Sky Image Classification Based on Transfer Learning Approaches.

Cloudy conditions at a local scale pose a significant challenge for forecasting renewable energy generation through photovoltaic panels. Consequently, having real-time knowledge of sky conditions becomes highly valuable. This information could inform decision-making processes in system operations, such as determining whether conditions are favorable for activating a standalone system requiring a minimum level of radiation or whether sky conditions might lead to higher energy consumption than generation during adverse cloudy conditions. This research leveraged convolutional neural networks (CNNs) and transfer learning (TL) classification techniques, testing various architectures from the EfficientNet family and two ResNet models for classifying sky images. Cross-validation methods were applied across different experiments, where the most favorable outcome was achieved with the EfficientNetV2-B1 and EfficientNetV2-B2 models boasting a mean Accuracy of 98.09%. This study underscores the efficacy of the architectures employed for sky image classification, while also highlighting the models yielding the best results.

Pannexin-1 expression in tumor cells correlates with colon cancer progression and survival.

AIMS: Pannexin-1 (PANX1) is a hemichannel that releases ATP upon opening, initiating inflammation, cell proliferation, and migration. However, the role of PANX1 channels in colon cancer remains poorly understood, thus constituting the focus of this study. MAIN METHODS: PANX1 mRNA expression was analyzed using multiple cancer databases. PANX1 protein expression and distribution were evaluated by immunohistochemistry on primary tumor tissue and non-tumor colonic mucosa from colon cancer patients. PANX1 inhibitors (probenecid or 10Panx) were used to assess colon cancer cell lines viability. To study the role of PANX1 in vivo, a subcutaneous xenograft model using HCT116 cells was performed in BALB/c NOD/SCID immunodeficient mice to evaluate tumor growth under PANX1 inhibition using probenecid. KEY FINDINGS: PANX1 mRNA was upregulated in colon cancer tissue compared to non-tumor colonic mucosa. Elevated PANX1 mRNA expression in tumors correlated with worse disease-free survival. PANX1 protein abundance was increased on tumor cells compared to epithelial cells in paired samples, in a cancer stage-dependent manner. In vitro and in vivo experiments indicated that blocking PANX1 reduced cell viability and tumor growth. SIGNIFICANCE: PANX1 can be used as a biomarker of colon cancer progression and blocking PANX1 channel opening could be used as a potential therapeutic strategy against this disease.

Analysis of variables to determine their influence on renewable energy forecasting using ensemble methods.

Forecasting is of great importance in the field of renewable energies because it allows us to know the quantity of energy that can be produced, and thus, to have an efficient management of energy sources. However, determining which prediction system is more adequate is very complex, as each energy infrastructure is different. This work studies the influence of some variables when making predictions using ensemble methods for different locations. In particular, the proposal analyzes the influence of the aspects: the variation of the sampling frequency of solar panel systems, the influence of the type of neural network architecture and the number of ensemble method blocks for each model. Following comprehensive experimentation across multiple locations, our study has identified the most effective solar energy prediction model tailored to the specific conditions of each energy infrastructure. The results offer a decisive framework for selecting the optimal system for accurate and efficient energy forecasting. The key point is the use of short time intervals, which is independent of type of prediction model and of their ensemble method.

Reptile Identification for Endemic and Invasive Alien Species Using Transfer Learning Approaches.

The Canary Islands are considered a hotspot of biodiversity and have high levels of endemicity, including endemic reptile species. Nowadays, some invasive alien species of reptiles are proliferating with no control in different parts of the territory, creating a dangerous situation for the ecosystems of this archipelago. Despite the fact that the regional authorities have initiated actions to try to control the proliferation of invasive species, the problem has not been solved as it depends on sporadic sightings, and it is impossible to determine when these species appear. Since no studies for automatically identifying certain species of reptiles endemic to the Canary Islands have been found in the current state-of-the-art, from the Signals and Communications Department of the Las Palmas de Gran Canaria University (ULPGC), we consider the possibility of developing a detection system based on automatic species recognition using deep learning (DL) techniques. So this research conducts an initial identification study of some species of interest by implementing different neural network models based on transfer learning approaches. This study concludes with a comparison in which the best performance is achieved by integrating the EfficientNetV2B3 base model, which has a mean Accuracy of 98.75%.

