PeerJ:Geriatricshttps://peerj.com/articles/index.atom?journal=peerj&subject=4700Geriatrics articles published in PeerJGut microbiota and its metabolites in Alzheimer’s disease: from pathogenesis to treatmenthttps://peerj.com/articles/170612024-03-132024-03-13Xinfu ZouGuoqiang ZouXinyan ZouKangfeng WangZetao Chen
Introduction
An increasing number of studies have demonstrated that altered microbial diversity and function (such as metabolites), or ecological disorders, regulate bowel–brain axis involvement in the pathophysiologic processes in Alzheimer’s disease (AD). The dysregulation of microbes and their metabolites can be a double-edged sword in AD, presenting the possibility of microbiome-based treatment options. This review describes the link between ecological imbalances and AD, the interactions between AD treatment modalities and the microbiota, and the potential of interventions such as prebiotics, probiotics, synbiotics, fecal microbiota transplantation, and dietary interventions as complementary therapeutic strategies targeting AD pathogenesis and progression.
Survey methodology
Articles from PubMed and china.com on intestinal flora and AD were summarized to analyze the data and conclusions carefully to ensure the comprehensiveness, completeness, and accuracy of this review.
Conclusions
Regulating the gut flora ecological balance upregulates neurotrophic factor expression, regulates the microbiota-gut-brain (MGB) axis, and suppresses the inflammatory responses. Based on emerging research, this review explored novel directions for future AD research and clinical interventions, injecting new vitality into microbiota research development.
Introduction
An increasing number of studies have demonstrated that altered microbial diversity and function (such as metabolites), or ecological disorders, regulate bowel–brain axis involvement in the pathophysiologic processes in Alzheimer’s disease (AD). The dysregulation of microbes and their metabolites can be a double-edged sword in AD, presenting the possibility of microbiome-based treatment options. This review describes the link between ecological imbalances and AD, the interactions between AD treatment modalities and the microbiota, and the potential of interventions such as prebiotics, probiotics, synbiotics, fecal microbiota transplantation, and dietary interventions as complementary therapeutic strategies targeting AD pathogenesis and progression.
Survey methodology
Articles from PubMed and china.com on intestinal flora and AD were summarized to analyze the data and conclusions carefully to ensure the comprehensiveness, completeness, and accuracy of this review.
Conclusions
Regulating the gut flora ecological balance upregulates neurotrophic factor expression, regulates the microbiota-gut-brain (MGB) axis, and suppresses the inflammatory responses. Based on emerging research, this review explored novel directions for future AD research and clinical interventions, injecting new vitality into microbiota research development.Neck circumference is a highly reliable anthropometric measure in older adults requiring long-term carehttps://peerj.com/articles/168162024-01-312024-01-31Ryo SatoYohei SawayaMasahiro IshizakaLu YinTakahiro ShibaTamaki HiroseTomohiko Urano
The reliability of neck circumference measurement as an assessment tool for older adults requiring long-term care remains unknown. This study aimed to evaluate the reliability of neck circumference measurement in older adults requiring long-term care, and the effect of edema on measurement error. Two physical therapists measured the neck circumference. Intraclass correlation coefficient (ICC) and Bland–Altman analyses were performed to examine the reliability of neck circumference measurement. Correlation analysis was used to evaluate the relationship between edema values (extracellular water/total body water) and neck circumference measurement difference. For inter-rater reliability of neck circumference measurement, the overall ICC (2,1) was 0.98. The upper and lower limits of the difference between examiners ranged from −0.9 to 1.2 cm. There was no association between edema values and neck circumference measurement error. Thus, measurement of the neck circumference in older adults requiring long-term care is a reliable assessment tool, with a low error rate, even in older adults with edema.
The reliability of neck circumference measurement as an assessment tool for older adults requiring long-term care remains unknown. This study aimed to evaluate the reliability of neck circumference measurement in older adults requiring long-term care, and the effect of edema on measurement error. Two physical therapists measured the neck circumference. Intraclass correlation coefficient (ICC) and Bland–Altman analyses were performed to examine the reliability of neck circumference measurement. Correlation analysis was used to evaluate the relationship between edema values (extracellular water/total body water) and neck circumference measurement difference. For inter-rater reliability of neck circumference measurement, the overall ICC (2,1) was 0.98. The upper and lower limits of the difference between examiners ranged from −0.9 to 1.2 cm. There was no association between edema values and neck circumference measurement error. Thus, measurement of the neck circumference in older adults requiring long-term care is a reliable assessment tool, with a low error rate, even in older adults with edema.Establishment and validation of a heart failure risk prediction model for elderly patients after coronary rotational atherectomy based on machine learninghttps://peerj.com/articles/168672024-01-312024-01-31Lixiang ZhangXiaojuan ZhouJiaoyu Cao
Objective
To develop and validate a heart failure risk prediction model for elderly patients after coronary rotational atherectomy based on machine learning methods.
