Search Results (8)

Background/Objectives: To compare the outcomes of single-port access laparoscopic surgery (SPALS) and single-site robotic surgery (SSRS) for benign gynecological diseases, we retrospectively analyzed clinical data from 367 patients who underwent gynecologic surgery at Sejong Chungnam National University Hospital from October 2020 to December 2023. Methods: Of these 367 patients, 197 underwent SPALS, whereas 170 underwent SSRS. The SPALS group comprised 87 patients who underwent hysterectomy; 107, adnexal surgery (cystectomy: 44, adnexectomy: 63); and 1 myomectomy. The SSRS group included 68 patients who underwent myomectomy; 61, adnexal surgery (cystectomy: 52, adnexectomy: 9); 35, hysterectomy, and 4, sacrocolpopexy. Results: Both surgical techniques were successful, with no patients requiring open surgery. No significant differences were observed in the baseline characteristics between the two groups. Compared with the SPALS group, the SSRS group had a younger age (39.8 ± 9.5 vs. 44.5 ± 12.3 years, p = 0.001). Severe intra-abdominal adhesions were more frequently observed in the SSRS group (p = 0.004). Operation time (118.1 ± 65.9 vs. 57.1 ± 27.3 min, p = 0.001), gas passing time (39.4 ± 15.37 vs. 30.4 ± 13.5 h, p = 0.001), and hospital length of stay (4.26 ± 1.02 vs. 4.02 ± 0.8 days, p = 0.012) were significantly longer in the SSRS group. However, no significant differences were found between the two groups in terms of intraoperative blood loss, intraoperative complications, or readmission rates. Conclusions: SSRS offers a feasible and promising approach for treating gynecological benign diseases. Younger and lower-parity patients tend to undergo SSRS rather than SPALS, with SSRS primarily performed for myomectomy and complex adnexal surgery. However, operation time and gas passing time were significantly longer in the SSRS group. Full article

Background: The European Foundation for the Study of Chronic Liver Failure (EF-CLIF) consortium suggested that the clinical courses after acute decompensation (AD) stratify the long-term prognosis: stable decompensated cirrhosis (SDC), unstable decompensated cirrhosis (UDC), pre acute-on-chronic liver failure (pre ACLF), and ACLF. However, previous studies included patients with a history of previous AD and had limitations associated with identifying the clinical factors related to prognosis after the first AD. Method: The prospective Korean Acute-on-Chronic Liver Failure (KACLiF) cohort included cirrhotic patients who were hospitalised with first AD between July 2015 and August 2018. We analysed the factors associated with readmission after the first AD and compared the characteristics and prognosis among each subgroup to evaluate the risk factors for the occurrence of pre ACLF after AD. Result: A total of 746 cirrhotic patients who were hospitalised with first AD were enrolled. The subgroups consisted of SDC (n = 565), UDC (n = 29), pre ACLF (n = 28), and ACLF (n = 124). Of note, pre ACLF showed a poorer prognosis than ACLF. The risk factors associated with readmission within 3 months of first AD were non-variceal gastrointestinal (GI) bleeding, hepatic encephalopathy (HE), and high MELD score. Viral aetiology was associated with the occurrence of pre ACLF compared with alcohol aetiology regardless of baseline liver function status. Conclusion: Cirrhotic patients with first AD who present as non-variceal GI bleeding and HE can easily relapse. Interestingly, the occurrence of AD with organ failure within 3 months of first AD (pre ACLF) has worse prognosis compared with the occurrence of organ failure at first AD (ACLF). In particular, cirrhotic patients with viral hepatitis with/without alcohol consumption showed poor prognosis compared to other aetiologies. Therefore, patients with ACLF after AD within 3 months should be treated more carefully and definitive treatment through LT should be considered. Full article

In recent years, the supply of electric vehicles, which are eco-friendly cars that use electric energy rather than fossil fuels, which cause air pollution, is increasing. Accordingly, it is emerging as an urgent task to predict the charging demand for the smooth supply of electric energy required to charge electric vehicle batteries. In this paper, to predict the charging demand, time series analysis is performed based on two types of frames: One is using traditional time series techniques such as dynamic harmonic regression, seasonal and trend decomposition using Loess, and Bayesian structural time series. The other is the most widely used machine learning techniques, including random forest and extreme gradient boosting. However, the tree-based machine learning approaches have the disadvantage of not being able to capture the trend, so a hybrid strategy is proposed to overcome this problem. In addition, the seasonal variation is reflected as the feature by using the Fourier transform which is useful in the case of describing the seasonality patterns of time series data with multiple seasonality. The considered time series models are compared and evaluated through various accuracy measures. The experimental results show that the machine learning approach based on the hybrid strategy generally achieves significant improvements in predicting the charging demand. Moreover, when compared with the original machine learning method, the prediction based on the proposed hybrid strategy is more accurate than that based on the original machine learning method. Based on these results, it can find out that the proposed hybrid strategy is useful for smoothly planning future power supply and demand and efficiently managing electricity grids. Full article

