Detection of gold cysteine thiolate complexes on gold nanoparticles with time-of-flight secondary ion mass spectrometry

Gold (Au) nanoparticles (NPs) are widely used in nanomedical applications as a carrier for molecules designed for different functionalities. Previous findings suggested that biological molecules, including amino acids, could contribute to the dissolution of Au NPs in physiological environments and that this phenomenon was size-dependent. We, therefore, investigated the interactions of L-cysteine with 5-nm Au NPs by means of time-of-flight secondary ion mass spectrometry (ToF-SIMS). This was achieved by loading Au NPs on a clean aluminum (Al) foil and immersing it in an aqueous solution containing L-cysteine. Upon rinsing off the excessive cysteine molecules, ToF-SIMS confirmed the formation of gold cysteine thiolate via the detection of not only the Au–S bond but also the hydrogenated gold cysteine thiolate molecular ion. The presence of NaCl or a 2-(N-morpholino)ethanesulfonic acid buffer disabled the detection of Au NPs on the Al foil. The detection of larger (50-nm) Au NPs was possible but resulted in weaker cysteine and gold signals, and no detected gold cysteine thiolate signals. Nano-gold specific adsorption of L-cysteine was also demonstrated by cyclic voltammetry using paraffine-impregnated graphite electrodes with deposited Au NPs. We demonstrate that the superior chemical selectivity and surface sensitivity of ToF-SIMS, via detection of elemental and molecular species, provide a unique ability to identify the adsorption of cysteine and formation of gold–cysteine bonds on Au NPs

Contact Angle & Electrochemical Measurements of Metallic Atmospheric Corrosion on Copper and Carbon Steel

Understanding atmospheric corrosion has been incredibly challenging due to the complex interplay between surface microstructures, environmental variables, and electrochemical processes. The methodology presented is being developed to apply to atmospheric corrosion models of metals and other advanced materials by observing the change in contact angle in situ as a function of corrosion parameters. Performed contact angle measurements on two industrially relevant metals (copper and carbon steel) over a 1 min to 30-day time span to track the change in wettability due to the formation of an air-formed oxide layer (aged) as a function of surface roughness

Location of cobalt impurities in the surface oxide of stainless steel 316L and metal release in synthetic biological fluids

Since 2021, cobalt (Co) is in Europe classified as carcinogen in quantities exceeding 0.1 wt-%. This affects nickel-rich stainless steels, which contain about 0.2 wt-% Co impurities. Previous findings show the bioaccessibility of Co in stainless steel to be primarily determined by the corrosion resistance. It has been unclear whether Co is distributed heterogeneously in the alloy and the outermost surface and whether a specific location would pose a risk for Co release under specific exposure conditions. This study aimed at locating Co in stainless steel 316L (0.2 wt-% Co) surfaces prior to and after exposure to different synthetic body fluids for 24 h at 37 °C. Time-of-flight secondary ion mass spectrometry (ToF-SIMS), X-ray photoelectron spectroscopy (XPS), and inductively coupled plasma mass spectrometry (ICPMS) investigated the location of Co in the surface oxide and extent of release along with other metals (iron, chromium, nickel, and manganese) into synthetic biological fluids (gastric fluid, pH 1.5; lysosomal fluid, pH 4.5; phosphate buffered saline-PBS, pH 7.4). Co was homogeneously distributed along with metallic nickel beneath the surface oxide and co-released with other metals upon surface reformation and passivation. Exposure in PBS resulted in the incorporation of both Co and phosphate in the oxide

Revisiting atomic force microscopy force spectroscopy sensitivity for single molecule studies

Recently, the rapid advances in quantitative biology and polymer science have led to the atomic force microscope ͑AFM͒ being extensively employed for single-molecule force spectroscopy. Deflection sensitivity, a critical factor in single molecule force spectroscopy, is changed due to the change in bending shape of AFM cantilever when a single molecule is attached to the AFM cantilever tip. We quantitatively study this variation in the deflection sensitivity by modeling the single molecule as an AFM tip coupled spring. We further propose correction factors for the deflection sensitivity in various cases of single molecule studies. Since many single biomolecule studies are conducted in aqueous environment, we outline and include the complications induced by the refractive index discontinuity at the air-glass-liquid medium interfaces, laser spot size, and spot location on the cantilever. Finally we present correction factor charts for easy calculation of correction factors for a wide variety of stiffness of single molecules

DISCO: Distribution-Aware Calibration for Object Detection with Noisy Bounding Boxes

