bluuebunny/crossref_metadata_2025 huggingface dataset:
A systematic review and research recommendations on artificial intelligence for automated cervical cancer detection
Authors: Khare Smith K. , Blanes‐Vidal Victoria , Booth Berit Bargum , Petersen Lone Kjeld , Nadimi Esmaeil S.
Published: July 2024

Early diagnosis of abnormal cervical cells enhances the chance of prompt treatment for cervical cancer (CrC). Artificial intelligence (AI)‐assisted decision support systems for detecting abnormal cervical cells are developed because manual identification needs trained healthcare professionals, and can be difficult, time‐consuming, and error‐prone. The purpose of this study is to present a comprehensive review of AI technologies used for detecting cervical pre‐cancerous lesions and cancer. The review study includes studies where AI was applied to Pap Smear test (cytological test), colposcopy, sociodemographic data and other risk factors, histopathological analyses, magnetic resonance imaging‐, computed tomography‐, and positron emission tomography‐scan‐based imaging modalities. We performed searches on Web of Science, Medline, Scopus, and Inspec. The preferred reporting items for systematic reviews and meta‐analysis guidelines were used to search, screen, and analyze the articles. The primary search resulted in identifying 9745 articles. We followed strict inclusion and exclusion criteria, which include search windows of the last decade, journal articles, and machine/deep learning‐based methods. A total of 58 studies have been included in the review for further analysis after identification, screening, and eligibility evaluation. Our review analysis shows that deep learning models are preferred for imaging techniques, whereas machine learning‐based models are preferred for sociodemographic data. The analysis shows that convolutional neural network‐based features yielded representative characteristics for detecting pre‐cancerous lesions and CrC. The review analysis also highlights the need for generating new and easily accessible diverse datasets to develop versatile models for CrC detection. Our review study shows the need for model explainability and uncertainty quantification to increase the trust of clinicians and stakeholders in the decision‐making of automated CrC detection models. Our review suggests that data privacy concerns and adaptability are crucial for deployment hence, federated learning and meta‐learning should also be explored.

This article is categorized under:

Fundamental Concepts of Data and Knowledge > Explainable AI

Technologies > Machine Learning

Technologies > Classification
Comparative Advantage Is an Old-Fashioned Trick
Authors: Lopes Carlos
Published: July 2024

A convergence of economic imperatives, including the need for raw materials and markets, alongside inter-European power struggles and social factors such as rising unemployment kickstarted Europe’s scramble for Africa. The resulting colonial era has left an indelible impact on Africa’s economic, political, and social dimensions. Much of this legacy is now encoded in the international protocols that govern trade between Africa and the rest of the world. These systems tend to protect the interests of established leaders and have systematically penalised latecomers. This puts Africa at an enduring disadvantage despite its bountiful resources and much-vaunted potential.

In this chapter, we revisit data and anecdotal evidence showing how countries that have ‘made it’ in the global trade arena often counted more on dynamic comparative advantages than on simplified comparative advantage theory interpretations based on their natural resources bounty. We also compare African and Asian countries after the independence movement of the 1960s regarding economic and social indicators, where they are now, and what it will take for Africa to chart a new course to a fairer trade system.
Estimation of Time-Dependent Transmission Rate for COVID-19 SVIRD Model Using Predictor–Corrector Algorithm
Authors: Luo Ruiyan , Herrera-Reyes Alejandra D. , Kim Yena , Rogowski Susan , White Diana , Smirnova Alexandra
Published: July 2024

Stable parameter estimation is an ongoing challenge within biomathematics, especially in epidemiology. Oftentimes epidemiological models are composed of large numbers of equations and parameters. Due to high dimensionality, classic parameter estimation approaches, such as least square fitting, are computationally expensive. Additionally, the presence of observational noise and reporting errors that accompany real-time data can make these parameter estimation problems ill-posed and unstable. The recent COVID-19 pandemic highlighted the need for efficient parameter estimation tools. In this chapter, we develop a modified version of a regularized predictor–corrector algorithm aimed at stable low-cost reconstruction of infectious disease parameters. This method is applied to a new compartmental model describing COVID-19 dynamics, which accounts for vaccination and immunity loss (from vaccinated and recovered populations). Numerical simulations are carried out with synthetic and real data for COVID-19 pandemic. Based on the reconstructed disease transmission rates (and known mitigation measures), observations on historical trends of COVID-19 in the states of Georgia and California are presented. Such observations can be used to provide insights into future COVID policies.
Natural Language Hypotheses in Scientific Papers and How to Tame Them
Authors: Heger Tina , Algergawy Alsayed , Brinner Marc , Jeschke Jonathan M. , König-Ries Birgitta , Mietchen Daniel , Zarrieß Sina
Published: July 2024

