bluuebunny/crossref_metadata_2025 huggingface dataset:
Lignocellulosic Biomass Pretreatment for Enhanced Bioenergy Recovery: Effect of Lignocelluloses Recalcitrance and Enhancement Strategies
Authors: Banu J Rajesh , Sugitha S , Kavitha S , Kannah R Yukesh , Merrylin J , Kumar Gopalakrishnan
Published: December 2021

Bioenergy recovery from lignocellulosic (LC) biomass is the beneficial and sustainable approach due to its abundant availability. On the Otherhand, its recalcitrant nature makes the biomass to resist biological hydrolysis and it limits the conversion potential of organics to biomethane. Thus, it is essential to evaluate the association among the recalcitrant nature of LC biomass and its biomethane conversion efficiency. Consequently, this review critically recaps the recalcitrance of LC biomass and its effects on bioenergy recovery, its composition and characteristics. In addition, various enhancement approaches (pretreatments) were conferred as main aspect which plays main role in biomass disintegration and biomethane increment. Based on up -to -date information, elevated energy input and cost necessities of the pretreatments are the main factors that mediates the economic feasibility of the process. The present review apart from spotlighting the pretreatment efficiency, it also focusses on the challenges and limitations of enhancement strategies, energy and technoeconomic feasibility of the various pretreatments of LC biomass.
Forecasting Electricity Load With Hybrid Scalable Model Based on Stacked Non Linear Residual Approach
Authors: Sinha Ayush , Tayal Raghav , Vyas Aamod , Pandey Pankaj , Vyas O. P.
Published: December 2021

Power has totally different attributes than other material commodities as electrical energy stockpiling is a costly phenomenon. Since it should be generated when demanded, it is necessary to forecast its demand accurately and efficiently. As electrical load data is represented through time series pattern having linear and non-linear characteristics, it needs a model that may handle this behavior well in advance. This paper presents a scalable and hybrid approach for forecasting the power load based on Vector Auto Regression (VAR) and hybrid deep learning techniques like Long Short Term Memory (LSTM) and Convolutional Neural Network (CNN). CNN and LSTM models are well known for handling time series data. The VAR model separates the linear pattern in time series data, and CNN-LSTM is utilized to model non-linear patterns in data. CNN-LSTM works as CNN can extract complex features from electricity data, and LSTM can model temporal information in data. This approach can derive temporal and spatial features of electricity data. The experiment established that the proposed VAR-CNN-LSTM(VACL) hybrid approach forecasts better than more recent deep learning methods like Multilayer Perceptron (MLP), CNN, LSTM, MV-KWNN, MV-ANN, Hybrid CNN-LSTM and statistical techniques like VAR, and Auto Regressive Integrated Moving Average (ARIMAX). Performance metrics such as Mean Square Error, Root Mean Square Error, and Mean Absolute Error have been used to evaluate the performance of the discussed approaches. Finally, the efficacy of the proposed model is established through comparative studies with state-of-the-art models on Household Power Consumption Dataset (UCI machine learning repository) and Ontario Electricity Demand dataset (Canada).
Cooperative Trading Mechanism and Satisfaction-Based Profit Distribution in a Multi-Energy Community
Authors: Wang Jian , Xie Ning , Ilea Valentin , Bovo Cristian , Xin Hao , Wang Yong
Published: December 2021

With the development of distributed generation and demand-side response, traditional consumers are now converted into prosumers that can actively produce and consume electricity. Moreover, with the help of energy integration technique, prosumers are encouraged to form a multi-energy community (MEC), which can increase their social welfare through inside multi-energy sharing. This paper proposes a day-ahead cooperative trading mechanism in a MEC that depends on an energy hub (EH) to couple electricity, natural gas, and heat for all prosumers. The model of the traditional uncooperative local integrated energy system (ULIES) is also built as a comparison. A satisfaction-based profit distribution mechanism is set according to prosumers’ feelings about the extra cost they save or extra profit they gain in MEC compared with that in ULIES. Finally, case studies are set to analyze the utility of MEC in enlarging social welfare, after considering the effects of prosumers’ electricity usage patterns and buy-and-sell prices in retail market. The results of satisfaction-based profit distribution are also analyzed to verify that it can save the cost or increase the profit of each prosumer and EH.
A Dynamic Multivariate Causality Analysis of Energy–Growth Nexus Using ARDL Approach: A Malaysian Energy Policy Perspective
Authors: Khan Habib Nawaz , Alrasheedi Melfi , Shahzada Gulap
Published: December 2021

This study analyzes a dynamic long-run and short-run causal nexus between energy consumption and economic growth in the presence of capital, labor, and urbanization over the period 1971–2014, in Malaysia. The stationarity issue was tested using augmented Dickey–Fuller (ADF), Kwiatkowski–Phillips–Schmidt–Shin (KPSS), and Ng–Perron tests. However, a dynamic long-run co-integration relation between variables was checked through the ARDL technique. An unrestricted vector error correction model (MUVECM) was used to estimate the short-run and long-run dynamic relations between the parameters and the Engle–Granger method was used for causality analysis. Results of statistical analysis confirmed that all variables were found to be I (1) except variable labour was I(0) and none of the variables was I(2). Total energy consumption Granger caused GDP in one direction over the period 1992-2010 in the case of Croatia. However, labor and urbanization impacts were mixed. The Granger causality analysis confirmed mixed results in the short run and the long run. Moreover, estimated results confirmed a feedback hypothesis between income and capital was in the short term and the long run. The short-run and long-run causal effects of labor force on economic growth were confirmed. This study provides important insights to policymakers and energy economists. Prudent energy conservation policies and economically improved measures would be of great help. However, demand-side management-based policies would have no adverse effect on the economic performance of Malaysia.
Human Development Index, ICT, and Renewable Energy-Growth Nexus for Sustainable Development: A Novel PVAR Analysis
Authors: Azam Anam , Rafiq Muhammad , Shafique Muhammad , Yuan Jiahai , Salem Sultan
Published: December 2021

