Air disinfection by nanosecond pulsed DBD plasma.

Atmospheric pressure dielectric barrier discharge (DBD) plasma is an emerging and promising technique for air disinfection in public environments. Power supply is a crucial factor but it remains unclear about its impacts on the air disinfection performance of plasmas. In this work, a nanosecond (ns) pulsed power supply was applied to drive an in-duct grating-like DBD array to achieve fast single-pass air disinfection. The influence of pulse parameters and environmental factors on both the discharge characteristics and the single-pass bacterial inactivation efficiency were uncovered. At a close relative humidity (RH) level, the efficiency was dominated by the discharge power, namely, specific input energy could serve as the disinfection dose. A higher frequency, shorter pulse rising time, and suitable pulse width are preferred to obtain a higher Z value. The pulsed source was not notably superior to an alternating current source, or even worse at a low voltage frequency at the same discharge power. Airflow humidity was a predominant factor to improve the efficiency and a single-pass efficiency of ∼ 99% and a Z value of 2.2 L/J were achieved under an optimal RH of 50%-60%. This work provides fundamental knowledge of ns-pulsed DBD on discharge characteristics and air disinfection behaviors.

Persistent pollution of genetic materials in a typical laboratory environment.

From the onset of coronavirus disease (COVID-19) pandemic, there are concerns regarding the disease spread and environmental pollution of biohazard since studies on genetic engineering flourish and numerous genetic materials were used such as the nucleic acid test of the severe acute respiratory syndrome coronavirus (SARS-CoV-2). In this work, we studied genetic material pollution in an institute during a development cycle of plasmid, one of typical genetic materials, with typical laboratory settings. The pollution source, transmission routes, and pollution levels in laboratory environment were examined. The Real-Time quantitative- Polymerase Chain Reaction results of all environmental mediums (surface, aerosol, and liquid) showed that a targeted DNA segment occurred along with routine experimental operations. Among the 79 surface and air samples collected in the genetic material operation, half of the environment samples (38 of 79) are positive for nucleic acid pollution. Persistent nucleic acid contaminations were observed in all tested laboratories and spread in the public area (hallway). The highest concentration for liquid and surface samples were 1.92 × 108 copies/uL and 5.22 × 107 copies/cm2, respectively. Significant amounts of the targeted gene (with a mean value of 74 copies/L) were detected in the indoor air of laboratories utilizing centrifuge devices, shaking tables, and cell homogenizers. Spills and improper disposal of plasmid products were primary sources of pollution. The importance of establishing designated experimental zones, employing advanced biosafety cabinets, and implementing highly efficient cleaning systems in laboratories with lower biosafety levels is underscored. SYNOPSIS: STATEMENT. Persistent environmental pollutions of genetic materials are introduced by typical experiments in laboratories with low biosafety level.

Variations in the morphological and chemical composition of the rhizomes of Polygonatum species based on a common garden experiment.

Polygonatum species have great potential in fighting chronic and hidden hunger. In this study, five Polygonatum species collected from different populations were cultivated in a common garden for 4 years. The species mainly differed in yield, saponin and polysaccharide contents, stem diameter, leaf width, inflorescence length, and floret inflorescence length. P. cyrtonema (PC) provides high-quality yield when planted in Zhejiang, with output as high as 7.5 tons per hectare and a promising breeding potential. Moreover, stem diameter can be used as an indicator of the harvest in the screening of varieties. In addition, the formation of plant genetic traits from different provenances is affected by the climatic factors of the origin. Furthermore, near-infrared spectroscopy combined with chemometrics for polysaccharide and saponin quantitation provides a rapid assessment of PC quality. Our findings provide a scientific basis for the development and sustainable utilization of PC as a high-yielding and high-quality forest crop.

Grating-like DBD plasma for air disinfection: Dose and dose-response characteristics.

