An Unparalleled Sexual Dimorphism of Sperm Whale Encephalization

The sperm whale Physeter macrocephalus (Linnaeus, 1758) is the largest toothed whales and possesses the highest absolute values for brain weight on the planet (together with the killer whale Orcinus orca). Former calculations of the encephalization quotient (EQ), which is used to compare brain size of different mammalian species, showed that the sperm whale brain is smaller than expected for its body mass. However, the data reported in the literature and formerly used to calculate the sperm whale EQ suffered from a potential bias due to the tendency to measure mostly larger males of this extreme sexually dimorphic species. Accordingly, we found that the brains of female sperm whales are close to the absolute weight range of the males, but, given the much lower body mass of females, their EQ results more than double of what reported before for the whole species, and is thus nearly into the primate range (female EQ = 1.28, male EQ = 0.56). This sexual dimorphism is unique among mammals. Female sperm whales live in large families in which social interactions and inter-individual communication are essential, while adult males live solitarily. Thus the particular sex-specific behavior of SWs may have led to a maternally-driven social evolution, and eventually contributed to achieve female EQ values (but not male EQs) among the highest ever calculated for mammals with respect to their large body mass

Evaluation about clinical risk knowledge in Italian medicine students: How to implement the concept of healthcare quality among future doctors

The aim of the study is to offer to all the future health providers an opportunity of education in the specific field of patient's safety and clinical risk management. The study develops a complete picture of the knowledge of a whole class of future physicians about clinical risk theme, involved 1228 students of a medicine course. We elaborated a survey (18 explorative questions) that evaluated the levels about basic concepts in clinical risk management and investigated the future doctors' opinion about the use of these instruments. The results emphasize a deep delay compared to international standards about basic notions. We propose as future target both monitoring the notional trend about investigated themes of the survey and sensitizing the future health operators and decision makers about basic clinical risk concepts. Moreover, we try to give the timing of fundamental steps to improve the awareness and the management of Clinical Risk

Relationship of diagnostic accuracy of renal cortical echogenicity with renal histopathology in dogs and cats, a quantitative study

Renal cortical echogenicity is routinely evaluated during ultrasonographic investigation of the kidneys. Both in dog and cat previous ex-vivo studies have revealed a poor correlation between renal echogenicity and corresponding lesions. The aim of this study was to establish the in-vivo relationship between renal cortical echogenicity and renal histopathology

Normal computed tomographic features and reference values for the coelomic cavity in pet parrots

BACKGROUND: The increasing popularity gained by pet birds over recent decades has highlighted the role of avian medicine and surgery in the global veterinary scenario; such a need for speciality avian medical practice reflects the rising expectation for high-standard diagnostic imaging procedures. The aim of this study is to provide an atlas of matched anatomical cross-sections and contrast-enhanced CT images of the coelomic cavity in three highly diffused psittacine species. RESULTS: Contrast-enhanced computed tomographic studies of the coelomic cavity were performed in 5 blue-and-gold macaws, 4 African grey parrots and 6 monk parakeets by means of a 4-multidetector-row CT scanner. Both pre- and post-contrast scans were acquired. Anatomical reference cross-sections were obtained from 5 blue-and-gold macaw, 7 African grey parrot, and 9 monk parakeet cadavers. The specimens were stored in a −20 °C freezer until completely frozen and then sliced at 5-mm intervals by means of a band saw. All the slices were photographed on both sides. Individual anatomical structures were identified by means of the available literature. Pre- and post-contrast attenuation reference values for the main coelomic organs are reported in Hounsfield units (HU). CONCLUSIONS: The results provide an atlas of matched anatomical cross-sections and contrast-enhanced CT images of the coelomic cavity in three highly diffused psittacine species

Accuracy of deep learning to differentiate the histopathological grading of meningiomas on MR images: a preliminary study