Methods
A retrospective cohort study was conducted to select 303 elderly patients with severe coronary calcification as the study subjects. According to the occurrence of postoperative heart failure, the study subjects were divided into the heart failure group (n = 53) and the non-heart failure group (n = 250). Retrospective collection of clinical data from the study subjects during hospitalization. After processing the missing values in the original data and addressing sample imbalance using Adaptive Synthetic Sampling (ADASYN) method, the final dataset consists of 502 samples: 250 negative samples (i.e., patients not suffering from heart failure) and 252 positive samples (i.e., patients with heart failure). According to a 7:3 ratio, the datasets of 502 patients were randomly divided into a training set (n = 351) and a validation set (n = 151). On the training set, logistic regression (LR), extreme gradient boosting (XGBoost), support vector machine (SVM), and lightweight gradient boosting machine (LightGBM) algorithms were used to construct heart failure risk prediction models; Evaluate model performance on the validation set by calculating the area under the receiver operating characteristic curve (ROC) curve (AUC), sensitivity, specificity, positive predictive value, negative predictive value, F1-score, and prediction accuracy.
Result
A total of 17.49% of 303 patients occured postoperative heart failure. The AUC of LR, XGBoost, SVM, and LightGBM models in the training set were 0.872, 1.000, 0.699, and 1.000, respectively. After 10 fold cross validation, the AUC was 0.863, 0.972, 0.696, and 0.963 in the training set, respectively. Among them, XGBoost had the highest AUC and better predictive performance, while SVM models had the worst performance. The XGBoost model also showed good predictive performance in the validation set (AUC = 0.972, 95% CI [0.951–0.994]). The Shapley additive explanation (SHAP) method suggested that the six characteristic variables of blood cholesterol, serum creatinine, fasting blood glucose, age, triglyceride and NT-proBNP were important positive factors for the occurrence of heart failure, and LVEF was important negative factors for the occurrence of heart failure.
Conclusion
The seven characteristic variables of blood cholesterol, blood creatinine, fasting blood glucose, NT-proBNP, age, triglyceride and LVEF are all important factors affecting the occurrence of heart failure. The prediction model of heart failure risk for elderly patients after CRA based on the XGBoost algorithm is superior to SVM, LightGBM and the traditional LR model. This model could be used to assist clinical decision-making and improve the adverse outcomes of patients after CRA.
Objective
To develop and validate a heart failure risk prediction model for elderly patients after coronary rotational atherectomy based on machine learning methods.
Methods
A retrospective cohort study was conducted to select 303 elderly patients with severe coronary calcification as the study subjects. According to the occurrence of postoperative heart failure, the study subjects were divided into the heart failure group (n = 53) and the non-heart failure group (n = 250). Retrospective collection of clinical data from the study subjects during hospitalization. After processing the missing values in the original data and addressing sample imbalance using Adaptive Synthetic Sampling (ADASYN) method, the final dataset consists of 502 samples: 250 negative samples (i.e., patients not suffering from heart failure) and 252 positive samples (i.e., patients with heart failure). According to a 7:3 ratio, the datasets of 502 patients were randomly divided into a training set (n = 351) and a validation set (n = 151). On the training set, logistic regression (LR), extreme gradient boosting (XGBoost), support vector machine (SVM), and lightweight gradient boosting machine (LightGBM) algorithms were used to construct heart failure risk prediction models; Evaluate model performance on the validation set by calculating the area under the receiver operating characteristic curve (ROC) curve (AUC), sensitivity, specificity, positive predictive value, negative predictive value, F1-score, and prediction accuracy.
Result
A total of 17.49% of 303 patients occured postoperative heart failure. The AUC of LR, XGBoost, SVM, and LightGBM models in the training set were 0.872, 1.000, 0.699, and 1.000, respectively. After 10 fold cross validation, the AUC was 0.863, 0.972, 0.696, and 0.963 in the training set, respectively. Among them, XGBoost had the highest AUC and better predictive performance, while SVM models had the worst performance. The XGBoost model also showed good predictive performance in the validation set (AUC = 0.972, 95% CI [0.951–0.994]). The Shapley additive explanation (SHAP) method suggested that the six characteristic variables of blood cholesterol, serum creatinine, fasting blood glucose, age, triglyceride and NT-proBNP were important positive factors for the occurrence of heart failure, and LVEF was important negative factors for the occurrence of heart failure.
