bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring P450 superfamily diversity with P450Atlas ‐ Online tool for automated subfamily assignment
Authors: Gront Dominik , Syed Khajamohiddin , Nelson David R.
Published: February 2025

Cytochrome P450 monooxygenases (CYPs/P450s) are heme‐containing enzymes known to biology for more than six decades. Their stereo‐ and regio‐specific enzymatic activities on various compounds led to exploring their potential in almost all areas of life. The P450 superfamily, encompassing nearly 10,000 known families, boasts a staggering diversity represented by numerous families, highlighting its immense scale within the realm of enzymes. In this contribution, we describe the P450Atlas website: the ultimate source of information about all named P450 families and subfamilies. The website's main functionality is the automated assignment of a query sequence to one of the known subfamilies. The new subfamily assignment algorithm relies on Hidden Markov Models (HMM) and has been extensively tested and compared to an approach based on the BLAST program. Extensive validation shows that the HMM approach is more sensitive than the latter one, offering almost perfect automated P450 sequence assignment to subfamilies. A user can also browse and search through the online list of families across the Tree of Life. We believe that the P450Atlas website (https://p450atlas.org) will become a comprehensive and unified source of information on cytochrome 450 nomenclature.
Low Muscle Mass and Treatment Tolerance in Patients With Upper Gastrointestinal Cancer: A Systematic Review and Meta‐Analysis
Authors: Stanhope E. N. , Thomsen S. N. , Turner J. E. , Fairman C. M. , Lahart I. M.
Published: February 2025

Background

Upper gastrointestinal (GI) cancers carry notable mortality risks. While systemic therapies are vital for their management, they are often hindered by adverse events (AE), which can compromise their effectiveness. The presence of low skeletal muscle mass (LSMM) may be linked with the prevalence of AE and could potentially undermine treatment tolerance by impacting drug metabolism. The primary objective of this systematic review and meta‐analysis was to evaluate the association between LSMM and the risk of grades 3 and 4 AE and treatment discontinuation.

Methods

Studies investigating the association between skeletal muscle mass and AE or treatment tolerability in adult patients diagnosed with upper GI cancer scheduled to undergo systemic treatment were eligible. The primary outcomes were grades 3 and 4 AE and treatment discontinuations. Four electronic databases were systematically searched with no date restrictions on 10 October 2022. Data were analysed via random‐effects meta‐analyses, and the risk of bias was assessed using the risk of bias in non‐randomised studies—of exposure (ROBINS‐E) appraisal tool.

Results

We identified 50 eligible publications from 49 studies. Our meta‐analyses revealed evidence of a higher risk of grades 3 and 4 AE (RR 1.44, 95% CI 1.23–1.68, N = 13) and treatment discontinuation (RR 2.39, 95% CI 1.87–3.07, N = 11) in LSMM versus non‐LSMM. Secondary analyses revealed an increased risk of fatigue, febrile neutropenia, intestinal pneumonia, stomatitis and thrombocytopenia in LSMM. However, 92% of studies assessing grades 3 and 4 AE and 73% of studies examining treatment discontinuation had a very high risk of bias.

Conclusions

LSMM in patients with upper GI cancer is associated with a higher risk of grades 3 and 4 AE and the discontinuation of systemic cancer treatment. The high risk of bias should be considered in the interpretation of these findings. Further evaluation of the association between LSMM and treatment tolerability in confirmatory, prospective studies is needed.
Statistics of Received Power Time Series for Optical LEO Satellite Uplinks
Authors: Carrillo‐Flores Andrea , Giggenbach Dirk , Knopp Marcus T.
Published: February 2025

In free‐space optical satellite communications, a transmitted optical signal is perturbed by pointing inaccuracies and through the atmosphere's index‐of‐refraction turbulence. This leads to signal fluctuations and power fading when detected by a receiver. Knowledge of these signal instability statistics is advantageous for the design of robust ground‐ and space‐based optical communication systems. For example, the development of optimized automatic repeat request (ARQ) and forward error correction (FEC) protocols to compensate these losses is facilitated. The channel characteristics of a ground‐to‐satellite (uplink) and satellite‐to‐ground (downlink) transmission change with the elevation angle of the link direction, and consequently, the signal fluctuations and power fading also vary. In this work, numerical time series of received power are generated for uplink scenarios to low Earth orbit (LEO) satellites for different satellite elevations. The time series are generated for two experimental scenarios, considering the effects of a gamma‐gamma and lognormal‐distributed atmospheric scintillation and the use of transmitter diversity. The generated series of power are compared with analytical results and measurements in terms of the run of statistical parameters, and the results are contrasted. The results can be used for link‐budget design, for communications standardization, and for the analysis and design of fading mitigation techniques that prevent signal fading and data loss.
Predictors of Sustainable Investment Motivation: An Interpretable Machine Learning Approach
Authors: Sosnovskikh Sergey , Valko Danila , Meyer‐Alten Raphael
Published: February 2025

