Estimating genetic nurture with summary statistics of multigenerational genome-wide association studies.

Marginal effect estimates in genome-wide association studies (GWAS) are mixtures of direct and indirect genetic effects. Existing methods to dissect these effects require family-based, individual-level genetic, and phenotypic data with large samples, which is difficult to obtain in practice. Here, we propose a statistical framework to estimate direct and indirect genetic effects using summary statistics from GWAS conducted on own and offspring phenotypes. Applied to birth weight, our method showed nearly identical results with those obtained using individual-level data. We also decomposed direct and indirect genetic effects of educational attainment (EA), which showed distinct patterns of genetic correlations with 45 complex traits. The known genetic correlations between EA and higher height, lower body mass index, less-active smoking behavior, and better health outcomes were mostly explained by the indirect genetic component of EA. In contrast, the consistently identified genetic correlation of autism spectrum disorder (ASD) with higher EA resides in the direct genetic component. A polygenic transmission disequilibrium test showed a significant overtransmission of the direct component of EA from healthy parents to ASD probands. Taken together, we demonstrate that traditional GWAS approaches, in conjunction with offspring phenotypic data collection in existing cohorts, could greatly benefit studies on genetic nurture and shed important light on the interpretation of genetic associations for human complex traits.

Curved and Annular Diaphragm Coupled Piezoelectric Micromachined Ultrasonic Transducers for High Transmit Biomedical Applications.

In this paper, we present a novel three-dimensional (3D) coupled configuration of piezoelectric micromachined ultrasound transducers (pMUTs) by combing a curved and an annular diaphragm for transmit performance optimization in biomedical applications. An analytical equivalent circuit model (EQC) is developed with varied excitation methods to incorporate the acoustic-structure coupling of the curved and annular diaphragm-coupled pMUTs (CAC-pMUTs). The model-derived results align well with the reference simulated by the finite element method (FEM). Using this EQC model, we optimize the key design parameters of the CAC-pMUTs in order to improve the output sound pressure, including the width of the annular membrane, the thickness of the passive layer, and the phase difference of the driving voltage. In the anti-phase mode, the designed CAC-pMUTs demonstrate a transmit efficiency 285 times higher than that of single annular pMUTs. This substantial improvement underscores the potential of CAC-pMUTs for large array applications.

Additive Manufacturing of Micro-Architected Copper based on an Ion-Exchangeable Hydrogel.

Additive manufacturing (AM) of copper through laser-based processes poses challenges, primarily attributed to the high thermal conductivity and low laser absorptivity of copper powder or wire as the feedstock. Although the use of copper salts in vat photopolymerization-based AM techniques has garnered recent attention, achieving micro-architected copper with high conductivity and density has remained elusive. In this study, we present a facile and efficient process to create complex 3D micro-architected copper structures with superior electrical conductivity and hardness. The process entails the formulation of an ion-exchangeable photoresin, followed by the utilization of digital light processing (DLP) printing to sculpt 3D hydrogel scaffolds, which were transformed into Cu2+-chelated polymer frameworks (Cu-CPFs) with a high loading of Cu2+ ions through ion exchange, followed by debinding and sintering, results in the transformation of Cu-CPFs into miniaturized copper architectures. This methodology represents an efficient pathway for the creation of intricate micro-architected 3D metal structures.

Heterocyclic Modulated Electronic States of Alkynyl-Containing Conjugated Microporous Polymers for Efficient Oxygen Reduction.

The oxygen reduction reaction (ORR) is a key process in green energy conversion technology. Heteroatom doping has been proven to be a prospective strategy to prepare metal-free carbon-based electrocatalysts, but such methods often suffer from uncontrollable catalyst frameworks and imprecise active sites. Herein, an organic heterocyclic strategy is adopted to modulate the charge redistribution of alkynyl-containing conjugated microporous polymers (CMPs) by introducing varied five-membered heterocyclic structures. Among these CMPs, the S, 2N-containing thiadiazole heterocyclic molecule (CMP-Tdz) with carbonized alginate materials (CCA ) displays a remarkable quasi-four-electron-transfer ORR pathway, exhibiting an excellent half-wave potential (E1/2 ) of 0.77 V, coupled with superior methanol tolerance and electrochemical stability, which are among the highest performance in the metal-free organic catalytic material systems. Density functional theory calculations prove that the high catalytic performance of these catalysts originates from the sp-hybridized C atom (site-2) which is activated by their adjacent heterocyclic structures. Importantly, the five-membered heterocyclic structures can also modulate the local charge distribution, and increase dipole moment, with significantly improved catalytic kinetics. This incorporation of chemically designed heterocyclic-containing alkynyl-CMPs provides a new approach to developing efficient metal-free carbon-based electrocatalysts for fuel cells.

