Development and first-stage validation of a digital version of the Digit Symbol Substitution test for use in assessing cognitive function in older people with diabetes.

AIMS: To describe the development and report the first-stage validation of a digital version of the digit symbol substitution test (DSST), for assessment of cognitive function in older people with diabetes. MATERIALS AND METHODS: A multidisciplinary team of experts was convened to conceptualize and build a digital version of the DSST and develop a machine-learning (ML) algorithm to analyse the inputs. One hundred individuals with type 2 diabetes (aged ≥ 60 years) were invited to participate in a one-time meeting in which both the digital and the pencil-and-paper (P&P) versions of the DSST were administered. Information pertaining to demographics, laboratory measurements, and diabetes indices was collected. The correlation between the digital and P&P versions of the test was determined. Additionally, as part of the validation process, the performance of the digital version in people with and without known risk factors for cognitive impairment was analysed. RESULTS: The ML model yielded an overall accuracy of 89.1%. A strong correlation was found between the P&P and digital versions (r = 0.76, p < 0.001) of the DSST, as well as between the ML model and the manual reading of the digital DSST (r = 0.99, p < 0.001). CONCLUSIONS: This study describes the development of and provides first-stage validation data for a newly developed digital cognitive assessment tool that may be used for screening and surveillance of cognitive function in older people with diabetes. More studies are needed to further validate this tool, especially when self-administered and in different clinical settings.

Diketoenamine-Based Vitrimers via Thiol-ene Photopolymerization.

Likened to both thermosets and thermoplastics, vitrimers are a unique class of materials that combine remarkable stability, healability, and reprocessability. Herein, this work describes a photopolymerized thiol-ene-based vitrimer that undergoes dynamic covalent exchanges through uncatalyzed transamination of enamines derived from cyclic ß-triketones, whereby the low energy barrier for exchange facilitates reprocessing and enables rapid depolymerization. Accordingly, an alkene-functionalized ß-triketone, 5,5-dimethyl-2-(pent-4-enoyl)cyclohexane-1,3-dione, is devised which is then reacted with 1,6-diaminohexane in a stoichiometrically imbalanced fashion (≈1:0.85 primary amine:triketone). The resulting networks exhibit subambient glass transition temperature (Tg = 5.66 °C) by differential scanning calorimetry. Using a Maxwell stress-relaxation fit, the topology-freezing temperature (Tv ) is calculated to be -32 °C. Small-amplitude oscillatory shear rheological analysis enables to identify a practical critical temperature above which the vitrimer can be successfully reprocessed (Tv,eff ). Via the introduction of excess primary amines, this work can readily degrade the networks into monomeric precursors, which are in turn reacted with diamines to regenerate reprocessable networks. Photopolymerization provides unique spatiotemporal control over the network topology, thereby opening the path for further investigation of vitrimer properties. As such, this work expands the toolbox of chemical upcycling of networks and enables their wider implementation.

Correction to "ß-Phase Crystallinity, Printability, and Piezoelectric Characteristics of Polyvinylidene Fluoride (PVDF)/Poly(methyl methacrylate) (PMMA)/Cyclopentyl-polyhedral Oligomeric Silsesquioxane (Cp-POSS) Melt-Compounded Blends".

[This corrects the article DOI: 10.1021/acsapm.4c00468.].

ß-Phase Crystallinity, Printability, and Piezoelectric Characteristics of Polyvinylidene Fluoride (PVDF)/Poly(methyl methacrylate) (PMMA)/Cyclopentyl-Polyhedral Oligomeric Silsesquioxane (Cp-POSS) Melt-Compounded Blends.

Poly(vinylidene fluoride) (PVDF) is a semicrystalline polymer that exhibits unique piezoelectric characteristics along with good chemical resistance and high thermal stability. Layer-based material extrusion (MEX) 3D printing of PVDF is desired to create complex structures with piezoelectric properties; however, the melt processing of PVDF typically directs the formation of the α crystalline allomorph, which does not contribute to the piezoelectric response. In this work, PVDF was compounded with poly(methyl methacrylate) (PMMA) and cyclopentyl-polyhedral oligomeric silsesquioxane (Cp-POSS) nanostructured additives in binary and ternary blends to improve MEX printability while maintaining piezoelectric performance. Overall crystallinity and ß phase content were evaluated and quantified using a combination of attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) and differential scanning calorimetry (DSC). Enhancement of MEX printability was measured by quantifying the interlayer adhesion and warpage of printed parts. All blends studied contained a significant percentage of ß allomorph, but it could be detected by ATR-FTIR only after the removal of a thin surface layer. Inclusion of 1% Cp-POSS and up to 10% PMMA in blends with PVDF improved interlayer adhesion (2.3-3.6x) and lowered warpage of MEX printed parts compared to neat PVDF. The blend of 1% Cp-POSS/1% PMMA/PVDF was demonstrated to significantly improve the quality of MEX printed parts while showing similar piezoelectric performance to that of neat PVDF (average piezoelectric coefficient 24 pC/N). MEX printing of PVDF blends directly into usable parts with significant piezoelectric performance while reducing the challenges of printing the semicrystalline polymer opens the potential for application in a number of high value sectors.

Exploiting Partial Solubility in Partially Fluorinated Thermoplastic Blends to Improve Adhesion during Fused Deposition Modeling.

This work studies the effect of interlayer adhesion on mechanical performance of fluorinated thermoplastics produced by fused deposition modeling (FDM). Here, we study the anisotropic mechanical response of 3D-printed binary blends of poly (vinylidene fluoride) (PVDF) and poly (methyl methacrylate) (PMMA) with the isotropic mechanical response of these blends fabricated via injection molding. Various PVDF/PMMA filament compositions were produced by twin-screw extrusion and, subsequently, injection-molded or 3D printed into dog-bone shapes. Specimen mechanical and thermal properties were evaluated by mode I tensile testing and differential scanning calorimetry, respectively. Results show that higher PMMA concentration not only improved the tensile strength and decreased ductility but reduced PVDF crystallization. As expected, injection-molded samples revealed better mechanical properties compared to 3D printed specimens. Interestingly, 3D printed blends with lower PMMA content demonstrated better diffusion (adhesion) across interfaces than those with a higher amount of PMMA. The present study provides new findings that may be used to tune mechanical response in 3D printed fluorinated thermoplastics, particularly for energy applications.