bluuebunny/crossref_metadata_2025 huggingface dataset:
Rapid Responses of Greenhouse Gas Emissions and Microbial Communities to Carbon and Nitrogen Addition in Sediments
Authors: Liang Jin-Feng , Yao Bo , Zhang Xiao-Ya , Hu Qi-Wu
Published: September 2024

Massive labile carbon and nitrogen inputs into lakes change greenhouse gas emissions. However, the rapid driving mechanism from eutrophic and swampy lakes is not fully understood and is usually contradictory. Thus, we launched a short-term and anaerobic incubation experiment to explore the response of greenhouse gas emissions and microbial communities to glucose and nitrate nitrogen (NO3−-N) inputs. Glucose addition significantly increased CH4 and CO2 emissions and decreased N2O emissions, but there were no significant differences. NO3−-N addition significantly promoted N2O emissions but reduced CH4 accumulative amounts, similar to the results of the Tax4Fun prediction. Bacterial relative abundance changed after glucose addition and coupled with the abundance of denitrification genes (nirS and nirK) decreased while maintaining a negative impact on N2O emissions, considerably increasing methanogenic bacteria (mcrA1) while maintaining a positive impact on CH4 emissions. Structural equation modeling showed that glucose and NO3−-N addition directly affected MBC content and greenhouse gas emissions. Further, MBC content was significantly negative with nirS and nirK, and positive with mcrA1. These results significantly deepen the current understanding of the relationships between labial carbon, nitrogen, and greenhouse emissions, further highlighting that labile carbon input is the primary factor driving greenhouse gas emissions from eutrophic shallow lakes.
Design and Synthesis of Pyridyl and 2-Hydroxyphenyl Chalcones with Antitubercular Activity
Authors: Aziafor Kelphina , Ruparelia Ketan , Moulds Brandon , Zloh Mire , Parish Tanya , Brucoli Federico
Published: September 2024

A focussed library of pyridyl and 2-hydroxyphenyl chalcones were synthesized and tested for growth inhibitory activity against Mycobacterium tuberculosis H37Rv, and normal and cancer breast cell lines. Pyridyl chalcones bearing lipophilic A-ring, e.g., dichloro-phenyl-(14), pyrene-1-yl (20)- and biphenyl-4-yl (21) moieties were found to be the most potent of the series inhibiting the growth of M. tuberculosis H37Rv with IC90 values ranging from 8.9–28 µM. Aryl chalcones containing a 3-methoxyphenyl A-ring and either p-Br-phenyl (25) or p-Cl-phenyl (26) B-rings showed an IC90 value of 28 µM. Aryl-chalcones were generally less toxic to HepG2 cells compared to pyridyl-chalcones. Dose-dependent antiproliferative activity against MDA468 cells was observed for trimethoxy-phenyl (16) and anthracene-9-yl (19) pyridyl-chalcones with IC50 values of 0.7 and 0.3 µM, respectively. Docking studies revealed that chalone 20 was predicted to bind to the M. tuberculosis protein tyrosine phosphatases B (PtpB) with higher affinity compared to a previously reported PtpB inhibitor.
The Coordination of Aluminum Sulfate with a Water-Soluble Block Copolymer Containing Carboxyl, Amide, Sulfonic and Anhydride Groups Providing Both Accelerating and Hardening Effects in Cement Setting
Authors: Song Zhiyuan , Chaudhary Sidra , Bibi Zainab , Wu Yong , Jia Qinxiang , Li Xiaoyong , Ouyang Weiyi , Sun Yang
Published: September 2024

Two water-soluble block copolymers composed of acrylic acid (AA), 2-acrylamido-2-methylpropane sulfonic acid (AMPS), and optionally maleic anhydride (MAH) were synthesized through ammonium persulfate-catalyzed free radical polymerization in water. The introduction of aluminum sulfate (AS) into the resulting mixtures significantly reduced the setting times of the paste and enhanced the mechanical strength of the mortar compared to both the additive-free control and experiments facilitated solely by pure AS. This improvement was primarily attributed to the inhibition of rapid Al3+ hydrolysis, which was achieved through coordination of the synthesized block copolymers, along with the formation of newly identified hydrolytic intermediates. Notably, the ternary copolymer (AA–AMPS–MAH) exhibited superior performance compared to that of the binary copolymer (AA–AMPS). In the early stages of cement setting, clusters of ettringite (AFt) were found to be immobilized over newly detected linkage phases, including unusual calcium silicate hydrate and epistilbite. In contrast to the well-documented role of polymers in retarding cement hydration, this study presents a novel approach by providing both accelerating and hardening agents for cement setting, which has significant implications for the future design of cement additives.
The Antioxidant Activity of Atomized Extracts of the Leaves and Stems of Cnidoscolus diacanthus (Pax & K. Hoffm.) J.F. Macbr. from Peru and Their Effect on Sex Hormone Levels in Rats
Authors: Tinco-Jayo Johnny Aldo , Pérez-Chauca León Fernando , Castilla-Torres Nancy Victoria , Enciso-Roca Edwin Carlos , Taboada-Huaman Diana , Nuñez-Soto Litman , Moscoso-García Luis Uriel , Arroyo-Acevedo Jorge Luis , Aguilar-Felices Enrique Javier , Herrera-Calderon Oscar
Published: September 2024

