Small extracellular vesicle-mediated CRISPR-Cas9 RNP delivery for cardiac-specific genome editing.

Myocardial infarction (MI) is a major cause of morbidity and mortality worldwide. Although clustered regularly interspaced short palindromic repeats (CRISPR)-associated protein 9 (Cas9) gene editing holds immense potential for genetic manipulation, its clinical application is hindered by the absence of an efficient heart-targeted drug delivery system. Herein, we developed CRISPR-Cas9 ribonucleoprotein (RNP)-loaded extracellular vesicles (EVs) conjugated with cardiac-targeting peptide (T) for precise cardiac-specific genome editing. RNP complexes containing Cas9 and single guide RNA targeting miR-34a, an MI-associated molecular target, were loaded into EVs (EV@RNP). Gene editing by EV@RNP attenuated hydrogen peroxide-induced apoptosis in cardiomyocytes via miR-34a inhibition, evidenced by increased B-cell lymphoma 2 levels, decreased Bcl-2-associated X protein levels, and the cleavage of caspase-3. Additionally, to improve cardiac targeting in vivo, we used click chemistry to form functional T-EV@RNP by conjugating T peptides to EV@RNP. Consequently, T-EV@RNP-mediated miR-34a genome editing might exert a protective effect against MI, reducing apoptosis, ameliorating MI injury, and facilitating the recovery of cardiac function. In conclusion, the genome editing delivery system established by loading CRISPR/Cas9 RNP with cardiac-targeting EVs is a powerful approach for precise and tissue-specific gene therapy for cardiovascular disease.

Engineered small extracellular vesicle-mediated NOX4 siRNA delivery for targeted therapy of cardiac hypertrophy.

Small-interfering RNA (siRNA) therapy is considered a powerful therapeutic strategy for treating cardiac hypertrophy, an important risk factor for subsequent cardiac morbidity and mortality. However, the lack of safe and efficient in vivo delivery of siRNAs is a major challenge for broadening its clinical applications. Small extracellular vesicles (sEVs) are a promising delivery system for siRNAs but have limited cell/tissue-specific targeting ability. In this study, a new generation of heart-targeting sEVs (CEVs) has been developed by conjugating cardiac-targeting peptide (CTP) to human peripheral blood-derived sEVs (PB-EVs), using a simple, rapid and scalable method based on bio-orthogonal copper-free click chemistry. The experimental results show that CEVs have typical sEVs properties and excellent heart-targeting ability. Furthermore, to treat cardiac hypertrophy, CEVs are loaded with NADPH Oxidase 4 (NOX4) siRNA (siNOX4). Consequently, CEVs@siNOX4 treatment enhances the in vitro anti-hypertrophic effects by CEVs with siRNA protection and heart-targeting ability. In addition, the intravenous injection of CEVs@siNOX4 into angiotensin II (Ang II)-treated mice significantly improves cardiac function and reduces fibrosis and cardiomyocyte cross-sectional area, with limited side effects. In conclusion, the utilization of CEVs represents an efficient strategy for heart-targeted delivery of therapeutic siRNAs and holds great promise for the treatment of cardiac hypertrophy.

Neuropharmacological computational analysis of longitudinal electroencephalograms in clozapine-treated patients with schizophrenia using hierarchical dynamic causal modeling.

The hierarchical characteristics of the brain are prominent in the pharmacological treatment of psychiatric diseases, primarily targeting cellular receptors that extend upward to intrinsic connectivity within a region, interregional connectivity, and, consequently, clinical observations such as an electroencephalogram (EEG). To understand the long-term effects of neuropharmacological intervention on neurobiological properties at different hierarchical levels, we explored long-term changes in neurobiological parameters of an N-methyl-D-aspartate canonical microcircuit model (CMM-NMDA) in the default mode network (DMN) and auditory hallucination network (AHN) using dynamic causal modeling of longitudinal EEG in clozapine-treated patients with schizophrenia. The neurobiological properties of the CMM-NMDA model associated with symptom improvement in schizophrenia were found across hierarchical levels, from a reduced membrane capacity of the deep pyramidal cell and intrinsic connectivity with the inhibitory population in DMN and intrinsic and extrinsic connectivity in AHN. The medication duration mainly affects the intrinsic connectivity and NMDA time constant in DMN. Virtual perturbation analysis specified the contribution of each parameter to the cross-spectral density (CSD) of the EEG, particularly intrinsic connectivity and membrane capacitances for CSD frequency shifts and progression. It further reveals that excitatory and inhibitory connectivity complements frequency-specific CSD changes, notably the alpha frequency band in DMN. Positive and negative synergistic interactions exist between neurobiological properties primarily within the same region in patients treated with clozapine. The current study shows how computational neuropharmacology helps explore the multiscale link between neurobiological properties and clinical observations and understand the long-term mechanism of neuropharmacological intervention reflected in clinical EEG.

