Modification of brain conductivity in human focal epilepsy: A model-based estimation from stereoelectroencephalography.

OBJECTIVE: We have developed a novel method for estimating brain tissue electrical conductivity using low-intensity pulse stereoelectroencephalography (SEEG) stimulation coupled with biophysical modeling. We evaluated the hypothesis that brain conductivity is correlated with the degree of epileptogenicity in patients with drug-resistant focal epilepsy. METHODS: We used bipolar low-intensity biphasic pulse stimulation (.2 mA) followed by a postprocessing pipeline for estimating brain conductivity. This processing is based on biophysical modeling of the electrical potential induced in brain tissue between the stimulated contacts in response to pulse stimulation. We estimated the degree of epileptogenicity using a semi-automatic method quantifying the dynamic of fast discharge at seizure onset: the epileptogenicity index (EI). We also investigated how the location of stimulation within specific anatomical brain regions or within lesional tissue impacts brain conductivity. RESULTS: We performed 1034 stimulations of 511 bipolar channels in 16 patients. We found that brain conductivity was lower in the epileptogenic zone (EZ; unpaired median difference = .064, p < .001) and inversely correlated with the epileptogenic index value (p < .001, Spearman rho = -.32). Conductivity values were also influenced by anatomical site, location within lesion, and delay between SEEG electrode implantation and stimulation, and had significant interpatient variability. Mixed model multivariate analysis showed that conductivity is significantly associated with EI (F = 13.45, p < .001), anatomical regions (F = 5.586, p < .001), delay since implantation (F = 14.71, p = .003), and age at SEEG (F = 6.591, p = .027), but not with the type of lesion (F = .372, p = .773) or the delay since last seizure (F = 1.592, p = .235). SIGNIFICANCE: We provide a novel model-based method for estimating brain conductivity from SEEG low-intensity pulse stimulations. The brain tissue conductivity is lower in EZ as compared to non-EZ. Conductivity also varies significantly across anatomical brain regions. Involved pathophysiological processes may include changes in the extracellular space (especially volume or tortuosity) in epileptic tissue.

Tuning the Emission of Homometallic DyIII, TbIII, and EuIII 1-D Coordination Polymers with 2,6-Di(1H-1,2,4-triazole-1-yl-methyl)-4-R-phenoxo Ligands: Sensitization through the Singlet State.

This work reports the structural characterization and photophysical properties of DyIII, TbIII, and EuIII coordination polymers with two phenoxo-triazole-based ligands [2,6-di(1H-1,2,4-triazole-1-yl-methyl)-4-R-phenoxo, LRTr (R = CH3; Cl)]. These ligands permitted us to obtain isostructural polymers, described as a 1D double chain, with LnIII being nona-coordinated. The energies of the ligand triplet (T1) states were estimated using low-temperature time-resolved emission spectra of YIII analogues. Compounds with LClTr present higher emission intensity than those with LMeTr. The emission of TbIII compounds was not affected by the different excitation wavelengths used and was emitted in the pure green region. In contrast, DyLMeTr emits in the blue-to-white region, while the luminescence of DyLClTr remains in the white region for all excitation wavelengths. On the other hand, EuIII compounds emit in the blue (ligand) or red region (EuIII) depending on the substituent of the phenoxo moiety and excitation wavelength. Theoretical calculations were employed to determine the excited states of the ligands by using time-dependent density functional theory. These calculations aided in modeling the intramolecular energy transfer and rationalizing the optical properties and demonstrated that the sensitization of the LnIII ions is driven via S1 → LnIII, a process that is less common as compared to T1 → LnIII.

A comparative dataset: Bridging COVID-19 and other diseases through epistemonikos and CORD-19 evidence.

