bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mycochemical screening reveals exopolysaccharide secretion, antioxidant and larvicidal activities of three oyster mushrooms
Authors: Asemoloye Michael D , Sunmola Nurudeen , Jonathan Gbolagade , Chikwem John 
Published: October 2021

AbstractBACKGROUNDHigher fungi such as oyster mushrooms have been well reported to have vast therapeutic and nutritive importance due to their bioactive constituents. Today, many interesting facts are also emerging regarding their importance in pest control. In this study,Pleurotus floridanus,P. ostreatusandP. sajor‐cajuwere studied for exopolysacharide (EPS) and antioxidant production under different carbon sources, and assayed for larvicidal properties.RESULTSWe observed a positive response of these mushrooms to carbon sources. The highest EPS was produced byP. sajor‐cajuunder sucrose carbon source, whereasP. ostreatusandP. floridanuspreferred glucose. The antioxidant activity of their EPS was confirmed using radical scavenging of 1,1‐diphenyl‐2‐picrylhydrazyl and potassium ferricyanide reduction methods. We also established the inhibition of lipid peroxidation by the EPS produced by these mushrooms, although this was concentration dependent, whileP. floridanusEPS had the highest antioxidant properties. An EPS concentration of 100 mg L−1from all the mushrooms was sufficient for inhibition of lipid peroxidation; this also showed a significant difference from the scavenging effect of butylated hydroxytoluene. All the mushroom extracts in this study had positive inhibitory effects on the late third and early fourth stages ofAnopheles gambiae. However, they were significantly different from each other asP. floridanusrecorded a lethal concentration (LC50) of 0.0.563,P. ostreatushad an LC50of 0.352, whileP. sajor‐cajuhad an LC50of 0.715.CONCLUSIONThis study affirms the influence of carbon source on EPS production by selected oyster mushrooms, and reveals their antioxidant properties and potential applications in pest control. © 2021 Society of Chemical Industry.
New insights into moisture sorption characteristics, nutritional composition, and antioxidant and morphological properties of dried duckweed [Wolffia arrhiza (L.) Wimm]
Authors: Masavang Supuksorn , Winckler Pascale , Tira‐umphon Arak , Phahom Traiphop 
Published: October 2021

AbstractBACKGROUNDDuckweed has been considered as an alternative future food material as a result of its high nutritional values, although it also has a high moisture content resulting in a short shelf life. Moisture sorption isotherms are used to design dehydration and storage conditions to prolong the shelf life food products. To date, information regarding the sorption isotherm of duckweed has not been reported. Scanning electron microscopy (SEM) is frequently used to study food microstructure. However, this technique has to be performed under high‐vacuum conditions and takes a long time. In the present study, two‐photon imaging microscopy was selected to investigate the microstructure of dried duckweed instead of SEM.RESULTSAmong five sorption isotherm models, the Peleg model gave the highest goodness of fit. The monolayer moisture content (M0) of duckweed was in the range 7.43–7.92% dry basis (d.b.) and 8.87–8.86% d.b. for the GAB and BET multilayer kinetic models, respectively. The moisture changing behavior at each relative humidity step could be described by two exponential and reaction order kinetics. A clear cell structure (hexagonal shape) and stomata, as well as structural images (both 2D and 3D), were obtained using the two‐photon microscopy technique.CONCLUSIONThe Peleg model best described the moisture sorption behaviors of dried duckweed and the shape of sorption isotherms were classified as type III isotherm. The M0 of dried duckweed ranged from 7.43 to 8.86% d.b. Two‐photon microscopy was a potent tool for investigating the microstructure and composition of dried duckweed. © 2021 Society of Chemical Industry.
Surgical phocomelia or phoco‐reduction as a method of limb salvage for sarcomas of the upper limb: A suitable alternative to amputation
Authors: Kapoor Love , Banjara Roshan , Kumar Venkatesan S. , Khan Shah A. 
Published: October 2021