This study investigates the determinants influencing retail investors' capital allocation to sustainable financial products, focusing specifically on Germany—a pertinent case due to its strong commitment to sustainability, supportive regulatory environment and substantial market growth. We utilised two surveys conducted in 2020 by the 2° Investing Initiative and Choyze GmbH in collaboration with the German Environment Agency to obtain a measurement invariant combined dataset. Utilising robust and generalised linear modelling and interpretable machine learning techniques, our analysis identified that three primary motivation components—personal values, social and environmental impact and investment return—exhibit significant overlap. The findings demonstrate that investment motivations are consistently predicted by sustainability interests. In contrast, socio‐demographic factors (age, gender, education, household income) exhibit inconsistent patterns across investment motivations and exert weaker influence. As a result, we propose robust models to predict sustainable investment motivation and highlight their consistency and applicability in the green finance sector.
The Impact of Sustainability Disclosure on Firm Value in the Energy Sector of BRICS Economies: The Holistic Approach of GRI Guidelines
Authors: Hussain Farhan , Zhou Zhifang , Abbas Hussain , Dusengemungu Didier Robert
Published: February 2025

Sustainability disclosure is a key concern for the corporate sector in terms of safeguarding nature and preserving long‐term trust. This research investigates the impact of 20 comprehensive sustainability dimensions on the performance of energy firms in BRICS economies. The data were collected through content analysis, guided by the Global Reporting Initiative (GRI) farmwork, and analysis with the generalized method of moments (GMM) to ensure robustness. The findings show a significant relationship between environmental disclosure and firm value. Furthermore, the study highlights the importance of social and economic disclosures in developing economies driven by industry‐specific challenges, climate risks, and stakeholder demands. In addition, companies with high sustainability disclosure enhance legitimacy by gaining advantages from effective management and governmental support. BRICS governments and corporations promote sustainability through impactful interventions aligned with GRI guidelines.
Individualized Time‐Varying Nonparametric Model With an Application in Mobile Health
Authors: Rim Jenifer , Xu Qi , Tang Xiwei , Guo Yuqing , Qu Annie
Published: February 2025

Individualized modeling has become increasingly popular in recent years with its growing application in fields such as personalized medicine and mobile health studies. With rich longitudinal measurements, it is of great interest to model certain subject‐specific time‐varying covariate effects. In this paper, we propose an individualized time‐varying nonparametric model by leveraging the subgroup information from the population. The proposed method approximates the time‐varying covariate effect using nonparametric B‐splines and aggregates the estimated nonparametric coefficients that share common patterns. Moreover, the proposed method can effectively handle various missing data patterns that frequently arise in mobile health data. Specifically, our method achieves subgrouping by flexibly accommodating varying dimensions of B‐spline coefficients due to missingness. This capability sets it apart from other fusion‐type approaches for subgrouping. The subgroup information can also potentially provide meaningful insight into the characteristics of subjects and assist in recommending an effective treatment or intervention. An efficient ADMM algorithm is developed for implementation. Our numerical studies and application to mobile health data on monitoring pregnant women's deep sleep and physical activities demonstrate that the proposed method achieves better performance compared to other existing methods.
Network Meta‐Analysis With Individual Participant‐Level Data of Time‐to‐Event Outcomes Using Cox Regression
Authors: Hua Kaiyuan , Wojdyla Daniel , Carnicelli Anthony , Granger Christopher , Wang Xiaofei , Hong Hwanhee
Published: February 2025

The accessibility of individual participant‐level data (IPD) enhances the evaluation of moderation effects of patient covariates. It facilitates the provision of accurate estimation of intervention effects and confidence intervals by incorporating covariate correlations across multiple clinical trials. With a time‐to‐event outcome, Cox regression can be applied for network meta‐analysis (NMA) using IPD. However, there lacks comprehensive reviews and comparisons of the specifications and assumptions of these Cox models and their impact on the interpretation of hazard ratios, effect moderation, and trial heterogeneity in IPD‐NMA. In this paper, we examine various Cox models for IPD‐NMA and compare different approaches to modeling trial, treatment, and covariate effects. We employ multiple graphical tools and statistical tests to assess proportional hazard assumptions and discuss their implications. Additionally, we explore the application of extended Cox models when the proportional hazard assumption is violated. Practical guidance on interpreting and reporting NMA results is provided. A simulation study is conducted to compare the performance of different models. We illustrate the methods to conduct IPD‐NMA through a real data example.
Energy Saving and Carbon Reduction in Steel Production: Synergy and Optimization Based on Long and Short Processes
Authors: Feng Mingyang , Liu Guangxin , Yue Qiang , Wang Heming
Published: February 2025

In light of global climate crisis, it is imperative to implement measures aimed at reducing energy consumption and carbon emissions in the iron and steel industry. This study focuses on the development of innovative methodologies for minimizing energy consumption and carbon emissions during steel production, with particular emphasis on the synergistic optimization of both long‐ and short‐flow steelmaking processes. A carbon flow model has been constructed to analyze the material and energy flows associated with long‐process (BF–BOF) and short‐process (electric arc furnace (EAF)) steelmaking, as well as to assess the potential for carbon reduction through industrial symbiotic technologies. The findings illustrate that in the S2 scenario, where the proportion of EAF steel is increased to 50%, carbon emissions are reduced to 1,464.12 kg tcs, representing an 18.9% decrease. This reduction is lower than that achieved by traditional long‐process steelmaking; and the industrial symbiosis technologies, such as chemical production and coke oven gas hydrogen production, can facilitate an additional reduction in carbon emissions of 41.33 kg tcs. This study offers a new pathway and reference for the green transformation of the iron and steel industry.
Functionalization of Hydrophilic and Amphiphilic Carbon Dots with Polyethylene Glycol for Electroluminescent Devices
Authors: Miruschenko Mikhail D. , Kosolapova Kseniia D. , Aleinik Ivan A. , Borodina Lyubov’ N. , Vedernikova Anna A. , Sokolova Anastasiia V. , Sandzhieva Maria A. , Mitroshin Aleksandr M. , Yakimansky Alexander V. , Koroleva Aleksandra V. , Zhizhin Evgeniy V. , Cherevkov Sergei A. , Langer Michal , Otyepka Michal , Ushakova Elena V. , Rogach Andrey L.
Published: February 2025

