bluuebunny/crossref_metadata_2025_split huggingface dataset:
Parafoveal cone function in choroideremia assessed with adaptive optics optoretinography
Authors: Xu Peiluo , Cooper Robert F. , Jiang Yu You , Morgan Jessica I. W. 
Published: April 2024

AbstractChoroideremia (CHM) is an X-linked retinal degeneration leading to loss of the photoreceptors, retinal pigment epithelium (RPE), and choroid. Adaptive optics optoretinography is an emerging technique for noninvasive, objective assessment of photoreceptor function. Here, we investigate parafoveal cone function in CHM using adaptive optics optoretinography and compare with cone structure and clinical assessments of vision. Parafoveal cone mosaics of 10 CHM and four normal-sighted participants were imaged with an adaptive optics scanning light ophthalmoscope. While acquiring video sequences, a 2 s 550Δ10 nm, 450 nW/deg2 stimulus was presented. Videos were registered and the intensity of each cone in each frame was extracted, normalized, standardized, and aggregated to generate the population optoretinogram (ORG) over time. A gamma-pdf was fit to the ORG and the peak was extracted as ORG amplitude. CHM ORG amplitudes were compared to normal and were correlated with bound cone density, ellipsoid zone to RPE/Bruch’s membrane (EZ-to-RPE/BrM) distance, and foveal sensitivity using Pearson correlation analysis. ORG amplitude was significantly reduced in CHM compared to normal (0.22 ± 0.15 vs. 1.34 ± 0.31). In addition, CHM ORG amplitude was positively correlated with cone density, EZ-to-RPE/BrM distance, and foveal sensitivity. Our results demonstrate promise for using ORG as a biomarker of photoreceptor function.
SNORA69 is up-regulated in the lateral habenula of individuals with major depressive disorder
Authors: Lin Rixing , Mitsuhashi Haruka , Fiori Laura M. , Denniston Ryan , Ibrahim El Cherif , Belzung Catherine , Mechawar Naguib , Turecki Gustavo 
Published: April 2024

AbstractMajor depressive disorder (MDD) is a complex and potentially debilitating illness whose etiology and pathology remains unclear. Non-coding RNAs have been implicated in MDD, where they display differential expression in the brain and the periphery. In this study, we quantified small nucleolar RNA (snoRNA) expression by small RNA sequencing in the lateral habenula (LHb) of individuals with MDD (n = 15) and psychiatrically-healthy controls (n = 15). We uncovered five snoRNAs that exhibited differential expression between MDD and controls (FDR < 0.01). Specifically, SNORA69 showed increased expression in MDD and was technically validated via RT-qPCR. We further investigated the expression of Snora69 in the LHb and peripheral blood of an unpredicted chronic mild stress (UCMS) mouse model of depression. Snora69 was specifically up-regulated in mice that underwent the UCMS paradigm. SNORA69 is known to guide pseudouridylation onto 5.8S and 18S rRNAs. We quantified the relative abundance of pseudouridines on 5.8S and 18S rRNA in human post-mortem LHb samples and found increased abundance of pseudouridines in the MDD group. Overall, our findings indicate the importance of brain snoRNAs in the pathology of MDD. Future studies characterizing SNORA69’s role in MDD pathology is warranted.
Dietary restriction reveals sex-specific expression of the mTOR pathway genes in Japanese quails
Authors: Reda Gebrehaweria K. , Ndunguru Sawadi F. , Csernus Brigitta , Knop Renáta , Lugata James K. , Szabó Csaba , Czeglédi Levente , Lendvai Ádám Z. 
Published: April 2024

