Chemotherapy-induced peripheral neurotoxicity (CIPN) is a severe dose-limiting adverse event of chemotherapy. Presently, the mechanism underlying the induction of CIPN remains unclear, and no effective treatment is available. In this study, through metabolomics analyses, we found that nab-paclitaxel therapy markedly increased serum serotonin [5-hydroxtryptamine (5-HT)] levels in both cancer patients and mice compared to the respective controls. Furthermore, nab-paclitaxel-treated enterochromaffin (EC) cells showed increased 5-HT synthesis, and serotonin-treated Schwann cells showed damage, as indicated by the activation of CREB3L3/MMP3/FAS signaling. Venlafaxine, an inhibitor of serotonin and norepinephrine reuptake, was found to protect against nerve injury by suppressing the activation of CREB3L3/MMP3/FAS signaling in Schwann cells. Remarkably, venlafaxine was found to significantly alleviate nab-paclitaxel-induced CIPN in patients without affecting the clinical efficacy of chemotherapy. In summary, our study reveals that EC cell-derived 5-HT plays a critical role in nab-paclitaxel-related neurotoxic lesions, and venlafaxine co-administration represents a novel approach to treating chronic cumulative neurotoxicity commonly reported in nab-paclitaxel-based chemotherapy.
Paclitaxel/toxicity* ; Animals ; Albumins/adverse effects* ; Serotonin/metabolism* ; Mice ; Humans ; Male ; Female ; Venlafaxine Hydrochloride/therapeutic use* ; Neurotoxicity Syndromes/metabolism* ; Middle Aged ; Schwann Cells/metabolism* ; Peripheral Nervous System Diseases/drug therapy* ; Antineoplastic Agents

Objective:To characterize fine motor function in middle-aged and elderly individuals utilizing a novel wearable inertial motion capture device.Additionally, it seeks to investigate the relationship between fine motor deficits and overall cognitive function, as well as various cognitive dimensions.Methods:Participants aged 50 years and older were recruited between November 2022 and April 2023.The Montreal Cognitive Assessment Scale(MoCA)was employed to evaluate the cognitive function of the subjects, and a radar chart was utilized to illustrate the extent of impairment across different cognitive dimensions.An independent computerized fine motor evaluation system was developed using the motion capture technology of a novel wearable microelectromechanical system(MEMS)inertial sensor, enabling a quantitative assessment of fine motor skills.The differences in fine motor function characteristics between the two groups were compared.Spearman's correlation analysis and multivariate logistic regression were conducted to examine the relationship between fine motor deficits and cognitive dysfunction.Results:A total of 289 participants were recruited, among whom 140(48.4%)were classified into the cognitive impairment group.The mean MoCA scores for the cognitive impairment group and the non-cognitive impairment group were 22.2 ± 2.79 and 27.7 ± 1.19, respectively( P<0.001).The electronic assessment of fine motor function revealed that the motion parameters of hand function in the cognitive impairment group were significantly poorer across all three numerical evaluation tasks.Spearman's correlation analysis demonstrated a robust correlation between deficits in fine motor function and cognitive dysfunction.Furthermore, in the multiple logistic regression model, after adjusting for potential confounding factors including age, gender, and education level, a significant association between cognitive dysfunction and fine motor dysfunction persisted. Conclusions:A novel wearable motion capture technology was employed to facilitate the digital assessment of fine motor function.The findings revealed a significant correlation between deficits in fine motor function and cognitive dysfunction among middle-aged and elderly populations.

Objective To investigate the cognition level and behavior compliance of blood pressure measurement in community residents and analyze the related influencing factors, and to provide evidence for community health management and blood pressure control. Methods A questionnaire survey was conducted to investigate 4470 community patients. Questionnaires included basic personal information，blood pressure measurement cognition, and blood pressure measurement behavior related issues. SPSS 19.0 was used to analyze the basic information, blood pressure measurement cognition, and pressure measurement behavior of the survey subjects. Logistic regression was performed to analyze relevant factors affecting blood pressure measurement cognition and behavior compliance. Results The overall cognitive compliance rate for blood pressure measurement among the visiting community patients was 31.52%. Age, education level, and chronic disease had a statistically significant impact on the cognitive knowledge (P<0.05). The overall behavior compliance rate of blood pressure measurement among the community patients was 23.69%. The cognition, age and education had a statistically significant impact on the overall behavior compliance rate of blood pressure measurement (P<0.05). Conclusion The cognitive level and standardized behavior of blood pressure measurement of community patients need to be improved. More attention should be paid to the elderly, low education level residents and community residents without chronic diseases, to promote community residents to form correct and standardized behavior of blood pressure measurement through health education.

