Nanoparticles for use for treating a neuronal disorder

Abstract

The present invention relates to the medical field, in particular to the treatment of neurological disorders. More specifically the present invention relates to a nanoparticle or nanoparticles' aggregate for use in prevention or treatment of a neurological disease or at least one symptom thereof in a subject without exposure of the nanoparticle or nanoparticles' aggregate to an electric field, and preferably without exposure thereof to any other external activation source, wherein the nanoparticle's or nanoparticles' aggregate's material is selected from a conductor material, a semiconductor material, an insulator material with a dielectric constant ε.sub.ijk equal to or above 200, and an insulator material with a dielectric constant ε.sub.ijk equal to or below 100. It further relates to compositions and kits comprising such nanoparticles and/or nanoparticles' aggregates as well as to uses thereof without exposure thereof to an electric field, and preferably without exposure thereof to any other external activation source.

Claims

1. A method for preventing or treating a neurological disease selected from Parkinson's disease, Alzheimer's disease, epilepsy, obsessive compulsive disorder, autism spectrum disorder, depression disorder, dystonia, Tourette's syndrome, schizophrenia, stroke, aphasia, dementia, tinnitus, Huntington's disease, essential tremor, bipolar disorder, anxiety disorder, addiction disorder, and consciousness vegetative state, or at least one symptom thereof in a subject, wherein the method comprises a step of administering nanoparticle or nanoparticle aggregate, or a composition comprising nanoparticles and/or nanoparticle aggregates and a pharmaceutically acceptable support, to a subject, the material of the nanoparticle or nanoparticle aggregate being selected from the group consisting of a conductor material that is a metal having a standard reduction potential E° above 0.2 selected from Tl, Po, Ag, Pd, Ir, Pt, Au, and a mixture thereof, or an organic material having contiguous sp2 hybridized carbon centers in its structure, a semiconductor material with a band gap Eg below 3.0 eV selected from a mixed composition of elements from groups III and V of the Mendeleev's periodic table, a mixed composition of elements from groups II and VI of the Mendeleev's periodic table, and an element from group IV-A of the Mendeleev's periodic table, and an insulator material with a dielectric constant ε.sub.ijk equal to or above 200, or an insulator material with a dielectric constant ε.sub.ijk equal to or below 100 selected from Al.sub.2O.sub.3, LaAlO.sub.3, La.sub.2O.sub.3, SiO.sub.2, SnO.sub.2, Ta.sub.2O.sub.5, ReO.sub.2, ZrO.sub.2, HfO.sub.2 and carbon diamond, the relative dielectric constant ε.sup.ijk being measured between 20° C. and 30° C. and between 10.sup.2 Hz up to the infrared frequency, wherein i) the median largest size of the core of the nanoparticle or nanoparticles' aggregate of the population is of at least 30 nm when the material is a conductor material, a semiconductor material or an insulator material with a dielectric constant ε.sub.ijk equal to or above 200, and wherein ii) the core of the nanoparticle or nanoparticle aggregate is coated with a biocompatible coating providing a neutral or a negative surface charge when measured in a solution of water having a concentration of electrolytes between 0.001 and 0.2 M, the concentration of the nanoparticle or nanoparticle aggregate material is between 0.01 and 10 g/L and a pH between 6 and 8, wherein iii) the method does not include any step of exposing the nanoparticles or nanoparticle aggregates to an electric field nor to any other external activation source, wherein iv) the nanoparticles or nanoparticle aggregates remain in the subject, and wherein v), the nanoparticles or aggregates of nanoparticles is not used as carriers of therapeutic compound(s) or drug(s).

2. The method according to claim 1, wherein the conductor material is selected from Ir, Pd, Pt, Au, and any mixture thereof, and an organic material having contiguous sp2 hybridized carbon centers in its structure, said organic material being selected from polyaniline, polypyrrole, polyacetylene, polythiophene, polycarbazole, polypyrene and any mixture thereof.

3. The method according to claim 1, wherein the nanoparticle's or nanoparticles aggregate's material is an element from group IV-A of the Mendeleev's periodic table and is doped with a charge carrier selected from Al, B, Ga, In and P.

4. The method according to claim 1, wherein the insulator material with a band gap Eg equal to or above 3.0 eV and the relative dielectric constant ε.sub.ijk is-equal to or above 200 is a dielectric material which is a mixed-metal oxide selected from BaTiO.sub.3, KTaNbO.sub.3, KTaO.sub.3, SrTiO.sub.3 and BaSrTiO.sub.3.

5. The method according to claim 1, wherein the insulator material with a band gap Eg equal to or above 3.0 eV and a relative dielectric constant ε.sub.ijk equal to or below 100 is selected from ReO.sub.2, ZrO.sub.2 and HfO.sub.2.

6. The method according to claim 1, wherein the neurological disease is Parkinson's disease or Alzheimer's disease.

7. The method according to claim 1, wherein the composition comprises at least two distinct nanoparticles and/or nanoparticle aggregates.

8. A composition or kit comprising at least two distinct nanoparticles and/or nanoparticle aggregates, the nanoparticles' or nanoparticles aggregates' material being selected from the group consisting of a conductor material that is a metal having a standard reduction potential E° above 0.2 selected from Tl, Po, Ag, Pd, Ir, Pt, Au, and a mixture thereof, or an organic material having contiguous sp2 hybridized carbon centers in its structure, a semiconductor material with a band gap Eg below 3.0 eV selected from a mixed composition of elements from groups III and V of the Mendeleev's periodic table, a mixed composition of elements from groups II and VI of the Mendeleev's periodic table, and an element from group IV-A of the Mendeleev's periodic table, and an insulator material with a dielectric constant ε.sub.ijk equal to or above 200, and an insulator material with a dielectric constant ε.sub.ijk equal to or below 100 selected from Al.sub.2O.sub.3, LaAlO.sub.3, La.sub.2O.sub.3, SiO.sub.2, SnO.sub.2, Ta.sub.2O.sub.5, ReO.sub.2, ZrO.sub.2, HfO.sub.2 and carbon diamond, the relative dielectric constant ε.sub.ijk being measured between 20° C. and 30° C. and between 10.sup.2 Hz up to the infrared frequency, wherein i) the median largest size of the core of the nanoparticle or nanoparticle aggregate of the population is of at least 30 nm when the material is a conductor material, a semiconductor material or an insulator material with a dielectric constant ε.sub.ijk equal to or above 200, and wherein ii) the core of the nanoparticle or nanoparticles aggregate is coated with a biocompatible coating providing a neutral or a negative surface charge when measured in a solution of water having a concentration of electrolytes between 0.001 and 0.2 M, the concentration of the nanoparticle or nanoparticle aggregate material is between 0.01 and 10 g/L and a pH between 6 and 8.

9. The method according to claim 1, wherein the element from group IV-A of the Mendeleev's periodic table is silicon (Si) or Germanium (Ge).

Description

FIGURES

(1) FIG. 1. Schematic representation of the brain (sagittal plane).

(2) FIG. 2. Hypersynchrony and impaired synchrony between two neuronal networks.

(3) FIG. 3. Brain areas involved in various neurological diseases.

(4) FIG. 4. Effect of nanoparticles (NP) on normalization of hypersynchrony (motor disorders).

(5) FIG. 5. Effect of nanoparticles (NP) on normalization of impaired synchrony (psychiatric and cognitive disorders).

(6) FIG. 6. Experimental scheme of induction of Parkinson's disease with MPP.sup.+ treatment and electrical activity recording.

(7) The mouse ventral midbrain/cortex co-cultures were prepared from E14.5 NMRI mice and cultured on 48 well MEAs for 3 weeks (total culture period). The cultures were treated after 7 days in culture (day 7) with the nanoparticles' suspensions (“Nanoparticles” groups), GDNF (20 ng/ml) (“Reference” group) or water (“Control” group and “MPP.sup.+” group) and at day 8 with MPP (20 μM) (“Nanoparticles” groups, “Reference” group and “MPP.sup.+” group) or water (“Control” group). The spontaneous activity was recorded at day 21.

