bluuebunny/crossref_metadata_2025 huggingface dataset:
Supplementation of Miso to a Western-Type Diet Stimulates ILC3s and Decreases Inflammation in the Small Intestine
Authors: Budau River , Okamura Takuro , Hasegawa Yuka , Nakanishi Naoko , Hamaguchi Masahide , Fukui Michiaki
Published: October 2024

Background/Objectives: Western-type diets (WDs) damage the intestinal barrier by disrupting the gut microbiota composition and causing inflammation, leading to the development of obesity, type 2 diabetes, and non-alcoholic fatty liver disease. Short-chain fatty acids (SCFAs) are produced by the gut microbiota and found in fermented foods and can stimulate the anti-inflammatory action of type 3 innate lymphoid cells (ILCS3s) in the intestine. This study hypothesised that supplementing miso, a Japanese fermented food, to a WD could increase the levels of SCFAs and thus stimulate ILC3s, decreasing inflammation in the intestine and protecting intestinal barrier integrity. Methods: Mice with RORγt total (KI/KI) or partial (KI/w) knockout were fed a high-fat high-sugar diet (HFHSD) for eight weeks as a model of WD. Half of the mice received miso supplementation in addition to the HFHSD. Weight gain, glucose tolerance and insulin resistance, intestinal barrier integrity, intestinal immunity, and liver condition were assessed. Results: Miso supplementation increased SCFA levels in the small intestine, which stimulated ILC3 function in KI/w mice. Glucose tolerance was improved, intestinal barrier integrity was ameliorated, and mucus production was increased. The level of IL-22 was increased, while pro-inflammatory ILC1s, M1 macrophages, TNF-α, and IL-1β were decreased. Liver condition was not affected. Conclusions: This study demonstrated that miso supplementation influenced several factors involved in inflammation and intestinal barrier integrity by stimulating ILC3s in RORγt heterozygous mice. Moreover, it showed that the number of ILC3s is not the key factor in immune regulation, but rather the ability of ILC3 to produce IL-22 and employ it to control the immune response in the small intestine.
Serum Iron Status and Retinal Degenerative Diseases: A Mendelian Randomization Study on AMD, RP, and DR
Authors: Qu Sichang , Zhu Yewen , Pfeiffer Norbert , Grus Franz H.
Published: October 2024

Background: Observational studies have noted that patients with certain retinal degenerative diseases exhibit iron disturbances in the retina or vitreous compared to healthy controls. However, the connection between serum iron status and these diseases remains unclear. This study aims to explore the potential causal relationship between serum iron status biomarkers and the development of age-related macular degeneration (AMD), retinitis pigmentosa (RP), and diabetic retinopathy (DR). Methods: A two-sample Mendelian randomization (MR) analysis was conducted to investigate the causal relationship between serum iron status and several retinal degenerative diseases. Genome-wide association study (GWAS) summary-level data were extracted from public GWAS databases. Inverse-variance weighting (IVW), MR-Egger regressions, Simple model, Weighted median, and Weight mode were used as MR methods. Sensitivity analysis was conducted to confirm the robustness of the results by examining horizontal pleiotropy and heterogeneity through MR-Egger intercept and leave-one-out analysis. Results: The MR analysis revealed causal relationships between genetically predicted serum iron status biomarkers and various retinal diseases. Transferrin was positively associated with the odds of AMD (whether dry or wet) (OR = 1.167, 95% CI = 1.045–1.304, p = 0.006) and wet AMD (OR = 1.194, 95% CI = 1.018–1.402, p = 0.030). Ferritin was negatively associated with the odds of wet AMD (OR = 0.555, 95% CI = 0.333–0.927, p = 0.024). Serum iron (OR = 0.508, 95% CI = 0.260–0.993, p = 0.048) and transferrin saturation (OR = 0.508, 95% CI = 0.260–0.993, p = 0.048) were negatively associated with the odds of RP. Conclusions: These findings provide evidence supporting a potential causal relationship between serum iron status and various retinal degenerative diseases, highlighting a direction for future research into the underlying mechanisms of these diseases.
Updated-Food Choice Questionnaire: Cultural Adaptation and Validation in a Spanish-Speaking Population from Mexico
Authors: Salas-García Miguel , Bernal-Orozco María , Díaz-López Andrés , Betancourt-Núñez Alejandra , Nava-Amante Pablo , Danquah Ina , Martínez J. , de Luis Daniel , Vizmanos Barbara
Published: October 2024

Background: Determinants and motives related to food selection have evolved in a globalized and changing world. The traditional and useful Food Choice Questionnaire (FCQ), created in 1995, needs to be updated, adapted to new scenarios, and validated. Objectives: This study aimed to: (1) assess face validity (FV) of the original 36-item FCQ, (2) generate an Updated-FCQ (U-FCQ) and assess its content validity (CV) (instrument suitability), and (3) evaluate its construct validity and reliability in a Spanish-speaking population from Mexico. Methods: FV involved a panel of nutrition professionals (NPs) rating the original items’ clarity, relevance, specificity, and representativeness. A literature review process updated the FCQ by adding new items. CV with a second NP panel allowed calculating content validity ratio (CVR). Construct validation was performed via exploratory and confirmatory factor analysis (EFA-CFA). Internal consistency through Cronbach’s alpha (CA) and test–retest reliability via intra-class correlation (ICC) were assessed. Results: The FV (n = 8) resulted in the modification of 11 original items. The literature review added 36 new items (15 from previous adaptations and 21 original items). The CV (n = 13) identified nine items (non-acceptable CVR), prompting reformulation of seven and removal of two. The NPs’ feedback added six new items. The EFA-CFA (n = 788) developed a 75-item U-FCQ with eight dimensions: sensory appeal, mood, health and nutritional content, price, food identity, environmental and wildlife awareness, convenience, and image management. CA ranged from 0.74–0.97 (good–excellent) and ICC from 0.51–0.78 (moderate–good). Conclusions: This study provides a useful instrument for the assessment of food choices and lays the groundwork for future cross-cultural comparisons, expanding its applicability in wider settings.
Sodium Benzoate Induces Fat Accumulation and Reduces Lifespan via the SKN-1/Nrf2 Signaling Pathway: Evidence from the Caenorhabditis elegans Model
Authors: Lee Jiah D. , Lee Jiwoo , Vang Jerry , Pan Xiaoping
Published: October 2024

