bluuebunny/crossref_metadata_2025 huggingface dataset:
Characterization of Virulence Factors and Antimicrobial Susceptibility of Streptococcus agalactiae Associated with Bovine Mastitis Cases in Thailand
Authors: Wataradee Sirirat , Boonserm Thanasak , Samngamnim Sukuma , Ajariyakhajorn Kittisak
Published: January 2024

Streptococcus agalactiae is a contagious pathogen that causes bovine mastitis. The ability of S. agalactiae to cause widespread mastitis relies on bacterial virulence factors. In this study, we detected 10 virulence determinants associated with mastitis pathogenicity using conventional PCR. The antimicrobial susceptibility of 100 S. agalactiae isolates from 13 Thai dairy herds was assessed using the Kirby–Bauer disk diffusion susceptibility test. All strains had at least three virulence factors responsible for invasion, adhesion, and infection (fbsB, bibA, and cfb, respectively). The predominant virulent profile of S. agalactiae strains revealed the presence of fbsA, fbsB, bibA, cfb, and cyl (n = 96). Most strains were sensitive to penicillin, ampicillin, amoxicillin-clavulanic acid, cefotaxime, ceftiofur, erythromycin, sulfamethoxazole-trimethoprim, and vancomycin. However, all strains were resistant to aminoglycosides, including kanamycin and gentamicin attributed to the unnecessary antimicrobial use. Furthermore, we identified seven multidrug resistant (MDR) S. agalactiae strains among four dairy herds, of which, two were vancomycin resistant. Our study provides profiles for virulence factors and antimicrobial susceptibility, which are beneficial for the clinical monitoring, prevention, and control of bovine mastitis in dairy cattle in Thailand. Moreover, we emphasize the need for awareness regarding the judicious use of antimicrobials on dairy farms.
Risk Factors Associated with Soil-Transmitted Helminths in Dog Feces That Contaminate Public Areas of Warsaw, Poland
Authors: Tylkowska Agnieszka , Mocha Natalia , Kołnierzak Marta Małgorzata , Szenejko Magdalena
Published: January 2024

A constant increase in dog numbers, especially in large towns, has been observed recently. The presence of dogs in urban spaces increases the risk of pollution by dogs’ feces, which may contain growth forms of parasites including canine, soil-transmitted helminths (cSTHs), most of which have a proven zoonotic potential. This study assessed the frequency of occurrence and estimated the potential risk associated with the presence of cSTHs in dogs’ feces left uncollected in urban areas. The study material consisted of 200 fecal samples obtained from city and dog parks situated in selected Warsaw districts. Each fecal sample was processed using the flotation technique. Eggs of cSTHs, including Toxocara canis, Toxascaris leonina, Trichuris vulpis, and hookworms from the Ancylostomatidae family were found in 23 (11.5%) of the examined fecal samples. The most prevalent species were hookworms from the family Ancylostomatidae (8%). The presence of parasites was confirmed in 14 out of 20 studied locations (70%), including eight city parks (72.7%) and six dog parks (66.7%). City and dog parks did not differ significantly in the frequency of parasite occurrence. This study indicated that dogs’ feces, left uncollected, may cause environmental contamination with cSTHs. It also indicated that the presence of dogs’ feces in public areas and the associated presence of parasites is still a problem.
Spotting the Pattern: A Review on White Coat Color in the Domestic Horse
Authors: McFadden Aiden , Vierra Micaela , Martin Katie , Brooks Samantha A. , Everts Robin E. , Lafayette Christa
Published: January 2024

Traits such as shape, size, and color often influence the economic and sentimental value of a horse. Around the world, horses are bred and prized for the colors and markings that make their unique coat patterns stand out from the crowd. The underlying genetic mechanisms determining the color of a horse’s coat can vary greatly in their complexity. For example, only two genetic markers are used to determine a horse’s base coat color, whereas over 50 genetic variations have been discovered to cause white patterning in horses. Some of these white-causing mutations are benign and beautiful, while others have a notable impact on horse health. Negative effects range from slightly more innocuous defects, like deafness, to more pernicious defects, such as the lethal developmental defect incurred when a horse inherits two copies of the Lethal White Overo allele. In this review, we explore, in detail, the etiology of white spotting and its overall effect on the domestic horse to Spot the Pattern of these beautiful (and sometimes dangerous) white mutations.
Enhanced Hippocampus–Nidopallium Caudolaterale Interaction in Visual–Spatial Associative Learning of Pigeons
Authors: Zhu Jun-Yao , Zhang Zhi-Heng , Liu Gang , Wan Hong
Published: January 2024

Learning the spatial location associated with visual cues in the environment is crucial for survival. This ability is supported by a distributed interactive network. However, it is not fully understood how the most important task-related brain areas in birds, the hippocampus (Hp) and the nidopallium caudolaterale (NCL), interact in visual–spatial associative learning. To investigate the mechanisms of such coordination, synchrony and causal analysis were applied to the local field potentials of the Hp and NCL of pigeons while performing a visual–spatial associative learning task. The results showed that, over the course of learning, theta-band (4–12 Hz) oscillations in the Hp and NCL became strongly synchronized before the pigeons entered the critical choice platform for turning, with the information flowing preferentially from the Hp to the NCL. The learning process was primarily associated with the increased Hp–NCL interaction of theta rhythm. Meanwhile, the enhanced theta-band Hp–NCL interaction predicted the correct choice, supporting the pigeons’ use of visual cues to guide navigation. These findings provide insight into the dynamics of Hp–NCL interaction during visual–spatial associative learning, serving to reveal the mechanisms of Hp and NCL coordination during the encoding and retrieval of visual–spatial associative memory.
Routing Design for Pipe System Considering Natural Frequency
Authors: Fan Jiang , Xu Hongbin , Meng Qingze , Su Yumin
Published: January 2024

