and is essential for their functional integrity and the survival of neurons [START_REF] Nave | Axon-glial signaling and the glial support of axon function[END_REF].

In rodents, the process of brain myelination begins around postnatal day 5, when oligodendrocyte progenitor cells (OPC) start differentiating into mature oligodendrocytes, the myelin forming glial cells of the central nervous system [START_REF] Ghanem | Longlasting masculinizing effects of postnatal androgens on myelin governed by the brain androgen receptor[END_REF]. Of note, even in the adult brain, lost myelin can be replaced after injury or during demyelinating diseases as part of a natural healing process that has been named "remyelination" [START_REF] Franklin | Regenerating CNS myelin -from mechanisms to experimental medicines[END_REF]. As already mentioned, the regeneration of myelin involves the proliferation and differentiation of OPC, which remain present and are ubiquitous in the adult brain and spinal cord [START_REF] Crawford | Oligodendrocyte progenitors: adult stem cells of the central nervous system?[END_REF]. In patients with multiple sclerosis, myelin can regenerate during the early relapsing/remitting stages [START_REF] Franklin | Why does remyelination fail in multiple sclerosis?[END_REF]. In the light of the great regenerative capacity of myelin, which is preserved during adulthood, it is unexpected that damage to the periventricular white matter during a sensitive period only lasting a few weeks, between 24 th and 32 nd weeks of gestation, has such persistent neurological sequelae.

Progesterone promotes both developmental myelination and the regeneration of myelin in the adult brain [START_REF] Schumacher | Progesterone synthesis in the nervous system: implications for myelination and myelin repair[END_REF]. However, the first demonstration of a role of progesterone and of PR signaling in myelin formation was made in the peripheral nervous system, where axons are myelinated by Schwann cells [START_REF] Koenig | Progesterone synthesis and myelin formation by Schwann cells[END_REF]. Subsequently, a role of progesterone in oligodendrocyte maturation and developmental myelination has been demonstrated in organotypic slice cultures prepared from the cerebellum of postnatal day 7 rats or mice [START_REF] Ghoumari | Progesterone and its metabolites increase myelin basic protein expression in organotypic slice cultures of rat cerebellum[END_REF][START_REF] Ghoumari | Progesterone increases oligodendroglial cell proliferation in rat cerebellar slice cultures[END_REF]. These organotypic cultures offer an integrated system, which closely reproduces developmental events, and they provide a unique model for studying the myelination of axons. The promyelinating effect of progesterone involved PR, as it could be mimicked by the very selective PR agonist promegestone (R5020) and as it was not observed in cerebellar slices prepared from PR knockout mice [START_REF] Ghoumari | Progesterone and its metabolites increase myelin basic protein expression in organotypic slice cultures of rat cerebellum[END_REF].

Progesterone was then shown to also stimulate the proliferation and differentiation of OPC via a PR-dependent mechanism. In fact, its mitogenic effect could be inhibited by the PR antagonist mifepristone and could not be mimicked by allopregnanolone, which activates GABAA receptors, but does not bind to PR [START_REF] Ghoumari | Progesterone increases oligodendroglial cell proliferation in rat cerebellar slice cultures[END_REF]. However, at a very early maturational stage, OPC transiently synthesize progesterone and its metabolite allopregnanolone, the latter being involved in a complex autocrine loop controlling early OPC proliferation [START_REF] Gago | Progesterone and the oligodendroglial lineage: stage-dependent biosynthesis and metabolism[END_REF][START_REF] Gago | Control of cell survival and proliferation of postnatal PSA-NCAM(+) progenitors[END_REF][START_REF] Gago | 3alpha,5alpha-Tetrahydroprogesterone (allopregnanolone) and gamma-aminobutyric acid: autocrine/paracrine interactions in the control of neonatal PSA-NCAM+ progenitor proliferation[END_REF].

Effects of progesterone on the remyelination of axons during brain development have been tested after the demyelination of cerebellar slice cultures prepared from P10 rodent pups with lysophosphatidylcholine (LPC), which has myelinolytic actions but spares axons when well dosed. Four days after LPC-induced demyelination, myelin immunostaining appeared sparse when slices were cultured in medium devoid of progesterone or progestins. However, in brain slices cultured for 4 days in the presence of progesterone, there was a marked increase in the number of remyelinated axons [START_REF] Hussain | Progesterone and nestorone facilitate axon remyelination: a role for progesterone receptors[END_REF]. The synthetic 19-norprogesterone derivative Nestorone, which selectively targets PR, also efficiently promoted the remyelination of axons and stimulated the proliferation, migration and differentiation of OPC. The remyelinating action of Nestorone required the presence of PR, as it was not observed after invalidation of the PR in mice [START_REF] Hussain | Progesterone and nestorone facilitate axon remyelination: a role for progesterone receptors[END_REF].

