Curcumin (Curcumin) belongs to the polyphenol family. It is extracted by drying the root of a plant of Asian origin, belonging to the Zingiberaceae family. The best-known species is Curcumincuma Longa. Curcumin has been recognized as having great therapeutic powers since ancient times. Studies on curcumin have since confirmed its powerful antioxidant properties, preventing both the formation of free radicals and their neutralization, having anti-inflammatory, antibacterial, immunological, and neuroprotective properties, as well as being a regulator of the intestinal microbiota with beneficial effects on the clinical manifestations of metabolic syndrome. Our study aimed to highlight how all these therapeutic aspects could benefit oral health, both preventing and improving the course of pathological processes. The effect of mouthwashes, and curcumin-based gels on the regulation of bacterial plaque and in the control of gingivitis, was largely comparable to that of using 0.20% chlorhexidine, with fewer side effects. Being a highly hydrophobic substance, it has a high permeability to cross the cell membrane. Bioavailability increases when combined with liposoluble substances (e.g., olive oil) and piperine, which improves absorption. Curcumin also has a negligible degree of toxicity, making it an excellent alternative to the use of gold standard products for oral disinfection. Full article

The autonomous vehicle is an innovative field for the application of machine learning algorithms. Controlling an agent designed to drive safely in traffic is very complex as human behavior is difficult to predict. An individual’s actions depend on a large number of factors that cannot be acquired directly by visualization. The size of the vehicle, its vulnerability, its perception of the environment and weather conditions, among others, are all parameters that profoundly modify the actions that the optimized model should take. The agent must therefore have a great capacity for adaptation and anticipation in order to drive while ensuring the safety of users, especially pedestrians, who remain the most vulnerable users on the road. Deep reinforcement learning (DRL), a sub-field that is supported by the community for its real-time learning capability and the long-term temporal aspect of its objectives looks promising for AV control. In a previous article, we were able to show the strong capabilities of a DRL model with a continuous action space to manage the speed of a vehicle when approaching a pedestrian crossing. One of the points that remains to be addressed is the notion of discrete decision-making intrinsically linked to speed control. In this paper, we will present the problems of AV control during a pedestrian crossing, starting with a modelization and a DRL model with hybrid action space adapted to the scalability of a vehicle-to-pedestrian (V2P) encounter. We will also present the difficulties raised by the scalability and the curriculum-based method. Full article

Herbal teas have attracted attention as functional beverages containing luteolin and apigenin, which exhibit antioxidant and anti-inflammatory effects. The objective of this study was to develop a sensitive online automated method to determine these flavones’ contents in herbal teas using in-tube solid-phase microextraction (IT-SPME) coupled with liquid chromatography–tandem mass spectrometry (LC–MS/MS). These compounds were extracted and concentrated by IT-SPME using a Supel Q PLOT capillary column and then separated and detected within 6 min using a CAPCELL PAK C18 MG III analytical column and a negative electrospray ionization-mode multiple-reaction monitoring system by LC–MS/MS. The detection limits (S/N = 3) for luteolin and apigenin were 0.4 and 0.8 pg mL⁻¹, respectively, and the calibration curves were linear in the range of 2–2000 pg mL⁻¹ with correlation coefficients above 0.9995, and intra-day and inter-day precisions with relative standard deviations below 2.9 and 3.6% (n = 6), respectively. The luteolin and apigenin in herbal tea were quantified using IT-SPME/LC-MS/MS following the acid hydrolysis of their glycosides. Among the 10 herbal teas tested, luteolin was detected in peppermint and sage at concentrations of 375 and 99 µg mL⁻¹, respectively, while apigenin was detected in German chamomile at 110 µg mL⁻¹, which were higher than in the other herbal teas. The method is expected to be a useful method for evaluating the efficacy of luteolin and apigenin in herbal teas as functional beverages. Full article

