Purpose: Peri-implant mucositis (PIM) and peri-implantitis (PI) are multicausal conditions with several risk factors contributing to their pathogenesis. In this study, we retrospectively investigated risk variables potentially associated with these peri-implant diseases (PIDs) over a follow-up period of 1 to 18 years. Methods: The study sample consisted of 379 implants placed in 155 patients. Single-visit clinical and radiographic evaluations were employed to determine the presence or absence of PIDs. Parameters related to the patient, site, surgery, implant, and prosthetic restoration were documented. The relationships between risk variables and the occurrence of PIDs were individually examined and adjusted for confounders using multivariate binary logistic regression models. Results: The prevalence rates of PIM and PI were 28.4% and 36.8% at the patient level and 33.5% and 24.5% at the implant level, respectively. Poor oral hygiene, active gingivitis/ periodontitis, preoperative alveolar ridge deficiency, early or delayed implant placement, implant length of 11.0 mm or less, and poor restoration quality were strong and independent risk indicators for both PIDs. Furthermore, a follow-up period of more than 5 years and a loading time of more than 4 years were important indicators for PI. Simultaneously, age and smoking status acted as modifiers of the effect of mesiodistal (MD) and buccolingual (BL) widths of restoration on PI. Conclusions In this study population, oral hygiene, periodontal status, preoperative alveolar ridge status, implant placement protocol, implant length, and the quality of coronal restoration appear to be robust risk indicators for both PIM and PI. Additionally, the length of follow-up and functional loading time are robust indicators of PI. Furthermore, the potential modifying relationships of age and smoking status with the MD and BL widths of restoration may be crucial for the development of PI.

Purpose: Peri-implant mucositis (PIM) and peri-implantitis (PI) are multicausal conditions with several risk factors contributing to their pathogenesis. In this study, we retrospectively investigated risk variables potentially associated with these peri-implant diseases (PIDs) over a follow-up period of 1 to 18 years. Methods: The study sample consisted of 379 implants placed in 155 patients. Single-visit clinical and radiographic evaluations were employed to determine the presence or absence of PIDs. Parameters related to the patient, site, surgery, implant, and prosthetic restoration were documented. The relationships between risk variables and the occurrence of PIDs were individually examined and adjusted for confounders using multivariate binary logistic regression models. Results: The prevalence rates of PIM and PI were 28.4% and 36.8% at the patient level and 33.5% and 24.5% at the implant level, respectively. Poor oral hygiene, active gingivitis/ periodontitis, preoperative alveolar ridge deficiency, early or delayed implant placement, implant length of 11.0 mm or less, and poor restoration quality were strong and independent risk indicators for both PIDs. Furthermore, a follow-up period of more than 5 years and a loading time of more than 4 years were important indicators for PI. Simultaneously, age and smoking status acted as modifiers of the effect of mesiodistal (MD) and buccolingual (BL) widths of restoration on PI. Conclusions In this study population, oral hygiene, periodontal status, preoperative alveolar ridge status, implant placement protocol, implant length, and the quality of coronal restoration appear to be robust risk indicators for both PIM and PI. Additionally, the length of follow-up and functional loading time are robust indicators of PI. Furthermore, the potential modifying relationships of age and smoking status with the MD and BL widths of restoration may be crucial for the development of PI.

Purpose: Peri-implant mucositis (PIM) and peri-implantitis (PI) are multicausal conditions with several risk factors contributing to their pathogenesis. In this study, we retrospectively investigated risk variables potentially associated with these peri-implant diseases (PIDs) over a follow-up period of 1 to 18 years. Methods: The study sample consisted of 379 implants placed in 155 patients. Single-visit clinical and radiographic evaluations were employed to determine the presence or absence of PIDs. Parameters related to the patient, site, surgery, implant, and prosthetic restoration were documented. The relationships between risk variables and the occurrence of PIDs were individually examined and adjusted for confounders using multivariate binary logistic regression models. Results: The prevalence rates of PIM and PI were 28.4% and 36.8% at the patient level and 33.5% and 24.5% at the implant level, respectively. Poor oral hygiene, active gingivitis/ periodontitis, preoperative alveolar ridge deficiency, early or delayed implant placement, implant length of 11.0 mm or less, and poor restoration quality were strong and independent risk indicators for both PIDs. Furthermore, a follow-up period of more than 5 years and a loading time of more than 4 years were important indicators for PI. Simultaneously, age and smoking status acted as modifiers of the effect of mesiodistal (MD) and buccolingual (BL) widths of restoration on PI. Conclusions In this study population, oral hygiene, periodontal status, preoperative alveolar ridge status, implant placement protocol, implant length, and the quality of coronal restoration appear to be robust risk indicators for both PIM and PI. Additionally, the length of follow-up and functional loading time are robust indicators of PI. Furthermore, the potential modifying relationships of age and smoking status with the MD and BL widths of restoration may be crucial for the development of PI.

Hepatocellular carcinoma (HCC) is one of the most common and deadly cancers worldwide and is characterized by complex molecular carcinogenesis. Neuropilins (NRPs) NRP1 and NRP2 are the receptors of multiple proteins involved in key signaling pathways associated with tumor progression. We aimed to systematically review all the available findings on their role in HCC. We searched the Scopus, Web of Science (WOS), PubMed, Cochrane and Embase databases for articles evaluating NRPs in preclinical or clinical HCC models. This study was registered in PROSPERO (CRD42022349774) and include 49 studies. Multiple cellular and molecular processes have been associated with one or both NRPs, indicating that they are potential diagnostic and prognostic biomarkers in HCC patients. Mainly NRP1 has been shown to promote tumor cell survival and progression by modulating several signaling pathways. NRPs mainly regulate angiogenesis, invasion and migration and have shown to induce invasion and metastasis. They also regulate the immune response and tumor microenvironment, showing a crucial interplay with the hypoxia response and microRNAs in HCC. Altogether, NRP1 and NRP2 are potential biomarkers and therapeutic targets, providing novel insight into the clinical landscape of HCC patients.