bluuebunny/crossref_metadata_2025 huggingface dataset:
Muscle Strength Moderates the Relationship between Nutritional Health Risk and Depression in Korean Older Adults
Authors: Kim Jeonghyeon , Kang Seamon , Hong Haeryun , Kang Hyunsik , Kim Ju-Hyoung , Woo Sang-Koo
Published: February 2022

Background: Little is known about the relationships between muscle strength and nutritional health risk with late-in-life depression. This study aimed to investigate the moderating effect of lower-extremity muscle strength on the relationship between nutritional health risk and depression in Korean older adults. Methods: Data obtained from 5949 women and 3971 men aged ≥ 65 years in the 2020 Korea Longitudinal Study on Aging were used in this study. Exposures included lower-extremity muscle strength and nutritional health risk. Lower-extremity muscle strength was measured with a modified sit-to-stand test. The nutritional health risk was assessed using a screening tool. Depression was defined as a score ≥ 8 points on the Geriatric Depression Scale (GDS). Results: Logistic regression analyses showed that depression was positively associated with nutritional health risk (p < 0.001) and inversely associated with lower-extremity muscle strength (p < 0.001). A moderation analysis with Andrew Hayes’ PROCESS macro showed a significant moderating effect of lower-extremity muscle strength (β = −0.119; 95% confidence interval, −0.172 to −0.066; p < 0.001) on the relationship between nutritional health risk and depression; the weaker was the muscle strength, the steeper was the slope of the GDS score for nutritional health risk. Conclusions: The current findings suggest the need for an intervention targeting both high nutritional risk and weak muscle strength as a therapeutic strategy against depression in Korean older adults.
Association between Dietary Nitrate, Nitrite Intake, and Site-Specific Cancer Risk: A Systematic Review and Meta-Analysis
Authors: Said Abasse Kassim , Essien Eno E. , Abbas Muhammad , Yu Xiaojin , Xie Weihua , Sun Jinfang , Akter Laboni , Cote Andre
Published: February 2022

Background: People consume nitrates, nitrites, nitrosamines, and NOCs compounds primarily through processed food. Many studies have yielded inconclusive results regarding the association between cancer and dietary intakes of nitrates and nitrites. This study aimed to quantify these associations across the reported literature thus far. Methods: We performed a systematic review following PRISMA and MOOSE guidelines. A literature search was performed using Web of Science, Embase, PubMed, the Cochrane library, and google scholar up to January 2020. STATA version 12.0 was used to conduct meta-regression and a two-stage meta-analysis. Results: A total of 41 articles with 13 different cancer sites were used for analysis. Of these 13 cancer types/sites, meta-regression analysis showed that bladder and stomach cancer risk was greater, and that pancreatic cancer risk was lower with increasing nitrite intakes. Kidney and bladder cancer risk were both lower with increasing nitrate intakes. When comparing highest to lowest (reference) categories of intake, meta-analysis of studies showed that high nitrate intake was associated with an increased risk of thyroid cancer (OR = 1.40, 95% CI: 1.02, 1.77). When pooling all intake categories and comparing against the lowest (reference) category, higher nitrite intake was associated with an increased risk of glioma (OR = 1.12, 95% CI: 1.03, 1.22). No other associations between cancer risk and dietary intakes of nitrates or nitrites were observed. Conclusion: This study showed varied associations between site-specific cancer risks and dietary intakes of nitrate and nitrite. Glioma, bladder, and stomach cancer risks were higher and pancreatic cancer risk was lower with higher nitrite intakes, and thyroid cancer risk was higher and kidney cancer risk lower with higher nitrate intakes. These data suggest type- and site-specific effects of cancer risk, including protective effects, from dietary intakes of nitrate and nitrite.
Effect of Magnesium Supplementation on Inflammatory Parameters: A Meta-Analysis of Randomized Controlled Trials
Authors: Veronese Nicola , Pizzol Damiano , Smith Lee , Dominguez Ligia J. , Barbagallo Mario
Published: February 2022

Magnesium (Mg) may have several beneficial effects on human health outcomes. One hypothesized mechanism eliciting such effects is the action of Mg on serum inflammatory parameters. However, studies on this topic to date have several important limitations. Therefore, the present systematic review and meta-analysis aimed to summarize the current state of the art of all randomized control trials (RCTs) investigating the effects of Mg supplementation versus placebo on serum parameters of inflammation. We searched several databases until 23 November 2021 for RCTs. Eligible studies were RCTs investigating the effect of oral Mg supplementation vs. placebo and having serum inflammatory markers as an outcome. Among 2484 papers initially screened, 17 randomized controlled trials (889 participants; mean age: 46 years; females: 62.5%) were included. Generally, a low risk of bias was present. In meta-analysis, Mg supplementation significantly decreased serum C reactive protein (CRP) and increased nitric oxide (NO) levels. In descriptive findings, Mg supplementation significantly reduced plasma fibrinogen, tartrate-resistant acid phosphatase type 5, tumor necrosis factor-ligand superfamily member 13B, ST2 protein, and IL-1. In conclusion, Mg supplementation may significantly reduce different human inflammatory markers, in particular serum CRP and NO levels.
Nutritional Habits and Recommendations in the COVID-19 Era
Authors: Zampelas Antonis
Published: February 2022