Atmospheric pressure dielectric barrier discharge (DBD) plasma is an emerging technique for effective bioaerosol decontamination and is promising to be used in indoor environments to reduce infections. However, fundamental knowledge of the dose and dose-response characteristics of plasma-based disinfection technology is very limited. By examining the single-pass removal efficiency of S. lentus aerosol by in-duct grating-like DBD plasma reactors with varied discharge setups (gap distance, electrode size, number of discharge layers, frequency, dielectric material), it was found that the specific input energy (SIE) could be served as the dose for disinfection, and the efficiency was exponentially dependent on SIE in most cases. The corresponding susceptibility constants (Z values) were obtained hereinafter. Humidity was a prominent factor boosting the efficiency with a Z value of 0.36 L/J at relative humidity (RH) of 20% and 1.68 L/J at RH of 60%. MS2 phage showed a much higher efficiency of 2.66-3.08 log10 of reduction than those of S. lentus (38-85%) and E. coli (42%-95%) under the same condition. Using SIE as the dose, the performance of plasma reactors in the literature was compared and evaluated. This work provides a theoretical and engineering basis for air disinfection by plasma-based technology.

Integrated System for On-Site Rapid and Safe Screening of COVID-19.

Since the outbreak of coronavirus disease 2019 (COVID-19), the epidemic has been spreading around the world for more than 2 years. Rapid, safe, and on-site detection methods of COVID-19 are in urgent demand for the control of the epidemic. Here, we established an integrated system, which incorporates a machine-learning-based Fourier transform infrared spectroscopy technique for rapid COVID-19 screening and air-plasma-based disinfection modules to prevent potential secondary infections. A partial least-squares discrimination analysis and a convolutional neural network model were built using the collected infrared spectral dataset containing 857 training serum samples. Furthermore, the sensitivity, specificity, and prediction accuracy could all reach over 94% from the results of the field test regarding 968 blind testing samples. Additionally, the disinfection modules achieved an inactivation efficiency of 99.9% for surface and airborne tested bacteria. The proposed system is conducive and promising for point-of-care and on-site COVID-19 screening in the mass population.

Identifying key mutations of radioresponsive genes in esophageal squamous cell carcinoma.

Background: Radiotherapy plays an important effect on the standard therapy of esophageal squamous cell carcinoma (ESCC). However, the efficacy of the therapy is limited and a few patients do not achieve satisfactory treatment results due to the existence of radiation resistance. Therefore, it is necessary to identify the potential predictive biomarkers and treatment targets for ESCC. Methods: We performed the whole-exome sequencing to determine the germline and somatic mutations in ESCC. Functional enrichment and pathway-based protein-protein interaction analyses were used to ascertain potential regulatory networks. Cell survival and cell death after treatment with radiotherapy were determined by CCK-8 and LDH release assays in ESCC cells. The correlations of NOTCH1 and tumor immune infiltration were also analyzed in ESCC. Results: Our results showed that 344 somatic and 65 germline differentially mutated genes were detected to be radiosensitivity-related loci. The tumor mutational burdens (TMB) or microsatellite instability (MSI) were not significantly correlated with the response to radiotherapy in ESCC patients. Pathway-based protein-protein interaction analyses implied several hub genes with most nodes (such as PIK3CA, NOTCH1, STAT3 and KDR). The in vitro studies showed that the knockdown of NOTCH1 inhibited cell survival and rendered more cell death after the treatment with radiotherapy in ESCC cells, while NOTCH1 overexpression had the opposite effects. Moreover, NOTCH1, frequently up-regulated in ESCC, was negatively correlated with activated B cell and immature dendritic cell in ESCC. High expression of NOTCH1 was accompanied with the low levels of some immunotherapy-related cells, including CD8(+) T cells and NK cells. Conclusions: These results indicate the differences of the germline mutations and somatic mutations between the radiosensitive and radioresistence groups in ESCC and imply that NOTCH1 plays important roles in regulating the radiosensitivity of ESCC. The findings might provide the biomarkers and potential treatment targets for improving the sensitivity to radiotherapy in ESCC.

In-duct grating-like dielectric barrier discharge system for air disinfection.

