Prospective validation of a mobile health application for blood pressure management in patients with hypertensive disorders of pregnancy: study protocol for a randomized controlled trial.

BACKGROUND: Hypertensive disorders of pregnancy (HDP) pose significant risks to both maternal and fetal health, contributing to global morbidity and mortality. Management of HDP is complex, particularly because of concerns regarding potential negative effects on utero-placental circulation and limited therapeutic options due to fetal safety. Our study investigates whether blood pressure monitoring through a mobile health (mHealth) application can aid in addressing the challenges of blood pressure management in pregnant individuals with HDP. Additionally, we aim to assess whether this intervention can improve short-term maternal and fetal outcomes and potentially mitigate long-term cardiovascular consequences. METHODS: This prospective, randomized, single-center trial will include 580 pregnant participants who meet the HDP criteria or who have a heightened risk of pregnancy-related hypertension due to factors such as multiple pregnancies, obesity, diabetes, or a history of HDP in prior pregnancies leading to preterm birth. Participants will be randomized to either the mHealth intervention group or the standard care group. The primary endpoint is the difference in systolic blood pressure from enrollment to 1 month after childbirth. The secondary endpoints include various blood pressure parameters, obstetric outcomes, body mass index trajectory, step counts, mood assessment, and drug adherence. CONCLUSIONS: This study emphasizes the potential of mHealth interventions, such as the Heart4U application, to improve blood pressure management in pregnant individuals with HDP. By leveraging technology to enhance engagement, communication, and monitoring, this study aims to positively impact maternal, fetal, and postpartum outcomes associated with HDP. This innovative approach demonstrates the potential of personalized technology-driven solutions for managing complex health conditions. TRIAL REGISTRATION: ClinicalTrials.gov NCT05995106. Registered on 16 August 2023.

Artificial intelligence-enhanced automation of left ventricular diastolic assessment: a pilot study for feasibility, diagnostic validation, and outcome prediction.

Background: Evaluating left ventricular diastolic function (LVDF) is crucial in echocardiography; however, the complexity and time demands of current guidelines challenge clinical use. This study aimed to develop an artificial intelligence (AI)-based framework for automatic LVDF assessment to reduce subjectivity and improve accuracy and outcome prediction. Methods: We developed an AI-based LVDF assessment framework using a nationwide echocardiographic dataset from five tertiary hospitals. This framework automatically identifies views, calculates diastolic parameters, including mitral inflow and annular velocities (E/A ratio, e' velocity, and E/e' ratio), maximal tricuspid regurgitation velocity, left atrial (LA) volume index, and left atrial reservoir strain (LARS). Subsequently, it grades LVDF according to guidelines. The AI-framework was validated on an external dataset composed of randomly screened 173 outpatients who underwent transthoracic echocardiography with suspicion for diastolic dysfunction and 33 individuals from medical check-ups with normal echocardiograms at Seoul National University Bundang Hospital, tertiary medical center in Korea, between May 2012 and June 2022. Additionally, we assessed the predictive value of AI-derived diastolic parameters and LVDF grades for a clinical endpoint, defined as a composite of all-cause death and hospitalization for heart failure, using Cox-regression risk modelling. Results: In an evaluation with 200 echocardiographic examinations (167 suspected diastolic dysfunction patients, 33 controls), it achieves an overall accuracy of 99.1% in identifying necessary views. Strong correlations (Pearson coefficient 0.901-0.959) were observed between AI-derived and manually-derived measurements of diastolic parameters, including LARS as well as conventional parameters. When following the guidelines, whether utilizing AI-derived or manually-derived parameters, the evaluation of LVDF consistently showed high concordance rates (94%). However, both methods exhibited lower concordance rates with the clinician's prior assessments (77.5% and 78.5%, respectively). Importantly, both AI-derived and manually-derived LVDF grades independently demonstrated significant prognostic value [adjusted hazard ratio (HR) =3.03; P=0.03 and adjusted HR =2.75; P=0.04, respectively] for predicting clinical outcome. In contrast, the clinician's prior grading lost its significance as a prognostic indicator after adjusting for clinical risk factors (adjusted HR =1.63; P=0.36). AI-derived LARS values significantly decreased with worsening LVDF (P for trend <0.001), and low LARS (<17%) was associated with increased risk for the clinical outcome (Log-rank P=0.04) relative to that for preserved LARS (≥17%). Conclusions: Our AI-based approach for automatic LVDF assessment on echocardiography is feasible, potentially enhancing clinical diagnosis and outcome prediction.

