bluuebunny/crossref_metadata_2025 huggingface dataset:
Multi-Level Hazard Detection Using a UAV-Mounted Multi-Sensor for Levee Inspection
Authors: Su Shan , Yan Li , Xie Hong , Chen Changjun , Zhang Xiong , Gao Lyuzhou , Zhang Rongling
Published: March 2024

This paper introduces a developed multi-sensor integrated system comprising a thermal infrared camera, an RGB camera, and a LiDAR sensor, mounted on a lightweight unmanned aerial vehicle (UAV). This system is applied to the inspection tasks of levee engineering, enabling the real-time, rapid, all-day, all-round, and non-contact acquisition of multi-source data for levee structures and their surrounding environments. Our aim is to address the inefficiencies, high costs, limited data diversity, and potential safety hazards associated with traditional methods, particularly concerning the structural safety of dam bodies. In the preprocessing stage of multi-source data, techniques such as thermal infrared data enhancement and multi-source data alignment are employed to enhance data quality and consistency. Subsequently, a multi-level approach to detecting and screening suspected risk areas is implemented, facilitating the rapid localization of potential hazard zones and assisting in assessing the urgency of addressing these concerns. The reliability of the developed multi-sensor equipment and the multi-level suspected hazard detection algorithm is validated through on-site levee engineering inspections conducted during flood disasters. The application reliably detects and locates suspected hazards, significantly reducing the time and resource costs associated with levee inspections. Moreover, it mitigates safety risks for personnel engaged in levee inspections. Therefore, this method provides reliable data support and technical services for levee inspection, hazard identification, flood control, and disaster reduction.
Convergence of Relative Entropy for Euler–Maruyama Scheme to Stochastic Differential Equations with Additive Noise
Authors: Yu Yuan
Published: March 2024

For a family of stochastic differential equations driven by additive Gaussian noise, we study the asymptotic behaviors of its corresponding Euler–Maruyama scheme by deriving its convergence rate in terms of relative entropy. Our results for the convergence rate in terms of relative entropy complement the conventional ones in the strong and weak sense and induce some other properties of the Euler–Maruyama scheme. For example, the convergence in terms of the total variation distance can be implied by Pinsker’s inequality directly. Moreover, when the drift is β(0<β<1)-Hölder continuous in the spatial variable, the convergence rate in terms of the weighted variation distance is also established. Both of these convergence results do not seem to be directly obtained from any other convergence results of the Euler–Maruyama scheme. The main tool this paper relies on is the Girsanov transform.
Explorative Study of Developing a Mathematical Model for Evaluating HOTS in the Mathematics Curriculum Operating in the KZN TVET Colleges
Authors: Mazibuko Godfrey Nkululeko , Maharaj Aneshkumar
Published: March 2024

This study developed a mathematical evaluation model, attempting to evaluate the capability of the curriculum (N1 to N2 mathematics) to equip students with higher-order thinking skills (HOTS) in the Technical and Vocational Education and Training (TVET) Colleges. The data set was collected at eMnambithi TVET College during March 2022 and October 2022. The two most crucial elements contributing to students attaining HOTS during teaching and learning are the lecturer’s content delivery ability and the curriculum. In that regard, this study began by partially evaluating the lecturer’s content delivery ability using students’ perspectives through a questionnaire. It was found that N1 and N2 mathematics lecturers’ content delivery abilities from the perspective of the students might be adequate. That left the curriculum as the only major contributing factor in a case where students were found to have poor HOTS at eMnambithi TVET College. Then, the SVHIR model (susceptible S(t), vaccinated V(t), healthy H(t), infected I(t), and recovered R(t)) was successfully developed to attempt the evaluation of students’ HOTS. The model indicated poor HOTS in students at eMnambithi TVET College. That ultimately meant that the curriculum might be incapable of equipping students with HOTS, since the lecturers’ content delivery abilities were deemed to be adequate by the participants of this study.
A Survey of Intelligent End-to-End Networking Solutions: Integrating Graph Neural Networks and Deep Reinforcement Learning Approaches
Authors: Tam Prohim , Ros Seyha , Song Inseok , Kang Seungwoo , Kim Seokhoon
Published: March 2024

This paper provides a comprehensive survey of the integration of graph neural networks (GNN) and deep reinforcement learning (DRL) in end-to-end (E2E) networking solutions. We delve into the fundamentals of GNN, its variants, and the state-of-the-art applications in communication networking, which reveal the potential to revolutionize access, transport, and core network management policies. This paper further explores DRL capabilities, its variants, and the trending applications in E2E networking, particularly in enhancing dynamic network (re)configurations and resource management. By fusing GNN with DRL, we spotlight novel approaches, ranging from radio access networks to core management and orchestration, across E2E network layers. Deployment scenarios in smart transportation, smart factory, and smart grids demonstrate the practical implications of our survey topic. Lastly, we point out potential challenges and future research directions, including the critical aspects for modelling explainability, the reduction in overhead consumption, interoperability with existing schemes, and the importance of reproducibility. Our survey aims to serve as a roadmap for future developments in E2E networking, guiding through the current landscape, challenges, and prospective breakthroughs in the algorithm modelling toward network automation using GNN and DRL.
A Novel Modular Sigma DC/DC Converter with a Wide Input Voltage Range
Authors: Ren Chunguang , He Yapeng , Qin Yue , Hui Yue , Li Xinqi , Han Xiaoqing , He Xiangning
Published: March 2024

