Recent studies found that mutations in the human SLC30A10 gene, which encodes a manganese (Mn) efflux transporter, are associated with hypermanganesemia with dystonia, polycythemia, and cirrhosis (HMDPC). However, the relationship between Mn metabolism and HMDPC is poorly understood, and no specific treatments are available for this disorder. Here, we generated two zebrafish slc30a10 mutant lines using the CRISPR/Cas9 system. Compared to wild-type animals, mutant adult animals developed significantly higher systemic Mn levels, and Mn accumulated in the brain and liver of mutant embryos in response to exogenous Mn. Interestingly, slc30a10 mutants developed neurological deficits in adulthood, as well as environmental Mn-induced manganism in the embryonic stage; moreover, mutant animals had impaired dopaminergic and GABAergic signaling. Finally, mutant animals developed steatosis, liver fibrosis, and polycythemia accompanied by increased epo expression. This phenotype was rescued partially by EDTA- CaNa2 chelation therapy and iron supplementation. Interestingly, prior to the onset of slc30a10 expression, expressing ATP2C1 (ATPase secretory pathway Ca2+ transporting 1) protected mutant embryos from Mn exposure, suggesting a compensatory role for Atp2c1 in the absence of Slc30a10. Notably, expressing either wild-type or mutant forms of SLC30A10 was sufficient to inhibit the effect of ATP2C1 in response to Mn challenge in both zebrafish embryos and HeLa cells. These findings suggest that either activating ATP2C1 or restoring the Mn-induced trafficking of ATP2C1 can reduce Mn accumulation, providing a possible target for treating HMDPC.

In this article we introduce tension as a means for qualitative data analysis based on Mikhail Bakhtin's dialogical theory. We first explain the foundations of Bakhtin's theory and show the inevitability of tension in our lives and qualitative data analysis. We then offer a review of how Bakhtin's notion of tension has manifested itself in qualitative research, which prompts us to establish a tensional approach to qualitative data analysis. Finally, we outline our framework for a tensional approach to data analysis and illustrate examples of putting this approach into practice in our own study. Our tensional approach (1) explores key moments of tension; (2) seeks out unease and discomfort; (3) involves researcher and research participants in ongoing dialogue; (4) and embraces multiple perspectives on a range of tensions during the data analysis process. It encourages uncertainties and questions instead of pursuing certainty of meaning and fixed conclusions.

Background: The incidence of deep venous thrombosis (DVT) is higher in surgical patients, but there have been few studies on the risk factors of DVT in intensive care unit (ICU) patients after oral cancer surgery, particularly in relation to the inflammatory and nutritional scores, and intervene with these risk factors early may decrease the occurrence of DVT. Methods:We performed a retrospective study of adult patients who were admitted to ICU after undergoing radical resection of oral cancer and performed ultrasound detection for DVT within 1 week after surgery from April 2019 to July 2021. DVT was diagnosed by venous ultrasonography of the lower extremities. Preoperative inflammatory and nutritional scores, including neutrophil to lymphocyte ratio (NLR), plate to lymphocyte ratio (PLR), prognostic nutritional index (PNI) were retrospectively calculated according to test results before surgery. Clinical characteristics, including the Acute Physiology and Chronic Health Evaluation II (APACHE II) score, Caprini Risk Score (CRS), Charlson comorbidity index, anticoagulation therapy, and mechanical ventilation time (MVT) after admitted to ICU were obtained. The risk factors affecting DVT occurrence were analyzed by logistic regression, and the receiver operating characteristic (ROC) curve was used to analyze the value of the relevant indicators in evaluating DVT.Results: Among the 128 patients, 43 patients (33.6%) developed DVT. Compared with the non-DVT group, the preoperative glucose (GLU), postoperative D-dimer (P<0.05), and postoperative NLR (P<0.001) were higher in the DVT group than in the non-DVT group. In multivariate logistic analysis, NLR (P=0.001), postoperative D-dimer >5.57 μg/mL (P=0.002), GLU >5.15 mmol/L (P=0.025) was associated with DVT, and the areas under the curve (AUCs) of NLR in predicting DVT was 0.729. We also found that the DVT group had longer MVT and length of stay (LOS) than the non-DVT group, and correlation analysis indicated that NLR level was positively related with MVT (r=0.36; P<0.0001) and LOS (r=0.452; P<0.0001).Conclusions: A high level of NLR, indicative of a poor immunity and nutrition status, increases the risk of DVT in patients after oral cancer surgery, and improvement of immunity and nutrition status may help decrease the occurrence of postoperative DVT.