A Case of Recurrent Renal Infarction Following Transient Resolution: Evidence From Serial Computed Tomography.

Although renal infarction (RI) is not a rare disease, its outcomes have not been well-documented. Furthermore, transient resolution and recurrence of RI have not been captured through imaging. We report a case of idiopathic RI that recurred within a short period following transient resolution, as demonstrated by serial computed tomography (CT). A 53-year-old man diagnosed with RI was transferred to the emergency room. An abdominal CT scan at the local hospital revealed a segmental wedge-shaped perfusion defect in the left kidney and a focal thrombotic filling defect in the anterior segmental branch of the left renal artery. Since his left flank pain improved, another CT scan was performed again 6 hours after the initial CT scan. A repeat CT scan showed that the thrombus in the renal artery remained, but the perfusion defect had spontaneously resolved. We initiated anticoagulant therapy using unfractionated heparin. On the sixth day of hospitalization, the left flank pain recurred, prompting another CT scan. The follow-up CT scan confirmed that RI had recurred in the same area as before. We continued anticoagulant therapy and switched to warfarin. After treatment, his symptoms improved, and he was discharged. RI can recur at any time, even after it has spontaneously resolved, as evidenced by our case. Therefore, it is crucial to closely monitor patients who experience resolution of RI for any recurrence of symptoms, and repeat radiological evaluation should be performed even within a short period.

Mitral Annular Tissue Velocity Predicts Survival in Patients With Primary Mitral Regurgitation.

BACKGROUND AND OBJECTIVES: Early diastolic mitral annular tissue (e') velocity is a commonly used marker of left ventricular (LV) diastolic function. This study aimed to investigate the prognostic implications of e' velocity in patients with mitral regurgitation (MR). METHODS: This retrospective cohort study included 1,536 consecutive patients aged <65 years with moderate or severe chronic primary MR diagnosed between 2009 and 2018. The primary and secondary outcomes were all-cause and cardiovascular mortality, respectively. According to the current guidelines, the cut-off value of e' velocity was defined as 7 cm/s. RESULTS: A total of 404 individuals were enrolled (median age, 51.0 years; 64.1% male; 47.8% severe MR). During a median 6.0-year follow-up, there were 40 all-cause mortality and 16 cardiovascular deaths. Multivariate analysis revealed a significant association between e' velocity and all-cause death (adjusted hazard ratio [aHR], 0.770; 95% confidence interval [CI], 0.634-0.935; p=0.008) and cardiovascular death (aHR, 0.690; 95% CI, 0.477-0.998; p=0.049). Abnormal e' velocity (≤7 cm/s) independently predicted all-cause death (aHR, 2.467; 95% CI, 1.170-5.200; p=0.018) and cardiovascular death (aHR, 5.021; 95% CI, 1.189-21.211; p=0.028), regardless of symptoms, LV dimension and ejection fraction. Subgroup analysis according to sex, MR severity, mitral valve replacement/repair, and symptoms, showed no significant interactions. Including e' velocity in the 10-year risk score improved reclassification for mortality (net reclassification improvement [NRI], 0.154; 95% CI, 0.308-0.910; p<0.001) and cardiovascular death (NRI, 1.018; 95% CI, 0.680-1.356; p<0.001). CONCLUSIONS: In patients aged <65 years with primary MR, e' velocity served as an independent predictor of all-cause and cardiovascular deaths.

TAZ is involved in breast cancer cell migration via regulating actin dynamics.

