bluuebunny/crossref_metadata_2025 huggingface dataset:
Do Financial Barrier Beliefs About Marriage Predict Building Wealth? Latent Growth Curves of Emerging Adults’ Financial Barrier Beliefs, Assets, and Debt
Authors: Saxey Matthew T. , LeBaron-Black Ashley B. , Willoughby Brian J. , Yorgason Jeremy B.
Published: May 2024

Scholars have found that among emerging adults, financial barrier beliefs about marriage—like believing financial independence should be achieved prior to marriage—appear to be common. Despite the prevalence of beliefs about finances regarding marriage readiness, scholars have not established whether and how these financial barrier beliefs about marriage predict emerging adults’ debt and assets over time. Through the lens of marital paradigms theory, we sought to address this gap by examining whether and how the initial level and changes in financial barrier beliefs about marriage predict changes in young emerging adults’ debt and assets across four waves of data from 1,033 young U.S. emerging adults. We found that, on average, financial barrier beliefs about marriage increased, assets were relatively stable, and debt increased over the early years of emerging adulthood. We also found that increases in emerging adults’ agreement with financial barrier beliefs like ‘finances are a barrier to marriage’ over time were associated with a decrease in assets over time. However, neither the initial level nor changes in financial barrier beliefs about marriage predicted changes in debt over time. In short, our findings provide some evidence that beliefs like a certain amount of money should be saved before marriage, somewhat paradoxically, do not appear to help young emerging adults build their assets.
Carbon stock increase during post-agricultural succession in central France: no change of the superficial soil stock and high variability within forest stages
Authors: Weissgerber Magali , Chanteloup Laine , Bonis Anne
Published: May 2024

Forest development following agricultural abandonment concerns extensive areas including the Massif Central region of France where this study was undertaken. This land-use and land-cover change is expected to have effects on biodiversity and ecosystem services, including an increase of carbon sequestration—a major concern in the face of climate change. Nevertheless, uncertainties about carbon stock changes during successions are remaining, especially as to the total stock and the contribution of the different carbon pools. Our work contributes to this field by studying carbon stocks in multiple plots of different successional stages. We measured and estimated carbon stocks in aboveground and belowground vegetation, deadwood, litter and superficial soil, and surveyed plant communities and plot conditions (slope, aspect, soil characteristics). The average total carbon stock increased along the succession from 70.60 at stage 0 to 314.19 tC ha−1 at stage 5. However, the total carbon stocks at the young forest stage (abandoned for 74 years maximum) and the older forest stage (forested for at least 74 years) were not significantly different, and probably reflected strong local heterogeneity in the older forest stage. An increase of the carbon stock was found in all pools, except the soil pool that did not vary significantly between the successional stages. The aboveground carbon stock was found strongly related to the woody species cover, especially the macrophanerophyte cover. This case study supports the view that the succession dynamics of former agricultural plots participates in carbon sequestration, sometimes with great local variations.
Differential Item Functioning via Robust Scaling
Authors: Halpin Peter F.
Published: May 2024

This paper proposes a method for assessing differential item functioning (DIF) in item response theory (IRT) models. The method does not require pre-specification of anchor items, which is its main virtue. It is developed in two main steps: first by showing how DIF can be re-formulated as a problem of outlier detection in IRT-based scaling and then tackling the latter using methods from robust statistics. The proposal is a redescending M-estimator of IRT scaling parameters that is tuned to flag items with DIF at the desired asymptotic type I error rate. Theoretical results describe the efficiency of the estimator in the absence of DIF and its robustness in the presence of DIF. Simulation studies show that the proposed method compares favorably to currently available approaches for DIF detection, and a real data example illustrates its application in a research context where pre-specification of anchor items is infeasible. The focus of the paper is the two-parameter logistic model in two independent groups, with extensions to other settings considered in the conclusion.
What qualitative systems mapping is and what it could be: integrating and visualizing diverse knowledge of complex problems
Authors: Hanger-Kopp Susanne , Lemke Leonard Kwhang-Gil , Beier Julia
Published: May 2024

Researchers in sustainability science deal with increasingly complex problems that cross administrative, geographical, disciplinary, and sectoral boundaries, and are characterized by high stakes and deep uncertainties. This in turn creates methodological challenges to frame, structure, and solve complex problems in science and practice. There is a long tradition in visualizing systems as diagrams, and concept and cognitive maps, but there is insufficient differentiation and comparison between these methods and no clear umbrella term has yet been established. Against this background, we systematically review three foundational methods from different academic disciplines—causal diagrams, concept mapping, and cognitive mapping. Comparing and contrasting them, we facilitate a coherent understanding of qualitative systems mapping (QSM) as an umbrella term. We then proceed to explore the evident intersections between these methods to showcase some of the inter- and transdisciplinary opportunities and challenges crystallizing in integrated QSM approaches. Finally, we share case study insights from the food–water–biodiversity nexus in Austria and elaborate on some of the methodological nuances to data integration in QSM. Overall, with this overview paper, we lay the groundwork for a systematic, transparent, and yet flexible development and application of QSM methods to support mixed-methods research design and clear case study documentation, as well as fostering effective inter- and transdisciplinary communication in sustainability science. Further research needs to explore these QSM applications in depth across alternative sustainability science contexts, particularly with respect to efficient and rigorous protocols for knowledge and data integration vis-a-vis complex problems and transdisciplinary research processes.
Machine Learning in Biomaterials, Biomechanics/Mechanobiology, and Biofabrication: State of the Art and Perspective
Authors: Wu Chi , Xu Yanan , Fang Jianguang , Li Qing
Published: May 2024