The most recent coronavirus outbreak is that of 2019 SARS-CoV-2, which causes the Coronavirus Disease-2019 (COVID-19) [...]
Unfavorable Dietary Quality Contributes to Elevated Risk of Ischemic Stroke among Residents in Southwest China: Based on the Chinese Diet Balance Index 2016 (DBI-16)
Authors: Wang Yingying , Su Xu , Chen Yun , Wang Yiying , Zhou Jie , Liu Tao , Wang Na , Fu Chaowei
Published: February 2022

Background: Little is known about the effects of dietary quality on the risk of ischemic stroke among Southwest Chinese, and evidence from prospective studies is needed. We aimed to evaluate the associations of ischemic stroke with dietary quality assessed by the Chinese Diet Balance Index 2016 (DBI-2016). Methods: The Guizhou Population Health Cohort Study (GPHCS) recruited 9280 residents aged 18 to 95 years from 12 areas in Guizhou Province, Southwest China. Baseline investigations, including information collections of diet and demographic characteristics, and anthropometric measurements were performed from 2010 to 2012. Dietary quality was assessed by using DBI-2016. The primary outcome was incident ischemic stroke diagnosed according to the International Classification of Diseases 10th revision (ICD-10) until December 2020. Data analyzed in the current study was from 7841 participants with complete information of diet assessments and ischemic stroke certification. Cox proportional hazards models were used to estimate the risk of ischemic stroke associated with dietary quality. Results: During a median follow-up of 6.63 years (range 1.11 to 9.53 years), 142 participants were diagnosed with ischemic stroke. Participants with ischemic stroke had a more excessive intake of cooking oils, alcoholic beverages, and salt, and had more inadequacy in meats than those without ischemic stroke. (p < 0.05). Compared with participants in the lowest quartile (Q1), those in the highest quartile (Q4) of the higher bound score (HBS) and of the dietary quality distance (DQD) had an elevated risk for ischemic stroke, with the corresponding hazard ratios (HRs) of 3.31 (95%CI: 1.57–6.97) and 2.26 (95%CI: 1.28–4.00), respectively, after adjustment for age, ethnic group, education level, marriage status, smoking and waist circumference, and the medical history of diabetes and hypertension at baseline. In addition, excessive intake levels (score 1–6) of cooking oils, excessive intake levels (score 1–6) of salt, and inadequate intake levels (score −12 to −7) of dietary variety were positively associated with an increased risk for ischemic stroke, with the multiple HRs of 3.00 (95%CI: 1.77–5.07), 2.03 (95%CI: 1.33–3.10) and 5.40 (95%CI: 1.70–17.20), respectively. Conclusions: Our results suggest that unfavorable dietary quality, including overall excessive consumption, excessive intake of cooking oils and salt, or under adequate dietary diversity, may increase the risk for ischemic stroke.
Exploring the Natural Compounds in Flavonoids for Their Potential Inhibition of Cancer Therapeutic Target MEK1 Using Computational Methods
Authors: AlZahrani Wejdan M. , AlGhamdi Shareefa A. , Zughaibi Torki A. , Rehan Mohd
Published: February 2022

The Mitogen-Activated Protein Kinase (MAPK) signaling pathway plays an important role in cancer cell proliferation and survival. MAPKs’ protein kinases MEK1/2 serve as important targets in drug designing against cancer. The natural compounds’ flavonoids are known for their anticancer activity. This study aims to explore flavonoids for their inhibition ability, targeting MEK1 using virtual screening, molecular docking, ADMET prediction, and molecular dynamics (MD) simulations. Flavonoids (n = 1289) were virtually screened using molecular docking and have revealed possible inhibitors of MEK1. The top five scoring flavonoids based on binding affinity (highest score for MEK1 is −10.8 kcal/mol) have been selected for further protein–ligand interaction analysis. Lipinski’s rule (drug-likeness) and absorption, distribution, metabolism, excretion, and toxicity predictions were followed to find a good balance of potency. The selected flavonoids of MEK1 have been refined with 30 (ns) molecular dynamics (MD) simulation. The five selected flavonoids are strongly suggested to be promising potent inhibitors for drug development as anticancer therapeutics of the therapeutic target MEK1.
7-Acetoxyhorminone from Salvia multicaulis Vahl. as Promising Inhibitor of 3-Hydroxy-3-methylglutaryl Coenzyme A (HMG-CoA) Reductase
Authors: Yigitkan Serkan , Ertas Abdulselam , Salmas Ramin Ekhteiari , Firat Mehmet , Orhan Ilkay Erdogan
Published: February 2022

3-Hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase is a key enzyme involved in cholesterol biosynthesis and one of the most important targets for the treatment of hypercholesterolemia. A limited number of studies on the HMG-CoA reductase inhibitory potential of natural products are available. Thus, in the current study, we aimed to test the HMG-CoA reductase inhibitory capacity of extracts from the roots and aerial parts of Salvia multicaulis Vahl., through activity-guided isolation. Our findings revealed that the root extract prepared with dichloromethane–acetone (1:1) showed the highest inhibition (71.97 ± 0.37%) at 100 µg/mL. The extract was then initially fractionated by column chromatography and the obtained fractions were monitored by thin layer chromatography. Fractions which were similar to each other were combined and a total of 15 fractions were obtained. Further conventional chromatographic studies were carried out on the active fractions. Based on these fractions, 10 known compounds, comprising 9 terpenes and 1 steroid derivative in total, were isolated and their structures were verified by a combination of IT-TOF-MS, and 1D and 2D NMR techniques. According to the enzyme inhibition data of the identified compounds, 7-acetoxyhorminone exerted the highest inhibition (84.15 ± 0.10%, IC50 = 63.6 ± 1.21 µg/mL). The molecular docking experiments on 7-acetoxyhorminone and horminone indicated that both compounds strongly bind to the active site of the enzyme.
Associations of Plasma Concentration Profiles of Dapagliflozin, a Selective Inhibitor of Sodium–Glucose Co-Transporter Type 2, with Its Effects in Japanese Patients with Type 2 Diabetes Mellitus
Authors: Hayakawa Tetsuo , Kato Ken-Ichiro , Kobuchi Shinji , Kataoka Kaede , Sakaeda Toshiyuki
Published: February 2022

