Serum Raman spectroscopy combined with multiple classification models for rapid diagnosis of breast cancer.

Breast cancer is a malignant tumor with the highest incidence rate in women. Current diagnostic methods are time-consuming, costly, and dependent on physician experience. In this study, we used serum Raman spectroscopy combined with multiple classification algorithms to implement an auxiliary diagnosis method for breast cancer, which will help in the early diagnosis of breast cancer patients. We analyzed the serum Raman spectra of 171 invasive ductal carcinoma (IDC) and 100 healthy volunteers; The analysis showed differences in nucleic acids, carotenoids, amino acids, and lipid concentrations in their blood. These differences provide a theoretical basis for this experiment. First, we used adaptive iteratively reweighted penalized least squares (airPLS) and Savitzky-Golay (SG) for baseline correction and smoothing denoising to remove the effect of noise on the experiment. Then, the Principal component analysis (PCA) algorithm was used to extract features. Finally, we built four classification models: support vector machine (SVM), decision tree (DT), linear discriminant analysis (LDA), and Neural Network Language Model (NNLM). The LDA, SVM, and NNLM achieve 100% accuracy. As supplementary, we added the classification experiment of the raw data. By comparing the experimental results of the two groups, We concluded that the NNLM was the best model. The results show the reliability of the combination of serum Raman spectroscopy and classification models under large sample conditions.

Serum metabolomics study of anxiety disorder patients based on LC-MS.

BACKGROUND: In the current environment of increasing social pressure, anxiety disorder has become a kind of health problem that needs to be solved urgently. However, the pathological mechanism of anxiety is still unclear, the classification of clinical diagnosis and symptoms is complex, and there is still a lack of biomarkers that can be identified and judged. METHODS: This study used LC-MS and non-targeted metabolomics to analyze the clinically collected plasma of 18 samples from anxiety disorder patients and 31 samples from healthy people to screen differential metabolites and perform subsequent metabolic pathway analysis. Binary Logistic regression was used to construct the anxiety disorder diagnosis prediction model and evaluate the prediction efficacy. RESULTS: The results showed that 22 metabolites were disturbed in the plasma of anxiety patients compared with healthy people. These metabolites mainly participate in 6 metabolic pathways. The combined diagnostic factors 4-Acetamidobutanoate, 3-Hydroxysebacic acid, and Cytosine were used to construct the diagnosis prediction model. The prediction probability of the model is 91.8%, the Youden index is 0.889, the sensitivity is 0.889, and the specificity is 1.000, so the prediction effect is good. CONCLUSIONS: This study preliminarily analyzed and explored the differences between plasma samples from patients with anxiety disorder and healthy individuals, increased the types of potential biomarkers for anxiety disorder, and provided a valuable reference for subsequent research related to anxiety disorder.

Application of lipidomics strategy to explore aging-related biomarkers and potential anti-aging mechanisms of ginseng.

Aging often leads to an increase risk of age-related diseases, and the development of anti-aging drugs have become the trend and focus of the current scientific research. In this experiment, serum samples from healthy people of different ages were analyzed based on clinical lipidomics, and a total of 10 potential biomarkers in middle-aged and youth group, 20 biomarkers in the youth and the elderly group were obtained. Furthermore, dhSph and dhCer involved above may affect the aging process through sphingolipid metabolic pathway. As the first and rate-limiting step of catalyzing de novo sphingolipid pathway, SPT may play a key role in human anti-aging, which is revealed by lipidomics liposome tracer analysis. The potential active components in ginseng on SPT was further verified by molecular docking virtual screening and atomic force microscope. Four ingredients of ginseng may reduce the levels of metabolites dhSph and dhCer by inhibiting the activity of SPT, and play an anti-aging effect by affecting the sphingolipid metabolism pathway.A clinical trials registration number: ChiCTR1900026836.

The Effects of Mobile-App-Based Low-Carbohydrate Dietary Guidance on Postprandial Hyperglycemia in Adults with Prediabetes.

