bluuebunny/crossref_metadata_2025_split huggingface dataset:
VISTA drives macrophages towards a pro-tumoral phenotype that promotes cancer cell phagocytosis yet down-regulates T cell responses
Authors: Lin Yusheng , Choukrani Ghizlane , Dubbel Lena , Rockstein Lena , Freile Jimena Alvarez , Qi Yuzhu , Wiersma Valerie , Zhang Hao , Koch Karl-Wilhelm , Ammatuna Emanuele , Schuringa Jan Jacob , van Meerten Tom , Huls Gerwin , Bremer Edwin 
Published: March 2024

Abstract
Background
VISTA is a well-known immune checkpoint in T cell biology, but its role in innate immunity is less established. Here, we investigated the role of VISTA on anticancer macrophage immunity, with a focus on phagocytosis, macrophage polarization and concomitant T cell activation.

Methods
Macrophages, differentiated from VISTA overexpressed THP-1 cells and cord blood CD34+ cell-derived monocytes, were used in phagocytosis assay using B lymphoma target cells opsonized with Rituximab. PBMC-derived macrophages were used to assess the correlation between phagocytosis and VISTA expression. qRT-PCR, flow cytometry, and enzyme-linked immunosorbent assay were performed to analyze the impact of VISTA on other checkpoints and M1/M2-like macrophage biology. Additionally, flow cytometry was used to assess the frequency of CD14+ monocytes expressing VISTA in PBMCs from 65 lymphoma patients and 37 healthy donors.

Results
Ectopic expression of VISTA in the monocytic model cell line THP-1 or in primary monocytes triggered differentiation towards the macrophage lineage, with a marked increase in M2-like macrophage-related gene expression and decrease in M1-like macrophage-related gene expression. VISTA expression in THP-1 and monocyte-derived macrophages strongly downregulated expression of SIRPα, a prominent ‘don’t eat me’ signal, and augmented phagocytic activity of macrophages against cancer cells. Intriguingly, expression of VISTA’s extracellular domain alone sufficed to trigger phagocytosis in ∼ 50% of cell lines, with those cell lines also directly binding to recombinant human VISTA, indicating ligand-dependent and -independent mechanisms. Endogenous VISTA expression was predominantly higher in M2-like macrophages compared to M0- or M1-like macrophages, with a positive correlation observed between VISTA expression in M2c macrophages and their phagocytic activity. VISTA-expressing macrophages demonstrated a unique cytokine profile, characterized by reduced IL-1β and elevated IL-10 secretion. Furthermore, VISTA interacted with MHC-I and downregulated its surface expression, leading to diminished T cell activation. Notably, VISTA surface expression was identified in monocytes from all lymphoma patients but was less prevalent in healthy donors.

Conclusions
Collectively, VISTA expression associates with and drives M2-like activation of macrophages with a high phagocytic capacity yet a decrease in antigen presentation capability to T cells. Therefore, VISTA is a negative immune checkpoint regulator in macrophage-mediated immune suppression.
Vaccination with a combination of STING agonist-loaded lipid nanoparticles and CpG-ODNs protects against lung metastasis via the induction of CD11bhighCD27low memory-like NK cells
Authors: Khalifa Alaa M. , Nakamura Takashi , Sato Yusuke , Harashima Hideyoshi 
Published: March 2024

Abstract
Background
Natural killer (NK) cells are effective in attacking tumor cells that escape T cell attack. Memory NK cells are believed to function as potent effector cells in cancer immunotherapy. However, knowledge of their induction, identification, and potential in vivo is limited. Herein, we report on the induction and identification of memory-like NK cells via the action of a combination of a stimulator of interferon genes (STING) agonist loaded into lipid nanoparticles (STING-LNPs) and cytosine-phosphorothioate-guanine oligodeoxynucleotides (CpG-ODNs), and the potential of the inducted memory-like NK cells to prevent melanoma lung metastasis.

