bluuebunny/crossref_metadata_2025 huggingface dataset:
Dynamics of Primary Succession in Airborne Microbial Communities on Urban Masonry
Authors: Winn-Swanson Kendall , Kostich Lauren , Castañeda-Childress Mackenzie , Solis Isiah , Remillard Jade , Agustin Avaleen , Gonzalez Demitri , Carmona-Galindo Víctor D.
Published: February 2025

Microbial succession on urban masonry surfaces is a critical yet understudied aspect of environmental microbiology, with implications for public health within the One Health framework. This study investigated how building age, orientation, and vegetative cover influence microbial diversity on masonry, metal, and glass substrates at the University of La Verne, California. Biophysical characterizations were conducted, and microbial communities were analyzed using morphospecies richness and DNA sequencing. Significant variation in microbial species richness (χ2 = 20.3882, p = 0.0011) and diversity (Fisher’s LSD, p < 0.05) was observed. Masonry surfaces exhibited the highest microbial diversity, with a mean richness of 23 morphospecies compared to 14 on metal and 12 on glass. Penicillium fungi dominated masonry sites, comprising 45% of colonies, while Pseudomonas and Klebsiella were more prevalent on metal and glass surfaces (35% and 28%, respectively). Microbial succession did not follow a linear progression but showed non-sequential shifts influenced by local conditions. The abundance of Penicillium, known for antibiotic production, raises concerns about spreading antibiotic resistance genes. Opportunistic pathogens further highlight potential health risks. These findings underscore the importance of understanding primary successional processes in urban environments to manage microbial communities and mitigate public health risks.
Prevalence and Multidrug Resistance in Non-Typhoidal Salmonella in India: A 20-Year Outlook
Authors: Sahu Arpita Arsmika , Sephalika Somya , Mohakud Nirmal Kumar , Sahu Bikash Ranjan
Published: February 2025

Non-typhoidal Salmonella (NTS) infection poses a significant public health challenge globally, particularly in developing countries like India. NTS, predominantly represented by S. enterica serovars, is a major cause of intestinal and extra-intestinal infections. This review provides a comprehensive overview of longitudinal analyses of the prevalence of NTS in different regions of India encountered in the last 20 years and their antimicrobial resistance patterns. We followed several research investigations published during 2000–2024 to examine the incidence and prevalence of different serovars of NTS in several parts of India and followed published articles on NTS showing resistance to different antibiotics. We pointed out NTS serovars, which are predominantly isolated in various human and non-human sources, as observed in several investigations conducted in different regions of India. Our analysis revealed that, among serovars detected from various sources, S. Typhimurium is the most predominant one occurring across both human and non-human sources, followed by S. Enteritidis and S. Weltevreden. The occurrence of similar serovars of Salmonella in both human and non-human sources may be due to zoonotic transmission between animals and humans. Extensive research conducted across many geographic locations reveals that NTS isolates exhibit resistance to several antibiotics, with multidrug-resistance (MDR) being more common. These MDR strains basically show resistance to three or more classes of antibiotics, including critically important antimicrobials such as nalidixic acid, ciprofloxacin, and third-generation cephalosporins. Temporal trends suggest an alarming increase in resistance to these antibiotics, particularly in serovars such as S. Typhimurium and S. Enteritidis. Overall, the current article sheds light on the urgent need for surveillance, judicious antibiotic use, and the development of alternative treatment strategies to combat the rising tide of antibiotic-resistant NTS strains.
Surgical Site Preparation Using Alcohol with Chlorhexidine Compared with Povidone Iodine with Chlorhexidine Results in Similar Rate of Infection After Primary Total Joint Arthroplasty
Authors: Hanish Stefan J. , Kirwan Mateo J. , Hou Nuanqiu , Coble Tori J. , Mihalko William M. , Holland Christopher T.
Published: February 2025

Background: Periprosthetic joint infection (PJI) is a devastating complication after total joint arthroplasty. A skin antiseptic solution is used to reduce the bacterial count and prevent PJI. There is no consensus in the literature on the application of antiseptic solutions. This study aims to compare the rate of infection between patients who received alcohol wash with Chloraprep to those who received povidone iodine wash with Chloraprep. Methods: A total of 607 patients who underwent total hip arthroplasty (THA) and total knee arthroplasty (TKA) at a single institution between January 2009 and July 2023 were reviewed. Perioperative variables were collected. The infection rate was used as a primary outcome. An odds ratio was calculated to compare infection and complication rates between the groups. Results: For patients who underwent THA, no difference in the rate of complications (alcohol wash: n = 6, 4.5%; povidone wash: n = 5, 3.6%; OR: 0.796; 95% CI: 0.237–2.673) or infection (alcohol wash: n = 1, 0.7%; povidone wash: n = 2, 1.4%; OR: 1.942; 95% CI: 0.174–21.667) was found. No difference in the rate of complications (alcohol wash: n = 3, 1.9%; povidone wash: n = 2, 1.2%; OR: 0.635; 95% CI: 0.105–3.849) or infection (alcohol wash: n = 0; povidone wash: n = 1, 0.6%; OR: 0.994; 95% CI: 0.983–1.006) was found in patients who underwent TKA. Conclusions: Surgical site preparation using alcohol wash with chlorhexidine offers similar short-term benefits in preventing postoperative infection to a povidone iodine wash with chlorhexidine in primary total joint arthroplasty. The use of alcohol wash and chlorhexidine is effective, while reducing the preparation time.
Agar-Dilution Is Comparable to Broth Dilution for MIC Determination in Streptococcus agalactiae
Authors: Portal Edward A. R. , Farley Caitlin , Iannetelli Teresa , Coelho Juliana , Efstratiou Androulla , Bentley Stephen D. , Chalker Victoria J. , Spiller Owen B.
Published: February 2025

