Cathelicidin LL-37 promotes wound healing in diabetic mice by regulating TFEB-dependent autophagy.

Diabetic patients often experience impaired wound healing. Human cathelicidin LL-37 possesses various biological functions, such as anti-microbial, anti-inflammatory, and pro-wound healing activities. Autophagy has important effects on skin wound healing. However, little is known about whether LL-37 accelerates diabetic wound healing by regulating autophagy. In the study, we aimed to investigate the role of autophagy in LL-37-induced wound healing and uncover the underlying mechanisms involved. A full-thickness wound closure model was established in diabetic mice to evaluate the effects of LL-37 and an autophagy inhibitor (3-MA) on wound healing. The roles of LL-37 and 3-MA in regulating keratinocyte migration were assessed using transwell migration and wound healing assays. The activation of transcription factor EB (TFEB) was measured using western blotting and immunofluorescence (IF) assays of its nuclear translocation. The results showed that LL-37 treatment improved wound healing in diabetic mice, whereas these effects were reversed by 3-MA. In vitro, 3-MA decreased the effects of LL-37 on promoting HaCat keratinocyte migration in the presence of high glucose (HG). Mechanistically, LL-37 promoted TFEB activation and resulted in subsequent activation of autophagy, as evidenced by increased nuclear translocation of TFEB and increased expression of ATG5, ATG7, and beclin 1 (BECN1), whereas these changes were blocked by TFEB knockdown. As expected, TFEB knockdown damaged the effects of LL-37 on promoting keratinocyte migration. Collectively, these results suggest that LL-37 accelerates wound healing in diabetic mice by activating TFEB-dependent autophagy, providing new insights into the mechanism by which LL-37 promotes diabetic wound healing.

A tiered approach of hazard-prioritization and risk-ranking for chemical hazards in food commodities: Application for selected mycotoxins.

Chemical hazards in foods, especially naturally occurring food contaminants like mycotoxins, are of serious public health concern. It is important to develop a practical framework to assess and rank health risks of chemical contaminants which can be further utilized by regulatory agencies to prioritize resources for risk assessment and management. In this study, a tiered hazard-prioritization and risk-ranking approach, which included two steps: exposure-based screening and margin of exposure (MOE)-based probabilistic risk ranking; was proposed to efficiently identify and rank chemicals of health concerns. Given the exposure-based hazard prioritization, chemicals with negligible or low health risks were first excluded. The remaining chemicals, imposing a higher health risk, were then ranked to facilitate risk-based decision making. The proposed approach was applied to identify and rank the mycotoxins with substantial health concerns in food commodities randomly sampled in China. A total of 19 mycotoxins were analyzed in 783 food commodities, including infant cookie, noodle, rice flour samples, wheat flour, millet, and rice. Results showed that the mycotoxins in infant foods with the highest health risk were Tenuazonic acid, Deoxynivalenol, and Enniatin B1, but as indicated by the probabilistic MOE estimation, the risks were still in the acceptable range and generally lower than the risks imposed by trace elements (e.g., Arsenic and Cadmium). The health risks of the other 16 mycotoxins were negligible mainly due to their low exposure levels. This study demonstrated that the proposed tiered approach was an efficient and effective tool to quantify and prioritize health risks in support of human health risk management.

Quantitative Integration of Mode of Action Information in Dose-Response Modeling and POD Estimation for Nonmutagenic Carcinogens: A Case Study of TCDD.

BACKGROUND: Traditional dose-response assessment applies different low-dose extrapolation methods for cancer and noncancer effects and assumes that all carcinogens are mutagenic unless strong evidence suggests otherwise. Additionally, primarily focusing on one critical effect, dose-response modeling utilizes limited mode of action (MOA) data to inform low-dose risk. OBJECTIVE: We aimed to build a dose-response modeling framework that continuously extends the curve into the low-dose region via a quantitative integration of MOA information and to estimate MOA-based points of departure (PODs) for nonmutagenic carcinogens. METHODS: 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) was used as an example to demonstrate the new dose-response modeling framework. There were three major steps included: a) identifying and extracting key quantifiable events (KQEs), b) calculating essential doses that sequentially activate KQEs using the benchmark dose (BMD) methodology, and c) characterizing pathway dose-response relationship for MOA-based POD estimation. RESULTS: We identified and extracted six KQEs and corresponding essential events composing the MOA of TCDD-induced liver tumors. With the essential doses estimated from the BMD method using various settings, three link functions were applied to model the pathway dose-response relationship. Given a toxicologically plausible definition of adversity, an MOA-based POD was derived from the pathway dose-response curve. The estimated MOA-based PODs were generally comparable with traditional PODs and can be further used to calculate reference doses (RfDs). CONCLUSIONS: The proposed framework quantitatively integrated mechanistic information in the modeling process and provided a promising strategy to harmonize cancer and noncancer dose-response assessment through pathway dose-response modeling. However, the framework can also be limited by data availability and the understanding of the underlying mechanism. https://doi.org/10.1289/EHP12677.

