bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Continuous Manure Application on the Microbial Community and Labile Organic Carbon Fractions
Authors: Yan Han , Fan Wei , Wu Jinggui
Published: November 2023

The application of organic materials contributes to the sustainable development of agriculture. Increased manure inputs have a fundamental effect on the composition and dynamics of soil organic carbon (SOC). In this study, we conducted a 10-year field experiment in Changchun, Jilin, Northeast China, to investigate the effects of manure addition on soil organic carbon components and soil microorganisms. Specifically, we established four treatments: (i) chemical fertilizer or no addition of manure (CK), (ii) pig manure with chemical fertilizer (ZF), (iii) cow manure with chemical fertilizer (NF), and (iv) chicken manure with chemical fertilizer (JF). The results showed that the JF treatment significantly increased the soil organic carbon (SOC), dissolved organic carbon (DOC), and readily oxidized organic carbon (ROC) content by 20.36%, 105.9%, and 61.32%, respectively, relative to CK. The microbial biomass carbon (MBC) content in JF, ZF, and NF treatments were significantly higher than that of CK, which increased by 107.24%, 116.45%, and 96.71%, respectively. The particulate organic carbon (POC) content in NF and JF treatments differed significantly, increasing by 25.61% and 19.01%, respectively, relative to CK. Redundancy analysis showed that continuous manure application had a positive effect on soil microbial community diversity and abundance, which was favorable for the accumulation of soil carbon. We also found that soil fungi were more sensitive than bacteria to changes in soil carbon composition following manure application. In conclusion, adding different organic materials can better support biodiversity conservation and realize ecosystem services of surface carbon storage and soil conservation. Our results reveal the importance of microbial fixation in soil carbon dynamics according to the different distribution of active organic carbon pools, which will help enhance our understanding of the carbon cycle.
Evaluation of Organic Matter Contribution Using Absorbance and Chromatographic Parameters in Lake Paldang, Republic of Korea
Authors: Cho Yeon Jung , Seong Ki Seon , Byeon Myeong Seop , Kang Taegu , Im Jong Kwon
Published: November 2023

Organic matter in lakes is categorized into allochthonous organic matter, such as leaves and sewage effluent, and autochthonous organic matter, generated by microorganisms within the water system. In this study, organic matter composition was analyzed using UV-vis spectroscopy and liquid chromatography-organic carbon detection (LC-OCD). Several allochthonous natural organic matter substances were collected including leaves, green leaves, forest soils, and paddy soils. The organic matter composition analysis in our study sites revealed that humic substances comprised the highest proportion (36.5–42.3%). Also, individual samples at each site exhibited distinct characteristics. This study used a humic substance-diagram (HS-diagram) and principal component analysis (PCA) to trace the sources affecting the river water quality and identify their origins. The humic substances of soil origin predominantly influenced the water quality, with the impact of organic matter significantly pronounced during the July rainfall period. Compared with the PCA results, the contribution of the humic substance (HS, 48.9%) and building block (BB, 42.0%) indices appeared higher between June and July in summer, likely due to non-degradable substances released by heavy rain. In fall, the contribution of low molecular weight neutrals increased from 71.2% to 85.2%, owing to a humic substance influx and decomposition. This study demonstrated the application of estimating the relative contributions of source materials in lakes utilized for drinking and agricultural water to identify sources, aiding in the development of efficient watershed management plans.
Assimilation of Nitrate into Asparagine for Transport in Soybeans
Authors: Li Sha , Lyu Xiaochen , Wang Xuelai , Zhao Shuhong , Ma Chunmei , Yan Chao , Gong Zhenping
Published: November 2023

In this study, the systematic analysis of nitrate assimilation and transport in soybean roots was further improved by analyzing the concentrations of nitrate assimilates, asparagine and glutamine, in soybean roots and the related enzyme activities. This provided a theoretical basis for the efficient utilization of nitrogen fertilizer in soybean farming. A dual-root soybean system with both sides being nodulated was used to provide nitrate withdrawal and resupply in three phases on one side, while the other side received nutrients without nitrogen under sand culture conditions. Measurements were taken of the root’s nitrate reductase and glutamine synthetase activities, as well as the concentrations of asparagine. Measurements were also taken of the asparagine concentration in the basal root peeled skin (where the primary transport pathway is the phloem) and the woody parts (where the primary transport pathway is the xylem). Furthermore, the concentration of glutamine in the roots was also assessed. The findings indicated a positive correlation between the nitrate concentration in the roots and the activity of glutamine synthetase in the roots on both sides. The levels of asparagine in the roots, specifically those in the basal root peeled skin and woody part on both sides, rose when nitrate was added and declined when nitrate was removed. There was no significant change in glutamine concentration within the roots of soybeans. Hence, we deduced that the local provision of nitrate to the dual-root soybeans might enhance the absorption of nitrate into the roots on both sides. Additionally, the assimilated substances were predominantly carried as asparagine through the peeled skin and woody sections of the basal root, facilitating transportation in both directions within the soybean plants (from shoot to root and from root to shoot).
Tithonia diversifolia Improves In Vitro Rumen Microbial Synthesis of Sheep Diets without Changes in Total Gas and Methane Production
Authors: Pérez-Márquez Simón , Ovani Vagner S. , Lima Paulo de Mello Tavares , Lana Ângela Maria Quintão , Louvandini Helder , Abdalla Adibe Luiz , Maurício Rogério Martins
Published: November 2023