Labeled dataset for training despeckling filters for SAR imagery.

When training Artificial Intelligence and Deep Learning models, especially by using Supervised Learning techniques, a labeled dataset is required to have an input with data and its corresponding labeled output data. In the case of images, for classification, segmentation, or other processing tasks, a pair of images is required in the same sense, one image as an input (the noisy image) and the desired (the denoised image) one as an output. For SAR despeckling applications, the common approach is to have a set of optical images that then are corrupted with synthetic noise, since there is no ground truth available. The corrupted image is considered the input and the optical one is the noiseless one (ground truth). In this paper, we provide a dataset based on actual SAR images. The ground truth was obtained from SAR images of Sentinel 1 of the same region in different instants of time and then they were processed and merged into one single image that serves as the output of the dataset. Every SAR image (noisy and ground truth) was split into 1600 images of 512 × 512 pixels, so a total of 3200 images were obtained. The dataset was also split into 3000 for training and 200 for validation, all of them available in four labeled folders.

Robust Identification System for Spanish Sign Language Based on Three-Dimensional Frame Information.

Nowadays, according to the World Health Organization (WHO), of the world's population suffers from a hearing disorder that makes oral communication with other people challenging. At the same time, in an era of technological evolution and digitization, designing tools that could help these people to communicate daily is the base of much scientific research such as that discussed herein. This article describes one of the techniques designed to transcribe Spanish Sign Language (SSL). A Leap Motion volumetric sensor has been used in this research due to its capacity to recognize hand movements in 3 dimensions. In order to carry out this research project, an impaired hearing subject has collaborated in the recording of 176 dynamic words. Finally, for the development of the research, Dynamic Time Warping (DTW) has been used to compare the samples and predict the input with an accuracy of 95.17%.

Cassava Starch Films with Anthocyanins and Betalains from Agroindustrial by-Products: Their Use for Intelligent Label Development.

The development of biodegradable packaging materials has become a widely addressed topic in recent years. Microparticles generated from Brassica oleracea var. capitata f. rubra (red cabbage, RC) and Beta vulgaris L. var. conditiva (beetroot, BR) which contained anthocyanins or betalains, were included in the formulation of edible films based on cassava starch (CS) giving origin to films CSRC, CSBR, or CSBC (mixture of both particles). The inclusion of the filler determined an increase in the stress at rupture from 0.8 MPa (CS) to 1.2 MPa (CSRC) or 1.0 MPa (CSBC), of the contact angle from 2.6° to 13.8° (CSBR) or 19.6° (CSBC). The use of these films for developing a smart label for hake packaging and the study of the TBV-N content, the microbiological characteristics of the muscle, and the color changes of the label with time, allowed us to conclude that the films CSRC and CSBC would be suitable for sensing the deterioration of packaged and chilled hake and that the color change of the label CSBC was completely consistent with fish muscle deterioration. As the microparticles can be obtained from by-products of the production and industrialization of plant tissues, the composite films and the smart labels developed can contribute not only to the development of safe food but also to the addition of value to those residues and to environmental protection.

Information and Communication Technologies in Patients With Immune-Mediated Inflammatory Diseases: Cross-sectional Survey.