Background: Cancer metastasis is dependent on cell migration. Several mechanisms, including epithelial-to-mesenchymal transition (EMT) and actin fiber formation, could be involved in cancer cell migration. As a downstream effector of the Hippo signaling pathway, transcriptional coactivator with PDZ-binding motif (TAZ) is recognized as a key mediator of the metastatic ability of breast cancer cells. We aimed to examine whether TAZ affects the migration of breast cancer cells through the regulation of EMT or actin cytoskeleton. Methods: MCF-7 and MDA-MB-231 cells were treated with siRNA to attenuate TAZ abundance. Transwell migration assay and scratch wound healing assay were performed to study the effects of TAZ knockdown on cancer cell migration. Fluorescence microscopy was conducted to examine the vinculin and phalloidin. Semiquantitative immunoblotting and quantitative real-time PCR were performed to study the expression of small GTPases and kinases. Changes in the expression of genes associated with cell migration were examined through next-generation sequencing. Results: TAZ-siRNA treatment reduced TAZ abundance in MCF-7 and MDA-MB-231 breast cancer cells, which was associated with a significant decrease in cell migration. TAZ knockdown increased the expression of fibronectin, but it did not exhibit the typical pattern of EMT progression. TGF-ß treatment in MDA-MB-231 cells resulted in a reduction in TAZ and an increase in fibronectin levels. However, it paradoxically promoted cell migration, suggesting that EMT is unlikely to be involved in the decreased migration of breast cancer cells in response to TAZ suppression. RhoA, a small Rho GTPase protein, was significantly reduced in response to TAZ knockdown. This caused a decrease in the expression of the Rho-dependent downstream pathway, i.e., LIM kinase 1 (LIMK1), phosphorylated LIMK1/2, and phosphorylated cofilin, leading to actin depolymerization. Furthermore, myosin light chain kinase (MLCK) and phosphorylated MLC2 were significantly decreased in MDA-MB-231 cells with TAZ knockdown, inhibiting the assembly of stress fibers and focal adhesions. Conclusion: TAZ knockdown inhibits the migration of breast cancer cells by regulating the intracellular actin cytoskeletal organization. This is achieved, in part, by reducing the abundance of RhoA and Rho-dependent downstream kinase proteins, which results in actin depolymerization and the disassembly of stress fibers and focal adhesions.

Machine Learning-Based Discrimination of Cardiovascular Outcomes in Patients With Hypertrophic Cardiomyopathy.

Background: Current risk stratification strategies for patients with hypertrophic cardiomyopathy (HCM) are limited to traditional methodologies. Objectives: The authors aimed to establish machine learning (ML)-based models to discriminate major cardiovascular events in patients with HCM. Methods: We enrolled consecutive HCM patients from 2 tertiary referral centers and used 25 clinical and echocardiographic features to discriminate major adverse cardiovascular events (MACE), including all-cause death, admission for heart failure (HF-adm), and stroke. The best model was selected for each outcome using the area under the receiver operating characteristic curve (AUROC) with 20-fold cross-validation. After testing in the external validation cohort, the relative importance of features in discriminating each outcome was determined using the SHapley Additive exPlanations (SHAP) method. Results: In total, 2,111 patients with HCM (age 61.4 ± 13.6 years; 67.6% men) were analyzed. During the median 4.0 years of follow-up, MACE occurred in 341 patients (16.2%). Among the 4 ML models, the logistic regression model achieved the best AUROC of 0.800 (95% CI: 0.760-0.841) for MACE, 0.789 (95% CI: 0.736-0.841) for all-cause death, 0.798 (95% CI: 0.736-0.860) for HF-adm, and 0.807 (95% CI: 0.754-0.859) for stroke. The discriminant ability of the logistic regression model remained excellent when applied to the external validation cohort for MACE (AUROC = 0.768), all-cause death (AUROC = 0.750), and HF-adm (AUROC = 0.806). The SHAP analysis identified left atrial diameter and hypertension as important variables for all outcomes of interest. Conclusions: The proposed ML models incorporating various phenotypes from patients with HCM accurately discriminated adverse cardiovascular events and provided variables with high importance for each outcome.

Low-Temperature Nanosecond Laser Process of HZO-IGZO FeFETs toward Monolithic 3D System on Chip Integration.

