Effects of Pancreatic Fistula After Minimally Invasive and Open Pancreatoduodenectomy.

Importance: Postoperative pancreatic fistulas (POPF) are the biggest contributor to surgical morbidity and mortality after pancreatoduodenectomy. The impact of POPF could be influenced by the surgical approach.

Objective: To assess the clinical impact of POPF in patients undergoing minimally invasive pancreatoduodenectomy (MIPD) and open pancreatoduodenectomy (OPD).

Unveiling the biological side of PET-derived biomarkers: a simulation-based approach applied to PDAC assessment.

Purpose: Radiomics has revolutionized clinical research by enabling objective measurements of imaging-derived biomarkers. However, the true potential of radiomics necessitates a comprehensive understanding of the biological basis of extracted features to serve as a clinical decision support. In this work, we propose an end-to-end framework for the in silico simulation of [F]FLT PET imaging process in Pancreatic Ductal Adenocarcinoma, accounting for the biological characterization of tissues (including perfusion and fibrosis) on tracer delivery.

Tackling challenges in rare diseases: The ISGACA approach on non-pancreatic cancers in the periampullary region.

Objective: Rare but aggressive cancer types like non-pancreatic periampullary cancers pose unique challenges for cancer research due to their low incidence rates and lack of consensus on optimal treatment strategies, therefore necessitating a collaborative approach. The International Study Group on non-pancreatic peri-Ampullary CAncer (ISGACA) aimed to build a collaborative initiative to pool expertise, funding opportunities, and data from over 60 medical centers, in order to improve outcomes for underrepresented patients with rare cancers.

Methods: The ISGACA approach predefined a stepwise approach including a research scope, establishing a dedicated steering committee, creating a recognizable brand, identifying research gaps, following a well-defined timeline, ensuring robust data collection, addressing legal and ethical considerations, securing financial resources, investing in research ethics training and statistical expertise, raising awareness, creating uniformity, and initiating prospective studies.

Uncertainty quantification and sensitivity analysis of neuron models with ion concentration dynamics.

This paper provides a comprehensive and computationally efficient case study for uncertainty quantification (UQ) and global sensitivity analysis (GSA) in a neuron model incorporating ion concentration dynamics. We address how challenges with UQ and GSA in this context can be approached and solved, including challenges related to computational cost, parameters affecting the system's resting state, and the presence of both fast and slow dynamics. Specifically, we analyze the electrodiffusive neuron-extracellular-glia (edNEG) model, which captures electrical potentials, ion concentrations (Na+, K+, Ca2+, and Cl-), and volume changes across six compartments.

Deep learning-based surrogate models for parametrized PDEs: Handling geometric variability through graph neural networks.

Mesh-based simulations play a key role when modeling complex physical systems that, in many disciplines across science and engineering, require the solution to parametrized time-dependent nonlinear partial differential equations (PDEs). In this context, full order models (FOMs), such as those relying on the finite element method, can reach high levels of accuracy, however often yielding intensive simulations to run. For this reason, surrogate models are developed to replace computationally expensive solvers with more efficient ones, which can strike favorable trade-offs between accuracy and efficiency.

Efficient approximation of cardiac mechanics through reduced-order modeling with deep learning-based operator approximation.

Reducing the computational time required by high-fidelity, full-order models (FOMs) for the solution of problems in cardiac mechanics is crucial to allow the translation of patient-specific simulations into clinical practice. Indeed, while FOMs, such as those based on the finite element method, provide valuable information on the cardiac mechanical function, accurate numerical results can be obtained at the price of very fine spatio-temporal discretizations. As a matter of fact, simulating even just a few heartbeats can require up to hours of wall time on high-performance computing architectures.

Minimally invasive versus open distal pancreatectomy for resectable pancreatic cancer (DIPLOMA): an international randomised non-inferiority trial.

Background: The oncological safety of minimally invasive surgery has been questioned for several abdominal cancers. Concerns also exist regarding the use of minimally invasive distal pancreatectomy (MIDP) in patients with resectable pancreatic cancer as randomised trials are lacking.

Methods: In this international randomised non-inferiority trial, we recruited adults with resectable pancreatic cancer from 35 centres in 12 countries.

Learning Curves of Minimally Invasive Distal Pancreatectomy in Experienced Pancreatic Centers.

Importance: Understanding the learning curve of a new complex surgical technique helps to reduce potential patient harm. Current series on the learning curve of minimally invasive distal pancreatectomy (MIDP) are mostly small, single-center series, thus providing limited data.

