bluuebunny/crossref_metadata_2025_split huggingface dataset:
Environmental impacts and environmental justice implications of supplementary cementitious materials for use in concrete
Authors: Brinkman Leah , Miller Sabbie A 
Published: June 2021

Abstract
As the second most used material after water and the producer of 8%–9% of anthropogenic greenhouse gas (GHG) emissions, concrete is a key target for environmental sustainability efforts. Of these efforts, a main focus has been the use of industrial byproducts as supplementary cementitious materials (SCMs) to replace some of the cement binder, the source of most of the GHG emissions from concrete production. As byproducts, these SCMs are frequently assumed to have limited or no emissions from production. Our goal is to see if this assumption should continue to drive mitigation efforts and to arrive at a clearer understanding of the contribution of SCMs to the environmental impacts of concrete. Needing further examination are: (1) how environmentally beneficial SCMs are if some of the primary process impacts are attributed to them rather than considering them waste products; (2) whether transporting SCMs creates greater environmental impacts than the materials they are replacing; and (3) whether location of primary processes that result in SCMs as well as location of concrete production creates particular burdens on lower income and minority communities. This work focuses on three of the most common industrial byproduct SCMs, namely silica fume, fly ash (FA), and ground granulated blast furnace slag (BFS), exploring both GHG and particulate matter emissions. We show that allocation of impacts from primary processes dramatically increases emissions attributed to SCMs. High levels of transportation of FA and BFS typically do not result in these SCMs having higher GHG emissions than a 95% clinker-content Portland cement. We find that SCMs may be produced in areas with low income or minority populations then used to lower GHG emissions concrete in another location. As such, beyond common environmental impact assessment methods, the role of environmental justice should be incorporated into impact assessments.
Daily Instrumental and Affective Attitudes About Exercise: An Ecological Momentary Assessment Study
Authors: Emerson Jessica A , Dunsiger Shira , Lee Harold H , Kahler Christopher W , Bock Beth , Williams David M 
Published: June 2021

AbstractBackgroundDaily decisions to exercise may be influenced by day-to-day changes in affective attitudes (AA) and instrumental attitudes (IA) toward exercise. However, the within-day association between AA, IA, and exercise behavior has received little attention.PurposeTo examine the effects of more temporally proximal (daily) AA and IA on daily exercise behavior beyond traditionally assessed distal (at the beginning of an exercise program) AA and IA.MethodsIn the context of a 3-month exercise promotion program (N = 50), distal AA and IA were assessed at baseline. Ecological momentary assessment was used to assess proximal AA, IA, and exercise each day.ResultsBetween-subject differences in distal AA (OR = 1.28, p = .03) and distal IA (OR = 1.34, p = .01) were predictive of average likelihood of exercise each day over the 3-month period. Within-subject differences in proximal AA (OR = 1.19, p = .007), but not proximal IA (OR = 1.11, p = .18), predicted exercise each day beyond the between-subjects effects of distal AA and IA. Exploratory analysis revealed an interaction, such that the within-subjects impact of proximal AA on daily exercise was most evident among individuals who held more negative distal AA at baseline (OR = 0.80, p &lt; .0001).ConclusionsAttitude type (affective versus instrumental) and temporality (distal versus proximal) are important to consider in attempts to predict and understand exercise behavior. In addition to targeting change in distal attitudes, exercise interventions should target changes in daily AA to impact exercise later in the same day.
Hepatocellular Carcinoma
Authors: Jain Anisha , Mazer Benjamin , Deng Yanhong , Ciarleglio Maria , Jain Dhanpat , Taddei Tamar , Zhang Xuchen 
Published: June 2021

Abstract

Objectives
The pathologic differences between hepatocellular carcinoma (HCC) arising in noncirrhotic and cirrhotic livers have not been well studied.

Methods
We performed a retrospective analysis of 378 HCC cases (95 in noncirrhotic, 283 in cirrhotic livers) from pathology archives (2010-2017).

Results
Patients without cirrhosis were more likely to have hepatitis B (13.68% vs 2.83%, P &lt; .001) or no known liver disease (30.53% vs 4.24%, P &lt; .001), while hepatitis C was more common in patients with cirrhosis (65.72% vs 30.53%, P &lt; .001). HCCs in noncirrhotic livers were larger in size (P &lt; .001); were more likely to have a macrotrabecular histologic pattern (13.68% vs 4.95%, P &lt; .01); were more likely to have fibrolamellar (3.16% vs 0%, P = .02), macrotrabecular-massive (13.68% vs 6.01%, P = .03), and clear cell (16.84% vs 6.71%, P &lt; .01) subtypes; have a higher histologic grade (P &lt; .01); be anaplastic tumor cells (P &lt; .001); have a higher rate of vascular invasion (P &lt; .01); and have a higher tumor stage (P = .04).

