Primary small cell neuroendocrine carcinoma of the breast: The histogenetic diatribe

LETTER TO EDITO

Deep roots: Improving CNN efficiency with hierarchical filter groups

We propose a new method for creating computationally efficient and compact convolutional neural networks (CNNs) using a novel sparse connection structure that resembles a tree root. This allows a significant reduction in computational cost and number of parameters compared to state-of-the-art deep CNNs, without compromising accuracy, by exploiting the sparsity of inter-layer filter dependencies. We validate our approach by using it to train more efficient variants of state-of-the-art CNN architectures, evaluated on the CIFAR10 and ILSVRC datasets. Our results show similar or higher accuracy than the baseline architectures with much less computation, as measured by CPU and GPU timings. For example, for ResNet 50, our model has 40% fewer parameters, 45% fewer floating point operations, and is 31% (12%) faster on a CPU (GPU). For the deeper ResNet 200 our model has 25% fewer floating point operations and 44% fewer parameters, while maintaining state-of-the-art accuracy. For GoogLeNet, our model has 7% fewer parameters and is 21% (16%) faster on a CPU (GPU).Microsoft Research PhD Scholarshi

Metastatic seeding of colon adenocarcinoma manifesting as synchronous breast and chest wall localization: report of a case.

Colon carcinoma rarely metastasizes to the breast and it is usually associated with a poor prognosis. Even rarer is metastatic seeding of colon cancer cells in an intramammary location after surgery. Including a primary breast malignancy in the differential diagnosis of such cases is mandatory. We report a rare case of double seeding implantation of colon adenocarcinoma inside the breast parenchyma and intercostal muscles 6 years after resection of a pulmonary metastasis from colon adenocarcinoma. The metastasis was revealed by the presence of bone metaplasia in the intercostal muscles. We discuss how negative immunostaining for estrogen receptors, progesterone receptors, and HER-2, along with the immunohistochemical pattern of cytokeratin (CK) 20+/7-/5- and CDX2-positive immunostaining, excludes a primary breast malignancy, namely, a "matrix-producing" carcinoma, from the differential diagnosis. We also present the hypothesis of a paracrine pathogenetic mechanism to explain the bone metaplasia

Rainfall depth-duration-frequency curves for short-duration precipitation events in Sicily (Italy)

The design criteria of the hydraulic infrastructures, including, for instance, those for flood defense, urban drainage systems, reservoirs spillways and bridges, are based on the coupled analysis of the magnitude of rainfall events for a fixed duration and their estimated annual exceedance probability. The well-known rainfall depth-duration-frequency (DDF) curves, typically derived from the analysis of long historical annual maxima data series, synthesize the relationships between rainfall depth, duration and exceedance probability which is usually expressed as a return period. The time-resolution of rainfall data typically available for the construction of DDF curves and provided by gauges having large sample size, is hourly or coarser; this has allowed the definition of statistically consistent and reliable curves, suitable for rainfall duration hourly or longer, while, for shorter duration, empirical relationships with a high degree of approximation are generally used. Small river basins and plot-size areas with short response time, as well as urban drainage systems, are expected to be particularly vulnerable to sub-hourly intense rainfall events. Many practical applications, design procedures and mathematical models indeed require a finer time-resolution (i.e. sub - hourly). Moreover, in many regions of the world, such as the Sicily (Italy), an intensification of short-duration rainfall events is observed probably in response to the ongoing climate changes. This work proposes an approach for estimating the distribution of sub-hourly extreme rainfalls and extending depth–duration–frequency (DDF) curves derived for duration over the hourly also to sub-hourly durations. The approach is applied in Sicily starting from the coupled analysis of two different databases. The former (OA-ARRA database) contains long series of annual maxima for the fixed duration of 1, 3, 6, 12 and 24 hours for about 250 gauges, while the latter (SIAS database), include 10-minutes rainfall data series for about 100 gauges collected during the last 15 years (from 2003 to now), form which annual maxima time-series for fixed sub-hourly duration are derived. The approach includes a procedure for pairing raingauges, provided from the two databases, according to a distance- and elevation-based criterion and consolidated inference statistical techniques for the coupled analysis of the data-series from the two gauges

Detecting precipitation trend using a multiscale approach based on quantile regression over a Mediterranean area

One of the most relevant and debated topics related to the effects of the climate change is whether intense rainfall events have become more frequent over the last decades. It is a crucial aspect, since an increase in the magnitude and frequency of occurrence of heavy rainfall events could result in a dramatic growth of floods and, in turn, human lives losses and economic damages. Because of its central position in the Mediterranean area, Sicily has been often screened with the aim to capture some trends in precipitation, potentially related to climate change. While Mann-Kendall test has been largely used for the rainfall trend detection, in this work a different procedure is considered. Precipitation trends are here investigated by processing the whole rainfall time-series, provided by the regional agency SIAS at a 10-min resolution, through the quantile regression method by aggregating precipitation across a wide spectrum of durations and considering different quantiles. Results show that many rain gauges are characterized by an increasing trend in sub-hourly precipitation intensity, especially at the highest quantiles, thus suggesting that, from 2002 to 2019, sub-hourly events have become more intense in most of the island. Moreover, by analysing some spatial patterns, it has been revealed that the south and the east of Sicily are more interested in significant increasing rainfall trends, especially at the 10-min duration. Finally, the comparison between the two procedures revealed a stronger reliability of the quantile regression in the trend analysis detection, mainly due to the possibility of investigating the temporal variation of the tails of precipitation distribution

