Regulating Lateral Adsorbate Interaction for Efficient Electroreforming of Bio-polyols.

Tailoring the selectivity at the electrode-electrolyte interface is one of the greatest challenges for heterogeneous electrocatalysis, and complementary strategies to catalyst structural designs need to be developed. Herein, we proposed a new strategy of controlling the electrocatalytic pathways by lateral adsorbate interaction for the bio-polyol oxidation. Redox-innocent 1,1,1,3,3,3-hexafluoro-2-propanol (HFIP) anion possesses the alcoholic property that facilely adsorbs on the nickel oxyhydroxide catalyst, but is resistant to oxidation due to the electron-withdrawing trifluoromethyl groups. The alien HFIP adsorbents can compete with bio-polyols and form a mixed adsorbate layer that creates lateral adsorbate interaction via hydrogen bonding, which achieved a >2-fold enhancement of the oxalate selectivity to 55 % for the representative glycerol oxidation and can be extended to various bio-polyol substrates. Through in situ spectroscopic analysis and DFT calculation on the glycerol oxidation, we reveal that the hydrogen-bonded adsorbate interaction can effectively tune the adsorption energies and tailor the oxidation capabilities toward the targeted products. This work offers an additional perspective of tuning electrocatalytic reactions via introducing redox-innocent adsorbates to create lateral adsorbate interactions.

Engineering a Dual-Receptor Targeted Multivalent Probe for Enhanced Magnetic Resonance Imaging of Metastatic Cancer.

Noninvasive monitoring of cancer metastasis is essential to improving clinical outcomes. Molecular MRI (mMRI) is a special implementation of noninvasive molecular imaging that promises to offer a powerful means for early detection and analysis of pathological states of cancer by tracking molecular markers. However, this is often hindered by the challenging issue of obtaining transformable mMRI contrast agents with high sensitivity, specificity, and broad applicability, given the high tumor heterogeneity and complex metastatic features. Herein, we present a dual-receptor targeted, multivalent recognition strategy and report a new class of mMRI probes for enhanced imaging of metastatic cancer. This probe is designed by covalently conjugating Gd-chelate with phenylboronic acid and an aptamer via an affordable polymerization chemistry to concurrently target two different cell-membrane receptors that are commonly overexpressed and highly implicated in both tumorigenesis and metastasis. Moreover, the polymerization chemistry allows the probe to contain a bunch of targeting ligands and signal reporters in a single chain, which not only leads to more than 2-fold enhancement in T1 relaxivity at 1.5 T compared to the commercial contrast agent but also enables it to actively target tumor cells in a multivalent recognition manner, contributing to a much higher imaging contrast than single-receptor targeted probes and the commercial agent in mouse models with lung metastases, yet without inducing systemic side effects. We expect this study to offer a useful molecular tool to promote transformable applications of mMRI and a better understanding of molecular mechanisms involved in cancer development.

Recent advances in nanomedicine for metabolism-targeted cancer therapy.

Metabolism denotes the sum of biochemical reactions that maintain cellular function. Different from most normal differentiated cells, cancer cells adopt altered metabolic pathways to support malignant properties. Typically, almost all cancer cells need a large number of proteins, lipids, nucleotides, and energy in the form of ATP to support rapid division. Therefore, targeting tumour metabolism has been suggested as a generic and effective therapy strategy. With the rapid development of nanotechnology, nanomedicine promises to have a revolutionary impact on clinical cancer therapy due to many merits such as targeting, improved bioavailability, controllable drug release, and potentially personalized treatment compared to conventional drugs. This review comprehensively elucidates recent advances of nanomedicine in targeting important metabolites such as glucose, glutamine, lactate, cholesterol, and nucleotide for effective cancer therapy. Furthermore, the challenges and future development in this area are also discussed.

Topological Single-stranded DNA Encoding and Programmable Assembly of Molecular Nanostructures for NIR-II Cancer Theranostics.

Molecular nanotechnology promises to offer privileged access to developing NIR-II materials with precise structural and functional manipulation for transformable theranostic applications. However, the lack of an affordable, yet general, method makes this goal currently inaccessible. By virtue of the intriguing nucleic acid chemistry, here we present an artificial base-directed topological single-strand DNA encoding design that enables one-step synthesis of valence-controlled NIR-II molecular nanostructures and spatial assembly of these nanostructures to modulate their behaviors in living systems. As proof-of-concept studies, we construct ultrasmall Ag2 S quantum dots and pH-responsive, size-tunable CuS assemblies for in vivo NIR-II fluorescence imaging and deep tumor photothermal therapy. This work paves a new way for creating functionally diversified architectures and broadens the scope of DNA-encoded material engineering.

