Ramipril for claudication?

This ACE inhibitor can help patients with peripheral artery disease walk longer while remaining pain free

Sum-Product Network structure learning by efficient product nodes discovery

Sum-Product Networks (SPNs) are recently introduced deep probabilistic models providing exact and tractable inference. SPNs have been successfully employed in several application domains, from computer vision to natural language processing, as accurate density estimators. However, learning their structure and parameters from high dimensional data poses a challenge in terms of time complexity. Classical SPNs structure learning algorithms work by repeating several times two high cost operations: determining independencies among random variables (RVs)-introducing product nodes-and finding sub-populations among samples-introducing sum nodes. Even one of the simplest greedy structure learner, LearnSPN, scales quadratically in the number of the variables to determine RVs independencies. In this work, we investigate the trade-off between accuracy and efficiency when employing approximate but fast procedures to determine independencies among RVs. We introduce and evaluate sub-quadratic procedures based on a random subspace approach and leveraging entropy as a proxy criterion to split independent RVs. Experimental results on many benchmark datasets for density estimation show that LearnSPN-like structure learners, when equipped by our splitting procedures, provide reduced learning and/or inference times, generally containing the degradation of inference accuracy. Ultimately, we provide an empirical confirmation of a "no free lunch" when learning the structure of SPNs

Anthropogenic modifications to the drainage network of Rome (Italy). The case study of the Aqua Mariana

Rome is characterized by millennia of urbanization. Long lasting geomorphological investigations have allowed the geomorphological description of the city centre and the valorisation of its geomorphological heritage. In this paper the spatial change of the hydrographic network in historical times is illustrated, with some examples showing how deep has been, and still it is, the link between the historical-cultural development and the natural geomorphological and hydrological characteristics of the Roman territory. In particular, the most relevant human interventions on the drainage network, in the southern area of the city centre, have been investigated. Before the land-use modifications of Roman-age, this area was drained by the most important left tributary of the Tiber River within the city walls, the Nodicus River, more recently known as Aqua Mariana. This stream has undergone many anthropogenic modifications and diversions during the centuries, and its original path is known only downstream of the San Giovanni Basilica. According to geomorphological, archaeological and geological evidences, it is possible to hypothesize that the dimension of the pre-urbanization drainage basin, as known and reconstructed in the available literature, should have been until now underestimated

Random sum-product networks: A simple and effective approach to probabilistic deep learning

Sum-product networks (SPNs) are expressive probabilistic models with a rich set of exact and efficient inference routines. However, in order to guarantee exact inference, they require specific structural constraints, which complicate learning SPNs from data. Thereby, most SPN structure learners proposed so far are tedious to tune, do not scale easily, and are not easily integrated with deep learning frameworks. In this paper, we follow a simple “deep learning” approach, by generating unspecialized random structures, scalable to millions of parameters, and subsequently applying GPU-based optimization. Somewhat surprisingly, our models often perform on par with state-of-the-art SPN structure learners and deep neural networks on a diverse range of generative and discriminative scenarios. At the same time, our models yield well-calibrated uncertainties, and stand out among most deep generative and discriminative models in being robust to missing features and being able to detect anomalies

An Outlook on Uterine Neoplasms: From Hormonal and DNA Damaging to Cervical and Endometrial Cancer Development and Minimally Invasive Management.

Uterine neoplasms are common tumors, formed by endometrial and cervical cancers; endometrial cancer is the fourth most frequently diagnosed cancer in developed countries and the eighth leading cause of cancer death in women, and cervical cancer is the second most common cancer in women worldwide and is a leading cause of cancer-related death in women in underdeveloped countries. Cervical cancer arises by HPV DNA damaging; in fact cervical cancer starts in the cells on the surface of the cervix, exposed to viral infective agents, as HPV, founded in 80% of patients affected by cervical cancer. Thus, more than 99% of cervical uterine cancer cases show HPV presence. Nevertheless, Endometrial cancer involves cancerous growth of the endometrium, and increasing evidence indicates that different biological and genetic factors play relevant roles its onset so as carcinogenesis generally develops by hormonal modifications. Both tumors can be safely and feasibly managed from minimally invasive surgical techniques till to endoscopic radical operations, such as hysterectomy, bilateral salpingo- oophorectomy, pelvic and para-aortic lymphadenectomy for surgical treatment. The authors reviewed several excellent reviews and studies in the area of hormonal, viral and genetical risk factors associated with endometrial and cervical cancer risk and development, analyzing the area of biologic markers, all papers dealing with serum and plasma markers involved in uterine cancer detection, development, progression and minimally invasive treatment