In the context of spreading Coronavirus disease 2019 (COVID-19), the combination of heating, ventilation, and air-conditioning (HVAC) system with air disinfection device is an effective way to reduce transmissible infections. Atmospheric-pressure non-equilibrium plasma is an emerging technique for fast pathogen aerosol abatement. In this work, in-duct disinfectors based on grating-like dielectric barrier discharge (DBD) plasmas with varied electrode arrangements were established and evaluated. The highest airborne bacterial inactivation efficiency was achieved by 'vertical' structure, namely when aerosol was in direct contact with the discharge region, at a given discharge power. For all reactors, the efficiency was linearly correlated to the discharge power (R2 =0.929-0.994). The effects of environmental factors were examined. Decreased airflow rates boosted the efficiency, which reached 99.8% at the velocity of 0.5 m/s with an aerosol residence time of ~3.6 ms. Increasing humidity (relative humidity (RH)=20-60%) contributed to inactivation efficacy, while high humidity (RH=70%-90%) led to a saturated efficiency, possibly due to the disruption of discharge uniformity. As suggested by the plasma effluent treatment and scavenger experiments, gaseous short-lived chemical species or charged particles were concluded as the major agents accounting for bacterial inactivation. This research provides new hints for air disinfection by DBD plasmas.

Determinants and the Moderating Effects of Individual Characteristics on Autonomous Vehicle Adoption in China.

Along with the increasing popularity of autonomous vehicles (AVs), urban livability and public health will be enhanced due to ecofriendly issues: alleviated traffic congestion, lower car ownership, and reduced transport emissions. However, some emerging issues, including public safety, trust, privacy, reliability, underdeveloped legislation, and liability, may deter user intentions to adopt an AV. This study introduces an extensive factor, playfulness, into the technology acceptance model (TAM) to quantify the impacts of psychological factors (perceived usefulness, perceived ease of use, and perceived playfulness) on AV adoption intention. This study proposes four AV-related policy measures (financial incentivization, information dissemination, convenience, and legal normalization) and examines how policy measures motivate users to adopt an AV to facilitate public safety. Furthermore, this study investigated the moderating effects of demographic factors on the relationships between independent variables and AV adoption intention. Two models were proposed and estimated using a total of 1831 survey responses in China. The psychology-related and policy-related models explained 62.2% and 33.6% of the variance in AV adoption intention, respectively. The results suggest that perceived playfulness (ß = 0.524, p < 0.001) and information dissemination (ß = 0.348, p < 0.001) are the most important influencing factors of AV adoption intention. In addition, demographic factors (gender, education, income, the number of private cars owned by a family, and types of cities) can moderate the effects of psychological factors and policy measures on user intentions to adopt an AV. These insights can be employed to design more cost-effective policies and strategies for subgroups of the population to maximize the AV adoption intention.

Impacts of Pokémon GO on route and mode choice decisions: exploring the potential for integrating augmented reality, gamification, and social components in mobile apps to influence travel decisions.

This study aims to understand the impacts of Pokémon GO, a popular location-based augmented reality (AR) mobile gaming app, on route and mode choices. Pokémon GO leverages AR to introduce virtual objects at fixed and dynamic locations that translate through the app interface to incentives in the real world that potentially influence users' route and mode choices. Its gaming nature and social components can possibly enhance long-term user engagement through applying the characteristics of game elements and providing opportunities for competition, collaboration, companionship, and social reinforcement. An online survey is conducted to collect the self-reported behavior of a group of Pokémon GO users to explore its impacts on the following aspects of travel behavior: (1) the frequency of changing the route to interact with virtual objects; (2) the likelihood of carpooling more instead of driving alone for more in-app collaboration; and (3) the likelihood of shifting mode from drive alone to public transit, walking, and cycling if provided with additional incentives. The ordered survey responses including frequency and likelihood are analyzed using random parameters ordered probit models to account for the unobserved heterogeneity across users and identify subpopulations of travelers who are more susceptible to the influence of Pokémon GO. The modeling results identify four types of variables (attitude and perceptions related to Pokémon GO, app engagement, play style, and sociodemographic characteristics) that affect users' travel behavior. The results illustrate that such apps with integrated AR, gamification, and social components can be used by policymakers to influence various aspects of travel behavior. The study findings and insights can provide valuable feedback to system operators for designing such apps to dynamically manage traffic in real-time and promote long-term sustainable mode shifts.

