bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comprehensive Genomic Dependency Landscape of Human Colon Cancer
Authors: Khalili Sana , Mohseninia Atefeh , Liu Changlong , Banister Carolyn E. , Morrison Sidney E. , Heine Paige , Gokare Prashanth , Cowley Glenn S. , Weir Barbara A. , Pocalyko David , Bachman Kurtis E. , Buckhaults Phillip J. 
Published: June 2024

Abstract

Identifying genetic dependencies in human colon cancer could help identify effective treatment strategies. Genome-wide CRISPR-Cas9 dropout screens have the potential to reveal genetic dependencies, some of which could be exploited as therapeutic targets using existing drugs. In this study, we comprehensively characterized genetic dependencies present in a colon cancer organoid avatar, and validated tumor-specific selectivity of select pharmacologic agents. We conducted a genome-wide CRISPR dropout screen to elucidate the genetic dependencies that interacted with select driver somatic mutations. We found distinct genetic dependencies that interacted with WNT, MAPK, PI3K, TP53, and mismatch repair pathways and validated targets that could be exploited as treatments for this specific subtype of colon cancer. These findings demonstrate the utility of functional genomic screening in the context of personalized medicine.
Screening and identification of plant growth promoting bacteria and their influence on soil heavy metal forms
Authors: Deng Yi , Hu Nan , Gu Weihua , Chen Mengjun 
Published: June 2024

Abstract

The unregulated dismantling of electronic products has led to heavy metal contamination of soil at electronic waste (e-waste) dismantling sites, causing serious environmental problems and not conductive to environmentally sustainable development. Therefore, four bacterial strains from soil collected from a contaminated e-waste site were screened. The objectives of this study were: to identify plant growth-promoting strains with useful characteristics; to determine the behavior of the strains by various qualitative and quantitative tests; to determine the effect of each strain on the migration of different forms of heavy metals from the soil by shake flask tests; and to determine the mechanisms by which this migration occurs. This study investigated the nitrogen fixation, inorganic phosphorus solubilization, iron carrier production, indole-3-acetic acid secretion, and metal tolerance of each bacterial strain, and used 16S rDNA analysis to determine its taxonomic status and growth characteristics. The 16S rDNA analysis revealed that strains RH1 and RH3 belonged to the genus Rhizobium, and strains MO2 and MO4 belonged to the genus Microbacterium. MO4 had the highest indole-3-acetic acid production capacity of 26.98 mg/L; RH3 had the highest inorganic phosphorus solubilization capacity of 1.33; RH1, MO2, RH3, and MO4 were capable of fixing nitrogen; and MO2 and MO4 were capable of producing iron carriers (MO4 was the most efficient of the two, with an iron carrier activity of up to 35%). A series of shake flask tests showed that the strains affected the levels of different forms of heavy metals and played a mobilizing role. Therefore, they are potentially useful for the remediation of heavy metal contaminated soils. In conclusion, Rhizobium RH3 and Microbacterium MO4 are excellent plant growth-promoting bacteria and have considerable potential for the green remediation of soils contaminated with heavy metals.
Impact of papillary morphology and diverticular type on needle-knife precut sphincterotomy in patients with periampullary diverticulum with difficult biliary cannulation
Authors: Wang Sheng-Fu , Wu Chi-Huan , Lee Mu-Hsien , Tsou Yung-Kuan , Lin Cheng-Hui , Sung Kai-Feng , Liu Nai-Jen 
Published: June 2024

