Bone mineral density in patients on home parenteral nutrition: a follow-up study.

Home artificial nutrition

Computed Tomography Evaluation of Normal Canine Abdominal Lymph Nodes: Retrospective Study of Size and Morphology According to Body Weight and Age in 45 Dogs

The morphological characteristics of the largest lymphatic vessels and lymph nodes of the body have been described through ultrasonography, although food and gas in the gastrointestinal tract can often have negative effects on the response of small abdominal structures. The aim of the study was to describe the size of normal abdominal lymph nodes (ALs) in dogs affected by disease, not including lymphadenomegaly or lymphadenopathy, and divided according to body weight and age. The ALs studied included the jejunal, medial iliac, portal, gastric, splenic, and pancreaticoduodenal lymph nodes. Statistical correlation considering body weight and age as continuous variables showed that all measurements of the ALs increased according to body weight changes (p p p < 0.05). Other characteristics (shape, attenuation, and enhancement) are subsequently reported. The resulting data can be used to categorize CT measurements of normal ALs displayed based on the body weight and age of the subjects. This study aimed to propose a new parameter of normalcy that may serve as a reference for the evaluation of infectious or neoplastic events

Prothrombotic genetic risk factors in chronic daily headache

The aetiology of chronic daily or near-daily headache (CDH) is unknown. We evaluated prothrombotic genetic risk factors (factor V G1691A, factor II 20210 G/A, methylenetetrahydrofolate reductase mutations and plasminogen activator inhibitor-1 4G/5G polymorphism) in 100 patients with CDH, and in 73 healthy controls. Patients did not differ from controls for the studied prothrombotic polymorphisms. These findings suggest that prothrombotic genetic risk factors do not play a role in the development of CDH

Bone structural similarity score: a multiparametric tool to match properties of biomimetic bone substitutes with their target tissues

Background: One of the hardest tasks in developing or selecting grafts for bone substitution surgery or tissue engineering is to match the structural and mechanical properties of tissue at the recipient site, because of the large variability of tissue properties with anatomical site, sex, age and health conditions of the patient undergoing implantation. We investigated the feasibility of defining a quantitative bone structural similarity score based on differences in the structural properties of synthetic grafts and bone tissue. Methods: Two biocompatible hydroxyapatite porous scaffolds with different nominal pore sizes were compared with trabecular bone tissues from equine humerus and femur. Images of samples’ structures were acquired by high-resolution micro-computed tomography and analyzed to estimate porosity, pore size distribution and interconnectivity, specific surface area, connectivity density and degree of anisotropy. Young’s modulus and stress at break were measured by compression tests. Structural similarity distances between sample pairs were defined based on scaled and weighted differences of the measured properties. Their feasibility was investigated for scoring structural similarity between considered scaffolds or bone tissues. Results: Manhattan distances and Quadrance generally showed sound and consistent similarities between sample pairs, more clearly than simple statistical comparison and with discriminating capacity similar to image-based scores to assess progression of pathologies affecting bone structure. Conclusions: The results suggest that a quantitative and objective bone structural similarity score may be defined to help biomaterials scientists fabricate, and surgeons select, the graft or scaffold best mimicking the structure of a given bone tissue

The application of artificial intelligence to understand the pathophysiological basis of psychogenic nonepileptic seizures

Abstract Psychogenic nonepileptic seizures (PNES) are episodes of paroxysmal impairment associated with a range of motor, sensory, and mental manifestations, which perfectly mimic epileptic seizures. Several patterns of neural abnormalities have been described without identifying a definite neurobiological substrate. In this multicenter cross-sectional study, we applied a multivariate classification algorithm on morphological brain imaging metrics to extract reliable biomarkers useful to distinguish patients from controls at an individual level. Twenty-three patients with PNES and 21 demographically matched healthy controls (HC) underwent an extensive neuropsychiatric/neuropsychological and neuroimaging assessment. One hundred and fifty morphological brain metrics were used for training a random forest (RF) machine-learning (ML) algorithm. A typical complex psychopathological construct was observed in PNES. Similarly, univariate neuroimaging analysis revealed widespread neuroanatomical changes affecting patients with PNES. Machine-learning approach, after feature selection, was able to perform an individual classification of PNES from controls with a mean accuracy of 74.5%, revealing that brain regions influencing classification accuracy were mainly localized within the limbic (posterior cingulate and insula) and motor inhibition systems (the right inferior frontal cortex (IFC)). This study provides Class II evidence that the considerable clinical and neurobiological heterogeneity observed in individuals with PNES might be overcome by ML algorithms trained on surface-based magnetic resonance imaging (MRI) data