Background: Streptococcus agalactiae (Group B Streptococcus, GBS) is a leading cause of neonatal sepsis in high-income countries. While intrapartum antibiotic screening reduces this risk, increasing resistance to macrolides and lincosamides in Europe since the 1990s has limited therapeutic options for penicillin-allergic patients. Reports of reduced beta-lactam susceptibility in GBS further emphasise the need for robust antimicrobial resistance (AMR) surveillance. However, broth microdilution (BMD) methods are unsuitable for large-scale antimicrobial susceptibility testing (AST). Objective: To demonstrate that agar-dilution AST provides equivalent results to broth dilution methods, with superior capacity for high-throughput screening. Methods: Agar-dilution and microdilution AST methods were compared using a panel of 24 characterised susceptible and resistant GBS strains for benzylpenicillin, chloramphenicol, clindamycin, erythromycin, gentamicin, levofloxacin, tetracycline, and vancomycin. Minimum inhibitory concentration (MIC) agreements were evaluated, and resistance profile correlations were assessed using Cohen’s kappa values. Results: Agar-dilution demonstrated >90% agreement with BMD MIC for most antimicrobials, except vancomycin (87.5%), erythromycin (83.33%), and tetracycline (52.78%). Cohen’s kappa values indicated strong agreement (0.88–1.00) for resistance determination. Agar-dilution avoided “trailing growth” issues associated with BMD and facilitated easier detection of non-GBS contaminants. Conclusions: Agar-dilution is a valid method for high-throughput AMR surveillance of retrospective cohorts (96 isolates per plate) and is critical for identifying emerging GBS resistance trends and informing therapeutic guidelines. However, due to the large number of plates required per antimicrobial, it is impractical for routine clinical diagnostics.
Pet Owners’ Knowledge of Antibiotic Use and Antimicrobial Resistance and Their Antibiotic Practices: Comparison Between Contexts of Self and Pet
Authors: Aithal Seema , Guo Huiling , Teo Boon Han , Chua Timothy , Hildon Zoe Jane-Lara , Chow Angela
Published: February 2025

Objective: This study aimed to compare pet owners’ knowledge of antibiotic use, understanding of antimicrobial resistance (AMR) and antibiotic practices for themselves and their pets to guide behavioral interventions to reduce AMR. Methods: A cross-sectional study conducted between March 2023 and December 2023 involved 1080 pet owners recruited from 16 veterinary clinics in Singapore. An anonymous self-administered survey assessed the participants’ knowledge of antibiotic use and AMR as well as their adherence to recommended antibiotic practices for themselves and their pets. McNemar’s Chi-square test was used to identify significant differences in the outcome variables between self and pets. The differences between the type of pet owned (dog owner/non-dog owner) were assessed using Pearson’s Chi-square test. Results: Among the 1080 pet owners surveyed, poorer knowledge of antibiotic use (46.3% vs. 33.2%; p < 0.001) and inappropriate antibiotic use (33.9% vs. 23.5%; p < 0.001) was more common for participants’ pets than for themselves. Compared to dog owners, non-dog owners had poorer knowledge of antibiotic use for their pets (poor knowledge, 55.2%; 42.4%; p < 0.001), but the knowledge of AMR occurrence and antibiotic practices did not differ between the dog owners and the non-dog owners. Conclusions: Pet owners have significantly poorer antibiotic use knowledge and antibiotic practices for their pets than for themselves. Compared to dog owners, non-dog owners have poorer knowledge of antibiotic use. Educational initiatives addressing pet owners’ knowledge deficits may improve their antibiotic practices for their pets and themselves, emphasizing the importance of cross-sectoral One Health planning.
Effect of OSEM Reconstruction Iteration Number and Monte Carlo Collimator Modeling on 166Ho Activity Quantification in SPECT/CT
Authors: Albergueiro Rita , Antunes Vera , Santos João
Published: February 2025

