bluuebunny/crossref_metadata_2025 huggingface dataset:
Advancements in Organ‐on‐a‐Chip Systems: Materials, Characterization, and Applications
Authors: Gunasekaran Balu Mahendran , Srinivasan Soorya , Ezhilan Madeshwari , Rajagopal Venkatachalam , Nesakumar Noel
Published: October 2024

Recent advancements in 3D tissue engineering and organ‐on‐a‐chip systems have revolutionized biomedical research by providing sophisticated platforms that mimic complex physiological environments. This review explores various techniques in 3D printing, including bioprinting materials, laser‐induced forward transfer, ink‐jet systems, and microextrusion methods, highlighting their roles in fabricating intricate tissue constructs. Physical and biochemical characterization methods for assessing these engineered tissues on microchips are discussed in detail, emphasizing their importance in accurately replicating physiological conditions. The review further delves into the development of multiple organ and single organ‐on‐a‐chip systems. It covers two‐organ, three‐organ, and four‐organ platforms, as well as individual systems such as pancreas‐on‐a‐chip, kidney‐on‐a‐chip, liver‐on‐a‐chip, lung‐on‐a‐chip, blood–brain barrier‐on‐a‐chip, heart‐on‐a‐chip, breast cancer‐on‐a‐chip, gut‐on‐a‐chip, and blood vessels‐on‐a‐chip. Each section addresses the unique challenges and advancements associated with these models, providing insights into their potential applications in drug testing, disease modelling, and personalized medicine. In conclusion, the article discusses current challenges and offers perspectives on future directions in 3D tissue engineering and organ‐on‐a‐chip technology, highlighting the transformative impact of these systems on biomedical research and healthcare.
Hydrazine Oxidation in Aqueous Solutions II: N4H4 Decomposition
Authors: Breza Martin , Gatial Anton
Published: October 2024

The reaction mechanism for the N2H4 homogeneous oxidation in aqueous solutions is more complex than its heterogeneous electrochemical oxidation on the electrode surfaces. Homogenous oxidation of a mixture of non‐labeled (14N2H4) and 15N‐labeled (15N2H4) hydrazine in aqueous solutions produces 14N15N, indicating the intermediate existence of N4H6 or N4H4 intermediates with subsequent hydrogen transfers and splitting lateral N─N bonds. To explain the key part of the hydrazine oxidation reaction, the structures, thermodynamics, and electron characteristics of N4H4 in aqueous solution are investigated. Unlike N4H6, we have not found any spontaneous splitting of the bond between the lateral nitrogens in N4H4. The most probable products of N4H4 disproportionation are H2N─NH2 and N2, which are obtained by splitting the bond between the central nitrogen atoms, and so only 15N2 and 14N2 molecules are formed. Additionally, the formation of H3N─NH and N2 products is also preferred to structures without N─N fissions. The formation of H2N═N and HN═NH is energetically less advantageous. Cyclo‐N4H4 structures are stable, without any N─N fissions, but their energies indicate their vanishing abundance in aqueous solution, so their involvement in hydrazine oxidation is highly improbable. Unlike N4H6, the oxidation of hydrazine to 14N15N molecules cannot be explained by N4H4 intermediates.
Active Quantum Biomaterials‐Enhanced Microrobots for Food Safety
Authors: Jyoti  , Castillo Alberto‐Rodríguez , Jurado‐Sánchez Beatriz , Pumera Martin , Escarpa Alberto
Published: October 2024

Timely disruptive tools for the detection of pathogens in foods are needed to face global health and economic challenges. Herein, the utilization of quantum biomaterials‐enhanced microrobots (QBEMRs) as autonomous mobile sensors designed for the precise detection of endotoxins originating from Salmonella enterica (S. enterica) as an indicator species for food‐borne contamination globally is presented. A fluorescent molecule‐labeled affinity peptide functions as a specific probe, is quenched upon binding to the surface of QBEMRs. Owing to its selective affinity for endotoxin, in the presence of S. enterica the fluorescence is restored and easy to observe and quantifies optical color change to indicate the presence of Salmonella. The devised approach is designed to achieve highly sensitive detection of the S. enterica serovar Typhimurium endotoxin with exquisite selectivity through the utilization of QBEMRs. Notably, no fluorescence signal is observed in the presence of endotoxins bearing similar structural characteristics, highlighting the selectivity of the approach during food sample analysis. Technically, the strategy is implemented in microplate readers to extend microrobots‐based approaches to the routine laboratory. This new platform can provide fast and anticipated results in food safety.
Visible Light‐Sensitive Sustainable Quantum Dot Crystals of Co/Mg Doped Natural Hydroxyapatite Possessing Antimicrobial Activity and Biocompatibility
Authors: Maleki‐Ghaleh Hossein , Kamiński Bartosz , Moradpur‐Tari Ehsan , Raza Sada , Khanmohammadi Mehdi , Zbonikowski Rafał , Shakeri Mohammad Sadegh , Siadati M. Hossein , Akbari‐Fakhrabadi Ali , Paczesny Jan
Published: October 2024

