bluuebunny/crossref_metadata_2025 huggingface dataset:
In Vitro Gene Therapy Using Human iPS-Derived Mesoangioblast-Like Cells (HIDEMs) Combined with Microdystrophin (μDys) Expression as the New Strategy for Duchenne Muscular Dystrophy (DMD) Experimental Treatment
Authors: Budzińska Marta , Malcher Agnieszka , Zimna Agnieszka , Kurpisz Maciej
Published: November 2024

Duchenne Muscular Dystrophy (DMD) is a genetic disorder characterized by disruptions in the dystrophin gene. This study aims to investigate potential a therapeutic approach using genetically modified human iPS-derived mesoangioblast-like cells (HIDEMs) in mdx mouse model. This study utilizes patient-specific myoblasts reprogrammed to human induced pluripotent stem cells (iPSCs) and then differentiated into HIDEMs. Lentiviral vectors carrying microdystrophin sequences have been employed to deliver the genetic construct to express a shortened, functional dystrophin protein in HIDEMs. The study indicated significant changes within redox potential between healthy and pathological HIDEM cells derived from DMD patients studied by catalase and superoxide dismutase activities. Microdystrophin expressing HIDEMs also improved expression of genes involved in STARS (striated muscle activator of Rho signaling) pathway albeit in selective DMD patients (with mild phenotype). Although in vivo observations did not bring progress in the mobility of mdx mice with HIDEMs, microdystrophin interventions this may argue against “treadmill test” as suitable for assessment of mdx mice recovery. Low-level signaling of the Rho pathway and inflammation-related factors in DMD myogenic cells can also contribute to the lack of success in a functional study. Overall, this research contributes to the understanding of DMD pathogenesis and provides insights into potential novel therapeutic strategy, highlighting the importance of personalized gene therapy.
A Novel Single Base Mutation in OsSPL42 Leads to the Formation of Leaf Lesions in Rice
Authors: Li Panpan , Shang Huihui , Xu Xia , Gong Junyi , Wu Jian-Li , Zhang Xiaobo
Published: November 2024

Rice spotted-leaf mutants serve as valuable resources for studying plant programmed cell death (PCD) and disease resistance mechanisms, making them crucial for research on disease resistance in rice. Map-based cloning was used to identify and clone the spotted-leaf gene OsSPL42. Then, functional complementation and CRISPR/Cas9 techniques were also employed to further validate the function of this gene. By applying leaf clippings for bacterial blight (BB) inoculation, the BB resistance of different rice lines was assessed. The results in this study were as follows: The OsSPL42 behaved as a recessive nuclear gene and was narrowed down to a 111 kb region on chromosome 8. All T0 transgenic rice plants in the complementation experiments exhibited a wild-type phenotype, without any lesion spots on the rice leaves. This suggests that the LOC_Os08g06100 encoding O-methyltransferase is the candidate gene for the mutant spl42. The OsSpl42 is widely expressed and the OsSPL42-GFP protein is mainly localized in the cytoplasm. OsSPL42 overexpression lines are more susceptible to BBs, which indicates that OsSPL42 may act as a negative regulator of rice resistance to BB. In summary, we speculate that OsSPL42 plays an important role in the regulation of pathogen response, providing new insights into plant defense mechanisms.
Antiviral Effect of Melatonin on Caco-2 Cell Organoid Culture: Trick or Treat?
Authors: Šeškutė Milda , Žukaitė Dominyka , Laucaitytė Goda , Inčiūraitė Rūta , Malinauskas Mantas , Jankauskaitė Lina
Published: November 2024

Melatonin is a hormone naturally produced by the body that has recently been found to have antiviral properties. However, its antiviral mechanisms are not entirely understood. Using Caco-2 cells, we developed a gastrointestinal organoid model to investigate the impact of melatonin on cellular organoid culture response to Poly I:C-induced viral inflammation in the gastrointestinal tract. Melatonin was found to have different effect when applied as a pretreatment before the induction of viral inflammation or as a treatment after it. Melatonin pretreatment after Poly I:C stimulation did not protect organoids from size reduction but enhanced cell proliferation, especially when lower (1 and 10 µM) melatonin concentrations were used. On the other hand, treatment with melatonin after the induction of viral inflammation helped to maintain the size of the organoids while reducing cell proliferation. In pretreated cells, reduced IFNLR1 expression was found, while melatonin treatment increased IFNLR1 expression and reduced the production of viral cytokines, such as IFNλ1 and STAT1-3, but did not prevent from apoptosis. The findings of this study emphasize the importance of type III IFNs in antiviral defense in epithelial gastrointestinal cells and shed more light on the antiviral properties of melatonin as a potential therapeutic substance.
Linking Antibodies Against Apolipoprotein A-1 to Metabolic Dysfunction-Associated Steatohepatitis in Mice
Authors: Pagano Sabrina , Somm Emmanuel , Juillard Catherine , Liaudet Nicolas , Ino Frédérique , Ferrari Johan , Braunersreuther Vincent , Jornayvaz François R. , Vuilleumier Nicolas
Published: November 2024

