bluuebunny/crossref_metadata_2025_split huggingface dataset:
Caring for the informal cancer caregiver
Authors: Sun Virginia , Raz Dan J. , Kim Jae Y. 
Published: June 2019

Purpose of review
Informal cancer caregivers play a vital role in the physical, functional, and emotional well being of cancer patients. However, the majority of informal caregivers are not prepared for their caregiving role. We reviewed and synthesized the recent literature (last 18 months) and focused on research in the following understudied areas: technology-driven interventions for informal caregivers; informal caregivers of older adults with cancer; interrelationship between informal caregiver and dyadic outcomes; and research priorities and guidelines to improve informal caregiver support.

Recent findings
Studies focused on technology-driven informal caregiver interventions, with evidence of good feasibility and acceptability with benefits for burden and quality of life (QOL). Studies also focused on QOL for caregivers of older adults with cancer. Finally, research priorities and clinical guidelines were established through Delphi survey studies.

Summary
Despite the substantial evidence on informal cancer caregiving, more research is needed to further characterize caregivers at high risk for burden, explicate interrelationships between caregiver/patient outcomes, and test innovative and scalable interventions. Studies are also needed to understand the specific needs of informal caregivers in cancer surgery, an understudied treatment population.
Genetic correlates of evolutionary adaptations in cognitive functional brain networks and their relationship to human cognitive functioning and disease
Authors: Wei Yongbin , de Lange Siemon C. , Scholtens Lianne H. , Watanabe Kyoko , Ardesch Dirk Jan , Jansen Philip R. , Savage Jeanne E. , Li Longchuan , Preuss Todd M. , Rilling James K. , Posthuma Danielle , van den Heuvel Martijn P. 
Published: June 2019

AbstractCognitive functional networks such as the default-mode network (DMN), frontal-parietal network (FPN), and salience network (SN), are key networks of the human brain. Here, we show that the distinct rapid evolutionary cortical expansion of cognitive networks in the human brain, and most pronounced the DMN, runs parallel with high expression of genes important for human evolution (so-called HAR genes). Comparative gene expression examination then shows that HAR genes are more differentially expressed in cognitive networks in humans compared to the chimpanzee and macaque. Genes with distinct high expression in the DMN display broad involvement in the formation of synapses and dendrites. Next, we performed a genome-wide association analysis on functional MRI data, and show that HAR genes are associated with individual variations in DMN functional connectivity in today’s human population. Finally, gene-set analysis suggests associations of HAR genes with intelligence, social cognition, and mental conditions such as schizophrenia and autism. Taken together, our results indicate that the expansion of higher-order functional networks and their cognitive properties have been an important locus of change in recent human brain evolution.
Unexpectedly High Subclonal Mutational Diversity in Human Colorectal Cancer and Its Significance
Authors: Loeb Lawrence A. , Kohrn Brendan F. , Loubet-Senear Kaitlyn J. , Dunn Yasmin J. , Ahn Eun Hyun , O’Sullivan Jacintha N. , Salk Jesse J. , Bronner Mary P. , Beckman Robert A. 
Published: June 2019

