bluuebunny/crossref_metadata_2025_split huggingface dataset:
Measuring age-dependent viscoelasticity of organelles, cells and organisms with time-shared optical tweezer microrheology
Authors: Català-Castro Frederic , Ortiz-Vásquez Santiago , Martínez-Fernández Carmen , Pezzano Fabio , Garcia-Cabau Carla , Fernández-Campo Martín , Sanfeliu-Cerdán Neus , Jiménez-Delgado Senda , Salvatella Xavier , Ruprecht Verena , Frigeri Paolo-Antonio , Krieg Michael 
Published: January 2025

AbstractQuantifying the mechanical response of the biological milieu (such as the cell’s interior) and complex fluids (such as biomolecular condensates) would enable a better understanding of cellular differentiation and aging and accelerate drug discovery. Here we present time-shared optical tweezer microrheology to determine the frequency- and age-dependent viscoelastic properties of biological materials. Our approach involves splitting a single laser beam into two near-instantaneous time-shared optical traps to carry out simultaneous force and displacement measurements and quantify the mechanical properties ranging from millipascals to kilopascals across five decades of frequency. To create a practical and robust nanorheometer, we leverage both numerical and analytical models to analyse typical deviations from the ideal behaviour and offer solutions to account for these discrepancies. We demonstrate the versatility of the technique by measuring the liquid–solid phase transitions of MEC-2 stomatin and CPEB4 biomolecular condensates, and quantify the complex viscoelastic properties of intracellular compartments of zebrafish progenitor cells. In Caenorhabditis elegans, we uncover how mutations in the nuclear envelope proteins LMN-1 lamin A, EMR-1 emerin and LEM-2 LEMD2, which cause premature aging disorders in humans, soften the cytosol of intestinal cells during organismal age. We demonstrate that time-shared optical tweezer microrheology offers the rapid phenotyping of material properties inside cells and protein blends, which can be used for biomedical and drug-screening applications.
Local and regional food production diversity are positively associated with household dietary diversity in rural Africa
Authors: Nguyen Thanh-Tung , Qaim Matin 
Published: January 2025

Abstract
Undernutrition and low dietary quality remain widespread issues in Africa. As most rural households in the region are involved in farming, the diversification of own farm production could improve their access to nutritious foods. Here we use representative panel data from six African countries to estimate this effect across different scales. We show that farm production diversity is positively associated with household dietary diversity—yet the average magnitude of the association is small, depends on the specific measure of production diversity and increases with distance from urban centres. In all countries, markets and market access are more important for dietary diversity than own production. Because village-, town- and district-level production diversity are often positively associated with dietary diversity, higher diversity on each individual farm may not be required. The appropriate spatial scale should be considered when designing diversification strategies.
Seafood supply mapping reveals production and consumption mismatches and large dietary nutrient losses through exports in the United Kingdom
Authors: Löfstedt Anneli , Scheliga Bernhard , Aceves-Martins Magaly , de Roos Baukje 
Published: January 2025

AbstractSeafood can contribute towards healthy and sustainable food systems by improving public health and helping achieve net zero carbon emissions. Here, we provide a high-resolution perspective on UK seafood supplies and nutrient flows at the species level. We mapped seafood production (capture and aquaculture), trade (imports and exports), purchases (within and out of home) and seafood consumption between 2009 and 2020. UK dietary recommendations for finfish consumption were not achieved by domestic production nor national supplies. Mapping dietary nutrient flows revealed that the UK undergoes substantial losses of omega-3 fatty acids, vitamin B12 and vitamin D, which could contribute 73%, 46% and 7% towards UK-recommended nutrient intakes, respectively, through exports of oily fish such as salmon, herring and mackerel. Policies should consider promoting greater consumption of locally produced oily fish species to improve public health and seafood system resilience.
Photo-induced nitroxyl anion/HNO release from a nitrosyl complex of Mn(ii)–porphyrinate
Authors: Saha Shankhadeep , Maity Sayani , Samanta Bapan , Ghosh Riya , Bhattacharyya Kalishankar , Mondal Biplab 
Published: January 2025

