PLOS ONE: [sortOrder=DATE_NEWEST_FIRST, sort=Date, newest first, q=subject:"Neurology"]PLOShttps://journals.plos.org/plosone/webmaster@plos.orgaccelerating the publication of peer-reviewed sciencehttps://journals.plos.org/plosone/search/feed/atom?sortOrder=DATE_NEWEST_FIRST&unformattedQuery=subject:%22Neurology%22&sort=Date,+newest+firstAll PLOS articles are Open Access.https://journals.plos.org/plosone/resource/img/favicon.icohttps://journals.plos.org/plosone/resource/img/favicon.ico2024-03-28T15:39:47ZDifficulties and challenges experienced by nurses in eldercare institutions in Albania: A qualitative content analysisNertila PodgoricaEmiljano PjetriAndreas W. Müller (M. A.)Susanne Perkhofer10.1371/journal.pone.03007742024-03-27T14:00:00Z2024-03-27T14:00:00Z<p>by Nertila Podgorica, Emiljano Pjetri, Andreas W. Müller (M. A.), Susanne Perkhofer</p>
Introduction <p>The global and Albanian populations of elderly people are steadily increasing. It is estimated that the number of elderly adults requiring care in Albania will rise from 90.9 thousand to 130.4 thousand by 2030. Despite the envisaged increase in the number and life expectancy of the elderly population in Albania, which will result in an increased demand for nursing care, little is known about the difficulties and challenges that nurses face while providing care for elderly Albanian individuals.</p> Aim <p>To explore the difficulties and challenges nurses experience while caring for elderly people in Albanian eldercare institutions.</p> Methods <p>The study employed a qualitative design using purposive sampling of 20 nurses in 8 eldercare institutions who participated in face-to-face semi-structured interviews. The audio-recorded interviews were transcribed and subsequently subjected to analysis using Graneheim and Lundman’s qualitative conventional content analysis. Data analysis was supported by the qualitative data analysis software MAXQDA 2020. The reporting of this study followed the consolidated criteria for reporting qualitative research (COREQ) checklist.</p> Results <p>Five key categories emerged from data analysis: (1) professional difficulties, (2) educational difficulties, (3) relationship challenges, (4) increased mental stress, and (5) participation in advocacy. This study showed that nursing staff experienced many barriers, challenges, and unmet needs when implementing care for elderly people in long-term care facilities.</p> Conclusion <p>The findings indicate that nurses working in eldercare institutions faced significant challenges in caring for elderly people. Nurses need more legal, financial, educational, and emotional support. The study indicates that more organizational and national support is necessary for nursing staff to care for elderly people in eldercare Albanian institutions properly. Eldercare institution leaders need to recognize the importance of their role in overcoming the barriers and providing adequate support for their staff in caring for elderly people.</p>How to provide existential and spiritual support to people with mild to moderate dementia and their loved ones. A pilot studyMarc HaufeSaskia TeunissenCarlo Leget10.1371/journal.pone.02987832024-03-27T14:00:00Z2024-03-27T14:00:00Z<p>by Marc Haufe, Saskia Teunissen, Carlo Leget</p>
Background <p>People with mild to moderate dementia and their loved ones may experience strong existential and spiritual challenges due to the disease. People with dementia could therefore benefit greatly from ongoing conversational support. Within the literature and in supportive practice, there are very few tools that help professionals provide this type of support. Professionals may therefore be unaware of, or uncertain of, how support can be given.</p> Objective <p>To develop and test support approaches that may enable professionals to better conduct conversations with attention for existential and spiritual issues.</p> Methods <p>Participatory action research was conducted with dementia care professionals who spoke to 62 clients and 36 loved ones. Research consisted of two cycles of analyzing support, formulating strategies to try, testing and reflecting on the success of these actions and formulating new ones. The Diamond model for existential and spiritual issues regarding mild to moderate dementia, developed in previous research, was used as a framework.