Endoscopic endonasal management of recurrent petrous apex cholesterol granuloma.

Petrous apex cholesterol granulomas (PACG) are uncommon lesions. Recurrence following transcranial or endonasal approaches to aerate the cyst occurs in up to 60% of cases. We describe the technical nuances pertinent to the endonasal endoscopic management of a recurrent symptomatic PACG and review the literature. A 19-year-old woman presented with a recurrent right abducens nerve paresis. Four months prior, she underwent an endonasal transsphenoidal surgery (TSS) for drainage of a symptomatic PACG. Current imaging documented recurrence of the right PACG. Transsphenoidal and infrapetrous approaches were performed to obtain a wider bony opening along the petrous apex and drain the cyst. A Doyle splint was inserted into the cyst's cavity and extended out into the sphenoid, maintaining patency during the healing process. Three months after surgery, the splint was removed endoscopically, allowing visualization of a patent cylindrical communication between both aerated cavities. The patient remains symptom- and recurrence-free. Endoscopic endonasal surgery must be adapted to manage recurrent PACG. A TSS may not be sufficient. An infrapetrous approach with wider bony opening, extensive removal of the cyst's anterior wall, and use of a stent are indicated for the treatment of recurrent PACG and to prevent recurrences

Mortality Prediction Analysis among COVID-19 Inpatients Using Clinical Variables and Deep Learning Chest Radiography Imaging Features.

The emergence of the COVID-19 pandemic over a relatively brief interval illustrates the need for rapid data-driven approaches to facilitate clinical decision making. We examined a machine learning process to predict inpatient mortality among COVID-19 patients using clinical and chest radiographic data. Modeling was performed with a de-identified dataset of encounters prior to widespread vaccine availability. Non-imaging predictors included demographics, pre-admission clinical history, and past medical history variables. Imaging features were extracted from chest radiographs by applying a deep convolutional neural network with transfer learning. A multi-layer perceptron combining 64 deep learning features from chest radiographs with 98 patient clinical features was trained to predict mortality. The Local Interpretable Model-Agnostic Explanations (LIME) method was used to explain model predictions. Non-imaging data alone predicted mortality with an ROC-AUC of 0.87 ± 0.03 (mean ± SD), while the addition of imaging data improved prediction slightly (ROC-AUC: 0.91 ± 0.02). The application of LIME to the combined imaging and clinical model found HbA1c values to contribute the most to model prediction (17.1 ± 1.7%), while imaging contributed 8.8 ± 2.8%. Age, gender, and BMI contributed 8.7%, 8.2%, and 7.1%, respectively. Our findings demonstrate a viable explainable AI approach to quantify the contributions of imaging and clinical data to COVID mortality predictions

An Intermediate Redshift Supernova Search at ESO: Reduction Tools and Efficiency Tests

We present the reduction and archiving tools developed for our search for supernovae at intermediate redshifts at ESO as well as the efficiency tests performed. The data reduction recipes developed for the SN candidates selection are described. All the variable sources detected are stored using a MySQL database which enables the identification of previously detected variable sources during past observational runs. Finally, experiments performed with artificial stars have shown that seeing plays a crucial role for the limiting magnitude of detection. Crucial is also the detection threshold used by Sextractor.Comment: Poster presented at the ESO/MPA/MPE Workshop "From Twilight to Highlight, The Physics of Supernovae", Garching, Jul 29-31, 2002, to be published in the Conference Proceeding

Relationship between gastric pouch and GERD after laparoscopic sleeve gastrectomy

open9noAims and objectives Laparoscopic Sleeve Gastrectomy (LSG) is considered safe and effective even as conversion procedure after primary bariatric operations. The correlation between gastric pouch volumes and gastro-esophageal reflux disease's (GERD) symptoms (heartburn, reflux, regurgitation) remains unclear (1, 2). With this study we want to assess a correlation between the gastric remnant size and GERD.openPomerri, F.; Romanucci, G.; Barbiero, G.; Zuliani, M.; Ortu, V.; Miotto, D.; Albanese, A.; Prevedello, L.; Foletto, M.Pomerri, Fabio; Romanucci, G.; Barbiero, G.; Zuliani, M.; Ortu, V.; Miotto, Diego; Albanese, A.; Prevedello, L.; Foletto, M