In this research, we aimed to determine the antioxidant activity of an atomized extract of Cnidoscolus diacanthus (Pax & K. Hoffm.) J.F. Macbr., known in Peru as “huanarpo hembra”, and its effect on sex hormone levels. Its phytochemical profile was determined using liquid chromatography–mass spectrometry (LC–MS), while its total phenol content (TPC) and total flavonoids (TFs) were determined using the Folin–Ciocalteu method and the aluminum chloride method. Its antioxidant activity was determined using 2,2-diphenyl-1-picrylhydrazyl (DPPH), the radical 2,2-azino-bis-3-ethylbenzthiazolin-6 sulfonic acid (ABTS), and ferric-reducing antioxidant power (FRAP). The biological activity of C. diacanthus and its effect on sexual hormones were determined in Holtzman rats of both sexes. Phytochemical analysis revealed the presence of flavonoids and phenolic compounds in its leaves and stems, mainly rutin, quercetin, chlorogenic acid, and genistein. However, the stem extract contained higher total phenol (464.38 ± 4.40 GAE/g) and flavonoid (369.17 ± 3.16 mg QE/g of extract) contents than the leaf extract (212.38 ± 3.19 mg GAE/g and 121.49 ± 2.69 mg QE/g). For DPPH, ABTS, and FRAP, the Trolox-equivalent antioxidant capacity (TEAC) was 597.20 ± 5.40 µmol/g, 452.67 ± 5.76 µmol/g, and 535.91 ± 1.56 µmol/g, respectively, for the stems, while for the leaves, it was 462.39 ± 3.99 µmol/g, 202.32 ± 5.20 µmol/g, and 198.13 ± 1.44 µmol/g, respectively. In terms of the values for hormonal levels, at a dose of 100 mg/kg of the extract, testosterone levels of 1.430 ng/mL (with the leaf extract) and 1.433 ng/mL (with the stem extract), respectively, were found in the male rats. Regarding estradiol levels, in the female rats, these were 10.425 ng/mL (leaf extract) and 8.775 ng/mL (stem extract), while their levels of luteinizing hormone were 0.320 mIU/mL (leaf extract) and 0.273 mIU/mL (stem extract). For the follicle-stimulating hormone, levels of 0.858 mIU/mL (leaf extract) and 0.840 mIU/mL (stem extract) were found in the female rats, and levels of 0.220 mIU/mL (leaf extract) and 0.200 mIU/mL (stem extract) were found in the male rats. It is concluded that the C. diacanthus stem extract had a greater antioxidant capacity than the leaf extract, while both extracts had a superior effect on the sex hormone levels in the female rats compared to the male rats.
Coexistence of the Band Filling Effect and Trap-State Filling in the Size-Dependent Photoluminescence Blue Shift of MAPbBr3 Nanoparticles
Authors: Sun Jing , Chen Mengzhen , Huang Tao , Ding Guqiao , Wang Zhongyang
Published: September 2024

The size-dependent photoluminescence (PL) blue shift in organometal halide perovskite nanoparticles has traditionally been attributed to quantum confinement effects (QCEs), irrespective of nanoparticle size. However, this interpretation lacks rigor for nanoparticles with diameters exceeding the exciton Bohr radius (rB). To address this, we investigated the PL of MAPbBr3 nanoparticles (MNPs) with diameters ranging from ~2 to 20 nm. By applying the Brus equation and Burstein–Moss theory to fit the PL and absorption blue shifts, we found that for MNPs larger than rB, the blue shift is not predominantly governed by QCEs but aligns closely with the band filling effect. This was further corroborated by a pronounced excitation-density-dependent PL blue shift (Burstein−Moss shift) at high photoexcitation densities. Additionally, trap-state filling was also found to be not a negligible origin of the PL blue shift, especially for the smaller MNPs. The time-resolved PL spectra (TRPL) and excitation-density-dependent TRPL are collected to support the coexistence of both filling effects by the high initial carrier density (~1017–1018 cm−3) and the recombination dynamics of localized excitons and free carriers in the excited state. These findings underscore the combined role of the band filling and trap-state filling effects in the size-dependent PL blue shift for solution-prepared MNPs with diameters larger than rB, offering new insights into the intrinsic PL blue shift in organometal halide perovskite nanoparticles.
A Review on Pulsed Laser Preparation of Quantum Dots in Colloids for the Optimization of Perovskite Solar Cells: Advantages, Challenges, and Prospects
Authors: Sun Liang , Li Yang , Yan Jiujiang , Xu Wei , Xiao Liangfen , Zheng Zhong , Liu Ke , Huang Zhijie , Li Shuhan
Published: September 2024

In recent years, academic research on perovskite solar cells (PSCs) has attracted remarkable attention, and one of the most crucial issues is promoting the power conversion efficiency (PCE) and operational stability of PSCs. Generally, modification of the electron or hole transport layers between the perovskite layers and electrodes via surface engineering is considered an effective strategy because the inherent structural defects between charge carrier transport layers and perovskite layers can be reshaped and modified by adopting the functional nanomaterials, and thus the charge recombination rate can be naturally decreased. At present, large amounts of available nanomaterials for surface modification of the perovskite films are extensively investigated, mainly including nanocrystals, nanorods, nanoarrays, and even colloidal quantum dots (QDs). In particular, as unique size-dependent nanomaterials, the diverse quantum properties of colloidal QDs are different from other nanomaterials, such as their quantum confinement effects, quantum-tunable effects, and quantum surface effects, which display great potential in promoting the PCE and operational stability of PSCs as the charge carriers in perovskite layers can be effectively tuned by these quantum effects. However, preparing QDs with a neat and desirable size remains a technical difficulty, even though the present chemical engineering is highly advanced. Fortunately, the rapid advances in laser technology have provided new insight into the precise preparation of QDs. In this review, we introduce a new approach for preparing the QDs, namely pulsed laser irradiation in colloids (PLIC), and briefly highlight the innovative works on PLIC-prepared QDs for the optimization of PSCs. This review not only highlights the advantages of PLIC for QD preparation but also critically points out the challenges and prospects of QD-based PSCs.
Extra Virgin Olive Oil Reduces the Risk of Non-Alcoholic Fatty Liver Disease in Females but Not in Males: Results from the NUTRIHEP Cohort
Authors: Donghia Rossella , Tatoli Rossella , Campanella Angelo , Losurdo Giuseppe , Di Leo Alfredo , De Pergola Giovanni , Bonfiglio Caterina , Giannelli Gianluigi
Published: September 2024

