Notes

Unleashing the reinforcement-learning circuits of the orbitofrontal cortex.
LASSI-L is a novel neuropsychological test specifically designed for the early diagnosis of Alzheimer's disease (AD) based on semantic interference.

To examine the cognitive and neural underpinnings of the failure to recover from proactive semantic and retroactive semantic interference.

One hundred and fifty-five patients consulting for memory loss were included. Patients underwent neuropsychological assessment, including the LASSI-L, and FDG-PET imaging. They were categorized as subjective memory complaints (SMC) (n=32), pre-mild cognitive impairment (MCI) due to AD (Pre-MCI) (n=39), MCI due to AD (MCI-AD) (n=71), and MCI without evidence of neurodegeneration (MCI-NN) (n=13). Voxel-based brain mapping and metabolic network connectivity analyses were conducted.

A significant group effect was found for all the LASSI-L scores. LASSI-L scores measuring failure to recover from proactive semantic interference and retroactive semantic interference were predicted by other neuropsychological tests with a precse findings support the role of the LASSI-L in the detection, monitoring and outcome prediction during the early stages of AD.Advances in biomarkers, genetics, and other data used as dementia risk evidence (DRE) are increasingly informing clinical diagnosis and management. The purpose of this Mini-Forum is to provide a solutions-based discussion of the ethical and legal gaps and practical questions about how to use and communicate these data. Investigators often use DRE in research. When participants ask for their personal results, investigators have concerns. Will data that was intended to study groups be valid for individuals? Will sharing data cause distress? Debates around sharing DRE became heated when blood-based amyloid tests and amyloid reducing drugs appeared poised to enable clinicians easily to identify people with elevated brain amyloid and reduce it with a drug. Such an approach would transform the traditional role of DRE from investigational to foundational; however, then the high costs, uncertain clinical benefits and risks of the therapy led to an urgent need for education to support clinical decision making. Further complicating DRE use are direct to consumer genetic testing and increasingly available biomarker testing. Withholding DRE becomes less feasible and public education around responsible use and understanding become vital. A critical answer to these legal and ethical issues is supporting education that clearly delineates known risks, benefits, and gaps in knowledge, and communication to promote understanding among researchers, clinicians, patients, and all stakeholders. This paper provides an overview and identifies general concepts and resource documents that support more informed discussions for individuals and interdisciplinary groups.
As an acetylcholinesterase inhibitor (AChEI), Huperzine-A (Hup-A) is marketed for treatment of mild to moderate Alzheimer's disease (AD) for decades in China. However, Hup-A causes some side effects. To search for new analogs or derivatives of Hup-A, we produced five Lycopodium alkaloids and two analogues by chemical synthesis Lyconadins A-E, H-R-NOB, and 2JY-OBZ4.

To systematically evaluate the therapeutic effects of the seven compounds on AD cell models.

We assessed the effects of the seven compounds on cell viability via CCK-8 kit and used HEK293-hTau cells and N2a-hAPP cells as AD cell models to evaluate their potential therapeutic effects. We examined their effects on cholinesterase activity by employing the mice primary neuron.

All compounds did not affect cell viability; in addition, Lyconadin A and 2JY-OBZ4 particularly increased cell viability. Lyconadin D and Lyconadin E restored tau phosphorylation at Thr231, and H-R-NOB and 2JY-OBZ4 restored tau phosphorylation at Thr231 and Ser396 in GSK-3β-transfected HEK293-hTau cells. 2JY-OBZ4 decreased the level of PP2Ac-pY307 and increased the level of PP2Ac-mL309, supporting that 2JY-OBZ4 may activate PP2A. Lyconadin B, Lyconadin D, Lyconadin E, H-R-NOB, and 2JY-OBZ4 increased sAβPPα level in N2a-hAPP cells. 2JY-OBZ4 decreased the levels of BACE1 and sAβPPβ, thereby reduced Aβ production. GDC-6036 solubility dmso Seven compounds exhibited weaker AChE activity inhibition efficiency than Hup-A. Among them, 2JY-OBZ4 showed the strongest AChE inhibition activity with an inhibition rate of 17% at 10μM.

Among the seven Lycopodium compounds, 2JY-OBZ4 showed the most expected effects on promoting cell viability, downregulating tau hyperphosphorylation, and Aβ production and inhibiting AChE in AD.
Among the seven Lycopodium compounds, 2JY-OBZ4 showed the most expected effects on promoting cell viability, downregulating tau hyperphosphorylation, and Aβ production and inhibiting AChE in AD.
DNA methylation is expected to become a kind of new diagnosis and treatment method of Alzheimer's disease (AD). Neuroinflammation- and immune-related pathways represent one of the major genetic risk factors for AD.

We aimed to investigate DNA methylation levels of 7 key immunologic-related genes in peripheral blood and appraise their applicability in the diagnosis of AD.

Methylation levels were obtained from 222 participants (101 AD, 72 MCI, 49 non-cognitively impaired controls). Logistic regression models for diagnosing AD were established after least absolute shrinkage and selection operator (LASSO) and best subset selection (BSS), evaluated by respondent working curve and decision curve analysis for sensitivity.

