bluuebunny/crossref_metadata_2025 huggingface dataset:
Amelioration of Toll-like Receptor-4 Signaling and Promotion of Mitochondrial Function by Mature Silkworm Extracts in Ex Vivo and in Vitro Macrophages
Authors: Phan Trinh Yen Binh , Jang Byungki , Kang Sang-Kuk , Seo Jongbok , Kim Seong-Ryul , Kim Kee-Young , Koh Young Ho
Published: November 2024

Objectives: The unknown immune-enhancing effects of steamed mature silkworms (Bombyx mori L.), known as HongJam (HJ), were investigated. Methods: Supercritical fluid extracts from the White Jade variety of HJ (WJ-SCEs) were applied to in vitro RAW264.7 macrophages (RAWMs) and ex vivo bone marrow-derived macrophages (BMDMs). Results: WJ-SCE enhanced the proliferation and viability of both RAWMs and BMDMs. Supplementation with WJ-SCE significantly reduced the lipopolysaccharide (LPS)-induced expression of iNOS mRNA and protein, resulting in decreased nitric oxide (NO) production. Additionally, WJ-SCE lowered the mRNA and protein expression of COX-2 and reduced the levels of pro-inflammatory cytokines. The mitochondrial function, ATP levels, and reactive oxygen species levels in LPS-treated macrophages were restored following WJ-SCE treatment. WJ-SCE modulated LPS-Toll-like receptor-4 (TLR-4) signaling by reducing the levels of phosphorylated (p)-p38, p-ERK1/2, and p-p65. WJ-SCE also restored gene expression related to cytokines, chemokines, glucose transport, mitochondrial metabolism, and TLR-4 signaling, suggesting the inhibition of pro-inflammatory M1 macrophage polarization. Furthermore, WJ-SCE enhanced macrophage phagocytic and pinocytotic activity. Conclusions: WJ-SCE demonstrated anti-inflammatory effects by inhibiting LPS-induced M1 polarization in both macrophage types, potentially suppressing chronic inflammation while enhancing phagocytosis and pinocytosis.
Vitamin D Is Associated with Lipid Metabolism: A Sex- and Age-Dependent Analysis of a Large Outpatient Cohort
Authors: Li Xitong , Liu Yvonne , Wang Jingyun , Chen Xin , Reichetzeder Christoph , Elitok Saban , Krämer Bernhard K. , Doebis Cornelia , Huesker Katrin , von Baehr Volker , Hocher Berthold
Published: November 2024

Background: Vitamin D is a fat-soluble steroid that influences cardiovascular health by affecting lipid metabolism. Since dyslipidemia is a key risk factor for cardiovascular disease (CVD), our study aimed to explore the relationship between vitamin D levels and lipid parameters, considering the effects of age and gender. Methods: In this cross-sectional study of 47,778 outpatients, we analyzed correlations between two forms of vitamin D—25-hydroxyvitamin D (25(OH)D) and 1,25-dihydroxyvitamin D (1,25(OH)2D)—and lipid parameters, including low-density lipoprotein (LDL), high-density lipoprotein (HDL), and total cholesterol (TC). Subgroup analyses by age and gender provided additional insights. Results: Results showed that 25(OH)D levels were negatively correlated with LDL and TC across the cohort. This association was particularly evident in men over 50, whereas women showed a positive correlation with LDL and TC before age 50 and a negative correlation after. HDL levels positively correlated with 25(OH)D across all age groups, with the strongest association in postmenopausal women. In contrast, 1,25(OH)2D showed a positive correlation only with HDL in individuals over 50, with no significant correlation with LDL or TC in any age group. Conclusions: In conclusion, findings from this cross-sectional study underscore an association between elevated levels of 25(OH)D and more favorable lipid profiles, characterized by reduced LDL and total cholesterol, as well as increased HDL levels. This association is particularly pronounced among individuals over 50 years of age and postmenopausal women.
Associations Between Body Appreciation, Body Weight, Lifestyle Factors and Subjective Health Among Bachelor Students in Lithuania and Poland: Cross-Sectional Study
Authors: Kriaučionienė Vilma , Gajewska Danuta , Raskilienė Asta , Myszkowska-Ryciak Joanna , Ponichter Julia , Paulauskienė Lina , Petkevičienė Janina
Published: November 2024

Background/Objectives: Positive body image is linked to improved mental and physical well-being, healthier lifestyles, and fewer unhealthy weight control behaviors. Cultural factors also play a role in influencing body appreciation. This study investigated the associations between body appreciation, body weight, lifestyle factors, and subjective health among bachelor’s students in Lithuania and Poland. Methods: A cross-sectional online survey was conducted with 1290 students from universities in both countries. The Body Appreciation Scale-2 (BAS-2) measured body appreciation, while participants provided self-reported data on their dietary habits, physical activity, sleep, health perceptions, and body weight and height. Linear regression models explored associations between BAS-2 scores, actual and perceived body weight, lifestyle habits, and subjective health. Results: Gender and country-based differences in body appreciation were observed. Lithuanian female students reported a higher median BAS score of 33 compared to 32 among Polish female students (p = 0.02), despite having a higher median BMI (22.3 kg/m2 vs. 21.1 kg/m2, p = 0.001). Positive body appreciation was linked to healthier dietary behaviors, such as higher consumption of fruits, vegetables, fish, and regular breakfasts. Additionally, greater physical activity and sufficient sleep were associated with higher body appreciation, while higher intake of sweets, sugary drinks, and fast food correlated with lower BAS-2 scores. Both BMI and perceived weight were negatively associated with body appreciation, particularly among females. Conclusions: Body appreciation is closely linked to body weight, healthier lifestyle, and positive health perceptions, suggesting that promoting healthier habits may improve body appreciation.
Characterization of the Gut and Skin Microbiome over Time in Young Children with IgE-Mediated Food Allergy
Authors: Roth Michèle S. , d’Aujourd’hui Muriel , Künstner Axel , Hirose Misa , Olbrich Michael , Ibrahim Saleh , Hartmann Karin , Roduit Caroline , Busch Hauke , Bellutti Enders Felicitas
Published: November 2024

