bluuebunny/crossref_metadata_2025 huggingface dataset:
Selenium Deficiency Exacerbates Hyperoxia-Induced Lung Injury in Newborn C3H/HeN Mice
Authors: Bailey-Downs Lora C. , Sherlock Laura G. , Crossley Michaela N. , Rivera Negron Aristides , Pierce Paul T. , Wang Shirley , Zhong Hua , Carter Cynthia , Burge Kathryn , Eckert Jeffrey V. , Rogers Lynette K. , Vitiello Peter F. , Tipple Trent E.
Published: March 2024

Extremely preterm infants are often treated with supraphysiological oxygen, which contributes to the development of bronchopulmonary dysplasia (BPD). These same infants exhibit compromised antioxidant capacities due in part to selenium (Se) deficiency. Se is essential for basal and inducible antioxidant responses. The present study utilized a perinatal Se deficiency (SeD) mouse model to identify the combined effects of newborn hyperoxia exposure and SeD on alveolarization and antioxidant responses, including the identification of affected developmental pathways. Se-sufficient (SeS) and SeD C3H/HeN breeding pairs were generated, and pups were exposed to room air or 85% O2 from birth to 14 d. Survival, antioxidant protein expression, and RNA seq analyses were performed. Greater than 40% mortality was observed in hyperoxia-exposed SeD pups. Surviving SeD pups had greater lung growth deficits than hyperoxia-exposed SeS pups. Gpx2 and 4 protein and Gpx activity were significantly decreased in SeD pups. Nrf2-regulated proteins, Nqo1 and Gclc were increased in SeD pups exposed to hyperoxia. RNA seq revealed significant decreases in the Wnt/β-catenin and Notch pathways. Se is a biologically relevant modulator of perinatal lung development and antioxidant responses, especially in the context of hyperoxia exposure. The RNA seq analyses suggest pathways essential for normal lung development are dysregulated by Se deficiency.
Exploring the Antioxidative Effects of Ginger and Cinnamon: A Comprehensive Review of Evidence and Molecular Mechanisms Involved in Polycystic Ovary Syndrome (PCOS) and Other Oxidative Stress-Related Disorders
Authors: Novakovic Sladjana , Jakovljevic Vladimir , Jovic Nikola , Andric Kristina , Milinkovic Milica , Anicic Teodora , Pindovic Bozidar , Kareva Elena Nikolaevna , Fisenko Vladimir Petrovich , Dimitrijevic Aleksandra , Joksimovic Jovic Jovana
Published: March 2024

Oxidative stress represents the pathophysiological basis for most disorders, including reproductive issues. Polycystic ovary syndrome (PCOS) is heterogeneous endocrine disorder of women characterized primarily by irregular menstrual cycles, hyper-androgenism, and ovulatory dysfunction. In the last decades, PCOS was recognized as a systemic silent inflammation and an oxidative disturbance-related disorder, exerting multifaceted symptoms, including metabolic. PCOS treatment should involve a personalized approach tailored to individual symptoms; however, the results are often unsatisfactory. Various supplementary treatments have been proposed to assist in the management and alleviation of PCOS symptoms. Cinnamon and ginger, known for millennia as herbs used in spices or traditional medicine for the treatment of various diseases, are of interest in this study. The aim of this study is to evaluate and investigate the effects of cinnamon and ginger in PCOS patients. Using relevant keywords we searched through PubMed/MEDLINE, Science Direct, Google Scholar and Web of science to find animal studies, pre-clinical, and clinical studies which were then reviewed for usage. Out of all of the reviewed studies a total of 65 studies were included in this review article. Cinnamon and ginger can affect hormonal status, lipid profile, obesity, and insulin resistance by mitigating oxidative stress and inflammation. Generally, based on current clinical evidence, it was revealed that supplementation with cinnamon or ginger had a useful impact in patients with PCOS. This review summarizes the antioxidative effects of ginger and cinnamon in PCOS treatment, highlighting their potential benefits in other oxidative stress-related pathologies.
Critical Steps and Conditions to Be Included in a Business Model in Logistics, Seeking Competitive Advantage from the Perspective of the Modern Digital Age and Industry 4.0
Authors: Tsarouhas Panagiotis , Papaevangelou Nikolaos
Published: March 2024

The main purpose of this study is to research the literature and examine how logistics companies can effectively integrate modern digital technologies of Industry 4.0 internally and then present the most critical steps and conditions that determine the successful operation of an innovative business model in logistics, as well as the expected benefits of this process. This study was written entirely as a literature review. Four steps of literature review research were completed: (a) initial formulation of the problem, (b) search of literature sources, (c) selection and evaluation of articles, and d) final classification and presentation of data. The results show that the most critical steps and conditions that contribute to the successful adoption of new Industry 4.0 technologies in the business models of logistics companies are Business Model Innovation, Digital Transformation, Quality 4.0, Human Resource Management, and Logistics 4.0. These critical prerequisites and Industry 4.0 architecture are now at the forefront of logistics, proving the key role they play in modernizing a business and gaining competitive advantage, and to fully reap these benefits, businesses must be prepared to adapt their organizational culture, embrace change, and invest in the necessary resources.
Environmental Interference Suppression by Hybrid Segmentation Algorithm for Open-Area Electromagnetic Capability Testing
Authors: Yang Shun , Chen Shuai , Zhang Fan , Yang Xiaqing , Shi Jun , Zhang Xiaoling
Published: March 2024

