Identification of Human Body Fluid Stains and Non-Biological Stains by Three-Dimensional Fluorescence Spectroscopy.

OBJECTIVES: To establish a rapid and nondestructive identification method for human body fluid stains and non-biological stains using three-dimensional fluorescence spectroscopy. METHODS: The collected three-dimensional fluorescence spectrum data of human saliva, 3% blood, coffee and Fanta® stains were processed with dimensionality reduction. After wavelet transform, spectral denoising and feature extraction, the classification formula was established. The Fisher discriminant was used for spectrum matching and recognition to establish the analysis method to distinguish stain types. RESULTS: According to the results of data training and comparison, all the recognition accuracies of Fanta®, coffee, saliva and blood were more than 91.39%. Among them, saliva reached 100% recognition accuracy. CONCLUSIONS: Three-dimensional fluorescence spectroscopy is a potential method for rapid and nondestructive identification of biological and non-biological stains.

Impact of liver fibrosis score on the incidence of stroke: A cohort study.

PURPOSE: The purpose was to explore the value of liver fibrosis scores (fibrosis-4, BAAT score and BARD score) for incidence risk of stroke in a cohort study. METHODS: A total of 9088 participants without stroke history enrolled the follow-up. Three liver fibrosis scores (LFSs) including FIB-4, BARD score and BAAT score were adopted. The end point was stroke. Cox regression analysis was used to calculate hazard ratios and 95% confidence interval. Kaplan-Meier curve was used to show the probability of stoke in different levels of LFSs. Subgroup analysis showed the association between LFSs and stroke under different stratification. Restricted cubic spline could further explore whether there is a linear relationship between LFSs and stroke. Finally, we used C-statistics, Net Reclassification Index (NRI) and Integrated Discrimination Improvement (IDI) to assess the discriminatory power of each LFS for stroke. RESULTS: During a median follow-up time of 4.66 years, 272 participants had a stroke. Through the baseline characteristics, we observed that the stroke incidence population tends to be male and older. It was shown by Kaplan-Meier that three LFSs were associated with stroke and high levels of LFSs significantly increase the probability of stroke. In the univariate Cox regression analysis, the HR of stroke risk was 6.04 (4.14-8.18) in FIB-4, 2.10 (1.45-3.04) in BAAT score and 1.81 (1.38-2.38) in BARD score by comparing the high level with the low level at each LFSs. The adjusted HRs for three LFSs were 2.05 (1.33-3.15) in FIB-4, 1.61 (1.10-2.35) in BAAT score and 1.54 (1.17-2.04) in BARD score by comparing the high group with low group. We found that multivariable-adjusted HRs of three LFSs still increased for stroke when stratified by various factors in subgroup analysis. Moreover, after adding LFSs to original risk prediction model which consist of age, sex, drinking, smoking, hypertension, diabetes, low-density lipoprotein cholesterol, total cholesterol and triglycerides, we found that new models have higher C-statistics of stroke. Furthermore, we calculated Net Reclassification Index (NRI) and Integrated Discrimination Improvement (IDI) to show the ability of LFSs to predict stroke. CONCLUSIONS: Our study showed that three LFSs were associated with stroke amongst middle-aged populations in rural areas of Northeast China. Furthermore, it suggests that LFSs can be used as a risk stratification tool to predict stroke.

Image reconstruction method based on CCD calibration in frequency domain.

We demonstrate a method to reconstruct CCD images by calculating out the pixel response function accurately with laser interference patterns. This method is proven theoretically to have the ability to improve image quality greatly and thus may find great application in high-quality imaging fields.

Autophagy machinery in glioblastoma: The prospect of cell death crosstalk and drug resistance with bioinformatics analysis.

