Background: Substantial studies have reported the prevalence and the affecting factors of subjective cognitive decline (SCD). The complaints screening scale has also been used for probing. However, little is known in China. Objective: To investigate the prevalence and risk factors of SCD, and explore an SCD complaints screening scale in China. Methods: Stratified cluster random sampling was conducted. 2,689 residents aged 60–80 years completed questionnaire 1. 814 residents were included for clinical and neuropsychological evaluations. Two standards were used to make the diagnosis of mild cognitive impairment (MCI) and SCD, and a preliminary screening rate comparison was carried out. Finally, we assessed the risk factors of SCD and the correlation between the SCD-questionnaire 9 (SCD-Q9) and the Auditory Verbal Learning Test-Long Delay Free Recall (AVLT-LR). Results: 1) Standard 1 (ADNI2): the prevalence of SCD was 18.8% (95% CI = 14.7–22.9%) and zero conformed to six criteria (SCD plus). 2) Standard 2 (Jak/Bondi): the prevalence of SCD was 14.4% (95% CI = 10.7–18.1%). 3) Standard 1 had a relatively higher “false” positive rate, whereas Standard 2 had higher “false” negative rate. 4) Age, low education, fewer close friends, and daily drinking were independent risk factors for SCD progressing to MCI. 5) Total points of SCD-Q9 were negatively correlated to the value of AVLT-LR. Conclusions: The prevalence of SCD is high in the ShunYi District in Beijing, China. Age, low education, less social support, and daily drinking are independent risk factors. The brief SCD-Q9 can be used as a reference.

Background: Since SCD (plus) was standardized, little is known about its demographic characteristics and its outcomes of neuropsychological assessments, including the SCD questionnaire 9 (SCD‐Q9).Objective: To characterize SCD (plus) by comparing the neuropsychological features among its subgroups and with normal controls (NC). Also, to explore its demographics and to understand the relation of the chief complaints and the scores of SCD‐Q9.Methods: Multistage stratified cluster random sampling was conducted to select participants. As a result, 84 NC and 517 SCD (plus) were included. SCD (plus) was further classified into several subgroups (SCD‐C: concerned cognitive decline; SCD‐F: complaints about SCD within the past five years; SCD‐P: feeling performance being not as good as their peers; SCD+: presented> 3 of SCD (plus) features; SCD‐: presented ≤ 3 of SCD (plus) features (see the diagnostic criteria for the details)) and between‐group comparisons of neuropsychological scores were conducted. Point‐biserial correlation and binary logistic regression analyses were performed to investigate the demographic characteristics of its subgroups. Finally, Spearman correlation was used to better understand the relation of SCD (plus) to SCD‐Q9.Results: (1) Scores of AVLT‐LR (AVLT‐LR: Auditory Verbal Learning Test‐Long Delayed Recall) and MoCA‐B (MoCA: Montreal Cognitive Assessment‐Basic) were lower in the SCD‐P group than those in the NC group, and the SCD+ group scored lower in the MoCA‐B and CDT(CDT: Clock Drawing Test) than the SCD‐ group. (2) Females were more concerned than male participants. Individuals with lower education level felt that their cognitive performance were worse than their peers. Also, younger people might express concerns more than the more elderly. People who had complaints of SCD‐P might be more likely to report SCD‐C, but less likely to report SCD‐F. (3) Positive correlations were found between the chief complaints of SCD (plus) and some items of SCD‐Q9.Conclusions: SCD (plus) may be related to demographic factors. Individuals with SCD (plus) already exhibited cognitive impairment, which can be detected by SCD‐Q9.

Background: Since subjective cognitive decline (SCD) was standardized in 2014, many studies have investigated its features. However, the risk of SCD (plus) progressing to AD is much higher, and yet there have been few studies reporting the risk factors and neuropsychological assessment characteristics of SCD (plus). Objective: To characterize SCD (plus) by comparing it with normal control (NC), amnesic mild cognitive impairment (aMCI), and Alzheimer Disease (AD) regarding their demographics, lifestyle, family history of dementia, multimorbidity and the neuropsychological assessments. Methods: A total of 135 participants were recruited, including 23 NC, 30 SCD (plus), 45 aMCI and 37 AD. Descriptive statistics were provided. A logistic regression model was used to analyze the affecting factors of SCD (plus), and finally the Receiver Operating Characteristic (ROC) analysis was applied to distinguish between SCD (plus) and NC. Results: (1) SCD (plus) group was younger than both the aMCI group and AD group. It consisted of more participants with mental work and higher body mass index (BMI) than the AD group. (2) Scores of Auditory Verbal Learning Test - Immediate recall (AVLT-IR) and AVLT-Long delayed recall (AVLT-LR) decreased in the following order: NC→SCD (plus)→aMCI→AD. (3) The Area Under Curve (AUC) for discriminating SCD (plus) and NC group was from 0.673 to 0.838. Conclusion: Aging is an important risk factor of both NC progressing to SCD (plus), and SCD (plus) progressing to aMCI or AD. In addition to aging, lower education level and lower BMI were significantly associated with greater odds of SCD (plus) progressing to aMCI or AD patients, whereas mental work was a protective factor of SCD (plus) progressing to AD. Finally, AVLT is a sensitive indicator of the cognitive decline and impairment in SCD (plus) in relative to normal controls.

