Purpose: Accurate prediction of blood glucose variability is crucial for effective diabetes management, as both hypoglycemia and hyperglycemia are associated with increased morbidity and mortality. However, conventional predictive models rely primarily on patient-specific biometric data, often neglecting the influence of patient–provider interactions, which can significantly impact outcomes. This study introduces Cyclic Dual Latent Discovery (CDLD), a deep learning framework that explicitly models patient–provider interactions to improve prediction of blood glucose levels. By leveraging a real-world intensive care unit (ICU) dataset, the model captures latent attributes of both patients and providers, thus improving forecasting accuracy. Methods: ICU patient records were obtained from the MIMIC-IV v3.0 critical care database, including approximately 5,014 instances of patient–provider interaction. The CDLD model uses a cyclic training mechanism that alternately updates patient and provider latent representations to optimize predictive performance. During preprocessing, all numeric features were normalized, and extreme glucose values were capped at 500 mg/dL to mitigate the effect of outliers. Results: CDLD outperformed conventional models, achieving a root mean square error of 0.0852 on the validation set and 0.0899 on the test set, which indicates improved generalization. The model effectively captured latent patient–provider interaction patterns, yielding more accurate glucose variability predictions than baseline approaches. Conclusion Integrating patient–provider interaction modeling into predictive frameworks can increase blood glucose prediction accuracy. The CDLD model offers a novel approach to diabetes management, potentially paving the way for artificial intelligence-driven personalized treatment strategies.

Purpose: Although some medications trigger the worsening of myasthenia gravis (MG), their clinical influence on patients with MG has not been significantly evaluated. We aimed to investigate whether the risk of clinical worsening of MG increases after administering cautionary drugs in patients with MG. Materials and Methods: This retrospective case-control study was based on the medical records of patients diagnosed with MG between 2007 and 2020. We analyzed the risk of MG worsening in patients exposed to cautionary drugs during the risk period, defined as 6 months from the first exposure to cautionary drugs. The risk of MG worsening in the exposed patients was compared to that in the non-exposed patients, who were individually matched in a 1:1 ratio with exposed cases for sex, age, thymoma, and autoantibodies. Results: Of the 2002 patients diagnosed with MG, 552 (27.6%) were exposed to cautionary drugs. Neuromuscular blocking agents (320 patients) and beta blockers (66123 person-days) were the most frequently prescribed medications. After exact matching, 220 exposed and 220 non-exposed patients were enrolled. The incidence rate of clinical worsening during the risk period was significantly higher in the exposed patients than in the non-exposed patients (odds ratio=4.09; 95% confidence interval, 1.88–8.90;p<0.001). Clinical worsening was observed in 31 (14.1%) of the exposed patients and in 8 (3.6%) of the non-exposed patients. Conclusion The administration of cautionary drugs increased the risk of clinical worsening in patients with MG. Clinicians should be aware of this risk when cautionary drugs need to be administered.

Purpose: Improvement of left ventricular (LV) diastolic dysfunction (DD) is known to be a good prognostic factor in patients with heart failure with reduced ejection fraction (EF). In the present study, we investigated the predisposing risk factors affecting the reversibility of LV diastolic filling pattern (DFP) in patients with preserved EF. Materials and Methods: A total of 600 patients with pseudonormal LVDFP and preserved EF who underwent follow-up echocardiography were enrolled between 2011 and 2020. We compared their index and follow-up echocardiography findings and determined the predisposing risk factor affecting the reversibility of LVDFP. Results: Comparing the index and follow-up echocardiography findings showed that 379 (63%) patients had improved to normal or impaired relaxation LVDFP (improved group) and 221 (37%) patients had maintained or worsened LVDFP (unimproved group).The incidence of paroxysmal atrial fibrillation (PAF) was significantly higher in the unimproved group than in the improved group (4.7% vs. 9.5%, p=0.026). After adjustment for relevant clinical risk factors of diastolic dysfunction, PAF was determined to be an independent predisposing risk factor for the unimproved LVDFP (odds ratio: 2.10, 95% confidence interval: 1.06–4.15, p=0.033).Among the parameters of diastolic dysfunction in follow-up echocardiography, the left atrial volume index, mean E/A ratio, and E/e' were significantly improved in patients without PAF but remained in patients with PAF. Conclusion We identified that PAF was an independent predisposing risk factor of the unimproved LVDFP in patients with pseudonormal LVDFP and preserved EF. Therefore, early detection and management of PAF might be required in patients with LVDD and preserved EF to prevent adverse cardiovascular events.