Cutting‐edge research in advanced materials is increasingly turning toward the development of novel multifunctional nanomaterials for use in high‐tech applications. This research uses the solid‐state method as a solvent‐free technique to create multifunctional quantum dot (QD) hydroxyapatite (HA) crystals from bovine bone waste. By incorporating cobalt (Co) and magnesium (Mg) into the HA structure, the crystallinity of the hexagonal HA nanoparticles (99.7%), showing QD crystals is enhanced. Oxygen vacancies on the surfaces of the HA nanoparticles contributed to their bandgap falling within the visible light range. In addition, the dopants substituted calcium in the HA crystal structure and generated a divalent oxidation state, shifting the bandgap of natural HA toward red wavelengths (3.26 to 1.94 eV). Moreover, the incorporation of Co led to magnetization within the HA structure through spin polarization. Additionally, the doped QD crystals of HA nanoparticles showed significant antimicrobial activity against Escherichia coli, Staphylococcus aureus, and bacteriophages MS2, particularly under visible light exposure. In short, the Co/Mg co‐doped HA nanoparticles exhibited ferromagnetic properties, sensitivity to visible light, biocompatibility, and considerable antimicrobial effects, establishing their potential as sustainable multifunctional materials for biomedical applications, especially in anti‐infection treatments.
Impact of a Dual Treatment on Resistant Starch Level and Techno‐Functional Properties of Pea and Faba Bean Flours
Authors: Arroqui Cristina , Noriega María José , Ibañez Francisco C. , Milagro Fermín I. , Beriain María José , Virseda Paloma
Published: October 2024

Starch‐rich pulses’ flours, which are rich in fiber and resistant starch (RS), can be an interesting gluten‐free ingredient for the development of novel healthy foods. The study aims to increase the RS content of protein‐reduced fraction of legume flours (pea [P] and faba bean [FB]) by the application of thermal (autoclaving‐cooling) and dual (thermal plus high‐hydrostatic pressure) treatments. Both treatments enhance the RS contents, reaching 6.8% in P flour after dual treatment. The techno‐functional properties are dependent both on the type of flour and the treatment applied. A loss of water solubility (WS) and an increase in water binding capacity are observed. The WS index and emulsion activity remained unchanged or slightly changed, but emulsion stability decreased significantly. The viscosity of the samples is modified according mainly to the flour type. P flour is more affected by the dual treatment than FB flour, which is evidenced by the greater changes shown in RS, WS, and pasting properties.
Boronolipids
Authors: Dembitsky Valery M.
Published: October 2024

The interactions between boron and polyols significantly impact the functioning of bioactive metabolites, algae, plant growth, and quorum determination in certain bacterial species. This wide array of boron‐inclusive compounds aligns with the expectation as boron ranks among the top ten most plentiful elements in seawater. Moreover, carbohydrates, largely comprising polyols, represent the most abundant class of biomass on earth. Lately, the complexes formed between boron and sugars have garnered interest. They have been employed to construct synthetic carbohydrate receptors. These complexes are typified by covalent interactions, enabling their conversion into aqueous solutions. The physical and chemical traits of boron and its established compounds suggest the feasibility of generating boron‐based lipids and glycolipids. Building upon the chemical and mathematical models that demonstrate the formation of protomembranes and biological membranes from complex lipids using low molecular weight polyols as their framework, it appears that the abiotic synthesis of boronolipids follows a parallel route. This review offers a succinct overview of naturally occurring boron compounds and delves into the possible existence of boronolipids within the makeup of protomembranes and biological membranes.
QuAK: Quantitative Automata Kit
Authors: Chalupa Marek , Henzinger Thomas A. , Mazzocchi Nicolas , Saraç N. Ege
Published: October 2024

System behaviors are traditionally evaluated through binary classifications of correctness, which do not suffice for properties involving quantitative aspects of systems and executions. Quantitative automata offer a more nuanced approach, mapping each execution to a real number by incorporating weighted transitions and value functions generalizing acceptance conditions. In this paper, we introduce QuAK, the first tool designed to automate the analysis of quantitative automata. QuAK currently supports a variety of quantitative automaton types, including $${\textsf{Inf}}$$
Inf
, $${\textsf{Sup}}$$
Sup
, $${\textsf{LimInf}}$$
LimInf
, $${\textsf{LimSup}}$$
LimSup
, $${\textsf{LimInfAvg}}$$
LimInfAvg
, and $${\textsf{LimSupAvg}}$$
LimSupAvg
automata, and implements decision procedures for problems such as emptiness, universality, inclusion, equivalence, as well as for checking whether an automaton is safe, live, or constant. Additionally, QuAK is able to compute extremal values when possible, construct safety-liveness decompositions, and monitor system behaviors. We demonstrate the effectiveness of QuAK through experiments focusing on the inclusion, constant-function check, and monitoring problems.
Philosophy for Environmental Policy and Law
Authors: Parasain Mohan
Published: October 2024

