bluuebunny/crossref_metadata_2025 huggingface dataset:
Childcare as a social determinant of access to healthcare: a scoping review
Authors: McArthur Megan , Tian Persephone , Kho Kimberly A. , Bhavan Kavita P. , Balasubramanian Bijal A. , Ganguly Anisha P.
Published: December 2024

Introduction

As health systems strive to screen for and address social determinants of health (SDOH), the role of access to childcare and barriers to healthcare posed by childcare needs remains underexplored. A gap exists in synthesizing existing evidence on the role of access to childcare as a SDOH.

Methods

This scoping review aimed to examine and analyze existing literature on the role of childcare needs as a social determinant of access to healthcare. We conducted a structured literature search across PubMed, Scopus, health policy fora, and professional healthcare societies to inclusively aggregate studies across interdisciplinary sources published between January 2000 and June 2023. Two independent reviewers reviewed results to determine inclusions and exclusions. Studies were coded into salient themes utilizing an iterative inductive approach.

Results

Among 535 search results, 526 met criteria for eligibility screening. Among 526 eligible studies, 91 studies met inclusion criteria for analysis. Five key themes were identified through data analysis: (1) barriers posed by childcare needs to healthcare appointments, (2) the opportunity for alternative care delivery models to overcome childcare barriers, (3) the effect of childcare needs on participation in medical research, (4) the impact of the COVID-19 pandemic on childcare needs, and (5) the disproportionate burden of childcare experienced by vulnerable populations.

Discussion

Childcare needs remain underexplored in existing research. Current evidence demonstrates the relevance of childcare needs as a barrier to healthcare access, however dedicated studies are lacking. Future research is needed to understand mechanisms of childcare barriers in access to healthcare and explore potential interventions.
Retrospective research: identifying and conducting phylogenetic analyses on four Orf virus strains isolated in Yunnan province between 2021 and 2023—revealing their significance and characteristic features
Authors: Xie Jiarui , Kou Meiling , Wang Yinan , Su Xiaohang , Gao Huafeng , Miao Haisheng
Published: December 2024

Contagious Eczema (CE), caused by ORFV, impacts sheep and goats globally, with severe symptoms and economic losses. The ORFV situation in Yunnan, China, was unclear before 2021–2023 study. Eleven scab samples from goats on small farms in three Yunnan municipalities were collected. Four ORFV strains were isolated and characterized using scanning electron microscopy, cytopathic effect observation, and PCR. Phylogenetic analyses of ORFV011 and ORFV059 genes showed significant results. For ORFV011, the nucleotide similarity of the four strains to D1701 strain was 98.4–99%. For ORFV059, it was 97.2–97.9% with OV-SA00 strain. These findings suggest gene rearrangements and interactions among strains during Yunnan’s ORFV outbreak, forming a unique evolutionary lineage. Our study is the first comprehensive one on Yunnan’s ORFV prevalence with in-depth phylogenetic analysis. It has important implications. In vaccine development, understanding genetic variances helps create better vaccines. For disease control, customized strategies like targeted quarantine and disinfection can be designed based on strain characteristics. From a public health aspect, as CE is zoonotic, closely monitoring ORFV in goats aids in predicting and preventing human infections, thus being significant for protecting goats against CE in Yunnan.
New Insights into Fuzzy Genetic Algorithms for Optimization Problems
Authors: Syzonov Oleksandr , Tomasiello Stefania , Capuano Nicola
Published: December 2024

In this paper, we shed light on the use of two types of fuzzy genetic algorithms, which stand out from the literature due to the innovative ideas behind them. One is the Gendered Fuzzy Genetic Algorithm, where the crossover mechanism is regulated by the gender and the age of the population to generate offspring through proper fuzzy rules. The other one is the Elegant Fuzzy Genetic Algorithm, where the priority of the parent genome is updated based on the child’s fitness. Both algorithms present a significant computational burden. To speed up the computation, we propose to adopt a nearest-neighbor caching strategy. We first performed several experiments, using some well-known benchmark functions, and tried different types of membership functions and logical connectives. Afterward, some additional benchmarks were retrieved from the literature for a fair comparison against published results, which were obtained by means of former variants of fuzzy genetic algorithms. A real-world application problem, which was retrieved from the literature and dealt with rice production, was also tackled. All the numerical results show the potential of the proposed strategy.
Adaptive Time-Varying Formation Maneuvering Control for Multi-Robot Systems in Complex Obstacle-Rich Environments
Authors: Zhao Junmei , Zhang Liping , Li Xiao , Li Kewu , Wang He , Liu Yeye
Published: December 2024

To tackle the challenge of time-varying formation control for underactuated robots under model parameter uncertainties and environmental disturbances, this study proposes an affine formation control approach enhanced by an Extended State Observer. Initially, using affine positioning theory and polynomial interpolation, guidelines for selecting leader vehicles and trajectory planning methods are established, whereby the trajectory of follower vehicles is uniquely determined through the stress matrix. To address the cumulative disturbances arising from model uncertainties and environmental factors impacting the formation, an Extended State Observer with optimized parameters is introduced. Furthermore, a distributed affine formation control method with disturbance rejection is designed specifically for underactuated robots with “nonlinear, strongly coupled” dynamics, ensuring that the formation system can track the target configuration within bounded error margins. Finally, theoretical analysis and simulation outcomes ultimately confirm the efficacy of the control approach in achieving resilient formation tracking.
Short-Term Impacts on Soil Biological Properties After Amendment with Biochar from Residual Forestry Biomass
Authors: Morim Ana Carolina , Santos Márcia , Tarelho Luís A. C. , Silva Flávio C.
Published: December 2024

