Significance Of The Behavior Of Sensitive Stigmas Ii.

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141143/1/ajb205763.pd

Behavior Of Plants In Unventilated Chambers

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142325/1/ajb205503.pd

Elastic cavitation, tube hollowing, and differential growth in plants and biological tissues

Elastic cavitation is a well-known physical process by which elastic materials under stress can open cavities. Usually, cavitation is induced by applied loads on the elastic body. However, growing materials may generate stresses in the absence of applied loads and could induce cavity opening. Here, we demonstrate the possibility of spontaneous growth-induced cavitation in elastic materials and consider the implications of this phenomenon to biological tissues and in particular to the problem of schizogenous aerenchyma formation

Neurite dispersion: a new marker of multiple sclerosis spinal cord pathology?

Objective: Conventional magnetic resonance imaging (MRI) of the multiple sclerosis spinal cord is limited by low specificity regarding the underlying pathological processes, and new MRI metrics assessing microscopic damage are required. We aim to show for the first time that neurite orientation dispersion (i.e., variability in axon/dendrite orientations) is a new biomarker that uncovers previously undetected layers of complexity of multiple sclerosis spinal cord pathology. Also, we validate against histology a clinically viable MRI technique for dispersion measurement (neurite orientation dispersion and density imaging,NODDI), to demonstrate the strong potential of the new marker. Methods: We related quantitative metrics from histology and MRI in four post mortem spinal cord specimens (two controls; two progressive multiple sclerosis cases). The samples were scanned at high field, obtaining maps of neurite density and orientation dispersion from NODDI and routine diffusion tensor imaging (DTI) indices. Histological procedures provided markers of astrocyte, microglia, myelin and neurofilament density, as well as neurite dispersion. Results: We report from both NODDI and histology a trend toward lower neurite dispersion in demyelinated lesions, indicative of reduced neurite architecture complexity. Also, we provide unequivocal evidence that NODDI-derived dispersion matches its histological counterpart (P < 0.001), while DTI metrics are less specific and influenced by several biophysical substrates. Interpretation: Neurite orientation dispersion detects a previously undescribed and potentially relevant layer of microstructural complexity of multiple sclerosis spinal cord pathology. Clinically feasible techniques such as NODDI may play a key role in clinical trial and practice settings, as they provide histologically meaningful dispersion indices

Two Years Later: Journals Are Not Yet Enforcing the ARRIVE Guidelines on Reporting Standards for Pre-Clinical Animal Studies

There is growing concern that poor experimental design and lack of transparent reporting contribute to the frequent failure of pre-clinical animal studies to translate into treatments for human disease. In 2010, the Animal Research: Reporting of In Vivo Experiments (ARRIVE) guidelines were introduced to help improve reporting standards. They were published in PLOS Biology and endorsed by funding agencies and publishers and their journals, including PLOS, Nature research journals, and other top-tier journals. Yet our analysis of papers published in PLOS and Nature journals indicates that there has been very little improvement in reporting standards since then. This suggests that authors, referees, and editors generally are ignoring guidelines, and the editorial endorsement is yet to be effectively implemented

Automatic localisation and per-region quantification of traumatic brain injury on head CT using atlas mapping

Rationale and objectives To develop a method for automatic localisation of brain lesions on head CT, suitable for both population-level analysis and lesion management in a clinical setting. Materials and methods Lesions were located by mapping a bespoke CT brain atlas to the patient’s head CT in which lesions had been previously segmented. The atlas mapping was achieved through robust intensity-based registration enabling the calculation of per-region lesion volumes. Quality control (QC) metrics were derived for automatic detection of failure cases. The CT brain template was built using 182 non-lesioned CT scans and an iterative template construction strategy. Individual brain regions in the CT template were defined via non-linear registration of an existing MRI-based brain atlas. Evaluation was performed on a multi-centre traumatic brain injury dataset (TBI) (n = 839 scans), including visual inspection by a trained expert. Two population-level analyses are presented as proof-of-concept: a spatial assessment of lesion prevalence, and an exploration of the distribution of lesion volume per brain region, stratified by clinical outcome. Results 95.7% of the lesion localisation results were rated by a trained expert as suitable for approximate anatomical correspondence between lesions and brain regions, and 72.5% for more quantitatively accurate estimates of regional lesion load. The classification performance of the automatic QC showed an AUC of 0.84 when compared to binarised visual inspection scores. The localisation method has been integrated into the publicly available Brain Lesion Analysis and Segmentation Tool for CT (BLAST-CT). Conclusion Automatic lesion localisation with reliable QC metrics is feasible and can be used for patient-level quantitative analysis of TBI, as well as for large-scale population analysis due to its computational efficiency (<2 min/scan on GPU)

Accuracy of dementia diagnosis—a direct comparison between radiologists and a computerized method

There has been recent interest in the application of machine learning techniques to neuroimaging-based diagnosis. These methods promise fully automated, standard PC-based clinical decisions, unbiased by variable radiological expertise. We recently used support vector machines (SVMs) to separate sporadic Alzheimer's disease from normal ageing and from fronto-temporal lobar degeneration (FTLD). In this study, we compare the results to those obtained by radiologists. A binary diagnostic classification was made by six radiologists with different levels of experience on the same scans and information that had been previously analysed with SVM. SVMs correctly classified 95% (sensitivity/specificity: 95/95) of sporadic Alzheimer's disease and controls into their respective groups. Radiologists correctly classified 65–95% (median 89%; sensitivity/specificity: 88/90) of scans. SVM correctly classified another set of sporadic Alzheimer's disease in 93% (sensitivity/specificity: 100/86) of cases, whereas radiologists ranged between 80% and 90% (median 83%; sensitivity/specificity: 80/85). SVMs were better at separating patients with sporadic Alzheimer's disease from those with FTLD (SVM 89%; sensitivity/specificity: 83/95; compared to radiological range from 63% to 83%; median 71%; sensitivity/specificity: 64/76). Radiologists were always accurate when they reported a high degree of diagnostic confidence. The results show that well-trained neuroradiologists classify typical Alzheimer's disease-associated scans comparable to SVMs. However, SVMs require no expert knowledge and trained SVMs can readily be exchanged between centres for use in diagnostic classification. These results are encouraging and indicate a role for computerized diagnostic methods in clinical practice

Systematic review of orogenital HIV-1 transmission probabilities

Background The objective was to assess the risk of HIV transmission from orogenital intercourse (OI)

Ipl1/aurora kinase suppresses S-CDK-driven spindle formation during prophase I to ensure chromosome integrity during meiosis

Cells coordinate spindle formation with DNA repair and morphological modifications to chromosomes prior to their segregation to prevent cell division with damaged chromosomes. Here we uncover a novel and unexpected role for Aurora kinase in preventing the formation of spindles by Clb5-CDK (S-CDK) during meiotic prophase I and when the DDR is active in budding yeast. This is critical since S-CDK is essential for replication during premeiotic S-phase as well as double-strand break induction that facilitates meiotic recombination and, ultimately, chromosome segregation. Furthermore, we find that depletion of Cdc5 polo kinase activity delays spindle formation in DDR-arrested cells and that ectopic expression of Cdc5 in prophase I enhances spindle formation, when Ipl1 is depleted. Our findings establish a new paradigm for Aurora kinase function in both negative and positive regulation of spindle dynamics