bluuebunny/crossref_metadata_2025_split huggingface dataset:
Temporal dynamics, patterns and correlates of single and multimorbidity in India, 1994–2018
Authors: Puri Parul , Singh Shri Kant , Pati Sanghamitra 
Published: December 2021

Objective As a consequence of the epidemiological transition, multimorbidity has been identified as a critical public health challenge in India. The majority of the studies in the domain are grounded on hospital-based data or are based on small sample size, findings from which can only be generalized to a specific sub-group. These studies recommend exploring multimorbidity holistically at a national level to ensure adequate healthcare management in the country. Therefore, the present study examines the pattern and correlates of single and multimorbidity over the past two decades in India. Methods The study utilized data on 397901, 257519, and 399705 individuals from 52nd (1994–1995), 60th (2004–2005), and 75th (2018) rounds of cross-sectional data from the National Sample Survey (NSS). Univariate, bivariate, and multivariable statistical methods were applied to draw inferences from the data. The findings depict an increase in single and multimorbidity burden over individuals’ age and NSS rounds. Results Hypertension and diabetes were the fastest-growing morbidities over time. Higher education, urban residence, and belonging to an affluent class were significantly associated with both single and multimorbidity occurrence over time. Conclusion The burden of single and multimorbidity increases over time among India’s older adults. Therefore, there is an urgent need to recuperate chronic disease management strategies for older adults in the Indian healthcare infrastructure.
RSDM: A Powerful Direct Method to Predict the Asymptotic Cyclic Behavior of Elastoplastic Structures
Authors: Spiliopoulos Konstantinos V. , Kapogiannis Ioannis A. 
Published: December 2021

AbstractMechanical engineering structures and structural components are often subjected to cyclic thermomechanical loading which stresses their material beyond its elastic limits well inside the inelastic regime. Depending on the level of loading inelastic strains may lead either to failure, due to low cycle fatigue or ratcheting, or to safety, through elastic shakedown. Thus, it is important to estimate the asymptotic stress state of such structures. This state may be determined by cumbersome incremental time-stepping calculations. Direct methods, alternatively, have big computational advantages as they focus on the characteristics of these states and try to establish them, in a direct way, right from the beginning of the calculations. Among the very few such general-purpose direct methods, a powerful direct method which has been called RSDM has appeared in the literature. The method may directly predict any asymptotic state when the exact time history of the loading is known. The advantage of the method is due to the fact that it addresses the physics of the asymptotic cycle and exploits the cyclic nature of its expected residual stress distribution. Based on RSDM a method for the shakedown analysis of structures, called RSDM-S has also been developed. Despite most direct methods for shakedown, RSDM-S does not need an optimization algorithm for its implementation. Both RSDM and RSDM-S may be implemented in any Finite Element Code. A thorough review of both these methods, together with examples of implementation are presented herein.
Impact of age and sex on the efficacy of fremanezumab in patients with difficult-to-treat migraine: results of the randomized, placebo-controlled, phase 3b FOCUS study
Authors: MaassenVanDenBrink Antoinette , Terwindt Gisela M. , Cohen Joshua M. , Barash Steve , Campos Verena Ramirez , Galic Maja , Ning Xiaoping , Kärppä Mikko 
Published: December 2021

Abstract
Background
Migraine prevalence is age and sex dependent, predominating in women in early and middle adulthood; however, migraine also represents a substantial burden for men and adults of all ages. Thus, understanding this burden and the efficacy of migraine preventive medications in both sexes and across age groups is critical. The randomized, placebo-controlled, double-blind, phase 3b FOCUS study demonstrated the safety and efficacy of fremanezumab, a fully humanized monoclonal antibody (IgG2∆a) that selectively targets calcitonin gene-related peptide as a migraine preventive treatment for individuals with migraine and prior inadequate response to 2 to 4 migraine preventive medication classes. Here, we assessed the efficacy of fremanezumab in participants from FOCUS subgrouped by age (18–45 years and > 45 years) and sex.

Methods
In the FOCUS study, eligible participants were randomized (1:1:1) to 12 weeks of double-blind treatment with quarterly fremanezumab, monthly fremanezumab, or matched monthly placebo. In this post hoc analysis, we evaluated changes from baseline in monthly migraine days (primary endpoint of FOCUS) and other secondary and exploratory efficacy outcomes in prespecified age (18–45 and > 45 years) and sex subgroups.

