Novel polymeric hydrogel scaffolds for corneal epithelium cell culturing based on blends of chitosan with some other biopolymers such as hydroxypropylcellulose, collagen and elastin crosslinked with genipin, a natural substance, were prepared. Physicochemical and biomechanical properties of these materials were determined. The in vitro cell culture experiments with corneal epithelium cells have indicated that a membrane prepared from chitosan–collagen blend (Ch–Col) provided the regular stratified growth of the epithelium cells, good surface covering and increased number of the cell layers. Ch–Col membranes are therefore the most promising material among those studied. The performance of Ch–Col membranes is comparable with that of the amniotic membrane which is currently recommended for clinical applications.

Purpose. Efficacy of cultivated oral mucosa epithelial transplantation (COMET) procedure in corneal epithelium restoration of aniridia patients.Methods. Study subjects were aniridia patients (13 patients; 17 eyes) with irregular, vascular conjunctival pannus involving visual axis who underwent autologous transplantation of cultivated epithelium. For the procedure oral mucosa epithelial cells were obtained from buccal mucosa with further enzymatic treatment. Suspension of single cells was seeded on previously prepared denuded amniotic membrane. Cultures were carried on culture dishes inserts in the presence of the inactivated with Mitomycin C monolayer of 3T3 fibroblasts. Cultures were carried for seven days. Stratified oral mucosa epithelium with its amniotic membrane carrier was transplanted on the surgically denuded corneal surface of aniridia patients with total or subtotal limbal stem cell deficiency.Outcome Measures. Corneal surface, epithelial regularity, and visual acuity improvement were evaluated.Results. At the end of the observation period, 76.4% of the eyes had regular transparent epithelium and 23.5% had developed epithelial defects or central corneal haze; in 88.2% of cases visual acuity had increased. VA range was from HM 0.05 before the surgery to HM up to 0.1 after surgery.Conclusion. Application of cultivated oral mucosa epithelium restores regular epithelium on the corneal surface with moderate improvement in quality of vision.

The molecular etiology of keratoconus (KC), a pathological condition of the human cornea, remains unclear. The aim of this work was to perform profiling of metabolites and identification of features discriminating this pathology from the normal cornea. The combination of gas chromatography and mass spectrometry (GC/MS) techniques has been applied for profiling and identification of metabolites in corneal buttons from 6 healthy controls and 7 KC patients. An untargeted GC/MS-based approach allowed the detection of 377 compounds, including 46 identified unique metabolites, whose levels enabled the separation of compared groups of samples in unsupervised hierarchical cluster analysis. There were 13 identified metabolites whose levels differentiated between groups of samples. Downregulation of several carboxylic acids, fatty acids, and steroids was observed in KC when compared to the normal cornea. Metabolic pathways associated with compounds that discriminated both groups were involved in energy production, lipid metabolism, and amino acid metabolism. An observed signature may reflect cellular processes involved in the development of KC pathology, including oxidative stress and inflammation.

The most common cause of the development of odontogenic infection is untreated dental caries, which initially leads to pulpitis. If an odontogenic infection is left untreated, it will pass through the limiting bone plate and will infiltrate deeper structures. Odontogenic infections are different in adults and children. The study was conducted at the Department of Pediatric Otolaryngology and Pediatric Head and Neck Surgery of Upper Silesian Children’s Health Center in Katowice in the 2020–2022. We included 27 patients aged 2–16 in the study. Patients were diagnosed with an active, acute odontogenic inflammatory process in the head and neck area. We assessed pain, trismus, extraoral and intraoral swelling and the level of CRP [C Reactive Protein], WBC [White Blood Cells], NLR [Neutrophil Lymphocyte Ratio], D-dimers and Prealbumins. The results were analyzed in terms of the location of the source of inflammation: maxilla or mandible and the type of source of infection: deciduous tooth or permanent tooth. Deciduous teeth are more often the cause of odontogenic infection in the maxilla, while permanent teeth in the mandible. Trismus, extraoral, and intraoral swelling occurred in all infections caused by permanent teeth. The CRP and NLR ratio is statistically higher in infection, which originates from permanent teeth. The mean hospitalization time was also longer for infections from permanent teeth 3.42 days than for deciduous teeth 2.2 days. The varied clinical picture of odontogenic infections in children requires periodic analyzes of statistical data related to epidemiology, etiology, and symptomatology in order to update diagnostic and therapeutic procedures.

Artificial intelligence (AI) has seen significant progress in medical diagnostics, particularly in image and video analysis. This review focuses on the application of AI in analyzing in vivo confocal microscopy (IVCM) images for corneal diseases. The cornea, as an exposed and delicate part of the body, necessitates the precise diagnoses of various conditions. Convolutional neural networks (CNNs), a key component of deep learning, are a powerful tool for image data analysis. This review highlights AI applications in diagnosing keratitis, dry eye disease, and diabetic corneal neuropathy. It discusses the potential of AI in detecting infectious agents, analyzing corneal nerve morphology, and identifying the subtle changes in nerve fiber characteristics in diabetic corneal neuropathy. However, challenges still remain, including limited datasets, overfitting, low-quality images, and unrepresentative training datasets. This review explores augmentation techniques and the importance of feature engineering to address these challenges. Despite the progress made, challenges are still present, such as the “black-box” nature of AI models and the need for explainable AI (XAI). Expanding datasets, fostering collaborative efforts, and developing user-friendly AI tools are crucial for enhancing the acceptance and integration of AI into clinical practice.