A modular Sigma DC/DC converter with wide input voltage range is proposed in this paper. The proposed converter is combined with a traditional LLC converter and two multi-resonant converters via Sigma architecture. Among them, the traditional LLC converter operates as a DC transformer (DCX) at resonant frequency to achieve maximum efficiency. Meanwhile, one of the multi-resonant converters, the DC to DC (D2D) part of the Sigma structure, is responsible for voltage regulation over a wide input voltage range. In addition, the other multi-resonant converter has two operation modes, including DCX and D2D. When it operates in the DCX mode, the Sigma converter has better performance and higher efficiency. When it operates in the D2D mode, the Sigma converter can handle a wider input voltage range. For each submodule, the operation principle and characteristics of the proposed Sigma converter are analyzed in detail. In addition, some key points of the parameter design for each part are also demonstrated. Finally, an experimental prototype with an input voltage of 540~1100 V is built to verify the effectiveness of the proposed converter.
Robust EMPC-Based Frequency-Adaptive Grid Voltage Sensorless Control for an LCL-Filtered Grid-Connected Inverter
Authors: Kim Yubin , Tran Thuy Vi , Kim Kyeong-Hwa
Published: March 2024

A robust explicit model predictive control (EMPC)-based frequency-adaptive grid voltage sensorless control is developed for a grid-connected inverter (GCI) via a linear matrix inequality (LMI) approach under the model parametric uncertainties as well as distorted and imbalanced grid voltages. In order to ensure the quality of grid currents injected into the utility grid even when the system model parameters vary, the proposed control scheme is accomplished by an enhanced prediction model rather than the conventional prediction model obtained by fixed parameters. Furthermore, an LMI-based observer is integrated with the disturbance observer to improve the reference tracking performance and to reject disturbances. The proposed observer is employed for the grid frequency-adaptive control without the need for grid voltage sensors. The proposed current controller and observer employ the LMI scheme to maintain a stable and robust operation of the GCI. The discrete-time frequency response and pole-zero map analyses are utilized to examine the system performance including the stability and robustness against parametric uncertainties. Comprehensive simulation and experimental tests as well as theoretical analyses clearly validate the robustness of the proposed control scheme under various harsh test conditions with non-ideal and unexpected grid and system parametric uncertainties.
MIX-Net: Hybrid Attention/Diversity Network for Person Re-Identification
Authors: Li Minglang , Tao Zhiyong , Lin Sen , Feng Kaihao
Published: March 2024

Person re-identification (Re-ID) networks are often affected by factors such as pose variations, changes in viewpoint, and occlusion, leading to the extraction of features that encompass a considerable amount of irrelevant information. However, most research has struggled to address the challenge of simultaneously endowing features with both attentive and diversified information. To concurrently extract attentive yet diverse pedestrian features, we amalgamated the strengths of convolutional neural network (CNN) attention and self-attention. By integrating the extracted latent features, we introduced a Hybrid Attention/Diversity Network (MIX-Net), which adeptly captures attentive but diverse information from personal images via a fusion of attention branches and attention suppression branches. Additionally, to extract latent information from secondary important regions to enrich the diversity of features, we designed a novel Discriminative Part Mask (DPM). Experimental results establish the robust competitiveness of our approach, particularly in effectively distinguishing individuals with similar attributes.
Evaluating the Efficiency of Surface-Based Air Heating Systems
Authors: Rabczak Slawomir , Nowak Krzysztof
Published: March 2024

This study explores the synergistic potential of integrating forced air heating with flat surface heating, presenting a promising solution for structures with intermittent occupancy or where conventional water-based heating proves impractical. The objective is to enhance thermal comfort and reduce long-term energy consumption. A comprehensive examination of the interaction between heated surfaces and forced air heating reveals that excess energy generated can be redirected for more efficient heat distribution. Various scenarios were tested, indicating that the power necessary for maintaining consistent surface temperature could be significantly reduced. A noteworthy approach involves utilizing heat from pellet smoke to maximize heat recovery efficiency from pellet combustion. This, however, raises issues related to smoke introduction into heated spaces. Despite challenges, this approach provides a means to minimize the delivery of overheated air and accumulate energy within room partitions, thereby enhancing system efficiency. The study concludes that while the stand-alone flat surface heating system is better suited as a supplementary heating source within buildings, it offers a compelling alternative within traditional construction, aligning with historical systems.
Hybrid Deloading Control Strategy in MMC-Based Wind Energy Conversion Systems for Enhanced Frequency Regulation
Authors: Zhang Jimiao , Li Jie
Published: March 2024

