Purpose: Retroperitoneal sarcomas (RPS) are rare tumors that present unique challenges, often due to late presentation, and the proximity of critical organs makes complete surgical resection challenging. This study aimed to assess the feasibility of neoadjuvant short-course radiotherapy (SCRT) targeting margins-at-risk and to assess its potential impact on outcomes. Materials and Methods: This is a single-center, prospective, non-randomized feasibility study. SCRT was administered via image-guided volumetric modulated arc therapy, consisting of 5 fractions of daily radiotherapy followed by immediate surgery. As a starting dose, patients were prescribed 25 Gy in 5 fractions. For the escalation stage, patients were prescribed 30 Gy in 5 fractions. Only the presumed threatened surgical margins were delineated for large tumors. Results: Patients with either primary or recurrent RPS were recruited. Eight patients underwent SCRT but one patient did not have a resection as planned. Seven patients underwent surgical resection, of whom one passed away 3 months postoperative from a cardiac event. After a median follow-up of 20.5 months for the six postoperative survivors, there were no overt long-term toxicities and one patient relapsed out-of-radiotherapy-field. Conclusion SCRT to RPS with a margin boost followed by immediate surgery is worth investigating. A starting dose of 30 Gy in 5 fractions is recommended for further studies. Longer-term follow-up is necessary.

Purpose: Retroperitoneal sarcomas (RPS) are rare tumors that present unique challenges, often due to late presentation, and the proximity of critical organs makes complete surgical resection challenging. This study aimed to assess the feasibility of neoadjuvant short-course radiotherapy (SCRT) targeting margins-at-risk and to assess its potential impact on outcomes. Materials and Methods: This is a single-center, prospective, non-randomized feasibility study. SCRT was administered via image-guided volumetric modulated arc therapy, consisting of 5 fractions of daily radiotherapy followed by immediate surgery. As a starting dose, patients were prescribed 25 Gy in 5 fractions. For the escalation stage, patients were prescribed 30 Gy in 5 fractions. Only the presumed threatened surgical margins were delineated for large tumors. Results: Patients with either primary or recurrent RPS were recruited. Eight patients underwent SCRT but one patient did not have a resection as planned. Seven patients underwent surgical resection, of whom one passed away 3 months postoperative from a cardiac event. After a median follow-up of 20.5 months for the six postoperative survivors, there were no overt long-term toxicities and one patient relapsed out-of-radiotherapy-field. Conclusion SCRT to RPS with a margin boost followed by immediate surgery is worth investigating. A starting dose of 30 Gy in 5 fractions is recommended for further studies. Longer-term follow-up is necessary.

Purpose: Retroperitoneal sarcomas (RPS) are rare tumors that present unique challenges, often due to late presentation, and the proximity of critical organs makes complete surgical resection challenging. This study aimed to assess the feasibility of neoadjuvant short-course radiotherapy (SCRT) targeting margins-at-risk and to assess its potential impact on outcomes. Materials and Methods: This is a single-center, prospective, non-randomized feasibility study. SCRT was administered via image-guided volumetric modulated arc therapy, consisting of 5 fractions of daily radiotherapy followed by immediate surgery. As a starting dose, patients were prescribed 25 Gy in 5 fractions. For the escalation stage, patients were prescribed 30 Gy in 5 fractions. Only the presumed threatened surgical margins were delineated for large tumors. Results: Patients with either primary or recurrent RPS were recruited. Eight patients underwent SCRT but one patient did not have a resection as planned. Seven patients underwent surgical resection, of whom one passed away 3 months postoperative from a cardiac event. After a median follow-up of 20.5 months for the six postoperative survivors, there were no overt long-term toxicities and one patient relapsed out-of-radiotherapy-field. Conclusion SCRT to RPS with a margin boost followed by immediate surgery is worth investigating. A starting dose of 30 Gy in 5 fractions is recommended for further studies. Longer-term follow-up is necessary.

Purpose: Retroperitoneal sarcomas (RPS) are rare tumors that present unique challenges, often due to late presentation, and the proximity of critical organs makes complete surgical resection challenging. This study aimed to assess the feasibility of neoadjuvant short-course radiotherapy (SCRT) targeting margins-at-risk and to assess its potential impact on outcomes. Materials and Methods: This is a single-center, prospective, non-randomized feasibility study. SCRT was administered via image-guided volumetric modulated arc therapy, consisting of 5 fractions of daily radiotherapy followed by immediate surgery. As a starting dose, patients were prescribed 25 Gy in 5 fractions. For the escalation stage, patients were prescribed 30 Gy in 5 fractions. Only the presumed threatened surgical margins were delineated for large tumors. Results: Patients with either primary or recurrent RPS were recruited. Eight patients underwent SCRT but one patient did not have a resection as planned. Seven patients underwent surgical resection, of whom one passed away 3 months postoperative from a cardiac event. After a median follow-up of 20.5 months for the six postoperative survivors, there were no overt long-term toxicities and one patient relapsed out-of-radiotherapy-field. Conclusion SCRT to RPS with a margin boost followed by immediate surgery is worth investigating. A starting dose of 30 Gy in 5 fractions is recommended for further studies. Longer-term follow-up is necessary.

