bluuebunny/crossref_metadata_2025_split huggingface dataset:
International business education experiences through temporary learning environments: evidence from Atlantic Canada
Authors: Kalafsky Ronald V. , Raymond Mark P. 
Published: January 2025

Purpose
International environments introduce a number of learning-related barriers for students endeavoring to understand global business practices. One way in which these obstacles can be addressed is through participation in temporary learning environments (TLEs), such as trade fairs and similar events. This paper aims to examine how international trade missions (ITMs) – a type of short-term, study-abroad experience – were used as TLEs by students at an Atlantic Canada university as part of their EMBA curriculum to gain practical experience in international business environments.

Design/methodology/approach
This study explores the ways in which students benefitted from participation in the ITMs and resulting TLEs. Accordingly, an online survey that explored export-related issues and learning outcomes was administered to EMBA students who participated in this program to ascertain the ways in which these events furthered their educational experience and how the ITMs enabled them to perceive challenges and strategies related to international market expansion.

Findings
A survey of ITM participants revealed that students gained insights into firm-level barriers to internationalization in addition to a practical understanding of general challenges in international trade. At the same time, some observations suggested that more emphasis could be placed on pre-trip preparations and post-trip networking. The paper concludes with discussions on how short-term study abroad opportunities can serve as TLEs, in addition to proposing future ways in which the ITMs could provide even more experiences for the students.

Originality/value
The value-added from this paper is found in two ways. The first is to illustrate how ITMs can be a form of a TLE for students. The second, linked contribution, is to reinforce and to provide further evidence on how the TLEs – a short study-abroad opportunity – can be an environment in which students obtain valuable, hands-on international business experience.
Trends and hotspots in public food procurement: exploring planetary boundaries and human needs in an integrative literature review
Authors: Akim Erica Kushihara , Silva Diogo Aparecido Lopes , Faria Luiz Carlos de 
Published: January 2025

Purpose
Using an Integrative Literature Review (ILR), this study aims to investigate the components defining the Safe and Just Operating Space (SJOS) within food systems and assess their applicability in decision-making for public food procurement (PFP).

Design/methodology/approach
Data concerning SJOS implementation in food systems and the criteria used in PFP were retrieved from the Web of Science and Scopus databases, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol.

Findings
The analysis of the literature highlights that climate change (n = 31; 17%) and water use (n = 29; 16%) are the primary focus areas regarding Planetary Boundaries (PB), followed the nitrogen cycle, land use, biodiversity loss and the phosphorus cycle. In PFP, key criteria linked to PB encompass climate change (n = 19; 7.2%), water use (n = 17; 6.44%) and chemical pollution (n = 17; 6.44%). The social and ethical dimensions underscore labour (n = 18; 6.82%), water (n = 17; 6.44%), income (n = 16; 6.06%) and energy (n = 16; 6.06%).

Research limitations/implications
Despite the strengths of this study, certain limitations should be acknowledged. Although the inclusion and exclusion criteria for the reviewed articles were clearly defined, it is possible that relevant literature was unintentionally excluded. Expanding the scope to include grey literature – such as government documents, reports, policy statements and statistical reports – could provide additional insights and broaden the scope of the findings. Moreover, the search was limited to the Web of Science and Scopus databases, which may have resulted in the omission of relevant studies, particularly those published in non-English languages or not indexed journals.

Practical implications
The identified procurement criteria can help public administrators develop guidelines and tools for food procurement that consider the SJOS.

Social implications
This paper offers an understanding of the connection between planetary processes and human well-being in the context of PFP.

Originality/value
This pioneering research lays the groundwork for future agendas in this field and encourages reflection on critical factors essential for selecting methods and standards applied in practical public procurement.
Understanding the influence of ride-sharing value on consumers’ continuance intention
Authors: Chen Hao , Zhou Xi 
Published: January 2025

Purpose
This study aims to understand the mechanism by which the value of ride-sharing services influences consumers’ continuance intention.

Design/methodology/approach
The authors collected data from 484 Chinese ride-sharing respondents and analyzed them using partial least squares structural equation modeling.