Among the alternatives identified as capable of making livestock farming a more efficient activity and reducing its environmental impact, the use of feeds with high digestibility and the use of non-conventional fodder species can be highlighted. Tithonia diversifolia (Hemsl.) A. Gray (TD) has already gained attention as a feed for ruminants. Nonetheless, there has been little discussion about the impacts of this plant on the rumen dynamics that lead to better animal performance. The aim of this study was to assess how increasing levels of TD could affect ruminal microbial biomass synthesis, degradability, and in vitro gas production (IVGP) of diets. Four diets were evaluated: a control diet (TD0: 400 g kg−1 soybean meal and maize grain, and 600 g kg−1 Tifton 85 hay (Cynodon spp.)) and three increasing levels of TD (TD9: 90, TD27: 270, and TD45: 450 g kg−1–dry matter basis) as a replacement for dietary roughage. A 96 h IVGP assay was carried out and five incubation times (2, 4, 10, 24, and 96 h) were used for degradability determination. Gas produced, methane (CH4), degradability of organic matter (IVDOM), short-chained fatty acid (SCFA) production, partitioning factor (PF), and microbial biomass (MB) were evaluated among treatments. There was no significant effect (p > 0.05) between TD inclusion and IVGP at most incubation times; only at 6 h of incubation did gas production increase linearly with TD inclusion (R2 = 0.19; p < 0.05). TD inclusion had no effects on CH4. IVDOM increased linearly with TD inclusion at 6 and 10 h, with TD45 being more degradable than the control diet at 6 h only. There was a positive linear relationship (R2 = 0.20; p < 0.05) between TD inclusion and PF. TD45 had significantly higher PF values than the control. MB also increased linearly (R2 = 0.30; p < 0.05) with TD inclusion, and all diets with TD had significantly more MB than the control diet. The inclusion of TD at the levels used in this work was revealed to have a positive impact on microbial protein synthesis, which could be related to the higher microbial efficiency of increased substrate quality.
Comparable Evaluation of Nutritional Benefits of Lactobacillus plantarum and Bacillus toyonensis Probiotic Supplementation on Growth, Feed Utilization, Health, and Fecal Microbiota in Pre-Weaning Male Calves
Authors: Ayyat Mohamed S. , El-Nagar Hamdy A. , Wafa Wael M. , Abd El-Latif Khaled M. , Mahgoub Samir , Al-Sagheer Adham A.
Published: November 2023

This study was conducted to investigate the impact of probiotic supplementation using Lactobacillus plantarum DSA 20174 and/or Bacillus toyonensis ATCC 55050 on growth performance, blood parameters, hematological measures, and fecal microbiota in pre-weaning Holstein calves. Thirty-two four-day-old male calves with a similar genetic background, weighing an average of 38.27 ± 0.12 kg, were randomly assigned to four groups. The groups consisted of a control group (CON) without supplementation, a group receiving B. toyonensis (BT) at 3 × 109 cfu/calf/day, a group receiving L. plantarum (LP) at 1 × 1010 cfu/calf/day, and a group receiving a combination of LP and BT (LP + BT) at half the dosage for each. The study found that calves supplemented with LP and LP + BT experienced significant improvements in average daily gain and final body weight compared to the control group. The LP + BT group showed the most positive effects on TDMI, starter intake, and CP intake. RBC counts tended to be higher in the probiotic groups, with the LP + BT group having the highest values. The LP + BT group also had higher total protein, albumin, globulin, and hematocrit concentrations. All probiotic groups showed higher serum IgG concentrations. Probiotic supplementation led to increased total bacterial count and decreased levels of E. coli, salmonella, and clostridium. The LP + BT group had a significant decrease in coliform count, while both LP and LP + BT groups had increased Lactobacillus populations. In conclusion, LP + BT probiotic supplement showed the most beneficial effects on growth, feed efficiency, blood constituents, and modulation of fecal microbiota composition.
The Recommendation Algorithm Based on Improved Conditional Variational Autoencoder and Constrained Probabilistic Matrix Factorization
Authors: Zhang Yunfei , Xu Hongzhen , Yu Xiaojun
Published: November 2023

An improved recommendation algorithm based on Conditional Variational Autoencoder (CVAE) and Constrained Probabilistic Matrix Factorization (CPMF) is proposed to address the issues of poor recommendation performance in traditional user-based collaborative filtering algorithms caused by data sparsity and suboptimal feature extraction. Firstly, in the data preprocessing stage, a hidden layer is added to CVAE, and random noise is introduced into the hidden layer to constrain the data features, thereby obtaining more accurate latent features and improving the model’s robustness and generative capability. Secondly, the category of items is incorporated as auxiliary information in CVAE to supervise the encoding and decoding of item data. By learning the distribution characteristics of the data, missing values in the rating data can be effectively reconstructed, thereby reducing the sparsity of the rating matrix. Subsequently, the reconstructed data is processed using CPMF, which optimizes the feature extraction performance by imposing constraints on user features. Finally, the prediction rating of a user for an item can be obtained through the matrix product of user and item feature matrices. Experimental results on the MovieLens-100K and MovieLens-1M datasets demonstrate the effectiveness and superiority of the proposed algorithm over four comparative algorithms, as it exhibits significant advantages in terms of root mean square error and mean absolute error metrics.
Optimization of the Antifungal Property in a Composite of Polyurethane and Silver Nanoparticles against the Trichophyton rubrum Fungus
Authors: Mares Castro Armando , Estrada Monje Anayansi , Saldívar Campos Alejandra Imelda , Zaragoza Estrada Anayansi
Published: November 2023