Abstract

Background and Aims
Several studies have investigated the relationship between the technical success of ERCP and periampullary diverticulum (PAD), but only limited studies have specifically examined advanced cannulation techniques such as needle-knife precut sphincterotomy (NKPS). This study aimed to explore the outcomes of NKPS in patients with PAD.
Methods
This retrospective study was conducted on 122 patients with PAD who underwent NKPS due to difficult biliary cannulation. Patient characteristics, ERCP indications, CBD diameter, PAD classification, diverticular size, major duodenal papilla (MDP) morphology, and post-ERCP adverse events were assessed. We analyzed factors associated with the outcomes of NKPS in patients with PAD, with a specific focus on the type of PAD and the morphology of MDP.
Results
Among 122 patients, 82 (67.2%) belonged to the NKPS success group and 40 (32.8%) belonged to the NKPS failure group. Diverticular size was significantly larger in the NKPS failure group. For type I, type II, and type III PAD, the median dimeters of diverticula were 1.2 cm, 0.9 cm, and 0.5 cm, respectively (P<0.001), and the NKPS success rates were 50%, 66.3%, and 75%, respectively (P=0.391). Regarding MDP morphology, the NKPS success rates were 73.7%, 38.2%, 92.9%, and 82.4% for types I, II, III, and IV MDP, respectively (P =0.059). The overall adverse event rate was 16.4%, including pancreatitis (6.6%), delayed bleeding (5.7%), and cholangitis (4.1%). There were no significant differences in adverse event rates between the NKPS success and failure groups. Multivariate analysis showed that MDP morphology (type II vs. type I, OR: 0.256, 95% CI: 0.089-0.734, P=0.011) and bleeding during NKPS (OR: 0.117, 95% CI: 0.039-0.351, P< 0.001) were independent factors associated with NKPS outcome.
Conclusions
MDP morphology and bleeding during NKPS are independent predictors of NKPS failure in PAD patients with difficult biliary cannulation.
Advanced KPI Framework for IVF Pregnancy Prediction Models in IVF protocols
Authors: Sergeev Sergei , Diakova Iuliia 
Published: June 2024

Abstract

The utilization of neural networks in assisted reproductive technology is essential due to their capability to process complex and multidimensional data inherent in IVF procedures, offering opportunities for clinical outcome prediction, personalized treatment implementation, and overall advancement in fertility treatment. The aim of this study was to develop a novel approach to IVF laboratory data analysis, employing deep neural networks to predict the likelihood of clinical pregnancy occurrence within an individual protocol, integrating both key performance indicators and clinical data. We conducted a retrospective analysis spanning 11 years, encompassing 8732 protocols, to extract the most relevant features to our goal and train the model. Internal validation was performed on 1600 preimplantation genetic testing for aneuploidy embryo transfers, while external was conducted across two independent clinics (over 10,000 cases). Leveraging recurrent neural networks, our model demonstrates high accuracy in predicting the likelihood of clinical pregnancy within specific IVF protocols (AUC: 0.68–0.86; Test accuracy: 0.78, F1 Score: 0.71, Sensitivity: 0.62; Specificity: 0.86) comparable to time-lapse system but with a simpler approach. Our model facilitates both retrospective analysis of outcomes and prospective evaluation of clinical pregnancy chances, thus presenting a promising avenue for quality management programs and promotes their realization in medical centers.
Permeability Monitoring of Underground Concrete Structures using Elastic wave Characteristics with Biot’s Model
Authors: Lee Jong-Won , Kim Jin-Seop , Hong Chang-Ho , Oh Tae-Min 
Published: June 2024

Abstract

Underground environments are preferred for the construction of important infrastructures to overcome social problems, such as the tunnel or disposal of radioactive waste at deep depth. Concrete is primarily used as a structural material owing to its high strength and cost efficiency. To utilize these structures safely in the long term, the permeability of the concrete should be monitored. If the permeability is increased due to crack generation in a concrete medium, groundwater can flow into the underground structure. However, permeability monitoring is challenging at depths of 500 m–1 km under high-temperature, high-pressure, and limited space conditions. In this study, a theoretical model was developed to predict the permeability of concrete using compressive elastic waves. To derive the relationship between the permeability and elastic wave characteristics, Biot’s model, which can associate the characteristics of P-waves with the properties of porous media, was applied. The P-wave velocity and attenuation were investigated according to the permeability of the concrete based on Biot’s model. Subsequently, the concrete specimens were prepared to measure the permeability, P-wave velocity, and attenuation, and the permeability results from the experiment were compared to those obtained from the model for validation. Biot’s model is expected to be useful for permeability monitoring based on the characteristics of the elastic waves in underground structures.
Active integrated fabrication method and evaluation of polymer with microneedles LED light source integration
Authors: Zhang Xiaoning , Han Qingxin , Hu Xiaoqing , Zhang Lei , Kang Xiaoya , Li Ming , Gao Qiang , Liu Fengyi , Sun Jingyao , Zhu Jingxian , Zhuang Jian 
Published: June 2024

