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Abstract Introduction The prevalence of type 2 diabetes (T2D) has increased dramatically in recent decades, and there are increasing indications that dementia is related to T2D. Previous attempts to analyze such relationships principally relied on traditional multiple linear regression (MLR). However, recently developed machine learning methods (Mach-L) outperform MLR in capturing non-linear relationships. The present study applied four different Mach-L methods to analyze the relationships between risk factors and cognitive function in older T2D patients, seeking to compare the accuracy between MLR and Mach-L in predicting cognitive function and to rank the importance of risks factors for impaired cognitive function in T2D. Methods We recruited older T2D between 60–95 years old without other major comorbidities. Demographic factors and biochemistry data were used as independent variables and cognitive function assessment (CFA) was conducted using the Montreal Cognitive Assessment as an independent variable. In addition to traditional MLR, we applied random forest (RF), stochastic gradient boosting (SGB), Naïve Byer’s classifier (NB) and eXtreme gradient boosting (XGBoost). Results Totally, the test cohort consisted of 197 T2D (98 men and 99 women). Results showed that all ML methods outperformed MLR, with symmetric mean absolute percentage errors for MLR, RF, SGB, NB and XGBoost respectively of 0.61, 0.599, 0.606, 0.599 and 0.2139. Education level, age, frailty score, fasting plasma glucose and body mass index were identified as key factors in descending order of importance. Conclusion In conclusion, our study demonstrated that RF, SGB, NB and XGBoost are more accurate than MLR for predicting CFA score, and identify education level, age, frailty score, fasting plasma glucose, body fat and body mass index as important risk factors in an older Chinese T2D cohort.

AIM: To evaluate the functional and structural changes of photoreceptors in patients and asymptomatic carriers with Leber hereditary optic neuropathy (LHON) using full-field electroretinography (FERG) and optical coherence tomography (OCT). METHODS: Individuals diagnosed with LHON at the Renmin Hospital of Wuhan University and their family members were included in this cross-sectional observational study. The FERG a-wave amplitude of affected patients and asymptomatic carriers was analyzed. The thickness of the outer nuclear layer (ONL), inner and outer segment (IS/OS) and total photoreceptors in the macular fovea and parafovea were measured. RESULTS: This study included 14 LHON patients (mean age: 20.00±9.37y), 12 asymptomatic carriers (mean age: 39.83±6.48y), and 14 normal subjects (mean age: 24.20±1.52y). The FERG results showed that the dark-adapted 3.0 electroretinography and light-adapted 3.0 electroretinography a-wave amplitudes of patients and carriers were significantly decreased (P0.05). CONCLUSION: Photoreceptors function is significantly impaired in LHON-affected patients and asymptomatic carriers. Meanwhile, photoreceptors morphology is slightly altered, mainly manifesting as a change in ONL thickness.

Abstract Background Age, obesity, and metabolic syndrome are known risk factors for gallstones; however, the combined impact of these different risk factors on gallstone formation has not yet been examined. Methods This retrospective, cross-sectional study involved 3190 participants, including 207 participants (6.5%) with gallstones and 986 (30.9%) with metabolic syndrome. Participants were divided into four phenotypes according to metabolic syndrome and obesity status: 1378 participants were metabolically healthy and non-obese (MHNO); 826 were metabolically healthy but obese (MHO); 185 were metabolically abnormal but not obese (MANO); and 801 participants were metabolically abnormal and obese (MAO). Results The MAO and MANO phenotypes had more gallstones than the MHO and MHNO phenotypes, regardless of age (

The urine albumin–creatinine ratio (uACR) is a warning for the deterioration of renal function in type 2 diabetes (T2D). The early detection of ACR has become an important issue. Multiple linear regression (MLR) has traditionally been used to explore the relationships between risk factors and endpoints. Recently, machine learning (ML) methods have been widely applied in medicine. In the present study, four ML methods were used to predict the uACR in a T2D cohort. We hypothesized that (1) ML outperforms traditional MLR and (2) different ranks of the importance of the risk factors will be obtained. A total of 1147 patients with T2D were followed up for four years. MLR, classification and regression tree, random forest, stochastic gradient boosting, and eXtreme gradient boosting methods were used. Our findings show that the prediction errors of the ML methods are smaller than those of MLR, which indicates that ML is more accurate. The first six most important factors were baseline creatinine level, systolic and diastolic blood pressure, glycated hemoglobin, and fasting plasma glucose. In conclusion, ML might be more accurate in predicting uACR in a T2D cohort than the traditional MLR, and the baseline creatinine level is the most important predictor, which is followed by systolic and diastolic blood pressure, glycated hemoglobin, and fasting plasma glucose in Chinese patients with T2D.

