bluuebunny/crossref_metadata_2025 huggingface dataset:
Patterns of Postoperative Visits Among Medicare Fee-for-service Beneficiaries
Authors: Kranz Ashley M. , Mulcahy Andrew , Ruder Teague , Lovejoy Susan , Mehrotra Ateev
Published: December 2018

Objective:

To describe patterns of postoperative visits reported for Medicare fee-for-service (FFS) patients.

Background:

Payment for most surgical procedures bundles postoperative visits within a global period of either 10 or 90 days after a procedure. There is concern that payments for some procedures are excessive because the number of postoperative visits provided is less than the number of postoperative visits used to help determine payment. To obtain data to inform this concern, Medicare required select surgeons to report on their postoperative visits starting July 1, 2017.

Methods:

We analyzed Medicare FFS claims data from surgeons who billed Medicare for 1 or more of the 293 common procedure codes between July 1, 2017 and December 31, 2017 in the 9 states where surgeons were required to report postoperative visits. We examined the share of procedures with any reported postoperative visits and the proportion of expected postoperative visits provided. To address concerns about underreporting, we also examined procedures performed by a subset of surgeons actively reporting postoperative visits.

Results:

We linked 663,681 procedures to 422,432 postoperative visits. The share of procedures with any postoperative visits was higher for procedures with 90-day global periods (70.1%) than for procedures with 10-day global periods (3.7%). The proportions of expected postoperative visits provided for 90-day global and 10-day global periods were 0.37 and 0.04 respectively. Among surgeons actively reporting postoperative visits, the proportions of expected postoperative visits provided were modestly higher (procedures with 90-day global periods=0.46 and 10-day global periods=0.16).

Conclusions:

The proportion of expected postoperative visits that were provided is low. These results support the need for a reassessment of payment for surgical procedures.
The Promise of PROMIS in Pelvic Organ Prolapse
Authors: Bochenska Katarzyna , Hall Evelyn , Griffith James W. , Kenton Kimberly , Alverdy Alexandria , Lewicky-Gaupp Christina , Mueller Margaret
Published: December 2018

Objectives

The aims of the study were to determine the relationship between pelvic organ prolapse (POP) and health-related quality of life dimensions and to evaluate the utility of the PROMIS Profile in women undergoing surgical treatment for POP.

Methods

We performed a planned ancillary analysis of 103 women recruited between January 2014 and December 2015 to the Restricted Convalescence Outcomes following Urogynecologic Procedures study. All participants underwent surgery for POP and completed the Pelvic Floor Distress Inventory (PFDI-20), Pelvic Floor Impact Questionnaire (PFIQ-7), Patient Global Impression of Severity Scale, and the 57-item Patient Reported Outcomes Measurement Information System (PROMIS-57) questionnaire, preoperatively and at 3 months postoperatively. Data were analyzed using Pearson and Spearman correlations.

Results

Preoperative PFDI-20 and PFIQ-7 scores were significantly correlated with all PROMIS domains including physical function, anxiety, depression, fatigue, sleep disturbance, satisfaction with participation in social roles, pain interference, and higher pain intensity. Worse self-reported condition assessments on the Patient Global Impression of Severity were significantly correlated with worse physical function, more pain interference, and higher pain intensity on the PROMIS Profile at baseline. Postoperatively, PFDI-20, PFIQ-7, and all PROMIS Profile domain scores improved significantly (P ≤ 0.05). Correlations between PDFI-20, PFIQ-7, and PROMIS domains persisted at 3 months.

Conclusions

In a cohort of women undergoing surgery for POP, pelvic floor symptom severity is associated with health-related quality of life domains measured by the PROMIS-57.
Immunomics of Renal Allograft Acute T Cell-Mediated Rejection Biopsies of Tacrolimus- and Belatacept-Treated Patients
Authors: van der Zwan Marieke , Baan Carla C. , Colvin Robert B. , Smith Rex N. , White Rebecca A. , Ndishabandi Dorothy , Nigg Alex L. , van den Bosch Thierry P.P. , de Graav Gretchen N. , Clahsen-van Groningen Marian C. , Hesselink Dennis A.
Published: December 2018

Background

Belatacept-based therapy in kidney transplant recipient has been shown to increase long-term renal allograft and patient survival compared with calcineurin inhibitor–based therapy, however, with an increased risk of acute T cell-mediated rejection (aTCMR). An improved understanding of costimulation blockade-resistant rejections could lead to a more personalized approach to belatacept therapy. Here, immunomic profiles of aTCMR biopsies of patients treated with either tacrolimus or belatacept were compared.

Methods

Formalin-fixed paraffin-embedded renal transplant biopsies were used for immunohistochemistry and gene expression analysis using the innovative NanoString technique. To validate NanoString, transcriptomic profiles of patients with and without biopsy-proven aTCMR were compared. Biopsies from 31 patients were studied: 14 tacrolimus-treated patients with aTCMR, 11 belatacept-treated patients with aTCMR, and 6 controls without rejection.