AbstractBackgroundReconstruction following resection of sarcomas of the upper extremity with methods described in the prevalent literature may not be possible in few selected cases. We describe surgical phocomelia or phoco‐reduction as a method of limb salvage in such cases of extensive sarcomas of the upper limb with its functional and oncological outcomes.MethodsEvaluation of functional and oncological outcomes was performed for 11 patients who underwent surgical phocomelia or phoco‐reduction for extensive sarcomas of the upper limb between 2010 and 2019.ResultsThe mean follow‐up period in the study was 27.8 months. Five patients required a segmental resection including the entire humerus while six patients underwent segmental resection around the elbow with a mean resection length of 21.5 cm. Mean Musculoskeletal Tumor Society 93 score was 22 depicting a good functional outcome. Mean handgrip strength on the operated side was 62% of the contralateral side with preservation of useful hand function. Meantime to humeroulnar union was 6.7 months. Radial nerve palsy and implant failure occurred in one patient each. No patient developed local recurrence while three patients died of metastasis.ConclusionSurgical phocomelia is a prudent alternative to severely incapacitating amputations in situations where other reconstruction methods are not feasible.
The spatiotemporal patterns and pathways of forest transition in China
Authors: Lu Longhui , Marcos‐Martinez Raymundo , Xu Yueqing , Huang An , Duan Yaming , Ji Zhengxin , Huang Ling 
Published: October 2021

AbstractChina experienced a shift from net forest losses to gains (forest transition) between 1976 and 1981. Such transition has increased timber volume in natural forests and expanded the provision of forests ecosystem services. However, the timing, magnitude, and impact of the forest transition varied at provincial scales due to heterogeneous socio‐economic and institutional conditions. The aim of this study is to quantify the impact of spatial drivers of forest transition in China through integrated comparative and spatial regression methods. This approach allows the documentation of feedbacks and interactions of theoretical pathways to forest transition at different geographical scales, which is of relevance for large‐scale land restoration efforts. Our analysis also accounts for changes in forest volumes, a parameter that is usually not studied in the forest transition literature. Here, we used key indicators of demographic, economic, agricultural, and urbanization processes coupled with forest area data to investigate factors influencing forest transitions at multiple geographic scales between 1973 and 2013. Stepwise and geographically weighted regression models were adapted to quantify the key drivers' integrated and distributed magnitude effects on forest transition patterns, respectively. We assessed changes across forest types (i.e., primary and secondary forests, plantation forests) and investigated pathways to forest transition at provincial scales. The results indicate that increasing demand for timber and other forest ecosystem services, rising gross domestic product and population, forest policy, and increasing employment in the industry and service sectors generated multiple pathways to forest transition. The impact of those drivers varied within provinces, and some transition pathways were more relevant than others at sub‐national scales. Despite the Country scale shift to net forest gains, the loss of natural forests continued in some provinces (e.g., Guangdong, Guangxi) until recent years. The loss of ecosystem services from mature forests offset some of the benefits of China's forest transition. Coordinated forest management strategies across political jurisdictions could speed up the path to net forest gains, reduce trade‐offs of forest transitions processes, and achieve sustainable afforestation processes. Such an effort could have significant contributions to the preservation and increase of key forest ecosystem services for the Country and the world.
Ecological network analysis to assess the restoration success of disturbed mine soil in Zoucheng, China
Authors: Ma Jing , Gonzalez‐Ollauri Alejandro , Zhang Qi , Xiao Dong , Chen Fu 
Published: October 2021

AbstractUnderstanding the interactions among soil microbial species and how they respond to land reclamation is essential to evaluate the success of ecological restoration actions in disturbed mine soil. In this study, we strived to reveal the interactions among soil bacterial communities along the reclamation timeline of a coal mine in Zoucheng, China. To do so, we investigated changes in the composition of soil bacterial over time and constructed molecular ecological networks (i.e., microbial network) following mining soil reclamation into agricultural land. The relationships between microbial networks and selected soil attributes (i.e., soil pH, electric conductivity, organic matter, soil nutrients and enzymatic activities) were also analyzed. The results showed that the composition of soil bacteria changed significantly along the reclamation timeline. The microbial network profile revealed that Acidobacteria, Planctomycetes and Proteobacteria were the key microbial populations. Soil pH, soil organic matter content, soil dehydrogenase and urease activities were significantly correlated (0.001 ≤ p < 0.05) with the microbial network structure, suggesting that the microbial networks found influenced the provision of relevant soil ecological functions after reclamation. The variation in complexity of the microbial networks along the reclamation timeline revealed that microbial development was promoted by the shift in land use from mining into agriculture. Overall, our findings shed light on how soil microbial communities and networks change following mine reclamation into agricultural land. The results presented herein will undoubtedly aid in the establishment of success indicators of ecological restoration activities in disturbed mining soil.
Scan‐specific artifact reduction in k‐space (SPARK) neural networks synergize with physics‐based reconstruction to accelerate MRI
Authors: Arefeen Yamin , Beker Onur , Cho Jaejin , Yu Heng , Adalsteinsson Elfar , Bilgic Berkin 
Published: October 2021

