Table of Contents

Table of contents for Volume 10, Issue 3 of the Linfield Magazin

Recent Advances and Future Challenges in Pancreatic Cancer Care: Early Detection, Liquid Biopsies, Precision Medicine and Artificial Intelligence

The incidence of pancreatic ductal adenocarcinoma (PDAC) is rising. While surgical techniques and peri-operative care have improved, the overall survival for PDAC remains poor. Thus, novel and bold research initiatives are needed along the spectrum of clinical care, a few of which will be discussed in this article. Early detection is crucial, with specific high-risk groups possibly benefiting from targeted screening programs. Liquid biopsies (such as circulating exosomes, tumor DNA, or tumor cells) offer promise as multifunctional biomarkers for early detection, treatment guidance, and recurrence monitoring. Precision medicine is being explored via targeted therapies for actionable mutations, such as PARP inhibitors for BRCA mutations, and immunotherapy strategies. Artificial intelligence (AI) is emerging as a powerful tool in medical imaging, biomarker discovery, genetics research, and treatment planning, and it can aid in diagnosis, treatment selection, and patient monitoring. However, its associated challenges include ethics, data security, algorithm reliability, and validation. Collaborative efforts between medical professionals, researchers, and AI experts are vital for unlocking AI’s potential to enhance pancreatic cancer care. In conclusion, despite the challenges, advancements in liquid biopsies, precision medicine, and AI offer hope for enhancing the diagnosis, treatment, and management of pancreatic cancer

A theoretical study on the damping of collective excitations in a Bose-Einstein condensate

We study the damping of low-lying collective excitations of condensates in a weakly interacting Bose gas model within the framework of imaginary time path integral. A general expression of the damping rate has been obtained in the low momentum limit for both the very low temperature regime and the higher temperature regime. For the latter, the result is new and applicable to recent experiments. Theoretical predictions for the damping rate are compared with the experimental values.Comment: 15 pages, LaTeX, revised for minor corrections on LaTeX file forma

Non-invasive focus localization, right ventricular epicardial potential mapping in patients with an MRI-conditional pacemaker system ‐ a pilot study

Abstract Background With the advent of magnetic resonance imaging (MRI) conditional pacemaker systems, the possibility of performing MRI in pacemaker patients has been introduced. Besides for the detailed evaluation of atrial and ventricular volumes and function, MRI can be used in combination with body surface potential mapping (BSPM) in a non-invasive inverse potential mapping (IPM) strategy. In non-invasive IPM, epicardial potentials are reconstructed from recorded body surface potentials (BSP). In order to investigate whether an IPM method with a limited number of electrodes could be used for the purpose of non-invasive focus localization, it was applied in patients with implanted pacing devices. Ventricular paced beats were used to simulate ventricular ectopic foci. Methods Ten patients with an MRI-conditional pacemaker system and a structurally normal heart were studied. Patientspecific 3D thorax volume models were reconstructed from the MRI images. BSP were recorded during ventricular pacing. Epicardial potentials were inversely calculated from the BSP. The site of epicardial breakthrough was compared to the position of the ventricular lead tip on MRI and the distance between these points was determined. Results For all patients, the site of earliest epicardial depolarization could be identified. When the tip of the pacing lead was implanted in vicinity to the epicardium, i.e. right ventricular (RV) apex or RV outflow tract, the distance between lead tip position and epicardial breakthrough was 6.0±1.9 mm. Conclusions In conclusion, the combined MRI and IPM method is clinically applicable and can identify sites of earliest depolarization with a clinically useful accuracy

Qadence: a differentiable interface for digital-analog programs

Digital-analog quantum computing (DAQC) is an alternative paradigm for universal quantum computation combining digital single-qubit gates with global analog operations acting on a register of interacting qubits. Currently, no available open-source software is tailored to express, differentiate, and execute programs within the DAQC paradigm. In this work, we address this shortfall by presenting Qadence, a high-level programming interface for building complex digital-analog quantum programs developed at Pasqal. Thanks to its flexible interface, native differentiability, and focus on real-device execution, Qadence aims at advancing research on variational quantum algorithms built for native DAQC platforms such as Rydberg atom arrays