Compared with electromagnetic compatibility (EMC) testing in anechoic rooms, open-area EMC testing takes advantage of in situ and engine running status measurement but suffers from non-negligible external electromagnetic interference. This paper proposes a novel environmental interference suppression method (named the EMC environmental interference suppression algorithm (E2ISA)) that separates signals from backgrounds via image segmentation and recognizes the near–far site signal via a group of time-varying features based on the difference in the near-site EM radiative characteristic. We find that the proposed E2ISA method, which combines the deep learning segmentation network with the classical recognition methods, is able to suppress environmental interference signals accurately. The experiment results show that the accuracy of E2ISA reaches up to 95% in the face of VHF (Very High Frequency) EMC testing tasks.
A New Surrogate Safety Measure Considering Temporal–Spatial Proximity and Severity of Potential Collisions
Authors: Tang Shuning , Lu Yichen , Liao Yankun , Cheng Kai , Zou Yajie
Published: March 2024

Accurate identification and analysis of traffic conflicts through surrogate safety measures (SSMs) are crucial for safety evaluation in road systems. Existing SSMs for conflict identification and analysis mostly consider the temporal–spatial proximity of conflicts without taking into account the severity of potential collisions. This makes SSMs unsuitable for traffic safety evaluation in complex road environments. In order to address the shortcomings above, this study first introduces a new SSM called the Potential Conflict Risk Index (PCRI). To validate the effectiveness of PCRI, the inD dataset is adopted for conflict identification comparison between time-to-collision (TTC) and PCRI. Using PCRI, this study conducts a conflict analysis in the freeway merging areas based on the data from the Outer Ring Expressway Dataset (ORED), accounting for differences between cars and trucks. The comparative results between TTC and PCRI show that PCRI can provide a more comprehensive identification of conflicts and a more accurate identification of the moment with the highest conflict risk. The results of conflict analysis suggest that conflicts occur more frequently in situations involving trucks, and these conflicts commonly occur in closer proximity to the on-ramp at freeway merging areas. The findings from this study can improve the accuracy of conflict identification under different conflict patterns, enhancing the specificity of traffic safety measures and ultimately ensuring the safety of road systems.
Effects of Temperature and Salinity on the LMS (Lysosomal Membrane Stability) Biomarker in Clams Donax trunculus and Chamelea gallina
Authors: Soms-Molina Paula , Martínez-Gómez Concepción , Zuñiga Esther , Rodilla Miguel , Falco Silvia
Published: March 2024

Population of clams Donax trunculus and Chamelea gallina have been declining significantly in recent decades, and environmental pollution and accelerated global warming have been proposed as contributing factors to this decline, in addition to overfishing. Lysosomal membrane stability (LMS) is a sensitive indicator of health status of the organisms. In this study, we investigate the LMS in these species after exposure for 21 days to nine combined conditions of water temperature (12, 20, and 27.5 °C) and salinity ranges (27–28, 32–33, and 37–38). LMS was assessed in living hemocytes by using the neutral red retention assay. Mortality and the condition index of the organisms were evaluated as supporting parameters. The results indicated interspecies differences in the LMS under similar environmental conditions. Overall, LMS was found to be more sensitive to temperature than to salinity changes. Although both species can tolerate changes in either salinity or temperature seawater conditions, the tolerance range is narrower for D. trunculus, showing a significant cytotoxicity (NRRT < 50 min) at temperatures above 27.5 °C and salinities above 32, and 100% mortality at 27.5 °C and a low salinity range (27–28). This study is the first to assess the combined effect of temperature and salinity on the LMS in C. gallina and D. trunculus, and provide necessary information before using LMS as contaminant-related biomarker in field studies with these species.
Multi-Frequency GPR Data Fusion through a Joint Sliding Window and Wavelet Transform-Weighting Method for Top-Coal Structure Detection
Authors: Guan Zenglun , Liu Wanli
Published: March 2024

Top-coal structure detection is an important basis for realizing effective mining in fully mechanized cave faces. However, the top-coal structure is very complex and often contains multi-layer gangues, which seriously influence the level of effective mining. For these reasons, this paper proposes a novel multi-frequency ground-penetrating radar (GPR) data-fusing method through a joint sliding window and wavelet transform weighting method to accurately detect the top-coal structure. It possesses the advantages of both high resolution and great detection depth, and it can also integrate multi-frequency GPR data into one composite profile to interpret the internal structure information of top coal in detail. The detection procedure is implemented following several steps: First of all, the multi-frequency GPR data are preprocessed and aligned through a band-pass filter and a zero offset elimination method to establish their spatial correspondences. Secondly, the proposed method is used to determine the time-varying weight values of each frequency GPR signal according to the wavelet energy proportion within the sliding window; also, the edge detection algorithm is introduced to improve the fusion efficiency of the wavelet transform so as to realize the effective fusion of the multi-frequency GPR data. Thirdly, a reflection intensity model of multi-frequency GPR signals traveling in the top-coal is established by using the stratified identification method, and then, the detailed top-coal structure can be inversely interpreted. Finally, the quantitative evaluation criteria, information entropy (IE), space–frequency (SF) and Laplacian gradient (LG), are used to evaluate the multi-frequency GPR data fusion’s effectiveness in laboratory and field environments. The experimental results show that, compared with the genetic, time-varying and wavelet transform fusion method, the fusion performance of the presented method possesses higher values in the IE, SF and LG evaluation criteria, and it also has both the merits of high resolution and great detection depth.
Characteristics of Perimeter Rock Damage in a Bottom-Pumping Roadway under the Influence of Mining Activities and Rational Location Studies: A Case Study
Authors: Bai Libin , Wu Fengfeng , Yang Peiju , Zhang Shurong , Li Bin
Published: March 2024