Nitrate removal rates, isotopic fractionation, and denitrifying bacteria in a woodchip-based permeable reactive barrier system: a long-term column experiment.

This study evaluated the effectiveness of using organic carbon materials (i.e., woodchips) to remove nitrate from groundwater. The results of our flow-through column experiment, which was conducted over 1.6 years, suggested that denitrifying bacteria reduce nitrate by using it as an electron acceptor and woodchips as an electron donor. The nitrate removal rates were sufficiently high (0.39-1.04 mmol L-1 day-1) during the operation of the column. Denitrification process was supported by fractionation of nitrogen and oxygen isotopes (δ15N and δ18O), with the δ15N and δ18O values enriched from 7.4‰ and 22.3‰ to 21.2‰ and 30.4‰, respectively. Enrichment factors ([Formula: see text]) for 15 N and 18O were calculated using the Rayleigh fractionation model, with values of - 13.2‰ for ε15N and - 7.1‰ for ε18O. The fractionation ratio of 15 N to 18O was 1.9:1, confirming denitrification. The most abundant bacterial genera in the soil used for inoculation were Enterobacter (86.7%), Nitrospira (1.8%), and Arthrobacter (1.5%), while those in the column effluent were Macrococcus (37.1%), Escherichia (14.7%), and Shigella (14.6%), indicating that bacterial communities changed in response to geochemical conditions in the column. This study suggests that nitrate in groundwater can be effectively removed using woodchip-based passive treatment systems and that information on isotopic fractionation and denitrifying bacteria can be key tools to understand denitrification.

Generation of two PITX2 knock-out human induced pluripotent stem cell lines using CRISPR/Cas9 system.

PITX2 is a homeobox gene located in the human 4q25 locus and is commonly associated with atrial fibrillation (AF). Here, we generated two PITX2 knock-out human induced pluripotent stem cell (iPSC) lines using CRISPR/Cas9 genome editing. The edited iPSCs maintained fullpluripotency, normal karyotype and spontaneousdifferentiation capability. This cell line provides a suitable model for investigating the physiopathologyof PITX2 mutation in atrial fibrillation.

Generation of three TTN knock-out human induced pluripotent stem cell lines using CRISPR/Cas9 system.

TTN mutations are the common genetic cause for various types of cardiomyopathies (e.g., dilated cardiomyopathy, hypertrophic cardiomyopathy, restrictive cardiomyopathy, and arrhythmogenic right ventricular cardiomyopathy) and skeletal myopathies. Here, we generated three TTN knock-out human induced pluripotent stem cell (iPSC) lines using CRISPR/Cas9 system. These cell lines, which exhibit normal karyotype, typical morphology and pluripotency, could provide useful platform for investigating the role of TTN in associated disorders.

Generation of a heterozygous TPM1-E192K knock-in human induced pluripotent stem cell line using CRISPR/Cas9 system.

E192K missense mutation of TPM1 has been found in different types of cardiomyopathies (e.g., hypertrophic cardiomyopathy, dilated cardiomyopathy, and left ventricular non-compaction), leading to systolic dysfunction, diastolic dysfunction, and/or tachyarrhythmias. Here, we generated a heterozygous TPM1-E192K knock-in human induced pluripotent stem cell (iPSC) line using CRISPR/Cas9-based genome editing system. The cells exhibit normal karyotype, typical stem cell morphology, expression of pluripotency markers and differentiation ability into three germ layers. Accordingly, this cell line could provide a useful cell resource for exploring the pathogenic role of TPM1-E192K mutation in different types of cardiomyopathies.

Serum exosomal long noncoding RNAs as a diagnostic biomarker for atrial fibrillation.

