bluuebunny/crossref_metadata_2025_split huggingface dataset:
Importance of Normalization of CA19-9 Levels Following Neoadjuvant Therapy in Patients With Localized Pancreatic Cancer
Authors: Tsai Susan , George Ben , Wittmann David , Ritch Paul S. , Krepline Ashley N. , Aldakkak Mohammed , Barnes Chad A. , Christians Kathleen K. , Dua Kulwinder , Griffin Michael , Hagen Catherine , Hall William A. , Erickson Beth A. , Evans Douglas B. 
Published: October 2018

Objective:
Carbohydrate antigen 19-9 (CA19-9) is a prognostic marker for patients with pancreatic cancer (PC), but its value as a treatment biomarker is unclear.

Summary Background Data:
Although CA19-9 is an established prognostic marker for patients with PC, it is unclear how CA19-9 monitoring should be used to guide multimodality treatment and what level of change in CA19-9 constitutes a meaningful treatment response.

Methods:
CA19-9 measurements at diagnosis (pretx), after completion of all planned neoadjuvant therapy (preop), and after surgery (postop) were analyzed in patients with localized PC who had an elevated CA19-9 (≥35 U/dL) at diagnosis. Patients were classified by: 1) quartiles of pretx CA19-9 (Q1-4); 2) proportional changes in CA19-9 (ΔCA19-9) after the completion of neoadjuvant therapy; 3) normalization (CA19-9 <35 U/dL) of preop CA19-9; and 4) normalization of postop CA19-9.

Results:
Among 131 patients, the median overall survival (OS) was 30 months; 68 months for the 33 patients in Q1 of pretx CA19-9 (<80 U/dL) compared with 25 months for the 98 patients in Q2-4 (P = 0.03). For the 98 patients in Q2-4, preop CA19-9 declined (from pretx) in 86 (88%), but there was no association between the magnitude of ΔCA19-9 and OS (P = 0.77). Median OS of the 98 patients who did (n = 29) or did not (n = 69) normalize their preop CA19-9 were 46 and 23 months, respectively (P = 0.02). Of the 69 patients with an elevated preop CA19-9, 32 (46%) normalized their postop CA19-9. Failure to normalize preop or postop CA19-9 was associated with a 2.77-fold and 4.03-fold increased risk of death, respectively (P < 0.003) as compared with patients with normal preop CA19-9.

Conclusions:
Following neoadjuvant therapy, normalization of CA19-9, rather than the magnitude of change, is the strongest prognostic marker for long-term survival.
Risk factors for avoidable transfer to a pediatric trauma center among patients 2 years and older
Authors: Snyder Christopher W. , Kauffman Jeremy D. , Pracht Etienne E. , Danielson Paul D. , Ciesla David J. , Chandler Nicole M. 
Published: October 2018

BACKGROUND
Effective and sustainable pediatric trauma care requires systems of regionalization and interfacility transfer. Avoidable transfer, also known as secondary overtriage, occurs when a patient is transferred to a regional trauma center after initial evaluation at another facility that is capable of providing definitive care. The purpose of this study was to identify risk factors for avoidable transfer among pediatric trauma patients in southwest Florida.

METHODS
All pediatric trauma patients 2 years and older transferred from outlying hospitals to the emergency department of a single state-designated pediatric trauma center between 2009 and 2017 were obtained from the institutional registry. Transfers were classified as avoidable if the patient suffered only minor injuries (International Classification of Diseases—9th Rev. Injury Severity Score > 0.9), did not require invasive procedures or intensive care unit monitoring, and was discharged within 48 hours. Demographics and injury characteristics were compared for avoidable and nonavoidable transfers. Logistic regression was used to estimate the independent effects of age, sex, insurance type, mechanism of injury, diagnosis, within region versus out-of-region residence, suspected nonaccidental trauma, and abnormal Glasgow Coma Scale score on the risk of avoidable transfer.

RESULTS
A total of 3,876 transfer patients met inclusion criteria, of whom 1,628 (42%) were classified as avoidable. Among avoidable transfers, 29% had minor head injuries (isolated skull fractures, concussions, and mild traumatic brain injury not otherwise specified), and 58% received neurosurgery consultation. On multivariable analysis, the strongest risk factors for avoidable transfer were diagnoses of isolated skull fracture or concussion. Suspected nonaccidental trauma was predictive of nonavoidable transfer.

