University of Abou Bekr Belkaïd

Importance: Mammography screening currently relies on subjective human interpretation. Artificial intelligence (AI) advances could be used to increase mammography screening accuracy by reducing missed cancers and false positives. Objective: To evaluate whether AI can overcome human mammography interpretation limitations with a rigorous, unbiased evaluation of machine learning algorithms. Design, Setting, and Participants: In this diagnostic accuracy study conducted between September 2016 and November 2017, an international, crowdsourced challenge was hosted to foster AI algorithm development focused on interpreting screening mammography. More than 1100 participants comprising 126 teams from 44 countries participated. Analysis began November 18, 2016. Main Outcomes and Measurements: Algorithms used images alone (challenge 1) or combined images, previous examinations (if available), and clinical and demographic risk factor data (challenge 2) and output a score that translated to cancer yes/no within 12 months. Algorithm accuracy for breast cancer detection was evaluated using area under the curve and algorithm specificity compared with radiologists' specificity with radiologists' sensitivity set at 85.9% (United States) and 83.9% (Sweden). An ensemble method aggregating top-performing AI algorithms and radiologists' recall assessment was developed and evaluated. Results: Overall, 144 231 screening mammograms from 85 580 US women (952 cancer positive ≤12 months from screening) were used for algorithm training and validation. A second independent validation cohort included 166 578 examinations from 68 008 Swedish women (780 cancer positive). The top-performing algorithm achieved an area under the curve of 0.858 (United States) and 0.903 (Sweden) and 66.2% (United States) and 81.2% (Sweden) specificity at the radiologists' sensitivity, lower than community-practice radiologists' specificity of 90.5% (United States) and 98.5% (Sweden). Combining top-performing algorithms and US radiologist assessments resulted in a higher area under the curve of 0.942 and achieved a significantly improved specificity (92.0%) at the same sensitivity. Conclusions and Relevance: While no single AI algorithm outperformed radiologists, an ensemble of AI algorithms combined with radiologist assessment in a single-reader screening environment improved overall accuracy. This study underscores the potential of using machine learning methods for enhancing mammography screening interpretation.

BACKGROUND: Deep dermatophytosis is a severe and sometimes life-threatening fungal infection caused by dermatophytes. It is characterized by extensive dermal and subcutaneous tissue invasion and by frequent dissemination to the lymph nodes and, occasionally, the central nervous system. The condition is different from common superficial dermatophyte infection and has been reported in patients with no known immunodeficiency. Patients are mostly from North African, consanguineous, multiplex families, which strongly suggests a mendelian genetic cause. METHODS: We studied the clinical features of deep dermatophytosis in 17 patients with no known immunodeficiency from eight unrelated Tunisian, Algerian, and Moroccan families. Because CARD9 (caspase recruitment domain-containing protein 9) deficiency has been reported in an Iranian family with invasive fungal infections, we also sequenced CARD9 in the patients. RESULTS: Four patients died, at 28, 29, 37, and 39 years of age, with clinically active deep dermatophytosis. No other severe infections, fungal or otherwise, were reported in the surviving patients, who ranged in age from 37 to 75 years. The 15 Algerian and Tunisian patients, from seven unrelated families, had a homozygous Q289X CARD9 allele, due to a founder effect. The 2 Moroccan siblings were homozygous for the R101C CARD9 allele. Both alleles are rare deleterious variants. The familial segregation of these alleles was consistent with autosomal recessive inheritance and complete clinical penetrance. CONCLUSIONS: All the patients with deep dermatophytosis had autosomal recessive CARD9 deficiency. Deep dermatophytosis appears to be an important clinical manifestation of CARD9 deficiency. (Funded by Agence Nationale pour la Recherche and others.).

