Intraprocedural delayed reassessment of paravalvular regurgitation in TAVR significantly reduces the use of postdilatation.

OBJECTIVES: We sought to investigate the effect of a 15-min delayed intraprocedural reassessment of paravalvular aortic regurgitation (PVR) after an immediate evaluation of posttranscatheter aortic valve replacement (TAVR) on the regurgitation grading and usage of postdilatation. BACKGROUND: PVR after TAVR is associated with poor prognosis, but postdilatation may increase the risk of other complications. METHODS: In a prospective cohort of consecutive patients treated with balloon-expandable valve ES-3 ultra, the degree of PVR was assessed immediately and 15 min after that first evaluation (excluded severe cases), with the indication of postdilatation based on the delayed assessment. As a control group, the previous consecutive series of patients also treated with the same model of valve prosthesis was used. RESULTS: A total of 180 patients were included in the prospective study cohort and 152 in the retrospective control group. In the study group, the immediate PVR assessment showed none-trace 27.5%, mild 52%, moderate 19%, and severe 1.5%, and the delayed re-evaluation graded PVR as none-trace 83%, mild 15.6%, and moderate 1.2% (p < 0.001 as compared to immediate). In the control group, the immediate PVR assessment showed none-trace 33.5%, mild 52%, moderate 13%, and severe 1.5%. The rate of postdilatation was 2.8% in the study group versus 10.5% in the control group (p = 0.006). At discharge, no differences were observed between groups in PVR echocardiographic grading. CONCLUSIONS: A post-TAVR delayed intraprocedural reassessment of the PVR shows a clearly lower degree of regurgitation as compared to immediate evaluation, which significantly decreased the indication of postdilatation.

Increased IGFBP2 Levels by Placenta-Derived Mesenchymal Stem Cells Enhance Glucose Metabolism in a TAA-Injured Rat Model via AMPK Signaling Pathway.

The insulin resistance caused by impaired glucose metabolism induces ovarian dysfunction due to the central importance of glucose as a source of energy. However, the research on glucose metabolism in the ovaries is still lacking. The objectives of this study were to analyze the effect of PD-MSCs on glucose metabolism through IGFBP2-AMPK signaling and to investigate the correlation between glucose metabolism and ovarian function. Thioacetamide (TAA) was used to construct a rat injury model. PD-MSCs were transplanted into the tail vein (2 × 106) 8 weeks after the experiment started. The expression of the IGFBP2 gene and glucose metabolism factors (e.g., AMPK, GLUT4) was significantly increased in the PD-MSC group compared to the nontransplantation (NTx) group (* p < 0.05). The levels of follicular development markers and the sex hormones AMH, FSH, and E2 were also higher than those in the TAA group. Using ex vivo cocultivation, the mRNA and protein expression of IGFBP2, AMPK, and GLUT4 were significantly increased in the cocultivation with the PD-MSCs group and the recombinant protein-treated group (* p < 0.05). These findings suggest that the increased IGFBP2 levels by PD-MSCs play an important role in glucose metabolism and ovarian function through the IGFBP2-AMPK signaling pathway.

Estimation of Axle Torque for an Agricultural Tractor Using an Artificial Neural Network.

The objective of this study was to develop a model to estimate the axle torque (AT) of a tractor using an artificial neural network (ANN) based on a relatively low-cost sensor. ANN has proven to be useful in the case of nonlinear analysis, and it can be applied to consider nonlinear variables such as soil characteristics, unlike studies that only consider tractor major parameters, thus model performance and its implementation can be extended to a wider range. In this study, ANN-based models were compared with multiple linear regression (MLR)-based models for performance verification. The main input data were tractor engine parameters, major tractor parameters, and soil physical properties. Data of soil physical properties (i.e., soil moisture content and cone index) and major tractor parameters (i.e., engine torque, engine speed, specific fuel consumption, travel speed, tillage depth, and slip ratio) were collected during a tractor field experiment in four Korean paddy fields. The collected soil physical properties and major tractor parameter data were used to estimate the AT of the tractor by the MLR- and ANN-based models: 250 data points were used for developing and training the model were used, the 50 remaining data points were used to test the model estimation. The AT estimated with the developed MLR- and ANN-based models showed agreement with actual measured AT, with the R2 value ranging from 0.825 to 0.851 and from 0.857 to 0.904, respectively. These results suggest that the developed models are reliable in estimating tractor AT, while the ANN-based model showed better performance than the MLR-based model. This study can provide useful results as a simple method using ANNs based on relatively inexpensive sensors that can replace the existing complex tractor AT measurement method is emphasized.