BACKGROUND: Information and communication technologies (ICTs) are changing the traditional health care model and redefining personalized health. ICTs offer effective communication and real-time monitoring of patients and provide additional data to support clinical decision-making, improve the quality of care, and contribute to the empowerment of patients. However, evidence on the use of ICTs and digital preferences of immune-mediated inflammatory disease (IMID) patients is scarce. OBJECTIVE: The aim of this study is to describe the degree of use of ICTs in patients with IMIDs (including rheumatic diseases, inflammatory bowel diseases, and psoriasis), identify their needs, and analyze their interest in the use of apps as tools for better management of their disease. METHODS: A questionnaire was created by a multidisciplinary team including pharmacists, rheumatologists, gastroenterologists, dermatologists, and nurses with experience in ICTs applied to the field of IMID. The survey included 27 questions organized into 3 blocks: (1) sociodemographic characteristics, (2) ICT use for health-related information, and (3) patient expectations about mobile health. RESULTS: A total of 472 questionnaires were analyzed. Overall, 52.9% (250/472) of patients were diagnosed with a rheumatologic disease, 39.4% (186/472) with inflammatory bowel disease, and 12.3% (58/472) with psoriasis. The state of health was considered good by 45.6% (215/472) of patients. Patients were interested in staying informed about health issues in 86.9% (410/427) of cases and sought health-related information mainly from the internet (334/472, 70.8%) and health care professionals (318/472, 67.4%). Overall, 13.6% (64/472) did not trust the health information they found in internet. Of the patients, 42.8% (202/472) had a health app, and 42.2% (199/472) had found it on their own. Patients would like a health app to help mainly to manage appointments (281/472, 59.5%), obtain information about their diseases and treatments (274/472, 58.1%), and get in contact with health professionals (250/472, 53.0%). Overall, 90.0% (425/472) of patients reported they would use an app to manage their IMID if their health professional recommended it, and 58.0% (274/472) would pay or probably be willing to pay for it. CONCLUSIONS: IMID patients were very interested in finding health-related information via ICTs, especially using smartphones and apps recommended by health professionals. Appointment management, advice on disease and treatment management, and personalized communication with health professionals were the most desired app features identified. Health professionals should play an essential role in recommending and validating these tools to ensure they are of high quality.

Regulation of the Intestinal Extra-Adrenal Steroidogenic Pathway Component LRH-1 by Glucocorticoids in Ulcerative Colitis.

Ulcerative colitis (UC) is an inflammatory bowel disease (IBD) and can be treated with glucocorticoids (GC), although some patients are unresponsive to this therapy. The transcription factor LRH-1/NR5A2 is critical to intestinal cortisol production (intestinal steroidogenesis), being reduced in UC patients. However, the relationship between LRH-1 expression and distribution with altered corticosteroid responses is unknown. To address this, we categorized UC patients by their steroid response. Here, we found that steroid-dependent and refractory patients presented reduced glucocorticoid receptor (GR)-mediated intestinal steroidogenesis compared to healthy individuals and responder patients, possibly related to increased colonic mucosa GR isoform beta (GRß) content and cytoplasmic LRH-1 levels in epithelial and lamina propria cells. Interestingly, an intestinal epithelium-specific GR-induced knockout (GRiKO) dextran sodium sulfate (DSS)-colitis mice model presented decreased epithelial LRH-1 expression, whilst it increased in the lamina propria compared to DSS-treated control mice. Mechanistically, GR directly induced NR5A2 gene expression in CCD841CoN cells and human colonic organoids. Furthermore, GR bound to two glucocorticoid-response elements within the NR5A2 promoter in dexamethasone-stimulated CCD841CoN cells. We conclude that GR contributes to intestinal steroidogenesis by inducing LRH-1 in epithelial cells, suggesting LRH-1 as a potential marker for glucocorticoid-impaired response in UC. However, further studies with a larger patient cohort will be necessary to confirm role of LRH-1 as a therapeutic biomarker.

Treatment of early rheumatoid arthritis: Methotrexate and beyond.

For the last several decades, the standard of care for the initial management of rheumatoid arthritis (RA) has been methotrexate. Methotrexate is effective as monotherapy and in combination with conventional, biologic, and targeted-synthetic therapies. Methotrexate is generally well-tolerated, but has important, albeit uncommon, potential side-effects including a risk of liver toxicity and cytopenias. Some studies suggest that more active monitoring in patients with fatty liver disease may be appropriate. With reassuring safety data, more rapid dose escalation and use of subcutaneous therapy may provide even greater success. Some off-target benefits such as a reduction in cardiovascular disease risk have also been demonstrated, though these studies may suffer from confounding. Recent published guidelines continue to endorse methotrexate as first-line therapy. Methotrexate is a low-cost, safe, and effective therapy for RA that should not be overlooked nor too quickly abandoned.

