bluuebunny/crossref_metadata_2025_split huggingface dataset:
Screening and Preliminary Identification of Inhibin α Subunit-Specific Nanobodies by High-Throughput Sequencing Combined with Mass Spectrometry
Authors: Ma Jifu , Jarkhen Miragul , Li Zhenwei , Rizabek Kadyken , Nurzhan Shaugimbayeva , Karlygash Omarova , Ulzhan Nuralieva , Bodai Bakhet , Kazkhan Oralhazi 
Published: February 2023

Abstract
Inhibin is mainly a glycoprotein heterodimer secreted by female ovaries and male testes, which belongs to the TGF-β superfamily. In female animals, inhibin inhibits pituitary follicle stimulating hormone (FSH) synthesis through the endocrine pathway, and regulates follicular development, gametogenesis, and hormone secretion. In this study, high-throughput sequencing of the nanobody (VHH）gene in lymphocytes of Bactrian camels before and after immunization with inhibin α protein and mass spectrometry analysis of specific antibodies to inhibin α protein in serum after immunization were used to screen for inhibin α subunit-specific nanobodies.
The results of high-throughput sequencing showed that there were 57841 valid sequences in the VHH database before immunization, 53994 in the VHH database after immunization, and 816 in the specific VHH database after immunization. After searching the database, the results of mass spectrometry showed that 35 peptides and 135 proteins were found in the serum-specific antibodies after immunization. Inhibin α subunit-specific antibody contains 31 peptides and 33 proteins. Finally, 10 nanobody gene sequences were screened according to the location of the complementary determinant region and protein score, namely Nb-1712, Nb-573, Nb-267, Nb-1971, Nb-2000, Nb-799, Nb-1581, Nb-2004, Nb-1737, and Nb-338. In addition, 10 nanobodies had high affinity to the inhibin α protein by protein simulation docking and indirect enzyme linked immunosorbent assay (ELISA ) affinity identification.
In this study, 10 inhibin α subunit-specific nanobody genes were screened from the lymphocyte genome of a Xinjiang Bactrian camel by high-throughput sequencing combined with mass spectrometry for the first time, and their affinity with the inhibin α subunit was preliminary identified. This study will provide theoretical guidance and technical support for improving the FSH level and ovulation rate of animals and will also provide a certain reference value for the development of reproductive immunology.
Pre-transplant Biomarkers of Immune Dysfunction Improve Risk Assessment of Post-transplant Mortality Compared to Conventional Clinical Risk Scores
Authors: Medina-Morales J. Esli , Panayotova Guergana G. , Nguyen Duc T. , Graviss Edward A. , Prakash Gagan S. , Marsh Jeffery A. , Simonishvili Sopio , Shah Yash , Ayorinde Tumininu , Qin Yong , Jin Lianhua , Zoumpou Theofano , Minze Laurie J. , Paterno Flavio , Amin Arpit , Riddle Grace Lee , Ghobrial R. Mark , Guarrera James V. , Lunsford Keri E. 
Published: February 2023

Abstract

Introduction: There is a critical need to accurately stratify liver transplant (LT) candidates' risk of post-LT mortality prior to LT to optimize patient selection and avoid futility. Here, we compare previously described pre-LT clinical risk scores with the recently developed Liver Immune Frailty Index (LIFI) for prediction of post-LT mortality. LIFI measures immune dysregulation based on pre-LT plasma HCV IgG, MMP3 and Fractalkine. LIFI accurately predicts post-LT mortality, with LIFI-low corresponding to 1.4% 1-year post-LT mortality compared with 58.3% for LIFI-high (C-statistic=0.85).
Methods: LIFI was compared to MELD, MELD-Na, MELD 3.0, D-MELD, MELD-GRAIL, MELD-GRAIL-Na, UCLA-FRS, BAR, SOFT, P-SOFT, and LDRI scores on 289 LT recipients based on waitlist data at the time of LT. Survival, hazard of early post-LT death, and discrimination power (C-statistic) were assessed.
Results: LIFI showed superior discrimination (highest C-statistic) for post-LT mortality when compared to all other risk scores, irrespective of biologic MELD. On univariate analysis, the LIFI showed a significant correlation with mortality 6-months, as well as 1-, 3-, and 5-years. No other pre-LT scoring system significantly correlated with post-LT mortality. On bivariate adjusted analysis, African American race (p<0.05) and pre-LT cardiovascular disease (p=0.053) were associated with early- and long-term post-LT mortality. Patients who died within 1-yr following LT had a significantly higher incidence of infections, including 30-day and 90-day incidence of any infection, pneumonia, abdominal infections, and UTI (p<0.05).
Conclusions: LIFI, which measures pre-LT biomarkers of immune dysfunction, more accurately predicts risk of post-LT futility compared with current clinical predictive models. Pre-LT assessment of immune dysregulation may be critical in predicting mortality after LT and may optimize selection of candidates with lowest risk of futile outcomes.
A Semantic Segmentation Scheme for Night Driving improved by Irregular Convolution
Authors: Xuantao Yang , Junying Han , Chenzhong Liu 
Published: February 2023