Methods
The antitumor effects of either the STING-LNPs, CpG-ODNs, or the combination therapy were evaluated using a B16-F10 lung metastasis model. The effect of the combined treatment was evaluated by measuring cytokine production. The induction of memory-like NK cells was demonstrated via flow cytometry and confirmed through their preventative effect.

Results
The combination of STING-LNPs and CpG-ODNs tended to enhance the production of interleukin 12 (IL-12) and IL-18, and exerted a therapeutic effect against B16-F10 lung metastasis. The combination therapy increased the population of CD11bhighCD27low NK cells. Although monotherapies failed to show preventative effects, the combination therapy induced a surprisingly strong preventative effect, which indicates that CD11bhighCD27low cells could be a phenotype of memory-like NK cells.

Conclusion
As far as could be ascertained, this is the first report of the in vivo induction, identification, and confirmation of a phenotype of the memory-like NK cells through a prophylactic effect via the use of an immunotherapeutic drug. Our findings provide novel insights into the in vivo induction of CD11bhighCD27low memory-like NK cells thus paving the way for the development of efficient immunotherapies.

Graphical Abstract
The financial and social impacts of the COVID-19 pandemic on youth with eating disorders, their families, clinicians and the mental health system: a mixed methods cost analysis
Authors: Obeid Nicole , Silva-Roy Patricia , Booij Linda , Coelho Jennifer S. , Dimitropoulos Gina , Katzman Debra K. 
Published: March 2024

Abstract
Background
The onset of the COVID-19 pandemic has had an adverse impact on children, youth, and families with eating disorders (EDs). The COVID-19 pandemic exacerbated pre-existing personal and financial costs to youth, caregivers, and health professionals accessing or delivering ED services. The objectives of this mixed methods study were to (1) understand the indirect, direct medical and non-medical costs reported by youth, caregivers, and clinicians; (2) understand how the COVID-19 pandemic may have impacted these costs, and (3) explore implications of these costs with regards to barriers and resources to inform future decisions for the ED system of care.

Methods
Youth (aged 16–25 years) with lived/living experience, primary caregivers, clinicians, and decision-makers were recruited with support from various partners across Canada to complete group specific surveys. A total of 117 participants responded to the survey. From those respondents, 21 individuals volunteered to further participate in either a discussion group or individual interview to provide additional insights on costs.

Results
Youth and primary caregivers reported costs relating to private services, transportation and impacts of not attending school or work. Additionally, primary caregivers reported the top direct medical cost being special food or nutritional supplements (82.8%). In discussion groups, youth and caregivers elaborated further on the challenges with long waitlists and cancelled services, impact on siblings and effect on family dynamics. Clinicians and decision-makers reported increased work expectations (64.3%) and fear/isolation due to COVID-19 in the workplace (58.9%). Through discussion groups, clinicians expanded further on the toll these expectations took on their personal life. Approximately 1 in 3 health professionals reported contemplating leaving their position in 1–2 years, with greater than 60% of this group stating this is directly related to working during the pandemic.

Conclusions
Findings demonstrate the need for increased support for youth and caregivers when accessing ED services both during crisis and non-crisis times. Additionally, attention must be given to acknowledging the experience of health professionals to support better retention and resource management as they continue to navigate challenges in the health care system.
Agricultural habitat use and selection by a sedentary bird over its annual life cycle in a crop-depredation context
Authors: Chambon Rémi , Paillisson Jean-Marc , Fournier-Sowinski Jérôme , Dugravot Sébastien 
Published: March 2024

Abstract
Background
Modern agriculture has undoubtedly led to increasing wildlife-human conflicts, notably concerning bird damage in productive and attractive crops during some parts of the annual cycle. This issue requires utmost attention for sedentary birds that may impact agricultural crops at any stage of their annual life cycle. Reducing bird-human conflicts requires a better understanding of the relationship between bird foraging activity and the characteristics of agricultural areas, notably with respect to changes in food-resource availability and crop sensitivity across the year.

