bluuebunny/crossref_metadata_2025 huggingface dataset:
Characterization of Serum Cytokine Profiles of Patients with Active Lupus Nephritis
Authors: Rahmé Zahrà , Franco Chiara , Cruciani Claudio , Pettorossi Federico , Zaramella Alice , Realdon Stefano , Iaccarino Luca , Frontini Giulia , Moroni Gabriella , Doria Andrea , Ghirardello Anna , Gatto Mariele
Published: October 2023

Cytokines contribute to the pathogenesis of lupus nephritis (LN), yet their value as prognostic biomarkers is still debated. We aimed to describe the serum cytokines’ profiles and prospectively assess correlations with disease features and renal response in a multicentric cohort of consecutive adult patients with biopsy-proven active LN. Cytokine associations with clinical and serological data were performed at LN diagnosis (T0), and at 3 (T3) and 6 months (T6) of follow up. Renal response according to EULAR definition was assessed at T3, T6 and T12. BAFF and interleukin (IL)-37 were measured by ELISA; IL-2, IL-10, IL-17A and IL-18 by a bead-based multiplex cytokine assay (Luminex). Thirty-nine patients with active LN (age 40.5 ± 15.6 years; F 71.8%; 84.6% proliferative LN) were enrolled, of whom twenty-nine displayed complete longitudinal records. At T0, we observed higher levels of IL-37 and IL-17 in proliferative vs. non-proliferative LN (IL-37: 0.0510 (0.0110–0.2300) vs. 0.0000 (0.0000–0.0397) ng/mL, p = 0.0441; IL-17: 2.0920 (0.5125–17.9400) vs. 0.0000 (0.0000–0.6025) pg/mL, p = 0.0026, respectively), and positive correlations between IL-10 and 24 h proteinuria (r = 0.416, p = 0.0249) and anti-dsDNA levels (r = 0.639, p = 0.0003). BAFF was higher in patients with low complement (p < 0.0001). We observed a sustained correlation between BAFF and IL-10 throughout T6 (r = 0.654, p = 0.0210). Higher baseline IL-37 and BAFF levels were associated with renal response at T3 and T6, respectively, while baseline IL-18 levels were higher in patients achieving response at T12. Our study highlights the complexity of the cytokine network and its potential value as a marker of active LN and renal response.
Retrovirus-Derived RTL9 Plays an Important Role in Innate Antifungal Immunity in the Eutherian Brain
Authors: Ishino Fumitoshi , Itoh Johbu , Irie Masahito , Matsuzawa Ayumi , Naruse Mie , Suzuki Toru , Hiraoka Yuichi , Kaneko-Ishino Tomoko
Published: October 2023

Retrotransposon Gag-like (RTL) genes play a variety of essential and important roles in the eutherian placenta and brain. It has recently been demonstrated that RTL5 and RTL6 (also known as sushi-ichi retrotransposon homolog 8 (SIRH8) and SIRH3) are microglial genes that play important roles in the brain’s innate immunity against viruses and bacteria through their removal of double-stranded RNA and lipopolysaccharide, respectively. In this work, we addressed the function of RTL9 (also known as SIRH10). Using knock-in mice that produce RTL9-mCherry fusion protein, we examined RTL9 expression in the brain and its reaction to fungal zymosan. Here, we demonstrate that RTL9 plays an important role, degrading zymosan in the brain. The RTL9 protein is localized in the microglial lysosomes where incorporated zymosan is digested. Furthermore, in Rtl9 knockout mice expressing RTL9ΔC protein lacking the C-terminus retroviral GAG-like region, the zymosan degrading activity was lost. Thus, RTL9 is essentially engaged in this reaction, presumably via its GAG-like region. Together with our previous study, this result highlights the importance of three retrovirus-derived microglial RTL genes as eutherian-specific constituents of the current brain innate immune system: RTL9, RTL5 and RTL6, responding to fungi, viruses and bacteria, respectively.
Key FAD2, FAD3, and SAD Genes Involved in the Fatty Acid Synthesis in Flax Identified Based on Genomic and Transcriptomic Data
Authors: Dvorianinova Ekaterina M. , Zinovieva Olga L. , Pushkova Elena N. , Zhernova Daiana A. , Rozhmina Tatiana A. , Povkhova Liubov V. , Novakovskiy Roman O. , Sigova Elizaveta A. , Turba Anastasia A. , Borkhert Elena V. , Krasnov George S. , Ruan Chengjiang , Dmitriev Alexey A. , Melnikova Nataliya V.
Published: October 2023