Hypotheses are critical components of scientific argumentation. Knowing established hypotheses is often a prerequisite for following and contributing to scientific arguments in a research field. In scientific publications, hypotheses are usually presented for specific empirical settings, whereas the related general claim is assumed to be known. Prerequisites for developing argumentation machines for assisting scientific workflows are to account for domain-specific concepts needed to understand established hypotheses, to clarify the relationships between specific hypotheses and general claims, and to take steps towards formalization. Here, we develop a framework for formalizing hypotheses in the research field of invasion biology. We suggest conceiving hypotheses as consisting of three basic building blocks: a subject, an object, and a hypothesized relationship between them. We show how the subject-object-relation pattern can be applied to well-known hypotheses in invasion biology and demonstrate that the contained concepts are quite diverse, mirroring the complexity of the research field. We suggest a stepwise approach for modeling them to be machine-understandable using semantic web ontologies. We use the SuperPattern Ontology to categorize hypothesized relationships. Further, we recommend treating every hypothesis as part of a hierarchical system with ‘parents’ and ‘children’. There are three ways of moving from a higher to a lower level in the hierarchy: (i) specification, (ii) decomposition, and (iii) operationalization. Specification involves exchanging subjects or objects. Decomposition means zooming in and making explicit assumptions about underlying (causal) relationships. Finally, operationalizing a hypothesis means providing concrete descriptions of what will be empirically tested.
“Do Not Disturb My Circles!” Identifying the Type of Counterfactual at Hand (Short Paper)
Authors: Willig Moritz , Zečević Matej , Kersting Kristian
Published: July 2024

When the phenomena of interest are in need of explanation, we are often in search of the underlying root causes. Causal inference provides tools for identifying these root causes—by performing interventions on suitably chosen variables we can observe down-stream effects in the outcome variable of interest. On the other hand, argumentation as an approach of attributing observed outcomes to specific factors, naturally lends itself as a tool for determining the most plausible explanation. We can further improve the robustness of such explanations by measuring their likelihood within a mutually agreed-upon causal model. For this, typically one of in-principle two distinct types of counterfactual explanations is used: interventional counterfactuals, which treat changes as deliberate interventions to the causal system, and backtracking counterfactuals, which attribute changes exclusively to exogenous factors. Although both frameworks share the common goal of inferring true causal factors, they fundamentally differ in their conception of counterfactuals. Here, we present the first approach that decides when to expect interventional and when to opt for backtracking counterfactuals.
Automatic Analysis of Political Debates and Manifestos: Successes and Challenges
Authors: Ceron Tanise , Barić Ana , Blessing André , Haunss Sebastian , Kuhn Jonas , Lapesa Gabriella , Padó Sebastian , Papay Sean , Zauchner Patricia F.
Published: July 2024

The opinions of political actors (e.g., politicians, parties, organizations) expressed through claims are the core elements of political debates and decision-making. Political actors communicate through different channels: parties publish manifestos for major elections, while individual actors make statements on a day-to-day basis as reflected in the media. These two channels offer different approaches for analysis: Manifestos, on the one hand, are useful to characterize the parties’ positions at a global ideological level over time. In contrast, individual statements can be collected to analyze debates in particular policy domains on a fine-grained level, in terms of individual actors and claims. In this article, we summarize a series of studies we have carried out. We apply NLP-driven (semi-)automatic analyses on these two channels and compare their potentials and challenges. The fine-grained analysis yields rich insights into the communication but comes at the cost of three challenges: (a) a substantial hunger for manual annotation, introducing practical hurdles for analysis both within and across languages; (b) difficulties in claim classification arising from the uneven frequency distribution over the theory-based annotation schemas; (c) the need to map actor mentions onto canonical versions. Manifesto-based analysis avoids these challenges to a substantial extent when a more coarse-grained analysis of party positions is sufficient. We highlight the benefits and challenges of both approaches, and conclude by outlining perspectives for addressing the challenges in future research.
PolArg: Unsupervised Polarity Prediction of Arguments in Real-Time Online Conversations
Authors: Lenz Mirko , Bergmann Ralph
Published: July 2024

The increasing usage of social networks has led to a growing number of discussions on the Internet that are a valuable source of argumentation that occurs in real time. Such conversations are often made up of a large number of participants and are characterized by a fast pace. Platforms like X/Twitter and Hacker News (HN) allow users to respond to other users’ posts, leading to a tree-like structure. Previous work focused on training supervised models on datasets obtained from debate portals like Kialo where authors provide polarity labels (i.e., support/attack) together with their posts. Such classifiers may yield suboptimal predictions for the noisier posts from X or HN, so we propose unsupervised prompting strategies for large language models instead. Our experimental evaluation found this approach to be more effective for X conversations than a model fine-tuned on Kialo debates, but less effective for HN posts (which are more technical and less argumentative). Finally, we provide an open-source application for converting discussions on these platforms into argument graphs.
Integrating Mathematical Data and Resources: Advancements in zbMATH Open for Enhanced Mathematical Research Accessibility and Reproducibility
Authors: Azzouz-Thuderoz Maxence , Deb Madhurima , Petrera Matteo , Schubotz Moritz , Teschke Olaf
Published: July 2024

We report the ongoing efforts of swMATH, an integral part of zbMATH Open, to collect precise referencing software metadata. zbMATH Open is emerging as a unified platform offering a spectrum of mathematical resources, including mathematical software, formulas, reviews, and serial and mathematical item classification. zbMATH Open offers connection to external partners, DLMF and OEIS, via its Links API by indexing approximately 6,330 documents containing 65,069 references to OEIS sequences and 15,858 references to 2,053 DLMF functions. Significantly, the collection of 44,594 software entries from swMATH is entirely accessible through zbMATH Open. Here, we emphasize the accurate referencing of mathematical software in swMATH for maintaining integrity, advancing mathematical research, and enhancing reproducibility. We describe how swMATH is embedded into zbMATH open and elaborate on the relationship of software and other mathematical research data like OEIS and DLMF, ensuring a complete and FAIR resource for the mathematical research community.
Sharp Semiclassical Spectral Asymptotics for Local Magnetic Schrödinger Operators on $${\mathbb {R}}^d$$ Without Full Regularity
Authors: Mikkelsen Søren
Published: July 2024

