Resting‐state fMRI (rs‐fMRI) detects functional connectivity (FC) abnormalities that occur in the brains of patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI). FC of the default mode network (DMN) is commonly impaired in AD and MCI. We conducted a systematic review aimed at determining the diagnostic power of rs‐fMRI to identify FC abnormalities in the DMN of patients with AD or MCI compared with healthy controls (HCs) using machine learning (ML) methods. Multimodal support vector machine (SVM) algorithm was the commonest form of ML method utilized. Multiple kernel approach can be utilized to aid in the classification by incorporating various discriminating features, such as FC graphs based on “nodes” and “edges” together with structural MRI‐based regional cortical thickness and gray matter volume. Other multimodal features include neuropsychiatric testing scores, DTI features, and regional cerebral blood flow. Among AD patients, the posterior cingulate cortex (PCC)/Precuneus was noted to be a highly affected hub of the DMN that demonstrated overall reduced FC. Whereas reduced DMN FC between the PCC and anterior cingulate cortex (ACC) was observed in MCI patients. Evidence indicates that the nodes of the DMN can offer moderate to high diagnostic power to distinguish AD and MCI patients. Nevertheless, various concerns over the homogeneity of data based on patient selection, scanner effects, and the variable usage of classifiers and algorithms pose a challenge for ML‐based image interpretation of rs‐fMRI datasets to become a mainstream option for diagnosing AD and predicting the conversion of HC/MCI to AD.

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Background Persicaria minor extract exhibits antioxidant and anti-inflammatory properties and has potential effects on cognitive function and mood. However, the effects of P.minor on brain activation and biomarkers have not been studied among older adults. This multicentre, randomized, double-blinded, placebo-controlled study aimed to investigate the effect of 6 months P.minor extract supplement (Biokesum®) on cognition, mood, biomarkers, and brain activation among older adults with Mild Cognitive Impairment (MCI). Method A total of 36 Malaysian community-dwelling older adults with MCI (60–75-year-old) were randomized into Biokesum® (n = 18) and placebo group (n = 18). Each subject consumed one capsule of Biokesum® (250 mg/capsule) or placebo (maltodextrin, 280 mg/capsule) twice daily for 6 months. Cognitive function and mood were assessed at baseline, 3rd, and 6th-month using neuropsychological tests (MMSE, Digit Span, RAVLT, Digit Symbol, and Visual Reproduction) and Profile of Mood State (POMS) questionnaire. Blood lipid profile, fasting blood glucose, and biomarkers (MDA, LPO, COX-2, iNOS, and BDNF) were measured at baseline and 6th month. By the end of the intervention, there were 30 compliers (Biokesum®: N = 15; Placebo: N = 15) and 6 dropouts. For brain activation assessment, 15 subsamples (Biokesum®: N = 8; Placebo: N = 7) completed N-back and Stroop tasks during fMRI scanning at baseline and 6th month. The dorsolateral prefrontal cortex (Brodmann’s area 9 and 46) was identified as a region of interest (ROI) for brain activation analysis using SPM software. Results Two-way mixed ANOVA analysis showed significant improvements in Visual Reproduction II (p = 0.012, partial η2 = 0.470), tension (p = 0.042, partial η2 = 0.147), anger (p = 0.010, partial η2 = 0.207), confusion (p = 0.041, partial η2 = 0.148), total negative subscales (p = 0.043, partial η2 = 0.145), BDNF (p = 0.020, partial η2 = 0.179) and triglyceride (p = 0.029, partial η2 = 0.237) following 6 months of Biokesum® supplementation. Preliminary finding also demonstrated significant improvement at 0-back task-induced right DLPFC activation (p = 0.028, partial η2 = 0.652) among subsamples in Biokesum® group. No adverse events were reported at the end of the study. Conclusion Six months Biokesum® supplementation potentially improved visual memory, negative mood, BDNF, and triglyceride levels among older adults with MCI. Significant findings on brain activation at the right DPLFC must be considered as preliminary. Trial registration Retrospectively registered on 30th August 2019 [ISRC TN12417552].

BackgroundDorsolateral prefrontal cortex (DLPFC) is a key node in the cognitive control network that supports working memory. DLPFC dysfunction is related to cognitive impairment. It has been suggested that dietary components and high-density lipoprotein cholesterol (HDL-C) play a vital role in brain health and cognitive function.PurposeThis study aimed to investigate the relationships between dietary nutrient intake and lipid levels with functional MRI (fMRI) brain activation in DLPFC among older adults with mild cognitive impairment.Participants and methodsA total of 15 community-dwelling older adults with mild cognitive impairment, aged ≥60 years, participated in this cross-sectional study at selected senior citizen clubs in Klang Valley, Malaysia. The 7-day recall Diet History Questionnaire was used to assess participants’ dietary nutrient intake. Fasting blood samples were also collected for lipid profile assessment. All participants performed N-back (0- and 1-back) working memory tasks during fMRI scanning. DLPFC (Brodmann’s areas 9 and 46, and inferior, middle, and superior frontal gyrus) was identified as a region of interest for analysis.ResultsPositive associations were observed between dietary intake of energy, protein, cholesterol, vitamins B6 and B12, potassium, iron, phosphorus, magnesium, and HDL-C with DLPFC activation (P<0.05). Multivariate analysis showed that vitamin B6 intake, β=0.505, t (14)=3.29, P=0.023, and Digit Symbol score, β=0.413, t (14)=2.89, P=0.045; R2=0.748, were positively related to DLPFC activation.ConclusionIncreased vitamin B6 intake and cognitive processing speed were related to greater activation in the DLPFC region, which was responsible for working memory, executive function, attention, planning, and decision making. Further studies are needed to elucidate the mechanisms underlying the association.

