bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identification of plasma protein panels for detection of cognitive decline in MCI and AD by LC‐MS/MS
Authors: Inoue Makoto , Ito Hitomi , Liu Shan , Suzuki Hideaki , Akatsu Hiroyasu , Matsukawa Noriyuki , Asada Takashi , Arai Tetsuaki , Uchida Kazuhiko 
Published: December 2021

AbstractBackgroundFor the prevention of dementia, noninvasive screening methods which detect the signs of cognitive decline before clinical symptom occurs are needed. We previously reported blood‐based composite marker for mild cognitive impairment (MCI) and Alzheimer's disease (AD) consisting of apoA1, TTR, and C3. A combination of blood proteins could be a promising biomarker for monitoring the progression of cognitive decline from early stages of the disease. Here, we developed LC‐MS/MS‐based blood test using plasma proteins for MCI and AD to explore accurate and practical screening of the disease.MethodWe constructed a robust and reproducible LC‐MS/MS blood test system equipped with MRM to quantify 45 major plasma proteins with relatively high amounts using isotope‐labeled synthetic peptide. These plasma protein levels from 192 cases (NDC: 58, MCI: 71, AD: 63) were determined. Multinomial regression and ROC analyses were performed to identify the combination of the plasma protein panels that could discriminate NDC vs. MCI and/or AD.ResultWe found eight interpretable protein biomarker candidates in plasma for MCI and AD, which were related to innate immunity, coagulation pathways, lipid metabolism, and nutrition. Some of them are involved in the neurovascular unit injury. The optimal combination of these proteins and the coefficients of the logistic models revealed different clinical potential between male and female. In the model discriminating cognitive impairment from NDC, the AUC values of the ROC analysis were 0.82 and 0.72 for male and female, respectively. Furthermore, we constructed composite scores optimized for male and female using these plasma protein panels, and they had a significant correlation with severity of the cognitive decline determined by clinical manifestation.ConclusionLC‐MS‐based plasma protein panels interpretable for pathophysiology of AD detect signs of cognitive decline and progression of the disease.
The relationship between regional amyloid deposition and executive function decline in adults with Down syndrome
Authors: Hom Christy , Taylor Lisa , Mapstone Mark , Rosas H. Diana , Silverman Wayne , Krinsky‐McHale Sharon J , Pulsifer Margaret , Lai Florence , Schupf Nicole , Lott Ira T , Keator David 
Published: December 2021

AbstractBackgroundAn increase in global deposition of amyloid is known to be related to declines in a variety of cognitive domains among people with Down syndrome (DS). Less known is the correspondence between increased regional amyloid load and declines in specific functions. Since a decline in frontal lobe functions (e.g., attention, inhibitory control, shifting, motivation) is considered by many to be a key early indicator of AD dementia in adults with DS, the current study aims to identify regional amyloid changes that are associated with executive function (EF) decline in both pre‐symptomatic and symptomatic adults with DS.MethodLongitudinal data from participants of the Biomarkers of Alzheimer’s Disease in Adults with Down Syndrome (ADDS) consortium, at all stages of AD (pre‐clinical, prodromal, and clinical dementia), were examined. Forty‐two participants received amyloid PET and MRI scans and extensive neuropsychological testing of select cognitive functions at two time points, approximately 16 months apart. Changes in amyloid accumulation in the anterior and posterior cingulate, frontal lobe, superior temporal lobe, and parietal lobe were hypothesized to be related to performance on three measures of EF: Rapid Assessment of Developmental Disabilities (RADD) Digit Span Forward and Stroop Cats and Dogs Naming and Switching. PET data were co‐registered with T1‐weighted MRIs, converted to SUVR units using the cerebellum cortex reference region, and spatially normalized using a DS MRI template in MNI space. We modeled relationships between amyloid SUVR and EF using multiple regression in SPM12 with covariates accounting for time difference between the scans and neurocognitive assessment acquisition and sex.ResultsConsistent with our hypothesis, we found clear associations between increased amyloid deposition and decline in EF in people with DS in approximately the same regions as found in neurotypical populations without AD (Figure 1). Frontal lobe amyloid deposition disrupts dorsal and ventral attention network processes.ConclusionsWe found amyloid deposition in specific functional networks correspond to EF decline in a population with lifelong amyloid production and cognitive impairments. These findings bring us one step closer to validating biomarkers of early AD in DS.
Analysis and proposal of healthcare‐related applications for the elderly
Authors: Lee Hey Sig , Park Hae Yean 
Published: December 2021

