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This study is an investigation of the impact of volatile phenols (VPs) released from burning wood during wildfires on grape composition and the resulting wines. Baseline levels of VPs in grapes and sensory differences between smoke-impacted wines and non-smoke-impacted wines were determined. The differences were related to different levels of smoke taint marker compounds in different wine matrices, using modified descriptive analysis (DA), multivariate statistics, gas chromatography mass spectrometry (GC-MS) and liquid chromatography-triple quadrupole tandem mass spectrometry (LC-QqQ-MS) of the free and total VPs, and individual bound glycosides, respectively. Across two DA panels, Cabernet Sauvignon, Cabernet Franc, Petite Verdot, Merlot, Syrah, Malbec, and Zinfandel wines made from grape originating from different areas in California were evaluated. The results show sensory differences between highly smoke-impacted and non-impacted wines with wines made from highly smoke-impacted grapes characterized as smoky, barbeque, medicinal, and having a retro-nasal ashtray character. Low smoke-impact wines based on free and total VP concentrations were not significantly different from the non-impacted wines when rated through descriptive analysis. The amount of smoke exposure was the largest contributor to smoke impact determined by sensory evaluation, but the different wine matrices from different locations and varietals also played an important role in determining the level of perceived smoke impact. The results of this study will contribute to our understanding of smoke impact and how it influences wine characteristics by relating smoke marker indicator compounds to wine sensory attributes.

Particle tracking (PT) is a popular technique in microscopy, microfluidics and colloidal transport studies, where image analysis is used to reconstruct trajectories from bright spots in a video. The performance of many PT algorithms has been rigorously tested for directed and Brownian motion in open media. However, PT is frequently used to track particles in porous media where complex geometries and viscous flows generate particles with high velocity variability over time. Here, we present an evaluation of four PT algorithms for a simulated dispersion of particles in porous media across a range of particle speeds and densities. Of special note, we introduce a new velocity-based PT linking algorithm (V-TrackMat) that achieves high accuracy relative to the other PT algorithms. Our findings underscore that traditional statistics, which revolve around detection and linking proficiency, fall short in providing a holistic comparison of PT codes because they tend to underpenalize aggressive linking techniques. We further elucidate that all codes analyzed show a decrease in performance due to high speeds, particle densities, and trajectory noise. However, linking algorithms designed to harness velocity data show superior performance, especially in the case of high-speed advective motion. Lastly, we emphasize how PT error can influence transport analysis.

In the human genome, heterozygous sites refer to genomic positions with a different allele or nucleotide variant on the maternal and paternal chromosomes. Resolving these allelic differences by chromosomal copy, also known as phasing, is achievable on a short-read sequencer when using a library preparation method that captures long-range genomic information. TELL-Seq is a library preparation that captures long-range genomic information with the aid of molecular identifiers (barcodes). The same barcode is used to tag the reads derived from the same long DNA fragment within a range of up to 200 kilobases (kb), generating linked-reads. This strategy can be used to phase an entire genome. Here, we introduce a TELL-Seq protocol developed for targeted applications, enabling the phasing of enriched loci of varying sizes, purity levels, and heterozygosity. To validate this protocol, we phased 2-200 kb loci enriched with different methods: CRISPR/Cas9-mediated excision coupled with pulse-field electrophoresis for the longest fragments, CRISPR/Cas9-mediated protection from exonuclease digestion for mid-size fragments, and long PCR for the shortest fragments. All selected loci have known clinical relevance: BRCA1, BRCA2, MLH1, MSH2, MSH6, APC, PMS2, SCN5A-SCN10A, and PKI3CA. Collectively, the analyses show that TELL-Seq can accurately phase 2-200 kb targets using a short-read sequencer.