Margin of exposure to free formaldehyde in personal care products containing formaldehyde-donor preservatives: Evidence for consumer safety.

Formaldehyde has been classified as carcinogenic to humans by International Agency for Research on Cancer and found in personal care (PC) products containing formaldehyde-donor (FD) preservatives. However, the cancer risk associated with the use of FD-containing PC products has not been well established. Our study provides the quantitative cancer risk assessment of formaldehyde in FD-containing PC products. The carbon-13 nuclear magnetic resonance (13C-NMR) spectroscopy was used in this risk assessment to provide reliable exposure information to formaldehyde in PC products and aqueous solutions containing sodium hydroxymethylglycinate. The risk assessment was conducted using the margin of exposure (MOE) approach with benchmark doses (BMDs) for 10% effect. For hemolymphoreticular neoplasias in male rats, a BMD of 28.03 mg/kg/day and a BMD lower confidence limit (BMDL) of 2.52 mg/kg/day were calculated from available long-term animal experiments. The worst-case consumer exposure to formaldehyde from FD-containing PC products was 0.007 µg/kg/day. Comparing the consumer exposure with BMDL, the resulting MOE was 360,000 for the worst-case scenario. The consumer exposure to formaldehyde (0.007 µg/kg/day) from using FD-containing PC products represents less than 1.0 × 10-6 % of background level endogenous formaldehyde (878-1310 mg/kg/day). The cancer risk from formaldehyde to consumers using FD-containing PC products is negligible.

Probiotic-loaded edible films made from proteins, polysaccharides, and prebiotics as a quality factor for minimally processed fruits and vegetables: A review.

Minimally processed fruits and vegetables (MPFVs) are gaining popularity in households because of their freshness, convenience, and rapid consumption, all of which align with today's busy lifestyles. However, their exposure of large surface areas during peeling and slicing can result in contamination by foodborne pathogens and spoilage bacteria, posing potential food safety concerns. In addition, enzymatic browning of MPFVs can significantly reduce their consumer appeal. Therefore, it is necessary to adopt certain methods to protect MPFVs. Recent studies have shown that utilizing biopolymer-based edible films containing probiotics is a promising approach to preserving MPFVs. These active food packaging films exhibit barrier function, antioxidant function, and antimicrobial function while protecting the viability of probiotics, which is essential to maintain the nutritional value and quality of MPFVs. This paper reviews microbial contamination in MPFVs and the preparation of probiotic-loaded edible films with common polysaccharides (alginate, gellan gum, and starch), proteins (zein, gelatin, and whey protein isolate), prebiotics (oligofructose, inulin, and fructooligosaccharides). It also explores the potential application of probiotic-loaded biopolymer films/coatings on MPFVs, and finally examines the practical application requirements from a consumer perspective.

A mode of action-based probabilistic framework of dose-response assessment for nonmutagenic liver carcinogens: a case study of PCB-126.