Clinical characteristics and evolution of hematological patients and COVID-19 in Argentina: a report from the Argentine Society of Hematology.

Individuals with malignancies and COVID-19 have a lower survival compared with the general population. However, the information about the impact of COVID-19 on the whole hematological population is scarce. We aimed to describe the 30th day overall survival (OS) after COVID-19 infection in patients with a hematological disease in Argentina. A completely anonymous survey from the Argentine Society of Hematology was delivered to all the hematologists in Argentina; it started in April 2020. A cut-off to analyze the data was performed in December 2020 and, finally, 419 patients were reported and suitable for the analysis (average age: 58 years, 90% with malignant diseases). After the COVID-19 diagnosis, the 30-day OS for the whole population was 80.2%. From the entire group (419), 101 (24.1%) individuals required intensive care unit admission, where the 30-day OS was 46.6%. Among allogeneic stem cell transplant recipients, the 30-day OS was 70.3%. Factors associated with a low OS were two or more comorbidities, an active hematological disease and history of chemotherapy. In individuals with the three factors, the 30-day OS was 49.6% while the 30-day OS in those without those factors was 100%. Patients with hematological diseases have a higher mortality than the general population. This group represents a challenge and requires careful decision-making of the treatment in order not to compromise the chances of cure.

El presente estudio tuvo por objetivo primario conocer la mortalidad de pacientes con enfermedad hematológica que presentaron infección por COVID-19 en Argentina. Para ello se difundió una encuesta desde la Sociedad Argentina de Hematología (SAH) entre los hematológos para informar sobre los pacientes con enfermedades hematológicas y diagnóstico de infección por SARS- CoV-2, entre el 19/4/2020, y el 7/12/2020. Se incluyeron individuos de todas las edades con diagnóstico de enfermedad hematológica benigna o maligna e infección por SARS-CoV-2 confirmada por técnica de RTPCR. Se analizaron 419 pacientes (mediana 58 años; 90% enfermedades malignas). La supervivencia al día 30 fue de 80.2%. La supervivencia fue menor en aquellos que requirieron internación (74.2%), cuidados intensivos (46.6%) y asistencia respiratoria mecánica (36.8%). Entre los trasplantados alogénicos la supervivencia fue 70.3%. Los factores vinculados a la supervivencia global fueron las comorbilidades, el estado de la enfermedad al momento de la infección y el antecedente de quimioterapia. Se pudo establecer un score en el que aquellos que tuvieron un puntaje de 4 alcanzaron una supervivencia del 49.6% al día 30, mientras que la de los pacientes con score 0 fue del 100% a 30 días. En comparación con la población general, los pacientes con enfermedades hematológicas presentan una mayor mortalidad vinculada al COVID-19, motivo por el cual es primordial definir pautas destinadas a disminuir la exposición de los mismos sin comprometer las posibilidades de beneficiarse del tratamiento de la enfermedad de base.

Clinical characteristics and evolution of hematological patients and COVID-19 in Argentina: a report from the Argentine Society of Hematology / Características clínicas y evolución de pacientes hematológicos y COVID-19 en Argentina: datos de la Sociedad Argentina de Hematología

