Combined exposure of polystyrene microplastics and benzo[a]pyrene in rat: Study of the oxidative stress effects in the liver.

Microplastics (MPs) and benzo[a]pyrene (B[a]P) are prevalent environmental pollutants. Numerous studies have extensively reported their individual adverse effects on organisms. However, the combined effects and mechanisms of exposure in mammals remain unknown. Thus, this study aims to investigate the potential effects of oral administration of 0.5µm polystyrene (PS) MPs (1 mg/mL or 5 mg/mL), B[a]P (1 mg/mL or 5 mg/mL) and combined (1 mg/mL or 5 mg/mL) on 64 male SD rats by gavage method over 6-weeks. The results demonstrate that the liver histopathological examination showed that the liver lobules in the combined (5 mg/kg) group had blurred and loose boundaries, liver cord morphological disorders, and significant steatosis. The levels of AST, ALT, TC, and TG in the combined dose groups were significantly higher than those in the other groups, the combined (5 mg/kg) group had the lowest levels of antioxidant enzymes and the highest levels of oxidants. The expression of Nrf2 was lowest and the expression of P38, NF-κB, and TNF-α was highest in the combined (5 mg/kg) group. In conclusion, these findings indicate that the combination of PSMPs and B[a]P can cause the highest levels of oxidative stress and elicit markedly enhanced toxic effects, which cause severe liver damage.

Effects of Benzo (a) Pyrene and 2,2',4,4'-Tetrabromodiphenyl Ether Exposure on the Thyroid Gland in Rats by Attenuated Total Reflection Fourier-Transform Infrared Spectroscopy.

Benzo[a]pyrene (B[a]P) and 2,2',4,4'-tetrabromodiphenyl ether (BDE-47) are widespread environmental pollutants and can destroy thyroid function. We assessed the biochemical changes in the thyroid tissue of rats exposed to B[a]P and BDE-47 using attenuated total reflection Fourier-transform infrared spectroscopy combined with support vector machine(SVM). After B[a]P and BDE-47 treatment in rats, the structure of thyroid follicles was destroyed and epithelial cells were necrotic, indicating that B[a]P and BDE-47 may lead to changes of the thyroid morphology of the rats. These damages are mainly related to C=O stretch vibrations of lipids (1743 cm-1), as well as the secondary structure of proteins [amide I (1645 cm-1) and amide II (1550 cm-1)], and carbohydrates [C-OH (1138 cm-1), C-O (1106 cm-1, 1049 cm-1, 991 cm-1), C-C (1106 cm-1) stretching] and collagen (phosphodiester stretching at 922 cm-1) vibration modes. When SVM was used for classification, there was a substantial separation between the control and the exposure groups (accuracy = 96%; sensitivity = 98%; specificity = 87%), and there was also a major separation between the exposed groups (accuracy = 93%; sensitivity = 94%; and specificity = 92%).

Serum-based ATR-FTIR spectroscopy combined with multivariate analysis for the diagnosis of pre-diabetes and diabetes.

Diabetes mellitus (DM) is a metabolic disease with an increasing prevalence that is causing worldwide concern. The pre-diabetes stage is the only reversible stage in the patho-physiological process towards DM. Due to the limitations of traditional methods, the diagnosis and detection of DM and pre-diabetes are complicated, expensive, and time-consuming. Therefore, it would be of great benefit to develop a simple, rapid and inexpensive diagnostic test. Herein, the infrared (IR) spectra of serum samples from 111 DM patients, 111 pre-diabetes patients and 333 healthy volunteers were collected using attenuated total reflection Fourier-transform IR (ATR-FTIR) spectroscopy and this was combined with the multivariate analysis of principal component analysis linear discriminant analysis (PCA-LDA) to develop a discriminant model to verify the diagnostic potential of this approach. The study found that the accuracy of the test model established by ATR-FTIR spectroscopy combined with PCA-LDA was 97%, and the sensitivity and specificity were 100% and 100% in the control group, 94% and 98% in the pre-diabetes group, and 91% and 98% in the DM group, respectively. This indicates that this method can effectively diagnose DM and pre-diabetes, which has far-reaching clinical significance.

The causal relationship between bacterial pneumonia and diabetes: a two-sample mendelian randomization study.

