bluuebunny/crossref_metadata_2025 huggingface dataset:
Impacts of Protein and Energy Levels on Rumen Fermentation and Microbial Activity Under Different Incubation Temperatures
Authors: Jo Yong-Ho , Kim Won-Seob , Kim Yoo-Rae , Ju Mun-Su , Nejad Jalil Ghassemi , Lee Hong-Gu
Published: October 2024

This study aimed to explore the effects of different incubation temperatures on ruminal fermentation and rumen microorganisms and determine the appropriate protein and energy levels to enhance microbial protein synthesis using an in vitro system. Rumen inoculum was collected from two fistulated Holstein heifers (trial 1: BW: 652.3 kg ± 25.2; trial 2: BW: 683.3 kg ± 30.2) and assessed using a closed-batch culture system. The experimental model employed a 2 × 5 factorial arrangement using incubation temperatures set to 39 and 41 °C, with protein levels set to 12.0, 13.5, 15.0, 16.5, and 18.0% of DM in trial 1 or with energy levels set to 2.4, 2.5, 2.6, 2.7, and 2.8 Mcal/kg of DM in trial 2. The data were analyzed using the MIXED procedure. The results showed increased (p < 0.05) NH3-N concentrations and total volatile fatty acids (TVFAs) with higher incubation temperatures, while the liquid-associated bacterial (LAB) amounts decreased (p < 0.05) in trials 1 and 2. The interaction between the energy level and incubation temperature affected (p < 0.05) the LAB protein levels in trial 2. Higher protein levels led to increased (p < 0.05) NH3-N and acetate concentrations, but it decreased (p < 0.05) the propionate percentage. Conversely, higher energy levels decreased (p < 0.05) the amount of acetate and increased the propionate concentration, altering the acetate-to-propionate ratio. However, no interaction involving TVFA and LAB was observed between the incubation temperature and the protein or energy levels. Changes in the NH3-N, TVFAs, and LAB protein amounts were observed under different incubation temperatures and energy levels. In conclusion, these findings provide insight into the metabolic adaptation under different ruminal temperatures and the impacts of dietary adjustments on rumen fermentation and microbial activity. However, there are limitations to replicating the complex physiological responses that occur within the whole body solely through in vitro experiments.
Does the Use of the Yeast Probiotic Saccharomyces cerevisiae Actisaf Sc 47 Reduce the Environmental Impacts of Beef Cattle? A Study Based on Life Cycle Assessment
Authors: Salah Nizar , Legendre Héloïse , Paiva Erika , Duclos Julie , Briche Maxime , Colbalchini Florine , Gac Armelle , Kerihuel Thomas , Boute Céline Garat
Published: October 2024

Increasing animal protein, especially from beef, is necessary to satisfy the requirements of the growing global population. However, this is becoming increasingly challenging due to stakeholders prioritizing sustainable systems with low environmental impacts. To answer these challenges, the use of feed additives such as yeast probiotics seems to be an effective route for improvements in feed efficiency and growth performance. The current study was performed to quantify the environmental impacts of the production and use of a yeast probiotic (Actisaf® Sc 47) through an LCA method in four trials performed during the fattening period: France (French trial), Spain (Spanish trial), and Italy (Italian trials A and B). During each trial, two groups of animals with the same characteristics were compared during the fattening period: the control group without Actisaf® Sc 47 supplementation used as a baseline, and the experimental group with Actisaf® Sc 47 supplementation. The calves started the trial at the ages of 224, 92, and 186 days during the French, Spanish, and Italian trials A and B, respectively. Of the sixteen impact category indicators, nine were analyzed. In Italian trials A and B, the Spanish trial, and the French trial, the use of Actisaf® Sc 47 reduced CC by 4.8, 3.8, 6.6, and 5.4%; FE by 4.8, 3.9, 8.2, and 6.3%; ME by 4.9, 4.0, 6, and 6.4%; and TE by 5.3, 4.1, and 6.2%, respectively. Moreover, during the same trials, Actisaf® Sc 47 reduced AC by 6.0, 4.1, 6.3, and 7.1%; LU by 4.7, 3.9, 5.8, and 6.1%; WU by 4.5, 3.4, 5.2, and 5.9%; RU (fossils) by 4.8, 3.7, 7.3, and 4.8%; and PM by 5.2, 4.1, 6.3, and 7.1%, respectively. The use of Actisaf® Sc 47 has beneficial effects on the environment. Regarding Actisaf® Sc 47 production, the results showed that the production of 1 kg of Actisaf® Sc 47 emitted 2.1 kg of CO2 eq, 60% of which came from the fermentation process and 39% from drying. The results demonstrate the interest in using Actisaf® Sc during the fattening period for its multiple positive outcomes: improving performance and efficiency, while reducing the global carbon footprint.
Editorial for the Special Issue “Oxidative Stress, Inflammation and Antioxidant Defense System in Psychiatric Disorders” in Antioxidants (2022–2023)
Authors: Steullet Pascal
Published: October 2024

A growing body of evidence indicates that many genetic and environmental factors associated with psychiatric disorders affect redox homeostasis, mitochondria and energy metabolism, and neuroendocrine and immune systems in a complex synergistic manner, leading to oxidative stress and inflammation [...]
Multi-Attention Recurrent Neural Network for Multi-Step Prediction of Chlorophyll Concentration
Authors: Jin Yingying , Zhang Feng , Chen Kuo , Chen Liangyu , Gao Jingxia , Dai Wenjuan
Published: October 2024