</p> Results <p>Five types of approaches, corresponding to the five fundamental polarities within the basic framework, were found to be helpful in alleviating tensions and bolstering strengths. For issues of self-confidence and -worth, an approach of <i>exploring the felt self</i> was developed; for issues of capacity and adaptability, an <i>exploring daily routines</i> approach; for issues of security and loss, an <i>exploring a trinity of needs</i> approach; for issues of burden and enrichment, an <i>exploring memory</i> approach; and for issues of faith and meaning, an <i>exploring ones’ predicament</i> approach. When exploring these approaches, participants found sets and sequencing of questions and prompts to be helpful and transformative.</p> Conclusion <p>Professionals can use the Diamond framework to provide conversational support to alleviate tension, enhance meaning and bolster strength for clients and loved ones.</p>Breastfeeding, cognitive ability, and residual confounding: A comment on studies by Pereyra-Elìas et al.Kimmo SorjonenGustav NilsonneMichael IngreBo Melin10.1371/journal.pone.02972162024-03-27T14:00:00Z2024-03-27T14:00:00Z<p>by Kimmo Sorjonen, Gustav Nilsonne, Michael Ingre, Bo Melin</p>
Recent studies found positive effects of breastfeeding on the child’s cognitive ability and educational outcomes even when adjusting for maternal cognitive ability in addition to a large number of other potential confounders. The authors claimed an important role of breastfeeding for the child’s cognitive scores. However, it is well known that error in the measurement of confounders can leave room for residual confounding. In the present reanalyses, we found incongruent effects indicating simultaneous increasing and decreasing effects of breastfeeding on the child’s cognitive ability and educational outcomes. We conclude that findings in the reanalyses may have been due to residual confounding due to error in the measurement of maternal cognitive ability. Consequently, it appears premature to assume a genuine increasing effect of breastfeeding on the child’s cognitive ability and educational outcomes and claims in this regard may be challenged.Bayesian-knowledge driven ontologies: A framework for fusion of semantic knowledge under uncertainty and incompletenessEugene Santos Jr.Jacob JurmainAnthony Ragazzi10.1371/journal.pone.02968642024-03-27T14:00:00Z2024-03-27T14:00:00Z<p>by Eugene Santos Jr., Jacob Jurmain, Anthony Ragazzi</p>
The modeling of uncertain information is an open problem in ontology research and is a theoretical obstacle to creating a truly semantic web. Currently, ontologies often do not model uncertainty, so stochastic subject matter must either be normalized or rejected entirely. Because uncertainty is omnipresent in the real world, knowledge engineers are often faced with the dilemma of performing prohibitively labor-intensive research or running the risk of rejecting correct information and accepting incorrect information. It would be preferable if ontologies could explicitly model real-world uncertainty and incorporate it into reasoning. We present an ontology framework which is based on a seamless synthesis of description logic and probabilistic semantics. This synthesis is powered by a link between ontology assertions and random variables that allows for automated construction of a probability distribution suitable for inferencing. Furthermore, our approach defines how to represent stochastic, uncertain, or incomplete subject matter. Additionally, this paper describes how to fuse multiple conflicting ontologies into a single knowledge base that can be reasoned with using the methods of both description logic and probabilistic inferencing. This is accomplished by using probabilistic semantics to resolve conflicts between assertions, eliminating the need to delete potentially valid knowledge and perform consistency checks. In our framework, emergent inferences can be made from a fused ontology that were not present in any of the individual ontologies, producing novel insights in a given domain.Dysregulation of LINC00324 promotes poor prognosis in patients with gliomaXin JinJiandong ZhuHaoyun YuShengjun ShiKecheng ShenJingyu GuZiqian YinZhengquan YuJiang Wu10.1371/journal.pone.02980552024-03-26T14:00:00Z2024-03-26T14:00:00Z<p>by Xin Jin, Jiandong Zhu, Haoyun Yu, Shengjun Shi, Kecheng Shen, Jingyu Gu, Ziqian Yin, Zhengquan Yu, Jiang Wu</p>