Conclusions
The findings indicate that HCCs in noncirrhotic livers demonstrate a larger tumor size; have a more macrotrabecular histologic pattern; have fibrolamellar, macrotrabecular-massive, and clear cell subtypes; have a higher tumor grade and stage; have a higher rate of vascular invasion; and have more anaplastic tumor cells compared with cirrhotic livers. Further studies to explore different pathways that promote oncogenesis in noncirrhotic livers are needed to better understand the pathogenesis of HCC.
Impact Evaluation of Coronavirus Disease 2019 Policy: A Guide to Common Design Issues
Authors: Haber Noah A , Clarke-Deelder Emma , Salomon Joshua A , Feller Avi , Stuart Elizabeth A 
Published: June 2021

AbstractPolicy responses to coronavirus disease 2019 (COVID-19), particularly those related to nonpharmaceutical interventions, are unprecedented in scale and scope. However, evaluations of policy impacts require a complex combination of circumstance, study design, data, statistics, and analysis. Beyond the issues that are faced for any policy, evaluation of COVID-19 policies is complicated by additional challenges related to infectious disease dynamics and a multiplicity of interventions. The methods needed for policy-level impact evaluation are not often used or taught in epidemiology, and they differ in important ways that may not be obvious. Methodological complications of policy evaluations can make it difficult for decision-makers and researchers to synthesize and evaluate the strength of the evidence in COVID-19 health policy papers. Here we 1) introduce the basic suite of policy-impact evaluation designs for observational data, including cross-sectional analyses, pre-/post- analyses, interrupted time-series analysis, and difference-in-differences analysis; 2) demonstrate key ways in which the requirements and assumptions underlying these designs are often violated in the context of COVID-19; and 3) provide decision-makers and reviewers with a conceptual and graphical guide to identifying these key violations. Our overall goal is to help epidemiologists, policy-makers, journal editors, journalists, researchers, and other research consumers understand and weigh the strengths and limitations of evidence.
Associations Between Prenatal Exposure to Air Pollution and Congenital Hypothyroidism
Authors: Harari-Kremer Ruthie , Calderon-Margalit Ronit , Korevaar Tim I M , Nevo Daniel , Broday David , Kloog Itai , Grotto Itamar , Karakis Isabella , Shtein Alexandra , Haim Alon , Raz Raanan 
Published: June 2021

Abstract
Adequate thyroid hormone availability is required for normal brain development. Studies have found associations between prenatal exposure to air pollutants and thyroid hormones in pregnant women and newborns. We aimed to examine associations of trimester-specific residential exposure to common air pollutants with congenital hypothyroidism (CHT). All term infants born in Israel during 2009–2015 were eligible for inclusion. We used data on CHT from the national neonatal screening lab of Israel, and exposure data from spatiotemporal air pollution models. We used multivariable logistic regression models to estimate associations of exposures with CHT, adjusting for ethnicity, socioeconomic status, geographical area, conception season, conception year, gestational age, birth weight, and child sex. To assess residual confounding, we used postnatal exposures to the same pollutants as negative controls. The study population included 696,461 neonates. We found a positive association between third-trimester nitrogen oxide exposure and CHT (per interquartile-range change, odds ratio = 1.23, 95% confidence interval: 1.08, 1.41) and a similar association for nitrogen dioxide. There was no evidence of residual confounding or bias by correlation among exposure periods for these associations.
S2L-PSIBLAST: a supervised two-layer search framework based on PSI-BLAST for protein remote homology detection
Authors: Jin Xiaopeng , Liao Qing , Liu Bin 
Published: June 2021

Abstract

Motivation
Protein remote homology detection is a challenging task for the studies of protein evolutionary relationships. PSI-BLAST is an important and fundamental search method for detecting homology proteins. Although many improved versions of PSI-BLAST have been proposed, their performance is limited by the search processes of PSI-BLAST.