Integrative Analysis of miRNAs Involved in Fat Deposition in Different Pig Breeds.

BACKGROUND: miRNAs are a set of small, noncoding RNAs that bind to partially complementary sequences on target mRNAs. This leads to the post-transcriptional regulation of gene expression. Many studies have shown that microRNAs play critical roles in adipose cell differentiation and fat metabolism. The aim of this study was to explore the regulatory functions of miRNAs in fat deposition for the prevention and therapy of lipid metabolism-related diseases. METHODS: The significant differences in the fat deposition of Laiwu (LW) pigs and Large White (LY) pigs were studied. To investigate the genetic relationships of miRNAs that regulate fat deposition, we performed a genome-wide analysis of miRNAs derived from subcutaneous adipose tissue of LW and LY pigs using RNA-seq. RESULTS: There were 39 known miRNAs and 56 novel miRNAs significantly differential expressed between the two breeds of pigs. In the analysis of the Gene Ontology and KEGG pathways, predicted targets of these differentially expressed miRNAs were involved in several fat-associated pathways, such as the peroxisome proliferator-activated receptor (PPAR), mitogen-activated protein kinases (MAPK) and Wnt signaling pathways. In addition, ssc-miR-133a-3p, ssc-miR-486 and ssc-miR-1 each had a great impact on the development of porcine subcutaneous fat through the PPAR signaling pathway. CONCLUSIONS: We explored the role of differentially expressed miRNAs and studied the mechanisms of adipogenesis and fat deposition between two different pig breeds. In addition, these results also contribute to research relevant to human obesity.

Disinfection of Escherichia coli in ice by surface dielectric barrier discharge plasma.

A variety of pathogens can cause people to suffer from serious diseases, and the transmission of COVID-19 through the cold chain has once again attracted people's attention to cold chain disinfection. Unfortunately, there is no mature cold chain disinfection technique yet. In this study, a low-temperature plasma disinfection technique for a cold chain is proposed. The disinfection effect of plasma generated by surface dielectric barrier discharge on Escherichia coli in ice at cryogenic temperature is studied, and the possible disinfection mechanism is discussed. It is found that the O3 mode and the NOx mode also exist in the surface dielectric barrier discharge at cryogenic temperature, just as at room temperature. The disinfection effect of both modes is weak in 5 min plasma treatment, but in 60 min post-treatment, the NOx mode shows a stronger disinfection effect, with 4.45 log reduction. It is speculated that gaseous H2O2 and NOx can be adsorbed on the ice surface in the NOx mode and then converted into peroxynitrite, which is a powerful bactericidal species. In conclusion, a low-temperature plasma is a promising technique for cold chain disinfection, which is of great significance for ensuring people's health.

A Bayesian Method for Dynamic Origin-Destination Demand Estimation Synthesizing Multiple Sources of Data.

In this paper a Bayesian method is proposed to estimate dynamic origin-destination (O-D) demand. The proposed method can synthesize multiple sources of data collected by various sensors, including link counts, turning movements at intersections, flows, and travel times on partial paths. Time-dependent demand for each O-D pair at each departure time is assumed to satisfy the normal distribution. The connections among multiple sources of field data and O-D demands for all departure times are established by their variance-covariance matrices. Given the prior distribution of dynamic O-D demands, the posterior distribution is developed by updating the traffic count information. Then, based on the posterior distribution, both point estimation and the corresponding confidence intervals of O-D demand variables are estimated. Further, a stepwise algorithm that can avoid matrix inversion, in which traffic counts are updated one by one, is proposed. Finally, a numerical example is conducted on Nguyen-Dupuis network to demonstrate the effectiveness of the proposed Bayesian method and solution algorithm. Results show that the total O-D variance is decreasing with each added traffic count, implying that updating traffic counts reduces O-D demand uncertainty. Using the proposed method, both total error and source-specific errors between estimated and observed traffic counts decrease by iteration. Specifically, using 52 multiple sources of traffic counts, the relative errors of almost 50% traffic counts are less than 5%, the relative errors of 85% traffic counts are less than 10%, the total error between the estimated and "true" O-D demands is relatively small, and the O-D demand estimation accuracy can be improved by using more traffic counts. It concludes that the proposed Bayesian method can effectively synthesize multiple sources of data and estimate dynamic O-D demands with fine accuracy.