FAD (fatty acid desaturase) and SAD (stearoyl-ACP desaturase) genes play key roles in the synthesis of fatty acids (FA) and determination of oil composition in flax (Linum usitatissimum L.). We searched for FAD and SAD genes in the most widely used flax genome of the variety CDC Bethune and three available long-read assembled flax genomes—YY5, 3896, and Atlant. We identified fifteen FAD2, six FAD3, and four SAD genes. Of all the identified genes, 24 were present in duplicated pairs. In most cases, two genes from a pair differed by a significant number of gene-specific SNPs (single nucleotide polymorphisms) or even InDels (insertions/deletions), except for FAD2a-1 and FAD2a-2, where only seven SNPs distinguished these genes. Errors were detected in the FAD2a-1, FAD2a-2, FAD3c-1, and FAD3d-2 sequences in the CDC Bethune genome assembly but not in the long-read genome assemblies. Expression analysis of the available transcriptomic data for different flax organs/tissues revealed that FAD2a-1, FAD2a-2, FAD3a, FAD3b, SAD3-1, and SAD3-2 were specifically expressed in embryos/seeds/capsules and could play a crucial role in the synthesis of FA in flax seeds. In contrast, FAD2b-1, FAD2b-2, SAD2-1, and SAD2-2 were highly expressed in all analyzed organs/tissues and could be involved in FA synthesis in whole flax plants. FAD2c-2, FAD2d-1, FAD3c-1, FAD3c-2, FAD3d-1, FAD3d-2, SAD3-1, and SAD3-2 showed differential expression under stress conditions—Fusarium oxysporum infection and drought. The obtained results are essential for research on molecular mechanisms of fatty acid synthesis, FAD and SAD editing, and marker-assisted and genomic selection for breeding flax varieties with a determined fatty acid composition of oil.
The Molecular Mechanism and Therapeutic Application of Autophagy for Urological Disease
Authors: Chueh Kuang-Shun , Lu Jian-He , Juan Tai-Jui , Chuang Shu-Mien , Juan Yung-Shun
Published: October 2023

Autophagy is a lysosomal degradation process known as autophagic flux, involving the engulfment of damaged proteins and organelles by double-membrane autophagosomes. It comprises microautophagy, chaperone-mediated autophagy (CMA), and macroautophagy. Macroautophagy consists of three stages: induction, autophagosome formation, and autolysosome formation. Atg8-family proteins are valuable for tracking autophagic structures and have been widely utilized for monitoring autophagy. The conversion of LC3 to its lipidated form, LC3-II, served as an indicator of autophagy. Autophagy is implicated in human pathophysiology, such as neurodegeneration, cancer, and immune disorders. Moreover, autophagy impacts urological diseases, such as interstitial cystitis /bladder pain syndrome (IC/BPS), ketamine-induced ulcerative cystitis (KIC), chemotherapy-induced cystitis (CIC), radiation cystitis (RC), erectile dysfunction (ED), bladder outlet obstruction (BOO), prostate cancer, bladder cancer, renal cancer, testicular cancer, and penile cancer. Autophagy plays a dual role in the management of urologic diseases, and the identification of potential biomarkers associated with autophagy is a crucial step towards a deeper understanding of its role in these diseases. Methods for monitoring autophagy include TEM, Western blot, immunofluorescence, flow cytometry, and genetic tools. Autophagosome and autolysosome structures are discerned via TEM. Western blot, immunofluorescence, northern blot, and RT-PCR assess protein/mRNA levels. Luciferase assay tracks flux; GFP-LC3 transgenic mice aid study. Knockdown methods (miRNA and RNAi) offer insights. This article extensively examines autophagy’s molecular mechanism, pharmacological regulation, and therapeutic application involvement in urological diseases.
Stem Cells: Engines of Plant Growth and Development
Authors: Hong Liu , Fletcher Jennifer C.
Published: October 2023

The development of both animals and plants relies on populations of pluripotent stem cells that provide the cellular raw materials for organ and tissue formation. Plant stem cell reservoirs are housed at the shoot and root tips in structures called meristems, with the shoot apical meristem (SAM) continuously producing aerial leaf, stem, and flower organs throughout the life cycle. Thus, the SAM acts as the engine of plant development and has unique structural and molecular features that allow it to balance self-renewal with differentiation and act as a constant source of new cells for organogenesis while simultaneously maintaining a stem cell reservoir for future organ formation. Studies have identified key roles for intercellular regulatory networks that establish and maintain meristem activity, including the KNOX transcription factor pathway and the CLV-WUS stem cell feedback loop. In addition, the plant hormones cytokinin and auxin act through their downstream signaling pathways in the SAM to integrate stem cell activity and organ initiation. This review discusses how the various regulatory pathways collectively orchestrate SAM function and touches on how their manipulation can alter stem cell activity to improve crop yield.
Prostate Cancer Stem Cells: Biology and Treatment Implications
Authors: Koukourakis Ioannis M. , Platoni Kalliopi , Kouloulias Vassilis , Arelaki Stella , Zygogianni Anna
Published: October 2023

Stem cells differentiate into mature organ/tissue-specific cells at a steady pace under normal conditions, but their growth can be accelerated during the process of tissue healing or in the context of certain diseases. It is postulated that the proliferation and growth of carcinomas are sustained by the presence of a vital cellular compartment resembling stem cells residing in normal tissues: ‘stem-like cancer cells’ or cancer stem cells (CSCs). Mutations in prostate stem cells can lead to the formation of prostate cancer. Prostate CSCs (PCSCs) have been identified and partially characterized. These express surface markers include CD44, CD133, integrin α2β1, and pluripotency factors like OCT4, NANOG, and SOX2. Several signaling pathways are also over-activated, including Notch, PTEN/Akt/PI3K, RAS-RAF-MEK-ERK and HH. Moreover, PCSCs appear to induce resistance to radiotherapy and chemotherapy, while their presence has been linked to aggressive cancer behavior and higher relapse rates. The development of treatment policies to target PCSCs in tumors is appealing as radiotherapy and chemotherapy, through cancer cell killing, trigger tumor repopulation via activated stem cells. Thus, blocking this reactive stem cell mobilization may facilitate a positive outcome through cytotoxic treatment.
Effect of Linker Substituent Nature on Performance of Active Sites in UiO-66: Combined FT-IR and DFT Study
Authors: Torbina Viktoriia V. , Salaev Mikhail A. , Paukshtis Evgeniy A. , Liotta Leonarda F. , Vodyankina Olga V.
Published: October 2023

