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Recent advancements in spatial transcriptomics (ST) technologies offer unprecedented opportunities to unveil the spatial heterogeneity of gene expression and cell states within tissues. Despite these capabilities of the ST data, accurately dissecting spatiotemporal structures (e.g., spatial domains, temporal trajectories, and functional interactions) remains challenging. Here, we introduce a computational framework, PearlST (partial differential equation [PDE]-enhanced adversarial graph autoencoder of ST), for accurate inference of spatiotemporal structures from the ST data using PDE-enhanced adversarial graph autoencoder. PearlST employs contrastive learning to extract histological image features, integrates a PDE-based diffusion model to enhance characterization of spatial features at domain boundaries, and learns the latent low-dimensional embeddings via Wasserstein adversarial regularized graph autoencoders. Comparative analyses across multiple ST datasets with varying resolutions demonstrate that PearlST outperforms existing methods in spatial clustering, trajectory inference, and pseudotime analysis. Furthermore, PearlST elucidates functional regulations of the latent features by linking intercellular ligand-receptor interactions to most contributing genes of the low-dimensional embeddings, as illustrated in a human breast cancer dataset. Overall, PearlST proves to be a powerful tool for extracting interpretable latent features and dissecting intricate spatiotemporal structures in ST data across various biological contexts.

Objective To evaluate the applicability of a modified U-shaped forearm flap for the repair of small- and medium-sized defects in the oral and maxillary areas to provide a reference for clinicians. Methods This study was reviewed and approved by the Ethics Committee, and informed consent was obtained from the patients. Ten patients with small- and medium-sized defects in the oral and maxillary areas underwent surgical repair using modified U-shaped forearm flaps. There were 8 males and 2 females aged 43-72 years. The donor site was apposed primarily after harvesting the modified U-shaped forearm skin flap. The flaps ranged from 6 cm × 4 cm to 8 cm × 5 cm in size. Six months after the operation, hand movements (finger extension, fist clenching, wrist rotation upward and wrist rotation downward), the forearm donor site, hand sensations and the satisfaction score for the postoperative quality of the scar at the donor site were evaluated (0 to 10; 0: very unattractive, 10: very satisfactory). Results A total of 10 patients with modified U-shaped forearm flaps survived. One patient developed venous crisis 24 hours after surgery and survived after surgical exploration. Delayed healing occurred at the donor site of the forearm in 1 patient, and the wounds at the donor site of the forearm in the other patients all healed in the first stage. One patient presented with dysesthesia in the hand 2 weeks after surgery and recovered within 3 months. Six months after surgery, all patients had no limited hand movement and no paresthesia at the forearm donor site or hand. The patients were basically satisfied with the appearance of the donor site,and the average satisfaction score of the subjective questionnaire was 8.4 points. Conclusion Modified U-shaped forearm flaps can directly close forearm donor site wounds, which avoids surgical trauma to the secondary donor site and significantly reduces related complications. Modified U-shaped forearm flaps provide an alternative to conventional forearm flaps for the repair of small- and medium-sized defects in the oral and maxillary areas.

Unraveling molecular regulatory networks underlying disease progression is critically important for understanding disease mechanisms and identifying drug targets. The existing methods for inferring gene regulatory networks (GRNs) rely mainly on time-course gene expression data. However, most available omics data from cross-sectional studies of cancer patients often lack sufficient temporal information, leading to a key challenge for GRN inference. Through quantifying the latent progression using random walks-based manifold distance, we propose a latent-temporal progression-based Bayesian method, PROB, for inferring GRNs from the cross-sectional transcriptomic data of tumor samples. The robustness of PROB to the measurement variabilities in the data is mathematically proved and numerically verified. Performance evaluation on real data indicates that PROB outperforms other methods in both pseudotime inference and GRN inference. Applications to bladder cancer and breast cancer demonstrate that our method is effective to identify key regulators of cancer progression or drug targets. The identified ACSS1 is experimentally validated to promote epithelial-to-mesenchymal transition of bladder cancer cells, and the predicted FOXM1-targets interactions are verified and are predictive of relapse in breast cancer. Our study suggests new effective ways to clinical transcriptomic data modeling for characterizing cancer progression and facilitates the translation of regulatory network-based approaches into precision medicine.

Stem cells are crucial in tissue engineering, and their microenvironment greatly influences their behavior. Among the various dental stem cell types, stem cells from the apical papilla (SCAPs) have shown great potential for regenerating the pulp–dentin complex. Microenvironmental cues that affect SCAPs include physical and biochemical factors. To research optimal pulp–dentin complex regeneration, researchers have developed several models of controlled biomimetic microenvironments, ranging from in vivo animal models to in vitro models, including two-dimensional cultures and three-dimensional devices. Among these models, the most powerful tool is a microfluidic microdevice, a tooth-on-a-chip with high spatial resolution of microstructures and precise microenvironment control. In this review, we start with the SCAP microenvironment in the regeneration of pulp–dentin complexes and discuss research models and studies related to the biological process. [ABSTRACT FROM AUTHOR]

When an ultrasonic pulse propagates in a thin plate, nonlinear Lamb waves with higher harmonics and a zero-frequency component (ZFC) will be generated because of the nonlinearity of materials. The ZFC, also known as the static displacement or static component, has its unique application on the evaluation of early-stage damages in the elastic symmetrical undulated plate. In this study, analysis of the excitation mechanism of the ZFC and the second harmonic component (SHC) was theoretically and numerically investigated, and the material early-stage damage of a symmetrical undulated was characterized by studying the propagation of nonlinear Lamb waves. Both the ZFC and SHC can be effectively employed in monitoring the material damages of the undulated plate in its early stage. However, several factors must be considered for the propagation of the SHC in an undulated plate because of the geometric curvature and interference between the second harmonics during propagation, preventing efficient application of this technique. If the fundamental wave can propagate in the plate regardless of the plate boundary conditions, an accumulative effect always exists for the ZFC in a thin plate, indicating that the ZFC is independent of the structural geometry. This study reveals that the ZFC-based inspection technique is more efficient and powerful in characterizing the damages of a symmetrical undulated plate in the early stage of service compared to the second harmonic method. [ABSTRACT FROM AUTHOR]