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Periodontal disease is a widespread global health concern that necessitates an accurate diagnosis for effective treatment. Traditional diagnostic methods based on panoramic radiographs are often limited by subjective evaluation and low-resolution imaging, leading to suboptimal precision. This study presents an approach that integrates Super-Resolution Generative Adversarial Networks (SRGANs) with deep learning-based segmentation models to enhance the segmentation of periodontal bone loss (PBL) areas on panoramic radiographs. By transforming low-resolution images into high-resolution versions, the proposed method reveals critical anatomical details that are essential for precise diagnostics. The effectiveness of this approach was validated using datasets from the Chungbuk National University Hospital and the Kaggle data portal, demonstrating significant improvements in both image resolution and segmentation accuracy. The SRGAN model, evaluated using the Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) metrics, achieved a PSNR of 30.10 dB and an SSIM of 0.878, indicating high fidelity in image reconstruction. When applied to semantic segmentation using a U-Net architecture, the enhanced images resulted in a dice similarity coefficient (DSC) of 0.91 and an intersection over union (IoU) of 84.9%, compared with 0.72 DSC and 65.4% IoU for native low-resolution images. These results underscore the potential of SRGAN-enhanced imaging to improve PBL area segmentation and suggest broader applications in medical imaging, where enhanced image clarity is crucial for diagnostic accuracy. This study also highlights the importance of further research to expand the dataset diversity and incorporate clinical validation to fully realize the benefits of super-resolution techniques in medical diagnostics.

Rice is one of the plants proven to possess antioxidant, anti-inflammatory, anti-proliferative, and whitening properties, making it one of the most beneficial plants in this regard. This study aimed to introduce a novel natural cosmetic and pharmaceutical product based on rice callus as a source of active ingredients that can inhibit skin melanoma cell (B16F10) proliferation and brighten the skin. The 2,4-D hormone at concentrations of 1 µg/mL and 1.5 µg/mL was used to induce rice callus formation. Rice callus extracts were then prepared using aqueous and ethanolic solvents, with a concentration of 1 mg/mL used for characterization tests. To determine the optimal hormone concentration, the phenols/flavonoids, antioxidant activity, proteins, and carbohydrates in the extracts were measured. The optimal concentration of the hormone was found to be 1 µg/mL. Finally, the anti-melanocyte and skin-whitening activity of the extracts was assessed through measurements of their cytotoxicity and inhibition of melanin synthesis-related enzymes. Cellular cytotoxicity measurements revealed that the ethanolic extract induced more cytotoxicity than the aqueous extract, with IC50 values of 566.3 µg/mL for the ethanolic extract and 1327 µg/mL for the aqueous extract. Skin-whitening-related tests demonstrated that the extracts were 1.7 times more effective than arbutin in inhibiting factors that cause hyperpigmentation. The aqueous extract achieved 85% inhibition of melanin biosynthesis at a concentration of 3200 µg/mL, compared to 68% for the ethanolic extract and 50% for arbutin. Based on these findings, rice callus extract can be introduced as a new, effective substance for skin-lightening and anti-melanocyte products in cosmeceutical and pharmaceutical formulations.

