TIRESIA and TISBE: Explainable Artificial Intelligence Based Web Platforms for the Transparent Assessment of the Developmental Toxicity of Chemicals and Drugs.

Developmental toxicity is key human health endpoint, especially relevant for safeguarding maternal and child well-being. It is an object of increasing attention from international regulatory bodies such as the US EPA (US Environmental Protection Agency) and ECHA (European CHemicals Agency). In this challenging scenario, non-test methods employing explainable artificial intelligence based techniques can provide a significant help to derive transparent predictive models whose results can be easily interpreted to assess the developmental toxicity of new chemicals at very early stages. To accomplish this task, we have developed web platforms such as TIRESIA and TISBE.Based on a benchmark dataset, TIRESIA employs an explainable artificial intelligence approach combined with SHAP analysis to unveil the molecular features responsible for calculating the developmental toxicity. Descending from TIRESIA, TISBE employs a larger dataset, an explainable artificial intelligence framework based on a fragment-based fingerprint encoding, a consensus classifier, and a new double top-down applicability domain. We report here some practical examples for getting started with TIRESIA and TISBE.

Small Molecules for the Treatment of Long-COVID-Related Vascular Damage and Abnormal Blood Clotting: A Patent-Based Appraisal.

People affected by COVID-19 are exposed to, among others, abnormal clotting and endothelial dysfunction, which may result in deep vein thrombosis, cerebrovascular disorders, and ischemic and non-ischemic heart diseases, to mention a few. Treatments for COVID-19 include antiplatelet (e.g., aspirin, clopidogrel) and anticoagulant agents, but their impact on morbidity and mortality has not been proven. In addition, due to viremia-associated interconnected prothrombotic and proinflammatory events, anti-inflammatory drugs have also been investigated for their ability to mitigate against immune dysregulation due to the cytokine storm. By retrieving patent literature published in the last two years, small molecules patented for long-COVID-related blood clotting and hematological complications are herein examined, along with supporting evidence from preclinical and clinical studies. An overview of the main features and therapeutic potentials of small molecules is provided for the thromboxane receptor antagonist ramatroban, the pan-caspase inhibitor emricasan, and the sodium-hydrogen antiporter 1 (NHE-1) inhibitor rimeporide, as well as natural polyphenolic compounds.

TISBE: A Public Web Platform for the Consensus-Based Explainable Prediction of Developmental Toxicity.

Despite being extremely relevant for the protection of prenatal and neonatal health, the developmental toxicity (Dev Tox) is a highly complex endpoint whose molecular rationale is still largely unknown. The lack of availability of high-quality data as well as robust nontesting methods makes its understanding even more difficult. Thus, the application of new explainable alternative methods is of utmost importance, with Dev Tox being one of the most animal-intensive research themes of regulatory toxicology. Descending from TIRESIA (Toxicology Intelligence and Regulatory Evaluations for Scientific and Industry Applications), the present work describes TISBE (TIRESIA Improved on Structure-Based Explainability), a new public web platform implementing four fundamental advancements for in silico analyses: a three times larger dataset, a transparent XAI (explainable artificial intelligence) framework employing a fragment-based fingerprint coding, a novel consensus classifier based on five independent machine learning models, and a new applicability domain (AD) method based on a double top-down approach for better estimating the prediction reliability. The training set (TS) includes as many as 1008 chemicals annotated with experimental toxicity values. Based on a 5-fold cross-validation, a median value of 0.410 for the Matthews correlation coefficient was calculated; TISBE was very effective, with a median value of sensitivity and specificity equal to 0.984 and 0.274, respectively. TISBE was applied on two external pools made of 1484 bioactive compounds and 85 pediatric drugs taken from ChEMBL (Chemical European Molecular Biology Laboratory) and TEDDY (Task-Force in Europe for Drug Development in the Young) repositories, respectively. Notably, TISBE gives users the option to clearly spot the molecular fragments responsible for the toxicity or the safety of a given chemical query and is available for free at https://prometheus.farmacia.uniba.it/tisbe.

Where developmental toxicity meets explainable artificial intelligence: state-of-the-art and perspectives.