Background/Objectives: The prevalence of food allergy (FA) in children is increasing. Dysbiosis of the microbiome has been linked to FA but needs to be better understood. We aimed to characterize the gut and skin microbiome of young food-allergic children over time and within different types of immunoglobulin E (IgE)-mediated FA. Methods: We studied 23 patients, as a pilot study of an ongoing prospective multicenter cohort study including children < 2y with newly diagnosed IgE-mediated FA. Samples (feces/skin swabs) were collected at enrollment and at 1-year follow-up and sequenced for the bacterial 16S rRNA gene (hypervariable v1–v2 region). Results: Gut and skin bacterial diversity was significantly higher in patients compared with controls and increased over time (beta test, Shannon diversity, p < 0.01). Within different types of IgE-mediated FA, bacterial diversity was similar. Community composition differed significantly over time and within IgE-mediated FA types (PERMANOVA: p < 0.01). Several significantly different genus abundances were revealed. We observed a positive correlation between high total IgE and a high abundance of the genus Collinsella in patients with a higher number of allergies/sensitizations (≥3), and patients with tree nut and/or peanut allergy. Conclusions: This study revealed an increased bacterial diversity in children with FA compared with non-atopic children. Importantly, the gut and skin microbiome differed in their composition over time and within different types of IgE-mediated FA. These findings contribute to the understanding of microbiome changes in children with FA and indicate the potential of the genus Collinsella as a biomarker for tree nut and/or peanut allergy and possibly for allergy persistence.
Impact of Genetic Polymorphisms on Electrochemical Parameters and Acid-Base Disorders in Brazilian Runners During a 105-Kilometer Ultramarathon
Authors: Ribas Marcelo Romanovitch , Schneider Fábio Kurt , Ribas Danieli Isabel Romanovitch , Badicu Georgian , Bonatto Ana Claudia , Ardigò Luca Paolo , Bassan Júlio Cesar
Published: November 2024

Background/Objectives: This study focused on a group of 22 elite male mountain runners from Brazil (average age of 35.9 ± 6.5 years) with the objective of exploring the possible roles of the ACTN3 R577X, ACE I/D, and CK MM A/G NcoI genetic variants in shaping electrochemical profiles and maintaining acid-base homeostasis during a 105-km ultramarathon. Methods: Genotyping for each polymorphism (ACTN3: RR, RX, XX; ACE: DD, ID, II; CK MM: AA, AG, GG) was conducted using PCR-RFLP (Polymerase Chain Reaction-Restriction Fragment Length Polymorphism), and saliva samples were used to obtain DNA. Analyses of electrochemical and acid-base disturbances were performed in real time. Results: It was observed that athletes who completed the race in less time had lower calcium concentrations (Rs = 0.35; p = 0.016). Pre-race, the RX genotype showed a 14.19% reduction in potassium levels compared to RR (p = 0.01). The GG genotype showed potassium levels 19.36% higher than AA (p = 0.01) and a 6.11% increase in hematocrit values compared to AA (p = 0.03). Additionally, the AG genotype exhibited hematocrit values 5.44% higher than AA (p = 0.03). Post-race, the XX genotype demonstrated higher hematocrit values compared to RX, with an increase of 8.92% (p = 0.03). The II genotype showed a 0.27% increase in pH compared to ID (p = 0.02) and a 20.42% reduction in carbon dioxide levels (p = 0.01). Conclusions: The findings emphasize the impact of the examined polymorphisms on the modulation of electrochemical factors and the maintenance of acid-base equilibrium in athletes during 105 km ultramarathons.
A Combined Extract Derived from Black Sticky Rice and Dill Improves Clinical Symptoms and Ischemic Stroke Biomarkers in Transient Ischemic Attack and Ischemic Stroke Patients
Authors: Kongbunkiat Kannikar , Thukham-mee Wipawee , Tiamkao Somsak , Kasemsap Narongrit , Vorasoot Nisa , Wattanathorn Jintanaporn
Published: November 2024

Currently, the adjuvant therapy to optimize the restorative process after stroke is required due to the unsatisfied therapeutic efficacy. A combined extract of black sticky rice and dill showed potential in the preclinical state, so we hypothesized that it could provide clinical benefits. A three-arm, randomized, placebo-controlled study was set up to elucidate this issue. Both males and females (18–80 years old) who had experienced transient ischemic attacks or ischemic strokes within the last 5–10 days with an NIHSS score ≤ 7 and received standard treatment were randomly assigned to receive either a placebo or capsule containing a combined extract of black sticky rice and dill at a dose of 600 or 1200 mg per day. The safety parameters, movement control, and degree of disability were assessed 1, 2, and 6 weeks after the intervention, and serum stroke biomarkers were assessed at the mentioned time points, except at 2 weeks. After week 1, the high-dose (1200 mg/day) treatment group had improved NIHSSS, VCAM1, and MMP-9. Both S100β and VCAM1 also improved at week 6, while the low-dose treatment group (600 mg/day) only exhibited improved VCAM1. Therefore, a high dose of the developed adjuvant supplement improves stroke recovery by improving motor impairment by reducing endothelial dysfunction and inflammation.
Effect of Postbiotic Bifidobacterium longum CECT 7347 on Gastrointestinal Symptoms, Serum Biochemistry, and Intestinal Microbiota in Healthy Adults: A Randomised, Parallel, Double-Blind, Placebo-Controlled Pilot Study
Authors: Naghibi Malwina , Pont-Beltran Adria , Lamelas Araceli , Llobregat Laura , Martinez-Blanch Juan , Rojas Antonia , Álvarez Beatriz , López Plaza Bricia , Arcos Castellanos Lucia , Chenoll Empar , Vijayakumar Vineetha , Day Richard
Published: November 2024

