Progress in Early Detection of HIV in Tajikistan.

HIV early detection (CD4 counts ≥350 cells/µL) is correlated with higher life expectancy among people living with HIV (PLHIV). Several factors, including physical, cultural, structural, and financial barriers, may limit early detection of HIV. This is a first-of-its-kind study on population-level differences in early detection of HIV across time within Tajikistan and any country in the Central Asia region. Utilizing the Tajikistan Ministry of Health's national HIV data (N = 10,700) spanning 2010 to 2023, we developed median regression models with the median CD4 cell count as the outcome and with the following predictors: time (years), region, age, gender, and area (urban/rural status). Individuals younger than 19 years old were detected early for HIV, whereas those older than 39 years were detected late. Females were detected earlier compared to their male counterparts regardless of region of residence. Rural populations were detected earlier in most years compared to their urban counterparts. The COVID-19 pandemic accelerated HIV early detection in 2021 but most regions have returned to near pre-pandemic levels of detection in 2022 and 2023. There were differences identified among different demographic and geographic groups which warrant further attention.

DeepDRA: Drug repurposing using multi-omics data integration with autoencoders.

Cancer treatment has become one of the biggest challenges in the world today. Different treatments are used against cancer; drug-based treatments have shown better results. On the other hand, designing new drugs for cancer is costly and time-consuming. Some computational methods, such as machine learning and deep learning, have been suggested to solve these challenges using drug repurposing. Despite the promise of classical machine-learning methods in repurposing cancer drugs and predicting responses, deep-learning methods performed better. This study aims to develop a deep-learning model that predicts cancer drug response based on multi-omics data, drug descriptors, and drug fingerprints and facilitates the repurposing of drugs based on those responses. To reduce multi-omics data's dimensionality, we use autoencoders. As a multi-task learning model, autoencoders are connected to MLPs. We extensively tested our model using three primary datasets: GDSC, CTRP, and CCLE to determine its efficacy. In multiple experiments, our model consistently outperforms existing state-of-the-art methods. Compared to state-of-the-art models, our model achieves an impressive AUPRC of 0.99. Furthermore, in a cross-dataset evaluation, where the model is trained on GDSC and tested on CCLE, it surpasses the performance of three previous works, achieving an AUPRC of 0.72. In conclusion, we presented a deep learning model that outperforms the current state-of-the-art regarding generalization. Using this model, we could assess drug responses and explore drug repurposing, leading to the discovery of novel cancer drugs. Our study highlights the potential for advanced deep learning to advance cancer therapeutic precision.

The Relationship between Diet, Depression, and Alzheimer's Disease: A Narrative Review.

PURPOSE OF REVIEW: This narrative review evaluates the role of diet in the relationship between depression and Alzheimer's disease (AD). RECENT FINDINGS: AD and depression are often comorbid, and depression appears to independently increase the future risk of AD. Evidence suggests diet influences the risk of both conditions directly and indirectly. Diet impacts neurochemical and biological processes that may affect the development and progression of depression and cognitive dysfunction. The dietary components offering the greatest protection against depression and AD are yet to be determined. Current evidence highlights the importance of polyphenolic compounds, folate, B vitamins, and polyunsaturated fatty acids, along with adherence to dietary patterns like the Mediterranean diet, which includes multiple beneficial dietary factors. SUMMARY: The investigation of dietary factors in the prevention of depression and AD is a comparatively young field of research. Comprehensive highly characterised longitudinal datasets and advanced analytical approaches are required to further examine the complex relationship between diet, depression, and AD. There is a critical need for more research in this area to develop effective preventive strategies aimed at maintaining mental and physical health with advancing age.

The McCusker Subjective Cognitive Impairment Inventory (McSCI): a novel measure of perceived cognitive decline.