Philosophy is understood as an art of “suspension of judgement” and also as “a quest for new metaphor and new language”. With both the above spirits in mind, i.e., openness to new perspectives and a quest for new language in environmental humanities, this chapter argues for a shift in perspective from the anthropocentricity of theories in environmental discourse to give way to a wider approach. The first part evaluates the efficacy of moral theories as dialogue partners for environmental policies and laws, analyses Leopold's criticism of the anthropocentric presumptions of moral theories and highlights the limitations of the Land ethics of Leopold. The second part focuses on the Indian Constitutional provisions for the protection of the environment and the environmental jurisprudence developed in various judicial pronouncements from the right-to-life perspective. Our sensibility seems to be still enduring the presumption of the biotic/abiotic community as property in our policies and laws. Therefore, the third part reflects on the evolutionary possibility of philosophical reflections on the environment from the anthropocentricity of moral theories to Dharmic understanding through the Land ethics of Leopold. In Dharmic tradition, our theories are not only grounded in practice but the integrity, stability and beauty of the biotic community and reverence for it is considered, rather prescribed as important pursuits for human beings.
“When the Black Half of the Kunni Seed Whitens”: Plant-Lore and the Plantationocene in Ambikasuthan Mangad’s Swarga
Authors: Venugopal Varna , Rangarajan Swarnalatha
Published: October 2024

In 2009, Ambikasuthan Mangad published Enmakaje, a novel based on the experiences of the inhabitants of Enmakaje, a village in Kerala, who were adversely affected by the aerial spraying of the pesticide Endosulfan, by the Plantation Corporation of Kerala, the state's largest public sector plantation company. The novel, translated into English by J. Devika as Swarga in 2017, has since then established itself as a narrative of toxicity, offering “transnational visibility and audibility” (Nixon 37) to those victimized by the slow violence of multigenerational toxic exposure. Even though state-owned cashew plantations constitute a significant portion of the novel's toxic-scape, Swarga has rarely been regarded as a ‘plantation narrative’. This chapter will analyze how the novel responds to the ‘Plantationocene’ by mobilizing a new form of pastoral, namely the ‘mythic pastoral’, casting Swarga as an ‘earthly paradise’ which has now fallen into decadence. The idyllic charm of this pastoral past is placed in opposition to the bleak, anti-pastoral vision of the ‘lifeless’ plantations inhabited by poisoned plants. The chapter looks at how arboreal tropes and botanical imagery are interwoven into the narrative to construe the mythic pastoral and the anti-pastoral. In doing so, we recontextualize Swarga as an exemplar of contemporary plantation fiction that situates its environmental politics at the intersections of social and ecological justice struggles in post-colonial societies.
Discrete-Time Hybrid Control Processes with Unbounded Costs
Authors: Jasso-Fuentes Héctor , Salgado-Suárez Gladys D.
Published: October 2024

This paper extends the results provided in Jasso-Fuentes et al. (Appl Math Optim 81(2):409–441, 2020b) and Jasso-Fuentes et al. (Pure Appl Funct Anal 9(3):675–704, 2024) regarding the study of discrete-time hybrid stochastic models with general spaces and total discounted payoffs. This extension incorporates the handling of negative and/or unbounded costs per stage. In particular, it encompasses interesting applications, such as scenarios where the controller optimizes net costs, social welfare costs, or distances between points. These situations arise when assumptions of both non-negativeness and boundedness on the cost per stage do not apply. Our proposal relies on Lyapunov-like conditions, enabling, among other aspects, the finiteness of the value function and the existence of solutions to the associated dynamic programming equation. This equation is crucial for deriving optimal control policies. To illustrate our theory, we include an example in inventory-manufacturing management, highlighting its evident hybrid nature.
Perspectives of aminoacylases in biocatalytic synthesis of N-acyl-amino acids surfactants
Authors: Haeger Gerrit , Wirges Jessika , Bongaerts Johannes , Schörken Ulrich , Siegert Petra
Published: October 2024

Many industrial processes are performed using harmful chemicals. The current technical synthesis ofN-acyl-amino acids relies on acyl chlorides, which are typically obtained from phosgene chemistry. A greener alternative is the application of whole cells or enzymes to carry out synthesis in an environmentally friendly manner. Aminoacylases belong to the hydrolase family and the resolution of racemic mixtures ofN-acetyl-amino acids is a well-known industrial process. Several new enzymes accepting long-chain fatty acids as substrates were discovered in recent years. This article reviews the synthetic potential of aminoacylases to produce biobasedN-acyl-amino acid surfactants. The focus lays on a survey of the different types of aminoacylases available for synthesis and their reaction products. The enzymes are categorized according to their protein family classification and their biochemical characteristics including substrate spectra, reaction optima and process stability, both in hydrolysis and under process conditions suitable for synthesis. Finally, the benefits and future challenges of enzymaticN-acyl-amino acid synthesis with aminoacylases will be discussed.

Key points

• Enzymatic synthesis of N-acyl-amino acids, biobased surfactants by aminoacylases.
Prognostic utility of mid-regional pro-adrenomedullin and growth differentiation factor 15 in patients undergoing transfemoral transcatheter aortic valve implantation
Authors: Piayda Kerstin , Keranov Stanislav , Schulz Luisa , Arsalan Mani , Liebetrau Christoph , Kim Won-Keun , Hofmann Felsix J. , Bauer Pascal , Voss Sandra , Troidl Christian , Sossalla Samuel T. , Hamm Christian W. , Nef Holger M. , Dörr Oliver
Published: October 2024

Background

Risk prediction in patients with severe, symptomatic aortic stenosis (AS) undergoing transcatheter aortic valve implantation (TAVI) remains an unsolved issue. In addition to classical risk scoring systems, novel circulating biomarkers like mid-regional pro-adrenomedullin (MR-proADM) and growth differentiation factor 15 (GDF-15) may be of value in assessing risk.

