The power of stories in Pediatrics and Genetics

On the occasion of the opening ceremony of the 43rd Sicilian Congress of Pediatrics, linked with Italian Society of Pediatrics SIP, SIN, SIMEUP, SIAIP and SINP, held in Catania in November 2015, the Organizing Committee dedicated a tribute to Professor John Opitz and invited him to give a Masters Lecture for the attendees at the Congress. The theme expounded was "Storytelling in Pediatrics and Genetics: Lessons from Aesop and from Mendel". The contribution of John Opitz to the understanding of pediatric clinical disorders and genetic anomalies has been extremely relevant. The interests of Professor John Opitz are linked not only to genetic disorders but also extend to historical medicine, history of the literature and to human evolution. Due to his exceptional talent, combined with his specific interest and basal knowledge in the genetic and pediatric fields, he is widely credited to be one of the best pediatricians in the world

Dynamic Multi-Vehicle Routing with Multiple Classes of Demands

In this paper we study a dynamic vehicle routing problem in which there are multiple vehicles and multiple classes of demands. Demands of each class arrive in the environment randomly over time and require a random amount of on-site service that is characteristic of the class. To service a demand, one of the vehicles must travel to the demand location and remain there for the required on-site service time. The quality of service provided to each class is given by the expected delay between the arrival of a demand in the class, and that demand's service completion. The goal is to design a routing policy for the service vehicles which minimizes a convex combination of the delays for each class. First, we provide a lower bound on the achievable values of the convex combination of delays. Then, we propose a novel routing policy and analyze its performance under heavy load conditions (i.e., when the fraction of time the service vehicles spend performing on-site service approaches one). The policy performs within a constant factor of the lower bound (and thus the optimal), where the constant depends only on the number of classes, and is independent of the number of vehicles, the arrival rates of demands, the on-site service times, and the convex combination coefficients.Comment: Extended version of paper presented in American Control Conference 200

Why No One Knew that Hillary Clinton Would Lose the 2016 Election

Why No One Knew that Hillary Clinton Would Lose the 2016 Election By Donald Lee Buresh, Ph.D. and Theresa Pavone, Ph.D. ABSTRACTThe paper argues that a blind reliance on the use and results of predictive models lead to the major pollsters never knowing that Hillary Rodham Clinton losing the 2016 Presidental election. The reason was that history is not necessarily a good predictor of the future and that predictive models employed by the pollsters assumed the existence of a steady-state which was not present at the time. The paper introduces predictive models by providing a short history, followed by explaining how predictive models work. The paper then lists the fundamental assumptions of predictive models, highlighting the advantages and disadvantages. The paper then analyzes in some detail why various predictive models incorrectly predicted that Hillary Clinton would win the 2016 presidential election, when in fact Donald Trump was elected President of the United States. The thesis is that when a predictive model experiences an exogenous shock or a superseding intervening cause, the dependence on data before the shock occurred is unwarranted. In fact, it is argued that all data before the exogenous shock or superseding intervening cause should be ignored, and only the data that appears after the shock should be used in making predictions. The paper concludes that the predictive models used by the pollsters during the 2016 Presidential election were incapable of recognizing an exogenous shock or a superseding intervening cause and that human intervention was needed to correct for the limitations of predictive models that were employed

Short-Term Neurodevelopmental Outcome in Term Neonates Treated with Phenobarbital versus Levetiracetam: A Single-Center Experience

BACKGROUND: Phenobarbital (PB) has been traditionally used as the first-line treatment for neonatal seizures. More recently, levetiracetam (LEV) has been increasingly used as a promising newer antiepileptic medication for treatment of seizures in neonates. OBJECTIVES: The aim of our study was to compare the effect of PB vs. LEV on short-term neurodevelopmental outcome in infants treated for neonatal seizures. METHOD: This randomized, one-blind prospective study was conducted on term neonates admitted to the Neonatal Intensive Care Unit of S. Bambino Hospital, University Hospital "Policlinico-Vittorio Emanuele," Catania, Italy, from February 2016 to February 2018. Thirty term neonates with seizures were randomized to receive PB or LEV; the Hammersmith Neonatal Neurological Examination (HNNE) was used at baseline (T0) and again one month after the initial treatment (T1). RESULTS: We found a significantly positive HNNE score for the developmental outcomes, specifically tone and posture, in neonates treated with LEV. There was no significant improvement in the HNNE score at T1 in the neonates treated with PB. CONCLUSION: This study suggests a positive effect of levetiracetam on tone and posture in term newborns treated for neonatal seizures. If future randomized-controlled studies also show better efficacy of LEV in the treatment of neonatal seizures, LEV might potentially be considered as the first-line anticonvulsant in this age grou