Abstract
In order to solve the poor performance of real-time semantic segmentation of road conditions in video images due to insufficient light and motion blur when vehicles are driving at night, This study proposes a scheme: a fuzzy information complementation strategy based on generative models and a network that fuses different intermediate layer outputs to complement spatial semantics with also embeds irregular convolutional attention modules for fine extraction of motion target boundaries. First, DeblurGan is used to generate information to fix the lost semantics in the original image due to blurring; then, the outputs of different intermediate layers in the backbone network are taken out, assigned different weight scaling factors and fused; finally, by comparing the performance of different attention mechanisms, the irregular convolutional attention with the best effect is selected. The scheme achieves Global Accuracy:89.1% Mean IOU:94.2% on the night driving dataset of this experiment, which exceeds the best performance of DeepLabv3 by 1.3% and 7.2%, and achieves Accuracy:83.0% on the small volume label (Moveable), which is underperformed by all control models. The experimental results demonstrate that the solution can effectively cope with various problems faced by night driving and enhance the model's perception and analysis of driving road conditions. The results of the study provide a technical reference for the semantic segmentation problem of vehicles driving in the nighttime environment.
Cellulose Microspheres As Promising Sustainable Controlled Release Carriers for Fertilizers
Authors: Balang Joshua Blucha , Tay Kimberly Wei-Wei , Chin Suk-Fun , Wasli Mohd Effendi , Musa Zaki , Chen Yi-Chun 
Published: February 2023

Abstract
Background: Cellulose fibers extracted from printed paper wastes are utilized to synthesize spherical cellulose microspheres via water-in-oil microemulsion and precipitation methods. Span 80 was used as a surfactant and acetic acid as a precipitating agent in the microemulsion and precipitation process to obtain cellulose microspheres. The effects of synthesis conditions such as cellulose concentrations and drying techniques were observed to have profound effects on the surface morphology, particle sizes, and surface area of cellulose microspheres produced.
Results: Spherical cellulose microspheres with particle sizes ranging from 5.2 to 9.3 µm were synthesized. Increasing cellulose concentrations led to larger particle sizes. Among various kinds of drying techniques, freeze-drying is the most preferable method for obtaining better yields of cellulose microspheres. The potential applications of the synthesized cellulose microspheres as controlled-release carriers for fertilizer in various soil types were evaluated. The larger particle sizes of cellulose microspheres have a smaller specific surface area, but with higher loading capacities and slower urea release.
Conclusions: Our studies showed that the loading capacity and release profiles of urea could be tailored by modulating the mean particle sizes of the cellulose microspheres. Hence, cellulose microspheres demonstrated great potential to be utilized as sustainable controlled-release carriers for fertilizer.
On refinements of the Fekete-Szegö inequality for a class of holomorphic mappings associated with spirallike mappings
Authors: Fang Weikang , Xu Qinghua 
Published: February 2023

Abstract
In this paper, we establish some refinements of the Fekete and Szegö inequalities for a class of holomorphic mappings holomorphic relatedto spirallike mappings in several complex variables. The results presented here would generalize some known results.
Mathematics Subject Classification. Primary 32H02; Secondary 30C45.
Analysis of human neuronal cells carrying ASTN2 deletion: A cross-disorder risk variant of schizophrenia, autism spectrum disorder, and bipolar disorder
Authors: Arioka Yuko , Hayashi Yu , Okumura Hiroki , Kushima Itaru , Mori Daisuke , Lo Tzuyao , Otgonbayar Gantsooj , Kato Hidekazu , Nawa Yoshihiro , Kimura Hiroki , Aleksic Branko , Ozaki Norio 
Published: February 2023

