bluuebunny/crossref_metadata_2025 huggingface dataset:
Projected Climate Change Effects on Global Vegetation Growth: A Machine Learning Approach
Authors: Nguyen Kieu Anh , Seeboonruang Uma , Chen Walter
Published: November 2023

In this study, a machine learning model was used to investigate the potential consequences of climate change on vegetation growth. The methodology involved analyzing the historical Normalized Difference Vegetation Index (NDVI) data and future climate projections under four Shared Socioeconomic Pathways (SSPs). Data from the Global Inventory Monitoring and Modeling System (GIMMS) dataset for the period 1981–2000 were used to train the machine learning model, while CMIP6 (Coupled Model Intercomparison Project Phase 6) global climate projections from 2021–2100 were employed to predict future NDVI values under different SSPs. The study results revealed that the global mean NDVI is projected to experience a significant increase from the period 1981–2000 to the period 2021–2040. Following this, the mean NDVI slightly increases under SSP126 and SSP245 while decreasing substantially under SSP370 and SSP585. In the near-term span of 2021–2040, the average NDVI value of SSP585 slightly exceeds that of SSP245 and SSP370, suggesting a positive vegetation development in response to a more pronounced temperature increase in the near term. However, if the trajectory of SSP585 persists, the mean NDVI will commence a decline over the subsequent three periods (2041–2060, 2061–2080, and 2080–2100) with a faster speed than that of SSP370. This decline is attributed to the adverse effects of a rapid temperature rise on vegetation. Based on the examination of individual continents, it is projected that the NDVI values in Africa, South America, and Oceania will decline over time, except under the scenario SSP126 during 2081–2100. On the other hand, the NDVI values in North America and Europe are anticipated to increase, with the exception of the scenario SSP585 during 2081–2100. Additionally, Asia is expected to follow an increasing trend, except under the scenario SSP126 during 2081–2100. In the larger scope, our research findings carry substantial implications for biodiversity preservation, greenhouse gas emission reduction, and efficient environmental management. The utilization of machine learning technology holds the potential to accurately predict future changes in vegetation growth and pinpoint areas where intervention is imperative.
Diversity and Functional Potential of Prokaryotic Communities in Depth Profile of Boreo-Nemoral Minerotrophic Pine Swamp (European Russia)
Authors: Golovchenko Alla V. , Dobrovolskaya Tatiana G. , Sokolova Diyana Sh. , Gracheva Tatiana A. , Dorchenkova Yuliya A. , Glukhova Tamara V. , Manucharova Natalia A.
Published: November 2023

Natural peatlands represent a wide range of habitats that contribute to the conservation of biodiversity, including microbial biodiversity. Molecular biological methods make it possible to significantly increase the accounting of microbial diversity compared to the cultivation methods. The studies on microbial diversity in minerotrophic peatlands using molecular biological methods lag significantly behind such studies for ombrotrophic peatlands. In this work, we characterized the taxonomic composition and functional potential of the prokaryotic community of the minerotrophic pine swamp (fen) in the Tver region of northwestern Russia using high-throughput sequencing of 16S rRNA gene fragments. This study is unique, since it was carried out not in individual horizons but across the entire fen profile, taking into account the differentiation of the profile into the acrotelm and catotelm. The composition and dominants of bacterial and archaeal communities were determined not only at the level of phyla but also at the level of classes, families, and cultivated genera. The prokaryotic community of the studied fen was shown to have a high taxonomic diversity (28 bacterial and 10 archaeal phyla were identified). The profile differentiation of the taxonomic composition of prokaryotic communities is most clearly manifested in the analysis of the acrotelm and catotelm. In the bacterial communities of the acrotelm, the top three phyla included Acidobacteriota, Alphaproteobacteria, and Actinomycetota, in the catotelm—Betaproteobacteria, Bacteroidota, and Chloroflexota. In archaeal communities of the acrotelm, we discovered the monodominance of Nitrososphaerota, in the catotelm—the dominance of Bathyarchaeota and subdominance of Thermoplasmatota, Halobacterota, and Aenigmarchaeota. The hot spots of microbial diversity in the studied fen profile were found to be the 0–20 cm layer of the acrotelm and the 150–200 cm layer of the catotelm. In contrast to the taxonomic composition, the functional profiles of the prokaryotic communities of the acrotelm and catotelm were generally similar, except for methane metabolism, which was primarily carried out in the catotelm.
Predicting the Stand Growth and Yield of Mixed Chinese Fir Forests Based on Their Site Quality, Stand Density, and Species Composition
Authors: Pan Xin , Sun Shuaichao , Hua Weiping , Li Jun , Zhuang Chongyang , Jiang Xidian
Published: November 2023