This paper proposes a novel path planning method that considers the natural frequencies of pipes. The approach begins by presenting an adaptive decomposition method to accurately define the routing space for aero engines. Compared with the traditional decomposition method, obstacle identification efficiency is improved by more than 50%. This paper improves the initial population of the genetic algorithm based on the rapidly exploring random tree. Subsequently, a numerical surrogate model is developed to predict the natural frequencies of pipes. An evaluation function is created incorporating the weighted values of the natural frequency and the tube length. Additionally, this paper introduces several new operators to mitigate the issue of illegal paths during algorithm iterations. Finally, the proposed algorithm is demonstrated through experiments on two well-designed examples and an application in an aero engine.
Enhancement of GUI Display Error Detection Using Improved Faster R-CNN and Multi-Scale Attention Mechanism
Authors: Pan Xi , Huan Zhan , Li Yimang , Cao Yingying
Published: January 2024

Graphical user interfaces (GUIs) hold an irreplaceable position in modern software and applications. Users can interact through them. Due to different terminal devices, there are sometimes display errors, such as component occlusion, image loss, text overlap, and empty values during software rendering. To address the aforementioned common four GUI display errors, a target detection algorithm based on the improved Faster R-CNN is proposed. Specifically, ResNet-50 is used instead of the traditional VGG-16 as the feature extraction network. The feature pyramid network (FPN) and the enhanced multi-scale attention (EMA) algorithm are introduced to improve accuracy. ROI-Align is used instead of ROI-Pooling to enhance the generalization capability of the network. Since training models require a large number of labeled screenshots of errors, there is currently no publicly available dataset with GUI display problems. Therefore, a training data generation algorithm has been developed, which can automatically generate screenshots with GUI display problems based on the Rico dataset. Experimental results show that the improved Faster R-CNN achieves a detection accuracy of 87.3% in the generated GUI problem dataset, which is a 7% improvement compared to the previous version.
Integration of Deep Reinforcement Learning with Collaborative Filtering for Movie Recommendation Systems
Authors: Peng Sony , Siet Sophort , Ilkhomjon Sadriddinov , Kim Dae-Young , Park Doo-Soon
Published: January 2024

In the era of big data, effective recommendation systems are essential for providing users with personalized content and reducing search time on online platforms. Traditional collaborative filtering (CF) methods face challenges like data sparsity and the new-user or cold-start issue, primarily due to their reliance on limited user–item interactions. This paper proposes an innovative movie recommendation system that integrates deep reinforcement learning (DRL) with CF, employing the actor–critic method and the Deep Deterministic Policy Gradient (DDPG) algorithm. This integration enhances the system’s ability to navigate the recommendation space effectively, especially for new users with less interaction data. The system utilizes DRL for making initial recommendations to new users and to generate optimal recommendation as more data becomes available. Additionally, singular value decomposition (SVD) is used for matrix factorization in CF, improving the extraction of detailed embeddings that capture the latent features of users and movies. This approach significantly increases recommendation precision and personalization. Our model’s performance is evaluated using the MovieLens dataset with metrics like Precision, Recall, and F1 Score and demonstrates its effectiveness compared with existing recommendation benchmarks, particularly in addressing sparsity and new-user challenges. Several benchmarks of existing recommendation models are selected for the purpose of model comparison.
A Pavement Crack Detection and Evaluation Framework for a UAV Inspection System Based on Deep Learning
Authors: Chen Xinbao , Liu Chang , Chen Long , Zhu Xiaodong , Zhang Yaohui , Wang Chenxi
Published: January 2024

Existing studies often lack a systematic solution for an Unmanned Aerial Vehicles (UAV) inspection system, which hinders their widespread application in crack detection. To enhance its substantial practicality, this study proposes a formal and systematic framework for UAV inspection systems, specifically designed for automatic crack detection and pavement distress evaluation. The framework integrates UAV data acquisition, deep-learning-based crack identification, and road damage assessment in a comprehensive and orderly manner. Firstly, a flight control strategy is presented, and road crack data are collected using DJI Mini 2 UAV imagery, establishing high-quality UAV crack image datasets with ground truth information. Secondly, a validation and comparison study is conducted to enhance the automatic crack detection capability and provide an appropriate deployment scheme for UAV inspection systems. This study develops automatic crack detection models based on mainstream deep learning algorithms (namely, Faster-RCNN, YOLOv5s, YOLOv7-tiny, and YOLOv8s) in urban road scenarios. The results demonstrate that the Faster-RCNN algorithm achieves the highest accuracy and is suitable for the online data collection of UAV and offline inspection at work stations. Meanwhile, the YOLO models, while slightly lower in accuracy, are the fastest algorithms and are suitable for the lightweight deployment of UAV with online collection and real-time inspection. Quantitative measurement methods for road cracks are presented to assess road damage, which will enhance the application of UAV inspection systems and provide factual evidence for the maintenance decisions made by road authorities.
A Two-Stage Registration Strategy for Thermal–Visible Images in Substations
Authors: Sun Wanfeng , Gao Haibo , Li Cheng
Published: January 2024