Background: Grading of meningiomas is important in the choice of the most effective treatment for each patient. Purpose: To determine the diagnostic accuracy of a deep convolutional neural network (DCNN) in the differentiation of the histopathological grading of meningiomas from MR images. Study Type: Retrospective. Population: In all, 117 meningioma-affected patients, 79 World Health Organization [WHO] Grade I, 32 WHO Grade II, and 6 WHO Grade III. Field Strength/Sequence: 1.5 T, 3.0 T postcontrast enhanced T1 W (PCT1W), apparent diffusion coefficient (ADC) maps (b values of 0, 500, and 1000 s/mm2). Assessment: WHO Grade II and WHO Grade III meningiomas were considered a single category. The diagnostic accuracy of the pretrained Inception-V3 and AlexNet DCNNs was tested on ADC maps and PCT1W images separately. Receiver operating characteristic curves (ROC) and area under the curve (AUC) were used to asses DCNN performance. Statistical Test: Leave-one-out cross-validation. Results: The application of the Inception-V3 DCNN on ADC maps provided the best diagnostic accuracy results, with an AUC of 0.94 (95% confidence interval [CI], 0.88\u20130.98). Remarkably, only 1/38 WHO Grade II\u2013III and 7/79 WHO Grade I lesions were misclassified by this model. The application of AlexNet on ADC maps had a low discriminating accuracy, with an AUC of 0.68 (95% CI, 0.59\u20130.76) and a high misclassification rate on both WHO Grade I and WHO Grade II\u2013III cases. The discriminating accuracy of both DCNNs on postcontrast T1W images was low, with Inception-V3 displaying an AUC of 0.68 (95% CI, 0.59\u20130.76) and AlexNet displaying an AUC of 0.55 (95% CI, 0.45\u20130.64). Data Conclusion: DCNNs can accurately discriminate between benign and atypical/anaplastic meningiomas from ADC maps but not from PCT1W images. Level of evidence: 2 Technical Efficacy: Stage

Use of deep learning to detect cardiomegaly on thoracic radiographs in dogs

The purpose of this study was to develop a computer-aided detection (CAD) device based on convolutional neural networks (CNNs) to detect cardiomegaly from plain radiographs in dogs. Right lateral chest radiographs (n = 1465) were retrospectively selected from archives. The radiographs were classified as having a normal cardiac silhouette (No-vertebral heart scale [VHS]-Cardiomegaly) or an enlarged cardiac silhouette (VHS-Cardiomegaly) based on the breed-specific VHS. The database was divided into a training set (1153 images) and a test set (315 images). The diagnostic accuracy of four different CNN models in the detection of cardiomegaly was calculated using the test set. All tested models had an area under the curve >0.9, demonstrating high diagnostic accuracy. There was a statistically significant difference between Model C and the remainder models (Model A vs. Model C, P = 0.0298; Model B vs. Model C, P = 0.003; Model C vs. Model D, P = 0.0018), but there were no significant differences between other combinations of models (Model A vs. Model B, P = 0.395; Model A vs. Model D, P = 0.128; Model B vs. Model D, P = 0.373). Convolutional neural networks could therefore assist veterinarians in detecting cardiomegaly in dogs from plain radiographs

Patient Safety Walkaround: a communication tool for the reallocation of health service resources: An Italian experience of safety healthcare implementation

The study aims to evaluate the use of Patient Safety Walkaround (SWR) execution model in an Italian Hospital, through the adoption of parametric indices, survey tools, and process indicators.In the 1st meeting an interview was conducted to verify the knowledge of concepts of clinical risk management (process indicators). One month after, the questions provided by Frankel (survey tool) were administered.Each month after, an SWR has been carried trying to assist the healthcare professionals and collecting suggestions and solutions.Results have been classified according to Vincent model and analyzed to define an action plan. The amount of risk was quantified by the risk priority index (RPI).An organizational deficit concerns the management of the operating theatre.A state of intolerance was noticed of queuing patients for outpatient visits. The lack of scheduling of the operating rooms is often the cause of sudden displacements. A consequence is the conflict between patients and caregivers. Other causes of the increase of waiting times are the presence in the ward of a single trolley for medications and the presence of a single room for admission and preadmission of patients.Patients victims of allergic reactions have attributed such reactions to the presence of other patients in the process of acceptance and collection of medical history.All health professionals have reported the problem of n high number of relatives of the patients in the wards.Our study indicated the consistency of SWR as instrument to improve the quality of the care

Fracture strength and ribbond fibers : in vitro analysis of mod restorations

Ribbond fibers are supposed to be a reinforcing material in restoration of compromised teeth. This study aims to compare MOD restorations with and without Ribbond Fiber in terms of fracture strength under axial loading; to identify the minimum depth of M