Neck Flexion Induces Larger Deformation of the Brain Than Extension at a Rotational Acceleration, Closed Head Trauma

A closed head trauma induces incompletely characterized temporary movement and deformation of the brain, contributing to the primary traumatic brain injury. We used the pressure patterns recorded with light-operated miniature sensors in anaesthetized adult rabbits exposed to a sagittal plane rotational acceleration of the head, lasting 1 ms, as a measure of brain deformation. Two exposure levels were used and scaled to correspond to force levels reported to cause mild and moderate diffuse injury in an adult man, respectively. Flexion induced transient, strong, extended, and predominantly negative pressures while extension generated a short positive pressure peak followed by a minor negative peak. Low level flexion caused as strong, extended negative pressures as did high level extension. Time differences were demonstrated between the deformation of the cerebrum, brainstem, and cerebellum. Available X-ray and MRI techniques do not have as high time resolution as pressure recordings in demonstrating complex, sequential compression and stretching of the brain during a trauma. The exposure to flexion caused more protracted and extensive deformation of the brain than extension, in agreement with a published histopathological report. The severity and extent of the brain deformation generated at a head trauma thus related to the direction at equal force

Tumor Genome Wide DNA Alterations Assessed by Array CGH in Patients with Poor and Excellent Survival Following Operation for Colorectal Cancer

Genome wide DNA alterations were evaluated by array CGH in addition to RNA expression profiling in colorectal cancer from patients with excellent and poor survival following primary operations

Genes with Relevance for Early to Late Progression of Colon Carcinoma Based on Combined Genomic and Transcriptomic Information from the Same Patients

Background: Genetic and epigenetic alterations in colorectal cancer are numerous. However, it is difficult to judge whether such changes are primary or secondary to the appearance and progression of tumors. Therefore, the aim of the present study was to identify altered DNA regions with significant covariation to transcription alterations along colon cancer progression. Methods: Tumor and normal colon tissue were obtained at primary operations from 24 patients selected by chance. DNA, RNA and microRNAs were extracted from the same biopsy material in all individuals and analyzed by oligo-nucleotide array-based comparative genomic hybridization (CGH), mRNA- and microRNA oligo-arrays. Statistical analyses were performed to assess statistical interactions (correlations, co-variations) between DNA copy number changes and significant alterations in gene and microRNA expression using appropriate parametric and non-parametric statistics. Results: Main DNA alterations were located on chromosome 7, 8, 13 and 20. Tumor DNA copy number gain increased with tumor progression, significantly related to increased gene expression. Copy number loss was not observed in Dukes A tumors. There was no significant relationship between expressed genes and tumor progression across Dukes A–D tumors; and no relationship between tumor stage and the number of microRNAs with significantly altered expression. Interaction analyses identified overall 41 genes, which discriminated early Dukes A plus B tumors from late Dukes C plus D tumor; 28 of these genes remained with correlations between genomic and transcriptomic alterations in Dukes C plus D tumors and 17 in Dukes D. One microRNA (microR-663) showed interactions with DNA alterations in all Dukes A-D tumors. Conclusions: Our modeling confirms that colon cancer progression is related to genomic instability and altered gene expression. How- ever, early invasive tumor growth seemed rather related to transcriptomic alterations, where changes in microRNA may be an early phenomenon, and less to DNA copy number changes

Genetically modified (GM) late blight-resistant potato and consumer attitudes before and after a field visit

Late blight, caused by Phytophthora infestans, is the most devastating disease in potato production. Here, we show full late blight resistance in a location with a genetically diverse pathogen population with the use of GM potato stacked with three resistance (R) genes over three seasons. In addition, using this field trials, we demonstrate that in-the-field intervention among consumers led to change for more favorable attitude generally toward GM crops

Exceptional evolutionary divergence of human muscle and brain metabolomes parallels human cognitive and physical uniqueness

