bluuebunny/crossref_metadata_2025_split huggingface dataset:
Depression Before and After a Diagnosis of Pancreatic Cancer
Authors: Seoud Talal , Syed Aslam , Carleton Neil , Rossi Caitlan , Kenner Barbara , Quershi Hassan , Anand Mary , Thakkar Payal , Thakkar Shyam 
Published: August 2020

Objectives
The aim of this study was to evaluate depression in pancreatic cancer (PC) patients before and after a cancer diagnosis using a US-based healthcare database. We also sought to study the impact of treatment of depression in PC patients on all-cause mortality.

Methods
Pancreatic cancer patients with comorbid depression in Explorys (1999–2019) were compared with controls using odds ratios with 95% confidence intervals. Rates of depression diagnosed within 6 months, 1 year, and 3 years before and after a PC diagnosis were recorded. Patients who developed depression after a PC diagnosis were further categorized into those treated for depression using mental health professionals (MHPs), pharmacologic treatment, or both (2015–2019).

Results
Of the 62,450 PC patients, 10,220 (16.4%) were diagnosed with depression before PC and 8130 (13%) were diagnosed with depression after PC. Patients diagnosed with depression after PC had a significantly higher all-cause mortality than patients with PC alone (P < 0.0001). Involvement of MHP significantly improved all-cause mortality (P = 0.0041).

Conclusions
Most post-PC depression is diagnosed in the first 6 months after a PC diagnosis. Although depression significantly increases PC mortality, integrating MHP in the care of PC patients with depression improves outcomes.
Southeast Asian Ovalocytosis and Hemoglobinopathies in Newborns: Prevalence, Molecular, and Hematologic Analyses
Authors: Yamsri Supawadee , Kawon Watcharaphong , Duereh Amara , Fucharoen Goonnapa , Fucharoen Supan 
Published: August 2020

Objectives:
Southeast Asian ovalocytosis (SAO) is an inherited red blood cell (RBC) membrane disorder, whereas hemoglobinopathies are inherited globin gene disorders. In an area where both diseases are prevalent, the interaction between them resulting in variable hematologic parameters can be encountered. However, little is known about the genetic interaction of SAO and thalassemia. We investigated the prevalence of SAO and hemoglobinopathy genotypes among newborns in southern Thailand.

Patients and Methods:
This study was carried out on 297 newborns recruited consecutively at Naradhiwas Rajanagarindra Hospital in the south of Thailand. The SAO was identified on blood smear examination and polymerase chain reaction analysis. Thalassemia genotypes were defined. Hematologic parameters and hemoglobin (Hb) profiles were recorded and analyzed.

Results:
Among 297 newborns, 15 (5.1%) carried SAO, whereas 70 (23.6%) had thalassemia with 15 different thalassemia genotypes. Abnormal Hb including Hb C, Hb Q-Thailand, and Hb D-Punjab were observed in 5 newborns. It was found in the nonthalassemic newborns that RBC count, Hb, and hematocrit of the nonthalassemic newborns with SAO were significantly lower than those without SAO. The same finding was also observed in the thalassemic newborns; RBC count, Hb, and hematocrit of the thalassemic newborns with SAO were significantly lower than those without SAO. However, the mean corpuscular volume, mean corpuscular Hb, and RBC distribution width of the SAO-newborns were significantly higher.

Conclusions:
Both SAO and hemoglobinopathy genotypes are common in southern Thailand. One should take this into consideration when evaluating neonatal anemia and other hematologic abnormalities. Identification of both genetic defects and long-term monitoring on the clinical outcome of this genetic interaction should be essential to understand the pathogenesis of these common genetic disorders in the region.
Sleep Disturbance Trajectories in Osteoarthritis
Authors: Song Jing , Lee Jungwha , Lee Yvonne C. , Chang Alison H. , Semanik Pamela A. , Chang Rowland W. , Ehrlich-Jones Linda , Dunlop Dorothy D. 
Published: August 2020

Background/Objective
Sleep disturbance is common among adults with osteoarthritis (OA), but little is known about patterns over time. In this cohort study, we identified restless sleep trajectories and associated factors in adults with or at high risk for knee OA.

Methods
Longitudinal (2004–2014) restless sleep (≥3 nights/week) annual reports over 8 years from 4359 Osteoarthritis Initiative participants were analyzed. Group-based trajectory modeling identified heterogeneous temporal patterns. Logistic regression identified baseline health and behavioral predictors of trajectory membership.

Results
Four restless sleep trajectory groups were identified: good (69.7%, persistently low restless sleep probabilities), worsening (9.1%), improving (11.7%), and poor (9.5%, persistently high). Among 2 groups initially having low restless sleep prevalence, the worsening trajectory group had an increased likelihood of baseline cardiovascular disease (odds ratio [OR], 1.53; 95% confidence interval [CI], 1.01–2.33), pulmonary disease (OR, 1.48; 95% CI, 1.07–2.05), lower physical activity (OR, 1.29; 95% CI, 1.03–1.61), knee pain (OR, 1.04; 95% CI, 1.00–1.07), depressive symptoms (OR, 1.03; 95% CI, 1.01–1.06), and a decreased likelihood of better mental health (OR, 0.97; 95% CI, 0.95–0.98) at baseline. Among 2 groups initially having high restless sleep prevalence, the poor group had an increased likelihood of baseline depressive symptoms (OR, 1.03; 95% CI, 1.00–1.05).

Conclusions
Four trajectories of restless sleep over 8 years were identified using data collected from over 4000 older adults aged 45 to 79 years with or at higher risk for knee OA. The presence of depressive symptoms, less physical activity, knee pain, poor mental health, cardiovascular disease, or pulmonary disease was each associated with unfavorable trajectories.
Stages of Lyme Arthritis
Authors: Miller John B. , Aucott John N. 
Published: August 2020

Background/Historical Perspective
Lyme arthritis was described in 1977, after an apparent outbreak of juvenile idiopathic arthritis in Lyme, Connecticut. The evolution of the disease has been meticulously described with presentation dependent on disease duration and previous therapy.

Summary Integrating Published Literature
Erythema migrans is typically the first manifestation. Untreated patients often develop early disseminated disease, characterized by migratory polyarthralgia, potentially with cardiac and/or neurologic sequelae. If untreated, most patients develop late Lyme arthritis, characterized as a monoarthritis or oligoarthritis, typically involving the knees. Serologies are strongly positive at this stage; if positive, Lyme PCR from synovial fluid confirms the diagnosis. Doxycycline is recommended for late Lyme arthritis, although amoxicillin or ceftriaxone may be considered.
Initial antibiotic therapy for late Lyme arthritis is insufficient for a subset of patients. However, serologies and synovial fluid PCR are not useful at determining whether infection persists after oral therapy. As such, ceftriaxone is recommended in patients with inadequate response to doxycycline or amoxicillin.
Approximately 10% of patients have persistent arthritis despite antimicrobial therapy, termed postinfectious Lyme arthritis, which is thought to be related to prolonged inflammation and unique microbial and host interaction. Therapy at this stage relies on immunosuppression and/or synovectomy.

Major Conclusions and Future Research
Lyme arthritis provides unique insights into the complex interplay between microbes and host immunity. The progression from localized erythema migrans to early disseminated disease and late Lyme arthritis allows insight into arthritis initiation, and the study of postinfectious Lyme arthritis allows further insight into mechanisms of arthritis persistence.
The use of a new type of heart rate-controlled training system “HeartGo ®” for patients with chronic Heart failure on the pedelec
Authors: Friedrich Erik B. , Löllgen Herbert , Röder Helmut , Baltes Wolfgang , Adam Oliver , Schlickel Martin , Hennersdorf Günter 
Published: August 2020

SummaryBackgroundThe study “HI-Herz.BIKE Saar” (August 2017 - September 2019) examined the health benefits and training effect of e-bikes (pedelecs) in patients from ambulatory heart groups with moderate chronic heart failure (CHI).Method10 subjects with NYHA stage II-III and a left ventricular ejection fraction LVEF of <=50% were selected. The presented study is explicitly marked as a pilot study.The new HeartGo® system used here for the first time allows heart rate controlled training on a special pedelec via a smartphone app. The groups were accompanied during the training rides by a doctor and a paramedic. No cardiac complications occurred. The training units were increased in duration, distance and target frequency every six months.Frequency behaviour, pedaling and motor load on the pedelec as well as climatic data such as ejection fraction, a biomarker (NT-pro BNP), risk factors, arterial blood pressure and ergometric courses were measured.ResultsThe power tolerance increased by almost 2.5 times, a discrete decrease of the resting heart rate by 3.7% was observed and pedaling power improved accordingly. In the clinical data the ergometric power increased by 44% and the LVEF improved by 29%. The NT-pro BNP value decreased by 27%. Body Mass Index BMI remained constant at 27 and cholesterol levels showed no significant changes.ConclusionsPedaling according to this pilot study with its methodological limitations of low number was safe and accompanied by significant health benefits. The subjects were enthusiastic and satisfied with this form of training. This training form can therefore be recommended to heart group participants under certain medical conditions and can be used in the training process. The results of this pilot study with its methodological weaknesses should be verified in a larger follow-up study.
Troxerutin acts on complement mediated inflammation to ameliorate arthritic symptoms in rats
Authors: Sahu Debasis , Bishwal Subasa Chandra , Malik Md. Zubbair , Sahu Sukanya , Kaushik Sandeep Rai , Sharma Shikha , Saini Ekta , Arya Rakesh , Rastogi Archana , Sharma Sandeep , Sen Shanta , Singh R. K. Brojen , Nanda Ranjan Kumar , Panda Amulya Kumar 
Published: August 2020

AbstractTroxerutin (TXR), is a phytochemical reported to possess anti-inflammatory and hepatoprotective effects. In this study, we aimed to exploit anti-arthritic properties of TXR using an adjuvant induced arthritic (AIA) rat model. AIA induced rats showed highest arthritis score at disease onset and by oral administration of TXR (50, 100, 200 mg/kg body weight), reduced to basal level in a dose dependent manner. Isobaric tag for relative and absolute quantitative (iTRAQ) proteomics tool was employed to identify deregulated joint homogenate proteins in AIA and TXR treated rats to decipher probable mechanism of the TXR action in arthritis. iTRAQ analysis identified a set of 434 joint homogenate proteins with 65 deregulated proteins (log2case/control ≥1.5) in AIA. Expressions of a set of important proteins (AAT, T-kininogen, vimentin, desmin, and nucleophosmin) that could classify AIA from healthy were validated using Western blot analysis. Western blot data corroborated proteomics findings.In silicoprotein-protein interaction study of joint homogenate proteome revealed that complement component 9, the major building blocks of the membrane attack complex (MAC) responsible for sterile inflammation, gets perturbed in AIA. Our dosimetry study suggests that a TXR dose of 200 mg/kg body weight for 15 days is sufficient to bring the arthritis score to basal levels in AIA rats. We have shown the importance of TXR as an anti-arthritis agent in AIA model and after additional investigation its arthritis ameliorating properties could be exploited for clinical usability.
Methionine stress induces a ferroptotic gene signature in methionine dependent cancer cells
Authors: Wallis Katherine , Bird Jordan T. , Gies Allen , Mackintosh Sam G. , Tackett Alan J. , Byrum Stephanie , Miousse Isabelle R. 
Published: August 2020

ABSTRACTDietary methionine restriction is associated with a reduction in tumor growth in preclinical studies and an increase in lifespan in animal models. The mechanism by which methionine restriction inhibits tumor growth while sparing normal cells is incompletely understood, except for the observation that normal cells can utilize methionine or homocysteine interchangeably (methionine independence) while most cancer cells are strictly dependent on methionine availability. Here, we compared a typical methionine dependent and a rare methionine independent melanoma cell line. We found that replacing methionine with homocysteine generally induced hypomethylation in gene promoters. We isolated nuclear proteins and submitted it for tandem mass tag (TMT) proteomics. This analysis revealed that several proteins involved in the mitochondrial integrated stress response (ISR) were upregulated in response to the replacement of methionine to homocysteine in both cell lines, but to a much greater degree in the methionine dependent cell line. Consistent with the ISR signature, a proteomic analysis of a subcellular fraction enriched for mitochondrial content revealed a strong enrichment for proteins involved in oxidative phosphorylation. Analysis of cellular bioenergetics confirmed that homocysteine induces a decrease in ATP production from oxidative phosphorylation and glycolysis, but to a similar extent in methionine dependent and methionine independent cells. The mitochondrial integrated stress response shared a signature with ferroptosis. Methionine dependent cells displayed a strong ferroptotic signature, which was decreased by half in methionine independent cells. Consistent with ferroptosis, lipid peroxidation was significantly increased in methionine independent cells grown in homocysteine, and viability could be rescued partially but significantly with the inhibitor ferrostatin. Therefore, we propose that methionine stress induces ferroptotic cell death in methionine dependent cancer cells.
nanotatoR: A tool for enhanced annotation of genomic structural variants
Authors: Bhattacharya Surajit , Barseghyan Hayk , Délot Emmanuèle C. , Vilain Eric 
Published: August 2020

AbstractWhole genome sequencing is effective at identification of small variants but, because it is based on short reads, assessment of structural variants (SVs) is limited. The advent of Optical Genome Mapping (OGM), which utilizes long fluorescently labeled DNA molecules for de novo genome assembly and SV calling, has allowed for increased sensitivity and specificity in SV detection. However, compared to small variant annotation tools, OGM-based SV annotation software has seen little development, and currently available SV annotation tools do not provide sufficient information for determination of variant pathogenicity.We developed an R-based package,nanotatoR, which provides comprehensive annotation as a tool for SV classification. nanotatoR uses both external (DGV; DECIPHER; Bionano Genomics BNDB) and internal (user-defined) databases to estimate SV frequency. Human genome reference GRCh37/38-based BED files are used to annotate SVs with overlapping, upstream, and downstream genes. Overlap percentages and distances for nearest genes are calculated and can be used for filtration. A primary gene list is extracted from public databases based on the patient’s phenotype and used to filter genes overlapping SVs, providing the analyst with an easy way to prioritize variants. If available, expression of overlapping or nearby genes of interest is extracted (e.g. from an RNA-Seq dataset, allowing the user to assess the effects of SVs on the transcriptome). Most quality-control filtration parameters are customizable by the user. The output is given in an Excel file format, subdivided into multiple sheets based on SV type and inheritance pattern (INDELs, inversions, translocations, de novo, etc.).nanotatoRpassed all quality and run time criteria of Bioconductor, where it was accepted in the April 2019 release. We evaluatednanotatoR’sannotation capabilities using publicly available reference datasets: the singleton sample NA12878, mapped with two types of enzyme labeling, and the NA24143 trio.nanotatoRwas also able to accurately filter the known pathogenic variants in a cohort of patients with Duchenne Muscular Dystrophy for which we had previously demonstrated the diagnostic ability of OGM. The extensive annotation enables users to rapidly identify potential pathogenic SVs, a critical step toward use of OGM in the clinical setting.
Identification of potential key genes for SARS-CoV-2 infected human bronchial organoids based on bioinformatics analysis
Authors: Gu Hanming , Yuan Gongsheng 
Published: August 2020

AbstractThere is an urgent need to understand the pathogenesis of the severe acute respiratory syndrome coronavirus clade 2 (SARS-CoV-2) that leads to COVID-19 and respiratory failure. Our study is to discover differentially expressed genes (DEGs) and biological signaling pathways by using a bioinformatics approach to elucidate their potential pathogenesis. The gene expression profiles of the GSE150819 datasets were originally produced using an Illumina NextSeq 500 (Homo sapiens). KEGG (Kyoto Encyclopedia of Genes and Genomes) and GO (Gene Ontology) were utilized to identify functional categories and significant pathways. KEGG and GO results suggested that the Cytokine-cytokine receptor interaction, P53 signaling pathway, and Apoptosis are the main signaling pathways in SARS-CoV-2 infected human bronchial organoids (hBOs). Furthermore, NFKBIA, C3, and CCL20 may be key genes in SARS-CoV-2 infected hBOs. Therefore, our study provides further insights into the therapy of COVID-19.
Meningococcal Deduced Vaccine Antigen Reactivity (MenDeVAR) Index: a Rapid and Accessible Tool that Exploits Genomic Data in Public Health and Clinical Microbiology Applications
Authors: Rodrigues Charlene M.C. , Jolley Keith A. , Smith Andrew , Cameron J. Claire , Feavers Ian M. , Maiden Martin C.J. 
Published: August 2020

AbstractAs microbial genomics makes increasingly important contributions to clinical and public health microbiology, the interpretation of whole genome sequence data by non-specialists becomes essential. In the absence of capsule-based vaccines, two protein-based vaccines have been used for the prevention of invasive serogroup B meningococcal disease (IMD), since their licensure in 2013/14. These vaccines have different components and different coverage of meningococcal variants. Hence, decisions regarding which vaccine to use in managing serogroup B IMD outbreaks require information about the index case isolate including: (i) the presence of particular vaccine antigen variants; (ii) the expression of vaccine antigens; and (iii) the likely susceptibility of its antigen variants to antibody-dependent bactericidal killing. To obtain this information requires a multitude of laboratory assays, impractical in real-time clinical settings, where the information is most urgently needed. To facilitate assessment for public health and clinical purposes, we synthesised genomic and experimental data from published sources to develop and implement the ‘Meningococcal Deduced Vaccine Antigen Reactivity’ (MenDeVAR) Index, which is publicly-available on PubMLST (https://pubmlst.org). Using whole genome sequences or individual gene sequences obtained from IMD isolates or clinical specimens, MenDeVAR provides rapid evidence-based information on the presence and possible immunological cross-reactivity of different meningococcal vaccine antigen variants. The MenDeVAR Index enables practitioners who are not genomics specialists to assess the likely reactivity of vaccines for individual cases, outbreak management, or the assessment of public health vaccine programmes. MenDeVAR has been developed in consultation with, but independently of, both vaccine manufacturers.
Autocorrelation-based method to identify disordered rhythm in Parkinson’s disease tasks: a novel approach applicable to multimodal devices
Authors: Sato Kenichiro , Mano Tatsuo , Iwata Atsushi , Toda Tatsushi 
Published: August 2020

AbstractObjectiveWe aim to propose a novel method of evaluating the degree of rhythmic irregularity during repetitive tasks in Parkinson’s disease (PD) by using autocorrelation to extract serial perturbation in the periodicity of body part movements as recorded by objective devices.MethodsWe used publicly distributed sequential joint movement data recorded during a leg agility task or pronation-supination task. The sequences of body part trajectory were processed to extract their short-time autocorrelation (STACF) matrices; the sequences of single task conducted by participants were then divided into two clusters according to their similarity in terms of their STACF representation. The Unified Parkinson’s Disease Rating Scale sub-score rated for each task was compared with cluster membership to obtain the area under the curve (AUC) to evaluate the discrimination performance of the clustering. We compared the AUC with those obtained from the clustering of the raw sequence or short-time Fourier transform (STFT).ResultsIn classifying the pose estimator-based trajectory data of the knee during the leg agility task, the AUC was the highest when the STACF sequence was used for clustering instead of other types of sequences with up to 0.815, being comparable to the results reported in the original analysis of the data using an approach different from ours. In addition, in classifying another dataset of accelerometer-based trajectory data of the wrist during a pronation-supination task, the AUC was again highest up to 0.785 when clustering was performed using the STACF rather than other types of sequence.ConclusionOur autocorrelation-based method achieved a fair performance in detecting sequences with irregular rhythm, suggesting that it might be used as another evaluation strategy that is potentially widely applicable to qualify the disordered rhythm of PD regardless of the kinds of task or the modality of devices, although further refinement is needed.
Nested versus independent sampling: Solving the mystery of contradictory species-area relationships
Authors: Reinhard Johannes , Drossel Barbara 
Published: August 2020

AbstractSpecies-area relationships (SARs) describe how the number of species increases with the size of the area surveyed, and they usually take the shape of a power law on regional spatial scales. A meta-review of empirical data has shown that the exponent of the power law is on average larger when the areas are sampled in a nested manner, compared to sampling of independent areas such as islands of different sizes. As this is in contrast to ecological reasoning, we performed computer simulations of three qualitatively different models that generate species distributions in space and time by the mechanisms of speciation, dispersal, and extinction. We find that in all cases and over a wide parameter range the SARs obtained by nested sampling have a smaller slope in the regional scale than those obtained by independent sampling. We explain the discrepancy to the empirical data by the different spatial scales on which the two types of empirical investigations were performed.