A main function of dose-response assessment is to estimate a "safe" dose in the target population to support chemical risk assessment. Typically, a "safe" dose is developed differently for cancer and noncancer effects based on a 2-step procedure, ie, point of departure (POD) derivation and low-dose extrapolation. However, the current dose-response assessment framework is criticized for its dichotomized strategy without integrating the mode of action (MOA) information. The objective of this study was, based on our previous work, to develop a MOA-based probabilistic dose-response framework that quantitatively synthesizes a biological pathway in a dose-response modeling process to estimate the risk of chemicals that have carcinogenic potential. 3,3',4,4',5-Pentachlorobiphenyl (PCB-126) was exemplified to demonstrate our proposed approach. There were 4 major steps in the new modeling framework, including (1) key quantifiable events (KQEs) identification and extraction, (2) essential dose calculation, (3) MOA-based POD derivation, and (4) MOA-based probabilistic reference dose (RfD) estimation. Compared with reported PODs and traditional RfDs, the MOA-based estimates derived from our approach were comparable and plausible. One key feature of our approach was the use of overall MOA information to build the dose-response relationship on the entire dose continuum including the low-dose region. On the other hand, by adjusting uncertainty and variability in a probabilistic manner, the MOA-based probabilistic RfDs can provide useful insights of health protection for the specific proportion of population. Moreover, the proposed framework had important potential to be generalized to assess different types of chemicals other than nonmutagenic carcinogens, highlighting its utility to improve current chemical risk assessment.

Benchmark dose modeling for epidemiological dose-response assessment using prospective cohort studies.

Benchmark dose (BMD) methodology has been employed as a default dose-response modeling approach to determine the toxicity value of chemicals to support regulatory chemical risk assessment. Especially, a relatively standardized BMD analysis framework has been established for modeling toxicological data regarding the formats of input data, dose-response models, definitions of benchmark response, and model uncertainty consideration. However, the BMD approach has not been well developed for epidemiological data mainly because of the diverse designs of epidemiological studies and various formats of data reported in the literature. Although most of the epidemiological BMD analyses were developed to solve a particular question, the methods proposed in two recent studies are able to handle cohort and case-control studies using summary data with consideration of adjustments for confounders. Therefore, the purpose of the present study is to investigate and compare the "effective count"-based BMD modeling approach and adjusted relative risk (RR)-based BMD analysis approach to identify an appropriate BMD modeling framework that can be generalized for analyzing published data of prospective cohort studies for BMD analysis. The two methods were applied to the same set of studies that investigated the association between bladder and lung cancer and inorganic arsenic exposure for BMD estimation. The results suggest that estimated BMDs and BMDLs are relatively consistent; however, with the consideration of established common practice in BMD analysis, modeling adjusted RR values as continuous data for BMD estimation is a more generalizable approach harmonized with the BMD approach using toxicological data.

The Effect of Historical Data-Based Informative Prior on Benchmark Dose Estimation of Toxicogenomics.

High-throughput toxicogenomics as an advanced toolbox of Tox21 plays an increasingly important role in facilitating the toxicity assessment of environmental chemicals. However, toxicogenomic dose-response analyses are typically challenged by limited data, which may result in significant uncertainties in parameter and benchmark dose (BMD) estimation. Integrating historical data via prior distribution using a Bayesian method is a useful but not-well-studied strategy. The objective of this study is to evaluate the effectiveness of informative priors in genomic dose-response modeling and BMD estimation. Specifically, we aim to identify plausible informative priors and evaluate their effects on BMD estimates at both gene and pathway levels. A general informative prior and eight time-specific (from 3 h to 29 d) informative priors for seven commonly used continuous dose-response models were derived. Results suggest that the derived informative priors are sensitive to the specific data sets used for elicitation. Real data-based simulations indicate that BMD estimation with the time-specific informative priors can achieve increased or equivalent accuracy, significantly decreased uncertainty, and a slightly enhanced correlation with the points of departure estimated from apical end points than the counterparts with noninformative priors. Overall, our study systematically examined the effects of historical data-based informative priors on BMD estimates, highlighting the benefits of plausible information priors in advancing the practice of toxicogenomics.

Beyond the cancer slope factor: Broad application of Bayesian and probabilistic approaches for cancer dose-response assessment.

Traditional cancer slope factors derived from linear low-dose extrapolation give little consideration to uncertainties in dose-response model choice, interspecies extrapolation, and human variability. As noted previously by the National Academies, probabilistic methods can address these limitations, but have only been demonstrated in a few case studies. Here, we applied probabilistic approaches for Bayesian Model Averaging (BMA), interspecies extrapolation, and human variability distributions to 255 animal cancer bioassay datasets previously used by governmental agencies. We then derived predictions for both population cancer incidence and individual cancer risk. For model uncertainty, we found that lower confidence limits from BMA and from U.S. Environmental Protection Agency (EPA)'s Benchmark Dose Software (BMDS) correlated highly, with 86% differing by <10-fold. Incorporating other uncertainties and human variability, the lower confidence limits of the probabilistic risk-specific dose (RSD) at 10-6 population incidence were typically 3- to 30-fold lower than traditional slope factors. However, in a small (<7%) number of cases of highly non-linear experimental dose-response, the probabilistic RSDs were >10-fold less stringent. Probabilistic RSDs were also protective of individual risks of 10-4 in >99% of the population. We conclude that implementing Bayesian and probabilistic methods provides a more scientifically rigorous basis for cancer dose-response assessment and thereby improves overall cancer risk characterization.

