Background: Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis and lacks clinical biomarkers. Exosomes are extracellular vesicles that facilitate cell–cell communication by distributing macromolecules, such as small RNAs (smRNAs). We assessed the potential of exosome-derived small RNAs (Ex-smRNAs) as PDAC biomarkers. Methods: Peripheral blood was collected from 51 patients with PDAC and 15 control individuals. Exosomes were isolated using an aqueous two-phase system. Ex-smRNAs were analyzed using smRNA sequencing. smRNA-mediated target gene regulation was verified via The Cancer Genome Atlas analysis and in vitro transfection and wound-healing assays using PDAC organoids. Results: The total Ex-smRNA count was substantially reduced in patients with PDAC compared with that in control individuals. The levels of microRNAs (miRNAs) miR-125a-5p, miR-30e-5p, miR-16-2-3p, miR-98-5p, and the let-7 family were significantly suppressed, whereas that of miR-6731-5p was significantly elevated. Let-7c-5p and miR-98-5p were found to interact with the long non-coding RNA OLMALINC to regulate their common target genes, BACH1 and CCND1, thus controlling PDAC proliferation and migration. The expressions of CARS1-AS1 and miR-142-5p were upregulated in treatment-responsive patients.Multivariable Cox regression analyses, adjusting for potential prognostic factors such as sex, Eastern Cooperative Oncology Group performance status, and tumor size and stage, revealed that CARS1-AS1 (adjusted hazard ratio [HR] 0.33; 95% confidence interval [CI], 0.15–0.73; P = 0.0061) and miR-142-5p (adjusted HR 0.79; 95% CI, 0.61–1.01; P = 0.0581) were associated with improved overall survival. Conclusions We identified potential Ex-smRNA biomarkers involved in PDAC progression and prognosis that reflect key molecular alterations in PDAC and may serve as clinically relevant biomarkers for disease monitoring.

Purpose: This study explored the feasibility of utilizing a deep learning artificial intelligence (AI) model to detect ileocolic intussusception on grayscale ultrasound images. Methods: This retrospective observational study incorporated ultrasound images of children who underwent emergency ultrasonography for suspected ileocolic intussusception. After excluding video clips, Doppler images, and annotated images, 40,765 images from two tertiary hospitals were included (positive-to-negative ratio: hospital A, 2,775:35,373; hospital B, 140:2,477). Images from hospital A were split into a training set, a tuning set, and an internal test set (ITS) at a ratio of 7:1.5:1.5. Images from hospital B comprised an external test set (ETS). For each image indicating intussusception, two radiologists provided a bounding box as the ground-truth label. If intussusception was suspected in the input image, the model generated a bounding box with a confidence score (0-1) at the estimated lesion location. Average precision (AP) was used to evaluate overall model performance. The performance of practical thresholds for the modelgenerated confidence score, as determined from the ITS, was verified using the ETS. Results: The AP values for the ITS and ETS were 0.952 and 0.936, respectively. Two confidence thresholds, CTopt and CTprecision, were set at 0.557 and 0.790, respectively. For the ETS, the perimage precision and recall were 95.7% and 80.0% with CTopt, and 98.4% and 44.3% with CTprecision. For per-patient diagnosis, the sensitivity and specificity were 100.0% and 97.1% with CTopt, and 100.0% and 99.0% with CTprecision. The average number of false positives per patient was 0.04 with CTopt and 0.01 for CTprecision. Conclusion The feasibility of using an AI model to diagnose ileocolic intussusception on ultrasonography was demonstrated. However, further study involving bias-free data is warranted for robust clinical validation.

