bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fasting glucose levels at diagnosis and delivery are associated with postpartum glucose abnormalities in GDM women
Authors: Gu Ying , Chen Yu , Hu Lingli , Chen Sha , Wang Lin , Chen Mengting , Gu Yanfang , Chen Qi 
Published: January 2025

Abstract
Women with a history of gestational diabetes mellitus (GDM) significantly increase the risk of developing type 2 diabetes later in life. Although the increased glucose levels typically return to normal range after delivery for most GDM women, a significant proportion of GDM women develop impaired glucose tolerance or overt diabetes after delivery. Several factors associated with postpartum glucose abnormalities have been identified, yet the link between fasting glucose levels at diagnosis of GDM and postpartum glucose abnormalities remains unclear. In this retrospective study with 866 GDM women, we found that 12.5% presented with abnormal postpartum fasting glucose levels (prediabetes). Among those with postpartum fasting glucose abnormalities (n = 109), 63 (57%) women had abnormal fasting glucose levels at diagnosis, indicating an odds ratio of 1.662 (95% CI: 1.12, 2.479, p < 0.001) for these GDM women developing postpartum fasting glucose abnormalities, compared to those GDM women with normal postpartum fasting glucose levels. Additionally, of GDM women with abnormal postpartum glucose levels (n = 109),70 (64%) presented with abnormal fasting glucose levels one day before delivery. The odds ratio for these GDM women presenting with abnormal postpartum fasting glucose levels was 3.751 (95% CI: 2.462, 5.664, p < 0.001) compared to those GDM women with normal postpartum fasting glucose levels. Furthermore, GDM women with additional insulin treatment or delivered an LGA infant significantly increased the risk of developing postpartum fasting glucose abnormalities. Our findings suggest that abnormal fasting glucose levels at diagnosis or shortly before delivery could be a predictive indicator for postpartum glucose abnormalities in GDM women.
Validation of mortality risk scores after esophagectomy
Authors: Schiefer Sabine , Crnovrsanin Nerma , Rompen Ingmar F. , Jorek Nicolas , Al-Saeedi Mohammed , Schmidt Thomas , Nienhüser Henrik , Sisic Leila 
Published: January 2025

Abstract

Purpose
Oncological esophagectomy is the mainstay in esophageal cancer treatment, but perioperative mortality remains a significant concern. Various scoring systems exist to identify patients at high risk for postoperative complications and death. In the following, we aim to evaluate and compare these different scoring systems.

Methods
We analyzed data from 714 patients who underwent esophagectomy between 2002 and 2021. Each patient’s risk was calculated using three models: the International Esodata Study Group (IESG) 90-day mortality risk prediction, the Steyerberg 30-day mortality score, and the Fuchs et al. preoperative in-hospital mortality score (Fuchs score). The diagnostic performance of these models was assessed using the area under the receiver operating characteristic (ROC) curves.

Results
Of the 714 patients, the majority (87.67%) underwent abdomino-thoracic esophagectomy with intrathoracic anastomosis. The IESG score classified 52.1% as very low, 26.6% low, 17.5% middle, 2.8% high, and 1% as very high risk, while the Fuchs score identified 94.5% as low-risk and 5.5% as high-risk patients. Mortality rates were 6.9% at 90 days, 3.4% at 30 days, and 6.7% in-hospital. The area under the ROC curve was 0.634 (95%CI: 0.557–0.712) for the IESG model, 0.637 (95%CI: 0.526–0.747) for the Steyerberg score, and 0.686 (95%CI: 0.611–0.760) for the Fuchs score.

Conclusions
Existing risk score systems provide a possibility for preoperative risk stratification, particularly for identifying high-risk patients. However, due to their limited predictive ability, improvements are needed to apply these strategies effectively in clinical practice.
A framework for nurturing champions of digital innovation
Authors: Horstmann Svea , Drechsler Katharina , Chandra Kruse Leona 
Published: January 2025

