3D printable and mechanically tunable hydrogels achieved through hydrophobic and ionic interactions.

Thermal stiffening materials are commonly applied in the aerospace and automotive industries, among others, since their dimensional stabilities and stiffness characteristics improve at high temperatures. In this study, temperature-triggered modulus-tunable hydrogels were prepared by combining Pluronic F-127 with charged polymers. Pluronic F-127, a triblock copolymer micelle, provided three-dimensional printing capabilities of fine resolution with high viscosity, while hydrophobic and ionic interactions among polymer networks provided thermal stiffening. The hydrogel ink's printability was demonstrated by successfully creating complex 3D structures. A calcium ion carrying a hydrophobic propionate and carboxylate group in polymer chains was used to form additional physical crosslinking at high temperature, ultimately leading to the thermal stiffening effect without volume change. The thermal stiffening behavior was found to be fully reversible and repeatable. Finally, to demonstrate the versatility of this work, graphene oxide was added to produce a light-controllable modulus based on its photothermal properties.

CWAS-Plus: estimating category-wide association of rare noncoding variation from whole-genome sequencing data with cell-type-specific functional data.

Variants in cis-regulatory elements link the noncoding genome to human pathology; however, detailed analytic tools for understanding the association between cell-level brain pathology and noncoding variants are lacking. CWAS-Plus, adapted from a Python package for category-wide association testing (CWAS), enhances noncoding variant analysis by integrating both whole-genome sequencing (WGS) and user-provided functional data. With simplified parameter settings and an efficient multiple testing correction method, CWAS-Plus conducts the CWAS workflow 50 times faster than CWAS, making it more accessible and user-friendly for researchers. Here, we used a single-nuclei assay for transposase-accessible chromatin with sequencing to facilitate CWAS-guided noncoding variant analysis at cell-type-specific enhancers and promoters. Examining autism spectrum disorder WGS data (n = 7280), CWAS-Plus identified noncoding de novo variant associations in transcription factor binding sites within conserved loci. Independently, in Alzheimer's disease WGS data (n = 1087), CWAS-Plus detected rare noncoding variant associations in microglia-specific regulatory elements. These findings highlight CWAS-Plus's utility in genomic disorders and scalability for processing large-scale WGS data and in multiple-testing corrections. CWAS-Plus and its user manual are available at https://github.com/joonan-lab/cwas/ and https://cwas-plus.readthedocs.io/en/latest/, respectively.

READRetro: natural product biosynthesis predicting with retrieval-augmented dual-view retrosynthesis.

Plants, as a sessile organism, produce various secondary metabolites to interact with the environment. These chemicals have fascinated the plant science community because of their ecological significance and notable biological activity. However, predicting the complete biosynthetic pathways from target molecules to metabolic building blocks remains a challenge. Here, we propose retrieval-augmented dual-view retrosynthesis (READRetro) as a practical bio-retrosynthesis tool to predict the biosynthetic pathways of plant natural products. Conventional bio-retrosynthesis models have been limited in their ability to predict biosynthetic pathways for natural products. READRetro was optimized for the prediction of complex metabolic pathways by incorporating cutting-edge deep learning architectures, an ensemble approach, and two retrievers. Evaluation of single- and multi-step retrosynthesis showed that each component of READRetro significantly improved its ability to predict biosynthetic pathways. READRetro was also able to propose the known pathways of secondary metabolites such as monoterpene indole alkaloids and the unknown pathway of menisdaurilide, demonstrating its applicability to real-world bio-retrosynthesis of plant natural products. For researchers interested in the biosynthesis and production of secondary metabolites, a user-friendly website (https://readretro.net) and the open-source code of READRetro have been made available.

Highly efficient CRISPR/Cas9-RNP mediated CaPAD1 editing in protoplasts of three pepper (Capsicum annuum L.) cultivars.

Parthenocarpy, characterized by seedless fruit development without pollination or fertilization, offers the advantage of consistent fruit formation, even under challenging conditions such as high temperatures. It can be induced by regulating auxin homeostasis; PAD1 (PARENTAL ADVICE-1) is an inducer of parthenocarpy in Solanaceae plants. However, precise editing of PAD1 is not well studied in peppers. Here, we report a highly efficient clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) ribonucleoprotein (RNP) for CaPAD1 editing in three valuable cultivars of pepper (Capsicum annuum L.): Dempsey, a gene-editable bell pepper; C15, a transformable commercial inbred line; and Younggo 4, a Korean landrace. To achieve the seedless pepper trait under high temperatures caused by unstable climate change, we designed five single guide RNAs (sgRNAs) targeting the CaPAD1 gene. We evaluated the in vitro on-target activity of the RNP complexes in three cultivars. Subsequently, we introduced five CRISPR/Cas9-RNP complexes into protoplasts isolated from three pepper leaves and compared indel frequencies and patterns through targeted deep sequencing analyses. We selected two sgRNAs, sgRNA2 and sgRNA5, which had high in vivo target efficiencies for the CaPAD1 gene across the three cultivars and were validated as potential off-targets in their genomes. These findings are expected to be valuable tools for developing new seedless pepper cultivars through precise molecular breeding of recalcitrant crops in response to climate change.

