More Like this

1. Interictal epileptiform discharges contribute to word‐finding difficulty in epilepsy through multiple cognitive mechanisms

   https://doi.org/10.1111/epi.17781  

   Silva, Alexander B. ; Leonard, Matthew K. ; Oganian, Yulia ; D'Esopo, Emma ; Krish, Devon ; Kopald, Brandon ; Tran, Edwina B. ; Chang, Edward F. ; Kleen, Jonathan K. ( October 2023 , Epilepsia)

   Cognitive impairment often impacts quality of life in epilepsy even if seizures are controlled. Word‐finding difficulty is particularly prevalent and often attributed to etiological (static, baseline) circuit alterations. We sought to determine whether interictal discharges convey significant superimposed contributions to word‐finding difficulty in patients, and if so, through which cognitive mechanism(s).

   Twenty‐three patients undergoing intracranial monitoring for drug‐resistant epilepsy participated in multiple tasks involving word production (auditory naming, short‐term verbal free recall, repetition) to probe word‐finding difficulty across different cognitive domains. We compared behavioral performance between trials with versus without interictal discharges across six major brain areas and adjusted for intersubject differences using mixed‐effects models. We also evaluated for subjective word‐finding difficulties through retrospective chart review.

   Subjective word‐finding difficulty was reported by the majority (79%) of studied patients preoperatively. During intracranial recordings, interictal epileptiform discharges (IEDs) in the medial temporal lobe were associated with long‐term lexicosemantic memory impairments as indexed by auditory naming (p = .009), in addition to their established impact on short‐term verbal memory as indexed by free recall (p = .004). Interictal discharges involving the lateral temporal cortex and lateral frontal cortex were associated with delayed reaction time in the auditory naming task (p = .016 andp = .018), as well as phonological working memory impairments as indexed by repetition reaction time (p = .002). Effects of IEDs across anatomical regions were strongly dependent on their precise timing within the task.

   IEDs appear to act through multiple cognitive mechanisms to form a convergent basis for the debilitating clinical word‐finding difficulty reported by patients with epilepsy. This was particularly notable for medial temporal spikes, which are quite common in adult focal epilepsy. In parallel with the treatment of seizures, the modulation of interictal discharges through emerging pharmacological means and neurostimulation approaches may be an opportunity to help address devastating memory and language impairments in epilepsy.

    

   more » « less
2. The Importance of Reaction Energy in Predicting Chemical Reaction Barriers with Machine Learning Models

   https://doi.org/10.1002/cphc.202300933  

   Lalith, Nithin ; Singh, Aayush R. ; Gauthier, Joseph A. ( April 2024 , ChemPhysChem)

   Improving our fundamental understanding of complex heterocatalytic processes increasingly relies on electronic structure simulations and microkinetic models based on calculated energy differences. In particular, calculation of activation barriers, usually achieved through compute‐intensive saddle point search routines, remains a serious bottleneck in understanding trends in catalytic activity for highly branched reaction networks. Although the well‐known Brønsted‐Evans‐Polyani (BEP) scaling – a one‐feature linear regression model – has been widely applied in such microkinetic models, they still rely on calculated reaction energies and may not generalize beyond a single facet on a single class of materials, e. g., a terrace sites on transition metals. For highly branched and energetically shallow reaction networks, such as electrochemical CO₂reduction or wastewater remediation, calculating even reaction energies on many surfaces can become computationally intractable due to the combinatorial explosion of states that must be considered. Here, we investigate the feasibility of activation barrier prediction without knowledge of the reaction energy using linear and nonlinear machine learning (ML) models trained on a new database of over 500 dehydrogenation activation barriers. We also find that inclusion of the reaction energy significantly improves both classes of ML models, but complex nonlinear models can achieve performance similar to the simplest BEP scaling when predicting activation barriers on new systems. Additionally, inclusion of the reaction energy significantly improves generalizability to new systems beyond the training set. Our results suggest that the reaction energy is a critical feature to consider when building models to predict activation barriers, indicating that efforts to reliably predict reaction energies through, e. g., the Open Catalyst Project and others, will be an important route to effective model development for more complex systems.

