Background: Chronic wounds are a significant health problem with devastating consequences for patients’ physical, social, and mental health, increasing healthcare systems’ costs. Their prolonged healing times, economic burden, diminished quality of life, increased infection risk, and impact on patients’ mobility and functionality make them a major concern for healthcare professionals. Purpose: This review offers a multi-perspective analysis of the medical literature focusing on chronic wound management. Methods used: We evaluated 48 articles from the last 21 years registered in the MEDLINE and Global Health databases. The articles included in our study had a minimum of 20 citations, patients > 18 years old, and focused on chronic, complex, and hard-to-heal wounds. Extracted data were summarized into a narrative synthesis using the same health-related quality of life instrument. Results: We evaluated the efficacy of existing wound care therapies from classical methods to modern concepts, and wound care products to regenerative medicine that uses a patient’s pluripotent stem cells and growth factors. Regenerative medicine and stem cell therapies, biologic dressings and scaffolds, negative pressure wound therapy (NPWT), electrical stimulation, topical growth factors and cytokines, hyperbaric oxygen therapy (HBOT), advanced wound dressings, artificial intelligence (AI), and digital wound management are all part of the new arsenal of wound healing. Conclusion: Periodic medical evaluation and proper use of modern wound care therapies, including the use of plasma-derived products [such as platelet-rich plasma (PRP) and platelet-rich fibrin (PRF)] combined with proper systemic support (adequate protein levels, blood sugar, vitamins involved in tissue regeneration, etc.) are the key to a faster wound healing, and, with the help of AI, can reach the fastest healing rate possible.

Langerhans cells (LCs) constitute a cellular immune network across the epidermis. Because they are located at the skin barrier, they are considered immune sentinels of the skin. These antigen-presenting cells are capable of migrating to skin draining lymph nodes to prime adaptive immune cells, namely T- and B-lymphocytes, which will ultimately lead to a broad range of immune responses. Moreover, LCs have been shown to possess important roles in the anti-cancer immune responses. Indeed, the literature nicely highlights the role of LCs in melanoma. In line with this, LCs have been found in melanoma tissues where they contribute to the local immune response. Moreover, the immunogenic properties of LCs render them attractive targets for designing vaccines to treat melanoma and autoimmune diseases. Overall, future studies will help to enlarge the portfolio of immune properties of LCs, and aid the prognosis and development of novel therapeutic approaches to treating skin pathologies, including cancers.

Pancreatic cystic lesions (PCLs) are a heterogenous group of lesions ranging from benign to malignant. There has been an increase in PCLs prevalence in recent years, mostly due to advances in imaging techniques, increased awareness of their existence and population aging. Reliable discrimination between neoplastic and non-neoplastic cystic lesions is paramount to ensuring adequate treatment and follow-up. Although conventional diagnostic techniques such as ultrasound (US), magnetic resonance imaging (MRI) and computer tomography (CT) can easily identify these lesions, assessing the risk of malignancy is limited. Endoscopic ultrasound (EUS) is superior to cross-sectional imaging in identifying potentially malignant lesions due to its high resolution and better imaging characteristics, and the advantage of allowing for cyst fluid sampling via fine-needle aspiration (FNA). More complex testing, such as cytological and histopathological analysis and biochemical and molecular testing of the aspirated fluid, can ensure an accurate diagnosis.

Despite the substantial decrease in mortality rates following a pancreaticoduodenectomy to less than 5%, morbidity rates remain significant, reaching even 73%. Postoperative pancreatic fistula is one of the most frequent major complications and is significantly associated with other complications, including patient death. Currently, there is no consensus regarding the ideal type of pancreatic anastomosis, as the question of the choice between a pancreaticogastrostomy and pancreaticojejunostomy is still open. Furthermore, worldwide implementation of an ideal pancreatic fistula risk prediction score is missing. Our study found several significant predictive factors for the postoperative occurrence of fistulas, such as the soft consistency of the pancreas, non-dilated Wirsung duct, important intraoperative blood loss, other perioperative complications, preoperative patient hypoalbuminemia, and patient weight loss. Our study also revealed that for patients who exhibit fistula risk factors, pancreaticogastrostomy demonstrates a significantly lower pancreatic fistula rate than pancreaticojejunostomy. The occurrence of pancreatic fistulas has been significantly associated with the development of other postoperative major complications, and patient death. As the current pancreatic fistula risk scores proposed by various authors have not been consensually validated, we propose a simple, easy-to-use, and sensitive score for the risk prediction of postoperative pancreatic fistula occurrence based on important predictors from statistical analyses that have also been found to be significant by most of the reported studies. The new pancreatic fistula risk score proposed by us could be extremely useful for improved therapeutic management of cephalic pancreaticoduodenectomy patients.

The presence of lymphovascular invasion (LVI) in urothelial carcinoma (UC) is a poor prognostic finding. This is difficult to identify on routine hematoxylin–eosin (H&E)-stained slides, but considering the costs and time required for examination, immunohistochemical stains for the endothelium are not the recommended diagnostic protocol. We developed an AI-based automated method for LVI identification on H&E-stained slides. We selected two separate groups of UC patients with transurethral resection specimens. Group A had 105 patients (100 with UC; 5 with cystitis); group B had 55 patients (all with high-grade UC; D2-40 and CD34 immunohistochemical stains performed on each block). All the group A slides and 52 H&E cases from group B showing LVI using immunohistochemistry were scanned using an Aperio GT450 automatic scanner. We performed a pixel-per-pixel semantic segmentation of selected areas, and we trained InternImage to identify several classes. The DiceCoefficient and Intersection-over-Union scores for LVI detection using our method were 0.77 and 0.52, respectively. The pathologists’ H&E-based evaluation in group B revealed 89.65% specificity, 42.30% sensitivity, 67.27% accuracy, and an F1 score of 0.55, which is much lower than the algorithm’s DCC of 0.77. Our model outlines LVI on H&E-stained-slides more effectively than human examiners; thus, it proves a valuable tool for pathologists.