The First Data Release of the Sloan Digital Sky Survey

The Sloan Digital Sky Survey has validated and made publicly available its First Data Release. This consists of 2099 square degrees of five-band (u, g, r, i, z) imaging data, 186,240 spectra of galaxies, quasars, stars and calibrating blank sky patches selected over 1360 square degrees of this area, and tables of measured parameters from these data. The imaging data go to a depth of r ~ 22.6 and are photometrically and astrometrically calibrated to 2% rms and 100 milli-arcsec rms per coordinate, respectively. The spectra cover the range 3800--9200 A, with a resolution of 1800--2100. Further characteristics of the data are described, as are the data products themselves.Comment: Submitted to The Astronomical Journal. 16 pages. For associated documentation, see http://www.sdss.org/dr

Directing Cluster Formation of Au Nanoparticles from Colloidal Solution

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

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

An Open Resource for Non-human Primate Imaging.

Non-human primate neuroimaging is a rapidly growing area of research that promises to transform and scale translational and cross-species comparative neuroscience. Unfortunately, the technological and methodological advances of the past two decades have outpaced the accrual of data, which is particularly challenging given the relatively few centers that have the necessary facilities and capabilities. The PRIMatE Data Exchange (PRIME-DE) addresses this challenge by aggregating independently acquired non-human primate magnetic resonance imaging (MRI) datasets and openly sharing them via the International Neuroimaging Data-sharing Initiative (INDI). Here, we present the rationale, design, and procedures for the PRIME-DE consortium, as well as the initial release, consisting of 25 independent data collections aggregated across 22 sites (total = 217 non-human primates). We also outline the unique pitfalls and challenges that should be considered in the analysis of non-human primate MRI datasets, including providing automated quality assessment of the contributed datasets

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Site-Specific Fluorescent Labeling of Hemagglutinin-Specific Antigen Binding Fragment through Amine Chemistry Revealed by Mass Spectrometry

To capture the structure of assembled hemagglutinin (HA) nanoparticles at single-particle resolution, HA-specific antigen binding fragments (Fabs) were labeled by fluorescent (FLR) dyes as probes to highlight the HA trimers displayed on the assembled tetravalent HA nanoparticles for a qualitative localization microscopic study. The FLR dyes were conjugated to the Fabs through N-hydroxysuccinimide (NHS) ester mediated amine coupling chemistry. The labeling profile, including labeling ratio, distribution, and site-specific labeling occupancy, can affect the imaging results and introduce inconsistency. To evaluate the labeling profile so as to evaluate the labeling efficiency, a combination of intact mass measurement by MALDI-MS and peptide mapping through LC-MS/MS was implemented. At the intact molecular level, the labeling ratio and distribution were determined. Through peptide mapping, the labeled residues were identified and the corresponding site-specific labeling occupancy was measured. A systematic comparative investigation of four different FLR-labeled 1H01-Fabs (generated from H1 strain HA specific mAb 1H01) allowed accurate profiling of the labeling pattern. The data indicate that the labeling was site-specific and semiquantitative. This warrants the consistency of single-particle fluorescent imaging experiments and allows a further imaging characterization of the single nanoparticles

Mosaic quadrivalent influenza vaccine single nanoparticle characterization

Abstract Recent work by our laboratory and others indicates that co-display of multiple antigens on protein-based nanoparticles may be key to induce cross-reactive antibodies that provide broad protection against disease. To reach the ultimate goal of a universal vaccine for seasonal influenza, a mosaic influenza nanoparticle vaccine (FluMos-v1) was developed for clinical trial (NCT04896086). FluMos-v1 is unique in that it is designed to co-display four recently circulating haemagglutinin (HA) strains; however, current vaccine analysis techniques are limited to nanoparticle population analysis, thus, are unable to determine the valency of an individual nanoparticle. For the first time, we demonstrate by total internal reflection fluorescence microscopy and supportive physical–chemical methods that the co-display of four antigens is indeed achieved in single nanoparticles. Additionally, we have determined percentages of multivalent (mosaic) nanoparticles with four, three, or two HA proteins. The integrated imaging and physicochemical methods we have developed for single nanoparticle multivalency will serve to further understand immunogenicity data from our current FluMos-v1 clinical trial