BMEMat最新文献

Taking advantage of autonomous navigation and deep penetration capabilities of bacteria, the use of bacteria as carriers for nanomedicine has attracted significant attention. In the review (DOI: 10.1002/bmm2.12110), Shujing Zheng, Xingwei Li, and Shutao Guo have systematically summarized current strategies for integrating bacteria and nanomedicines through different administration routes, highlighting both the clinical progress and the challenges faced in bacterial-based anti-tumor therapies. They have provided a perspective on the future development of nanomedicine hitchhiking on bacteria for cancer treatment.

In this article number 10.1002/bmm2.12104, He Ren, Zewen Wu, Liyun Zhang, Yumiao Zhang and their co-authors designed an antirheumatic nanoparticle termed CeViM-micelle@B. A methotrexate-conjugated Pluronic F127 micelle was developed to encapsulate anti-inflammatory agent Celastrol (Cel) and the stabilizer Vitamin K (VK), which was further coated by B-cell membrane. The use of CeViM-micelle@B significantly increased drug accumulation at pathological synovial joints, potently inhibited immune cell activation, and effectively prevented erosion of bone and cartilage. This new nanoplatform holds potential for the next-generation targeted rheumatoid arthritis therapy.

The liver is an immune organ, especially an immune tolerance organ. The critical shortage of donor organs and disease models for the treatment of end-stage liver failure underscores the urgent need for the generation of liver organoids from human induced pluripotent stem cells (iPSCs). Notably, significant advancements have been made in the study of liver organoids over the past decade. The construction of liver organoids has transitioned from single cell type to multicellular models, and from two-dimensional to three-dimensional cultures. Here we provide the progress surrounding the different liver organoids culture techniques from 3D printing to organ-on-chip, as well as focuses on the present and future applications of liver organoids, and then to present challenges and perspectives ahead for further advancement.

Extranodal NK/T cell lymphoma (ENKTL) poses significant challenges in efficient treatment processes due to its aggressive nature and high recurrence rates. There is a critical need to develop a robust statistical model to predict treatment efficacy by dynamically quantifying biomarkers tailored to various stages of lymphoma. Recent analytics such as sequencing and microbiome tests have only been utilized to understand lymphoma progression and treatment response in clinical settings. However, these methods are limited by their quantitative analysis capabilities, long turnaround times, and lack of single-cell resolution, which are essential for understanding the heterogeneous nature of lymphoma. In this study, we developed a deep learning-enhanced image cytometry (DLIC) to investigate biophysical heterogeneities in peripheral blood mononuclear cells (PBMCs) from newly diagnosed (ND) ENKTL patients. We established a substantial cohort of 23 ND ENKTL patients, categorizing them into interim of treatment (n = 21) and end of treatment (n = 19) stages along their serial treatment timelines. Using a basic optical microscope and a commercial microchip, we analyzed over 270,000 single PBMCs in high-throughput, profiling their size, eccentricity, and refractive index in a completely label-free and quantified manner through AI-based nanophotonic computation. We observed distinct heterogeneity variations in these three biophysical indicators across treatment stages and relapse statuses, revealing solid mechanistic correlations among the phenotypes. We established a three-dimensional single-cell distribution map for ENKTL patients and created a standard for quantifying the change in occupational volume. Leveraging this extensive database, DLIC offers on-site analytics in clinical settings, facilitating treatment assessment and prognosis prediction through label-free biophysical analysis of patient PBMCs, extracted directly without additional sample preparation.

X-rays, a form of ionizing radiation with high energy and significant penetration capability, are commonly used in clinical tumor treatment through radiotherapy. Despite their widespread use, optimizing X-ray efficacy remains a critical challenge due to issues such as radiation resistance and damage to surrounding health tissues. Recent advancements in nanotechnology have introduced new opportunities and challenges in cancer diagnosis and treatment. This review summarizes the latest progress in nanomaterials for X-ray-triggered cancer therapy, highlighting their various advantages such as targeted delivery, reduced side effects, and enhanced therapeutic efficacy. We examine how nanomaterials, including metals, metal oxides, metal sulfides, metal fluorides, rare earth oxides, cluster compounds, metal-organic frameworks, and nanohybrids, enhance the effectiveness of X-ray-triggered treatments. Furthermore, we address the current challenges and future prospects of efficient X-ray-triggered cancer therapy, aiming to provide a comprehensive overview for researchers and clinicians in the field.

The importance of continuous healthcare management has significantly accelerated the development of wearable devices for monitoring health-related physical and biochemical markers. Despite extensive research on wearable devices for physiological and biochemical monitoring, critical issues of power management and device/skin interfacial properties restrict the advancement of personalized healthcare and early disease detection. Here, we report a multimodal sweat monitoring device featuring a real-time display and long-term data analysis based on self-powered format of sweat-activated batteries (SABs). The polyvinyl alcohol-sucrose (PVA-Suc) hydrogel serves as the key component for the SAB, offering not only great long-term adhesive properties for conformable wearability but also significant power generation capabilities. A maximum current density of 44.06 mA cm⁻² and a maximum power density of 21.89 mW cm⁻² can be realized for the hydrogel based SAB. The resulting device integrates an advanced colorimetric and electrochemical sensor array to measure pH levels, glucose concentrations, and chloride ion levels in human sweat, with data wirelessly transmitted by Near Field Communication. The self-powering features and multiple mode sensing function offer sufficient power to support real-time monitoring of metabolic biomarkers in sweat, with the ability to visually observe changes in the colorimetric sensors for long-term data monitoring.

Liver fibrosis is a pathological process resulting from prolonged exposure to various injury factors. It is characterized by the abnormal proliferation and activation of hepatic stellate cells and excessive deposition of extracellular matrix. If left untreated, it can progress to cirrhosis, liver failure, and even liver cancer. There is currently no efficient and accurate clinical diagnostic method for early liver fibrosis. Therefore, there is an urgent need to address the challenge of accurate staging and early diagnosis of liver fibrosis in clinical practice. Recently, nanomaterials have demonstrated significant potential for enhancing the diagnosis of liver fibrosis. Nanomaterials possess the ability to precisely identify and target the microenvironment associated with liver fibrosis. By enhancing their enrichment in the target area, nanomaterials can improve imaging contrast of fibrosis lesions in the liver, thereby enabling accurate diagnosis of liver fibrosis. Accordingly, this review delves into the latest research and advancements concerning nanomaterials in liver fibrosis diagnosis.