Salix chaenomeloides Kimura, commonly known as pussy willow, is a deciduous shrub and tree belonging to the Salicaceae family. The genus Salix spp. has been known as a healing herb for the treatment of fever, inflammation, and pain relief. The current study aimed to investigate the potential bioactive natural products from S. chaenomeloides leaves and evaluate their antibacterial activity against Helicobacter pylori. A phytochemical investigation of the ethanol (EtOH) extract of S. chaenomeloides leaves led to the isolation of 13 phenolic compounds (1–13) from the ethyl acetate (EtOAc) fraction, which showed antibacterial activity against H. pylori strain 51. The chemical structure of a new phenolic glycoside, chaenomelin (1), was established by a detailed analysis of 1D and 2D (1H-1H correlation spectroscopy (COSY), heteronuclear single-quantum coherence (HSQC), and heteronuclear multiple-bond correlation (HMBC)) nuclear magnetic resonance (NMR), high-resolution electrospray ionization mass spectroscopy (HR-ESIMS), and chemical reactions. The other known compounds were identified as 5-O-trans-p-coumaroyl quinic acid methyl ester (2), tremulacin (3), citrusin C (4), benzyl 3-O-β-d-glucopyranosyl-7-hydroxybenzoate (5), tremuloidin (6), 1-[O-β-d-glucopyranosyl(1→2)-β-d-glucopyranosyl]oxy-2-phenol (7), arbutin cinnamate (8), tremulacinol (9), catechol (10), 4-hydroxybenzaldehyde (11), kaempferol 3-rutinoside (12), and narcissin (13), based on the comparison of their NMR spectra with the reported data and liquid chromatography/mass spectrometry (LC/MS) analysis. The isolated compounds were evaluated for antibacterial activity against H. pylori strain 51. Among the isolates, 1-[O-β-d-glucopyranosyl(1→2)-β-d-glucopyranosyl]oxy-2-phenol (7) and arbutin cinnamate (8) exhibited antibacterial activity against H. pylori strain 51, with inhibitions of 31.4% and 33.9%, respectively, at a final concentration of 100 μM. These results were comparable to that of quercetin (38.4% inhibition), which served as a positive control. Generally, these findings highlight the potential of the active compounds 7 and 8 as antibacterial agents against H. pylori.

Abstract Background Gene silencing using siRNA can be a new potent strategy to treat many incurable diseases at the genetic level, including cancer and viral infections. Treatments using siRNA essentially requires an efficient and safe method of delivering siRNA into cells while maintaining its stability. Thus, we designed novel synergistic fusion peptides, i.e., SPACE and oligoarginine. Results Among the novel fusion peptides and siRNAs, nanocomplexes have enhanced cellular uptake and gene silencing effect in vitro and improved retention and gene silencing effects of siRNAs in vivo. Oligoarginine could attract siRNAs electrostatically to form stable and self-assembled nanocomplexes, and the SPACE peptide could interact with the cellular membrane via hydrogen bonding. Therefore, nanocomplexes using fusion peptides showed improved and evident cellular uptake and gene silencing of glyceraldehyde 3-phosphate dehydrogenase (GAPDH) via the lipid raft-mediated endocytosis pathway, especially to the HDFn cells of the skin, and all of the fusion peptides were biocompatible. Also, intratumorally injected nanocomplexes had increased retention time of siRNAs at the site of the tumor. Finally, nanocomplexes demonstrated significant in vivo gene silencing effect without overt tissue damage and immune cell infiltration. Conclusions The new nanocomplex strategy could become a safe and efficient platform for the delivery of siRNAs into cells and tissues to treat various target diseases through gene silencing.

Physical interactions between cells and micro/nanometer-sized architecture presented in an extracellular matrix (ECM) environment significantly influence cell adhesion and morphology, often facilitating the incidence of diseases, such as cancer invasion and metastasis. Sensing and responding to the topographical cues are deeply associated with a physical interplay between integrins, ligands, and mechanical force transmission, ultimately determining diverse cell behavior. Thus, how the tension applied to the integrin-ligand bonds controls cells’ response to the topographical cues needs to be elucidated through quantitative analysis. Here, in this brief research report, we reported a novel platform, termed “topo-tension gauge tether (TGT),” to visualize single-molecule force applied to the integrin-ligand on the aligned anisotropic nanopatterns. Using the topo-TGT assay, first, topography-induced adhesion and morphology of cancerous and normal cells were compared with the pre-defined peak integrin tension. Next, spatial integrin tensions underneath cells were identified using reconstructed integrin tension maps. As a result, we characterized each cell’s capability to comply with nanotopographies and the magnitude of the spatial integrin tension. Altogether, the quantitative information on integrin tension will be a valuable basis for understanding the biophysical mechanisms underlying the force balance influencing adhesion to the topographical cues.