Background: Sodium benzoate (SB) is widely used in food products, cosmetics, and medical solutions due to its antimicrobial properties. While it is generally considered safe and has potential neuroprotective benefits, SB has also been linked to adverse effects, including hepatic oxidative stress and inflammation. However, the potential effects of SB on obesity and lifespan remain poorly understood. Objectives: In this study, we investigated the effects of SB on fat accumulation and lifespan using the nematode Caenorhabditis elegans (C. elegans) as a model system. Methods: Wild-type worms were exposed to various SB concentrations (0%, 0.0004%, 0.0008%, 0.004%, and 0.1%) and 0.016% glucose as a positive control for 72 h in liquid or on NGM agar plates. Result: Fat accumulation was assessed through the Oil Red O staining, which revealed that SB induced more fat accumulation compared to vehicle control, even at low concentrations, including the dosage of 0.0004%. Lifespan analysis also demonstrated that SB significantly reduced lifespan in wild-type worms, even at low concentrations. Further investigations found that SKN-1 (an Nrf2 homolog) is necessary for SB-induced fat accumulation and lifespan reduction. Moreover, SB inhibited the nuclear localization of SKN-1 under oxidative stress conditions. Conclusion: These findings suggest that SB may induce fat accumulation and reduce lifespan by inhibiting the oxidative stress-mediated SKN-1 signaling pathway.
Assessing Drug Product Shelf Life Using the Accelerated Stability Assessment Program: A Case Study of a GLPG4399 Capsule Formulation
Authors: Modhave Dattatray , Vrielynck Sara , Roeleveld Kevin
Published: October 2024

Objective: To evaluate and project the shelf life of GLPG4399, an early-phase clinical drug formulation by applying the Accelerated Stability Assessment Program (ASAP) approach. Methods: Forced degradation conditions were implemented to identify the stability-limiting degradation product. The drug and its degradation products were separated using a validated liquid chromatography method. Then, the selected clinical capsule formulation was placed in a glass vial and exposed to accelerated short-term conditions of combinations of high- and low-level heat and humidity in an open state for 5 weeks. The liquid chromatography results were evaluated using the ASAP, which is based on the moisture-modified Arrhenius principle. The resulting data were fitted using a suitable diffusion kinetics method. Results: The developed model was applied to predict the shelf life of the drug product when using clinically appropriate primary packaging (high-density polyethylene container). The derived stability parameters of the moisture-modified Arrhenius equation were the Arrhenius collision frequency, activation energy, and humidity sensitivity constant. The goodness of fit parameters R2 (>0.95) and goodness of prediction Q2 (>0.80) parameters for the selected model were acceptable. The results of the accelerated, short-term stability study were verified against real-time, long-term 12-month data. Conclusions: We demonstrated the application of the ASAP approach to evaluate the shelf life of a GLPG4399 solid capsule formulation. The studied ASAP approach can be extended to evaluate the stability and shelf-life estimations of other early-phase clinical formulations.
Skin Structure, Physiology, and Pathology in Topical and Transdermal Drug Delivery
Authors: Brito Sofia , Baek Moonki , Bin Bum-Ho
Published: October 2024

Several industries are increasingly focused on enhancing the delivery of active ingredients through the skin to optimize therapeutic outcomes. By facilitating the penetration of active ingredients through the skin barrier, these enhancers can significantly improve the efficacy of various formulations, ranging from skincare products to therapeutic agents targeting systemic circulation. As the understanding of skin physiology and the mechanisms of drug absorption deepen, these industries are adopting permeation enhancers more widely, ultimately leading to better patient outcomes and expanded treatment options. However, the structure and physiological function of the skin can vary according to different factors, such as the area of the body and between individuals. These variations, along with external environmental exposures, aging and pathological conditions, introduce complexities that must be carefully considered when designing effective delivery systems. Considering the intricacies of skin structure and physiology, tailoring systems to account for regional differences, individual variability, and changes induced by environmental factors or disease is critical to optimizing therapeutic outcomes. This review discusses the features of skin structure, physiology, and pathologies, as well as the application of permeation enhancers in these contexts. Furthermore, it addresses the use of animal skin models in transdermal delivery and dermatological studies, along with the latest developments in this field.
New Chalcone-Derived Molecule for the Topical Regulation of Hyperpigmentation and Skin Aging
Authors: Martínez-Gutiérrez Alfredo , Bertran Alexandra , Noya Teresa , Pena-Rodríguez Eloy , Gómez-Escalante Susana , Pascual Sergio , Luis Luis Shotze , González Mari Carmen
Published: October 2024