Background: Non-alcoholic fatty liver disease (NAFLD) is the most prevalent chronic liver disease worldwide. One way to resolve this reversible condition is by making dietary changes. Extra virgin olive oil (EVOO) is often associated with an improvement in this disease. The aim of this study was to explore the protective role of EVOO on NAFLD conditions, stratified by gender. Methods: The study cohort included 1426 participants assessed in the second recall of the NUTRIHEP cohort (2014–2018), subdivided by gender and dividing the EVOO intake into quartiles of daily gram intake. Results: The results indicated a protective role of the last quartile of EVOO only for female subjects, OR = 0.43, p = 0.02, 0.21 to 0.85 at 95% C.I., whereas in the male sub-cohort, the effect was not statistically significant. Conclusions: The protective role of EVOO is different between genders. This difference has not been explored in the literature, so we conclude that this is one of the few papers in the literature to evaluate a gender difference in the intestinal absorption of humans based on an epidemiological study.
Effects of Acute Citrulline Malate Supplementation on CrossFit® Exercise Performance: A Randomized, Double-Blind, Placebo-Controlled, Cross-Over Study
Authors: Devrim-Lanpir Asli , Ihász Ferenc , Demcsik Máté , Horváth András Csaba , Góczán Pál , Czepek Péter , Takács Johanna , Kimble Rachel , Zare Reza , Gunes Fatma Esra , Knechtle Beat , Weiss Katja , Rosemann Thomas , Heinrich Katie M.
Published: September 2024

Given the increasing popularity of CrossFit® as a high-intensity functional training program and the potential benefits of citrulline malate (CM) in enhancing exercise performance through its role as a precursor to L-arginine and nitric oxide production, this study aimed to investigate the acute effects of CM supplementation on CrossFit® performance and cardiovascular function. Using a randomized, double-blind, placebo-controlled, cross-over design, 21 recreationally active participants (mean age 22.2 ± 2.6 years, mean body weight 75.9 ± 10.4 kg) with CrossFit® experience completed the “Cindy” workout under CM and placebo conditions. Participants consumed 4.4 g of CM or a placebo 60 min before the workout, and the performance was measured by the number of rounds completed. Secondary outcomes included heart rate response, time spent in different heart rate intensity zones, and post-exercise recovery time. The results indicated no significant difference in the number of rounds completed between the CM and placebo conditions (13.5 ± 5.2 vs. 13.8 ± 6.7 rounds, respectively; p = 0.587). However, the time spent in zone 4 (80–90% of HR max) was significantly increased in the CM condition (527 ± 395 s vs. 453 ± 334 s; p = 0.017), suggesting a potential benefit for aerobic capacity and anaerobic threshold. No significant differences in post-exercise recovery time were observed (6.6 ± 4.7 h vs. 6.9 ± 4.7 h; p = 0.475). This study highlights the need for further research with larger sample sizes, both genders, and different CM dosages to clarify these findings and better understand CM’s role in enhancing athletic performance.
Tackling Cravings in Medical Weight Management: An Update on Pathophysiology and an Integrated Approach to Treatment
Authors: Kakoschke Naomi , Henry Belinda A. , Cowley Michael A. , Lee Kevin
Published: September 2024

Background/Objectives: Food cravings involve a strong drive to consume palatable foods irrespective of nutritional status. Importantly, cravings contribute substantially to the obesity epidemic. Managing hunger alone is insufficient for weight management as this relates only to homeostatic eating and does not address the complex aetiology of hedonic eating and its crucial role in food cravings. Medical weight management clinics and anti-obesity medication trials do not routinely identify and address food cravings. Methods: We conducted a narrative review of the literature consisting of 115 peer-reviewed articles (original articles and reviews). We included articles focused on food craving pathophysiology, assessment, and management strategies providing contrasts against the current medical model of weight management seen in obesity pharmacotherapy trials as well as the current standard of practise. Results: We outline the neurohormonal and psychological drivers of cravings, which lead to a spectrum of eating behaviours, from comfort food eating to binge eating disorders. We provide an overview of ways of identification and measurement options, including their strengths and weaknesses, and an overview of management strategies and their cravings control efficacy, spanning lifestyle modifications like nutrition and sleep, psychological therapies (i.e., cognitive behavioural therapy [CBT], acceptance-based therapies such as mindfulness) and, last but not least, medications that not only are approved for weight reduction but reduce cravings. Finally, based on these findings, we provide a proposed integrated and iterative model that is able to evolve and adapt to the individual over time in tackling cravings for long-term weight loss maintenance. Conclusions: The findings emphasise the importance of cravings management and provide a synthesis on how cravings can be identified in a medical weight management setting, which can be practically implemented in an integrated iterative model spanning anti-obesity medications that have craving control data to evidence-based lifestyle and psychological interventions.
Hypertensive Disorders of Pregnancy: A Window into Breastfeeding Outcomes in Varied Healthcare Systems
Authors: Francis Jimi , Gelner Elizabeth , Dickton Darby
Published: September 2024

