Modelización de las distribuciones diamétricas en masas de Betula alba L. en el noroeste de España con la función Weibull biparamétrica

The diameter distributions of 125 permanent plots installed in birch dominated (Betula alba L.) stands in Galicia were modelled with the two-parameter Weibull distribution. Four different fitting methods were used: that based on percentiles of the distribution, non linear regression, maximum likelihood and the method of moments. The most accurate fit was obtained with the non linear regression (NLR) approach, considering the following statistics in the comparison: bias, mean absolute error (MAE), mean square error (MSE) and number of plots rejected by the Kolmogoroff-Smirnoff (KS) test. The scale parameter (b) and the shape parameter (c) obtained with the most accurate method (non linear regression), were first modelled with simple linear models and then related to commonly measured prediction variables (quadratic mean diameter, dominant height and stand density) with the parameter prediction model (PPM). The parameters fitted with the method of moments were recovered with the parameter recovery model (PRM) from the first and the second moments of the distribution (mean diameter and variance, respectively). Results indicated that both methods were successful in predicting the diameter frequency distributions. The PRM was more accurate than the PPM method.Las distribuciones diamétricas de 125 parcelas permanentes instaladas en masas puras de abedul (Betula alba L.) en Galicia fueron modelizadas con la distribución Weibull de dos parámetros. Se emplearon cuatro métodos de ajuste: basados en percentiles de la distribución, regresión no lineal, máxima verosimilitud y el método de los momentos. Los ajustes más precisos fueron obtenidos con regresión no lineal, considerando los siguientes estadísticos en la comparación de los resultados: sesgo, error medio absoluto, error medio cuadrático y número de parcelas rechazadas por el test de Kolmogoroff-Smirnoff. El parámetro de escala (b) y el parámetro de forma (c) obtenidos con el método más preciso (regresión no lineal), fueron relacionados con variables de masa de frecuente medición (diámetro medio cuadrático, altura dominante y densidad) mediante modelos lineales sencillos aplicando la metodología de predicción de parámetros. Los parámetros ajustados con el método de los momentos fueron recuperados con modelos de recuperación de parámetros a partir del primer y del segundo momento de la distribución (diámetro medio y varianza, respectivamente). Los resultados indicaron que ambos métodos fueron satisfactorios para predecir las distribuciones de frecuencias de diámetros. El método de recuperación de parámetros fue más preciso que el método de predicción de parámetros

NeuroVoz: a Castillian Spanish corpus of parkinsonian speech

The advancement of Parkinson's Disease (PD) diagnosis through speech analysis is hindered by a notable lack of publicly available, diverse language datasets, limiting the reproducibility and further exploration of existing research. In response to this gap, we introduce a comprehensive corpus from 108 native Castilian Spanish speakers, comprising 55 healthy controls and 53 individuals diagnosed with PD, all of whom were under pharmacological treatment and recorded in their medication-optimized state. This unique dataset features a wide array of speech tasks, including sustained phonation of the five Spanish vowels, diadochokinetic tests, 16 listen-and-repeat utterances, and free monologues. The dataset emphasizes accuracy and reliability through specialist manual transcriptions of the listen-and-repeat tasks and utilizes Whisper for automated monologue transcriptions, making it the most complete public corpus of Parkinsonian speech, and the first in Castillian Spanish. NeuroVoz is composed by 2,903 audio recordings averaging $26.88 \pm 3.35$ recordings per participant, offering a substantial resource for the scientific exploration of PD's impact on speech. This dataset has already underpinned several studies, achieving a benchmark accuracy of 89% in PD speech pattern identification, indicating marked speech alterations attributable to PD. Despite these advances, the broader challenge of conducting a language-agnostic, cross-corpora analysis of Parkinsonian speech patterns remains an open area for future research. This contribution not only fills a critical void in PD speech analysis resources but also sets a new standard for the global research community in leveraging speech as a diagnostic tool for neurodegenerative diseases.Comment: Preprint versio

El efecto de la crisis financiera internacional sobre los flujos de ayuda oficial al desarrollo. El caso España-Colombia

El presente artículo busca hacer una aproximación de las consecuencias de la crisis financiera internacional de 2008 sobre los flujos de ayuda oficial al desarrollo (AOD) de España hacia Colombia en el período 2008-2013. Las cifras revelan que los efectos de la crisis económica han derivado en importantes variaciones sobre los flujos de ayuda para Colombia. No obstante, la voluntad política se ha hecho manifiesta, razón por la cual existe una clara disposición para reforzar la cooperación y el intercambio comercial entre los dos países.