Background: Accurate reconstruction and quantification in the post-therapy SPECT/CT imaging of 166Ho microspheres for hepatic malignancies is crucial for treatment evaluation. This present study aimed to explore the impact of the OSEM reconstruction parameters on SPECT/CT image features for dose distribution determination, using Hybrid Recon™ (Hermes Medical Solutions AB) and full Monte Carlo (MC) collimator modeling. Methods: Image quality and activity quantification were assessed through two acquisitions of the Jaszczak phantom using a Siemens Symbia Intevo Bold SPECT/CT system. The datasets were reconstructed using the OSEM method, with variations in the number of iterations for 15 and 8 subsets, both with and without full MC collimator modeling. Contrast recovery coefficient (QH), coefficient of variation (CV), contrast-to-noise ratio (CNR), calibration factor (CF), and activity recovery coefficient (ARC) were calculated and used to evaluate image quality and activity quantification. Results: Reconstructions with 5 iterations and 15 subsets, as well as 10 iterations and 8 subsets, were selected as the most suitable for 166Ho imaging, as they provided higher QH and ARCs. Incorporating full MC collimator modeling in both reconstructions led to significant improvements in image quality and activity recovery. The CFs remained consistent for a fixed value of 15 and 8 subsets, with values of (14.9 ± 0.5) cps/MBq and (14.6 ± 0.5) cps/MBq, respectively. However, when applying full collimator modeling, the CF values decreased to a range between 10.9 and 12.1 cps/MBq. Conclusions: For 166Ho SPECT/CT imaging, OSEM (with either 5 iterations and 15 subsets or 10 iterations and 8 subsets) combined with full MC collimator modeling yielded superior image quality and quantification results.
Assessment of Transport Value and Environmental Impact of Automotive Driving: A Physical-Action-Based Approach
Authors: Müller J. Gerhard
Published: February 2025

This paper is concerned with the problem of assigning, in a physically transparent way, value to automotive transport services and their related environmental impacts. We discuss the idea that the transport value of an automotive service can be measured in units of physical action, i.e., in terms of the physical entity that measures the effect of work performed within a specified physical process. It is further argued that from this action-based transport value, two dimensionless figures of merit (FOM), TV and ETV, can be derived, which can be used as cost factors in algorithms designed to optimize transport services and logistic networks.
Experimental Identification of Characteristic Curves of Supersonic Vacuum Ejector and Empirical Prediction of Total Evacuation Time
Authors: Macia Llorenç , Castilla Robert , Raush Gustavo , Gamez-Montero Pedro Javier
Published: February 2025

Supersonic vacuum generators, or ejectors, operate pneumatically to extract air from tanks in industrial applications. A key performance metric for ejectors is the Total Evacuation Time (TET), which measures the time required to reach minimum pressure. This research predicts TET using empirical models that rely on two key metrics: the characteristic curve, which relates absorbed flow rate to the working pressure, and the polytropic curve, which describes the evolution of the polytropic coefficient across working pressures. Accurately capturing both curves for subsequent fitting to polynomial curves is crucial for forecasting TET. Several experimental setups were employed to capture the curves, each of which refined the data and improved the quality of the polynomial fits and coefficients. Multiple setups were necessary to pinpoint the breakpoint, from supersonic to subsonic operation mode, which is a critical factor that affects the characteristic curve and the TET. Furthermore, the research shows an improvement in the TET forecasts for each setup, with deviations between experimental and predicted TET ranging from 7.6% (14.5 s) to a 1.4% (2.6 s) in the most precise setup. Once the models were validated, an optimized ejector design, extracted from an author’s previous article, was tested. It revealed a 4% improvement (8 s) in the TET. These results highlight the importance of the mathematical models developed, which can be used in the future to compare ejectors and reduce the need for experimental data.
Realistic Data Delays and Alternative Inactivity Definitions in Telecom Churn: Investigating Concept Drift Using a Sliding-Window Approach
Authors: Bugajev Andrej , Kriauzienė Rima , Chadyšas Viktoras
Published: February 2025

Predicting customer churn is essential for telecommunications companies to maintain profitability. However, training models on historical models leads to performance degradation when they are applied to future conditions—a phenomenon known as concept drift. We employ a sliding-window approach that separates the training and testing time windows, creating a future-based “true test”. Using unique real data, we show that a CatBoost classifier model trained on older data can remain relevant when new, unseen intervals are used. A key innovation of our work is the use of 40-day “partial churn” labels; a model trained on these labels accurately predicts 90-day churn by simply adjusting the decision threshold. Out of the six modeled scenarios, in the main realistic scenario, CatBoost retained an accuracy above 0.798 and an F1 of near 0.704, reflecting its robustness even under real-world delays and potential drift. Overall, our findings emphasize that models do not necessarily “expire” with time; rather, their performance varies according to when they are tested. This research underscores the importance of a truly future-based evaluation (instead of artificial splits) and offers practical guidance for earlier churn detection when facing real-world data delays.
Development of N-Acetylneuraminic Acid Reference Material from Fermentation Products
Authors: Lan Tao , Chen Xiangsong , Yuan Lixia , Wang Wei , Yao Jianming , Wu Jinyong , Xu Dunming
Published: February 2025

N-acetylneuraminic acid (NANA) is a key ingredient in bird’s nest, as well as in health products and infant formulas. However, the absence of suitable reference materials (RMs) makes it challenging to ensure the quality of these products. Currently, NANA is primarily extracted from bird’s nest, but this process is costly and difficult to scale up. In this study, we successfully prepared a large-scale yield of NANA RM from fermentation products, which increases the yield of the RM and reduces its cost. IR, MS, and NMR methods were used for the qualitative analysis of the NANA RM, and HPLC was used for homogeneity and stability testing. The F test showed that the NANA RM remained stable over a 12-month period. In collaboration with eight quantification laboratories in China, the certified value and uncertainty of the NANA RM were calculated. The certified value of the NANA RM is 98.26%, with an expanded uncertainty of 0.10% (k = 2). This prepared NANA RM can now be used for quality control in bird’s nest, health products, infant-formula-related food products, medicine, and cosmetics.
Optimization of Ship Permanent Magnet Synchronous Motor ADRC Based on Improved QPSO
Authors: Xu Hongbo , Zhang Jundong , Liu Jiale , Cao Yang , Ma Ao
Published: February 2025