Findings
The results show that hedonic value, social connection value and environmental value positively affect consumers’ cognitive fit and emotional fit, while utilitarian value has no significant effect on either cognitive fit or emotional fit. In addition, both cognitive fit and emotional fit significantly affect consumers’ satisfaction and continuance intention. Furthermore, satisfaction mediates the effects of cognitive and emotional fit on continuance intention.

Practical implications
Ride-sharing practitioners should have a clear understanding of all the value dimensions of ride-sharing services, which would subsequently increase customers’ continuance intention.

Originality/value
This study defines and divides the dimensions of ride-sharing value and demonstrates the significant impact of environmental value on the sustainability of ride-sharing services. This study extends fit theory by dividing it into two dimensions.
Pancreatic endometrioma in a post‐menopausal woman: A rare differential diagnosis for cystic lesions of the pancreas
Authors: Koçi Sara , Dinçer Hilmi Anıl , Arslan Alican , Kiki Zehranur , Sökmensüer Cenk , Doğrul Ahmet Bülent 
Published: January 2025

AbstractBackgroundAlthough endometriosis is a relatively common condition affecting women, pancreatic endometriosis remains rare, with only a few cases reported in the literature. The primary challenges this condition poses today are its inability to be diagnosed radiologically and the difficulty in distinguishing it from other cystic lesions of the pancreas preoperatively.MethodsThis report presents a case of a 53‐year‐old female patient with 3 months long left upper quadrant pain and no previous medical history. Imaging revealed an enlarging cyst in the tail of the pancreas, with findings suggestive of a mucinous neoplasm.ResultsThe patient underwent a distal pancreatectomy and splenectomy. Histopathological analysis confirmed the presence of endometrial stroma.ConclusionsConsidering the possibility of pancreatic endometriosis may help avoid extensive surgery. However, as the definite diagnosis of endometriosis remains histopathological, surgical resection continues to be the treatment of choice if malignancy is suspected.
Long‐Term Real‐World Survival of Immunotherapy Compared to Chemotherapy for Metastatic Nonsmall Cell Lung Cancer: A Propensity Score‐Matched Analysis
Authors: Kim Kun , Sweeting Michael , Jönsson Linus , Wilking Nils 
Published: January 2025

ABSTRACTBackgroundThe long‐term real‐world effect of immunotherapy (IO) is uncertain in metastatic nonsmall cell lung cancer (mNSCLC). This retrospective observational study aimed to describe treatment patterns following the introduction of IO, estimate real‐world treatment effects of IO compared to standard of care, and evaluate the impact of introduction of IO on a real‐world population, based on a large dataset of over 10 000 patients with several years of follow‐up.MethodsData from routine care of lung cancer patients were extracted from Flatiron Health including those who received either IO or platinum‐based doublet chemotherapy (PBDC) in the first line (1L), or either IO or chemotherapy (CT) in the second line (2L). Real‐world overall survival (rwOS) and real‐world time to next therapy (rwTTNT) were estimated using Cox regression. Flexible parametric models, relaxing proportional hazard assumptions, were used to evaluate long‐term IO effects.ResultsAfter 1:1 nearest neighbor matching among 16 754 1L and 6548 2L patients, the hazard ratio (HR) was 0.942 (95% CI, 0.902–0.984) in 1L and 0.853 (95% CI, 0.795–0.915) in 2L. Adjusting for crossover effects, HR was 0.887 in 1L and 0.775 in 2L. Over the 7‐year follow‐up, the mean rwOS benefit was 3.2 months for 1L and 2.7 months for 2L. IO significantly delayed rwTTNT in both 1L and 2L. The IO effects increased and persisted over time, with uncertainty in the time‐varying HR estimate.ConclusionIO improves survival in patients with mNSCLC, though the effect size is smaller than in trials and long‐term survival estimates are uncertain.
Intratumor Heterogeneity Predicts Prognosis in Lepidic Predominant Lung Adenocarcinoma
Authors: Niedermaier Benedikt , Allgäuer Michael , Muley Thomas , Schneider Marc A. , Eichhorn Martin E. , Winter Hauke , Klotz Laura V. 
Published: January 2025