In the past three decades, biomedical engineering has emerged as a significant and rapidly growing field across various disciplines. From an engineering perspective, biomaterials, biomechanics, and biofabrication play pivotal roles in interacting with targeted living biological systems for diverse therapeutic purposes. In this context, in silico modelling stands out as an effective and efficient alternative for investigating complex interactive responses in vivo. This paper offers a comprehensive review of the swiftly expanding field of machine learning (ML) techniques, empowering biomedical engineering to develop cutting-edge treatments for addressing healthcare challenges. The review categorically outlines different types of ML algorithms. It proceeds by first assessing their applications in biomaterials, covering such aspects as data mining/processing, digital twins, and data-driven design. Subsequently, ML approaches are scrutinised for the studies on mono-/multi-scale biomechanics and mechanobiology. Finally, the review extends to ML techniques in bioprinting and biomanufacturing, encompassing design optimisation and in situ monitoring. Furthermore, the paper presents typical ML-based applications in implantable devices, including tissue scaffolds, orthopaedic implants, and arterial stents. Finally, the challenges and perspectives are illuminated, providing insights for academia, industry, and biomedical professionals to further develop and apply ML strategies in future studies.
The vegetation around the foothills of the Hijaz Mountains, Saudi Arabia
Authors: Hofland Nick , Hatim Mohamed Z. , Thomas Jacob , Janssen John A. M. , Alharti Awad S. , Alfarhan Ahmed H. , Alatar Abdulrahman A. , Schaminée Joop H. J. , El-Sheikh Mohamed A.
Published: May 2024

Despite Saudi Arabia being an interesting area from a floristic perspective, its vegetation is still relatively poorly studied. This certainly applies to the Hijaz Mountains and adjacent coastal zones. We aim to describe the flora and vegetation of the foothills of the Hijaz Mountains regarding the environmental conditions. Hijaz Mountains and adjacent coastal zones, Saudi Arabia. We studied the vegetation at the Hijaz Mountains’ foothills along two transects of vegetation surveys, one along the coast and one more inland. In addition, soil samples were taken and analyzed for soil texture, pH, electrical conductivity, organic matter, calcium carbonate and the concentration of the elements N, Na, K, Ca, Mg, Fe and Mn were determined. We calculated the data clustering tendency (Hopkins’ test analysis) and its optimal number of clusters (Elbow method). We used modified TWINSPAN to cluster the data and validated the resulting communities using the Silhouette algorithm. Seven plant communities resulted, each one dominated by a different plant species, namely: Haloxylon salicornicum, Lycium shawii, Senegalia hamulosa, Vachellia tortilis, Zygophyllum coccineum, Vachellia flavaand Stipagrostis plumosa, and were described based on their floristic composition and could be further grouped into three vegetation clusters. The communities had varying ranges of occurrence in the study area, some dominating certain sections, with latitude and altitude being the biggest distinguishing environmental variables between the communities. We present a description of the vegetation of the Hijaz Mountains foothills. Our study is considered an important basis for decision-making of nature conservation and in-depth surveys of the area.

Graphic abstract
CXCL10 could be a prognostic and immunological biomarker in bladder cancer
Authors: Yin Tao , Mou Shuanzhu , Zhang Haiyu , Dong Ying , Yan Bing , Huang Weisheng , Liu Yuhan , Mei Hongbing
Published: May 2024

Introduction

As proteins that promote immune cell differentiation, chemokines have attracted great interest regarding their role in anti-tumor immune responses within the cancer environment. However, the exact role of CXCL10, a chemokine, in bladder cancer (BLCA) is still not fully elucidated.

Method

In the present study, we employed bioinformatics approaches to examine the expression pattern, prognostic value, and immune infiltration of CXCL10 in BLCA. Furthermore, we focused on examining the impact of CXCL10 on immune therapy in BLCA. Additionally, we validated the expression of CXCL10 in various BLCA cell lines using PCR techniques.

Results

We observed an upregulation of CXCL10 in BLCA tissues as well as in different cell lines. Additionally, upregulation of CXCL10 indicates a better prognosis for BLCA patients. ESTIMATE and CIBERSORT algorithms suggest that CXCL10 is closely associated with the immune microenvironment of BLCA. Through multiple immune therapy cohorts, we also identified that CXCL10 has shown promising predictive value for assessing the efficacy of immune therapy in in BLCA.

Conclusion

Our study indicates that CXCL10 has the potential to serve as a favorable prognostic factor and is strongly associated with immune infiltration in BLCA.