Abstract Individuals with malignancies and COVID-19 have a lower survival compared with the general population. However, the information about the impact of COVID-19 on the whole hematological population is scarce. We aimed to describe the 30th day overall survival (OS) after COVID-19 infection in pa tients with a hematological disease in Argentina. A completely anonymous survey from the Argentine Society of Hematology was delivered to all the hematologists in Argentina; it started in April 2020. A cut-off to analyze the data was performed in December 2020 and, finally, 419 patients were reported and suitable for the analysis (average age: 58 years, 90% with malignant diseases). After the COVID-19 diagnosis, the 30-day OS for the whole population was 80.2%. From the entire group (419), 101 (24.1%) individuals required intensive care unit admission, where the 30-day OS was 46.6%. Among allogeneic stem cell transplant recipients, the 30-day OS was 70.3%. Factors associated with a low OS were two or more comorbidities, an active hematological disease and history of chemotherapy. In individuals with the three factors, the 30-day OS was 49.6% while the 30-day OS in those without those factors was 100%. Patients with hematological diseases have a higher mortality than the general population. This group represents a challenge and requires careful decision-making of the treatment in order not to compromise the chances of cure.

Resumen El presente estudio tuvo por objetivo primario conocer la mortalidad de pacientes con enfermedad hematológica que presentaron infección por COVID-19 en Argentina. Para ello se difundió una encuesta desde la Sociedad Argentina de Hematología (SAH) entre los hematológos para informar sobre los pacientes con enfermedades hematológicas y diagnóstico de infección por SARS- CoV-2, entre el 19/4/2020, y el 7/12/2020. Se incluyeron individuos de todas las edades con diagnóstico de enfermedad hematológica benigna o maligna e infección por SARS-CoV-2 confirmada por técnica de RT-PCR. Se analizaron 419 pacientes (mediana 58 años; 90% enfermedades malignas). La supervivencia al día 30 fue de 80.2%. La supervivencia fue menor en aquellos que requirieron internación (74.2%), cuidados intensivos (46.6%) y asistencia respiratoria mecánica (36.8%). Entre los trasplantados alogénicos la supervivencia fue 70.3%. Los factores vinculados a la supervivencia global fueron las comorbilidades, el estado de la enfermedad al momento de la infección y el antecedente de quimioterapia. Se pudo establecer un score en el que aquellos que tuvieron un puntaje de 4 alcanzaron una supervivencia del 49.6% al día 30, mientras que la de los pacientes con score 0 fue del 100% a 30 días. En comparación con la población general, los pacientes con enfermedades hematológicas presentan una mayor mortalidad vinculada al COVID-19, motivo por el cual es primordial definir pautas destinadas a disminuir la exposición de los mismos sin comprometer las posibilidades de beneficiarse del tratamiento de la enfermedad de base.

Analysis of the Nosema Cells Identification for Microscopic Images.

The use of image processing tools, machine learning, and deep learning approaches has become very useful and robust in recent years. This paper introduces the detection of the Nosema disease, which is considered to be one of the most economically significant diseases today. This work shows a solution for recognizing and identifying Nosema cells between the other existing objects in the microscopic image. Two main strategies are examined. The first strategy uses image processing tools to extract the most valuable information and features from the dataset of microscopic images. Then, machine learning methods are applied, such as a neural network (ANN) and support vector machine (SVM) for detecting and classifying the Nosema disease cells. The second strategy explores deep learning and transfers learning. Several approaches were examined, including a convolutional neural network (CNN) classifier and several methods of transfer learning (AlexNet, VGG-16 and VGG-19), which were fine-tuned and applied to the object sub-images in order to identify the Nosema images from the other object images. The best accuracy was reached by the VGG-16 pre-trained neural network with 96.25%.

Effectiveness and persistence of golimumab as a second biological drug in patients with spondyloarthritis: A retrospective study.

