bluuebunny/crossref_metadata_2025_split huggingface dataset:
Correlation Between Muscle Strength Asymmetry and Its Impact on Functional Scores after Ankle Sprain Rehabilitation
Authors: Mohriak Rafael , Mansur Nacime SB , Alloza José Felipe M. 
Published: November 2022

Category: Sports; Ankle Introduction/Purpose: Ankle sprain is one of the most common sports-related injuries. Treatment of these lesions can be performed conservatively with satisfactory results in up to 80% of cases. The main goals of rehabilitation are the recovery of mobility, strength and balance; but there is no consensus on decision make criteria to return to sport. It is known that the time elapsed from trauma may be insufficient reference and may induce early return, while the individual still does not have symmetric parameters of mobility, strength and proprioception. Purpose: To assess the proportionality of muscle strength between the healthy and rehabilitated sides 16 weeks after ankle sprain related to physical activity and to correlate with its impact on function scores. Methods: 131 individuals, from 18 to 64 years old, were evaluated after rehabilitation of simple sprain. Physical examination was performed with anterior drawer test, measurement of leg circumference by perimetry and by the method of figure in '8'; determination of active and passive range of motion using goniometer; muscle strength conference with hand held dynamometer and finally with the application of function scores. Equality test between two proportions, T-student test, Chi-square test and Pearson correlation were used to determine the significance between the values and correlations found. Results: We identified an average age of 36.1 (+- 2.5) years, 56 (42.70%) women and 75 (57.30%) men. 19.8% of sprains were severe. Limb volume and range of motion evaluations did not show significant differences. The anterior drawer remained positive in 19.1% of the individuals with the highest proportion in severe sprains (36.6%). Force asymmetry for flexion (52.7%), extension (50.4%), eversion (46.6%) and inversion (56.5%) movements above the 10% limit were observed. Impact on function scores showed a moderate correlation (0.59) with the proportionality of ankle extension forces. Conclusion: Individuals adequately rehabilitated after an ankle sprain and considered able to return to sports may present changes anterior drawer test and asymmetries in lower limb muscle strength impacting performance on function scores.
Zaykovite, Rh3Se4, a new mineral from the Kazan placer, South Urals, Russia
Authors: Belogub Elena V. , Britvin Sergey N. , Shilovskikh Vladimir V. , Pautov Leonid A. , Kotlyarov Vasiliy A. , Zaykova Elisaveta V. 
Published: November 2022

AbstractZaykovite, ideally Rh3Se4, is a new mineral, the first natural rhodium selenide. It was discovered in the assemblages of platinum-group minerals from the Kazan gold placer, South Urals, Russia. The mineral occurs as crystals up to 40 μm in size within the grains of Pt3Fe alloy, in association with unnamed Pd–Sb–Te phase and Au–Pd alloy. In reflected light, zaykovite has a grey colour with bluish-greenish tint; it shows weak bireflectance and anisotropy. Reflectance values [Rmax/Rmin(%) for COM approved wavelengths (nm)] are: 30.1/29.3(470), 32.2/31.0(546), 33.4/32.0(589) and 35.1/33.7(650). The chemical composition corresponds to the empirical formula (Rh2.26Pt0.46Ir0.25Ru0.01Pd0.01Fe0.01)Σ3.00(Se2.77S1.21Te0.02)Σ4.00Zaykovite is monoclinic, space groupC2/m,a= 10.877(1),b= 11.192(1),c= 6.4796(6) Å, β = 108.887(2)°,V= 746.3(1) Å3,Z= 6 andDcalc= 8.32 g cm–1. The crystal structure has been solved and refined toR1= 0.016 based on 858 unique observed reflections. The strongest lines of the powder X-ray diffraction pattern [d(Å), (I), (hkl)] are: 5.43(37)($\bar{1}$11), 3.275(75)(310), 3.199(100)($\bar{1}$31), 3.061(87)(002), 2.568(62)(400), 2.545(41)(041), 3.413(34)($\bar{2}$41) and 1.697(34)(441). Zaykovite is a Se analogue of kingstonite, Rh3S4. A continuous series of solid solutions between kingstonite and zaykovite was encountered in the samples from the Kazan placer. The possible sources of this unique Rh–Se mineralisation in the South Urals could be serpentinised dunite–harzburgite or gabbro–clinopyroxenite–dunite complexes in the vicinity.
Matrix factorization for the reconstruction of cervical cancer screening histories and prediction of future screening results
Authors: Langberg Geir Severin R. E. , Stapnes Mikal , Nygård Jan F. , Nygård Mari , Grasmair Markus , Naumova Valeriya 
Published: November 2022