Chitosan, alginate, hyaluronic acid and other novel multifunctional hydrogel dressings for wound healing: A review.

Wound healing is a complex project, and effectively promoting skin repair is a huge clinical challenge. Hydrogels have great prospect in the field of wound dressings because their physical properties are very similar to those of living tissue and have excellent properties such as high water content, oxygen permeability and softness. However, the single performance of traditional hydrogels limits their application as wound dressings. Therefore, natural polymers such as chitosan, alginate and hyaluronic acid, which are non-toxic and biocompatible, are individually or combined with other polymer materials, and loaded with typical drugs, bioactive molecules or nanomaterials. Then, the development of novel multifunctional hydrogel dressings with good antibacterial, self-healing, injectable and multi-stimulation responsiveness by using advanced technologies such as 3D printing, electrospinning and stem cell therapy has become a hot topic of current research. This paper focuses on the functional properties of novel multifunctional hydrogel dressings such as chitosan, alginate and hyaluronic acid, which lays the foundation for the research of novel hydrogel dressings with better performance.

Using Prior Toxicological Data to Support Dose-Response Assessment─Identifying Plausible Prior Distributions for Dichotomous Dose-Response Models.

The benchmark dose (BMD) methodology has significantly advanced the practice of dose-response analysis and created substantial opportunities to enhance the plausibility of BMD estimation by synthesizing dose-response information from different sources. Particularly, integrating existing toxicological information via prior distribution in a Bayesian framework is a promising but not well-studied strategy. The study objective is to identify a plausible way to incorporate toxicological information through informative prior to support BMD estimation using dichotomous data. There are four steps in this study: determine appropriate types of distribution for parameters in common dose-response models, estimate the parameters of the determined distributions, investigate the impact of alternative strategies of prior implementation, and derive endpoint-specific priors to examine how prior-eliciting data affect priors and BMD estimates. A plausible distribution was estimated for each parameter in the common dichotomous dose-response models using a general database. Alternative strategies for implementing informative prior have a limited impact on BMD estimation, but using informative prior can significantly reduce uncertainty in BMD estimation. Endpoint-specific informative priors are substantially different from the general one, highlighting the necessity for guidance on prior elicitation. The study developed a practical way to employ informative prior and laid a foundation for advanced Bayesian BMD modeling.

Non-gelated polymeric photonic crystal films.

A rapid curing method for the preparation of colloidal photonic crystal films is presented. Firstly, a colloidal crystal array template was prepared by self-assembly of nanospheres, and then a dilute polymer solution was poured into the gap of the template. Then the composite photonic film was obtained as the polymer solution was cured. Such films have good properties in mechanical strength, anti pH interference, rapid solvent response and are easy to preserve. The films show good linear response to ethanol aqueous solutions of different concentrations, and the response equilibrium takes less than 20 s. The films also show long-term stability and reusability, and further functionalization can make the films multi-sensitive.

Simplified, Low-Cost Method on Glucose Tolerance Testing in High-Risk Group of Diabetes, Explored by Simulation of Diagnosis.

