Self-assembled supermolecular hydrogels of therapeutic agents without structural modification are of great significance in biomedical applications. Nevertheless, the complex conformations and elusive interactions of therapeutic molecules limit the controlled assembly of hydrogels. Molecules at the interface might have different arrangements and assemblies compared to those in bulk aqueous solution, which could potentially alter the selectivity of supramolecular polymorphs. However, this effect is still not well understood. Here, we demonstrate the interface-induced self-assembly of fibers for hydrogels, which is distinct from the spherical aggregates in the bulk aqueous solution, using cephradine (CEP) as a model compound. This phenomenon is caused by the packing of anisotropic molecules at the interface, and it can be applied to control the supramolecular polymorphism for the direct self-assembly of hydrogels of therapeutic agents. The interface-induced hydrogel exhibits a high degree of adjustable release and a long-acting bactericidal effect.

Spiny lobsters (Decapoda: Palinuridae) in the genus Panulirus are targets of lucrative fisheries globally and have relevant ecological functions in tropical and subtropical environments. Only a few, but increasing, number of genetic and genomic resources exist for them. Nuclear and mitochondrial genome assemblies can provide insights into their phylogenetic relationships and support fishery management strategies in species that are heavily exploited. Herein, using Illumina short reads whole genome sequencing, we assembled the nuclear and mitochondrial genomes of a total of 14 species. Genomic DNA was extracted from specimens deposited at Clemson University Crustacean Collection and sequenced in a HiSeq X Ten system. The number of paired-end (PE) reads generated for the different studied species varied between 219,917,346 in P. argus and 70,215,423 in P. cygnus. Nuclear and mitochondrial genomes were \'de novo\' assembled. Nuclear genomes ranged between 1,624,400,357 bp in P. guttatus and 935,571,898 bp in P. cygnus with scaffold numbers varying between 466,583 in P. versicolor and 852,228 in P. longipes. Mitochondrial genomes varied between 15,613 bp and 15,768 bp in P. pascuensis and P. versicolor, respectively. The totality of the short reads, nuclear, and mitochondrial genome assemblies are available at NCBI\'s GenBank.

Research on supergenes, non-recombining genomic regions housing tightly linked genes that control complex phenotypes, has recently gained prominence in genomics. Heterostyly, a floral heteromorphism promoting outcrossing in several angiosperm families, is controlled by the S-locus supergene. The S-locus has been studied primarily in closely related Primula species and, more recently, in other groups that independently evolved heterostyly. However, it remains unknown whether genetic architecture and composition of the S-locus are maintained among species that share a common origin of heterostyly and subsequently diverged across larger time scales. To address this research gap, we present a chromosome-scale genome assembly of Primula edelbergii, a species that shares the same origin of heterostyly with Primula veris (whose S-locus has been characterized) but diverged from it 18 million years ago. Comparative genomic analyses between these two species allowed us to show, for the first time, that the S-locus can \'jump\' (i.e. translocate) between chromosomes maintaining its function in controlling heterostyly. Additionally, we found that four S-locus genes were conserved but reshuffled within the supergene, seemingly without affecting their expression, thus we could not detect changes explaining the lack of self-incompatibility in P. edelbergii. Furthermore, we confirmed that the S-locus is not undergoing genetic degeneration. Finally, we investigated P. edelbergii evolutionary history within Ericales in terms of whole genome duplications and transposable element accumulation. In summary, our work provides a valuable resource for comparative analyses aimed at investigating the genetics of heterostyly and the pivotal role of supergenes in shaping the evolution of complex phenotypes.

This study describes the development of a resource module that is part of a learning platform named \"NIGMS Sandbox for Cloud-based Learning\" (https://github.com/NIGMS/NIGMS-Sandbox). The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox at the beginning of this Supplement. This module delivers learning materials on de novo transcriptome assembly using Nextflow in an interactive format that uses appropriate cloud resources for data access and analysis. Cloud computing is a powerful new means by which biomedical researchers can access resources and capacity that were previously either unattainable or prohibitively expensive. To take advantage of these resources, however, the biomedical research community needs new skills and knowledge. We present here a cloud-based training module, developed in conjunction with Google Cloud, Deloitte Consulting, and the NIH STRIDES Program, that uses the biological problem of de novo transcriptome assembly to demonstrate and teach the concepts of computational workflows (using Nextflow) and cost- and resource-efficient use of Cloud services (using Google Cloud Platform). Our work highlights the reduced necessity of on-site computing resources and the accessibility of cloud-based infrastructure for bioinformatics applications.

Single-walled carbon nanotubes (SWCNTs) present excellent electronic and mechanical properties desired in wearable and flexible devices. The preparation of SWCNT films is the first step for fabricating various devices. This work developed a scalable and feasible method to assemble SWCNT thin films on water surfaces based on Marangoni flow induced by surface tension gradient. The films possess a large area of 40 cm × 30 cm (extensible), a tunable thickness of 15∼150 nm, a high transparency of up to 96%, and a decent conductivity. They are ready to be directly transferred to various substrates, including flexible ones. Flexible strain sensors were fabricated with the films on flexible substrates. These sensors worked with high sensitivity and repeatability. By realizing multi-functional human motion sensing, including responding to voices, monitoring artery pulses, and detecting knuckle and muscle actions, the assembled SWCNT films demonstrated the potential for application in smart devices.