Ferroelectric field-effect transistors (FeFETs) are increasingly important for in-memory computing and monolithic 3D (M3D) integration in system-on-chip (SoC) applications. However, the high-temperature processing required by most ferroelectric memories can lead to thermal damage to the underlying device layers, which poses significant physical limitations for 3D integration processes. To solve this problem, the study proposes using a nanosecond pulsed laser for selective annealing of hafnia-based FeFETs, enabling precise control of heat penetration depth within thin films. Sufficient thermal energy is delivered to the IGZO oxide channel and HZO ferroelectric gate oxide without causing thermal damage to the bottom layer, which has a low transition temperature (<250 °C). Using optimized laser conditions, a fast response time (<1 µs) and excellent stability (cycle > 106, retention > 106 s) are achieved in the ferroelectric HZO film. The resulting FeFET exhibited a wide memory window (>1.7 V) with a high on/off ratio (>105). In addition, moderate ferroelectric properties (2·Pr of 14.7 µC cm-2) and pattern recognition rate-based linearity (potentiation: 1.13, depression: 1.6) are obtained. These results demonstrate compatibility in HZO FeFETs by specific laser annealing control and thin-film layer design for various structures (3D integrated, flexible) with neuromorphic applications.

Artificial intelligence-enhanced automation for M-mode echocardiographic analysis: ensuring fully automated, reliable, and reproducible measurements.

To enhance M-mode echocardiography's utility for measuring cardiac structures, we developed and evaluated an artificial intelligence (AI)-based automated analysis system for M-mode images through the aorta and left atrium [M-mode (Ao-LA)], and through the left ventricle [M-mode (LV)]. Our system, integrating two deep neural networks (DNN) for view classification and image segmentation, alongside an auto-measurement algorithm, was developed using 5,958 M-mode images [3,258 M-mode (LA-Ao), and 2,700 M-mode (LV)] drawn from a nationwide echocardiographic dataset collated from five tertiary hospitals. The performance of view classification and segmentation DNNs were evaluated on 594 M-mode images, while automatic measurement accuracy was tested on separate internal test set with 100 M-mode images as well as external test set with 280 images (140 sinus rhythm and 140 atrial fibrillation). Performance evaluation showed the view classification DNN's overall accuracy of 99.8% and segmentation DNN's Dice similarity coefficient of 94.3%. Within the internal test set, all automated measurements, including LA, Ao, and LV wall and cavity, resonated strongly with expert evaluations, exhibiting Pearson's correlation coefficients (PCCs) of 0.81-0.99. This performance persisted in the external test set for both sinus rhythm (PCC, 0.84-0.98) and atrial fibrillation (PCC, 0.70-0.97). Notably, automatic measurements, consistently offering multi-cardiac cycle readings, showcased a stronger correlation with the averaged multi-cycle manual measurements than with those of a single representative cycle. Our AI-based system for automatic M-mode echocardiographic analysis demonstrated excellent accuracy, reproducibility, and speed. This automated approach has the potential to improve efficiency and reduce variability in clinical practice.

Structural and biochemical analysis of penicillin-binding protein 2 from Campylobacter jejuni.

Penicillin-binding protein 2 (PBP2) plays a key role in the formation of peptidoglycans in bacterial cell walls by crosslinking glycan chains through transpeptidase activity. PBP2 is also found in Campylobacter jejuni, a pathogenic bacterium that causes food-borne enteritis in humans. To elucidate the essential structural features of C. jejuni PBP2 (cjPBP2) that mediate its biological function, we determined the crystal structure of cjPBP2 and assessed its protein stability under various conditions. cjPBP2 adopts an elongated two-domain structure, consisting of a transpeptidase domain and a pedestal domain, and contains typical active site residues necessary for transpeptidase activity, as observed in other PBP2 proteins. Moreover, cjPBP2 responds to ß-lactam antibiotics, including ampicillin, cefaclor, and cefmetazole, suggesting that ß-lactam antibiotics inactivate cjPBP2. In contrast to typical PBP2 proteins, cjPBP2 is a rare example of a Zn2+-binding PBP2 protein, as the terminal structure of its transpeptidase domain accommodates a Zn2+ ion via three cysteine residues and one histidine residue. Zn2+ binding helps improve the protein stability of cjPBP2, providing opportunities to develop new C. jejuni-specific antibacterial drugs that counteract the Zn2+-binding ability of cjPBP2.

Deep Learning Model for Real­time Semantic Segmentation During Intraoperative Robotic Prostatectomy.

