Chiral recognition and discrimination studies of tyrosine enantiomers on (-)-18-crown-6-tetracarboxylic acid as a chiral selector by nuclear magnetic resonance spectroscopy and docking simulations.

Considering the substantial significance of chiral biomolecules, such as amino acids, in our daily routines, we performed chiral recognition and discrimination of tyrosine (Tyr) enantiomers on (-)-(18-crown-6)-2,3,11,12-tetracarboxylic acid [(-)-18-C-6-TA] as crown-ether type chiral selector (CS) by nuclear magnetic resonance (NMR) spectroscopy and docking simulations. In this study, successful discrimination of the enantiomers of Tyr was achieved, as evidenced by the proton chemical shift differences (ΔΔδ) of Tyr enantiomers observed in the 1 H NMR spectra with (-)-18-C-6-TA CS. We compared the results of these two techniques with the findings obtained from high performance liquid chromatography (HPLC) investigations. In both NMR and HPLC experimental and docking simulation studies, a stronger interaction between the L-Tyr enantiomer with (-)-18-C-6-TA CS than the D-Tyr was consistently observed. Also, the binding energy differences (ΔΔEL-D ) found in simulation data that correspond to enantioselectivity aligned well with the NMR experimental result.

Induction of Autophagy by Extract from Corydalis heterocarpa for Skin Anti-Aging.

The extracts of Corydalis heterocarpa, a salt-tolerant plant, exhibit diverse physiological properties, including anti-inflammatory, anticancer, and antiadipogenic effects. However, the anti-aging effects of C. heterocarpa extract (CHE) on human skin cells have not yet been investigated. In the present study, we determined that CHE inhibited senescence-associated ß-galactosidase (SA-ß-gal)-stained senescent human dermal fibroblasts (HDFs). Furthermore, CHE markedly suppressed the expression of major regulatory proteins involved in senescence, including p53, p21, and caveolin-1. Interestingly, CHE promoted autophagic flux, as confirmed by the formation of microtubule-associated protein 1 light chain 3B (LC3B) puncta and lysosomal activity. Notably, using RNA sequencing (RNA-seq), we showed that CHE selectively regulated the gene expression of leucine-rich repeat and sterile alpha motif-containing 1 (LRSAM1), an important regulator of autophagy. The adenosine-monophosphate activated protein kinase/mammalian target of rapamycin (AMPK/mTOR) pathway, which is essential for autophagy regulation, was also modulated by CHE. LRSAM1 depletion not only inhibited LC3B expression but also decreased the autophagy flux induced by CHE. Moreover, the knockdown of LRSAM1 suppressed the reversal of CHE-induced senescence in old HDFs. Collectively, our study has revealed the rejuvenating effects and molecular mechanisms of CHE, suggesting that CHE may be a promising anti-aging agent.

FBXW7-mediated stability regulation of signal transducer and activator of transcription 2 in melanoma formation.

In this study, we provide critical evidence that STAT2 stability regulation plays an essential role in melanoma cell proliferation and colony growth. We found that the interaction of FBXW7 and STAT2 induced STAT2 destabilization via a ubiquitination-mediated proteasomal degradation pathway. Notably, GSK3ß-mediated STAT2 phosphorylation facilitated STAT2-FBXW7 interactions via the DNA binding domain of STAT2 and domains 1, 2, 6, and 7 of FBXW7 WD40. Importantly, the inverse correlation between protein levels of STAT2 and FBXW7 were observed not only in human melanoma cells but also in a human skin cancer tissue array. The relationship between protein levels of STAT2 and FBXW7, cell proliferation, and colony growth were similarly observed in the melanoma cell lines SK-MEL-2, -5, and -28. Moreover, STAT2 knockdown in melanoma cells suppressed melanoma cell proliferation and colony formation. These data demonstrated that FBXW7-mediated STAT2 stability regulation plays an essential role in melanoma cell proliferation and cancer growth.

CMOS Detector Staggered Array Module for Sub-Terahertz Imaging on Conveyor Belt System.