Objective: To determine the clinical impact of the baseline sagittal imbalance severity in patients with adult spinal deformity (ASD). Methods: We retrospectively reviewed patients who underwent ≥ 5-level fusion including the pelvis, for ASD with a ≥ 2-year follow-up. Using the Scoliosis Research Society-Schwab classification system, patients were classified into 3 groups according to the severity of the preoperative sagittal imbalance: mild, moderate, and severe. Postoperative clinical and radiographic results were compared among the 3 groups. Results: A total of 259 patients were finally included. There were 42, 62, and 155 patients in the mild, moderate, and severe groups, respectively. The perioperative surgical burden was greatest in the severe group. Postoperatively, this group also showed the largest pelvic incidence minus lumbar lordosis mismatch, suggesting a tendency towards undercorrection. No statistically significant differences were observed in proximal junctional kyphosis, proximal junctional failure, or rod fractures among the groups. Visual analogue scale for back pain and Scoliosis Research Society-22 scores were similar across groups. However, severe group’s last follow-up Oswestry Disability Index (ODI) scores significantly lower than those of the severe group. Conclusion Patients with severe sagittal imbalance were treated with more invasive surgical methods along with increased the perioperative surgical burden. All patients exhibited significant radiological and clinical improvements after surgery. However, regarding ODI, the severe group demonstrated slightly worse clinical outcomes than the other groups, probably due to relatively higher proportion of undercorrection. Therefore, more rigorous correction is necessary to achieve optimal sagittal alignment specifically in patients with severe baseline sagittal imbalance.

Objective: This study aimed to examine the psychiatric impact of the Seoul Halloween crowd crush on individuals related to the victims compared to the general population. It also explores the moderating effect of resilience on the relationship between trauma exposure and psychiatric symptoms. Methods: In total, 2,220 participants completed various post-incident questionnaires (Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, Hwa-byung symptom scale, post-traumatic stress disorder checklist for DSM-5, and Brief Resilience Scale) 30 days after the incident. Moderation analyses were conducted using the PROCESS macro in the statistical package for the social sciences. Results: Individuals related to the victims exhibited higher symptom severity and a greater risk for clinically significant levels of depression, anxiety, anger, and post-traumatic stress disorder (PTSD) (odds ratio=3.28, 3.33, 1.51, and 4.39 respectively). The impact of relevance to victims on anxiety and PTSD symptoms was moderated by resilience, with a stronger effect observed for individuals with low resilience (β=3.51, 95% confidence interval [CI] 2.78–4.24 for anxiety and β=14.53, 95% CI 12.43–16.63 for PTSD) than for those with high resilience (β=1.69, 95% CI 0.72–2.65 for anxiety and β=8.33, 95% CI 5.56–11.09 for PTSD). Conclusion When related to the victims, it was found that not only PTSD, but also depression, anxiety, and anger could intensify. Resilience emerged as a potential buffer against these adverse effects, emphasizing its significance in mitigating the psychiatric impact of community trauma.

Purpose: This study explored the feasibility of utilizing a deep learning artificial intelligence (AI) model to detect ileocolic intussusception on grayscale ultrasound images. Methods: This retrospective observational study incorporated ultrasound images of children who underwent emergency ultrasonography for suspected ileocolic intussusception. After excluding video clips, Doppler images, and annotated images, 40,765 images from two tertiary hospitals were included (positive-to-negative ratio: hospital A, 2,775:35,373; hospital B, 140:2,477). Images from hospital A were split into a training set, a tuning set, and an internal test set (ITS) at a ratio of 7:1.5:1.5. Images from hospital B comprised an external test set (ETS). For each image indicating intussusception, two radiologists provided a bounding box as the ground-truth label. If intussusception was suspected in the input image, the model generated a bounding box with a confidence score (0-1) at the estimated lesion location. Average precision (AP) was used to evaluate overall model performance. The performance of practical thresholds for the modelgenerated confidence score, as determined from the ITS, was verified using the ETS. Results: The AP values for the ITS and ETS were 0.952 and 0.936, respectively. Two confidence thresholds, CTopt and CTprecision, were set at 0.557 and 0.790, respectively. For the ETS, the perimage precision and recall were 95.7% and 80.0% with CTopt, and 98.4% and 44.3% with CTprecision. For per-patient diagnosis, the sensitivity and specificity were 100.0% and 97.1% with CTopt, and 100.0% and 99.0% with CTprecision. The average number of false positives per patient was 0.04 with CTopt and 0.01 for CTprecision. Conclusion The feasibility of using an AI model to diagnose ileocolic intussusception on ultrasonography was demonstrated. However, further study involving bias-free data is warranted for robust clinical validation.