Nature-Inspired Photocatalytic Azo Bond Cleavage with Red Light.

The emerging field of photoredox catalysis in mammalian cells enables spatiotemporal regulation of a wealth of biological processes. However, the selective cleavage of stable covalent bonds driven by low-energy visible light remains a great challenge. Herein, we report that red light excitation of a commercially available dye, abbreviated NMB+, leads to catalytic cleavage of stable azo bonds in both aqueous solutions and hypoxic cells and hence a means to photodeliver drugs or functional molecules. Detailed mechanistic studies reveal that azo bond cleavage is triggered by a previously unknown consecutive two-photon process. The first photon generates a triplet excited state, 3NMB+*, that is reductively quenched by an electron donor to generate a protonated NMBH•+. The NMBH•+ undergoes a disproportionation reaction that yields the initial NMB+ and two-electron-reduced NMBH (i.e., leuco-NMB, abbreviated as LNMB). Interestingly, LNMB forms a charge transfer complex with all four azo substrates that possess an intense absorption band in the red region. A second red photon induces electron transfer from LNMB to the azo substrate, resulting in azo bond cleavage. The charge transfer complex mediated two-photon catalytic mechanism reported herein is reminiscent of the flavin-dependent natural photoenzyme that catalyzes bond cleavage reactions with high-energy photons. The red-light-driven photocatalytic strategy offers a new approach to bioorthogonal azo bond cleavage for photodelivery of drugs or functional molecules.

Aptamer Conjugate-Based Ratiometric Fluorescent Probe for Precise Imaging of Therapy-Induced Cancer Senescence.

Therapy-induced cellular senescence has been increasingly recognized as a key mechanism to promote various aspects of carcinogenesis in a nonautonomous manner. Thus, real-time imaging monitoring of cellular senescence during cancer therapy is imperative not only to further elucidate its roles in cancer progression but also to provide guidance for medical management of cancer. However, it has long been a challenging task due to the lack of effective imaging molecule tools with high specificity and accuracy toward cancer senescence. Herein, we report the rational design, synthesis, and evaluation of an aptamer conjugate-based ratiometric fluorescent probe for precise imaging of therapy-induced cancer senescence. Unlike traditional senescence imaging systems, our probe targets two senescence-associated markers at both cellular and subcellular dimensions, namely, aptamer-mediated membrane marker recognition for active cell targeting and lysosomal marker-triggered ratiometric fluorescence changes of two cyanine dyes for site-specific, high-contrast imaging. Moreover, such a two-channel fluorescence response is activated after a one-step reaction and at the same location, avoiding the diffusion-caused signal decay previously encountered in dual-marker activated probes, contributing to spatiotemporally specific imaging of therapy-induced cancer senescence in living cells and three-dimensional multicellular tumor spheroids. This work may offer a valuable tool for a basic understanding of cellular senescence in cancer biology and interventions.

Electrochemical Synthesis of Functionalized Graphene/Polyaniline Composite Using Two Electrode Configuration for Supercapacitors.

An effective approach for the large-scale fabrication of conducting polyaniline (PANI) using in situ anodic electrochemical polymerization on nickel foam which had been coated in aryl diazonium salt (ADS)-modified graphene (ADS-G). In the present work, ADS-G was used as a high surface-area support material for the electrochemical polymerization of PANI. The electrochemical performances of the ADS-G/PANI composites exhibited better suitability as supercapacitor electrode materials than those of the PANI. The ADS-G/PANI composites achieved a specific capacitance of 528 F g-1, which was higher than that of PANI (266 F g-1) due to excellent electrode-electrolyte interaction and the synergistic effect of electrical conductivity between ADS-G and PANI in the composites. These findings suggest that the ADS-G/PANI composites are a suitable composite for potential supercapacitor applications.

The Identity of Nickel Peroxide as a Nickel Superoxyhydroxide for Enhanced Electrocatalysis.

