A neural network potential based on pairwise resolved atomic forces and energies

Molecular simulations have become a key tool in molecular and materials design. Machine learning (ML)-based potential energy functions offer the prospect of simulating complex molecular systems efficiently at quantum chemical accuracy. In previous work, we have introduced the ML-based PairF-Net approach to neural network potentials, that adopts a pairwise interatomic scheme to predicting forces within a molecular system. Here, we further develop the PairF-Net model to intrinsically incorporate energy conservation and couple the model to a molecular mechanical (MM) environment within the OpenMM package. The updated PairF-Net model yields energy and force predictions and dynamical distributions in good agreement with the rMD17 dataset of ten small organic molecules in the gas-phase. We further show that these in vacuo ML models of small molecules can be applied to force predictions in aqueous solution via hybrid ML/MM simulations. We present a new benchmark dataset for these ten molecules in solution, obtained from QM/MM simulations, which we denote as rMD17-aq (https://zenodo.org/records/10048644); and assess the ability of PairF-Net to reproduce the molecular energy, atomic forces and dynamical distributions of these solution conformations via ML/MM simulations.

Epidemiology of neurodegenerative diseases in the East African region: A meta-analysis

INTRODUCTION

There is a scarcity of epidemiological data on neurodegenerative diseases (NDs) in East Africa. This meta-analysis provides the regional prevalence of NDs, their contributing factors, and evidence of change over time concerning gender per age or year.

METHODS

Articles were retrieved from electronic databases following the PRISMA standard.

RESULTS

Forty-two studies were reviewed, and 25 were meta-analyzed with a random-effects model. The pool estimate proportion of 15.27%, 95% CI (0.09-0.23) (I² = 98.25%), (Q = 1,369.15, p < 0.0001) among a population of 15,813 male/female and 1,257 with NDs. Epidemiological characteristics associated with NDs include Dyskinesias prevalence 55.4%, 95% CI (13.5; 90.9), I² (96%) and subsistence farming prevalence 11.3%, 95% CI (5.8; 20.9), I² (99%). Publication bias by Egger test was (z = 4.1913, p < 0.0001), while rank correlation test using Kendall's model was (tau = 0.1237, p = 0.3873). Heterogeneity (R² design = 5.23%, p design < 0.0001; R² size = 52.163%, p size < 0.001; and R² period = 48.13, p period < 0.0001. Covariates (R² design + size + period = 48.41%, p < 0.001).

CONCLUSION

There is a high prevalence of NDs in the East African region, which could impact life expectancy, morbidity, and quality of life. Thus, early screening and regular surveillance could assist in management strategies.

Machine learning interatomic potentials for aluminium: application to solidification phenomena

In studying solidification process by simulations on the atomic scale, the modeling of crystal nucleation or amorphization requires the construction of interatomic interactions that are able to reproduce the properties of both the solid and the liquid states. Taking into account rare nucleation events or structural relaxation under deep undercooling conditions requires much larger length scales and longer time scales than those achievable byab initiomolecular dynamics (AIMD). This problem is addressed by means of classical molecular dynamics simulations using a well established high dimensional neural network potential trained on a set of configurations generated by AIMD relevant for solidification phenomena. Our dataset contains various crystalline structures and liquid states at different pressures, including their time fluctuations in a wide range of temperatures. Applied to elemental aluminium, the resulting potential is shown to be efficient to reproduce the basic structural, dynamics and thermodynamic quantities in the liquid and undercooled states. Early stages of crystallization are further investigated on a much larger scale with one million atoms, allowing us to unravel features of the homogeneous nucleation mechanisms in the fcc phase at ambient pressure as well as in the bcc phase at high pressure with unprecedented accuracy close to theab initioone. In both cases, a single step nucleation process is observed.

Mesenchymal Stem Cells Seeded Decellularized Tendon Scaffold for Tissue Engineering

Tendon is a collagenous tissue to connect bone and muscle. Healing of damaged/injured tendon is the primary clinical challenge in musculoskeletal regeneration because they often react poorly to treatment. Tissue engineering (a triad strategy of scaffolds, cells and growth factors) may have the potential to improve the quality of tendon tissue healing under such impaired situations. Tendon tissue engineering aims to synthesize graft alternatives to repair the injured tendon. Biological scaffolds derived from decellularized tissue may be a better option as their biomechanical properties are similar to the native tissue. This review is designed to provide background information on the current challenges in curing torn/worn out the tendon and the clinical relevance of decellularized scaffolds for such applications.