Results

A distinct pattern was seen in biopsies with aTCMR compared to negative controls: 78 genes had a higher expression in the aTCMR group (false discovery rate P value <.05 to 1.42e–05). The most significant were T cell-associated genes (CD3, CD8, and CD4; P < 1.98e-04), γ-interferon-inducible genes (CCL5, CXCL9, CXCL11, CXCL10, TBX21; P < 1.33e-04) plus effector genes (GNLY, GZMB, ITGAX; P < 2.82e-03). Immunophenotypical analysis of the classic immune markers of the innate and adaptive immune system was comparable between patients treated with either tacrolimus or belatacept. In addition, the transcriptome of both groups was not significantly different.

Conclusions

In this small pilot study, no difference was found in immunomics of aTCMR biopsies of tacrolimus- and belatacept-treated patients. This suggests that clinically diagnosed aTCMR reflects a final common pathway of allorecognition which is unaffected by the type of immunosuppressive therapy.
Analysis of >30,000 abstracts suggests higher false discovery rates for oncology journals, especially those with low impact factors
Authors: Hall LM , Hendricks AE
Published: December 2018

Background

Recently, there has been increasing concern about the replicability, or lack thereof, of published research. An especially high rate of false discoveries has been reported in some areas motivating the creation of resource-intensive collaborations to estimate the replication rate of published research by repeating a large number of studies. The substantial amount of resources required by these replication projects limits the number of studies that can be repeated and consequently the generalizability of the findings.

Methods and findings

In 2013, Jager and Leek developed a method to estimate the empirical false discovery rate from journal abstracts and applied their method to five high profile journals. Here, we use the relative efficiency of Jager and Leek’s method to gather p-values from over 30,000 abstracts and to subsequently estimate the false discovery rate for 94 journals over a five-year time span. We model the empirical false discovery rate by journal subject area (cancer or general medicine), impact factor, and Open Access status. We find that the empirical false discovery rate is higher for cancer vs. general medicine journals (p = 5.14E-6). Within cancer journals, we find that this relationship is further modified by journal impact factor where a lower journal impact factor is associated with a higher empirical false discovery rates (p = 0.012, 95% CI: -0.010, -0.001). We find no significant differences, on average, in the false discovery rate for Open Access vs closed access journals (p = 0.256, 95% CI: -0.014, 0.051).

Conclusions

We find evidence of a higher false discovery rate in cancer journals compared to general medicine journals, especially those with a lower journal impact factor. For cancer journals, a lower journal impact factor of one point is associated with a 0.006 increase in the empirical false discovery rate, on average. For a false discovery rate of 0.05, this would result in over a 10% increase to 0.056. Conversely, we find no significant evidence of a higher false discovery rate, on average, for Open Access vs. closed access journals from InCites. Our results provide identify areas of research that may need of additional scrutiny and support to facilitate replicable science. Given our publicly available R code and data, others can complete a broad assessment of the empirical false discovery rate across other subject areas and characteristics of published research.
MYC Functions as a Switch for Natural Killer Cell-Mediated Immune Surveillance of Lymphoid Malignancies
Authors: Swaminathan Srividya , Heftdal Line D. , Liefwalker Daniel F. , Dhanasekaran Renumathy , Deutzmann Anja , Horton Crista , Mosley Adriane , Liebersbach Mariola , Maecker Holden T. , Felsher Dean W.
Published: December 2018

The MYC oncogene drives T and B lymphoid malignancies, including Burkitt’s lymphoma (BL) and Acute Lymphoblastic Leukemia (ALL). Using CyTOF, we demonstrate a systemic reduction in natural killer (NK) cell-mediated surveillance inSRα-tTA/Tet-O-MYCONmice bearing MYC-driven T-lymphomas, due to an arrest in NK cell maturation. Inactivation of lymphoma-intrinsic MYC releases the brakes on NK maturation restoring NK homeostasis. Lymphoma-intrinsic MYC arrests NK maturation by transcriptionally repressing STAT1/2 and secretion of Type I Interferons (IFNs). Treating T-lymphoma-bearing mice with Type I IFN improves survival by rescuing NK cell maturation. In MYC-driven BL patients, low expression of both STAT1 and STAT2 correlates significantly with the absence of activated NK cells and predicts unfavorable clinical outcomes. Adoptive transfer of mature NK cells is sufficient to delay both T-lymphoma growth and recurrence post MYC inactivation. Our studies thus provide a rationale for developing NK cell-based therapies to effectively treat MYC-driven lymphomas in the future.

Abbreviations:

CyTOF

Cytometry Time of Flight

BL

Burkitt’s Lymphoma

ALL

Acute Lymphoblastic Leukemia

DLBCL

Diffuse Large B Cell Lymphoma

NK Cell

Natural Killer Cell

STAT1/2

Signal Transducer and Activator of Transcription 1/2

IFN

Interferon

DC

Dendritic Cell

MYC

v-myc avian myelocytomatosis viral oncogene homolog

PRECOG

Prediction of Clinical Outcomes from Genomic Profiles

BLI

Bioluminescence Imaging

TSS

Transcriptional Start Site

HTLV

Human T-lymphotropic Virus

hMYC

human MYC
Imputation of single-cell gene expression with an autoencoder neural network
Authors: Badsha Md. Bahadur , Li Rui , Liu Boxiang , Li Yang I. , Xian Min , Banovich Nicholas E. , Fu Audrey Qiuyan
Published: December 2018

Background

Single-cell RNA-sequencing (scRNA-seq) is a rapidly evolving technology that enables measurement of gene expression levels at an unprecedented resolution. Despite the explosive growth in the number of cells that can be assayed by a single experiment, scRNA-seq still has several limitations, including high rates of dropouts, which result in a large number of genes having zero read count in the scRNA-seq data, and complicate downstream analyses.