BACKGROUND: Previous observational studies have established the high prevalence of bacterial pneumonia in diabetic patients, which in turn leads to increased mortality. However, the presence of a causal connection between bacterial pneumonia and diabetes remains unobserved. METHODS: We chose genome-wide significant (Ρ < 1 × 10-5 and Ρ < 1 × 10-6) and independent (r2 < 0.001) single-nucleotide polymorphisms (SNPs) as instrumental variables (IVs) to proceed a bidirectional two-sample MR study. The extracted SNPs explored the relationship between bacterial pneumonia and diabetes by Inverse variance weighted (IVW), MR-Egger, and weighted median methods. In addition, we conducted the Heterogeneity test, the Pleiotropy test, MR-presso and the Leave-one-out (LOO) sensitivity test to validate the reliability of results. RESULTS: In an MR study with bacterial pneumonia as an exposure factor, four different types of diabetes as outcome. It was observed that bacterial pneumonia increases the incidence of GDM (OR = 1.150 (1.027-1.274, P = 0.011) and T1DM (OR = 1.277 (1.024-1.531), P = 0.016). In the reverse MR analysis, it was observed that GDM (OR = 1.112 (1.023-1.201, P = 0.009) is associated with an elevated risk of bacterial pneumonia. However, no significant association was observed bacterial pneumonia with T1DM and other types of diabetes (P > 0.05). CONCLUSION: This study utilizing MR methodology yields robust evidence supporting a bidirectional causal association between bacterial pneumonia and GDM. Furthermore, our findings suggest a plausible causal link between bacterial pneumonia and T1DM.

Application of flipped classroom combined with case-based learning in Introduction to Environmental Health Science.

Objectives: To explore the effect of flipped classroom combined with case-based learning in Introduction to Environmental Health Science for the Master of Public Health (MPH). Methods: The MPH Master's class of 2022 was selected as the experimental group at Guilin Medical University from September to December 2022, and the flipped classroom combined with the case-based learning was adopted. The class of 2021 was the control group, and we taught them with the traditional teaching method. A self-designed questionnaire and academic performance were used to evaluate the teaching effects of the two groups. Results: There was no difference in the paper score between grades 2022 and 2021, and the design question score of grade 2022 was higher than that of grade 2021. The difference was statistically significant (p < 0.05). The students in grade 2022 had a high overall recognition of the teaching effect of the flipped classroom combined with case-based learning in Introduction to Environmental Health Science. Conclusion: The teaching method of the flipped classroom combined with case-based learning is more suitable than the traditional teaching method in the Introduction to Environmental Health Science for MPH. It can stimulate the independent learning ability of MPH students and improve their ability to use knowledge and an innovative spirit.

Application of spectrochemical analysis with chemometrics to profile biochemical alterations in nanoplastic-exposed HepG2 cells.

Humans are routinely exposed to nanoplastics (NPs) in various ways, and this exposure presents a significant health risk. Nevertheless, there remain gaps in our knowledge, particularly in the mechanisms of toxicity of NPs with different surface charges at very low environmental concentrations. Herein, a spectrochemical approach was used to profile the cytotoxicity of NPs with different surface charges in HepG2 cells. It was found that all three NPs can cause some biomolecular alterations in cells, affecting cellular lipids, proteins, amino acids, and genetic material. Of these, PS and PS-COOH led to a non-linear dose-response, which may be related to a biphasic dose-response, whereas PS-NH2 led to a linear dose-response with a gradual increase in toxicity with increasing exposure concentration. In addition, the spectroscopic results showed that surface modifications led to cellular biochemical changes and caused adverse biological effects, with PS-NH2 exhibiting higher toxicity compared to PS or PS-COOH along with an inhibition of cell proliferation. Surprisingly PS-COOH, although considered the least toxic NP, appears to cause DNA damage. Overall, the toxic effects of different surface-modified NPs in cells were detected for the first time by applying spectrochemical techniques, and these findings provide important data towards understanding the emerging widespread environmental pollution of NPs and their effects on humans.

Correlation between dietary patterns and cognitive function in older Chinese adults: A representative cross-sectional study.