Objective: To determine the clinical impact of the baseline sagittal imbalance severity in patients with adult spinal deformity (ASD). Methods: We retrospectively reviewed patients who underwent ≥ 5-level fusion including the pelvis, for ASD with a ≥ 2-year follow-up. Using the Scoliosis Research Society-Schwab classification system, patients were classified into 3 groups according to the severity of the preoperative sagittal imbalance: mild, moderate, and severe. Postoperative clinical and radiographic results were compared among the 3 groups. Results: A total of 259 patients were finally included. There were 42, 62, and 155 patients in the mild, moderate, and severe groups, respectively. The perioperative surgical burden was greatest in the severe group. Postoperatively, this group also showed the largest pelvic incidence minus lumbar lordosis mismatch, suggesting a tendency towards undercorrection. No statistically significant differences were observed in proximal junctional kyphosis, proximal junctional failure, or rod fractures among the groups. Visual analogue scale for back pain and Scoliosis Research Society-22 scores were similar across groups. However, severe group’s last follow-up Oswestry Disability Index (ODI) scores significantly lower than those of the severe group. Conclusion Patients with severe sagittal imbalance were treated with more invasive surgical methods along with increased the perioperative surgical burden. All patients exhibited significant radiological and clinical improvements after surgery. However, regarding ODI, the severe group demonstrated slightly worse clinical outcomes than the other groups, probably due to relatively higher proportion of undercorrection. Therefore, more rigorous correction is necessary to achieve optimal sagittal alignment specifically in patients with severe baseline sagittal imbalance.

Objective: This study aimed to examine the psychiatric impact of the Seoul Halloween crowd crush on individuals related to the victims compared to the general population. It also explores the moderating effect of resilience on the relationship between trauma exposure and psychiatric symptoms. Methods: In total, 2,220 participants completed various post-incident questionnaires (Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, Hwa-byung symptom scale, post-traumatic stress disorder checklist for DSM-5, and Brief Resilience Scale) 30 days after the incident. Moderation analyses were conducted using the PROCESS macro in the statistical package for the social sciences. Results: Individuals related to the victims exhibited higher symptom severity and a greater risk for clinically significant levels of depression, anxiety, anger, and post-traumatic stress disorder (PTSD) (odds ratio=3.28, 3.33, 1.51, and 4.39 respectively). The impact of relevance to victims on anxiety and PTSD symptoms was moderated by resilience, with a stronger effect observed for individuals with low resilience (β=3.51, 95% confidence interval [CI] 2.78–4.24 for anxiety and β=14.53, 95% CI 12.43–16.63 for PTSD) than for those with high resilience (β=1.69, 95% CI 0.72–2.65 for anxiety and β=8.33, 95% CI 5.56–11.09 for PTSD). Conclusion When related to the victims, it was found that not only PTSD, but also depression, anxiety, and anger could intensify. Resilience emerged as a potential buffer against these adverse effects, emphasizing its significance in mitigating the psychiatric impact of community trauma.

Purpose: This study explored the feasibility of utilizing a deep learning artificial intelligence (AI) model to detect ileocolic intussusception on grayscale ultrasound images. Methods: This retrospective observational study incorporated ultrasound images of children who underwent emergency ultrasonography for suspected ileocolic intussusception. After excluding video clips, Doppler images, and annotated images, 40,765 images from two tertiary hospitals were included (positive-to-negative ratio: hospital A, 2,775:35,373; hospital B, 140:2,477). Images from hospital A were split into a training set, a tuning set, and an internal test set (ITS) at a ratio of 7:1.5:1.5. Images from hospital B comprised an external test set (ETS). For each image indicating intussusception, two radiologists provided a bounding box as the ground-truth label. If intussusception was suspected in the input image, the model generated a bounding box with a confidence score (0-1) at the estimated lesion location. Average precision (AP) was used to evaluate overall model performance. The performance of practical thresholds for the modelgenerated confidence score, as determined from the ITS, was verified using the ETS. Results: The AP values for the ITS and ETS were 0.952 and 0.936, respectively. Two confidence thresholds, CTopt and CTprecision, were set at 0.557 and 0.790, respectively. For the ETS, the perimage precision and recall were 95.7% and 80.0% with CTopt, and 98.4% and 44.3% with CTprecision. For per-patient diagnosis, the sensitivity and specificity were 100.0% and 97.1% with CTopt, and 100.0% and 99.0% with CTprecision. The average number of false positives per patient was 0.04 with CTopt and 0.01 for CTprecision. Conclusion The feasibility of using an AI model to diagnose ileocolic intussusception on ultrasonography was demonstrated. However, further study involving bias-free data is warranted for robust clinical validation.

