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Abstract Background This study aims to assess the joint and independent effects of self-reported physical activity and sedentary behavior on mortality in older persons. Methods A prospective community-based cohort study was conducted to examine physical activity (PA) level and sitting time (ST) in relation to mortality among 1,786 older persons aged 65 years and above. PA was assessed by a checklist of 26 self-reported items about PA and hours per week, and the metabolic equivalent hours/week was derived, and ST was measured by a self-reported item asking the average number of hours spent sitting per day. The participants were divided into four combination groups of PA and ST based on WHO guideline and values found in literature: high PA/short ST group, high PA/long ST group, low PA/long ST group, and low PA/short ST group. Data on death ascertainment were obtained through linkage with the national death datasets and expanded cardiovascular disease (CVD) included cardiovascular disease, diabetes, and chronic kidney disease. Results After follow-up for a median 11.1 years, 599 mortality cases were recorded, giving a crude all-cause mortality of 32.5/1,000 person-years, CVD mortality of 8.6/1,000 person-years, expanded CVD mortality of 11.9/1,000 person-years, and nonexpanded CVD mortality of 20.8/1,000 person-years. For all-cause, and expanded CVD, the hazards ratios (HRs) for the low PA/long ST group remained significant compared with that for the high PA/short ST group after all covariates were considered [HRs for all-cause mortality: 1.4 [95% confidence interval (CI) 1.1, 1.8]; and expanded CVD mortality: 1.7 (95% CI 1.1, 2.4). Conclusions The independent effect of PA and the joint effects of PA and ST are associated with all-cause and expanded CVD death risks. Expanded CVD mortality may be minimized by engaging in PA and reducing sedentary behaviors.

Abstract Carotid intima-media thickness (cIMT), a marker of subclinical atherosclerosis, has been found to be associated with incident stroke. High-sensitivity C-reactive protein (CRP) and fibrinogen have been demonstrated to be associated with atherosclerosis. Previous studies on heritability estimates of IMT, CRP, and fibrinogen among Chinese populations are limited. This study aims to estimate the heritability of these risk factors in residents who participated in the Taichung Community Health Study (TCHS) and their family members. A total of 2671 study subjects from 805 families were enrolled in the study, selected from a random sample of TCHS participants and their family members. CRP, and fibrinogen were obtained from each participant, and a questionnaire interview was conducted. cIMT was measured by high-resolution B-mode ultrasound and expressed as the mean of the maximum. Heritability estimates and the familial correlation of cIMT, CRP, and fibrinogen among family pairs were determined with SAGE software. With multivariate adjustments, significant heritability was found for cIMT (h2 = 0.26, P

Abstract Purpose This study aims to develop an ensemble machine learning-based (EML-based) risk prediction model for radiation dermatitis (RD) in patients with head and neck cancer undergoing proton radiotherapy, with the goal of achieving superior predictive performance compared to traditional models. Materials and methods Data from 57 head and neck cancer patients treated with intensity-modulated proton therapy at Kaohsiung Chang Gung Memorial Hospital were analyzed. The study incorporated 11 clinical and 9 dosimetric parameters. Pearson’s correlation was used to eliminate highly correlated variables, followed by feature selection via LASSO to focus on potential RD predictors. Model training involved traditional logistic regression (LR) and advanced ensemble methods such as Random Forest and XGBoost, which were optimized through hyperparameter tuning. Results Feature selection identified six key predictors, including smoking history and specific dosimetric parameters. Ensemble machine learning models, particularly XGBoost, demonstrated superior performance, achieving the highest AUC of 0.890. Feature importance was assessed using SHAP (SHapley Additive exPlanations) values, which underscored the relevance of various clinical and dosimetric factors in predicting RD. Conclusion The study confirms that EML methods, especially XGBoost with its boosting algorithm, provide superior predictive accuracy, enhanced feature selection, and improved data handling compared to traditional LR. While LR offers greater interpretability, the precision and broader applicability of EML make it more suitable for complex medical prediction tasks, such as predicting radiation dermatitis. Given these advantages, EML is highly recommended for further research and application in clinical settings.

Cerebral ischemic stroke is a major cerebrovascular disease and the leading cause of adult disability. We and others previously demonstrated that transplantation of human Wharton’s jelly mesenchymal stromal cells (WJ-MSCs) attenuated neuronal damage and promoted functional improvement in stroke animals. This study aimed to investigate the protective effects of human WJ-MSC exosome (Exo) transplant in cellular and rat models of cerebral stroke. Administration of Exo significantly antagonized glutamate-mediated neuronal loss and terminal deoxynucleotidyl transferase (TdT)-mediated dUTP-X nick end labeling (TUNEL) in rat primary cortical neuronal cultures. Adult male rats underwent a 60-min middle cerebral artery occlusion (MCAo); Exo or vehicle was injected through the tail vein 5–10 min after the MCAo. Two days later, the rats underwent a series of behavioral tests. Stroke rats receiving Exo developed a significant improvement in locomotor function and forelimb strength while reductions in body asymmetry and Bederson’s neurological score. After the behavioral test, brain tissues were harvested for histological and quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) analyses. Animals receiving Exo had less infarction volume, measured by 2,3,5-triphenyl tetrazolium chloride (TTC) staining. Transplantation of Exo increased the expression of protective neurotrophic factors (BMP7, GDNF) and anti-apoptotic factors (Bcl2, Bcl-xL) in the ischemic brain. These findings suggest that early post-treatment with WJ-MSC Exo, given non-invasively through the vein, improved functional recovery and reduced brain damage in the stroke brain.

BackgroundResearchers have developed a variety of indices to assess frailty. Recent research indicates that the human voice reflects frailty status. Frailty phenotypes are seldom discussed in the literature on the aging voice. ObjectiveThis study aims to examine potential phenotypes of frail older adults and determine their correlation with vocal biomarkers. MethodsParticipants aged ≥60 years who visited the geriatric outpatient clinic of a teaching hospital in central Taiwan between 2020 and 2021 were recruited. We identified 4 frailty phenotypes: energy-based frailty, sarcopenia-based frailty, hybrid-based frailty–energy, and hybrid-based frailty–sarcopenia. Participants were asked to pronounce a sustained vowel “/a/” for approximately 1 second. The speech signals were digitized and analyzed. Four voice parameters—the average number of zero crossings (A1), variations in local peaks and valleys (A2), variations in first and second formant frequencies (A3), and spectral energy ratio (A4)—were used for analyzing changes in voice. Logistic regression was used to elucidate the prediction model. ResultsAmong 277 older adults, an increase in A1 values was associated with a lower likelihood of energy-based frailty (odds ratio [OR] 0.81, 95% CI 0.68-0.96), whereas an increase in A2 values resulted in a higher likelihood of sarcopenia-based frailty (OR 1.34, 95% CI 1.18-1.52). Respondents with larger A3 and A4 values had a higher likelihood of hybrid-based frailty–sarcopenia (OR 1.03, 95% CI 1.002-1.06) and hybrid-based frailty–energy (OR 1.43, 95% CI 1.02-2.01), respectively. ConclusionsVocal biomarkers might be potentially useful in estimating frailty phenotypes. Clinicians can use 2 crucial acoustic parameters, namely A1 and A2, to diagnose a frailty phenotype that is associated with insufficient energy or reduced muscle function. The assessment of A3 and A4 involves a complex frailty phenotype.

Abstract Disuse muscle atrophy occurs consequent to prolonged limb immobility or bed rest, which represents an unmet medical need. As existing animal models of limb immobilization often cause skin erosion, edema, and other untoward effects, we here report an alternative method via thermoplastic immobilization of hindlimbs in mice. While significant decreases in the weight and fiber size were noted after 7 days of immobilization, no apparent skin erosion or edema was found. To shed light onto the molecular mechanism underlying this muscle wasting, we performed the next-generation sequencing analysis of gastrocnemius muscles from immobilized versus non-mobilized legs. Among a total of 55,487 genes analyzed, 787 genes were differentially expressed (> fourfold; 454 and 333 genes up- and down-regulated, respectively), which included genes associated with muscle tissue development, muscle system process, protein digestion and absorption, and inflammation-related signaling. From a clinical perspective, this model may help understand the molecular/cellular mechanism that drives muscle disuse and identify therapeutic strategies for this debilitating disease.