Abstract

Recent genetic studies have found common genomic risk variants among schizophrenia (SCZ), autism spectrum disorder (ASD), and bipolar disorder (BP), strongly suggesting the overlaps in their molecular and cellular mechanism. Our research group identified the variant in ASTN2 as one of the candidate risk factors across these psychiatric disorders by whole-genome copy number variation analysis. However, the alterations in the human neuronal cells resulting from ASTN2 variants identified in patients remain unknown. To address this, we used patient-derived and genome-edited iPS cells with ASTN2 deletion; cells were further differentiated into neuronal cells. A comprehensive gene expression analysis revealed that the expression level of ZNF558, a gene specifically expressed in human forebrain neural progenitor cells, was greatly reduced in ASTN2-deleted neuronal cells. Furthermore, the expression of the mitophagy-related gene SPATA18, which is repressed by ZNF558, and mitophagy activity were increased in ASTN2-deleted neuronal cells. These phenotypes were detected in both neuronal cells from patient-derived and genome-edited iPS cells with ASTN2 deletion. Our results suggest that ASTN2 deletion is related to the common pathogenic mechanism of SCZ, ASD, and BP by regulating mitophagy via ZNF558.
Applying Design Principles to Support Healthcare Interiors
Authors: Guevara Diane 
Published: February 2023

Abstract
The purpose of this study aimed to continue the research from a previous peer reviewed pilot-study. In the pilot-study, data was collected and applied to healthcare interior design and renovation recommendations. This current study continued the analysis of that data and added links to Research Informed Design (RID), Evidence-Based Design (EBD) principles, and Universal Design (UD) principles. The objective of the study is to produce a data collection instrument for use in any healthcare interior, not solely healthcare patient rooms, and to recommend the use of inclusive UD principles by healthcare interior designers and facility managers when considering new and renovated of healthcare facilities. The method in this study used pilot-study data, conducted a review of the literature, and added a systematic method for applying UD principles to support ant healthcare interior design renovation recommendations. The results of this study included the proposed data collection instrument, with pilot-study data applied, and a 40% increase (over the pilot study) in design guidelines for practice. The conclusion of this article summarizes with implications for practice for healthcare interior design and renovations.
nmODE: Neural Memory Ordinary Differential Equation
Authors: Yi Zhang 
Published: February 2023

Abstract
Brain neural networks are regarded as dynamical systems in neural science, in which memories are interpreted as attractors of the systems. Mathematically, ordinary differential equations (ODEs) can be utilized to describe dynamical systems. Any ODE that employed to describe the dynamics of a neural network can be called a neuralODE. Inspired by rethinking the nonlinear representation ability of existing artificial neural networks together with the functions of columns in neocortex, this paper proposes a theory of memory based neuralODE, which composes of two novel artificial neural network models: nmODE, ε-net, and two learning algorithms: nmLA, ε-LA. The nmODE (neural memory Ordinary Differential Equation) is designed with a special structure of separating learning neurons from memory neurons, which makes it has clear dynamics. Given any external input, the nmODE possesses the global attractor property and thus embedded with a memory mechanism accordingly. The nmODE establishes a nonlinear mapping from the external input to its associated attractor and does not have the problem of learning features homeomorphic to the input data space as occurred frequently in most existing neuralODEs. The nmLA (neural memory Learning Algorithm) is developed by proposing an interesting three-dimensional inverse ODE (invODE), it has advantages on memory and parameter efficiency. The proposed ε-net is a discrete version of nmODE, which is particularly feasible for digital computing. The proposed ε-LA (ε learning algorithm) requires no prior knowledge of the number of network layers. Both nmLA and ε-LA have no problem on gradient vanishing. Experimental results show that the proposed theory is comparable to state-of-the-art methods.
Path Planning for Intelligent Vehicles Based on Improved D* Lite
Authors: Li Xiaomei , Lu Ye , Zhao Xiaoyu , Deng Xiong , Xie Zhijiang 
Published: February 2023