The Chinese fir (Cunninghamia lanceolata) is the largest tree species used for afforestation in China. The purpose of this study was to explore the effects of site quality, stand density, and tree species composition on the growth and yield of mixed Chinese fir forests and to build prediction models for their stand average DBH (diameter at breast height), average height, and volume. Using 430 plots of mixed Chinese fir forests in the Fujian Province of China, the optimal base models for predicting stand average DBH, average height, and volume were selected from the Schumacher, Korf, Logistic, Mitscherlich, and Richards equations. On this basis, the site class index (SCI), stand density index (SDI), and tree species composition coefficient (TSCC) were introduced to improve the model’s performance, and the applicability of the different models was evaluated. The optimal base models for the average DBH, average height, and stand volume of mixed Chinese fir forests all used the Richards equation. The best fitting effect was obtained when the SCI was introduced into parameter a in the average height model, while the inclusion of the TSCC did not improve the model significantly. The fitting effects of the average DBH and stand volume models were both best in the form of y=a1SCIa2[1−exp⁡(−b1SDIb2)t]c when the SCI and SDI were introduced. When the TSCC was further included, the fitting effects of the stand average DBH and volume models were significantly improved, with their R2 increased by 47.47% and 58.45%, respectively, compared to the base models. The optimal models developed in this study showed good applicability; the residuals were small and distributed uniformly. We found that the SCI had an impact on the maximum values of the stand average DBH, average height, and volume; the SDI was closely related to the growth rate of the diameter and volume, while the TSCC influenced the maximum values of the stand average DBH and volume. The model system established in this study can provide a reference for the harvest prediction and mixing ratio optimization of mixed Chinese fir forests.
Silver Nanoparticles and Chitosan Oligomers Composites as Poplar Wood Protective Treatments against Wood-Decay Fungi and Termites
Authors: Spavento Eleana , de Troya-Franco María Teresa , Acuña-Rello Luis , Murace Mónica , Santos Sara M. , Casado-Sanz Milagros , Martínez-López Roberto D. , Martín-Gil Jesús , Álvarez-Martínez Javier , Martín-Ramos Pablo
Published: November 2023

This study focuses on Populus ×euramericana (Dode) Guinier, a globally distributed fast-growing tree. Despite its valuable wood, it exhibits low durability. The aim of this study was to assess the efficacy of a binary composite comprising silver nanoparticles (AgNPs) and chitosan oligomers (COS) in protecting P. ×euramericana ‘I-214’ wood against degradation caused by xylophagous fungi and termites through vacuum-pressure impregnation. The test material was carefully selected and conditioned following the guidelines of EN 350:2016, and impregnation was carried out in accordance with EN 113-1:2021. Five concentrations of AgNPs–COS composites were utilized. Biodeterioration resistance was evaluated based on EN 350:2016 for white (Trametes versicolor (L.) Lloyd) and brown (Coniophora puteana (Schumach.) P.Karst.) rot fungi, and EN 117:2012 for subterranean termites (Reticulitermis grassei Clément). The durability class and use class were assigned following EN 350:2016 and EN 335:2013, respectively. In comparison to the untreated control, the binary solution at its highest concentration (AgNPs 4 ppm + COS 20 g·L−1) demonstrated a notable reduction in weight loss, decreasing from 41.96 ± 4.49% to 30.15 ± 3.08% for white-rot fungi and from 41.93 ± 4.33% to 27.22 ± 0.66% for brown rot fungi. Furthermore, the observed termite infestation shifted from “heavy” to “attempted attack”, resulting in a decrease in the survival rate from 53.98 ± 10.40% to 26.62 ± 8.63%. Consequently, the durability classification of P. ×euramericana I-214 witnessed an enhancement from “Not durable” to “Slightly” and “Moderately durable” concerning decay fungi and termites, respectively. These findings expand the potential applications of this wood and substantiate the advantages of employing this environmentally friendly treatment.
Effects of Different Nitrogen Application Rates on Root Growth and Distribution of Fine Root Length across Diameter Classes of Wolfberry (Lycium barbarum L.)
Authors: Liang Xiaojie , An Wei , Li Yuekun , Wang Yajun , Su Shuchai
Published: November 2023

The optimized cultivation process of wolfberry (Lycium barbarum L.) to maintain a consistently high and stable yield relies on the prolonged use of significant amounts of nitrogen fertilizers. However, this practice leads to increased production costs and various issues, such as soil pollution and compaction. To address these concerns, a three-year field trial was conducted involving different nitrogen application rates: N1 (20% nitrogen (N) reduction, 540 kg·hm−2), N2 (medium N, 675 kg·hm−2), and N3 (20% nitrogen increase, 810 kg·hm−2). The results showed that the inter-annual growth and development of wolfberry roots had two rapid growth peaks. In comparison with the N3 treatment, the root morphological characteristics index increased significantly under the N1 and N2 treatments. Among the different diameter classes, the most significant increase in fine root length, with an average diameter between 0.4 and 0.8 mm, occurred under the N1, N2, and N3 treatments, accounting for 50.6%, 50.92%, and 47.72% of the total annual growth of root length increments, respectively. Concerning the distribution of fine roots, the active layer depth extended under the N2 treatment suggesting that medium nitrogen application favored the longitudinal extension of fine roots. Leaf nitrogen content and the chlorophyll meter values (SPAD values) in the upper part of the plant, at the tip of shoots/branches, were the most sensitive indicators to changes in nitrogen application rates. These values increased significantly with higher nitrogen application amounts. Similarly, the contents of total sugar, betaine, and β-carotene increased with increasing nitrogen application rates, while the contents of Lycium barbarum polysaccharides (LBPs) and total flavonoids decreased. Finally, based on a comprehensive principal component evaluation, the rankings for root growth and plant development under various nitrogen application treatments were as follows: N2 (1.891) > N1 (0.002) > N3 (−1.894). The results showed that both the aboveground and belowground growth and development of wolfberry plants were most optimized under the N2 treatment. These findings provide a foundational reference for constructing good root morphology of wolfberry through cultivation practices such as nitrogen fertilizer management.
Study on the Extraction and Identification of DNA from Ten Dalbergia Species
Authors: Gan Changtao , He Haishan , Qiu Jian
Published: November 2023