The Bi-Loop, a new general four-stranded DNA motif

The crystal structure of the cyclic octanucleotide d contains two independent molecules that form a novel quadruplex by means of intermolecular Watson-Crick A.T pairs and base stacking. A virtually identical quadruplex composed of G.C pairs was found by earlier x-ray analysis of the linear heptamer d(GCATGCT), when the DNA was looped in the crystal. The close correspondence between these two structures of markedly dissimilar oligonucleotides suggests that they are both examples of a previously unrecognized motif. Their nucleotide sequences have little in common except for two separated 5'-purine-pyrimidine dinucleotides forming the quadruplex, and by implication these so-called 'bi-loops' could occur widely in natural DNA. Such structures provide a mechanism for noncovalent linking of polynucleotides in vivo. Their capacity to associate by base stacking, demonstrated in the crystal structure of d(GCATGCT), creates a compact molecular framework made up of four DNA chains within which strand exchange could take place

Classification of kinematic and electromyographic signals associated with pathological tremor using machine and deep learning.

Peripheral Electrical Stimulation (PES) of afferent pathways has received increased interest as a solution to reduce pathological tremors with minimal side effects. Closed-loop PES systems might present some advantages in reducing tremors, but further developments are required in order to reliably detect pathological tremors to accurately enable the stimulation only if a tremor is present. This study explores different machine learning (K-Nearest Neighbors, Random Forest and Support Vector Machines) and deep learning (Long Short-Term Memory neural networks) models in order to provide a binary (Tremor; No Tremor) classification of kinematic (angle displacement) and electromyography (EMG) signals recorded from patients diagnosed with essential tremors and healthy subjects. Three types of signal sequences without any feature extraction were used as inputs for the classifiers: kinematics (wrist flexion-extension angle), raw EMG and EMG envelopes from wrist flexor and extensor muscles. All the models showed high classification scores (Tremor vs. No Tremor) for the different input data modalities, ranging from 0.8 to 0.99 for the f1 score. The LSTM models achieved 0.98 f1 scores for the classification of raw EMG signals, showing high potential to detect tremors without any processed features or preliminary information. These models may be explored in real-time closed-loop PES strategies to detect tremors and enable stimulation with minimal signal processing steps

Prediction of Pathological Tremor Signals Using Long Short-Term Memory Neural Networks

Previous implementations of closed-loop peripheral electrical stimulation (PES) strategies have provided evidence about the effect of the stimulation timing on tremor reduction. However, these strategies have used traditional signal processing techniques that only consider phase prediction and might not model the non-stationary behavior of tremor. Here, we tested the use of long short-term memory (LSTM) neural networks to predict tremor signals using kinematic data recorded from Essential Tremor (ET) patients. A dataset comprising wrist flexion-extension data from 12 ET patients was pre-processed to feed the predictors. A total of 180 models resulting from the combination of network (neurons and layers of the LSTM networks, length of the input sequence and prediction horizon) and training parameters (learning rate) were trained, validated and tested. Predicted tremor signals using LSTM-based models presented high correlation values (from 0.709 to 0.998) with the expected values, with a phase delay between the predicted and real signals below 15 ms, which corresponds approximately to 7.5% of a tremor cycle. The prediction horizon was the parameter with a higher impact on the prediction performance. The proposed LSTM-based models were capable of predicting both phase and amplitude of tremor signals outperforming results from previous studies (32 - 56% decreased phase prediction error compared to the out-of-phase method), which might provide a more robust PES-based closed-loop control applied to PES-based tremor reduction.The authors would like to thank Cristina Montero Pardo for illustrations from Fig. 1 and the patients from Gregorio Marañón Hospital who voluntarily participated in this study

