The axion particle may or may not exist, but the axion field can be used, as shown here, in an explicitly local formulation of a chiral U(1) gauge theory with both classical and quantum gauge ...invariance. Nonabelian analogues of axion fields, which have recently been introduced, can be used, together with their special symmetries, in a similar construction of nonabelian chiral gauge theories. As in known cases, the gauge symmetry is broken and the gauge boson acquires a mass by swallowing the axions which are therefore not physical in this construction.
Vertebrate brains of even moderate size are composed of astronomically large numbers of neurons and show a great degree of individual variability at the microscopic scale. This variation is ...presumably the result of phenotypic plasticity and individual experience. At a larger scale, however, relatively stable species-typical spatial patterns are observed in neuronal architecture, e.g., the spatial distributions of somata and axonal projection patterns, probably the result of a genetically encoded developmental program. The mesoscopic scale of analysis of brain architecture is the transitional point between a microscopic scale where individual variation is prominent and the macroscopic level where a stable, species-typical neural architecture is observed. The empirical existence of this scale, implicit in neuroanatomical atlases, combined with advances in computational resources, makes studying the circuit architecture of entire brains a practical task. A methodology has previously been proposed that employs a shotgun-like grid-based approach to systematically cover entire brain volumes with injections of neuronal tracers. This methodology is being employed to obtain mesoscale circuit maps in mouse and should be applicable to other vertebrate taxa. The resulting large data sets raise issues of data representation, analysis, and interpretation, which must be resolved. Even for data representation the challenges are nontrivial: the conventional approach using regional connectivity matrices fails to capture the collateral branching patterns of projection neurons. Future success of this promising research enterprise depends on the integration of previous neuroanatomical knowledge, partly through the development of suitable computational tools that encapsulate such expertise.
In this Perspective, Mitra describes the mesoscopic scale of analysis for brain architecture and discusses the opportunities for and challenges in defining principles of neural dynamics and function from mesoscale circuit maps.
It has recently been suggested that the attempt to understand Hawking radiation as tunnelling across black hole horizons produces a Hawking temperature double the standard value. It is explained here ...how one can obtain the standard value in the same tunnelling approach.
Chronux is an open-source software package developed for the analysis of neural data. The current version of Chronux includes software for signal processing of neural time-series data including ...several specialized mini-packages for spike-sorting, local regression, audio segmentation, and other data-analysis tasks typically encountered by a neuroscientist. Chronux is freely available along with user tutorials, sample data, and extensive documentation from
http://chronux.org/.
The biomedical sciences have recently undergone revolutionary change, due to the ability to digitize and store large data sets. In neuroscience, the data sources include measurements of neural ...activity measured using electrode arrays, EEG and MEG, brain imaging data from PET, fMRI, and optical imaging methods. Analysis, visualization, and management of these time series data sets is a growing field of research that has become increasingly important both for experimentalists and theorists interested in brain function. The first part of the book contains a set of chapters which provide non-technical conceptual background to the subject. Salient features include the adoption of an active perspective of the nervous system, an emphasis on function, and a brief survey of different theoretical accounts in neuroscience. The second part is the longest in the book, and contains a refresher course in mathematics and statistics leading up to time series analysis techniques. The third part contains applications of data analysis techniques to the range of data sources indicated above, and the fourth part contains special topics.
Purpose Enhanced recovery after surgery protocols aim to improve patient care and decrease complications and hospital stay. We evaluated our enhanced recovery after surgery protocol, focusing on ...length of stay, early complication and readmission rates after radical cystectomy for bladder cancer. Materials and Methods From May 2012 to July 2013 a perioperative protocol was applied in 126 consecutive patients who underwent open radical cystectomy and urinary diversion. Nonconsenting patients (2), those with previous diversion (2) and prolonged postoperative intubation (3), and those who underwent additional surgery (9) were excluded from study. The protocol focuses on avoiding bowel preparation and nasogastric tube, early feeding, nonnarcotic pain management and the use of cholinergic and μ-opioid antagonists. Outcomes were compared to those in matched controls from our bladder cancer database. Results A total of 110 patients with a median age of 69 years were included in analysis, of whom 68% underwent continent urinary diversion. Of the patients 82% had a bowel movement by postoperative day 2. Median length of stay was 4 days. The 30-day minor and major complication rates were 64% and 14%, respectively. The most common minor complication was anemia requiring transfusion in 19% of patients, urinary tract infection in 13% and dehydration in 10%. The latter 2 complications were the most common etiologies for readmission. The 30-day readmission rate was 21% (23 patients). Patients 75 years old or older had a longer length of stay (5 vs 4 days, p = 0.03) and a higher minor complication rate (72% vs 51%, p = 0.04) than younger patients. Conclusions Our enhanced recovery after surgery protocol expedites bowel function recovery and shortens hospital stay after RC and urinary diversion without an increase in the hospital readmission rates.