Graphical Abstract
Assessment of structural mechanical effects related to torsional deformations of propellers
Authors: Möhren F. , Bergmann O. , Janser F. , Braun C.
Published: May 2024

Lifting propellers are of increasing interest for Advanced Air Mobility. All propellers and rotors are initially twisted beams, showing significant extension–twist coupling and centrifugal twisting. Torsional deformations severely impact aerodynamic performance. This paper presents a novel approach to assess different reasons for torsional deformations. A reduced-order model runs large parameter sweeps with algebraic formulations and numerical solution procedures. Generic beams represent three different propeller types for General Aviation, Commercial Aviation, and Advanced Air Mobility. Simulations include solid and hollow cross-sections made of aluminum, steel, and carbon fiber-reinforced polymer. The investigation shows that centrifugal twisting moments depend on both the elastic and initial twist. The determination of the centrifugal twisting moment solely based on the initial twist suffers from errors exceeding 5% in some cases. The nonlinear parts of the torsional rigidity do not significantly impact the overall torsional rigidity for the investigated propeller types. The extension–twist coupling related to the initial and elastic twist in combination with tension forces significantly impacts the net cross-sectional torsional loads. While the increase in torsional stiffness due to initial twist contributes to the overall stiffness for General and Commercial Aviation propellers, its contribution to the lift propeller’s stiffness is limited. The paper closes with the presentation of approximations for each effect identified as significant. Numerical evaluations are necessary to determine each effect for inhomogeneous cross-sections made of anisotropic material.
Understanding Australia’s teacher shortage: the importance of psychosocial working conditions to turnover intentions
Authors: Rahimi Mark , Arnold Ben
Published: May 2024

Australian policymakers are currently attempting to address an ‘unprecedented teacher shortage’. Through a survey of 905 teachers in Australian government schools, this paper examines some of the key factors influencing the career intentions of teachers in Australian government schools. Drawing upon the concept of the psychosocial work environment from the field of occupational health, this analysis examines the relationship between key workplace demands, workplace resources, teachers’ experiences and attitudes towards work, teachers’ mental health outcomes, and their intentions to either remain in or leave their roles. The results reveal significant relationships between teachers’ intentions to leave their roles and challenging working conditions, adverse work experiences, as well as heightened levels of stress, burnout, and depressive symptoms. In contrast, remaining in their role was associated with factors indicative of a supportive psychosocial work environment, such as job recognition, trust in management, organisational justice, positive work experiences, and lower levels of mental health difficulties. The study underscores the urgent need to understand and assess the psychosocial work environments of teachers, and for multi-level strategies that address both protective and risk factors.
The effect of hot isostatic pressing pressure level and solution annealing cooling rate on CM247 LC nickel-based superalloy processed by laser-based powder bed fusion
Authors: Martelli P. A. , Bassini E. , Ugues D.
Published: May 2024

In the present work, CM247 LC samples produced by laser-based powder bed fusion (PBF-LB) were heat treated inside a hot isostatic pressing (HIP) furnace (HIP quench treatment) at 1260 °C for 3 h to combine the solution annealing with the elimination of defects of the additively manufactured parts. In particular, the effects of different applied pressures (50–170 MPa) and cooling rates (from 162 to 2450 °C/min) on the final densification, grain coarsening, and γ’ precipitation were studied. The results were also compared to a sample heat treated in a low-pressure furnace and gas-quenched at 195 °C/min. The study revealed that the applied pressure has a negligible effect on densification, grain coarsening, and the size and shape of γ’, which is always irregular after solution annealing, independently from the cooling rate. For this reason, first aging was subsequently applied at 1080 °C for 4 h to HIP-quenched samples, revealing that this step of treatment is effectively responsible for the final cubic shape of γ’, even if a starting irregular morphology is considered. Finally, additional samples were heat treated in an air furnace and air cooled to room temperature prior to the HIP quench; this procedure allowed assessing the solutioning effectiveness of the HIP quench with coarse precipitates typical of conventional processing (e.g., investment casting). Overall, this study underscores the efficacy of the HIP quench in enhancing microstructural attributes and mitigating defects, providing valuable insights for enhancing the properties of challenging Ni-based alloys fabricated through additive manufacturing techniques.
Parabolic trough concentrator design, characterization, and application: solar wastewater purification targeting textile industry dyes and pharmaceuticals—techno-economic study
Authors: El Golli Asma , Fendrich Murilo , Bajpai Om Prakash , Bettonte Marco , Edebali Serpil , Orlandi Michele , Miotello Antonio
Published: May 2024

Solar energy, along with other renewable resources, has the potential to be a major contributor to solving environmental issues in the future, as illustrated by the most recent advancements in solar photocatalytic technology. Indeed, wastewater treatment using a parabolic solar collector for industrial processes is gaining ground owing to improved system performance and economic benefits. The fabricated parabolic trough collector (PTC) incorporates reflective, parabolic panels that focus solar energy onto a transparent tube positioned along the parabolic focal line, where solar-powered photochemical reactions occur. This study investigated the design, implementation, and effectiveness of a concentrated sunlight system for removing industrial dyes and emerging large-use pharmaceutical contaminants in the presence of H2O2 at a small demonstrator scale (10 L/h). A spectrophotometric assessment revealed that subjecting Remazol Brilliant Blue (RBB, 60 ppm) and ciprofloxacin (CIP, 10 ppm) to irradiation in the presence of 0.1 M H2O2 (RBB) or 0.01 M H2O2 (CIP) for 3 h resulted in a degradation rate exceeding 60% and 80%, respectively. Furthermore, the total organic content (TOC) analysis indicates a very high total removal yield for RBB. On these bases, a techno-economic analysis is produced, and economic viability is discussed. The data reveal that the annual costs for water treatment, considering investment, electricity, and catalyst expenses over a 12-month period are significantly lower for our PTC-based prototype than for a comparable artificial UV-based equipment.
Hydrothermal liquefaction of wet microalgal biomass for biofuels and platform chemicals: advances and future prospects
Authors: Deepika Charu , Mrinal  , Pohrmen Cheryl Bernice , Jaiswal Km Smriti , Sangmesh B. , Jaiswal Krishna Kumar , Ramasamy Arun Prasath , Jaiswal Amit K.
Published: May 2024

