Monounsaturated and polyunsaturated fatty acids concerning prediabetes and type 2 diabetes mellitus risk among participants in the National Health and Nutrition Examination Surveys (NHANES) from 2005 to March 2020.

Objective: Unsaturated fatty acids (UFA) may be related to glycometabolism. While associations between UFA intake (especially their subtype) and prediabetes or type 2 diabetes mellitus (T2DM) need to be further studied. In this study, we aimed to evaluate the potential relation of UFA with prediabetes and T2DM. Methods: A total of 16,290 adults aged older than 18 years from the National Health and Nutrition Examination Survey (NHANES) from 2005 to March 2020 were included in the present analysis. Dietary intake was assessed by two day, 24-hour dietary recalls and daily intake of total monounsaturated fatty acids (MUFA) and polyunsaturated fatty acids (PUFA); four specific fatty acids of MUFA and seven specific fatty acids of PUFA were calculated. Prediabetes and T2DM were diagnosed by fasting glucose, glycohemoglobin, and self-reported medication or insulin. Rao-Scott modified chi-square tests, the Taylor series linearization method, and multivariable logistic regression analyses were applied to analyze the associations of dietary MUFA and PUFA intake with diabetes risk. Results: Of the participants, 44.34% had prediabetes and 13.16% had T2DM patients. From multivariate analysis, we found that intake of MUFA, PUFA, and some subtypes was negatively associated with the risk of prediabetes and T2DM in Americans. Compared with adults in the lowest tertile, those in the highest MUFA (PUFA) tertile had an approximately 50% (49%) and 69% (68%) lower risk of prediabetes and T2DM, respectively. Moreover, the effects of the subtypes of MUFA and PUFA on prediabetes and T2DM were different. Higher intakes of MFA 18:1, MFA 20:1, PFA 18:2, and PFA 18:3 and higher tertile intakes of MFA 16:1 and PFA 20:4 were related to a lower risk of prediabetes and T2DM. Similarly, the effects of MUFA, PUFA, and subtype on prediabetes and T2DM varied among different age groups, being weakened along with age. Conclusion: Our study suggested that total MUFA and PUFA intake might be essential in preventing prediabetes and T2DM, especially in Americans. However, this protective effect may decrease with age. Moreover, the effects of the specific UFA on prediabetes and T2DM need further consideration.

The prognostic value of tumor mutation burden (TMB) and its relationship with immune infiltration in breast cancer patients.

OBJECTIVE: Although the tumor mutation burden (TMB) was reported as a biomarker for immunotherapy of various cancers, whether it can effectively predict the survival prognosis in breast cancer patients remains unclear. In this study, the prognostic value of TMB and its correlation with immune infiltration were explored by using multigroup studies. METHODS: The somatic mutation data of 986 breast cancer patients were obtained from TCGA database. Breast cancer patients were divided into a low-TMB group and a high-TMB group according to the quartile of TMB scores. The differentially expressed genes (DEGs) were identified by the "limma" R program. The CIBERSORT algorithm was utilized to estimate the immune cell fraction of each sample. The TIMER database was utilized to evaluate the association between CNVs of immune genes and tumor immune cell infiltration and the prognostic value of the immune cells in breast cancer. RESULTS: In breast cancer, TP53, PIK3CA, TTN, CDH1 and other genes were the most important mutated genes. Higher survival rate of patients was found in the low-TMB group. Among the top 10 DEGs, three of them belong to the KRT gene family. GSEA enrichment analysis showed that MAPK, Hedgehog, mTOR, TGF-bate and GnRH signaling pathways were enriched in the low-TMB group. The infiltration levels of the most of immune cells were higher in the low-TMB group (P < 0.01). Higher expression of CCL18 and TRGC1 was correlated with poor prognosis. Breast cancer patients with CCL18 copy number variations, especially arm-level gains, showed significantly decreased immune cell infiltration. In the low B cell infiltration group, the survival prognosis of breast cancer patients was poor. CONCLUSIONS: TMB is a potential prognosis marker in breast cancer. Immune-related gene CCL18 and TRGC1 are biomarkers of poor prognosis while immune (B cell) infiltration is a biomarker of good prognosis.