Abstract Background Sleeping problems and cognitive impairment are common in elders. Baseline sleep duration and cognitive status are predictors of mortality. But few studies have explored whether longitudinal changes in sleep duration and cognitive function are related to mortality in older adults. The present study investigated the time-varying relationships of sleep duration and cognitive function with subsequent mortality among community-dwelling elders by using 12 years of repeated-measure data. Methods Taichung Community Health Study for Elders (TCHS-E) is a retrospective, population-based cohort that started in 2009 (wave 1) with a total of 912 elders aged 65 years or above. Follow up was conducted in 2010 (wave 2), 2018 (wave 3), and 2020 (wave 4). Sleep duration and Mini-Mental State Examination (MMSE) forms were executed at baseline and three visits during follow-up. Time-varying Cox proportional hazards regression estimated adjusted hazard ratios (HRs) of mortality with 95% confidence intervals (CIs). Results During about 12 years (9,396 person-years) follow-up, 329 deaths from all causes were documented, including 102 deaths due to expanded cardiovascular disease (CVD). In the multivariable-adjusted, time-varying Cox proportional hazard model, the adjusted HR values of all-cause mortality were 1.47 (1.02–2.12) for sleep duration > 9 h/day (vs. 7 h/day) and 1.81 (1.26–2.59) for MMSE

Abstract Machine learning algorithms were used to analyze the odds and predictors of complications of thyroid damage after radiation therapy in patients with head and neck cancer. This study used decision tree (DT), random forest (RF), and support vector machine (SVM) algorithms to evaluate predictors for the data of 137 head and neck cancer patients. Candidate factors included gender, age, thyroid volume, minimum dose, average dose, maximum dose, number of treatments, and relative volume of the organ receiving X dose (X: 10, 20, 30, 40, 50, 60 Gy). The algorithm was optimized according to these factors and tenfold cross-validation to analyze the state of thyroid damage and select the predictors of thyroid dysfunction. The importance of the predictors identified by the three machine learning algorithms was ranked: the top five predictors were age, thyroid volume, average dose, V50 and V60. Of these, age and volume were negatively correlated with thyroid damage, indicating that the greater the age and thyroid volume, the lower the risk of thyroid damage; the average dose, V50 and V60 were positively correlated with thyroid damage, indicating that the larger the average dose, V50 and V60, the higher the risk of thyroid damage. The RF algorithm was most accurate in predicting the probability of thyroid damage among the three algorithms optimized using the above factors. The Area under the receiver operating characteristic curve (AUC) was 0.827 and the accuracy (ACC) was 0.824. This study found that five predictors (age, thyroid volume, mean dose, V50 and V60) are important factors affecting the chance that patients with head and neck cancer who received radiation therapy will develop hypothyroidism. Using these factors as the prediction basis of the algorithm and using RF to predict the occurrence of hypothyroidism had the highest ACC, which was 82.4%. This algorithm is quite helpful in predicting the probability of radiotherapy complications. It also provides references for assisting medical decision-making in the future.

Stem cells exhibit pluripotency and self-renewal abilities. Adipose-derived mesenchymal stem cells can potentially be used to reconstruct various tissues. They possess significant versatility and alleviate various aging-related diseases. Unfortunately, aging leads to senescence, apoptosis, and a decline in regenerative capacity in adipose-derived mesenchymal stem cells. These changes necessitate a strategy to mitigate the effects of aging on stem cells. Ohwia caudata (O. caudata) has therapeutic effects against several illnesses. However, studies on whether O. caudata has therapeutic effects against aging are lacking. In this study, we aimed to identify potential therapeutic anti-aging effects in the crude aqueous extract of O. caudata on adipose-derived mesenchymal stem cells. Using 0.1 μM doxorubicin, we induced aging in human adipose-derived mesenchymal stem cells (hADMSCs) and evaluated whether various concentrations of O. caudata aqueous extract exhibit anti-aging effects on them. The O. caudata extract exhibited significant antioxidant effects on hADMSCs without any toxicity. Furthermore, after treatment with the O. caudata aqueous extract, the levels of mitochondrial superoxide, DNA double-strand breaks, and telomere shortening were reduced in the hADMSCs subjected to doxorubicin-induced aging. The extract also suppressed doxorubicin-induced aging by upregulating klotho and downregulating p21 in hADMSCs. These findings indicated that the O. caudata extract exhibited anti-aging properties that modulated hADMSC homeostasis. Therefore, it could be a potential candidate for restoring the self-renewal ability and multipotency of aging hADMSCs.

Abstract Helicobacter pylori (H. pylori) infection is the principal cause of chronic gastritis, gastric ulcers, duodenal ulcers, and gastric cancer. In clinical practice, diagnosis of H. pylori infection by a gastroenterologists’ impression of endoscopic images is inaccurate and cannot be used for the management of gastrointestinal diseases. The aim of this study was to develop an artificial intelligence classification system for the diagnosis of H. pylori infection by pre-processing endoscopic images and machine learning methods. Endoscopic images of the gastric body and antrum from 302 patients receiving endoscopy with confirmation of H. pylori status by a rapid urease test at An Nan Hospital were obtained for the derivation and validation of an artificial intelligence classification system. The H. pylori status was interpreted as positive or negative by Convolutional Neural Network (CNN) and Concurrent Spatial and Channel Squeeze and Excitation (scSE) network, combined with different classification models for deep learning of gastric images. The comprehensive assessment for H. pylori status by scSE-CatBoost classification models for both body and antrum images from same patients achieved an accuracy of 0.90, sensitivity of 1.00, specificity of 0.81, positive predictive value of 0.82, negative predicted value of 1.00, and area under the curve of 0.88. The data suggest that an artificial intelligence classification model using scSE-CatBoost deep learning for gastric endoscopic images can distinguish H. pylori status with good performance and is useful for the survey or diagnosis of H. pylori infection in clinical practice.

Abstract Background This study aimed to explore trends, in 3 periods, in the intake of energy and macronutrients among Taiwanese older adults. Methods Study subjects were those aged ≥65 years in the Nutrition and Health Survey in Taiwan 1999–2000 as well as the surveys in 2005–2008 and 2013–2016. Twenty-four-hour dietary recall data were obtained. This study used the 3 nutrition survey datasets for 1999–2000, 2005–2008, and 2013–2016, including data on the questionnaire, physical examination, and dietary intakes. Each nutrition survey involved the face-to-face household interview, and individual’s dietary intake of carbohydrate, fat, and protein (% of energy) was estimated. Subsequently, intake statuses of the three macronutrients were classified into below, meeting, and above intake categories. Results In the 2013–2016 survey, approximately 40% of the older adults had a low intake of energy. The prevalence of older adults with a meeting intake of carbohydrate, fat, and protein have increased from the 1999–2000 to 2013–2016 periods. The prevalence of people having a low intake of carbohydrate declined from the 1999–2000 period to the 2013–2016 period. The prevalence of high fat intake in 2013–2016 was approximately 5% higher than that in 1999–2000. In the 2013–2016 period, the prevalence of low intake of carbohydrate, fat, and protein were 25.9, 24.5, and 4.9%, respectively; moreover, the prevalence of high intake of the aforementioned macronutrients were 38.7, 36.2, and 17.6%, respectively. Conclusions Our study provides important evidence on the dietary patterns, as well as their changes over time among Taiwanese older adults. Such information would be useful for health policy makers about the burden of unbalanced diet and for nutrition educators on planning nutrition promotion interventions about well-balanced dietary for the older persons.

Abstract Various attempts have been conducted to improve the performance of text-based sentiment analysis. These significant attempts have focused on text representation and model classifiers. This paper introduced a hybrid model based on the text representation and the classifier models, to address sentiment classification with various topics. The combination of BERT and a distilled version of BERT (DistilBERT) was selected in the representative vectors of the input sentences, while the combination of long short-term memory and temporal convolutional networks was taken to enhance the proposed model in understanding the semantics and context of each word. The experiment results showed that the proposed model outperformed various counterpart schemes in considered metrics. The reliability of the proposed model was confirmed in a mixed dataset containing nine topics.