Methods

Consecutive patients undergoing elective transfemoral TAVI were included in this prospective observational study. Baseline information, imaging findings, blood samples, and clinical outcomes were collected. Blood levels of the classical biomarkers interleukin-6 (IL-6) and high-sensitivity C-reactive peptide (hsCRP) and of the novel biomarkers MR-proADM and GDF-15 were measured and their predictive utility for mortality assessed.

Results

The study cohort consisted of 92 patients undergoing TAVI. The median age was 80.7 years [IQR 77.2;83.3], and 48 (52.2%) were male. Analysis of the area under the curve (AUC) of the receiver-operating characteristics showed that the hsCRP levels discriminated poorly (AUC 0.66, 95% CI [0.52;0.8], p = 0.027), whereas all other biomarkers reached a higher level of discrimination (IL-6: AUC 0.76, 95% CI [0.66;0.86], p < 0.001; MR-proADM: AUC 0.73, 95% CI [0.61;0.85], p = 0.002; GDF-15: AUC 0.73, 95% CI [0.61;0.85], p = 0.002). Kaplan–Meier analysis in conjunction with Youden J-statistics yielded the optimal cutoff points for each biomarker to predict survival: IL-6 4.65 pg/mL, hsCRP 12.9 mg/L, MR-proADM 1.02 nmol/L, and GDF-15 2400.1 pg/mL.

Conclusion

Novel circulating biomarkers like MR-proADM and GDF-15 may provide additional value in predicting survival after TAVI.
Silexan in anxiety, depression, and related disorders: pharmacological background and clinical data
Authors: Kasper Siegfried , Eckert Anne
Published: October 2024

We present a narrative review of clinical trials investigating the anxiolytic and antidepressant effects of silexan, an active substance derived from lavender oil and summarize nonclinical findings from pharmacological studies supporting its therapeutic use. Six studies investigated the efficacy of the lavender oil in patients with subthreshold and generalized anxiety disorders as well as in mixed anxiety and depressive disorder (MADD). Furthermore, we present data indicating that silexan may influence sleep quality as well as anxiety or depressive disorders in individuals with post-COVID-19. Silexan taken orally at a daily dose of 80 mg for 10 weeks was significantly superior to placebo in reducing psychic and somatic symptoms of anxiety and was as effective as 0.5 mg/d lorazepam and 20 mg/d paroxetine. In patients with mild or moderate major depression, silexan was superior to placebo and comparably effective to 50 mg/d sertraline. Significant antidepressant effects were also observed in MADD and depression co-morbid with anxiety. The herbal product had a beneficial effect on activities of daily living and health-related quality of life. Adverse events associated with silexan in clinical trials were limited to eructation and mild, transient gastrointestinal complaints. The herbal product was not associated with drug interactions, sedation, sleep disturbance, dependence and abuse potential, sexual dysfunction, weight gain or withdrawal symptoms. Silexan was therefore safe and effective in subthreshold and syndromal anxiety disorders and in major depression.
Mesh topology-based spurious pressure stabilization in 3D finite elasticity using Voronoi tessellations
Authors: Sauren Bjorn , Klinkel Sven
Published: October 2024

In this paper, we present a mesh topology-based stabilization approach to suppress spurious pressure modes in 3D nearly-incompressible finite elasticity. The focus lies on a mixed formulation with lowest-order approximation for the displacement and pressure fields. Motivated by the fact that the popular H1/P0 element does not fulfill the inf-sup condition, all possible local spurious pressure modes are derived on a patch of elements. The nullspace method is used to determine all spurious pressure solutions. From this, the topological requirements of the finite element mesh are established. We conclude that no more than four elements are allowed to intersect in the same vertex to overcome local checkerboarding. To fulfill this requirement, we employ non-degenerate 3D Voronoi diagrams with several different site distributions. These result in random, centroidal, and honeycomb Voronoi meshes. The resulting convex polyhedral elements are discretized by a polyhedral mixed finite element based on the lowest possible interpolation pair. The numerical examples illustrate that spurious pressure modes do not occur for any degree of mesh refinement as long as the topological mesh requirements are met. Furthermore, it is shown that the numerical inf-sup test is passed. By violating the topological requirements, it is shown that a stable pressure field cannot be guaranteed and the checkerboard phenomenon is provoked.
Machine Learning Approach for Rock Mass Classification with Imbalanced Database of TBM Tunnelling in Himalayan Geology
Authors: Katuwal Tek Bahadur , Panthi Krishna Kanta , Basnet Chhatra Bahadur
Published: October 2024

The geological condition of the Himalayan region is very complex and challenging. So far, empirical and analytical approaches for rock mass characterization have been a common practice in the Himalayas. Due to the limitations of input parameters and governing equations in design practices, rock mass characterization in tunnel boring machine (TBM) excavated tunnels is crucial. This research introduces robust machine learning (ML) approaches to predict rock mass quality conditions in complex geological environments, leveraging a large database of TBM parameters and rock mass rating (RMR) values. To do so, a total of 6879 stable phase TBM cycle data were collected from 12 km long tunnel in Nepal. The pre-processed parameters were randomly split into a training set (80%) and a testing set (20%). Seven individual classifiers consisting of logistic regression (LR), support vector machine (SVM), decision tree (DT), random forest (RF), k-nearest neighbor (KNN), extreme gradient boosting (XGBoost), and bagging, and stacking ensemble classifier were exploited with optimal hyperparameters. The comprehensive assessment carried out has shown that the ensemble classifier gave highest overall accuracy as compared to other individual classifiers. More importantly, the synthetic minority over-sampling technique (SMOTE) performs better to handle the imbalanced database, while the RF and stacking classifier demonstrated the best prediction performance with accuracy of 92%. Moreover, for the minority rock mass class, the RF shows better performance compared to stacking classifier. The authors emphasize that the effective application of ML-based data-driven approach shows substantial potential for rock mass characterization in TBM tunnelling.
Green Financing, Energy Transformation, and the Moderating Effect of Digital Economy in Developing Countries
Authors: Nepal Rabindra , Liu Yang , Dong Kangyin , Jamasb Tooraj
Published: October 2024

