bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of rare earth elements on bacteria in rhizosphere, root, phyllosphere and leaf of soil–rice ecosystem
Authors: Zhang Xinzhuan , Hu Zhongjun , Pan Huahua , Bai Yijun , Hu Ying , Jin Shulan 
Published: February 2022

AbstractThe effects of rare earth mining on rice biomass, rare earth element (REE) content and bacterial community structure was studied through pot experiment. The research shows that the REE content in rice roots, shoots and grains was significantly positive correlated with that in soil, and the dry weight of rice roots, shoots and grains was highly correlated with soil physical and chemical properties, nutrient elements and REE contents; The exploitation of rare earth minerals inhibited a-diversity of endophytic bacteria in rhizosphere, root, phyllosphere and leaf of rice, significantly reduced the abundance index, OTU number, Chao, Ace index and also significantly reduced the diversity index–Shannon index, and also reduced uniformity index: Pielou’s evenness index, which caused β-diversity of bacteria to be quite different. The exploitation of rare earth minerals reduces the diversity of bacteria, but forms dominant bacteria, such as Burkholderia, Bacillus, Buttiauxella, Acinetobacter, Bradyrhizobium, Candida koribacter, which can degrade the pollutants formed by exploitation of rare earth minerals, alleviate the compound pollution of rare earth and ammonia nitrogen, and also has the function of fixing nitrogen and resisting rare earth stress; The content of soil available phosphorus in no-mining area is lower, and the dominant bacteria of Pantoea formed in such soil, which has the function of improving soil phosphorus availability. Rare earth elements and physical and chemical properties of soil affect the community structure of bacteria in rhizosphere and phyllosphere of rice, promote the parallel movement of some bacteria in rhizosphere, root, phyllosphere and leaf of rice, promote the construction of community structure of bacteria in rhizosphere and phyllosphere of rice, give full play to the growth promoting function of Endophytes, and promote the growth of rice. The results showed that the exploitation of rare earth minerals has formed the dominant endophytic bacteria of rice and ensured the yield of rice in the mining area, however, the mining of mineral resources causes the compound pollution of rare earth and ammonia nitrogen, which makes REE content of rice in mining area significantly higher than that in non-mining area, and the excessive rare earth element may enter the human body through the food chain and affect human health, so the food security in the REE mining area deserves more attention.
Thoracolumbar epidural stimulation effects on bladder and bowel function in uninjured and chronic transected anesthetized rats
Authors: Hoey Robert F. , Medina-Aguiñaga Daniel , Khalifa Fahmi , Ugiliweneza Beatrice , Wang Dengzhi , Zdunowski Sharon , Fell Jason , Naglah Ahmed , El-Baz Ayman S. , Herrity April N. , Harkema Susan J. , Hubscher Charles H. 
Published: February 2022

AbstractPre-clinical studies have shown that spinal cord epidural stimulation (scES) at the level of pelvic and pudendal nerve inputs/outputs (L5-S1) alters storage and/or emptying functions of both the bladder and bowel. The current mapping experiments were conducted to investigate scES efficacy at the level of hypogastric nerve inputs/outputs (T13-L2) in male and female rats under urethane anesthesia. As found with L5-S1 scES, T13-L2 scES at select frequencies and intensities of stimulation produced an increase in inter-contraction interval (ICI) in non-injured female rats but a short-latency void in chronic T9 transected rats, as well as reduced rectal activity in all groups. However, the detrusor pressure during the lengthened ICI (i.e., urinary hold) remained at a low pressure and was not elevated as seen with L5-S1 scES, an effect that’s critical for translation to the clinic as high fill pressures can damage the kidneys. Furthermore, T13-L2 scES was shown to stimulate voiding post-transection by increasing bladder activity while also directly inhibiting the external urethral sphincter, a pattern necessary to overcome detrusor-sphincter dyssynergia. Additionally, select scES parameters at T13-L2 also increased distal colon activity in all groups. Together, the current findings suggest that optimization of scES for bladder and bowel will likely require multiple electrode cohorts at different locations that target circuitries coordinating sympathetic, parasympathetic and somatic outputs.
Identification and characterization of L- and D-lactate-inducible systems from Escherichia coli MG1655, Cupriavidus necator H16 and Pseudomonas species
Authors: Augustiniene Ernesta , Malys Naglis 
Published: February 2022

