Browsing by Author "Mendez-Orellana, Carolina"

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    Adiponectin and resistin modulate the progression of Alzheimer's disease in a metabolic syndrome model
    (2023) Cisternas, Pedro; Gherardelli, Camila; Gutierrez, Joel; Salazar, Paulina; Mendez-Orellana, Carolina; Wong, G. William; Inestrosa, Nibaldo C.
    Metabolic syndrome (MetS), a cluster of metabolic conditions that include obesity, hyperlipidemia, and insulin resistance, increases the risk of several aging-related brain diseases, including Alzheimer's disease (AD). However, the underlying mechanism explaining the link between MetS and brain function is poorly understood. Among the possible mediators are several adipose-derived secreted molecules called adipokines, including adiponectin (ApN) and resistin, which have been shown to regulate brain function by modulating several metabolic processes. To investigate the impact of adipokines on MetS, we employed a diet-induced model to induce the various complications associated with MetS. For this purpose, we administered a high-fat diet (HFD) to both WT and APP/PSN1 mice at a pre-symptomatic disease stage. Our data showed that MetS causes a fast decline in cognitive performance and stimulates A beta(42) production in the brain. Interestingly, ApN treatment restored glucose metabolism and improved cognitive functions by 50% while decreasing the A beta(42/40) ratio by approximately 65%. In contrast, resistin exacerbated Ab pathology, increased oxidative stress, and strongly reduced glucose metabolism. Together, our data demonstrate that ApN and resistin alterations could further contribute to AD pathology.
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    Age- and Sex-Associated Glucose Metabolism Decline in a Mouse Model of Alzheimer's Disease
    (2022) Gherardelli, Camila; Cisternas, Pedro; Vera-Salazar, Roberto F.; Mendez-Orellana, Carolina; Inestrosa, Nibaldo C.
    Background: Alzheimer's disease (AD) is characterized by a high etiological and clinical heterogeneity, which has obscured the diagnostic and treatment efficacy, as well as limited the development of potential drugs. Sex differences are among the risk factors that contribute to the variability of disease manifestation. Unlike men, women are at greater risk of developing AD and suffer from higher cognitive deterioration, together with important changes in pathological features. Alterations in glucose metabolism are emerging as a key player in the pathogenesis of AD, which appear even decades before the presence of clinical symptoms.
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    An international core outcome set for primary progressive aphasia (COS-PPA): Consensus-based recommendations for communication interventions across research and clinical settings
    (2024) Volkmer, Anna; Alves, Emily Viega; Bar-Zeev, Hagit; Barbieri, Elena; Battista, Petronilla; Beales, Ashleigh; Beber, Barbara Costa; Brotherhood, Emilie; Cadorio, Ines Ribeiro; Carthery-Goulart, Maria Teresa; Cartwright, Jade; Crutch, Sebastian; Croot, Karen; Freitas, Maria Isabel d'Avila; Gallee, Jeanne; Grasso, Stephanie M.; Haley, Katarina; Hendriksen, Heleen; Henderson, Shalom; Jiskoot, Lize; Almeida, Isabel Junqueira; Kindell, Jackie; Kingma, Rachel; Kwan-Chen, Lorinda L. Y.; Lavoie, Monica; Lifshitz-Ben-Basat, Adi; Jokel, Regina; Mahut-Dubos, Aurore; Matias-Guiu, Jordi A.; Masson-Trottier, Michele; Meinzer, Marcus; Mcgowan, Ellen; Mendez-Orellana, Carolina; Meyer, Aaron M.; Millanski, Carly; Montagut, Nuria; Mooney, Aimee; Morhardt, Darby J.; Nickels, Lyndsey; Norvik, Monica; Nowenstein, Iris Edda; Paplikar, Avanthi; Pozzebon, Margaret; Renard, Antoine; Ruggero, Leanne; Rogalski, Emily; Rysop, Anna U.; Sand Aronsson, Fredrik; Suarez-Gonzalez, Aida; Savage, Sharon; Thi, Mai Tran; Tsapkini, Kyriana; Taylor-Rubin, Cathleen; Tippett, Donna C.; Unger, Nina; van Ewijk, Lizet; Wielaert, Sandra; Winsnes, Ingvild Elisabeth; Whitworth, Anne; Yasa, Ibrahim Can; Copland, David; Henry, Maya L.; Warren, Jason D.; Varley, Rosemary; Wallace, Sarah J.; Hardy, Chris J. D.