We consider operators acting in $$L^2({\mathbb {R}}^d)$$

L
2

(

R

d

)

with $$d\ge 3$$

d
≥
3

that locally behave as a magnetic Schrödinger operator. For the magnetic Schrödinger operators, we suppose the magnetic potentials are smooth and the electric potential is five times differentiable and the fifth derivatives are Hölder continuous. Under these assumptions, we establish sharp spectral asymptotics for localised counting functions and Riesz means.
Mutations of noncommutative crepant resolutions in geometric invariant theory
Authors: Hara Wahei , Hirano Yuki
Published: July 2024

Let X be a generic quasi-symmetric representation of a connected reductive group G. The GIT quotient stack $$\mathfrak {X}=[X^\text {ss}(\ell )/G]$$

X
=
[

X
ss

(
ℓ
)

/
G
]

with respect to a generic $$\ell $$
ℓ
is a (stacky) crepant resolution of the affine quotient X/G, and it is derived equivalent to a noncommutative crepant resolution (=NCCR) of X/G. Halpern-Leistner and Sam showed that the derived category $${{\textrm{D}}^{\textrm{b}}}({\text {coh}}\mathfrak {X})$$

D

b

(
coh
X
)

is equivalent to certain subcategories of $${{\textrm{D}}^{\textrm{b}}}({\text {coh}}[X/G])$$

D

b

(
coh

[
X
/
G
]

)

, which are called magic windows. This paper studies equivalences between magic windows that correspond to wall-crossings in a hyperplane arrangement in terms of NCCRs. We show that those equivalences coincide with derived equivalences between NCCRs induced by tilting modules, and that those tilting modules are obtained by certain operations of modules, which is called exchanges of modules. When G is a torus, it turns out that the exchanges are nothing but iterated Iyama–Wemyss mutations. Although we mainly discuss resolutions of affine varieties, our theorems also yield a result for projective Calabi-Yau varieties. Using techniques from the theory of noncommutative matrix factorizations, we show that Iyama–Wemyss mutations induce a group action of the fundamental group $$\pi _1(\mathbb {P}^1\,\backslash \{0,1,\infty \})$$

π
1

(

P

1

\

{
0
,
1
,
∞
}

)

on the derived category of a Calabi-Yau complete intersection in a weighted projective space.
Dreaming of AI: environmental sustainability and the promise of participation
Authors: Zehner Nicolas , Ullrich André
Published: July 2024

There is widespread consensus among policymakers that climate change and digitalisation constitute the most pressing global transformations shaping human life in the 21st century. Seeking to address the challenges arising at this juncture, governments, technologists and scientists alike increasingly herald artificial intelligence (AI) as a vehicle to propel climate change mitigation and adaptation. In this paper, we explore the intersection of digitalisation and climate change by examining the deployment of AI in government-led climate action. Building on participant observations conducted in the context of the “Civic Tech Lab for Green”—a government-funded public interest AI initiative—and eight expert interviews, we investigate how AI shapes the negotiation of environmental sustainability as an issue of public interest. Challenging the prescribed means–end relationship between AI and environmental protection, we argue that the unquestioned investment in AI curtails political imagination and displaces discussion of climate “problems” and possible “solutions” with “technology education”. This line of argumentation is rooted in empirical findings that illuminate three key tensions in current coproduction efforts: “AI talk vs. AI walk”, “civics washing vs. civics involvement” and “public invitation vs. public participation”. Emphasising the importance of re-exploring the innovative state in climate governance, this paper extends academic literature in science and technology studies that examines public participation in climate change adaptation by shedding light on the emergent phenomenon of public interest AI.
Exploring deep fully convolutional neural networks for surface defect detection in complex geometries
Authors: García Peña Daniel , García Pérez Diego , Díaz Blanco Ignacio , Juárez Jorge Marina
Published: July 2024

In this paper, we propose a machine learning approach for detecting superficial defects in metal surfaces using point cloud data. We compare the performance of two popular deep learning architectures, multilayer perceptron networks (MLPs) and fully convolutional networks (FCNs), with varying feature sets. Our results show that FCNs (F1=0.94) outperformed MLPs (F1=0.52) in terms of precision, recall, and F1-score. We found that transfer learning with pre-trained models can improve performance when the amount of available data is limited. Our study highlights the importance of considering the amount and quality of training data in developing machine learning models for defect detection in industrial settings with 3D images.
Metabolic versatility of anaerobic sludge towards platform chemical production from waste glycerol
Authors: Magalhães Carla P. , Alves Joana I. , Duber Anna , Oleskowicz-Popiel Piotr , Stams Alfons J. M. , Cavaleiro Ana J.
Published: July 2024

