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Objective Serum lipid levels may be associated with the affective severity of bipolar disorder, but data on lipid profiles in Asian patients with bipolar disorder and the lipid alterations in different states of opposite polarities are scant. We investigated the lipid profiles of patients in the acute affective, partial, and full remission state in bipolar mania and depression. Methods The physically healthy patients aged between 18 and 45 years with bipolar I disorder, as well as age-matched healthy normal controls were enrolled. We compared the fasting blood levels of glucose, cholesterol, triglyceride, low-density lipoprotein, and high-density lipoprotein of manic or depressed patients in the acute phase and subsequent partial and full remission with those of their normal controls. Results A total of 32 bipolar manic patients (12 women and 20 men), 32 bipolar depressed participants (18 women and 14 men), and 64 healthy control participants took part in this study. The mean cholesterol level in acute mania was significantly lower than that in acute depression (p < 0.025). The lowest rate of dyslipidemia (hypertriglyceridemia or low high-density lipoprotein cholesterol) was observed in acute bipolar mania. Conclusion Circulating lipid profiles may be easily affected by affective states. The acute manic state may be accompanied by state-dependent lower cholesterol and triglyceride levels relative to that in other mood states.

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This study investigates the key antecedents and mechanisms that influence customer identification in healthcare contexts, based on two studies from different stakeholders: healthcare workers and patients (customers) of healthcare organisations. The first study (N = 788) explored a positive relationship between a hospital's service tangibility and service reliability. The second (N = 657) affirmed and expanded this finding, and revealed that the service reliability of a hospital was positively related to customer identification with the hospital. This service reliability further mediated the positive relationship between service tangibility and customer identification. Our results highlight the role of service tangibility and reliability in enhancing customer identification in healthcare contexts. Implications for theory and practice are discussed.

Green technology innovation is increasingly becoming an important driver of modern development. Facing the pressure of the carbon neutrality target, China has been strengthening environmental regulations in recent years, and the green technology innovation ability of market players has been affected. Moreover, the impact of environmental regulations on green technology innovation and the strategies to develop green technology innovation still need to be further explored. Here, we used 285 cities from 2010–2020 as research subjects, constructed indicators such as environmental regulation and green technology innovation capability, and used panel regression, threshold effect and mediating effect methods. The results reveal that: (1) environmental regulation has a disincentive effect on green technology innovation, as increased environmental regulation increases production costs, external costs and opportunity costs for firms, causing a mismatch of resources and creating a “crowding-out effect” that inhibits innovation development; (2) further study finds that when the human capital level reaches a certain threshold value, the impact of environmental regulation on green technology innovation shifts significantly, i.e., there is a threshold effect; (3) industrial structure can further be upgraded and optimized by environmental regulation, which will have an impact on green technology innovation, thus industrial structure optimization plays a mediating role. We conclude with recommendations for improving green innovation techniques for market players, and provide some lessons for accelerating the goal of carbon neutrality and promoting quality economic development.

Background:In patients with diabetes mellitus, painful diabetic peripheral neuropathy (PDPN) is a frequent complication and can cause poor quality of life. We compared the efficacy and safety of duloxetine with those of gabapentin in patients with PDPN through a systematic review and meta-analysis of randomised controlled trials. MaterialsandMethods:PubMed, Embase and the Cochrane Library were searched for eligible studies published from database inception to January 2021. Visual Analogue Scale (VAS), sleep interference score, Clinical Global Impression of Change (CGIC), Patient Global Impression of Change (PGIC), Diabetic Neuropathy Symptom (DNS) score, Diabetic Neuropathic Examination (DNE) score, Neuropathic Disability Score (NDS) and side effects were used to compare duloxetine and gabapentin in patients with PDPN. Results:Three eligible randomised controlled trials involving 290 patients were included. No significant differences were observed between patients receiving duloxetine and gabapentin with respect to VAS (mean change difference = −1.23, 95% CI, −6.09 to 3.62; P = .62), sleep interference score (mean change difference = 0.42, 95% CI, −0.15 to 1.00; P = .15), CGIC (mean difference = 0.04, 95% CI, −0.11 to 0.20; P = .60), PGIC (mean difference= 0.24, 95% CI, −0.13 to 0.60; P = .21), DNS (mean change difference = 0.14, 95% CI, −0.35 to 0.63; P = .58), DNE (mean change difference = 0.26, 95% CI, −0.35 to 0.86; P = .41) and NDS (mean change difference = 0.30, 95% CI, −0.02 to 0.63; P = .07).Conclusions:No significant differences were observed in the efficacy of duloxetine and gabapentin when treating patients with PDPN.

Aim Older patients with bipolar disorder (BD) are at a high risk of stroke. Silent stroke could be neglected in BD patients after middle age, particularly in those with illness onset at the young age. Therefore, we investigated the morbidity and related factors for stroke in older BD patients with typical‐onset age. Methods Older patients with bipolar I disorder (age > 50 years) and their illness onset prior to the age of 40 years were recruited. After whole‐brain magnetic resonance imaging was conducted, the patients were divided into stroke and non‐stroke groups. Clinical data were obtained by reviewing all available medical records and directly interviewing the patients along with their reliable family members. Results We recruited 62 patients with a mean age of 60.4 years and illness onset at the mean age of 28.4 years. Cerebral infarction or old stroke was observed in 24 (38.7%) patients, including 22 without any reported clinical history of stroke. That is, silent stroke (n = 22) was detected in 36.7% of 60 patients without clinical history of stroke. The stroke group had significantly higher mean numbers of lifetime mood episodes (P = 0.006) than the non‐stroke one. Logistic regression analysis showed that 10 or more prior mood episodes (odds ratio = 3.43, 95% confidence interval = 1.12–10.47, P < 0·04) was significantly associated with the occurrence of stroke. The two study groups did not exhibit any other differences in demographic and clinical variables, such as age, laboratory or physical measurements during the last acute psychiatric hospitalisation, body mass index, and substance use problems and concurrent medical diseases. Conclusions High morbidity of stroke, particularly silent stroke, could be found in older bipolar patients with typical‐onset age. In addition to traditional risk factors, the number of recurrent mood episodes in a lifetime may increase the risk of stroke in older BD patients.