Objective: The objective of this study was to investigate the relationship between dietary patterns and cognitive function in older adults (≥60 years old). Methods: Food intake was quantitatively assessed by the Food Frequency Questionnaire (FFQ), and cognitive function was assessed by the Chinese version of the Simple Mental State Examination Scale (MMSE). Four major dietary patterns were identified by the factor analysis (FA) method. The relationship between dietary patterns and cognitive function was evaluated by logistic regression. Results: A total of 884 participants were included in the study. Four dietary patterns (vegetable and mushroom, oil and salt, seafood and alcohol, and oil tea dietary patterns) were extracted. In the total population, Model III results showed that the fourth quartile of dietary pattern factor scores for the vegetable and mushroom pattern was 0.399 and 7.056. The vegetable and mushroom dietary pattern may be a protective factor for cognitive function, with p-value = 0.033, OR (95% CI): 0.578 (0.348, 0.951) in Model III (adjusted for covariates: sex, ethnic, marital, agricultural activities, smoking, drinking, hypertension, diabetes, dyslipidemia, BMI, and dietary fiber). In the ethnic stratification analysis, the scores of dietary pattern factors of the vegetable and mushroom among the Yao participants were 0.333 and 5.064. The Vegetable and mushroom diet pattern may be a protective factor for cognitive function, p-value = 0.012, OR (95% CI): 0.415 (0.206, 0.815). Conclusion: The fourth quartile of the vegetable and mushroom dietary pattern scores showed dose-dependent and a strong correlation with cognitive function. Currently, increasing vegetable and mushroom intake may be one of the effective ways to prevent and mitigate cognitive decline. It is recommended to increase the dietary intake of vegetables and mushroom foods.

The relationship between dietary complexity and cognitive function in Guangxi, China: A cross-sectional study.

BACKGROUND AND OBJECTIVES: The composition of the human diet is complex and diverse, and the relation-ship between dietary composition and cognitive decline has not been adequately studied. Therefore, this study explored the possible association between food items and the risk of cognitive impairment. METHODS AND STUDY DESIGN: This cross-sectional study was based on an ecological longevity cohort and included 2881 participants (1086 men and 1795 women) aged ≥30 years between December 2018 and November 2019. The association between food items and the risk of cognitive impairment was explored using the Bayesian kernel machine regression (BKMR) learning model. RESULTS: Finally, 2881 participants (1086 men and 1795 women) were included. In all participants, the multivariable logistic analysis showed that fresh fruit consumption was associated with cognitive function (OR=0.999, 95% CI: 0.998-0.999, p=0.021). Using the BKMR model, none of the 18 food items were significantly correlated with cognitive function among women. In men, when the other food items were fixed at the 25th, 50th, and 75th percentile values (P25, estimate=-0.239; P50, estimate=-0.210; P75, estimate=-0.158), there was a negative correlation between fresh fruit consumption and the predicted risk of cognitive function disorders. CONCLUSIONS: Men displayed a negative association be-tween fresh fruit consumption and the risk of cognitive function disorders, but this was not apparent among women.

Causal Associations of PM2.5 and GDM: A Two-Sample Mendelian Randomization Study.

Epidemiological studies have linked particulate matter (PM2.5) to gestational diabetes mellitus (GDM). However, the causality of this association has not been established; Mendelian randomization was carried out using summary data from genome-wide association studies (GWAS). For the analysis of the causal relationship between PM2.5 and GDM, the inverse variance weighted (IVW) method was used. The exposure data came from a GWAS dataset of IEU analysis of the United Kingdom Biobank phenotypes consisting of 423,796 European participants. The FinnGen consortium provided the GDM data, which included 6033 cases and 123,000 controls. We also performed multivariate MR (MVMR), adjusting for body mass index (BMI) and smoking. As a result, we found that each standard deviation increase in PM2.5 is associated with a 73.6% increase in the risk of GDM (OR: 1.736; 95%CI: 1.226-2.457). Multivariable MR analysis showed that the effect of PM2.5 on GDM remained after accounting for BMI and smoking. Our results demonstrate a causal relationship between PM2.5 and GDM.

Whole transcriptome sequencing and competitive endogenous RNA regulation network construction analysis in benzo[a]pyrene-treated breast cancer cells.