This study was conducted to evaluate the long-term plasma concentration profiles of dapagliflozin and its effects on the glycated hemoglobin (HbA1c) level, body weight, and estimated glomerular filtration rate (eGFR) in 72 Japanese outpatients with type 2 diabetes mellitus (T2DM) receiving metformin and a dipeptidyl peptidase-4 inhibitor. At baseline, HbA1c level, body weight, and eGFR were 6.9 ± 0.6%, 77.9 ± 13.5 kg, and 78.8 ± 20.7 mL/min/1.73 m2, respectively. A once-daily oral dose of 5 mg dapagliflozin was administered, and its trough plasma concentrations were evaluated at 1, 3, 6, 9, and 12 months. In this study, the patients with stable dapagliflozin concentrations were defined, based on a well-organized clinical trial, as those with average plasma concentrations of 2–5 ng/mL with a coefficient of variation <30%; these values were achieved if patients complied with their once-daily dosage. Multivariate analysis showed a significant decrease in the HbA1c levels among patients with stable concentrations (−0.6 ± 0.4%, p < 0.01), which was greater than the mean change among all 72 patients (−0.2 ± 0.5%, p < 0.01). The patients’ mean body weight also decreased (−2.3 ± 4.0 kg, p = 0.060). Average plasma concentrations ranged from 1.6 to 11.8 ng/mL; however, multivariate analysis indicated it was unrelated to the HbA1c-lowering effect. In conclusion, the long-term stability of plasma dapagliflozin concentration was important in lowering HbA1c level, and a once-daily oral dose of 5 mg was sufficient in achieving this effect.
Understanding the Impact of Age-Related Changes in Pediatric GI Solubility by Multivariate Data Analysis
Authors: Guimarães Mariana , Maharaj Anil , Edginton Andrea , Vertzoni Maria , Fotaki Nikoletta
Published: February 2022

The aim of this study was to understand drug solubilization as a function of age and identify drugs at risk of altered drug solubility in newborns and young infants in comparison to adults. Multivariate statistical analysis was used to understand drug solubilization as a function of drug’s physicochemical properties and the composition of gastrointestinal fluids. The solubility of seven poorly soluble compounds was assessed in adult and age-specific fasted and fed state biorelevant media. Partial least squares regression (PLS-R) was used to assess the influence of (i) drug physicochemical properties and (ii) age-related changes in simulated GI fluids, as well as (iii) their interactions, on the pediatrics-to-adult solubility ratio (Sp/Sa (%)). For five out of seven of the compounds investigated, Sp/Sa (%) values fell outside of the 80–125% limits in at least one of the pediatric media. Lipophilicity was responsible for driving drug solubility differences between adults and children in all the biorelevant media investigated, while drug ionization was most relevant in the fed gastric media, and the fasted/fed intestinal media. The concentration of bile salts and lecithin in the fasted and fed intestinal media was critical in influencing drug solubility, while food composition (i.e., cow’s milk formula vs. soy formula) was a critical parameter in the fed gastric state. Changes in GI fluid composition between younger pediatric patients and adults can significantly alter drug luminal solubility. The use of pediatric biorelevant media can be helpful to identify the risk of altered drug solubilization in younger patients during drug development.
Fast-Dissolving Nifedipine and Atorvastatin Calcium Electrospun Nanofibers as a Potential Buccal Delivery System
Authors: Alshaya Hassa A. , Alfahad Ahmed J. , Alsulaihem Fatemah M. , Aodah Alhassan H. , Alshehri Abdullah A. , Almughem Fahad A. , Alfassam Haya A. , Aldossary Ahmad M. , Halwani Abdulrahman A. , Bukhary Haitham A. , Badr Moutaz Y. , Massadeh Salam , Alaamery Manal , Tawfik Essam A.
Published: February 2022

Geriatric patients are more likely to suffer from multiple chronic diseases that require using several drugs, which are commonly ingested. However, to enhance geriatric patients’ convenience, the electrospun nanofiber system was previously proven to be a successful alternative for the existing oral dosage forms, i.e., tablets and capsules. These nanofibers prepared either as single- or multi-layered fibers could hold at least one active compound in each layer. They might also be fabricated as ultra-disintegrated fibrous films for oral cavity administration, i.e., buccal or sublingual, to improve the bioavailability and intake of the administered drugs. Therefore, in this work, a combination of nifedipine and atorvastatin calcium, which are frequently prescribed for hypertension and hyperlipidemia patients, respectively, was prepared in a coaxial electrospinning system for buccal administration. Scanning electron microscopy image showed the successful preparation of smooth, non-beaded, and non-porous surfaces of the drug-loaded nanofibers with an average fiber diameter of 968 ± 198 nm. In contrast, transmission electron microscopy distinguished the inner and outer layers of those nanofibers. The disintegration of the drug-loaded nanofibers was ≤12 s, allowing the rapid release of nifedipine and atorvastatin calcium to 61% and 47%, respectively, after 10 min, while a complete drug release was achieved after 120 min. In vitro, a drug permeation study using Franz diffusion showed that the permeation of both drugs from the core–shell nanofibers was enhanced significantly (p < 0.05) compared to the drugs in a solution form. In conclusion, the development of drug-loaded nanofibers containing nifedipine and atorvastatin calcium can be a potential buccal delivery system.
Gallic Acid as a Non-Selective Inhibitor of α/β-Hydrolase Fold Enzymes Involved in the Inflammatory Process: The Two Sides of the Same Coin
Authors: Toyama Marcos Hikari , Rogero Airam , de Moraes Laila Lucyane Ferreira , Fernandes Gustavo Antônio , da Cruz Costa Caroline Ramos , Belchor Mariana Novo , De Carli Agatha Manzi , de Oliveira Marcos Antônio
Published: February 2022

