83 research outputs found
A GPU-accelerated Direct-sum Boundary Integral Poisson-Boltzmann Solver
In this paper, we present a GPU-accelerated direct-sum boundary integral
method to solve the linear Poisson-Boltzmann (PB) equation. In our method, a
well-posed boundary integral formulation is used to ensure the fast convergence
of Krylov subspace based linear algebraic solver such as the GMRES. The
molecular surfaces are discretized with flat triangles and centroid
collocation. To speed up our method, we take advantage of the parallel nature
of the boundary integral formulation and parallelize the schemes within CUDA
shared memory architecture on GPU. The schemes use only
size-of-double device memory for a biomolecule with triangular surface
elements and partial charges. Numerical tests of these schemes show
well-maintained accuracy and fast convergence. The GPU implementation using one
GPU card (Nvidia Tesla M2070) achieves 120-150X speed-up to the implementation
using one CPU (Intel L5640 2.27GHz). With our approach, solving PB equations on
well-discretized molecular surfaces with up to 300,000 boundary elements will
take less than about 10 minutes, hence our approach is particularly suitable
for fast electrostatics computations on small to medium biomolecules
Integral equation method for the 1D steady-state Poisson-Nernst-Planck equations
An integral equation method is presented for the 1D steady-state
Poisson-Nernst-Planck equations modeling ion transport through membrane
channels. The differential equations are recast as integral equations using
Green's 3rd identity yielding a fixed-point problem for the electric potential
gradient and ion concentrations. The integrals are discretized by a combination
of midpoint and trapezoid rules and the resulting algebraic equations are
solved by Gummel iteration. Numerical tests for electroneutral and
non-electroneutral systems demonstrate the method's 2nd order accuracy and
ability to resolve sharp boundary layers. The method is applied to a 1D model
of the K ion channel with a fixed charge density that ensures cation
selectivity. In these tests, the proposed integral equation method yields
potential and concentration profiles in good agreement with published results.Comment: 15 pages, 7 figure
Poisson-Boltzmann based machine learning (PBML) model for electrostatic analysis
Electrostatics is of paramount importance to chemistry, physics, biology, and
medicine. The Poisson-Boltzmann (PB) theory is a primary model for
electrostatic analysis. However, it is highly challenging to compute accurate
PB electrostatic solvation free energies for macromolecules due to the
nonlinearity, dielectric jumps, charge singularity , and geometric complexity
associated with the PB equation. The present work introduces a PB based machine
learning (PBML) model for biomolecular electrostatic analysis. Trained with the
second-order accurate MIBPB solver, the proposed PBML model is found to be more
accurate and faster than several eminent PB solvers in electrostatic analysis.
The proposed PBML model can provide highly accurate PB electrostatic solvation
free energy of new biomolecules or new conformations generated by molecular
dynamics with much reduced computational cost
Rapid Colorimetric Testing for Pyrazinamide Susceptibility of M. tuberculosis by a PCR-Based In-Vitro Synthesized Pyrazinamidase Method
Pyrazinamide (PZA) is an important first-line anti-tuberculosis drug. But PZA susceptibility test is challenging because PZA activity is optimal only in an acid environment that inhibits the growth of M. tuberculosis. For current phenotypic methods, inconsistent results between different labs have been reported. Direct sequencing of pncA gene is being considered as an accurate predictor for PZA susceptibility, but this approach needs expensive sequencers and a mutation database to report the results. An in-vitro synthesized Pyrazinamidase (PZase) assay was developed based on PCR amplification of pncA gene and an in vitro wheat germ system to express the pncA gene into PZase. The activity of the synthesized PZase was used as an indicator for PZA susceptibility. Fifty-one clinical isolates were tested along with pncA sequencing and the BACTEC MGIT 960 methods. The in-vitro synthesized PZase assay was able to detect PZA susceptibility of M. tuberculosis within 24 h through observing the color difference either by a spectrometer or naked eyes. This method showed agreements of 100% (33/33) and 88% (14/16) with the pncA sequencing method, and agreements of 96% (27/28) and 65% (15/23) with the BACTEC MGIT 960 method, for susceptible and resistant strains, respectively. The novel in-vitro synthesized PZase assay has significant advantages over current methods, such as its fast speed, simplicity, no need for expensive equipment, and the potentials of being a direct test, predicting resistance level and easy reading results by naked eyes. After confirmation by more clinical tests, this method may provide a radical change to the current PZA susceptibility assays
Advances in artificial intelligence in thyroid-associated ophthalmopathy