The energy sector in many developing nations faces the difficulty of insufficient financing throughout the low-carbon transition, highlighting the importance of international green financing in alleviating financial constraints. The advancement of digital technology could facilitate green financing for energy transition in the digital economy, but this statement lacks empirical evidence. The primary objective of this research is to investigate the impact of international green financing on low-carbon energy transformation in developing nations. Additionally, we investigate the moderating role of digital economy between the two. Our findings validate the favorable impact of international green financing on low-carbon energy transformation, and this impact is particularly evident for hydro and wind energy consumption. We show that this beneficial effect is greater for low-income countries or regions with high levels of energy transition. We also provide evidence of the positive moderation effects of digital economy and find that its effects are still present in the transition to hydro and wind energy. This research helps to broaden green financing channels for the energy sector in developing countries, especially from the perspective of digital economy.
Numerical investigation of the late-time tails of the solutions of the Fackerell–Ipser equation
Authors: Rácz István , Tóth Gábor Zsolt
Published: October 2024

The late-time behaviour of the solutions of the Fackerell–Ipser equation (which is a wave equation for the spin-zero component of the electromagnetic field strength tensor) on the closure of the domain of outer communication of sub-extremal Kerr spacetime is studied numerically. Within the Kerr family, the case of Schwarzschild background is also considered. Horizon-penetrating compactified hyperboloidal coordinates are used, which allow the behaviour of the solutions to be observed at the event horizon and at future null infinity as well. For the initial data, pure multipole configurations that have compact support and are either stationary or non-stationary are taken. It is found that with such initial data the solutions of the Fackerell–Ipser equation converge at late times either to a known static solution (up to a constant factor) or to zero. As the limit is approached, the solutions exhibit a quasinormal ringdown and finally a power-law decay. The exponents characterizing the power-law decay of the spherical harmonic components of the field variable are extracted from the numerical data for various values of the parameters of the initial data, and based on the results a proposal for a Price’s law relevant to the Fackerell–Ipser equation is made. Certain conserved energy and angular momentum currents are used to verify the numerical implementation of the underlying mathematical model. In the construction of these currents a discrete symmetry of the Fackerell–Ipser equation, which is the product of an equatorial reflection and a complex conjugation, is also taken into account.
Trauma-informed Financial Empowerment Programming Associated with Improved Financial Well-being
Authors: Weida Emily B. , Carroll-Scott Amy , Le-Scherban Felice , Bloom Sandra , Chilton Mariana
Published: October 2024

Financial well-being and overall health are significantly linked, especially among those in poverty who have been exposed to violence and suffer from unaddressed trauma. Yet existing public assistance programs fail to address the presence or impact of trauma and adversity. Built specifically for families living in poverty who experience adversity, the Building Wealth and Health Network (the Network) provides a space for families to heal from the effects of trauma while also building social networks and economic security. The sample for this study was primarily Black (91%) women (92%) in Philadelphia with at least one child. A repeated measures linear regression model was performed via a Difference-in-Differences approach to test differences in financial well-being scores between two groups (full participation vs. low/no participation) at two time points (baseline vs 3 months, and baseline vs 6 months). We use this program as a field study to better understand the financial well-being of program participants who took part in fewer or more program sessions. Those who participated in more sessions reported greater increases in two measures of financial well-being at three months and six months post baseline, when compared to those with low or no participation.
The Impact of Caregiving on Informal Caregivers of People with Dementia: Family Functioning, Burden, and Burnout
Authors: Brites Rute , Brandão Tânia , Nunes Odete , Hipólito João , Pires Catarina Tomé
Published: October 2024

Caregiving is a complex occupation, with a significant impact for informal caregivers (IC). Stress-process models propose a framework that considers that this impact depends on primary and secondary stressors, but also on the IC situation appraisal. This work aimed to verify: whether being, or not, an IC of an individual with dementia influenced the relationship between family functioning and burnout; the association between neuropsychiatric symptoms of the individual with dementia and IC burnout and whether the IC burden and perceived family functioning had a mediating role in such relationship. This cross-sectional study investigated differences in family functioning and its association with burnout between IC and non-IC. For IC specifically, the study examined a mediation model to explore the possibility of neuropsychiatric symptoms indirectly affecting IC burnout through the impact on family functioning and burden. Measures included the Copenhagen Burnout Inventory, the McMaster Family Assessment Device, the Neuropsychiatric Inventory, and the Zarit Burden Interview. Results showed an association between poorer family function and high burnout, specifically in IC. They also showed that burden mediated the relationship between neuropsychiatric symptoms and burnout. The findings offer a significant contribution to the growing knowledge about the relationship between stressors associated with informal caregiving in dementia context, such as neuropsychiatric symptoms and its outcomes, like burnout.
Scheduling of e-commerce packaging machines: blocking machines and their impact on the performance–waste tradeoff
Authors: Briskorn Dirk , Boysen Nils , Zey Lennart
Published: October 2024

