A Fuzzy Inference System for Closed-Loop Deep Brain Stimulation in Parkinson’s Disease

Parkinsons disease is a complex neurodegenerative disorder for which patients present many symptoms, tremor being the main one. In advanced stages of the disease, Deep Brain Stimulation is a generalized therapy which can significantly improve the motor symptoms. However despite its beneficial effects on treating the symptomatology, the technique can be improved. One of its main limitations is that the parameters are fixed, and the stimulation is provided uninterruptedly, not taking into account any fluctuation in the patients state. A closed-loop system which provides stimulation by demand would adjust the stimulation to the variations in the state of the patient, stimulating only when it is necessary. It would not only perform a more intelligent stimulation, capable of adapting to the changes in real time, but also extending the devices battery life, thereby avoiding surgical interventions. In this work we design a tool that learns to recognize the principal symptom of Parkinsons disease and particularly the tremor. The goal of the designed system is to detect the moments the patient is suffering from a tremor episode and consequently to decide whether stimulation is needed or not. For that, local field potentials were recorded in the subthalamic nucleus of ten Parkinsonian patients, who were diagnosed with tremor-dominant Parkinsons disease and who underwent surgery for the implantation of a neurostimulator. Electromyographic activity in the forearm was simultaneously recorded, and the relation between both signals was evaluated using two different synchronization measures. The results of evaluating the synchronization indexes on each moment represent the inputs to the designed system. Finally, a fuzzy inference system was applied with the goal of identifying tremor episodes. Results are favourable, reaching accuracies of higher 98.7 % in 70 % of the patients.Centro de Investigación Biomédica en RedDepto. de Psicología Experimental, Procesos Cognitivos y LogopediaDepto. de Radiología, Rehabilitación y FisioterapiaFac. de PsicologíaFac. de MedicinaTRUEpu

Effect of thermomechanical processing schedule on the texture and microstructure of pipeline grade API X80 microalloyed steel

The presence of micro alloying constituents like Ti, Nb in microalloyed steel enhances its mechanical properties through grain size control and precipitation strengthening. The strengthening capability of microalloying additions can be fully utilized by choosing proper thermomechanical processing (TMP) schedule. The TMP schedule needs to be designed based on determination of critical temperatures of transformation in steel including no recrystallisation temperature (i.e ., Tnr) of microalloyed steels. The TMP was carried out on API X80 grade pipeline steel using Gleeble® 3800 Thermal mechanical simulator. The samples were deformed in plain strain condition at three different temperatures (860, 950 and 1050°C) by keeping other deformation parameters constant. The deformation temperature was chosen based on CCT and Tnr determination studies. The deformed samples were examined in EBSD and TEM to obtain the texture and microstructural information. It is also observed that formation of acicular ferrite and bainite microstructures in these steel is very much dependent on the deformation strain levels in the austenite matrix prior to transformation. The grain boundary misorientation angle distribution obtained from EBSD analysis can be a very important parameter to distinguish the different microstructural constituents apart from grain shape and image quality. Effect of thermomechanical processing schedule on the texture and microstructure of pipeline grade API X80 microalloyed steel (PDF Download Available). Available from: https://www.researchgate.net/publication/303524095_Effect_of_thermomechanical_processing_schedule_on_the_texture_and_microstructure_of_pipeline_grade_API_X80_microalloyed_steel [accessed Nov 15 2017]

Oscillatory neural representations in the sensory thalamus predict neuropathic pain relief by deep brain stimulation

Objective Understanding the function of sensory thalamic neural activity is essential for developing and improving interventions for neuropathic pain. However, there is a lack of investigation of the relationship between sensory thalamic oscillations and pain relief in patients with neuropathic pain. This study aims to identify the oscillatory neural characteristics correlated with pain relief induced by deep brain stimulation (DBS), and develop a quantitative model to predict pain relief by integrating characteristic measures of the neural oscillations. Approach Measures of sensory thalamic local field potentials (LFPs) in thirteen patients with neuropathic pain were screened in three dimensional feature space according to the rhythm, balancing, and coupling neural behaviours, and correlated with pain relief. An integrated approach based on principal component analysis (PCA) and multiple regression analysis is proposed to integrate the multiple measures and provide a predictive model. Main results This study reveals distinct thalamic rhythms of theta, alpha, high beta and high gamma oscillations correlating with pain relief. The balancing and coupling measures between these neural oscillations were also significantly correlated with pain relief. Significance The study enriches the series research on the function of thalamic neural oscillations in neuropathic pain and relief, and provides a quantitative approach for predicting pain relief by DBS using thalamic neural oscillations