Present and Future of Parkinson’s Disease in Spain: PARKINSON-2030 Delphi Project

Parkinson's disease (PD) is a chronic progressive and irreversible disease and the second most common neurodegenerative disease worldwide. In Spain, it affects around 120.000-150.000 individuals, and its prevalence is estimated to increase in the future. PD has a great impact on patients' and caregivers' lives and also entails a substantial socioeconomic burden. The aim of the present study was to examine the current situation and the 10-year PD forecast for Spain in order to optimize and design future management strategies. This study was performed using the modified Delphi method to try to obtain a consensus among a panel of movement disorders experts. According to the panel, future PD management will improve diagnostic capacity and follow-up, it will include multidisciplinary teams, and innovative treatments will be developed. The expansion of new technologies and studies on biomarkers will have an impact on future PD management, leading to more accurate diagnoses, prognoses, and individualized therapies. However, the socio-economic impact of the disease will continue to be significant by 2030, especially for patients in advanced stages. This study highlighted the unmet needs in diagnosis and treatment and how crucial it is to establish recommendations for future diagnostic and therapeutic management of PD

Long-term efficacy of botulinum toxin A for treatment of blepharospasm,hemifacial spasm, and spastic entropion: a multicentre study using two drug-dose escalation indexes

PURPOSE: To investigate the long-term effectiveness and safety of botulinum neurotoxin A (BoNT-A) treatment in patients with blepharospasm (BEB), hemifacial spasm (HFS), and entropion (EN) and to use for the first time two modified indexes, 'botulin toxin escalation index-U' (BEI-U) and 'botulin toxin escalation index percentage' (BEI-%), in the dose-escalation evaluation. METHODS: All patients in this multicentre study were followed for at least 10 years and main outcomes were clinical efficacy, duration of relief, BEI-U and BEI-%, and frequency of adverse events. RESULTS: BEB, HFS, and EN patients received a mean BoNT-A dose with a significant inter-group difference (P<0.0005, respectively). The mean (+/-SD) effect duration was statistically different (P=0.009) among three patient groups. Regarding the BoNT-A escalation indexes, the mean (+/-SD) values of BEI-U and BEI-% were statistically different (P=0.035 and 0.047, respectively) among the three groups. In BEB patients, the BEI-% was significantly increased in younger compared with older patients (P=0.008). The most frequent adverse events were upper lid ptosis, diplopia, ecchymosis, and localized bruising. CONCLUSIONS: This long-term multicentre study supports a high efficacy and good safety profile of BoNT-A for treatment of BEB, HFS, and EN. The BEI indexes indicate a significantly greater BoNT-A-dose escalation for BEB patients compared with HFS or EN patients and a significantly greater BEI-% in younger vsolder BEB patients. These results confirm a greater efficacy in the elderly and provide a framework for long-term studies with a more flexible and reliable evaluation of drug-dose escalation