Metabolic dysfunction-associated fatty liver disease (MASLD) is a common liver and health issue associated with heightened cardiovascular disease (CVD) risk, with Cytokeratin 18 (CK-18) as a marker of liver injury across the MASLD to cirrhosis spectrum. Autoantibodies against apolipoprotein A-1 (AAA-1s) predict increased CVD risk, promoting atherosclerosis and liver steatosis in apoE−/− mice, though their impact on liver inflammation and fibrosis remains unclear. This study examined AAA-1s’ impact on low-grade inflammation, liver steatosis, and fibrosis using a MASLD mouse model exposed to AAA-1s passive immunization (PI). Ten-week-old male C57BL/6J mice under a high-fat diet underwent PI with AAA-1s or control antibodies for ten days. Compared to controls, AAA-1-immunized mice showed higher plasma CK-18 (5.3 vs. 2.1 pg/mL, p = 0.031), IL-6 (13 vs. 6.9 pg/mL, p = 0.035), IL-10 (27.3 vs. 9.8 pg/mL, p = 0.007), TNF-α (32.1 vs. 24.2 pg/mL, p = 0.032), and liver steatosis (93.4% vs. 73.8%, p = 0.007). Transcriptomic analyses revealed hepatic upregulation of pro-fibrotic mRNAs in AAA-1-recipient mice, though histological changes were absent. In conclusion, short-term AAA-1 PI exacerbated liver steatosis, inflammation, and pro-fibrotic gene expression, suggesting that AAA-1s may play a role in MASLD progression. Further research with prolonged AAA-1 exposure is warranted to clarify their potential role in liver fibrosis and associated complications.
Iodinated PSMA Ligands as XFI Tracers for Targeted Cell Imaging and Characterization of Nanoparticles
Authors: Kerpa Svenja , Holzapfel Malte , Staufer Theresa , Kuhrwahl Robert , Mutas Marina , Werner Stefan , Schulze Verena R. , Nakielski Pascal , Feliu Neus , Oetjen Elke , Haak Jannis , Ziegler Florian , Buchin Rasmus , Han Jili , Parak Wolfgang J. , Grüner Florian , Maison Wolfgang
Published: November 2024

Prostate cancer is the second most commonly diagnosed cancer in men worldwide. Despite this, current diagnostic tools are still not satisfactory, lacking sensitivity for early-stage or single-cell diagnosis. This study describes the development of small-molecule tracers for the well-known tumor marker prostate-specific membrane antigen (PSMA). These tracers contain a urea motif for PSMA-targeting and iodinated aromatic moieties to allow detection via X-ray fluorescence imaging (XFI). Tracers with a triiodobenzoyl moiety allowed the specific targeting and successful imaging of PSMA+ cell lines with XFI. The XFI-measured uptake of 7.88 × 10−18 mol iodine (I) per cell is consistent with the uptake of known PSMA tracers measured by other techniques such as inductively coupled plasma mass spectrometry (ICP-MS). This is the first successful application of XFI to tumor cell targeting with a small-molecule tracer. In addition, iodinated tracers were used for the characterization of quantum dots (QDs) conjugated to PSMA-targeting urea motifs. The resulting targeted QD conjugates were shown to selectively bind PSMA+ cell lines via confocal microscopy. The immobilized iodinated targeting vectors allowed the determination of the tracer/QD ratio via XFI and ICP-MS. This ratio is a key property of targeted particles and difficult to measure by other techniques.
Structure–Tissue Exposure/Selectivity Relationship (STR) on Carbamates of Cannabidiol
Authors: Wang Sheng , Yang Jian-Guo , Rong Kuanrong , Li Huan-Huan , Wu Chengyao , Tang Wenjian
Published: November 2024

The structure–tissue exposure/selectivity relationship (STR) aids in lead optimization to improve drug candidate selection and balance clinical dose, efficacy, and toxicity. In this work, butyrocholinesterase (BuChE)-targeted cannabidiol (CBD) carbamates were used to study the STR in correlation with observed efficacy/toxicity. CBD carbamates with similar structures and same molecular target showed similar/different pharmacokinetics. L2 and L4 had almost same plasma exposure, which was not correlated with their exposure in the brain, while tissue exposure/selectivity was correlated with efficacy/safety. Structural modifications of CBD carbamates not only changed drug plasma exposure, but also altered drug tissue exposure/selectivity. The secondary amine of carbamate can be metabolized into CBD, while the tertiary amine is more stable. Absorption, distribution, metabolism, excretion, and toxicity (ADMET) parameters can be used to predict STR. Therefore, STR can alter drug tissue exposure/selectivity in normal tissues, impacting efficacy/toxicity. The drug optimization process should balance the structure–activity relationship (SAR) and STR of drug candidates for improving clinical trials.
Novel Basidiomycetous Alcohol Oxidase from Cerrena unicolor—Characterisation, Kinetics, and Proteolytic Modifications
Authors: Stefanek Sylwia , Typek Rafał , Dybowski Michał , Wianowska Dorota , Jaszek Magdalena , Janusz Grzegorz
Published: November 2024

