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The CRISPR-Cas9 technology has the potential to revolutionize the treatment of various diseases, including Rett syndrome, by enabling the correction of genes or mutations in human patient cells. However, several challenges need to be addressed before its widespread clinical application. These challenges include the low delivery efficiencies to target cells, the actual efficiency of the genome-editing process, and the precision with which the CRISPR-Cas system operates. Herein, the study presents a Magnetic Nanoparticle-Assisted Genome Editing (MAGE) platform, which significantly improves the transfection efficiency, biocompatibility, and genome-editing accuracy of CRISPR-Cas9 technology. To demonstrate the feasibility of the developed technology, MAGE is applied to correct the mutated MeCP2 gene in induced pluripotent stem cell-derived neural progenitor cells (iPSC-NPCs) from a Rett syndrome patient. By combining magnetofection and magnetic-activated cell sorting, MAGE achieves higher multi-plasmid delivery (99.3%) and repairing efficiencies (42.95%) with significantly shorter incubation times than conventional transfection agents without size limitations on plasmids. The repaired iPSC-NPCs showed similar characteristics as wild-type neurons when they differentiated into neurons, further validating MAGE and its potential for future clinical applications. In short, the developed nanobio-combined CRISPR-Cas9 technology offers the potential for various clinical applications, particularly in stem cell therapies targeting different genetic diseases.

Cellular dynamics and fate decision in early human embryogenesis remain largely unknown owing to the challenges of performing studies in human embryos.sup.1. Here, we explored whole-genomes of 334 single-cell colonies and targeted deep sequences of 379 bulk tissues obtained from various anatomical locations of seven recently deceased adult human donors. Using somatic mutations as an intrinsic barcode, we reconstructed early cellular phylogenies that demonstrate (1) an endogenous mutational rate that is higher in the first cell division but decreases to approximately one per cell per cell division later in life; (2) universal unequal contribution of early cells to embryo proper, resulting from early cellular bottlenecks that stochastically set aside epiblast cells within the embryo; (3) examples of varying degrees of early clonal imbalances between tissues on the left and right sides of the body, different germ layers and specific anatomical parts and organs; (4) emergence of a few ancestral cells that will substantially contribute to adult cell pools in blood and liver; and (5) presence of mitochondrial DNA heteroplasmy in the fertilized egg. Our approach also provides insights into the age-related mutational processes and loss of sex chromosomes in normal somatic cells. In sum, this study provides a foundation for future studies to complete cellular phylogenies in human embryogenesis. Adult human tissues from diverse sites around the body are used to reconstruct cellular phylogenies from early development, using somatic mutations as an internal barcode., Author(s): Seongyeol Park [sup.1] [sup.2] , Nanda Maya Mali [sup.3] , Ryul Kim [sup.1] , Jeong-Woo Choi [sup.3] [sup.4] , Junehawk Lee [sup.5] , Joonoh Lim [sup.1] , Jung Min [...]

Polymer actuators are promising, as they are widely used in various fields, such as sensors and soft robotics, for their unique properties, such as their ability to form high-quality films, sensitivity, and flexibility. In recent years, advances in structural and fabrication processes have significantly improved the reliability of polymer sensing-based actuators. Polymer actuators have attracted considerable attention for use in artificial or biohybrid systems, as they have the potential to operate under diverse conditions with high durability. This review briefly describes different types of polymer actuators and provides an understanding of their working mechanisms. It focuses on actuation modes controlled by diverse or multiple stimuli. Furthermore, it discusses the fabrication processes of polymer actuators; the fabrication process is an important consideration in the development of high-quality actuators with sensing properties for a wide range of applications in soft robotics. Additionally, the high potential of polymer actuators for use in sensing technology is examined, and the latest developments in the field of polymer actuators, such as the development of biohybrid polymers and the use of polymer actuators in 4D printing, are briefly described. [ABSTRACT FROM AUTHOR]

Accurate measurement of vital signs are important at skilled nursing facilities (SNF). Recent technological advancements now enable automated vital sign measurements. This overcomes the limitations of traditional manual vital sign measurement, which is time-consuming and error-prone. We present a novel case where continuous vital sign measurement was used to detect meaningful vital sign changes that led to early detection of a COVID-19 outbreak at a SNF. Residents were continuously monitored for changes to baseline respiratory rate and heart rate and with a Probability of Change (POC). Variations in baseline respiratory rate and heart rate occurred in 66% and 42%, respectively, of COVID-19 positive individuals; 83% of participants had statistically significant variations in either vital sign. Clinical investigations are typically triggered by vital signs outside normal ranges. We present a novel methodology to detect subtle vital sign changes that can lead to earlier diagnosis, treatment, and recovery from infections, like COVID-19. [ABSTRACT FROM AUTHOR]