This research aims to analyze and optimize the antifungal property of a composite material made of polyurethane (PUR) and silver nanoparticles (AgNPs) against the fungus Trichophyton rubrum to find the optimal parameters that allow the highest inhibition of the fungal growth to be used in healthcare aimed at the population vulnerable to fungal infections, such as people suffering from diabetes mellitus, thus creating an opportunity for the generation of antifungal products for healthcare applications. This study analyzes the effect of three variables on the antifungal properties of the composite material: nanoparticle size, concentration, and the application of an ultrasonic treatment as a method to aid the dispersion of the AgNPs into PUR matrix. The proposed methodology includes tests in accordance with a standar to evaluate the growth inhibition of the fungi on a culture medium. A categorical logistic regression model was adjusted from 23 factorial design with five replicates, which was optimized by the use of multi-objective genetic algorithms. The experimental factors showed a significant effect on the growth inhibition of the fungus, and the optimal levels were determined.
Individualized Stress Mobile Sensing Using Self-Supervised Pre-Training
Authors: Islam Tanvir , Washington Peter
Published: November 2023

Stress is widely recognized as a major contributor to a variety of health issues. Stress prediction using biosignal data recorded by wearables is a key area of study in mobile sensing research because real-time stress prediction can enable digital interventions to immediately react at the onset of stress, helping to avoid many psychological and physiological symptoms such as heart rhythm irregularities. Electrodermal activity (EDA) is often used to measure stress. However, major challenges with the prediction of stress using machine learning include the subjectivity and sparseness of the labels, a large feature space, relatively few labels, and a complex nonlinear and subjective relationship between the features and outcomes. To tackle these issues, we examined the use of model personalization: training a separate stress prediction model for each user. To allow the neural network to learn the temporal dynamics of each individual’s baseline biosignal patterns, thus enabling personalization with very few labels, we pre-trained a one-dimensional convolutional neural network (1D CNN) using self-supervised learning (SSL). We evaluated our method using the Wearable Stress and Affect Detection(WESAD) dataset. We fine-tuned the pre-trained networks to the stress-prediction task and compared against equivalent models without any self-supervised pre-training. We discovered that embeddings learned using our pre-training method outperformed the supervised baselines with significantly fewer labeled data points: the models trained with SSL required less than 30% of the labels to reach equivalent performance without personalized SSL. This personalized learning method can enable precision health systems that are tailored to each subject and require few annotations by the end user, thus allowing for the mobile sensing of increasingly complex, heterogeneous, and subjective outcomes such as stress.
The Effects of Angelica ternata Extract from Kyrgyzstan on the Formation of Candida albicans ATCC 10231 Biofilms
Authors: Sachivkina Nadezhda , Karamyan Arfenya , Semenova Valentina , Ignatiev Aleksej , Abdurasulov Abdugani , Muratova Rakhima , Emilbekova Dinara , Ermatova Venera , Risvanli Ali , Salykov Ruslan , Ibragimova Alfia , Neborak Ekaterina
Published: November 2023

The therapeutic potential of Angelica ternata extract was tested against biofilm-associated fungi Candida albicans. Such an extract with a 1.896 ± 0.071% per 1 mL rutin content of flavonoids can reliably suppress the formation of biofilms of pathogenic yeast-like fungi up to 76.6%. The herbal medicine has a significant effect on the initiation, adhesion, and development of biofilms. If the extract is added to a developed biofilm, it has a significant effect on the matrix. As a result, the “glue” between the cells is washed out and they are more easily washed away from the well of the microplate to which they are attached. In this case, the optical density of the biofilm is halved (50.5%).
A Maturity Detection Method for Hemerocallis Citrina Baroni Based on Lightweight and Attention Mechanism
Authors: Sheng Bin , Wu Ligang , Zhang Nan
Published: November 2023

Hemerocallis citrina Baroni with different maturity levels has different uses for food and medicine and has different economic benefits and sales value. However, the growth speed of Hemerocallis citrina Baroni is fast, the harvesting cycle is short, and the maturity identification is completely dependent on experience, so the harvesting efficiency is low, the dependence on manual labor is large, and the identification standard is not uniform. In this paper, we propose a GCB YOLOv7 Hemerocallis citrina Baroni maturity detection method based on a lightweight neural network and attention mechanism. First, lightweight Ghost convolution is introduced to reduce the difficulty of feature extraction and decrease the number of computations and parameters of the model. Second, between the feature extraction backbone network and the feature fusion network, the CBAM mechanism is added to perform the feature extraction independently in the channel and spatial dimensions, which improves the tendency of the feature extraction and enhances the expressive ability of the model. Last, in the feature fusion network, Bi FPN is used instead of the concatenate feature fusion method, which increases the information fusion channels while decreasing the number of edge nodes and realizing cross-channel information fusion. The experimental results show that the improved GCB YOLOv7 algorithm reduces the number of parameters and floating-point operations by about 2.03 million and 7.3 G, respectively. The training time is reduced by about 0.122 h, and the model volume is compressed from 74.8 M to 70.8 M. In addition, the average precision is improved from 91.3% to 92.2%, mAP@0.5 and mAP@0.5:0.95 are improved by about 1.38% and 0.20%, respectively, and the detection efficiency reaches 10 ms/frame, which meets the real-time performance requirements. It can be seen that the improved GCB YOLOv7 algorithm is not only lightweight but also effectively improves detection precision.
Rethinking the Medieval Visual Culture of Eastern Europe: Two Case Studies in Dialogue (Serbia and Wallachia)
Authors: Rossi Maria Alessia , Sullivan Alice Isabella
Published: November 2023