The increasing challenges posed by climate change demand efficient strategies to mitigate soil degradation. Valorization of low-grade residual forestry biomass (acacia) into biochar could be used as a soil amendment strategy. A short-term incubation assay was conducted in forest soil, where the effects of biochar produced at two pyrolysis temperatures (450 °C and 550 °C) with varying particle sizes (S < 0.5 mm, M = [0.5; 3.15], L > 3.15 mm) and application rates (0, 3, 6 and 10% (w/w)) were assessed. Organic matter was analyzed through the water-soluble carbon, hot-water-extractable carbon, and microbial biomass. Microbial activity was evaluated by measuring the soil respiration and metabolic quotient. Biochar application increased the water-soluble carbon by 21 to 143% and the hot-water-extractable carbon by 27 to 137%, while decreasing the microbial biomass to 86%. The soil respiration and metabolic quotient increased in all the conditions, indicating an increase in microbial activity but low efficiency in carbon mineralization. This suggests the inefficient acclimatization of the microorganisms to biochar, lowering their ability to co-metabolize the recalcitrant carbon. Additionally, the potential adsorption of beneficial nutrients onto the biochar could have inhibited their release into the soil, hindering microbial growth. Increased biochar application rates resulted in adverse effects on microbial communities, indicating possible inhibitory effects on the soil biota.
Yield Impact of Data-Informed Surface Drainage: An On-Farm Case Study
Authors: Regmi Sagar , Davidson Paul , Allen Cody
Published: December 2024

Drainage is an important aspect of effective water management in row-crop agriculture. Drainage systems can be broadly categorized as either subsurface or surface drainage. A significant amount of design goes into subsurface drainage installations, such as tile networks, and permanent surface drainage installations, such as waterways and berms. However, many farmers also implement temporary surface drainage installations to drain localized areas within their fields each year. This practice involves creating shallow water paths, typically using spinner ditchers, and it is especially commonplace in areas with poor soil permeability. However, this practice is traditionally performed using only observations by farmers and without any data-based workflows. The objective of this study was to analyze the potential yield benefits from a more data-informed approach to surface drainage on a production row-crop farm by exploring corn and soybean yield data from 2008–2021 from two fields where a data-informed approach to surface drainage was implemented. Field topography and drainage information were combined with yield maps from prior years with traditional ad hoc drainage and the years following the incorporation of the data-informed approach to better understand the impact of the workflow. Geospatial distribution of the average normalized crop yields and elevation maps for the fields were analyzed to isolate the yield impacts of the areas affected by the data-informed on-farm surface drainage artifacts. In the years after implementation of the data-informed surface drainage approach, Field 1 and Field 2 showed respective increases of 18.3% and 13.9% in average corn yields. Further analysis isolating three areas affected by the surface drainage using topography and drainage layout showed that all three isolated areas improved more than the field averages, ranging from 15.9–26.5% for Field 1 and 21.4–40.2% for Field 2. Similarly, soybean yields were also higher in the isolated affected areas after the data-informed drainage ditch construction. The findings highlight the effectiveness of data-informed on-farm surface drainage, a relatively straightforward approach that proved beneficial for both soybean and corn production.
Severity Estimation of Inter-Turn Short-Circuit Fault in PMSM for Agricultural Machinery Using Bayesian Optimization and Enhanced Convolutional Neural Network Architecture
Authors: Wang Mingsheng , Lai Wuxuan , Sun Peng , Li Hong , Song Qiang
Published: December 2024

The permanent magnet synchronous motor (PMSM) is a key power component in agricultural machinery. The harsh and variable working environments encountered during the operation of agricultural machinery pose significant challenges to the safe operation of PMSMs. Early diagnosis of inter-turn short-circuit (ITSC) faults is crucial for improving the safety of the motor. In this study, a fault diagnosis method based on an improved convolutional neural network (CNN) architecture is proposed, featuring two main contributions. First, a dilated convolutional neural network is combined with residual structures, multi-scale structures, and channel attention mechanisms to enhance the training efficiency of the model and the quality of feature extraction. Second, Bayesian optimization algorithms are applied for the automatic tuning of architecture hyperparameters in deep learning models, achieving automatic optimization of the hyperparameters for the fault diagnosis model of ITSCs. To validate the effectiveness of the proposed algorithm, 17 simulated tests of ITSC fault severities were conducted under both constant conditions and dynamic conditions. The results show that the proposed model achieves the best performance regarding the validation accuracy (98.2%), standard deviation, F1 scores, and feature learning capability compared to four other models with different architectures, demonstrating the effectiveness and superiority of the algorithm.
MiR-26a Inhibits Porcine Adipogenesis by Regulating ACADM and ACSL1 Genes and Cell Cycle Progression
Authors: Zhang Dongjie , Hao Wanjun , Zhu Rongru , Wang Liang , Wu Xiaoxu , Tian Ming , Liu Di , Yang Xiuqin
Published: December 2024