Weakly Supervised Crop Area Segmentation for an Autonomous Combine Harvester.

Machine vision with deep learning is a promising type of automatic visual perception for detecting and segmenting an object effectively; however, the scarcity of labelled datasets in agricultural fields prevents the application of deep learning to agriculture. For this reason, this study proposes weakly supervised crop area segmentation (WSCAS) to identify the uncut crop area efficiently for path guidance. Weakly supervised learning has advantage for training models because it entails less laborious annotation. The proposed method trains the classification model using area-specific images so that the target area can be segmented from the input image based on implicitly learned localization. This way makes the model implementation easy even with a small data scale. The performance of the proposed method was evaluated using recorded video frames that were then compared with previous deep-learning-based segmentation methods. The results showed that the proposed method can be conducted with the lowest inference time and that the crop area can be localized with an intersection over union of approximately 0.94. Additionally, the uncut crop edge could be detected for practical use based on the segmentation results with post-image processing such as with a Canny edge detector and Hough transformation. The proposed method showed the significant ability of using automatic perception in agricultural navigation to infer the crop area with real-time level speed and have localization comparable to existing semantic segmentation methods. It is expected that our method will be used as essential tool for the automatic path guidance system of a combine harvester.

Estimation of carcass weight of Hanwoo (Korean native cattle) as a function of body measurements using statistical models and a neural network.

OBJECTIVE: The objective of this study was to develop a model for estimating the carcass weight of Hanwoo cattle as a function of body measurements using three different modeling approaches: i) multiple regression analysis, ii) partial least square regression analysis, and iii) a neural network. METHODS: Data from a total of 134 Hanwoo cattle were obtained from the National Institute of Animal Science in South Korea. Among the 372 variables in the raw data, 20 variables related to carcass weight and body measurements were extracted to use in multiple regression, partial least square regression, and an artificial neural network to estimate the cold carcass weight of Hanwoo cattle by any of seven body measurements significantly related to carcass weight or by all 19 body measurement variables. For developing and training the model, 100 data points were used, whereas the 34 remaining data points were used to test the model estimation. RESULTS: The R2 values from testing the developed models by multiple regression, partial least square regression, and an artificial neural network with seven significant variables were 0.91, 0.91, and 0.92, respectively, whereas all the methods exhibited similar R2 values of approximately 0.93 with all 19 body measurement variables. In addition, relative errors were within 4%, suggesting that the developed model was reliable in estimating Hanwoo cattle carcass weight. The neural network exhibited the highest accuracy. CONCLUSION: The developed model was applicable for estimating Hanwoo cattle carcass weight using body measurements. Because the procedure and required variables could differ according to the type of model, it was necessary to select the best model suitable for the system with which to calculate the model.

Procedural resources utilization and clinical outcomes with bioresorbable everolimus-eluting scaffolds and Pt-Cr everolimus-eluting stent with resorbable abluminal polymer in clinical practice. A randomized trial.

OBJECTIVES: We sought to compare the procedural implications of using bioresorbable everolimus-eluting scaffolds (BVS) and Pt-Cr everolimus-eluting stent with abluminal bioabsorbable polymer (Synergy). BACKGROUND: There are important differences in the respective platforms, which could impact on procedural performance, complications and outcomes. METHODS: A prospective, randomized single center study including consecutive patients in stable clinical condition and with lesions amenable to be treated with BVS according to predefined criteria. Patients were randomized to either treatment with BVS or Synergy. All procedural data were collected and 12 months clinical follow up conducted. Primary objectives were fluoroscopy time, median dose-area product, contras agent volumen, and peri-procedural troponin release. RESULTS: A total of 200 patients were included, 100 in BVS group and 100 in Synergy group. No significant differences were observed in baseline clinical and angiographic characteristics. Predilatation (97.6 vs. 25.4%; P < 0.001), postdilatation (64.8 vs. 38.4%: P < 0.01), and use of 2 wires (20.8 vs. 10%; P = 0.02) were more frequent with BVS. The BVS group showed a significant increase in fluoroscopy time (18%), dose-area product (20%), and contrast volume (10%). Post-procedural increase of creatinine was similar and amount of TnI release was significantly higher with BVS but incidence of peri-procedural infarction was comparable. Clinical outcomes at 12 months were similar with definite thrombosis being 1% with BVS and 0% with Synergy. CONCLUSIONS: The use of BVS in comparison with the Synergy stent in a similar lesional setting is associated with a higher use of resources in the procedure, more radiation, and higher TnI release. © 2016 Wiley Periodicals, Inc.