Most Dalbergia species are economically valuable and have been over-exploited, which has raised concerns. The regulation and protection of this genus require accurate and rapid authentication and identification processes. To address the issue of high residual inhibitors in extracted DNA from the Dalbergia xylem, an optimized DNA extraction experiment was performed on 10 species of Dalbergia wood stored for 1–5 years; in particular, no gene sequence for D. tsoi can be found in the NCBI database. Additionally, universal primers ITS2 were used for PCR amplification and sequencing to confirm the effectiveness of DNA extraction. The results revealed that rinsing the wood with 0.25 M ammonium acetate buffer produced DNA with a high purity, without a significant decrease in the DNA yield. To achieve an optimal DNA yield, the wood DNA should be rinsed with ammonium acetate fewer than three times. All the wood DNA obtained using the kit method and treated with the ammonium acetate buffer rinsing solution one to four times was successfully amplified. The NJ phylogenetic tree constructed based on ITS2 can distinguish D. tsoi from other Dalbergia spp., and the predicted ITS2 secondary structure showed the difference between species. This experiment extracted high-quality DNA from wood, without the need for purification kits, thereby improving the efficiency of the extraction process. The extracted DNA was directly used for follow-up molecular experiments.
Effects of Climate Change and Fire on the Middle and Late Holocene Forest History in Yenisei Siberia
Authors: Novenko Elena , Rudenko Olga , Mazei Natalia , Kupriyanov Dmitriy , Andreev Rodion , Shatunov Anton , Kusilman Maria , Prokushkin Anatoly , Olchev Alexander
Published: November 2023

This study presents the long-term forest history in the forest–tundra ecotone of the Low Yenisei River basin. The new high-resolution pollen and macroscopic charcoal data were inferred from the 8.6 m long peat archive covering the last 6300 years. Climate reconstructions are based on the application of the best modern analogue technique using pollen data. Our findings suggest an alternation of phases of middle-taiga forests of Larix sibirica, Abies sibirica, Picea obovata, and Pinus sibirica (intervals of climate warming: 6320–6050, 5790–5370, 4480–4220, and 3600–2700 cal yr BP, respectively) and open larch woodlands with the participation of Betula, Picea, and Pinus sibirica, typical for northern taiga (intervals of climate cooling and increasing humidification: 5370–4480, 4220–3600 cal yr BP, respectively). The vegetation pattern of the region became similar to the modern one around 2700 cal yr BP. Climate warming caused a northward shift of vegetation-zone boundaries in Yenisei Siberia and an expansion of the range of Abies sibirica by about 200 km to the north compared to the present day. The increased frequency of fires and biomass burning during warm periods may promote the melting of the local permafrost, thereby enhancing the tree growth and regeneration.
Empowering Digital Twin for Future Networks with Graph Neural Networks: Overview, Enabling Technologies, Challenges, and Opportunities
Authors: Ngo Duc-Thinh , Aouedi Ons , Piamrat Kandaraj , Hassan Thomas , Raipin-Parvédy Philippe
Published: November 2023

As the complexity and scale of modern networks continue to grow, the need for efficient, secure management, and optimization becomes increasingly vital. Digital twin (DT) technology has emerged as a promising approach to address these challenges by providing a virtual representation of the physical network, enabling analysis, diagnosis, emulation, and control. The emergence of Software-defined network (SDN) has facilitated a holistic view of the network topology, enabling the use of Graph neural network (GNN) as a data-driven technique to solve diverse problems in future networks. This survey explores the intersection of GNNs and Network digital twins (NDTs), providing an overview of their applications, enabling technologies, challenges, and opportunities. We discuss how GNNs and NDTs can be leveraged to improve network performance, optimize routing, enable network slicing, and enhance security in future networks. Additionally, we highlight certain advantages of incorporating GNNs into NDTs and present two case studies. Finally, we address the key challenges and promising directions in the field, aiming to inspire further advancements and foster innovation in GNN-based NDTs for future networks.
Statistical Model Checking in Process Mining: A Comprehensive Approach to Analyse Stochastic Processes
Authors: Mangi Fawad Ali , Su Guoxin , Zhang Minjie
Published: November 2023