MicroRNAs play essential roles in biological processes by regulating gene expression at the post-transcriptional level. Our previous studies suggested the role of miR-26a in porcine fat accumulation. Here, through gain- and loss-of-function analyses, we first showed that miR-26a increased the proliferation of porcine preadipocytes by promoting cell division and that miR-26a inhibited the preadipocyte differentiation. Next, acyl-CoA dehydrogenase, medium chain (ACADM) was revealed to promote the proliferation and differentiation of preadipocytes for the first time. Then, it was revealed that miR-26a regulates adipogenesis by directly binding to the 3′ untranslated region of ACADM and the long-chain acyl-Co A synthetase 1 (ACSL1) gene, a previously known regulator of adipogenesis. Finally, RNA-sequencing, performed on preadipocytes overexpressing miR-26a, identified 337 differentially expressed genes in the early stage of adipogenesis; among them, nine genes were characterized as potential targets of miR-26a. The 337 genes were mainly involved in Gene Ontology terms related to cell division, indicating that cell cycle progression was also a major event regulated by miR-26a during adipogenesis. We provide novel data for understanding the molecular mechanisms underlying adipogenesis, which will contribute to controlling fat accumulation in animals.
Clinical Utility of Broad-Range PCR Testing and Impact on Outcomes in Adults with Suspected Infection
Authors: Weinert-Stein Kaitlyn , Cater Mackenzie , Cherian Sree Sarah , Azem Reem , Khazan Ana E. , Desai Ankita P. , Tripp LeAnne , Lim Peter Paul , Stempak Lisa M. , Hojat Leila S.
Published: December 2024

Background: The development of broad-range polymerase chain reaction (BR-PCR) and next-generation sequencing techniques has significant implications for antimicrobial stewardship by increasing clinicians’ ability to provide a tailored antimicrobial regimen. We sought to explore the clinical utility of BR-PCR testing and its impact on antimicrobial treatment among an adult cohort in a large hospital system. Methods: We retrospectively evaluated samples that underwent BR-PCR testing between 2017 and 2021 and summarized their clinical characteristics and impact on antimicrobial therapy. We identified BR-PCR testing as having clinical utility if the results led to adjustment of antimicrobial choice or duration or to confirmation of the initial empiric regimen, while no clinical utility was assigned to results that were negative or clinically insignificant, unavailable due to loss to follow-up, or lacking clinical indication (treatment completed before the test results returned or conventional cultures revealed the causative pathogen). Results: Among 359 specimens, BR-PCR was positive for 107 (30%). Clinical utility was identified for 106 (29.5%) specimens, including 45 with negative BR-PCR results. The rates of clinical utility varied based on the type of sample tested, with the highest clinical utility associated with cranial samples (60%), followed by body fluid (56%) and endovascular (54%) samples, and the lowest with CSF (15%) and bone and joint (19%) samples. We also identified many BR-PCR tests that were not clinically indicated (23.4%). Conclusions: This study highlights the utility of BR-PCR testing to support antimicrobial stewardship initiatives. Further studies are needed to identify clinical scenarios in which it is appropriate to order BR-PCR testing and for a careful interpretation of negative BR-PCR results.
Resilient Responses to Global Supply Chain Disruptions: Focusing on the Stock Price of Global Logistics Companies
Authors: Sim Min-Seop , Lee Jeong-Min , Kim Yul-Seong , Lee Chang-Hee
Published: December 2024

This study clarifies the impact of global supply chain risks on global logistics companies, with a focus on the potential implications for sustainable supply chain management. The study employs the vector auto-regression model to examine the relationship between the Global Supply Chain Pressure Index (GSCPI) and the stock prices of global logistics companies, yielding the following results. First, the GSCPI does not have a statistically significant effect on most global logistics firms, except for shipping companies, which tend to be negatively impacted by supply chain disruptions. The t-statistics of the GSCPI on air cargo, integrated logistics, and pipeline companies were below the threshold of 1.291, corresponding to a 90% confidence level, which indicates that these results were not statistically significant. Therefore, logistics companies should prioritize the development of resilient and sustainable supply chain strategies incorporating alternative energy sources, such as liquefied hydrogen, ammonia, green methanol, and liquefied natural gas, to enhance their ability to respond to unexpected situations. Second, contrary to other logistics sectors, shipping enterprises have been positively impacted by the GSCPI, suggesting that they may find new opportunities during periods of global instability. By adopting eco-friendly fuel alternatives and green technologies, shipping companies can capitalize on these opportunities and contribute to the global transition toward sustainable logistics practices. These findings suggest that global logistics companies, including pipeline, air cargo, and integrated logistics companies, should develop resilient global supply chain management strategies that incorporate supply chain platforms, nearshoring, and import diversification. This study offers important implications for entrepreneurs and policymakers, emphasizing the role of sustainable energy solutions in stabilizing global supply chains.
Migration Prevention of Carbonate Apatite Granules Through Crystal Interlocking Driven by Bassanite-to-Gypsum Transformation on Granule Surface
Authors: Torres Escalante Luis Miguel , Hayashi Koichiro , Ishikawa Kunio
Published: December 2024