AbstractHuman colorectal cancers (CRC) contain both clonal and subclonal mutations. Clonal mutations are positively selected, present in most cells and drive malignant progression. Subclonal mutations are randomly dispersed throughout the genome; they provide a vast reservoir of mutant cells that can expand, repopulate the tumor and result in the rapid emergence of resistance, as well as being a major contributor to tumor heterogeneity. Here, we apply Duplex Sequencing (DS) methodology to quantify subclonal mutations in CRC tumor with unprecedented depth (104) and accuracy (<10−7). We measured mutation frequencies in genes encoding replicative DNA polymerases and in genes frequently mutated in CRC, and found an unexpectedly high effective mutation rate, 7.1 × 10−7. The curve of subclonal mutation accumulation as a function of sequencing depth, using DNA obtained from five different tumors, is in accord with a neutral model of tumor evolution. We present a new theoretical approach to model neutral evolution independent of the infinite sites assumption (which states that a particular mutation arises only in one tumor cell at any given time). Our analysis indicates that the infinite sites assumption is not applicable once the number of tumor cells exceeds the reciprocal of the mutation rate, a circumstance relevant to even the smallest clinically diagnosable tumor. Our methods allow accurate estimation of the total mutation burden in clinical cancers. Our results indicate that no DNA locus is wild type in every malignant cell within a tumor at the time of diagnosis (probability of all cells wild type = 10−308).Significance StatementCancers evolve many mutations. Clonal mutations are selected early. Subsequent evolution occurs in a branching fashion, possibly without selection (“neutral evolution”). Rarer mutations occur later on smaller branches of the evolutionary tree. Using a DNA sequencing method, duplex sequencing, with unprecedented accuracy and sensitivity, we quantified very rare unique subclonal mutations in diagnostic specimens from five human colorectal cancers. Rarer subclones probe later evolutionary timepoints than previously possible. We confirm neutral evolution at later times and find many more subclonal mutations than expected. A novel theoretical method allowed us to extrapolate further forward in time to diagnosis. At diagnosis, every base in DNA is mutated in at least one cancer cell. In particular any therapy resistance mutation would be present.
High-density lipoprotein characteristics and coronary heart disease: a Mendelian randomization study
Authors: Prats-Uribe Albert , Sayols-Baixeras Sergi , Fernández-Sanlés Alba , Subirana Isaac , Carreras-Torres Robert , Vilahur Gemma , Civeira Fernando , Marrugat Jaume , Fitó Montserrat , Hernáez Álvaro , Elosua Roberto 
Published: June 2019

ABSTRACTBackgroundThe causal role of high-density lipoproteins (HDL) in coronary artery disease (CAD) has been questioned. Our aim was to analyze whether genetically determined quantitative and qualitative HDL characteristics were independently associated with CAD.MethodsWe designed a two-sample multivariate Mendelian randomization study with available genome-wide association summary data. We identified genetic variants associated with HDL cholesterol and apolipoprotein A-I quantity, HDL size, particle levels, and lipid content to define our genetic instrumental variables in one sample (Kettunen et al study,N=24,925) and analyzed their association with CAD risk in a different study (CARDIoGRAMplusC4D,N=184,305). We validated these results by defining our genetic variables in another database (METSIM,N=8,372) and studied their relationship with CAD in the CARDIoGRAMplusC4D dataset. To estimate the effect size of the associations of interest adjusted for other lipoprotein traits (potential pleiotropy) we used the Multi-trait-based Conditional & Joint analysis.ResultsGenetically determined HDL cholesterol and apolipoprotein A-I levels were not associated with CAD. HDL mean diameter (β=0.27 [95%CI=0.19; 0.35]), cholesterol levels in very large HDLs (β=0.29 [95%CI=0.17; 0.40]), and triglyceride content in very large HDLs (β=0.14 [95%CI=0.040; 0.25]) were directly associated with CAD risk, whereas the cholesterol content in medium-sized HDLs (β=-0.076 [95%CI=-0.10; −0.052]) was inversely related to this risk. These results were validated in the METSIM-CARDIoGRAMplusC4D data. Genetic variants linked to both HDL qualitative traits and CAD risk were located withinLIPC, theAPOE/C1/C4/C2cluster,APOB, PCIF1-PLTP, andTTC39B.ConclusionsSome HDL characteristics related to size, particle distribution, and triglyceride content are related to CAD risk whilst HDL cholesterol levels are not. This relationship could be mediated by the hepatic lipase; the apolipoproteins E, C-I, and B; the phospholipid transfer protein; and the tetratricopeptide repeat domain protein 39B, which arise as potential therapeutic targets in cardiovascular disease.
A DNA Methylation Fingerprint of Cellular Senescence
Authors: Levine Morgan E. , Leung Diana , Minteer Christopher , Gonzalez John 
Published: June 2019