Intracellular alcohol oxidase (AOX) was isolated from the basidiomycetous white rot fungus Cerrena unicolor FCL139. The enzyme was semi-purified (13-fold) using two-step chromatography with 30% activity recovery. The identity of the protein was confirmed by LC-MS/MS analysis, and its MW (72 kDa) and pI (6.18) were also determined. The kinetics parameters of the AOX reaction towards various substrates were analysed, which proved that, in addition to methanol (4.36 ± 0.27% of the oxidised substrate), AOX most potently oxidises aromatic alcohols, such as 4-hydroxybenzyl alcohol (14.0 ± 0.8%), benzyl alcohol (4.2 ± 0.3%), anisyl alcohol (7.6 ± 0.4%), and veratryl alcohol (5.0 ± 0.3%). Moreover, the influence of selected commercially available proteases on the biocatalytic properties of AOX from C. unicolor was studied. It was proved that the digested enzyme lost its catalytic potential properties except when incubated with pepsin, which significantly boosted its activity up to 123%.
Mechanisms of Immune Evasion in PTEN Loss Prostate Cancer
Authors: Esteban-Villarrubia Jorge , Ballesteros Pablo Alvarez , Martín-Serrano Miguel , Vico María Ruiz , Funes Juan M , de Velasco Guillermo , Castro Elena , Olmos David , Castellano Daniel , González-Billalabeitia Enrique
Published: November 2024

PTEN (phosphatase and tensin homolog) is a frequently lost tumor suppressor gene in prostate cancer, leading to aggressive tumor behavior and poor clinical outcomes. PTEN loss results in aberrant activation of the PI3K/AKT/mTOR pathway, promoting oncogenesis. These alterations also lead to an immunosuppressive tumor microenvironment with altered immune cell infiltration, cytokine profiles, and immune checkpoint regulation. This review aims to provide a comprehensive overview of the mechanisms underlying PTEN loss in prostate cancer and the consequent immune alterations observed in this subtype, thus underscoring the importance of understanding PTEN-mediated immune modulation for the development of effective therapeutic interventions in prostate cancer.
Unsupervised Decision Trees for Axis Unimodal Clustering
Authors: Chasani Paraskevi , Likas Aristidis
Published: November 2024

The use of decision trees for obtaining and representing clustering solutions is advantageous, due to their interpretability property. We propose a method called Decision Trees for Axis Unimodal Clustering (DTAUC), which constructs unsupervised binary decision trees for clustering by exploiting the concept of unimodality. Unimodality is a key property indicating the grouping behavior of data around a single density mode. Our approach is based on the notion of an axis unimodal cluster: a cluster where all features are unimodal, i.e., the set of values of each feature is unimodal as decided by a unimodality test. The proposed method follows the typical top-down splitting paradigm for building axis-aligned decision trees and aims to partition the initial dataset into axis unimodal clusters by applying thresholding on multimodal features. To determine the decision rule at each node, we propose a criterion that combines unimodality and separation. The method automatically terminates when all clusters are axis unimodal. Unlike typical decision tree methods, DTAUC does not require user-defined hyperparameters, such as maximum tree depth or the minimum number of points per leaf, except for the significance level of the unimodality test. Comparative experimental results on various synthetic and real datasets indicate the effectiveness of our method.
Uncovering Key Factors That Drive the Impressions of Online Emerging Technology Narratives
Authors: Williams Lowri , Anthi Eirini , Burnap Pete
Published: November 2024

Social media platforms play a significant role in facilitating business decision making, especially in the context of emerging technologies. Such platforms offer a rich source of data from a global audience, which can provide organisations with insights into market trends, consumer behaviour, and attitudes towards specific technologies, as well as monitoring competitor activity. In the context of social media, such insights are conceptualised as immediate and real-time behavioural responses measured by likes, comments, and shares. To monitor such metrics, social media platforms have introduced tools that allow users to analyse and track the performance of their posts and understand their audience. However, the existing tools often overlook the impact of contextual features such as sentiment, URL inclusion, and specific word use. This paper presents a data-driven framework to identify and quantify the influence of such features on the visibility and impact of technology-related tweets. The quantitative analysis from statistical modelling reveals that certain content-based features, like the number of words and pronouns used, positively correlate with the impressions of tweets, with increases of up to 2.8%. Conversely, features such as the excessive use of hashtags, verbs, and complex sentences were found to decrease impressions significantly, with a notable reduction of 8.6% associated with tweets containing numerous trailing characters. Moreover, the study shows that tweets expressing negative sentiments tend to be more impressionable, likely due to a negativity bias that elicits stronger emotional responses and drives higher engagement and virality. Additionally, the sentiment associated with specific technologies also played a crucial role; positive sentiments linked to beneficial technologies like data science or machine learning significantly boosted impressions, while similar sentiments towards negatively viewed technologies like cyber threats reduced them. The inclusion of URLs in tweets also had a mixed impact on impressions—enhancing engagement for general technology topics, but reducing it for sensitive subjects due to potential concerns over link safety. These findings underscore the importance of a strategic approach to social media content creation, emphasising the need for businesses to align their communication strategies, such as responding to shifts in user behaviours, new demands, and emerging uncertainties, with dynamic user engagement patterns.
Pressure and Temperature Prediction of Oil Pipeline Networks Based on a Mechanism-Data Hybrid Driven Method
Authors: Gong Faming , Zhao Xingfang , Du Chengze , Zheng Kaiwen , Shi Zhuang , Wang Hao
Published: November 2024