Two Years of ePrescription in Slovenia - Applications and Potentials

ePrescription is one of the most successful eHealth solutions in Slovenia. Since its national roll-out in early 2016, the quality of its operations has been constantly improving, and the number of users has been growing ever since to reach today's 90% of all healthcare providers. ePrescription facilitates more transparent and safer prescribing of medications, an overview of possible medication interactions, and reduction of administrative and opportunity costs. This paper initially explores the current state of ePrescription in Slovenia and different aspects of its application. Based on the research findings, the paper finally outlines potentials of ePrescription, which could be transformed into tangible benefits with particular implications for healthcare system. The research is based on focus group methodology. Structured discussions were conducted with eminent experts currently in charge of ePrescription (and other eHealth solutions) development and implementation in Slovenia. Research results imply that certain application aspects are relatively easy to define and evaluate, while the overall potentials of ePrescription are difficult to determine in many cases, and relatively unexplored in terms of their implications and operational feasibility.

Test-Retest of Long Latency Auditory Evoked Potentials (P300) with Pure Tone and Speech Stimuli

Introduction Long latency auditory evoked potentials, especially P300, have been used for clinical evaluation of mental processing. Many factors can interfere with Auditory Evoked Potential - P300 results, suggesting large intra and inter-subject variations.

Objective The objective of the study was to identify the reliability of P3 components (latency and amplitude) over 4–6 weeks and the most stable auditory stimulus with the best test-retest agreement.

Methods Ten normal-hearing women participated in the study. Only subjects without auditory processing problems were included. To determine the P3 components, we elicited long latency auditory evoked potential (P300) by pure tone and speech stimuli, and retested after 4–6 weeks using the same parameters. We identified P300 latency and amplitude by waveform subtraction.

Results We found lower coefficient of variation values in latency than in amplitude, with less variability analysis when speech stimulus was used. There was no significant correlation in latency measures between pure tone and speech stimuli, and sessions. There was a significant intrasubject correlation between measures of latency and amplitude.

Conclusion These findings show that amplitude responses are more robust for the speech stimulus when compared with its pure tone counterpart. The P300 indicated stability for latency and amplitude measures when the test-retest was applied. Reliability was higher for amplitude than for latency, with better agreement when the pure tone stimulus was used. However, further research with speech stimulus is needed to clarify how these stimuli are processed by the nervous system.

Predicting XAFS scattering path cumulants and XAFS spectra for metals (Cu, Ni, Fe, Ti, Au) using molecular dynamics simulations

The ability of molecular dynamics (MD) simulations to support the analysis of X-ray absorption fine-structure (XAFS) data for metals is evaluated. The low-order cumulants (ΔR, σ(2), C3) for XAFS scattering paths are calculated for the metals Cu, Ni, Fe, Ti and Au at 300 K using 28 interatomic potentials of the embedded-atom method type. The MD cumulant predictions were evaluated within a cumulant expansion XAFS fitting model, using global (path-independent) scaling factors. Direct simulations of the corresponding XAFS spectra, χ(R), are also performed using MD configurational data in combination with the FEFF ab initio code. The cumulant scaling parameters compensate for differences between the real and effective scattering path distributions, and for any errors that might exist in the MD predictions and in the experimental data. The fitted value of ΔR is susceptible to experimental errors and inadvertent lattice thermal expansion in the simulation crystallites. The unadjusted predictions of σ(2) vary in accuracy, but do not show a consistent bias for any metal except Au, for which all potentials overestimate σ(2). The unadjusted C3 predictions produced by different potentials display only order-of-magnitude consistency. The accuracy of direct simulations of χ(R) for a given metal varies among the different potentials. For each of the metals Cu, Ni, Fe and Ti, one or more of the tested potentials was found to provide a reasonable simulation of χ(R). However, none of the potentials tested for Au was sufficiently accurate for this purpose.