Abstract
Information Systems (IS) champions enthusiastically promote a digital innovation project throughout its development by obtaining the necessary resources. These individuals shape the innovativeness of an organization, as they initiate digital innovation projects and lead them toward successful completion. We still know little about how these champions can be identified and nurtured in organizations. We follow the Design Science Research approach in developing a framework for nurturing IS champions that can guide human resource practitioners. Our framework offers a strategic view of the champion journey and prescribes recommendations for action. The design decisions were derived from literature on digital innovation and innovation champions, and the framework was subsequently refined and evaluated meticulously. The design underwent two stages based on expert interviews from the IT industry (formative evaluation) and was subsequently evaluated by experts in digital innovation project management and human resource development in the IT industry (summative evaluation). The results demonstrate the feasibility of the framework and offer further insights into the problem and solution space of nurturing IS champions.
Prediction and decoding of metaverse coin dynamics: a granular quest using MODWT-Facebook’s prophet-TBATS and XAI methodology
Authors: Ghosh Indranil , Megaravalli Amith Vikram , Abedin Mohammad Zoynul , Topuz Kazim 
Published: January 2025

Abstract
The growing media buzz and industry focus on the emergence and rapid development of Metaverse technology have paved the way for the escalation of multifaceted research. Specific Metaverse coins have come into existence, but they have barely seen any traction among practitioners despite their tremendous potential. The current work endeavors to deeply analyze the temporal characteristics of 6 Metaverse coins through the lens of predictive analytics and explain the forecasting process. The dearth of research imposes serious challenges in building the forecasting model. We resort to a granular prediction setup incorporating the Maximal Overlap Discrete Wavelet Transformation (MODWT) technique to disentangle the original series into subseries. Facebook's Prophet and TBATS algorithms are utilized to individually draw predictions on granular components. Aggregating components-wise forecasted figures achieve the final forecast. Facebook's Prophet is deployed in a multivariate setting, applying a set of explanatory features covering macroeconomic, technical, and social media indicators. Rigorous performance checks justify the efficiency of the integrated forecasting framework. Additionally, to interpret the black box typed prediction framework, two explainable artificial intelligence (XAI) frameworks, SHAP and LIME, are used to gauge the nature of the influence of the predictor variables, which serve several practical insights.
Interventions to Teacher Well-Being and Burnout A Scoping Review
Authors: Avola Pauliina , Soini-Ikonen Tiina , Jyrkiäinen Anne , Pentikäinen Viivi 
Published: January 2025

Abstract
Teacher burnout, stress, and turnover are increasing globally, underscoring the need to explore ways to reduce burnout and support teacher well-being. This scoping review identifies the contents, characteristics, and results of interventions to increase teacher well-being and reduce burnout. The search was conducted using two databases (Education Research Complete and ERIC). Out of 958 studies, 46 addressed interventions to support teacher well-being or reduce teacher burnout. The data covered 7369 participants in 15 countries. Of the 46 studies, 14 used mixed methods, four qualitative approaches, and 28 used quantitative approaches. The content of the interventions primarily focused on improving individual well-being, with some interventions incorporating communal activities. The qualitative content analysis revealed a broad spectrum of intervention activities, including physical activity, mindfulness and meditation, professional development, therapy-based techniques, gratitude practices, and a mix of multiple activities. The PERMA-H model of positive psychology is applied to unify the heterogeneous field of teacher well-being intervention research. The PERMA-H model's contents were broadly consistent with the intervention's contents, emphasising engagement (E), positive emotions (P), relationships (R), and health (H). The gratitude interventions, therapy-based interventions, physical activity interventions, and most mindfulness and meditation interventions, professional development and mixed activities interventions positively contributed to teacher well-being. Overall, the review highlights the diverse methods and theoretical frameworks employed to address teacher well-being, which the PERMA-H model can unify.
Tetrahedron instantons on orbifolds
Authors: Szabo Richard J. , Tirelli Michelangelo 
Published: January 2025

Abstract
Given a homomorphism

$$\tau $$

τ

from a suitable finite group

$${\mathsf {\Gamma }}$$

Γ

to

$$\textsf{SU}(4)$$

SU
(
4
)

with image

$${\mathsf {\Gamma }}^\tau $$

Γ

τ

, we construct a cohomological gauge theory on a non-commutative resolution of the quotient singularity

$$\mathbbm {C}^4/{\mathsf {\Gamma }}^\tau $$

C
4

/

Γ

τ

whose BRST fixed points are

$${\mathsf {\Gamma }}$$

Γ

-invariant tetrahedron instantons on a generally non-effective orbifold. The partition function computes the expectation values of complex codimension one defect operators in rank r cohomological Donaldson–Thomas theory on a flat gerbe over the quotient stack

$$[\mathbbm {C}^4/\,{\mathsf {\Gamma }}^\tau ]$$

[

C
4

/

Γ

τ

]

