In response to a global shift towards health-conscious and environmentally sustainable food choices, seaweed has emerged as a focus for researchers due to its large-scale cultivation potential and the development of bioactive substances. This research explores the potential anticancer properties of seaweed extracts, focusing on analyzing the impact of four common edible seaweeds in Taiwan on prostate cancer (PCa) cells’ activity. The study used bioassay-guided fractionation to extract Cl80 from various seaweeds with androgen receptor (AR)-inhibitory activity. Cl80 demonstrated effective suppression of 5α-dihydrotestosterone (DHT)-induced AR activity in 103E cells and attenuated the growth and prostate-specific antigen (PSA) protein expression in LNCaP and 22Rv1 cells. Additionally, Cl80 exhibited differential effects on various PCa cell lines. Concentrations above 5 μg/mL significantly inhibited LNCaP cell proliferation, while 22Rv1 cells were more resistant to Cl80. PC-3 cell proliferation was inhibited at 5 μg/mL but not completely at 50 μg/mL. A clonogenic assay showed that at a concentration of 0.5 μg/mL, the colony formation in LNCaP and PC-3 cells was significantly reduced, with a dose-dependent effect. Cl80 induced apoptosis in all PCa cell types, especially in LNCaP cells, with increased apoptotic cells observed at higher concentrations. Cl80 also decreased the mitochondrial membrane potential (ΔΨm) in a dose-dependent manner in all PCa cell lines. Furthermore, Cl80 suppressed the migration ability of PCa cells, with significant reductions observed in LNCaP, 22Rv1, and PC-3 cells at various concentrations. These compelling findings highlight the promising therapeutic potential of C. lentillifera J.Agardh and its isolated compound Cl80 in the treatment of PCa. Full article

Electronic textiles (E-textiles) have experienced an increase in interest in recent years leading to a variety of new concepts emerging in the field. Despite these technical innovations, there is limited literature relating to the testing of E-textiles for some of the fundamental properties linked to wearer comfort. As such, this research investigates four fundamental properties of E-textiles: air permeability, drape, heat transfer, and moisture transfer. Three different types of E-textiles were explored: an embroidered electrode, a knitted electrode, and a knitted structure with an embedded electronic yarn. All of the E-textiles utilized the same base knitted fabric structure to facilitate a comparative study. The study used established textile testing practices to evaluate the E-textiles to ascertain the suitability of these standards for these materials. The study provides a useful point of reference to those working in the field and highlights some limitations of existing textile testing methodologies when applied to E-textiles. Full article

The most common form of hereditary spastic paraplegia (HSP), SPG4 is caused by single nucleotide variants and microrearrangements in the SPAST gene. The high percentage of multi-exonic deletions or duplications observed in SPG4 patients is predisposed by the presence of a high frequency of Alu sequences in the gene sequence. In the present study, we analyzed DNA and RNA samples collected from patients with different microrearrangements in SPAST to map gene breakpoints and evaluate the mutation mechanism. The study group consisted of 69 individuals, including 50 SPG4 patients and 19 healthy relatives from 18 families. Affected family members from 17 families carried varying ranges of microrearrangements in the SPAST gene, while one individual had a single nucleotide variant in the 5′UTR of SPAST. To detect the breakpoints of the SPAST gene, long-range PCR followed by sequencing was performed. The breakpoint sequence was detected for five different intragenic SPAST deletions and one duplication, revealing Alu-mediated microhomology at breakpoint junctions resulting from non-allelic homologous recombination in these patients. Furthermore, SPAST gene expression analysis was performed using patient RNA samples extracted from whole blood. Quantitative real-time PCR tests performed in 14 patients suggest no expression of transcripts with microrearrangements in 5 of them. The obtained data indicate that nonsense-mediated decay degradation is not the only mechanism of hereditary spastic paraplegia in patients with SPAST microrearrangements. Full article