Waste glycerol is produced in excess by several industries, such as during biodiesel production. In this work, the metabolic versatility of anaerobic sludge was explored towards waste glycerol valorization. By applying different environmental (methanogenic and sulfate-reducing) conditions, three distinct microbial cultures were obtained from the same inoculum (anaerobic granular sludge), with high microbial specialization, within three different phyla (Thermodesulfobacteriota, Euryarchaeota and Pseudomonadota). The cultures are capable of glycerol conversion through different pathways: (i) glycerol conversion to methane by a bacterium closely related to Solidesulfovibrio alcoholivorans (99.8% 16S rRNA gene identity), in syntrophic relationship with Methanofollis liminatans (98.8% identity), (ii) fermentation to propionate by Propionivibrio pelophilus strain asp66 (98.6% identity), with a propionate yield of 0.88 mmol mmol−1 (0.71 mg mg−1) and a propionate purity of 80–97% and (iii) acetate production coupled to sulfate reduction by Desulfolutivibrio sulfoxidireducens (98.3% identity). In conclusion, starting from the same inoculum, we could drive the metabolic and functional potential of the microbiota towards the formation of several valuable products that can be used in industrial applications or as energy carriers.

Key points

Versatility of anaerobic cultures was explored for waste glycerol valorization

Different environmental conditions lead to metabolic specialization

Biocommodities such as propionate, acetate and methane were produced
Building up a model family for inflammations
Authors: Reisch Cordula , Nickel Sandra , Tautenhahn Hans-Michael
Published: July 2024

The paper presents an approach for overcoming modeling problems of typical life science applications with partly unknown mechanisms and lacking quantitative data: A model family of reaction–diffusion equations is built up on a mesoscopic scale and uses classes of feasible functions for reaction and taxis terms. The classes are found by translating biological knowledge into mathematical conditions and the analysis of the models further constrains the classes. Numerical simulations allow comparing single models out of the model family with available qualitative information on the solutions from observations. The method provides insight into a hierarchical order of the mechanisms. The method is applied to the clinics for liver inflammation such as metabolic dysfunction-associated steatohepatitis or viral hepatitis where reasons for the chronification of disease are still unclear and time- and space-dependent data is unavailable.
Higher levels of markers for early atherosclerosis in anti-citrullinated protein antibodies positive individuals at risk for RA, a cross sectional study
Authors: Hinkema Helma J. , Westra Johanna , Arends Suzanne , Brouwer Elisabeth , Mulder Douwe J.
Published: July 2024

Objective

To identify differences in levels of serum biomarkers associated with atherosclerosis between anti-citrullinated protein antibodies (ACPA) positive groups.

Methods

Cross-sectional data were used from the Dutch Lifelines Cohort Study combined with data derived from RA risk and early RA studies conducted at the University Medical Center Groningen (UMCG).

Serum biomarkers of inflammation, endothelial cell activation, tissue remodeling and adipokine, which were previously associated with atherosclerosis, were measured with Luminex in four ACPA positive groups with different characteristics: without joint complaints, with joint complaints, RA risk and early RA groups.

Results

Levels of C-reactive protein (CRP), Interleukin-6 (IL-6), Tumor Necrosis Factor Receptor 1 (TNFR1) and vascular endothelial growth factor (VEGF) were significantly higher in the RA risk and early RA groups compared to the joint complaints and the no joint complaints groups. The difference remained statistically significant after correcting for renal function, smoking and hypertension in multivariate logistic regression analysis, with focus on ACPA positive with joint complaints group versus RA risk group: CRP OR = 2.67, p = 0.033; IL-6 OR = 3.73, p = 0.019; TNFR1 OR = 1.003, p < 0.001; VGEF OR = 8.59, p = 0.019.

Conclusion

Individuals at risk for RA have higher levels of inflammatory markers and VEGF, which suggests that they might also have a risk of higher cardiovascular disease (CVD); however, this does not apply to individuals with ACPA positivity with self-reported joint complaints or without joint complaints only. Therefore, it is important that individuals with RA risk are referred to a rheumatologist to rule in or out arthritis/development of RA and discuss CVD risk.
Evaluation of ophthalmic vascular and neuroretinal alterations in fibromyalgia syndrome: a cross-sectional comparative study
Authors: Öztürk Gülşah Yaşa , Emekli Duygu Topaktaş , Sahutoglu Eda , Kocyigit Burhan Fatih
Published: July 2024

Introduction

Fibromyalgia syndrome (FMS) is a prevalent rheumatic disorder, and its pathogenesis includes genetic, neuroendocrine, and autonomic abnormalities, which may impact ocular structures. The aim was to conduct a comparative analysis of the ophthalmic vasculature and the retinal nerve fiber layer (RNFL) thickness between FMS and control groups using optical coherence tomography (OCT) and OCT angiography (OCTA).

Methods

This cross-sectional comparative study included 43 FMS patients and 40 healthy controls recruited from a tertiary education and research hospital between January 2024 and May 2024. All patients satisfied the 2016 American College of Rheumatology criteria for FMS and consented. OCT and OCTA were used to assess the RNFL thickness and the retinal microvasculature structure. The Fibromyalgia Impact Questionnaire (FIQ) was performed to evaluate disease severity.

Results

The study found significantly higher total retinal parafoveal thickness and foveal density in FMS patients (p = 0.017 and p = 0.044, respectively). Nevertheless, there were no significant differences among the groups concerning total retinal foveal thickness, foveal avascular zone characteristics, superficial and deep capillary plexus densities, choriocapillaris flow area, and outer retinal flow area values (p > 0.05). The RNFL thickness in all quadrants did not reveal significant differences between the groups (p > 0.05). Furthermore, there was no significant correlation between FIQ scores and OCTA parameters or RNFL thickness values (p > 0.05).

