Electrocardiogram (ECG) abnormalities are the most common cardiac complications after acute ischemic stroke (AIS) and predict poor outcomes. The arterial baroreflex is an essential determinant of cardiovascular autonomic regulation, with receptors mainly residing in carotid sinuses and aortic arch. The atherosclerosis of these baroreceptor-resident arteries (BRA) is very common in AIS patients and might impair baroreflex function. However, the associations between the atherosclerosis of BRA and ECG abnormalities after AIS are still unknown. In total, 228 AIS patients within 7 days after onset without a pre-existing heart disease were prospectively recruited. With computed tomography angiography, atherosclerosis conditions in 10 segments of the carotid sinuses and aortic arch were scored and summed as the Total Atherosclerosis Burden of BRA (TAB-BRA), and asymptomatic coronary artery stenosis (ACAS) ≥50% was simultaneously assessed. We performed 12-lead ECG to dynamically detect abnormal repolarization, and 24 h Holter ECG to monitor arrhythmias and heart rate variability (HRV) parameters, which are reliable indicators to assess cardiac autonomic function. We found that TAB-BRA was positively associated with abnormal repolarization (OR 1.09; CI% 1.03–1.16; p = 0.003) and serious cardiac arrhythmias (OR 1.08; CI% 1.01–1.15; p = 0.021). In addition, TAB-BRA was an important predictor of abnormal repolarization, persisting over 3 days (OR 1.17; CI% 1.05–1.30; p = 0.003). However, ACAS ≥ 50% did not relate to these ECG abnormalities. TAB-BRA was negatively correlated with parasympathetic-related HRV parameters. Our results indicated that AIS patients with a high TAB-BRA are more likely to have ECG abnormalities and delayed normalization, which may relate to the decreased cardiac parasympathetic activity, but not the accompanied ACAS ≥ 50%. Full article

Cultural industries constitute a crucial part of the sustainable economy. In accordance with the principles of socialist public ownership nations, the economic benefits of cultural industries should be ultimately transformed into more significant social benefits. Guided by the policies and requirements of the Chinese government concerning the social benefits of cultural industries, this paper innovatively integrates Data Envelopment Analysis (DEA) and Tobit models to empirically analyze the social benefits and their influencing factors within China’s cultural industries. The findings indicate that the social benefits of China’s cultural industries are currently in a state of diminishing returns to scale, with fiscal support and educational levels significantly enhancing the industry’s social benefits. This paper recommends that policymakers aiming to convert the economic benefits of cultural industries into social benefits more systematically and effectively should focus on enhancing the quality of industry outputs. Full article

Pile spacing is an important factor affecting the bearing capacity of concrete expansion pile (CEP) groups. In this study, a pile group was simulated and analyzed using ANSYS software R19.0. The influence of pile spacing on the bearing capacity of the pile group under a vertical load was determined using three sets of four-, six-, and nine-pile models with different pile spacings. The grid division of the pile soil model adopts a mapping method, using the contact types of rigid and flexible bodies and applying surface loads to the model piles step-by-step. After vertical pressure was applied to the model pile, in-depth analysis was conducted on the displacement cloud map, pile top displacement, and other data. The different stress conditions of corner, edge, and center piles in each model group were compared and analyzed, revealing the relationship between the stress mechanism and failure law of the soil around the pile and the pile spacing. It was found that the soil displacement range of edge piles is slightly larger than that of corner piles. This phenomenon gradually decreases with increasing pile spacing. When the pile spacing increases to four times the cantilever diameter, the difference in soil displacement at different pile positions is small, and the pile spacing has little effect on the compressive bearing capacity of the pile group. Thus, it is reasonable to control the pile spacing at three to four times the cantilever diameter. In the nine-pile model, when the load is loaded to the 20-step level, the displacement value of the central pile is −72.278 mm, while the displacement values of the edge pile and corner pile are −69.012 mm and −66.806 mm. It is shown that increasing the pile spacing can effectively reduce the pile group effect and improve the bearing capacity of the pile foundation. At present, CEP pile groups are gradually being applied in practical engineering, but research on the influence of pile spacing on the compressive bearing performance of CEP pile groups is still at a very early stage. This article reinforces the influence of pile spacing on the compressive bearing performance of CEP pile groups. It provides theoretical support for its application in practical engineering. Full article