Background: The platelet-to-white blood cell ratio (PWR) is a hematologic marker of the systemic inflammatory response. Recently, the PWR was revealed to have a role as an independent prognostic factor for mortality in patients with hepatitis B virus (HBV)-related acute-on-chronic failure (ACLF) and HBV-related liver cirrhosis (LC) with acute decompensation (AD). However, the prognostic role of the PWR still needs to be investigated in LC patients with AD. In this study, we analyzed whether the PWR could stratify the risk of adverse outcomes (death or liver transplantation (LT)) in these patients. Methods: A prospective cohort of 1670 patients with AD of liver cirrhosis ((age: 55.2 ± 7.8, male = 1226 (73.4%)) was enrolled and evaluated for 28-day and overall adverse outcomes. Results: During a median follow-up of 8.0 months (range, 1.9–15.5 months), 424 (25.4%) patients had adverse outcomes (death = 377, LT = 47). The most common etiology of LC was alcohol use (69.7%). The adverse outcome rate was higher for patients with a PWR ? 12.1 than for those with a PWR > 12.1. A lower PWR level was a prognostic factor for 28-day adverse outcomes (PWR: hazard ratio 1.707, p = 0.034) when adjusted for the etiology of cirrhosis, infection, ACLF, and the MELD score. In the subgroup analysis, the PWR level stratified the risk of 28-day adverse outcomes regardless of the presence of ACLF or the main form of AD but not for those with bacterial infection. Conclusions: A lower PWR level was associated with 28-day adverse outcomes, indicating that the PWR level can be a useful and simple tool for stratifying the risk of 28-day adverse outcomes in LC patients with AD. Full article

This paper proposes a new approach based on the regression framework employing a pivotal quantity to estimate unknown parameters of a Weibull distribution under the progressive Type-II censoring scheme, which provides a closed form solution for the shape parameter, unlike its maximum likelihood estimator counterpart. To resolve serious rounding errors for the exact mean and variance of the pivotal quantity, two different types of Taylor series expansion are applied, and the resulting performance is enhanced in terms of the mean square error and bias obtained through the Monte Carlo simulation. Finally, an actual application example, including a simple goodness-of-fit analysis of the actual test data based on the pivotal quantity, proves the feasibility and applicability of the proposed approach. Full article

Lactate dehydrogenase A (LDHA) is an important enzyme responsible for cancer growth and energy metabolism in various cancers via the aerobic glycolytic pathway. Here, we report that machilin A (MA), which acts as a competitive inhibitor by blocking the nicotinamide adenine dinucleotide (NAD) binding site of LDHA, suppresses growth of cancer cells and lactate production in various cancer cell types, including colon, breast, lung, and liver cancers. Furthermore, MA markedly decreased LDHA activity, lactate production, and intracellular adenosine triphosphate (ATP) levels induced by hypoxia-induced LDHA expression in cancer cells, and significantly inhibited colony formation, leading to reduced cancer cell survival. In mouse models inoculated with murine Lewis lung carcinoma, MA significantly suppressed tumor growth as observed by a reduction of tumor volume and weight; resulting from the inhibition of LDHA activity. Subsequently, the suppression of tumor-derived lactic acid in MA-treated cancer cells resulted in decrease of neovascularization through the regulation of alternatively activated macrophages (M2) polarization in macrophages. Taken together, we suggest that the reduction of lactate by MA in cancer cells directly results in a suppression of cancer cell growth. Furthermore, macrophage polarization and activation of endothelial cells for angiogenesis were indirectly regulated preventing lactate production in MA-treated cancer cells. Full article

This paper derives the entropy of a generalized half-logistic distribution based on Type-II censored samples, obtains some entropy estimators by using Bayes estimators of an unknown parameter in the generalized half-logistic distribution based on Type-II censored samples and compares these estimators in terms of the mean squared error and the bias through Monte Carlo simulations. Full article

In many life-testing and reliability studies, the experimenter might not always obtain complete information on failure times for all experimental units. Multiply Type-II censored sampling arises in a life-testing experiment whenever the experimenter does not observe the failure times of some units placed on a life-test. In this paper, we obtain estimators for the entropy function of a double exponential distribution under multiply Type-II censored samples using the maximum likelihood estimation and the approximate maximum likelihood estimation procedures. We compare the proposed estimators in the sense of the mean squared errors by using Monte Carlo simulation. Full article