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Background No standardized written or volumetric definition exists for ‘loss of domain’ (LOD). This limits the utility of LOD as a morphological descriptor and as a predictor of peri- and postoperative outcomes. Consequently, our aim was to establish definitions for LOD via consensus of expert abdominal wall surgeons. Methods A Delphi study involving 20 internationally recognized abdominal wall reconstruction (AWR) surgeons was performed. Four written and two volumetric definitions of LOD were identified via systematic review. Panelists completed a questionnaire that suggested these definitions as standardized definitions of LOD. Consensus on a preferred term was pre-defined as achieved when selected by ≥80% of panelists. Terms scoring <20% were removed. Results Voting commenced August 2018 and was completed in January 2019. Written definition: During Round 1, two definitions were removed and seven new definitions were suggested, leaving nine definitions for consideration. For Round 2, panelists were asked to select all appealing definitions. Thereafter, common concepts were identified during analysis, from which the facilitators advanced a new written definition. This received 100% agreement in Round 3. Volumetric definition: Initially, panelists were evenly split, but consensus for the Sabbagh method was achieved. Panelists could not reach consensus regarding a threshold LOD value that would preclude surgery. Conclusions Consensus for written and volumetric definitions of LOD was achieved from 20 internationally recognized AWR surgeons. Adoption of these definitions will help standardize the use of LOD for both clinical and academic activities.

Background Trocar-site hernia is an underappreciated condition with estimates of approximately 25% at 2 years follow-up. Duramesh™ has emerged as a novel product with potential benefits for incisional hernia prevention. The aim of this trial is to establish if Duramesh is superior to conventional suture for prevention of periumbilical trocar-site hernia following laparoscopic surgery. Methods The TROCAR trial is a prospective single-centre, parallel arm, double-blind randomised controlled trial conducted in the United Kingdom. A total of 250 randomised participants (1:1 ratio) will be allocated to receive either Duramesh or conventional suture (J-vicryl or J-PDS). The primary outcome is the cumulative incidence of sonographically detected periumbilical trocar-site hernia at 2 years of the index operation. Secondary outcomes are 90-day surgical site occurrence (SSO), 90-day surgical site infection (SSI), 90-day rate of reoperation, 90-day mortality, length of hospital stay, and quality of life at 3 months, 1 year and 2 years measured using a modified EuraHS-QoL score and modified Carolinas Comfort Scale. Conclusion TROCAR will provide level 1 evidence on trocar-site hernia prevention in both the emergency and elective settings. Trial registration Registration number ISRCTN14473961 ( https://doi.org/10.1186/ISRCTN14473961 ). Registered on 14th April 2025.

Protein‐based biomaterial use is expanding within medicine, together with the demand to visualize their placement and behavior in vivo. However, current medical imaging techniques struggle to differentiate between protein‐based implants and surrounding tissue. Here a fast, simple, and translational solution for tracking transplanted protein‐based scaffolds is presented using X‐ray CT–facilitating long‐term, non‐invasive, and high‐resolution imaging. X‐ray visible scaffolds are engineered by selectively iodinating tyrosine residues under mild conditions using readily available reagents. To illustrate translatability, a clinically approved hernia repair mesh (based on decellularized porcine dermis) is labeled, preserving morphological and mechanical properties. In a mouse model of mesh implantation, implants retain marked X‐ray contrast up to 3 months, together with an unchanged degradation rate and inflammatory response. The technique's compatibility is demonstrated with a range of therapeutically relevant protein formats including bovine, porcine, and jellyfish collagen, as well as silk sutures, enabling a wide range of surgical and regenerative medicine uses. This solution tackles the challenge of visualizing implanted protein‐based biomaterials, which conventional imaging methods fail to differentiate from endogenous tissue. This will address previously unanswered questions regarding the accuracy of implantation, degradation rate, migration, and structural integrity, thereby accelerating optimization and safe translation of therapeutic biomaterials. Selective iodination of tyrosine residues provides a fast, robust, and cost‐effective route to engineering X‐ray visible protein scaffolds. Using one of the most widely used surgical biomaterials – collagen‐based hernia meshes, materials are visible up to 3 months post‐implantation in vivo with clinically‐relevant X‐ray doses. This will address previously unanswered questions on implantation accuracy, degradation rate, migration, and structural integrity.

Abdominal wall reconstruction is a rapidly evolving area of surgical interest. Due to the increase in prevalence and size of ventral hernias and the high recurrence rates, the academic community has become motivated to find the best reconstruction techniques. Whilst interrogating the abdominal wall reconstruction literature, we discovered an inconsistency in hernia nomenclature that must be addressed. The terms used to describe the anatomical planes of mesh implantation ‘inlay’, ‘sublay’ and ‘underlay’ are misinterpreted throughout. We describe the misinterpretation of these terms and give evidence of where it exists in the literature. We give three critical arguments of why these misinterpretations hinder advances in abdominal wall reconstruction research. The correct definitions of the anatomical planes, and their respective terms, are described and illustrated. Clearly defined nomenclature is required as academic surgeons strive to improve abdominal wall reconstruction outcomes and lower complication rates.