With the aim of determining the damage characteristics and a reasonable positional arrangement of the surrounding rock in a bottom-pumping roadway influenced by mining in a high-gas mine, the boundary equation for the plastic zone of the surrounding rock in a circular roadway under an unequal compressive stress field was adopted to analyze the relationship between the distribution characteristics of the plastic zone of the bottom-pumping roadway and the stability of the rock surrounding the bottom-pumping roadway under different bidirectional stress ratios. This was carried out in the bottom-pumping roadway of the working face of Licun coal mine 3301 as the engineering background, where the nature of the coal seams mined is bituminous coal, and the absolute gas outflow is 0.5 m3/min−1. A numerical simulation was used to analyze the distribution characteristics of the surrounding rock stress and the bidirectional stress ratio, as well as the deformation and damage characteristics of the surrounding rock at different positions in the bottom-pumping roadway. A numerical simulation was applied to analyze the distribution characteristics of the surrounding rock stress and the two-way stress ratio, as well as the deformation and damage characteristics of the rock surrounding the bottom-pumping roadway when the bottom-pumping roadway was arranged in different locations. The results show that, with an increase in the bidirectional stress ratio, the plastic zone of the perimeter rock in the bottom-pumping roadway shows nonuniform “butterfly” distribution characteristics, which seriously affects the stability of the rock on the perimeter of the roadway; the stress on the bottom plate of the working face after excavation can be divided into four areas according to the size of the bidirectional stress ratio and the stress loading and unloading states. In addition, the size of the perimeter rock deformation can be sorted into four areas according to the damage range of the perimeter of the rock plastic zone in the bottom-pumping roadway. The size of the deformation in the surrounding rock can be sorted as follows: unpressurized high-stress ratio > unpressurized stress ratio stable area > pressurized low-stress ratio area > original rock stress ratio area. Accordingly, we found that the reasonable location of the bottom-pumping roadway is arranged at the 15 m position outside the hollow area below the coal pillar, along the limestone upper medium-grained sandstone layer along the bottom. The study’s results were applied to the field. The industrial experiments on the site show that the deformation of the surrounding rock is reasonable when the bottom-pumping roadway is dug along the limestone roof and arranged 15 m outside the fault of the mining hollow area below the coal pillar.
Phytomicrobiomes: A Potential Approach for Sustainable Pesticide Biodegradation
Authors: Salam Md. Tareq Bin , Mahmood Ahmad , Asghar Waleed , Ito Koji , Kataoka Ryota
Published: March 2024

Globally, pest-induced crop losses ranging from 20% to 40% have spurred the extensive use of pesticides, presenting a double-edged sword that threatens not only human health but also our environment. Amidst various remediation techniques, bioremediation stands out as a compelling and eco-friendly solution. Recently, the phytomicrobiome has garnered increasing attention as endophytic microbes, colonizing plants from their roots, not only foster plant growth but also enhance the host plant’s resilience to adverse conditions. Given the persistent demand for high crop yields, agricultural soils often bear the burden of pesticide applications. Biodegradation, the transformation of complex pesticide compounds into simpler forms through the activation of microbial processes and plant-based enzymatic systems, emerges as a pivotal strategy for restoring soil health. Manipulating the phytomicrobiome may emerge as a viable solution for this purpose, offering a native metabolic pathway that catalyzes pollutant degradation through enzymatic reactions. This review delves into the pivotal role of phytomicrobiomes in the degradation of diverse pesticides in soil. It explores contemporary innovations and paves the way for discussions on future research directions in this promising field.
Automatic Medical Image Segmentation with Vision Transformer
Authors: Zhang Jie , Li Fan , Zhang Xin , Wang Huaijun , Hei Xinhong
Published: March 2024

Automatic image segmentation is vital for the computer-aided determination of treatment directions, particularly in terms of labelling lesions or infected areas. However, the manual labelling of disease regions is inconsistent and a time-consuming assignment. Meanwhile, radiologists’ comments are exceedingly subjective, regularly impacted by personal clinical encounters. To address these issues, we proposed a transformer learning strategy to automatically recognize infected areas in medical images. We firstly utilize a parallel partial decoder to aggregate high-level features and then generate a global feature map. Explicit edge attention and implicit reverse attention are applied to demonstrate boundaries and enhance their expression. Additionally, to alleviate the need for extensive labeled data, we propose a segmentation network combining propagation and transformer architectures that requires only a small amount of labeled data while leveraging fundamentally unlabeled images. The attention mechanisms are integrated within convolutional networks, keeping their global structures intact. Standalone transformers connected straightforwardly and receiving image patches can also achieve impressive segmentation performance. Our network enhanced the learning ability and attained a higher quality execution. We conducted a variety of ablation studies to demonstrate the adequacy of each modelling component. Experiments conducted across various medical imaging modalities illustrate that our model beats the most popular segmentation models. The comprehensive results also show that our transformer architecture surpasses established frameworks in accuracy while better preserving the natural variations in anatomy. Both quantitatively and qualitatively, our model achieves a higher overlap with ground truth segmentations and improved boundary adhesion.
Active Faults, Kinematics, and Seismotectonic Evolution during Tajogaite Eruption 2021 (La Palma, Canary Islands, Spain)
Authors: Rodríguez-Pascua Miguel Ángel , Perez-Lopez Raúl , Perucha María Ángeles , Sánchez Nieves , López-Gutierrez Julio , Mediato José F. , Sanz-Mangas David , Lozano Gonzalo , Galindo Inés , García-Davalillo Juan Carlos , Lorenzo Carnicero Carlos , Béjar Marta
Published: March 2024

