Search Results (48)

Background/Objectives: Biventricular pacing (BVP) to deliver cardiac resynchronization therapy (CRT) is a standard intervention for heart failure, yet suboptimal response remains common due to challenges in left ventricular (LV) lead placement. Left bundle branch area pacing (LBBAP) has emerged as a promising alternative, offering physiological activation via direct conduction system engagement. However, comparative data on electrocardiographic (ECG) and procedural outcomes between LBBAP-CRT and BVP-CRT are limited. Methods: This retrospective, single-center study compared LBBAP-CRT and BVP-CRT in 114 patients with left bundle branch block and LV ejection fraction ≤ 35%. LBBAP-CRT was performed using a Medtronic SelectSecure™ 3830 lead via a fixed-curve sheath Medtronic C315HIS, with successful capture confirmed by ECG criteria (Qr/qR in V1, LV activation time < 100 ms). BVP-CRT involved coronary sinus LV lead placement. Outcomes included QRS duration, pacing thresholds, complications, and procedural metrics. Statistical analysis employed logistic regression to identify predictors of optimal pacing thresholds (≤1.0 V at 0.5 ms). Results: LBBAP-CRT yielded greater degree of QRS narrowing than BVP-CRT (136.7 ± 13.5 ms vs. 147.2 ± 14.6 ms, p < 0.001) and lower pacing thresholds (p < 0.05). Complications occurred in 18.1% of BVP-CRT patients (phrenic nerve stimulation, lead dislocation) versus none in LBBAP-CRT (p = 0.011). According to the multivariable analysis LBBAP-CRT was associated with an optimal thresholds (p = 0.007), alongside lower E/e′ ratio and lead impedance. Conclusions: LBBAP-CRT was associated with superior electrical resynchronization, fewer complications, and better pacing thresholds compared to BVP, suggesting its potential as a preferred CRT strategy. Larger randomized trials are needed to validate long-term outcomes. Full article

Quantitative analyses in drug-delivery research are frequently distributed across multiple tools, which increases manual handling and the risk of transcription errors. NanoEDW 1.0 is an open source Python application that integrates calibration-curve generation, encapsulation-efficiency (EE%) calculation, and release kinetics modeling in a single, streamlined workflow. This study aims to validate the performance of NanoEDW 1.0 by benchmarking it against spreadsheet/OriginLab^® OriginPro 2025 analyses on experimental datasets from polymeric nanocarrier systems commonly used in drug encapsulation. The software performs linear regression to convert absorbance into concentration, computes EE% from raw experimental values, and fits drug-release profiles to classical models (including zero/first-order, Higuchi, Korsmeyer–Peppas, Weibull, and Modified Gompertz) using non-linear least squares with standard goodness-of-fit metrics (R², RMSE). Results show close agreement with reference workflows for calibration parameters and EE%, as well as statistically comparable release-model fits, while reducing manual steps and analysis time. In conclusion, the validation confirms that NanoEDW 1.0 can streamline routine analyses and enhance reproducibility and accessibility in nanopharmaceutical research; source code and example datasets are provided to foster adoption. Full article

The escalating demand for sustainable development in the built environment necessitates the integration of innovative, system-based assessment tools. This study investigates the role of energy efficiency (EE) within a nature-inspired sustainability assessment framework, drawing from biomimicry principles to evaluate green building practices in South Africa. Grounded in the ethos of nature’s efficiency, such as closed-loop energy systems, passive energy use, efficiency through form and function, and decentralised and localised energy generation, this study identifies and prioritises key EE criteria, including efficient energy management, renewable energy optimisation, passive heating, ventilation and air conditioning (HVAC) systems, and energy-saving technologies. Using the Analytic Hierarchy Process (AHP), this research engaged 38 highly experienced, practising, and registered construction professionals to perform pairwise comparisons of EE criteria. Results revealed that efficient energy management (29.8%) emerged as the most significant factor, followed closely by energy-saving equipment (26.4%), with strong expert consensus (consistency ratio = 0.03). The findings reflect a convergence of ecological wisdom and industry expertise, suggesting that nature’s design strategies offer a compelling roadmap for achieving sustainable energy performance in buildings. This study reinforces the applicability of biomimicry in shaping context-specific sustainability metrics and informs the development of adaptive, ecologically aligned certification frameworks. This study recommends the integration of these EE criteria into building rating systems, fostering interdisciplinary collaboration, and scaling nature-based frameworks to inform global sustainability practice. By bridging theory and application, this study advances a regenerative approach to construction that aligns with the UN Sustainable Development Goals and long-term environmental resilience. Full article