This article explores how the visual culture of Eastern Europe has been studied and often excluded from the grander narratives of art history and more specialized conversations due to political and cultural limitations, as well as bias in the field. The history and visual culture of Eastern Europe have been shaped by contacts with Byzantium, transforming, in local contexts, aspects of the rich legacy of the empire before and after the fall of Constantinople in 1453. This study expands and theorizes the eclectic visual cultures of Eastern Europe during the late medieval period by focusing on two ecclesiastical buildings of the 14th century built under princely and noble patronage in regions of North Macedonia and Wallachia, respectively: the Church of St George at Staro Nagoričane, near Skopje, modern-day North Macedonia (1315–17) and Cozia Monastery in Călimănești, Wallachia, modern-day Romania (founded 1388). The 14th century was a transformative period for the regions to the north and south of the Danube River, establishing the contacts that were to develop further during the 15th century and especially after 1453.
A Comparison of Atmospheric Boundary Layer Height Determination Methods Using GNSS Radio Occultation Data
Authors: Qiu Cong , Wang Xiaoming , Li Haobo , Zhou Kai , Zhang Jinglei , Li Zhe , Liu Dingyi , Yuan Hong
Published: November 2023

The accurate determination of Atmospheric Boundary Layer Height (ABLH) is crucial in various atmospheric studies and practical applications. In this study, we present a comprehensive comparative analysis of five distinct methods for estimating ABLH using Global Navigation Satellite System (GNSS) Radio Occultation (RO) data. These methods encompass the use of bending angle and refractivity profiles, namely Minimum Gradient methods of the Bending Angle (MGBA) and Refractivity (MGR) profiles, breaking point, Wavelet Covariance Transform (WCT), and Double-Parameter Model Function (DPMF). GNSS-RO data from COSMIC-2 and Spire are used. To establish robust validation, radiosonde data are employed as a reference, ensuring the reliability of our findings. The results reveal notable variations in the performances of these ABLH estimation methods. Specifically, the MGBA, MGR, breaking point, and DPMF methods exhibit strong correlations with the reference data. Conversely, the WCT method displays weaker correlations, higher biases, and elevated root-mean-square-errors, suggesting limitations in capturing the true ABLH. Furthermore, we remove outlier screening to facilitate a comparison of the differences among the five methods. The WCT and DPMF methods can detect strong variations in the profiles near the Earth’s surface and consider them as ABLH. However, these variations are caused by errors. The MGBA method emerges as a reliable and stable option, while the WCT and DPMF methods should be used with caution due to the lower quality of the GNSS-RO profiles near the Earth’s surface.
Comparative Tensile Properties and Collagen Patterns in Domestic Cat (Felis catus) and Dog (Canis lupus familiaris) Ovarian Cortical Tissues
Authors: Nagashima Jennifer B. , Zenilman Shoshana , Raab April , Aranda-Espinoza Helim , Songsasen Nucharin
Published: November 2023

The importance of the ovarian extracellular environment and tissue rigidity on follicle survival and development has gained attention in recent years. Our laboratory has anecdotally observed differences in the rigidity of domestic cat and dog ovarian cortical tissues, which have been postulated to underlie the differences in in vitro culture responses between the species, wherein cat ovarian tissues display higher survival in extended incubation. Here, the tensile strengths of cat and dog ovarian cortical tissues were compared via micropipette aspiration. The underlying collagen patterns, including fiber length, thickness, alignment, curvature, branch points and end points, and overall tissue lacunary and high-density matrix (HDM) were quantified via picrosirius red staining and TWOMBLI analysis. Finally, we explored the potential of MMP (−1 and −9) and TIMP1 supplementation in modulating tissue rigidity, collagen structure, and follicle activation in vitro. No differences in stiffness were observed between cat or dog cortical tissues, or pre- versus post-pubertal status. Cat ovarian collagen was characterized by an increased number of branch points, thinner fibers, and lower HDM compared with dog ovarian collagen, and cat tissues exposed to MMP9 in vitro displayed a reduced Young’s modulus. Yet, MMP exposure had a minor impact on follicle development in vitro in either species. This study contributes to our growing understanding of the interactions among the physical properties of the ovarian microenvironment, collagen patterns, and follicle development in vitro.
Utilizing a Two-Stage Taguchi Method and Artificial Neural Network for the Precise Forecasting of Cardiovascular Disease Risk
Authors: Lin Chia-Ming , Lin Yu-Shiang
Published: November 2023