(8) FIG. 7. Scheme of two simplified bursts outlining some of the parameters that can be extracted from the electrical activity recording. Parameters describing general activity (spike, burst, inter burst interval (IBI) and burst period) and burst structure (burst duration, burst plateau, burst amplitude, burst inter spike interval (ISI) and burst area) are indicated. Standard deviations (SD) of these parameters are measures for regularity of general activity and burst structure respectively. Coefficient of variation in time (CVtime) reflects the temporal regularity of the activity pattern of each unit. CVtime is calculated by the ratio of parameter's standard deviation and mean. Coefficient of variation among the network (CVnet) reflects synchronization among neurons within the network. CVnet is calculated by the ratio of parameter's standard deviation by mean over the network. Large CVnet values imply a wide range of variation in the activity across the network, meaning less synchronization.

(9) FIG. 8. Functional effects observed in “Nanoparticles” groups (nanoparticles from examples 1 and 2) and “Reference” group compared to “Control” group and “MPP.sup.+” group on midbrain/cortex network activity. The data show MPP.sup.+-induced functional effects and demonstrate the prevention/rescue efficacy allowed by the nanoparticles of the invention or by GDNF (i.e. ability to prevent/rescue functional effects to a level similar to that of “Control” group).

(10) FIG. 9. Functional effects observed in “Nanoparticles” groups (nanoparticles from examples 5 and 6) compared to “Control” group and “MPP.sup.+” group on midbrain/cortex network activity. The data show MPP.sup.+-induced functional effects and demonstrate the prevention/rescue efficacy allowed by the nanoparticles of the invention (i.e. ability to prevent/rescue functional effects to a level similar to that of “Control” group).

(11) FIG. 10. Effect Score analysis for the “Nanoparticles” groups, “Reference” group, “Control” group and “MPP.sup.+” group.

(12) FIG. 11. Experimental scheme of induction of Alzheimer's disease with amyloid beta 1-42 (Abeta 1-42), treatment and electrical activity recordings. After 4 weeks in cultures (culture period), Abeta 1-42 (100 nM) (“Nanoparticle” group, “Reference” group and “Abeta” group) or water (“Control” group) (T0) were added to the neuronal network. Four (4) hours later, the nanoparticles' suspensions (“Nanoparticle” groups), Donepezil (300 nM) (“Reference” group) or water (“Control” group and “Abeta” group) were added. The spontaneous activity was recorded as follow: at T0 (prior addition of Abeta 1-42) at T0+1 h, +2 h, +3 h, +4 h (prior to nanoparticles, donepezil or water addition), +5 h, and +6 h.

(13) FIG. 12. Functional effects observed in “Nanoparticles” groups and “Reference” group compared to “Control” group and “Abeta 1-42” group on cortex network activity. The data show Abeta 1-42 functional effects and demonstrate the rescue efficacy allowed by the nanoparticles of the invention or by donepezil (i.e. ability to rescue functional effects to a level similar to that of the “Control” group).

(14) FIG. 13. Effect Score analysis for the “Nanoparticles” groups, “Reference” group, “Control” group (Effect Score=0) and “Abeta” group (Effect Score=1).

(15) FIG. 14. Representative TEM images of gold nanoparticles from examples 9, the median largest size of the core of the nanoparticles of the population being equal to 108 nm (GOLD-110), 83 nm (GOLD-80), 45 nm (GOLD-45), 34 nm (GOLD-30) and 15 nm (GOLD-15) respectively.

(16) FIG. 15. Effect Score analysis for the “Nanoparticles” groups (GOLD-45 and GOLD-15 nanoparticles from example 9), “Control” group (Effect Score=0) and “MPP.sup.+” group (Effect Score=1).

(17) FIG. 16. Representative scanning electron microscopy (SEM) image of PEDOT nanoparticles from example 11.

(18) FIG. 17. Effect Score analysis for the “Nanoparticles” groups (PEDOT nanoparticles from example 11), “Control” group (Effect Score=0) and “MPP.sup.+” group (Effect Score=1).

EXAMPLES

(19) In Vitro Studies of Neurons

(20) At the neuron level, Patch clamp technique is very useful for detecting action potentials, as it allows simultaneous direct measurement and control of membrane potential of a neuron. This technique is used to assess the effects of nanoparticles on a single neuron.

(21) In Vitro Studies of a Network of Neurons

(22) Dissociated neuronal cultures coupled to multi electrode arrays (MEAs) are widely used to better understand the complexity of brain networks. In addition, the use of dissociated neuronal assemblies allows the manipulation and control of the network's connectivity. The MEA system enables non-invasive, long-lasting, simultaneous extracellular recordings from multiple sites in the neuronal network in real time, increasing spatial resolution and thereby providing a robust measure of network activity. The simultaneous gathering of action potential and field potential data over long periods of time allows the monitoring of network functions that arise from the interaction of all cellular mechanisms responsible for spatio-temporal pattern generation (Johnstone A. F. M et al., Neurotoxicology, 2010, 31, 331-350: Microelectrode arrays: a physicologically based neurotoxicity testing platform for the 21.sup.st century). Compared to patch-clamp and other single electrode recording techniques, MEA measures responses of a whole network, integrating global information on the interaction of all receptors, synapses and neuronal types which are present in the network (Novellino A. et al., Frontiers in Neuroengineering, 2011, 4(4), 1-14: Development of micro-electrode array based tests for neurotoxicity: assessment of interlaboratory reproducibility with neuroactive chemicals). As such, MEA recordings have been employed to understand neuronal communication, information encoding, propagation, and processing in neuronal cultures (Taketani, M., and Baudry, M. (2006). Advances in Network Electrophysiology. New York, N.Y.: Springer; Obien et al., Frontiers in Neurosciences, 2015, 8(423): Revealing neuronal functions through microelectrode array recordings). The MEA technology is a sophisticated phenotypic high-content screening method to characterize functional changes in network activity in electrically active cell cultures and it is very sensitive to neurogenesis, as well as neuroregenerative and neurodegenerative aspects. Moreover, neuronal networks grown on MEAs are known as being capable of responding to neuroactive or neurotoxic compounds in approximately the same concentration ranges that alter functions of an intact mammalian nervous system (Xia et al., Alcohol, 2003, 30, 167-174: Histiotypic electrophysiological responses of cultured neuronal networks to ethanol; Gramowski et al., European Journal of Neuroscience, 2006, 24, 455-465: Functional screening of traditional antidepressants with primary cortical neuronal networks grown on multielectrode neurochips; Gramowski et al., Frontiers in Neurology, 2015, 6(158): Enhancement of cortical network activity in vitro and promotion of GABAergic neurogenesis by stimulation with an electromagnetic field with 150 MHz carrier wave pulsed with an alternating 10 and 16 Hz modulation).

(23) This technique is used to assess the effect of nanoparticles on neuronal network(s).

(24) In Vivo Studies of a Network of Neurons

(25) An appropriate animal model is considered to assess the effect on neuronal networks of animals of nanoparticles of the invention.

(26) For instance, mouse models of Parkinson's disease are used to assess the effects of nanoparticles on the relief of behavior impairment (motor disorders). Also, rat or mouse models of Alzheimer's disease are used to assess the effects of nanoparticles on the spatial learning and memory dysfunction (cognitive disorders) of animals.

Example 1. Nanoparticles Prepared with a Conductor Material: Synthesis of Gold Nanoparticles Coated with a Biocompatible Coating Having a Neutral Surface Charge

(27) Gold nanoparticles were synthesized by reducing a gold chloride salt (HAuCl.sub.4) with a capping agent (sodium citrate) (protocol was adapted from G. Frens Nature Physical Science 241 (1973) 21). In a typical experiment, HAuCl.sub.4 solution was heated to boiling. Subsequently, sodium citrate solution was added. The resulting solution was maintained under boiling for an additional period of 5 minutes.

(28) A 0.22 μm filtration (filter membrane: poly(ether sulfone) (PES)) of the nanoparticles' suspension was performed and gold concentration in suspension was determined by a UV-visible spectroscopy assay at 530 nm.

(29) A surface coating was performed using α-methoxy-ω-mercaptopoly(ethylene glycol) 20 kDa (“thiol-PEG20 kDa”). A sufficient amount of “thiol-PEG 20 kDa” was added to the nanoparticles' suspension to reach at least half a monolayer coverage (2.5 molecules/nm.sup.2) on the gold nanoparticle surface. pH was adjusted between 7 and 7.2, and the nanoparticles' suspension was stirred overnight.