Environmental enrichment (EE) is a vital component of modern zoo husbandry, improving welfare by encouraging natural behaviours and supporting ex situ conservation goals. While EE is widely integrated into the management of many taxa, its welfare benefits remain poorly understood for certain species. The armadillos are examples of such species—underrepresented in research with few targeted EE strategies. Importantly, although olfaction is recognised as their primary sensory modality, methods to promote behaviour linked to olfaction (e.g., exploration and foraging) remain unclear. This review synthesises knowledge on EE for armadillos, using Bloomsmith’s five categories of enrichment and Positive Reinforcement Training (PRT) as a framework. We identify species-typical behaviours to maintain in captivity, consider their ecological relevance in the wild, and explore how tailored EE and PRT can adjust environments. We then evaluate how such approaches can enhance behavioural outcomes, support visitor engagement, and promote welfare critical for in situ and ex situ conservation. Furthermore, we highlight EE’s role in safeguarding adaptive traits for population sustainability and argue that integrating EE and PRT into a broader One Plan Approach provides a pathway for aligning ex situ management with wild ecology. Finally, we identify key gaps, emphasising multi-institutional collaboration, standardised metrics, and long-term research to guide evidence-based practices for armadillos. Full article

Background: Coronary artery disease (CAD) and left-ventricular (LV) diastolic dysfunction are leading drivers of morbidity and mortality. Clarifying how anatomical CAD burden relates to diastolic impairment may refine diagnosis and risk stratification. Methods: We conducted a cross-sectional analytical study of 200 adults with intermediate pretest probability of CAD who underwent both coronary CT angiography (CCTA) and transthoracic echocardiography (TTE) within ≤1 year. Coronary burden was quantified by Segment Involvement Score (SIS). Diastolic function was graded by contemporary echocardiographic guidelines. Patients were classified as obstructive (≥50% LM or ≥70% in other major epicardial arteries) or non-obstructive CAD. Results: Obstructive CAD was present in 73/200 (36.5%). Diastolic dysfunction occurred in 161/200 (80.5%) and was markedly more prevalent/severe in obstructive vs. non-obstructive CAD (p < 0.001). SIS rose stepwise with higher diastolic dysfunction grades; SIS correlated strongly with diastolic grade (r = 0.809, p < 0.001). Compared with non-obstructive CAD, obstructive CAD showed worse diastolic indices (higher E/e′, larger LAVI, shorter DT and IVRT; all p < 0.001) and a shift toward Grades II–III. Obstructive CAD was also associated with higher total cholesterol, triglycerides, LDL, HbA1c, lower HDL (all p ≤ 0.002), and a greater prevalence of hypertension and diabetes. Discussion: Increasing coronary atherosclerotic burden—captured by SIS, parallels progressive impairment of LV relaxation and elevated filling pressures, supporting a pathophysiologic link between epicardial disease extent and diastolic dysfunction. Conclusions: In symptomatic intermediate-risk patients, greater CAD extent on CCTA is strongly associated with higher grades of LV diastolic dysfunction on echocardiography. Integrating anatomic (SIS) and functional (TTE) metrics may enhance risk assessment and guide management in CAD. Full article

Background: Paroxysmal atrial fibrillation (PAF) is a common arrhythmia often treated with catheter ablation, particularly pulmonary vein isolation (PVI). However, recurrence remains frequent and is often linked to unrecognized structural and functional remodeling of the left atrium. Methods: We introduce the Echocardiographic Atrial Strain and conduction Evaluation (EASE) score as a theoretical, noninvasive model to stratify recurrence risk in patients undergoing catheter ablation for PAF. The score is based on the hypothesis that integrated echocardiographic parameters can reflect the extent of atrial remodeling relevant to ablation outcomes. Results: The EASE score combines six echocardiographic metrics—left atrial reservoir strain (LASr), atrial conduction time (PA-TDI), left atrial volume index (LAVI), stiffness index (E/e′/LASr), E/e′ ratio, and contractile strain (LASct)—each representing structural, electrical, or mechanical remodeling. The total score ranges from 0 to 12, stratifying patients into low, intermediate, and high-risk categories for arrhythmia recurrence. Preliminary retrospective data suggest a significant association between higher EASE scores and increased recurrence rates following ablation. Conclusions: The EASE score offers a biologically plausible, multidimensional framework for noninvasive risk prediction in PAF ablation. Prospective studies are warranted to validate its clinical utility and refine its structure. Full article