To ensure the operational safety of oil transportation stations, it is crucial to predict the impact of pressure and temperature before crude oil enters the pipeline network. Accurate predictions enable the assessment of the pipeline’s load-bearing capacity and the prevention of potential safety incidents. Most existing studies primarily focus on describing and modeling the mechanisms of the oil flow process. However, monitoring data can be skewed by factors such as instrument aging and pipeline friction, leading to inaccurate predictions when relying solely on mechanistic or data-driven approaches. To address these limitations, this paper proposes a Temporal-Spatial Three-stream Temporal Convolutional Network (TS-TTCN) model that integrates mechanistic knowledge with data-driven methods. Building upon Temporal Convolutional Networks (TCN), the TS-TTCN model synthesizes mechanistic insights into the oil transport process to establish a hybrid driving mechanism. In the temporal dimension, it incorporates real-time operating parameters and applies temporal convolution techniques to capture the time-series characteristics of the oil transportation pipeline network. In the spatial dimension, it constructs a directed topological map based on the pipeline network’s node structure to characterize spatial features. Data analysis and experimental results show that the Three-stream Temporal Convolutional Network (TTCN) model, which uses a Tanh activation function, achieves an error rate below 5%. By analyzing and validating real-time data from the Dongying oil transportation station, the proposed hybrid model proves to be more stable, reliable, and accurate under varying operating conditions.
Identification on Key Volatiles Contributed to Oviposition Preference of Plodia interpunctella (Hübner, 1813) (Lepidoptera: Pyralidae) from High and Normal Oleic Varieties of Peanut
Authors: Wang Chen , Wang Dianxuan , Zeng Fangfang , Chen Liang , Zhao Xinxin , Zhu Xi , Yao Junji , Li Yihan
Published: November 2024

The Indian meal moth, Plodia interpunctella (Hübner, 1813) (Lepidoptera: Pyralidae), a primary stored peanut insect pest, exhibited a significant difference in oviposition preference among normal-oleic peanuts (NOPs) and high-oleic peanuts (HOPs). Identifying key volatile organic compounds (VOCs) that are attractive or repellent to P. interpunctella is of great significance for the ecological management of pests. The profiles and contents of VOCs among NOP and HOP varieties were measured and compared, and key bioactive VOCs were further confirmed via an electroantennogram (EAG) analysis, as well as behavioral responses in Y-tube olfactometer and wind tunnel bioassays. Females prefer to lay eggs on NOP varieties more than on HOP ones. Acetophenone, nonanal, decanal, dodecane, 2,5-dimethylbenzaldehyde, and 4-ethyl-benzaldehy derived from tested peanuts elicited stronger antennal EAG responses. The results of the Y-tube olfactometer and wind tunnel bioassay showed that the relative high levels of nonanal, dodecane, and unique VOC acetophenone in NOP varieties have a significant attraction to P. interpunctella. Conversely, 4-ethyl-benzaldehyde and the unique VOC 2,5-dimethyl-benzaldehyde commonly found in HOP varieties exhibit notable repellent effects on P. interpunctella. These VOCs could contribute to the development of attractants or repellents derived from special peanut varieties for pest management.
The Impact of Triglyceride-Glucose (TyG) Index on Future Cardio and Cerebrovascular Events in Patients with Acute Coronary Syndrome, During 3 Years of Follow-Up
Authors: Macaione Francesca , Di Lisi Daniela , Madaudo Cristina , D’agostino Alessandro , Adorno Daniele , Sucato Vincenzo , Novo Giuseppina , Evola Salvatore
Published: November 2024

Background: The triglyceride-glucose (TyG) index is a new alternative insulin resistance (IR) biomarker. The purpose of this study was to assess whether the TyG index can have a prognostic value in patients with acute coronary syndrome (ACS). Moreover, we wanted to compare the TyG index with HOMA index. Methods: We retrospectively enrolled 115 consecutive subjects, 81 males and 34 females, referred for ACS to our Unit of Cardiovascular Care of Policlinico Paolo Giaccone, Palermo. The subjects were divided into tertiles according to TyG index values and we performed a 3-year follow-up study. We considered as an end point new cardiovascular and cerebral events (MACCEs) during follow-up. Results: We found a significant statistical correlation between the HOMA index and the TyG index (p = 0.001). Patients with elevated TyG index have a higher incidence of MACCE at a 3-year follow-up. In our study the TyG index was an independent predictor of MACCEs (95% CI 1.8158 to 16.8068; P 0.0026) and the optimal TyG index cut-off for predicting MACCEs was 4.92 (sensitivity 76.56% and specificity 72.55%). Conclusions: The TyG index seems to significantly have an important prognostic role in patients with ACS and high values of TyG index are superior to HOMA-IR in predicting MACCEs.
Impact of a 20-Week Resistance Training Program on the Force–Velocity Profile in Novice Lifters Using Isokinetic Two-Point Testing
Authors: Drigny Joffrey , Pamart Nicolas , Azambourg Hélène , Remilly Marion , Reboursière Emmanuel , Gauthier Antoine , Hodzic Amir
Published: November 2024

