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Biocatalytic cascades were developed to synthesize 15 benzylisoquinoline alkaloids in excellent ee values from dopamine and p-coumaric acid derivatives.

Tyrosine kinase inhibitors (TKIs) have been widely used for cancer chemotherapy, but they also cause cardiotoxicities in cancer patients. In this study, we used human stem cells as an in-vitro system to interrogate the mechanisms underlying drug-induced toxicity in differentiated cardiomyocytes, including anticancer tyrosine kinase inhibitor (TKI) drugs, including imatinib, sunitinib, and vandetanib. Sublethal TKI exposure produces multiple effects, including disarranged sarcomere structure, interrupted Ca2+-handling, and impaired mitochondrial function, evident of TKI-induced toxicity in differentiated cardiomyocytes. GATA4-mediated regulatory networks, including key mitochondrial target genes, emerge as significant molecular signatures in integrated analyses of transcriptome and chromatin accessibility dynamics. We find that, on a molecular level, GATA4 acts as a regulatory factor in mitochondrial biogenesis and OXPHOS by directly regulating specific metabolism-related genes, such as PPARGC1A. Functional genomic experiments targeting GATA4 reveals that GATA4 upregulation by CRISPR-activation is able to restore mitochondrial morphology and OXPHOS upon TKI exposure. In addition, we also identified that GATA4 is involved in regulation of mitochondrial biogenesis during early cardiac differentiation; inhibition of GATA4 during differentiation reduces mitochondrial DNA content, ATP production, and OXPHOS in differentiated cardiomyocytes, demonstrating a developmental role of GATA4 in metabolic management during early cardiac differentiation. Altogether, our study identifies a novel link between GATA4 and mitochondria in cardiomyocytes, and identifies GATA4 as a promising therapeutic target for reducing TKI-induced cardiotoxicity for human health.

Pulmonary atresia with intact ventricular septum (PA-IVS) is a detrimental congenital heart disease where the pulmonary valve is not appropriately developed. Several hypotheses speculated to explain the pathogenesis of this disorder contains abnormal coronary arterial development, atypical blood flow through venous valve and atretic pulmonary valve formation. Conventional treatment strategy is pulmonary valve perforation, and PA-IVS patients after treatment present with varying degrees of ventricular hypoplasia: from single ventricle palliation (1v) to 1½-ventricle palliation (1.5v) and bi-ventricle repair (2v). Mechanistic studies are required to further explain the different levels of RV hypoplasia in PA-IVS patients. Here, we generated PA-IVS-specific induced pluripotent stem cells (iPSCs) from patients with a spectrum of RV hypoplasia. PA-IVS iPSC-derived cardiomyocytes (iPSC-CMs) contracted normally and displayed sarcomeric structures with intercalated cardiac troponin T and α-actinin. Early-stage PA-IVS iPSC-CMs exhibited a variety of compromised proliferation activities, which were not able to be rescued by Wnt signaling pathway activation. Transcriptomic profiling by bulk RNA seq suggested that pathways involved in the cell cycle and mitosis were downregulated in day13 PA-IVS-1v iPSC-CMs, but not in PA-IVS-2v iPSC-CMs. However, at later stage (day20), pathways involved in the regulation of cell division and mitosis was upregulated in PA-IVS-1v cardiomyocytes, indicating a possible developmental delay in the cardiomyocyte proliferation for PA-IVS-1v. Intriguingly, differentially expressed genes between PA-IVS-2v and control CMs were mostly enriched in the pathways relevant to glucose metabolism, mitochondrial biogenesis, and muscle contraction. The differentially involved pathways between PA-IVS-1v and PA-IVS-2v cardiomyocytes suggest that an intrinsic transcriptional program may lead to divergent degrees of cardiomyocyte proliferation and ventricular growth in PA-IVS. We conclude that patient iPSC-CMs can recapitulate cardiomyocyte proliferation defects which are involved in ventricular hypoplasia in PA-IVS.

