bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of rs958804 and rs7858836 single‐nucleotide polymorphisms of the ASTN2 gene on pain‐related phenotypes in patients who underwent laparoscopic colectomy and mandibular sagittal split ramus osteotomy
Authors: Inoue Rie , Nishizawa Daisuke , Hasegawa Junko , Nakayama Kyoko , Fukuda Ken‐ichi , Ichinohe Tatsuya , Mieda Tsutomu , Tsujita Miki , Nakagawa Hideyuki , Kitamura Akira , Sumikura Hiroyuki , Ikeda Kazutaka , Hayashida Masakazu 
Published: January 2021

AbstractBackgroundOpioids are widely used as effective analgesics, but opioid sensitivity varies widely among individuals. The underlying genetic and nongenetic factors are not fully understood. Based on the results of our previous genome‐wide association study, we investigated the effects of single nucleotide polymorphisms (SNPs) of the astrotactin 2 (ASTN2) gene on pain‐related phenotypes in surgical patients.MethodsWe investigated the effects of two SNPs, rs958804 T/C and rs7858836 C/T, of the ASTN2 gene on eight and seven pain‐related phenotypes in 350 patients who underwent laparoscopic colectomy (LAC) and 358 patients who underwent mandibular sagittal split ramus osteotomy (SSRO), respectively. In both surgical groups, intravenous fentanyl patient‐controlled analgesia (PCA) was used for postoperative analgesia, and 24‐hour postoperative PCA fentanyl use was the primary endpoint.ResultsThe association analyses among the two SNPs and pain‐related traits showed that 24‐hour fentanyl use was significantly associated with the two SNP genotypes in both surgical groups. The Mann‐Whitney test showed that 24‐hour fentanyl use was lower in patients with the C allele than in patients with the TT genotype of the rs958804 T/C SNP (P = .0019 and .0200 in LAC and SSRO patients, respectively), and it was lower in patients with the T allele than in patients with the CC genotype of the rs7858836 C/T SNP (P = .0017 and .0098 in LAC and SSRO patients, respectively).ConclusionThe two SNPs of the ASTN2 gene were consistently associated with fentanyl requirements after two different types of surgery. These findings may contribute to personalized pain control.
Performance assessment of different machine learning approaches in predicting diabetic ketoacidosis in adults with type 1 diabetes using electronic health records data
Authors: Li Lin , Lee Chuang‐Chung , Zhou Fang Liz , Molony Cliona , Doder Zoran , Zalmover Evgeny , Sharma Kristen , Juhaeri Juhaeri , Wu Chuntao 
Published: January 2021

AbstractPurposeTo assess the performance of different machine learning (ML) approaches in identifying risk factors for diabetic ketoacidosis (DKA) and predicting DKA.MethodsThis study applied flexible ML (XGBoost, distributed random forest [DRF] and feedforward network) and conventional ML approaches (logistic regression and least absolute shrinkage and selection operator [LASSO]) to 3400 DKA cases and 11 780 controls nested in adults with type 1 diabetes identified from Optum® de‐identified Electronic Health Record dataset (2007–2018). Area under the curve (AUC), accuracy, sensitivity and specificity were computed using fivefold cross validation, and their 95% confidence intervals (CI) were established using 1000 bootstrap samples. The importance of predictors was compared across these models.ResultsIn the training set, XGBoost and feedforward network yielded higher AUC values (0.89 and 0.86, respectively) than logistic regression (0.83), LASSO (0.83) and DRF (0.81). However, the AUC values were similar (0.82) among these approaches in the test set (95% CI range, 0.80–0.84). While the accuracy values >0.8 and the specificity values >0.9 for all models, the sensitivity values were only 0.4. The differences in these metrics across these models were minimal in the test set. All approaches selected some known risk factors for DKA as the top 10 features. XGBoost and DRF included more laboratory measurements or vital signs compared with conventional ML approaches, while feedforward network included more social demographics.ConclusionsIn our empirical study, all ML approaches demonstrated similar performance, and identified overlapping, but different, top 10 predictors. The difference in selected top predictors needs further research.
Comparative studies of the noncovalent interactions in the single‐crystal packing of pyrene, pyrene‐4,5‐dione, and pyrene‐4,5,9,10‐tetraone
Authors: Zreid Monther , Tabasi Zahra A. , Zhao Yuming 
Published: January 2021

