The Gaggle: An open-source software system for integrating bioinformatics software and data sources

BACKGROUND: Systems biologists work with many kinds of data, from many different sources, using a variety of software tools. Each of these tools typically excels at one type of analysis, such as of microarrays, of metabolic networks and of predicted protein structure. A crucial challenge is to combine the capabilities of these (and other forthcoming) data resources and tools to create a data exploration and analysis environment that does justice to the variety and complexity of systems biology data sets. A solution to this problem should recognize that data types, formats and software in this high throughput age of biology are constantly changing. RESULTS: In this paper we describe the Gaggle -a simple, open-source Java software environment that helps to solve the problem of software and database integration. Guided by the classic software engineering strategy of separation of concerns and a policy of semantic flexibility, it integrates existing popular programs and web resources into a user-friendly, easily-extended environment. We demonstrate that four simple data types (names, matrices, networks, and associative arrays) are sufficient to bring together diverse databases and software. We highlight some capabilities of the Gaggle with an exploration of Helicobacter pylori pathogenesis genes, in which we identify a putative ricin-like protein -a discovery made possible by simultaneous data exploration using a wide range of publicly available data and a variety of popular bioinformatics software tools. CONCLUSION: We have integrated diverse databases (for example, KEGG, BioCyc, String) and software (Cytoscape, DataMatrixViewer, R statistical environment, and TIGR Microarray Expression Viewer). Through this loose coupling of diverse software and databases the Gaggle enables simultaneous exploration of experimental data (mRNA and protein abundance, protein-protein and protein-DNA interactions), functional associations (operon, chromosomal proximity, phylogenetic pattern), metabolic pathways (KEGG) and Pubmed abstracts (STRING web resource), creating an exploratory environment useful to 'web browser and spreadsheet biologists', to statistically savvy computational biologists, and those in between. The Gaggle uses Java RMI and Java Web Start technologies and can be found at

Longitudinal evaluation of cognitive functioning in young children with type 1 diabetes over 18 months

OBJECTIVE: Decrements in cognitive function may already be evident in young children with type 1 diabetes (T1D). Here we report prospectively acquired cognitive results over 18 months in a large cohort of young children with and without T1D. METHODS: 144 children with T1D (mean HbA1c: 7.9%) and 70 age-matched healthy controls (mean age both groups 8.5 years; median diabetes duration 3.9 yrs; mean age of onset 4.1 yrs) underwent neuropsychological testing at baseline and after 18-months of follow-up. We hypothesized that group differences observed at baseline would be more pronounced after 18 months, particularly in those T1D patients with greatest exposure to glycemic extremes. RESULTS: Cognitive domain scores did not differ between groups at the 18 month testing session and did not change differently between groups over the follow-up period. However, within the T1D group, a history of diabetic ketoacidosis (DKA) was correlated with lower Verbal IQ and greater hyperglycemia exposure (HbA1c area under the curve) was inversely correlated to executive functions test performance. In addition, those with a history of both types of exposure performed most poorly on measures of executive function. CONCLUSIONS: The subtle cognitive differences between T1D children and nondiabetic controls observed at baseline were not observed 18 months later. Within the T1D group, as at baseline, relationships between cognition (VIQ and executive functions) and glycemic variables (chronic hyperglycemia and DKA history) were evident. Continued longitudinal study of this T1D cohort and their carefully matched healthy comparison group is planned

The Inferelator: an algorithm for learning parsimonious regulatory networks from systems-biology data sets de novo

We present a method (the Inferelator) for deriving genome-wide transcriptional regulatory interactions, and apply the method to predict a large portion of the regulatory network of the archaeon Halobacterium NRC-1. The Inferelator uses regression and variable selection to identify transcriptional influences on genes based on the integration of genome annotation and expression data. The learned network successfully predicted Halobacterium's global expression under novel perturbations with predictive power similar to that seen over training data. Several specific regulatory predictions were experimentally tested and verified

Seafloor warm water temperature anomalies impact benthic macrofauna communities of a high-Arctic cold-water fjord