Biomass-derived hydroxycinnamates (mainly including p-coumaric acid and ferulic acid), which are natural sources of aromatic compounds, are highly underutilized resources. There is a need to upgrade them to make them economically feasible. Value-added phenolic glycosides and their derivatives, both belonging to a class of plant aromatic natural products, are widely used in the nutraceutical, pharmaceutical, and cosmetic industries. However, their complex aromatic structures make their efficient biosynthesis a challenging process. To overcome this issue, we created three novel synthetic cascades for the biosynthesis of phenolic glycosides (gastrodin, arbutin, and salidroside) and their derivatives (hydroquinone, tyrosol, hydroxytyrosol, and homovanillyl alcohol) from p-coumaric acid and ferulic acid. Moreover, because the biomass-derived hydroxycinnamates directly provided aromatic units, the cascades enabled efficient biosynthesis. We achieved substantially high production rates (up to or above 100-fold enhancement) relative to the glucose-based biosynthesis. Given the ubiquity of the aromatic structure in natural products, the use of biomass-derived aromatics should facilitate the rapid biosynthesis of numerous aromatic natural products.

Agglomeration in solid composite propellants is known to exacerbate two-phase flow losses. In this experimental study, we investigate the substitution of aluminum particles with metallic alloys in order to reduce agglomeration in aluminized propellants. We consider five different aluminum-based alloys: Al-Mg, Al-Ni, Al-Si, Al-B, and Al-Zn. Through thermogravimetric-differential scanning calorimetry measurements, we find that all five alloys can increase the initial oxidation temperature relative to a baseline Al propellant, but that only Al-Si and Al-Zn exhibit lower melting temperatures. Laser ignition experiments show that Al-Mg produces the most balanced combination of a short ignition delay time and a short self-sustaining combustion time. High-pressure experiments at 0.5 to 3 MPa show that Al-Si has a markedly higher burning rate than the baseline Al propellant, while Al-Mg and Al-Ni have the lowest pressure exponents. High-speed microscopic surface imaging at 0.5 and 1 MPa shows that Al-Ni produces the largest reduction in agglomeration, with an average agglomerate size some 30% smaller than the baseline value. By contrast, Al-Zn produces the worst agglomeration, with an average agglomerate size around 15% larger than the baseline value. From these findings, we propose a qualitative phenomenological mechanism for agglomeration in metallic-alloy propellants based on a competition among four distinct effects: the metal melting temperature, the adhesive force of the agglomerates, the propellant burning rate, and micro-explosions. We then analyze the agglomeration of the different alloys using the proposed mechanism. As well as providing new experimental data on the agglomeration, ignition and combustion characteristics of solid composite propellants containing aluminum-based alloys, this study reinforces the notion that the agglomeration and combustion performance of aluminized propellants can be optimized through a judicious choice of alloying elements.

In this paper, we investigate the variable selection for varying coefficient errors-in-variables (EV) models with longitudinal data when some covariates are measured with additive errors. A variable selection method based on bias-corrected penalized quadratic inference function (pQIF) is proposed by combining the basis function approximation to coefficient functions and bias-corrected quadratic inference function (QIF) with shrinkage estimations. The proposed method can handle the measurement errors of covariates and within-subject correlation, estimate and select non-zero nonparametric coefficient functions. With appropriate selection of the tuning parameters, we establish the consistency of the variable selection method and the sparsity properties of the regularized estimators. The finite sample performance of the proposed method is assessed by simulation studies. The utility of the method is further demonstrated via a real data analysis.

Congenital heart disease (CHD) represents a major class of birth defects worldwide and is associated with cardiac malformations that often require surgical intervention immediately after birth. Despite the intense efforts from multicentric genome/exome sequencing studies that have identified several genetic variants, the etiology of CHD remains diverse and often unknown. Genetically modified animal models with candidate gene deficiencies continue to provide novel molecular insights that are responsible for fetal cardiac development. However, the past decade has seen remarkable advances in the field of human induced pluripotent stem cell (hiPSC)-based disease modeling approaches to better understand the development of CHD and discover novel preventative therapies. The iPSCs are derived from reprogramming of differentiated somatic cells to an embryonic-like pluripotent state via overexpression of key transcription factors. In this review, we describe how differentiation of hiPSCs to specialized cardiac cellular identities facilitates our understanding of the development and pathogenesis of CHD subtypes. We summarize the molecular and functional characterization of hiPSC-derived differentiated cells in support of normal cardiogenesis, those that go awry in CHD and other heart diseases. We illustrate how stem cell-based disease modeling enables scientists to dissect the molecular mechanisms of cell-cell interactions underlying CHD. We highlight the current state of hiPSC-based studies that are in the verge of translating into clinical trials. We also address limitations including hiPSC-model reproducibility and scalability and differentiation methods leading to cellular heterogeneity. Last, we provide future perspective on exploiting the potential of hiPSC technology as a predictive model for patient-specific CHD, screening pharmaceuticals, and provide a source for cell-based personalized medicine. In combination with existing clinical and animal model studies, data obtained from hiPSCs will yield further understanding of oligogenic, gene-environment interaction, pathophysiology, and management for CHD and other genetic cardiac disorders.