Background/Objectives: Skin hyperpigmentation is a biological process that results in an excessive production of melanin and is highly regulated by several mechanisms, tyrosinase being one of the key enzymes involved. Current reported inhibitors lack clinical efficacy, show toxic side effects, have poor bioavailability, or low formulation compatibility. The aim of this study was to design a new effective tyrosinase inhibitor for topical hyperpigmentation and anti-aging treatments. Methods: Homology modeling was used to build the tridimensional structure of human tyrosinase, and virtual docking was used to predict molecule–enzyme binding modes. The tyrosinase activity of the designed and synthesized compounds was assessed and water solubility was determined by HPLC. Cell assays were performed to determine melanin content, cytotoxicity, wound healing, anti-glycation, antioxidation, and autophagy efficacy. Gene expression and miRNA levels were quantified by qPCR and chromatin accessibility by ATAC-Seq. Human reconstructed epidermis was used to test the depigmenting efficacy as well as the skin irritation potential. Results: The 3D structure of human tyrosinase was designed and validated. The new molecule could effectively inhibit human tyrosinase and melanin synthesis in 2D monocultures and a 3D epidermis model. Two melanogenesis-related miRNAs were increased in treated cells. Anti-glycation, antioxidant, mitochondria protection, autophagy activation, and wound healing properties were also observed, with special emphasis on epigenetics. Conclusions: The designed molecule is a potential candidate to be used as a depigmenting and anti-aging agent, with suitable properties to be introduced in final product formulations for dermatology or cosmetics treatments.
Treatment of Inflammatory Bowel Disease by Using Curcumin-Containing Self-Microemulsifying Delivery System: Macroscopic and Microscopic Analysis
Authors: Ameer Nabeela , Hanif Muhammad , Abbas Ghulam , Azeem Muhammad , Mahmood Khalid , Shahwar Dure , Khames Ahmed , Eissa Essam Mohamed , Daihom Baher
Published: October 2024

Background: The lack of local availability for drugs in the colon can be addressed by preparing a self-microemulsifying drug delivery system (SMEDDS) of curcumin (Cur) which is ultimately used for the treatment of inflammatory bowel disease (IBD). Methods: From preformulation studies, Lauroglycol FCC (oil), Tween 80 (surfactant), Transcutol HP (co-surfactant), and Avicel (solid carrier) were selected for the preparation of blank liquid and solid Cur-loaded SMEDDSs (S-Cur-SMEDDSs). Results: Z-average size (12.36 ± 0.04 nm), zeta potential (−14.7 ± 0.08 mV), and polydispersity index (PDI) (0.155 ± 0.036) showed a comparative droplet surface area and charge of both SMEDDSs. The physicochemical stability of Cur in S-Cur-SMEDDSs was confirmed via FTIR, DSC, TGA, and XRD analyses, while morphological analysis through SEM and atomic force microscopy (AFM) confirmed Cur loading into SMEDDSs with an increased surface roughness root mean square (RMS) of 11.433 ± 0.91 nm, greater than the blank SMEDDS. Acute toxicity studies with an organ weight ratio and % hemolysis of 15.65 ± 1.32% at a high concentration of 600 mM showed that S-Cur-SMEDDSs are safe at a medium dose (0.2–0.8 g/kg/day). The excellent in vitro antioxidant (68.54 ± 1.42%) and anti-inflammatory properties (56.47 ± 1.17%) of S-Cur-SMEDDS proved its therapeutic efficacy for IBD. Finally, S-Cur-SMEDDS significantly improved acetic acid-induced IBD in albino rats through a reduction in the disease activity index (DAI) and macroscopic ulcer score (MUS) from 4.15 ± 0.21 to 1.62 ± 0.12 at 15 mg/kg/day dose, as confirmed via histopathological assay. Conclusions: Based on the above findings, S-Cur-SMEDDS appears to be a stable, less toxic, and more efficacious alternative for Cur delivery with strong competence in treating IBD.
Improvements in Injection Moulds Cooling and Manufacturing Efficiency Achieved by Wire Arc Additive Manufacturing Using Conformal Cooling Concept
Authors: Marqués Alejandro , Dieste Jose Antonio , Monzón Iván , Laguía Alberto , Gracia Pascual , Javierre Carlos , Clavería Isabel , Elduque Daniel
Published: October 2024

The plastic injection moulding industry is a constantly developing industrial field. This industrial process requires the manufacturing of metal moulds using complex heating and cooling systems. The purpose of this research is to optimize both the plastic injection moulding process and the mould manufacturing process itself by combining practices in this industry with current additive manufacturing technologies, specifically Wire Arc Additive Manufacturing (WAAM) technology. A mould punch was manufactured by using both WAAM technology, whose internal cooling system has been designed under the concept of Conformal Cooling, and conventional cooling channel designs and manufacturing techniques in order to carry out a comparative analysis. Theoretical results obtained by CAE methods showed an improvement in heat extraction in the WAAM mould. In addition, the WAAM mould was able to achieve better temperature homogeneity in the final part, minimizing deformations in the final part after extraction. Finally, the WAAM manufacturing process was proven to be more efficient in terms of material consumption than the conventional mould, reducing the buy-to-fly ratio of the part by 5.11.
Low-Velocity Impact Resistance and Compression After Impact Strength of Thermoplastic Nanofiber Toughened Carbon/Epoxy Composites with Different Layups
Authors: Meireman Timo , Verboven Erik , Kersemans Mathias , Van Paepegem Wim , De Clerck Karen , Daelemans Lode
Published: October 2024