ABSTRACTRecent years have witnessed an influx of therapies aimed at targeting the biological aging process. While many hold promise for potentially delaying the simultaneous onset of multiple chronic conditions, a major hurdle in developing interventions to slow human aging is the lack of reliable and valid endpoints from which to evaluate potential candidates. The aim of this study was to develop a biomarker that could serve as a potential endophenotype in evaluation of one of the most promising and exciting aging therapeutics being developed—senolytics. Senolytics are compounds which selectively clear senescent cells by targeting anti-apoptotic pathways. Using DNAm data from fibroblasts and mesenchymal stromal cells (MSC) in culture, we developed a predictor of cellular senescence that related to three distinct senescence inducers (replicative, oncogene induced (OIS), and ionizing radiation (IR)). Our measure, termed DNAmSen, showed expected classification of validation data from embryonic stem cells (ESC), induced pluripotent stem cells (iPSC), and near senescent cells in culture. Further, using bulk data from whole blood, peripheral tissue samples, and postmortem tissue, we observed robust correlations between age and DNAmSen. We also observed age adjusted associations between DNAmSen and idiopathic pulmonary fibrosis (IPS), COPD, lung cancer, and Werner syndrome compared to controls. When characterizing the 88 CpGs in the DNAmSen measure, we observed a enrichment for those located in enhancer regions and regulatory regions marked by DNase I hypersensitive sites (DHSs). Interestingly most of the CpGs were observed to be moderately hypomethyled in early passage cells, yet exhibited further hypomethylation upon induction of cellular senescence, suggesting senescence is accompanied by programmatic alterations to the epigenome, rather than entropic drift.
Does Sex Modify an Association of Electrophysiological Substrate with Sudden Cardiac Death? The Atherosclerosis Risk in Communities (ARIC) Study
Authors: Howell Stacey J. , German David , Bender Aron , Phan Francis , Mukundan Srini V. , Perez-Alday Erick A. , Rogovoy Nichole M. , Haq Kazi , Yang Katherine , Wirth Ashley , Jensen Kelly , Tereshchenko Larisa G. 
Published: June 2019

AbstractBackgroundSex is a well-recognized risk factor for sudden cardiac death (SCD). Sex differences in electrophysiological (EP) substrate of SCD are known. However, it remains unknown whether sex can modify an association of EP substrate with SCD.MethodsParticipants from the Atherosclerosis Risk in Communities study with analyzable ECGs (n=14,725; age, 54.2±5.8 yrs; 55% female, 74% white) were included. EP substrate was characterized by traditional 12-lead ECG (heart rate, QRS, QTc, Cornell voltage), spatial ventricular gradient (SVG) and sum absolute QRST integral (SAI QRST) metrics. Two competing outcomes were adjudicated SCD and nonSCD. Interaction of ECG metrics with sex was studied in Cox proportional hazards and Fine-Gray competing risk models. Relative hazard ratio (RHR) and relative sub-hazard ratio (RSHR) with a 95% confidence interval for SCD and nonSCD risk for women relative to men were calculated. Model 1 was adjusted for prevalent cardiovascular disease (CVD) and risk factors. Time-updated model 2 was additionally adjusted for incident non-fatal CVD.ResultsOver a median follow-up of 24.4 years, there were 530 SCDs (incidence 1.72 (1.58-1.88)/1000 person-years) and 2,178 nonSCDs (incidence 7.09; (6.80-7.39)/ 1000 person-years). Women experienced a greater than men risk of SCD associated with Cornell voltage (RHR 1.18(1.06-1.32); P=0.003), SAI QRST (RHR 1.16(1.04-1.30); P=0.007), area SVG magnitude (RHR 1.24(1.05-1.45); P=0.009), and peak SVG magnitude (RHR 1.22(1.04-1.44); P=0.018), independently from incident CVD. Greater risk of SCD for women than men associated with QRS duration (RHR 1.24(1.07-1.44); P=0.004) and QTc (RSHR 1.15(1.02-1.30); P=0.025) was explained by incident CVD. Furthermore, women had greater odds of SCD associated with heart rate (RSHR 1.19(1.01-1.40); P=0.036), independently of incident CVD.ConclusionsSex modifies an association of EP substrate with SCD. In women, global EP substrate is associated with up to 27% greater risk of SCD than in men. Development of sex-specific risk scores of SCD is necessary. Further studies of mechanisms behind sex differences in EP substrate of SCD are warranted.
Efficacy and safety of a novel vaginal medical device in recurrent bacterial vaginosis: an international multicentre clinical trial
Authors: Murina Filippo , Crişan Ciprian , Biriş Marius , Sîrbu Daniela , Barattini Dionisio Franco , Ardolino Luca Ivan , Casolati Elena 
Published: June 2019

ABSTRACTSeveral risk factors have been identified but the etiology and pathogenesis of Bacterial vaginosis (BV) are still not completely understood, and the recurrence rate of BV remains high despite adequate chemotherapy treatment.The primary objective of the study was to assess the effectiveness of a new vaginal medical device, which contains polycarbophil, 0.04 % lauryl glucoside, and glycerides (Polybactum®– Effik Italia), in reducing BV recurrence rate.This was a multicenter, open label, not comparative study performed in Italy and Romania. Female subjects over 18-years-old affected by recurrent BV were included. The latest episode was diagnosed by Amsel criteria 6-9 days before the start of the study and treated with vaginal metronidazole (gel 0.75% mg for 5 days or ovules 500 mg for 7 days). The recurrence was defined by at least 2 episodes in the previous 12 months. Polybactum®vaginal ovules, day 1-4-7, were started within the 12th and the 24th hr after the end of metronidazole therapy and repeated monthly for 3 cycles.The first 41 patients enrolled were evaluated for an interim analysis 6 months after the study started; 2 patients interrupted the trial, leaving 39 evaluable subjects. The recurrence rate was significantly reduced compared to previous published data (10.26% vs 40% p<0.001). In 35 patients without recurrence, the assessment of Lactobacillus vaginal flora performed by phase contrast microscopy evidenced a significant improvement form baseline (p=0.022) The Investigator global assessment of tolerability was excellent in 38 out of 39 cases.IMPORTANCEBacterial vaginosis (BV) is the most common vaginal disorder in women of childbearing age. In BV, Lactobacillus species, which are predominant in a healthy vaginal flora, are replaced by anaerobes, mainly Gardnerella vaginalis. BV is responsible for more than 60% of vulvovaginal infections and has been linked to serious, potentially life-threatening conditions, including: pelvic inflammatory disease, postoperative infections, acquisition and transmission of the human immunodeficiency virus, preterm birth, and several adverse pregnancy outcomes. Our research showed that 3 monthly cycles of Polybactum®ovules administered after one course of metronidazole vaginal therapy can reduce the rate of Bacterial vaginosis recurrence and improve the vaginal milieu, favouring the growth of vaginal lactobacillus species. Taken together our results confirm that Polibactum®is a safe and effective treatment to reduce BV recurrence rate after a first line therapy with metronidazole.
Serum level of High-density lipoprotein particles are independently associated with long-term prognosis in patients with coronary artery disease: The GENES study
Authors: Duparc Thibaut , Ruidavets Jean-Bernard , Genoux Annelise , Ingueneau Cécile , Najib Souad , Ferrieres Jean , Perret Bertrand , Martinez Laurent O. 
Published: June 2019

AbstractBACKGROUNDHDL-Cholesterol (HDL-C) is not an accurate surrogate marker to measure the cardioprotective functions of HDL in coronary artery diseases (CAD) patients. Hence, measurement of other HDL-related parameters may have prognostic superiority over HDL-C.OBJECTIVEThis work aimed to examine the predictive value of HDL particles profile for long-term mortality in CAD patients. Its informative value was compared to that of HDL-C and apoA-I.METHODSHDL particles profile were measured by nuclear magnetic resonance (NMR) spectroscopy in 214 male participants with stable CAD (45-74 years). Median follow up was 12.5 years with a 36.4% mortality rate. Cardiovascular mortality accounted for 64.5 %.RESULTSMean concentrations of total HDL particles (HDL-P), small-sized HDL (SHDL-P) and apoA-I were lower in deceased than in surviving patients whereas no difference was observed according to HDL-C and large HDL particles. All NMR-HDL measures were correlated between themselves and with other HDL markers (HDL-C, apoA-I and LpA-I). In a multivariate model adjusted for 14 cardiovascular risk factors and bioclinical variables, HDL-P and SHDL-P displayed the strongest inverse association with all-cause and cardiovascular mortality. Weaker associations were recorded for apoA-I.CONCLUSIONHDL particle profile measured by NMR spectroscopy should be considered to better stratify risk in population at high risk or in the setting of pharmacotherapy.
Using machine learning to predict quantitative phenotypes from protein and nucleic acid sequences
Authors: Sauer David B. , Wang Da-Neng 
Published: June 2019

ABSTRACTBackgroundThe link between protein or nucleic acid sequence and biochemical or organismal phenotype is essential for understanding the molecular mechanisms of evolution, reverse ecology, and designing proteins and genes with specific properties. However, it is difficult to practically make use of the relationship between sequence and phenotype due to the complex relationship between sequence and folding or activity.ResultsHere, we predict the originating species’ optimal growth temperatures of individual protein sequences using trained machine learning models. Both multilayer perceptron and k Nearest Neighbor regression outperformed linear regression could predict the originating species’ optimal growth temperature from protein sequences, achieving a root mean squared error of 3.6 °C. Similar machine learning models could predict organismal optimal growth pH and oxygen tolerance, and the quantitative properties of individual proteins or nucleic acids.ConclusionsUsing multilayer perceptron and k Nearest Neighbor regressions, we were able to build models specific to individual protein or nucleic acid families that can predict a variety of quantitative phenotypes. This methodology will be useful thein silicoscreening of individual mutations for particular properties, and also effective in the predicting the phenotypes of uncharacterized biological sequences and organisms.
Regulation of community functional composition across taxonomic variation by resource-consumer dynamics
Authors: Worden Lee 
Published: June 2019

AbstractHigh-throughput sequencing techniques such as metagenomic and metatranscriptomic technologies allow cataloging of functional characteristics of microbial community members as well as their taxonomic identity. Such studies have found that a community’s composition in terms of ecologically relevant functional traits or guilds can be conserved more strictly across varying settings than taxonomic composition is. I use a standard ecological resource-consumer model to examine the dynamics of traits relevant to resource consumption, and analyze determinants of functional composition. This model demonstrates that interaction with essential resources can regulate the community-wide abundance of ecologically relevant traits, keeping them at consistent levels despite large changes in the abundances of the species housing those traits in response to changes in the environment, and across variation between communities in species composition. Functional composition is shown to be able to track differences in environmental conditions faithfully across differences in community composition. Mathematical conditions on consumers’ vital rates and functional responses sufficient to produce conservation of functional community structure across taxonomic differences are presented.
Studies on Biochemical Changes and Prolactin Level Evaluation in Patients with Chronic Kidney Disease
Authors: Rahman Foyzur , Kabir Faisal , Rezwan Sawgat 
Published: June 2019

AbstractBackgroundChronic kidney disease (CKD) is progressive loss in kidney function over a period of months or years. CKD is an internationally recognized public health problem affecting 5–10% of the world population and day-by-day the number of cases are increasing at an alarming rate. In CKD, raised levels of prolactin in blood may cause vascular derangements which might lead to worse cardiovascular consequences in CKD patients.ObjectivesTo assess serum creatinine, hemoglobin (Hb), urea, red blood cell (RBC), protein creatinine ratio (PCR) and prolactin in CKD patients.Material and MethodsThis study included 110 patients, 61 were males and 49 were females and their age range 1 to more than 60 years. The control group also consisted of same number of participants as the patients; who were free from signs and symptoms of kidney disease and prolactin hormone disorders.ResultsThe study shows that all the biochemical parameters in CKD patients were found to be significantly high compared with control group (P<0.001). Serum prolactin concentrations in CKD patients were also increased significantly compared with control group (P≤ 0.05). It was found that level of prolactin hormone secretion was higher in male CKD patients than male control.ConclusionAlthough males are more prone to chronic kidney disease, but the percentage of females is not negligible. All the biochemical parameters and prolactin level changed significantly in the CKD patients. It is interesting that in case of CKD, male’s prolactin secretion becomes higher.
SPsimSeq: semi-parametric simulation of bulk and single cell RNA sequencing data
Authors: Assefa Alemu Takele , Vandesompele Jo , Thas Olivier 
Published: June 2019

SummarySPsimSeq is a semi-parametric simulation method for bulk and single cell RNA sequencing data. It simulates data from a good estimate of the actual distribution of a given real RNA-seq dataset. In contrast to existing approaches that assume a particular data distribution, our method constructs an empirical distribution of gene expression data from a given source RNA-seq experiment to faithfully capture the data characteristics of real data. Importantly, our method can be used to simulate a wide range of scenarios, such as single or multiple biological groups, systematic variations (e.g. confounding batch effects), and different sample sizes. It can also be used to simulate different gene expression units resulting from different library preparation protocols, such as read counts or UMI counts.Availability and implementationThe R package and associated documentation is available from https://github.com/CenterForStatistics-UGent/SPsimSeq.Supplementary informationSupplementary data are available at bioRχiv online.