In this paper, four kinds of polyamide yarns with different graphene contents and three kinds of seamless knitting structures were used. The scheme of samples was established according to the comprehensive experimental design method, and 12 pieces of knitted fabric samples were woven on the seamless knitting machine. Through testing and analyzing the influence of each sample on the blood-flow rate of human-surface-skin microcirculation, the research shows that the higher the content of graphene in the veil, the better the promotion effect of the fabric prepared under this process condition on the blood-flow rate of human-surface-skin microcirculation. Sample 11# with the veil type of GP-0.8% and fabric weave of 1+1 simulated ribbed stitch has the strongest effect in this experiment, with a promotion multiple of 1.2189, and the influence of tissue structure is not obvious. The relevant performance test data and experimental research results in this paper provide empirical data support for developing medical or health textiles related to promoting the blood-flow velocity of skin microcirculation.

In this paper, the effects of the structural parameters of magnetic-knitted fabric on human skin microcirculation (HSM) were studied in relation to magnetic polypropylene yarn, which was used as raw material. Three experimental factors were designed: the magnetic powder content of polypropylene, the feeding ratio of magnetic polypropylene (MP) and graphene viscous (GV), and stitch. Twelve pieces of seamless knitted fabric were prepared according to the comprehensive experimental design method. The BIV angiography was used to proceed with an HSM test of about 12 pieces of seamless knitted fabric. The results show the following: The magnetic powder content of polypropylene has the greatest influence on the blood flow promotion multiples of skin–blood microcirculation, followed by the feeding ratio of MP and GV, while stitch has the least influence. When the plating yarn feeding ratio was 100:0, the magnetic powder content of polypropylene was 50%, and the stitch was 1 + 1 false rib, meaning that the fabric could promote HSM more efficiently. This is compared against the common polypropylene knitted fabric, where the blood flow promotion multiples increased by 9.87%. The purpose of this study was to explore the structural parameters of magnetic polypropylene-knitted fabric that has a better effect on promoting HSM, and to provide a reference for the development of functional health-knitted fabrics.

In this paper, we consider the estimation and model selection for longitudinal partial linear varying coefficient errors-in-variables (EV) models when the covariates are measured with some additive errors. Bias-corrected penalized quadratic inference functions method is proposed based on quadratic inference functions with two penalty function terms. The proposed method can not only handle the measurement errors of covariates and within-subject correlations but also estimate and select significant non-zero parametric and nonparametric components simultaneously. With some regularization conditions, the resulting estimators of parameters are asymptotically normal and the estimators of nonparametric varying coefficient achieves the optimal convergence rate. Furthermore, we present simulation studies and a real example analysis to evaluate the finite sample performance of the proposed method.

Next-generation sequencing has emerged as an essential technology for the quantitative analysis of gene expression. In medical research, RNA sequencing (RNA-seq) data are commonly used to identify which type of disease a patient has. Because of the discrete nature of RNA-seq data, the existing statistical methods that have been developed for microarray data cannot be directly applied to RNA-seq data. Existing statistical methods usually model RNA-seq data by a discrete distribution, such as the Poisson, the negative binomial, or the mixture distribution with a point mass at zero and a Poisson distribution to further allow for data with an excess of zeros. Consequently, analytic tools corresponding to the above three discrete distributions have been developed: Poisson linear discriminant analysis (PLDA), negative binomial linear discriminant analysis (NBLDA), and zero-inflated Poisson logistic discriminant analysis (ZIPLDA). However, it is unclear what the real distributions would be for these classifications when applied to a new and real dataset. Considering that count datasets are frequently characterized by excess zeros and overdispersion, this paper extends the existing distribution to a mixture distribution with a point mass at zero and a negative binomial distribution and proposes a zero-inflated negative binomial logistic discriminant analysis (ZINBLDA) for classification. More importantly, we compare the above four classification methods from the perspective of model parameters, as an understanding of parameters is necessary for selecting the optimal method for RNA-seq data. Furthermore, we determine that the above four methods could transform into each other in some cases. Using simulation studies, we compare and evaluate the performance of these classification methods in a wide range of settings, and we also present a decision tree model created to help us select the optimal classifier for a new RNA-seq dataset. The results of the two real datasets coincide with the theory and simulation analysis results. The methods used in this work are implemented in the open-scource R scripts, with a source code freely available at https://github.com/FocusPaka/ZINBLDA.