Identification of genes and pathways leading to poor prognosis of non-small cell lung cancer using integrated bioinformatics analysis.

Background: Non-small cell lung cancer (NSCLC) is a common malignancy with a high morbidity and mortality rate worldwide, but the driver genes and signaling pathways involved are largely unclear. Herein, our study aimed to identify significant genes with poor outcome and underlying mechanisms in NSCLC using bioinformatics analyses. Methods: Gene expression profiles (GSE33532, GSE19188, GSE102287, GSE27262), including 319 NSCLC and 232 adjacent lung tissues, were downloaded from the GEO database. Differentially expressed genes (DEGs) were identified by the GEO2R online tool. Functional and pathway enrichment analyses were performed via the DAVID database. The protein-protein interactions (PPIs) of these DEGs were constructed by the STRING website and visualized by the Cytoscape software platform. The expression of hub genes in NSCLC was validated through the GEPIA database. Kaplan-Meier plotter was used to analyse the survival rate with multivariate Cox regression. The expression of protein tyrosine kinase 2 (PTK2) in NSCLC and adjacent lung tissues was evaluated on the UALCAN database platform. Results: A total of 225 significant DEGs were obtained between NSCLC and adjacent lung tissues, containing 52 upregulated genes and 173 downregulated genes. The DEGs were clustered based on functions and signaling pathways that may be closely associated with NSCLC occurrence. A total of 174 DEGs were identified from the PPI network complex. Top 10 hub genes were selected by CytoHubba plugin. As independent predictors, seven genes (COL1A1, ADAM12, VWF, OGN, EDN1, CAV1, ITGA8) were associated with poor prognosis in NSCLC via multivariate Cox regression (P<0.01). Four genes (VWF, CAV1, ITGA8, COL1A1) were found to be significantly enriched in the focal adhesion pathway (P=1.04E-04) and to be upstream regulators of PTK2. PTK2 was upregulated in NSCLC and associated with poor survival prognosis in lung squamous cell carcinoma (LUSC). Conclusions: Taken together, the important genes and pathways in NSCLC were identified by using integrated bioinformatics analysis. PTK2 could be a key gene associated with the biological process of NSCLC formation and progression and a potential therapeutic target for NSCLC treatment.

Development of silica molecularly imprinted polymer on carbon dots as a fluorescence probe for selective and sensitive determination of cetirizine in saliva and urine.

A fluorescence probe based on carbon dots (CDs) coated with silica molecularly imprinted polymer (MIPs) was synthesized for selective and sensitive determination of cetirizine (CTZ). Green source carbon dots were firstly derived from orange peels through a microwave method, and had the merits of eco-friendly and low toxicity. Then a thin silica film was formed on the surface of CDs by reverse microemulsion technique, and molecularly imprinted polymer coated on silica-carbon dots. In this scene, CTZ, 3-aminopropyltriethoxysilane (APTES) and tetraethoxysilane (TEOS) were employed as a template, a functional monomer and cross linker, respectively. The obtained CDs-MIPs can selectively bind CTZ through the specific interaction between recognition sites and template, and obey photoinduced electron transfer fluorescence quenching mechanism. Fluorescence dropped linearly in the range of 0.5-500 ng mL-1, under the optimal conditions, with a detection limit of 0.41 ng mL-1. Furthermore, the proposed method was successfully intended for the determination of trace CTZ in human saliva and urine samples without the interference of other molecules and ions. And recoveries ranged from 95.8% to 99.8% with relative standard deviation less than 3.0%.

A simple and accurate HFCF-UF method for the analysis of homocysteine, cysteine, cysteinyl-glycine, and glutathione in human blood.