Early healing assessment with optical coherence tomography of everolimus-eluting stents with bioabsorbable polymer (synergy™) at 3 and 6 months after implantation.

OBJECTIVES: In this study we sought to evaluate coverage and apposition of Synergy™ stent at 3 and 6 months after implantation. BACKGROUND: The Pt-Cr everolimus-eluting stent with abluminal bioabsorbable polymer (Synergy™) is a new generation drug-eluting stent with features potentially favoring an early healing process which could make safe a shorter period of dual antiplatelet-therapy treatment. METHODS: Prospective, two-centers study enrolling patients with similar lesions treated with Synergy™ stents undergoing examination with OCT at 3 and 6 months in the respective centers. Blinded analysis was done at a core lab. Co-primary endpoints were proportion of struts with coverage and with apposition at 3 and 6 months. RESULTS: Finally, 22 patients (30 stents) in the 3 months group and 20 patients (30 stents) in the 6 months group were included. There were no significant differences between groups regarding clinical, angiographic measurements, and procedural data. The rate of strut coverage was 94.5% at 3 months and 96.6% at 6 months (P < 0.001), the rates of apposition were 93.8% and 96.2%, respectively, (P < 0.001), the proportion of uncovered but apposed struts was 2.5% and 1.9% (P = 0.03) and the proportion of uncovered and malapposed struts was 3% and 1.8%, respectively (P < 0.001). The maximal area of malapposition related with uncovered struts was 0.43 ± 0.4 mm(2) at 3 months and 0.14 ± 0.2 mm(2) at 6 months (P = 0.001). CONCLUSIONS: The everolimus-eluting stent with absorbable polymer, Synergy™, is associated to a high degree of intimal coverage and apposition at 3 months after implantation with additional increase at 6 months. © 2015 Wiley Periodicals, Inc.

A 10-Channel, 120 nW/Channel Reconfigurable Capacitance-to-Digital Converter for Sub-µW Robust Wearable Sensing.

This paper presents a 10-channel, 120 nW/channel, reconfigurable capacitance-to-digital converter (CDC) enabling sub-µW wearable sensing applications. The proposed multi-channel architecture supports 10 channels with a shared reconfigurable 6-bit differential analog-to-digital converter (ADC). The reconfigurable nature of the CDC enables adaptive sensing range and sensing speed based on the target application. Furthermore, the architecture performs both on/off-chip parasitic correction and baseline calibration to measure the change in capacitance (ΔC), excluding baseline and parasitic capacitances. The experimental results show the measurement range of ΔC are 5.34 pF for 1x sensitivity and 1.8 pF for 3x sensitivity respectively. The capacitive divider-based architecture excludes power-hungry operational trans-impedance amplifiers for capacitance to voltage conversion, and the architecture supports programmable channel access to activate or deactivate each channel independently. The random interrupt protection logic avoids any broken sample or data error in a sampling window. Additionally, the channel monitoring logic helps keep track of specific channel information. The measured silicon result shows a total power consumption of 1.2 µW for 1.6 kHz sampling frequency when driven by a 32 kHz clock, which is 8.6x less than prior works. The CDC is also tested with DMMP (dimethyl-methylphosphonate) gas sensor in gas chromatography (GC). Implemented in 65 nm CMOS process, the 10-channel CDC occupies 0.251 mm2 of active area (0.0251 mm2/Ch).

sEMG-based Sarcopenia risk classification using empirical mode decomposition and machine learning algorithms.