TTF-1/p63-positive poorly differentiated NSCLC: A histogenetic hypothesis from the basal reserve cell of the terminal respiratory unit

TTF-1 is expressed in the alveolar epithelium and in the basal cells of distal terminal bronchioles. It is considered the most sensitive and specific marker to define the adenocarcinoma arising from the terminal respiratory unit (TRU). TTF-1, CK7, CK5/6, p63 and p40 are useful for typifying the majority of non-small-cell lung cancers, with TTF and CK7 being typically expressed in adenocarcinomas and the latter three being expressed in squamous cell carcinoma. As tumors with coexpression of both TTF-1 and p63 in the same cells are rare, we describe different cases that coexpress them, suggesting a histogenetic hypothesis of their origin. We report 10 cases of poorly differentiated non-small-cell lung carcinoma (PD-NSCLC). Immunohistochemistry was performed by using TTF-1, p63, p40 (∆Np63), CK5/6 and CK7. EGFR and BRAF gene mutational analysis was performed by using real-time PCR. All the cases showed coexpression of p63 and TTF-1. Six of them showing CK7+ and CK5/6− immunostaining were diagnosed as “TTF-1+ p63+ adenocarcinoma”. The other cases of PD-NSCLC, despite the positivity for CK5/6, were diagnosed as “adenocarcinoma, solid variant”, in keeping with the presence of TTF-1 expression and p40 negativity. A “wild type” genotype of EGFR was evidenced in all cases. TTF1 stained positively the alveolar epithelium and the basal reserve cells of TRU, with the latter also being positive for p63. The coexpression of p63 and TTF-1 could suggest the origin from the basal reserve cells of TRU and represent the capability to differentiate towards different histogenetic lines. More aggressive clinical and morphological features could characterize these “basal-type tumors” like those in the better known “basal-like” cancer of the breast

Refining Architectures of Deep Convolutional Neural Networks

© 2016 IEEE. Deep Convolutional Neural Networks (CNNs) have recently evinced immense success for various image recognition tasks [11, 27]. However, a question of paramount importance is somewhat unanswered in deep learning research - is the selected CNN optimal for the dataset in terms of accuracy and model size? In this paper, we intend to answer this question and introduce a novel strategy that alters the architecture of a given CNN for a specified dataset, to potentially enhance the original accuracy while possibly reducing the model size. We use two operations for architecture refinement, viz. stretching and symmetrical splitting. Stretching increases the number of hidden units (nodes) in a given CNN layer, while a symmetrical split of say K between two layers separates the input and output channels into K equal groups, and connects only the corresponding input-output channel groups. Our procedure starts with a pre-trained CNN for a given dataset, and optimally decides the stretch and split factors across the network to refine the architecture. We empirically demonstrate the necessity of the two operations. We evaluate our approach on two natural scenes attributes datasets, SUN Attributes [16] and CAMIT-NSAD [20], with architectures of GoogleNet and VGG-11, that are quite contrasting in their construction. We justify our choice of datasets, and show that they are interestingly distinct from each other, and together pose a challenge to our architectural refinement algorithm. Our results substantiate the usefulness of the proposed method

Adopting the IS 2009 Model Curriculum: Apanel Session to Address the Challenges for Program Implementation

This panel session is designed to initiate an open forum and frank discussion of the IS 2009 Model Curriculum proposed by the Joint IS 2009 Curriculum Task Force and developed as a cooperative effort by the Association for Computing Machinery (ACM) and the Association for Information Systems (AIS). Following an introduction to the new model curriculum, a summary and overview of the changes from IS 97/2002 to the IS 2009 recommended core and elective courses will be presented and a panel representing academia and business will address possible issues, challenges, and implications of implementing the suggested curriculum changes on the major stakeholders that include students, faculty, administration, infrastructure resources, and the business community. Concluding the session will be an open forum to allow audience participation in the discussion for the purpose of exchanging ideas on the implementation of the new model curriculum

In vitro and ex vivo methods predict the enhanced lung residence time of liposomal ciprofloxacin formulations for nebulisation

Liposomal ciprofloxacin formulations have been developed with the aim of enhancing lung residence time, thereby reducing the burden of inhaled antimicrobial therapy which requires multiple daily administration due to rapid absorptive clearance of antibiotics from the lungs. However, there is a lack of a predictive methodology available to assess controlled release inhalation delivery systems and their effect on drug disposition. In this study, three ciprofloxacin formulations were evaluated: a liposomal formulation, a solution formulation and a 1:1 combination of the two (mixture formulation). Different methodologies were utilised to study the release profiles of ciprofloxacin from these formulations: (i) membrane diffusion, (ii) air interface Calu-3 cells and (iii) isolated perfused rat lungs. The data from these models were compared to the performance of the formulations in vivo. The solution formulation provided the highest rate of absorptive transport followed by the mixture formulation, with the liposomal formulation providing substantially slower drug release. The rank order of drug release/transport from the different formulations was consistent across the in vitro andex vivo methods, and this was predictive of the profiles in vivo. The use of complimentary in vitro and ex vivo methodologies provided a robust analysis of formulation behaviour, including mechanistic insights, and predicted in vivo pharmacokinetics.© 2013 Elsevier B.V. All rights reserved