1,674 research outputs found
An anaphase surveillance mechanism prevents micronuclei formation from frequent chromosome segregation errors
Micronuclei are a hallmark of cancer and several other human disorders. Recently, micronuclei were implicated in chromothripsis, a series of massive genomic rearrangements that may drive tumor evolution and progression. Here, we show that Aurora B kinase mediates a surveillance mechanism that integrates error correction during anaphase with spatial control of nuclear envelope reassembly to prevent micronuclei formation. Using high-resolution live-cell imaging of human cancer and non-cancer cells, we uncover that anaphase lagging chromosomes are more frequent than previously anticipated, yet they rarely form micronuclei. Micronuclei formation from anaphase lagging chromosomes is prevented by a midzone-based Aurora B phosphorylation gradient that stabilizes kinetochore-microtubule attachments and assists spindle forces required for anaphase error correction while delaying nuclear envelope reassembly on lagging chromosomes, independently of microtubule density. We propose that a midzone-based Aurora B phosphorylation gradient actively monitors and corrects frequent chromosome segregation errors to prevent micronuclei formation during human cell division.We thank António Pereira and Ana Almeida for assistance with CH-STED, Ariana Jacome for the generation of lentiviral vectors, Cristina Ferrás and Marco Novais-Cruz for drawing attention to the effects of nocodazole treatment and washout on the Aurora B phosphorylation gradient, current and former lab members for suggestions, and Jonathan Higgins and Andrew McAinsh for discussing results prior to publication. This work was funded by the European Research Council (ERC) consolidator grant CODECHECK , under the European Union’s Horizon 2020 research and innovation programme (grant agreement 681443 ), and Fundação para a Ciência e a Tecnologia of Portugal ( PTDC/MED-ONC/3479/2020 )
The identification of informative genes from multiple datasets with increasing complexity
Background
In microarray data analysis, factors such as data quality, biological variation, and the increasingly multi-layered nature of more complex biological systems complicates the modelling of regulatory networks that can represent and capture the interactions among genes. We believe that the use of multiple datasets derived from related biological systems leads to more robust models. Therefore, we developed a novel framework for modelling regulatory networks that involves training and evaluation on independent datasets. Our approach includes the following steps: (1) ordering the datasets based on their level of noise and informativeness; (2) selection of a Bayesian classifier with an appropriate level of complexity by evaluation of predictive performance on independent data sets; (3) comparing the different gene selections and the influence of increasing the model complexity; (4) functional analysis of the informative genes.
Results
In this paper, we identify the most appropriate model complexity using cross-validation and independent test set validation for predicting gene expression in three published datasets related to myogenesis and muscle differentiation. Furthermore, we demonstrate that models trained on simpler datasets can be used to identify interactions among genes and select the most informative. We also show that these models can explain the myogenesis-related genes (genes of interest) significantly better than others (P < 0.004) since the improvement in their rankings is much more pronounced. Finally, after further evaluating our results on synthetic datasets, we show that our approach outperforms a concordance method by Lai et al. in identifying informative genes from multiple datasets with increasing complexity whilst additionally modelling the interaction between genes.
