scMaui: a widely applicable deep learning framework for single-cell multiomics integration in the presence of batch effects and missing data.

The recent advances in high-throughput single-cell sequencing have created an urgent demand for computational models which can address the high complexity of single-cell multiomics data. Meticulous single-cell multiomics integration models are required to avoid biases towards a specific modality and overcome sparsity. Batch effects obfuscating biological signals must also be taken into account.

Recent Advances in the Chemobiological Upcycling of Polyethylene Terephthalate (PET) into Value-Added Chemicals.

Polyethylene terephthalate (PET) is a plastic material commonly applied to beverage packaging used in everyday life. Owing to PET's versatility and ease of use, its consumption has continuously increased, resulting in considerable waste generation. Several physical and chemical recycling processes have been developed to address this problem.

Systematic evaluation of cell-type deconvolution pipelines for sequencing-based bulk DNA methylomes.

DNA methylation analysis by sequencing is becoming increasingly popular, yielding methylomes at single-base pair and single-molecule resolution. It has tremendous potential for cell-type heterogeneity analysis using intrinsic read-level information. Although diverse deconvolution methods were developed to infer cell-type composition based on bulk sequencing-based methylomes, systematic evaluation has not been performed yet.

Anti-tumor effects of jaceosidin on apoptosis, autophagy, and necroptosis in human glioblastoma multiforme.

Glioblastoma multiforme (GBM) is the most aggressive and common malignant neoplasm. Nevertheless, a 5-year survival rate of patients with GBM has remained below 5%. , used as a food and traditional medicine, have shown beneficial properties including anti-inflammatory, anti-oxidative, and anti-cancer activities.

Dilated Saliency U-Net for White Matter Hyperintensities Segmentation Using Irregularity Age Map.

White matter hyperintensities (WMH) appear as regions of abnormally high signal intensity on T2-weighted magnetic resonance image (MRI) sequences. In particular, WMH have been noteworthy in age-related neuroscience for being a crucial biomarker for all types of dementia and brain aging processes. The automatic WMH segmentation is challenging because of their variable intensity range, size and shape.