The growing integration of renewable energy sources, especially offshore wind (OSW), is introducing frequency stability challenges to electric power grids. This paper presents a novel hybrid deloading control strategy that enables modular multilevel converter (MMC)-based wind energy conversion systems (WECSs) to actively contribute to grid frequency regulation. This research investigates a permanent-magnet synchronous generator (PMSG)-based direct-drive configuration, sourced from the International Energy Agency’s (IEA’s) 15 MW reference turbine model. Specifically, phase-locked loop (PLL)-free grid-forming (GFM) control is employed via the grid-side converter (GSC), and DC-link voltage control is realized through the machine-side converter (MSC), both of which boost the energy support for the integrated AC grid’s frequency stability. This control strategy combines the benefits of over-speeding and pitch control modes, facilitating smooth transitions between different modes based on real-time wind speed measurements. In addition, the practical challenges of MMCs, such as circulating currents and capacitor voltage imbalances, are addressed. Numerical simulations under varying wind speeds and loading conditions validate the enhanced frequency regulation capability of the proposed approach.
Antitumor Strategies Targeting Peptidergic Systems
Authors: Rodríguez Francisco D. , Coveñas Rafael
Published: March 2024

Peptidergic systems show promise as targets for fighting tumors. While some peptides encourage the growth and spread of tumor cells and angiogenic mechanisms, others display antitumor properties. As such, peptide ligands and receptor antagonists could be used as antitumor agents alone or in conjunction with chemotherapy or radiotherapy. Peptide receptor antagonists can counteract the oncogenic effects of specific peptides by inducing apoptosis in various types of tumor cells, hindering cancer cell migration and inhibiting angiogenesis. Peptides and peptide receptor antagonists are not currently used in clinical practice as antitumor agents. Still, aprepitant, a neurokinin 1 receptor antagonist, is a promising candidate due to its ability to promote apoptosis in many cancer cells. However, to utilize aprepitant as an anticancer agent, the dosage must be increased and administered for a more extended period. Moving beyond current protocols for aprepitant’s use as an antiemetic is essential. Additionally, a common anticancer strategy with aprepitant is possible regardless of cancer cell type. Finally, combining aprepitant with chemotherapy or radiotherapy is encouraged.
Human Resources’ Burnout
Authors: Pirrolas Olga Alexandra Chinita , Correia Pedro Miguel Alves Ribeiro
Published: March 2024

The reality of the occurrence of burnout in human resources has been increasingly recognised as a result of today’s transforming and competitive society, which exerts a very high level of stress and anxiety on workers, generating a notorious problem in the field of human resource management. Problems related to symptoms of exhaustion, mental weakness, personal devaluation, inability to solve professional problems, restlessness, and eating disorders. These problems manifest themselves in terms of personality, triggering feelings of threat, panic, nervousness, or suicide. Such disorders pose a threat not only to the person but also to the quality of their professional activities. In this way, burnout syndrome can cause a mental and physical breakdown requiring complex medical assistance. In view of the above, it is imperative that organisations take preventative and corrective measures to tackle this phenomenon. This entry covers topics such as the history of the concept of burnout, the concept, its causes and consequences, and predictive methods. By approaching the aforementioned topics using the existing literature on burnout syndrome, this entry aims to demystify the subject of burnout in human resources.
Debaryomyces hansenii Strains from Traditional Chinese Dry-Cured Ham as Good Aroma Enhancers in Fermented Sausage
Authors: Yang Xiaoying , Xiao Shan , Wang Jihui
Published: March 2024

In some countries, yeasts are still not allowed in the production of commercially fermented sausages. Therefore, further research is needed on producing fermented meat products using different strains of yeasts. In this study, two strains of Debaryomyces hansenii (D. hansenii Y61 and Y67) were inoculated in fermented sausages to study their effects as starter cultures. The inoculation of D. hansenii strains affected ripening by decreasing the pH and aw. The sausages inoculated with Y61 and Y67 exhibited decreases in lipid oxidation of 40.70% and 36.04%, respectively, and Enterobacteriaceae counts of 50% and 100%, respectively. The inoculating yeasts Y61 and Y67 increased the lightness (L*) and redness (a*) of fermented sausages. The D. hansenii-inoculated sausages had higher levels of free amino acids and fatty acids, which improved the digestibility, sensory value, and safety of these sausages. Moreover, the total amount of ester compounds increased by 87.14% and 83.31% in the Y61- and Y67-inoculated groups, respectively, which contributed to the aroma. Better sensory attributes were also found in the sausages inoculated with Y61 and Y67 D. hansenii. Native D. hansenii Y61 and Y67 are, therefore, good starter cultures for fermented sausage production. Together, the results provide data supporting future research and the use of yeast-fermented sausages.
Optimization of Solid-State Fermentation Process of Radix Ranunculi ternate Using Response Surface Method and Addressing Its Antioxidant and Hypoglycemic Activity
Authors: He Dingxuan , Duan Dingyu , Lv Xueyan , Xiong Baihui , Li Zhuojia , Zhang Shaojun , Cai Jing , Qiao Xinrong , Chen Qiong
Published: March 2024