Abstract
Background
Mass screening programs for cervical cancer prevention in the Nordic countries have strongly reduced cancer incidence and mortality at the population level. An alternative to the current mass screening is a more personalised screening strategy adapting the recommendations to each individual. However, this necessitates reliable risk prediction models accounting for disease dynamics and individual data. Herein we propose a novel matrix factorisation framework to classify females by the time-varying risk of being diagnosed with cervical cancer. We cast the problem as a time-series prediction model where the data from females in the Norwegian screening population are represented as sparse vectors in time and then combined into a single matrix. Using novel temporal regularisation and discrepancy terms for the cervical cancer screening context, we reconstruct complete screening profiles from this scarce matrix and use these to predict the next exam results indicating the risk of cervical cancer. The algorithm is validated on both synthetic and registry screening data by measuring the probability of agreement (PoA) between Kaplan-Meier estimates.

Results
In numerical experiments on synthetic data, we demonstrate that the novel regularisation and discrepancy term can improve the data reconstruction ability as well as prediction performance over varying data scarcity. Using a hold-out set of screening data, we compare several numerical models and find that the proposed framework attains the strongest PoA. We observe strong correlations between the empirical survival curves from our method and the hold-out data, and evaluate the ability of our framework to predict the females’ next results for up to five years ahead in time using only their current screening histories as input.

Conclusions
We have proposed a matrix factorization model for predicting future screening results and evaluated its performance in a female cohort to demonstrate the potential for developing prediction models for more personalized cervical cancer screening.
Annotation of structural variants with reported allele frequencies and related metrics from multiple datasets using SVAFotate
Authors: Nicholas Thomas J. , Cormier Michael J. , Quinlan Aaron R. 
Published: November 2022

AbstractBackgroundIdentification of deleterious genetic variants using DNA sequencing data relies on increasingly detailed filtering strategies to isolate the small subset of variants that are more likely to underlie a disease phenotype. Datasets reflecting population allele frequencies of different types of variants serve as powerful filtering tools, especially in the context of rare disease analysis. While such population-scale allele frequency datasets now exist for structural variants (SVs), it remains a challenge to match SV calls between multiple datasets, thereby complicating estimates of a putative SV's population allele frequency.ResultsWe introduce SVAFotate, a software tool that enables the annotation of SVs with variant allele frequency and related information from existing SV datasets. As a result, VCF files annotated by SVAFotate offer a variety of metrics to aid in the stratification of SVs as common or rare in the broader human population.ConclusionsHere we demonstrate the use of SVAFotate in the classification of SVs with regards to their population frequency and illustrate how SVAFotate's annotations can be used to filter and prioritize SVs. Lastly, we detail how best to utilize these SV annotations in the analysis of genetic variation in studies of rare disease.
INFLECT: an R-package for cytometry cluster evaluation using marker modality
Authors: Verhoeff Jan , Abeln Sanne , Garcia-Vallejo Juan J. 
Published: November 2022

