Clinical characteristics and cognitive function in bipolar disorder patients with different onset symptom

BackgroundIn recent years, studies on the clinical features and cognitive impairment of patients with different first-episode types of bipolar disorder have received increasing attention. The patients with bipolar disorder may present with different symptoms at first onset. The aim of this study is to assess the cognitive functions of a patient’s index episode of bipolar disorder, depression or mania, on risk factors of effecting on cognitive functions.MethodOne hundred sixty eight patients with bipolar disorder diagnosed for the first time were enrolled in the study. All patients were divided into two groups according to their index episode of bipolar disorder, either depression or mania. Seventy three patients of the cohort had an index episode mania and 95 patients had initial symptoms of depression. Demographic and clinical disease characteristic data of all enrolled patients were collected. Meanwhile, 75 healthy controls were included. Demographic data of controls were collected. The cognitive functions of all patients and controls were detected by continuous performance test (CPT), digital span test (DST) and Wisconsin card sorting test (WCST). The main cognitive functions data were compared among the mania group, depression group and control group. The relevant risk factors affecting cognitive function were analyzed.Results(1) Most patients with bipolar disorder had an index episode depression (56.55% vs. 43.45%). Compared with the depression group, the mania group had later age of onset [(24.01 ± 4.254) vs. (22.25 ± 6.472), t = 2. 122, p = 0.035]. The education level of patient groups was lower than control group (p < 0.001). (2) The healthy control group’s DST, WCST and CPT scores were better than the patient groups (All p < 0.05). The mania group’s DST (forward, reverse, sum), WCST (total responses, completed classifications, correct responses, incorrect responses, percentage of correct responses, completed the number of responses required for classification, the percentage of conceptualization level, the number of persistent responses, non-persistent errors), CPT (2 digit score, 3 digit score, 4 digit score) was better than the depression group (p < 0.05). (3) In mania group, correlation analysis showed that all CPT parameter, inverse digit span, and the sum of DST was negatively correlated with the education level (All p < 0.05). The CPT-4 digit score was negatively correlated with onset age (p < 0.05). In the WCST, the number of correct responses, the percentage of correct responses and the percentage of conceptualization level were positively correlated with the BRMS score (All p < 0.05). The number of false responses and persistent responses were negatively correlated with the BRMS score (All p < 0.05). The number of persistent errors and percentage of persistent errors was positively correlated with education years (All p < 0.05). In depression group, there was a positive correlation between inverse digit span and the education level (p < 0.05).ConclusionIn our study, there were cognitive impairments in attention, memory, and executive function of patients with different onset syndromes of bipolar disorder. Compared with the mania group, the degree of cognitive impairments in bipolar patients with the depressive episode was more severe. The risk factors affecting cognitive impairments included the age of onset, education level, number of hospitalizations and severity of illness

Reflections on Solving the Problem of Food Safety Based on Credit Enhancement

Based on current situation of frequent occurrence of food incidents, this paper made an in-depth analysis on causes of food incidents, mainly including weak awareness of frontline staff, excessive pursuit of food producers and operators for profit, vacancy and lagging of administrative supervision, and lack of honesty and public interests. In view of these four causes, it came up with pertinent recommendations from the perspective of improving the credit situation

Naphthalene-Based Microporous Polyimides: Adsorption Behavior of CO₂ and Toxic Organic Vapors and Their Separation from Other Gases

Naphthalene was selected as a building block to prepare three polyimide networks with different topological structures via one-pot polycondensation from naphthalene-1,4,5,8-tetracarboxylic dianhydride with tetrakis­(4-aminophenyl)­methane, tris­(4-aminophenyl)­amine, and 1,3,5-tris­(4-aminophenyl)­benzene. The resultant polymers have moderately large BET surface areas with narrow pore size distribution at around 6 Å. Interestingly, it is found that they can uptake 90.5 wt % benzene vapor (298 K, 0.8 bar), and the separation factors of benzene over nitrogen, water, and cyclohexane are as high as 759.3, 40.3, and 13.8, respectively. The high adsorption capacity and selectivity of benzene vapor are attributed to the incorporation of large amount of naphthalene groups in the network since naphthalene is highly hydrophobic in nature and has strong π-electron-delocalization effect. On the other hand, the CO₂ uptakes in polymers reach 12.3 wt % (273 K, 1 bar), and the adsorption curves are reversible. Moreover, the separation factors of CO₂/N₂ and CO₂/CH₄ are 88.6 and 12.9, respectively, superior to many other microporous organic polymers. The above experimental results were analyzed and explained with respect to the kinetic diameters, polarity, critical temperature of the vapors and gases, and the stereoconfiguration of net nodes, porous characteristics, and hydrophobic/hydrophilic nature of the pore walls of the microporous polyimides

