Diffuse Idiopathic Skeletal Hyperostosis (DISH)-Phagia: A Case Report and Review of Literature of a Rare Disease Manifestation.

Diffuse idiopathic skeletal hyperostosis (DISH), also called Forestier disease, is a clinical entity characterized by ossification of the anterolateral ligaments of the spine. DISH is more commonly diagnosed in older males, with an estimated prevalence of 42% in patients older than 65 years. As the disease affects predominantly the thoracic spine, dysphagia is a rare presentation of this entity observed in only 0.6-1.0% of the cases. We present a clinical case of an 84-year-old male with complaints of progressive dysphagia and foreign body sensation within one year of evolution. Computed tomography imaging revealed an anterior C4-C5 osteophyte compressing the posterior hypopharyngeal wall. Flexible endoscopy revealed a deformed and stenotic hypopharynx. The patient underwent surgical treatment with anterior cervical osteophyte resection using the Smith-Robinson approach. The patient showed significant improvement in preoperative symptoms, and no recurrence was detected at six months of follow-up. We also aim to discuss the clinical and radiological characteristics of the disease, as well as the crucial steps for a correct diagnosis and treatment of this rare disease.

Effects of forage quality and particle size on feed intake and ruminoreticulum content of goats.

The aim was to evaluate the effect of particle size and hay quality on feed intake, granulometric profile, and composition of the ruminoreticulum content in goats. We used 54 Alpine bucks in a completely randomized design with a factorial arrangement of 3 × 3. Treatments were a combination of Bermuda grass hay (Cynodon dactylon) with three quality levels: high (35 days), medium (50 days), and low (65 d) harvested at regrowth times. Were evaluated three particle sizes: small (16% ≥4.76 mm), medium (48% ≥4.76 mm), and large (75% ≥4.76 mm), which accounted for 66%, 75%, and 94% of physically effective fiber, respectively. Samples of offered diet, intake, and ruminoreticulum content were used to generate the granulometric profile. The offered diet, intake, and ruminoreticulum content presented different granulometric profiles regarding hay quality and particle size. Dry matter intake (DMI) and neutral detergent fiber intake (NDFI) increased (P < 0.05) when low-quality hay and large particles were offered. However, when particle size in low-quality hay was reduced, DMI and NDF decreased (P < 0.05). When analyzing the ruminoreticulum content (DM, NDF, peNDF, and indigestible DM), we did not observe any effect (P > 0.05) of hay quality or particle size on the variables. Thus, reducing hay quality and increasing particle size increase dry matter and fiber intake, presenting an interaction between forage quality and particle size. Forage quality and particle size promote intense selective behavior and chewing, which leads to a homogeneous content of particle profile in ruminoreticulum and a uniform average retention time.

Skin deformation analysis for pre-operative planning of DIEAP flap reconstruction surgery.

Deep inferior epigastric artery perforator (DIEAP) flap reconstruction surgeries can potentially benefit from augmented reality (AR) in the context of surgery planning and outcomes improvement. Although three-dimensional (3D) models help visualize and map the perforators, the anchorage of the models to the patient's body during surgery does not consider eventual skin deformation from the moment of computed tomography angiography (CTA) data acquisition until the position of the patient while in surgery. In this work, we compared the 3D deformation registration from supine arms down (CTA position) to supine with arms at 90° degrees (surgical position), estimating the patient's skin deformation. We processed the data sets of 20 volunteers with a 3D rigid registration tool and performed a descriptive statistical analysis and statistical inference. With 2.45 mm of root mean square and 2.89 mm of standard deviation, results include 30% cases of deformation above 3 mm and 15% above 4 mm. Pose transformation deformation indicates that 3D surface data from the CTA scan position differs from data acquired in loco at the surgical table. Such results indicate that research should be conducted to construct accurate 3D models using CTA data to display on the patient, while considering projection errors when using AR technology.

Preclinical dental students self-assessment of an improved operative dentistry virtual reality simulator with haptic feedback.