The relevance of information and communication technology to long-lasting human improvement cannot be disregarded in this modern world. From this perspective, this study analyzed the association between information and communication technologies, renewable energy, economic growth, and human development indices considering CO2 emissions and remittances from 1990 to 2017 in 30 developing countries by using the panel vector autoregressive (PVAR) model. The findings of the empirical investigation point to the considerable favorable relationship between information and communication technology, renewable energy, and economic growth with the human development index. The causality results suggest that there is bidirectional causality between renewable energy and the human development index. In addition, there is unidirectional causality from human development to information and communication technology. However, the study recommends implementing information and communication technology-related policies to trigger renewable energy for sustainable growth and the human development index.
Polyacrylonitrile/Crown Ether Composite Nanofibres With High Efficiency for Adsorbing Li(I): Experiments and Theoretical Calculations
Authors: Ding Tao , Wu Qian , Zheng Mianping , Nie Zhen , Li Min , Peng Suping , Wang Yunsheng , Yu Xudong , Qian Cheng , Tang Si , Wang Mingliang
Published: December 2021

Lithium, as the lightest alkali metal, is widely used in military and new energy applications. With the rapid growth in demand for lithium resources, it has become necessary to improve the effectiveness of extraction thereof. By using chemical grafting and electrospinning techniques, nanofibres containing crown ether were developed for adsorbing Li(I) from the brine in salt lakes, so as to selectively adsorb Li(I) on the premise of retaining specific vacancies of epoxy groups in crown ether. In lithium-containing solution, the adsorbing materials can reach adsorption equilibrium within three hours, and the maximum adsorption capacity is 4.8 mg g−1. The adsorption mechanisms of the adsorbing materials for Li(I) were revealed by combining Fourier transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), and X-ray photoelectron spectroscopy (XPS) with density functional theory (DFT) calculation. The results indicated that in crown ether, O in epoxy groups was coordinated with Li(I) to form Li–O and four O atoms in the epoxy groups were used as electron donors. After coordination, two O atoms protruded from the plane and formed a tetrahedral structure with Li(I), realising the specific capture of Li(I). By desorbing fibres that adsorbed Li(I) with 0.5-M HCl, the adsorption capacity only decreased by 10.4% after five cycles, proving ability to regenerate such materials. The nanofibres containing crown ether synthesised by chemical grafting and electrospinning have the potential to be used in extracting lithium resources from the brine in salt lakes.
Optimal Dispatch of Multi-Energy Integrated Micro-Energy Grid: A Model Predictive Control Method
Authors: Huang Xurui , Yang Bo , Yu Fengyuan , Pan Jun , Xu Qin , Xu Wanxin
Published: December 2021

In order to reduce the impacts caused by large-scale renewable energy resources accessing the utility grid, the micro-energy grid system, as a natural extension of the microgrid in the energy internet era, is proposed and developed to provide a new solution for the optimal utilization of renewable energy resources. In this paper, a multi-energy integrated micro-energy system is proposed which contains wind, PV, bedrock energy storage, magnetic levitation electric refrigeration, solid oxide fuel cell, solar thermal collector, energy storage, and V2G technologies, and detailed models of the energy generation/conversion/storage devices are formulated. Besides this, the uncertainties of renewable energy resources and cold/heat/electricity loads are considered, and the optimal dispatch problem of the micro-energy system is established from day-ahead and real-time time scales based on a model predictive control method. The day-ahead optimal scheduling aims at economic optimization and guides real-time scheduling, and real-time scheduling utilizes rolling optimization and a feedback correction mechanism to effectively correct the deviation of renewable energy generations and loads at a real-time horizon, which improves the optimization control accuracy, follows the day-ahead dispatch plan, and ensures the economics of real-time scheduling at the same time.
Financial Consideration of Energy and Environmental Nexus with Energy Poverty: Promoting Financial Development in G7 Economies
Authors: Huang Jialiang , Wang Xiaoxia , Liu Hongda , Iqbal Sajid
Published: December 2021