ABSTRACT: This observational, longitudinal retrospective, noncomparative study was designed to assess the persistence and effectiveness of golimumab as a second anti-tumor necrosis factor (TNF) drug in patients with spondyloarthritis requiring discontinuation from a first anti-TNF drug.Data were collected retrospectively for all patients with axial spondyloarthritis or psoriatic arthritis from 20 rheumatology clinics in Spain who started golimumab as a second anti-TNF drug between January 2013 and December 2015. Golimumab persistence was assessed with Kaplan-Meier survival analysis, and associated factors were assessed with Cox regression analysis.210 patients started golimumab as a second anti-TNF drug: 131 with axial spondyloarthritis and 79 with psoriatic arthritis. In axial spondyloarthritis patients, the mean (standard deviation) Bath Ankylosing Spondylitis Disease Activity Index score at baseline was 5.5 (2.1), decreasing to 3.9 (2.0) at month 3 and 3.5 (2.0) at year 1, and remaining stable thereafter. In psoriatic arthritis patients, mean (standard deviation) baseline Disease Activity Score was 4.0 (1.3), reducing to 2.5 (1.2) at month 3 and to 2.2 (1.3) at year 1. Corresponding improvements were recorded from baseline in C-reactive protein levels and erythrocyte sedimentation rates. The probability of persistence of treatment with golimumab was 80% at year 1, 70% at year 2 and 65% at years 3 and year 4, and was similar in those who had stopped the first anti-TNF due to loss of efficacy or other reasons. Cox regression analysis showed that the probability of survival with golimumab was higher in patients with higher erythrocyte sedimentation rate, in patients with axial spondyloarthritis than with psoriatic arthritis, and in those who had discontinued adalimumab as first anti-TNF. Seventy-two patients (34.3%) discontinued golimumab during follow-up, 50 of them due to lack of efficacy.In patients with spondyloarthritis requiring discontinuation from a first anti-TNF drug, treatment with golimumab was effective and showed a high probability of persistence up to 4 years of treatment.

A deep learning-based COVID-19 automatic diagnostic framework using chest X-ray images.

The lethal novel coronavirus disease 2019 (COVID-19) pandemic is affecting the health of the global population severely, and a huge number of people may have to be screened in the future. There is a need for effective and reliable systems that perform automatic detection and mass screening of COVID-19 as a quick alternative diagnostic option to control its spread. A robust deep learning-based system is proposed to detect the COVID-19 using chest X-ray images. Infected patient's chest X-ray images reveal numerous opacities (denser, confluent, and more profuse) in comparison to healthy lungs images which are used by a deep learning algorithm to generate a model to facilitate an accurate diagnostics for multi-class classification (COVID vs. normal vs. bacterial pneumonia vs. viral pneumonia) and binary classification (COVID-19 vs. non-COVID). COVID-19 positive images have been used for training and model performance assessment from several hospitals of India and also from countries like Australia, Belgium, Canada, China, Egypt, Germany, Iran, Israel, Italy, Korea, Spain, Taiwan, USA, and Vietnam. The data were divided into training, validation and test sets. The average test accuracy of 97.11 ± 2.71% was achieved for multi-class (COVID vs. normal vs. pneumonia) and 99.81% for binary classification (COVID-19 vs. non-COVID). The proposed model performs rapid disease detection in 0.137 s per image in a system equipped with a GPU and can reduce the workload of radiologists by classifying thousands of images on a single click to generate a probabilistic report in real-time.

Efficient Multi-Object Detection and Smart Navigation Using Artificial Intelligence for Visually Impaired People.

Visually impaired people face numerous difficulties in their daily life, and technological interventions may assist them to meet these challenges. This paper proposes an artificial intelligence-based fully automatic assistive technology to recognize different objects, and auditory inputs are provided to the user in real time, which gives better understanding to the visually impaired person about their surroundings. A deep-learning model is trained with multiple images of objects that are highly relevant to the visually impaired person. Training images are augmented and manually annotated to bring more robustness to the trained model. In addition to computer vision-based techniques for object recognition, a distance-measuring sensor is integrated to make the device more comprehensive by recognizing obstacles while navigating from one place to another. The auditory information that is conveyed to the user after scene segmentation and obstacle identification is optimized to obtain more information in less time for faster processing of video frames. The average accuracy of this proposed method is 95.19% and 99.69% for object detection and recognition, respectively. The time complexity is low, allowing a user to perceive the surrounding scene in real time.

Patients' perceptions on shared decision making during prescription of subcutaneous biological drug treatments for inflammatory arthritis: The RHEU-LIFE survey.