Background and objective: Recently, deep learning algorithms, including convolutional neural networks (CNNs), have shown remarkable progress in medical imaging analysis. Semantic segmentation, which segments an unknown image into different parts and objects, has potential applications in robotic surgery in areas where artificial intelligence (AI) can be applied, such as in AI-assisted surgery, surgeon training, and skill assessment. We aimed to investigate the performance of a CNN-based deep learning model in real-time segmentation in robot-assisted radical prostatectomy (RALP). Methods: Intraoperative videos of RALP procedures were obtained. The reinforcement U-Net model was used for segmentation. Segmentation of the images of instruments, bladder, prostate, and seminal vesicle-vas deferens was performed. The dataset was preprocessed and split randomly into training, validation, and test data in a 7:2:1 ratio. Dice coefficient, intersection over union (IoU), and accuracy by class, which are commonly used in medical image segmentation, were calculated to evaluate the performance of the model. Key findings and limitations: From 120 patient videos, 2400 images were selected for RALP procedures. The mean Dice scores for the identification of the instruments, bladder, prostate, and seminal vesicle-vas deferens were 0.96, 0.74, 0.85, and 0.84, respectively. Overall, when applied to the test data, the model had a mean Dice coefficient value of 0.85, IoU of 0.77, and accuracy of 0.85. Limitations included the sample size, lack of diversity in the methods of surgery, incomplete surgical processes, and lack of external validation. Conclusions and clinical implications: The CNN-based segmentation provides accurate real-time recognition of surgical instruments and anatomy in RALP. Deep learning algorithms can be used to identify anatomy within the surgical field and could potentially be used to provide real-time guidance in robotic surgery. Patient summary: We demonstrate the potential effectiveness of deep learning segmentation in robotic prostatectomy procedures. Deep learning algorithms could be used to identify anatomical structures within the surgical field and may provide real-time guidance in robotic surgery.

Occurrence and Multiplex PCR Detection of Citrus Yellow Vein Clearing Virus in Korea.

Citrus yellow vein clearing virus (CYVCV) is a member of the Alphaflexiviridae family that causes yellow vein clearing symptoms on citrus leaves. A total of 118 leaf samples from nine regions of six provinces in Korea were collected from various citrus species in 2020 and 2021. Viral diagnosis using next-generation sequencing and reverse transcription polymerase chain reaction (RT-PCR) identified four viruses: citrus tristeza virus, citrus leaf blotch virus, citrus vein enation virus, and CYVCV. A CYVCV incidence of 9.3% was observed in six host plants, including calamansi, kumquat, Persian lime, and Eureka lemon. Among the citrus infected by CYVCV, only three samples showed a single infection; the other showed a mixed infection with other viruses. Eureka lemon and Persian lime exhibited yellow vein clearing, leaf distortion, and water-soak symptom underside of the leaves, while the other hosts showed only yellowing symptoms on the leaves. The complete genome sequences were obtained from five CYVCV isolates. Comparison of the isolates reported from the different geographical regions and hosts revealed the high sequence identity (95.2% to 98.8%). Phylogenetic analysis indicated that all the five isolates from Korea were clustered into same clade but were not distinctly apart from isolates from China, Pakistan, India, and Türkiye. To develop an efficient diagnosis system for the four viruses, a simultaneous detection method was constructed using multiplex RT-PCR. Sensitivity evaluation, simplex RT-PCR, and stability testing were conducted to verify the multiplex RT-PCR system developed in this study. This information will be useful for developing effective disease management strategies for citrus growers in Korea.

Mildly Reduced Renal Function Is Associated With Increased Heart Failure Admissions in Patients With Hypertrophic Cardiomyopathy.

BACKGROUND: The association between renal dysfunction and cardiovascular outcomes has yet to be determined in patients with hypertrophic cardiomyopathy (HCM). We aimed to investigate whether mildly reduced renal function is associated with the prognosis in patients with HCM. METHODS: Patients with HCM were enrolled at two tertiary HCM centers. Patients who were on dialysis, or had a previous history of heart failure (HF) or stroke were excluded. Patients were categorized into 3 groups by estimated glomerular filtration rate (eGFR): stage I (eGFR ≥ 90 mL/min/1.73 m², n = 538), stage II (eGFR 60-89 mL/min/1.73 m², n = 953), and stage III-V (eGFR < 60 mL/min/1.73 m², n = 265). Major adverse cardiovascular events (MACEs) were defined as a composite of cardiovascular death, hospitalization for HF (HHF), or stroke during median 4.0-year follow-up. Multivariable Cox regression model was used to adjust for covariates. RESULTS: Among 1,756 HCM patients (mean 61.0 ± 13.4 years; 68.1% men), patients with stage III-V renal function had a significantly higher risk of MACEs (adjusted hazard ratio [aHR], 2.71; 95% confidence interval [CI], 1.39-5.27; P = 0.003), which was largely driven by increased incidence of cardiovascular death and HHF compared to those with stage I renal function. Even in patients with stage II renal function, the risk of MACE (vs. stage I: aHR, 2.21' 95% CI, 1.23-3.96; P = 0.008) and HHF (vs. stage I: aHR, 2.62; 95% CI, 1.23-5.58; P = 0.012) was significantly increased. CONCLUSION: This real-world observation showed that even mildly reduced renal function (i.e., eGFR 60-89 mL/min/1.73 m²) in patients with HCM was associated with an increased risk of MACEs, especially for HHF.