AbstractPyrene‐4,5‐dione and pyrene‐4,5,9,10‐tetraone are K‐region oxidized derivatives of pyrene, which show interesting structural and electronic properties as well as useful application in organic electronic and optoelectronic devices. The single‐crystal structures of pyrene and pyrene‐4,5‐dione have been published, but the crystallographic data of pyrene‐4,5,9,10‐tetraone has not. In this work, the single‐crystal structure of pyrene‐4,5,9,10‐tetraone has been clearly elucidated for the first time, and the detailed crystallographic properties were analyzed and discussed in comparison with those of pyrene and pyrene‐4,5‐dione. Various noncovalent interactions taking place within the supramolecular assemblies that exist in the crystal packing of these compounds were studied by Hirshfeld surface analysis and density functional theory (DFT) calculations. Our joint experimental and computational analyses provide fundamental understanding of the electron density properties, interaction energies, and frontier molecular orbital (FMO) properties for these pyrene systems and establish correlations of these properties with diverse supramolecular assembling motifs.
How does economic growth impact on income inequality across ethnic groups in Malaysia?
Authors: Banna Hasanul , Masud Muhammad Mehedi , Rodrigo Shamsulbahriah K. A. 
Published: January 2021

AbstractThis study aims to examine the impact of economic growth on income inequality in Malaysia with special attention to the distribution of income among different ethnic groups. Twofold methodologies have been used in this analysis. The primary methodology is descriptive in nature where tables, charts, and diagrams have been extracted from the specific sources for analysis. Second, this paper applies the Granger noncausality test to estimate the causality and also applies the ARDL (autoregressive distributed lag) regression model to see the shot‐run and long‐run dynamic relationship between economic growth and income inequality in the context of Malaysia using the data of 1970–2018 from the household income survey, World Development Indicators, and the Standardized World Income Inequality Database. Additionally, it deploys panel Granger noncausality and dynamic pool mean group regression for the robustness of the results. This study reveals that the income gap among ethnic groups has been narrowed; although, intra‐ethnic income inequality is still very high, especially among Indians. The study further advises that income inequality does not Granger‐cause economic growth; rather, economic growth does Granger‐cause income inequality, and economic growth affects income inequality negatively, regardless of ethnicity, suggesting that economic growth significantly contributes to the reduction of income inequality in Malaysia. The paper concludes with a few policies which could significantly contribute to reducing income inequalities and achieving greater economic development goals, such that Malaysia can become a developed country by 2030.
Permafrost thaw‐related slope failures in Alaska’s Arctic National Parks, c. 1980–2019
Authors: Swanson David K. 
Published: January 2021

AbstractActive‐layer detachments (ALD) and retrogressive thaw slumps (RTS) are landslides that occur as a result of thaw in permafrost regions. I mapped the extent of bare soil exposed in these thaw‐related slope failures in four study areas with continuous permafrost in Alaska’s Arctic National Parks, on mosaics of aerial photographs from 1977–1985 (sampling episode 1), satellite images from 2006–2009 (sampling episode 2), and satellite images from 2018–2019 (sampling episode 3). In all four study areas the count of ALD and RTS, and the area of bare soil they exposed, was greater during the first or second sampling episode than the third sampling episode, in spite of record high mean annual temperatures in 2014–2019. One study area had frozen debris lobes (FDL) in addition to ALD and RTS. In that study area the bare ground exposed by destabilization and rapid movement of FDL was greatest in the third sampling episode, probably as a result of deep thaw and talik formation. The destabilization of FDL in episode 3 was probably a long‐term consequence of warming and permafrost loss, while the observed pulses of ALD and RTS in episodes 1 and 2 were closely tied to short‐term deep thaw events in areas where the underlying permafrost remained stable.
Simulating Nanomaterial Transformation in Cascaded Biological Compartments to Enhance the Physiological Relevance of In Vitro Dosing Regimes: Optional or Required?
Authors: Llewellyn Samantha V. , Kämpfer Angela , Keller Johannes G. , Vilsmeier Klaus , Büttner Veronika , Ag Seleci Didem , Schins Roel P. F. , Doak Shareen H. , Wohlleben Wendel 
Published: January 2021