Early detection of the risk of sarcopenia at younger ages is crucial for implementing preventive strategies, fostering healthy muscle development, and minimizing the negative impact of sarcopenia on health and aging. In this study, we propose a novel sarcopenia risk detection technique that combines surface electromyography (sEMG) signals and empirical mode decomposition (EMD) with machine learning algorithms. First, we recorded and preprocessed sEMG data from both healthy and at-risk individuals during various physical activities, including normal walking, fast walking, performing a standard squat, and performing a wide squat. Next, electromyography (EMG) features were extracted from a normalized EMG and its intrinsic mode functions (IMFs) were obtained through EMD. Subsequently, a minimum redundancy maximum relevance (mRMR) feature selection method was employed to identify the most influential subset of features. Finally, the performances of state-of-the-art machine learning (ML) classifiers were evaluated using a leave-one-subject-out cross-validation technique, and the effectiveness of the classifiers for sarcopenia risk classification was assessed through various performance metrics. The proposed method shows a high accuracy, with accuracy rates of 0.88 for normal walking, 0.89 for fast walking, 0.81 for a standard squat, and 0.80 for a wide squat, providing reliable identification of sarcopenia risk during physical activities. Beyond early sarcopenia risk detection, this sEMG-EMD-ML system offers practical values for assessing muscle function, muscle health monitoring, and managing muscle quality for an improved daily life and well-being.

Effect of total knee replacement on skeletal muscle mass measurements using dual energy X-ray absorptiometry.

Sarcopenia is becoming prevalent in an increasing number of older adults undergoing total knee replacement (TKR) surgery. Metal implants may overestimate lean mass (LM) measured using dual-energy X-ray absorptiometry (DXA). This study aimed to examine the effects of TKR on LM measurements according to automatic metal detection (AMD) processing. The participants from Korean Frailty and Aging Cohort Study, who had underwent TKR were enrolled. A total of 24 older adults (mean age 76.4 ± 4.0 years, 92% female) were included in the analysis. The SMI with AMD processing was 6.1 ± 0.6 kg/m2, which was lower than that without AMD processing of 6.5 ± 0.6 kg/m2 (p < 0.001). The LM of the right leg with AMD processing was lower than that without AMD in 20 participants who had underwent TKR surgery on the right (5.5 ± 0.2 kg vs. 6.0 ± 0.2 kg, p < 0.001), and that of the left leg was also lower in with AMD processing than in without AMD processing in 18 participants who had underwent TKR surgery on the left (5.7 ± 0.2 kg vs. 5.2 ± 0.2 kg, p < 0.001). Only one participant was classified as having low muscle mass without AMD processing, but this came to four after AMD processing. LM assessment in individuals who had TKR could be significantly different according to the use of AMD.

Utilization of Electrical Conductivity to Improve Prediction Accuracy of Cooking Loss of Pork Loin.

This study investigated the predictability of cooking loss of pork loin through relatively easy and quick measurable quality properties. The pH, color, moisture, protein content, and cooking loss of 100 pork loins were measured. The explanatory variables included in all linear regression models with an adjust-r2 value of ≥0.5 were pH and the protein content. In the linear regression model predicting cooking loss, the highest adjust-r2 value was 0.7, with pH, CIE L*, CIE b*, moisture, and protein content as the explanatory variables. In 30 pork loins, electrical conductivity was additionally measured, and as a result of linear regression analysis for predicting cooking loss, the highest adjust-r2 value was 0.646 with electrical conductivity measured at 40 Hz, with pH and color as the explanatory variables. Ordinal logistic regression analysis was performed to predict the three grades (low, middle, and high) of loin cooking loss using pH, color, and 40 Hz electrical conductivity as the explanatory variables, and the percent concordance was 93.8%. In conclusion, the addition of electrical conductivity as an explanatory variable did not increase the prediction accuracy of the linear regression model for predicting cooking loss; however, it was demonstrated that it is possible to predict and classify the cooking loss grade of pork loin through quality properties that can be measured quickly and easily.

The Dose-Related Efficacy of Human Placenta-Derived Mesenchymal Stem Cell Transplantation on Antioxidant Effects in a Rat Model with Ovariectomy.