Investigation of Association between Susceptibility to Leprosy and SNPs inside and near the BCHE Gene of Butyrylcholinesterase

Leprosy is a chronic disease caused by Mycobacterium leprae and affects the skin and the peripheral nervous system. Butyrylcholinesterase is coded by the BCHE gene, and the atypical allele (70G; rs1799807) has been investigated as a leprosy risk factor, with conflicting results. The present study estimated the frequencies of variants of rs1799807 and of five additional SNPs at the BCHE gene or near it: rs1126680, rs1803274, rs2863381, rs4440084, and rs4387996. A total of 167 patients and 150 healthy controls were genotyped by TaqMan PCR. Significantly higher allelic (70G) and genotypic (70DG) frequencies in rs1799807 were found in the patient group, with odds ratio (OR) of 6.33 (1.40 to 28.53) for the heterozygote. This finding was replicated in a comparison of the cases against a control group of 361 blood donors. The present data suggest that the atypical BChE variant may predispose to leprosy per se

The effect of timing and composition of gestational weight gain in obese pregnant women on infant birth weight: A prospective cohort study.

Introduction: CK2 is a protein kinase implicated in several essential cellular processes, over-expressed in cancer and described to regulate insulin signaling cascade. Recently CK2 has been described to negatively regulate thermogenesis (Shinoda K et al, 2015, Cell Metabolism) and to inhibit insulin release (Rossi M et al, 2015, PNAS). Nevertheless, the role of CK2 in adipose tissue (AT) and its involvement in human obesity development and therapy has been poorly investigated. Methods: Our multi-disciplinary team performed biochemical analysis of signaling pathways by WB and in vitro kinase activity assays, and glucose handling studies using glucose uptake assay and IF in adipocyte cultures and glucose and insulin tolerance test in mice. Moreover we quantify CK2 expression/activity in human AT specimens of 27 obese patients, clinically characterized, in 12 obese patients underwent relevant weight loss and 11 normal-weight controls. Results: We proved that CK2 amount and activity were not influenced by insulin stimulation and that CK2 activity was efficiently inhibited by specific inhibitors, structurally unrelated. We worked with CX-4945, a CK2 inhibitor currently used in cancer clinical trials, using the minimal concentration (2.5 \u192 dM) and pre-treatment time (1hr) able to efficiently inhibit CK2 activity, avoiding any cytotoxic effect. Pharmacological inhibition of CK2 did not significantly affect in vitro adipogenic differentiation or expression profiling of mature adipocytes. Conversely, we showed that in human and murine adipocytes CK2-inhibition decreases the insulin-induced glucose uptake by counteracting Akt-signaling and GLUT4-translocation to the plasma membrane. We compared CK2 expression and activity in different mouse tissues highlighted that white skeletal muscle fibres and liver contained the highest quantity of this kinase. CK2 was expressed more in brown AT than in white AT depots. We show that CK2 promotes insulin-signaling in mouse AT, liver and skeletal muscle and that in vivo acute treatment with CX-4945 impairs glucose- tolerance in mice. Studies in tissues of ob/ob and db/db mice highlights an up-regulation of CK2 expression and activity only in WAT. CK2 hyper-activation is strongly evident also in SAT and VAT of obese patients and weight loss obtained by bariatric surgery or hypocaloric diet reverts CK2 up-regulation to normal level. Conclusion: We show that CK2 is involved in insulin sensitivity, glucose handling and remodeling of WAT. Moreover we identify CK2 hyper-activation as a hallmark of human obesity, suggesting a new potential therapeutic target for metabolic diseases