To test and evaluate the second installment of DENTIFY, a virtual reality haptic simulator for Operative Dentistry (OD), on preclinical dental students, by focusing on user performance and self-assessment. Twenty voluntary unpaid preclinical dental students, with different background experience, were enrolled for this study. After the completion of an informed consent, a demographic questionnaire, and being introduced to the prototype (on the first testing session), three testing sessions followed (S1, S2, S3). Each session involved the following steps: (I) free experimentation; (II) task execution; S3 also included (III) completion of questionnaires associated with the experiment (total of 8 Self-Assessment Questions (SAQ)); and (IV) guided interview. As expected, drill time decreased steadily for all tasks when increasing prototype use, verified by RM ANOVA. Regarding performance metrics (Comparisons by Student's t-test and ANOVA) recorded at S3, in overall, a higher performance was verified for participants with the following characteristics: female, non-gamer, no previous VR experience and with over 2 semesters of previous experience of working on phantom models. The correlation between the participants' performance (drill time), for the four tasks, and user self-assessment evaluation, verified by Spearman's rho analysis, allowed to conclude that a higher performance was observed in students who responded that DENTIFY improved their self perception of manual force applied. Regarding the questionnaires, Spearman's rho analysis showed a positive correlation between the improvement DENTIFY inputs on conventional teaching sensed by students, also enhancing their interest in learning OD, their desire to have more simulator hours and the improvement sensed on manual dexterity. All participating students adhered well to the DENTIFY experimentation. DENTIFY allows for student self-assessment and contributes to improving student performance. Simulators with VR and haptic pens for teaching in OD should be designed as a consistent and gradual teaching strategy, allowing multiplicity of simulated scenarios, bimanual manipulation, and the possibility of real-time feedback to allow for the student's immediate self-assessment. Additionally, they should create performance reports per student to ensure self-perception/criticism of their evolution over longer periods of learning time.

Imaging Signs of May-Thurner Syndrome in Asymptomatic Patients: Computed Tomography Angiography Analysis of Kidney Donors.

BACKGROUND: The current study aimed to evaluate the distance between the right common iliac artery (RCIA) and lumbar vertebra in asymptomatic patients in order to determine whether such distance was statistically correlated with the left common iliac vein (LCIV) diameter (LCIVD) and to investigate if both measures were related to demographic characteristics and anthropometric data, such as sex, age, height, and body mass index (BMI). METHODS: In this descriptive and uncontrolled anatomic study, data from high-definition computed tomography (CT) angiography images of living kidney donors without a medical history of chronic venous insufficiency or past deep vein thrombosis (DVT) were analyzed. The RCIA crossed over the LCIV in 311 individuals, who were then included in this study. CT scans were reviewed to measure (1) the narrowest space between the RCIA and fifth lumbar vertebral body and (2) the LCIVD. Measures were subjected to normality tests and were divided according to the sex of the study population. Correlations of measures with age, BMI, and height were calculated. RESULTS: Of the 311 patients analyzed, 66.6% (n = 207) were female. The mean lumbar vertebral body-iliac artery distance (LVBIAD) was 7.2 mm, whereas the mean LCIVD was 8.5 mm; both were higher in men (P < 0.001). The statistical analysis of LVBIAD and LCIVD distributions revealed no normality pattern (P < 0.05). The analysis of the correlation between them showed a weak statistically significant relationship with age. A linear regression model considering the normality percentile interval indicated a strong positive correlation between LVBIAD and LCIVD (R2 = 0.884). CONCLUSIONS: The LVBIAD was <5 mm and <3 mm in 25% and 5% of asymptomatic individuals, respectively. The LCIVD correlated with the space between the RCIA and lumbar vertebra. The distance between the RCIA and lumbar vertebra and the LCIVD were higher in male subjects and older patients, but did not correlate with BMI and height.

EvoDesigner: Evolving Poster Layouts.