The study of business process analysis and optimisation has attracted significant scholarly interest in the recent past, due to its integral role in boosting organisational performance. A specific area of focus within this broader research field is process mining (PM). Its purpose is to extract knowledge and insights from event logs maintained by information systems, thereby discovering process models and identifying process-related issues. On the other hand, statistical model checking (SMC) is a verification technique used to analyse and validate properties of stochastic systems that employs statistical methods and random sampling to estimate the likelihood of a property being satisfied. In a seamless business setting, it is essential to validate and verify process models. The objective of this paper is to apply the SMC technique in process mining for the verification and validation of process models with stochastic behaviour and large state space, where probabilistic model checking is not feasible. We propose a novel methodology in this research direction that integrates SMC and PM by formally modelling discovered and replayed process models and apply statistical methods to estimate the results. The methodology facilitates an automated and proficient evaluation of the extent to which a process model aligns with user requirements and assists in selecting the optimal model. We demonstrate the effectiveness of our methodology with a case study of a loan application process performed in a financial institution that deals with loan applications submitted by customers. The case study highlights our methodology’s capability to identify the performance constraints of various process models and aid enhancement efforts.
Extended Reality (XR) Engines for Developing Gamified Apps and Serious Games: A Scoping Review
Authors: Marín-Vega Humberto , Alor-Hernández Giner , Bustos-López Maritza , López-Martínez Ignacio , Hernández-Chaparro Norma Leticia
Published: November 2023

Extended Reality (XR) is an emerging technology that enables enhanced interaction between the real world and virtual environments. In this study, we conduct a scoping review of XR engines for developing gamified apps and serious games. Our study revolves around four aspects: (1) existing XR game engines, (2) their primary features, (3) supported serious game attributes, and (4) supported learning activities. We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) model to conduct the scoping review, which included 40 primary studies published between 2019 and 2023. Our findings help us understand how current XR engines support the development of XR-enriched serious games and gamified apps for specific learning activities. Additionally, based on our findings, we suggest a set of pre-established game attributes that could be commonly supported by all XR game engines across the different game categories proposed by Lameras. Hence, this scoping review can help developers (1) select important game attributes for their new games and (2) choose the game engine that provides the most support to these attributes.
Open Radio Access Networks for Smart IoT Systems: State of Art and Future Directions
Authors: Musa Abubakar Ahmad , Hussaini Adamu , Qian Cheng , Guo Yifan , Yu Wei
Published: November 2023

The Internet of Things (IoT) constitutes a vast network comprising various components such as physical devices, vehicles, buildings, and other items equipped with sensors, actuators, and software. These components are interconnected, facilitating the collection and exchange of copious data across networked communications. IoT empowers extensive monitoring and control over a myriad of objects, enabling them to gather and disseminate data that bolster applications, thereby enhancing the system’s capacity for informed decision making, environmental surveillance, and autonomous inter-object interaction, all without the need for direct human involvement. These systems have achieved seamless connectivity requirements using the next-generation wireless network infrastructures (5G, 6G, etc.), while their diverse reliability and quality of service (QoS) requirements across various domains require more efficient solutions. Open RAN (O-RAN), i.e., open radio open access network (RAN), promotes flexibility and intelligence in the next-generation RAN. This article reviews the applications of O-RAN in supporting the next-generation smart world IoT systems by conducting a thorough survey. We propose a generic problem space, which consists of (i) IoT Systems: transportation, industry, healthcare, and energy; (ii) targets: reliable communication, real-time analytics, fault tolerance, interoperability, and integration; and (iii) artificial intelligence and machine learning (AI/ML): reinforcement learning (RL), deep neural networks (DNNs), etc. Furthermore, we outline future research directions concerning robust and scalable solutions, interoperability and standardization, privacy, and security. We present a taxonomy to unveil the security threats to emerge from the O-RAN-assisted IoT systems and the feasible directions to move this research forward.
The Multiband over Spatial Division Multiplexing Sliceable Transceiver for Future Optical Networks
Authors: Nadal Laia , Ali Mumtaz , Vílchez Francisco Javier , Fàbrega Josep Maria , Svaluto Moreolo Michela
Published: November 2023

In the last 15 years, global data traffic has been doubling approximately every 2–3 years, and there is a strong indication that this pattern will persist. Hence, also driven by the emergence of new applications and services expected within the 6G era, new transmission systems and technologies should be investigated to enhance network capacity and achieve increased bandwidth, improved spectral efficiency, and greater flexibility to effectively accommodate all the expected data traffic. In this paper, an innovative transmission solution based on multiband (MB) over spatial division multiplexing (SDM) sliceable bandwidth/bitrate variable transceiver (S-BVT) is implemented and assessed in relation to the provision of sustainable capacity scaling. MB transmission (S+C+L) over 25.4 km of 19-cores multicore fibre (MCF) is experimentally assessed and demonstrated achieving an aggregated capacity of 119.1 Gb/s at 4.62×10−3 bit error rate (BER). The proposed modular sliceable transceiver architecture arises as a suitable option towards achieving 500 Tb/s per fibre transmission, by further enabling more slices covering all the available S+C+L spectra and the 19 cores of the MCF.
Macroeconomic Predictions Using Payments Data and Machine Learning
Authors: Chapman James T. E. , Desai Ajit
Published: November 2023

