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Experimental evidence has shown that per- and polyfluoroalkyl substances (PFAS) alternatives and mixtures may exert hepatotoxic effects in animals. However, epidemiological evidence ...is limited. This research aimed to explore associations of PFAS and the alternatives with liver function in a general adult population. The study participants consisted of 1,303 adults from a community-based cross-sectional investigation in Guangzhou, China, from November 2018 to August 2019. We selected 13 PFAS with detection rates > 85% in serum samples and focused on perfluorooctane-sulfonic acid (PFOS), perfluorooctanoic acid (PFOA) and their alternatives 6:2 chlorinated polyfluorinated ether sulfonate (6:2 Cl-PFESA), 8:2 Cl-PFESA, and perfluorohexanoic acid (PFHxA) as predictors of outcome. Six liver function biomarkers (ALB, ALT, AST, GGT, ALP, and DBIL) were chosen as outcomes. We applied regression models with restricted cubic spline function to explore correlations between single PFAS and liver function and inspected the combined effect of PFAS mixtures on liver by applying Bayesian kernel machine regression (BKMR). We discovered positive associations among PFAS and liver function biomarkers except for ALP. For example, compared with the 25th percentile of PFAS concentration, the level of ALT increased by 12.36% (95% CI: 7.91%, 16.98%) for ln-6:2 Cl-PFESA, 5.59% (95% CI: 2.35%, 8.92%) for ln-8:2 Cl-PFESA, 3.56% (95% CI: −0.39%, 7.68%) for ln-PFHxA, 13.91% (95% CI: 8.93%, 19.13%) for ln-PFOA, and 14.25% (95% CI: 9.91%, 18.77%) for ln-PFOS at their 75th percentile. In addition, higher exposed serum PFAS was found to be correlated with greater odds of abnormal liver function. Analysis from BKMR models also showed an adverse association between PFAS mixtures and liver function. The combined effect of the PFAS mixture appeared to be non-interactive, in which PFOS was the main contributor to the overall effect. Our findings provide evidence of associations between PFAS alternatives, PFAS mixtures, and liver function in the general adult population.
Background Whether serum lactate dehydrogenase-to-albumin ratio (LAR) influenced the outcomes of colorectal cancer (CRC) patients after radical surgery remained unclear. Therefore, this study sought ...to examine how LAR influences the short-term and long-term outcomes of CRC patients who have undergone radical surgery. Methods This study retrospectively included CRC patients who underwent radical resection between January 2011 and January 2020. We compared short-term outcomes, as well as overall survival (OS) and disease-free survival (DFS), among various groups. Both univariate and multivariate logistic regression analyses were utilized to pinpoint independent risk factors associated with overall complications and major complications. Moreover, Cox regression analysis were conducted for OS and DFS. Odds ratio (OR) and Hazard ratio (HR) were adjusted. Results This study encompassed a cohort of 3868 patients. 3440 patients were in the low LAR group and 428 patients constituted the high LAR group. In the high LAR group, patients experienced significantly longer operative times (p < 0.01), larger intraoperative blood loss (p < 0.01), and extended postoperative hospital stays (p < 0.01). Additionally, the incidence of both overall complications (p < 0.01) and major complications (p < 0.01) was higher in the high LAR group compared to the low LAR group. Furthermore, LAR was emerged as an independent prognostic factor for overall complications OR/95% CI: (1.555/1.237 to 1.954), p < 0.01 and major complications OR/95% CI: (2.178/1.279 to 3.707), p < 0.01. As for long-term survival, the high LAR group had worse OS in stage II (p < 0.01) and stage III (p < 0.01). In both stage II (p < 0.01) and stage III (p < 0.01), the high LAR group exhibited poorer DFS. Additionally, according to Cox regression analysis, LAR was identified as an independent predictor for both OS HR/95% CI: (1.930/1.554 to 2.398), p < 0.01 and DFS HR/95% CI: (1.750/1.427 to 2.146), p < 0.01. Conclusion LAR emerged as an independent predictor not only for overall complications and major complications but also for both OS and DFS, highlighting its significance and deserving the attention of surgeons. Keywords: Colorectal cancer, Lactate dehydrogenase-to-albumin ratio, Short-term outcomes, Prognosis
Novel capacitance-type humidity sensors based on MoS 2 /Ag composite films with a simple preparation method were proposed. The sensing characteristics of sensors against relative humidity were ...investigated, and the test results demonstrated that the humidity sensitivity of the MoS 2 /Ag-based sensors was significantly Enhanced, which is ten times that of the pure MoS 2 -based humidity sensors. Meanwhile, this kind of sensors exhibited fast response speed capable of detecting the human breath. Furthermore, complex impedance spectroscopy was discussed to understand the sensing mechanisms of MoS 2 /Ag-based sensors.