During the 2021 La Palma strombolian and fissure eruption, two faults were identified that controlled the spatial distribution of earthquake hypocenters and effusive eruptive vents. One of these faults has a NW-SE trend (Tazacorte Fault: TZF) and the other one shows an ENE-WSW trend (Mazo Fault: MZF). Previous works on fault structural analysis in La Palma indicated that the eruption zone was compatible with an extensional tectonic strain ellipsoid which activated normal-strike-slip directional faults at the confluence of TZF and MZF. These fractures were activated during the 2021 Tajogaite eruption, determining the NW-SE and WSW-ENE spatial distribution of vents. Both faults were mapped in real time during the volcanic eruption from fieldwork and remote sensing imagery (aerial drone images). We have collected more than 300 fracture data associated with the effusive vents and post-eruption seismic creep. Since the affected area was densely inhabited, most of these fractures affect houses and infrastructures. Some of the houses affected by the TZF were damaged 9 months after the eruption, although they were not damaged during the eruption. Surprisingly, these houses already had repairs made to the same fractures since 1980, giving information of previous fault creep movement. During the 2021 Tajogaite eruption, shallow seismicity was spatially related to both faults, suggesting a seismic behavior instead of the precedent creep movement. However, the lack of seismicity after the eruption indicates that the faults went back to creep aseismic behavior, similarly to 1980. The mapping and monitoring of these faults (TZF and MZF) is relevant bearing in mind that they have been active since 1980 and the post-eruptive phase of the 2021 volcanic eruption, which has to be included in the land use planning in areas affected by the volcanic eruption and creep movement. Furthermore, both faults could act as seismogenic sources triggering volcanic earthquakes with potential high macroseismic intensities and mass movements. The data presented here show the importance of having this type of study before the onset of the eruption, thus allowing a better interpretation of seismic data during volcanic unrest.
Analysing and Computing the Impact of Geometric Asymmetric Coils on Transformer Stray Losses
Authors: Hernandez-Robles Ivan A. , Gonzalez-Ramirez Xiomara , Olivares-Galvan Juan C. , Escarela-Perez Rafael , Ocon-Valdez Rodrigo
Published: March 2024

Designing and manufacturing transformers often involves variations in heights and thicknesses of windings. However, such geometric asymmetry introduces a significant impact on the magnitude of stray transformer losses. This study examines the effects of asymmetric coils on the generation of stray losses within core clamps and transformer tank walls. A model has been introduced to ascertain the dispersion magnetic field’s value at a specific distance from the coil. The analysis extends to characterising the dispersion magnetic field reaching the tank walls by using electromagnetic simulation by a finite element method. It explores strategies to diminish stray losses, including the placement of magnetic shunts as protective shields for the tank walls. It delves into the efficacy of employing a transformer shell-type configuration to mitigate the magnetic dispersion field. The findings revealed that achieving greater symmetry in transformer coils can minimise stray losses. Specifically, the incorporation of magnetic shunts has the potential to reduce additional losses by 40%, while the adoption of a shell-type configuration alone can lead to a 14% reduction. This work provides valuable insights into optimising transformer designs, contributes a user-friendly tool for estimating additional tank losses, thereby enhancing the knowledge base for transformer manufacturers.
Finite and Symmetric Euler Sums and Finite and Symmetric (Alternating) Multiple T-Values
Authors: Zhao Jianqiang
Published: March 2024

In this paper, we will study finite multiple T-values (MTVs) and their alternating versions, which are level two and level four variations of finite multiple zeta values, respectively. We will first provide some structural results for level two finite multiple zeta values (i.e., finite Euler sums) for small weights, guided by the author’s previous conjecture that the finite Euler sum space of weight, w, is isomorphic to a quotient Euler sum space of weight, w. Then, by utilizing some well-known properties of the classical alternating MTVs, we will derive a few important Q-linear relations among the finite alternating MTVs, including the reversal, linear shuffle, and sum relations. We then compute the upper bound for the dimension of the Q-span of finite (alternating) MTVs for some small weights by rigorously using the newly discovered relations, numerically aided by computers.
Cross Curvature Solitons of Lorentzian Three-Dimensional Lie Groups
Authors: Azami Shahroud , Jafari Mehdi , Haseeb Abdul , Ahmadini Abdullah Ali H.
Published: March 2024

In this paper, we study left-invariant cross curvature solitons on Lorentzian three-dimensional Lie groups and classify these solitons.
Analysis of Tandem Queue with Multi-Server Stages and Group Service at the Second Stage
Authors: Dudin Sergei A. , Dudina Olga S. , Dudin Alexander N.
Published: March 2024