AbstractBackgroundCurrent methods of high-dimensional unsupervised clustering of mass cytometry data lack means to monitor and evaluate clustering results. Whether unsupervised clustering is correct is typically evaluated by agreement with dimensionality reduction techniques or based on benchmarking with manually classified cells. The ambiguity and lack of reproducibility of sequential gating has been replaced with ambiguity in interpretation of clustering results. On the other hand, spurious overclustering of data leads to loss of statistical power. We have developed INFLECT, an R-package designed to give insight in clustering results and provide an optimal number of clusters. In our approach, a mass cytometry dataset is overclustered intentionally to ensure the smallest phenotypically different subsets are captured using FlowSOM. A range of metacluster number endpoints are generated and evaluated using marker interquartile range and distribution unimodality checks. The fraction of marker distributions that pass these checks is taken as a measure of clustering success. The fraction of unimodal distributions within metaclusters is plotted against the number of generated metaclusters and reaches a plateau of diminishing returns. The inflection point at which this occurs gives an optimal point of capturing cellular heterogeneity versus statistical power.ResultsWe applied INFLECT to four publically available mass cytometry datasets of different size and number of markers. The unimodality score consistently reached a plateau, with an inflection point dependent on dataset size and number of dimensions. We tested both ConsenusClusterPlus metaclustering and hierarchical clustering. While hierarchical clustering is less computationally expensive and thus faster, it achieved similar results to ConsensusClusterPlus. The four datasets consisted of labeled data and we compared INFLECT metaclustering to published results. INFLECT identified a higher optimal number of metaclusters for all datasets. We illustrated the underlying heterogeneity within labels, showing that these labels encompass distinct types of cells.ConclusionINFLECT addresses a knowledge gap in high-dimensional cytometry analysis, namely assessing clustering results. This is done through monitoring marker distributions for interquartile range and unimodality across a range of metacluster numbers. The inflection point is the optimal trade-off between cellular heterogeneity and statistical power, applied in this work for FlowSOM clustering on mass cytometry datasets.
lmerSeq: an R package for analyzing transformed RNA-Seq data with linear mixed effects models
Authors: Vestal Brian E. , Wynn Elizabeth , Moore Camille M. 
Published: November 2022

AbstractBackgroundStudies that utilize RNA Sequencing (RNA-Seq) in conjunction with designs that introduce dependence between observations (e.g. longitudinal sampling) require specialized analysis tools to accommodate this additional complexity. This R package contains a set of utilities to fit linear mixed effects models to transformed RNA-Seq counts that properly account for this dependence when performing statistical analyses.ResultsIn a simulation study comparing lmerSeq and two existing methodologies that also work with transformed RNA-Seq counts, we found that lmerSeq was comprehensively better in terms of nominal error rate control and statistical power.ConclusionsExisting R packages for analyzing transformed RNA-Seq data with linear mixed models are limited in the variance structures they allow and/or the transformation methods they support. The lmerSeq package offers more flexibility in both of these areas and gave substantially better results in our simulations.
The phylogeny of Seseli (Apiaceae, Apioideae): insights from molecular and morphological data
Authors: Cai Jing , Qin Huan-Huan , Lei Jia-Qing , Liu Chang-Kun , He Xing-Jin , Zhou Song-Dong 
Published: November 2022

Abstract
Background
The genus Seseli L., which consists of 125–140 species distributed in the Old World from western Europe and northwestern Africa to China and Japan, is one of the largest and most taxonomically difficult genera of Apiaceae Lindl. Although several previous studies have been conducted on Seseli based on limited morphological characteristics and molecular fragments, a robust and comprehensive phylogeny of Seseli remains elusive. Plastomes provide abundant genetic information and have been widely used in studying plant phylogeny and evolution. Consequently, we newly generated the complete plastomes of eleven Seseli taxa. We combined plastome data and morphological characteristics to investigate the phylogeny of Seseli.

Results
In our study, we observed that the genome length, gene numbers, IR/SC borders, and repeat composition of the eleven Seseli plastomes were variable. Several appropriate mutation hotspot regions may be developed as candidate DNA barcodes for evolution, phylogeny, and species identification of Seseli. The phylogenetic results identified that Seseli was not a monophyletic group. Moreover, the eleven newly sequenced Seseli taxa did not cluster with S. tortuosum (the type species of Seseli, belonging to the tribe Selineae), where S. delavayi clustered with Eriocycla belonging to the tribe Echinophoreae and the other ten belonged to Selineae. The comparative plastome and morphological characteristics analyses confirmed the reliability of the phylogenetic analyses and implied the complex evolution of Seseli.

