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Secure extraction of Personally Identifiable Information (PII) from Electronic Health Records (EHRs) presents significant privacy and security challenges. This study explores the application of Federated Learning (FL) to overcome these challenges within the context of French EHRs. By utilizing a multilingual BERT model in an FL simulation involving 20 hospitals, each represented by a unique medical department or pole, we compared the performance of two setups: individual models, where each hospital uses only its own training and validation data without engaging in the FL process, and federated models, where multiple hospitals collaborate to train a global FL model. Our findings demonstrate that FL models not only preserve data confidentiality but also outperform the individual models. In fact, the Global FL model achieved an F1 score of 75,7%, slightly comparable to that of the Centralized approach at 78,5%. This research underscores the potential of FL in extracting PIIs from EHRs, encouraging its broader adoption in health data analysis.
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Segurança Computacional , Confidencialidade , Registros Eletrônicos de Saúde , Aprendizado de Máquina , França , Humanos , Registros de Saúde PessoalRESUMO
The imidazole nucleus represents a significant group of heterocyclic molecules with diverse significance in the modern world due to its exploration potential and various pharmacological applications. The relevance of imidazole and its derivatives has gained popularity in recent years, especially in the production of commercial drugs and the treatment of various conditions. The imidazole nucleus is present in many natural compounds and widely distributed in essential amino acids, such as l-histidine, whose derivatives exhibit powerful pharmacological properties. In this review, we delve into the historical timeline and development of synthetic pathways for tri- and tetra-substituted imidazoles used in the renowned Radziszewski reaction. Furthermore, we explore various bacteriological applications documented in the literature, as well as current advances in preclinical approaches to imidazole-based drug discovery. Tri- or tetra-substituted imidazole derivatives show strong potential for new synthesis methods, such as reflux or microwave, as well as various biological activities.
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BACKGROUND: Electronic health records (EHRs) contain valuable information for clinical research; however, the sensitive nature of healthcare data presents security and confidentiality challenges. De-identification is therefore essential to protect personal data in EHRs and comply with government regulations. Named entity recognition (NER) methods have been proposed to remove personal identifiers, with deep learning-based models achieving better performance. However, manual annotation of training data is time-consuming and expensive. The aim of this study was to develop an automatic de-identification pipeline for all kinds of clinical documents based on a distant supervised method to significantly reduce the cost of manual annotations and to facilitate the transfer of the de-identification pipeline to other clinical centers. METHODS: We proposed an automated annotation process for French clinical de-identification, exploiting data from the eHOP clinical data warehouse (CDW) of the CHU de Rennes and national knowledge bases, as well as other features. In addition, this paper proposes an assisted data annotation solution using the Prodigy annotation tool. This approach aims to reduce the cost required to create a reference corpus for the evaluation of state-of-the-art NER models. Finally, we evaluated and compared the effectiveness of different NER methods. RESULTS: A French de-identification dataset was developed in this work, based on EHRs provided by the eHOP CDW at Rennes University Hospital, France. The dataset was rich in terms of personal information, and the distribution of entities was quite similar in the training and test datasets. We evaluated a Bi-LSTM + CRF sequence labeling architecture, combined with Flair + FastText word embeddings, on a test set of manually annotated clinical reports. The model outperformed the other tested models with a significant F1 score of 96,96%, demonstrating the effectiveness of our automatic approach for deidentifying sensitive information. CONCLUSIONS: This study provides an automatic de-identification pipeline for clinical notes, which can facilitate the reuse of EHRs for secondary purposes such as clinical research. Our study highlights the importance of using advanced NLP techniques for effective de-identification, as well as the need for innovative solutions such as distant supervision to overcome the challenge of limited annotated data in the medical domain.
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Aprendizado Profundo , Humanos , Anonimização de Dados , Registros Eletrônicos de Saúde , Análise Custo-Benefício , Confidencialidade , Processamento de Linguagem NaturalRESUMO
In this study, (E)-2-phenyl-N-(thiophen-2-ylmethylene)imidazo[1,2-a]pyrimidin-3-amine (3) is synthesized, and detailed spectral characterizations using 1H NMR, 13C NMR, mass, and Fourier transform infrared (FT-IR) spectroscopy were performed. The optimized geometry was computed using the density functional theory method at the B3LYP/6-311++G(d,p) basis set. The theoretical FT-IR and NMR (1H and 13C) analysis are agreed to validate the structural assignment made for (3). Frontier molecular orbitals, molecular electrostatic potential, Mulliken atomic charge, electron localization function, localized orbital locator, natural bond orbital, nonlinear optical, Fukui functions, and quantum theory of atoms in molecules analyses are undertaken and meticulously interpreted, providing profound insights into the molecular nature and behaviors. In addition, ADMET and drug-likeness studies were carried out and investigated. Furthermore, molecular docking and molecular dynamics simulations have been studied, indicating that this is an ideal molecule to develop as a potential vascular endothelial growth factor receptor-2 inhibitor.