BACKGROUND: Subjective cognitive decline (SCD), i.e. self/other-reported concerns on one's cognitive functioning without objective evidence of significant decline, is an indicator of dementia risk. There is little consensus on reliability and validity of the available SCD measures. Therefore, introducing a novel and psychometrically sound measure of SCD is timely. OBJECTIVE: The psychometric properties of a new SCD measure, the McCusker Subjective Cognitive Impairment Inventory-Self-Report (McSCI-S), are reported. METHODS: Through review of previously published measures as well as our clinical and research data on people with SCD, we developed a 46-item self-report questionnaire to assess concerns on six cognitive domains, namely, memory, language, orientation, attention and concentration, visuoconstruction abilities and executive function. The McSCI-S was examined in a cohort of 526 participants using factor analysis, item response theory analysis and receiver operating characteristic (ROC) curve. RESULTS: A unidimensional model provided acceptable fit (CFI = 0.94, TLI = 0.94, RMSEA [90% CI] = 0.052 [.049, 0.055], WRMR = 1.45). The McSCI-S internal consistency was excellent (.96). A cut-off score of ≥24 is proposed to identify participants with SCDs. Higher McSCI-S scores were associated with poorer general cognition, episodic verbal memory, executive function and greater memory complaints and depressive scores (P < .001), controlling for age, sex and education. CONCLUSIONS: Excellent reliability and construct validity suggest the McSCI-S estimates SCDs with acceptable accuracy while capturing self-reported concerns for various cognitive domains. The psychometric analysis indicated that this measure can be used in cohort studies as well as on individual, clinical settings to assess SCDs.

Sex and gender differences in cognitive resilience to aging and Alzheimer's disease.

Sex and gender-biological and social constructs-significantly impact the prevalence of protective and risk factors, influencing the burden of Alzheimer's disease (AD; amyloid beta and tau) and other pathologies (e.g., cerebrovascular disease) which ultimately shape cognitive trajectories. Understanding the interplay of these factors is central to understanding resilience and resistance mechanisms explaining maintained cognitive function and reduced pathology accumulation in aging and AD. In this narrative review, the ADDRESS! Special Interest Group (Alzheimer's Association) adopted a multidisciplinary approach to provide the foundations and recommendations for future research into sex- and gender-specific drivers of resilience, including a sex/gender-oriented review of risk factors, genetics, AD and non-AD pathologies, brain structure and function, and animal research. We urge the field to adopt a sex/gender-aware approach to resilience to advance our understanding of the intricate interplay of biological and social determinants and consider sex/gender-specific resilience throughout disease stages. HIGHLIGHTS: Sex differences in resilience to cognitive decline vary by age and cognitive status. Initial evidence supports sex-specific distinctions in brain pathology. Findings suggest sex differences in the impact of pathology on cognition. There is a sex-specific change in resilience in the transition to clinical stages. Gender and sex factors warrant study: modifiable, immune, inflammatory, and vascular.

SPLICE - Streamlining Digital Pathology Image Processing.

Digital pathology and the integration of artificial intelligence (AI) models have revolutionized histopathology, opening new opportunities. With the increasing availability of Whole Slide Images (WSIs), there's a growing demand for efficient retrieval, processing, and analysis of relevant images from vast biomedical archives. However, processing WSIs presents challenges due to their large size and content complexity. Full computer digestion of WSIs is impractical, and processing all patches individually is prohibitively expensive. In this paper, we propose an unsupervised patching algorithm, Sequential Patching Lattice for Image Classification and Enquiry (SPLICE). This novel approach condenses a histopathology WSI into a compact set of representative patches, forming a "collage" of WSI while minimizing redundancy. SPLICE prioritizes patch quality and uniqueness by sequentially analyzing a WSI and selecting nonredundant representative features. We evaluated SPLICE for search and match applications, demonstrating improved accuracy, reduced computation time, and storage requirements compared to existing state-of-the-art methods. As an unsupervised method, SPLICE effectively reduces storage requirements for representing tissue images by 50%. This reduction enables numerous algorithms in computational pathology to operate much more efficiently, paving the way for accelerated adoption of digital pathology.

HGTDR: Advancing drug repurposing with heterogeneous graph transformers.