Frequently, one of the goals of Graphic Design (gd) is discovering disruptive visual solutions that stand out and attract people's attention. However, due to the increasing democratisation of gd, graphic designers tend to adopt design trends, leading to designs that many times lack innovative and catchy features. EvoDesigner is an evolutionary extension for Adobe InDesign that aims to aid gd processes by automatically evolving layout and style variations of given InDesign pages. The generated pages might be previously created and post-edited by designers, promoting co-creation. As an extension of the study EvoDesigner: Towards Aiding Creativity in Graphic Design, this article begins with a general introduction of EvoDesigner. Then, we review previous experiments on evolving pages towards the page balance of existing target posters. Furthermore, we present new experiments exploring the benefits of using grid systems to position and scale page items along with a user survey made to gather feedback about the impact of grid systems in the generated pages and showcase examples of artefacts created from the collaboration between designers and the system. The findings indicate that the presented techniques can be used to interpret current layouts in different manners, and suggest that grid systems may be a useful tool for promoting the automatic production of layouts with better organisation when compared to applying no organisational constraints. However, a conducted user survey indicates that, depending on the goals of the designers, more organised layouts might not always be synonymous with better results.

Effects of sliding window variation in the performance of acceleration-based human activity recognition using deep learning models.

Deep learning (DL) models are very useful for human activity recognition (HAR); these methods present better accuracy for HAR when compared to traditional, among other advantages. DL learns from unlabeled data and extracts features from raw data, as for the case of time-series acceleration. Sliding windows is a feature extraction technique. When used for preprocessing time-series data, it provides an improvement in accuracy, latency, and cost of processing. The time and cost of preprocessing can be beneficial especially if the window size is small, but how small can this window be to keep good accuracy? The objective of this research was to analyze the performance of four DL models: a simple deep neural network (DNN); a convolutional neural network (CNN); a long short-term memory network (LSTM); and a hybrid model (CNN-LSTM), when variating the sliding window size using fixed overlapped windows to identify an optimal window size for HAR. We compare the effects in two acceleration sources': wearable inertial measurement unit sensors (IMU) and motion caption systems (MOCAP). Moreover, short sliding windows of sizes 5, 10, 15, 20, and 25 frames to long ones of sizes 50, 75, 100, and 200 frames were compared. The models were fed using raw acceleration data acquired in experimental conditions for three activities: walking, sit-to-stand, and squatting. Results show that the most optimal window is from 20-25 frames (0.20-0.25s) for both sources, providing an accuracy of 99,07% and F1-score of 87,08% in the (CNN-LSTM) using the wearable sensors data, and accuracy of 98,8% and F1-score of 82,80% using MOCAP data; similar accurate results were obtained with the LSTM model. There is almost no difference in accuracy in larger frames (100, 200). However, smaller windows present a decrease in the F1-score. In regard to inference time, data with a sliding window of 20 frames can be preprocessed around 4x (LSTM) and 2x (CNN-LSTM) times faster than data using 100 frames.

Costovertebral Osteoarthrosis: Rare Differential Diagnosis of Back pain in young patients. Case Report.

The differential diagnosis of dorsal thoracic pain can be a challange due to the proximity of the dorsal column to vital organs as well as to its unique anatomy, innervation, and rib joint. The patterns of referred visceral pain require, in most cases, extensive complementary diagnostic tests in order to exclude severe conditions. Referred pain patterns often result in numerous and expensive visceral workups in order to exclude serious conditions, and costovertebral joint osteoarthritis is usually only considered when the origin of the pain remains unexplained. The authors present the case of a 40-year-old man with disabling dorsal pain due to isolated costovertebral osteoarthrosis. The symptomatology was controlled after injection of methylprednisolone guided by computed tomography. This clinical case aims to describe the clinical presentation of a rare entity that should be considered in the differential diagnosis of back pain.

Usability, acceptance, and educational usefulness study of a new haptic operative dentistry virtual reality simulator.

