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Introduction: Simple markers are required to recognize older adults at higher risk for neurodegenerative disease. Mild behavioural impairment (MBI) and plasma β-amyloid (Aβ) have been independently implicated in the development of incident cognitive decline and dementia. Here we studied the associations between MBI and plasma Aβ42/Aβ40. Methods: Participants with normal cognition (n = 86) or mild cognitive impairment (n = 53) were selected from the Alzheimer’s Disease Neuroimaging Initiative. MBI scores were derived from Neuropsychiatric Inventory items. Plasma Aβ42/Aβ40 ratios were assayed using mass spectrometry. Linear regressions were fitted to assess the association between MBI total score as well as MBI domain scores with plasma Aβ42/Aβ40. Results: Lower plasma Aβ42/Aβ40 was associated with higher MBI total score ( p = 0.04) and greater affective dysregulation ( p = 0.04), but not with impaired drive/motivation ( p = 0.095) or impulse dyscontrol ( p = 0.29) MBI domains. Conclusion: In persons with normal cognition or mild cognitive impairment, MBI was associated with low plasma Aβ42/Aβ40. Incorporating MBI into case detection may help capture preclinical and prodromal Alzheimer’s disease.

Neural networks based on memristive devices [1][2][3] have shown potential in substantially improving throughput and energy efficiency for machine learning [4] and artificial intelligence [5], especially in edge applications. [6][7][8][9][10][11][12][13][14][15][16][17][18][19] Because training a neural network model from scratch is very costly, it is impractical to do it individually on billions of memristive neural networks distributed at the edge. A practical approach would be to download the synaptic weights obtained from the cloud training and program them directly into memristors for the commercialization of edge applications (Figure 1a). Some posttuning in memristor conductance to adapt local situations may follow afterward or during applications. Therefore, a critical requirement on memristors for neural network applications is a high-precision programming ability to guarantee uniform and accurate performance across a massive number of memristive networks. [20][21][22][23][24][25][26] That translates into the requirement of many distinguishable conductance levels on each memristive device, not just lab-made devices but more importantly, devices fabricated in foundries. High precision memristors also benefit other neural network applications, such as training and scientific computing. [23,27] Here we report over 2048 conductance levels, the largest number among all types of memories ever reported, achieved with memristors in fully integrated chips with 256 ´ 256 memristor arrays monolithically integrated on CMOS circuits in a standard foundry. We have unearthed the underlying physics that previously limited the number of achievable conductance levels in memristors and developed electrical operation protocols to circumvent such limitations. These results reveal insights into the fundamental understanding of the microscopic picture of memristive switching and provide approaches to enable high-precision memristors for various applications.Memristive switching devices are known for their relatively large dynamical range of conductance, which can potentially lead to a large number of discrete conductance levels. However, the highest number reported to date has been no more than two hundred. [20]

[1] This study reports the first high and low molecular weight measurements of dissolved organic nitrogen (DON) in size-fractionated atmospheric particles. The variations in concentration of nitrogen species corresponded to varying sources and weather conditions. The results indicate that continental, local, and marine origins are the key factors controlling the particle size distribution of inorganic and organic nitrogen species. For dissolved inorganic nitrogen and DON, relatively high concentrations and fine-mode particle (particle diameter <1 mm) enrichment were significantly affected by continental and locally derived sources, which were mainly attributable to anthropogenic activities. However, the coarse/fine ratios indicate that DON was derived from a coarse particle (particle diameter >1 mm) source that may be sea salt particles. To investigate the possible sources of DON, an ultrafiltration method was used to separate DON into high (HMW) and low (LMW) molecular weight categories. The results indicate that HMW-DON and LMW-DON contributed 57 ± 9% and 43 ± 9%, respectively, to the total DON concentration. Correlations and positive matrix factorization analysis of HMW-DON and LMW-DON levels with major and non-sea-salt ions indicated that HMW-DON and LMW-DON in coarse particles may be generated from continental soil dust and sea spray, respectively, whereas, in fine particles, DON may originate from aerosols derived from combustion processes. The annual fluxes of HMW-DON and LMW-DON were estimated to be 11.0 and 11.3 mmol m −2 yr −1 , respectively. Consequently, the inputs of HMW-DON and LMW-DON appear to make equal contributions to DON in aerosols over the studied coastal area.

[1] We analyzed 156 aerosol samples, including 10 dust storm samples, collected from January to December 2005 at a coastal site on the southern East China Sea at Keelung city, Taiwan, for water-soluble major ions, nitrogen, and phosphorus species. In addition, 4-d back trajectories of air masses arriving daily at the sampling site were calculated to determine the potential aerosol source regions. The obtained concentrations of major ions indicate that a continental source was dominant from January to May and from November to December, a local source during July, and an oceanic source from September to October. The measured atmospheric concentrations of nitrogen and phosphorus species show clear seasonal variations and correspond to the different sources and weather conditions. During the dust storm period, dissolved inorganic nitrogen (DIN) and dissolved inorganic phosphorus (DIP) concentrations showed statistically significant linear relationships with the amount of aerosol particles, suggesting a continental source. The results of a factor analysis of combined major ions and DIN and DIP indicate that crustal sources, marine sources, and combustion sources are the three major controlling factors during the non-dust-storm period. Natural and anthropogenic land sources and marine sources are the most influential factors in terms of the distribution of aerosol during the dust storm period. A strong correlation was also found between DIN and DIP, indicating similar sources and transportation mechanisms. The results of flux calculations indicate that aerosols derived from dust storms and biomass burning provide 12 ± 8% and 46 ± 36% of total DIN and 16 ± 10% and 46 ± 38% of total DIP, respectively. Consequently, the inputs of aerosol derived from biomass burning may be an important source of nitrogen and phosphorus in aerosols over the East China Sea.

The results of an extensive study of 47 azaarenes in the Liverpool urban atmosphere through the period from September 1994 to March 1996 are reported. Total suspended particles and size-fractionated particles were collected by high volume sampling techniques and cascade impactor sampling techniques. The overall mean ∑azaarene concentration was 2.80 ng m -3 . The monthly mean ∑azaarene concentrations show a very strong seasonal variation in which the maximum concentration occurred in the winter and the minimum in the summer months, with a concentration range of 0.4-7.64 ng m -3 . There are highly significant covariations between the different ring sized group, which suggests that there are similar source strengths and transport mechanisms for these compounds. The particle size distributions indicate that the combustion of fossil fuel is probably the main source of azaarene compounds during the winter. The percentage concentrations of azaarene show that these compounds also tend to associate with larger particles in warm periods and enrich in fine particles in cold weather conditions.

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