Deep Brain Stimulation of the Subthalamic Nucleus for Parkinson's Disease in a Patient with HIV Infection: Dual Clinical Benefit

As a result of the efficacy of highly active antiretroviral therapy (HAART), patients with human immunodeficiency virus (HIV) can survive longer and are thus naturally prone to ageing-related degenerative disorders such as Parkinson's disease (PD). Managing PD and HIV in the same patient may be challenging, as HAART and levodopa interact and may cause intolerable side effects. Concerns about the increased risk of hardware infection in immunocompromised patients submitted to deep brain stimulation of the subthalamic nucleus (STN-DBS) still persist. We report a PD patient with HIV infection who suffered peak-dose dyskinesias and intolerable gastrointestinal side effects while on HAART, prompting its suspension. STN-DBS allowed complete postoperative levodopa withdrawal and HAART restart, without infectious complications after 12 months of follow-up. STN-DBS seems to be a safe procedure in selected patients with both medically refractory PD and HIV infection, and may result in clinical optimization of both conditions

Role of 99mTc-Sulesomab Immunoscintigraphy in the Management of Infection following Deep Brain Stimulation Surgery

Infection constitutes a serious adverse event in patients submitted to deep brain stimulation, often leading to removal of the device. We set to evaluate the potential role of immunoscintigraphy with 99mTc-labelled antigranulocyte antibody fragments (99mTc-sulesomab) in the management of infection following DBS. 99mTc-sulesomab immunoscintigraphy seems to correlate well with the presence and extent of infection, thus contributing to differentiate between patients who should remove the hardware entirely at presentation and those who could undergo a more conservative approach. Also, 99mTc-sulesomab immunoscintigraphy has a role in determining the most appropriate timing for reimplantation. Finally, we propose an algorithm for the management of infection following DBS surgery, based on the results of the 99mTc-sulesomab immunoscintigraphy

Discrimination of idiopathic Parkinson's disease and vascular parkinsonism based on gait time series and the levodopa effect

Idiopathic Parkinson's disease (IPD) and vascular parkinsonism (VaP) present highly overlapping phenotypes, making it challenging to distinguish between these two parkinsonian syndromes. Recent evidence suggests that gait assessment and response to levodopa medication may assist in the objective evaluation of clinical differences. In this paper, we propose a new approach for gait pattern differentiation that uses convolutional neural networks (CNNs) based on gait time series with and without the influence of levodopa medication. Wearable sensors positioned on both feet were used to acquire gait data from 14 VaP patients, 15 IPD patients, and 34 healthy subjects. An individual's gait features are affected by physical characteristics, including age, height, weight, sex, and walking speed or stride length. Therefore, to reduce bias due to intersubject variations, a multiple regression normalization approach was used to obtain gait data. Recursive feature elimination using the linear support vector machine, lasso, and random forest were applied to infer the optimal feature subset that led to the best results. CNNs were implemented by means of various hyperparameters and feature subsets. The best CNN classifiers achieved accuracies of 79.33%±6.46, 82.33%±10.62, and 86.00%±7.12 without (off state), with (on state), and with the simultaneous consideration of the effect of levodopa medication (off/on state), respectively. The response to levodopa medication improved classification performance. Based on gait time series and response to medication, the proposed approach differentiates between IPD and VaP gait patterns and reveals a high accuracy rate, which might prove useful when distinguishing other diseases related to movement disorders.This research was partially financed by NORTE2020 and FEDER within the project NORTE-01–0145-FEDER- 000026 (DeM-Deus Ex Machina) and by Portuguese Funds through FCT (Fundação para a Ciência e a Tecnologia) within the Projects UIDB/00013/2020, UIDP/00013/2020 and UIDB/00319/2020

Gait classification of patients with Fabry's disease based on normalized gait features obtained using multiple regression models