ObjectivesStudies concerning the risk of metabolic syndrome associated with night work have shown inconsistent findings, due to imprecise working time data and cross-sectional design. We used register-based daily working time data to examine the risk of incident metabolic syndrome associated with night shift work.MethodsWorking time data collected between 2010 and 2018 of 5775 Taiwanese hospital workers were used to identify night shift workers and to calculate the number of night shifts. Metabolic syndrome was identified by annual occupational health examination results, which were linked to the working time data. Logistic regression models and generalized estimating equations were used to examine the association between night shift work and metabolic syndrome and the 5 components of metabolic syndrome.ResultsNight shift work is associated with a higher risk of developing metabolic syndrome (adjusted OR = 1.36, 95% CI = 1.04 to 1.78) and high waist circumference (adjusted OR = 1.27, 95% CI = 1.07 to 1.78) compared to day work. Among night shift workers, increased number of night shifts was associated with high blood pressure (adjusted OR = 1.15, 95% CI = 1.01 to 1.31).ConclusionsNight shift work is associated with metabolic risk factors. Long-term effects of circadian rhythm disruption on metabolic disturbances needs to be further studied.

Inhibition of phosphodiesterase-4 (PDE4) by rolipram, a prototypical PDE4 inhibitor, reverses memory impairment produced pharmacologically or genetically. Comparably, much less is known about the effect of rolipram on cerebral ischemia-induced memory deficits. The objective of this study was to determine the effects of rolipram on ischemia-induced memory deficit, neuronal damage, and alteration of PDE4 activity in the hippocampus. Memory was examined using Morris water-maze and step-through passive avoidance tests in rats subjected to global cerebral ischemia with or without repeated treatment with rolipram (0.3 or 1 mg/kg, i.p.); neuronal damage in the hippocampus and PDE4 activity in hippocampal tissues were determined using Nissl staining and HPLC, respectively. In the water-maze test, cerebral ischemia significantly increased the escape latency to reach the platform during acquisition training and decreased the exploration time in the target quadrant in the probe trial test; these were blocked by rolipram in a dose-dependent manner. Rolipram also reduced the distracted platform searches induced by cerebral ischemia. In the passive avoidance test, ischemia decreased the 24-h latency to the dark compartment, which was also blocked by rolipram treatment. In addition, Nissl staining revealed ischemia-induced neuron loss in hippocampal CA1; this was blocked by rolipram. Further, cerebral ischemia led to increases in activity of PDE, primarily PDE4, in the hippocampus, which also was antagonized by rolipram. These results suggest that rolipram prevents cerebral ischemia-induced memory deficits via inhibition of increased PDE4 activity and attenuation of hippocampal, neuronal damages induced by ischemia. PDE4 may be a target for treatment of cognitive disorders associated with cerebral ischemia. [ABSTRACT FROM AUTHOR]

Phosphodiesterase-4 (PDE4) plays an important role in mediating memory via the control of intracellular cAMP signaling; inhibition of PDE4 enhances memory. However, development of PDE4 inhibitors as memory enhancers has been hampered by their major side effect of emesis. PDE4 has four subtypes (PDE4A-D) consisting of 25 splice variants. Mice deficient in PDE4D displayed memory enhancement in radial arm maze, water maze, and object recognition tests. These effects were mimicked by repeated treatment with rolipram in wild-type mice. In addition, similarly as rolipram-treated wild-type mice, PDE4D-deficient mice also displayed increased hippocampal neurogenesis and phosphorylated cAMP response element-binding protein (pCREB). Furthermore, microinfusion of lentiviral vectors that contained microRNAs (miRNAs) targeting long-form PDE4D isoforms into bilateral dentate gyri of the mouse hippocampus downregulated PDE4D4 and PDE4D5, enhanced memory, and increased hippocampal neurogenesis and pCREB. Finally, while rolipram and PDE4D deficiency shortened α2 adrenergic receptor-mediated anesthesia, a surrogate measure of emesis, miRNA-mediated PDE4D knock-down in the hippocampus did not. The present results suggest that PDE4D, in particular long-form PDE4D, plays a critical role in the mediation of memory and hippocampal neurogenesis, which are mediated by cAMP/CREB signaling; reduced expression of PDE4D, or at least PDE4D4 and PDE4D5, in the hippocampus enhances memory but appears not to cause emesis. These novel findings will aid in the development of PDE4 subtype- or variant-selective inhibitors for treatment of disorders involving impaired cognition, including Alzheimer's disease. [ABSTRACT FROM AUTHOR]