ABSTRACTObjectiveAmong the different subtypes of invasive lung adenocarcinoma, lepidic predominant adenocarcinoma (LPA) has been recognized as the lowest‐risk subtype with good prognosis. The aim of this study is to provide insight into the heterogeneity within LPA tumors and to better understand the influence of other sub‐histologies on survival outcome.MethodsOverall, 75 consecutive patients with LPA in pathologic stage I (TNM 8th edition) who underwent resection between 2010 and 2022 were included into this retrospective, single center analysis. The proportions of different growth patterns were reported in 5% increments according to the WHO classification.ResultsAll tumors exhibited a predominantly lepidic growth pattern (median proportion 70%, IQR 60%–85%). The invasive component included acinar (n = 66, 88%), papillary (n = 41, 55%), micropapillary (n = 14, 19%), and solid growth patterns (n = 4, 5%), with most tumors exhibiting more than one invasive growth pattern. The presence of high‐risk growth, that is, micropapillary and solid, was associated with higher T stage (r = 0.423, p = 0.0002). A classification of patients as lepidic/high‐risk or lepidic/low‐risk based on the presence of micropapillary and solid growth patterns resulted in a significantly worse disease‐free survival (p = 0.0169, 5‐year DFS: lepidic/high‐risk 73% vs. lepidic/low‐risk: 95%) for the lepidic/high‐risk group, while the groups did not differ in age, gender, smoking status, or extent of resection.ConclusionPatients with stage I LPA exhibit considerable intratumor heterogeneity regarding growth patterns, which can be used for prognostic stratification. The occurrence of micropapillary and solid growth patterns in LPA is associated with poorer disease‐free survival.
Using causal diagrams and superpopulation models to correct geographic biases in biodiversity monitoring data
Authors: Boyd Robin J. , Botham Marc , Dennis Emily , Fox Richard , Harrower Collin , Middlebrook Ian , Roy David B. , Pescott Oliver L. 
Published: January 2025

Abstract

Biodiversity monitoring schemes periodically measure species' abundances and distributions at a sample of sites to understand how they have changed over time. Often, the aim is to infer change in an average sense across some wider landscape. Inference to the wider landscape is simple if the species' abundances and distributions are similar at sampled to non‐sampled locations. Otherwise, the data are geographically biased, and some form of correction is desirable.

We combine causal diagrams with ‘superpopulation models’ to correct time‐varying geographic biases in biodiversity monitoring data. For a given time‐period, expert‐derived causal diagrams are used to deduce the set of variables that explain the geographic bias, and superpopulation models adjust for these variables to produce a corrected estimate of a landscape‐wide mean of for example abundance or occupancy. Estimating a time trend in the variable of interest is achieved by fitting models for multiple time‐periods and, if the drivers of bias are suspected to change over time, by constructing per period causal diagrams. We test the approach using simulated data then apply it to real data from the UK Butterfly Monitoring Scheme (UKBMS).

If the variables that explain the geographic bias are known and measured without error, our method is unbiased. Introducing measurement error reduces the method's efficacy, but it is still an improvement on using the sample mean. When applied to data from the UKBMS, the approach gives different results to the scheme's current method, which assumes no geographic bias.

Where the goal is to estimate change in some variable of interest at the landscape level (e.g. biodiversity indicators), models that do not adjust for geographic bias implicitly assume it does not exist. Our approach makes the weaker assumption that there is no geographic bias conditional on the adjustment variables, so it should yield more accurate estimates of time trends in many circumstances. The method does require assumptions about the drivers of bias, but these are codified explicitly in the causal diagrams. Operationalising our approach should be less costly than full probability sampling, which would be needed to satisfy the assumptions of conventional approaches.
Farming the North: Cycles of Extraction and Dispossession
Authors: Rotz Sarah , Rück Daniel , LeBlanc Joseph 
Published: January 2025

