Analysis of educational trajectories of students with disabilities at the Universidad Nacional del Tucumán

En el marco del proyecto de investigación "Los alumnos con discapacidad en la Universidad Nacional del Tucumán: prácticas inclusivas y condiciones de accesibilidad"; aprobado y financiado por el Consejo de Ciencia y Técnica de la mencionada universidad, se analizaron las trayectorias educativas de un colectivo de alumnos universitarios con discapacidad. La muestra se conformó por estudiantes de las facultades de Filosofía y Letras; Artes y Derecho y Ciencias Sociales. Se administró una encuesta semiestructurada a fin de conocer los obstáculos físicos y las condiciones de accesibilidad académicas de los alumnos. La cual permitió identificar los tipos de discapacidad de los estudiantes y las condiciones necesarias para garantizar su ingreso, permanencia y egreso. Los encuestados identificaron como principales obstáculos la falta de: formación de los docentes, materiales adecuados (braille y digitalización), intérpretes y accesibilidad en las condiciones edilicias. Este trabajo plantea analizar las trayectorias educativas reales de cada alumno en particular y dar respuestas concretas, desde un modelo social de discapacidad y una educación inclusiva.Under the research project "Students with disabilities in the UNT: inclusive practices and accessibility"; approved and funded by the Council of Science and Technology of the UNT (CIUNT) educational trajectories of a group of university students with disabilities was analyzed. The sample was composed by students from the Faculty of Philosophy and Letters; Arts; Law and Social Sciences. A semi-structured survey was administered in order to know the physical obstacles and the academic accessibility conditions of the students. This allowed to identify the types of students' disabilities and the necessary conditions to guarantee their entrance, permanence and graduation. Respondents identified as main obstacles the lack of: teacher training, adequate materials (braille and digitization), interpreters and accessibility in the building conditions. This work aims to analyze the real educational trajectories of each student in particular and give concrete answers, from a social model of disability and an inclusive education.Fil: Esterking, Ana Elena. Universidad Nacional de TucumánFil: González, Juana B.. Universidad Nacional de TucumánFil: Chávez, María Gabriela. Universidad Nacional de Tucumá

Automated colonoscopy withdrawal phase duration estimation using cecum detection and surgical tasks classification

Colorectal cancer is the third most common type of cancer with almost two million new cases worldwide. They develop from neoplastic polyps, most commonly adenomas, which can be removed during colonoscopy to prevent colorectal cancer from occurring. Unfortunately, up to a quarter of polyps are missed during colonoscopies. Studies have shown that polyp detection during a procedure correlates with the time spent searching for polyps, called the withdrawal time. The different phases of the procedure (cleaning, therapeutic, and exploration phases) make it difficult to precisely measure the withdrawal time, which should only include the exploration phase. Separating this from the other phases requires manual time measurement during the procedure which is rarely performed. In this study, we propose a method to automatically detect the cecum, which is the start of the withdrawal phase, and to classify the different phases of the colonoscopy, which allows precise estimation of the final withdrawal time. This is achieved using a Resnet for both detection and classification trained with two public datasets and a private dataset composed of 96 full procedures. Out of 19 testing procedures, 18 have their withdrawal time correctly estimated, with a mean error of 5.52 seconds per minute per procedure

Synthesis Of Ag@silica Nanoparticles By Assisted Laser Ablation.

This paper reports the synthesis of silver nanoparticles coated with porous silica (Ag@Silica NPs) using an assisted laser ablation method. This method is a chemical synthesis where one of the reagents (the reducer agent) is introduced in nanometer form by laser ablation of a solid target submerged in an aqueous solution. In a first step, a silicon wafer immersed in water solution was laser ablated for several minutes. Subsequently, an AgNO3 aliquot was added to the aqueous solution. The redox reaction between the silver ions and ablation products leads to a colloidal suspension of core-shell Ag@Silica NPs. The influence of the laser pulse energy, laser wavelength, ablation time, and Ag(+) concentration on the size and optical properties of the Ag@Silica NPs was investigated. Furthermore, the colloidal suspensions were studied by UV-VIS-NIR spectroscopy, X-Ray diffraction, and high-resolution transmission electron microscopy (HRTEM).1039

Identifying key mechanisms leading to visual recognition errors for missed colorectal polyps using eye-tracking technology

BACKGROUND AND AIMS: Lack of visual recognition of colorectal polyps may lead to interval cancers. The mechanisms contributing to perceptual variation, particularly for subtle and advanced colorectal neoplasia, has scarcely been investigated. We aimed to evaluate visual recognition errors and provide novel mechanistic insights. METHODS: Eleven participants (7 trainees, 4 medical students) evaluated images from the UCL polyp perception dataset, containing 25 polyps, using eye tracking equipment. Gaze errors were defined as those where the lesion was not observed according to eye tracking technology. Cognitive errors occurred when lesions were observed but not recognised as polyps by participants. A video study was also performed including 39 subtle polyps, where polyp recognition performance was compared with a convolutional neural network (CNN). RESULTS: Cognitive errors occurred more frequently than gaze errors overall (65.6%) , with a significantly higher proportion in trainees (P=0.0264). In the video validation, the CNN detected significantly more polyps than trainees and medical students, with per polyp sensitivities of 79.5%, 30.0% and 15.4% respectively. CONCLUSIONS: Cognitive errors were the most common reason for visual recognition errors. The impact of interventions such as artificial intelligence, particularly on different types of perceptual errors, needs further investigation including potential effects on learning curves. To facilitate future research, a publicly accessible visual perception colonoscopy polyp database was created