(30) The hydrodynamic diameter (measure in intensity) was determined by Dynamic Light Scattering (DLS) at room temperature (about 25° C.), with a Nano-Zetasizer (Malvern) at a scattering angle of 173° with a laser emitting at 633 nm, by diluting the nanoparticles' suspension in water (final concentration: [Au]=0.1 g/L). The hydrodynamic diameter of the so obtained biocompatible gold nanoparticles in suspension was found equal to 118 nm, with a polydispersity index (dispersion of the nanoparticles' population in size) of 0.13.

(31) The zeta potential was determined by measuring the electrophoretic mobility of the nanoparticles (Nano-Zetasizer, Malvern) by diluting the nanoparticles' suspension in a NaCl solution at 1 mM at pH 7 (final concentration: [Au]=0.1 g/L). The zeta potential at pH 7 was found equal to −1 mV.

Example 2. Nanoparticles Prepared with a Conductor Material: Synthesis of Gold Nanoparticles Coated with a Biocompatible Coating Having a Negative Surface Charge

(32) Gold nanoparticles were prepared as described in example 1 (same gold inorganic core).

(33) A 0.22 μm filtration on PES membrane filter was performed and gold concentration in suspension was determined by a UV-visible spectroscopy assay at 530 nm.

(34) A biocompatible surface coating was performed using meso-2, 3-dimercaptosuccinic acid (DMSA). A sufficient amount of DMSA was added to the nanoparticles' suspension to reach at least half a monolayer coverage (2.5 molecules/nm.sup.2) on the surface. pH was adjusted between 7 and 7.2, and the nanoparticles' suspension was stirred overnight.

(35) The hydrodynamic diameter (measure in intensity) was determined by Dynamic Light Scattering (DLS) at room temperature (about 25° C.), with a Nano-Zetasizer (Malvern) at a scattering angle of 173° with a laser emitting at 633 nm, by diluting the nanoparticles' suspension in water (final concentration: [Au]=0.1 g/L). The hydrodynamic diameter of the so obtained nanoparticles in suspension was equal to 76 nm, with a polydispersity index (dispersion of the nanoparticles' population in size) of 0.46.

(36) The zeta potential was determined by measuring the electrophoretic mobility of the nanoparticles (Nano-Zetasizer, Malvern) by diluting the nanoparticles' suspension in a NaCl solution at 1 mM at pH 7 (final concentration: [Au]=0.1 g/L). The zeta potential at pH 7 was found equal to −23 mV.

Example 3. Nanoparticles Prepared with an Insulator Material Having a Low Relative Dielectric Constant Equal to or Below 100: Synthesis of Zirconium Oxide Nanoparticles Coated with a Biocompatible Coating Having a Neutral Surface Charge

(37) Zirconium oxide (ZrO.sub.2) nanoparticles were synthesized by precipitation of zirconium chloride (ZrCl.sub.4) with tetramethyl ammonium hydroxide (TMAOH) at a basic pH. The resulting suspension was transferred in an autoclave and heated at a temperature above 110° C. After cooling, the suspension was washed with deionized water and acidified.

(38) The median largest size of the core of the nanoparticles or nanoparticles' aggregates of the population and the size of the core of the nanoparticles or nanoparticles' aggregates representing the 30%-70% percentile of the population of nanoparticles and nanoparticles' aggregates were evaluated using transmission electron microscopy and found equal to 10 nm and 8 nm-12 nm respectively. 446 nanoparticles were counted and their largest dimension was measured.

(39) A 0.22 μm filtration on PES membrane filter was performed and (ZrO.sub.2) nanoparticles' concentration was determined by drying the aqueous solution into a powder and weighing the as-obtained mass. A biocompatible coating was prepared using silane-poly(ethylene) glycol 2 kDa (“Si-PEG 2 kDa”). A sufficient amount of “Si-PEG 2 kDa” was added to the nanoparticles' suspension to reach at least half a monolayer coverage (2.5 molecules/nm.sup.2) on the surface. The nanoparticles' suspension was stirred overnight and subsequently the pH was adjusted to 7.

(40) The hydrodynamic diameter (measure in intensity) was determined by Dynamic Light Scattering (DLS) at room temperature (about 25° C.), with a Nano-Zetasizer (Malvern) at a scattering angle of 173° with a laser emitting at 633 nm, by diluting the nanoparticles' suspension in water (final concentration of the ZrO.sub.2 constituting the nanoparticle's core: [ZrO.sub.2]=0.1 g/L). The nanoparticles' hydrodynamic diameter was found equal to 55 nm, with a polydispersity index (dispersion of the nanoparticles' population in size) of 0.1.

(41) The zeta potential was determined by measuring the electrophoretic mobility of the nanoparticles (Nano-Zetasizer, Malvern) by diluting the nanoparticles' suspension in a NaCl solution at 1 mM at pH 7 (final concentration: [ZrO.sub.2]=0.1 g/L). The zeta potential at pH7 was found equal to −1 mV.

Example 4. Nanoparticles Prepared with an Insulator Material Having a Low Relative Dielectric Constant Equal to or Below 100: Synthesis of Zirconium Oxide Nanoparticles Coated with a Biocompatible Coating Having a Negative Surface Charge

(42) Zirconium oxide nanoparticles were prepared as described in example 3 (same inorganic core).

(43) A 0.22 μm filtration on PES membrane filter was performed and the (ZrO.sub.2) nanoparticles' concentration was determined by drying the aqueous suspension to a powder and weighing the as-obtained mass. Surface functionalization was performed using sodium hexametaphosphate. A sufficient mass of sodium hexametaphosphate was added to the nanoparticles' suspension to reach at least half a monolayer coverage (2.5 molecules/nm.sup.2) on the surface. The nanoparticles' suspension was stirred overnight and pH was subsequently adjusted to 7.

(44) The hydrodynamic diameter (measure in intensity) was determined by Dynamic Light Scattering (DLS) at room temperature (about 25° C.), with a Nano-Zetasizer (Malvern) at a scattering angle of 173° with a laser emitting at 633 nm, by diluting the nanoparticles' suspension in water (final concentration of the ZrO.sub.2 constituting the nanoparticle's core: [ZrO.sub.2]=0.1 g/L). The nanoparticles' hydrodynamic diameter was found equal to 70 nm, with a polydispersity index (dispersion of the nanoparticles population in size) of 0.11.

(45) The zeta potential was determined by measuring the electrophoretic mobility of the nanoparticles (Nano-Zetasizer, Malvern) by diluting the nanoparticles' suspension in a NaCl solution at 1 mM at pH 7 (final concentration: [ZrO.sub.2]=0.1 g/L). The zeta potential at pH 7 was found equal to −33 mV.

Example 5. Nanoparticles Prepared with a Semiconductor Material: Silicon (Si) Nanoparticles Coated with a Biocompatible Coating Having a Negative Surface Charge

(46) Silicon (Si) nanoparticles (powder) were obtained from US Research Nanomaterials Inc. They were coated with PVP (1% wt), representing less than 0.1 molecule/nm.sup.2 on the surface.

(47) They were dispersed in water at 30 g/L under sonication (with a probe).

(48) A 0.22 μm filtration on PES membrane filter was performed and the (Si) nanoparticles' concentration was determined by drying the suspension to a powder and weighing the as-obtained mass.

(49) The hydrodynamic diameter (measure in intensity) was determined by Dynamic Light Scattering (DLS) at room temperature (about 25° C.), with a Nano-Zetasizer (Malvern) at a scattering angle of 173° with a laser emitting at 633 nm, by diluting the nanoparticles' suspension in water (final concentration final concentration of the Si constituting the nanoparticle's core: [Si]=0.1 g/L). The nanoparticles' hydrodynamic diameter was found equal to 164 nm, with a polydispersity index (dispersion of the nanoparticles' population in size) of 0.16.

(50) The median largest size of the core of the nanoparticles or nanoparticles' aggregates of the population and the size of the core of the nanoparticles or nanoparticles' aggregates representing the 30%-70% percentile of the population of nanoparticles and nanoparticles' aggregates were evaluated using transmission electron microscopy and found equal to 53 nm and 45-61 nm respectively. Seventy-one (71) nanoparticles were counted and their largest dimension was measured.