In genome research, it is a fundamental issue to identify few but important survival‐related biomarkers. The Cox model is a widely used survival analysis technique, which is used to study the ...relationship between characteristics and survival response. However, limitations of the existing Cox methods for genomic data are as follows: (1) a typical gene expression data set consists of tens of thousands of genes, and the result of current methods may not be sparse enough; (2) a wealth of structural information about many biological processes, such as regulatory networks and pathways, has often been ignored; (3) genomic data is usually considered as high noise, which is usually ignored in current methods. To alleviate the above problems, in this paper, we study a novel sparse Cox regression model, called SPLSN, which combines self‐paced learning (SPL) and a log‐sum absolute network‐based penalty (Logsum‐Net), especially for biomarker selection in survival analysis. SPL is embedded in curriculum design, and the model is trained by gradually increasing samples from low noise to high noise during the training process. The Logsum‐Net encourages smoothness among the coefficients of adjacent genes on a specific biological network. We compare the proposed method with five alternative approaches in various experimental scenarios, including a comprehensive simulation, seven benchmark gene expression data sets, and one large validation data set. Results show that the SPLSN can identify fewer meaningful biomarkers and obtain the best or equivalent prediction performance. Moreover, the biological analysis shows that the genes selected by the SPLSN might be helpful to tumor treatment.
Accurately predicting the survival rate of breast cancer patients is a major issue for cancer researchers. Machine learning (ML) has attracted much attention with the hope that it could provide ...accurate results, but its modeling methods and prediction performance remain controversial. The aim of this systematic review is to identify and critically appraise current studies regarding the application of ML in predicting the 5-year survival rate of breast cancer.
In accordance with the PRISMA guidelines, two researchers independently searched the PubMed (including MEDLINE), Embase, and Web of Science Core databases from inception to November 30, 2020. The search terms included breast neoplasms, survival, machine learning, and specific algorithm names. The included studies related to the use of ML to build a breast cancer survival prediction model and model performance that can be measured with the value of said verification results. The excluded studies in which the modeling process were not explained clearly and had incomplete information. The extracted information included literature information, database information, data preparation and modeling process information, model construction and performance evaluation information, and candidate predictor information.
Thirty-one studies that met the inclusion criteria were included, most of which were published after 2013. The most frequently used ML methods were decision trees (19 studies, 61.3%), artificial neural networks (18 studies, 58.1%), support vector machines (16 studies, 51.6%), and ensemble learning (10 studies, 32.3%). The median sample size was 37256 (range 200 to 659820) patients, and the median predictor was 16 (range 3 to 625). The accuracy of 29 studies ranged from 0.510 to 0.971. The sensitivity of 25 studies ranged from 0.037 to 1. The specificity of 24 studies ranged from 0.008 to 0.993. The AUC of 20 studies ranged from 0.500 to 0.972. The precision of 6 studies ranged from 0.549 to 1. All of the models were internally validated, and only one was externally validated.
Overall, compared with traditional statistical methods, the performance of ML models does not necessarily show any improvement, and this area of research still faces limitations related to a lack of data preprocessing steps, the excessive differences of sample feature selection, and issues related to validation. Further optimization of the performance of the proposed model is also needed in the future, which requires more standardization and subsequent validation.
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•We provided more evidence on associations between legacy PFASs and PFAS alternatives and glucose-homeostasis.•We explored the joint associations of legacy PFASs and PFAS ...alternatives.•6:2 Cl-PFESA contributed the most in the joint associations.•Sex-specific associations were observed.
Epidemiological studies on the associations of legacy per- and polyfluoroalkyl substances (PFASs) and glucose homeostasis remain discordant. Understanding of PFAS alternatives is limited, and few studies have reported joint associations of PFASs and PFAS alternatives.
To investigate associations of novel PFAS alternatives (chlorinated perfluoroalkyl ether sulfonic acids, Cl-PFESAs and perfluorobutanoic acid, PFBA) and two legacy PFASs (Perfluorooctanoic acid, PFOA and perfluorooctane sulfonate, PFOS) with glucose-homeostasis markers and explore joint associations of 13 legacy and alternative PFASs with the selected outcomes.
We used cross-sectional data of 1,038 adults from the Isomers of C8 Health Project in China. Associations of PFASs and PFAS alternatives with glucose-homeostasis were explored in single-pollutant models using generalized linear models with natural cubic splines for PFASs. Bayesian Kernel Machine Regression (BKMR) models were applied to assess joint associations of exposures and outcomes. Sex-specific analyses were also conducted to evaluate effect modification.