Results
The modified intention-to-treat population (received ≥ 1 dose of study drug and had ≥ 10 days of postbaseline efficacy assessments for the primary endpoint) totaled 837 participants (18–45 years, n = 373; > 45 years, n = 464; male, n = 138; female, n = 699). Consistent reductions in monthly average number of migraine days during 12 weeks were observed, regardless of age (18–45 years: quarterly fremanezumab, − 4.1 days; monthly fremanezumab, − 4.7 days; placebo, − 0.9 days; P < 0.001; > 45 years: quarterly fremanezumab, − 3.6 days; monthly fremanezumab, − 3.7 days; placebo, − 0.3 days; P < 0.001) and sex (male: quarterly fremanezumab, − 4.1 days; monthly fremanezumab, − 4.6 days; placebo, − 0.3 days; P < 0.001; female: quarterly fremanezumab, − 3.6 days; monthly fremanezumab, − 3.9 days; placebo, − 0.6 days; P < 0.001). Fremanezumab also reduced monthly headache days of at least moderate severity, monthly days of acute medication use, and improved Migraine Disability Assessment scores across subgroups.

Conclusions
These results demonstrate the efficacy of fremanezumab in patients with difficult-to-treat migraine for reducing migraine and headache days, acute medication use, and disability, regardless of age or sex.

Trial registration
ClinicalTrials.gov Identifier NCT03308968 (FOCUS), registered October 13, 2017.
The relationship between headache-attributed disability and lost productivity: 2. Empirical evidence from population-based studies in nine disparate countries
Authors: Thomas Hallie , Kothari Simple Futarmal , Husøy Andreas , Jensen Rigmor Højland , Katsarava Zaza , Tinelli Michela , Steiner Timothy J. 
Published: December 2021

Abstract
Background
Headache disorders are disabling, with major consequences for productivity, yet the literature is silent on the relationship between headache-attributed disability and lost productivity, often erroneously regarding the two as synonymous. We evaluated the relationship empirically, having earlier found that investment in structured headache services would be cost saving, not merely cost-effective, if reductions in headache-attributed disability led to > 20% pro rata recovery of lost productivity.

Methods
We used individual participant data from Global Campaign population-based studies conducted in China, Ethiopia, India, Nepal, Pakistan and Russia, and from Eurolight in Lithuania, Luxembourg and Spain. We assessed relationships in migraine and probable medication-overuse headache (pMOH), the most disabling common headache disorders. Available symptom data included headache frequency, usual duration and usual intensity. We used frequency and duration to estimate proportion of time in ictal state (pTIS). Disability, in the sense used by the Global Burden of Disease study, was measured as the product of pTIS and disability weight for the ictal state. Impairment was measured as pTIS * intensity. Lost productivity was measured as lost days (absence or < 50% productivity) from paid work and corresponding losses from household work over the preceding 3 months. We used Spearman correlation and linear regression analyses.

Results
For migraine, in a linear model, we found positive associations with lost paid worktime, significant (p < 0.05) in many countries and highly significant (p < 0.001) in some despite low values of R2 (0–0.16) due to high variance. With lost household worktime and total lost productivity (paid + household), associations were highly significant in almost all countries, although still with low R2 (0.04–0.22). Applying the regression equations for each country to the population mean migraine-attributed disability, we found pro rata recoveries of lost productivity in the range 16–56% (> 20% in all countries but Pakistan). Analysing impairment rather than disability increased variability. For pMOH, with smaller numbers, associations were generally weaker, occasionally negative and mostly not significant.