A nitrosyl complex of Mn(ii)-porphyrinate, 1, [Mn(TTMPP2−)(NO)], in dichloromethane solution at −40 °C, in the presence of visible light was found to donate nitroxyl anion (NO−) to suitable acceptors.
l1‐ATSXKF‐based state and bias estimation for non‐linear systems with non‐Gaussian process noise
Authors: Yang Boyu , Chen Xueqin , Wu Fan , Liu Ming 
Published: January 2025

AbstractTo solve the problem of state and bias estimation for the non‐linear system with non‐Gaussian noise terms, a series of exogenous Kalman filters (XKF)‐based state and bias estimation algorithms are proposed. First, a non‐linear system model with bias and non‐Gaussian process noise is established. Second, the l1 norm is incorporated into the two‐stage exogenous Kalman filter (TSXKF) algorithm, known as the l1‐TSXKF, to mitigate the effect of non‐Gaussian process noise. Considering the uncertainty in the system transition model, adaptive factors are introduced into the Kalman filter, known as the adaptive Kalman filter algorithm, to enhance the estimation accuracy by modifying the predicted state covariance. Then, the l1 norm adaptive two‐stage exogenous Kalman filter (l1‐ATSXKF) algorithm is designed by combining the advantages of the l1 norm, adaptive factors and XKF in dealing with non‐Gaussian process noise, model uncertainty and state/bias simultaneous estimation, respectively. Finally, the simulation results show that the proposed algorithms can reduce the influence of the non‐Gaussian characteristics of the system and obtain high‐precision attitude and bias estimation results quickly in the process of satellite attitude manoeuvre, which is conducive to the application of satellite in orbit.
SGD-SLAM: a visual SLAM system with a dynamic feature rejection strategy combining semantic and geometric information for dynamic environments
Authors: Chen Yuqian , Lu Tongwei 
Published: January 2025

Abstract
Simultaneous localization and mapping (SLAM) is a key technology for mobile robots to perform localization and navigation in unknown environments. The majority of existing visual SLAM systems are predicated on the assumption of a static scene, which can result in suboptimal performance, reduced accuracy, and diminished system robustness in complex dynamic environments. In this paper, we propose SGD-SLAM, an improved SLAM system developed on the ORB-SLAM2 framework, designed for complex dynamic scenes. The system proffers a newly devised methodology that integrates semantic data with geometric data to address challenges to dynamic scenes. First, real-time instance segmentation algorithms are used to obtain semantic information about the surrounding environment and identify prior dynamic objects. Then, epipolar constraints are employed to find potential dynamic points, while the density-based spatial clustering of applications with noise clustering algorithm is used to group dynamic points into different clusters and compute the centers of these clusters to obtain geometric information. Finally, a dynamic feature rejection strategy is implemented, combining both semantic and geometric information, to exclude dynamic feature points. The system is tested and evaluated using the TUM dataset. The outcomes illustrate that, in dynamic scenes, the SGD-SLAM system outperforms existing algorithms with respect to enhanced accuracy and robustness.
The evolution of ChatGPT for programming: a comparative study
Authors: Jain Rushabh , Thanvi Jyoti , Subasinghe Akila 
Published: January 2025

Abstract
The introduction of Transformer models has significantly advanced natural language processing, with the development of Large Language Models (LLMs) like GPT-4 and Gemini revolutionizing industries by automating programming tasks. However, challenges remain regarding their ability to fully replace human programmers, especially in terms of efficiency and handling complex problems. This study aims to evaluate the performance of GPT models in solving algorithmic problems across three programming languages—Python, Java, and C++. It focuses on assessing runtime and memory efficiency to provide insights into the capabilities and limitations of LLMs in practical programming tasks. We selected 15 LeetCode problems categorized by difficulty and instructed GPT-3.5, GPT-4, and GPT-4o to generate solutions in Python, Java, and C++. Code was generated and executed 10 times for each problem, measuring runtime and memory usage. Statistical analyses, including two-way ANOVA and post hoc Tukey’s HSD tests, were conducted to evaluate the results. The findings indicate that programming language has a significant effect on memory and runtime efficiency, with C++ outperforming Python and Java. However, there were no statistically significant differences in performance between GPT-3.5, GPT-4, and GPT-4o across most tasks. Python was found to be significantly slower and more memory-intensive compared to C++ and Java. While GPT models show promise in assisting with programming tasks, their practical utility remains limited, particularly for complex problems. Improvements in newer GPT models do not always translate into significant performance gains. The choice of programming language plays a crucial role in optimizing LLM-generated code, suggesting that LLMs are better suited for augmenting human programmers rather than replacing them in critical tasks.
Chaucer’s Ethical Philosophy
Authors: Ashe Laura 
Published: January 2025