MOTIVATION: Drug repurposing is a viable solution for reducing the time and cost associated with drug development. However, thus far, the proposed drug repurposing approaches still need to meet expectations. Therefore, it is crucial to offer a systematic approach for drug repurposing to achieve cost savings and enhance human lives. In recent years, using biological network-based methods for drug repurposing has generated promising results. Nevertheless, these methods have limitations. Primarily, the scope of these methods is generally limited concerning the size and variety of data they can effectively handle. Another issue arises from the treatment of heterogeneous data, which needs to be addressed or converted into homogeneous data, leading to a loss of information. A significant drawback is that most of these approaches lack end-to-end functionality, necessitating manual implementation and expert knowledge in certain stages. RESULTS: We propose a new solution, Heterogeneous Graph Transformer for Drug Repurposing (HGTDR), to address the challenges associated with drug repurposing. HGTDR is a three-step approach for knowledge graph-based drug repurposing: (1) constructing a heterogeneous knowledge graph, (2) utilizing a heterogeneous graph transformer network, and (3) computing relationship scores using a fully connected network. By leveraging HGTDR, users gain the ability to manipulate input graphs, extract information from diverse entities, and obtain their desired output. In the evaluation step, we demonstrate that HGTDR performs comparably to previous methods. Furthermore, we review medical studies to validate our method's top 10 drug repurposing suggestions, which have exhibited promising results. We also demonstrated HGTDR's capability to predict other types of relations through numerical and experimental validation, such as drug-protein and disease-protein inter-relations. AVAILABILITY AND IMPLEMENTATION: The source code and data are available at https://github.com/bcb-sut/HGTDR and http://git.dml.ir/BCB/HGTDR.

Minimising warm ischaemia time during robot-assisted partial nephrectomy. A video-based assessment of tumour excision, kidney reconstruction and intermediate time.

INTRODUCTION: Surgical video review is an emerging tool for assessing patient outcomes, especially in complex surgeries such as robot-assisted partial nephrectomy (RAPN). Assessing and measuring warm ischaemia time (WIT) during RAPN by dividing it into the time used for tumour excision time (ExcT), time used for kidney reconstruction time (RecT) and intermediate time (IntT) has not been performed before. This study aimed to analyse the factors that can influence all surgical times and assess their impact on positive surgical margins (PSMs) and complication rates. METHODS: We evaluated 32 surgical video recordings from patients undergoing RAPN and measured WIT, ExcT, RecT and IntT with a stopwatch. Factors such as tumour characteristics and surgeon experience were also recorded. SPSS software was used to identify the predictors for all surgical times and to correlate ExcT with PSM and RecT with complication rate. RESULTS: We recorded a median WIT of 1,048 s (17 min and 28 s). The median of ExcT, RecT and IntT was 398 s (37.1% of WIT), 518 s (46.7% of WIT) and 180 s (16.2% of WIT), respectively. We found a significant correlation (P < 0.001) between R.E.N.A.L. score and all surgical times. No correlation was found between ExcT and PSM (P = 0.488) and between RecT and the probability of developing complications (P = 0.544). CONCLUSION: Tumour morphology influences all surgical times, and surgeon experience influences only ExcT. We observed a short RecT during RAPN though at the cost of increased ExcT, and we believe that improving surgical experience, especially for the excision of more complex tumours, can reduce WIT during RAPN.

Sorghum Grain Polyphenolic Extracts Demonstrate Neuroprotective Effects Related to Alzheimer's Disease in Cellular Assays.

Sorghum grain contains high levels and a diverse profile of polyphenols (PPs), which are antioxidants known to reduce oxidative stress when consumed in the diet. Oxidative stress leading to amyloid-ß (Aß) aggregation, neurotoxicity, and mitochondrial dysfunction is implicated in the pathogenesis of Alzheimer's disease (AD). Thus, PPs have gained attention as possible therapeutic agents for combating AD. This study aimed to (a) quantify the phenolic compounds (PP) and antioxidant capacities in extracts from six different varieties of sorghum grain and (b) investigate whether these PP extracts exhibit any protective effects on human neuroblastoma (BE(2)-M17) cells against Aß- and tau-induced toxicity, Aß aggregation, mitochondrial dysfunction, and reactive oxygen species (ROS) induced by Aß and tert-butyl hydroperoxide (TBHP). PP and antioxidant capacity were quantified using chemical assays. Aß- and tau-induced toxicity was determined using the 3-(4,5-dimenthylthiazol-2-yl)-2,5-dimethyltetrazolium bromide (MTS) assay. The thioflavin T (Th-T) assay assessed anti-Aß aggregation. The dichlorodihydrofluorescein diacetate (DCFDA) assay determined the levels of general ROS and the MitoSOX assay determined the levels of mitochondrial superoxide. Sorghum varieties Shawaya short black-1 and IS1311C possessed the highest levels of total phenolics, total flavonoids, and antioxidant capacity, and sorghum varieties differed significantly in their profile of individual PPs. All extracts significantly increased cell viability compared to the control (minus extract). Variety QL33 (at 2000 µg sorghum flour equivalents/mL) showed the strongest protective effect with a 28% reduction in Aß-toxicity cell death. The extracts of all sorghum varieties significantly reduced Aß aggregation. All extracts except that from variety B923296 demonstrated a significant (p ≤ 0.05) downregulation of Aß-induced and TBHP-induced ROS and mitochondrial superoxide relative to the control (minus extract) in a dose- and variety-dependent manner. We have demonstrated for the first time that sorghum polyphenolic extracts show promising neuroprotective effects against AD, which indicates the potential of sorghum foods to exert a similar beneficial property in the human diet. However, further analysis in other cellular models and in vivo is needed to confirm these effects.