CONCLUSION
Among injured children 2 years and older, those with minor head injuries were at greatest risk for avoidable transfer. Many were transferred because of a perceived need for evaluation by a pediatric neurosurgeon. Future projects seeking to reduce avoidable transfers should focus on children with isolated skull fractures and concussions, in whom there is no suspicion of nonaccidental trauma.

LEVEL OF EVIDENCE
Therapeutic/care management, level IV.
A simple microbiome in the European common cuttlefish, Sepia officinalis
Authors: Lutz Holly L. , Ramírez-Puebla S. Tabita , Abbo Lisa , Durand Amber , Schlundt Cathleen , Gottel Neil , Sjaarda Alexandra K. , Hanlon Roger T. , Gilbert Jack A. , Mark Welch Jessica L. 
Published: October 2018

ABSTRACTThe European common cuttlefish, Sepia officinalis, is used extensively in biological and biomedical research yet its microbiome remains poorly characterized. We analyzed the microbiota of the digestive tract, gills, and skin in mariculture-raised S. officinalis using a combination of 16S rRNA amplicon sequencing, qPCR and fluorescence spectral imaging. Sequencing revealed a highly simplified microbiota consisting largely of two single bacterial amplicon sequence variants (ASVs) of Vibrionaceae and Piscirickettsiaceae. The esophagus was dominated by a single ASV of the genus Vibrio. Imaging revealed bacteria in the family Vibrionaceae distributed in a discrete layer that lines the esophagus. This Vibrio was also the primary ASV found in the microbiota of the stomach, cecum, and intestine, but occurred at lower abundance as determined by qPCR and was found only scattered in the lumen rather than in a discrete layer via imaging analysis. Treatment of animals with the commonly-used antibiotic enrofloxacin led to a nearly 80% reduction of the dominant Vibrio ASV in the esophagus but did not significantly alter the relative abundance of bacteria overall between treated versus control animals. Data from the gills was dominated by a single ASV in the family Piscirickettsiaceae, which imaging visualized as small clusters of cells. We conclude that bacteria belonging to the Gammaproteobacteria are the major symbionts of the cuttlefish Sepia officinalis cultured from eggs in captivity, and that the esophagus and gills are major colonization sites.IMPORTANCEMicrobes can play critical roles in the physiology of their animal hosts, as evidenced in cephalopods by the role of Vibrio (Aliivibrio) fischeri in the light organ of the bobtail squid and the role of Alpha- and Gammaproteobacteria in the reproductive system and egg defense in a variety of cephalopods. We sampled the cuttlefish microbiome throughout the digestive tract, gills, and skin and found dense colonization of an unexpected site, the esophagus, by a microbe of the genus Vibrio, as well as colonization of gills by Piscirickettsiaceae. This finding expands the range of organisms and body sites known to be associated with Vibrio and is of potential significance for understanding host-symbiont associations as well as for understanding and maintaining the health of cephalopods in mariculture.
The key parameters that govern translation efficiency
Authors: Erdmann-Pham Dan D. , Dao Duc Khanh , Song Yun S. 
Published: October 2018

AbstractTranslation of mRNA into protein is a fundamental yet complex biological process with multiple factors that can potentially affect its efficiency. In particular, different genes can have quite different initiation rates, while site-specific elongation rates can vary substantially along a given transcript. Here, we analyze a stochastic model of translation dynamics to identify the key parameters that govern the overall rate of protein synthesis and the efficiency of ribosome usage. The mathematical model we study is an interacting particle system that generalizes the Totally Asymmetric Simple Exclusion Process (TASEP), where particles correspond to ribosomes. While the TASEP and its variants have been studied for the past several decades through simulations and mean field approximations, a general analytic solution has remained challenging to obtain. By analyzing the so-called hydrodynamic limit, we here obtain exact closed-form expressions for stationary currents and particle densities that agree well with Monte Carlo simulations. In addition, we provide a complete characterization of phase transitions in the system. Surprisingly, phase boundaries depend on only four parameters: the particle size, and the first, last and minimum particle jump rates. Relating these theoretical results to translation, we formulate four design principles that detail how to tune these parameters to optimize translation efficiency in terms of protein production rate and resource usage. We then analyze ribosome profiling data of S. cerevisiae and demonstrate that its translation system is generally efficient, consistent with the design principles we found. We discuss implications of our findings on evolutionary constraints and codon usage bias.
Dynamic load balancing enables large-scale flux variability analysis
Authors: Guebila Marouen Ben 
Published: October 2018