Despite recent advances, the prognosis of acute myeloid leukemia (AML) remains unsatisfactory due to disease recurrence and the development of resistance to both conventional and novel therapies. Engineered T cells expressing chimeric antigen receptors (CARs) on their cellular surface represent one of the most promising anticancer agents. CAR-T cells are increasingly used in patients with B cell malignancies, with remarkable clinical results despite some immune-related toxicities. However, at present, the role of CAR-T cells in myeloid neoplasms, including AML, is extremely limited, as specific molecular targets for immune cells are generally lacking on AML blasts. Besides the paucity of dispensable targets, as myeloid antigens are often co-expressed on normal hematopoietic stem and progenitor cells with potentially intolerable myeloablation, the AML microenvironment is hostile to T cell proliferation due to inhibitory soluble factors. In addition, the rapidly progressive nature of the disease further complicates the use of CAR-T in AML. This review discusses the current state of CAR-T cell therapy in AML, including the still scanty clinical evidence and the potential approaches to overcome its limitations, including genetic modifications and combinatorial strategies, to make CAR-T cell therapy an effective option for AML patients. Full article

The Epstein-Barr virus (EBV) is frequently found in endomyocardial biopsies (EMBs) from patients with heart failure, but the detection of EBV-specific DNA has not been associated with progressive hemodynamic deterioration. In this paper, we investigate the use of targeted next-generation sequencing (NGS) to detect EBV transcripts and their correlation with myocardial inflammation in EBV-positive patients with heart failure with reduced ejection fraction (HFrEF). Forty-four HFrEF patients with positive EBV DNA detection and varying degrees of myocardial inflammation were selected. EBV-specific transcripts from EMBs were enriched using a custom hybridization capture-based workflow and, subsequently, sequenced by NGS. The short-read sequencing revealed the presence of EBV-specific transcripts in 17 patients, of which 11 had only latent EBV genes and 6 presented with lytic transcription. The immunohistochemical staining for CD3⁺ T lymphocytes showed a significant increase in the degree of myocardial inflammation in the presence of EBV lytic transcripts, suggesting a possible influence on the clinical course. These results imply the important role of EBV lytic transcripts in the pathogenesis of inflammatory heart disease and emphasize the applicability of targeted NGS in EMB diagnostics as a basis for specific treatment. Full article

The Côa region in inner-northern Portugal heavily relies on viticulture, which is a cornerstone of its economy and cultural identity. Understanding the intricate relationship between climatic variables and wine production (WP) is crucial for adapting management practices to changing climatic conditions. This study employs machine learning (ML), specifically random forest (RF) regression, to predict grapevine yields in the Côa region using high-resolution climate data for 2004–2020. SHAP (SHapley Additive exPlanations) values are used to potentially explain the non-linear relationships between climatic factors and WP. The results reveal a complex interplay between predictors and WP, with precipitation emerging as a key determinant. Higher precipitation levels in April positively impact WP by replenishing soil moisture ahead of flowering, while elevated precipitation and humidity levels in August have a negative effect, possibly due to late-season heavy rainfall damaging grapes or creating more favorable conditions for fungal pathogens. Moreover, warmer temperatures during the growing season and adequate solar radiation in winter months favor higher WP. However, excessive radiation during advanced growth stages can lead to negative effects, such as sunburn. This study underscores the importance of tailoring viticultural strategies to local climatic conditions and employing advanced analytical techniques such as SHAP values to interpret ML model predictions effectively. Furthermore, the research highlights the potential of ML models in climate change risk reduction associated with viticulture, specifically WP. By leveraging insights from ML and interpretability techniques, policymakers and stakeholders can develop adaptive strategies to safeguard viticultural livelihoods and stable WP in a changing climate, particularly in regions with a rich agrarian heritage, such as the Côa region. Full article

We reanalyze the phenomenon of verbal (non)agreement with the 2SG tu in a megacorpus of Brazilian Portuguese compiled from the web. Unlike previous research, which has analyzed sociolinguistic interview data and regional differences, we examine these data with a focus on the internal linguistic factors that constrain the variability. Our analysis of 4860 tokens of tu + verb reveals that non-agreement with the 3SG verb form is by far the most common pattern, 2SG agreement being relatively infrequent. Individual verb lexemes show highly distinct rates of (non)agreement. In addition, the specific tense/aspect/mood forms and main/auxiliary status are likewise significant factors affecting the variation. We conclude that future studies of this phenomenon should not ignore these internal linguistic factors. We situate our study within a group of other recent studies in Romance linguistics, which have found that individual verbal and constructional patterns can have diverse effects on morphosyntactic variation. Full article