Cosmetics, like any product containing water and organic/inorganic compounds, require preservation against microbial contamination to guarantee consumer’s safety and to increase their shelf-life. The microbiological safety has as main goal of consumer protection against potentially pathogenic microorganisms, together with the product’s preservation resulting from biological and physicochemical deterioration. This is ensured by chemical, physical, or physicochemical strategies. The most common strategy is based on the application of antimicrobial agents, either by using synthetic or natural compounds, or even multifunctional ingredients. Current validation of a preservation system follow the application of good manufacturing practices (GMPs), the control of the raw material, and the verification of the preservative effect by suitable methodologies, including the challenge test. Among the preservatives described in the positive lists of regulations, there are parabens, isothiasolinone, organic acids, formaldehyde releasers, triclosan, and chlorhexidine. These chemical agents have different mechanisms of antimicrobial action, depending on their chemical structure and functional group’s reactivity. Preservatives act on several cell targets; however, they might present toxic effects to the consumer. Indeed, their use at high concentrations is more effective from the preservation viewpoint being, however, toxic for the consumer, whereas at low concentrations microbial resistance can develop.

Automatic emotion recognition based on facial expression is an interesting research field, which has presented and applied in several areas such as safety, health and in human machine interfaces. Researchers in this field are interested in developing techniques to interpret, code facial expressions and extract these features in order to have a better prediction by computer. With the remarkable success of deep learning, the different types of architectures of this technique are exploited to achieve a better performance. The purpose of this paper is to make a study on recent works on automatic facial emotion recognition FER via deep learning. We underline on these contributions treated, the architecture and the databases used and we present the progress made by comparing the proposed methods and the results obtained. The interest of this paper is to serve and guide researchers by review recent works and providing insights to make improvements to this field.

Natural flavonoids such as quercetin, (+)catechin and rutin as well as four methoxylated derivatives of quercetin used as models were investigated to elucidate their impact on the oxidant and antioxidant status of human red blood cells (RBCs). The impact of these compounds against metal toxicity was studied as well as their antiradical activities with DPPH assay. Antihemolytic experiments were conducted on quercetin, (+)catechin and rutin with excess of Fe, Cu and Zn (400 μM), and the oxidant (malondialdehyde, carbonyl proteins) and antioxidant (reduced glutathione, catalase activity) markers were evaluated. The results showed that Fe and Zn have the highest prooxidant effect (37 and 33% of hemolysis, respectively). Quercetin, rutin and (+)catechin exhibited strong antioxidant properties toward Fe, but this effect was decreased with respect to Zn ions. However, the Cu showed a weak antioxidant effect at the highest flavonoid concentration (200 μM), while a prooxidant effect was observed at the lowest flavonoid concentration (100 μM). These results are in agreement with the physico-chemical and antiradical data which demonstrated that binding of the metal ions (for FeNTA: (+)Catechin, KLFeNTA = 1.6(1) × 106 M-1 > Rutin, KLFeNTA = 2.0(9) × 105 M-1 > Quercetin, KLFeNTA = 1.0(7) × 105 M-1 > Q35OH, KLFeNTA = 6.3(8.7) × 104 M-1 > Quercetin3'4'OH and Quercetin 3OH, KLFeNTA ~ 2 × 104 M-1) reflects the (anti)oxidant status of the RBCs. This study reveals that flavonoids have both prooxidant and antioxidant activity depending on the nature and concentration of the flavonoids and metal ions.