INTRODUCTION: The application of Artificial Intelligence (AI) to predictive toxicology is rapidly increasing, particularly aiming to develop non-testing methods that effectively address ethical concerns and reduce economic costs. In this context, Developmental Toxicity (Dev Tox) stands as a key human health endpoint, especially significant for safeguarding maternal and child well-being. AREAS COVERED: This review outlines the existing methods employed in Dev Tox predictions and underscores the benefits of utilizing New Approach Methodologies (NAMs), specifically focusing on eXplainable Artificial Intelligence (XAI), which proves highly efficient in constructing reliable and transparent models aligned with recommendations from international regulatory bodies. EXPERT OPINION: The limited availability of high-quality data and the absence of dependable Dev Tox methodologies render XAI an appealing avenue for systematically developing interpretable and transparent models, which hold immense potential for both scientific evaluations and regulatory decision-making.

Making sense of chemical space network shows signs of criticality.

Chemical space modelling has great importance in unveiling and visualising latent information, which is critical in predictive toxicology related to drug discovery process. While the use of traditional molecular descriptors and fingerprints may suffer from the so-called curse of dimensionality, complex networks are devoid of the typical drawbacks of coordinate-based representations. Herein, we use chemical space networks (CSNs) to analyse the case of the developmental toxicity (Dev Tox), which remains a challenging endpoint for the difficulty of gathering enough reliable data despite very important for the protection of the maternal and child health. Our study proved that the Dev Tox CSN has a complex non-random organisation and can thus provide a wealth of meaningful information also for predictive purposes. At a phase transition, chemical similarities highlight well-established toxicophores, such as aryl derivatives, mostly neurotoxic hydantoins, barbiturates and amino alcohols, steroids, and volatile organic compounds ether-like chemicals, which are strongly suspected of the Dev Tox onset and can thus be employed as effective alerts for prioritising chemicals before testing.

CIRCE: Web-Based Platform for the Prediction of Cannabinoid Receptor Ligands Using Explainable Machine Learning.

The endocannabinoid system, which includes cannabinoid receptor 1 and 2 subtypes (CB1R and CB2R, respectively), is responsible for the onset of various pathologies including neurodegeneration, cancer, neuropathic and inflammatory pain, obesity, and inflammatory bowel disease. Given the high similarity of CB1R and CB2R, generating subtype-selective ligands is still an open challenge. In this work, the Cannabinoid Iterative Revaluation for Classification and Explanation (CIRCE) compound prediction platform has been generated based on explainable machine learning to support the design of selective CB1R and CB2R ligands. Multilayer classifiers were combined with Shapley value analysis to facilitate explainable predictions. In test calculations, CIRCE predictions reached ∼80% accuracy and structural features determining ligand predictions were rationalized. CIRCE was designed as a web-based prediction platform that is made freely available as a part of our study.

Synthesis, computational and experimental pharmacological studies for (thio)ether-triazine 5-HT6R ligands with noticeable action on AChE/BChE and chalcogen-dependent intrinsic activity in search for new class of drugs against Alzheimer's disease.

Alzheimer's disease is becoming a growing problem increasing at a tremendous rate. Serotonin 5-HT6 receptors appear to be a particularly attractive target from a therapeutic perspective, due to their involvement not only in cognitive processes, but also in depression and psychosis. In this work, we present the synthesis and broad biological characterization of a new series of 18 compounds with a unique 1,3,5-triazine backbone, as potent 5-HT6 receptor ligands. The main aim of this research is to compare the biological activity of the newly synthesized sulfur derivatives with their oxygen analogues and their N-demethylated O- and S-metabolites obtained for the first time. Most of the new triazines displayed high affinity (Ki < 200 nM) and selectivity towards 5-HT6R, with respect to 5-HT2AR, 5-HT7R, and D2R, in the radioligand binding assays. For selected, active compounds crystallographic studies, functional bioassays, and ADME-Tox profile in vitro were performed. The exciting novelty is that the sulfur derivatives exhibit an agonistic mode of action contrary to all other compounds obtained to date in this chemical class herein and previously reported. Advanced computational studies indicated that this intriguing functional shift might be caused by presence of chalcogen bonds formed only by the sulfur atom. In addition, the N-demethylated derivatives have emerged highly potent antioxidants and, moreover, show a significant improvement in metabolic stability compared to the parent structures. The cholinesterase study present micromolar inhibitory AChE and BChE activity for both 5-HT6 agonist 19 and potent antagonist 5. Finally, the behavioral experiments of compound 19 demonstrated its antidepressant-like properties and slight ability to improve cognitive deficits, without inducing memory impairments by itself. Described pharmacological properties of both compounds (5 and 19) allow to give a design clue for the development of multitarget compounds with 5-HT6 (both agonist and antagonist)/AChE and/or BChE mechanism in the group of 1,3,5-triazine derivatives.