Nickel peroxides are a class of stoichiometric oxidants that can selectively oxidize various organic compounds, but their molecular level structure remained elusive until now. Herein, we utilized structural prediction using the Stochastic Surface Walking method based on a neural network potential energy surface and advanced characterization using the as-synthesized nickel peroxide to unravel its chemical identity as the bridging superoxide containing nickel hydroxide, or nickel superoxyhydroxide. Superoxide incorporation tunes the local chemical environment of nickel and oxygen beyond the conventional Bode plot, offering a 6.4-fold increase in the electrocatalytic activity of urea oxidation. A volcanic dependence of the activity on the oxygen equivalents leads to the proposed active site of the Ni(OO)(OH)Ni five-membered ring. This work not only unveils the possible structures of nickel peroxides but also emphasizes the significance of tailoring the oxygen environment for advanced catalysis.

Chemical Amplification-Enabled Topological Modification of Nucleic Acid Aptamers for Enhanced Cancer-Targeted Theranostics.

Site-specific chemical conjugation has long been a challenging endeavor in the field of ligand-directed modification to produce homogeneous conjugates for precision medicine. Here, we develop a chemical amplification-enabled topological modification (Chem-ATM) methodology to establish a versatile platform for the programmable modification of nucleic acid aptamers with designated functionalities. Differing from conventional conjugation strategies, a three-dimensional artificial base is designed in Chem-ATM as a chemical amplifier, giving access to structurally and functionally diversified conjugation of aptamers, with precise control over loading capacity but in a sequence-independent manner. Meanwhile, the sp3 hybridized atom-containing amplifier enables planar-to-stereo conformational transformation of the entire conjugate, eliciting high steric hindrance against enzymatic degradation in complex biological environments. The versatility of Chem-ATM is successfully demonstrated by its delivery of anticancer drugs and imaging agents for enhanced therapy and high-contrast noninvasive tumor imaging in xenograft and orthotopic tumor models. This study offers a different perspective for ligand-directed chemical conjugation to enrich the molecular toolbox for bioimaging and drug development.

In Situ Structure of a Mo-Doped Pt-Ni Catalyst during Electrochemical Oxygen Reduction Resolved from Machine Learning-Based Grand Canonical Global Optimization.

Pt-Ni alloy is by far the most active cathode material for oxygen reduction reaction (ORR) in the proton-exchange membrane fuel cell, and the addition of a tiny amount of a third-metal Mo can significantly improve the catalyst durability and activity. Here, by developing machine learning-based grand canonical global optimization, we are able to resolve the in situ structures of this important three-element alloy system under ORR conditions and identify their correlations with the enhanced ORR performance. We disclose the bulk phase diagram of Pt-Ni-Mo alloys and determine the surface structures under the ORR reaction conditions by exploring millions of likely structure candidates. The pristine Pt-Ni-Mo alloy surfaces are shown to undergo significant structure reconstruction under ORR reaction conditions, where a surface-adsorbed MoO4 monomer or Mo2O x dimers cover the Pt-skin surface above 0.9 V vs RHE and protect the surface from Ni leaching. The physical origins are revealed by analyzing the electronic structure of O atoms in MoO4 and on the Pt surface. In viewing the role of high-valence transition metal oxide clusters, we propose a set of quantitative measures for designing better catalysts and predict that six elements in the periodic table, namely, Mo, Tc, Os, Ta, Re, and W, can be good candidates for alloying with PtNi to improve the ORR catalytic performance. We demonstrate that machine learning-based grand canonical global optimization is a powerful and generic tool to reveal the catalyst dynamics behavior in contact with a complex reaction environment.

Ligand vacancy channels in pillared inorganic-organic hybrids for electrocatalytic organic oxidation with enzyme-like activities.

Simultaneously achieving abundant and well-defined active sites with high selectivity has been one of the ultimate goals for heterogeneous catalysis. Herein, we construct a class of Ni hydroxychloride-based inorganic-organic hybrid electrocatalysts with the inorganic Ni hydroxychloride chains pillared by the bidentate N-N ligands. The precise evacuation of N-N ligands under ultrahigh-vacuum forms ligand vacancies while partially retaining some ligands as structural pillars. The high density of ligand vacancies forms the active vacancy channel with abundant and highly-accessible undercoordinated Ni sites, exhibiting 5-25 fold and 20-400 fold activity enhancement compared to the hybrid pre-catalyst and standard ß-Ni(OH)2 for the electrochemical oxidation of 25 different organic substrates, respectively. The tunable N-N ligand can also tailor the sizes of the vacancy channels to significantly impact the substrate configuration leading to unprecedented substrate-dependent reactivities on hydroxide/oxide catalysts. This approach bridges heterogenous and homogeneous catalysis for creating efficient and functional catalysis with enzyme-like properties.