Computer aided characterization of early cancer in Barrett's esophagus on i-scan magnification imaging - Multicenter international study

BACKGROUND AND AIMS: We aimed to develop a computer aided characterization system that can support the diagnosis of dysplasia in Barrett's esophagus (BE) on magnification endoscopy. METHODS: Videos were collected in high-definition magnification white light and virtual chromoendoscopy with i-scan (Pentax Hoya, Japan) imaging in patients with dysplastic/ non-dysplastic BE (NDBE) from 4 centres. We trained a neural network with a Resnet101 architecture to classify frames as dysplastic or non-dysplastic. The network was tested on three different scenarios: high-quality still images, all available video frames and a selected sequence within each video. RESULTS: 57 different patients each with videos of magnification areas of BE (34 dysplasia, 23 NDBE) were included. Performance was evaluated using a leave-one-patient-out cross-validation methodology. 60,174 (39,347 dysplasia, 20,827 NDBE) magnification video frames were used to train the network. The testing set included 49,726 iscan-3/optical enhancement magnification frames. On 350 high-quality still images the network achieved a sensitivity of 94%, specificity of 86% and Area under the ROC (AUROC) of 96%. On all 49,726 available video frames the network achieved a sensitivity of 92%, specificity of 82% and AUROC of 95%. On a selected sequence of frames per case (total of 11,471 frames) we used an exponentially weighted moving average of classifications on consecutive frames to characterize dysplasia. The network achieved a sensitivity of 92%, specificity of 84% and AUROC of 96% The mean assessment speed per frame was 0.0135 seconds (SD, + 0.006) CONCLUSION: Our network can characterize BE dysplasia with high accuracy and speed on high-quality magnification images and sequence of video frames moving it towards real time automated diagnosis

A new artificial intelligence system successfully detects and localises early neoplasia in Barrett's esophagus by using convolutional neural networks

BACKGROUND AND AIMS: Seattle protocol biopsies for Barrett's Esophagus (BE) surveillance are labour intensive with low compliance. Dysplasia detection rates vary, leading to missed lesions. This can potentially be offset with computer aided detection. We have developed convolutional neural networks (CNNs) to identify areas of dysplasia and where to target biopsy. METHODS: 119 Videos were collected in high-definition white light and optical chromoendoscopy with i-scan (Pentax Hoya, Japan) imaging in patients with dysplastic and non-dysplastic BE (NDBE). We trained an indirectly supervised CNN to classify images as dysplastic/non-dysplastic using whole video annotations to minimise selection bias and maximise accuracy. The CNN was trained using 148,936 video frames (31 dysplastic patients, 31 NDBE, two normal esophagus), validated on 25,161 images from 11 patient videos and tested on 264 iscan-1 images from 28 dysplastic and 16 NDBE patients which included expert delineations. To localise targeted biopsies/delineations, a second directly supervised CNN was generated based on expert delineations of 94 dysplastic images from 30 patients. This was tested on 86 i-scan one images from 28 dysplastic patients. FINDINGS: The indirectly supervised CNN achieved a per image sensitivity in the test set of 91%, specificity 79%, area under receiver operator curve of 93% to detect dysplasia. Per-lesion sensitivity was 100%. Mean assessment speed was 48 frames per second (fps). 97% of targeted biopsy predictions matched expert and histological assessment at 56 fps. The artificial intelligence system performed better than six endoscopists. INTERPRETATION: Our CNNs classify and localise dysplastic Barrett's Esophagus potentially supporting endoscopists during surveillance

Analyse multicritère pour établir l’état environnemental des zones littorales

En prens

Steroid hormone-related polymorphisms associate with the development of bone erosions in rheumatoid arthritis and help to predict disease progression: Results from the REPAIR consortium

Here, we assessed whether 41 SNPs within steroid hormone genes associated with erosive disease. The most relevant finding was the rheumatoid factor (RF)-specific effect of the CYP1B1, CYP2C9, ESR2, FcγR3A, and SHBG SNPs to modulate the risk of bone erosions (P = 0.004, 0.0007, 0.0002, 0.013 and 0.015) that was confirmed through meta-analysis of our data with those from the DREAM registry (P = 0.000081, 0.0022, 0.00074, 0.0067 and 0.0087, respectively). Mechanistically, we also found a gender-specific correlation of the CYP2C9rs1799853T/T genotype with serum vitamin D3 levels (P = 0.00085) and a modest effect on IL1β levels after stimulation of PBMCs or blood with LPS and PHA (P = 0.0057 and P = 0.0058). An overall haplotype analysis also showed an association of 3 ESR1 haplotypes with a reduced risk of erosive arthritis (P = 0.009, P = 0.002, and P = 0.002). Furthermore, we observed that the ESR2, ESR1 and FcγR3A SNPs influenced the immune response after stimulation of PBMCs or macrophages with LPS or Pam3Cys (P = 0.002, 0.0008, 0.0011 and 1.97•10−7). Finally, we found that a model built with steroid hormone-related SNPs significantly improved the prediction of erosive disease in seropositive patients (PRF+ = 2.46•10−8) whereas no prediction was detected in seronegative patients (PRF− = 0.36). Although the predictive ability of the model was substantially lower in the replication population (PRF+ = 0.014), we could confirm that CYP1B1 and CYP2C9 SNPs help to predict erosive disease in seropositive patients. These results are the first to suggest a RF-specific association of steroid hormone-related polymorphisms with erosive disease