AbstractBackgroundTrend analysis and discussion of existing elderly health‐related application studies are essential for elderly health care. Therefore, in this study, the trend of research on elderly health‐related applications is to be identified, classified and analyzed for the form, method, and purpose of the application.MethodIn this study, ten related studies were selected by searching the literature for the last five years from January 2015 to July 2020 to analyze trends in health‐related applications for the elderly, and the applications in the selected studies were divided into type, method and purpose.ResultThere were three types of applications: mobile phone, tablet PC, and computer and were three methods of applications: Direct Control‐Direct Information, Indirect Control‐Indirect Information, Direct Control‐Indirect Information and were four purposes of applications: cognitive health, physical health, mental health, lifestyle education.ConclusionThrough this study, we can grasp information and trends on the application related to health for the elderly, and it is expected to be used as a basis for research on the long‐term effects of the application related to health for the elderly.
Outpatient cognitive therapy can change the course of dementia irrespective of etiology
Authors: Kumar Suresh , Shah Shalin , Chalamalasetty Prasanth , Kumar Aryan 
Published: December 2021

AbstractIntroductionNeuroplasticity can only occur in an ideal body condition and establish a new synaptic connection with repeated stimulations in weak cognitive domains or circuits.MethodA Two‐phase study was planned as a course of memory loss treatment in an outpatient clinic for a period of 3 years. 49 of 72 acquired brain injury and dementia patients completed X≥14 sessions of cognitive therapy intervention within the period of 2‐4 months. Patients selected for intervention had mild severe memory loss on MoCA Score [(9‐24)/30]. The first phase of intervention was the correction of nutraceutical status and sleep optimization. The second phase of the intervention was individualized cognitive therapy (CT) by trained cognitive therapists after the Digital Mobile Assessment of Cognitive test (DMAC) was given before and after an intervention. The domains included visual, auditory, delayed recall, attention, executive, number recall, disinhibition, language, and working memory.ResultsStatistical analysis of n‐49 with confidence interval 95%, series paired t‐tests showed in the post‐intervention group, on average, scores were higher as follows: Visual domain 4.89% to 13.74% (p < 0.001), Auditory domain 8.35% to 19.72% (p < 0.001), Delayed recall 21.34% to 33.95% (p < 0.001), Disinhibition Frontal domain 6.89% to 21.80% (p < 0.001), Attention domain 9.33%, 26.12% (p < 0.001 ), Executive domain 9.81%, 23.06% ( p < 0.001), Number domain 5.22% to 17.91% (p < 0.001), and Working memory 2.96%, 29.85% (p = 0.01).DiscussionDr. Eric Kandel, Nobel Laureate, showed that damaged neurons can synapse after repeated neuron stimulation. Physical therapy is a standard of practice after acquired brain injury, but cognitive impairment evaluation is often ignored. The systematic approach to body optimization for learning and cognitive therapy can change the course of cognitive decline in dementia or acquired brain injury.ConclusionThe significant improvement in mild to severe dementia in short‐term memory or patients’ ability of memory retention improved 22% to 34% in the intervention group provides statistically significant evidence that a systematic approach to cognitive therapy can reverse the course of cognitive decline.
Multimodal brain imaging demonstrates that both amyloid burden and glucose metabolism predict the severity of cognitive impairment in patients with Alzheimer’s disease
Authors: Atay Lutfiye Ozlem , Akdemir Umit Ozgur , Yetim Ezgi , Balci Erdem , Arsava Ethem Murat , Topcuoglu Mehmet Akif , Saka Esen 
Published: December 2021