COVID-19 is a rapidly growing pandemic with its first case identified during December 2019 in Wuhan, Hubei Province, China. Due to the rampant rise in the number of cases in China and globally, WHO declared COVID-19 as a pandemic on 11th March 2020. The disease is transmitted via respiratory droplets of infected patients during coughing or sneezing and affects primarily the lung parenchyma. The spectrum of clinical manifestations can be seen in COVID-19 patients ranging from asymptomatic infections to severe disease resulting in mortality. Although respiratory involvement is most common in COVID-19 patients, the virus can affect other organ systems as well. The systemic inflammation induced by the disease along with multisystem expression of Angiotensin Converting Enzyme 2 (ACE2), a receptor which allows viral entry into cells, explains the manifestation of extra-pulmonary symptoms affecting the gastrointestinal, cardiovascular, hematological, renal, musculoskeletal, and endocrine system. Here, we have reviewed the extensive literature available on COVID-19 about various clinical presentations based on the organ system involved as well as clinical presentation in specific population including children, pregnant women, and immunocompromised patients. We have also briefly discussed about the Multisystemic Inflammatory Syndrome occurring in children and adults with COVID-19. Understanding the various clinical presentations can help clinicians diagnose COVID-19 in an early stage and ensure appropriate measures to be undertaken in order to prevent further spread of the disease.

Knowledge of left atrial (LA) anatomy is important for atrial fibrillation ablation guidance, fibrosis quantification and biophysical modelling. Segmentation of the LA from Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) images is a complex problem. This manuscript presents a benchmark to evaluate algorithms that address LA segmentation. The datasets, ground truth and evaluation code have been made publicly available through the http://www.cardiacatlas.org website. This manuscript also reports the results of the Left Atrial Segmentation Challenge (LASC) carried out at the STACOM'13 workshop, in conjunction with MICCAI'13. Thirty CT and 30 MRI datasets were provided to participants for segmentation. Each participant segmented the LA including a short part of the LA appendage trunk and proximal sections of the pulmonary veins (PVs). We present results for nine algorithms for CT and eight algorithms for MRI. Results showed that methodologies combining statistical models with region growing approaches were the most appropriate to handle the proposed task. The ground truth and automatic segmentations were standardised to reduce the influence of inconsistently defined regions (e.g., mitral plane, PVs end points, LA appendage). This standardisation framework, which is a contribution of this work, can be used to label and further analyse anatomical regions of the LA. By performing the standardisation directly on the left atrial surface, we can process multiple input data, including meshes exported from different electroanatomical mapping systems.

can be used as potential inhibitors to the ACE2 receptor of SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

A novel coronavirus responsible of acute respiratory infection closely related to SARS-CoV has recently emerged. So far there is no consensus for drug treatment to stop the spread of the virus. Discovery of a drug that would limit the virus expansion is one of the biggest challenges faced by the humanity in the last decades. In this perspective, to test existing drugs as inhibitors of SARS-CoV-2 main protease is a good approach. Among natural phenolic compounds found in plants, fruit, and vegetables; flavonoids are the most abundant. Flavonoids, especially in their glycosylated forms, display a number of physiological activities, which makes them interesting to investigate as antiviral molecules. The flavonoids chemical structures were downloaded from PubChem and protease structure 6LU7 was from the Protein Data Bank site. Molecular docking study was performed using AutoDock Vina. Among the tested molecules Quercetin-3-O-rhamnoside showed the highest binding affinity (-9,7 kcal/mol). Docking studies showed that glycosylated flavonoids are good inhibitors for the SARS-CoV-2 protease and could be further investigated by in vitro and in vivo experiments for further validation. MD simulations were further performed to evaluate the dynamic behavior and stability of the protein in complex with the three best hits of docking experiments. Our results indicate that the rutin is a potential drug to inhibit the function of Chymotrypsin-like protease (3CL pro) of Coronavirus.

