In recent years, phosphonic acids and their derivatives have received increasing attention as analogues of a series of naturally occurring phosphates and as "bio-isosteric phosphorus analogues" of ...amino acids. Unlike a phosphate group, the phosphonate moiety is not readily hydrolyzed, in a biological environment, by the enzymes involved in the phosphate cleavage. This feature makes these compounds extremely useful in several applications, in metabolic regulation, in enhancement or inhibition studies, in the development of potential drugs against several metabolic disorders. The great potential of these compounds in biological applications resulted in an intense effort directed to the development of efficient synthetic methods for their preparation, with particular attention to stereoselective synthesis. The purpose of this review is to give an up-to-date account of the chemistry, the synthesis and the biological activity of aminophosphonic acids and their derivatives.
Motor imagery is increasingly being used in clinical settings, such as in neurorehabilitation and brain computer interface (BCI). In stroke, patients lose upper limb function and must re-learn ...bimanual coordination skills necessary for the activities of daily living. Physiotherapists integrate motor imagery with physical rehabilitation to accelerate recovery. In BCIs, users are often asked to imagine a movement, often with sparse instructions. The EEG pattern that coincides with this cognitive task is captured, then used to execute an external command, such as operating a neuroprosthetic device. As such, BCIs are dependent on the efficient and reliable interpretation of motor imagery. While motor imagery improves patient outcome and informs BCI research, the cognitive and neurophysiological mechanisms which underlie it are not clear. Certain types of motor imagery techniques are more effective than others. For instance, focusing on kinesthetic cues and adopting a first-person perspective are more effective than focusing on visual cues and adopting a third-person perspective. As motor imagery becomes more dominant in neurorehabilitation and BCIs, it is important to elucidate what makes these techniques effective. The purpose of this review is to examine the research to date that focuses on both motor imagery and bimanual coordination. An assessment of current research on these two themes may serve as a useful platform for scientists and clinicians seeking to use motor imagery to help improve bimanual coordination, either through augmenting physical therapy or developing more effective BCIs.
We present a 3‐D two‐fluid simulation using plasma parameters as measured by MMS on 8 September 2015 concerning the nonlinear development of the Kelvin‐Helmholtz instability at the Earth's ...magnetopause. We observe an extremely rich nonlinear dynamics including the development of a complex magnetic topology, vortex merging, and secondary Kelvin‐Helmholtz instability driven by large‐scale vortices distributed asymmetrically in latitude. Vortex induced and midlatitude magnetic reconnection coexist and produce an asymmetric distribution of magnetic reconnection events. These results are in good agreement with MMS observations on the same day, in particular for the presence of both equatorial and off‐equator reconnection. Regarding the latter only, we note a predominance of reconnection in the Southern Hemisphere during the early nonlinear phase. The estimated effective diffusion coefficient associated with the dynamics is found to be large enough to account for the observed mass transport at the Earth's magnetospheric flanks.
Key Points
We present a 3‐D two‐fluid simulation using plasma parameters as measured by MMS on 8 September 2015
We observe that (Kelvin‐Helmholtz) vortex induced and midlatitude magnetic reconnection coexist and cooperate
We estimate the effective diffusion associated with reconnection, obtaining Deff ≃ 1010 m2/s, large enough to explain the observed mixing
Context.
In the last few decades, increasing evidence has been found in both numerical studies and high-resolution in situ data that magnetic turbulence spontaneously generates coherent structures ...over a broad range of scales. Those structures play a key role in energy conversion because they are sites where magnetic energy is locally dissipated in plasma heating and particle energization. How much turbulent energy is dissipated via processes such as magnetic reconnection of thin coherent structures, namely current sheets, remains an open question.
Aims.
We aim to develop semi-automated methods for detecting reconnection sites over multiple spatial scales. This is indeed pivotal in advancing our knowledge of plasma dissipation mechanisms and for future applications to space data.
Methods.
By means of hybrid–Vlasov–Maxwell 2D–3V simulations, we combine three methods based on the partial variance of increments measured at a broad range of spatial scales and on the current density, which together, and in a synergistic way, provide indications as to the presence of sites of magnetic reconnection. We adopt the virtual satellite method, which in upcoming works will allow us to easily extend this analysis to in situ time-series.
Results.
We show how combining standard threshold analysis to a 2D scalogram based on magnetic field increments represents an efficient diagnostic for recognizing reconnecting structure in 1D spatial- and time-series. This analysis can serve as input to automated machine-learning algorithms.
Positional plagiocephaly (PP) denotes flattening of the skull that occurs frequently in healthy infants. Aim of this study was to estimate the prevalence of positional plagiocephaly and to identify ...the risk factors in a cohort of healthy infants in order to help prevention of PP. In a prospective design, all healthy full-term infants, ranging from 8 to 12 weeks of age, who presented at the public immunization clinic in Ferrara, were eligible for the study. After obtaining informed consent, we interviewed the parents and examined the infants using the Argenta’s assessment tool. Of 283 infants examined, 107 (37.8%) were found to have PP at 8–12 weeks of age. In 64.5%, PP was on the right side, 50.5% were male and 15% presented also with brachycephaly. Risk factors significantly associated were lower head circumference, advanced maternal age, Italian compared to African, and supine sleep position, in particular for infants born at 37 weeks, preference for one side of the head. In logistic regression, risk factors significantly associated were lower birth weight, advanced maternal age, and supine sleep position.