Salix species, including willow trees, are distributed in the temperate regions of Asian countries, including South Korea. Willow trees are used to treat pain and inflammatory diseases. Due to the medicinal properties of willow trees, pharmacological studies of other Salix spp. have gained attention; however, only a few studies have investigated the phytochemicals of these species. As part of our ongoing natural product research to identify bioactive phytochemicals and elucidate their chemical structures from natural resources, we investigated the marker compounds from indigenous Korean Salix species, namely, Salix triandra, S. chaenomeloides, S. gracilistyla, S. koriyanagi, S. koreensis, S. pseudolasiogyne, S. caprea, and S. rorida. The ethanolic extract of each Salix sp. was investigated using high-performance liquid chromatography combined with thin-layer chromatography and liquid chromatography–mass spectrometry-based analysis, and marker compounds of each Salix sp. were isolated. The chemical structures of the marker compounds (1–8), 3-(4-hydroxyphenyl)propyl β-D-glucopyranoside (1), 2-O-acetylsalicin (2), 1-O-p-coumaroyl glucoside (3), picein (4), isograndidentatin B (5), 2′-O-acetylsalicortin (6), dihydromyricetin (7), and salicin (8) were elucidated via nuclear magnetic resonance spectroscopy and high-resolution liquid chromatography–mass spectrometry using ultrahigh-performance liquid chromatography coupled with a G6545B Q-TOF MS system with a dual electrospray ionization source. The identified marker compounds 1–8 were examined for their antimicrobial effects against plant pathogenic fungi and bacteria. Dihydromyricetin (7) exhibited antibacterial activity against Staphylococcus aureus, inducing 32.4% inhibition at a final concentration of 125 μg/mL with an MIC50 value of 250 μg/mL. Overall, this study isolated the marker compounds of S. triandra, S. chaenomeloides, S. gracilistyla, S. koriyanagi, S. koreensis, S. pseudolasiogyne, S. caprea, and S. rorida and identified the anti-Staphylococcus aureus bacterial compound dihydromyricetin.

Objective To investigate longitudinal changes in language function in left-hemispheric ischemic stroke patients as well as factors that influence language recovery until 1 year after stroke onset. Methods We analyzed data from 235 patients with first-ever left-hemispheric ischemic stroke. All patients completed the Korean version of the Frenchay Aphasia Screening Test (K-FAST) at 7 days (T1), 3 months (T2), 6 months (T3), and 1 year (T4) after stroke onset. Repeated measures analysis of variance (ANOVA) was used to investigate changes in language function between time points. Subgroup analysis was performed according to the K-FAST scores at T1. Stroke lesion volume was assessed using diffusion tensor images, and involvement of language-related brain regions was examined. Multiple regression analysis was used to analyze factors influencing improvement of K-FAST score. Results The K-FAST scores at T1, T2, T3, and T4 differed significantly (p

In this study, an integrated deep learning framework was developed for classifying the periodontitis stages of each individual tooth using dental panoramic radiographs. Based on actual patient panoramic radiographs data, the bone loss by periodontitis and cementoenamel junction boundaries were detected, while the tooth number and tooth length were identified using data from AIHub, an open database platform. The two factors were integrated to classify and to evaluate the periodontitis staging on dental panoramic radiography. Periodontitis is classified into four stages based on the criteria of the radiographic bone level, as suggested at the relevant international conference in 2017. For the integrated deep learning framework developed in this study, the classification performance was evaluated by comparing the results of dental specialists, which indicated that the integrated framework had an accuracy of 0.929, with a recall and precision of 0.807 and 0.724, respectively, in average across all four stages. The novel framework was thus shown to exhibit a relatively high level of performance, and the findings in this study are expected to assist dental specialists with detecting the periodontitis stage and subsequent effective treatment. A systematic application will be developed in the future, to provide ancillary data for diagnosis and basic data for the treatment and prevention of periodontal disease.

Objectives The aim of this research was to determine intra-oral factors that affect halitosis in young women. Methods This study was performed between March 2014 to May 2014, and included 35 women in their 20s with good oral health. Correlation and logistic regression analyses were performed to investigate the change in halitosis immediately, and 1 hour after scaling. Results In both oral gas (OG) and extraoral gas (EG) groups, halitosis was reduced after scaling compared to before scaling. The logistic regression analysis of oral state factors in OG showed that as oral fluid [odds ratio (OR) = 0.792, p = 0.045] and dental plaque (OR = 0.940, p = 0.016) decreased by 1 unit, the OR in the OG group decreased (> 50). In addition, as glucose levels in the oral cavity (OR = 1.245, p = 0.075) and tongue coating index (OR = 2.912, p = 0.064) increased by 1 unit, the OR in the OG group increased (> 50). Furthermore, in the EG group, as oral fluid (OR = 0.66, p = 0.01) and dental plaque (OR = 0.95, p = 0.04) decreased, the OR in the EG group decreased (> 50) significantly. Conclusion To control halitosis, it is necessary to increase oral fluid and decrease the amount of tongue plaque. Furthermore, maintaining a healthy oral environment, aided by regular scaling and removal of dental plaque, may significantly control halitosis.