. We describe the generalized ADHM parametrization of the tetrahedron instanton moduli space and evaluate the orbifold partition functions through virtual torus localization. If

$${\mathsf {\Gamma }}$$

Γ

is an abelian group the partition function is expressed as a combinatorial series over arrays of

$${\mathsf {\Gamma }}$$

Γ

-coloured plane partitions, while if

$${\mathsf {\Gamma }}$$

Γ

is non-abelian the partition function localizes onto a sum over torus-invariant connected components of the moduli space labelled by lower-dimensional partitions. When

$${\mathsf {\Gamma }}=\mathbbm {Z}_n$$

Γ
=

Z
n

is a finite abelian subgroup of

$$\textsf{SL}(2,\mathbbm {C})$$

SL
(
2
,
C
)

, we exhibit the reduction of Donaldson–Thomas theory on the toric Calabi–Yau four-orbifold

$$\mathbbm {C}^2/\,{\mathsf {\Gamma }}\times \mathbbm {C}^2$$

C
2

/

Γ
×

C
2

to the cohomological field theory of tetrahedron instantons, from which we express the partition function as a closed infinite product formula. We also use the crepant resolution correspondence to derive a closed formula for the partition function on any polyhedral singularity.
Efficacy and Safety of Boswellia serrata and Apium graveolens L. Extract Against Knee Osteoarthritis and Cartilage Degeneration: A Randomized, Double-blind, Multicenter, Placebo-Controlled Clinical Trial
Authors: Vaidya Narendra , Agarwal Ramshyam , Dipankar D. G. , Patkar Hrishikesh , Ganu Gayatri , Nagore Dheeraj , Godse Chhaya , Mehta Anirudh , Mehta Dilip , Nair Sujit 
Published: January 2025

Abstract

Background
Osteoarthritis is the prevailing form of inflammatory condition in joints of adults and the aging population, leading to long-term disability and chronic pain. Current therapeutic options have variable therapeutic efficacy and/or several side effects.

Methods
A randomized, placebo-controlled, double-blind clinical trial was conducted in 62 participants using a nutraceutical [standardized Boswellia serrata Roxb. gum resin (300 mg) and Apium graveolens L. seed extract (250 mg)], to determine its safety and efficacy for supporting cartilage health and reduction in knee osteoarthritis symptoms. All participants were assessed for physical function and pain with the help of WOMAC, VAS, Physicians' Global Assessment for the six-minute walk test/pain. Knee X-ray, KOOS questionnaire score, and FACIT-F score were assessed. Additionally, inflammatory, cartilage degeneration and regeneration biomarkers in serum and urine were evaluated at baseline and after 90 days of treatment.

Results
Oral administration of the nutraceutical resulted in prolonged symptomatic relief with reduced pain, stiffness, and swelling. Inflammatory (serum IL-7, IL-1, IL-6, hs-CRP, TNF-α, ESR) and cartilage degeneration biomarkers (serum CTX-II, COMP, MMP-3 and urinary CTX-II) were decreased in the nutraceutical group compared to baseline and placebo. Furthermore, serum N-propeptide of collagen IIA (PIIANP) and procollagen-type-C propeptide (PIICP) levels were increased in the nutraceutical group, suggesting collagen synthesis contributing to cartilage regeneration. At given doses for 90 days, there were no adverse effects based on the clinical examination, biochemical, hematological, and ECG analysis.

Conclusions
Taken together, the combination of Boswellia and celery could be a safe and promising herbal nutraceutical option for managing osteoarthritis and cartilage health effectively.
The negative relationship between brain-age gap and psychological resilience defines the age-related neurocognitive status in older people
Authors: Gu Yue , Wong Nichol M. L. , Chan Chetwyn C. H. , Wu Jingsong , Lee Tatia M. C. 
Published: January 2025