Short-term anti-remodeling effects of gliflozins in diabetic patients with heart failure and reduced ejection fraction: an explainable artificial intelligence approach.

Introduction: Sodium-glucose cotransporter type 2 inhibitors (SGLT2i), gliflozins, play an emerging role for the treatment of heart failure with reduced left ventricular ejection fraction (HFrEF). Nevertheless, the effects of SGLT2i on ventricular remodeling and function have not been completely understood yet. Explainable artificial intelligence represents an unprecedented explorative option to clinical research in this field. Based on echocardiographic evaluations, we identified some key clinical responses to gliflozins by employing a machine learning approach. Methods: Seventy-eight consecutive diabetic outpatients followed for HFrEF were enrolled in the study. Using a random forests classification, a single subject analysis was performed to define the profile of patients treated with gliflozins. An explainability analysis using Shapley values was used to outline clinical parameters that mostly improved after gliflozin therapy and machine learning runs highlighted specific variables predictive of gliflozin response. Results: The five-fold cross-validation analyses showed that gliflozins patients can be identified with a 0.70 ± 0.03% accuracy. The most relevant parameters distinguishing gliflozins patients were Right Ventricular S'-Velocity, Left Ventricular End Systolic Diameter and E/e' ratio. In addition, low Tricuspid Annular Plane Systolic Excursion values along with high Left Ventricular End Systolic Diameter and End Diastolic Volume values were associated to lower gliflozin efficacy in terms of anti-remodeling effects. Discussion: In conclusion, a machine learning analysis on a population of diabetic patients with HFrEF showed that SGLT2i treatment improved left ventricular remodeling, left ventricular diastolic and biventricular systolic function. This cardiovascular response may be predicted by routine echocardiographic parameters, with an explainable artificial intelligence approach, suggesting a lower efficacy in case of advanced stages of cardiac remodeling.

TIRESIA: An eXplainable Artificial Intelligence Platform for Predicting Developmental Toxicity.

Herein, a robust and reproducible eXplainable Artificial Intelligence (XAI) approach is presented, which allows prediction of developmental toxicity, a challenging human-health endpoint in toxicology. The application of XAI as an alternative method is of the utmost importance with developmental toxicity being one of the most animal-intensive areas of regulatory toxicology. In this work, the established CAESAR (Computer Assisted Evaluation of industrial chemical Substances According to Regulations) training set made of 234 chemicals for model learning is employed. Two test sets, including as a whole 585 chemicals, were instead used for validation and generalization purposes. The proposed framework favorably compares with the state-of-the-art approaches in terms of accuracy, sensitivity, and specificity, thus resulting in a reliable support system for developmental toxicity ensuring informativeness, uncertainty estimation, generalization, and transparency. Based on the eXtreme Gradient Boosting (XGB) algorithm, our predictive model provides easy interpretative keys based on specific molecular descriptors and structural alerts enabling one to distinguish toxic and nontoxic chemicals. Inspired by the Organisation for Economic Co-operation and Development (OECD) principles for the validation of Quantitative Structure-Activity Relationships (QSARs) for regulatory purposes, the results are summarized in a standard report in portable document format, enclosing also details concerned with a density-based model applicability domain and SHAP (SHapley Additive exPlanations) explainability, the latter particularly useful to better understand the effective roles played by molecular features. Notably, our model has been implemented in TIRESIA (Toxicology Intelligence and Regulatory Evaluations for Scientific and Industry Applications), a free of charge web platform available at http://tiresia.uniba.it.

Virtual Reverse Screening Approach to Target Type 2 Cannabinoid Receptor.

A screening pool consisting of 617710 drug-like query molecules properly filtered from the ChEMBL database was employed for a ligand-based reverse screening toward the type 2 cannabinoid receptor (CB2) target. By using our recently developed PLATO polypharmacological web platform, 233 out of 617710 drug-like molecules were prioritized on the basis of the predicted bioactivity values, better than 0.2 µM with a probability of about 98%, toward the CB2 target. Building on these results, the occurrence of putative CB2-related targets was also investigated for prospective repurposing studies.