Abstract Background Ultrasonography (US) is recommended as a standard surveillance tool for patients with a high risk of developing hepatocellular carcinoma (HCC). However, the low sensitivity of US for small HCC can lead to surveillance failure, resulting in advanced stage tumor presentations. For the early detection of HCC in high-risk patients and to improve survival and prognosis, a new efficient imaging tool with a high sensitivity for HCC detection is needed. The purpose of this study is to evaluate and compare the feasibility and efficacy of non-contrast magnetic resonance imaging (MRI) with US as a surveillance tool for HCC in patients with liver cirrhosis. Methods MAGNUS-HCC is a prospective, multicenter clinical trial with a crossover design for a single arm of patients. This study was approved by six Institutional Review Boards, and informed consent was obtained from all participants. All patients will undergo liver US every 6 months and non-contrast liver MRI every 12 months during a follow-up period of 3 years. If a focal liver lesion suspected of harboring HCC is detected, dynamic liver computed tomography (CT) will be performed to confirm the diagnosis. After the last surveillance round, patients without suspicion of HCC or who are not diagnosed with HCC will be evaluated with a dynamic liver CT to exclude false-negative findings. The primary endpoint is to compare the rate of detection of HCC by US examinations performed at 6-month intervals with that of yearly non-contrast liver MRI studies during a 3-year follow-up. The secondary endpoint is the survival of the patients who developed HCC within the 3-year follow-up period. Discussion MAGNUS-HCC is the first study to compare the feasibility of non-contrast MRI with US as a surveillance tool for the detection of HCC in high-risk patients. We anticipate that the evidence presented in this study will establish the efficacy of non-contrast MRI as a surveillance tool for HCC in high-risk patients. Trial registration The date of trial registration ( NCT02551250 ) in this study was September 15, 2015, and follow-up is still ongoing.

An ectopic liver is a rare congenital abnormality that is difficult to detect before surgery due to its small size. A 53-year-old man had liver cirrhosis and received regular surveillance. An ovoid mass on the surface of the gallbladder separated from the liver proper was found on computed tomography (CT). The mass had grown slowly over five years of surveillance. Upon further evaluation, the mass exhibited iso-signal intensity compared to liver on T2-weighted images, precontrast T1-weighted images, and the hepatobiliary phase of gadoxetic acid-enhanced magnetic resonance imaging (MRI). Surgical resection was performed, and the mass was diagnosed as an ectopic liver with normal liver parenchyma without cirrhotic changes. This case demonstrates that ectopic liver with normal liver tissue can develop in a patient with liver cirrhosis and can grow in the absence of a tumor. MRI with gadoxetic acid is useful to identify this condition correctly.

Erdheim-Chester disease is a rare non-Langerhans-cell histiocytosis involving multiple organs. On histological evaluation, lipid-laden histiocyte aggregates in Erdheim-Chester disease is detected, but fat tissue in affected organs is not noted grossly on computed tomography. A 40-year-old man presented with bilateral perirenal masses containing fat tissue. He was diagnosed as perirenal involvement of Erdheim-Chester disease. This report describes a case of Erdheim-Chester disease with perirenal involvement that demonstrates unusual features.

PURPOSEWe aimed to compare polyvinyl alcohol (PVA) particles with calibrated superparamagnetic iron oxide (SPIO) nanoparticle-loaded chitosan microspheres in a rabbit model, specifically regarding the relative distribution of embolic agents within the uterus based on magnetic resonance imaging (MRI) and pathological evaluation.METHODSTwelve New Zealand white rabbits underwent uterine artery embolization using either standard PVA particles (45–150 µm or 350–500 µm) or calibrated SPIO-embedded chitosan microspheres (45–150 µm or 300–500 µm). MRI and histopathological findings were compared one week after embolization.RESULTSCalibrated SPIO-loaded chitosan microspheres 45–150 µm in size were detected on T2-weighted images. On histological analysis, calibrated SPIO-embedded chitosan microspheres were found in both myometrium and endometrium, whereas PVA particles were found only in the perimyometrium or extrauterine fat pads. A proportional relationship was noted between the calibrated SPIO-embedded chitosan microsphere size and the size of the occluded artery.CONCLUSIONCalibrated SPIO-embedded chitosan microspheres induced greater segmental arterial occlusion than PVA particles and showed great potential as a new embolic material. SPIO-embedded chitosan microspheres can be used to follow distribution of embolic particles through MRI studies.