Energy and environmental concepts have been extensively studied in the past. However, these studies often lacked integrated analysis of energy, monetary, public, and ecological aspects to assess energy and environmental issues. This article provides analyzation of the G7 nations’ qualitative, social, cultural, and health achievement in the energy poverty indexes. These include the energy economics and climate change of energy poverty, by using DEA like a composite indicator. The G7 countries’ combined energy consumption is equal to 34% of the world’s total, whereas the GDP is 50% of the global total. As a result, this article develops a comprehensive series of energy, financial, societal, and environmental indicators that are up to date. Such indicators are utilized to assess energy financial, societal, and EPI using a mathematical composite indicator. Canada has the greatest EPII score, indicating that it can deal better than the other G7 countries with energy independence, productivity expansion, and social impact, and France’s and Italy’s the second tier. While Japan has a 0.50 EPI grade and the United States will have the lowest, the G7 countries are growing faster. Finally, we propose a policy framework for enhancing the research area. The energy, societal, and EPI were created by combining these elements. In terms of energy independence, economic growth, and sustainability practices, Canada beats the other G7 countries according to the data. France and Italy are in the 2nd and 3rd places, respectively. Despite having a higher level of economic development than the G7 countries, Japan has a 0.50 Environmental Performance Index rating, whereas the United States has a minimum average Environmental Performance Index rating. Finally, in order to improve the study’s subject, we propose a policy framework.
Intensive Agriculture as Climate Change Adaptation? Economic and Environmental Tradeoffs in Securing Rural Livelihoods in Tanzanian River Basins
Authors: Ires Idil
Published: December 2021

Tanzania is one of the East African countries most vulnerable to climate change impacts. Droughts and floods in 2015–16 had devastating effects on food production, crop failures and livestock deaths reaching record levels. One of the underlying projects of the Tanzanian government to mitigate these impacts is the Southern Agricultural Growth Corridors of Tanzania (SAGCOT), an area spanning the country’s largest river basin, the Rufiji, where it collaborates with national and transnational companies to intensify irrigated crop production. Irrigation, drought-tolerant seeds, and employment are three of the key government-advised strategies to help smallholders increase crop yield, adapt to climate change, and alleviate poverty through the corridor. However, little research is available on whether these goals have been achieved. This paper aims to contribute to the literature by assessing harvest and income levels following the 2015–16 drought. Through fieldwork conducted in 2016–17 in Usangu, a key paddy production area in the Great Ruaha Basin within SAGCOT, data is collected from documents and 114 informants. This study finds that irrigation did not significantly contribute to rising paddy production in the case study. Prioritizing the downstream national park and the energy sector, the government periodically cut down the water access of the case-study irrigation scheme, which exacerbated water stress. Moreover, though farmers widely shifted to intensive farming and used hybrid seeds, mainly, the high-income groups ensured and increased the crop yield and profit. The-low income groups encountered crop failure and, due to rising production costs, debt. Many of them left farming, impoverished, and sought to secure subsistence through wage laboring. This study discusses the shortcomings of the transitions from traditional to intensive farming and from farming to employment as climate change adaptation strategies and draws critical policy-relevant conclusions.
Towards a Living Lab for Enhanced Thermal Comfort and Air Quality: Analyses of Standard Occupancy, Weather Extremes, and COVID-19 Pandemic
Authors: Ulpiani Giulia , Nazarian Negin , Zhang Fuyu , Pettit Christopher J.
Published: December 2021

Maintaining indoor environmental (IEQ) quality is a key priority in educational buildings. However, most studies rely on outdoor measurements or evaluate limited spatial coverage and time periods that focus on standard occupancy and environmental conditions which makes it hard to establish causality and resilience limits. To address this, a fine-grained, low-cost, multi-parameter IOT sensor network was deployed to fully depict the spatial heterogeneity and temporal variability of environmental quality in an educational building in Sydney. The building was particularly selected as it represents a multi-use university facility that relies on passive ventilation strategies, and therefore suitable for establishing a living lab for integrating innovative IoT sensing technologies. IEQ analyses focused on 15 months of measurements, spanning standard occupancy of the building as well as the Black Summer bushfires in 2019, and the COVID-19 lockdown. The role of room characteristics, room use, season, weather extremes, and occupancy levels were disclosed via statistical analysis including mutual information analysis of linear and non-linear correlations and used to generate site-specific re-design guidelines. Overall, we found that 1) passive ventilation systems based on manual interventions are most likely associated with sub-optimum environmental quality and extreme variability linked to occupancy patterns, 2) normally closed environments tend to get very unhealthy under periods of extreme pollution and intermittent/protracted disuse, 3) the elevation and floor level in addition to room use were found to be significant conditional variables in determining heat and pollutants accumulation, presumably due to the synergy between local sources and vertical transport mechanisms. Most IEQ inefficiencies and health threats could be likely mitigated by implementing automated controls and smart logics to maintain adequate cross ventilation, prioritizing building airtightness improvement, and appropriate filtration techniques. This study supports the need for continuous and capillary monitoring of different occupied spaces in educational buildings to compensate for less perceivable threats, identify the room for improvement, and move towards healthy and future-proof learning environments.
Peatlands Are More Beneficial if Conserved and Restored than Drained for Monoculture Crops
Authors: Tarigan Suria , Zamani Neviaty P. , Buchori Damayanti , Kinseng Rilus , Suharnoto Yuli , Siregar Iskandar Z.
Published: December 2021