Medicinal plants are currently used by local populations to treat different diseases around the world. In the present study, the local knowledge of medicinal plants used by indigenous populations living in the Park of Tlemcen (North-West Algeria) has been documented. A total of 254 informants with a strong ethnomedicinal knowledge living in the national park of Tlemcen were interviewed by using a questionnaire. Data collected was analyzed using quantitative indices such as the ethnobotanicity index (EI), use value (UV), and Informant Consensus Factor (FIC). 109 species belonging to 54 families were identified and used by indigenous populations to treat different diseases. The most frequent families were lamiaceae (15.5%), asteraceae (11.9%), and rosaceae (5.5%). Roots, rhizomes or tubers were the most used part for medical care (37.6%), followed by leaves (33.6%), other aerial parts (16%), fruits (8%), flowers (1.6%), and seeds (3.2%). Regarding modes of preparation, we noticed that decoction (40.4%) and infusion (28.5%) were the most predominant. Moreover, Thymus lanceolatus (UV=0.96), Origon glandulosum (UV=0.96) and Ammoides verticillata (UV=0.94) were the most frequently used species. FIC values ranged from 0.65 to 0.98. The highest FIC were recorded for reproductive and sexual disorders (0.98), respiratory tract diseases (0.98), cardiovascular system disease and blood disorders (0.94), digestive disorders (0.93), and general health (0.93). A variety of species are used to treat several ailments. Recorded species with high UV should be prioritized for conservation and subjected to further phytochemical and pharmacological studies.

Rapid detection of carbapenem-resistant Acinetobacter baumannii strains is critical and will benefit patient care by optimizing antibiotic therapies and preventing outbreaks. Herein we describe the development and successful application of a mass spectrometry profile generated by matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) that utilized the imipenem antibiotic for the detection of carbapenem resistance in a large series of A. baumannii clinical isolates from France and Algeria. A total of 106 A. baumannii strains including 63 well-characterized carbapenemase-producing and 43 non-carbapenemase-producing strains, as well as 43 control strains (7 carbapenem-resistant and 36 carbapenem-sensitive strains) were studied. After an incubation of bacteria with imipenem for up to 4 h, the mixture was centrifuged and the supernatant analyzed by MALDI-TOF MS. The presence and absence of peaks representing imipenem and its natural metabolite was analyzed. The result was interpreted as positive for carbapenemase production if the specific peak for imipenem at 300.0 m/z disappeared during the incubation time and if the peak of the natural metabolite at 254.0 m/z increased as measured by the area under the curves leading to a ratio between the peak for imipenem and its metabolite being <0.5. This assay, which was applied to the large series of A. baumannii clinical isolates, showed a sensitivity of 100.0% and a specificity of 100.0%. Our study is the first to demonstrate that this quick and simple assay can be used as a routine tool as a point-of-care method for the identification of A. baumannii carbapenemase-producers in an effort to prevent outbreaks and the spread of uncontrollable superbugs.

A series of dinuclear [Ni(II)Ln(III)] Schiff-base complexes (using a Schiff-base dicompartmental ligand derived from o-vanillin [H(2)valpn = 1,3-propanediylbis(2-iminomethylene-6-methoxy-phenol)]) with Ln = La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, and a hydroxo-bridged tetranuclear [Ni(II)Yb(III)] are reported. The crystal structures have been solved for 10 dinuclear complexes revealing four arrangements for the dinuclear units, which are modulated by the coordinated solvent molecules and the nitrato-anion interactions. The magnetic behaviors have been investigated, and the nature of the Ni(II)-Ln(III) exchange interaction has been emphasized by comparison with the behavior of the related [Zn(II)Ln(III)] derivatives. This allowed for establishing that the interaction within these compounds is antiferromagnetic with the 4f ions of the beginning of the Ln series and turns ferromagnetic from Gd(III) toward the end of the series. AC susceptibility investigations clearly show the occurrence of slow relaxation processes of the magnetization close to 2 K for the dinuclear [Ni(II)Dy(III)] complex.

