Wernicke encephalopathy, also known as thiamine deficiency, is characterized by a triad of symptoms: ophthalmoplegia, ataxia, and confusion. However, additional symptoms may manifest depending on the area affected by the lesion. Although multiple cranial neuropathies are possible, sudden onset bilateral hearing loss has been described in rare situations as the first manifestation of Wernicke encephalopathy. Here, we present a case report detailing the clinical experience of a patient diagnosed with Wernicke encephalopathy, whose initial presentation included sudden bilateral deafness. The patient was a 57-year-old man with alcoholism who was successfully diagnosed with Wernicke encephalopathy, and his hearing improved after high-dose intravenous thiamine therapy. Our case study results and a literature review indicate that video findings and suppression head impulse tests can be used to evaluate Wernicke encephalopathy.

Wernicke encephalopathy, also known as thiamine deficiency, is characterized by a triad of symptoms: ophthalmoplegia, ataxia, and confusion. However, additional symptoms may manifest depending on the area affected by the lesion. Although multiple cranial neuropathies are possible, sudden onset bilateral hearing loss has been described in rare situations as the first manifestation of Wernicke encephalopathy. Here, we present a case report detailing the clinical experience of a patient diagnosed with Wernicke encephalopathy, whose initial presentation included sudden bilateral deafness. The patient was a 57-year-old man with alcoholism who was successfully diagnosed with Wernicke encephalopathy, and his hearing improved after high-dose intravenous thiamine therapy. Our case study results and a literature review indicate that video findings and suppression head impulse tests can be used to evaluate Wernicke encephalopathy.

Wernicke encephalopathy, also known as thiamine deficiency, is characterized by a triad of symptoms: ophthalmoplegia, ataxia, and confusion. However, additional symptoms may manifest depending on the area affected by the lesion. Although multiple cranial neuropathies are possible, sudden onset bilateral hearing loss has been described in rare situations as the first manifestation of Wernicke encephalopathy. Here, we present a case report detailing the clinical experience of a patient diagnosed with Wernicke encephalopathy, whose initial presentation included sudden bilateral deafness. The patient was a 57-year-old man with alcoholism who was successfully diagnosed with Wernicke encephalopathy, and his hearing improved after high-dose intravenous thiamine therapy. Our case study results and a literature review indicate that video findings and suppression head impulse tests can be used to evaluate Wernicke encephalopathy.

A biosynthetic gene cluster for the bioactive fungal sesterterpenoids variecolin ( 1) and variecolactone ( 2) was identified in Aspergillus aculeatus ATCC 16872. Heterologous production of 1 and 2 was achieved in Aspergillus oryzae by expressing the sesterterpene synthase VrcA and the cytochrome P450 VrcB. Intriguingly, the replacement of VrcB with homologous P450s from other fungal terpenoid pathways yielded three new variecolin analogues ( 5- 7). Analysis of the compounds' anticancer activity in vitro and in vivo revealed that although 5 and 1 had comparable activities, 5 was associated with significantly reduced toxic side effects in cancer-bearing mice, indicating its potentially broader therapeutic window. Our study describes the first tests of variecolin and its analogues in animals and demonstrates the utility of synthetic biology for creating molecules with improved biological activities.

This study aimed to develop a machine learning-based 2-year risk prediction model for early identification of patients with rapid progressive immunoglobulin A nephropathy (IgAN). We also assessed the model’s performance to predict the long-term kidney-related outcome of patients. Methods: A retrospective cohort of 1,301 patients with biopsy-proven IgAN from two tertiary hospitals was used to derive and externally validate a random forest-based prediction model predicting primary outcome (30% decline in estimated glomerular filtration rate from baseline or end-stage kidney disease requiring renal replacement therapy) and secondary outcome (improvement of proteinuria) within 2 years after kidney biopsy. Results: For the 2-year prediction of primary outcomes, precision, recall, area-under-the-curve, precision-recall-curve, F1, and Brier score were 0.259, 0.875, 0.771, 0.242, 0.400, and 0.309, respectively. The values for the secondary outcome were 0.904, 0.971, 0.694, 0.903, 0.955, and 0.113, respectively. From Shapley Additive exPlanations analysis, the most informative feature identifying both outcomes was baseline proteinuria. When Kaplan-Meier analysis for 10-year kidney outcome risk was performed with three groups by predicting probabilities derived from the 2-year primary outcome prediction model (low, moderate, and high), high (hazard ratio [HR], 13.00; 95% confidence interval [CI], 9.52–17.77) and moderate (HR, 12.90; 95% CI, 9.92–16.76) groups showed higher risks compared with the low group. From the 2-year secondary outcome prediction model, low (HR, 1.66; 95% CI, 1.42–1.95) and moderate (HR, 1.42; 95% CI, 0.99–2.03) groups were at greater risk for 10-year prognosis than the high group. Conclusion: Our machine learning-based 2-year risk prediction models for the progression of IgAN showed reliable performance and effectively predicted long-term kidney outcome.