Dynamic neural state identification in deep brain local field potentials of neuropathic pain

In neuropathic pain, the neurophysiological and neuropathological function of the ventro-posterolateral nucleus of the thalamus (VPL) and the periventricular gray/periaqueductal gray area (PVAG) involves multiple frequency oscillations. Moreover, oscillations related to pain perception and modulation change dynamically over time. Fluctuations in these neural oscillations reflect the dynamic neural states of the nucleus. In this study, an approach to classifying the synchronization level was developed to dynamically identify the neural states. An oscillation extraction model based on windowed wavelet packet transform was designed to characterize the activity level of oscillations. The wavelet packet coefficients sparsely represented the activity level of theta and alpha oscillations in local field potentials (LFPs). Then, a state discrimination model was designed to calculate an adaptive threshold to determine the activity level of oscillations. Finally, the neural state was represented by the activity levels of both theta and alpha oscillations. The relationship between neural states and pain relief was further evaluated. The performance of the state identification approach achieved sensitivity and specificity beyond 80% in simulation signals. Neural states of the PVAG and VPL were dynamically identified from LFPs of neuropathic pain patients. The occurrence of neural states based on theta and alpha oscillations were correlated to the degree of pain relief by deep brain stimulation. In the PVAG LFPs, the occurrence of the state with high activity levels of theta oscillations independent of alpha and the state with low-level alpha and high-level theta oscillations were significantly correlated with pain relief by deep brain stimulation. This study provides a reliable approach to identifying the dynamic neural states in LFPs with a low signal-to-noise ratio by using sparse representation based on wavelet packet transform. Furthermore, it may advance closed-loop deep brain stimulation based on neural states integrating multiple neural oscillations

Burst or conventional peripheral nerve field stimulation for treatment of neuropathic facial pain

Background Trigeminal Neuropathic Pain (TNP) is a chronic facial pain syndrome caused by a lesion or disease affecting one or more branches of the trigeminal nerve. It may, for example, result from accidental injury to a branch of the trigeminal nerve by trauma or during surgery; it may also be idiopathic. TNP is typically constant, in contrast to most cases of the commoner trigeminal neuralgia. In some cases, pain may be refractory to pharmacological treatment. Peripheral nerve field stimulation is recognized as an effective minimally invasive surgical treatment option for this debilitating condition. To date, stimulation has used conventional tonic waveforms, which generate paraesthesia in the stimulated area. This is the first report of the use of paraesthesia‐free burst pattern stimulation for TNP. Methods Seven patients were treated at the John Radcliffe Hospital for TNP from 2016 to 2018. Mean duration of preoperative symptoms was five years. All patients had exhausted pharmacological measures to limited effect. The initial three patients had tonic stimulation with the subsequent four having burst stimulation. Outcome was assessed using the numeric pain rating scale preoperatively and postoperatively at three and six months and one year. Side‐effects and complications were also assessed as well as reduction in analgesic medication use. Results All patients achieved pain reduction of at least 50% at 6 months (range 50–100%, mean 81%, p = 0.0082). Those in the burst stimulation group were paraesthesia free. One patient developed a postoperative infection for which the system had to be removed and is awaiting reimplantation. There were no other complications in either group. Conclusion Burst stimulation conferred similar pain control to tonic stimulation in our small cohort, and there were similar reductions in pain medication use. An additional benefit of burst stimulation is freedom from paraesthesia. Larger scale studies are needed to further evaluate burst stimulation and compare its efficacy with that of tonic stimulation

In silico identification of epitopes from house cat and dog proteins as peptide immunotherapy candidates based on human leukocyte antigen binding affinity

Summary The objective of this descriptive study was to determine Felis domesticus (cat) and Canis familiaris (dog) protein epitopes that bind strongly to selected HLA class II alleles to identify synthetic vaccine candidate epitopes and to identify individuals/populations who are likely to respond to vaccines. FASTA amino acid sequences of experimentally validated allergenic proteins of house cat and dog were identified using International Union of Immunological Societies (IUIS) allergen nomenclature database. NetMHCII 2.2 server was used to determine binding affinities in the form of 1-log 50 k and in nM with commonly found HLA II alleles. Screening of house cat and dog allergenic proteins identified 4 (with 2 isoforms for chain 1 and 3 isoforms for chain 2 for fel d 1) and 6 proteins, respectively. Number of strong binders from each protein against each HLA type was determined as potential candidate for allergen immunotherapy. HLA-DRB1 * 0101 bound maximum number of epitopes (207 and 275 from house cat and dog, respectively) while HLA-DRB1 * 0802 bound none. We conclude that HLA specific epitope prediction can help identify synthetic peptide vaccine candidates and predict response as well

Adaptive deep brain stimulation in advanced Parkinson disease.