Objective: Explore the distribution of basic characteristics of high-risk groups of diabetes; verify the practical significance and diagnostic value of the "three-point method"; layered analysis of glycated hemoglobin and glycated serum albumin, and study its value and significance in the diagnosis of diabetes mellitus, Type II and pre-diabetes mellitus, Type II.Methods: 1304 high-risk individuals with T2D in Shanghai, 529 males and 841 females with an average of (50.5 ± 15.2) years old, were examined by oral glucose tolerance test (OGTT), HbA1c and GA were determined. Process the data by Python and GraphPad; judge the diagnostic value of HbA1C, GA by ROC.Results: (1) The numbers of DM, NGT, HOG, IFG, Mild-IGT and Mid-IGT in the objects were 647, 141, 70, 4, 208 and 234 respectively. In the 43-49 age group with a higher incidence, the proportion of selected high-risk groups is low. (2) The sensitivity and specificity about "three-point method" used to determine NGT is 100% and 90.11%; to determine IGR is 75.11% and 97.32%; to determine HOG is 97.14% and 100%; to determine DM is 94.67% and 100%. (3) According to ROC judgment, it is found that these 2 did not have the function of separate diagnoses, the optimal critical point of HbA1C related to DM status is 5.95%, (P<.01); HbA1C related to IGR status is 5.75% (P<.01); of GA related to DM status is 15.25% (P<.01); GA related to IGR status is 14.95% (P<.01).

A computational system for Bayesian benchmark dose estimation of genomic data in BBMD.

BACKGROUND: Existing studies have revealed that the benchmark dose (BMD) estimates from short-term in vivo transcriptomics studies can approximate those from long-term guideline toxicity assessments. Existing software applications follow this trend by analyzing omics data through the maximum likelihood estimation and choosing the "best" model for BMD estimates. However, this practice ignores the model uncertainty and may result in over-confident inferences and predictions, leading to an inadequate decision. OBJECTIVE: By generally following the National Toxicology Program Approach to Genomic Dose-Response Modeling, we developed a web-based dose-response modeling and BMD estimation system, Bayesian BMD (BBMD), for genomic data to quantitatively address uncertainty from various sources. The performances of BBMD are compared with BMDExpress. METHODS: The system is primarily based on the previously developed BBMD system and further developed in a genomic perspective. Bayesian model averaging method is applied to BMD estimation and pathways analyses. Generally, the system is unique regarding the flexibility in preparing/storing data and in characterizing uncertainties. RESULTS: This system was tested and validated versus 24 previously published in-vivo microarray dose-response datasets (GSE45892) and 64 molecules data from the Open TG-Gates database. Short term transcriptional BMD values for the median pathway in BBMD are highly correlated with the long-term apical BMD values (R = 0.78-0.91). The BMD estimates obtained by BBMD were compared to those by BMDExpress. The results indicate that BBMD provides more adequate results in terms of less extreme values and no failure in BMD and BMDL calculations. Also, the pathway analysis in BBMD provides a conservative estimate because a broader confidence interval is established. DISCUSSION: Overall, this study demonstrates that dose-response modeling using genomic data can play a substantial role in support of chemical risk assessment. BBMD represents a robust and user-friendly alternative for genomic dose-response data analysis with outstanding functionalities to quantify uncertainty from various sources.

Photonic Crystal-Embedded Molecularly Imprinted Contact Lenses for Controlled Drug Release.

As a noninvasive eye disease detection and drug delivery device, contact lenses can improve eye bioavailability and enable continuous drug delivery. In order to monitor the release of drugs in real time, molecularly imprinted contact lenses (MICLs) based on photonic crystals (PCs) were prepared for the treatment of diabetes-related diseases. The specific adsorption of molecularly imprinted polymers on dexamethasone sodium phosphate (DSP) increased the drug loading and optimized the drug release behavior. At the same time, the drug release ensures the rapid color report during the loading and releasing of drugs due to the volume and refractive index change of the hydrogel matrix. The continuous and slow release of DSP by MICLs in artificial tears was successfully monitored through structural color changes, and the cytotoxicity test results showed that the MICL had good biocompatibility. Therefore, MICLs with a PC structure color have great biomedical potentiality in the future.

Circular RNA circEIF4G2 aggravates renal fibrosis in diabetic nephropathy by sponging miR-218.

Circular RNAs play essential roles in the development of various human diseases. However, how circRNAs are involved in diabetic nephropathy (DN) are not fully understood. Our study aimed to investigate the effects of circRNA circEIF4G2 on DN. Experiments were performed in the db/db mouse model of type 2 diabetes and NRK-52E cells. We found that circEIF4G2 was significantly up-regulated in the kidneys of db/db mice and NRK-52E cells stimulated by high glucose. circEIF4G2 knockdown inhibited the expressions of TGF-ß1, Collagen I and Fibronectin in high glucose-stimulated NRK-52E cells, which could be rescued by miR-218 inhibitor. Knockdown of SERBP1 reduced the expression of TGF-ß1, Collagen I and Fibronectin in HG-stimulated NRK-52E cells. In summary, our findings suggested that circEIF4G2 promotes renal tubular epithelial cell fibrosis via the miR-218/SERBP1 pathway, presenting a novel insight for DN treatment.