To address the impact of load variations, external environmental changes, and the tuning of the parameters on Permanent Magnet Synchronous Motors (PMSMs) used in ships, this study proposes an Active Disturbance Rejection Control (ADRC) strategy for PMSMs, optimized by the Quantum-behaved Particle Swarm Optimization (QPSO) algorithm. First, based on the PMSM model, the study addresses the limited disturbance rejection capability of the traditional fal function in the Extended State Observer (ESO) of conventional ADRC. To improve the accuracy of the state observer, the faln function is introduced as a replacement for the traditional fal function. Second, due to the numerous parameters in ADRC, which are difficult to tune, the QPSO algorithm—known for its strong global search capabilities and fast convergence speed—is utilized for parameter optimization. Additionally, the position update formula within the optimization algorithm is revised and optimized. Finally, simulation experiments are conducted using the Matlab/Simulink platform, where practical conditions, such as load fluctuations and random noise, are incorporated. The simulation results demonstrate that, compared to PSO-ADRC control, IPSO-ADRC control, and ICFO-ADRC control, the proposed method offers a superior dynamic response. Specifically, the speed control accuracy is improved by 46.7%, torque ripple is reduced by 50.8%, and harmonic distortion decreases by 23.1%. These results highlight the significant advantages of this method in enhancing system robustness, dynamic response speed, and steady-state accuracy, making it particularly suitable for PMSM control systems in complex dynamic environments, such as those encountered on ships.
A Multi-Objective Nutcracker Optimization Algorithm Based on Cubic Chaotic Map for Numerical Association Rule Mining
Authors: Hu Qiwei , Hu Shengbo , Liu Mengxia
Published: February 2025

Traditional numerical association rule mining optimization algorithms have limitations in handling discrete attributes, and they are susceptible to becoming trapped in local optima, uneven population distribution, and poor convergence. To address these challenges, we propose a multi-objective nutcracker optimization algorithm based on a cubic chaotic map (C-MONOA), specifically designed for mining association rules from mixed data (continuous and discrete). Unlike existing models, C-MONOA leverages a chaotic map for population initialization, alongside Michigan rule encoding, to dynamically optimize feature intervals during the optimization process. This algorithm integrates continuous and discrete data more effectively and efficiently. This article uses support, confidence, Kulc metric, and comprehensibility as evaluation indicators for multi-objective optimization. The experimental results show that C-MONOA performs well in rule scoring and can generate frequent, simple, and accurate rule sets. This study extends the association rule mining method for mixed data, demonstrating high performance and robustness and providing new technical tools for application fields such as market analysis and disease prediction.
Lactiplantibacillus plantarum, the Integral Member of Vegetable Fermentations
Authors: Paramithiotis Spiros
Published: February 2025

Lactiplantibacillus plantarum is omnipresent in vegetable fermentations. Its large metabolic capacity and its ability to adapt to the fermenting microenvironment enable this species, in many cases, to dominate the microecosystem and drive the fermentation. In addition, its metabolic capacity enables it to produce bioactive compounds of great interest for human health. These attributes have directed research for many decades. The widespread application of next-generation sequencing approaches has enabled the genotypic verification of the phenotypically assessed attributes and supplemented them with novel insights, justifying the characterization of a multifunctional tool that has been awarded to this species. However, there are still issues that need to be properly addressed in order to improve our understanding of the microecosystem functionality and to enhance our knowledge regarding the capacities of this species. The aim of the present article is to collect and critically discuss the available information on Lp. plantarum subsistence in vegetable fermentations.
A Review of Deep Learning Techniques for Leukemia Cancer Classification Based on Blood Smear Images
Authors: Oybek Kizi Rakhmonalieva Farangis , Theodore Armand Tagne Poupi , Kim Hee-Cheol
Published: February 2025

This research reviews deep learning methodologies for detecting leukemia, a critical cancer diagnosis and treatment aspect. Using a systematic mapping study (SMS) and systematic literature review (SLR), thirty articles published between 2019 and 2023 were analyzed to explore the advancements in deep learning techniques for leukemia diagnosis using blood smear images. The analysis reveals that state-of-the-art models, such as Convolutional Neural Networks (CNNs), transfer learning, Vision Transformers (ViTs), ensemble methods, and hybrid models, achieved excellent classification accuracies. Preprocessing methods, including normalization, edge enhancement, and data augmentation, significantly improved model performance. Despite these advancements, challenges such as dataset limitations, the lack of model interpretability, and ethical concerns regarding data privacy and bias remain critical barriers to widespread adoption. The review highlights the need for diverse, well-annotated datasets and the development of explainable AI models to enhance clinical trust and usability. Additionally, addressing regulatory and integration challenges is essential for the safe deployment of these technologies in healthcare. This review aims to guide researchers in overcoming these challenges and advancing deep learning applications to improve leukemia diagnostics and patient outcomes.
Study of the Current–Voltage Characteristics of Membrane Systems Using Neural Networks
Authors: Kirillova Evgenia , Kovalenko Anna , Urtenov Makhamet
Published: February 2025