The analysis of infrared video images is becoming one of the methods used to detect thermal hazards in many large-scale engineering sites. The fusion of infrared thermal imaging and visible image data in the target area can help people to identify and locate the fault points of thermal hazards. Among them, a very important step is the registration of thermally visible images. However, the direct registration of images with large-scale differences may lead to large registration errors or even failure. This paper presents a novel two-stage thermal–visible-image registration strategy specifically designed for exceptional scenes, such as a substation. Firstly, the original image pairs that occur after binarization are quickly and roughly registered. Secondly, the adaptive downsampling unit partial-intensity invariant feature descriptor (ADU-PIIFD) algorithm is proposed to correct the small-scale differences in details and achieve finer registration. Experiments are conducted on 30 data sets containing complex power station scenes and compared with several other methods. The results show that the proposed method exhibits an excellent and stable performance in thermal–visible-image registration, and the registration error on the entire data set is within five pixels. Especially for multimodal images with poor image quality and many detailed features, the robustness of the proposed method is far better than that of other methods, which provides a more reliable image registration scheme for the field of fire safety.
A New Method for Defining the Optimal Separation Gap Distance and the Acceptable Structural Pounding Risk on Multistory RC Structures
Authors: Flenga Maria G. , Favvata Maria J.
Published: January 2024

A proposal to control the structural pounding hazard imposed on multistory reinforced concrete (RC) structures is presented. The main goal is to guarantee the seismic performance of a structure with an acceptable (predefined) risk-targeted parameter without the need to eliminate structural pounding collisions. The key target parameters of this study are the annual probability of exceeding an engineering demand parameter (EDP) capacity level and the separation distance dg between adjacent structures. In this direction, a method that ensures the performance level of critical EDPs due to structural pounding conditions is proposed. The new method involves two decision frameworks that define (a) the optimal separation gap distance dg,minPt at a targeted value of pounding risk (probability per year) Pt (Decision A) and (b) the minimum acceptable structural pounding risk Pmindg,t at a targeted value of separation gap distance dg,t (Decision B). The demand parameters that are incorporated in the proposed method are the peak relative displacement δmax at the top level of colliding without considering pounding conditions and any other critical EDP due to the structural pounding effect. The overall method is based on two distinct acceptable performance objectives, the POs-δmax and the POs-EDP, defined as a function of P vs. dg. For this purpose, a seismic hazard curve compatible with Eurocode’s 8 hazard zone is adopted, and the corresponding demand hazard curves of δmax and EDP are developed. The proposed method is implemented to study the floor-to-floor structural pounding hazard of an eight-story RC frame taking into account different risk-targeted scenarios. The results show that the seismic risk (probability per year) of exceeding the EDP’s capacity level is significantly increased due to structural pounding in comparison to the case of no pounding. Calibration of the structural pounding risk can be obtained by adjusting the separation gap distance dg between the adjacent structures based on the acceptable POs. The POs-δmax is not always an accurate criterion for verifying the capacity level of the critical EDP. Finally, with the proposed method, a variety of POs-EDPs can be used to control the structural pounding risk in terms of dg,minPt and/or Pmindg,t.
Mineralogical Characterization of the Grot Lead and Zinc Mine Tailings from Aspects of Their Further Use as Raw Material
Authors: Gulicovski Jelena , Stojmenović Marija , Rosić Milena , Vasić Andrijana , Ristović Ivica , Janković-Častvan Ivona , Kragović Milan
Published: January 2024

The possibility of using waste tailings produced by flotation in the lead and zinc mine of Grot, Serbia as a potential source of secondary mineral raw materials was examined. The aim of the research was primarily to carry out a detailed characterization in order to determine the dominant minerals, and, for the first time, to trace the changes occurring in the unit cells of the minerals present in that deposit. There was also a need to determine the exact proportions of the present mineral phases for their further application and utilization as natural resources in environmental protection. Samples were taken from three different sections of tailings: the crest of dam (JKB), outlet pipe of the flotation facility (JOF) and hydrocyclone overflow (JHC). Granulometric separation was performed to facilitate the extraction of certain minerals from waste. The results showed that all samples mainly contained quartz, clinochlore, calcite, albite, pyrite and biotite, but their ratios in each sample varied significantly. After characterization, samples were separated into different fractions and their mineralogical compositions were determined. Depending on the fraction, the mineralogical compositions also changed. Mineralogy and geochemical analysis indicate that waste tailings can be used as a secondary mineral raw materials source applicable in various industries.
VL-Few: Vision Language Alignment for Multimodal Few-Shot Meta Learning
Authors: Ma Han , Fan Baoyu , Ng Benjamin K. , Lam Chan-Tong
Published: January 2024