OBJECTIVES: The aim of this study was to explore the preferences of patients with rheumatic diseases and their perceived experience regarding participation in shared decision making (SDM) when they were prescribed a subcutaneous (SC) biological drug. METHODS: A printed survey was handed to 1,000 patients with inflammatory rheumatic diseases treated with SC biological drug. The survey included closed questions about preferences regarding decision making and about patients' experience when they were prescribed an SC biological drug. Descriptive statistics were performed with stratification by patient profiles, using chi-square for comparisons between groups. RESULTS: A total of 592 surveys were received (response rate 59.2%, mean age 51.7 years, 57.6% women). Some 28.2% of patients reported preferring to take part in treatment selection, a percentage that was higher in younger patients, in those with higher academic degree and in those who search information in sources different to that of health care professionals. Over half of patients (56.3%) perceived that the rheumatologist considered their opinion when prescribing an SC biological drug, a percentage higher in younger people. Only in 40.8% of cases did the patients' preference match their perception of their participation in the process. No differences were observed by sex, disease or number of biologics. CONCLUSIONS: Patients with inflammatory rheumatic diseases want information about their treatments but mostly leave the prescription decision to the rheumatologist. Younger people, or those with higher academic degree, more often want to participate in the SDM. There are discrepancies between patient preferences and perceptions of this process.

Perspective and Evolution of Gesture Recognition for Sign Language: A Review.

This review analyses the different gesture recognition systems through a timeline, showing the different types of technology, and specifying which are the most important features and their achieved recognition rates. At the end of the review, Leap Motion sensor possibilities are described in detail, in order to consider its application on the field of sign language. This device has many positive characteristics that make it a good option for sign language. One of the most important conclusions is the ability of the Leap Motion sensor to provide 3D information from the hands for due identification.

Pistol and Rifle Performance: Gender and Relative Age Effect Analysis.

BACKGROUND: The sport overrepresentation of early-born athletes within a selection year is called relative age effect (RAE). Moreover, gender performance differences depend on the sport. The main objectives of the study were to compare performances between gender and RAE in precision shooting events. METHOD: The results of 704 shooters who participated in the most recent World Shooting Championship were compared. Performance was analysed by event (rifle and pistol), gender and category (junior and senior), together with RAE and six ranges of ranking positions. RESULTS: The results of the study indicated that men scored higher than women in pistol events and that no performance differences were found in rifle events when the whole group was compared. According to the birth trimester, no significant differences were found in the participant's distribution, nor in performance in any case. CONCLUSIONS: The main conclusions of the study are: (1) the men's pistol performance is better than the women's even though RAE is not associated to the shooting score in any case; (2) men and women performed equally in the general analysis, but their performances were different depending on category and event with no RAE influence.

Oral masses in African pygmy hedgehogs.

African pygmy hedgehogs (Atelerix albiventris) frequently develop oral neoplasms, and most of these neoplasms are malignant. We characterized oral masses detected in hedgehogs at clinical examination. During a 1-y period, we diagnosed oral cavity masses in 27 privately owned hedgehogs; 16 were female and 11 were male, with ages of 2-7 y (mean: 4.3 y). Eight masses were non-neoplastic and were diagnosed as gingival hyperplasia (GH). Nineteen masses were neoplastic, of which 17 were squamous cell carcinomas (SCCs) and 2 were mesenchymal tumors (1 spindle cell tumor of probable neural origin, and 1 hemangiosarcoma). The GHs were noninvasive, exophytic, and did not recur after surgical excision. The SCCs were highly invasive tumors that induced facial deformation and were located in the caudal portion of the oral cavity, with 12 of them arising from the right-caudal maxilla. Thus, clinical signs, growth pattern, and anatomic location can be used to suspect a diagnosis of SCC among the other possible diagnoses, such as GH, in this location. However, histopathology is necessary for confirmation. Also, hemangiosarcoma should be considered among the differential diagnoses.