    INTRODUCTIONInterventions to treat speech-language difficulties in primary progressive aphasia (PPA) often use word accuracy as a highly comparable outcome. However, there are more constructs of importance to people with PPA that have received less attention.METHODSFollowing Core Outcome Set Standards for Development Recommendations (COSSTAD), this study comprised: Stage 1 - systematic review to identify measures; Stage 2 - consensus groups to identify important outcome constructs for people with PPA (n = 82) and care partners (n = 91); Stage 3 - e-Delphi consensus with 57 researchers.RESULTSThe systematic review identified 84 Outcome Measurement Instruments. Core outcome constructs identified included: (1) Participate in conversations with family and friends, (2) get words out, (3) be more fluent, (4) convey a message by any means, and (5) understand what others are saying. Researchers were unable to reach a consensus on measurement instruments.DISCUSSIONFurther work is required to develop appropriate measurement instruments that address all core outcome constructs important to key stakeholders.Highlights We introduce new symptom-led perspectives on primary progressive aphasia (PPA). The focus is on non-fluent/agrammatic (nfvPPA) and semantic (svPPA) variants. Foregrounding of early and non-verbal features of PPA and clinical trajectories is featured. We introduce a symptom-led staging scheme for PPA. We propose a prototype for a functional impairment scale, the PPA Progression Planning Aid.
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    Assessing Language Lateralization through Gray Matter Volume: Implications for Preoperative Planning in Brain Tumor Surgery
    (2024) Solomons, Daniel; Rodriguez-Fernandez, Maria; Mery-Munoz, Francisco; Arrano-Carrasco, Leonardo; Costabal, Francisco Sahli; Mendez-Orellana, Carolina
    Background/Objectives: Functional MRI (fMRI) is widely used to assess language lateralization, but its application in patients with brain tumors can be hindered by cognitive impairments, compensatory neuroplasticity, and artifacts due to patient movement or severe aphasia. Gray matter volume (GMV) analysis via voxel-based morphometry (VBM) in language-related brain regions may offer a stable complementary approach. This study investigates the relationship between GMV and fMRI-derived language lateralization in healthy individuals and patients with left-hemisphere brain tumors, aiming to enhance accuracy in complex cases. Methods: The MRI data from 22 healthy participants and 28 individuals with left-hemisphere brain tumors were analyzed. Structural T1-weighted and functional images were obtained during three language tasks. Language lateralization was assessed based on activation in predefined regions of interest (ROIs), categorized as typical (left) or atypical (right or bilateral). The GMV in these ROIs was measured using VBM. Linear regressions explored GMV-lateralization associations, and logistic regressions predicted the lateralization based on the GMV. Results: In the healthy participants, typical left-hemispheric language dominance correlated with higher GMV in the left pars opercularis of the inferior frontal gyrus. The brain tumor participants with atypical lateralization showed increased GMV in six right-hemisphere ROIs. The GMV in the language ROIs predicted the fMRI language lateralization, with AUCs from 80.1% to 94.2% in the healthy participants and 78.3% to 92.6% in the tumor patients. Conclusions: GMV analysis in language-related ROIs effectively complements fMRI for assessing language dominance, particularly when fMRI is challenging. It correlates with language lateralization in both healthy individuals and brain tumor patients, highlighting its potential in preoperative language mapping. Further research with larger samples is needed to refine its clinical utility.