AbstractLactic acid is an important platform chemical used for the production of various compounds including polylactic acid (PLA). Optically pure L- and D-lactic acids are required to obtain high quality PLA. To advance the development and selection of microbial strains for improved production of lactic acid enantiomers, a high-throughput screening, dynamic pathway control, or real-time monitoring are often applied. Inducible gene expression systems and their application in the genetically encoded biosensors contribute to the development of these techniques and are important devices for the advancement of lactic acid biotechnology. Here, we identify and characterize eleven lactate-inducible systems from Escherichia coli, Cupriavidus necator, and Pseudomonas spp. The specificity and dynamics of these systems in response to L- and D-lactate, or structurally similar compounds are investigated. We demonstrate that the inducible systems EcLldR/PlldP and CnGntR/PH16_RS19190 respond only to the L-lactate, exhibiting approximately 19- and 24-fold induction, respectively. Despite neither of the examined bacteria possess the D-lactate-specific inducible system, the PaPdhR/PlldP and PfPdhR/PlldP are induced approximately 37- and 366-fold, respectively, by D-lactate and can be used for developing biosensor with improved specificity. The findings of this study provide an insight into understanding of L- and D-lactate-inducible systems that can be employed as sensing and tuneable devices in synthetic biology.
Long term influence of groundwater preservation policy on stubble burning and air pollution over North-West India
Authors: Kant Yogesh , Chauhan Prakash , Natwariya Aryan , Kannaujiya Suresh , Mitra Debashis 
Published: February 2022

AbstractStubble burning (SB) has been a major source of seasonal aerosol loading and pollution over northern India. The aftereffects of groundwater preservation act i.e., post 2010 era (2011–2020) has seen delay in crop harvesting thereby shifting the peak SB to May (Wheat SB) and to November (Paddy SB) by 8–10 and 10–12 days compared to pre-2010. Groundwater storage depletion rate of 29.2 mm yr−1 was observed over the region. Post 2010 era shows an increase of 1.4% in wheat SB and 21% in Paddy SB fires over Punjab and Haryana with 70% of PM2.5 air mass clusters (high probability > 0.8) advecting to the downwind regions leading to 23–26% increase in PM2.5 and 4–6% in aerosol loading over National Capital Region (NCR). Although the objective of water conservation policy was supposed to preserve the groundwater by delaying the paddy transplantation and sowing, on the contrary the implementation of this policy has seen groundwater storage after 2013 depleting at a rate of 29.2 mmyr−1 over these regions. Post policy implementation has led to shift and shrinking of harvest window with increased occurrences in SB fires which also increase associated particulate matter pollution over North India.
Uncertainty quantification for Bayesian active learning in rupture life prediction of ferritic steels
Authors: Mamun Osman , Taufique M. F. N. , Wenzlick Madison , Hawk Jeffrey , Devanathan Ram 
Published: February 2022

AbstractThree probabilistic methodologies are developed for predicting the long-term creep rupture life of 9–12 wt%Cr ferritic-martensitic steels using their chemical and processing parameters. The framework developed in this research strives to simultaneously make efficient inference along with associated risk, i.e., the uncertainty of estimation. The study highlights the limitations of applying probabilistic machine learning to model creep life and provides suggestions as to how this might be alleviated to make an efficient and accurate model with the evaluation of epistemic uncertainty of each prediction. Based on extensive experimentation, Gaussian Process Regression yielded more accurate inference ($$Pearson\;correlation\;coefficent> 0.95$$

