Publications by authors named "Jimin Hong"

Background: Perceived health status (PHS) can be influenced by mental health. A negative correlation between high levels of depression and self-evaluation of health has been reported, but research focusing on depression as a risk factor for poor PHS has been limited in Asia. This study aimed to analyse the association between depression and PHS in Korean adult women and explore the degree of depression's association on poor PHS.

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Background: Although the combined treatment with radiopharmaceutical therapy (RPT) and poly (ADP-ribose) polymerase inhibitors (PARPi) shows promise, a critical challenge remains in the limited quantitative understanding needed to optimize treatment protocols. This study introduces a mathematical model that quantitatively represents homologous recombination deficiency (HRD) and facilitates patient-specific customization of therapeutic schedules.

Methods: The model predicts therapeutic outcomes based on the absorbed dose by DNA and the resulting radiobiological responses, with DNA double-strand breaks (DSBs) being the critical determinant of cancer cell fate.

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Nitrate-nitrogen (NO-N) is a major contaminant in groundwater and seawater. Significant amounts of ammonia are oxidized to nitrate through nitrification, leading to an imbalance in the nitrogen cycle and causing nitrate pollution in water bodies. Controlling NO-N levels is a significant challenge for both marine aquaculture and human health.

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Radiopharmaceutical therapy (RPT) is an emerging prostate cancer treatment that delivers radiation to specific molecules within the tumor microenvironment (TME), causing DNA damage and cell death. Given TME heterogeneity, it's crucial to explore RPT dosimetry and biological impacts at the cellular level. We integrated spatial transcriptomics (ST) with computational modeling to investigate the effects of RPT targeting prostate-specific membrane antigen (PSMA), fibroblast activation protein (FAP), and gastrin-releasing peptide receptor (GRPR) each labelled with beta-emitting lutetium-177 (Lu) and alpha-emitting actinium-225 (Ac).

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Purpose: Radiomics has revolutionized clinical research by enabling objective measurements of imaging-derived biomarkers. However, the true potential of radiomics necessitates a comprehensive understanding of the biological basis of extracted features to serve as a clinical decision support. In this work, we propose an end-to-end framework for the in silico simulation of [F]FLT PET imaging process in Pancreatic Ductal Adenocarcinoma, accounting for the biological characterization of tissues (including perfusion and fibrosis) on tracer delivery.

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Purpose: Dopamine transporter imaging is routinely used in Parkinson's disease (PD) and atypical parkinsonian syndromes (APS) diagnosis. While [C]CFT PET is prevalent in Asia with a large APS database, Europe relies on [I]FP-CIT SPECT with limited APS data. Our aim was to develop a deep learning-based method to convert [C]CFT PET images to [I]FP-CIT SPECT images, facilitating multicenter studies and overcoming data scarcity to promote Artificial Intelligence (AI) advancements.

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Background: Progressive supranuclear palsy (PSP) is a primary 4-repeat tauopathy with diverse clinical phenotypes. Previous post-mortem studies examined tau deposition sequences in PSP, but in vivo scrutiny is lacking.

Methods: We conducted [F]Florzolotau tau positron emission tomography (PET) scans on 148 patients who were clinically diagnosed with PSP and 20 healthy controls.

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While F-florzolotau tau PET is an emerging biomarker for progressive supranuclear palsy (PSP), its interpretation has been hindered by a lack of consensus on visual reading and potential biases in conventional semi-quantitative analysis. As clinical manifestations and regions of elevated F-florzolotau binding are highly overlapping in PSP and the Parkinsonian type of multiple system atrophy (MSA-P), developing a reliable discriminative classifier for F-florzolotau PET is urgently needed. Herein, we developed a normalization-free deep-learning (NFDL) model for F-florzolotau PET, which achieved significantly higher accuracy for both PSP and MSA-P compared to semi-quantitative classifiers.

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Purpose: Left-right asymmetry, an important feature of brain development, has been implicated in neurodegenerative diseases, although it's less discussed in typical Alzheimer's disease (AD). We sought to investigate whether asymmetric tau deposition plays a potential role in AD heterogeneity.

Methods: Two independent cohorts consisting of patients with mild cognitive impairment due to AD and AD dementia with tau PET imaging were enrolled [the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort with F-Flortaucipir, the Shanghai Memory Study (SMS) cohort with F-Florzolotau].

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Purpose: Characteristic features of amyloid-PET (A), tau-PET (T), and FDG-PET (N) can serve for the A/T/N classification of neurodegenerative diseases. Recent studies showed that the early, perfusion-weighted phases of amyloid- or tau-PET recordings serve to detect cerebrometabolic deficits equally to FDG-PET, therefore providing a surrogate of neuronal injury. As such, two channels of diagnostic information can be obtained in the setting of a single PET scan.