Abstract
Chaucer’s Ethical Philosophy reads Chaucer in new ways, revealing his deep engagement with the most urgent questions of modern political and ethical philosophy. The book offers original readings of Troilus and Criseyde, the Canterbury Tales, and the Book of the Duchess, placing Chaucer in close dialogue not only with medieval philosophy and theology, and his great European literary sources (Boccaccio, Dante, Guillaume de Machaut), but also with some major figures and concepts of modern philosophical thought (Hegel, Levinas, Wittgenstein, Butler; recognition, subjectivity, gender). It thereby illuminates his use of distinctively medieval forms and structures of narrative to explore ideas and develop philosophies that we have been conditioned to think of as exclusively modern. Chaucer’s fictional experiments are shown to be as philosophically complex and ethically powerful as anything in current thought.
Facial Emotion Recognition and its Associations With Psychological Well-Being Across Four Schizotypal Dimensions: a Cross-Sectional Study
Authors: Karamaouna Penny , Zouraraki Chrysoula , Economou Elias , Bitsios Panos , Giakoumaki Stella G 
Published: January 2025

Abstract

Objective
The present study aimed to examine facial emotion recognition in a sample from the general population with elevated schizotypal traits, as defined by the four-factor model of schizotypy, and the association of facial emotion recognition and the schizotypal dimensions with psychological well-being.

Method
Two hundred and thirty-eight participants were allocated into four schizotypal groups and one control group. Following a cross-sectional study design, facial emotion recognition was assessed with a computerized task that included images from the Radboud Faces Database, schizotypal traits were measured with the Schizotypal Personality Questionnaire, and psychological well-being was evaluated with the Flourishing scale.

Results
The results revealed distinct patterns of performance across the schizotypal groups and the application of a dimensional approach that included all participants as one group indicated specific associations between the four schizotypal dimensions and psychological well-being. Specifically, (a) negative schizotypes showed poor identification of sadness and fear potentially due to the activation of coping mechanisms, (b) disorganized schizotypes inaccurately recognized surprise, possibly reflecting the effects of disorganized thought on distinguishing this ambiguous emotion, and (c) psychological well-being was predicted by high cognitive-perceptual along with low negative and disorganized schizotypy as well as the accurate recognition of specific emotional states that are common in daily social interactions.

Conclusions
In conclusion, the study findings further advance the identification of emotion-processing difficulties in schizophrenia-vulnerable individuals and further highlight the need for highly personalized early intervention strategies.
Structured feature ranking for genomic marker identification accommodating multiple types of networks
Authors: Ge Yeheng , Li Tao , Feng Xingdong , Wu Mengyun , Liu Hailong 
Published: January 2025

ABSTRACT
Numerous statistical methods have been developed to search for genomic markers associated with the development, progression, and response to treatment of complex diseases. Among them, feature ranking plays a vital role due to its intuitive formulation and computational efficiency. However, most of the existing methods are based on the marginal importance of molecular predictors and share the limitation that the dependence (network) structures among predictors are not well accommodated, where a disease phenotype usually reflects various biological processes that interact in a complex network. In this paper, we propose a structured feature ranking method for identifying genomic markers, where such network structures are effectively accommodated using Laplacian regularization. The proposed method innovatively investigates multiple network scenarios, where the networks can be known a priori and data-dependently estimated. In addition, we rigorously explore the noise and uncertainty in the networks and control their impacts with proper selection of tuning parameters. These characteristics make the proposed method enjoy especially broad applicability. Theoretical result of our proposal is rigorously established. Compared to the original marginal measure, the proposed network structured measure can achieve sure screening properties with a faster convergence rate under mild conditions. Extensive simulations and analysis of The Cancer Genome Atlas melanoma data demonstrate the improvement of finite sample performance and practical usefulness of the proposed method.
Modified intralesional aciclovir treatment in the management of recalcitrant palmoplantar and ungual warts: a case series of 14 patients
Authors: Agarwal Akash , Bansal Parul , Madhual Subhasree , Panda Maitreyee 
Published: January 2025