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for the holdout test set) in addition to meaningful uncertainty estimate (i.e., coverage ranges from 94 to 98% for the test set) as compared to quantile regression and natural gradient boosting algorithm. Furthermore, the possibility of an active learning framework to iteratively explore the material space intelligently was demonstrated by simulating the experimental data collection process. This framework can be subsequently deployed to improve model performance or to explore new alloy domains with minimal experimental effort.
The prognostic significance of apical lymph node metastasis in patients with high-risk stage III colon cancer
Authors: Ishii Kenichi , Watanabe Jun , Goto Kouki , Suwa Yusuke , Nakagawa Kazuya , Suwa Hirokazu , Ozawa Mayumi , Ishibe Atsushi , Kunisaki Chikara , Endo Itaru 
Published: February 2022

AbstractThe effect of apical lymph node (APN) metastasis on the prognosis of colon cancer is unknown. The present study investigated the impact of APN metastasis on the prognosis of the patients with high-risk stage III colon cancer. This retrospective multi-institutional study included patients with pathological high-risk stage III colon cancer who underwent surgery between April 2009 and December 2014. Clinicopathological factors were examined by univariate and multivariate analyses to clarify independent risk factors for overall survival (OS) and relapse-free survival (RFS). A total of 185 patients were collected. The 5-year OS rates of patients with and without APN metastasis were 35.0% and 72.1%, respectively (p = 0.0014). The 5-year RFS rates of patients with and without APN metastasis was 16.2% and 57.2%, respectively (p = 0.0002). The rate of distant metastasis in patients with APN metastasis was significantly higher than that in patients without APN metastasis (68.8% vs. 36.7%, p = 0.012). The univariate analysis revealed that the differentiation, lymph node ratio, and APN metastasis were significantly associated with 5-year OS, and the preoperative CEA and CA19-9 levels and APN metastasis were significantly associated with 5-year RFS. The multivariate analysis showed that APN metastasis was an independent risk factor for 5-year OS and RFS. APN metastasis may be independently associated with the prognosis of patients with high-risk Stage III colon cancer.
Measurement precision enhancement of surface plasmon resonance based angular scanning detection using deep learning
Authors: Thadson Kitsada , Sasivimolkul Suvicha , Suvarnaphaet Phitsini , Visitsattapongse Sarinporn , Pechprasarn Suejit 
Published: February 2022

AbstractAngular scanning-based surface plasmon resonance measurement has been utilized in label-free sensing applications. However, the measurement accuracy and precision of the surface plasmon resonance measurements rely on an accurate measurement of the plasmonic angle. Several methods have been proposed and reported in the literature to measure the plasmonic angle, including polynomial curve fitting, image processing, and image averaging. For intensity detection, the precision limit of the SPR is around 10–5 RIU to 10–6 RIU. Here, we propose a deep learning-based method to locate the plasmonic angle to enhance plasmonic angle detection without needing sophisticated post-processing, optical instrumentation, and polynomial curve fitting methods. The proposed deep learning has been developed based on a simple convolutional neural network architecture and trained using simulated reflectance spectra with shot noise and speckle noise added to generalize the training dataset. The proposed network has been validated in an experimental setup measuring air and nitrogen gas refractive indices at different concentrations. The measurement precision recovered from the experimental reflectance images is 4.23 × 10–6 RIU for the proposed artificial intelligence-based method compared to 7.03 × 10–6 RIU for the cubic polynomial curve fitting and 5.59 × 10–6 RIU for 2-dimensional contour fitting using Horner's method.
Cooling-induced reactivation of distant faults during long-term geothermal energy production in hot sedimentary aquifers
Authors: Kivi Iman Rahimzadeh , Pujades Estanislao , Rutqvist Jonny , Vilarrasa Víctor 
Published: February 2022