Chlorophyll prediction facilitates the comprehension of red tide characteristics and enables early warning. In practice, it is formulated as a multivariate time series forecasting problem aimed at forecasting future chlorophyll concentrations by considering both exogenous factors and chlorophyll. However, the multi-step prediction of chlorophyll concentration poses a formidable challenge due to the intricate interaction between factors and the long temporal dependence between input sequences. In this work, we propose a Multi-attention Recurrent Neural Network (MaRNN) for the multi-step prediction of chlorophyll concentration. The MaRNN comprises an encoder incorporating two-stage spatial attention and a decoder employing temporal attention. The encoder first learns the significance of exogenous factors for prediction in the first phase, and subsequently captures the spatial correlation between the exogenous sequence and chlorophyll sequence in the second phase. The decoder further excavates input sequences that exhibit a strong correlation with the task through temporal attention module, thereby enhancing the prediction accuracy of the model. Experiments conducted on two real-world datasets reveal that MaRNN not only surpasses state-of-the-art methods in performance, but also offers interpretability for chlorophyll prediction.
Spatial and Temporal Patterns of Rainfall Erosivity in Southern Africa in Extreme Wet and Dry Years
Authors: Knight Jasper , Abd Elbasit Mohamed A. M.
Published: October 2024

Soil erosivity is a key indicator of the effectiveness of precipitation acting on the land’s surface and is mainly controlled by event-scale and seasonal weather and climatic factors but is also influenced by the nature of the land’s surface, including relief and vegetation cover. The aim of this study is to examine spatial and temporal variations in soil erosivity across southern Africa using rainfall data for the period 2000–2023 and a gridded raster spatial modelling approach. The two wettest and driest years in the record (±>1.5 standard deviation of rainfall values) were identified, which were 2000 and 2006, and 2003 and 2019, respectively. Monthly rainfall values in these extreme wet/dry years were then analyzed for four rainfall regions (arid, semiarid, subhumid, humid), identified according to their annual rainfall totals. These data were then used to calculate Precipitation Concentration Index (PCI) values as an expression of rainfall seasonality, and the modified Fournier index (MFI) was used to quantify rainfall erosivity. The results show that there are significant differences in erosivity between the different climate regions based on rainfall seasonality and also their distinctive environmental settings. In turn, these reflect the synoptic climatic conditions in these regions, their different precipitation sources, and rainfall totals. The results of this study show that calculated MFI values at the national scale, which is the approach taken in most previous studies, cannot effectively describe or account for erosivity values that characterize different climatic regions at the sub-national scale. Furthermore, the mismatch between PCI and MFI spatial patterns across the region highlights that, under semiarid, and highly seasonal rainfall regimes, episodic rainfall events interspersed with periods of dryness result in significant variability in erosivity values that are unaccounted for by rainfall totals or seasonality alone. In these environments, flash floods and wind erosion result in regional-scale soil erosion and land degradation, but these processes and outcomes are not clear when considering MFI values alone. Fully evaluating spatial and temporal patterns of erosivity in their climatic and environmental contexts, as developed in this study, has implications for sediment and carbon exports, as well as identifying the major regions in which land degradation is an environmental and agricultural issue.
Sources and Variability of Greenhouse Gases over Greece
Authors: Bougiatioti Aikaterini , Gialesakis Nikos , Sarafidis Yannis , Gini Maria I. , Mermigkas Marios , Kalkavouras Panayiotis , Mirasgedis Sebastian , Ramonet Michel , Narbaud Clement , Lopez Morgan , Balis Dimitris , Eleftheriadis Konstantinos , Kanakidou Maria , Mihalopoulos Nikolaos
Published: October 2024

This study provides an overview of the atmospheric drivers of climate change over Greece (Eastern Mediterranean), focusing on greenhouse gases (GHG: carbon dioxide, CO2; methane, CH4; etc.). CO2 in Greece is mostly produced by energy production, followed by transport, construction, and industry. Waste management is the largest anthropogenic source of methane, accounting for 47% of total CH4 emissions, surpassing emissions from the agricultural sector in 2017, while the energy sector accounts for the remaining 10.5%. In situ simultaneous observations of GHG concentrations in Greece conducted at three sites with different topologies (urban background; Athens, regional background; Finokalia and free troposphere; and Helmos) during the last 5 years (2019–2023) showed increasing trends of the order of 2.2 ppm·yr−1 and ~15 ppb·yr−1 for CO2 and CH4, respectively, in line with the global trends. These increasing trends were found from both ground-based and satellite-based remote-sensing observations. Finally, during the lockdown period due to the COVID-19 global pandemic, a 58% reduction in CO2 levels was observed in the urban background site of Athens after subtracting the regional background levels from Finokalia, while the respective reduction in CH4 was of only the order of 15%, highlighting differences in emission sources.
Classifying Seismic Events Linked to Solar Activity: A Retrospective LSTM Approach Using Proton Density
Authors: Altaibek Aizhan , Nurtas Marat , Zhantayev Zhumabek , Zhumabayev Beibit , Kumarkhanova Ayazhan
Published: October 2024