Background <p>LINC00324 is a long-stranded non-coding RNA, which is aberrantly expressed in various cancers and is associated with poor prognosis and clinical features. It involves multiple oncogenic molecular pathways affecting cell proliferation, migration, invasion, and apoptosis. However, the expression, function, and mechanism of LINC00324 in glioma have not been reported.</p> Material and methods <p>We assessed the expression of LINC00324 of LINC00324 in glioma patients based on data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) to identify pathways involved in LINC00324-related glioma pathogenesis.</p> Results <p>Based on our findings, we observed differential expression of LINC00324 between tumor and normal tissues in glioma patients. Our analysis of overall survival (OS) and disease-specific survival (DSS) indicated that glioma patients with high LINC00324 expression had a poorer prognosis compared to those with low LINC00324 expression. By integrating clinical data and genetic signatures from TCGA patients, we developed a nomogram to predict OS and DSS in glioma patients. Gene set enrichment analysis (GSEA) revealed that several pathways, including JAK/STAT3 signaling, epithelial-mesenchymal transition, STAT5 signaling, NF-κB activation, and apoptosis, were differentially enriched in glioma samples with high LINC00324 expression. Furthermore, we observed significant correlations between LINC00324 expression, immune infiltration levels, and expression of immune checkpoint-related genes (HAVCR2: r = 0.627, P = 1.54e-77; CD40: r = 0.604, P = 1.36e-70; ITGB2: r = 0.612, P = 6.33e-7; CX3CL1: r = -0.307, P = 9.24e-17). These findings highlight the potential significance of LINC00324 in glioma progression and suggest avenues for further research and potential therapeutic targets.</p> Conclusion <p>Indeed, our results confirm that the LINC00324 signature holds promise as a prognostic predictor in glioma patients. This finding opens up new possibilities for understanding the disease and may offer valuable insights for the development of targeted therapies.</p>A deeply supervised adaptable neural network for diagnosis and classification of Alzheimer’s severity using multitask feature extractionMohsen AhmadiDanial JavaheriMatin KhajaviKasra DaneshJunbeom Hur10.1371/journal.pone.02979962024-03-26T14:00:00Z2024-03-26T14:00:00Z<p>by Mohsen Ahmadi, Danial Javaheri, Matin Khajavi, Kasra Danesh, Junbeom Hur</p>
Alzheimer’s disease is the most prevalent form of dementia, which is a gradual condition that begins with mild memory loss and progresses to difficulties communicating and responding to the environment. Recent advancements in neuroimaging techniques have resulted in large-scale multimodal neuroimaging data, leading to an increased interest in using deep learning for the early diagnosis and automated classification of Alzheimer’s disease. This study uses machine learning (ML) methods to determine the severity level of Alzheimer’s disease using MRI images, where the dataset consists of four levels of severity. A hybrid of 12 feature extraction methods is used to diagnose Alzheimer’s disease severity, and six traditional machine learning methods are applied, including decision tree, K-nearest neighbor, linear discrimination analysis, Naïve Bayes, support vector machine, and ensemble learning methods. During training, optimization is performed to obtain the best solution for each classifier. Additionally, a CNN model is trained using a machine learning system algorithm to identify specific patterns. The accuracy of the Naïve Bayes, Support Vector Machines, K-nearest neighbor, Linear discrimination classifier, Decision tree, Ensembled learning, and presented CNN architecture are 67.5%, 72.3%, 74.5%, 65.6%, 62.4%, 73.8% and, 95.3%, respectively. Based on the results, the presented CNN approach outperforms other traditional machine learning methods to find Alzheimer severity.Clinical gait analysis using video-based pose estimation: Multiple perspectives, clinical populations, and measuring changeJan StenumMelody M. HsuAlexander Y. PantelyatRyan T. Roemmich10.1371/journal.pdig.00004672024-03-26T14:00:00Z2024-03-26T14:00:00Z<p>by Jan Stenum, Melody M. Hsu, Alexander Y. Pantelyat, Ryan T. Roemmich</p>
