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Background: Metastasis commonly occur in the bone tissue. Artificial intelligence (AI) has become increasingly prevalent in the medical sector as support in decision-making, diagnosis, and treatment processes. The objective of this systematic review was to assess the reliability of AI systems in clinical, radiological, and pathological aspects of bone metastases. Methods: We included studies that evaluated the use of AI applications in patients affected by bone metastases. Two reviewers performed a digital search on 31 December 2023 on PubMed, Scopus, and Cochrane library and extracted authors, AI method, interest area, main modalities used, and main objectives from the included studies. Results: We included 59 studies that analyzed the contribution of computational intelligence in diagnosing or forecasting outcomes in patients with bone metastasis. Six studies were specific for spine metastasis. The study involved nuclear medicine (44.1%), clinical research (28.8%), radiology (20.4%), or molecular biology (6.8%). When a primary tumor was reported, prostate cancer was the most common, followed by lung, breast, and kidney. Conclusions: Appropriately trained AI models may be very useful in merging information to achieve an overall improved diagnostic accuracy and treatment for metastasis in the bone. Nevertheless, there are still concerns with the use of AI systems in medical settings. Ethical considerations and legal issues must be addressed to facilitate the safe and regulated adoption of AI technologies. The limitations of the study comprise a stronger emphasis on early detection rather than tumor management and prognosis as well as a high heterogeneity for type of tumor, AI technology and radiological techniques, pathology, or laboratory samples involved. Full article

The efficient solution (fast and accurate) of parametric partial differential equations (pPDE) is of major interest in many domains of science and engineering, enabling evaluations of the quantities of interest, optimization, control, and uncertainty propagation—all them under stringent real-time constraints. Different methodologies have been proposed in the past within the model order reduction (MOR) community, based on the use of reduced bases (RB) or the separated representation at the heart of the so-called proper generalized decompositions (PGD). In PGD, an alternate-direction strategy is employed to circumvent the integration issues of operating in multi-dimensional domains. Recently, physics informed neural networks (PINNs), a particular collocation schema where the unknown field is approximated by a neural network (NN), have emerged in the domain of scientific machine learning. PNNs combine the versatility of NN-based approximation with the ease of collocating pPDE. The present paper proposes a combination of both procedures to find an efficient solution for pPDE, that can either be viewed as an efficient collocation procedure for PINN, or as a monolithic PGD that bypasses the use of the fixed-point alternated directions. Full article

The high temperature generated by the DC pantograph-catenary arc of urban rail systems will aggravate the wear of the pantograph-catenary system. When the ablation intensifies, it will lead to disconnection accidents on the contact line. In this paper, through the establishment of a pantograph-catenary arc model and contact line arc ablation model, considering the flow of the molten pool, it is reported that the temperature distribution of the pantograph-catenary arc is axisymmetric. With the increase in the arcing time, the maximum temperature of the arc increases. The heat flux density of the arc injection contact line presents a Gaussian distribution and is positively correlated with the arcing time. The high-temperature area of the contact line and the distribution of the molten pool show an approximate arc shape. The velocity of the molten pool shows a symmetrical distribution about the center of the electrode. The area, depth, and radius of the molten pool of the contact line increase with an increase in the arcing time, and the radius of the molten pool is always greater than the depth of the molten pool. The work presented in this paper is helpful to further our understanding of the basic physical process of pantograph-catenary arc ablation of contact lines. Full article

Diffuse low-grade gliomas are infiltrative tumors whose margins are not distinguishable from the adjacent healthy brain parenchyma. The aim was to precisely examine the results provided by the intraoperative use of macroscopic fluorescence in diffuse low-grade gliomas and to describe the new fluorescence-based techniques capable of guiding the resection of low-grade gliomas. Only about 20% and 50% of low-grade gliomas are macroscopically fluorescent after 5-amino-levulinic acid (5-ALA) or fluorescein sodium intake, respectively. However, 5-ALA is helpful for detecting anaplastic foci, and thus choosing the best biopsy targets in diffuse gliomas. Spectroscopic detection of 5-ALA-induced fluorescence can detect very low and non-macroscopically visible concentrations of protoporphyrin IX, a 5-ALA metabolite, and, consequently, has excellent performances for the detection of low-grade gliomas. Moreover, these tumors have a specific spectroscopic signature with two fluorescence emission peaks, which is useful for distinguishing them not only from healthy brain but also from high-grade gliomas. Confocal laser endomicroscopy can generate intraoperative optic biopsies, but its sensitivity remains limited. In the future, the coupled measurement of autofluorescence and induced fluorescence, and the introduction of fluorescence detection technologies providing a wider field of view could result in the development of operator-friendly tools implementable in the operative routine. Full article