The complexity of cardiovascular disease onset emphasizes the vital role of early detection in prevention. This study aims to enhance disease prediction accuracy using personal devices, aligning with point-of-care testing (POCT) objectives. This study introduces a two-stage Taguchi optimization (TSTO) method to boost predictive accuracy in an artificial neural network (ANN) model while minimizing computational costs. In the first stage, optimal hyperparameter levels and trends were identified. The second stage determined the best settings for the ANN model’s hyperparameters. In this study, we applied the proposed TSTO method with a personal computer to the Kaggle Cardiovascular Disease dataset. Subsequently, we identified the best setting for the hyperparameters of the ANN model, setting the hidden layer to 4, activation function to tanh, optimizer to SGD, learning rate to 0.25, momentum rate to 0.85, and hidden nodes to 10. This setting led to a state-of-the-art accuracy of 74.14% in predicting the risk of cardiovascular disease. Moreover, the proposed TSTO method significantly reduced the number of experiments by a factor of 40.5 compared to the traditional grid search method. The TSTO method accurately predicts cardiovascular risk and conserves computational resources. It is adaptable for low-power devices, aiding the goal of POCT.
Association of Asymmetric and Symmetric Dimethylarginine with Inflammation in the Population-Based Study of Health in Pomerania
Authors: Winkler Martin Sebastian , Bahls Martin , Böger Rainer H. , Ittermann Till , Dörr Marcus , Friedrich Nele , Schwedhelm Edzard
Published: November 2023

The amino acids arginine (Arg), asymmetric (ADMA) and symmetric dimethylarginine (SDMA) are related to nitric oxide (NO) metabolism and potential markers of two different disease entities: cardiovascular disease such as atherosclerosis and systemic inflammation in critically ill patients with sepsis. Although very different in their pathophysiological genesis, both entities involve the functional integrity of blood vessels. In this context, large population-based data associating NO metabolites with proinflammatory markers, e.g., white blood cell count (WBC), high-sensitivity C-reactive protein (hsCRP), and fibrinogen, or cytokines are sparse. We investigated the association of Arg, ADMA and SDMA with WBC, hsCRP, and fibrinogen in 3556 participants of the Study of Health in Pomerania (SHIP)-TREND study. Furthermore, in a subcohort of 456 subjects, 31 inflammatory markers and cytokines were analyzed. We identified Arg and SDMA to be positively associated with hsCRP (β coefficient 0.010, standard error (SE) 0.002 and 0.298, 0.137, respectively) as well as fibrinogen (β 5.23 × 10−3, SE 4.75 × 10−4 and 0.083, 0.031, respectively). ADMA was not associated with WBC, hsCRP, or fibrinogen. Furthermore, in the subcohort, Arg was inversely related to a proliferation-inducing ligand (APRIL). SDMA was positively associated with osteocalcin, tumor necrosis factor receptor 1 and 2, and soluble cluster of differentiation 30. Our findings provide new insights into the involvement of Arg, ADMA, and SDMA in subclinical inflammation in the general population.
Identification of Neurotransmission and Synaptic Biological Processes Disrupted in Autism Spectrum Disorder Using Interaction Networks and Community Detection Analysis
Authors: Vilela Joana , Martiniano Hugo , Marques Ana Rita , Santos João Xavier , Asif Muhammad , Rasga Célia , Oliveira Guiomar , Vicente Astrid Moura
Published: November 2023

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by communication deficits and repetitive behavioral patterns. Hundreds of candidate genes have been implicated in ASD, including neurotransmission and synaptic (NS) genes; however, the genetic architecture of this disease is far from clear. In this study, we seek to clarify the biological processes affected by NS gene variants identified in individuals with ASD and the global networks that link those processes together. For a curated list of 1216 NS candidate genes, identified in multiple databases and the literature, we searched for ultra-rare (UR) loss-of-function (LoF) variants in the whole-exome sequencing dataset from the Autism Sequencing Consortium (N = 3938 cases). Filtering for population frequency was carried out using gnomAD (N = 60,146 controls). NS genes with UR LoF variants were used to construct a network of protein–protein interactions, and the network’s biological communities were identified by applying the Leiden algorithm. We further explored the expression enrichment of network genes in specific brain regions. We identified 356 variants in 208 genes, with a preponderance of UR LoF variants in the PDE11A and SYTL3 genes. Expression enrichment analysis highlighted several subcortical structures, particularly the basal ganglia. The interaction network defined seven network communities, clustering synaptic and neurotransmitter pathways with several ubiquitous processes that occur in multiple organs and systems. This approach also uncovered biological pathways that are not usually associated with ASD, such as brain cytochromes P450 and brain mitochondrial metabolism. Overall, the community analysis suggests that ASD involves the disruption of synaptic and neurotransmitter pathways but also ubiquitous, but less frequently implicated, biological processes.
Changes in Inner Retina Thickness and Macular Sensitivity in Patients with Type 2 Diabetes with Moderate Diabetic Retinopathy
Authors: Boned-Murillo Ana , Fernández-Espinosa Guisela , Orduna-Hospital Elvira , Díaz-Barreda Maria Dolores , Sánchez-Cano Ana , Sopeña-Pinilla María , Bielsa-Alonso Sofía , Pinilla Isabel
Published: November 2023