Background: Since the emergence of hypervirulent strains of Clostridioides difficile, the incidence of C. difficile infections (CDI) has increased significantly. Methods: To assess the incidence of CDI in Korea, we conducted a prospective multicentre observational study from October 2020 to October 2021. Additionally, we calculated the incidence of CDI from mass data obtained from the Health Insurance Review and Assessment Service (HIRA) from 2008 to 2020. Results: In the prospective study with active surveillance, 30,212 patients had diarrhoea and 907 patients were diagnosed with CDI over 1,288,571 patient-days and 193,264 admissions in 18 participating hospitals during 3 months of study period; the CDI per 10,000 patientdays was 7.04 and the CDI per 1,000 admission was 4.69. The incidence of CDI was higher in general hospitals than in tertiary hospitals: 6.38 per 10,000 patient-days (range: 3.25–12.05) and 4.18 per 1,000 admissions (range: 1.92–8.59) in 11 tertiary hospitals, vs. 9.45 per 10,000 patient-days (range: 5.68–13.90) and 6.73 per 1,000 admissions (range: 3.18–15.85) in seven general hospitals. With regard to HIRA data, the incidence of CDI in all hospitals has been increasing over the 13-year-period: from 0.3 to 1.8 per 10,000 patient-days, 0.3 to 1.6 per 1,000 admissions, and 6.9 to 56.9 per 100,000 population, respectively. Conclusion The incidence of CDI in Korea has been gradually increasing, and its recent value is as high as that in the United State and Europe. CDI is underestimated, particularly in general hospitals in Korea.

Background: It is unclear how exposure to and perception of community trauma creates a mental health burden. This study aimed to examine the psychological distress trends among community residents in acute stress reaction, acute stress disorder, and post-traumatic stress disorder phases following the Seoul Halloween crowd crush. Methods: A three-wave repeated cross-sectional survey was conducted with participants after the incident. Analysis of covariance (ANCOVA) with post hoc Bonferroni test was adopted to examine temporal changes in psychological distress and psychological outcomes resulting from media impacts. A two-way ANCOVA was adopted to examine the interaction effects of time and relevance to victims on psychological distress. Results: A total of 807, 1,703, and 2,220 individuals participated in the three waves. Anxiety (estimated mean [standard error of the mean]: 2.28 [0.03] vs. 2.12 [0.02] vs. 2.03 [0.02]; P < 0.001), depression (2.22 [0.03] vs. 2.01 [0.02] vs. 1.90 [0.02]; P < 0.001), and anger (2.70 [0.03] vs. 2.66 [0.02] vs. 2.49 [0.02]; P < 0.001) gradually improved. However, sense of safety initially worsened and did not recover well (2.96 [0.03] vs. 2.75 [0.02] vs. 2.77 [0.02];P < 0.001). The interaction effect of time and relevance to the victim were significant in depression (P for interaction = 0.049), anger (P for interaction = 0.016), and sense of safety (P for interaction = 0.004). Among participants unrelated to the victim, those exposed to graphics exhibited higher levels of anxiety (2.09 [0.02] vs. 1.87 [0.07]; P = 0.002), depression (1.99 [0.02] vs. 1.83 [0.07]; P = 0.020), and anger (2.71 [0.03] vs. 2.47 [0.08]; P = 0.003) at W2 and higher anger (2.49 [0.02] vs. 2.31 [0.06]; P = 0.005) at W3. Conclusion Community residents indirectly exposed to trauma also experienced psychological distress in the early stages after the incident. A significant impact of media which might have served as a conduit for unfiltered graphics and rumors was also indicated.