High-throughput mutational analysis of TOR1A in primary dystonia

<p>Abstract</p> <p>Background</p> <p>Although the c.904_906delGAG mutation in Exon 5 of <it>TOR1A </it>typically manifests as early-onset generalized dystonia, DYT1 dystonia is genetically and clinically heterogeneous. Recently, another Exon 5 mutation (c.863G>A) has been associated with early-onset generalized dystonia and some ΔGAG mutation carriers present with late-onset focal dystonia. The aim of this study was to identify <it>TOR1A </it>Exon 5 mutations in a large cohort of subjects with mainly non-generalized primary dystonia.</p> <p>Methods</p> <p>High resolution melting (HRM) was used to examine the entire <it>TOR1A </it>Exon 5 coding sequence in 1014 subjects with primary dystonia (422 spasmodic dysphonia, 285 cervical dystonia, 67 blepharospasm, 41 writer's cramp, 16 oromandibular dystonia, 38 other primary focal dystonia, 112 segmental dystonia, 16 multifocal dystonia, and 17 generalized dystonia) and 250 controls (150 neurologically normal and 100 with other movement disorders). Diagnostic sensitivity and specificity were evaluated in an additional 8 subjects with known ΔGAG DYT1 dystonia and 88 subjects with ΔGAG-negative dystonia.</p> <p>Results</p> <p>HRM of <it>TOR1A </it>Exon 5 showed high (100%) diagnostic sensitivity and specificity. HRM was rapid and economical. HRM reliably differentiated the <it>TOR1A </it>ΔGAG and c.863G>A mutations. Melting curves were normal in 250/250 controls and 1012/1014 subjects with primary dystonia. The two subjects with shifted melting curves were found to harbor the classic ΔGAG deletion: 1) a non-Jewish Caucasian female with childhood-onset multifocal dystonia and 2) an Ashkenazi Jewish female with adolescent-onset spasmodic dysphonia.</p> <p>Conclusion</p> <p>First, HRM is an inexpensive, diagnostically sensitive and specific, high-throughput method for mutation discovery. Second, Exon 5 mutations in <it>TOR1A </it>are rarely associated with non-generalized primary dystonia.</p

Relevance of genetic testing in the gene-targeted trial era: the Rostock Parkinson\u27s disease study

\ua9 The Author(s) 2024. Estimates of the spectrum and frequency of pathogenic variants in Parkinson’s disease (PD) in different populations are currently limited and biased. Furthermore, although therapeutic modification of several genetic targets has reached the clinical trial stage, a major obstacle in conducting these trials is that PD patients are largely unaware of their genetic status and, therefore, cannot be recruited. Expanding the number of investigated PD-related genes and including genes related to disorders with overlapping clinical features in large, well-phenotyped PD patient groups is a prerequisite for capturing the full variant spectrum underlying PD and for stratifying and prioritizing patients for gene-targeted clinical trials. The Rostock Parkinson’s disease (ROPAD) study is an observational clinical study aiming to determine the frequency and spectrum of genetic variants contributing to PD in a large international cohort. We investigated variants in 50 genes with either an established relevance for PD or possible phenotypic overlap in a group of 12 580 PD patients from 16 countries [62.3% male; 92.0% White; 27.0% positive family history (FH+), median age at onset (AAO) 59 years] using a next-generation sequencing panel. Altogether, in 1864 (14.8%) ROPAD participants (58.1% male; 91.0% White, 35.5% FH+, median AAO 55 years), a PD-relevant genetic test (PDGT) was positive based on GBA1 risk variants (10.4%) or pathogenic/likely pathogenic variants in LRRK2 (2.9%), PRKN (0.9%), SNCA (0.2%) or PINK1 (0.1%) or a combination of two genetic findings in two genes (∼0.2%). Of note, the adjusted positive PDGT fraction, i.e. the fraction of positive PDGTs per country weighted by the fraction of the population of the world that they represent, was 14.5%. Positive PDGTs were identified in 19.9% of patients with an AAO ≤ 50 years, in 19.5% of patients with FH+ and in 26.9% with an AAO ≤ 50 years and FH+. In comparison to the idiopathic PD group (6846 patients with benign variants), the positive PDGT group had a significantly lower AAO (4 years, P = 9 7 10−34). The probability of a positive PDGT decreased by 3% with every additional AAO year (P = 1 7 10−35). Female patients were 22% more likely to have a positive PDGT (P = 3 7 10−4), and for individuals with FH+ this likelihood was 55% higher (P = 1 7 10−14). About 0.8% of the ROPAD participants had positive genetic testing findings in parkinsonism-, dystonia/dyskinesia- or dementia-related genes. In the emerging era of gene-targeted PD clinical trials, our finding that ∼15% of patients harbour potentially actionable genetic variants offers an important prospect to affected individuals and their families and underlines the need for genetic testing in PD patients. Thus, the insights from the ROPAD study allow for data-driven, differential genetic counselling across the spectrum of different AAOs and family histories and promote a possible policy change in the application of genetic testing as a routine part of patient evaluation and care in PD