Current efforts in medical diagnostic technology focus toward developing biological sensors with the capacity for detecting trace quantities of specified organic molecules. In this study, metallic nanoparticles were investigated for the development of field-enhanced chemical and biological detection devices with the capacity to achieve single-molecule level detection resulting from surface enhanced Raman scattering (SERS) associated with closely spaced noble metal nanostructures.[1, 2] Localized surface plasmon resonance (LSPR) sensors likewise benefit from the incorporation of ordered metal nanoparticles on surfaces, providing increased shift in minimum of reflectivity with biological binding event (figure 1).[3]

Discrete clusters of closely spaced Au nanoparticles can be utilized in devices from photovoltaics to molecular sensors because of the formation of strong local electromagnetic field enhancements when illuminated near their plasmon resonance. In this study, scalable, chemical self-organization methods are shown to produce Au nanoparticle clusters with uniform nanometer interparticle spacing. The performance of two different methods, namely electrophoresis and diffusion, for driving the attachment of Au nanoparticles using a chemical cross-linker on chemically patterned domains of polystyrene-block-poly(methyl methacrylate) (PS-b-PMMA) thin films are evaluated. Significantly, electrophoresis is found to produce similar surface coverage as diffusion in 1/6th of the processing time with an ~2-fold increase in the number of Au nanoparticles forming clusters. Furthermore, average interparticle spacing within Au nanoparticle clusters was found to decrease from 2-7 nm for diffusion deposition to approximately 1-2 nm for electrophoresis deposition, and the latter method exhibited better uniformity with most clusters appearing to have about 1 nm spacing between nanoparticles. The advantage of such fabrication capability is supported by calculations of local electric field enhancements using electromagnetic full-wave simulations from which we can estimate surface-enhanced Raman scattering (SERS) enhancements. In particular, full-wave results show that the maximum SERS enhancement, as estimated here as the fourth power of the local electric field, increases by a factor of 100 when the gap goes from 2 to 1 nm, reaching values as large as 10(10), strengthening the usage of electrophoresis versus diffusion for the development of molecular sensors.

We investigate local electromagnetic field enhancements in oligomers of plasmonic nanospheres. We first evaluate via full-wave simulations the field between spheres in several oligomer systems: linear dimers, linear trimers, trimers 60°, trimers 90° and linear quadrumers. To gain a better understanding of the field enhancement values, we compare the results with local fields in a hexagonal close-packed (HCP) configuration with same structural dimensions. We then inter-relate the field enhancement values found via full-wave simulations to SERS enhancements of actual fabricated self-assembled oligomers. We find that linear oligomers provide the largest field enhancement values. Finally, we provide closed-form formulas for the prediction of the resonance frequency responsible for field enhancement in linear oligomers, namely dimers, trimers and quadrumers, modeling each nanosphere as a single electric dipole. These formulas provide with resonance values less than 7% shifted when compared to full-wave results even when the gap between spheres is only about one fifth of the radius, showing the powerfulness of dipolar approximations. The results shown in this paper demonstrate that ad hoc clusters of nanospheres can be designed and fabricated to obtain larger field enhancements than with the HCP structure and this may pave the way for the development of improved sensors for molecular spectroscopy.

Near-field plasmonic coupling and local field enhancement in metal nanoarchitectures, such as arrangements of nanoparticle clusters, have application in many technologies from medical diagnostics, solar cells, to sensors. Although nanoparticle-based cluster assemblies have exhibited signal enhancements in surface-enhanced Raman scattering (SERS) sensors, it is challenging to achieve high reproducibility in SERS response using low-cost fabrication methods. Here an innovative method is developed for fabricating self-organized clusters of metal nanoparticles on diblock copolymer thin films as SERS-active structures. Monodisperse, colloidal gold nanoparticles are attached via a crosslinking reaction on self-organized chemically functionalized poly(methyl methacrylate) domains on polystyrene-block-poly(methyl methacrylate) templates. Thereby nanoparticle clusters with sub-10-nanometer interparticle spacing are achieved. Varying the molar concentration of functional chemical groups and crosslinking agent during the assembly process is found to affect the agglomeration of Au nanoparticles into clusters. Samples with a high surface coverage of nanoparticle cluster assemblies yield relative enhancement factors on the order of 10⁹ while simultaneously producing uniform signal enhancements in point-to-point measurements across each sample. High enhancement factors are associated with the narrow gap between nanoparticles assembled in clusters in full-wave electromagnetic simulations. Reusability for small-molecule detection is also demonstrated. Thus it is shown that the combination of high signal enhancement and reproducibility is achievable using a completely non-lithographic fabrication process, thereby producing SERS substrates having high performance at low cost.

Wildfire smoke harms health. We add to this literature by evaluating the health effects of California's 2018 Carr Fire and preceding wildfire seasons in Shasta County.

Methods

With data from the Shasta County Health and Human Services Agency, we examined the link between weekly wildfire fine particulate matter (PM_2.5) exposure estimated using a spatiotemporal multiple imputation approach and emergency department (ED) visits and mortality using time-series models that controlled for temporal trends and temperature.