Abstract Background Obesity and cognitive impairment prevalence increases as age increases. Recent growing evidence finds links between obesity and cognitive impairment in older adults. However, the association between the two is controversial. This study aims to identify obesity marker trajectory patterns, and to assess whether these patterns are associated with cognitive impairment and cognitive decline during a 10-year follow-up period among community-dwelling older adults. Methods A total of 626 older adults aged 65 and older were involved in the study, with at least two repeated measurements at baseline, one-year or 10-year follow-up. Cognitive function was measured through the Mini Mental State Examination. Obesity markers included body mass index, waist circumference, waist-to-hip (WHR), fat mass (FM), and abdominal fat (AF) measured by dual-energy X-ray absorptiometry. Multivariate logistic regression analyses were performed to estimate the adjusted odds ratios (ORs) and 95% confidence intervals (CIs) of cognitive impairment and cognitive decline for obesity marker trajectory patterns. Results After a 10-year follow-up, 168 older adults with incident cognitive impairment and 156 with rapid cognitive decline were defined as the top 25th percentile of cognitive decline. Four distinct trajectory groups of obesity markers were identified. In multivariate logistic regression analyses, a low likelihood of cognitive impairment was observed in the consistently high-level group from FM trajectory (ORs = 0.41, 95% CI = 0.20–0.85); the high-level U-shaped group from WHR trajectory (0.43, 0.22–0.84); and the median-level flat inverse U-shaped, consistently high-level, and low-level flat U-shaped groups from AF trajectory (0.44, 0.26–0.77; 0.33, 0.18–0.61; 0.39, 0.18–0.82). In addition, a low likelihood of rapid decline was found in the low-level, slightly increasing trend group from WHR trajectory (0.43, 0.22–0.85). Conclusion FM and AF trajectories with consistent high levels and WHR trajectory with high level with U-shaped group are associated with low risks of incident cognitive impairment in older adults. Similarly, WHR trajectory with a low but slowly increasing trend is associated with a decreased risk of cognitive decline.

Introduction A body shape index (ABSI) is independently associated with mortality in general population, but studies on the predictability of ABSI in the risk of mortality in patients with type 2 diabetes (T2D) are limited. We aimed to examine the independent and joint association of ABSI, body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), and body roundness index (BRI) with mortality in patients with T2D.Research design and methods The study included 11 872 patients (46.5% women) aged 30 years and older and who took part in diabetes care management program of a medical center in Taiwan. Body indices were evaluated by anthropometric measurements at baseline between 2001 and 2016, and their death status was followed up through 2021. Multivariate Cox regression models were used to assess the effect of body indices on mortality.Results During a mean follow-up of 10.2 years, 560 cardiovascular disease (CVD) deaths and 3043 deaths were recorded. For ABSI, WC, WHR, WHtR and BRI, all-cause mortality rates were statistically significantly greater in Q4 versus Q2. For BMI and WHtR, all-cause mortality rates were also statistically significantly greater in Q1 versus Q2. The combination of BMI and ABSI exhibited a superiority in identifying risks of all-cause mortality and CVD mortality (HRs: 1.45 and 1.37, both p

Abstract Background Despite recent advances in understanding the pathophysiology of cancer cachexia, prevention/treatment of this debilitating disease remains an unmet medical need. Methods We developed an integrated, multi‐tiered strategy involving both in vitro and in vivo muscle atrophy platforms to identify traditional Chinese medicine (TCM)‐based anti‐cachectic agents. In the initial screening, we used inflammatory cytokine‐induced atrophy of C2C12 myotubes as a phenotypic screening platform to assess the protective effects of TCMs. The selected TCMs were then evaluated for their abilities to protect Caenorhabditis elegans from age‐related reduction of mobility and contractility, followed by the C‐26 colon adenocarcinoma mouse model of cachexia to confirm the anti‐muscle atrophy effects (body/skeletal muscle weights, fibre size distribution, grip strengths, and serum IL‐6). Transcriptome analysis, quantitative real‐time polymerase chain reaction, and immunoblotting were performed to gain understanding of the potential mechanism(s) by which effective TCM protected against C26 tumour‐induced muscle atrophy. Results Of 29 widely used TCMs, Dioscorea radix (DR) and Mu Dan Pi (MDP) showed a complete protection (all P values, 0.0002) vis‐à‐vis C26 conditioned medium control in the myotube atrophy platform. MDP exhibited a unique ability to ameliorate age‐associated decreases in worm mobility, accompanied by improved total body contractions, relative to control (P

Abstract Background Decreased skeletal muscle mass and low physical performance are independently associated with increased mortality in elderly individuals. However, little is known about the effects of skeletal muscle mass combined with physical performance on the prediction of mortality risk among community-dwelling older adults. This study aimed to determine the combined effects of skeletal muscle mass and physical performance on total mortality. Methods A community-based prospective cohort study was conducted among 641 participants aged 65 and older in 2009. The height-adjusted skeletal muscle index (hSMI) and the weight-adjusted SMI (wSMI) were determined by dual-energy X-ray absorptiometry examination. Physical performance tests measured at baseline included gait speed (GS), timed up-and-go (TUG) test, timed chair stand (TCS), weight-adjusted leg press (WaLP), and handgrip strength (HS). Cox proportional hazards regression models were applied to determine the adjusted hazard ratios (HRs) of mortality with 95% confidence intervals (95% CIs) for baseline skeletal muscle mass, physical performance, and traditional risk factors. Results During the follow-up of 12 years, 198 (30.89%) participants died. Low hSMI, low GS, high TUG, high TCS, low WaLP, and low HS were associated with high risks of mortality after the adjustment for confounders. The results of receiver operating characteristic (ROC) curve analyses revealed the values of ROC for models with additional consideration for TUG or all indicators significantly improved the discriminatory ability of mortality compared with the model with traditional factors (all P

Abstract Background Frailty is a common issue in the aging population. Given that frailty syndrome is little discussed in the literature on the aging voice, the current study aims to examine the relationship between frailty and vocal biomarkers in older people. Methods Participants aged ≥ 60 years visiting geriatric outpatient clinics were recruited. They underwent frailty assessment (Cardiovascular Health Study [CHS] index; Study of Osteoporotic Fractures [SOF] index; and Fatigue, Resistance, Ambulation, Illness, and Loss of weight [FRAIL] index) and were asked to pronounce a sustained vowel /a/ for approximately 1 s. Four voice parameters were assessed: average number of zero crossings (A1), variations in local peaks and valleys (A2), variations in first and second formant frequencies (A3), and spectral energy ratio (A4). Results Among 277 older adults, increased A1 was associated with a lower likelihood of frailty as defined by SOF (odds ratio [OR] 0.84, 95% confidence interval [CI] 0.74–0.96). Participants with larger A2 values were more likely to be frail, as defined by FRAIL and CHS (FRAIL: OR 1.41, 95% CI 1.12–1.79; CHS: OR 1.38, 95% CI 1.10–1.75). Sex differences were observed across the three frailty indices. In male participants, an increase in A3 by 10 points increased the odds of frailty by almost 7% (SOF: OR 1.07, 95% CI 1.02–1.12), 6% (FRAIL: OR 1.06, 95% CI 1.02–1.11), or 6% (CHS: OR 1.06, 95% CI 1.01–1.11). In female participants, an increase in A4 by 0.1 conferred a significant 2.8-fold (SOF: OR 2.81, 95% CI 1.71–4.62), 2.3-fold (FRAIL: OR 2.31, 95% CI 1.45–3.68), or 2.8-fold (CHS: OR 2.82, 95% CI 1.76–4.51, CHS) increased odds of frailty. Conclusions Vocal biomarkers, especially spectral-domain voice parameters, might have potential for estimating frailty, as a non-invasive, instantaneous, objective, and cost-effective estimation tool, and demonstrating sex differences for individualised treatment of frailty.

