OTUD7B knockdown inhibits proliferation and autophagy through AKT/mTOR signaling pathway in human prostate cancer cell.

Prostate cancer (PCa) is the second leading disease of cancer-related death in men around the world, and it is almost impossible to treat advanced PCa. OTUD7B is a member of the deubiquitinase family that undergoes a post-translational transformation process, which is essential for cell stability and signaling and is known to play a critical role in cancer. However, its role in PCa has not been discovered. The aim of the study was to investigate the expression and mechanism of OTUD7B in PCa cells. According to the database, high OTUD7B expression showed a poor prognosis. Therefore, we downregulated OTUD7B using siRNA and confirmed the role of OTUD7B in PC3 prostate cancer cells. OTUD7B knockdown effectively induced apoptosis and inhibited the proliferation in PC3 cells. OTUD7B knockdown inhibited autophagy through AKT/mTOR signaling. We also confirmed the relationship between AKT/mTOR signaling and autophagy through rapamycin, an mTOR inhibitor. Taken together, OTUD7B promotes the proliferation, and autophagy, and inhibits apoptosis of prostate cancer cells via the AKT/mTOR signaling pathway.

Novel role of LLGL2 silencing in autophagy: reversing epithelial-mesenchymal transition in prostate cancer.

PURPOSE: Prostate cancer (PCa) is a major urological disease that is associated with significant morbidity and mortality in men. LLGL2 is the mammalian homolog of Lgl. It acts as a tumor suppressor in breast and hepatic cancer. However, the role of LLGL2 and the underlying mechanisms in PCa have not yet been elucidated. Here, we investigate the role of LLGL2 in the regulation of epithelial-mesenchymal transition (EMT) in PCa through autophagy in vitro and in vivo. METHODS: PC3 cells were transfected with siLLGL2 or plasmid LLGL2 and autophagy was examined. Invasion, migration, and wound healing were assessed in PC3 cells under autophagy regulation. Tumor growth was evaluated using a shLLGL2 xenograft mouse model. RESULTS: In patients with PCa, LLGL2 levels were higher with defective autophagy and increased EMT. Our results showed that the knockdown of LLGL2 induced autophagy flux by upregulating Vps34 and ATG14L. LLGL2 knockdown inhibits EMT by upregulating E-cadherin and downregulating fibronectin and α-SMA. The pharmacological activation of autophagy by rapamycin suppressed EMT, and these effects were reversed by 3-methyladenine treatment. Interestingly, in a shLLGL2 xenograft mouse model, tumor size and EMT were decreased, which were improved by autophagy induction and worsened by autophagy inhibition. CONCLUSION: Defective expression of LLGL2 leads to attenuation of EMT due to the upregulation of autophagy flux in PCa. Our results suggest that LLGL2 is a novel target for alleviating PCa via the regulation of autophagy.

SleepMI: An AI-based screening algorithm for myocardial infarction using nocturnal electrocardiography.

Myocardial infarction (MI) is a common cardiovascular disease, the early diagnosis of which is essential for effective treatment and reduced mortality. Therefore, novel methods are required for automatic screening or early diagnosis of MI, and many studies have proposed diverse conventional methods for its detection. In this study, we aimed to develop a sleep-myocardial infarction (sleepMI) algorithm for automatic screening of MI based on nocturnal electrocardiography (ECG) findings from diagnostic polysomnography (PSG) data using artificial intelligence (AI) models. The proposed sleepMI algorithm was designed using representation and ensemble learning methods and optimized via dropout and batch normalization. In the sleepMI algorithm, a deep convolutional neural network and light gradient boost machine (LightGBM) models were mixed to obtain robust and stable performance for screening MI from nocturnal ECG findings. The nocturnal ECG signal was extracted from 2,691 participants (2,331 healthy individuals and 360 patients with MI) from the PSG data of the second follow-up stage of the Sleep Heart Health Study. The nocturnal ECG signal was extracted 3 h after sleep onset and segmented at 30-s intervals for each participant. All ECG datasets were divided into training, validation, and test sets consisting of 574,729, 143,683, and 718,412 segments, respectively. The proposed sleepMI model exhibited very high performance with precision, recall, and F1-score of 99.38%, 99.38%, and 99.38%, respectively. The total mean accuracy for automatic screening of MI using a nocturnal single-lead ECG was 99.387%. MI events can be detected using conventional 12-lead ECG signals and polysomnographic ECG recordings using our model.

Hemodialysis Efficiency Predictor in End-Stage Kidney Disease Using Real-Time Heart Rate Variability.