The COVID-19 pandemic has underlined the need for reliable information for clinical decision-making and public health policies. As such, evidence-based medicine (EBM) is essential in identifying and evaluating scientific documents pertinent to novel diseases, and the accurate classification of biomedical text is integral to this process. Given this context, we introduce a comprehensive, curated dataset composed of COVID-19-related documents. This dataset includes 20,047 labeled documents that were meticulously classified into five distinct categories: systematic reviews (SR), primary study randomized controlled trials (PS-RCT), primary study non-randomized controlled trials (PS-NRCT), broad synthesis (BS), and excluded (EXC). The documents, labeled by collaborators from the Epistemonikos Foundation, incorporate information such as document type, title, abstract, and metadata, including PubMed id, authors, journal, and publication date. Uniquely, this dataset has been curated by the Epistemonikos Foundation and is not readily accessible through conventional web-scraping methods, thereby attesting to its distinctive value in this field of research. In addition to this, the dataset also includes a vast evidence repository comprising 427,870 non-COVID-19 documents, also categorized into SR, PS-RCT, PS-NRCT, BS, and EXC. This additional collection can serve as a valuable benchmark for subsequent research. The comprehensive nature of this open-access dataset and its accompanying resources is poised to significantly advance evidence-based medicine and facilitate further research in the domain.

New Highly Charged Iron(III) Metal-Organic Cube Stabilized by a Bulky Amine.

In this work, we report a new octanuclear cluster based on FeIII and the ligand 1H-imidazole-4,5-dicarboxylic acid, [Et3NH]12[Fe8(IDC)12]·10DMF·13H2O (1), with a metal core containing eight FeIII connected by only one type of organic ligand. A peak at 573 m/z in the mass spectra of the compound suggests the adduct species {[Fe8(IDC)12]+8H}4-. By X-ray photoelectron spectroscopy, the oxidation state of the iron cation was confirmed to be 3+, also identifying the presence of a quaternary nitrogen species, which act as a countercation of the anionic metal core [Fe8(IDC)12]12-. Mössbauer spectra recorded at different temperatures show an isomer shift and quadrupole splitting parameters that confirm the existence of only FeIII-HS in the structure of 1. X-ray analysis reveals that compound 1 crystallizes in the orthorhombic system space group Ibam, confirming a molecular cluster structure with an almost regular cube as geometry, with the FeIII atoms located at the corners of the cube and connected by µ-1κ2 N,O:2κ2 N',O‴-IDC3- bridges. Additionally, the magnetic measurements reveal a weak antiferromagnetic coupling in the Fe8 III coordination cluster (J = -3.8 cm-1). To the best of our knowledge, 1 is the first member of the family of cubes assembled with 1H-imidazole-4,5-dicarboxylic acid and FeIII cation, exhibiting high pH stability over a broad pH range, making it an ideal candidate for the design of supramolecular structures and metal-organic frameworks.

Biophysical Modeling for Brain Tissue Conductivity Estimation Using SEEG Electrodes.

OBJECTIVE: We aimed at providing an accurate estimation of human brain tissue electrical conductivity in clinico, using local, low-intensity pulsed stimulation. METHODS: Using the quasi-static approximation of Maxwell equations, we derived an analytical model of the electric field generated by intracerebral stereotactic-EEG (SEEG) electrodes. We coupled this electric field model with a model of the electrode-electrolyte interface to provide an explicit, analytical expression of brain tissue conductivity based on the recorded brain tissue response to pulse stimulation. RESULTS: We validated our biophysical model using saline solutions calibrated in electrical conductivity, rat brain tissue, and electrophysiological data recorded in clinico from two epileptic patients during SEEG. CONCLUSION: This new model-based method offers a fast and reliable estimation of brain tissue electrical conductivity by accounting for contributions from the electrode-electrolyte interface. SIGNIFICANCE: This method outperforms standard bioimpedance measurements since it provides absolute (as opposed to relative) changes in brain tissue conductivity. Application for diagnosis is envisioned since conductivity values strongly differ when estimated in the healthy versus hyperexcitable brain tissue.