Abstract Ankle-brachial index (ABI) and brachial-ankle pulse wave velocity (baPWV) are used as non-invasive indicators for detecting atherosclerosis and arterial stiffness, two well-known predictors of mortality in patients with type 2 diabetes mellitus (T2DM). ABI and baPWV have independent associations with mortality; however, their joint and interactive effects on mortality have not been assessed in patients with T2DM. This work aims to evaluate the independent, joint, and interactive associations of ABI and baPWV with all-cause and expanded cardiovascular disease (CVD) mortality in patients with T2DM. This observational study included 2160 patients with T2DM enlisted in the Diabetes Care Management Program database of China Medical University Hospital from 2001 to 2016 and then followed their death status until August 2021. Cox proportional hazard models were used to evaluate the independent, joint, and interactive effects of ABI and baPWV on the risk of all-cause and expanded CVD mortality. A total of 474 patient deaths occurred after a mean follow-up of 8.4 years, and 268 of which were attributed to cardiovascular events. Abnormal ABI (≤ 0.9) and highest baPWV quartile were independently associated with increased risks of all-cause [ABI: hazard ratio (HR) 1.67, 95% confidence interval (CI) 1.30–2.11; baPWV: 1.63, 1.16–2.27] and expanded CVD mortality (ABI: 2.21, 1.62–3.02; baPWV: 1.75, 1.09–2.83). The combination of abnormal ABI (≤ 0.9) and highest baPWV quartile was associated with a significantly higher risk of all-cause (4.51, 2.50–8.11) and expanded CVD mortality (9.74, 4.21–22.51) compared with that of the combination of normal ABI and lowest baPWV quartile. Significant interactions were observed between ABI and baPWV in relation to all-cause and expand CVD mortality (both p for interaction

Abstract Background Sleep duration is associated with mortality. However, prior studies exploring whether sleep duration predicts subsequent long-term mortality in patients with diabetes are limited. This study aims to examine whether metabolic factors affect the associations between baseline sleep duration and subsequent risks of all-cause, expanded, and non-expanded cardiovascular disease (CVD) mortalities among patients with type 2 diabetes (T2D). Methods A total of 12,526 T2D patients aged 30 years and older, with a follow-up period ≥ 3 years, were identified from the Diabetes Case Management Program of a medical center in Taiwan. Sleep duration was measured using computerized questionnaires by case managers, and the time frame for this question was 1 month prior to the interview date. Sleep duration in relation to subsequent mortality from all causes, expanded CVD, and non-expanded CVD was examined using Cox proportional hazard models. Results Within 10 years of follow-up, 2918 deaths (1328 CVD deaths and 1590 non-CVD deaths) were recorded. A J-shaped association was observed for all-cause, expanded CVD, and non-expanded CVD mortalities, and the lowest risks were observed for patients with 5–7 h of sleep. The significant joint effects included sleep duration of more or less than 7 h with age ≥ 65 years [adjusted HRs: 4.00 (3.49–4.60)], diabetes duration ≥ 5 years [1.60 (1.40–1.84)], age at diabetes diagnosis ≤ 45 years [1.69 (1.38–2.07)], insulin use [1.76 (1.54–2.03)], systolic blood pressure/diastolic blood pressure > 130/85 mmHg [1.24 (1.07–1.43)], triglyceride ≥ 150 mg/dL [1.38 (1.22–1.56)], HbA1c ≥ 7% [1.31 (1.13–1.52)], and body mass index

Abstract Many studies had established the chronic kidney disease (CKD) prediction models, but most of them were conducted on the general population and not on patients with type 2 diabetes, especially in Asian populations. This study aimed to develop a risk prediction model for CKD in patients with type 2 diabetes from the Diabetes Care Management Program (DCMP) in Taiwan. This research was a retrospective cohort study. We used the DCMP database to set up a cohort of 4,601 patients with type 2 diabetes without CKD aged 40–92 years enrolled in the DCMP program of a Taichung medical center in 2002–2016. All patients were followed up until incidences of CKD, death, and loss to follow-up or 2016. The dataset for participants of national DCMP in 2002–2004 was used as external validation. The incident CKD cases were defined as having one of the following three conditions: ACR data greater than or equal to 300 (mg/g); both eGFR data less than 60 (ml/min/1.73 m2) and ACR data greater than or equal to 30 (mg/g); and eGFR data less than 45 (ml/min/1.73 m2). The study subjects were randomly allocated to derivation and validation sets at a 2:1 ratio. Cox proportional hazards regression model was used to identify the risk factors of CKD in the derivation set. Time-varying area under receiver operating characteristics curve (AUC) was used to evaluate the performance of the risk model. After an average of 3.8 years of follow-up period, 3,067 study subjects were included in the derivation set, and 786 (25.63%) were newly diagnosed CKD cases. A total of 1,534 participants were designated to the validation set, and 378 (24.64%) were newly diagnosed CKD cases. The final CKD risk factors consisted of age, duration of diabetes, insulin use, estimated glomerular filtration rate, albumin-to-creatinine ratio, high-density lipoprotein cholesterol, triglyceride, diabetes retinopathy, variation in HbA1c, variation in FPG, and hypertension drug use. The AUC values of 1-, 3-, and 5-year CKD risks were 0.74, 0.76, and 0.77 in the validation set, respectively, and were 0.76, 0.77, and 0.76 in the sample for external validation, respectively. The value of Harrell’s c-statistics was 0.76 (0.74, 0.78). The proposed model is the first CKD risk prediction model for type 2 diabetes patients in Taiwan. The 1-, 3-, and 5-year CKD risk prediction models showed good prediction accuracy. The model can be used as a guide for clinicians to develop medical plans for future CKD preventive intervention in Chinese patients with type 2 diabetes.

Introduction Observational studies support the relationship between C-reactive protein (CRP) level and diabetic nephropathy (DN) in patients with diabetes. The research question regarding whether the relationship between serum high-sensitivity C-reactive protein (hsCRP) level and DN is causal lacks experimental evidence. Therefore, this study aimed to evaluate the causality between hsCRP and DN based on Mendelian randomization (MR) analysis.Research design and methods A total of 2332 participants with type 2 diabetes from the Taiwan Biobank database was analyzed. Genetic risk scores (GRSs), which comprise four validated CRP loci as two instrumental variables, were calculated as unweighted and weighted scores to evaluate the causal relationship of hsCRP with DN risk. The two-stage regression model was used to estimate OR and 95% CI.Results The analyses of the observational study showed that the hsCRP level was significantly associated with DN after multivariate adjustment (adjusted OR 1.15; 95% CI 1.01 to 1.32). Unweighted/weighted GRSs for log-transformed hsCRP satisfied MR assumptions 1 and 3, respectively; that is, a significant association with hsCRP was observed but that with DN was absent (adjusted OR 1.00, 95% CI 0.92 to 1.09; 1.00, 0.72 to 1.39, respectively). The MR analyses demonstrated that a 1-unit increase in the log-transformed genetically predicted hsCRP by unweighted and weighted GRSs was associated with DN, demonstrating ORs of 1.80 (95% CI 1.51 to 2.14) and 1.67 (95% CI 1.40 to 1.98), respectively.Conclusions The current study provided experimental evidence that hsCRP level was causally related to DN. These findings suggest that the elevated hsCRP may be a causal risk factor for DN in patients with type 2 diabetes.

Abstract Background Dyslipidemia is a major cardiovascular risk factor and common in diabetes patients. Most guidelines focus on optimal lipid levels, while variation of lipid profiles is far less discussed. This study aims to investigate the association of visit-to-visit variability in blood lipids with all-cause, cardiovascular, and non-cardiovascular mortality in patients with type 2 diabetes. Methods We identified 10,583 type 2 diabetes patients aged ≥ 30 years with follow-up ≥ 3 years and who participated in the Diabetes Care Management Program at a medical center in Taiwan. Variability in lipid profiles within 3 years after entry was calculated using coefficient of variation. Cox proportional hazard models were used to evaluate lipid variability in relation to subsequent mortality. Results Over a mean follow-up of 6.4 years, 1838 all-cause deaths (809 cardiovascular deaths) were observed. For each 10% increase in variability in high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and total cholesterol, the hazard ratios (95% confidence intervals) of all-cause mortality were 1.30 (1.22–1.37), 1.05 (1.01–1.09), and 1.10 (1.03–1.16), respectively; those of cardiovascular mortality were 1.27 (1.16–1.39), 1.08 (1.02–1.15), and 1.16 (1.07–1.27), respectively. Each 10% increase in high-density lipoprotein cholesterol variability conveyed 31% greater risk of non-cardiovascular mortality. High variability in total cholesterol and low-density lipoprotein cholesterol increased all-cause mortality in subgroups of nonsmoking, regular exercising, non-dyslipidemia, and more severe status of diabetes at baseline. Conclusions Blood lipid variability except for triglyceride variability was associated with all-cause and cardiovascular mortality in patients with type 2 diabetes.