AbstractGenome-scale metabolic models (GSMMs) of living organisms are used in a wide variety of applications pertaining to health and bioengineering. They are formulated as linear programs (LP) that are often under-determined. Flux Variability Analysis (FVA) characterizes the alternate optimal solution (AOS) space enabling thereby the assessment of the robustness of the solution. fastFVA (FFVA), the C implementation of MATLAB FVA, allowed to gain substantial speed up, although, the parallelism was managed through MATLAB. Here veryfastFVA (VFFVA) is presented, which is a pure C implementation of FVA, that relies on lower level management of parallelism through a hybrid MPI/OpenMP. The flexibility of VFFVA allowed to gain a threefold speedup factor and to decrease memory usage 14 fold in comparison to FFVA. Finally, VFFVA allows processing a higher number of GSMMs in faster times accelerating thereby biomedical modeling and simulation. VFFVA is available online athttps://github.com/marouenbg/VFFVA.
Assessing reliability of intra-tumor heterogeneity estimates from single sample whole exome sequencing data
Authors: Abécassis Judith , Hamy Anne-Sophie , Laurent Cécile , Sadacca Benjamin , Bonsang-Kitzis Hélène , Reyal Fabien , Vert Jean-Philippe 
Published: October 2018

AbstractTumors are made of evolving and heterogeneous populations of cells which arise from successive appearance and expansion of subclonal populations, following acquisition of mutations conferring them a selective advantage. Those subclonal populations can be sensitive or resistant to different treatments, and provide information about tumor aetiology and future evolution. Hence, it is important to be able to assess the level of heterogeneity of tumors with high reliability for clinical applications.In the past few years, a large number of methods have been proposed to estimate intra-tumor heterogeneity from whole exome sequencing (WES) data, but the accuracy and robustness of these methods on real data remains elusive. Here we systematically apply and compare 6 computational methods to estimate tumor heterogeneity on 1,697 WES samples from the cancer genome atlas (TCGA) covering 3 cancer types (breast invasive carcinoma, bladder urothelial carcinoma, and head and neck squamous cell carcinoma), and two distinct input mutation sets. We observe significant differences between the estimates produced by different methods, and identify several likely confounding factors in heterogeneity assessment for the different methods. We further show that the prognostic value of tumor heterogeneity for survival prediction is limited in those datasets, and find no evidence that it improves over prognosis based on other clinical variables.In conclusion, heterogeneity inference from WES data on a single sample, and its use in cancer prognosis, should be considered with caution. Other approaches to assess intra-tumoral heterogeneity such as those based on multiple samples may be preferable for clinical applications.
Detection of introduced and resident marine species using environmental DNA metabarcoding of sediment and water
Authors: Holman Luke E. , de Bruyn Mark , Creer Simon , Carvalho Gary , Robidart Julie , Rius Marc 
Published: October 2018

AbstractEnvironmental DNA (eDNA) surveys are increasingly being used for biodiversity monitoring, principally because they are sensitive and can provide high resolution community composition data. Despite considerable progress in recent years, eDNA studies examining how different environmental sample types can affect species detectability remain rare. Comparisons of environmental samples are especially important for providing best practice guidance on early detection and subsequent mitigation of non-indigenous species. Here we used eDNA metabarcoding of COI (cytochrome c oxidase subunit I) and 18S (nuclear small subunit ribosomal DNA) genes to compare community composition between sediment and water samples in artificial coastal sites across the United Kingdom. We first detected markedly different communities and a consistently greater number of distinct operational taxonomic units in sediment compared to water. We then compared our eDNA datasets with previously published rapid assessment biodiversity surveys and found excellent concordance among the different survey techniques. Finally, our eDNA surveys detected many non-indigenous species, including several newly introduced species, highlighting the utility of eDNA metabarcoding for both early detection and temporal / spatial monitoring of non-indigenous species. We conclude that careful consideration on environmental sample type is needed when conducting eDNA surveys, especially for studies assessing community change.
The ghr-miR164 and GhNAC100 module participates in cotton plant defence against Verticillium dahliae
Authors: Hu Guang , Lei Yu , Wang Le , Liu Jianfen , Tang Ye , Zhang Zhennan , Chen Aiming , Peng Qingzhong , Yang Zuoren , Wu Jiahe 
Published: October 2018

