bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multilevel proteomic analyses reveal molecular diversity between diffuse-type and intestinal-type gastric cancer
Authors: Shi Wenhao , Wang Yushen , Xu Chen , Li Yan , Ge Sai , Bai Bin , Zhang Kecheng , Wang Yunzhi , Zheng Nairen , Wang Juan , Wang Shiqi , Ji Gang , Li Jipeng , Nie Yongzhan , Liang Wenquan , Wu Xiaosong , Cui Jianxin , Wang Yi , Chen Lin , Zhao Qingchuan , Shen Lin , He Fuchu , Qin Jun , Ding Chen 
Published: February 2023

AbstractDiffuse-type gastric cancer (DGC) and intestinal-type gastric cancer (IGC) are the major histological types of gastric cancer (GC). The molecular mechanism underlying DGC and IGC differences are poorly understood. In this research, we carry out multilevel proteomic analyses, including proteome, phospho-proteome, and transcription factor (TF) activity profiles, of 196 cases covering DGC and IGC in Chinese patients. Integrative proteogenomic analysis reveals ARIDIA mutation associated with opposite prognostic effects between DGC and IGC, via diverse influences on their corresponding proteomes. Systematical comparison and consensus clustering analysis identify three subtypes of DGC and IGC, respectively, based on distinct patterns of the cell cycle, extracellular matrix organization, and immune response-related proteins expression. TF activity-based subtypes demonstrate that the disease progressions of DGC and IGC were regulated by SWI/SNF and NFKB complexes. Furthermore, inferred immune cell infiltration and immune clustering show Th1/Th2 ratio is an indicator for immunotherapeutic effectiveness, which is validated in an independent GC anti-PD1 therapeutic patient group. Our multilevel proteomic analyses enable a more comprehensive understanding of GC and can further advance the precision medicine.
Ideal acoustic quantum spin Hall phase in a multi-topology platform
Authors: Sun Xiao-Chen , Chen Hao , Lai Hua-Shan , Xia Chu-Hao , He Cheng , Chen Yan-Feng 
Published: February 2023

AbstractFermionic time-reversal symmetry ($${T}_{f}$$

T

f

)-protected quantum spin Hall (QSH) materials feature gapless helical edge states when adjacent to arbitrary trivial cladding materials. However, due to symmetry reduction at the boundary, bosonic counterparts usually exhibit gaps and thus require additional cladding crystals to maintain robustness, limiting their applications. In this study, we demonstrate an ideal acoustic QSH with gapless behaviour by constructing a global Tf on both the bulk and the boundary based on bilayer structures. Consequently, a pair of helical edge states robustly winds several times in the first Brillouin zone when coupled to resonators, promising broadband topological slow waves. We further reveal that this ideal QSH phase behaves as a topological phase transition plane that bridges trivial and higher-order phases. Our versatile multi-topology platform sheds light on compact topological slow-wave and lasing devices.
A three-dimensional antifungal wooden cone evaporator for highly efficient solar steam generation
Authors: Xie Meihua , Zhang Ping , Cao Yizhong , Yan Yutao , Wang Zhe , Jin Chunde 
Published: February 2023

AbstractInterfacial solar energy evaporation is an effective measure to alleviate the current global shortage of clean water resources. However, many solar evaporators are two-dimensional (2D) structured devices developed by coating light-absorbing materials on the surface of host materials, and the efficiency of solar steam generation is limited. For this reason, the present study reports a facile and environment-friendly method to construct a conical three-dimensional (3D) wooden evaporator, which uses flexible wood as the substrate and tannic acid complex as the light-absorbing material and is formed by further convolution. Reasonable structural design and material combination enable the evaporator to show excellent mildew resistance and highly efficient evaporation performance. The black decoration considerably improves the wood light absorption, resulting in high absorbance (>90%) of DW-TA-Fe3+ in the wavelength range of 200–800 nm. The water evaporation rate of the wooden cone evaporator can reach up to 1.79 kg m−2 h−1, about 1.6 times higher than that of the 2D evaporator. Moreover, the evaporator exhibits outstanding biological stability and effective desalination performance. This work is expected to offer a new direction in designing a 3D wooden evaporator for effective solar water desalination.
Potential benefits of public–private partnerships to improve the efficiency of urban wastewater treatment
Authors: Cheng Shulei , Yu Yu , Meng Fanxin , Chen Jiandong , Chen Yongtao , Liu Gengyuan , Fan Wei 
Published: February 2023