Dual-Parameter Recognition-Directed Design of the Activatable Fluorescence Probe for Precise Imaging of Cellular Senescence.

Specific imaging of cellular senescence emerges as a promising strategy for early diagnosis and treatment of various age-related diseases. The currently available imaging probes are routinely designed by targeting a single senescence-related marker. However, the inherently high heterogeneity of senescence makes them inaccessible to achieve specific and accurate detection of broad-spectrum cellular senescence. Here, we report the design of a dual-parameter recognition fluorescent probe for precise imaging of cellular senescence. This probe remains silent in non-senescent cells, yet produces bright fluorescence after sequential responses to two senescence-associated markers, namely, SA-ß-gal and MAO-A. In-depth studies reveal that this probe allows for high-contrast imaging of senescence, independent of the cell source or stress type. More impressively, such dual-parameter recognition design further allows it to distinguish senescence-associated SA-ß-gal/MAO-A from cancer-related ß-gal/MAO-A, compared to commercial or previous single-marker detection probes. This study offers a valuable molecular tool for imaging cellular senescence, which is expected to significantly expand the basic studies on senescence and facilitate advances of senescence-related disease theranostics.

Engineering Hierarchical Recognition-Mediated Senolytics for Reliable Regulation of Cellular Senescence and Anti-Atherosclerosis Therapy.

Precise regulation of vascular senescence represents a far-reaching strategy to combat age-related diseases. However, the high heterogeneity of senescence, alongside the lack of targeting and potent senolytics, makes it very challenging. Here we report a molecular design to tackle this challenge through multidimensional, hierarchical recognition of three hallmarks commonly shared among senescence, namely, aptamer-mediated recognition of a membrane marker for active cell targeting, a self-immolative linker responsive to lysosomal enzymes for switchable drug release, and a compound against antiapoptotic signaling for clearance. Such senolytic can target and trigger severe cell apoptosis in broad-spectrum senescent endothelial cells, and importantly, distinguish them from the quiescent state. Its potential for in vivo treatment of vascular diseases is successfully illustrated in a model of atherosclerosis, with effective suppression of the plaque progression yet negligible side effects.

Recent Advances in Strategies for Imaging Detection and Intervention of Cellular Senescence.

Cellular senescence is a stable cell cycle arrest state that can be triggered by a wide range of intrinsic or extrinsic stresses. Increased burden of senescent cells in various tissues is thought to contribute to aging and age-related diseases. Thus, the detection and interventions of senescent cells are critical for longevity and treatment of disease. However, the highly heterogeneous feature of senescence makes it challenging for precise detection and selective clearance of senescent cells in different age-related diseases. To address this issue, considerable efforts have been devoted to developing senescence-targeting molecular theranostic strategies, based on the potential biomarkers of cellular senescence. Herein, we review recent advances in the field of anti-senescence research and highlight the specific visualization and elimination of senescent cells. Additionally, the challenges in this emerging field are outlined.

Efficient Oxygen Vacancy Defect Engineering for Enhancing Visible-Light Photocatalytic Performance over SnO2-x Ultrafine Nanocrystals.

Regardless of its good electron-transfer ability and chemical stability, pure Zn2SnO4 (ZSO) still has intrinsic deficiencies of a narrow spectral response region, poor absorption ability, and high photo-activated carrier recombination rate. Aiming to overcome the deficiencies above-mentioned, we designed a facile hydrothermal route for etching ZSO nanoparticles in a dilute acetic acid solution, through which efficient oxygen vacancy defect engineering was accomplished and SnO2-x nanocrystals were obtained with an ultrafine particle size. In comparison with the untreated ZSO nanoparticles, the specific surface area of SnO2-x nanocrystals was substantially enlarged, subsequently leading to the notable augmentation of active sites for the photo-degradation reaction. Aside from the above, it is worth noting that SnO2-x nanocrystals were endowed with a broad spectral response, enhancing light absorption capacity and the photo-activated carrier transfer rate with the aid of oxygen vacancy defect engineering. Accordingly, SnO2-x nanocrystals exhibited significantly enhanced photoactivity toward the degradation of the organic dye rhodamine B (RhB), which could be imputed to the synergistic effect of increasing active sites, intensified visible-light harvesting, and the separation rate of the photo-activated charge carrier caused by the oxygen vacancy defect engineering. In addition, these findings will inspire us to open up a novel pathway to design and prepare oxide compound photocatalysts modified by oxygen vacancy defects in pursuing excellent visible-light photoactivity.