BACKGROUND: Autonomic dysfunction as a long-term complication may occur in end-stage kidney disease (ESKD) patients and can be diagnosed using heart rate variability (HRV) analyzed from electrocardiogram (ECG) recordings. There is limited data about HRV using real-time ECG to predict hemodialysis (HD) efficiency in patients with ESKD who are routinely doing HD in the real world. METHODS: A total of 50 patients (62.1 ± 10.7 years) with ESKD underwent continuous real-time ECG monitoring (237.4 ± 15.3 min) during HD for HRV using remote monitoring system. Their electrolyte levels were checked before and after HD. We compared HRV according to electrolyte levels. RESULTS: During the monitor, we checked the ECG and electrolyte levels simultaneously a total of 2374 times for all of the patients. Both time and frequency domain HRV were higher when the patients had lower K+ level (<0.5 mEq/L) and P+ level change (<2 mEq/L) before and after HD as compared to those with a higher K+ level (≥0.5 mEq/L) and P+ level change (≥2 mEq/L). Additionally, patients with lower K+ and P+ level change groups had higher incidences of arrhythmic events including atrial/ventricular premature complexes, despite no difference of mean heart rate (p < 0.001). CONCLUSIONS: Higher HRV was independently associated with a poorly controlled K+ and P+ level during HD in patients with ESKD. This is consistently evidenced by the independent association between higher HRV, K+ and P+ levels in real time, suggesting that low electrolyte changes before and after HD alone may cause cardiac autonomic dysfunction.

Fulvestrant alleviates cisplatin-induced acute kidney injury via repression of BNIP3-mediated apoptosis and autophagy.

Cisplatin-induced acute kidney injury (AKI) is a clinical disease characterized by a sudden loss of renal function within a few hours or days, due to cisplatin uptake. Fulvestrant is an oestrogen receptor alpha (ERα) antagonist used for endocrine therapy. However, the role of fulvestrant in cisplatin-induced AKI remains unclear. In this study, we investigated the effects of fulvestrant on the regulation of apoptotic cell death and autophagic response in cisplatin-induced AKI. The human kidney proximal tubule epithelial cell line (HK-2) was co-treated with fulvestrant and cisplatin. C57BL/6 mice were subcutaneously injected with fulvestrant and cisplatin was administered via intraperitoneal injection. First, cisplatin treatment increased ERα expression, apoptosis, and autophagy in HK-2 cells. Fulvestrant treatment decreased apoptosis and autophagy, which were accompanied by cisplatin treatment in HK-2 cells. Consistent with in vitro results, cisplatin treatment significantly increased ERα expression in vivo. Additionally, cisplatin treatment increased renal injury, apoptosis, and autophagy. Surprisingly, compared to that in the cisplatin-treated mice group, reduced cisplatin-induced renal injury, apoptosis, and autophagy was observed in the cisplatin+fulvestrant-treated mice group. In summary, these results suggest that fulvestrant plays an important role in cisplatin-induced AKI by decreasing apoptosis and autophagy.

Real-time heart rate variability according to ambulatory glucose profile in patients with diabetes mellitus.

Background: Autonomic neuropathy commonly occurs as a long-term complication of diabetes mellitus (DM) and can be diagnosed based on heart rate variability (HRV), calculated from electrocardiogram (ECG) recordings. There are limited data on HRV using real-time ECG and ambulatory glucose monitoring in patients with DM. The aim of this study was to investigate real-time HRV according to ambulatory glucose levels in patients with DM. Methods: A total of 43 patients (66.3 ± 7.5 years) with DM underwent continuous real-time ECG monitoring (225.7 ± 107.3 h) for HRV and ambulatory glucose monitoring using a remote monitoring system. We compared the HRV according to the ambulatory glucose profile. Data were analyzed according to the target in glucose range (TIR). Results: There were no significant differences in the baseline characteristics of the patients according to the TIR. During monitoring, we checked ECG and ambulatory glucose levels (a total of 15,090 times) simultaneously for all patients. Both time- and frequency-domain HRVs were lower when the patients had poorly controlled glucose levels (TIR < 70%) compared with well controlled glucose levels (TIR > 70%). In addition, heart and respiratory rates increased with real-time glucose levels (P < 0.001). Conclusions: Poorly controlled glucose levels were independently associated with lower HRV in patients with DM. This was further substantiated by the independent continuous association between real-time measurements of hyperglycemia and lower HRV. These data strongly suggest that cardiac autonomic dysfunction is caused by elevated blood sugar levels.

Simply structured polarization-independent high efficiency multilayer dielectric gratings.

A polarization-independent multilayer dielectric diffraction grating with a low aspect ratio and high diffraction efficiency was designed and fabricated. The diffraction grating designed with a grating density of 1200 lines/mm had an aspect ratio of 0.59, mean polarization-independent diffraction efficiency in the Littrow angle of ±2.5∘, and 1030-1080 nm wavelength range of 97.2%. The designed grating was fabricated using ion assisted deposition and reactive ion etching techniques. The mean polarization-independent diffraction efficiency of the fabricated grating was 96.1%, and its standard deviation was 0.68%. The fabricated diffraction grating was irradiated with a 1064 nm cw laser, with a power density of 30kW/cm2, for 1 min to measure the temperature change before and after the laser application. It was verified that the temperature variation of the diffraction grating without heat treatment was 8.8°C, and the temperature variation after heat treatment at 400°C decreased to 2.3°C.

New real-time heartbeat detection method using the angle of a single-lead electrocardiogram.