Early diagnosis is essential for the successful management of Burkholderia pseudomallei infection, but it cannot be achieved by the current gold standard culture technique. Therefore, this study aimed to develop a lateral flow immunoassay (LFIA) targeting B. pseudomallei capsular polysaccharide. The development was performed by varying nitrocellulose membrane reaction pads and chase buffers. The prototype LFIA is composed of Unisart CN95 and chase buffer containing tris-base, casein, and Surfactant 10G. The assay showed no cross-reactivity with E. coli, S. aureus, P. aeruginosa, and P. acne. The limit of detections (LODs) of the prototype LFIA was 10⁷ and 10⁶ CFU/mL B. pseudomallei in hemoculture medium and artificial urine, respectively. These LODs suggest that this prototype can detect melioidosis from positive hemoculture bottles but not straight from urine. Additionally, these LODs are still inferior compared to Active Melioidosis Detect (AMD^TM). Overall, this prototype holds the potential to be used clinically with hemoculture bottles. However, further improvements should be considered, especially for use with urine samples. Full article

This article provides an overview of the use of ¹⁸F-FDG PET/CT in various clinical scenarios of head–neck squamous cell carcinoma, ranging from initial staging to treatment-response assessment, and post-therapy follow-up, with a focus on the current evidence, debated issues, and innovative applications. Methodological aspects and the most frequent pitfalls in head–neck imaging interpretation are described. In the initial work-up, ¹⁸F-FDG PET/CT is recommended in patients with metastatic cervical lymphadenectomy and occult primary tumor; moreover, it is a well-established imaging tool for detecting cervical nodal involvement, distant metastases, and synchronous primary tumors. Various ¹⁸F-FDG pre-treatment parameters show prognostic value in terms of disease progression and overall survival. In this scenario, an emerging role is played by radiomics and machine learning. For radiation-treatment planning, ¹⁸F-FDG PET/CT provides an accurate delineation of target volumes and treatment adaptation. Due to its high negative predictive value, ¹⁸F-FDG PET/CT, performed at least 12 weeks after the completion of chemoradiotherapy, can prevent unnecessary neck dissections. In addition to radiomics and machine learning, emerging applications include PET/MRI, which combines the high soft-tissue contrast of MRI with the metabolic information of PET, and the use of PET radiopharmaceuticals other than ¹⁸F-FDG, which can answer specific clinical needs. Full article

BRCA1 mutations predispose women to breast and ovarian cancer. The anticancer effect of zinc is typically linked to its antioxidant abilities and protecting cells against oxidative stress. Zinc regulates key processes in cancer development, including DNA repair, gene expression, and apoptosis. We took a blood sample from 989 female BRCA1 mutation carriers who were initially unaffected by cancer and followed them for a mean of 7.5 years thereafter. There were 172 incident cases of cancer, including 121 cases of breast cancer, 29 cases of ovarian cancers, and 22 cancers at other sites. A zinc level in the lowest tertile was associated with a modestly higher risk of ovarian cancer compared to women with zinc levels in the upper two tertiles (HR = 1.65; 95% CI 0.80 to 3.44; p = 0.18), but this was not significant. Among those women with zinc levels in the lowest tertile, the 10-year cumulative risk of ovarian cancer was 6.1%. Among those in the top two tertiles of zinc level, the ten-year cumulative risk of ovarian cancer was 4.7%. There was no significant association between zinc level and breast cancer risk. Our preliminary study does not support an association between serum zinc level and cancer risk in BRCA1 mutation carriers. Full article