    

   more » « less
3. Fracture Intensity Impacts on Reaction Front Propagation and Mineral Weathering in Three‐Dimensional Fractured Media

   https://doi.org/10.1029/2022WR032121  

   Andrews, E. M. ; Hyman, J. D. ; Sweeney, M. R. ; Karra, S. ; Moulton, J. D. ; Navarre‐Sitchler, A. ( February 2023 , Water Resources Research)

   Studying reaction front propagation in heterogeneous natural settings is challenging, but numerical simulations can provide insight into the varying spatial and temporal scales of reaction front propagation. Here, the impact of increasing fracture intensity on mineral dissolution rates, and the extent of reaction front propagation is investigated using reactive transport simulations in upscaled discrete fracture network domains with varied fracture intensity. Domain‐averaged dissolution rates vary less than 0.5 log units regardless of the fracture intensity, but the spatial distribution of reactions is controlled by the location and number of dead‐end fractures and the number of connected flowpaths through the domain. Higher fracture intensities lead to more weathering in the domain because of more available mineral for water‐rock interactions. We find that reaction fronts propagate through the primary flowpaths in the first 10,000 years of the simulation for a 10‐m length domain, then propagate into secondary flowpaths and dead‐end fractures between 10,000 and 100,000 years, and finally into the matrix over timescales of hundreds of thousands of years. The domain‐averaged reaction rates decrease through time corresponding to a transition from dissolution in advection‐dominated, fast‐flowing pathways, to dissolution in transport‐limited zones of disconnected fractures and matrix. Matrix dissolution, or dissolution under transport‐limited conditions, is the dominant process at late times in these simulations. The results of these simulations recreate the observed paradox found in nature where highly fractured hillslopes tend to be more weathered but have slower weathering rates, while hillslopes with fewer fractures, are less weathered but have higher dissolution rates.

    

   more » « less
4. Combined Crossed Molecular Beams and Ab Initio Study of the Bimolecular Reaction of Ground State Atomic Silicon (Si; 3 P) with Germane (GeH 4 ; X 1 A 1 )

   https://doi.org/10.1002/cphc.202100235  

   Krasnoukhov, Vladislav S. ; Azyazov, Valeriy N. ; Mebel, Alexander M. ; Doddipatla, Srinivas ; Yang, Zhenghai ; Goettl, Shane ; Kaiser, Ralf I. ( June 2021 , ChemPhysChem)

   The chemical dynamics of the elementary reaction of ground state atomic silicon (Si;³P) with germane (GeH₄; X¹A₁) were unraveled in the gas phase under single collision condition at a collision energy of 11.8±0.3 kJ mol⁻¹exploiting the crossed molecular beams technique contemplated with electronic structure calculations. The reaction follows indirect scattering dynamics and is initiated through an initial barrierless insertion of the silicon atom into one of the four chemically equivalent germanium‐hydrogen bonds forming a triplet collision complex (HSiGeH₃;³i1). This intermediate underwent facile intersystem crossing (ISC) to the singlet surface (HSiGeH₃;¹i1). The latter isomerized via at least three hydrogen atom migrations involving exotic, hydrogen bridged reaction intermediates eventually leading to the H₃SiGeH isomeri5. This intermediate could undergo unimolecular decomposition yielding the dibridged butterfly‐structured isomer¹p1(Si(μ‐H₂)Ge) plus molecular hydrogen through a tight exit transition state. Alternatively, up to two subsequent hydrogen shifts toi6andi7, followed by fragmentation of each of these intermediates, could also form¹p1(Si(μ‐H₂)Ge) along with molecular hydrogen. The overall non‐adiabatic reaction dynamics provide evidence on the existence of exotic dinuclear hydrides of main group XIV elements, whose carbon analog structures do not exist.

    

   more » « less
5. Computing optimal factories in metabolic networks with negative regulation

   https://doi.org/10.1093/bioinformatics/btac231  

   Krieger, Spencer ; Kececioglu, John ( June 2022 , Bioinformatics)

   A factory in a metabolic network specifies how to produce target molecules from source compounds through biochemical reactions, properly accounting for reaction stoichiometry to conserve or not deplete intermediate metabolites. While finding factories is a fundamental problem in systems biology, available methods do not consider the number of reactions used, nor address negative regulation.

   We introduce the new problem of finding optimal factories that use the fewest reactions, for the first time incorporating both first- and second-order negative regulation. We model this problem with directed hypergraphs, prove it is NP-complete, solve it via mixed-integer linear programming, and accommodate second-order negative regulation by an iterative approach that generates next-best factories.

   This optimization-based approach is remarkably fast in practice, typically finding optimal factories in a few seconds, even for metabolic networks involving tens of thousands of reactions and metabolites, as demonstrated through comprehensive experiments across all instances from standard reaction databases.

   Source code for an implementation of our new method for optimal factories with negative regulation in a new tool called Odinn, together with all datasets, is available free for non-commercial use at http://odinn.cs.arizona.edu.

    

   more » « less