Peatlands are especially important but fragile tropical landscapes. The importance of peatlands is owing to their ability to 1) sequester a considerable amount of terrestrial carbon, 2) store freshwater, and 3) regulate floods during the rainy season. Nowadays, extensive peatland degradation occurs because of peatland utilization for agriculture purposes, causing severe environmental consequences such as carbon emission, loss of biodiversity, risk of flooding, and peat fire. Meanwhile, local planners and decision makers tend to overlook the long-term strategic function of peatlands for carbon storage and hydrological regulation, preferring peatland utilization for short-term economic benefits. The objective of our study is to quantify the total ecosystem services (except biodiversity) of a tropical peatland landscape in various peat-utilization scenarios to help build awareness among local planners and decision makers on the strategic tradeoff between peatland utilization and restoration. Studies on the total ecosystem services in a tropical peatland landscape involving hydrological regulation are still rare. Based on the net present value calculation, provisioning services, carbon regulation, and hydrological regulation in our study area account for 19, 70, and 11% of the total ecosystem services, respectively. Based on uncertainty analysis, at any combination of the social cost of carbon emission (within a range of USD 52.7–USD 107.4) and discount rate (within a range of 5–10%), the enrichment of peatlands with paludiculture crops (e.g., jelutong) shows superior ecosystem services compared to other peatland-utilization scenarios. Conversely, planting peatlands with monoculture crops, which are associated with peatland drainage, shows a rapid decrease in the total ecosystem services. The fluvial carbon export in our study, which is often neglected in a peatland carbon budget, increases the estimate of the total carbon budget by 8%. Restoring undrained peatlands with paludiculture crops such as jelutong contributes positively to carbon sequestration and potentially reduces carbon emissions by 11%. These quantitative findings can help local planners and decision makers in understanding the tradeoff between the long-term benefits of peatland restoration and the short-term economic benefits of peatland utilization for monoculture crops.
Farmyard Manure as K-Fertilizer Modulates Soil Biological Activities and Yield of Wheat Using the Integrated Fertilization Approach
Authors: Kumar Sanjeev , Dhar Shiva , Barthakur Sharmistha , Rajawat Mahendra Vikram Singh , Kochewad S. A. , Kumar Sudhir , Kumar Dileep , Meena L. R.
Published: December 2021

Potassium fertilization is often ignored by assuming alluvial soils have sufficient K reserves in the North West Plain Zone of India under cereal-based cropping systems. There is scanty information on the impact of integrated K fertilization on soil enzymes, nutrients availability, microbial population, and wheat yield cultivated in the corn–wheat cropping system. The current study exhibits that treatment (T7) applied with a dose of 90 kg K ha−1[30 kg K by farmyard manure (FYM) and 60 kg K by muriate of potash (MOP)] significantly enhances the various microbial populations from 48.00 to 123.10% and 39.00 to 124.00%, soil enzymatic activities from 70.31 to 180.00% and 102.42 to 175.68%, and available nutrients from 2.43 to 8.44% and 14.79 to 22.87% for the first and second years of wheat cultivation, respectively. It also improved various yield parameters (12.39–41.71% and 18.24–41.14%) during both the consecutive years of cultivation. Statistical analyses revealed that the treatments (T4, T5,and T7) applied with integrated fertilization of wheat cultivation through FYM and MOP were more promising for improving soil enzymatic activities (11.59–57.22%), microbial populations (5.14–15.70%), available nutrients in soil (7.60–16.54%), and crop yield (1.06–5.85%) during the second year of cultivation as compared to the first year of cultivation. This study might be helpful to reclaim soil health and reduce chemical fertilizers used in agricultural lands.
Heterogeneity and Contribution of Microplastics From Industrial and Domestic Sources in a Wastewater Treatment Plant in Xiamen, China
Authors: Long Zouxia , Wang Wenling , Yu Xingguang , Lin Zhongyang , Chen Jian
Published: December 2021

Plastic-related industrial discharge is suspected as a significant source of microplastics (MPs) in the influent of wastewater treatment plants (WWTPs). However, little is known about the characteristics of MPs in industrial wastewater. Taking the Haicang WWTP in Xiamen, China, as an example, this study compared MPs in industrial wastewater with the domestic one in terms of abundance, particle size, polymer type, shape and color. Wentworth modulus, grain size parameters and principal component analysis (PCA) were performed to describe the MP difference between those two. It was found that the abundance of MPs in industrial wastewater was more than twice that in domestic wastewater, and the flux of MPs discharged into the aquatic environment through industrial wastewater was about 3.2 times that of domestic wastewater. The main shapes of MPs in industrial wastewater and domestic wastewater were fiber and granule, respectively. The proportion of polyester (PES) and polyethylene terephthalate (PET) in industrial wastewater was higher than that in domestic wastewater, related to the type of factories served by the WWTP. Compared with domestic wastewater, the rough surface of MPs in industrial wastewater was more complex and diverse, which might have a high capability of adsorbing other pollutants, thereby causing more significant harm to the environment. Our results supported that industrial sources of MPs are the priority areas in environmental management, and immediate action is taken to prevent industrial-sources MPs from entering the environment.
Assessing Energy Efficiency for Economic and Sustainable Development in the Region of European Union Countries
Authors: Yan Dong , Liu Hongda , Yao Pinbo
Published: December 2021