Novel Phenothiazine/Donepezil-like Hybrids Endowed with Antioxidant Activity for a Multi-Target Approach to the Therapy of Alzheimer's Disease.

Alzheimer's disease (AD) is a complex multi-factorial neurodegenerative disorder for which only few drugs (including donepezil, DPZ) are available as symptomatic treatments; thus, researchers are focusing on the development of innovative multi-target directed ligands (MTDLs), which could also alter the course of the disease. Among other pathological factors, oxidative stress has emerged as an important factor in AD that could affect several pathways involved in the onset and progression of the pathology. Herein, we propose a new series of hybrid molecules obtained by linking a phenothiazine moiety, known for its antioxidant properties, with N-benzylpiperidine or N-benzylpiperazine fragments, mimicking the core substructure of DPZ. The investigation of the resulting hybrids showed, in addition to their antioxidant properties, their activity against some AD-related targets, such as the inhibition of cholinesterases (both AChE and BChE) and in vitro Aß1-40 aggregation, as well as the inhibition of the innovative target fatty acid amide hydrolase (FAAH). Furthermore, the drug-likeness properties of these compounds were assessed using cheminformatic tools. Compounds 11d and 12d showed the most interesting multi-target profiles, with all the assayed activities in the low micromolar range. In silico docking calculations supported the obtained results. Compound 13, on the other hand, while inactive in the DPPH assay, showed the best results in the in vitro antioxidant cell assays conducted on both HepG2 and SHSY-5Y cell lines. These results, paired with the low or absent cytotoxicity of these compounds at tested concentrations, allow us to aim our future research at the study of novel and effective drugs and pro-drugs with similar structural characteristics.

Evaluation of Novel Guanidino-Containing Isonipecotamide Inhibitors of Blood Coagulation Factors against SARS-CoV-2 Virus Infection.

Coagulation factor Xa (fXa) and thrombin (thr) are widely expressed in pulmonary tissues, where they may catalyze, together with the transmembrane serine protease 2 (TMPRSS2), the coronaviruses spike protein (SP) cleavage and activation, thus enhancing the SP binding to ACE2 and cell infection. In this study, we evaluate in vitro the ability of approved (i.e., dabigatran and rivaroxaban) and newly synthesized isonipecotamide-based reversible inhibitors of fXa/thr (cmpds 1-3) to hinder the SARS-CoV-2 infectivity of VERO cells. Nafamostat, which is a guanidine/amidine antithrombin and antiplasmin agent, disclosed as a covalent inhibitor of TMPRSS2, was also evaluated. While dabigatran and rivaroxaban at 100 µM concentration did not show any effect on SARS-CoV-2 infection, the virus preincubation with new guanidino-containing fXa-selective inhibitors 1 and 3 did decrease viral infectivity of VERO cells at subtoxic doses. When the cells were pre-incubated with 3, a reversible nanomolar inhibitor of fXa (Ki = 15 nM) showing the best in silico docking score toward TMPRSS2 (pdb 7MEQ), the SARS-CoV-2 infectivity was completely inhibited at 100 µM (p < 0.0001), where the cytopathic effect was just about 10%. The inhibitory effects of 3 on SARS-CoV-2 infection was evident (ca. 30%) at lower concentrations (3-50 µM). The covalent TMPRSS2 and the selective inhibitor nafamostat mesylate, although showing some effect (15-20% inhibition), did not achieve statistically significant activity against SARS-CoV-2 infection in the whole range of test concentrations (3-100 µM). These findings suggest that direct inhibitors of the main serine proteases of the blood coagulation cascade may have potential in SARS-CoV-2 drug discovery. Furthermore, they prove that basic amidino-containing fXa inhibitors with a higher docking score towards TMPRSS2 may be considered hits for optimizing novel small molecules protecting guest cells from SARS-CoV-2 infection.

In Vivo Investigation of (2-Hydroxypropyl)-ß-cyclodextrin-Based Formulation of Spironolactone in Aqueous Solution for Paediatric Use.