Carbon dots (CDs) are fluorescent carbon nanomaterials that are considered for applications in optoelectronics, sensorics, and biofields due to their low‐cost and robust synthesis, and versatile optical properties. Herein, it is demonstrated how chemical functionalization of hydrophilic or amphiphilic CDs with polyethylene glycol influences their energy level structure and hence the emission properties. Functionalization of CDs with polyethylene glycol results in an increase in emission quantum yield: from 30% to 75% for hydrophilic CDs and from 20% to 25% for amphiphilic CDs. The estimated absolute values of energy levels, including the highest occupied molecular orbital and the lowest unoccupied molecular orbital energies, are dependent on chemical composition and size of CDs. Moreover, polyethylene glycol‐functionalized CD can form good quality films based on their composite with polyvinylcarbazole (PVK), that together with intense emission is crucial for light‐emitting diode (LED) fabrication. By studying spectral properties of fabricated CD‐LEDs, it is shown that their electroluminescence (EL) originates from mixed energy levels of CD and PVK in the composite, resulting in the shifting of the EL maximum from blue to green during several seconds of LED operation. The optimized CD‐LEDs show brightness up to 2600 cd m−2.
Laser‐Induced in situ Synthesis and Assembly of Nano‐Cotton TiO2 Humidity Sensors with High Sensitivity and Fast Response for Real‐Time Respiratory Monitoring
Authors: Yu Zhichao , Li Juqing , Zhang Qiurui , Xiang Pei , Lei Jincheng
Published: February 2025

Humidity sensors functioned by 1D nanostructural metal oxides (1D NMOs) are promising for real‐time respiratory monitoring. However, the preparation and assembly of 1D NMOs on sensor structures are quite challenging due to the complicated synthesis procedures and vulnerability of nanomaterials. Herein, a multi‐laser processing technology is developed to fabricate nano‐cotton TiO2 humidity sensors for respiratory monitoring. The nano‐cotton TiO2 is in situ synthesized and assembled to the interdigitate electrodes of the sensor structure using the transmitted picosecond laser deposition. The as‐deposited TiO2 layers are in situ post‐annealed by a CO2 laser to optimize the crystallinity and phase compositions for humidity sensing. By investigating the evolution mechanism of the nanostructures of the laser‐induced plasma plumes during sputtering, it is demonstrated that the nanostructures of the laser‐deposited TiO2 layers can be flexibly controlled by varying the target‐to‐substrate distance. The crystallinity, phase composition, surface roughness, and layer thickness of the nano‐cotton TiO2 are estimated to evaluate the developed technology. The fabricated sensors exhibit high sensitivity and rapid response to the variation of relative humidity under both steady and transient states. To demonstrate for real‐time respiratory monitoring, the fabricated sensor is integrated into a commercial mask to monitor human's breathing under different respiratory modes.
Review, part 2: Lifting the Veil on Enrollment Management
Authors: Dennis Marguerite J.
Published: February 2025

In last month's article I wrote about the assessment of enrollment management raised by several enrollment management experts in the book Lifting the Veil on Enrollment Management and how the current system of enrollment management has not served colleges, universities, and students well.
Surgical gestures—An emerging field for surgical assessment and training
Authors: Ma Runzhuo
Published: February 2025

As surgical training shifts from a traditional method to a more standardized approach, objective analysis and assessment of surgeon performance has become a key focus. Surgical gestures, defined as the smallest independent units of instrument‐tissue interaction, offer a quantifiable way to analyze surgical performance. Standardizing the terminology for describing surgical gestures can enhance communication during surgical training in the operating room. More importantly, surgical gesture usage has been linked to surgeon expertise and has been shown to be associated with patient outcomes. This review examines current classification systems for surgical gestures in dissection and suturing tasks, across open, laparoscopic, and robotic procedures, which serve as an armamentarium for training surgeons. It also explores how surgical gestures can complement conventional surgical assessment tools. Finally, it reviews current artificial intelligent models on gesture recognition and automation, envisions a future where gesture recognition forms the foundation for intelligent assistance in the operating room.
From Traces to Intelligence: Forensic Science Contributions to Counterfeiting Understanding Through Profiling of Counterfeit Goods
Authors: Mireault Caroline , Dumont Pier‐Louis , Delémont Olivier
Published: February 2025