Recent advances in hydrothermal liquefaction (HTL) have established this biomass conversion technology as a potent tool for the effective valorization and energy densification of varied feedstocks, ranging from lignocelluloses to microalgae and organic wastes. Emphasizing its application across biomass types, this exploration delves into the evolving landscape of HTL. Microalgae, recognized as a promising feedstock, offer a rich source of biomolecules, including lipids, carbohydrates, and proteins, making them particularly attractive for biofuel production. The comprehensive review explores the biofuel products and platform chemicals obtained through HTL of microalgae, delving into biodiesel production, bio-oil composition, characteristics, and to produce high-valued by-products. Challenges and limitations, such as reactor design, scalability issues, and the impact of microalgal composition on yields, are critically analyzed. The future prospects and research directions section envision advancements in HTL technology, integration with biorefinery processes, and the exploration of hybrid approaches for enhanced biofuel production. Overall, the paper emphasizes the promising potential of HTL for wet microalgal biomass and underscores the need for continued research to overcome existing challenges and unlock further opportunities in sustainable biofuel and platform chemical production.
Topp-Leone Exponentiated Pareto Distribution: Properties and Application to Covid-19 Data
Authors: Correa Fabio M. , Odunayo Braimah J. , Sule Ibrahim , Bello Olalekan A.
Published: May 2024

This paper proposes a new Topp-Leone Exponentiated Pareto (TLEtP) distribution. The new distribution family is derived by expanding the Topp Leone-G family of distributions with additional positive shape parameters. The corresponding density and distribution functions are derived and shown. Some of the derived mathematical properties of the distribution include quantile function, ordinary and incomplete moments generating function (mgf), hazard function, survival function, odd function, probability weighted moment, and distribution of order statistic. The parameters of the distribution are estimated using Maximum Likelihood method. The proposed distribution’s validity is demonstrated by fitting two sets of real data and comparing the results with two existing same-family distributions, the Topp-Leone Pareto type I(TLPI) and Pareto (P), with the Akaike Information Criteria (AIC) and Bayesian Information Criteria (BIC), respectively. The comparison of the proposed Topp-Leone Exponentiated Pareto (TLEtP) to the Topp-Leone Pareto type I(TLPI) and Pareto (P) distribution demonstrate that the TLEtP distribution offers a better fit for the data sets than the other two distributions.
Intraday residual transfer learning in minimally observed power distribution networks dynamic state estimation
Authors: Lu Junyi , Stephen Bruce , Brown Blair
Published: May 2024

Traditionally, electricity distribution networks were designed for unidirectional power flow without the need to accommodate generation installed at the point of use. However, with the increase in Distributed Energy Resources and other Low Carbon Technologies, the role of distribution networks is changing. This shift brings challenges, including the need for intensive metering and more frequent reconfiguration to identify threats from voltage and thermal violations. Mitigating action through reconfiguration is informed by State Estimation, which is especially challenging for low voltage distribution networks where the constraints of low observability, non-linear load relationships, and highly unbalanced systems all contribute to the difficulty of producing accurate state estimates. To counter low observability, this paper proposes the application of a novel transfer learning methodology, based upon the concept of conditional online Bayesian transfer, to make forward predictions of bus pseudo-measurements. Day ahead load forecasts at a fully observed point on the network are adjusted using the intraday residuals at other points in the network to provide them with load forecasts without the need for a complete set of forecast models at all substations. These form pseudo-measurements that then inform the state estimates at future time points. This methodology is demonstrated on both a representative IEEE Test network and on an actual GB 11 kV feeder network.
The SDGs Provide Limited Evidence That Environmental Policies Are Delivering Multiple Ecological and Social Benefits
Authors: Fairbrass A. J. , O’Sullivan A. , Campbell J. , Ekins P.
Published: May 2024

