Purpose: Cancer survivors are at increased risk of diabetes mellitus (DM). Additionally, the prevalence of obesity, which is also a risk factor for DM, is increasing in cancer survivors. We investigated the associations between weight change after cancer diagnosis and DM risk. Materials and Methods: This retrospective cohort study used data from the Korean National Health Insurance Service. Participants who were newly diagnosed with cancer from 2010 to 2016 and received national health screening before and after diagnosis were included and followed until 2019. Weight change status after cancer diagnosis was categorized into four groups: sustained normal weight, obese to normal weight, normal weight to obese, or sustained obese. Cox proportional hazard analyses were performed to examine associations between weight change and DM. Results: The study population comprised 264,250 cancer survivors. DM risk was highest in sustained obese (adjusted hazard ratios [aHR], 2.17; 95% confidence interval [CI], 2.08 to 2.26), followed by normal weight to obese (aHR, 1.66; 95% CI, 1.54 to 1.79), obese to normal weight (aHR, 1.29; 95% CI, 1.21 to 1.39), and then sustained normal weight group (reference). In subgroup analyses according to cancer type, most cancers showed the highest risks in sustained obese group. Conclusion Obesity at any time point was related to increased DM risk, presenting the highest risk in cancer survivors with sustained obesity. Survivors who changed from obese to normal weight had lower risk than survivors with sustained obesity. Survivors who changed from normal weight to obese showed increased risk compared to those who sustained normal weight. Our finding supports the significance of weight management among cancer survivors.

Purpose: Cancer survivors are at increased risk of diabetes mellitus (DM). Additionally, the prevalence of obesity, which is also a risk factor for DM, is increasing in cancer survivors. We investigated the associations between weight change after cancer diagnosis and DM risk. Materials and Methods: This retrospective cohort study used data from the Korean National Health Insurance Service. Participants who were newly diagnosed with cancer from 2010 to 2016 and received national health screening before and after diagnosis were included and followed until 2019. Weight change status after cancer diagnosis was categorized into four groups: sustained normal weight, obese to normal weight, normal weight to obese, or sustained obese. Cox proportional hazard analyses were performed to examine associations between weight change and DM. Results: The study population comprised 264,250 cancer survivors. DM risk was highest in sustained obese (adjusted hazard ratios [aHR], 2.17; 95% confidence interval [CI], 2.08 to 2.26), followed by normal weight to obese (aHR, 1.66; 95% CI, 1.54 to 1.79), obese to normal weight (aHR, 1.29; 95% CI, 1.21 to 1.39), and then sustained normal weight group (reference). In subgroup analyses according to cancer type, most cancers showed the highest risks in sustained obese group. Conclusion Obesity at any time point was related to increased DM risk, presenting the highest risk in cancer survivors with sustained obesity. Survivors who changed from obese to normal weight had lower risk than survivors with sustained obesity. Survivors who changed from normal weight to obese showed increased risk compared to those who sustained normal weight. Our finding supports the significance of weight management among cancer survivors.

Purpose: Cancer survivors are at increased risk of diabetes mellitus (DM). Additionally, the prevalence of obesity, which is also a risk factor for DM, is increasing in cancer survivors. We investigated the associations between weight change after cancer diagnosis and DM risk. Materials and Methods: This retrospective cohort study used data from the Korean National Health Insurance Service. Participants who were newly diagnosed with cancer from 2010 to 2016 and received national health screening before and after diagnosis were included and followed until 2019. Weight change status after cancer diagnosis was categorized into four groups: sustained normal weight, obese to normal weight, normal weight to obese, or sustained obese. Cox proportional hazard analyses were performed to examine associations between weight change and DM. Results: The study population comprised 264,250 cancer survivors. DM risk was highest in sustained obese (adjusted hazard ratios [aHR], 2.17; 95% confidence interval [CI], 2.08 to 2.26), followed by normal weight to obese (aHR, 1.66; 95% CI, 1.54 to 1.79), obese to normal weight (aHR, 1.29; 95% CI, 1.21 to 1.39), and then sustained normal weight group (reference). In subgroup analyses according to cancer type, most cancers showed the highest risks in sustained obese group. Conclusion Obesity at any time point was related to increased DM risk, presenting the highest risk in cancer survivors with sustained obesity. Survivors who changed from obese to normal weight had lower risk than survivors with sustained obesity. Survivors who changed from normal weight to obese showed increased risk compared to those who sustained normal weight. Our finding supports the significance of weight management among cancer survivors.