Counterfeiting is not a phenomenon to be underestimated. It has broad implications including economic losses, health, and safety risks, and the financing of organized crime. Forensic science, beyond merely detecting counterfeit goods, can offer critical insights into the production and distribution stages of counterfeiting, thereby supporting more effective law enforcement and policy interventions. The first part of this paper explores the role forensic science can play in understanding counterfeiting and the clandestine markets it fosters, through forensic intelligence. By analyzing counterfeit specimens, utilizing physical, chemical, and digital traces, forensic science can significantly contribute by mapping the connections between them and uncovering the modus operandi of counterfeiters. The second part showcases specific initiatives that have been developed and implemented, including the profiling of fraudulent identity documents, the physical and chemical analysis of counterfeit perfumes and boots, and the intelligence produced from examining counterfeit watches. These examples demonstrate the methodologies employed and the potential outcomes of adopting a forensic intelligence perspective. They illustrate how forensic techniques can reveal connections between different counterfeit items and provide insights into their production and distribution networks. The findings underscore the importance of interdisciplinary collaboration and the cross‐fertilization of operational deployments with research initiatives.
Electrodynamics and geometric continuum mechanics
Authors: Segev Reuven
Published: February 2025

This paper offers an informal instructive introduction to some of the main notions of geometric continuum mechanics for the case of smooth fields. We use a metric invariant stress theory of continuum mechanics to formulate a simple generalization of the fields of electrodynamics and Maxwell’s equations to general differentiable manifolds of any dimension, thus viewing generalized electrodynamics as a special case of continuum mechanics. The basic kinematic variable is the potential, which is represented as a p-form in an n-dimensional spacetime. The stress for the case of generalized electrodynamics is assumed to be represented by an

$$(n-p-1)$$

(
n
-
p
-
1
)

-form, a generalization of the Maxwell 2-form.
A multi-energy meta-model strategy for multi-step ahead energy load forecasting
Authors: Mystakidis Aristeidis , Ntozi Evangelia , Koukaras Paraskevas , Katsaros Nikolaos , Ioannidis Dimosthenis , Tjortjis Christos , Tzovaras Dimitrios
Published: February 2025

Energy load forecasting (ELF) is necessary for optimal scheduling of electricity distribution to customers, reducing energy losses and for regulating power distribution. There are numerous approaches for ELF based on statistical, Machine Learning (ML) and deep learning (DL) methods. This paper performs a comparative multi-step ahead ELF utilising rolling (or recursive) versus direct forecasting techniques for three energy types (ETs), i.e. heating, cooling and electricity. It introduces a multi-energy meta-model strategy (MEMMS), a unified approach that combines the best outcomes of the comparison and utilises one model per time step ahead for all ETs. The findings were validated on three datasets, one per ET, employing metrics such as mean absolute error (MAE), root-mean-squared error (RMSE),

$$R^{2}$$

R
2

and execution time. The novel aspects of this work can be attributed to the possible identification of the best-performing ML and DL models across all ETs, as well as the multi-energy behaviour recognition of the multi-step ahead strategies and the employed MEMMS approach. Initial comparison results indicated that direct multi-step ahead voting ensemble with light gradient boosting machine (LGBM) and CatBoost (CB) was the best-performing baseline ensemble approach. MEMMS reduced training time by 50%, achieving up to 2 kW lower RMSE, 0.5 kW lower MAE and 5% higher

$$R^{2}$$

R
2

for cooling, and up to 2 kW lower RMSE, 4 kW higher MAE and 2% higher

$$R^{2}$$

R
2

for heating, showcasing versatility across ETs and forecasting horizons.
Charge Transport Systems with Fermi–Dirac Statistics for Memristors
Authors: Herda Maxime , Jüngel Ansgar , Portisch Stefan
Published: February 2025

An instationary drift–diffusion system for the electron, hole, and oxygen vacancy densities, coupled to the Poisson equation for the electric potential, is analyzed in a bounded domain with mixed Dirichlet–Neumann boundary conditions. The electron and hole densities are governed by Fermi–Dirac statistics, while the oxygen vacancy density is governed by Blakemore statistics. The equations model the charge carrier dynamics in memristive devices used in semiconductor technology. The global existence of weak solutions is proved in up to three space dimensions. The proof is based on the free energy inequality, an iteration argument to improve the integrability of the densities, and estimations of the Fermi–Dirac integral. Under a physically realistic elliptic regularity condition, it is proved that the densities are bounded.
Prior hospitalizations as a predictor of prognosis in heart failure with mildly reduced ejection fraction
Authors: Steffen Henning Johann , Behnes Michael , Schmitt Alexander , Abel Noah , Lau Felix , Reinhardt Marielen , Akin Muharrem , Bertsch Thomas , Ayoub Mohamed , Mashayekhi Kambis , Weidner Kathrin , Akin Ibrahim , Schupp Tobias
Published: February 2025

Objective

This study aims to investigate the prognostic impact of the presence and type of prior hospitalizations in patients with heart failure with mildly reduced ejection fraction (HFmrEF).

Background

Data investigating the prognostic impact of the present and type of previous all-cause hospitalizations in HFmrEF is limited.

Methods

Consecutive patients hospitalized with HFmrEF at a single medical center were retrospectively included from 2016 to 2022. The prognosis of patients with a prior hospitalization < 12 months was compared to patients without. The primary endpoint was all-cause mortality at 30 months (median follow-up), the key secondary endpoint was heart failure (HF)-related rehospitalization at 30 months.