With an ageing global population, healthcare systems confront challenges unique to the elderly. Current care models primarily manage health–illness shifts but frequently miss developmental transitions, particularly for older adults. Meleis’s transition theory offers an underutilized framework to rejuvenate our gerontogeriatric nursing approach. This article aims to articulate and advocate the value of Meleis’s transition theory as a framework for gerontogeriatric nursing, focusing on developmental transitions, thereby seeking a transformative change in the quality of elderly care. The article delves into Meleis’s transition theory’s vital components—transition types, conditions, and nursing therapeutics. It explores how these can be a multifaceted guide for gauging and overseeing ageing’s developmental shifts; adopting this theoretical perspective deepens our comprehension and bears tangible implications. Nurses versed in this theory could appreciate the benefits of a nuanced approach to the elderly, distinguishing it from the conventional biomedical stance. As the demands of an ageing populace grow, the integration of Meleis’s transition theory into nursing practices is not merely beneficial but imperative, setting a new standard for comprehensive and specialized elderly care. Full article

Malawi has the potential to explore the utilization of biogas technology. The technology has existed in the country for decades. However, the uptake has been lower than expected. Further, there has been a high rate of dis-adoption of the installed systems. To deal with the problem, this study explored the opportunities and barriers to biogas technology to enhance biogas adoption and utilization in Malawi. Qualitative research methods using key informant interviews were employed to collect the data from biogas adopters, dis-adopters, potential adopters, and experts. A total of 22 households and 6 experts were interviewed. The findings of the study show that the country has opportunities for biogas adoption and utilization. The most mentioned opportunities were livestock farming practices, constraints to access to reliable energy sources, associated benefits of biogas technology, and land holding. However, the adoption of the technology has faced several challenges. Commonly cited barriers were the high installation and maintenance costs, inadequate feedstock, inappropriate dissemination approaches, lack of training after installation services and expertise, lack of reliable water sources, absence of ownership, lack of cooperation amongst institutions involved in biogas promotion, lack of a coordinating body for institutions involved in biogas dissemination, lack of standards, and socio-cultural factors. To overcome the challenges, strategies were identified, and these include the provision of incentives, loans and subsidies, provision of technical support services, having demonstration sites, employing suitable dissemination approaches, co-digestion or diversification of raw materials, awareness campaigns, and collaboration amongst sectors involved in biogas dissemination. Full article

In modern agricultural production, where a small number of commercial cultivars dominate, the collection, evaluation, and preservation of germplasm are important tasks to reduce the erosion of genes and preserve biodiversity. The aim of this study is to characterize the morphological and fruit chemical properties of the pomegranate germplasm grown on the East Adriatic coast, including the commercial cultivars ‘Hicaznar’, ‘Granada’, and ‘Wonderful’, and to highlight the characteristics with the greatest discriminating power. The characterization of the tree, leaf, flower, arils, seed, and juice was carried out using the UPOV descriptor. The colors of the peel, arils, and juice were analyzed according to the CIEL*a*b* method, total soluble solids were measured using refractometers, and total acidity was determined by titration with 0.1 M NaOH. The research results showed significant diversity between the cultivars, which were grouped into several clusters using an unsupervised analysis technique. Factors such as plant vigor, plant growth habit, predominant number of leaves per node on young shoots, crown type, fruit shape, fruit shape in cross-section, peel weight, total aril weight, aril weight, number of arils per fruit, seed length and width, seed yield, total acidity, TSS/TA ratio, and color parameters of the peel, arils, and juice showed high variability, indicating their strong discriminating power in determining the phenotypic diversity of pomegranate. Full article