(51) The zeta potential was determined by measuring the electrophoretic mobility of the nanoparticles (Nano-Zetasizer, Malvern) by diluting the nanoparticles' suspension in a NaCl solution at 1 mM at pH 7 (final concentration: [Si]=0.1 g/L). The zeta potential at pH 7 was found equal to −19 mV.

Example 6. Nanoparticles Prepared with an Insulator Material Having a High Relative Dielectric Constant Equal to or Above 200: Barium Titanate Nanoparticles Coated with a Biocompatible Coating Having a Negative Surface Charge

(52) Barium titanate (BaTiO.sub.3) nanoparticles' suspension (20% wt in water) was obtained from US Research Materials Inc. (US3835).

(53) Surface functionalization was performed using Silane-poly(ethylene) glycol 10 kDa (“Si-PEG 10 kDa”). Briefly, “Si-PEG 10 kDa” was first dissolved in an ethanol/water solution (⅓ v/v) and added to the BaTiO.sub.3 suspension (20% wt in water) to achieve a full monolayer coverage on the surface of the nanoparticles. The suspension was sonicated and subsequently stirred overnight. After a 0.22 μm filtration (filter membrane: poly(ether sulfone)), a washing step was performed in order to eliminate unreacted “Si-PEG 10 kDa” polymers.

(54) The hydrodynamic diameter (measure in intensity) was determined by Dynamic Light Scattering (DLS) at room temperature (about 25° C.), with a Nano-Zetasizer (Malvern) at a scattering angle of 173° with a laser emitting at 633 nm, by diluting the nanoparticles' suspension in water (final concentration of the BaTiO.sub.3 constituting the nanoparticle's core: [BaTiO.sub.3]=0.1 g/L). The nanoparticles' hydrodynamic diameter was found equal to 164 nm, with a polydispersity index (dispersion of the nanoparticles' population in size) of 0.16.

(55) The zeta potential was determined by measuring the electrophoretic mobility of the nanoparticles (Nano-Zetasizer, Malvern) by diluting the nanoparticles' suspension in a NaCl solution at 1 mM at pH 7 (final concentration: [BaTiO.sub.3]=0.1 g/L). The zeta potential at pH 7 was found at −11 mV.

(56) The median largest size of the core of the nanoparticles or nanoparticles' aggregates of the population and the size of the core of the nanoparticles or nanoparticles' aggregates representing the 30%-70% percentile of the population of nanoparticles and nanoparticles' aggregates were evaluated using transmission electron microscopy and found equal to 67 nm and 60-77 nm respectively. Fifty-one (51) nanoparticles were counted and their largest dimension was measured.

Example 7. Evaluation of the Prevention/Rescue Efficacy of Nanoparticles from Examples 1, 2, 5 and 6, on MPP.SUP.+.-Induced Neuronal Networks Using the Phenotypic Mea Screening Technology

(57) The prevention/rescue efficacy of nanoparticles of the invention was tested on MPP.sup.+-treated mouse ventral midbrain/cortex co-cultures, cultured on a 48-wells MEA for 3 weeks. This model represents an in vitro Parkinson's model for screening compounds, based on the functional rescue of dopaminergic neurons using challenged midbrain/cortex cultures growing on MEAs. Midbrain is a region of the brain including the substantia nigra which is part of the basal ganglia and which contains most of the dopaminergic neurons. The evaluation of the nanoparticles' prevention/rescue effect was performed via the measurement of the extracellular electrical activity of the co-culture of neurons plated on Microelectrode Array (MEA) chips.

(58) The induction of a parkinsonian phenotype in mouse neurons in vitro was performed with 1-methyl-4-phenyl pyridinium iodide (MPP.sup.+). There is strong evidence that mitochondrial impairment plays a role in the pathogenesis of Parkinson's disease (PD). MPP.sup.+ was found to be mitochondrial poison that inhibits cellular respiration through the blockade of the electron transport enzyme complex I (NADH: ubiquinone oxidoreductase). Several laboratories have reported that there is a selective defect in complex I of mitochondrial electron transport chain in the substantia nigra of postmortem tissue of PD patients, and there is also reduction of complex I activity in platelets of patients with early PD. Drugs such as glial cell-derived neurotrophic factor (GDNF), act as neuroprotector agents to prevent/rescue the effect of MPP.sup.+ with good preclinical outcomes. GDNF is frequently used as reference in experimental preclinical protocols (Peng J. et al., Journal of Biomolecular screening, 2013, 18(5), 522-533: Using human pluripotent stem cell-derived dopaminergic neurons to evaluate candidate Parkinson's disease therapeutic agents in MPP+ and rotenone models.).

(59) Material and Methods

(60) Primary Cell Culture, Treatment Conditions

(61) Midbrain and frontal cortex tissue was harvested from embryonic day 14.5 chr:NMRI mice (Charles River). Mice were sacrificed by cervical dislocation. Tissue was dissociated by enzymatic digestion (133.3 Kunitz units/ml DNase; 10 Units/ml Papain) and mechanical trituration, counted, vitality controlled, and plated in a 20 μl drop of DMEM containing laminin (10 μg/ml), 10% fetal bovine serum and 10% horse serum on MEAs. Cultures on MEAs were incubated at 37° C. in a 10% CO.sub.2 atmosphere until ready for use. Culture media were replenished two times a week with DMEM containing 10% horse serum.

(62) In the “Nanoparticles” groups, wells were treated at day 7 with nanoparticles' suspension from examples 1 ([Au]=800 μM), 2 ([Au]=800 μM), 5 ([Si]=800 μM) and with nanoparticles' suspension from example 6 ([BaTiO.sub.3]=2000 μM), followed by 20 μM of MPP.sup.+ at day 8. In the “Control” group, water was added to the wells at day 7, followed by water addition at day 8. In the “MPP.sup.+” group, water was added to the wells at day 7, followed by 20 μM of MPP.sup.+ at day 8. In the “Reference” group, GDNF (20 ng/ml) was added to the wells at day 7, followed by 20 μM of MPP.sup.+ at day 8.

(63) Twenty-four (24) hours following MPP.sup.+ (or water for “Control” group) addition, the medium was changed to achieve wash out of MPP.sup.+. Medium was subsequently changed twice per week and GDNF was added for the “Reference” group only, at each medium change.

(64) At day 21, 120 minutes of neuronal activity were recorded, and 30 minutes of stable activity were analyzed (FIG. 6).

(65) Microelectrode Array Neurochips

(66) The 48 wells microelectrode array neurochips were purchased from Axion Biosystems Inc. These chips have 16 passive electrodes per well. The surface was coated for 1 hour with Polyethyleneimine (PEI, 50% in Borate buffer), washed and air-dried.

(67) Multichannel Recording and Multiparametric Data Analysis

(68) For the recording, the multichannel MAESTRO recording system by Axion Biosystems (USA) was used. For extracellular recording, 48-wells MEAs were placed into the MAESTRO recording station and maintained at 37° C. Recordings were made in DMEM/10% heat inactivated horse serum. The pH was maintained at 7.4 with a continuous stream of filtered, humidified airflow with 10% CO.sub.2.

(69) Each unit represents the activity originating from one neuron recorded at one electrode. Units are separated at the beginning of the recording. For each unit, action potentials (i.e. spikes), were recorded as spike trains, which are clustered in so-called “bursts”. Bursts were quantitatively described via direct spike train analysis using the programs Spike Wrangler and NPWaveX (both NeuroProof GmbH, Rostock, Germany). Bursts were defined by the beginning and end of short spike events (FIG. 7).