Abstract
In this retrospective study, we evaluated the efficacy and safety of modified intralesional aciclovir for the treatment of recalcitrant palmoplantar and ungual warts in 14 patients (7 men and 7 women) of mean age 24.5 years (SD 8.19). Modified aciclovir (50 mg mL–1) was prepared by mixing 250 mg of lyophilized aciclovir powder with 4 mL of distilled water and 1 mL of 2% lignocaine. Then, this solution was injected into each wart at a dose of 0.1 mL or until blanching occurred. Every 2 weeks, the eschar was pared off and the treatment was repeated until a complete cure was observed, for a maximum of five sessions. After five sessions, 82% (n = 55/67) of warts showed a complete response, and 18% (n = 12/67) showed a partial response. Adverse effects reported included lesional tenderness for 2–3 days following injection in 23% (n = 3/13) of patients. Blistering and nail-plate damage were each seen in one patient. Modifying aciclovir treatment by adding lignocaine resulted in an unaltered concentration of aciclovir while maintaining its efficacy. The efficacy and safety were comparable with those reported for previous studies but with greater patient acceptability.
Mouse CD8+ T cell subsets differentially generate IL-17-expressing cells in the colon epithelium and lamina propria
Authors: Ge Cunjin , Tong Qiaoyun , Zheng Shihua , Liu Lei , Tian Lugao , Luo Hesheng 
Published: January 2025

Abstract
Colon-resident CD8+ T cells actively contribute to gut homeostasis and the pathogenesis of inflammatory bowel disease. However, their heterogeneity in generating IL-17-expressing CD8+ T cells, i.e. Tc17 cells, has not been thoroughly revealed. This study aims to characterize the abilities of mouse colonic intraepithelial (IE) and lamina propria (LP) CD8+ T cell subsets to differentiate into Tc17 cells. Using flow cytometry, we found that normal TCRβ+CD4–CD8αα+ cells (CD8αα T cells) and TCRβ+CD4–CD8αβ T cells, (CD8αβ T cells), either IE or LP, expressed abundant granzymes and IFN-γ but minute IL-17A. Under the in vitro Tc17-inducing condition, IE CD8αα T cells showed the weakest Tc17 differentiation ability and LP CD8αβ T cells exhibited the strongest Tc17 differentiation ability, whereas IE CD8αβ T cells and LP CD8αα T cells demonstrated moderate Tc17 differentiation abilities. The expression of IL-6 receptor, TGF-β receptor, TCR signaling indicators, CD161, and IL-23 receptor was low in IE CD8αα T cells, median in IE CD8αβ T cells and LP CD8αα T cells, but high in LP CD8αβ T cells. IE CD8αα T cells weakly induced the expression of chemokines, cytokines, and host defense mediators in colonic epithelial cells while LP CD8αβ T cells showed a robust up-regulatory effect. Furthermore, these colonic CD8+ T cell subsets also exhibited different abilities to generate Tc17 cells in inflamed colons. Collectively, LP CD8αβ T cells have the strongest Tc17 differentiation ability and might play a more significant role than the other subsets in Tc17-mediated immunity or inflammation in the colon.
Exploring symptom clusters and core symptoms during the vulnerable phase in patients with chronic heart failure: a network-based analysis
Authors: Bian Zekun , Shang Bin , Luo Caifeng , Lv Fei , Sun Weiyi , Gong Yijing , Liu Jun 
Published: January 2025

Abstract

Aims
To construct a symptom network of chronic heart failure patients in the vulnerable period and identify core symptoms and bridge symptoms between different symptom clusters.

