bluuebunny/crossref_metadata_2025_split huggingface dataset:
Water, energy and climate benefits of urban greening throughout Europe under different climatic scenarios
Authors: Quaranta Emanuele , Dorati Chiara , Pistocchi Alberto 
Published: June 2021

AbstractUrban greening is an effective mitigation option for climate change in urban areas. In this contribution, a European Union (EU)-wide assessment is presented to quantify the benefits of urban greening in terms of availability of green water, reduction of cooling costs and CO2 sequestration from the atmosphere, for different climatic scenarios. Results show that greening of 35% of the EU’s urban surface (i.e. more than 26,000 km2) would avoid up to 55.8 Mtons year−1 CO2 equivalent of greenhouse gas emissions, reducing energy demand for the cooling of buildings in summer by up to 92 TWh per year, with a net present value (NPV) of more than 364 billion Euro. It would also transpire about 10 km3 year−1 of rain water, turning into “green” water about 17.5% of the “blue” water that is now urban runoff, helping reduce pollution of the receiving water bodies and urban flooding. The greening of urban surfaces would decrease their summer temperature by 2.5–6 °C, with a mitigation of the urban heat island effect estimated to have a NPV of 221 billion Euro over a period of 40 years. The monetized benefits cover less than half of the estimated costs of greening, having a NPV of 1323 billion Euro on the same period. Net of the monetized benefits, the cost of greening 26,000 km2 of urban surfaces in Europe is estimated around 60 Euro year−1 per European urban resident. The additional benefits of urban greening related to biodiversity, water quality, health, wellbeing and other aspects, although not monetized in this study, might be worth such extra cost. When this is the case, urban greening represents a multifunctional, no-regret, cost-effective solution.
Menopause impacts human brain structure, connectivity, energy metabolism, and amyloid-beta deposition
Authors: Mosconi Lisa , Berti Valentina , Dyke Jonathan , Schelbaum Eva , Jett Steven , Loughlin Lacey , Jang Grace , Rahman Aneela , Hristov Hollie , Pahlajani Silky , Andrews Randolph , Matthews Dawn , Etingin Orli , Ganzer Christine , de Leon Mony , Isaacson Richard , Brinton Roberta Diaz 
Published: June 2021

AbstractAll women undergo the menopause transition (MT), a neuro-endocrinological process that impacts aging trajectories of multiple organ systems including brain. The MT occurs over time and is characterized by clinically defined stages with specific neurological symptoms. Yet, little is known of how this process impacts the human brain. This multi-modality neuroimaging study indicates substantial differences in brain structure, connectivity, and energy metabolism across MT stages (pre-menopause, peri-menopause, and post-menopause). These effects involved brain regions subserving higher-order cognitive processes and were specific to menopausal endocrine aging rather than chronological aging, as determined by comparison to age-matched males. Brain biomarkers largely stabilized post-menopause, and gray matter volume (GMV) recovered in key brain regions for cognitive aging. Notably, GMV recovery and in vivo brain mitochondria ATP production correlated with preservation of cognitive performance post-menopause, suggesting adaptive compensatory processes. In parallel to the adaptive process, amyloid-β deposition was more pronounced in peri-menopausal and post-menopausal women carrying apolipoprotein E-4 (APOE-4) genotype, the major genetic risk factor for late-onset Alzheimer’s disease, relative to genotype-matched males. These data show that human menopause is a dynamic neurological transition that significantly impacts brain structure, connectivity, and metabolic profile during midlife endocrine aging of the female brain.
Metabolic shift precedes the resolution of inflammation in a cohort of patients undergoing bariatric and metabolic surgery
Authors: Villarreal-Calderon Jose Romeo , Cuellar-Tamez Ricardo , Castillo Elena C. , Luna-Ceron Eder , García-Rivas Gerardo , Elizondo-Montemayor Leticia 
Published: June 2021