This study investigates the effectiveness of polyether block amide (PEBA) thermoplastic elastomeric nanofibers in reducing low-velocity impact damage across three carbon fiber composite lay-up configurations: a cross-ply [0°/90°]2s (CP) and a quasi-isotropic [0°/45°/90°/−45°]s (QI) lay-up utilizing unidirectional plies, and a stacked woven [(0°,90°)]4s (W) lay-up using twill woven fabric plies. The flexural strength and interlaminar shear strength of the composites remained unaffected by the addition of nanofibers: around 750 MPa and 63 MPa for CP, 550 MPa and 58 MPa for QI, and 650 MPa and 50 MPa for W, respectively. The incorporation of nanofibers in the interlaminar regions resulted in a substantial reduction in projected damage area, ranging from 30% to 50% reduction over an impact energy range of 5–20 J. Microscopic analysis showed that especially the delamination damage decreased in toughened composites, while intralaminar damage remained similar for the cross-ply and quasi-isotropic lay-ups and decreased only in the woven lay-up. This agrees with the broad body of research that shows that interleaved nanofibers result in a higher delamination resistance due to toughening mechanisms related to nanofiber bridging of cracks. Despite their ability to mitigate delamination during impact, nanofibers showed limited positive effects on Compression After Impact (CAI) strength in quasi-isotropic and cross-ply composites. Interestingly, only the woven fabric composites demonstrated improved CAI strength, with a 12% improvement on average over the impact energy range, attributed to a reduction in both interlaminar and intralaminar damage. This study indicates the critical role of fiber integrity over delamination size in determining CAI performance, suggesting that the delaminations are not sufficiently large to induce buckling of sub-layers, thereby minimizing the effect of nanofiber toughening on the CAI strength.
Processing and Properties of Polyhydroxyalkanoate/ZnO Nanocomposites: A Review of Their Potential as Sustainable Packaging Materials
Authors: Buntinx Mieke , Vanheusden Chris , Hermans Dries
Published: October 2024

The escalating environmental concerns associated with conventional plastic packaging have accelerated the development of sustainable alternatives, making food packaging a focus area for innovation. Bioplastics, particularly polyhydroxyalkanoates (PHAs), have emerged as potential candidates due to their biobased origin, biodegradability, and biocompatibility. PHAs stand out for their good mechanical and medium gas permeability properties, making them promising materials for food packaging applications. In parallel, zinc oxide (ZnO) nanoparticles (NPs) have gained attention for their antimicrobial properties and ability to enhance the mechanical and barrier properties of (bio)polymers. This review aims to provide a comprehensive introduction to the research on PHA/ZnO nanocomposites. It starts with the importance and current challenges of food packaging, followed by a discussion on the opportunities of bioplastics and PHAs. Next, the synthesis, properties, and application areas of ZnO NPs are discussed to introduce their potential use in (bio)plastic food packaging. Early research on PHA/ZnO nanocomposites has focused on solvent-assisted production methods, whereas novel technologies can offer additional possibilities with regard to industrial upscaling, safer or cheaper processing, or more specific incorporation of ZnO NPs in the matrix or on the surface of PHA films or fibers. Here, the use of solvent casting, melt processing, electrospinning, centrifugal fiber spinning, miniemulsion encapsulation, and ultrasonic spray coating to produce PHA/ZnO nanocomposites is explained. Finally, an overview is given of the reported effects of ZnO NP incorporation on thermal, mechanical, gas barrier, UV barrier, and antimicrobial properties in ZnO nanocomposites based on poly(3-hydroxybutyrate), poly(3-hydroxybutyrate-co-3-hydroxyvalerate), and poly(3-hydroxybutyrate-co-3-hydroxyhexanoate). We conclude that the functionality of PHA materials can be improved by optimizing the ZnO incorporation process and the complex interplay between intrinsic ZnO NP properties, dispersion quality, matrix–filler interactions, and crystallinity. Further research regarding the antimicrobial efficiency and potential migration of ZnO NPs in food (simulants) and the End-of-Life will determine the market potential of PHA/ZnO nanocomposites as active packaging material.
Chitosan Nanoparticles Embedded in In Situ Gel for Nasal Delivery of Imipramine Hydrochloride: Short-Term Stage Development and Controlled Release Evaluation
Authors: Adwan Samer , Obeidi Teiba , Al-Akayleh Faisal
Published: October 2024