Concomitant MPZ and MFN2 Gene Variants and Charcot Marie Tooth Disease in a Boy: Clinical and Genetic Analysis-Literature Review

: Charcot- Marie- Tooth (CMT) disease includes a group of clinically and genetically heterogeneous neuropathic disorders with an estimated frequency of 1 on 2.500 individuals. CMTs are differently classified according to the age of onset, type of inheritance, and type of inheritance plus clinical features. For these disorders, more than 100 genes have been implicated as causal factors, with mutations in the PMP22 being one of the most common. The demyelinating type (CMT1) affects more than 30% of the CMTs patients and manifests with motor and sensory dysfunctions of the peripheral nervous system mainly starting with slow progressive weakness of the lower extremities. We report here a 12 year- old boy presenting with typical features of CMT1 type, hearing impairment, and inguinal hernia who at the next-generation sequence analysis displayed a concomitant presence of two variants: the c.233 C>T p.Ser 78Leu of the MPZ gene (NM_000530.6) characterized as pathogenetic and the c.1403 G>A p.Arg 468His of the MFN2 gene (NM_014874.3) characterized as VUS. Concomitant variant mutations in CMTs have been uncommonly reported. The role of these gene mutations on the clinical expression and a literature review on this topic is discussed

Calibration of optical tweezers with positional detection in the back-focal-plane

We explain and demonstrate a new method of force- and position-calibration for optical tweezers with back-focal-plane photo detection. The method combines power spectral measurements of thermal motion and the response to a sinusoidal motion of a translation stage. It consequently does not use the drag coefficient of the trapped ob ject as an input. Thus, neither the viscosity, nor the size of the trapped ob ject, nor its distance to nearby surfaces need to be known. The method requires only a low level of instrumentation and can be applied in situ in all spatial dimensions. It is both accurate and precise: true values are returned, with small error-bars. We tested this experimentally, near and far from surfaces. Both position- and force-calibration were accurate to within 3%. To calibrate, we moved the sample with a piezo-electric translation stage, but the laser beam could be moved instead, e.g. by acousto-optic deflectors. Near surfaces, this precision requires an improved formula for the hydrodynamical interaction between an infinite plane and a micro-sphere in non-constant motion parallel to it. We give such a formula.Comment: Submitted to: Review of Scientific Instruments. 13 pages, 5 figures. Appendix added (hydrodynamically correct calibration

Clinical Electroencephalography for Anesthesiologists

The widely used electroencephalogram-based indices for depth-of-Anesthesia monitoring assume that the same index value defines the same level of unconsciousness for all anesthetics. In contrast, we show that different anesthetics act at different molecular targets and neural circuits to produce distinct brain states that are readily visible in the electroencephalogram. We present a two-part review to educate anesthesiologists on use of the unprocessed electroencephalogram and its spectrogram to track the brain states of patients receiving anesthesia care. Here in part I, we review the biophysics of the electroencephalogram and the neurophysiology of the electroencephalogram signatures of three intravenous anesthetics: propofol, dexmedetomidine, and ketamine, and four inhaled anesthetics: sevoflurane, isoflurane, desflurane, and nitrous oxide. Later in part II, we discuss patient management using these electroencephalogram signatures. Use of these electroencephalogram signatures suggests a neurophysiologically based paradigm for brain state monitoring of patients receiving anesthesia care.National Institutes of Health (U.S.) (Grant DP1-OD003646)National Institutes of Health (U.S.) (Grant TR01-GM104948