Malaria sterile immunity has been reproducibly induced by immunization with Plasmodium radiation-attenuated sporozoites (RAS). Analyses of sera from RAS-immunized individuals allowed the identification of P. falciparum antigens, such as the circumsporozoite protein (CSP), the basis for the RTS, S and R21Matrix-M vaccines. Similar advances in P. vivax (Pv) vaccination have been elusive. We previously reported 42% (5/12) of sterile protection in malaria-unexposed, Duffy-positive (Fy +) volunteers immunized with PvRAS followed by a controlled human malaria infection (CHMI). Using a custom protein microarray displaying 515 Pv antigens, we found a significantly higher reactivity to PvCSP and one hypothetical protein (PVX_089630) in volunteers protected against P. vivax infection. In mock-vaccinated Fy + volunteers, a strong antibody response to CHMI was also observed. Although the Fy- volunteers immunized with non-irradiated Pv-infected mosquitoes (live sporozoites) did not develop malaria after CHMI, they recognized a high number of antigens, indicating the temporary presence of asexual parasites in peripheral blood. Together, our findings contribute to the understanding of the antibody response to P. vivax infection and allow the identification of novel parasite antigens as vaccine candidates.Trial registration: ClinicalTrials.gov number: NCT01082341.

Abstract Monometallic and bimetallic Cu:Ni catalysts with different Cu:Ni molar ratios (3:1, 2:1, 1:1, 1:2, 1:3) were synthesized by wetness impregnation on activated carbon and characterized by TPR (temperature programmed reduction), XRD (X-ray diffraction) and XPS (X-ray photoelectron spectroscopy). The synthesized catalysts were evaluated in the gas phase production of diethyl carbonate from ethanol and carbon dioxide. The largest catalytic activity was obtained over the bimetallic catalyst with a Cu:Ni molar ratio of 3:1. Its improved activity was attributed to the formation of a Cu–Ni alloy on the surface of the catalyst, evidenced by XPS and in agreement with a previous assignment based on Vegard law and TPR analysis. During the reaction rate experiments, it observed the presence of a maximum of the reaction rate as a function of temperature, a tendency also reported for other carbon dioxide–alcohol reactions. It showed that the reaction rate-temperature data can be adjusted with a reversible rate equation. The initial rate as a function of reactant partial pressure data was satisfactorily adjusted using the forward power law rate equation and it was found that the reaction rate is first order in CO2 and second order in ethanol.

Abstract The excessive accumulation and malfunctioning of visceral adipose tissue (VAT) is a major determinant of increased risk of obesity-related comorbidities. Thus, risk stratification of people living with obesity according to their amount of VAT is of clinical interest. Currently, the most common VAT measurement methods include mathematical formulae based on anthropometric dimensions, often biased by human measurement errors, bio-impedance, and image techniques such as X-ray absorptiometry (DXA) analysis, which requires specialized equipment. However, previous studies showed the possibility of classifying people living with obesity according to their VAT through blood chemical concentrations by applying machine learning techniques. In addition, most of the efforts were spent on men living with obesity while little was done for women. Therefore, this study aims to compare the performance of the multilinear regression model (MLR) in estimating VAT and six different supervised machine learning classifiers, including logistic regression (LR), support vector machine and decision tree-based models, to categorize 149 women living with obesity. For clustering, the study population was categorized into classes 0, 1, and 2 according to their VAT and the accuracy of each MLR and classification model was evaluated using DXA-data (DXAdata), blood chemical concentrations (BLDdata), and both DXAdata and BLDdata together (ALLdata). Estimation error and $$\hbox {R}^{2}$$ R 2 were computed for MLR, while receiver operating characteristic (ROC) and precision-recall curves (PR) area under the curve (AUC) were used to assess the performance of every classification model. MLR models showed a poor ability to estimate VAT with mean absolute error $$\ge 401.40$$ ≥ 401.40 and $$\hbox {R}^{2} \le 0.62$$ R 2 ≤ 0.62 in all the datasets. The highest accuracy was found for LR with values of 0.57, 0.63, and 0.53 for ALLdata, DXAdata, and BLDdata, respectively. The ROC AUC showed a poor ability of both ALLdata and DXAdata to distinguish class 1 from classes 0 and 2 (AUC = 0.31, 0.71, and 0.85, respectively) as also confirmed by PR (AUC = 0.24, 0.57, and 0.73, respectively). However, improved performances were obtained when applying LR model to BLDdata (ROC AUC $$\ge $$ ≥ 0.61 and PR AUC $$\ge $$ ≥ 0.42), especially for class 1. These results seem to suggest that, while a direct and reliable estimation of VAT was not possible in our cohort, blood sample-derived information can robustly classify women living with obesity by machine learning-based classifiers, a fact that could benefit the clinical practice, especially in those health centres where medical imaging devices are not available. Nonetheless, these promising findings should be further validated over a larger population.