Conclusion
Relief of disability through effective treatment of migraine is expected, in most countries, to recover > 20% pro rata of lost productivity, above the threshold for investment in structured headache services to be cost saving.
Assessing Bos taurus introgression in the UOA Bos indicus assembly
Authors: Naji Maulana M. , Utsunomiya Yuri T. , Sölkner Johann , Rosen Benjamin D. , Mészáros Gábor 
Published: December 2021

Abstract
Background
Reference genomes are essential in the analysis of genomic data. As the cost of sequencing decreases, multiple reference genomes are being produced within species to alleviate problems such as low mapping accuracy and reference allele bias in variant calling that can be associated with the alignment of divergent samples to a single reference individual. The latest reference sequence adopted by the scientific community for the analysis of cattle data is ARS_UCD1.2, built from the DNA of a Hereford cow (Bos taurus taurus—B. taurus). A complementary genome assembly, UOA_Brahman_1, was recently built to represent the other cattle subspecies (Bos taurus indicus—B. indicus) from a Brahman cow haplotype to further support analysis of B. indicus data. In this study, we aligned the sequence data of 15 B. taurus and B. indicus breeds to each of these references.

Results
The alignment of B. taurus individuals against UOA_Brahman_1 detected up to five million more single-nucleotide variants (SNVs) compared to that against ARS_UCD1.2. Similarly, the alignment of B. indicus individuals against ARS_UCD1.2 resulted in one and a half million more SNVs than that against UOA_Brahman_1. The number of SNVs with nearly fixed alternative alleles also increased in the alignments with cross-subspecies. Interestingly, the alignment of B. taurus cattle against UOA_Brahman_1 revealed regions with a smaller than expected number of counts of SNVs with nearly fixed alternative alleles. Since B. taurus introgression represents on average 10% of the genome of Brahman cattle, we suggest that these regions comprise taurine DNA as opposed to indicine DNA in the UOA_Brahman_1 reference genome. Principal component and admixture analyses using genotypes inferred from this region support these taurine-introgressed loci. Overall, the flagged taurine segments represent 13.7% of the UOA_Brahman_1 assembly. The genes located within these segments were previously reported to be under positive selection in Brahman cattle, and include functional candidate genes implicated in feed efficiency, development and immunity.

Conclusions
We report a list of taurine segments that are in the UOA_Brahman_1 assembly, which will be useful for the interpretation of interesting genomic features (e.g., signatures of selection, runs of homozygosity, increased mutation rate, etc.) that could appear in future re-sequencing analysis of indicine cattle.
ddPCR allows 16S rRNA gene amplicon sequencing of very small DNA amounts from low-biomass samples
Authors: Abellan-Schneyder Isabel , Schusser Andrea Janina , Neuhaus Klaus 
Published: December 2021

Abstract
Background
One limiting factor of short amplicon 16S rRNA gene sequencing approaches is the use of low DNA amounts in the amplicon generation step. Especially for low-biomass samples, insufficient or even commonly undetectable DNA amounts can limit or prohibit further analysis in standard protocols.

Results
Using a newly established protocol, very low DNA input amounts were found sufficient for reliable detection of bacteria using 16S rRNA gene sequencing compared to standard protocols. The improved protocol includes an optimized amplification strategy by using a digital droplet PCR. We demonstrate how PCR products are generated even when using very low concentrated DNA, unable to be detected by using a Qubit. Importantly, the use of different 16S rRNA gene primers had a greater effect on the resulting taxonomical profiles compared to using high or very low initial DNA amounts.

Conclusion
Our improved protocol takes advantage of ddPCR and allows faithful amplification of very low amounts of template. With this, samples of low bacterial biomass become comparable to those with high amounts of bacteria, since the first and most biasing steps are the same. Besides, it is imperative to state DNA concentrations and volumes used and to include negative controls indicating possible shifts in taxonomical profiles. Despite this, results produced by using different primer pairs cannot be easily compared.
Combined application of biochar and nitrogen fertilizer promotes the activity of starch metabolism enzymes and the expression of related genes in rice in a dual cropping system
Authors: Ali Izhar , Ullah Saif , Iqbal Anas , Quan Zhao , Liang He , Ahmad Shakeel , Muhammad Ihsan , Amanullah  , Imran  , Guo Zixiong , Wei Shangqing , Jiang Ligeng 
Published: December 2021