Six differentially methylated positions (DMPs) in the MCI group and 64 in the AD group were found, respectively. Among them, there were 2 DMPs in the MCI group and 30 DMPs in the AD group independent of age, gender, and APOE4 carriers (p <  0.05). AD diagnostic prediction models differentiated AD from normal controls both in a training dataset (LASSO 8 markers, including methylation levels at ABCA7 1040077, CNR1 88166293, CX3CR1 39322324, LRRK2 40618505, LRRK2 40618493, NGFR 49496745, TARDBP 11070956, TARDBP 11070840 area under the curve [AUC] = 0.81; BSS 2 markers, including methylation levels at ABCA7 1040077 and CX3CR1 39322324, AUC = 0.80) and a testing dataset (AUC = 0.84, AUC = 0.82, respectively).

Our work indicated that methylation levels of 7 key immunologic-related genes (ABCA7, CNR1, CX3CR1, CSF1R, LRRK2, NGFR, and TARDBP) in peripheral blood was altered in AD and the models including methylation of immunologic-related genes biomarkers improved prediction of AD.
Our work indicated that methylation levels of 7 key immunologic-related genes (ABCA7, CNR1, CX3CR1, CSF1R, LRRK2, NGFR, and TARDBP) in peripheral blood was altered in AD and the models including methylation of immunologic-related genes biomarkers improved prediction of AD.Although the cause(s) of Alzheimer's disease in the majority of cases remains elusive, it has long been associated with hypertension. In animal models of the disease, hypertension has been shown to exacerbate Alzheimer-like pathology and behavior, while in humans, hypertension during mid-life increases the risk of developing the disease later in life. Unfortunately, once individuals are diagnosed with the disease, there are few therapeutic options available. There is neither an effective symptomatic treatment, one that treats the debilitating cognitive and memory deficits, nor, more importantly, a neuroprotective treatment, one that stops the relentless progression of the pathology. Further, there is no specific preventative treatment that offsets the onset of the disease. A key factor or clue in this quest for an effective preventative and therapeutic treatment may lie in the contribution of hypertension to the disease. In this review, we explore the idea that photobiomodulation, the application of specific wavelengths of light onto body tissues, can reduce the neuropathology and behavioral deficits in Alzheimer's disease by controlling hypertension. We suggest that treatment with photobiomodulation can be an effective preventative and therapeutic option for this neurodegenerative disease.
Diagnostic tests, such as amyloid-β positron emission tomography (PET) scans, can increase appropriate therapeutic management for the underlying causes of cognitive decline. To evaluate the full utility of this diagnostic tool, information is needed on whether results from amyloid-β PET scans influence care-partner outcomes.

This study examines the extent to which previous disclosure of elevated amyloid (suggestive of Alzheimer's disease (AD) etiology) versus not-elevated amyloid (not suggestive of AD etiology) is associated with changes in care-partner wellbeing.

The study used data derived from a national longitudinal survey of Medicare beneficiaries (n = 921) with mild cognitive impairment (MCI) or dementia and their care-partners. Care-partner wellbeing outcomes included depressive symptoms (PHQ-8), subjective burden (4-item Zarit burden score), and a 3-item measure of loneliness. Change was measured between 4 (Time 1) and 18 (Time 2) months after receiving the scan results. Adjusted linear regression models regressed change (Time 2-Time 1) in each outcome on scan result.

Care-partners were primarily white, non-Hispanic, college-educated, and married to the care recipient. Elevated amyloid was not associated with statistically significant Time 1 differences in outcomes or with statistically significant changes in depressive symptoms 0.22 (-0.18, 0.61), subjective burden 0.36 (-0.01, 0.73), or loneliness 0.15 (-0.01, 0.32) for care-partners from one time point to another.

Given advances in AD biomarker testing, future research in more diverse samples is needed to understand the influence of scan results on care-partner wellbeing across populations.
Given advances in AD biomarker testing, future research in more diverse samples is needed to understand the influence of scan results on care-partner wellbeing across populations.
The progression of Alzheimer's disease (AD) varies in different patients at different stages, which makes predicting the time of disease conversions challenging.

We established an algorithm by leveraging machine learning techniques to predict the probability of the conversion time to next stage for different subjects during a given period.

Firstly, we used Kaplan-Meier (KM) estimation to get the transition curves of different AD stages, and calculated Log-rank statistics to test whether the progression rate between different stages was identical. This quantitatively confirmed the progression rates known in the literature. Then, we developed an approach based on deep learning model, DeepSurv, to predict the probabilities of time-to-conversion. Finally, to help interpret the deep learning model in our approach, we identified important variables contributing the most to the DeepSurv prediction, whose significance were validated with the analysis of variance (ANOVA).

Our machine learning approach predicted the time to conversion with a high accuracy. For each of the different stages, the concordance index (CI) of our approach was at least 86%, and the integrated Brier score (IBS) was less than 0.1. To facilitate interpretability of the prediction results, our approach identified the top 10 variables for each disease conversion scenario, which were clinicopathologically meaningful, and most of them were also statistically significant.

Our study has the potential to provide individualized prediction for future time course of AD conversions years before their actual occurrence, thus facilitating personalized prevention and intervention strategies to slow down the progression of AD.
Our study has the potential to provide individualized prediction for future time course of AD conversions years before their actual occurrence, thus facilitating personalized prevention and intervention strategies to slow down the progression of AD.
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