bluuebunny/crossref_metadata_2025_split huggingface dataset:
Borderline personality disorder and stigma: Lived experience perspectives on helpful and hurtful language
Authors: van Schie Charlotte C. , Lewis Kate , Barr Karlen R. , Jewell Mahlie , Malcolmson Natalie , Townsend Michelle L. , Grenyer Brin F. S. 
Published: March 2024

AbstractBorderline personality disorder (BPD) is a severe mental health disorder that is subject to significant stigmatisation. With language being a key reinforcer of stigma, this co‐produced study aims to explore the language use regarding BPD and its effect on those with BPD and carers. Recommendations to reduce stigmatisation are provided for both clinicians and researchers. Participants with BPD (consumer n = 33) and those supporting someone with BPD (carer n = 30) discussed their experience of hurtful and helpful language. Reflexive thematic analysis was used to analyse written and verbal responses into core conflictual relationship themes (CCRT) reflecting how different words were heard and experienced. All consumers and carers in the study reported experiences with stigmatising language. Feelings of inadequacy and frustration were common amongst consumers, specifically when they perceived others as trivialising their needs or not seeing them as a unique individual. Carers often reported feelings of frustration when they perceived others as blaming them or not acknowledging their needs. Both consumers and carers reported helpful language as being connecting, validating and accepting. Unhelpful communication patterns have negative consequences for the person's self‐understanding (i.e., self‐stigma) and their relationships with others, including the therapeutic alliance. A consideration of these communication patterns may foster the use of reflective positive language that is compassionate and hopeful.
Efficient and accurate binding free energy calculation of Aβ9–40 protofilament propagation
Authors: Frost Christina V. , Schwierz Nadine , Zacharias Martin 
Published: March 2024

AbstractSelf‐assembled aggregation of peptides and proteins into regular amyloid fibrils is associated with several neurodegenerative diseases. In case of Alzheimer's disease proteolytic cleavage products of the amyloid precursor protein form pathological amyloid‐beta fibrils in a nucleation and propagation phase. The molecular details and thermodynamic driving forces of amyloid formation are not well understood, but are of high relevance for potential pharmacological interference. We used atomistic binding free energy simulations to calculate the free energy of protofilament propagation by an additional Aβ9–40 peptide binding to the protofilament tip. It requires sampling of relevant conformational transitions which is challenging since the monomeric Aβ9–40 peptide is intrinsically disordered. However, the convergence of umbrella simulations can be enhanced by applying additional restraining potentials on the axial, orientational and conformational degrees of freedom. The improved convergence leads to a much closer agreement with experimental binding free energy data compared to unrestrained umbrella sampling. Moreover, the restraining approach results in a separation of contributions to the total binding free energy. The calculated contributions indicate that the free energy change associated with the restriction of conformational freedom upon propagation makes a large opposing contribution of higher magnitude than the total binding free energy. Finally, optimization of the approach leads to further significant reduction of the computational demand which is crucial for systematic studies on mutations, denaturants and inhibitors in the fibril propagation step.
Effects of Bipolaris yamadae strain HXDC‐1‐2 as a bioherbicide against Echinochloa crus‐galli in rice and dry fields
Authors: Tan Min , Zhang Yuanhe , Zhang Yangjiao , Vurro Maurizio , Qiang Sheng 
Published: March 2024