This study aimed to develop a machine learning-based 2-year risk prediction model for early identification of patients with rapid progressive immunoglobulin A nephropathy (IgAN). We also assessed the model’s performance to predict the long-term kidney-related outcome of patients. Methods: A retrospective cohort of 1,301 patients with biopsy-proven IgAN from two tertiary hospitals was used to derive and externally validate a random forest-based prediction model predicting primary outcome (30% decline in estimated glomerular filtration rate from baseline or end-stage kidney disease requiring renal replacement therapy) and secondary outcome (improvement of proteinuria) within 2 years after kidney biopsy. Results: For the 2-year prediction of primary outcomes, precision, recall, area-under-the-curve, precision-recall-curve, F1, and Brier score were 0.259, 0.875, 0.771, 0.242, 0.400, and 0.309, respectively. The values for the secondary outcome were 0.904, 0.971, 0.694, 0.903, 0.955, and 0.113, respectively. From Shapley Additive exPlanations analysis, the most informative feature identifying both outcomes was baseline proteinuria. When Kaplan-Meier analysis for 10-year kidney outcome risk was performed with three groups by predicting probabilities derived from the 2-year primary outcome prediction model (low, moderate, and high), high (hazard ratio [HR], 13.00; 95% confidence interval [CI], 9.52–17.77) and moderate (HR, 12.90; 95% CI, 9.92–16.76) groups showed higher risks compared with the low group. From the 2-year secondary outcome prediction model, low (HR, 1.66; 95% CI, 1.42–1.95) and moderate (HR, 1.42; 95% CI, 0.99–2.03) groups were at greater risk for 10-year prognosis than the high group. Conclusion: Our machine learning-based 2-year risk prediction models for the progression of IgAN showed reliable performance and effectively predicted long-term kidney outcome.

This study aimed to develop a machine learning-based 2-year risk prediction model for early identification of patients with rapid progressive immunoglobulin A nephropathy (IgAN). We also assessed the model’s performance to predict the long-term kidney-related outcome of patients. Methods: A retrospective cohort of 1,301 patients with biopsy-proven IgAN from two tertiary hospitals was used to derive and externally validate a random forest-based prediction model predicting primary outcome (30% decline in estimated glomerular filtration rate from baseline or end-stage kidney disease requiring renal replacement therapy) and secondary outcome (improvement of proteinuria) within 2 years after kidney biopsy. Results: For the 2-year prediction of primary outcomes, precision, recall, area-under-the-curve, precision-recall-curve, F1, and Brier score were 0.259, 0.875, 0.771, 0.242, 0.400, and 0.309, respectively. The values for the secondary outcome were 0.904, 0.971, 0.694, 0.903, 0.955, and 0.113, respectively. From Shapley Additive exPlanations analysis, the most informative feature identifying both outcomes was baseline proteinuria. When Kaplan-Meier analysis for 10-year kidney outcome risk was performed with three groups by predicting probabilities derived from the 2-year primary outcome prediction model (low, moderate, and high), high (hazard ratio [HR], 13.00; 95% confidence interval [CI], 9.52–17.77) and moderate (HR, 12.90; 95% CI, 9.92–16.76) groups showed higher risks compared with the low group. From the 2-year secondary outcome prediction model, low (HR, 1.66; 95% CI, 1.42–1.95) and moderate (HR, 1.42; 95% CI, 0.99–2.03) groups were at greater risk for 10-year prognosis than the high group. Conclusion: Our machine learning-based 2-year risk prediction models for the progression of IgAN showed reliable performance and effectively predicted long-term kidney outcome.