Tetraphenyladamantane-Based Microporous Polyimide and Its Nitro-Functionalization for Highly Efficient CO₂ Capture

A new microporous polyimide network (PI-ADNT) is synthesized from 1,3,5,7-tetrakis­(4-aminophenyl)­adamantane and naphthalene-1,4,5,8-tetracarboxylic dianhydride. Subsequently, PI-ADNT is nitrated in fuming nitric acid with different nitration time to produce three nitro-decorated porous polyimides (PI-NO₂s). Their chemical structures and nitration degrees are characterized by FTIR, solid-state ¹³C CP/MAS NMR spectra and element analysis. The interesting evolution of porous morphology and porosity of PI-NO₂s with nitration time is investigated in detail. The results show that PI-ADNT has the BET surface area of 774 m² g^–1 with microporous size centering at 0.75 nm. After nitration-modifications, PI-NO₂s display decreased surface area but remarkably increased CO₂ uptake up to 4.03 mmol g^–1, which is superior to most of porous polymers reported in the literature. Moreover, the CO₂ adsorption selectivites over CH₄ and N₂ in PI-NO₂s are also significantly improved in comparison with PI-ADNT. The CO₂ adsorption/separation properties of PI-ADNT and its nitrated products are studied and explained in terms of the variations of porous structure and chemical composition as well as the interaction parameters between CO₂ molecule and polymer skeleton such as Henry’s constant, first virial coefficient, and enthalpy of adsorption

Anisotropy-Based Adaptive Polynomial Chaos Method for Hybrid Uncertainty Quantification and Reliability-Based Design Optimization of Structural-Acoustic System

The evaluation of objective functions and component reliability in the optimisation of structural-acoustic systems with random and interval variables is computationally expensive, especially when strong nonlinearity exhibits between the response and input variables. To reduce the computational cost and improve the computational efficiency, a novel anisotropy-based adaptive polynomial chaos (ABAPC) expansion method was developed in this study. In ABAPC, the anisotropy-based polynomial chaos expansion, namely the retained order of polynomial chaos expansion (PCE) differs from each variable, is used to construct the initial surrogate model instead of first-order polynomial chaos expansion in conventional methods. Then, an anisotropy-based adaptive basis growth strategy was developed to reduce the estimation of the coefficients of the polynomial chaos expansion method and increase its computational efficiency. Finally, to solve problems with probabilistic and interval parameters, an adaptive basis truncation strategy was introduced and implemented. Using the ABAPC method, the computational cost of reliability-based design optimisation for structural-acoustic systems can be efficiently reduced. The effectiveness of the proposed method were demonstrated by solving two numerical examples and optimisation problems of a structural-acoustic system

Anisotropy-Based Adaptive Polynomial Chaos Method for Hybrid Uncertainty Quantification and Reliability-Based Design Optimization of Structural-Acoustic System

The evaluation of objective functions and component reliability in the optimisation of structural-acoustic systems with random and interval variables is computationally expensive, especially when strong nonlinearity exhibits between the response and input variables. To reduce the computational cost and improve the computational efficiency, a novel anisotropy-based adaptive polynomial chaos (ABAPC) expansion method was developed in this study. In ABAPC, the anisotropy-based polynomial chaos expansion, namely the retained order of polynomial chaos expansion (PCE) differs from each variable, is used to construct the initial surrogate model instead of first-order polynomial chaos expansion in conventional methods. Then, an anisotropy-based adaptive basis growth strategy was developed to reduce the estimation of the coefficients of the polynomial chaos expansion method and increase its computational efficiency. Finally, to solve problems with probabilistic and interval parameters, an adaptive basis truncation strategy was introduced and implemented. Using the ABAPC method, the computational cost of reliability-based design optimisation for structural-acoustic systems can be efficiently reduced. The effectiveness of the proposed method were demonstrated by solving two numerical examples and optimisation problems of a structural-acoustic system