Differences in membrane properties in simulated cases of demyelinating neuropathies: internodal focal demyelinations with conduction block

The aim of this study is to investigate the membrane properties (potentials and axonal excitability indices) in the case of myelin wrap reduction (96%) in one, two and three consecutive internodes along the length of human motor nerve fibre. The internodally focally demyelinated cases (termed as IFD1, IFD2 and IFD3, respectively, with one, two and three demyelinated internodes are simulated using our previous double cable model of the fibre. The progressively greater increase of focal loss of myelin lamellae blocks the invasion of the intracellular potentials into the demyelinated zones. For all investigated cases, the radial decline of the extracellular potential amplitudes increases with the increase of the radial distance and demyelination, whereas the electrotonic potentials show a decrease in the slow part of the depolarizing and hyperpolarizing responses. The time constants are shorter and the rheobases higher for the IFD2 and IFD3 cases than for the normal case. In the recovery cycles, the same cases have less refractoriness, greater supernormality and less late subnormality than the normal case. The simulated membrane abnormalities can be observed in vivo in patients with demyelinating forms of Guillain-Barré syndrome. The study provides new information about the pathophysiology of acquired demyelinating neuropathies.

Differences in membrane properties in simulated cases of demyelinating neuropathies: internodal focal demyelinations without conduction block

The membrane properties (intracellular, extracellular, electrotonic potentials, strength-duration time constants, rheobasic currents and recovery cycles), which can now be measured in healthy subjects and patients with demyelinating neuropathies, are investigated in simulated cases of focal reduction (70%) of the myelin sheath in one, two and three successive internodal segments along the length of human motor fibres. The internodally focally demyelinated cases (termed as IFD1, IFD2 and IFD3, respectively) are simulated using our previous double cable model of the fibres. The results show that the intracellular potentials are with reduced amplitude and slowed conduction velocity in the vicinity of demyelinated segments, however the segmental conduction block is not achieved. The radial decline of the extracellular potential amplitudes slightly increases with the increase of the radial distance and demyelination. In contrast, the electrotonic potentials, strength-duration time constants and rheobases are normal. In the recovery cycles, the refractoriness, supernormality and less late subnormality are close to the normal, showing that the pathology is relatively minor. The obtained abnormalities in the potentials and excitability properties provide new information about the pathophysiology of the demyelinated human motor axons and can be observed in vivo in patients with acquired demyelinating neuropathies.

Individual-based modelling: potentials and limitations

Individual-based modelling (IBM) is an important option in ecology for the study of specific properties of complex ecological interaction networks. The main application of this model type is the analysis of population characteristics at high resolution. IBM also contributes to the advancement of ecological theory. One of the remarkable potentials of the approach is the possibility of studying self-organization and emergent properties that arise from individual actions on higher integration levels, especially on the population level. This review outlines the background and different application fields of individual-based models together with a short description of the technical implications of model setup. The limitations of this modelling approach result from the technical basis of model construction, which can handle a limited number of active entities only. Limits in biological knowledge also restrict the application of this model type. The paper presents some individual-based models that have been developed for different purposes and briefly discusses these models. Concerning the perspective of IBM, a coincidence with developments in artificial life research is explained. IBM shifts the focus of ecological analysis of dynamic systems from structurally fixed settings to the analysis of self-organizing interaction patterns that are variable in quantity and quality.

The value of somatosensory and motor evoked evoked potentials in pre-clinical spondylotic cervical cord compression

Previous studies have yielded conflicting data concerning the value of evoked potential parameters in the assessment of clinical relevance of cervical cord compression in clinically "silent" cases. The aim of this study was to assess the value of somatosensory (SEP) and motor evoked potentials (MEP) in the evaluation and prediction of the clinical course, by means of a 2-year follow-up prospective electrophysiological and clinical study performed in patients with clinically "silent" spondylotic cervical cord compression. Thirty patients with MR signs of spondylotic cervical cord compression but without clinical signs of myelopathy were evaluated clinically and using SEPs and MEPs during a 2-year period. The results of the study showed that SEPs and MEPs documented subclinical involvement of cervical cord in 50% of patients with clinically "silent" spondylotic cervical cord compression. During the 2-year period clinical signs of cervical myelopathy were observed in one-third of patients with entry EP abnormality in comparison with no patients with normal EP tests. Combined SEPs and MEPs proved to be a valuable tool in the assessment of the functional relevance of subclinical spondylotic cervical cord compression. Normal EP findings predict a favourable 2-year clinical outcome.