Thyroid-associated ophthalmopathy (TAO), also referred to as Graves’ ophthalmopathy, is a medical condition wherein ocular complications arise due to autoimmune thyroid illness. The diagnosis of TAO, reliant on imaging, typical ocular symptoms, and abnormalities in thyroid function or thyroid-associated antibodies, is generally graded and staged. In recent years, Artificial intelligence(AI), particularly deep learning(DL) technology, has gained widespread use in the diagnosis and treatment of ophthalmic diseases. This paper presents a discussion on specific studies involving AI, specifically DL, in the context of TAO, highlighting their applications in TAO diagnosis, staging, grading, and treatment decisions. Additionally, it addresses certain limitations in AI research on TAO and potential future directions for the field
Improvements to the APBS biomolecular solvation software suite
The Adaptive Poisson-Boltzmann Solver (APBS) software was developed to solve
the equations of continuum electrostatics for large biomolecular assemblages
that has provided impact in the study of a broad range of chemical, biological,
and biomedical applications. APBS addresses three key technology challenges for
understanding solvation and electrostatics in biomedical applications: accurate
and efficient models for biomolecular solvation and electrostatics, robust and
scalable software for applying those theories to biomolecular systems, and
mechanisms for sharing and analyzing biomolecular electrostatics data in the
scientific community. To address new research applications and advancing
computational capabilities, we have continually updated APBS and its suite of
accompanying software since its release in 2001. In this manuscript, we discuss
the models and capabilities that have recently been implemented within the APBS
software package including: a Poisson-Boltzmann analytical and a
semi-analytical solver, an optimized boundary element solver, a geometry-based
geometric flow solvation model, a graph theory based algorithm for determining
p values, and an improved web-based visualization tool for viewing
electrostatics
Tirofiban for Stroke without Large or Medium-Sized Vessel Occlusion
The effects of the glycoprotein IIb/IIIa receptor inhibitor tirofiban in patients with acute ischemic stroke but who have no evidence of complete occlusion of large or medium-sized vessels have not been extensively studied. In a multicenter trial in China, we enrolled patients with ischemic stroke without occlusion of large or medium-sized vessels and with a National Institutes of Health Stroke Scale score of 5 or more and at least one moderately to severely weak limb. Eligible patients had any of four clinical presentations: ineligible for thrombolysis or thrombectomy and within 24 hours after the patient was last known to be well; progression of stroke symptoms 24 to 96 hours after onset; early neurologic deterioration after thrombolysis; or thrombolysis with no improvement at 4 to 24 hours. Patients were assigned to receive intravenous tirofiban (plus oral placebo) or oral aspirin (100 mg per day, plus intravenous placebo) for 2 days; all patients then received oral aspirin until day 90. The primary efficacy end point was an excellent outcome, defined as a score of 0 or 1 on the modified Rankin scale (range, 0 [no symptoms] to 6 [death]) at 90 days. Secondary end points included functional independence at 90 days and a quality-of-life score. The primary safety end points were death and symptomatic intracranial hemorrhage. A total of 606 patients were assigned to the tirofiban group and 571 to the aspirin group. Most patients had small infarctions that were presumed to be atherosclerotic. The percentage of patients with a score of 0 or 1 on the modified Rankin scale at 90 days was 29.1% with tirofiban and 22.2% with aspirin (adjusted risk ratio, 1.26; 95% confidence interval, 1.04 to 1.53, P = 0.02). Results for secondary end points were generally not consistent with the results of the primary analysis. Mortality was similar in the two groups. The incidence of symptomatic intracranial hemorrhage was 1.0% in the tirofiban group and 0% in the aspirin group. In this trial involving heterogeneous groups of patients with stroke of recent onset or progression of stroke symptoms and nonoccluded large and medium-sized cerebral vessels, intravenous tirofiban was associated with a greater likelihood of an excellent outcome than low-dose aspirin. Incidences of intracranial hemorrhages were low but slightly higher with tirofiban
A boundary integral Poisson-Boltzmann solvers package for solvated bimolecular simulations
Numerically solving the Poisson-Boltzmann equation is a challenging task due to the existence
of the dielectric interface, singular partial charges representing the biomolecule, discontinuity of the electrostatic
field, infinite simulation domains, etc. Boundary integral formulation of the Poisson-Boltzmann
equation can circumvent these numerical challenges and meanwhile conveniently use the fast numerical
algorithms and the latest high performance computers to achieve combined improvement on both efficiency
and accuracy. In the past a few years, we developed several boundary integral Poisson-Boltzmann solvers
in pursuing accuracy, efficiency, and the combination of both. In this paper, we summarize the features and
functions of these solvers, and give instructions and references for potential users. Meanwhile, we quantitatively
report the solvation free energy computation of these boundary integral PB solvers benchmarked with
Matched Interface Boundary Poisson-Boltzmann solver (MIBPB), a current 2nd order accurate finite difference
Poisson-Boltzmann solver
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