Results
For further improving the performance of PSI-BLAST for protein remote homology detection, a supervised two-layer search framework based on PSI-BLAST (S2L-PSIBLAST) is proposed. S2L-PSIBLAST consists of a two-level search: the first-level search provides high-quality search results by using SMI-BLAST framework and double-link strategy to filter the non-homology protein sequences, the second-level search detects more homology proteins by profile-link similarity, and more accurate ranking lists for those detected protein sequences are obtained by learning to rank strategy. Experimental results on the updated version of Structural Classification of Proteins-extended benchmark dataset show that S2L-PSIBLAST not only obviously improves the performance of PSI-BLAST, but also achieves better performance on two improved versions of PSI-BLAST: DELTA-BLAST and PSI-BLASTexB.

Availability and implementation
http://bliulab.net/S2L-PSIBLAST.

Supplementary information
Supplementary data are available at Bioinformatics online.
Toward comprehensive functional analysis of gene lists weighted by gene essentiality scores
Authors: Fan Rui , Cui Qinghua 
Published: June 2021

AbstractMotivationGene functional enrichment analysis represents one of the most popular bioinformatics methods for annotating the pathways and function categories of a given gene list. Current algorithms for enrichment computation such as Fisher’s exact test and hypergeometric test totally depend on the category count numbers of the gene list and one gene set. In this case, whatever the genes are, they were treated equally. However, actually genes show different scores in their essentiality in a gene list and in a gene set. It is thus hypothesized that the essentiality scores could be important and should be considered in gene functional analysis.ResultsFor this purpose, here, we proposed weighted enrichment analysis tool (WEAT) (https://www.cuilab.cn/weat/), a weighted gene set enrichment algorithm and online tool by weighting genes using essentiality scores. We confirmed the usefulness of WEAT using three case studies, the functional analysis of one aging-related gene list, one gene list involved in Lung Squamous Cell Carcinoma and one cardiomyopathy gene list from Drosophila model. Finally, we believe that the WEAT method and tool could provide more possibilities for further exploring the functions of given gene lists.Availability and implementationThe datasets generated and analyzed during the current study are available on our website at https://www.cuilab.cn/weat/.Supplementary informationSupplementary data are available at Bioinformatics online.
Determination of 15 + 1 European Priority Polycyclic Aromatic Hydrocarbons in Smoked Meat Products by Saponification/Solid-Phase Extraction and Gas Chromatography–Mass Spectrometry
Authors: Zhang Liqun , Wu Pinggu , Zhou Hua , Hu Zhengyan , Zhang Nianhua , Wang Liyuan , Zhao Yongxin 
Published: June 2021

Abstract
A method for the determination of 15 + 1 European priority polycyclic aromatic hydrocarbons (EUPAHs) in smoked meat samples by saponification/solid-phase extraction and gas chromatography–mass spectrometry has been developed. Both saponification and solid-phase extraction conditions were optimized, which lead to shorter sample preparation time and excellent sensitivity and selectivity. The optimal saponification condition for the lipid extract of 5.00 g smoked food sample was 5 mL KOH (1.5 mol/L)–ethanol at 70°C for 5 min, and the shorter alkaline treatment time avoided the loss of volatile EUPAHs such as Benzo[c]fluorene. All the EUPAHs showed good linearity in the range between 5.0 and 50.0 ng/mL with correlation coefficients between 0.997 and 1.00. The estimated LODs for the EUPAHs were 0.15–0.30 μg/kg, while the LOQs were 0.50–1.0 μg/kg. The three spiking levels of EUPAHs were 1.0, 2.0 and 5.0 μg/kg, and the average recovery was between 75.2 and 99.6%, while the RSD were 2.3–12.4%. This sensitive and rapid method was successfully applied to smoked meat samples from Zhejiang Province of China, and the results revealed the presence of 13 EUPAHs. Benzo[a]pyrene (BaP) was found in 19 out of 20 samples, with concentration ranging from 0.51 to 4.57 μg/kg. The sum of concentrations of PAH4 (summation of benzo(a)pyrene, chrysene, benzo(a)anthracene, and benzo(b)fluoranthene) were 2.40–53.56 μg/kg.
Patterns of Antibiotic Nonsusceptibility Among Invasive Group A Streptococcus Infections—United States, 2006–2017
Authors: Fay Katherine , Onukwube Jennifer , Chochua Sopio , Schaffner William , Cieslak Paul , Lynfield Ruth , Muse Alison , Smelser Chad , Harrison Lee H , Farley Monica , Petit Susan , Alden Nisha , Apostal Mirasol , Snippes Vagnone Paula , Nanduri Srinivas , Beall Bernard , Van Beneden Chris A 
Published: June 2021

Abstract

Background
Treatment of severe group A Streptococcus (GAS) infections requires timely and appropriate antibiotic therapy. We describe the epidemiology of antimicrobial-resistant invasive GAS (iGAS) infections in the United States (US).