Abstract

This article proposes a new process for fabricating a polymer microneedles (MNs) patch integrated with an LED light source (LED-HEMA/MN, LH-MN) using ultraviolet (UV) curing technology. Hydroxyethyl methacrylate (HEMA) is used as the base material, with a focus on studying the active integrated fabrication process of the MNs patch. The study also investigates the morphology, size, mechanical properties, ex vivo skin penetration performance, operating temperature, and performance optimization of the LH-MN. The experimental results show that the LH-MN fabricated using the optimal process has a good appearance, high molding rate, short production cycle, and excellent mechanical properties. It can effectively penetrate the skin without the risk of thermal injury. In addition, the MNs patch (LED-HEMA/HEA-MN, LHH-MN) prepared by optimizing and modifying with hydroxyethyl acrylate (HEA) possesses good flexibility and mechanical properties. It can adapt to different shapes and locations of the affected area, greatly enhancing the practicality of the MNs.
Temporal-Spatial Evolution Patterns and Driving Factors Analysis of China's Public Charging Infrastructure Development
Authors: Ma Zechao , Liu Xiaoming , Li Yishu , Wang Weiqiang , Zhao Yingjie , You Xiancheng 
Published: June 2024

Abstract

The development of public charging infrastructure has become an important component of smart city construction and energy conservation and emission reduction. As the country with the largest number of electric vehicles in the world, China's experience in the development of public charging infrastructure is of demonstrative significance globally. This article constructs a comprehensive evaluation index of the development level of public charging infrastructure based on provincial panel data from 2018 to 2023 and measures it using the entropy weight-TOPSIS method. By analyzing the coupling coordination degree between the development level of public charging infrastructure and regional resilience, spatial and temporal differences and evolutionary characteristics are explored. Finally, the factors influencing the development are analyzed using a spatial Durbin model with mixed fixed effects. The results show that: 1) The development level of public charging infrastructure in China has been increasing year by year, but regional disparities are gradually widening, with an increasing probability of downward transfer of coupling coordination status; 2) The coupling coordination degree in most regions of China has reached a primary coordination level or above, and there is a significant spatial agglomeration relationship, with high-value agglomeration areas in the eastern region showing a significant spillover effect in the east-west direction; 3) The development level of public charging infrastructure is influenced by various factors, among which economic development level, power supply capacity, government budget expenditure, urbanization process, pollutant emissions, and environmental temperature are key driving factors. This study analyzes the spatial and temporal pattern evolution of public charging infrastructure in China and its influencing factors, providing decision-making references for the development of global electrified transportation.
Performance Study of High-Precision Coal Composition and Carbon Emission Rapid Quantitative Analysis LIBS System
Authors: Wang Meng , Liu Shulin , Liu Xiaodong , Zhang Ying , Li An , Liu Ruibin 
Published: June 2024

Abstract

Rapid and high-precision quantitative analysis of coal composition and carbon emissions is an essential aspect of efficient energy utilization in factories. A rapid coal quality analysis system based on LIBS technology enables fast quantitative analysis of the elements, industrial parameters, and carbon emissions contained in coal. This article introduces the working principle of the CoalCam LIBS rapid coal quality analyzer, evaluates the measurement accuracy, robustness, equipment stability, and measurement precision technical parameters of the analysis equipment in industrial applications, and describes the method of using the equipment to assess coal quality carbon emissions. The final results indicate that the CoalCam rapid coal quality analyzer developed by our laboratory using LIBS technology has high accuracy and stability, with broad prospects for application in online coal quality monitoring, particularly in carbon emission assessment.
The quantitative anatomy of the hippocampus in homing pigeons and other pigeon breeds: implications for spatial cognition.
Authors: Iwaniuk Andrew N , Racicot Kelsey J , Guyonnet Audrey EM , Brinkman Ben 
Published: June 2024