Oxidative stress initiates various degenerative diseases, and it is caused by excessive reactive oxygen species (ROS) production. Oxidative stress is a key factor that causes infertility by inducing ovarian dysfunction, characterized by irregular hormone levels, lower quality of mature follicles, and loss of follicles. Hence, stem cell therapy has been actively studied as an approach to overcome the side effects of hormone replacement therapy (HRT) on ovarian dysfunction. However, there is a lack of evidence about the appropriate number of cells required for stem cell therapy. Therefore, based on the antioxidant effects investigated in this study, we focused on determining the appropriate dose of stem cells for transplantation in an animal model with ovarian dysfunction. One week after half-ovariectomy, placenta-derived mesenchymal stem cells (PD-MSCs, 1 × 105 cells, 5 × 105 cells, or 2.5 × 106 cells) were injected intravenously into the Tx groups through the tail vein. As a result, the mRNA expression of hAlu gradually increased as the transplanted cell concentration increased. Compared with no transplantation (NTx), the transplantation of PD-MSCs improved folliculogenesis, including the levels of secreted hormones and numbers of follicles, by exerting antioxidant effects. Also, the levels of oxidized glutathione in the serum of animal models after transplantation were significantly increased (* p < 0.05). These results indicated that PD-MSC transplantation improved ovarian function in half-ovariectomized rats by exerting antioxidant effects. According to our data, increasing the number of transplanted cells did not proportionally increase the effectiveness of the treatment. We suggest that low-dose PD-MSC transplantation has the same therapeutic effect as described in previous studies. These findings provide new insights for further understanding reproductive systems and provide evidence for related clinical trials.

Modeling of the control logic of a UASS based on coefficient of variation spraying distribution analysis in an indoor flight simulator.

Introduction: In the past decade, unmanned aerial spraying systems (UASS) have emerged as an effective crop treatment platform option, competing with other ground vehicle treatments. The development of this platform has provided an effective spraying system that can be used on all crop types and in all weather conditions. However, related research has not been able to develop a UASS that can be operated in windy conditions with a low drift percentage. Methods: In this research, spraying was simulated in an indoor flight simulator by considering flight speed, altitude, wind speed, wind direction, rotor rotation, interval, spraying pattern, and nozzle type, which were used as the parameters affecting the output value of the coefficient of variation (CV) of spraying. These parameters were referenced as properties that occur in the field, and using machine learning methods, the CV value was used as a dataset to develop a model that can execute pump opening by controlling the flow rate. There are four machine learning methods used, i.e. random forest regression, gradient boosting, ada boost, and automatic relevance determination regression which are compared with simple linear regression and ridge regression as linear regression. Results: The results revealed that the random forest regression model was the most accurate, with R2 of 0.96 and root mean square error (RMSE) of 0.04%. The developed model was used to simulate spraying with pump opening A, which connects two nozzles in front, and pump opening AB, which connects all four nozzles. Discussion: Using the logic based on CV value and pesticide quantity, the model can execute the pump opening against the environment and UASS operation.

A new integrative approach to assess aortic stenosis burden and predict objective functional improvement after TAVR.

Background: A non-negligible rate of patients undergoing transcatheter aortic valve replacement (TAVR) do not report symptomatic improvement or even die in the short-midterm. We sought to assess the degree of objective functional recovery after TAVR and its prognostic implications and to develop a predictive model. Methods: In a cohort of patients undergoing TAVR, a prospective evaluation of clinical, anatomical, and physiological parameters was conducted before and after the procedure. These parameters were derived from echocardiography, non-invasive analysis of arterial pulse waves, and cardiac tomography. Objective functional improvement 6 months after TAVR was assessed using a 6-min walk test and nitro-terminal pro-brain natriuretic peptide (NT-proBNP) levels. The derived predictive model was prospectively validated in a different cohort. A clinical follow-up was conducted at 2 years. Results: Among the 212 patients included, objective functional improvement was observed in 169 patients (80%) and subjective improvement in 187 (88%). Patients with objective functional improvement showed a much lower death rate at 2 years (9% vs. 31% p = 0.0002). Independent predictors of improvement were as follows: mean aortic gradient of ≥40 mmHg, augmentation index75 of ≥45%, the posterior wall thickness of ≤12 mm, and absence of atrial fibrillation. A simple integer-based point score was developed (GAPA score), which showed an area under the curve of 0.81 for the overall cohort and 0.78 for the low-gradient subgroup. In a validation cohort of 216 patients, these values were 0.75 and 0.76, respectively. Conclusion: A total of 80% of patients experienced objective functional improvement after TAVR, showing a significantly lower 2-year mortality rate. A predictive score was built that showed a good discriminative performance in overall and low-gradient populations.

First description and validation of a new method for estimating aortic stenosis burden and predicting the functional response to TAVI.