Objectives: A randomised, double-blind, placebo-controlled pilot trial was conducted to assess the effect of heat-treated Bifidobacterium longum CECT 7347 (HT-ES1) in healthy adults with mild to moderate digestive symptoms. A total of 60 participants were recruited and received either HT-ES1 or an identical placebo for 8 weeks with a further follow-up at week 10. Methods: This study monitored changes in the total Gastrointestinal Symptom Rating Scale for IBS score (GSRS-IBS), Irritable Bowel Syndrome Symptom Severity Scale (IBS-SSS), IBS Quality of Life index (IBS-QoL), gut microbiome using 16S rRNA sequencing, and the Visceral Sensitivity Index, as well as a range of biochemical markers, anthropometric parameters, and adverse events. Results: While minimal changes were observed in gastrointestinal (GI) symptoms, the HT-ES1 group showed a significant decrease in total and non-HDL cholesterol compared to the placebo. The intervention group also exhibited a significant increase in the abundance of the genera Faecalibacterium and Anaerobutyricum, both of which were positively correlated with butyrate concentrations. Faecal calprotectin significantly increased over time in the placebo group but remained stable in the HT-ES1 group. Conclusions: Overall, these findings suggest that HT-ES1 may promote gut health by increasing butyrate-producing bacteria in the gut, maintaining normal levels of faecal calprotectin and reducing serum cholesterol.
Anti-Inflammatory Effects of Honeysuckle Leaf Against Lipopolysaccharide-Induced Neuroinflammation on BV2 Microglia
Authors: Kweon Bitna , Oh Jinyoung , Lim Yebin , Noh Gyeongran , Yu Jihyun , Kim Donggu , Jang Mikyung , Kim Donguk , Bae Gisang
Published: November 2024

Background/Objectives: Neurodegenerative disorders have emerged as a major global public health concern, and the burden is predicted to increase over time. Modulating neuroinflammation and microglial activity is considered a promising target for improving neurodegenerative disorders. The leaf of honeysuckle (LH), which has anti-inflammatory properties, has long been collected, regardless of the season, and used for medicinal purposes. However, research on its effects on neuroinflammation is scarce. In this study, we determined the neuroprotective effects of LH water extract by inhibiting microglial activation induced by lipopolysaccharide (LPS). Methods: The production or secretion of pro-inflammatory mediators was examined in LPS-exposed BV2 cells to ascertain the efficacy of LH water extract in improving neuroinflammation. In addition, the phosphorylation of mitogen-activated protein kinases (MAPKs) and the degradation of inhibitory κBα (IκBα) were analyzed to elucidate the regulatory mechanisms of LH water extract. Ultra-performance liquid chromatography (UPLC) analysis was conducted to identify the active component of the LH. Results: LH water extract suppressed the formation of inducible nitric oxide synthase (iNOS), nitric oxide (NO), and pro-inflammatory cytokines, including interleukin (IL)-1β and tumor necrosis factor (TNF)-α, in LPS-activated BV2 cells. LH impeded the activation of c-Jun N-terminal kinase (JNK). Moreover, chlorogenic acid was found in LH. Conclusions: The above findings suggest that LH water extract could improve neuroinflammation.
Effect of Intermittent Fasting on Immune Parameters and Intestinal Inflammation
Authors: Haasis Eva , Bettenburg Anna , Lorentz Axel
Published: November 2024

Intermittent fasting (IF), including alternate day fasting (ADF) and time-restricted feeding (TRF) or, in humans, time-restricted eating (TRE), has been associated with the prevention and improvement of diseases, including inflammatory bowel disease (IBD). This review summarizes 20 animal and human studies on the influence of IF on intestinal inflammation. In the animal studies, TRF and ADF improved histological scores, inflammatory markers, markers of oxidative stress, and microbiota composition. Apart from the studies on Ramadan fasting, there are no studies on IF in IBD patients, so human studies on IF in healthy people were included. The studies on Ramadan fasting showed almost no effects, but this particular type of fasting is not directly comparable to TRE or ADF. However, TRE and ADF appear to have anti-inflammatory effects in healthy individuals, as they significantly reduce CRP levels and inflammatory markers. TRE also improved the composition of microbiota and the circadian oscillation of clock genes. The beneficial effects of TRE and ADF in healthy people appear to depend on the number of uninterrupted days of fasting, while in animal studies improvements in colitis have been observed regardless of the duration of fasting.
The Leishmania Skin Test Predicts Clinic-Immunologic and Therapeutic Outcomes in Cutaneous Leishmaniasis
Authors: Guimarães Luiz H. , Zacarias Evelyn , Nolasco Sandra T. , Filho Almério N. , Lago Jamile , Machado Paulo R. L. , Oliveira Joyce , Carvalho Lucas P. , Carvalho Augusto , Carvalho Edgar M. , Arruda Sérgio
Published: November 2024

