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Abstract Apoptotic bodies (ABs) are extracellular vesicles released during apoptosis and possess diverse biological activities. Initially, ABs were regarded as garbage bags with the main function of apoptotic cell clearance. Recent research has found that ABs carry and deliver various biological agents and are taken by surrounding and distant cells, affecting cell functions and behavior. ABs-mediated intercellular communications are involved in various physiological processes including anti-inflammation and tissue regeneration as well as the pathogenesis of a variety of diseases including cancer, cardiovascular diseases, neurodegeneration, and inflammatory diseases. ABs in biological fluids can be used as a window of altered cellular and tissue states which can be applied in the diagnosis and prognosis of various diseases. The structural and constituent versatility of ABs provides flexibility for tailoring ABs according to disease diagnostic and therapeutic needs. An in-depth understanding of ABs’ constituents and biological functions is mandatory for the effective tailoring of ABs including modification of bio membrane and cargo constituents. ABs’ tailoring approaches including physical, chemical, biological, and genetic have been proposed for bench-to-bed translation in disease diagnosis, prognosis, and therapy. This review summarizes the updates on ABs tailoring approaches, discusses the existing challenges, and speculates the prospects for effective diagnostic and therapeutic applications.

Abstract Cancer immunotherapy has sparked a wave of cancer research, driven by recent successful proof-of-concept clinical trials. However, barriers are emerging during its rapid development, including broad adverse effects, a lack of reliable biomarkers, tumor relapses, and drug resistance. Integration of nanomedicine may ameliorate current cancer immunotherapy. Ultra-large surface-to-volume ratio, extremely small size, and easy modification surface of nanoparticles enable them to selectively detect cells and kill cancer cells in vivo. Exciting synergistic applications of the two approaches have emerged in treating various cancers at the intersection of cancer immunotherapy and cancer nanomedicine, indicating the potential that the combination of these two therapeutic modalities can lead to new paradigms in the treatment of cancer. This review discusses the status of current immunotherapy and explores the possible opportunities that the nanomedicine platform can make cancer immunotherapy more powerful and precise by synergizing the two approaches.

Abstract Background Elderly patients with acute myeloid leukemia or myelodysplastic syndromes (AML/MDS) have historically had poor prognoses. However, there has been a recent increase in the use of allogenic hematopoietic stem cell transplantation (allo-HSCT) are in this patient population. Nevertheless, the optimal choice of donor type for the patients remains an unmet need. Limited data exist on the use of allo-HSCT in elderly patients with AML/MDS from China. To better understand and optimize the selection of donor type for the elderly patients, particularly for those with refractory or relapsed disease, in comparison with the previous studies in the US and Europe. Methods Our retrospective study enrolled 259 patients aged over 55 years who underwent their first allo-HSCT between April 2015 and August 2022. These patients were divided into three groups based on donor type: haploidentical related donor group (haploidentical related donor transplantation [HID], n = 184), matched sibling donor group (matched sibling donor transplantation [MSD], n = 39), and matched unrelated donor group (matched unrelated donor transplantation [MUD], n = 36). Statistics were performed with the chi-square test, the log-rank and Fine-Gray tests. Results The median age of the cohort was 57 years (range: 55–75) and 26.25% of patients were over 60 years old. Younger patients had a higher incidence of acute graft-versus-host disease (HR = 1.942, P = 0.035), faster neutrophil recovery (HR = 1.387, P = 0.012), and better overall survival (HR = 0.567, P = 0.043) than patients aged ≥ 60 years across the entire cohort. Patients with refractory or relapsed (R/R) diseases had delayed neutrophil engraftment (P = 0.010, HR = 0.752) and platelet engraftment (P

Abstract Objective Observational studies have suggested an association between frozen shoulder (FS) and carpal tunnel syndrome (CTS). However, due to challenges in establishing a temporal sequence, the causal relationship between these two conditions remains elusive. This study, based on aggregated data from large-scale population-wide genome-wide association studies (GWAS), investigates the genetic causality between FS and CTS. Methods Initially, a series of quality control measures were employed to select single nucleotide polymorphisms (SNPs) closely associated with the exposure factors. Two-sample Mendelian randomization (MR) was utilized to examine the genetic causality between FS and CTS, employing methods including Inverse-Variance Weighted (IVW), MR-Egger, Weighted Median, Simple Mode, and Weighted Mode approaches. Subsequently, sensitivity analyses were conducted to assess the robustness of the MR analysis results. Results IVW analysis results indicate a positive causal relationship between CTS and FS (p 1), while a negative causal relationship between the two conditions was not observed. Heterogeneity tests suggest minimal heterogeneity in our IVW analysis results (p > 0.05). Multivariable MR testing also indicates no pleiotropy in our IVW analysis (p > 0.05), and stepwise exclusion tests demonstrate the reliability and stability of the MR analysis results. Gene Ontology (GO) pathway analysis reveals enrichment of genes regulated by the associated SNPs in the TGFβ-related pathways. Conclusion This study provides evidence of the genetic causal association between frozen shoulder and carpal tunnel syndrome and provides new insights into the genetics of fibrotic disorders.

Abstract Objective To develop high-quality synthetic CT (sCT) generation method from low-dose cone-beam CT (CBCT) images by using attention-guided generative adversarial networks (AGGAN) and apply these images to dose calculations in radiotherapy. Methods The CBCT/planning CT images of 170 patients undergoing thoracic radiotherapy were used for training and testing. The CBCT images were scanned under a fast protocol with 50% less clinical projection frames compared with standard chest M20 protocol. Training with aligned paired images was performed using conditional adversarial networks (so-called pix2pix), and training with unpaired images was carried out with cycle-consistent adversarial networks (cycleGAN) and AGGAN, through which sCT images were generated. The image quality and Hounsfield unit (HU) value of the sCT images generated by the three neural networks were compared. The treatment plan was designed on CT and copied to sCT images to calculated dose distribution. Results The image quality of sCT images by all the three methods are significantly improved compared with original CBCT images. The AGGAN achieves the best image quality in the testing patients with the smallest mean absolute error (MAE, 43.5 ± 6.69), largest structural similarity (SSIM, 93.7 ± 3.88) and peak signal-to-noise ratio (PSNR, 29.5 ± 2.36). The sCT images generated by all the three methods showed superior dose calculation accuracy with higher gamma passing rates compared with original CBCT image. The AGGAN offered the highest gamma passing rates (91.4 ± 3.26) under the strictest criteria of 1 mm/1% compared with other methods. In the phantom study, the sCT images generated by AGGAN demonstrated the best image quality and the highest dose calculation accuracy. Conclusions High-quality sCT images were generated from low-dose thoracic CBCT images by using the proposed AGGAN through unpaired CBCT and CT images. The dose distribution could be calculated accurately based on sCT images in radiotherapy.