Background: Up to one-fifth of patients continue to have poor quality of life after transcatheter aortic valve implantation (TAVI), with an additional similar proportion not surviving 1 year after the procedure. We aimed to assess the value of a new method based on an integrated analysis of left ventricular outflow tract flow velocity and aortic pressure to predict objective functional improvement and prognosis after TAVI. Methods: In a cohort of consecutive patients undergoing TAVI, flow velocity-pressure integrated analysis was obtained from simultaneous pressure recordings in the ascending aorta and flow velocity recordings in the left ventricular outflow tract by echocardiography. Objective functional improvement 6 months after TAVI was assessed through changes in a 6-min walk test and NT-proBNP levels. A clinical follow-up was conducted at 2 years. Results: Of the 102 patients studied, 82 (80.4%) showed objective functional improvement. The 2-year mortality of these patients was significantly lower (9% vs. 44%, p = 0.001). In multivariate analysis, parameter "(Pressure at Vmax - Pressure at Vo)/Vmax" was found to be an independent predictor for objective improvement. The C-statistic was 0.70 in the overall population and 0.78 in the low-gradient subgroup. All echocardiographic parameters and the valvuloarterial impedance showed a C-statistic of <0.6 for the overall and low-gradient patients. In a validation cohort of 119 patients, the C-statistic was 0.67 for the total cohort and 0.76 for the low-gradient subgroup. Conclusion: This new method allows predicting objective functional improvement after TAVI more precisely than the conventional parameters used to assess the severity of aortic stenosis, particularly in low-gradient patients.

Overlapping versus single long stents in long chronic total occlusions: insights of the Iberian CTO Registry.

BACKGROUND: It is unknown whether the availability of long drug-eluting stents modify the PCI strategy of long CTO. To describe the contemporary PCI strategy of long chronic total occlusions (CTO) using overlapping (OS) or single long stents (SS) and to analyze its results. METHODS: 2842 consecutive CTO PCIs were included. Those with an occlusion length ≥20 mm in which ≥1 drug eluting stent (DES) was implanted were analyzed. We compared procedural characteristics and clinical outcomes of CTO treated with OS or SS. RESULTS: 1088 CTO PCIs were analyzed (79.9% males; 64.7±10.6 years). Mean J-score was 2.8±0.9. A SS was used in 38.5% of cases and OS in 61.5%. Total stent length was 64.1±29.9 mm; it was higher in the OS group (OS: 79.9±25.5 mm vs. SS: 38.3±14.7 mm; P<0.0001). Mean number of stents in the OS group was 2.3±1. Very long stents (≥40 mm) were used in 27.4% of cases, more frequently in the OS group (OS:32.4% vs. SS:19.3%; P<0.0001). After a mean follow-up of 19±15.9 months, the rate of adverse events (MACE) was 2% (cardiac death: 1.6%, myocardial infarction: 1.6%, target lesion revascularization: 1.9% and stent thrombosis: 0.18%) with no significant differences between both groups. Overlapping was not an independent predictor of MACE. CONCLUSIONS: In long CTO PCIs, OS is more frequently used than single stenting, especially in more complex procedures. Clinical outcomes at a mid-term follow-up are favorable. Using newer generation DES, overlapping was not an independent predictor of MACE; however, a trend toward a higher event rate was observed in the OS group.

Common and different characteristics among combinations of physical frailty and sarcopenia in community-dwelling older adults: The Korean Frailty and Aging Cohort Study.

AIM: Physical frailty and sarcopenia are geriatric syndromes associated with adverse health outcomes. However, the common and different conditions associated with physical frailty and sarcopenia remain unclear. This study aimed to compare the clinical characteristics of older adults with physical frailty and sarcopenia. METHODS: This cross-sectional study analyzed 2028 community-dwelling older adults, aged 70-84 years (mean age 75.9 ± 4.0 years; 50.1% men). Physical frailty was defined using the Fried frailty phenotype, whereas sarcopenia was defined using the Asian Working Group for Sarcopenia 2014 and 2019 criteria. RESULTS: The prevalence of physical frailty was 5.5%, whereas that of sarcopenia, using the Asian Working Group for Sarcopenia 2014 and 2019, was 9.1% and 17.5%, respectively. The concordance of physical frailty with sarcopenia was higher in the Asian Working Group for Sarcopenia 2019 criteria than in 2014. Frail-only participants had a higher incidence of disability, cognitive dysfunction, poor self-perceived health, and depressive symptoms than the sarcopenic-only participants. Frail-and-sarcopenic participants showed a lower body mass index (≥23 kg/m2 ) than frail-only participants. Furthermore, in frail-and-sarcopenic participants, recurrent falls (16.9% vs 5.5%) were higher than in the neither-frail-nor-sarcopenic participants; falls with fracture (11.5% vs 1.7%) and fear of falling (59.0% vs 36.7%) were higher in frail-and-sarcopenic participants than in sarcopenic-only participants. CONCLUSIONS: This study showed significant differences between physical frailty and sarcopenia among community-dwelling older adults. Older adults with physical frailty and sarcopenia were more likely to have higher fall-related outcomes than the others. Geriatr Gerontol Int 2022; 22: 42-49.