Keloids, marked by abnormal cellular proliferation and excessive extracellular matrix (ECM) accumulation, pose significant therapeutic challenges. Ethyl pyruvate (EP), an inhibitor of the high-mobility group box 1 (HMGB1) and TGF-β1 pathways, has emerged as a potential anti-fibrotic agent. Our research evaluated EP’s effects on keloid fibroblast (KF) proliferation and ECM production, employing both in vitro cell cultures and ex vivo patient-derived keloid spheroids. We also analyzed the expression levels of ECM components in keloid tissue spheroids treated with EP through immunohistochemistry. Findings revealed that EP treatment impedes the nuclear translocation of HMGB1 and diminishes KF proliferation. Additionally, EP significantly lowered mRNA and protein levels of collagen I and III by attenuating TGF-β1 and pSmad2/3 complex expression in both human dermal fibroblasts and KFs. Moreover, metalloproteinase I (MMP-1) and MMP-3 mRNA levels saw a notable increase following EP administration. In keloid spheroids, EP induced a dose-dependent reduction in ECM component expression. Immunohistochemical and western blot analyses confirmed significant declines in collagen I, collagen III, fibronectin, elastin, TGF-β, AKT, and ERK 1/2 expression levels. These outcomes underscore EP’s antifibrotic potential, suggesting its viability as a therapeutic approach for keloids. Full article

This paper discusses the time-fractional nonlinear Schrödinger model with optical soliton solutions. We employ the $\left(f+\left(\frac{G^{\prime }}{G}\right)\right)$-expansion method to attain the optical solution solutions. An important tool for explaining the particular explosion of brief pulses in optical fibers is the nonlinear Schrödinger model. It can also be utilized in a telecommunications system. The suggested method yields trigonometric solutions such as dark, bright, kink, and anti-kink-type optical soliton solutions. Mathematica 11 software creates 2D and 3D graphs for many physically important parameters. The computational method is effective and generally appropriate for solving analytical problems related to complicated nonlinear issues that have emerged in the recent history of nonlinear optics and mathematical physics. Furthermore, we venture into uncharted territory by subjecting our model to chaotic and sensitivity analysis, shedding light on its robustness and responsiveness to perturbations. The proposed technique is being applied to this model for the first time. Full article

Prion diseases are fatal neurodegenerative disorders characterized by an accumulation of misfolded prion protein (PrP^Sc) in brain tissues. The shadow of prion protein (Sho) encoded by the shadow of prion protein gene (SPRN) is involved in prion disease progress. The interaction between Sho and PrP accelerates the PrP^Sc conversion rate while the SPRN gene polymorphisms have been associated with prion disease susceptibility in several species. Until now, the SPRN gene has not been investigated in ducks. We identified the duck SPRN gene sequence and investigated the genetic polymorphisms of 184 Pekin ducks. We compared the duck SPRN nucleotide sequence and the duck Sho protein amino acid sequence with those of several other species. Finally, we predicted the duck Sho protein structure and the effects of non-synonymous single nucleotide polymorphisms (SNPs) using computational programs. We were the first to report the Pekin duck SPRN gene sequence. The duck Sho protein sequence showed 100% identity compared with the chicken Sho protein sequence. We found 27 novel SNPs in the duck SPRN gene. Four amino acid substitutions were predicted to affect the hydrogen bond distribution in the duck Sho protein structure. Although MutPred2 and SNPs&GO predicted that all non-synonymous polymorphisms were neutral or benign, SIFT predicted that four variants, A22T, G49D, A68T, and M105I, were deleterious. To the best of our knowledge, this is the first report about the genetic and structural characteristics of the duck SPRN gene. Full article

An intelligent optimization technology was proposed to mitigate prevalent multi-defects, particularly failure, wrinkling, and springback in sheet metal forming. This method combined deep neural networks (DNNs), genetic algorithms (GAs), and Monte Carlo simulation (MCS), collectively as DNN-GA-MCS. Our primary aim was to determine intricate process parameters while elucidating the intricate relationship between processing methodologies and material properties. To achieve this goal, variable blank holder force (VBHF) trajectories were implemented into five sub-stroke steps, facilitating adjustments to the blank holder force via numerical simulations with an oil pan model. The Forming Limit Diagram (FLD) predicted by machine learning algorithms based on the Generalized Incremental Stress State Dependent Damage (GISSMO) model provided a robust framework for evaluating sheet failure dynamics during the stamping process. Numerical results confirmed significant improvements in formed quality: compared with the average value of training sets, the improvements of 18.89%, 13.59%, and 14.26% are achieved in failure, wrinkling, and springback; in the purposed two-segmented mode VBHF case application, the average value of three defects is improved by 12.62%, and the total summation of VBHF is reduced by 14.07%. Statistical methodologies grounded in material flow analysis were applied, accompanied by the proposal of distinctive optimization strategies for the die structure aimed at enhancing material flow efficiency. In conclusion, our advanced methodology exhibits considerable potential to improve sheet metal forming processes, highlighting its significant effect on defect reduction. Full article