Granular bone substitutes are commonly used in dental treatments owing to their adaptability to irregular bone defects. However, granule migration during and after implantation poses a significant challenge, impairing bone regeneration. This study addresses this issue by setting carbonate apatite (CAp) granules using crystal interlocking owing to the bassanite (calcium sulfate hemihydrate (CSH))-to-gypsum (calcium sulfate dihydrate (CSD)) transformation on the granule surface. CAp granules were mixed with CSH slurry (water/CSH ratio of 0.4) at varying CSH/CAp ratios of 0.33, 0.43, 0.54, 0.67, and 0.82. At all of these mixing ratios, needle-shaped CSD crystals formed on the CAp granule surface, and the CSD crystals interlocked with each other; consequently, CAp granules were set. As the CSH/CAp ratio increased from 0.33 to 0.82, the CSD crystal length increased from 6.58 to 6.79 μm, while the setting time decreased from 30.3 to 15.5 min. Although the porosity of the set CAp granules decreased with an increase in the CSH/CAp ratio, the set granules maintained intergranular spaces of 77.3 μm at a CSH/CAp ratio of 0.82 conducive to cellular infiltration. After immersion in saline for six days, the set CAp granules at a CSH/CAp ratio of 0.82 maintained their original shape, demonstrating enhanced stability compared to lower CSH/CAp ratios where partial or complete collapse occurred. The porosity and specific surface area increased to 59.9% and 3.66 m2/g, respectively, and the intergranular spaces increased to 176.4 μm. Therefore, mixing the CAp granules with CSH at a ratio of 0.82 may prevent granule migration during and after implantation. Moreover, the CSD component of the granules is likely to resorb more rapidly than the CAp component in vivo, promoting porosity in the set granules and facilitating efficient bone replacement.
Development of a Deployable Reflector Antenna for the Synthetic Aperture Radar Satellite, Part 2: Manufacturing and Qualification of the Main Reflector Using a Honeycomb Sandwich Composite Structure
Authors: Kim Dong-Geon , Kim Hyun-Guk , Kim Dong-Yeon , Do Ryoon-Ho , Koo Kyung-Rae , Yu Young-Joon
Published: December 2024

A deployable reflector antenna (DR-A) is a structure that can be stored in a large-diameter Synthetic Aperture Radar (SAR) antenna and be mounted onto a launch vehicle. Considering the performance of the launch vehicle, it is necessary to develop a lightweight, high-performance antenna structure. The solid-type deployable reflector antenna is composed of a number of unit main reflectors. To reduce the weight of the antenna, a lightweight main reflector must be developed. In this paper, following “Development of Deployable Reflector Antenna for the SAR Satellite (Part 1)”, the manufacturing and qualification of the main reflector using honeycomb sandwich composites are described. Four types of composite main reflectors were manufactured with variables in the manufacturing process. The manufacturing variables include the curing process of the structure, the application of an adhesive film between the sheet and the core, and the venting path inside of the sandwich core. After manufacturing the main reflector, we performed weight measurements, non-destructive testing (NDT), surface error measurement using a Coordinate Measurement Machine (CMM), and modal testing for each type of composite main reflector. Through the research and development process, we found that a perforated hole is necessary when excluding the adhesive film during bonding of an aramid core and a CFRP sheet, and a lightweight composite reflector could be developed through this process. We selected the main reflector with the best performance and developed a composite main reflector that can be applied to satellites.
Demand Flexibility: A Review of Quantification Methods, Models, and Required Data
Authors: Shepherd Morgan M. , Mohagheghi Salman
Published: December 2024

As renewable energy is increasingly integrated into our electricity supply, it becomes more challenging to ensure reliability and security due to the intermittent nature of these resources. With the electrification of buildings and technological advancements across various aspects of their operations, the building sector is expected to play a key role in reducing emissions while supporting the needs of the grid. Buildings and the loads they house can provide grid resources via demand flexibility, shifting, and shedding electric load, as necessary. This key resource has received increased attention from researchers, building operators, electric utilities, policymakers, and system operators as a tool to improve power grid reliability and reduce system costs. Before increasing reliance on demand flexibility, however, a better understanding of its availability is needed to inform planning efforts. This paper includes a review of the literature on current methods and data used to model the available flexibility of power delivered to customers. This review also summarizes how demand flexibility is defined and quantified to help inform future studies in this field. The results of this review illustrate the diversity found within this field of research and the innovation that researchers are employing to solve this complex problem.
Impact of Saharan Dust Intrusions on Atmospheric Boundary Layer Height over Madrid
Authors: Molero Francisco , Salvador Pedro , Pujadas Manuel
Published: December 2024