AbstractFor emerging economies lacking public budgets, continuous improvement of urban wastewater treatment efficiency (UWTE) requires effective government supervision of wastewater treatment infrastructures (WTIs) and participation of private capital seeking to profit-maximising. However, to what extent this public–private partnership (PPP) model, aimed at a reasonable sharing of benefit and risk, in delivering WTIs can improve the UWTE is unknown. We evaluated the impact of the PPP model on the UWTE by collecting data from 1303 urban wastewater treatment PPP projects in 283 prefecture-level cities in China from 2014 to 2019 and used data envelopment analysis and Tobit regression model. The UWTE was significantly higher in prefecture-level cities that introduced the PPP model in the construction and operation of WTIs, particularly those with a feasibility gap subsidy, competitive procurement, privatised operation, and non-demonstration. Moreover, the effects of PPPs on UWTE were limited by the economic development level, marketisation, and climatic conditions.
Quantifying the physical processes leading to atmospheric hot extremes at a global scale
Authors: Röthlisberger Matthias , Papritz Lukas 
Published: February 2023

AbstractHeat waves are among the deadliest climate hazards. Yet the relative importance of the physical processes causing their near-surface temperature anomalies (𝑇′)—advection of air from climatologically warmer regions, adiabatic warming in subsiding air and diabatic heating—is still a matter of debate. Here we quantify the importance of these processes by evaluating the 𝑇′ budget along air-parcel backward trajectories. We first show that the extreme near-surface 𝑇′ during the June 2021 heat wave in western North America was produced primarily by diabatic heating and, to a smaller extent, by adiabatic warming. Systematically decomposing 𝑇′ during the hottest days of each year (TX1day events) in 1979–2020 globally, we find strong geographical variations with a dominance of advection over mid-latitude oceans, adiabatic warming near mountain ranges and diabatic heating over tropical and subtropical land masses. In many regions, however, TX1day events arise from a combination of these processes. In the global mean, TX1day anomalies form along trajectories over roughly 60 h and 1,000 km, although with large regional variability. This study thus reveals inherently non-local and regionally distinct formation pathways of hot extremes, quantifies the crucial factors determining their magnitude and enables new quantitative ways of climate model evaluation regarding hot extremes.
Early morning university classes are associated with impaired sleep and academic performance
Authors: Yeo Sing Chen , Lai Clin K. Y. , Tan Jacinda , Lim Samantha , Chandramoghan Yuvan , Tan Teck Kiang , Gooley Joshua J. 
Published: February 2023

AbstractAttending classes and sleeping well are important for students’ academic success. Here, we tested whether early morning classes are associated with lower attendance, shorter sleep and poorer academic achievement by analysing university students’ digital traces. Wi-Fi connection logs in 23,391 students revealed that lecture attendance was about ten percentage points lower for classes at 08:00 compared with later start times. Diurnal patterns of Learning Management System logins in 39,458 students and actigraphy data in 181 students demonstrated that nocturnal sleep was an hour shorter for early classes because students woke up earlier than usual. Analyses of grades in 33,818 students showed that the number of days per week they had morning classes was negatively correlated with grade point average. These findings suggest concerning associations between early morning classes and learning outcomes.
Genome-wide subcellular protein map for the flagellate parasite Trypanosoma brucei
Authors: Billington Karen , Halliday Clare , Madden Ross , Dyer Philip , Barker Amy Rachel , Moreira-Leite Flávia Fernandes , Carrington Mark , Vaughan Sue , Hertz-Fowler Christiane , Dean Samuel , Sunter Jack Daniel , Wheeler Richard John , Gull Keith 
Published: February 2023