The Sustainable Development Goals (SDGs), aiming for global targets by 2030, are tracked by a monitoring framework comprising 231 environmental, social, and economic indicators. The framework provides data to assess whether, across countries, environmental policies are: (a) Addressing environmental pressures, (b) Linked to environmental improvements, and (c) Linked with social benefits delivered by healthy environments. While several studies have analyzed the implementation and impacts of the SDGs, there remains a critical research gap in assessing the linkage between environmental policies and their potential to deliver multiple ecological and social benefits. This study examines the efficacy of environmental policies and their implications for global environmental health and social wellbeing. We use a generalized linear modeling approach to test for correlations between SDG indicators. We show that some environmental policies, particularly protected areas and sustainable forest certification, are linked with environmental improvements, mainly in forest and water ecosystems. However, we find no evidence that environmental improvements are linked with positive social impacts. Finally, environmental pressures, including freshwater withdrawal, domestic material consumption, and tourism, are linked with environmental degradation. Environmental policy responses are generally increasing across countries. Despite this, the state of the environment globally continues to decline. Governments must focus on understanding why environmental policies have not been sufficient to reverse environmental decline, particularly concerning the pressures that continue to degrade the environment. To better track progress toward sustainable development, we recommend that the SDG monitoring framework is supplemented with additional indicators on the state of the environment.
Targeting CXCR4 impaired T regulatory function through PTEN in renal cancer patients
Authors: Santagata Sara , Rea Giuseppina , Bello Anna Maria , Capiluongo Anna , Napolitano Maria , Desicato Sonia , Fragale Alessandra , D’Alterio Crescenzo , Trotta Anna Maria , Ieranò Caterina , Portella Luigi , Persico Francesco , Di Napoli Marilena , Di Maro Salvatore , Feroce Florinda , Azzaro Rosa , Gabriele Lucia , Longo Nicola , Pignata Sandro , Perdonà Sisto , Scala Stefania
Published: May 2024

Background

Tregs trafficking is controlled by CXCR4. In Renal Cell Carcinoma (RCC), the effect of the new CXCR4 antagonist, R54, was explored in peripheral blood (PB)-Tregs isolated from primary RCC patients.

Methods

PB-Tregs were isolated from 77 RCC patients and 38 healthy donors (HDs). CFSE-T effector-Tregs suppression assay, IL-35, IFN-γ, IL-10, TGF-β1 secretion, and Nrp-1+Tregs frequency were evaluated. Tregs were characterised for CTLA-4, PD-1, CD40L, PTEN, CD25, TGF-β1, FOXP3, DNMT1 transcriptional profile. PTEN-pAKT signalling was evaluated in the presence of R54 and/or triciribine (TCB), an AKT inhibitor. Methylation of TSDR (Treg-Specific-Demethylated-Region) was conducted.

Results

R54 impaired PB-RCC-Tregs function, reduced Nrp-1+Tregs frequency, the release of IL-35, IL-10, and TGF-β1, while increased IFN-γ Teff-secretion. The CXCR4 ligand, CXCL12, recruited CD25+PTEN+Tregs in RCC while R54 significantly reduced it. IL-2/PMA activates Tregs reducing pAKT+Tregs while R54 increases it. The AKT inhibitor, TCB, prevented the increase in pAKT+Tregs R54-mediated. Moreover, R54 significantly reduced FOXP3-TSDR demethylation with DNMT1 and FOXP3 downregulation.

Conclusion

R54 impairs Tregs function in primary RCC patients targeting PTEN/PI3K/AKT pathway, reducing TSDR demethylation and FOXP3 and DNMT1 expression. Thus, CXCR4 targeting is a strategy to inhibit Tregs activity in the RCC tumour microenvironment.
Genetic association of inflammatory marker GlycA with lung function and respiratory diseases
Authors: Guo Yanjun , Liu Quanhong , Zheng Zhilin , Qing Mengxia , Yao Tianci , Wang Bin , Zhou Min , Wang Dongming , Ke Qinmei , Ma Jixuan , Shan Zhilei , Chen Weihong
Published: May 2024

Association of circulating glycoprotein acetyls (GlycA), a systemic inflammation biomarker, with lung function and respiratory diseases remain to be investigated. We examined the genetic correlation, shared genetics, and potential causality of GlycA (N = 115,078) with lung function and respiratory diseases (N = 497,000). GlycA showed significant genetic correlation with FEV1 (rg = −0.14), FVC (rg = −0.18), asthma (rg = 0.21) and COPD (rg = 0.31). We consistently identified ten shared loci (includingchr3p21.31andchr8p23.1) at both SNP and gene level revealing potential shared biological mechanisms involving ubiquitination, immune response, Wnt/β-catenin signaling, cell growth and differentiation in tissues or cells including blood, epithelium, fibroblast, fetal thymus, and fetal intestine. Genetically elevated GlycA was significantly correlated with lung function and asthma susceptibility (354.13 ml decrement of FEV1, 442.28 ml decrement of FVC, and 144% increased risk of asthma per SD increment of GlycA) from MR analyses. Our findings provide insights into biological mechanisms of GlycA in relating to lung function, asthma, and COPD.
Controlling the broadband enhanced light chirality with L-shaped dielectric metamaterials
Authors: Kilic Ufuk , Hilfiker Matthew , Wimer Shawn , Ruder Alexander , Schubert Eva , Schubert Mathias , Argyropoulos Christos
Published: May 2024