Identification of Key Genes Mutations Associated With the Radiosensitivity by Whole Exome Sequencing in Pancreatic Cancer.

BACKGROUND: Pancreatic cancer (PC) is one of the most lethal human cancers, and radiation therapy (RT) is an important treating option. Many patients diagnosed with PC do not achieve objective responses because of the existence of intrinsic and acquired radioresistance. Therefore, biomarkers, which predict radiotherapy benefit in PC, are eagerly needed to be identified. METHODS: Whole-exome sequencing of six pancreatic ductal adenocarcinoma patients (PDAC) (three with a good response and three with a poor response) who had received radical surgery and then radiotherapy has been performed as standard of care treatment. Somatic and germline variants and the mutational signatures were analyzed with bioinformatics tools and public databases. Functional enrichment and pathway-based protein-protein interaction analyses were utilized to address the possibly mechanism in radioresistance. MTT, LDH, and colony formation assay were applied to evaluate cell growth and colony formation ability. RESULTS: In the present study, somatic mutations located in 441 genes were detected to be radiosensitivity-related loci. Seventeen genes, including the Smad protein family members (SMAD3 and SMAD4), were identified to influence the radiosensitivity in PDAC. The SMAD3 and SMAD4 genes mutate differently between radiosensitive and radioresistant PDAC patients. Mutation of SMAD3 potentiates the effects of ionizing radiation (IR) on cell growth and colony formation in PDAC cells, whereas mutation of SMAD4 had the opposite effects. SMAD3 and SMAD4 regulate the radiosensitivity of PDAC, at least in part, by P21 and FOXO3a, respectively. CONCLUSIONS: These results indicate that mutations of SMAD3 and SMAD4 likely cause the difference of response to radiotherapy in PDAC, which might be considered as the biomarkers and potential targets for the radiotherapy of pancreatic cancer.

Safety and health perceptions of location-based augmented reality gaming app and their implications.

This study seeks to understand the potential safety and health implications of location-based augmented reality gaming apps ("LAR apps") through studying people perception of Pokémon GO, a popular LAR gaming app. These perceptions can affect app usage behavior, app retention rate, and market share which can be critical to policymakers and app developers. An online survey is conducted to capture the impacts of Pokémon GO regarding: (i) perceived risk of using the app and opinion of prohibiting its usage while driving and cycling, (ii) frequency of app-related distracted driving and cycling, (iii) frequency of app-induced driving and potentially unsafe driving behavior, (iv) average daily steps before and after using the app, and (v) perceived physical and mental health benefits. Multivariate binary probit models and random parameters ordered probit models were estimated to capture users' and non-users' characteristics that affect these perceptions, attitude, and behavior. The results suggest that LAR gaming apps can potentially promote physical activity by encouraging people to walk more, increase social interactions such as app-related discussions, but also contribute to increased app-related distracted driving and cycling, app-induced driving, and unsafe driving behavior. The study findings and insights can provide valuable feedback to legislators and LAR gaming app developers for designing policies and app mechanisms that can address the safety concerns of using such apps, and provide physical and mental health benefits to its users.

SP1-Mediated Upregulation of Long Noncoding RNA ZFAS1 Involved in Non-syndromic Cleft Lip and Palate via Inactivating WNT/ß-Catenin Signaling Pathway.