Promoting environmental stewardship among youths is crucial for inspiring collaborative, multi-generational actions to tackle long-term environmental challenges. This research study explores the impact of an environmental education (EE) field trip, which highlighted wastewater management and renewable energy technology, on high school students using the revised new ecological paradigm (NEP) scale as a key metric in a pre-post survey, which uses traditionally pro (NEP) and anti (dominant social paradigm, DSP) conservationist statements to measure beliefs towards the environment. When applying the Wilcoxon signed-rank test (null hypothesis t = 0, no change) to the series of environmental stewardship action questions “___ is an extremely important part of protecting the environment”, we identified ten out of the thirteen scale questions to show significant change, all of which were positive. Additionally, the overall impact score was positive and significant (p ≤ 0.05). This finding demonstrates that respondents felt more strongly that these variables played a role in protecting the environment after experiencing the field trip. This suggests that exposure to environmental management intervention strategies utilizing man-made infrastructure and technology may enhance human capability to positively influence the environment and mitigate environmental threats, potentially alleviating concerns about environmental issues. These results suggest that environmental stewardship in youth needs to be reconceptualized in an increasingly STEM-focused world, and a new metric should be developed to assess environmental beliefs. Full article

Short-chain fatty acids (SCFA), particularly propionate and butyrate, reduce food intake, body weight, and modulate gut microbiota composition. However, it is unclear whether encapsulation of propionate and butyrate enhances their delivery to distal gut to improve energy balance and gut microbiota composition in obesity. Objectives: We determined the effects of microencapsulated propionate and butyrate on energy balance, gut microbiota and metabolite composition in obese rats. Methods: In experiment-1, obese male Sprague-Dawley rats were fed microencapsulated propionate and butyrate (5–10% wt/wt) or control high-fat diet. In experiment-2, obese rats were fed 10% microencapsulated propionate and butyrate, non-encapsulated butyrate (10% wt/wt), and pair-fed to non-capsulated butyrate. Food intake, energy expenditure (EE), sympathetic-mediated EE changes by propranolol, body composition, gut microbiota and fecal and plasma metabolites were analyzed. Results: Microencapsulated propionate decreased caloric intake, weight and fat mass, while microencapsulated butyrate had modest effects. Non-encapsulated butyrate reduced intake and prevented weight gain beyond pair-fed controls. Microencapsulated propionate and non-encapsulated butyrate reduced respiratory quotient suggestive of a shift towards lipid utilization, and enhanced β-adrenergic-mediated EE. Microencapsulated propionate and butyrate altered alpha and beta diversity metrics, microencapsulated propionate increased Verrucomicrobiae, microencapsulated butyrate increased Lactobacillaceae, and microencapsulated propionate and butyrate reduced Erysipelotrichia. Microencapsulated propionate and butyrate increased fecal amino acids and altered select plasma metabolites; microencapsulated propionate increased fecal and plasma propionate, supporting distal gut delivery. Conclusions: Dietary supplementation with microencapsulated propionate and butyrate improved energy balance, enhanced lipid utilization, beneficially modulated gut microbiota composition, and altered metabolite profiles in obese rats. Full article