Conclusion
The seven characteristic variables of blood cholesterol, blood creatinine, fasting blood glucose, NT-proBNP, age, triglyceride and LVEF are all important factors affecting the occurrence of heart failure. The prediction model of heart failure risk for elderly patients after CRA based on the XGBoost algorithm is superior to SVM, LightGBM and the traditional LR model. This model could be used to assist clinical decision-making and improve the adverse outcomes of patients after CRA.Fall risk prediction ability in rehabilitation professionals: structural equation modeling using time pressure test data for Kiken-Yochi Traininghttps://peerj.com/articles/167242024-01-032024-01-03Ryohei KishitaHideki MiyaguchiTomoko OhuraKatsuhiko ArihisaWataru MatsushitaChinami Ishizuki
Background
Falls occur frequently during rehabilitation for people with disabilities. Fall risk prediction ability (FRPA) is necessary to prevent falls and provide safe, high-quality programs. In Japan, Kiken Yochi Training (KYT) has been introduced to provide training to improve this ability. Time Pressure-KYT (TP-KYT) is an FRPA measurement specific to fall risks faced by rehabilitation professionals. However, it is unclear which FRPA factors are measured by the TP-KYT; as this score reflects clinical experience, a model can be hypothesized where differences between rehabilitation professionals (licensed) and students (not licensed) can be measured by this tool.
Aims
To identify the FRPA factors included in the TP-KYT and verify the FRPA factor model based the participants’ license status.
Methods
A total of 402 participants, with 184 rehabilitation professionals (physical and occupational therapists) working in 12 medical facilities and three nursing homes, and 218 rehabilitation students (physical and occupational therapy students) from two schools participated in this study. Participant characteristics (age, gender, job role, and years of experience and education) and TP-KYT scores were collected. The 24 TP-KYT items were qualitatively analyzed using an inductive approach based on content, and FRPA factors were extracted. Next, the correction score (acquisition score/full score: 0–1) was calculated for each extracted factor, and an observation variable for the job role (rehabilitation professional = 1, rehabilitation student = 0) was set. To verify the FRPA factors associated with having or not having a rehabilitation professional license, FRPA as a latent variable and the correction score of factors as an observed variable were set, and structural equation modeling was performed by drawing a path from the job role to FRPA.
Results
The results of the qualitative analysis aggregated patient ability (PA), physical environment (PE), and human environment (HE) as factors. The standardized coefficients of the model for participants with or without a rehabilitation professional license and FRPA were 0.85 (p < 0.001) for FRPA from job role, 0.58 for PA, 0.64 for PE, and 0.46 for HE from FRPA to each factor (p < 0.001). The model showed a good fit, with root mean square error of approximation < 0.001, goodness of fit index (GFI) = 0.998, and adjusted GFI = 0.990.
Conclusion
Of the three factors, PA and PE were common components of clinical practice guidelines for fall risk assessment, while HE was a distinctive component. The model’s goodness of fit, which comprised three FRPA factors based on whether participants did or did not have rehabilitation professional licenses, was good. The system suggested that rehabilitation professionals had a higher FRPA than students, comprising three factors. To provide safe and high-quality rehabilitation for patients, professional training to increase FRPA should incorporate the three factors into program content.
Background
Falls occur frequently during rehabilitation for people with disabilities. Fall risk prediction ability (FRPA) is necessary to prevent falls and provide safe, high-quality programs. In Japan, Kiken Yochi Training (KYT) has been introduced to provide training to improve this ability. Time Pressure-KYT (TP-KYT) is an FRPA measurement specific to fall risks faced by rehabilitation professionals. However, it is unclear which FRPA factors are measured by the TP-KYT; as this score reflects clinical experience, a model can be hypothesized where differences between rehabilitation professionals (licensed) and students (not licensed) can be measured by this tool.
Aims
To identify the FRPA factors included in the TP-KYT and verify the FRPA factor model based the participants’ license status.
Methods
A total of 402 participants, with 184 rehabilitation professionals (physical and occupational therapists) working in 12 medical facilities and three nursing homes, and 218 rehabilitation students (physical and occupational therapy students) from two schools participated in this study. Participant characteristics (age, gender, job role, and years of experience and education) and TP-KYT scores were collected. The 24 TP-KYT items were qualitatively analyzed using an inductive approach based on content, and FRPA factors were extracted. Next, the correction score (acquisition score/full score: 0–1) was calculated for each extracted factor, and an observation variable for the job role (rehabilitation professional = 1, rehabilitation student = 0) was set. To verify the FRPA factors associated with having or not having a rehabilitation professional license, FRPA as a latent variable and the correction score of factors as an observed variable were set, and structural equation modeling was performed by drawing a path from the job role to FRPA.
Results
The results of the qualitative analysis aggregated patient ability (PA), physical environment (PE), and human environment (HE) as factors. The standardized coefficients of the model for participants with or without a rehabilitation professional license and FRPA were 0.85 (p < 0.001) for FRPA from job role, 0.58 for PA, 0.64 for PE, and 0.46 for HE from FRPA to each factor (p < 0.001). The model showed a good fit, with root mean square error of approximation < 0.001, goodness of fit index (GFI) = 0.998, and adjusted GFI = 0.990.