Methods

To overcome this problem, we treat zeros as missing values and develop nonparametric deep learning methods for imputation. Specifically, our LATE (Learning with AuToEncoder) method trains an autoencoder with random initial values of the parameters, whereas our TRANSLATE (TRANSfer learning with LATE) method further allows for the use of a reference gene expression data set to provide LATE with an initial set of parameter estimates.

Results

On both simulated and real data, LATE and TRANSLATE outperform existing scRNA-seq imputation methods, achieving lower mean squared error in most cases, recovering nonlinear gene-gene relationships, and better separating cell types. They are also highly scalable and can efficiently process over 1 million cells in just a few hours on a GPU.

Conclusions

We demonstrate that our nonparametric approach to imputation based on autoencoders is powerful and highly efficient.
Chlamydiapan-genomic analysis reveals balance between host adaptation and selective pressure to genome reduction
Authors: Sigalova Olga , Chaplin Andrei V , Bochkareva Olga O , Shelyakin Pavel , Filaretov Vsevolod A , Akkuratov Evgeny , Burskaya Valentina , Gelfand Mikhail S
Published: December 2018

Chlamydiaare ancient intracellular pathogens with reduced, though strikingly conserved genome. Despite their parasitic lifestyle and isolated intracellular environment, these bacteria managed to avoid accumulation of deleterious mutations leading to subsequent genome degradation characteristic for many parasitic bacteria.

We report pan-genomic analysis of eleven species from genusChlamydiaincluding identification and functional annotation of orthologous genes, and characterization of gene gains, losses, and rearrangements. We demonstrate the overall genome stability of these bacteria as indicated by a large fraction of common genes with conserved genomic locations. On the other hand, extreme evolvability is confined to several paralogous gene families such as polymorphic membrane proteins and phospholipase D and likely is caused by the pressure from the host immune system.

This combination of a large, conserved core genome and a small, evolvable periphery likely reflect the balance between the selective pressure towards genome reduction and the need to adapt to changing host environment.
Flowers respond to pollinator sound within minutes by increasing nectar sugar concentration
Authors: Veits Marine , Khait Itzhak , Obolski Uri , Zinger Eyal , Boonman Arjan , Goldshtein Aya , Saban Kfir , Ben-Dor Udi , Estlein Paz , Kabat Areej , Peretz Dor , Ratzersdorfer Ittai , Krylov Slava , Chamovitz Daniel , Sapir Yuval , Yovel Yossi , Hadany Lilach
Published: December 2018

Can plants hear? That is, can they sense airborne sounds and respond to them? Here we show that Oenothera drummondii flowers, exposed to the playback sound of a flying bee or to synthetic sound-signals at similar frequencies, produced sweeter nectar within 3 minutes, potentially increasing the chances of cross pollination. We found that the flowers vibrated mechanically in response to these sounds, suggesting a plausible mechanism where the flower serves as the plant’s auditory sensory organ. Both the vibration and the nectar response were frequency-specific: the flowers responded to pollinator sounds, but not to higher frequency sound. Our results document for the first time that plants can rapidly respond to pollinator sounds in an ecologically relevant way. Sensitivity of plants to pollinator sound can affect plant-pollinator interactions in a wide range of ways: Plants could allocate their resources more adequately, focusing on the time of pollinator activity; pollinators would then be better rewarded per time unit; flower shape may be selected for its effect on hearing ability, and not only on signaling; and pollinators may evolve to make sounds that the flowers can hear. Finally, our results suggest that plants may be affected by other sounds as well, including antropogenic ones.
Synapse propensity of human memory CD8 T cells confers competitive advantage over naïve counterparts
Authors: Mayya Viveka , Judokusumo Edward , Abu-Shah Enas , Neiswanger Willie , Kam Lance C , Dustin Michael L
Published: December 2018

Memory T cells are endowed with multiple functional features that enable them to be more protective than naïve T cells against infectious threats. It is not known if memory cells have a higher synapse propensity, i.e. increased probability to form immature immunological synapses that then provide an entry into different modes of durable interaction with antigen presenting cells. Here we show that only human memory CD8 T cells have remarkably high synapse propensity compared to naïve counterparts. Such a dichotomy between naïve and memory cells is not observed within the human CD4 or murine CD8 T cell population. Increased surface expression of LFA1 contributes to the higher synapse propensity in human memory CD8 T cells. Finally, we show that higher synapse propensity in human memory CD8 T cells allows them to compete out naïve CD8 T cells from getting recruited to the response. This observation has implications for original antigenic sin and aging of the immune system in humans.
Quantitative interactions driveBotrytis cinereadisease outcome across the plant kingdom
Authors: Caseys Celine , Shi Gongjun , Soltis Nicole , Gwinner Raoni , Corwin Jason , Atwell Susanna , Kliebenstein Daniel
Published: December 2018