Herein, I will review our efforts to develop a comprehensive and robust model for the estimation of the first oxidation potential, E_p1, and antioxidant activity, AA, of flavonoids that would, besides enabling fast and cheap prediction of E_p1 and AA for a flavonoid of interest, help us explain the relationship between E_p1, AA and electronic structure. The model development went forward with enlarging the set of flavonoids and, that way, we had to learn how to deal with the structural peculiarities of some of the 35 flavonoids from the final calibration set, for which the E_p1 measurements were all made in our laboratory. The developed models were simple quadratic models based either on atomic spin densities or differences in the atomic charges of the species involved in any of the three main oxidation mechanisms. The best model takes into account all three mechanisms of oxidation, single electron transfer-proton transfer (SET-PT), sequential proton loss electron transfer (SPLET) and hydrogen atom transfer (HAT), yielding excellent statistics (R² = 0.970, S.E. = 0.043). Full article

Prolonged ethanol (EtOH) consumption is associated with male infertility, with a decreased spermatogenesis rate as one cause. The defective maturation and development of sperm during their storage in the cauda epididymis and transit in the seminal vesicle can be another cause, possibly occurring before the drastic spermatogenesis disruption. Herein, we demonstrated that the cauda epididymis and seminal vesicle of rats, orally administered with EtOH under a regimen in which spermatogenesis was still ongoing, showed histological damage, including lesions, a decreased height of the epithelial cells and increased collagen fibers in the muscle layer, which implicated fibrosis. Lipid peroxidation (shown by malondialdehyde (MDA) levels) was observed, indicating that reactive oxygen species (ROS) were produced along with acetaldehyde during EtOH metabolism by CYP2E1. MDA, acetaldehyde and other lipid peroxidation products could further damage cellular components of the cauda epididymis and seminal vesicle, and this was supported by increased apoptosis (shown by a TUNEL assay and caspase 9/caspase 3 expression) in these two tissues of EtOH-treated rats. Consequently, the functionality of the cauda epididymis and seminal vesicle in EtOH-treated rats was impaired, as demonstrated by a decreases in ¹H NMR-analyzed metabolites (e.g., carnitine, fructose), which were important for sperm development, metabolism and survival in their lumen. Full article

This study aims to understand the main nutrient composition and comprehensively evaluate the differences in the mineral element contents of fruits of different macadamia cultivars, as well as screen good cultivars that are suitable for use in rocky desert mountains. Nine macadamia nut cultivars were selected as test materials in rocky desert mountain orchards. The contents of crude fat, crude protein, and total soluble sugar in kernels and N, P, K, Ca, Mg, Fe, Mn, Cu, Zn, and B in peels and kernels were determined, respectively. Then, the kernels’ mineral element contents were comprehensively evaluated based on principal component analysis. The results showed that the kernels were rich in crude fat, protein, and soluble sugar, with the crude fat content reaching 75% or greater, and the variation among cultivars was small. However, the variation in soluble sugar content was extensive. The content of mineral elements varied in different cultivars and parts of the fruit, with the average macronutrient content being K > N > Ca > P > Mg in the pericarp and N > K > P > Mg > Ca in the kernel, and the content of micronutrients in the pericarp and the kernel being Mn > Fe > Zn > Cu > B. By principal component analysis, the 10 mineral nutrient indexes were calculated as four principal components, with a cumulative contribution rate of 88.051%. Using the affiliation function value method and the calculation of the comprehensive evaluation value, the nine cultivars could be classified into three categories. The cultivar with the highest comprehensive evaluation value of the mineral element content was O.C. The one with the lowest value was H2, which indicated that O.C is a suitable variety for popularization in rocky desert mountainous areas. Stepwise regression analysis concluded that P, K, Fe, Mn, and Cu were the indicators significantly influencing the mineral element content of macadamia nuts and fruits in rocky desert mountains. Full article

A number of sentinel species are regularly sampled from the environment near the Oil Sands Region (OSR) in Alberta, Canada. In particular, trout-perch are sampled as a proxy for the health of the aquatic ecosystem. As the development of the OSR began before the environmental monitoring program was in place, there is currently no established measure for the baseline health of the local ecosystem. A common solution is to calculate normal ranges for fish endpoints. Observations found to be outside the normal range are then flagged, alerting researchers to the potential presence of stressors in the local environment. The quality of the normal ranges is dependent on the accuracy of the estimates used to calculate them. This paper explores the use of neural networks and regularized regression for improving the prediction accuracy of fish endpoints. We also consider the trade-off between the prediction accuracy and interpretability of each model. We find that neural networks can provide increased prediction accuracy, but this improvement in accuracy may not be worth the loss in interpretability in some ecological studies. The elastic net offers both good prediction accuracy and interpretability, making it a safe choice for many ecological applications. A hybridized method combining both the neural network and elastic net offers high prediction accuracy as well as some interpretability, and therefore it is the recommended method for this application. Full article