Conclusion
Combining molecular and morphological data is efficient and useful for studying the phylogeny of Seseli. We suggest that “a narrow sense” of Seseli will be meaningful for further study and the current taxonomic system of Seseli needs to be revised. In summary, our study can provide new insights into the phylogenetic relationships and taxonomic framework of Seseli.
Enhanced stent visualization system for percutaneous coronary intervention in patients with chronic kidney disease: effects on contrast media volume and radiation exposure
Authors: Tian Yunpeng , Zhao Xiangdong , Yang Yang , Cai Xiaoshu , Jian Lian , Guo Suzhen , Xia Dasheng , Chen Xin , Li Chao , Guo Qianyu , Chen Bingwei , Lu Chengzhi 
Published: November 2022

Abstract
Objective
We aimed to assess the impact of using enhanced stent visualization (ESV) systems on contrast media volume and radiation dose in percutaneous coronary intervention (PCI), especially for patients with chronic kidney disease (CKD).

Background
Coronary heart disease (CHD) is associated with chronic kidney disease (CKD), as they share a similar pathological pathway. In addition, the iodinated contrast media used for angiography is a risk factor for contrast-associated acute kidney injury (CA-AKI), which could aggravate the progression of CKD. We hypothesized that ESV systems have the potential to reduce the use of contrast media as well as the radiation dose; however, few studies have reported the impact on contrast media with the use of ESV systems.

Methods
We retrospectively collected 124 patients with acute coronary syndrome who underwent PCI from May 2020 to July 2021. The patients were divided into the ESV-guided group (n = 64) and angiography-guided group (n = 60). Procedural parameters, including contrast media volume, radiation exposure (in Air Kerma-AK and Dose Area Product-DAP), number of cines, cine frames, fluoroscopy and procedure time, were recorded and analysed.

Results
The groups were comparable regarding the patient characteristics. There was a significant reduction in contrast media volume (174.7 ± 29.6 ml vs.132.6 ± 22.3 ml, p = 0.0001), radiation exposure (776 (499 - 1200) mGy vs. 1065 (791 - 1603) mGy, p = 0.002 in AK; 43 (37 - 73) Gycm2 vs. 80 (64 - 133) Gycm2, p = 0.030 in DAP) and procedure time (53.06 ± 21.20 min vs. 72.00 ± 30.55 min, p = 0.01) with the use of ESV systems. Similar results were observed in the subgroup analysis for the patients with CKD.

Conclusion
This study suggested that the use of ESV is associated with reduced contrast media usage, radiation dose and procedure time during PCI. The same results were observed in a subgroup analysis in patients with CKD, and this shows that ESV-guided PCI has the potential to reduce renal impairment and mitigate the progression of CKD for those CHD patients with CKD.
The CT-based intratumoral and peritumoral machine learning radiomics analysis in predicting lymph node metastasis in rectal carcinoma
Authors: Yuan Hang , Xu Xiren , Tu Shiliang , Chen Bingchen , Wei Yuguo , Ma Yanqing 
Published: November 2022

Abstract
Background
To construct clinical and machine learning nomogram for predicting the lymph node metastasis (LNM) status of rectal carcinoma (RC) based on radiomics and clinical characteristics.

Methods
788 RC patients were enrolled from January 2015 to January 2021, including 303 RCs with LNM and 485 RCs without LNM. The radiomics features were calculated and selected with the methods of variance, correlation analysis, and gradient boosting decision tree. After feature selection, the machine learning algorithms of Bayes, k-nearest neighbor (KNN), logistic regression (LR), support vector machine (SVM), and decision tree (DT) were used to construct prediction models. The clinical characteristics combined with intratumoral and peritumoral radiomics was taken to develop a radiomics and machine learning nomogram. The relative standard deviation (RSD) was used to predict the stability of machine learning algorithms. The area under curves (AUCs) with 95% confidence interval (CI) were calculated to evaluate the predictive efficacy of all models.