Conclusions
We show that Bayesian networks derived from simpler controlled systems have better performance than those trained on datasets from more complex biological systems. Further, we present that highly predictive and consistent genes, from the pool of differentially expressed genes, across independent datasets are more likely to be fundamentally involved in the biological process under study. We conclude that networks trained on simpler controlled systems, such as in vitro experiments, can be used to model and capture interactions among genes in more complex datasets, such as in vivo experiments, where these interactions would otherwise be concealed by a multitude of other ongoing events
The knowledge and expectations of parents about the role of antibiotic treatment in upper respiratory tract infection – a survey among parents attending the primary physician with their sick child
BACKGROUND: Upper respiratory tract infections (URTI) are common. The etiologic factor is usually viral, but many physicians prescribe antibiotics. We aimed to evaluate parents' expectations of and knowledge about the role of antibiotics in childhood URTI. METHODS: The study was conducted in thirteen primary care pediatric clinics. Parents of children aged 3 months to 6 years who attended with URTI symptoms were included when it was the first attendance in the current illness. Questionnaire about the current illness, reasons for attending and expectations from the visit, knowledge about URTI was filled before the visit. RESULTS: In 122 visits the average age was 2.8 ± 1.9 years. The main reasons for the visit were to avoid complications (81%) and to be examined (78%). Expected treatment was: cough suppressants (64%), anti-congestants (57%), paracetamol (56%), natural remedies (53%) and antibiotics (25%). In 28% the child had received antibiotics in past URTI. Only 37% thought that antibiotics would not help in URTI and 27% knew that URTI is a self-limited disease. 61% knew that URTI is a viral disease. Younger parental age and higher education were associated with lower expectations to receive antibiotics (p = 0.01, p < 0.005 respectively). While previous antibiotic treatment (p < 0.001), past perceived complications (p = 0.05) and the thought that antibiotics help in URTI (p < 0.001) were associated with a greater expectation for antibiotics. CONCLUSIONS: A quarter of the parents attending the physician with URTI are expecting to get antibiotics. Predictors were lower education, older parental age, receiving antibiotics in the past and the belief that antibiotics help in URTI
Quantifying the Adaptive Potential of an Antibiotic Resistance Enzyme
For a quantitative understanding of the process of adaptation, we need to understand its “raw material,” that is, the frequency and fitness effects of beneficial mutations. At present, most empirical evidence suggests an exponential distribution of fitness effects of beneficial mutations, as predicted for Gumbel-domain distributions by extreme value theory. Here, we study the distribution of mutation effects on cefotaxime (Ctx) resistance and fitness of 48 unique beneficial mutations in the bacterial enzyme TEM-1 β-lactamase, which were obtained by screening the products of random mutagenesis for increased Ctx resistance. Our contributions are threefold. First, based on the frequency of unique mutations among more than 300 sequenced isolates and correcting for mutation bias, we conservatively estimate that the total number of first-step mutations that increase Ctx resistance in this enzyme is 87 [95% CI 75–189], or 3.4% of all 2,583 possible base-pair substitutions. Of the 48 mutations, 10 are synonymous and the majority of the 38 non-synonymous mutations occur in the pocket surrounding the catalytic site. Second, we estimate the effects of the mutations on Ctx resistance by determining survival at various Ctx concentrations, and we derive their fitness effects by modeling reproduction and survival as a branching process. Third, we find that the distribution of both measures follows a Fréchet-type distribution characterized by a broad tail of a few exceptionally fit mutants. Such distributions have fundamental evolutionary implications, including an increased predictability of evolution, and may provide a partial explanation for recent observations of striking parallel evolution of antibiotic resistance
Male breast cancer
Male breast cancer (MBC) is a rare disease representing less than 1% of all breast cancers (BC) and less than 1% of cancers in men. Age at presentation is mostly in the late 60s. MBC is recognized as an estrogen-driven disease, specifically related to hyperestrogenism. About 20% of MBC patients have family history for BC. Mutations in BRCA1 and, predominantly, BRCA2, account for approximately 10% of MBC cases.
Because of its rarity, MBC is often compared with female BC (FBC). Based on age-frequency distribution, age-specific incidence rate patterns and prognostic factors profiles, MBC is considered similar to late-onset, postmenopausal estrogen/progesterone receptor positive (ER+/PR+) FBC. However, clinical and pathological characteristics of MBC do not exactly overlap FBC. Compared with FBC, MBC has been reported to occur later in life, present at a higher stage, and display lower histologic grade, with a higher proportion of ER+ and PR+ tumors.
Although rare, MBC remains a substantial cause for morbidity and mortality in men, probably because of its occurrence in advanced age and delayed diagnosis. Diagnosis and treatment of MBC generally is similar to that of FBC. Men tend to be treated with mastectomy rather than breast-conserving surgery. The backbone of adjuvant therapy or palliative treatment for advanced disease is endocrine, mostly tamoxifen.