A complementary metal-oxide-semiconductor (CMOS) detector array is proposed to improve the sub-terahertz imaging resolution for objects in the conveyor belt system. The image resolution is limited to the implemented configuration, such as the wide spacing in the detector array, the high conveyor belt speed, and the slow response of the signal conditioning block. The proposed array can improve the image resolution in the direction perpendicular to the movement of the belt, which is determined by the size and interval of the detector pixel, by configuring the array into two replaceable columns located at the misaligned horizontal positions. Replaceable detector unit pixels are individually attached to the motherboard after measuring and evaluating the detection performance to construct the proposed array. The intensities of 32 detector pixels placed under the conveyor belt with a width of 160 mm were initially calibrated in every image, including the beam pattern of 0.2 THz signals generated from the gyrotron. The image resolution of the perpendicular direction obtained from the proposed array was measured to be approximately 5 mm at a conveyor belt speed of 16 mm/s, demonstrating a 200% improvement in resolution compared to the conventional linear array under the same conditions.

Molecular Mechanisms for the Regulation of Nuclear Membrane Integrity.

The nuclear membrane serves a critical role in protecting the contents of the nucleus and facilitating material and signal exchange between the nucleus and cytoplasm. While extensive research has been dedicated to topics such as nuclear membrane assembly and disassembly during cell division, as well as interactions between nuclear transmembrane proteins and both nucleoskeletal and cytoskeletal components, there has been comparatively less emphasis on exploring the regulation of nuclear morphology through nuclear membrane integrity. In particular, the role of type II integral proteins, which also function as transcription factors, within the nuclear membrane remains an area of research that is yet to be fully explored. The integrity of the nuclear membrane is pivotal not only during cell division but also in the regulation of gene expression and the communication between the nucleus and cytoplasm. Importantly, it plays a significant role in the development of various diseases. This review paper seeks to illuminate the biomolecules responsible for maintaining the integrity of the nuclear membrane. It will delve into the mechanisms that influence nuclear membrane integrity and provide insights into the role of type II membrane protein transcription factors in this context. Understanding these aspects is of utmost importance, as it can offer valuable insights into the intricate processes governing nuclear membrane integrity. Such insights have broad-reaching implications for cellular function and our understanding of disease pathogenesis.

A deep learning-based automatic analysis of cardiovascular borders on chest radiographs of valvular heart disease: development/external validation.

OBJECTIVES: Cardiovascular border (CB) analysis is the primary method for detecting and quantifying the severity of cardiovascular disease using posterior-anterior chest radiographs (CXRs). This study aimed to develop and validate a deep learning-based automatic CXR CB analysis algorithm (CB_auto) for diagnosing and quantitatively evaluating valvular heart disease (VHD). METHODS: We developed CB_auto using 816 normal and 798 VHD CXRs. For validation, 640 normal and 542 VHD CXRs from three different hospitals and 132 CXRs from a public dataset were assigned. The reliability of the CB parameters determined by CB_auto was evaluated. To evaluate the differences between parameters determined by CB_auto and manual CB drawing (CB_hand), the absolute percentage measurement error (APE) was calculated. Pearson correlation coefficients were calculated between CB_hand and echocardiographic measurements. RESULTS: CB parameters determined by CB_auto yielded excellent reliability (intraclass correlation coefficient > 0.98). The 95% limits of agreement for the cardiothoracic ratio were 0.00 ± 0.04% without systemic bias. The differences between parameters determined by CB_auto and CB_hand as defined by the APE were < 10% for all parameters except for carinal angle and left atrial appendage. In the public dataset, all CB parameters were successfully drawn in 124 of 132 CXRs (93.9%). All CB parameters were significantly greater in VHD than in normal controls (all p < 0.05). All CB parameters showed significant correlations (p < 0.05) with echocardiographic measurements. CONCLUSIONS: The CB_auto system empowered by deep learning algorithm provided highly reliable CB measurements that could be useful not only in daily clinical practice but also for research purposes. KEY POINTS: • A deep learning-based automatic CB analysis algorithm for diagnosing and quantitatively evaluating VHD using posterior-anterior chest radiographs was developed and validated. • Our algorithm (CB_auto) yielded comparable reliability to manual CB drawing (CB_hand) in terms of various CB measurement variables, as confirmed by external validation with datasets from three different hospitals and a public dataset. • All CB parameters were significantly different between VHD and normal control measurements, and echocardiographic measurements were significantly correlated with CB parameters measured from normal control and VHD CXRs.

