bluuebunny/crossref_metadata_2025 huggingface dataset:
Economic Impacts and Challenges of Chinese Mining Industry: An Input–Output Analysis
Authors: Zhang Binyuan , Yao Jinge , Lee Hyuck-Jin
Published: May 2022

The mining industry (MI) has played a key role in ensuring a stable supply of minerals for industrial production and human survival. The Chinese government is implementing various policies to promote the MI and needs quantitative information on the economic role and effects of the MI. Thus, this article uses comprehensive and multi-period input-output (IO) analysis to investigate the roles of four mining sectors, including the entire mining sector in the Chinese national economy, from the period 2007–2017. To this end, three models are employed. First, the production-inducing effects, value-added creation effects, and wage-inducing effects of 1 dollar of production in the MI sector are analyzed using a demand-driven model. One dollar of production or investment in the sector causes 0.862–1.171 dollars of production, 0.271–0.333 dollar of value-added, and 0.106–0.125 dollar of wage, respectively. Second, by applying a supply-driven model, it is found that one dollar of supply shortage in the MI causes 4.383–5.949 dollars of production failure throughout the national economy. Third, by utilizing a price-side model, it is discovered that a 10% increase in the price of output of the MI raises the overall price level by 0.108%–0.171%. The results of this article were critical to enlighten policy-makers to forward ever-improvement on the MI and combine the MI within national economic system reform and planning, by offering a clear vision of how MI will affect the various sectors and the economic system as a whole.
Investigating the Performance of Solar Steam Generation Using a Carbonized Cotton-Based Evaporator
Authors: Chen Haoming , Chen Yuchao , Zang Jinqi , Sha Changchang , Xiao Yupeng , Wang Wenju , Wang Haihou , Wu Juai
Published: May 2022

Solar-driven steam generation as a potential green technology has attracted extensive attention to solve the freshwater scarcity crisis. Photothermal materials as the key section of solar steam generation have been widely reported. However, there is still a challenge in developing easily prepared, environmental-friendly, and low-cost materials. Herein, the simple, scalable, and porous carbonized cotton was prepared as an evaporator to enhance solar-based evaporation, which has excellent light absorption ability in the range of the full spectrum (300–2,500 nm). Benefiting from 95% solar absorption and the pores between the cellulose tubes, the carbonized cotton heated by plate carbonization reaches a steam generation rate of 0.8 kg m−2 h−1, which is about 5 times that of untreated cotton. Compared with tube furnace carbonization, flat plate heating carbonization of cotton requires lower equipment requirements and does not need nitrogen protection and cleaning tar, and the photothermal conversion efficiencies of both are similar. In addition, carbonized cotton as an evaporator was heated up rapidly under 1 sun irradiation and reached a stable temperature in 20 s, greatly improving the photothermal conversion rate. Therefore, plate heating carbonized cotton provides a good idea for preparing solar photothermal conversion materials and a novel strategy for simplifying the production of biomass thermal evaporators.
Classification Model of Point Cloud Along Transmission Line Based on Group Normalization
Authors: Yin Zhimin , Ji Shichao , Zhang Xuyong , Dai Jianhua , Yu Weiyong , Wu Song
Published: May 2022

This article proposes a point cloud classification model based on group normalization to increase the classification accuracy when the computing power of the terminal device is limited. This model groups and normalizes the features of point cloud during inference and increases the classification accuracy when the computing power is limited. The group normalization first groups the features of point cloud by their channel, then computes their statistic metrics and normalizes them. Also, one-dimensional convolution layers are used to replace the fully connected layers to decrease the model parameters and keep the model's performance when the computing power is limited. In the experiment, PointNet++ is used to pretrain on ModelNet40 and then fine-tune on the point cloud data of transmission lines. The result shows that the proposed method can effectively increase the classification accuracy and help the 3D modeling process of the transmission line.
Non-Invasive Load Identification Algorithm Based on Color Coding and Feature Fusion of Power and Current
Authors: Xiang Yuzhu , Ding Yifan , Luo Qiang , Wang Puyu , Li Qing , Liu Haojie , Fang Kaijie , Cheng Hanmiao
Published: May 2022

In the traditional non-invasive load monitoring (NILM) algorithms, the identification accuracy is enhanced with the increased network scale while sacrificing the calculation speed, which restricts the efficiency of the load identification. In this study, a multi-feature (active/reactive power and current peak-to-peak value) fusion algorithm is proposed, which can achieve enhanced identification accuracy with a smaller network scale while maintaining the calculation speed. The features of the power and current amplitudes of the loads are transformed into the values of red-green-blue (RGB) color channels by color coding and then fused into the V-I trajectory features. After that, the true-color feature image with higher discrimination is generated and input into the convolutional neural network (CNN). The testing results on the PLAID data set indicate that in comparison with the traditional load identification algorithm, the algorithm proposed in this study performs higher identification accuracy with a smaller neural network parameter scale, which significantly improves the identification efficiency.
Virtual Inertial Control Strategy Based on Fuzzy Logic Algorithm for PMSG Wind Turbines to Enhance Frequency Stability
Authors: Li Qun , Ren Bixing , Li Qiang , Wang Dajiang , Tang Weijia , Meng Jianhui , Wu Xiaolong
Published: May 2022