This article is dedicated to the construction of neural networks for the prediction of the current–voltage characteristic (CVC). CVC is the most important characteristic of the mass transfer process in electro-membrane systems (EMS). CVC is used to evaluate and select the optimal design and effective operating modes of EMS. Each calculation of the CVC at the given values of the input parameters, using developed analytical-numerical models, takes a lot of time, so the CVC is calculated in a limited range of parameter changes. The creation of neural networks allowed for the use of prediction to obtain the CVC for a wider range of input parameter values and much faster, saving computing resources. The regularities of the behavior of CVC for various values of input parameters were revealed. During this work, several different neural network architectures were developed and tested. The best predictive results on test samples are given by the neural network consisting of convolutional and LSTM (Long Short-Term Memory) layers.
Source Contribution Analysis of Polycyclic Aromatic Hydrocarbons in PM2.5 at Three Japanese Cities Using Positive Matrix Factorization with Organic Tracers
Authors: Ikemori Fumikazu , Murakami Yuki , Takabayashi Megumi , Nishimura Rie , Hiramatsu Mami , Ueda Maku , Yoshino Ayako , Chatani Satoru , Sato Kei , Sugata Seiji
Published: February 2025

To estimate the sources of polycyclic aromatic hydrocarbons (PAHs) and their contributions to the total PAH emissions, more than 40 PAHs and organic tracers in PM2.5 collected in 3 cities of Japan were measured and a positive matrix factorization (PMF) model analysis was performed. During the warm season, high PAH concentrations were detected in Nagoya, which is located in the port area. Total PAHs were classified into five sources: biomass combustion, semivolatile PAHs, and ship and industrial emissions, which were major, and road traffic and plastic combustion, which were minor. Analysis of the ship and industrial emissions revealed that the concentrations of these sources in the severe PAH pollution event in Nagoya exceeded 15 ng/m3 and the significant contribution exceeded 80%. In addition, PAHs indicating a risk of carcinogenicity, such as 1 to 2B by IARC and 1 to B2 by U.S. EPA, had the highest contribution to this factor among the five factors such as biomass burning and ship and industrial emissions. Our results suggest that sources of high PAH emissions exist in the port areas of Nagoya. The PMF analysis performed in this study, using combustion organics as indicators, is expected to aid other countries and regions in identifying the sources of PAHs for their effective control.
Atmospheric Estrogenic Semi-Volatile Compounds and PAH in PM2.5 in Mexico City
Authors: Ronderos-Lara José Gustavo , Millán-Vázquez Fernando , Murillo-Tovar Mario Alfonso , Saldarriaga-Noreña Hugo Albeiro , Valle-Hernández Brenda Liz , López-Velázquez Khirbet , Mugica-Álvarez Violeta
Published: February 2025

The quantification of semi-volatile organic compounds with potential endocrine-disrupting activity contained in fine atmospheric particles (PM2.5) is essential to understand their temporal behavior, identify their sources, and evaluate the health risks resulting from population exposure to said compounds. Since information and research outcomes regarding their presence in the atmosphere in developing countries are scarce, the main objective of this work was the development of a methodology devoted to extracting, characterizing, and quantifying, for the first time in Mexico, the concentration levels of three important groups of endocrine-disrupting compounds (EDCs) bonded to PM2.5 and collected during a year, namely: alkylphenols (4-n-nonylphenol (4NP) and 4-tert-octylphenol (4tOP)); bisphenols (bisphenol A (BPA) and bisphenol F (BPF)); natural and synthetic hormones (17β-estradiol (E2), estriol (E3) and 17α-ethinyl estradiol (EE2)). Further, priority polycyclic aromatic hydrocarbons (PAH) that also disrupt endocrine activity were analyzed. All compounds were determined by gas chromatography coupled to tandem mass spectrometry, and the concentration levels were analyzed for different climatic seasons. Cold-dry (CD) season displayed higher levels of 4NP, bisphenols, and hormones (between 0.71 (4NP) and 1860 pg m−3 (BPA)), as well as PAH concentrations (9.12 ng m−3). Regarding health effects, concentrations of alkylphenols, bisphenols, and hormones quantified had a value of estradiol equivalent concentration (EEQE2) between 0.07 and 0.17 ng m−3. PAH concentrations did not have carcinogenic and mutagenic risk with BaP(PEQ) < 1 ng m−3. These results can be used by policymakers in the design of strategies for air pollution control.
Volatile Organic Compounds in Early Childhood Education Facilities: Simultaneous Indoor and Outdoor Measurements in the Haifa Bay Area
Authors: Darzi Ran , Bareket Merav , Yuval  , Dubowski Yael
Published: February 2025