Abstract
Biological brain age is a brain-predicted age using machine learning to indicate brain health and its associated conditions. The presence of an older predicted brain age relative to the actual chronological age is indicative of accelerated aging processes. Consequently, the disparity between the brain’s chronological age and its predicted age (brain-age gap) and the factors influencing this disparity provide critical insights into cerebral health dynamics during aging. In this study, we employed a Lasso regression model and analyzed multimodal imaging data from 124 participants aged 53 to 76 to formulate and predict brain age. Additionally, we conducted partial correlation analyses to explore the complex relationship between the brain-age gap and network metrics, cognitive assessments, and emotional evaluations, while controlling for chronological age, gender, and education. Our findings highlight psychological resilience as a significant mitigating factor against premature brain aging. It is established that psychological resilience significantly influences the modulation of the brain-age gap. Moreover, psychological resilience and the brain-age gap exhibit a high accuracy (above 0.72) in segregating Montreal Cognitive Assessment score–based cohorts. This observation underscores significant insight into the potential of utilizing the brain-age gap as a diagnostic tool for the early detection of accelerated aging. It advocates for the timely application of interventions, including the development of programs aimed at bolstering psychological resilience.
Finding relevant stakeholders and related social topics for the implementation of Social Life Cycle Assessment in the multistorey timber construction sector
Authors: Bruno Morena , Zanchi Laura , Patrizi Nicoletta , Neri Elena , Rusen Madalina , Elisei Pietro , Gioia Carmela , Pulselli Federico Maria , Bastianoni Simone 
Published: January 2025

Abstract

Purpose
This study aims to identify the most relevant stakeholder groups and related social topics for the multistorey timber construction sector and provide first insights on the potential social effects—negative (risks) and positive (benefits)—produced by the prospective increase of multistorey timber constructions in Europe considering their whole life cycle.

Methods
The advancement of social materiality assessment was conducted to unveil the most relevant stakeholder groups and related social topics of the building sector by considering what is proposed by the UNEP Guidelines for Social Life Cycle Assessment and Handbook for Product Social Impact Assessment. To verify selected social topics and collect information on their level of relevance, we based our research approach on stakeholder engagement through a dedicated online workshop and interviews.

Results
Seventeen social topics were selected as material for the multistorey timber construction sector according to the literature review and the stakeholder engagement activities. No significant variance in relevance level was observed according to a five-level Likert scale (from 1, not at all relevant, to 5, very relevant), all rating above level 3 (relevant); the ones perceived as very relevant being “Health and safety” (Users), “Safe and healthy living conditions” (Local Community), and “Fair salary” (Workers).

Conclusions
This study highlights how conducting a social materiality assessment and engaging stakeholders play a crucial role in identifying an initial set of critical social topics to focus on for further evaluation of potential impacts and performance. Since there is not yet a standardized approach for the S-LCA application in the construction sector, results from this work represent an initial step towards the prioritization process of social topics. This prioritization process aims to assign priority levels to a list of social topics derived from a review process based on various sources.
18F-FDG PET/CT radiomic analysis and artificial intelligence to predict pathological complete response after neoadjuvant chemotherapy in breast cancer patients
Authors: Urso Luca , Manco Luigi , Cittanti Corrado , Adamantiadis Sara , Szilagyi Klarisa Elena , Scribano Giovanni , Mindicini Noemi , Carnevale Aldo , Bartolomei Mirco , Giganti Melchiore 
Published: January 2025

Abstract

Purpose
Build machine learning (ML) models able to predict pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer (BC) patients based on conventional and radiomic signatures extracted from baseline [18F]FDG PET/CT.

Material and methods
Primary tumor and the most significant lymph node metastasis were manually segmented in baseline [18F]FDG PET/CT of 52 newly diagnosed BC patients. Clinical parameters, NAC and conventional semiquantitative PET parameters were collected. The standard of reference considered was surgical pCR after NAC (ypT0;ypN0). Eight-hundred-fifty-four radiomic features (RFts) were extracted from both PET and CT datasets, according to IBSI; robust RFTs were selected. The cohort was split in training (70%) and validation (30%) sets. Four ML Models (Clinical Model, CT Model, PET Model_T and PET Model_T + N) each one with 3 learners (Random Forest (RF), Neural Network and Stochastic Gradient Descendent) were trained and tested using RFts and clinical signatures. PET Models were built considering robust RFTs extracted from either primary tumor alone (PET Model_T) or also including the reference lymph node (PET Model_T + N).

Results
72 pathological uptakes (52 primary BC and 20 lymph node metastasis) at [18F]FDG PET/CT were segmented. pCR occurred in 44.2% cases. Twelve, 46 and 141 robust RFts were selected from CT Model, PET Model_T and PET Model_T + N, respectively. PET Models showed better performance than CT and Clinical Models. The best performances were obtained by the RF algorithm of the PET Model_T + N (AUC = 0.83;CA = 0.74;TP = 78%;TN = 72%).