The objective of this research is to estimate the energy-saving intensities of nations within the European Union, applying varied equations of the DEA analysis, such as the DEA, modified radial equation, Russel dynamic envelope analysis, and the adjusted Russel Dynamic envelope Analysis, throughout the period of 2010–2018. Unlike other studies, this analysis seeks to unravel whether European nations are effective in increasing the EE finance of their respective economies. Because the European Union not only has geographical ties between regions, it is also a collection of interests of various sovereign states, its energy exhibits efficiency changes under the relationship of competition and cooperation under that economic effect. Regarding this circumstance, different dynamic envelope evaluations were formulated. One primary finding is that nations such as Germany, Sweden, or Austria attain robust ecological safeguard performance, seem to be using less energy, and are ecologically efficient relative to other nations such as Denmark, Belgium, Spain, France, or Ireland. Furthermore, a group of Eastern EU nations attained reduced efficiency marks, which could be categorized as anticipated, as a result of reduced technological implementation within the principal manufacturing sectors. The main result of this study is that few nations are performing in terms of efficiency. Additionally, RE (Renewable Energy) power production expands as nations’ dynamic envelope analysis marks and creates inefficient governments nearer to the efficiency frontline. Inversely, the presence of peak-time power consumption reduced the dynamic envelope analysis marks and increased the distance from the Frontier of efficiency (the optimal value of efficiency).
A Systematic Review of Research Investigating the Combined Ecological Impact of Anthropogenic Noise and Artificial Light at Night
Authors: Halfwerk Wouter , Jerem Paul
Published: December 2021

Levels of anthropogenic noise and artificial light at night (ALAN) are rapidly rising on a global scale. Both sensory pollutants are well known to affect animal behavior and physiology, which can lead to substantial ecological impacts. Most studies on noise or light pollution to date have focused on single stressor impacts, studying both pollutants in isolation despite their high spatial and temporal co-occurrence. However, few studies have addressed their combined impact, known as multisensory pollution, with the specific aim to assess whether the interaction between noise and light pollution leads to predictable, additive effects, or less predictable, synergistic or antagonistic effects. We carried out a systematic review of research investigating multisensory pollution and found 28 studies that simultaneously assessed the impact of anthropogenic noise and ALAN on animal function (e.g., behavior, morphology or life-history), physiology (e.g., stress, oxidative, or immune status), or population demography (e.g., abundance or species richness). Only fifteen of these studies specifically tested for possible interactive effects when both sensory pollutants were combined. Four out of eight experimental studies revealed a significant interaction effect, in contrast to only three out seven observational studies. We discuss the benefits and limitations of experimental vs. observational studies addressing multisensory pollution and call for more specific testing of the diverse ways in which noise and light pollution can interact to affect wildlife.
Snow Leopard Dietary Preferences and Livestock Predation Revealed by Fecal DNA Metabarcoding: No Evidence for Apparent Competition Between Wild and Domestic Prey
Authors: Lu Qi , Xiao Lingyun , Cheng Chen , Lu Zhi , Zhao Jindong , Yao Meng
Published: December 2021

Accurate assessments of the patterns and drivers of livestock depredation by wild carnivores are vital for designing effective mitigation strategies to reduce human-wildlife conflict. Snow leopard’s (Panthera uncia) range extensively overlaps pastoralist land-use and livestock predation there is widely reported, but the ecological determinants of livestock consumption by snow leopards remain obscure. We investigated snow leopard dietary habits at seven sites across the Sanjiangyuan region of the Qinghai–Tibetan Plateau (QTP), an area central to the species’ global range. Snow leopard abundance, wild prey composition, and livestock density varied among those sites, thus allowing us to test the effects of various factors on snow leopard diet and livestock predation. Using DNA metabarcoding, we obtained highly resolved dietary data from 351 genetically verified snow leopard fecal samples. We then analyzed the prey preferences of snow leopards and examined ecological factors related to their livestock consumption. Across the sites, snow leopard prey was composed mainly of wild ungulates (mean = 81.5% of dietary sequences), particularly bharal (Pseudois nayaur), and supplemented with livestock (7.62%) and smaller mammals (marmots, pikas, mice; 10.7%). Snow leopards showed a strong preference for bharal, relative to livestock, based on their densities. Interestingly, both proportional and total livestock consumption by snow leopards increased linearly with local livestock biomass, but not with livestock density. That, together with a slight negative relationship with bharal density, supports apparent facilitation between wild and domestic prey. We also found a significant positive correlation between population densities of snow leopard and bharal, yet those densities showed slight negative relationships with livestock density. Our results highlight the importance of sufficient wild ungulate abundance to the conservation of viable snow leopard populations. Additionally, livestock protection is critically needed to reduce losses to snow leopard depredation, especially where local livestock abundances are high.
Case Report: Exome Sequencing Identified Variants in Three Candidate Genes From Two Families With Hearing Loss, Onychodystrophy, and Epilepsy
Authors: Li Yuan , Xiong Jianjun , Zhang Yi , Xu Lin , Liu Jianyun , Cai Tao
Published: December 2021