AbstractBariatric and metabolic surgery has shown to promote weight loss and reduce systemic inflammation. However, the sequence and timing of events regarding metabolic improvement and inflammation resolution has been rarely explored. Furthermore, data on inflammatory markers of Th17 and Th1 cell responses after bariatric surgery is scarce. We conducted a prospective study in subjects with obesity that underwent bariatric and metabolic surgery, with follow-ups at 3 and 6 months. Anthropometric and metabolic markers such as insulin levels, HOMA-IR, and lipid parameters declined significantly 3 months after surgery; while hs-CRP, TNF-α, IL-1β, IL-6, and IL-8 serum concentrations decreased 6 months after the procedure. Concentrations of Th1 signature and driver cytokines, particularly IFN-γ, IL-12, and IL-18, and of Th17 driver IL-23 also decreased significantly after 6 months. Significant positive correlations between triglyceride levels and hs-CRP, IL-1β, and IFN-γ concentrations, and between Apo B and IFN-γ levels were observed 6 months after bariatric and metabolic surgery. In addition, BMI was associated with hs-CRP and TNF-α concentrations. Fat mass correlated with hs-CRP, TNF-α, and IL-12. Analysis of the temporality of metabolic and inflammatory events suggests that improvement in the metabolic status occurs before resolution of systemic inflammation and may be a requisite for the later event.
Small-scale dissolution test screening tool to select potentially substandard and falsified (SF) medicines requiring full pharmacopoeial analysis
Authors: Rahman Mohammad Sofiqur , Yoshida Naoko , Tsuboi Hirohito , Ishii Yuichiro , Akimoto Yoshio , Kimura Kazuko 
Published: June 2021

AbstractThe purpose of this study was to design a convenient, small-scale dissolution test for extracting potential substandard and falsified (SF) medicines that require full pharmacopoeial analysis. The probability of metronidazole samples complying with the US Pharmacopoeia (USP) dissolution test for immediate-release tablet formulations was predicted from small-scale dissolution test results using the following criteria: (1) 95% confidence interval lower limit (95% CIlow) of the average dissolution rate of any n = 3 of n = 24 units of each sample, and (2) average and minimum dissolution rates for any n = 3 of n = 24 units. Criteria values were optimized via bootstrap sampling with Thinkeye data-mining software. Compliant metronidazole samples in the USP first-stage and second-stage dissolution test showed complying probabilities of 99.7% and 81.0%, respectively, if the average dissolution rate of n = 3 units is equal to or greater than the monograph-specified amount of dissolved drug (Q; 85% of labeled content for metronidazole). The complying probabilities were 100.0% and 79.0%, respectively, if the average dissolution rate of n = 3 units is 91% or higher and the minimum dissolution rate is 87% or higher. Suitable compliance criteria for the small-scale dissolution test are: average dissolution rate of n = 3 units is Q + 6% or more and minimum dissolution rate is Q + 2% or more.
Functional prediction of environmental variables using metabolic networks
Authors: Weber Zendrera Adèle , Sokolovska Nataliya , Soula Hédi A. 
Published: June 2021

AbstractIn this manuscript, we propose a novel approach to assess relationships between environment and metabolic networks. We used a comprehensive dataset of more than 5000 prokaryotic species from which we derived the metabolic networks. We compute the scope from the reconstructed graphs, which is the set of all metabolites and reactions that can potentially be synthesized when provided with external metabolites. We show using machine learning techniques that the scope is an excellent predictor of taxonomic and environmental variables, namely growth temperature, oxygen tolerance, and habitat. In the literature, metabolites and pathways are rarely used to discriminate species. We make use of the scope underlying structure—metabolites and pathways—to construct the predictive models, giving additional information on the important metabolic pathways needed to discriminate the species, which is often absent in other metabolic network properties. For example, in the particular case of growth temperature, glutathione biosynthesis pathways are specific to species growing in cold environments, whereas tungsten metabolism is specific to species in warm environments, as was hinted in current literature. From a machine learning perspective, the scope is able to reduce the dimension of our data, and can thus be considered as an interpretable graph embedding.
The effect of pregnancy on maternal cognition
Authors: Barda Giulia , Mizrachi Yossi , Borokchovich Irina , Yair Lampl , Kertesz Diana Paleacu , Dabby Ron 
Published: June 2021