To achieve sustainable development goals and meet the demand for clean and efficient energy utilization, it is imperative to advance the penetration of renewable energy in various sectors. Energy storage systems can mitigate the intermittent issues of renewable energy and enhance the efficiency and economic viability of existing energy facilities. Among various energy storage technologies, thermocline heat storage (THS) has garnered widespread attention from researchers due to its stability and economic advantages. Currently, there are only a few review articles focusing on THS, and there is a gap in the literature regarding the optimization design of THS systems. Therefore, this paper provides a comprehensive review of the recent research progress in THS, elucidating its principles, thermal storage materials, applications, and optimization designs. The novelty of this work lies in the detailed classification and analysis of various optimization designs for THS, including tank shape, aspect ratio, inlet/outlet configuration, thermal energy storage materials arrangement, operating strategies, and numerical model optimization approaches. The limitations of existing research are also identified, and future perspectives are proposed, aiming to provide recommendations for THS research and contribute to the development and promotion of THS technology. Full article

This multimethod study investigated an environmental recycling project in a Finnish kindergarten group, tailored for children aged 4 to 6, as part of early childhood environmental education for sustainable development. We aimed to identify the main drivers of sustainable lifestyles in the families of kindergarten children and evaluate the project’s effective practices. We utilized a qualitative approach using interviews with parents and feedback from teachers and employed the Following a Thread approach alongside inductive thematic analysis. The results highlight the crucial role of Finland’s socio-cultural context, including the emphasis on free play in natural settings and the encouragement of exploration under gentle guidance, in fostering sustainable behaviors among children. Additionally, the parents’ strong environmental sensitivity was manifested in their will to engage with their surrounding community to promote sustainability. The results underscore the importance of collaboration between parents and educators in promoting environmental awareness from an early age. The study advocates for policy changes to ensure that children and teachers have access to natural environments during day care, suggesting that integrating free play in nature with hands-on recycling activities can significantly contribute to sustainable education. Moreover, this topic should be further investigated in different living environments. Full article

To clarify the migration and accumulation of nitrogen (N), magnesium (Mg), calcium (Ca), and potassium (K) in soil profiles of plastic-greenhouse vegetable fields with cultivation years, soil samples from the 0–7 m soil profiles were collected from 10 pepper greenhouses with 10 and 20 years planting history, and parallel soil samples were taken from adjacent wheat-maize fields as controls. The results showed that: (1) Compared with wheat-maize fields, the total N amount in the 0–7 m soil layers from the greenhouses increased by 6.19 ± 1.16 and 9.11 ± 3.43 t ha⁻¹ at 10 and 20 years, respectively, accounting for about 30.4% and 17.5% of the N input. (2) The N amount that entered the environment outside the 0–7 m soil layers were 6.95 t ± 2.76 and 29.10 ± 10.14 t ha⁻¹ after 10 and 20 years of continuous planting, accounting for approximately 34.2% and 55.9% of the N input, respectively. (3) The concentration of water-soluble Ca and Mg in the 0–7 m soil layers increased significantly with cultivation years, and correlated positively with mineral N concentration. (4) Moreover, K mainly accumulates in the form of non-exchangeable K in the surface layers (0–50 cm). Our results demonstrated that huge amounts of N migrate to the deep soil with the extension of cultivation years in plastic-greenhouse pepper production systems, accompanied by significant leaching of Ca and Mg, while K mainly accumulates in the surface layers. Full article