With the increase of the penetration rate of wind power in the power grid, the high proportion of renewable energy and the high proportion of power electronic equipment in the power system will continuously reduce the inertia of the grid, and the frequency stability of the system will be seriously affected. The inertia of the system is an important parameter for system frequency regulation and stability calculation. For this reason, a virtual inertial control technology based on fuzzy logic control is proposed in this paper, which is used for wind turbines to participate in grid frequency regulation. In this method, based on power tracking, a fuzzy logic controller is designed to adjust the frequency adjustment coefficient adaptively, and fuzzy logic rules are used to optimize the power tracking curve online. Finally, by building a hardware-in-the-loop real-time simulation platform, the effectiveness of this method in providing system frequency support and improving the frequency response of the power grid is verified.
Short-Term Wind Power Prediction via Spatial Temporal Analysis and Deep Residual Networks
Authors: Li Huajin
Published: May 2022

Wind power is a rapidly growing source of clean energy. Accurate short-term forecasting of wind power is essential for reliable energy generation. In this study, we propose a novel wind power forecasting approach using spatiotemporal analysis to enhance forecasting performance. First, the wind power time-series data from the target turbine and adjacent neighboring turbines were utilized to form a graph structure using graph neural networks (GNN). The graph structure was used to compute the spatiotemporal correlation between the target turbine and adjacent turbines. Then, the prediction models were trained using a deep residual network (DRN) for short-term wind power prediction. Considering the wind speed, the historic wind power, air density, and historic wind power in adjacent wind turbines within the supervisory control and data acquisition (SCADA) system were utilized. A comparative analysis was performed using conventional machine-learning approaches. Industrial data collected from Hami County, Xinjiang, China, were used for the case study. The computational results validate the superiority of the proposed approach for short-term wind-power forecasting.
A Future for the Inland Fish and Fisheries Hidden Within the Sustainable Development Goals
Authors: Elliott Vittoria L. , Lynch Abigail J. , Phang Sui C. , Cooke Steven J. , Cowx Ian G. , Claussen Julie E. , Dalton James , Darwall William , Harrison Ian , Murchie Karen J. , Steel E. Ashley , Stokes Gretchen L.
Published: May 2022

The United Nations Sustainable Development Goals (SDGs) are a unifying call for change - guiding global actions at multiple levels of governance for a better planet and better lives. Consequently, achieving the “future we want” may be hindered by overlooking valuable natural resources and services that are not explicitly included in the SDGs. Not recognizing the direct, intrinsic value of some natural resources may threaten the sustainability of the services they provide and their contributions to the SDGs. Here, we use inland aquatic ecosystems, and the fish and fisheries therein, as an example to explore opportunities for recognition and inclusion of other natural resources that are missing from the SDGs. Key resources absent from the SDGs are less likely to be incorporated in global, national, and regional objectives, dialogues, and policies. We outline multiple potential pathways for better inclusion and capitalization of contributions from these overlooked natural resources during the operationalization of the SDGs and other global instruments.
The Costs and Costs Avoided From Wildfire Fire Management—A Conceptual Framework for a Value of Information Analysis
Authors: Simon Benjamin , Crowley Christian , Franco Fabiano
Published: May 2022

Wildfire is an integral part of many ecosystems, and wildland fires also have the potential for costly impacts to human health and safety, and damage to structures and natural resources. Public land managers use various strategies for managing landscape conditions that can affect wildfire, broadly: fuel treatment (and other pre-fire risk mitigation), fire suppression, and post-fire landscape rehabilitation. However, with any of these strategies there is considerable uncertainty in the outcomes that managers can obtain, and thus on the societal costs and benefits associated with wildland fire management. Managers address that uncertainty by using available information to inform their strategy choices. The value of information (VOI) to the land manager is defined as the expected gains from improved wildland fire management outcomes that result from using the information. This paper discusses estimating the value of information using two approaches: a microeconomic theoretical approach, and the Bayesian decision-tree approach frequently used in the VOI literature. These approaches could be used for valuing specific pieces of information (with absolute values), and for prioritizing (with relative values) which areas to focus on for future research.
Resilience Analysis Framework for a Water–Energy–Food Nexus System Under Climate Change
Authors: Ioannou Alexandra E. , Laspidou Chrysi S.
Published: May 2022

Climate change impacts the water–energy–food security; given the complexities of interlinkages in the nexus system, these effects may become exacerbated when feedback loops magnify detrimental effects and create vicious cycles. Resilience is understood as the system’s adaptive ability to maintain its functionality even when the system is being affected by a disturbance or shock; in WEF nexus systems, climate change impacts are considered disturbances/shocks and may affect the system in different ways, depending on its resilience. Future global challenges will severely affect all vital resources and threaten environmental resilience. In this article, we present a resilience analysis framework for a water–energy–food nexus system under climate change, and we identify how such systems can become more resilient with the implementation of policies. We showcase results in the national case study of Greece. Parametric sensitivity analysis for socioecological systems is performed to identify which parameter the model is the most sensitive to. The case study is based on the structure of a system dynamics model that maps sector-specific data from major national and international databases while causal loop diagrams and stock-and-flow diagrams are presented. Through engineering and ecological resilience metrics, we quantify system resilience and identify which policy renders the system more resilient in terms of how much perturbation it can absorb and how fast it bounces back to its original state, if at all. Two policies are tested, and the framework is implemented to identify which policy is the most beneficial for the system in terms of resilience.
Conversion of Mangroves Into Rice Cultivation Alters Functional Soil Microbial Community in Sub-Humid Tropical Paddy Soil
Authors: Kumar Upendra , Kaviraj Megha , Panneerselvam P. , Nayak A. K.
Published: May 2022