Conclusion
Of the three factors, PA and PE were common components of clinical practice guidelines for fall risk assessment, while HE was a distinctive component. The model’s goodness of fit, which comprised three FRPA factors based on whether participants did or did not have rehabilitation professional licenses, was good. The system suggested that rehabilitation professionals had a higher FRPA than students, comprising three factors. To provide safe and high-quality rehabilitation for patients, professional training to increase FRPA should incorporate the three factors into program content.Relationship between walking speed, respiratory muscle strength, and dynamic balance in community-dwelling older people who required long-term care or support and used a daycare centerhttps://peerj.com/articles/166302023-12-212023-12-21Takumi JiroumaruYutaro HyodoMichio WachiNobuko ShichiriJunko OchiTakamitsu Fujikawa
Background
Focusing on the relationship between frail older people and gait speed is vital to minimize the need for long-term care or increased support. The relationship between gait speed, respiratory muscle strength, and dynamic balance, is not well understood in older people requiring long-term care or support. Therefore, this study aimed to provide new insights into the relationship between gait speed, respiratory muscle strength, and dynamic balance in community-dwelling older people who required long-term care or support and used a daycare center.
Methods
This was a cross-sectional study of 49 community-dwelling older people (21 men, 28 women) aged ≥65 years who were certified as requiring long-term care or support under the Japanese system. The participants’ maximal inspiratory pressure (PImax), maximal expiratory pressure (PEmax), walking speed (maximal and normal walking speed), and maximal double-step length test (MDST) results were recorded. The measurement data were evaluated using Pearson’s correlation coefficient and multiple regression analysis.
Results
Pearson’s correlation coefficient revealed correlations between PImax and the following: maximal walking speed (r = 0.606, p < 0.001), normal walking speed (r = 0.487, p < 0.001), and MDST (r = 0.435, p = 0.002). Correlations were also observed between PEmax and the following: maximal walking speed (r = 0.522, p < 0.001), normal walking speed (r = 0.467, p < 0.001), and MDST (r = 0.314, p = 0.028). Moreover, a correlation was found between MDST and both maximal walking speed and (r = 0.684, p < 0.001) and normal walking speed (r = 0.649, p < 0.001). The effect size was 0.379. Multiple regression analysis using a forced entry method with maximal walking speed as the dependent variable showed that maximal walking speed was significantly associated with MDST (p < 0.001) and PEmax (p = 0.036), with an effect size of 0.272. The model’s adjusted coefficient of determination was 0.593 (p < 0.001). Multiple regression analysis using a forced entry method with normal walking speed as the dependent variable showed that normal walking speed was significantly associated with MDST (p < 0.001) and PEmax (p = 0.021), with an effect size of 0.272. The model’s adjusted coefficient of determination was 0.497 (p < 0.001). Multiple regression analysis using a forced entry method with MDST as the dependent variable showed that MDST was significantly associated with PImax (p < 0.025), with an effect size of 0.243. The model’s adjusted coefficient of determination was 0.148 (p = 0.017).
Conclusions
Respiratory muscle strength and dynamic balance were related to walking speed in older people requiring long-term care or support.
Background
Focusing on the relationship between frail older people and gait speed is vital to minimize the need for long-term care or increased support. The relationship between gait speed, respiratory muscle strength, and dynamic balance, is not well understood in older people requiring long-term care or support. Therefore, this study aimed to provide new insights into the relationship between gait speed, respiratory muscle strength, and dynamic balance in community-dwelling older people who required long-term care or support and used a daycare center.
Methods
This was a cross-sectional study of 49 community-dwelling older people (21 men, 28 women) aged ≥65 years who were certified as requiring long-term care or support under the Japanese system. The participants’ maximal inspiratory pressure (PImax), maximal expiratory pressure (PEmax), walking speed (maximal and normal walking speed), and maximal double-step length test (MDST) results were recorded. The measurement data were evaluated using Pearson’s correlation coefficient and multiple regression analysis.
Results
Pearson’s correlation coefficient revealed correlations between PImax and the following: maximal walking speed (r = 0.606, p < 0.001), normal walking speed (r = 0.487, p < 0.001), and MDST (r = 0.435, p = 0.002). Correlations were also observed between PEmax and the following: maximal walking speed (r = 0.522, p < 0.001), normal walking speed (r = 0.467, p < 0.001), and MDST (r = 0.314, p = 0.028). Moreover, a correlation was found between MDST and both maximal walking speed and (r = 0.684, p < 0.001) and normal walking speed (r = 0.649, p < 0.001). The effect size was 0.379. Multiple regression analysis using a forced entry method with maximal walking speed as the dependent variable showed that maximal walking speed was significantly associated with MDST (p < 0.001) and PEmax (p = 0.036), with an effect size of 0.272. The model’s adjusted coefficient of determination was 0.593 (p < 0.001). Multiple regression analysis using a forced entry method with normal walking speed as the dependent variable showed that normal walking speed was significantly associated with MDST (p < 0.001) and PEmax (p = 0.021), with an effect size of 0.272. The model’s adjusted coefficient of determination was 0.497 (p < 0.001). Multiple regression analysis using a forced entry method with MDST as the dependent variable showed that MDST was significantly associated with PImax (p < 0.025), with an effect size of 0.243. The model’s adjusted coefficient of determination was 0.148 (p = 0.017).