AbstractLimited resources affect an organism’s physiology through the conserved metabolic pathway, the mechanistic target of rapamycin (mTOR). Males and females often react differently to nutritional limitation, but whether it leads to differential mTOR pathway expression remains unknown. Recently, we found that dietary restriction (DR) induced significant changes in the expression of mTOR pathway genes in female Japanese quails (Coturnix japonica). We simultaneously exposed 32 male and female Japanese quails to either 20%, 30%, 40% restriction or ad libitum feeding for 14 days and determined the expression of six key genes of the mTOR pathway in the liver to investigate sex differences in the expression patterns. We found that DR significantly reduced body mass, albeit the effect was milder in males compared to females. We observed sex-specific liver gene expression. DR downregulated mTOR expression more in females than in males. Under moderate DR, ATG9A and RPS6K1 expressions were increased more in males than in females. Like females, body mass in males was correlated positively with mTOR and IGF1, but negatively with ATG9A and RS6K1 expressions. Our findings highlight that sexes may cope with nutritional deficits differently and emphasise the importance of considering sexual differences in studies of dietary restriction.
Integrated machine learning for modeling bearing capacity of shallow foundations
Authors: Liu Yuzhen , Liang Yan 
Published: April 2024

AbstractAnalyzing the stability of footings is a significant step in civil/geotechnical engineering projects. In this work, two novel predictive tools are suggested based on an artificial neural network (ANN) to analyze the bearing capacity of a footing installed on a two-layered soil mass. To this end, backtracking search algorithm (BSA) and equilibrium optimizer (EO) are employed to train the ANN for approximating the stability value (SV) of the system. After executing a set of finite element analyses, the settlement values lower/higher than 5 cm are considered to indicate the stability/failure of the system. The results demonstrated the efficiency of these algorithms in fulfilling the assigned task. In detail, the training error of the ANN (in terms of root mean square error—RMSE)) dropped from 0.3585 to 0.3165 (11.72%) and 0.2959 (17.46%) by applying the BSA and EO, respectively. Moreover, the prediction accuracy of the ANN climbed from 93.7 to 94.3% and 94.1% (in terms of area under the receiving operating characteristics curve—AUROC). A comparison between the elite complexities of these algorithms showed that the EO enjoys a larger accuracy, while BSA is a more time-effective optimizer. Lastly, an explicit mathematical formula is derived from the EO-ANN model to be conveniently used in predicting the SV.
Translational research of boron neutron capture therapy for spinal cord gliomas using rat model
Authors: Kayama Ryo , Tsujino Kohei , Kawabata Shinji , Fujikawa Yoshiki , Kashiwagi Hideki , Fukuo Yusuke , Hiramatsu Ryo , Takata Takashi , Tanaka Hiroki , Suzuki Minoru , Hu Naonori , Miyatake Shin-Ichi , Takami Toshihiro , Wanibuchi Masahiko 
Published: April 2024

AbstractBoron neutron capture therapy (BNCT) is a type of targeted particle radiation therapy with potential applications at the cellular level. Spinal cord gliomas (SCGs) present a substantial challenge owing to their poor prognosis and the lack of effective postoperative treatments. This study evaluated the efficacy of BNCT in a rat SCGs model employing the Basso, Beattie, and Bresnahan (BBB) scale to assess postoperative locomotor activity. We confirmed the presence of adequate in vitro boron concentrations in F98 rat glioma and 9L rat gliosarcoma cells exposed to boronophenylalanine (BPA) and in vivo tumor boron concentration 2.5 h after intravenous BPA administration. In vivo neutron irradiation significantly enhanced survival in the BNCT group when compared with that in the untreated group, with a minimal BBB scale reduction in all sham-operated groups. These findings highlight the potential of BNCT as a promising treatment option for SCGs.
Bacterial biota associated with the invasive insect pest Tuta absoluta (Meyrick)
Authors: Lateef A. A. , Azeez A. A. , Ren W. , Hamisu H. S. , Oke O. A. , Asiegbu F. O. 
Published: April 2024