Effective management of urban solid waste in the Metropolitan Region of Belém, State of Pará, Brazil is essential for conserving ecosystems and public health in eight cities, emphasizing the municipality of Marituba. Considering the vulnerability of underground water resources in Marituba to pollution due to the possible impact of leachate percolation from the landfill, this study evaluates the quality of groundwater captured in tubular wells from different adjacent locations potentially used for human consumption. For this purpose, the systematic methodologies of the groundwater quality index and human health risk assessment analysis: non-carcinogenic and carcinogenic risk to human health were used based on chronic daily intake of heavy metals by consumption and dermal adsorption of groundwater, measured through risk quotients, risk index, and incremental lifetime cancer risk. To evaluate the interrelationships of pollutants, analysis of variance, hierarchical cluster analysis, and principal component analysis were used based on the spatio-temporal quantification of pH, temperature, electrical conductivity, As, Al, Ba, Co, Cd, Cu, Cr, Fe, Hg, Ni, Pb, Sb, Se, U, and Zn. Residents of the study area are not at potential risk, as the results demonstrate that groundwater is within the potability standards of Brazilian legislation, except for aluminum concentrations, which ranged from 53.12 to 378.01 μg L⁻¹ and 3.82 to 339.5 μg L⁻¹ in the dry and rainy seasons, respectively, exceeding the established limit of 200.0 μg L⁻¹. The quality index for groundwater and the heavy metal pollution index demonstrated that groundwater has good drinking quality with low metal contamination. The risk was considered low at all sampling sites in the non-carcinogenic risk assessment. Principal component analysis indicated that the sources of metal pollution are natural origins and anthropogeny. In this sense, they become worried because aluminum is a recognized neurotoxicant that can interfere with the central nervous system’s critical physiological and biochemical processes. Furthermore, despite complying with potability standards, trace concentrations of highly toxic metals such as As, Pb, Cd, and Ni may indicate initial contamination by landfill leachate. Full article

Hyssopus officinalis L. (HO) is, as one of the most prevalently utilized plants, used in traditional medicine to cure various diseases as well as the in food and cosmetic industries. Moreover, HO is a rich source of polyphenols with potent antioxidant properties. However, the studies on the extraction of such compounds from HO are scanty and sparse. This study aims to optimize the extraction of polyphenols and maximize the antioxidant activity in HO extracts. A comprehensive experimental design was employed, encompassing varied extraction parameters to determine the most effective ones. Alongside conventional stirring (ST), two green approaches, the ultrasonic treatment (US) and the pulsed electric field (PEF), were explored, either alone or in combination. The extracted polyphenolic compounds were identified with a high-performance liquid chromatography–diode array detector (HPLC-DAD). According to the results, the employment of ST along with an ethanolic solvent at 80 °C for 150 min seems beneficial in maximizing the extraction of polyphenols from HO, resulting in extracts with enhanced antioxidant activity. The total polyphenol was noted at 70.65 ± 2.76 mg gallic acid equivalents (GAE)/g dry weight (dw) using the aforementioned techniques, and the antioxidant activity was noted as 582.23 ± 16.88 μmol ascorbic acid equivalents (AAE)/g dw (with FRAP method) and 343.75 ± 15.61 μmol AAE/g dw (with the DPPH method). The as-prepared extracts can be utilized in the food and cosmetics industries to bestow or enhance the antioxidant properties of commercial products. Full article