Objectives: The association between statin use and depression is well studied, but the studies on the association of statin use and bipolar disorders are limited. Thus, we aimed to investigate the effects of taking statin on risk of bipolar disorder using national claims data of South Korea. Methods: A total of 5713871 subjects who did not take statin and were not diagnosed with bipolar disorder before the health examination were included. Among eligible subjects, 315537 subjects started taking statin within 1 year after taking the health examination and 5398334 subjects did not. After 9 years of follow-up, the incidence of bipolar disorder was determined for each group. Results: Compared to subjects who were not exposed to statin, subjects who were exposed to statin showed a greater incidence of bipolar disorder and an increased risk of bipolar disorder (hazard ratio [HR]: 1.66; 95% confidence interval [CI]: 1.58 to 1.75), and after adjusting for age, sex, low income, regular exercise, smoking, drinking, diabetes mellitus, hypertension, body mass index, cholesterol and depression (adjusted HR: 1.32; 95% CI: 1.24 to 1.40). Conclusions This result showed an increased risk of bipolar disorder after taking statin, but the underlying biological mechanism needs further investigations. This study has clinical implications for patients taking statins, which require early assessment and response in addition to drug treatment and lifestyle modification, considering the possibility that unhealthy lifestyle habits may appear as part of the mood symptoms of bipolar disorder.

Objectives: The association between statin use and depression is well studied, but the studies on the association of statin use and bipolar disorders are limited. Thus, we aimed to investigate the effects of taking statin on risk of bipolar disorder using national claims data of South Korea. Methods: A total of 5713871 subjects who did not take statin and were not diagnosed with bipolar disorder before the health examination were included. Among eligible subjects, 315537 subjects started taking statin within 1 year after taking the health examination and 5398334 subjects did not. After 9 years of follow-up, the incidence of bipolar disorder was determined for each group. Results: Compared to subjects who were not exposed to statin, subjects who were exposed to statin showed a greater incidence of bipolar disorder and an increased risk of bipolar disorder (hazard ratio [HR]: 1.66; 95% confidence interval [CI]: 1.58 to 1.75), and after adjusting for age, sex, low income, regular exercise, smoking, drinking, diabetes mellitus, hypertension, body mass index, cholesterol and depression (adjusted HR: 1.32; 95% CI: 1.24 to 1.40). Conclusions This result showed an increased risk of bipolar disorder after taking statin, but the underlying biological mechanism needs further investigations. This study has clinical implications for patients taking statins, which require early assessment and response in addition to drug treatment and lifestyle modification, considering the possibility that unhealthy lifestyle habits may appear as part of the mood symptoms of bipolar disorder.

Objectives: The association between statin use and depression is well studied, but the studies on the association of statin use and bipolar disorders are limited. Thus, we aimed to investigate the effects of taking statin on risk of bipolar disorder using national claims data of South Korea. Methods: A total of 5713871 subjects who did not take statin and were not diagnosed with bipolar disorder before the health examination were included. Among eligible subjects, 315537 subjects started taking statin within 1 year after taking the health examination and 5398334 subjects did not. After 9 years of follow-up, the incidence of bipolar disorder was determined for each group. Results: Compared to subjects who were not exposed to statin, subjects who were exposed to statin showed a greater incidence of bipolar disorder and an increased risk of bipolar disorder (hazard ratio [HR]: 1.66; 95% confidence interval [CI]: 1.58 to 1.75), and after adjusting for age, sex, low income, regular exercise, smoking, drinking, diabetes mellitus, hypertension, body mass index, cholesterol and depression (adjusted HR: 1.32; 95% CI: 1.24 to 1.40). Conclusions This result showed an increased risk of bipolar disorder after taking statin, but the underlying biological mechanism needs further investigations. This study has clinical implications for patients taking statins, which require early assessment and response in addition to drug treatment and lifestyle modification, considering the possibility that unhealthy lifestyle habits may appear as part of the mood symptoms of bipolar disorder.

Objectives: The association between statin use and depression is well studied, but the studies on the association of statin use and bipolar disorders are limited. Thus, we aimed to investigate the effects of taking statin on risk of bipolar disorder using national claims data of South Korea. Methods: A total of 5713871 subjects who did not take statin and were not diagnosed with bipolar disorder before the health examination were included. Among eligible subjects, 315537 subjects started taking statin within 1 year after taking the health examination and 5398334 subjects did not. After 9 years of follow-up, the incidence of bipolar disorder was determined for each group. Results: Compared to subjects who were not exposed to statin, subjects who were exposed to statin showed a greater incidence of bipolar disorder and an increased risk of bipolar disorder (hazard ratio [HR]: 1.66; 95% confidence interval [CI]: 1.58 to 1.75), and after adjusting for age, sex, low income, regular exercise, smoking, drinking, diabetes mellitus, hypertension, body mass index, cholesterol and depression (adjusted HR: 1.32; 95% CI: 1.24 to 1.40). Conclusions This result showed an increased risk of bipolar disorder after taking statin, but the underlying biological mechanism needs further investigations. This study has clinical implications for patients taking statins, which require early assessment and response in addition to drug treatment and lifestyle modification, considering the possibility that unhealthy lifestyle habits may appear as part of the mood symptoms of bipolar disorder.