The Difficulty of Detecting Occult Metastases in Patients with Potentially Resectable Pancreatic Cancer:Development and External Validation of a Preoperative Prediction Model

Occult metastases are detected in 10–15% of patients during exploratory laparotomy for pancreatic cancer. This study developed and externally validated a model to predict occult metastases in patients with potentially resectable pancreatic cancer. Model development was performed within the Dutch Pancreatic Cancer Audit, including all patients operated for pancreatic cancer (January 2013–December 2017). Multivariable logistic regression analysis based on the Akaike Information Criteria was performed with intraoperative pathologically proven metastases as the outcome. The model was externally validated with a cohort from the University Hospital of Verona (January 2013–December 2017). For model development, 2262 patients were included of whom 235 (10%) had occult metastases, located in the liver (n = 143, 61%), peritoneum (n = 73, 31%), or both (n = 19, 8%). The model included age (OR 1.02, 95% CI 1.00–1.03), BMI (OR 0.96, 95% CI 0.93–0.99), preoperative nutritional support (OR 1.73, 95% CI 1.01–2.74), tumor diameter (OR 1.60, 95% CI 1.04–2.45), tumor composition (solid vs. cystic) (OR 2.33, 95% CI 1.20–4.35), and indeterminate lesions on preoperative imaging (OR 4.01, 95% CI 2.16–7.43). External validation showed poor discrimination with a C-statistic of 0.56. Although some predictor variables were significantly associated with occult metastases, the model performed insufficiently at external validation.</p

In silico assessment of potential druggable pockets on the surface of α1-Antitrypsin conformers

The search for druggable pockets on the surface of a protein is often performed on a single conformer, treated as a rigid body. Transient druggable pockets may be missed in this approach. Here, we describe a methodology for systematic in silico analysis of surface clefts across multiple conformers of the metastable protein α1-antitrypsin (A1AT). Pathological mutations disturb the conformational landscape of A1AT, triggering polymerisation that leads to emphysema and hepatic cirrhosis. Computational screens for small molecule inhibitors of polymerisation have generally focused on one major druggable site visible in all crystal structures of native A1AT. In an alternative approach, we scan all surface clefts observed in crystal structures of A1AT and in 100 computationally produced conformers, mimicking the native solution ensemble. We assess the persistence, variability and druggability of these pockets. Finally, we employ molecular docking using publicly available libraries of small molecules to explore scaffold preferences for each site. Our approach identifies a number of novel target sites for drug design. In particular one transient site shows favourable characteristics for druggability due to high enclosure and hydrophobicity. Hits against this and other druggable sites achieve docking scores corresponding to a Kd in the µM–nM range, comparing favourably with a recently identified promising lead. Preliminary ThermoFluor studies support the docking predictions. In conclusion, our strategy shows considerable promise compared with the conventional single pocket/single conformer approach to in silico screening. Our best-scoring ligands warrant further experimental investigation

Detection, Treatment, and Survival of Pancreatic Cancer Recurrence in the Netherlands A Nationwide Analysis

OBJECTIVE: To evaluate whether detection of recurrent pancreatic ductal adenocarcinoma (PDAC) in an early, asymptomatic stage increases the number of patients receiving additional treatment, subsequently improving survival. SUMMARY OF BACKGROUND DATA: International guidelines disagree on the value of standardized postoperative surveillance for early detection and treatment of PDAC recurrence. METHODS: A nationwide, observational cohort study was performed including all patients who underwent PDAC resection (2014-2016). Prospective baseline and perioperative data were retrieved from the Dutch Pancreatic Cancer Audit. Data on follow-up, treatment, and survival were collected retrospectively. Overall survival (OS) was evaluated using multivariable Cox regression analysis, before and after propensity-score matching, stratified for patients with symptomatic and asymptomatic recurrence. RESULTS: Eight hundred thirty-six patients with a median follow-up of 37 months (interquartile range 30-48) were analyzed. Of those, 670 patients (80%) developed PDAC recurrence after a median follow-up of 10 months (interquartile range 5-17). Additional treatment was performed in 159/511 patients (31%) with symptomatic recurrence versus 77/159 (48%) asymptomatic patients (P < 0.001). After propensity-score matching on lymph node ratio, adjuvant therapy, disease-free survival, and recurrence site, additional treatment was independently associated with improved OS for both symptomatic patients [hazard ratio 0.53 (95% confidence interval 0.42-0.67); P < 0.001] and asymptomatic patients [hazard ratio 0.45 (95% confidence interval 0.29-0.70); P < 0.001]. CONCLUSIONS: Additional treatment of PDAC recurrence was independently associated with improved OS, with asymptomatic patients having a higher probability to receive recurrence treatment. Therefore, standardized postoperative surveillance aiming to detect PDAC recurrence before the onset of symptoms has the potential to improve survival. This provides a rationale for prospective studies on standardized surveillance after PDAC resection

