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Artificial intelligence (AI)-based diagnostic algorithms have achieved ambitious aims through automated image pattern recognition. For neurological disorders, this includes neurodegeneration and inflammation. Scalable imaging technology for big data in neurology is optical coherence tomography (OCT). We highlight that OCT changes observed in the retina, as a window to the brain, are small, requiring rigorous quality control pipelines. There are existing tools for this purpose. Firstly, there are human-led validated consensus quality control criteria (OSCAR-IB) for OCT. Secondly, these criteria are embedded into OCT reporting guidelines (APOSTEL). The use of the described annotation of failed OCT scans advances machine learning. This is illustrated through the present review of the advantages and disadvantages of AI-based applications to OCT data. The neurological conditions reviewed here for the use of big data include Alzheimer disease, stroke, multiple sclerosis (MS), Parkinson disease, and epilepsy. It is noted that while big data is relevant for AI, ownership is complex. For this reason, we also reached out to involve representatives from patient organizations and the public domain in addition to clinical and research centers. The evidence reviewed can be grouped in a five-point expansion of the OSCAR-IB criteria to embrace AI (OSCAR-AI). The review concludes by specific recommendations on how this can be achieved practically and in compliance with existing guidelines.

Land use is recognized to impact soil geochemistry on the centennial to millennial timescale, with implications for the distribution and stability of soil organic carbon (SOC). Young volcanic soils in tropical areas are subject to much faster pedogenesis, noticeable already on the centennial or even decadal timescale. As land use is a recognized factor for soil formation, it is thus conceivable that even relatively recent land use conversion in such areas would already bear a significant impact on the resulting formed soils., e.g., in terms of content of pedogenic oxides. Very scarce observational evidence exists, so such indirect implications of land use on SOC cycling are largely unknown. We here investigated SOC fractions, substrate-specific mineralization (SOC or added plant residue), and net priming of SOC as a function of forest or agricultural land use on Indonesian volcanic soils. The content of oxalate-extracted Al (Alo) correlated well with organic carbon (OC) associated with sand-sized aggregates, particularly in the subsoil. The proportion of SOC in sand-sized ultrasonication-resistant (400 J mL−1) aggregates was also higher in agricultural land use compared to pine forest land use, and a likewise contrast existed for Alo. These combined observations suggest that enhanced formation of Al (hydr)oxides promoted aggregation and physical occlusion of OC. This was, importantly, also consistent with a relatively lesser degradability of SOC in the agricultural sites, though we found no likewise difference in degradability of added 13C-labeled ryegrass or in native SOC priming between the pine forest and agricultural land uses. We expected that amorphous Al content under agricultural land use would mainly have promoted mineral association of SOC compared to under pine forest land use but found no indications for this. Improved small-scale aggregation of tropical Andosols caused by conversion to agriculture and high carbon input via organic fertilizer may thus partially counter the otherwise expectable decline of SOC stocks following cultivation. Such indirect land use effects on the SOC balance appeared relevant for correct interpretation and prediction of the long-term C balance of (agro)ecosystems with soil subject to intense development, like the here-studied tropical Andosols.

Erika CS Künstler,1,2 Peter Bublak,1 Kathrin Finke,1 Nicolas Koranyi,1 Marie Meinhard,1 Matthias Schwab,1,2 Sven Rupprecht1,2 1Department of Neurology, Jena University Hospital, Jena, Germany; 2Interdisciplinary Centre for Sleep and Ventilatory Medicine, Jena University Hospital, Jena, GermanyCorrespondence: Erika CS Künstler, Department of Neurology, Jena University Hospital, Am Klinikum 1, Jena, 07747, Germany, Tel +49 3641 9323525, Email Erika.Kuenstler@med.uni-jena.deStudy Objectives: Persistent insomnia disorder (pID) is linked to neurocognitive decline and increased risk of Alzheimer’s Disease (AD) in later life. However, research in this field often utilizes self-reported sleep quality data - which may be biased by sleep misperception - or uses extensive neurocognitive test batteries - which are often not feasible in clinical settings. This study therefore aims to assess whether a simple screening tool could uncover a specific pattern of cognitive changes in pID patients, and whether these relate to objective aspect(s) of sleep quality.Methods: Neurocognitive performance (Montreal Cognitive Assessment; MoCA), anxiety/depression severity, and subjective sleep quality (Pittsburgh Sleep Quality Index: PSQI; Insomnia Severity Index: ISI) data were collected from 22 middle-aged pID patients and 22 good-sleepers. Patients underwent overnight polysomnography.Results: Compared to good-sleepers, patients had lower overall cognitive performance (average: 24.6 versus 26.3 points, Mann–Whitney U = 136.5, p = < 0.006), with deficits in clock drawing and verbal abstraction. In patients, poorer overall cognitive performance correlated with reduced subjective sleep quality (PSQI: r(42) = − 0.47, p = 0.001; and ISI: r(42) = − 0.43, p = 0.004), reduced objective sleep quality (lower sleep efficiency: r(20) = 0.59, p = 0.004 and less REM-sleep: r(20) = 0.52, p = 0.013; and increased sleep latency: r(20) = − 0.57, p = 0.005 and time awake: r(20) = − 0.59, p = 0.004). Cognitive performance was not related to anxiety/depression scores.Conclusion: Using a simple neurocognitive screening tool, we found that pID patients showed cognitive deficiencies that related to both subjective/self-reported and objective/polysomnographic measures of sleep quality. Furthermore, these cognitive changes resembled those seen in preclinical non-amnestic AD, and thus could indicate incumbent neurodegenerative processes in pID. Interestingly, increased REM-sleep was correlated with better cognitive performance. However, whether REM-sleep is protective against neurodegeneration requires further investigation.Keywords: insomnia, sleep, neurodegeneration, Alzheimer’s disease, polysomnography, cognitive screening

Low-protein diets promote metabolic health in rodents and humans, and the benefits of low-protein diets are recapitulated by specifically reducing dietary levels of the three branched-chain amino acids (BCAAs), leucine, isoleucine, and valine. Here, we demonstrate that each BCAA has distinct metabolic effects. A low isoleucine diet reprograms liver and adipose metabolism, increasing hepatic insulin sensitivity and ketogenesis and increasing energy expenditure, activating the FGF21-UCP1 axis. Reducing valine induces similar but more modest metabolic effects, whereas these effects are absent with low leucine. Reducing isoleucine or valine rapidly restores metabolic health to diet-induced obese mice. Finally, we demonstrate that variation in dietary isoleucine levels helps explain body mass index differences in humans. Our results reveal isoleucine as a key regulator of metabolic health and the adverse metabolic response to dietary BCAAs and suggest reducing dietary isoleucine as a new approach to treating and preventing obesity and diabetes.