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Acute kidney injury (AKI) is a significant complication in burn patients, impacting outcomes substantially. This study explores the heterogeneity of AKI in burn patients by analyzing creatinine time-series data to identify distinct AKI clusters and evaluating routine biomarkers' predictive values. A retrospective cohort analysis was performed on 2608 adult burn patients admitted to Hangang Sacred Heart Hospital's Burn Intensive Care Unit (BICU) from July 2010 to December 2022. Patients were divided into four clusters based on creatinine trajectories, ranging from high-risk, severe cases to lower-risk, short-term care cases. Cluster A, characterized by high-risk, severe cases, showed the highest mortality and severity, with significant predictors being PT and TB. Cluster B, representing intermediate recovery cases, highlighted PT and albumin as useful predictors. Cluster C, a low-risk, high-resilience group, demonstrated predictive values for cystatin C and eGFR cys. Cluster D, comprising lower-risk, short-term care patients, indicated the importance of PT and lactate. Key biomarkers, including albumin, prothrombin time (PT), cystatin C, eGFR cys, and total bilirubin (TB), were identified as significant predictors of AKI development, varying across clusters. Diagnostic accuracy was assessed using area under the curve (AUC) metrics, reclassification metrics (NRI and IDI), and decision curve analysis. Cystatin C and eGFR cys consistently provided significant predictive value over creatinine, with AUC values significantly higher (p < 0.05) in each cluster. This study highlights the need for a tailored, biomarker-driven approach to AKI management in burn patients, advocating for the integration of diverse biomarkers in clinical practice to facilitate personalized treatment strategies. Future research should validate these biomarkers prospectively to confirm their clinical utility. [ABSTRACT FROM AUTHOR]

Hippo signaling restricts tissue growth by inhibiting the transcriptional effector YAP. Here we uncover a role of Hippo signaling and a tumor suppressor function of YAP in estrogen receptor positive (ER+) breast cancer. We find that inhibition of Hippo/MST1/2 or activation of YAP blocks the ERα transcriptional program and ER+ breast cancer growth. Mechanistically, the Hippo pathway transcription factor TEAD physically interacts with ERα to increase its promoter/enhancer occupancy whereas YAP inhibits ERα/TEAD interaction, decreases ERα occupancy on its target promoters/enhancers, and promotes ERα degradation by the proteasome. Furthermore, YAP inhibits hormone-independent transcription of ERα gene (ESR1). Consistently, high levels of YAP correlate with good prognosis of ER+ breast cancer patients. Finally, we find that pharmacological inhibition of Hippo/MST1/2 impeded tumor growth driven by hormone therapy resistant ERα mutants, suggesting that targeting the Hippo-YAP-TEAD signaling axis could be a potential therapeutical strategy to overcome endocrine therapy resistance conferred by ERα mutants. Recent studies have reported that oncoprotein YAP can function as tumour suppressor in certain contexts. Here the authors show that inhibition of Hippo signalling or YAP activation blocks ERα transcriptional program and ER + breast cancer growth and mechanistically this is through YAP interfering with TEAD-ERα signalling axis. [ABSTRACT FROM AUTHOR]

Acute Respiratory Distress Syndrome (ARDS) is a severe complication in burn patients, characterized by rapid lung inflammation and hypoxemia. Managing ARDS is challenging due to its high mortality rates and the complex interplay of various pathophysiological factors. This study aims to investigate the heterogeneity of ARDS in burn patients admitted to the Intensive Care Unit (ICU) and evaluate the predictive efficacy of biomarkers in comparison to the PaO2/FiO2 (PF) ratio. A retrospective cohort study was conducted at the Burn Intensive Care Unit of Hangang Sacred Heart Hospital in Seoul, Korea, from July 2010 to December 2022, involving 2,318 patients. Longitudinal k-means clustering was employed to identify patient subgroups based on PF ratio trajectories. Biomarkers, including albumin, white blood cell (WBC) count, and lactate, were assessed for their predictive accuracy using multivariable logistic regression, area under the curve (AUC) analysis, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Four distinct patient clusters were identified. Cluster A exhibited the highest mortality rate at 54.9%, while Cluster D showed the lowest at 7.9%. Albumin demonstrated significantly higher predictive accuracy in Cluster A (AUC: 0.905, NRI: 0.421) and Cluster C (AUC: 0.915, NRI: 0.845), outperforming the PF ratio in both groups. However, in Clusters B and D, biomarkers did not significantly improve upon the predictive power of the PF ratio. Across all clusters, the integration of biomarkers with the PF ratio led to modest improvements but did not consistently outperform the PF ratio as a standalone predictor. This study reveals substantial heterogeneity in ARDS progression among burn patients, with varying mortality rates and biomarker efficacy across clusters. While biomarkers such as albumin showed potential in specific subgroups, their overall contribution to predictive accuracy was limited. Further multicenter, prospective studies are required to validate these findings and develop more refined predictive models. Personalized treatment strategies, based on biomarker profiles and traditional clinical metrics, could enhance ARDS management in burn patients., (© 2024. The Author(s).)