The influence of solar activity on seismic activity is a subject of debate. Previous studies have shown that there is sometimes a correlation and sometimes a contradiction between solar activity maxima and large earthquakes. Long-term memory neural network is used to study the relationship between solar activity and seismic activity. This study emphasizes retrospective classification rather than direct prediction, refining the LSTM architecture to maximize classification accuracy and processing data from the Solar and Heliospheric Observatory and the U.S. Geological Survey earthquake catalogs. A declustering technique is used to select large seismic events and weighted learning corrects for class imbalances. The LSTM model accurately classified earthquakes (84.47%) and proton density variations. The results support the theory that solar activity, in particular proton density, can anticipate earthquake events.
Exploring Climate Change Impacts on Temperature Extremes in the South Saskatchewan River Watershed, Alberta, Canada
Authors: Mousavi Roya , Johnson Daniel L. , Byrne James M. , Kroebel Roland
Published: October 2024

In recent years, the frequency and intensity of extreme temperature events have escalated, posing unprecedented challenges to ecosystems, economies, and human health. As global temperatures rise, these events are emerging as critical threats; therefore, understanding their changes is essential for developing strategies to mitigate their growing risks under global warming. In this study, we used ETCCDI (Expert Team on Climate Change Detection, Monitoring, and Indices) temperature indices to analyze future changes in extreme temperature events in the South Saskatchewan River Watershed (SSRW) in Southern Alberta, Canada, a critical area for irrigation, agriculture, and food production. This analysis is based on an ensemble of 26 Global Circulation Models (GCMs) and three Shared Socio-economic Pathway (SSP) scenarios, in three periods (2015–2030, 2041–2060, 2071–2100), compared against the base period of 1951–1990. The results suggest substantial changes in most of the studied indices towards higher temperatures, with a significant rise in both the numbers of days with extreme temperatures and the magnitude of the temperature itself, as well as a notable drop in the number of cold days. As a result of warming, the growing season length is 16 days longer in 2015–2030 compared to the base period and is projected to increase substantially by the end of the century. A longer growing season might seem favourable for agriculture, but it can disrupt water availability and cause unpleasant environmental consequences. Overall, the scenarios considered in this research suggest that the SSRW could experience warming at a significant rate. This finding underscores the urgent need for adaptation and mitigation actions to enhance resilience and sustainability.
Is It Possible to Combine Non-Invasive Brain Stimulation and Evidence-Based Psychosocial Interventions in Schizophrenia? A Critical Review
Authors: Lisoni Jacopo , Nibbio Gabriele , Baglioni Antonio , Dini Simona , Manera Bianca , Maccari Alessandra , Altieri Luca , Calzavara-Pinton Irene , Zucchetti Andrea , Deste Giacomo , Barlati Stefano , Vita Antonio
Published: October 2024

In schizophrenia, it was suggested that an integrated and multimodal approach, combining pharmacological and non-pharmacological interventions, could improve functional outcomes and clinical features in patients living with schizophrenia (PLWS). Among these alternatives, evidence-based psychosocial interventions (EBPIs) and Non-Invasive Brain Stimulation (NIBS) represent feasible treatment options targeting the clinical features that are unmet needs of PLWS (especially negative and cognitive symptoms). As no clear evidence is available on the combination of these non-pharmacological approaches, this review aimed to collect the available literature on the combination of EBPIs and NIBS in the treatment of PLWS. We demonstrated that the field of combining EBPIs and NIBS in schizophrenia is in its infancy, as only 11 studies were reviewed. In fact, only a few trials, with divergent results, combined these non-pharmacological modalities; while emerging evidence is available on the combination of cognitive remediation and rTMS/iTBS, inconclusive results were obtained. Conversely, albeit preliminary, more solid findings are available on the combination of HF-rTMS and family intervention. Moreover, despite the fact that cognitive activation could not be considered an EBPI, promising results are available in combination with tDCS to improve the working memory domain. To overcome these limitations, we considered several methodological issues to promote research in this field.
Impact of Physical Activity, Sedentary Behavior, and Basal Metabolic Rate on PTSD, Depression, and Emotional Instability
Authors: Lyu Tianyi , Qian Haonan , Chung Sung-Pil
Published: October 2024

Objective: This study aimed to investigate the potential associations between physical activity, sedentary behavior, and the basal metabolic rate (BMR) with post-traumatic stress disorder (PTSD), major depressive disorder (MDD), and emotional instability (EI) using bidirectional Mendelian randomization (MR). Additionally, it sought to identify key molecular mechanisms underlying emotional instability through a comprehensive bioinformatic analysis. Methods: MR analyses utilizing genome-wide association study (GWAS) data were conducted to estimate the effects of physical activity, sedentary behavior, and the BMR on PTSD, MDD, and EI. Sensitivity analyses were performed to assess the robustness of the findings. Concurrently, a bioinformatic analysis was executed on gene expression datasets (GSE53987 and GSE21138) derived from emotionally unstable patients. This analysis encompassed the differential gene expression analysis to identify differentially expressed genes (DEGs), followed by an functional enrichment analysis to uncover key molecular pathways associated with EI. Results: The MR analysis revealed that increased physical activity may have a protective effect against PTSD, albeit with inconsistent effects on MDD and EI. Sedentary behavior and the BMR demonstrated minimal associations with PTSD, MDD, or EI. The bioinformatic analysis identified 114 DEGs associated with EI, with YWHAB, SRRM2, MST1, HDAC10, and HSPA1A highlighted as significant genes. The functional enrichment analysis of these DEGs unveiled key pathways potentially involved in the molecular pathology of emotional instability. Conclusions: Physical activity appears to protect against PTSD, whereas its effects on MDD and EI are less definitive. The bioinformatic findings offer a deeper molecular understanding of EI, pinpointing specific genes and pathways that may serve as potential therapeutic targets. Further research is warranted to elucidate these intricate interactions and the identified molecular mechanisms.
The Adult Changes in Thought (ACT) Medical Records Abstraction Project: A Resource for Research on Biological, Psychosocial and Behavioral Factors on the Aging Brain and Alzheimer’s Disease and Related Dementias
Authors: Gatto Nicole M. , Renz Anne , Tom Sarah E. , Lyons Mary , Macuiba Jennifer A. , Dodd Tammy S. , Lind Bonnie K. , Gray Shelly L. , Meyers Kelly , Larson Eric B. , Nelson Jennifer C. , McEvoy Linda K. , Sankaran Sundary , Key Dustin , Litondo Jeremiah A. , Crane Paul K.
Published: October 2024