Conclusions
Respiratory muscle strength and dynamic balance were related to walking speed in older people requiring long-term care or support.Multi-modal sleep intervention for community-dwelling people living with dementia and primary caregiver dyads with sleep disturbance: protocol of a single-arm feasibility trialhttps://peerj.com/articles/165432023-12-142023-12-14Sumedha VermaPrerna VarmaAimee BrownBei BeiRosemary GibsonTom ValentaAnn PietschMarina CavuotoMichael WoodwardSusan McCurryMelinda L. Jackson
Background
Disturbed sleep is common among people living with dementia and their informal caregivers, and is associated with negative health outcomes. Dyadic, multi-modal interventions targeting caregiver and care-recipient sleep have been recommended yet remain limited. This protocol details the development of a single-arm feasibility trial of a multi-modal, therapist-led, six-week intervention targeting sleep disturbance in dyads of people living with dementia and their primary caregiver.
Methods
We aim to recruit 24 co-residing, community-dwelling dyads of people living with dementia and their primary informal caregiver (n = 48) with sleep concerns (Pittsburgh Sleep Quality Index ≥5 for caregivers, and caregiver-endorsed sleep concerns for the person living with dementia). People who live in residential care settings, are employed in night shift work, or are diagnosed with current, severe mental health conditions or narcolepsy, will be excluded. Participants will wear an actigraph and complete sleep diaries for two weeks prior, and during the last two weeks, of active intervention. The intervention is therapist-led and includes a mix of weekly small group video sessions and personalised, dyadic sessions (up to 90 min each) over six weeks. Sessions are supported by a 37-page workbook offering strategies and spaces for reflections/notes. Primary feasibility outcomes are caregiver: session attendance, attrition, and self-reported project satisfaction. Secondary outcomes include dyadic self-reported and objectively-assessed sleep, depression and anxiety symptoms, quality of life, and social support. Self-report outcomes will be assessed at pre- and post-intervention.
Discussion
If feasible, this intervention could be tested in a larger randomised controlled trial to investigate its efficacy, and, upon further testing, may potentially represent a non-pharmacological approach to reduce sleep disturbance among people living with dementia and their caregivers.
ANZCTR Trial registration
ACTRN12622000144718: https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=382960&showOriginal=true&isReview=true
Background
Disturbed sleep is common among people living with dementia and their informal caregivers, and is associated with negative health outcomes. Dyadic, multi-modal interventions targeting caregiver and care-recipient sleep have been recommended yet remain limited. This protocol details the development of a single-arm feasibility trial of a multi-modal, therapist-led, six-week intervention targeting sleep disturbance in dyads of people living with dementia and their primary caregiver.
Methods
We aim to recruit 24 co-residing, community-dwelling dyads of people living with dementia and their primary informal caregiver (n = 48) with sleep concerns (Pittsburgh Sleep Quality Index ≥5 for caregivers, and caregiver-endorsed sleep concerns for the person living with dementia). People who live in residential care settings, are employed in night shift work, or are diagnosed with current, severe mental health conditions or narcolepsy, will be excluded. Participants will wear an actigraph and complete sleep diaries for two weeks prior, and during the last two weeks, of active intervention. The intervention is therapist-led and includes a mix of weekly small group video sessions and personalised, dyadic sessions (up to 90 min each) over six weeks. Sessions are supported by a 37-page workbook offering strategies and spaces for reflections/notes. Primary feasibility outcomes are caregiver: session attendance, attrition, and self-reported project satisfaction. Secondary outcomes include dyadic self-reported and objectively-assessed sleep, depression and anxiety symptoms, quality of life, and social support. Self-report outcomes will be assessed at pre- and post-intervention.
Discussion
If feasible, this intervention could be tested in a larger randomised controlled trial to investigate its efficacy, and, upon further testing, may potentially represent a non-pharmacological approach to reduce sleep disturbance among people living with dementia and their caregivers.