White Matter Hyperintensity in Patients with Sudden Sensorineural Hearing Loss.

OBJECTIVE: To compare white matter hyperintensities (WMHs) on T2-weighted magnetic resonance imaging (MRI) of patients with sudden sensorineural hearing loss (SSNHL) and analyze subpopulations with age-matched controls. METHODS: T2-weighted MRI scans of 150 patients with SSNHL were assessed for WMHs and compared with the data of 148 healthy age-matched adults. Assessments of WMHs included independent grading of deep white matter hyperintensities (DWMHs) and periventricular hyperintensities (PVHs). WMH severity was visually rated using the Fazekas and Mirsen scales by two independent observers. RESULTS: Fazekas grades for PVHs (p < 0.001) and DWMHs (p < 0.001) of SSNHL patients were found to be significantly greater than those of healthy participants. The average Mirsen grades for DWMHs of healthy and SSNHL patients were evaluated to be 0.373 ± 0.550 and 2.140 ± 0.859, respectively. Mirsen grades for DWMHs of SSNHL patients were found to be significantly greater (p < 0.001) than those of healthy participants. The Mirsen scale was found to have higher sensitivity (p < 0.001) than the Fazekas scale in grading PVHs and DWMHs. No significant difference (p = 0.24) was found in specificities between the two scales. CONCLUSIONS: Patients with sudden hearing loss have a much higher likelihood of having periventricular and deep white matter hyperintensities compared to age-matched controls. These findings indicate that sudden hearing loss patients are more likely to have microvascular changes in the brain, which may indicate a vascular and/or migraine origin to sudden sensorineural hearing loss.

A cross-cultural study of the Montreal Cognitive Assessment for people with hearing impairment.

BACKGROUND: Cognitive screening tools enable the detection of cognitive impairment, facilitate timely intervention, inform clinical care, and allow long-term planning. The Montreal Cognitive Assessment for people with hearing impairment (MoCA-H) was developed as a reliable cognitive screening tool for people with hearing loss. Using the same methodology across four languages, this study examined whether cultural or linguistic factors affect the performance of the MoCA-H. METHODS: The current study investigated the performance of the MoCA-H across English, German, French, and Greek language groups (n = 385) controlling for demographic factors known to affect the performance of the MoCA-H. RESULTS: In a multiple regression model accounting for age, sex, and education, cultural-linguistic group accounted for 6.89% of variance in the total MoCA-H score. Differences between languages in mean score of up to 2.6 points were observed. CONCLUSIONS: Cultural or linguistic factors have a clinically significant impact on the performance of the MoCA-H such that optimal performance cut points for identification of cognitive impairment derived in English-speaking populations are likely inappropriate for use in non-English speaking populations. To ensure reliable identification of cognitive impairment, it is essential that locally appropriate performance cut points are established for each translation of the MoCA-H.

Functionally distinct pericyte subsets differently regulate amyloid-ß deposition in patients with Alzheimer's disease.

Although the concept that the blood-brain barrier (BBB) plays an important role in the etiology and pathogenesis of Alzheimer's disease (AD) has become increasingly accepted, little is known yet about how it actually contributes. We and others have recently identified a novel functionally distinct subset of BBB pericytes (PCs). In the present study, we sought to determine whether these PC subsets differentially contribute to AD-associated pathologies by immunohistochemistry and amyloid beta (Aß) peptidomics. We demonstrated that a disease-associated PC subset (PC2) expanded in AD patients compared to age-matched, cognitively unimpaired controls. Surprisingly, we found that this increase in the percentage of PC2 (%PC2) was correlated negatively with BBB breakdown in AD patients, unlike in natural aging or other reported disease conditions. The higher %PC2 in AD patients was also correlated with a lower Aß42 plaque load and a lower Aß42:Aß40 ratio in the brain as determined by immunohistochemistry. Colocalization analysis of multicolor confocal immunofluorescence microscopy images suggests that AD patient with low %PC2 have higher BBB breakdown due to internalization of Aß42 by the physiologically normal PC subset (PC1) and their concomitant cell death leading to more vessels without PCs and increased plaque load. On the contrary, it appears that PC2 can secrete cathepsin D to cleave and degrade Aß built up outside of PC2 into more soluble forms, ultimately contributing to less BBB breakdown and reducing Aß plaque load. Collectively our data shows functionally distinct mechanisms for PC1 and PC2 in high Aß conditions, demonstrating the importance of correctly identifying these populations when investigating the contribution of neurovascular dysfunction to AD pathogenesis.