Objective: The aim of this study was to optimize the fermentation process of Radix Ranunculi ternate via microbial fermentation and analyze the changes in the contents of the main components, the antioxidant and hypoglycemic capacities of the extract before and after fermentation. Methods: The solid-state fermentation process was optimized using single-factor tests and the response surface method, with the yield of the alcohol extract of R. ternate as an evaluation index. Results: The best fermentation process was optimized using solid-state endophytic fungus fermentation technology as follows: strain addition ratio of Chaetomium globosum/Fusarium equiseti = 1:1, fermentation for 5 d, sieve size of 40 mesh, liquid/material ratio of 0.8:1 mL·g−1, fermentation temperature of 31 °C, and inoculation amount of 7.5%. Under the optimized conditions, the contents of the water-soluble extract and total polysaccharides decreased by 12.71% and 12.95%, respectively. In the fermentation, the contents of the ethanol-soluble extract, flavonoids, saponins, polyphenols, organic acids, and total amino acids of the fermented R. ternate increased by 19.77%, 57.14%, 79.67%, 14.29%, 17.63%, and 3.82%, respectively. The scavenging rate for DPPH, ABTS+, and ·OH free radicals and inhibitory rate for α-amylase of the fermented R. ternate also increased by 19.02%, 14.17%, 7.53%, and 34.54%, respectively, compared with the unfermented R. ternate. Conclusions: Solid-state fermentation opens new avenues for the development and application of R. ternate as a natural antioxidant and hypoglycemic food.
Modeling and Optimization of the Culture Medium for Efficient 4′-N-Demethyl-Vicenistatin Production by Streptomyces parvus Using Response Surface Methodology and Artificial-Neural-Network-Genetic-Algorithm
Authors: Yu Zhixin , Fu Hongxin , Wang Jufang
Published: March 2024

4′-N-demethyl-vicenistatin is a vicenistatin analogue that has better antitumor activity with promising applications in the pharmaceuticals industry. The harnessing of the complete potential of this compound necessitates a systematic optimization of the culture medium to enable the cost-effective production of 4′-N-demethyl-vicenistatin by Streptomyces parvus SCSIO Mla-L010/ΔvicG. Therefore, in this study, a sequential approach was employed to screen the significant medium compositions, as follows: one-factor-at-a-time (OFAT) and Plackett–Burman designs (PBD) were initially utilized. Cassava starch, glycerol, and seawater salt were identified as the pivotal components influencing 4′-N-demethyl-vicenistatin production. To further investigate the direct and interactive effects of these key components, a three-factor, five-level central composite design (CCD) was implemented. Finally, response surface methodology (RSM) and an artificial-neural-network-genetic-algorithm (ANN-GA) were employed for the modeling and optimization of the medium components to enhance efficient 4′-N-demethyl-vicenistatin production. The ANN-GA model showed superior reliability, achieving the most 4′-N-demethyl-vicenistatin, at 0.1921 g/L, which was 17% and 283% higher than the RSM-optimized and initial medium approaches, respectively. This study represents pioneering work on statistically guided optimization strategies for enhancing 4′-N-demethyl-vicenistatin production through medium optimization.
An Advanced Path Planning and UAV Relay System: Enhancing Connectivity in Rural Environments
Authors: El Debeiki Mostafa , Al-Rubaye Saba , Perrusquía Adolfo , Conrad Christopher , Flores-Campos Juan Alejandro
Published: March 2024

The use of unmanned aerial vehicles (UAVs) is increasing in transportation applications due to their high versatility and maneuverability in complex environments. Search and rescue is one of the most challenging applications of UAVs due to the non-homogeneous nature of the environmental and communication landscapes. In particular, mountainous areas pose difficulties due to the loss of connectivity caused by large valleys and the volumes of hazardous weather. In this paper, the connectivity issue in mountainous areas is addressed using a path planning algorithm for UAV relay. The approach is based on two main phases: (1) the detection of areas of interest where the connectivity signal is poor, and (2) an energy-aware and resilient path planning algorithm that maximizes the coverage links. The approach uses a viewshed analysis to identify areas of visibility between the areas of interest and the cell-towers. This allows the construction of a blockage map that prevents the UAV from passing through areas with no coverage, whilst maximizing the coverage area under energy constraints and hazardous weather. The proposed approach is validated under open-access datasets of mountainous zones, and the obtained results confirm the benefits of the proposed approach for communication networks in remote and challenging environments.
Envisioning Transition from Open Landscapes to Forested Landscapes in the Routt National Forest, Colorado, United States
Authors: Hanberry Brice B. , Seidel Jacob M.
Published: March 2024

Globally, in remaining wildlands, tree densities and forested cover have increased in grasslands and open forests since European settlement. In the southern Rocky Mountains of Colorado, United States, we determined tree composition and tree cover from historical (years 1875 to 1896) surveys and compared them to current (2002 to 2011) tree composition and current (year 2016) forested land cover for 500,000 ha of the Routt National Forest. Additionally, we examined whether changes in precipitation occurred. Regarding composition, pine (primarily lodgepole pine; Pinus contorta) decreased from 65% to 32% of all trees, with increased subalpine fir (Abies lasiocarpa) from 0.5% to 23% of all trees, and quaking aspen (Populus tremuloides) from 13% to 30% of all trees. According to 80% of 5175 survey points not in forests, the historical landscape was very open, comprised of grasslands, mountain meadows, and other open ecosystems. In contrast, 75% of the current landscape is covered by forests. Change points in the Palmer Modified Drought Index were within historical limits, indicating that forestation was not related to a change in water availability. Based on historical surveys and accounts, we envisioned a historical landscape that was open but embedded with dense lodgepole pine clusters and spruce stands at high elevations, which has now become a predominantly forested landscape of dense forests, similar to global forestation patterns.
Convolution Kernel Function and Its Invariance Properties of Bone Fractal Operators
Authors: Jian Zhimo , Peng Gang , Luo Chaoqian , Zhou Tianyi , Yin Yajun
Published: March 2024

