Accurate and efficient constrained molecular dynamics of polymers using Newton's method and special purpose code

In molecular dynamics simulations we can often increase the time step by imposing constraints on bond lengths and bond angles. This allows us to extend the length of the time interval and therefore the range of physical phenomena that we can afford to simulate. We examine the existing algorithms and software for solving nonlinear constraint equations in parallel and we explain why it is necessary to advance the state-of-the-art. We present ILVES-PC, a new algorithm for imposing bond constraints on proteins accurately and efficiently. It solves the same system of differential algebraic equations as the celebrated SHAKE algorithm, but ILVES-PC solves the nonlinear constraint equations using Newton’s method rather than the nonlinear Gauss-Seidel method. Moreover, ILVES-PC solves the necessary linear systems using a specialized linear solver that exploits the structure of the protein. ILVES-PC can rapidly solve constraint equations as accurately as the hardware will allow. The run-time of ILVES-PC is proportional to the number of constraints. We have integrated ILVES-PC into GROMACS and simulated proteins of different sizes. Compared with SHAKE, we have achieved speedups of up to 4.9× in single-threaded executions and up to 76× in shared-memory multi-threaded executions. Moreover, ILVES-PC is more accurate than P-LINCS algorithm. Our work is a proof-of-concept of the utility of software designed specifically for the simulation of polymers

Detection of cytomegalovirus in bronchoalveolar lavage fluid from immunocompromised patients with pneumonitis by viral culture and DNA quantification

Altres ajuts: acords transformatius de la UABTo compare the detection of human cytomegalovirus (HCMV) in bronchoalveolar lavage (BAL) fluid by viral culture and quantitative polymerase chain reaction (qPCR), and to establish a viral load threshold that can identify cases of HCMV replication indicative of pneumonitis. There is currently no universal viral load cut-off to differentiate between patients with and without pneumonitis, and the interpretation of qPCR results is challenging. 176 consecutive BAL samples from immunosuppressed hosts with signs and/or symptoms of respiratory infection were prospectively studied by viral culture and qPCR. Concordant results were obtained in 81.25% of the BAL samples. The rest were discordant, as only 34% of the qPCR-positive BAL samples were positive by culture. The median HCMV load was significantly higher in culture-positive than in culture-negative BAL samples (5038 vs 178 IU/mL). Using a cut-off value of 1258 IU/mL of HCMV in BAL, pneumonia was diagnosed with a sensitivity of 76%, a specificity of 100%, a VPP of 100% and VPN of 98%, and HCMV was isolated in 100% of the BAL cultures. We found that a qPCR-negative was a quick and reliable way of ruling out HCMV pneumonitis, but a positive result did not always indicate clinically significant replication in the lung. However, an HCMV load in BAL fluid of ≥ 1258 IU/mL was always associated with disease, whereas < 200 IU/mL rarely so

Leveraging gene expression subgroups to classify DLBCL patients and select for clinical benefit from a novel agent

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease, commonly described by cell-of-origin (COO) molecular subtypes. We sought to identify novel patient subgroups through an unsupervised analysis of a large public dataset of gene expression profiles from newly diagnosed de novo DLBCL patients, yielding 2 biologically distinct subgroups characterized by differences in the tumor microenvironment. Pathway analysis and immune deconvolution algorithms identified higher B-cell content and a strong proliferative signal in subgroup A and enriched T-cell, macrophage, and immune/inflammatory signals in subgroup B, reflecting similar biology to published DLBCL stratification research. A gene expression classifier, featuring 26 gene expression scores, was derived from the public dataset to discriminate subgroup A (classifier-negative, immune-low) and subgroup B (classifier-positive, immune-high) patients. Subsequent application to an independent series of diagnostic biopsies replicated the subgroups, with immune cell composition confirmed via immunohistochemistry. Avadomide, a CRL4CRBN E3 ubiquitin ligase modulator, demonstrated clinical activity in relapsed/refractory DLBCL patients, independent of COO subtypes. Given the immunomodulatory activity of avadomide and the need for a patient-selection strategy, we applied the gene expression classifier to pretreatment biopsies from relapsed/refractory DLBCL patients receiving avadomide (NCT01421524). Classifier-positive patients exhibited an enrichment in response rate and progression-free survival of 44% and 6.2 months vs 19% and 1.6 months for classifier-negative patients (hazard ratio, 0.49; 95% confidence interval, 0.280-0.86; P = .0096). The classifier was not prognostic for rituximab, cyclophosphamide, doxorubicin, vincristine, prednisone or salvage immunochemotherapy. The classifier described here discriminates DLBCL tumors based on tumor and nontumor composition and has potential utility to enrich for clinical response to immunomodulatory agents, including avadomide