In this paper, we consider a tandem dual queuing system consisting of multi-server stages. Stage 1 is characterized by an infinite buffer, one-by-one service of customers, and an exponential distribution of service times. Stage 2 is characterized by a finite buffer and a phase-type distribution of service times. Service at Stage 2 is provided to groups of customers. The service time of a group depends on the size of the group. The size is restricted by two thresholds. The waiting time of a customer at each stage is limited by a random variable with an exponential distribution, with the parameter depending on the stage. After service at Stage 1, a customer can depart from the system or try to enter Stage 2. If the buffer at this stage is full, the customer is either lost or returns for service at Stage 1. Customer arrivals are described by the versatile Markov arrival process. The system is studied via consideration of a multi-dimensional continuous-time Markov chain. Numerical examples, which highlight the influence of the thresholds on the system performance measures, are presented. The possibility of solving optimization problems is illustrated.
On the Conjecture over Dimensions of Associated Lie Algebra to the Isolated Singularities
Authors: Hussain Naveed , Al-Kenani Ahmad N. , Asif Muhammad
Published: March 2024

Lie algebra plays an important role in the study of singularity theory and other fields of sciences. Finding numerous invariants linked with isolated singularities has always been a primary interest in the field of classification theory of isolated singularities. Any Lie algebra that characterizes simple singularity produces a natural question. The study of properties such as to find the dimensions of newly defined algebra is a remarkable work. Hussain, Yau and Zuo have found a new class of Lie algebra Lk(V), k≥1, i.e., Der (Mk(V),Mk(V)) and proposed a conjecture over its dimension δk(V) for k≥0. Later, they proved it true for k up to k=1,2,3,4,5. In this work, the main concern is whether it is true for a higher value of k. According to this, we first calculate the dimension of Lie algebra Lk(V) for k=6 and then compute the upper estimate conjecture of fewnomial isolated singularities. Additionally, we also justify the inequality conjecture δk+1(V)<δk(V) for k=6. Our calculated results are innovative and serve as a new addition to the study of singularity theory.
Radial Basis Function–Finite Difference Solution Combined with Level-Set Embedded Boundary Method for Improving a Diffusive Logistic Model with a Free Boundary
Authors: Zhang Chunyan , Qiao Yuanyang
Published: March 2024

In this paper, we propose an efficient numerical method to solve the problems of diffusive logistic models with free boundaries, which are often used to simulate the spreading of new or invasive species. The boundary movement is tracked by the level-set method, where the Hamilton–Jacobi weighted essentially nonoscillatory (HJ-WENO) scheme is utilized to capture the boundary curve embedded by the Cartesian grids via the embedded boundary method. Then the radial basis function–finite difference (RBF-FD) method is adopted for spatial discretization and the implicit–explicit (IMEX) scheme is considered for time integration. A variety of numerical examples are utilized to demonstrate the evolution of the diffusive logistic model with different initial boundaries.
Influence of Mutations and N-Glycosylation Sites in the Receptor-Binding Domain (RBD) and the Membrane Protein of SARS-CoV-2 Variants of Concern on Antibody Binding in ELISA
Authors: Schwarze Mandy , Volke Daniela , Rojas Echeverri Juan Camilo , Schick Robin , Lakowa Nicole , Grünewald Thomas , Wolf Johannes , Borte Stephan , Scholz Markus , Krizsan Andor , Hoffmann Ralf
Published: March 2024

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can infect human cells by first attaching to the ACE-2 receptor via its receptor-binding domain (RBD) in the spike protein. Here, we report the influence of N-glycosylation sites of the RBD and the membrane (M) protein on IgG antibody binding in serum samples from patients infected with the original SARS-CoV-2 strain in Germany. The RBDs of the wildtype, alpha, beta, gamma, and kappa variants expressed in HEK293S GnTI− cells were all N-glycosylated at Asn331, Asn334, Asn343, and Asn360 or Asn370, whereas the M-protein was glycosylated at Asn5. An ELISA using a coated RBD and probed with anti-RBD IgG antibodies gave a sensitivity of 96.3% and a specificity of 100% for the wildtype RBD, while the sensitivity decreased by 5% to 10% for the variants of concern, essentially in the order of appearance. Deglycosylation of the wildtype RBD strongly reduced antibody recognition by ~20%, considering the mean of the absorbances recorded for the ELISA. This effect was even stronger for the unglycosylated RBD expressed in Escherichia coli, suggesting structural changes affecting epitope recognition. Interestingly, the N-glycosylated M-protein expressed in HEK293S GnTI− cells gave good sensitivity (95%), which also decreased to 65% after deglycosylation, and selectivity (100%). In conclusion, N-glycosylation of the M-protein, the RBD, and most likely the spike protein are important for proper antibody binding and immunological assays, whereas the type of N-glycosylation is less relevant.
Enhanced TfR1 Recognition of Myocardial Injury after Acute Myocardial Infarction with Cardiac Fibrosis via Pre-Degrading Excess Fibrotic Collagen
Authors: Yang Wenwen , Wang Yueqi , Li Hongzheng , Liao Feifei , Peng Yuxuan , Lu Aimei , Tan Ling , Qu Hua , Long Linzi , Fu Changgeng
Published: March 2024