Objectives: This study aimed to assess the impact of a 20-week resistance training program on force–velocity (F-V) parameters using an isokinetic two-point method and comparing one-repetition maximum (1-RM) methods in novice lifters. Methods: Previously untrained individuals completed a supervised, three-session weekly resistance training program involving concentric, eccentric, and isometric phases, repeated every 2 to 4 weeks. Isokinetic dynamometry measured the strength of elbow flexors/extensors at 60°/s and 150°/s, and knee flexors/extensors at 60°/s and 240°/s at Baseline, 3 months, and 5 months. F-V parameters, including maximal theoretical force (F0) and the F-V slope, were calculated. Participants also performed 1-RM tests for the upper and lower limbs. Repeated measures ANOVA with effect size (η2 > 0.14 as large) was used to analyze changes in F-V parameters and repeated measures correlation was used to test their association with 1-RM outcomes. Results: Eighteen male participants (22.0 ± 3.4 years) were analyzed. F0 significantly increased for all muscle groups (η2 = 0.423 to 0.883) except elbow flexors. F-V slope significantly decreased (steeper) for knee extensors and flexors (η2 = 0.348 to 0.695). Knee extensors showed greater F0 gains and steeper F-V slopes than flexors (η2 = 0.398 to 0.686). F0 gains were associated with 1-RM changes (r = 0.38 to 0.83), while F-V slope changes correlated only with lower limb 1-RM (r = −0.37 to −0.68). Conclusions: The 20-week resistance training program significantly increased F0 and shifted the F-V profile towards a more “force-oriented” state in knee muscles. These changes correlated with improved 1-RM performance. Future studies should include longer follow-ups and control groups.
Eye Movement Patterns in Russian-Speaking Adolescents with Differing Reading Comprehension Proficiency: Exploratory Scanpath Analysis
Authors: Berlin Khenis Alexandra , Markevich Maksim , Streltsova Anastasiia , Grigorenko Elena L.
Published: November 2024

Previous research has indicated that individuals with varying levels of reading comprehension (often used as a proxy for general cognitive ability) employ distinct reading eye movement patterns. This exploratory eye-tracking study aimed to investigate the text-reading process in adolescents with differing reading comprehension, specifically examining how these differences manifest at the global eye movement level through scanpath analysis. Our findings revealed two distinct groups of scanpaths characterized by statistically significant differences in eye movement parameters. These groups were identified as “fast readers” and “slow readers”. Both groups exhibited similar oculomotor performance during the initial reading. However, significant differences emerged when they reread and revisited the text. Notably, these findings align with prior research conducted with different samples and languages, although discrepancies emerged in saccade amplitude and first-pass reading behavior. This study contributes to the understanding of how reading comprehension levels are reflected in global eye movement strategies among adolescents. However, limitations inherent in the experimental design, particularly the potential influence of the task on reading patterns, warrant further investigation. Future research should aim to explore these phenomena in more naturalistic reading settings, employing a design specifically tailored to capture the nuances of spontaneous reading behavior.
Taguchi, Grey Relational Analysis, and ANOVA Optimization of TIG Welding Parameters to Maximize Mechanical Performance of Al-6061 T6 Alloy
Authors: Rojas Hugo , Vargas Zully , Valdez Socorro , Serrano Manuel , del Pozo Adrián , Alcántara Ma.
Published: November 2024

This study presents a comprehensive investigation into optimizing Tungsten Inert Gas (TIG) welding parameters to enhance the mechanical performance of the widely used Al-6061 T6 alloy, specifically in a double V joint configuration with a plate thickness of 6 mm, for aerospace applications. The Taguchi method was employed to design the experiments, providing a robust framework for analyzing the influence of the electrical current, voltage, and gas flow rate on weld quality. Additionally, a Grey Relational Analysis (GRA) and an Analysis of Variance (ANOVA) were used to validate the optimal welding parameters and quantify the significance of each factor. The optimized parameters were determined to be an amperage of 180 A, a voltage of 18 V, and a gas flow rate of 10 L/min, resulting in significant improvements of up to 40% in tensile strength and 23% in hardness, demonstrating the effectiveness of the optimized conditions. The findings provide valuable insights into welding metallurgy, offering practical guidelines for enhancing high-performance welded joints in critical industrial applications. This study underscores the potential of combining Taguchi, GRA, and ANOVA methodologies to achieve superior mechanical properties and reliability in welded structures.
Type, Genesis, and Provenance Implications of Amphiboles in Sediments in the Northwest Indian Ocean over 42,000 Years
Authors: Wang Feng , Li Yunhai , Jin Bingfu , Wang Mengyao , Li Dongyi , Lai Zhikun , Chen Jian , Shen Pengfei , Wang Liang , Cai Mingjiang
Published: November 2024

Five layers of detrital amphiboles in the CJ08-008 sediment core from the northwest Indian Ocean have been found. To analyze their genetic types and provenance, an electron probe microanalysis of 300 amphibole grains from the core was conducted to calculate the numerical and characteristic values of cations in the crystal structure. The results showed that amphiboles with high Si, Ca, and Mg contents and low Na and K contents exhibit a low degree of weathering and that amphiboles mainly comprise tschermakite (46.43~70.69%), followed by magnesiohornblende, in the calcic amphibole subgroup. The types of sources for these amphiboles are mainly different types of metamorphic and magmatic rock. A large proportion of the detrital amphiboles (>60%) are derived from metamorphic rocks, followed by intermediate acid-intrusive rocks. The genetic analysis of amphiboles showed that most of the medium acid-intrusive amphiboles belong to the crust–mantle type, followed by the mantle type. Most of the amphiboles of metamorphic origin are of the low-pressure type. The amphiboles in the CJ08-008 sediment core exhibit characteristics different from those brought by monsoons from surrounding land masses. The variations in the amphiboles indicate different sources, which may have different origins; these origins could include the Carlsberg Ridge, the Owen Fault Zone, or older submarine sediment sequences eroded by turbidity currents.
Upper Ocean Thermodynamic Response to Coupling Currents to Wind Stress over the Gulf Stream
Authors: May Jackie , Bourassa Mark A.
Published: November 2024