Integrative Assessment of Cardiopulmonary Fitness Using Cardiopulmonary Exercise Test With Supine Bicycle Echocardiography in Patients Presenting Dyspnea.

BACKGROUND: Cardiopulmonary exercise test (CPET) with supine bicycle echocardiography (SBE) enables comprehensive physiologic assessment during exercise. We characterized cardiopulmonary fitness by integrating CPET-SBE parameters and evaluated its prognostic value in patients presenting with dyspnea. METHODS AND RESULTS: We retrospectively reviewed 473 consecutive patients who underwent CPET-SBE for dyspnea evaluation. A dimensionality reduction process was applied, transforming 24 clinical and CPET-SBE parameters into a 2-dimensional feature map, followed by patient clustering based on the data distribution. Clinical and exercise features were compared among the clusters in addition to the 5-year risk of clinical outcome (a composite of cardiovascular death and heart failure hospitalization). Maximum exercise effort (R >1) was achieved in 95% of cases. Through dimensionality reduction, 3 patient clusters were derived: Group 1 (n=157), 2 (n=104), and 3 (n=212). Median age and female proportion increased from Group 1 to 2, and 3, although resting echocardiography parameters showed no significant abnormalities among the groups. There was a worsening trend in the exercise response from Group 1 to 2 and 3, including left ventricular diastolic function, oxygen consumption, and ventilatory efficiency. During follow-up (median 6.0 [1.6-10.4] years), clinical outcome increased from Group 1 to 2 and 3 (5-year rate 3.7% versus 7.0% versus 13.0%, respectively; log-rank P=0.02), with higher risk in Group 2 (hazard ratio, 1.94 [95% CI, 0.52-7.22]) and Group 3 (3.92 [1.34-11.42]) compared with Group 1. CONCLUSIONS: Comprehensive evaluation using CPET-SBE can reveal distinct characteristics of cardiopulmonary fitness in patients presenting with dyspnea, potentially enhancing outcome prediction.

Overexpression of R2R3-MYB IbMYB1a induces anthocyanin pigmentation in soybean cotyledon.

KEY MESSAGE: This is the first report showing anthocyanin accumulation in the soybean cotyledon via genetic transformation of a single gene. Soybean [Glycine max (L.) Merrill] contains valuable components, including anthocyanins. To enhance anthocyanin production in Korean soybean Kwangankong, we utilized the R2R3-type MYB gene (IbMYB1a), known for inducing anthocyanin pigmentation in Arabidopsis. This gene was incorporated into constructs using two promoters: the CaMV 35S promoter (P35S) and the ß-conglycinin promoter (Pß-con). Kwangankong was transformed using Agrobacterium, and the presence of IbMYB1a and Bar transgenes in T0 plants was confirmed through polymerase chain reaction (PCR), followed by gene expression validation. Visual inspection revealed that one P35S:IbMYB1a and three Pß-con:IbMYB1a lines displayed seed color change. Pß-con:IbMYB1a T1 seeds accumulated anthocyanins in cotyledon outer layers, whereas P35S:IbMYB1a and non-transgenic black soybean (Cheongja 5 and Seum) accumulated anthocyanins in the seed coat. During the germination and growth phase, T1 seedlings from Pß-con:IbMYB1a lines exhibited anthocyanin pigmentation in cotyledons for up to 1 month without growth aberrations. High-performance liquid chromatography confirmed cyanidin-3-O-glucoside as the major anthocyanin in the Pß-con:IbMYB1a line (#3). We analyzed the expression patterns of anthocyanin biosynthesis genes, chalcone synthase 7,8, chalcone isomerase 1A, flavanone 3-hydroxylase, flavanone 3'-hydroxylase, dihydroflavanol reductase 1, dihydroflavanol reductase 2, anthocyanidin synthase 2, anthocyanidin synthase 3, and UDP glucose flavonoid 3-O-glucosyltransferase in transgenic and control Kwangankong and black soybean (Cheongja 5 and Seum) seeds using quantitative real-time PCR. We conclude that the induction of gene expression in transgenic plants in comparison with Kwangankong was attributable to IbMYB1a transformation. Notably, flavanone 3-hydroxylase, flavanone 3'-hydroxylase, and dihydroflavanol reductase 1 were abundantly expressed in black soybean seed coat, distinguishing them from transgenic cotyledons.