Objective: To evaluate the length of pooled learning curves of MIDP in experienced centers.

Effects of clopidogrel bisulfate on B16-F10 cells and tumor development in a murine model of melanoma.

Metastatic melanoma is a very aggressive skin cancer. Platelets are constituents of the tumor microenvironment and, when activated, contribute to cancer progression, especially metastasis and inflammation. P2Y12 is an adenosine diphosphate receptor that triggers platelet activation.

Use and outcome of minimally invasive pancreatic surgery in the European E-MIPS registry.

Background: The European registry for minimally invasive pancreatic surgery (E-MIPS) collects data on laparoscopic and robotic MIPS in low- and high-volume centers across Europe.

Methods: Analysis of the first year (2019) of the E-MIPS registry, including minimally invasive distal pancreatectomy (MIDP) and minimally invasive pancreatoduodenectomy (MIPD). Primary outcome was 90-day mortality.

Reduced Order Modeling of Nonlinear Vibrating Multiphysics Microstructures with Deep Learning-Based Approaches.

Micro-electro-mechanical-systems are complex structures, often involving nonlinearites of geometric and multiphysics nature, that are used as sensors and actuators in countless applications. Starting from full-order representations, we apply deep learning techniques to generate accurate, efficient, and real-time reduced order models to be used for the simulation and optimization of higher-level complex systems. We extensively test the reliability of the proposed procedures on micromirrors, arches, and gyroscopes, as well as displaying intricate dynamical evolutions such as internal resonances.

Robot-Assisted Versus Laparoscopic Distal Pancreatectomy in Patients with Resectable Pancreatic Cancer: An International, Retrospective, Cohort Study.

Background: Robot-assisted distal pancreatectomy (RDP) is increasingly used as an alternative to laparoscopic distal pancreatectomy (LDP) in patients with resectable pancreatic cancer but comparative multicenter studies confirming the safety and efficacy of RDP are lacking.

Methods: An international, multicenter, retrospective, cohort study, including consecutive patients undergoing RDP and LDP for resectable pancreatic cancer in 33 experienced centers from 11 countries (2010-2019). The primary outcome was R0-resection.

Learning high-order interactions for polygenic risk prediction.

Within the framework of precision medicine, the stratification of individual genetic susceptibility based on inherited DNA variation has paramount relevance. However, one of the most relevant pitfalls of traditional Polygenic Risk Scores (PRS) approaches is their inability to model complex high-order non-linear SNP-SNP interactions and their effect on the phenotype (e.g.

Approximation bounds for convolutional neural networks in operator learning.

Recently, deep Convolutional Neural Networks (CNNs) have proven to be successful when employed in areas such as reduced order modeling of parametrized PDEs. Despite their accuracy and efficiency, the approaches available in the literature still lack a rigorous justification on their mathematical foundations. Motivated by this fact, in this paper we derive rigorous error bounds for the approximation of nonlinear operators by means of CNN models.

Stereotactic Radiosurgery with Gamma Knife in Recurrent Rathke's Cleft Cyst: Case Report and Literature Analysis.

Background: Rathke's cleft cyst is a benign expansive lesion of the sella turcica. If related to clinical disorders, the patient needs surgical treatment.

Objective: To demonstrate the efficacy of radiosurgery in the treatment of relapse of Rathke's cleft cyst as an alternative to surgery.

Slow Conduction Corridors and Pivot Sites Characterize the Electrical Remodeling in Atrial Fibrillation.

Objectives: This study aimed to evaluate the progression of electrophysiological phenomena in a cohort of patients with paroxysmal atrial fibrillation (PAF) and persistent atrial fibrillation (PsAF).

Background: Electrical remodeling has been conjectured to determine atrial fibrillation (AF) progression.

Methods: High-density electroanatomic maps during sinus rhythm of 20 patients with AF (10 PAF, 10 PsAF) were compared with 5 healthy control subjects (subjects undergoing ablation of a left-sided accessory pathway).

Discriminative and Predictive Analysis of the Brazilian Version of the Örebro Musculoskeletal Pain Screening Questionnaire (ÖMPSQ) Short-Form in Patients With Low Back Pain.

Objective: The purpose of this study was to analyze the discriminative and predictive validity of the Brazilian Portuguese version of the Örebro Musculoskeletal Pain Screening Questionnaire Short-Form (ÖMPSQ-Short).

Methods: In this prospective longitudinal cohort study, the ÖMPSQ-Short was administered to 150 patients with acute, subacute, and chronic nonspecific low back pain. A 6-month follow-up was also completed to assess the predictive ability of the questionnaire for risk of pain, disability, and absence from work.

