Performance Evaluation of Foamed Concrete with Lightweight Aggregate: Strength, Shrinkage, and Thermal Conductivity.

Lightweight concrete offers numerous advantages for modular construction, including easier construction planning and logistics, and the ability to offset additional dead loads induced by double-wall and double-slab features. In a previous study, authors proposed incorporating lightweight aggregate into foamed concrete instead of adding extra foam to achieve lower density, resulting in lightweight concrete with an excellent strength-to-density ratio. This paper further investigated the performance aspects of foamed concrete with lightweight aggregate beyond mechanical strength. To evaluate the effect of aggregate type and foam content, three mix compositions were designed for the lightweight concrete. Specimens were prepared for experimental tests on thermal conductivity and drying shrinkage of lightweight concrete. Results showed that while both the increase in foam volume and the incorporation of lightweight aggregate led to higher drying shrinkage, they also contributed to improved insulating properties and reduced potential of cracking. Using typical multi-storey modular residential buildings in Hong Kong and three other Chinese cities as case studies, simulations were performed to assess potential savings in annual cooling and heating loads by employing the proposed lightweight concrete. These findings demonstrate the practical benefits of using foamed concrete with lightweight aggregate in modular construction and provide valuable insights for further optimization and implementation.

Identification and validation of neutrophils-related subtypes and prognosis model in triple negative breast cancer.

BACKGROUND: Neutrophils are considered to be crucial players in the initiation and progression of cancer. However, the complex relationship between neutrophils and cancer prognosis remains elusive, mainly due to the significant plasticity and diversity exhibited by these immune cells. METHODS: As part of our thorough investigation, we examined 38 Neutrophils-Related Genes (NRGs) and the associated copy number variations (CNV), somatic mutations, and gene expression patterns in relation to triple negative breast cancer (TNBC). The interactions between these genes, their biological roles, and their possible prognostic significance were then examined. With the NRGs as our basis, we applied Lasso and Cox regression analyses to create a predictive model for overall survival (OS). Furthermore, TNBC tissue and a public database were used to assess changes in MYO1D expression (MYO1D is characterized as a member of the myosin-I family, a group of motor proteins based on actin), its connection to neutrophil infiltration, and the clinical importance of MYO1D in TNBC. RESULTS: Four neutrophil-related genes were included in the development of a prognostic model based on neutrophils. The model was further shown to be an independent predicted factor for overall survival by multivariate Cox regression analysis. According to this study, neutrophil subtype B as well as gene subtype B, were associated with activated cancer immunity and poor prognosis of TNBC patients. Furthermore, considering that poor OS was linked to increased MYO1D expression, MYO1D was increased in TNBC tissues and associated with neutrophil infiltration. In vitro experiments also confirmed that MYO1D facilitates breast cancer invasion and metastasis. CONCLUSION: Based on the degree of gene expression linked to neutrophils, a unique prognostic model was created. MYO1D could be a potential prognostic biomarker in TNBC patients and also a prospective target for therapy.

HydrogelFinder: A Foundation Model for Efficient Self-Assembling Peptide Discovery Guided by Non-Peptidal Small Molecules.

Self-assembling peptides have numerous applications in medicine, food chemistry, and nanotechnology. However, their discovery has traditionally been serendipitous rather than driven by rational design. Here, HydrogelFinder, a foundation model is developed for the rational design of self-assembling peptides from scratch. This model explores the self-assembly properties by molecular structure, leveraging 1,377 self-assembling non-peptidal small molecules to navigate chemical space and improve structural diversity. Utilizing HydrogelFinder, 111 peptide candidates are generated and synthesized 17 peptides, subsequently experimentally validating the self-assembly and biophysical characteristics of nine peptides ranging from 1-10 amino acids-all achieved within a 19-day workflow. Notably, the two de novo-designed self-assembling peptides demonstrated low cytotoxicity and biocompatibility, as confirmed by live/dead assays. This work highlights the capacity of HydrogelFinder to diversify the design of self-assembling peptides through non-peptidal small molecules, offering a powerful toolkit and paradigm for future peptide discovery endeavors.