Methods
We analyzed population-based iGAS surveillance data at 10 US sites from 2006 through 2017. Cases were defined as infection with GAS isolated from normally sterile sites or wounds in patients with necrotizing fasciitis or streptococcal toxic shock syndrome. GAS isolates were emm typed. Antimicrobial susceptibility was determined using broth microdilution or whole genome sequencing. We compared characteristics among patients infected with erythromycin-nonsusceptible (EryNS) and clindamycin-nonsusceptible (CliNS) strains to those with susceptible infections. We analyzed proportions of EryNS and CliNS among isolates by site, year, risk factors, and emm type.

Results
Overall, 17 179 iGAS cases were reported; 14.5% were EryNS. Among isolates tested for both inducible and constitutive CliNS (2011–2017), 14.6% were CliNS. Most (99.8%) CliNS isolates were EryNS. Resistance was highest in 2017 (EryNS: 22.8%; CliNS: 22.0%). All isolates were susceptible to β-lactams. EryNS and CliNS infections were most frequent among persons aged 18–34 years and in persons residing in long-term care facilities, experiencing homelessness, incarcerated, or who injected drugs. Patterns varied by site. Patients with nonsusceptible infections were significantly less likely to die. The emm types with &gt;30% EryNS or CliNS included types 77, 58, 11, 83, and 92.

Conclusions
Increasing prevalence of EryNS and CliNS iGAS infections in the US is predominantly due to expansion of several emm types. Clinicians should consider local resistance patterns when treating iGAS infections.
Depression screening and clinical outcomes among adults initiating maintenance hemodialysis
Authors: Fischer Michael J , Streja Elani , Hsiung Jui-Ting , Crowley Susan T , Kovesdy Csaba P , Kalantar-Zadeh Kamyar , Kourany Wissam M 
Published: June 2021

ABSTRACT

Background
Transitioning to maintenance hemodialysis (HD) is a vulnerable period for persons with end-stage renal disease (ESRD), punctuated by high rates of depression, hospitalizations and death. Screening for depression during this time may help to improve patient outcomes but formal inquiry has yet to be conducted. Among a national Veteran cohort, we examined whether depression screening in the year prior to HD initiation led to improved outcomes in the year thereafter.

Methods
Associations between pre-ESRD depression screening and post-ESRD outcomes were examined with Cox proportional hazards models (mortality) and Poisson regression models (hospitalization). Hierarchal adjustment models accounted for sociodemographic, clinical, pre-ESRD care and dialysis characteristics.

Results
The final analytic cohort of the study was 30 013 Veterans of whom 64% underwent pre-ESRD depression screening. During the 12 months post-transition, the crude all-cause mortality rate was 0.32 person-year for those screened and 0.35 person-year for those not screened, while the median (interquartile range) hospitalizations were 2 (2, 2) per year for both groups. In fully adjusted models, pre-ESRD depression screening was associated with a lower risk of mortality [hazard ratio (95% confidence interval): 0.94 (0.90–0.99)] and hospitalization [incidence rate ratio (95% confidence interval): 0.97 (0.9–0.99)].

Conclusion
Depression screening among adults prior to maintenance HD transition may be associated with better outcomes during the following year.
Serum anti-CRP antibodies differentiate etiology and predict relapse in acute tubulointerstitial nephritis
Authors: Huang Jun-Wen , Su Tao , Tan Ying , Wang Jin-Wei , Tang Jia-Wei , Wang Su-Xia , Liu Gang , Zhao Ming-Hui , Yang Li 
Published: June 2021

ABSTRACT

Introduction
Acute tubulointerstitial nephritis (ATIN) is a common cause of acute kidney injury with various etiologies. It has been shown that autoimmune-related ATIN (AI-ATIN) has a higher recurrence rate and a greater likelihood of developing into chronic kidney disease compared with drug-induced ATIN, yet misdiagnosis at renal biopsy is not uncommon.

