81 research outputs found
Reduced resonance schemes and Chen ranks
The resonance varieties are cohomological invariants that are studied in a
variety of topological, combinatorial, and geometric contexts. We discuss their
scheme structure in a general algebraic setting and introduce various
properties that ensure the reducedness of the associated projective resonance
scheme. We prove an asymptotic formula for the Hilbert series of the associated
Koszul module, then discuss applications to vector bundles on algebraic curves
and to Chen ranks formulas for finitely generated groups, with special emphasis
on K\"ahler and right-angled Artin groups.Comment: 34 page
Higher resonance schemes and Koszul modules of simplicial complexes
Each connected graded, graded-commutative algebra of finite type over a
field of characteristic zero defines a complex of finitely generated,
graded modules over a symmetric algebra, whose homology graded modules are
called the (higher) Koszul modules of . In this note, we investigate the
geometry of the support loci of these modules, called the resonance schemes of
the algebra. When is the exterior
Stanley-Reisner algebra associated to a finite simplicial complex , we
show that the resonance schemes are reduced. We also compute the Hilbert series
of the Koszul modules and give bounds on the regularity and projective
dimension of these graded modules. This leads to a relationship between
resonance and Hilbert series that generalizes a known formula for the Chen
ranks of a right-angled Artin group.Comment: 16 page
Many-task computing on many-core architectures
Many-Task Computing (MTC) is a common scenario for multiple parallel systems, such as cluster, grids, cloud and supercomputers, but it is not so popular in shared memory parallel processors. In this sense and given the spectacular growth in performance and in number of cores integrated in many-core architectures, the study of MTC on such architectures is becoming more and more relevant. In this paper, authors present what are those programming mechanisms to take advantages of such massively parallel features for the particular target of MTC. Also, the hardware features of the two dominant many-core platforms (NVIDIA's GPUs and Intel Xeon Phi) are also analyzed for our specific framework. Given the important differences in terms of hardware and software in our two many-core platforms, we have considered different strategies based on CUDA (for GPUs) and OpenMP (for Intel Xeon Phi). We carried out several test cases based on an appropriate and widely studied problem for benchmarking as matrix multiplication. Essentially, this study consisted of comparing the time consumed for computing in parallel several tasks one by one (the whole computational resources are used just to compute one task at a time) with the time consumed for computing in parallel the same set of tasks simultaneously (the whole computational resources are used for computing the set of tasks at very same time). Finally, we compared both software-hardware scenarios to identify the most relevant computer features in each of our many-core architectures
Förster Resonance Energy Transfer (FRET) Correlates of Altered Subunit Stoichiometry in Cys-Loop Receptors, Exemplified by Nicotinic α4β2
We provide a theory for employing Förster resonance energy transfer (FRET)
measurements to determine altered heteropentameric ion channel stoichiometries in
intracellular compartments of living cells. We simulate FRET within nicotinic receptors
(nAChRs) whose α4 and β2 subunits contain acceptor and donor fluorescent protein
moieties, respectively, within the cytoplasmic loops. We predict FRET and normalized
FRET (NFRET) for the two predominant stoichiometries, (α4)3(β2)2 vs. (α4)2(β2)3.
Studying the ratio between FRET or NFRET for the two stoichiometries, minimizes
distortions due to various photophysical uncertainties. Within a range of assumptions
concerning the distance between fluorophores, deviations from plane pentameric geometry,
and other asymmetries, the predicted FRET and NFRET for (α4)3(β2)2 exceeds that of
(α4)2(β2)3. The simulations account for published data on transfected Neuro2a cells in
which α4β2 stoichiometries were manipulated by varying fluorescent subunit cDNA ratios:
NFRET decreased monotonically from (α4)3(β2)2 stoichiometry to mostly (α4)2(β2)3. The
simulations also account for previous macroscopic and single-channel observations that
pharmacological chaperoning by nicotine and cytisine increase the (α4)2(β2)3 and
(α4)3(β2)2 populations, respectively. We also analyze sources of variability. NFRET-based monitoring of changes in subunit stoichiometry can contribute usefully to studies on
Cys-loop receptors
DNA Methylation Profiling Enables Accurate Classification of Nonductal Primary Pancreatic Neoplasms