(1) Background: Gallic acid (GA) has been characterized as an effective anti-inflammatory, antivenom, and promising drug for therapeutic use. (2/3) Methods and Results: GA was identified from ethanolic extract of fresh pitanga (Eugenia uniflora) leaves, which was identified using commercial GA. Commercial GA neutralized the enzymatic activity of secretory PLA2 (sPLA2) by inhibiting the active site and inducing changes in the secondary structure of the enzyme. Pharmacological edema assays showed that GA strongly decreased edema when the compound was previously incubated with sPLA2. However, prior treatment of GA (30 min before) significantly increased the edema and myotoxicity induced by sPLA2. The molecular docking results of GA with platelet-acetylhydrolase (PAF-AH) and acetylcholinesterase reveal that this compound was able to interact with the active site of both molecules, inhibiting the hydrolysis of platelet-activating factor (PAF) and acetylcholine (ACh). (4) Conclusion: GA has a great potential application; however, our results show that this compound can also induce adverse effects in previously treated animals. Additionally, the increased edema and myotoxicity observed experimentally in GA-treated animals may be due to the inhibition of PAF-AH and Acetylcholinesterase.
A Survey of Enhanced Cold Tolerance and Low-Temperature-Induced Anthocyanin Accumulation in a Novel Zoysia japonica Biotype
Authors: Jin Hai-Xiang , Jiang Ming , Yang Jian-Feng , Wu Zhi-Hao , Ma Long-Long , Wang Cong-Cong , Liang Chen , Ning Xin-Yi , Ge Liang-Fa , Chen Shu
Published: February 2022

Zoysia japonica is a warm-season turfgrass that is extensively used in landscaping, sports fields, and golf courses worldwide. Uncovering the low-temperature response mechanism of Z. japonica can help to accelerate the development of new cold-tolerant cultivars, which could be used to prolong the ornamental and usage duration of turf. A novel Z. japonica biotype, YueNong-9 (YN-9), was collected from northeastern China for this study. Phenotypic measurements, cold-tolerance investigation, and whole-transcriptome surveys were performed on YN-9 and LanYin-3 (LY-3), the most popular Z. japonica cultivar in Southern China. The results indicated the following: YN-9 has longer second and third leaves than LY-3; when exposed to the natural low temperature during winter in Guangzhou, YN-9 accumulated 4.74 times more anthocyanin than LY-3; after cold acclimation and freezing treatment, 83.25 ± 9.55% of YN-9 survived while all LY-3 leaves died, and the dark green color index (DGCI) value of YN-9 was 1.78 times that of LY-3; in YN-9, there was a unique up-regulation of Phenylalanine ammonia-lyase (PAL), Homeobox-leucine Zipper IV (HD-ZIP), and ATP-Binding Cassette transporter B8 (ABCB8) expressions, as well as a unique down-regulation of zinc-regulated transporters and iron-regulated transporter-like proteins (ZIPs) expression, which may promote anthocyanin biosynthesis, transport, and accumulation. In conclusion, YN-9 exhibited enhanced cold tolerance and is thus an excellent candidate for breeding cold-tolerant Z. japonica variety, and its unique low-temperature-induced anthocyanin accumulation and gene responses provide ideas and candidate genes for the study of low-temperature tolerance mechanisms and genetic engineering breeding.
Sensing beyond Senses: An Overview of Outstanding Strides in Architecting Nanopolymer-Enabled Sensors for Biomedical Applications
Authors: Malini S. , Roy Arpita , Raj Kalyan , Raju K. , Ali Ismat , Mahesh B. , Yadav Krishna , Islam Saiful , Jeon Byong-Hun , Lee Sean
Published: February 2022

Nano-enabled sensing is an expanding interdisciplinary field of emerging science with dynamic multifunctional detecting capabilities, equipped with a wide range of multi-faceted nanomaterial having diverse dimensions and composition. They have proven to be highly robust, sensitive, and useful diagnostic tools ranging from advanced industrial processes to ordinary consumer products. As no single nanomaterial has proved to be unparalleled, recent years has witnessed a large number of nanomaterial-based sensing strategies for rapid detection and quantification of processes and substances with a high degree of reliability. Nano-furnished platforms, because of easy fabrication methods and chemical versatility, can serve as ideal sensing means through different transduction mechanisms. This article, through a unified experimental-theoretical approach, uses literature of recent years to introduce, evaluate, and analyze significant developments in the area of nanotechnology-aided sensors incorporating the various classes of nanomaterial. Addressing the broad interests, the work also summarizes the sensing mechanisms using schematic illustrations, attempts to integrate the performance of different categories of nanomaterials in the design of sensors, knowledge gaps, regulatory aspects, future research directions, and challenges of implementing such techniques in standalone devices. In view of a dependency of analysis and testing on sustained growth of sensor-supported platforms, this article inspires the scientific community for more attention in this field.
Influence of Biomimetically Mineralized Collagen Scaffolds on Bone Cell Proliferation and Immune Activation
Authors: Bacakova Lucie , Novotna Katarina , Hadraba Daniel , Musilkova Jana , Slepicka Petr , Beran Milos
Published: February 2022