Concurrent-Mode CMOS Detector IC for Sub-Terahertz Imaging System.

A CMOS detector with a concurrent mode for high-quality images in the sub-terahertz region has been proposed. The detector improves output-signal coupling characteristics at the output node. A cross-coupling capacitor is added to isolate the DC bias between the drain and gate. The detector is designed to combine a 180° phase shift based on common source operation and an in-phase output signal based on the drain input. The circuit layout and phase shift occurring in the cross-coupled capacitor during phase coupling are verified using an EM simulation. The detector is fabricated using the TSMC 0.25-µm mixed-signal 1-poly 5-metal layer CMOS process, where the size, including the pad, is 1.13 mm × 0.74 mm. The detector IC comprises a folded dipole antenna, the proposed detector, a preamplifier, and a voltage buffer. Measurement results using a 200-GHz gyrotron source demonstrate that the proposed detector voltage responsivity is 14.13 MV/W with a noise-equivalent power of 34.42 pW/√Hz. The high detection performance helps resolve the 2-mm line width. The proposed detector exhibits a signal-to-noise ratio of 49 dB with regard to the THz imaging performance, which is 9 dB higher than that of the previous CMOS detector core circuits with gate-drain capacitors.

Deep learning-based algorithm to detect primary hepatic malignancy in multiphase CT of patients at high risk for HCC.

OBJECTIVES: To develop and evaluate a deep learning-based model capable of detecting primary hepatic malignancies in multiphase CT images of patients at high risk for hepatocellular carcinoma (HCC). METHODS: A total of 1350 multiphase CT scans of 1280 hepatic malignancies (1202 HCCs and 78 non-HCCs) in 1320 patients at high risk for HCC were retrospectively analyzed. Following the delineation of the focal hepatic lesions according to reference standards, the CT scans were categorized randomly into the training (568 scans), tuning (193 scans), and test (589 scans) sets. Multiphase CT information was subjected to multichannel integration, and livers were automatically segmented before model development. A deep learning-based model capable of detecting malignancies was developed using a mask region-based convolutional neural network. The thresholds of the prediction score and the intersection over union were determined on the tuning set corresponding to the highest sensitivity with < 5 false-positive cases per CT scan. The sensitivity and the number of false-positives of the proposed model on the test set were calculated. Potential causes of false-negatives and false-positives on the test set were analyzed. RESULTS: This model exhibited a sensitivity of 84.8% with 4.80 false-positives per CT scan on the test set. The most frequent potential causes of false-negatives and false-positives were determined to be atypical enhancement patterns for HCC (71.7%) and registration/segmentation errors (42.7%), respectively. CONCLUSIONS: The proposed deep learning-based model developed to automatically detect primary hepatic malignancies exhibited an 84.8% of sensitivity with 4.80 false-positives per CT scan in the test set. KEY POINTS: • Image processing, including multichannel integration of multiphase CT and automatic liver segmentation, enabled the application of a deep learning-based model to detect primary hepatic malignancy. • Our model exhibited a sensitivity of 84.8% with a false-positive rate of 4.80 per CT scan.

Metagenomic analysis of the dust particles collected from the suction tube and the suction funnel of a dermatological laser smoke evacuator system.