Photoacoustic testing of shear viscoelastic properties of soft tissues using annular beam illumination.

This Letter reports a new, to the best of our knowledge, photoacoustic excitation method for evaluating the shear viscoelastic properties of soft tissues. By illuminating the target surface with an annular pulsed laser beam, circularly converging surface acoustic waves (SAWs) are generated, focused, and detected at the center of the annular beam. The shear elasticity and shear viscosity of the target are extracted from the dispersive phase velocity of the SAWs based on the Kelvin-Voigt model and nonlinear regression fitting. Agar phantoms with different concentrations, and animal liver and fat tissue samples have successfully been characterized. Different from previous methods, the self-focusing of the converging SAWs allows sufficient SNR to be obtained even with low pulsed laser energy density, which makes this approach well compatible with soft tissues under both ex vivo and in vivo testing conditions.

Ring-shaped photoacoustic tweezers for single particle manipulation.

This Letter reports ring-shaped photoacoustic (PA) tweezers that are capable of manipulating single or multiple micron-sized particles. By illuminating a thin layer of an optically absorptive liquid medium with a focused annular pulsed laser beam and a higher pulse repetition rate (e.g., 800 Hz), both acoustic radiation force and instantaneous vaporization repulsion are generated within a certain distance of the illumination region. This makes it possible to conduct continuous and versatile locomotion of single or multiple microparticles. In this Letter, interactions between two or more particles are demonstrated, such as separation, attachment, and grouping of microparticles. The PA tweezers combine some of the advantages of conventional optical and acoustic tweezers and are expected to be a useful alternative approach for the manipulation of microscale objects.

Extending eyebox with tunable viewpoints for see-through near-eye display.

The Maxwellian display presents always-focused images to the viewer, alleviating the vergence-accommodation conflict (VAC) in near-eye displays (NEDs). However, the limited eyebox of the typical Maxwellian display prevents it from wider applications. We propose a Maxwellian see-through NED based on a multiplexed holographic optical element (HOE) and polarization gratings (PGs) to extend the eyebox by viewpoint multiplication. The multiplexed HOE functions as multiple convex lenses to form multiple viewpoints, which are copied to different locations by PGs. To mitigate the imaging problem that multiple viewpoints or no viewpoints enter the eye pupil, the viewpoints can be tuned by mechanically moving a PG. We implement our method in a proof-of-concept system. The optical experiments confirm that the proposed display system provides always in-focus images within a 12 mm eyebox in the horizontal direction with a 32.7° diagonal field of view (FOV) and a 16.5 mm eye relief (ERF), and its viewpoints are tunable to match the actual eye pupil size. Compared with other techniques to extend the eyebox of Maxwellian displays, the proposed method shows competitive performances of a large eyebox, adaptability to the eye pupil size, and focus cues within a large depth range.

Identification of novel anti-inflammatory Nur77 modulators by virtual screening.

Orphan nuclear receptor Nur77 is a unique member of the NR4A nuclear receptor subfamily, which is critical for cellular processes especially the inflammatory responses. Many efforts have been made to discover novel scaffold small molecules targeting Nur77. Herein, we evaluated the previously reported binding sites in crystal structures of Nur77 with small molecules, and then discovered compound 13 as a hit of Nur77 via virtual screening targeting the best-scored binding site. Based on the results of fluorescence titration assay, structure-activity relationship (SAR) analysis was summarized for compound 13 and its analogs. Among these analogs, compound 13e displayed the most potent binding affinity (0.54 ± 0.02 µM). The binding mode of compound 13e was predicted via molecule docking. Moreover, 13e exhibited significant anti-inflammation activity in TNF-α induced HepG2 cell model. Taken together, these results provided a new insight into the understanding the functions of specific binding sites on Nur77 for small molecular compounds, and the development of new scaffold Nur77 modulators.

Analysis and elimination of bias error in a fiber-optic current sensor.