The fibrosis process after myocardial infarction (MI) results in a decline in cardiac function due to fibrotic collagen deposition and contrast agents’ metabolic disorders, posing a significant challenge to conventional imaging strategies in making heart damage clear in the fibrosis microenvironment. To address this issue, we developed an imaging strategy. Specifically, we pretreated myocardial fibrotic collagen with collagenase I combined with human serum albumin (HSA-C) and subsequently visualized the site of cardiac injury by near-infrared (NIR) fluorescence imaging using an optical contrast agent (CI, CRT-indocyanine green) targeting transferrin receptor 1 peptides (CRT). The key point of this strategy is that pretreatment with HSA-C can reduce background signal interference in the fibrotic tissue while enhancing CI uptake at the heart lesion site, making the boundary between the injured heart tissue and the normal myocardium clearer. Our results showed that compared to that in the untargeted group, the normalized fluorescence intensity of cardiac damage detected by NIR in the targeted group increased 1.28-fold. The normalized fluorescence intensity increased 1.21-fold in the pretreatment group of the targeted groups. These data demonstrate the feasibility of applying pretreated fibrotic collagen and NIR contrast agents targeting TfR1 to identify ferroptosis at sites of cardiac injury, and its clinical value in the management of patients with MI needs further study.
Infectious Keratitis: Characterization of Microbial Diversity through Species Richness and Shannon Diversity Index
Authors: Schiano-Lomoriello Domenico , Abicca Irene , Contento Laura , Gabrielli Federico , Alfonsi Cinzia , Di Pietro Fabio , Papa Filomena Tiziana , Ballesteros-Sánchez Antonio , Sánchez-González José-María , Rocha-De-Lossada Carlos , Mazzotta Cosimo , Giannaccare Giuseppe , Bonzano Chiara , Borroni Davide
Published: March 2024

Purpose: To characterize microbial keratitis diversity utilizing species richness and Shannon Diversity Index. Methods: Corneal impression membrane was used to collect samples. All swabs were processed and analyzed by Biolab Laboratory (level V—SSN Excellence: ISO 9001:2015), Biolab Srl (Ascoli Piceno, Italy). DNA extraction, library preparation, and sequencing were performed in all samples. After sequencing, low-quality and polyclonal sequences were filtered out by the Ion software. At this point, we employed Kraken2 for microbial community analysis in keratitis samples. Nuclease-free water and all the reagents included in the experiment were used as a negative control. The primary outcome was the reduction in bacterial DNA (microbial load) at T1, expressed as a percentage of the baseline value (T0). Richness and Shannon alpha diversity metrics, along with Bray–Curtis beta diversity values, were calculated using the phyloseq package in R. Principal coordinate analysis was also conducted to interpret these metrics. Results: 19 samples were included in the study. The results exhibited a motley species richness, with the highest recorded value surpassing 800 species. Most of the samples displayed richness values ranging broadly from under 200 to around 600, indicating considerable variability in species count among the keratitis samples. Conclusions: A significant presence of both typical and atypical bacterial phyla in keratitis infections, underlining the complexity of the disease’s microbial etiology.
Using the Traditional Ex Vivo Whole Blood Model to Discriminate Bacteria by Their Inducible Host Responses
Authors: Chick Heather M. , Rees Megan E. , Lewis Matthew L. , Williams Lisa K. , Bodger Owen , Harris Llinos G. , Rushton Steven , Wilkinson Thomas S.
Published: March 2024

Whole blood models are rapid and versatile for determining immune responses to inflammatory and infectious stimuli, but they have not been used for bacterial discrimination. Staphylococcus aureus, S. epidermidis and Escherichia coli are the most common causes of invasive disease, and rapid testing strategies utilising host responses remain elusive. Currently, immune responses can only discriminate between bacterial ‘domains’ (fungi, bacteria and viruses), and very few studies can use immune responses to discriminate bacteria at the species and strain level. Here, whole blood was used to investigate the relationship between host responses and bacterial strains. Results confirmed unique temporal profiles for the 10 parameters studied: IL-6, MIP-1α, MIP-3α, IL-10, resistin, phagocytosis, S100A8, S100A8/A9, C5a and TF3. Pairwise analysis confirmed that IL-6, resistin, phagocytosis, C5a and S100A8/A9 could be used in a discrimination scheme to identify to the strain level. Linear discriminant analysis (LDA) confirmed that (i) IL-6, MIP-3α and TF3 could predict genera with 95% accuracy; (ii) IL-6, phagocytosis, resistin and TF3 could predict species at 90% accuracy and (iii) phagocytosis, S100A8 and IL-10 predicted strain at 40% accuracy. These data are important because they confirm the proof of concept that host biomarker panels could be used to identify bacterial pathogens.
Comparison of MRI Sequences to Predict IDH Mutation Status in Gliomas Using Radiomics-Based Machine Learning
Authors: Kasap Dilek N. G. , Mora Nabila Gala Nacul , Blömer David A. , Akkurt Burak Han , Heindel Walter Leonhard , Mannil Manoj , Musigmann Manfred
Published: March 2024