The coast of São Paulo, Brazil, is exposed to storm surges that can cause damage and floods. These storm surges are produced by slowly traveling cyclone–anticyclone systems. The motivation behind this work was the need to evaluate high-resolution forecasts of the mean sea-level pressure and 10 m winds, which are the major drivers of the wave model. This work is part of the activity in devising an early warning system for São Paulo coastal storm surges. For the evaluation, four case studies that had a major impact on the coast of São Paulo in 2020 were selected. Because storm surges that reach the coast may cause coastal flooding, precipitation forecasts were also evaluated. The mesoscale Eta model produces forecasts with a 5 km resolution for up to an 84 h lead time. The model was set up in a region that covers part of southeast and south Brazil. The ERA5 reanalysis was used to describe the large-scale synoptic conditions and to evaluate the weather forecasts. The cases showed a region in common between 35° S, 40° S and 35° W, 45° W where the low-pressure center deepened rapidly on the day before the highest waves reached the coast of São Paulo, with a mostly eastward, rather than northeastward, displacement of the associated surface cyclone and minimal or no tilt with height. The winds on the coast were the strongest on the day before the surge reached the coast of São Paulo, and then the winds weakened on the day of the maximum wave height. The pattern of the mean sea-level pressure and 10 m wind in the 36 h, 60 h, and 84 h forecasts agreed with the ERA5 reanalysis, but the pressure was slightly underestimated. In contrast, the winds along the coast were slightly overestimated. The 24 h accumulated precipitation pattern was also captured by the forecast, but was overestimated, especially at high precipitation rates. The 36 h forecasts showed the smallest error, but the growth in the error for longer lead times was small, which made the 84 h forecasts useful for driving wave models and other local applications, such as an early warning system. Full article

Outpatient parenteral antimicrobial therapy (OPAT) aims to deliver intravenous antimicrobials to medically stable patients with complex infections outside of a hospital setting. There is good evidence to demonstrate the safety and efficacy of OPAT in the literature. Anecdotally, the feedback from patients has been positive, but only a few studies evaluate this topic in detail. The aim of this qualitative study was to examine patients’ experiences with and feedback on the OPAT service in Bristol, United Kingdom, which was established in 2021. A total of 92 patient feedback surveys were reviewed retrospectively, and thematic analysis was undertaken. Feedback from OPAT patients in our centre was overwhelmingly positive. The key themes identified were benefits to the patients, their friends, and family, and positive feedback about OPAT staff. The mean overall satisfaction score for OPAT was 9.6 out of 10. Areas to improve included communication between the OPAT and parent teams, improving OPAT capacity, and expansion of the service. Full article

Accurate predictions of photovoltaic generation are essential for effectively managing power system resources, particularly in the face of high variability in solar radiation. This is especially crucial in microgrids and grids, where the proper operation of generation, load, and storage resources is necessary to avoid grid imbalance conditions. Therefore, the availability of reliable prediction models is of utmost importance. Authors address this issue investigating the potential benefits of a machine learning approach in combination with photovoltaic power forecasts generated using weather models. Several machine learning methods have been tested for the combined approach (linear model, Long Short-Term Memory, eXtreme Gradient Boosting, and the Light Gradient Boosting Machine). Among them, the linear models were demonstrated to be the most effective with at least an RMSE improvement of 3.7% in photovoltaic production forecasting, with respect to two numerical weather prediction based baseline methods. The conducted analysis shows how machine learning models can be used to refine the prediction of an already established PV generation forecast model and highlights the efficacy of linear models, even in a low-data regime as in the case of recently established plants. Full article