Varied hospital systems demonstrate diverse and often very different approaches to patient care. This may best be analyzed by looking at specific disorders and outcomes in a population with these disorders. As one such lens, hypertensive disorders of pregnancy (HDPs) continue to pose a severe health risk for mothers and infants, and breastfeeding outcomes play a crucial role in determining long-term maternal and fetal health. This pilot study investigated breastfeeding outcomes in two hospitals, as representatives for differing healthcare systems, among patients diagnosed with HDPs. Data were collected for 12 months at two hospitals, one private and one military, on 729 patients diagnosed with HDPs. Data were analyzed for infant maturity at birth and breastfeeding outcomes. Most participants (83.2%) stated their intention to breastfeed for the first six months of life. By hospital discharge, only 56% (p = 0.0001) of the private hospital participants were breastfeeding compared to 65% of the military hospital participants. In addition, while 69% of infants were born before term, more infants were born before term at the private hospital (71%) than at the military hospital (65%), with 37% (private) and 42% (military) of preterm infants breastfeeding at hospital discharge. Significant differences existed between these two hospital systems in the number of those initiating breastfeeding and breastfeeding at hospital discharge. The military hospital was more successful in assisting these high-risk women in meeting their breastfeeding intentions. Changes in hospital practices, such as metrics and incentivization, focusing on breastfeeding support, could improve the rate of breastfeeding at hospital discharge and impact long-term health outcomes.
Is Short-Read 16S rRNA Sequencing of Oral Microbiome Sampling a Suitable Diagnostic Tool for Head and Neck Cancer?
Authors: Yeo Kenny , Wu Fangmeinuo , Li Runhao , Smith Eric , Wormald Peter-John , Valentine Rowan , Psaltis Alkis James , Vreugde Sarah , Fenix Kevin
Published: September 2024

The oral microbiome, studied by sampling the saliva or by oral rinse, has been long thought to have diagnostic capacity for head and neck cancers (HNC). However, previous reports on the HNC oral microbiome provide inconsistent results. The aim of this study is to consolidate these datasets and determine the oral microbial composition between HNC patients to healthy and premalignant individuals. We analyzed 16 published head and neck cancer (HNC) short-read 16S rRNA sequencing datasets, specifically targeting the V3V4, V4 and V4V5 regions. These datasets included saliva and oral rinse samples from donors with HNC, as well as from healthy and premalignant donors. Differences in diversities and microbial abundance were determined. HNC saliva displayed lower alpha diversity than healthy donors. In contrast, the opposite trend was observed for oral rinse samples. Beta diversity scores were largely similar across different patient types. Similar oral phyla were detected for all samples, but proportions were largely dependent on sample type (i.e., saliva or oral rinse) and primer set utilized for 16S rRNA sequencing. Neisseria, Leptotrichia and Megasphaera were elevated in healthy saliva, while Mycoplasma was elevated in HNC saliva. Oral rinse and saliva displayed similar enrichment for Fusobacterium, while Veillonella, Alloprevotella, and Campylobacter showed conflicting results. The sparse partial least squares discriminant analysis model performed effectively in discriminating HNC from healthy or premalignant patients using V3V4 saliva (AUC = 0.888) and V3V4 oral rinse (AUC = 0.928), while poor discriminative capacity was observed for V4 saliva (AUC = 0.688). In conclusion, our meta-analysis highlighted the limitations of 16S rRNA sequencing, particularly due to variations across study batches, primer sets (i.e., V3V4, V4), and sample types. Hence, caution should be exercised when interpreting 16S rRNA sequencing results across studies, especially when different primer sets and sample types are used.
Modular Polymerase Synthesis and Internal Protein Domain Swapping via Dual Opposed Frameshifts in the Ebola Virus L Gene
Authors: Stubbs David B. , Ruzicka Jan A. , Taylor Ethan W.
Published: September 2024

Sequence analysis of the Zaire ebolavirus (EBOV) polymerase (L gene) mRNA, using online tools, identified a highly ranked −1 programmed ribosomal frameshift (FS) signal including an ideal slippery sequence heptamer (UUUAAAA), with an overlapping coding region featuring two tandem UGA codons, immediately followed by an RNA region that is the inverse complement (antisense) to a region of the mRNA of the selenoprotein iodothyronine deiodinase II (DIO2). This antisense interaction was confirmed in vitro via electrophoretic gel shift assay, using cDNAs at the EBOV and DIO2 segments. The formation of a duplex between the two mRNAs could trigger the ribosomal frameshift, by mimicking the enhancing role of a pseudoknot structure, while providing access to the selenocysteine insertion sequence (SECIS) element contained in the DIO2 mRNA. This process would allow the −1 frame UGA codons to be recoded as selenocysteine, forming part of a C-terminal module in a low abundance truncated isoform of the viral polymerase, potentially functioning in a redox role. Remarkably, 90 bases downstream of the −1 FS site, an active +1 FS site can be demonstrated, which, via a return to the zero frame, would enable the attachment of the entire C-terminal of the polymerase protein. Using a construct with upstream and downstream reporter genes, spanning a wildtype or mutated viral insert, we show significant +1 ribosomal frameshifting at this site. Acting singly or together, frameshifting at these sites (both of which are highly conserved in EBOV strains) could enable the expression of several modified isoforms of the polymerase. The 3D modeling of the predicted EBOV polymerase FS variants using the AI tool, AlphaFold, reveals a peroxiredoxin-like active site with arginine and threonine residues adjacent to a putative UGA-encoded selenocysteine, located on the back of the polymerase “hand”. This module could serve to protect the viral RNA from peroxidative damage.
Roles of Prostaglandins and Hydrogen Sulfide in an Outflow Model of the Porcine Ocular Anterior Segment Ex Vivo
Authors: Robinson Jenaye , Bush Leah , Okolie Anthonia , Muili Fatima , Ohia Sunny , Opere Catherine , Mbye Ya Fatou Njie
Published: September 2024