Results

Two thousand one hundred eighty four patients with HFmrEF were included, 34.8% had a previous hospitalization < 12 months (admission to internal medicine and geriatrics: 60.8%, surgical department: 23.5%). The presence of a previous hospitalization was associated with an increased risk of all-cause mortality (38.6% vs. 27.4%; HR = 1.51; 95% CI 1.30–1.76; p = 0.01) and HF-related rehospitalization at 30 months (21.2% vs. 9.1%; HR = 2.48; 95% CI 1.96–3.14; p = 0.01), even after multivariable adjustments. However, the department of previous hospitalization (internal medicine vs. surgical) did not significantly affect the risk of 30-months all-cause mortality (37.1% vs. 43.2%; HR = 0.82, 95% CI 0.63–1.08; p = 0.16) or HF-related rehospitalization (24.0% vs. 16.8%; HR = 1.47, 95% CI 0.98–2.24; p = 0.07). Finally, the type of previous admission (i.e., elective, emergency vs. HF-related admission) (log-rank p = 0.29) did not affect the risk of 30-months all-cause mortality.

Conclusion

Prior hospitalizations within 12 months were independently associated with impaired long-term mortality in patients with HFmrEF, irrespective of the department or type of prior admission.
Determination of DNA recovery from human teeth exposed to various acids
Authors: Sapan Tuğba Ünsal , Karaboğa Nejla
Published: February 2025

Forensic sciences encompass a comprehensive application of various scientific disciplines working together to solve crimes. In forensic cases, identification is the primary procedure. Due to the variety of crimes, difficulties can arise in identification. The ability to extract DNA from all types of biological tissues has made DNA analysis one of the most frequently used and reliable methods in identification. Teeth, which are noted for their relatively low degradation over long periods despite exposure to environmental, physical, and chemical factors, and their ability to securely preserve DNA material, are among the most used samples in DNA analysis. With the evolution of crime and methods of concealing it, body integrity-threatening procedures such as exposure to acids are frequently used by perpetrators. However, several studies have shown that DNA can still be recovered from dental samples exposed to various chemicals for specific durations. This study aimed to recover DNA from teeth exposed to strong acids. Dental samples obtained from volunteers were exposed to strong acids, including HCl, HNO3, and H2SO4, for 8, 12, and 120 hours, respectively, with each duration parameter tested separately. Following exposure, DNA isolation was performed, and the amount of DNA was assessed. Samples deemed suitable for identification underwent PCR and electrophoresis to obtain DNA profiles. The results showed that it was possible to successfully obtain a full DNA profile from molars exposed to sulfuric, hydrochloric, and nitric acid for up to 24 h, while it was possible to obtain a partial DNA profile from molars exposed to sulfuric acid for up to 120 h.
Synthesis, characterization and evaluation of experimental dental composite resin modified by grapefruit seed extract-mediated TiO₂ nanoparticles: green approach
Authors: Ezzat Dina , Sheta Mai Samy , Kenawy El-Refaie , Eid Mohammed A. , Elkafrawy Hend
Published: February 2025

Dental composite resins often face challenges related to secondary caries, polymerization shrinkage and fracture failure. This study aimed to synthesize an experimental composite resin modified with grapefruit seed extract-mediated titanium dioxide nanoparticles (GSE-TiO₂NPs) and evaluate its antibacterial activity and mechanical and physical properties. Green synthesis of TiO₂ nanoparticles was conducted utilizing GSE. The chemical profile of GSE was identified through gas chromatography-mass spectrometry. The as-prepared nanoparticles were incorporated into experimental composites at concentrations of 10 wt.% (10 wt.% GSE-TiO₂NPs group) and 20 wt.% (20 wt.% GSE-TiO₂NPs group), with an unmodified composite as the control group. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) confirmed the morphology and size of synthesized nanoparticles, with SEM revealing uniform particle distribution in the composite. Antibacterial activity against Streptococcus mutans was assessed using the agar disc diffusion method. Mechanical properties, including flexural strength (FS) and flexural modulus (FM), were evaluated according to ISO 4049 standards. Microhardness was tested according to the American Society for Testing Materials (ASTM E-384:1999) criteria. Polymerization shrinkage was measured using the strain gauge method. Modified composites exhibited significantly greater antibacterial activity against S. mutans compared to the control (p < 0.001). The 10 wt.% GSE-TiO₂NPs group demonstrated increased FS and FM values compared to the control group (p < 0.05). All groups surpassed the clinically acceptable microhardness threshold without significant differences (p = 0.588). Polymerization shrinkage was reduced in the modified groups (p < 0.01), with the 20 wt.% GSE-TiO₂NPs group showing the lowest value (13.06 ± 0.92%). Incorporating GSE-TiO₂NPs into composite resins enhances antibacterial activity, improves mechanical properties, and reduces polymerization shrinkage, suggesting a promising approach for developing advanced dental materials with integrated natural bioactive components.