Understanding the role that settlement can have on the base resistance of piles is a crucial matter in the design and safety control of deep foundations under various buildings and infrastructure, especially for long to super-long piles (60–90 m length) in soft soil. This paper presents a novel assessment of this issue by applying explainable machine learning (ML) techniques to a robust database (1131 datapoints) of fully instrumented pile tests across 37 real-life projects in the Mekong Delta. The analysis of data based on conventional methods shows distinct responses of long piles to rising settlement, as compared to short piles. The base resistance can rapidly develop at a small settlement threshold (0.015–0.03% of pile’s length) and contribute up to 50–55% of the total bearing capacity in short piles, but it slowly rises over a wide range of settlement to only 20–25% in long piles due to considerable loss of settlement impact over the depth. Furthermore, by leveraging the advantages of ML methods, the results significantly enhance our understanding of the settlement–base resistance relationship through explainable computations. The ML-based prediction method is compared with popular practice codes for pile foundations, further attesting to the high accuracy and reliability of the newly established model. Full article

Using the solid-state reactions method Na_0.55(Co,M)O₂ (M = Cr, Ni, Zn, W, and Bi) ceramics were prepared and their crystal structure, microstructure, electrophysical, thermophysical, and thermoelectric properties were studied. Doping of Na_0.55CoO₂ by transition or heavy metal oxides led to the increase in the grain size of ceramics, a decrease in electrical resistivity and thermal diffusivity values, and a sharp increase in the Seebeck coefficient, which resulted in essential enhancement of their thermoelectric properties. The largest power factor (1.04 mW/(m·K²) at 1073 K) and figure of merit (0.702 at 1073 K) among the studied samples possessed the Na_0.55Co_0.9Bi_0.1O₂ compound, which also demonstrated the highest values of the Seebeck coefficient (666 μV/K at 1073 K). The obtained results show that the doping of layered sodium cobaltite by different metal oxides allows for improving its stability, microstructure, and functional properties, which proves the effectiveness of the doping strategy for developing new thermoelectric oxides with enhanced thermoelectric performance. Full article

Estrogen receptor (ER) β (ERβ) is the second ER subtype that mediates the effects of estrogen in target tissues along with ERα that represents a validated biomarker and target for endocrine therapy in breast cancer. ERα was the only known ER subtype until 1996 when the discovery of ERβ opened a new chapter in endocrinology and prompted a thorough reevaluation of the estrogen signaling paradigm. Unlike the oncogenic ERα, ERβ has been proposed to function as a tumor suppressor in breast cancer, and extensive research is underway to uncover the full spectrum of ERβ activities and elucidate its mechanism of action. Recent studies have relied on new transgenic models to capture effects in normal and malignant breast that were not previously detected. They have also benefited from the development of highly specific synthetic ligands that are used to demonstrate distinct mechanisms of gene regulation in cancer. As a result, significant new information about the biology and clinical importance of ERβ is now available, which is the focus of discussion in the present article. Full article

Introduction: Up to 50% of community-dwelling older adults report living with some chronic pain that interferes with their daily functioning and leads to disabilities. Hence, it is crucial to provide these individuals with strategies to effectively manage pain. An interdisciplinary approach is warranted considering the numerous factors contributing to pain among older adults. Although several studies have been conducted on various interdisciplinary pain self-management programs, little effort has been made to synthesize knowledge about such programs for older adults. Objective: The objective of this review was to synthesize the characteristics and effects of interdisciplinary chronic pain self-management interventions targeting community-dwelling older adults. Methods: A scoping review was conducted following the steps recommended by Arksey and O’Malley (2005) and Levac et al. (2010). Keyword searches were performed in MEDLINE, CINAHL, EMBASE, and the Cochrane Library. Results: Sixty-six articles were included. Most interventions were based on a cognitive-behavioral group approach and used a combination of modalities, including education and training on the use of self-management strategies. The professionals most frequently involved in group interventions were psychologists, physiotherapists, and occupational therapists. Several benefits of these programs have been reported concerning pain intensity, independence in daily functioning, mental health, and quality of life. Conclusions: Interdisciplinary chronic pain self-management programs appear promising in guiding clinical and rehabilitation interventions for older adults living with chronic pain. Full article