Atmospheric pollution caused by aerosols deteriorates air quality, increasing public health risks. Anthropogenic aerosols are usually located within the atmospheric boundary layer (ABL), which presents a daytime evolution that determines the air pollutants’ vertical mixing of those produced near the surface and, therefore, their ground-level concentration from local sources. Precise and complete characterization of the mixing layer is of crucial importance for numerical weather forecasting and climate models, but traditional methods such as radiosounding present some spatial and temporal limitations. Better resolutions have been obtained using lidar, which provides the aerosol vertical distribution. A particular type of lidar, the ceilometer, has demonstrated continuous measurement capabilities, providing vertical profiles with sub-minute time resolution and several-meter spatial resolution. Advanced methods, such as the recently developed STRATfinder algorithm, are required to estimate the ABL height in the presence of residual layers. More complex situations occur due to the advection of aerosols (e.g., due to long-range transport of desert dust, volcanic eruptions, or pyrocloud convection), producing a lofted layer in the free troposphere that may remain decoupled from the local ABL but can also be mixed. Aerosol-based methods for determination of the ABL height are challenging in those situations. The main objective of this research is the assessment of the impact of Saharan dust intrusions on the ABL using ceilometer signals, over a period of four years, 2020–2023. The ABL height database, obtained from ceilometer measurements every hour, is analyzed based on the most frequent synoptic patterns. A reduction in the ABL height was obtained from high dust load days (1576 ± 876 m) with respect to low dust load days (1857 ± 914 m), although it was still higher than clean days (1423 ± 772 m). This behavior is further studied discriminating by season and synoptic patterns. These results are relevant for health advice during Saharan dust intrusion days.
Theoretical Study of the Dissociative Recombination and Vibrational (De-)Excitation of HCNH+ and Its Isomers by Electron Impact
Authors: Ayouz Mehdi Adrien , Buch Arnaud
Published: December 2024

Protonated hydrogen cyanide, HCNH+, is one of the most important molecules of interest in the astrophysical and astrochemical fields. This molecule not only plays the role of a reaction intermediary in various types of interstellar reactions but was also identified in Titan’s upper atmosphere. The cross sections for the dissociative recombination (DR) and vibrational (de-)excitation (VE and VDE) of HCNH+ and its CNH2+ isomer are computed using a theoretical approach based on a combination of the normal mode approximation for the vibrational states of the target ions and the UK R-matrix code to evaluate electron-ion scattering matrices for fixed geometries of ions. The theoretical convoluted DR cross section for HCNH+ agrees well with the experimental data and a previous study. It was also found that the DR of the CNH2+ isomer is important, which suggests that this ion might be present in DR experiments of HCNH+. Moreover, the ab initio calculations performed on the H2CN+ isomer predict that this ion is a transition state. This result was confirmed by the study of the reaction path of the HCNH+ isomerization that was carried out by evaluating the intrinsic reaction coordinate (IRC). Finally, thermally averaged rate coefficients derived from the cross sections are provided for temperatures in the 10–10,000 K range. A comprehensive set of calculations is performed to assess the uncertainty of the obtained data. These results should help in modeling non-LTE spectra of HCNH+, taking into account the role of its most stable isomer, in various astrophysical environments.
SOC Estimation of a Lithium-Ion Battery at Low Temperatures Based on a CNN-Transformer and SRUKF
Authors: Gong Xun , Jiang Tianzhu , Zou Bosong , Wang Huijie , Yang Kaiyi , Liu Xinhua , Ma Bin , Lin Jiamei
Published: December 2024

As environmental regulations become stricter, the advantages of pure electric vehicles over fuel vehicles are becoming more and more significant. Due to the uncertainty of the actual operating conditions of the vehicle, accurate estimation of the state-of-charge (SOC) of the power battery under multi-temperature scenarios plays an important role in guaranteeing the safety, economy, and reliability of electric vehicles. In this paper, a SOC estimation method based on the fusion of convolutional neural network-transformer (CNN-Transformer) and square root unscented Kalman filter (SRUKF) for lithium-ion batteries in low-temperature scenarios is proposed. First, the CNN-Transformer base model is established. Then, the SRUKF algorithm is used to update the state of the Coulomb counting method results based on the base model results. Finally, ensemble learning theory is applied to estimate SOC in multi-temperature scenarios. Data is obtained from laboratory conditions at −20 °C, −7 °C, and 0 °C. The experimental results show that the SOC estimation method proposed in this study is stable in terms of the root mean square error (RMSE) being between 2.69% and 4.22%. The proposed base model is also compared with the long short-term memory (LSTM) network and gated recurrent unit (GRU) network to demonstrate its relative advantages.
Exploring Named Entity Recognition via MacBERT-BiGRU and Global Pointer with Self-Attention
Authors: Yuan Chengzhe , Tang Feiyi , Shan Chun , Shen Weiqiang , Lin Ronghua , Mao Chengjie , Li Junxian
Published: December 2024