The inherently weak chiroptical responses of natural materials limit their usage for controlling and enhancing chiral light-matter interactions. Recently, several nanostructures with subwavelength scale dimensions were demonstrated, mainly due to the advent of nanofabrication technologies, as a potential alternative to efficiently enhance chirality. However, the intrinsic lossy nature of metals and the inherent narrowband response of dielectric planar thin films or metasurface structures pose severe limitations toward the practical realization of broadband and tailorable chiral systems. Here, we tackle these problems by designing all-dielectric silicon-based L-shaped optical metamaterials based on tilted nanopillars that exhibit broadband and enhanced chiroptical response in transmission operation. We use an emerging bottom-up fabrication approach, named glancing angle deposition, to assemble these dielectric metamaterials on a wafer scale. The reported strong chirality and optical anisotropic properties are controllable in terms of both amplitude and operating frequency by simply varying the shape and dimensions of the nanopillars. The presented nanostructures can be used in a plethora of emerging nanophotonic applications, such as chiral sensors, polarization filters, and spin-locked nanowaveguides.
Diet-omics in the Study of Urban and Rural Crohn disease Evolution (SOURCE) cohort
Authors: Braun Tzipi , Feng Rui , Amir Amnon , Levhar Nina , Shacham Hila , Mao Ren , Hadar Rotem , Toren Itamar , Algavi Yadid , Abu-Saad Kathleen , Zhuo Shuoyu , Efroni Gilat , Malik Alona , Picard Orit , Yavzori Miri , Agranovich Bella , Liu Ta-Chiang , Stappenbeck Thaddeus S. , Denson Lee , Kalter-Leibovici Ofra , Gottlieb Eyal , Borenstein Elhanan , Elinav Eran , Chen Minhu , Ben-Horin Shomron , Haberman Yael
Published: May 2024

Crohn disease (CD) burden has increased with globalization/urbanization, and the rapid rise is attributed to environmental changes rather than genetic drift. The Study Of Urban and Rural CD Evolution (SOURCE, n = 380) has considered diet-omics domains simultaneously to detect complex interactions and identify potential beneficial and pathogenic factors linked with rural-urban transition and CD. We characterize exposures, diet, ileal transcriptomics, metabolomics, and microbiome in newly diagnosed CD patients and controls in rural and urban China and Israel. We show that time spent by rural residents in urban environments is linked with changes in gut microbial composition and metabolomics, which mirror those seen in CD. Ileal transcriptomics highlights personal metabolic and immune gene expression modules, that are directly linked to potential protective dietary exposures (coffee, manganese, vitamin D), fecal metabolites, and the microbiome. Bacteria-associated metabolites are primarily linked with host immune modules, whereas diet-linked metabolites are associated with host epithelial metabolic functions.
Mutation characteristics and molecular evolution of ovarian metastasis from gastric cancer and potential biomarkers for paclitaxel treatment
Authors: Yu Pengfei , Hu Can , Ding Guangyu , Shi Xiaoliang , Xu Jingli , Cao Yang , Chen Xiangliu , Wu Wei , Xu Qi , Fang Jingquan , Huang Xingmao , Yuan Shaohua , Chen Hui , Wang Zhizheng , Huang Ling , Pang Fei , Du Yian , Cheng Xiangdong
Published: May 2024

Ovarian metastasis is one of the major causes of treatment failure in patients with gastric cancer (GC). However, the genomic characteristics of ovarian metastasis in GC remain poorly understood. In this study, we enroll 74 GC patients with ovarian metastasis, with 64 having matched primary and metastatic samples. Here, we show a characterization of the mutation landscape of this disease, alongside an investigation into the molecular heterogeneity and pathway mutation enrichments between synchronous and metachronous metastasis. We classify patients into distinct clonal evolution patterns based on the distribution of mutations in paired samples. Notably, the parallel evolution group exhibits the most favorable prognosis. Additionally, by analyzing the differential response to chemotherapy, we identify potential biomarkers, including SALL4, CCDC105, and CLDN18, for predicting the efficacy of paclitaxel treatment. Furthermore, we validate that CLDN18 fusion mutations improve tumor response to paclitaxel treatment in GC with ovarian metastasis in vitro and vivo.
Effects of emissions caps on the costs and feasibility of low-carbon hydrogen in the European ammonia industry
Authors: Mingolla Stefano , Gabrielli Paolo , Manzotti Alessandro , Robson Matthew J. , Rouwenhorst Kevin , Ciucci Francesco , Sansavini Giovanni , Klemun Magdalena M. , Lu Zhongming
Published: May 2024

The European ammonia industry emits 36 million tons of carbon dioxide annually, primarily from steam methane reforming (SMR) hydrogen production. These emissions can be mitigated by producing hydrogen via water electrolysis using dedicated renewables with grid backup. This study investigates the impact of decarbonization targets for hydrogen synthesis on the economic viability and technical feasibility of retrofitting existing European ammonia plants for on-site, semi-islanded electrolytic hydrogen production. Results show that electrolytic hydrogen cuts emissions, on average, by 85% (36%-100% based on grid price and carbon intensity), even without enforcing emission limits. However, an optimal lifespan average well-to-gate emission cap of 1 kg carbon dioxide equivalent (CO2e)/kg H2leads to a 95% reduction (92%-100%) while maintaining cost-competitiveness with SMR in renewable-rich regions (mean levelized cost of hydrogen (LCOH) of 4.1 euro/kg H2). Conversely, a 100% emissions reduction target dramatically increases costs (mean LCOH: 6.3 euro/kg H2) and land area for renewables installations, likely hindering the transition to electrolytic hydrogen in regions with poor renewables and limited land. Increasing plant flexibility effectively reduces costs, particularly in off-grid plants (mean reduction: 32%). This work guides policymakers in defining cost-effective decarbonization targets and identifying region-based strategies to support an electrolytic hydrogen-fed ammonia industry.
An oxylipin signal confers protection against antifungal echinocandins in pathogenic aspergilli
Authors: Calise Dante G. , Park Sung Chul , Bok Jin Woo , Goldman Gustavo H. , Keller Nancy P.
Published: May 2024