Objectives: Regarding the 2021 World Health Organization (WHO) classification of central nervous system (CNS) tumors, the isocitrate dehydrogenase (IDH) mutation status is one of the most important factors for CNS tumor classification. The aim of our study is to analyze which of the commonly used magnetic resonance imaging (MRI) sequences is best suited to obtain this information non-invasively using radiomics-based machine learning models. We developed machine learning models based on different MRI sequences and determined which of the MRI sequences analyzed yields the highest discriminatory power in predicting the IDH mutation status. Material and Methods: In our retrospective IRB-approved study, we used the MRI images of 106 patients with histologically confirmed gliomas. The MRI images were acquired using the T1 sequence with and without administration of a contrast agent, the T2 sequence, and the Fluid-Attenuated Inversion Recovery (FLAIR) sequence. To objectively compare performance in predicting the IDH mutation status as a function of the MRI sequence used, we included only patients in our study cohort for whom MRI images of all four sequences were available. Seventy-one of the patients had an IDH mutation, and the remaining 35 patients did not have an IDH mutation (IDH wild-type). For each of the four MRI sequences used, 107 radiomic features were extracted from the corresponding MRI images by hand-delineated regions of interest. Data partitioning into training data and independent test data was repeated 100 times to avoid random effects associated with the data partitioning. Feature preselection and subsequent model development were performed using Random Forest, Lasso regression, LDA, and Naïve Bayes. The performance of all models was determined with independent test data. Results: Among the different approaches we examined, the T1-weighted contrast-enhanced sequence was found to be the most suitable for predicting IDH mutations status using radiomics-based machine learning models. Using contrast-enhanced T1-weighted MRI images, our seven-feature model developed with Lasso regression achieved a mean area under the curve (AUC) of 0.846, a mean accuracy of 0.792, a mean sensitivity of 0.847, and a mean specificity of 0.681. The administration of contrast agents resulted in a significant increase in the achieved discriminatory power. Conclusions: Our analyses show that for the prediction of the IDH mutation status using radiomics-based machine learning models, among the MRI images acquired with the commonly used MRI sequences, the contrast-enhanced T1-weighted images are the most suitable.
Identification of Novel Tumor Pyroptosis-Related Antigens and Pyroptosis Subtypes for Developing mRNA Vaccines in Pancreatic Adenocarcinoma
Authors: Lin Qiaowei , Liang Li , Wang Qing , Wang Xiao , You Yang , Rong Yefei , Zhou Yuhong , Guo Xi
Published: March 2024

Background: As one of the important components of immunotherapies, mRNA vaccines have displayed promising clinical outcomes in solid tumors. Nonetheless, their efficacy remains unclear in pancreatic adenocarcinoma (PAAD). Given the interaction of pyroptosis with anticancer immunity, our study aims to identify pyroptosis-related antigens for mRNA vaccine development and discern eligible candidates for vaccination. Methods: Utilizing gene expression data from TCGA and ICGC, we integrated RNA-seq data and compared genetic alterations through cBioPortal. Differential gene expressions were integrated using GEPIA. Relationships between immune cell abundance and tumor antigens were analyzed and visualized via TIMER. WGCNA facilitated the clustering of pyroptosis-related genes, identification of hub genes, and pathway enrichment analyses. Pyroptosis landscape was depicted through graph learning-based dimensional reduction. Results: Four overexpressed and mutant pyroptosis-related genes associated with poor prognosis were identified as potential antigens for mRNA vaccines in PAAD, including ANO6, PAK2, CHMP2B, and RAB5A. These genes displayed positive associations with antigen-presenting cells. PAAD patients were stratified into three pyroptosis subtypes. Notably, the PS3 subtype, characterized by a lower mutation count and TMB, exhibited “cold” immunological traits and superior survival compared to other subtypes. The pyroptosis landscape exhibited considerable heterogeneity among individuals. Furthermore, the turquoise module emerged as an independent prognostic indicator and patients with high expressions of hub genes might not be suitable candidates for mRNA vaccination. Conclusions: In PAAD, ANO6, PAK2, CHMP2B, and RAB5A are prospective pyroptosis-related antigens for mRNA vaccine development, which holds potential benefits for patients classified as PS3 and those with diminished hub gene expressions, providing insights into personalized mRNA vaccine strategies.
The Association between Diabetic Retinopathy and Macular Degeneration: A Nationwide Population-Based Study
Authors: Lin Hsin-Ting , Zheng Cai-Mei , Tsai Cheng-Hung , Chen Ching-Long , Chou Yu-Ching , Zheng Jing-Quan , Lin Yuh-Feng , Lin Chia-Wei , Chen Yong-Chen , Sun Chien-An , Chen Jiann-Torng
Published: March 2024

Objective: Age-related macular degeneration (AMD), particularly its exudative form, is a primary cause of vision impairment in older adults. As diabetes becomes increasingly prevalent in aging, it is crucial to explore the potential relationship between diabetic retinopathy (DR) and AMD. This study aimed to assess the risk of developing overall, non-exudative, and exudative AMD in individuals with DR compared to those without retinopathy (non-DR) based on a nationwide population study in Taiwan. Methods: A retrospective cohort study was conducted using the Taiwan National Health Insurance Database (NHIRD) (2000–2013). A total of 3413 patients were placed in the study group (DR) and 13,652 in the control group (non-DR) for analysis. Kaplan–Meier analysis and the Cox proportional hazards model were used to calculate the hazard ratios (HRs) and adjusted hazard ratios (aHRs) for the development of AMD, adjusting for confounding factors, such as age, sex, and comorbid conditions. Results: Kaplan–Meier survival analysis indicated a significantly higher cumulative incidence of AMD in the DR group compared to the non-DR group (log-rank test, p < 0.001). Adjusted analyses revealed that individuals with DR faced a greater risk of overall AMD, with an aHR of 3.50 (95% CI = 3.10–3.95). For senile (unspecified) AMD, the aHR was 3.45 (95% CI = 3.04–3.92); for non-exudative senile AMD, it was 2.92 (95% CI = 2.08–4.09); and for exudative AMD, the aHR was 3.92 (95% CI = 2.51–6.14). Conclusion: DR is a significant risk factor for both overall, senile, exudative, and non-exudative AMD, even after adjusting for demographic and comorbid conditions. DR patients tend to have a higher prevalence of vascular comorbidities; however, our findings indicate that the ocular pathologies inherent to DR might have a more significant impact on the progression to AMD. Early detection and appropriate treatment of AMD is critically important among DR patients.
Exploring the Role of ChatGPT in Oncology: Providing Information and Support for Cancer Patients
Authors: Cè Maurizio , Chiarpenello Vittoria , Bubba Alessandra , Felisaz Paolo Florent , Oliva Giancarlo , Irmici Giovanni , Cellina Michaela
Published: March 2024