The nature of organic linker substituents plays an important role in gas sorption and separation as well as in catalytic applications of metal–organic frameworks. Zirconium-based UiO-66 is one of the most tunable members of this class of materials. However, the prediction of its properties is still not a fully solved problem. Here, the infrared spectroscopic measurements using highly sensitive CO probe molecules, combined with DFT calculations, are used in order to characterize the performance of different acidic sites caused by the presence of different organic linker substituents. The proposed model allowed differentiation between various active sites over the UiO-66 and clarification of their behavior. The experimental IR bands related to CO adsorption can be unambiguously assigned to one type of site or another. The previously undescribed highly red-shifted band is attributed to CO adsorbed on coordinatively unsaturated zirconium sites through an O atom. The results confirm the lower and higher Lewis’s acidity of coordinatively unsaturated Zr sites on linker defects in the UiO-66 structure when electron-withdrawing and electron-donating groups are, respectively, included in a terephthalate moiety, whilst the Brønsted acidity of zirconium oxo-cluster remains almost unchanged.
Metallic Nanoparticles: A Promising Arsenal against Antimicrobial Resistance—Unraveling Mechanisms and Enhancing Medication Efficacy
Authors: Wahab Shahid , Salman Alishba , Khan Zaryab , Khan Sadia , Krishnaraj Chandran , Yun Soon-Il
Published: October 2023

The misuse of antibiotics and antimycotics accelerates the emergence of antimicrobial resistance, prompting the need for novel strategies to combat this global issue. Metallic nanoparticles have emerged as effective tools for combating various resistant microbes. Numerous studies have highlighted their potential in addressing antibiotic-resistant fungi and bacterial strains. Understanding the mechanisms of action of these nanoparticles, including iron-oxide, gold, zinc oxide, and silver is a central focus of research within the life science community. Various hypotheses have been proposed regarding how nanoparticles exert their effects. Some suggest direct targeting of microbial cell membranes, while others emphasize the release of ions from nanoparticles. The most compelling proposed antimicrobial mechanism of nanoparticles involves oxidative damage caused by nanoparticles-generated reactive oxygen species. This review aims to consolidate knowledge, discuss the properties and mechanisms of action of metallic nanoparticles, and underscore their potential as alternatives to enhance the efficacy of existing medications against infections caused by antimicrobial-resistant pathogens.
A Narrative Review of the Use of Artificial Intelligence in Breast, Lung, and Prostate Cancer
Authors: Patel Kishan , Huang Sherry , Rashid Arnav , Varghese Bino , Gholamrezanezhad Ali
Published: October 2023

Artificial intelligence (AI) has been an important topic within radiology. Currently, AI is used clinically to assist with the detection of lesions through detection systems. However, a number of recent studies have demonstrated the increased value of neural networks in radiology. With an increasing number of screening requirements for cancers, this review aims to study the accuracy of the numerous AI models used in the detection and diagnosis of breast, lung, and prostate cancers. This study summarizes pertinent findings from reviewed articles and provides analysis on the relevancy to clinical radiology. This study found that whereas AI is showing continual improvement in radiology, AI alone does not surpass the effectiveness of a radiologist. Additionally, it was found that there are multiple variations on how AI should be integrated with a radiologist’s workflow.
Accuracy of Four Intra-Oral Scanners in Subgingival Vertical Preparation: An In Vitro 3-Dimensional Comparative Analysis
Authors: Casucci Alessio , Verniani Giulia , Habib Ralph , Ricci Nicolò Maria , Carboncini Clelia , Ferrari Marco
Published: October 2023

One of the most critical aspects in intraoral impression is the detection of the finish line, particularly in the case of subgingival preparations. The aim of this in vitro study was to evaluate the accuracy among four different Intra Oral Scanners (IOSs) in scanning a subgingival vertical margins preparation (VP). A reference maxillary typodont (MT) was fabricated with a VP for full crown on #16 and #21. The MT was scanned with a laboratory scanner (Aadva lab scanner, GC, Tokyo, Japan) to obtain a digital MT (dMT) in .stl format file. A group of 40 digital casts (dIOC) were obtained by scanning the MT 10 times with four different IOSs: Trios 3, 3Shape A/S; I700, Medit; Vivascan, Ivoclar; and Experimental IOS, GC. All the obtained dIOCs were imported into an inspection software program (Geomagic Control X; 3D SYSTEMS) to be superimposed to the dMT in order to calculate trueness. Therefore, in order to calculate precision, all the scans of the same scanner group were superimposed onto the cast that obtained the best result of trueness. The results were collected as the root mean square value (RMS) on the #16 and #21 abutment surfaces and on a marginal area positioned 1 mm above and below the gingival margin. A nonparametric analysis Kruskal–Wallis test was performed to compare the RMS values obtained in the different iOS groups for trueness and precision. Statistical significance was set at 0.05. For the trueness on the #16 abutment, the Vivascan reported statistically lower values, while on the #21 abutment, Vivascan (56.0 ± 12.1) and Experimental IOS, GC (59.2 ± 2.7) performed statistically better than the others. Regarding precision, Experimental IOS, GC were significantly better than the others on #16 (10.7 ± 2.1) and in the #21 area Experimental, GC, and Trios 3 performed statistically better(16.9 ± 13.8; 18.0 ± 2.7). At the subgingival marginal level for both #16 and #21, all the IOS reported reduced accuracy compared to clinical acceptance.
Pursuit Problem of Unmanned Aerial Vehicles
Authors: Oleg Malafeyev , Zhang Kun
Published: October 2023