MicroRNAs post-transcriptionally regulate gene expression in animals and plants. The aim of this study was to identify new target genes for microRNA polymorphisms (miR-146aC>G and miR-196a2T>C) in primary ovarian insufficiency (POI). We cloned and transfected miR-146aC>G and miR-196a2T>C into human granulosa cells and used microarrays and qPCR-arrays to examine the changes in the messenger RNA expression profile. We show miR-146aC>G and miR-196a2T>C change the mRNA expression patterns in granulosa cell. In each case, mRNAs were up or down-regulated after treatments with miR-146a C or G and miR-196a2 T or C. We found that miR-146a led to a significantly altered regulation of the mRNA levels of FOXO3, FOXL2 and CCND2 compared to controls. We also found that the polymorphisms of miR-146a led to a significantly altered regulation of CCND2 and FOXO3. Our results suggest that miR-146aC>G and miR-196a2T>C can regulate the levels of many of their target transcripts. In addition, specific target genes of miR-146aC>G polymorphisms may be involved in granulosa cell regulation.

OBJECTIVE:To assess the added value of arterial enhancement fraction (AEF) color maps for the differentiation of small metastases from hepatic benign lesions. SUBJECTS AND METHODS:We retrospectively analyzed 46 patients with colorectal cancer who underwent multiphasic liver CT imaging and had low-attenuating liver lesions smaller than 3 cm (123 total lesions; metastasis: benign = 32:91). AEF color maps of the liver were created from multiphasic liver CT images using dedicated software. Two radiologists independently reviewed multiphasic CT image sets alone and in combination with image sets with AEF color maps using a five-point scale. The additional diagnostic value of the color maps was assessed by means of receiver-operating characteristic (ROC) analysis. RESULTS:The area under the ROC curve (Az) increased when multiphasic CT images were combined with AEF color map analysis as compared with evaluation based only on multiphasic CT images (from 0.698 to 0.897 for reader 1, and from 0.825 to 0.945 for reader 2; P < 0.001 and 0.002, respectively). The increase Az was especially significant for lesions less than 1 cm (from 0.702 to 0.888 for reader 1, and from 0.768 to 0.958 for reader 2; P = 0.001 and P = 0.001, respectively). The mean AEF of tumor-adjacent parenchyma (35.07 ± 27.2) was significantly higher than that of tumor-free liver parenchyma (27.3 ± 20.6) (P = 0.04). CONCLUSIONS:AEF color mapping can improve the diagnostic performance for small hepatic metastases from colorectal cancer and may allow for the elimination of additional examinations.

The purpose of this study was to estimate the value of addition of liver imaging to initial rectal magnetic resonance imaging (MRI) for detection of liver metastasis and evaluate imaging predictors of a high risk of liver metastasis on rectal MRI.We enrolled 144 patients who from October 2010 to May 2013 underwent rectal MRI with T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) (b values = 50, 500, and 900 s/mm2) of the liver and abdominopelvic computed tomography (APCT) for the initial staging of rectal cancer. Two reviewers scored the possibility of liver metastasis on different sets of liver images (T2WI, DWI, and combined T2WI and DWI) and APCT and reached a conclusion by consensus for different analytic results. Imaging features from rectal MRI were also analyzed. The diagnostic performances of CT and an additional liver scan to detect liver metastasis were compared. Multivariate logistic regression to determine independent predictors of liver metastasis among rectal MRI features and tumor markers was performed. This retrospective study was approved by the Institutional Review Board, and the requirement for informed consent was waived.All sets of liver images were more effective than APCT for detecting liver metastasis, and DWI was the most effective. Perivascular stranding and anal sphincter invasion were statistically significant for liver metastasis (p = 0.0077 and p = 0.0471), while extramural vascular invasion based on MRI (mrEMVI) was marginally significant (p = 0.0534).The addition of non-contrast-enhanced liver imaging, particularly DWI, to initial rectal MRI in rectal cancer patients could facilitate detection of liver metastasis without APCT. Perivascular stranding, anal sphincter invasion, and mrEMVI detected on rectal MRI were important imaging predictors of liver metastasis.

