For practical applications, molecules often exist in an aggregate state. Therefore, it is of great value if one can predict the performance of molecules when forming aggregates, for example, aggregation-induced emission (AIE) or aggregation-caused quenching (ACQ). Herein, a database containing AIE/ACQ molecules reported in the literature is first established. Through training, these machine learning (ML) models can build up the structure-property relationship and thus implement fast prediction of AIE/ACQ properties. To this end, a multi-modal approach is proposed, multiple prediction methods are compared and designed, and thus an ensemble strategy is developed. First, multiple molecular descriptors are considered at the same time, major features are extracted by dimensionality reduction, and multi-modal features are synthesized. Then, several state-of-the-art methods are designed and compared to analyze the advantages of the different methods. Finally, the ensemble strategy combines the advantages of the multiple methods to obtain the final prediction result. The reliability of this approach in an unknown molecular space is further verified by three newly designed molecules. Reasonable consistency between model predictions and experimental outcomes is obtained. The result indicates that ML can be a powerful tool to predict molecular properties in the aggregated state, thus accelerating the development of solid-state optical materials.

Alternative splicing (AS) of messenger RNAs occurs in ∼95% of multi-exon human genes and generates diverse RNA and protein isoforms. We investigated AS events associated with human epidermal differentiation, a process crucial for skin function. We identified 6,413 AS events, primarily involving cassette exons. We also predicted 34 RNA-binding proteins (RBPs) regulating epidermal AS, including 19 previously undescribed candidate regulators. From these results, we identified FUS as an RBP that regulates the balance between keratinocyte proliferation and differentiation. Additionally, we characterized the function of a cassette exon AS event in MAP3K7, which encodes a kinase involved in cell signaling. We found that a switch from the short to long isoform of MAP3K7, triggered during differentiation, enforces the demarcation between proliferating basal progenitors and overlying differentiated strata. Our findings indicate that AS occurs extensively in the human epidermis and has critical roles in skin homeostasis.

Coherent optics has profoundly impacted diverse applications ranging from communications, LiDAR to quantum computations. However, developing coherent systems in integrated photonics comes at great expense in hardware integration and energy efficiency. Here we demonstrate a high-coherence parallelization strategy for advanced integrated coherent systems at minimal cost. By using a self-injection locked microcomb to injection lock distributed feedback lasers, we achieve a record high on-chip gain of 60 dB with no degradation in coherence. This strategy enables highly coherent channels with linewidths down to 10 Hz and power over 20 dBm. The overall electrical-to-optical efficiency reaches 19%, comparable to that of advanced semiconductor lasers. This method supports a silicon photonic communication link with an unprecedented data rate beyond 60 Tbit/s and reduces phase-related DSP consumption by 99.99999% compared to traditional III-V laser pump schemes. This work paves the way for realizing scalable, high-performance coherent integrated photonic systems, potentially benefiting numerous applications.