Enhanced therapeutic impact of Shikonin-encapsulated exosomes in the inhibition of colorectal cancer progression.

Colorectal cancer (CRC) is a prevalent malignancy with high mortality rates and poor prognosis. Shikonin (SHK) has demonstrated extensive anti-tumor activity across various cancers, yet its clinical application is hindered by poor solubility, limited bioavailability, and high toxicity. This study aims to develop SHK-loaded exosomes (SHK-Exos) and assess their efficacy in CRC progression. Exosomes were isolated using ultracentrifugation and characterized via TEM, NTA, and western blotting. Their cellular internalization was confirmed through confocal microscopy post PKH67 labeling. Effects on cell behaviors were assessed using CCK-8 and Transwell assays. Cell cycle and apoptosis were analyzed via flow cytometry. A xenograft tumor model evaluatedin vivotherapeutic potential, and tumor tissues were examined using H&E staining andin vivoimaging. SHK-Exos demonstrated effective cell targeting and internalization in CRC cells.In vitro, SHK-Exos surpassed free SHK in inhibiting aggressive cellular behaviors and promoting apoptosis, whilein vivostudies showed substantial efficacy in reducing tumor growth with excellent tumor targeting and minimal toxicity. Employing SHK-Exos effectively impedes CRC progressionin vitroandin vivo, offering significant therapeutic potential. This research underscores the advantages of using autologous exosomes as a drug carrier, enhancing efficacy and reducing toxicity.

Comparison of the long-term effects of atropine in combination with Orthokeratology and defocus incorporated multiple segment lenses for myopia control in Chinese children and adolescents.

PURPOSE: The aim of this study was to evaluate the efficacy of Orthokeratology (Ortho-K), defocus incorporated multiple segment (DIMS) lens, combined Ortho-K/atropine, and combined DIMS/atropine for myopia control in children. METHODS: A retrospective study included 167 myopic children aged 6-14 years with a spherical equivalent refraction (SER) of -0.75 to -4.00 diopter treated with Ortho-K (OK, n = 41), combined Ortho-K/atropine (OKA, n = 43), DIMS (n = 41), or combined DIMS/atropine (DIMSA, n = 42). Axial length (AL) was measured at baseline and at 3, 6, 9 and 12 months. Axial elongation over time and between groups were analysed. RESULTS: After 12 months, the AL change was 0.20 ± 0.12 mm, 0.12 ± 0.14 mm, 0.22 ± 0.14 mm, and 0.15 ± 0.15 mm in the OK, OKA, DIMS, and DIMSA, respectively. There was no significant difference in AL change between OK and DIMS. OKA and DIMSA significantly slowed axial elongation compared to OK and DIMS monotherapy. After stratification by age, in the subgroup aged 6-10 years, there was significant difference in AL change between OKA and DIMS (p = 0.013), and no difference between other groups, while in the subgroup aged 10-14 years, the difference between OKA and DIMS became insignificant (p = 0.237), and the difference between OK and OKA, OK and DIMSA, DIMS and DIMSA became significant. CONCLUSIONS: Ortho-K and DIMS lenses show similar reductions in myopia progression among children with low initial myopia. Atropine can significantly improve the efficacy of myopia control of both Ortho-K and DIMS lenses, and this add-on effect is better in older children.

Development and Validation of Data-Level Innovation Data-Balancing Machine Learning Models for Predicting Optimal Implantable Collamer Lens Size and Postoperative Vault.

INTRODUCTION: There are only four sizes of implantable collamer lens (ICL) available for selection, which cannot completely fit all patients as a result of the discontinuity of ICL sizes. Sizing an optimal ICL and predicting postoperative vault are still unresolved problems. This study aimed to develop and validate innovative data-level data-balancing machine learning-based models for predicting ICL size and postoperative vault. METHODS: The patients were randomly assigned to training and internal validation sets in a 4:1 ratio. Feature selection was performed using analysis of variance (ANOVA) and Kruskal-Wallis feature importance methods. Traditional linear regression model and machine learning-based models were used. The accuracy of models was assessed using the area under the curve (AUC) and confusion matrix. RESULTS: A total of 564 patients (1127 eyes) were eligible for this study, consisting of 808 eyes in the training set, 202 eyes in the internal validation set, and 117 eyes in the external validation set. Compared with the traditional linear regression method, the machine learning model bagging tree showed the best performance for ICL size selection, with an accuracy of 84.5% (95% confidence interval (CI) 83.2-85.8%), and the AUC ranged from 0.88 to 0.99; the prediction accuracy of 12.1 mm and 13.7 mm ICL sizes was improved by 49% and 59%, respectively. The bagging tree model achieved the best accuracy [90.2%, (95% CI 88.9-91.5%)] for predicting the postoperative vault, and the AUC ranged from 0.90 to 0.94. The prediction accuracies of internal and external validation dataset for ICL sizing were 82.2% (95% CI 81.1-83.3%) and 82.1% (95% CI 81.1-83.1%), respectively. CONCLUSIONS: The innovative data-level data balancing-based machine learning model can be used to predict ICL size and postoperative vault more accurately, which can assist surgeons in choosing optimal ICL size, thus reducing risks of postoperative complications and secondary surgery.

Infective Spondylitis with Epidural Abscess Formation Caused by Roseomonas mucosa: A Case Report and Literature Review.

Roseomonas mucosa (R. mucosa) is a pink-pigmented, aerobic, nonfermentative, slow-growing Gram-negative coccus typically isolated from the natural environment, human skin, and hospital environment. This pathogen, in most circumstances, leads to infections in immunocompromised hosts, but it may sometimes invade immunocompetent individuals. Bacteraemia is the most common form of infection caused by R. mucosa. In contrast, only two case reports have described R. mucosa-related epidural abscess formation and infective spondylitis. In this case report, we shared the history and treatment experience of a 76-year-old female who was diagnosed with infective spondylitis and epidural abscess caused by R. mucosa. She received a local transdermal injection into the lower back to relieve her back pain two months before symptom onset, which was considered to be associated with this infection episode. After admission to the hospital, neurosurgeons performed emergent decompression and debridement. She was treated with intravenous ceftriaxone for four weeks, followed by oral ciprofloxacin for another eight weeks. The patient recovered well without any sequelae and had no relapse of infection at least six months after the end of treatment. In addition to the case report, we reviewed the literature for reported cases caused by R. mucosa. Our experience suggests that clinicians should include R. mucosa as one of the possible healthcare-associated pathogens among individuals who have undergone transdermal procedures. We believe that this article will help clinicians better recognize R. mucosa infection.