AbstractBackgroundThe purpose of this study is to assess brain glucose metabolism and Amyloid‐β burden in patients with Alzheimer’s disease with 3 Tesla PET/MR imaging and to seek possible relation of imaging findings with the extent of cognitive impairment.Method45 consecutive subjects with memory complaints were evaluated with a detailed neuropsychological test battery and F18‐Fluorodeoxyglucose(FDG)‐PET/MRI and F18‐Flutemetamol‐PET/MRI scans. The imaging modalities were performed with a hybrid 3T PET / MR camera at a maximum of 7 days intervals. Images were visually evaluated by two nuclear medicine experts. The centiloid scores were calculated through amyloid standardized uptake value ratios (SUVR) for all participants and regional glucose metabolism characteristics were analyzed.ResultThe study population consisted of 30 males and 15 females with a mean age of 65.9±8.2 years. Mean MMSE was 21.7±7.2 for the overall group. Five patients had imaging features suggestive of non‐AD type of dementias and were excluded from further analyses. Visual examination of F18‐Flutemetamol PET/MRI was consistent with the Alzheimer’s disease continuum in 29 cases, 9 of them demonstrated normal glucose metabolism, whereas 20 remaining cases showed F18‐FDG‐PET/MRI patterns characteristic to Alzheimer’s disease (hypometabolism in parieto‐temporal cortices and/or posterior cingulate cortex). In bivariate analysis, MMSE was positively correlated with the glucose metabolism in temporal lobe and posterior cingulate gyrus (r= 0.382, p=0.020; r=0.330, p=0.046; respectively), additionally, a significant negative correlation was observed between MMSE and amyloid burden designated by the centiloid score (r=‐0.461, p=0.004). Memory performance tested by Enhanced Cued Recall (ECR) was also positively associated with the glucose metabolism in posterior cingulate gyrus (r= 0.446, p=0.006), and negatively associated with the centiloid value (r= ‐0.458, p=0.005). The relationship between the ECR test and the centiloid value persisted when adjusted for age, gender, and year of education (β=‐0.121, p=0.021) in multivariate models.ConclusionGeneral cognitive ability and memory were predicted by imaging markers of regional glucose metabolism and amyloid deposition in this study population with early‐stage Alzheimer’s disease. Further research should investigate the predictive value of those imaging markers for the rate of cognitive decline. Acknowledgment: We acknowledge the support of GE Health Care for the [F18]flutemetamol doses.
The impact of ICT use on feelings of loneliness and isolation during the COVID‐19 lockdown among older people
Authors: Vaccaro Roberta , Rolandi Elena , Colombo Mauro , Abbondanza Simona , Pettinato Laura , Poloni Tino Emanuele , Davin Annalisa , Guaita Antonio 
Published: December 2021