(70) With a multiparametric high-content analysis of the network activity patterns, 204 activity-describing spike train parameters were extracted. These parameters allow obtaining a precise description of activity changes in the following four categories: general activity, burst structure, oscillatory behavior and synchronicity. Changes in “general activity parameters” describe the effects on action potential firing rate (spike rate), burst rate, and burst period as the time between the bursts. “Burst structure parameters” define not only the internal structure of spikes within a high-frequency spiking phase (“burst”), e.g., spike frequency in bursts, spike rate in bursts, and burst spike density, but also the overall structure of the burst, such as duration, area, and plateau. “Oscillatory parameters” quantify the regularity of occurrence or structure of bursts, which is calculated by coefficients of variation of primary activity parameters describing the variability of parameters (general activity, burst structure) within experimental episodes (Gramowski A. et al., Eur. J. Neurosci., 2004, 19, 2815-2825: Substance identification by quantitative characterization of oscillator activity in murine spinal cord networks on microelectrode arrays). Higher values indicate less regular burst structure or less regular general activity (e.g., spiking, bursting). As a measure of synchronicity in the spike trains, “CVnet parameters” reflect “synchronization” among neurons within the network (Gramowski A. et al., Eur. J. Neurosci., 2004, 19, 2815-2825: Substance identification by quantitative characterization of oscillator activity in murine spinal cord networks on microelectrode arrays). CVnet is the coefficient of variation over the network. Large CVnet values imply a wide range of variation in the activity across the network, meaning less synchronization. (Gramowski A. et al., Frontiers in Neurology, 2015, 6(158): Enhancement of cortical network activity in vitro and promotion of GABAergic neurogenesis by stimulation with an electromagnetic field with 150 MHz carrier wave pulsed with an alternating 10 and 16 Hz modulation).

(71) Functional effects induced by MPP.sup.+ on neuronal network and prevention/rescue efficacy of the nanoparticles of the invention were evaluated through the above described parameters (also recapitulated for some of them in the Table 2 below).

(72) TABLE-US-00002 TABLE 2 Activity-describing parameters from the multiparametric data analysis in the following three categories: general activity, oscillatory behavior and synchronicity. General activity Spike rate Number of spikes per second, averaged over all spike trains recorded Oscillatory Burst rate SD Standard deviation of number of bursts per minute, behavior (bursting indicating the variability of burstiness of units within regularity) experimental episodes Burst area SD Standard deviation of area under the curve after (burst structure integrating the bursts, defined by burst duration, number regularity) of spikes in bursts, spike frequency in bursts. The parameter describes the variability of burst area within experimental episodes. Higher values indicate less regular burst structure Burst spikes' Standard deviation of spikes' number in bursts describes number SD the variation of a single unit spikes' number in bursts (bursting structure within experimental episodes. Lower values are a measure regularity) indicating lower degree of variation in burst spikes' number, therewith more regular structure. Synchronicity Simplex (spiking For spike simplex calculation, the spikes' trains are complexity) divided into timeframes of 1 ms bin-size. Within those bins, different units within the network generate spikes. All units exhibiting a spike are defined as one simplex. The outcome of the quantity of all simplex is the spike simplex. It is a measure for connectivity and complexity in neuronal network. Higher values reflect higher synchronicity among neurons.

(73) Values related to spontaneous native activity at day 21 were derived from 60 seconds bin data taken from a 30 minutes span after a 30 minutes stabilization of activity. Results (parameter values) were expressed as mean±SEM of independent networks. For each “Nanoparticles” group, at least 8 active wells, for the “Control” group, at least 30 active wells, and for the “MPP.sup.+” group, at least 26 active wells (“active” meaning wells with a sufficient number of electrodes measuring electrical activity) were included in the analysis. The absolute parameters' distributions were tested for normality and the statistical significance between groups was assessed via one-way ANOVA.

(74) FIGS. 8 and 9 present some representative parameters from the following categories: general activity, oscillatory behavior and synchronicity. These parameters characterize MPP.sup.+-induced functional effects and the prevention/rescue efficacy of the nanoparticles of the invention or of GDNF (i.e. the ability to prevent/rescue functional effects to a level similar to that of “Control” group).

(75) To evaluate compound effects, multiparametric results of a selection of 204 parameters were projected into a single parameter termed the “Effect Score”. It is a linear combination of selected features, transforming the datasets onto a vector with “Control” group at a mean value of “0” and “MPP.sup.+” group at a mean value of “1”. Calculation of the Z-factor of the Effect Score was performed through feature selection of 18 out of the 204 parameters measured, optimized to find the best discrimination between the “Control” group and the “MPP.sup.+” group (Kümmel A, et al., J Biomol Screen., 2010, 15(1), 95-101: Integration of multiple readouts into the z′ factor for assay quality assessment).

(76) The Effect Score analysis is shown in FIG. 10.

(77) The prevention/rescue efficacy of the nanoparticles of the invention is shown in Table 3.

(78) TABLE-US-00003 TABLE 3 Summary of Effect Score and prevention/rescue efficacy of nanoparticles of the invention (from examples 1, 2, 5 and 6) or of GDNF, on MPP.sup.+-induced effects on neuronal network. Prevention/ Group Effect Score rescue efficacy “Control” group 0 Reference (set at 100%) “MPP.sup.+” group 1  0% “Nanoparticles” 0 100%  group: biocompatible gold nanoparticles from example 1 “Nanoparticles” group: 0.22 78% biocompatible gold nanoparticles from example 2 “Nanoparticles” 0.49 51% group: biocompatible Si nanoparticles from example 5 “Nanoparticles” group: 0.39 61% biocompatible BaTiO.sub.3 nanoparticles from example 6 “Reference” group: 0.44 56% GDNF

(79) FIGS. 8, 9 and 10 and table 3 show that pretreatment of the neuronal network with nanoparticles of the invention prevents/rescues MPP.sup.+ induced functional effects on the neuronal network. Interestingly, the prevention/rescue efficacy is observed for parameters in categories related to oscillatory behavior and synchronicity and it can reach a level up to what is observed in “Control” group. These oscillatory behavior and synchronization parameters are typically monitored as a measure of altered network development. These parameters can advantageously be rescued in presence of the nanoparticles of the invention.

(80) These results highlight the ability of the nanoparticles described in the present application to prevent/rescue MPP.sup.+ induced functional effects on the neuronal network.

Example 8: Evaluation of the Effects of the Nanoparticles from Examples 1, 2, 3, 4, 5 and 6 on Amyloid Beta 1-42-Induced Functional Effects on Primary Mouse Neuronal Networks Using the Phenotypic MEA Screening Technology

(81) The rescue efficacy of nanoparticles of the invention was tested in vitro via MEAs on an amyloid beta 1-42 (Abeta 1-42)-induced model of Alzheimer's disease in frontal cortex cultures of mouse neurons. β-Amyloid peptide 1-42, the principal constituent of the neurotic plaques seen in Alzheimer disease (AD) patients, is known to trigger excess amount of glutamate in the synaptic cleft by inhibiting the astroglial glutamate transporter and to increase the intracellular Ca.sup.2+ level through enhancement of N-methyl-D-aspartate (NMDA) receptor activity. Other mechanisms leading to excitotoxicity may include the induction of oxidative stress and the direct impact of abeta on the glutamatergic NMDA receptor. Whatever the precise underlying pathogenic processes, overstimulation of the nerve cell by glutamate and intracellular calcium accumulation will eventually cause neuronal apoptosis, disrupt synaptic plasticity and as a result of such dysregulation will profoundly impair learning and memory function (Nyakas C. et al., Behavioural Brain Research, 2011, 221, 594-603: The basal forebrain cholinergic system in aging and dementia. Rescuing cholinergic neurons from neurotoxic amyloid-β42 with memantine.). Currently, FDA-approved anti AD drugs are limited to acetylcholinesterase (AChE) inhibitors and NMDA receptor antagonists. Traditional AChE inhibitors include donepezil which mainly act on the central action site of AChE.

(82) Material and Methods

(83) Primary Cell Culture

(84) Frontal cortex tissue was harvested from embryonic day 15/16 chr:NMRI mice (Charles River). Mice were sacrificed by cervical dislocation. Tissue was dissociated by enzymatic digestion (133.3 Kunitz units/ml DNase; 10 Units/ml Papain) and mechanical trituration, counted, vitality controlled, and plated in a 20 μl drop of DMEM containing laminin (10 μg/ml), 10% fetal bovine serum and 10% horse serum on MEAs. Cultures on MEAs were incubated at 37° C. in a 10% CO.sub.2 atmosphere until ready for use. Culture media were replenished two times a week with DMEM containing 10% horse serum. The developing co-cultures were treated with the mitosis inhibitors 5-fluoro-2′-deoxyuridine (25 μM) and uridine (63 μM) on day 5 after seeding to prevent further glial proliferation.