Gait dysfunction is common in many clinical populations and often has a profound and deleterious impact on independence and quality of life. Gait analysis is a foundational component of rehabilitation because it is critical to identify and understand the specific deficits that should be targeted prior to the initiation of treatment. Unfortunately, current state-of-the-art approaches to gait analysis (e.g., marker-based motion capture systems, instrumented gait mats) are largely inaccessible due to prohibitive costs of time, money, and effort required to perform the assessments. Here, we demonstrate the ability to perform quantitative gait analyses in multiple clinical populations using only simple videos recorded using low-cost devices (tablets). We report four primary advances: 1) a novel, versatile workflow that leverages an open-source human pose estimation algorithm (OpenPose) to perform gait analyses using videos recorded from multiple different perspectives (e.g., frontal, sagittal), 2) validation of this workflow in three different populations of participants (adults without gait impairment, persons post-stroke, and persons with Parkinson’s disease) via comparison to ground-truth three-dimensional motion capture, 3) demonstration of the ability to capture clinically relevant, condition-specific gait parameters, and 4) tracking of within-participant changes in gait, as is required to measure progress in rehabilitation and recovery. Importantly, our workflow has been made freely available and does not require prior gait analysis expertise. The ability to perform quantitative gait analyses in nearly any setting using only low-cost devices and computer vision offers significant potential for dramatic improvement in the accessibility of clinical gait analysis across different patient populations.Interventions to address mealtime support needs in dementia: A scoping reviewLígia PassosJoão TavaresMelissa BatchelorDaniela Figueiredo10.1371/journal.pone.03009872024-03-25T14:00:00Z2024-03-25T14:00:00Z<p>by Lígia Passos, João Tavares, Melissa Batchelor, Daniela Figueiredo</p>
The decrease in cognitive and physical ability among people with dementia can significantly affect eating performance, resulting in mealtime support needs that could lead to inadequate oral intake, weight loss, malnutrition, and reduced functionality in activities of daily living. This scoping review aimed to identify and summarize available research literature on mealtime interventions for people with dementia, and their impact on older people with dementia living in a residential care setting, care staff, and care context/environment. A scoping review of available research published in English, French, Portuguese, or Spanish, was conducted according to the methodology established by The Joanna Briggs Institute. The search was conducted between November 2022 and February 2023 in the following databases: MEDLINE, Web of Science, Scopus, CINAHL Complete, and SciELO. A total of 275 articles were retrieved, of which 33 studies were selected according to inclusion criteria. The interventions were classified into four general categories: environmental, mealtime assistance, staff training, and multicomponent. Most studies demonstrated effectiveness in increasing oral intake and improving behaviors such as agitation and aggression in people with dementia. The impact of interventions on care staff was linked to greater knowledge and attitudes towards mealtime support needs. There is a lack of reporting on the impact of interventions on the care context/environment. Most interventions examined the effects exclusively on residents, focusing on their oral intake and behavioral patterns, particularly agitation among individuals with dementia. However, it is crucial to conduct studies that evaluate the impact on administrators, to comprehend the viewpoints of various hierarchical levels within an organization regarding challenges associated with mealtime. The findings of this scoping review can support the development of new supportive programs, or strategies to improve mealtime experience with positive impact according to the reality and needs of each person or institution.Natalizumab promotes anti-inflammatory and repair effects in multiple sclerosisRagnhild Reehorst LereimPetra NytrovaAstrid GuldbrandsenEva Kubala HavrdovaKjell-Morten MyhrHarald BarsnesFrode S. Berven10.1371/journal.pone.03009142024-03-25T14:00:00Z2024-03-25T14:00:00Z<p>by Ragnhild Reehorst Lereim, Petra Nytrova, Astrid Guldbrandsen, Eva Kubala Havrdova, Kjell-Morten Myhr, Harald Barsnes, Frode S. Berven</p>
