As an emerging drug carrier, hydrogels have been widely used for tumor drug delivery. A hydrogel drug carrier can cause less severe side effects than systemic chemotherapy and can achieve sustained delivery of a drug at tumor sites. In addition, hydrogels have excellent biocompatibility and biodegradability and lower toxicity than nanoparticle carriers. Smart hydrogels can respond to stimuli in the environment (e.g., heat, pH, light, and ultrasound), enabling in situ gelation and controlled drug release, which greatly enhance the convenience and efficiency of drug delivery. Here, we summarize the different sizes of hydrogels used for cancer treatment and their related delivery routes, discuss the design strategies for stimuli-responsive hydrogels, and review the research concerning smart hydrogels reported in the past few years.

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Background Age-related cataract (ARC) is the main cause of blindness in older individuals but its specific pathogenic mechanism is unclear. This study aimed to identify differentially expressed genes (DEGs) associated with ARC and to improve our understanding of the disease mechanism. Methods Anterior capsule samples of the human lens were collected from ARC patients and healthy controls and used for RNA sequencing to detect DEGs. Identified DEGs underwent bioinformatics analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Subsequently, reverse transcription quantitative RT-qPCR was used to validate the different expression levels of selected genes. Results A total of 698 up-regulated DEGs and 414 down-regulated DEGs were identified in ARC patients compared with controls by transcriptome analysis. Through GO and KEGG bioinformatics analysis, the functions of significantly DEGs and their possible molecular mechanisms were determined. Sequencing results were verified by RT-qPCR as being accurate and reliable. Conclusions This study identified several genes associated with ARC, which improves our knowledge of the disease mechanism.

Objectives Suicide presents a major public health challenge worldwide, affecting people across the lifespan. While previous studies revealed strong associations between Social Determinants of Health (SDoH) and suicide deaths, existing evidence is limited by the reliance on structured data. To resolve this, we aim to adapt a suicide-specific SDoH ontology (Suicide-SDoHO) and use natural language processing (NLP) to effectively identify individual-level SDoH-related social risks from death investigation narratives. Materials and Methods We used the latest National Violent Death Report System (NVDRS), which contains 267 804 victim suicide data from 2003 to 2019. After adapting the Suicide-SDoHO, we developed a transformer-based model to identify SDoH-related circumstances and crises in death investigation narratives. We applied our model retrospectively to annotate narratives whose crisis variables were not coded in NVDRS. The crisis rates were calculated as the percentage of the group’s total suicide population with the crisis present. Results The Suicide-SDoHO contains 57 fine-grained circumstances in a hierarchical structure. Our classifier achieves AUCs of 0.966 and 0.942 for classifying circumstances and crises, respectively. Through the crisis trend analysis, we observed that not everyone is equally affected by SDoH-related social risks. For the economic stability crisis, our result showed a significant increase in crisis rate in 2007–2009, parallel with the Great Recession. Conclusions This is the first study curating a Suicide-SDoHO using death investigation narratives. We showcased that our model can effectively classify SDoH-related social risks through NLP approaches. We hope our study will facilitate the understanding of suicide crises and inform effective prevention strategies.

Fatigue life prediction for the notched components is an essential step within the design process of machines. Fatigue strength and life prediction of 40Cr notched steel before and after shot peening were studied. Fatigue fracture of specimens treated by three shot peening intensity parameters was discussed. The life prediction considering residual stress, work hardening and surface roughness caused by shot peening was analyzed. The results indicated that fatigue strength was obviously improved after shot peening and the improvement effect was gradually enhanced with the increase of shot peening intensity. The predicted values based on Rz coefficient showed a good correspondence with the experimental data.