The study examines scenarios involving a single pursuer tracking a single evader, as well as situations where multiple pursuers are involved in chasing multiple evaders. We formulate this problem as a search and pursuit problem for unmanned aerial vehicles (UAVs). Game theory offers a mathematical framework to model and examine strategic interactions involving multiple decision-makers. By employing game theory principles to address the search and pursuit problem, our objective is to optimize the efficiency of strategies for detecting and capturing unmanned aerial vehicles (UAVs).
Flavonoids in the Spotlight: Bridging the Gap between Physicochemical Properties and Formulation Strategies
Authors: Berga Marta , Logviss Konstantins , Lauberte Liga , Paulausks Artūrs , Mohylyuk Valentyn
Published: October 2023

Flavonoids are hydroxylated polyphenols that are widely distributed in plants with diverse health benefits. Despite their popularity, the bioavailability of flavonoids is often overlooked, impacting their efficacy and the comparison of products. The study discusses the bioavailability-related physicochemical properties of flavonoids, with a focus on the poorly soluble compounds commonly found in dietary supplements and herbal products. This review sums up the values of pKa, log P, solubility, permeability, and melting temperature of flavonoids. Experimental and calculated data were compiled for various flavonoid subclasses, revealing variations in their physicochemical properties. The investigation highlights the challenges posed by poorly soluble flavonoids and underscores the need for enabling formulation approaches to enhance their bioavailability and therapeutic potential. Compared to aglycones, flavonoid glycosides (with sugar moieties) tend to be more hydrophilic. Most of the reviewed aglycones and glycosides exhibit relatively low log P and high melting points, making them “brick dust” candidates. To improve solubility and absorption, strategies like size reduction, the potential use of solid dispersions and carriers, as well as lipid-based formulations have been discussed.
Methyleugenol Has an Antidepressant Effect in a Neuroendocrine Model: In Silico and In Vivo Evidence
Authors: Oliveira Mayara Cecile Nascimento , Cavalcante Ikla Lima , de Araújo Alana Natalícia , Ferreira dos Santos Aline Matilde , de Menezes Renata Priscila Barros , Herrera-Acevedo Chonny , Ferreira de Sousa Natália , de Souza Aquino Jailane , Barbosa-Filho José Maria , de Castro Ricardo Dias , Almeida Reinaldo Nóbrega , Scotti Luciana , Scotti Marcus Tullius , Da Silva Stiebbe Salvadori Mirian Graciela
Published: October 2023

Major depressive disorder is a severe mood disorder characterized by different emotions and feelings. This study investigated the antidepressant activity of the phenylpropanoid methyleugenol (ME) in adult female mice exposed to a stress model induced by dexamethasone. The animals were randomly divided into groups containing eight animals and were pre-administered with dexamethasone (64 μg/kg subcutaneously). After 165 and 180 min, they were treated with ME (25, 50 and 100 mg/kg intraperitoneally) or imipramine (10 mg/kg intraperitoneally) after 45 min and 30 min, respectively; they were then submitted to tests which were filmed. The videos were analyzed blindly. In the tail suspension test, ME (50 mg/kg) increased latency and reduced immobility time. In the splash test, ME (50 mg/kg) decreased grooming latency and increased grooming time. In the open field, there was no statistical difference for the ME groups regarding the number of crosses, and ME (50 mg/kg) increased the number of rearing and time spent in the center. Regarding in silico studies, ME interacted with dopaminergic D1 and α1 adrenergic pathway receptors and with tryptophan hydroxylase inhibitor. In the in vivo evaluation of the pathways of action, the antidepressant potential of ME (50 mg/kg) was reversed by SCH23390 (4 mg/kg intraperitoneally) dopaminergic D1 receptor, Prazosin (1 mg/kg intraperitoneally) α1 adrenergic receptor, and PCPA (4 mg/kg intraperitoneally) tryptophan hydroxylase inhibitor. Our findings indicate that ME did not alter with the locomotor activity of the animals and shows antidepressant activity in female mice with the participation of the D1, α1 and serotonergic systems.
The Role of Immune Checkpoint Inhibitors in Metastatic Pancreatic Cancer: Current State and Outlook
Authors: Tran Linh Chi , Özdemir Berna C. , Berger Martin D.
Published: October 2023

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest tumors, characterized by its aggressive tumor biology and poor prognosis. While immune checkpoint inhibitors (ICIs) play a major part in the treatment algorithm of various solid tumors, there is still no evidence of clinical benefit from ICI in patients with metastatic PDAC (mPDAC). This might be due to several reasons, such as the inherent low immunogenicity of pancreatic cancer, the dense stroma-rich tumor microenvironment that precludes an efficient migration of antitumoral effector T cells to the cancer cells, and the increased proportion of immunosuppressive immune cells, such as regulatory T cells (Tregs), cancer-associated fibroblasts (CAFs), and myeloid-derived suppressor cells (MDSCs), facilitating tumor growth and invasion. In this review, we provide an overview of the current state of ICIs in mPDAC, report on the biological rationale to implement ICIs into the treatment strategy of pancreatic cancer, and discuss preclinical studies and clinical trials in this field. Additionally, we shed light on the challenges of implementing ICIs into the treatment strategy of PDAC and discuss potential future directions.
Analysis of miRNAs in Osteogenesis imperfecta Caused by Mutations in COL1A1 and COL1A2: Insights into Molecular Mechanisms and Potential Therapeutic Targets
Authors: Botor Malwina , Auguściak-Duma Aleksandra , Lesiak Marta , Sieroń Łukasz , Dziedzic-Kowalska Agata , Witecka Joanna , Asman Marek , Madetko-Talowska Anna , Bik-Multanowski Mirosław , Galicka Anna , Sieroń Aleksander L. , Gawron Katarzyna
Published: October 2023