Aspergillus fumigatus is the leading causative agent of life-threatening invasive aspergillosis in immunocompromised individuals. One antifungal class used to treat Aspergillus infections is the fungistatic echinocandins, semisynthetic drugs derived from naturally occurring fungal lipopeptides. By inhibiting beta-1,3-glucan synthesis, echinocandins cause both fungistatic stunting of hyphal growth and repeated fungicidal lysis of apical tip compartments. Here, we uncover an endogenous mechanism of echinocandin tolerance in A. fumigatus whereby the inducible oxylipin signal 5,8-diHODE confers protection against tip lysis via the transcription factor ZfpA. Treatment of A. fumigatus with echinocandins induces 5,8-diHODE synthesis by the fungal oxygenase PpoA in a ZfpA dependent manner resulting in a positive feedback loop. This protective 5,8-diHODE/ZfpA signaling relay is conserved among diverse isolates of A. fumigatus and in two other Aspergillus pathogens. Our findings reveal an oxylipin-directed growth program—possibly arisen through natural encounters with native echinocandin producing fungi—that enables echinocandin tolerance in pathogenic aspergilli.
The impact of spike timing precision and spike emission reliability on decoding accuracy
Authors: Nicola Wilten , Newton Thomas Robert , Clopath Claudia
Published: May 2024

Precisely timed and reliably emitted spikes are hypothesized to serve multiple functions, including improving the accuracy and reproducibility of encoding stimuli, memories, or behaviours across trials. When these spikes occur as a repeating sequence, they can be used to encode and decode a potential time series. Here, we show both analytically and in simulations that the error incurred in approximating a time series with precisely timed and reliably emitted spikes decreases linearly with the number of neurons or spikes used in the decoding. This was verified numerically with synthetically generated patterns of spikes. Further, we found that if spikes were imprecise in their timing, or unreliable in their emission, the error incurred in decoding with these spikes would be sub-linear. However, if the spike precision or spike reliability increased with network size, the error incurred in decoding a time-series with sequences of spikes would maintain a linear decrease with network size. The spike precision had to increase linearly with network size, while the probability of spike failure had to decrease with the square-root of the network size. Finally, we identified a candidate circuit to test this scaling relationship: the repeating sequences of spikes with sub-millisecond precision in area HVC (proper name) of the zebra finch. This scaling relationship can be tested using both neural data and song-spectrogram-based recordings while taking advantage of the natural fluctuation in HVC network size due to neurogenesis.
A Deep Auto-Optimized Collaborative Learning (DACL) model for disease prognosis using AI-IoMT systems
Authors: Nandagopal Malarvizhi , Seerangan Koteeswaran , Govindaraju Tamilmani , Abi Neeba Eralil , Balusamy Balamurugan , Selvarajan Shitharth
Published: May 2024

In modern healthcare, integrating Artificial Intelligence (AI) and Internet of Medical Things (IoMT) is highly beneficial and has made it possible to effectively control disease using networks of interconnected sensors worn by individuals. The purpose of this work is to develop an AI-IoMT framework for identifying several of chronic diseases form the patients’ medical record. For that, the Deep Auto-Optimized Collaborative Learning (DACL) Model, a brand-new AI-IoMT framework, has been developed for rapid diagnosis of chronic diseases like heart disease, diabetes, and stroke. Then, a Deep Auto-Encoder Model (DAEM) is used in the proposed framework to formulate the imputed and preprocessed data by determining the fields of characteristics or information that are lacking. To speed up classification training and testing, the Golden Flower Search (GFS) approach is then utilized to choose the best features from the imputed data. In addition, the cutting-edge Collaborative Bias Integrated GAN (ColBGaN) model has been created for precisely recognizing and classifying the types of chronic diseases from the medical records of patients. The loss function is optimally estimated during classification using the Water Drop Optimization (WDO) technique, reducing the classifier’s error rate. Using some of the well-known benchmarking datasets and performance measures, the proposed DACL’s effectiveness and efficiency in identifying diseases is evaluated and compared.
Development of a clinical calculator to aid the identification of MODY in pediatric patients at the time of diabetes diagnosis
Authors: Shields Beverley M. , Carlsson Annelie , Patel Kashyap , Knupp Julieanne , Kaur Akaal , Johnston Des , Colclough Kevin , Larsson Helena Elding , Forsander Gun , Samuelsson Ulf , Hattersley Andrew , Ludvigsson Johnny
Published: May 2024