Methods
Patients who were clinicopathologically diagnosed as ATIN from January 2006 to December 2015 in Peking University First Hospital were enrolled. Clinical, pathological and follow-up data were collected. Serum samples on the day of renal biopsy were collected and tested for anti-C-reactive protein (CRP) antibodies. CRP and its linear peptides were used as coating antigens to detect antibodies. Statistical analysis was used to assess the diagnostic value of the antibodies.

Results
Altogether 146 patients were enrolled. The receiver operating characteristic–area under the curve of the anti-CRP antibody for the identification of late-onset AI-ATIN was 0.750 (95% confidence interval 0.641–0.860, P &lt; 0.001) and the positivity was associated with ATIN relapse (adjusted hazard ratio = 4.321, 95% confidence interval 2.402–7.775, P &lt; 0.001). Antibodies detected by CRP linear peptide 6 (PT6) were superior with regard to differentiating patients with AI-ATIN, while antibodies detected by peptide 17 (PT17) could predict ATIN relapse. Antibodies detected by these two peptides were positively correlated with the severity of tubular dysfunction and pathological injury.

Conclusions
Serum anti-CRP antibody could be used to differentiate late-onset AI-ATIN and predict relapse of ATIN at the time of renal biopsy. The CRP linear peptides PT6 and PT17 could be used as coating antigens to detect anti-CRP antibodies, which may provide more information for the clinical assessment of ATIN.
Non-parametric estimation of the preferential attachment function from one network snapshot
Authors: Pham Thong , Sheridan Paul , Shimodaira Hidetoshi 
Published: June 2021

Abstract
Preferential attachment is commonly invoked to explain the emergence of those heavy-tailed degree distributions characteristic of growing network representations of diverse real-world phenomena. Experimentally confirming this hypothesis in real-world growing networks is an important frontier in network science research. Conventional preferential attachment estimation methods require that a growing network be observed across at least two snapshots in time. Numerous publicly available growing network datasets are, however, only available as single snapshots, leaving the applied network scientist with no means of measuring preferential attachment in these cases. We propose a nonparametric method, called PAFit-oneshot, for estimating preferential attachment in a growing network from one snapshot. PAFit-oneshot corrects for a previously unnoticed bias that arises when estimating preferential attachment values only for degrees observed in the single snapshot. Our work provides a means of measuring preferential attachment in a large number of publicly available one-snapshot networks. As a demonstration, we estimated preferential attachment in three such networks, and found sublinear preferential attachment in all cases. PAFit-oneshot is implemented in the $\textsf{R}$ package $\texttt{PAFit}$.
Revisiting the lipid paradox in ST-elevation myocardial infarction in the Chinese population: findings from the CCC-ACS project
Authors: Sun Haonan , Li Ziping , Song Xiwen , Liu Hangkuan , Li Yongle , Hao Yongchen , Teng Tianmin , Liu Jun , Liu Jing , Zhao Dong , Zhou Xin , Yang Qing ,   the CCC-ACS Investigators
Published: June 2021

Abstract

Aims
Previous observations revealed a negative association between low-density lipoprotein cholesterol (LDL-C) and clinical outcomes following myocardial infarction, i.e., the lower level the higher mortality, which was referred to as lipid paradox. We sought to re-evaluate this association in ST-elevation myocardial infarction (STEMI) in contemporary practice.

Methods and results
We examined the association between admission LDL-C and in-hospital mortality among 44 563 STEMI patients enrolled from 2014 to 2019 in a nationwide registry in China. A total of 43 covariates, which were temporally classified into the following three domains were used for adjustment: (i) pre-admission characteristics; (ii) percutaneous coronary intervention (PCI)-related variables; and (iii) other in-hospital medications. In-hospital mortality was 2.01% (897/44 563). When no covariate adjustment was performed, an inversely ‘J-shaped’ curve was observed between admission LDL-C levels and in-hospital mortality by restricted cubic spline in logistic regression, with a threshold value of &lt;75 mg/dL that associated with increased risk for in-hospital mortality. However, a gradual attenuation for this association was noted when step-wise adjustments were performed, with the threshold values for LDL-C decreasing from 75 mg/dL to 70 mg/dL after accounting for pre-admission characteristics, further to 65 mg/dL after accounting for PCI-related variables, and finally to no statistical association after further adjustment for other in-hospital medications.

Conclusions
In a nationwide registry in China, our findings do not support the lipid paradox in terms of in-hospital mortality in STEMI patients in contemporary practice. Previous findings in this scenario are possibly due to inadequate control for confounders.