Abstract
Typical path planning algorithms are good for static obstacles avoidance, but not for dynamic obstacles, so path planning of intelligent vehicles in uncharted regions is a fundamental and critical problem. This study suggests an improved D* Lite path planning algorithm to address the issues of large corner, node redundancy and close to obstacles in the path planned by D* Lite algorithm. Firstly, in order to increase the safety of the path, the D* Lite algorithm sets the safety distance between the intelligent vehicle and obstacles. Then, the kinematic constraints of intelligent vehicles are introduced to increase the path search direction and avoid path corners exceeding the steering maneuverability of intelligent vehicles. Next, the path is optimized, and the optimization process of removing redundant points is employed to tackle the problem of curved search path and redundant nodes, and the path is smoothed by using third-order Bezier curve to generate a path with continuous curvature. Finally, the enhanced D* Lite algorithm is fused with the improved dynamic window approach (IDWA) to achieve real-time obstacle avoidance based on the global optimal path for moving obstacles. Simulation studies in static and dynamic contexts are used to demonstrate the usefulness of the revised D* Lite algorithm. The results show that compared with other path planning methods, the path generated by the proposed method has more safety and smoothness features, and improves the path quality. Therefore, the proposed algorithm has certain effectiveness and superiority in path planning problems in static and dynamic environments
Exploring root architecture and rhizosphere biology in fourteen winter wheat varieties released in Chile from 1965 to 2020
Authors: Paz-Vidal Paula , Castillo-Rosales Dalma , López María Dolores , Tejos Iván Matus , Noriega Felipe , Schoebitz Maurico 
Published: February 2023

Abstract

Background and Aims. The study aims to explore the impact of advancements in wheat genetics on root structure and rhizosphere biology, which are still not fully understood. Specifically, we investigated various factors including the exudation of carboxylates, colonization by arbuscular mycorrhizal fungi, microbial activity, and root architecture in winter wheat varieties that have been released between 1965 and 2020. Methods. To conduct our study, we sowed fourteen different winter wheat varieties with four replicates on acidic Andisol at field conditions. Complete root systems and soil samples were extracted using a tractor-mounted hydraulic sampler tube of 3.5 cm diameter, which reached a depth of 60 cm. Results. In this sense, succinate showed a significant increase by 21%. Mycorrhizal colonization was inversely proportional to P concentrations and all varieties showed higher microbial activity at anthesis. The longest roots were found in varieties released after the year 2000, but no significant differences were found in other root architecture parameters. There was no clear pattern observed in root architecture or biological activity as a function of the year of release. Plant genetics moderated root architecture, carboxylate exudation, microbial activity, and mycorrhizal colonization, all of which are affected by high P concentrations. Conclusions. This study investigated plant-microorganism interactions, often overlooked due to root system analysis challenges. Older wheat varieties showed higher carboxylate exudation. We identified wheat varieties with potential for improved root systems and crop efficiency.
Improving performance of natural rubber composites by the application of functional biofiller - horsetail modified with silane coupling agents
Authors: Miedzianowska Justyna , Masłowski Marcin , Strzelec Krzysztof 
Published: February 2023

Abstract
The growing ecological awareness of society and increasingly stringent legal requirements regarding environmental protection and the strategy of implementing the principles of sustainable development force the search for and continuous development of environmentally friendly solutions in the field of polymer materials technology. One of the directions is the use of raw materials from renewable sources. For this reason, the research object of the presented work was natural rubber composites containing a filler of plant origin in the form of ground horsetail (HT) biomass. Despite its health-promoting properties, it is commonly considered a weed. What's more, the ubiquitous occurrence and surplus make it a valuable source of waste biomass for management. Taking into account the limitations resulting from the hydrophilic nature of the lignocellulosic filler, and the related poor adhesion to the non-polar elastomer matrix, the horsetail filler was modified with organoalkoxysilanes. The study used silane compounds containing groups that can affect the properties of vulcanizates in various ways, such as vinyltriethoxysilane (VTES), 3,3′-Tetrathiobis(propyl-triethoxysilane) (TESPT), 3-(aminopropyl)triethoxysilane (APTES), 3-(chloropropyl)triethoxysilane (CPTES) and octyltriethoxysilane (OTES). The process of modifying the natural filler contributed to structural changes in the lignocellulosic material, which may indicate the effective attachment of silane compounds to the horsetail surface. The results of the contact angle analysis show that the treatment strongly influenced the surface characteristics of the fillers, making them more hydrophobic.
The results show that the type of silane coupling agent affects not only the processing associated with the vulcanization process but also the mechanical properties of the NR vulcanizates. This phenomenon is probably the result of increased rubber-bioadditive interaction and improved filler dispersion. Moreover, all composites with modified HT, show a greater flame permanence time than the one using unmodified filler.
Bamboo fiber-derived bifunctional electrocatalyst for rechargeable Zn- Air batteries
Authors: Yu Jian , Chen Zehong , Zhong Linxin , Yang Wu , Li Tingzhen , Huang Yongfa , Wei Yujia , Peng Xinwen 
Published: February 2023