BACKGROUND: Exosomal long noncoding RNAs (lncRNAs) are known as ideal diagnostic biomarkers of various diseases. However, there are no reports on the use of serum exosomal lncRNAs as diagnostic biomarkers for atrial fibrillation (AF). OBJECTIVE: The purpose of this study was to explore serum exosomal lncRNAs as a useful tool for diagnosing AF. METHODS: Serum exosomes from patients with persistent AF and controls were isolated using a polymer-based exosome precipitation kit. We conducted a multiphase process including screening and 2 independent validation phases. In the screening phase, serum exosomal lncRNA expression profiles were examined using RNA sequencing analysis. In 2 validation phases, we evaluated the expression levels of candidate exosomal lncRNAs using quantitative reverse transcription polymerase chain reaction. Finally, we performed different statistical and functional analyses. RESULTS: After the screening phase, we identified 26 differentially expressed lncRNAs (ie, 15 upregulated and 11 downregulated lncRNAs with a |fold change| ≥2 and P <.05) in serum exosomes from patients with persistent AF compared with controls. We then screened out 6 exosomal lncRNAs as biomarker candidates following parameters: read length ≥200 nucleotides; exon number ≥2; and coding potential score <0.1. In 2 validation phases, exosomal lncRNAs LOC105377989 and LOC107986997 were consistently upregulated in the serum of patients with persistent AF compared with controls (P <.0001). Moreover, both exosomal lncRNAs exhibited significant diagnostic validity for AF. Notably, exosomal lncRNA LOC107986997 was involved in AF-related pathophysiological mechanisms. CONCLUSION: Serum-derived exosomal lncRNA LOC107986997 could serve as a potential biomarker for AF diagnosis.

Small extracellular vesicles derived from patients with persistent atrial fibrillation exacerbate arrhythmogenesis via miR-30a-5p.

Small extracellular vesicles (sEVs) are nanometer-sized membranous vesicles that contribute to the pathogenesis of atrial fibrillation (AF). Here, we investigated the role of sEVs derived from patients with persistent AF in the pathophysiology of AF. First, we evaluated the pathological effects of sEVs derived from the peripheral blood of patients with persistent AF (AF-sEVs). AF-sEVs treatment reduced cell viability, caused abnormal Ca2+ handling, induced reactive oxygen species (ROS) production and led to increased CaMKII activation of non-paced and paced atrial cardiomyocytes. Next, we analyzed the miRNA profile of AF-sEVs to investigate which components of AF-sEVs promote arrhythmias, and we selected six miRNAs that correlated with CaMKII activation. qRT-PCR experiment identified that miR-30a-5p was significantly down-regulated in AF-sEVs, paced cardiomyocytes, and atrial tissues of patients with persistent AF. CaMKII was predicted by bioinformatics analysis as a miR-30a-5p target gene and validated by a dual luciferase reporter; hence, we evaluated the effects of miR-30a-5p on paced cardiomyocytes and validated miR-30a-5p as a pro-arrhythmic signature of AF-sEVs. Consequently, AF-sEVs-loaded with miR-30a-5p attenuated pacing-induced Ca2+-handling abnormalities, whereas AF-sEVs-loaded with anti-miR-30a-5p reversed the change in paced cardiomyocytes. Taken together, the regulation of CaMKII by miR-30a-5p revealed that miR-30a-5p is a major mediator for AF-sEVs-mediated AF pathogenesis. Accordingly, these findings suggest that sEVs derived from patients with persistent AF exacerbate arrhythmogenesis via miR-30a-5p.

Association Between Frailty-Related Factors and Depression among Older Adults.

OBJECTIVES: We analyzed the association between individual frailty-related factors and depression in older adults. METHODS: A total of 796 older adults who underwent geriatric assessments were included in this cross-sectional study. The frailty-related factors studied were grip strength, physical activity, walking speed, weight loss, and recurrent falls. Depression was based on the Geriatric Depression Scale. RESULTS: After adjustment for covariates, recurrent falls were associated with depression in males (OR 3.84, 95% CI 1.30-11.35). Among females, weakest grip strength, slow walking speed, and weight loss were associated with depression (OR 2.61, 95% CI 1.52-4.49; OR 1.78, 95% CI 1.02-3.11; and OR 2.52, 95% CI 1.17-5.44, respectively). Having more frailty-related factors was also associated with higher odds of depression. CONCLUSIONS: The associations between individual frailty-related factors and depression differed among males and females. Further prospective studies on depression and individual frailty-related factors by sex may help elucidate specific targets to be prioritized for clinical assessment and intervention. CLINICAL IMPLICATIONS: Older adults affected by depression and frailty may present different clinical manifestations based on sex, and require different treatment approaches. Clinicians should assess both physical and psychological needs for integrated care in frail older adults.