Cutaneous leishmaniasis (CL), caused by Leishmania braziliensis, is closely associated with a severe form of the disease, indicated by a positive Leishmania skin test (LST) that assesses and reflects the presence of immune T cells specific to Leishmania antigens. In this study, we compare the clinical, immunologic, and histopathologic features between Leishmania skin test-positive (LST+) and Leishmania skin test-negative (LST-) in CL. Compared to LST+ patients, LST- patients had larger lesions and had been sicker for longer, presented with more instances of therapeutic failure with meglumine antimonate, (MA) and the healing times were higher than LST+. While granulomas were less frequent and the parasite load was higher in LST-, there were more CD8+ T cells and an enhanced production of Granzyme B in the supernatants of biopsies from LST- subjects. This study shows that in LST-, an impairment in Th1 immune response is associated with a high parasite burden, and the pathology is mediated by CD8+ T cells and the enhanced production of Granzyme B. The abnormalities in the immunologic response in LST- patients lead to a more severe disease with a high rate of failure to therapy.
Artificial Intelligence and Machine Learning Models for Predicting Drug-Induced Kidney Injury in Small Molecules
Authors: Rao Mohan , Nassiri Vahid , Srivastava Sanjay , Yang Amy , Brar Satjit , McDuffie Eric , Sachs Clifford
Published: November 2024

Background/Objectives: Drug-Induced Kidney Injury (DIKI) presents a significant challenge in drug development, often leading to clinical-stage failures. The early prediction of DIKI risk can improve drug safety and development efficiency. Existing models tend to focus on physicochemical properties alone, often overlooking drug–target interactions crucial for DIKI. This study introduces an AI/ML (artificial intelligence/machine learning) model that integrates both physicochemical properties and off-target interactions to enhance DIKI prediction. Methods: We compiled a dataset of 360 FDA-classified compounds (231 non-nephrotoxic and 129 nephrotoxic) and predicted 6064 off-target interactions, 59% of which were validated in vitro. We also calculated 55 physicochemical properties for these compounds. Machine learning (ML) models were developed using four algorithms: Ridge Logistic Regression (RLR), Support Vector Machine (SVM), Random Forest (RF), and Neural Network (NN). These models were then combined into an ensemble model for enhanced performance. Results: The ensemble model achieved an ROC-AUC of 0.86, with a sensitivity and specificity of 0.79 and 0.78, respectively. The key predictive features included 38 off-target interactions and physicochemical properties such as the number of metabolites, polar surface area (PSA), pKa, and fraction of Sp3-hybridized carbons (fsp3). These features effectively distinguished DIKI from non-DIKI compounds. Conclusions: The integrated model, which combines both physicochemical properties and off-target interaction data, significantly improved DIKI prediction accuracy compared to models that rely on either data type alone. This AI/ML model provides a promising early screening tool for identifying compounds with lower DIKI risk, facilitating safer drug development.
Zingiber officinale Uncovered: Integrating Experimental and Computational Approaches to Antibacterial and Phytochemical Profiling
Authors: Sulieman Abdel Moneim Elhadi , Ibrahim Safa Mustafa , Alshammari Mamdouh , Abdulaziz Fahad , Idriss Hajo , Alanazi Naimah Asid H. , Abdallah Emad M. , Siddiqui Arif Jamal , Shommo Sohair A. M. , Jamal Arshad , Badraoui Riadh
Published: November 2024

Background: Zingiber officinale rhizome is widely cultivated in the central region of Sudan (Gezira) and data on the biological properties of this variety grown in Sudan’s climate are scarce. This study aims to comprehensively analyze the antibacterial, antioxidant, phytochemical, and GC-MS properties of Zingiber officinale (ginger rhizome) to explore its potential applications. Methods and Results: The in vitro antibacterial assessment of the aqueous extract of Sudanese ginger revealed moderate activity against Staphylococcus aureus, Salmonella typhi, Pseudomonas aeruginosa, Escherichia coli, and Klebsiella pneumonia, as determined by the disc diffusion method. The inhibition zones ranged from 12.87 ± 0.11 mm to 14.5 ± 0.12 mm at 30 µg/disc. The minimum inhibitory concentration ranged from 6.25 to 25 µg/mL, while the MBC ranged from 25 to 50 µg/mL. The MBC/MIC exhibited a bactericidal effect against all tested bacteria. Phytochemical screening revealed the presence of various chemical constituents, such as saponins, flavonoids, glycosides, alkaloids, steroids, terpenoids, and the absence of tannins in Sudanese ginger rhizome. Furthermore, GC-MS analysis of ginger rhizome identified 22 chemical compounds with retention times ranging from 7.564 to 17.023 min. The identification of 22 chemical compounds through GC-MS analysis further underscores the prospect of harnessing ginger rhizome for the development of novel medications. Computational analyses showed that ginger compounds bind the Protein Data Bank (PDB) codes 1JIJ and 2QZW with high binding affinities, reaching −9.5 kcal/mol. Ginger compounds also established promising molecular interactions with some key residues, satisfactorily explaining the in vitro results and supporting the pharmacokinetic and experimental findings. Conclusions: This study lays the groundwork for future research and pharmaceutical exploration aimed at harnessing the beneficial properties of ginger rhizome for medicinal and therapeutic purposes, particularly its antimicrobial potential.
GC–MS Characterization and Bioactivity Study of Eucalyptus globulus Labill. (Myrtaceae) Essential Oils and Their Fractions: Antibacterial and Antioxidant Properties and Molecular Docking Modeling
Authors: Ait benlabchir Abdessamad , Fikri-Benbrahim Kawtar , Moutawalli Amina , Alanazi Mohammed M. , Halmoune Asma , Benkhouili Fatima Zahra , Oubihi Asmaa , Kabra Atul , Hanoune Elbatoul , Assila Hamza , Ouaritini Zineb Benziane
Published: November 2024