A cohort of 542 individuals in 166 families with congenital hearing loss was recruited for whole-exome sequencing analysis. Here, we report the identification of three variants in five affected individuals in two unrelated families. In family 1, a nonsense mutation (c.1516C>T, p.R506*) in the ATP6V1B2 gene, a known causal allele for dominant deafness-onychodystrophy (DDOD), was identified in the mother and son with DDOD. However, a novel heterozygous variant (c.1590T>G, p.D530E) in TJP2, a known causal gene for hearing-loss, was also detected in the patients. In family 2, the same mutation (c.1516C>T, p.R506*) of ATP6V1B2 was detected from the father and daughter with DDOD. Furthermore, a novel heterozygous variant (c.733A>G, p.M245V) in the KIF11 gene was identified from the spouse with sensorineural hearing-loss and epilepsy. Notably, genotype-phenotype analysis of KIF11-associated disorders revealed that the p.M245V and two reported hearing-loss-associated variants (p.S235C and p.H244Y) are all mapped to a single β-sheet (Ser235∼M245) in the kinesin motor domain. Together, this is the first demonstration that ATP6V1B2-caused DDOD is an autosomal dominant genetic disease, compared to previous cases with de novo mutation. Our findings expand the variant spectrum of hearing-loss-associated genes and provide new insights on understanding of hearing-loss candidate genes ATP6V1B2, TJP2, and KIF11.
Case Report: Lennox–Gastaut Epileptic Encephalopathy Responsive to Cannabidiol Treatment Associated With a Novel de novo Mosaic SHANK1 Variant
Authors: Paprocka Justyna , Ziętkiewicz Szymon , Kosińska Joanna , Kaczorowska Ewa , Płoski Rafał
Published: December 2021

The SH3 and multiple ankyrin repeat domains (SHANKs) are a family of scaffolding proteins located in excitatory synapses required for their development and function. Molecular defects of SHANK3 are a well-known cause of several neurodevelopmental entities, in particular autism spectrum disorders and epilepsy, whereas relatively little is known about disease associations of SHANK1. Here, we propose a novel de novo mosaic p.(Gly126Arg) SHANK1 variant as the monogenic cause of disease in a patient who presented, from the age of 2 years, moderate intellectual disability, autism, and refractory epilepsy of the Lennox–Gastaut type. The epilepsy responded remarkably well to cannabidiol add-on therapy. In silico analyses including homology modeling and molecular dynamics simulations indicated the deleterious effect of SHANK1 p.(Gly126Arg) on the protein structure and the related function associated with protein–protein interactions. In particular, the variant was predicted to disrupt a hitherto unknown conserved region of SHANK1 protein with high homology to a recently recognized functionally relevant domain in SHANK3 implicated in ligand binding, including the “non-canonical” binding of Rap1.
SRD5A3-CDG: Emerging Phenotypic Features of an Ultrarare CDG Subtype
Authors: Kamarus Jaman Nazreen , Rehsi Preeya , Henderson Robert H. , Löbel Ulrike , Mankad Kshitij , Grunewald Stephanie
Published: December 2021

Background: SRD5A3-CDG is a rare N-glycosylation defect caused by steroid 5 alpha reductase type 3 deficiency. Its key feature is an early severe visual impairment with variable ocular anomalies often leading to diagnosis. Additional symptoms are still poorly defined. In this case study, we discuss 11 genetically confirmed cases, and report on emerging features involving other systems in addition to the eye phenotype.

Methods: In total, 11 SRD5A3-CDG patients in five sets of sibships were included in the study. Data on 9 of 11 patients are as of yet unpublished. Patients’ results on biochemical and genetic investigations and on in-depth phenotyping are presented.

Results: Key diagnostic features of SRD5A3-CDG are ophthalmological abnormalities with early-onset retinal dystrophy and optic nerve hypoplasia. SRD5A3-CDG is also characterized by variable neurological symptoms including intellectual disability, ataxia, and hypotonia. Furthermore, ichthyosiform skin lesions, joint laxity, and scoliosis have been observed in our cohort. We also report additional findings including dystonia, anxiety disorder, gastrointestinal symptoms, and MRI findings of small basal ganglia and mal-rotated hippocampus, whereas previous publications described dysmorphic features as a common finding in SRD5A3, which could not be confirmed in our patient cohort.

Conclusion: The detailed description of the phenotype of this large cohort of patients with SRD5A3-CDG highlights that the key clinical diagnostic features of SRD5A3-CDG are an early onset form of ophthalmological problems in patients with a multisystem disorder with variable symptoms evolving over time. This should aid earlier diagnosis and confirms the need for long-time follow-up of patients.
Identification of Immune-Related Genes Associated With Bladder Cancer Based on Immunological Characteristics and Their Correlation With the Prognosis
Authors: Kang Zhen , Li Wei , Yu Yan-Hong , Che Meng , Yang Mao-Lin , Len Jin-Jun , Wu Yue-Rong , Yang Jun-Feng
Published: December 2021