AbstractThis paper examines recent initiatives to expand farming in Northern Ontario, Canada, situating these within the historical context of settler colonial agriculture. We ask: how do contemporary efforts in agricultural expansion differ from, or replicate, earlier forms of land acquisition? Focusing on land assembly, we explore how land consolidation, privatisation, and conversion meet agricultural and economic objectives under contemporary colonial capitalism. We consider whether agricultural expansion reinforces narratives that valorise settler agriculture and/or perpetuates patterns of dispossession. Through privatisation and competitive marketisation of “underutilised” lands, agricultural expansion may reconfigure land ownership in ways that serve capital interests and, primarily, settler agricultural entities. This case highlights the role of agricultural development and the interdependence of corporate and state actors in extending financialised land economies, potentially undermining Indigenous food sovereignty, jurisdiction, and autonomy.
Understanding the Importance of the Small Artery Media–Lumen Ratio: Past and Present
Authors: Aalkjaer Christian 
Published: January 2025

ABSTRACTThe media–lumen diameter ratio of small arteries is increased in hypertension, diabetes and obesity. It is likely that both shear stress on the endothelial cells, transmural pressure and smooth muscle cell tone are important for the altered vascular structure. However, the precise interaction and importance of these factors are incompletely understood. At the molecular level transglutaminases, metalloproteinases, integrins, NO and several other factors have been suggested to be important, but our understanding of how the many factors together control vascular structure is surprisingly limited. The media–lumen diameter ratio of the small arteries has prognostic value, which is independent of the classical risk factors for cardiovascular disease. Importantly this is also the case in patients treated pharmacologically for high blood pressure. It is therefore relevant to consider small artery structure as a potential target in relation to prevention of cardiovascular disease.
Reanalysis of Exome Sequencing Data in the Indian Undiagnosed Diseases Program: Improving Diagnostic Yield and Ending Diagnostic Odyssey
Authors: Garg Neha , Lakshmi Pragna , Singh Suzena M. , Kulshreshta Samarth , Ranganath Prajnya , Moirangthem Amita , Dalal Ashwin , Gahlot Aakanksha , Puri Ratna Dua 
Published: January 2025

ABSTRACTIn 2021, the Indian Undiagnosed Diseases Program was initiated for patients without a definite diagnosis despite extensive evaluation in four participating sites. Between February 2021 and March 2023, a total of 88 patients were recruited and underwent deep phenotyping. A uniform methodology for data re‐analysis was implemented as the first step prior to conducting additional genomic testing. The largest cohort was of 38 patients with neurodevelopmental disorders (NDD). A genetic diagnosis was achieved in 24 of the 88 patients (27.2%), including 7 cases within the NDD cohort. Factors contributing to the increased diagnostic yield included: (a) identification of a novel disease association in DAAM2 gene, and (b) limitations of the standard analysis pipeline, particularly for synonymous variants in SELENOI and KIAA0753 genes, non‐frameshift variant in GLRX5 gene, low‐coverage variant in GJC2 gene, large deletions in PCNT and PHKG2 genes, and intronic variants in VPS33B and FBN1. Improved phenotyping led to a diagnosis in three cases, while genomic variants missed in the previous bioinformatics analysis were identified in 12 cases. The study also contributed to the development of enhanced bioinformatics scripts for variant prioritization and more refined literature search for novel disease associations. It highlights the importance of incorporating data reanalysis into clinical workflows before pursuing advanced diagnostic tests, particularly in resource‐limited settings where healthcare expenses are often borne out of pocket.
Comparison of Different Machine Learning Methodologies for Predicting the Non‐Specific Treatment Response in Placebo Controlled Major Depressive Disorder Clinical Trials
Authors: Gomeni Roberto , Bressolle‐Gomeni Françoise 
Published: January 2025

