Effect and mechanism of needleless transcutaneous neuromodulation on gastrointestinal function after pancreaticoduodenectomy.

BACKGROUND: Gastrointestinal motility disorders tend to develop after pancreaticoduodenectomy (PD). The objectives of this study were: (1) to investigate the impact of needleless transcutaneous neuromodulation (TN) on the postoperative recuperation following pancreaticoduodenectomy (PD), and (2) to explore the underlying mechanisms by which TN facilitates the recovery of gastrointestinal function after PD. METHODS: A total of 41 patients scheduled for PD were randomized into two groups: the TN group (n = 21) and the Sham-TN group (n = 20). TN was performed at acupoints ST-36 and PC-6 twice daily for 1 h from the postoperative day 1 (POD1) to day 7. Sham-TN was performed at non-acupoints. Subsequent assessments incorporated both heart rate variation and dynamic electrogastrography to quantify alterations in vagal activity (HF) and gastric pacing activity. RESULTS: 1)TN significantly decreased the duration of the first passage of flatus (p < 0.001) and defecation (p < 0.01) as well as the time required to resume diet (p < 0.001) when compared to sham-TN;2)Compared with sham-TN, TN increased the proportion of regular gastric pacing activity (p < 0.01);3) From POD1 to POD7, there was a discernible augmentation in HF induced by TN stimulation(p < 0.01);4) TN significantly decreased serum IL-6 levels from POD1 to POD7 (p < 0.001);5) TN was an independent predictor of shortened hospital stay(ß = - 0.349, p = 0.035). CONCLUSION: Needleless TN accelerates the recovery of gastrointestinal function and reduces the risk of delayed gastric emptying in patients after PD by enhancing vagal activity and controlling the inflammatory response.

A novel method for detecting credit card fraud problems.

Credit card fraud is a significant problem that costs billions of dollars annually. Detecting fraudulent transactions is challenging due to the imbalance in class distribution, where the majority of transactions are legitimate. While pre-processing techniques such as oversampling of minority classes are commonly used to address this issue, they often generate unrealistic or overgeneralized samples. This paper proposes a method called autoencoder with probabilistic xgboost based on SMOTE and CGAN(AE-XGB-SMOTE-CGAN) for detecting credit card frauds.AE-XGB-SMOTE-CGAN is a novel method proposed for credit card fraud detection problems. The credit card fraud dataset comes from a real dataset anonymized by a bank and is highly imbalanced, with normal data far greater than fraud data. Autoencoder (AE) is used to extract relevant features from the dataset, enhancing the ability of feature representation learning, and are then fed into xgboost for classification according to the threshold. Additionally, in this study, we propose a novel approach that hybridizes Generative Adversarial Network (GAN) and Synthetic Minority Over-Sampling Technique (SMOTE) to tackle class imbalance problems. Our two-phase oversampling approach involves knowledge transfer and leverages the synergies of SMOTE and GAN. Specifically, GAN transforms the unrealistic or overgeneralized samples generated by SMOTE into realistic data distributions where there is not enough minority class data available for GAN to process effectively on its own. SMOTE is used to address class imbalance issues and CGAN is used to generate new, realistic data to supplement the original dataset. The AE-XGB-SMOTE-CGAN algorithm is also compared to other commonly used machine learning algorithms, such as KNN and Light GBM, and shows an overall improvement of 2% in terms of the ACC index compared to these algorithms. The AE-XGB-SMOTE-CGAN algorithm also outperforms KNN in terms of the MCC index by 30% when the threshold is set to 0.35. This indicates that the AE-XGB-SMOTE-CGAN algorithm has higher accuracy, true positive rate, true negative rate, and Matthew's correlation coefficient, making it a promising method for detecting credit card fraud.

Measurement of electrolyte concentrations in expressed prostatic secretion and urine from patients with chronic prostatitis and its implications.

This study was aimed at measuring concentration of electrolytes, especially K+ in expressed prostatic secretion (EPS) and urine from patients with chronic prostatitis. The concentration of potassium, sodium, chloride, calcium in EPS and urine of 31 controls and 79 patients with prostatitis were measured and analyzed. There was no significant difference in the concentrations of potassium, sodium, chloride and calcium between the patients and the controls. Among the patients treated effectively, potassium concentration was 40.66 +/- 17.10 mmol/l before treatment and 33.42 +/- 17.27 mmol/l after treatment. While among the patients treated ineffectively, potassium concentration was measured as 37.57 +/- 16.93 mmol/l and 50.66 +/- 18.77 mmol/l before and after treatment respectively. The concentrations of electrolytes in prostatic fluid varied greatly between individuals. Potassium concentration in EPS decreased significantly after treatment among the patients with obvious treatment effectiveness, while increased among those who failed the treatment. EPS potassium concentration was also found to be lower in patients with pain than those without pain. No significant difference was found between the normal group and the no-pain patients.