Named Entity Recognition (NER) is a fundamental task in natural language processing that aims to identify and categorize named entities within unstructured text. In recent years, with the development of deep learning techniques, pre-trained language models have been widely used in NER tasks. However, these models still face limitations in terms of their scalability and adaptability, especially when dealing with complex linguistic phenomena such as nested entities and long-range dependencies. To address these challenges, we propose the MacBERT-BiGRU-Self Attention-Global Pointer (MB-GAP) model, which integrates MacBERT for deep semantic understanding, BiGRU for rich contextual information, self-attention for focusing on relevant parts of the input, and a global pointer mechanism for precise entity boundary detection. By optimizing the number of attention heads and global pointer heads, our model achieves an effective balance between complexity and performance. Extensive experiments on benchmark datasets, including ResumeNER, CLUENER2020, and SCHOLAT-School, demonstrate significant improvements over baseline models.
The Gut–Lung Axis During Ethanol Exposure and a Pseudomonas aeruginosa Bacterial Challenge
Authors: Santilli Anthony , Han Yingchun , Yan Hannah , Sangwan Naseer , Cresci Gail A. M.
Published: December 2024

Background: Susceptibility to and severity of pulmonary infections increase with ethanol consumption. We have previously shown that ethanol-induced changes in the gut microbiome disrupt gut homeostasis, allowing for the translocation of proinflammatory mediators into the circulation and eliciting an immune response in the lung. Additionally, targeting the gut with butyrate supplementation not only rescues ethanol-induced disruptions to gut health but also reverses aspects of immune dysregulation in the lungs. Here, we assessed the impact of this connection on a subsequent infectious challenge. Methods: To assess if ethanol-induced alterations to the gut microbiome could also impact the host response to a pulmonary infectious challenge, we employed a chronic-binge ethanol-feeding mouse model followed by a nasal instillation of Pseudomonas aeruginosa. Results: In addition to altering gut microbiome composition and metabolism, ethanol consumption also disrupted the local immune response as demonstrated by suppressed cecal SIgA levels, a decreased presence of CD3+CD8a+ cytotoxic T cells in the proximal colon mucosa, and depleted CD3+CD8a+ T cells and CD11c+CD8a+ dendritic cells in the mesenteric lymph nodes. Circulatory Ly6G+CD11b+ neutrophils increased, indicating a systemic change in immune-cell presence with ethanol exposure. Ethanol exposure increased CD11c+CD64+ macrophages and Ly6G+CD11b+ neutrophils in the lungs, with neutrophil populations being further exacerbated during a bacterial challenge with Pseudomonas aeruginosa. Lipocalin 2, a marker of oxidative stress, was also elevated with ethanol consumption, though not with infection. Conclusions: These data suggest that ethanol-induced changes in the gut microbiome and immune environment are linked to dysfunctional immune responses in the intestine, blood, and the lungs, compromising the pulmonary immune response during an infectious challenge in mice.
Choroidal Response to Intravitreal Bevacizumab Injections in Treatment-Naïve Macular Neovascularization Secondary to Chronic Central Serous Chorioretinopathy
Authors: Rabinovitch David , Shulman Shiri , Goldenberg Dafna , Wang Liang , Iyer Prashanth , Loewenstein Anat , Igra Noah , Levine Olivia , Herrera Gissel , Trivizki Omer
Published: December 2024

Background/Objectives: To evaluate the impact of intravitreal bevacizumab (IVB) therapy on anatomical and visual outcomes in patients with macular neovascularization (MNV) secondary to chronic central serous chorioretinopathy (cCSC). Methods: This retrospective observational study reviewed the medical records of treatment-naïve patients diagnosed with cCSC complicated by MNV and treated with IVB injections over a 5-year period. The presence of MNV was confirmed using optical coherence tomography angiography (OCTA). Best-corrected visual acuity (BCVA), subfoveal choroidal thickness (SFCT), and subretinal fluid (SRF) were recorded pre- and post-IVB treatment. Results: Twenty-two eyes of 22 patients (mean age, 68 ± 11 years) were included. After a mean follow-up of 21.0 ± 14.6 months, SRF significantly decreased from baseline (176.86 ± 115.62 µm) to the final follow-up (80.95 ± 87.32 µm, p = 0.003). A greater SRF reduction was associated with more injections (>7) (p = 0.047). However, no significant changes were observed in BCVA (p > 0.05) or SFCT (p > 0.05), irrespective of follow-up duration or injection frequency. Complete resolution of SRF was achieved in nine patients (40.9%), and a significantly greater reduction in SFCT was observed in complete responders compared to non-responders (p = 0.03). Conclusions: IVB therapy significantly reduced SRF in cCSC patients with secondary MNV, though it did not lead to visual improvement or significant changes in SFCT. However, greater choroidal thinning in patients with complete fluid resorption may suggest distinct underlying mechanisms or alternative sources of subretinal fluid beyond the MNV itself.
A Novel Application of B.EL.D™ Technology: Biosensor-Based Detection of Salmonella spp. in Food
Authors: Konstantinou Lazaros , Varda Eleni , Apostolou Theofylaktos , Loizou Konstantinos , Dougiakis Lazaros , Inglezakis Antonios , Hadjilouka Agni
Published: December 2024