Objective To explore the characteristics of fine motor deficits in the elderly individuals with MCI due to AD through a new wearable inertial motion capture device,and then construct a prediction model for MCI.Methods A total of 260 elderly subjects were recruited in community from November,2022 to April,2023,and based on diagnosis,they were divided into a MCI group(134 cases)and a control group(126 cases).A new wearable inertial motion capture device,which was self-designed and developed based on MEMS inertial sensor,was used to capture the fine mo-tor movements of the hands,and the obtained data were analyzed with a computerized assessment system to make the quantitative evaluation of fine motor.LASSO learning algorithm and logistic regression analysis were employed to identify the predictive factors for MCI,and then a nomo-gram was constructed based on these factors.ROC curve was plotted to evaluate the predictive ability of the model by calculating its AUC value.DC A,CIC,and Bootstrap method were applied to evaluate and validate the clinical utility and stability of the model.Results The total score of MoCA(22.18±2.84 vs 27.60±1.10)and scores of the dimensions were significantly lower in the MCI group than the control group(all P＜0.01).In the five digital assessment tasks,the MCI group showed obviously poorer fine motor performance of both hands than the control group(P＜0.05,P＜0.01).ROC curve analysis showed that the AUC value of our nomogram model in predicting MCI was 0.762(95％CI:0.705-0.819).DCA,CIC,and Bootstrap methods demonstra-ted good and relatively stable discrimination,calibration,and clinical applicability of the model.Conclusion MEMS inertial sensor motion capture technology can make digital evaluation of fine motor.For the elderly,fine motor deficits are significantly associated with risk for MCI.Our no-mogram model based on fine motion parameters shows good predictive efficacy in assessing the risk of MCI.

Objective To explore the characteristics of fine motor deficits in the elderly individuals with MCI due to AD through a new wearable inertial motion capture device,and then construct a prediction model for MCI.Methods A total of 260 elderly subjects were recruited in community from November,2022 to April,2023,and based on diagnosis,they were divided into a MCI group(134 cases)and a control group(126 cases).A new wearable inertial motion capture device,which was self-designed and developed based on MEMS inertial sensor,was used to capture the fine mo-tor movements of the hands,and the obtained data were analyzed with a computerized assessment system to make the quantitative evaluation of fine motor.LASSO learning algorithm and logistic regression analysis were employed to identify the predictive factors for MCI,and then a nomo-gram was constructed based on these factors.ROC curve was plotted to evaluate the predictive ability of the model by calculating its AUC value.DC A,CIC,and Bootstrap method were applied to evaluate and validate the clinical utility and stability of the model.Results The total score of MoCA(22.18±2.84 vs 27.60±1.10)and scores of the dimensions were significantly lower in the MCI group than the control group(all P＜0.01).In the five digital assessment tasks,the MCI group showed obviously poorer fine motor performance of both hands than the control group(P＜0.05,P＜0.01).ROC curve analysis showed that the AUC value of our nomogram model in predicting MCI was 0.762(95％CI:0.705-0.819).DCA,CIC,and Bootstrap methods demonstra-ted good and relatively stable discrimination,calibration,and clinical applicability of the model.Conclusion MEMS inertial sensor motion capture technology can make digital evaluation of fine motor.For the elderly,fine motor deficits are significantly associated with risk for MCI.Our no-mogram model based on fine motion parameters shows good predictive efficacy in assessing the risk of MCI.

Objective:To characterize fine motor function in middle-aged and elderly individuals utilizing a novel wearable inertial motion capture device.Additionally, it seeks to investigate the relationship between fine motor deficits and overall cognitive function, as well as various cognitive dimensions.Methods:Participants aged 50 years and older were recruited between November 2022 and April 2023.The Montreal Cognitive Assessment Scale(MoCA)was employed to evaluate the cognitive function of the subjects, and a radar chart was utilized to illustrate the extent of impairment across different cognitive dimensions.An independent computerized fine motor evaluation system was developed using the motion capture technology of a novel wearable microelectromechanical system(MEMS)inertial sensor, enabling a quantitative assessment of fine motor skills.The differences in fine motor function characteristics between the two groups were compared.Spearman's correlation analysis and multivariate logistic regression were conducted to examine the relationship between fine motor deficits and cognitive dysfunction.Results:A total of 289 participants were recruited, among whom 140(48.4%)were classified into the cognitive impairment group.The mean MoCA scores for the cognitive impairment group and the non-cognitive impairment group were 22.2 ± 2.79 and 27.7 ± 1.19, respectively( P<0.001).The electronic assessment of fine motor function revealed that the motion parameters of hand function in the cognitive impairment group were significantly poorer across all three numerical evaluation tasks.Spearman's correlation analysis demonstrated a robust correlation between deficits in fine motor function and cognitive dysfunction.Furthermore, in the multiple logistic regression model, after adjusting for potential confounding factors including age, gender, and education level, a significant association between cognitive dysfunction and fine motor dysfunction persisted. Conclusions:A novel wearable motion capture technology was employed to facilitate the digital assessment of fine motor function.The findings revealed a significant correlation between deficits in fine motor function and cognitive dysfunction among middle-aged and elderly populations.