Background/Objectives: Eucalyptus globulus is a medicinal plant extensively used by the Moroccan population for treating a range of illnesses, especially respiratory conditions. Methods: This study aimed to assess the antioxidant and antibacterial properties of E. globulus essential oil and its individual fractions (F1, F2, and F3). Antioxidant activity was evaluated through iron-reducing power, 2,2′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS), and 2,2-diphenyl-1-picrylhydrazyl (DPPH) assays. Antibacterial activity was tested using disk diffusion and dilution methods, supported by molecular docking studies. Furthermore, GC–MS analysis was conducted on the essential oil and its individual fractions. Results: GC–MS analysis identified the major compounds in the essential oil and its fractions as eucalyptol (62.32–42.60%), globulol (5.9–26.24%), o-cymene (6.89–24.35%), cryptone (7.10–15.95%), terpinen-4-ol (2.43–15.24%), and α-pinene (2.46–7.89%). Fraction F3 displayed the highest antioxidant activity in DPPH (IC50 = 3.329 ± 0.054 mg/mL) and ABTS assays (IC50 = 3.721 ± 0.027 mg/mL), while fraction F2 was most effective in the FRAP assay (IC50 = 1.054 ± 0.008 mg/mL). The essential oil and its fractions also showed antibacterial activity against Staphylococcus aureus, Staphylococcus epidermidis, Klebsiella pneumoniae, Enterobacter cloacae, Escherichia coli, and Acinetobacter baumannii. Molecular docking further corroborated these findings, supporting both antioxidant and antibacterial activities. Conclusions: The present findings demonstrate the antioxidant and antimicrobial properties of Eucalyptus globulus essential oil and its fractions, underscoring the need for further research to confirm their medicinal potential and explore pharmaceutical applications.
Threshold Behavior Hidden in the Growth Response of Peat Moss Sphagnum riparium to Temperature
Authors: Mironov Victor L.
Published: November 2024

The balance between photosynthetic carbon accumulation and respiratory loss in plants varies depending on temperature. This leads to a situation where the increased need for carbon is not met when a certain temperature threshold is reached. Over the last two decades, temperature thresholds in carbon metabolism in autotrophic systems have been widely studied. However, it remains unclear how these thresholds manifest themselves in the natural growth of individual plant species. To address this issue, we used data from an extensive monitoring of the growth of peat moss Sphagnum riparium over 9 years in mires in Karelia (Russia). We measured the growth of shoots in sample plots and obtained 1609 estimates of growth rates during the monitoring period. Investigating the relationship between growth rate and temperature, we identified two distinct intervals in response to temperature. These two intervals are separated by the temperature threshold of 13.2 °C. The first interval, which covers 42% of the growing season, exhibits a strong exponential dependence of growth rate on temperature, with a coefficient Q10 = 4.01. This indicates that growth is most sensitive to changes in temperature within this range. In contrast, the second interval (58% of the growing season) shows a weaker dependence, with a Q10 coefficient of 1.21, suggesting that growth is less responsive to changes within this temperature range. The temperature threshold was found to be negatively related to May (r = −0.76; p = 0.018) and September (r = −0.78; p = 0.012) temperatures of the previous growing season, and together they best explain (r = −0.91; p = 0.0007) the temperature threshold. Overall, our findings suggest that the temperature threshold does exist in the growth of S. riparium and can be identified in different years. The negative correlation between temperature threshold and May and September temperatures from the previous year indicates that intervals in the growing season with temperatures near the temperature threshold have an impact on subsequent carbon balance and are particularly significant for the further growth and development of Sphagnum mosses.
Genome-Wide Identification and Stress Responses of Cowpea Thaumatin-like Proteins: A Comprehensive Analysis
Authors: Jesús-Pires Carolline de , Ferreira-Neto José Ribamar Costa , Oliveira-Silva Roberta Lane de , Silva Jéssica Barboza da , Silva Manassés Daniel da , Costa Antônio Félix da , Benko-Iseppon Ana Maria
Published: November 2024

Cowpea (Vigna unguiculata (L.) Walp.) is an important legume cultivated mainly in regions with limited water availability across the African and American continents. Its productivity is significantly affected by environmental stresses. Thaumatin-like proteins (TLPs), which belong to the PR-5 (pathogenesis-related 5) protein family, are known to be responsive to both biotic and abiotic stresses. However, their role remains controversial, with some TLPs associated with plant defense (particularly against fungal infections) and others associated with abiotic stresses response. In this study, we evaluated the structural diversity and gene expression of TLPs in cowpea (VuTLPs) under different stress conditions, including biotic [mechanical injury followed by inoculation with Cowpea Aphid-borne Mosaic Virus (CABMV) or Cowpea Severe Mosaic Virus (CPSMV)] and abiotic (root dehydration). Genomic anchoring of VuTLPs revealed 34 loci encoding these proteins. Neighbor- joining analysis clustered the VuTLPs into three distinct groups. We identified 15 segmental duplication and 6 tandem duplication gene pairs, with the majority of VuTLP genes found to be under purifying selection. Promoter analysis associated VuTLPs with bHLH, Dof-type, and MYB- related transcription factors, supporting their diverse roles. Diversity in VuTLP function was also observed in their expression profiles under the studied stress conditions. Gene expression data showed that most VuTLPs are recruited within the first minutes after biotic stress imposition. For the root dehydration assay, the most transcripts were up-regulated 150 min post-stress. Moreover, the gene expression data suggested that VuTLPs exhibit functional specialization depending on the stress condition, highlighting their diverse roles and biotechnological potential.
Modeling of Spiral Wound Membranes for Gas Separations—Part IV: Real-Time Monitoring Based on Detailed Phenomenological Model
Authors: Sá Marília Caroline C. de , Menezes Diego Q. F. de , Fontoura Tahyná B. , Campos Luiz Felipe de O. , Anzai Thiago K. , Diehl Fábio C. , Thompson Pedro H. , Pinto José Carlos
Published: November 2024