PurposeTo develop a scan‐specific model that estimates and corrects k‐space errors made when reconstructing accelerated MRI data.MethodsScan‐specific artifact reduction in k‐space (SPARK) trains a convolutional‐neural‐network to estimate and correct k‐space errors made by an input reconstruction technique by back‐propagating from the mean‐squared‐error loss between an auto‐calibration signal (ACS) and the input technique’s reconstructed ACS. First, SPARK is applied to generalized autocalibrating partially parallel acquisitions (GRAPPA) and demonstrates improved robustness over other scan‐specific models, such as robust artificial‐neural‐networks for k‐space interpolation (RAKI) and residual‐RAKI. Subsequent experiments demonstrate that SPARK synergizes with residual‐RAKI to improve reconstruction performance. SPARK also improves reconstruction quality when applied to advanced acquisition and reconstruction techniques like 2D virtual coil (VC‐) GRAPPA, 2D LORAKS, 3D GRAPPA without an integrated ACS region, and 2D/3D wave‐encoded imaging.ResultsSPARK yields SSIM improvement and 1.5 – 2× root mean squared error (RMSE) reduction when applied to GRAPPA and improves robustness to ACS size for various acceleration rates in comparison to other scan‐specific techniques. When applied to advanced reconstruction techniques such as residual‐RAKI, 2D VC‐GRAPPA and LORAKS, SPARK achieves up to 20% RMSE improvement. SPARK with 3D GRAPPA also improves RMSE performance by ~2×, SSIM performance, and perceived image quality without a fully sampled ACS region. Finally, SPARK synergizes with non‐Cartesian, 2D and 3D wave‐encoding imaging by reducing RMSE between 20% and 25% and providing qualitative improvements.ConclusionSPARK synergizes with physics‐based acquisition and reconstruction techniques to improve accelerated MRI by training scan‐specific models to estimate and correct reconstruction errors in k‐space.
Prevalence of subjective impairments of the sense of smell and taste in employees of retirement and nursing homes during SARS‐CoV‐2 pandemic
Authors: Jungbauer Frederic , Huber Lena , Lammert Anne , Ludwig Sonja , Rotter Nicole , Zaubitzer Lena , Schell Angela 
Published: October 2021

AbstractAimTo investigate the usability of querying subjective impairments of the sense of smell and taste in order to improve pre‐test probability in testing for SARS‐CoV‐2. To achieve this, exploring the prevalence of these restrictions in the COVID‐19‐negative population, as well as nasal co‐symptoms.DesignA cross‐sectional study was carried out as part of the secondary prophylaxis, following the STROBE guidelines of the EQUATOR network.MethodsIn total, 1,734 employees of retirement and nursing homes were tested for COVID‐19 and asked for subjective reduction or loss in the sense of smell and taste, furthermore about nasal co‐symptoms such as nasal obstruction and rhinorrhoea.ResultsAll employees tested negative for COVID‐19. Subjective hyposmia and hypogeusia rarely occurred and were usually accompanied by other nasal symptoms such as nasal obstruction. Querying subjective hyposmia/anosmia or hypogeusia/ageusia appears to be a useful anamnestic instrument for the clinical assessment of the probability of SARS‐CoV‐2 infection.
Chain conformations and phase separation in polymer solutions with varying solvent quality
Authors: Huang Yisheng , Cheng Shengfeng 
Published: October 2021