AbstractBACKGROUNDBarnyardgrass (Weed Science Society of America recommended) or Barnyard grass (Britannica recommended) (Echinochloa crus‐galli (L.) P. Beauv.) is one of the most problematic and dominant weeds in world agricultural systems, especially in paddy fields, where tillering and grain yield can be reduced by 50–70% because of its competitive pressure. The frequent use of chemical herbicides to control E. crus‐galli has led to the evolution of herbicide resistance. Developing bioherbicides using pathogenic fungi to control E. crus‐galli could be an alternative option.RESULTSIn a previous study we showed that a strain of Bipolaris yamadae (HXDC‐1‐2) was promising in controlling gramineous weeds. Here we present a study that evaluated this fungus as a mycoherbicide against E. crus‐galli in greenhouse and paddy fields, characterized mycelium growth and conidial production, and examined the infection development. The median effective dose (ED50) and 90% effective dose (ED90) values of microcapsulated B. yamadae strain HXDC‐1‐2 on E. crus‐galli in the greenhouse were 7.17 × 102 and 9.35 × 103 conidia mL−1, respectively. Conidial germination, mycelial growth, and attachment formation occurred on E. crus‐galli leaves within 1 to 6 h. The hyphae directly invaded cells and stomata, primarily from the appressorium on the epidermis, and necrotic lesions were observed on the leaf surface within 20 to 24 h. Applied to E. crus‐galli plants at 1 × 105 conidia mL−1, the fungus reduced the weed's fresh weight of 75%.CONCLUSIONB. yamadae strain HXDC‐1‐2 has the potential to be developed as a bioherbicide against E. crus‐galli plants, especially in rice fields. © 2024 Society of Chemical Industry.
Pulmonary endarterectomy for chronic thromboembolic pulmonary hypertension with bronchial obstruction by a carcinoid tumor
Authors: Monden Yuki , Une Dai , Mitsumune Sho , Shimokawahara Hiroto , Okada Hirofumi , Yoshida Kenji , Kato Shutaro , Kamaguchi Suzuka , Nakai Mikizo , Ando Motomi 
Published: March 2024

AbstractPulmonary endarterectomy (PEA) is a standard treatment for chronic thromboembolic pulmonary hypertension (CTEPH). CTEPH combined with bronchial obstruction by a tumor is rare but should be assessed carefully because PEA for obstructed segments can be less therapeutic and make the subsequent surgical resection challenging. This report describes a case of CTEPH with bronchial obstruction by a typical carcinoid tumor in a 75‐year‐old man. On‐site evaluation and removal of the obstructive tumor were performed bronchoscopically, increasing the effectiveness of subsequent PEA for all affected pulmonary segments. This report illustrates a PEA strategy to treat CTEPH with bronchial tumor obstruction.
Robotics‐driven gait analysis: Assessing Azure Kinect's performance in in‐lab versus in‐corridor environments
Authors: Guffanti Diego , Brunete Alberto , Hernando Miguel , Álvarez David , Gambao Ernesto , Chamorro William , Fernández‐Vázquez Diego , Navarro‐López Víctor , Carratalá‐Tejada María , Miangolarra‐Page Juan Carlos 
Published: March 2024

AbstractGait analysis offers vital insights into human movement, aiding in the diagnosis, treatment, and rehabilitation of various conditions. Analyzing gait in corridors, rather than in lab, provides unique advantages for a more comprehensive understanding of human locomotion. However, limited dedicated technologies constrain gait data analysis in this context. In this study, a markerless gait analysis system using an Azure Kinect sensor mounted on a mobile robot is proposed and validated as a potential solution for gait analysis in corridors. Ten healthy participants (4 males and 6 females) underwent two tests. The first test (5 trials per participant) took place in the laboratory. Here, Azure Kinect performance was validated against a Vicon system, assessing eight gait signals and 22 gait parameters. The second test (2 trials per participant) was performed in the corridors over a 32‐m walking distance to compare this gait pattern with the one developed within the laboratory. The intrasession Intraclass Correlation Coefficient (ICC) reliability for in‐lab experiments was assessed by calculating the ICC between gait cycles captured in each session per participant. Notably, knee flexion/extension (ICC‐0.95), hip flexion/extension (ICC‐0.96), pelvis rotation (ICC‐0.88), and interankle distance (ICC‐0.98) demonstrated excellent reliability with high confidence. Similarly, hip adduction/abduction showed good reliability (ICC‐0.79), while trunk rotation exhibited moderate reliability (ICC‐0.72). In contrast, both trunk tilt (ICC‐0.24) and pelvis tilt (ICC‐0.41) consistently displayed lower reliability. This was observed for both the Vicon and the Azure systems, highlighting the intricate nature of capturing precise data for these specific signals in both systems. Validity outcomes indicated comparable error rates to literature standards ( knee flexion/extension, hip flexion/extension, and hip adduction/abduction), with 11 parameters having no significant differences from Vicon. Comparison of in‐lab and in‐corridor experiments show that individuals exhibit significantly longer stride time (1.10 s vs. 1.05 s), lower pelvis tilt ( vs. ), and lower minimum pelvis rotation ( vs. ) when walking in the laboratory. This study demonstrates promising outcomes in outdoor gait analysis with a robot‐mounted camera, revealing significant distinctions from controlled laboratory evaluations
Autonomous navigation and adaptive path planning in dynamic greenhouse environments utilizing improved LeGO‐LOAM and OpenPlanner algorithms
Authors: Yao Xingbo , Bai Yuhao , Zhang Baohua , Xu Dahua , Cao Guangzheng , Bian Yifan 
Published: March 2024