This study addresses the challenge of predicting mortality in sepsis among burn patients. Given the heterogeneity of sepsis, especially in the context of burn injuries, this study aims to identify reliable biomarkers for mortality prediction. The study is a retrospective review, focusing on the evaluation of various biomarkers and their changes over time in a burn patient cohort. Conducted in the Burn Intensive Care Unit of Hangang Sacred Heart Hospital, the study involved a retrospective review of 1,659 adult burn patients from January 2010 to December 2022. Key biomarkers analyzed include lactate levels, pH, platelets, procalcitonin, and others. Advanced clustering methodologies, such as dynamic time warping and hierarchical clustering, were utilized to classify patients into distinct groups based on their biomarker profiles and clinical outcomes. The study identified four patient clusters with unique lactate level trajectories. Significant findings include the identification of procalcitonin, pH, and platelets as key predictors of mortality, with varying degrees of efficacy across different clusters. For instance, in the "Persistent Rise" cluster, pH and platelet count showed Area Under the Curve (AUC) values of 0.756 and 0.753, respectively, indicating their strong predictive power. The study concludes that a combination of biomarkers, especially lactate dynamics, can effectively predict mortality in burn-induced sepsis. The results advocate for a more personalized approach in managing sepsis in burn patients, considering the specific biomarker trajectories. These findings are crucial for enhancing treatment strategies and improving patient outcomes in burn care., (© 2024. The Author(s).)

Background: Few studies have focused on computed tomography findings before a pancreatic cancer diagnosis. We aimed to investigate the prediagnostic computed tomography findings of patients who had undergone computed tomography within the prediagnostic period of their pancreatic cancer diagnosis., Methods: Between January 2008 and December 2019, 27 patients who underwent contrast-enhanced abdominal or chest computed tomography including the pancreas within 1 year of a pancreatic cancer diagnosis were enrolled in this retrospective study. The prediagnostic computed tomography imaging findings were divided into pancreatic parenchyma and pancreatic duct findings., Results: All patients underwent computed tomography for reasons unrelated to pancreatic cancer. The pancreatic parenchyma and ducts showed normal findings in seven patients and abnormal findings in 20 patients. Hypoattenuating mass-like lesions were detected in nine patients with a median size of 1.2 cm. Six patients had focal pancreatic duct dilatations, and two patients had distal parenchymal atrophy. In three patients, two of these findings were found simultaneously. Taken together, 14 (51.9%) of 27 patients had findings suggestive of pancreatic cancer in prediagnostic computed tomography., Conclusions: In contrast-enhanced computed tomography performed for other purposes, attention should be paid to the presence of a hypoattenuating mass, focal pancreatic duct dilatation, or distal parenchymal atrophy of the pancreas. These features may be clues for an early diagnosis of pancreatic cancer., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jgo.amegroups.com/article/view/10.21037/jgo-22-863/coif). The authors have no conflicts of interest to declare., (2023 Journal of Gastrointestinal Oncology. All rights reserved.)

The GPCR-family protein Smoothened (Smo) is an obligatory signal transducer of the Hedgehog (Hh) signaling pathway. Binding of Hh to its receptor Patched (Ptc) alleviates Ptc-mediated inhibition of Smo, allowing Smo to activate the Cubitus interruptus (Ci)/Gli family of zinc finger transcription factors. The activation of Smo is an early and crucial event in Hh signal transduction. Studies have shown that Hh induces cell surface/ciliary accumulation and phosphorylation of Smo by multiple kinases, including protein kinase A (PKA), casein kinase 1 (CK1), casein kinase 2 (CK2), G protein-coupled receptor kinase 2 (Gprk2/GRK2), and atypical PKC (aPKC). Here, we describe the assays used to examine the phosphorylation and activity of Smo, including in vitro kinase assay, phospho-specific antibodies, luciferase reporter assay, cell surface accumulation, and ciliary localization assays. These assays provide powerful tools to study Smo phosphorylation and activation, leading to mechanistic insight into Smo regulation., (© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)