Cognitive impairment is a progressive disorder, it is important to early detect the risk and identify the disease to control its progression and reduce the burden of society. In recent years, the rapidly developing digital biomarkers of cognitive impairment have been used to compensate for the shortcomings of traditional cognitive assessment. This article reviews the research progress of digital biomarkers in the early identification of cognitive impairment for the elderly and to provide reference for improving diagnosis and treatment of this disorder.

Mild cognitive impairment(MCI)has a high prevalence and may progress to dementia.MCI is considered a key stage in the prevention of dementia, but the number of early identification methods is limited.Fine motor function of the hand and cognitive function both decline with age.Therefore, analyzing the correlation between cognitive dysfunction and fine motor function of the hand and exploring whether fine motor dysfunction of the hand can be used as a sensitive screening method for MCI may have important significance for early detection of MCI.At the same time, electronic devices are increasingly used for the evaluation of hand function and may be a promising option to be used for the assessment of fine motor function of the hand in patients with MCI.

With the acceleration of aging process and the increase of average life in China, the number of disabled elderly in China is also growing rapidly, which undoubtedly brings a heavy care burden and pressure to families and society.Facing the great challenges brought by aging, the increasing evidences show that only by reducing the incidence of disease and disability from the source, improving the health level of the elderly, prolonging their healthy life and realizing healthy aging, we can fundamentally alleviate the great pressure brought by the aging society.The concept of motor function maintenance and health promotion of the elderly has become an important link and breakthrough to realize healthy aging and active health.Facing the requirements of active health medicine and the development trend of science and technology in the future, it is imperative to deeply study the motion characteristics and function maintenance of the elderly, and promote the development of sports medicine with innovative technologies such as internet, big data and artificial intelligence.In the future, we will continue to improve the assessment and maintenance system for motor function of the elderly, develop and optimize functional maintenance products that meet the exercise needs of the elderly, and actively build an elderly-friendly sports environment support system, thereby promoting the healthy China strategy and realize healthy aging to the greatest extent.

[摘 要] 目的：体内外实验探讨木鳖子单体化合物对羟基桂皮醛[Momordica cochinchinensis(Lour.)Spreng.p-hydroxycinnamaldehyde，CMSP]对小鼠黑色素瘤移植瘤生长和转移的影响及其作用机制。方法：建立荷瘤小鼠动物模型，并将18只C57BL/6小鼠随机分成3组（每组6只）：对照组（腹腔注射0.1 ml生理盐水）、CMSP治疗组（分别腹腔注射0.1 ml 1、2 mg/ml CMSP），给药的第5天开始，每次给药前用卡尺分别测量和计算小鼠移植瘤的体积，实验结束后称量移植瘤的质量；H-E染色后光镜观察肝组织的病理学变化；免疫组织化学SP法观察移植瘤组织E-cadherin和vimentin蛋白的表达。采用细胞划痕和Transwell实验分别检测CMSP实验组（10、20 µg/ml）黑色素瘤B16细胞24、48 h的迁移能力，qPCR法检测CMSP处理24 h后B16细胞EMT相关mRNA表达，WB法检测CMSP处理B16细胞48 h后β-catenin、p-β-catenin（Ser675）、vimentin和E-cadherin蛋白的表达水平。结果：CMSP治疗组小鼠移植瘤平均体积和肿瘤质量明显降低（均P<0.05）；对照组小鼠肝脏中转移灶的数量明显多于CMSP（1、2 mg/kg）治疗组（均P<0.05），CMSP（2 mg/kg）处理组小鼠的肝组织内未发现明显转移灶。CMSP治疗组（1、2 mg/kg）移植瘤组织中E-cadherin蛋白表达水平明显高于对照组（均P<0.05），而vimentin蛋白表达显著低于对照组（均P<0.01）。体外实验中，CMSP实验组（10、20 μg/ml）B16细胞24、48 h后划痕愈合率较对照组均明显降低（均P<0.05）。20 μg/ml CMSP处理B16细胞24、48 h后穿过Transwell小室的细胞数较对照组则显著下降（均P<0.01）。CMSP（10、20 μg/ml）处理B16细胞后β-catenin mRNA表达水平较对照组明显降低（均P<0.01），E-cadherin mRNA表达水平则明显升高（均P<0.05），而vimentin mRNA表达水平在10 μg/ml处理组与对照组相比差异无统计学意义（P>0.05），20 μg/ml处理组则明显降低（P<0.01）。与对照组相比，CMSP实验组（10、20 μg/ml）处理B16细胞后β-catenin、p-β-catenin和vimentin蛋白表达均显著降低（均P<0.01），而E-cadherin蛋白表达则明显升高（均P<0.01）。结论：CMSP能够抑制小鼠黑色素瘤移植瘤的生长和转移，其作用机制可能与抑制wnt/β-catenin通路的活性相关。