Metabolite concentrations reflect the physiological states of tissues and cells. However, the role of metabolic changes in species evolution is currently unknown. Here, we present a study of metabolome evolution conducted in three brain regions and two non-neural tissues from humans, chimpanzees, macaque monkeys, and mice based on over 10,000 hydrophilic compounds. While chimpanzee, macaque, and mouse metabolomes diverge following the genetic distances among species, we detect remarkable acceleration of metabolome evolution in human prefrontal cortex and skeletal muscle affecting neural and energy metabolism pathways. These metabolic changes could not be attributed to environmental conditions and were confirmed against the expression of their corresponding enzymes. We further conducted muscle strength tests in humans, chimpanzees, and macaques. The results suggest that, while humans are characterized by superior cognition, their muscular performance might be markedly inferior to that of chimpanzees and macaque monkeys.Publisher PDFPeer reviewe

High-throughput muscle fiber typing from RNA sequencing data

Background: Skeletal muscle fiber type distribution has implications for human health, muscle function, and performance. This knowledge has been gathered using labor-intensive and costly methodology that limited these studies. Here, we present a method based on muscle tissue RNA sequencing data (totRNAseq) to estimate the distribution of skeletal muscle fiber types from frozen human samples, allowing for a larger number of individuals to be tested. Methods: By using single-nuclei RNA sequencing (snRNAseq) data as a reference, cluster expression signatures were produced by averaging gene expression of cluster gene markers and then applying these to totRNAseq data and inferring muscle fiber nuclei type via linear matrix decomposition. This estimate was then compared with fiber type distribution measured by ATPase staining or myosin heavy chain protein isoform distribution of 62 muscle samples in two independent cohorts (n = 39 and 22). Results: The correlation between the sequencing-based method and the other two were r(ATpas) = 0.44 [0.13-0.67], [95% CI], and r(myosin) = 0.83 [0.61-0.93], with p = 5.70 x 10(-3) and 2.00 x 10(-6), respectively. The deconvolution inference of fiber type composition was accurate even for very low totRNAseq sequencing depths, i.e., down to an average of similar to 10,000 paired-end reads. Conclusions: This new method (https://github.com/OlaHanssonLab/PredictFiberType) consequently allows for measurement of fiber type distribution of a larger number of samples using totRNAseq in a cost and labor-efficient way. It is now feasible to study the association between fiber type distribution and e.g. health outcomes in large well-powered studies.Peer reviewe

High-throughput muscle fiber typing from RNA sequencing data

Background Skeletal muscle fiber type distribution has implications for human health, muscle function, and performance. This knowledge has been gathered using labor-intensive and costly methodology that limited these studies. Here, we present a method based on muscle tissue RNA sequencing data (totRNAseq) to estimate the distribution of skeletal muscle fiber types from frozen human samples, allowing for a larger number of individuals to be tested. Methods By using single-nuclei RNA sequencing (snRNAseq) data as a reference, cluster expression signatures were produced by averaging gene expression of cluster gene markers and then applying these to totRNAseq data and inferring muscle fiber nuclei type via linear matrix decomposition. This estimate was then compared with fiber type distribution measured by ATPase staining or myosin heavy chain protein isoform distribution of 62 muscle samples in two independent cohorts (n = 39 and 22). Results The correlation between the sequencing-based method and the other two were rATPas = 0.44 [0.13–0.67], [95% CI], and rmyosin = 0.83 [0.61–0.93], with p = 5.70 × 10–3 and 2.00 × 10–6, respectively. The deconvolution inference of fiber type composition was accurate even for very low totRNAseq sequencing depths, i.e., down to an average of ~ 10,000 paired-end reads. Conclusions This new method (https://github.com/OlaHanssonLab/PredictFiberType) consequently allows for measurement of fiber type distribution of a larger number of samples using totRNAseq in a cost and labor-efficient way. It is now feasible to study the association between fiber type distribution and e.g. health outcomes in large well-powered studies.journal articl

Sven Lidman: Silfverstååhl i den judiska finansvärlden

Sven Lidman was a Swedish author who had a great interest in the industrialization and financial growth in Sweden. In his novel Köpmän och krigare (1911) the noble family Silfverstååhl encounter what Lidman calls “the Jewish finance world”. The response to his work was of mixed character, including response of anti-Semitic character

Sven Lidman: Silfverstååhl i den judiska finansvärlden

Sven Lidman was a Swedish author who had a great interest in the industrialization and financial growth in Sweden. In his novel Köpmän och krigare (1911) the noble family Silfverstååhl encounter what Lidman calls “the Jewish finance world”. The response to his work was of mixed character, including response of anti-Semitic character