We use high-resolution coupled atmosphere–ocean model simulations over the Gulf Stream extension region during a winter season to examine the upper ocean thermodynamic response to including current feedback to atmospheric wind stress. We demonstrate that a model that includes current feedback leads to significant changes in the structure and transport of heat throughout the upper ocean in comparison to the same model without current feedback. We find that including the current feedback leads to changes in the upper ocean temperature pattern that match the vorticity pattern. Areas with cyclonic ocean vorticity, typically north of the Gulf Stream extension, correspond to areas with warmer temperatures throughout the water column. Areas with anticyclonic ocean vorticity, typically south of the Gulf Stream extension, correspond to areas with cooler temperatures throughout the water column. We also find that including current feedback leads to an overall reduction in the submesoscale vertical heat flux spectra across all spatial scales, with differences in the submesoscale vertical heat flux corresponding to SST minus mixed layer temperature differences. The direct impact of current feedback on the thermodynamic structure within the upper ocean also has indirect impacts on other aspects of the ocean, such as the energy transfer between the ocean and the atmosphere, ocean stratification, and acoustic parameters.
Comparative Mitogenomics Provides Valuable Insights for the Phylogeny and New DNA Barcodes of Ganoderma
Authors: Chen Ti-Qiang , Yang Chi , Xu Xiao-Lan , Yang Lin , He Huan-Qing , Weng Meng-Ting , Ying Zheng-He , Shi Xiao-Kun , Ding Meng-Guang
Published: November 2024

Ganoderma is the most important genus in the family Ganodermataceae; many species have attracted much attention and widely cultivated because of their medicinal values, but so far, not a sequenced mitogenome derived from dikaryon strains has been explicitly recorded. Herein, four novel mitogenomes of commonly cultivated Ganoderma (G. leucocontextum H4, G. lucidum G6, G. sinense MZ96 and G. tsugae SS) were de novo assembled and given detail functional annotations. Collinearity analysis revealed that the four mitogenomes shared 82.93–92.02% similarity with their corresponding reference mitogenomes at the nucleotide level. A total of 15 core protein-coding genes (PCGs), along with rrnL and rrnS (mtLSU and mtSSU) were chosen as potential candidates for constructing their individual phylogenetic trees. These trees were compared with those derived from the concatenated sequences of 15 core PCGs. And finally, we found that the atp9 and nad4L were the most reliable markers for the phylogenetic analysis of Ganoderma and chosen as standard sequences to generate new DNA barcodes. This finding was further verified by comparing it against almost all available Ganoderma mitogenomes in the NCBI, with Trametes versicolor (Polyporaceae) and Rigidoporus microporus (Meripilaceae) as two outgroups. A total of 52 mitogenomes from three families were highly conserved, with identical gene lengths for atp9 (222 bp) and nad4L (267 bp). These genes were capable of distinguish distinctly different various species, which are grouped into separate clades within the phylogenetic trees. The closest related clades (I and II), including at least 30 samples of the three classical taxonomic species (G. lingzhi, G. sichuanense and G. lucidum), differed in only one SNP. The single base mutation rate increased with the evolutionary divergence of the phylogenetic clades, from two to three SNPs in earlier clades (e.g., clade IV containing G. leucocontextum) to five to six SNPs in later clades (e.g., clade X containing G. sinense). Despite these variations between species, the atp9 and nad4L genes of Ganoderma mitogenomes consistently encoded the same ATP synthase F0 subunit c (73 aa) and NADH dehydrogenase subunit 4L (88 aa). These two genes have been identified as reliable markers of new DNA barcodes, offering valuable insights and contributing significantly to understanding the evolutionary relationships and phylogeny of the Ganoderma genus and even the Ganodermataceae family.
Integrating Artificial Intelligence and Big Data in Spanish Journalism Education: A Curricular Analysis
Authors: Tejedor Santiago , Cervi Laura , Romero-Rodríguez Luis M. , Vick Stephanie
Published: November 2024

Artificial intelligence (AI) and big data have impacted different professional sectors in our society. Communication and journalism are clearly among them. From the automatic generation of content to the identification of topics of interest or monitoring of users’ usage habits, AI introduces important training challenges for professionals in the field of communication. Meanwhile, big data analytics enables data journalists to handle large amounts of information in an automated manner, allowing them to perform in-depth analysis of disorganized data. This study analyzes the integration of artificial intelligence (AI) and big data in the curricula of journalism degrees offered by Spanish universities. The research employs quantitative and qualitative methods to examine the typology, syllabus, and distribution of subjects directly or indirectly addressing AI and big data topics, based on indicators such as structure, credit system, objectives, competencies, and professional profiles. The results reveal a scarce integration of AI and Big Data subjects in journalism curricula in Spain. Among the analyzed courses, only seven addressed data journalism as a complete course, while 19 introduced AI and Big Data as part of more general content. The study highlights the need for journalism education to adapt to the disruptive impact of AI and big data on the profession. It discusses the debate between focusing on teaching technological skills versus providing critical and ethical values. The research aims to contribute to the discussion on the readiness of journalism curricula to cope with technological advancements by analyzing the Spanish case.
Consumer Safety and Pesticide Residues: Evaluating Mitigation Protocols for Greengrocery
Authors: Popescu (Stegarus) Diana Ionela , Oprita (Cioara) Corina Mihaela , Tamaian Radu , Niculescu Violeta-Carolina
Published: November 2024