The prevalence of foodborne diseases is continuously increasing, causing numerous hospitalizations and deaths, as well as money loss in the agri-food sector and food supply chain worldwide. The standard analyses currently used for bacteria detection have significant limitations with the most important being their long procedural time that can be crucial for foodborne outbreaks. In this study, a biosensor system able to perform robust and accurate detection of Salmonella spp. in meat products was developed. To achieve this, a portable device developed by EMBIO Diagnostics called B.EL.DTM (Bio Electric Diagnostics) and cell-based biosensor technology (BERA) were used. Results indicated that the new method could detect the pathogen within 24 h after a 3-min analysis and discriminate samples with and without Salmonella with high accuracy. Achieving an accuracy of 86.1% and a detection limit (LOD) of 1 log CFU g−1, this innovative technology enables rapid and sensitive identification of Salmonella spp. in meat and meat products, making it an excellent tool for pathogen screening.
Sensing Biomechanical Alterations in Red Blood Cells of Type 1 Diabetes Patients: Potential Markers for Microvascular Complications
Authors: Di Santo Riccardo , Niccolini Benedetta , Rizzi Alessandro , Bertini Laura , Marafon Denise Pires , Vaccaro Maria , Cristallo Federica , Rosa Enrico , Tartaglione Linda , Leo Laura , De Spirito Marco , Ciasca Gabriele , Pitocco Dario
Published: December 2024

In physiological conditions, red blood cells (RBCs) demonstrate remarkable deformability, allowing them to undergo considerable deformation when passing through the microcirculation. However, this deformability is compromised in Type 1 diabetes mellitus (T1DM) and related pathological conditions. This study aims to investigate the biomechanical properties of RBCs in T1DM patients, focusing on identifying significant mechanical alterations associated with microvascular complications (MCs). We conducted a case-control study involving 38 T1DM subjects recruited from the Diabetes Care Unit at Fondazione Policlinico Gemelli Hospital, comprising 22 without MCs (control group) and 16 with MCs (pathological group). Atomic Force Microscopy was employed to assess RBC biomechanical properties in a liquid environment. We observed significant RBC stiffening in individuals with MCs, particularly during large indentations that mimic microcirculatory deformations. Univariate analysis unveiled significant differences in RBC stiffness (median difference 0.0006 N/m, p = 0.012) and RBC counts (median difference −0.39 × 1012/L, p = 0.009) between the MC and control groups. Bivariate logistic regression further demonstrated that combining these parameters could effectively discriminate between MC and non-MC conditions, achieving an AUC of 0.82 (95% CI: 0.67–0.97). These findings reveal the potential of RBC biomechanical properties as diagnostic and monitoring tools in diabetes research. Exploring RBC mechanical alterations may lead to the development of novel biomarkers, which, in combination with clinical markers, could facilitate the early diagnosis of diabetes-related complications.
Prospects in the Use of Cannabis sativa Extracts in Nanoemulsions
Authors: Vitola Ian , Angulo Carlos , Baptista-Rosas Raul C. , Anaya-Esparza Luis Miguel , Escalante-García Zazil Yadel , Villarruel-López Angélica , Silva-Jara Jorge Manuel
Published: December 2024

Cannabis sativa plants have been widely investigated for their specific compounds with medicinal properties. These bioactive compounds exert preventive and curative effects on non-communicable and infectious diseases. However, C. sativa extracts have barely been investigated, although they constitute an affordable option to treat human diseases. Nonetheless, antioxidant, antimicrobial, and immunogenicity effects have been associated with C. sativa extracts. Furthermore, innovative extraction methods in combination with nanoformulations have been proposed to increase desirable compounds’ availability, distribution, and conservation, which can be aided by modern computational tools in a transdisciplinary approach. This review aims to describe available extraction and nanoformulation methods for C. sativa, as well as its known antioxidant, antimicrobial, and immunogenic activities. Critical points on the use of C. sativa extracts in nanoformulations are identified and some prospects are envisaged.
A Review of the Consequences of Gut Microbiota in Neurodegenerative Disorders and Aging
Authors: Menezes Amanda A. , Shah Zahoor A.
Published: December 2024

Age-associated alterations in the brain lead to cognitive deterioration and neurodegenerative disorders (NDDs). This review with a particular focus on Alzheimer’s disease (AD), emphasizes the burgeoning significance of the gut microbiota (GMB) in neuroinflammation and its impact on the gut–brain axis (GBA), a communication conduit between the gut and the central nervous system (CNS). Changes in the gut microbiome, including diminished microbial diversity and the prevalence of pro-inflammatory bacteria, are associated with AD pathogenesis. Promising therapies, such as fecal microbiota transplantation (FMT), probiotics, and prebiotics, may restore gut health and enhance cognitive performance. Clinical data remain insufficient, necessitating further research to elucidate causes, enhance therapy, and consider individual variances. This integrative approach may yield innovative therapies aimed at the GMB to improve cognitive function and brain health in older people.
The Association of Family Incivility with Adolescent Depression: A Moderated Mediation Model
Authors: Miao Miao , Jin Shuai , Gan Yiqun
Published: December 2024