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Metagenome community analyses, driven by the continued development in sequencing technology, is rapidly providing insights in many aspects of microbiology and becoming a cornerstone tool. Illumina, Oxford Nanopore Technologies (ONT) and Pacific Biosciences (PacBio) are the leading technologies, each with their own advantages and drawbacks. Illumina provides accurate reads at a low cost, but their length is too short to close bacterial genomes. Long reads overcome this limitation, but these technologies produce reads with lower accuracy (ONT) or with lower throughput (PacBio high-fidelity reads). In a critical first analysis step, reads are assembled to reconstruct genomes or individual genes within the community. However, to date, the performance of existing assemblers has never been challenged with a complex mock metagenome. Here, we evaluate the performance of current assemblers that use short, long or both read types on a complex mock metagenome consisting of 227 bacterial strains with varying degrees of relatedness. We show that many of the current assemblers are not suited to handle such a complex metagenome. In addition, hybrid assemblies do not fulfil their potential. We conclude that ONT reads assembled with CANU and Illumina reads assembled with SPAdes offer the best value for reconstructing genomes and individual genes of complex metagenomes, respectively.

OCCUPATIONAL APPLICATIONSIn the context of Industry 5.0, our study advances manufacturing factory layout planning by integrating multi-objective optimization with nature-inspired algorithms and a digital human modeling tool. This approach aims to overcome the limitations of traditional planning methods, which often rely on engineers\' expertise and inputs from various functions in a company, leading to slow processes and risk of human errors. By focusing the multi-objective optimization on three primary targets, our methodology promotes objective and efficient layout planning, simultaneously considering worker well-being and system performance efficiency. Illustrated through a pedal car assembly station layout case, we demonstrate how layout planning can transition into a transparent, cross-disciplinary, and automated activity. This methodology provides multi-objective decision support, showcasing a significant step forward in manufacturing factory layout design practices.
Rationale: Integrating multi-objective optimization in manufacturing layout planning addresses simultaneous considerations of productivity, worker well-being, and space efficiency, moving beyond traditional, expert-reliant methods that often overlook critical design aspects. Leveraging nature-inspired algorithms and a digital human modeling tool, this study advances a holistic, automated design process in line with Industry 5.0. Purpose: This research demonstrates an innovative approach to manufacturing layout optimization that simultaneously considers worker well-being and system performance. Utilizing the Non-dominated Sorting Genetic Algorithm II (NSGA-II) and Particle Swarm Optimization (PSO) alongside a Digital Human Modeling (DHM) tool, the study proposes layouts that equally prioritize ergonomic factors, productivity, and area utilization. Methods: Through a pedal car assembly station case, the study illustrates the transition of layout planning into a transparent, cross-disciplinary, and automated process. This method offers objective decision support, balancing diverse objectives concurrently. Results: The optimization results obtained from the NSGA-II and PSO algorithms represent feasible non-dominated solutions of layout proposals, with the NSGA-II algorithm finding a solution superior in all objectives compared to the expert engineer-designed start solution for the layout. This demonstrates the presented method’s capacity to refine layout planning practices significantly. Conclusions: The study validates the effectiveness of combining multi-objective optimization with digital human modeling in manufacturing layout planning, aligning with Industry 5.0’s emphasis on human-centric processes. It proves that operational efficiency and worker well-being can be simultaneously considered and presents future potential manufacturing design advancements. This approach underscores the necessity of multi-objective consideration for optimal layout achievement, marking a progressive step in meeting modern manufacturing’s complex demands.

There are a staggering number of publicly available bacterial genome sequences (at writing, 2.0 million assemblies in NCBI\'s GenBank alone), and the deposition rate continues to increase. This wealth of data begs for phylogenetic analyses to place these sequences within an evolutionary context. A phylogenetic placement not only aids in taxonomic classification, but informs the evolution of novel phenotypes, targets of selection, and horizontal gene transfer. Building trees from multi-gene codon alignments is a laborious task that requires bioinformatic expertise, rigorous curation of orthologs, and heavy computation. Compounding the problem is the lack of tools that can streamline these processes for building trees from large scale genomic data. Here we present OrthoPhyl, which takes bacterial genome assemblies and reconstructs trees from whole genome codon alignments. The analysis pipeline can analyze an arbitrarily large number of input genomes (>1200 tested here) by identifying a diversity spanning subset of assemblies and using these genomes to build gene models to infer orthologs in the full dataset. To illustrate the versatility of OrthoPhyl, we show three use-cases: E. coli/Shigella, Brucella/Ochrobactrum, and the order Rickettsiales. We compare trees generated with OrthoPhyl to trees generated with kSNP3 and GToTree along with published trees using alternative methods. We show that OrthoPhyl trees are consistent with other methods while incorporating more data, allowing for greater numbers of input genomes, and more flexibility of analysis.

The development of smart systems for pesticidal delivery presents a significant advancement in enhancing the utilization efficiency of pesticides and mitigating environmental risks. Here an acid-responsive pesticidal delivery system using microspheres formed by the self-assembly of halloysite clay nanotubes (HNTs) is proposed. Insecticide avermectin (AVM) and herbicide prometryn (PMT) are used as two models of hydrophobic pesticide and encapsulated within the porous microspheres, followed by a coating of tannic acid/iron (TA/FeIII) complex films to generate two controlled-release pesticides, named as HCEAT and HCEPT, resulting in the loading capacity of AVM and PMT being 113.3 and 120.3 mg g-1, respectively. Both HCEAT and HCEPT exhibit responsiveness to weak acid, achieving 24 h-release ratios of 85.8% and 80.5% at a pH of 5.5. The experiment and simulation results indicate that the coordination interaction between EDTA2- and Ca2+ facilitates the spherical aggregation of HNTs. Furthermore, these novel pesticide formulations demonstrate better resistance against ultraviolet (UV) irradiation, higher foliar affinity, and less leaching effect, with negligible impact of the carrier material on plants and terrestrial organisms. This work presents a promising approach toward the development of efficient and eco-friendly pesticide formulations, greatly contributing to the sustainable advancement of agriculture.