Background <p>Multiple sclerosis is an inflammatory and degenerative disease of the central nervous system leading to demyelination and axonal loss. Relapsing-remitting multiple sclerosis (RRMS) is commonly treated by anti-inflammatory drugs, where one of the most effective drugs to date is the monoclonal antibody natalizumab.</p> Methods <p>The cerebrospinal fluid (CSF) proteome was analyzed in 56 patients with RRMS before and after natalizumab treatment, using label-free mass spectrometry and a subset of the changed proteins were verified by parallel reaction monitoring in a new cohort of 20 patients, confirming the majority of observed changes.</p> Results <p>A total of 287 differentially abundant proteins were detected including (i) the decrease of proteins with roles in immunity, such as immunoglobulin heavy constant mu, chitinase-3-like protein 1 and chitotriosidase, (ii) an increase of proteins involved in metabolism, such as lactate dehydrogenase A and B and malate-dehydrogenase cytoplasmic, and (iii) an increase of proteins associated with the central nervous system, including lactadherin and amyloid precursor protein. Comparison with the CSF-PR database provided evidence that natalizumab counters protein changes commonly observed in RRMS. Furthermore, vitamin-D binding protein and apolipoprotein 1 and 2 were unchanged during treatment with natalizumab, implying that these may be involved in disease activity unaffected by natalizumab.</p> Conclusions <p>Our study revealed that some of the previously suggested biomarkers for MS were affected by the natalizumab treatment while others were not. Proteins not previously suggested as biomarkers were also found affected by the treatment. In sum, the results provide new information on how the natalizumab treatment impacts the CSF proteome of MS patients, and points towards processes affected by the treatment. These findings ought to be explored further to disclose potential novel disease mechanisms and predict treatment responses.</p>Retinoic acid attenuates ischemic injury-induced activation of glial cells and inflammatory factors in a rat stroke modelJu-Bin KangHyun-Kyoung SonMurad-Ali ShahPhil-Ok Koh10.1371/journal.pone.03000722024-03-25T14:00:00Z2024-03-25T14:00:00Z<p>by Ju-Bin Kang, Hyun-Kyoung Son, Murad-Ali Shah, Phil-Ok Koh</p>
Stroke is a leading cause of death and long-term disability which can cause oxidative damage and inflammation of the neuronal cells. Retinoic acid is an active metabolite of vitamin A that has various beneficial effects including antioxidant and anti-inflammatory effects. In this study, we investigated whether retinoic acid modulates oxidative stress and inflammatory factors in a stroke animal model. A middle cerebral artery occlusion (MCAO) was performed on adult male rats to induce focal cerebral ischemia. Retinoic acid (5 mg/kg) or vehicle was injected into the peritoneal cavity for four days before MCAO surgery. The neurobehavioral tests were carried out 24 h after MCAO and cerebral cortex tissues were collected. The cortical damage was assessed by hematoxylin-eosin staining and reactive oxygen species assay. In addition, Western blot and immunohistochemical staining were performed to investigate the activation of glial cells and inflammatory cytokines in MCAO animals. Ionized calcium-binding adapter molecule-1 (Iba-1) and glial fibrillary acidic protein (GFAP) were used as markers of microglial and astrocyte activation, respectively. Tumor necrosis factor-α (TNF-α) and interleukin-1β (IL-1β) were used as representative pro-inflammatory cytokines. Results showed that MCAO damage caused neurobehavioral defects and histopathological