Imipramine hydrochloride (IMP), a tricyclic antidepressant used for major depression, enuresis, and neuropathic pain, is limited by gastrointestinal complications, low oral bioavailability (44%), and complex dosing requirements. This study aimed to explore a novel non-invasive nasal delivery system using chitosan nanoparticles (Cs NPs) embedded in an in situ gel to address the limitations of oral IMP administration. Cs NPs loaded with IMP were synthesized via ionic gelation and assessed for precision in drug concentration using a validated HPLC method. The particles were integrated into a thermoresponsive polymer, Pluronic F127, to form an in situ gel suitable for nasal administration. The formulation was characterized for gelation temperature, duration, viscosity, mucoadhesive strength, and overall gel robustness. Drug release kinetics and the controlled release mechanism were studied using ex vivo permeation tests with Franz diffusion cells and nasal sheep mucosa. The optimized nanoparticle formulation (F4-50) exhibited a consistent PS of 141.7 ± 2.2 nm, a zeta potential (ZP) of 16.79 ± 2.1 mV, and a high encapsulation efficiency of 67.71 ± 1.9%. The selected in situ gel formulation, F4-50-P1, demonstrated a gelation temperature of 33.6 ± 0.94 °C and a rapid gelation time of 48.1 ± 0.7 s. Transform-attenuated total reflectance infrared spectroscopy (ATR-IR) confirmed the compatibility and effective encapsulation of IMP within the formulation. The release profile of F4-50 included an initial burst release followed by a sustained release phase, with F4-50-P1 showing improved control over the burst release. The flux rates were 0.50 ± 0.01 mg/cm2/h for F4-50 and 0.33 ± 0.06 mg/cm2/h for F4-50-P1, indicating effective permeation. The developed chitosan nanoparticle-based in situ gel formulation provides a promising approach for the controlled release of IMP, enhancing therapeutic efficacy and patient compliance while mitigating the disadvantages associated with oral delivery.
Effect of Surface Polymeric Organosilicon Nanolayers on the Electrochemical and Corrosion Behavior of Copper
Authors: Petrunin M. A. , Yurasova T. A. , Rybkina A. A. , Maksaeva L. B.
Published: October 2024

The formation of polymeric self-organizing organosilicon surface nanolayers on copper occuring as a result of modification of the metal surface with organosilane-based formulations has been studied. The anticorrosive effect of such surface layers in corrosive chloride-containing electrolytes as well as in artificial and natural atmospheres has been studied in detail. It has been found that the maximum protective effect is observed at a thickness of 3.8 molecular layers, where the densest cross-linked polymer layers are formed that hinder the adsorption of chloride ions and other corrosive agents on the metal surface, thus significantly reducing the rate of their reactions with the surface copper atoms, and, as a result, inhibiting the corrosion and local anodic dissolution of the metal.
Effect of Medium-Chain-Length Alkyl Silane Modified Nanocellulose in Poly(3-hydroxybutyrate) Nanocomposites
Authors: Uşurelu Cătălina Diana , Panaitescu Denis Mihaela , Oprică Gabriela Mădălina , Nicolae Cristian-Andi , Gabor Augusta Raluca , Damian Celina Maria , Ianchiş Raluca , Teodorescu Mircea , Frone Adriana Nicoleta
Published: October 2024

Poly (3-hydroxybutyrate) (PHB) is a valuable biopolymer that is produced in industrial quantity but is not widely used in applications due to some drawbacks. The addition of cellulose nanofibers (CNF) as a biofiller in PHB/CNF nanocomposites may improve PHB properties and enlarge its application field. In this work, n-octyltriethoxy silane (OTES), a medium-chain-length alkyl silane, was used to surface chemically modify the CNF (CNF_OTES) to enhance their hydrophobicity and improve their compatibility with PHB. The surface functionalization of CNF and nanodimension were emphasized by Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy, thermogravimetric analysis, atomic force microscopy, dynamic light scattering, and water contact angle (CA). Surface modification of CNF with OTES led to an increase in thermal stability by 25 °C and more than the doubling of CA. As a result of the higher surface hydrophobicity, the CNF_OTES were more homogeneously dispersed in PHB than unmodified CNF, leading to a PHB nanocomposite with better thermal and mechanical properties. Thus, an increase by 122% of the storage modulus at 25 °C, a slight increase in crystallinity, a better melting processability, and good thermal stability were obtained after reinforcing PHB with CNF_OTES, paving the way for increasing PHB applicability.
Fabrication of Highly Sensitive Porous Polydimethylsiloxane Pressure Sensor Through Control of Rheological Properties
Authors: Jang Yunseok , Lee Seung-Hyun , Lee Youn-Ki , Kim Inyoung , Lee Taik-Min , Kwon Sin , Kang Boseok
Published: October 2024

In order to enhance the sensitivity of elastomers, pores were integrated into their structure. These pores facilitate the adjustment of thickness in response to external pressure variations, thereby improving the sensitivity of pressure sensors. Pores were introduced by emulsifying immiscible polydimethylsiloxane (PDMS) and water with a surfactant. By controlling the water content in the PDMS and water emulsion, we controlled the size, density, uniformity, and spatial distribution (2D or 3D) of the pores within the PDMS matrix. The presence of these pores significantly improved the sensitivity of PDMS under low external pressure conditions compared to high pressures. Specifically, porous PDMS exhibited approximately 10-times greater sensitivity under low-pressure conditions than non-porous PDMS. The effectiveness of porous PDMS was demonstrated through dynamic loading and unloading detection of a small Lego toy and monitoring of human heartbeats. These results highlight the efficacy of our pressure sensor based on porous PDMS, which is fabricated through a simple and cost-effective process using a PDMS and water emulsion. This approach is highly suitable for developing the ability to detect applied pressures or contact forces.
Fabrication of Functionalized Graphene Oxide–Aluminum Hypophosphite Nanohybrids for Enhanced Fire Safety Performance in Polystyrene
Authors: Deng Zhenzhen , Tang Tao , Huo Junjie , He Hui , Dai Kang
Published: October 2024