Background: Adult Changes in Thought (ACT), a prospective cohort study, enrolls older adult members of Kaiser Permanente Washington. We describe an ambitious project to abstract medical records facilitating epidemiological investigation. Methods: Abstracted data include medications; laboratory results; women’s health; blood pressure; physical injuries; cardiovascular, neurological, psychiatric and other medical conditions. Results: Of 1419 of 5763 participants with completed abstractions, 1387 (97.7%) were deceased; 602 (42.4%) were diagnosed with Alzheimer’s Disease and Related Dementias; 985 (69.4%) had a brain autopsy. Each participant had an average of 34.3 (SD = 13.4) years of data abstracted. Over 64% had pharmacy data preceding 1977; 87.5% had laboratory data preceding 1988. Stroke, anxiety, depression and confusion during hospitalization were common among participants diagnosed with dementia. Conclusions: Medical records are transformed into data for analyses with outcomes derived from other ACT data. We provide detailed, unparalleled longitudinal clinical data to support a variety of epidemiological research on clinical-pathological correlations.
Self-Choice Emotion Regulation Enhances Stress Reduction: Neural Basis of Self-Choice Emotion Regulation
Authors: Imajo Nozomi , Matsuzaki Yutaka , Kobayashi Akiko , Sakaki Kohei , Nouchi Rui , Kawashima Ryuta
Published: October 2024

Background/Objectives: Opting to perform emotion regulation when facing high-arousal stimuli enhances the reduction in negative emotions. Previous research has indicated that self-choice, that is, personally choosing from multiple alternatives, can improve performance. However, it is unclear whether the emotion regulation strategy chosen among multiple alternatives in daily life enhances stress reduction compared to a forced strategy. This study aimed to reveal the effects of self-choice emotion regulation and its underlying neural basis. Methods: Participants were 40 healthy adults who met the inclusion criteria; they performed self-choice emotion regulation, forced emotion regulation, and no emotion regulation (the control condition) while their brain activity was captured using a functional magnetic resonance imaging scanner. First, the participants were shown a stressful scenario. Secondly, they rated the stress they experienced. Thirdly, they performed self-choice or forced emotion regulation or did nothing. Finally, participants rated their stress level again. Results: Self-choice emotion regulation reduced stress better than forced-choice emotion regulation. The stress reduction was associated with decreases in the activation of the left opercular part of the inferior frontal gyrus. Conclusions: Self-choice can improve emotion regulation, and this effect is likely mediated by the neural efficiency of the left inferior frontal gyrus.
Maternal and Paternal Education on Italian Monolingual Toddlers’ Language Skills
Authors: Cattani Allegra , Celik Emre
Published: October 2024

Background. Language development in toddlers can be influenced by social interactions in environments and proximal contexts with mothers and fathers. We present the literature on mothers’ and fathers’ education level and socioeconomic status on the child’s language development; further evidence is needed in the Italian-speaking context. Aims. The study aims to confirm the role of mother and father education level on toddlers’ language skills assessed with direct and indirect measures. Methods and Procedures. Participants were 51 Italian-speaking children aged 33 to 41 months. Children were tested with a lexical test (PinG test) for comprehension and production of nouns and predicates and a morpho-syntactic test for grammar comprehension (PCGO). Parents of the children completed a demographic form and the Italian adaptation of the MacArthur-Bates CDI long version. Two series of one-way ANCOVAs were performed to study the role of mothers’ and fathers’ level of education on separate measures of their child’s language. Outcomes and Results. Findings suggest that in most families, mothers’ level of education is higher than fathers’ level of education. There was no significant difference between children of parents with low–middle level of education and children of parents with high level of education for the grammar comprehension tasks (PCGO) and indirect measure of vocabulary production (MacArthur-Bates CDI). However, both mothers’ and fathers’ level of education appears to be significant for the direct measurement of word production. Conclusions and Implications. This study provides new evidence for the role of mothers’ and fathers’ education on the development of word production in children aged 33 to 41 months, contributing to enriching the literature on the Italian context; it lays the groundwork for future research on the social and environmental factors that can affect language development.
Do Progressive Intensities of Transcranial Direct Current Stimulation with and Without 40 Hz Binaural Beats Change Pre-Frontal Cortex Hemodynamics? A Randomized Controlled Trial
Authors: Macedo Maria de Cassia Gomes Souza , Ferreira Kariny Realino do Rosário , Meira Paula Almeida , Esquírio Arthur Ferreira , Barbosa Michelle Cristina Sales Almeida , Gama Gabriela Lopes , Barbosa Alexandre Wesley Carvalho
Published: October 2024

