Dynamic microphysiological system chip platform for high-throughput, customizable, and multi-dimensional drug screening.

Spheroids and organoids have attracted significant attention as innovative models for disease modeling and drug screening. By employing diverse types of spheroids or organoids, it is feasible to establish microphysiological systems that enhance the precision of disease modeling and offer more dependable and comprehensive drug screening. High-throughput microphysiological systems that support optional, parallel testing of multiple drugs have promising applications in personalized medical treatment and drug research. However, establishing such a system is highly challenging and requires a multidisciplinary approach. This study introduces a dynamic Microphysiological System Chip Platform (MSCP) with multiple functional microstructures that encompass the mentioned advantages. We developed a high-throughput lung cancer spheroids model and an intestine-liver-heart-lung cancer microphysiological system for conducting parallel testing on four anti-lung cancer drugs, demonstrating the feasibility of the MSCP. This microphysiological system combines microscale and macroscale biomimetics to enable a comprehensive assessment of drug efficacy and side effects. Moreover, the microphysiological system enables evaluation of the real pharmacological effect of drug molecules reaching the target lesion after absorption by normal organs through fluid-based physiological communication. The MSCP could serves as a valuable platform for microphysiological system research, making significant contributions to disease modeling, drug development, and personalized medical treatment.

Patterning Techniques Based on Metallized Electrospun Nanofibers for Advanced Stretchable Electronics.

Stretchable electronics have experienced remarkable progress, especially in sensors and wireless communication systems, attributed to their ability to conformably contact with rough or uneven surfaces. However, the development of complex, multifunctional, and high-precision stretchable electronics faces substantial challenges, including instability at rigid-soft interfaces and incompatibility with traditional high-precision patterning technologies. Metallized electrospun nanofibers emerge as a promising conductive filler, offering exceptional stretchability, electrical conductivity, transparency, and compatibility with existing patterning technologies. Here, this review focuses on the fundamental properties, preparation processes, patterning technologies, and application scenarios of conductive stretchable composites based on metallized nanofibers. Initially, it introduces the fabrication processes of metallized electrospun nanofibers and their advantages over alternative materials. It then highlights recent progress in patterning technologies, including collector collection, vapor deposition with masks, and lithography, emphasizing their role in enhancing precision and integration. Furthermore, the review shows the broad applicability and potential influence of metallized electrospun nanofibers in various fields through their use in sensors, wireless systems, semiconductor devices, and intelligent healthcare solutions. Ultimately, this review seeks to spark further innovation and address the prevailing challenges in stretchable electronics, paving the way for future breakthroughs in this dynamic field.

Ca2+ storage function is altered in the sarcoplasmic reticulum of skeletal muscle lacking mitsugumin 23.

Mitsugumin 23 (MG23) has been identified as a ball-shaped cation channel in the sarcoplasmic reticulum (SR) but its physiological role remains unclear. This study aimed to examine the contribution of MG23 to Ca2+ storage function in skeletal muscle by using Mg23-knockout (Mg23-/-) mice. There was no difference in the isometric specific force of the extensor digitorum longus (EDL) and soleus (SOL) muscles between Mg23-/- and wild-type (Wt) mice. In Mg23-/- mice, the calsequestrin 2 content in the EDL muscle and SR Ca2+-ATPase 2 content in the SOL were increased. We have examined SR and myofibril functions using mechanically skinned fibers and determined their fiber types based on the response to Sr2+, which showed that Mg23-/- mice, compared with Wt, had: 1) elevated total Ca2+ content in the membranous components including SR, mitochondria, and transverse tubular system referred to as endogenous Ca2+ content, in both type I and II fibers of the EDL and SOL; 2) increased maximal Ca2+ content in both type I and II fibers of the EDL and SOL; 3) decreased SR Ca2+ leakage in type I fibers of the SOL; and 4) enhanced SR Ca2+ uptake in type I fibers of the SOL, although myofibril function was not different in both type I and II fibers of the SOL and EDL muscles. These results suggest that MG23 decreases SR Ca2+ storage in both type I and type II fibers, likely due to increased SR Ca2+ leakage.NEW & NOTEWORTHY The function of calcium storage within sarcoplasmic reticulum (SR) plays a pivotal role in influencing the health and disease states of skeletal muscle. In the present study, we demonstrated that mitsgumin 23, a novel non-selective cation channel, modifies SR Ca2+ storage in skeletal muscle fibers. These findings provide valuable insights into the physiological regulation of Ca2+ in skeletal muscle, offering significant potential for uncovering the mechanisms underlying muscle fatigue, muscle adaptation, and muscle diseases.

Deep Learning Model for Static Ocular Torsion Detection Using Synthetically Generated Fundus Images.

Purpose: The objective of the study is to develop deep learning models using synthetic fundus images to assess the direction (intorsion versus extorsion) and amount (physiologic versus pathologic) of static ocular torsion. Static ocular torsion assessment is an important clinical tool for classifying vertical ocular misalignment; however, current methods are time-intensive with steep learning curves for frontline providers. Methods: We used a dataset (n = 276) of right eye fundus images. The disc-foveal angle was calculated using ImageJ to generate synthetic images via image rotation. Using synthetic datasets (n = 12,740 images per model) and transfer learning (the reuse of a pretrained deep learning model on a new task), we developed a binary classifier (intorsion versus extorsion) and a multiclass classifier (physiologic versus pathologic intorsion and extorsion). Model performance was evaluated on unseen synthetic and nonsynthetic data. Results: On the synthetic dataset, the binary classifier had an accuracy and area under the receiver operating characteristic curve (AUROC) of 0.92 and 0.98, respectively, whereas the multiclass classifier had an accuracy and AUROC of 0.77 and 0.94, respectively. The binary classifier generalized well on the nonsynthetic data (accuracy = 0.94; AUROC = 1.00). Conclusions: The direction of static ocular torsion can be detected from synthetic fundus images using deep learning methods, which is key to differentiate between vestibular misalignment (skew deviation) and ocular muscle misalignment (superior oblique palsies). Translational Relevance: Given the robust performance of our models on real fundus images, similar strategies can be adopted for deep learning research in rare neuro-ophthalmologic diseases with limited datasets.

Enhanced Electrochemical Performance of the LiNi0.5Mn1.5O4 Cathode Material by the Construction of Uniform Lithium Silicate Nanoshells.

In order to alleviate the rapid capacity decay caused by the instability of the crystal structure and electrode/electrolyte interface, a series of Li2SiO3-coated LiNi0.5Mn1.5O4 materials have been prepared via the lithium acetate-assisted sol-gel method followed by a short-term calcination process. During the sol-gel process, TEOS is hydrolyzed, condensed, and polymerized with the assistance of lithium acetate to form a Li+-embedded [Si-O-Si]n network structure to ensure the uniformity of the coating. By changing the amount of TEOS and lithium acetate, the coating thickness can be precisely controlled, whose effects on the structural and electrochemical properties of LiNi0.5Mn1.5O4 materials are intensively investigated. The results show that the material with an appropriate thickness of Li2SiO3 coating exhibits a larger primary particle size and reduced secondary particle agglomeration. The uniform Li2SiO3 coating with appropriate thickness can not only improve Li+ ion diffusion kinetics but also suppress side reactions and CEI growth at the electrode/electrolyte interface. Besides, the interaction of Li2SiO3 with HF can alleviate electrode corrosion and the dissolution of transition metal ions. All the abovementioned factors together promote the significant improvement of the electrochemical performance of Li2SiO3-coated LiNi0.5Mn1.5O4 materials.