This article focuses on the application of clay, kaolinite, for the removal of fluoride ion from Saharan groundwater located in the Tindouf region (Algeria) because high concentrations are detected in potable water. Adsorption tests show that fluoride ion removal was efficient when the pH varies from 4.5 to 6. Under these conditions, the adsorption capacities were 0.442 and 0.448 mg/g, respectively. Kinetic and isotherm adsorption correlations were applied to describe the adsorption process. The results showed that the pseudo-second-order kinetic model and Freundlich isotherm fit well the experimental data. Thermodynamic calculation indicated that fluoride sorption into clay increased with increasing temperature from 30 to 55 °C, indicating the endothermic nature of sorption process. The investigation of the removal of fluoride from simulated potable water shows that the presence of nitrate and chloride ions did not influence the fluoride uptake. However, sulfate and carbonate ions decrease the adsorption capacity. Such results show that these ions may enter in competition with each other that may result in electrostatic repulsive forces between fluoride and clay surface. From this study, it can be concluded that the kaolinite is an effective and low-cost material for the removal of fluoride ions from groundwater.

Gram-negative carbapenem-resistant bacteria, in particular those producing New Delhi Metallo-betalactamase-1 (NDM-1), are a major global health problem. To inform the scientific and medical community in real time about worldwide dissemination of isolates of NDM-1-producing bacteria, we used the PubMed database to review all available publications from the first description in 2009 up to 31 December 2012, and created a regularly updated worldwide dissemination map using a web-based mapping application. We retrieved 33 reviews, and 136 case reports describing 950 isolates of NDM-1-producing bacteria. Klebsiella pneumoniae (n= 359) and Escherichia coli (n=268) were the most commonly reported bacteria producing NDM-1 enzyme. Several case reports of infections due to imported NDM-1 producing bacteria have been reported in a number of countries, including the United Kingdom, Italy, and Oman. In most cases (132/153, 86.3%), patients had connections with the Indian subcontinent or Balkan countries. Those infected were originally from these areas, had either spent time and/or been hospitalised there, or were potentially linked to other patients who had been hospitalised in these regions. By using Google Maps, we were able to trace spread of NDM-1-producing bacteria. We strongly encourage epidemiologists to use these types of interactive tools for surveillance purposes and use the information to prevent the spread and outbreaks of such bacteria.

Non-canonical NF-κB-pathway signaling is integral in immunoregulation. Heterozygous mutations in NFKB2 have recently been established as a molecular cause of common variable immunodeficiency (CVID) and DAVID-syndrome, a rare condition combining deficiency of anterior pituitary hormone with CVID. Here, we investigate 15 previously unreported patients with primary immunodeficiency (PID) from eleven unrelated families with heterozygous NFKB2-mutations including eight patients with the common p.Arg853* nonsense mutation and five patients harboring unique novel C-terminal truncating mutations. In addition, we describe the clinical phenotype of two patients with proximal truncating mutations. Cohort analysis extended to all 35 previously published NFKB2-cases revealed occurrence of early-onset PID in 46/50 patients (mean 5.5 yrs, median 2 yrs). ACTH-deficiency occurred in 44%. Three mutation carriers have deceased, four developed malignancies. Only two mutation carriers were clinically asymptomatic. In contrast to typical CVID, most patients suffered from early-onset and severe disease manifestations, including clinical signs of T cell dysfunction e.g. chronic-viral or opportunistic infections. In addition, 80% of patients suffered from autoimmune (AI) phenomena (alopecia > various lymphocytic organ-infiltration > diarrhea > arthritis > AI-cytopenia). Lymphoproliferation was not a hallmark of disease. Immunophenotyping showed largely normal quantities of naïve and memory CD4+ or CD8 + T-cells and normal T-cell proliferation. NK-cell number and function were also normal. In contrast, impaired B-cell differentiation and hypogammaglobinemia were consistent features of NFKB2-associated disease. In addition, an array of lymphocyte subpopulations such as regulatory T cell, Th17-, cTFH-, NKT-, and MAIT-cell numbers were decreased. We conclude that heterozygous damaging mutations in NFKB2 represent a distinct PID entity exceeding the usual clinical spectrum of CVID. Impairment of the non-canonical NF-κB pathways affects function and differentiation of numerous lymphocyte-subpopulations and thus causes a heterogeneous, more severe form of PID phenotype with early-onset. Further characteristic features are multifaceted, primarily T cell-mediated autoimmunity such as alopecia, lymphocytic organ infiltration, and frequently ACTH-deficiency.

via a molecular sieving that paves the way toward the optimization of current separation-based processes.