This article studies the error function and its invariance properties in the convolutional kernel function of bone fractal operators. Specifically, the following contents are included: (1) demonstrating the correlation between the convolution kernel function and error function of bone fractal operators; (2) focusing on the main part of bone fractal operators: p+α2-type differential operator, discussing the convolutional kernel function image; (3) exploring the fractional-order correlation between the error function and other special functions from the perspective of fractal operators.
Abdominal Pain—Beyond Colonic Lipoma Intussusception
Authors: Dascalu Raluca-Ioana , Constantinescu Gabriel , Scafa Alexandru , Plotogea Oana-Mihaela , Sandru Vasile , Rinja Ecaterina Mihaela , Jichitu Alexandra , Ilie Madalina
Published: March 2024

Colonic lipomas are relatively rare benign tumors which are composed of mature fat cells and occur most frequently in the large intestine. The occurrence of colonic lipomas in the transverse colon is relatively uncommon. Generally, colonic lipomas are asymptomatic, and many individuals might not experience any noticeable symptoms. Therefore, they are usually discovered incidentally during colonoscopy or as a result of diagnostic imaging prescribed for other reasons. The size and location of the lipoma could influence the clinical presentation. If symptoms occur, they include abdominal pain, changes in bowel habits, or gastrointestinal bleeding. The prognosis for colonic lipomas is generally excellent but it requires an individualized approach based on the specific characteristics of the tumor, the patient’s symptoms, and other clinical considerations. We report a case of a colonic intussusception caused by a colonic lipoma in an adult who underwent surgery, with an uneventful recovery.
Computational Tools to Assist in Analyzing Effects of the SERPINA1 Gene Variation on Alpha-1 Antitrypsin (AAT)
Authors: Mróz Jakub , Pelc Magdalena , Mitusińska Karolina , Chorostowska-Wynimko Joanna , Jezela-Stanek Aleksandra
Published: March 2024

In the rapidly advancing field of bioinformatics, the development and application of computational tools to predict the effects of single nucleotide variants (SNVs) are shedding light on the molecular mechanisms underlying disorders. Also, they hold promise for guiding therapeutic interventions and personalized medicine strategies in the future. A comprehensive understanding of the impact of SNVs in the SERPINA1 gene on alpha-1 antitrypsin (AAT) protein structure and function requires integrating bioinformatic approaches. Here, we provide a guide for clinicians to navigate through the field of computational analyses which can be applied to describe a novel genetic variant. Predicting the clinical significance of SERPINA1 variation allows clinicians to tailor treatment options for individuals with alpha-1 antitrypsin deficiency (AATD) and related conditions, ultimately improving the patient’s outcome and quality of life. This paper explores the various bioinformatic methodologies and cutting-edge approaches dedicated to the assessment of molecular variants of genes and their product proteins using SERPINA1 and AAT as an example.
Incidence and Risk Factors for Acute Articular Cartilage Tears in Military and Other Occupational Settings: A Systematic Review
Authors: Robson Kristy , Pope Rodney , Orr Robin
Published: March 2024

Damage to the articular cartilage resulting in an acute tear can lead to functional changes within the joint and increase the risk of osteoarthritis developing. There is limited understanding of the association between occupational risk factors and sustaining an acute articular cartilage tear in the military and other physically demanding occupations. Therefore, the aim of this systematic review was to identify and evaluate original research reporting on occupational risk factors associated with sustaining acute articular cartilage tears. Methods: A systematic review following the Preferred Reporting Items for Systematic review and Meta-Analysis—Protocols was conducted and registered with the Open Science Framework. Key academic databases were searched using terms from the following concepts: risk or cause, paid occupations, and acute articular cartilage tears. Results: Of an initial 941 studies, 2 studies met the eligibility criteria, both reporting data from military contexts; only one evaluated acute articular cartilage tears in both males and females. One paper focused on articular cartilage injury within the knee and the other within the ankle joint with incidence rates being 0.2 and 0.3 per 1000 person-years, respectively. People in more physically active occupations and individuals with an above-normal body mass index were reported as being at higher risk of sustaining an acute articular cartilage tear. Conclusion: Physically demanding occupations, such as the military, may increase the risk for acute tears of the articular cartilage. However, the findings of this review indicate there is a paucity of research to underpin understanding of the injury mechanisms and occupational risk factors for acute articular cartilage tears.
The Association of Hypertensive Disorders of Pregnancy with Infant Mortality, Preterm Delivery, and Small for Gestational Age
Authors: Wilson Dulaney A. , Mateus Julio , Ash Emily , Turan Tanya N. , Hunt Kelly J. , Malek Angela M.
Published: March 2024