In the last few decades, there has essentially been an explosion in the use of lasers in medicine, especially in the area of cosmetic dermatology. Potentially harmful substances are liberated when tissues are vaporized with laser. This creates numerous risks, including the spread of infectious disease. Smoke evacuators are devices that capture and filter laser plume, thereby maintaining a safe environment for the surgical team and patient. Our aim was to characterize the microbial community structure within the suction tube and funnel of the smoke evacuator system, identify their origin, and evaluate pathogenicity. Dust particles were collected from the instruments with a cotton swab. DNA was extracted from the swabs and the transport media, and sequencing was performed using the Illumina HiSeq Xplatform. Metagenomic analysis was conducted using the Empowering the Development of Genomics Expertise (EDGE) Bioinformatics pipeline and custom Python scripts. The most abundant bacterial species were Micrococcus luteus and Brevibacterium casei in the suction tube, and Dermacoccus sp. Ellin 185 and Janibacter hoylei in the suction funnel. A total of 15 medium- to high-quality metagenome-assembled genomes (MAGs) were constructed where we found 104 antibiotic-resistant genes (ARGs) and 741 virulence factors. Findings indicate that the suction tube and funnel are likely a reservoir of virulence factor genes and ARGs, which can possibly be passed on to other bacteria via horizontal gene transfer. We would like to emphasize the health risk these microorganisms pose and the need to reevaluate the current hygiene standards with regard to the smoke evacuator system.

Fargesin Inhibits EGF-Induced Cell Transformation and Colon Cancer Cell Growth by Suppression of CDK2/Cyclin E Signaling Pathway.

Although the lignan compound fargesin is a major ingredient in Shin-Yi, the roles of fargesin in carcinogenesis and cancer cell growth have not been elucidated. In this study, we observed that fargesin inhibited cell proliferation and transformation by suppression of epidermal growth factor (EGF)-stimulated G1/S-phase cell cycle transition in premalignant JB6 Cl41 and HaCaT cells. Unexpectedly, we found that signaling pathway analyses showed different regulation patterns in which fargesin inhibited phosphatidylinositol 3-kinase/AKT signaling without an alteration of or increase in mitogen activated protein kinase (MAPK) in JB6 Cl41 and HaCaT cells, while both signaling pathways were abrogated by fargesin treatment in colon cancer cells. We further found that fargesin-induced colony growth inhibition of colon cancer cells was mediated by suppression of the cyclin dependent kinase 2 (CDK2)/cyclin E signaling axis by upregulation of p21WAF1/Cip1, resulting in G1-phase cell cycle accumulation in a dose-dependent manner. Simultaneously, the suppression of CDK2/cyclin E and induction of p21WAF1/Cip1 were correlated with Rb phosphorylation and c-Myc suppression. Taken together, we conclude that fargesin-mediated c-Myc suppression inhibits EGF-induced cell transformation and colon cancer cell colony growth by the suppression of retinoblastoma (Rb)-E2F and CDK/cyclin signaling pathways, which are mainly regulated by MAPK and PKB signaling pathways.

Analysis of furan and monosaccharides in various coffee beans.

The furan levels in commercial coffee product samples (17 instant coffees, 12 mixed coffee, 8 canned coffee) were 49-2155, 10-201 and 15-209 ng/g, respectively. Since thermal degradation/rearrangement of carbohydrates is the main source of furan, the concentrations of furan and monosaccharides (mannose, rhamnose, glucose, galactose and arabinose) were analysed in 26 green and roasted coffee bean (Coffea arabica) varieties. In coffee beans, furan levels ranged from 4.71 (Bourbon Cerrado, Brazil) to 8.63 mg/kg (San Vicente, Honduras). Galactose was the main monosaccharide in green beans, followed by arabinose, glucose, mannose and rhamnose, on average. Roasting decreased the glucose content by about 81%, and arabinose decreased about 27% in all coffee beans. Glucose decreased the greatest after roasting and is thereby considered the major contributor to the formation of furan.

Maternal Mental Disorders before Delivery and the Risk of Dental Caries in Children.

