WNKs (with-no-lysine [K]) are a family of serine-threonine protein kinases with an atypical placement of the catalytic lysine relative to all other protein kinases. The roles of WNK kinases in regulating ion transport were first revealed by the findings that mutations of two members cause a genetic hypertension and hyperkalemia syndrome. More recent studies suggest that WNKs are pleiotropic protein kinases with important roles in many cell processes in addition to ion transport. Here, we review roles of WNK kinases in the regulation of ion balance, cell signaling, survival, and proliferation, and embryonic organ development.
Amino Acid Sequence ; Animals ; Cell Proliferation ; Cell Survival ; Humans ; Hyperkalemia/enzymology/etiology/genetics ; Hypertension/enzymology/etiology/genetics ; Kidney/enzymology ; Models, Molecular ; Molecular Sequence Data ; Mutation ; Neoplasms/enzymology/etiology/genetics ; Protein Structure, Tertiary ; Protein-Serine-Threonine Kinases/*chemistry/genetics/*metabolism ; Pseudohypoaldosteronism/enzymology/etiology/genetics ; Sequence Homology, Amino Acid ; Signal Transduction ; Syndrome

To evaluate the papilla alterations around single-implant restorations in the anterior maxillae after crown attachment and to study the influence of soft tissue thickness on the papilla fill alteration. According to the inclusion criteria, 32 patients subjected to implant-supported single-tooth restorations in anterior maxillae were included. The patients were assigned to two groups according to the mucosal thickness: (i) group 1, 1.5 mm s mucosal thickness 3 mm; and (ii) group 2, 3 mm Adult ; Crowns ; Dental Implantation, Endosseous ; methods ; Dental Implants, Single-Tooth ; Dental Prosthesis Design ; Dental Prosthesis, Implant-Supported ; Esthetics, Dental ; Female ; Follow-Up Studies ; Gingiva ; anatomy & histology ; Humans ; Male ; Maxilla ; Middle Aged ; Outcome Assessment (Health Care) ; Prospective Studies ; Tooth Cervix ; anatomy & histology ; Young Adult

To evaluate the papilla alterations around single-implant restorations in the anterior maxillae after crown attachment and to study the influence of soft tissue thickness on the papilla fill alteration. According to the inclusion criteria, 32 patients subjected to implant-supported single-tooth restorations in anterior maxillae were included. The patients were assigned to two groups according to the mucosal thickness: (i) group 1, 1.5 mmfmucosal thicknessf3 mm; and (ii) group 2, 3 mm,mucosal thicknessf4.5 mm. Assessments of interproximal papillae at the time of crown placement (baseline) and at 6-month postloading (follow-up) were made by two prosthodontists using papilla fill index (PFI). The mean mucosal thickness was (2.4960.31) mm(group 1) and (3.8160.31)mm (group 2) for the two groups respectively. A significant difference in PFI between the groups was detected at the baseline (P,0.001). PFI improvements over time occurred after 6-month follow-up irrespective of the groups. When compared to group 1, the likelihood to obtain papilla fill was significantly higher for group 2 with an odds ratio of 6.05 (P,0.001). The interproximal papilla level around single-implant restorations could improve significantly over time after 6-month restoration according to PFI assessment. The thicker mucosa before implant placement implied a more favorable esthetic outcome in papilla alteration.

Background/Aims: Obstacles exist in facilitating hepatitis C virus (HCV) care cascade. To increase timely and accurate diagnosis, disease awareness and accessibility, in-hospital HCV reflex testing followed by automatic appointments and a late call-back strategy (R.N.A. model) was applied. We aimed to compare the HCV treatment rate of patients treated with this strategy compared to those without. Methods: One hundred and twenty-five anti-HCV seropositive patients who adopted the R.N.A. model in 2020 and another 1,396 controls treated in 2019 were enrolled to compare the gaps in accurate HCV RNA diagnosis to final treatment allocation. Results: The HCV RNA testing rate was significantly higher in patients who received reflex testing than in those without reflex testing (100% vs. 84.8%, P<0.001). When patients were stratified according to the referring outpatient department, a significant improvement in the HCV RNA testing rate was particularly noted in patients from non-hepatology departments (100% vs. 23.3%, P<0.001). The treatment rate in HCV RNA seropositive patients was 83% (83/100) after the adoption of the R.N.A. model, among whom 96.1% and 73.9% of patients were from the hepatology and non-hepatology departments, respectively. Compared to subjects without R.N.A. model application, a significant improvement in the treatment rate was observed for patients from non-hepatology departments (73.9% vs. 27.8%, P=0.001). The application of the R.N.A. model significantly increased the in-hospital HCV treatment uptake from 6.4% to 73.9% for patients from non-hepatology departments (P<0.001). Conclusions The care cascade increased the treatment uptake and set up a model for enhancing in-hospital HCV elimination.

Background/Aims: Chronic hepatitis C (CHC) patients who failed antiviral therapy are at increased risk for hepatocellular carcinoma (HCC). This study assessed the potential role of metformin and statins, medications for diabetes mellitus (DM) and hyperlipidemia (HLP), in reducing HCC risk among these patients. Methods: We included CHC patients from the T-COACH study who failed antiviral therapy. We tracked the onset of HCC 1.5 years post-therapy by linking to Taiwan’s cancer registry data from 2003 to 2019. We accounted for death and liver transplantation as competing risks and employed Gray’s cumulative incidence and Cox subdistribution hazards models to analyze HCC development. Results: Out of 2,779 patients, 480 (17.3%) developed HCC post-therapy. DM patients not using metformin had a 51% increased risk of HCC compared to non-DM patients, while HLP patients on statins had a 50% reduced risk compared to those without HLP. The 5-year HCC incidence was significantly higher for metformin non-users (16.5%) versus non-DM patients (11.3%; adjusted sub-distribution hazard ratio [aSHR]=1.51; P=0.007) and metformin users (3.1%; aSHR=1.59; P=0.022). Statin use in HLP patients correlated with a lower HCC risk (3.8%) compared to non-HLP patients (12.5%; aSHR=0.50; P<0.001). Notably, the increased HCC risk associated with non-use of metformin was primarily seen in non-cirrhotic patients, whereas statins decreased HCC risk in both cirrhotic and non-cirrhotic patients. Conclusions Metformin and statins may have a chemopreventive effect against HCC in CHC patients who failed antiviral therapy. These results support the need for personalized preventive strategies in managing HCC risk.