Graphical abstract
Disrupting disruptions: enhancing supply chain resilience—lessons from the US Air Force
Authors: Berger Ron , Wagner Ralf , Dion Paul M. , Matthias Olga
Published: February 2025

Black swan events have highlighted the importance of supply chain resilience and hence drawn increased attention from academia. Using military supply chains as our research setting, we illustrate how supply chain resilience can be implemented in civilian networks and incorporate agility and flexibility into a responsive system-to-system model. We use a simulation model based on the Cassandra application to further develop supply chain network resilience theory. Our model provides updated situational awareness to decision makers and allows managers to identify direct and indirect threats to supply chains, allowing adaptation to unforeseen situations. We developed a dynamic, whole-system network model to provide timely, accurate, updateable and scalable information to planners and decision-makers at all levels in-order to reduce risk and increase resilience.
Frozen detritus: a novel nutritious food for juvenile mussels in captive breeding
Authors: Macháček Vojtěch , Simon Ondřej P. , Horáčková Jitka
Published: February 2025

Captive breeding of freshwater mussels is essential for conservation strategies to maintain populations of endangered bivalve mollusks. In the Czech Republic, breeders use detritus from natural sources, preferably from nearby streams and spring areas, to prepare pearl mussels for release into the target localities to reestablish sustainable populations in their native habitats. This strategy is subject to sudden changes, and breeders must consider different detritus qualities between seasons and the unpredictability of weather conditions. Therefore, harvesting natural detritus on a regular basis is challenging and time-consuming, and more samples require more testing, which increases the cost of captive breeding. We proved that juvenile freshwater pearl mussels grew faster when fed detritus stored frozen in a freezer than when fed the same chilled detritus. Therefore, detritus can be harvested under optimal conditions and stored in a freezer for the remaining season, thereby simplifying and reducing mussel conservation costs. Moreover, this approach offers a sustainable, environmentally friendly method that does not require the industrial production of artificial feeds.
Exploring the impact of climate change on respiratory health in Nigeria: a scoping review of current research, government policies and programs
Authors: Niyi-Odumosu Faatihah , Ozoh Obianuju B. , Ope Victor Oloruntoba , Ale Boni M. , Akinnola Olayemi , Iseolorunkanmi Alexander , Adeloye Davies
Published: February 2025

Climate change significantly impacts health globally, especially in densely populated, rapidly industrialising and ecologically diverse countries like Nigeria. We analysed climate change policies, studies, programs, and events at the national and subnational levels in Nigeria and explored their effects on public and respiratory health. Using the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMAScR) checklist, we searched PubMed, African Journals Online (AJoL), Google Scholar and government data repositories on January 10, 2024. We synthesised results using an adapted sector-level framework based on the World Health Organization (WHO) guidelines. Our searches returned 262 items, of which 32, including research studies, reports and grey documents, were retained for synthesis. Although some policies and programmes, like the Climate Change Act and Nigerian Climate and Health Observatory, exist, implementation is limited across many settings. Key reported respiratory pollutants in Nigeria include particulate matter (PM2.5, PM10), gaseous emissions (CO, SO₂, NOx), agricultural by-products (NH₃, H₂S), greenhouse gases (CH₄, CO₂), and microbial contaminants, which collectively increase the risk of respiratory inflammation, infections, and exacerbations of chronic respiratory symptoms and diseases. Our findings underscore a clear link between climate change and worsening respiratory health in many Nigerian settings. The current policies and programmes’ have limited impact, calling for comprehensive reforms, including improved enforcement and targeted action against major pollution sources, recognition of environmental rights, and stronger public health initiatives and community action.
The Destitute Working Class and the Rule-Abiding Citizen: The Contestation of Populist Tropes in the Gilets Jaunes Movement
Authors: Dumitrica Delia , Sommier Mélodine
Published: February 2025

This paper examines the discursive articulation and contestation of populist tropes for social movements. Where existing scholarship has regarded populism as a master frame for social movement mobilization, this paper foregrounds the precarity of “the people” in the case of the Gilets Jaunes (Yellow Vests) in France. To answer the question of how social and political actors (re)produce and challenge meanings about “the people,” we performed a discourse analysis of online news items (N = 100) about the Gilets Jaunes. We identify two oppositional discourses—the destitute working class and the rule-abiding citizen—through which the Gilets Jaunes become a polarized object of public discussion. Our findings suggest that the mobilizing potential of populist tropes can serve not only social movements, but also their political opponents. We conclude by exploring the political implications of the normalization of populist tropes in the context of social movements.
Nursing Students’ Perceptions of Spiritual Care in Türkiye: A Mixed Methods Study
Authors: Kırca Kamile , Gülnar Emel , Özveren Hüsna
Published: February 2025

Student nurses’ sensitivity and personal perceptions about spirituality and spiritual care are important in providing spiritual care because student nurses need to explore their spirituality and their relationship to care. The study was carried out with a sequential explanatory mixed method design. Quantitative data for the research was collected using the descriptive characteristics form and the spirituality and spiritual care rating scale. As a result of the data obtained from the focus group interviews, the authors identified five contexts, fifteen themes and many sub-themes. As a result of this study, it was determined that the student’s perceptions of spirituality and spiritual care were above average, and they saw spiritual care as a dimension of holistic care. However, they did not feel competent in providing spiritual care in clinical practice.
An empirical study on impact of label noise on synthetic tabular data generation
Authors: Kim Jeonghoon , Huang Chao , Liu Xin
Published: February 2025