Few-shot object detection is a challenging task aimed at recognizing novel classes and localizing with limited labeled data. Although substantial achievements have been obtained, existing methods mostly struggle with forgetting and lack stability across various few-shot training samples. In this paper, we reveal two gaps affecting meta-knowledge transfer, leading to unstable performance and forgetting in meta-learning-based frameworks. To this end, we propose sample normalization, a simple yet effective method that enhances performance stability and decreases forgetting. Additionally, we apply Z-score normalization to mitigate the hubness problem in high-dimensional feature space. Experimental results on the PASCAL VOC data set demonstrate that our approach outperforms existing methods in both accuracy and stability, achieving up to +4.4 [email protected] and +5.3 mAR in a single run, with +4.8 [email protected] and +5.1 mAR over 10 random experiments on average. Furthermore, our method alleviates the drop in performance of base classes. The code will be released to facilitate future research. Full article

Land formation seriously disturbs coastal salt marsh wetland ecosystems, while its influences on soil organic carbon (SOC) under chronosequences remain unclear. In this study, the impacts of the land formation time (from one to fourteen years) and soil properties on the chronosequences changes of SOC in the nascent wetland of Hengsha Island were investigated. The study results showed the following. (1) As the land-formation time extended, the SOC experienced a significant increase, tripling after a period of 14 years. The changes in SOC occurred mainly in the surface layer but not in the deep soil layer. Specifically, the surface layer’s average SOC reached 5.52 g·kg⁻¹, markedly higher than 3.17 g·kg⁻¹ in the deeper layer. (2) Spearman correlation analysis revealed that the ammonium nitrogen (${\mathrm{NH}}_4^{+}$-N), aboveground biomass (AGB), and soil water content (SWC) were positively correlated with the SOC. Methane emissions (CH₄) and SOC exhibited a negative correlation. (3) The structural equation model (SEM) illustrated that the duration of soil deformation directly impacted the vegetation growth and affected the distribution characteristics of the SOC by modifying the soil environmental conditions. Changes in SOC following land formation influenced the rapid succession of soil properties and vegetation, with the modification of carbon sinks in the ecosystems. Full article

Lacticaseibacillus rhamnosus is applied as a probiotic to alleviate various metabolic, gastrointestinal, and psychological symptoms and diseases, and its probiotic effectiveness is strain-specific. In this study, we obtained 21 strains of Ls. rhamnosus, and their genomes were sequenced. We defined the pan- and core-genomes of Ls. rhamnosus. Phenotypes such as the assimilation of carbohydrates and antibiotic resistance were experimentally characterized and associated with genome annotations. Nine strains were selected and tested for growth rates, tolerance to acidity/alkalinity and bile acids, the production of short-chain fatty acids, and competition with pathogenic microbes. Strains WL11 and WL17 were targeted as potential probiotics and were applied in mouse model tests for the alleviation of chronic fatigue syndrome (CFS) and irritable bowel syndrome (IBS). The results showed that WL11 and WL17 effectively alleviated slow body weight gain, anxiety, poor memory, and cognitive impairment in CFS mouse models. They also reduced the expression of pro-inflammatory factors, such as TNF-α and IL-6, and alleviated intestinal peristalsis, visceral hypersensitivity, and anxiety-like behavior in IBS mouse models. This study reports new Ls. rhamnosus strain resources and their effect on alleviation of both IBS and CFS symptoms with mouse models; the probiotic functions of those strains in human patients remain to be further tested. Full article