Use of FBC-based therapy led to the observation that treatment outcomes for MBC are worse and that survival rates for MBC do not improve like FBC. These different outcomes may suggest a non-appropriate utilization of treatments and that different underlying pathogenetic mechanisms may exist between male and female BC
X-ray Absorption and Reflection in Active Galactic Nuclei
X-ray spectroscopy offers an opportunity to study the complex mixture of
emitting and absorbing components in the circumnuclear regions of active
galactic nuclei, and to learn about the accretion process that fuels AGN and
the feedback of material to their host galaxies. We describe the spectral
signatures that may be studied and review the X-ray spectra and spectral
variability of active galaxies, concentrating on progress from recent Chandra,
XMM-Newton and Suzaku data for local type 1 AGN. We describe the evidence for
absorption covering a wide range of column densities, ionization and dynamics,
and discuss the growing evidence for partial-covering absorption from data at
energies > 10 keV. Such absorption can also explain the observed X-ray spectral
curvature and variability in AGN at lower energies and is likely an important
factor in shaping the observed properties of this class of source.
Consideration of self-consistent models for local AGN indicates that X-ray
spectra likely comprise a combination of absorption and reflection effects from
material originating within a few light days of the black hole as well as on
larger scales. It is likely that AGN X-ray spectra may be strongly affected by
the presence of disk-wind outflows that are expected in systems with high
accretion rates, and we describe models that attempt to predict the effects of
radiative transfer through such winds, and discuss the prospects for new data
to test and address these ideas.Comment: Accepted for publication in the Astronomy and Astrophysics Review. 58
pages, 9 figures. V2 has fixed an error in footnote
Translational, rotational and vibrational relaxation dynamics of a solute molecule in a non-interacting solvent
Neuroinflammation, Mast Cells, and Glia: Dangerous Liaisons
The perspective of neuroinflammation as an epiphenomenon following neuron damage is being replaced by the awareness of glia and their importance in neural functions and disorders. Systemic inflammation generates signals that communicate with the brain and leads to changes in metabolism and behavior, with microglia assuming a pro-inflammatory phenotype. Identification of potential peripheral-to-central cellular links is thus a critical step in designing effective therapeutics. Mast cells may fulfill such a role. These resident immune cells are found close to and within peripheral nerves and in brain parenchyma/meninges, where they exercise a key role in orchestrating the inflammatory process from initiation through chronic activation. Mast cells and glia engage in crosstalk that contributes to accelerate disease progression; such interactions become exaggerated with aging and increased cell sensitivity to stress. Emerging evidence for oligodendrocytes, independent of myelin and support of axonal integrity, points to their having strong immune functions, innate immune receptor expression, and production/response to chemokines and cytokines that modulate immune responses in the central nervous system while engaging in crosstalk with microglia and astrocytes. In this review, we summarize the findings related to our understanding of the biology and cellular signaling mechanisms of neuroinflammation, with emphasis on mast cell-glia interactions
Genetic Variants at Chromosomes 2q35, 5p12, 6q25.1, 10q26.13, and 16q12.1 Influence the Risk of Breast Cancer in Men
Male breast cancer accounts for approximately 1% of all breast cancer. To date, risk factors for male breast cancer are poorly defined, but certain risk factors and genetic features appear common to both male and female breast cancer. Genome-wide association studies (GWAS) have recently identified common single nucleotide polymorphisms (SNPs) that influence female breast cancer risk; 12 of these have been independently replicated. To examine if these variants contribute to male breast cancer risk, we genotyped 433 male breast cancer cases and 1,569 controls. Five SNPs showed a statistically significant association with male breast cancer: rs13387042 (2q35) (odds ratio (OR) = 1.30, p = 7.98×10−4), rs10941679 (5p12) (OR = 1.26, p = 0.007), rs9383938 (6q25.1) (OR = 1.39, p = 0.004), rs2981579 (FGFR2) (OR = 1.18, p = 0.03), and rs3803662 (TOX3) (OR = 1.48, p = 4.04×10−6). Comparing the ORs for male breast cancer with the published ORs for female breast cancer, three SNPs—rs13387042 (2q35), rs3803662 (TOX3), and rs6504950 (COX11)—showed significant differences in ORs (p<0.05) between sexes. Breast cancer is a heterogeneous disease; the relative risks associated with loci identified to date show subtype and, based on these data, gender specificity. Additional studies of well-defined patient subgroups could provide further insight into the biological basis of breast cancer development
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