Transcranial direct current stimulation (tDCS) is often reported to have positive effects on brain hemodynamics as well as cognitive performance. Binaural beats (BBs) have also shown the potential to improve cognitive performance. However, we could not find any studies assessing prefrontal hemodynamics using a combination of these techniques or assessing the effects on hemodynamic response at different intensity levels of tDCS (two and three mA). This study aimed to compare the immediate hemodynamic responses to tDCS at different intensities (two and three mA) with and without 40 Hz BBs. Sixty-eight healthy young individuals of both sexes were split into four groups: the tDCS 2 mA group; tDCS 3 mA group; tDCS 2 mA + BB group; and tDCS 3 mA + BB group. All groups received 20 min tDCS (F3-Fp2) alone or combined with BBs. The hemodynamic effect was assessed using a functional near-infrared intracranial spectroscope (fNIRS) positioned on the left supraorbital region (Fp1). The mean values of rates of oxygen saturation (SatO2) were recorded at baseline, during the intervention period, and post-stimulation. The oxygenated hemoglobin rates (HbO) were also extracted. No between-group differences were observed. The within-group analysis did not show significant differences in terms of the time×groups factor. However, the time factor showed significant within-group differences. No differences were found for the HbO rates. The present findings showed that two and three mA tDCS had effects on pre-frontal cortex SatO2; however, the use of additional BBs did not change the SatO2 levels compared to the use of tDCS alone.
Developing Programs for Converting MIDAS GEN to ANSYS Models Based on Python
Authors: Yang Yuqing , Kong Fanchang , Jiang Zhelong , Mu Zaigen
Published: October 2024

The reasonableness and accuracy of engineering design are often assessed through the use of a variety of structural design analysis software, which are then compared and verified. However, it is challenging for a single analysis software to meet the diverse and complex design requirements. In order to meet the specific engineering requirements, it is necessary to convert the MIDAS result model into an ANSYS structural model and conduct a nonlinear analysis and simulation in ANSYS. Nevertheless, the existing interface is unable to facilitate direct conversion of the model. Accordingly, this paper presents a Python-based ANSYS APDL program that enables the complete conversion of MIDAS GEN structural models to ANSYS finite element models. The program is capable of converting a range of data, including material, section, element, connection, load, node mass, constraint, time history function, and so forth. The program is capable of converting specific connection units, including elastic and general connection units. Additionally, the beam-column section direction, beam end freedom release, rigid element, and special anti-rocking structure of the structure can be considered. Ultimately, the theatre model is transformed. Following a comparison of the analysis results, it was found that the mass and mode of the model before and after the transformation were essentially identical. The maximum error of the first six orders of the structure is 2.95%, with the structural displacement under gravity load remaining essentially unchanged. The research and analysis demonstrate the accuracy and reliability of the MIDAS GEN conversion ANSYS program. The conversion program significantly reduces the time required for direct modeling in ANSYS, enhancing work efficiency. The study has considerable practical significance for the seismic sway design and analysis of buildings based on vibration isolation design.
A Global Snapshot of 3D-Printed Buildings: Uncovering Robotic-Oriented Fabrication Strategies
Authors: Placzek Gerrit , Schwerdtner Patrick
Published: October 2024

This paper aims to provide a global snapshot of concrete 3D-printed buildings and to uncover robotic-oriented large-scale fabrication strategies. Therefore, an extensive internet search and literature review was carried out to investigate 3D-printed buildings. In this study, 154 construction projects with 204 buildings were systematically recorded and evaluated from 2013 up to 2023. Using an exploratory mixed-methods approach and a comparative case study analysis, a total of 88 3D-printed buildings were first evaluated descriptively. Thereafter, different existing printing strategies for in situ, on-site, and off-site production were identified, using an iterative approach. In addition to the geographical distribution, the descriptive evaluation also showed the key players as drivers for the spread of the 3D-printing technology and the correlations between printer type, fabrication strategy, and the building size. With regard to the printing strategy, three different approaches for in situ and off-site fabrication can be defined, depending on the printer types and their characteristics (work size and mobility): print-in-one-go, horizontal or vertical segmentation, and the multi-element vs. full-scaled wall strategy. However, the study showed that the data quality was sometimes difficult due to a lack of information and essential details of the printing process and segmentation.
A Comprehensive Review of the Key Deterioration Factors of Concrete Bridge Decks
Authors: Ibrahim Abdelazim , Abdelkhalek Sherif , Zayed Tarek , Qureshi Abdul Hannan , Mohammed Abdelkader Eslam
Published: October 2024

Bridges are generally acknowledged as one of the vital structures of transportation systems. Meanwhile, they are prone to time-variant damage and deterioration mechanisms over their life span. With that in mind, this research study aims to explore state-of-the-art work in relation to deterioration models and related critical factors of reinforced concrete bridges. Particularly, this study presents a mixed review methodology (scientometric and systematic) that reviews over 300 publications in Scopus and Web of Science databases over the period 1985–2023. The study scrutinized and categorized the wide spectrum of deterioration factors in reinforced concrete bridges with the help of deterioration models. Results manifested that implicating deterioration factors can be grouped into seven main clusters, namely chemical, material properties, design & construction, physical, operational, environmental, and force majeure. In addition, it is noted that hitherto, there has been a lack of sufficient research efforts on non-destructive evaluation-based deterioration models.
Cement-Free Geopolymer Paste: An Eco-Friendly Adhesive Agent for Concrete and Masonry Repairs
Authors: Batran Tayseer Z. , Ismail Mohamed K. , Serag Mohamed I. , Ragab Ahmed M.
Published: October 2024