AbstractDeep geothermal energy (DGE) represents an opportunity for a sustainable and carbon-free energy supply. One of the main concerns of DGE is induced seismicity that may produce damaging earthquakes, challenging its widespread exploitation. It is widely believed that the seismicity risk can be controlled by using doublet systems circulating water to minimize the injection-induced pressure changes. However, cold water reinjection may also give rise to thermal stresses within and beyond the cooled region, whose potential impacts on fault reactivation are less well understood. Here, we investigate by coupled thermo-hydro-mechanical modeling the processes that may lead to fault reactivation in a hot sedimentary aquifer (HSA) in which water is circulated through a doublet. We show that thermal stresses are transmitted much ahead of the cooled region and are likely to destabilize faults located far away from the doublet. Meanwhile, the fault permeability mainly controls the fault reactivation timing, which entails the importance of employing appropriate characterization methods. This investigation is crucial for understanding the mechanisms controlling induced seismicity associated with DGE in a HSA and allows the success of future DGE projects.
Effect of silver nanoparticles on gene transcription of land snail Helix aspersa
Authors: Turki Faten , Ben Younes Ridha , Sakly Mohsen , Ben Rhouma Khemais , Martinez-Guitarte José-Luis , Amara Salem 
Published: February 2022

AbstractSilver nanoparticles (Ag-NPs) are extremely useful in a diverse range of consumer goods. However, their impact on the environment is still under research, especially regarding the mechanisms involved in their effect. Aiming to provide some insight, the present work analyzes the transcriptional activity of six genes (Hsp83, Hsp17.2, Hsp19.8, SOD Cu–Zn, Mn-SOD, and BPI) in the terrestrial snail Helix aspersa in the presence of different concentrations of Ag-NPs. The animals were exposed for seven days to Lactuca sativa soaked for one hour in different concentrations of Ag-NPs (20, 50, 100 mg/L). The results revealed that the highest concentration tested of Ag-NPs (100 mg/L) led to a statistically significant induction of the Hsp83 and BPI expression in the digestive gland compared to the control group. However, a trend to upregulation with no statistical significance was observed for all the genes in the digestive gland and the foot, while in the hemolymph, the trend was to downregulation. Ag-NPs affected the stress response and immunity under the tested conditions, although the impact was weak. It is necessary to explore longer exposure times to confirm that the effect can be maintained and impact on health. Our results highlight the usefulness of the terrestrial snail Helix aspersa as a bioindicator organism for silver nanoparticle pollution biomonitoring and, in particular, the use of molecular biomarkers of pollutant effect as candidates to be included in a multi-biomarker strategy.
Association between birth weight and neurodevelopmental disorders assessed using the Korean National Health Insurance Service claims data
Authors: Song In Gyu , Kim Han-Suk , Cho Yoon-Min , Lim You-na , Moon Duk-Soo , Shin Seung Han , Kim Ee-Kyung , Park Joonsik , Shin Jeong Eun , Han Jungho , Eun Ho Seon 
Published: February 2022

AbstractThe risk of neurodevelopmental disorders in low birth weight (LBW) infants has gained recognition but remains debatable. We investigated the risk of attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) in school-aged children according to their birth weight. We conducted a retrospective cohort study using the Korean National Health Insurance claims data of 2,143,652 children who were born between 2008 and 2012. Gestational age of infants was not available; thus, outcomes were not adjusted with it. Not only infants with birth weights of < 1.5 kg, but also 2.0–2.4 kg and 1.5–1.9 kg were associated with having ADHD; odds ratio (OR), 1.41 (95% confidence interval [CI] 1.33–1.50), and 1.49 (95% CI 1.33–1.66), respectively. The OR in infants with birth weights of 2.0–2.4 kg and 1.5–1.9 kg was 1.91 (95% CI 1.79–2.05) and 3.25 (95% CI 2.95–3.59), respectively, indicating increased odds of having ASD. Subgroup analysis for children without perinatal diseases showed similar results. In this national cohort, infants with birth weights of < 2.5 kg were associated with ADHD and ASD, regardless of perinatal history. Children born with LBW need detailed clinical follow-up.
Optical coherence tomography and visual evoked potentials in evaluation of optic chiasm decompression
Authors: Poczos Pavel , Česák Tomáš , Jirásková Naďa , Macháčková Markéta , Čelakovský Petr , Adamkov Jaroslav , Gabalec Filip , Soukup Jiří , Kremláček Jan 
Published: February 2022