Preoperative predictors for early and very early disease recurrence in patients undergoing resection of pancreatic ductal adenocarcinoma

BACKGROUND: This study aimed to identify predictors for early and very early disease recurrence in patients undergoing resection of pancreatic ductal adenocarcinoma (PDAC) resection with and without neoadjuvant therapy. METHODS: Included were patients who underwent PDAC resection (2014-2016). Multivariable multinomial regression was performed to identify preoperative predictors for manifestation of recurrence within 3, 6 and 12 months after PDAC resection. RESULTS: 836 patients with a median follow-up of 37 (interquartile range [IQR] 30-48) months and overall survival of 18 (IQR 10-32) months were analyzed. 670 patients (80%) developed recurrence: 82 patients (10%) <3 months, 96 patients (11%) within 3-6 months and 226 patients (27%) within 6-12 months. LogCA 19-9 (OR 1.25 [95% CI 1.10-1.41]; P < 0.001) and neoadjuvant treatment (OR 0.09 [95% CI 0.01-0.68]; P = 0.02) were associated with recurrence <3 months. LogCA 19-9 (OR 1.23 [95% CI 1.10-1.38]; P < 0.001) and 0-90° venous involvement on CT imaging (OR 2.93 [95% CI 1.60-5.37]; P < 0.001) were associated with recurrence within 3-6 months. A Charlson Age Comorbidity Index ≥4 (OR 1.53 [95% CI 1.09-2.16]; P = 0.02) and logCA 19-9 (OR 1.24 [95% CI 1.14-1.35]; P < 0.001) were related to recurrence within 6-12 months. CONCLUSION: This study demonstrates preoperative predictors that are associated with the manifestation of early and very early recurrence after PDAC resection. Knowledge of these predictors can be used to guide individualized surveillance and treatment strategies

Textbook Outcome Nationwide Analysis of a Novel Quality Measure in Pancreatic Surgery:Nationwide Analysis of a Novel Quality Measure in Pancreatic Surgery

Background: Textbook outcome (TO) is a multidimensional measure for quality assurance, reflecting the ‘‘ideal’’ surgical outcome. Methods: Post-hoc analysis of patients who underwent pancreatoduodenectomy (PD) or distal pancreatectomy (DP) for all indications between 2014 and 2017, queried from the nationwide prospective Dutch Pancreatic Cancer Audit. An international survey was conducted among 24 experts from 10 countries to reach consensus on the requirements for TO in pancreatic surgery. Univariable and multivariable logistic regression was performed to identify TO predictors. Between-hospital variation in TO rates was compared using observed-versus-expected rates. Results: Based on the survey (92% response rate), TO was defined by the absence of postoperative pancreatic fistula, bile leak, postpancreatectomy hemorrhage (all ISGPS grade B/C), severe complications (Clavien–Dindo III), readmission, and in-hospital mortality. Overall, 3341 patients were included (2633 (79%) PD and 708 (21%) DP) of whom 60.3% achieved TO; 58.3% for PD and 67.4% for DP. On multivariable analysis, ASA class 3 predicted a worse TO rate after PD (ASA 3 OR 0.59 [0.44–0.80]), whereas a dilated pancreatic duct (>3 mm) and pancreatic ductal ade