Conclusion

The study revealed slight differences in retinal parafoveal thickness and foveal density in FMS patients, but no substantial vascular or neurodegenerative alterations were observed compared to healthy controls. These data indicate that FMS may not substantially affect ocular structures, contrary to earlier hypotheses.
The pros and cons of lung cancer screening
Authors: Ledda Roberta Eufrasia , Funk Georg-Christian , Sverzellati Nicola
Published: July 2024

Several trials have shown that low-dose computed tomography-based lung cancer screening (LCS) allows a substantial reduction in lung cancer-related mortality, carrying the potential for other clinical benefits. There are, however, some uncertainties to be clarified and several aspects to be implemented to optimize advantages and minimize the potential harms of LCS.

This review summarizes current evidence on LCS, discussing some of the well-established and potential benefits, including lung cancer (LC)-related mortality reduction and opportunity for smoking cessation interventions, as well as the disadvantages of LCS, such as overdiagnosis and overtreatment.

Clinical relevance statement

Different perspectives are provided on LCS based on the updated literature.

Key Points

Lung cancer is a leading cancer-related cause of death and screening should reduce associated mortality.

This review summarizes current evidence related to LCS.

Several aspects need to be implemented to optimize benefits and minimize potential drawbacks of LCS.
Evaluating the quality of radiomics-based studies for endometrial cancer using RQS and METRICS tools
Authors: Russo Luca , Bottazzi Silvia , Kocak Burak , Zormpas-Petridis Konstantinos , Gui Benedetta , Stanzione Arnaldo , Imbriaco Massimo , Sala Evis , Cuocolo Renato , Ponsiglione Andrea
Published: July 2024

Objective

To assess the methodological quality of radiomics-based models in endometrial cancer using the radiomics quality score (RQS) and METhodological radiomICs score (METRICS).

Methods

We systematically reviewed studies published by October 30th, 2023. Inclusion criteria were original radiomics studies on endometrial cancer using CT, MRI, PET, or ultrasound. Articles underwent a quality assessment by novice and expert radiologists using RQS and METRICS. The inter-rater reliability for RQS and METRICS among radiologists with varying expertise was determined. Subgroup analyses were performed to assess whether scores varied according to study topic, imaging technique, publication year, and journal quartile.

Results

Sixty-eight studies were analysed, with a median RQS of 11 (IQR, 9–14) and METRICS score of 67.6% (IQR, 58.8–76.0); two different articles reached maximum RQS of 19 and METRICS of 90.7%, respectively. Most studies utilised MRI (82.3%) and machine learning methods (88.2%). Characterisation and recurrence risk stratification were the most explored outcomes, featured in 35.3% and 19.1% of articles, respectively. High inter-rater reliability was observed for both RQS (ICC: 0.897; 95% CI: 0.821, 0.946) and METRICS (ICC: 0.959; 95% CI: 0.928, 0.979). Methodological limitations such as lack of external validation suggest areas for improvement. At subgroup analyses, no statistically significant difference was noted.

Conclusions

Whilst using RQS, the quality of endometrial cancer radiomics research was apparently unsatisfactory, METRICS depicts a good overall quality. Our study highlights the need for strict compliance with quality metrics. Adhering to these quality measures can increase the consistency of radiomics towards clinical application in the pre-operative management of endometrial cancer.

Clinical relevance statement

Both the RQS and METRICS can function as instrumental tools for identifying different methodological deficiencies in endometrial cancer radiomics research. However, METRICS also reflected a focus on the practical applicability and clarity of documentation.

Key Points

The topic of radiomics currently lacks standardisation, limiting clinical implementation.

METRICS scores were generally higher than the RQS, reflecting differences in the development process and methodological content.

A positive trend in METRICS score may suggest growing attention to methodological aspects in radiomics research.
Turing Bifurcation in the Swift–Hohenberg Equation on Deterministic and Random Graphs
Authors: Medvedev Georgi S. , Pelinovsky Dmitry E.
Published: July 2024

The Swift–Hohenberg equation (SHE) is a partial differential equation that explains how patterns emerge from a spatially homogeneous state. It has been widely used in the theory of pattern formation. Following a recent study by Bramburger and Holzer (SIAM J Math Anal 55(3):2150–2185, 2023), we consider discrete SHE on deterministic and random graphs. The two families of the discrete models share the same continuum limit in the form of a nonlocal SHE on a circle. The analysis of the continuous system, parallel to the analysis of the classical SHE, shows bifurcations of spatially periodic solutions at critical values of the control parameters. However, the proximity of the discrete models to the continuum limit does not guarantee that the same bifurcations take place in the discrete setting in general, because some of the symmetries of the continuous model do not survive discretization. We use the center manifold reduction and normal forms to obtain precise information about the number and stability of solutions bifurcating from the homogeneous state in the discrete models on deterministic and sparse random graphs. Moreover, we present detailed numerical results for the discrete SHE on the nearest-neighbor and small-world graphs.
Effect of infundibulopelvic angle on outcomes of ureteroscopy: a systematic review and meta-analysis
Authors: Leighton James , Dingwall Arran , Whitehead Sophie , Luk Angus , Gauhar Vineet , Somani Bhaskar , Geraghty Robert
Published: July 2024

Purpose

The infundibulo-pelvic angle (IPA) is reportedly a predictor of successful ureteroscopy for lower pole renal stones, however there is uncertainty at which IPA success is likely. We therefore aimed to perform a meta-analysis and determine at which the angle of likely success and failure.