Rationale: Cyclic AMP signaling plays an important role in memory loss associated with Alzheimer’s disease (AD). However, little is known about whether inhibition of phosphodiesterase-4 (PDE4), which increases intracellular cAMP, reverses β-amyloid peptide (Aβ)-induced memory deficits. Objective: Experiments were performed to demonstrate the effect of the PDE4 inhibitor rolipram on memory impairment produced by Aβ1–40 (Aβ40) or its core fragment Aβ25–35. Methods: We tested memory using Morris water-maze and passive avoidance tasks and examined expression of phosphorylated cAMP response-element binding protein (pCREB) in the hippocampus in rats treated with Aβ25–35 or Aβ40 into bilateral CA1 subregions, with or without rolipram administration. Results: Aβ25–35 (10 μg/side) increased escape latency during acquisition training and decreased swimming time and distance in the target quadrant in the water-maze probe trial; it also decreased 24-h retention in the passive avoidance paradigm. All these were reversed by chronic administration of rolipram (0.5 mg/kg). Similarly, Aβ40 (4 μg/side) produced memory impairment, as demonstrated by decreased retention in passive avoidance; this was also reversed by repeated treatment with rolipram. In addition, rolipram blocked extinction of memory during the 32-day testing period in the passive avoidance test. Further, Aβ40 decreased pCREB expression in the hippocampus, which was also reversed by rolipram; the changes in pCREB were highly correlated with those in memory. Conclusions: These results suggest that the PDE4 inhibitor rolipram reverses cognitive deficits associated with AD most likely via increased cAMP/CREB signaling in the hippocampus; PDE4 could be a target for drugs that improve cognition in AD. [ABSTRACT FROM AUTHOR]

The article offers information on a study which examines the combined effects of follicle stimulating hormone (FSH) and luteinizing hormone (LH) on in vitro development and secretion of estradiol of bovine preantral follicles. It notes that the growth of prentral follicles are not influenced by the addition of LH to the culture medium. It mentions however that FSH in the culture medium stimulated the growth, and influenced the development of estradiol production of bovine preantral follicles.

A novel polymer-stabilized blue phase liquid crystal display (PS-BPLCD) using an optimized BPLC for new wall-electrode cell structure and also new driving method has been developed. Those technologies enable BPLCDs to apply conventional source driver IC in AMLCD applications. This novel PS-BPLCDs successfully achieved high-performance LCDs with over 2 times higher optoelectronic properties and a superior reliability. [ABSTRACT FROM AUTHOR]

Blue phase liquid crystal displays (BPLCDs) have attracted considerable attention in recent years because of its many advantages. However, BPLCDs exhibit narrow temperature range, high driving voltage, and tough process. In our works, polymer-stabilized technology using newly optimized BPLC material was applied to enlarge BP temperature range. In order to overcome high driving voltage, 2D1G design was used to apply conventional source driver IC for cost. Furthermore, novel groove cell structure which could gain more effective electric field without adding special masks for the groove was successfully implemented. Finally, 10-inch BPLCDs was demonstrated by optimization of ODF process. [ABSTRACT FROM AUTHOR]

The article describes the case of a 47-year-old woman who was admitted for left hemiparesis due to right corona radiata infarct. She initially received constraint-induced movement therapy (CIMT) to restrain the unaffected upper extremity. She was diagnosed with congenital mirror movements (CMMs) enhanced by stroke.