Complex tasks in the real world involve different modal models, such as visual question answering (VQA). However, traditional multimodal learning requires a large amount of aligned data, such as image text pairs, and constructing a large amount of training data is a challenge for multimodal learning. Therefore, we propose VL-Few, which is a simple and effective method to solve the multimodal few-shot problem. VL-Few (1) proposes the modal alignment, which aligns visual features into language space through a lightweight model network and improves the multimodal understanding ability of the model; (2) adopts few-shot meta learning in the multimodal problem, which constructs a few-shot meta task pool to improve the generalization ability of the model; (3) proposes semantic alignment to enhance the semantic understanding ability of the model for the task, context, and demonstration; (4) proposes task alignment that constructs training data into the target task form and improves the task understanding ability of the model; (5) proposes generation alignment, which adopts the token-level training and multitask fusion loss to improve the generation ability of the model. Our experimental results show the effectiveness of VL-Few for multimodal few-shot problems.
Optimization of Structural Steel Used in Concrete-Encased Steel Composite Columns via Topology Optimization
Authors: İnce Elif Gökçe , Özkal Fatih Mehmet
Published: January 2024

Concrete-encased steel composite columns are preferred for their exceptional ductility and strength, particularly in high-rise buildings. This research aims to enhance both the strength and ductility of these composite columns by increasing the height of the steel profile. Typically, hexagonal or circular openings, referred to as castellated elements, are incorporated into the steel profile to achieve this height increase. This study employed a topology optimization method to identify the ideal opening shape for the steel profile in concrete-encased steel composite columns. The analysis revealed a sinusoidal-like opening shape, which was then refined for manufacturing. The optimal opening shape was used to increase the height of the existing steel profile, and nonlinear analyses were conducted to evaluate the effectiveness of this new optimized steel profile in concrete-encased steel composite columns. Two concrete-encased steel composite columns were designed: one with the optimal steel profile and the other with a standard steel I profile. ANSYS APDL 19.0 software was used to simulate an experiment based on an existing concrete-encased steel column to validate the nonlinear analysis. The verification analysis demonstrated a remarkable similarity between the experimental and numerical load–displacement graphs, indicating that the numerical analysis was reliable. In the analysis of the composite columns, both axial and lateral forces were applied in the nonlinear analyses. The axial force was applied at 15% of the column’s capacity, while the lateral force was applied until the composite column reached a state of failure. The results of the nonlinear analyses allowed for a comparison of load–displacement curves and the performance of the composite columns. In comparison to the standard steel I profile, the steel profile with the optimal opening shape increased load-carrying capacity by approximately 19% and energy absorption capacity by approximately 24%.
White Atmospheres: Choreographing Racial Materialities in Academic Space
Authors: Spatz Ben
Published: January 2024

This essay offers a critical introduction to the circulation of racial materialities, and especially whiteness, in North American and European academic contexts. It proposes that we can escape from the dominant epistemology of identity as a fixed attribute of individuals without losing the urgent and much-needed analytics of identity as social and material force. In the gap between “identity politics” and a richer critical politics of identity lies the difference between a discursive public sphere of agonistic conflict and one of potentially transformative relationality. Drawing on critical race theory and especially black radical thought, my analysis rejects the reduction of identity to discrete census categories and attempts to situate contemporary scholarly practices in the context of a planetary decolonial movement. If “identity” today is all too frequently dismissed by a methodological whiteness that strictly separates it from materiality, politics, and knowledge, then a dramaturgical or choreographic analytics of race might better address how racial materialities operate both above and below the level of individual bodies, subjects, and citizens. Synthesizing practical insights from artistic research and performing arts with critical theories of race and identity, this essay refers to some of the author’s recent personal experiences at academic events in order to describe and analyze whiteness as a form of social choreography.
Art, Affect, and Enslavement: The Song of the Oxcart in Colonial Dutch Brazil
Authors: Vanhaelen Angela
Published: January 2024

Focusing on a single artwork, Frans Post’s painting called The Oxen Cart of 1638, this article explores what Édouard Glissant calls the emotional apartheid of the plantation system. It argues that the affective evasion of Post’s painting fosters anti-Black racism by denying the full humanity of captive peoples. The painting is read together with Caspar Barlaeus’s contemporary apologia for the leadership of Maurits of Nassau, who was the governor-general of Dutch Brazil and Post’s patron. Focusing on classical and Neostoic understandings of governance and enslavement, the article turns to Paul Alpers’s analysis of the pastoral mode as an art of evasion that justifies the exploitation of rural labourers. It concludes by taking up Saidiya Hartman’s concept of critical fabulation to consider the oppositional views and counter-narratives expressed in the music-making traditions of enslaved people.
Computing Transiting Exoplanet Parameters with 1D Convolutional Neural Networks
Authors: Iglesias Álvarez Santiago , Díez Alonso Enrique , Sánchez Rodríguez María Luisa , Rodríguez Rodríguez Javier , Pérez Fernández Saúl , de Cos Juez Francisco Javier
Published: January 2024