Botrytis cinereais a polyphagous fungal pathogen that causes necrotic disease on more than a thousand known hosts widely spread across the plant kingdom. While it is known that quantitative resistance in the host and quantitative virulence in the pathogen largely mediate this pathosystem, how this pathogen interacts with the extensive host diversity is unknown. Does this pathogen have quantitative virulence efficiency on all hosts or individual solutions for each host? To address this question, we generated an infectivity matrix of 98 strains ofBotrytis cinereaon 90 genotypes representing eight host plants. This experimental infectivity matrix showed that the predominant sources of quantitative variation are between host species and among pathogen strains. Furthermore, the eight eudicot hosts interacted individually withBotrytis cinereastrains independently of the evolutionary relatedness between hosts. An additive quantitative model can explain the complexity of these interactions in which Botrytis host specificity and general virulence have distinct polygenic architectures.
Impact of Kuntai Capsules on LIF, IGF-1 and EGF Expression in the Implantation Window of Endometrium in Mice
Authors: Tan Li , Li Xiao-Xu , Chu Xi-Ying , Li Yan , Wan Li-Jing
Published: December 2018

Objective: This study aims to investigate the influence of Kuntai capsules on the expression level of leukemia inhibitory factor (LIF), insulin-like growth factor-I (IGF-1) and epidermal growth factor (EGF) during the mouse implantation window of superovulation period and controlled ovarian hyperstimulation period. Methods: A total of 90 female mice were randomly divided into six groups (n=15, each group). The RNA expression of EGF, LIF and IGF-1 in the endometrium on the 4th day of pregnancy was detected using the fluorescence quantitative PCR method, and the relative expression of these three factors in each group was compared. Results: The mRNA expression of these three factors in the endometrium during the mouse implantation window period was significantly lower in the superovulation group and COH group than in the control group (P<0.001), and was obviously lower in the superovulation group than in the COH group (P<0.05). The mRNA expression of these three factors in the endometrium remained obviously lower in the superovulation plus kuntai capsule group and COH plus kuntai capsule group, compared with the control group (P<0.01). The mRNA expression of these three factors in the endometrium was lower in control group than in the NS plus kuntai capsule group (P<0.05). Furthermore, the expression in the superovulation and COH groups was lower than in the COH plus kuntai capsule group (P<0.05). Conclusions: Both the superovulation and COH procedure could reduce the mouse endometrial receptivity. The application of the Chinese medicine Kuntai capsule could partially improve a mouse endometrial receptivity through the increasing expression of three relevant cytokines during the implantation window.
TIGAR: An Improved Bayesian Tool for Transcriptomic Data Imputation Enhances Gene Mapping of Complex Traits
Authors: Nagpal Sini , Meng Xiaoran , Epstein Michael P. , Tsoi Lam C. , Patrick Matthew , Gibson Greg , De Jager Philip L. , Bennett David A. , Wingo Aliza P. , Wingo Thomas S. , Yang Jingjing
Published: December 2018

The transcriptome-wide association studies (TWAS) that test for association between the study trait and the imputed gene expression levels from cis-acting expression quantitative trait loci (cis-eQTL) genotypes have successfully enhanced the discovery of genetic risk loci for complex traits. By using the gene expression imputation models fitted from reference datasets that have both genetic and transcriptomic data, TWAS facilitates gene-based tests with GWAS data while accounting for the reference transcriptomic data. The existing TWAS tools like PrediXcan and FUSION use parametric imputation models that have limitations for modeling the complex genetic architecture of transcriptomic data. Therefore, we propose an improved Bayesian method that assumes a data-driven nonparametric prior to impute gene expression. Our method is general and flexible and includes both the parametric imputation models used by PrediXcan and FUSION as special cases. Our simulation studies showed that the nonparametric Bayesian model improved both imputation R2 for transcriptomic data and the TWAS power over PrediXcan. In real applications, our nonparametric Bayesian method fitted transcriptomic imputation models for 2X number of genes with 1.7X average regression R2 over PrediXcan, thus improving the power of follow-up TWAS. Hence, the nonparametric Bayesian model is preferred for modeling the complex genetic architecture of transcriptomes and is expected to enhance transcriptome-integrated genetic association studies. We implement our Bayesian approach in a convenient software tool “TIGAR” (Transcriptome-Integrated Genetic Association Resource), which imputes transcriptomic data and performs subsequent TWAS using individual-level or summary-level GWAS data.
Protect, Modify, Deprotect (PMD): A strategy for creating vaccines to elicit antibodies targeting a specific epitope
Authors: Weidenbacher Payton A. , Kim Peter S.
Published: December 2018