BACKGROUND: Dental preclinical training has been traditionally centered onverbal instructions and subsequent execution on phantom heads and plastic training models. However, these present present limitations. Virtual Reality (VR) and haptic simulators have been proposed with promising results and advantages and have showed usefullness in the preclinical training environment. We designed DENTIFY, a multimodal immersive simulator to assist Operative Dentistry learning, which exposes the user to different virtual clinical scenarios while operating a haptic pen to simulate dental drilling. OBJECTIVE: The main objective is to assess DENTIFY's usability, acceptance, and educational usefulness to dentists, in order to make the proper changes and, subsequently, to test DENTIFY with undergraduate preclinical dental students. METHODS: DENTIFY combines an immersive head mounted VR display, a haptic pen in which the pen itself has been replaced by a 3D printed model of a dental turbine and a controller with buttons to adjust and select the scenario of the simulation, along with 3D sounds of real dental drilling. The user's dominant hand operated the virtual turbine on the VR-created scenario, while the non-dominant hand is used to activate the simulator and case selection. The simulation sessions occurred in a controlled virtual environment. We evaluated DENTIFY's usability and acceptance over the course of 13 training sessions with dental professionals, after the users performed a drilling task in virtual dental tissues. RESULTS: The conducted user acceptance indicates that DENTIFY shows potencial enhancing learning in operative dentistry as it promotes self-evaluation and multimodal immersion on the dental drilling experience. CONCLUSIONS: DENTIFY presented significant usability and acceptance from trained dentists. This tool showed to have teaching and learning (hence, pedagogical) potential in operative dentistry.

Costovertebral Osteoarthrosis: Rare Differential Diagnosis of Back pain in young patients. Case Report / Osteoartrose costovertebral: Diagnóstico diferencial raro de dorsalgia no paciente jovem. Relato de caso

Abstract The differential diagnosis of dorsal thoracic pain can be a challange due to the proximity of the dorsal column to vital organs as well as to its unique anatomy, innervation, and rib joint. The patterns of referred visceral pain require, in most cases, extensive complementary diagnostic tests in order to exclude severe conditions. Referred pain patterns often result in numerous and expensive visceral workups in order to exclude serious conditions, and costovertebral joint osteoarthritis is usually only considered when the origin of the pain remains unexplained. The authors present the case of a 40-year-old man with disabling dorsal pain due to isolated costovertebral osteoarthrosis. The symptomatology was controlled after injection of methylprednisolone guided by computed tomography. This clinical case aims to describe the clinical presentation of a rare entity that should be considered in the differential diagnosis of back pain.

Resumo O diagnóstico diferencial de dorsalgia revela-se um desafio pela proximidade da coluna dorsal a órgãos vitais assim como por sua anatomia única, inervação e articulação com as costelas. Os padrões de dor referida visceral obrigam, na maioria das vezes, a extensivos exames complementares de diagnóstico de forma a excluir condições graves. A osteoartrose da articulação costovertebral é um diagnóstico pouco reconhecido, e habitualmente é somente considerado quando a fonte de dor continua sem explicação após extensa investigação. Os autores apresentam o caso de um homem de 40 anos de idade com dor dorsal incapacitante devido a osteoartrose costovertebral isolada. A sintomatologia foi controlada após a injeção de metilprednisolona guiada por tomografia computadorizada. Este caso clínico tem como objetivo descrever a apresentação clínica de uma entidade rara que deverá ser considerada no diagnóstico diferencial de dorsalgia.

Encaixando possibilidades: uma proposta pedagógica para o malabarismo com caixas / Fitting possibilities: a pedagogical proposal for juggling boxes / Encajando posibilidades: una propuesta pedagógica para hacer malabares con cajas

Recentemente, educadores físicos e artistas atuantes na escola vêm direcionando atenção para o potencial pedagógico do circo e evidenciando a aproximação entre educação corporal e a arte. Diante da amplitude das práticas circenses, contamos com as modalidades de malabarismo com distintos aparelhos, destacandose claves, bolas e aros. Fundamentadas na manipulação de objetos, essas práticas requerem atenção dos professores, visando o oferecimento de um ensino envolvente, seguro e expressivo. Assim, o presente artigo discute elementos básicos para o ensino do malabarismo com caixas, procurando fomentar essa prática entre os profissionais que se aventuram no ensino da arte circense e que buscam uma educação artístico-estética. Partindo de referenciais teóricos, artísticos e de nossa práxis com pedagogia circense e malabarismo com caixas, acreditamos que essa modalidade possa compor o repertório de profissionais da Educação Física e das Artes e almejamos com essa contribuição que o malabarismo com caixas se torne mais disseminado e acessível.