Breast cancer is the most common malignant tumor in women worldwide, and environmental pollutants are considered to be risk factors. Currently, most studies into benzo[a]pyrene (B[a]P)-induced breast cancer focus on biological effects such as proliferation, invasion, and metastasis, DNA damage, estrogen receptor (ER)-related molecular mechanisms, oxidative damage, and other metabolic pathways. This study aims to provide insights into the role of B[a]P in breast cancer development through RNA-seq and bioinformatics analysis and construction of a competing endogenous RNA (ceRNA) regulatory network. By analyzing RNA-seq results, we identified 144 differentially-expressed circRNAs, 69 differentially-expressed lncRNAs, 20 differentially-expressed miRNAs, and 212 differentially-expressed mRNAs. Following on, we analyzed the gene ontology (GO) and KEGG enrichment functions of the differentially-expressed RNAs. In addition, the protein-protein interaction (PPI) network was mapped for differentially-expressed mRNAs. Subsequently, we constructed ceRNA networks, one of which consisted of 45 dysregulated circRNAs, 11 miRNAs, and 9 mRNAs, and a second consisted of 40 lncRNAs, 11 miRNAs, and 9 mRNAs. Finally, 6 circRNAs, 4 lncRNAs, 1 miRNA, and 4 mRNAs were randomly selected for quantitative real-time PCR verification. PCR results were further verified by Western blotting assays. These results show that the expression level of differentially-expressed RNA was consistent with the sequencing data, and the Western blotting results were highly consistent with the PCR results, confirming that the sequencing result was very reliable. This study systematically explores the ceRNA atlas of differentially-expressed genes related to B[a]P exposure in breast cancer cells, providing new insights into mechanisms of environmental pollutants in breast cancer.

MYCBP2 expression correlated with inflammatory cell infiltration and prognosis immunotherapy in thyroid cancer patients.

Introduction: Immune checkpoint inhibitors (ICIs) have shown promising results for the treatment of multiple cancers. ICIs and related therapies may also be useful for the treatment of thyroid cancer (TC). In TC, Myc binding protein 2 (MYCBP2) is correlated with inflammatory cell infiltration and cancer prognosis. However, the relationship between MYCBP2 expression and ICI efficacy in TC patients is unclear. Methods: We downloaded data from two TC cohorts, including transcriptomic data and clinical prognosis data. The Tumor Immune Dysfunction and Exclusion (TIDE) algorithm was used to predict the efficacy of ICIs in TC patients. MCPcounter, xCell, and quanTIseq were used to calculate immune cell infiltration scores. Gene set enrichment analysis (GSEA) and single sample GSEA (ssGSEA) were used to evaluate signaling pathway scores. Immunohistochemical (IHC) analysis and clinical follow up was used to identify the MYCBP2 protein expression status in patients and associated with clinical outcome. Results: A higher proportion of MYCBP2-high TC patients were predicted ICI responders than MYCBP2-low patients. MYCBP2-high patients also had significantly increased infiltration of CD8+ T cells, cytotoxic lymphocytes (CTLs), B cells, natural killer (NK) cells and dendritic cells (DC)s. Compared with MYCBP2-low patients, MYCBP2-high patients had higher expression of genes associated with B cells, CD8+ T cells, macrophages, plasmacytoid dendritic cells (pDCs), antigen processing and presentation, inflammatory stimulation, and interferon (IFN) responses. GSEA and ssGSEA also showed that MYCBP2-high patients had significantly increased activity of inflammatory factors and signaling pathways associated with immune responses.In addiation, Patients in our local cohort with high MYCBP2 expression always had a better prognosis and greater sensitivity to therapy while compared to patients with low MYCBP2 expression after six months clinic follow up. Conclusions: In this study, we found that MYCBP2 may be a predictive biomarker for ICI efficacy in TC patients. High MYCBP2 expression was associated with significantly enriched immune cell infiltration. MYCBP2 may also be involved in the regulation of signaling pathways associated with anti-tumor immune responses or the production of inflammatory factors.

Tamoxifen resistance-related ceRNA network for breast cancer.