The present study presents, for the first time, the real-time monitoring of an actual spiral-wound membrane unit used for CO2 removal from natural gas in an actual industrial offshore platform, utilizing a detailed phenomenological model. An Object-Oriented Programming (OOP) paradigm was employed to simulate the offshore membrane separation unit, accounting for the diverse levels of the membrane separation setup. A parameter estimation procedure was implemented to fit the phenomenological model to the real industrial data in real-time, for the first time. In addition, estimated permeance parameters and calculated unmeasured variables (soft sensor) were used for monitoring Key Performance Indicators (KPIs), such as membrane selectivity, dew point temperature, and hydrocarbon loss. Finally, a reparametrization of the parameters was implemented to improve the robustness of the optimization procedure. Thus, the model variables presented good adjustments to the data, indicating the satisfactory performance of the estimation. Consequently, the good accuracy of the model provided reliable information to the soft sensors and KPIs.
Effects of L-Aspartic Acid on Cr(VI) Adsorption onto the Lepidocrocite with Different Exposed Facets: Batch Experiments and In Situ ATR-FTIR Analysis
Authors: Li Xiaofei , Li Tianfu , Jin Xiaohu , Wei Yanfu , Bao Yanping , Yao Qian , Li Fuhua , Xu Weicheng , Wu Xiaolian
Published: November 2024

The adsorption of toxic metals onto iron oxides is a prevalent geochemical process in natural environments. Organic acids are known to modify the adsorption features of toxic ions through either competitive or cooperative effects. Nowadays, the toxic metal adsorption influenced by organic acids on iron oxides with varying facet exposures is not fully understood. This study explored how L-Aspartic acid (LA) influences Cr(VI) adsorption on two different exposure facets of lepidocrocite through batch adsorption experiments, in situ ATR-FTIR spectroscopy, and 2D-COS analysis. The results reveal that LA competes for available binding sites on lepidocrocite, consequently inhibiting the adsorption of Cr(VI). Rod-shaped lepidocrocite (R-LEP) owns more (001) facets and shows stronger Cr(VI) adsorption and LA competition than plate-like lepidocrocite (P-LEP), which mainly has (010) facets. The data for Cr(VI) uptake on both P-LEP and R-LEP within the effect of LA are well-fitted by the pseudo-second-order kinetics and the Freundlich isotherm model, suggesting chemical interaction as the dominant process for Cr(VI) coordination on lepidocrocite. Cr(VI) ions favor interaction with R-LEP over P-LEP, forming inner-sphere complexes on (001) facets. Concurrently, LA’s carboxyl groups can compete for the active sites on the lepidocrocite surfaces, engaging in anion exchange with hydroxyl groups, and forming outer-sphere and inner-sphere structures. This competitive effect is particularly pronounced in the R-LEP system. The current findings are expected to broaden insights into how the exposed facets of lepidocrocite influence the fate of Cr(VI) in the organic acid coexistence environment.
Navigating Dividend Decisions: The Impact of Outsider CEOs in Imputation Tax Environments
Authors: Hoque Ariful , Islam Md Rayhan , Hossain Shahadat
Published: November 2024

This study examines the influence of outsider CEOs on corporate dividend policies, specifically within the framework of an imputation tax environment, like in Australia. The study analyses 9826 firm-year observations from Australian firms listed on the ASX from 2012 to 2021. The study reveals that outsider CEOs tend to distribute lower dividend payouts; a trend observed even after robustness tests. Methodologically, the study addresses potential endogeneity issues through sophisticated methods like propensity score matching, difference-in-difference approach, and two-stage system generalized method of moments. The findings indicate that firms led by outsider CEOs, particularly those with specialized industry knowledge, are more inclined to invest undistributed profits in capital expenditure projects, reflecting an investment-oriented strategy. This research contributes significantly to understanding the strategic decision-making of outsider CEOs and their impact on dividend policies in specific tax environments.
Methodology for Object-Level Change Detection in Post-Earthquake Building Damage Assessment Based on Remote Sensing Images: OCD-BDA
Authors: Xie Zhengtao , Zhou Zifan , He Xinhao , Fu Yuguang , Gu Jiancheng , Zhang Jiandong
Published: November 2024