The health benefits of long-chain omega-3 polyunsaturated fatty acid (LCn-3PUFA) intake have been well documented. However, currently, the consumption of oily fish (the richest dietary source of LCn-3PUFA) in the UK is far below the recommended level, and the low digestibility of LCn-3PUFA bulk oil-based supplements from triglyceride-based sources significantly impacts their bioavailability. LCn-3PUFA-rich microalgal oil offers a potential alternative for populations who do not consume oily fish, and nanoemulsions have the potential to increase LCn-3PUFA digestibility and bioavailability. The aims of this study were to produce stable algal oil-in-water nanoemulsions with ultrasonic technology to increase DHA digestibility, measured using an in vitro digestion model. A nanoemulsion of LCn-3PUFA algal oil was developed with 6% w/w emulsifiers: lecithin (LE) or an equal ratio of Tween 40 (3%) and lecithin (LTN) (3%), 50% w/w, algal oil and 44% w/w water using rotor–stator and ultrasound homogenization. The in vitro digestion experiments were conducted with a gastric and duodenal digestion model. The results showed the creation of nanoemulsions of LCn-3PUFA algal oils offers potentially significant increases in the bioavailability of DHA in the human body. The increase in digestibility can be attributed to the smaller particle size of the nanoemulsions, which allows for higher absorption in the digestive system. This showed that the creation of nanoemulsions of LCn-3PUFA algal oils offers a potentially significant increase in the bioavailability of DHA in the human body. The LE and LTN nanoemulsions had average droplet sizes of 0.340 ± 0.00 µm and 0.267 ± 0.00 µm, respectively, but the algal oil mix (sample created with same the components as the LTN nanoemulsion, hand mixed, not processed by rotor–stator and ultrasound homogenization) had an average droplet size of 73.6 ± 6.98 µm. The LTN algal oil nanoemulsion was stable in the gastric and duodenal phases without detectable destabilization; however, the LE nanoemulsion showed signs of oil phase separation in the gastric phase. Under the same conditions, the amount of DHA digested from the LTN nanoemulsion was 47.34 ± 3.14 mg/g, compared to 16.53 ± 0.45 mg/g from the algal oil mix, showing DHA digestibility from the LTN nanoemulsion was 2.86 times higher. The findings of this study contribute to the insight of in vitro DHA digestion under different conditions. The stability of the LTN nanoemulsion throughout digestion suggests it could be a promising delivery system for LCn-3PUFAs, such as DHA, in various food and pharmaceutical applications. Full article

Regular detection of land-use and land-cover (LULC) changes with high accuracy is necessary for natural resources management and sustainable urban planning. The produced LULC maps from Google Earth Engine (GEE) also illustrate the transformation of the LULC for the respective landscape over time. The selected study area, Cottbus City and the Spree-Neisse district in northeastern Germany, has undergone significant development over the past decades due to various factors, including urbanization and industrialization; also, the landscape has been converted in some areas for post-mining activities. Detection of LULC changes that have taken place over the last few decades thus plays a vital role in quantifying the impact of these factors while improving the knowledge of these developments and supporting the city planners or urban management officials before implementing further long-term development initiatives for the future. Therefore, the study aims to (i) detect LULC changes for the time slices 2002 and 2022, testing machine learning (ML) algorithms in supervised and unsupervised classification for Landsat satellite imageries, and (ii) validate the newly produced LULC maps with the available regional database (RDB) from the federal and state statistical offices, Germany, and the Dynamic World (DW) near real-time 10 m global LULC data set powered by artificial intelligence (AI). The results of the Random Forest (RF) and the Smilecart classifiers of supervised classification using Landsat 9 OLI-2/TIRS-2 in 2022 demonstrated a validation accuracy of 88% for both, with Kappa Index (KI) of 83% and 84%, respectively. Moreover, the Training Overall Accuracy (TOA) was 100% for both years. The wekaKMeans cluster of the unsupervised classification also illustrated a similar transformation pattern in the LULC maps. Overall, the produced LULC maps offered an improved representation of the selected region’s various land-cover classes (i.e., vegetation, waterbodies, built areas, and bare ground) in the last two decades (20022 to 2022). Full article

Vaccine-preventable diseases continue to generate a substantial burden on health, healthcare systems, and societies, which is projected to increase with population ageing. There is a need to better understand the full value of adult immunisation programmes corresponding to the broader value of vaccine frameworks that are recommended for evidence-based decision-making. This review aims to summarise and map evidence for the value of selected adult immunisation programmes (seasonal influenza, pneumococcal disease, RSV, and HZ) in ten diverse countries. We conducted a structured literature review of evidence published from 2017 to 2023. An existing framework was used to structure the assessment, developing matrices demonstrating the elements of value evidenced for each vaccine and country of focus. Our analysis showed substantial evidence base on the value of adult immunisation programmes, but the availability of evidence varied by value element and by vaccine. The impact on the quality of life of the vaccinated individual was the most evidenced value element. Mortality benefits for vaccinated individuals and cost-offsets to healthcare systems were also well-evidenced. The availability of evidence for ‘broader’ societal value elements (such as transmission value, carer productivity and impact on social equity, and antimicrobial resistance prevention) varied. No evidence was identified relating to the broader value elements of macroeconomic effects, value to other interventions, or effects on the quality of life of caregivers. Robust evidence exists to show that adult immunisation programmes generate substantial value for population health and health systems, yet some elements of broader value remain underrepresented in the academic literature. Without such evidence, the full value of immunisation programmes is underestimated, risking suboptimal policy decisions. Full article