Effectiveness of eHealth Self-management Interventions in Patients With Heart Failure: Systematic Review and Meta-analysis.

BACKGROUND: Heart failure (HF) is a common clinical syndrome associated with substantial morbidity, a heavy economic burden, and high risk of readmission. eHealth self-management interventions may be an effective way to improve HF clinical outcomes. OBJECTIVE: The aim of this study was to systematically review the evidence for the effectiveness of eHealth self-management in patients with HF. METHODS: This study included only randomized controlled trials (RCTs) that compared the effects of eHealth interventions with usual care in adult patients with HF using searches of the EMBASE, PubMed, CENTRAL (Cochrane Central Register of Controlled Trials), and CINAHL databases from January 1, 2011, to July 12, 2022. The Cochrane Risk of Bias tool (RoB 2) was used to assess the risk of bias for each study. The Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) criteria were used to rate the certainty of the evidence for each outcome of interest. Meta-analyses were performed using Review Manager (RevMan v.5.4) and R (v.4.1.0 x64) software. RESULTS: In total, 24 RCTs with 9634 participants met the inclusion criteria. Compared with the usual-care group, eHealth self-management interventions could significantly reduce all-cause mortality (odds ratio [OR] 0.83, 95% CI 0.71-0.98, P=.03; GRADE: low quality) and cardiovascular mortality (OR 0.74, 95% CI 0.59-0.92, P=.008; GRADE: moderate quality), as well as all-cause readmissions (OR 0.82, 95% CI 0.73-0.93, P=.002; GRADE: low quality) and HF-related readmissions (OR 0.77, 95% CI 0.66-0.90, P<.001; GRADE: moderate quality). The meta-analyses also showed that eHealth interventions could increase patients' knowledge of HF and improve their quality of life, but there were no statistically significant effects. However, eHealth interventions could significantly increase medication adherence (OR 1.82, 95% CI 1.42-2.34, P<.001; GRADE: low quality) and improve self-care behaviors (standardized mean difference -1.34, 95% CI -2.46 to -0.22, P=.02; GRADE: very low quality). A subgroup analysis of primary outcomes regarding the enrolled population setting found that eHealth interventions were more effective in patients with HF after discharge compared with those in the ambulatory clinic setting. CONCLUSIONS: eHealth self-management interventions could benefit the health of patients with HF in various ways. However, the clinical effects of eHealth interventions in patients with HF are affected by multiple aspects, and more high-quality studies are needed to demonstrate effectiveness.

Artificial Nucleobase-Directed Programmable Synthesis and Assembly of Amphiphilic Nucleic Acids as an All-in-One Platform for Cation-Free siRNA Delivery.

Efficient transport of nucleic acid therapeutics into targeted cells is the key step of genetic modulation in disease treatment. Nowadays, delivery systems strongly rely on cationic materials, but how to balance the trade-off between effectiveness and toxicity of these exogenous materials remains incredibly challenging. Here, we take inspiration from nucleic acid chemistry and introduce a new concept of amphiphilic nucleic acids (ANAs), as an all-in-one platform for cation-free nucleic acid delivery, by programmatically conjugating two different artifical nucleobases with sequence-independent activities. Specifically, the hydrophilic artificial nucleobases in ANAs act as both delivery vectors and therapeutic cargos for integrated benefits, while the hydrophobic nucleobases enable molecular self-assembly for improved stability and endosomal membrane oxidation for enhanced endosomal escape. By virtue of these merits, this platform is successfully used for short interference RNA (siRNA) delivery, which demonstrates a high siRNA loading capacity, rapid cellular uptake, and efficient endosomal escape, eliciting remarkable gene silencing and synergistic inhibitory effects on cancer cell proliferation and migration. This work is a case study in exploiting the basis of nucleic acid chemistry to afford new paradigms for advanced cancer theranostics.

The effectiveness of eHealth self-management interventions in patients with chronic heart failure: Protocol for a systematic review and meta-analysis.