Recently, physical educators and artists working at the school have been directing attention to the pedagogical potential of circus and showing a approach between body education and art. In view of the vast repertoire of circus practices, we have the juggling's modalities with different implements, highlighting clubs, balls, hoops. Based on the manipulation, these practices require attention from teachers who are aiming to offer a playful, engaging, safe and expressive teaching. Thus, this article discusses basic elements for teaching cigar box manipulation, seeking to encourage this practice among professionals working in the teaching of circus art and who seek an artistic-aesthetic education. Based on theoretical, artistic and practical references, also in our circus pedagogical praxis and cigar boxes manipulation. We believe that this modality can compose the repertoire for Physical Education and the Arts professionals and we aim that the cigar box manipulation becomes more widespread and accessible.

Recientemente, los educadores físicos y artistas que trabajan en la escuela están dirigiendo la atención sobre la pedagogia del circo y la aproximación entre la educación corporal y el arte. Dada la amplitud de estas prácticas, contamos con modalidades de malabares con diferentes aparatos como mazas, pelotas y aros. Basadas en la manipulación, estas prácticas requieren la atención de los docentes que buscan una enseñanza lúdica, participativa, segura y expresiva. Así, este artículo discute elementos para la enseñanza de los malabares con cajas, buscando promover esta práctica entre los profesionales que incursionan en la enseñanza del arte circense y que buscan una formación artístico-estética. Partiendo de referentes teóricos, artísticos y de nuestra praxis con la enseñanza y los malabares con cajas, creemos que esta modalidad puede componer el repertorio de los profesionales de la Educación Física y Artes y pretendemos que los malabares con cajas sean más difundidos y accesibles.

Motion envelopes: unfolding longitudinal rotation data from walking stick-figures.

This work presents Motion Envelopes (ME), a simple method to estimate the missing longitudinal rotations of minimal stick figures, which is based on the spatial-temporal surface traced by line segments that connect contiguous pairs of joints. We validate ME by analyzing the gait patterns of 6 healthy subjects, comprising a total of 18 gait cycles. A strong correlation between experimental and estimated data was obtained for lower limbs and upper arms, indicating that ME can predict their longitudinal orientation in normal gait, hence, ME can be used to complement the kinematic information of stick figures whenever it is incomplete.

Ambulatório de Gênero e Sexualidades (AmbGen/ HC/ UNICAMP): relato da experiência do serviço / Gender and Sexualities Outpatient Clinic (AmbGen/ HC/UNICAMP): report of the service experience

0 Ambulatório de Género e Sexualidades (AmbGen) do Hospital das Clinicas da Universidade Estadual de Campinas é um dos poucos dispositivos públicos que acolhem população da infância e adolescência com variabilidade de género. A psiquiatria e psicologia investigam transtornos mentais, desencadeadores do sofrimento psíquico, disforias relacionados à incongruência de gênero e, no caso de crianças e adolescentes, acolhem as familías buscando compreensão da dinâmica familiar, esclarecimento de duvidas e estigmas. A intervenção hormonal na adolescência é possível em dois momentos: no inicio da puberdade, através de terapia medicamentosa visando blogueio puberal, e hormonização cruzada. A adequação corporal & identidade de género da pessoa trans, através da hormonização, é desejada pela maior parte dos adultos atendidos. A arteterapia realiza atendimentos nos quais busca fornecer padrões adequados à questões relevantes, utilizando- se de modalidades expressivas e vivências de processos criativos, uma maneira terapêutica diferenciada que propicia um ambiente acolhedor por um viés artístico. Características de género e voz são muito abrangentes. Sendo assim, a terapia fonoaudiológica a pessoas trans não se restringe apenas a produção vocal, mas também se relaciona a outros aspectos da comunicação e do discurso.