Growing industrialization of China exposes its labor population to the risk of musculoskeletal disorders (MSDs). This study aimed to investigate the prevalence and risk factors of musculoskeletal disorders (MSDs) in a modern industrial region of Beijing. A cross-sectional study included1,415 employees in six industrial companieswas conducted between January and May 2018, in Fangshan district, Beijng, China. Nordic Musculoskeletal Questionnaire (NMQ) was used to collect the information about MSDs. Demographic factors, lifestyle factors, health and medical factors, and work-related factors were collected as independent variables. Descriptive statistics, the chi-squared (χ 2) test and binary logistic regression analysis were used to analyze data. Among 1,415 participants, 498 reported MSDs. The regions involved were the neck (25.16%), shoulders (17.17%), and upper back (13.29%). There was a significant statistically difference between frontline industrial workers compared with other staff in the prevalence of self-reported symptoms involving the shoulders (χ 2 = 4.33, P = 0.037), wrists and hands (χ 2 = 8.90, P = 0.003), ankles and feet (χ 2 = 12.88, P < 0.001).Increased age (P = 0.005, OR = 1.63; P = 0.001, OR = 2.33), a high or a low salary (P < 0.001, OR = 0.49; P < 0.001, OR = 0.30), night-shift (P = 0.027, OR = 1.46), two-week-history of illness and treatment (P = 0.004, OR = 5.60; P = 0.013, OR = 4.19), concurrent chronic diseases (P = 0.001, OR = 3.45; P = 0.092, OR = 7.81), limited access to health information (P = 0.004, OR = 0.49), and negative attitude towards seeking healthcare (P = 0.010, OR = 1.77; P = 0.009, OR = 2.75) were associated with MSDs in frontline workers. Female gender (P < 0.001, OR = 2.30), high education (P = 0.001, OR = 1.96), noexercises (P = 0.027, OR = 0.59), night-shift (P = 0.017, OR = 1.98), concurrent chronic diseases (P = 0.002, OR = 3.73; P = 0.020, OR = 13.42), limited access to health information (P = 0.013, OR = 0.53),far distance to medical institution (P = 0.009, OR = 1.83), and negative propensity (P = 0.009, OR = 1.94; P = 0.014, OR = 2.74) were associated with MSDs in other staffs. The prevalence of MSDs among industrial employees has changed. Frontline workers had different prevalence and risk factors for MSDs compared with other employees. Negative propensity to healthcare, limited ways to obtain health knowledge, and concomitant chronic diseases were associated with MSDs. Surprisingly, highly educated and high-income employees had a higher risk of MSDs. This is an-open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0

Background and Objective: Myocardial infarction (MI) leads to pathological cardiac remodeling and heart failure. Sodium tanshinone IIA sulfonate (STS) shows to possess therapeutic potential. The present study aimed to explore the potential role of STS in ventricular remodeling post-MI. Methods: Mice were randomly divided into sham, MI + normal saline (NS) and MI + STS (20.8 mg/kg/day intraperitoneally) groups. MI was established following left anterior descending artery ligation. Cardiac function was evaluated using echocardiography. Scar size and myocardial fibrosis-associated markers were detected using Masson’s trichrome staining and western blot analysis (WB). Necrosis and inflammation were assessed using H&E staining, lactate dehydrogenase (LDH) detection, ELISA, immunohistochemical staining, and WB. Furthermore, angiogenesis markers and associated proteins were detected using immunohistochemical staining and WB. Results: Mice treated with STS exhibited significant improvements in cardiac function, smaller scar size, and low expression levels of α-smooth muscle actin and collagen I and III at 28 days following surgery, compared with the NS-treated group. Moreover, treatment with STS reduced eosinophil necrosis, the infiltration of inflammatory cells, plasma levels of LDH, high mobility group protein B1, interleukin-1β and tumor necrosis factor- α, and protein expression of these cytokines at 3 days. Macrophage infiltration was also decreased in the STS group in the early phase. Additionally, CD31+ vascular density, protein levels of hypoxia-inducible factor- 1α, and vascular endothelial growth factor were elevated in the STS-treated mice at 28 days. Conclusion: STS improved pathological remodeling post-MI, and the associated therapeutic effects may be a result of a decrease in myocardial necrosis, modulation of inflammation, and an increase in angiogenesis.

By employing a proteomic analysis on supernatant of mechanically stretched cardiomyocytes, we found that stretch induced a significantly high level of β-2 microglobulin (β2M), a non-glycosylated protein, which is related to inflammatory diseases but rarely known in cardiovascular diseases. The present data showed that serum β2M level was increased in patients with hypertension and further increased in patients with chronic heart failure (HF) as compared with control group, and the high level of serum β2M level correlated to cardiac dysfunction in these patients. In pressure overload mice model by transverse aortic constriction (TAC), β2M levels in serum and heart tissue increased progressively in a time-dependent manner. Exogenous β2M showed pro-fibrotic effects in cultured cardiac fibroblasts but few effects in cardiomyocytes. Adeno-associated virus 9 (AAV9)-mediated knockdown of β2M significantly reduced cardiac β2M level and inhibited myocardial fibrosis and cardiac dysfunction but not cardiac hypertrophy at 4 weeks after TAC. In vitro, mechanical stretch induced the rapid secretion of β2M mainly from cardiomyocytes by activation of extracellular-regulated protein kinase (ERK). Conditional medium (CM) from mechanically stretched cardiomyocytes activated cultured cardiac fibroblasts, and the effect was partly abolished by CM from β2M-knockdown cardiomyocytes. In vivo, knockdown of β2M inhibited the increase in phosphorylation of epidermal growth factor receptor (EGFR) induced by TAC. In cultured cardiac fibroblasts, inhibition of EGFR significantly attenuated the β2M-induced the activation of EGFR and pro-fibrotic responses. The present study suggests that β2M is a paracrine pro-fibrotic mediator and associated with cardiac dysfunction in response to pressure overload.