After adjusting for confounders, both legacy (PFOA, PFOS) and alternative (Cl-PFESAs and PFBA) PFASs were positively associated with glucose-homeostasis markers in single-pollutant models. For example, in the total study population, estimated changes with 95% confidence intervals (CI) of fasting glucose at the 95th percentile of 6:2Cl-PFESA and PFOS against the thresholds were 0.90 (95% CI: 0.59, 1.21) and 0.44 (95% CI: 0.26, 0.62). Positive joint associations were found in BKMR models with 6:2Cl-PFESA contributing most. Sex-specific associations existed in both single- and multi-pollutant models.
Legacy and alternative PFASs were positively associated with glucose-homeostasis markers. 6:2Cl-PFESA was the primary contributor. Sex-specific associations were also identified. These results indicate that joint associations and effect modification should be considered in risk assessment. However, further studies are recommended to strengthen our findings and to elucidate the mechanisms of action of legacy and alternative PFASs.
The polynuclear metal clusters continually attract wide interest due to their intriguing structures and potential applications in various scientific fields. Here, four actinide clusters have been ...synthesized by the utilization of multifunctional ligand ferrocenecarboxylic acid (HFcc) and Th4+/U4+ ions by solvent evaporation or solvothermal synthesis strategies in different solvents. Therein, compounds 1, 2 and 4 feature similar An6(μ3‐O)4(μ3‐OH)412+ cores, which are further coordinated by 12 Fcc− ligands and different solvent molecules. The U6Fe12 cluster of compound 4 is linked by four free HFcc molecules via multiple hydrogen bonding to form a supramolecular cluster U6(μ3‐O)4(μ3‐OH)4(Fcc)12(H2O)4 ⋅ 4HFcc. The cluster core of compound 3 is a μ3‐O2− bridged U3(μ3‐O)10+ unit, which is further coordinated by 10 Fcc− ligands via three kinds of coordination modes. It is worth noting that multifunctional Fcc− ligand not only endows compound 1 a main redox wave at E1/2=0.720 V in CH2Cl2/DMF solution, but also enables it to exhibit aggregation‐induced emission (AIE) property.
Four actinide clusters have been synthesized by the utilization of multifunctional ligand ferrocenecarboxylic acid (HFcc) and Th4+/U4+ ions by solvent evaporation or solvothermal synthesis strategies in different solvents. Multifunctional Fcc− ligand not only endows compound 1 a main redox wave at E1/2=0.720 V in CH2Cl2/DMF solution, but also enables it to exhibit aggregation‐induced emission (AIE) property.
The objective of the current study was to investigate the expression pattern and clinicopathological significance of SCC‐S2 in patients with non‐small‐cell lung cancer (NSCLC). The expression profile ...of SCC‐S2 in NSCLC tissues and adjacent noncancerous lung tissues was detected by real‐time RT‐PCR, western blot analysis, and immunohistochemistry. In 25 lung cancer tissues examined, 18 (72%) of them exhibited stronger levels of SCC‐S2 mRNA compared with their corresponding normal tissues. SCC‐S2 protein level was up‐regulated in cancerous lung tissues compared to adjacent normal tissue. Moreover, the expression level of SCC‐S2 in 93 archived NSCLC tissues was measured by immunohistochemical staining. SCC‐S2 was found to be overexpressed in 71 of 93 (76.3%) human lung cancer samples and correlated with lymph node metastasis (P = 0.0181), p‐TNM stage (P = 0.0042), Ki‐67 expression (P = 0.0028), and poor survival (P = 0.012). In addition, depleting SCC‐S2 expression by small‐interfering RNA inhibited growth and invasion in lung cell lines. These results indicate that SCC‐S2 plays an important role in NSCLC and might be a useful therapeutic target of NSCLC. (Cancer Sci 2010)
In this letter, a MoS 2 -based humidity sensor braced by SiO 2 microsphere layers with rapid response was developed. The results demonstrated that the humidity sensor can exhibit a subsecond ...response. A mechanism based on the morphology and structure of the sensing film was proposed to explain the rapid response behavior of humidity sensors. In addition, the effect of film thickness on response time was discussed. This letter demonstrated that the MoS 2 -based humidity sensor braced by SiO 2 microspheres is suitable for the miniature drip infusion rate detection device.
Cu2O/CuO sub-microspheres were synthesized via a one-step reduction approach using copper (II) acetate as precursor in triethylene glycol solution at reaction temperature ranging from 100 to 180°C. ...It is found that the reaction temperature plays a very important role in the size, the Cu2O content, and morphology of the products. The sub-microspheres obtained at the reaction temperature below 140°C are assembled by smaller particles with a diameter of about 10nm. As the reaction temperature is increased to above 160°C, uneven samples with larger size will be synthesized. The sensing performances of the sub-microspheres are related to the Cu2O content, porous characteristics and their surface areas. The sensor response of the sub-microspheres obtained at 120°C is up to 2.1–50ppb H2S gas at 95°C, and the recovery time is only about 76s. Thus, the sub-microspheres are promising for H2S sensors.
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