changes in the ischemic region and increased oxidative stress. Retinoic acid treatment reduced these changes caused by MCAO damage. We detected increases in Iba-1 and GFAP in MCAO animals treated with vehicle. However, retinoic acid alleviated increases in Iba-1 and GFAP caused by MCAO damage. Moreover, MCAO increased levels of nuclear factor-κB and pro-inflammatory cytokines, including TNF-α and IL-1β. Retinoic acid alleviated the expression of these inflammatory proteins. These findings elucidate that retinoic acid regulates microglia and astrocyte activation and modulates pro-inflammatory cytokines. Therefore, this study suggests that retinoic acid exhibits strong antioxidant and anti-inflammatory properties by reducing oxidative stress, inhibiting neuroglia cell activation, and preventing the increase of pro-inflammatory cytokines in a cerebral ischemia.The proton-sensing receptors TDAG8 and GPR4 are differentially expressed in human and mouse oligodendrocytes: Exploring their role in neuroinflammation and multiple sclerosisFionä CaratisMikołaj OpiełkaMartin HausmannMaria Velasco-EstevezBartłomiej RojekCheryl de VallièreKlaus SeuwenGerhard RoglerBartosz KaraszewskiAleksandra Rutkowska10.1371/journal.pone.02830602024-03-25T14:00:00Z2024-03-25T14:00:00Z<p>by Fionä Caratis, Mikołaj Opiełka, Martin Hausmann, Maria Velasco-Estevez, Bartłomiej Rojek, Cheryl de Vallière, Klaus Seuwen, Gerhard Rogler, Bartosz Karaszewski, Aleksandra Rutkowska</p>
Acidosis is one of the hallmarks of demyelinating central nervous system (CNS) lesions in multiple sclerosis (MS). The response to acidic pH is primarily mediated by a family of G protein-coupled proton-sensing receptors: OGR1, GPR4 and TDAG8. These receptors are inactive at alkaline pH, reaching maximal activation at acidic pH. Genome-wide association studies have identified a locus within the TDAG8 gene associated with several autoimmune diseases, including MS. Accordingly, we here found that expression of <i>TDAG8</i>, as opposed to <i>GPR4</i> or <i>OGR1</i>, is upregulated in MS plaques. This led us to investigate the expression of TDAG8 in oligodendrocytes using mouse and human <i>in vitro</i> and <i>in vivo</i> models. We observed significant upregulation of TDAG8 in human MO3.13 oligodendrocytes during maturation and in response to acidic conditions. However, its deficiency did not impact normal myelination in the mouse CNS, and its expression remained unaltered under demyelinating conditions in mouse organotypic cerebellar slices. Notably, our data revealed no expression of TDAG8 in primary mouse oligodendrocyte progenitor cells (OPCs), in contrast to its expression in primary human OPCs. Our investigations have revealed substantial species differences in the expression of proton-sensing receptors in oligodendrocytes, highlighting the limitations of the employed experimental models in fully elucidating the role of TDAG8 in myelination and oligodendrocyte biology. Consequently, the study does not furnish robust evidence for the role of TDAG8 in such processes. Nonetheless, our findings tentatively point towards a potential association between TDAG8 and myelination processes in humans, hinting at a potential link between TDAG8 and the pathophysiology of MS and warrants further research.Incidence of oncogenic HPV infection in women with and without mental illness: A population-based cohort study in SwedenEva HerweijerKejia HuJiangrong WangDonghao LuPär SparénHans-Olov AdamiUnnur ValdimarsdóttirKarin SundströmFang Fang10.1371/journal.pmed.10043722024-03-25T14:00:00Z2024-03-25T14:00:00Z<p>by Eva Herweijer, Kejia Hu, Jiangrong Wang, Donghao Lu, Pär Sparén, Hans-Olov Adami, Unnur Valdimarsdóttir, Karin Sundström, Fang Fang</p>