AbstractWould an engineered nanomaterial (ENM) still have the same identity once it reaches a secondary target tissue after a journey through several physiological compartments? Probably not. Does it matter? ENM pre‐treatments may enhance the physiological relevance of in vitro testing via controlled transformation of the ENM identity. The implications of material transformation upon reactivity, cytotoxicity, inflammatory, and genotoxic potential of Ag and SiO2 ENM on advanced gastro‐intestinal tract cell cultures and 3D liver spheroids are demonstrated. Pre‐treatments are recommended for certain ENM only.
Model uncertainty in non‐linear numerical analyses of slender reinforced concrete members
Authors: Gino Diego , Castaldo Paolo , Giordano Luca , Mancini Giuseppe 
Published: January 2021

AbstractThe present study aims to characterize the epistemic uncertainty within the use of global non‐linear numerical analyses (i.e., NLNAs) for design and assessment purposes of slender reinforced concrete (RC) members. The epistemic uncertainty associated to NLNAs may be represented by approximations and choices performed during the definition of a structural numerical model. In order to quantify epistemic uncertainty associated to a non‐linear numerical simulation, the resistance model uncertainty random variable has to be characterized by means of the comparison between experimental and numerical results. With this aim, a set of experimental tests on slender RC columns known from the literature is considered. Then, the experimental results in terms of maximum axial load are compared to the outcomes achieved from NLNAs. Nine different modeling hypotheses are herein considered to characterize the resistance model uncertainty random variable. The probabilistic analysis of the results has been performed according to Bayesian approach accounting also for both the previous knowledge from the scientific literature and the influence of the experimental uncertainty on the estimation of the statistics of the resistance model uncertainty random variable. Finally, the resistance model uncertainty partial safety factor is evaluated in line with the global resistance format of fib Model Code for Concrete Structures 2010 with reference to new and existing RC structures.
Anti‐apoptotic and pro‐survival effects of longan flower extracts on rat hearts with fructose‐induced metabolic syndrome
Authors: Cheng Shiu‐Min , Kumar V. Bharath , Wu Liang‐Yi , Chang Hsiao‐Chuan , Kuo Chia‐Hua , Wei Li‐Shan , Lin Yueh‐Min , Padma V. Vijaya , Lee Shin‐Da , Huang Chih‐Yang 
Published: January 2021

AbstractThe aim of this study was to investigate the effects of longan flower (LF) water extract on cardiac apoptotic and survival pathways in rat models of fructose‐induced metabolic syndrome. The study findings revealed that the levels of glucose, insulin, triglyceride, and cholesterol and TUNEL‐positive apoptotic cells were significantly increased in the HF group compared with the control group; whereas, the levels were decreased in the HFLF group. The expressions of Fas, FADD, and activated caspases 8 and 3, as well as the expressions of Bax, Bak, Bax/Bcl‐2, Bak/Bcl‐xL, cytosolic cytochrome c, and activated caspases 9 and 3 were increased in the HF group were significantly reversed in HFLF administrated group. Furthermore, LF extract increased IGF‐1R, p‐PI3K, p‐Akt, Bcl‐2, and Bcl‐xL expression compared to HF group. Taken together, the present findings help identify LF as a potential cardioprotective agent that can be effectively used in treating fructose‐induced metabolic syndrome.
Hsa_circ_0001073 targets miR‐626/LIFR axis to inhibit lung cancer progression
Authors: Liu Qun , Cao Gang , Wan Yufeng , Xu Chuanqin , He Yuanqiang , Li Gang 
Published: January 2021

AbstractCircular RNAs (circRNAs) are associated with lung cancer progression. However, it is unclear whether and how circRNA hsa_circ_0001073 (circ_0001073) are involved in lung cancer progression. circ_0001073, microRNA (miR)‐626, and leukemia inhibitory factor receptor (LIFR) abundances were determined via quantitative reverse transcription polymerase chain reaction or western blot. Cell viability, invasion, and apoptosis were analyzed by cell counting kit‐8, transwell analysis and flow cytometry, respectively. The target correlation was tested by dual‐luciferase reporter analysis or RNA immunoprecipitation. Results showed that circ_0001073 abundance was down‐regulated in lung cancer cells. circ_0001073 constrained cell viability and invasion and facilitated apoptosis in lung cancer cells. miR‐626 was targeted via circ_0001073, and circ_0001073 inhibited lung cancer progression via reducing miR‐626 expression. LIFR was targeted via miR‐626, and miR‐626 knockdown constrained cell viability and invasion and facilitated apoptosis in lung cancer cells via up‐regulating LIFR. circ_0001073 increased LIFR expression via miR‐626 in lung cancer cells. In conclusion, circ_0001073 represses lung cancer progression via miR‐626/LIFR axis, indicating the potential value of circ_0001073 in lung cancer treatment.
Introgression of “QTL‐hotspot” region enhances drought tolerance and grain yield in three elite chickpea cultivars
Authors: Bharadwaj Chellapilla , Tripathi Shailesh , Soren Khela R. , Thudi Mahendar , Singh Rajesh K. , Sheoran Seema , Roorkiwal Manish , Patil Basavanagouda Siddanagouda , Chitikineni Annapurna , Palakurthi Ramesh , Vemula Anilkumar , Rathore Abhishek , Kumar Yogesh , Chaturvedi Sushil K. , Mondal Biswajit , Shanmugavadivel Pichandampalayam Subramaniam , Srivastava Avinash K. , Dixit Girish P. , Singh Narendra P. , Varshney Rajeev K. 
Published: January 2021