The transit method allows the detection and characterization of planetary systems by analyzing stellar light curves. Convolutional neural networks appear to offer a viable solution for automating these analyses. In this research, two 1D convolutional neural network models, which work with simulated light curves in which transit-like signals were injected, are presented. One model operates on complete light curves and estimates the orbital period, and the other one operates on phase-folded light curves and estimates the semimajor axis of the orbit and the square of the planet-to-star radius ratio. Both models were tested on real data from TESS light curves with confirmed planets to ensure that they are able to work with real data. The results obtained show that 1D CNNs are able to characterize transiting exoplanets from their host star’s detrended light curve and, furthermore, reducing both the required time and computational costs compared with the current detection and characterization algorithms.
Variations in Morpho-Cultural Characteristics and Pathogenicity of Fusarium moniliforme of Bakanae Disease of Rice and Evaluation of In Vitro Growth Suppression Potential of Some Bioagents
Authors: Al Amin Abdullah , Ali Md. Hosen , Islam Md. Morshedul , Chakraborty Shila , Kabir Muhammad Humayun , Khokon Md. Atiqur Rahman
Published: January 2024

Bakanae is one of the important diseases of rice in Bangladesh that causes substantial yield loss every year. We collected thirty isolates of Fusarium spp. from bakanae-infected rice plants from different agroecological zones of Bangladesh and investigated the variations in cultural and morphological characteristics and pathogenicity. Diversity was found in cultural characteristics, viz., colony features, phialide, chlamydospore formation, shape, and size of macro- and microconidia. Three variants of Fusarium species such as F. moniliforme, F. fujikuroi, and F. proliferatum were identified on PDA media based on their cultural and morphological characteristics. Isolate FM10 (F. moniliforme) exhibited the highest disease aggressiveness in developing elongated plants (26.50 cm), the highest number of chlorotic leaves (5.75), and a lower germination percentage. We evaluated different bioagents against the virulent isolate of F. moniliforme to develop a rice bakanae disease management approach. Four bioagents, viz., Trichoderma spp., Bacillus subtilis, Pseudomonas fluorescens, and Achromobacter spp., were evaluated for growth suppression of F. moniliforme. Among the bioagents, Achromobacter spp. and B. subtilis (BS21) showed 73.54% and 71.61% growth suppression, respectively. The investigation revealed that the application of Achromobacter spp. and B. subtilis (BS21) would be a potential candidate for effective and eco-friendly management of the bakanae disease of rice.
Advances and Challenges in Wearable Glaucoma Diagnostics and Therapeutics
Authors: Shean Ryan , Yu Ning , Guntipally Sourish , Nguyen Van , He Ximin , Duan Sidi , Gokoffski Kimberly , Zhu Yangzhi , Xu Benjamin
Published: January 2024

Glaucoma is a leading cause of irreversible blindness, and early detection and treatment are crucial for preventing vision loss. This review aims to provide an overview of current diagnostic and treatment standards, recent medical and technological advances, and current challenges and future outlook for wearable glaucoma diagnostics and therapeutics. Conventional diagnostic techniques, including the rebound tonometer and Goldmann Applanation Tonometer, provide reliable intraocular pressure (IOP) measurement data at single-interval visits. The Sensimed Triggerfish and other emerging contact lenses provide continuous IOP tracking, which can improve diagnostic IOP monitoring for glaucoma. Conventional therapeutic techniques include eye drops and laser therapies, while emerging drug-eluting contact lenses can solve patient noncompliance with eye medications. Theranostic platforms combine diagnostic and therapeutic capabilities into a single device. Advantages of these platforms include real-time monitoring and personalized medication dosing. While there are many challenges to the development of wearable glaucoma diagnostics and therapeutics, wearable technologies hold great potential for enhancing glaucoma management by providing continuous monitoring, improving medication adherence, and reducing the disease burden on patients and healthcare systems. Further research and development of these technologies will be essential to optimizing patient outcomes.
Glycan Modifications as Regulators of Stem Cell Fate
Authors: Alghazali Raghad , Nugud Ahmed , El-Serafi Ahmed
Published: January 2024

Glycosylation is a process where proteins or lipids are modified with glycans. The presence of glycans determines the structure, stability, and localization of glycoproteins, thereby impacting various biological processes, including embryogenesis, intercellular communication, and disease progression. Glycans can influence stem cell behavior by modulating signaling molecules that govern the critical aspects of self-renewal and differentiation. Furthermore, being located at the cell surface, glycans are utilized as markers for stem cell pluripotency and differentiation state determination. This review aims to provide a comprehensive overview of the current literature, focusing on the effect of glycans on stem cells with a reflection on the application of synthetic glycans in directing stem cell differentiation. Additionally, this review will serve as a primer for researchers seeking a deeper understanding of how synthetic glycans can be used to control stem cell differentiation, which may help establish new approaches to guide stem cell differentiation into specific lineages. Ultimately, this knowledge can facilitate the identification of efficient strategies for advancing stem cell-based therapeutic interventions.
An Efficient Homologous Recombination-Based In Situ Protein-Labeling Method in Verticillium dahliae
Authors: Yang Jie , Liu Mengran , Jiao Yue , Guo Hui-Shan , Shan Chun-Min , Wang Haiting
Published: January 2024