Collagen, as the main component of connective tissue, is frequently used in various tissue engineering applications. In this study, porous sponge-like collagen scaffolds were prepared by freeze-drying and were then mineralized in a simulated body fluid. The mechanical stability was similar in both types of scaffolds, but the mineralized scaffolds (MCS) contained significantly more calcium, magnesium and phosphorus than the unmineralized scaffolds (UCS). Although the MCS contained a lower percentage (~32.5%) of pores suitable for cell ingrowth (113–357 μm in diameter) than the UCS (~70%), the number of human-osteoblast-like MG-63 cells on days 1, 3 and 7 after seeding was higher on MCS than on UCS, and the cells penetrated deeper into the MCS. The cell growth in extracts prepared by eluting the scaffolds for 7 days in a cell culture medium was also markedly higher in the MCS extracts, as indicated by real-time monitoring in the sensory xCELLigence system for 7 days. From this point of view, MCS are more promising for bone tissue engineering than UCS. However, MCS evoked a more pronounced inflammatory response than UCS, as indicated by the production of tumor necrosis factor-alpha (TNF-α) in macrophage-like RAW 264.7 cells in cultures on these scaffolds.
Recovery Observations from Alkali, Nanoparticles and Polymer Flooding as Combined Processes
Authors: Hincapie Rafael E. , Borovina Ante , Neubauer Elisabeth , Tahir Muhammad , Saleh Samhar , Arekhov Vladislav , Biernat Magdalena , Clemens Torsten
Published: February 2022

We have studied wettability alterations through imbibition/flooding and their synergy with interfacial tension (IFT) for alkalis, nanoparticles and polymers. Thus, the total acid number (TAN) of oil may determine the wetting-state of the reservoir and influence recovery and IFT. Data obtained demonstrate how the oil TAN number (low and high), chemical agent and reservoir mineralogy influence fluid–fluid and rock–fluid interactions. We used a laboratory evaluation workflow that combines complementary assessments such as spontaneous imbibition tests, IFT, contact angle measurements and selected core floods. The workflow evaluates wettability alteration, IFT changes and recovery when injecting alkalis, nanoparticles and polymers, or a combination of them. Dynamics and mechanisms of imbibition were tracked by analyzing the recovery change with the inverse bond number. Three sandstone types (outcrops) were used, which mainly differed in clay content and permeability. Oils with low and high TANs were used, the latter from the potential field pilot 16 TH reservoir in the Matzen field (Austria). We have investigated and identified some of the conditions leading to increases in recovery rates as well as ultimate recovery by the imbibition of alkali, nanoparticle and polymer aqueous phases. This study presents novel data on the synergy of IFT, contact angle Amott imbibition, and core floods for the chemical processes studied.
Bioactive Graphene Quantum Dots Based Polymer Composite for Biomedical Applications
Authors: Mousavi Seyyed Mojtaba , Hashemi Seyyed Alireza , Kalashgrani Masoomeh Yari , Omidifar Navid , Bahrani Sonia , Vijayakameswara Rao Neralla , Babapoor Aziz , Gholami Ahmad , Chiang Wei-Hung
Published: February 2022

Today, nanomedicine seeks to develop new polymer composites to overcome current problems in diagnosing and treating common diseases, especially cancer. To achieve this goal, research on polymer composites has expanded so that, in recent years, interdisciplinary collaborations between scientists have been expanding day by day. The synthesis and applications of bioactive GQD-based polymer composites have been investigated in medicine and biomedicine. Bioactive GQD-based polymer composites have a special role as drug delivery carriers. Bioactive GQDs are one of the newcomers to the list of carbon-based nanomaterials. In addition, the antibacterial and anti-diabetic potentials of bioactive GQDs are already known. Due to their highly specific surface properties, π-π aggregation, and hydrophobic interactions, bioactive GQD-based polymer composites have a high drug loading capacity, and, in case of proper correction, can be used as an excellent option for the release of anticancer drugs, gene carriers, biosensors, bioimaging, antibacterial applications, cell culture, and tissue engineering. In this paper, we summarize recent advances in using bioactive GQD-based polymer composites in drug delivery, gene delivery, thermal therapy, thermodynamic therapy, bioimaging, tissue engineering, bioactive GQD synthesis, and GQD green resuscitation, in addition to examining GQD-based polymer composites.
Terahertz Spectroscopic Analysis in Protein Dynamics: Current Status
Authors: Mancini Tiziana , Mosetti Rosanna , Marcelli Augusto , Petrarca Massimo , Lupi Stefano , D’Arco Annalisa
Published: February 2022