Health risk assessment of As due to rice ingestion based on iAs distribution and actual consumption patterns for the residents in Beijing: a cross-sectional study.

As a well-known human carcinogen, arsenic (As) could pose various detrimental health effects to humans mainly through the exposure pathway of food ingestion. In comparison with other foods, rice can accumulate more arsenic due to its tissue specificity. Thus, it is of great significance to assess the health risk of As due to rice ingestion. However, the study on risk assessment from exposure to As in rice is still in an early stage and lack accuracy to date. In this study, after obtaining the rice exposure behavior patterns based on a questionnaire survey, a total of 160 rice samples, which consisted of 4 types (i.e., japonica, indica, glutinous and brown rice), rice from 4 areas and consumed by most of the population in Beijing, were collected. On the basis of the actual intake rate and the species weighted average concentration of consumed rice, average daily exposure dose and health risks of inorganic As (iAs) from rice ingestion were assessed for the population among different genders and ages in Beijing. The results show that japonica rice and rice from Northeast China had higher As content, with the same value of 0.064 mg kg-1. And, they were the most popular rice consumed by people, with the intake rates of 75.50 g d-1, and 67.91 g d-1, respectively. The proportion of iAs to total As (tAs) was 58.34%, with a range of 43.18-71.88%. The average daily dose of iAs for the population was 1.15 × 10-4, which mainly came from japonica rice and the rice from Northeast China ingestion. In comparison with the acceptable non-cancer risk, which had a HQ value of 0.38, the carcinogenic risk of the population in Beijing was 1.73 × 10-4 on average. Furthermore, males had higher carcinogenic risk (1.88 × 10-4) than females (1.62 × 10-4), and the people in the age of 45-55 suffered from the highest carcinogenic risk (2.22 × 10-4), which mainly was attributed to the japonica rice and the rice from Northeast China. This study strengthened that appropriate dietary patterns should be paid more attention in order to control the health risk due to As exposure.

MicroRNA-139-5p Alleviates High Glucose-Triggered Human Retinal Pigment Epithelial Cell Injury by Targeting LIM-Only Factor 4.

Diabetic retinopathy (DR) is a type of diabetes complication, which can result in loss of vision in adults worldwide. Increasing evidence has revealed that microRNAs (miRs) can regulate DR progression. Thus, the present study was aimed at assessing the possible mechanism of miR-139-5p in high glucose- (HG-) incubated retinal pigment epithelial (ARPE-19) cells. The present results demonstrated that miR-139-5p expression was notably reduced in the serum samples of patients with DR, as well as in ARPE-19 cells treated with HG in a time-dependent manner. Moreover, miR-139-5p was markedly overexpressed by transfection of miR-139-5p mimics into ARPE-19 cells. Overexpression of miR-139-5p markedly induced cell viability and repressed HG-triggered apoptosis. Furthermore, overexpression of miR-139-5p relived HG-enhanced oxidative stress injury. It was found that HG induced malondialdehyde levels but decreased superoxide dismutase and glutathione peroxidase activities in ARPE-19 cells. In addition, overexpression of miR-139-5p could markedly decrease intracellular stress. The results demonstrated that overexpression of miR-139-5p effectively repressed HG-activated inflammation, as indicated by the upregulation of inflammation cytokines, including TNF-α, IL-6, and Cox-2, in ARPE-19 cells. Subsequently, it was identified that LIM-only factor 4 (LMO4) could act as a downstream target for miR-139-5p. LMO4 expression was significantly increased in patients with DR and HG-treated ARPE-19 cells. Mechanistically, knockdown of LMO4 reversed the biological role of miR-139-5p in proliferation, apoptosis, oxidative stress, and release of inflammation factors in vitro. Collectively, these results suggested that miR-139-5p significantly decreased ARPE-19 cell injury caused by HG by inducing proliferation and suppressing cell apoptosis, oxidant stress, and inflammation by modulating LMO4.