Prevention of childhood caries is an ongoing public health challenge, but the possibility of an association with maternal mental disorders has received limited attention. We estimated the extent to which maternal mental disorders are associated with an increased risk of hospitalization due to dental caries. We conducted a longitudinal cohort study of 790,758 infants born in Quebec, Canada between 2006 and 2016, with follow-up extending to 2018. We identified women with mental disorders before or during pregnancy and computed the incidence of dental caries in their children. We estimated HR and 95% CI for the association of maternal mental disorders with the risk of dental caries, adjusted for personal characteristics. Infants of women with mental disorders before or during pregnancy had a higher incidence of dental caries compared to children of women with no mental disorder (56.1 vs. 27.2 per 10,000 person-years). Maternal stress and anxiety disorders (HR = 1.73; 95% CI 1.60-1.86), depression (HR = 1.81; 95% CI 1.60-2.03), schizophrenia and delusional disorders (HR = 1.69; 95% CI 1.29-2.22), and personality disorders (HR = 1.89; 95% CI 1.70-2.11) were associated with the risk of dental caries. The associations were present throughout childhood, including after 7 years (HR = 1.65; 95% CI 1.38-1.96). Maternal mental disorders were associated with caries of the enamel, dentin, and cementum and caries that reached the dental pulp. Maternal mental disorders before or during pregnancy, especially stress and anxiety, depression, schizophrenia, and personality disorders, are associated with the risk of childhood caries. Women with a history of mental disorders may benefit from enhanced strategies for prevention of dental caries in their children.

Deep Learning-based Image Conversion of CT Reconstruction Kernels Improves Radiomics Reproducibility for Pulmonary Nodules or Masses.

Background Intratumor heterogeneity in lung cancer may influence outcomes. CT radiomics seeks to assess tumor features to provide detailed imaging features. However, CT radiomic features vary according to the reconstruction kernel used for image generation. Purpose To investigate the effect of different reconstruction kernels on radiomic features and assess whether image conversion using a convolutional neural network (CNN) could improve reproducibility of radiomic features between different kernels. Materials and Methods In this retrospective analysis, patients underwent non-contrast material-enhanced and contrast material-enhanced axial chest CT with soft kernel (B30f) and sharp kernel (B50f) reconstruction using a single CT scanner from April to June 2017. To convert different kernels without sinogram, the CNN model was developed using residual learning and an end-to-end way. Kernel-converted images were generated, from B30f to B50f and from B50f to B30f. Pulmonary nodules or masses were semiautomatically segmented and 702 radiomic features (tumor intensity, texture, and wavelet features) were extracted. Measurement variability in radiomic features was evaluated using the concordance correlation coefficient (CCC). Results A total of 104 patients were studied, including 54 women and 50 men, with pulmonary nodules or masses (mean age, 63.2 years ± 10.5). The CCC between two readers using the same kernel was 0.92, and 592 of 702 (84.3%) of the radiomic features were reproducible (CCC ≥ 0.85); using different kernels, the CCC was 0.38 and only 107 of 702 (15.2%) of the radiomic features were reliable. Texture features and wavelet features were predominantly affected by reconstruction kernel (CCC, from 0.88 to 0.61 for texture features and from 0.92 to 0.35 for wavelet features). After applying image conversion, CCC improved to 0.84 and 403 of 702 (57.4%) radiomic features were reproducible (CCC, 0.85 for texture features and 0.84 for wavelet features). Conclusion Chest CT image conversion using a convolutional neural network effectively reduced the effect of two different reconstruction kernels and may improve the reproducibility of radiomic features in pulmonary nodules or masses. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Park in this issue.

Single residue mutation in integrase catalytic core domain affects feline foamy viral DNA integration.

DD(35)E motif in catalytic core domain (CCD) of integrase (IN) is extremely involved in retroviral integration step. Here, nine single residue mutants of feline foamy virus (FFV) IN were generated to study their effects on IN activities and on viral replication. As expected, mutations in the highly conserved D107, D164, and E200 residues abolished all IN catalytic activities (3'-end processing, strand transfer, and disintegration) as well as viral infectivity by blocking viral DNA integration into cellular DNA. However, Q165, Y191, and S195 mutants, which are located closely to DDE motif were observed to have diverse levels of enzymatic activities, compared to those of the wild type IN. Their mutant viruses produced by one-cycle transfection showed different infectivity on their natural host cells. Therefore, it is likely that effects of single residue mutation at DDE motif is critical on viral replication depending on the position of the residues.

Different mutational characteristics of the subsets of EGFR-tyrosine kinase inhibitor sensitizing mutation-positive lung adenocarcinoma.