Introduction: Oncological patients face numerous challenges throughout their cancer journey while navigating complex medical information. The advent of AI-based conversational models like ChatGPT (San Francisco, OpenAI) represents an innovation in oncological patient management. Methods: We conducted a comprehensive review of the literature on the use of ChatGPT in providing tailored information and support to patients with various types of cancer, including head and neck, liver, prostate, breast, lung, pancreas, colon, and cervical cancer. Results and Discussion: Our findings indicate that, in most instances, ChatGPT responses were accurate, dependable, and aligned with the expertise of oncology professionals, especially for certain subtypes of cancers like head and neck and prostate cancers. Furthermore, the system demonstrated a remarkable ability to comprehend patients’ emotional responses and offer proactive solutions and advice. Nevertheless, these models have also showed notable limitations and cannot serve as a substitute for the role of a physician under any circumstances. Conclusions: Conversational models like ChatGPT can significantly enhance the overall well-being and empowerment of oncological patients. Both patients and healthcare providers must become well-versed in the advantages and limitations of these emerging technologies.
Warm Air Delivery in Adhesive Application: Effect on Bonding Performance and Morphological Outcomes
Authors: Bourgi Rim , Kharouf Naji , Cuevas-Suárez Carlos Enrique , Lukomska-Szymanska Monika , Kharma Khalil , Moussa Fabienne Hajj , Metlej Manar , Haikel Youssef , Hardan Louis
Published: March 2024

Solvent evaporation within an adhesive layer is a crucial step during a bonding process. The aim of this current research was to test whether the use of different air temperatures (20 °C, 40 °C, and 60 °C) for solvent evaporation improves the performance of four adhesive systems to dentin. Sixty non-carious human molar teeth were randomly prepared for micro-tensile bond strength (μTBS) tests. Four different adhesive systems, Prime&Bond Universal (PBU), OptiBond Universal (OBU), OptiBond FL (OBFL), and Clearfil SE (CSE), were applied following the manufacturer’s instructions. Three groups based on the air-drying temperature were used: solvent evaporation was performed with either of warm (40 °C), (60 °C), and cold air as control group (20 °C) for 10 s at a distance of 5 cm. In all bonded surfaces, three resin composite (Reflectys, Itena Clinical, Paris, France) layers of 2 mm thickness were built up. The resin–dentin samples were kept in distilled water at 37 °C for 24 h and 6 months, respectively, before μTBS testing. Failure analysis, scanning electron microscopy of resin–dentin bonded interface, and solvent evaporation rate were tested as secondary variables. All analyses were conducted using a significance level of α = 0.05. Bond strength (BS) values were similar among all the adhesive systems used (p > 0.05). Also, the aging factor did not affect the BS (p > 0.05). Only the factor of temperature used for solvent evaporation resulted in a statistically significant effect (p < 0.05), with the temperature of 60 °C being the highest value (p < 0.05). A failure mode evaluation revealed mostly adhesive or mixed modes of failures in all the different temperatures of air used for the solvent evaporation of each adhesive system. The thickness of the adhesive layer and the creation of resin tags varied amongst the temperatures evaluated. For all adhesive systems tested, the use of 40 °C or 60 °C air for solvent evaporation led to an increased mass loss. Warmer temperatures for solvent evaporation contributed positively to bonding performance, enhancing both the quality of the adhesive layer and its interaction with the dentin tissue. Optimizing solvent evaporation with warmer air temperatures (40 °C and 60 °C) significantly improved µTBS, offering a practical means to enhance the quality and longevity of adhesive restorations in esthetic dentistry.
Evaluation of Cherts in Gumushane Province in Terms of Alkali Silica Reaction
Authors: Demir Şahin Demet
Published: March 2024

Alkali–silica reaction (ASR) occurs when alkali oxides coming from the cement composition in concrete come together with reactive silica and moisture coming from the aggregate. Additional maintenance and repair costs caused by the development of ASR in concrete cause the cost to increase. However, thanks to the measures taken against ASR in the early period, it contributes to the creation of sustainable and durable concrete structures. The article investigated the usability of cherts with eight different chemical compositions as aggregates in ready-mixed concrete plants in Gümüşhane. Cherts have been investigated for alkaline reactivity and are intended to be used largely as a source for concrete plants. ASR length changes of the samples prepared according to ASTM C1260 standard were determined after 3, 7, 14, and 28 days of the curing period. Microstructural examination, ultrasonic P-wave velocity, and bending and compressive strength experiments supporting ASR were carried out. The obtained test results were compared between the reference (limestone) sample and each other, as well as with the values specified in the standards. The compressive and bending strength values of the samples increase depending on their ASR. It was observed that the crack structures and types increased depending on the increase in the crack values.