Telemedicine has the advantage of providing medical resources in rural areas, but few studies have been conducted to investigate its efficacy in dementia care, compared to face-to-face care. This study evaluated the effectiveness of telemedicine in relation to cognitive changes in patients with dementia. We evaluated cognitive changes over time, according to care modality, in 188 patients with dementia who were registered at our university-based dementia clinic. We followed 98 patients using telemedicine services and 90 patients who attended the dementia clinic in person. Patients in the telemedicine group also visited a public health center located in a rural area about 50 km from the dementia clinic. Changes in the mean annualized Mini-Mental State Examination (MMSE) score were not significantly different between the telemedicine group and the face-to-face dementia clinic group (p = 0.291), with changes of 0.60 and 1.03 points, respectively. However, cognitive decline was significantly lower in the telemedicine group for the less severe initial cognitive performance subgroup than more severe cognitive performance subgroup (p = 0.049), with changes of 0.62 and 1.59 points, respectively. Higher initial Clinical Dementia Rating (CDR) scores, MMSE scores, and age were found to be independent predictive factors of subsequent cognitive changes, as indicated by mean annualized MMSE scores. These findings suggest that telemedicine may be a useful alternative to face-to-face clinical visits for management of dementia in patients who are located in rural areas.

Jang JW, et al. J Clin Neurol. 2021 Apr;17(2):249-256. https://doi.org/10.3988/jcn.2021.17.2.249

Leukemia is a cancer of blood cells in the bone marrow that affects both children and adolescents. The rapid growth of unusual lymphocyte cells leads to bone marrow failure, which may slow down the production of new blood cells, and hence increases patient morbidity and mortality. Age is a crucial clinical factor in leukemia diagnosis, since if leukemia is diagnosed in the early stages, it is highly curable. Incidence is increasing globally, as around 412,000 people worldwide are likely to be diagnosed with some type of leukemia, of which acute lymphoblastic leukemia accounts for approximately 12% of all leukemia cases worldwide. Thus, the reliable and accurate detection of normal and malignant cells is of major interest. Automatic detection with computer-aided diagnosis (CAD) models can assist medics, and can be beneficial for the early detection of leukemia. In this paper, a single center study, we aimed to build an aggregated deep learning model for Leukemic B-lymphoblast classification. To make a reliable and accurate deep learner, data augmentation techniques were applied to tackle the limited dataset size, and a transfer learning strategy was employed to accelerate the learning process, and further improve the performance of the proposed network. The results show that our proposed approach was able to fuse features extracted from the best deep learning models, and outperformed individual networks with a test accuracy of 96.58% in Leukemic B-lymphoblast diagnosis.

The endoplasmic reticulum (ER) is selectively degraded by ER-phagy to maintain cell homeostasis. α-synuclein accumulates in the ER, causing ER stress that contributes to neurodegeneration in Parkinson’s disease (PD), but the role of ER-phagy in α-synuclein modulation is largely unknown. Here, we investigated the mechanisms by which ER-phagy selectively recognizes α-synuclein for degradation in the ER. We found that ER-phagy played an important role in the degradation of α-synuclein and recovery of ER function through interaction with FAM134B, where calnexin is required for the selective FAM134B-mediated α-synuclein clearance via ER-phagy. Overexpression of α-synuclein in the ER of the substantia nigra (SN) resulted in marked loss of dopaminergic neurons and motor deficits, mimicking PD characteristics. However, enhancement of ER-phagy using FAM134B overexpression in the SN exerted neuroprotective effects on dopaminergic neurons and recovered motor performance. These data suggest that ER-phagy represents a specific ER clearance mechanism for the degradation of α-synuclein.

Objective To investigate the effects of single sensory impairment (SSI; visual or auditory) or dual sensory impairment (DSI; visual and auditory) on dementia and longitudinal changes of neuropsychological test scores. Methods In this nationwide, prospective, community-based elderly cohort study, KLOSCAD (the Korean Longitudinal Study on Cognitive Aging and Dementia), 6,520 elderly individuals (58–101 years) representing the general population were included. We defined visual and auditory sensory impairment via self-report questionnaire: 932 had normal sensory function, 2,957 had an SSI, and 2,631 had a DSI. Demographic and clinical variables including cognitive outcomes were evaluated every 2 years over 6 years. Through logistic regression, Cox regression, and linear mixed model analysis, the relationship between SSI or DSI and dementia prevalence, dementia incidence, and change in neuropsychological scores were evaluated. Results At baseline, DSI was significantly associated with increased dementia prevalence compared to normal sensory function (odds ratio [OR] 2.17, 95% confidence interval [CI] 1.17–4.02), but SSI was not (OR 1.27, 95% CI 0.66–2.41). During the 6-year follow-up, the incidence of dementia was significantly higher in the DSI group than in the normal sensory function group (hazard ratio 1.9, 95% CI 1.04–3.46) and neuropsychological scores significantly decreased (β −0.87, 95% CI [−1.17 to −0.58]). Conclusions Our results suggest that coexisting visual and hearing impairments facilitate dementia prevalence, dementia incidence, and cognitive decline, but visual or hearing impairment alone do not. Visual and hearing impairment may lead to dementia or cognitive decline independent of Alzheimer pathology.

We aimed to present the study design of an independent validation cohort from the Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer’s disease (AD) (KBASE-V) and to investigate the baseline characteristics of the participants according to the AD clinical spectrum. We recruited 71 cognitively normal (CN) participants, 96 with subjective cognitive decline (SCD), 72 with mild cognitive impairment (MCI), and 56 with AD dementia (ADD). The participants are followed for three years. The Consortium to Establish a Registry for AD scores was significantly different between all of the groups. The logical memory delayed recall scores were significantly different between all groups, except between the MCI and ADD groups. The Mini-Mental State Examination score, hippocampal volume, and cerebrospinal fluid (CSF) amyloid-β42 level were significant difference among the SCD, MCI, and ADD groups. The frequencies of participants with amyloid pathology according to PET or CSF studies were 8.9%, 25.6%, 48.3%, and 90.0% in the CN, SCD, MCI, and ADD groups, respectively. According to ATN classification, A+/T+/N+ or A+/T+/N− was observed in 0%, 15.5%, 31.0%, and 78.3% in the CN, SCD, MCI, and ADD groups, respectively. The KBASE-V showed a clear difference according to the AD clinical spectrum in neuropsychological tests and AD biomarkers.