Remote sensing and computer vision technologies are increasingly leveraged for rapid post-disaster building damage assessment, becoming a crucial and practical approach. In this context, the accuracy of employing various AI models in pixel-level change detection methods is significantly dependent on the consistency between pre- and post-disaster building images, particularly regarding variations in resolution, viewing angle, and lighting conditions; in object-level feature recognition methods, the low richness of semantic details of damaged buildings in images leads to a poor detection accuracy. This paper proposes a novel method, OCD-BDA (Object-Level Change Detection for Post-Disaster Building Damage Assessment), as an alternative to pixel-level change detection and object-level feature recognition methods. Inspired by human cognitive processes, this method incorporates three key steps: an efficient sample acquisition for object localization, labeling via HGC (Hierarchical and Gaussian Clustering), and model training and prediction for classification. Furthermore, this study establishes a change detection dataset based on Google Earth imagery of regions in Hatay Province before and after the Turkish earthquake. This dataset is characterized by pixel inconsistency and significant differences in photographic angles and lighting conditions between pre- and post-disaster images, making it a valuable test dataset for other studies. As a result, in the experiments of comparative generalization capabilities, OCD-BDA demonstrated a significant improvement, achieving an accuracy of 71%, which is twice that of the second-ranking method. Moreover, OCD-BDA exhibits superior performance in tasks with small sample amounts and rapid training time. With only 1% of the training samples, it achieves a prediction accuracy exceeding that of traditional transfer learning methods with 60% of samples. Additionally, it completes assessments across a large disaster area (450 km²) with 93% accuracy in under 23 min.
Small Object Detection in UAV Remote Sensing Images Based on Intra-Group Multi-Scale Fusion Attention and Adaptive Weighted Feature Fusion Mechanism
Authors: Yuan Zhe , Gong Jianglei , Guo Baolong , Wang Chao , Liao Nannan , Song Jiawei , Wu Qiming
Published: November 2024

In view of the issues of missed and false detections encountered in small object detection for UAV remote sensing images, and the inadequacy of existing algorithms in terms of complexity and generalization ability, we propose a small object detection model named IA-YOLOv8 in this paper. This model integrates the intra-group multi-scale fusion attention mechanism and the adaptive weighted feature fusion approach. In the feature extraction phase, the model employs a hybrid pooling strategy that combines Avg and Max pooling to replace the single Max pooling operation used in the original SPPF framework. Such modifications enhance the model’s ability to capture the minute features of small objects. In addition, an adaptive feature fusion module is introduced, which is capable of automatically adjusting the weights based on the significance and contribution of features at different scales to improve the detection sensitivity for small objects. Simultaneously, a lightweight intra-group multi-scale fusion attention module is implemented, which aims to effectively mitigate background interference and enhance the saliency of small objects. Experimental results indicate that the proposed IA-YOLOv8 model has a parameter quantity of 10.9 MB, attaining an average precision (mAP) value of 42.1% on the Visdrone2019 test set, an mAP value of 82.3% on the DIOR test set, and an mAP value of 39.8% on the AI-TOD test set. All these results outperform the existing detection algorithms, demonstrating the superior performance of the IA-YOLOv8 model in the task of small object detection for UAV remote sensing.
Reconstruction of Hourly Gap-Free Sea Surface Skin Temperature from Multi-Sensors
Authors: Tu Qianguang , Hao Zengzhou , Liu Dong , Tao Bangyi , Shi Liangliang , Yan Yunwei
Published: November 2024

The sea surface skin temperature (SSTskin) is of critical importance with regard to air–sea interactions and marine carbon circulation. At present, no single remote sensor is capable of providing a gap-free SSTskin. The use of data fusion techniques is therefore essential for the purpose of filling these gaps. The extant fusion methodologies frequently fail to account for the influence of depth disparities and the diurnal variability of sea surface temperatures (SSTs) retrieved from multi-sensors. We have developed a novel approach that integrates depth and diurnal corrections and employs advanced data fusion techniques to generate hourly gap-free SST datasets. The General Ocean Turbulence Model (GOTM) is employed to model the diurnal variability of the SST profile, incorporating depth and diurnal corrections. Subsequently, the corrected SSTs at the same observed time and depth are blended using the Markov method and the remaining data gaps are filled with optimal interpolation. The overall precision of the hourly gap-free SSTskin generated demonstrates a mean bias of −0.14 °C and a root mean square error of 0.57 °C, which is comparable to the precision of satellite observations. The hourly gap-free SSTskin is vital for improving our comprehension of air–sea interactions and monitoring critical oceanographic processes with high-frequency variability.
A Gradual Adversarial Training Method for Semantic Segmentation
Authors: Zan Yinkai , Lu Pingping , Meng Tingyu
Published: November 2024

Deep neural networks (DNNs) have achieved great success in various computer vision tasks. However, they are susceptible to artificially designed adversarial perturbations, which limit their deployment in security-critical applications. In this paper, we propose a gradual adversarial training (GAT) method for remote sensing image segmentation. Our method incorporates a domain-adaptive mechanism that dynamically modulates input data, effectively reducing adversarial perturbations. GAT not only improves segmentation accuracy on clean images but also significantly enhances robustness against adversarial attacks, all without necessitating changes to the network architecture. The experimental results demonstrate that GAT consistently outperforms conventional standard adversarial training (SAT), showing increased resilience to adversarial attacks of varying intensities on both optical and Synthetic Aperture Radar (SAR) images. Compared to the SAT defense method, GAT achieves a notable defense performance improvement of 1% to 12%.
Reawakening of Voragine, the Oldest of Etna’s Summit Craters: Insights from a Recurrent Episodic Eruptive Behavior
Authors: Calvari Sonia , Nunnari Giuseppe
Published: November 2024