Spironolactone (SPL), a potent anti-aldosterone steroidal drug used to treat several diseases in paediatric patients (e.g., hypertension, primary aldosteronism, Bartter's syndrome, and congestive heart failure), is not available in child-friendly dosage forms, and spironolactone liquids have been reported to be unpalatable. Aiming to enhance SPL solubility in aqueous solution and overcome palatability, herein, the effects of (2-hydroxypropyl)-ß-cyclodextrin (HP-ß-CyD) were thoroughly investigated on solubilisation in water and on masking the unpleasant taste of SPL in vivo. Although the complexation of SPL with HP-ß-CyD was demonstrated through phase solubility studies, Job's plot, NMR and computational docking studies, our in vivo tests did not show significant effects on taste aversion. Our findings, on the one hand, suggest that the formation of an inclusion complex of SPL with HP-ß-CyD itself is not necessarily a good indicator for an acceptable degree of palatability, whereas, on the other hand, they constitute the basis for investigating other cyclodextrin-based formulations of the poorly water-soluble steroidal drug, including solid dosage forms, such as spray-dried powders and orodispersible tablets.

Structure-based design of novel donepezil-like hybrids for a multi-target approach to the therapy of Alzheimer's disease.

Alzheimer's disease (AD) is a widespread multifactorial aging-related pathology, which includes cholinergic deficit among its main causes. Following a multi-target design strategy, the structure of the approved drug donepezil was taken as the starting point for generating some new potential multi-functional compounds. Therefore, a series of twenty molecular hybrids were synthesized and assayed against three different enzymes, namely the well-established targets acetylcholinesterase (AChE) and butyrylcholinesterase (BChE), and the innovative one fatty acid amide hydrolase (FAAH). In silico studies confirmed the interaction of benzylpiperidine and the benzylpiperazine isostere with the catalytic anionic site (CAS) of AChE, while the aryloxycarbonyl portion appeared to be important for the interaction with the peripheral site (PAS). A QSAR study was carried out on AChE inhibition data, which revealed that the inhibition potency seems to depend upon the length of the spacer and the number of polar atoms. The docking poses of selected compounds within BChE and FAAH were also calculated. Furthermore, pharmacokinetics and drug-likeness properties were assessed by chemoinformatic tools. Several piperidine derivatives (in particular compound 10) showed interesting profiles as multi-target directed agents, while the lead piperazine derivative 12 (SON38) was found to be a more potent and selective AChE inhibitor (IC50 = 0.8 nM) than donepezil, besides being able to bind bivalent copper cations (pCu = 7.9 at physiological pH). Finally, the selected lead compounds (10 and 12, SON38) did not show significant cytotoxicity on SH-SY5Y and HepG2 cells at the highest tested concentration (100 µM) in a MTT assay.

Probing Fluorinated Motifs onto Dual AChE-MAO B Inhibitors: Rational Design, Synthesis, Biological Evaluation, and Early-ADME Studies.

Bioisosteric H/F or CH2OH/CF2H replacement was introduced in coumarin derivatives previously characterized as dual AChE-MAO B inhibitors to probe the effects on both inhibitory potency and drug-likeness. Along with in vitro screening, we investigated early-ADME parameters related to solubility and lipophilicity (Sol7.4, CHI7.4, log D7.4), oral bioavailability and central nervous system (CNS) penetration (PAMPA-HDM and PAMPA-blood-brain barrier (BBB) assays, Caco-2 bidirectional transport study), and metabolic liability (half-lives and clearance in microsomes, inhibition of CYP3A4). Both specific and nonspecific tissue toxicities were determined in SH-SY5Y and HepG2 lines, respectively. Compound 15 bearing a -CF2H motif emerged as a water-soluble, orally bioavailable CNS-permeant potent inhibitor of both human AChE (IC50 = 550 nM) and MAO B (IC50 = 8.2 nM, B/A selectivity > 1200). Moreover, 15 behaved as a safe and metabolically stable neuroprotective agent, devoid of cytochrome liability.

First Synthesis of Racemic Trans Propargylamino-Donepezil, a Pleiotrope Agent Able to Both Inhibit AChE and MAO-B, with Potential Interest against Alzheimer's Disease.