Methods

We performed a systematic review and meta-analysis as per Cochrane guidelines in accordance to the PRISMA statement. The review was registered with PROSPERO prior to commencement (ID: CRD42022296732). We included studies reporting on outcomes of ureteroscopy for lower pole stones, with IPA. We excluded patients undergoing alternative treatments for lower pole stones, anatomical abnormalities and studies with < 10 patients. We assessed bias with the Newcastle-Ottawa scale. We performed meta-analysis in R, and summarised the findings as per GRADE.

Results

Overall, there were 13 studies included, with 10 included for meta-analysis. These studies covered n = 1964 patients (71% stone free). Overall, the stone free patients had a significantly less acute mean IPA (52o ± 9o), compared to the non-stone free patients (39o ± 7o), on meta-analysis (REM MD = -13.0, 95% CI: -18.7 to -7.2, p < 0.001). On examination of forest plots, at IPA < 30o no patients were stone free, whilst > 50o all were stone free. Risk of bias was moderate, and certainty of evidence was ‘very low’.

Conclusion

With a very low certainty of evidence, we demonstrate that at an IPA of < 30o no patient is stone free, whilst > 50o all patients (in this review) are stone free. More evidence is therefore needed.
Epidemiological changes in the pattern of children’s traumatic injuries at Hong Kong emergency departments during the COVID-19 pandemic: a retrospective, single-institutional, serial and comparative study
Authors: Tsang Jaime Tsz-wing , Fung Adrian Chi-heng , Wong Heidi Hay-tai , Dai Wing Chiu , Wong Kenneth Kak-yuen
Published: July 2024

Introduction

Trauma is the leading cause of paediatric mortality and morbidity. Stay-home regulations for coronavirus disease 2019 (COVID-19) reportedly changed trauma severity, yet data from Hong Kong were lacking. This study examined Hong Kong’s spectrum of paediatric trauma and addressed knowledge gaps concerning epidemiological changes during COVID-19.

Methods

Children with traumatic injuries who attended a tertiary trauma centre from January 2010 to March 2022 were included in this retrospective, cross-sectional study. We analysed demographic and clinical data and conducted unadjusted bivariate analyses of injury patterns before and after the pandemic.

Results

In total, 725 children attended the Accident and Emergency Department due to trauma, 585 before and 140 during COVID-19. The male-to-female ratio was 1.84:1. The 90-day trauma-related mortality was 0.7%. The overall Injury Severity Score was 3.52 ± 5.95. The paediatric trauma incidence was similar before and after social-distancing policies (both 5.8 cases monthly). Gender, ISS distribution, intensive care unit stay length, and hospital stay length values were similar (p > 0.05). Trauma call activation (8.4% vs. 5.7%, p = 0.002) and road traffic accidents (10.6% vs. 5.7%, p = 0.009) significantly decreased, yet younger-patient injuries (< 10 years old; 85.7% vs. 71%, p < 0.001), burns (28% vs. 45.7%, p < 0.001), and domestic injuries (65.5% vs. 85.7%, p < 0.001) significantly increased. No significant self-harm, assault, or abuse increases were found.

Conclusions

The paediatric trauma incidences were similar before and during the pandemic. However, domestic and burn injuries significantly increased, highlighting the importance of injury prevention.
A screening for cerebral deoxygenation during VT ablations in patients with structural heart disease
Authors: Müller Julian , Koch Lena , Halbfass Philipp , Nentwich Karin , Berkovitz Artur , Barth Sebastian , Wächter Christian , Lehrmann Heiko , Deneke Thomas
Published: July 2024

Background

Patients undergoing ventricular tachycardia (VT) ablation often present with structural heart disease (SHD) and reduced ejection fraction. Inducing VT by programmed electrical stimulation (PES) puts these patients at risk for hemodynamic instability and cerebral hypoperfusion.

Objective

The present study screens for cerebral oxygen desaturation phases (ODPs) in patients undergoing VT ablation.

Methods

Forty-seven patients (age 61 ± 14 years, 72% males) underwent ablation of sustained VT with simultaneous neuromonitoring using near-infrared spectroscopy (NIRS).

Results

Analysis of NIRS signal identified ODPs in 29 patients (62%). ODPs were associated with a higher prevalence of ischemic heart disease (IHD) (45% vs. 11%, p = 0.024), previous VT episodes (n = 16 vs. 4, p = 0.018), and VTs inducible by PES (n = 2.4 vs. 1.2, p = 0.004). Patients with ODPs were more likely to be admitted to intensive care unit (ICU) (78% vs. 33%, p = 0.005) and had more in-hospital VT recurrences (24% vs. 0%, p = 0.034). No differences were observed in VT recurrence rates after hospital discharge (41.4% vs. 44.4%, p = 0.60) and left ventricular ejection fraction (34% vs. 38%, p = 0.567). IHD (OR: 32.837, p = 0.006), ICU admission (OR: 14.112, p = 0.013), and the number of VTs inducible at PES (OR: 2.705, p = 0.015) were independently associated with ODPs.

