The Relationship between Gut Microbiome and Cognition in Older Australians

Ageing is associated with changes in biological processes, including reductions in cognitive functions and gut microbiome diversity. However, not much is known about the relationship between cognition and the microbiome with increasing age. Therefore, we examined the relationship between the gut microbiome and cognition in 69 healthy participants aged 60–75 years. The gut microbiome was analysed with the 16S rRNA sequencing method. The cognitive assessment included the Cognitive Drug Research computerised assessment battery, which produced five cognitive factors corresponding to ‘Quality of Episodic Secondary Memory’, ‘Quality of Working Memory’, ‘Continuity of Attention, ‘Speed of Memory’ and ‘Power of Concentration’. Multiple linear regression showed that the bacterial family Carnobacteriaceae explained 9% of the variance in predicting Quality of Episodic Secondary Memory. Alcaligenaceae and Clostridiaceae explained 15% of the variance in predicting Quality of Working Memory; Bacteroidaceae, Barnesiellaceae, Rikenellaceae and Gemellaceae explained 11% of the variance in Power of Concentration. The present study provides specific evidence of a relationship between specific families of bacteria and different domains of cognition.

Innate Memory Reprogramming by Gold Nanoparticles Depends on the Microbial Agents That Induce Memory

Innate immune memory, the ability of innate cells to react in a more protective way to secondary challenges, is induced by exposure to infectious and other exogeous and endogenous agents. Engineered nanoparticles are particulate exogenous agents that, as such, could trigger an inflammatory reaction in monocytes and macrophages and could therefore be also able to induce innate memory. Here, we have evaluated the capacity of engineered gold nanoparticles (AuNPs) to induce a memory response or to modulate the memory responses induced by microbial agents. Microbial agents used were in soluble vs. particulate form (MDP and the gram-positive bacteria Staphylococcus aureus; β-glucan and the β-glucan-producing fungi C. albicans), and as whole microrganisms that were either killed (S. aureus, C. albicans) or viable (the gram-negative bacteria Helicobacter pylori). The memory response was assessed in vitro, by exposing human primary monocytes from 2-7 individual donors to microbial agents with or without AuNPs (primary response), then resting them for 6 days to allow return to baseline, and eventually challenging them with LPS (secondary memory response). Primary and memory responses were tested as production of the innate/inflammatory cytokine TNFα and other inflammatory and anti-inflammatory factors. While inactive on the response induced by soluble microbial stimuli (muramyl dipeptide -MDP-, β-glucan), AuNPs partially reduced the primary response induced by whole microorganisms. AuNPs were also unable to directly induce a memory response but could modulate stimulus-induced memory in a circumscribed fashion, limited to some agents and some cytokines. Thus, the MDP-induced tolerance in terms of TNFα production was further exacerbated by co-priming with AuNPs, resulting in a less inflammatory memory response. Conversely, the H. pylori-induced tolerance was downregulated by AuNPs only relative to the anti-inflammatory cytokine IL-10, which would lead to an overall more inflammatory memory response. These effects of AuNPs may depend on a differential interaction/association between the reactive particle surfaces and the microbial components and agents, which may lead to a change in the exposure profiles. As a general observation, however, the donor-to-donor variability in memory response profiles and reactivity to AuNPs was substantial, suggesting that innate memory depends on the individual history of exposures.

Remembering

This chapter makes the case for understanding memory in terms of qualitatively different codes represented by active processes, as opposed to such memory systems as episodic and semantic memory. A distinction is made between primary memory (PM), viewed as active conscious processing, and secondary memory (SM), viewed as the long-term representations of events and knowledge. The notion that PM involves attention paid to the information held in mind is discussed in light of current views of working memory. SM is described in terms of a hierarchically organized set of analytic representations running from specific episodes to context-free knowledge, as an alternative description to Tulving’s account in terms of separate episodic and semantic systems. The role of the external context in supporting retrieval is emphasized, and also the role of executive processes in enabling self-initiated activities when such environmental support is absent. Following previous researchers, the chapter endorses the notion of remembering as a set of active analytic operations, and stresses the similarity between the processes of perceiving and remembering. These ideas are illustrated by empirical examples.