Osteogenesis imperfecta (OI) is a group of connective tissue disorders leading to abnormal bone formation, mainly due to mutations in genes encoding collagen type I (Col I). Osteogenesis is regulated by a number of molecules, including microRNAs (miRNAs), indicating their potential as targets for OI therapy. The goal of this study was to identify and analyze the expression profiles of miRNAs involved in bone extracellular matrix (ECM) regulation in patients diagnosed with OI type I caused by mutations in COL1A1 or COL1A2. Primary skin fibroblast cultures were used for DNA purification and sequence analysis, followed by analysis of miRNA expression. Sequencing analysis revealed mutations of the COL1A1 or COL1A2 genes in all OI patients, including four previously unreported. Amongst the 40 miRNAs analyzed, 9 were identified exclusively in OI cells and 26 in both OI patients and the controls. In the latter case, the expression of six miRNAs (hsa-miR-10b-5p, hsa-miR-19a-3p, hsa-miR-19b-3p, has-miR-204-5p, has-miR-216a-5p, and hsa-miR-449a) increased, while four (hsa-miR-129-5p, hsa-miR-199b-5p, hsa-miR-664a-5p, and hsa-miR-30a-5p) decreased significantly in OI cells in comparison to their expression in the control cells. The identified mutations and miRNA expression profiles shed light on the intricate processes governing bone formation and ECM regulation, paving the way for further research and potential therapeutic advancements in OI and other genetic diseases related to bone abnormality management.
Chemoselective Coatings of GL13K Antimicrobial Peptides for Dental Implants
Authors: Mutreja Isha , Lan Caixia , Li Qishun , Aparicio Conrado
Published: October 2023

Dental implant−associated infection is a clinical challenge which poses a significant healthcare and socio−economic burden. To overcome this issue, developing antimicrobial surfaces, including antimicrobial peptide coatings, has gained great attention. Different physical and chemical routes have been used to obtain these biofunctional coatings, which in turn might have a direct influence on their bioactivity and functionality. In this study, we present a silane−based, fast, and efficient chemoselective conjugation of antimicrobial peptides (Cys−GL13K) to coat titanium implant surfaces. Comprehensive surface analysis was performed to confirm the surface functionalization of as−prepared and mechanically challenged coatings. The antibacterial potency of the evaluated surfaces was confirmed against both Streptococcus gordonii and Streptococcus mutans, the primary colonizers and pathogens of dental surfaces, as demonstrated by reduced bacteria viability. Additionally, human dental pulp stem cells demonstrated long−term viability when cultured on Cys−GL13K−grafted titanium surfaces. Cell functionality and antimicrobial capability against multi−species need to be studied further; however, our results confirmed that the proposed chemistry for chemoselective peptide anchoring is a valid alternative to traditional site−unspecific anchoring methods and offers opportunities to modify varying biomaterial surfaces to form potent bioactive coatings with multiple functionalities to prevent infection.
Characterization and Bio-Evaluation of the Synergistic Effect of Simvastatin and Folic Acid as Wound Dressings on the Healing Process
Authors: Hashem Mahmoud , Alotaibi Badriyah , Elsayed Mahmoud , Alosaimi Manal , Hussein Amal , Abduljabbar Maram , Lee Kyung-Tae , Abdelkader Hamdy , El-Mokhtar Mohamed , Hassan Ahmed , Abdel-Rheem Amany , Belal Amany , Saddik Mohammed
Published: October 2023

Wound healing is a significant healthcare problem that decreases the patient’s quality of life. Hence, several agents and approaches have been widely used to help accelerate wound healing. The challenge is to search for a topical delivery system that could supply long-acting effects, accurate doses, and rapid healing activity. Topical forms of simvastatin (SMV) are beneficial in wound care. This study aimed to develop a novel topical chitosan-based platform of SMV with folic acid (FA) for wound healing. Moreover, the synergistic effect of combinations was determined in an excisional wound model in rats. The prepared SMV-FA-loaded films (SMV-FAPFs) were examined for their physicochemical characterizations and morphology. Box-Behnken Design and response surface methodology were used to evaluate the tensile strength and release characteristics of the prepared SMV-FAPFs. Additionally, Fourier transform infrared (FT-IR), differential scanning calorimetry (DSC), X-ray diffraction pattern (XRD), and animal studies were also investigated. The developed SMV-FAPFs showed a contraction of up to 80% decrease in the wound size after ten days. The results of the quantitative real-time polymerase chain reaction (RT-PCR) analysis demonstrated a significant upregulation of dermal collagen type I (CoTI) expression and downregulation of the inflammatory JAK3 expression in wounds treated with SMV-FAPFs when compared to control samples and individual drug treatments. In summary, it can be concluded that the utilization of SMV-FAPFs holds great potential for facilitating efficient and expeditious wound healing, hence presenting a feasible substitute for conventional topical administration methods.
Compatibilizing Biodegradable Poly(lactic acid)/polybutylene adipate-co-terephthalate Blends via Reactive Graphene Oxide for Screw-Based 3D Printing
Authors: Yu Wei , Hu Zhonglue , Zhang Ye , Zhang Yakuang , Dong Weiping , Li Xiping , Wang Sisi
Published: October 2023