In creating vaccines against infectious agents, there is often a desire to direct an immune response toward a particular conformational epitope on an antigen. We present a method, called Protect, Modify, Deprotect (PMD), to generate immunogenic proteins aimed to direct a vaccine-induced antibody response toward an epitope defined by a specific monoclonal antibody (mAb). The mAb is used to protect the target epitope on the protein. Then, the remaining exposed surfaces of the protein are modified to render them non-immunogenic. Finally, the epitope is deprotected by removal of the mAb. The resultant protein is modified at surfaces other than the target epitope. We validate PMD using the well-characterized antigen, hen egg white lysozyme (HEWL). Then, we demonstrate the utility of PMD using influenza virus hemagglutinin (HA). Specifically, we use a mAb to protect a highly conserved epitope on the stem domain of HA. Exposed surface amines are then modified by introducing short polyethylene glycol (PEG) chains. The resultant antigen shows markedly reduced binding to mAbs that target the variable head region of HA, while maintaining binding to mAbs at the epitope of interest in the stem region. This antigenic preference is also observed with yeast cells displaying antibody fragments. Antisera from guinea pigs immunized with the PMD modified HA show increased cross-reactivity with HAs from other influenza strains, as compared to antisera obtained with unmodified HA trimers. PMD has the potential to direct an antibody response at high-resolution and could be used in combination with other such strategies. There are many attractive targets for the application of PMD.
Estrogen receptor alpha controls gene expression via translational offsetting
Authors: Lorent Julie , Rebello Richard J. , Hoef Vincent van , Lawrence Mitchell G. , Szkop Krzysztof J. , Kusnadi Eric , Samreen Baila , Balanathan Preetika , Scharmann Karin , Takizawa Itsuhiro , Leidel Sebastian A. , Risbridger Gail P. , Topisirovic Ivan , Larsson Ola , Furic Luc
Published: December 2018

Estrogen receptor alpha (ERα) activity is associated with increased cancer cell proliferation. Studies aiming to understand the impact of ERα on cancer-associated phenotypes have largely been limited to its transcriptional activity. Herein, we demonstrate that ERα coordinates its transcriptional output with selective modulation of mRNA translation. Importantly, translational perturbations caused by depletion of ERα largely manifest as “translational offsetting” of the transcriptome, whereby amounts of translated mRNA and protein levels are maintained constant despite changes in mRNA abundance. Transcripts whose levels, but not polysome-association, are reduced following ERα depletion lack features which limit translational efficiency including structured 5’UTRs and miRNA target sites. In contrast, mRNAs induced upon ERα depletion whose polysome-association remains unaltered are enriched in codons requiring U34-modified tRNAs for efficient decoding. Consistently, ERα regulates levels of U34-modification enzymes, whereas altered expression of U34-modification enzymes disrupts ERα dependent translational offsetting. Altogether, we unravel a hitherto unprecedented mechanism of ERα-dependent orchestration of transcriptional and translational programs, and highlight that translational offsetting may be a pervasive mechanism of proteome maintenance in hormone-dependent cancers.
Plants emit informative airborne sounds under stress
Authors: Khait I. , Lewin-Epstein O. , Sharon R. , Saban K. , Perelman R. , Boonman A. , Yovel Y. , Hadany L.
Published: December 2018

Stressed plants show altered phenotypes, including changes in color, smell, and shape. Yet, the possibility that plants emitairborne soundswhen stressed – similarly to many animals – has not been investigated. Here we show, to our knowledge for the first time, that stressed plants emit airborne sounds that can be recorded remotely, both in acoustic chambers and in greenhouses. We recorded ∼65 dBSPL ultrasonic sounds 10 cm from tomato and tobacco plants, implying that these sounds could be detected by some organisms from up to several meters away. We developed machine learning models that were capable of distinguishing between plant sounds and general noises, and identifying the condition of the plants – dry, cut, or intact – based solely on the emitted sounds. Our results suggest that animals, humans, and possibly even other plants, could use sounds emitted by a plant to gain information about the plant’s condition. More investigation on plant bioacoustics in general and on sound emission in plants in particular may open new avenues for understanding plants and their interactions with the environment, and it may also have a significant impact on agriculture.
Novel Dual Labeled Fluorescence Probe Based Assay to Measure the Telomere Length
Authors: Sethi Itty , Bhat Gh. Rasool , Kumar Rakesh , Rai Ekta , Sharma Swarkar
Published: December 2018

Telomeres are highly repetitive regions capping the chromosomes and composed of multiple units of hexa-nucleotides, TTAGGG, making their quantification difficult. Most of the methods developed to estimate telomeres are extensively cumbersome and expensive. The quantitative polymerase chain reaction (qPCR) based assay is relatively easy and cheaper method that applies SyBr Green dye chemistry to measure telomere length. As SyBr Green dye fluoresces after intercalation into the dsDNA, lack of differentiation between specific PCR target products and unspecific products is a limitation and it affects accuracy in quantitation of telomeres. To overcome the limitations of SyBr Green, we developed a dual labeled fluorescence probe based quantitative polymerase chain reaction (qPCR) to measure the telomere length. This robust, accurate and highly reproducible (R2=0.96) proprietary method (patent pending), yet cost effective and easy, utilizes a probe that targets specifically the telomeric DNA.
Deciphering copper coordination in the animal prion protein amyloidogenic domain
Authors: Salzano Giulia , Brennich Martha , Mancini Giordano , Tran Thanh Hoa , Legname Giuseppe , Angelo Paola D’ , Giachin Gabriele
Published: December 2018