AbstractThe autonomous navigation of greenhouse robots depends on precise mapping, accurate localization information and a robust path planning strategy. However, the complex agricultural environment introduces significant challenges to robot perception and path planning. In this study, a hardware system designed exclusively for greenhouse agricultural environments is presented, employing multi‐sensor fusion to diminish the interference of complex environmental conditions. Furthermore, a robust autonomous navigation framework based on the improved lightweight and ground optimized lidar odometry and mapping (LeGO‐LOAM) and OpenPlanner has been proposed. In the perception phase, a relocalization module is integrated into the LeGO‐LOAM framework. Comprising two key steps—map matching and filtering optimization, it ensures a more precise pose relocalization. During the path planning process, ground structure and plant density are considered in our Enhanced OpenPlanner. Additionally, a hysteresis strategy is introduced to enhance the stability of system state transitions. The performance of the navigation system in this paper was evaluated in several complex greenhouse environments. The integration of the relocalization module significantly decreases the absolute pose error (APE) in the perception process, resulting in more accurate pose estimation and relocalization information. In our experiments, the APE was reduced by at least 24.42%. Moreover, our enhanced OpenPlanner exhibits the capability to plan safer trajectories and achieve more stable state transitions in the experiments. The results underscore the safety and robustness of our proposed approach, highlighting its promising application prospects in autonomous navigation for agricultural robots.
Development of a hazard risk map for assessing pedestrian risk in urban flash floods: A case study in Cúcuta, Colombia
Authors: Corzo Perez Gerald Augusto , Sanchez Tapiero Diego Ivan , Contreras Martínez Manuel Antonio , Zevenbergen Chris 
Published: March 2024

AbstractThe rapid growth of impervious areas in urban basins worldwide has increased the number of impermeable surfaces in cities, leading to severe flooding and significant economic losses for civilians. This trend highlights the urgent need for methodologies that assess flood hazards and specifically address the direct impact on pedestrians, which is often overlooked in traditional flood hazard analyses. This study aims to evaluate a methodology for assessing the risk to pedestrians from hydrodynamic forces during urban floods, with a specific focus on Cúcuta, Colombia. The methodology couples research outcomes from other studies on the impact of floodwaters on individuals of different ages and sizes with 1D/2D hydrological modeling. Advanced computational algorithms for image recognition were used to measure water levels at 5‐s intervals on November 6, 2020, using drones for digital elevation model data collection. In Cúcuta, where flood risk is high and drainage infrastructure is limited, the PCSWMM (Computer‐based Urban Stormwater Management Model) was calibrated and validated to simulate extreme flood events. The model incorporated urban infrastructure details and geomorphological parameters of Cúcuta's urban basin. Four return periods (5, 10, 50, 100), with extreme rainfall of 3 h, were used to estimate the variability of the risk map. The output of the model was analyzed, and an integrated and time‐varying comparison of the results was done. Results show that the regions of high‐water depth and high velocity could vary significantly along the duration of the different extreme events. Also, from 5 to 100 years return period, the percentage of area at risk increased from 9.6% to 16.6%. The pedestrian sensitivity appears much higher than the increase in velocities or water depth individually. This study identified medium to high‐risk locations, which are dynamic in time. We can conclude dynamics are spatiotemporal, and the added information layer of pedestrians brings vulnerability information that is also dynamic. Areas of immediate concern in Cúcuta can enhance pedestrian safety during flash flood events. The spatiotemporal variation of patterns requires further studies to map trajectories and sequences that machine learning models could capture.
N2O consumption, uptake, and microbial reduction processes in flooded sandy loamy paddy soils
Authors: Wang Wei , Li Kun , Li Jun , Zhong Jinmei , Xia Lei , Chen Wenqin , Li Zhaohua , Wang Ling 
Published: March 2024