Methods
We explored how GPS-tagged adult male western jackdaws– sedentary corvids– utilize agricultural areas throughout their annual cycle, in a context of crop depredation. More precisely, we described their daily occurrence distribution and the extent of habitat use and selection consistency with respect to landscape composition across time.

Results
Jackdaws moved in the close agricultural surroundings of their urban nesting place over the year (< 2.5 km from the nest, on average). Daily occurrence distributions were restricted (< 2.2 km2), relatively centered on the nesting locality (distance between the daily occurrence centroid and the nest < 0.9 km), and rather spatially stable during each annual life-cycle period (overlap range: 63.4–76.1%). Their foraging patterns highlighted that they fed mainly in grasslands all year round, and foraged complementarily and opportunistically in maize (during sowing– coinciding with the first stages of the birds’ breeding period) and cereal crops (during harvesting– their post-fledging period).

Conclusions
Our findings demonstrate the very limited space use by breeding male jackdaws which foraged preferentially in grasslands. We call for future investigations in other agricultural contexts and also considering non-breeders for extrapolation purposes.
Quantitative analysis of the use of virtual reality environments among higher education professors
Authors: Antón-Sancho Álvaro , Vergara Diego , Fernández-Arias Pablo 
Published: March 2024

AbstractVirtual Reality (VR) is a computer-generated environment with noteworthy didactic applications in different educational levels and areas of knowledge. The study of the perceptions of the agents involved about the use of VR in lectures is a fruitful line of research because it has implications in terms of the measures to be taken to improve the training and competence of professors in its use. In this paper, a quantitative, descriptive, and correlational research is carried out on the assessments of a sample of 1638 Latin American university professors on both (i) the didactic use of VR and (ii) the influence of the professors' area of knowledge on these assessments. For this purpose, a validated questionnaire was used, the responses to which were subjected to statistical analysis. As a result, it was found that the ratings of VR are very high, but professors believe that their digital skills for its use are insufficient. In addition, the professors' area of knowledge significantly influences their ratings, being higher in the areas of knowledge in which professors have a better self-concept of their digital skills. Furthermore, gender gaps have also been identified in the answers given, which behave differently according to the area of knowledge. Finally, some conclusions, implications, and recommendations are drawn from the results obtained.
Optimal Implant Sizing Using Machine Learning Is Associated With Increased Range of Motion After Cervical Disk Arthroplasty
Authors: Lakomkin Nikita , Pennington Zach , Bhandarkar Archis , Mikula Anthony L. , Michalopoulos Giorgos D. , Katsos Konstantinos , Chen Selby , McClendon Jamal , Freedman Brett A. , Bydon Mohamad 
Published: March 2024

BACKGROUND AND OBJECTIVES:
Cervical disk arthroplasty (CDA) offers the advantage of motion preservation in the treatment of focal cervical pathology. At present, implant sizing is performed using subjective tactile feedback and imaging of trial cages. This study aims to construct interpretable machine learning (IML) models to accurately predict postoperative range of motion (ROM) and identify the optimal implant sizes that maximize ROM in patients undergoing CDA.

METHODS:
Adult patients who underwent CDA for single-level disease from 2012 to 2020 were identified. Patient demographics, comorbidities, and outcomes were collected, including symptoms, examination findings, subsidence, and reoperation. Affected disk height, healthy rostral disk height, and implant height were collected at sequential time points. Linear regression and IML models, including bagged regression tree, bagged multivariate adaptive regression spline, and k-nearest neighbors, were used to predict ROM change. Model performance was assessed by calculating the root mean square error (RMSE) between predicted and actual changes in ROM in the validation cohort. Variable importance was assessed using RMSE loss. Area under the curve analyses were performed to identify the ideal implant size cutoffs in predicting improved ROM.

