Background: We evaluated the diagnostic efficacy of deep learning radiomics (DLR) and hand-crafted radiomics (HCR) features in differentiating acute and chronic vertebral compression fractures (VCFs). Methods: A total of 365 patients with VCFs were retrospectively analysed based on their computed tomography (CT) scan data. All patients completed MRI examination within 2 weeks. There were 315 acute VCFs and 205 chronic VCFs. Deep transfer learning (DTL) features and HCR features were extracted from CT images of patients with VCFs using DLR and traditional radiomics, respectively, and feature fusion was performed to establish the least absolute shrinkage and selection operator. The MRI display of vertebral bone marrow oedema was used as the gold standard for acute VCF, and the model performance was evaluated using the receiver operating characteristic (ROC).To separately evaluate the effectiveness of DLR, traditional radiomics and feature fusion in the differential diagnosis of acute and chronic VCFs, we constructed a nomogram based on the clinical baseline data to visualize the classification evaluation. The predictive power of each model was compared using the Delong test, and the clinical value of the nomogram was evaluated using decision curve analysis (DCA). Results: Fifty DTL features were obtained from DLR, 41 HCR features were obtained from traditional radiomics, and 77 features fusion were obtained after feature screening and fusion of the two. The area under the curve (AUC) of the DLR model in the training cohort and test cohort were 0.992 (95% confidence interval (CI), 0.983-0.999) and 0.871 (95% CI, 0.805-0.938), respectively. While the AUCs of the conventional radiomics model in the training cohort and test cohort were 0.973 (95% CI, 0.955-0.990) and 0.854 (95% CI, 0.773-0.934), respectively. The AUCs of the features fusion model in the training cohort and test cohort were 0.997 (95% CI, 0.994-0.999) and 0.915 (95% CI, 0.855-0.974), respectively. The AUCs of nomogram constructed by the features fusion in combination with clinical baseline data were 0.998 (95% CI, 0.996–0.999) and 0.946 (95% CI, 0.906–0.987) in the training cohort and test cohort, respectively. The Delong test showed that the differences between the features fusion model and the nomogram in the training cohort and the test cohort were not statistically significant (P values were 0.794 and 0.668, respectively), and the differences in the other prediction models in the training cohort and the test cohort were statistically significant (P < 0.05). DCA showed that the nomogram had high clinical value. Conclusion: The features fusion model can be used for the differential diagnosis of acute and chronic VCFs, and its differential diagnosis ability is improved when compared with that when either radiomics is used alone. At the same time, the nomogram has a high predictive value for acute and chronic VCFs and can be a potential decision-making tool to assist clinicians, especially when a patient is unable to undergo spinal MRI examination.

In the progression of X‐ray‐based radiotherapy for the treatment of cancer, the incorporation of nanoparticles (NPs) has a transformative impact. This study investigates the potential of NPs, particularly those comprised of high atomic number elements, as radiosensitizers. This aims to optimize localized radiation doses within tumors, thereby maximizing therapeutic efficacy while preserving surrounding tissues. The multifaceted applications of NPs in radiotherapy encompass collaborative interactions with chemotherapeutic, immunotherapeutic, and targeted pharmaceuticals, along with contributions to photodynamic/photothermal therapy, imaging enhancement, and the integration of artificial intelligence technology. Despite promising preclinical outcomes, the paper acknowledges challenges in the clinical translation of these findings. The conclusion maintains an optimistic stance, emphasizing ongoing trials and technological advancements that bolster personalized treatment approaches. The paper advocates for continuous research and clinical validation, envisioning the integration of NPs as a revolutionary paradigm in cancer therapy, ultimately enhancing patient outcomes.

Cancer remains a significant global health concern, necessitating the development of innovative therapeutic strategies. This research paper aims to investigate the role of pyroptosis induction in cancer treatment. Pyroptosis, a form of programmed cell death characterized by the release of pro-inflammatory cytokines and the formation of plasma membrane pores, has gained significant attention as a potential target for cancer therapy. The objective of this study is to provide a comprehensive overview of the current understanding of pyroptosis and its role in cancer treatment. The paper discusses the concept of pyroptosis and its relationship with other forms of cell death, such as apoptosis and necroptosis. It explores the role of pyroptosis in immune activation and its potential for combination therapy. The study also reviews the use of natural, biological, chemical, and multifunctional composite materials for pyroptosis induction in cancer cells. The molecular mechanisms underlying pyroptosis induction by these materials are discussed, along with their advantages and challenges in cancer treatment. The findings of this study highlight the potential of pyroptosis induction as a novel therapeutic strategy in cancer treatment and provide insights into the different materials and mechanisms involved in pyroptosis induction.

This work presents a flexible biosensor with independent pH and uric acid modules. The integrated real-time pH calibration corrects signal drift, enabling reliable uric acid detection in human serum.

Primary omental tumors are uncommon, and omental fibromas account for 2% of these tumors. Due to the low incidence of omental fibromas and the limited relevant literature, it is challenging for clinicians to make an accurate diagnosis of this condition, especially before surgery. A 30-year-old man was admitted to the hospital because of a left epididymal mass with vague discomfort for more than 1 mo. A physical examination was performed, and the findings showed that the epididymal mass may have entered the abdominal cavity. Pelvic computed tomography was performed in our hospital and revealed a left inguinal hernia with a mass in the hernial contents, and no masses were found in the left epididymis. A traditional inguinal hernia incision was made. Intraoperative hernia contents were found to be of the greater omentum, and a 2.5 cm-diameter mass was found at the distal end of the greater omentum. The scrotum and epididymis did not exhibit other masses. Then, the mass of the greater omentum was excised. Intraoperative frozen pathological examination suggested a spindle cell tumor. The postoperative pathological examination suggested that the mass was an omental angiofibroma. Postoperatively, the patient recovered well and was discharged. Outpatient re-examinations were performed at 1 mo and half a year after the operation and showed no obvious abnormalities. Due to the low morbidity rate associated with and latent nature of omental tumors, these tumors are difficult to diagnose preoperatively; thorough medical history taking, detailed physical examinations, and necessary imaging auxiliary examinations can help clinicians diagnose and treat these cases.