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In the present work, a new series of imidazo[1,2-a]pyrimidine Schiff base derivatives have been obtained using an easy and conventional synthetic route. The synthesized compounds were spectroscopically characterized using 1H, 13C NMR, LC-MS(ESI), and FT-IR techniques. Green metric calculations indicate adherence to several green chemistry principles. The energy of Frontier Molecular Orbitals (FMO), Molecular Electrostatic Potential (MEP), Quantum Theory of Atoms in Molecules (QTAIM), and Reduced Density Gradient (RDG) were determined by the Density Functional Theory (DFT) method at B3LYP/6-31 G (d, p) as the basis set. Moreover, molecular docking studies targeting the human ACE2 and the spike, key entrance proteins of the severe acute respiratory syndrome coronavirus-2 were carried out along with hACE2 natural ligand Angiotensin II, the MLN-4760 inhibitor as well as the Cannabidiolic Acid CBDA which has been demonstrated to bind to the spike protein and block cell entry. The molecular modeling results showed auspicious results in terms of binding affinity as the top-scoring compound exhibited a remarkable affinity (-9.1 and -7.3 kcal/mol) to the ACE2 and spike protein respectively compared to CBDA (-5.7 kcal/mol), the MLN-4760 inhibitor (-7.3 kcal/mol), and angiotensin II (-9.2 kcal/mol). These findings suggest that the synthesized compounds may potentially act as effective entrance inhibitors, preventing the SARS-CoV-2 infection of human cells. Furthermore, in silico, ADMET, and drug-likeness prediction expressed promising drug-like characteristics.
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Pharmaceuticals, especially antibiotics, constitute an important group of aquatic contaminants given their environmental impact. Specifically, tetracycline antibiotics (TCs) are produced in great amounts for the treatment of bacterial infections in both human and veterinary medicine. Several studies have shown that, among all antibiotics, oxytetracycline hydrochloride (OTC HCl) is one of the most frequently detected TCs in soil and surface water. The results of the photocatalytic degradation of OTC HCL in aqueous suspensions (30 mg·L-1) of 0.5 wt.% cobalt-doped TiO2 catalysts are reported in this study. The heterogeneous Co-TiO2 photocatalysts were synthesized by two different solvothermal methods. Evonik Degussa Aevoxide P25 and self-prepared TiO2 modified by the same methods were used for comparison. The synthesized photocatalysts were characterized by X-ray powder diffraction (XRD), Raman spectroscopy, transmission electron microscopy (TEM), UV/vis diffuse reflectance spectroscopy (DRS), and N2 adsorption (BET) for specific surface area determination. The XRD and Raman results suggest that Ti4+ was substituted by Co2+ in the TiO2 crystal structure. Uv/visible spectroscopy of Co-TiO2-R showed a substantial redshift in comparison with bare TiO2-R. The photocatalytic performance of the prepared photocatalysts in OTC HCL degradation was investigated employing Uv/vis spectroscopy and high-performance liquid chromatography (HPLC). The observed initial reaction rate over Co-TiO2-R was higher compared with that of Co-TiO2-HT, self-prepared TiO2, and the commercial P25. The enhanced photocatalytic activity was attributed to the high surface area (153 m2·g-1) along with the impurity levels within the band gap (2.93 eV), promoting the charge separation and improving the charge transfer ability. From these experimental results, it can be concluded that Co-doping under reflux demonstrates better photocatalytic performances than with the hydrothermal treatment.
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Antibacterianos/química , Cobalto/química , Nanopartículas/química , Oxitetraciclina/química , Titânio/química , Poluentes Químicos da Água/química , Catálise , Luz , Microscopia Eletrônica de Transmissão , Nanopartículas/ultraestrutura , Oxirredução , Análise Espectral Raman , Raios Ultravioleta , Purificação da Água/instrumentação , Purificação da Água/métodos , Difração de Raios XRESUMO
RATIONALE: 5-Amino-4-chloro-2-phenyl-3(2H)-pyridazone (Chloridazon) is an important systemic herbicide; its transformation by different Advanced Oxidation Processes could result in the formation of different and complex products. These products, that need to be identified, may present a more toxic effect than the parent compound. METHODS: The exact and unequivocal structural characterization of the detected by-products of Chloridazon was performed by in-depth analysis of the liquid chromatography/negative electrospray ionization tandem mass spectrometric (LC/ESI+/MS(2) ) fragmentation. Such a technique is a powerful and sensitive analytical tool to study environmental issues. The reactive radicals that induce the degradation of Chloridazon were generated by selective excitation of titanium dioxide as photocatalyst and also by UV photolysis of hydrogen peroxide. RESULTS: Several processes are initiated by hydroxyl radical reaction with Chloridazon. Among them (i) hydroxylation of the phenyl group at the ortho, meta and para positions; (ii) a second hydroxylation process as a secondary reaction is also obtained within the phenyl moiety; (iii) scission of the phenyl-N bond through a hydrolysis process; and (iv) a substitution of the chlorine atom by a hydroxyl group. CONCLUSIONS: LC/ESI-Q-TOFMS appeared to be a valuable and precise tool for structural elucidation of the unknown by-products that were generated during hydroxyl radical reactions with Chloridazon. Several hydroxylated and dihydroxylated isomers were identified together with dechlorinated and bridge opening products.