AbstractTuta absoluta (the tomato pinworm) is an invasive insect pest with a highly damaging effect on tomatoes causing between 80 and 100% yield losses if left uncontrolled. Resistance to chemical pesticides have been reported in some T. absoluta populations. Insect microbiome plays an important role in the behavior, physiology, and survivability of their host. In a bid to explore and develop an alternative control method, the associated microbiome of this insect was studied. In this study, we unraveled the bacterial biota of T. absoluta larvae and adults by sequencing and analyzing the 16S rRNA V3-V4 gene regions using Illumina NovaSeq PE250. Out of 2,092,015 amplicon sequence variants (ASVs) recovered from 30 samples (15 larvae and 15 adults), 1,268,810 and 823,205 ASVs were obtained from the larvae and adults, respectively. A total of 433 bacterial genera were shared between the adults and larval samples while 264 and 139 genera were unique to the larvae and adults, respectively. Amplicon metagenomic analyses of the sequences showed the dominance of the phylum Proteobacteria in the adult samples while Firmicutes and Proteobacteria dominated in the larval samples. Linear discriminant analysis effect size (LEfSe) comparison revealed the genera Pseudomonas, Delftia and Ralstonia to be differentially enriched in the adult samples while Enterococcus, Enterobacter, Lactococcus, Klebsiella and Wiessella were differentially abundant in the larvae. The diversity indices showed that the bacterial communities were not different between the insect samples collected from different geographical regions. However, the bacterial communities significantly differed based on the sample type between larvae and adults. A co-occurrence network of significantly correlated taxa revealed a strong interaction between the microbial communities. The functional analysis of the microbiome using FAPROTAX showed that denitrification, arsenite oxidation, methylotrophy and methanotrophy as the active functional groups of the adult and larvae microbiomes. Our results have revealed the core taxonomic, functional, and interacting microbiota of T. absoluta and these indicate that the larvae and adults harbor a similar but transitory set of bacteria. The results provide a novel insight and a basis for exploring microbiome-based biocontrol strategy for this invasive insect pest as well as the ecological significance of some of the identified microbiota is discussed.
A new dynamic nomogram for predicting the risk of severe Mycoplasma pneumoniae pneumonia in children
Authors: Zhang Xue , Sun Ruiyang , Jia Wanyu , Li Peng , Song Chunlan 
Published: April 2024

AbstractMycoplasma pneumoniaepneumonia (MPP) is usually mild and self-limiting, but still about 12% of them will progress to severeMycoplasma pneumoniaepneumonia (SMPP), which have poor survival rates and often require intensive medical resource utilization. We retrospectively collected clinical data from 526 children with MPP admitted to the Children’s Hospital Affiliated to Zhengzhou University from June 2018 to February 2023 and randomly divided the data into a training cohort and a validation cohort at a ratio of 4:1. Univariate and multivariate logistic regressions were used to identify independent risk factors for SMPP. Age, AGR, NLR, CRP, ESR, MPV, coinfection, pleural effusion, primary disease, fever days ≥ 7 and wheeze are independent risk factors for SMPP in children. Then, we built an online dynamic nomogram (https://ertongyiyuanliexiantu.shinyapps.io/SMPP/) based on the 11 independent risk factors. The C-index, ROC curve, DCA curve and calibration curve were used to assess the performance of the nomogram, which all showed that the dynamic nomogram has excellent clinical value. Based on age, AGR, NLR, CRP, ESR, MPV, coinfection, pleural effusion, primary disease, fever days ≥ 7 and wheeze, the first dynamic nomogram for accurately predicting SMPP was successfully established.
Dynamic Bayesian network structure learning based on an improved bacterial foraging optimization algorithm
Authors: Meng Guanglei , Cong Zelin , Li Tingting , Wang Chenguang , Zhou Mingzhe , Wang Biao 
Published: April 2024