Abstract Hypertension (HTN), which frequently co‐exists with diabetes mellitus, is the leading major cause of cardiovascular disease and death globally. This study aimed to develop and validate a risk scoring system considering the effects of glycemic and blood pressure (BP) variabilities to predict HTN incidence in patients with type 2 diabetes. This research is a retrospective cohort study that included 3416 patients with type 2 diabetes without HTN and who were enrolled in a managed care program in 2001–2015. The patients were followed up until April 2016, new‐onset HTN event, or death. HTN was defined as diastolic BP (DBP) ≥ 90 mm Hg, systolic BP (SBP) ≥ 140 mm Hg, or the initiation of antihypertensive medication. Cox proportional hazard regression model was used to develop the risk scoring system for HTN. Of the patients, 1738 experienced new‐onset HTN during an average follow‐up period of 3.40 years. Age, sex, physical activity, body mass index, type of DM treatment, family history of HTN, baseline SBP and DBP, variabilities of fasting plasma glucose, SBP, and DBP and macroalbuminuria were significant variables for the prediction of new‐onset HTN. Using these predictors, the prediction models for 1‐, 3‐, and 5‐year periods demonstrated good discrimination, with AUC values of 0.70–0.76. Our HTN scoring system for patients with type 2 DM, which involves innovative predictors of glycemic and BP variabilities, has good classification accuracy and identifies risk factors available in clinical settings for prevention of the progression to new‐onset HTN.

Abstract This study aimed to explore the associations between renal-related and arterial stiffness biomarkers with all-cause and expanded cardiovascular disease (CVD) mortality in a general Taiwanese population. This prospective community-based cohort study included 4883 subjects aged ≥ 20 years who were followed up until December 31, 2016. Renal-related biomarkers consisted of blood urea nitrogen (BUN), estimated glomerular filtration rate (eGFR), and urine albumin-to-creatinine ratio (UACR). Arterial stiffness biomarker consisted of brachial-ankle pulse wave velocity (baPWV). The death status of the subjects was ascertained by matching information from death records with the identification number and date of birth of the subjects. Cox proportional hazard models with restricted cubic splines estimated the hazard ratios and 95% confidence intervals for all-cause mortality and expanded CVD mortality. During a mean 8.3 years of follow up, 456 deaths were recorded, 146 of which were due to expanded CVD mortality. The multivariable-adjusted hazard ratios of all-cause mortality was 1.53 (95% CI 1.21–1.94) for BUN (≥ 20 mg/dL vs.

Abstract Background This study determined (1) whether a change in frailty status after a 1 year follow up is associated with healthcare utilization and evaluated (2) whether a change in frailty status after a 1 year follow up and health care utilization are associated with all-cause mortality in a sample of Taiwan population. Methods This work is a population-based prospective cohort study involving residents aged ≥65 years in 2009. A total of 548 elderly patients who received follow-ups in the subsequent year were included in the current data analysis. Fried frailty phenotype was measured at baseline and 1 year. Information on the outpatient visits of each specialty doctor, emergency care utilization, and hospital admission during the 2 month period before the second interview was collected through standardized questionnaires administered by an interviewer. Deaths were verified by indexing to the national database of deaths. Results At the subsequent 1 year follow-up, 73 (13.3%), 356 (64.9%), and 119 (21.7%) elderly participants exhibited deterioration, no change in status, and improvement in frailty states, respectively. Multivariate logistic analysis showed the high risk of any type of outpatient use (odds ratios [OR] 1.94, 95% confidence interval [CI] 1.02–3.71) among older adults with worse frailty status compared with those who were robust at baseline and had unchanged frailty status after 1 year. After multivariate adjustment, participants with high outpatient clinic utilization had significantly higher mortality than those with low outpatient clinic visits among unchanged pre-frail or frail (hazard ratios [HR] 2.79, 95% CI: 1.46–5.33) and frail to pre-frail/robust group (HR 9.32, 95% CI: 3.82–22.73) if the unchanged robustness and low outpatient clinic visits group was used as the reference group. Conclusions The conditions associated with frailty status, either after 1 year or at baseline, significantly affected the outpatient visits and may have increased medical expenditures. Combined change in frailty status and number of outpatient visits is related to increased mortality.

Abstract Background Renal function is a key factor of cardiovascular disease. Carotid intima-media thickness (IMT) has been widely used as a marker of early subclinical atherosclerosis. The determinants of cystatin C, a novel marker of renal function, have not been extensively studied in the Asian population. This study aimed to assess the determinants of cystatin C and explore whether carotid thickening was associated with urinary albumin-creatinine ratio and cystatin C in community-living Taiwanese adults. Methods A cross-sectional study was conducted on participants from Taichung City, Taiwan. All the participants underwent carotid ultrasonography. Carotid IMT-mean and IMT-maximum were derived. Kidney biomarkers were measured on the basis of urinary albumin-to-creatinine ratio (ACR) and cystatin C. Multiple linear regression analysis was used. Results A total of 1032 individuals were recruited, and 469 (45.44%) of them were men. An increased cystatin C level was significantly associated with older age, male gender, lack of physical activity, low HDL cholesterol, abdominal obesity, high hs-CRP, and high ACR. The multivariate-adjusted mean carotid IMT-mean and IMT-maximum values significantly increased by 80.49 and 195.23 μm for every one unit of increase in cystatin C level and by 0.07 and 0.14 μm for every one unit of increase in ACR, respectively (all p

Abstract Background Cognitive impairment is accompanied with high rates of comorbid conditions, leading ultimately to death. Few studies examine the relation between cognitive transition and mortality, especially in Asian population. This study evaluated baseline cognition and cognitive transition in relation to all-cause mortality among community-dwelling older adults. Methods We conducted a community-based prospective cohort study among 921 participants of Taichung Community Health Study for Elders in 2009. Cognitive function was evaluated by the Mini-Mental State Examination. Cognitive impairment was considered if the total score is less than 27, 24, and 21 for a participant’s educational level of more than 6 years, equal or less than 6 years, and illiteracy, respectively. One-year transition in cognitive function was obtained among 517 individuals who were assessed in both 2009 and 2010. Mortality was followed up until 2016. Cox proportional hazards models were applied to estimate the adjusted hazard ratios of mortality for baseline cognitive impairment and one-year transition in cognitive status. Results After a follow-up of 6.62 years, 160 deaths were recorded. The multivariate adjusted hazard ratio (95% confidence interval) for baseline cognitive impairment was 2.08 (1.43, 3.01). Significantly increased mortality risk was observed for cognitively impaired–normal and impaired–impaired subgroups over 1 year as compared with those who remained normal [2.87 (1.25, 6.56) and 3.79 (1.64, 8.73), respectively]. The area under the receiver operating characteristic curves demonstrated that baseline cognition and one-year cognitive transition had no differential predictive ability for mortality. Besides, there was an interaction of cognitive impairment and frailty, with an additive mortality risk [5.41 (3.14, 9.35)] for the elders who presented with both. Conclusion Baseline cognitive impairment rather than one-year progression is associated with mortality in a six-year follow-up on older adults.

For continuous sliding mode control (SMC) in the unified chaotic systems subjected to matched/unmatched uncertainties, a novel chattering-free SMC design is proposed. First, an augmented state is introduced such that it becomes possible to develop a continuous controller to eliminate the undesired chattering which often appears in the typical SMC. Then by using this chattering-free controller, the chaos behavior in unified chaotic systems with matched uncertainties can be completely suppressed. As for the unmatched uncertainties, every state of controlled systems can be driven and limited to a predictable bound, which is not addressed in the literature. Finally, the effectiveness of the proposed chattering-free controller is verified by the numerical simulations.

BackgroundAlthough carotid sonographic features have been used as predictors of recurrent stroke, few large-scale studies have explored the use of machine learning analysis of carotid sonographic features for the prediction of recurrent stroke.MethodsWe retrospectively collected electronic medical records of enrolled patients from the data warehouse of China Medical University Hospital, a tertiary medical center in central Taiwan, from January 2012 to November 2018. We included patients who underwent a documented carotid ultrasound within 30 days of experiencing an acute first stroke during the study period. We classified these participants into two groups: those with non-recurrent stroke (those who has not been diagnosed with acute stroke again during the study period) and those with recurrent stoke (those who has been diagnosed with acute stroke during the study period). A total of 1,235 carotid sonographic parameters were analyzed. Data on the patients' demographic characteristics and comorbidities were also collected. Python 3.7 was used as the programming language, and the scikit-learn toolkit was used to complete the derivation and verification of the machine learning methods.ResultsIn total, 2,411 patients were enrolled in this study, of whom 1,896 and 515 had non-recurrent and recurrent stroke, respectively. After extraction, 43 features of carotid sonography (36 carotid sonographic parameters and seven transcranial color Doppler sonographic parameter) were analyzed. For predicting recurrent stroke, CatBoost achieved the highest area under the curve (0.844, CIs 95% 0.824–0.868), followed by the Light Gradient Boosting Machine (0.832, CIs 95% 0.813–0.851), random forest (0.819, CIs 95% 0.802–0.846), support-vector machine (0.759, CIs 95% 0.739–0.781), logistic regression (0.781, CIs 95% 0.764–0.800), and decision tree (0.735, CIs 95% 0.717–0.755) models.ConclusionWhen using the CatBoost model, the top three features for predicting recurrent stroke were determined to be the use of anticoagulation medications, the use of NSAID medications, and the resistive index of the left subclavian artery. The CatBoost model demonstrated efficiency and achieved optimal performance in the predictive classification of non-recurrent and recurrent stroke.