Prediction of cooking loss of pork belly using quality properties of pork loin.

The predictability of cooking loss in pork belly using the quality properties of pork loin was investigated. Pork belly at the 6th thoracic vertebra and pork loin at the 14th thoracic vertebra from 120 pork carcasses were used in this study. Quality properties, such as pH, proximate composition, color (L*, a*, and b* values), and cooking loss were measured. Linear regression analysis showed that the L*, a*, and b* values of pork loin were significant variables for predicting the cooking loss of pork belly (P < 0.05). However, the adjusted correlation coefficient (R2) of the linear regression was 0.51. Logistic regression analysis for the prediction of cooking loss groups (low, middle, and high) of pork belly, with the L*, a*, and b* values as the independent variables, resulted in 84% concordance. Pork carcasses can be sorted based on the cooking loss groups of pork belly by using the color parameters of pork loin.

Therapeutic Effects of Functional Electrical Stimulation on Physical Performance and Muscle Strength in Post-stroke Older Adults: A Review.

Stroke-related disabilities cause poor physical performance, especially among older adults, and can lead to sarcopenia. Functional electrical stimulation (FES) has been used to improve physical performance in individuals with neurological disorders and increase muscle mass and strength to counteract muscle atrophy. This review covers the principles, underlying mechanisms, and therapeutic effects of FES on physical performance and skeletal muscle function in post-stroke older adults. We found that FES restored weakened dorsiflexor and hip abductor strength during the swing and stance phases of gait, respectively, to help support weight-bearing and upright posture and facilitate static and dynamic balance in this population. FES may also be effective in improving muscle mass and strength to prevent muscle atrophy. However, previous studies on this topic in post-stroke older adults are scarce, and further studies are needed to confirm this supposition.

Clinical Predictors for Procedural Stroke and Implications for Embolic Protection Devices during TAVR: Results from the Multicenter Transcatheter Aortic Valve Replacement In-Hospital Stroke (TASK) Study.

Background: Data to support the routine use of embolic protection devices for stroke prevention during transcatheter aortic valve replacement (TAVR) are controversial. Identifying patients at high risk for peri-procedural cerebrovascular events may facilitate effective patient selection for embolic protection devices during TAVR. Aim: To generate a risk score model for stratifying TAVR patients according to peri-procedural cerebrovascular events risk. Methods and results: A total of 8779 TAVR patients from 12 centers worldwide were included. Peri-procedural cerebrovascular events were defined as an ischemic stroke or a transient ischemic attack occurring ≤24 h from TAVR. The peri-procedural cerebrovascular events rate was 1.4% (n = 127), which was independently associated with 1-year mortality (hazards ratio (HR) 1.78, 95% confidence interval (CI) 1.06−2.98, p < 0.028). The TASK risk score parameters were history of stroke, use of a non-balloon expandable valve, chronic kidney disease, and peripheral vascular disease, and each parameter was assigned one point. Each one-point increment was associated with a significant increase in peri-procedural cerebrovascular events risk (OR 1.96, 95% CI 1.56−2.45, p < 0.001). The TASK score was dichotomized into very-low, low, intermediate, and high (0, 1, 2, 3−4 points, respectively). The high-risk TASK score group (OR 5.4, 95% CI 2.06−14.16, p = 0.001) was associated with a significantly higher risk of peri-procedural cerebrovascular events compared with the low TASK score group. Conclusions: The proposed novel TASK risk score may assist in the pre-procedural risk stratification of TAVR patients for peri-procedural cerebrovascular events.