AbstractSandy loamy soils are widely distributed in fluvial floodplains and experience flooding events frequently, resulting in a large amount of nitrous oxide (N2O) emissions. This case is more serious when the soil use is changed to paddies. It is of great significance to figure out the N2O consumption and its influencing factors in sandy loamy paddy soils to mitigate N2O emissions. In this study, three sandy loamy paddy soils (0–5 cm) originated from lake deposits were selected (S1, S2, and S3) as objectives. A certain concentration of exogenous N2O was added at the bottom of the flooded soil column to monitor the dynamics of N2O and nitrogen (N2) on the soil surface. Total N2O consumption, N2O uptake, and N2 production were quantified, and the abundance of nitrous oxide reductase genes (nosZI, and nosZII) and other soil properties (ammonium‐nitrogen, nitrate‐nitrogen, and dissolved organic carbon [DOC] content) were analyzed. The results showed that the sandy loamy paddy soil column with a depth of 0–5 cm could intercept more than 95% of the exogenous N2O under the flooded anaerobic condition, indicating that the three sandy loamy paddy soils all had extremely strong N2O consumption capacities. And the increment of N2 accounted for 68.73%–76.09% of the total N2O consumption, which had a stronger relationship with the increase of nosZI gene abundance than nosZII gene. In addition, the total N2O consumption and N2 increment of S1 and S3 soils were significantly higher than those of S2 soil. This difference was mainly related to soil organic matter content, total nitrogen content, DOC consumption, and the increase of nosZI gene abundance (p < 0.05). The strong N2O consumption potential of sandy loamy soils can provide feasible solutions for regulating N2O emissions in a wide range of similar environments in fluvial floodplains.
Tailored (La0.2Pr0.2Nd0.2Tb0.2Dy0.2)2Ce2O7 as a Highly Active and Stable Nanocatalyst for the Oxygen Evolution Reaction
Authors: Paladugu Sreya , Abdullahi Ibrahim Munkaila , Jothi Palani Raja , Jiang Bo , Nath Manashi , Page Katharine 
Published: March 2024

AbstractDesigning highly active and robust catalysts for the oxygen evolution reaction is key to improving the overall efficiency of the water splitting reaction. It has been previously demonstrated that evaporation induced self‐assembly (EISA) can be used to synthesize highly porous and high surface area cerate‐based fluorite nanocatalysts, and that substitution of Ce with 50% rare earth (RE) cations significantly improves electrocatalyst activity. Herein, the defect structure of the best performing nanocatalyst in the series are further explored, Nd2Ce2O7, with a combination of neutron diffraction and neutron pair distribution function analysis. It is found that Nd3 + cation substitution for Ce in the CeO2 fluorite lattice introduces higher levels of oxygen Frenkel defects and induces a partially reduced RE1.5Ce1.5O5 + x phase with oxygen vacancy ordering. Significantly, it is demonstrated that the concentration of oxygen Frenkel defects and improved electrocatalytic activity can be further enhanced by increasing the compositional complexity (number of RE cations involved) in the substitution. The resulting novel compositionally‐complex fluorite– (La0.2Pr0.2Nd0.2Tb0.2Dy0.2)2Ce2O7 is shown to display a low OER overpotential of 210 mV at a current density of 10 mAcm−2 in 1M KOH, and excellent cycling stability. It is suggested that increasing the compositional complexity of fluorite nanocatalysts expands the ability to tailor catalyst design.
Alternatives to Fluoropolymers for Motion‐Based Energy Harvesting: Perspectives on Piezoelectricity, Triboelectricity, Ferroelectrets, and Flexoelectricity
Authors: Sherrell Peter C. , Šutka Anna , Timusk Martin , Šutka Andris 
Published: March 2024