Background: Tamoxifen (TMX) is one of the most widely used drugs to treat breast cancer (BC). However, acquired drug resistance is still a major obstacle to its application, rendering it crucial to explore the mechanisms of TMX resistance in BC. This aims of this study were to identify the mechanisms of TMX resistance and construct ceRNA regulatory networks in breast cancer. Methods: GEO2R was used to screen for differentially expressed mRNAs (DEmRNAs) leading to drug resistance in BC cells. MiRTarbase and miRNet were used to predict miRNAs and lncRNAs upstream, and the competing endogenous RNA (ceRNA) regulatory network of BC cell resistance was constructed by starBase. We used the Kaplan-Meier plotter and Gene Expression Profiling Interactive Analysis (GEPIA) to analyze the expression and prognostic differences of genes in the ceRNA network with core axis, and qRT-PCR was used to further verify the above conclusions. Results: We found that 21 DEmRNAs were upregulated and 43 DEmRNA downregulated in drug-resistant BC cells. DEmRNAs were noticeably enriched in pathways relevant to cancer. We then constructed a protein-protein interaction (PPI) network based on the STRING database and defined 10 top-ranked hub genes among the upregulated and downregulated DEmRNAs. The 20 DEmRNAs were predicted to obtain 113 upstream miRNAs and 501 lncRNAs. Among them, 7 mRNAs, 22 lncRNAs, and 11 miRNAs were used to structure the ceRNA regulatory network of drug resistance in BC cells. 4 mRNAs, 4 lncRNAs, and 3 miRNAs were detected by GEPIA and the Kaplan-Meier plotter to be significantly associated with BC expression and prognosis. The differential expression of the genes in BC cells was confirmed by qRT-PCR. Conclusion: The ceRNA regulatory network of TMX-resistant BC was successfully constructed and confirmed. This will provide an important resource for finding therapeutic targets for TMX resistance, where the discovery of candidate conventional mechanisms can aid clinical decision-making. In addition, this resource will help discover the mechanisms behind this type of resistance.

COL11A1 as an novel biomarker for breast cancer with machine learning and immunohistochemistry validation.

Machine learning (ML) algorithms were used to identify a novel biological target for breast cancer and explored its relationship with the tumor microenvironment (TME) and patient prognosis. The edgR package identified hub genes associated with overall survival (OS) and prognosis, which were validated using public datasets. Of 149 up-regulated genes identified in tumor tissues, three ML algorithms identified COL11A1 as a hub gene. COL11A1was highly expressed in breast cancer samples and associated with a poor prognosis, and positively correlated with a stromal score (r=0.49, p<0.001) and the ESTIMATE score (r=0.29, p<0.001) in the TME. Furthermore, COL11A1 negatively correlated with B cells, CD4 and CD8 cells, but positively associated with cancer-associated fibroblasts. Forty-three related immune-regulation genes associated with COL11A1 were identified, and a five-gene immune regulation signature was built. Compared with clinical factors, this gene signature was an independent risk factor for prognosis (HR=2.591, 95%CI 1.831-3.668, p=7.7e-08). A nomogram combining the gene signature with clinical variables, showed better predictive performance (C-index=0.776). The model correction prediction curve showed little bias from the ideal curve. COL11A1 is a potential therapeutic target in breast cancer and may be involved in the tumor immune infiltration; its high expression is strongly associated with poor prognosis.

Associations Between Plasma Metals and Cognitive Function in People Aged 60 and Above.

The objective of the study was to explore the relationship between the plasma levels of 22 metals and cognition status in older adults aged 60 years and above. A cross-sectional survey was conducted between 2018 and 2019. Inductively coupled plasma mass spectrometry (ICP-MS) was used to detect the concentrations of metals, and a mini-mental state examination (MMSE) questionnaire was used to estimate the cognition status of the elderly. Based on the years of education and MMSE scores, the participants were separated into the normal and impaired cognition groups. Lasso regression, logistic regression, and restricted cubic spline models were used to explore the relationship between the metals and cognitive status. A total of 1667 subjects were included in the study, and 333 (19.97%) of the participants had impaired cognition. Then, 12 metals, including Al, Fe, Ni, Cu, As, Se, Rb, Sr, Mo, Cd, Sn, and Sb were selected by lasso regression. Before the multivariate adjustment, Al and Cu were associated with the risk of increasing cognitive impairment (OR = 1.756, 95% CI: 1.166-2.646, P = 0.007; OR = 1.519, 95% CI: 1.050-2.197, P = 0.026, respectively). By contrast, Rb was associated with a decrease in the risk of cognitive impairment (OR = 0.626, 95% CI: 0.427-0.918, P = 0.017), but Cd was significantly associated with an increase in this risk (OR = 1.456, 95% CI: 1.003-2.114, P = 0.048). After multivariate adjustment, only Al (OR = 1.533, 95% CI: 1.000-2.350, P = 0.050) maintained a borderline difference with the risk of cognitive impairment. A significant positive correlation was found between the risk of cognitive impairment and Al, Cu, and Cd, contrary to the negative correlation found with Rb.

Direct identification and visualisation of real-world contaminating microplastics using Raman spectral mapping with multivariate curve resolution-alternating least squares.