In autumn and winter, the climate is dry and human skin tends to become dry as a result. The application of hyaluronic acid to a fabric has a certain moisturizing effect, which can further improve the wearing comfort of the fabric. In this study, three knitted fabric structures including weft plain stitch, 1 + 1 mock rib, and 1 + 3 mock rib were designed. The face yarn adopted hyaluronic acid viscose fiber, graphene viscose fiber, nylon, and viscose with different interweaving ratios, and the inner yarn adopted nylon/spandex-coated wire. A total of 18 sample knitted fabrics were woven according to the experimental method of the full test. The effects of the fabric structure and fabric raw materials on skin moisturizing properties were studied and analyzed by testing the skin water content and trans-epidermal water loss before and after coating the fabric on the human skin. The results show that the most significant factor affecting the skin moisture content is the raw material used in the fabric. When the interweaving ratio of hyaluronic acid viscose fiber in the fabric decreases, the moisturizing performance of the fabric on human skin is weakened. The second is the fabric structure. In terms of structure, 1 + 1 mock rib fabric has better moisturizing performance for human skin. When the material adopts hyaluronic acid viscose fiber/graphene viscose fiber (100:0) and the structure adopts 1 + 1 mock rib, the moisturizing effect on human skin is better.

DNA methylation is an essential epigenetic modification involved in regulating the expression of mammalian genomes. A variety of experimental approaches to generate genome-wide or whole-genome DNA methylation data have emerged in recent years. Methylated DNA immunoprecipitation followed by sequencing (MeDIP-seq) is one of the major tools used in whole-genome epigenetic studies. However, analyzing this data in terms of accuracy, sensitivity, and speed still remains an important challenge. Existing methods, such as BATMAN and MEDIPS, analyze MeDIP-seq data by dividing the whole genome into equal length windows and assume that each CpG of the same window has the same methylation level. More precise work is necessary to estimate the methylation level of each CpG site in the whole genome. In this paper, we propose a Statistical Inferences with MeDIP-seq Data (SIMD) to infer the methylation level for each CpG site. In addition, we analyze a real dataset for DNA methylation. The results show that our method displays improved precision in detecting differentially methylated CpG sites compared to the existing method. To meet the demands of the application, we have developed an R package called "SIMD", which is freely available in https://github.com/FocusPaka/SIMD.

Background and Purpose— Extravascular optical coherence tomography (OCT), as a noninvasive imaging methodology with micrometer resolution, was evaluated in a murine model of carotid atherosclerosis by way of assessing the efficacy of pravastatin therapy. Methods— An OCT device was engineered for extravascular plaque imaging. Wild-type mice and apolipoprotein E–deficient (ApoE −/− ) mice were randomized to 3 treatment groups: (1) wild-type on a diet of standard rodent chow (n=13); (2) ApoE −/− on a high-fat, atherosclerotic diet (HFD; n=13); and (3) ApoE −/− on a HFD given daily pravastatin (n=13). Mice were anesthetized and the left common carotid was surgically exposed. Three-dimensional (3D; 2 spatial dimensions+time) and 4D (3 spatial dimensions+time) OCT images of the vessel lumen patency were evaluated. After perfusion, in situ OCT imaging was performed for statistical comparison with the in vivo results and final histology. Results— Intraoperative OCT imaging positively identified carotid plaque in 100% of ApoE −/− mice on HFD. ApoE −/− mice on HFD had a significantly decreased lumen patency when compared with that in wild-type mice ( P −/− mice on HFD ( P −/− on HFD). The findings were confirmed with OCT imaging after perfusion and histology. Conclusions— OCT imaging offers the potential for real-time, detailed vessel lumen evaluation, potentially improving surgical accuracy and outcomes during cerebrovascular neurosurgical procedures. Pravastatin significantly increases vessel lumen patency in the ApoE −/− mouse on HFD.