Notice of retraction: Auraptene-induced cytotoxicity mechanisms in human malignant glioblastoma (U87) cells: role of reactive oxygen species (ROS).

[This retracts the article DOI: 10.17179/excli2019-1136.].

Arginine Vasotocin Directly Regulates Spermatogenesis in Adult Zebrafish (Danio rerio) Testes.

The neuropeptide vasopressin is known for its regulation of osmotic balance in mammals. Arginine vasotocin (AVT) is a non-mammalian homolog of this neuropeptide that is present in fish. Limited information suggested that vasopressin and its homologs may also influence reproductive function. In the present study, we investigated the direct effect of AVT on spermatogenesis, using zebrafish as a model organism. Results demonstrate that AVT and its receptors (avpr1aa, avpr2aa, avpr1ab, avpr2ab, and avpr2l) are expressed in the zebrafish brain and testes. The direct action of AVT on spermatogenesis was investigated using an ex vivo culture of mature zebrafish testes for 7 days. Using histological, morphometric, and biochemical approaches, we observed direct actions of AVT on zebrafish testicular function. AVT treatment directly increased the number of spermatozoa in an androgen-dependent manner, while reducing mitotic cells and the proliferation activity of type B spermatogonia. The observed stimulatory action of AVT on spermiogenesis was blocked by flutamide, an androgen receptor antagonist. The present results support the novel hypothesis that AVT stimulates short-term androgen-dependent spermiogenesis. However, its prolonged presence may lead to diminished spermatogenesis by reducing the proliferation of spermatogonia B, resulting in a diminished turnover of spermatogonia, spermatids, and spermatozoa. The overall findings offer an insight into the physiological significance of vasopressin and its homologs in vertebrates as a contributing factor in the multifactorial regulation of male reproduction.

Botulinum toxin therapy for isolated first dorsal interosseous muscle pain and hypertrophy: A case report.

Botulinum toxin (BTX) injection can be an effective treatment for persistent pain and functional impairment associated with hypertrophy of the first dorsal interosseous muscle. It offers a non-surgical and minimally invasive alternative for those who have failed conservative treatment, showcasing the therapeutic promise of BTX for addressing similar musculoskeletal conditions.

Google Trends Analysis of Otologic Symptom Searches Following COVID-19.

Introduction: COVID-19 infection was accompanied by otologic symptoms, a pattern that was captured early by Google Trends. The objective of this study is to investigate searches for otologic symptoms and identify correlations with the pandemic onset. Materials and Methods: Search interest for otologic symptoms was gathered using Google Trends from two years before and two years following the pandemic start date. A two-tailed Mann-Whitney U test was used to identify significant changes and effect size. Results: In total, search interest for 14 terms was collected, with significant changes identified in 11. Six terms showed increased search interest, with the most significant rises observed for headache (r=0.589, p<0.001), dizziness (r=0.554, p<0.001), and tinnitus (r=0.410, p<0.001). Search interest decreased for five terms, with the most notable declines found in searches for migraine headache (r=0.35, p<0.001) and phonophobia (r=0.22, p=0.002). No significant changes were seen in ear pressure (p=0.142), neck pain (p=0.935), and sudden hearing loss (p=0.863) searches. Conclusion: COVID-19 infection is often accompanied otologic symptoms and holds a diagnostic role. Fluctuating search interest may be attributed to a true increase in cases, media trends, or people's desires to stay informed. Google Trends robustly captured trends in search interest and presented itself as a valuable epidemiological tool.

Application of boosted trees to the prognosis prediction of COVID-19.