Abstract Background This study investigated whether visit-to-visit fasting plasma glucose (FPG) variability, as measured by the coefficient of variation (CV), increased peripheral artery disease (PAD) risk. Methods Individuals with type 2 diabetes from the National Diabetes Care Management Program during the period 2002–2004, ≥ 30 years of age, and free of PAD (n = 30,932) were included and monitored until 2011. Cox proportional hazards regression models were implemented to analyze related determinants of PAD. Results A total of 894 incident cases of PAD were identified during an average 8.2 years of follow-up, resulting in a crude incidence rate of 3.53 per 1000 person-years. Both FPG-CV and HbA1c were significantly associated with PAD after multivariate adjustment, with corresponding hazard ratios of 1.24 [95% confidence interval (CI) 1.04–1.47] for FPG-CV in the third tertile and 1.50 (95% CI 1.10–2.04) for HbA1c ≥ 10%. The findings of the sensitivity analysis remained consistent after excluding potential confounders, demonstrating the consistency of the results. Conclusions The associations between HbA1c, variability in FPG-CV, and PAD suggest a linked pathophysiological mechanism, suggesting the crucial role of glycemic variability in clinical management and therapeutic goals in preventing PAD in type 2 diabetes.

BackgroundTo evaluate the lifetime secondary cancer risk (SCR) of stereotactic body radiotherapy (SBRT) using the CyberKnife (CK) M6 system with a lung-optimized treatment (LOT) module for lung cancer patients.MethodsWe retrospectively enrolled 11 lung cancer patients curatively treated with SBRT using the CK M6 robotic radiosurgery system. The planning treatment volume (PTV) and common organs at risk (OARs) for SCR analysis included the spinal cord, total lung, and healthy normal lung tissue (total lung volume - PTV). Schneider’s full model was used to calculate SCR according to the concept of organ equivalent dose (OED).ResultsCK-LOT-SBRT delivers precisely targeted radiation doses to lung cancers and achieves good PTV coverage and conformal dose distribution, thus posing limited SCR to surrounding tissues. The three OARs had similar risk equivalent dose (RED) values among four different models. However, for the PTV, differences in RED values were observed among the models. The cumulative excess absolute risk (EAR) value for the normal lung, spinal cord, and PTV was 70.47 (per 10,000 person-years). Schneider’s Lnt model seemed to overestimate the EAR/lifetime attributable risk (LAR).ConclusionFor lung cancer patients treated with CK-LOT optimized with the Monte Carlo algorithm, the SCR might be lower. Younger patients had a greater SCR, although the dose–response relationship seemed be non-linear for the investigated organs, especially with respect to the PTV. Despite the etiological association, the SCR after CK-LOT-SBRT for carcinoma and sarcoma, is low, but not equal to zero. Further research is required to understand and to show the lung SBRT SCR comparisons and differences across different modalities with motion management strategies.

CyberKnife is a robotic stereotactic body radiotherapy (SBRT) system that precisely delivers large radiation doses to a target. Tissue heterogeneity and shape can be problems. The treatment -planning system allows for use of the Monte Carlo (MC) or fundamental Ray Tracing (RyTc) algorithms for ultimate dose calculation. The MC is more accurate but consumes more computer resources and time. We compared radiation dose calculations for lung targets between the MC and RyTc algorithms. We placed a prosthetic marker at different thorax sites in a Rando phantom to compare the calculation results. The peripheral sites followed by the diaphragm showed the greatest significant differences in parameters for evaluating the treatment quality. For gross tumor volume dose, peripheral lung targets were the most critical for the calculation algorithm. The MC mean doses were lower than the RyTc mean doses and generally demonstrated better conformity. However, the deviation between conformal index (CI) and new CI at the peripheral location was large. The coverage differences between the RyTc and MC were most obvious at the peripheral lung site. The MC algorithm for radiation dose calculation in the lungs was indispensable in SBRT using CyberKnife for accurate dose evaluation, especially at the peripheral and diaphragm locations.

Abstract Background Previous studies have reported the associations of frailty phenotype or its components with mortality. However, studies that explored the effects of transition in frailty status on mortality were far less in Asian or Chinese. The aim of this study was to evaluate baseline frailty status and one-year change of frailty status in relation to all-cause mortality in Taiwanese community-dwelling older adults who participated in the Taichung Community Health Study for Elders. Methods We conducted a community-based prospective cohort study. A total of 921 community-dwelling elderly men and women aged 65–99 years in Taichung City were enrolled in 2009–2010 and were followed up through 2016. We adopted the definition of frailty proposed by Fried et al., including five components: shrinking, weakness, poor endurance and energy, slowness, and low physical activity. Cox proportional hazards models were used to determine adjusted hazard ratios (HRs) of mortality with 95% confidence intervals (CIs) for frailty at baseline and one-year change in frailty status. Results There were 160 deaths during the follow-up period. The mortality rates in groups of robust and frail were 20.26 and 84.66 per 1000 person-years respectively. After multivariate adjustment, the HR (CIs) for baseline frailty was 2.67 (1.73–4.12). Poor endurance and energy [1.88 (1.03–3.42)], slowness [2.60 (1.76–3.83)] and weakness [1.65 (1.16–2.33)] were found to be predictors of mortality. Increased risks in mortality for subgroups of robust-to-frail [2.76 (1.22–6.27)], frail-to-robust [3.87 (1.63, 9.19)], and frail-to-frail [4.08 (1.92–8.66)] over one-year period were observed compared with those remaining robust. Conclusion Baseline frailty status and one-year change in frailty status are associated with 6-year all-cause mortality among Taiwanese elderly adults. Frailty may be useful for identifying older adults at high risks for mortality prevention.

Power consumption forecasting is a crucial need for power management to achieve sustainable energy. The power demand is increasing over time, while the forecasting of power consumption possesses challenges with nonlinearity patterns and various noise in the datasets. To this end, this paper proposes the RobustSTL and temporal convolutional network (TCN) model to forecast hourly power consumption. Through the RobustSTL, instead of standard STL, this decomposition method can extract time series data despite containing dynamic patterns, various noise, and burstiness. The trend, seasonality, and remainder components obtained from the decomposition operation can enhance prediction accuracy by providing significant information from the dataset. These components are then used as input for the TCN model applying deep learning for forecasting. TCN employing dilated causal convolutions and residual blocks to extract long-term data patterns outperforms recurrent networks in time series forecasting studies. To assess the proposed model, this paper conducts a comparison experiment between the proposed model and counterpart models. The result shows that the proposed model can grasp the rules of historical time series data related to hourly power consumption. Our proposed model overcomes the counterpart schemes in MAPE, MAE, and RMSE metrics. Additionally, the proposed model obtains the best results in precision, recall, and F1-score values. The result also indicates that the predicted data can fit the pattern of the actual data.

With an increasing geriatric population, the need for effective management of chronic conditions and medication use in the elderly is growing. Medication use in the elderly presents significant challenges due to changes in pharmacodynamic and pharmacokinetic profiles. We aimed to examine the impact of a collaborative physician-pharmacist medication therapy management (MTM) program for polypharmacy elderly patients. Methods: Elderly patients with multiple chronic conditions on polypharmacy were enrolled in this prospective, randomized, and controlled study over 16 months of implementation. The intervention group consisted of patients randomized to a collaborative pharmacist-physician MTM program. They were monitored continuously by a clinical pharmacist, while patients in the control group received only usual care with follow-up assessment. Primary outcome was economic differences, measured in total medical expenditure. Secondary outcomes of clinical and humanistic effects were compared between the two groups. Results: The total number of enrolled patients was 87 and 91 in the MTM and usual groups, respectively. The difference-in-difference estimate on medical expenditure during the 16-month implementation period was $3,758,373 New Taiwan Dollars ($127,015 US Dollars) less than the usually care group. Impact was also seen in humanistic outcomes while lipid profiles and mortality trended toward improvement. Conclusion: The pharmacist-physician collaborative MTM program for polypharmacy elderly had significant cost savings and improvement in humanistic measures, demonstrating the importance of clinical pharmacists and MTM programs for elderly patients in Taiwan. The results suggest the possibility of clinical benefits, but the study was not substantially powered to find a statistical difference.

