Background: Understanding the virulence and pathogenicity of invasive nontyphoidal Salmonella (iNTS) in children may support timely treatment and enable closer monitoring of chronic infections. iNTS epidemiology in Asia remains inadequately described. We analyzed the genetic diversity and virulence genes associated with extra-intestinal invasion in Korean children. Methods: Salmonella isolates from children < 18 yrs of age diagnosed with moderate-tosevere salmonellosis between January 2019 and December 2021 were subjected to antibiotic susceptibility testing and whole-genome sequencing. Results: In total, 58 cases were included. We identified 20 serotypes, the most prevalent being Salmonella Enteritidis (N = 21), followed by Infantis (N = 6), I 4,[5],12:i:- (N = 5), and Bareilly (N = 5). Extra-intestinal invasion occurred in 12 (20.7%) cases involving Salmonella Oranienburg (2/2), Give (1/1), Javiana (1/1), Paratyphi B var. L(+) tartrate+ (1/1), Schwarzengrund (1/1), Singapore (1/1), Montevideo (1/2), Saintpaul (1/2), I 4:b:- (1/2), Infantis (1/6), and Enteritidis (1/21). While the numbers of total virulence genes and genes belonging to major virulence categories did not significantly differ between iNTS and noniNTS, several genetic factors, including Salmonella pathogenicity island (SPI)-1 (P = 0.039), SPI-2 (P = 0.020), SPI-5 (P = 0.014), SPI-13 (P = 0.010), cytolethal distending toxin-related genes (P = 1.4 × 10 –4 ), fepC (P = 0.021), and tcpC (P = 0.040) were more frequent in invasive isolates. Conclusions Salmonella Enteritidis-ST11 predominated in infections among Korean children, but invasive isolates were rare. Early detection of genetic factors associated with extra-intestinal invasion will be helpful for prompt and appropriate treatment.

Background: The choice of an appropriate type of orthosis depends on the patient’s specific condition and needs. Different types of orthoses can affect plantar pressure distribution during certain gait patterns. Toe and heel gaits are common patterns of gait assigned for optimal recovery in patients with foot or ankle injuries. This study aimed to evaluate differences in plantar pressure between postoperative shoes and walker boots during toe and heel gaits in healthy individuals. Methods: A total of 30 healthy individuals with a mean age of 21.7 ± 1.2 years were included in this study. Two types of gaits, toe and heel, were performed while wearing each orthosis on the right side of the foot. A standardized running shoe was worn on the left side of the foot. Plantar pressure variables including contact area, peak pressure, and maximum force were collected using the Pedar-X in-shoe pressure measuring system. Results: During toe gait, while both orthoses demonstrated similar offloading in the hindfoot areas, walker boots were superior in reducing the peak pressure (first toe, p = 0.003; second to fifth toes, p < 0.001) and contact area (first toe, p = 0.003; second to fifth toes, p = 0.003) in the forefoot areas. During heel gait, both orthoses demonstrated similar offloading in the toe areas; however, the walker boots were superior in reducing the peak pressure in the lateral hindfoot (p < 0.001). Conclusions The results of our study can serve as a guideline for orthopedic physicians in prescribing an appropriate type of orthosis during specific types of gait for patients following foot and ankle injury and postoperative recovery.

Objective: This study aimed to develop and validate a deep learning (DL) algorithm for the quantitative measurement of thoracolumbar (TL) fracture features, and to evaluate its efficacy across varying levels of clinical expertise. Methods: Using the pretrained Mask Region-Based Convolutional Neural Networks model, originally developed for vertebral body segmentation and fracture detection, we fine-tuned the model and added a new module for measuring fracture metrics—compression rate (CR), Cobb angle (CA), Gardner angle (GA), and sagittal index (SI)—from lumbar spine lateral radiographs. These metrics were derived from six-point labeling by 3 radiologists, forming the ground truth (GT). Training utilized 1,000 nonfractured and 318 fractured radiographs, while validations employed 213 internal and 200 external fractured radiographs. The accuracy of the DL algorithm in quantifying fracture features was evaluated against GT using the intraclass correlation coefficient. Additionally, 4 readers with varying expertise levels, including trainees and an attending spine surgeon, performed measurements with and without DL assistance, and their results were compared to GT and the DL model. Results: The DL algorithm demonstrated good to excellent agreement with GT for CR, CA, GA, and SI in both internal (0.860, 0.944, 0.932, and 0.779, respectively) and external (0.836, 0.940, 0.916, and 0.815, respectively) validations. DL-assisted measurements significantly improved most measurement values, particularly for trainees. Conclusion The DL algorithm was validated as an accurate tool for quantifying TL fracture features using radiographs. DL-assisted measurement is expected to expedite the diagnostic process and enhance reliability, particularly benefiting less experienced clinicians.