AbstractBackgroundOlder adults are at risk of psychological consequences along home segregation during COVID‐19 pandemic. Information Communication Technologies (ICTs) are crucial in such context even among older people. Aim: to explore the impact of being ICTusers on loneliness and ICTs use among older adults from pre to lockdown period.MethodsData were extracted from the fourth follow‐up (2018) of the InveCe.Ab, a multidimensional population‐based study (NCT01345110) on 70‐75 older people living in Abbiategrasso (Milan, Lombardy) at baseline (2009). Sixty‐six of them were trained for SNS use in 2019, as a part of the ANS‐SE study (NCT04242628). A telephone interview was administered during the lockdown period (March‐May 2020), collecting information on self‐perceived loneliness measured by the 3‐item UCLA loneliness scale and ICT use [smartphones, computers, internet and Social Network Sites (SNSs)]. Participants in the pre‐lockdown assessment reporting use of any ICT were defined as ICTusers. Cross‐sectional differences between ICTusers and non‐users were explored using Independent Sample t‐test or Chi‐square test. Analysis of covariance (ANCOVA) was applied to compare the long‐term effect of being ICTusers and non‐users on loneliness change (UCLA 3‐item total and subscales) and ICT use change, including the pre‐lockdown measures and being trained for SNSs use as covariates, followed by post‐hoc comparisons.ResultsPre‐lockdown participants with ICT use data available were 623 (163 ICT users, 460 non‐users). Table 1 shows that ICTusers were mostly men, more educated, showed fewer depressive symptoms (GDS) and higher global cognition (MMSE) than ICTnon‐users. ICTusers felt less total loneliness, fewer feelings of a lack of companionship and isolation from others than ICTnon‐users. Pre‐lockdown ICT use was on average 2.11 (DS 1.05). Longitudinal significant difference emerged between the two groups on total loneliness, with ICTusers (n=130), showing a decrease (mean difference (SE): ‐0.382 (0.179); 95% CI: ‐0.733, ‐0.030; p=0.033) compared to non‐users (n=296). ICTusers (n=130), reported fewer feelings of isolation (mean difference (SE): ‐0.213 (0.068); 95% CI: ‐0.348, ‐0.079; p=0.002) than non‐users (n=300).ConclusionsDuring the COVID‐19 lockdown, former ICTusers were protected against feelings of loneliness and isolation. The ICT use did not change in both groups.
Effects of coach robot pepper versus tablet training on psychosocial and physical outcomes of persons with dementia: A mixed‐methods study
Authors: Schüssler Sandra , Zuschnegg Julia , Paletta Lucas , Lodron Gerald , Steiner Josef , Pansy‐Resch Sandra , Prodromou Dimitrios , Brunsch Sebastian , Carnevale Lorenzo , Orgel Thomas , Schneeberger Michael , Russegger Silvia , Fellner Maria , Lammer Lara , Holter Magdalena 
Published: December 2021

AbstractBackgroundThe evidence of social robots for people with dementia (PwD) living at home is unclear. The aim was to explore the effects of Coach Pepper (socially assistive humanoid robot system “AMIGO” combined with external tablet‐based training) versus an exclusively tablet‐based training on quality of life, motivation, cognition, mobility, care dependency, depression, and neuropsychiatric symptoms, as well as the user experience with Coach Pepper.MethodsThe study (2019‐2020) includes a randomized controlled trial with complementary interviews using content analysis. The intervention group (16 PwD) received Coach Pepper and the control group (16 PwD) an exclusively tablet‐based training for three weeks. Data were collected using standardized questionnaires (AES, MOCA, DEMQOL, PAS, TUG, GDS, NPI) and interviews.ResultsIn both groups, PwD were >80 years old and mainly female. The mild stage of Alzheimer's was predominant in both groups. The comparison of quality of life (DEMQOL questionnaire) between the groups showed a significantly greater increase in the Coach Pepper group (X̅: 5.48 vs. ‐0.31; med: 4 vs. 2 points, p = 0.0226). Furthermore, global quality of life increased significantly in the Coach Pepper group (X̅: 0.4 vs. ‐0.2; med: 1.0 vs. 0.0 points; p = 0.013). All other outcomes did not differ significantly. Main qualitative results: Attitude/feelings ‐ PwD reacted mainly positively to Pepper. The PwD were generally not afraid of Pepper and did not feel repulsed. They found Pepper nice/pleasant and funny. Communication, social contacts ‐ Pepper was received well and integrated as a family member. His presence was not disturbing, more an enrichment. PwD regarded Pepper as a friend, child and contact person. He promoted communication in PwD. The life of PwD “bloomed” and they bonded with Pepper, which caused feelings of sadness after Pepper moved out. Meaningful activities‐ music and dance activities stimulated PwD particularly positively.ConclusionCoach Pepper significantly increased the quality of life of the PwD in the robot group. As the additional qualitative results demonstrate, this increase can be attributed in particular to the promotion of communication and social contacts by Pepper. Further research should focus on the increase of Pepper’s communication skills and program content.
A convolutional neural network algorithm for step and gait bout estimation from wristband accelerometry
Authors: Peraza Luis R. , Kinnunen Kirsi M. , Joules Richard , Wolz Robin 
Published: December 2021