Conclusions

This study registers episodes of cerebral hypoperfusion in 62% of patients undergoing VT ablation and identifies IHD and the number of VTs inducible at PES as possible risk factors for these episodes.
Genetic and epigenetic instability as an underlying driver of progression and aggressive behavior in IDH-mutant astrocytoma
Authors: Richardson Timothy E. , Walker Jamie M. , Hambardzumyan Dolores , Brem Steven , Hatanpaa Kimmo J. , Viapiano Mariano S. , Pai Balagopal , Umphlett Melissa , Becher Oren J. , Snuderl Matija , McBrayer Samuel K. , Abdullah Kalil G. , Tsankova Nadejda M.
Published: July 2024

In recent years, the classification of adult-type diffuse gliomas has undergone a revolution, wherein specific molecular features now represent defining diagnostic criteria of IDH-wild-type glioblastomas, IDH-mutant astrocytomas, and IDH-mutant 1p/19q-codeleted oligodendrogliomas. With the introduction of the 2021 WHO CNS classification, additional molecular alterations are now integrated into the grading of these tumors, given equal weight to traditional histologic features. However, there remains a great deal of heterogeneity in patient outcome even within these established tumor subclassifications that is unexplained by currently codified molecular alterations, particularly in the IDH-mutant astrocytoma category. There is also significant intercellular genetic and epigenetic heterogeneity and plasticity with resulting phenotypic heterogeneity, making these tumors remarkably adaptable and robust, and presenting a significant barrier to the design of effective therapeutics. Herein, we review the mechanisms and consequences of genetic and epigenetic instability, including chromosomal instability (CIN), microsatellite instability (MSI)/mismatch repair (MMR) deficits, and epigenetic instability, in the underlying biology, tumorigenesis, and progression of IDH-mutant astrocytomas. We also discuss the contribution of recent high-resolution transcriptomics studies toward defining tumor heterogeneity with single-cell resolution. While intratumoral heterogeneity is a well-known feature of diffuse gliomas, the contribution of these various processes has only recently been considered as a potential driver of tumor aggressiveness. CIN has an independent, adverse effect on patient survival, similar to the effect of histologic grade and homozygous CDKN2A deletion, while MMR mutation is only associated with poor overall survival in univariate analysis but is highly correlated with higher histologic/molecular grade and other aggressive features. These forms of genomic instability, which may significantly affect the natural progression of these tumors, response to therapy, and ultimately clinical outcome for patients, are potentially measurable features which could aid in diagnosis, grading, prognosis, and development of personalized therapeutics.
Anti-Ku + myositis: an acquired inflammatory protein-aggregate myopathy
Authors: Holzer Marie-Therese , Uruha Akinori , Roos Andreas , Hentschel Andreas , Schänzer Anne , Weis Joachim , Claeys Kristl G. , Schoser Benedikt , Montagnese Federica , Goebel Hans-Hilmar , Huber Melanie , Léonard-Louis Sarah , Kötter Ina , Streichenberger Nathalie , Gallay Laure , Benveniste Olivier , Schneider Udo , Preusse Corinna , Krusche Martin , Stenzel Werner
Published: July 2024

Myositis with anti-Ku-autoantibodies is a rare inflammatory myopathy associated with various connective tissue diseases. Histopathological studies have identified inflammatory and necrotizing aspects, but a precise morphological analysis and pathomechanistic disease model are lacking. We therefore aimed to carry out an in-depth morpho-molecular analysis to uncover possible pathomechanisms. Muscle biopsy specimens from 26 patients with anti-Ku-antibodies and unequivocal myositis were analyzed by immunohistochemistry, immunofluorescence, transcriptomics, and proteomics and compared to biopsy specimens of non-disease controls, immune-mediated necrotizing myopathy (IMNM), and inclusion body myositis (IBM). Clinical findings and laboratory parameters were evaluated retrospectively and correlated with morphological and molecular features. Patients were mainly female (92%) with a median age of 56.5 years. Isolated myositis and overlap with systemic sclerosis were reported in 31%, respectively. Isolated myositis presented with higher creatine kinase levels and cardiac involvement (83%), whereas systemic sclerosis-overlap patients often had interstitial lung disease (57%). Histopathology showed a wide spectrum from mild to pronounced myositis with diffuse sarcolemmal MHC-class I (100%) and -II (69%) immunoreactivity, myofiber necrosis (88%), endomysial inflammation (85%), thickened capillaries (84%), and vacuoles (60%). Conspicuous sarcoplasmic protein aggregates were p62, BAG3, myotilin, or immunoproteasomal beta5i-positive. Proteomic and transcriptomic analysis identified prominent up-regulation of autophagy, proteasome, and hnRNP-related cell stress. To conclude, Ku + myositis is morphologically characterized by myofiber necrosis, MHC-class I and II positivity, variable endomysial inflammation, and distinct protein aggregation varying from IBM and IMNM, and it can be placed in the spectrum of scleromyositis and overlap myositis. It features characteristic sarcoplasmic protein aggregation on an acquired basis being functionally associated with altered chaperone, proteasome, and autophagy function indicating that Ku + myositis exhibit aspects of an acquired inflammatory protein-aggregate myopathy.
Modeling and simulation of chemo-elasto-plastically coupled battery active particles
Authors: Schoof Raphael , Niermann Johannes , Dyck Alexander , Böhlke Thomas , Dörfler Willy
Published: July 2024

