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Abstract Human hallmarks of sarcopenia include muscle weakness and a blunted response to exercise. Nicotinamide N-methyltransferase inhibitors (NNMTis) increase strength and promote the regenerative capacity of aged muscle, thus offering a promising treatment for sarcopenia. Since human hallmarks of sarcopenia are recapitulated in aged (24-month-old) mice, we treated mice from 22 to 24 months of age with NNMTi, intensive exercise, or a combination of both, and compared skeletal muscle adaptations, including grip strength, longitudinal running capacity, plantarflexor peak torque, fatigue, and muscle mass, fiber type, cross-sectional area, and intramyocellular lipid (IMCL) content. Exhaustive proteome and metabolome analyses were completed to identify the molecular mechanisms underlying the measured changes in skeletal muscle pathophysiology. Remarkably, NNMTi-treated aged sedentary mice showed ~ 40% greater grip strength than sedentary controls, while aged exercised mice only showed a 20% increase relative to controls. Importantly, the grip strength improvements resulting from NNMTi treatment and exercise were additive, with NNMTi-treated exercised mice developing a 60% increase in grip strength relative to sedentary controls. NNMTi treatment also promoted quantifiable improvements in IMCL content and, in combination with exercise, significantly increased gastrocnemius fiber CSA. Detailed skeletal muscle proteome and metabolome analyses revealed unique molecular mechanisms associated with NNMTi treatment and distinct molecular mechanisms and cellular processes arising from a combination of NNMTi and exercise relative to those given a single intervention. These studies suggest that NNMTi-based drugs, either alone or combined with exercise, will be beneficial in treating sarcopenia and a wide range of age-related myopathies.

Abstract In-vivo estimation of mechanical properties of the myocardium is essential for patient-specific diagnosis and prognosis of cardiac disease involving myocardial remodeling, including myocardial infarction and heart failure with preserved ejection fraction. Current approaches use time-consuming finite-element (FE) inverse methods that involve reconstructing and meshing the heart geometry, imposing measured loading, and conducting computationally expensive iterative FE simulations. In this paper, we propose a machine learning (ML) model that feasibly and accurately predicts passive myocardial properties directly from select geometric, architectural, and hemodynamic measures, thus bypassing exhaustive steps commonly required in cardiac FE inverse problems. Geometric and fiber-orientation features were chosen to be readily obtainable from standard cardiac imaging protocols. The end-diastolic pressure-volume relationship (EDPVR), which can be obtained using a single-point pressure-volume measurement, was used as a hemodynamic (loading) feature. A comprehensive ML training dataset in the geometry-architecture-loading space was generated, including a wide variety of partially synthesized rodent heart geometry and myofiber helicity possibilities, and a broad range of EDPVRs obtained using forward FE simulations. Latin hypercube sampling was used to create 2500 examples for training, validation, and testing. A multi-layer feed-forward neural network (MFNN) was used as a deep learning agent to train the ML model. The model showed excellent performance in predicting stiffness parameters $$a_f$$ a f and $$b_f$$ b f associated with fiber direction ( $$R^2_{a_f}=99.471\%$$ R a f 2 = 99.471 % and $$R^2_{b_f}=92.837\%$$ R b f 2 = 92.837 % ). After conducting permutation feature importance analysis, the ML performance further improved for $$b_f$$ b f ( $$R^2_{b_f}=96.240\%$$ R b f 2 = 96.240 % ), and the left ventricular volume and endocardial area were found to be the most critical geometric features for accurate predictions. The ML model predictions were evaluated further in two cases: (i) rat-specific stiffness data measured using ex-vivo mechanical testing, and (ii) patient-specific estimation using FE inverse modeling. Excellent agreements with ML predictions were found for both cases. The trained ML model offers a feasible technology to estimate patient-specific myocardial properties, thus, bridging the gap between EDPVR, as a confounded organ-level metric for tissue stiffness, and intrinsic tissue-level properties. These properties provide incremental information relative to traditional organ-level indices for cardiac function, improving the clinical assessment and prognosis of cardiac diseases.