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    Identification of perceived sentences using deep neural networks in EEG
    (2024) Valle, Carlos; Mendez-Orellana, Carolina; Herff, Christian; Rodriguez-Fernandez, Maria
    Objetive. Decoding speech from brain activity can enable communication for individuals with speech disorders. Deep neural networks (DNNs) have shown great potential for speech decoding applications. However, the limited availability of large datasets containing neural recordings from speech-impaired subjects poses a challenge. Leveraging data from healthy participants can mitigate this limitation and expedite the development of speech neuroprostheses while minimizing the need for patient-specific training data. Approach. In this study, we collected a substantial dataset consisting of recordings from 56 healthy participants using 64 EEG channels. Multiple neural networks were trained to classify perceived sentences in the Spanish language using subject-independent, mixed-subjects, and fine-tuning approaches. The dataset has been made publicly available to foster further research in this area. Main results. Our results demonstrate a remarkable level of accuracy in distinguishing sentence identity across 30 classes, showcasing the feasibility of training DNNs to decode sentence identity from perceived speech using EEG. Notably, the subject-independent approach rendered accuracy comparable to the mixed-subjects approach, although with higher variability among subjects. Additionally, our fine-tuning approach yielded even higher accuracy, indicating an improved capability to adapt to individual subject characteristics, which enhances performance. This suggests that DNNs have effectively learned to decode universal features of brain activity across individuals while also being adaptable to specific participant data. Furthermore, our analyses indicate that EEGNet and DeepConvNet exhibit comparable performance, outperforming ShallowConvNet for sentence identity decoding. Finally, our Grad-CAM visualization analysis identifies key areas influencing the network's predictions, offering valuable insights into the neural processes underlying language perception and comprehension. Significance. These findings advance our understanding of EEG-based speech perception decoding and hold promise for the development of speech neuroprostheses, particularly in scenarios where subjects cannot provide their own training data.
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    Reusable Low-Cost 3D Training Model for Aneurysm Clipping
    (2021) Mery, Francisco; Aranda, Francisco; Mendez-Orellana, Carolina; Caro, Ivan; Pesenti, Jose; Torres, Javier; Rojas, Ricardo; Villanueva, Pablo; Germano, Isabelle
    BACKGROUND: Aneurysm clipping requires the proficiency of several skills, yet the traditional way of practicing them has been recently challenged, especially by the growth of endovascular techniques. The use of simulators could be an alternative educational tool, but some of them are cumbersome, expensive to implement, or lacking in realism. The aim of this study is to evaluate a reusable low-cost 3-dimensional printed training model we developed for aneurysm clipping.
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    Validation of the abbreviated version of the Token Test in Latin American Spanish stroke patients
    (2024) Julio-Ramos, Teresa; Mora-Castelletto, Valentina; Conejeros-Pavez, Jose; Saez-Martinez, Josette; Solinas-Ivys, Pia; Donoso, Pamela; Soler-Leon, Bernardita; Martinez-Ferreiro, Silvia; Quezada, Camilo; Mendez-Orellana, Carolina
    Background: The abbreviated version of the Token Test (aTT) is widely used to assess language comprehension deficits in stroke patients (SPs). However, aTT has not been validated for Latin American Spanish speakers, so clinicians tend to use cut-off scores for aTT validated in developed countries. Aims: To provide normative data for the Spanish aTT (Sp-aTT) in healthy Chilean Spanish-speaking and SP, determining the influence of sociodemographic variables such as gender, age and education on Sp-aTT performance. Methods & Procedures: A total of 210 healthy volunteers (age range = 18-88 years) and 197 SPs (age range = 23-94 years), all native speakers of Chilean Spanish, were recruited. The association of age, gender and years of education on the Sp-aTT performance was analysed. Specificity and sensibility analyses of the Sp-aTT to diagnose language comprehension deficits were completed. Outcomes & Results: Only age (p < 0.001) and years of education (p < 0.001) impacted the total score of Sp-aTT. Gender did not show an association with Sp-aTT performance (p = 0.181). For SPs, the Sp-aTT score showed a significant positive correlation (rho = 0.4, p < 0.001) with the aphasia severity rating scale (ASRS) score. For Sp-aTT, the area under the curve was 0.97, and the optimal cut-off score for the Sp-aTT was 30 (0.73 of sensitivity, 0.92 of specificity and a Youden index of 0.644). Conclusions & Implications: Age and years of education are two key factors to be controlled for when determining the optimal cut-off points for the Sp-aTT. Our results also highlight the need for language-specific norms in stroke and aphasia research.