Objective: This study aimed to develop and validate a deep learning (DL) algorithm for the quantitative measurement of thoracolumbar (TL) fracture features, and to evaluate its efficacy across varying levels of clinical expertise. Methods: Using the pretrained Mask Region-Based Convolutional Neural Networks model, originally developed for vertebral body segmentation and fracture detection, we fine-tuned the model and added a new module for measuring fracture metrics—compression rate (CR), Cobb angle (CA), Gardner angle (GA), and sagittal index (SI)—from lumbar spine lateral radiographs. These metrics were derived from six-point labeling by 3 radiologists, forming the ground truth (GT). Training utilized 1,000 nonfractured and 318 fractured radiographs, while validations employed 213 internal and 200 external fractured radiographs. The accuracy of the DL algorithm in quantifying fracture features was evaluated against GT using the intraclass correlation coefficient. Additionally, 4 readers with varying expertise levels, including trainees and an attending spine surgeon, performed measurements with and without DL assistance, and their results were compared to GT and the DL model. Results: The DL algorithm demonstrated good to excellent agreement with GT for CR, CA, GA, and SI in both internal (0.860, 0.944, 0.932, and 0.779, respectively) and external (0.836, 0.940, 0.916, and 0.815, respectively) validations. DL-assisted measurements significantly improved most measurement values, particularly for trainees. Conclusion The DL algorithm was validated as an accurate tool for quantifying TL fracture features using radiographs. DL-assisted measurement is expected to expedite the diagnostic process and enhance reliability, particularly benefiting less experienced clinicians.

Objectives: This study analyzed the current state of community mental health programs in Korea to develop evidence-based criteria for these programs. Methods: Seventy community mental health facilities nationwide were surveyed about the scope of their operated mental health programs. Details, including program structure, staff expertise, standardization, and quality management, of the 511 programs submitted by the facilities as their representative programs were also analyzed to evaluate their efforts for evidence-based practice. Results: The average number of programs operated by community mental health welfare centers was 15.9. The most common programs were those related to serious mental illness (SMI), followed by child/adolescent mental health programs, early psychosis programs, and non-SMI adult mental health programs. In the case of community addiction management centers, there were 7.2 different addiction-related programs per center. Among the psychiatric rehabilitation facilities for SMI, the average number of programs for SMI was 13.1, with some programs for early psychosis. Of the 511 programs submitted as representative programs in their facilities, only 12.3% were judged to be good evidence-based programs. Conclusion More efforts by mental health professionals and governments are needed to implement evidence-based programs in Korea.

Background/Aims: The prognostic significance of 18F-fluorodeoxyglucose (FDG)-positron emission tomography-computed tomography (PET/CT) in peripheral T-cell lymphomas (PTCLs) are controversial. We explored the prognostic impact of sequential 18F-FDG PET/CT during frontline chemotherapy of patients with PTCLs. Methods: In total, 143 patients with newly diagnosed PTCLs were included. Sequential 18F-FDG PET/CTs were performed at the time of diagnosis, during chemotherapy, and at the end of chemotherapy. The baseline total metabolic tumor volume (TMTV) was calculated using the the standard uptake value with a threshold method of 2.5. Results: A baseline TMTV of 457.0 cm3 was used to categorize patients into high and low TMTV groups. Patients with a requirehigh TMTV had shorter progression-free survival (PFS) and overall survival (OS) than those with a low TMTV (PFS, 9.8 vs. 26.5 mo, p = 0.043; OS, 18.9 vs. 71.2 mo, p = 0.004). The interim 18F-FDG PET/CT response score was recorded as 1, 2–3, and 4–5 according to the Deauville criteria. The PFS and OS showed significant differences according to the interim 18F-FDG PET/CT response score (PFS, 120.7 vs. 34.1 vs. 5.1 mo, p < 0.001; OS, not reached vs. 61.1 mo vs. 12.1 mo, p < 0.001). Conclusions The interim PET/CT response based on visual assessment predicts disease progression and survival outcome in PTCLs. A high baseline TMTV is associated with a poor response to anthracycline-based chemotherapy in PTCLs. However, TMTV was not an independent predictor for PFS in the multivariate analysis.

Background: The choice of an appropriate type of orthosis depends on the patient’s specific condition and needs. Different types of orthoses can affect plantar pressure distribution during certain gait patterns. Toe and heel gaits are common patterns of gait assigned for optimal recovery in patients with foot or ankle injuries. This study aimed to evaluate differences in plantar pressure between postoperative shoes and walker boots during toe and heel gaits in healthy individuals. Methods: A total of 30 healthy individuals with a mean age of 21.7 ± 1.2 years were included in this study. Two types of gaits, toe and heel, were performed while wearing each orthosis on the right side of the foot. A standardized running shoe was worn on the left side of the foot. Plantar pressure variables including contact area, peak pressure, and maximum force were collected using the Pedar-X in-shoe pressure measuring system. Results: During toe gait, while both orthoses demonstrated similar offloading in the hindfoot areas, walker boots were superior in reducing the peak pressure (first toe, p = 0.003; second to fifth toes, p < 0.001) and contact area (first toe, p = 0.003; second to fifth toes, p = 0.003) in the forefoot areas. During heel gait, both orthoses demonstrated similar offloading in the toe areas; however, the walker boots were superior in reducing the peak pressure in the lateral hindfoot (p < 0.001). Conclusions The results of our study can serve as a guideline for orthopedic physicians in prescribing an appropriate type of orthosis during specific types of gait for patients following foot and ankle injury and postoperative recovery.