A popular approach, generalized estimating equations (GEE), has been applied to the multivariate accelerated failure time (AFT) model of the clustered and censored data. However, this method needs to estimate the correlation parameters and calculate the inverse of the correlation matrix. Meanwhile, the efficiency of the parameter estimators is low when the correlation structure is misspecified and/or the marginal distribution is heavy-tailed. This paper proposes using the quadratic inference functions (QIF) with a mixture correlation structure to estimate the coefficients in the multivariate AFT model, which can avoid estimating the correlation parameters and computing the inverse matrix of the correlation matrix. Moreover, the estimator derived from the QIF is consistent and asymptotically normal. Simulation studies indicate that the proposed method outperforms the method based on GEE when the marginal distribution has a heavy tail. Finally, the proposed method is used to analyze a real dataset for illustration.

BGA (ball-grid array) is an advanced electronic packaging technology that has increasingly become more important and demanding in microelectronic industry. However, no effective technique is available to inspect the performances of the welding points and its co-planarity. The moire fringe method is often employed to measure the three-dimensional (3D) shape of the welding spot on BGA, and a high-resolution CCD camera is utilised to capture the deformation stripe image. In order to gain high measuring accuracy, a frequency-shift moire fringe technique is proposed in this paper, in which three light-sources are deployed to create the fringe. The system parameters are designed to ensure the BGA ball height within exactly one grade moire fringe. By using zero-maximum equation transformation, the measuring range can be segregated into eight subsets. Equal-step interpolation and indexed table approaches are also introduced to greatly improve the measurement speed, so it may be useful for industrial on-line application. Finally, the predicted results based on the simulated images are presented, demonstrating that its measuring accuracy can be achieved to 5 micron.

We describe a novel common-path optical coherence tomography (CP-OCT) fiber probe design using a sapphire ball lens for cross-sectional imaging and sensing in retina vitrectomy surgery. Single mode Gaussian beam (TEM00) simulation was used to optimize lateral resolution and working distance (WD) of the common-path probe. A theoretical sensitivity model for CP-OCT was prosed to assess its optimal performance based an unbalanced photodetector configuration. Two probe designs with working distances (WD) 415μm and 1221μm and lateral resolution 11μm and 18μm, respectively were implemented with sensitivity up to 88dB. The designs are also fully compatible with conventional Michelson interferometer based OCT configurations. The reference plane of the probe, located at the distal beam exit interface of the single mode fiber (SMF), was encased within a 25-gauge hypodermic needle by the sapphire ball lens facilitates its applications in bloody and harsh environments. The performances of the fiber probe with 11μm of lateral resolution and 19μm of axial resolution were demonstrated by cross-sectional imaging of a cow cornea and retina in vitro with a 1310nm swept source OCT system. This probe was also attached to a piezoelectric motor for active compensation of physiological tremor for handheld retinal surgical tools.

We describe a novel dual-functional optical coherence tomography (OCT) system with both a fiber probe using a sapphire ball lens for cross-sectional imaging and sensing, and a 3-D bulk scanner for 3-D OCT imaging. A theoretical sensitivity model for Common Path (CP)-OCT was proposed to assess its optimal performance based on an unbalanced photodetector configuration. A probe design with working distances (WD) 415μm and lateral resolution 11 μm was implemented with sensitivity up to 88dB. To achieve high-speed data processing and real-time three-dimensional visualization, we use graphics processing unit (GPU) based real-time signal processing and visualization to boost the computing performance of swept source optical coherence tomography. Both the basal turn and facial nerve bundles inside the cadaveric human cochlea temporal bone can be clearly identified and 3D images can be rendered with the OCT system, which was integrated with a flexible robotic arm for robotically assisted microsurgery.