Prions are pathological isoforms of the cellular prion protein (PrPC) responsible for transmissible spongiform encephalopathies (TSE). PrPC interacts with copper through unique octarepeat and non-octarepeat (non-OR) binding sites. Previous works on human PrPC suggest that copper binding to the non-OR region may have a role during prion conversion. The molecular details of copper coordination within the non-OR region are not well characterized. By means of small angle X-ray scattering (SAXS) and extended X-ray absorption fine structure (EXAFS) spectroscopy, we have investigated the Cu(II) structural effects on the protein folding and its coordination geometries when bound to the non-OR region of recombinant PrPC (recPrP) from animal species considered high or less resistant to TSE. As TSE-resistant model, we used ovine PrPC carrying the protective polymorphism at residues A136, R154 and R171 (OvPrP ARR); while as highly TSE-susceptible PrPC models we employed OvPrP with polymorphism V136, R154 and Q171 (OvPrP VRQ) and Bank vole recPrP (BvPrP). Our results reveal that Cu(II) affects the structural plasticity of the non-OR region leading to a more compacted conformation of recPrP. We also identified two Cu(II) coordinations in the non-OR region of these animal species. In type-1 coordination present in OvPrP ARR, Cu(II) is coordinated by four residues (S95, Q98, M109 and H111). Conversely, the type-2 coordination is present in OvPrP VRQ and BvPrP, where Cu(II) is coordinated by three residues (Q98, M109 and H111) and by one water molecule, making the non-OR region more flexible and open to the solvent. These changes in copper coordination in prion resistant and susceptible species provide new insights into the molecular mechanisms governing the resistance or susceptibility of certain species to TSE.
The complete structure of the human TFIIH core complex
Authors: Greber Basil , Toso Daniel , Fang Jie , Nogales Eva
Published: December 2018

Transcription factor IIH (TFIIH) is a heterodecameric protein complex critical for transcription initiation by RNA polymerase II and nucleotide excision DNA repair. The TFIIH core complex is sufficient for its repair functions and harbors the XPB and XPD DNA-dependent ATPase/helicase subunits, which are affected by human disease mutations. Transcription initiation additionally requires the CdK activating kinase subcomplex. Previous structural work has provided only partial insight into the architecture of TFIIH and its interactions within transcription pre-initiation complexes. Here, we present the complete structure of the human TFIIH core complex, determined by phase-plate cryo-electron microscopy at 3.7 Angstroms resolution. The structure uncovers the molecular basis of TFIIH assembly, revealing how the recruitment of XPB by p52 depends on a pseudo-symmetric dimer of homologous domains in these two proteins. The structure also suggests a function for p62 in the regulation of XPD, and allows the mapping of previously unresolved human disease mutations.
High throughput genotyping of structural variations in a complex plant genome using an original Affymetrix® Axiom® array
Authors: Mabire Clément , Duarte Jorge , Darracq Aude , Pirani Ali , Rimbert Hélène , Madur Delphine , Combes Valérie , Vitte Clémentine , Praud Sébastien , Rivière Nathalie , Joets Johann , Pichon Jean-Philippe , Nicolas Stéphane D.
Published: December 2018

Background

Insertions/deletions (InDels) and more specifically presence/absence variations (PAVs) are pervasive in several species and have strong functional and phenotypic effect by removing or drastically modifying genes. Genotyping of such variants on large panels remains poorly addressed, while necessary for approaches such as association mapping or genomic selection.

Results

We have developed, as a proof of concept, a new high-throughput and affordable approach to genotype InDels. We first identified 141,000 InDels by aligning reads from the B73 line against the genome of three temperate maize inbred lines (F2, PH207, and C103) and reciprocally. Next, we designed an Affymetrix® Axiom® array to target these InDels, with a combination of probes selected at breakpoint sites (13%) or within the InDel sequence, either at polymorphic (25%) or non-polymorphic sites (63%) sites. The final array design is composed of 662,772 probes and targets 105,927 InDels, including PAVs ranging from 35bp to 129kbp. After Affymetrix® quality control, we successfully genotyped 86,648 polymorphic InDels (82% of all InDels interrogated by the array) on 445 maize DNA samples with 422,369 probes. Genotyping InDels using this approach produced a highly reliable dataset, with low genotyping error (~3%), high call rate (~98%), and high reproducibility (>95%). This reliability can be further increased by combining genotyping of several probes calling the same InDels (<0.1% error rate and >99.9% of call rate for 5 probes). This “proof of concept” tool was used to estimate the kinship matrix between 362 maize lines with 57,824 polymorphic InDels. This InDels kinship matrix was highly correlated with kinship estimated using SNPs from Illumina 50K SNP arrays.

Conclusions

We efficiently genotyped thousands of small to large InDels on a sizeable number of individuals using a new Affymetrix®Axiom®array. This powerful approach opens the way to studying the contribution of InDels to trait variation and heterosis in maize. The approach is easily extendable to other species and should contribute to decipher the biological impact of InDels at a larger scale.
Human microbiome aging clocks based on deep learning and tandem of permutation feature importance and accumulated local effects
Authors: Galkin Fedor , Aliper Alexander , Putin Evgeny , Kuznetsov Igor , Gladyshev Vadim N , Zhavoronkov Alex
Published: December 2018

The human gut microbiome is a complex ecosystem that both affects and is affected by its host status. Previous analyses of gut microflora revealed associations between specific microbes and host health and disease status, genotype and diet. Here, we developed a method of predicting the biological age of the host based on the microbiological profiles of gut microbiota using a curated dataset of 1,165 healthy individuals (1,663 microbiome samples). Our predictive model, a human microbiome clock, has an architecture of a deep neural network and achieves the accuracy of 3.94 years mean absolute error in cross-validation. The performance of the deep microbiome clock was also evaluated on several additional populations. We further introduce a platform for biological interpretation of individual microbial features used in age models, which relies on permutation feature importance and accumulated local effects. This approach has allowed us to define two lists of 95 intestinal biomarkers of human aging. We further show that this list can be reduced to 39 taxa that convey the most information on their host's aging. Overall, we show that (a) microbiological profiles can be used to predict human age; and (b) microbial features selected by models are age-related.
Past–future information bottleneck framework for simultaneously sampling biomolecular reaction coordinate, thermodynamics and kinetics
Authors: Wang Yihang , Lamim Ribeiro João Marcelo , Tiwary Pratyush
Published: December 2018