Non-syndromic cleft lip and palate (NSCLP) is one of the most common congenital malformations with multifactorial etiology. Although long non-coding RNAs (lncRNAs) have been implicated in the development of lip and palate, their roles in NSCLP are not fully elucidated. This study aimed to investigate how dysregulated lncRNAs contribute to NSCLP. Using lncRNA sequencing, bioinformatics analysis, and clinical tissue sample detection, we identified that lncRNA ZFAS1 was significantly upregulated in NSCLP. The upregulation of ZFAS1 mediated by SP1 transcription factor (SP1) inhibited expression levels of Wnt family member 4 (WNT4) through the binding with CCCTC-binding factor (CTCF), subsequently inactivating the WNT/ß-catenin signaling pathway, which has been reported to play a significant role on the development of lip and palate. Moreover, in vitro, the overexpression of ZFAS1 inhibited cell proliferation and migration in human oral keratinocytes and human umbilical cord mesenchymal stem cells (HUC-MSCs) and also repressed chondrogenic differentiation of HUC-MSCs. In vivo, ZFAS1 suppressed cell proliferation and numbers of chondrocyte in the zebrafish ethmoid plate. In summary, these results indicated that ZFAS1 may be involved in NSCLP by affecting cell proliferation, migration, and chondrogenic differentiation through inactivating the WNT/ß-catenin signaling pathway.

Exploring the impacts of travel-implied policy factors on COVID-19 spread within communities based on multi-source data interpretations.

The global Coronavirus Disease 2019 (COVID-19) pandemic has led to the implementation of social distancing measures such as work-from-home orders that have drastically changed people's travel-related behavior. As countries are easing up these measures and people are resuming their pre-pandemic activities, the second wave of COVID-19 is observed in many countries. This study proposes a Community Activity Score (CAS) based on inter-community traffic characteristics (in and out of community traffic volume and travel distance) to capture the current travel-related activity level compared to the pre-pandemic baseline and study its relationship with confirmed COVID-19 cases. Fourteen other travel-related factors belonging to five categories (Social Distancing Index, residents staying at home, travel frequency and distance, mobility trend, and out-of-county visitors) and three social distancing measures (stay-at-home order, face-covering order, and self-quarantine for out-of-county travels) are also considered to reflect the likelihood of exposure to the COVID-19. Considering that it usually takes days from exposure to confirming the infection, the exposure-to-confirm temporal delay between the time-varying travel-related factors and their impacts on the number of confirmed COVID-19 cases is considered in this study. Honolulu County in the State of Hawaii is used as a case study to evaluate the proposed CAS and other factors on confirmed COVID-19 cases with various temporal delays at a county-level. Negative Binomial models were chosen to study the impacts of travel-related factors and social distancing measures on COVID-19 cases. The case study results show that CAS and other factors are correlated with COVID-19 spread, and models that factor in the exposure-to-confirm temporal delay perform better in forecasting COVID-19 cases later. Policymakers can use the study's various findings and insights to evaluate the impacts of social distancing policies on travel and effectively allocate resources for the possible increase in confirmed COVID-19 cases.

Fast Screening and Primary Diagnosis of COVID-19 by ATR-FT-IR.

The outbreak of coronavirus disease 2019 (COVID-19) has led to substantial infections and mortality around the world. Fast screening and diagnosis are thus crucial for quick isolation and clinical intervention. In this work, we showed that attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FT-IR) can be a primary diagnostic tool for COVID-19 as a supplement to in-use techniques. It requires only a small volume (∼3 µL) of the serum sample and a shorter detection time (several minutes). The distinct spectral differences and the separability between normal control and COVID-19 were investigated using multivariate and statistical analysis. Results showed that ATR-FT-IR coupled with partial least squares discriminant analysis was effective to differentiate COVID-19 from normal controls and some common respiratory viral infections or inflammation, with the area under the receiver operating characteristic curve (AUROC) of 0.9561 (95% CI: 0.9071-0.9774). Several serum constituents including, but not just, antibodies and serum phospholipids could be reflected on the infrared spectra, serving as "chemical fingerprints" and accounting for good model performances.

Understanding the Interaction between Cyclists' Traffic Violations and Enforcement Strategies: An Evolutionary Game-Theoretic Analysis.