Validação de um Algoritmo de Inteligência Artificial para a Predição Diagnóstica de Doença Coronariana: Comparação com um Modelo Estatístico Tradicional / Validation of an Artificial Intelligence Algorithm for Diagnostic Prediction of Coronary Disease: Comparison with a Traditional Statistical Model

Resumo Fundamento: A análise prognóstica multivariada tem sido realizada tradicionalmente por modelos de regressão. No entanto, muitos algoritmos surgiram, capazes de traduzir uma infinidade de padrões em probabilidades. A acurácia dos modelos de inteligência artificial em comparação à de modelos estatísticos tradicionais não foi estabelecida na área médica. Objetivo: Testar a inteligência artificial como um algoritmo preciso na predição de doença coronariana no cenário de dor torácica aguda, e avaliar se seu desempenho é superior a do modelo estatístico tradicional. Métodos: Foi analisada uma amostra consecutiva de 962 pacientes admitidos com dor torácica. Dois modelos probabilísticos de doença coronariana foram construídos com os primeiros 2/3 dos pacientes: um algoritmo machine learning e um modelo logístico tradicional. O desempenho dessas duas estratégias preditivas foi avaliado no último terço de pacientes. O modelo final de regressão logística foi construído somente com variáveis significativas a um nível de significância de 5%. Resultados: A amostra de treinamento tinha idade média de 59 ± 15 anos, 58% do sexo masculino, e uma prevalência de doença coronariana de 52%. O modelo logístico foi composto de nove preditores independentes. O algoritmo machine learning foi composto por todos os candidatos a preditores. Na amostra teste, a área sob a curva ROC para predição de doença coronariana foi de 0,81 (IC95% = 0,77 - 0,86) para o algoritmo machine learning, similar à obtida no modelo logístico (0,82; IC95% = 0,77 - 0,87), p = 0,68. Conclusão: O presente estudo sugere que um modelo machine learning acurado não garante superioridade à um modelo estatístico tradicional

Abstract Background: Multivariate prognostic analysis has been traditionally performed by regression models. However, many algorithms capable of translating an infinity of patterns into probabilities have emerged. The comparative accuracy of artificial intelligence and traditional statistical models has not been established in the medical field. Objective: To test the artificial intelligence as an accurate algorithm for predicting coronary disease in the scenario of acute chest pain and evaluate whether its performance is superior to traditional statistical model. Methods: A consecutive sample of 962 patients admitted with chest pain was analyzed. Two probabilistic models of coronary disease were built using the first two-thirds of patients: a machine learning algorithm and a traditional logistic model. The performance of these two predictive strategies were evaluated in the remaining third of patients. The final logistic regression model had significant variables only, at the 5% significance level. Results: The training sample had an average age of 59 ± 15 years, 58% males, and a 52% prevalence of coronary disease. The logistic model was composed of nine independent predictors. The machine learning algorithm was composed of all candidates for predictors. In the test sample, the area under the ROC curve for prediction of coronary disease was 0.81 (95% CI = 0.77 - 0.86) for the machine learning algorithm, similar to that obtained in logistic model (0.82; 95% CI = 0.77 - 0.87), p = 0.68. Conclusion: The present study suggests that an accurate machine learning prediction tool did not prove to be superior to the statistical model of logistic regression.

Breast cancer surgery with augmented reality.

INTRODUCTION: Innovations in 3D spatial technology and augmented reality imaging driven by digital high-tech industrial science have accelerated experimental advances in breast cancer imaging and the development of medical procedures aimed to reduce invasiveness. PRESENTATION OF CASE: A 57-year-old post-menopausal woman presented with screen-detected left-sided breast cancer. After undergoing all staging and pre-operative studies the patient was proposed for conservative breast surgery with tumor localization. During surgery, an experimental digital and non-invasive intra-operative localization method with augmented reality was compared with the standard pre-operative localization with carbon tattooing (institutional protocol). The breast surgeon wearing an augmented reality headset (Hololens) was able to visualize the tumor location projection inside the patient's left breast in the usual supine position. DISCUSSION: This work describes, to our knowledge, the first experimental test with a digital non-invasive method for intra-operative breast cancer localization using augmented reality to guide breast conservative surgery. In this case, a successful overlap of the previous standard pre-operative marks with carbon tattooing and tumor visualization inside the patient's breast with augmented reality was obtained. CONCLUSION: Breast cancer conservative guided surgery with augmented reality can pave the way for a digital non-invasive method for intra-operative tumor localization.