Conclusions
: Positional plagiocephaly is a common issue faced by pediatricians; our results reinforce the need of improving prevention both of sudden infant death and positional plagiocephaly, through uniform messages provided prenatally and postnatally by different health professionals.
“What is Known:”
•
The incidence of positional plagiocephaly varies due to population studied and measuring methods.
•Different factors are considered in the literature as being associated to positional plagiocephaly (infant factors, obstetric factors, infant care practices, sociodemographic factors).
“What is New:”
•This is one of the few European studies quantifying positional plagiocephaly prevalence in a population of unselected healthy infants.
•In this study, positional plagiocephaly is confirmed as a common issue, related to some factor (as supine sleep position and positional head prevalence) that should be addressed in pre and postnatal counseling.
•The prone sleepers rate in our population highlight the need to improve parental awareness regarding SIDS prevention, in particular in borderline gestational age.
Radioactivity was recently discovered as a source of decoherence and correlated errors for the real-world implementation of superconducting quantum processors. In this work, we measure levels of ...radioactivity present in a typical laboratory environment (from muons, neutrons, and
γ
-rays emitted by naturally occurring radioactive isotopes) and in the most commonly used materials for the assembly and operation of state-of-the-art superconducting qubits. We present a GEANT-4 based simulation to predict the rate of impacts and the amount of energy released in a qubit chip from each of the mentioned sources. We finally propose mitigation strategies for the operation of next-generation qubits in a radio-pure environment.
The complex MR imaging appearance of glioblastoma is a function of underlying histopathologic heterogeneity. A better understanding of these correlations, particularly the influence of infiltrating ...glioma cells and vasogenic edema on T2 and diffusivity signal in nonenhancing areas, has important implications in the management of these patients. With localized biopsies, the objective of this study was to generate a model capable of predicting cellularity at each voxel within an entire tumor volume as a function of signal intensity, thus providing a means of quantifying tumor infiltration into surrounding brain tissue.
Ninety-one localized biopsies were obtained from 36 patients with glioblastoma. Signal intensities corresponding to these samples were derived from T1-postcontrast subtraction, T2-FLAIR, and ADC sequences by using an automated coregistration algorithm. Cell density was calculated for each specimen by using an automated cell-counting algorithm. Signal intensity was plotted against cell density for each MR image.
T2-FLAIR (
= -0.61) and ADC (
= -0.63) sequences were inversely correlated with cell density. T1-postcontrast (
= 0.69) subtraction was directly correlated with cell density. Combining these relationships yielded a multiparametric model with improved correlation (
= 0.74), suggesting that each sequence offers different and complementary information.
Using localized biopsies, we have generated a model that illustrates a quantitative and significant relationship between MR signal and cell density. Projecting this relationship over the entire tumor volume allows mapping of the intratumoral heterogeneity in both the contrast-enhancing tumor core and nonenhancing margins of glioblastoma and may be used to guide extended surgical resection, localized biopsies, and radiation field mapping.
Both the hippocampus and the medial prefrontal cortex (mPFC) play an important role in the negative feedback regulation of hypothalamic–pituitary–adrenal (HPA) activity during physiologic and ...behavioral stress. Moreover, chronic behavioral stress is known to affect the morphology of CA3c pyramidal neurons in the rat, by reducing total branch number and length of apical dendrites. In the present study, we investigated the effects of behavioral stress on the mPFC, using the repeated restraint stress paradigm. Animals were perfused after 21 days of daily restraint, and intracellular iontophoretic injections of Lucifer Yellow were carried out in pyramidal neurons of layer II/III of the anterior cingulate cortex and prelimbic area. Cellular reconstructions were performed on apical and basal dendrites of pyramidal neurons in layer II/III of the anterior cingulate and prelimbic cortices. We observed a significant reduction on the total length (20%) and branch numbers (17%) of apical dendrites, and no significant reduction in basal dendrites. These cellular changes may impair the capacity of the mPFC to suppress the response of the HPA axis to stress, and offer an experimental model of stress-induced neocortical reorganization that may provide a structural basis for the cognitive impairments observed in post-traumatic stress disorder.
Magnetic reconnection is a fundamental process that quickly releases magnetic energy stored in a plasma. Identifying from simulation outputs where reconnection is taking place is nontrivial and, in ...general, has to be performed by human experts. Hence, it would be valuable if such an identification process could be automated. Here, we demonstrate that a machine-learning algorithm can help to identify reconnection in 2D simulations of collisionless plasma turbulence. Using a Hybrid Vlasov Maxwell model, a data set containing over 2000 potential reconnection events was generated and subsequently labeled by human experts. We test and compare two machine-learning approaches with different configurations on this data set. The best results are obtained with a convolutional neural network combined with an "image cropping" step that zooms in on potential reconnection sites. With this method, more than 70% of reconnection events can be identified correctly. The importance of different physical variables is evaluated by studying how they affect the accuracy of predictions. Finally, we also discuss various possible causes for wrong predictions from the proposed model.
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