Purpose: Feeding intolerance (FI) is a prevalent clinically sequential condition in preterm infants. To clarify its relationship with the gut microbiota, we compared microbial diversity and taxonomic composition at 2 and 4 weeks of age in infants born before 32 weeks of gestation. Methods: Between August 2021 and December 2022, we prospectively enrolled infants who delivered before 32 weeks of gestation and were admitted to the neonatal intensive care unit at CHA Bundang Medical Center. Forty-four preterm infants were grouped based on the presence (n=16) or absence (n=28) of FI. Fecal samples were obtained at 2 and 4 weeks after birth and analyzed using 16S rRNA gene sequencing to determine microbial profiles. Results: Microbial α-diversity and β-diversity did not differ significantly between groups at either time point. At the genus level, Staphylococcus was significantly more abundant in the FI group than in the feeding tolerance group at 2 weeks postnatal age (P=0.016). Linear discriminant analysis effect size revealed that Staphylococcus, Pseudomonas, and Escherichia were markedly enriched in the FI group at all time points. Conclusion Early colonization by potentially pathogenic genera, particularly Staphylococcus, may precede the development of FI in preterm infants. These findings highlight the potential microbial composition associated with FI and may provide preliminary insights for future microbiome-targeted research in neonatal care.

During the celebration of the 50th anniversary of the founding of the Korean Cancer Association, articles published in Cancer Research and Treatment from 2004 to 2023 were assessed based on the subject and design of each study. Based on this analysis, trends in domestic cancer research were inferred and directions were suggested for the future development of Cancer Research and Treatment.

Purpose: Feeding intolerance (FI) is a prevalent clinically sequential condition in preterm infants. To clarify its relationship with the gut microbiota, we compared microbial diversity and taxonomic composition at 2 and 4 weeks of age in infants born before 32 weeks of gestation. Methods: Between August 2021 and December 2022, we prospectively enrolled infants who delivered before 32 weeks of gestation and were admitted to the neonatal intensive care unit at CHA Bundang Medical Center. Forty-four preterm infants were grouped based on the presence (n=16) or absence (n=28) of FI. Fecal samples were obtained at 2 and 4 weeks after birth and analyzed using 16S rRNA gene sequencing to determine microbial profiles. Results: Microbial α-diversity and β-diversity did not differ significantly between groups at either time point. At the genus level, Staphylococcus was significantly more abundant in the FI group than in the feeding tolerance group at 2 weeks postnatal age (P=0.016). Linear discriminant analysis effect size revealed that Staphylococcus, Pseudomonas, and Escherichia were markedly enriched in the FI group at all time points. Conclusion Early colonization by potentially pathogenic genera, particularly Staphylococcus, may precede the development of FI in preterm infants. These findings highlight the potential microbial composition associated with FI and may provide preliminary insights for future microbiome-targeted research in neonatal care.

Intraflagellar transport (IFT) particles, a multi-protein apparatus composed of complex A and B, are known to be involved in homeostasis of flagella formation. IFT particles have recently become an interesting topic in Giardia lamblia, which has 4 pairs of flagella. In this experiment, we examined the function of giardial IFT components. When 7 components (IFT121, 140, 20, 46, 52, 81, and 88) of IFT were expressed in Giardia trophozoites as a tagged form with mNeonGreen, all of them were found in both flagella pores and cytoplasmic axonemes. In addition, motor proteins for IFT particles (kinesin-13 and kinesin-2b), were localized to a median body and cytoplasmic flagella, respectively. The CRISPRi-mediated knockdown of IFT88 significantly affected the lengths of all 4 flagella compared to the control cells, Giardia expressing dead Cas9 using control guide RNA. Decreased expression of kinesin-2b also resulted in shortening of flagella, excluding the ventral flagella. Live Giardia cells expressing IFT88-mNeonGreen clearly demonstrated fluorescence in flagella pores and cytoplasmic axonemes. These results on IFT88 and kinesin-2b indicate that IFT complex plays a role in maintenance of G. lamblia flagella.