Bias error, along with scale factor, is a key factor that affects the measurement accuracy of the fiber-optic current sensor. Because of polarization crosstalk, the coherence of parasitic interference signals could be rebuilt and form an output independent of the current to be measured, i.e., the bias error. The bias error is a variable of the birefringence optical path difference. Hence, when the temperature changes, the bias error shows a quasi-periodical tendency whose envelope curve reflects the coherence function of light source. By identifying the key factors of bias error and setting the propagation directions of a super-luminescent diode, polarization-maintaining coupler and polarizer to fast axis, it is possible to eliminate the coherence of parasitic interference signals. Experiments show that the maximum bias error decreases by one order of magnitude at temperatures between -40°C to 60°C.

Controlling for polygenic genetic confounding in epidemiologic association studies.

Epidemiologic associations estimated from observational data are often confounded by genetics due to pervasive pleiotropy among complex traits. Many studies either neglect genetic confounding altogether or rely on adjusting for polygenic scores (PGS) in regression analysis. In this study, we unveil that the commonly employed PGS approach is inadequate for removing genetic confounding due to measurement error and model misspecification. To tackle this challenge, we introduce PENGUIN, a principled framework for polygenic genetic confounding control based on variance component estimation. In addition, we present extensions of this approach that can estimate genetically-unconfounded associations using GWAS summary statistics alone as input and between multiple generations of study samples. Through simulations, we demonstrate superior statistical properties of PENGUIN compared to the existing approaches. Applying our method to multiple population cohorts, we reveal and remove substantial genetic confounding in the associations of educational attainment with various complex traits and between parental and offspring education. Our results show that PENGUIN is an effective solution for genetic confounding control in observational data analysis with broad applications in future epidemiologic association studies.

Vitamin D status and variable responses to supplements depend in part on genetic factors in adults with cystic fibrosis.

Vitamin D sufficiency has been difficult to achieve consistently in patients with cystic fibrosis (CF), even with robust oral supplements. To assess vitamin D status and resistance to supplementation, we studied 80 adults using 25-hydroxyvitamin D (25OHD) determinations and whole genome sequencing to construct polygenic risk scores (PRS) that aggregate variants associated with vitamin D status. The results revealed that 30 % of patients were below the threshold of 30 ng/mL and thus should be regarded as insufficient despite normal vitamin E status, a reflection of adherence to fat soluble vitamin supplementation. The PRS values were significantly correlated with 25OHD concentrations, confirming our results in children with CF, and indicating that genetic factors play a role and have implications for therapy.

The production of within-family inequality: Insights and implications of integrating genetic data.

The integration of genetic data within large-scale social and health surveys provides new opportunities to test long-standing theories of parental investments in children and within-family inequality. Genetic predictors, called polygenic scores, allow novel assessments of young children's abilities that are uncontaminated by parental investments, and family-based samples allow indirect tests of whether children's abilities are reinforced or compensated. We use over 16,000 sibling pairs from the UK Biobank to test whether the relative ranking of siblings' polygenic scores for educational attainment is consequential for actual attainments. We find evidence consistent with compensatory processes, on average, where the association between genotype and phenotype of educational attainment is reduced by over 20% for the higher-ranked sibling compared to the lower-ranked sibling. These effects are most pronounced in high socioeconomic status areas. We find no evidence that similar processes hold in the case of height or for relatives who are not full biological siblings (e.g. cousins). Our results provide a new use of polygenic scores to understand processes that generate within-family inequalities and also suggest important caveats to causal interpretations the effects of polygenic scores using sibling difference designs. Future work should seek to replicate these findings in other data and contexts.

Quantifying portable genetic effects and improving cross-ancestry genetic prediction with GWAS summary statistics.

Polygenic risk scores (PRS) calculated from genome-wide association studies (GWAS) of Europeans are known to have substantially reduced predictive accuracy in non-European populations, limiting their clinical utility and raising concerns about health disparities across ancestral populations. Here, we introduce a statistical framework named X-Wing to improve predictive performance in ancestrally diverse populations. X-Wing quantifies local genetic correlations for complex traits between populations, employs an annotation-dependent estimation procedure to amplify correlated genetic effects between populations, and combines multiple population-specific PRS into a unified score with GWAS summary statistics alone as input. Through extensive benchmarking, we demonstrate that X-Wing pinpoints portable genetic effects and substantially improves PRS performance in non-European populations, showing 14.1%-119.1% relative gain in predictive R2 compared to state-of-the-art methods based on GWAS summary statistics. Overall, X-Wing addresses critical limitations in existing approaches and may have broad applications in cross-population polygenic risk prediction.