Accurate determination of protein localization, levels, or protein−protein interactions is pivotal for the study of their function, and in situ protein labeling via homologous recombination has emerged as a critical tool in many organisms. While this approach has been refined in various model fungi, the study of protein function in most plant pathogens has predominantly relied on ex situ or overexpression manipulations. To dissect the molecular mechanisms of development and infection for Verticillium dahliae, a formidable plant pathogen responsible for vascular wilt diseases, we have established a robust, homologous recombination-based in situ protein labeling strategy in this organism. Utilizing Agrobacterium tumefaciens-mediated transformation (ATMT), this methodology facilitates the precise tagging of specific proteins at their C-termini with epitopes, such as GFP and Flag, within the native context of V. dahliae. We demonstrate the efficacy of our approach through the in situ labeling of VdCf2 and VdDMM2, followed by subsequent confirmation via subcellular localization and protein-level analyses. Our findings confirm the applicability of homologous recombination for in situ protein labeling in V. dahliae and suggest its potential utility across a broad spectrum of filamentous fungi. This labeling method stands to significantly advance the field of functional genomics in plant pathogenic fungi, offering a versatile and powerful tool for the elucidation of protein function.
Integrative Multi-Omics Analysis Identifies Transmembrane p24 Trafficking Protein 1 (TMED1) as a Potential Prognostic Marker in Colorectal Cancer
Authors: Guo Xin , Zhou Wei , Jin Jinmei , Lin Jiayi , Zhang Weidong , Zhang Lijun , Luan Xin
Published: January 2024

Several TMED protein family members are overexpressed in malignant tumors and associated with tumor progression. TMED1 belongs to the TMED protein family and is involved in protein vesicular trafficking. However, the expression level and biological role of TMED1 in colorectal cancer (CRC) have yet to be fully elucidated. In this study, the integration of patient survival and multi-omics data (immunohistochemical staining, transcriptomics, and proteomics) revealed that the highly expressed TMED1 was related to the poor prognosis in CRC. Crystal violet staining indicated the cell growth was reduced after knocking down TMED1. Moreover, the flow cytometry results showed that TMED1 knockdown could increase cell apoptosis. The expression of TMED1 was positively correlated with other TMED family members (TMED2, TMED4, TMED9, and TMED10) in CRC, and the protein–protein interaction network suggested its potential impact on immune regulation. Furthermore, TMED1 expression was positively associated with the infiltration levels of regulatory T cells (Tregs), cancer-associated fibroblasts (CAFs), and endothelial cells and negatively correlated with the infiltration levels of CD4+ T cells, CD8+ T cells, and B cells. At last, the CTRP and GDSC datasets on the GSCA platform were used to analyze the relationship between TMED1 expression and drug sensitivity (IC50). The result found that the elevation of TMED1 was positively correlated with IC50 and implied it could increase the drug resistance of cancer cells. This research revealed that TMED1 is a novel prognostic biomarker in CRC and provided a valuable strategy for analyzing potential therapeutic targets of malignant tumors.
sTREM2 Differentially Affects Cytokine Expression in Myeloid-Derived Cell Models via MAPK–JNK Signaling Pathway
Authors: Arsenault Ryan , Marshall Steven , Salois Patrick , Li Qiao , Zhang Wandong
Published: January 2024

TREM2 is a critical innate immune receptor primarily expressed on myeloid-derived cells, such as microglia and macrophages. Mutations in TREM2 are linked to several neurodegenerative diseases including Alzheimer’s disease (AD). TREM2 can be cleaved from the cell membrane and released as soluble TREM2 (sTREM2). sTREM2 levels are shown to peak prior to AD, with its levels fluctuating throughout disease progression. However, the mechanism by which sTREM2 may affect innate immune responses is largely uncharacterized. In this study, we investigated whether sTREM2 can induce inflammatory response in myeloid-derived THP-1 monocytes and macrophages and characterized the signaling mechanisms involved. Our results show that sTREM2 was capable of stimulating the expression of several inflammatory cytokines in THP-1 cells throughout the time course of 2 h to 8 h but inducing anti-inflammatory cytokine expression at later time points. A TREM2 antibody was capable of inhibiting the expression of some cytokines induced by sTREM2 but enhancing others. The complex of sTREM2/TREM2 antibody was shown to enhance IL-1β expression, which was partially blocked by an NLRP3 specific inhibitor, indicating that the complex activated the NRLP3 inflammasome pathway. sTREM2 was also shown to have differential effects on cytokine expression in M0, M1, and M2 macrophages differentiated from THP-1 cells. sTREM2 has a more stimulating effect on cytokine expression in M0 macrophages, less of an effect on M2 macrophages, and some inhibitory effects on cytokine expression in M1 macrophages at early time points. Analyses of several signaling pathways revealed that sTREM2-induced expression of cytokines occurs mainly through MAPK–JNK signaling. Our work reveals differential effects of sTREM2 on cytokine expression profiles of THP-1 cells and macrophages and demonstrates that the MAPK–JNK signaling pathway is mainly responsible for sTREM2-induced cytokine expression.
Correlation between Polymorphisms of Vitamin D Metabolism Genes and Perianal Disease in Crohn’s Disease
Authors: Cusato Jessica , Cafasso Carla , Antonucci Miriam , Palermiti Alice , Manca Alessandra , Caviglia Gian Paolo , Vernero Marta , Armandi Angelo , Saracco Giorgio Maria , D’Avolio Antonio , Ribaldone Davide Giuseppe
Published: January 2024