The SURPRISE demonstrator: a super-resolved compressive instrument in the visible and medium infrared for Earth Observation

While Earth Observation (EO) data has become ever more vital to understanding the planet and addressing societal challenges, applications are still limited by revisit time and spatial resolution. Though low Earth orbit missions can achieve resolutions better than 100 m, their revisit time typically stands at several days, limiting capacity to monitor dynamic events. Geostationary (GEO) missions instead typically provide data on an hour-basis but with spatial resolution limited to 1 km, which is insufficient to understand local phenomena. In this paper, we present the SURPRISE project - recently funded in the frame of the H2020 programme – that gathers the expertise from eight partners across Europe to implement a demonstrator of a super-spectral EO payload - working in the visible (VIS) - Near Infrared (NIR) and in the Medium InfraRed (MIR) and conceived to operate from GEO platform -with enhanced performance in terms of at-ground spatial resolution, and featuring innovative on-board data processing and encryption functionalities. This goal will be achieved by using Compressive Sensing (CS) technology implemented via Spatial Light Modulators (SLM). SLM-based CS technology will be used to devise a super-resolution configuration that will be exploited to increase the at-ground spatial resolution of the payload, without increasing the number of detector’s sensing elements at the image plane. The CS approach will offer further advantages for handling large amounts of data, as is the case of superspectral payloads with wide spectral and spatial coverage. It will enable fast on-board processing of acquired data for information extraction, as well as native data encryption on top of native compression. SURPRISE develops two disruptive technologies: Compressive Sensing (CS) and Spatial Light Modulator (SLM). CS optimises data acquisition (e.g. reduced storage and transmission bandwidth requirements) and enables novel onboard processing and encryption functionalities. SLM here implements the CS paradigm and achieves a super-resolution architecture. SLM technology, at the core of the CS architecture, is addressed by: reworking and testing off-the-shelf parts in relevant environment; developing roadmap for a European SLM, micromirror array-type, with electronics suitable for space qualification. By introducing for the first time the concept of a payload with medium spatial resolution (few hundreds of meters) and near continuous revisit (hourly), SURPRISE can lead to a EO major breakthrough and complement existing operational services. CS will address the challenge of large data collection, whilst onboard processing will improve timeliness, shortening time needed to extract information from images and possibly generate alarms. Impact is relevant to industrial competitiveness, with potential for market penetration of the demonstrator and its components

Sex-based electroclinical differences and prognostic factors in epilepsy with eyelid myoclonia

Although a striking female preponderance has been consistently reported in epilepsy with eyelid myoclonia (EEM), no study has specifically explored the variability of clinical presentation according to sex in this syndrome. Here, we aimed to investigate sex-specific electroclinical differences and prognostic determinants in EEM. Data from 267 EEM patients were retrospectively analyzed by the EEM Study Group, and a dedicated multivariable logistic regression analysis was developed separately for each sex. We found that females with EEM showed a significantly higher rate of persistence of photosensitivity and eye closure sensitivity at the last visit, along with a higher prevalence of migraine with/without aura, whereas males with EEM presented a higher rate of borderline intellectual functioning/intellectual disability. In female patients, multivariable logistic regression analysis revealed age at epilepsy onset, eyelid myoclonia status epilepticus, psychiatric comorbidities, and catamenial seizures as significant predictors of drug resistance. In male patients, a history of febrile seizures was the only predictor of drug resistance. Hence, our study reveals sex-specific differences in terms of both electroclinical features and prognostic factors. Our findings support the importance of a sex-based personalized approach in epilepsy care and research, especially in genetic generalized epilepsies

