Perceived Threat of Alzheimer's Disease and Related Dementias Among Chinese Family Caregivers of Older Adults with Cognitive Impairment.

Perceived threat of Alzheimer's disease and related dementias (ADRD) has been found a widespread phenomenon in developed countries, but has not yet been fully explored in developing countries. Analyzing data from 300 family caregivers of older adults with cognitive impairment in China, this study found caregiver burden was positively associated with the perceived threat of ADRD, and this association was buffered by higher family income and longer caregiving time. To alleviate undue ADRD concerns, it suggests expanding respite care and community elder care beds, and initiating education programs on reducing unnecessary worries about developing ADRD.

Yb/Si frustrated Lewis pairs with a labile naphthalenyl bridge.

The first examples of RE/Si FLPs (RE: rare-earth metal, FLPs: frustrated Lewis pairs), namely Yb/Si FLPs were synthesized, where Yb⋯Si distances are in the range of 3.55 to 3.72 Å. These FLPs react with triphenylphosphine sulfide and aryl isocyanide to produce novel silylyne group transfer products through dissociation of naphthalene.

Exploring the evolving roles and clinical significance of circRNAs in head and neck squamous cell carcinoma.

Head and neck squamous cell carcinoma (HNSCC) represents the predominant malignancies in the head and neck region, and has limited therapeutic alternatives. Circular RNAs (circRNAs), a substantial category of non-coding RNA molecules, exert influential roles in human disease development and progression, employing various mechanisms such as microRNA sponging, interaction with RNA-binding proteins, and translational capabilities. Accumulating evidence highlights the differential expression of numerous circRNAs in HNSCC, and numerous dysregulated circRNAs underscore their crucial involvement in malignant advancement and resistance to treatment. This review aims to comprehensively outline the characteristics, biogenesis, and mechanisms of circRNAs, elucidating their functional significance in HNSCC. In addition, we delve into the clinical implications of circRNAs, considering their potential as biomarkers or targets for diagnosis, prognosis, and therapeutic applications in HNSCC. The discussion extends to exploring future challenges in the clinical translation of circRNAs, emphasizing the need for further research.

Zero-shot prediction of mutation effects with multimodal deep representation learning guides protein engineering.

Mutations in amino acid sequences can provoke changes in protein function. Accurate and unsupervised prediction of mutation effects is critical in biotechnology and biomedicine, but remains a fundamental challenge. To resolve this challenge, here we present Protein Mutational Effect Predictor (ProMEP), a general and multiple sequence alignment-free method that enables zero-shot prediction of mutation effects. A multimodal deep representation learning model embedded in ProMEP was developed to comprehensively learn both sequence and structure contexts from ~160 million proteins. ProMEP achieves state-of-the-art performance in mutational effect prediction and accomplishes a tremendous improvement in speed, enabling efficient and intelligent protein engineering. Specifically, ProMEP accurately forecasts mutational consequences on the gene-editing enzymes TnpB and TadA, and successfully guides the development of high-performance gene-editing tools with their engineered variants. The gene-editing efficiency of a 5-site mutant of TnpB reaches up to 74.04% (vs 24.66% for the wild type); and the base editing tool developed on the basis of a TadA 15-site mutant (in addition to the A106V/D108N double mutation that renders deoxyadenosine deaminase activity to TadA) exhibits an A-to-G conversion frequency of up to 77.27% (vs 69.80% for ABE8e, a previous TadA-based adenine base editor) with significantly reduced bystander and off-target effects compared to ABE8e. ProMEP not only showcases superior performance in predicting mutational effects on proteins but also demonstrates a great capability to guide protein engineering. Therefore, ProMEP enables efficient exploration of the gigantic protein space and facilitates practical design of proteins, thereby advancing studies in biomedicine and synthetic biology.