AbstractBackgroundWalking depends on an intricate interplay between cognitive and motor functions that can be impaired by neurodegeneration. Recent developments on the use of wearable sensors permit the measurement of multiple gait markers to establish their association with symptoms of neurodegeneration. To estimate gait markers, accurate algorithms have been developed for sensors worn around the trunk (e.g., waist) or on lower limbs. However, there has been limited research to develop gait algorithms for wristband accelerometry, despite their superior wear compliance compared to other body‐worn sensors. Our work aims to investigate the feasibility of gait metrics estimated from wrist‐worn accelerometry devices.MethodHealthy adults (N=26) were recruited in a multiactivity study which also included a 25‐feet walking exercise along a corridor. Participants wore a lumbar wearable sensor (AX3, Axivity) and a wristband sensor on the non‐dominant hand (GENEActiv, Activinsights). Both devices were mechanically synchronised before and after each study session. Steps were detected and labelled with a heel‐impact detection algorithm applied on the lumbar sensor accelerometry data. Posterior visual inspection was implemented to correct for non‐steps or missing steps. Step labels were posteriorly used to train a convolutional neural network (CNN) algorithm to detect individual steps from the wristband device as well as standing and walking segments. Algorithm performance was assessed with a leave‐one‐subject‐out (LOSO) validation procedure.ResultThe LOSO validation resulted in an average global accuracy of 88% (95% confidence interval, CI: 87 – 90%) for the three labels of standing, walking, and steps. For the detection of individual steps, the percentage of absolute error was 6.5% (95% CI: 4.9 ‐ 8.0%), or an error of 6.5 steps per 100. The heel impact time error detection showed a mean delay of +9.7 msecs (95% CI: ‐2.2 ‐ 21.7 msecs).ConclusionOur investigation shows that it is feasible to assess gait from wristband devices using CNNs with high accuracy and an acceptable level of model generalisation. Our future work will focus on further improvements to our gait models, and on transferring the trained CNN models to estimate gait in populations affected by neurodegenerative conditions such as different forms of dementia, Parkinsonian disorders, and Huntington’s disease.
Association of air quality reduction with incident dementia: Effects of natural course and hypothetical air pollutant interventions using g‐computation
Authors: Letellier Noemie , Gutierrez Laure‐Anne , Berr Claudine , Mortamais Marion , Benmarhnia Tarik 
Published: December 2021

AbstractBackgroundThe benefits of air quality improvement on the burden of neurological disorders could be substantial given the emerging evidence regarding the role of air pollution on dementia incidence. However, none evidence exists about the impact of air pollution reduction on incidence of dementia. The aim of this study is to quantify how observed reduction in PM2.5 concentration leads to dementia‐incidence benefits and simulate the benefits of hypothetical air quality improvement interventions on the reduction of dementia incidence.MethodsAmong the French Three‐City Cohort (12 years of follow‐up), dementia diagnoses were made using DSM‐IV criteria and validated by an adjudication committee. Exposure to PM2.5 was estimated using Land Use Regression models. We performed multi‐level Cox proportional and Aalen additive hazard regression models to assess the effect of observed PM2.5 reduction on dementia risk. Then, we used a parametric g‐computation approach to quantify the effects of various hypothetical interventions to reduce PM2.5 exposure on dementia risk.ResultsAmong 7051 participants (median age: 73), the median PM2.5 reduction between 1990 and 2000, 10 years prior to inclusion, was 12.2 (µg/m3). Such reduction reduced the risk of all‐type of dementia (hazard ratio (HR) 0.85, 95% confidence interval (CI):0.76‐0.95) and Alzheimer's disease (HR 0.83, 95%CI:0.72‐0.94). Approximately 197 less cases of all type of dementia per 100 000 persons and year could be attributed to PM2.5 reduction. Using g‐computation, we quantified the expected number of prevented dementia cases under different hypothetical interventions. For example, for compliance with a hypothetical reduction of more than 13.10 µg/m3 (reduction observed in the city of Montpellier), the rate difference was ‐0.33 (95%CI, −0.51 to −0.15).ConclusionThese findings highlight the possible substantial benefits of reducing air pollution in the prevention of dementia.