Results

Between 2013 and 2018, Shasta County experienced 19 weeks with average wildfire PM_2.5 ≥5.5 μg/m³ (hereafter, "high wildfire PM_2.5 concentration"). Among all Shasta County Zip Code Tabulation Areas (ZCTAs; n = 36), we detected no association between high wildfire PM_2.5 concentrations and respiratory or circulatory disease-related ED visits or mortality. Subsequent analyses were confined to valley ZCTAs (n = 11, lower elevation, majority of population, worse air quality in general). In valley ZCTAs, high wildfire PM_2.5 was associated with a 14.6% (95% confidence interval [CI] = 4.2, 24.9) increase in same-week respiratory disease-related ED visits but no increase in the subsequent 2 weeks nor on circulatory disease-related mortality or ED visits or all-cause mortality. Two weeks after high wildfire PM_2.5 weeks, respiratory disease-related deaths decreased (-31.5%, 95% CI = -64.4, 1.5). The 2018 Carr Fire appeared to increase respiratory disease-related ED visits by 27.0% (95% CI = 4.0, 50.0) over expectation and possibly reduce circulatory disease-related deaths (-18.2%, 95% CI = -39.4, 2.9).

Conclusions

As climate change fuels wildfire seasons, studies must continue to evaluate their health effects, particularly in highly exposed populations.

Background

Important insights into the early pathogenesis of Alzheimer's disease can be provided by studies of autosomal dominant Alzheimer's disease and Down syndrome. However, it is unclear whether the timing and spatial distribution of amyloid accumulation differs between people with autosomal dominant Alzheimer's disease and those with Down syndrome. We aimed to directly compare amyloid changes between these two groups of people.

Methods

In this cross-sectional study, we included participants (aged ≥25 years) with Down syndrome and sibling controls who had MRI and amyloid PET scans in the first data release (January, 2020) of the Alzheimer's Biomarker Consortium-Down Syndrome (ABC-DS) study. We also included carriers of autosomal dominant Alzheimer's disease genetic mutations and non-carrier familial controls who were within a similar age range to ABC-DS participants (25-73 years) and had MRI and amyloid PET scans at the time of a data freeze (December, 2020) of the Dominantly Inherited Alzheimer Network (DIAN) study. Controls from the two studies were combined into a single group. All DIAN study participants had genetic testing to determine PSEN1, PSEN2, or APP mutation status. APOE genotype was determined from blood samples. CSF samples were collected in a subset of ABC-DS and DIAN participants and the ratio of amyloid β42 (Aβ42) to Aβ40 (Aβ42/40) was measured to evaluate its Spearman's correlation with amyloid PET. Global PET amyloid burden was compared with regards to cognitive status, APOE ɛ4 status, sex, age, and estimated years to symptom onset. We further analysed amyloid PET deposition by autosomal dominant mutation type. We also assessed regional patterns of amyloid accumulation by estimated number of years to symptom onset. Within a subset of participants the relationship between amyloid PET and CSF Aβ42/40 was evaluated.

Findings

192 individuals with Down syndrome and 33 sibling controls from the ABC-DS study and 265 carriers of autosomal dominant Alzheimer's disease mutations and 169 non-carrier familial controls from the DIAN study were included in our analyses. PET amyloid centiloid and CSF Aβ42/40 were negatively correlated in carriers of autosomal dominant Alzheimer's disease mutations (n=216; r=-0·565; p<0·0001) and in people with Down syndrome (n=32; r=-0·801; p<0·0001). There was no difference in global PET amyloid burden between asymptomatic people with Down syndrome (mean 18·80 centiloids [SD 28·33]) versus asymptomatic mutation carriers (24·61 centiloids [30·27]; p=0·11) and between symptomatic people with Down syndrome (77·25 centiloids [41·76]) versus symptomatic mutation carriers (69·15 centiloids [51·10]; p=0·34). APOE ɛ4 status and sex had no effect on global amyloid PET deposition. Amyloid deposition was elevated significantly earlier in mutation carriers than in participants with Down syndrome (estimated years to symptom onset -23·0 vs -17·5; p=0·0002). PSEN1 mutations primarily drove this difference. Early amyloid accumulation occurred in striatal and cortical regions for both mutation carriers (n=265) and people with Down syndrome (n=128). Although mutation carriers had widespread amyloid accumulation in all cortical regions, the medial occipital regions were spared in people with Down syndrome.

Interpretation

Despite minor differences, amyloid PET changes were similar between people with autosomal dominant Alzheimer's disease versus Down syndrome and strongly supported early amyloid dysregulation in individuals with Down syndrome. Individuals with Down syndrome aged at least 35 years might benefit from early intervention and warrant future inclusion in clinical trials, particularly given the relatively high incidence of Down syndrome.

Funding

The National Institute on Aging, Riney and Brennan Funds, the Eunice Kennedy Shriver National Institute of Child Health and Human Development, the German Center for Neurodegenerative Diseases, and the Japan Agency for Medical Research and Development.