Brain tumors are common malignancies with high mortality and morbidity in which glioblastoma (GB) is a grade IV astrocytoma with heterogeneous nature. The conventional therapeutics for the GB mainly include surgery and chemotherapy, however their efficacy has been compromised due to the aggressiveness of tumor cells. The dysregulation of cell death mechanisms, especially autophagy has been reported as a factor causing difficulties in cancer therapy. As a mechanism contributing to cell homeostasis, the autophagy process is hijacked by tumor cells for the purpose of aggravating cancer progression and drug resistance. The autophagy function is context-dependent and its role can be lethal or protective in cancer. The aim of the current paper is to highlight the role of autophagy in the regulation of GB progression. The cytotoxic function of autophagy can promote apoptosis and ferroptosis in GB cells and vice versa. Autophagy dysregulation can cause drug resistance and radioresistance in GB. Moreover, stemness can be regulated by autophagy and overall growth as well as metastasis are affected by autophagy. The various interventions including administration of synthetic/natural products and nanoplatforms can target autophagy. Therefore, autophagy can act as a promising target in GB therapy.

Raman ConvMSANet: A High-Accuracy Neural Network for Raman Spectroscopy Blood and Semen Identification.

Animal blood and semen analysis plays a significant role in national biological resource management, wildlife conservation, and customs security quarantine. Traditional blood analysis methods have disadvantages, such as complex sample preparation, time consumption, and false positives. Therefore, proposing a rapid and highly accurate analysis method is highly valuable. Raman spectroscopy has been widely used in blood analysis, and efficient and accurate analysis results can be obtained through the machine learning algorithm feature extraction. Recently, the transformer network structure was applied to Raman spectroscopy recognition. However, the multihead self-attention mechanism does not perform well in extracting local feature peaks, although it obtains global feature relations. This paper proposes a neural network based on the combination of one-dimensional convolution and multihead self-attention mechanism (Raman ConvMSANet) to identify 52 species of blood and semen Raman spectra. The network can achieve reliable identification effects in multiclassification and sample imbalance situations, and the average identification accuracy of blood and semen can reach more than 98.5%. The proposed network model can be applied not only to blood and semen identification but also to other biological fields.

Predictive value of liver fibrosis scores in cardiovascular diseases among hypertensive population.

PURPOSE: To explore the predictive value of liver fibrosis scores [fibrosis-4, AST/platelet ratio index, BAAT score (BMI Age ALT TG), and BARD score (BMI AST/ALT Ratio Diabetes)] for the risk of cardiovascular disease (CVD) in a hypertensive population. METHODS: A total of 4164 hypertensive participants without history of CVD were enrolled in the follow-up. Four liver fibrosis scores (LFSs) were used, including the fibrosis-4 (FIB-4), APRI, BAAT score, and BARD score. The endpoint was CVD incidence which was defined as stroke or coronary heart disease (CHD) during the follow-up period. Cox regression analyses were used to calculate hazard ratios between LFSs and CVD. Kaplan-Meier curve was used to show the probability of CVD in different levels of LFSs. Restricted cubic spline further explored whether the relationship between LFSs and CVD was linear. Finally, we assessed the discriminatory ability of each LFS for CVD was assessed using C -statistics, net reclassification index (NRI), and integrated discrimination improvement (IDI). RESULTS: During a median follow-up time of 4.66 years, 282 hypertensive participants had CVD. Kaplan-Meier curve showed that four LFSs were associated with CVD and high levels of LFSs significantly increase the probability of CVD in hypertensive population. In the multivariate Cox regression analysis, the adjusted hazard ratios for four LFSs were 3.13 in FIB-4, 1.66 in APRI, 1.47 in BAAT score, and 1.36 in BARD score. Moreover, after adding LFSs to original risk prediction model, we find that all four new models have higher C -statistics of CVD than the traditional model. Furthermore, the results of both NRI and IDI were positive, indicating that LFSs enhanced the effect on the prediction of CVD. CONCLUSIONS: Our study showed that LFSs were associated with CVD in hypertensive populations in northeastern China. Furthermore, it suggested that LFSs could be a new tool for identifying patients at high risk of primary CVD in a hypertensive population.

The association between liver fibrosis scores and chronic kidney disease.