El nicho ecológico de los hominidos del Pleistoceno Medio de Atapuerca.

Sin resume

Advancing Key Gaps in the Knowledge of Plasmodium vivax Cryptic Infections Using Humanized Mouse Models and Organs-on-Chips

Plasmodium vivax is the most widely distributed human malaria parasite representing 36.3% of disease burden in the South-East Asia region and the most predominant species in the region of the Americas. Recent estimates indicate that 3.3 billion of people are under risk of infection with circa 7 million clinical cases reported each year. This burden is certainly underestimated as the vast majority of chronic infections are asymptomatic. For centuries, it has been widely accepted that the only source of cryptic parasites is the liver dormant stages known as hypnozoites. However, recent evidence indicates that niches outside the liver, in particular in the spleen and the bone marrow, can represent a major source of cryptic chronic erythrocytic infections. The origin of such chronic infections is highly controversial as many key knowledge gaps remain unanswered. Yet, as parasites in these niches seem to be sheltered from immune response and antimalarial drugs, research on this area should be reinforced if elimination of malaria is to be achieved. Due to ethical and technical considerations, working with the liver, bone marrow and spleen from natural infections is very difficult. Recent advances in the development of humanized mouse models and organs-on-a-chip models, offer novel technological frontiers to study human diseases, vaccine validation and drug discovery. Here, we review current data of these frontier technologies in malaria, highlighting major challenges ahead to study P. vivax cryptic niches, which perpetuate transmission and burden

Human Gene Coexpression Landscape: Confident Network Derived from Tissue Transcriptomic Profiles

This is an open-access article distributed under the terms of the Creative Commons Attribution License.[Background]: Analysis of gene expression data using genome-wide microarrays is a technique often used in genomic studies to find coexpression patterns and locate groups of co-transcribed genes. However, most studies done at global >omic> scale are not focused on human samples and when they correspond to human very often include heterogeneous datasets, mixing normal with disease-altered samples. Moreover, the technical noise present in genome-wide expression microarrays is another well reported problem that many times is not addressed with robust statistical methods, and the estimation of errors in the data is not provided. [Methodology/Principal Findings]: Human genome-wide expression data from a controlled set of normal-healthy tissues is used to build a confident human gene coexpression network avoiding both pathological and technical noise. To achieve this we describe a new method that combines several statistical and computational strategies: robust normalization and expression signal calculation; correlation coefficients obtained by parametric and non-parametric methods; random cross-validations; and estimation of the statistical accuracy and coverage of the data. All these methods provide a series of coexpression datasets where the level of error is measured and can be tuned. To define the errors, the rates of true positives are calculated by assignment to biological pathways. The results provide a confident human gene coexpression network that includes 3327 gene-nodes and 15841 coexpression-links and a comparative analysis shows good improvement over previously published datasets. Further functional analysis of a subset core network, validated by two independent methods, shows coherent biological modules that share common transcription factors. The network reveals a map of coexpression clusters organized in well defined functional constellations. Two major regions in this network correspond to genes involved in nuclear and mitochondrial metabolism and investigations on their functional assignment indicate that more than 60% are house-keeping and essential genes. The network displays new non-described gene associations and it allows the placement in a functional context of some unknown non-assigned genes based on their interactions with known gene families. [Conclusions/Significance]: The identification of stable and reliable human gene to gene coexpression networks is essential to unravel the interactions and functional correlations between human genes at an omic scale. This work contributes to this aim, and we are making available for the scientific community the validated human gene coexpression networks obtained, to allow further analyses on the network or on some specific gene associations. The data are available free online at http://bioinfow.dep.usal.es/coexpression/. © 2008 Prieto et al.Funding and grant support was provided by the Ministery of Health, Spanish Government (ISCiii-FIS, MSyC; Project reference PI061153) and by the Ministery of Education, Castilla-Leon Local Government (JCyL; Project reference CSI03A06).Peer Reviewe