Background: Hydrogen sulfide (H2S)-releasing compounds can reduce intraocular pressure in normotensive rabbits by increasing aqueous humor (AH) outflow through the trabecular meshwork. In the present study, we investigated the contribution of endogenous H2S and the role of intramurally generated prostaglandins in the observed increase in AH outflow facility in an ex vivo porcine ocular anterior segment model. Material and Methods: Porcine ocular anterior segment explants were perfused with Dulbecco’s Modified Eagle’s Medium maintained at 37 °C and gassed with 5% CO2 and 95% air under an elevated pressure of 15 mmHg for four hours. Perfusates from the anterior segment explants were collected and immediately assayed for their H2S and prostaglandin E2 content. Results: Elevating perfusion pressure from 7.35 to 15 mm Hg significantly (p < 0.001) increased H2S concentration in the perfusate from 0.4 ± 0.1 to 67.6 ± 3.6 nM/µg protein. In the presence of an inhibitor of cystathionine ß-synthase/cystathionine γ-lyase, aminooxyacetic acid (AOAA, 30 µM), or an inhibitor of 3-mercaptopyruvate sulfurtransferase, α-ketobutyric acid (KBA, 1 mM), the effects of elevated pressure on H2S levels in the perfusate was significant (p < 0.001). Furthermore, flurbiprofen (30 µM) and indomethacin (10 µM) attenuated the elevated pressure-induced increase in H2S levels in the perfusate. Interestingly, elevating perfusion pressure had no significant effect on PGE2 concentrations in the perfusate. While the inhibition of H2S biosynthesis by AOAA or KBA did not affect PGE2 levels in perfusate, flurbiprofen (30 µM) caused a significant (p < 0.05) decrease in the concentration of PGE2 under conditions of elevated perfusion pressure. Conclusions: We conclude that the elevated perfusion pressure-induced increase in H2S concentrations depends upon the endogenous biosynthesis of H2S and intramurally produced prostaglandins in the porcine anterior segment explants. While the concentration of PGE2 in the perfusate under elevated perfusion pressure was unaffected by pretreatment with inhibitors of H2S biosynthesis, it was reduced in the presence of an inhibitor of cyclooxygenase.
Antimicrobial Peptide Octoprohibitin-Encapsulated Chitosan Nanoparticles Enhanced Antibacterial Activity against Acinetobacter baumannii
Authors: Jayathilaka E. H. T. Thulshan , Han Jinwook , De Zoysa Mahanama , Whang Ilson
Published: September 2024

Background: This study focused on evaluating the physiochemical characteristics and antibacterial activity of Octoprohibitin-encapsulated CNPs (Octoprohibitin-CNPs) against Acinetobacter baumannii. Methods: Octoprohibitin was encapsulated into CNPs via ionotropic gelation with carboxymethyl chitosan (CMC) and low molecular weight chitosan (CS). Octoprohibitin-CNPs were dispersed in phosphate-buffered saline and the release kinetic profile was determined. Then Octoprohibitin-CNPs were examined using field-emission transmission electron microscopy and physicochemical characterization was performed. Antibacterial activity of Octoprohibitin-CNPs against A. baumannii was evaluated. Biofilm inhibition and eradication assays were performed using the crystal violet (CV) staining-based method for biofilm quantification. Results: The average diameter, zeta potential, encapsulation efficiency, and loading capacity of Octoprohibitin-CNPs were 244.5 ± 21.97 nm, +48.57 ± 0.38 mV, and 85.7% and 34.2%, respectively. TEM analysis imaging revealed that Octoprohibitin-CNPs are irregularly shaped, with fewer aggregates than CNPs. Octoprohibitin-CNPs exhibited a biphasic release pattern, characterized by an initial rapid phase followed by a sustained release over time, extending up to 93.68 ± 6.48% total release until 96 h. In vitro, Octoprohibitin-CNPs showed lower cytotoxicity compared to Octoprohibitin alone. Time-kill kinetic and bacterial viability reduction assays showed Octoprohibitin-CNPs exhibited slightly higher antibacterial activity against A. baumannii than Octoprohibitin. Conclusions: Octoprohibitin-CNP-treated A. baumannii exhibited higher levels of morphological deviation, increased membrane permeability, and the production of reactive oxygen species, as well as antibiofilm activity with greater biofilm inhibition and eradication than Octoprohibitin. These findings show that Octoprohibitin-CNPs perform better against A. baumannii compared to Octoprohibitin alone.
Transcriptome Profiling Identifies Plant Hormone Signaling Pathway-Related Genes and Transcription Factors in the Drought and Re-Watering Response of Ginkgo biloba
Authors: Ming Meiling , Zhang Juan , Zhang Jiamin , Tang Jing , Fu Fangfang , Cao Fuliang
Published: September 2024