Understanding the role of oxygen vacancies in the phase transformation of metal oxide nanomaterials is fundamental to design more efficient opto-electronic devices for a variety of applications, including sensing, spintronics, photocatalysis, and photo-electrochemistry. However, the structural mechanisms behind the phase transformation in reducible oxides remain poorly described. Here, we compare P25 and black TiO₂ during the thermal anatase-to-rutile transformation using in situ synchrotron powder diffraction. The precise measurement of the phase fractions, unit cell parameters, and Ti-O bond sheds light on the phase transformation dynamics. Notably, we observe distinct temperature-dependent shifts in the relative phase fractions of anatase and rutile in both materials highlighting the role of the oxygen vacancy in promoting the phase transformation. We employ bond valence concepts for structural modeling, revealing unique trends in temperature evolution of Ti-O distances of black rutile, confirming that this TiO₂ phase is preferentially reduced over anatase. These findings not only enhance our understanding of phase transitions in TiO₂ but also open new ways for the design of advanced photocatalytic materials through targeted phase control. Full article

In the near future, fully autonomous vehicles may revolutionise mobility and contribute to the development of the smart city concept. In this work, we assume that vehicles are not only fully autonomous but also centrally controlled by a single operator, who can also define the traffic light control parameters at intersections. With the aim of optimising the system to achieve a global optimum, the operator can define both the routes of the fleet of vehicles and the traffic light control parameters. This paper proposes a model for the joint optimisation of traffic light control parameters and autonomous vehicle routes to achieve the system optimum. The model, which is solved using a gradient algorithm, is tested on networks of different sizes. The results obtained show the validity of the proposed approach and the advantages of centralised management of vehicles and intersection control parameters. Full article

This paper aims to emphasize the need for enhancing inclusivity and accessibility within smart-city societies. It represents the first attempt to apply Amartya Sen’s capability approach by exploring the implications of digital divides for promoting inclusive and climate-friendly cities that prioritize well-being, equity, and societal participation. Sen’s framework recognizes individual variations in converting resources into valuable ‘functionings’, and herein emphasizes the importance of aligning personal, social, and environmental conversion factors for individuals to fully navigate, participate in, and enjoy the benefits provided by smart cities. Adopting the capability approach and employing a cross-disciplinary analysis of the scientific literature, the primary objective is to broaden understanding of how to improve inclusivity and accessibility within smart-city societies, with a specific focus on marginalized community members facing first- and second-level digital divides. This paper underscores the importance of adopting a systemic perspective on climate-smart city navigation and stresses the importance of establishing a unified governing body responsible for monitoring, evaluating, and enhancing smart-city functionality. The paper concludes by summarizing some policy recommendations to boost social inclusion and address climate change in smart cities, such as creating capability-enhancing institutions, safeguarding redundancy in public-choice options, empowering citizens, and leveraging academic knowledge in smart-city policy formulation. Full article

Outlier detection plays a critical role in building operation optimization and data quality maintenance. However, existing methods often struggle with the complexity and variability of building energy data, leading to poorly generalized and explainable results. To address the gap, this study introduces a novel Vision-based Outlier Detection (VOD) approach, leveraging computer vision models to spot outliers in the building energy records. The models are trained to identify outliers by analyzing the load shapes in 2D time series plots derived from the energy data. The VOD approach is tested on four years of workday time-series electricity consumption data from 290 commercial buildings in the United States. Two distinct models are developed for different usage purposes, namely a classification model for broad-level outlier detection and an object detection model for the demands of precise pinpointing of outliers. The classification model is also interpreted via Grad-CAM to enhance its usage reliability. The classification model achieves an F1 score of 0.88, and the object detection model achieves an Average Precision (AP) of 0.84. VOD is a very efficient path to identifying energy consumption outliers in building operations, paving the way for the enhancement of building energy data quality, operation efficiency, and energy savings. Full article

This study focused on the osmotic dehydration (OD) of ready-to-eat spinach leaves combined with the pulsed electric field (PEF) pre-treatment. Untreated and PEF-treated (0.6 kV/cm, 0–200 pulses) spinach leaves were osmotically dehydrated at room temperature for up to 120 min. The application of PEF (0.6 kV/20 pulses) prior to OD (60% glycerol, 25 °C, 60 min) lowered water activity (a_w = 0.891) while achieving satisfactory product acceptability (total sensory hedonic scoring of 8). During the storage of the product (at 4, 8, 12, and 20 °C for up to 30 d), a significant reduction in total microbial count evolution was observed (9.7 logCFU/g for the untreated samples vs. 5.1 logCFU/g for the PEF-OD-treated samples after 13 d of storage at 4 °C). The selection of these PEF and OD treatment conditions enabled the extension of the product shelf life by up to 33 d under chilled storage. Osmotically treated spinach could find application in ready-to-eat salad products with an extended shelf life, which is currently not possible due to the high perishability of the specific plant tissue. Full article