The ability to rapidly learn from high-dimensional data to make reliable bets about the future outcomes is crucial in many contexts. This could be a fly avoiding predators, or the retina processing gigabytes of data almost instantaneously to guide complex human actions. In this work we draw parallels between such tasks, and the efficient sampling of complex biomolecules with hundreds of thousands of atoms. For this we use the Predictive Information Bottleneck (PIB) framework developed and used for the first two classes of problems, and re-formulate it for the sampling of biomolecular structure and dynamics, especially when plagued with rare events. Our method considers a given biomolecular trajectory expressed in terms of order parameters or basis functions, and uses a deep neural network to learn the minimally complex yet most predictive aspects of this trajectory, viz the PIB. This information is used to perform iterative rounds of biased simulations that enhance the sampling along the PIB to gradually improve its accuracy, directly obtaining associated thermodynamic and kinetic information. We demonstrate the method on two test-pieces, including benzene dissociation from the protein lysozyme, where we calculate the dissociation pathway and timescales slower than milliseconds. Finally, by performing an analysis of residues contributing to the PIB, we predict the critical mutations in the system which would be most impactful on the stability of the crucial but ephemeral transition state. We believe this work marks a big step forward in the use of predictive artificial intelligence ideas for the sampling of biomolecules.
A pairwise maximum entropy model uncovers the white matter scaffold underlying emergent dynamics in intracranial EEG
Authors: Ashourvan Arian , Shah Preya , Pines Adam , Gu Shi , Lynn Christopher W. , Bassett Danielle S. , Davis Kathryn A. , Litt Brian
Published: December 2018

A major challenge in systems neuroscience is to understand how the brain’s structural architecture gives rise to its complex functional dynamics. Here, we address this challenge by examining the inter-ictal activity of five patients with medically refractory epilepsy during ∼ 15 hours of multi-channel intracranial recording. By constructing a pairwise maximum entropy model (MEM) of the observed neural dynamics, we seek to uncover the fundamental relationship between functional activity and its underlying structural substrate. Despite only incorporating the pairwise correlations in the observed neural activity, we find that the pairwise MEM robustly fits large-scale patterns of inter-ictal power dynamics across a wide range of frequency bands, notably displaying time-invariance and cross-frequency similarity. Furthermore, across all frequency bands, we demonstrate that the pairwise MEM accurately identifies the structural white matter connections between brain regions, outperforming other common model-free measures of functional connectivity. Together, our findings show that a simple pairwise MEM, which is explicitly ignorant of higher-order correlations between three or more brain regions, not only captures complex spatiotemporal patterns of neural activity across the frequency spectrum, but also suggests that the network of structural connections in the human brain is a plausible scaffold capable of supporting observed wide-band neural dynamics.
Revisiting the dimensionality of biological diversity
Authors: Nakamura Gabriel , Gonçalves Larissa Oliveira , Duarte Leandro
Published: December 2018

Biodiversity can be represented by a variety of different dimensions (e.g. functional diversity, phylogenetic diversity, genetic diversity and taxonomic diversity). While the many different representations of biodiversity can lead to a more complete description of communities, they also lead to a degree of ‘fragmentation’ of the biodiversity concept. Developing a unified measure that integrates all the dimensions of biodiversity is a theoretical solution for this problem, however, it remains an operationally utopian task. Alternatively, quantifying the dimensionality of biodiversity is a way to integrate the different dimensions of biological diversity. This concept is explored in the present study. We define the dimensionality of diversity as the number of different diversity metrics needed to effectively describe biodiversity. We provide a solution that joins the two components of dimensionality (correlation and the variation of each diversity metric) in the same framework, allowing us to quantify dimensionality. We show, through a simulation study, that considering the correlation among dimensions with the variation of each dimension offers important information that is neglected when only correlation information (the component used in the current methodology to measure dimensionality) is considered. We demonstrate how to apply the proposed framework by investigating the dimensionality of South American small mammal communities (cricetids and marsupials). Our example demonstrates that the taxonomic dimension of diversity captures most of the spatial variation among these communities. We conclude by highlighting the greater understanding of dimensionality that is obtained through this method, as well as the insights it provides into the importance of each diversity metric to the whole biodiversity space, insights which can not be obtained through the current common method.
Prefrontal pathways provide top down control of memory for sequences of events
Authors: Jayachandran Maanasa , Linley Stephanie , Schlecht Maximilian , Mahler Stephen V. , Vertes Robert P. , Allen Timothy A.
Published: December 2018