Vinyl-functionalized graphene oxide (VGO) was used as a reactive compatibilizer to prepare poly(lactic acid)/polybutylene adipate-co-terephthalate (PLA/PBAT) blends. The linear rheological and scanning electron microscopy results confirmed that the VGO nanosheets were quite efficient in compatibilizing PLA/PBAT blends. The size of the PBAT dispersed phase was remarkably decreased in the presence of VGO nanosheets. Moreover, the VGO nanosheets exhibited strong nucleating effects on the crystallization process of PLA. The crystallinity of PLA component in the compatibilized blend with various VGO nanosheets was higher than 40%, upon the cooling rate of 20 °C/min. The prepared PLA/PBAT pellets were applied to 3D printing, using a self-developed screw-based 3D printer. The results showed that all the prepared PLA/PBAT blend pellets can be 3D printed successfully. The notched Izod impact test results showed that, in the presence of VGO, an increase of at least 142% in impact strength was achieved for PLA/PBAT blend. This could be attributed to the compatibilizing effect of the VGO nanosheets. Thus, this work provides a novel way to prepare tough PLA-based materials for 3D printing.
A Swin Transformer with Dynamic High-Pass Preservation for Remote Sensing Image Pansharpening
Authors: Li Weisheng , Hu Yijian , Peng Yidong , He Maolin
Published: October 2023

Pansharpening is a technique used in remote sensing to combine high-resolution panchromatic (PAN) images with lower resolution multispectral (MS) images to generate high-resolution multispectral images while preserving spectral characteristics. Recently, convolutional neural networks (CNNs) have been the mainstream in pansharpening by extracting the deep features of PAN and MS images and fusing these abstract features to reconstruct high-resolution details. However, they are limited by the short-range contextual dependencies of convolution operations. Although transformer models can alleviate this problem, they still suffer from weak capability in reconstructing high-resolution detailed information from global representations. To this end, a novel Swin-transformer-based pansharpening model named SwinPAN is proposed. Specifically, a detail reconstruction network (DRNet) is developed in an image difference and residual learning framework to reconstruct the high-resolution detailed information from the original images. DRNet is developed based on the Swin Transformer with a dynamic high-pass preservation module with adaptive convolution kernels. The experimental results on three remote sensing datasets with different sensors demonstrate that the proposed approach performs better than state-of-the-art networks through qualitative and quantitative analysis. Specifically, the generated pansharpening results contain finer spatial details and richer spectral information than other methods.
HAM-Transformer: A Hybrid Adaptive Multi-Scaled Transformer Net for Remote Sensing in Complex Scenes
Authors: Ren Keying , Chen Xiaoyan , Wang Zichen , Liang Xiwen , Chen Zhihui , Miao Xia
Published: October 2023

The quality of remote sensing images has been greatly improved by the rapid improvement of unmanned aerial vehicles (UAVs), which has made it possible to detect small objects in the most complex scenes. Recently, learning-based object detection has been introduced and has gained popularity in remote sensing image processing. To improve the detection accuracy of small, weak objects in complex scenes, this work proposes a novel hybrid backbone composed of a convolutional neural network and an adaptive multi-scaled transformer, referred to as HAM-Transformer Net. HAM-Transformer Net firstly extracts the details of feature maps using convolutional local feature extraction blocks. Secondly, hierarchical information is extracted, using multi-scale location coding. Finally, an adaptive multi-scale transformer block is used to extract further features in different receptive fields and to fuse them adaptively. We implemented comparison experiments on a self-constructed dataset. The experiments proved that the method is a significant improvement over the state-of-the-art object detection algorithms. We also conducted a large number of comparative experiments in this work to demonstrate the effectiveness of this method.
A Systematic Stereo Camera Calibration Strategy: Leveraging Latin Hypercube Sampling and 2k Full-Factorial Design of Experiment Methods
Authors: Hao Yanan , Tai Vin Cent , Tan Yong Chai
Published: October 2023

This research aimed to optimize the camera calibration process by identifying the optimal distance and angle for capturing checkered board images, with a specific focus on understanding the factors that influence the reprojection error (ϵRP). The objective was to improve calibration efficiency by exploring the impacts of distance and orientation factors and the feasibility of independently manipulating these factors. The study employed Zhang’s camera calibration method, along with the 2k full-factorial analysis method and the Latin Hypercube Sampling (LHS) method, to identify the optimal calibration parameters. Three calibration methods were devised: calibration with distance factors (D, H, V), orientation factors (R, P, Y), and the combined two influential factors from both sets of factors. The calibration study was carried out with three different stereo cameras. The results indicate that D is the most influential factor, while H and V are nearly equally influential for method A; P and R are the two most influential orientation factors for method B. Compared to Zhang’s method alone, on average, methods A, B, and C reduce ϵRP by 25%, 24%, and 34%, respectively. However, method C requires about 10% more calibration images than methods A and B combined. For applications where lower value of ϵRP is required, method C is recommended. This study provides valuable insights into the factors affecting ϵRP in calibration processes. The proposed methods can be used to improve the calibration accuracy for stereo cameras for the applications in object detection and ranging. The findings expand our understanding of camera calibration, particularly the influence of distance and orientation factors, making significant contributions to camera calibration procedures.
RDD-YOLOv5: Road Defect Detection Algorithm with Self-Attention Based on Unmanned Aerial Vehicle Inspection
Authors: Jiang Yutian , Yan Haotian , Zhang Yiru , Wu Keqiang , Liu Ruiyuan , Lin Ciyun
Published: October 2023