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We theoretically analyze the resilience (efficiency) of health insurance systems and diverse factors including trace and test technology, infection and contagion rates, and social distancing/lockdown policy, in coping with contagious diseases like COVID-19. Our findings can be summarized as follows. First, public insurance is more resilient than market insurance, as the former's investment in test technology is made at the social optimum, whereas the latter's investment is less.

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Purpose: This work attempts to decode the discriminative information in dopamine transporter (DAT) imaging using deep learning for the differential diagnosis of parkinsonism.

Methods: This study involved 1017 subjects who underwent DAT PET imaging ([C]CFT) including 43 healthy subjects and 974 parkinsonian patients with idiopathic Parkinson's disease (IPD), multiple system atrophy (MSA) or progressive supranuclear palsy (PSP). We developed a 3D deep convolutional neural network to learn distinguishable DAT features for the differential diagnosis of parkinsonism.

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The clinical presentations of early idiopathic Parkinson disease (IPD) substantially overlap with those of atypical parkinsonian syndromes such as multiple system atrophy (MSA) and progressive supranuclear palsy (PSP). This study aimed to develop metabolic imaging indices based on deep learning to support the differential diagnosis of these conditions. A benchmark Huashan parkinsonian PET imaging (HPPI, China) database including 1,275 parkinsonian patients and 863 nonparkinsonian subjects with F-FDG PET images was established to support artificial intelligence development.

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Purpose: Alzheimer's disease (AD) studies revealed that abnormal deposition of tau spreads in a specific spatial pattern, namely Braak stage. However, Braak staging is based on post mortem brains, each of which represents the cross section of the tau trajectory in disease progression, and numerous studies were reported that do not conform to that model. This study thus aimed to identify the tau trajectory and quantify the tau progression in a data-driven approach with the continuous latent space learned by variational autoencoder (VAE).

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Hypercholesterolemia is one of the modifiable and primary risk factors for cardiovascular diseases (CVD). Emerging evidence suggests the stimulation of transintestinal cholesterol excretion (TICE), the nonbiliary cholesterol excretion, using natural products can be an effective way to reduce CVD. Bilberry ( L.

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Article Synopsis
  • - The paper introduces a new method for tracking how people manipulate objects with their hands, focusing on changing and consistent movements during tasks like rotating cubes.
  • - Researchers created a kinematic model using data from six-degree-of-freedom (6-DOF) magnetic sensors placed at seven points on the hand, calibrated through specific procedures for accuracy.
  • - By analyzing videos of subjects rotating different-sized cubes and applying dynamic time warping, the study reconstructed hand movements, discovering consistent patterns in joint angles among subjects.
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Background: 2,3-Butanediol (2,3-BDO) is a synthetic chemical compound that also can be produced by biomass fermentation, which is gaining share in the global market as an intermediate product for numerous applications, i.e. as liquid fuel or fuel additive.

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Peritoneal carcinomatosis (PC) of gastric origin has a poor prognosis with short survival due to lack of effective therapeutic modalities. Here, we evaluated the therapeutic efficacy of an injectable thermosensitive poly (organophosphazene) (PPZ) hydrogel with docetaxel (DTX-gel) to develop an effective therapeutic agent for patient with PC. Three days after inoculation of highly metastatic 44As3Luc cells into peritoneal cavity, the mice were intravenously or intraperitoneally administered with docetaxel alone (DTX-sol IV or IP), and intraperitoneally injected with DTX-gel.

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This study describes the process and results of drug reimbursement decision-making in South Korea and evaluates its performance from the perspectives of the various stakeholders involved. Data were retrieved from the evaluation report posted on the Health Insurance Review and Assessment Service (HIRA) website. As of 2014, 253 new drugs had been submitted to the HIRA for appraisal.

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Objective: To identify the effect of price control policies on drug expenditure in South Korea.

Methods: We retrospectively examined the effects of price-reduction policies on drug expenditures, in particular regarding anti-hyperlipidemic drugs. The National Health Insurance claims data for a 60-month period between 2006 and 2010 were analysed.

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Objective: We performed a cost-utility analysis to assess the cost-effectiveness of a chemotherapy sequence including a combination of polyethylene glycolated liposomal doxorubicin (PLD)/carboplatin versus paclitaxel/carboplatin as a second-line treatment in women with platinum-sensitive ovarian cancer.

Methods: A Markov model was constructed with a 10-year time horizon. The treatment sequence consisted of first- to sixth-line chemotherapies and best supportive care (BSC) before death.

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