Surgical outcome of a post-traumatic dystonic foot: Case report and literature review.

Post-traumatic dystonia is an underrecognized condition that can present with bizarre symptoms after trauma, usually out of proportion to the trigger event. We describe the case of a 31-year-old man with a severe lower extremity deformity, gradually developed after minor trauma. An interdisciplinary treatment was tried without any improvement and surgery was performed as a rescue approach. Tibialis anterior tendon transfer and hindfoot triple arthrodesis were carried out, successfully achieving a plantigrade foot and a functional gait. Despite the scarce literature available about functional results of surgery in dystonic feet, we present a step-by-step comprehensive approach to this disorder. LEVEL OF CLINICAL EVIDENCE: 4.

Validation of an Artificial Intelligence Algorithm for Diagnostic Prediction of Coronary Disease: Comparison with a Traditional Statistical Model. / Validação de um Algoritmo de Inteligência Artificial para a Predição Diagnóstica de Doença Coronariana: Comparação com um Modelo Estatístico Tradicional.

BACKGROUND: Multivariate prognostic analysis has been traditionally performed by regression models. However, many algorithms capable of translating an infinity of patterns into probabilities have emerged. The comparative accuracy of artificial intelligence and traditional statistical models has not been established in the medical field. OBJECTIVE: To test the artificial intelligence as an accurate algorithm for predicting coronary disease in the scenario of acute chest pain and evaluate whether its performance is superior to traditional statistical model. METHODS: A consecutive sample of 962 patients admitted with chest pain was analyzed. Two probabilistic models of coronary disease were built using the first two-thirds of patients: a machine learning algorithm and a traditional logistic model. The performance of these two predictive strategies were evaluated in the remaining third of patients. The final logistic regression model had significant variables only, at the 5% significance level. RESULTS: The training sample had an average age of 59 ± 15 years, 58% males, and a 52% prevalence of coronary disease. The logistic model was composed of nine independent predictors. The machine learning algorithm was composed of all candidates for predictors. In the test sample, the area under the ROC curve for prediction of coronary disease was 0.81 (95% CI = 0.77 - 0.86) for the machine learning algorithm, similar to that obtained in logistic model (0.82; 95% CI = 0.77 - 0.87), p = 0.68. CONCLUSION: The present study suggests that an accurate machine learning prediction tool did not prove to be superior to the statistical model of logistic regression.

FUNDAMENTO: A análise prognóstica multivariada tem sido realizada tradicionalmente por modelos de regressão. No entanto, muitos algoritmos surgiram, capazes de traduzir uma infinidade de padrões em probabilidades. A acurácia dos modelos de inteligência artificial em comparação à de modelos estatísticos tradicionais não foi estabelecida na área médica. OBJETIVO: Testar a inteligência artificial como um algoritmo preciso na predição de doença coronariana no cenário de dor torácica aguda, e avaliar se seu desempenho é superior a do modelo estatístico tradicional. MÉTODOS: Foi analisada uma amostra consecutiva de 962 pacientes admitidos com dor torácica. Dois modelos probabilísticos de doença coronariana foram construídos com os primeiros 2/3 dos pacientes: um algoritmo machine learning e um modelo logístico tradicional. O desempenho dessas duas estratégias preditivas foi avaliado no último terço de pacientes. O modelo final de regressão logística foi construído somente com variáveis significativas a um nível de significância de 5%. RESULTADOS: A amostra de treinamento tinha idade média de 59 ± 15 anos, 58% do sexo masculino, e uma prevalência de doença coronariana de 52%. O modelo logístico foi composto de nove preditores independentes. O algoritmo machine learning foi composto por todos os candidatos a preditores. Na amostra teste, a área sob a curva ROC para predição de doença coronariana foi de 0,81 (IC95% = 0,77 ­ 0,86) para o algoritmo machine learning, similar à obtida no modelo logístico (0,82; IC95% = 0,77 ­ 0,87), p = 0,68. CONCLUSÃO: O presente estudo sugere que um modelo machine learning acurado não garante superioridade à um modelo estatístico tradicional.