This paper assesses the usefulness of comprehensive payments data for macroeconomic predictions in Canada. Specifically, we evaluate which type of payments data are useful, when they are useful, why they are useful, and whether machine learning (ML) models enhance their predictive value. We find payments data with a factor model can help improve accuracy up to 25% in predicting GDP, retail, and wholesale sales; and nonlinear ML models can further improve the accuracy up to 20%. Furthermore, we find the retail payments data are more useful than the data from the wholesale system; and they add more value during crisis and at the nowcasting horizon due to the timeliness. The contribution of the payments data and ML models is small and linear during low and normal economic growth periods. However, their contribution is large, asymmetrical, and nonlinear during crises such as COVID-19. Moreover, we propose a cross-validation approach to mitigate overfitting and use tools to overcome interpretability in the ML models to improve their effectiveness for policy use.
Development and Characterization of Econazole Topical Gel
Authors: Bayan Mohammad F. , Chandrasekaran Balakumar , Alyami Mohammad H.
Published: November 2023

The purpose of this work was to develop a novel topical formulation of econazole nitrate based on gel that can be easily scaled up in one pot for the potential treatment of fungal and yeast infections. Econazole nitrate, a topical antifungal, is used to treat tinea versicolor, tinea pedis, and tinea cruris. Compared to applying cream or ointment, topical gels offer numerous advantages, one of which is that the drug is released more quickly to the intended site of action. A viscous mixture of propylene glycol, Capmul® MCM C8, methyl and propyl paraben, and econazole nitrate were mixed together before being formulated into the optimized Carbopol® gel bases. The gel’s color, appearance, and homogeneity were assessed visually. For every formulation, the drug content, pH, viscosity, spreadability, and gel strength were characterized. The cup plate diffusion method was used to evaluate the anti-fungal activity of the prepared formulations. To assess the behavior of the developed system, studies on in vitro release and mechanism were conducted. The manufactured formulations were transparent, pale yellow, and exhibited excellent homogeneity. The pH of each formulation was roughly 6.0, making them suitable for topical use. The concentration of Carbopol® 940 resulted in a significant increase in viscosity and gel strength but a significant decrease in spreadability. It was demonstrated that the prepared formulations inhibited the growth of Candida albicans and Aspergillus fumigatus. In contrast, the standard blank gel showed no signs of antifungal action. By increasing the concentration of Carbopol® 940, the in vitro release profile of econazole nitrate significantly decreased. Following the Korsmeyer–Peppas model fitting, all formulations exhibited n values greater than 0.5 and less than 1, indicating that diffusion and gel swelling control econazole nitrate release.
Population Structure and Genetic Diversity of Yunling Cattle Determined by Whole-Genome Resequencing
Authors: Chen Jian , Zhang Lilian , Gao Lutao , Wei Zaichao , Dang Dong , Yang Linnan
Published: November 2023

The Yunling cattle breed, a three-breed crossbreed, which comprises 50% Brahman cattle, 25% Murray Grey cattle and 25% Yunnan Yellow cattle, has several advantageous traits, including rapid growth, superior meat quality, ability to improve tolerance in hot and humid climates, tick resistance and rough feed. It can be rightfully stated that Yunling cattle serve as vital genetic repositories of the local Yunnan cattle. Gaining insights into the genetic information of Yunling cattle plays a significant role in the formulation of sound breeding strategies for this breed, safeguarding genetic resources and mitigating the risks associated with inbreeding depression. In this study, we constructed the Yunling cattle standard reference genome and aligned the whole genomes of 129 Yunling cattle individuals to the constructed reference genome to estimate the current genetic status of Yunling cattle in Yunnan Province, China. The average alignment rate and the average percentage of properly paired are both 99.72%. The average nucleotide diversity in Yunling cattle is 0.000166, which indicates a lower level of diversity. Population structure analysis classified Yunling cattle into two subgroups. Inbreeding analysis revealed that inbreeding events did occur in the Yunling cattle, which may have contributed to the low genetic diversity observed. This study presents a comprehensive assessment of the genetic structure and diversity among the Yunling cattle and provides a theoretical foundation for the preservation and exploitation of these precious germplasm resources.
Functional Characterization of the Almstn2 Gene and Its Association with Growth Traits in the Yellowfin Seabream Acanthopagrus latus (Hottuyn, 1782)
Authors: Guo Jianyi , Guo Huayang , Chen Chuanghua , Yu Fangzhao , Liu Baosuo , Zhang Nan , Xian Lin , Luo Zhiping , Liu Wen , Zhu Kecheng , Zhang Dianchang
Published: November 2023

Myostatin (mstn), also known as GDF8, is a growth and differentiation factor of the transforming growth factor-β (TGF-β) superfamily and plays a key inhibitory effect in the regulation of skeletal muscle development and growth in vertebrates. In the present study, to comprehend the role of the mstn2 gene of the yellowfin seabream Acanthopagrus latus (Almstn2b), the genomic sequence of Almstn2b is 2359 bp, which encodes 360 amino acids and is composed of three exons and two introns, was obtained. Two typical regions, a TGF-β propeptide and TGF-β domain, constitute Almstn2b. The topology indicated that Almstn2 was grouped together with other Perciformes, such as the gilthead seabream Sparus aurata. Moreover, Almstn2b was mainly expressed in the brain, fins, and spleen. Furthermore, five SNPs, one in the exons and four in the introns, were identified in the Almstn2b gene. The allele and genotype frequencies of SNP-Almstn2b +1885 A/G were significantly related to the total weight, interorbital distance, stem length, tail length, caudal length, caudal height, body length, and total length (p < 0.05). The allele and genotype frequencies of SNP-Almstn2b +1888 A/G were significantly related to the weight, interorbital distance, long head behind the eyes, body height, tail length, caudal length, and body length. Additionally, the relationship between the SNP-Almstn2b +1915 A/G locus and weight and long head behind the eyes was significant (p < 0.05). Furthermore, the other two SNPs were not significantly associated with any traits. Thus, the SNPs identified in this study could be utilized as candidate SNPs for breeding and marker-assisted selection in A. latus.
Genomics of Shrimp Allergens and Beyond
Authors: Li Shanshan , Chu Ka Hou , Wai Christine Yee Yan
Published: November 2023