Speed and agility have been described as crucial abilities for soccer players. The purpose of this study was to analyze, in detail, the variance in speed and agility tasks explained by lower-body power after controlling for age and body composition. The participants were 96 male soccer players aged 16.1 ± 1.6 years. Body composition (stature, body fat percentage—BF%, body mass, and fat-free mass—FFM), lower-body power (countermovement jump—CMJ, and squat jump—SJ), speed (5-, 10-, and 35 m sprints), and agility (t-test) were assessed. Among body composition parameters, BF% presented the highest number of significant relationships with speed and agility, with the strength of correlations ranging from small (5 m sprint, r = 0.25) to large (35 m sprint, r = 0.52). The strongest correlation coefficient emerged between FFM and the 35 m sprint (r = −0.65). Significant correlations were found between vertical jump performance and the 35 m sprint (CMJ: r = −0.68; SJ: r = −0.69), followed by the t-test (CMJ: r = −0.35; SJ: r = −0.47). The hierarchical multiple regression model could explain 22% to 67% of the variance observed in agility scores and speed. BF% remained the most statistically significant negative predictor of all regression models. The CMJ remained a statistically significant positive predictor of the 35 m sprint (β = −0.581, p ≤ 0.01) after controlling for age and body composition. Integrating programs targeting lower-body power might be important to enhance speed and agility performance in youth soccer. On the other hand, future research based on multidisciplinary approaches to investigate the effects of nutritional strategies in reducing or preventing gains in BF% is still needed, which remained a significant predictor of sprint and agility performance in the final models. Full article

Lattice structures have become an innovative solution for the improvement of part design, as they are able to substitute solid regions, maintain mechanical capabilities, and reduce material usage; however, dimensional quality control of these geometries is challenging. X-ray computed tomography (XCT) is the most suitable non-destructive metrological technique as it is capable of characterizing internal features and hidden elements. Uncertainty estimation of XCT is still in development, and studies typically use high-resolution calibrated devices such as focal variation microscopes (FVMs) as a reference, focusing on certain parts of the lattice but not the whole structure. In this paper, an estimation of the accuracy of XCT evaluation of a complete lattice structure in comparison to a higher-resolution reference device (FVM) is presented. Experimental measurements are taken on ad hoc designed test objects manufactured in polyamide 12 (PA12) using selective laser sintering (SLS), optimized for the evaluation on both instruments using different cubic-based lattice typologies. The results confirm higher precision on XCT evaluation in both qualitative and quantitative analysis. Even with a lower resolution, XCT is able to characterize details of the surface such as re-entrant features; as well, standard deviations and uncertainties in strut diameter evaluation remain more stable in all cells in XCT, identifying on the other hand reconstruction problems on FVM measurements. Moreover, it is shown that, using XCT, no additional evaluation errors were found in inner cells, suggesting that the measurement of external elements could be representative of the whole structure for metrological purposes. Full article

Effective emission control technologies and eco-friendly propulsion systems have been developed to decrease exhaust particle emissions. However, more work must be conducted on non-exhaust traffic-related sources such as tyre wear. The advent of automated vehicles (AVs) enables researchers and automotive manufacturers to consider ways to further decrease tyre wear, as vehicles will be controlled by the system rather than by the driver. In this direction, this work presents the formulation of an optimal control problem for the trajectory optimisation of automated articulated vehicles for tyre wear minimisation. The optimum velocity profile is sought for a predefined road path from a specific starting point to a final one to minimise tyre wear in fixed time cases. Specific boundaries and constraints are applied to the problem to ensure the vehicle’s stability and the feasibility of the solution. According to the results, a small increase in the journey time leads to a significant decrease in the mass loss due to tyre wear. The employment of articulated vehicles with low powertrain capabilities leads to greater tyre wear, while excessive increases in powertrain capabilities are not required. The conclusions pave the way for AV researchers and manufacturers to consider tyre wear in their control modules and come closer to the zero-emission goal. Full article