Indoor air quality (IAQ) is of great importance, as people spend up to 90% of their time indoors, leading to significant exposure to air pollutants. The IAQ in early childhood education (ECE) facilities is of particular interest since young children are more vulnerable and poor air quality may have possible long-lasting impacts on them. In the present study, simultaneous indoor and outdoor VOC measurements were carried out in three ECE facilities in the Haifa Bay area, Israel. Three sampling campaigns were utilized, each lasted for a minimum of one week, encompassing four consecutive working days and at least one weekend. During working days, sampling was performed during daytime activity hours and at nighttime (off hours). Twenty-three VOCs were identified, quantified, and classified into six chemical groups—aromatic hydrocarbons, aliphatic alkanes, terpenes, alcohols, carbonyls, and “others”. The total outdoor VOC concentration was 23 μg m−3 during the daytime and 22 μg m−3 at night, with carbonyls and aromatic hydrocarbons accounting for ~80% of it. Despite the heterogeneity of the study area, outdoor concentrations depicted a smaller spatial and temporal variability than was observed indoors. In the ECE facilities, the total VOC reached 134 and 204 μg m−3 during the daytime and nighttime, respectively, and were strongly impacted by the air exchange rate. Carbonyls, alcohols, and terpenes were more prevalent indoors, accounting for 77.5–81.1% of the total. Their high indoor/outdoor ratios, especially for formaldehyde and limonene, suggest a significant contribution from indoor emission sources. Exposure calculations were compared to reference values for carcinogenic and non-carcinogenic effects. While the lifetime average daily dose (LADD) did not exceed the available reference values, the upper-limit estimates of continuous lifetime exposure to measured indoor levels indicate that formaldehyde and acetaldehyde surpassed their respective limits by factors of 10 and 3, respectively.
Prediction of In Vivo Knee Mechanics During Daily Activities Based on a Musculoskeletal Model Incorporated with a Subject-Specific Knee Joint
Authors: Zhang Li , Li Hui , Wan Xianjie , Xu Peng , Zhu Aibin , Wei Pingping
Published: February 2025

The objective of this study was to develop a musculoskeletal model incorporated with a subject-specific knee joint to predict the tibiofemoral contact force (TFCF) during daily motions. For this purpose, 18 healthy participants were recruited to perform the motion data acquisition using synchronized motion capture and force platform systems, and motion simulation based on an improved musculoskeletal model for five daily activities, including normal walking, stair ascent, stair descent, sit-to-stand, and stand-to-sit. The proposed musculoskeletal model included subject-specific models of bones, cartilages, and meniscus, detailed knee ligaments and muscles, deformable elastic contacts, and multiple degrees of freedom (DOFs) of the knee joint. The prediction accuracy was demonstrated by the good agreements of TFCF curves between the model predictions and in vivo measurements for the five activities (RMSE: 0.216~0.311 BW, R2: 0.928~0.992, and CE: 0.048~0.141). Based on the validated model, the TFCF on total, medial, and lateral compartments (TFCFTotal, TFCFMedial, and TFCFLateral) during the five daily activities were predicted. For TFCFTotal, the peak force for stair descent or sit-to-stand was the largest, followed by stair ascent or stand-to-sit, and finally normal walking. For TFCFMedial, stair descent had the largest peak, followed by stair ascent. There were no significant differences between the peak TFCFMedial values of normal walking, sit-to-stand, and stand-to-sit. For TFCFLateral, the peak of sit-to-stand was the largest, followed by stand-to-sit or stair descent, and finally normal walking or stair ascent. This study is valuable for further understanding the biomechanics of a healthy knee joint and providing theoretical guidance for the treatment of knee osteoarthritis (KOA).
Chemical Production Based on Biomass—Potential and Limits
Authors: Kircher Manfred
Published: February 2025

As the raw material transition from fossil to renewable feedstock progresses, the demand for biogenic raw materials for industrial purposes will increase. This applies above all to the energy and chemical sectors. However, the capacities for biogenic energy and carbon sources to be provided by agriculture and forestry are limited. This review examines the contribution that biogenic raw materials and CO2 from biogenic sources can make to sustainable chemical production in the EU. It analyses statistical data from the EU and studies from the chemical industry. First priority needs to be given to edible biomass for the sector of nutrition. When it comes to the industrial use of biomass, sectors should be prioritised that cannot do without carbon-supplying raw materials. This is particularly the case in the field of organic chemistry. This review focuses on bio-based organic chemical products and gives an outlook on the future of chemical production in Europe based on primary, secondary, and tertiary biomass and CO2 from biogenic sources. Finally, two new indicators for economically and ecologically sustainable industrial use of biomass are proposed. Both indicators can support the determination of the sustainability status of the sustainable integration of agriculture, forestry, residual, and biowaste management in bioeconomic value networks.
Patient-Derived Cancer-Associated Fibroblasts Support the Colonization of Tumor Cells in Head and Neck Squamous Cell Carcinoma
Authors: Federspiel Julia , Steinbichler Teresa Bernadette , Vorbach Samuel Moritz , Eling Marie Theres , Borena Wegene , Seifarth Christof , Hofauer Benedikt Gabriel , Dudas Jozsef
Published: February 2025