Synthetic data has been actively used for various machine learning-based tasks due to its benefits such as massive reproducibility and privacy enhancement compared to using the original data. The quality of the generated synthetic dataset crucially depends on the quality of the original data, and the latter is often corrupted by label noise. While there have been studies on feature noise, how label noise affects synthetic data generation is under-explored. In this paper, we evaluate the impact of the noisy label on synthetic data generation with a focus on tabular data. One challenge is how to evaluate the quality of synthetic data under label noise. To this end, we design comprehensive experiments to measure the impact of label noise on synthetic data generation in different aspects: synthetic data quality, data utility, and convergence for training synthesizers and machine learning models for downstream tasks. The empirical results cover wide aspects of synthetic data generation under label noise and they show quality and utility degrades with higher noise levels while there is no significant effect on the synthesizer convergence observed.
Bias, machine learning, and conceptual engineering
Authors: Rudolph Rachel Etta , Shech Elay , Tamir Michael
Published: February 2025

Large language models (LLMs) such as OpenAI’s ChatGPT reflect, and can potentially perpetuate, social biases in language use. Conceptual engineering aims to revise our concepts to eliminate such bias. We show how machine learning and conceptual engineering can be fruitfully brought together to offer new insights to both conceptual engineers and LLM designers. Specifically, we suggest that LLMs can be used to detect and expose bias in the prototypes associated with concepts, and that LLM de-biasing can serve conceptual engineering projects that aim to revise such conceptual prototypes. At present, these de-biasing techniques primarily involve approaches requiring bespoke interventions based on choices of the algorithm’s designers. Thus, conceptual engineering through de-biasing will include making choices about what kind of normative training an LLM should receive, especially with respect to different notions of bias. This offers a new perspective on what conceptual engineering involves and how it can be implemented. And our conceptual engineering approach also offers insight, to those engaged in LLM de-biasing, into the normative distinctions that are needed for that work.
Turning the Plurality of Chemistry into a Resource for Learning: A Core Competency of Chemistry Teachers
Authors: Nehring Andreas , Schanze Sascha
Published: February 2025

Chemistry is a science that not only examines substances at different levels of abstraction and involves a wide multitude of cognitive and experimental operations, but also used and uses a variety of concepts and representations referring to the same term. At the same time, many studies on the professional competencies of teachers underline the importance of content knowledge as a prerequisite for pedagogical content knowledge and instructional quality for example. While these studies use a quantitative logic of more or less chemistry knowledge, this paper argues that teachers do not only have to understand chemical concepts but also have to be able to manage conceptual plurality. This involves explaining phenomena based on different concepts, comparing their explanatory power and their limitations, and reflecting upon their sometimes different ontological and epistemological status. We propose conceptual clarifications for acid–base chemistry, redox chemistry, and atomic and bonding models to indicate how plurality manifests itself in chemistry in the first place. On this basis, we derive five approaches showing how managing conceptual plurality in chemistry helps to support learning chemistry. Teachers are more likely to make adequate curricular decisions, to anticipate students’ conceptions, to support transitions between concepts meaningfully, or to foster epistemic cognition as a part of learning chemistry. We discuss these approaches as explanations for findings in the field of teachers’ professional competencies.
Die Digitalisierung des Personalwesens als Transformationsbeschleuniger – Ein Einblick in die Praxis am Beispiel der Volkswagen Aktiengesellschaft
Authors: Dahm Johanna , Hofmann Martin , Kauffeld Simone
Published: February 2025

Dieser Artikel der Zeitschrift „Gruppe. Interaktion. Organisation.“ untersucht die Auswirkungen der Digitalisierung auf die Automobilindustrie, mit besonderem Fokus auf den Bereich Personal, Organisation und Bildung. Er beleuchtet und analysiert die HR-Digitalisierungsstrategie in der Volkswagen AG sowie die globale Umsetzung als Teil einer nicht mehr wegzudenkenden Dimension der Prozess- und Organisationsgestaltung. Die Einblicke in die digitalen Interventionen, die mit einer Effizienzsteigerung und Standardisierung von HR-Prozessen einhergehen, zeigen auch die kulturellen und regulatorischen Herausforderungen bei der Implementierung globaler Systeme im Personal- und Organisationsbereich. Die sich daraus abgeleiteten Schlüsselerkenntnisse setzen wichtige Impulse für zukünftige Digitalisierungsstrategien. Zudem eröffnen sie einen neuen Forschungshorizont im Bereich des Personal- und Organisationsmanagements.
Fertility Sparing Medical Management Options in Gynecologic Cancers
Authors: Kouri Ana , Darby Janelle P.
Published: February 2025

