1.The use of implant-assisted removable partial denture in the partially edentulous maxilla with a few unilateral remaining teeth and implant overdenture in the mandible: A case report
Yina YUN ; Hyun-Ah KIM ; Sangwon PARK ; Chan PARK ; Woohyung JANG
The Journal of Korean Academy of Prosthodontics 2021;59(4):515-522
Successful cases of the implant-assisted removable partial denture and implant overdentures are reported in which a few implants are additionally placed to secure the maintenance, support, and stability of the denture when there are a few residual teeth. When the lateral force applied to the tooth abutment and implant surveyed crown is minimized, the horizontal and rotational movement of the denture is significantly reduced which is an effective method that can improve the address in patients who complain of reduced retention and stability of their dentures. In this case, a small number of implants were placed to fabricate an implant-assisted removable partial denture with implant surveyed crown in the maxilla and implant overdenture with Locator® attachment in the mandible to improve the retention, stability, and support of the dentures. The patient was satisfied with both functional and aesthetic aspects after the final dentures were delivered.
2.Early Diagnosis of Bipolar Disorder Coming Soon: Application of an Oxidative Stress Injury Biomarker (BIOS) Model.
Zhiang NIU ; Xiaohui WU ; Yuncheng ZHU ; Lu YANG ; Yifan SHI ; Yun WANG ; Hong QIU ; Wenjie GU ; Yina WU ; Xiangyun LONG ; Zheng LU ; Shaohua HU ; Zhijian YAO ; Haichen YANG ; Tiebang LIU ; Yong XIA ; Zhiyu CHEN ; Jun CHEN ; Yiru FANG
Neuroscience Bulletin 2022;38(9):979-991
Early distinction of bipolar disorder (BD) from major depressive disorder (MDD) is difficult since no tools are available to estimate the risk of BD. In this study, we aimed to develop and validate a model of oxidative stress injury for predicting BD. Data were collected from 1252 BD and 1359 MDD patients, including 64 MDD patients identified as converting to BD from 2009 through 2018. 30 variables from a randomly-selected subsample of 1827 (70%) patients were used to develop the model, including age, sex, oxidative stress markers (uric acid, bilirubin, albumin, and prealbumin), sex hormones, cytokines, thyroid and liver function, and glycolipid metabolism. Univariate analyses and the Least Absolute Shrinkage and Selection Operator were applied for data dimension reduction and variable selection. Multivariable logistic regression was used to construct a model for predicting bipolar disorder by oxidative stress biomarkers (BIOS) on a nomogram. Internal validation was assessed in the remaining 784 patients (30%), and independent external validation was done with data from 3797 matched patients from five other hospitals in China. 10 predictors, mainly oxidative stress markers, were shown on the nomogram. The BIOS model showed good discrimination in the training sample, with an AUC of 75.1% (95% CI: 72.9%-77.3%), sensitivity of 0.66, and specificity of 0.73. The discrimination was good both in internal validation (AUC 72.1%, 68.6%-75.6%) and external validation (AUC 65.7%, 63.9%-67.5%). In this study, we developed a nomogram centered on oxidative stress injury, which could help in the individualized prediction of BD. For better real-world practice, a set of measurements, especially on oxidative stress markers, should be emphasized using big data in psychiatry.
Biomarkers/metabolism*
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Bipolar Disorder/metabolism*
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Depressive Disorder, Major/diagnosis*
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Early Diagnosis
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Humans
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Oxidative Stress