Paroxysmal explosive activity at Etna volcano (Italy) has become quite frequent over the last three decades, raising concerns with the civil protection authorities due to its significant impact on the local population, infrastructures, viability and air traffic. Between 4 July and 15 August 2024, during the tourist season peak when the local population doubles, Etna volcano gave rise to a sequence of six paroxysmal explosive events from the summit crater named Voragine. This is the oldest and largest of Etna’s four summit craters and normally only produces degassing, with the previous explosive sequences occurring in December 2015 and May 2016. In this paper, we use thermal images recorded by the monitoring system maintained by the Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo (INGV–OE), and an automatic procedure previously tested in order to automatically define the eruptive parameters of the six lava fountain episodes. These data allowed us to infer the eruptive processes and gain some insights on the evolution of the explosive sequences that are useful for hazard assessment. Specifically, our results lead to the hypothesis that the Voragine shallow storage has a capacity of ~12–15 Mm3, which was not completely emptied with the last two paroxysmal events. It is thus possible that one or two additional explosive paroxysmal events could occur in the future. It is noteworthy that an additional paroxysmal episode occurred at Voragine on 10 November 2024, after the submission of this paper, thus confirming our hypothesis.
Utilizing LuTan-1 SAR Images to Monitor the Mining-Induced Subsidence and Comparative Analysis with Sentinel-1
Authors: Yang Fengqi , Shi Xianlin , Dai Keren , Zhang Wenlong , Yang Shuai , Han Jing , Wen Ningling , Deng Jin , Li Tao , Yao Yuan , Zhang Rui
Published: November 2024

The LuTan-1 (LT-1) satellite, launched in 2022, is China’s first L-band full-polarimetric Synthetic Aperture Radar (SAR) constellation, boasting interferometry capabilities. However, given its limited use in subsidence monitoring to date, a comprehensive evaluation of LT-1’s interferometric quality and capabilities is necessary. In this study, we utilized the Differential Interferometric Synthetic Aperture Radar (DInSAR) technique to analyze mining-induced subsidence results near Shenmu City (China) with LT-1 data, revealing nine subsidence areas with a maximum subsidence of −19.6 mm within 32 days. Furthermore, a comparative analysis between LT-1 and Sentinel-1 data was conducted focusing on the aspects of subsidence results, interferometric phase, scattering intensity, and interferometric coherence. Notably, LT-1 detected some subsidence areas larger than those identified by Sentinel-1, attributed to LT-1’s high resolution, which significantly enhances the detectability of deformation gradients. Additionally, the coherence of LT-1 data exceeded that of Sentinel-1 due to LT-1’s L-band long wavelength compared to Sentinel-1’s C-band. This higher coherence facilitated more accurate capturing of differential interferometric phases, particularly in areas with large-gradient subsidence. Moreover, the quality of LT-1’s monitoring results surpassed that of Sentinel-1 in root mean square error (RMSE), standard deviation (SD), and signal-to-noise ratio (SNR). In conclusion, these findings provide valuable insights for future subsidence-monitoring tasks utilizing LT-1 data. Ultimately, the systematic differences between LT-1 and Sentinel-1 satellites confirm that LT-1 is well-suited for detailed and accurate subsidence monitoring in complex environments.
Near-Inertial Oscillations Induced by Winter Monsoon Onset in the Southwest Taiwan Strait
Authors: Peng Xiaolin , Wang Li , Wu Xiongbin , Ai Weihua
Published: November 2024

The near-inertial motion in ocean surface currents directly reflects the energy transported by wind towards the surface layer, playing an important role in climate regulation and energy balance. Previous studies have mainly focused on near inertial oscillations (NIOs) induced by tropical cyclones in the Taiwan Strait, with few reports on near inertial oscillations induced by monsoon onset. Using high-frequency radar observations, we detected an amplification of NIOs induced by the winter monsoon onset. While not as strong as NIOs induced by tropical cyclones, the near-inertial current (NIC) induced by winter monsoon onset in the Taiwan Strait has peak speeds reaching up to 5.2 cm/s and explaining up to 0.7% of non-tidal variance. This study presents observational results of NIOs during three monsoon onset events, and analyzes the impact of winds and temperature changes on NIOs. Temporal and spectral analysis reveals that the monsoon onset is the primary driver behind the formation of NIOs. Results indicate that near-inertial kinetic energy is relatively lower in shallower waters, such as the Taiwan Bank, compared to deeper regions. Furthermore, by integrating the air and sea surface temperature from reanalysis products, we have examined the abrupt changes in sea surface temperature (SST) before and after monsoon onset and their correlation with NIOs. The findings suggest that temperature falling favors the intensification of NICs during monsoon onset, and a lack of significant SST changes precludes the triggering of notable NICs. These insights enhance our understanding of the mechanisms driving NIOs and their roles in seawater mixing.
Joint Sparse Local Linear Discriminant Analysis for Feature Dimensionality Reduction of Hyperspectral Images
Authors: Cao Cong-Yin , Li Meng-Ting , Deng Yang-Jun , Ren Longfei , Liu Yi , Zhu Xing-Hui
Published: November 2024

Although linear discriminant analysis (LDA)-based subspace learning has been widely applied to hyperspectral image (HSI) classification, the existing LDA-based subspace learning methods exhibit several limitations: (1) They are often sensitive to noise and demonstrate weak robustness; (2) these methods ignore the local information inherent in data; and (3) the number of extracted features is restricted by the number of classes. To address these drawbacks, this paper proposes a novel joint sparse local linear discriminant analysis (JSLLDA) method by integrating embedding regression and locality-preserving regularization into the LDA model for feature dimensionality reduction of HSIs. In JSLLDA, a row-sparse projection matrix can be learned, to uncover the joint sparse structure information of data by imposing a L2,1-norm constraint. The L2,1-norm is also employed to measure the embedding regression reconstruction error, thereby mitigating the effects of noise and occlusions. A locality preservation term is incorporated to fully leverage the local geometric structural information of the data, enhancing the discriminability of the learned projection. Furthermore, an orthogonal matrix is introduced to alleviate the limitation on the number of acquired features. Finally, extensive experiments conducted on three hyperspectral image (HSI) datasets demonstrated that the performance of JSLLDA surpassed that of some related state-of-the-art dimensionality reduction methods.