State-Dependent Effective Connectivity in Resting-State fMRI.

The human brain at rest exhibits intrinsic dynamics transitioning among the multiple metastable states of the inter-regional functional connectivity. Accordingly, the demand for exploring the state-specific functional connectivity increases for a deeper understanding of mental diseases. Functional connectivity, however, lacks information about the directed causal influences among the brain regions, called effective connectivity. This study presents the dynamic causal modeling (DCM) framework to explore the state-dependent effective connectivity using spectral DCM for the resting-state functional MRI (rsfMRI). We established the sequence of brain states using the hidden Markov model with the multivariate autoregressive coefficients of rsfMRI, summarizing the functional connectivity. We decomposed the state-dependent effective connectivity using a parametric empirical Bayes scheme that models the effective connectivity of consecutive windows with the time course of the discrete states as regressors. We showed the plausibility of the state-dependent effective connectivity analysis in a simulation setting. To test the clinical applicability, we applied the proposed method to characterize the state- and subtype-dependent effective connectivity of the default mode network in children with combined-type attention deficit hyperactivity disorder (ADHD-C) compared with age-matched, typically developed children (TDC). All 88 children were subtyped according to the occupation times (i.e., dwell times) of the three dominant functional connectivity states, independently of clinical diagnosis. The state-dependent effective connectivity differences between ADHD-C and TDC according to the subtypes and those between the subtypes of ADHD-C were expressed mainly in self-inhibition, magnifying the importance of excitation inhibition balance in the subtyping. These findings provide a clear motivation for decomposing the state-dependent dynamic effective connectivity and state-dependent analysis of the directed coupling in exploring mental diseases.

Effect of Communication and Education within the Rehabilitation Team: Therapists' and Nurses' Views.

BACKGROUND: To improve the rehabilitation team's awareness of patient mobility and participation by enhancing communication between therapists and nurses and conducting patient education. METHODS: This study used a non-equivalent control group with a non-synchronized design. To facilitate communication between therapists and nurses, we used a manual for mobility management to improve the sharing of information on the functional status of patients. We also implemented patient education to improve their awareness of mobility and participation. Finally, we conducted newly devised surveys related to patient functional status and awareness that were applied by therapists and nurses. RESULTS: The nurses reported significantly lower functional levels of patients compared to those assessed by therapists. After the intervention, the kappa values representing the concordance between therapists and nurses improved to almost perfect agreement for transfer ability (κ=0.836), mobility (κ=0.664), and toileting (κ=1.000). We also observed a statistically significant increase in questionnaire scores with respect to nurses' awareness (p<0.05). CONCLUSION: Improving communication among the rehabilitation team, including nurses through the use of a continuous education program, was effective in promoting the mobility and functional level of patients in the inpatient ward.

Empirical Bayes estimation of pairwise maximum entropy model for nonlinear brain state dynamics.

The pairwise maximum entropy model (pMEM) has recently gained widespread attention to exploring the nonlinear characteristics of brain state dynamics observed in resting-state functional magnetic resonance imaging (rsfMRI). Despite its unique advantageous features, the practical application of pMEM for individuals is limited as it requires a much larger sample than conventional rsfMRI scans. Thus, this study proposes an empirical Bayes estimation of individual pMEM using the variational expectation-maximization algorithm (VEM-MEM). The performance of the VEM-MEM is evaluated for several simulation setups with various sample sizes and network sizes. Unlike conventional maximum likelihood estimation procedures, the VEM-MEM can reliably estimate the individual model parameters, even with small samples, by effectively incorporating the group information as the prior. As a test case, the individual rsfMRI of children with attention deficit hyperactivity disorder (ADHD) is analyzed compared to that of typically developed children using the default mode network, executive control network, and salient network, obtained from the Healthy Brain Network database. We found that the nonlinear dynamic properties uniquely established on the pMEM differ for each group. Furthermore, pMEM parameters are more sensitive to group differences and are better associated with the behavior scores of ADHD compared to the Pearson correlation-based functional connectivity. The simulation and experimental results suggest that the proposed method can reliably estimate the individual pMEM and characterize the dynamic properties of individuals by utilizing empirical information of the group brain state dynamics.

The Development and Application of Drama-Combined Nursing Educational Content for Cancer Care.