Allergy to shellfishes, including mollusks and crustaceans, is a growing health concern worldwide. Crustacean shellfish is one of the “Big Eight” allergens designated by the U.S. Food and Drug Administration and is the major cause of food-induced anaphylaxis. Shrimp is one of the most consumed crustaceans triggering immunoglobulin E (IgE)-mediated allergic reactions. Over the past decades, the allergen repertoire of shrimp has been unveiled based on conventional immunodetection methods. With the availability of genomic data for penaeid shrimp and other technological advancements like transcriptomic approaches, new shrimp allergens have been identified and directed new insights into their expression levels, cross-reactivity, and functional impact. In this review paper, we summarize the current knowledge on shrimp allergens, as well as allergens from other crustaceans and mollusks. Specific emphasis is put on the genomic information of the shrimp allergens, their protein characteristics, and cross-reactivity among shrimp and other organisms.
Pleistocene Landscape Dynamics Drives Lineage Divergence of a Temperate Freshwater Fish Gobio rivuloides in Coastal Drainages of Northern China
Authors: Ni Xiaomin , Chen Yun , Deng Guangmin , Fu Cuizhang
Published: November 2023

Understanding historical processes underlying lineage distribution patterns is a primary goal of phylogeography. We selected Gobio rivuloides (Cypriniformes: Gobionidae) as a model to improve our knowledge about how intraspecific genetic divergence of freshwater fishes arises in coastal drainages of northern China via statistical analysis using cytochrome b gene. The time-calibrated phylogeny of G. rivuloides showed the divergence of two major lineages (I and II) at ~0.98 Ma (million years ago). Lineage I can be divided into two sub-lineages (I-A and I-B) with a divergence time of ~0.83 Ma. Sub-lineage I-A inhabits the Amur River, and sub-lineage I-B lives in the Luan River and Liao River. Lineage II is distributed in the Yellow River and Hai River, with close genetic relationships between the two drainages, and can be split into two sub-lineages (II-C and II-D) with a divergence time of ~0.60 Ma. Our findings indicate that the splitting of lineages and sub-lineages could be attributed to geographic isolation caused by the formation of the Bohai Sea, river capture, and the episodic hydrologic closing of a paleolake during the late Lower–Middle Pleistocene. It is also the first report we know of displaying a clear phylogeographic break for freshwater fishes across coastal drainages in northern China.
Angioimmunoblastic T-Cell Lymphoma after Treatment of Classic Hodgkin Lymphoma: A Case Report
Authors: Tanaka Ken , Miyoshi Hiroaki , Yamashita Yusuke , Iwamoto Ryuta , Yokoya Yuma , Tochino Yuichi , Arakawa Fumiko , Tamura Shinobu , Murata Shin-Ichi , Sonoki Takashi , Ohshima Koichi
Published: November 2023

We report a case of a 24-year-old man who developed angioimmunoblastic T-cell lymphoma (AITL) after treatment for refractory lymphocyte-rich classic Hodgkin lymphoma (LR-CHL). This patient was treated with the BV+AVD (brentuximab vedotin, doxorubicin, vinblastine, and dacarbazine) protocol for LR-CHL but progressed before completing chemotherapy. The pathological imaging showed the typical findings of LR-CHL at the first onset and first progression. Rescue chemotherapy and high-dose chemotherapy combined with autologous hematopoietic stem cell transplantation (AHSCT) were performed for refractory LR-CHL, and complete remission was achieved. However, the recurrence was suspected 6 months after AHSCT. The pathological findings of the lymph node biopsy at this time were different from those of the previous two lymph node biopsies, demonstrating findings of AITL. The finding of the immunohistochemical staining and polymerase chain reaction results supported the diagnosis. Although it has been reported that the risk for the development of non-Hodgkin lymphoma after treatment for Hodgkin lymphoma is increased, most are B-cell lymphomas, and few cases of AITL have been reported. AITL is a type of peripheral T-cell lymphoma that generally occurs in middle-aged and elderly people and that rarely occurs in young people. Here, we were able to make an accurate diagnosis by performing re-examination even when recurrence of LR-CHL was suspected. As there are no detailed case reports of AITL developing into secondary non-Hodgkin lymphoma, here we report on an identified case.
Warm Bulb Storage Optimises Flowering Attributes and Foliage Characteristics in Amaryllis belladonna L.
Authors: Wilmot Carolyn Margaret , Jimoh Muhali Olaide , Laubscher Charles Petrus
Published: November 2023