Bright Bifacial White-Light Illumination by Highly Deformable Electroluminescent Devices Based on Transparent Ionic-Hydrogel Electrodes and Quantum-Dot Color Conversion.

Deformable alternating-current electroluminescent (ACEL) devices are of increasing interest because of their potential to drive innovation in soft optoelectronics. Despite the research focus on efficient white ACEL devices, achieving deformable devices with high luminance remains difficult. In this study, this challenge is addressed by fabricating white ACEL devices using color-conversion materials, transparent and durable hydrogel electrodes, and high-k nanoparticles. The incorporation of quantum dots enables the highly efficient generation of red and green light through the color conversion of blue electroluminescence. Although the ionic-hydrogel electrode provides high toughness, excellent light transmittance, and superior conductivity, the luminance of the device is remarkably enhanced by the incorporation of a high-k dielectric, BaTiO3. The fabricated ACEL device uniformly emits very bright white light (489 cd m-2) with a high color-rendering index (91) from both the top and bottom. The soft and tough characteristics of the device allow seamless operation in various deformed states, including bending, twisting, and stretching up to 400%, providing a promising platform for applications in a wide array of soft optoelectronics.

CWAS-Plus: Estimating category-wide association of rare noncoding variation from whole-genome sequencing data with cell-type-specific functional data.

Variants in cis-regulatory elements link the noncoding genome to human brain pathology; however, detailed analytic tools for understanding the association between cell-level brain pathology and noncoding variants are lacking. CWAS-Plus, adapted from a Python package for category-wide association testing (CWAS) employs both whole-genome sequencing and user-provided functional data to enhance noncoding variant analysis, with a faster and more efficient execution of the CWAS workflow. Here, we used single-nuclei assay for transposase-accessible chromatin with sequencing to facilitate CWAS-guided noncoding variant analysis at cell-type specific enhancers and promoters. Examining autism spectrum disorder whole-genome sequencing data (n = 7,280), CWAS-Plus identified noncoding de novo variant associations in transcription factor binding sites within conserved loci. Independently, in Alzheimer's disease whole-genome sequencing data (n = 1,087), CWAS-Plus detected rare noncoding variant associations in microglia-specific regulatory elements. These findings highlight CWAS-Plus's utility in genomic disorders and scalability for processing large-scale whole-genome sequencing data and in multiple-testing corrections. CWAS-Plus and its user manual are available at https://github.com/joonan-lab/cwas/ and https://cwas-plus.readthedocs.io/en/latest/, respectively.

SpatialSPM: statistical parametric mapping for the comparison of gene expression pattern images in multiple spatial transcriptomic datasets.

Spatial transcriptomic (ST) techniques help us understand the gene expression levels in specific parts of tissues and organs, providing insights into their biological functions. Even though ST dataset provides information on the gene expression and its location for each sample, it is challenging to compare spatial gene expression patterns across tissue samples with different shapes and coordinates. Here, we propose a method, SpatialSPM, that reconstructs ST data into multi-dimensional image matrices to ensure comparability across different samples through spatial registration process. We demonstrated the applicability of this method by kidney and mouse olfactory bulb datasets as well as mouse brain ST datasets to investigate and directly compare gene expression in a specific anatomical region of interest, pixel by pixel, across various biological statuses. Beyond traditional analyses, SpatialSPM is capable of generating statistical parametric maps, including T-scores and Pearson correlation coefficients. This feature enables the identification of specific regions exhibiting differentially expressed genes across tissue samples, enhancing the depth and specificity of ST studies. Our approach provides an efficient way to analyze ST datasets and may offer detailed insights into various biological conditions.

Development of finely tuned liposome nanoplatform for macrophage depletion.

BACKGROUND: Immunotherapy with clodronate-encapsulated liposomes, which induce macrophage depletion, has been studied extensively. However, previously reported liposomal formulation-based drugs (Clodrosome® and m-Clodrosome®) are limited by their inconsistent size and therapeutic efficacy. Thus, we aimed to achieve consistent therapeutic effects by effectively depleting macrophages with uniform-sized liposomes. RESULTS: We developed four types of click chemistry-based liposome nanoplatforms that were uniformly sized and encapsulated with clodronate, for effective macrophage depletion, followed by conjugation with Man-N3 and radiolabeling. Functionalization with Man-N3 improves the specific targeting of M2 macrophages, and radioisotope labeling enables in vivo imaging of the liposome nanoplatforms. The functionalized liposome nanoplatforms are stable under physiological conditions. The difference in the biodistribution of the four liposome nanoplatforms in vivo were recorded using positron emission tomography imaging. Among the four platforms, the clodronate-encapsulated mannosylated liposome effectively depleted M2 macrophages in the normal liver and tumor microenvironment ex vivo compared to that by Clodrosome® and m-Clodrosome®. CONCLUSION: The newly-developed liposome nanoplatform, with finely tuned size control, high in vivo stability, and excellent ex vivo M2 macrophage targeting and depletion effects, is a promising macrophage-depleting agent.