Pyocyanin is considered a maker of Pseudomonas aeruginosa (P. aeruginosa) infection. Pyocyanin is among the toxins released by the P. aeruginosa bacteria. Therefore, the development of a direct detection of PYO is crucial due to its importance. Among the different optical techniques, the Raman technique showed unique advantages because of its fingerprint data, no sample preparation, and high sensitivity besides its ease of use. Noble metal nanostructures were used to improve the Raman response based on the surface-enhanced Raman scattering (SERS) technique. Anodic metal oxide attracts much interest due to its unique morphology and applications. The porous metal structure provides a large surface area that could be used as a hard template for periodic nanostructure array fabrication. Porous shapes and sizes could be controlled by controlling the anodization parameters, including the anodization voltage, current, temperature, and time, besides the metal purity and the electrolyte type/concentration. The anodization of aluminum foil results in anodic aluminum oxide (AAO) formation with different roughness. Here, we will use the roughness as hotspot centers to enhance the Raman signals. Firstly, a thin film of gold was deposited to develop gold/alumina (Au/AAO) platforms and then applied as SERS-active surfaces. The morphology and roughness of the developed substrates were investigated using scanning electron microscopy (SEM) and atomic force microscopy (AFM) techniques. The Au/AAO substrates were used for monitoring pyocyanin secreted from Pseudomonas aeruginosa microorganisms based on the SERS technique. The results showed that the roughness degree affects the enhancement efficiency of this sensor. The high enhancement was obtained in the case of depositing a 30 nm layer of gold onto the second anodized substrates. The developed sensor showed high sensitivity toward pyocyanin with a limit of detection of 96 nM with a linear response over a dynamic range from 1 µM to 9 µM. [ABSTRACT FROM AUTHOR]

Biohybrid robots have been developed for biomedical applications and industrial robotics. However, the biohybrid robots have limitations to be applied in neurodegenerative disease research due to the absence of a central nervous system. In addition, the organoids‐on‐a‐chip has not yet been able to replicate the physiological function of muscle movement in the human motor system, which is essential for evaluating the accuracy of the drugs used for treating neurodegenerative diseases. Here, a human motor system‐based biohybrid robot‐on‐a‐chip composed of a brain organoid, multi‐motor neuron spheroids, and muscle bundle on solid substrateis proposed to evaluate the drug effect on neurodegenerative diseases for the first time. The electrophysiological signals from the cerebral organoid induced the muscle bundle movement through motor neuron spheroids. To evaluate the drug effect on Parkinson's disease (PD), a patient‐derived midbrain organoid is generated and incorporated into a biohybrid robot‐on‐a‐chip. The drug effect on PD is successfully evaluated by measuring muscle bundle movement. The muscle bundle movement of PD patient‐derived midbrain organoid‐based biohybrid robot‐on‐a‐chip is increased from 4.5 ± 0.99 µm to 18.67 ± 2.25 µm in response to levodopa. The proposed human motor system‐based biohybrid robot‐on‐a‐chip can serve as a standard biohybrid robot model for drug evaluation. [ABSTRACT FROM AUTHOR]

As IT technology advances, the number and types of applications, such as SNS, content, and shopping, have increased across various fields, leading to the emergence of complex and diverse application traffic. As a result, the demand for effective network operation, management, and analysis has increased. In particular, service or application traffic classification research is an important area of study in network management. Web services are composed of a combination of multiple applications, and one or more application traffic can be mixed within service traffic. However, most existing research only classifies application traffic by service unit, resulting in high misclassification rates and making detailed management impossible. To address this issue, this paper proposes three multitask learning methods for application traffic classification using the relationships among tasks composed of browsers, protocols, services, and application units. The proposed methods aim to improve classification performance under the assumption that there are relationships between tasks. Experimental results demonstrate that by utilizing relationships between various tasks, the proposed method can classify applications with 4.4%p higher accuracy. Furthermore, the proposed methods can provide network administrators with information about multiple perspectives with high confidence, and the generalized multitask methods are freely portable to other backbone networks. [ABSTRACT FROM AUTHOR]