Negative family interactions have an adverse impact on adolescent mental health. The present study focused on the influence of family incivility on adolescent depression. In order to examine the association of family incivility with depression, an integrated framework was constructed to explore the mediating role of self-compassion and the moderating role of sex differences. Two waves of data were collected from 999 Chinese senior high school students (43.6% males and 56.4% females), with a mean age of 16.58 ± 0.54 years. Time 1 family incivility was positively associated with depression at Time 2 (r = 0.40, p < 0.001). Sex differences moderated the link between family incivility and self-compassion, with their association being significant in females (B = −0.07, SE = 0.03, p = 0.013) but not in males (B = 0.03, SE = 0.03, p = 0.376). Regarding the effect of family incivility on depression, the direct effect was significant only in males (B = 0.13, SE = 0.03, p < 0.001), whereas the indirect effect via self-compassion was significant only in females (B = 0.01, SE = 0.01, 95% CI [0.0010, 0.0232]). The present findings revealed a positive association between family incivility and adolescent depression. Moreover, family incivility has a direct impact on depression in male adolescents and an indirect impact through self-compassion in female adolescents. These findings underscore the important role of adolescent sex differences in the impact of family incivility on adolescent depression and highlight the practical importance of developing interventions to reduce family incivility.
Cynical Hostility, Intimacy and Relationship Satisfaction: The Role of Depressive Symptoms
Authors: Segel-Karpas Dikla , Estlein Roi , Elran-Barak Roni
Published: December 2024

Background: An individual’s own and their perceived partner cynical hostility are conceptualized as vulnerability factors, decreasing couples’ intimacy and relationship satisfaction. The perceived partner cynical hostility may be especially harmful when distress is high. Method: Longitudinal data were collected in two waves (during and after the COVID-19 lockdown), relying on the respondents’ self-reports. Results: Intimacy mediated the association between perceived partner cynical hostility and relationship satisfaction in both waves. The association between perceived partner cynical hostility and intimacy was stronger when depressive symptoms were higher. No longitudinal effects were found. Conclusions: The perceived partner cynical hostility could be a meaningful vulnerability factor, hampering the ability to establish intimacy and, in turn, relationship satisfaction. The toll may be greater when individuals experience greater vulnerability.
Risk−Based Cost−Benefit Optimization Design for Steel Frame Structures to Resist Progressive Collapse
Authors: Guo Feng , Li Xuancen , Xu Aiyan , Zhang Yuchen , Pan Wanping
Published: December 2024

The design of structures to resist progressive collapse primarily focuses on enhancing structural safety and robustness. However, given the low probability of accidental events, such designs often lead to a negative cost–benefit. To address this problem, this paper uses risk analysis to optimize the progressive collapse resistance design of steel frame structures. The elements’ cross-section design for the progressive collapse resistance of steel frame structures is optimized using genetic algorithms and SAP2000 23, which identify the structural model with the minimum robustness index while ensuring safety. The results show that the risk-based robustness index can effectively assess the cost of progressive collapse design. More importantly, the optimization model can rapidly identify the most cost-effective structural design solution that complies with progressive collapse resistance guidelines, enhancing the simplicity and usability of the structure design optimization process. Additionally, the integration of the SAP2000 API with Python 3.8 automation streamlines the parameterization process, minimizes manual errors, and enhances the precision and efficiency of the structural design optimization. Finally, the model’s effectiveness is validated through a case study, where the refined single-frame structure shows a reduction in initial construction and collapse-related costs by 2.4% and 9.1%, respectively. Meanwhile, the three-dimensional frame shows a 2.9% rise in initial costs but a 13.5% decrease in total collapse-resistant design costs, illustrating the model’s ability to balance safety with cost-effectiveness.
The Influence of Sex and Age on Survival in Patients with Hepatocellular Carcinoma
Authors: Radu Iuliana Pompilia , Scheiner Bernhard , Schropp Jonas , Delgado Maria Gabriela , Schwacha-Eipper Birgit , Jin Chaonan , Dufour Jean-Francois , Pinter Matthias
Published: December 2024

Background and Aim: Age and biological sex are risk factors for hepatocellular carcinoma (HCC) occurrence, but their impact on overall survival (OS) is a matter of debate. This study aims to investigate how sex and age at diagnosis, along with other associated factors (i.e., comorbidities, etiologies, therapy) impact OS in the HCC population. Method: Data from two HCC cohorts—a prospective registry from the University Hospital of Bern, Switzerland, and a retrospective registry from General Hospital Vienna, Austria—were combined and analyzed. Clinical and laboratory data were reviewed, and OS was compared using Kaplan-Meier curves and the log-rank test. Cox regression models with penalized splines were applied to examine how age at diagnosis influenced OS. Results: Of 1547 HCC patients, 1284 (84.1%) were male. Females were older (67 vs. 63 years, p < 0.001) and had lower rates of liver cirrhosis (p < 0.001), cardiac comorbidities (p < 0.001), and diabetes (p < 0.001). No significant difference in median OS between men and women was observed (18 months vs. 16 months, p = 0.304). Mortality risk increased with age, particularly between 60 and 70 years. However, after adjusting for treatment, the age effect became non-significant (p = 0.171). Conclusions: After controlling the model for therapy, neither age nor sex independently influenced OS in HCC patients, underscoring the impact of therapy on survival.