From Short-term Memory to Working Memory

The concept of primary memory (PM) in the levels-of-processing (LOP) framework is described and illustrated. The history of the short-term/long-term memory (STM/LTM) distinction is reviewed. Early studies of STM in the Craik laboratory are described, including work on dichotic listening, the negative recency effect, and the surprising finding of long-lasting auditory information in STM. The distinction between PM and secondary memory is reviewed, and their respective roles in short-term retention discussed. Some experiments on release from proactive interference are described. The theoretical evolution of the construct of PM to that of working memory (WM) is described. The proposal that WM is equivalent to “attention paid to information in conscious awareness” is evaluated. It is argued that PM and WM are not separate entities, but are on a descriptive continuum. Further topics include the role of secondary memory in WM, and the possibility of LOP effects in WM (explored in experiments carried out by Craik and Nathan Rose). Further topics include a consideration of WM as a set of separable abilities, hierarchical views of WM, and a final integrated view of short-term retention.

Benson’s Disease or Posterior Cortical Atrophy, Revisited

Background: D. Frank Benson and colleagues first described the clinical and neuropathological features of posterior cortical atrophy (PCA) from patients in the UCLA Neurobehavior Program. Objective: We reviewed the Program’s subsequent clinical experience with PCA, and its potential for clarifying this relatively rare syndrome in comparison to the accumulated literature on PCA. Methods: Using the original criteria derived from this clinic, 65 patients with neuroimaging-supported PCA were diagnosed between 1995 and 2020. Results: On presentation, most have visual localization complaints and related visuospatial symptoms, but nearly half had memory complaints followed by symptoms of depression. Neurobehavioral testing showed predominant difficulty with visuospatial constructions, Gerstmann’s syndrome, and Balint’s syndrome, but also impaired memory and naming. On retrospective application of the current Consensus Criteria for PCA, 59 (91%) met PCA criteria with a modification allowing for “significantly greater visuospatial over memory and naming deficits.” There were 37 deaths (56.9%) with the median overall survival of 10.3 years (95% CI: 9.6–13.6 years), consistent with a slow neurodegenerative disorder in most patients. Conclusion: Together, these findings recommend modifying the PCA criteria for “relatively spared” memory, language, and behavior to include secondary memory and naming difficulty and depression, with increased emphasis on the presence of Gerstmann’s and Balint’s syndromes.

Analysis of C9orf72 Intermediate Alleles in a Retrospective Cohort of Neurological Patients: Risk Factors for Alzheimer’s Disease?

Background: C9orf72 hexanucleotide GGGGCC (G4C2) large repeat expansions within the first intron of the gene are a major cause of familial frontotemporal dementia, but also of apparently sporadic cases. Alleles with > 30 repeats are often considered pathogenic, but the repeat length threshold is still undefined. It is also unclear if C9orf72 intermediate alleles (9–30 repeats) have clinically significant effects. Objectives: We correlated the presence of C9orf72 intermediate alleles with clinical diagnoses in a perspective cohort referred to a secondary memory clinic. Methods: All samples were genotyped with AmplideXPCR/CE C9ORF72 Kit (Asuragen, Inc), an optimized C9orf72 PCR amplification reagent. Results: We showed that in patients with Alzheimer’s disease (AD) the frequency of the intermediate repeat allele was significantly increased versus controls (34/54, 63%AD versus 16/39, 41%CTRLs, *p = 0.01, OR 2.91 CI 95%1.230–6.077), whereas no significant differences (p > 0.05) were observed when comparing all other dementias with non-demented individuals. Conclusion: Our findings suggest that C9orf72 intermediate repeat units may represent a genetic risk factor, contributing to the occurrence of AD. Nevertheless, further longitudinal studies, including larger cohort of subjects with intermediate alleles with long-term follow-up, would be needed to confirm these results.