AbstractTrypanosoma brucei is a model trypanosomatid, an important group of human, animal and plant unicellular parasites. Understanding their complex cell architecture and life cycle is challenging because, as with most eukaryotic microbes, ~50% of genome-encoded proteins have completely unknown functions. Here, using fluorescence microscopy and cell lines expressing endogenously tagged proteins, we mapped the subcellular localization of 89% of the T. brucei proteome, a resource we call TrypTag. We provide clues to function and define lineage-specific organelle adaptations for parasitism, mapping the ultraconserved cellular architecture of eukaryotes, including the first comprehensive ‘cartographic’ analysis of the eukaryotic flagellum, which is vital for morphogenesis and pathology. To demonstrate the power of this resource, we identify novel organelle subdomains and changes in molecular composition through the cell cycle. TrypTag is a transformative resource, important for hypothesis generation for both eukaryotic evolutionary molecular cell biology and fundamental parasite cell biology.
High-throughput microbial culturomics using automation and machine learning
Authors: Huang Yiming , Sheth Ravi U. , Zhao Shijie , Cohen Lucas A. , Dabaghi Kendall , Moody Thomas , Sun Yiwei , Ricaurte Deirdre , Richardson Miles , Velez-Cortes Florencia , Blazejewski Tomasz , Kaufman Andrew , Ronda Carlotta , Wang Harris H. 
Published: February 2023

AbstractPure bacterial cultures remain essential for detailed experimental and mechanistic studies in microbiome research, and traditional methods to isolate individual bacteria from complex microbial ecosystems are labor-intensive, difficult-to-scale and lack phenotype–genotype integration. Here we describe an open-source high-throughput robotic strain isolation platform for the rapid generation of isolates on demand. We develop a machine learning approach that leverages colony morphology and genomic data to maximize the diversity of microbes isolated and enable targeted picking of specific genera. Application of this platform on fecal samples from 20 humans yields personalized gut microbiome biobanks totaling 26,997 isolates that represented >80% of all abundant taxa. Spatial analysis on >100,000 visually captured colonies reveals cogrowth patterns between Ruminococcaceae, Bacteroidaceae, Coriobacteriaceae and Bifidobacteriaceae families that suggest important microbial interactions. Comparative analysis of 1,197 high-quality genomes from these biobanks shows interesting intra- and interpersonal strain evolution, selection and horizontal gene transfer. This culturomics framework should empower new research efforts to systematize the collection and quantitative analysis of imaging-based phenotypes with high-resolution genomics data for many emerging microbiome studies.
Relations of hippocampal subfields atrophy patterns with memory and biochemical changes in end stage renal disease
Authors: Jiang Yuhan , Gao Bingbing , Li Mingshuai , Liu Yangyingqiu , Li Yuan , Liu Na , Zhang Yukun , Song Qingwei , Wen Xinyu , Jiang Jian , Wang Weiwei , Wang Nan , Miao Yanwei 
Published: February 2023

AbstractEnd-stage renal disease (ESRD) results in hippocampal volume reduction, but the hippocampal subfields atrophy patterns cannot be identified. We explored the volumes and asymmetry of the hippocampal subfields and their relationships with memory function and biochemical changes. Hippocampal global and subfields volumes were derived from 33 ESRD patients and 46 healthy controls (HCs) from structural MRI. We compared the volume and asymmetric index of each subfield, with receiver operating characteristic curve analysis to evaluate the differentiation between ESRD and HCs. The relations of hippocampal subfield volumes with memory performance and biochemical data were investigated in ESRD group. ESRD patients had smaller hippocampal subfield volumes, mainly in the left CA1 body, left fimbria, right molecular layer head, right molecular layer body and right HATA. The right molecular layer body exhibited the highest accuracy for differentiating ESRD from HCs, with a sensitivity of 80.43% and specificity of 72.73%. Worse learning process (r = 0.414, p = 0.032), immediate recall (r = 0.396, p = 0.041) and delayed recall (r = 0.482, p = 0.011) was associated with left fimbria atrophy. The left fimbria volume was positively correlated with Hb (r = 0.388, p = 0.05); the left CA1 body volume was negatively correlated with Urea (r = − 0.469, p = 0.016). ESRD patients showed global and hippocampal subfields atrophy. Left fimbria atrophy was related to memory function. Anemia and Urea level may be associated with the atrophy of left fimbria and CA1 body, respectively.
Elucidation of the (R)-enantiospecific benzylisoquinoline alkaloid biosynthetic pathways in sacred lotus (Nelumbo nucifera)
Authors: Menéndez-Perdomo Ivette M. , Facchini Peter J. 
Published: February 2023