Amaryllis belladonna is an autumn-flowering bulbous geophyte endemic to the Western Cape, South Africa. The species’ erratic flowering disposition and brief flowering period upon maturity limit its economic productivity and competitiveness within the traditional genera of cut flowers and potted plants. However, it can be an attractive, eco-friendly, seasonal addition to the specialty floriculture market. A 10-month study evaluated the effects of a warm storage period on A. belladonna bulbs’ flowering yield, flowering time, quality characteristics, and foliage growth. The experiment comprised dormant flower-sized bulbs randomly assigned to one of six storage regimes of either a 0- (no storage control), 4-, 6-, 8-, 10-, or 12-week interval periods at a continuous warm temperature of 23 ± 1 °C before planting into pots between mid-November 2021 and mid-February 2022 in the greenhouse. The results showed that flowering production (64.3% flowering after the 12-week storage), flowering time (anthesis occurring 9 days after the 10- and 12-week storage), and quality attributes (number of florets in the inflorescence, scape diameter, inflorescence fullness ratio, and pot longevity) of A. belladonna scapes were significantly impacted by warm bulb storage, but not foliage growth. Irrespective of bulb storage, inflorescence abortion occurred. An extended bulb storage did not advance the flowering time despite a greater harvest and shorter cultivation periods after planting. This study established that a cumulative temperature range during bulb dormancy is crucial for supporting the A. belladonna inflorescence maturity’s energetic demands and the opening of floret buds. Bulbs should be stored at elevated temperatures for at least 8–10 weeks to attain the best floret-quality attributes and longevity. However, for an economical and sustainable greenhouse and specialty cut flower production, 12-week warm bulb storage is recommended to achieve the optimal anthesis in the shortest interval for this seasonal single-harvest species after planting.
The Placement of Children in Need of Out-of-Home Care: Forms of Care and Differences in Attachment Security and Behavioral Problems in the Italian Context
Authors: Cassibba Rosalinda , Balenzano Caterina , Silletti Fabiola , Coppola Gabrielle , Costantini Alessandro , Giorgio Stefania , Taurino Alessandro , Cheah Charissa S. L. , Musso Pasquale
Published: November 2023

The current paper investigated differences in secure attachment levels and behavioral problems among four groups of children in out-of-home care in Italy: closed adoption (child and birth parents not in contact following adoption), open adoption (child and birth parents still in contact after placement), foster care (child living temporarily with relatives or unrelated foster parents) and institutional care (child in residential care for large groups of children). One hundred and thirty children aged 10–19 were included in this study. The Attachment Interview for Childhood and Adolescence and the Achenbach Youth Self-Report were employed to measure participants’ secure attachment levels and behavioral problems. Both a multivariate analysis of covariance and measured variable path analysis were performed. Age, gender and time elapsed between the request for child protection and placement on out-of-home care were used as covariates. The results showed that adolescents in closed adoption had higher secure attachment scores than those in foster care and institutional care, while adolescents in open adoption scored significantly higher on problem behaviors than those in the other out-of-home care groups. Findings were discussed in terms of limitations and implications for future research.
Modelling the Predictors of Mobile Health (mHealth) Adoption among Healthcare Professionals in Low-Resource Environments
Authors: Azam Mehreen , Bin Naeem Salman , Kamel Boulos Maged N. , Faiola Anthony
Published: November 2023

This study was conducted with objectives to measure and validate the unified theory of the acceptance and use of technology (UTAUT) model as well as to identify the predictors of mobile health (mHealth) technology adoption among healthcare professionals in limited-resource settings. A cross-sectional survey was conducted at the six public and private hospitals in the two districts (Lodhran and Multan) of Punjab, Pakistan. The participants of the study comprised healthcare professionals (registered doctors and nurses) working in the participating hospitals. The findings of the seven-factor measurement model showed that behavioral intention (BI) to mHealth adoption is significantly influenced by performance expectancy (β = 0.504, CR = 5.064, p < 0.05) and self-concept (β = 0.860, CR = 5.968, p < 0.05) about mHealth technologies. The findings of the structural equation model (SEM) showed that the model is acceptable (χ2 (df = 259) = 3.207; p = 0.000; CFI = 0.891, IFI = 0.892, TLI = 0.874, RMSEA = 0.084). This study suggests that the adoption of mHealth can significantly help in improving people’s access to quality healthcare resources and services as well as help in reducing costs and improving healthcare services. This study is significant in terms of identifying the predictors that play a determining role in the adoption of mHealth among healthcare professionals. This study presents an evidence-based model that provides an insight to policymakers, health organizations, governments, and political leaders in terms of facilitating, promoting, and implementing mHealth adoption plans in low-resource settings, which can significantly reduce health disparities and have a direct impact on health promotion.
Prospective Associations between Maternal Depressive Symptoms during Early Infancy and Growth Deficiency from Childhood to Adolescence
Authors: Pagani Linda S. , Harandian Kianoush , Necsa Beatrice , Harbec Marie-Josée
Published: November 2023