ANZCTR Trial registration
ACTRN12622000144718: https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=382960&showOriginal=true&isReview=true
Involvement of plasminogen activator inhibitor-1 in p300/p53-mediated age-related atrial fibrosishttps://peerj.com/articles/165452023-12-122023-12-12Yingyu LaiJintao HeXiaoyan GaoDewei PengHuishan ZhouYuwen XuXueshan LuoHui YangMengzhen ZhangChunyu DengShulin WuYumei XueFeng ZhouFang Rao
Plasminogen activator inhibitor-1 (PAI-1), a key regulator of the fibrinolytic system, is also intimately involved in the fibrosis. Although PAI-1 may be involved in the occurrence of atrial fibrillation (AF) and thrombosis in the elderly, but whether it participated in aging-related atrial fibrosis and the detailed mechanism is still unclear. We compared the transcriptomics data of young (passage 4) versus senescent (passage 14) human atrial fibroblasts and found that PAI-1 was closely related to aging-related fibrosis. Aged mice and senescent human and mouse atrial fibroblasts underwent electrophysiological and biochemical studies. We found that p300, p53, and PAI-1 protein expressions were increased in the atrial tissue of aged mice and senescent human and mouse atrial fibroblasts. Curcumin or C646 (p300 inhibitor), or p300 knockdown inhibited the expression of PAI-1 contributing to reduced atrial fibroblasts senescence, atrial fibrosis, and the AF inducibility. Furthermore, p53 knockdown decreased the protein expression of PAI-1 and p21 in senescent human and mouse atrial fibroblasts. Our results suggest that p300/p53/PAI-1 signaling pathway participates in the mechanism of atrial fibrosis induced by aging, which provides new sights into the treatment of elderly AF.
Plasminogen activator inhibitor-1 (PAI-1), a key regulator of the fibrinolytic system, is also intimately involved in the fibrosis. Although PAI-1 may be involved in the occurrence of atrial fibrillation (AF) and thrombosis in the elderly, but whether it participated in aging-related atrial fibrosis and the detailed mechanism is still unclear. We compared the transcriptomics data of young (passage 4) versus senescent (passage 14) human atrial fibroblasts and found that PAI-1 was closely related to aging-related fibrosis. Aged mice and senescent human and mouse atrial fibroblasts underwent electrophysiological and biochemical studies. We found that p300, p53, and PAI-1 protein expressions were increased in the atrial tissue of aged mice and senescent human and mouse atrial fibroblasts. Curcumin or C646 (p300 inhibitor), or p300 knockdown inhibited the expression of PAI-1 contributing to reduced atrial fibroblasts senescence, atrial fibrosis, and the AF inducibility. Furthermore, p53 knockdown decreased the protein expression of PAI-1 and p21 in senescent human and mouse atrial fibroblasts. Our results suggest that p300/p53/PAI-1 signaling pathway participates in the mechanism of atrial fibrosis induced by aging, which provides new sights into the treatment of elderly AF.Feasibility of using chest computed tomography (CT) imaging at the first lumbar vertebra (L1) level to assess skeletal muscle mass: a retrospective studyhttps://peerj.com/articles/166522023-12-112023-12-11Shaohua LiuXia HanJianjun LiXia XieYunkai YangWangyan JiangLi LiuZhelong Liu
Background
Skeletal muscle mass is an essential parameter for diagnosing sarcopenia. The gold standard for assessing skeletal muscle mass is using computed tomography (CT) to measure skeletal muscle area at the third lumbar vertebra (L3) level. This study aims to investigate whether skeletal muscle mass could be evaluated at the first lumbar vertebra (L1) level using images obtained from routine chest CT scans.
Methods
Skeletal muscle index (SMI, cm2/m2) and skeletal muscle density (SMD, HU) are commonly used to measure relative muscle mass and the degree of fat infiltration. This study used CT images at the L1 level to measure the skeletal muscle area (SMA, cm2) in 815 subjects from the health examination center. Linear regression analysis was used to explore the association between L1 and L3 measurements. The receiver operating characteristic (ROC) analysis was used to assess the predictive performance of L1 SMI for sarcopenia. The sex-specific cut-off values for low skeletal muscle mass in patients under the age of 60 were determined using the following formula: “mean − 1.28 × standard deviation.” A multivariate linear regression model was established.
Results
A significantly higher SMI at the L1 level was found in males than in females (43.88 ± 6.33 cm2/m2 vs 33.68 ± 5.03 cm2/m2; P < 0.001). There were strong correlations between measures at the L1 and L3 levels in both the total subject and sex-specific analyses. A negative association was found between age and L3 SMI in males (r = −0.231, P = 0.038). Both body mass index (BMI) and body surface area (BSA) were positively associated with L1 SMI in both males and females. A multivariate analysis was used to establish a prediction rule to predict SMI at the L3 level. The assessment of consistency and interchangeability between predicted and actual SMI at the L3 level yielded moderately good results. Considering the significant differences observed between male and female participants, the sex-specific cut-off values of the L1 SMI for defining low skeletal muscle mass were 36.52 cm2/m2 in males and 27.29 cm2/m2 in females.