Diagnosis of Fabry disease (FD) remains a challenge mostly due to its rare occurrence and phenotipical variability, with considerable delay between onset and clinical diagnosis. It is then of extreme importance to explore biomarkers capable of assisting the earlier diagnosis of FD. There is growing evidence supporting the use of gait assessment in the diagnosis and management of several neurological diseases. In fact, gait abnormalities have previously been observed in FD, justifying further investigation. The aim of this study is to evaluate the effectiveness of different machine learning strategies when distinguishing patients with FD from healthy controls based on normalized gait features. Gait features of an individual are affected by physical characteristics including age, height, weight, and gender, as well as walking speed or stride length. Therefore, in order to reduce bias due to inter-subject variations a multiple regression (MR) normalization approach for gait data was performed. Four different machine learning strategies - Support Vector Machines (SVM), Random Forest (RF), Multiple Layer Perceptrons (MLPs), and Deep Belief Networks (DBNs) - were employed on raw and normalized gait data. Wearable sensors positioned on both feet were used to acquire the gait data from 36 patients with FD and 34 healthy subjects. Gait normalization using MR revealed significant differences in percentage of stance phase spent in foot flat and pushing (p < 0.05), with FD presenting lower percentages in foot flat and higher in pushing. No significant differences were observed before gait normalization. Support Vector Machine was the superior classifier achieving an FD classification accuracy of 78.21% after gait normalization, compared to 71.96% using raw gait data. Gait normalization improved the performance of all classifiers. To the best of our knowledge, this is the first study on gait classification that includes patients with FD, and our results support the use of gait assessment on the clinical assessment of FD.This work was partially supported by the projects NORTE-01-0145- FEDER- 000026 (DeM-Deus Ex Machina) financed by NORTE2020 and FEDER, and the Pluriannual Funding Programs of the research centres CMAT and Algoritm

Compensatory postural adjustments in na oculus virtual reality environment and the risk of falling in Alzheimer’s disease

Background/Aims Alzheimer's disease (AD) patients have an impaired ability to quickly reweight central sensory dependence in response to unexpected body perturbations. Herein, we aim to study provoked compensatory postural adjustments (CPAs) in a conflicting sensory paradigm with unpredictable visual displacements using virtual reality goggles. Methods We used kinematic time-frequency analyses of two frequency bands: a low-frequency band (LB; 0.3-1.5 Hz; mechanical strategy) and a high-frequency band (HB; 1.5-3.5 Hz; cognitive strategy). We enrolled 19 healthy subjects (controls) and 21 AD patients, divided according to their previous history of falls. Results The AD faller group presented higher-power LB CPAs, reflecting their worse inherent postural stability. The AD patients had a time lag in their HB CPA reaction. Conclusion The slower reaction by CPA in AD may be a reflection of different cognitive resources including body schema self-perception, visual motion, depth perception, or a different state of fear and/or anxiety.The Centro ALGORITMI was funded by the FP7 Marie Curie ITN Neural Engineering Transformative Technologies (NETT) project. The authors have no conflicts of interest to report.info:eu-repo/semantics/publishedVersio

Surface waters of the NW Iberian margin: upwelling on the shelf versus outwelling of upwelled waters from the Rías Baixas

A set of hydrographic surveys were carried out in the Ría of Vigo (NW Spain) at 2–4 d intervals during four 2–3 week periods in 1997, covering contrasting seasons. Residual exchange fluxes with the adjacent shelf were estimated with a 2-D, non-steady-state, salinity–temperature weighted box model. Exchange fluxes consist of a steady-state term (dependent on the variability of continental runoff) and a non-steady-state term (dependent on the time changes of density gradients in the embayment). More than 95% of the short-time-scale variability of the exchange fluxes in the middle and outer ría can be explained by the non-steady-state term that, in turns, is correlated (R2>75%) with the offshore Ekman transport. Conversely, 96% of the variability of exchange fluxes in the inner ría rely on the steady-state term. The outer and middle ría are under the direct influence of coastal upwelling, which enhances the positive residual circulation pattern by an order of magnitude: from 10 2 to 10 3 m3s−1. On the contrary, downwelling provokes a reversal of the circulation in the outer ría. The position of the downwelling front along the embayment depends on the relative importance of Ekman transport (Qx, m3s−1km−1) and continental runoff (R, m3s−1). When Qx/ R>7±2 the reversal of the circulation affects the middle ría. Our results are representative for the ‘Rías Baixas’, four large coastal indentations in NW Spain. During the upwelling season (spring and summer), 60% of shelf surface waters off the ‘Rías Baixas’ consist of fresh Eastern North Atlantic Central Water (ENACW) upwelled in situ. The remaining 40% consists of upwelled ENACW that previously enters the rías and it is subsequently outwelled after thermohaline modification. During the downwelling season (autumn and winter), 40% of the warm and salty oceanic subtropic surface water, which piled on the shelf by the predominant southerly winds, enters the rias

Safinamide: a new hope for Parkinson's disease?