Carotid endarterectomy is a common vascular surgical procedure which may help prevent patients’ risk of having a stroke. A high resolution real-time imaging technique that can detect the position and size of vascular plaques would provide great value to reduce the risk level and increase the surgical outcome. Optical coherence tomography (OCT), as a high resolution high speed noninvasive imaging technique, was evaluated in this study. Twenty-four 24-week old apolipoprotein E-deficient (ApoE-/-) mice were divided into three groups with 8 in each. One served as the control group fed with normal diet. One served as the study group fed with high-fat diet to induce atherosclerosis. The last served as the treatment group fed with both high-fat diet and medicine to treat atherosclerosis. Full-range, complex-conjugate-free spectral-domain OCT was used to image the mouse aorta near the neck area in-vivo with aorta exposed to the imaging head through surgical procedure. 2D and 3D images of the area of interest were presented real-time through graphics processing unit accelerated algorithm. In-situ imaging of all the mice after perfusion were performed again to validate the invivo detection result and to show potential capability of OCT if combined with surgical saline flush. Later all the imaged arteries were stained with H and E to perform histology analysis. Preliminary results confirmed the accuracy and fast imaging speed of OCT imaging technique in determining atherosclerosis.

We describe a novel dual-functional optical coherence tomography (OCT) system with both a 3-D OCT real time scanner and a fiber probe using a sapphire ball lens for imaging and sensing the critical structures of the temporal bone. To prevent injury to facial nerve, 3-D visualization links anatomic landmarks to 3-D map of critical intracochlear structures. We used a graphics processing unit to boost the computing and 3-D rendering performance of swept source OCT. Both the intracochlear structures and facial nerve trunk of cadaveric human temporal bones are clearly identified with 3-D OCT volumetric rendering.

We describe a common-path swept source optical coherence tomography fiber probe design using a sapphire ball lens for cross-sectional imaging and sensing for retina vitrectomy surgery. The high refractive index (n=1.75) of the sapphire ball lens improves the focusing power and enables the probe to operate in the intraocular space. The highly precise spherical shape of the sapphire lens also reduces astigmatism and coma compared to fused nonspherical ball lenses. A theoretical sensitivity model for common-path optical coherence tomography (CP-OCT) was developed to assess its optimal performance based on an unbalanced photodetector configuration. Two probe designs-with working distances 415 and 1221 μm and lateral resolution 11 and 18 μm-were implemented with sensitivity up to 88 dB, which is significantly higher than previously reported CP-OCT probes. We assessed the performances of the fiber probes by cross-sectional imaging a bovine cornea and retina in air and in vitreous gel with a 1310 nm swept source OCT system. To the best of our knowledge, this is the first demonstration of sapphire ball lens-based CP-OCT probes directly inserted into the vitreous gel of a bovine eyeball for ocular imaging with a sensitivity approaching the theoretical limitation of CP-OCT.

Phase-sensitive adjuncts to optical coherence tomography (OCT) including Doppler and polarization-sensitive implementations allow for quantitative depth-resolved measurements of sample structure and dynamics including fluid flows and orientation of birefringent structures. The development of Fourier-domain OCT (FDOCT), particularly spectrometer-based spectral-domain systems with no moving parts (spectral-domain OCT or SDOCT), have greatly enhanced the phase stability of OCT systems particularly when implemented in a common-path geometry. The latter combination has given rise to a new class of nm-scale sensitive quantitative phase microscopies we have termed spectral domain phase microscopy. However, the phase information in all of these techniques suffers from a 2π ambiguity that limits resolvable pathlength differences to less than half the source center wavelength. This is problematic for situations such as cellular imaging, Doppler velocimetry, or polarization sensitive applications where it may be necessary to monitor sample profiles, displacements, phase differences, or refractive index variations which vary rapidly in space or time. A technique previously introduced in phase shifting interferometry uses phase information from multiple wavelengths to overcome this limitation. We show that by appropriate spectral windowing of the broadband light source already used in OCT, particularly by reshaping the source spectrum about two different center wavelengths, the resulting phase variation may be cast in terms of a much longer synthetic wavelength chosen to span the phase variation of interest. We show theoretically that the optimal choice of synthetic wavelength depends upon a tradeoff between the minimum resolvable phase and the length of unambiguous phase measurement. We demonstrate this technique using a broadband source centered at 790 nm by correctly reconstructing the phase profile from a phantom sample containing multiple 2π wrapping artifacts at the center wavelength and compare our result with atomic force microscopy.

Phase sensitive optical coherence tomography allows for nanometer scale resolution of cellular dynamics, but suffers from phase wrapping artifacts. We present a synthetic wavelength spectral windowing technique for phase ambiguity removal in phase based OCT.