To enhance the fire safety performance in polystyrene (PS), a novel organic–inorganic hybrid material (FGO–AHP) was successfully prepared by the combination of functionalized graphene oxide (FGO) and aluminum hypophosphite (AHP) via a chemical deposition method. The resulting FGO–AHP nanohybrids were incorporated into PS via a masterbatch-melt blending to produce PS/FGO–AHP nanocomposites. Scanning electron microscope images confirm the homogeneous dispersion and exfoliation state of FGO–AHP in the PS matrix. Incorporating FGO–AHP significantly improves the thermal behavior and fire safety performance of PS. By incorporating 5 wt% FGO–AHP, the maximum mass loss rate (MMLR) in air, total heat release (THR), and maximum smoke density value (Dsmax) of PS nanocomposite achieve a reduction of 53.1%, 23.4%, and 50.9%, respectively, as compared to the pure PS. In addition, thermogravimetry–Fourier transform infrared (TG–FTIR) results indicate that introducing FGO–AHP notably inhibits the evolution of volatile products from PS decomposition. Further, scanning electron microscopy (SEM), FTIR, and Raman spectroscopy were employed to investigate the char residue of PS nanocomposite samples, elaborating the flame-retardant mechanism in PS/FGO–AHP nanocomposites.
Dual Loading of Trans-Cinnamaldehyde and Either Paclitaxel or Curcumin in Chitosan Nanoparticles: Physicochemical Characterization and Biological Evaluation Against MDCK and HeLa Cells
Authors: Barrera-Martínez Cynthia L. , Meléndez-Ortiz Héctor I. , Padilla-Vaca Felipe , Atanase Leonard I. , Peralta-Rodríguez René D. , Liakos Ioannis
Published: October 2024

Biopolymer chitosan sub-micron particles (CSMPs) were prepared by the ionic gelation technique crosslinked with sodium tripolyphosphate co-loaded with trans-cinnamaldehyde (TCIN), and either curcumin (CUR) or paclitaxel (PTX). The size of the spherical CSMPs increased from 118 nm to 136 nm and 170 nm after the loading of TCIN and CUR, whereas the loading of PTX led to a slight decrease (114 nm). Polydispersity indexes of all the samples were smaller than 0.4, indicating monodisperse particles. Zeta potential values higher than +40 mV were determined, which is direct proof of the high stability of these nanoparticles. TCIN and PTX release studies in vitro, at pH 6.5 and 7.4, showed a pH dependence on the release rate with a higher value at pH 6.5. However, CUR was not released from CSMPs probably due to strong interactions with CS biopolymer chains. Cytotoxicity studies showed that the systems loaded with TCIN and PTX were more cytotoxic for HeLa cancer cells than for MDCK cells. Moreover, a synergistic effect against HeLa cells was observed for the TCIN-PTX-loaded CSMP samples. The Sensitivity Index indicated that the CSMPs loaded with TCIN have a prospective attraction to carry and release conventional or new chemotherapeutic drugs. This study demonstrates the in vitro efficiency of the obtained drug delivery system, but in vivo studies are necessary to confirm its potential for clinical applications.
Evaluation of the UV Protection Properties of Para-Aramid Woven Fabrics with Various Specialty Core Yarns
Authors: Kostajnšek Klara , Bizjak Matejka , Ertekin Gözde , Ertekin Mustafa
Published: October 2024

Para-aramid fibers, known for their remarkable strength and thermal stability, are frequently employed in protective textiles for military and aerospace applications. However, continuous exposure to ultraviolet (UV) radiation can damage their protective characteristics. This study analyzes the ultraviolet protection factor (UPF) and UV transmittance of woven fabrics produced from 30/2 Ne spun para-aramid yarns in the warp and 10 Ne core-spun yarns in the weft. The weft yarns consisted of three sheath fibers—para-aramid, meta-aramid, and polyester—in combination with different specialty core materials. The results show significant differences in UPF before and after UV exposure, with para-aramid sheaths giving the highest improvement. UV exposure caused structural changes in the fibers, resulting in increased UV protection, particularly in fabrics with para-aramid sheaths. This study concludes that the combination of para-aramid fibers with specific core materials significantly enhances UV protection, making them well-suited for applications in high UV exposure environments.
Air Conditioning System Integrated with Thermal Energy Storage for Buildings in Tropical Climates
Authors: Santos Alex , Duarte Willian , Barbieri Paulo , Machado Luiz , Xu Tianhao , Paulino Tiago
Published: October 2024

Thermal energy storage (TES) is an innovative technology that can help mitigate environmental problems and make energy consumption in air conditioning systems more efficient. TES also helps to decouple the production and use of cooling. In this work, a mathematical model was used to obtain the thermal loads of the environment based on Brazilian standards and to simulate the operation of an air conditioning system integrated with TES. A refrigeration system capable of providing cooling capacity for the selected environment was used. It simulated the operation of refrigeration systems to evaluate the coefficient of performance of the refrigeration cycle and the refrigeration system, including the TES, for the city of Teresina, in the northeast region of Brazil. On each day, the efficiency of the air-cooled chiller coupled with a TES that used paraffin with phase change material was verified. Based on the data obtained from the mathematical model, the reduction in energy consumption achieved by coupling TES with the air conditioning system varied between 10.6% and 1.3%.
Non-Destructive Analysis for Machine-Picked Tea Leaf Composition Using Near-Infrared Spectroscopy Combined Chemometric Methods
Authors: Jiang Qinghai , Chen Bin , Chen Jia , Song Zhiyu
Published: October 2024