RESULTS:
Forty-seven patients were included. The average RMSE between predicted and actual ROM was 7.6° (range: 5.8-10.1) in the k-nearest neighbors model, 7.8° (range: 6.5-10.0) in the bagged regression tree model, 7.8° (range: 6.2-10.0) in the bagged multivariate adaptive regression spline model, and 15.8° (range: 14.3-17.5°) in a linear regression model. In the highest-performing IML model, graft size was the most important predictor with RMSE loss of 6.2, followed by age (RMSE loss = 5.9) and preoperative caudal disk height (RMSE loss = 5.8). Implant size at 110% of the normal adjacent disk height was the optimal cutoff associated with improved ROM.

CONCLUSION:
IML models can reliably predict change in ROM after CDA within an average of 7.6 degrees of error. Implants sized comparably with the healthy adjacent disk may maximize ROM.
The Impact of Passive Social Media Viewers in Influence Maximization
Authors: Kahr Michael , Leitner Markus , Ljubić Ivana 
Published: March 2024

A frequently studied problem in the context of digital marketing for online social networks is the influence maximization problem that seeks for an initial seed set of influencers to trigger an information propagation cascade (in terms of active message forwarders) of expected maximum impact. Previously studied problems typically neglect that the probability that individuals passively view content without forwarding it is much higher than the probability that they forward content. Considering passive viewing enables us to maximize more natural (social media) marketing metrics, including (a) the expected organic reach, (b) the expected number of total impressions, or (c) the expected patronage, all of which are investigated in this paper for the first time in the context of influence maximization. We propose mathematical models to maximize these objectives, whereby the model for variant (c) includes individual’s resistances and uses a multinomial logit model to model customer behavior. We also show that these models can be easily adapted to a competitive setting in which the seed set of a competitor is known. In a computational study based on network graphs from Twitter (now X) and from the literature, we show that one can increase the expected patronage, organic reach, and number of total impressions by 36% on average (and up to 13 times in particular cases) compared with seed sets obtained from the classical maximization of message-forwarding users. History: Accepted by Andrea Lodi, Area Editor for Design & Analysis of Algorithms—Discrete. Funding: This work was supported by the Federal Ministry of Education, Science and Research of Austria and by the Austrian Agency for International Mobility and Cooperation in Education, Science and Research [Reference ICM-2019-13384]. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2023.0047 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2023.0047 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .
Computing Bipath Multicommodity Flows with Constraint Programming–Based Branch-and-Price-and-Cut
Authors: Zhang Jiachen , Magnouche Youcef , Bauguion Pierre , Martin Sebastien , Beck J. Christopher 
Published: March 2024

We propose a constraint programming (CP)–based branch-and-price-and-cut framework to exactly solve bipath multicommodity flow (MCF): an MCF problem with two paths for each demand. The goal is to route demands in a capacitated network under the minimum cost. The two paths must have disjoint arcs, and the delays accumulated along the two paths must be within a small deviation of each other. CP is used at multiple points in this framework: for solving pricing problems, for cut generation, and for primal and branching node heuristics. These modules use a CP solver designed for network routing problems and can be adapted to other combinatorial optimization problems. We also develop a novel, complete, two-level branching scheme. On a set of diverse bipath MCF instances, experimental results show that our algorithm significantly outperforms monolithic CP and mixed integer linear programming models and demonstrate the efficiency and flexibility brought by the tailored integration of linear programming and CP methodologies. History: Accepted by Pascal Van Hentenryck, Area Editor for Computational Modeling: Methods & Analysis. Funding: This work was supported by the Natural Sciences and Engineering Research Council of Canada; Huawei Technologies. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2023.0128 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2023.0128 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .
Amazon Locker Capacity Management
Authors: Sethuraman Samyukta , Bansal Ankur , Mardan Setareh , Resende Mauricio G. C. , Jacobs Timothy L. 
Published: March 2024