The accurate prediction of heavy precipitation in convective environments is crucial because such events, often occurring in Italy during the summer and fall seasons, can be a threat for people and properties. In this paper, we analyse the impact of satellite-derived surface-rainfall-rate data assimilation on the Weather Research and Forecasting (WRF) model’s precipitation prediction, considering 15 days in summer 2022 and 17 days in fall 2022, where moderate to intense precipitation was observed over Italy. A 3DVar realised at CNR-ISAC (National Research Council of Italy, Institute of Atmospheric Sciences and Climate) is used to assimilate two different satellite-derived rain rate products, both exploiting geostationary (GEO), infrared (IR), and low-Earth-orbit (LEO) microwave (MW) measurements: One is based on an artificial neural network (NN), and the other one is the operational P-IN-SEVIRI-PMW product (H60), delivered in near-real time by the EUMETSAT HSAF (Satellite Application Facility in Support of Operational Hydrology and Water Management). The forecast is verified in two periods: the hours from 1 to 4 (1–4 h phase) and the hours from 3 to 6 (3–6 h phase) after the assimilation. The results show that the rain rate assimilation improves the precipitation forecast in both seasons and for both forecast phases, even if the improvement in the 3–6 h phase is found mainly in summer. The assimilation of H60 produces a high number of false alarms, which has a negative impact on the forecast, especially for intense events (30 mm/3 h). The assimilation of the NN rain rate gives more balanced predictions, improving the control forecast without significantly increasing false alarms. Full article

A bacterium was isolated and identified from the secretion of a rhesus monkey with endometritis. The morphological results showed that the strain exhibited round, convex, gray-white colonies with smooth surfaces and diameters ranging from 1 to 2 mm when cultured on Columbia blood agar at 37 °C for 24 h; on salmonella–shigella agar (S.S.) at 37 °C for 24 h, the colonies appeared round, flat, and translucent. Gram staining showed negative results with blunt ends and non-spore-forming characteristics. Molecular biology results showed that the 16S rRNA sequence of the strain revealed over 96.9% similarity with published sequences of M. morganii from different sources in the NCBI GenBank database. Morphological and molecular biology analysis confirmed that the strain (RM2023) isolated from cervical secretions of rhesus monkey was M. morganii. Drug sensitivity testing demonstrated that the isolated strain (RM2023) was sensitive to ceftriaxone, amikacin, gentamicin, cefazolin, cefuroxime, ceftazidime, levofloxacin, cotrimoxazole, norfloxacin, and tetracycline; moderately sensitive to ampicillin; and resistant to penicillin, vancomycin, ciprofloxacin, and clindamycin. The research findings provide valuable insights for disease prevention in rhesus monkeys and contribute to molecular epidemiological studies. Full article

 This research, focusing on the environmental impact of tire and brake disc pad wear, constitutes a significant area of transport-related studies. These two key vehicle components are not only the most frequently worn but also generate micro- and nano-pollutants (i.e., rubber, metal oxides) that potentially harm the environment. Over half of the globally produced natural and synthetic rubbers, which amounted to about 30 million tons in 2022, are used for tire production. This work focuses on the study of roadside snow, sand, and standing water deposits from various locations in the urban agglomeration (Poznań, Poland) during the winter season, determining their qualitative composition and the quantitative content of pollutants originating from tire abrasion. In addition, the method of washing nano- and micro-rubber particles and their full characteristics was also presented. Fourier-transform infrared (FT-IR) and nuclear magnetic resonance (NMR) spectroscopic studies, optical and scanning electron microscopy (SEM-EDS), particle size studies using a dynamic light scattering (DLS) particle analyzer, and thermogravimetric analysis (TGA) were conducted for a detailed characterization of the pollutants in the environment. The conducted particle separation methods allowed for the extraction of a fraction mainly containing gum residues with particle sizes less than 2 µm. The results of these tests make it possible to estimate the level of contamination with rubber and metal residues during the abrasion of tires, pads, and brake discs while driving, which is crucial for understanding the impact of vehicle part exploitation on the environment.  Full article