AbstractWith the rapid development of artificial intelligence and data science, Dynamic Bayesian Network (DBN), as an effective probabilistic graphical model, has been widely used in many engineering fields. And swarm intelligence algorithm is an optimization algorithm based on natural selection with the characteristics of distributed, self-organization and robustness. By applying the high-performance swarm intelligence algorithm to DBN structure learning, we can fully utilize the algorithm's global search capability to effectively process time-based data, improve the efficiency of network generation and the accuracy of network structure. This study proposes an improved bacterial foraging optimization algorithm (IBFO-A) to solve the problems of random step size, limited group communication, and the inability to maintain a balance between global and local searching. The IBFO-A algorithm framework comprises four layers. First, population initialization is achieved using a logistics-sine chaotic mapping strategy as the basis for global optimization. Second, the activity strategy of a colony foraging trend is constructed by combining the exploration phase of the Osprey optimization algorithm. Subsequently, the strategy of bacterial colony propagation is improved using a "genetic" approach and the Multi-point crossover operator. Finally, the elimination-dispersal activity strategy is employed to escape the local optimal solution. To solve the problem of complex DBN learning structures due to the introduction of time information, a DBN structure learning method called IBFO-D, which is based on the IBFO-A algorithm framework, is proposed. IBFO-D determines the edge direction of the structure by combining the dynamic K2 scoring function, the designed V-structure orientation rule, and the trend activity strategy. Then, according to the improved reproductive activity strategy, the concept of "survival of the fittest" is applied to the network candidate solution while maintaining species diversity. Finally, the global optimal network structure with the highest score is obtained based on the elimination-dispersal activity strategy. Multiple tests and comparison experiments were conducted on 10 sets of benchmark test functions, two non-temporal and temporal data types, and six data samples of two benchmark 2T-BN networks to evaluate and analyze the optimization performance and structure learning ability of the proposed algorithm under various data types. The experimental results demonstrated that IBFO-A exhibits good convergence, stability, and accuracy, whereas IBFO-D is an effective approach for learning DBN structures from data and has practical value for engineering applications.
Exploring the effects of structure and melting on sweetness in additively manufactured chocolate
Authors: Burkard Johannes , Kohler Lucas , Caciagli Sophia , Herren Nicolas , Kozamernik Mark , Mantovani Saskia , Windhab Erich J. , Denkel Christoph 
Published: April 2024

AbstractIn view of the health concerns associated with high sugar intake, this study investigates methods to enhance sweetness perception in chocolate without increasing its sugar content. Using additive manufacturing, chocolate structures were created from masses with varying sugar and fat compositions, where hazelnut oil served as a partial cocoa butter replacement. The study found that while variations in sugar content minimally affected the physical properties of the chocolate masses, hazelnut oil significantly modified melting behavior and consumption time. Chocolate masses with higher hazelnut oil content but similar sugar content exhibited a 24% increase in sweetness perception, likely due to accelerated tastant (i.e., sucrose) release into saliva. Multiphase structures, designated as layered, cube-in-cube, and sandwich structures, exhibited less sensory differences compared to the homogeneous control. Nonetheless, structures with hazelnut oil-rich outer layers resulted in an 11% increase in sweetness perception, even without sugar gradients. This suggests that tastant release plays a more critical role than structural complexity in modifying sweetness perception. This research highlights the efficacy of simpler multiphase structures, such as sandwich designs, which offer sensory enhancements comparable to those of more complex designs but with reduced manufacturing effort, thus providing viable options for industrial-scale production.
Acoustic imaging of stable double diffusion in the Madeira abyssal plain
Authors: Duarte Ana F. , Peliz Álvaro , Matias Luís , Mendes Renato , Azevedo Leonardo 
Published: April 2024

AbstractSub-mesoscale and mesoscale (i.e., 1–10 km and 10–200 km, respectively) ocean processes are highly relevant for the understanding of global circulation, mixing of water masses and energy exchange between ocean layers. However, the processes happening at these scales are hard to be characterized using direct measurements of temperature and salinity. Direct measurements are obtained from vertical probes and/or autonomous vehicles, which, despite their high vertical resolution, are sparsely located in space and therefore unable to capture spatial details at these scales. Seismic oceanography (SO) data have been successfully used to imaging and characterize the ocean at these spatial scales. These data represent indirect measurements of the ocean temperature and salinity along kilometric transects with high horizontal resolution (i.e., a near-synaptic view of the system under investigation), but lower vertical resolution when compared with direct observations. Despite its complex oceanographic setting, the Madeira Abyssal Plain is still largely uncharacterized due to the lack of direct observations. We show for the first time a comprehensive processing, modelling and interpretation of three 2-D seismic oceanography sections from this region. The data show coherent seismic reflection in space, depth and time and shed light into this oceanographic setting with an unprecedent horizontal resolution. The SO modelling and interpretation are combined with existing direct measurements and a quantitative method to correlate thermohaline staircases interpreted from conductivity-temperature-depth casts and seismic reflections is proposed. The results show the relatively stable presence of thermohaline staircases in simultaneously time and space between 1200 and 2000 m of water depth and their spatial variability and contribute to the generalization of SO in physical oceanography.
Exploring the spatial and seasonal heterogeneity of cooling effect of an urban river on a landscape scale
Authors: Zhou Wen , Wu Tao , Tao Xin 
Published: April 2024