Ginkgo biloba, usually referred to as a “living fossil,” is widely planted in many countries because of its medicinal value and beautiful appearance. Owing to ginkgo’s high resistance to drought stress, ginkgo seedlings can even survive withholding water for several days without exhibiting leaf wilting and desiccation. To assess the physiological and transcriptomic mechanisms involved in the drought stress and re-watering responses of Ginkgo biloba, ginkgo seedlings were subjected to drought treatment for 15 d (D_15 d) and 22 d (D_22 d) until they had severely wilted, followed by re-watering for 3 d (D_Re3 d) to restore normal growth. Variations in physiological characteristics (relative water content, malondialdehyde (MDA) content, stomatal aperture, and antioxidant enzyme activity) during drought and re-watering were assessed. In total, 1692, 2031, and 1038 differentially expressed genes (DEGs) were upregulated, while 1691, 2820, and 1910 were downregulated in D_15 d, D_22 d, and D_Re3 d, respectively, relative to the control. Three pathways, namely, plant hormone signal transduction, plant–pathogen interaction, and the plant MAPK signaling pathway, were enriched during drought stress and re-watering. The DEGs involved in plant hormone signal transduction pathways (those of IAA, CTK, GA, ABA, ETH, BR, SA, and JA) and the major differentially expressed transcription factors (TFs; MYB, bHLH, AP2/ERF, NAC, WRKY, and bZIP) were identified. Quantitative real-time PCR revealed six TFs as positive or negative regulators of drought stress response. These phenotype-related physiological characteristics, DEGs, pathways, and TFs provide valuable insights into the drought stress and re-watering responses in G. biloba.
Guanidine Derivatives Leverage the Antibacterial Performance of Bio-Based Polyamide PA56 Fibres
Authors: Wang Lili , Zhou Bobo , Du Yuliu , Bai Miao , Xu Xiang , Guan Yong , Liu Xiucai
Published: September 2024

Bacterial damage has significantly impacted humanity, prompting the control of harmful microorganisms and infectious diseases. In this study, antibacterial bio-based PA56 fibres were prepared with high-speed spinning using ethylene-methyl acrylate-glycidyl methacrylate terpolymer (EMA) as the compatibiliser and polypentamethylene guanidine sulphate (PPGS) as the antibacterial agent. The effects of PPGS content on the properties of PA56 draw-textured yarns (DTYs) were investigated. The compatibility between PPGS and PA greatly improved with EMA incorporation. Compared with PA56 fibres, the elongation at break of the sample containing 2.0 wt% EMA and PPGS increased by 25.93%. The inhibition rates of the fibres with 1.0 wt% PPGS against Escherichia coli and Staphylococcus aureus reached over 99.99%. Samples were easily coloured with dyes, exhibiting good colour fastness, regardless of the EMA content. However, the antibacterial performances of dyed DTYs decreased to varying degrees. the inhibition rates of samples of 0.5wt% addition of PPGS against E. coli were reduced from 99.99% to 28.50% and 25.36% after dyeing with Acid Blue 80 and Dispersible Blue 2BLN, respectively. The EMA-modified fibres exhibited the best antibacterial activity after dyeing with neutral gray 2BL. These findings are expected to promote the wider use of biobased PA56 in practical applications that require antibacterial performance and to guide the dyeing process of antimicrobial fibres.
Study of Factors Affecting UV-Induced Photo-Degradation in Different Types of Polyethylene Sheets
Authors: Du Bochu , Lee Chenghao , Ji Ying
Published: September 2024

Enhancing the degradability of polyethylene plastics could provide a potential solution to the overwhelming crisis of plastic waste. Conventional studies have focused on the degradation of polyethylene thin films. This study investigated UV-induced photo-degradation according to ASTM D5208-14 in polyethylene sheets with thicknesses ranging from 0.4 to 1.2 mm. The impacts of sample thickness, metal pro-oxidants, polyethylene resin types and foaming were explored through the characterization of the carbonyl index, molecular weight, tensile properties and crystallinity. As pro-oxidants, single iron or manganese stearate demonstrated a concentration-dependent trend in accelerating the photo-degradation of polyethylene sheets. The thickness, foaming and resin type—such as low-density polyethylene (LDPE) and high-density polyethylene (HDPE)—significantly impacted the rate of photo-oxidation. Thick polyethylene sheets (1.2 mm) exhibited a heterogenous and depth-dependent degradation profile. As the photo-degradation progressed, the enhanced crystallinity, reduced UV transmittance and formation of crosslinks were able to prevent further oxidative cleavage of the polyethylene chain. This study investigated the time course and factors affecting the photo-degradation of polyethylene sheets, which could provide insights into the formulation design of photo-degradable polyethylene plastics.
Data-Driven Calibration of SWOT’s Systematic Errors: First In-Flight Assessment
Authors: Ubelmann Clément , Dibarboure Gérald , Flamant Benjamin , Delepoulle Antoine , Vayre Maxime , Faugère Yannice , Prandi Pierre , Raynal Matthias , Briol Frédéric , Bracher Geoffroy , Cadier Emeline
Published: September 2024