Gestational hypertension, preeclampsia, eclampsia, and chronic hypertension (CHTN) are associated with adverse infant outcomes and disproportionately affect minoritized race/ethnicity groups. We evaluated the relationships between hypertensive disorders of pregnancy (HDP) and/or CHTN with infant mortality, preterm delivery (PTD), and small for gestational age (SGA) in a statewide cohort with a diverse racial/ethnic population. All live, singleton deliveries in South Carolina (2004–2016) to mothers aged 12–49 were evaluated for adverse outcomes: infant mortality, PTD (20 to less than <37 weeks) and SGA (<10th birthweight-for-gestational-age percentile). Logistic regression models adjusted for sociodemographic, behavioral, and clinical characteristics. In 666,905 deliveries, mothers had superimposed preeclampsia (HDP + CHTN; 1.0%), HDP alone (8.0%), CHTN alone (1.8%), or no hypertension (89.1%). Infant mortality risk was significantly higher in deliveries to women with superimposed preeclampsia, HDP, and CHTN compared with no hypertension (relative risk [RR] = 1.79, 1.39, and 1.48, respectively). After accounting for differing risk by race/ethnicity, deliveries to women with HDP and/or CHTN were more likely to result in PTD (RRs ranged from 3.14 to 5.25) or SGA (RRs ranged from 1.67 to 3.64). As CHTN, HDP and superimposed preeclampsia confer higher risk of adverse outcomes, prevention efforts should involve encouraging and supporting mothers in mitigating modifiable cardiovascular risk factors.
Bone-Differentiation-Associated Circ-Spen Regulates Death of Mouse Bone Marrow Mesenchymal Stem Cells by Inhibiting Apoptosis and Promoting Autophagy
Authors: Liang Ziwen , Luo Bingjie , Peng Bojia , Li Yunchuan , Hu Xueling , Zhong Wenqiang , Li Xiaoyun , Wang Panpan , Zhu Xiaofeng , Zhang Ronghua , Yang Li
Published: March 2024

The role of estrogen receptor β (ERβ) in bone health is closely associated with its function in vivo, and ERβ−/− mice have been widely utilized to explore the related influences. In this study, ERβ−/− female mice were established to investigate the differential expression of circular RNAs (circRNAs) by RNA-Sequencing (RNA-Seq). Among these circRNAs, mmu_circ_0011379 (named Circ-Spen) exhibited high expression in ERβ−/− female mice. However, the precise mechanism by which Circ-Spen regulates bone health remained unclear. This study identified Circ-Spen as a positive regulator of mouse bone marrow mesenchymal stem cell (mBMSC) viability. The expression of Circ-Spen was markedly increased in ERβ−/− mice femurs tested by RT-qPCR. Moreover, Circ-Spen exhibited an enhanced expression during the bone formation process of mBMSCs. Qualitative experiments also demonstrated that Circ-Spen possessed a circular structure and was localized within the nucleus of mBMSCs. Functionally, it inhibited apoptosis via caspase-3, BCL-2, and BAX, while also promoting autophagy through BECN1 and P62 in mBMSCs tested by MTT assays, transmission electron microscopy (TEM), and Western blotting. These findings reveal the potential of targeting Circ-Spen as a promising therapeutic strategy for rejuvenating senescent mBMSCs and enhancing the efficiency of mBMSC transplantation, which lays the foundation for advancements in the field of bone therapy.
Gestational Weight Gain: Is the Role of Genetic Variants a Determinant? A Review
Authors: Sámano Reyna , Martínez-Rojano Hugo , Chico-Barba Gabriela , Gamboa Ricardo , Mendoza-Flores María Eugenia , Robles-Alarcón Francisco Javier , Pérez-Martínez Itzel , Monroy-Muñoz Irma Eloisa
Published: March 2024

Excessive or insufficient gestational weight gain (GWG) leads to diverse adverse maternal and neonatal outcomes. There is evidence that pregestational body mass index (pBMI) plays a role in GWG, but no genetic cause has been identified. In this review, we aim to analyze genotype variants associated with GWG. Results: We identified seven genotype variants that may be involved in GWG regulation that were analyzed in studies carried out in Brazil, Romania, the USA, Turkey, Ukraine, and Canada. Some genetic variants were only associated with GWG in certain races or depending on the pBMI. In women who were obese or overweight before gestation, some genetic variants were associated with GWG. Environmental and genetic factors together showed a greater association with GWG than genetic factors alone; for example, type of diet was observed to have a significant influence. Conclusions: We found little scientific evidence of an association between genotype variants in countries with a high prevalence of women of reproductive age who are overweight and obese, such as in Latin America. GWG may be more dependent on environmental factors than genetic variants. We suggest a deeper study of genetic variants, cytokines, and their possible association with GWG, always with the respective control of potential cofounding factors, such as pBMI, diet, and race.
Glioblastoma: An Update in Pathology, Molecular Mechanisms and Biomarkers
Authors: Lan Zhong , Li Xin , Zhang Xiaoqin
Published: March 2024

Glioblastoma multiforme (GBM) is the most common and malignant type of primary brain tumor in adults. Despite important advances in understanding the molecular pathogenesis and biology of this tumor in the past decade, the prognosis for GBM patients remains poor. GBM is characterized by aggressive biological behavior and high degrees of inter-tumor and intra-tumor heterogeneity. Increased understanding of the molecular and cellular heterogeneity of GBM may not only help more accurately define specific subgroups for precise diagnosis but also lay the groundwork for the successful implementation of targeted therapy. Herein, we systematically review the key achievements in the understanding of GBM molecular pathogenesis, mechanisms, and biomarkers in the past decade. We discuss the advances in the molecular pathology of GBM, including genetics, epigenetics, transcriptomics, and signaling pathways. We also review the molecular biomarkers that have potential clinical roles. Finally, new strategies, current challenges, and future directions for discovering new biomarkers and therapeutic targets for GBM will be discussed.
Investigation of Serum Endocan Levels in SARS-CoV-2 Patients
Authors: Constantin Laura , Ungurianu Anca , Streinu-Cercel Anca , Săndulescu Oana , Aramă Victoria , Margină Denisa , Țârcomnicu Isabela
Published: March 2024