The increase in diabetic retinopathy (DR) prevalence demonstrates the need for the determination of biomarkers for assessing disease development to obtain an early diagnosis and stop its progression. We aimed to analyse total retinal (RT) and inner retinal layer (IRL) thicknesses in type 2 diabetes mellitus (DM2) patients and correlate these results with retinal sensitivity using swept-source OCT (SS-OCT) and microperimetry. For this purpose, a total of 54 DM2 subjects with moderate diabetic retinopathy (DR) with no signs of diabetic macular oedema (DME) and 73 age-matched healthy individuals were assessed using SS-OCT to quantify retinal thickness in the nine macular areas of the ETDRS grid. Retinal sensitivity was measured via microperimetry with a Macular Integrity Assessment Device (MAIA). The mean ages were 64.06 ± 11.98 years for the DM2 group and 60.79 ± 8.62 years for the control group. DM2 patients presented lower visual acuity (p < 0.001) and a thicker RT (260.70 ± 19.22 μm in the control group vs. 271.90 ± 37.61 μm in the DM2 group, p = 0.01). The retinal nerve fibre layer (RNFL) was significantly lower in the outer nasal area (50.38 ± 8.20 μm vs. 45.17 ± 11.25 μm, p = 0.005) in ganglion cells and inner plexiform layers (GCL+) in DM2. A positive correlation between the LDL-C and RNFL and a negative correlation between HDL-C levels and the inner temporal and central RNFL thickness were detected. The central (p = 0.021) and inner nasal (p = 0.01) areas were negatively correlated between the RNFL and MAIA, while GCL++ was positively correlated with the outer inferior (p = 0.015) and outer nasal areas (p = 0.024). Retinal sensitivity and macular RNFL thickness decrease in DM2 patients with moderate DR with no DME, and this study enables an accurate approach to this disease with personalised assessment based on the DR course or stage. Thus, GCL+ and GCL++ thinning may support ganglion cell loss before the RNFL is affected.
Optimizing Image Classification: Automated Deep Learning Architecture Crafting with Network and Learning Hyperparameter Tuning
Authors: Ang Koon Meng , Lim Wei Hong , Tiang Sew Sun , Sharma Abhishek , Eid Marwa M. , Tawfeek Sayed M. , Khafaga Doaa Sami , Alharbi Amal H. , Abdelhamid Abdelaziz A.
Published: November 2023

This study introduces ETLBOCBL-CNN, an automated approach for optimizing convolutional neural network (CNN) architectures to address classification tasks of varying complexities. ETLBOCBL-CNN employs an effective encoding scheme to optimize network and learning hyperparameters, enabling the discovery of innovative CNN structures. To enhance the search process, it incorporates a competency-based learning concept inspired by mixed-ability classrooms during the teacher phase. This categorizes learners into competency-based groups, guiding each learner’s search process by utilizing the knowledge of the predominant peers, the teacher solution, and the population mean. This approach fosters diversity within the population and promotes the discovery of innovative network architectures. During the learner phase, ETLBOCBL-CNN integrates a stochastic peer interaction scheme that encourages collaborative learning among learners, enhancing the optimization of CNN architectures. To preserve valuable network information and promote long-term population quality improvement, ETLBOCBL-CNN introduces a tri-criterion selection scheme that considers fitness, diversity, and learners’ improvement rates. The performance of ETLBOCBL-CNN is evaluated on nine different image datasets and compared to state-of-the-art methods. Notably, ELTLBOCBL-CNN achieves outstanding accuracies on various datasets, including MNIST (99.72%), MNIST-RD (96.67%), MNIST-RB (98.28%), MNIST-BI (97.22%), MNST-RD + BI (83.45%), Rectangles (99.99%), Rectangles-I (97.41%), Convex (98.35%), and MNIST-Fashion (93.70%). These results highlight the remarkable classification accuracy of ETLBOCBL-CNN, underscoring its potential for advancing smart device infrastructure development.
Dimensionality Reduction Hybrid U-Net for Brain Extraction in Magnetic Resonance Imaging
Authors: Du Wentao , Yin Kuiying , Shi Jingping
Published: November 2023

In various applications, such as disease diagnosis, surgical navigation, human brain atlas analysis, and other neuroimage processing scenarios, brain extraction is typically regarded as the initial stage in MRI image processing. Whole-brain semantic segmentation algorithms, such as U-Net, have demonstrated the ability to achieve relatively satisfactory results even with a limited number of training samples. In order to enhance the precision of brain semantic segmentation, various frameworks have been developed, including 3D U-Net, slice U-Net, and auto-context U-Net. However, the processing methods employed in these models are relatively complex when applied to 3D data models. In this article, we aim to reduce the complexity of the model while maintaining appropriate performance. As an initial step to enhance segmentation accuracy, the preprocessing extraction of full-scale information from magnetic resonance images is performed with a cluster tool. Subsequently, three multi-input hybrid U-Net model frameworks are tested and compared. Finally, we propose utilizing a fusion of two-dimensional segmentation outcomes from different planes to attain improved results. The performance of the proposed framework was tested using publicly accessible benchmark datasets, namely LPBA40, in which we obtained Dice overlap coefficients of 98.05%. Improvement was achieved via our algorithm against several previous studies.
Synaptotagmin 1 Suppresses Colorectal Cancer Metastasis by Inhibiting ERK/MAPK Signaling-Mediated Tumor Cell Pseudopodial Formation and Migration
Authors: Shi Jianyun , Li Wenjing , Jia Zhenhua , Peng Ying , Hou Jiayi , Li Ning , Meng Ruijuan , Fu Wei , Feng Yanlin , Wu Lifei , Zhou Lan , Wang Deping , Shen Jing , Chang Jiasong , Wang Yanqiang , Cao Jimin
Published: November 2023