Circulating osteoprotegerin levels and cardiovascular outcomes in patients with pre-dialysis chronic kidney disease: results from the KNOW-CKD study.

While the relationship between circulating osteoprotegerin (OPG) and cardiovascular events is well-established in the general population, its association with cardiovascular risks in chronic kidney disease (CKD) patients remains less robust. This study hypothesized that elevated circulating OPG levels might be associated with an increased risk of major adverse cardiac events (MACE) in CKD patients, a total of 2,109 patients with CKD stages 1 through pre-dialysis 5 from the KNOW-CKD cohort were categorized into quartiles based on serum OPG levels. The primary outcome of the study was 3-point MACE, defined as a composite of nonfatal myocardial infarction, nonfatal stroke, or cardiac death. The median follow-up duration was 7.9 years. The cumulative incidence of 3-point MACE significantly varied across serum OPG levels in Kaplan-Meier curve analysis (P < 0.001, log-rank test), with the highest incidence observed in the 4th quartile. Cox regression analysis indicated that, relative to the 1st quartile, the risk of 3-point MACE was significantly higher in the 3rd (adjusted hazard ratio 2.901, 95% confidence interval 1.009 to 8.341) and the 4th quartiles (adjusted hazard ratio 4.347, 95% confidence interval 1.410 to 13.395). In conclusion, elevated circulating OPG levels are associated with adverse cardiovascular outcomes in pre-dialysis CKD patients.

Circulating osteoprotegerin as a cardiac biomarker for left ventricular diastolic dysfunction in patients with pre-dialysis chronic kidney disease: the KNOW-CKD study.

BACKGROUND: Heart failure with preserved ejection fraction (HFpEF) is a major cause of mortality in patients with chronic kidney disease (CKD), and diagnosis is challenging. Moreover, no specific biomarker for HFpEF has been validated in patients with CKD. The present study aimed to investigate the association between serum osteoprotegerin (OPG) levels and the risk of left ventricular diastolic dysfunction (LVDD), a surrogate of HFpEF, in patients with pre-dialysis CKD. METHODS: A total of 2039 patients with CKD at stage 1 to pre-dialysis 5 were categorized into quartiles (Q1 to Q4) by serum OPG levels, and were cross-sectionally analyzed. The study outcome was LVDD, which was operationally defined as the ratio of early transmitral blood flow velocity to early diastolic velocity of the mitral annulus (E/e') > 14. RESULTS: In the analysis of baseline characteristics, higher serum OPG levels were clearly related to the risk factors of HFpEF. A scatter plot analysis revealed a moderate correlation between serum OPG levels and E/e' (R = 0.351, P < 0.001). Logistic regression analysis demonstrated that the risk of LVDD in Q3 (adjusted odds ratio 2.576, 95% confidence interval 1.279 to 5.188) and Q4 (adjusted odds ratio 3.536, 95% confidence interval 1.657 to 7.544) was significantly higher than that in Q1. CONCLUSIONS: Elevated serum OPG levels are associated with the risk of LVDD in patients with pre-dialysis CKD. The measurement of serum OPG levels may help the diagnosis of LVDD, which is an important echocardiographic feature of HFpEF.

Immunogenicity and protective efficacy of RipA, a peptidoglycan hydrolase, against Mycobacterium tuberculosis Beijing outbreak strains.