Conversion of mangrove vegetation into rice cultivation is considerably enhanced nowadays which adversely affects ecological sustainability. Soil microbial community is one of the key indicators to monitor soil health in mangroves. Studies on the variations in the microbial community within mangroves are plenty, whereas reports in mangrove-converted paddy soils are scarce. Therefore, Biolog® eco-plate-based technique was used in this study to assess soil microbial community in the Bhitarkanika (MB) and Sundarban (MS) sub-humid tropical mangroves-converted paddy soil. The results showed that significantly lower soil microbial biomass carbon and enzyme activities were recorded in MB and MS compared to the NRRI (National Rice Research Institute) paddy soil where continuous rice cultivation is being practiced conventionally since 1946 under the sub-humid tropical region. Biolog®-based average well color development (AWCD) was found significantly lower in MS and MB compared to NRRI. Shannon–Weaver and McIntosh indices followed the similar trends of AWCD. A biplot analysis indicated the positive correlation of pH, available phosphorus, actinomycetes population, and phenolic compound utilization under MS, whereas EC and phosphate-solubilizing bacteria were positively correlated under MB. Compared to MS and MB, NRRI paddy soil harbored more carbohydrate-utilizing microbes and showed a positive correlation with fluorescin-diacetate, dehydrogenase, and acid phosphatase. Overall, the present study suggested that the conversion of the Sundarban and Bhitarkanika mangroves into rice cultivation adversely affected the microbial diversity, thereby altering natural sustainability.
Oil Load Reduction of Oilfield-Produced Water by Applying Swirl–Cyclonic Flotation: A Pilot-Scale Investigation
Authors: Liu Jianfei , Wang Huihui , Zhao Yongfeng , Zhang Yi , Zhao Hongbing , Zhao Weilong , Zhang Yongsheng , Wang Xiaowei , Li Xue , Zhang Ming
Published: May 2022

A swirl–cyclonic flotation (SCF) apparatus was fabricated by combining hydrocyclone and air flotation separation to reduce the oil droplet load of oilfield-produced water. The apparatus was designed as three concentric cylinders with functions of swirling, air flotation separation, and oil collection. Influencing factors such as influent flow, oil concentration, and aeration rate were investigated in the pilot-scale test. The oil concentration of the effluent was below 100 mg/L during the continuous operation under an influent flow rate of 1.5 m3/h and an aeration rate of 0.4 L/min without addition of any chemicals. Results could be explained by the improvement in the floating velocity of oil droplets, resulting in oil load reduction. The oil and water separation mechanism of the SCF apparatus was determined by analysis of oil droplet size distribution. Compared with other flotation apparatus, the SCF apparatus had the advantages of high oil removal efficiency, low retention time, and stable water treatment quality. The apparatus also had no chemical agents added and had less floor area, leading to reduced chemical cost. The designed SCF apparatus has potential industrial application as pretreatment for oil–water load reduction.
Influence of Citrate and Phosphate on the Adsorption of Adenosine-5′-Monophosphate at the Hematite Water Interface
Authors: Rakshit Sudipta , Ray Avedananda , Taheri Ali , Essington Michael E.
Published: May 2022

Nucleic acid derived organic phosphorus (Po) is an important source of plant available P when degraded to inorganic phosphate (P(V)i). It is known that when nucleic acids or components are adsorbed on mineral surfaces, the enzymatic degradation is hindered or delayed. Thus, understanding adsorption/desorption mechanisms of nucleic acids and their derivatives are key to assess the biogeochemical pathways of Po cycling. Here we report adsorption mechanisms of adenosine-5′-monophosphate (AMP) on hematite, a common iron oxide mineral, under various solution properties using macroscopic and in situ attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopic probes. The effects of citrate, mimicking organic acids from roots exudates, and the influence of P(V)i, representing inorganic fertilizer application, were also evaluated on the release of adsorbed AMP under various solution properties. The results suggested that AMP adsorbed with the hematite surface via the phosphate moiety, N7 atom and the π electron systems of the adenine moiety. The presence of citrate significantly decreased the AMP adsorption, which was also corroborated by the negative phosphate IR bands in the results of AMP and citrate competitive adsorption experiments monitored by in situ ATR-FTIR probe. Like citrate, P(V)i also reduced AMP adsorption on hematite. Our findings suggest a potential novel pathway of nucleic acid derived Po cycling in the soil environment.
Filtering Effect of Large Rivers on Primate Distribution in the Brazilian Amazonia
Authors: Mourthé Ítalo , Hilário Renato R. , Carvalho William D. , Boubli Jean P.
Published: May 2022