This paper is concerned with a novel secure data transmission design based on adaptive synchronization of master and slave unified chaotic systems. First, by introducing an augmented error state, an adaptive continuous sliding mode control (SMC) is derived to guarantee the synchronization of unified chaotic systems. Then, the secret message embedded in the master chaotic system can be transmitted from transmitter to receiver. Different from previous works using discontinuous SMC, the undesired chattering phenomenon can be fully eliminated, and it becomes possible to precisely recover the embedded secret message at the receiver. Last, an example is given to illustrate the success of secure data transmission with the continuous SMC developed in this paper.

Abstract We assessed gene–gene and gene-physical activity interactions of polymorphisms in C-reactive protein (CRP), tumor necrosis factor-α (TNF-α), and lymphotoxin α (LTA) genes on lower extremity performance in community-dwelling elders in Taiwan. Five SNPs (rs1205, rs1130864, rs1800947, rs2794520, and rs3093059) of CRP gene, three SNPs (rs909253, rs1041981, and rs2239704) of LTA gene, and three SNPs (rs3093662, rs1800629, and rs1799964) of TNF-α gene of 472 unrelated elders were genotyped. Lower extremity performance included timed up-and-go test (TUG), walking speed, weight-adjusted leg press (waLP), and timed chair stand (TCS). We detected significant interactions between physical activity with CRP rs2794520, rs1205, and rs3093059; LTA rs909253 and rs1041981; and TNF-α rs1799964 for TCS in women after covariate adjustment (all P

This study assessed the interactions among IGF-1, AKT2, FOXO1, and FOXO3 variations and the interactions of gene and physical activity on handgrip strength, arm muscle mass-adjusted handgrip (armGrip), gait speed (GS), timed up and go (TUG), and leg press strength (LPS). Nine single nucleotide polymorphisms (SNPs) containing three IGF-1 SNPs (rs6214, rs5742692, and rs35767), two AKT2 SNPs (rs892119 and rs35817154), two FOXO1 SNPs (rs17446593 and rs10507486), and two FOXO3 SNPs (rs9480865 and rs2153960) were genotyped in 472 unrelated elders with a mean age of 73.8 years. We observed significant interactions of IGF-1 SNP rs6214 and rs35767 with regular physical activity on TUG and GS; and AKT2 SNP rs892119 and FOXO3 SNP rs9480865 with regular physical activity on armGrip. Genotype GG of IGF-1 rs6214 and rs35767 in individuals without regular physical activity had poor performance in TUG and GS, as well as GG of AKT2 rs892119 decreased armGrip in individuals without regular physical activity. After FDR adjustment, no significant gene-gene interactions were found. A sedentary lifestyle may increase the risk of impairing physical performance and regular physical activity is a remedy for sarcopenia, even a little regular physical activity can overcome carrying some risk alleles in this pathway.

Evidence suggests the existence of association between a large panel of modifiable biomarkers representing inflammation, coagulation, paraoxonase, and endothelial activation pathways and carotid atherosclerosis. Thus, this study investigated whether CRP, FGA, FGB, FGG, PON1, and EDNRA gene variants affected plasma hs-CRP, fibrinogen levels, and thickness of carotid intima media thickness (IMT). Nineteen single-nucleotide polymorphisms of CRP, FGA, FGB, FGG, PON1, and EDNRA genes were examined in 480 participants from 160 families. Carotid IMT was measured by ultrasound. Generalized linear models with generalized estimating equation were utilized to consider the dependence of subjects within families. In the recessive model, homozygotes for the minor alleles of rs1800789, rs1800790 and rs4220 SNPs in FGB gene indicated a reduced risk of IMT (Exp. β = 0.89, 0.89, 0.88), which remained significant after adjustment for confounding factors. Significant interaction effects between CRP SNP rs1130864 and rs3093059 and gender for IMT were observed with a significant association in men only. Men carrying minor-minor genotype of CRP SNP rs1130864 and rs3093059 had 0.70- and 0.78-fold lower IMT than men carrying minor-major/major-major genotype. We also observed that the interaction of CRP SNP rs1130864 and rs3093059 with obesity on IMT, hs-CRP and fibrinogen levels. These results support the hypothesis that inflammatory genes are involved in atherosclerosis, most likely via complex gene-gender and gene-obesity interactions.

Prediction model mainly focused on specific diseases, such as diabetes, hypertension, cardiovascular disease, or patients with cancer, or populations of Europe and America, thereby limiting its generalization. This study aimed to develop and validate a 10-year mortality risk score by using data from a population-representative sample of adults. Data were collected from 2,221 Taichung Community Health study participants aged ≥40 years. The baseline period of the study was 2004, and all participants were followed up until death or in 2016. Cox's proportional hazards regression analyses were used to develop the prediction model. A total of 262 deaths were ascertained during the 10-year follow-up. The all-cause mortality prediction model calculated the significant risk factors, namely, age, sex, marital status, physical activity, tobacco use, estimated glomerular filtration rate, and albumin-to-creatinine ratio, among the baseline risk factors. The expanded cardiovascular disease (CVD) mortality prediction model consisted of six variables: age, sex, body mass index, heart disease plus heart disease medication use, stroke plus medication use, and ankle-brachial index. The areas under receiver operating curves of the 3-, 5- and 10-year predictive models varied between 0.97, 0.96, and 0.88 for all-cause mortality, and between 0.97, 0.98, and 0.84 for expanded CVD mortality. These mortality prediction models are valid and can be used as tools to identify the increased risk for mortality.

This study aimed to design chaos-based synchronized dynamic keys and develop an improved chaos-based advanced encryption standard (AES) algorithm with the proposed synchronized random keys. First, based on sliding mode control (SMC) technology, a rippling control scheme was introduced to guarantee the synchronization between master–slave discrete chaotic systems. Under the synchronization, the same dynamic random chaos signals could be simultaneously obtained at the transmitter and receiver in communication systems. Then, a novel modified AES cryptosystem with dynamic random keys based on chaos synchronization was presented. In a traditional AES cryptosystem, a static key is used, and it must be exchanged in advance and confirmed to be safely kept. However, in the proposed design, by introducing the synchronization technology of chaotic systems, the static key becomes dynamic and random, and it does not need to be kept or transmitted in open channels. Consequently, the disadvantage of key storage could be eliminated and the security of encryption could be improved. Finally, the developed chaos-based AES (CAES) algorithm has been applied to construct a novel image encryption algorithm. The statistical analysis, histogram, information entropy, and correlation indexes have been calculated and analyzed through simulation experiments in order to demonstrate the capability and improvement of this presented CAES cryptosystem.

This study is concerned with robust synchronization for master–slave chaotic systems with matched/mismatched disturbances and uncertainty in the control input. A robust sliding mode control (SMC) is presented to achieve chaos synchronization even under the influence of matched/mismatched disturbances and uncertainty of inputs. A proportional-integral (PI) switching surface is introduced to make the controlled error dynamics in the sliding manifold easy to analyze. Furthermore, by using the proposed SMC scheme even subjected to input uncertainty, we can force the trajectories of the error dynamics to enter the sliding manifold and fully synchronize the master–slave systems in spite of matched uncertainties and input nonlinearity. As for the mismatched disturbances, the bounds of synchronization errors can be well estimated by introducing the limit of the Riemann sum, which is not well addressed in previous works. Simulation experiments including matched and mismatched cases are presented to illustrate the robustness and synchronization performance with the proposed SMC synchronization controller.