In the adult brain, therapy with progesterone or Nestorone also promoted the repair of severe chronic demyelinating lesions, induced by feeding the oligodendrocyte toxin cuprizone to female mice. Progesterone and Nestorone both increased the density of OPC and mature oligodendrocytes in the cuprizone demyelinated corpus callosum and stimulated the formation of new myelin sheaths. As for myelination and remyelination during brain development, the pro-remyelinating effect of progesterone in adults was PR-dependent, as it was absent in PR knockout mice [START_REF] El-Etr | Progesterone and nestorone promote myelin regeneration in chronic demyelinating lesions of corpus callosum and cerebral cortex[END_REF]. Interestingly, progesterone and Nestorone also decreased neuroinflammation, in particular astrocyte and microglial cell activation.

Progesterone has been shown to protect against demyelination or to promote myelin regeneration in a variety of animal models of toxin-or lesion-induced demyelination [START_REF] Schumacher | Progesterone synthesis in the nervous system: implications for myelination and myelin repair[END_REF][START_REF] Koenig | Progesterone synthesis and myelin formation by Schwann cells[END_REF][START_REF] Ghoumari | Progesterone and its metabolites increase myelin basic protein expression in organotypic slice cultures of rat cerebellum[END_REF][START_REF] Ghoumari | Progesterone increases oligodendroglial cell proliferation in rat cerebellar slice cultures[END_REF][START_REF] Gago | Progesterone and the oligodendroglial lineage: stage-dependent biosynthesis and metabolism[END_REF][START_REF] Gago | Control of cell survival and proliferation of postnatal PSA-NCAM(+) progenitors[END_REF][START_REF] Gago | 3alpha,5alpha-Tetrahydroprogesterone (allopregnanolone) and gamma-aminobutyric acid: autocrine/paracrine interactions in the control of neonatal PSA-NCAM+ progenitor proliferation[END_REF][START_REF] Hussain | Progesterone and nestorone facilitate axon remyelination: a role for progesterone receptors[END_REF][START_REF] El-Etr | Progesterone and nestorone promote myelin regeneration in chronic demyelinating lesions of corpus callosum and cerebral cortex[END_REF][START_REF] Kipp | Multiple sclerosis: neuroprotective alliance of estrogen-progesterone and gender[END_REF][START_REF] Labombarda | Effects of progesterone on oligodendrocyte progenitors, oligodendrocyte transcription factors, and myelin proteins following spinal cord injury[END_REF].

Importantly, progesterone also exerts remyelinating, neuroprotective, and anti-inflammatory actions and improves neurological outcomes in mice after the induction of experimental autoimmune encephalomyelitis (EAE), a preclinical experimental model of multiple sclerosis [START_REF] Garay | Effects of progesterone in the spinal cord of a mouse model of multiple sclerosis[END_REF][START_REF] Yates | Progesterone treatment reduces disease severity and increases IL-10 in experimental autoimmune encephalomyelitis[END_REF].

One recent study deserves particular attention, as it shows that modifications in the synthesis of progesterone and allopregnanolone within the brain plays a role in demyelinating diseases such as MS. Thus, three micro-RNAs that specifically inhibit the expression of enzymes involved in the synthesis of these two neurosteroids, were induced in the brains of multiple sclerosis patients [START_REF] Noorbakhsh | Impaired neurosteroid synthesis in multiple sclerosis[END_REF]. Analysis of the neurosteroidogenic pathways inhibited by the micro-RNAs revealed suppression of enzyme transcripts and proteins as well as reduced levels of allopregnanolone in white matter. Importantly, diminished expression of neurosteroidogenic enzymes and brain allopregnanolone was also observed in mice with EAE, and allopregnanolone therapy limited neuroinflammation, myelin damage, axonal injury and improved neurological outcomes [START_REF] Noorbakhsh | Impaired neurosteroid synthesis in multiple sclerosis[END_REF].