As an anode material for lithium-ion batteries, amorphous silicon offers a significantly higher energy density than the graphite anodes currently used. Alloying reactions of lithium and silicon, however, induce large deformation and lead to volume changes up to 300%. We formulate a thermodynamically consistent continuum model for the chemo-elasto-plastic diffusion-deformation behavior of amorphous silicon and it’s alloy with lithium based on finite deformations. In this paper, two plasticity theories, i.e. a rate-independent theory with linear isotropic hardening and a rate-dependent one, are formulated to allow the evolution of plastic deformations and reduce occurring stresses. Using modern numerical techniques, such as higher order finite element methods as well as efficient space and time adaptive solution algorithms, the diffusion-deformation behavior resulting from both theories is compared. In order to further increase the computational efficiency, an automatic differentiation scheme is used, allowing for a significant speed up in assembling time as compared to an algorithmic linearization for the global finite element Newton scheme. Both plastic approaches lead to a more heterogeneous concentration distribution and to a change to tensile tangential Cauchy stresses at the particle surface at the end of one charging cycle. Different parameter studies show how an amplification of the plastic deformation is affected. Interestingly, an elliptical particle shows only plastic deformation at the smaller half axis. With the demonstrated efficiency of the applied methods, results after five charging cycles are also discussed and can provide indications for the performance of lithium-ion batteries in long term use.
FFT-based homogenisation for efficient concurrent multiscale modelling of thin plate structures
Authors: Li Haolin , Sharif Khodaei Zahra , Aliabadi M. H.
Published: July 2024

This paper presents a novel approach to concurrent multiscale analysis, where structures are formulated at both microscopic and macro levels for simulation purposes. The proposed method employs a plate model to formulate structures at both scales, and homogenisation is performed using the FFT-based approach, offering higher efficiency compared to conventional methods. Additionally, the macroscopic tangent operator of the microscopic model is derived through an algorithmically consistent process within the FFT-based framework, incorporating the application of Lippman–Schwinger equations as outlined in this work. The effectiveness of the proposed method is demonstrated through case studies in real simulations, revealing comparable results to traditional multiscale schemes in addressing multiscale thin plate structures. Importantly, the method significantly reduces computing time and memory usage, attributed to the efficiency of plate modelling and the FFT-based homogenisation strategy.
Hardy–Sobolev interpolation inequalities
Authors: Dietze Charlotte , Nam Phan Thành
Published: July 2024

We derive a family of interpolation estimates which improve Hardy’s inequality and cover the Sobolev critical exponent. We also determine all optimizers among radial functions in the endpoint case and discuss open questions on nonrestricted optimizers.
The use of constrained methods to analyze the molecular reactivity and to define a new type of pseudo atoms
Authors: Cedillo Andrés , Martínez-Aguilar José-Remy
Published: July 2024

Context

Constrained methods in electronic structure methodologies add terms to the variational equations and generate solutions that represent distorted electronic distributions. In some cases, the new solutions can be used to study the chemical reactivity of parts of the molecule. Additionally, this contribution presents the use of population constraints to define pseudo atoms in a molecule. The effects of the pseudo atom on the molecular properties are analyzed. The pseudo atoms are used to simulate the inductive effect of the substituent in a group of carbonyl molecules and their effect on the stability of the complexes between these organic species and one molecule of water. A discussion on the assumptions involved in the present definition of pseudo atoms is also included.

Method

The constrained RHF computations are done in a modified Hartree-Fock code for Gaussian basis sets. The selected basis set is STO-6 G.
Assessing uncertainty in bioclimatic modelling: a comparison of two high-resolution climate datasets in northern Patagonia
Authors: Fierke Jonas , Joelson Natalia Zoe , Loguercio Gabriel Angel , Putzenlechner Birgitta , Simon Alois , Wyss Daniel , Kappas Martin , Walentowski Helge
Published: July 2024

Climate change is reshaping forest ecosystems, presenting urgent and complex challenges that demand attention. In this context, research that quantifies interactions between climate and forests is substantial. However, modelling at a spatial resolution relevant for ecological processes presents a significant challenge, especially given the diverse geographical contexts in which it is applied. In our study, we aimed to assess the effects of applying CHELSA v.2.1 and WorldClim v2.1 data on bioclimatic analysis within the Río Puelo catchment area in northern Patagonia. To achieve this, we inter-compared and evaluated present and future bioclimates, drawing on data from both climate datasets. Our findings underscore substantial consistency between both datasets for temperature variables, confirming the reliability of both for temperature analysis. However, a strong contrast emerges in precipitation predictions, with significant discrepancies highlighted by minimal overlap in bioclimatic classes, particularly in steep and elevated terrains. Thus, while CHELSA and WorldClim provide valuable temperature data for northern Patagonia, their use for precipitation analysis requires careful consideration of their limitations and potential inaccuracies. Nevertheless, our bioclimatic analyses of both datasets under different scenarios reveal a uniform decline in mountain climates currently occupied by N. pumilio, with projections suggesting a sharp decrease in their coverage under future climate scenarios.