Background:To identify the immune-related genes of bladder cancer (BLCA) based on immunological characteristics and explore their correlation with the prognosis. Methods:We downloaded the gene and clinical data of BLCA from the Cancer Genome Atlas (TCGA) as the training group, and obtained immune-related genes from the Immport database. We downloaded GSE31684 and GSE39281 from the Gene Expression Omnibus (GEO) as the external validation group. R (version 4.0.5) and Perl were used to analyze all data. Result:Univariate Cox regression analysis and Lasso regression analysis revealed that 9 prognosis-related immunity genes (PIMGs) of differentially expressed immune genes (DEIGs) were significantly associated with the survival of BLCA patients (p < 0.01), of which 5 genes, including NPR2, PDGFRA, VIM, RBP1, RBP1 and TNC, increased the risk of the prognosis, while the rest, including CD3D, GNLY, LCK, and ZAP70, decreased the risk of the prognosis. Then, we used these genes to establish a prognostic model. We drew receiver operator characteristic (ROC) curves in the training group, and estimated the area under the curve (AUC) of 1-, 3- and 5-year survival for this model, which were 0.688, 0.719, and 0.706, respectively. The accuracy of the prognostic model was verified by the calibration chart. Combining clinical factors, we established a nomogram. The ROC curve in the external validation group showed that the nomogram had a good predictive ability for the survival rate, with a high accuracy, and the AUC values of 1-, 3-, and 5-year survival were 0.744, 0.770, and 0.782, respectively. The calibration chart indicated that the nomogram performed similarly with the ideal model. Conclusion:We had identified nine genes, including PDGFRA, VIM, RBP1, RBP1, TNC, CD3D, GNLY, LCK, and ZAP70, which played important roles in the occurrence and development of BLCA. The prognostic model based on these genes had good accuracy in predicting the OS of patients and might be promising candidates of therapeutic targets. This study may provide a new insight for the diagnosis, treatment and prognosis of BLCA from the perspective of immunology. However, further experimental studies are necessary to reveal the underlying mechanisms by which these genes mediate the progression of BLCA.
Epigenetic Regulation of miR-92a and TET2 and Their Association in Non-Hodgkin Lymphoma
Authors: Elliott Esther K. , Hopkins Lloyd N. , Hensen Robert , Sutherland Heidi G. , Haupt Larisa M. , Griffiths Lyn R.
Published: December 2021

MicroRNAs (miRNAs) are well known for their ability to regulate the expression of specific target genes through degradation or inhibition of translation of the target mRNA. In various cancers, miRNAs regulate gene expression by altering the epigenetic status of candidate genes that are implicated in various difficult to treat haematological malignancies such as non-Hodgkin lymphoma by acting as either oncogenes or tumour suppressor genes. Cellular and circulating miRNA biomarkers could also be directly utilised as disease markers for diagnosis and monitoring of non-Hodgkin lymphoma (NHL); however, the role of DNA methylation in miRNA expression regulation in NHL requires further scientific inquiry. In this study, we investigated the methylation levels of CpGs in CpG islands spanning the promoter regions of the miR-17–92 cluster host gene and the TET2 gene and correlated them with the expression levels of TET2 mRNA and miR-92a-3p and miR-92a-5p mature miRNAs in NHL cell lines, tumour samples, and the whole blood gDNA of an NHL case control cohort. Increased expression of both miR-92a-3p and miR-92a-5p and aberrant expression of TET2 was observed in NHL cell lines and tumour tissues, as well as disparate levels of dysfunctional promoter CGI methylation. Both miR-92a and TET2 may play a concerted role in NHL malignancy and disease pathogenesis.
Heart Failure and Ischemic Stroke: A Bidirectional and Multivariable Mendelian Randomization Study
Authors: Zhang Luyang , Liu Weishi , Sun Wenxian , Wang Xin , Tian Mengke , Pei Lu-Lu , Liu Kai , Liang Jing , Zhou Lue , Lu Jie , Ning Mingming , Buonanno Ferdinando S. , Xu Yuming , Song Bo
Published: December 2021

Background: Heart failure (HF) is a potential cause of ischemic stroke (IS), and previous studies have reported an association between HF and IS. This study aimed to analyze the causal link between HF and IS using bidirectional and multivariable Mendelian randomization (MR) studies.

Methods: Genetic variants significantly associated with HF and IS were selected in the MR analysis from two large genome-wide association studies. Bidirectional and multivariable MR analyses were performed to evaluate the effect of HF on IS or the effect of IS on HF.

Results: Two-sample MR analysis showed causal effects of HF on IS of all causes [odds ratio (OR) = 1.555, 95% confidence interval (CI): 1.343–1.799, p = 3.35 × 10−9] and large artery atherosclerosis stroke (LAS) (OR = 1.678, 95% CI: 1.044–2.696, p = 3.03 × 10−5), while there was a suggestive effect of HF on cardioembolic stroke (CES) (OR = 3.355, 95% CI: 1.031–10.919, p = 0.044). Genetically predicted HF was not associated with small artery occlusion stroke. Bidirectional MR analysis showed causal effects of IS of all causes (OR = 1.211, 95% CI: 1.040–1.410, p = 0.014) and CES (OR = 1.277, 95% CI: 1.213–1.344, p = 6.73 × 10−21) on HF, while there were no causal effects of LAS on HF.

Conclusion: This MR analysis provided evidence of the causal links between genetically predicted HF and IS. Subgroup analysis highlighted the causal or suggestive relationship between genetically predicted HF and LAS or CES. The potential causal links need further investigation with genetic information about other ancestries or etiologies of HF.
Graph Embedding Based Novel Gene Discovery Associated With Diabetes Mellitus
Authors: Du Jianzong , Lin Dongdong , Yuan Ruan , Chen Xiaopei , Liu Xiaoli , Yan Jing
Published: December 2021

