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Since the discovery of cell-penetrating peptides (CPP) in the 1980s, they have played a unique role in various fields owing to their excellent and unique cell membrane penetration function. In particular, in the treatment of tumours, CPPS have been used to deliver several types of 'cargos' to cancer cells. To address the insufficient targeting ability, non-selectivity, and blood instability, activatable cell-penetrating peptides, which can achieve targeted drug delivery in tumour treatment, enhance curative effects, and reduce toxicity have been developed. This study reviews the application of different cell-penetrating peptides in tumour-targeted delivery, overcoming multidrug resistance, organelle targeting, tumour imaging, and diagnosis, and summarises the different mechanisms of activatable cell-penetrating peptides in detail. [ABSTRACT FROM AUTHOR]

Laryngeal squamous cell carcinoma (LSCC) is the most common malignant tumor, which occurs in the head and neck. Current treatments for LSCC are all largely weakened by increasing drug resistance. Our study aimed to investigate the effects of long noncoding RNA (lncRNA) H19 on drug resistance in LSCC. In our study, we found that the level of H19 was sharply upregulated in LSCC tissues and drug‐resistant cells compared with the control. Besides, the expression of high‐mobility group B1 (HMGB1) was elevated, and microRNA107 (miR‐107) was suppressed in drug‐resistant cells compared with the control. Further study revealed that the interference of H19 by short hairpin RNA (shRNA) effectively suppressed high autophagy level and obvious drug resistance in drug‐resistant cells. Besides that, miR‐107 was predicted as a target of H19 and inhibiting effects of H19 shRNA on autophagy and drug resistance were both reversed by miR‐107 inhibitor. Moreover, HMGB1 was predicted as a target of miR‐107 in LSCC cells and knockdown of HMGB1 was able to suppress autophagy and drug resistance in LSCC cells. In addition, our investigation demonstrated that H19 shRNA exerted an inhibiting effect on autophagy and drug resistance by downregulating HMGB1 by targeting miR‐107. Finally, the in vivo experiment revealed that LV‐H19 shRNA strongly suppressed drug resistance compared with the usage of cisplatin individually. Taken together, our research indicated an H19–miR‐107–HMGB1 axis in regulating the autophagy‐induced drug resistance in LSCC in vitro and in vivo, providing novel targets for molecular‐targeted therapy and broadening the research for LSCC. [ABSTRACT FROM AUTHOR]

Background: With the rapid advancement of deep learning network technology, the application of facial recognition technology in the medical field has received increasing attention., Objective: This study aims to systematically review the literature of the past decade on facial recognition technology based on deep learning networks in the diagnosis of rare dysmorphic diseases and facial paralysis, among other conditions, to determine the effectiveness and applicability of this technology in disease identification., Methods: This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for literature search and retrieved relevant literature from multiple databases, including PubMed, on 31 December 2023. The search keywords included deep learning convolutional neural networks, facial recognition, and disease recognition. A total of 208 articles on facial recognition technology based on deep learning networks in disease diagnosis over the past 10 years were screened, and 22 articles were selected for analysis. The meta-analysis was conducted using Stata 14.0 software., Results: The study collected 22 articles with a total sample size of 57 539 cases, of which 43 301 were samples with various diseases. The meta-analysis results indicated that the accuracy of deep learning in facial recognition for disease diagnosis was 91.0% [95% CI (87.0%, 95.0%)]., Conclusion: The study results suggested that facial recognition technology based on deep learning networks has high accuracy in disease diagnosis, providing a reference for further development and application of this technology., (© The Author(s) 2024. Published by Oxford University Press on behalf of Fellowship of Postgraduate Medicine. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: The challenges posed by an aging society are increasingly recognized, particularly regarding the potential impacts of high-fat diets and the trend toward younger ages of disease onset. The purpose of this study was to clarify the relationships between the prevalence of stroke in the general US population and PhenoAge (PA) and PhenoAgeAccel (PAA)., Methods: Key methods included a correlation heatmap to explore linear relationships between some of the variables and weighted multivariable logistic regression to assess associations between PA, PAA, and stroke. Restricted cubic spline (RCS) analysis was used to investigate nonlinear relationships and dose-response effects. The ability of the PAA to predict stroke risk was assessed by a nomogram model and a receiver operating characteristic curve., Results: After adjusting for confounding variables, both continuous and categorical PA and PAA were significantly associated with stroke prevalence. RCS analysis revealed a significant nonlinear relationship between PA and stroke prevalence. Further subgroup RCS analysis indicated that maintaining PA below 31.6 could provide greater benefits across all races and genders, specifically for individuals aged 40-80 years and those who are overweight or obese., Conclusion: This study highlights the importance of stroke prevention in overweight and obese populations. Monitoring intermediary factors such as high-density lipoprotein cholesterol and waist circumference may reduce stroke risk. Additionally, PA and PAA may serve as novel markers for stroke, offering new directions for health management in an aging society., (© The Author(s) 2024. Published by Oxford University Press on behalf of Fellowship of Postgraduate Medicine. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Sonodynamic therapy (SDT) is an advanced non-invasive cancer treatment strategy with moderate tissue penetration, less invasiveness and a reliable curative effect. However, due to the low stability, potential bio-toxicity and lack of tumor targeting capability of most sonosensitizers, the vast clinical application of SDT has been challenging and limited. Therefore, it is desirable to develop a novel approach to implement sonosensitizers to SDT for cancer treatments. In this study, an amphiphilic polypeptide was designed to effectively encapsulate rose bengal (RB) as a model sonosensitizer to form peptido-nanomicelles (REPNs). The as-fabricated REPNs demonstrated satisfactory tumor targeting and fluorescence performances, which made them superb imaging tracers in vivo . In the meantime, they generated considerable amounts of reactive oxygen species (ROS) to promote tumor cell apoptosis under ultrasound irradiation and showed excellent anti-tumor performance without obvious side effects. These engineered nanomicelles in combination with medical ultrasound may be used to achieve integrin α v β 3 -targeted sonodynamic therapy against breast cancer, and it is also a promising non-invasive cancer treatment strategy for clinical translations.