AbstractTo determine whether there are differences in measures of cognitive function between second and third trimester pregnant women compared to non-pregnant controls. This prospective study comprised 40 pregnant and 40 non-pregnant women, 20–40 years old, native-Hebrew speakers who were recruited from the outpatient clinics during a period of nearly 2 years. The patients underwent cognitive and affective evaluation. The performance on the three following tests: difficult and total items of Verbal Paired Associates, the Digit Span—forward and the Naming Objects and Fingers test scores were significantly better among non- pregnant women. All the other test results were similar between the two groups, including the depression scores. On multivariate linear regression analysis, after adjusting for age and years of education , Verbal Paired Associates total score (p = 0.04), and Naming Objects and Fingers (p = 0.01) remained significantly associated with pregnancy, but not Digit Span (p = 0.09). Our study demonstrates an impairment in memory among pregnant women. Furthermore language skills, particularly naming, were also impaired, a finding which has not been previously described.
Expression pattern and prognostic impact of glycoprotein non-metastatic B (GPNMB) in triple-negative breast cancer
Authors: Huang Yu-Hsiang , Chu Pei-Yi , Chen Ji-Lin , Huang Chun-Teng , Huang Chi-Cheng , Tsai Yi‐Fang , Wang Yu-Ling , Lien Pei-Ju , Tseng Ling-Ming , Liu Chun-Yu 
Published: June 2021

AbstractGlycoprotein non-metastatic B (GPNMB) is a transmembrane protein overexpressed in numerous cancers including triple-negative breast cancers (TNBC). It has been linked to promote cancer aggressiveness and implicated as a novel target for GPNMB-expressing cancers. In current study, we aimed to explore the clinical significance of GPNMB in TNBC. Among 759 specimens, immunohistochemistry (IHC) exhibited GPNMB expressions were variable in different subtypes and significantly higher in TNBC. Kaplan–Meier analysis revealed GPNMB overexpression in TNBC was associated with worse prognosis especially distant metastasis (P = 0.020, HR = 2.515, CI 1.154–5.480). Multivariate analysis showed GPNMB expression was an independent prognostic factor in terms of recurrence and distant metastasis (P = 0.008, HR = 3.22, CI 1.36–7.61; P = 0.017, HR = 3.08, CI 1.22–7.74). In silico analysis showed high mRNA expression of GPNMB was associated with distant metastasis and GPNMB was overexpressed in TNBC. Furthermore, GPNMB positively correlated with epithelial–mesenchymal transition (EMT) regulators, mesenchymal marker vimentin, MMP and integrins. The protein levels of Twist and MMP2 were upregulated by GPNMB overexpression in TNBC cells. GPNMB-enhanced cell invasion was attenuated by broad spectrum MMP inhibitor (GM 6001) and the selective inhibitor of MMP-2 (ARP100). In summary, GPNMB expression is prevalent in TNBC and may be implicated as a prognostic biomarker in patients with TNBC.
Transcriptome and metabolome analyses revealing the potential mechanism of seed germination in Polygonatum cyrtonema
Authors: Liu Rong , Lu Jing , Xing Jiayi , Du Mei , Wang Mingxiu , Zhang Lei , Li Yunfang , Zhang Chihong , Wu Yu 
Published: June 2021

AbstractPolygonatum cyrtonema Hua (Huangjing, HJ) has medicinal and edible value in China. However, the seeds of this plant are naturally difficult to germinate. Therefore, to elucidate the mechanism underlying the germination of this plant in order to meet the market demand, the metabolomic and transcriptomic analyses were performed in this study. We observed that plant hormones and α-amylase activity were differentially regulated when comparing germinated and un-germinated seeds. In addition, the metabolites related to phenylpropanoid and flavonoid biosynthesis were significantly up-accumulated in germinated seeds. Hydroxycinnamoyl derivatives and organic acids were observed to be significantly decreased during germination. The results of this study suggested that compared to un-germinated seeds, germinated seeds promote flavonoid synthesis and inhibit lignin synthesis which could be beneficial to the germination of HJ seeds. Furthermore, these results suggested that starch if hydrolyzed into glucose, which could provide the necessary energy for germination. Our results may help to establish a foundation for further research investigating the regulatory networks of seed germination and may facilitate the propagation of HJ seeds.
A network meta-analysis and systematic review of change in QRS duration after left bundle branch pacing, His bundle pacing, biventricular pacing, or right ventricular pacing in patients requiring permanent pacemaker
Authors: Tokavanich Nithi , Prasitlumkum Narut , Mongkonsritragoon Wimwipa , Cheungpasitporn Wisit , Thongprayoon Charat , Vallabhajosyula Saraschandra , Chokesuwattanaskul Ronpichai 
Published: June 2021