To streamline their fulfillment processes, many e-commerce retailers today use automated packaging machines for their outbound parcels. An important performance–waste tradeoff is associated with these machines: To reduce packaging waste when handling different sized goods, packaging machines should be able to handle different carton sizes. However, more carton sizes lead to a more involved scheduling process, so that the throughput performance deteriorates (and vice versa). To investigate this tradeoff, this paper develops scheduling procedures for a specific type of packaging machine, called blocking machines. These packaging machines provide multiple back-to-back packaging devices, each continuously processing a dedicated carton size, but blocking each other whenever incoming goods are not properly ordered according to carton sizes on the infeed conveyor. To reduce the resulting throughput loss, we derive various scheduling problems for optimizing the inflow of goods, provide a thorough analysis of the computational complexity, and derive an exact dynamic programming approach that is polynomial in the number of orders to be packed. This allows us to solve even large real-world instances to proven optimality with which we can analyze the performance–waste tradeoff of blocking machines.
Intolerance of Uncertainty as a Central Influence on Social Media Use: A School-Based Program for Adolescents
Authors: Einstein Danielle A. , McMaugh Anne , Rapee Ronald M. , McEvoy Peter , Fraser Madeleine I. , Abbott Maree , Mansell Warren , Karin Eyal
Published: October 2024

This study evaluated a classroom program to address Intolerance of uncertainty (IU) in secondary school students in Australia. IU is a transdiagnostic vulnerability factor for a range of psychological difficulties. A universal classroom program aimed to increase student understanding of feelings of uncertainty and explored socioemotional factors that could influence behaviors when facing uncertainty. Classroom teachers in two high schools were trained to deliver an 18-lesson program under naturalistic classroom conditions. Relative to the control group, the intervention lowered IU at post-test, but not at a later follow-up. The only socioemotional outcome measure to demonstrate a concurrent change was social media use. Limitations of the study were associated with the naturalistic classroom intervention, including the high level of attrition. Future studies may need to address broader factors in the students’ context that could influence intolerance of uncertainty.
Deep learning-based segmentation of abdominal aortic aneurysms and intraluminal thrombus in 3D ultrasound images
Authors: Nievergeld Arjet , Çetinkaya Bünyamin , Maas Esther , van Sambeek Marc , Lopata Richard , Awasthi Navchetan
Published: October 2024

Ultrasound (US)-based patient-specific rupture risk analysis of abdominal aortic aneurysms (AAAs) has shown promising results. Input for these models is the patient-specific geometry of the AAA. However, segmentation of the intraluminal thrombus (ILT) remains challenging in US images due to the low ILT-blood contrast. This study aims to improve AAA and ILT segmentation in time-resolved three-dimensional (3D + t) US images using a deep learning approach. In this study a “no new net” (nnU-Net) model was trained on 3D + t US data using either US-based or (co-registered) computed tomography (CT)-based annotations. The optimal training strategy for this low-contrast data was determined for a limited dataset. The merit of augmentation was investigated, as well as the inclusion of low-contrast areas. Segmentation results were validated with CT-based geometries as the ground truth. The model trained on CT-based masks showed the best performance in terms of DICE index, Hausdorff distance, and diameter differences, covering a larger part of the AAA. With a higher accuracy and less manual input the model outperforms conventional methods, with a mean Hausdorff distance of 4.4 mm for the vessel and 7.8 mm for the lumen. However, visibility of the lumen-ILT interface remains the limiting factor, necessitating improvements in image acquisition to ensure broader patient inclusion and enable rupture risk assessment of AAAs in the future.

Graphical abstract
Demographic, Clinical, Psychosocial, and Behavioral Predictors of Continuous Glucose Monitor Use in Adults with Type 2 Diabetes
Authors: Morrow Emily L. , Spieker Andrew J. , Greevy Robert A. , Roddy McKenzie K. , Mayberry Lindsay S.
Published: October 2024

Background

Continuous glucose monitor (CGM) use is increasing rapidly among people with type 2 diabetes, although little is known about predictors of CGM use beyond clinical and demographic information available in electronic medical records. Behavioral and psychosocial characteristics may also predict CGM use.

Objective

We examined clinical, psychosocial, and behavioral characteristics that may predict CGM use in adults with type 2 diabetes.

Design

This longitudinal observational study comprised a secondary analysis of data collected in a larger trial. Enrollment included HbA1c tests and surveys assessing demographic, clinical, psychosocial, and behavioral characteristics. We queried participants regarding their CGM use during the study on their final self-report surveys, 15 months post-enrollment.

Participants

Participants were 245 community-dwelling adults with type 2 diabetes recruited from primary care.

Approach

We used logistic regression to predict CGM use during the 15-month trial period from baseline characteristics.