AbstractMolecular dynamics simulations are used to investigate the conformations of a single polymer chain, represented by the Kremer‐Grest bead‐spring model, in a solution with a Lennard‐Jones liquid as the solvent when the interaction strength between the polymer and solvent is varied. Results show that when the polymer‐solvent interaction is unfavorable, the chain collapses as one would expect in a poor solvent. For more attractive polymer‐solvent interactions, the solvent quality improves and the chain is increasingly solvated and exhibits ideal and then swollen conformations. However, as the polymer‐solvent interaction strength is increased further to be more than about twice the strength of the polymer‐polymer and solvent‐solvent interactions, the chain exhibits an unexpected collapsing behavior. Correspondingly, for strong polymer‐solvent attractions, phase separation is observed in the solutions of multiple chains. These results indicate that the solvent becomes effectively poor again at very attractive polymer‐solvent interactions. Nonetheless, the mechanism of chain collapsing and phase separation in this limit differs from the case with a poor solvent rendered by unfavorable polymer‐solvent interactions. In the latter, the solvent is excluded from the domain of the collapsed chains while in the former, the solvent is still present in the pervaded volume of a collapsed chain or in the polymer‐rich domain that phase separates from the pure solvent. In the limit of strong polymer‐solvent attractions, the solvent behaves as a glue to stick monomers together, causing a single chain to collapse and multiple chains to aggregate and phase separate.
Novel poly(1H‐benzo[g]indole)/TiO2 nanocomposites for high‐performance electrochromic supercapacitor application
Authors: Wang Baoying , Li Qing , Zou Huixue , Guo Qingfu , Nie Guangming 
Published: October 2021

AbstractPoly(1H‐benzo[g]indole) (PBIn)/TiO2 nanocomposites with core‐shell nanorod array morphology are successfully prepared via simply hydrothermal synthesis combined with electrochemical polymerization. The synergistic effect between PBIn and TiO2 and the matched energy level distribution make PBIn/TiO2 nanocomposites have a specific capacitance of 29.65 mF cm−2. At the same time, it can reversibly change between light yellow and light green and show excellent cycling stability (86% retention after 3000 cycles). Thus, the electrochromic supercapacitor device (ESD) is also constructed based on PBIn/TiO2 nanocomposite and poly(3,4‐ethylenedioxythiophene). This ESD shows a good specific capacitance (13.2 mF cm−2) and high‐coloring efficiency (487 cm2 C−1). In the charging and discharging stage, the color of ESD can reversibly change between yellow and dark blue. Thus, the accumulated energy state of the ESD can be simply judged by monitoring the color or transmittance value of the device. To verify the good energy storage and actual application, this ESD can light up the Light Emitting Diode (LED) after charging, which provides new possibilities for the application of intelligent supercapacitors in the future.
Dynamics of binding interactions of TDP‐43 and RNA: An equally weighted multiscale elastic network model study
Authors: Deng Xueqing , Wang Shihao , Han Zhongjie , Gong Weikang , Liu Yang , Li Chunhua 
Published: October 2021

AbstractTransactive response DNA binding protein 43 (TDP‐43), an alternative‐splicing regulator, can specifically bind long UG‐rich RNAs, associated with a range of neurodegenerative diseases. Upon binding RNA, TDP‐43 undergoes a large conformational change with two RNA recognition motifs (RRMs) connected by a long linker rearranged, strengthening the binding affinity of TDP‐43 with RNA. We extend the equally weighted multiscale elastic network model (ewmENM), including its Gaussian network model (ewmGNM) and Anisotropic network model (ewmANM), with the multiscale effect of interactions considered, to the characterization of the dynamics of binding interactions of TDP‐43 and RNA. The results reveal upon RNA binding a loss of flexibility occurs to TDP‐43's loop3 segments rich in positively charged residues and C‐terminal of high flexibility, suggesting their anchoring RNA, induced fit and conformational adjustment roles in recognizing RNA. Additionally, based on movement coupling analyses, it is found that RNA binding strengthens the interactions among intra‐RRM β‐sheets and between RRMs partially through the linker's mediating role, which stabilizes RNA binding interface, facilitating RNA binding efficiency. In addition, utilizing our proposed thermodynamic cycle method combined with ewmGNM, we identify the key residues for RNA binding whose perturbations induce a large change in binding free energy. We identify not only the residues important for specific binding, but also the ones critical for the conformational rearrangement between RRMs. Furthermore, molecular dynamics simulations are also performed to validate and further interpret the ENM‐based results. The study demonstrates a useful avenue to utilize ewmENM to investigate the protein‐RNA interaction dynamics characteristics.
Unique features of different classes of G‐protein‐coupled receptors revealed from sequence coevolutionary and structural analysis
Authors: Do Hung N. , Haldane Allan , Levy Ronald M. , Miao Yinglong 
Published: October 2021