AbstractFluoropolymers, including polytetrafluoroethylene (PTFE, Teflon), polyvinylidene difluoride (PVDF), and fluorine kautschuk materials (FKMs, Viton) are critical polymers for applications ranging from non‐stick coatings, corrosion resistant seals, semiconductor manufacturing, membranes, and energy harvesting technologies. However, the synthesis of these fluoropolymers requires the use of per‐ and polyfluorinated alkyl substances (PFAS) known colloquially as “forever chemicals,” and as such there is a pressing need to develop alternative technologies that can serve the end‐use of fluoropolymers without the environmental cost of using PFAS. Further, fluoropolymers themselves fall under the PFAS umbrella. Here, alternative mechanical‐to‐electrical energy harvesting polymers are reviewed and benchmarked against the leading fluoropolymer energy harvesters. These alternative technologies include nonfluoropolymer piezoelectric polymers, triboelectric nanogenerators (TENGs), ferroelectric elastomers, and flexoelectric polymers. A vision towards sustainable, non‐fluoropolymer‐based energy harvesting is provided.
RETRACTED: Refining molecular subtypes and risk stratification of ovarian cancer through multi‐omics consensus portfolio and machine learning
Authors: Zhang Jing , He Shanshan , Ying Hongjun 
Published: March 2024

AbstractOvarian cancer (OC), known for its pronounced heterogeneity, has long evaded a unified classification system despite extensive research efforts. This study integrated five distinct multi‐omics datasets from eight multicentric cohorts, applying a combination of ten clustering algorithms and ninety‐nine machine learning models. This methodology has enabled us to refine the molecular subtyping of OC, leading to the development of a novel Consensus Machine Learning‐driven Signature (CMLS). Our analysis delineated two prognostically significant cancer subtypes (CS), each marked by unique genetic and immunological signatures. Notably, CS1 is associated with an adverse prognosis. Leveraging a subtype classifier, we identified five key genes (CTHRC1, SPEF1, SCGB3A1, FOXJ1, and C1orf194) instrumental in constructing the CMLS. Patients classified within the high CMLS group exhibited a poorer prognosis and were characterized by a “cold tumor” phenotype, indicative of an immunosuppressive microenvironment rich in MDSCs, CAFs, and Tregs. Intriguingly, this group also presented higher levels of tumor mutation burden (TMB) and tumor neoantigen burden (TNB), factors that correlated with a more favorable response to immunotherapy compared to their low CMLS counterparts. In contrast, the low CMLS group, despite also displaying a “cold tumor” phenotype, showed a favorable prognosis and a heightened responsiveness to chemotherapy. This study's findings underscore the potential of targeting immune‐suppressive cells, particularly in patients with high CMLS, as a strategic approach to enhance OC prognosis. Furthermore, the redefined molecular subtypes and risk stratification, achieved through sophisticated multi‐omics analysis, provide a framework for the selection of therapeutic agents.
Integrated analysis of gut microbiota and metabolomic profiling in colorectal cancer metastasis
Authors: Xia Yang , Duan Ling , Zhang Xin‐lian , Niu Yu‐juan , Ling Xiaoling 
Published: March 2024

AbstractColorectal cancer (CRC) is characterized by its heterogeneity and complex metastatic mechanisms, presenting significant challenges in treatment and prognosis. This study aimed to unravel the intricate interplay between the gut microbiota and metabolic alterations associated with CRC metastasis. By employing high‐throughput sequencing and advanced metabolomic techniques, we identified distinct patterns in the gut microbiome and fecal metabolites across different CRC metastatic sites. The differential gene analysis highlighted significant enrichment in biological processes related to immune response and extracellular matrix organization, with key genes playing roles in the complement and clotting cascades, and staphylococcus aureus infections. Protein–protein interaction networks further elucidated the potential mechanisms driving CRC spread, emphasizing the importance of extracellular vesicles and the PPAR signaling pathway in tumor metastasis. Our comprehensive microbiota analysis revealed a relatively stable alpha diversity across groups but identified specific bacterial genera associated with metastatic stages. Metabolomic profiling using OPLS‐DA models unveiled distinct metabolic signatures, with differential metabolites enriched in pathways crucial for cancer metabolism and immune modulation. Integrative analysis of the gut microbiota and metabolic profiles highlighted significant correlations, suggesting a complex interplay that may influence CRC progression and metastasis. These findings offer novel insights into the microbial and metabolic underpinnings of CRC metastasis, paving the way for innovative diagnostic and therapeutic strategies targeting the gut microbiome and metabolic pathways.