Key Results

Around one-third of participants (37.1%; 91/245) started CGM. Predictors of starting CGM in bivariate models included younger age, higher socioeconomic status, insulin use, higher HbA1c, and more diabetes distress. When including all potential predictors in a single multivariable model, only younger age (aOR = 0.95, p = 0.001), insulin use (aOR = 2.33, p = 0.006), and higher socioeconomic status (aOR = 0.44, p = 0.037) were significant predictors. Despite the association between higher HbA1c and CGM use, neither diabetes self-care behaviors nor diabetes self-efficacy significantly predicted CGM use. Of participants who tried a CGM, 14.3% (13/91) had stopped, with cost being the most-cited reason.

Conclusions

Even when including behavioral and psychological characteristics, younger age, using insulin, and higher socioeconomic status remain key predictors of CGM use. These findings emphasize the importance of access and affordability for people who may benefit from CGM. Providers should not bias their introduction of CGM towards those with (perceived or actual) optimal or sub-optimal self-care behaviors.
Evaluation of the Technological Performance of Soft Wheat Flours for Fresh-Pasta Production as Affected by Industrial Refining Degree
Authors: Iacovino S. , Garzon R. , Rosell C. M. , Marconi E. , Albors A. , Martín-Esparza M. E.
Published: October 2024

Nowadays, whole grain and less refined flours deriving from higher extraction rate milling processes have received much attention due to the presence of the external parts of the grain constituting the bran, with well-known health benefits. The use of these flours can represent a rational option for the valorization of native bran with minimal by-product generation while improving the nutritional and functional profile of the end products. This work aims to evaluate the techno-functional characteristics of commercial soft wheat flours with different refining degrees (proximate composition, functional, rheological, and starch-related properties) and their relation to the produced fresh-pasta quality (cooking behavior, mechanical and optical properties, and sensory assessment). Specifically, water holding capacity, fat absorption capacity, and swelling ability of flours gradually decreased with the refining degree (up to 25%, 16%, and 36%, respectively). Regarding the starch properties, the overall gelatinization process resulted to be negatively influenced by higher extraction rates, leading to a lower consistency of the whole grain starch gels (~17% in the maximum force during heating and ~12.39% peak viscosity). Cooked pasta was darker and redder when increasing the extraction rate. In addition, whole grain-based pasta had 42% higher cooking loss, and it was 86% harder and 101% firmer, leading to the production of a less elastic fresh-pasta with lower swelling ability. However, a good quality end product with naturally high nutritional value can be produced with flours with low refining degree. Results are useful to assess the best productive destination of flours basing on their technological properties.
Exploring circulation dynamics in Han Dynasty China: insights from isotopic analysis of lead glazed pottery
Authors: Wang Chen , De Ceuster Sarah , Eremin Katherine , Laursen Sarah , Degryse Patrick
Published: October 2024

This study investigates lead provenance and circulation patterns in Han Dynasty (202BC-220AD) China through the analysis of lead glazed pottery. Four objects were studied using a combination of typological study, elemental chemistry and lead isotope ratio analysis. The results for each object were compared with databases of ‘lead mining districts’ (lead deposits) and ‘lead usage districts’ (lead-containing artifacts unearthed in different spatial and temporal ranges) to assess the lead sources used for each sample and offers a spatial-temporal range of the use of these lead resources. Three distinct groups of lead and their possible circulating spatial-temporal scales are identified across six samples in this study. A possible change in lead supply networks between the Western Han Dynasty (202BC-9AD) and the Eastern Han Dynasty (25AD-220AD) is proposed. This study also highlights the probable changes in the movement of lead resources from the Western Han Dynasty to the Tang Dynasty (618AD-690AD), suggesting improvements in long-distance transport capabilities, and the development of economic divisions and exchange connections in ancient Chinese society. Our findings contribute to a deeper understanding of the economic and political dynamics during the Han Dynasty and emphasize the significance of lead isotope analysis of glazed pottery in exploring resource movement.
Integrative analysis of bulk and single-cell transcriptomic data reveals novel insights into lipid metabolism and prognostic factors in hepatocellular carcinoma
Authors: Qi Feiyu , Zha Guiming , Zhang Yanfang , Liu Sihua , Yang Yuhang , Sun Wanliang , Wang Dongdong , Liu Zhong , Lu Zheng , Zhang Dengyong
Published: October 2024

Hepatocellular carcinoma (HCC) is associated with high mortality rate. This study investigated the status of lipid metabolism-related genes in HCC. Bulk transcriptomic and single-cell sequencing data for HCC were retrieved from public databases. The single-cell sequencing data was subjected to dimensionality reduction, which facilitated the annotation of distinct cell subpopulations and marker gene expression analysis within each subpopulation. Genes associated with lipid metabolism in liver cells were identified, and a machine-learning model was developed using the bulk transcriptomic data randomly partitioned into training and validation sets. The efficacy of the model was validated using these two sets. A multifactorial Cox analysis on the model genes combined with clinical features, led to the identification of age, HMGCS2, HNRNPU, and RAN as independent prognostic factors, which were included in the nomogram model construction and validation. A weighted gene co-expression analysis of all genes of the bulk transcriptome samples revealed the correlation between gene modules and risk score. Genes with cor > 0.4 in the highest-expressing module were selected for Gene Ontology and Kyoto Encyclopedia of Genes and Genomes functional enrichment analysis. Immune-related analysis was conducted based on seven algorithms for immune cell infiltration prediction. For the genes in the nomogram model, the expression in clinical pathological factors was also analyzed. The drug sensitivity analysis offered a reference for the selection of targeting drugs. This investigation provides novel insights and a theoretical basis for the prognosis, treatment, and pharmaceutical advancements for patients diagnosed with HCC.
Enhancing bevacizumab efficacy in a colorectal tumor mice model using dextran-coated albumin nanoparticles
Authors: Pangua Cristina , Espuelas Socorro , Simón Jon Ander , Álvarez Samuel , Martínez-Ohárriz Cristina , Collantes María , Peñuelas Iván , Calvo Alfonso , Irache Juan M.
Published: October 2024

