AI-dente: an open machine learning based tool to interpret nano-indentation data of soft tissues and materials.

Nano-indentation is a promising method to identify the constitutive parameters of soft materials, including soft tissues. Especially when materials are very small and heterogeneous, nano-indentation allows mechanical interrogation where traditional methods may fail. However, because nano-indentation does not yield a homogeneous deformation field, interpreting the resulting load-displacement curves is non-trivial and most investigators resort to simplified approaches based on the Hertzian solution. Unfortunately, for small samples and large indentation depths, these solutions are inaccurate. We set out to use machine learning to provide an alternative strategy. We first used the finite element method to create a large synthetic data set. We then used these data to train neural networks to inversely identify material parameters from load-displacement curves. To this end, we took two different approaches. First, we learned the indentation forward problem, which we then applied within an iterative framework to identify material parameters. Second, we learned the inverse problem of directly identifying material parameters. We show that both approaches are effective at identifying the parameters of the neo-Hookean and Gent models. Specifically, when applied to synthetic data, our approaches are accurate even for small sample sizes and at deep indentation. Additionally, our approaches are fast, especially compared to the inverse finite element approach. Finally, our approaches worked on unseen experimental data from thin mouse brain samples. Here, our approaches proved robust to experimental noise across over 1000 samples. By providing open access to our data and code, we hope to support others that conduct nano-indentation on soft materials.

Mechanistic Computational Modeling of Implantable, Bioresorbable Drug Release Systems.

Implantable, bioresorbable drug delivery systems offer an alternative to current drug administration techniques; allowing for patient-tailored drug dosage, while also increasing patient compliance. Mechanistic mathematical modeling allows for the acceleration of the design of the release systems, and for prediction of physical anomalies that are not intuitive and may otherwise elude discovery. This study investigates short-term drug release as a function of water-mediated polymer phase inversion into a solid depot within hours to days, as well as long-term hydrolysis-mediated degradation and erosion of the implant over the next few weeks. Finite difference methods are used to model spatial and temporal changes in polymer phase inversion, solidification, and hydrolysis. Modeling reveals the impact of non-uniform drug distribution, production and transport of H+ ions, and localized polymer degradation on the diffusion of water, drug, and hydrolyzed polymer byproducts. Compared to experimental data, the computational model accurately predicts the drug release during the solidification of implants over days and drug release profiles over weeks from microspheres and implants. This work offers new insight into the impact of various parameters on drug release profiles, and is a new tool to accelerate the design process for release systems to meet a patient specific clinical need.

Crystal structures of two coordination isomers of copper(II) 4-sulfo-benzoic acid hexa-hydrate and two mixed silver/potassium 4-sulfo-benzoic acid salts.

A reaction of copper(II) carbonate and potassium 4-sulfo-benzoic acid in water acidified with hydro-chloric acid yielded two crystalline products. Tetra-aqua-bis-(4-carb-oxy-benzene-sulfonato)-copper(II) dihydrate, [Cu(O3SC6H4CO2H)2(H2O)4]·2H2O, (I), crystallizes in the triclinic space group P with the Cu2+ ions located on centers of inversion. Each copper ion is coordinated to four water mol-ecules in a square plane with two sulfonate O atoms in the apical positions of a Jahn-Teller-distorted octa-hedron. The carboxyl-ate group is protonated and not involved in coordination to the metal ions. The complexes pack so as to create a layered structure with alternating inorganic and organic domains. The packing is reinforced by several O-H⋯O hydrogen bonds involving coordinated and non-coordinated water mol-ecules, the carb-oxy-lic acid group and the sulfonate group. Hexa-aqua-copper(II) 4-carb-oxy-benzene-sulfonate, [Cu(H2O)6](O3SC6H4CO2H)2, (II), also crystallizes in the triclinic space group P with Jahn-Teller-distorted octa-hedral copper(II) aqua complexes on the centers of inversion. As in (I), the carboxyl-ate group on the anion is protonated and the structure consists of alternating layers of inorganic cations and organic anions linked by O-H⋯O hydrogen bonds. A reaction of silver nitrate and potassium 4-sulfo-benzoic acid in water also resulted in two distinct products that have been structurally characterized. An anhydrous silver potassium 4-carb-oxy-benzene-sulfonate salt, [Ag0.69K0.31](O3SC6H4CO2H), (III), crystallizes in the monoclinic space group C2/c. There are two independent metal sites, one fully occupied by silver ions and the other showing a 62% K+/38% Ag+ (fixed) ratio, refined in two slightly different positions. The coordination environments of the metal ions are composed primarily of sulfonate O atoms, with some participation by the non-protonated carboxyl-ate O atoms in the disordered site. As in the copper compounds, the cations and anions cleanly segregate into alternating layers. A hydrated mixed silver potassium 4-carb-oxy-benzene-sulfonate salt dihydrate, [Ag0.20K0.80](O3SC6H4CO2H)·2H2O, (IV), crystallizes in the monoclinic space group P21/c with the Ag+ and K+ ions sharing one unique metal site coordinated by two water mol-ecules and six sulfonate O atoms. The packing in (IV) follows the dominant motif of alternating inorganic and organic layers. The protonated carboxyl-ate groups do not inter-act with the cations directly, but do participate in hydrogen bonds with the coordinated water mol-ecules. (IV) is isostructural with pure potassium 4-sulfo-benzoic acid dihydrate.

N-Benzylnicotinamide and N-benzyl-1,4-dihydronicotinamide: useful models for NAD+ and NADH.

3-Aminocarbonyl-1-benzylpyridinium bromide (N-benzylnicotinamide, BNA), C13H13N2O+·Br-, (I), and 1-benzyl-1,4-dihydropyridine-3-carboxamide (N-benzyl-1,4-dihydronicotinamide, rBNA), C13H14N2O, (II), are valuable model compounds used to study the enzymatic cofactors NAD(P)+ and NAD(P)H. BNA was crystallized successfully and its structure determined for the first time, while a low-temperature high-resolution structure of rBNA was obtained. Together, these structures provide the most detailed view of the reactive portions of NAD(P)+ and NAD(P)H. The amide group in BNA is rotated 8.4 (4)° out of the plane of the pyridine ring, while the two rings display a dihedral angle of 70.48 (17)°. In the rBNA structure, the dihydropyridine ring is essentially planar, indicating significant delocalization of the formal double bonds, and the amide group is coplanar with the ring [dihedral angle = 4.35 (9)°]. This rBNA conformation may lower the transition-state energy of an ene reaction between a substrate double bond and the dihydropyridine ring. The transition state would involve one atom of the double bond binding to the carbon ortho to both the ring N atom and the amide substituent of the dihydropyridine ring, while the other end of the double bond accepts an H atom from the methylene group para to the N atom.