Although the role of vitamin D (VD) in the pathogenesis and progression of Crohn’s disease (CD) is known, the association between single-nucleotide polymorphisms (SNPs) of genes linked to vitamin D pathway and CD risk is still under study. Furthermore, no significant association has been previously found between these SNPs and perianal CD (pCD), a severe phenotypic manifestation of CD that may present as perianal fistula, abscess, and recto-vaginal fistula. Among the mechanisms involved in its pathogenesis, local inflammation and intestinal microbiota alteration are recognized. VD seems to act on these elements. The aim of this study was to evaluate the presence of an association between SNPs of genes coding for enzymes, transporters, and receptors involved in the VD pathway and the occurrence of pCD. Blood samples of 206 patients with CD, including 34 with pCD, were analyzed for VDR, CYP27B1, CYP24A1, and GC genetic variants. VDR Apal Aa genotype and VDR BsmI Bb genotype resulted in an association with pCD (p = 0.01 and p = 0.02, respectively). Our study demonstrates for the first time the impact of the polymorphisms of genes associated with the VD pathway on the onset of pCD. Future multicenter studies are needed to confirm these data.
Bioinspired Artificial Intelligence Applications 2023
Authors: Wei Haoran , Tao Fei , Huang Zhenghua , Long Yanhua
Published: January 2024

With rapid development of Artificial Intelligence (AI), researchers have found many bioinspired AI applications, such as bioinspired images and speech processing, which can increase accuracy [...]
Ti3C2Tx MXene-Based Fluorescent Aptasensor for Detection of Dimethoate Pesticide
Authors: Li Zhichao , Pu Hongbin , Wei Qingyi
Published: January 2024

Dimethoate contaminants in food pose a threat to human health. Rapid and sensitive trace detection methods are required to keep food safe. In this study, a novel fluorescent aptasensor was developed for the sensitive detection of dimethoate based on carbon quantum dots labeled with double-stranded DNA (CQDs−apt−cDNA) and Ti3C2Tx flakes. Under optimal conditions, the aptasensor showed a good linear range of 1 × 10−9 to 5 × 10−5 M for dimethoate with a coefficient of determination (R2) of 0.996. Besides, a low detection limit of 2.18 × 10−10 M was obtained. The aptasensor showed high selectivity in interference samples and good reproducibility with an RSD of 3.06% (<5%) for dimethoate detection. Furthermore, the proposed aptasensor was applied to the detection of dimethoate in apple juice and tap water with satisfactory recoveries from 96.2 to 104.4%. Because of these benefits, this aptasensor has the potential and promise for detecting food contaminants in the food industry.
The Interplay of Anxiety, Depression, Sleep Quality, and Socioeconomic Factors in Somali Hemodialysis Patients
Authors: Kose Samet , Mohamed Nur Adam
Published: January 2024

Objective: This study aimed to assess anxiety, depression, and sleep quality in kidney failure patients receiving hemodialysis (HD) in Somalia and examine the relationship between anxiety, depression, and sleep quality. Methods: We conducted a study with 200 kidney failure patients on HD treatment for over 3 months. Participants completed sociodemographic questionnaires, the Patient Health Questionnaire-9 (PHQ-9), the Hospital Anxiety and Depression Scale (HADS), the Insomnia Severity Index (ISI), and the Pittsburgh Sleep Quality Index (PSQI). Results: Among the 200 participants (mean age = 52.3; SD = 14.13), 58.5% were men, 64% had CKD for 1–5 years, and 52.6% received HD for 1–5 years. Depressive symptoms were found in 61.5% (PHQ-9) and 37.5% (HADS depression subscale) of HD patients. Poor sleep quality (PSQI) was observed in 31.5% and significantly correlated with PHQ-9 (rs = 0.633), HADS anxiety (rs = 0.491), and HADS depression (rs = 0.529). The ISI score correlated significantly with PHQ-9 (rs = 0.611), HADS anxiety (rs = 0.494), and HADS depression (rs = 0.586). All PSQI components correlated with depression and anxiety, except sleep medication use. Hierarchical regression analysis revealed that HADS anxiety (β = 0.342) and HADS depression (β = 0.372) predicted ISI scores. HADS anxiety (β = 0.307) and HADS depression (β = 0.419) predicted PSQI scores. Conclusions: Higher anxiety and depression levels negatively correlated with various dimensions of sleep quality in kidney failure patients. Early identification and appropriate management of these psychological disturbances are crucial for enhancing patients’ overall quality of life.
Association between Shift Work and Health Outcomes in the General Population in China: A Cross-Sectional Study
Authors: Gao Nan , Zheng Yongbo , Yang Yingbo , Huang Yuetong , Wang Sanwang , Gong Yimiao , Zeng Na , Ni Shuyu , Wu Shuilin , Su Sizhen , Zhang Zhibo , Yuan Kai , Shi Le , Zhang Zhaohui , Yan Wei , Lu Lin , Bao Yanping
Published: January 2024