AbstractWith an aim of enhancing drought tolerance using a marker‐assisted backcrossing (MABC) approach, we introgressed the “QTL‐hotspot” region from ICC 4958 accession that harbors quantitative trait loci (QTLs) for several drought‐tolerance related traits into three elite Indian chickpea (Cicer arietinum L.) cultivars: Pusa 372, Pusa 362, and DCP 92‐3. Of eight simple sequence repeat (SSR) markers in the QTL‐hotspot region, two to three polymorphic markers were used for foreground selection with respective cross‐combinations. A total of 47, 53, and 46 SSRs were used for background selection in case of introgression lines (ILs) developed in genetic backgrounds of Pusa 372, Pusa 362, and DCP 92‐3, respectively. In total, 61 ILs (20 BC3F3 in Pusa 372; 20 BC2F3 in Pusa 362, and 21 BC3F3 in DCP 92‐3), with >90% recurrent parent genome recovery were developed. Six improved lines in different genetic backgrounds (e.g. BGM 10216 in Pusa 372; BG 3097 and BG 4005 in Pusa 362; IPC(L4‐14), IPC(L4‐16), and IPC(L19‐1) in DCP 92‐3) showed better performance than their respective recurrent parents. BGM 10216, with 16% yield gain over Pusa 372, has been released as Pusa Chickpea 10216 by the Central Sub‐Committees on Crop Standards, Notification and Release of Varieties of Agricultural Crops, Ministry of Agriculture and Farmers Welfare, Government of India, for commercial cultivation in India. In summary, this study reports introgression of the QTL‐hotspot for enhancing yield under rainfed conditions, development of several introgression lines, and release of Pusa Chickpea 10216 developed through molecular breeding in India.
Estimating antimicrobial usage based on sales to beef and dairy farms from UK veterinary practices
Authors: Humphry Roger William , Henry Madeleine Kate , Reeves Aaron , Correia‐Gomes Carla , Innocent Giles Thomas , Smith R. , Mason Colin Stuart , Gunn George John , Tongue Sue C. 
Published: January 2021

AbstractBackground: Accurate estimation of antimicrobial use (AMU) is important in assessing reduction of agricultural AMU. This cross‐sectional study aimed to evaluate several approaches for estimating AMU at the herd level and to report on AMU for beef and dairy farms in Scotland.Methods: Pharmaceutical sales data for 75 cattle herds (2011‐2015) were screened for antimicrobial products and aggregated by herd and year. Several denominators for usage estimates were calculated and compared for their suitability at the herd level.Results: The median total mass of active ingredient sold per kg of bovine livestock was 9.5 mg/kg for beef herds and 14.3 mg/kg for dairy herds. The ‘highest priority critically important’ antimicrobials (HPCIA) were by total mass of active ingredient, 10.6% of all sales; by total defined daily dose veterinary (DDDVet), 29.8% and by DCDvet, 20.0%. These are the first estimates of AMU for beef cattle in the UK, and for cattle of any kind in Scotland. Estimates of herd‐level usage based on population correction unit (PCU) were sensitive to low values for PCU for specific herd‐years due to their demographic composition.Conclusion: Pharmaceutical sales data can provide useful estimates of AMU, but estimating usage per PCU is not appropriate for comparing groups of cattle with different demographic compositions or for setting herd‐level targets. Total mass of active ingredient per kilogram of livestock is more stable and hence suitable than PCU‐based methods for assessing AMU at the herd level.
Prognostic markers and their discriminant score in predicting the outcome of Babesia gibsoni infection
Authors: Kandasamy Rajamanickam , Venkatasubramanian Leela , Loganathasamy Karuppusamy , Latha Bhaskaran Ravi , Mani Balagangatharathilagar 
Published: January 2021