Amid the alarming atmospheric and oceanic warming rates taking place in the Arctic, western fjords around the Svalbard archipelago are experiencing an increased frequency of warm water intrusions in recent decades, causing ecological shifts in their ecosystems. However, hardly anything is known about their potential impacts on the until recently considered stable and colder northern fjords. We analyzed macrobenthic fauna from four locations in Rijpfjorden (a high-Arctic fjord in the north of Svalbard) along its axis, sampled intermittently in the years 2003, 2007, 2010, 2013 and 2017. After a strong seafloor warm water temperature anomaly (SfWWTA) in 2006, the abundance of individuals and species richness dropped significantly across the entire fjord in 2007, together with diversity declines at the outer parts (reflected in Shannon index drops) and increases in beta diversity between inner and outer parts of the fjord. After a period of three years with stable water temperatures and higher sea-ice cover, communities recovered through recolonization processes by 2010, leading to homogenization in community composition across the fjord and less beta diversity. For the last two periods (2010-2013 and 2013-2017), beta diversity between the inner and outer parts gradually increased again, and both the inner and outer sites started to re-assemble in different directions. A few taxa began to dominate the fjord from 2010 onwards at the outer parts, translating into evenness and diversity drops. The inner basin, however, although experiencing strong shifts in abundances, was partially protected by a fjordic sill from impacts of these temperature anomalies and remained comparatively more stable regarding community diversity after the disturbance event. Our results indicate that although shifts in abundances were behind important spatio-temporal community fluctuations, beta diversity variations were also driven by the occurrence-based macrofauna data, suggesting an important role of rare taxa. This is the first multidecadal time series of soft-bottom macrobenthic communities for a high-Arctic fjord, indicating that potential periodic marine heatwaves might drive shifts in community structure, either through direct effects from thermal stress on the communities or through changes in environmental regimes led by temperature fluctuations (i.e. sea ice cover and glacial runoff, which could lead to shifts in primary production and food supply to the benthos). Although high-Arctic macrobenthic communities might be resilient to some extent, sustained warm water anomalies could lead to permanent changes in cold-water fjordic benthic systems

Dark resonances as a probe for the motional state of a single ion

Single, rf-trapped ions find various applications ranging from metrology to quantum computation. High-resolution interrogation of an extremely weak transition under best observation conditions requires an ion almost at rest. To avoid line-broadening effects such as the second order Doppler effect or rf heating in the absence of laser cooling, excess micromotion has to be eliminated as far as possible. In this work the motional state of a confined three-level ion is probed, taking advantage of the high sensitivity of observed dark resonances to the trapped ion's velocity. Excess micromotion is controlled by monitoring the dark resonance contrast with varying laser beam geometry. The influence of different parameters such as the cooling laser intensity has been investigated experimentally and numerically

Competing pairing interactions responsible for the large upper critical field in a stoichiometric iron-based superconductor, CaKFe4_4As4_4

The upper critical field of multiband superconductors is an important quantity that can reveal the details about the nature of the superconducting pairing. Here we experimentally map out the complete upper critical field phase diagram of a stoichiometric superconductor, CaKFe$_4$As$_4$, up to 90T for different orientations of the magnetic field and at temperatures down to 4.2K. The upper critical fields are extremely large, reaching values close to ~3$T_c$ at the lowest temperature, and the anisotropy decreases dramatically with temperature leading to essentially isotropic superconductivity at 4.2K. We find that the temperature dependence of the upper critical field can be well described by a two-band model in the clean limit with band coupling parameters favouring intraband over interband interactions. The large Pauli paramagnetic effects together with the presence of the shallow bands is consistent with the stabilization of an FFLO state at low temperatures in this clean superconductor.Comment: to appear in Physical Review B (2020); 13 pages, 9 figure

The development and validation of a cerebral ultrasound scoring system for infants with hypoxic-ischaemic encephalopathy