Purpose: This study aimed to clarify the relationship between liver fibrosis scores (Fibrosis-4, BARD score, and BAAT score) and chronic kidney disease (CKD). Methods: We collected a range of data from 11,503 subjects (5,326 men and 6,177 women) from the rural regions of Northeastern China. Three liver fibrosis scores (LFSs) including fibrosis-4 (FIB-4), BARD score, and BAAT score were adopted. A logistic regression analysis was used to calculate odds ratios and the 95% confidence interval. A subgroup analysis showed the association between LFSs and CKD under different stratifications. Restricted cubic spline could further explore whether there is a linear relationship between LFSs and CKD. Finally, we used C-statistics, Net Reclassification Index (NRI), and Integrated Discrimination Improvement (IDI) to assess the effect of each LFS on CKD. Results: Through the baseline characteristics, we observed that LFSs were higher in the CKD population than in non-CKD. The proportion of participants with CKD also increased with LFSs. In a multivariate logistic regression analysis, the ORs of CKD were 6.71 (4.45-10.13) in FIB-4, 1.88 (1.29-2.75) in the BAAT score, and 1.72 (1.28-2.31) in the BARD score by comparing the high level with the low level in each LFSs. Moreover, after adding LFSs to the original risk prediction model, which consisted of age, sex, drinking, smoking, diabetes, low-density lipoprotein cholesterol, total cholesterol, triglycerides, and mean waist circumference, we found the new models have higher C-statistics. Furthermore, NRI and IDI both indicate LFSs had a positive effect on the model. Conclusions: Our study showed that LFSs are associated with CKD among middle-aged populations in rural areas of northeastern China.

Prevalence and Risk Factors of Mitral, Tricuspid, and Aortic Regurgitation: A Population-Based Study from Rural Northeast China.

The population-based studies on the epidemiologic features of valvular regurgitation in Northeast China are scarce. We aim to estimate the prevalence and risk factors of mitral regurgitation (MR), tricuspid regurgitation (TR), and aortic regurgitation (AR) in a general population from rural Northeast China. Valvular regurgitation was assessed by color flow Doppler echocardiography in a population-based survey of 11,278 participants aged ≥35 years in rural areas of Liaoning Province during 2012 to 2013. The prevalence of mild or greater MR and TR were 1.6% and 1.5%, respectively. Trace or greater AR was present in 4.1% of the participants. In the multivariable regression model, older age, left atrial dimension, low left ventricular (LV) ejection fraction, and fasting plasma glucose were associated with higher risk of MR in men, whereas only older age and left atrial dimension increased the risk in women. Body mass index was found to be a protective factor for MR in women (odds ratio 0.847, 95% confidence interval 0.741 to 0.969). TR was independently associated with age, heart rate, low LV ejection fraction, current drinking status, and high-density lipoprotein cholesterol. The risk for AR significantly increased with age in both genders. LV mass index and aortic dimension increased the risk of AR in males, and females with higher LV mass index and high-density lipoprotein cholesterol had an increased risk for AR. In both genders, systolic blood pressure presented as a risk factor for AR, while diastolic blood pressure as a protective factor. In this large Chinese population-based study, we found remarkably low prevalence of valvular regurgitation, adding evidence for estimating disease burden and making policy strategies in Northeast China.

Regulation of the Tec family of non-receptor tyrosine kinases in cardiovascular disease.

Tyrosine phosphorylation by protein tyrosine kinases (PTKs) is a type of post-translational modification. Tec kinases, which are a subfamily of non-receptor PTKs, were originally discovered in the hematopoietic system and include five members: Tec, Btk, Itk/Emt/Tsk, Etk/Bmx, and Txk/Rlk. With the progression of modern research, certain members of the Tec family of kinases have been found to be expressed outside the hematopoietic system and are involved in the development and progression of a variety of diseases. The role of Tec family kinases in cardiovascular disease is receiving increasing attention. Tec kinases are involved in the occurrence and progression of ischemic heart disease, atherosclerosis, cardiac dysfunction associated with sepsis, atrial fibrillation, myocardial hypertrophy, coronary atherosclerotic heart disease, and myocardial infarction and post-myocardial. However, no reviews have comprehensively clarified the role of Tec kinases in the cardiovascular system. Therefore, this review summarizes research on the role of Tec kinases in cardiovascular disease, providing new insights into the prevention and treatment of cardiovascular disease.