Metal-Free Carbon-Based Covalent Organic Frameworks with Heteroatom-Free Units Boost Efficient Oxygen Reduction.

Accurate identification of carbon-based metal-free electrocatalyst (CMFE) activity and enhancing their catalytic efficiency for O2 conversion is an urgent and challenging task. This study reports a promising strategy to simultaneously develop a series of covalent organic frameworks (COFs) with well-defined heterocyclic-free biphenyl or fluorenyl units. Unlike heteroatom doping, the developed method not only supplies methyl-induced molecular configuration to promote activity, but also provides a direct opportunity to identify heteroatom-free carbon active centers. The introduction of methyl groups (MGs) with reversible valence bonds into a pristine biphenyl-based COF results in an excellent performance with a half-wave potential of 0.74 V versus the reversible hydrogen electrode (RHE), which is among the highest values for CMFE-COFs as oxygen reduction reaction (ORR) electrocatalysts. Combined with in situ Raman spectra and theoretical calculations, the MG-bound skeleton (DAF-COF) is found to produce ortho activation, confirming the ortho carbon (site-5) adjacent to MGs as active centers. This may be attributed to the opening and binding of MGs, which effectively regulate the molecular configuration and charge redistribution, as well as improve charge transfer and reduce the energy barrier. This study provides insight into the design of highly efficient metal-free organic electrocatalysts via the regulation of valence bonds.

Synthesis and Characterization of an Environmentally Friendly Phenol-Formaldehyde Resin Modified with Waste Plant Protein.

To develop a lower-cost, excellent-performance, and environmentally friendly phenol-formaldehyde (PF) resin, soybean meal was used to modify PF resin, and soybean meal-phenol-formaldehyde (SMPF) resins were prepared. This reveals the effect of soybean meal on the structural, bonding, and curing properties of PF resin, which are very important for its applications in the wood industry. The resins' physicochemical properties and curing performance were investigated, showing that SMPF resins have higher curing temperatures than PF resin. The Fourier transform infrared spectroscopy results indicated that a cross-linking reaction occurred between the amino groups of soybean protein and the hydroxymethyl phenol. Moreover, with the addition of soybean meal, the viscosity of SMPF increased while the gel time decreased. It is worth mentioning that SMPF-2 resin has favorable viscosity, short gel time, low curing temperature (135.78 °C), and high water resistance and bonding strength (1.01 MPa). Finally, all the plywoods bonded with SMPF resins have good water resistance and bonding strength, which could meet the standard (GB/T 17657-2013, type I) for plywood. The optimized SMPF resins showed the potential for application to partially replace PF resin in the wood industry.

Impact of intrinsic and extrinsic risk factors on early-onset lung disease in cystic fibrosis.

BACKGROUND: Although respiratory pathology is known to develop in young children with cystic fibrosis (CF), the determinants of early-onset lung disease have not been elucidated. OBJECTIVE: We aimed to determine the impact of potential intrinsic and extrinsic risk factors during the first 3 years of life, testing the hypothesis that both contribute significantly to early-onset CF lung disease. DESIGN: We studied 104 infants born during 2012-2017, diagnosed through newborn screening by age 3 months, and evaluated comprehensively to 36 months of age. Lung disease manifestations were quantified with a new scoring system known as CFELD for Cystic Fibrosis Early-onset Lung Disease. The variants in the cystic fibrosis transmembrane conductance regulator (CFTR) gene were determined and categorized. Whole genome sequencing was performed on each subject and the data transformed to polygenic risk scores (PRS) that aggregate variants associated with lung function. Extrinsic factors included socioeconomic status (SES) indicators and environmental experiences such as exposures to smoking, pets, and daycare. RESULTS: We found by univariate analysis that CFTR genotype and genetic modifiers aggregated by the PRS method were significantly associated with early-onset CF lung disease. Ordinal logistic regression analysis demonstrated that high and stable SES (maternal education ≥community college, stable 2-parent home, and not receiving Medicaid) and better growth (weight-for-age and height-for-age z-scores) reduced risks, while exposure to smoking and daycare ≥20 h/week increased the risk of CFELD severity. CONCLUSIONS: Extrinsic, modifiable determinants are influential early and potentially as important as the intrinsic risk factors in the onset of CF lung disease.

Celastrol suppresses colorectal cancer via covalent targeting peroxiredoxin 1.