Proteins play a key role in living organisms. The study of proteins and their dynamics provides information about their functionality, catalysis and potential alterations towards pathological diseases. Several techniques are used for studying protein dynamics, e.g., magnetic resonance, fluorescence imaging techniques, mid-infrared spectroscopy and biochemical assays. Spectroscopic analysis, based on the use of terahertz (THz) radiation with frequencies between 0.1 and 15 THz (3–500 cm−1), was underestimated by the biochemical community. In recent years, however, the potential of THz spectroscopy in the analysis of both simple structures, such as polypeptide molecules, and complex structures, such as protein complexes, has been demonstrated. The THz absorption spectrum provides some information on proteins: for small molecules the THz spectrum is dominated by individual modes related to the presence of hydrogen bonds. For peptides, the spectral information concerns their secondary structure, while for complex proteins such as globular proteins and viral glycoproteins, spectra also provide information on collective modes. In this short review, we discuss the results obtained by THz spectroscopy in the protein dynamics investigations. In particular, we will illustrate advantages and applications of THz spectroscopy, pointing out the complementary information it may provide.
Humanizing the It: Martin Buber on Technology and the Ethics of Things
Authors: Biemann Asher
Published: February 2022

Martin Buber’s writings on technology are scarce and seemingly subordinated to what he described in I and Thou as the “tyranny of the It”. But a closer look at his writings reveals, in fact, a life-long reflection on the dialogical potentiality of things—whether artworks, buildings, or machines—that echoed broader discourses on technology at the time. Beginning with Julius Goldstein’s Die Technik (1912), which Buber edited for his series Die Gesellschaft, and concluding with Buber’s reception and critique of Heidegger, especially during the 1950s, we can see that Buber critically engaged with the question of technology with respect to labor and community, art and artisanship, and the ethics of thinghood. The essay contextualizes Buber’s repeated call to “humanize technology” in early 20th-century debates on technology and in the post-1945 crisis of humanism. What it argues is that Buber framed technology not only through its aesthetic potential, as Werk, but also as another form of solidarity and care without which community and respect for our environment would not be possible.
Large-Scale Rice Mapping Using Multi-Task Spatiotemporal Deep Learning and Sentinel-1 SAR Time Series
Authors: Lin Zhixian , Zhong Renhai , Xiong Xingguo , Guo Changqiang , Xu Jinfan , Zhu Yue , Xu Jialu , Ying Yibin , Ting K. C. , Huang Jingfeng , Lin Tao
Published: February 2022

Timely and accurate cropland information at large spatial scales can improve crop management and support the government in decision making. Mapping the spatial extent and distribution of crops on a large spatial scale is challenging work due to the spatial variability. A multi-task spatiotemporal deep learning model, named LSTM-MTL, was developed in this study for large-scale rice mapping by utilizing time-series Sentinel-1 SAR data. The model showed a reasonable rice classification accuracy in the major rice production areas of the U.S. (OA = 98.3%, F1 score = 0.804), even when it only utilized SAR data. The model learned region-specific and common features simultaneously, and yielded a significant improved performance compared with RF and AtBiLSTM in both global and local training scenarios. We found that the LSTM-MTL model achieved a regional F1 score up to 10% higher than both global and local baseline models. The results demonstrated that the consideration of spatial variability via LSTM-MTL approach yielded an improved crop classification performance at a large spatial scale. We analyzed the input-output relationship through gradient backpropagation and found that low VH value in the early period and high VH value in the latter period were critical for rice classification. The results of in-season analysis showed that the model was able to yield a high accuracy (F1 score = 0.746) two months before rice maturity. The integration between multi-task learning and multi-temporal deep learning approach provides a promising approach for crop mapping at large spatial scales.
Effects of Mulching on Maize Yield and Evapotranspiration in the Heihe River Basin, Northwest China
Authors: Shen Qianxi , Niu Jun , Sivakumar Bellie , Lu Na
Published: February 2022

Plastic film mulching is an effective way to manage agricultural fields in water shortage areas. Through increasing the soil surface temperature at the early stage of crop growth and reducing the soil evaporation during the whole growth period, plastic film mulching can realize the effect of water saving and yield increase. This study examined the effects of plastic film mulching on crop yield and evapotranspiration (ET) in the Heihe River basin in Northwest China. By using remote sensing data, the gridding G-AquaCrop model was built to simulate the maize yield and ET in the basin under conditions of film mulching and no-film mulching. Through an analysis of changes in maize yield and ET before and after film mulching, suitable areas for film mulching in the whole basin were identified. Through comparative analysis, it was found that after plastic film mulching, maize yield in 12–41% of the Heihe River basin increased to a certain extent, reaching 8%. Furthermore, film mulching decreased ET by 5–30% in 34–41% of areas planted with maize. Based on these results, suggestions were made on suitable areas for expansion of maize cultivation to balance the benefits of water saving and production increase with environmental pollution. Furthermore, the way of assessing the suitable mulching area is obtained by examining the meteorological condition directly. The results of this study are of great significance for rational allocation of agricultural production resources and efficient utilization of agricultural water resources.
Mapping Sugarcane in Central India with Smartphone Crowdsourcing
Authors: Lee Ju Young , Wang Sherrie , Figueroa Anjuli Jain , Strey Rob , Lobell David B. , Naylor Rosamond L. , Gorelick Steven M.
Published: February 2022

In India, the second-largest sugarcane producing country in the world, accurate mapping of sugarcane land is a key to designing targeted agricultural policies. Such a map is not available, however, as it is challenging to reliably identify sugarcane areas using remote sensing due to sugarcane’s phenological characteristics, coupled with a range of cultivation periods for different varieties. To produce a modern sugarcane map for the Bhima Basin in central India, we utilized crowdsourced data and applied supervised machine learning (neural network) and unsupervised classification methods individually and in combination. We highlight four points. First, smartphone crowdsourced data can be used as an alternative ground truth for sugarcane mapping but requires careful correction of potential errors. Second, although the supervised machine learning method performs best for sugarcane mapping, the combined use of both classification methods improves sugarcane mapping precision at the cost of worsening sugarcane recall and missing some actual sugarcane area. Third, machine learning image classification using high-resolution satellite imagery showed significant potential for sugarcane mapping. Fourth, our best estimate of the sugarcane area in the Bhima Basin is twice that shown in government statistics. This study provides useful insights into sugarcane mapping that can improve the approaches taken in other regions.
Modelling Impacts of Environmental Water on Vegetation of a Semi-Arid Floodplain–Lakes System Using 30-Year Landsat Data
Authors: Wu Chunying , Webb James Angus , Stewardson Michael J.
Published: February 2022