Abstract

The artificial selection for specific behavioural and physical traits domesticated animals has resulted in a wide variety of breeds. One of the most widely recognized examples of behavioural selection is the homing pigeon (Columba livia), which has undergone intense selection for fast and efficient navigation, likely resulting in significant anatomical changes to the hippocampal formation. Previous neuroanatomical comparisons between homing and other pigeon breeds yielded mixed results, but only focused on volumes. We completed a more systematic test for differences in hippocampal formation anatomy between homing and other pigeon breeds by measuring volumes, neuron numbers and neuron densities in the hippocampal formation and septum across homing pigeons and seven other breeds. Overall, we found few differences in hippocampal formation volume across breeds, but large, significant differences in neuron numbers and densities. More specifically, homing pigeons have significantly more hippocampal neurons and at higher density than most other pigeon breeds, with nearly twice as many neurons as feral pigeons. These findings suggest that neuron numbers may be important component of homing behaviour in homing pigeons. Our data also provide the first evidence that neuronal density can be modified by artificial selection, which has significant implications for the study of domestication and interbreed variation in anatomy and behaviour.
Imitating the respiratory activity of the brain stem by using artificial neural networks: exploratory study on an animal model of lactic acidosis and proof of concept
Authors: Perchiazzi Gaetano , Kawati Rafael , Pellegrini Mariangela , Liangpansakul Jasmine , Colella Roberto , Bollella Paolo , Rangaiah Pramod , Cannone Annamaria , Venkataramana Deepthi Hulithala , Perez Mauricio , Stramaglia Sebastiano , Torsi Luisa , Bellotti Roberto , Augustine Robin 
Published: June 2024

Abstract

Purpose: Artificial neural networks (ANNs) are versatile tools capable of learning without prior knowledge. This study aims to evaluate whether ANN can calculate minute volume during spontaneous breathing after being trained using data from an animal model of metabolic acidosis.
Methods: Data was collected from ten anesthetized, spontaneously breathing pigs divided randomly into two groups, one without dead space and the other with dead space at the beginning of the experiment. Each group underwent two equal sequences of pH lowering with pre-defined targets by continuous infusion of lactic acid. The inputs to ANNs were pH, DPaCO2 (variation of the arterial partial pressure of CO2), PaO2, and blood temperature which were sampled from the animal model. The output was the delta minute volume (DVM), (the change of minute volume as compared to the minute volume the animal had at the beginning of the experiment). The ANN performance was analyzed using mean squared error (MSE), linear regression, and the Bland-Altman (B-A) method.
Results: The animal experiment provided the necessary data to train the ANN. The best architecture of ANN had 17 intermediate neurons; the best performance of the finally trained ANN had a linear regression with R2 of 0.99, an MSE of 0.001 [L/min], a B-A analysis with bias ± standard deviation of 0.006 ± 0.039 [L/min].
Conclusions: ANNs can accurately estimate DVM using the same information that arrives at the respiratory centers. This performance makes them a promising component for the future development of closed-loop artificial ventilators.
Flexible aerogel composites for the elimination of crystal violet and methyl orange
Authors: Nguyen Phuong X.T. , Pham Anh P.N. , Nguyen Hong T.T. , Do Tai C. , Le Phung K. 
Published: June 2024

Abstract

The application of porous aerogels for dye adsorption has proven to be an effective approach in wastewater treatment. In this study, bio-cellulose aerogels from coconut fibrils were successfully developed via the formation of physically cross-linking cellulose with non-toxic binders (polyvinyl alcohol (PVA) and xanthan gum (XTG)) after a freeze-drying technique. The resulting cellulose aerogel demonstrated remarkably low density (27.59–47.76 g/cm3), high porosity (> 96.0%), a specific surface area of 518.01 m2/g, and a desorption average pore diameter distribution of 3.77 nm. These aerogels were tested for crystal violet (CV) and methyl orange (MO) adsorption to evaluate their effectiveness in treating dye-polluted water via various conditions such as contact time, pH values, initial concentrations, and temperature. The dye adsorption process reached equilibrium after approx. 30 mins and strictly followed pseudo-second-order and the Redlich-Peterson model. FT-IR and SEM-EDX analyses proved that the adsorption mechanism is primarily ascribed to the hydrogen bonding, electrostatic, π-π, and Vander Waals interactions between aerogel and dye molecules. The eco-friendly synthesis of recycled cellulose aerogels from coconut fibrils using green chemicals holds great promise for dye elimination.
GGC-SLAM: A VSLAM System Based on Predicted Static Probability of Feature Points in Dynamic Environments
Authors: Sun Qian , Liu Wa , Zou Junjing , Xu Ziqiang , Li Yibing 
Published: June 2024