The Internet of Things (IoT) has revolutionized modern communication systems by enabling seamless connectivity among low-power devices. However, the increasing demand for high-performance wireless networks necessitates advanced frameworks that optimize both energy efficiency (EE) and security. Cell-free massive multiple-input multiple-output (CF m-MIMO) has emerged as a promising solution for IoT networks, offering enhanced spectral efficiency, low-latency communication, and robust connectivity. Nevertheless, balancing EE and security in such systems remains a significant challenge due to the stringent power and computational constraints of IoT devices. This study employs secrecy energy efficiency (SEE) as a key performance metric to evaluate the trade-off between power consumption and secure communication efficiency. By jointly considering energy consumption and secrecy rate, our analysis provides a comprehensive assessment of security-aware energy efficiency in CF m-MIMO-based IoT networks. To enhance SEE, we introduce a hybrid deep-learning (DL) framework that integrates convolutional neural networks (CNN) and long short-term memory (LSTM) networks for joint EE and security optimization. The CNN extracts spatial features, while the LSTM captures temporal dependencies, enabling a more robust and adaptive modeling of dynamic IoT communication patterns. Additionally, a multi-objective improved biogeography-based optimization (MOIBBO) algorithm is utilized to optimize hyperparameters, ensuring an improved balance between convergence speed and model performance. Extensive simulation results demonstrate that the proposed MOIBBO-CNN–LSTM framework achieves superior SEE performance compared to benchmark schemes. Specifically, MOIBBO-CNN–LSTM attains an SEE gain of up to 38% compared to LSTM and 22% over CNN while converging significantly faster at early training epochs. Furthermore, our results reveal that SEE improves with increasing AP transmit power up to a saturation point (approximately 9.5 Mb/J at $P_{\mathrm{AP}}^{max}=500$ mW), beyond which excessive power consumption limits efficiency gains. Additionally, SEE decreases as the number of APs increases, underscoring the need for adaptive AP selection strategies to mitigate static power consumption in backhaul links. These findings confirm that MOIBBO-CNN–LSTM offers an effective solution for optimizing SEE in CF m-MIMO-based IoT networks, paving the way for more energy-efficient and secure IoT communications. Full article

Maritime communication networks are critical for supporting the increasing demands of oceanic and coastal activities, including shipping, fishing, and offshore operations. However, traditional systems face significant challenges in providing reliable, high-throughput connectivity due to dynamic sea environments, mobility, and non-line-of-sight (NLoS) conditions. Reconfigurable intelligent surfaces (RISs) have been proposed as a promising solution to overcome these limitations by enabling programmable control of electromagnetic wave propagation in next-generation mobile communication networks, such as beyond fifth generation and sixth generation ones (B5G/6G). This paper presents a deep learning-based (DL) scheme for beam selection in RIS-aided maritime next-generation networks. The proposed approach leverages deep learning to optimize beam selection dynamically, enhancing signal quality, coverage, and network efficiency in complex maritime environments. By integrating RIS configurations with data-driven insights, the proposed framework adapts to changing channel conditions and potential vessel mobility while minimizing latency and computational overhead. Simulation results demonstrate significant improvements in both machine learning (ML) metrics, such as beam selection accuracy, and overall communication reliability compared to traditional methods. More specifically, the proposed scheme reaches around 99% Top-$K$ Accuracy levels while jointly improving energy efficiency (ee) and spectral efficiency (SE) by approx. 2 times compared to state-of-the-art approaches. This study provides a robust foundation for employing DL in RIS-aided maritime networks, contributing to the advancement of intelligent, high-performance wireless communication systems for advanced maritime applications, such as autonomous mooring, the autonomous approach, and just-in-time arrival (JIT). Full article

Fish oil, a rich source of omega-3 polyunsaturated fatty acids (PUFA), is a vital nutritional component, but considering its susceptibility to oxidation, it could benefit from an effective encapsulation system. This study aims to optimize high-pressure homogenization (HPH) parameters (pressure, number of passes) and wall material composition to maximize the encapsulation efficiency (EE) of fish oil, using different concentrations of maltodextrin with Arabic gum or sodium alginate. Key metrics such as emulsion droplet size, encapsulation efficiency, color, and oxidation in the final freeze-dried product were evaluated. Optimal values were achieved at 60 MPa, resulting in the lowest mean droplet diameter (369.4 ± 3.8 nm) and narrow distribution (0.197 ± 0.011) of the fish oil micelles prepared with a mixture of Tween80 and sodium caseinate as an emulsifier, without significant oxidation after four cycles of homogenization, while 80 MPa led to the highest EE (up to 95.6%), but increased oxidation. The combination of 10% w/w Arabic gum or 1% w/w sodium alginate with 20% w/w maltodextrin achieved the highest EE (79.1–82.9%) and whiteness index (82.5–83.0), indicating neutral-colored well-encapsulated fish oil without oxidation, which is desirable for product stability. Selecting optimal HPH conditions and wall material is crucial for the encapsulation efficiency and oxidation stability of omega-3 PUFA delivered in dehydrated forms. Full article