Atlantic mammal traits: a dataset of morphological traits of mammals in the atlantic forest of south America

Measures of traits are the basis of functional biological diversity. Numerous works consider mean species-level measures of traits while ignoring individual variance within species. However, there is a large amount of variation within species and it is increasingly apparent that it is important to consider trait variation not only between species, but also within species. Mammals are an interesting group for investigating trait-based approaches because they play diverse and important ecological functions (e.g., pollination, seed dispersal, predation, grazing) that are correlated with functional traits. Here we compile a data set comprising morphological and life history information of 279 mammal species from 39,850 individuals of 388 populations ranging from −5.83 to −29.75 decimal degrees of latitude and −34.82 to −56.73 decimal degrees of longitude in the Atlantic forest of South America. We present trait information from 16,840 individuals of 181 species of non-volant mammals (Rodentia, Didelphimorphia, Carnivora, Primates, Cingulata, Artiodactyla, Pilosa, Lagomorpha, Perissodactyla) and from 23,010 individuals of 98 species of volant mammals (Chiroptera). The traits reported include body mass, age, sex, reproductive stage, as well as the geographic coordinates of sampling for all taxa. Moreover, we gathered information on forearm length for bats and body length and tail length for rodents and marsupials. No copyright restrictions are associated with the use of this data set. Please cite this data paper when the data are used in publications. We also request that researchers and teachers inform us of how they are using the data.Fil: Gonçalves, Fernando. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Bovendorp, Ricardo S.. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Beca, Gabrielle. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Bello, Carolina. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Costa Pereira, Raul. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Muylaert, Renata L.. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Rodarte, Raisa R.. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Villar, Nacho. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Souza, Rafael. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Graipel, Maurício E.. Universidade Federal de Santa Catarina; BrasilFil: Cherem, Jorge J.. Caipora Cooperativa, Florianopolis; BrasilFil: Faria, Deborah. Universidade Estadual de Santa Cruz; BrasilFil: Baumgarten, Julio. Universidade Estadual de Santa Cruz; BrasilFil: Alvarez, Martín R.. Universidade Estadual de Santa Cruz; BrasilFil: Vieira, Emerson M.. Universidade do Brasília; BrasilFil: Cáceres, Nilton. Universidade Federal de Santa María. Santa María; BrasilFil: Pardini, Renata. Universidade de Sao Paulo; BrasilFil: Leite, Yuri L. R.. Universidade Federal do Espírito Santo; BrasilFil: Costa, Leonora Pires. Universidade Federal do Espírito Santo; BrasilFil: Mello, Marco Aurelio Ribeiro. Universidade Federal de Minas Gerais; BrasilFil: Fischer, Erich. Universidade Federal do Mato Grosso do Sul; BrasilFil: Passos, Fernando C.. Universidade Federal do Paraná; BrasilFil: Varzinczak, Luiz H.. Universidade Federal do Paraná; BrasilFil: Prevedello, Jayme A.. Universidade do Estado de Rio do Janeiro; BrasilFil: Cruz-Neto, Ariovaldo P.. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Carvalho, Fernando. Universidade do Extremo Sul Catarinense; BrasilFil: Reis Percequillo, Alexandre. Universidade de Sao Paulo; BrasilFil: Paviolo, Agustin Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; ArgentinaFil: Duarte, José M. B.. Universidade Estadual Paulista Julio de Mesquita Filho; Brasil. Fundación Oswaldo Cruz; BrasilFil: Bernard, Enrico. Universidade Federal de Pernambuco; BrasilFil: Agostini, Ilaria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; ArgentinaFil: Lamattina, Daniela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste; Argentina. Ministerio de Salud de la Nación; ArgentinaFil: Vanderhoeven, Ezequiel Andres. Ministerio de Salud de la Nación; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste; Argentin