Abstract
Background
Overuse of chemical fertilizer highly influences grain filling rate and quality of rice grain. Biochar is well known for improving plant growth and grain yield under lower chemical fertilization. Therefore field trials were conducted in the early and late seasons of 2019 at Guangxi University, China to investigate the effects of combined biochar (B) and nitrogen (N) application on rice yield and yield components. There were a total of eight treatments: N1B0, 135 kg N ha− 1+ 0 t B ha− 1; N2B0,180 kg N ha− 1+ 0 t B ha− 1; N1B1,135 kg N ha− 1+ 10 t B ha− 1; N1B2,135kg N ha− 1+ 20 t B ha− 1; N1B3,135 kg N ha− 1+ 30 t B ha− 1; N2B1,180 kg N ha− 1+ 10 t B ha− 1; N2B2,180 kg N ha− 1+ 20 t B ha− 1; and N2B3,180 kg N ha− 1+ 30 t B ha− 1.

Results
Biochar application at 30 t ha− 1combined with low N application (135 kg ha− 1) increased the activity of starch-metabolizing enzymes (SMEs) during the early and late seasons compared with treatments without biochar. The grain yield, amylose concentration, and starch content of rice were increased in plots treated with 30 t B ha−1and low N. RT-qPCR analysis showed that biochar addition combined with N fertilizer application increased the expression of AGPS2b, SSS1, GBSS1, and GBSE11b, which increased the activity of SMEs during the grain-filling period.

Conclusion
Our results suggest that the use of 20 to 30 t B ha− 1coupled with 135 kg N ha− 1 is optimal for improving the grain yield and quality of rice.
Genomic regions and candidate genes linked with Phytophthora capsici root rot resistance in chile pepper (Capsicum annuum L.)
Authors: Lozada Dennis N. , Nunez Guillermo , Lujan Phillip , Dura Srijana , Coon Danise , Barchenger Derek W. , Sanogo Soumaila , Bosland Paul W. 
Published: December 2021

Abstract
Background
Phytophthora root rot, caused by Phytophthora capsici, is a major disease affecting Capsicum production worldwide. A recombinant inbred line (RIL) population derived from the hybridization between ‘Criollo de Morellos-334’ (CM-334), a resistant landrace from Mexico, and ‘Early Jalapeno’, a susceptible cultivar was genotyped using genotyping-by-sequencing (GBS)-derived single nucleotide polymorphism (SNP) markers. A GBS-SNP based genetic linkage map for the RIL population was constructed. Quantitative trait loci (QTL) mapping dissected the genetic architecture of P. capsici resistance and candidate genes linked to resistance for this important disease were identified.

Results
Development of a genetic linkage map using 1,973 GBS-derived polymorphic SNP markers identified 12 linkage groups corresponding to the 12 chromosomes of chile pepper, with a total length of 1,277.7 cM and a marker density of 1.5 SNP/cM. The maximum gaps between consecutive SNP markers ranged between 1.9 (LG7) and 13.5 cM (LG5). Collinearity between genetic and physical positions of markers reached a maximum of 0.92 for LG8. QTL mapping identified genomic regions associated with P. capsici resistance in chromosomes P5, P8, and P9 that explained between 19.7 and 30.4% of phenotypic variation for resistance. Additive interactions between QTL in chromosomes P5 and P8 were observed. The role of chromosome P5 as major genomic region containing P. capsici resistance QTL was established. Through candidate gene analysis, biological functions associated with response to pathogen infections, regulation of cyclin-dependent protein serine/threonine kinase activity, and epigenetic mechanisms such as DNA methylation were identified.

Conclusions
Results support the genetic complexity of the P. capsici–Capsicum pathosystem and the possible role of epigenetics in conferring resistance to Phytophthora root rot. Significant genomic regions and candidate genes associated with disease response and gene regulatory activity were identified which allows for a deeper understanding of the genomic landscape of Phytophthora root rot resistance in chile pepper.
Anthropometric measures and the risk of developing atrial fibrillation: a Swedish Cohort Study
Authors: Zia Isac , Johnson Linda , Memarian Ensieh , Borné Yan , Engström Gunnar 
Published: December 2021

Abstract
Aims
Obesity is a risk factor for several cardiovascular diseases (CVDs), including atrial fibrillation (AF). However, it is less clear whether overall fat or abdominal fat distribution are most important for risk of developing AF. This study investigates how different anthropometric measures correlate to the risk of developing clinical AF in the Malmö Diet and Cancer cohort (MDC-cohort).