Background and Aims: The precise prediction of COVID-19 prognosis remains a clinical challenge. In this regard, early identification of severe cases facilitates the triage and management of COVID-19 cases. The present paper aims to explore the prognosis of COVID-19 patients based on routine laboratory tests taken when patients are admitted. Methods: A data set including 1455 COVID-19 patients (727 male, 728 female) and their routine laboratory tests conducted upon hospital admission, age, Intensive Care Unit (ICU) admission, and outcome were gathered. The data set was randomly split into the train (75% of the data) and test data set (25% of the data). The explainable boosting machine (EBM) and extreme gradient boosting (XGBoost) were used for predicting the mortality and ICU admission of COVID-19 cases. Also, feature importance was extracted using EBM and XGBoost. Results: The EBM and XGBoost achieved 86.38% and 88.56% accuracy in the test data set, respectively. In addition, EBM and XGBoost predicted the ICU admission with an accuracy of 89.37%, and 79.29% in the test data set for COVID-19 patients, respectively. Also, obtained models indicated that aspartate transaminase (AST), lymphocyte, blood urea nitrogen (BUN), and age are the most significant predictors of COVID-19 mortality. Furthermore, the lymphocyte count, AST, and BUN level were the most significant ICU admission predictors of COVID-19 patients. Conclusions: The current study indicated that both EBM and XGBoost could predict the ICU admission and mortality of COVID-19 cases based on routine hematological and clinical chemistry evaluation at the time of admission. Also, based on the results, AST, lymphocyte count, and BUN levels could be used as early predictors of COVID-19 prognosis.

Navigating intellectual property (IP): A comparative analysis of Australian universities' IP policies.

The push towards research commercialisation at universities has highlighted the importance of intellectual property (IP) policies in fostering innovation and guiding and managing research commercialisation activities. This paper undertakes a content analysis of intellectual property policies of all (37) Australian public universities, focusing on policy objectives, definition of IP, ownership of IP created by different creators, and distribution of net commercialisation revenues. It is found that all universities assert ownership over staff-created IP, particularly when related to employment or utilisation of university resources. For students, policies tend to balance their rights with university interests, with nuanced approaches for different types of student participation, but the focus of most policies was on postgraduate students engaging in research activities. While some policies had clear arrangements for IP created by visitors and affiliates and Indigenous cultural and intellectual property (ICIP), about a quarter of policies did not specify arrangements for these groups. Revenue sharing arrangements vary but generally award something between a third to a half of net revenue to creators, to both acknowledge their contribution and incentivise further innovation. Policies included a broad spectrum of objectives, from protecting and commercialising IP to fostering innovation and societal benefit, reflecting varying strategies across the higher education sector. Policies could benefit from further clarity in certain areas such as the rights of students or other creator groups. Research is needed to assess the effectiveness of these policies and their influence on innovation and commercialisation activities.

The AUstralian multidomain Approach to Reduce dementia Risk by prOtecting brain health With lifestyle intervention study (AU-ARROW): A study protocol for a single-blind, multi-site, randomized controlled trial.

INTRODUCTION: The Finnish Geriatric Intervention Study (FINGER) led to the global dementia risk reduction initiative: World-Wide FINGERS (WW-FINGERS). As part of WW-FINGERS, the Australian AU-ARROW study mirrors aspects of FINGER, as well as US-POINTER. METHOD: AU-ARROW is a randomized, single-blind, multisite, 2-year clinical trial (n = 600; aged 55-79). The multimodal lifestyle intervention group will engage in aerobic exercise, resistance training and stretching, dietary advice to encourage MIND diet adherence, BrainHQ cognitive training, and medical monitoring and health education. The Health Education and Coaching group will receive occasional health education sessions. The primary outcome measure is the change in a global composite cognitive score. Extra value will emanate from blood biomarker analysis, positron emission tomography (PET) imaging, brain magnetic resonance imaging (MRI), and retinal biomarker tests. DISCUSSION: The finalized AU-ARROW protocol is expected to allow development of an evidence-based innovative treatment plan to reduce cognitive decline and dementia risk, and effective transfer of research outcomes into Australian health policy. Highlights: Study protocol for a single-blind, randomized controlled trial, the AU-ARROW Study.The AU-ARROW Study is a member of the World-Wide FINGERS (WW-FINGERS) initiative.AU-ARROW's primary outcome measure is change in a global composite cognitive score.Extra significance from amyloid PET imaging, brain MRI, and retinal biomarker tests.Leading to development of an innovative treatment plan to reduce cognitive decline.