BACKGROUND: A subset of lung adenocarcinoma with EGFR-tyrosine kinase inhibitor sensitizing mutations (mEGFR) is common in non-smokers and women, suggesting that mutational stressors other than smoking are involved. METHODS: Targeted sequencing using a custom panel containing 70 cancer-related genes were performed from 73 cases of lung adenocarcinoma with mEGFR (study cohort). In parallel, publicly available data of 47 TCGA-LUAD cases with mEGFR (LUAD cohort) were extracted from the GDC data portal and analyzed by non-negative matrix factorization using the Maftools package. RESULTS: In the study cohort, the C > A transversions accounted for 12.9% of all single nucleotide variations (SNVs), comprising the second smallest proportion among SNVs. The E19del-subgroup had a significantly lower mutational burden with significantly higher Ti/Tv ratio than the SNV-subgroup, which includes cases with L858R and other EGFR-TKI sensitizing SNVs. (P = 0.0326 and 0.0002, respectively, Mann-Whitney U test). In the LUAD cohort, the mutational burden was substantially lower than in other TCGA cancer cohorts, and the frequency of C > A transversions was 30.3%, occupying the second frequency. The E19del-subgroup had a lower mutational burden overall and a higher Ti/Tv ratio than the SNV-subgroup (P = 0.0497 and P = 0.0055, respectively, Mann-Whitney U test). Smoking-related signature 4 was observed only in the L858R-subgroup, while ignature 30 and 5 was observed in both groups. CONCLUSIONS: Lung adenocarcinoma with mEGFR(+) has a lower mutational burden and does not show a characteristic mutation pattern influenced by smoking. E19del and L858R, which are representative subtypes of mEGFR(+) lung adenocarcinoma, differ in terms of mutational spectrum, as the E19del-subgroup has a lower mutation burden and a higher Ti/Tv ratio than the SNV-subgroup. These findings could help explain the differences in the responses to EGFR-TKIs and in the clinical courses between the two lung adenocarcinoma subgroups.

Aquimarina spongiicola sp. nov., isolated from spongin.

A Gram-reaction-negative, aerobic, motile by gliding, non-spore-forming, rod-shaped bacterial strain, designated 122CH820-2T, was isolated from spongin. This bacterium was characterized to determine its taxonomic position by using a polyphasic approach. Strain 122CH820-2T grew well at 25-30 °C on marine agar. On the basis of 16S rRNA gene sequence similarity, strain 122CH820-2T belonged to the family Flavobacteriaceae and was closely related to Aquimarina mytili PSC33T (96.8 % sequence similarity) and A. penaei P3-1T (96.7 %). Lower sequence similarities (<96.5 %) were found with all of the other recognized members of the genus Aquimarina. The G+C content of the genomic DNA was 35.2 mol%. The major respiratory quinone was menaquinone MK-6 and the major fatty acids were C15 : 0, iso-C17 : 0 3-OH, iso-C15 : 1 G and iso-C15 : 0 3-OH. The polar lipids were phosphatidylethanolamine, one aminophospholipid and five unidentified polar lipids. Strain 122CH820-2T could be differentiated genotypically and phenotypically from recognized species of the genus Aquimarina. The isolate therefore represents a novel species, for which the name Aquimarina spongiicola sp. nov. is proposed, with the type strain 122CH820-2T (=KACC 19274T=LMG 30078T).

Vibrio hannami sp. nov., Isolated from Seawater.

A Gram-reaction negative, aerobic, motile, non-pigmented and rod-shaped bacterium, designated as 168GH5-2-16T, was isolated from seawater Jeju island. Phylogenetic analysis based on 16S rRNA gene sequence comparison revealed that the strain formed a distinct lineage within the genus Vibrio and was most closely related to Vibrio variabilis R-40492T (96.0%). The DNA G+C content was 49.3 mol%. The major polar lipids were phosphatidylethanolamine (PE) and phosphatidylglycerol (PG). The predominant quinone was ubiquinone-8 (Q-8). The major fatty acids were C16:0, summed feature 3 (comprising C16:1 ω7c/C16:1 ω6c) and summed feature 8 (C18:1 ω7c/C18:1 ω6c) supported the affiliation of 168GH5-2-16T to the genus Vibrio. Moreover, the physiological, biochemical, and taxonomic analysis allowed the phenotypic and genotypic differentiation of strain 168GH5-2-16T from the recognized species of the genus Vibrio. Therefore, strain 168GH5-2-16T represents a novel species of the genus Vibrio, for which the name Vibrio hannami sp. nov. is proposed, with the type strain 168GH5-2-16T (=KACC 19277T = DSM105032T).