This paper aimed to predict the mechanical composition of machine-picked fresh tea leaves (MPFTLs) using near-infrared spectroscopy (NIRS) rapidly and non-destructively. Samples of MPFTL with different mechanical composition ratios were collected and subjected to NIRS analysis. Subsequently, various preprocessing methods were employed to eliminate extraneous noise information. Next, characteristic spectral information was extracted using the backward interval partial least squares (biPLS) method, which was subsequently subjected to principal component analysis (PCA). Finally, a predictive model was constructed by applying the back propagation artificial neural network (BP-ANN) method, which was tested by external samples to assess its predictive efficacy, and the results were expressed as root mean square error and determination coefficient of prediction (Rp2). The optimal spectral pretreatment method was the following: (standard normal variate (SNV) + second derivative (SD)). Four characteristic spectral subintervals of ([2, 3, 7, 10]) were screened out, and the cumulative contribution rate of 95.20%, attributable to the first three principal components, was determined. When the tanh transfer function was applied to construct the BP-ANN-NIRS model, the results demonstrated optimal performance, exhibiting a root mean square error and a determination coefficient of prediction (Rp2) of 0.976 and 0.027, respectively. The absolute values of prediction deviation for all prediction set samples were found to be less than 0.04. The results of the best BP-ANN model for external samples were found to be in close agreement with those of the prediction set model. NIRS technology has successfully achieved the forecasting of the mechanical composition of machine-picked fresh tea leaves rapidly and accurately, providing a fair and convenient new method for purchasing fresh tea raw materials by machines, according to their quality, and promoting the sustainable high-quality and healthy development of the tea industry.
Multimodal Deep Learning Integration of Image, Weather, and Phenotypic Data Under Temporal Effects for Early Prediction of Maize Yield
Authors: Shamsuddin Danial , Danilevicz Monica F. , Al-Mamun Hawlader A. , Bennamoun Mohammed , Edwards David
Published: October 2024

Maize (Zea mays L.) has been shown to be sensitive to temperature deviations, influencing its yield potential. The development of new maize hybrids resilient to unfavourable weather is a desirable aim for crop breeders. In this paper, we showcase the development of a multimodal deep learning model using RGB images, phenotypic, and weather data under temporal effects to predict the yield potential of maize before or during anthesis and silking stages. The main objective of this study was to assess if the inclusion of historical weather data, maize growth captured through imagery, and important phenotypic traits would improve the predictive power of an established multimodal deep learning model. Evaluation of the model performance when training from scratch showed its ability to accurately predict ~89% of hybrids with high-yield potential and demonstrated enhanced explanatory power compared with previously published models. Shapley Additive explanations (SHAP) analysis indicated the top influential features include plant density, hybrid placement in the field, date to anthesis, parental line, temperature, humidity, and solar radiation. Including weather historical data was important for model performance, significantly enhancing the predictive and explanatory power of the model. For future research, the use of the model can move beyond maize yield prediction by fine-tuning the model on other crop data, serving as a potential decision-making tool for crop breeders to determine high-performing individuals from diverse crop types.
A Cropland Disturbance Monitoring Method Based on Probabilistic Trajectories
Authors: Jiang Jiawei , Wang Juanle , Yang Keming , Fetisov Denis , Li Kai , Liu Meng , Zou Weihao
Published: October 2024

Acquiring the spatiotemporal patterns of cropland disturbance is of great significance for regional sustainable agricultural development and environmental protection. However, effective monitoring of cropland disturbances remains a challenge owing to the complexity of the terrain landscape and the reliability of the training samples. This study integrated automatic training sample generation, random forest classification, and the LandTrendr time-series segmentation algorithm to propose an efficient and reliable medium-resolution cropland disturbance monitoring scheme. Taking the Amur state of Russia in the Amur river basin, a transboundary region between Russia and China in east Asia with rich agriculture resources as research area, this approach was conducted on the Google Earth Engine cloud-computing platform using extensive remote-sensing image data. A high-confidence sample dataset was then created and a random forest classification algorithm was applied to generate the cropland classification probabilities. LandTrendr time-series segmentation was performed on the interannual cropland classification probabilities. Finally, the identification, spatial mapping, and analysis of cropland disturbances in Amur state were completed. Further cross-validation comparisons of the accuracy assessment and spatiotemporal distribution details demonstrated the high accuracy of the dataset, and the results indicated the applicability of the method. The study revealed that 2815.52 km2 of cropland was disturbed between 1990 and 2021, primarily focusing on the southern edge of the Amur state. The most significant disturbance occurred in 1991, affecting 1431.48 km2 and accounting for 50.84% of the total disturbed area. On average, 87.98 km2 of croplands are disturbed annually. Additionally, 2495.4 km2 of cropland was identified as having been disturbed at least once during the past 32 years, representing 83% of the total disturbed area. This study introduced a novel approach for identifying cropland disturbance information from long time-series probabilistic images. This methodology can also be extended to monitor the spatial and temporal dynamics of other land disturbances caused by natural and human activities.
Impacts of Climate Change on Forest Biodiversity Changes in Northeast China
Authors: Yang Xiguang , Mu Yingqiu , Yang Li , Yu Ying , Wu Zechuan
Published: October 2024