Over a century after Wallace’s proposition of the riverine barrier hypothesis, the role of rivers in the diversification of species remains a matter of interest in Amazon biogeography. Amazonian rivers, in particular those large and fast flowing rivers, are widely recognized to act as barriers to the dispersal of some organisms. However, the extent to which primate species changes across interfluves (β-diversity) in response to river features remains to be explicitly tested. In this study, we examine how river characteristics affect the variation in taxonomic and phylogenetic β-diversity to elucidate the ecological processes behind the differences in primate assemblages between neighboring interfluves in the Brazilian Amazonia. We compiled International Union for Conservation of Nature (IUCN) distribution maps of 80 river-bounded primate species in 10 interfluves separated by major rivers throughout the Brazilian Amazonia. We assessed both the taxonomic (disregarding phylogenetic relationships between species) and phylogenetic β-diversities. We applied multiple linear models to evaluate whether annual discharge, sinuosity, and reflectance (as a proxy for amount of sediments) in each river or river section that separates neighboring interfluves make rivers effective barriers to primates. We found that mean discharge has a positive effect, while both sinuosity and amount of sediments have negative effects on primate β-diversity. These variables have significant effects on total taxonomic and phylogenetic β-diversity between neighboring interfluves, and their species turnover components. River features, however, have no effect on species richness differences. Genera are capable of traversing almost all interfluves, but species are replaced by others in opposite interfluves. Discharge affected both small- and large-sized primate total β-diversity, but sinuosity only affected large-sized primate assemblages in neighboring interfluves. Our results indicate that although Amazonian rivers act as barriers for many primate species, this barrier effect seems limited to the short/medium time scales, as primate lineages are able to cross them over long-time scales.
Forest Diversity Reduces the Prevalence of Pathogens Transmitted by the Tick Ixodes ricinus
Authors: Bourdin Audrey , Bord Severine , Durand Jonas , Galon Clemence , Moutailler Sara , Scherer-Lorenzen Michael , Jactel Herve
Published: May 2022

Tick-borne diseases represent the majority of vector-borne human diseases in Europe, with Ixodes ricinus, mostly present in forests, as the main vector. Studies show that vertebrate hosts diversification would decrease the prevalence of these pathogens. However, it is not well known whether habitat diversity can have similar impact on ticks and their infection rates. We measured the presence and abundance of different stages of I. ricinus, and the prevalence of associated pathogens in a large-scale forest experiment in which we manipulated tree diversity and moisture level. We showed that larval abundance was influenced by tree species identity, with larvae being more present in pine plots than in oak plots, while nymph abundance increased with canopy tree density. The proportion of Borrelia burgdorferi s.l.-infected nymphs decreased with increasing tree diversity. Our findings suggest that tree overstorey composition, structure and diversity, can affect tick abundance and pathogen prevalence. They support the idea that forest habitats may have “diluting” or “amplifying” effects on tick-borne diseases with direct relevance for human health.
Forest Carbon Emission Sources Are Not Equal: Putting Fire, Harvest, and Fossil Fuel Emissions in Context
Authors: Bartowitz Kristina J. , Walsh Eric S. , Stenzel Jeffrey E. , Kolden Crystal A. , Hudiburg Tara W.
Published: May 2022

Climate change has intensified the scale of global wildfire impacts in recent decades. In order to reduce fire impacts, management policies are being proposed in the western United States to lower fire risk that focus on harvesting trees, including large-diameter trees. Many policies already do not include diameter limits and some recent policies have proposed diameter increases in fuel reduction strategies. While the primary goal is fire risk reduction, these policies have been interpreted as strategies that can be used to save trees from being killed by fire, thus preventing carbon emissions and feedbacks to climate warming. This interpretation has already resulted in cutting down trees that likely would have survived fire, resulting in forest carbon losses that are greater than if a wildfire had occurred. To help policymakers and managers avoid these unintended carbon consequences and to present carbon emission sources in the same context, we calculate western United States forest fire carbon emissions and compare them with harvest and fossil fuel emissions (FFE) over the same timeframe. We find that forest fire carbon emissions are on average only 6% of anthropogenic FFE over the past decade. While wildfire occurrence and area burned have increased over the last three decades, per area fire emissions for extreme fire events are relatively constant. In contrast, harvest of mature trees releases a higher density of carbon emissions (e.g., per unit area) relative to wildfire (150–800%) because harvest causes a higher rate of tree mortality than wildfire. Our results show that increasing harvest of mature trees to save them from fire increases emissions rather than preventing them. Shown in context, our results demonstrate that reducing FFEs will do more for climate mitigation potential (and subsequent reduction of fire) than increasing extractive harvest to prevent fire emissions. On public lands, management aimed at less-intensive fuels reduction (such as removal of “ladder” fuels, i.e., shrubs and small-diameter trees) will help to balance reducing catastrophic fire and leave live mature trees on the landscape to continue carbon uptake.
Weathering the Storm: Harnessing the Resolution of Inflammation to Limit COVID-19 Pathogenesis
Authors: Silberberg Esther , Filep János G. , Ariel Amiram
Published: May 2022