Conclusion
ML models trained on PET/CT radiomic features extracted from primary BC and lymph node metastasis could concur in the prediction of pCR after NAC and improve BC management.
On invariants of free metabelian bicommutative algebras
Authors: Öğüşlü Nazar Şahin , Fındık Şehmus 
Published: January 2025

Abstract
An algebra is bicommutative if it satisfies left and right symmetries; i.e.,

$$a(bc)=b(ac)$$

a
(
b
c
)
=
b
(
a
c
)

and

$$(ab)c=(ac)b$$

(
a
b
)
c
=
(
a
c
)
b

. Let K be a field of characteristic zero, and

$$M_n$$

M
n

,

$$n\ge 3$$

n
≥
3

, be the free metabelian bicommutative algebra generated by a set

$$X_n=\{x_1,\ldots ,x_n\}$$

X
n

=

{

x
1

,
…
,

x
n

}

of variables, in which the identity

$$(xy)(zt)=0$$

(
x
y
)
(
z
t
)
=
0

is being satisfied. We define the action of the alternating group

$$A_n$$

A
n

on

$$M_n$$

M
n

as follows.

$$\pi f(x_1,\ldots ,x_n)=f(x_{\pi (1)},\ldots ,x_{\pi (n)})$$

π
f

(

x
1

,
…
,

x
n

)

=
f

(

x

π
(
1
)

,
…
,

x

π
(
n
)

)

, where

$$\pi \in A_n$$

π
∈

A
n

and

$$f\in M_n$$

f
∈

M
n

. The set

$$M_n^{A_n}=\{f\in M_n\mid \pi f=f\ , \forall \pi \in A_n\}$$

M
n

A
n

=

{
f
∈

M
n

∣
π
f
=
f

,
∀
π
∈

A
n

}

is a subalgebra of

$$M_n$$

M
n

called the algebra of invariants of the group

$$A_n$$

A
n

. In the first part of this study, we describe the elements of the algebra

$$M_n^{A_n}$$

M
n

A
n

. We also give the description of the algebras

$$M_2^{C_2}$$

M
2

C
2

,

$$M_2^{C_3}$$

M
2

C
3

,

$$M_2^{C_2\times C_2}$$

M
2

C
2

×

C
2

, and

$$M_2^{C_4}$$

M
2

C
4

of invariants of the groups

$$C_2$$

C
2

,

$$C_3$$

C
3

,

$$C_2\times C_2$$

C
2

×

C
2

, and

$$C_4$$

C
4

of order up to 4, respectively, as a subgroups of the general linear group

$$\text {GL}_2(K)$$

GL
2

(
K
)

.
Individuals’ Desire for Social Needs Sharing Among Healthcare Providers: Findings from the 2022 Health Information National Trends Survey
Authors: Olvera Ramona G. , Swoboda Christine M. , Joseph Joshua J. , Bose-Brill Seuli , McAlearney Ann Scheck , Walker Daniel M. 
Published: January 2025

Abstract

Background
Increasingly, health systems are collecting and using social needs data, yet there is limited information about individuals’ preferences for how social needs information is shared among providers for treatment purposes.

Objective
To explore the connection between experiencing social needs and concerns about healthcare providers sharing social needs information.

Design and Participants
A nationally representative, cross-sectional study of 6252 US community-dwelling adults (≥ 18 years of age) who responded to the Health Information National Trends Survey (HINTS 6) (response rate 28.1%) from March to November 2022.

Main Measures
Core measures include experiencing social needs in the past year (food, transportation, housing issues), and comfort with providers sharing social needs information with each other for treatment purposes. Other key independent variables included patient-centered communication, discrimination, trust, and quality of care.

Key Results
Odds of reporting experiencing a social need varied by age, race, education, and income, yet those 75 years or older (compared to ages 18–34) had higher odds of reporting feeling comfortable with providers sharing information about social needs. Those who reported having experienced discrimination in healthcare had lower odds of reporting comfort with providers sharing information about food (adjusted odds ratio [aOR], 0.63; 95% confidence interval [CI], 0.41-0.98) and transportation (aOR, 0.64; 95%CI, 0.44-0.94) needs. Those who trusted the healthcare system had higher odds of being comfortable with providers sharing information about unmet needs for food (aOR, 1.33; 95%CI, 1.07-1.65). Also, those who report better patient-centered communication and quality of care had higher odds of being comfortable with providers sharing information on unmet social needs.

Conclusions
Individuals’ preferences regarding social needs information sharing for treatment purposes, as well as experience of discrimination, trust in healthcare, quality of care, and patient-provider communication, should be considered in health system efforts to capture social needs information.