The application of pesticides remains a necessary measure for pest management in agriculture, particularly in the cultivation of fruits and vegetables. After harvest, the presence of pesticide residues in greengrocery (fruits and vegetables) is significantly influenced by various factors, including storage conditions, handling practices, and subsequent processing methods. The mitigation of these residues to levels compliant with regulated maximum thresholds ensures the safety of raw and processed fruits and vegetables for consumption. A contemporary survey of pesticide residues in greengrocery has gathered considerable attention from consumers, driven by concerns over the potential health risk of pesticide exposure. Consequently, consumers want to be extensively informed about household processing techniques to minimize associated risks. Meanwhile, a critical question arises: does household processing effectively eliminate pesticide residues? A comprehensive review of the literature reveals that conventional methods, such as washing and soaking, offer only limited reduction in residue levels, while emerging treatments, suitable both at household and industrial scale, demonstrate increased efficiency in residues mitigation. This study aims to emphasise the ubiquitous use of pesticides in crop cultivation while providing recommendations for the implementation of efficient treatment protocols to address residue concerns. Following upon available evidence and database mining, the worldwide purpose must be to outline agriculturally and economically viable strategies that prioritize both the health and safety of consumers, as well as the green cultivation and processing of fruits and vegetables.
The Impact of Enterprise Digital Capability on Supply Chain Digitalization—From the Perspective of Supply Chain Cooperation
Authors: Chen Sijie , Tang Zhaobo
Published: November 2024

This paper explores in depth the mechanism of enterprise digital capability effects in supply chain digital development by reconstructing the supply chain cooperation capabilities (digital diffusion capability and digital collaborative capability). We use the questionnaire data covering 272 Chinese manufacturing enterprises and apply a structural equation model to test the hypothesis. The empirical result demonstrates that enterprise digital capability does not directly have a significant impact on supply chain digitalization, and the supply chain cooperation capabilities play a mediating role between an enterprise’s digital capability and supply chain digitalization. The results are robust as we thoroughly consider the direction of enterprise capabilities and verify the systematic requirements of supply chain digitalization and the high order of enterprise digital capability. These provide a theoretical basis for enterprises to promote the digital transformation of their supply chain through digital technology.
Methods for Extracting Fractional Vegetation Cover from Differentiated Scenarios Based on Unmanned Aerial Vehicle Imagery
Authors: Sun Changning , Ma Yonggang , Pan Heng , Wang Qingxue , Guo Jiali , Li Na , Ran Hong
Published: November 2024

Fractional vegetation cover (FVC) plays a key role in ecological and environmental status assessment because it directly reflects the extent of vegetation cover and its status, yet vegetation is an important component of ecosystems. FVC estimation methods have evolved from traditional manual interpretation to advanced remote sensing technologies, such as satellite data analysis and unmanned aerial vehicle (UAV) image processing. Extraction methods based on high-resolution UAV data are being increasingly studied in the fields of ecology and remote sensing. However, research on UAV-based FVC extraction against the backdrop of the high soil reflectance in arid regions remains scarce. In this paper, based on 12 UAV visible light images in differentiated scenarios in the Ebinur Lake basin, Xinjiang, China, various methods are used for high-precision FVC estimation: Otsu’s thresholding method combined with 12 Visible Vegetation Indices (abbreviated as Otsu-VVIs) (excess green index, excess red index, excess red minus green index, normalized green–red difference index, normalized green–blue difference index, red–green ratio index, color index of vegetation extraction, visible-band-modified soil-adjusted vegetation index, excess green minus red index, modified green–red vegetation index, red–green–blue vegetation index, visible-band difference vegetation index), color space method (red, green, blue, hue, saturation, value, lightness, ‘a’ (Green–Red component), and ‘b’ (Blue–Yellow component)), linear mixing model (LMM), and two machine learning algorithms (a support vector machine and a neural network). The results show that the following methods exhibit high accuracy in FVC extraction across differentiated scenarios: Otsu–CIVE, color space method (‘a’: Green–Red component), LMM, and SVM (Accuracy > 0.75, Precision > 0.8, kappa coefficient > 0.6). Nonetheless, higher scene complexity and image entropy reduce the applicability of precise FVC extraction methods. This study facilitates accurate, efficient extraction of vegetation information in differentiated scenarios within arid and semiarid regions, providing key technical references for FVC estimation in similar arid areas.
Terrain Analysis According to Multiscale Surface Roughness in the Taklimakan Desert
Authors: Trevisani Sebastiano , Guth Peter L.
Published: November 2024

Surface roughness, interpreted in the wide sense of surface texture, is a generic term referring to a variety of aspects and scales of spatial variability of surfaces. The analysis of solid earth surface roughness is useful for understanding, characterizing, and monitoring geomorphic factors at multiple spatiotemporal scales. The different geomorphic features characterizing a landscape exhibit specific characteristics and scales of surface texture. The capability to selectively analyze specific roughness metrics at multiple spatial scales represents a key tool in geomorphometric analysis. This research presents a simplified geostatistical approach for the multiscale analysis of surface roughness, or of image texture in the case of images, that is highly informative and interpretable. The implemented approach is able to describe two main aspects of short-range surface roughness: omnidirectional roughness and roughness anisotropy. Adopting simple upscaling approaches, it is possible to perform a multiscale analysis of roughness. An overview of the information extraction potential of the approach is shown for the analysis of a portion of the Taklimakan desert (China) using a 30 m resolution DEM derived from the Copernicus Glo-30 DSM. The multiscale roughness indexes are used as input features for unsupervised and supervised learning tasks. The approach can be refined both from the perspective of the multiscale analysis as well as in relation to the surface roughness indexes considered. However, even in its present, simplified form, it can find direct applications in relation to multiple contexts and research topics.
Synthesis of 1,2,4-Oxadiazoles Based on Diffractaic Acid
Authors: Filimonov Aleksandr , Diveikina Anastasia , Gatilov Yuri , Luzina Olga , Salakhutdinov Nariman
Published: November 2024