BACKGROUND: Hypoxic-ischaemic encephalopathy (HIE) is an important cause of morbidity and mortality in neonates. When the gold standard MRI is not feasible, cerebral ultrasound (CUS) might offer an alternative. In this study, the association between a novel CUS scoring system and neurodevelopmental outcome in neonates with HIE was assessed. METHODS: (Near-)term infants with HIE and therapeutic hypothermia, a CUS on day 1 and day 3-7 after birth and available outcome data were retrospectively included in cohort I. CUS findings on day 1 and day 3-7 were related to adverse outcome in univariate and the CUS of day 3-7 also in multivariable logistic regression analyses. The resistance index, the sum of deep grey matter and of white matter involvement were included in multivariable logistic regression analyses. A comparable cohort from another hospital was used for validation (cohort II). RESULTS: Eighty-three infants were included in cohort I and 35 in cohort II. The final CUS scoring system contained the sum of white matter (OR = 2.6, 95% CI 1.5-4.7) and deep grey matter involvement (OR = 2.7, 95% CI 1.7-4.4). The CUS scoring system performed well in cohort I (AUC = 0.90) and II (AUC = 0.89). CONCLUSION: This validated CUS scoring system is associated with neurodevelopmental outcome in neonates with HIE

APOLLO: A randomized phase II double-blind study of olaparib versus placebo following curative intent therapy in patients with resected pancreatic cancer and a pathogenic BRCA1, BRCA2 or PALB2 mutation-ECOG-ACRIN EA2192

Background: A meaningful subset of PDAC is characterized by a homologous recombination deficiency (HRD). The most well-defined patients within this group are those with pathogenic variants in BRCA1, BRCA2 and PALB2. In the metastatic setting, PARP inhibitor maintenance provides a progression-free survival benefit after a period of platinum based chemotherapy1,2, but the role of PARP inhibitors in the curative intent setting is undefined. The OlympiA study established one year of olaparib as the standard of care for patients with BRCA-related, early stage breast cancer who completed all other curative-intent treatment3. Therefore, we have designed a randomized, phase II double-blind study of one year of olaparib vs placebo in patients with pancreatic cancer and a germline or somatic variant in BRCA or PALB2 who have completed all curative intent therapy. Methods: We have enrolled and treated 23 of 152 planned patients on study NCT 04858334/EA2192. Eligibility criteria include: a pathogenic germline or somatic variant in BRCA1, BRCA2 or PALB2 as determined by local laboratory (central review required); completion of curative-intent resection and ≥ three months of multi-agent chemotherapy; no evidence of recurrent disease. At enrollment, patients must be within 12 weeks of their last anti-cancer intervention. Patients are randomized 2:1 to receive oral olaparib 300 mg twice daily or placebo for 12 28-day cycles. The primary endpoint is relapse-free survival. Overall survival is a secondary endpoint. Tumor tissue, fecal material (for microbiome analysis) and serial ctDNA samples are being collected

Cosmological parameter estimation using Very Small Array data out to l=1500

We estimate cosmological parameters using data obtained by the Very Small Array (VSA) in its extended configuration, in conjunction with a variety of other CMB data and external priors. Within the flat $\Lambda$CDM model, we find that the inclusion of high resolution data from the VSA modifies the limits on the cosmological parameters as compared to those suggested by WMAP alone, while still remaining compatible with their estimates. We find that $\Omega_{\rm b}h^2=0.0234^{+0.0012}_{-0.0014}$, $\Omega_{\rm dm}h^2=0.111^{+0.014}_{-0.016}$, $h=0.73^{+0.09}_{-0.05}$, $n_{\rm S}=0.97^{+0.06}_{-0.03}$, $10^{10}A_{\rm S}=23^{+7}_{-3}$ and $\tau=0.14^{+0.14}_{-0.07}$ for WMAP and VSA when no external prior is included.On extending the model to include a running spectral index of density fluctuations, we find that the inclusion of VSA data leads to a negative running at a level of more than 95% confidence ($n_{\rm run}=-0.069\pm 0.032$), something which is not significantly changed by the inclusion of a stringent prior on the Hubble constant. Inclusion of prior information from the 2dF galaxy redshift survey reduces the significance of the result by constraining the value of $\Omega_{\rm m}$. We discuss the veracity of this result in the context of various systematic effects and also a broken spectral index model. We also constrain the fraction of neutrinos and find that $f_{\nu}< 0.087$ at 95% confidence which corresponds to $m_\nu<0.32{\rm eV}$ when all neutrino masses are the equal. Finally, we consider the global best fit within a general cosmological model with 12 parameters and find consistency with other analyses available in the literature. The evidence for $n_{\rm run}<0$ is only marginal within this model