Endocan is an endothelial-cell-specific proteoglycan (ESM-1) and has emerged as an endothelial dysfunction and inflammatory marker in recent years. Endocan can be used as a marker of inflammatory endothelial dysfunction in endothelium-dependent disease: cardiovascular disease, sepsis, lung and kidney disease and malignancies. Recent data suggest that endothelial dysfunction is a key mechanism in COVID-19 pathogenesis. Endotheliitis and thrombo-inflammation are associated with severe forms of SARS-CoV-2 infection, and endocan is currently under investigation as a potential diagnostic and prognostic marker. The aim of this study was to determine serum endocan levels in patients with COVID-19 to evaluate the correlation between endocan levels and clinical disease diagnosis and prognosis. This study enrolled 56 patients, divided into three groups depending on disease severity: mild (15), moderate (25) and severe (16). The biochemical, demographic, clinical and imagistic data were collected and evaluated in correlation with the endocan levels. Serum endocan levels were significantly higher in the COVID-19 patients compared to the control group; also, endocan concentration correlated with vaccination status. The results revealed significantly elevated serum endocan levels in COVID-19 patients compared to the control group, with a correlation observed between endocan concentration and vaccination status. These findings suggest that endocan may serve as a novel biomarker for detecting inflammation and endothelial dysfunction risk in COVID-19 patients. There was no significant relationship between serum endocan levels and disease severity or the presence of cardiovascular diseases. Endocan can be considered a novel biomarker for the detection of inflammation and endothelial dysfunction risk in COVID-19 patients.
Molecular Mechanisms Linking Osteoarthritis and Alzheimer’s Disease: Shared Pathways, Mechanisms and Breakthrough Prospects
Authors: Umoh Idiongo Okon , dos Reis Helton Jose , de Oliveira Antonio Carlos Pinheiro
Published: March 2024

Alzheimer’s disease (AD) is a progressive neurodegenerative disease mostly affecting the elderly population. It is characterized by cognitive decline that occurs due to impaired neurotransmission and neuronal death. Even though deposition of amyloid beta (Aβ) peptides and aggregation of hyperphosphorylated TAU have been established as major pathological hallmarks of the disease, other factors such as the interaction of genetic and environmental factors are believed to contribute to the development and progression of AD. In general, patients initially present mild forgetfulness and difficulty in forming new memories. As it progresses, there are significant impairments in problem solving, social interaction, speech and overall cognitive function of the affected individual. Osteoarthritis (OA) is the most recurrent form of arthritis and widely acknowledged as a whole-joint disease, distinguished by progressive degeneration and erosion of joint cartilage accompanying synovitis and subchondral bone changes that can prompt peripheral inflammatory responses. Also predominantly affecting the elderly, OA frequently embroils weight-bearing joints such as the knees, spine and hips leading to pains, stiffness and diminished joint mobility, which in turn significantly impacts the patient’s standard of life. Both infirmities can co-occur in older adults as a result of independent factors, as multiple health conditions are common in old age. Additionally, risk factors such as genetics, lifestyle changes, age and chronic inflammation may contribute to both conditions in some individuals. Besides localized peripheral low-grade inflammation, it is notable that low-grade systemic inflammation prompted by OA can play a role in AD pathogenesis. Studies have explored relationships between systemic inflammatory-associated diseases like obesity, hypertension, dyslipidemia, diabetes mellitus and AD. Given that AD is the most common form of dementia and shares similar risk factors with OA—both being age-related and low-grade inflammatory-associated diseases, OA may indeed serve as a risk factor for AD. This work aims to review literature on molecular mechanisms linking OA and AD pathologies, and explore potential connections between these conditions alongside future prospects and innovative treatments.
Structures, Mechanisms, and Physiological Functions of Zinc Transporters in Different Biological Kingdoms
Authors: Bui Han Ba , Inaba Kenji
Published: March 2024

Zinc transporters take up/release zinc ions (Zn2+) across biological membranes and maintain intracellular and intra-organellar Zn2+ homeostasis. Since this process requires a series of conformational changes in the transporters, detailed information about the structures of different reaction intermediates is required for a comprehensive understanding of their Zn2+ transport mechanisms. Recently, various Zn2+ transport systems have been identified in bacteria, yeasts, plants, and humans. Based on structural analyses of human ZnT7, human ZnT8, and bacterial YiiP, we propose updated models explaining their mechanisms of action to ensure efficient Zn2+ transport. We place particular focus on the mechanistic roles of the histidine-rich loop shared by several zinc transporters, which facilitates Zn2+ recruitment to the transmembrane Zn2+-binding site. This review provides an extensive overview of the structures, mechanisms, and physiological functions of zinc transporters in different biological kingdoms.
Prediction of Human Pharmacokinetics of E0703, a Novel Radioprotective Agent, Using Physiologically Based Pharmacokinetic Modeling and an Interspecies Extrapolation Approach
Authors: Ge Yun-Xuan , Zhang Zhuo , Yan Jia-Yi , Ma Zeng-Chun , Wang Yu-Guang , Xiao Cheng-Rong , Zhuang Xiao-Mei , Gao Yue
Published: March 2024