Background: The crosstalk between cancer-associated fibroblasts (CAFs) and tumor cells promotes proliferation, tumor relapse, and the acquisition of a partial epithelial-to-mesenchymal (pEMT) phenotype in tumor cells. The aim of this study was to investigate the effects of patient-derived CAFs on tumor cell growth and radioresistance in head and neck squamous cell carcinoma (HNSCC). Methods: CAFs were isolated and cultured in a three-dimensional spheroid formation. SCC-25 tumor cells educated by the CAFs (SCC25-E cells) were subjected to irradiation, and the response of the CAF-stimulated tumor cells to radiotherapy was determined using an MTT assay, a clonogenic assay, and Western blotting. Tumor cell morphological changes and growth dynamics were assessed using 3D holotomographic microscopy and a live video microscope. Results: Patient-derived CAFs significantly increased the growth rate of SCC-25 cells. CAFs drove fibrosis in the tumor microenvironment (TME), functioned as a physical barrier, temporarily stopped tumor growth, and induced the p38 mitogen-activated protein kinase (MAPK) signaling pathway. Viability after irradiation at 4–8 Gy was significantly higher in SCC25-E cells than in the controls (p = 8 × 10–4 or lower). Furthermore, irradiation triggered the pEMT profile in HNSCC cells. Conclusions: CAFs’ education of tumor cells and the induced p38 phosphorylation had no influence on irradiation sensitivity. SCC25-E cultures demonstrated increased tumor cell growth, viability, and stress-induced phospho-p38 activation.
Consecutive Affinity and Ion-Exchange Chromatography for AAV9 Vectors Purification
Authors: Duzenli Ozgun Firat , Aslanidi George
Published: February 2025

Background: Irrespective of the rapid development of AAV-based gene therapy, the production of clinical-grade vectors has a bottleneck resulting from product-related impurities such as empty and partially filled capsids, which lack a functional recombinant genome. Methods: In the current study, we applied the sequential affinity chromatography (AC)- and anion-exchange chromatography (AEX)-based method for purification of AAV9 vector harboring single-stranded genome encoding the fusion of firefly luciferase (fLuc)-yellow fluorescent protein (YFP) under chicken beta actin (CBA) promoter. We assessed the efficiency of two different pre-packed cross-linked sepharose and one monolithic AEX columns following AC purification to separate fully encapsulated with recombinant DNA AAV vectors from byproducts. Results: We showed the possibility to achieve approximately 20–80% recovery and over 90% calculated DNA-containing/empty capsid ratio depending on column and buffers composition. Additionally, we confirmed the infectivity of AAV by in vitro luciferase assay regardless of recovery method from different AEX columns. Conclusions: Our purification data indicate the effectiveness of dual chromatography method to obtain rAAV9 vectors with DNA-containing capsid content over 90%.
Hypoxia-Regulated CD44 and xCT Expression Contributes to Late Postoperative Epilepsy in Glioblastoma
Authors: Kusakabe Kosuke , Inoue Akihiro , Ohnishi Takanori , Nakamura Yawara , Ohtsuka Yoshihiro , Nishikawa Masahiro , Yano Hajime , Choudhury Mohammed E. , Murata Motoki , Matsumoto Shirabe , Suehiro Satoshi , Yamashita Daisuke , Shigekawa Seiji , Watanabe Hideaki , Kunieda Takeharu
Published: February 2025

Background/Objectives: Late epilepsy occurring in the late stage after glioblastoma (GBM) resection is suggested to be caused by increased extracellular glutamate (Glu). To elucidate the mechanism underlying postoperative late epilepsy, the present study aimed to investigate the expressions and relations of molecules related to Glu metabolism in tumor tissues from GBM patients and cultured glioma stem-like cells (GSCs). Methods: Expressions of CD44, xCT and excitatory amino acid transporter (EAAT) 2 and extracellular Glu concentration in GBM patients with and without epilepsy were examined and their relationships were analyzed. For the study using GSCs, expressions and relationships of the same molecules were analyzed and the effects of CD44 knock-down on xCT, EAAT2, and Glu were investigated. In addition, the effects of hypoxia on the expressions of these molecules were investigated. Results: Tumor tissues highly expressed CD44 and xCT in the periphery of GBM with epilepsy, whereas no significant difference in EAAT2 expression was seen between groups with and without epilepsy. Extracellular Glu concentration was higher in patients with epilepsy than those without epilepsy. GSCs displayed reciprocal expressions of CD44 and xCT. Concentrations of extracellular Glu coincided with the degree of xCT expression, and CD44 knock-down elevated xCT expression and extracellular Glu concentrations. Hypoxia of 1% O2 elevated expression of CD44, while 5% O2 increased xCT and extracellular Glu concentration. Conclusions: Late epilepsy after GBM resection was related to extracellular Glu concentrations that were regulated by reciprocal expression of CD44 and xCT, which were stimulated by differential hypoxia for each molecule.
Update on the Study of Angiogenesis in Surgical Wounds in Patients with Childhood Obesity
Authors: Chelmu Voda Cristina , Stefanopol Ioana Anca , Gurau Gabriela , Hîncu Maria Andrada , Popa Gabriel Valeriu , Mateescu Olivia Garofita , Baroiu Liliana , Mehedinti Mihaela Cezarina
Published: February 2025

