bluuebunny/crossref_metadata_2025_split huggingface dataset:
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

AbstractAssociation 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

AbstractThe 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

AbstractCrohn 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

AbstractOvarian 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

AbstractThe 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

AbstractAspergillus 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

AbstractPrecisely 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

AbstractIn 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

AbstractMaturity 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

AbstractAlthough 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

AbstractDigital 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

AbstractProtected 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.
Turbulence-induced droplet grouping and augmented rain formation in cumulus clouds
Authors: Gumber Siddharth , Bera Sudarsan , Ghosh Satyajit , Prabhakaran Thara V. 
Published: May 2024

AbstractThis paper provides the first observational analysis of how droplet separation is impacted by the flinging action of microscale vortices in turbulent clouds over a select radii range and how they vary over cloud cores and along the peripheral edges. It is premised that this mechanism initiates droplet separation within a cloud volume soon after condensational growth, largely in the cloud core, and operates until the cloud droplet radii exceed 20–30 µm when this effect fades rapidly. New observations are presented showing how microscale vortices also impact the settling rates of droplets over a critical size range (6–18 µm) causing them to sediment faster than in still air affecting swept volumes and thereby impacting the rain initiation and formation. Large-scale atmospheric models ignore these microscale effects linked to rapid droplet growth during the early stages of cloud conversion. Previous studies on droplet spatial organization along the cloud edges and inside the deep core have shown that homogeneous Poisson statistics, indicative of the presence of a vigorous in-cloud mixing process at small scales obtained, in contrast to an inhomogeneous distribution along the edges. In this paper, it is established that this marked core region, homogeneity can be linked to microscale vortical activity which flings cloud droplets in the range of 6–18 µm outward. The typical radius of the droplet trajectories or the droplet flung radii around the vortices correlates with the interparticle distance strongly. The correlation starts to diminish as one proceeds from the central core to the cloud fringes because of the added entrainment of cloud-free air. These first results imply that droplet growth in the core is first augmented with this small-scale interaction prior to other more large-scale processes involving entrainment mixing. This first study, combining these amplified velocities are included in a Weather Research and Forecasting- LES case study. Not only are significant differences observed in the cloud morphology when compared to a baseline case, but the ‘enhanced’ case also shows early commencement of rainfall along with intense precipitation activity compared to the ‘standard’ baseline case. It is also shown that the modelled equilibrium raindrop spectrum agrees better with observations when the enhanced droplet sedimentation rates mediated by microscale vortices are included in the calculations compared to the case where only still-air terminal velocities are used.
A rat-based preclinical platform facilitating transcatheter hepatic arterial infusion in immunodeficient rats with liver xenografts of patient-derived pancreatic ductal adenocarcinoma
Authors: Ozaki Masanori , Kageyama Ken , Kimura Kenjiro , Eguchi Shinpei , Yamamoto Akira , Tanaka Ryota , Nota Takehito , Yonezawa Hiroki , Nishiofuku Hideyuki , Sakai Yuki , Tani Naoki , Jogo Atsushi , Terai Mizue , Sato Takami , Ishizawa Takeaki , Miki Yukio 
Published: May 2024

AbstractLiver metastases from pancreatic ductal adenocarcinoma (PDAC) are highly fatal. A rat-based patient-derived tumor xenograft (PDX) model is available for transcatheter therapy. This study aimed to create an immunodeficient rat model with liver xenografts of patient-derived primary PDAC and evaluate efficacy of hepatic arterial infusion chemotherapy with cisplatin in this model. Three patient-derived PDACs were transplanted into the livers of 21 rats each (totally, 63 rats), randomly assigned into hepatic arterial infusion, systemic venous infusion, and control groups (n = 7 each) four weeks post-implantation. Computed tomography evaluated tumor volumes before and four weeks after treatment. Post-euthanasia, resected tumor specimens underwent histopathological examination. A liver-implanted PDAC PDX rat model was established in all 63 rats, with first CT identifying all tumors. Four weeks post-treatment, arterial infusion groups exhibited significantly smaller tumor volumes than controls for all three tumors on second CT. Xenograft tumors histologically maintained adenocarcinoma features compared to original patient tumors. Ki67 expression was significantly lower in arterial infusion groups than in the other two for the three tumors, indicating reduced tumor growth in PDX rats. A liver-implanted PDAC PDX rat model was established as a rat-based preclinical platform. Arterial cisplatin infusion chemotherapy represents a potential therapy for PDAC liver metastasis.