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A 72-year-old man, who was extremely short-statured, underwent robot-assisted laparoscopic prostatectomy (RARP) for treatment of localized prostate cancer (cT1cNOMO). We report a case of congenital vertebral tip dysplasia with type II collagen dysplasia in a patient who underwent robot-assisted radical prostatectomy. Congenital vertebral tip dysplasia is characterized by short stature, and in this case, the height was 130 cm, which was equivalent to that of an 8-year-old child. The pelvic floor is narrow in short-statured individuals; therefore, the operative time tends to be longer than that required for routine surgery. However, using modifications in port positions and other adjustments, we performed RARP, and our perioperative results were similar to those obtained with routine RARPs.

Cattle behavior monitoring is critical for understanding cattle welfare and health status. One of the most powerful and cost-effective monitoring methods is a neural network-based monitoring system that analyzes time series data from inertial sensors attached to cows. However, while deep learning has achieved many successes in pattern recognition, large-scale datasets are often required. When given a limited number of data, data augmentation is an extremely useful and low-cost preprocessing step for neural network-based systems. Data augmentation for inertial sensor data, however, has yet to be thoroughly investigated. This letter proposes several inertial sensor data augmentation methods in a manner that fits the characteristics of cattle behavioral data. The proposed approaches are applied to the task of cattle behavior classification with convolutional neural networks, which is challenging given limited data. The classification performance increases from 83.07 to 94.43% with appropriate augmentation steps. In conclusion, the data augmentation approaches presented here can help to improve deep learning performance regarding cattle behavior classification and decrease the overall system cost stemming from data acquisition and labeling.

A 72-year-old man, who was extremely short-statured, underwent robot-assisted laparoscopic prostatectomy (RARP) for treatment of localized prostate cancer (cT1cNOMO). We report a case of congenital vertebral tip dysplasia with type II collagen dysplasia in a patient who underwent robot-assisted radical prostatectomy. Congenital vertebral tip dysplasia is characterized by short stature, and in this case, the height was 130 cm, which was equivalent to that of an 8-year-old child. The pelvic floor is narrow in short-statured individuals; therefore, the operative time tends to be longer than that required for routine surgery. However, using modifications in port positions and other adjustments, we performed RARP, and our perioperative results were similar to those obtained with routine RARPs.

Additional file 1: Supplementary A. List of radiomic features used in this study. Supplementary B: List of robust radiomic features. (FS1). Supplementary C: List of non-redundant radiomic features. (FS2). Supplementary D: List of robust and non-redundant radiomic features. (FS3). Supplementary E: Patient characteristics for each subgroup. Supplementary F: Prognostic performance of the radiomic model in each subgroup with five-fold cross-validation. Supplementary G: Prognostic performance of the combined model in each subgroup with five-fold cross-validation. Supplementary H: Feature selection using the LASSO Cox model in the radiomic and combined models for each subgroup. Supplementary I: Kaplan–Meier curves for low- and high-risk groups based on the rad score in the radiomic models for each subgroup. Supplementary J: Kaplan–Meier curves for low- and high-risk groups based on the rad score in the combined models for each subgroup. Supplementary K: For each analysis group, the features and their coefficients selected by the LASSO Cox regression model in the radiomic models. Supplementary L: For each analysis group, the features and their coefficients selected by the LASSO Cox regression model in the combined models. Supplementary M: Patient characteristics for the Lung 1 dataset. Supplementary N: Prognostic performance of the radiomic and combined models in each subgroup with five-fold cross-validation (Lung 1 dataset). Supplementary O: Kaplan–Meier curves for low- and high-risk groups based on the rad score in the radiomic and combined models for each subgroup (Lung 1 dataset). Supplementary P: For each analysis group, the features and their coefficients selected in the LASSO Cox regression model in the radiomic and combined models (Lung 1 dataset).

The patient was a 66-year-old woman who was examined by a local physician for the chief complaint of a mass palpable in the left lower abdomen. Abdominal plain computed tomography (CT) indicated a subcutaneous mass extending continuously from the apex of the bladder to the retropubic space, and she was referred to our medical department. Tumor markers were normal, and cystoscopic examination indicated no clear findings. Abdominal contrast-enhanced CT and plain abdominal magnetic resonance imaging results led to suspicion of actinomycosis. An open biopsy was performed on the subcutaneous mass, and subsequent histopathological testing led to a definitive diagnosis of actinomycosis. After 2 weeks of antibiotic therapy, the mass had diminished on CT. There has been no relapse approximately 24 weeks after discontinuation of the antibiotic therapy.