Amazon Locker is a self-service delivery or pickup location where customers can pick up packages and drop off returns. A basic first-come-first-served policy for accepting package delivery requests to lockers results in lockers becoming full with standard shipping speed (3- to 5-day shipping) packages, leaving no space for expedited packages, which are mostly next-day or two-day shipping. This paper proposes a solution to the problem of determining how much locker capacity to reserve for different ship-option packages. Yield management is a much-researched field with popular applications in the airline, car rental, and hotel industries. However, Amazon Locker poses a unique challenge in this field because the number of days a package will wait in a locker (package dwell time) is, in general, unknown. The proposed solution combines machine learning techniques to predict locker demand and package dwell time with linear programming to maximize throughput in lockers. The decision variables from this optimization provide optimal capacity reservation values for different ship options. This resulted in a year-over-year increase of 9% in Locker throughput worldwide during the holiday season of 2018, impacting millions of customers. History: This paper was refereed.
Nanohybridization Effects on Impact Behavior of Basalt/Glass Fiber Reinforced Epoxy Hybrid Nanocomposites
Authors: V. Boobalan  , T. Sathish  
Published: March 2024

Basalt fiber-based composites have received greater attention from manufacturers and researchers recently for use in a variety of structural applications, owing to their high strength-to-weight ratio, high stiffness, and excellent mechanical properties. The main objective of the current research is to examine the impact behavior of hybrid basalt/glass fiber reinforced composites that have been altered by the addition of MWCNTs and SiO2 (Nano silica) to the epoxy matrix as per the ASTM standards. All of the composites were created using Manual lay-up method followed by Compression molding using novel symmetric stacking sequence configurations of B/GG/BB/GG/BB/GG/B fibers with nanoparticles at weight percentages of 0%, 1% (0.5% MWCNTs + 0.5% SiO2) 2% (1% MWCNTs + 1% SiO2) and 3% (1.5 % MWCNTs + 1.5% SiO2). The homogeneous dispersion of nanoparticles in the epoxy matrix was achieved by ultrasonicator and magnetic stirrers. The maximum value of Izod impact strength was recorded as 203 kJ/m2 for the composite filled with 2 wt. % of nano-fillers. In comparison to the composite containing no fillers, the composite adding 2 wt. % showed a 24% improvement from 167 to 203 kJ/m2 in Izod impact resistance. It was observed that increasing the weight percentage of fillers in composites causes insufficient interfacial interaction between the matrix and fibers, thereby decreasing their impact resistance. The load transmission between the matrix and fibers is increased by the presence of MWCNTs/SiO2 at the fiber/matrix interface, which also improves the fracture toughness. According to images obtained by Scanning Electron Microscopy of the fracture surfaces of impact-tested specimens, the major reasons for failure include fiber/matrix deboning, fiber breaking, fiber fracture and fiber pull-out.
Bioremediation of Kraft Lignin in Wastewater: Optimization of Temperature and Isolation of Valuable Compounds
Authors: C. Swati  , J. Anandkumar  
Published: March 2024

Conventional methods for the treatment of complex lignin found in the pulp and paper mill effluent is a strenuous and expensive process. Microbial degradation is a promising technique to degrade lignin efficiently due to its adaptability and rapid growth of microbes in diverse environments. This study is focused on the isolation of potential ligninolytic bacterial strains from agricultural soil and decomposed wood sources for successful degradation of lignin present in the wastewater. Initially, 15 ligninolytic strains were identified and three dominant species, Staphylococcus lentus (SB5), Bacillus megaterium (RWB15) and Pseudomonas geniculata (RWP9) were isolated as per their growth tolerance pattern with different lignin concentrations. The lignin degradation study was carried out at different temperatures (25-45℃) with 1000 mg/l of feed lignin concentrations. The optimum degradation temperature of all the strains fell within the range 30-35℃. The maximum lignin degradation of SB5, RWB15 and RWP9 was identified as 89, 77 and 90% at the end of the 6th, 3rd and 7th day of biodegradation, respectively. There was a steep reduction of COD by all three microbes before attaining the stationary phase and thereafter COD reduction was sluggish due to the death phase. Besides, the microbes used in this study showed the transformation of lignin into valuable low-molecular by-products, vanillin, vanillic acid and adipic acid with their concentration being quantified as 28, 101 and 130 mg/l, respectively. This study shows the successful degradation of waste lignin and the recovery of valuable byproducts from waste streams.