AbstractBenzylisoquinoline alkaloids (BIAs) are a structurally diverse group of plant specialized metabolites found mainly in members of the order Ranunculales, including opium poppy (Papaver somniferum), for which BIA biosynthetic pathways leading to the critical drugs morphine, noscapine, and sanguinarine have been elucidated. Sacred lotus (Nelumbo nucifera), in the order Proteales, accumulates medicinal BIAs in the proaporphine, aporphine, and bisbenzylisoquinoline structural subgroups with a prevalence of R enantiomers, opposed to the dominant S configuration occurring in the Ranunculales. Nevertheless, distinctive BIA biosynthetic routes in sacred lotus have not been explored. In planta labeling experiments and in vitro assays with recombinant enzymes and plant protein extracts showed that dopamine and 4-hydroxyphenylacetaldehyde derived from l-tyrosine serve as precursors for the formation of (R,S)-norcoclaurine in sacred lotus, whereas only (R)-norcoclaurine byproducts are favored in the plant by action of R-enantiospecific methyltransferases and cytochrome P450 oxidoreductases (CYPs). Enzymes responsible for the R-enantiospecific formation of proaporphine (NnCYP80Q1) and bisbenzylisoquinoline (NnCYP80Q2) scaffolds, and a methylenedioxy bridge introduction on aporphine substrates (NnCYP719A22) were identified, whereas additional aspects of the biosynthetic pathways leading to the distinctive alkaloid profile are discussed. This work expands the availability of molecular tools that can be deployed in synthetic biology platforms for the production of high-value alkaloids.
A logarithmically amortising temperature effect for supervised learning of wheat solar disinfestation of rice weevil Sitophilus oryzae (Coleoptera: Curculionidae) using plastic bags
Authors: Abdelsamea Mohammed M. , Gaber Mohamed Medhat , Ali Aliyuda , Kyriakou Marios , Fawki Shams 
Published: February 2023

AbstractThis work investigates the effectiveness of solar heating using clear polyethylene bags against rice weevil Sitophilus oryzae (L.), which is one of the most destructive insect pests against many strategic grains such as wheat. In this paper, we aim at finding the key parameters that affect the control heating system against stored grain insects while ensuring that the wheat grain quality is maintained. We provide a new benchmark dataset, where the experimental and environmental data was collected based on fieldwork during the summer in Canada. We measure the effectiveness of the solution using a novel formula to describe the amortising temperature effect on rice weevil. We adopted different machine learning models to predict the effectiveness of our solution in reaching a lethal heating condition for insect pests, and hence measure the importance of the parameters. The performance of our machine learning models has been validated using a 10-fold cross-validation, showing a high accuracy of 99.5% with 99.01% recall, 100% precision and 99.5% F1-Score obtained by the Random Forest model. Our experimental study on machine learning with SHAP values as an eXplainable post-hoc model provides the best environmental conditions and parameters that have a significant effect on the disinfestation of rice weevils. Our findings suggest that there is an optimal medium-sized grain amount when using solar bags for thermal insect disinfestation under high ambient temperatures. Machine learning provides us with a versatile model for predicting the lethal temperatures that are most effective for eliminating stored grain insects inside clear plastic bags. Using this powerful technology, we can gain valuable information on the optimal conditions to eliminate these pests. Our model allows us to predict whether a certain combination of parameters will be effective in the treatment of insects using thermal control. We make our dataset publicly available under a Creative Commons Licence to encourage researchers to use it as a benchmark for their studies.
Analysis of quantitative metrics for assessing resilience of human-centered CPPS workstations
Authors: Aruväli Tanel , De Marchi Matteo , Rauch Erwin 
Published: February 2023