The potential outcomes framework serves as a fundamental tool for quantifying causal effects. The average dose–response function $\mu \left(t\right)$ (also called the effect curve) is typically of interest when dealing with a continuous treatment variable (exposure). The focus of this work is to determine the impact of an extreme level of treatment, potentially beyond the range of observed values—that is, estimating $\mu \left(t\right)$ for very large t. Our approach is grounded in the field of statistics known as extreme value theory. We outline key assumptions for the identifiability of the extreme treatment effect. Additionally, we present a novel and consistent estimation procedure that can potentially reduce the dimension of the confounders to at most 3. This is a significant result since typically, the estimation of $\mu \left(t\right)$ is very challenging due to high-dimensional confounders. In practical applications, our framework proves valuable when assessing the effects of scenarios such as drug overdoses, extreme river discharges, or extremely high temperatures on a variable of interest. Full article

Obesity is currently considered a public health problem in both developed and developing countries. Gender- and age-specific body mass index (BMI) growth standards or references are particularly effective in monitoring the global obesity pandemic. This study aimed to report disparities in age-, gender- and ethnic-specific statistical estimates of overweight and obesity for 2–18 years aged Pakistani children and adolescents using the World Health Organization (WHO), the Center for Disease Control (CDC) 2000 references, the International Obesity Task Force (IOTF) and Pakistani references for BMI. Methods: The study used secondary data of 10,668 pediatric population, aged 2–18 years. Demographic information like age (years), gender, city and anthropometric examinations, i.e., height (cm) and weight (kg) were used in this study. The recommended age- and gender-specific BMI cut-offs of the WHO, CDC 2000 and the IOTF references were used to classify the children sampled as overweight and obese. For the Pakistani reference, overweight and obesity were defined as BMI-for-age ≥ 85th percentile and BMI-for-age ≥ 95th percentile, respectively. Cohen’s κ statistic was used to assess the agreement between the international references and local study population references in the classification of overweight/obesity. Results: The statistical estimates (%) of the participants for overweight and obesity varied according to the reference used: WHO (7.4% and 2.2%), CDC (4.9% and 2.1%), IOTF (5.2% and 2.0%) and Pakistan (8.8% and 6.0%), respectively; suggesting higher levels of overweight and obesity prevalence when local study references are used. The Kappa statistic shows a moderate to excellent agreement (κ ≥ 0.6) among three international references when classifying child overweight and obesity and poor agreement between local references and the WHO (0.45, 0.52), CDC (0.25, 0.50) and IOTF references (0.16, 0.31), for overweight and obesity, respectively. Conclusions: The results of the study showed a visible difference in the estimates of excess body weight after applying the WHO, CDC, IOTF and local BMI references to the study population. Based on the disparity results and poor agreement between international references and the local study reference, this study recommends using local BMI references in identifying children with overweight and obesity. Full article

The escalating demand for enhanced therapeutic efficacy and reduced adverse effects in the pharmaceutical domain has catalyzed a new frontier of innovation and research in the field of pharmacy: novel drug delivery systems. These systems are designed to address the limitations of conventional drug administration, such as abbreviated half-life, inadequate targeting, low solubility, and bioavailability. As the disciplines of pharmacy, materials science, and biomedicine continue to advance and converge, the development of efficient and safe drug delivery systems, including biopharmaceutical formulations, has garnered significant attention both domestically and internationally. This article presents an overview of the latest advancements in drug delivery systems, categorized into four primary areas: carrier-based and coupling-based targeted drug delivery systems, intelligent drug delivery systems, and drug delivery devices, based on their main objectives and methodologies. Additionally, it critically analyzes the technological bottlenecks, current research challenges, and future trends in the application of novel drug delivery systems. Full article

Understanding the nuanced interplay between plant polyphenols and starch could have significant implications. For example, it could lead to the development of tailor-made starches for specific applications, from bakinag and brewing to pharmaceuticals and bioplastics. In addition, this knowledge could contribute to the formulation of functional foods with lower glycemic indexes or improved nutrient delivery. Variations in the complexes can be attributed to differences in molecular weight, structure, and even the content of the polyphenols. In addition, the unique structural characteristics of starches, such as amylose/amylopectin ratio and crystalline density, also contribute to the observed effects. Processing conditions and methods will always alter the formation of complexes. As the type of starch/polyphenol can have a significant impact on the formation of the complex, the selection of suitable botanical sources of starch/polyphenols has become a focus. Spectroscopy coupled with chemometrics is a convenient and accurate method for rapidly identifying starches/polyphenols and screening for the desired botanical source. Understanding these relationships is crucial for optimizing starch-based systems in various applications, from food technology to pharmaceutical formulations. Full article