People vary both in their embrace of their society's traditions, and in their perception of hazards as salient and necessitating a response. Over evolutionary time, traditions have offered avenues for addressing hazards, plausibly resulting in linkages between orientations toward tradition and orientations toward danger. Emerging research documents connections between traditionalism and threat responsivity, including pathogen-avoidance motivations. Additionally, because hazard-mitigating behaviors can conflict with competing priorities, associations between traditionalism and pathogen avoidance may hinge on contextually contingent tradeoffs. The COVID-19 pandemic provides a real-world test of the posited relationship between traditionalism and hazard avoidance. Across 27 societies (N = 7844), we find that, in a majority of countries, individuals' endorsement of tradition positively correlates with their adherence to costly COVID-19-avoidance behaviors; accounting for some of the conflicts that arise between public health precautions and other objectives further strengthens this evidence that traditionalism is associated with greater attention to hazards.

Mineral deficiencies are common in children living in low-resource areas. Eggs are a rich source of essential nutrients and have been shown to improve growth in young children, although little is known about their impact on mineral status. Children aged 6-9 months (n = 660) were randomized to receive either one egg/day for 6-months or no intervention. Anthropometric data, dietary recalls, and venous blood were collected at baseline and 6-months follow-up. Quantification of plasma minerals (n = 387) was done using inductively coupled plasma-mass spectroscopy. Difference-in-difference mean plasma mineral concentrations was determined from baseline and follow-up values and assessed between groups by intention-to-treat using ANCOVA regression models. Prevalence of zinc deficiency was 57.4% at baseline and 60.5% at follow-up. Mean difference (MD) of plasma magnesium, selenium, copper, and zinc levels were not different between groups. Plasma iron concentrations were significantly lower in the intervention compared to the control group (MD = - 9.29; 95% CI: - 15.95, - 2.64). Zinc deficiency was widely prevalent in this population. Mineral deficiencies were not addressed with the egg intervention. Further interventions are needed to improve the mineral status of young children.

Abstract When someone violates a social norm, others may think that some sanction would be appropriate. We examine how the experience of emotions like anger and disgust relate to the judged appropriateness of sanctions, in a pre-registered analysis of data from a large-scale study in 56 societies. Across the world, we find that individuals who experience anger and disgust over a norm violation are more likely to endorse confrontation, ostracism and, to a smaller extent, gossip. Moreover, we find that the experience of anger is consistently the strongest predictor of judgments of confrontation, compared to other emotions. Although the link between state-based emotions and judgments may seem universal, its strength varies across countries. Aligned with theoretical predictions, this link is stronger in societies, and among individuals, that place higher value on individual autonomy. Thus, autonomy values may increase the role that emotions play in guiding judgments of social sanctions.

A major roadblock to the development of photonic sensors is the scattering associated with many biological systems. We show the conservation of photonic states through optically self-arranged biological waveguides, for the first time, which can be implemented to transmit light through scattering media. The conservation of optical properties of light through biological waveguides allows for the transmission of high bandwidth information with low loss through scattering media. Here, we experimentally demonstrate the conservation of polarization state and orbital angular momentum of light through a self-arranged biological waveguide, several centimeters long, in a sheep red blood cell suspension. We utilize nonlinear optical effects to self-trap cells, which form waveguides at 532 nm and 780 nm wavelengths. Moreover, we use the formed waveguide channels to couple and guide probe beams without altering the information. The formed biological waveguides are in a sub-diffusive scattering regime, so the photons' information degrades insignificantly over several centimeters of propagation through the scattering media. Our results show the potential of biological waveguides as a methodology for the development of novel photonic biosensors, biomedical devices that require optical wireless communication, and the development of new approaches to noninvasive biomedical imaging.