With the recent increase in the number of cancer patients, it is important to educate nursing students using pedagogical techniques that nurture understanding and empathy for cancer patients. This study examined nursing students' experiences caring for cancer patients after receiving drama-combined nursing education for cancer care (DCC), which consisted of three elements: lectures, dramatic scenarios, and debriefing. The lectures dealt with cancer statistics, diseases, and nursing, and the dramatic scenarios depicted both breast cancer patients and lung cancer patients. Sixty-seven junior-year nursing students attended a 90 min DCC session developed by the authors. Focus group interviews were conducted to explore students' educational experiences, and the following three themes were derived using the thematic analysis method: 'understanding the lives of patients with severe diseases and their families', 'seeing a nursing role model provide patient-centered care', and 'projecting an image of oneself as a future nurse'. Using drama in nursing education for cancer patients provided an opportunity for students to imagine the clinical experiences of cancer patients, helping them to understand patients' points of view and reflect on their self-images as future nurses. The DCC developed for nursing students in this study is a promising way to deliver distinctive and meaningful learning experiences.

Sequential treatment of nitrate and phosphate in groundwater using a permeable reactive barrier system.

When not properly treated, nitrate and phosphate present in groundwater can damage human health and environments. In this study, laboratory column experiments were performed for sequential treatment of nitrate and phosphate in groundwater. Two columns were set up and connected: one to treat nitrate with organic carbon materials (i.e., woodchips) and the other to treat phosphate with basic oxygen furnace (BOF) slag. The columns were operated for a total of 1.6 years. The results showed that nitrate was removed through denitrification and phosphate was removed by precipitation of the phosphate minerals (e.g., hydroxyapatite). BOF slag was effective at removing phosphate, though the high pH (11-12) of the system's effluent water raised a concern for the downgradient areas. Of the three subsequent experiments performed, pH was near neutral when the effluent of the BOF slag column was passed through local soil. Sparging with CO2 and air, in contrast, resulted in pH levels that were either too low (5 in the case of CO2) or too high (9.5 in the case of air). The study shows that sequential permeable reactive barrier (PRB) systems consisting of woodchips and BOF slag can be effective for removal of nitrate and phosphate in groundwater and they can be a long-term remedial solution for groundwater contaminated with both nitrate and phosphate.

Effects of Chronic Low-Dose Internal Radiation on Immune-Stimulatory Responses in Mice.

The Linear-No-Threshold (LNT) model predicts a dose-dependent linear increase in cancer risk. This has been supported by biological and epidemiological studies at high-dose exposures. However, at low-doses (LDR ≤ 0.1 Gy), the effects are more elusive and demonstrate a deviation from linearity. In this study, the effects of LDR on the development and progression of mammary cancer in FVB/N-Tg(MMTVneu)202Mul/J mice were investigated. Animals were chronically exposed to total doses of 10, 100, and 2000 mGy via tritiated drinking water, and were assessed at 3.5, 6, and 8 months of age. Results indicated an increased proportion of NK cells in various organs of LDR exposed mice. LDR significantly influenced NK and T cell function and activation, despite diminishing cell proliferation. Notably, the expression of NKG2D receptor on NK cells was dramatically reduced at 3.5 months but was upregulated at later time-points, while the expression of NKG2D ligand followed the opposite trend, with an increase at 3.5 months and a decrease thereafter. No noticeable impact was observed on mammary cancer development, as measured by tumor load. Our results demonstrated that LDR significantly influenced the proportion, proliferation, activation, and function of immune cells. Importantly, to the best of our knowledge, this is the first report demonstrating that LDR modulates the cross-talk between the NKG2D receptor and its ligands.

Improved cardiac-specific delivery of RAGE siRNA within small extracellular vesicles engineered to express intense cardiac targeting peptide attenuates myocarditis.

Small extracellular vesicles (sEVs) are nanometer-sized membranous vesicles secreted by cells, with important roles in physiological and pathological processes. Recent research has established the application of sEVs as therapeutic vehicles in various conditions, including heart disease. However, the high risk of off-target effects is a major barrier for their introduction into the clinic. This study evaluated the use of modified sEVs expressing high levels of cardiac-targeting peptide (CTP) for therapeutic small interfering RNA (siRNA) delivery in myocarditis, an inflammatory disease of heart. sEVs were extracted from the cell culture medium of HEK293 cells stably expressing CTP-LAMP2b (referred to as C-sEVs). The cardiac targeting ability of C-sEVs with the highest CTP-LAMP2b expression was >2-fold greater than that of normal sEVs (N-sEVs). An siRNA targeting the receptor for advanced glycation end products (RAGE) (siRAGE) was selected as a therapeutic siRNA and loaded into C-sEVs. The efficiency of cardiac-specific siRNA delivery via C-sEVs was >2-fold higher than that via N-sEVs. Furthermore, siRAGE-loaded C-sEVs attenuated inflammation in both cell culture and an in vivo model of myocarditis. Taken together, C-sEVs may be a useful drug delivery vehicle for the treatment of heart disease.