Abstract

Most existing Visual Simultaneous Localization and Mapping (VSLAM) systems heavily rely on the assumption of a static world. However, in real-world scenarios, moving objects often reduce the accuracy and robustness of these systems. To mitigate the impact of moving objects on SLAM system performance, this paper introduces GGC-SLAM, a VSLAM system designed for dynamic environments based on the static probability of predictive feature points. Building on the foundation of ORB-SLAM2, this system incorporates a lightweight object detection thread for acquiring semantic information. It also integrates the Grid-based Motion Statistics (GMS) and Graph-Cut RANdom SAmple Consensus (GC-RANSAC) algorithms to enhance the speed and precision of fundamental matrix computation. The system preliminarily predicts the static probability of feature points by combining semantic information with epipolar constraints, then refines the differentiation between dynamic and static feature points using the initial probability information and a Conditional Random Field (CRF), ultimately excluding feature points deemed dynamic. We conducted evaluations using the TUM public dataset and in real-world environments, and the results show that GGC-SLAM can effectively handle dynamic feature points in dynamic scenes. While ensuring real-time operation, it demonstrates more accurate localization compared to other advanced dynamic SLAM systems. Particularly in high-dynamic scenes, our system's average absolute trajectory error is reduced by approximately 90% compared to ORB-SLAM2.
Nutritional and anti-nutritional potentials and variability among selected finger millet (Eleusine coracana subsp. coracana) landraces of Tigray, northern Ethiopia
Authors: Semere Tesfakiros , Tareke Lijalem , Teklay Ashenafi , Mesele Etsay , Kasegn Melaku Mekonen , Fisseha Haregot , Mekonen Girmay , Kahsay Birhanu , Embaye Lijalem Gebrewahid , Yigzaw Wendm , Gebremedhin Hailay Mehari , Weldekidan Negash Aregay , Tsehaye Yemane 
Published: June 2024

Abstract

Finger millet is one of the staple food crops used for different end-uses in Tigray, northern Ethiopia. However, limited research attention has been given to its nutritional and anti-nutritional profiling. Thus, this research was conducted to assess the potential and variability in protein, starch, minerals, flavonoid, tannin, and antioxidant activities among selected finger millet landraces. Protein and starch were analyzed using an infrared spectrophotometer, whereas mineral elements were estimated using an atomic absorption spectrophotometer. Antioxidant activity was analyzed using ferric-reducing antioxidant power and phosphomolybdenum assays. The result revealed significant variation among the landraces for all the evaluated nutritional and anti-nutritional components. Respectively, protein and starch contents ranged from 8.79 to 11.05% and 70.30 to 76.17%. Extensive variations were observed for Fe (93.56-742.59), Zn (14.76–30.13), Cu (8.29–13.11), Mn (88.40-201.303), and Cr (2.54–6.58) as measured in mg/100g. High variabilities for total flavonoid (4-33.88 mg CE/g) and tannin (0.76–2.70 mg CE/100 g) were also observed. Ferric reducing antioxidant power (15.55–57.06 mg AAE/g), and total antioxidant activity (7.78–20.59 mg BHTE/g) were also highly variable among the samples. Multivariate analysis revealed three distinct groups of the tested landraces. The rich genetic diversity in the nutritional and anti-nutritional attributes may be an opportunity for breeding for grain quality improvements of finger millet that, in turn, helps in addressing malnutrition.