ABSTRACTPlacebo effect represents a serious confounder for the assessment of treatment effect to the extent that it has become increasingly difficult to develop antidepressant medications appropriate for outperforming placebo. Treatment effect in randomized, placebo‐controlled trials, is usually estimated by the mean baseline adjusted difference of treatment response in active and placebo arms and is function of treatment‐specific and non‐specific effects. The non‐specific treatment effect varies subject by subject conditional to the individual propensity to respond to placebo. This effect is not estimable at an individual level using the conventional parallel‐group study design, since each subject enrolled in the trial is assigned to receive either active treatment or placebo, but not both. The objective of this study was to conduct a comparative analysis of the machine learning methodologies to estimate the individual probability of a non‐specific treatment effect. The estimated probability is expected to support novel methodological approaches for better controlling effect of excessively high placebo response. At this purpose, six machine learning methodologies (gradient boosting machine, lasso regression, logistic regression, support vector machines, k‐nearest neighbors, and random forests) were compared to the multilayer perceptrons artificial neural network (ANN) methodology for predicting the probability of individual non‐specific treatment response. ANN achieved the highest overall accuracy among all methods tested. A fivefold cross‐validation was used to assess performances and risks of overfitting of the ANN model. The analysis conducted without subjects with non‐specific effect indicated a significant increase of signal detection with significant increase in effect size.
From Lab to Clinic: Effect of Academia–Industry Collaboration Characteristics on Oncology Phase 1 Trial Entry
Authors: Yang Wonseok , Lee Sang‐Won 
Published: January 2025

ABSTRACTThis study investigated the success rate of Phase 1 clinical trial entry and the factors influencing it in oncology projects involving academia–industry collaboration during the discovery and preclinical stages. A total of 344 oncology projects in the discovery stage and 360 in the preclinical stage, initiated through collaborations with universities or hospitals between 2015 and 2019, were analyzed. The Phase 1 clinical trial entry success rates for oncology collaborative projects were 9.9% from the discovery stage and 24.2% from the preclinical stage. For discovery stage contracts, strong statistical significance was observed for contract type (co‐development OR 16.45, p = 0.008; licensing OR 42.43, p = 0.000) and technology (cell or gene therapy OR 3.82, p = 0.008). In contrast, for preclinical stage contracts, significant changes were noted for cancer type (blood cancer OR 2.24, p = 0.004), while the year of contract signing showed a relatively weak statistical significance (OR 1.24, p = 0.021). No significant changes were observed concerning partner firm size and the partnership territory. This study sheds light on how the characteristics of partnerships influence the success rates of early‐phase research, providing valuable insights for future strategic planning in oncology drug development.
Risk of insulin initiation with sodium‐glucose cotransporter‐2 inhibitors versus dipeptidyl peptidase‐4 inhibitors in patients with type 2 diabetes mellitus: A real‐world claims database study in Japan
Authors: Suzuki Ryo , Shoji Shingo , Yoshinaga Yoko , Kosakai Yoshinori , Shintani‐Tachi Mami 
Published: January 2025

AbstractAimsInsulin therapy is a cornerstone in type 2 diabetes mellitus (T2DM) management, but its use is associated with several barriers, including hypoglycaemia, fear of injections and high costs. We compared the risk of insulin initiation and other treatment intensification between patients with T2DM newly treated with a sodium‐glucose cotransporter‐2 inhibitor (SGLT2i) versus those newly treated with a dipeptidyl peptidase‐4 inhibitor (DPP4i).Materials and MethodsThis Japanese retrospective cohort study was conducted between 1 January 2015 and 31 March 2023 using the JMDC Claims Database. Patients with T2DM newly treated with an SGLT2i or a DPP4i were matched 1:1 using propensity score (n = 18 488 each). Incidence rates (IR) of insulin initiation, other antidiabetic drugs (OAD) and antihypertensive drugs added onto baseline treatment were calculated for each treatment group. Hazard ratios (HR) and 95% confidence intervals (CI) were calculated using a Cox proportional hazards model.ResultsThe IR of insulin initiation was 0.95 and 2.12 per 1000 person‐years in the SGLT2i and DPP4i groups, respectively, with significantly lower risk in the SGLT2i group than in the DPP4i group (HR 0.46, 95% CI: 0.28–0.74, p = 0.001). The risks of OAD (HR 0.66, 95% CI: 0.64–0.69, p < 0.001) and antihypertensive drugs (HR 0.90, 95% CI: 0.85–0.95, p < 0.001) added onto baseline treatment were lower in the SGLT2i group than in the DPP4i group.ConclusionsThe risk of insulin initiation was lower in patients with T2DM newly treated with an SGLT2i than in those newly treated with a DPP4i. SGLT2i may reduce or delay the need for insulin therapy.