Abstract Treatment with a nicotinamide N-methyltransferase inhibitor (NNMTi; 5-amino-1-methylquinolinium) combined with low-fat diet (LD) promoted dramatic whole-body adiposity and weight loss in diet-induced obese (DIO) mice, rapidly normalizing these measures to age-matched lean animals, while LD switch alone was unable to restore these measures to age-matched controls in the same time frame. Since mouse microbiome profiles often highly correlate with body weight and fat composition, this study was designed to test whether the cecal microbiomes of DIO mice treated with NNMTi and LD were comparable to the microbiomes of age-matched lean counterparts and distinct from microbiomes of DIO mice maintained on a high-fat Western diet (WD) or subjected to LD switch alone. There were minimal microbiome differences between lean and obese controls, suggesting that diet composition and adiposity had limited effects. However, DIO mice switched from an obesity-promoting WD to an LD (regardless of treatment status) displayed several genera and phyla differences compared to obese and lean controls. While alpha diversity measures did not significantly differ between groups, beta diversity principal coordinates analyses suggested that mice from the same treatment group were the most similar. K-means clustering analysis of amplicon sequence variants by animal demonstrated that NNMTi-treated DIO mice switched to LD had a distinct microbiome pattern that was highlighted by decreased Erysipelatoclostridium and increased Lactobacillus relative abundances compared to vehicle counterparts; these genera are tied to body weight and metabolic regulation. Additionally, Parasutterella relative abundance, which was increased in both the vehicle- and NNMTi-treated LD-switched groups relative to the controls, significantly correlated with several adipose tissue metabolites’ abundances. Collectively, these results provide a novel foundation for future investigations.

Abstract Obesity is a large and growing global health problem with few effective therapies. The present study investigated metabolic and physiological benefits of nicotinamide N-methyltransferase inhibitor (NNMTi) treatment combined with a lean diet substitution in diet-induced obese mice. NNMTi treatment combined with lean diet substitution accelerated and improved body weight and fat loss, increased whole-body lean mass to body weight ratio, reduced liver and epididymal white adipose tissue weights, decreased liver adiposity, and improved hepatic steatosis, relative to a lean diet substitution alone. Importantly, combined lean diet and NNMTi treatment normalized body composition and liver adiposity parameters to levels observed in age-matched lean diet control mice. NNMTi treatment produced a unique metabolomic signature in adipose tissue, with predominant increases in ketogenic amino acid abundance and alterations to metabolites linked to energy metabolic pathways. Taken together, NNMTi treatment’s modulation of body weight, adiposity, liver physiology, and the adipose tissue metabolome strongly support it as a promising therapeutic for obesity and obesity-driven comorbidities.

Root canal disinfection is one of the most important factors governing success of root canal treatment, especially when regenerative strategies are used. This study evaluated the efficacy of 5 intracanal medicaments against mature biofilms of Enterococcus fecalis in vitro: Light activated curcumin, triple antibiotic paste (TAP), double antibiotic paste (DAP), chlorhexidine, calcium hydroxide. Untreated teeth with biofilms served as controls. Confocal microscopy was used to analyse the biofilm mass and percentage of live/dead bacteria within the root canal as well as dentinal tubules. Dentinal shavings obtained from the root canal walls (at 200 and 400 microns depth) were used to quantify the colony forming units/mL. The results showed that light activated curcumin and triple antibiotic paste brought about complete disruption of the biofilm structure (P < 0.05) while chlorhexidine and calcium hydroxide were not significantly different from the control (P > 0.05). Light activated curcumin brought about the highest percentage of dead cells at both depths, but this was not significantly different from triple antibiotic paste (P > 0.05). Curcumin, TAP and DAP brought about a significant reduction of CFU/mL at both depths compared to the control and other groups (P < 0.05). Light activated curcumin brought about a 7 log reduction of bacteria at both depths.