Eelgrass meadows have attracted much attention not only for their ability to maintain marine ecosystems as feeding grounds for marine organisms but also for their potential to store atmospheric and dissolved CO₂ as blue carbon. This study comprehensively evaluated the bacterial and chemical data obtained from eelgrass sediments of different scales along the Japanese coast to investigate the effect on the acclimatization of eelgrass. Regardless of the eelgrass habitat, approximately 1% Anaerolineales, Babeliales, Cytophagales, and Phycisphaerales was present in the bottom sediment. Sulfate-reducing bacteria (SRB) were present at 3.69% in eelgrass sediment compared to 1.70% in bare sediment. Sulfur-oxidizing bacteria (SOB) were present at 2.81% and 1.10% in the eelgrass and bare sediment, respectively. Bacterial composition analysis and linear discriminant analysis revealed that SOB detoxified H₂S in the eelgrass meadows and that the larger-scale eelgrass meadows had a higher diversity of SOB. Our result indicated that there were regional differences in the system that detoxifies H₂S in eelgrass meadows, either microbial oxidation mediated by SOB or O₂ permeation via the physical diffusion of benthos. However, since bacterial flora and phylogenetic analyses cannot show bias and/or causality due to PCR, future kinetic studies on microbial metabolism are expected. Full article

Urethane acrylate (UA) was synthesized from various di-polyols, such as poly(tetrahydrofuran) (PTMG, Mn = 1000), poly(ethylene glycol) (PEG, Mn = 1000), and poly(propylene glycol) (PPG, Mn = 1000), for use as a polymer binder for paint. Polymethyl methacrylate (PMMA) and UA were blended to form an acrylic resin with high transmittance and stress-strain curve. When PMMA was blended with UA, a network structure was formed due to physical entanglement between the two polymers, increasing the mechanical properties. UA was synthesized by forming a prepolymer using di-polyol and hexamethylene diisocyanate, which were chain structure monomers, and capping them with 2-hydroxyethyl methacrylate to provide an acryl group. Fourier transform infrared spectroscopy was used to observe the changes in functional groups, and gel permeation chromatography was used to confirm that the three series showed similar molecular weight and PDI values. The yellowing phenomenon that appears mainly in the curing reaction of the polymer binder was solved, and the mechanical properties according to the effects of the polyol used in the main chain were compared. The content of the blended UA was quantified using ultravioletvisible spectroscopy at a wavelength of 370 nm based on 5, 10, 15, and 20 wt%, and the shear strength and tensile strength were evaluated using specimens in a suitable mode. The ratio for producing the polymer binder was optimized. The mechanical properties of the polymer binder with 5–10 wt% UA were improved in all series. Full article

Photodynamic therapy (PDT) shows promise in tumor treatment, particularly when combined with nanotechnology. This study examines the impact of deep learning, particularly the Cellpose algorithm, on the comprehension of cancer cell responses to PDT. The Cellpose algorithm enables robust morphological analysis of cancer cells, while logistic growth modelling predicts cellular behavior post-PDT. Rigorous model validation ensures the accuracy of the findings. Cellpose demonstrates significant morphological changes after PDT, affecting cellular proliferation and survival. The reliability of the findings is confirmed by model validation. This deep learning tool enhances our understanding of cancer cell dynamics after PDT. Advanced analytical techniques, such as morphological analysis and growth modeling, provide insights into the effects of PDT on hepatocellular carcinoma (HCC) cells, which could potentially improve cancer treatment efficacy. In summary, the research examines the role of deep learning in optimizing PDT parameters to personalize oncology treatment and improve efficacy. Full article