Purpose: Accurate prediction of blood glucose variability is crucial for effective diabetes management, as both hypoglycemia and hyperglycemia are associated with increased morbidity and mortality. However, conventional predictive models rely primarily on patient-specific biometric data, often neglecting the influence of patient–provider interactions, which can significantly impact outcomes. This study introduces Cyclic Dual Latent Discovery (CDLD), a deep learning framework that explicitly models patient–provider interactions to improve prediction of blood glucose levels. By leveraging a real-world intensive care unit (ICU) dataset, the model captures latent attributes of both patients and providers, thus improving forecasting accuracy. Methods: ICU patient records were obtained from the MIMIC-IV v3.0 critical care database, including approximately 5,014 instances of patient–provider interaction. The CDLD model uses a cyclic training mechanism that alternately updates patient and provider latent representations to optimize predictive performance. During preprocessing, all numeric features were normalized, and extreme glucose values were capped at 500 mg/dL to mitigate the effect of outliers. Results: CDLD outperformed conventional models, achieving a root mean square error of 0.0852 on the validation set and 0.0899 on the test set, which indicates improved generalization. The model effectively captured latent patient–provider interaction patterns, yielding more accurate glucose variability predictions than baseline approaches. Conclusion Integrating patient–provider interaction modeling into predictive frameworks can increase blood glucose prediction accuracy. The CDLD model offers a novel approach to diabetes management, potentially paving the way for artificial intelligence-driven personalized treatment strategies.

Purpose: Although some medications trigger the worsening of myasthenia gravis (MG), their clinical influence on patients with MG has not been significantly evaluated. We aimed to investigate whether the risk of clinical worsening of MG increases after administering cautionary drugs in patients with MG. Materials and Methods: This retrospective case-control study was based on the medical records of patients diagnosed with MG between 2007 and 2020. We analyzed the risk of MG worsening in patients exposed to cautionary drugs during the risk period, defined as 6 months from the first exposure to cautionary drugs. The risk of MG worsening in the exposed patients was compared to that in the non-exposed patients, who were individually matched in a 1:1 ratio with exposed cases for sex, age, thymoma, and autoantibodies. Results: Of the 2002 patients diagnosed with MG, 552 (27.6%) were exposed to cautionary drugs. Neuromuscular blocking agents (320 patients) and beta blockers (66123 person-days) were the most frequently prescribed medications. After exact matching, 220 exposed and 220 non-exposed patients were enrolled. The incidence rate of clinical worsening during the risk period was significantly higher in the exposed patients than in the non-exposed patients (odds ratio=4.09; 95% confidence interval, 1.88–8.90;p<0.001). Clinical worsening was observed in 31 (14.1%) of the exposed patients and in 8 (3.6%) of the non-exposed patients. Conclusion The administration of cautionary drugs increased the risk of clinical worsening in patients with MG. Clinicians should be aware of this risk when cautionary drugs need to be administered.

Purpose: Improvement of left ventricular (LV) diastolic dysfunction (DD) is known to be a good prognostic factor in patients with heart failure with reduced ejection fraction (EF). In the present study, we investigated the predisposing risk factors affecting the reversibility of LV diastolic filling pattern (DFP) in patients with preserved EF. Materials and Methods: A total of 600 patients with pseudonormal LVDFP and preserved EF who underwent follow-up echocardiography were enrolled between 2011 and 2020. We compared their index and follow-up echocardiography findings and determined the predisposing risk factor affecting the reversibility of LVDFP. Results: Comparing the index and follow-up echocardiography findings showed that 379 (63%) patients had improved to normal or impaired relaxation LVDFP (improved group) and 221 (37%) patients had maintained or worsened LVDFP (unimproved group).The incidence of paroxysmal atrial fibrillation (PAF) was significantly higher in the unimproved group than in the improved group (4.7% vs. 9.5%, p=0.026). After adjustment for relevant clinical risk factors of diastolic dysfunction, PAF was determined to be an independent predisposing risk factor for the unimproved LVDFP (odds ratio: 2.10, 95% confidence interval: 1.06–4.15, p=0.033).Among the parameters of diastolic dysfunction in follow-up echocardiography, the left atrial volume index, mean E/A ratio, and E/e' were significantly improved in patients without PAF but remained in patients with PAF. Conclusion We identified that PAF was an independent predisposing risk factor of the unimproved LVDFP in patients with pseudonormal LVDFP and preserved EF. Therefore, early detection and management of PAF might be required in patients with LVDD and preserved EF to prevent adverse cardiovascular events.