This study presents a new real-time heartbeat detection algorithm using the geometric angle between two consecutive samples of single-lead electrocardiogram (ECG) signals. The angle was adopted as a new index representing the slope of ECG signal. The method consists of three steps: elimination of high-frequency noise, calculation of the angle of ECG signal, and detection of R-waves using a simple adaptive thresholding technique. The MIT-BIH arrhythmia database, QT database, European ST-T database, T-wave alternans database and synthesized ECG signals were used to evaluate the performance of the proposed algorithm and compare with the results of other methods suggested in literature. The proposed method shows a high detection rate-99.95% of the sensitivity, 99.95% of the positive predictivity, and 0.10% of the fail detection rate on the four databases. The result shows that the proposed method can yield better or comparable performance than other literature despite the relatively simple process. The proposed algorithm needs only a single-lead ECG, and involves a simple and quick calculation. Moreover, it does not require post-processing to enhance the detection. Thus, it can be effectively applied to various real-time healthcare and medical devices.

A design of RF stimulator which is similar to temperature distribution by moxibustion (preliminary study).

We developed a novel radio-frequency (RF) stimulator to mimic heat effects similar to the temperature distributions created by moxibustion in porcine tissue. Moxibustion is a traditional Oriental medicine technique using moxa, which is utilized not only to cure disease, but also to increase immunity. However, it may lead to undesired effects including severe pains, blisters, and burns because of the difficulty of controlling heat intensity during the process. To overcome these problems, a novel RF stimulator that can conduct thermal energy to the deep tissue of the body and also easily control the power of heat stimulation was proposed. RF stimulating protocols were designed to mimic the temperature profiles of two types of moxibustion. In our results, the temperature distributions created by the proposed protocols were similar to those attained by moxibustion. It was also shown that the proposed protocols were more effective than moxibustion for transferring heat effects into deep tissues.

Development of a cardiorespiratory monitoring system based on pressure change of aircushion.

Heartbeat and respiration are fundamental vital signs used for estimation of patient's status. In this study, we have proposed a simple method to monitor the heartbeat and respiration based on displacements of human body which occur due to periodic heartbeat and breathing.

Novel algorithm for the hemiplegic gait evaluation using a single 3-axis accelerometer.

This paper suggests the novel algorithm for the estimating gait parameters of the hemiplegic patients using a 3-axis accelerometer. The signal processing for algorithm consists of a bandpass filter and a least square acceleration filter. To evaluate the performance of the algorithm, the correlation coefficients of the stride and the step time between the 3-axis accelerometer and the Vicon motion analysis system are compared. In consequence, correlation coefficient ranged from 0.90 to 0.99 for patients and ranged from 0.92 to 0.99 for normal subjects. The results showed that the novel algorithm is very useful for estimating not only hemiplegic gait but also normal gait.

The concurrent validity of the body center of mass in accelerometric measurement.

Accurate estimation of the body center of mass (COM) location has important clinical ramifications in locomotion associated with daily activities of living (ADL). This paper compared two computational estimation methods of COM using an accelerometric measurement and a VICON motion analysis system measurement (established or golden standard), respectively. A convenient sample of four healthy subjects participated. The body COM was measured when the subjects walked on the 6-m long walkway at their self-selected speed for 5 trials. VICON and accelerometer COM data signals were computed by VICON Polygon and trapezoidal double integration methods, respectively and compared to determine the concurrent validity of our COM estimation method. Correlation statistics showed excellent relationship between the two methods (r =0.87, P< 0.05), reflecting an acceptable validity. Our results suggest that the COM estimation using the accelerometer method is as accurate as the conventional method and provide clinical insights when designing a portable and inexpensive COM measurement tool for locomotion evaluation.

Adaptive noise canceling of electrocardiogram artifacts in single channel electroencephalogram.

A new method for estimating and eliminating electrocardiogram (ECG) artifacts from single channel scalp electroencephalogram (EEG) is proposed. The proposed method consists of emphasis of QRS complex from EEG using least squares acceleration (LSA) filter, generation of synchronized pulse with R-peak and ECG artifacts estimation and elimination using adaptive filter. The performance of the proposed method was evaluated using simulated and real EEG recordings, we found that the ECG artifacts were successfully estimated and eliminated in comparison with the conventional multi-channel techniques, which are independent component analysis (ICA) and ensemble average (EA) method. From this we can conclude that the proposed method is useful for the detecting and eliminating the ECG artifacts from single channel EEG and simple to use for ambulatory/portable EEG monitoring system.

The novel method for the fetal electrocardiogram extraction from the abdominal signal.

In this paper, we have proposed a new method to extract the fetal ECG from a pregnant woman's abdominal signal using least square acceleration (LSA) filter and adaptive impulse correlation (AIC) filter. To evaluate the performance, the proposed method and other fetal ECG extraction techniques were processed using the synthetic and real ECG data and then the results were compared. According to comparative results, the proposed method is powerful and successful for extracting the fetal ECG. It was able to separate perfectly even though the fetal beats overlap with the QRS wave of the maternal beats and to extract fetal ECG using any single-channel abdominal signal measured from pregnant woman's abdominal surface. Also, it could be implemented easily by fast computation time and simple structure. It is sure that our method could be useful for portable fetal monitoring system.