Our capacity to process and respond behaviourally to multiple incoming stimuli is very limited. To optimize the use of this limited capacity, attentional mechanisms give priority to behaviourally ...relevant stimuli at the expense of irrelevant distractors. In visual areas, attended stimuli induce enhanced responses and an improved synchronization of rhythmic neuronal activity in the gamma frequency band (40-70 Hz). Both effects probably improve the neuronal signalling of attended stimuli within and among brain areas. Attention also results in improved behavioural performance and shortened reaction times. However, it is not known how reaction times are related to either response strength or gamma-band synchronization in visual areas. Here we show that behavioural response times to a stimulus change can be predicted specifically by the degree of gamma-band synchronization among those neurons in monkey visual area V4 that are activated by the behaviourally relevant stimulus. When there are two visual stimuli and monkeys have to detect a change in one stimulus while ignoring the other, their reactions are fastest when the relevant stimulus induces strong gamma-band synchronization before and after the change in stimulus. This enhanced gamma-band synchronization is also followed by shorter neuronal response latencies on the fast trials. Conversely, the monkeys' reactions are slowest when gamma-band synchronization is high in response to the irrelevant distractor. Thus, enhanced neuronal gamma-band synchronization and shortened neuronal response latencies to an attended stimulus seem to have direct effects on visually triggered behaviour, reflecting an early neuronal correlate of efficient visuo-motor integration.
Clinicopathologic features and biochemical recurrence are sensitive, but not specific, predictors of metastatic disease and lethal prostate cancer. We hypothesize that a genomic expression signature ...detected in the primary tumor represents true biological potential of aggressive disease and provides improved prediction of early prostate cancer metastasis.
A nested case-control design was used to select 639 patients from the Mayo Clinic tumor registry who underwent radical prostatectomy between 1987 and 2001. A genomic classifier (GC) was developed by modeling differential RNA expression using 1.4 million feature high-density expression arrays of men enriched for rising PSA after prostatectomy, including 213 who experienced early clinical metastasis after biochemical recurrence. A training set was used to develop a random forest classifier of 22 markers to predict for cases--men with early clinical metastasis after rising PSA. Performance of GC was compared to prognostic factors such as Gleason score and previous gene expression signatures in a withheld validation set.
Expression profiles were generated from 545 unique patient samples, with median follow-up of 16.9 years. GC achieved an area under the receiver operating characteristic curve of 0.75 (0.67-0.83) in validation, outperforming clinical variables and gene signatures. GC was the only significant prognostic factor in multivariable analyses. Within Gleason score groups, cases with high GC scores experienced earlier death from prostate cancer and reduced overall survival. The markers in the classifier were found to be associated with a number of key biological processes in prostate cancer metastatic disease progression.
A genomic classifier was developed and validated in a large patient cohort enriched with prostate cancer metastasis patients and a rising PSA that went on to experience metastatic disease. This early metastasis prediction model based on genomic expression in the primary tumor may be useful for identification of aggressive prostate cancer.
Long non-coding RNAs (ncRNAs) have been shown to regulate important biological processes that support normal cellular functions. Aberrant regulation of these essential functions can promote tumor ...development. In this review, we underscore the importance of the regulatory role played by this distinct class of ncRNAs in cancer-associated pathways that govern mechanisms such as cell growth, invasion, and metastasis. We also highlight the possibility of using these unique RNAs as diagnostic and prognostic biomarkers in malignancies.
Highlights ► We describe the analysis challenges for different kinds of large-scale neuroanatomical data sets. ► We distinguish between isotropic 3D and highly anisotropic data sets and the ...corresponding analytical approaches. ► We review and compare some of the available software tools. ► We provide brief guideline for neural circuit reconstruction from large image data sets.
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