AbstractPrevious reports have shown that many miRNAs were identified at the early induction stage during which Verticillium dahliae localizes at the root surface. In this study, we constructed two sRNA libraries of cotton root responses to this fungus at the later induction stage when the pathogen enters the root vascular tissue. We identified 71 known miRNAs and 378 novel miRNAs from two pathogen-induced sRNAs and the control libraries. Combined with degradome and sRNA sequencing, 178 corresponding miRNA target genes were identified, in which 40 target genes from differentially expressed miRNAs were primarily associated with oxidation-reduction and stress responses. More importantly, we characterized the ghr-miR164-GhNAC100 module in the response of the plant to V dahliae infection. A GUS fusion reporter showed that ghr-miR164 directly cleaved the mRNA of GhNAC100 in the post-transcriptional process. ghr-miR164-silencing increased the resistance of the plant to this fungus, while the knockdown of GhNAC100 elevated the susceptibility of the plant, indicating that ghr-miR164-GhNAC100 modulates plant defence through the post-transcriptional regulation. Our data documented that there are numerous miRNAs at the later induction stage that participate in the plant response to V. dahliae, suggesting that miRNAs play important roles in plant resistance to vascular disease.HighlightAccording to degradome and sRNA sequencings of cotton root in responses to Verticillium dahliae at the later induction stage, many miRNAs and corresponding targets including ghr-miR164-GhNAC100 module participate plant defence.
PREPRINT: Using digital epidemiology methods to monitor influenza-like illness in the Netherlands in real-time: the 2017-2018 season
Authors: Schneider PP , van Gool CJAW , Spreeuwenberg P , Hooiveld M , Donker GA , Barnett DJ , Paget J 
Published: October 2018

AbstractIntroductionDespite the early development of Google Flu Trends in 2009, digital epidemiology methods have not been adopted widely, with most research focusing on the USA. In this article we demonstrate the prediction of real-time trends in influenza-like illness (ILI) in the Netherlands using search engine query data.MethodsWe used flu-related search query data from Google Trends in combination with traditional surveillance data from 40 general sentinel practices to build our predictive models. We introduced an artificial 4-week delay in the use of GP data in the models, in order to test the predictive performance of the search engine data.Simulating the weekly use of a prediction model across the 2017/2018 flu season we used lasso regression to fit 52 prediction models (one for each week) for weekly ILI incidence. We used rolling forecast cross-validation for lambda optimization in each model, minimizing the maximum absolute error.ResultsThe models accurately predicted the number of ILI cases during the 2017/18 ILI epidemic in real time with a mean absolute error of 1.40 (per 10,000 population) and a maximum absolute error of 6.36. The model would also have identified the onset, peak, and end of the epidemic with reasonable accuracyThe number of predictors that were retained in the prediction models was small, ranging from 3 to 5, with a single keyword (‘Griep’ = ‘Flu’) having by far the most weight in all models.DiscussionThis study demonstrates the feasibility of accurate real-time ILI incidence predictions in the Netherlands using internet search query data. Digital ILI monitoring strategies may be useful in countries with poor surveillance systems, or for monitoring emergent diseases, including influenza pandemics. We hope that this transparent and accessible case study inspires and supports further developments in field of digital epidemiology in Europe and beyond.
Activation of the endoplasmic reticulum unfolded protein response reverses an inflammation-like response to cytoplasmic DNA
Authors: Williams Ashley B. , Heider Felix , Messling Jan-Erik , Bloch Wilhelm , Schumacher Björn 
Published: October 2018