Conclusions
Based on a population from central China, the correlated indicators obtained at the L1 level from routine chest CT scans may serve as effective surrogate markers for those at the L3 level in assessing overall skeletal muscle mass.
Background
Skeletal muscle mass is an essential parameter for diagnosing sarcopenia. The gold standard for assessing skeletal muscle mass is using computed tomography (CT) to measure skeletal muscle area at the third lumbar vertebra (L3) level. This study aims to investigate whether skeletal muscle mass could be evaluated at the first lumbar vertebra (L1) level using images obtained from routine chest CT scans.
Methods
Skeletal muscle index (SMI, cm2/m2) and skeletal muscle density (SMD, HU) are commonly used to measure relative muscle mass and the degree of fat infiltration. This study used CT images at the L1 level to measure the skeletal muscle area (SMA, cm2) in 815 subjects from the health examination center. Linear regression analysis was used to explore the association between L1 and L3 measurements. The receiver operating characteristic (ROC) analysis was used to assess the predictive performance of L1 SMI for sarcopenia. The sex-specific cut-off values for low skeletal muscle mass in patients under the age of 60 were determined using the following formula: “mean − 1.28 × standard deviation.” A multivariate linear regression model was established.
Results
A significantly higher SMI at the L1 level was found in males than in females (43.88 ± 6.33 cm2/m2vs 33.68 ± 5.03 cm2/m2; P < 0.001). There were strong correlations between measures at the L1 and L3 levels in both the total subject and sex-specific analyses. A negative association was found between age and L3 SMI in males (r = −0.231, P = 0.038). Both body mass index (BMI) and body surface area (BSA) were positively associated with L1 SMI in both males and females. A multivariate analysis was used to establish a prediction rule to predict SMI at the L3 level. The assessment of consistency and interchangeability between predicted and actual SMI at the L3 level yielded moderately good results. Considering the significant differences observed between male and female participants, the sex-specific cut-off values of the L1 SMI for defining low skeletal muscle mass were 36.52 cm2/m2 in males and 27.29 cm2/m2 in females.
Conclusions
Based on a population from central China, the correlated indicators obtained at the L1 level from routine chest CT scans may serve as effective surrogate markers for those at the L3 level in assessing overall skeletal muscle mass.Upper extremity kinematics: development of a quantitative measure of impairment severity and dissimilarity after strokehttps://peerj.com/articles/163742023-12-082023-12-08Khadija F. ZaidiMichelle Harris-Love
Background
Strokes are a leading cause of disability worldwide, with many survivors experiencing difficulty in recovering upper extremity movement, particularly hand function and grasping ability. There is currently no objective measure of movement quality, and without it, rehabilitative interventions remain at best informed estimations of the underlying neural structures’ response to produce movement. In this article, we utilize a novel modification to Procrustean distance to quantify curve dissimilarity and propose the Reach Severity and Dissimilarity Index (RSDI) as an objective measure of motor deficits.
Methods
All experiments took place at the Medstar National Rehabilitation Hospital; persons with stroke were recruited from the hospital patient population. Using Fugl-Meyer (FM) scores and reach capacities, stroke survivors were placed in either mild or severe impairment groups. Individuals completed sets of reach-to-target tasks to extrapolate kinematic metrics describing motor performance. The Procrustes method of statistical shape analysis was modified to identify reaching sub-movements that were congruous to able-bodied sub-movements.
Findings
Movement initiation proceeds comparably to the reference curve in both two- and three-dimensional representations of mild impairment movement. There were significant effects of the location of congruent segments between subject and reference curves, mean velocities, peak roll angle, and target error. These metrics were used to calculate a preliminary RSDI score with severity and dissimilarity sub-scores, and subjects were reclassified in terms of rehabilitation goals as Speed Emphasis, Strength Emphasis, and Combined Emphasis.
Interpretation
The modified Procrustes method shows promise in identifying disruptions in movement and monitoring recovery without adding to patient or clinician burden. The proposed RSDI score can be adapted and expanded to other functional movements and used as an objective clinical tool. By reducing the impact of stroke on disability, there is a significant potential to improve quality of life through individualized rehabilitation.
Background
Strokes are a leading cause of disability worldwide, with many survivors experiencing difficulty in recovering upper extremity movement, particularly hand function and grasping ability. There is currently no objective measure of movement quality, and without it, rehabilitative interventions remain at best informed estimations of the underlying neural structures’ response to produce movement. In this article, we utilize a novel modification to Procrustean distance to quantify curve dissimilarity and propose the Reach Severity and Dissimilarity Index (RSDI) as an objective measure of motor deficits.
Methods
All experiments took place at the Medstar National Rehabilitation Hospital; persons with stroke were recruited from the hospital patient population. Using Fugl-Meyer (FM) scores and reach capacities, stroke survivors were placed in either mild or severe impairment groups. Individuals completed sets of reach-to-target tasks to extrapolate kinematic metrics describing motor performance. The Procrustes method of statistical shape analysis was modified to identify reaching sub-movements that were congruous to able-bodied sub-movements.