Chronic kidney disease (CKD) represents an increasing health burden. Evidence suggests the importance of miRNA in diagnosing CKD, yet the reports are inconsistent. This study aimed to determine novel miRNA biomarkers and potential therapeutic targets from hypothesis-free miRNA profiling studies in human and murine CKDs. Comprehensive literature searches were conducted on five databases. Subgroup analyses of kidney diseases, sample types, disease stages, and species were conducted. A total of 38 human and 12 murine eligible studies were analyzed using Robust Rank Aggregation (RRA) and vote-counting analyses. Gene set enrichment analyses of miRNA signatures in each kidney disease were conducted using DIANA-miRPath v4.0 and MIENTURNET. As a result, top target genes, Gene Ontology terms, the interaction network between miRNA and target genes, and molecular pathways in each kidney disease were identified. According to vote-counting analysis, 145 miRNAs were dysregulated in human kidney diseases, and 32 were dysregulated in murine CKD models. By RRA, miR-26a-5p was significantly reduced in the kidney tissue of Lupus nephritis (LN), while miR-107 was decreased in LN patients’ blood samples. In both species, epithelial-mesenchymal transition, Notch, mTOR signaling, apoptosis, G2/M checkpoint, and hypoxia were the most enriched pathways. These miRNA signatures and their target genes must be validated in large patient cohort studies. Full article

It is essential and forward-thinking to investigate the personalized use of four-wheel driving and steering wire-controlled unmanned chassis. This paper introduces a personalized path-tracking approach designed to adapt the vehicle’s control system to human-like characteristics, enhancing the fit and maximizing the potential of the chassis’ multi-directional driving and steering capabilities. By modifying the classic vehicle motion controller design, this approach aligns with individual driving habits, significantly improving upon traditional path-tracking control methods that rely solely on reference vector fields. First, the classic reference vector field’s logic was expanded upon, and it is shown that a personalized upgrade is feasible. Then, driving behavior data from multiple drivers were collected using a driving simulator. The fuzzy c-means clustering method was used to categorize drivers based on typical states that match vehicle path-tracking performance. Additionally, the random forest algorithm was used as the method for recognizing driving style. Subsequently, a personalized path-tracking control strategy based on the reference vector field was developed and a distributed execution architecture for four-wheel driving and steering wire-controlled unmanned chassis was established. Finally, the proposed personalized path-tracking approach was validated using a driving simulator. The results of the experimental tests demonstrated that the personalized path-tracking control approach not only fits well with various driving styles but also delivers high accuracy in driving style identification, making it highly suitable for application in four-wheel driving and steering wire-controlled chassis. Full article

The survival rate of cardiac arrest (CA) can be improved by utilizing percutaneous left ventricular assist devices (pLVADs) instead of conventional chest compressions. However, existing pLVADs require complex fluoroscopy-guided placement along a guidewire and suffer from limited blood flow due to their cross-sectional area. The recently developed self-expandable Impella CP (ECP) pLVAD addresses these limitations by enabling guidewire-free placement and increasing the pump cross-sectional area. This study evaluates the feasibility of resuscitation using the Impella ECP in a swine CA model. Eleven anesthetized pigs (73.8 ± 1.7 kg) underwent electrically induced CA, were left untreated for 5 min and then received pLVAD insertion and activation. Vasopressors were administered and defibrillations were attempted. Five hours after the return of spontaneous circulation (ROSC), the pLVAD was removed, and animals were monitored for an additional hour. Hemodynamics were assessed and myocardial function was evaluated using echocardiography. Successful guidewire-free pLVAD placement was achieved in all animals. Resuscitation was successful in 75% of cases, with 3.5 ± 2.0 defibrillations and 1.8 ± 0.4 mg norepinephrine used per ROSC. Hemodynamics remained stable post-device removal, with no adverse effects or aortic valve damage observed. The Impella ECP facilitated rapid guidewire-free pLVAD placement in fibrillating hearts, enabling successful resuscitation. These findings support a broader clinical adoption of pLVADs, particularly the Impella ECP, for CA. Full article