AbstractChiasmal compression is a known cause of visual impairment, often leading to surgical decompression of the optic chiasm (OC). A prospective study was held at University Hospital in Hradec Králové to explore sensitivity of optical coherence tomography (OCT) and visual evoked potentials (VEPs) to OC compression and eventual changes after a decompression. 16 patients with OC compression, caused by different sellar pathologies, were included. The main inclusion criterion was the indication for decompressive surgery. Visual acuity (VA), visual field (VF), retinal nerve fibre layer (RNFL) and ganglion cell layer (GCL) thickness, and peak time and amplitude of pattern-reversal (P-VEPs) and motion-onset VEPs (M-VEPs) were measured pre- and postoperatively. The degree of OC compression was determined on preoperative magnetic resonance imaging. For M-VEPs, there was a significant postoperative shortening of the peak time (N160) (p < 0.05). P100 peak time and its amplitude did not change significantly. The M-VEPs N160 amplitude showed a close relationship to the VF improvement. Thinner preoperative RNFL does not present a statistically important limiting factor for better functional outcomes. The morphological status of the sellar region should be taken into consideration when one evaluates the chiasmal syndrome. M-VEPs enable detection of functional changes in the visual pathway better than P-VEPs.
A graphical LASSO analysis of global quality of life, sub scales of the EORTC QLQ-C30 instrument and depression in early breast cancer
Authors: Poikonen-Saksela Paula , Kolokotroni Eleni , Vehmanen Leena , Mattson Johanna , Stamatakos Georgios , Huovinen Riikka , Kellokumpu-Lehtinen Pirkko-Liisa , Blomqvist Carl , Saarto Tiina 
Published: February 2022

AbstractWe aimed to (a) investigate the interplay between depression, symptoms and level of functioning, and (b) understand the paths through which they influence health related quality of life (QOL) during the first year of rehabilitation period of early breast cancer. A network analysis method was used. The population consisted of 487 women aged 35–68 years, who had recently completed adjuvant chemotherapy or started endocrine therapy for early breast cancer. At baseline and at the first year from randomization QOL, symptomatology and functioning by the EORTC QLQ-C30 and BR-23 questionnaires, and depression by the Finnish version of Beck's 13-item depression scale, were collected. The multivariate interplay between the related scales was analysed via regularized partial correlation networks (graphical LASSO). The median global quality of life (gQoL) at baseline was 69.9 ± 19.0 (16.7–100) and improved to 74.9 ± 19.0 (0–100) after 1 year. Scales related to mental health (emotional functioning, cognitive functioning, depression, insomnia, body image, future perspective) were clustered together at both time points. Fatigue was mediated through a different route, having the strongest connection with physical functioning and no direct connection with depression. Multiple paths existed connecting symptoms and functioning types with gQoL. Factors with the strongest connections to gQoL included: social functioning, depression and fatigue at baseline; emotional functioning and fatigue at month 12. Overall, the most important nodes were depression, gQoL and fatigue. The graphical LASSO network analysis revealed that scales related to fatigue and emotional health had the strongest associations to the EORTC QLQ-C30 gQoL score. When we plan interventions for patients with impaired QOL it is important to consider both psychological support and interventions that improve fatigue and physical function like exercise.Trial registration: http://www.clinicaltrials.gov/ (identifier number NCT00639210).
Adaptive deep learning-based neighborhood search method for point cloud
Authors: Xiang Qian , He Yuntao , Wen Donghai 
Published: February 2022

AbstractPoint cloud processing is a highly challenging task in 3D vision because it is unstructured and unordered. Recently, deep learning has been proven to be quite successful in point cloud recognition, registration, segmentation, etc. Neighborhood search operation is an important component of point cloud deep learning models, and directly affects the performance of the model. In this paper, we propose a learnable neighborhood search method. This method adaptively chooses an appropriate search method based on the characteristics of each point, thus avoiding the disadvantage of selecting the search method manually. We validate the proposed methods on ModelNet40 dataset and ShapeNetPart dataset, and all the chosen models achieved a performance improvement with a maximum improvement of 1.1%. The proposed method is a plug-and-play technique and can be easily integrated into existing methods.