Background: Angiogenesis, the formation of new blood vessels from pre-existing ones, plays a pivotal role in wound healing, particularly in surgical contexts. Methods and results: However, this process can be significantly impaired in patients with childhood obesity, resulting in delayed healing and additional complications. The biological process of wound healing is complex, involving angiogenesis, cell proliferation, inflammation, and tissue remodeling. This review aims to explore recent advancements in research on angiogenesis in surgical wounds in patients with childhood obesity, with a focus on growth factors, inflammation, microcirculation, and innovative therapeutic strategies. Conclusions: It highlights therapeutic approaches such as the administration of growth factors and the application of biomaterials to enhance angiogenesis.
The Effect of GO Flake Size on Field-Effect Transistor (FET)-Based Biosensor Performance for Detection of Ions and PACAP 38
Authors: Lee Seungjun , Park Jongdeok , Song Jaeyoon , Lee Jae-Joon , Kim Jinsik
Published: February 2025

The performance development of rGO-FET biosensors by analyzing the influence of GO flake size on biosensing efficacy. GO flakes of varying sizes, from 1 µm to 20 µm, were prepared under controlled conditions, followed by characterization through SEM and XPS to evaluate their size, surface area, and C/O ratio. The biosensing performance was systematically assessed by rGO-FET biosensors, examining the effects of GO flake size, C/O ratio, and film thickness. PACAP38 was employed as a biomarker for receptor-mediated detection, while chlorine ions served as model analytes for receptor-free small molecule detection. The results indicate that decreasing the GO flake size enhanced the performance for both target biomolecules. These findings highlight the crucial importance of selecting GO flake sizes specific to target analytes and detection strategies, thereby optimizing biosensor efficiency.
Student Burnout: A Review on Factors Contributing to Burnout Across Different Student Populations
Authors: Chong Liang Zhe , Foo Lee Kien , Chua Sook-Ling
Published: February 2025

Burnout refers to a process of chronic response to stress in life. For students, burnout can be caused by the stress related to their study. There are many factors that contribute to burnout in different student populations. The objective of this paper is to review the studies that investigated the factors contributing to burnout in various student populations. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, we selected 38 recent studies, published between 2019 and 2024. The findings of this review outline the study design, burnout questionnaire, factors investigated, and analysis methods employed in the literature. We further discuss the main factors contributing to student burnout and propose ways to mitigate this issue.
Gig Regulation: A Future Guide for the Construction Industry
Authors: Aigbe Fortune , Aigbavboa Clinton , Aliu John , Amusan Lekan
Published: February 2025

Technology has led to the advent of digitally enabled workforces like the gig workforce, but a number of issues confront this workforce. This study aims to identify the various issues facing the gig workforce as well as the regulatory measures and regulatory interactions proposed to guide stakeholders in addressing these challenges. This study is a review, with the methodology primarily based on secondary sources of data collection like journals and articles. This study reveals that the construction industry is not immune to the use of the gig workforce, as it often performs project-based construction work, jobs requiring highly specialized skills and commodity service jobs. This study also reveals that the gig workforce is confronted with primarily gig economy-induced platform-based challenges, such as the new nature of work, i.e., exploitative, precarious, and dangerous labour. Furthermore, this study also reveals that these issues can be addressed primarily through regulatory means and regulatory interactions between proposed regulatory measures and existing labour laws, which could be by Coordination, Competition, etc. This aligns with SDG 8, i.e., Decent Work and Economic Growth, as concerns issues related to their benefits, and SDG 10, i.e., Reduced Inequalities, as concerns issues related to their employment relations. The implication of this study for construction stakeholders relates to the development of new regulations and providing a valuable tool for analysing regulatory landscapes and understanding the dynamics of regulatory change, which contributes to scholarly discussions on fair labour practices and the protection of gig workers and helps inform policymaking that will help attract, motivate, retain, and engage more gig workers in the construction industry, which will foster proper workforce management.
Evaluating the Coupling Coordination Levels and Critical Obstacle Indicators of Urban Infrastructure Resilience: A Case Study in China
Authors: Chen Min , Zhang Qian , Jiang Yu , Wang Jinpeng , Zhu Shiyao
Published: February 2025

Natural and man-made disasters significantly challenge the safety and stability of urban infrastructure (UI), disrupting daily operations and impeding economic development. However, existing research on urban infrastructure resilience (UIR) lacks comprehensive categorization of critical infrastructure, insufficiently considers the impacts of natural disasters, and offers limited empirical analysis of the interactions among the pressure, state, and response (PSR) dimensions. This study aims to establish a comprehensive UIR assessment index and examine the coupling coordination (CC) levels and critical obstacle indicators of PSR resilience across four Chinese municipalities. The results reveal that (1) response resilience is most influential on overall coupling and is more amenable to artificial interventions than pressure and state resilience; (2) generally, the CC levels of PSR in the four municipalities were relatively high, advancing from an inferiorly to an intermediately balanced development stage over the study period, highlighting effective strategies such as enhanced resource allocation and post-disaster recovery initiatives are recommended for adoption by similar cities; and (3) critical obstacle indicators impeding UIR development were identified, and targeted interventions were proposed based on each municipality’s unique characteristics. The research findings offer theoretical insights and practical implications for enhancing UIR from the perspective of utilizing CC and PSR models.