Findings
Movement initiation proceeds comparably to the reference curve in both two- and three-dimensional representations of mild impairment movement. There were significant effects of the location of congruent segments between subject and reference curves, mean velocities, peak roll angle, and target error. These metrics were used to calculate a preliminary RSDI score with severity and dissimilarity sub-scores, and subjects were reclassified in terms of rehabilitation goals as Speed Emphasis, Strength Emphasis, and Combined Emphasis.
Interpretation
The modified Procrustes method shows promise in identifying disruptions in movement and monitoring recovery without adding to patient or clinician burden. The proposed RSDI score can be adapted and expanded to other functional movements and used as an objective clinical tool. By reducing the impact of stroke on disability, there is a significant potential to improve quality of life through individualized rehabilitation.Association between osteoporosis and cardiovascular disease in elderly people: evidence from a retrospective studyhttps://peerj.com/articles/165462023-12-082023-12-08Xiaoying HuShucan MaLiman ChenChunhui TianWeiwei Wang
Objective
This study aimed to investigate the associations between osteoporosis, biochemical indexes, bone mineral density (BMD), and cardiovascular disease.
Methods
A cross-sectional study design was used to examine the relationships between these parameters. Logistic regression and correlation analyses were conducted to assess the associations between elevated levels of triglyceride, total cholesterol, low-density lipoprotein (LDL), high-density lipoprotein (HDL), homocysteine, and the presence of osteoporosis. Additionally, correlations between BMD and biochemical indexes were analyzed. The incidence of cardiovascular disease and its correlation with BMD were evaluated. Receiver operating characteristic (ROC) analysis was performed to determine the utility of BMD in identifying cardiovascular disease.
Results
The results revealed that elevated triglyceride, total cholesterol, and LDL levels were positively associated with osteoporosis, while higher HDL levels and homocysteine were negatively associated. Correlation analysis demonstrated negative correlations between triglyceride levels and BMD, and positive correlations between total cholesterol and HDL levels with BMD. LDL levels showed a weak negative correlation, and homocysteine levels exhibited a strong negative correlation with BMD. The osteoporosis group had lower BMD and a higher incidence of cardiovascular disease compared to the non-osteoporosis group. Logistic regression analysis confirmed the correlation between lower BMD and increased risk of cardiovascular disease.
Conclusion
This study provides evidence supporting the associations between osteoporosis, biochemical indexes, BMD, and cardiovascular disease. Aberrations in lipid profiles and homocysteine levels may contribute to osteoporosis development. Lower BMD, particularly in individuals with osteoporosis, appears to increase the risk of cardiovascular disease. BMD shows promise as a diagnostic tool for identifying individuals at risk of cardiovascular disease. Further research is needed to elucidate the underlying mechanisms and establish the clinical implications of these relationships. Future longitudinal studies are necessary to determine causality and long-term prognostic implications.
Objective
This study aimed to investigate the associations between osteoporosis, biochemical indexes, bone mineral density (BMD), and cardiovascular disease.
Methods
A cross-sectional study design was used to examine the relationships between these parameters. Logistic regression and correlation analyses were conducted to assess the associations between elevated levels of triglyceride, total cholesterol, low-density lipoprotein (LDL), high-density lipoprotein (HDL), homocysteine, and the presence of osteoporosis. Additionally, correlations between BMD and biochemical indexes were analyzed. The incidence of cardiovascular disease and its correlation with BMD were evaluated. Receiver operating characteristic (ROC) analysis was performed to determine the utility of BMD in identifying cardiovascular disease.
Results
The results revealed that elevated triglyceride, total cholesterol, and LDL levels were positively associated with osteoporosis, while higher HDL levels and homocysteine were negatively associated. Correlation analysis demonstrated negative correlations between triglyceride levels and BMD, and positive correlations between total cholesterol and HDL levels with BMD. LDL levels showed a weak negative correlation, and homocysteine levels exhibited a strong negative correlation with BMD. The osteoporosis group had lower BMD and a higher incidence of cardiovascular disease compared to the non-osteoporosis group. Logistic regression analysis confirmed the correlation between lower BMD and increased risk of cardiovascular disease.
Conclusion
This study provides evidence supporting the associations between osteoporosis, biochemical indexes, BMD, and cardiovascular disease. Aberrations in lipid profiles and homocysteine levels may contribute to osteoporosis development. Lower BMD, particularly in individuals with osteoporosis, appears to increase the risk of cardiovascular disease. BMD shows promise as a diagnostic tool for identifying individuals at risk of cardiovascular disease. Further research is needed to elucidate the underlying mechanisms and establish the clinical implications of these relationships. Future longitudinal studies are necessary to determine causality and long-term prognostic implications.