Alzheimer's disease (AD) is a multifactorial neurodegenerative disease towards which pleiotropic approach using Multi-Target Directed Ligands is nowadays recognized as probably convenient. Among the numerous targets which are today validated against AD, acetylcholinesterase (ACh) and Monoamine Oxidase-B (MAO-B) appear as particularly convincing, especially if displayed by a sole agent such as ladostigil, currently in clinical trial in AD. Considering these results, we wanted to take benefit of the structural analogy lying in donepezil (DPZ) and rasagiline, two indane derivatives marketed as AChE and MAO-B inhibitors, respectively, and to propose the synthesis and the preliminary in vitro biological characterization of a structural compromise between these two compounds, we called propargylaminodonepezil (PADPZ). The synthesis of racemic trans PADPZ was achieved and its biological evaluation established its inhibitory activities towards both (h)AChE (IC50 = 0.4 µM) and (h)MAO-B (IC50 = 6.4 µM).

Novel Antiproliferative Biphenyl Nicotinamide: NMR Metabolomic Study of its Effect on the MCF-7 Cell in Comparison with Cisplatin and Vinblastine.

A 1H-NMR-based metabolomic study was performed on MCF-7 cell lines treated with a novel nicotinamide derivative (DT-8) in comparison with two drugs characterized by a well-established mechanism of action, namely the DNA-metalating drug cisplatin (cis-diamminedichloridoplatinum(II), CDDP) and the antimitotic drug vinblastine (vinblastine, VIN). The effects of the three compounds, each one at the concentration corresponding to the IC50 value, were investigated, with respect to the controls (K), by the 1H-NMR of cells lysates and multivariate analysis (MVA) of the spectroscopic data. Relevant differences were found in the metabolic profiles of the different treatments with respect to the controls. A large overlap of the metabolic profiles in DT-8 vs. K and VIN vs. K suggests a similar biological response and mechanism of action, significantly diverse with respect to CDDP. On the other hand, DT8 seems to act by disorganizing the mitotic spindle and ultimately blocking the cell division, through a mechanism implying methionine depletion and/or S-adenosylmethionine (SAM) limitation.

Chiral Separation, X-ray Structure, and Biological Evaluation of a Potent and Reversible Dual Binding Site AChE Inhibitor.

Acetylcholinesterase (AChE) inhibitors (AChEIs) still remain the leading therapeutic options for the symptomatic treatment of cognitive deficits associated with mild-to-moderate Alzheimer's disease. The search for new AChEIs benefits from well-established knowledge of the molecular interactions of selective AChEIs, such as donepezil and related dual binding site inhibitors. Starting from a previously disclosed coumarin-based inhibitor (±)-cis-1, active as racemate in the nanomolar range toward AChE, we proceeded on a double track by (i) achieving chiral resolution of the enantiomers of 1 by HPLC and (ii) preparing two close achiral analogues of 1, i.e., compounds 4 and 6. An eudismic ratio as high as 20 was observed for the (-) enantiomer of cis-1. The X-ray crystal structure of the complex between the (-)-cis-1 eutomer (coded as MC1420) and T. californica AChE was determined at 2.8 Å, and docking calculation results suggested that the eutomer in (1R,3S) absolute configuration should be energetically more favored in binding the enzyme than the eutomer in (1S,3R) configuration. The achiral analogues 4 and 6 were less effective in inhibiting AChE compared to (±)-cis-1, but interestingly butylamide 4 emerged as a potent inhibitor of butyrylcholinesterase (BChE).

Bridging repair of the abdominal wall in a rat experimental model. Comparison between uncoated and polyethylene oxide-coated equine pericardium meshes.

Biological meshes improve the outcome of incisional hernia repairs in infected fields but often lead to recurrence after bridging techniques. Sixty male Wistar rats undergoing the excision of an abdominal wall portion and bridging mesh repair were randomised in two groups: Group A (N = 30) using the uncoated equine pericardium mesh; Group B (N = 30) using the polyethylene oxide (PEO)-coated one. No deaths were observed during treatment. Shrinkage was significantly less common in A than in B (3% vs 53%, P < 0.001). Adhesions were the most common complication and resulted significantly higher after 90 days in B than in A (90% vs 30%, P < 0.01). Microscopic examination revealed significantly (P < 0.05) higher mesh integrity, fibrosis and calcification in B compared to A. The enzymatic degradation, as assessed with Raman spectroscopy and enzyme stability test, affected A more than B. The PEO-coated equine pericardium mesh showed higher resistance to biodegradation compared to the uncoated one. Understanding the changes of these prostheses in a surgical setting may help to optimize the PEO-coating in designing new biomaterials for the bridging repair of the abdominal wall.