The SWOT satellite, carrying the KaRIN first wide-swath onboard altimeter, was launched in December 2022, and has now delivered more than a year of surface water elevation data over the ocean and inland lakes/rivers. These data are affected by systematic errors which constitute the dominant part of the error budget at scales larger than a few thousands of kilometers. Some strategies for their estimation and calibration were explored during the pre-launch studies with performance estimations. Now, based on the real data, we propose in this study to assess the systematic error budget with statistical methods relying on spectral and co-spectral analysis. From this assessment, suggesting very low error levels (below requirements), we propose the implementation of the calibration algorithms at Level-2 and Level-3 with a few minor adjustments justified by the error spectra. The calibrated products are then validated with usual CalVal metrics.
A Multi-Scale Content-Structure Feature Extraction Network Applied to Gully Extraction
Authors: Dong Feiyang , Jin Jizhong , Li Lei , Li Heyang , Zhang Yucheng
Published: September 2024

Black soil is a precious soil resource, yet it is severely affected by gully erosion, which is one of the most serious manifestations of land degradation. The determination of the location and shape of gullies is crucial for the work of gully erosion control. Traditional field measurement methods consume a large amount of human resources, so it is of great significance to use artificial intelligence techniques to automatically extract gullies from satellite remote sensing images. This study obtained the gully distribution map of the southwestern region of the Dahe Bay Farm in Inner Mongolia through field investigation and measurement and created a gully remote sensing dataset. We designed a multi-scale content structure feature extraction network to analyze remote sensing images and achieve automatic gully extraction. The multi-layer information obtained through the resnet34 network is input into the multi-scale structure extraction module and the multi-scale content extraction module designed by us, respectively, obtained richer intrinsic information about the image. We designed a structure content fusion network to further fuse structural features and content features and improve the depth of the model’s understanding of the image. Finally, we designed a muti-scale feature fusion module to further fuse low-level and high-level information, enhance the comprehensive understanding of the model, and improve the ability to extract gullies. The experimental results show that the multi-scale content structure feature extraction network can effectively avoid the interference of complex backgrounds in satellite remote sensing images. Compared with the classic semantic segmentation models, DeepLabV3+, PSPNet, and UNet, our model achieved the best results in several evaluation metrics, the F1 score, recall rate, and intersection over union (IoU), with an F1 score of 0.745, a recall of 0.777, and an IoU of 0.586. These results proved that our method is a highly automated and reliable method for extracting gullies from satellite remote sensing images, which simplifies the process of gully extraction and provides us with an accurate guide to locate the location of gullies, analyze the shape of gullies, and then provide accurate guidance for gully management.
Enhanced Prototypical Network with Customized Region-Aware Convolution for Few-Shot SAR ATR
Authors: Yu Xuelian , Yu Hailong , Liu Yi , Ren Haohao
Published: September 2024

With the prosperous development and successful application of deep learning technologies in the field of remote sensing, numerous deep-learning-based methods have emerged for synthetic aperture radar (SAR) automatic target recognition (ATR) tasks over the past few years. Generally, most deep-learning-based methods can achieve outstanding recognition performance on the condition that an abundance of labeled samples are available to train the model. However, in real application scenarios, it is difficult and costly to acquire and to annotate abundant SAR images due to the imaging mechanism of SAR, which poses a big challenge to existing SAR ATR methods. Therefore, SAR target recognition in the situation of few-shot, where only a scarce few labeled samples are available, is a fundamental problem that needs to be solved. In this paper, a new method named enhanced prototypical network with customized region-aware convolution (CRCEPN) is put forward to specially tackle the few-shot SAR ATR tasks. To be specific, a feature-extraction network based on a customized and region-aware convolution is first developed. This network can adaptively adjust convolutional kernels and their receptive fields according to each SAR image’s own characteristics as well as the semantical similarity among spatial regions, thus augmenting its capability to extract more informative and discriminative features. To achieve accurate and robust target identity prediction under the few-shot condition, an enhanced prototypical network is proposed. This network can improve the representation ability of the class prototype by properly making use of training and test samples together, thus effectively raising the classification accuracy. Meanwhile, a new hybrid loss is designed to learn a feature space with both inter-class separability and intra-class tightness as much as possible, which can further upgrade the recognition performance of the proposed method. Experiments performed on the moving and stationary target acquisition and recognition (MSTAR) dataset, the OpenSARShip dataset, and the SAMPLE+ dataset demonstrate that the proposed method is competitive with some state-of-the-art methods for few-shot SAR ATR tasks.
A Highly Efficient Compressive Sensing Algorithm Based on Root-Sparse Bayesian Learning for RFPA Radar
Authors: Wang Ju , Shan Bingqi , Duan Song , Zhang Qin
Published: September 2024

Off-grid issues and high computational complexity are two major challenges faced by sparse Bayesian learning (SBL)-based compressive sensing (CS) algorithms used for random frequency pulse interval agile (RFPA) radar. Therefore, this paper proposes an off-grid CS algorithm for RFPA radar based on Root-SBL to address these issues. To effectively cope with off-grid issues, this paper derives a root-solving formula inspired by the Root-SBL algorithm for velocity parameters applicable to RFPA radar, thus enabling the proposed algorithm to directly solve the velocity parameters of targets during the fine search stage. Meanwhile, to ensure computational feasibility, the proposed algorithm utilizes a simple single-level hierarchical prior distribution model and employs the derived root-solving formula to avoid the refinement of velocity grids. Moreover, during the fine search stage, the proposed algorithm combines the fixed-point strategy with the Expectation-Maximization algorithm to update the hyperparameters, further reducing computational complexity. In terms of implementation, the proposed algorithm updates hyperparameters based on the single-level prior distribution to approximate values for the range and velocity parameters during the coarse search stage. Subsequently, in the fine search stage, the proposed algorithm performs a grid search only in the range dimension and uses the derived root-solving formula to directly solve for the target velocity parameters. Simulation results demonstrate that the proposed algorithm maintains low computational complexity while exhibiting stable performance for parameter estimation in various multi-target off-grid scenarios.
Spatial-Temporal Analysis of the Effects of Frost and Temperature on Vegetation in the Third Pole Based on Remote Sensing
Authors: Dong Caixia , Wang Xufeng , Li Zongxing , Xiao Jingfeng , Zhu Gaofeng , Li Xing
Published: September 2024