Maturity Onset Diabetes of the Young (MODY) is a young-onset, monogenic form of diabetes without needing insulin treatment. Diagnostic testing is expensive. To aid decisions on who to test, we aimed to develop a MODY probability calculator for paediatric cases at the time of diabetes diagnosis, when the existing “MODY calculator” cannot be used. Firth logistic regression models were developed on data from 3541 paediatric patients from the Swedish ‘Better Diabetes Diagnosis’ (BDD) population study (n = 46 (1.3%) MODY (HNF1A, HNF4A, GCK)). Model performance was compared to using islet autoantibody testing. HbA1c, parent with diabetes, and absence of polyuria were significant independent predictors of MODY. The model showed excellent discrimination (c-statistic = 0.963) and calibrated well (Brier score = 0.01). MODY probability > 1.3% (ie. above background prevalence) had similar performance to being negative for all 3 antibodies (positive predictive value (PPV) = 10% v 11% respectively i.e. ~ 1 in 10 positive test rate). Probability > 1.3% and negative for 3 islet autoantibodies narrowed down to 4% of the cohort, and detected 96% of MODY cases (PPV = 31%). This MODY calculator for paediatric patients at time of diabetes diagnosis will help target genetic testing to those most likely to benefit, to get the right diagnosis.
Feasibility experiment of a novel deformable self-assembled magnetic anastomosis ring (DSAMAR) for gastrointestinal anastomosis through a natural orifice
Authors: Zhang Miaomiao , Zhong Qiuye , Ma Jia , Mao Jianqi , Shi Aihua , Lyu Yi , Yan Xiaopeng
Published: May 2024

Although the application of magnetic compression anastomosis is becoming increasingly widespread, the magnets used in earlier studies were mostly in the shape of a whole ring. Hence, a deformable self-assembled magnetic anastomosis ring (DSAMAR) was designed in this study for gastrointestinal anastomosis. Furthermore, its feasibility was studied using a beagle model. The designed DSAMAR comprised 10 trapezoidal magnetic units. Twelve beagles were used as animal models, and DSAMARs were inserted into the stomach and colon through the mouth and anus, respectively, via endoscopy to achieve gastrocolic magnamosis. Surgical time, number of failed deformations, survival rate of the animals, and the time of magnet discharge were documented. A month later, specimens of the anastomosis were obtained and observed with the naked eye as well as microscopically. In the gastrocolic anastomosis of the 12 beagles, the procedure took 65–120 min. Although a deformation failure occurred during the operation in one of the beagles, it was successful after repositioning. The anastomosis was formed after the magnet fell off 12–18 days after the operation. Naked eye and microscopic observations revealed that the anastomotic specimens obtained 1 month later were well-formed, smooth, and flat. DSAMAR is thus feasible for gastrointestinal anastomosis under full endoscopy via the natural orifice.
Virtual reality, face-to-face, and 2D video conferencing differently impact fatigue, creativity, flow, and decision-making in workplace dynamics
Authors: Macchi Gregorio , De Pisapia Nicola
Published: May 2024

Digital communication technologies are rapidly evolving, and understanding their impact on group dynamics and cognitive performance in professional settings becomes central. This study investigates the psychological impact of different interaction settings—two-dimensional Video Conferencing (VC), Face-To-Face (FTF), and Virtual Reality (VR)—on group dynamics, cognitive performance, and aspects of well-being in a professional context. Utilizing a sample of 40 participants from a large Italian electricity transmission company, the study employs a within-subjects design to explore various metrics, including flow, creativity, fatigue and aspects of interaction. The results indicate that FTF interactions are optimal for idea generation and task absorption. VR, although initially more fatiguing for first-time users, fosters a more collaborative and peaceful environment, encouraging participants to engage more openly with each other. VC was found to be the least fatiguing, but also the least engaging in terms of task absorption and idea generation. Additionally, age-related differences were observed, particularly in the perception of motivational and emotional fatigue in the VR setting. The study provides empirical evidence supporting the integration of VR in professional settings for specific types of meetings, while also highlighting the limitations and areas for future research. These findings have implications for organizational well-being, cognitive ergonomics, and the evolving landscape of remote work technologies.
Leopard density and determinants of space use in a farming landscape in South Africa
Authors: J.E.T. McKaughan , P.A. Stephens , C. Lucas , N. Guichard-Kruger , F. Guichard-Kruger , R.A. Hill
Published: May 2024

Protected areas are traditionally the foundation of conservation strategy, but land not formally protected is of particular importance for the conservation of large carnivores because of their typically wide-ranging nature. In South Africa, leopard (Panthera pardus) population decreases are thought to be occurring in areas of human development and intense negative interactions, but research is biased towards protected areas, with quantitative information on population sizes and trends in non-protected areas severely lacking. Using Spatially Explicit Capture-Recapture and occupancy techniques including 10 environmental and anthropogenic covariates, we analysed camera trap data from commercial farmland in South Africa where negative human-wildlife interactions are reported to be high. Our findings demonstrate that leopards persist at a moderate density (2.21 /100 km2) and exhibit signs of avoidance from areas where lethal control measures are implemented. This suggests leopards have the potential to navigate mixed mosaic landscapes effectively, enhancing their chances of long-term survival and coexistence with humans. Mixed mosaics of agriculture that include crops, game and livestock farming should be encouraged and, providing lethal control is not ubiquitous in the landscape, chains of safer spaces should permit vital landscape connectivity. However, continuing to promote non-lethal mitigation techniques remains vital.