A Comparative Analysis of Disk Scheduling Algorithms

In an operating system, disk scheduling is the process of managing the I/O request to the secondary storage devices such as hard disk. The speed of the processor and primary memory has increased in a rapid way than the secondary storage. Seek time is the important factor in an operating system to get the best access time. For the better performance, speedy servicing of I/O request for secondary memory is very important. The goal of the disk-scheduling algorithm is to minimize the response time and maximize throughput of the system. This work analyzed and compared various basic disk scheduling techniques like First Come First Serve (FCFS), Shortest Seek Time First (SSTF), SCAN, LOOK, Circular SCAN (C-SCAN) and Circular LOOK (C-LOOK) along with the corresponding seek time. From the comparative analysis, the result show that C-LOOK algorithm give the least head movement and seek time in different cases as compared to other algorithm. Therefore, it maximizes the throughput for the storage devices.

Optimize Prime/Boost Vaccine Strategies: Trained Immunity as a New Player in the Game

Most vaccines require multiple doses to induce long-lasting protective immunity in a high frequency of vaccines, and to ensure strong both individual and herd immunity. Repetitive immunogenic stimulations not only increase the intensity and durability of adaptive immunity, but also influence its quality. Several vaccine parameters are known to influence adaptive immune responses, including notably the number of immunizations, the delay between them, and the delivery sequence of different recombinant vaccine vectors. Furthermore, the initial effector innate immune response is key to activate and modulate B and T cell responses. Optimization of homologous and heterologous prime/boost vaccination strategies requires a thorough understanding of how vaccination history affects memory B and T cell characteristics. This requires deeper knowledge of how innate cells respond to multiple vaccine encounters. Here, we review how innate cells, more particularly those of the myeloid lineage, sense and respond differently to a 1st and a 2nd vaccine dose, both in an extrinsic and intrinsic manner. On one hand, the presence of primary specific antibodies and memory T cells, whose critical properties change with time after priming, provides a distinct environment for innate cells at the time of re-vaccination. On the other hand, innate cells themselves can exert enhanced intrinsic antimicrobial functions, long after initial stimulation, which is referred to as trained immunity. We discuss the potential of trained innate cells to be game-changers in prime/boost vaccine strategies. Their increased functionality in antigen uptake, antigen presentation, migration, and as cytokine producers, could indeed improve the restimulation of primary memory B and T cells and their differentiation into potent secondary memory cells in response to the boost. A better understanding of trained immunity mechanisms will be highly valuable for harnessing the full potential of trained innate cells, to optimize immunization strategies.

Raptor: A fast and space-efficient pre-filter for querying very large collections of nucleotide sequences

We present Raptor, a tool for approximately searching many queries in large collections of nucleotide sequences. In comparison with similar tools like Mantis and COBS, Raptor is 12-144 times faster and uses up to 30 times less memory. Raptor uses winnowing minimizers to define a set of representative k-mers, an extension of the Interleaved Bloom Filters (IBF) as a set membership data structure, and probabilistic thresholding for minimizers. Our approach allows compression and a partitioning of the IBF to enable the effective use of secondary memory.

Resource management for model learning at entity level

Many current and future applications plan to provide entity-specific predictions. These range from individualized healthcare applications to user-specific purchase recommendations. In our previous stream-based work on Amazon review data, we could show that error-weighted ensembles that combine entity-centric classifiers, which are only trained on reviews of one particular product (entity), and entity-ignorant classifiers, which are trained on all reviews irrespective of the product, can improve prediction quality. This came at the cost of storing multiple entity-centric models in primary memory, many of which would never be used again as their entities would not receive future instances in the stream. To overcome this drawback and make entity-centric learning viable in these scenarios, we investigated two different methods of reducing the primary memory requirement of our entity-centric approach. Our first method uses the lossy counting algorithm for data streams to identify entities whose instances make up a certain percentage of the total data stream within an error-margin. We then store all models which do not fulfil this requirement in secondary memory, from which they can be retrieved in case future instances belonging to them should arrive later in the stream. The second method replaces entity-centric models with a much more naive model which only stores the past labels and predicts the majority label seen so far. We applied our methods on the previously used Amazon data sets which contained up to 1.4M reviews and added two subsets of the Yelp data set which contain up to 4.2M reviews. Both methods were successful in reducing the primary memory requirements while still outperforming an entity-ignorant model.