SUMMARYInnate immune responses protect organisms against various insults, but may lead to tissue damage when aberrantly activated. In higher organisms, cytoplasmic DNA can trigger inflammation that can lead to tissue degeneration. Simpler in vivo models could shed new mechanistic light on how inflammatory responses to cytoplasmic DNA lead to pathology. Here we show that in DNase II-deficient Caenorhabditis elegans, persistent foreign cytoplasmic DNA leads to systemic tissue degeneration, and we identify impaired protein homeostasis as an inflammatory pathomechanism. This pathological outcome can be alleviated by improving protein homeostasis, either via ectopic induction of the endoplasmic reticulum unfolded protein response (UPRER) or by treatment with N-acetylglucosamine. Our results establish C. elegans as an ancestral metazoan model for studying outcomes of inflammation-like conditions caused by persistent cytoplasmic DNA and provide insight into potential therapies for conditions involving chronic inflammation.
∆9-tetrahydrocannabinol negatively regulates neurite outgrowth and Akt signaling in hiPSC-derived cortical neurons
Authors: Shum Carole , Dutan Lucia , Annuario Emily , Warre-Cornish Katherine , Taylor Samuel E. , Taylor Ruth D. , Andreae Laura C. , Buckley Noel J. , Price Jack , Bhattacharyya Sagnik , Srivastava Deepak P. 
Published: October 2018

AbstractEndocannabinoids regulate different aspects of neurodevelopment. In utero exposure to the exogenous psychoactive cannabinoid Δ9-tetrahydrocannabinol (Δ9-THC), has been linked with abnormal cortical development in animal models. However, much less is known about the actions of endocannabinoids in human neurons. Here we investigated the effect of the endogenous endocannabinoid 2-arachidonoyl glycerol (2AG) and Δ9-THC on the development of neuronal morphology and activation of signaling kinases, in cortical glutamatergic neurons derived from human induced pluripotent stem cells (hiPSCs). Our data indicate that the cannabinoid type 1 receptor (CB1R), but not the cannabinoid 2 receptor (CB2R), GPR55 or TRPV1 receptors, is expressed in young, immature hiPSC-derived cortical neurons. Consistent with previous reports, 2AG and Δ9-THC negatively regulated neurite outgrowth. Interestingly, acute exposure to both 2AG and Δ9-THC inhibited phosphorylation of serine/threonine kinase extracellular signal-regulated protein kinases (ERK1/2), whereas Δ9-THC also reduced phosphorylation of Akt (aka PKB). Moreover, the CB1R inverse agonist SR 141716A attenuated the negative regulation of neurite outgrowth and ERK1/2 phosphorylation induced by 2AG and Δ9-THC. Taken together, our data suggest that hiPSC-derived cortical neurons express CB1Rs and are responsive to both endogenous and exogenous cannabinoids. Thus, hiPSC-neurons may represent a good cellular model for investigating the role of the endocannabinoid system in regulating cellular processes in human neurons.
The causal structure of age-dependent limbic decline: fornix white matter glia damage causes hippocampal grey matter damage, notvice versa
Authors: Metzler-Baddeley Claudia , Mole Jilu P. , Sims Rebecca , Fasano Fabrizio , Evans John , Jones Derek K. , Aggleton John P. , Baddeley Roland J. 
Published: October 2018

AbstractAging leads to gray and white matter decline but their causation remains unclear. We explored two broad classes of models of age and dementia risk related brain changes. The first class of models emphasises the importance of gray matter: age and risk-related processes cause neurodegeneration and this causes damage in associated white matter tracts. The second class of models reverses the direction of causation: aging and risk factors cause white matter damage and this leads to gray matter damage. We compared these models with linear mediation analysis and quantitative multi-modal MRI indices (from diffusion, quantitative magnetization transfer and relaxometry imaging) of tissue properties in two limbic structures implicated in age-related memory decline: the hippocampus and the fornix in 166 asymptomatic individuals (aged 38 - 71 years). Aging was associated with apparent glia but not axon density damage in the fornix. Mediation analysis unambiguously supported white matter damage causing gray matter decline; controlling for fornix glia damage, the correlation between age and hippocampal damage disappears, but notvice versa. Fornix and hippocampal tissue loss were both associated with reductions in episodic memory performance. The implications of these findings for neuroglia and neurodegenerative models of aging and late onset dementia are discussed.