Vegetation plays a vital role in connecting ecosystems and climate features. The biodiversity of vegetation is one of the most important features for evaluating ecosystems and it is becoming increasingly important with the threat of global warming. To clarify the effects of climate change on forest biodiversity in Northeast China, time-series NDVI data, meteorological data and land cover data from 2010 to 2021 were acquired, and the forest biodiversity of Northeast China was evaluated. The effect of climate change on forest biodiversity was analyzed, and the results indicated that the forest biodiversity features increased from west to east in Northeast China. There was also an increasing trend from 2010 to 2021, but the rate at which forest biodiversity was changing varied with different forest types of Northeast China, as different climatic factors had a different impact on forest biodiversity in different forest types. Average annual temperature, annual accumulated precipitation, CO2 fertilization and solar radiation were the main factors affecting forest biodiversity changing trends. This research indicated the potential impact of climate change on forest ecosystems, as it emphasized with evidence that climate change has a catalytic effect on forest biodiversity in Northeast China.
Tree Species Classification by Multi-Season Collected UAV Imagery in a Mixed Cool-Temperate Mountain Forest
Authors: Avtar Ram , Chen Xinyu , Fu Jinjin , Alsulamy Saleh , Supe Hitesh , Pulpadan Yunus Ali , Louw Albertus Stephanus , Tatsuro Nakaji
Published: October 2024

Effective forest management necessitates spatially explicit information about tree species composition. This information supports the safeguarding of native species, sustainable timber harvesting practices, precise mapping of wildlife habitats, and identification of invasive species. Tree species identification and geo-location by machine learning classification of UAV aerial imagery offer an alternative to tedious ground surveys. However, the timing (season) of the aerial surveys, input variables considered for classification, and the model type affect the classification accuracy. This work evaluates how the seasons and input variables considered in the species classification model affect the accuracy of species classification in a temperate broadleaf and mixed forest. Among the considered models, a Random Forest (RF) classifier demonstrated the highest performance, attaining an overall accuracy of 83.98% and a kappa coefficient of 0.80. Simultaneously using input data from summer, winter, autumn, and spring seasons improved tree species classification accuracy by 14–18% from classifications made using only single-season input data. Models that included vegetation indices, image texture, and elevation data obtained the highest accuracy. These results strengthen the case for using multi-seasonal data for species classification in temperate broadleaf and mixed forests since seasonal differences in the characteristics of species (e.g., leaf color, canopy structure) improve the ability to discern species.
TTMGNet: Tree Topology Mamba-Guided Network Collaborative Hierarchical Incremental Aggregation for Change Detection
Authors: Wang Hongzhu , Ye Zhaoyi , Xu Chuan , Mei Liye , Lei Cheng , Wang Du
Published: October 2024

Change detection (CD) identifies surface changes by analyzing bi-temporal remote sensing (RS) images of the same region and is essential for effective urban planning, ensuring the optimal allocation of resources, and supporting disaster management efforts. However, deep-learning-based CD methods struggle with background noise and pseudo-changes due to local receptive field limitations or computing resource constraints, which limits long-range dependency capture and feature integration, normally resulting in fragmented detections and high false positive rates. To address these challenges, we propose a tree topology Mamba-guided network (TTMGNet) based on Mamba architecture, which combines the Mamba architecture for effectively capturing global features, a unique tree topology structure for retaining fine local details, and a hierarchical feature fusion mechanism that enhances multi-scale feature integration and robustness against noise. Specifically, the a Tree Topology Mamba Feature Extractor (TTMFE) leverages the similarity of pixels to generate minimum spanning tree (MST) topology sequences, guiding information aggregation and transmission. This approach utilizes a Tree Topology State Space Model (TTSSM) to embed spatial and positional information while preserving the global feature extraction capability, thereby retaining local features. Subsequently, the Hierarchical Incremental Aggregation Module is utilized to gradually align and merge features from deep to shallow layers to facilitate hierarchical feature integration. Through residual connections and cross-channel attention (CCA), HIAM enhances the interaction between neighboring feature maps, ensuring that critical features are retained and effectively utilized during the fusion process, thereby enabling more accurate detection results in CD. The proposed TTMGNet achieved F1 scores of 92.31% on LEVIR-CD, 90.94% on WHU-CD, and 77.25% on CL-CD, outperforming current mainstream methods in suppressing the impact of background noise and pseudo-change and more accurately identifying change regions.
The Change Detection of Mangrove Forests Using Deep Learning with Medium-Resolution Satellite Imagery: A Case Study of Wunbaik Mangrove Forest in Myanmar
Authors: Win Kyaw , Sasaki Jun
Published: October 2024

This paper presents the development of a U-Net model using four basic optical bands and SRTM data to analyze changes in mangrove forests from 1990 to 2024, with an emphasis on the impact of restoration programs. The model, which employed supervised learning for binary classification by fusing multi-temporal Landsat 8 and Sentinel-2 imagery, achieved a superior accuracy of 99.73% for the 2020 image classification. It was applied to predict the long-term mangrove maps in Wunbaik Mangrove Forest (WMF) and to detect the changes at five-year intervals. The change detection results revealed significant changes in the mangrove forests, with 29.3% deforestation, 5.75% reforestation, and −224.52 ha/yr of annual rate of changes over 34 years. The large areas of mangrove forests have increased since 2010, primarily due to naturally recovered and artificially planted mangroves. Approximately 30% of the increased mangroves from 2015 to 2024 were attributed to mangrove plantations implemented by the government. This study contributes to developing a deep learning model with multi-temporal and multi-source imagery for long-term mangrove monitoring by providing accurate performance and valuable information for effective conservation strategies and restoration programs.