This study aimed to develop a machine learning-based 2-year risk prediction model for early identification of patients with rapid progressive immunoglobulin A nephropathy (IgAN). We also assessed the model’s performance to predict the long-term kidney-related outcome of patients. Methods: A retrospective cohort of 1,301 patients with biopsy-proven IgAN from two tertiary hospitals was used to derive and externally validate a random forest-based prediction model predicting primary outcome (30% decline in estimated glomerular filtration rate from baseline or end-stage kidney disease requiring renal replacement therapy) and secondary outcome (improvement of proteinuria) within 2 years after kidney biopsy. Results: For the 2-year prediction of primary outcomes, precision, recall, area-under-the-curve, precision-recall-curve, F1, and Brier score were 0.259, 0.875, 0.771, 0.242, 0.400, and 0.309, respectively. The values for the secondary outcome were 0.904, 0.971, 0.694, 0.903, 0.955, and 0.113, respectively. From Shapley Additive exPlanations analysis, the most informative feature identifying both outcomes was baseline proteinuria. When Kaplan-Meier analysis for 10-year kidney outcome risk was performed with three groups by predicting probabilities derived from the 2-year primary outcome prediction model (low, moderate, and high), high (hazard ratio [HR], 13.00; 95% confidence interval [CI], 9.52–17.77) and moderate (HR, 12.90; 95% CI, 9.92–16.76) groups showed higher risks compared with the low group. From the 2-year secondary outcome prediction model, low (HR, 1.66; 95% CI, 1.42–1.95) and moderate (HR, 1.42; 95% CI, 0.99–2.03) groups were at greater risk for 10-year prognosis than the high group. Conclusion: Our machine learning-based 2-year risk prediction models for the progression of IgAN showed reliable performance and effectively predicted long-term kidney outcome.

Background/Aims: Sorafenib is the standard of care in the management of advanced hepatocellular carcinoma (HCC). The purpose of this study was to investigate the characteristics, treatment patterns and outcomes of sorafenib among HCC patients in South Korea. Methods: This population-based retrospective, single-arm, observational study used the Korean National Health Insurance database to identify patients with HCC who received sorafenib between July 1, 2008, and December 31, 2014. A total of 9,923 patients were recruited in this study. Results: Among 9,923 patients, 6,669 patients (68.2%) received loco-regional therapy prior to sorafenib, and 1,565 patients (15.8%) received combination therapy with concomitant sorafenib;2,591 patients (26.1%) received rescue therapy after sorafenib, and transarterial chemoembolization was the most common modality applied in 1,498 patients (15.1%). A total of 3,591 patients underwent rescue therapy after sorafenib, and the median overall survival was 14.5 months compared to 4.6 months in 7,332 patients who received supportive care after sorafenib. The mean duration of sorafenib administration in all patients was 105.7 days; 7,023 patients (70.8%) received an initial dose of 600 to 800 mg. The longest survival was shown in patients who received the recommended dose of 800 mg, subsequently reduced to 400 mg (15.0 months). The second longest survival was demonstrated in patients with a starting dose of 800 mg, followed by a dose reduction to 400–600 mg (9.6 months). Conclusions Real-life data show that the efficacy of sorafenib seems similar to that observed in clinical trials, suggesting that appropriate subsequent therapy after sorafenib might prolong patient survival.

Purpose: In this study, we aimed to establish humanized patient-derived xenograft (PDX) models for triple-negative breast cancer (TNBC) using cord blood (CB) hematopoietic stem cells (HSCs). Additionally, we attempted to characterize the immune microenvironment of the humanized PDX model to understand the potential implications of altered tumorimmune interactions in the humanized PDX model on the behavior of TNBC cells. Methods: To establish a humanized mouse model, high-purity CD34+ HSCs from CB were transplanted into immunodeficient NOD scid γ mice. Peripheral and intratumoral immune cell compositions of humanized and non-humanized mice were compared. Additionally, RNA sequencing of the tumor tissues was performed to characterize the gene expression features associated with humanization. Results: After transplanting the CD34+ HSCs, CD45+ human immune cells appeared within five weeks. A humanized mouse model showed viable human immune cells in the peripheral blood, lymphoid organs, and in the tumor microenvironment. Humanized TNBC PDX models showed varying rates of tumor growth compared to that of non-humanized mice.RNA sequencing of the tumor tissue showed significant alterations in tumor tissues from the humanized models. tumor necrosis factor receptor superfamily member 11B (TNFRSF11B) is a shared downregulated gene in tumor tissues from humanized models. Silencing of TNFRSF11B in TNBC cell lines significantly reduced cell proliferation, migration, and invasion in vitro. Additionally, TNFRSF11B silenced cells showed decreased tumorigenicity and metastatic capacity in vivo. Conclusion Humanized PDX models successfully recreated tumor-immune interactions in TNBC. TNFRSF11B, a commonly downregulated gene in humanized PDX models, may play a key role in tumor growth and metastasis. Differential tumor growth rates and gene expression patterns highlighted the complexities of the immune response in the tumor microenvironment of humanized PDX models.