Frost events during the growing season can significantly impact vegetation function and structure. Solar-induced chlorophyll fluorescence (SIF) and the normalized difference vegetation index (NDVI) are two widely used proxies for measuring vegetation growth. However, the extent to which NDVI and SIF respond to frost events and how the responses vary under different temperature, precipitation, and shortwave radiation conditions are still unclear. In this study, spatially gridded meteorological data were employed to identify frost events during the growing season in the Third Pole. Subsequently, vegetation responses to the frost events were examined using remotely sensed SIF and NDVI data in different seasons in the Third Pole. During the growing season, the number of frost events declined faster from 2001 to 2009 than from 2010 to 2018. From 2001 to 2009, most alpine vegetation areas in the Third Pole exhibited greening trends. SIF exhibited a strong correlation with environmental factors and showed higher sensitivity to environmental factors compared to the NDVI. Over the past two decades, the impact of temperature and frost days on alpine vegetation has decreased while the impact of precipitation and radiation has increased. This suggests that the control mechanisms governing alpine vegetation are gradually shifting in response to ongoing climate change in the Third Pole. This study enhances our comprehension of frost changes in alpine regions during the growing season and enriches our understanding of how alpine vegetation responds to climate change.
Neural Network-Based Fusion of InSAR and Optical Digital Elevation Models with Consideration of Local Terrain Features
Authors: Gui Rong , Qin Yuanjun , Hu Zhi , Dong Jiazhen , Sun Qian , Hu Jun , Yuan Yibo , Mo Zhiwei
Published: September 2024

InSAR and optical techniques represent two principal approaches for the generation of large-scale Digital Elevation Models (DEMs). Due to the inherent limitations of each technology, a single data source is insufficient to produce high-quality DEM products. The increasing deployment of satellites has generated vast amounts of InSAR and optical DEM data, thereby providing opportunities to enhance the quality of final DEM products through the more effective utilization of the existing data. Previous research has established that complete DEMs generated by InSAR technology can be combined with optical DEMs to produce a fused DEM with enhanced accuracy and reduced noise. Traditional DEM fusion methods typically employ weighted averaging to compute the fusion results. Theoretically, if the weights are appropriately selected, the fusion outcome can be optimized. However, in practical scenarios, DEMs frequently lack prior information on weights, particularly precise weight data. To address this issue, this study adopts a fully connected artificial neural network for elevation fusion prediction. This approach represents an advancement over existing neural network models by integrating local elevation and terrain as input features and incorporating curvature as an additional terrain characteristic to enhance the representation of terrain features. We also investigate the impact of terrain factors and local terrain feature as training features on the fused elevation outputs. Finally, three representative study areas located in Oregon, USA, and Macao, China, were selected for empirical validation. The terrain data comprise InSAR DEM, AW3D30 DEM, and Lidar DEM. The results indicate that compared to traditional neural network methods, the proposed approach improves the Root-Mean-Squared Error (RMSE) ranges, from 5.0% to 12.3%, and the Normalized Median Absolute Deviation (NMAD) ranges, from 10.3% to 26.6%, in the test areas, thereby validating the effectiveness of the proposed method.
Cadastral-to-Agricultural: A Study on the Feasibility of Using Cadastral Parcels for Agricultural Land Parcel Delineation
Authors: Kim Han Sae , Song Hunsoo , Jung Jinha
Published: September 2024

Agricultural land parcels (ALPs) are essential for effective agricultural management, influencing activities ranging from crop yield estimation to policy development. However, traditional methods of ALP delineation are often labor-intensive and require frequent updates due to the dynamic nature of agricultural practices. Additionally, the significant variations across different regions and the seasonality of agriculture pose challenges to the automatic generation of accurate and timely ALP labels for extensive areas. This study introduces the cadastral-to-agricultural (Cad2Ag) framework, a novel approach that utilizes cadastral data as training labels to train deep learning models for the delineation of ALPs. Cadastral parcels, which are relatively widely available and stable elements in land management, serve as proxies for ALP delineation. Employing an adapted U-Net model, the framework automates the segmentation process using remote sensing images and geographic information system (GIS) data. This research evaluates the effectiveness of the proposed Cad2Ag framework in two U.S. regions—Indiana and California—characterized by diverse agricultural conditions. Through rigorous evaluation across multiple scenarios, the study explores diverse scenarios to enhance the accuracy and efficiency of ALP delineation. Notably, the framework demonstrates effective ALP delineation across different geographic contexts through transfer learning when supplemented with a small set of clean labels, achieving an F1-score of 0.80 and an Intersection over Union (IoU) of 0.67 using only 200 clean label samples. The Cad2Ag framework’s ability to leverage automatically generated, extensive, free training labels presents a promising solution for efficient ALP delineation, thereby facilitating effective management of agricultural land.