Background/Objectives: Chitosan–alginate microcapsules were produced to encapsulate bioactive compounds from Artemisia annua L. extract (apigenin, luteolin) and cannabidiol (CBD). The study aimed to optimize emulsion composition and encapsulation parameters for potential applications in food supplements and pharmaceuticals. Methods: A water-in-oil-in-water (W/O/W) emulsion and a modified coacervation extrusion technique were employed. The study was conducted in two phases using response surface methodology. Key metrics included encapsulation efficiency (EE), yield (EY), cumulative release in vitro, and physicochemical and morphological properties, analyzed via scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT-IR), high-performance liquid chromatography with a diode array detector (HPLC-DAD), and gas chromatography with flame ionization detection (GC-FID). Results: The optimal conditions were identified as 0.1% Tween 20, 3.8% Span 80, 3.8% CBD, 19.9% A. annua L. extract, 1.5% outer-phase Tween 20, 48.5% sodium alginate, 200 rpm stirring for 30 min, and a 0.05 mL/min flow rate. The EE values were 80.32 ± 4.11% for CBD, 88.13 ± 3.13% for apigenin, and 88.41 ± 4.17% for luteolin, with respective cumulative releases of 77.18 ± 4.4%, 75.12 ± 4.81%, and 75.32 ± 4.53%. Conclusions: The developed microcapsules demonstrated high encapsulation efficiency and controlled release, highlighting their potential for further development in food supplements and pharmaceuticals. Future studies should focus on refining the formulation for improved bioavailability and stability. Full article

Background/Objectives: Cardiac amyloidosis (CA) is a rare and severe multisystem disorder, associated with an average survival of approximately five years. Recently, Tafamidis has emerged as a promising treatment for transthyretin-related CA. This retrospective study aimed to assess disease progression through echocardiographic findings in patients with transthyretin-related CA, with a specific focus on evaluating the impact of Tafamidis in a cohort managed at our Cardiomyopathy Clinic. Methods: A total of 39 patients were included, of whom 28 received Tafamidis treatment, while 11 did not. Clinical, electrocardiographic, echocardiographic, biological, and other imaging data were collected at diagnosis. Comprehensive echocardiographic data were collected every six months over a two-year period (2021–2023). Results: At 1-year follow-up, the Tafamidis-treated cohort demonstrated stable global systolic and diastolic function. Left ventricular (LV) global longitudinal strain (GLS) and global work index (GWI) showed minimal change (GLS −12.9% (−15.6; −10.7) vs. −13.0% (−14.0; −10.7), p = 0.054; GWI 1113 mmHg/% (963; 1301) vs. 1208 mmHg/% (850; 1420), p = 0.054), and there was no significant increase in indexed LV mass (135.0 g/m² (118.0; 167.0) vs. 148.0 (128.0; 173.0), p = 0.25). Similarly, valvular heart disease severity remained unchanged. Longitudinal analysis using generalized linear mixed models further confirmed the stability of echocardiographic parameters over the 2-year follow-up period. Systolic function metrics, including LV ejection fraction (slope: −0.0098 ± 0.011, p = 0.38) and GLS (slope: 0.0036 ± 0.0041, p = 0.39) showed no significant decline. Diastolic function assessed through E/A ratio (slope: −0.0007 ± 0.0013, p = 0.59) and E/e’ (slope: −0.0042 ± 0.0073, p = 0.57) also remained stable. Indexed LV mass exhibited no significant progression (slope: 0.050 ± 0.061, p = 0.41). These findings were consistent across the various subgroups. Conclusions: Tafamidis appears to effectively stabilize transthyretin-related CA, limiting disease progression over the follow-up period. Full article