Purpose: Retroperitoneal sarcomas (RPS) are rare tumors that present unique challenges, often due to late presentation, and the proximity of critical organs makes complete surgical resection challenging. This study aimed to assess the feasibility of neoadjuvant short-course radiotherapy (SCRT) targeting margins-at-risk and to assess its potential impact on outcomes. Materials and Methods: This is a single-center, prospective, non-randomized feasibility study. SCRT was administered via image-guided volumetric modulated arc therapy, consisting of 5 fractions of daily radiotherapy followed by immediate surgery. As a starting dose, patients were prescribed 25 Gy in 5 fractions. For the escalation stage, patients were prescribed 30 Gy in 5 fractions. Only the presumed threatened surgical margins were delineated for large tumors. Results: Patients with either primary or recurrent RPS were recruited. Eight patients underwent SCRT but one patient did not have a resection as planned. Seven patients underwent surgical resection, of whom one passed away 3 months postoperative from a cardiac event. After a median follow-up of 20.5 months for the six postoperative survivors, there were no overt long-term toxicities and one patient relapsed out-of-radiotherapy-field. Conclusion SCRT to RPS with a margin boost followed by immediate surgery is worth investigating. A starting dose of 30 Gy in 5 fractions is recommended for further studies. Longer-term follow-up is necessary.

Purpose: We examined the self-care experiences of adolescents with spinal muscle atrophy (SMA) and their perceptions of the interactions between their body and the environment. Methods: We interviewed ten adolescents with SMA aged 13–18 years regarding personal care practices. Purposive sampling was conducted in two medical centers in northern Taiwan. Data were analyzed using the Giorgi analysis method. Results: Four constitutions were identified: (1) limited space for independent development, (2) multiple reconstructions of self-image to improve physical ability, (3) self-care of disease, and (4) developing activity styles to accommodate social culture. Conclusion The self-care lived experiences of patients reflect dynamic changes in the body and environment. Self-existence was exhibited by adjustment, practice, and creativity of physical activity to integrate into society. Nursing staff should understand the self-care experiences and needs of adolescents with SMA to develop a database of self-care skills. This study recommended that nursing staff improve their ability to guide patients in taking care of themselves by developing body awareness self-care courses and individual care plans in response to various stages of disability to help patients delay deterioration, realize their physical potential, and promote independence and social development.

The incidence of diabetes mellitus is increasing among companion animals. This disease has similar characteristics in both humans and animals. Diabetes is frequently identified as an independent risk factor for infections associated with increased mortality. In the present study, homozygous diabetic (db/db) mice were infected with Listeria (L.) monocytogenes and then treated with the anti-diabetic drug exendin-4, a glucagon-like peptide 1 analogue. In aged db/db mice, decreased CD11b+ macrophage populations with higher lipid content and lower phagocytic activity were observed. Exendin-4 lowered high lipid levels and enhanced phagocytosis in macrophages from db/db mice infected with L. monocytogenes. Exendin-4 also ameliorated obesity and hyperglycemia, and improved ex vivo bacteria clearance by macrophages in the animals. Liver histology examined during L. monocytogenes infection indicated that abscess formation was much milder in exendin-4-treated db/db mice than in the control animals. Moreover, mechanistic studies demonstrated that expression of ATP binding cassette transporter 1, a sterol transporter, was higher in macrophages isolated from the exendin-4-treated db/db mice. Overall, our results suggest that exendin-4 decreases the risk of infection in diabetic animals by modifying the interaction between intracellular lipids and phagocytic macrophages.
ATP-Binding Cassette Transporters/metabolism ; Age Factors ; Animals ; Blood Chemical Analysis ; Cholesterol/metabolism ; Diabetes Mellitus, Type 2/*drug therapy/genetics ; Dyslipidemias/drug therapy/genetics ; Female ; Hyperglycemia/drug therapy/genetics ; Hypoglycemic Agents/*therapeutic use ; Injections, Intraperitoneal ; *Lipid Metabolism/drug effects ; Listeria monocytogenes/*drug effects/immunology ; Listeriosis/*drug therapy/immunology/microbiology ; Macrophages/drug effects/*metabolism ; Mice ; Obesity/drug therapy/genetics ; Peptides/*therapeutic use ; Phagocytosis/drug effects ; Venoms/*therapeutic use

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.