Microplastics (MPs) contamination is ubiquitous in environmental matrices worldwide. Moreover these pollutants can be ingested by organisms and transported to organs via the circulatory system. Although efficient methods for the analysis of MPs derived from environment matrices and organisms' tissue samples have been developed after special sample pre-treatment, there remains a need for an optimised approach allowing direct identification and visualisation these MPs in real environmental matrices and organismal samples. Herein, we firstly used a multivariate curve resolution-alternating least squares (MCR-ALS) analysis of Raman hyperspectral imaging data to direct identification and visualisation of MPs in a complex serum background. Four common MPs types including polyethylene (PE), polystyrene (PS), polypropylene (PP) and polyethylene terephthalate (PET) were identified and visualised either individually or in mixtures within spiked samples at an 8-µm spatial resolution. Moreover, Raman imaging based on MCR-ALS was successfully applied in fish faeces biological samples and environmental sand samples for in situ MPs identification directly without washing or removal of organic matter. The current results demonstrate Raman imaging based on MCR-ALS as a novel imaging approach for direct identification and visualisation of MPs, through extraction of MPs' chemical spectra within a complicated biological or environmental background whilst eliminating overlapping Raman bands and fluorescence interference.

Deciphering the Oncogenic Role of VPS28 Modulated by miR-491-5p in Breast Cancer Cells Using In Silico and Functional Analysis.

Vacuolar protein sorting-associated protein 28 (VPS28), one of the four cytosolic proteins comprising the endosomal sorting complex required for the transport I (ESCRT-I) component, has been reported to be linked to various cancers. However, less evidence is available regarding the involvement of VPS28 in breast cancer. To this end, this study focused on exploring the function of VPS28 in breast cancer cells using the in silico analysis. VPS28 expression pattern data in breast cancer tissues were collected using the Cancer Genome Atlas (TCGA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC) databases and analyzed to assess the association of VPS28 with breast cancer prognosis. The elevated VPS28 expression was found in breast cancer tissues and was associated with a poor prognosis (p < 0.001). A higher VPS28 expression indicated a short survival duration (HR = 2.43; 95% CI: 1.44-4.1; p < 0.001). The CCLE database showed that VPS28 was expressed in breast cancer cell lines. The upstream targets of VPS28 were identified using the mirDIP, starBase, and TargetScan online tools. The correlation and binding relationship between miR-491-5p and VPS28 was analyzed. VPS28 or miR-491-5p gain and loss of function experiments were performed to verify their potential effect on the biological functions of breast cancer cells. Knockdown of VPS28 was shown to suppress the biological functions and enhance the apoptosis of breast cancer cell lines. Micro RNA-491-5p, identified as a posttranscriptional regulator of VPS28, was downregulated in breast cancer tissues. In contrast to the miR-491-5p inhibitor, the miR-491-5p mimic could suppress the migration, wound healing ability, and proliferation, while accelerating apoptosis. However, co-transfection of VPS28 and miR-491-5p counteracted the effect of the miR-491-5p mimic on breast cancer cell functions. Thus, our in silico analysis demonstrates that miR-491-5p can suppress breast cancer progression by attenuating the expression of VPS28.

Global, regional, and national mortality trends of female breast cancer by risk factor, 1990-2017.

BACKGROUND: Female breast cancer (FBC) is a malignancy involving multiple risk factors and has imposed heavy disease burden on women. We aim to analyze the secular trends of mortality rate of FBC according to its major risk factors. METHODS: Death data of FBC at the global, regional, and national levels were retrieved from the online database of Global Burden of Disease study 2017. Deaths of FBC attributable to alcohol use, high body-mass index (BMI), high fasting plasma glucose (FPG), low physical activity, and tobacco were collected. Estimated average percentage change (EAPC) was used to quantify the temporal trends of age-standardized mortality rate (ASMR) of FBC in 1990-2017. RESULTS: Worldwide, the number of deaths from FBC increased from 344.9 thousand in 1990 to 600.7 thousand in 2017. The ASMR of FBC decreased by 0.59% (95% CI, 0.52, 0.66%) per year during the study period. This decrease was largely driven by the reduction in alcohol use- and tobacco-related FBC, of which the ASMR was decreased by 1.73 and 1.77% per year, respectively. In contrast, the ASMR of FBC attributable to high BMI and high FPG was increased by 1.26% (95% CI, 1.22, 1.30%) and 0.26% (95% CI, 0.23, 0.30%) per year between 1990 and 2017, respectively. CONCLUSIONS: The mortality rate of FBC experienced a reduction over the last three decades, which was partly owing to the effective control for alcohol and tobacco use. However, more potent and tailored prevention strategies for obesity and diabetes are urgently warranted.