Bevacizumab is a monoclonal antibody (mAb) that prevents the growth of new blood vessels and is currently employed in the treatment of colorectal cancer (CRC). However, like other mAb, bevacizumab shows a limited penetration in the tumors, hampering their effectiveness and inducing adverse reactions. The aim of this work was to design and evaluate albumin-based nanoparticles, coated with dextran, as carriers for bevacizumab in order to promote its accumulation in the tumor and, thus, improve its antiangiogenic activity. These nanoparticles (B-NP-DEX50) displayed a mean size of about 250 nm and a payload of about 110 µg/mg. In a CRC mice model, these nanoparticles significantly reduced tumor growth and increased tumor doubling time, tumor necrosis and apoptosis more effectively than free bevacizumab. At the end of study, bevacizumab plasma levels were higher in the free drug group, while tumor levels were higher in the B-NP-DEX50 group (2.5-time higher). In line with this, the biodistribution study revealed that nanoparticles accumulated in the tumor core, potentially improving therapeutic efficacy while reducing systemic exposure. In summary, B-NP-DEX can be an adequate alternative to improve the therapeutic efficiency of biologically active molecules, offering a more specific biodistribution to the site of action.

Graphical abstract
Lipid and brain volumetric measures in multiple sclerosis patients: findings from a large observational study
Authors: Lorincz Balazs , Vrablik Michal , Murali Ramanathan , Havrdova Eva Kubala , Horakova Dana , Krasensky Jan , Vaneckova Manuela , Uher Tomas
Published: October 2024

Objectives

This study aimed to investigate relationships between cholesterol profile, brain volumetric MRI, and clinical measures in a large observational cohort of multiple sclerosis (MS) patients.

Materials and methods

We included 1.505 patients with 4.966 time points including complete lipid, clinical, and imaging data. The time among lipid, brain MRI and clinical measures was under 90 days. Cross-sectional statistical analysis at baseline was performed using an adjusted linear regression and analysis of longitudinal lipid and MRI measures data was performed using adjusted linear mixed models.

Results

We found associations between higher high-density lipoprotein cholesterol (HDL-C) and lower brain parenchymal fraction (BPF) at cross-sectional analysis at baseline (B = −0.43, CI 95%: −0.73, −0.12, p = 0.005), as well as in longitudinal analysis over follow-up (B = −0.32 ± 0.072, χ2 = 36.6; p = < 0.001). Higher HDL-C was also associated with higher T2-lesion volume in longitudinal analysis (B = 0.11 ± 0.023; χ2 = 23.04; p = < 0.001). We observed a weak negative association between low-density lipoprotein cholesterol (LDL-C) levels and BPF at baseline (B = −0.26, CI 95%: −0.4, −0.11, p = < 0.001) as well as in longitudinal analysis (B = −0.06 ± 0.03, χ2 = 4.46; p = 0.03). T2-LV did not show an association with LDL-C. We did not find any association between lipid measures and disability. The effect of lipid levels on MRI measures and disability was minimal (Cohen f2 < 0.02).

Conclusions

Our results contradict the previously described exclusively positive effect of HDL-C on brain atrophy in patients with MS. Higher LDL-C was weakly associated with higher brain atrophy but not with higher lesion burden.
Association of biological aging with prostate cancer: insights from the National Health and Nutrition Examination Survey
Authors: Yin Weiqi , Song Baiyang , Yu Chengling , Jiang Junhui , Yan Zejun , Xie Chengxin
Published: October 2024

The link between biological aging and prostate cancer (PCa) risk, particularly as indicated by elevated prostate-specific antigen (PSA) levels, remains uncertain. This study utilized data from the National Health and Nutrition Examination Survey (2001–2010) to explore this association. Biological age was assessed using Klemera-Doubal method age (KDMAge) and phenotypic age (PhenoAge). PCa was identified through self-reported diagnoses, and highly probable PCa was determined by PSA levels. We analyzed the prevalence of PCa and PSA-defined highly probable PCa across quartiles of biological age measures using weighted chi-square and linear trend tests. Associations were evaluated using weighted multiple logistic regression models. Among 7,209 and 6,682 males analyzed, the overall weighted prevalence of PCa was 2.86%, increasing to 9.60% in those aged 65 and above. A significant rise in PCa prevalence was observed with higher quartiles of KDMAge or PhenoAge (P for trend < 0.001), particularly in those under 65. In this younger group, higher PhenoAge acceleration quartiles were linked to increased PCa prevalence and higher risk of PCa (OR = 1.50, P = 0.015) as well as highly probable PCa in those without a diagnosis (OR = 1.28, P = 0.031). These findings suggest that accelerated biological aging is associated with an increased risk of PCa and may indicate early risk as signaled by PSA levels, even in those without a PCa diagnosis.