This study aimed to investigate the feasibility of using geopolymer paste (GP) as an adhesive agent for (i) anchoring steel bars in concrete substrates, (ii) repairing concrete, and (iii) repairing limestone and granite masonry blocks commonly found in historic buildings. In this investigation, seven cement-free GP mixes were developed with different combinations of binder materials (slag, silica fume, and metakaolin). The mechanical properties, adhesive performance, and production cost of the developed GP mixes were compared to those of a commercially epoxy adhesive mortar (EAM). The results obtained from this study indicated that the use of GPs enhanced the bonding between steel bars and concrete substrates, achieving bonding strengths that were 19.7% to 49.2% higher than those of control specimens with steel bars directly installed during casting. In concrete repairs, the GPs were able to restore about 60.6% to 87.9% of the original capacity of the control beams. Furthermore, GPs exhibited a promising performance in repairing limestone and granite masonry blocks, highlighting their potential suitability for masonry structures. The best adhesive performance was observed when a ternary binder material system consisting of 70% slag, 20% metakaolin and 10% silica fume was used. This combination, compared to the investigated EAM, showed comparable adhesive properties at a significantly low cost, indicating the viability of GPs as a cost-effective, eco-friendly adhesive agent.
Experimental Investigation of the Axial Load Capacity of Bilateral Helix-Stiffened Cement Mixing Piles in Soft Marine Soil
Authors: Zhang Zhenqing , Chen Bingsan , Zhao Junnan , Huang Yunhan
Published: October 2024

Bilateral helix-stiffened cement mixing piles (BHCMPs) are a new type of robust composite pile. In this paper, the influence of design parameters, such as the diameter of inner helix plates and the number and size of outer mixing helix plates, on the vertical bearing performance of the pile foundation and the behavior of the pile diameter are investigated through laboratory model tests. The results indicate that incorporating a reverse-mixing process in the pile formation of helix-stiffened cement mixing piles can enhance the overall ultimate bearing capacity and strengthen the soil-cement of the piles. In the case of the same double-blade inner drill pipe, for every 22 mm increase in the blades, its ultimate compressive load-bearing capacity was increased by 10% to 25%, and its pullout load-bearing capacity was increased by 15% to 45%. With further increases in the blades, the percentage increase in the compressive and pullout load-bearing capacity was reduced. With an increase in the number of external mixing blades, its compressive load capacity increased in the range of 5% to 20%, and the elevation load capacity increased in the range of 10% to 25%. Increasing the number of reverse-mixing helix plates on the outer casing enhances the soil-cement strength of the pile body by approximately 15–20% for each additional plate. The average strength of the pile-body soil-cement for each additional plate is estimated to be 1 to 1.4 times that of the previous set, indicating that increased mixing iterations can enhance the perimeter soil-cement strength of the pile. The average bond diameter of soil-cement piles with double-blade internal drilling rods could be seen from the diameter of the piles formed, which was 1.02 to 1.21 times the diameter of the blades.
Radiomics-Based Machine Learning with Natural Gradient Boosting for Continuous Survival Prediction in Glioblastoma
Authors: Karabacak Mert , Patil Shiv , Gersey Zachary Charles , Komotar Ricardo Jorge , Margetis Konstantinos
Published: October 2024

(1) Background: Glioblastoma (GBM) is the most common primary malignant brain tumor in adults, with an aggressive disease course that requires accurate prognosis for individualized treatment planning. This study aims to develop and evaluate a radiomics-based machine learning (ML) model to estimate overall survival (OS) for patients with GBM using pre-treatment multi-parametric magnetic resonance imaging (MRI). (2) Methods: The MRI data of 865 patients with GBM were assessed, comprising 499 patients from the UPENN-GBM dataset and 366 patients from the UCSF-PDGM dataset. A total of 14,598 radiomic features were extracted from T1, T1 with contrast, T2, and FLAIR MRI sequences using PyRadiomics. The UPENN-GBM dataset was used for model development (70%) and internal validation (30%), while the UCSF-PDGM dataset served as an external test set. The NGBoost Survival model was developed to generate continuous probability estimates as well as predictions for 6-, 12-, 18-, and 24-month OS. (3) Results: The NGBoost Survival model successfully predicted survival, achieving a C-index of 0.801 on internal validation and 0.725 on external validation. For 6-month OS, the model attained an AUROC of 0.791 (95% CI: 0.742–0.832) and 0.708 (95% CI: 0.654–0.748) for internal and external validation, respectively. (4) Conclusions: The radiomics-based ML model demonstrates potential to improve the prediction of OS for patients with GBM.
Integrated Care in Specialized Networks: Leveraging Early Referrals to Reduce Local Recurrence in Soft Tissue Sarcoma
Authors: Schärer Markus , Hösli Pascale , Heesen Philip , Schelling Georg , Obergfell Timothy , Nydegger Kim N. , Studer Gabriela , Bode-Lesniewska Beata , Fuchs Bruno
Published: October 2024