Existing methods for inverse synthetic aperture radar (ISAR) target recognition typically rely on a single high-resolution radar signal type, such as ISAR images or high-resolution range profiles (HRRPs). However, ISAR images and HRRP data offer representations of targets across different aspects, each containing valuable information crucial for radar target recognition. Moreover, the process of generating ISAR images inherently facilitates the acquisition of HRRP data, ensuring timely data collection. Therefore, to fully leverage the different information from both HRRP data and ISAR images and enhance ISAR ship target recognition performance, we propose a novel deep fusion network named the Separation-Decision Recognition network (SDRnet). First, our approach employs a convolutional neural network (CNN) to extract initial feature vectors from ISAR images and HRRP data. Subsequently, a feature separation module is employed to derive a more robust target representation. Finally, we introduce a weighted decision module to enhance overall predictive performance. We validate our method using simulated and measured data containing ten categories of ship targets. The experimental results confirm the effectiveness of our approach in improving ISAR ship target recognition. Full article

For developing novel photosensitizers with therapeutic potential in non-malignant and malignant cutaneous disorders, the unsymmetrical porphyrin, 5-(2-hydroxy-3-methoxyphenyl)-10, 15, 20-tris-(4-carboxymethylphenyl) porphyrin, was evaluated in silico and in vitro. The cellular uptake of the investigated porphyrin and its ability to perform photodynamic therapy were investigated in terms of the viability, proliferation, and necrosis of human HaCaT keratinocytes and human Hs27 skin fibroblasts, in correlation with the predictions regarding diffusion through cell membranes, ADMET profile (absorption, distribution, metabolism, elimination, toxicity), and potential pharmacological mechanism. Molecular docking and 250 ns molecular dynamics simulations revealed that P5.2 has the potential to form a relatively stable complex with the carbonic anhydrase IX catalytic site, the lowest predicted free energy of binding (MM/PBSA) being −39.097 kcal/mol. The results of the in vitro study showed that P5.2 is incorporated within 24 h in the investigated cells, especially in HaCaT keratinocytes, indicating its photosensitizing ability. Nevertheless, P5.2 does not exert significant cytotoxicity in “dark” conditions. In turn, PDT induced a decrease in the number of metabolically active HaCaT keratinocytes within 24 h, accompanied by a 4-fold increase in lactate dehydrogenase release, indicating its ability to perform PDT in human skin cells. The experimental results suggest that the asymmetrical porphyrin is a promising candidate theranostics agent for skin disorders. Full article

Shallow geothermal or ground source heat pump (GSHP) energy systems offer efficient space heating and cooling, reducing greenhouse gas emissions and electrical consumption. Incorporating ground heat exchangers (GHEs) within pile foundations, as part of these GSHP systems, has gained significant attention as it can reduce capital costs. The design and optimisation of GHEs connected in parallel within energy piles have been researched widely, considering symmetrical placement, while the potential misplacement due to construction errors and the optimal placement remain mostly unexplored. This study utilises 3D finite element numerical methods, analysing energy piles with diameters from 0.5 m to 1.4 m, equipped with parallelly connected U-tube and W-tube GHEs. The impact of GHE loop placement is analysed, considering the influence of the ground and concrete thermal conductivities, pile length, fluid flow rate, GHE pipe diameter, and pile spacing. Results indicate a marginal impact, less than 3%, on the overall heat transfer when loops deviate from symmetry and less than 5% on the total heat transfer shared by each loop, except for highly non-symmetric configurations. Symmetrical and evenly spaced loop placement generally maintains favourable thermal performance and ease of installation. This study underscores the flexibility in GHE design and construction with a low risk of thermal yield variations due to uncertainties, particularly with a separation-to-shank distance ratio between 0.5 and 1.5 in a symmetrical distribution. Full article

The Guangdong historical trail comprises two ancient trails, known as Yile (宜乐) and Xijing (西京); can be found within the borders of Lechang (乐昌); and is an integral part of the northern section of the Guangdong historical trail, connecting Hunan and Guangdong. Along these routes, there are various types of ancestral halls. The objectives of this study include analyzing various levels of information about ancestral hall architecture, determining their respective importance through AHP hierarchical analysis, classifying architectural features via cluster analysis using SPSS, and exploring the geographical distribution trajectories of ancestral halls along the ancient paths using GIS technology. Ultimately, this study seeks to shed light on the influence of different cultures brought by the ancient road on the distribution of architectural types and identify three distinct types of ancestral halls. Full article