BackgroundThis systematic review assesses the perioperative variables and post-operative outcomes reported by randomised controlled trials (RCTs) of VH repair. This review focuses particularly on definitions of hernia recurrence and techniques used for detection.ObjectiveOur aim is to identify and quantify the inconsistencies in perioperative variable and postoperative outcome reporting, so as to justify future development of clear definitions of hernia recurrence and a standardised dataset of such variables.MethodsThe PubMed database was searched for elective VH repair RCTs reported January 1995 to March 2016 inclusive. Three independent reviewers performed article screening, and two reviewers independently extracted data. Hernia recurrence, recurrence rate, timing and definitions of recurrence, and techniques used to detect recurrence were extracted. We also assessed reported post-operative complications, standardised operative outcomes, patient reported outcomes, pre-operative CT scan hernia dimensions, intra-operative variables, patient co-morbidity, and hernia morphology.Results31 RCTs (3367 patients) were identified. Only 6 (19.3%) defined hernia recurrence and methods to detect recurrence were inconsistent. Sixty-four different clinical outcomes were reported across the RCTs, with wound infection (30 trials, 96.7%), hernia recurrence (30, 96.7%), seroma (29, 93.5%), length of hospital stay (22, 71%) and haematoma (21, 67.7%) reported most frequently. Fourteen (45%), 11 (35%) and 0 trials reported CT measurements of hernia defect area, width and loss of domain, respectively. No trial graded hernias using generally accepted scales.ConclusionVH RCTs report peri- and post-operative variables inconsistently, and with poor definitions. A standardised minimum dataset, including definitions of recurrence, is required.

Ventral hernia disease is becoming increasingly prevalent and complex. Subspecialisation for patients with challenging conditions requiring surgery has been shown to improve postoperative outcomes. Worldwide, there is an emergence of specialist hernia centres using new and innovative techniques to repair large and complicated ventral hernias. After a national meeting of hernia experts, we present an algorithm to be used as a national triage system for patients with ventral hernias, with the aim of ensuring that patients are operated on by the most appropriate surgeon. Evidence-based clinical risk factors and ventral hernia parameters are used for risk stratification and patient triage. We hope that this algorithm will guide future ventral hernia management in the UK.

Infectious disease threats to individual and public health are numerous, varied and frequently unexpected. Artificial intelligence (AI) and related technologies, which are already supporting human decision making in economics, medicine and social science, have the potential to transform the scope and power of infectious disease epidemiology. Here we consider the application to infectious disease modelling of AI systems that combine machine learning, computational statistics, information retrieval and data science. We first outline how recent advances in AI can accelerate breakthroughs in answering key epidemiological questions and we discuss specific AI methods that can be applied to routinely collected infectious disease surveillance data. Second, we elaborate on the social context of AI for infectious disease epidemiology, including issues such as explainability, safety, accountability and ethics. Finally, we summarize some limitations of AI applications in this field and provide recommendations for how infectious disease epidemiology can harness most effectively current and future developments in AI. This Perspective considers the application to infectious disease modelling of AI systems that combine machine learning, computational statistics, information retrieval and data science.

Human endogenous retroviruses (hERVs) are remnants of exogenous retroviruses that have integrated into the genome throughout evolution. We developed a computational workflow, hervQuant, which identified more than 3,000 transcriptionally active hERVs within The Cancer Genome Atlas (TCGA) pan-cancer RNA-Seq database. hERV expression was associated with clinical prognosis in several tumor types, most significantly clear cell renal cell carcinoma (ccRCC). We explored two mechanisms by which hERV expression may influence the tumor immune microenvironment in ccRCC: (i) RIG-I-like signaling and (ii) retroviral antigen activation of adaptive immunity. We demonstrated the ability of hERV signatures associated with these immune mechanisms to predict patient survival in ccRCC, independent of clinical staging and molecular subtyping. We identified potential tumor-specific hERV epitopes with evidence of translational activity through the use of a ccRCC ribosome profiling (Ribo-Seq) dataset, validated their ability to bind HLA in vitro, and identified the presence of MHC tetramer-positive T cells against predicted epitopes. hERV sequences identified through this screening approach were significantly more highly expressed in ccRCC tumors responsive to treatment with programmed death receptor 1 (PD-1) inhibition. hervQuant provides insights into the role of hERVs within the tumor immune microenvironment, as well as evidence that hERV expression could serve as a biomarker for patient prognosis and response to immunotherapy.