This study evaluated the impact of care pathways on the incidence of local recurrence (LR) in patients with soft tissue sarcomas (STS) and identified factors predictive of LR. It compared outcomes between patients managed entirely within a comprehensive care pathway (CCP) at the Swiss Sarcoma Network (SSN) and those who experienced fragmented care pathways (FCPs), where initial treatment occurred outside specialized centers. This prospective study utilized real-world-time data from the SSN-Sarconnector, capturing quality indicators through weekly Multidisciplinary Team/Sarcoma-Board (MDT/SB) meetings. The overall incidence of LR was 17.6% (n = 68/386), higher than rates typically reported in sarcoma center-based studies due to the inclusion of patients with prior inadequate management from real-world referrals. In a univariable logistic regression analysis, the FCP was significantly associated with higher LR rates, unplanned “whoops” resections (25.4%, n = 96), and positive surgical margins, emphasizing the detrimental impact of suboptimal initial management outside of specialized centers. Multivariable analysis confirmed that the FCP (aOR 2.7, 95% CI [1.41, 5.12], p = 0.003), tumor size (aOR 1.49, 95% CI [1.1, 2.02], p = 0.01), and biological behavior (aOR 5.84 95% CI [1.8, 18.86], p = 0.0003) are independent predictors of LR. Notably, patients referred to sarcoma centers after an initial FCP presented with inadequately managed disease, such as incomplete resections and unplanned surgeries, leading to increased complexity of subsequent treatments. These findings underscore the critical role of referral patterns on sarcoma center outcomes, highlighting the significant disparity in LR rates between institutions. The need for improved education and standardized early referral strategies at the spoke level is paramount to optimize patient outcomes and reduce the burden of LR. Enhanced spoke-level education and standardized referral protocols are critical to ensuring effective initial management and optimizing patient outcomes within specialized sarcoma networks like the SSN.
Multimodal Optical Imaging of Ex Vivo Fallopian Tubes to Distinguish Early and Occult Tubo-Ovarian Cancers
Authors: Malone Jeanie , Tanskanen Adrian S. , Hill Chloe , Zuckermann Cynamon Allan , Hoang Lien , MacAulay Calum , McAlpine Jessica N. , Lane Pierre M.
Published: October 2024

Background: There are currently no effective screening measures to detect early or occult tubo-ovarian cancers, resulting in late-stage detection and high mortality. This work explores whether an optical imaging catheter can detect early-stage tubo-ovarian cancers or precursor lesions where they originate in the fallopian tubes. Methods: This device collects co-registered optical coherence tomography (OCT) and autofluorescence imaging (AFI). OCT provides three-dimensional assessment of underlying tissue structures; autofluorescence imaging provides functional contrast of endogenous fluorophores. Ex vivo fallopian tubes (n = 28; n = 7 cancer patients) are imaged; we present methods for the calculation of and analyze eleven imaging biomarkers related to fluorescence, optical attenuation, and OCT texture for their potential to detect tubo-ovarian cancers and other lesions of interest. Results: We visualize folded plicae, vessel-like structures, tissue layering, hemosiderin deposits, and regions of fibrotic change. High-grade serous ovarian carcinoma appears as reduced autofluorescence paired with homogenous OCT and reduced mean optical attenuation. Specimens containing cancerous lesions demonstrate a significant increase in median autofluorescence intensity and decrease in Shannon entropy compared to specimens with no lesion. Non-cancerous specimens demonstrate an increase in optical attenuation in the fimbriae when compared to the isthmus or the ampulla. Conclusions: We conclude that this approach shows promise and merits further investigation of its diagnostic potential.
Sacituzumab Govitecan in Triple Negative Breast Cancer: A Systematic Review of Clinical Trials
Authors: Pérez-Bermejo Marcelino , Caballero-Pascual Mónica , Legidos-García María Ester , Martínez-Peris Miriam , Casaña-Mohedo Jorge , Llorca-Colomer Francisco , Ventura Ignacio , Tomás-Aguirre Francisco , Asins-Cubells Adalberto , Murillo-Llorente María Teresa
Published: October 2024

Background/Objectives: Triple-negative breast cancer is difficult to treat due to the absence of hormone receptors and Her2neu. Sacituzumab govitecan is a new therapeutic approach that uses an antibody directed against the Trop-2 antigen present in solid epithelial tumors, linked to the active metabolite SN-38, similar to irinotecan, to specifically target cancer cells while minimizing damage to healthy cells. The objective of the present review was to evaluate the efficacy and safety of sacituzumab govitecan as a single treatment in patients with triple-negative breast cancer and to compare its results with the standard conventional chemotherapy regimen currently used in this disease. Methods: A systematic review of randomized clinical trials of sacituzumab govitecan was performed. The search was performed in Medline (PubMed), Web of Science, and Cochrane from September 2022 to January 2024. Results: Thirty-eight articles are included and evaluated according to inclusion and exclusion criteria corresponding to the two most relevant clinical trials, including specific analyses of cohorts and subgroup study arms within these trials. Data from more recent clinical trials are also reviewed. Conclusions: The efficacy results showed a significantly greater clinical benefit with sacituzumab govitecan compared to standard chemotherapy in patients with triple-negative breast cancer. This drug will become a treatment of substantial impact in future treatment guidelines for this type of cancer.
Artificial Intelligence in Head and Neck Cancer Diagnosis: A Comprehensive Review with Emphasis on Radiomics, Histopathological, and Molecular Applications
Authors: Broggi Giuseppe , Maniaci Antonino , Lentini Mario , Palicelli Andrea , Zanelli Magda , Zizzo Maurizio , Koufopoulos Nektarios , Salzano Serena , Mazzucchelli Manuel , Caltabiano Rosario
Published: October 2024