Although synaptotagmin 1 (SYT1) has been identified participating in a variety of cancers, its role in colorectal cancer (CRC) remains an enigma. This study aimed to demonstrate the effect of SYT1 on CRC metastasis and the underlying mechanism. We first found that SYT1 expressions in CRC tissues were lower than in normal colorectal tissues from the CRC database and collected CRC patients. In addition to this, SYT1 expression was also lower in CRC cell lines than in the normal colorectal cell line. SYT1 expression was downregulated by TGF-β (an EMT mediator) in CRC cell lines. In vitro, SYT1 overexpression repressed pseudopodial formation and reduced cell migration and invasion of CRC cells. SYT1 overexpression also suppressed CRC metastasis in tumor-bearing nude mice in vivo. Moreover, SYT1 overexpression promoted the dephosphorylation of ERK1/2 and downregulated the expressions of Slug and Vimentin, two proteins tightly associated with EMT in tumor metastasis. In conclusion, SYT1 expression is downregulated in CRC. Overexpression of SYT1 suppresses CRC cell migration, invasion, and metastasis by inhibiting ERK/MAPK signaling-mediated CRC cell pseudopodial formation. The study suggests that SYT1 is a suppressor of CRC and may have the potential to be a therapeutic target for CRC.
Plasmacytoid Dendritic Cell, Slan+-Monocyte and Natural Killer Cell Counts Function as Blood Cell-Based Biomarkers for Predicting Responses to Immune Checkpoint Inhibitor Monotherapy in Non-Small Cell Lung Cancer Patients
Authors: Pettinella Francesca , Lattanzi Chiara , Donini Marta , Caveggion Elena , Marini Olivia , Iannoto Giulia , Costa Sara , Zenaro Elena , Fortunato Tiago Moderno , Gasperini Sara , Giani Matteo , Belluomini Lorenzo , Sposito Marco , Insolda Jessica , Scaglione Ilaria Mariangela , Milella Michele , Adamo Annalisa , Poffe Ornella , Bronte Vincenzo , Dusi Stefano , Cassatella Marco A. , Ugel Stefano , Pilotto Sara , Scapini Patrizia
Published: November 2023

The advent of immune checkpoint inhibitors (ICIs), for instance, programmed cell death 1 (PD-1)/PD-1 ligand 1 (PD-L1) blockers, has greatly improved the outcome of patients affected by non-small cell lung cancer (NSCLC). However, most NSCLC patients either do not respond to ICI monotherapy or develop resistance to it after an initial response. Therefore, the identification of biomarkers for predicting the response of patients to ICI monotherapy represents an urgent issue. Great efforts are currently dedicated toward identifying blood-based biomarkers to predict responses to ICI monotherapy. In this study, more commonly utilized blood-based biomarkers, such as the neutrophil-to-lymphocyte ratio (NLR) and the lung immune prognostic index (LIPI) score, as well as the frequency/number and activation status of various types of circulating innate immune cell populations, were evaluated in NSCLC patients at baseline before therapy initiation. The data indicated that, among all the parameters tested, low plasmacytoid dendritic cell (pDC), slan+-monocyte and natural killer cell counts, as well as a high LIPI score and elevated PD-L1 expression levels on type 1 conventional DCs (cDC1s), were independently correlated with a negative response to ICI therapy in NSCLC patients. The results from this study suggest that the evaluation of innate immune cell numbers and phenotypes may provide novel and promising predictive biomarkers for ICI monotherapy in NSCLC patients.
Transoral Ultrasound in the Outpatient Clinic for the Diagnostic Work-Up of Oropharyngeal Cancer: A Feasibility Study
Authors: Garset-Zamani Martin , Norling Rikke , Hahn Christoffer Holst , Agander Tina Klitmøller , von Buchwald Christian , Todsen Tobias
Published: November 2023

Magnetic resonance imaging (MRI) is the preferred imaging modality for oropharyngeal cancers (OPCs), but it has difficulties distinguishing between small OPCs and unilateral tonsil hypertrophy. We hypothesized that surgeon-performed transoral ultrasound (US) could be used to accurately detect T-stage OPCs. We performed a single-center prospective diagnostic accuracy study including patients with suspected or biopsy-verified OPCs during outpatient appointments. All patients were offered transoral US and MRI. If transoral US could not be tolerated by the patient, transcervical US was performed. The primary outcome was the diagnostic accuracy of detecting OPCs with US compared to MRI, using histopathology as the reference standard. The secondary outcome was comparing the primary tumor diameters between US and MRI blinded to each other. Out of the 26 patients included in the study, 21 (81%) had OPCs. Transoral US could be performed in 21/21 and 1/5 patients with suspected palatine and lingual tonsil OPCs, respectively. Overall, US diagnostic accuracy was 92%, compared to 81% with MRI (p = 0.37). US and MRI had a high correlation between tumor diameters in the anteroposterior diameter (R = 0.80, p < 0.001), corresponding to the depth axis on US. In conclusion, this small study showed the promise and feasibility of transoral US to improve the initial clinical evaluations of patients with suspected OPCs.
Sustainably Sourced Mesoporous Carbon Molecular Sieves as Immobilization Matrices for Enzymatic Biofuel Cell Applications
Authors: Torrigino Federica , Nagel Marcel , Peng Zhujun , Hartmann Martin , Herkendell Katharina
Published: November 2023