OBJECTIVE: Brain-computer interfaces (BCIs) could potentially be used to interact with pathological brain signals to intervene and ameliorate their effects in disease states. Here, we provide proof-of-principle of this approach by using a BCI to interpret pathological brain activity in patients with advanced Parkinson disease (PD) and to use this feedback to control when therapeutic deep brain stimulation (DBS) is delivered. Our goal was to demonstrate that by personalizing and optimizing stimulation in real time, we could improve on both the efficacy and efficiency of conventional continuous DBS. METHODS: We tested BCI-controlled adaptive DBS (aDBS) of the subthalamic nucleus in 8 PD patients. Feedback was provided by processing of the local field potentials recorded directly from the stimulation electrodes. The results were compared to no stimulation, conventional continuous stimulation (cDBS), and random intermittent stimulation. Both unblinded and blinded clinical assessments of motor effect were performed using the Unified Parkinson's Disease Rating Scale. RESULTS: Motor scores improved by 66% (unblinded) and 50% (blinded) during aDBS, which were 29% (p = 0.03) and 27% (p = 0.005) better than cDBS, respectively. These improvements were achieved with a 56% reduction in stimulation time compared to cDBS, and a corresponding reduction in energy requirements (p < 0.001). aDBS was also more effective than no stimulation and random intermittent stimulation. INTERPRETATION: BCI-controlled DBS is tractable and can be more efficient and efficacious than conventional continuous neuromodulation for PD

AMPA receptor GluA2 subunit defects are a cause of neurodevelopmental disorders.

AMPA receptors (AMPARs) are tetrameric ligand-gated channels made up of combinations of GluA1-4 subunits encoded by GRIA1-4 genes. GluA2 has an especially important role because, following post-transcriptional editing at the Q607 site, it renders heteromultimeric AMPARs Ca2+-impermeable, with a linear relationship between current and trans-membrane voltage. Here, we report heterozygous de novo GRIA2 mutations in 28 unrelated patients with intellectual disability (ID) and neurodevelopmental abnormalities including autism spectrum disorder (ASD), Rett syndrome-like features, and seizures or developmental epileptic encephalopathy (DEE). In functional expression studies, mutations lead to a decrease in agonist-evoked current mediated by mutant subunits compared to wild-type channels. When GluA2 subunits are co-expressed with GluA1, most GRIA2 mutations cause a decreased current amplitude and some also affect voltage rectification. Our results show that de-novo variants in GRIA2 can cause neurodevelopmental disorders, complementing evidence that other genetic causes of ID, ASD and DEE also disrupt glutamatergic synaptic transmission

Cost-effectiveness analysis of two integrated early childhood development programs into Bangladeshi primary health-care services

Objectives: This study presents results of a cost and cost-effectiveness analysis of two parenting interventions (group-based and pairs) integrated into primary health care centers in rural Bangladesh. Methods: A within-trial cost-effectiveness analysis was conducted for two trials of parenting interventions aiming tosupport child development through play and interactions. Eligible participants for both trials were underweight children aged 5–24 months. Participants in the control arms in both trials received standard health services. Intervention costs were estimated rom the provider perspective over the time horizon of each study (21 months for the group-based intervention; 24 months for the pair-based intervention). Incremental cost effectiveness ratios were estimated for all primary child development outcomes and presented in terms of cost per standard deviation improvements in the outcomes. A series of cost scenario analyses were conducted to assess the effect of changing cost assumptions on the cost and cost-effectiveness results. All results are presented in 2022 USD. Results: Total provider costs in the within-trial analysis were US$67,668 for the group-based intervention and US$ 117,028 for the pair intervention. Estimated cost per child covered by the interventions was US$156 for the group intervention and US$136 for the pair intervention, reflecting likely economies of scale in delivery of the pair intervntion. An additional US$100 expenditure on the group intervention is estimated to lead to a 0.55 SD improvement in cognition, 0.44 SD in language development and 0.33 SD in motor development. For the pair intervention, the corresponding estimates are improvements of 0.95 SD, 0.81 SD, and 0.88 SD, respectively. Under potential scale up scenarios, the economic cost per child could reduce substantially to US$61 and US$77 for group and pair interventions, respectively. Conclusion: The findings indicates that cost-efficiency and cost-effectiveness results for both interventions are comparable with the results from limited similar interventions in LMICs. However, implementation costs of the interventions will be substantially lower at scale due to lower monitoring costs, economies of scale, and full integration into the public health system.<br/