Protein complex stoichiometry and expression dynamics of transcription factors modulate stem cell division

11 Pág.Stem cells divide and differentiate to form all of the specialized cell types in a multicellular organism. In the Arabidopsis root, stem cells are maintained in an undifferentiated state by a less mitotically active population of cells called the quiescent center (QC). Determining how the QC regulates the surrounding stem cell initials, or what makes the QC fundamentally different from the actively dividing initials, is important for understanding how stem cell divisions are maintained. Here we gained insight into the differences between the QC and the cortex endodermis initials (CEI) by studying the mobile transcription factor SHORTROOT (SHR) and its binding partner SCARECROW (SCR). We constructed an ordinary differential equation model of SHR and SCR in the QC and CEI which incorporated the stoichiometry of the SHR-SCR complex as well as upstream transcriptional regulation of SHR and SCR. Our model prediction, coupled with experimental validation, showed that high levels of the SHR-SCR complex are associated with more CEI division but less QC division. Furthermore, our model prediction allowed us to propose the putative upstream SHR regulators SEUSS and WUSCHEL-RELATED HOMEOBOX 5 and to experimentally validate their roles in QC and CEI division. In addition, our model established the timing of QC and CEI division and suggests that SHR repression of QC division depends on formation of the SHR homodimer. Thus, our results support that SHR-SCR protein complex stoichiometry and regulation of SHR transcription modulate the division timing of two different specialized cell types in the root stem cell niche.This work was supported by the NSF Graduate Research Fellowship Program (DGE-1252376, to N.M.C. and A.P.F.). Research in the R. Simon lab was funded by the Deutsche Forschungsge-meinschaft (Si947/10 and an Alexander von Humboldt Foundation fellowship, to B.B.). This work was also supported by a grant from the Ministerio de Economía y Competitividad of Spain and European Regional Development Fund (BFU2016-80315-P, to M.A.M.-R.). E.B.A. is supported by Ayudante de Investigacion contract PEJ-2017-AI/BIO-7360 from Comunidad Madrid. S.G.Z. was supported by the HHMI and by a grant from the NIH (GM118036). Research in the K.L.G. lab was funded by NSF Grant 1243945. The R. Sozzani lab is supported by an NSF CAREER grant (MCB-1453130) and the North Carolina Agricultural & Life Sciences Research Foundation at North Carolina State University’s College of Agricultural and Life Sciences.Peer reviewe

mRNA accumulation in the Cajal bodies of the diplotene larch microsporocyte

In microsporocytes of the European larch, we demonstrated the presence of several mRNAs in spherical nuclear bodies. In the nuclei of microsporocytes, we observed up to 12 bodies, ranging from 0.5 to 6 μm in diameter, during the prophase of the first meiotic division. Our previous studies revealed the presence of polyadenylated RNA (poly(A) RNA) in these bodies, but did not confirm the presence of nascent transcripts or splicing factors of the SR family. The lack of these molecules precludes the bodies from being the sites of synthesis and early maturation of primary transcripts (Kołowerzo et al., Protoplasma 236:13–19, 2009). However, the bodies serve as sites for the accumulation of splicing machinery, including the Sm proteins and small nuclear RNAs. Characteristic ultrastructures and the molecular composition of the nuclear bodies, which contain poly(A) RNA, are indicative of Cajal bodies (CBs). Here, we demonstrated the presence of several housekeeping gene transcripts—α-tubulin, pectin methylesterase, peroxidase and catalase, ATPase, and inositol-3-phosphate synthase—in CBs. Additionally, we observed transcripts of the RNA polymerase II subunits RPB2 and RPB10 RNA pol II and the core spliceosome proteins mRNA SmD1, SmD2, and SmE. The co-localization of nascent transcripts and mRNAs indicates that mRNA accumulation/storage, particularly in CBs, occurs in the nucleus of microsporocytes