River floodplains are among the most dynamic and diverse ecosystems on the planet. They are at risk of degradation due to river regulation and climate change. Environmental water has been delivered to floodplains to maintain environmental health by mimicking natural floods. It is important to understand the long-term effects of environmental water to floodplain vegetation to support its management. This study used Normalized Differences Vegetation index (NDVI) from the 30-year Landsat datasets of the Hattah Lakes floodplain in Australia to investigate the drivers of vegetation dynamics. We developed generalized additive mixed models (GAMM) to model responses of vegetation to environmental water, natural floods, precipitation, temperature, and distance to water across multiple spatial and temporal scales. We found the effect of environmental water on floodplain vegetation to be quite different from that of natural floods in both space and time. Vegetation in most areas of Hattah Lakes will respond to natural floods within one month of flooding, while positive responses to environmental water occur 1 to 3 months after inundation and are more restricted spatially. For environmental water planning, managers need to be aware of these differences. The implementation of new infrastructure to transport or retain environmental water on floodplains needs to be planned carefully, with continuous monitoring of rainfall and natural floods. Whilst environmental floods do not mimic the effect of natural floods, they do provide some positive benefits that can partially offset effects of reduced natural floods.
Evaluating Machine Learning and Remote Sensing in Monitoring NO2 Emission of Power Plants
Authors: Alnaim Ahmed , Sun Ziheng , Tong Daniel
Published: February 2022

Effective and precise monitoring is a prerequisite to control human emissions and slow disruptive climate change. To obtain the near-real-time status of power plant emissions, we built machine learning models and trained them on satellite observations (Sentinel 5), ground observed data (EPA eGRID), and meteorological observations (MERRA) to directly predict the NO2 emission rate of coal-fired power plants. A novel approach to preprocessing multiple data sources, coupled with multiple neural network models (RNN, LSTM), provided an automated way of predicting the number of emissions (NO2, SO2, CO, and others) produced by a single power plant. There are many challenges on overfitting and generalization to achieve a consistently accurate model simply depending on remote sensing data. This paper addresses the challenges using a combination of techniques, such as data washing, column shifting, feature sensitivity filtering, etc. It presents a groundbreaking case study on remotely monitoring global power plants from space in a cost-wise and timely manner to assist in tackling the worsening global climate.
Gravity Survey on the Oil-Bearing Dammam Dome (Eastern Saudi Arabia) and Its Implications
Authors: Chavanidis Konstantinos , Stampolidis Alexandros , Kirmizakis Panagiotis , Tranos Markos , Fedi Maurizio , Pasteka Roman , Al-Ramadan Khalid , Kaka SanLinn , Tsokas Grigorios N. , Soupios Pantelis
Published: February 2022

A detailed gravity survey with 235 measurements was carried out at the King Fahd University of Petroleum and Minerals campus, which is located at the crest of the oil-bearing Dammam Dome (Eastern Province of Saudi Arabia). This survey allows us to better understand the geometry of the underlying Dammam Dome and its tectonic regime. The acquired data were processed using conventional gravity data reduction techniques. The effectiveness of terrain correction was evaluated using several recently developed algorithms. Afterward, processed data were subject to geophysical filters for edge detection (terracing transformation and horizontal gradient) and depth estimation (tilt derivative and 3D inversion). 3D Bouguer maps were generated and compared to the proposed geological models for the Dammam Dome. The results show the existence of ENE-WSW striking tectonic lines, where two nearly vertical, km long tectonic lines were predominant. The orientation of these tectonic lines defines an NNW-SSE trend for the least principal stress axis (σ3) and an ENE-WSW trend for the σ1σ2 stress plane of the driving stress regime, fitting well with the transtension stress regime recently suggested for the area. More importantly, the results of this study demonstrate that the Dammam Dome was affected by the intraplate stresses transferred from the convergence between the Arabian and Eurasian plates along the Zagros orogeny.
Enhanced Ecosystem Services in China’s Xilingol Steppe during 2000–2015: Towards Sustainable Agropastoralism Management
Authors: Dou Huashun , Li Xiaobing , Gong Jirui , Wang Hong , Tian Yuqiang , Xuan Xiaojing , Wang Kai
Published: February 2022

Ecosystem services (ESs) provided by dryland regions are very vulnerable to environmental dynamics and management transformation, and it is still unclear how these services will be affected by the combined effects of accelerated climate variability and land-use changes at a regional macro level. In this study, the status, patterns and trends of ESs provided by the Xilingol steppe were quantitatively evaluated, and the impact of climate and land-use change on ESs were discussed. The results showed that favorable climatic conditions and the implementation of ecological policies had a substantial positive impact on regional vegetation restoration during 2000–2015. As a result of the vegetation greening, water retention and carbon sequestration increased significantly at rates of 16.01 m3 ha−1 and 1.75 g C m−2 yr−1, respectively. Soil loss caused by wind erosion, an ecosystem disservice, decreased significantly at a rate of −0.57 t ha−1 yr−1. Although several environmental factors had differing impacts on the ESs changes in the subregions, including the meadow, typical and desert steppes, the main factors that contributed to the enhancement of overall ESs benefits were the climatic humidification and the reduced grazing pressure in the entire study area. The above conclusion shows that, in the era of climate change, the implementation of sustainable farming–pastoral strategies can realize a “win-win” situation between ecological restoration and socioeconomic development in arid and semi-arid steppes.
Multiscale Feature Fusion Network Incorporating 3D Self-Attention for Hyperspectral Image Classification
Authors: Qing Yuhao , Huang Quanzhen , Feng Liuyan , Qi Yueyan , Liu Wenyi
Published: February 2022