Given that individuals with latent tuberculosis (TB) infection represent the major reservoir of TB infection, latency-associated antigens may be promising options for development of improved multi-antigenic TB subunit vaccine. Thus, we selected RipA, a peptidoglycan hydrolase required for efficient cell division of Mycobacterium tuberculosis (Mtb), as vaccine candidate. We found that RipA elicited activation of dendritic cells (DCs) by induction of phenotypic maturation, increased production of inflammatory cytokines, and prompt stimulation of MAPK and NF-κB signaling pathways. In addition, RipA-treated DCs promoted Th1-polarzied immune responses of naïve CD4+ T cells with increased proliferation and activated T cells from Mtb-infected mice, which conferred enhanced control of mycobacterial growth inside macrophages. Moreover, mice immunized with RipA formulated in GLA-SE adjuvant displayed remarkable generation of Ag-specific polyfunctional CD4+ T cells in both lung and spleen. Following an either conventional or ultra-low dose aerosol challenges with 2 Mtb Beijing clinical strains, RipA/GLA-SE-immunization was not inferior to BCG by mediating protection as single Ag. Collectively, our findings highlighted that RipA could be a novel candidate as a component of multi-antigenic TB subunit vaccines.

Angular dihydropyranocoumarins from the flowers of Peucedanum japonicum and their aldo-keto reductase inhibitory activities.

Twenty-one angular dihydropyranocoumarins and a linear furanocoumarin, including four previously undescribed compounds (1-4), were isolated from the flowers of Peucedanum japonicum (Umbelliferae). The structures of 1-4, along with their absolute stereochemistry, were determined to be (3'S,4'S)-3'-O-propanoyl-4'-O-(3‴-methyl-2‴-butenoyl)khellactone (1), (3'S,4'S)-3'-O-propanoyl-4'-O-(2‴-methyl-2‴Z-butenoyl)khellactone (2), (3'S,4'S)-3'-O-propanoyl-4'-O-(2‴-methylbutanoyl)khellactone (3), and (3'S,4'S)-3'-O-(2″-methylpropanoyl)-4'-O-(3‴-methyl-2‴-butenoyl)khellactone (4) using one- and two-dimensional nuclear magnetic resonance, high-resolution electrospray ionization mass spectroscopy, and electronic circular dichroism spectroscopy. In addition, the absolute configuration of the three angular dihydropyranocoumarins (5-7) was determined for the first time in this study. Among the previously reported compounds isolated in this study, 8 and 9 were isolated for the first time from the genus Peucedanum, whereas 10 and 11 were previously unreported and had not been isolated from P. japonicum to date. Furthermore, all isolated compounds were evaluated for their aldo-keto reductase 1C1 inhibitory activities on A549 human non-small-cell lung cancer cells. Compounds 10 and 12 exhibited substantial AKR1C1 inhibitory activities with IC50 values of 35.8 ± 0.9 and 44.2 ± 1.5 µM, respectively.

Age-dependent implications of left ventricular hypertrophy regression in patients with hypertension.

Left ventricular hypertrophy (LVH) is a significant risk factor for cardiovascular mortality and morbidity in patients with hypertension. However, the effect of age on LVH regression or persistence and its differential prognostic value remain unclear. Therefore, we investigated the clinical implications of LVH regression in 1847 patients with hypertension and echocardiography data (at baseline and during antihypertensive treatment at an interval of 6-18 months) according to age. LVH was defined as a left ventricular mass index (LVMI) > 115 g/m2 and >95 g/m2 in men and women, respectively. LVH prevalence at baseline was not different according to age (age < 65 years: 42.6%; age ≥65 years: 45.7%; p = 0.187), but LVH regression was more frequently observed in the younger group (36.4% vs. 27.5%; p = 0.008). Spline curves and multiple linear regression analysis showed a significant relationship between reductions in systolic blood pressure and LVMI in the younger group (ß = 0.425; p < 0.001), but not the elderly group (ß = 0.044; p = 0.308). LVH regression was associated with a lower risk of the study outcome (composite of cardiovascular death and hospitalization for heart failure) regardless of age. In conclusion, the association between the reduction in blood pressure and LVH regression was prominent in patients with age < 65 years, but not in those with age ≥65 years. However, an association between LVH regression and lower risk of cardiovascular death and hospitalization for heart failure was observed regardless of patient age, suggesting the prognostic value of the LVH regression not only in the younger patients but also in elderly patients.