The presence of reduced aminothiols, including homocysteine (Hcy), cysteine (Cys), cysteinyl-glycine (CG), and glutathione (GSH), is significantly increased in the pathological state. However, there have been no reports on the relationship between reduced aminothiols (Hcy, Cys, CG, and GSH) and different genders, ages, and drug combinations in human blood. The accurate quantification of these reduced thiols in biological fluids is important for monitoring some special pathological conditions of humans. However, the published methods typically not only require cumbersome and technically challenging processing procedures to ensure reliable measurements, but are also laborious and time-consuming, which may disturb the initial physiological balance and lead to inaccurate results. We developed a hollow fiber centrifugal ultrafiltration (HFCF-UF) method for sample preparation coupled with a high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) method and used it to determine four reduced aminothiols (Hcy, Cys, CG, and GSH) in human blood for the first time. A total of 96 clinical patients were enrolled in our study. The influence of different genders, ages, and drug combinations on the levels of four reduced thiols in human blood was also discussed by SPSS 24.0. The sample preparation was simplified to a single 5 min centrifugation step in a sealed system that did not disturb the physiological environment. The validation parameters for the methodological results were excellent. The procedure was successfully applied to monitoring the concentrations of four reduced aminothiols (Hcy, Cys, CG, and GSH) in 96 clinical blood samples. There were no significant differences in Hcy, Cys, CG, or GSH for the different genders, ages, or combinations with methotrexate or vancomycin (P > 0.05). However, there was a significant increase in Hcy concentration in patients treated with valproic acid who were diagnosed with epilepsy (p=0.0007). It is advisable to measure reduced Hcy level in patients taking valproic acid. The developed HFCF-UF method was simple and accurate. It can be easily applied in clinical research to evaluate oxidative stress in further study.

A new health prediction model for a sensor network based on belief rule base with attribute reliability.

Health prediction plays an essential role in improving the reliability of a sensor network by guiding the network maintenance. However, affected by interference factors in the real operational environment, the reliability of the monitoring information about the sensor network tends to decline, which affects the health prediction accuracy. Furthermore, the lack of monitoring information and high complexity of the network increase the difficulty of health prediction. To solve these three problems, this paper proposes a new sensor network health prediction model based on the belief rule base model with attribute reliability (BRB-r). The BRB-r model is an expert system that fully considers the qualitative knowledge and quantitative data of the sensor network. In addition, it can address the fuzziness and nondeterminacy of this qualitative knowledge. In the new model, the unreliable monitoring information of the sensor network is handled by the attribute reliability mechanism. The reliability of the sensor is calculated by the average distance method. Due to the effect of the fuzziness and nondeterminacy of expert knowledge, the health status of the sensor network cannot be accurately estimated by the initial health prediction model. Consequently, the optimization model for the health prediction model is established. Finally, a case study regarding a sensor network for oil storage tanks is conducted, and the validity of this method is demonstrated.

Complication Differences Between the Tumescent and Non-Tumescent Dissection Techniques for Mastectomy: A Meta-Analysis.

PURPOSE: We conducted a systematic literature search and pooled data from studies to compare the incidence of complications between the tumescent and non-tumescent techniques for mastectomy. METHODS: We searched PubMed, Embase, BioMed Central, Ovid, and CENTRAL databases for studies comparing the two mastectomy techniques up to November 1st, 2020. We used a random-effects model to calculate odds ratios (OR) with 95% confidence intervals (CI). RESULTS: Nine studies were included with one randomized controlled trial (RCT). Meta-analysis indicated no statistically significant difference in the incidence of total skin necrosis (OR 1.18 95% CI 0.71, 1.98 I2 = 82% p=0.52), major skin necrosis (OR 1.58 95% CI 0.69, 3.62 I2 = 71% p=0.28), minor skin necrosis (OR 1.11 95% CI 0.43, 2.85 I2 = 72% p=0.83), hematoma (OR 1.19 95% CI 0.80, 1.79 I2 = 4% p=0.39), and infections (OR 0.87 95% CI 0.54, 1.40 I2 = 54% p=0.56) between tumescent and non-tumescent groups. Analysis of studies using immediate alloplastic reconstruction revealed no statistically significant difference in the incidence of explantation between the two groups (OR 0.78 95% CI 0.46, 1.34 I2 = 62% p=0.37). Multivariable-adjusted ORs on total skin necrosis were available from three studies. Pooled analysis indicated no statistically significant difference between tumescent and non-tumescent groups (OR 1.72 95% CI 0.72, 4.13 I2 = 87% p=0.23). CONCLUSION: Low-quality evidence derived mostly from non-randomized studies is indicative of no difference in the incidence of skin necrosis, hematoma, seroma, infection, and explantation between the tumescent and non-tumescent techniques of mastectomy. There is a need for high-quality RCTs to further strengthen the evidence.