PURPOSE: The objective of this paper is to design a protocol for a systematic review and meta-analysis on the effectiveness of self-management interventions in patients with chronic heart failure. METHODS: The protocol is developed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The protocol has been registered in PROSPERO (CRD42021246973). Base on the population, intervention, comparator, and outcome (PICO) framework, our research questions are: 1) What are the effects of eHealth self-management interventions on patients with chronic heart failure? 2) What factors of interventions might affect outcomes? The process includes: 1) search strategy and inclusion criteria; 2) data extraction; 3) risk of bias assessment and 4) data analysis. Searching process and data extraction will be guided by Cochrane Handbook for Systematic Reviews of Interventions. We will use Cochrane Risk of Bias tool to assess the risk of bias. The data analysis will be performed using Metafor package in R. CONCLUSIONS: This systemic review will synthesize the current evidence and identify gaps. Findings in the meta-analysis will provide guidance for designing a more effective self-management intervention for patients with chronic heart failure in future.

Predicting Mortality in Intensive Care Unit Patients With Heart Failure Using an Interpretable Machine Learning Model: Retrospective Cohort Study.

BACKGROUND: Heart failure (HF) is a common disease and a major public health problem. HF mortality prediction is critical for developing individualized prevention and treatment plans. However, due to their lack of interpretability, most HF mortality prediction models have not yet reached clinical practice. OBJECTIVE: We aimed to develop an interpretable model to predict the mortality risk for patients with HF in intensive care units (ICUs) and used the SHapley Additive exPlanation (SHAP) method to explain the extreme gradient boosting (XGBoost) model and explore prognostic factors for HF. METHODS: In this retrospective cohort study, we achieved model development and performance comparison on the eICU Collaborative Research Database (eICU-CRD). We extracted data during the first 24 hours of each ICU admission, and the data set was randomly divided, with 70% used for model training and 30% used for model validation. The prediction performance of the XGBoost model was compared with three other machine learning models by the area under the curve. We used the SHAP method to explain the XGBoost model. RESULTS: A total of 2798 eligible patients with HF were included in the final cohort for this study. The observed in-hospital mortality of patients with HF was 9.97%. Comparatively, the XGBoost model had the highest predictive performance among four models with an area under the curve (AUC) of 0.824 (95% CI 0.7766-0.8708), whereas support vector machine had the poorest generalization ability (AUC=0.701, 95% CI 0.6433-0.7582). The decision curve showed that the net benefit of the XGBoost model surpassed those of other machine learning models at 10%~28% threshold probabilities. The SHAP method reveals the top 20 predictors of HF according to the importance ranking, and the average of the blood urea nitrogen was recognized as the most important predictor variable. CONCLUSIONS: The interpretable predictive model helps physicians more accurately predict the mortality risk in ICU patients with HF, and therefore, provides better treatment plans and optimal resource allocation for their patients. In addition, the interpretable framework can increase the transparency of the model and facilitate understanding the reliability of the predictive model for the physicians.

Relationship between the dietary inflammatory index and kidney stone prevalence.

PURPOSE: This study aimed to investigate the association between the dietary inflammatory index and lifetime kidney stone prevalence. METHODS: We performed a cross-sectional study utilizing the 2013-2014 National Health and Nutrition Examination Survey data. Data were available on 2192 participants aged > 20 years with a complete kidney stone history and 24 h dietary intake interview. Weighted multivariable linear regression, subgroup analyses, and interaction terms were employed. Covariates including age, race, sex, energy and protein intake, total serum calcium, serum iron, PIR, phosphorus, serum/urine creatinine, HDL, glucose, diastolic and systolic pressure, education level, eGFR, BMI, albuminuria, diabetes, smoking status, and marital status were hierarchically adjusted in three different models. RESULTS: The average dietary inflammatory index for 2192 participants was - 0.11 ± 1.73, ranging from - 4.52 to 4.28. In the fully adjusted model, participants in the highest dietary inflammatory index tertile (the most proinflammatory) had 72% higher odds of the lifetime prevalence of kidney stones than those in tertile 1 (OR = 1.72, 95% CI: 1.03, 2.88, P = 0.0367). Subgroup analysis showed that the association between the dietary inflammatory index and kidney stone history was only statistically significant in the younger age (age ≥ 60), female, Mexican American groups, married people or people without diabetes, hypertension, low eGFR, and albuminuria. CONCLUSIONS: There is a positive association between the dietary inflammatory index and self-reported kidney stones in US adults, which indicates that dietary patterns could greatly impact kidney stone prevalence.