Remediation of sediments contaminated by harmful heavy metals using aluminum sulfate: Sustainable approach for practical applications.

Chemical washing could be suitable for the remediation of marine sediments contaminated with harmful heavy metals. Considering green and sustainable remediation (GSR), the application of aluminum sulfate (AS) is intended to reduce the costs and environmental impacts. We extracted harmful heavy metals from manganese nodules using an ion exchange mechanism that occurs when AS dissociates in water. AS in the range from 2 % to 5 % was used. The remediation efficiencies using 5 % AS were found to be the highest, at 91.8 % for Ni and ≥ 100 % for other harmful heavy metals. The Pearson's coefficient evaluation showed that increasing elapsed time did not significantly affect the extraction of harmful heavy metals. Pollutants in post-processing products may not cause secondary pollutions if solidification/stabilization and additional treatments are used. Our results can serve as fundamental data for the actual remediation processes using AS not only for deep-sea mining tailings but also contaminated marine sediments.

Deep Learning-Based Lumen and Vessel Segmentation of Intravascular Ultrasound Images in Coronary Artery Disease.

BACKGROUND AND OBJECTIVES: Intravascular ultrasound (IVUS) evaluation of coronary artery morphology is based on the lumen and vessel segmentation. This study aimed to develop an automatic segmentation algorithm and validate the performances for measuring quantitative IVUS parameters. METHODS: A total of 1,063 patients were randomly assigned, with a ratio of 4:1 to the training and test sets. The independent data set of 111 IVUS pullbacks was obtained to assess the vessel-level performance. The lumen and external elastic membrane (EEM) boundaries were labeled manually in every IVUS frame with a 0.2-mm interval. The Efficient-UNet was utilized for the automatic segmentation of IVUS images. RESULTS: At the frame-level, Efficient-UNet showed a high dice similarity coefficient (DSC, 0.93±0.05) and Jaccard index (JI, 0.87±0.08) for lumen segmentation, and demonstrated a high DSC (0.97±0.03) and JI (0.94±0.04) for EEM segmentation. At the vessel-level, there were close correlations between model-derived vs. experts-measured IVUS parameters; minimal lumen image area (r=0.92), EEM area (r=0.88), lumen volume (r=0.99) and plaque volume (r=0.95). The agreement between model-derived vs. expert-measured minimal lumen area was similarly excellent compared to the experts' agreement. The model-based lumen and EEM segmentation for a 20-mm lesion segment required 13.2 seconds, whereas manual segmentation with a 0.2-mm interval by an expert took 187.5 minutes on average. CONCLUSIONS: The deep learning models can accurately and quickly delineate vascular geometry. The artificial intelligence-based methodology may support clinicians' decision-making by real-time application in the catheterization laboratory.

The therapeutic effects of vitamin D3 administration on the embryo implantation.

Various adjuvants have been tested clinically for patients with problems with embryo implantation during in vitro fertilization (IVF)-embryo transfer (ET). Vitamin D3, an essential modulator of various physiological processes, has received attention as an important adjuvant for successful pregnancy, as many studies have shown a strong association between vitamin D deficiency and implantation failure and fetal growth restriction. However, vitamin D has been widely utilized in different protocols, resulting in non-reproducible and debatable outcomes. In the present study, we demonstrated that cyclic intrauterine administration of vitamin D3 increased endometrial receptivity and angiogenesis, which could be attributed to increased recruitment of uterus-resident natural killer cells. In particular, cyclic treatment of vitamin D3 promoted stable attachment of the embryo onto endometrial cells in vitro, suggesting its merit during the early stage of embryo implantation to support the initial maternal-fetal interactions. Our findings suggest that women with repeated implantation failure may benefit from the use of vitamin D3 as a risk-free adjuvant prior to IVF-ET procedures to improve the uterine environment, and make it favorable for embryo implantation.