Abnormal aggregation of α-synuclein is a key element in the pathogenesis of several neurodegenerative diseases, including Parkinson’s disease (PD), dementia with Lewy bodies, and multiple system atrophy. α-synuclein aggregation spreads through various brain regions during the course of disease progression, a propagation that is thought to be mediated by the secretion and subsequent uptake of extracellular α-synuclein aggregates between neuronal cells. Thus, aggregated forms of this protein have emerged as promising targets for disease-modifying therapy for PD and related diseases. Here, we generated and characterized conformation-specific antibodies that preferentially recognize aggregated forms of α-synuclein. These antibodies promoted phagocytosis of extracellular α-synuclein aggregates by microglial cells and interfered with cell-to-cell propagation of α-synuclein. In an α-synuclein transgenic model, passive immunization with aggregate-specific antibodies significantly ameliorated pathological phenotypes, reducing α-synuclein aggregation, gliosis, inflammation, and neuronal loss. These results suggest that conformation-specific antibodies targeting α-synuclein aggregates are promising therapeutic agents for PD and related synucleinopathies.

Objective: This study evaluated the usefulness, as a risk factor of 30-day mortality, in patients residing in nursing-homes (NHs) or long-term care facilities with the diagnosis of pneumonia. Methods: We conducted a retrospective study in a public hospital between January 2017 and December 2017. The subjects included elderly patients residing in NHs and diagnosed with pneumonia in the emergency room. Data on age, gender, comorbidities, laboratory findings, pneumonia severity index score (PSI), and CURB-65 (Confusion, Urea, Respiratory rate, Blood pressure, and Age 65 or older) were entered into an electronic database. Results: A total of 439 patients were enrolled during the study period. The mean age was 82.1±8.0 years; 195 (44.4%) were men, and 30-day mortality was 21.8%. On multivariate Cox proportional hazard analysis, cerebrovascular accidents (hazard ratio [HR], 0.53; 95% confidence interval [CI], 0.33-0.87; P=0.012), chronic renal disease (HR, 2.28; 95% CI, 1.11-4.67; P=0.024), malignancy (HR, 1.69; 95% CI, 1.04-2.76; P=0.034), lactate (HR, 1.02; 95% CI, 1.01-1.03; P<0.001), albumin (HR, 0.52; 95% CI, 0.36-0.73; P<0.001), and red cell distribution width (RDW; HR, 1.11; 95% CI, 1.03- 1.19; P=0.007) were independently associated with 30-day mortality. Areas under the curve of PSI, RDW, albumin, lactate, and PSI+RDW+albumin+lactate were 0.690 (95% CI, 0.629-0.751), 0.721 (95% CI, 0.666-0.775), 0.668 (95% CI, 0.607-0.728), 0.661 (95% CI, 0.597-0.726), and 0.801 (95% CI, 0.750-0.852), respectively. Conclusion RDW, albumin, lactate and especially the combination of PSI and these factors appear to be major determinants of 30-day mortality in NH residents with pneumonia.

OBJECTIVE: Neuropathic pain causes patients feel indescribable pain. Deep Brain Stimulation (DBS) is one of the treatment methods in neuropathic pain but the action mechanism is still unclear. To study the effect and mechanism of analgesic effects from DBS in neuropathic pain and to enhance the analgesic effect of DBS, we stimulated the ventral posterolateral nucleus (VPL) in rats. METHODS: To observe the effect from VPL stimulation, we established 3 groups : normal group (Normal group), neuropathic pain group (Pain group) and neuropathic pain+DBS group (DBS group). Rats in DBS group subjected to electrical stimulation and the target is VPL. RESULTS: We observed the behavioral changes by DBS in VPL (VPL-DBS) on neuropathic pain rats. In our study, the pain score which is by conventional test method was effectively decreased. In specific, the time of showing withdrawal response from painful stimulation which is not used measuring method in our animal model was also decreased by DBS. CONCLUSION: The VPL is an effective target on pain modulation. Specifically we could demonstrate changes of pain response duration which is not used, and it was also significantly meaningful. We thought that this study would be helpful in understanding the relation between VPL-DBS and neuropathic pain.
Animals ; Deep Brain Stimulation ; Electric Stimulation ; Humans ; Models, Animal ; Neuralgia* ; Rats ; Ventral Thalamic Nuclei