Road defect detection is a crucial aspect of road maintenance projects, but traditional manual methods are time-consuming, labor-intensive, and lack accuracy. Leveraging deep learning frameworks for object detection offers a promising solution to these challenges. However, the complexity of backgrounds, low resolution, and similarity of cracks make detecting road cracks with high accuracy challenging. To address these issues, a novel road crack detection algorithm, termed Road Defect Detection YOLOv5 (RDD-YOLOv5), was proposed. Firstly, a model was proposed to integrate the transformer structure and explicit vision center to capture the long-distance dependency and aggregate key characteristics. Additionally, the Sigmoid-weighted linear activations in YOLOv5 were replaced with the Gaussian Error Linear Units to enhance the model’s nonlinear fitting capability. To evaluate the algorithm’s performance, a UAV flight platform was constructed, and experimental freebies were provided to boost inspection efficiency. The experimental results demonstrate the effectiveness of RDD-YOLOv5, achieving a mean average precision of 91.48%, surpassing the original YOLOv5 by 2.5%. The proposed model proves its ability to accurately identify road cracks, even under challenging and complex traffic backgrounds. This advancement in road crack detection technology has significant implications for improving road maintenance and safety.
A Self-Supervised Model Based on CutPaste-Mix for Ductile Cast Iron Pipe Surface Defect Classification
Authors: Zhang Hanxin , Sun Qian , Xu Ke
Published: October 2023

Online surface inspection systems have gradually found applications in industrial settings. However, the manual effort required to sift through a vast amount of data to identify defect images remains costly. This study delves into a self-supervised binary classification algorithm for addressing the task of defect image classification within ductile cast iron pipe (DCIP) images. Leveraging the CutPaste-Mix data augmentation strategy, we combine defect-free data with enhanced data to input into a deep convolutional neural network. Through Gaussian Density Estimation, we compute anomaly scores to achieve the classification of abnormal regions. Our approach has been implemented in real-world scenarios, involving equipment installation, data collection, and experimentation. The results demonstrate the robust performance of our method, in both the DCIP image dataset and practical field application, achieving an impressive 99.5 AUC (Area Under Curve). This presents a cost-effective means of providing data support for subsequent DCIP surface inspection model training.
PhysioKit: An Open-Source, Low-Cost Physiological Computing Toolkit for Single- and Multi-User Studies
Authors: Joshi Jitesh , Wang Katherine , Cho Youngjun
Published: October 2023

The proliferation of physiological sensors opens new opportunities to explore interactions, conduct experiments and evaluate the user experience with continuous monitoring of bodily functions. Commercial devices, however, can be costly or limit access to raw waveform data, while low-cost sensors are efforts-intensive to setup. To address these challenges, we introduce PhysioKit, an open-source, low-cost physiological computing toolkit. PhysioKit provides a one-stop pipeline consisting of (i) a sensing and data acquisition layer that can be configured in a modular manner per research needs, and (ii) a software application layer that enables data acquisition, real-time visualization and machine learning (ML)-enabled signal quality assessment. This also supports basic visual biofeedback configurations and synchronized acquisition for co-located or remote multi-user settings. In a validation study with 16 participants, PhysioKit shows strong agreement with research-grade sensors on measuring heart rate and heart rate variability metrics data. Furthermore, we report usability survey results from 10 small-project teams (44 individual members in total) who used PhysioKit for 4–6 weeks, providing insights into its use cases and research benefits. Lastly, we discuss the extensibility and potential impact of the toolkit on the research community.
Grant-Free NOMA: A Low-Complexity Power Control through User Clustering
Authors: Celik Abdulkadir
Published: October 2023

Non-orthogonal multiple access (NOMA) has emerged as a promising solution to support multiple devices on the same network resources, improving spectral efficiency and enabling massive connectivity required by ever-increasing Internet of Things devices. However, traditional NOMA schemes operate in a grant-based fashion and require channel-state information and power control, which hinders its implementation for massive machine-type communications. Accordingly, this paper proposes synchronous grant-free NOMA (GF-NOMA) frameworks that effectively integrate user equipment (UE) clustering and low-complexity power control to facilitate the power-reception disparity required by the power-domain NOMA. Although single-level GF-NOMA (SGF-NOMA) designates an identical transmit power for all UEs, multi-level GF-NOMA (MGF-NOMA) groups UEs into partitions based on the sounding reference signals strength and assigns partitions with different identical power levels. Based on the objective of interest (e.g., max–sum or max–min rate), the proposed UE clustering scheme iteratively admits UEs to form clusters whose size is dynamically determined based on the number of UEs and available resource blocks (RBs). Once the UEs are acknowledged with power levels and allocated RBs through random-access response (RAR) messages, UEs can transmit anytime without grant acquisition. Numerical results show that the proposed GF-NOMA frameworks can compute clusters in the order of milliseconds for hundreds of UEs. The MGF-NOMA can reach up to 96–99% of the optimal benchmark max–sum rate, and the SGF-NOMA reaches 87% of the optimal benchmark max–sum rate at the same power consumption. Since the MGF-NOMA and optimal benchmark enforce the strongest and weakest channel UEs to transmit at maximum and minimum transmit powers, respectively, the SGF-NOMA also offers a significantly higher energy consumption fairness and network lifetime as all UEs consume equal transmit powers. Although the MGF-NOMA delivers an inferior max–min rate performance, the SGF-NOMA is shown to reach 3e6 MbpJ energy efficiency compared to the 1e7 MbpJ benchmark.
Application of a Magnetic Field to Enhance the Environmental Sustainability and Efficiency of Microbial and Plant Biotechnological Processes
Authors: Sincak Miroslava , Luptakova Alena , Matusikova Ildiko , Jandacka Petr , Sedlakova-Kadukova Jana
Published: October 2023