The hierarchical response of human corneal collagen to load

Fibrillar collagen in the human cornea is integral to its function as a transparent lens of precise curvature, and its arrangement is now well-characterised in the literature. While there has been considerable effort to incorporate fibrillar architecture into mechanical models of the cornea, the mechanical response of corneal collagen to small applied loads is not well understood. In this study the fibrillar and molecular response to tensile load was quantified using small and wide angle X-ray scattering (SAXS/WAXS), and digital image correlation (DIC) photography was used to calculate the local strain field that gave rise to the hierarchical changes. A molecular scattering model was used to calculate the tropocollagen tilt relative to the fibril axis and changes associated with applied strain. Changes were measured in the D-period, molecular tilt and the orientation and spacing of the fibrillar and molecular networks. These measurements were summarised into hierarchical deformation mechanisms, which were found to contribute at varying strains. The change in molecular tilt is indicative of a sub-fibrillar “spring-like” deformation mechanism, which was found to account for most of the applied strain under physiological and near-physiological loads. This deformation mechanism may play an important functional role in tissues rich in fibrils of high helical tilt, such as skin and cartilage

Sufentanil sublingual tablet system. From rationale of use to clinical practice

The control of post-operative pain in Italy and other western countries is still suboptimal. In recent years, the Sufentanil Sublingual Tablet System (SSTS; Zalviso; AcelRx Pharmaceuticals, Redwood City, CA, USA), which is designed for patient-controlled analgesia (PCA), has entered clinical practice. SSTS enables patients to manage moderate-to-severe acute pain during the first 72 postoperative hours directly in the hospital setting. However, the role of SSTS within the current framework of options for the management of post-operative pain needs to be better established. This paper presents the position on the use of SSTS of a multidisciplinary group of Italian Experts and provides protocols for the use of this device

Denudation and geomorphic change in the Anthropocene; a global overview

The effects of human activity on geomorphic processes, particularly those related to denudation/sedimentation, are investigated by reviewing case studies and global assessments covering the past few centuries. Evidence we have assembled from different parts of the world, as well as from the literature, show that certain geomorphic processes are experiencing an acceleration, especially since the mid-twentieth century. This suggests that a global geomorphic change is taking place, largely caused by anthropogenic landscape changes

Transcutaneous spinal direct current stimulation

In the past 10\u2009years renewed interest has centered on non-invasive transcutaneous weak direct currents applied over the scalp to modulate cortical excitability ("brain polarization" or transcranial direct current stimulation, tDCS). Extensive literature shows that tDCS induces marked changes in cortical excitability that outlast stimulation. Aiming at developing a new, non-invasive, approach to spinal cord neuromodulation we assessed the after-effects of thoracic transcutaneous spinal DC stimulation (tsDCS) on somatosensory potentials (SEPs) evoked in healthy subjects by posterior tibial nerve (PTN) stimulation. Our findings showed that thoracic anodal tsDCS depresses the cervico-medullary PTN-SEP component (P30) without eliciting adverse effects. tsDCS also modulates post-activation H-reflex dynamics. Later works further confirmed that transcutaneous electric fields modulate spinal cord function. Subsequent studies in our laboratory showed that tsDCS modulates the flexion reflex in the human lower limb. Besides influencing the laser evoked potentials (LEPs), tsDCS increases pain tolerance in healthy subjects. Hence, though the underlying mechanisms remain speculative, tsDCS modulates activity in lemniscal, spinothalamic, and segmental motor systems. Here we review currently available experimental evidence that non-invasive spinal cord stimulation (SCS) influences spinal function in humans and argue that, by focally modulating spinal excitability, tsDCS could provide a novel therapeutic tool complementary to drugs and invasive SCS in managing various pathologic conditions, including pain