AbstractCardiac dyssynchrony is the proposed mechanism for pacemaker-induced cardiomyopathy, which can be prevented by biventricular pacing. Left bundle branch pacing and His bundle pacing are novel interventions that imitate the natural conduction of the heart with, theoretically, less interventricular dyssynchrony. One of the surrogate markers of interventricular synchrony is QRS duration. Our study aimed to compare the change of QRS duration before and after implantation between types of cardiac implantable electronic devices (CIEDs): left bundle branch pacing versus His bundle pacing versus biventricular pacing and conventional right ventricular pacing. A literature search for studies that reported an interval change of QRS duration after CIED implantation was conducted utilizing the MEDLINE, EMBASE, and Cochrane databases. All relevant works from database inception through November 2020 were included in this analysis. A random-effects model, Bayesian network meta-analysis was used to analyze QRS duration changes (eg, electrical cardiac synchronization) across different CIED implantations. The mean study sample size, from 14 included studies, was 185 subjects. The search found 707 articles. After exclusions, 14 articles remained with 2,054 patients. The His bundle pacing intervention resulted in the most dramatic decline in QRS duration (mean difference, − 53 ms; 95% CI − 67, − 39), followed by left bundle branch pacing (mean difference, − 46 ms; 95% CI − 60, − 33), and biventricular pacing (mean difference, − 19 ms; 95% CI − 37, − 1.8), when compared to conventional right ventricle apical pacing. When compared between LBBP and HBP, showed no statistically significant wider QRS duration in LBBP with mean different 6.5 ms. (95% CI − 6.7, 21). Our network meta-analysis found that physiologic pacing has the greatest effect on QRS duration after implantation. Thus, HBP and LBBP showed no significant difference between QRS duration after implantation. Physiologic pacing interventions result in improved electrocardiography markers of cardiac synchrony, narrower QRS duration, and might lower electromechanical dyssynchrony.
Clinical significance of tacrolimus intra-patient variability on kidney transplant outcomes according to pre-transplant immunological risk
Authors: Kim Eun Jin , Kim Soo Jin , Huh Kyu Ha , Kim Beom Seok , Kim Myoung Soo , Kim Soon Il , Kim Yu Seun , Lee Juhan 
Published: June 2021

AbstractHigh intra-patient variability (IPV) of tacrolimus trough concentrations is increasingly recognized as a predictor of poor long-term outcomes in kidney transplant. However, there is a lack of information regarding the association between tacrolimus IPV and graft outcomes according to immunological risk. We analyzed tacrolimus IPV using the coefficient of variability from months 6–12 after transplantation in 1080 kidney transplant recipients. Patients were divided into two immunological risk groups based on pre-transplant panel reactive antibodies and donor-specific antibodies. High immunological risk was defined as panel reactive antibodies ≥ 20% or the presence of donor-specific antibodies. The effects of tacrolimus IPV on graft outcomes were significantly different between low and high immunological risk patients. A multivariable Cox regression model confirmed that high tacrolimus IPV was an independent risk factor for graft failure in the high risk group (HR, 2.90; 95% CI, 1.42–5.95, P = 0.004). In the high risk group, high tacrolimus IPV was also significantly associated with increased risk of antibody-mediated rejection (P = 0.006). In contrast, death-censored graft survival and antibody-mediated rejection in the low immunological risk group was not significantly different by tacrolimus IPV. High tacrolimus IPV significantly increases the risk of graft failure and antibody-mediated rejection in patients with high immunological risk.
Preoperative estimate of natural ureteral length based on computed tomography and/or plain radiography
Authors: Hsu Jen-Ting , Tseng Jen-Shu , Chen Marcelo , Sun Fang-Ju , Chen Chien-Wen , Lin Wun-Rong , Chiang Pai-Kai , Chiu Allen W. 
Published: June 2021

AbstractTo predict natural ureter lengths based on clinical images. We reviewed our image database of patients who underwent multiphasic computed tomography urography from January 2019 to April 2020. Natural ureteral length (ULCTU) was measured using a three-dimensional curved multiplanar reformation technique. Patient parameters including age, height, and height of the lumbar spine, the index of ureteral length using kidney/ureter/bladder (KUB) radiographs (C-P and C-PS) and computed tomography (ULCT) were collected. ULCTU correlated most strongly with ULCT. R square and adjusted R square values from multivariate regression were 0.686 and 0.678 (left side) and 0.516 and 0.503 (right side), respectively. ULCTU could be estimated by the regression model in three different scenarios as follows:

ULCT + C-P

ULCTUL = 0.405 $$\times$$
×
ULCTL$$+$$
+
0.626 $$\times$$
×
C-PL – 0.508 cm

ULCTUR = 0.558 $$\times$$
×
ULCTR$$+$$
+
0.218 $$\times$$
×
C-PR + 6.533 cm

ULCT

ULCTUL = 0.876 $$\times$$
×
ULCTL$$+$$
+
6.337 cm

ULCTUR = 0.710 $$\times$$
×
ULCTR$$+$$
+
9.625 cm

C-P

ULCTUL = 0.678 $$\times$$
×
C-PL$$+$$
+
4.836 cm

ULCTUR = 0.495 $$\times$$
×
C-PR$$+$$
+
10.353 cm

We provide equations to predict ULCTU based on CT, KUB or CT plus KUB for different clinical scenarios. The formula based on CT plus KUB provided the most accurate estimation, while the others had lower validation values but could still meet clinical needs.
Design of mid-infrared filter array based on plasmonic metal nanodiscs array and its application to on-chip spectrometer
Authors: Lee Hwa-Seub , Hwang Gyu-Weon , Seong Tae-Yeon , Park Jongkil , Kim Jae Wook , Kim Won Mok , Kim Inho , Lee Kyeong-Seok 
Published: June 2021

AbstractMid-infrared wavelengths are called the molecular fingerprint region because it contains the fundamental vibrational modes inherent to the substances of interest. Since the mid-infrared spectrum can provide non-destructive identification and quantitative analysis of unknown substances, miniaturized mid-infrared spectrometers for on-site diagnosis have attained great concern. Filter-array based on-chip spectrometer has been regarded as a promising alternative. In this study, we explore a way of applying a pillar-type plasmonic nanodiscs array, which is advantageous not only for excellent tunability of resonance wavelength but also for 2-dimensional integration through a single layer process, to the multispectral filter array for the on-chip spectrometer. We theoretically and experimentally investigated the optical properties of multi-periodic triangular lattices of metal nanodiscs array that act as stopband filters in the mid-infrared region. Soft-mold reverse nanoimprint lithography with a subsequent lift-off process was employed to fabricate the multispectral filter array and its filter function was successfully extracted using a Fourier transform infrared microscope. With the measured filter function, we tested the feasibility of target spectrum reconstruction using a Tikhonov regularization method for an ill-posed linear problem and evaluated its applicability to the infrared spectroscopic sensor that monitors an oil condition. These results not only verify that the multispectral filter array composed of stopband filters based on the metal nanodiscs array when combined with the spectrum reconstruction technique, has great potential for use to a miniaturized mid-infrared on-chip spectrometer, but also provide effective guidance for the filter design.
XGBoost based machine learning approach to predict the risk of fall in older adults using gait outcomes
Authors: Noh Byungjoo , Youm Changhong , Goh Eunkyoung , Lee Myeounggon , Park Hwayoung , Jeon Hyojeong , Kim Oh Yoen 
Published: June 2021

AbstractThis study aimed to identify the optimal features of gait parameters to predict the fall risk level in older adults. The study included 746 older adults (age: 63–89 years). Gait tests (20 m walkway) included speed modification (slower, preferred, and faster-walking) while wearing the inertial measurement unit sensors embedded in the shoe-type data loggers on both outsoles. A metric was defined to classify the fall risks, determined based on a set of questions determining the history of falls and fear of falls. The extreme gradient boosting (XGBoost) model was built from gait features to predict the factor affecting the risk of falls. Moreover, the definition of the fall levels was classified into high- and low-risk groups. At all speeds, three gait features were identified with the XGBoost (stride length, walking speed, and stance phase) that accurately classified the fall risk levels. The model accuracy in classifying fall risk levels ranged between 67–70% with 43–53% sensitivity and 77–84% specificity. Thus, we identified the optimal gait features for accurate fall risk level classification in older adults. The XGBoost model could inspire future works on fall prevention and the fall-risk assessment potential through the gait analysis of older adults.