A Computational Framework for Controlling the Self-Restorative Brain Based on the Free Energy and Degeneracy Principles.

The brain is a non-linear dynamical system with a self-restoration process, which protects itself from external damage but is often a bottleneck for clinical treatment. To treat the brain to induce the desired functionality, formulation of a self-restoration process is necessary for optimal brain control. This study proposes a computational model for the brain's self-restoration process following the free-energy and degeneracy principles. Based on this model, a computational framework for brain control is established. We posited that the pre-treatment brain circuit has long been configured in response to the environmental (the other neural populations') demands on the circuit. Since the demands persist even after treatment, the treated circuit's response to the demand may gradually approximate the pre-treatment functionality. In this framework, an energy landscape of regional activities, estimated from resting-state endogenous activities by a pairwise maximum entropy model, is used to represent the pre-treatment functionality. The approximation of the pre-treatment functionality occurs via reconfiguration of interactions among neural populations within the treated circuit. To establish the current framework's construct validity, we conducted various simulations. The simulations suggested that brain control should include the self-restoration process, without which the treatment was not optimal. We also presented simulations for optimizing repetitive treatments and optimal timing of the treatment. These results suggest a plausibility of the current framework in controlling the non-linear dynamical brain with a self-restoration process.

Bayesian estimation of maximum entropy model for individualized energy landscape analysis of brain state dynamics.

The pairwise maximum entropy model (MEM) for resting state functional MRI (rsfMRI) has been used to generate energy landscape of brain states and to explore nonlinear brain state dynamics. Researches using MEM, however, has mostly been restricted to fixed-effect group-level analyses, using concatenated time series across individuals, due to the need for large samples in the parameter estimation of MEM. To mitigate the small sample problem in analyzing energy landscapes for individuals, we propose a Bayesian estimation of individual MEM using variational Bayes approximation (BMEM). We evaluated the performances of BMEM with respect to sample sizes and prior information using simulation. BMEM showed advantages over conventional maximum likelihood estimation in reliably estimating model parameters for individuals with small sample data, particularly utilizing the empirical priors derived from group data. We then analyzed individual rsfMRI of the Human Connectome Project to show the usefulness of MEM in differentiating individuals and in exploring neural correlates for human behavior. MEM and its energy landscape properties showed high subject specificity comparable to that of functional connectivity. Canonical correlation analysis identified canonical variables for MEM highly associated with cognitive scores. Inter-individual variations of cognitive scores were also reflected in energy landscape properties such as energies, occupation times, and basin sizes at local minima. We conclude that BMEM provides an efficient method to characterize dynamic properties of individuals using energy landscape analysis of individual brain states.

Simultaneous removal of nitrate and phosphate in groundwater using Ca-citrate complex.

Eutrophication can be caused by excessive input of nutrients, such as nitrate and phosphate, to surface water. Nutrients in groundwater can enter surface water by means of base flow, requiring treatment before they reach surface water bodies. While some studies have attempted to remove nitrate and phosphate, methods for simultaneous removal in groundwater have rarely been reported. In this study, we propose an innovative treatment method to simultaneously remove nitrate and phosphate in groundwater based on an injection of Ca-citrate complex. A total of five batch experiments with different conditions were conducted to identify the removal mechanisms of nitrate and phosphate and to evaluate the use of alternative organic materials, such as lactate. The results showed that Ca-citrate complex can remove nitrate and phosphate simultaneously. Nitrate was removed through denitrification by denitrifying bacteria which used citrate as a carbon source. The removal mechanisms for phosphate were precipitation of phosphate minerals (e.g., hydroxyapatite) and adsorption. The results also showed that reactive materials based on Ca-lactate complex were able to remove nitrate and phosphate. This study suggests that nitrate and phosphate in groundwater can simultaneously be removed using organic-based calcium complexes, proposing a promising remedial method to alleviate potential eutrophication in surface water as well as groundwater contamination.