Diffractic acid 1 is a secondary metabolite of depside lichens with antibacterial and insecticidal properties, and anticancer, hepatoprotective and antiviral activities. Novel diffractaic acid derivatives containing a 1,2,4-oxadiazole ring with an aryl substituent have been synthesized by the reaction of diffractaic acid with amidoximes.
Dichloro-bis[(Z)-1-styryl-benzimidazole]-zinc(II)
Authors: Şahin Neslihan , Özdemir İsmail , Sémeril David
Published: November 2024

We have successfully synthesized the dichloro-bis[(Z)-1-styryl-benzimidazole]-zinc(II) complex, which was fully characterized by IR, elemental analysis, and mass and NMR spectroscopy. The solid-state structure definitively shows that two benzimidazole moieties are coordinated to the zinc atom, which adopts a tetrahedral geometry.
Comprehensive Analysis of Major Fault-to-Failure Mechanisms in Harmonic Drives
Authors: Guida Roberto , Bertolino Antonio Carlo , De Martin Andrea , Sorli Massimo
Published: November 2024

The present paper proposes a detailed Failure Mode, Effects, and Criticality Analysis (FMECA) on harmonic drives, focusing on their integration within the UR5 cobot. While harmonic drives are crucial for precision and efficiency in robotic manipulators, they are also prone to several failure modes that may affect the overall reliability of a system. This work provides a comprehensive analysis intended as a benchmark for advancements in predictive maintenance and condition-based monitoring. The results not only offer insights into improving the operational lifespan of harmonic drives, but also provide guidance for engineers working with similar systems across various robotic platforms. Robotic systems have advanced significantly; however, maintaining their reliability is essential, especially in industrial applications where even minor faults can lead to costly downtimes. This article examines the impact of harmonic drive degradation on industrial robots, with a focus on collaborative robotic arms. Condition-Based Maintenance (CBM) and Prognostics and Health Management (PHM) approaches are discussed, highlighting how digital twins and data-driven models can enhance fault detection. A case study using the UR5 collaborative robot illustrates the importance of fault diagnosis in harmonic drives. The analysis of fault-to-failure mechanisms, including wear, pitting, and crack propagation, shows how early detection strategies, such as vibration analysis and proactive maintenance approaches, can improve system reliability. The findings offer insights into failure mode identification, criticality analysis, and recommendations for improving fault tolerance in robotic systems.
Targeting Bacterial Communication: Evaluating Phytochemicals as LuxS Inhibitors to Disrupt Quorum Sensing
Authors: Sarigiannis Yiannis , Papaneophytou Christos
Published: November 2024

Bacterial quorum sensing (QS) is a critical communication process that regulates gene expression in response to population density, influencing activities such as biofilm formation, virulence, and antibiotic resistance. This study investigates the inhibitory effects of five phytochemicals—apigenin, carnosol, chlorogenic acid, quercetin, and rosmarinic acid—on the S-ribosylhomocysteinase (LuxS) enzyme, a key player in AI-2 signaling across both Gram-positive and Gram-negative bacteria. Using molecular docking studies, we identified that these phytochemicals interact with the LuxS enzyme, with apigenin, carnosol, chlorogenic acid, and rosmarinic acid binding within the substrate-binding pocket and exhibiting binding scores below −7.0 kcal/mol. Subsequent in vitro assays demonstrated that these compounds inhibited AI-2 signaling and biofilm formation in Escherichia coli MG1655 in a concentration-dependent manner. Notably, carnosol and chlorogenic acid showed the most potent effects, with IC50 values of approximately 60 μM. These findings suggest that these phytochemicals may serve as potential QS inhibitors, providing a foundation for developing new anti-pathogenic agents to combat bacterial infections without promoting antibiotic resistance. Further studies are warranted to explore the therapeutic applications of these compounds in both clinical and agricultural settings.
Stability of Noncentrosymmetric Square Skyrmion Crystals with Easy-Axis and Easy-Plane Magnetic Anisotropy
Authors: Hayami Satoru
Published: November 2024

We investigate the stability tendency of a magnetic skyrmion crystal in noncentrosymmetric tetragonal systems with the Dzyaloshinskii–Moriya interaction. We show that the stability region of the square skyrmion crystal on a square lattice depends on the Ising-type magnetic anisotropic interaction by performing the simulated annealing for the spin model. The easy-axis anisotropic interaction tends to narrow the region where the square skyrmion crystal is stabilized when the magnetic field is applied in the out-of-plane direction. In contrast, the easy-plane anisotropic interaction tends to enlarge the stability region. Meanwhile, the square skyrmion crystal induced by the easy-axis anisotropic interaction is robust compared with that induced by the easy-plane anisotropic interaction when the magnetic field is tilted from the out-of-plane to the in-plane direction. The results indicate that the instability toward the square skyrmion crystal in noncentrosymmetric crystals is sensitive to both magnetic anisotropy and magnetic fields.