Shift work may adversely affect individuals’ health, thus, the current study aimed to investigate the association between shift work and health outcomes in the general population. A total of 41,061 participants were included in this online cross-sectional survey, among which 9612 (23.4%) individuals engaged in shift work and 31,449 (76.6%) individuals engaged in non-shift work. Multiple logistic regression analyses were conducted to explore the association between shift work and health outcomes (psychiatric disorders, mental health symptoms, and physical disorders). In addition, associations between the duration (≤1 year, 1–3 years, 3–5 years, 5–10 years, ≥10 years) and frequency of shift work (<1 or ≥1 night/week) and health outcomes were also explored. The results showed that compared to non-shift workers, shift workers had a higher likelihood of any psychiatric disorders (odds ratios [OR] = 1.80, 95% CI = 1.56–2.09, p < 0.001), mental health symptoms (OR = 1.76, 95% CI = 1.68–1.85, p < 0.001), and physical disorders (OR = 1.48, 95% CI = 1.39–1.57, p < 0.001). In addition, inverted U-shaped associations were observed between the duration of shift work and health outcomes. These results indicated that shift work was closely related to potential links with poor health outcomes. The findings highlighted the importance of paying attention to the health conditions of shift workers and the necessity of implementing comprehensive protective measures for shift workers to reduce the impact of shift work.
Extensive Visual Training in Adulthood Reduces an Implicit Neural Marker of the Face Inversion Effect
Authors: Hagen Simen , Laguesse Renaud , Rossion Bruno
Published: January 2024

Face identity recognition (FIR) in humans is supported by specialized neural processes whose function is spectacularly impaired when simply turning a face upside-down: the face inversion effect (FIE). While the FIE appears to have a slow developmental course, little is known about the plasticity of the neural processes involved in this effect—and in FIR in general—at adulthood. Here, we investigate whether extensive training (2 weeks, ~16 h) in young human adults discriminating a large set of unfamiliar inverted faces can reduce an implicit neural marker of the FIE for a set of entirely novel faces. In all, 28 adult observers were trained to individuate 30 inverted face identities presented under different depth-rotated views. Following training, we replicate previous behavioral reports of a significant reduction (56% relative accuracy rate) in the behavioral FIE as measured with a challenging four-alternative delayed-match-to-sample task for individual faces across depth-rotated views. Most importantly, using EEG together with a validated frequency tagging approach to isolate a neural index of FIR, we observe the same substantial (56%) reduction in the neural FIE at the expected occipito-temporal channels. The reduction in the neural FIE correlates with the reduction in the behavioral FIE at the individual participant level. Overall, we provide novel evidence suggesting a substantial degree of plasticity in processes that are key for face identity recognition in the adult human brain.
Strength Use and Well-Being at Work among Teachers: The Mediating Role of Basic Need Satisfaction
Authors: Wei Cangpi , Su Jiahe , Zhao Jingjing , Ding Ke , Kong Feng
Published: January 2024

Teachers’ well-being at work is an important indicator of their mental health. Strengths use has been identified as a significant predictor of enhanced well-being at work. However, there is a scarcity of studies that have examined the connection between teachers’ strengths use and well-being at work; thus, its underlying psychological mechanism is unclear. Therefore, this study aimed to explore the association between teachers’ strengths and well-being at work together with the mediating role of basic need satisfaction. A total of 374 university teachers completed a series of questionnaires on strengths use, basic need satisfaction, hedonic well-being, and eudaimonic well-being. The results showed that there were positive correlations between strength use and both types of well-being at work. Moreover, basic need satisfaction mediated the association between strength use and two types of well-being at work. The findings suggest that institutions should prioritize enhancing teachers’ ability to utilize their strengths and foster an environment conducive to such practices, thereby improving their workplace well-being.
Family Metacognitive Training (MCT-F): Adapting MCT to Mothers with Psychosis and Their Adolescent Children
Authors: Espinosa Victoria , Arin-González Paula , Jiménez-Lafuente Alba , Pardo Nerea , López-Carrilero Raquel , Birulés Irene , Barajas Ana , Pélaez Trinidad , Díaz-Cutraro Luciana , Verdaguer-Rodríguez Marina , Gutiérrez-Zotes Alfonso , Palma-Sevillano Carolina , Varela-Casals Paloma , Salas-Sender Miriam , Aznar Ana , Ayesa-Arriola Rosa , Pousa Esther , Canal-Rivero Manuel , Garrido-Torres Nathalia , Montserrat Clara , Muñoz-Lorenzo Laura , Crosas Josep Maria , Ochoa Susana
Published: January 2024

Over half of women with psychosis are mothers. Research suggests that mothers with psychosis face unique challenges affecting both their mental health prognosis and their relationship with their children. Moreover, those children have a higher risk of developing a mental disorder. Notwithstanding, interventions specifically tailored to these families remain largely uncovered. Metacognitive Training (MCT) has demonstrated its efficacy in improving cognitive insight, symptom management, and social cognition in people with psychosis. However, there is no evidence of the efficacy of MCT in a family setting (MCT-F). This study describes the first adaptation of MCT for mothers with psychosis and their adolescent children in an online group setting. The phases (assessment, decision, adaptation, production, topical experts’ integration) of the ADAPT-ITT model were systematically applied through a participatory approach (n = 22), including a first-person perspective and involving qualitative (e.g., topical expert literature review and consensus groups, interviews, thematic analyses) and quantitative methods. While MCT’s core components were retained, participants guided adaptations both in content and delivery. The findings suggest the importance of community engagement and sharing decision-making processes to demonstrate the acceptability and feasibility of the adapted intervention. Employing a structured approach such as the ADAPT-ITT model ensures readiness of the new training for efficacy trials.