Optical mapping of neuronal activity during seizures in zebrafish

Mapping neuronal activity during the onset and propagation of epileptic seizures can provide a better understanding of the mechanisms underlying this pathology and improve our approaches to the development of new drugs. Recently, zebrafish has become an important model for studying epilepsy both in basic research and in drug discovery. Here, we employed a transgenic line with pan-neuronal expression of the genetically-encoded calcium indicator GCaMP6s to measure neuronal activity in zebrafish larvae during seizures induced by pentylenetretrazole (PTZ). With this approach, we mapped neuronal activity in different areas of the larval brain, demonstrating the high sensitivity of this method to different levels of alteration, as induced by increasing PTZ concentrations, and the rescuing effect of an anti-epileptic drug. We also present simultaneous measurements of brain and locomotor activity, as well as a high-throughput assay, demonstrating that GCaMP measurements can complement behavioural assays for the detection of subclinical epileptic seizures, thus enabling future investigations on human hypomorphic mutations and more effective drug screening methods. Notably, the methodology described here can be easily applied to the study of many human neuropathologies modelled in zebrafish, allowing a simple and yet detailed investigation of brain activity alterations associated with the pathological phenotype

Dynamic Vehicle Routing for Robotic Systems

Recent years have witnessed great advancements in the science and technology of autonomy, robotics, and networking. This paper surveys recent concepts and algorithms for dynamic vehicle routing (DVR), that is, for the automatic planning of optimal multivehicle routes to perform tasks that are generated over time by an exogenous process. We consider a rich variety of scenarios relevant for robotic applications. We begin by reviewing the basic DVR problem: demands for service arrive at random locations at random times and a vehicle travels to provide on-site service while minimizing the expected wait time of the demands. Next, we treat different multivehicle scenarios based on different models for demands (e.g., demands with different priority levels and impatient demands), vehicles (e.g., motion constraints, communication, and sensing capabilities), and tasks. The performance criterion used in these scenarios is either the expected wait time of the demands or the fraction of demands serviced successfully. In each specific DVR scenario, we adopt a rigorous technical approach that relies upon methods from queueing theory, combinatorial optimization, and stochastic geometry. First, we establish fundamental limits on the achievable performance, including limits on stability and quality of service. Second, we design algorithms, and provide provable guarantees on their performance with respect to the fundamental limits.United States. Air Force Office of Scientific Research (Award FA 8650-07-2-3744)United States. Army Research Office. Multidisciplinary University Research Initiative (Award W911NF-05-1-0219)National Science Foundation (U.S.) (Award ECCS-0705451)National Science Foundation (U.S.) (Award CMMI-0705453)United States. Army Research Office (Award W911NF-11-1-0092

Rebalancing the Rebalancers: Optimally Routing Vehicles and Drivers in Mobility-on-Demand Systems

In this paper we study rebalancing strategies for a mobility-on-demand urban transportation system blending customer-driven vehicles with a taxi service. In our system, a customer arrives at one of many designated stations and is transported to any other designated station, either by driving themselves, or by being driven by an employed driver. The system allows for one-way trips, so that customers do not have to return to their origin. When some origins and destinations are more popular than others, vehicles will become unbalanced, accumulating at some stations and becoming depleted at others. This problem is addressed by employing rebalancing drivers to drive vehicles from the popular destinations to the unpopular destinations. However, with this approach the rebalancing drivers themselves become unbalanced, and we need to "rebalance the rebalancers" by letting them travel back to the popular destinations with a customer. Accordingly, in this paper we study how to optimally route the rebalancing vehicles and drivers so that stability (in terms of boundedness of the number of waiting customers) is ensured while minimizing the number of rebalancing vehicles traveling in the network and the number of rebalancing drivers needed; surprisingly, these two objectives are aligned, and one can find the optimal rebalancing strategy by solving two decoupled linear programs. Leveraging our analysis, we determine the minimum number of drivers and minimum number of vehicles needed to ensure stability in the system. Interestingly, our simulations suggest that, in Euclidean network topologies, one would need between 1/3 and 1/4 as many drivers as vehicles.Comment: Extended version of 2013 American Control Conference pape