AbstractUrban water bodies can effectively mitigate the urban heat island effect and thus enhance the climate resilience of urban areas. The cooling effect of different water bodies varies, however, the cooling heterogeneity of different sections of a single watercourse or river network is rarely considered. Based on various satellite images, geospatial approaches and statistical analyses, our study confirmed the cooling heterogeneity from spatial and seasonal perspectives of the Suzhou Outer-city River in detail in the urban area of Suzhou, China. The cooling effect of the river was observed in the daytime in four seasons, and it is strongest in summer, followed by spring and autumn, and weakest in winter. The combination of the width of the river reach, the width and the NDVI value of the adjacent green space can explain a significant part of the cooling heterogeneity of the different river sections in different seasons. Land surface temperature (LST) variations along the river are more related to the width of the river reach, but the variations of the cooling distance are more related to the adjacent green space. The cooling effect of a river reach could be enhanced if it is accompanied by green spaces. In addition, the cooling effect of a looping river is stronger on the inside area than on the outside. The methodology and results of this study could help orient scientific landscape strategies in urban planning for cooler cities.
Environmental concerns on the use of the electrospinning technique for the production of polymeric micro/nanofibers
Authors: Malara Angela 
Published: April 2024

AbstractThe production of micro and nanofibers through the electrospinning technique is a well assessed technology that finds application in a variety of fields. Indeed, the specific features of electrospun fibers, as well as the possibility to be modelled and functionalized, ensure their great versatility. In the last decades, the widespread use of electrospun fibers promoted studies related to the evaluation of both human health and environmental risks associated to their handling and exposure. However, to date, the environmental impact strictly related to the use of the manufacturing process has been barely considered. Therefore, the present work aims to assess the environmental impacts of the electrospinning technology used to produce micro and nanofibers. To this purpose, a model polymer was systematically electrospun, varying the main system, process and external parameters, that control the electrospinning technique. A simplified life cycle assessment analysis was finally used to evaluate how the fibrous morphology, closely linked to the choice of the technological parameters, intrinsically affected the environmental impacts.
Mycodegradation of low-density polyethylene by Cladosporium sphaerospermum, isolated from platisphere
Authors: Sathiyabama M. , Boomija R. V. , Sathiyamoorthy T. , Mathivanan N. , Balaji R. 
Published: April 2024

AbstractPlastic accumulation is a severe threat to the environment due to its resistivity to thermal, mechanical and biological processes. In recent years, microbial degradation of plastic waste disposal is of interest because of its eco-friendly nature. In this study, a total of 33 fungi were isolated from the plastisphere and out of which 28 fungal species showed halo zone of clearance in agarized LDPE media. The fungus showing highest zone of clearance was further used to evaluate its degradation potential. Based on morphological and molecular technique, the fungus was identified as Cladosporium sphaerospermum. The biodegradation of LDPE by C. sphaerospermum was evaluated by various methods. The exposure of LDPE with C. sphaerospermum resulted in weight loss (15.23%) in seven days, higher reduction rate (0.0224/day) and lower half-life (30.93 days). FTIR analysis showed changes in functional group and increased carbonyl index in LDPE treated with C. sphaerospermum. SEMimages evidenced the formation of pits, surface aberrations and grooves on the LDPE film treated with the fungus whereas the untreated control LDPE film showed no change. AFM analysis confirmed the surface changes and roughness in fungus treated LDPE film. This might be due to the extracellular lignolytic enzymes secreted by C. sphaerospermum grown on LDPE. The degradation of polyethylene by Short chain alkanes such as dodecane, hexasiloxane and silane were identified in the extract of fungus incubated with LDPE film through GC–MS analysis which might be due to the degradation of LDPE film by C. sphaerospermum. This was the first report on the LDPE degradation by C. sphaerospermum in very short duration which enables green scavenging of plastic wastes.