AbstractManufacturing companies’ preparedness level against external and internal disruptions is complex to assess due to a lack of widely recognized or standardized models. Resilience as the measure to characterize preparedness against disruptions is a concept with various numerical approaches, but still lacking in the industry standard. Therefore, the main contribution of the research is the comparison of existing resilience metrics and the selection of the practically usable quantitative metric that allows manufacturers to start assessing the resilience in digitally supported human-centered workstations more easily. An additional contribution is the detection and highlighting of disruptions that potentially influence manufacturing workstations the most. Using five weighted comparison criteria, the resilience metrics were pairwise compared based on multi-criteria decision-making Analytic Hierarchy Process analysis on a linear scale. The general probabilistic resilience assessment method Penalty of Change that received the highest score considers the probability of disruptions and related cost of potential changes as inputs for resilience calculation. Additionally, manufacturing-related disruptions were extracted from the literature and categorized for a better overview. The Frequency Effect Sizes of the extracted disruptions were calculated to point out the most influencing disruptions. Overall, resilience quantification in manufacturing requires further research to improve its accuracy while maintaining practical usability.
The effect of postmenopausal osteoporosis on subchondral bone pathology in a rat model of knee osteoarthritis
Authors: Wada Hiroyuki , Aso Koji , Izumi Masashi , Ikeuchi Masahiko 
Published: February 2023

AbstractThis study aimed to investigate the additional effect of ovariectomy-induced osteoporosis (OP) on the pathology of knee osteoarthritis (OA) in a rat meniscectomized model, particularly focusing on subchondral bone changes and pain behaviour. Rats were divided into four groups, sham, OP, OA, OP plus OA, and assessed for histology, osteoclast activity, subchondral bone microstructure, and pain-related behaviour. Rats with OP plus OA had significantly increased calcified cartilage and subchondral bone damage scores, increased densities of subchondral osteoclasts in the weight-bearing area, and more porous subchondral trabecular bone compared with rats with OA. Loss of tidemark integrity was observed most frequently in rats with OP plus OA. The density of subchondral osteoclasts correlated with the calcified cartilage and subchondral bone damage score in rats with OA (OA and OP plus OA). No significant differences in the receptor activator of nuclear factor-kappa B ligand (RANKL)/osteoprotegerin (OPG) expression ratio in subchondral bone and pain-related behavioural tests were observed between rats with OA and rats with OP plus OA. In rats with OA, coexisting OP potentially aggravated OA pathology mainly in calcified cartilage and subchondral trabecular bone by increasing subchondral osteoclast activity.
Taguchi optimization and modelling of stir casting process parameters on the percentage elongation of aluminium, pumice and carbonated coal composite
Authors: Ibrahim Tanimu Kogi , Yawas Danjuma Saleh , Dan-asabe Bashar , Adebisi Adetayo Abdulmumin 
Published: February 2023

AbstractAluminium matrix composites, which are a subclass of metal matrix composites, have characteristics including low density, high stiffness and strength, better wear resistance, controlled thermal expansion, greater fatigue resistance, and improved stability at high temperatures. The scientific and industrial communities are interested in these composites because they may be used to manufacture a broad variety of components for cutting-edge applications. This has study observed how the stirring speed, processing temperature, and stirring duration of the stir casting process affected the percentage elongation of Al-Pumice (PP)-Carbonized Coal Particles (CCP) hybrid composites. It also looked at the optimal weight of these natural ceramic reinforcements using the Taguchi optimization technique. While optimizing the percentage elongation property, the hard compound such as silica, iron oxide, and alumina, were discovered during the characterisation of the reinforcement, showing that PP and CCP can be used as reinforcement in metal matrix composite. The percentage of elongation of the hybrid composite was shown to be most affected by the PP, followed by processing temperature, stirring speed, CCP, and stirring time, using stir casting process parameter optimization. It was observed at 2.5 wt% of pumice particles, 2.5 wt% of carbonated coal particles, 700 °C processing temperature, 200 rpm stirring speed, and 5 min stirring time, the optimum percentage of elongation was discovered to be 5.6%, which is 25.43% lower than the percentage elongation of Al-alloy without reinforcing. The regression study developed a predictive mathematical model for the percentage elongation (PE) as a function of the stir casting process parameters and offered a high degree of prediction, with R-Square, R-Square (adj), and R-Square (pred) values of 91.60%, 87.41%, and 79.32% respectively.