Anaphylaxis, an allergic reaction caused by the massive release of active mediators, can lead to anaphylactic shock (AS), the most severe and potentially life-threatening form of anaphylactic reaction. Nevertheless, understanding of its pathophysiology to support new therapies still needs to be improved. We performed a systematic review, assessing the role and the complex cellular interplay of mitochondria and oxidative stress during anaphylaxis, mast cell metabolism and degranulation. After presenting the main characteristics of anaphylaxis, the oxidant/antioxidant balance and mitochondrial functions, we focused this review on the involvement of mitochondria and oxidative stress in anaphylaxis. Then, we discussed the role of oxidative stress and mitochondria following mast cell stimulation by allergens, leading to degranulation, in order to further elucidate mechanistic pathways. Finally, we considered potential therapeutic interventions implementing these findings for the treatment of anaphylaxis. Experimental studies evaluated mainly cardiomyocyte metabolism during AS. Cardiac dysfunction was associated with left ventricle mitochondrial impairment and lipid peroxidation. Studies evaluating in vitro mast cell degranulation, following Immunoglobulin E (IgE) or non-IgE stimulation, revealed that mitochondrial respiratory complex integrity and membrane potential are crucial for mast cell degranulation. Antigen stimulation raises reactive oxygen species (ROS) production from nicotinamide adenine dinucleotide phosphate (NADPH) oxidases and mitochondria, leading to mast cell degranulation. Moreover, mast cell activation involved mitochondrial morphological changes and mitochondrial translocation to the cell surface near exocytosis sites. Interestingly, antioxidant administration reduced degranulation by lowering ROS levels. Altogether, these results highlight the crucial role of oxidative stress and mitochondria during anaphylaxis and mast cell degranulation. New therapeutics against anaphylaxis should probably target oxidative stress and mitochondria, in order to decrease anaphylaxis-induced systemic and major organ deleterious effects. Full article

Accurate identification of lithology in petroleum engineering is very important for oil and gas reservoir evaluation, drilling decisions, and petroleum geological exploration. Using a cross-plot to identify lithology only considers two logging parameters, causing the accuracy of lithology identification to be insufficient. With the continuous development of artificial intelligence technology, machine learning has become an important means to identify lithology. In this study, the cutting logging data of the Junggar Basin were collected as lithologic samples, and the identification of argillaceous siltstone, mudstone, gravel mudstone, silty mudstone, and siltstone was established by logging and logging parameters at corresponding depths. Aiming at the non-equilibrium problem of lithologic data, this paper proposes using equilibrium accuracy to evaluate the model. In this study, manifold learning is used to reduce logging and logging parameters to three dimensions. Based on balance accuracy, four dimensionality reductions including isometric feature mapping (ISOMAP), principal component (PCA), independent component (ICA), and non-negative matrix factorization (NMF) are compared. It is found that ISOMAP improves the balance accuracy of the LightGBM model to 0.829, which can effectively deal with unbalanced lithologic data. In addition, the particle swarm optimization (PSO) algorithm is used to automatically optimize the super-parameters of the lightweight gradient hoist (LightGBM) model, which effectively improves the balance accuracy and generalization ability of the lithology identification model and provides strong support for fast and accurate lithology identification. Full article

Background/Objectives: This study aims to assess the relationship between physical and psychosocial pre-surgical factors and post-surgical evolution in patients undergoing orthognathic surgery. Methods: A cohort study with 3 months of follow-up after maxillofacial surgery was conducted. Participants were recruited from the Maxillofacial Surgery Unit of Hospital Universitario La Paz in Madrid, Spain. Primary variables included the range of motion of mouth opening, protrusion tongue force, anxiety, depression and kinesiophobia. Assessments were realised on-site or via video call. Statistical analysis was conducted using mixed-effects models. Results: The initial recruitment yielded 22 patients, with 19 ultimately eligible for analysis. The study found significant impacts of pre-surgical factors on post-surgical evolution. Both ranges of motion and anxiety showed influences from baseline measures, with the range of motion affected by a pre-surgical range of motion (estimate: 3.89) and positive expectations (estimate: 4.83). Anxiety was influenced by both pre-surgical (estimate: 0.48) and baseline anxiety levels (estimate: 0.64). Kinesiophobia demonstrated a trend toward significance, with baseline levels affecting post-surgical evolution (estimate: 0.77). Conclusions: Our results highlight the relationship between pre-surgical factors and post-surgical outcomes in orthognathic surgery patients. Pre-surgical range of motion and positive expectations were found to influence post-surgical range of motion, while pre-surgical anxiety levels impacted post-surgical anxiety evolution. Pre-surgical kinesiophobia also showed potential as a post-surgical kinesiophobia predictor, but further investigation is needed to confirm this relationship. Full article