(85) To induce an Alzheimer-related functional phenotype, synthetic HFIP (hexafluoroisopropanol)-treated Abeta 1-42 peptides (HFIP treatment produces monomers of amyloid beta) were used at a sub-toxic dose (100 nM).

(86) In the “Nanoparticles” groups, wells were first treated with Abeta 1-42 (synthetic HFIP-treated Amyloid-beta 1-42 peptides) at T0 (T0 being at the end of the 28 days-in vitro culture period). Wells were then treated at T0+4 hours with the nanoparticles' suspension from examples 1 ([Au]=800 μM), 2 ([Au]=800 μM), 3 ([ZrO.sub.2]=800 μM), 4 ([ZrO.sub.2]=800 μM), 5 ([Si]=800 μM) and from example 6 ([BaTiO.sub.3]=2000 μM), in independent and parallel experiments. In the “Control” group, water was added to the wells at T0, and then at T0+4 hours. In the “Abeta” group, Abeta 1-42 was added to the wells at T0, and then water was added to the wells at T0+4 hours. In the “Reference” group, Abeta 1-42 was added to the wells at T0, and donepezil (300 nM) was added to the wells at T0+4 hours.

(87) Neuronal activity was recorded as follows (cf. FIG. 11): At T0, prior Abeta 1-42 addition (or water in the “Control” group) At T0 30 1 h, T0+2 h, T0+3 h, T0+4 h (prior addition of the nanoparticles in the «Nanoparticles» group, or donepezil in the “Reference” group, or “water” in the Control group), T0+5 h and T0+6 h.

(88) Values were derived from 60 seconds bin data taken from a 30 minutes span after a 30 minutes stabilization of activity.

(89) Microelectrode Array Neurochips

(90) The 48 wells microelectrodes array neurochips were purchased from Axion Biosystems Inc. These chips have 16 passive electrodes per well. The surface was coated for 1 hour with Polyethyleneimine (PEI, 50% in Borate buffer), washed and air-dried.

(91) Multichannel Recording and Multiparametric Data Analysis

(92) For the recording, the multichannel MAESTRO recording system from Axion Biosystems (USA) was used. For extracellular recording, 48-wells MEAs were placed into the MAESTRO recording station and maintained at 37° C. Recordings were made in DMEM/10% heat inactivated horse serum. The pH was maintained at 7.4 with a continuous stream of filtered, humidified airflow with 10% CO.sub.2. The action potentials, or “spikes”, were recorded in spike trains and were clustered in so-called “bursts”. Bursts were quantitatively described via direct spike train analysis using the programs Spike Wrangler and NPWaveX (both NeuroProof GmbH, Rostock, Germany). Bursts were defined by the beginning and end of short spike events.

(93) With a multiparametric high-content analysis of the network activity patterns, 204 activity-describing spike train parameters were extracted. These parameters allow obtaining a precise description of activity changes in the four categories as follows: general activity, burst structure, oscillatory behavior and synchronicity.

(94) Functional effects of amyloid beta 1-42 on neuronal network and rescue efficacy of functional effects of the neuronal network by the nanoparticles of the invention were evaluated through the above described parameters (also recapitulated for some of them in Table 4 below).

(95) TABLE-US-00004 TABLE 4 Activity-describing parameters from the multiparametric data analysis in the following four categories: general activity, burst structure, oscillatory behavior and synchronicity General activity Spike contrast Describes the occurrence or absence of spikes in neighboring time segments of the spike train, reflecting the variability in burstiness of units within experimental episodes Burst structure Burst area Area under the curve integrating the bursts, defined by burst duration, number of spikes in the bursts, spikes' frequency in bursts Oscillatory Burst shape Each burst is separated in three intervals by use of their behavior count3 CVtime gravitational centers. Count is the ratio of spikes of each of these intervals to the total number of spikes in each burst. This parameter describes the coefficient of variation over time of the distribution of spikes within bursts Synchronicity Burst shape fast Coefficient of variation over the network of the fraction of CVnet bursts characterized by fast onset of action. Higher values indicate a lower synchronicity of burst shape within experimental episode

(96) Values related to spontaneous native activity were derived from 60 seconds bin data taken from a 30 minutes span after a 30 min stabilization of activity. Results (parameter values) were expressed as mean±SEM of independent networks. For each “Nanoparticles” group, at least 9 active wells, for the “Control” group, at least 18 active wells, and for the “Abeta” group, at least 18 active wells (“active” meaning wells with a sufficient number of electrodes measuring electrical activity), were included in the analysis. The absolute parameters' distributions were tested for normality and the statistical significance between groups was assessed via one-way ANOVA.

(97) FIG. 12 shows some representative parameters from the following categories: general activity, burst structure, oscillatory behavior and synchronicity, characterizing Abeta 1-42 functional effects and the rescue efficacy allowed by the nanoparticles of the invention or by donepezil (i.e. ability to rescue functional effects to a level similar to that of the “Control” group).

(98) To evaluate compound effects, multiparametric results of a selection of 204 parameters were projected into a single parameter termed the “Effect Score”. It is a linear combination of selected features, transforming the datasets onto a vector with “Control” group at a mean value of “0” and “Abeta” group at a mean value of “1”. Calculation of the Z-factor of the Effect Score was performed through feature selection of 15 out of the 204 parameters measured, optimized to find the best discrimination between the “Control” group and the “Abeta” group (Kümmel A, et al., J Biomol Screen., 2010, 15(1), 95-101: Integration of multiple readouts into the z′ factor for assay quality assessment.).

(99) The Effect Score analysis is shown in FIG. 13.

(100) The rescue efficacy of the nanoparticles of the invention is shown in Table 5.

(101) TABLE-US-00005 TABLE 5 Summary of Effect Score and rescue efficacy of the nanoparticles of the invention or of donepezil, on Abeta 1-42-induced effects on the neuronal network. Group Effect Score Rescue efficacy “Control” group 0 Reference (set at 100%) “Abeta” group 1  0% “Nanoparticles” 0.24 76% group: biocompatible gold nanoparticles from example 1 “Nanoparticles” group: 0.61 39% biocompatible gold nanoparticles from example 2 “Nanoparticles” group: 0.40 60% biocompatible zirconium oxide nanoparticles from example 3 “Nanoparticles” group: 0.49 51% biocompatible zirconium oxide nanoparticles from example 4 “Nanoparticles” group: 0.46 54% biocompatible silicon nanoparticles from example 5 “Nanoparticles” group: 0.36 64% biocompatible BaTiO.sub.3 nanoparticles from example 5 Donepezil 0.46 54%

(102) FIGS. 12 and 13 and Table 5 show that treatment of the neuronal network with the nanoparticles of the invention rescues Abeta 1-42 induced functional effects on the neuronal network. The rescue efficacy is observed for parameters in categories related to oscillatory behavior and synchronicity and it can advantageously reach a level up to what is observed in the “Control” group. These oscillatory behavior and synchronization parameters are classically evaluated to detect an altered network development. Oscillatory behavior and synchronization can be rescued in presence of the nanoparticles of the invention.

(103) These results highlight the advantageous performances of the nanoparticles described in the present application in rescuing Abeta 1-42 induced functional effects on the neuronal network.

Example 9: Synthesis and Physico-Chemical Characterization of Gold Nanoparticles with Different Sizes Having a Neutral Surface Charge

(104) Gold nanoparticles are obtained by reduction of gold chloride with sodium citrate in aqueous solution. Protocol was adapted from G. Frens Nature Physical Science 241 (1973) 21.

(105) In a typical experiment, HAuCl.sub.4 solution is heated to boiling. Subsequently, sodium citrate solution is added. The resulting suspension is maintained under boiling for an additional period of 5 minutes. The nanoparticle size is adjusted from about 15 nm up to about 110 nm by carefully modifying the citrate versus gold precursor ratio (cf. Table 6).

(106) The as prepared gold nanoparticles suspension is then concentrated using an ultrafiltration device (Amicon stirred cell model 8400 from Millipore) with cellulose membrane having an appropriate molecular weight cut-off (MWCO) and filtered through a 0.22 μm cutoff membrane filter (PES membrane from Millipore) under laminar hood.