Background: The choice of an appropriate type of orthosis depends on the patient’s specific condition and needs. Different types of orthoses can affect plantar pressure distribution during certain gait patterns. Toe and heel gaits are common patterns of gait assigned for optimal recovery in patients with foot or ankle injuries. This study aimed to evaluate differences in plantar pressure between postoperative shoes and walker boots during toe and heel gaits in healthy individuals. Methods: A total of 30 healthy individuals with a mean age of 21.7 ± 1.2 years were included in this study. Two types of gaits, toe and heel, were performed while wearing each orthosis on the right side of the foot. A standardized running shoe was worn on the left side of the foot. Plantar pressure variables including contact area, peak pressure, and maximum force were collected using the Pedar-X in-shoe pressure measuring system. Results: During toe gait, while both orthoses demonstrated similar offloading in the hindfoot areas, walker boots were superior in reducing the peak pressure (first toe, p = 0.003; second to fifth toes, p < 0.001) and contact area (first toe, p = 0.003; second to fifth toes, p = 0.003) in the forefoot areas. During heel gait, both orthoses demonstrated similar offloading in the toe areas; however, the walker boots were superior in reducing the peak pressure in the lateral hindfoot (p < 0.001). Conclusions The results of our study can serve as a guideline for orthopedic physicians in prescribing an appropriate type of orthosis during specific types of gait for patients following foot and ankle injury and postoperative recovery.

Background: The choice of an appropriate type of orthosis depends on the patient’s specific condition and needs. Different types of orthoses can affect plantar pressure distribution during certain gait patterns. Toe and heel gaits are common patterns of gait assigned for optimal recovery in patients with foot or ankle injuries. This study aimed to evaluate differences in plantar pressure between postoperative shoes and walker boots during toe and heel gaits in healthy individuals. Methods: A total of 30 healthy individuals with a mean age of 21.7 ± 1.2 years were included in this study. Two types of gaits, toe and heel, were performed while wearing each orthosis on the right side of the foot. A standardized running shoe was worn on the left side of the foot. Plantar pressure variables including contact area, peak pressure, and maximum force were collected using the Pedar-X in-shoe pressure measuring system. Results: During toe gait, while both orthoses demonstrated similar offloading in the hindfoot areas, walker boots were superior in reducing the peak pressure (first toe, p = 0.003; second to fifth toes, p < 0.001) and contact area (first toe, p = 0.003; second to fifth toes, p = 0.003) in the forefoot areas. During heel gait, both orthoses demonstrated similar offloading in the toe areas; however, the walker boots were superior in reducing the peak pressure in the lateral hindfoot (p < 0.001). Conclusions The results of our study can serve as a guideline for orthopedic physicians in prescribing an appropriate type of orthosis during specific types of gait for patients following foot and ankle injury and postoperative recovery.

Objective: This study aimed to develop and validate a deep learning (DL) algorithm for the quantitative measurement of thoracolumbar (TL) fracture features, and to evaluate its efficacy across varying levels of clinical expertise. Methods: Using the pretrained Mask Region-Based Convolutional Neural Networks model, originally developed for vertebral body segmentation and fracture detection, we fine-tuned the model and added a new module for measuring fracture metrics—compression rate (CR), Cobb angle (CA), Gardner angle (GA), and sagittal index (SI)—from lumbar spine lateral radiographs. These metrics were derived from six-point labeling by 3 radiologists, forming the ground truth (GT). Training utilized 1,000 nonfractured and 318 fractured radiographs, while validations employed 213 internal and 200 external fractured radiographs. The accuracy of the DL algorithm in quantifying fracture features was evaluated against GT using the intraclass correlation coefficient. Additionally, 4 readers with varying expertise levels, including trainees and an attending spine surgeon, performed measurements with and without DL assistance, and their results were compared to GT and the DL model. Results: The DL algorithm demonstrated good to excellent agreement with GT for CR, CA, GA, and SI in both internal (0.860, 0.944, 0.932, and 0.779, respectively) and external (0.836, 0.940, 0.916, and 0.815, respectively) validations. DL-assisted measurements significantly improved most measurement values, particularly for trainees. Conclusion The DL algorithm was validated as an accurate tool for quantifying TL fracture features using radiographs. DL-assisted measurement is expected to expedite the diagnostic process and enhance reliability, particularly benefiting less experienced clinicians.