We remember our lives as sequences of events, but it is unclear how these memories are controlled during retrieval. In rats, prelimbic cortex (PL) is positioned to influence sequence memory through extensive top down inputs to the nucleus reuniens of the thalamus (RE) and perirhinal cortex (PER), regions heavily interconnected with the hippocampus. Here, we tested the hypothesis that specific PL➔RE and PL➔PER projections regulate sequence memory retrieval using an hM4Di synaptic-silencing approach. First, we show that the suppression of PL activity impairs sequence memory. Second, we show that inhibiting PL➔RE and PL➔PER pathways effectively eliminated sequence memory. Last, we performed a sequential lag analysis showing that the PL➔RE pathway contributes to a working memory retrieval strategy, and the PL➔PER pathway contributes to a temporal context memory retrieval strategy. These results demonstrate that the PL➔RE and PL➔PER pathways serve as top down mechanisms that control sequence memory retrieval strategies.
Crowding and binding: Not all feature-dimensions behave in the same way
Authors: Yashar Amit , Wu Xiuyun , Chen Jiageng , Carrasco Marisa
Published: December 2018

Humans often fail to identify a target because of nearby flankers. The nature and stage(s) at which this 'crowding' occurs are unclear, and whether crowding operates via a common mechanism across visual dimensions is unknown. Using a dual estimation report, we quantitatively assessed the processing of each feature alone and in conjunction with another feature both within and between dimensions. Crowding emerged due to confusion between orientations or colors of target and flankers, but averaging of their spatial frequencies (SFs). Furthermore, crowding of orientation and color were independent, but crowding of orientation and SF were interdependent. This qualitative difference of crowding errors across dimensions revealed a tight link between crowding and 'illusory conjunctions' (mis-binding of feature dimensions). These results and a computational model suggest that crowding and illusory conjunction in the visual periphery are due to pooling across a joint coding of orientation and spatial frequencies but not of color.
Teachers’ perceptions on inclusion in basic school
Authors: Manrique Ana Lucia , Dirani Ely A.T. , Frere Annie F. , Moreira Geraldo E. , Arezes Pedro M.
Published: December 2018

Purpose

Despite dealing with special educational needs (SEN) students, many teachers feel unprepared for this task. This situation reveals the urgent need for studies in different areas, directed toward the inclusion of students in regular classrooms. Therefore, a diagnosis about the situation of inclusive education and the resources available in schools offering regular teaching becomes of paramount importance. Therefore, the purpose of this paper is to present the results of an investigation that sought information on pedagogical work in inclusive education and in the use of support materials by teachers of basic education in Brazil and Portugal.

Design/methodology/approach

In order to carry out this investigation, a questionnaire was developed by a partnership between researchers from the Pontifical Catholic University of São Paulo, Brazil and the University of Minho, Portugal, and applied to mathematics teachers. The study participants consisted of 197 mathematics teachers, working in primary school, secondary school and young people and adult education. Data collection was carried out through a questionnaire, available online and designed in Google Forms, with 48 questions (both open and closed formats).

Findings

From the results obtained, there is a clear need not only for promoting initial and further teacher training that takes into consideration the profile of this teacher, but also for promoting the development of support materials (games, software, devices and assistive technology) in a collaborative way, involving users, teachers, engineers in a way to ensure a good usability and adequate adaptability. Thus, the inclusion of SEN students in schools must not take place only with their physical integration, but also must consider their integration at social, emotional and educational levels.

Originality/value

It is understood that the teacher should receive a solid training in successful inclusion experiences in terms of technological, educational and didactic experiences. Another problem that seems to be recurrent is that support materials have been developed in a way that is somehow disconnected from the reality of the classroom. The context in which the support material is inserted is fundamental to the success of its utilization. What is more, it cannot be isolated from the individuals who will use it. It thus becomes urgent to prepare the school environment for the reality of inclusion. This involves aspects from changes in infrastructure and development of assistive technology to assist the student with SEN in their learning, to the establishment of public policies that involve teacher initial and further training, specialized support and curricular discussions.
Audiovisual aids application in the secondary-level vocational education establishments
Authors: Akhmetshin Elvir Munirovich , Ibatullin Rinat Rivkatovich , Gapsalamov Almaz Rafisovich , Vasilev Vladimir Lvovich , Bakhvalov Sergey Yurevich
Published: December 2018

Purpose

The purpose of this paper is to analyze how the audiovisual teaching aids are applied in the modern educational environment and to assess their application efficiency in the context of the secondary-level vocational education establishments.

Design/methodology/approach

A pedagogical experiment was conducted to confirm this hypothesis. At the preparatory stage, the authors have analyzed the teaching and learning process, as well as students learning at the secondary-level vocational education establishment. Statistical sample was 300 people.

Findings

Based on the research results, main mistakes made while applying the audiovisual teaching aids were identified, formulated and investigated. These mistakes were related to the insufficient methodological preparation. As these mistakes were eliminated, student achievements and learning skills have increased by 15–20 percent (experiment data). The average marks, obtained by students before and after eliminating the methodological mistakes, were taken in points (from 2 to 5) as achievement and learning skill criteria. Research conclusion is that audiovisual aids application quality can be improved only through the research on students’ educational and creative potential, their perception of various learning materials, and their preferences in the information structure, composition, types and forms.

Originality/value

Applying audiovisual teaching aids in the learning process is a challenge. This paper is driven by the need of new unique methods for applying audiovisual aids related to identifying the optimal temporal lesson structure, as well as the composition and the amount of auxiliary teaching materials, interactive communication level and ways to stimulate the emotional and creative activity of students.