Rubble-pile asteroids may be the type of near-Earth object most likely to threaten Earth in a future collision event. Small-scale impact experiments and numerical simulations for large-scale impacts were conducted to clarify the size ratio of the boulder/projectile diameter effects on ejecta size–velocity distribution. A series of small-scale impact cratering experiments were performed on porous gypsum–basalt targets at velocities of 2.3 to 5.5 km·s⁻¹. Three successive ejection processes were observed by high-speed and ultra-high-speed cameras. The momentum transfer coefficient and cratering size were measured. A three-dimensional numerical model reflecting the random distribution of the interior boulders of the rubble-pile structure asteroid is established. The size ratio (length to diameter) of the boulder size inside the asteroid to the projectile diameter changed from 0.25 to 1.7. We conducted a smoothed particle hydrodynamics numerical simulation in the AUTODYN software to study the boulder size effect on the ejecta size–velocity distribution. Simulation results suggest that the microscopic porosity on regolith affects the propagation of shock waves and reduces the velocity of ejecta. Experiments and numerical simulation results suggest that both excavation flow and spalling ejection mechanism can eject boulders (0.12–0.72 m) out of the rubble-pile asteroid. These experiments and simulation results help us select the potential impact site in a planetary defense scenario and reduce deflection risk. are comprised primarily of boulders of a range of sizes. Full article

Carcinoma-associated fibroblasts (CAFs) are highly accumulated in the tumor-surrounding stroma of primary epithelial ovarian cancer (OC). CAFs exert important functions for the vascularization, growth, and progression of OC cells. However, the origin of CAFs in primary OC had not yet been studied, and they were assumed to arise from the activation of resident fibroblasts. Here, we compared CAFs in the ovary to CAFs found in peritoneal metastases from patients with advanced OC. Our findings show that CAFs from primary tumors and peritoneal metastases share the expression of mesothelial markers. Therefore, similar to peritoneal carcinomatosis, CAFs in primary ovarian carcinomas may originate from mesothelial cells via a mesothelial-to-mesenchymal transition. The detection of mesothelial-derived CAFs in tumors confined to the ovary and identification of biomarkers could be the key to the early detection of OC and peritoneal spread. Full article

In southwest Florida, the Caloosahatchee River flows from Lake Okeechobee into a biologically productive tidal estuarine system. A combination of excess water during the wet season, insufficient fresh water in the dry season, and poor quality of the river water are damaging the estuarine ecosystem. To better control the quality and quantity of the water entering the estuary, reservoirs are being constructed to store excess, poor quality water during the wet season and return it to the river for discharge into the estuary at an appropriate time. This stored water is enriched in nutrients and organic carbon. Because of the subtropical nature of the climate in southwest Florida and potential increases in temperature in the future, the return flow of water from the reservoirs must be treated before it can be returned to the river. Hence, an experimental water treatment system was developed and operated to compare biological treatment processes consisting of solely wetland plants versus adding some engineered processes, including slow sand filtration and a combination of slow sand filtration and ultraviolet (UV) treatment. These three treatment trains were operated and monitored through a seasonal cycle in 2021–2022. All three treatment methods significantly reduced the concentrations of nutrients and total organic carbon. While the enhanced engineered wetlands’ treatment trains did slightly outperform the wetland train, a comparison of the three process trains showed no statistically significant difference. It was concluded that upscaling of the slow sand filtration and UV process could improve the treatment efficiency, but this change would have to be evaluated within a framework of long-term economic benefits. It was also concluded that the Caloosahatchee River water quality is quite enriched in nutrients so that reservoir storage would increase the organic carbon concentrations, making it imperative that it be treated before being returned to the river. It was also discovered that the green alga Cladophora sp. grew rapidly in the biological treatment tubs and will present a significant challenge for the treatment of the reservoir discharge water using the currently proposed alum treatment. Full article