Diabetes mellitus is a group of complex metabolic disorders which has affected hundreds of millions of patients world-widely. The underlying pathogenesis of various types of diabetes is still unclear, which hinders the way of developing more efficient therapies. Although many genes have been found associated with diabetes mellitus, more novel genes are still needed to be discovered towards a complete picture of the underlying mechanism. With the development of complex molecular networks, network-based disease-gene prediction methods have been widely proposed. However, most existing methods are based on the hypothesis of guilt-by-association and often handcraft node features based on local topological structures. Advances in graph embedding techniques have enabled automatically global feature extraction from molecular networks. Inspired by the successful applications of cutting-edge graph embedding methods on complex diseases, we proposed a computational framework to investigate novel genes associated with diabetes mellitus. There are three main steps in the framework: network feature extraction based on graph embedding methods; feature denoising and regeneration using stacked autoencoder; and disease-gene prediction based on machine learning classifiers. We compared the performance by using different graph embedding methods and machine learning classifiers and designed the best workflow for predicting genes associated with diabetes mellitus. Functional enrichment analysis based on Human Phenotype Ontology (HPO), KEGG, and GO biological process and publication search further evaluated the predicted novel genes.
SIRPγ-CD47 Interaction Positively Regulates the Activation of Human T Cells in Situation of Chronic Stimulation
Authors: Dehmani Safa , Nerrière-Daguin Véronique , Néel Mélanie , Elain-Duret Nathan , Heslan Jean-Marie , Belarif Lyssia , Mary Caroline , Thepenier Virginie , Biteau Kevin , Poirier Nicolas , Blancho Gilles , Haspot Fabienne
Published: December 2021

A numerous number of positive and negative signalsviavarious molecules modulate T-cell activation. Within the various transmembrane proteins, SIRPγ is of interest since it is not expressed in rodents. SIRPγ interaction with CD47 is reevaluated in this study. Indeed, we show that the anti-SIRPγ mAb clone LSB2.20 previously used by others has not been appropriately characterized. We reveal that the anti-SIRPα clone KWAR23 is a Pan anti-SIRP mAb which efficiently blocks SIRPα and SIRPγ interactions with CD47. We show that SIRPγ expression on T cells varies with their differentiation and while being expressed on Tregs, is not implicated in their suppressive functions. SIRPγ spatial reorganization at the immune synapse is independent of its interaction with CD47.In vitroSIRPα-γ/CD47 blockade with KWAR23 impairs IFN-γ secretion by chronically activated T cells.In vivoin a xeno-GvHD model in NSG mice, the SIRPγ/CD47 blockade with the KWAR23 significantly delays the onset of the xeno-GvHD and deeply impairs human chimerism. In conclusion, we have shown that T-cell interaction with CD47 is of importance notably in chronic stimulation.
Single-Cell Immunogenomic Approach Identified SARS-CoV-2 Protective Immune Signatures in Asymptomatic Direct Contacts of COVID-19 Cases
Authors: Sen Kaushik , Datta Sudeshna , Ghosh Arup , Jha Atimukta , Ahad Abdul , Chatterjee Sanchari , Suranjika Sandhya , Sengupta Soumya , Bhattacharya Gargee , Shriwas Omprakash , Avula Kiran , Kshatri Jayasingh , Prasad Punit , Swain Rajeeb , Parida Ajay K. , Raghav Sunil K.
Published: December 2021

The response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is largely impacted by the level of virus exposure and status of the host immunity. The nature of protection shown by direct asymptomatic contacts of coronavirus disease 2019 (COVID-19)-positive patients is quite intriguing. In this study, we have characterized the antibody titer, SARS-CoV-2 surrogate virus neutralization, cytokine levels, single-cell T-cell receptor (TCR), and B-cell receptor (BCR) profiling in asymptomatic direct contacts, infected cases, and controls. We observed significant increase in antibodies with neutralizing amplitude in asymptomatic contacts along with cytokines such as Eotaxin, granulocyte-colony stimulating factor (G-CSF), interleukin 7 (IL-7), migration inhibitory factor (MIF), and macrophage inflammatory protein-1α (MIP-1α). Upon single-cell RNA (scRNA) sequencing, we explored the dynamics of the adaptive immune response in few representative asymptomatic close contacts and COVID-19-infected patients. We reported direct asymptomatic contacts to have decreased CD4+ naive T cells with concomitant increase in CD4+ memory and CD8+ Temra cells along with expanded clonotypes compared to infected patients. Noticeable proportions of class switched memory B cells were also observed in them. Overall, these findings gave an insight into the nature of protection in asymptomatic contacts.
Infectious Keratitis: An Update on Role of Epigenetics
Authors: Verma Sudhir , Singh Aastha , Varshney Akhil , Chandru R. Arun , Acharya Manisha , Rajput Jyoti , Sangwan Virender Singh , Tiwari Amit K. , Bhowmick Tuhin , Tiwari Anil
Published: December 2021

Epigenetic mechanisms modulate gene expression and function without altering the base sequence of DNA. These reversible, heritable, and environment-influenced mechanisms generate various cell types during development and orchestrate the cellular responses to external stimuli by regulating the expression of genome. Also, the epigenetic modifications influence common pathological and physiological responses including inflammation, ischemia, neoplasia, aging and neurodegeneration etc. In recent past, the field of epigenetics has gained momentum and become an increasingly important area of biomedical research As far as eye is concerned, epigenetic mechanisms may play an important role in many complex diseases such as corneal dystrophy, cataract, glaucoma, diabetic retinopathy, ocular neoplasia, uveitis, and age-related macular degeneration. Focusing on the epigenetic mechanisms in ocular diseases may provide new understanding and insights into the pathogenesis of complex eye diseases and thus can aid in the development of novel treatments for these diseases. In the present review, we summarize the clinical perspective of infectious keratitis, role of epigenetics in infectious keratitis, therapeutic potential of epigenetic modifiers and the future perspective.