Results
To intratumoral radiomics analysis, the RSD of Bayes was minimal compared with other four machine learning algorithms. The AUCs of arterial-phase based intratumoral Bayes model (0.626 and 0.627) were higher than these of unenhanced-phase and venous-phase ones in both the training and validation group.The AUCs of intratumoral and peritumoral Bayes model were 0.656 in the training group and were 0.638 in the validation group, and the relevant Bayes-score was quantified. The clinical-Bayes nomogram containing significant clinical variables of diameter, PNI, EMVI, CEA, and CA19-9, and Bayes-score was constructed. The AUC (95%CI), specificity, and sensitivity of this nomogram was 0.828 (95%CI, 0.800-0.854), 74.85%, and 77.23%.

Conclusion
Intratumoral and peritumoral radiomics can help predict the LNM status of RCs. The machine learning algorithm of Bayes in arterial-phase conducted better in consideration of terms of RSD and AUC. The clinical-Bayes nomogram achieved a better performance in predicting the LNM status of RCs.
Association of social capital with obesity among older adults in China: a cross-sectional analysis
Authors: Yang Le , Wang Hongman , Cheng Jingmin 
Published: November 2022

Abstract
Background
Under the global aging trend, health issues of the elderly have received more and more attention. Among them, older adults’ obesity is one of the common health problems of the elderly. The association between social capital and obesity in the older adults has been analysed and discussed in previous studies but remains controversial. There are few studies on the association between social capital and obesity in the older adults in China. We examined whether social capital was associated with obesity in Chinese older adults.

Methods
The data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) —wave 8 (2017–2018) was used in this study. Totally, 10,164 respondents were included in the final analysis. Generalized trust, social participation (informal social interaction and participation of organized social activities), and social support was used as measures of social capital. Obesity status was defined by body mass index (BMI). Logistic regression analyses were used to assess associations between the social capital and obesity, adjusting for confounders.

Results
We found that the older adults who did not trust people around had greater odds of being overweighted/obese compared to those who trust [Adjusted Odds Ratio (AOR) 1.155, 95% CI 1.045 to 1.265]. The older adults having formal participation (participating in organized social activities) registered considerably higher BMI (AOR 1.155, 95% CI 1.041 to 1.269). The older adults who did not trust people around them had greater odds of being overweighted/obese both in males (AOR 1.172, 95% CI 1.012–1.333) and in females (AOR 1.155, 95% CI 1.004–1.306). Males having formal social participation were more likely to be overweighted/obese (AOR 1.181, 95% CI 1.024 to 1.337), but not in females.

Conclusions
Generalized trust and formal social participation was associated with overweight/obesity among older adults in China. Targeted obesity interventions for older adults are needed by developing public health policies for social capital optimization.
Sarcopenic obesity is associated with frailty among community-dwelling older adults: findings from the WCHAT study
Authors: Yang Mei , Hu Meng , Zhang Yan , Jia Shuli , Sun Xuelian , Zhao Wanyu , Ge Meiling , Dong Birong 
Published: November 2022

Abstract
Objective
Uncertainties remain regarding the relationship between sarcopenic obesity and frailty. This study aimed to explore the association of these two common geriatric syndromes among community-dwelling older adults.

Methods
Baseline data from the West China Health and Aging Trend (WCHAT) study was used. Sarcopenia was assessed based on the criteria established by the Asian working group for sarcopenia. Body fat percentages above the 60th percentile specified by sex were classified as obesity. Sarcopenic obesity was defined as the concurrence of obesity and sarcopenia. Frailty was assessed by Fried criteria. Multinomial logistic regression was adopted to explore associations of sarcopenic obesity with frailty.

Results
Overall, 2372 older adults (mean age 67.6 ± 5.9) were involved in this study. The prevalence of frailty and sarcopenic obesity was 6.2 and 6.28%, respectively. After adjusting for covariates, sarcopenic obesity was significantly associated with prefrailty (OR = 1.74, 95% CI = 1.15–2.64, P = 0.009) and frailty (OR = 4.42, 95% CI = 2.19–8.93, P < 0.001) compared to nonsarcopenia and nonobesity.

Conclusions
Sarcopenic obesity was significantly correlated with prefrailty and frailty among older adults. Intervention for sarcopenic obesity may contribute to the prevention of incident frailty.