The resolution of inflammation is a temporally and spatially coordinated process that in its innate manifestations, primarily involves neutrophils and macrophages. The shutdown of infection or injury-induced acute inflammation requires termination of neutrophil accumulation within the affected sites, neutrophil demise, and clearance by phagocytes (efferocytosis), such as tissue-resident and monocyte-derived macrophages. This must be followed by macrophage reprogramming from the inflammatory to reparative and consequently resolution-promoting phenotypes and the production of resolution-promoting lipid and protein mediators that limit responses in various cell types and promote tissue repair and return to homeostatic architecture and function. Recent studies suggest that these events, and macrophage reprogramming to pro-resolving phenotypes in particular, are not only important in the acute setting, but might be paramount in limiting chronic inflammation, autoimmunity, and various uncontrolled cytokine-driven pathologies. The SARS-CoV-2 (COVID-19) pandemic has caused a worldwide health and economic crisis. Severe COVID-19 cases that lead to high morbidity are tightly associated with an exuberant cytokine storm that seems to trigger shock-like pathologies, leading to vascular and multiorgan failures. In other cases, the cytokine storm can lead to diffuse alveolar damage that results in acute respiratory distress syndrome (ARDS) and lung failure. Here, we address recent advances on effectors in the resolution of inflammation and discuss how pro-resolution mechanisms with particular emphasis on macrophage reprogramming, might be harnessed to limit the universal COVID-19 health threat.
Benchmark Simulations of Dense Suspensions Flow Using Computational Fluid Dynamics
Authors: Haustein M. A. , Eslami Pirharati M. , Fataei S. , Ivanov D. , Jara Heredia D. , Kijanski N. , Lowke D. , Mechtcherine V. , Rostan D. , Schäfer T. , Schilde C. , Steeb H. , Schwarze R.
Published: May 2022

The modeling of fresh concrete flow is still very challenging. Nevertheless, it is of highest relevance to simulate these industrially important materials with sufficient accuracy. Often, fresh concrete is assumed to show a Bingham-behavior. In numerical simulations, regularization must be used to prevent singularities. Two different regularization models, namely the 1) Bi-viscous, and 2) Bingham-Papanastasiou are investigated. Those models can be applied to complex flows with common simulation methods, such as the Finite Volume Method (FVM), Finite Element Method (FEM) and Smoothed Particle Hydrodynamics (SPH). Within the scope of this investigation, two common software packages from the field of FVM, namely Ansys Fluent and OpenFOAM, COMSOL Multiphysics (COMSOL) from FEM side, and HOOMD-blue.sph from the field of SPH are used to model a reference experiment and to evaluate the modeling quality. According to the results, a good agreement of data with respect to the velocity profiles for all software packages is achieved, but on the other side there are remarkable difficulties in the viscosity calculation especially in the shear- to plug-flow transition zone. Also, a minor influence of the regularization model on the velocity profile is observed.
Multiscale Characterization of Erosion of TA2 Titanium Alloy Welded Joints
Authors: Liu Ran , Liu Yingshuang , Zhang Dalei
Published: May 2022

To prolong the service time of ship and seawater piping systems, titanium alloys have a series of excellent properties, such as their low density, high strength, and seawater corrosion resistance, and they have become the main material used in ocean engineering. A welded joint is a nonuniform structure that is composed of a weld seam (WM), base metal (BM), and heat-affected zone (HAZ). When an alloy is used, it is easier to form galvanic corrosion, stress corrosion, and pitting corrosion in a weld joint than when a single metal is used. Therefore, corrosion failure often occurs at a welded joint. In this article, classical electrochemical testing (EIS and Tafel) and surface morphology analysis (SEM and EDS) were used to study a welded joint, and microarray electrode (WBE) testing was added for the first time to study a welded joint. The corrosion behavior of each zone of a TA2 titanium alloy welded joint in flowing seawater and the overall corrosion tendency after coupling of three zones were studied at the macro- and submicroscales. Macroscopic results show that the HAZ and BM of a titanium alloy welded joint have better corrosion resistance in seawater. The microarray electrode shows that the WM is the main anode that accelerates corrosion, and at high flow rate, the electrode will change into the cathode. In conclusion, the data in this article provide a theoretical basis for the corrosion failure mechanism of TA2 welded joints.
Endoscopic Bariatric and Metabolic Therapies and Their Effects on Metabolic Syndrome and Non-alcoholic Fatty Liver Disease - A Systematic Review and Meta-Analysis
Authors: Lee Shi-Yan , Lai Haoxing , Chua Yang Jie , Wang Min Xian , Lee Guan-Huei
Published: May 2022

Background

Endoscopic bariatric and metabolic therapies (EBMTs) are procedures that utilize instruments that require flexible endoscopy or placement of devices for inducing weight loss. We perform a systematic review and meta-analysis to evaluate four modalities – intragastric balloon (IGB), endoscopic sleeve gastroplasty (ESG), duodeno-jejunal bypass liner (DJBL), and duodenal mucosa resurfacing (DMR), for their efficacy and safety on weight loss, non-alcoholic fatty liver disease, and metabolic syndrome.

Methods

Databases MEDLINE via PubMed, and EMBASE are searched and relevant publications up to January 26, 2022 are assessed. Studies are included if they involved human participants diagnosed with obesity and obesity-related comorbid conditions who are treated with any of the 4 EBMTs. IGB and DJBL were chosen as the interventions for the meta-analysis with weight loss (percentage total body weight loss or body mass index) and glycemic control (fasting plasma glucose or HbA1c) as the two main outcomes analyzed.

Results

Six hundred and forty-eight records are reviewed, of which 15 studies are found to be duplicates. Of the 633 records screened, 442 studies are excluded. One hundred and ninety-one articles are assessed for eligibility, for which 171 are excluded. A total of 21 publications are included. Twelve studies are on IGB, two studies on ESG, five studies on DJBL, and two studies on DMR. In these studies with appropriate control, IGB, ESG, and DJBL showed promising benefits on weight loss reduction compared to standard medical therapy (SMT), while DMR appeared to have the least weight reduction benefit. However, the impact on glycemic control featured more prominently in DMR as compared to the rest of the modalities. Different EBMTs have different adverse effect profiles, although device-related adverse events are featured more prominently in DJBL. In the IGB group, there was a significant reduction in 6-month %TBWL [weighted mean difference (WMD) 5.45 (3.88, 7.05)] and FPG WMD −4.89 mg/dL (−7.74, −2.04) compared to the SMT group. There was no significant reduction in BMI between the DJBL and SMT group WMD −2.73 (−5.52, 0.07) kg/m2.

Conclusion

EBMTs have demonstrated a significant impact on weight loss and metabolic comorbidities, and reasonable safety profiles in the studies reviewed. Some data is available to demonstrate reduction of hepatic steatosis, but there is no high-quality data supporting benefits on hepatic lobular inflammation or fibrosis.
Intravitreal Anti-vascular Endothelial Growth Factor Injection for Retinopathy of Prematurity: A Systematic Review and Meta-Analysis
Authors: Taher Nada O. , Ghaddaf Abdullah A. , Al-Ghamdi Sarah A. , Homsi Jumanah J. , Al-Harbi Bandar J. , Alomari Lugean K. , Almarzouki Hashem S.
Published: May 2022

Background

Laser photocoagulation and/or intravitreal anti-vascular endothelial growth factor (anti-VEGF) injections constitute the current standard treatment for retinopathy of prematurity (ROP). This systematic review and meta-analysis aimed to assess the efficacy and safety of anti-VEGF monotherapy for ROP treatment using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach.

Methods

We searched the Medline, Embase, and Cochrane Central Register of Controlled Trials (CENTRAL) databases. We included randomized controlled trials (RCTs) that compared intravitreal anti-VEGF monotherapy (e.g., bevacizumab, ranibizumab, aflibercept, and pegaptanib) with laser photocoagulation in preterm infants with ROP. We evaluated the rates of recurrence, treatment switching, retreatment, adverse events, and mortality. The risk ratio (RR) was used to represent dichotomous outcomes. Data were pooled using the inverse variance weighting method. The quality of evidence was assessed using the GRADE approach. Risk of bias was assessed using the Revised Cochrane risk of bias tool for randomized trials.

Results

Seven RCTs (n = 579; 1,158 eyes) were deemed eligible. Three RCTs had an overall low risk of bias, three had some concerns, and one had an overall high risk of bias. The pooled effect estimate showed a statistically significant reduction in adverse events in favor of anti-VEGF monotherapy [RR = 0.17, 95% confidence interval (CI) 0.07–0.44]. The pooled analysis showed no significant difference between the anti-VEGF and laser groups in terms of recurrence rate (RR = 1.56, 95% CI 0.23–10.54), treatment switching (RR = 2.92, 95% CI 0.40–21.05), retreatment (RR = 1.56, 95% CI 0.35–6.96), and mortality rate (RR = 1.28, 95% CI 0.48–3.41).

Conclusion

Overall, intravitreal anti-VEGF monotherapy was associated with fewer adverse events than laser therapy, rated as high quality of evidence according to the GRADE criteria. Pooled analysis revealed no significant difference between the two arms with respect to the recurrence rate, treatment switching, retreatment, and mortality rate, with quality of evidence ranging from moderate to very low as per the GRADE approach.

Systematic Review Registration

[https://www.crd.york.ac.uk/prospero/#recordDetails], identifier [CRD42021270077].
Application of PLASMIC Score in Risk Prediction of Thrombotic Thrombocytopenic Purpura: Real-World Experience From a Tertiary Medical Center in Taiwan
Authors: Lee Chun-Hui , Huang Yi-Ching , Li Sin-Syue , Hsu Ya-Ting , Chen Ya-Ping , Chen Tsai-Yun
Published: May 2022

Thrombotic thrombocytopenic purpura (TTP) is a life-threatening disorder caused by severe ADAMTS13 (a disintegrin and metalloprotease with thrombospondin type 1 repeats, member 13) deficiency (activity <10%). Urgent intervention based on the timely evaluation of ADAMTS13 level is crucial to guide optimal therapy. The recently developed PLASMIC score based on seven items allows the rapid identification of patients at high risk for TTP due to severe ADAMTS13 deficiency. This retrospective study included 31 hospitalized patients with suspicious thrombotic microangiopathy in National Cheng Kung University Hospital from December 2016 to July 2021. Data on ADAMTS13 activity and medical and laboratory information were retrieved from medical records. The PLASMIC score could be calculated in 24 of the 31 patients with available data, and the final cohort was stratified according to the 7-point PLASMIC score. All patients with high PLASMIC score (6–7) exhibited severe ADAMTS13 deficiency (activity ≤10%). One patient with a brain tumor and a PLASMIC score of 6 did not have severe ADAMTS13 activity of ≤10%. The patients in the intermediate- and low risk groups (PLASMIC scores of 5 and 0–4, respectively) exhibited ADAMTS13 activities of above 10%. Given the role of prompt diagnosis in the timely delivery of appropriate therapy, these findings confirm and strengthen the predictive value of the PLASMIC score in patients at high risk for TTP due to severe ADAMTS13 deficiency.
sFlt-1 Is an Independent Predictor of Adverse Maternal Outcomes in Women With SARS-CoV-2 Infection and Hypertensive Disorders of Pregnancy
Authors: Hernandez-Pacheco Jose Antonio , Torres-Torres Johnatan , Martinez-Portilla Raigam Jafet , Solis-Paredes Juan Mario , Estrada-Gutierrez Guadalupe , Mateu-Rogell Paloma , Nares-Torices Miguel Angel , Lopez-Marenco Mario Enmanuel , Escobedo-Segura Keren Rachel , Posadas-Nava Alejandro , Villafan-Bernal Jose Rafael , Rojas-Zepeda Lourdes , Becerra-Navarro Norma Patricia , Casillas-Barrera Manuel , Pichardo-Cuevas Mauricio , Muñoz-Manrique Cinthya , Cortes-Ramirez Ivan Alonso , Espino-y-Sosa Salvador
Published: May 2022

Background

Preeclampsia (PE) and COVID-19 share a common vascular–endothelial physiopathological pathway that may aggravate or worsen women's outcomes when both coexist. This study aims to evaluate the association of sFlt-1 levels and adverse maternal outcomes among positive SARS-CoV-2 pregnant women with and without hypertensive disorders of pregnancy (HDP).

Methods

We performed a multicenter retrospective cohort study of pregnant women with confirmed SARS-CoV-2 infection that required hospital admission. The exposed cohort comprised women with a diagnosis of an HDP. The primary outcome was a composite definition of adverse maternal outcome. The association between predictors and the main and secondary outcomes was assessed using an elastic-net regression which comprised a Lasso and Ridge regression method for automatic variable selection and penalization of non-statistically significant coefficients using a 10-fold cross-validation where the best model if automatically chosen by the lowest Akaike information criterion (AIC) and Bayesian information criteria (BIC).

Results

Among 148 pregnant women with COVID-19, the best predictive model comprised sFlt-1 MoMs [odds ratio (OR): 5.13; 95% CI: 2.19–12.05], and HDP (OR: 32.76; 95% CI: 5.24–205). sFlt-1 MoMs were independently associated with an increased probability of an adverse maternal outcome despite adjusting for HDP.

Conclusions

Our study shows that sFlt-1 is an independent predictor of adverse outcomes in women with SARS-CoV-2 despite hypertension status.
Identification of a Novel Metabolic Target for Bioactive Triterpenoids Biosynthesis in Ganoderma lucidum
Authors: Xu Juan , Wang Yiyi , Zhang Yi , Xiong Kehui , Yan Xiaoyun , Ruan Shiyu , Wu Xueqian
Published: May 2022

Triterpenoids are crucial active ingredients of Ganoderma lucidum (G. lucidum) with various health benefits. Yet the low biosynthesis greatly restricts their industrial applications, novel metabolic engineering strategies are needed to further enhance Ganoderma triterpenoids production. Transcription factors play vital roles in the metabolic regulation of terpenoids, which are still scarce to study in G. lucidum. Herein, a transcription factor GlbHLH5 (GenBank No. MZ436906.1) potential for metabolic regulation of Ganoderma triterpenes was identified for the first time. MeJA could increase Ganoderma triterpenoids biosynthesis, and GlbHLH5 significantly responded to MeJA induction, suggesting GlbHLH5 is a new target for Ganoderma triterpenoids overproduction. The regulatory effect of the newly identified target was further validated by homologous gene overexpression and silence in G. lucidum. It’s demonstrated that overexpression of GlbHLH5 significantly increased triterpenoids accumulation and the key enzyme genes transcription in the biosynthetic pathway, while silencing it displayed the opposite effect, indicating GlbHLH5 could positively regulate the triterpenoids biosynthesis by activating the synergistic expression of key enzyme genes in the biosynthetic pathway. Consequently, GlbHLH5 was identified as a positive regulator and novel metabolic target for Ganoderma triterpenoids biosynthesis, it sheds new lights on the regulatory effect regulation and synthetic biology of Ganoderma triterpenoids.
Identification of Candidate Genes Associated With Tolerance to Apple Replant Disease by Genome-Wide Transcriptome Analysis
Authors: Reim Stefanie , Winkelmann Traud , Cestaro Alessandro , Rohr Annmarie-Deetja , Flachowsky Henryk
Published: May 2022

Apple replant disease (ARD) is a worldwide economic risk in apple cultivation for fruit tree nurseries and fruit growers. Several studies on the reaction of apple plants to ARD are documented but less is known about the genetic mechanisms behind this symptomatology. RNA-seq analysis is a powerful tool for revealing candidate genes that are involved in the molecular responses to biotic stresses in plants. The aim of our work was to find differentially expressed genes in response to ARD in Malus. For this, we compared transcriptome data of the rootstock ‘M9’ (susceptible) and the wild apple genotype M. ×robusta 5 (Mr5, tolerant) after cultivation in ARD soil and disinfected ARD soil, respectively. When comparing apple plantlets grown in ARD soil to those grown in disinfected ARD soil, 1,206 differentially expressed genes (DEGs) were identified based on a log2 fold change, (LFC) ≥ 1 for up– and ≤ −1 for downregulation (p < 0.05). Subsequent validation revealed a highly significant positive correlation (r = 0.91; p < 0.0001) between RNA-seq and RT-qPCR results indicating a high reliability of the RNA-seq data. PageMan analysis showed that transcripts of genes involved in gibberellic acid (GA) biosynthesis were significantly enriched in the DEG dataset. Most of these GA biosynthesis genes were associated with functions in cell wall stabilization. Further genes were related to detoxification processes. Genes of both groups were expressed significantly higher in Mr5, suggesting that the lower susceptibility to ARD in Mr5 is not due to a single mechanism. These findings contribute to a better insight into ARD response in susceptible and tolerant apple genotypes. However, future research is needed to identify the defense mechanisms, which are most effective for the plant to overcome ARD.
Interlaboratory Studies Using the NISTmAb to Advance Biopharmaceutical Structural Analytics
Authors: Yandrofski Katharina , Mouchahoir Trina , De Leoz M. Lorna , Duewer David , Hudgens Jeffrey W. , Anderson Kyle W. , Arbogast Luke , Delaglio Frank , Brinson Robert G. , Marino John P. , Phinney Karen , Tarlov Michael , Schiel John E.
Published: May 2022

Biopharmaceuticals such as monoclonal antibodies are required to be rigorously characterized using a wide range of analytical methods. Various material properties must be characterized and well controlled to assure that clinically relevant features and critical quality attributes are maintained. A thorough understanding of analytical method performance metrics, particularly emerging methods designed to address measurement gaps, is required to assure methods are appropriate for their intended use in assuring drug safety, stability, and functional activity. To this end, a series of interlaboratory studies have been conducted using NISTmAb, a biopharmaceutical-representative and publicly available monoclonal antibody test material, to report on state-of-the-art method performance, harmonize best practices, and inform on potential gaps in the analytical measurement infrastructure. Reported here is a summary of the study designs, results, and future perspectives revealed from these interlaboratory studies which focused on primary structure, post-translational modifications, and higher order structure measurements currently employed during biopharmaceutical development.
Identification and Validation of Prognostic Biomarkers Specifically Expressed in Macrophage in IgA Nephropathy Patients Based on Integrated Bioinformatics Analyses
Authors: Ding Yuqing , Li Hua , Xu Lichen , Wang Yukun , Yang Huiying
Published: May 2022

Background: Immunoglobulin A nephropathy (IgAN) is the most common type of primary glomerulonephritis worldwide and a frequent cause of end-stage renal disease. The inflammation cascade due to the infiltration and activation of immune cells in glomeruli plays an essential role in the progression of IgAN. In this study, we aimed to identify hub genes involved in immune infiltration and explore potential prognostic biomarkers and therapeutic targets in IgAN.

Methods: We combined the single-cell and bulk transcriptome profiles of IgAN patients and controls with clinical data. Through single-cell analysis and weighted gene co-expression network analysis (WGCNA), Gene Ontology (GO) enrichment analysis, and differentially expressed gene (DEG) analysis in the bulk profile, we identified cell-type-specific potential hub genes in IgAN. Real hub genes were extracted via validation analysis and clinical significance analysis of the correlation between the expression levels of genes and the estimated glomerular filtration rate (eGFR) in the external dataset. Gene set enrichment analysis was performed to predict the probable roles of the real hub genes in IgAN.

Results: A total of eleven cell clusters were classified via single-cell analysis, among which macrophages showed a variable proportion between the IgAN and normal control samples. We recognized six functional co-expression gene modules through WGCNA, among which the black module was deemed an IgAN-related and immune-involving module via GO enrichment analysis. DEG analysis identified 45 potential hub genes from genes enriched in GO terms. A total of twenty-three potential hub genes were specifically expressed in macrophages. Furthermore, we validated the differential expression of the 23 potential hub genes in the external dataset and identified nine genes with prognostic significance as real hub genes, viz., CSF1R, CYBB, FPR3, GPR65, HCLS1, IL10RA, PLA2G7, TYROBP, and VSIG4. The real hub gens are thought to contribute to immune cell regulation, immunoreaction, and regulation of oxidative stress, cell proliferation, and material metabolism.

Conclusion: In this study, we demonstrated that macrophages infiltrated the glomeruli and contributed to the inflammatory response in IgAN. Based on integrated bioinformatics analyses of single-cell and bulk transcriptome data, we highlighted nine genes as novel prognostic biomarkers, which may enable the development of innovative prognostic and therapeutic strategies for IgAN.
Plasmonic Nanostructures for Optically Induced Movement
Authors: Balestrieri Sergio , Zito Gianluigi , Coppola Giuseppe , Iodice Mario
Published: May 2022

Optical forces generated at the nanoscale using electric field gradients have proven to be a powerful tool for trapping and moving nano-objects in a variety of application fields ranging from aerospace engineering to biology and medicine. Typically, to achieve this optical effect plasmonic resonant cavities that combine localized surface plasmon resonances and propagative surface plasmon polaritons are used. Indeed, these structures allow to engineer the distribution of the excited field hotspots, so inducing a precise movement of the nanoparticles interacting with the plasmonic field. In this paper, starting from the theoretical analysis of the surface plasmons, the potentialities of plasmonic nanostructures are reviewed, analysing the geometric conformation designed according to the application. The configurations with the most interesting performance, among those mentioned in the literature, are described in detail, examining their main characteristics and limitations. Finally, the future development and prospects of these plasmonic nanostructures are discussed.