Large-scale well-annotated datasets are of great importance for training an effective object detector. However, obtaining accurate bounding box annotations is laborious and demanding. Unfortunately, the resultant noisy bounding boxes could cause corrupt supervision signals and thus diminish detection performance. Motivated by the observation that the real ground-truth is usually situated in the aggregation region of the proposals assigned to a noisy ground-truth, we propose DIStribution-aware CalibratiOn (DISCO) to model the spatial distribution of proposals for calibrating supervision signals. In DISCO, spatial distribution modeling is performed to statistically extract the potential locations of objects. Based on the modeled distribution, three distribution-aware techniques, i.e., distribution-aware proposal augmentation (DA-Aug), distribution-aware box refinement (DA-Ref), and distribution-aware confidence estimation (DA-Est), are developed to improve classification, localization, and interpretability, respectively. Extensive experiments on large-scale noisy image datasets (i.e., Pascal VOC and MS-COCO) demonstrate that DISCO can achieve state-of-the-art detection performance, especially at high noise levels.Comment: 12 pages, 9 figure

The LAMOST Complete Spectroscopic Survey of Pointing Area (LaCoSSPAr) in the Southern Galactic Cap I. The Spectroscopic Redshift Catalog

We present a spectroscopic redshift catalog from the LAMOST Complete Spectroscopic Survey of Pointing Area (LaCoSSPAr) in the Southern Galactic Cap (SGC), which is designed to observe all sources (Galactic and extra-galactic) by using repeating observations with a limiting magnitude of $r=18.1~mag$ in two $20~deg^2$ fields. The project is mainly focusing on the completeness of LAMOST ExtraGAlactic Surveys (LEGAS) in the SGC, the deficiencies of source selection methods and the basic performance parameters of LAMOST telescope. In both fields, more than 95% of galaxies have been observed. A post-processing has been applied to LAMOST 1D spectrum to remove the majority of remaining sky background residuals. More than 10,000 spectra have been visually inspected to measure the redshift by using combinations of different emission/absorption features with uncertainty of $\sigma_{z}/(1+z)<0.001$. In total, there are 1528 redshifts (623 absorption and 905 emission line galaxies) in Field A and 1570 redshifts (569 absorption and 1001 emission line galaxies) in Field B have been measured. The results show that it is possible to derive redshift from low SNR galaxies with our post-processing and visual inspection. Our analysis also indicates that up to 1/4 of the input targets for a typical extra-galactic spectroscopic survey might be unreliable. The multi-wavelength data analysis shows that the majority of mid-infrared-detected absorption (91.3%) and emission line galaxies (93.3%) can be well separated by an empirical criterion of $W2-W3=2.4$. Meanwhile, a fainter sequence paralleled to the main population of galaxies has been witnessed both in $M_r$/$W2-W3$ and $M_*$/$W2-W3$ diagrams, which could be the population of luminous dwarf galaxies but contaminated by the edge-on/highly inclined galaxies ($\sim30\%$).Comment: 19 pages, 14 figures, 2 MRT, accepted by ApJ

Liver-heart crosstalk controls IL-22 activity in cardiac protection after myocardial infarction.

Interleukin (IL)-22 regulates tissue inflammation and repair. Here we report participation of the liver in IL-22-mediated cardiac repair after acute myocardial infarction (MI). Methods: We induced experimental MI in mice by ligation of the left ascending artery and evaluated the effect of IL-22 on post-MI cardiac function and ventricular remodeling. Results: Daily subcutaneous injection of 100 µg/kg mouse recombinant IL-22 for seven days attenuated adverse ventricular remodeling and improved cardiac function in mice at 28 days after left anterior descending coronary artery ligation-induced MI. Pharmacological inhibition of signal transducer and activator of transcription (STAT3) muted these IL-22 activities. While cardiomyocyte-selective depletion of STAT3 did not affect IL-22 activities in protecting post-MI cardiac injury, hepatocyte-specific depletion of STAT3 fully muted these IL-22 cardioprotective activities. Hepatocyte-derived fibroblast growth factor (FGF21) was markedly increased in a STAT3-dependent manner following IL-22 administration and accounted for the cardioprotective benefit of IL-22. Microarray analyses revealed that FGF21 controlled the expression of cardiomyocyte genes that are involved in cholesterol homeostasis, DNA repair, peroxisome, oxidative phosphorylation, glycolysis, apoptosis, and steroid responses, all of which are responsible for cardiomyocyte survival. Conclusions: Supplementation of IL-22 in the first week after acute MI effectively prevented left ventricular dysfunction and heart failure. This activity of IL-22 involved crosstalk between the liver and heart after demonstrating a role of the hepatic STAT3-FGF21 axis in IL-22-induced post-MI cardiac protection

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts