scholarly journals Bioinformatics Methods for Learning Radiation-Induced Lung Inflammation from Heterogeneous Retrospective and Prospective Data

2009 ◽  
Vol 2009 ◽  
pp. 1-14 ◽  
Author(s):  
Sarah J. Spencer ◽  
Damian Almiron Bonnin ◽  
Joseph O. Deasy ◽  
Jeffrey D. Bradley ◽  
Issam El Naqa
Keyword(s):  
Multiple Time ◽  
Biological Factors ◽  
Serum Samples ◽  
Prospective Data ◽  
Lung Cancer Patients ◽  
Complex Interactions ◽  
Treatment Conditions ◽  
Dose Volume ◽  
Radiation Induced ◽  
Multiple Time Points

Radiotherapy outcomes are determined by complex interactions between physical and biological factors, reflecting both treatment conditions and underlying genetics. Recent advances in radiotherapy and biotechnology provide new opportunities and challenges for predicting radiation-induced toxicities, particularly radiation pneumonitis (RP), in lung cancer patients. In this work, we utilize datamining methods based on machine learning to build a predictive model of lung injury by retrospective analysis of treatment planning archives. In addition, biomarkers for this model are extracted from a prospective clinical trial that collects blood serum samples at multiple time points. We utilize a 3-way proteomics methodology to screen for differentially expressed proteins that are related to RP. Our preliminary results demonstrate that kernel methods can capture nonlinear dose-volume interactions, but fail to address missing biological factors. Our proteomics strategy yielded promising protein candidates, but their role in RP as well as their interactions with dose-volume metrics remain to be determined.

scholarly journals Long-term Specific IgG Response to SARS-CoV-2 Nucleocapsid Protein in Recovered COVID-19 Patients

2021 ◽  
Author(s):  
Jira Chansaenroj ◽  
Ritthideach Yorsaeng ◽  
Nawarat Posuwan ◽  
Jiratchaya Puenpa ◽  
Nasamon Wanlapakorn ◽  
...  
Keyword(s):  
Symptom Onset ◽  
Multiple Time ◽  
Serum Samples ◽  
Asymptomatic Group ◽  
Seropositivity Rate ◽  
Chemiluminescent Microparticle Immunoassay ◽  
Specific Igg ◽  
Multiple Time Points ◽  
Respiratory Specimens

Abstract This study monitored the long-term immune response to severe acute respiratory syndrome coronavirus (SARS-CoV)-2 infection in patients who had recovered from coronavirus disease (COVID)-19. Anti-nucleocapsid immunoglobulin G (anti-N IgG) titer in serum samples collected at a single (N=302) or multiple time points (N=229) 3–12 months after COVID-19 symptom onset or SARS-CoV-2 detection in respiratory specimens was measured by semiquantitative chemiluminescent microparticle immunoassay. The 531 patients (966 specimens) were classified according to the presence or absence of pneumonia symptoms. Anti‑N IgG was detected in 87.5% of patients (328/375) at 3 months, 38.6% (93/241) at 6 months, 23.7% (49/207) at 9 months, and 26.6% (38/143) at 12 months. The anti-N IgG seropositivity rate was significantly lower at 6, 9, and 12 months than at 3 months (P<0.01) and was higher in the pneumonia group than in the non-pneumonia/asymptomatic group at 6 months (P<0.01), 9 months (P=0.04), and 12 months (P=0.04). The rate started to decline 6–12 months after symptom onset. Anti-N IgG sample/cutoff index was positively correlated with age (r=0.192, P<0.01) but negatively correlated with interval between symptom onset and blood sampling (r=−0.567, P<0.01). These findings can guide vaccine strategies in recovered COVID-19 patients.

scholarly journals Long-term specific IgG response to SARS-CoV-2 nucleocapsid protein in recovered COVID-19 patients

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jira Chansaenroj ◽  
Ritthideach Yorsaeng ◽  
Nawarat Posuwan ◽  
Jiratchaya Puenpa ◽  
Nasamon Wanlapakorn ◽  
...  
Keyword(s):  
Symptom Onset ◽  
Multiple Time ◽  
Serum Samples ◽  
Asymptomatic Group ◽  
Seropositivity Rate ◽  
Chemiluminescent Microparticle Immunoassay ◽  
Specific Igg ◽  
Multiple Time Points ◽  
Respiratory Specimens

AbstractThis study monitored the long-term immune response to severe acute respiratory syndrome coronavirus (SARS-CoV)-2 infection in patients who had recovered from coronavirus disease (COVID)-19. Anti-nucleocapsid immunoglobulin G (anti-N IgG) titer in serum samples collected at a single (N = 302) or multiple time points (N = 229) 3–12 months after COVID-19 symptom onset or SARS-CoV-2 detection in respiratory specimens was measured by semiquantitative chemiluminescent microparticle immunoassay. The 531 patients (966 specimens) were classified according to the presence or absence of pneumonia symptoms. Anti N IgG was detected in 87.5% of patients (328/375) at 3 months, 38.6% (93/241) at 6 months, 23.7% (49/207) at 9 months, and 26.6% (38/143) at 12 months. The anti-N IgG seropositivity rate was significantly lower at 6, 9, and 12 months than at 3 months (P < 0.01) and was higher in the pneumonia group than in the non-pneumonia/asymptomatic group at 6 months (P < 0.01), 9 months (P = 0.04), and 12 months (P = 0.04). The rate started to decline 6–12 months after symptom onset. Anti-N IgG sample/cutoff index was positively correlated with age (r = 0.192, P < 0.01) but negatively correlated with interval between symptom onset and blood sampling (r =  − 0.567, P < 0.01). These findings can guide vaccine strategies in recovered COVID-19 patients.

scholarly journals Selection-Enriched Genomic Loci (SEGL) Reveals Genetic Loci for Environmental Adaptation and Photosynthetic Productivity in Chlamydomonas reinhardtii.

2021 ◽  
Author(s):  
Ben Franklin Lucker ◽  
Nicolas Panchy ◽  
Joshua Temple ◽  
Urs Benning ◽  
Jacob Bibik ◽  
...  
Keyword(s):  
Chlamydomonas Reinhardtii ◽  
Environmental Conditions ◽  
Multiple Time ◽  
Environmental Isolates ◽  
Physiological Factors ◽  
Photosynthetic Productivity ◽  
Complex Interactions ◽  
Fluctuating Light ◽  
Improved Performance ◽  
Multiple Time Points

This work demonstrates an approach to produce and select hybrid algal strains exhibiting increased photosynthetic productivity under multiple environmental conditions. This simultaneously addresses two major impediments to improving algal bioenergy production: 1) generating new genetic variants with improved performance; and 2) disentangling complex interactions between genetic and physiological factors contributing to these improvements. We pooled progeny generated from mating two environmental isolates of the green alga Chlamydomonas reinhardtii and cultured the pools under multiple environmental conditions. Strains from the outcompeting populations showed substantial (in some cases over 3 fold) increases in productivity over the parental lines under certain environments related to biomass production, including laboratory conditions as well as hyperoxia, fluctuating light, high salinity and high temperature. The results indicate that C. reinhardtii has remarkable, untapped, directed evolution capacity that may be harnessed using breeding and competition approaches. The populations were deep sequenced at multiple time points to identify “Selection- Enriched Genomic Loci” (SEGL) that accumulated in the populations, and thus likely confer increased fitness under the respective environmental conditions. With improved resolution, SEGL mapping can identify allelic combinations used for targeted breeding approaches, generating elite algal lines with multiple desirable traits, as well as to further understand the genetic and mechanistic bases of photosynthetic productivity.

Antibodies to S-303 Treated RBC Prepared with the Original Treatment Process (OSRBC) for Pathogen Inactivation Do Not React with RBC Prepared with a Modified S-303 Treatment Process (MSRBC).

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 430-430
Author(s):  
Maureen G. Conlan ◽  
George Garratty ◽  
Grace Castro ◽  
Anna Erickson ◽  
Mary Ann Schott ◽  
...  
Keyword(s):  
Blood Donors ◽  
Treatment Process ◽  
Phase Iii ◽  
Antigenic Specificity ◽  
Multiple Time ◽  
Pathogen Inactivation ◽  
Serum Samples ◽  
Phase Iii Trials ◽  
Pre Treatment ◽  
Multiple Time Points

Abstract Background: S-303 (an acridine compound) treatment of RBCs inactivates a broad spectrum of pathogens. Two randomized, controlled Phase III trials of OSRBC to support patients (pts) undergoing cardiovascular surgery (CVS) or with hemoglobinopathies (HB) were in progress when antibodies (Ab) to OSRBC were detected. The specificity of these Ab was determined to be due to residual RBC-bound acridine. The S-303 treatment process was modified in an attempt to reduce immunoreactivity and immunogenicity. MSRBC show reduced RBC-bound S-303 and no reactivity with anti-S-303 Ab. Methods: Retrospective central laboratory testing was performed on all available trial pt serum samples (multiple time points for each pt). Crossmatch (CM) testing (PEG CM) against a minimum of 3 OSRBC units and the paired pre-treatment RBC segment was performed for each sample. CM was defined positive when reactive with any OSRBC, and consistent with anti-S-303 Ab when reactive with all OSRBC, but none of the paired pre-treatment RBC. CM-positive sera were tested for S-303 specificity with a CM inhibition assay using S-303 analogues and also tested for CM reactivity against MSRBC with a gel card CM test. All available baseline sera from trial pts, as well as plasma from 200 healthy blood donors, were also tested by gel card CM against OSRBC and MSRBC to determine prevalence of Ab reactivity to SRBC in absence of prior SRBC exposure. Results: Sera from 8 of 174 (4.6%) pts from both trials showed some CM reactivity with OSRBC. 4 were positive with all ORBC tested; and 4 were inconsistently positive, reactive with some but not all OSRBC. For the 4 pts (2.3%) with consistently positive CM, 3 had OSRBC exposure (HB trial) and 1 had only Control RBC exposure (CVS trial); 3 had positive CM with S-303 specificity. None of these 4 pt sera was CM positive with MSRBC. Only 1 of the other 4 pts with inconsistently positive CM tests had a CM test specific for SRBC (a Control CVS pt); sera from this pt were not reactive with MSRBC. 4 (1.8%) baseline sera from 220 trial pts (205 CVS and 15 HB) were CM-positive with OSRBC; only 2 (0.9%) were CM-positive with all units tested; none was positive with MSRBC. 3 of 200 (1.5%) healthy blood donor plasma were CM-positive with OSRBC; only 2 were positive with all units tested; none was positive with MSRBC. Conclusions: OSRBC were immunogenic in HB pts with prior chronic RBC exposure. Inconsistently positive CM to OSRBC without antigenic specificity for S-303 were detected with some pt sera; these results are under further investigation. Ab to OSRBC was detectable in sera of pts never exposed to S-303 treated RBC. Approximately 1% of pts and healthy blood donors had Ab that reacted with OSRBC. However, no sera with either inconsistent or confirmed CM reactivity to OSRBC were reactive with MSRBC. The MSRBC process eliminated CM reactivity to RBC treated with S-303 and offers the potential for pathogen inactivation treatment of RBC without immunologic reactivity.

scholarly journals Physical activity levels among ovarian cancer survivors: a prospective longitudinal cohort study

2021 ◽  
pp. ijgc-2020-002107
Author(s):  
Tamara Jones ◽  
Carolina Sandler ◽  
Dimitrios Vagenas ◽  
Monika Janda ◽  
Andreas Obermair ◽  
...  
Keyword(s):  
Physical Activity ◽  
Ovarian Cancer ◽  
Stage Iv ◽  
Multiple Time ◽  
Activity Levels ◽  
Prospective Longitudinal Study ◽  
Physical Activity Advice ◽  
Physical Activity Levels ◽  
Multiple Time Points ◽  
Prospective Longitudinal

ObjectivePhysical activity following cancer diagnosis is associated with improved outcomes, including potential survival benefits, yet physical activity levels among common cancer types tend to decrease following diagnosis and remain low. Physical activity levels following diagnosis of less common cancers, such as ovarian cancer, are less known. The objectives of this study were to describe physical activity levels and to explore characteristics associated with physical activity levels in women with ovarian cancer from pre-diagnosis to 2 years post-diagnosis.MethodsAs part of a prospective longitudinal study, physical activity levels of women with ovarian cancer were assessed at multiple time points between pre-diagnosis and 2 years post-diagnosis. Physical activity levels and change in physical activity were described using metabolic equivalent task hours and minutes per week, and categorically (sedentary, insufficiently, or sufficiently active). Generalized Estimating Equations were used to explore whether participant characteristics were related to physical activity levels.ResultsA total of 110 women with ovarian cancer with a median age of 62 years (range 33–88) at diagnosis were included. 53–57% of the women were sufficiently active post-diagnosis, although average physical activity levels for the cohort were below recommended levels throughout the 2-year follow-up period (120–142.5min/week). A decrease or no change in post-diagnosis physical activity was reported by 44–60% of women compared with pre-diagnosis physical activity levels. Women diagnosed with stage IV disease, those earning a lower income, those receiving chemotherapy, and those currently smoking or working were more likely to report lower physical activity levels and had increased odds of being insufficiently active or sedentary.ConclusionsInterventions providing patients with appropriate physical activity advice and support for behavior change could potentially improve physical activity levels and health outcomes.

scholarly journals The molecular make up of smoldering myeloma highlights the evolutionary pathways leading to multiple myeloma

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Eileen M. Boyle ◽  
Shayu Deshpande ◽  
Ruslana Tytarenko ◽  
Cody Ashby ◽  
Yan Wang ◽  
...  
Keyword(s):  
Tumour Suppressor Genes ◽  
Multiple Time ◽  
Clonal Structure ◽  
Time To Progression ◽  
Novel Mutations ◽  
Evolutionary Patterns ◽  
Risk Of Progression ◽  
Multiple Time Points ◽  
Smoldering Myeloma ◽  
Copy Number Changes

AbstractSmoldering myeloma (SMM) is associated with a high-risk of progression to myeloma (MM). We report the results of a study of 82 patients with both targeted sequencing that included a capture of the immunoglobulin and MYC regions. By comparing these results to newly diagnosed myeloma (MM) we show fewer NRAS and FAM46C mutations together with fewer adverse translocations, del(1p), del(14q), del(16q), and del(17p) in SMM consistent with their role as drivers of the transition to MM. KRAS mutations are associated with a shorter time to progression (HR 3.5 (1.5–8.1), p = 0.001). In an analysis of change in clonal structure over time we studied 53 samples from nine patients at multiple time points. Branching evolutionary patterns, novel mutations, biallelic hits in crucial tumour suppressor genes, and segmental copy number changes are key mechanisms underlying the transition to MM, which can precede progression and be used to guide early intervention strategies.

scholarly journals Use of TanDEM-X and SRTM-C Data for Detection of Deforestation Caused by Bark Beetle in Central European Mountains

2021 ◽  
Vol 13 (15) ◽  
pp. 3042
Author(s):  
Kateřina Gdulová ◽  
Jana Marešová ◽  
Vojtěch Barták ◽  
Marta Szostak ◽  
Jaroslav Červenka ◽  
...  
Keyword(s):  
Bark Beetle ◽  
Synergistic Effects ◽  
Canopy Height ◽  
Surface Model ◽  
Multiple Time ◽  
Central European ◽  
Time Points ◽  
Bohemian Forest ◽  
Multiple Time Points ◽  
Surrounding Areas

The availability of global digital elevation models (DEMs) from multiple time points allows their combination for analysing vegetation changes. The combination of models (e.g., SRTM and TanDEM-X) can contain errors, which can, due to their synergistic effects, yield incorrect results. We used a high-resolution LiDAR-derived digital surface model (DSM) to evaluate the accuracy of canopy height estimates of the aforementioned global DEMs. In addition, we subtracted SRTM and TanDEM-X data at 90 and 30 m resolutions, respectively, to detect deforestation caused by bark beetle disturbance and evaluated the associations of their difference with terrain characteristics. The study areas covered three Central European mountain ranges and their surrounding areas: Bohemian Forest, Erzgebirge, and Giant Mountains. We found that vertical bias of SRTM and TanDEM-X, relative to the canopy height, is similar with negative values of up to −2.5 m and LE90s below 7.8 m in non-forest areas. In forests, the vertical bias of SRTM and TanDEM-X ranged from −0.5 to 4.1 m and LE90s from 7.2 to 11.0 m, respectively. The height differences between SRTM and TanDEM-X show moderate dependence on the slope and its orientation. LE90s for TDX-SRTM differences tended to be smaller for east-facing than for west-facing slopes, and varied, with aspect, by up to 1.5 m in non-forest areas and 3 m in forests, respectively. Finally, subtracting SRTM and NASA DEMs from TanDEM-X and Copernicus DEMs, respectively, successfully identified large areas of deforestation caused by hurricane Kyril in 2007 and a subsequent bark beetle disturbance in the Bohemian Forest. However, local errors in TanDEM-X, associated mainly with forest-covered west-facing slopes, resulted in erroneous identification of deforestation. Therefore, caution is needed when combining SRTM and TanDEM-X data in multitemporal studies in a mountain environment. Still, we can conclude that SRTM and TanDEM-X data represent suitable near global sources for the identification of deforestation in the period between the time points of their acquisition.

scholarly journals Associations of Binge Drinking With Vascular Brain Injury and Atrophy in Older American Indians: The Strong Heart Study

2021 ◽  
Vol 33 (7-8_suppl) ◽  
pp. 51S-59S
Author(s):  
Jordan P. Lewis ◽  
Astrid M. Suchy-Dicey ◽  
Carolyn Noonan ◽  
Valarie Blue Bird Jernigan ◽  
Jason G. Umans ◽  
...  
Keyword(s):  
Brain Injury ◽  
Binge Drinking ◽  
American Indians ◽  
Multiple Time ◽  
Heart Study ◽  
Neurological Risk ◽  
The Us ◽  
Large Cohort Study ◽  
Magnetic Resonance Imaging Mri ◽  
Multiple Time Points

Objectives: American Indians (AIs) generally consume less alcohol than the US general population; however, the prevalence of alcohol use disorder is higher. This is the first large cohort study to examine binge drinking as a risk factor for vascular brain injury (VBI). Methods: We used linear and Poisson regression to examine the association of self-reported binge drinking with VBI, measured via magnetic resonance imaging (MRI), in 817 older AIs who participated in the Strong Heart and Cerebrovascular Disease and Its Consequences in American Indians studies. Results: Any binge drinking at multiple time-points was associated with increased sulcal (β = 0.360, 95% CI [0.079, 0.641]) and ventricle dilatation (β = 0.512, 95% CI [0.174, 0.850]) compared to no binge drinking. Discussion: These observed associations are consistent with previous findings. Identifying how binge drinking may contribute to VBI in older AIs may suggest modifiable health behaviors for neurological risk reduction and disease prevention.

scholarly journals Inferring time series chromatin states for promoter-enhancer pairs based on Hi-C data

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Henriette Miko ◽  
Yunjiang Qiu ◽  
Bjoern Gaertner ◽  
Maike Sander ◽  
Uwe Ohler
Keyword(s):  
Time Series ◽  
Histone Modifications ◽  
Gene Activation ◽  
Expectation Maximization Algorithm ◽  
Chromatin State ◽  
Open Chromatin ◽  
Multiple Time ◽  
Enhancer Activity ◽  
Chromatin States ◽  
Multiple Time Points

Abstract Background Co-localized combinations of histone modifications (“chromatin states”) have been shown to correlate with promoter and enhancer activity. Changes in chromatin states over multiple time points (“chromatin state trajectories”) have previously been analyzed at promoter and enhancers separately. With the advent of time series Hi-C data it is now possible to connect promoters and enhancers and to analyze chromatin state trajectories at promoter-enhancer pairs. Results We present TimelessFlex, a framework for investigating chromatin state trajectories at promoters and enhancers and at promoter-enhancer pairs based on Hi-C information. TimelessFlex extends our previous approach Timeless, a Bayesian network for clustering multiple histone modification data sets at promoter and enhancer feature regions. We utilize time series ATAC-seq data measuring open chromatin to define promoters and enhancer candidates. We developed an expectation-maximization algorithm to assign promoters and enhancers to each other based on Hi-C interactions and jointly cluster their feature regions into paired chromatin state trajectories. We find jointly clustered promoter-enhancer pairs showing the same activation patterns on both sides but with a stronger trend at the enhancer side. While the promoter side remains accessible across the time series, the enhancer side becomes dynamically more open towards the gene activation time point. Promoter cluster patterns show strong correlations with gene expression signals, whereas Hi-C signals get only slightly stronger towards activation. The code of the framework is available at https://github.com/henriettemiko/TimelessFlex. Conclusions TimelessFlex clusters time series histone modifications at promoter-enhancer pairs based on Hi-C and it can identify distinct chromatin states at promoter and enhancer feature regions and their changes over time.

scholarly journals Comprehensive characterization of 536 patient-derived xenograft models prioritizes candidates for targeted treatment

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Hua Sun ◽  
Song Cao ◽  
R. Jay Mashl ◽  
Chia-Kuei Mo ◽  
Simone Zaccaria ◽  
...  
Keyword(s):  
Human Tumors ◽  
Multiple Time ◽  
Cancer Treatments ◽  
Whole Genome Duplications ◽  
Patient Derived Xenograft ◽  
Genome Duplications ◽  
Genomic Characterization ◽  
Cancer Types ◽  
Multiple Time Points ◽  
Pdx Models

AbstractDevelopment of candidate cancer treatments is a resource-intensive process, with the research community continuing to investigate options beyond static genomic characterization. Toward this goal, we have established the genomic landscapes of 536 patient-derived xenograft (PDX) models across 25 cancer types, together with mutation, copy number, fusion, transcriptomic profiles, and NCI-MATCH arms. Compared with human tumors, PDXs typically have higher purity and fit to investigate dynamic driver events and molecular properties via multiple time points from same case PDXs. Here, we report on dynamic genomic landscapes and pharmacogenomic associations, including associations between activating oncogenic events and drugs, correlations between whole-genome duplications and subclone events, and the potential PDX models for NCI-MATCH trials. Lastly, we provide a web portal having comprehensive pan-cancer PDX genomic profiles and source code to facilitate identification of more druggable events and further insights into PDXs’ recapitulation of human tumors.

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