E0703, a new steroidal compound optimized from estradiol, significantly increased cell proliferation and the survival rate of KM mice and beagles after ionizing radiation. In this study, we characterize its preclinical pharmacokinetics (PK) and predict its human PK using a physiologically based pharmacokinetic (PBPK) model. The preclinical PK of E0703 was studied in mice and Rhesus monkeys. Asian human clearance (CL) values for E0703 were predicted from various allometric methods. The human PK profiles of E0703 (30 mg) were predicted by the PBPK model in Gastro Plus software 9.8 (SimulationsPlus, Lancaster, CA, USA). Furthermore, tissue distribution and the human PK profiles of different administration dosages and forms were predicted. The 0.002 L/h of CL and 0.005 L of Vss in mice were calculated and optimized from observed PK data. The plasma exposure of E0703 was availably predicted by the CL using the simple allometry (SA) method. The plasma concentration–time profiles of other dosages (20 and 40 mg) and two oral administrations (30 mg) were well-fitted to the observed values. In addition, the PK profile of target organs for E0703 exhibited a higher peak concentration (Cmax) and AUC than plasma. The developed E0703-PBPK model, which is precisely applicable to multiple species, benefits from further clinical development to predict PK in humans.
Astrocyte–Neuron Interaction via the Glutamate–Glutamine Cycle and Its Dysfunction in Tau-Dependent Neurodegeneration
Authors: Sidoryk-Węgrzynowicz Marta , Adamiak Kamil , Strużyńska Lidia
Published: March 2024

Astroglia constitute the largest group of glial cells and are involved in numerous actions that are critical to neuronal development and functioning, such as maintaining the blood–brain barrier, forming synapses, supporting neurons with nutrients and trophic factors, and protecting them from injury. These properties are deeply affected in the course of many neurodegenerative diseases, including tauopathies, often before the onset of the disease. In this respect, the transfer of essential amino acids such as glutamate and glutamine between neurons and astrocytes in the glutamate–glutamine cycle (GGC) is one example. In this review, we focus on the GGC and the disruption of this cycle in tau-dependent neurodegeneration. A profound understanding of the complex functions of the GGC and, in the broader context, searching for dysfunctions in communication pathways between astrocytes and neurons via GGC in health and disease, is of critical significance for the development of novel mechanism-based therapies for neurodegenerative disorders.
Molecular Pharmacology in Diabetes
Authors: Reis Flávio , Fernandes Rosa
Published: March 2024

This Special Issue highlights the key molecules and molecular signaling pathways associated with diabetes and its multifaceted complications [...]
TGF-β Signaling Pathways in the Development of Diabetic Retinopathy
Authors: Callan Andrew , Jha Sonal , Valdez Laura , Baldado Lois , Tsin Andrew
Published: March 2024

Diabetic retinopathy (DR), a prevalent complication of diabetes mellitus affecting a significant portion of the global population, has long been viewed primarily as a microvascular disorder. However, emerging evidence suggests that it should be redefined as a neurovascular disease with multifaceted pathogenesis rooted in oxidative stress and advanced glycation end products. The transforming growth factor-β (TGF-β) signaling family has emerged as a major contributor to DR pathogenesis due to its pivotal role in retinal vascular homeostasis, endothelial cell barrier function, and pericyte differentiation. However, the precise roles of TGF-β signaling in DR remain incompletely understood, with conflicting reports on its impact in different stages of the disease. Additionally, the BMP subfamily within the TGF-β superfamily introduces further complexity, with BMPs exhibiting both pro- and anti-angiogenic properties. Furthermore, TGF-β signaling extends beyond the vascular realm, encompassing immune regulation, neuronal survival, and maintenance. The intricate interactions between TGF-β and reactive oxygen species (ROS), non-coding RNAs, and inflammatory mediators have been implicated in the pathogenesis of DR. This review delves into the complex web of signaling pathways orchestrated by the TGF-β superfamily and their involvement in DR. A comprehensive understanding of these pathways may hold the key to developing targeted therapies to halt or mitigate the progression of DR and its devastating consequences.
The Incredible Adventure of Omalizumab
Authors: Domingo Christian , Monserrate Daniel R. , Sogo Ana , Mirapeix Rosa M.
Published: March 2024

The basis of our current understanding of allergies begins with the discovery of IgE in the mid-1960s. The whole theory of the physiology and pathophysiology of allergic diseases, including rhinitis and asthma, dates from that period. Among the key regions of IgE identified were the FAB (fragment antigen binding) portion that has the ability to capture allergens, and the Cε3 domain, through which IgE binds to its membrane receptor. It was then postulated that blocking IgE at the level of the Cε3 domain would prevent it from binding to its receptor and thus set in motion the allergic cascade. This was the beginning of the development of omalizumab, a monoclonal antibody with an anti-IgE effect. In this article, we review the pathophysiology of allergic disease and trace the clinical development of omalizumab. We also review the benefits of omalizumab treatment that are apparently unrelated to allergies, such as its effect on immunity and bronchial remodeling.