INTRODUCTION: Postprandial hyperglycemia is independently associated with many adverse complications, while diets with a low glycemic load are beneficial in improving post-meal glucose levels. This study aims to determine if mobile-app-based low-carbohydrate dietary guidance will reduce exposure to postprandial hyperglycemia in adults with prediabetes. METHODS: This single-blind, randomized controlled pilot study included 100 participants (39 men; mean age 53.6 ± 11.9 years) and was performed in the PKU Care CNOOC Hospital, China. The intervention group (n = 57) received low-carbohydrate dietary guidance through a moblie app (CAReNA) for 3 months, while the control group (n = 43) only received health education on a diabetic diet. The primary outcome was change in time of postprandial hyperglycemia between baseline and 3 months. RESULTS: The study revealed that the mean time in postprandial hyperglycemia (> 7.8 mmol/l [140 mg/dl]) monitored by flash glucose monitoring changed from 3.27 h/day at baseline to 2.34 h/day at 3 months in the intervention group and from 3.08 h/day to 2.96 h/day in the control group, with a between-group difference of - 0.81 h/day (P < 0.05). Fasting plasma glucose and glycated hemoglobin (HbA1c) in the intervention group decreased significantly, although no significant difference was seen between the two groups. Compared with the control group, the intervention group had a significant decrease in anthropometric and body composition measurements as well as triglycerides. CONCLUSION: The mobile-app-based low-carbohydrate dietary guidance effectively reduced the time spent in postprandial hyperglycemia in adults with prediabetes. This new type of nutritional management has beneficial effects on people with prediabetes and needs further research. CLINICAL TRIAL REGISTRATION: ChiCTR1900024880.

Comparison of the Wake-up Test and Combined TES-MEP and CSEP Monitoring in Spinal Surgery.

STUDY DESIGN: A retrospective clinical analysis. OBJECTIVE: The aim of this study was to compare the effectiveness of the wake-up test with that of combined monitoring of transcranial electrical stimulation motor evoked potentials (TES-MEP) and cortical somatosensory evoked potentials (CSEP) in spinal surgery. SUMMARY OF BACKGROUND DATA: TES-MEP/CSEP combined monitoring is being increasingly recognized as the ideal approach to detect spinal neurophysiological compromise during spinal surgery; however, as a result the merit of the wake-up test is now in doubt. MATERIALS AND METHODS: TES-MEP/CSEP combined monitoring was performed simultaneously in 426 patients who underwent spinal surgery at our department, and wake-up tests were conducted on 23 patients because of positive neurophysiological monitoring results with uncertain causes or persistent positive monitoring findings after all potential causes had been resolved. Preoperative and postoperative neurological examinations were performed as the gold standard to detect irreversible spinal function compromise. All data were collected to compare the efficiency of TES-MEP/CSEP combined monitoring with that of the wake-up test. RESULTS: Positive results of TES-MEP/CSEP combined monitoring were recorded in 64 cases. Among them, the positive monitoring findings agreed with the results of the neurological examination in 51 cases, and the monitoring results did not match that of neurological examination in 13 cases. No false-negative result was observed. The sensitivity of TES-MEP/CSEP monitoring was 100%, the specificity was 96.5%, and the Youden index was 0.965. Wake-up tests were conducted in 23 cases. In 8 patients the positive monitoring findings completely matched the postoperative neurological examination results. In contrast, in the other 15 cases with negative neurophysiological monitoring results, only 9 patients retained intact neurological function and 6 patients suffered compromised neurological function. The sensitivity of the wake-up test was 57.1%, the specificity was 100%, and the Youden index was 0.571. CONCLUSIONS: Combined TES-MEP and CSEP monitoring, with its high sensitivity and specificity, is an effective method for monitoring spinal function during surgery and should be the preferred choice. The wake-up test is a useful complementary method for monitoring because of its high specificity.