Methods
The MDC-cohort (n = 25,961) was examined in 1991–1996. The endpoint was clinical AF diagnosed in a hospital setting, and retrieved via linkage with national registers. Hazard Ratios (HR) for incident AF was calculated in relation to quartiles of body mass index (BMI), waist circumference, waist hip ratio, waist height ratio, body fat percentage, weight and height, using Cox regression with adjustment for age, biological (e.g. blood pressure, diabetes, blood lipid levels), and socioeconomic risk factors.

Results
After adjustment for multiple risk factors, the risk of AF was significantly increased in the 4th versus 1st quartile of weight (HR for men/women = 2.02/1.93), BMI (HR = 1.62/1.52), waist circumference (HR = 1.67/1.63), waist to hip ratio (HR = 1.30/1.24), waist to height ratio (1.37/1.39) and body fat percentage (HR = 1.21/1.45) in men/women. Measures of overall weight (BMI, weight) were slightly more predictive than measures of abdominal obesity (waist hip ratio and waist height ratio) both in men and women.

Conclusion
All measures of obesity were associated with increased risk of developing AF. Both overall obesity and abdominal obesity were related to incidence of AF in this population-based study, although the relationship for overall obesity was stronger.
The roles of predictors in cardiovascular risk models - a question of modeling culture?
Authors: Wallisch Christine , Agibetov Asan , Dunkler Daniela , Haller Maria , Samwald Matthias , Dorffner Georg , Heinze Georg 
Published: December 2021

AbstractBackgroundWhile machine learning (ML) algorithms may predict cardiovascular outcomes more accurately than statistical models, their result is usually not representable by a transparent formula. Hence, it is often unclear how specific values of predictors lead to the predictions. We aimed to demonstrate with graphical tools how predictor-risk relations in cardiovascular risk prediction models fitted by ML algorithms and by statistical approaches may differ, and how sample size affects the stability of the estimated relations.MethodsWe reanalyzed data from a large registry of 1.5 million participants in a national health screening program. Three data analysts developed analytical strategies to predict cardiovascular events within 1 year from health screening. This was done for the full data set and with gradually reduced sample sizes, and each data analyst followed their favorite modeling approach. Predictor-risk relations were visualized by partial dependence and individual conditional expectation plots.ResultsWhen comparing the modeling algorithms, we found some similarities between these visualizations but also occasional divergence. The smaller the sample size, the more the predictor-risk relation depended on the modeling algorithm used, and also sampling variability played an increased role. Predictive performance was similar if the models were derived on the full data set, whereas smaller sample sizes favored simpler models.ConclusionPredictor-risk relations from ML models may differ from those obtained by statistical models, even with large sample sizes. Hence, predictors may assume different roles in risk prediction models. As long as sample size is sufficient, predictive accuracy is not largely affected by the choice of algorithm.
Risk factors of early postoperative bowel obstruction for patients undergoing selective colorectal surgeries
Authors: Yang Shuguang , Zhao Huiying , Yang Jianhui , An Youzhong , Zhang Hua , Bao Yudi , Gao Zhidong , Ye Yingjiang 
Published: December 2021

Abstract
Objective
Postoperative bowel obstruction was one of the most severe complications in patients who received colorectal surgeries. This study aimed to explore risk factors of early postoperative obstruction and to construct a nomogram to predict the possibility of occurrence.

Methods
The records of 1437 patients who underwent elective colorectal surgery in Peking University People’s Hospital from 2015 to 2020 were retrospectively collected. Risk factors of early postoperative bowel obstruction were identified by logistic regression analysis and a nomogram was then constructed. Bootstrap was applied to verify the stability of the model.

Results
COPD, hypothyroidism, probiotic indications, duration of antibiotics, and time to postoperative feeding were identified as independent risk factors and were put into a nomogram for predicting early postoperative bowel obstruction. The nomogram showed robust discrimination, with the area under the receiver operating characteristic curve was 0.894 and was well-calibrated.

Conclusion
A nomogram including independent risk factors of COPD, hypothyroidism, probiotic indications, duration of antibiotics, and time to postoperative feeding were established to predict the risk of early postoperative bowel obstruction.