Opinion Statement

There is an increasing use of medical management for gynecologic cancers given the rise in neoadjuvant therapies, delayed childbearing, and use of assisted reproductive technology. Chemotherapy, albeit broadly used in most gynecologic cancers, lacks long term data with respect to its associated gonadotoxicity and potential adverse pregnancy outcomes. Immunotherapy and other targeted therapies that have demonstrated promising responses in other tumor types are increasingly being studied in gynecologic malignancies. These therapies may offer opportunities for enhanced treatment response in an effort to minimize more toxic, invasive, or surgical management approaches that could have significant negative implications on fertility. Given that some of these therapies do not represent the standard of care and currently only exist in the experimental setting, detailed counseling and careful selection of patients for fertility sparing treatment remains critical. It is reasonable for patients with early stage, low-risk endometrial cancers to attempt conservative management while establishing clear treatment objectives. Early involvement of fertility specialists is necessary in order to optimize these patients’ pregnancy goals. An emphasis on lifestyle changes and in particular weight loss should also be discussed with these patients. Neoadjuvant chemotherapy followed by fertility sparing surgery in cervix cancer patients with low-risk, small tumors shows promising results that suggest this can be a safe treatment option. Patients with advanced stage disease of any primary tumor or aggressive histology such as in many cases of ovarian cancer are not appropriate candidates for prioritization of fertility sparing treatment options. Ongoing and future studies will help to better identify appropriate patients and maximize medical management options in early-stage gynecologic cancers.
The effect of breastfeeding self-efficacy levels on maternal attachment: the mediation role of mothers’ traumatic childbirth perception
Authors: Kaynak Serap , Özçoban Filiz Aslantekin , Duran Songül
Published: February 2025

The perception of traumatic birth can negatively affect maternal and child health by influencing breastfeeding self-efficacy and maternal attachment. This study aimed to examine the mediating role of traumatic childbirth perception in the effect of breastfeeding self-efficacy on maternal attachment among mothers. A total of 195 mothers were included in this descriptive and cross-sectional research. The research data were collected by using the Descriptive Information Form, the Traumatic Childbirth Perception Scale, the Maternal Attachment Inventory, and the Breastfeeding Self-Efficacy Scale (Short Form). As a result of the research, it was determined that the mothers’ traumatic childbirth perception was at a moderate level, their maternal attachment scores were high and their breastfeeding self-efficacy scores were above average. Also, a positive correlation was identified between maternal attachment and breastfeeding self-efficacy. The research findings show that 48.7% of participant mothers had high-level or very high-level traumatic childbirth perceptions. Health professionals should support mothers about traumatic birth anxiety.
Evidence-Based Analysis of AI Chatbots in Oncology Patient Education: Implications for Trust, Perceived Realness, and Misinformation Management
Authors: Lawson McLean Aaron , Hristidis Vagelis
Published: February 2025

The rapid integration of AI-driven chatbots into oncology education represents both a transformative opportunity and a critical challenge. These systems, powered by advanced language models, can deliver personalized, real-time cancer information to patients, caregivers, and clinicians, bridging gaps in access and availability. However, their ability to convincingly mimic human-like conversation raises pressing concerns regarding misinformation, trust, and their overall effectiveness in digital health communication. This review examines the dual-edged role of AI chatbots, exploring their capacity to support patient education and alleviate clinical burdens, while highlighting the risks of lack of or inadequate algorithmic opacity (i.e., the inability to see the data and reasoning used to make a decision, which hinders appropriate future action), false information, and the ethical dilemmas posed by human-seeming AI entities. Strategies to mitigate these risks include robust oversight, transparent algorithmic development, and alignment with evidence-based oncology protocols. Ultimately, the responsible deployment of AI chatbots requires a commitment to safeguarding the core values of evidence-based practice, patient trust, and human-centered care.
Ionically crosslinked biohybrid gelatin-based hydrogels for 3D cell culture
Authors: Du Eric Y. , Duong H. T. Kim , Tolentino M. A. Kristine , Houng Jacinta L. , Suwannakot Panthipa , Tjandra Kristel C. , Nguyen Duyen H. T. , Tilley Richard D. , Justin Gooding J.
Published: February 2025

The transition from two-dimensional to three-dimensional cell cultures has transformed the understanding of cell physiology and cell–matrix interactions. Extracellular matrix (ECM) mimics tend to fall into either the natural or synthetic categories. Naturally occurring ECM mimics, such as collagen and gelatin, have superior bioactive properties but typically lack tuneability. Conversely, synthetic ECM mimics are highly defined but even with modifications, can lack the bioactivity of natural proteins. Therefore, to take advantage of the potential of both natural and synthetic ECM mimics, a biohybrid ionically crosslinked gelatin hydrogel was synthesised. This was achieved by utilising free amine groups along the gelatin backbone as the basis for a reversible addition − fragmentation chain-transfer (RAFT) reaction. The resulting polymers had tuneable stiffness and enhanced solubility compared to gelatin. The biohybrid gel also showed good biocompatibility, with MCF-7 cells forming larger spheroids when encapsulated within the biohybrid gel when compared to an unfunctionalized polyethylene-glycol (PEG) gel. Furthermore, due to the ionic crosslinking in the biohybrid gel, spheroids can be retrieved by digesting the matrix using 10 × phosphate-buffered saline (PBS). Retrieved cells were shown to be viable which allows for the potential of downstream analysis. Thus, this study highlights the potential of hybrid gelatin–PEG hydrogels for 3D cell culture.

Graphical abstract

The biohybrid gelatin (Gelatin-SPMA) is crosslinked with a positively charged polymer (PEG-MAETMA) to form a gel within seconds. MCF-7 cells survived encapsulation and formed spheroids over 7 days. 10x phosphate buffered saline (PBS) was then used to digest the hydrogel, allowing for the recovery of encapsulated spheroids.