Are the forearm muscles excited equally in different, professional piano players?

Background And Objectives: Professional pianists tend to develop playing-related musculoskeletal disorders mostly in the forearm. These injuries are often due to overuse, suggesting the existence of a common forearm region where muscles are often excited during piano playing across subjects. Here we use a grid of electrodes to test this hypothesis, assessing where EMGs with greatest amplitude are more likely to be detected when expert pianists perform different excerpts.

It is the lymph node ratio that determines survival and recurrence patterns in resected distal cholangiocarcinoma. A multicenter international study.

Background: Distal cholangiocarcinoma (dCC) is still associated with a poor overall survival (OS). This study aims to investigate the impact of novel prognostic scores in comparison with more traditional ones.

Methods: Multicentric retrospective analysis of patients who underwent a pancreatoduodenectomy (PD) for dCC.

SUIHTER: a new mathematical model for COVID-19. Application to the analysis of the second epidemic outbreak in Italy.

The COVID-19 epidemic is the latest in a long list of pandemics that have affected humankind in the last century. In this paper, we propose a novel mathematical epidemiological model named SUIHTER from the names of the seven compartments that it comprises: susceptible uninfected individuals (), undetected (both asymptomatic and symptomatic) infected (), isolated infected (), hospitalized (), threatened (), extinct () and recovered (). A suitable parameter calibration that is based on the combined use of the least-squares method and the Markov chain Monte Carlo method is proposed with the aim of reproducing the past history of the epidemic in Italy, which surfaced in late February and is still ongoing to date, and of validating SUIHTER in terms of its predicting capabilities.

Outcomes comparison of Pancreato-Gastrostomy and Isolated Jejunal Loop Pancreato-Jejunostomy following Pancreato-Duodenectomy in patients with soft pancreas and at moderate-high risk for POPF: a retrospective multicenter experience-based analysis.

Following pancreatoduodenectomy (PD), the modality of pancreato-enteric continuity restoration may impact on postoperative pancreatic fistula (POPF) risk. The aim of this study is to compare, among patients with soft pancreas and at moderate/high risk for POPF, the outcomes of PD with Pancreato-Gastrostomy (PG), versus Isolated Jejunal Loop Pancreato-Jejunostomy (IJL-PJ). 193 patients with a Callery Fistula Risk Score (C-FRS) ≥ 3 operated at 3 HPB Units, two performing PG and one IJL-PJ as their preferred anastomotic technique following PD (2009-2019) were included in this study (PG = 123, IJL-PJ = 70).

POD-Enhanced Deep Learning-Based Reduced Order Models for the Real-Time Simulation of Cardiac Electrophysiology in the Left Atrium.

The numerical simulation of multiple scenarios easily becomes computationally prohibitive for cardiac electrophysiology (EP) problems if relying on usual high-fidelity, full order models (FOMs). Likewise, the use of traditional reduced order models (ROMs) for parametrized PDEs to speed up the solution of the aforementioned problems can be problematic. This is primarily due to the strong variability characterizing the solution set and to the nonlinear nature of the input-output maps that we intend to reconstruct numerically.

Hepatectomy for Metabolic Associated Fatty Liver Disease (MAFLD) related HCC: Propensity case-matched analysis with viral- and alcohol-related HCC.

Background And Aims: We investigated the clinical impact of the newly defined metabolic-associated fatty liver disease (MAFLD) in patients undergoing hepatectomy for HCC (MAFLD-HCC) comparing the characteristics and outcomes of patients with MAFLD-HCC to viral- and alcoholic-related HCC (HCV-HCC, HBV-HCC, A-HCC).

Methods: A retrospective analysis of patients included in the He.RC.

A Computational Study of the Electrophysiological Substrate in Patients Suffering From Atrial Fibrillation.

In the context of cardiac electrophysiology, we propose a novel computational approach to highlight and explain the long-debated mechanisms behind atrial fibrillation (AF) and to reliably numerically predict its induction and sustainment. A key role is played, in this respect, by a new way of setting a parametrization of electrophysiological mathematical models based on conduction velocities; these latter are estimated from high-density mapping data, which provide a detailed characterization of patients' electrophysiological substrate during sinus rhythm. We integrate numerically approximated conduction velocities into a mathematical model consisting of a coupled system of partial and ordinary differential equations, formed by the monodomain equation and the Courtemanche-Ramirez-Nattel model.