(107) A surface coating is performed using α-methoxy-ω-mercaptopoly(ethylene glycol) 20 kDa (“thiol-PEG20 kDa”). A sufficient amount of “thiol-PEG 20 kDa” is added to the nanoparticles' suspension to obtain a monolayer coverage on the gold nanoparticle surface. pH is adjusted between 6.8 and 7.4, and the nanoparticles' suspension is stirred overnight. Excess of thiol-PEG 20 kDa is removed using a ultrafiltration centrifugal filter (Vivaspin from Sartorius or Amicon Ultra from Merck Millipore) with an appropriate MWCO membrane under laminar hood and the final suspension is stored at 4° C. Particle size is determined using transmission electronic microscopy by counting at least 200 nanoparticles, taking the largest nanoparticle dimension for size measurement. The median largest size of the core of the nanoparticles or nanoparticles' aggregates of the population and the size of the core of the nanoparticles or nanoparticles' aggregates representing the 30%-70% percentile of the population of nanoparticles and nanoparticles' aggregates are reported in table 6 together with the concentration of gold ([Au]) measured by Inductively-Coupled Optical Emission Spectroscopy (ICP-OES) and the zeta potential determined by measuring the electrophoretic mobility of the nanoparticles (Nano-Zetasizer, Malvern) by diluting the nanoparticles' suspension in a NaCl solution at 1 mM, at a gold concentration ([Au]) between 0.01 and 0.05 g/L and at pH about 7.

(108) TABLE-US-00006 TABLE 6 Median Synthesis largest size of Ratio the core of the 30%-70% Zeta Citrate/Au nanoparticle percentile potential [Au] mg/mL Samples (mol/mol) (nm) (nm) (mV) (by ICP-OES) GOLD-15 3.5 15 14-16 −3 3.6 GOLD-30 1.96 34 30-37 −3 3.9 GOLD-45 1.26 45 42-49 −4 3.6 Same nanoparticles core as nanoparticles from examples 1 & 2 GOLD-80 0.8 83 77-93 −2 3.4 GOLD-110 0.7 108  91-123 −2 2.9

(109) FIG. 14 shows representative transmission electronic microscopy (TEM) images of the gold nanoparticles described in table 6.

Example 10. Evaluation of the Prevention/Rescue Efficacy of Nanoparticles GOLD-15 and GOLD-45 from Example 9, on MPP.SUP.+.-Induced Neuronal Networks Using the Phenotypic MEA Screening Technology

(110) The prevention/rescue efficacy of nanoparticles of the invention was tested on MPP.sup.+-treated mouse ventral midbrain/cortex co-cultures, cultured on a 48-wells MEA for 3 weeks. The evaluation of the nanoparticles' prevention/rescue effect was performed via the measurement of the extracellular electrical activity of the co-culture of neurons plated on Microelectrode Array (MEA) chips. The induction of a parkinsonian phenotype in mouse neurons in vitro was performed with 1-methyl-4-phenyl pyridinium iodide (MPP.sup.+).

(111) Material and Methods

(112) Primary Cell Culture, Treatment Conditions

(113) Midbrain and frontal cortex tissue was harvested from embryonic day 14.5 chr:NMRI mice (Charles River). Mice were sacrificed by cervical dislocation. Tissue was dissociated by enzymatic digestion (133.3 Kunitz units/m1 DNase; 10 Units/ml Papain) and mechanical trituration, counted, vitality controlled, and plated in a 20 μl drop of DMEM containing laminin (10 μg/ml), 10% fetal bovine serum and 10% horse serum on MEAs. Cultures on MEAs were incubated at 37° C. in a 10% CO.sub.2 atmosphere until ready for use. Culture media were replenished two times a week with DMEM containing 10% horse serum.

(114) In the “Nanoparticles” groups, wells were treated at day 7 with nanoparticles' suspension ([Au]=310 +/−40 μM) from example 9 (GOLD-15 and GOLD-45), followed by 20 μM of MPP.sup.+ at day 8. In the “Control” group, water was added to the wells at day 7, followed by water addition at day 8. In the “MPP.sup.+” group, water was added to the wells at day 7, followed by 20 μM of MPP.sup.+ at day 8.

(115) Twenty-four (24) hours following MPP.sup.+ (or water for “Control” group) addition, the medium was changed to achieve wash out of MPP.sup.+. Medium was subsequently changed twice per week. At day 21, 120 minutes of neuronal activity were recorded, and 30 minutes of stable activity were analyzed.

(116) Microelectrode Array Neurochips

(117) The 48 wells microelectrode array neurochips were purchased from Axion Biosystems Inc. These chips have 16 passive electrodes per well. The surface was coated for 1 hour with Polyethyleneimine (PEI, 50% in Borate buffer), washed and air-dried.

(118) Multichannel Recording and Multiparametric Data Analysis

(119) For the recording, the multichannel recording system from Axion Biosystems (USA) was used. For extracellular recording, 48-wells MEAs were placed into the MAESTRO recording station and maintained at 37° C. Recordings were made in DMEM/10% heat inactivated horse serum. The pH was maintained at 7.4 with a continuous stream of filtered, humidified airflow with 10% CO.sub.2.

(120) Each unit represents the activity originating from one neuron recorded at one electrode. Units are separated at the beginning of the recording. For each unit, action potentials (i.e. spikes), were recorded as spike trains, which are clustered in so-called “bursts”. Bursts were quantitatively described via direct spike train analysis using the programs Spike Wrangler and NPWaveX (both NeuroProof GmbH, Rostock, Germany). Bursts were defined by the beginning and end of short spike events.

(121) With a multiparametric high-content analysis of the network activity patterns, 204 activity-describing spike train parameters were extracted. These parameters allow obtaining a precise description of activity changes in the following four categories: general activity, burst structure, oscillatory behavior and synchronicity.

(122) Functional effects induced by MPP on neuronal network and prevention/rescue efficacy of the nanoparticles of the invention were evaluated through the above described parameters.

(123) Values related to spontaneous native activity at day 21 were derived from 60 seconds bin data taken from a 30 minutes span after a 30 minutes stabilization of activity. Results (parameter values) were expressed as mean±SEM of independent networks. For each “Nanoparticles” group, the “Control” group, and the “MPP.sup.+” group, at least 19 active wells (“active” meaning wells with a sufficient number of electrodes measuring electrical activity) were included in the analysis. The absolute parameters' distributions were tested for normality and the statistical significance between groups was assessed via one-way ANOVA.

(124) To evaluate compound effects, multiparametric results of a selection of 204 parameters were projected into a single parameter termed the “Effect Score”. It is a linear combination of selected features, transforming the datasets onto a vector with “Control” group at a mean value of “0” and “MPP.sup.+” group at a mean value of “1”. Calculation of the Z-factor of the Effect Score was performed through feature selection of 20 out of the 204 parameters measured, optimized to find the best discrimination between the “Control” group and the “MPP.sup.+” group (Kümmel A, et al., J Biomol Screen., 2010, 15(1), 95-101: Integration of multiple readouts into the z′ factor for assay quality assessment).

(125) The Effect Score analysis is shown in FIG. 15.

(126) The prevention/rescue efficacy of the nanoparticles of the invention is shown in Table 7.

(127) TABLE-US-00007 TABLE 7 Summary of Effect Score and prevention/rescue efficacy of nanoparticles of the invention (GOLD-15 and GOLD-45 from examples 9), on MPP.sup.+-induced effects on neuronal network. Prevention/ Group Effect Score rescue efficacy “Control” group 0 Reference (set at 100%) “MPP.sup.+” group 1  0% “Nanoparticles” 0.14 86% group: biocompatible gold nanoparticles GOLD-45 from example 9 “Nanoparticles” group: 0.46 54% biocompatible gold nanoparticles GOLD- 15 from example 9

(128) FIG. 15 and table 7 show that pretreatment of the neuronal network with nanoparticles of the invention prevents/rescues MPP.sup.+ induced functional effects on the neuronal network. Interestingly, the gold nanoparticles with the median largest size of the core of the nanoparticles of the population equal to 15 nm are less efficient in preventing/rescuing MPP induced functional effects on the neuronal network than are gold nanoparticles having a median largest size of the core of the nanoparticles of the population equal to 45 nm.