Gene effects on osteoporosis have been studied separately and may have been masked by gene-gene and gene-environment interactions. We evaluated gene-gene and gene-physical activity interactions of the variants of tumor necrosis factor-α (TNF-α) and vitamin D receptor (VDR) genes on osteoporosis. A total of 472 elders were included. Seven variants (TNF-α: rs1799964, rs1800629, rs3093662; VDR: rs7975232, rs1544410, rs2239185, rs3782905) were genotyped. Bone mineral densities of the lumbar spine, femoral neck, and total hip were measured by dual-energy X-ray absorptiometry. Predictive models' ability to discriminate osteoporosis status was evaluated by areas under the receiver operating characteristics (AUROC) curve. After multivariable adjustment, significant interactions of TNF-α rs1800629 and VDR rs3782905 were observed on overall and lumbar spine osteoporosis. In elderly women, we found that those carrying the CG/CC genotype of VDR rs3782905 were significantly associated with increased odds of overall osteoporosis compared with those carrying the GG genotype of VDR rs3782905 among those carrying TNF-α rs1800629 GG genotype. The adjusted odds ratios (ORs) for VDR rs3782905 CG/CC genotype in elderly women carrying TNF-α rs1800629 AG/AA and GG genotypes were 0.1 (0.01, 0.98) and 3.54 (1.51, 8.30), respectively. We observed significant differences in AUROCs between the model with traditional covariates plus variants and their interaction term and the model with traditional covariates only (AUROCs: 0.77 and 0.81; p = 0.028). Although the sample size of this study may have been relatively small, our results suggest that the interaction of the CG/CC genotype of VDR rs3782905 with TNF-α rs1800629 GG genotype was associated with increased odds of overall and lumbar spine osteoporosis in elderly women.

The neodymium-doped yttrium aluminum garnet (Nd-YAG) laser is used for removal of pigmented skin patches and rejuvenation of skin. However, complications such as hyperpigmentation, hypopigmentation, and petechiae can occur after frequent treatments. Therefore, identifying the risk factors for such complications is important. The development of a multivariable logistic regression model with least absolute shrinkage and selection operator (LASSO) is needed to provide valid predictions about the incidence of post inflammatory hyperpigmentation complication probability (PIHCP) among patients treated with Nd-YAG laser toning. A total of 125 female patients undergoing laser toning therapy between January 2014 and January 2016 were examined for post-inflammatory hyperpigmentation (PIH) complications. Factor analysis was performed using 15 potential predictive risk factors of PIH determined by a physician. The LASSO algorithm with cross-validation was used to select the optimal number of predictive risk factors from the potential factors for a multivariate logistic regression PIH complication model. The optimal number of predictive risk factors for the model was five: immediate endpoints of laser (IEL), α-hydroxy acid (AHA) peels, Fitzpatrick skin phototype (FSPT), acne, and melasma. The area under the receiver operating characteristic curve (AUC) was 0.79 (95% CI, 0.70−0.88) in the optimal model. The overall performance of the LASSO-based PIHCP model was satisfactory based on the AUC, Omnibus, Nagelkerke R2, and Hosmer−Lemeshow tests. This predictive risk factor model is useful to further optimize laser toning treatment related to PIH. The LASSO-based PIHCP model could be useful for decision-making.

In this paper, a robust control design of chaos suppression is considered for generalized four-dimensional (4D) Lorenz−Stenflo systems subjected to matched/mismatched uncertainties and input nonlinearity. It is implemented by using rippling sliding mode control (SMC). A proportional-integral (PI) type scalar switching surface is designed such that the controlled dynamics in the sliding manifold becomes easy to analyze. Furthermore, only by using single rippling SMC even with input nonlinearity can we ensure the existence of the sliding mode for the controlled dynamics and suppress the chaotic behavior in a manner of rippling. Under the proposed control scheme, the chaos behavior in uncertain generalized 4D Lorenz−Stenflo systems subjected to mismatched uncertainties can be robustly suppressed to predictable bounds, which is not addressed in the literature. The numerical simulation results including matched/mismatched uncertainties and nonlinear inputs are presented to verify the robustness and validity of the rippling sliding mode controller.

In recent years, the development of the Intelligent Transportation System (ITS) has increased the popularity of vehicular ad hoc networks (VANET). A VANET is designed to enable vehicles to exchange information about traffic or vehicle conditions to help other vehicles avoid traffic accidents or traffic jams. To resist malicious attacks, all vehicles must be anonymous and their routings must be untraceable, but still verifiable. The vehicles must trust each other and communicate confidentially. In a VANET, Road Side Units (RSU) are installed on traffic signs or streetlights to help vehicles maintain anonymity, to authenticate messages, or to support confidentiality. However, the coverage of an RSU is limited and the cost of widespread installation is high. RSU installations are incremental, so messages must be authenticated using dense RSUs or sparse RSUs. In this paper, the concept of random key pre-distribution that is used in Wireless Sensor Networks (WSN) is modified to random secret pre-distribution (RSP), which integrates identity-based cryptography (IBC) to produce a message authentication scheme for VANETs in a sparse RSU environment. In the proposed scheme, vehicles follow a process to determine a common secret, allowing them to authenticate each other and obtain the pairing value as a key for use in message authentication and private communication. Evaluation results show that the proposed scheme outperforms related schemes.

Hepatitis C virus (HCV) infection is associated with increased systemic oxidative stress, which leads to cardiovascular events, diabetes, and chronic kidney disease. Similarly, cataract is also associated with increased oxidative stress. The association between HCV infection and increased risk of cataract remains unclear.A total of 11,652 HCV-infected patients and 46,608 age- and sex-matched non-HCV infected patients were identified during 2003-2011. All patient data were tracked until a diagnosis of cataract, death, or the end of 2011. Cumulative incidences and hazard ratios (HRs) were calculated.The mean follow-up durations were 5.29 and 5.86 years for the HCV and non-HCV cohorts, respectively. The overall incidence density rate for cataract was 1.36 times higher in the HCV cohort than in the non-HCV cohort (1.86 and 1.37 per 100 person-y, respectively). After adjusting for age, sex, comorbidities of diabetes, hypertension, hyperlipidemia, asthma, chronic obstructive pulmonary disease, coronary artery disease, and anxiety, patients with HCV infection had an increased risk of cataract compared with those without HCV infection [adjusted HR = 1.23, 95% confidence interval (CI) = 1.14-1.32]. HCV-infected patients receiving interferon-ribavirin therapy had a 1.83 times higher (95% CI = 1.40-2.38) risk of cataract than non-HCV infected patients did.HCV infection, even without the complication of cirrhosis, is associated with an increased risk of cataract, and this risk is higher in HCV-infected patients undergoing interferon-ribavirin therapy.

In wireless sensor networks, sensing information must be transmitted from sensor nodes to the base station by multiple hopping. Every sensor node is a sender and a relay node that forwards the sensing information that is sent by other nodes. Under an attack, the sensing information may be intercepted, modified, interrupted, or fabricated during transmission. Accordingly, the development of mutual trust to enable a secure path to be established for forwarding information is an important issue. Random key pre-distribution has been proposed to establish mutual trust among sensor nodes. This article modifies the random key pre-distribution to a random secret pre-distribution and incorporates identity-based cryptography to establish an effective method of establishing mutual trust for a wireless sensor network. In the proposed method, base station assigns an identity and embeds n secrets into the private secret keys for every sensor node. Based on the identity and private secret keys, the mutual trust method is utilized to explore the types of trust among neighboring sensor nodes. The novel method can resist malicious attacks and satisfy the requirements of wireless sensor network, which are resistance to compromising attacks, masquerading attacks, forger attacks, replying attacks, authentication of forwarding messages, and security of sensing information.

The prevalence of obesity and sarcopenia is high among the elderly. The simultaneous occurrence of these two disorders results in sarcopenic obesity. Research suggests that inflammation has an important role in the pathogenesis of obesity and sarcopenia. This study explores the impact of sarcopenic obesity on inflammatory markers, including interleukin-6 (IL-6), high-sensitivity C-reactive protein (hs-CRP), and tumor necrosis factor-alpha (TNF-α). This study is a community-based cross-sectional study. The study sample consisted of 844 community-dwelling people aged 65 years and older (448 men and 396 women). Sarcopenia was characterized by low muscle mass (skeletal muscle index < 6.87 and 5.46 kg/m2 for men and women, respectively), and obesity was characterized by excess body fat (body fat percentage greater than the 60th percentile of the study sample by sex [27.82% in men and 37.61% in women]). Older individuals identified with sarcopenic obesity were those who had both sarcopenia and obesity. Inflammatory markers such as IL-6, hs-CRP, and TNF-α were measured. The prevalence rates of obesity only, sarcopenia only, and sarcopenic obesity were 32.94%, 11.85%, and 7.23%, respectively. No difference was observed in the serum levels of IL-6 and TNF-α among the four groups of combined sarcopenia and obesity status. After multivariate adjustment, the serum hs-CRP levels in the obesity only and in the sarcopenic obesity groups were 0.14 and 0.16 mg/dL among males, respectively, which were significantly higher than that in the normal group (P=0.012 and 0.036). Our results provide evidence that obesity and sarcopenic obesity are associated with increased levels of serum hs-CRP among males.