Amid growing concern over the changing climate, environment, and health care, the interconnectivity between cardiovascular diseases, coupled with rapid industrialization, and a variety of environmental factors, has been the focus of recent research. It is necessary to research risk factor extraction techniques that consider individual external factors and predict diseases and conditions. Therefore, we designed a framework to collect and store various domains of data on the causes of cardiovascular disease, and constructed a big data integrated database. A variety of open source databases were integrated and migrated onto distributed storage devices. The integrated database was composed of clinical data on cardiovascular diseases, national health and nutrition examination surveys, statistical geographic information, population and housing censuses, meteorological administration data, and Health Insurance Review and Assessment Service data. The framework was composed of data, speed, analysis, and service layers, all stored on distributed storage devices. Finally, we proposed a framework for a cardiovascular disease prediction system based on lambda architecture to solve the problems associated with the real-time analyses of big data. This system can be used to help predict and diagnose illnesses, such as cardiovascular diseases.

OBJECTIVES: Glucose metabolism, perfusion, and water diffusion may have a relationship or affect each other in the same tumor. The understanding of their relationship could expand the knowledge of tumor characteristics and contribute to the field of oncologic imaging. The purpose of this study was to evaluate the relationships between metabolism, vasculature and cellularity of advanced hepatocellular carcinoma (HCC), using multimodality imaging such as ¹⁸F-FDG positron emission tomography (PET), dynamic contrast enhanced (DCE)-MRI, and diffusion weighted imaging(DWI). MATERIALS AND METHODS: Twenty-one patients with advanced HCC underwent ¹⁸F-FDG PET, DCE-MRI, and DWI before treatment. Maximum standard uptake values (SUV(max)) from ¹⁸F-FDG-PET, variables of the volume transfer constant (K(trans)) from DCE-MRI and apparent diffusion coefficient (ADC) from DWI were obtained for the tumor and their relationships were examined by Spearman's correlation analysis. The influence of portal vein thrombosis on SUV(max) and variables of K(trans) and ADC was evaluated by Mann-Whitney test. RESULTS: SUV(max) showed significant negative correlation with K(trans)(max) (ρ = -0.622, p = 0.002). However, variables of ADC showed no relationship with variables of K(trans) or SUV(max) (p>0.05). Whether portal vein thrombosis was present or not did not influence the SUV max and variables of ADC and K(trans) (p>0.05). CONCLUSION: In this study, SUV was shown to be correlated with K(trans) in advanced HCCs; the higher the glucose metabolism a tumor had, the lower the perfusion it had, which might help in guiding target therapy.

In neurointensive care units (NICUs), particularly in cases involving traumatic brain injury (TBI), swift and accurate decision-making is critical because of rapidly changing patient conditions and the risk of secondary brain injury. The use of artificial intelligence (AI) in NICU can enhance clinical decision support and provide valuable assistance in these complex scenarios. This article aims to provide a comprehensive review of the current status and future prospects of AI utilization in the NICU, along with the challenges that must be overcome to realize this. Presently, the primary application of AI in NICU is outcome prediction through the analysis of preadmission and high-resolution data during admission. Recent applications include augmented neuromonitoring via signal quality control and real-time event prediction. In addition, AI can integrate data gathered from various measures and support minimally invasive neuromonitoring to increase patient safety. However, despite the recent surge in AI adoption within the NICU, the majority of AI applications have been limited to simple classification tasks, thus leaving the true potential of AI largely untapped. Emerging AI technologies, such as generalist medical AI and digital twins, harbor immense potential for enhancing advanced neurocritical care through broader AI applications. If challenges such as acquiring high-quality data and ethical issues are overcome, these new AI technologies can be clinically utilized in the actual NICU environment. Emphasizing the need for continuous research and development to maximize the potential of AI in the NICU, we anticipate that this will further enhance the efficiency and accuracy of TBI treatment within the NICU. [ABSTRACT FROM AUTHOR]