Ordered mesoporous carbon CMK-3 sieves with a hexagonal structure and uniform pore size have recently emerged as promising materials for applications as adsorbents and electrodes. In this study, using sucrose as the sustainable carbon source and SBA-15 as a template, CMK-3 sieves are synthesized to form bioelectrocatalytic immobilization matrices for enzymatic biofuel cell (EFC) electrodes. Their electrochemical performance, capacitive features, and the stability of enzyme immobilization are analyzed and compared to commercially available multi-walled carbon nanotubes (MWCNT) using cyclic voltammetry and electrochemical impedance spectroscopy (EIS). The anodic reaction in the presence of glucose oxidase (GOx) and ferrocene methanol (FcMeOH) on the sustainably sourced CMK-3-based electrodes produces bioelectrocatalytic current responses at 0.5 V vs. saturated calomel electrode (SCE) that are twice as high as on the MWCNT-based electrodes under saturated glucose conditions. For the cathodic reaction, the MWCNT-based cathode performs marginally better than the CMK-3-based electrodes in the presence of bilirubin oxidase (BOD) and 2,2′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS2−). The CMK-3-based EFCs assembled from the GOx anode and BOD cathode results in a power output of 93 μW cm−2. In contrast, the output power of MWCNT-based EFCs is approximately 53 μW cm−2. The efficiency of CMK-3 as a support material for biofuel cell applications is effectively demonstrated.
Proteomic Analyses of the G Protein-Coupled Estrogen Receptor GPER1 Reveal Constitutive Links to Endoplasmic Reticulum, Glycosylation, Trafficking, and Calcium Signaling
Authors: Ahmadian Elmi Maryam , Motamed Nasrin , Picard Didier
Published: November 2023

The G protein-coupled estrogen receptor 1 (GPER1) has been proposed to mediate rapid responses to the steroid hormone estrogen. However, despite a strong interest in its potential role in cancer, whether it is indeed activated by estrogen and how this works remain controversial. To provide new tools to address these questions, we set out to determine the interactome of exogenously expressed GPER1. The combination of two orthogonal methods, namely APEX2-mediated proximity labeling and immunoprecipitation followed by mass spectrometry, gave us high-confidence results for 73 novel potential GPER1 interactors. We found that this GPER1 interactome is not affected by estrogen, a result that mirrors the constitutive activity of GPER1 in a functional assay with a Rac1 sensor. We specifically validated several hits highlighted by a gene ontology analysis. We demonstrate that CLPTM1 interacts with GPER1 and that PRKCSH and GANAB, the regulatory and catalytic subunits of α-glucosidase II, respectively, associate with CLPTM1 and potentially indirectly with GPER1. An imbalance in CLPTM1 levels induces nuclear association of GPER1, as does the overexpression of PRKCSH. Moreover, we show that the Ca2+ sensor STIM1 interacts with GPER1 and that upon STIM1 overexpression and depletion of Ca2+ stores, GPER1 becomes more nuclear. Thus, these new GPER1 interactors establish interesting connections with membrane protein maturation, trafficking, and calcium signaling.
GRF2 Is Crucial for Cone Photoreceptor Viability and Ribbon Synapse Formation in the Mouse Retina
Authors: Jimeno David , Lillo Concepción , de la Villa Pedro , Calzada Nuria , Santos Eugenio , Fernández-Medarde Alberto
Published: November 2023

Using constitutive GRF1/2 knockout mice, we showed previously that GRF2 is a key regulator of nuclear migration in retinal cone photoreceptors. To evaluate the functional relevance of that cellular process for two putative targets of the GEF activity of GRF2 (RAC1 and CDC42), here we compared the structural and functional retinal phenotypes resulting from conditional targeting of RAC1 or CDC42 in the cone photoreceptors of constitutive GRF2KO and GRF2WT mice. We observed that single RAC1 disruption did not cause any obvious morphological or physiological changes in the retinas of GRF2WT mice, and did not modify either the phenotypic alterations previously described in the retinal photoreceptor layer of GRF2KO mice. In contrast, the single ablation of CDC42 in the cone photoreceptors of GRF2WT mice resulted in clear alterations of nuclear movement that, unlike those of the GRF2KO retinas, were not accompanied by electrophysiological defects or slow, progressive cone cell degeneration. On the other hand, the concomitant disruption of GRF2 and CDC42 in the cone photoreceptors resulted, somewhat surprisingly, in a normalized pattern of nuclear positioning/movement, similar to that physiologically observed in GRF2WT mice, along with worsened patterns of electrophysiological responses and faster rates of cell death/disappearance than those previously recorded in single GRF2KO cone cells. Interestingly, the increased rates of cone cell apoptosis/death observed in single GRF2KO and double-knockout GRF2KO/CDC42KO retinas correlated with the electron microscopic detection of significant ultrastructural alterations (flattening) of their retinal ribbon synapses that were not otherwise observed at all in single-knockout CDC42KO retinas. Our observations identify GRF2 and CDC42 (but not RAC1) as key regulators of retinal processes controlling cone photoreceptor nuclear positioning and survival, and support the notion of GRF2 loss-of-function mutations as potential drivers of cone retinal dystrophies.