As a terpenoids natural product isolated from the plant Thunder God Vine, Celastrol is widely studied for its pharmacological activities, including anti-tumor activities. The clinical application of Celastrol is strictly limited due to its severe side effects, whereas previously revealed targets and mechanism of Celastrol seldom reduce its in vivo toxicity via structural optimization. Target identification has a far-reaching influence on the development of innovative drugs, and omics data has been widely used for unbiased target prediction. However, it is difficult to enrich target of specific phenotype from thousands of genes or proteins, especially for natural products with broad promising activities. Here, we developed a text-mining-based web-server tool to enrich targets from omics data of inquired compounds. Then peroxiredoxin 1 (PRDX1) was identified as the ROS-manipulating target protein of Celastrol in colorectal cancer. Our solved high-resolution crystal structure revealed the unique covalent binding mode of Celastrol with PRDX1. New derivative compound 19-048 with improved potency against PRDX1 and selectivity towards PRDX2~PRDX6 were synthesized based on crystal structure analysis. Both Celastrol and 19-048 effectively suppressed the proliferation of colorectal cancer cells. The anti-tumor efficacy of Celastrol and 19-048 was significantly diminished on xenograft nude mice bearing PRDX1 knock-down colorectal cancer cells. Several downstream genes of p53 signaling pathway were dramatically up-regulated with Celastrol or 19-048 treatment. Our findings reveal that the side effects of Celastrol could be reduced via structural modification, and PRDX1 inhibition is promising for the treatment of colorectal cancer.

Detecting genetic heterogeneities in response to trauma: The case of 9/11.

The current study evaluates genetic heterogeneities in response to trauma among U.S. young adults. Using Add Health Wave III, which coincidently overlapped with the September 11 attacks, and a depression mean and variance polygenic scores, we investigate how the polygenic scores moderate the causal effect of 9/11 on mental health. Our results show the presence of genetic heterogeneity, where those with high genetic plasticity experience an increase in depressive symptoms following trauma while those with low genetic plasticity do not. While the documented differences in reactions to trauma are important, we also note our ability to predict responses based only on genetic measures are too imprecise to identify susceptible clinical patients. We, therefore, contend that the expected benefits from genetic screening to identify susceptible individuals after trauma are limited. Our results provide novel evidence of a specific source of an additional heterogeneity contributing to the inequality of health following trauma.

Random forest analysis of factors affecting urban carbon emissions in cities within the Yangtze River Economic Belt.

China became the country with the largest global carbon emissions in 2007. Cities are regional population and economic centers and are the main sources of carbon emissions. However, factors influencing carbon emissions from cities can vary with geographic location and the development history of the cities, rendering it difficult to explicitly quantify the influence of individual factors on carbon emissions. In this study, random forest (RF) machine learning algorithms were applied to analyze the relationships between factors and carbon emissions in cities using real-world data from Chinese cities. Seventy-three cities in three urban agglomerations within the Yangtze River Economic Belt were evaluated with respect to urban carbon emissions using data from regional energy balance tables for the years 2000, 2007, 2012, and 2017. The RF algorithm was then used to select 16 prototypical cities based on 10 influencing factors that affect urban carbon emissions while considering five primary factors: population, industry, technology levels, consumption, and openness to the outside world. Subsequently, 18 consecutive years of data from 2000 to 2017 were used to construct RFs to investigate the temporal predictability of carbon emission variation in the 16 cities based on regional differences. Results indicated that the RF approach is a practical tool to study the connection between various influencing factors and carbon emissions in the Yangtze River Economic Belt from different perspectives. Furthermore, regional differences among the primary carbon emission influencing factors for each city were clearly observed and were related to urban population characteristics, urbanization level, industrial structures, and degree of openness to the outside world. These factors variably affected different cities, but the results indicate that regional emission reductions have achieved positive results, with overall simulation trends shifting from underestimation to overestimation of emissions.

PUMAS: fine-tuning polygenic risk scores with GWAS summary statistics.

Polygenic risk scores (PRSs) have wide applications in human genetics research, but often include tuning parameters which are difficult to optimize in practice due to limited access to individual-level data. Here, we introduce PUMAS, a novel method to fine-tune PRS models using summary statistics from genome-wide association studies (GWASs). Through extensive simulations, external validations, and analysis of 65 traits, we demonstrate that PUMAS can perform various model-tuning procedures using GWAS summary statistics and effectively benchmark and optimize PRS models under diverse genetic architecture. Furthermore, we show that fine-tuned PRSs will significantly improve statistical power in downstream association analysis.