The loss of dopaminergic neurons (DAn) and reduced dopamine (DA) production underlies the reasoning behind the gold standard treatment for Parkinson's disease (PD) using levodopa (L-DOPA). Recently licensed by the European Medicine Agency (EMA) and US Food and Drug Administration (FDA), safinamide [a monoamine oxidase B (MOA-B) inhibitor] is an alternative to L-DOPA; as we discuss here, it enhances dopaminergic transmission with decreased secondary effects compared with L-DOPA. In addition, nondopaminergic actions (neuroprotective effects) have been reported, with safinamide inhibiting glutamate release and sodium/calcium channels, reducing the excitotoxic input to dopaminergic neuronal death. Effects of safinamide have been correlated with the amelioration of non-motor symptoms (NMS), although these remain under discussion. Overall, safinamide can be considered to have potential antidyskinetic and neuroprotective effects and future trials and/or studies should be performed to provide further evidence for its potential as an anti-PD drug.The authors acknowledge funding from the Portuguese Foundation for Science and Technology (IF development grant IF/ 00111/2013 to A.J.S.) and a postdoctoral fellowship to F.G.T. (SFRH/BPD/118408/2016). This work was funded by FEDER funds, through the Competitiveness Factors Operational Programme (COMPETE), and by national funds, through the Foundation for Science and Technology (FCT), under the scope of the project POCI-01-0145-FEDER-007038. This article has also been developed under the scope of the project NORTE-01-0145-FEDER-000023, supported by the Northern Portugal Regional Operational Programme (NORTE 2020), under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund (FEDER)

Versatile Graphene-Based Platform for Robust Nanobiohybrid Interfaces

Technologically useful and robust graphene-based interfaces for devices require the introduction of highly selective, stable, and covalently bonded functionalities on the graphene surface, whilst essentially retaining the electronic properties of the pristine layer. This work demonstrates that highly controlled, ultrahigh vacuum covalent chemical functionalization of graphene sheets with a thiol-terminated molecule provides a robust and tunable platform for the development of hybrid nanostructures in different environments. We employ this facile strategy to covalently couple two representative systems of broad interest: metal nanoparticles, via S-metal bonds, and thiol-modified DNA aptamers, via disulfide bridges. Both systems, which have been characterized by a multi-technique approach, remain firmly anchored to the graphene surface even after several washing cycles. Atomic force microscopy images demonstrate that the conjugated aptamer retains the functionality required to recognize a target protein. This methodology opens a new route to the integration of high-quality graphene layers into diverse technological platforms, including plasmonics, optoelectronics, or biosensing. With respect to the latter, the viability of a thiol-functionalized chemical vapor deposition graphene-based solution-gated field-effect transistor array was assessed

Air-sea CO2 fluxes in the Atlantic as measured during the FICARAM cruises

A total of fourteen hydrographic cruises spanning from 2000 to 2008 were conducted during the spring and autumn seasons between Spain and the Southern Ocean, under the framework of the Spanish research project FICARAM. The performed underway measurements are processed and analysed to describe the meridional air-sea CO2 fluxes (F CO2) along the Atlantic Ocean. The data was organised into different biogeochemical oceanographic provinces, according mainly to the thermohaline characteristics. The obtained spatial and temporal distributions of F CO2 follow the generally expected patterns and annual trends. The Subtropical regions in both hemispheres alternated the CO2 source and sink nature from autumn to spring, respectively. On the other hand, Tropical waters and the Patagonian Sea clearly behaved as sinks of atmospheric CO2 like the waters of the Drake Passage during autumn. The obtained results during the cruises also revealed significant long-term trends, such as the warming of equatorial waters (0.11±0.03 Cyr−1) and the decrease of surface salinity (−0.16±0.01 yr−1) in tropical waters caused by the influence of the Amazon River plume. This reduction in surface salinity appears to have a direct influence over the CO2 storage rates, fostering the uptake capacity of atmospheric CO2 (−0.09±0.03 molm−2 yr−1). An analysis of the biogeochemical forcing on the CO2 fugacity (fCO2) variability performed from an empirical algorithm highlighted the major role of the Amazon River input in the tropical North Atlantic fluxes. In addition, it has provided a quantitative measure of the importance of the thermodynamic control of F CO2 at temperate latitudes

Spanish Research Report for 2015

Spanish catch information used in this Report is based on the logbook data contributed by the Spanish Administration. Table 1 presents the catches by species and Division in 2015 based on this information. The split of catches and effort between the different gears in this Report are based on information from NAFO observers on board. In 2015 NAFO observers information from 1,272 days was available while total effort of the Spanish fleet in NAFO Regulatory Area was 1,317 days (around 97% coverage). In addition to NAFO observers, IEO scientific observers were on board 320 fishing days that it means 24 % of the Spanish total effort. All length, age and biological information presented in this paper is based on sampling carried out by IEO scientific observers: 576 samples were taken in 2015, with 59,883 individuals of different species examined (Table 2).Postprint0,000