An artificial intelligence model for the pathological diagnosis of invasion depth and histologic grade in bladder cancer.

BACKGROUND: Accurate pathological diagnosis of invasion depth and histologic grade is key for clinical management in patients with bladder cancer (BCa), but it is labour-intensive, experience-dependent and subject to interobserver variability. Here, we aimed to develop a pathological artificial intelligence diagnostic model (PAIDM) for BCa diagnosis. METHODS: A total of 854 whole slide images (WSIs) from 692 patients were included and divided into training and validation sets. The PAIDM was developed using the training set based on the deep learning algorithm ScanNet, and the performance was verified at the patch level in validation set 1 and at the WSI level in validation set 2. An independent validation cohort (validation set 3) was employed to compare the PAIDM and pathologists. Model performance was evaluated using the area under the curve (AUC), accuracy, sensitivity, specificity, positive predictive value and negative predictive value. RESULTS: The AUCs of the PAIDM were 0.878 (95% CI 0.875-0.881) at the patch level in validation set 1 and 0.870 (95% CI 0.805-0.923) at the WSI level in validation set 2. In comparing the PAIDM and pathologists, the PAIDM achieved an AUC of 0.847 (95% CI 0.779-0.905), which was non-inferior to the average diagnostic level of pathologists. There was high consistency between the model-predicted and manually annotated areas, improving the PAIDM's interpretability. CONCLUSIONS: We reported an artificial intelligence-based diagnostic model for BCa that performed well in identifying invasion depth and histologic grade. Importantly, the PAIDM performed admirably in patch-level recognition, with a promising application for transurethral resection specimens.

A functional hydrogel of dopamine-modified gelatin with photothermal properties for enhancing infected wound healing.

Infected skin wound has gradually become a prevalent injury that affects overall health. Currently, biomaterials with good adhesion, efficient antibacterial properties, and angiogenesis are considered as a suitable way to effectively heal infected wound. Herein, a multifunctional hydrogel comprising gelatin, dopamine (DA), and ferric ions (Fe3+) was developed for infected wound healing. The modified gelatin-dopamine (Gel-DA) enhanced adhesive capability. Subsequently introducing ferric ions (Fe3+) to form Gel-DA-Fe3+ hydrogels by Fe3+ and catechol coordination bonds. The designed hydrogels demonstrated multifaceted functionality, encompassing photothermal antibacterial, angiogenesis, and so on. The introduction of DA enhanced the adhesion of Gel-DA-Fe3+ to the skin surface and might serve as a physical barrier to seal wound. Meanwhile, DA and Fe3+ jointly endowed good photothermal effects to composite hydrogels, which could eliminate over 95 % of bacteria. In vitro results revealed that Gel-DA-Fe3+ hydrogels had good biocompatibility and promoted HUVECs migration and tube formation. Furthermore, in vivo studies confirmed that Gel-DA-Fe3+ hydrogels markedly expedited the wound healing of rats through eradicating bacteria, accelerating the deposition of collagen, and promoting angiogenesis. What's more, Gel-DA-Fe3+ hydrogels under near-infrared laser had a more pronounced ability for wound healing. Therefore, Gel-DA-Fe3+ hydrogels had great potential for application in bacteria-infected wound healing.

Prospective study of efficacy and safety of non-ablative 1927†nm fractional thulium fiber laser in Asian skin photoaging.

Background and Objective: Photoaging manifests as deeper wrinkles and larger pores. It has been tried to rejuvenate photoaging skin using a variety of lasers, including fractionated lasers, which are a popular photorejuvenation treatment. A new breakthrough for skin rejuvenation is the 1927 nm fractional thulium fiber laser (FTL), a laser and light-based treatment option. Clinical data regarding the FTL for treating photoaging are limited despite its effectiveness and safety. This study is aim to evaluate FTL' clinical effectiveness and safety. Methods: Fitzpatrick skin types II-IV subjects with mild to moderate photoaging signs were enrolled in this prospective study. At intervals of one month, patients received three full face treatments. Wrinkles, spots, texture, pores, melanin index, erythema index (MI and EI), skin elasticity and hydration were measured with non-invasive tool. The epidermal thickness and dermal density on ultrasonography were compared between baseline and one month after all treatment sessions. The Global Score for Photoaging scale (GSP) was rated by two independent evaluators at the baseline and final follow-up visit. Secondary outcomes included patient-rated pain on a 10-point visual analog scale (VAS), as well as overall satisfaction. Following each treatment, adverse events were noted. Results: Totally 27 subjects (24 females and 3 males) with Fitzpatrick skin types II to IV and a mean age of 44.41 (range33-64) were enrolled. Results suggests that the epidermal thickness has significantly improved after treatment. Statistically significant improvements in melanin index, skin elasticity and wrinkles were noted. An analysis of 12 subjects' reports (44%) suggested their skin felt brighter. No post-inflammatory hyperpigmentation changes or adverse events were observed. 70% patients reporting "satisfied" or "extremely satisfied". Conclusions: In this study, FTL was found to be a safe and effective treatment option for treating photoaging.