Despite the growing prevalence of using living organisms in industry, the control of biotechnological processes remains highly complex and constitutes one of the foremost challenges in these applications. The usage of electromagnetic fields offers a great opportunity to control various biotechnological processes by alternating growth and cell metabolism without influencing the characteristics of the cultivation medium or the products of the biotechnological process. The investigation of electromagnetic field applications across various industries, including food production, medicine, and pollutant mitigation, has yielded substantial insights. We used the scientific databases PubMed and ScienceDirect to select 103 experimental and theoretical articles that included original results suitable for further investigation. This type of search was repeated with every new relevant article iteratively until no new articles could be detected. Notably, even weak, low-frequency magnetic fields can accelerate the growth of certain organisms, further stabilize the bacterial community in activated sludge within wastewater treatment plants, enhance the fermentation capabilities of both yeast and bacteria, enhance metal bioleaching by the activation of bacterial metabolism, or improve the metal tolerance of plants during the phytoremediation process. Moreover, magnetic fields exhibit a promising sustainable possibility for the better control of biotechnological processes, thus making these processes more competitive compared with the currently used long-term unsustainable extraction of metals. Although with these interesting results, these examples represent highly exceptional applications. Despite these examples, the overall application potential of magnetic fields remains largely unexplored and unknown.
Shaping the Conscious Behaviors of Product Designers in the Early Stages of Projects: Promoting Correct Material Selection and Green Self-Identity through a New Conceptual Model
Authors: Sun Zhonghua , Doiro Manuel , Sá José Carlos , Santos Gilberto
Published: October 2023

Material selection for product design is a complex task. Thus, one of the objectives of this work is to analyze and understand and to promote the importance of material selection to conceive quality products with the help of designers that promote green self-identity in the early stage of new product conception. A questionnaire was sent to professional designers and engineers. Thirty-eight responses were validated, which represented the sample for this study. The aspects that influence the complex material selection process and the final quality of the products through the design and production process are presented. Taking into consideration the responses from product designers who work in the market, as well as some engineers and students who are graduating in product design, a new approach for material selection was developed. Based on a collection of main ideas from the traditional and non-traditional material selection methods, seeking to group the maximum requirements of both methods, and inspired by the “canvas” model on the basic modular methodology, a new model for new product projects is presented. Our study focuses on material selection, since this aspect is one of the most relevant steps in the early stage of the prototyping phase of new products, with a view to reducing CO2 from the air in the atmosphere that we all breathe. The classification of materials is complex due to the diversity of available options. The novelty of this model is that all the properties of a newly designed product, such as technical, aesthetic, productive, and environmental properties, are grouped in the model, which serves as an innovative support. Thus, designers have a tool at their disposal that can help them to select the best materials for the products they design. The results of this study contribute to the field of material selection, to the quality and design of new products, and to promoting green self-identity of designers in the initial phase of product design. Consequently, all consumers in search of a sustainable planet will profit from this study.
Boosting Hot Mix Asphalt Dynamic Modulus Prediction Using Statistical and Machine Learning Regression Modeling Techniques
Authors: Awed Ahmed M. , Awaad Ahmed N. , Kaloop Mosbeh R. , Hu Jong Wan , El-Badawy Sherif M. , Abd El-Hakim Ragaa T.
Published: October 2023

The prediction of asphalt mixture dynamic modulus (E*) was investigated based on 1128 E* measurements, using three regression and thirteen machine learning models. Asphalt binder properties and mixture volumetrics were characterized using the same feeding features in the NCHRP 1-37A Witczak model. However, three aggregate gradation characterization approaches were involved in both modelling techniques: the NCHRP 1-37A gradation parameters, Weibull distribution factors, and Bailey method parameters. This study evaluated the performance of these models based on various performance indicators, using both statistical and machine learning regression modeling techniques. K-fold cross-validation and learning curve analysis were conducted to assess the models’ generalization capabilities. The conclusions of this study demonstrate the superiority of the ML models, particularly the Catboost ensemble learning regression (CbR). Hyperparameter optimization and residual analysis were performed to fine-tune and confirm the heteroscedasticity of the CbR model. The Bailey-based CbR model showed the highest coefficient of determination (R2) of 0.998 and the lowest root mean square error (RMSE) of 220 MPa. Moreover, SHAP values interpreted the CbR model and showed the relative importance of its feeding features. Based on the findings of this study, the CbR model is suggested to accurately predict E* for a variety of asphalt mixtures. This information can be used to improve pavement design and construction, leading to more durable and long-lasting pavements.