The influence of bakery waste (BAWA) in the diet of black goat kids on nutrient intake, health, growth potential, and carcass features was assessed. Three treatment diets, consisting of 0 BAWA (CON), 50 g/kg BAWA (BAWA50), and 100 BAWA (BAWA100) of dietary dry matter (DM), were administered to 27 male kids (initial body weight = 17.43 ± kg; age = 105 ± 3.5 days) at random (9/treatment). Bakery waste was included in diets BAWA50 and BAWA100, replacing some of the barley grain. The study lasted for 70 days (7 days used for adaptation and 63 days used for data collection). Kids in the BAWA100 group consumed considerably more (p < 0.01) DM, crude protein (CP), and metabolizable energy than those in the BAWA50 and CON groups. However, intakes of neutral detergent fiber (NDF), acid detergent fiber (ADF), and ether extract (EE) were similar (p ≥ 0.08) among the treatment diets. The kids’ initial and final body weights, total growth, and average daily weight were not substantially impacted (p ≥ 0.13) by the addition of BAWA. All diets had similar feed efficiency when it came to converting feed into body weight increases (p ≥ 0.11). Nevertheless, the BAWA diet yielded a considerably lower cost gain (p = 0.04) than the CON diet. The three treatment groups had no differences (p ≥ 0.15) in DM, ADF, NDF, and EE digestibility. However, compared to the CON group, the digestibility of CP tended to improve (p = 0.07) in the BAWA100 and BAWA50 groups. The three experimental groups’ nitrogen (N) intakes did not differ significantly from one another (p > 0.33). Additionally, the three diets’ N retention percentage and grams/d were equivalent (p > 0.33). Several carcass metrics, such as dressing percentage, hot and cold carcass weights, fasting live weight, and non-carcass components, were not significantly affected (p > 0.23) by the addition of BAWA. Additionally, no differences in carcass cut weights were found. The inclusion of BAWA100 and BAWA50 increased loin cut weight (p = 0.043) and total lean muscle weight (p = 0.001) compared to the CON group. Other components, such as intermuscular fat, subcutaneous fat, total fat, total bone, meat-to-bone ratio, and meat-to-fat ratio, were similar among the three diet groups. Concerning carcass linear dimension measurements, only rib fat depth was greater (p = 0.008) in kids fed the BAWA100 diet compared to the BAWA50 and CON diets. No significant variation was observed among the treatments concerning various physicochemical properties of the longissimus dorsi muscle in the black goat kids. All measured serum metabolites and hematological parameters were not affected by the incorporation of BAWA into the diet. In summary, the inclusion of 50 and 100 g/kg BAWA in the diet had comparable effects on the black goat kids’ feed intake, digestibility, growth performance, carcass characteristics, meat quality, and overall health. Importantly, feed costs can be reduced by using up to 100 g/kg of BAWA on a DM basis. Full article

The global deployment of fifth-generation (5G) mobile networks, especially in urban cities, is dedicated to accommodating the demand for high data rates and reliable wireless communications. While the latest 5G networks improve service quality, the support for a simultaneous serving of more user devices (UDs) with higher data rates than previous mobile network generations will require a massive installation of different 5G base station (BS) types dominantly in urban cities. Besides contributing to the smart city service improvements, this massive installation of heterogeneous 5G BSs will also contribute to the increase in 5G network energy consumption (EC) and carbon dioxide emissions. Since this increase in installed 5G BSs imposes environmental and economic challenges, this paper analyzes the impact of the continuously rising number of 5G UDs on the energy efficiency (EE) of the radio part of Croatian and Dutch 5G networks as example cases in the period of 2020s. Analyses consider the countries’ rural, suburban, urban, and dense urban UD density areas by utilizing the proposed simulation framework for the EE evaluation of 5G heterogeneous networks (HetNet) valued through standardized mobile networks EE metrics. The study examines four proposed BS installation and operation scenarios for reducing energy costs of 5G networks that differ in optimizing energy consumption via different BS installations, sleep modes, and transmission power scaling techniques. The obtained results indicate that dynamic adaptation of BS deployments and radio resource management during operation according to the increase in the number of UDs and corresponding DVs can enhance 5G HetNet EE. The findings provide valuable insights for mobile network operators looking to optimize 5G network EE in the upcoming decade. Full article