Composite Hydrogel Dressings with Enhanced Mechanical Properties and Anti-Inflammatory Ability for Effectively Promoting Wound Repair.

Background: Hydrogel dressings have been used as a crucial method to keep the wound wet and hasten the healing process. Due to safety concerns regarding the gel components, low mechanical adhesiveness, and unsatisfactory anti-inflammatory capacity qualities for practical uses in vivo, leading to the clinical translation of wound dressings is still difficult. Methods: A type of composite hydrogel (acrylamide/polyethylene glycol diacrylate/tannic acid, ie, AM/PEGDA/TA) by double bond crosslinking, Schiff base, and hydrogen bond interaction is proposed. The mechanical characteristics, adhesiveness, and biocompatibility of the hydrogel system were all thoroughly examined. Additionally, a full-thickness cutaneous wound model was employed to assess the in vivo wound healing capacity of resulting hydrogel dressings. Results: Benefiting the mechanism of multiple crosslinking, the designed composite hydrogels showed significant mechanical strength, outstanding adhesive capability, and good cytocompatibility. Moreover, the hydrogel system also had excellent shape adaptability, and they can be perfectly integrated into the irregularly shaped wounds through a fast in situ forming approach. Additional in vivo tests supported the findings that the full-thickness wound treated with the composite hydrogels showed quicker epithelial tissue regeneration, fewer inflammatory cells, more collagen deposition, and greater levels of platelet endothelial cell adhesion molecule (CD31) expression. Conclusion: These above results might offer a practical and affordable product or method of skin wound therapy in a medical context.

Identification of CDK1 as a candidate marker in cutaneous squamous cell carcinoma by integrated bioinformatics analysis.

BACKGROUND: Cutaneous squamous cell carcinoma (cSCC) is a relatively common cancer that accounts for nearly 50% of non-melanoma skin cancer cases. However, the genotypes that are linked with poor prognosis and/or high relapse rates and pathogenic mechanisms of cSCC are not fully understood. To address these points, three gene expression datasets were analyzed to identify candidate biomarker genes in cSCC. METHODS: The GSE117247, GSE32979, and GSE98767 datasets comprising a total of 32 cSCC samples and 31 normal skin tissue samples were obtained from the National Center for Biotechnology Information Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified and underwent pathway enrichment analyses with the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG). A putative DEG protein-protein interaction (PPI) network was also established that included hub genes. The expression of CDK1, MAD2L1, BUB1 ans CDC20 were examined in the study. RESULTS: A total of 335 genes were identified, encompassing 219 found to be upregulated and 116 genes that were downregulated in cSCC, compared to normal tissue. Enriched functions of these DEGs were associated with Ephrin receptor signaling and cell division; cytosol, membrane, and extracellular exosomes; ATP-, poly(A) RNA-, and identical protein binding. We also established a PPI network comprising 332 nodes and identified KIF2C, CDC42, AURKA, MAD2L1, MYC, CDK1, FEN1, H2AFZ, BUB1, BUB1B, CKS2, CDC20, CCT2, ACTR2, ACTB, MAPK14, and HDAC1 as candidate hub genes. The expression of CDK1 are significantly higher in the cSCC tissues than that in normal skin. CONCLUSIONS: The DEGs identified in this study are potential therapeutic targets and biomarkers for cSCC. CDK1 is a gene closely related to the occurrence and development of cSCC, which may play an important role. Bioinformatics analysis shows that it is involved in the important pathway of the pathogenesis of cSCC, and may be recognized and applied as a new biomarker in the future diagnosis and treatment of cSCC.