MAINTAINING STEROIDS IN EARLY PRETERM CHILDREN

Damage to the immature brain is one of the major concerns in preterm birth. It has been postulated that the abrupt removal of early preterm infants from a progesterone and estrogen rich environment, expected to protect the vulnerable developing brain, may contribute to neurodevelopmental disorders. Based on this concept, the effects of postnatal progesterone and estradiol replacement therapy have been examined in extremely low birth weight children. Infants with a gestational age of less than 29 weeks and a birth weight below 1000 gram received intravenously a lipid emulsion containing progesterone and estradiol for a maximum of 4 weeks to mimic intrauterine plasma levels of the hormones. A placebo group receiving the same emulsion without hormones. No negative side effects attributable to the hormone treatment were observed, and infants with progesterone and estradiol replacement showed trends toward improved bone mineral accretion and reduced incidence of chronic lung disease [START_REF] Trotter | Effects of postnatal estradiol and progesterone replacement in extremely preterm infants[END_REF]. However, cognitive and neurological outcomes at the age of 5 years showed only slight improvements [START_REF] Trotter | Neurodevelopmental follow-up at five years corrected age of extremely low birth weight infants after postnatal replacement of 17beta-estradiol and progesterone[END_REF]. One possibility is that brain abnormalities after preterm birth are compensated by regenerative processes during early childhood [START_REF] Volpe | Brain injury in premature infants: a complex amalgam of destructive and developmental disturbances[END_REF].

However, an important gap of knowledge needs to be filled, as we do not precisely know to what extend the developing brain is deprived of protective neurosteroids in the very preterm infants. First, the brain itself is a significant source of neurosteroids, in particular of progesterone, allopregnanolone and estrogens, the production of which may even be upregulated in response to stress or injury [START_REF] Stoffel-Wagner | Neurosteroid metabolism in the human brain[END_REF][START_REF] Schonemann | Expression of P450c17 in the human fetal nervous system[END_REF]. No information is available concerning brain neurosteroid levels in preterm infants.

Second, there is a debate concerning the fate of the fetal zone in preterm infants, which could remain a source of the precursor steroid DHEAS. Preterm birth disrupts the feto-placental unit, resulting in a drop of progesterone and estradiol levels [START_REF] Trotter | Effects of postnatal estradiol and progesterone replacement in extremely preterm infants[END_REF]. However, two studies report that the adrenal fetal zone of preterm infants may continue producing high amounts of DHEAS until the time of termed birth [START_REF] Midgley | Activity of the adrenal fetal zone in preterm infants continues to term[END_REF][START_REF] Heckmann | Persistent high activity of the fetal adrenal cortex in preterm infants: is there a clinical significance?[END_REF]. In that case, involution of the adrenal fetal zone is related to gestational age rather than birth, and preterm infants may continue to benefit from the protective effects of fetal zone steroids, which could also provide the necessary substrate for estrogen production within the brain [START_REF] Hubner | Protective Effects of fetal zone steroids are comparable to estradiol in hyperoxia-induced cell death of immature glia[END_REF]. Conversely, according to another study, the fetal zone may rapidly regress after preterm birth and levels of DHEAS decline regardless of gestational age [START_REF] Ben-David | Parturition itself is the basis for fetal adrenal involution[END_REF]. Precise steroid profiling by mass spectrometric methods in preterm infants is thus urgently needed to clarify this question.

It is of interest to mention here one of the outcomes of the OPPTIMUM study, a multicenter, randomized and placebo-controlled clinical trial aimed to test the usefulness of vaginal progesterone prophylaxis (200 mg daily taken from 22-24 to 34 weeks of gestation) for the prevention of preterm birth [START_REF] Norman | Vaginal progesterone prophylaxis for preterm birth (the OPPTIMUM study): a multicentre, randomised, double-blind trial[END_REF]. Neonatal and childhood outcomes were also evaluated.

Vaginal progesterone was not associated with a reduced risk of preterm birth or neonatal adverse outcomes, and had no long-term benefit or harm on outcomes in children at 2 years of age. However, ultrasound examination of the neonatal brains revealed a significant reduction in injury by progesterone [START_REF] Norman | Vaginal progesterone prophylaxis for preterm birth (the OPPTIMUM study): a multicentre, randomised, double-blind trial[END_REF].

FIGURE LEGENDS

Figure 1: Synthesis and metabolism of progesterone. At the level of the inner mitochondrial membrane, cholesterol is converted to pregnenolone by cytochrome P450scc. Pregnenolone is then converted to progesterone by the 3β-hydroxysteroid dehydrogenases (3β-HSD). These enzymes are either located inside the mitochondria or within the cytoplasm. Progesterone is irreversibly converted to 5α-dihydroprogesterone by the 5α-reductases. In neural cells, both progesterone and 5α-dihydroprogesterone bind to the intracellular progesterone receptors (PR). In the nucleus, dimers of the ligand-bound PR interact with regulatory progesterone response elements (PRE) and regulate gene expression. 5α-dihydroprogesterone is metabolized to allopregnanolone by the 3α-hydroxysteroid dehydrogenase (3α-HSD).

Allopregnanolone has no affinity for PR, but is a positive modulator of GABAA receptors.

Figure 2 :

 2 Figure 2: Throughout human pregnancy, levels of progesterone increase and reach highest

  Figure 1