Background & Aims: Cytologic and histopathologic diagnosis of non-ductal pancreatic neoplasms can be challenging in daily clinical practice, whereas it is crucial for therapy and prognosis. The cancer methylome is successfully used as a diagnostic tool in other cancer entities. Here, we investigate if methylation profiling can improve the diagnostic work-up of pancreatic neoplasms. Methods: DNA methylation data were obtained for 301 primary tumors spanning 6 primary pancreatic neoplasms and 20 normal pancreas controls. Neural Network, Random Forest, and extreme gradient boosting machine learning models were trained to distinguish between tumor types. Methylation data of 29 nonpancreatic neoplasms (n = 3708) were used to develop an algorithm capable of detecting neoplasms of non-pancreatic origin. Results: After benchmarking 3 state-of-the-art machine learning models, the random forest model emerged as the best classifier with 96.9% accuracy. All classifications received a probability score reflecting the confidence of the prediction. Increasing the score threshold improved the random forest classifier performance up to 100% with 87% of samples with scores surpassing the cutoff. Using a logistic regression model, detection of nonpancreatic neoplasms achieved an area under the curve of >0.99. Analysis of biopsy specimens showed concordant classification with their paired resection sample. Conclusions: Pancreatic neoplasms can be classified with high accuracy based on DNA methylation signatures. Additionally, non-pancreatic neoplasms are identified with near perfect precision. In summary, methylation profiling can serve as a valuable adjunct in the diagnosis of pancreatic neoplasms with minimal risk for misdiagnosis, even in the pre-operative setting
Axial slicing versus bivalving in the pathological examination of pancreatoduodenectomy specimens (APOLLO): a multicentre randomized controlled trial
Background: In pancreatoduodenectomy specimens, dissection method may affect the assessment of primary tumour origin (i.e. pancreatic, distal bile duct or ampullary adenocarcinoma), which is primarily determined macroscopically. This is the first study to prospectively compare the two commonly used techniques, i.e. axial slicing and bivalving. Methods: In four centres, a randomized controlled trial was performed in specimens of patients with a suspected (pre)malignant tumour in the pancreatic head. Primary outcome measure was the level of certainty (scale 0–100) regarding tumour origin by four independent gastrointestinal pathologists based on macroscopic assessment. Secondary outcomes were inter-observer agreement and R1 rate. Results: In total, 128 pancreatoduodenectomy specimens were randomized. The level of certainty in determining the primary tumour origin did not differ between axial slicing and bivalving (mean score 72 [sd 13] vs. 68 [sd 16], p = 0.21), nor did inter-observer agreement, both being moderate (kappa 0.45 vs. 0.47). In pancreatic cancer specimens, R1 rate (60% vs. 55%, p = 0.71) and the number of harvested lymph nodes (median 16 vs. 17, p = 0.58) were similar. Conclusion: This study demonstrated no differences in determining the tumour origin between axial slicing and bivalving. Both techniques performed similarly regarding inter-observer agreement, R1 rate, and lymph node harvest
Efficacy of dose-escalated chemoradiation on complete tumour response in patients with locally advanced rectal cancer (RECTAL-BOOST); a phase 2 randomised controlled trial
Purpose
Pathological complete tumour response following chemoradiation in patients with locally advanced rectal cancer (LARC) is associated with favourable prognosis and allows organ-sparing treatment strategies. We aimed to investigate the effect of an external radiation boost to the tumour prior to chemoradiation on pathological or sustained clinical complete tumour response in LARC.
Methods and materials
This multicentre, non-blinded, phase 2, randomised controlled trial followed the trials within cohorts-design, which is a pragmatic trial design allowing cohort participants to be randomized for an experimental intervention. Patients in the intervention group are offered the intervention (and can accept or refuse this), whereas patients in the control group are not notified about the randomisation. Participants of a colorectal cancer cohort referred for chemoradiation of LARC to either of two radiotherapy centres were eligible. Patients were randomised to no boost or an external radiation boost (5 x 3 Gy) without concurrent chemotherapy directly followed by standard pelvic chemoradiation (25 x 2 Gy with concurrent capecitabine). The primary outcome was pathological complete response (pCR, i.e. ypT0N0) in patients with planned surgery at 12 weeks or, as surrogate for pCR, a 2-year sustained clinical complete response for patients treated with an organ preservation strategy. Analyses were intention to treat. The study was registered with ClinicalTrials.gov, number NCTXXXXXX.
Results
Between Sept 2014 and July 2018, 128 patients were randomised. Fifty-one of the 64 (79.7%) patients in the intervention group accepted and received a boost. Compared with the control group, fewer patients in the intervention group had a cT4-stage and a low rectal tumour (31.3% versus 17.2% and 56.3% versus 45.3% respectively), and more patients had a cN2-stage (59.4% versus 70.3% respectively). Rate of pathological or sustained clinical complete tumour response was similar between the groups: 23 of 64 (35.9%, 95%CI 24.3-48.9) in the intervention group versus 24 of 64 (37.5%, 95%CI 25.7-50.5) in the control group (OR=0.94 95%CI 0.46-1.92). Near-complete or complete tumour regression was more common in the intervention group: 34 of 49 (69.4%) versus 24 of 53 (45.3%) in the control group (OR=2.74, 95%CI 1.21-6.18). Grade >3 acute toxicity was comparable: 6 of 64 (9.4%) in the intervention group versus 5 of 64 (7.8%) in the control group (OR=1.22 95%CI 0.35-4.22).
Conclusion
Dose escalation with an external radiotherapy boost to the tumour prior to neoadjuvant chemoradiation did not increase the pathological or sustained clinical complete tumour response rate in LARC
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