Background <p>Women with mental illness experience an increased risk of cervical cancer. The excess risk is partly due to low participation in cervical screening; however, it remains unknown whether it is also attributable to an increased risk of infection with human papillomavirus (HPV). We aimed to examine whether women with mental illness had an increased infection rate of HPV compared to women without mental illness.</p> Methods and findings <p>Using a cohort design, we analyzed all 337,116 women aged 30 to 64 and living in Stockholm, who had a negative test result of 14 high-risk HPV subtypes in HPV-based screening, during August 2014 to December 2019. We defined women as exposed to mental illness if they had a specialist diagnosis of mental disorder or had a filled prescription of psychotropic medication. We identified incident infection of any high-risk HPV during follow-up and fitted multivariable Cox models to estimate hazard ratios (HR) with 95% confidence intervals (CI) for HPV infection.A total of 3,263 women were tested positive for high-risk HPV during follow-up (median: 2.21 years; range: 0 to 5.42 years). The absolute infection rate of HPV was higher among women with a specialist diagnosis of mental disorder (HR = 1.45; 95% CI [1.34, 1.57]; <i>p</i> < 0.001) or a filled prescription of psychotropic medication (HR = 1.67; 95% CI [1.55, 1.79]; <i>p</i> < 0.001), compared to women without such. The increment in absolute infection rate was noted for depression, anxiety, stress-related disorder, substance-related disorder, and ADHD, and for use of antidepressants, anxiolytics, sedatives, and hypnotics, and was consistent across age groups.The main limitations included selection of the female population in Stockholm as they must have at least 1 negative test result of HPV, and relatively short follow-up as HPV-based screening was only introduced in 2014 in Stockholm.</p> Conclusions <p>Mental illness is associated with an increased infection rate of high-risk HPV in women. Our findings motivate refined approaches to facilitate the WHO elimination agenda of cervical cancer among these marginalized women worldwide.</p>Prevalence of fatigue and cognitive impairment after traumatic brain injuryTraver J. WrightTimothy R. ElliottKathleen M. RandolphRichard B. PylesBrent E. MaselRandall J. UrbanMelinda Sheffield-Moore10.1371/journal.pone.03009102024-03-22T14:00:00Z2024-03-22T14:00:00Z<p>by Traver J. Wright, Timothy R. Elliott, Kathleen M. Randolph, Richard B. Pyles, Brent E. Masel, Randall J. Urban, Melinda Sheffield-Moore</p>
Background <p>Following traumatic brain injury (TBI) some patients develop lingering comorbid symptoms of fatigue and cognitive impairment. The mild cognitive impairment self-reported by patients is often not detected with neurocognitive tests making it difficult to determine how common and severe these symptoms are in individuals with a history of TBI. This study was conducted to determine the relative prevalence of fatigue and cognitive impairment in individuals with a history of TBI.</p> Methods <p>The Fatigue and Altered Cognition Scale (FACs) digital questionnaire was used to assess self-reported fatigue and cognitive impairment. Adults aged 18–70 were digitally recruited for the online anonymous study. Eligible participants provided online consent, demographic data, information about lifetime TBI history, and completed the 20 item FACs questionnaire.</p> Results <p>A total of 519 qualifying participants completed the online digital study which included 204 participants with a history of TBI of varied cause and severity and 315 with no history of TBI. FACs Total Score was significantly higher in the TBI group (57.7 ± 22.2) compared to non-TBI (39.5 ± 23.9; p<0.0001) indicating more fatigue and cognitive impairment. When stratified by TBI severity, FACs score was significantly higher for all severity including mild (53.9 ± 21.9, p<0.0001), moderate (54.8 ± 24.4, p<0.0001), and severe (59.7 ± 20.9, p<0.0001) TBI. Correlation analysis indicated that more severe TBI was associated with greater symptom severity (p<0.0001, r = 0.3165). Ancillary analysis also suggested that FACs scores may be elevated in participants with prior COVID-19 infection but no history of TBI.</p> Conclusions <p>Adults with a history of even mild TBI report significantly greater fatigue and cognitive impairment than those with no history of TBI, and symptoms are more profound with greater TBI severity.</p>Monitoring the after-effects of ischemic stroke through EEG microstatesFang WangXue YangXueying ZhangFengyun Hu10.1371/journal.pone.03008062024-03-22T14:00:00Z2024-03-22T14:00:00Z<p>by Fang Wang, Xue Yang, Xueying Zhang, Fengyun Hu</p>