AbstractBackground: We aimed to identify prognostic markers and their discriminant score in predicting the lethal outcome of canine Babesia gibsoni.Methods: Blood samples were collected from 108 client‐owned dogs with clinical signs commensurate with babesiosis to analyze haematological, biochemical, haemostatic, antioxidant profile and thiobarbituric acid reactive substance levels. Samples were screened for Babesia infection (microscopic and molecular techniques). Babesiosis‐affected dogs were classified into survivors and non‐survivors, and 30 healthy dogs were used in the control group.Results: Haemoglobin, thrombocytes, catalase, urea, creatinine, alanine aminotransferase (ALT), alkaline phosphatase, lactate and reticulocytes were highly correlated to survival. Receiver operating characteristics analysis revealed urea, ALT and lactate as specific prognostic markers for the disease. The formula for calculation of discriminant scores (Di) for lethal outcome of the disease was generated with cut‐off score 0.141. The scoring system was 79% sensitive and 83% specific in predicting the lethal outcome of the disease.Conclusions: A scoring system developed from the prognosticating markers may aid in predicting the outcome of Babesia gibsoni infection on the day of presentation itself enabling intensive care for those animals with a cut‐off score more than 0.141.
Surgical management and histopathology of wen overgrowth and neoplasia in four oranda goldfish (Carassius auratus)
Authors: Mones Alissa , Schreeg Megan , Sommer Samantha , Linder Keith , Lewbart Gregory 
Published: January 2021

AbstractThe wen is a cap of gelatinous soft tissue that extends over the head and face of many varieties of fancy goldfish (Carassius auratus). Here, we describe the surgical management and histopathology of four fish with proliferative wen lesions. All fish were anesthetized for debulking or biopsy of the affected wen. One fish was diagnosed with wen hyperplasia, one fish was diagnosed with wen hyperplasia with a concurrent spindle cell neoplasm, and two fish were diagnosed with epithelial neoplasms of the wen, including a carcinoma arising within a papilloma and an epidermal papilloma with spindle cell and hyalinized matrix proliferation. This is the first published report of neoplasia in the wen of fancy goldfish. Regular evaluation of the wen during routine physical examinations may allow for biopsy of wen lesions, leading to early diagnosis and treatment interventions.
Engineered nanomedicines for tumor vasculature blockade therapy
Authors: Zhao Duoyi , Huang Xu , Zhang Zhiyu , Ding Jianxun , Cui Yan , Chen Xuesi 
Published: January 2021

AbstractTumor vasculature blockade therapy (TVBT), including angiogenesis inhibition, vascular disruption, and vascular infarction, provides a promising treatment modality for solid tumors. However, low selectivity, drug resistance, and possible severe side effects have limited the clinical transformation of TVBT. Engineered nanoparticles offer potential solutions, including prolonged circulation time, targeted transportation, and controlled release of TVBT agents. Moreover, engineered nanomedicines provide a promising combination platform of TVBT with chemotherapy, radiotherapy, photodynamic therapy, photothermal therapy, ultrasound therapy, and gene therapy. In this article, we offer a comprehensive summary of the current progress of engineered nanomedicines for TVBT and also discuss current deficiencies and future directions for TVBT development.This article is categorized under:
Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease
Therapeutic Approaches and Drug Discovery > Emerging Technologies
Analysis Protocols for MRI Mapping of Renal T1
Authors: Garteiser Philippe , Pagé Gwenaël , Doblas Sabrina , Bane Octavia , Hectors Stefanie , Friedli Iris , Van Beers Bernard E. , Waterton John C. 
Published: January 2021

AbstractThe computation of T1 maps from MR datasets represents an important step toward the precise characterization of kidney disease models in small animals. Here the main strategies to analyze renal T1 mapping datasets derived from small rodents are presented. Suggestions are provided with respect to essential software requirements, and advice is provided as to how dataset completeness and quality may be evaluated. The various fitting models applicable to T1 mapping are presented and discussed. Finally, some methods are proposed for validating the obtained results.This chapter is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This analysis protocol chapter is complemented by two separate chapters describing the basic concept and experimental procedure.