AbstractG‐protein‐coupled receptors (GPCRs) are the largest family of human membrane proteins and represent the primary targets of about one third of currently marketed drugs. Despite the critical importance, experimental structures have been determined for only a limited portion of GPCRs and functional mechanisms of GPCRs remain poorly understood. Here, we have constructed novel sequence coevolutionary models of the A and B classes of GPCRs and compared them with residue contact frequency maps generated with available experimental structures. Significant portions of structural residue contacts were successfully detected in the sequence‐based covariational models. “Exception” residue contacts predicted from sequence coevolutionary models but not available structures added missing links that were important for GPCR activation and allosteric modulation. Moreover, we identified distinct residue contacts involving different sets of functional motifs for GPCR activation, such as the Na+ pocket, CWxP, DRY, PIF, and NPxxY motifs in the class A and the HETx and PxxG motifs in the class B. Finally, we systematically uncovered critical residue contacts tuned by allosteric modulation in the two classes of GPCRs, including those from the activation motifs and particularly the extracellular and intracellular loops in class A GPCRs. These findings provide a promising framework for rational design of ligands to regulate GPCR activation and allosteric modulation.
Lessons learned from the 2011 Great East Japan Earthquake: A case study of tsunami risk assessment in a Japanese chemical corporation
Authors: Ochiai Nobukata , Nakayama Jo , Izato Yu‐ichiro , Miyake Atsumi 
Published: October 2021

AbstractNatural hazard triggering technological disasters (Natech) pose a major risk to chemical industries. Natural disasters, such as earthquakes, floods, and tsunamis, may cause massive fires, explosions, and toxic chemical release into the environment. Thus, Natech risks have recently attracted considerable research attention. Although Natech‐related case studies are seldom reported in the literature, the results obtained thereof facilitate concrete risk assessments and countermeasure implementation against natural hazards. This article presents a case study on tsunami risk assessment performed by Asahi Kasei Corporation, Japan, based on four steps: (1) review of Natech events caused by the 2011 Great East Japan Earthquake, (2) hazard identification at the plant, (3) risk assessment considering human casualties, equipment loss, environment, and business continuity, and (4) evaluation and implementation of appropriate countermeasures. The risks posed by tsunamis were identified and analyzed. The inundation heights of Level‐1 and Level‐2 tsunamis were estimated to be 1 and 10 m, respectively. A tsunami evacuation tower and tidal wall were built as appropriate countermeasures to prevent or mitigate fatalities, loss of containment, and business interruption. The results obtained in this study facilitate adequate preparedness of chemical plants against future tsunami occurrences.
Combining distribution‐based neural networks to predict weather forecast probabilities
Authors: Clare Mariana C.A. , Jamil Omar , Morcrette Cyril J. 
Published: October 2021

AbstractThe success of deep learning techniques over the last decades has opened up a new avenue of research for weather forecasting. Here, we take the novel approach of using a neural network to predict full probability density functions at each point in space and time rather than a single output value, thus producing a probabilistic weather forecast. This enables the calculation of both uncertainty and skill metrics for the neural network predictions, and overcomes the common difficulty of inferring uncertainty from these predictions. This approach is data‐driven and the neural network is trained on the WeatherBench dataset (processed ERA5 data) to forecast geopotential and temperature 3 and 5 days ahead. Data exploration leads to the identification of the most important input variables. In order to increase computational efficiency, several neural networks are trained on small subsets of these variables. The outputs are then combined through a stacked neural network, the first time such a technique has been applied to weather data. Our approach is found to be more accurate than some coarse numerical weather prediction models and as accurate as more complex alternative neural networks, with the added benefit of providing key probabilistic information necessary for making informed weather forecasts.