The spectrum of epilepsy with eyelid myoclonia: delineation of disease subtypes from a large multicenter study

Objective Epilepsy with eyelid myoclonia (EEM) has been associated with marked clinical heterogeneity. Early epilepsy onset has been recently linked to lower chances of achieving sustained remission and to a less favorable neuropsychiatric outcome. However, much work is still needed to better delineate this epilepsy syndrome. Methods In this multicenter retrospective cohort study, we included 267 EEM patients from nine countries. Data on electroclinical and demographic features, intellectual functioning, migraine with or without aura, family history of epilepsy, and epilepsy syndromes in relatives were collected in each patient. The impact of age at epilepsy onset (AEO) on EEM clinical features was investigated, along with the distinctive clinical characteristics of patients showing sporadic myoclonia involving body regions other than eyelids (body-MYO). Results Kernel density estimation revealed a trimodal distribution of AEO, and Fisher-Jenks optimization disclosed three EEM subgroups: early onset (EO-EEM), intermediate onset (IO-EEM), and late onset (LO-EEM). EO-EEM was associated with the highest rate of intellectual disability, antiseizure medication refractoriness, and psychiatric comorbidities and with the lowest rate of family history of epilepsy. LO-EEM was associated with the highest proportion of body-MYO and generalized tonic-clonic seizures (GTCS), whereas IO-EEM had the lowest observed rate of additional findings. A family history of EEM was significantly more frequent in IO-EEM and LO-EEM compared with EO-EEM. In the subset of patients with body-MYO (58/267), we observed a significantly higher rate of migraine and GTCS but no relevant differences in other electroclinical features and seizure outcome. Significance Based on AEO, we identified consistent EEM subtypes characterized by distinct electroclinical and familial features. Our observations shed new light on the spectrum of clinical features of this generalized epilepsy syndrome and may help clinicians toward a more accurate classification and prognostic profiling of EEM patients

A real‐world comparison among third‐generation antiseizure medications: Results from the COMPARE study

Objective: There are few comparative data on the third-generation antiseizure medications (ASMs). We aimed to assess and compare the effectiveness of brivaracetam (BRV), eslicarbazepine acetate (ESL), lacosamide (LCM), and perampanel (PER) in people with epilepsy (PWE). Efficacy and tolerability were compared as secondary objectives.Methods: This multicenter, retrospective study collected data from 22 Italian neurology/epilepsy centers. All adult PWE who started add-on treatment with one of the studied ASMs between January 2018 and October 2021 were included. Retention rate was established as effectiveness measure and described using Kaplan-Meier curves and the best fitting survival model. The responder status and the occurrence of adverse events (AEs) were used to evaluate efficacy and safety, respectively. The odds of AEs and drug efficacy were estimated by two multilevel logistic models.Results: A total of 960 patients (52.92% females, median age = 43 years) met the inclusion criteria. They mainly suffered from structural epilepsy (52.29%) with monthly (46.2%) focal seizures (69.58%). Compared with LCM, all the studied ASMs had a higher dropout risk, statistically significant in the BRV levetiracetam (LEV)-na & iuml;ve (hazard ratio [HR] = 1.97, 95% confidence interval [CI] = 1.17-3.29) and PER groups (HR = 1.64, 95% CI = 1.06-2.55). Women were at higher risk of discontinuing ESL (HR = 5.33, 95% CI = 1.71-16.61), as well as PER-treated patients with unknown epilepsy etiology versus those with structural etiology (HR = 1.74, 95% CI = 1.05-2.88). BRV with prior LEV therapy showed lower odds of efficacy (odds ratio [OR] = .08, 95% CI = .01-.48) versus LCM, whereas a higher efficacy was observed in women treated with BRV and LEV-na & iuml;ve (OR = 10.32, 95% CI = 1.55-68.78) versus men. PER (OR = 6.93, 95% CI = 3.32-14.44) and BRV in LEV-na & iuml;ve patients (OR = 6.80, 95% CI = 2.64-17.52) had a higher chance of AEs than LCM.Significance: Comparative evidence from real-world studies may help clinicians to tailor treatments according to patients' demographic and clinical characteristics