Background: Cognitive frailty (CF) is identified as one of the main precursors of dementia. Multidomain intervention has been found to delay or prevent the onset of CF. Objective: The aim of our present study is to determine the effectiveness of a comprehensive, multidomain intervention on CF; to evaluate its cost effectiveness and the factors influencing adherence toward this intensive intervention. Methods: A total of 1,000 community dwelling older adults, aged 60 years and above will be screened for CF. This randomized controlled trial involves recruitment of 327 older adults with CF from urban, semi-urban, and rural areas in Malaysia. Multidomain intervention comprised of physical, nutritional, cognitive, and psychosocial aspects will be provided to participants in the experimental group (n = 164). The control group (n = 164) will continue their usual care with their physician. Primary outcomes include CF status, physical function, psychosocial and nutritional status as well as cognitive performance. Vascular health and gut microbiome will be assessed using blood and stool samples. A 24-month intensive intervention will be prescribed to the participants and its sustainability will be assessed for the following 12 months. The effective intervention strategies will be integrated as a personalized telerehabilitation package for the reversal of CF for future use. Results: The multidomain intervention developed from this trial is expected to be cost effective compared to usual care as well as able to reverse CF. Conclusion: This project will be part of the World-Wide FINGERS (Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability) Network, of which common identifiable data will be shared and harmonized among the consortia.

Dyslexia is a neurological disorder that is characterized by imprecise comprehension of words and generally poor reading performance. It affects a significant population of school-age children, with more occurrences in males, thus, putting them at risk of poor academic performance and low selfesteem for a lifetime. The long-term hope is to have a dyslexia diagnostic method that is informed by neural-biomarkers. In this regard, large numbers of machine learning methods and, more recently, deep learning methods have been implemented across various types of dataset with the above-chance classification accuracy. However, attainment of clinical acceptability of these state-of-the-art methods is bedeviled by certain challenges including lack of biologically-interpretable biomarkers, privacy of dataset and classifiers, hyper-parameter selection/optimization, and overfitting problem among others. This review paper critically analyzes recent machine learning methods for detecting dyslexia and its biomarkers and discusses challenges that require proper attentions from the users of deep learning methods in order to enable them to attain clinically relevance and acceptable level. The review is conducted within the premise of implementation and experimental outcomes for each of the 22 selected articles using the Preferred Reporting Items for Systematic review and Meta-Analyses (PRISMA) protocol, with a view to outlining some critical challenges for achieving high accuracy and reliability of the state-of-the-art machine learning methods. As an evidence-based protocol for reporting in systematic reviews and meta-analyses, PRISMA helps to ensure clarity and transparency of this paper by showing a four-phase flow diagram of the selection process for articles used in this review. It is therefore envisaged that higher classification performance of clinical relevance can be achieved using deep learning models for dyslexia and its biomarkers by addressing identified potential challenges.

Objective:This study aims to investigate the public pattern in seeking breast cancer screening information in Malaysia using Google Trends.Methods:The Google Trends database was evaluated for the relative Internet search popularity of breast cancer and screening-related search terms from 2007 to 2018.Results:Result showed downward trends in breast cancer search, whereas mammogram and tomosynthesis search fluctuated consistently. A significant increment was found during Pink October month. Breast cancer search term achieved the highest popularity in the east coast of Malaysia with [x2 (5, N=661) = 110.93, P<0.05], whereas mammogram attained the highest search volume in central Malaysia [x2 (4, N=67) = 18.90, P<0.05]. The cross-correlation for breast cancer was moderate among northern Malaysia, Sabah, and Sarawak (0.3 ≤ rs ≤ 0.7).Conclusion:Public interest trend in breast cancer screening is strongly correlated with the breast cancer awareness campaign, Pink October. Breast cancer screening should be promoted in the rural areas in Malaysia.

A study on the radiation dose associated with cerebral CT angiography (CTA) and CT perfusion (CTP) was conducted on an anthropomorphic phantom with the aim of estimating the effective dose (E) and entrance skin dose (ESD) in the eyes and thyroid gland during different CTA and CTP protocols. The E was calculated to be 0.61 and 0.28 mSv in CTA with 100 and 80 kV(p), respectively. In contrast, CTP resulted in an estimated E of 2.74 and 2.07 mSv corresponding to 40 and 30 s protocols, respectively. The eyes received a higher ESD than the thyroid gland in all of these protocols. The results of this study indicate that combining both CTA and CTP procedures are not recommended in the stroke evaluation due to high radiation dose. Application of modified techniques in CTA (80 kV(p)) and CTP (30 s) is highly recommended in clinical practice for further radiation dose reduction.