Methods and results
A convenience sampling method was used to select 402 patients with chronic heart failure within 3 months after discharge from the cardiology departments of two tertiary-level A hospitals in Zhenjiang City, and symptom-related entries of the Minnesota living with heart failure questionnaire (MLHFQ) were used to conduct the survey. Symptom networks were constructed using the R language. The constructed symptom network was structurally stable, and the correlation stability coefficient was 0.595. In the network, ‘depression’ (MLHFQ9), ‘dyspnoea on exertion’ (MLHFQ3), and ‘worry’ (MLHFQ7) are the core symptoms. ‘Cognitive problems’ (MLHFQ8), ‘sleep difficulties’ (MLHFQ4), and ‘fatigue’ (MLHFQ6) are bridge symptoms connecting the emotional-cognitive and somatic symptom clusters. In the network comparison test, there were no significant differences in symptom networks between patients of different genders and places of residence.

Conclusion
‘Depression’ and ‘increased need to rest’ are the core and most severe symptoms, respectively, in the vulnerable phase of chronic heart failure, and ‘cognitive problems’ is the most important bridge symptom. Clinical caregivers can build a precise intervention programme based on the core and bridge symptoms and focus on the emotional and cognitive symptom clusters, in order to improve the efficacy of symptom management during the vulnerable period in patients with chronic heart failure.
Effect of interactive digital counselling on risk factors and lifestyle in patients with coronary artery disease: a systematic review and meta-analysis
Authors: Lahtinen Minna , Kaakinen Pirjo , Jansson Miia M , Paalimäki-Paakki Karoliina , Virtanen Mari , Kerimaa Heli , Kivelä Kirsi , Oikarinen Anne , Rajala Mira , Hylkilä Krista , Kääriäinen Maria 
Published: January 2025

Abstract

Aims
Digital counselling has gained paramount importance for coronary artery disease (CAD) patients’ treatment in recent years. It has been shown to provide a multitude of benefits, including improved risk factors and enhanced lifestyles. No previous reviews have emphasized the interactiveness of digital counselling. Consequently, the aim of this review is to determine whether interactive two-way digital counselling can provide effective secondary prevention as alternative or adjunct care compared with usual care, where patients visit a cardiac clinic and obtain verbal information and written recommendations of the risk factors without a digital intervention.

Methods and results
Studies that implemented digital interventions in patient counselling among CAD patients were identified by searching 10 electronic databases at the end of August 2022 and updated on 15 December 2023. The Joanna Briggs Institution (JBI) protocol was used for screening, quality assessment, data extraction, and meta-analysis. In total, 15 papers were identified that reported the effect of interactive digital counselling on risk factors and lifestyle changes in CAD patients. The results of the meta-analyses had neutral pre-defined outcomes and did not show any effect on cardiovascular risk factors or lifestyle changes.

Conclusion
There is a need for better descriptions of the content and delivery of interactive digital interventions in studies. In the future, digital interventions should be designed not only to focus on patient, but to incorporate social support, peer groups, and interactive tools on a digital platform. Social support has proved to be important in terms of adherence to treatment.

Registration
PROSPERO CRD42021247315.
Gerbils without Borders: Invasiveness, Plague, and Micro-Global Histories of Science, 1932-1939
Authors: Skotnes-Brown Jules , Silva Matheus Alves Duarte da 
Published: January 2025

Abstract
In the 1930s, a series of bubonic plague outbreaks among humans cropped up in several villages at the border of Angola and Namibia. These outbreaks provoked deep concern, laying bare social and political tensions amongst neighboring imperial powers and Indigenous people within the region. Despite the appearance of this disease in what was then considered a recondite place, its spread sparked debate in transnational forums, such as the League of Nations and the Office International d’Hygiène Publique. Drawing upon archival records in Namibia, South Africa, Portugal, the United States, and the United Kingdom, this article argues that concerns over the spread of plague across land borders led to the development of a nascent invasive species framework which indicted border-crossing “migrant” South African gerbils for the international spread of the disease. It follows the transnational political and scientific dynamics created by the plague “invasion” and discusses how these, like the gerbils, crossed numerous borders and scales. Ultimately, this article shows how localized inter-species and inter-imperial encounters can provide empirical insights into the feasibilities of a micro-global history of science in which more-than-human actors take on an important role.