Diagnostic segregation of human breast tumours using Fourier-transform infrared spectroscopy coupled with multivariate analysis: Classifying cancer subtypes.

The present study aimed to investigate whether attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy coupled with multivariate analysis could be applied to discriminate and classify among breast tumour molecular subtypes based on the unique spectral "fingerprints" of their biochemical composition. The different breast cancer tissues and normal breast tissues were collected and identified by pathology and ATR-FTIR spectroscopy respectively. The study indicates that the levels of the lipid-to-protein, nucleic acid-to-lipid, phosphate-to-carbohydrate and their secondary structure ratio, including RNA-to-DNA, Amide I-to-Amide II, and RNA-to-lipid ratios were significantly altered among the molecular subtype of breast tumour compared with normal breast tissues, which helps explain the changes in the biochemical structure of different molecular phenotypes of breast cancer. Tentatively-assigned characteristic peak ratios of infrared (IR) spectra reflect the changes of the macromolecule structure in different issues to a great extent and can be used as a potential biomarker to predict the molecular subtype of breast tumour. The present study acts as the first case study to show the successful application of IR spectroscopy in classifying subtypes of breast cancer with biochemical alterations. Therefore, the present study is likely to help to provide a new diagnostic approach for the accurate diagnosis of breast tumours and differential molecular subtypes and has the potential to be used for further intraoperative management.

Spectrochemical determination of effects on rat liver of binary exposure to benzo[a]pyrene and 2,2',4,4'-tetrabromodiphenyl ether.

Benzo[a]pyrene (B[a]P) and polybrominated diphenyl ethers (PBDEs) are persistent environmental contaminants. The effects in organisms of exposures to binary mixtures of such contaminants remain obscure. Attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy is a label-free, non-destructive analytical technique allowing spectrochemical analysis of macromolecular components, and alterations thereof, within tissue samples. Herein, we employed ATR-FTIR spectroscopy to identify biomolecular changes in rat liver post-exposure to B[a]P and BDE-47 (2,2',4,4'-tetrabromodiphenyl ether) congener mixtures. Our results demonstrate that significant separation occurs between spectra of tissue samples derived from control versus exposure categories (accuracy = 87%; sensitivity = 95%; specificity = 79%). Additionally, there is significant spectral separation between exposed categories (accuracy = 91%; sensitivity = 98%; specificity = 90%). Segregation between control and all exposure categories were primarily associated with wavenumbers ranging from 1600 to 1700 cm-1 . B[a]P and BDE-47 alone, or in combination, induces liver damage in female rats. However, it is suggested that binary exposure apparently attenuates the toxic effects in rat liver of the individual contaminants. This is supported by morphological observations of liver tissue architecture on hematoxylin and eosin (H&E)-stained liver sections. Such observations highlight the difficulties in predicting the endpoint effects in target tissues of exposures to mixtures of environmental contaminants.

An analysis of spatiotemporal pattern for COIVD-19 in China based on space-time cube.

This study seeks to examine and analyze the spatial and temporal patterns of 2019 novel coronavirus disease (COVID-19) outbreaks and identify the spatiotemporal distribution characteristics and changing trends of cases. Hence, local outlier analysis and emerging spatiotemporal hot spot analysis were performed to analyze the spatiotemporal clustering pattern and cold/hot spot trends of COVID-19 cases based on space-time cube during the period from 23 January 2020 to 24 February 2020. The main findings are as follows: (1) The outbreak had spread rapidly throughout the country within a short time and the current totality incidence rate has decreased. (2) The spatiotemporal distribution of cases was uneven. In terms of the spatiotemporal clustering pattern, Wuhan and Shiyan city were the center as both cities had high-high clustering pattern with a surrounding unstable multiple-type pattern in partial areas of Henan, Anhui, Jiangxi, and Hunan provinces, and Chongqing city. Those regions are continuously in the hot spot on the spatiotemporal tendency. (3) The spatiotemporal analysis technology based on the space-time cube can analyze comprehensively the spatiotemporal pattern of epidemiological data and produce a visual output of the consequences, which can reflect intuitively the distribution and trend of data in space-time. Therefore, the Chinese government should strengthen the prevention and control efforts in a targeted manner to cope with a highly changeable situation.