Background and purpose <p>Stroke may cause extensive after-effects such as motor function impairments and disorder of consciousness (DoC). Detecting these after-effects of stroke and monitoring their changes are challenging jobs currently undertaken via traditional clinical examinations. These behavioural examinations often take a great deal of manpower and time, thus consuming significant resources. Computer-aided examinations of the electroencephalogram (EEG) microstates derived from bedside EEG monitoring may provide an alternative way to assist medical practitioners in a quick assessment of the after-effects of stroke.</p> Methods <p>In this study, we designed a framework to extract microstate maps and calculate their statistical parameters to input to classifiers to identify DoC in ischemic stroke patients automatically. As the dataset is imbalanced with the minority of patients being DoC, an ensemble of support vector machines (EOSVM) is designed to solve the problem that classifiers always tend to be the majority classes in the classification on an imbalanced dataset.</p> Results <p>The experimental results show EOSVM get better performance (with accuracy and F1-Score both higher than 89%), improving sensitivity the most, from lower than 60% (SVM and AdaBoost) to higher than 80%. This highlighted the usefulness of the EOSVM-aided DoC detection based on microstates parameters.</p> Conclusion <p>Therefore, the classifier EOSVM classification based on features of EEG microstates is helpful to medical practitioners in DoC detection with saved resources that would otherwise be consumed in traditional clinic checks.</p>Incidence of type 2 diabetes, cardiovascular disease and chronic kidney disease in patients with multiple sclerosis initiating disease-modifying therapies: Retrospective cohort study using a frequentist model averaging statistical frameworkAlan J. M. BrnabicSarah E. CurtisJoseph A. JohnstonAlbert LoAnthony J. ZagarIlya LipkovichZbigniew KadziolaMegan H. MurrayTimothy Ryan10.1371/journal.pone.03007082024-03-22T14:00:00Z2024-03-22T14:00:00Z<p>by Alan J. M. Brnabic, Sarah E. Curtis, Joseph A. Johnston, Albert Lo, Anthony J. Zagar, Ilya Lipkovich, Zbigniew Kadziola, Megan H. Murray, Timothy Ryan</p>
Researchers are increasingly using insights derived from large-scale, electronic healthcare data to inform drug development and provide human validation of novel treatment pathways and aid in drug repurposing/repositioning. The objective of this study was to determine whether treatment of patients with multiple sclerosis with dimethyl fumarate, an activator of the nuclear factor erythroid 2-related factor 2 (Nrf2) pathway, results in a change in incidence of type 2 diabetes and its complications. This retrospective cohort study used administrative claims data to derive four cohorts of adults with multiple sclerosis initiating dimethyl fumarate, teriflunomide, glatiramer acetate or fingolimod between January 2013 and December 2018. A causal inference frequentist model averaging framework based on machine learning was used to compare the time to first occurrence of a composite endpoint of type 2 diabetes, cardiovascular disease or chronic kidney disease, as well as each individual outcome, across the four treatment cohorts. There was a statistically significantly lower risk of incidence for dimethyl fumarate versus teriflunomide for the composite endpoint (restricted hazard ratio [95% confidence interval] 0.70 [0.55, 0.90]) and type 2 diabetes (0.65 [0.49, 0.98]), myocardial infarction (0.59 [0.35, 0.97]) and chronic kidney disease (0.52 [0.28, 0.86]). No differences for other individual outcomes or for dimethyl fumarate versus the other two cohorts were observed. This study effectively demonstrated the use of an innovative statistical methodology to test a clinical hypothesis using real-world data to perform early target validation for drug discovery. Although there was a trend among patients treated with dimethyl fumarate towards a decreased incidence of type 2 diabetes, cardiovascular disease and chronic kidney disease relative to other disease-modifying therapies–which was statistically significant for the comparison with teriflunomide–this study did not definitively support the hypothesis that Nrf2 activation provided additional metabolic disease benefit in patients with multiple sclerosis.