Observation of abundant heat production from a reactor device and of isotopic changes in the fuel

New results are presented from an extended experimental investigation of anomalous heat production in a special type of reactor tube operating at high temperatures. The reactor, named E-Cat, is charged with a small amount of hydrogen-loaded nickel powder plus some additives, mainly Lithium. The reaction is primarily initiated by heat from resistor coils around the reactor tube. Measurements of the radiated power from the reactor were performed with high-resolution thermal imaging cameras. The measurements of electrical power input were performed with a large bandwidth three-phase power analyzer. Data were collected during 32 days of running in March 2014. The reactor operating point was set to about 1260 ºC in the first half of the run, and at about 1400 °C in the second half. The measured energy balance between input and output heat yielded a COP factor of about 3.2 and 3.6 for the 1260 ºC and 1400 ºC runs, respectively . The total net energy obtained during the 32 days run was about 1.5 MWh. This amount of energy is far more than can be obtained from any known chemical sources in the small reactor volume. A sample of the fuel was carefully examined with respect to its isotopic composition before the run and after the run, using several standard methods: XPS, EDS, SIMS, ICP-MS and ICP-AES. The isotope composition in Lithium and Nickel was found to agree with the natural composition before the run, while after the run it was found to have changed substantially . Nuclear reactions are therefore indicated to be present in the run process, which however is hard to reconcile with the fact that no radioactivity was detected outside the reactor during the run

Pre-B cell to macrophage transdifferentiation without significant promoter DNA methylation changes

Transcription factor-induced lineage reprogramming or transdifferentiation experiments are essential for understanding the plasticity of differentiated cells. These experiments helped to define the specific role of transcription factors in conferring cell identity and played a key role in the development of the regenerative medicine field. We here investigated the acquisition of DNA methylation changes during C/EBPα-induced pre-B cell to macrophage transdifferentiation. Unexpectedly, cell lineage conversion occurred without significant changes in DNA methylation not only in key B cell- and macrophage-specific genes but also throughout the entire set of genes differentially methylated between the two parental cell types. In contrast, active and repressive histone modification marks changed according to the expression levels of these genes. We also demonstrated that C/EBPα and RNA Pol II are associated with the methylated promoters of macrophage-specific genes in reprogrammed macrophages without inducing methylation changes. Our findings not only provide insights about the extent and hierarchy of epigenetic events in pre-B cell to macrophage transdifferentiation but also show an important difference to reprogramming towards pluripotency where promoter DNA demethylation plays a pivotal role

Inferring causal molecular networks: empirical assessment through a community-based effort

Inferring molecular networks is a central challenge in computational biology. However, it has remained unclear whether causal, rather than merely correlational, relationships can be effectively inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge that focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results constitute the most comprehensive assessment of causal network inference in a mammalian setting carried out to date and suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess the causal validity of inferred molecular networks

Observation of Abundant Heat Production from a Reactor Device

ABSTRACT New results are presented from an extended experimental investigation of anomalous heat production in a special type of reactor tube operating at high temperatures. The reactor, named E-Cat, is charged with a small amount of hydrogen-loaded nickel powder plus some additives, mainly Lithium. The reaction is primarily initiated by heat from resistor coils around the reactor tube. Measurements of the radiated power from the reactor were performed with high-resolution thermal imaging cameras. The measurements of electrical power input were performed with a large bandwidth three-phase power analyzer. Data were collected during 32 days of running in March 2014. The reactor operating point was set to about 1260 ºC in the first half of the run, and at about 1400 °C in the second half. The measured energy balance between input and output heat yielded a COP factor of about 3.2 and 3.6 for the 1260 ºC and 1400 ºC runs, respectively. The total net energy obtained during the 32 days run was about 1.5 MWh. This amount of energy is far more than can be obtained from any known chemical sources in the small reactor volume. A sample of the fuel was carefully examined with respect to its isotopic composition before the run and after the run, using several standard methods: XPS, EDS, SIMS, ICP-MS and ICP-AES. The isotope composition in Lithium and Nickel was found to agree with the natural composition before the run, while after the run it was found to have changed substantially. Nuclear reactions are therefore indicated to be present in the run process, which however is hard to reconcile with the fact that no radioactivity was detected outside the reactor during the run

Observation of Abundant Heat Production from a Reactor Device

ABSTRACT New results are presented from an extended experimental investigation of anomalous heat production in a special type of reactor tube operating at high temperatures. The reactor, named E-Cat, is charged with a small amount of hydrogen-loaded nickel powder plus some additives, mainly Lithium. The reaction is primarily initiated by heat from resistor coils around the reactor tube. Measurements of the radiated power from the reactor were performed with high-resolution thermal imaging cameras. The measurements of electrical power input were performed with a large bandwidth three-phase power analyzer. Data were collected during 32 days of running in March 2014. The reactor operating point was set to about 1260 ºC in the first half of the run, and at about 1400 °C in the second half. The measured energy balance between input and output heat yielded a COP factor of about 3.2 and 3.6 for the 1260 ºC and 1400 ºC runs, respectively. The total net energy obtained during the 32 days run was about 1.5 MWh. This amount of energy is far more than can be obtained from any known chemical sources in the small reactor volume. A sample of the fuel was carefully examined with respect to its isotopic composition before the run and after the run, using several standard methods: XPS, EDS, SIMS, ICP-MS and ICP-AES. The isotope composition in Lithium and Nickel was found to agree with the natural composition before the run, while after the run it was found to have changed substantially. Nuclear reactions are therefore indicated to be present in the run process, which however is hard to reconcile with the fact that no radioactivity was detected outside the reactor during the run

Implementation of the CDC translational informatics platform - from genetic variants to the national Swedish Rheumatology Quality Register

Background Sequencing of the human genome and the subsequent analyses have produced immense volumes of data. The technological advances have opened new windows into genomics beyond the DNA sequence. In parallel, clinical practice generate large amounts of data. This represents an underused data source that has much greater potential in translational research than is currently realized. This research aims at implementing a translational medicine informatics platform to integrate clinical data (disease diagnosis, diseases activity and treatment) of Rheumatoid Arthritis (RA) patients from Karolinska University Hospital and their research database (biobanks, genotype variants and serology) at the Center for Molecular Medicine, Karolinska Institutet. Methods Requirements engineering methods were utilized to identify user requirements. Unified Modeling Language and data modeling methods were used to model the universe of discourse and data sources. Oracle11g were used as the database management system, and the clinical development center (CDC) was used as the application interface. Patient data were anonymized, and we employed authorization and security methods to protect the system. Results We developed a user requirement matrix, which provided a framework for evaluating three translation informatics systems. The implementation of the CDC successfully integrated biological research database (15172 DNA, serum and synovial samples, 1436 cell samples and 65 SNPs per patient) and clinical database (5652 clinical visit) for the cohort of 379 patients presents three profiles. Basic functionalities provided by the translational medicine platform are research data management, development of bioinformatics workflow and analysis, sub-cohort selection, and re-use of clinical data in research settings. Finally, the system allowed researchers to extract subsets of attributes from cohorts according to specific biological, clinical, or statistical features. Conclusions Research and clinical database integration is a real challenge and a road-block in translational research. Through this research we addressed the challenges and demonstrated the usefulness of CDC. We adhered to ethical regulations pertaining to patient data, and we determined that the existing software solutions cannot meet the translational research needs at hand. We used RA as a test case since we have ample data on active and longitudinal cohort