Background Post-hepatectomy liver failure (PHLF) represents the major determinant for death after liver resection. Early recognition is essential. Perioperative lactate dynamics for risk assessment of PHLF and associated morbidity were evaluated. Methods This was a multicentre observational study of patients undergoing hepatectomy with validation in international high-volume units. Receiver operating characteristics analysis and cut-off calculation for the predictive value of lactate for clinically relevant International Study Group of Liver Surgery grade B/C PHLF (clinically relevant PHLF (CR-PHLF)) were performed. Lactate and other perioperative factors were assessed in a multivariable CR-PHLF regression model. Results The exploratory cohort comprised 509 patients. CR-PHLF, death, overall morbidity and severe morbidity occurred in 7.7, 3.3, 40.9 and 29.3 per cent of patients respectively. The areas under the curve (AUCs) regarding CR-PHLF were 0.829 (95 per cent c.i. 0.770 to 0.888) for maximum lactate within 24 h (Lactate_Max) and 0.870 (95 per cent c.i. 0.818 to 0.922) for postoperative day 1 levels (Lactate_POD1). The respective AUCs in the validation cohort (482 patients) were 0.812 and 0.751 and optimal Lactate_Max cut-offs were identical in both cohorts. Exploration cohort patients with Lactate_Max 50 mg/dl or greater more often developed CR-PHLF (50.0 per cent) than those with Lactate_Max between 20 and 49.9 mg/dl (7.4 per cent) or less than 20 mg/dl (0.5 per cent; P < 0.001). This also applied to death (18.4, 2.7 and 1.4 per cent), severe morbidity (71.1, 35.7 and 14.1 per cent) and associated complications such as acute kidney injury (26.3, 3.1 and 2.3 per cent) and haemorrhage (15.8, 3.1 and 1.4 per cent). These results were confirmed in the validation group. Combining Lactate_Max with Lactate_POD1 further increased AUC (ΔAUC = 0.053) utilizing lactate dynamics for risk assessment. Lactate_Max, major resections, age, cirrhosis and chronic kidney disease were independent risk factors for CR-PHLF. A freely available calculator facilitates clinical risk stratification (www.liver-calculator.com). Conclusion Early postoperative lactate values are powerful, readily available markers for CR-PHLF and associated complications after hepatectomy with potential for guiding postoperative care. Presented in part as an oral video abstract at the 2020 online Congress of the European Society for Surgical Research and the 2021 Congress of the Austrian Surgical Society.
Background Adipose-derived stem cells (ASC) and adipocytes are involved in numerous physiological and pathophysiological conditions, which have been extensively described in subcutaneous and visceral fat depots over the past two decades. However, much less is known about ASC and adipocytes outside classical fat tissue depots and their necessity in tissue remodeling after injury. Therefore, we investigated the etiology of adipocytes in human granulation tissue and define their possible role wound healing. Methods Identification of human wound tissue adipocytes was determined by immunohistochemical staining of granulation tissue sections from patients undergoing surgical debridement. Stromal cell fractions from granulation tissue and subcutaneous fat tissue were generated by collagenase type II-based protocols. Pro- and anti-inflammatory wound bed conditions were mimicked by THP1- and CD14+ monocyte-derived macrophage models in vitro. Effects of macrophage secretome on ASC differentiation and metabolism were determined by immunoblotting, flow cytometry, and microscopy assessing early and late adipocyte differentiation states. Functional rescuing experiments were conducted by lentiviral transduction of wildtype PPARG, IL1RA, and N-chlorotaurine (NCT) treatment. Results Single and clustered adipocyte populations were detected in 11 out of 13 granulation tissue specimens and single-cell suspensions from granulation tissue showed adipogenic differentiation potential. Pro-inflammatory signaling by IFNG/LPS-stimulated macrophages (M (IFNG/LPS)) inhibited the maturation of lipid droplets in differentiated ASC. In contrast, anti-inflammatory IL4/IL13-activated macrophages (M (IL4/IL13)) revealed minor effects on adipocyte development. The M (IFNG/LPS)-induced phenotype was associated with a switch from endogenous fatty acid synthesis to glycolysis-dominated cell metabolism and increased pro-inflammatory cytokine production. Impaired adipogenesis was associated with increased, but seemingly non-functional, CEBPB levels, which failed to induce downstream PPARG and CEBPA. Neither transgenic PPARG overexpression, nor inhibition of IL1B was sufficient to rescue the anti-adipogenic effects induced by IFNG/LPS-activated macrophages. Instead, macrophage co-treatment during stimulation with NCT, a mild oxidant produced by activated granulocytes present in human wounds in vivo, significantly attenuated the anti-adipogenic effects. Conclusions In conclusion, the appearance of adipocytes in wound tissue indicates a prevailing anti-inflammatory environment that could be promoted by NCT treatment and may be associated with improved healing outcomes. Graphical abstract
The expression of human epidermal growth factor receptor 2 (HER2) protein or gene transcripts is critical for therapeutic decision making in breast cancer. We examined the performance of a digitalized and artificial intelligence (AI)-assisted workflow for HER2 status determination in accordance with the American Society of Clinical Oncology (ASCO)/College of Pathologists (CAP) guidelines. Our preliminary cohort consisted of 495 primary breast carcinomas, and our study cohort included 67 primary breast carcinomas and 30 metastatic deposits, which were evaluated for HER2 status by immunohistochemistry (IHC) and in situ hybridization (ISH). Three practicing breast pathologists independently assessed and scored slides, building the ground truth. Following a washout period, pathologists were provided with the results of the AI digital image analysis (DIA) and asked to reassess the slides. Both rounds of assessment from the pathologists were compared to the AI results and ground truth for each slide. We observed an overall HER2 positivity rate of 15% in our study cohort. Moderate agreement (Cohen’s κ 0.59) was observed between the ground truth and AI on IHC, with most discrepancies occurring between 0 and 1+ scores. Inter-observer agreement amongst pathologists was substantial (Fleiss´ κ 0.77) and pathologists’ agreement with AI scores was 80.6%. Substantial agreement of the AI with the ground truth (Cohen´s κ 0.80) was detected on ISH-stained slides, and the accuracy of AI was similar for the primary and metastatic tumors. We demonstrated the feasibility of a combined HER2 IHC and ISH AI workflow, with a Cohen’s κ of 0.94 when assessed in accordance with the ASCO/CAP recommendations.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.