An immersive educational tool for dental implant placement: A study on user acceptance.

BACKGROUND: Tools for training and education of dental students can improve their ability to perform technical procedures such as dental implant placement. Shortage of training can negatively affect dental implantologists' performance during intraoperative procedures, resulting in lack of surgical precision and, consequently, inadequate implant placement, which may lead to unsuccessful implant supported restorations or other complications. OBJECTIVE: We designed and developed IMMPLANT a virtual reality educational tool to assist implant placement learning, which allows users to freely manipulate 3D dental models (e.g., a simulated patient's mandible and implant) with their dominant hand while operating a touchscreen device to assist 3D manipulation. METHODS: The proposed virtual reality tool combines an immersive head-mounted display, a small hand tracking device and a smartphone that are all connected to a laptop. The operator's dominant hand is tracked to quickly and coarsely manipulate either the 3D dental model or the virtual implant, while the non-dominant hand holds a smartphone converted into a controller to assist button activation and a greater input precision for 3D implant positioning and inclination. We evaluated IMMPLANT's usability and acceptance during training sessions with 16 dental professionals. RESULTS: The conducted user acceptance study revealed that IMMPLANT constitutes a versatile, portable, and complementary tool to assist implant placement learning, as it promotes immersive visualization and spatial manipulation of 3D dental anatomy. CONCLUSIONS: IMMPLANT is a promising virtual reality tool to assist student learning and 3D dental visualization for implant placement education. IMMPLANT may also be easily incorporated into training programs for dental students.

Untangling causes of variation in mercury concentration between flight feathers.

Bird feathers are one of the most widely used animal tissue in mercury biomonitoring, owing to the ease of collection and storage. They are also the principal excretory pathway of mercury in birds. However, limitations in our understanding of the physiology of mercury deposition in feathers has placed doubt on the interpretation of feather mercury concentratoins. Throughout the literature, moult sequence and the depletion of the body mercury pool have been taken to explain patterns such as the decrease in feather mercury from the innermost (P1) to the outermost primary feather (P10) of the wing. However, it has been suggested that this pattern is rather a measurement artefact as a result of the increased feather mass to length ratio along the primaries, resulting in a dilution effect in heavier feathers. Here, we attempt to untangle the causes of variation in feather mercury concentrations by quantifying the mercury concentration as µg of mercury (i) per gram of feather, (ii) per millimetre of feather, and (iii) per day of feather growth in the primary feathers of Bulwer's Petrel Bulweria bulwerii chicks, effectively controlling for some of the axes of variation that may be acting in adults, and monitoring the growth rate of primary feathers in chicks. The mercury concentration in Bulwer's Petrel chicks' primaries increased from the innermost to the outermost primary for all three concentration measures, following the order of feather emergence. These observations confirm that the pattern of mercury concentration across primary feathers is not an artefact of the measure of concentration, but is likely an effect of the order of feather growth, whereby the earlier grown feathers are exposed to higher blood mercury concentrations than are later moulted feathers as a result of blood mercury depletion.

Myasthenia Gravis Related to Thymic Carcinoma: A Case Study.

Myasthenia gravis and thymoma are often presented in association with ∼10% of myasthenic cases having concomitant thymoma. Thymic carcinoma is one of the rarest/aggressive human epithelial tumors and has no correlation with myasthenia gravis hitherto. Here is provided a clinical case and review of literature on a very rare association of thymic carcinoma (with no sign of thymoma) and myasthenia gravis (antiacetylcholine receptor antibody positive). Two years after thymectomy, clinical evolution was satisfactory. This clinical case elicits hypothesis that thymic carcinoma may be related with myasthenia gravis, what may have good prognostic from oncologic and neurologic perspectives.