In recent years, the deep learning-based hyperspectral image (HSI) classification method has achieved great success, and the convolutional neural network (CNN) method has achieved good classification performance in the HSI classification task. However, the convolutional operation only works with local neighborhoods, and is effective in extracting local features. It is difficult to capture interactive features over long distances, which affects the accuracy of classification to some extent. At the same time, the data from HSI have the characteristics of three-dimensionality, redundancy, and noise. To solve these problems, we propose a 3D self-attention multiscale feature fusion network (3DSA-MFN) that integrates 3D multi-head self-attention. 3DSA-MFN first uses different sized convolution kernels to extract multiscale features, samples the different granularities of the feature map, and effectively fuses the spatial and spectral features of the feature map. Then, we propose an improved 3D multi-head self-attention mechanism that provides local feature details for the self-attention branch, and fully exploits the context of the input matrix. To verify the performance of the proposed method, we compare it with six current methods on three public datasets. The experimental results show that the proposed 3DSA-MFN achieves competitive classification and highlights the HSI classification task.
Integrating Remotely Sensed Leaf Area Index with Biome-BGC to Quantify the Impact of Land Use/Land Cover Change on Water Retention in Beijing
Authors: Huang Binbin , Yang Yanzheng , Li Ruonan , Zheng Hua , Wang Xiaoke , Wang Xuming , Zhang Yan
Published: February 2022

Maintaining or increasing water retention in ecosystems (WRE) can reduce floods and increase water resource provision. However, few studies have taken the effect of the spatial information of vegetation structure into consideration when assessing the effects of land use/land cover (LULC) change on WRE. In this study, we integrated the remotely sensed leaf area index (LAI) into the ecosystem process-based Biome-BGC model to analyse the impact of LULC change on the WRE of Beijing between 2000 and 2015. Our results show that the volume of WRE increased by approximately 8.58 million m3 in 2015 as compared with 2000. The volume of WRE in forests increased by approximately 26.74 million m3, while urbanization, cropland expansion and deforestation caused the volume of WRE to decline by 11.96 million m3, 5.86 million m3 and 3.20 million m3, respectively. The increased WRE contributed by unchanged forests (14.46 million m3) was much greater than that of new-planted forests (12.28 million m3), but the increase in WRE capacity per unit area in new-planted forests (124.69 ± 14.30 m3/ha) was almost tenfold greater than that of unchanged forests (15.60 ± 7.85 m3/ha). The greater increase in WRE capacity in increased forests than that of unchanged forests was mostly due to the fact that the higher LAI in unchanged forests induced more evapotranspiration to exhaust more water. Meanwhile, the inverted U-shape relationship that existed between the forest LAI and WRE implied that continued increased LAI in forests probably caused the WRE decline. This study demonstrates that integrating remotely sensed LAI with the Biome-BGC model is feasible for capturing the impact of LULC change with the spatial information of vegetation structure on WRE and reduces uncertainty.
Ship Detection in SAR Images Based on Multi-Scale Feature Extraction and Adaptive Feature Fusion
Authors: Zhou Kexue , Zhang Min , Wang Hai , Tan Jinlin
Published: February 2022

Deep learning has attracted increasing attention across a number of disciplines in recent years. In the field of remote sensing, ship detection based on deep learning for synthetic aperture radar (SAR) imagery is replacing traditional methods as a mainstream research method. The multiple scales of ship objects make the detection of ship targets a challenging task in SAR images. This paper proposes a new methodology for better detection of multi-scale ship objects in SAR images, which is based on YOLOv5 with a small model size (YOLOv5s), namely the multi-scale ship detection network (MSSDNet). We construct two modules in MSSDNet: the CSPMRes2 (Cross Stage Partial network with Modified Res2Net) module for improving feature representation capability and the FC-FPN (Feature Pyramid Network with Fusion Coefficients) module for fusing feature maps adaptively. Firstly, the CSPMRes2 module introduces modified Res2Net (MRes2) with a coordinate attention module (CAM) for multi-scale features extraction in scale dimension, then the CSPMRes2 module will be used as a basic module in the depth dimension of the MSSDNet backbone. Thus, our backbone of MSSDNet has the capabilities of features extraction in both depth and scale dimensions. In the FC-FPN module, we set a learnable fusion coefficient for each feature map participating in fusion, which helps the FC-FPN module choose the best features to fuse for multi-scale objects detection tasks. After the feature fusion, we pass the output through the CSPMRes2 module for better feature representation. The performance evaluation for this study is conducted using an RTX2080Ti GPU, and two different datasets: SSDD and SARShip are used. These experiments on SSDD and SARShip datasets confirm that MSSDNet leads to superior multi-scale ship detection compared with the state-of-the-art methods. Moreover, in comparisons of network model size and inference time, our MSSDNet also has huge advantages with related methods.