(129) These results highlight the ability of both gold nanoparticles to prevent/rescue MPP.sup.+ induced functional effects on the neuronal network, with gold nanoparticles with median largest size of 45 nm being more efficient than gold nanoparticles with median largest size of 15 nm.

Example 11. Synthesis of Nanoparticles Prepared with a Conductor Material: Poly(3,4-Ethylenedioxythiophene) Nanoparticles (PEDOT Nanoparticles) Having a Negative Surface Charge

(130) Poly(3,4-ethylenedioxythiophene) nanoparticles (PEDOT nanoparticles) dispersion in water (1.1% w/w) were obtained from Sigma (sigma 675288) and used as such.

(131) The zeta potential was determined by measuring the electrophoretic mobility of the nanoparticles (Nano-Zetasizer, Malvern) by diluting the nanoparticles' suspension in a NaCl solution at 1 mM at pH 7.3 (final PEDOT concentration: 1 g/L). The zeta potential at pH 7.3 was found equal to −53 mV.

(132) The median largest dimension of the nanoparticles or nanoparticles' aggregates of the population and the size of the core of the nanoparticles or nanoparticles' aggregates representing the 30%-70% percentile of the population of nanoparticles and nanoparticles' aggregates were evaluated using scanning electron microscopy (SEM) and were equal to 408 nm and 311 nm-518 nm respectively (56 nanoparticles were counted and their largest dimension was measured).

Example 12. Evaluation of the Prevention/Rescue Efficacy of PEDOT Nanoparticles from Example 11 on MPP.SUP.+.-Induced Neuronal Networks Using the Phenotypic MEA Screening Technology

(133) The prevention/rescue efficacy of nanoparticles of the invention was tested on MPP.sup.+-treated mouse ventral midbrain/cortex co-cultures, cultured on a 48-wells MEA for 3 weeks. The evaluation of the nanoparticles' prevention/rescue effect was performed via the measurement of the extracellular electrical activity of the co-culture of neurons plated on Microelectrode Array (MEA) chips.

(134) The induction of a parkinsonian phenotype in mouse neurons in vitro was performed with 1-methyl-4-phenyl pyridinium iodide (MPP.sup.+).

(135) Material and Methods

(136) Primary Cell Culture, Treatment Conditions

(137) Midbrain and frontal cortex tissue was harvested from embryonic day 14.5 chr:NMRI mice (Charles River). Mice were sacrificed by cervical dislocation. Tissue was dissociated by enzymatic digestion (133.3 Kunitz units/ml DNase; 10 Units/ml Papain) and mechanical trituration, counted, vitality controlled, and plated in a 20 μl drop of DMEM containing laminin (10 μg/ml), 10% fetal bovine serum and 10% horse serum on MEAs. Cultures on MEAs were incubated at 37° C. in a 10% CO.sub.2 atmosphere until ready for use. Culture media were replenished two times a week with DMEM containing 10% horse serum.

(138) In the “Nanoparticles” groups, wells were treated at day 7 with nanoparticles' suspension ([PEDOT]=500 μM) from example 11, followed by 20 μM of MPP.sup.+ at day 8. In the “Control” group, water was added to the wells at day 7, followed by water addition at day 8. In the “MPP.sup.+” group, water was added to the wells at day 7, followed by 20 μM of MPP.sup.+ at day 8.

(139) Twenty-four (24) hours following MPP.sup.+ (or water for “Control” group) addition, the medium was changed to achieve wash out of MPP.sup.+. Medium was subsequently changed twice per week.

(140) At day 21, 120 minutes of neuronal activity were recorded, and 30 minutes of stable activity were analyzed.

(141) Microelectrode Array Neurochips

(142) The 48 wells microelectrode array neurochips were purchased from Axion Biosystems Inc. These chips have 16 passive electrodes per well. The surface was coated for 1 hour with Polyethyleneimine (PEI, 50% in Borate buffer), washed and air-dried.

(143) Multichannel Recording and Multiparametric Data Analysis

(144) For the recording, the multichannel MAESTRO recording system by Axion Biosystems (USA) was used. For extracellular recording, 48-wells MEAs were placed into the MAESTRO recording station and maintained at 37° C. Recordings were made in DMEM/10% heat inactivated horse serum. The pH was maintained at 7.4 with a continuous stream of filtered, humidified airflow with 10% CO.sub.2.

(145) Each unit represents the activity originating from one neuron recorded at one electrode. Units are separated at the beginning of the recording. For each unit, action potentials (i.e. spikes) were recorded as spike trains which are clustered in so-called “bursts”. Bursts were quantitatively described via direct spike train analysis using the programs Spike Wrangler and NPWaveX (both NeuroProof GmbH, Rostock, Germany). Bursts were defined by the beginning and end of short spike events.

(146) With a multiparametric high-content analysis of the network activity patterns, 204 activity-describing spike train parameters were extracted. These parameters allow obtaining a precise description of activity changes in the following four categories: general activity, burst structure, oscillatory behavior and synchronicity.

(147) Functional effects induced by MPP on neuronal network and prevention/rescue efficacy of the nanoparticles of the invention were evaluated through the above described parameters.

(148) Values related to spontaneous native activity at day 21 were derived from 60 seconds bin data taken from a 30 minutes span after a 30-90 minutes stabilization of activity. Results (parameter values) were expressed as mean±SEM of independent networks. For the “Nanoparticles” group, at least 5 active wells, for the “Control” group, at least 20 active wells, and for the “MPP.sup.+” group, at least 20 active wells (“active” meaning wells with a sufficient number of electrodes measuring electrical activity) were included in the analysis. The absolute parameters' distributions were tested for normality and the statistical significance between groups was assessed via one-way ANOVA.

(149) To evaluate compound effects, multiparametric results of a selection of 204 parameters were projected into a single parameter termed the “Effect Score”. It is a linear combination of selected features, transforming the datasets onto a vector with “Control” group at a mean value of “0” and “MPP.sup.+” group at a mean value of “1”. Calculation of the Z-factor of the Effect Score was performed through feature selection of 20 out of the 204 parameters measured, optimized to find the best discrimination between the “Control” group and the “MPP.sup.+” group (Kümmel A, et al., J Biomol Screen., 2010, 15(1), 95-101: Integration of multiple readouts into the z′ factor for assay quality assessment).

(150) The Effect Score analysis is shown in FIG. 17.

(151) The prevention/rescue efficacy of the nanoparticles of the invention is shown in Table 8.

(152) TABLE-US-00008 TABLE 8 Summary of Effect Score and prevention/rescue efficacy of PEDOT nanoparticles of the invention (from example 11), on MPP.sup.+-induced effects on neuronal network. Prevention/ Group Effect Score rescue efficacy “Control” group 0 Reference (set at 100%) “MPP.sup.+” group 1  0% “Nanoparticles” 0.59 41% group: biocompatible PEDOT nanoparticles from example 11

(153) FIG. 17 and table 8 show that pretreatment of the neuronal network with PEDOT nanoparticles of the invention prevents/rescues MPP.sup.+ induced functional effects on the neuronal network.

(154) These results highlight the ability of the nanoparticles described in the present application to prevent/rescue MPP.sup.+ induced functional effects on the neuronal network.

Example 13. Synthesis of Nanoparticles Prepared with an Insulator Material Having a Low Relative Dielectric Constant Equal to or Below 100: Synthesis of Hafnium Oxide Nanoparticles Coated with a Biocompatible Coating Having a Negative Surface Charge

(155) Hafnium oxide (HfO.sub.2) nanoparticles were synthesized by precipitation of Hafnium chloride (HfCl.sub.4) with tetramethyl ammonium hydroxide (TMAOH) at a basic pH. The resulting suspension was transferred in an autoclave and heated at a temperature above 110° C. After cooling, the suspension was washed with deionized water and acidified.

(156) Surface functionalization was performed using sodium hexametaphosphate. A sufficient mass of sodium hexametaphosphate was added to the nanoparticles' suspension to reach at least half a monolayer coverage (2.5 molecules/nm.sup.2) on the surface. The nanoparticles' suspension was stirred overnight and pH was subsequently adjusted to 7.