This paper deals with the electro-optic (EO) properties of polymer-dispersed liquid crystals (PDLCs). Several systems are considered to analyze the effects of preparation conditions and film characteristics on the EO response functions. Particular emphasis is put on systems based on mixtures of the commercial compound ASX-95, the difunctional acrylate tripropylene diacrylate and the eutectic mixture of low-molecular-weight liquid crystals E7. Other systems are considered to assess the influence of monomer functionality on EO properties using for example the trifunctional glycerylpropoxytriacrylate. Various modes of preparing PDLCs are considered based on the mechanism of polymerization-induced phase separation using either electron-beam (EB) or UV radiation curing processes. The dose is changed in both techniques to improve film strength and determine which method leads to the best samples in terms of EO response functions. Other important parameters, such as film thickness, composition and applied voltage, are also considered to evaluate the impact on these functions. The article focuses on a comparison of EO performances of films elaborated by exposure to EB and UV radiations. Under similar conditions, one definitively finds a net superiority of the former technique. In addition this technique does not require any photoinitiator and leads to a higher conversion of the monomeric compounds, i.e. higher mechanical strength and less severe aging conditions.

biochemical characterization showed differences with BSE and scrapie. Our identification of this prion disease in a geographically widespread livestock species requires urgent enforcement of surveillance and assessment of the potential risks to human and animal health.

We have investigated the artificial neural network method for the derivation of physically sound, easy‐to‐handle, predictive ground‐motion models. Avoiding the specification of any a priori functional form, artificial neural networks (ANNs) provide fully data‐driven predictive models and allow the testing of the relative importance of the effects of independent variables on seismic ground motion. This approach is applied here as an illustrative example, using a large subset of the KiK‐net seismic database, which includes 3891 records from 398 sites and 335 earthquakes. The independent variables tested are the moment magnitude ( M w), the focal depth, the epicentral distance ( R ), the site resonance frequency ( f ), and the time‐averaged shear‐wave velocity down to 30 m ( V S 30). The neural model output is the horizontal peak ground acceleration (PGA). The standard deviation obtained for the model of 0.34 is comparable to, or slightly lower than, conventional ground‐motion prediction equations (GMPEs). Although not imposed a priori , these results have a number of physically sound features: clear magnitude and depth dependency of the decay of the ground motion with distance, near‐fault saturation for large magnitudes, and indications of nonlinear effects in softer soils. In addition, the ANN method also allows the ranking of the importance of explanatory input parameters: while M w and R represent the key control parameters, depth is shown to mainly affect moderate magnitude events in the epicentral area. Considering the two site parameters V S 30 and f , the latter is shown to be more efficient in fitting the data than V S 30. The ability to implement this model using Microsoft Excel or another simple script is demonstrated, which opens a vast field for its use. Online Material: MATLAB script and parameters used for ANN model implementation.

First principle calculations have been performed to study the crystalline, electronic, and magnetic structures of three iron-carbide systems: θ-Fe3C, χ-Fe5C2, and η-Fe2C. The Kohn-Sham equations were solved by applying the full-potential linearized augmented plane wave method. The generalized gradient approximation in the Perdew-Wang formalism was used to the exchange and correlation energy functional. The internal positions of atoms within the unit cell were optimized and the ground state properties such as lattice parameter and bulk modulus were calculated. The results are compared with experimental data when available. Comparison of the two metastable systems χ-Fe5C2 and η-Fe2C shows that the last one has lower formation energy; this is corroborated by the formation sequence observed during tempering. The electronic structures of the three carbides were then studied and the magnetic moments calculated by means of electronic spin-resolved density of state calculations at their equilibrium lattice constants and optimized internal parameters.