Maternal health represents an important predictor of child development; yet it often goes unnoticed during pediatric visits. Previous work suggests that mental state affects parenting. The relationship between infant exposure to maternal depressive symptoms suggests conflicting findings on physical growth. Body mass index (BMI) has not been rigorously examined across development. Using a prospective-longitudinal birth cohort of 2120 infants (50.7% boys), we estimated the prospective relationship between symptoms of maternal depressive symptoms at 5 months postpartum and later BMI in typically developing children. We hypothesized that maternal depressive symptom severity would predict later BMI through to adolescence. Mothers self-reported depressive symptoms at 5 months. Child BMI was measured by a trained research assistant at ages 6, 8, 10, 13, and 15 years. We estimated a series of sex-stratified regressions in which BMI was linearly regressed on maternal symptoms, while controlling for potential pre-existing/concurrent individual and family confounding factors. Boys born to mothers with more severe depressive symptoms at age 5 months had a significantly lower BMI than other boys at subsequent ages. There were no such associations observed for girls. Maternal depressive symptoms were prospectively associated with later BMI for sons and not daughters, predicting risk of faltering in growth through to adolescence. Health practitioners should routinely assess maternal psychological functioning during pediatric visits to optimize parent and child flourishment.
Ginsenoside Rg3 Protects against Diabetic Cardiomyopathy and Promotes Adiponectin Signaling via Activation of PPAR-γ
Authors: Zhang Chenyang , Yu Huifang , Ye Jingxue , Tong Hongna , Wang Min , Sun Guibo
Published: November 2023

Ginsenoside Rg3 extracted from Panax notoginseng has therapeutic effects on diabetes and heart diseases. However, the underlying mechanism of ginsenoside Rg3 on diabetic cardiomyopathy (DCM) remains unclear. 24-week-old diabetic db/db mice were treated with ginsenoside Rg3 for 12 weeks, then body weight, serum lipids, adiponectin levels, as well as cardiac function and pathological morphology, were measured. The targets of ginsenoside Rg3 and its regulation of the adiponectin pathway were also evaluated on 3T3-L1 or H9c2 cells. Ginsenoside Rg3 directly bound to PPAR-γ, improving adiponectin secretion and promoting adiponectin signaling. Significantly attenuated overweight, hyperglycemia, and hyperlipidemia, as well as alleviated lipid accumulation and dysfunction in adipose, liver, and heart tissues, were observed in the ginsenoside Rg3-treated group. Ginsenoside Rg3 could be a promising drug targeting PPAR-γ to treat diabetic cardiomyopathy.
Biosourced Multiphase Systems Based on Poly(Lactic Acid) and Polyamide 11 from Blends to Multi-Micro/Nanolayer Polymers Fabricated with Forced-Assembly Multilayer Coextrusion
Authors: Jaouadi Nour , Jaziri Mohamed , Maazouz Abderrahim , Lamnawar Khalid
Published: November 2023

The objective of the present study was to investigate multiphase systems based on polylactic acid (PLA) and polyamide 11 (PA11) from blends to multilayers. Firstly, PLA/PA11 blends compatibilized with a multifunctionalized epoxide, Joncryl, were obtained through reactive extrusion, and the thermal, morphological, rheological, and mechanical behaviors of these materials were investigated. The role of Joncryl as a compatibilizer for the PLA/PA11 system was demonstrated by the significant decrease in particle size and interfacial tension as well as by the tensile properties exhibiting a ductile behavior. Based on these findings, we were able to further clarify the effects of interdiffusion and diffuse interphase formation on the structure, rheology, and mechanics of compatible multilayered systems fabricated with forced-assembly multilayer coextrusion. The results presented herein aim to provide a deeper understanding of the interfacial properties, including the rheological, mechanical, and morphological behaviors, towards the control of the interface and confinement in multilayer polymers resulting from coextrusion, and also to permit their use in advanced applications.
Increased RBP4 and Asprosin Are Novel Contributors in Inflammation Process of Periodontitis in Obese Rats
Authors: Zhang Yuwei , Zhang Yifei , Tan Yutian , Luo Xiao , Jia Ru
Published: November 2023

There is a significant comorbidity between obesity and periodontitis, while adipokines are pivotal in the immunoinflammatory process, which may play a role in this special relationship. We aimed to assess the effect of adipokines as mediators in the progression of periodontitis in obese Sprague Dawley rats. Rats were divided into four groups: normal body weight with and without periodontitis and obesity with and without periodontitis. Experimental obesity and periodontitis were induced by a high-fat diet or ligaturing, and the effect was measured using metabolic and micro-computed tomography analysis and histological staining. Compared with the other three groups, the group of periodontitis with obesity (OP) had the heaviest alveolar bone absorption, the largest increase in osteoclasts, the utmost inflammatory cell infiltration and the highest expressions of pro-inflammatory cytokines and nuclear factor-kappa B ligand (RANKL); meanwhile, its expression of the osteogenesis-related gene was the lowest among the four groups. The expressions of leptin, visfatin, resistin, retinol-binding protein 4 (RBP4) and asprosin were upregulated, while adiponectin was decreased significantly in OP. The strong positive associations between the periodontal or circulating levels of RBP4 (or asprosin) and the degree of alveolar resorption in experimental periodontitis and obese rats were revealed. The upregulated expression of inflammation biomarkers, the corresponding degradation in connective tissue and the generation of osteoclasts in periodontitis were activated and exacerbated in obesity. The elevated level of RBP4/asprosin may contribute to a more severe periodontal inflammatory state in obese rats.