DNA Polymerase Gamma Recovers Mitochondrial Function and Inhibits Vascular Calcification by Interacted with p53.

DNA polymerase gamma (PolG) is the major polymerase of mitochondrial DNA (mtDNA) and essential for stabilizing mitochondrial function. Vascular calcification (VC) is common senescence related degenerative pathology phenomenon in the end-stage of multiple chronic diseases. Mitochondrial dysfunction was often observed in calcified vessels, but the function and mechanism of PolG in the calcification process was still unknown. The present study found PolGD257A/D257A mice presented more severe calcification of aortas than wild type (WT) mice with vitamin D3 (Vit D3) treatment, and this phenomenon was also confirmed in vitro. Mechanistically, PolG could enhance the recruitment and interaction of p53 in calcification condition to recover mitochondrial function and eventually to resist calcification. Meanwhile, we found the mutant PolG (D257A) failed to achieve the same rescue effects, suggesting the 3'-5' exonuclease activity guarantee the enhanced interaction of p53 and PolG in response to calcification stimulation. Thus, we believed that it was PolG, not mutant PolG, could maintain mitochondrial function and attenuate calcification in vitro and in vivo. And PolG could be a novel potential therapeutic target against calcification, providing a novel insight to clinical treatment.

Predictive Value of the Age, Creatinine, and Ejection Fraction (ACEF) Score in Cardiovascular Disease among Middle-Aged Population.

PURPOSE: To explore the predictive value of ACEF scores for identifying the risk of cardiovascular disease (CVD) in the general population. METHODS: A total of 8613 participants without a history of CVD were enrolled in the follow-up. The endpoint was CVD incidence, defined as stroke or coronary heart disease (CHD) diagnosed during the follow-up period. Cox regression analyses were used to calculate hazard ratios (HRs) with respect to the age, creatinine, and ejection fraction (ACEF) scores and CVD. A Kaplan-Meier curve was used to analyze the probability of CVD in different quartiles of ACEF. Restricted cubic spline was used to further explore whether the relationship between ACEF and CVD was linear. Finally, we assessed the discriminatory ability of ACEF for CVD using C-statistics, net reclassification index, and integrated discrimination improvement (IDI). RESULTS: During a median follow-up period of 4.66 years, 388 participants were diagnosed with CVD. The Kaplan-Meier curve showed that ACEF was associated with CVD, and participants with high ACEF scores were significantly more likely to be diagnosed with CVD compared to participants with low ACEF scores in the general population. In the multivariate Cox regression analysis, the adjusted HRs for four quartiles of ACEF were as follows: the first quartile was used as a reference; the second quartile: HR = 2.33; the third quartile: HR = 4.81; the fourth quartile: HR = 8.00. Moreover, after adding ACEF to the original risk prediction model, we observed that new models had higher C-statistic values of CVD than the traditional model. Furthermore, the results of both NRI and IDI were positive, indicating that ACEF enhanced the prediction of CVD. CONCLUSIONS: Our study showed that the ACEF score was associated with CVD in the general population in northeastern China. Furthermore, ACEF could be a new tool for identifying patients at high risk of primary CVD in the general population.

[Design of full-polarized and multi-spectral imaging system based on LCVR].

A new full-polarized multi-spectral imaging system is described, which uses electronically controlled LCVR (liquid crystal variable retarder) to modulate the full-polarized state of light in the visible to IR range. The system consisted of optical lenses, LCVRs, filters and CCD. Firstly, the system structure, working theory and optical design are introduced in the present paper. A polarization calibration method is provided and the calibration system was set up, which realized high-precision polarization calibration using a small polarized source. Then, a field experiment with the imaging system was carried out. Polarized spectral images with higher spectral and spatial resolution were collected. Finally, the data acquired were rough processed to get polarization degree image of the targets. It is concluded that the experiment has proved that the imaging system is effective in obtaining full-polarized and multi- spectral data. The image captured by the system can be applied to object identification and object classification.