An evolutionary game-theoretic analysis method is developed in this study to understand the interactions between cyclists' traffic violations and the enforcement strategies. The evolutionary equilibrium stabilities were analysed under a fixed (FPS) and a dynamic penalty strategy (DPS). The simulation-based numerical experiments show that: (i) the proposed method can be used to study the interactions between traffic violations and the enforcement strategies; (ii) FPS and DPS can reduce cyclists' probability of committing traffic violations when the perceived traffic violations' relative benefit is less than the traffic violation penalty and the enforcement cost is less than the enforcement benefit, and using DPS can yield a stable enforcement outcome for law enforcement compared to using FPS; and (iii) strategy-related (penalty amount, enforcement effectiveness, and enforcement cost) and attitudinal factors (perceived relative benefit, relative public image cost, and cyclists' attitude towards risk) can affect the enforcement strategy's impacts on reducing cyclists' traffic violations.

Evaluating the Safety Risk of Rural Roadsides Using a Bayesian Network Method.

Evaluating the safety risk of rural roadsides is critical for achieving reasonable allocation of a limited budget and avoiding excessive installation of safety facilities. To assess the safety risk of rural roadsides when the crash data are unavailable or missing, this study proposed a Bayesian Network (BN) method that uses the experts' judgments on the conditional probability of different safety risk factors to evaluate the safety risk of rural roadsides. Eight factors were considered, including seven factors identified in the literature and a new factor named access point density. To validate the effectiveness of the proposed method, a case study was conducted using 19.42 km long road networks in the rural area of Nantong, China. By comparing the results of the proposed method and run-off-road (ROR) crash data from 2015⁻2016 in the study area, the road segments with higher safety risk levels identified by the proposed method were found to be statistically significantly correlated with higher crash severity based on the crash data. In addition, by comparing the respective results evaluated by eight factors and seven factors (a new factor removed), we also found that access point density significantly contributed to the safety risk of rural roadsides. These results show that the proposed method can be considered as a low-cost solution to evaluating the safety risk of rural roadsides with relatively high accuracy, especially for areas with large rural road networks and incomplete ROR crash data due to budget limitation, human errors, negligence, or inconsistent crash recordings.

Oncogenic TRIM31 confers gemcitabine resistance in pancreatic cancer via activating the NF-κB signaling pathway.

Background: Drug resistance is well known as a major obstacle for cancer recurrence and treatment failure, leading to poor survival in pancreatic cancer, which is a highly aggressive tumor. Identifying effective strategies to overcome drug resistance would have a significant clinical impact for patients with pancreatic cancer. Methods: The protein and mRNA expression of TRIM31 in pancreatic cancer cell lines and patient tissues were determined using Real-time PCR and Western blot, respectively. 89 human pancreatic cancer tissue samples were analyzed by IHC to investigate the association between TRIM31 expression and the clinicopathological characteristics of pancreatic cancer patients. Functional assays, such as MTT, FACS, and Tunel assay used to determine the oncogenic role of TRIM31 in human pancreatic cancer progression. Furthermore, western blotting and luciferase assay were used to determine the mechanism of TRIM31 promotes chemoresistance in pancreatic cancer cells. Results: The expression of TRIM31was markedly upregulated in pancreatic cancer cell lines and tissues, and high TRIM31 expression was associated with an aggressive phenotype and poor prognosis with pancreatic cancer patients. TRIM31 overexpression confers gemcitabine resistance on pancreatic cancer cells; however, inhibition of TRIM31 sensitized pancreatic cancer cell lines to gemcitabine cytotoxicity both in vitro and in vivo. Additionally, TRIM31 upregulated the levels of nuclear p65 by promoting K63-linked polyubiquitination of tumor necrosis factor receptor-associated factor 2 (TRAF2) and sustained the activation of nuclear transcription factor kappa B (NF-κB) in pancreatic cancer cells. Conclusions: Our findings provided evidence that TRIM31 is a potential therapeutic target for patients with pancreatic cancer. Targeting TRIM31 signaling may be a promising strategy to enhance gemcitabine response during pancreatic cancer chemo-resistance.