Abstract
Low-cost and high-performance bifunctional electrocatalysts for efficient oxygen reduction reaction (ORR)/oxygen evolution reaction (OER) are vital for the applications of rechargeable Zn-air batteries (ZABs). Herein, a porous carbon material is fabricated by traditional pulp and papermaking and carbonization process from bamboo. The resultant carbon paper catalyst possesses a high surface area, porous structure and high content of nitrogen. Benefiting from these characteristics, this material exhibits remarkable ORR and OER catalytic performances. The aqueous rechargeable Zn-air batteries assembled with this catalyst exhibit a high power density of 279.5 mW cm−2. This work paves an encouraging way for the industrial production of cost-effective catalysts in a sustainable manner.
Wong-zakai Approximation for a Stochastic 2D Cahn-hilliard-navier-stokes Model
Authors: MEDJO T. TACHIM 
Published: February 2023

Abstract
In this paper, we demonstrate the Wong-Zakai approximation results for two dimensional stochastic Cahn-Hilliard-Navier-Stokes model. The model consists of a Navier-Stokes system coupled with a convective Cahn-Hilliard equations. It describes the motion of an incompressible isothermal mixture of two (partially) immiscible fluids under the influence of multiplicative noise. Our main result describes the support of the distribution of solutions. As in [2], both inclusions are proved by means of a general Wong-Zakai type result of convergence in probability for nonlinear stochastic PDEs driven by a Hilbert-valued Brownian motion and some adapted finite dimensional approximation of this process. Note that the coupling between the Navier-Stokes system and the Cahn-Hilliard equations makes the analysis more involved.
A geometric approach to fixed point theorems for mappings satisfying implicit relations in quasi multiplicative metric spaces
Authors: Kamal A. 
Published: February 2023

Abstract
In this work, we introduce a generalized type of multiplicative metric space so-called quasi multiplicative metric space (abbreviated as q-multiplicative metric space). We state and prove fixed point theorems in this space. Also we investigate geometric properties of common fixed points in the context of the fixed-circle problem. To do this, we propose some new solutions to the fixed-circle problem on q-multiplicative metric space
Critical mass curves for a short-rangedchemical signaling loop
Authors: Yu Hao , Xue Bingqian , Zhao Lifen 
Published: February 2023

Abstract
In this paper, we consider a two-species and two-stimuli chemotaxis system,in which the interactions of the two species form a short-ranged chemical signaling loop. We establish the critical mass curves for the system to distinguish the global boundedness and finite-time blow-up of solutions.
2020MSC: 35B44, 35K57, 35Q92, 92C17.
In Vivo Porcine Model of Acute Iliocaval Deep Vein Thrombosis
Authors: Roberts Sophia , Zaghloul Mohamed , Ismail Usama , Rowe Roger A. , Engel Connor , Meade Rodrigo , Elizondo-Benedetto Santiago , Genin Guy M. , Zayed Mohamed A. 
Published: February 2023

Abstract

Acute deep vein thrombosis (DVT) is a potentially life-threatening condition in which blood clots form in the venous system. Recently, a number of endovascular thrombectomy devices have been commercialized for the treatment of acute DVT. With variable efficacy and safety profiles, the current state-of-the-art has identified potential areas for further device innovation and opportunities for improvement. However, a major limitation in the testing, verification, and validation of new thrombectomy is a clinically representative large animal model of acute DVT. Unfortunately, existing approaches to creating DVT in porcine models are time consuming, technically challenging, and provide inconsistent results. We therefore developed a rapid and more reproducible protocol for induction of large-volume iliocaval DVTs in a living porcine host. This approach involves sequestering the iliocaval with standard balloon occlusion catheters, and a controlled and limited infusion of a 25% ethanol solution within the sequestered segment. We observed that this method was safe, technically straightforward, and reproducible in creating large-volume acute DVTs. We believe this model can be utilized in a standardized approach for the future testing of future endovascular venous thrombectomy devices.