The present review discusses the transformative role of AI in the diagnosis and management of head and neck cancers (HNCs). Methods: It explores how AI technologies, including ML, DL, and CNNs, are applied in various diagnostic tasks, such as medical imaging, molecular profiling, and predictive modeling. Results: This review highlights AI’s ability to improve diagnostic accuracy and efficiency, particularly in analyzing medical images like CT, MRI, and PET scans, where AI sometimes outperforms human radiologists. This paper also emphasizes AI’s application in histopathology, where algorithms assist in whole-slide image (WSI) analysis, tumor-infiltrating lymphocytes (TILs) quantification, and tumor segmentation. AI shows promise in identifying subtle or rare histopathological patterns and enhancing the precision of tumor grading and treatment planning. Furthermore, the integration of AI with molecular and genomic data aids in mutation analysis, prognosis, and personalized treatment strategies. Conclusions: Despite these advancements, the review identifies challenges in AI adoption, such as data standardization and model interpretability, and calls for further research to fully integrate AI into clinical practice for improved patient outcomes.
Overexpression of Fibroblast Growth Factor 8 Is a Predictor of Impaired Survival in Esophageal Squamous Cell Carcinoma and Correlates with ALK/EML4 Alteration
Authors: Jomrich Gerd , Kollmann Dagmar , Yan Winny , Winkler Daniel , Paireder Matthias , Gensthaler Lisa , Puhr Hannah Christina , Ilhan-Mutlu Aysegül , Asari Reza , Schoppmann Sebastian F.
Published: October 2024

FGF8, ALK, and EML4 have been identified as promising biomarkers in a number of malignancies. The aim of this study was to examine the prognostic role of FGF8, ALK, and EML4 in esophageal squamous cell carcinoma (ESCC). Methods: Consecutive patients with ESCC who underwent upfront resection were included in this study. ALK and EML4 gene status was evaluated by fluorescence in situ hybridization (FISH) using a triple-color break-apart single-fusion probe and a probe against 2p11. FGF8, ALK, and EML4 protein expression was determined by immunohistochemistry. Results: A total of 122 patients were included in this study. Multivariate analysis revealed that FGF8 overexpression is an independent negative prognostic factor for patients’ overall survival (OS) (p = 0.04). Furthermore, a significant correlation between the expression of FGF8, and ALK (p = 0.04) and EML4 (p = 0.01) alteration was found. Conclusions: FGF8 overexpression is an adverse independent prognostic factor in patients with upfront resected ESCC. Furthermore, FGF8 expression significantly correlates with ALK and EML4 amplification and may therefore qualify as a future therapeutic target.
Selective Sentinel Node Dissection in Melanoma with Trends and Future Directions
Authors: Pletcher Eric , Faries Mark B.
Published: October 2024

Starting with its earliest descriptions, melanoma has been recognized as a tumor with a predilection for metastasis to regional lymph nodes. This tendency led to initial recommendations for very aggressive early surgical management of the regional nodal basin. However, those recommendations were the source of much controversy over nearly a century, until the minimally invasive surgical technique of sentinel lymph node (SLN) biopsy was developed by Morton, Cochran and colleagues. This technique has been evaluated in a series of prospective clinical trials, which have clarified its role and the management of lymph nodes in this disease. Current controversies relating to SLN biopsy include optimal selection of patients for the procedure, the role of gene expression profiling in initial melanoma management, and the potential therapeutic effects of SLN biopsy-based management. In addition, the SLN appears to be a rich source of data relating to the host–tumor interface and the immune microenvironment, which may advance our understanding of the biology of melanoma. Finally, although the surgical technique is well developed at this point, there may be additional technical improvements that are possible as well.
Significance of LIF/LIFR Signaling in the Progression of Obesity-Driven Triple-Negative Breast Cancer
Authors: Randolph Lois , Joshi Jaitri , Rodriguez Sanchez Alondra Lee , Pratap Uday P. , Gopalam Rahul , Chen Yidong , Lai Zhao , Santhamma Bindu , Kost Edward R. , Nair Hareesh B. , Vadlamudi Ratna K. , Subbarayalu Panneerdoss , Viswanadhapalli Suryavathi
Published: October 2024

American women with obesity have an increased incidence of triple-negative breast cancer (TNBC). The impact of obesity conditions on the tumor microenvironment is suspected to accelerate TNBC progression; however, the specific mechanism(s) remains elusive. This study explores the hypothesis that obesity upregulates leukemia inhibitory factor receptor (LIFR) oncogenic signaling in TNBC and assesses the efficacy of LIFR inhibition with EC359 in blocking TNBC progression. TNBC cell lines were co-cultured with human primary adipocytes, or adipocyte-conditioned medium, and treated with EC359. The effects of adiposity were measured using cell viability, colony formation, and invasion assays. Mechanistic studies utilized RNA-Seq, Western blotting, RT-qPCR, and reporter gene assays. The therapeutic potential of EC359 was tested using xenograft and patient-derived organoid (PDO) models. The results showed that adipose conditions increased TNBC cell proliferation and invasion, and these effects correlated with enhanced LIFR signaling. Accordingly, EC359 treatment reduced cell viability, colony formation, and invasion under adipose conditions and blocked adipose-mediated organoid growth and TNBC xenograft tumor growth. RNA-Seq analysis identified critical pathways modulated by LIF/LIFR signaling in diet-induced obesity mouse models. These findings suggest that adiposity contributes to TNBC progression via the activation of the LIF/LIFR pathway, and LIFR inhibition with EC359 represents a promising therapeutic approach for obesity-associated TNBC.