The Role of Interferon Regulatory Factor 1 in Regulating Microglial Activation and Retinal Inflammation.

Microglia are resident immune cells in the central nervous system (CNS). Microglial activation plays a prominent role in neuroinflammation and CNS diseases. However, the underlying mechanisms of microglial activation are not well understood. Here, we report that the transcription factor interferon regulatory factor 1 (IRF1) plays critical roles in microglial activation and retinal inflammation by regulating pro- and anti-inflammatory gene expression. IRF1 expression was upregulated in activated retinal microglia compared to those at the steady state. IRF1 knockout (KO) in BV2 microglia cells (BV2ΔIRF1) created by CRISPR/Cas9 genome-editing technique causes decreased microglia proliferation, migration, and phagocytosis. IRF1-KO decreased pro-inflammatory M1 marker gene expression induced by lipopolysaccharides (LPS), such as IL-6, COX-2, and CCL5, but increased anti-inflammatory M2 marker gene expression by IL-4/13, such as Arg-1, CD206, and TGF-ß. Compared to the wild-type cells, microglial-conditioned media (MCM) of activated BV2ΔIRF1 cell cultures reduced toxicity or death to several retinal cells, including mouse cone photoreceptor-like 661 W cells, rat retinal neuron precursor R28 cells, and human ARPE-19 cells. IRF1 knockdown by siRNA alleviated microglial activation and retinal inflammation induced by LPS in mice. Together, the findings suggest that IRF1 plays a vital role in regulating microglial activation and retinal inflammation and, therefore, may be targeted for treating inflammatory and degenerative retinal diseases.

Isolation and molecular characterization of MYB60 in Solanum lycopersicum.

Stomatal closure is a common adaptation response of plants to the onset of drought condition and its regulation is controlled by transcription factors. MYB60, a transcription factor involved in the regulation of light-induced stomatal opening, has been characterized in arabidopsis and grapevine. In this work, we studied the role of MYB60 homolog SIMYB60 in tomato plants. We identified, isolated, and sequenced the SIMYB60 coding sequence, and found domains and motifs characteristic of other MYB60 proteins. We determined that SlMYB60 is mainly expressed in leaves, and its expression is repressed by abscisic acid. Next, we isolated a putative promoter region containing regulatory elements responsible for guard cell expression and other putative regulatory elements related to ABA repression and vascular tissue expression. Protein localization assays demonstrated that SlMYB60 localizes to the nucleus. Finally, SlMYB60 is able to complement the mutant phenotype of atmyb60-1 in Arabidopsis. Together, these results indicate that SlMYB60 is the homologous gene in tomato and potentially offer a molecular target to improve crops.

Evolution of increased virulence is associated with decreased spite in the insect-pathogenic bacterium Xenorhabdus nematophila.

Disease virulence may be strongly influenced by social interactions among pathogens, both during the time course of an infection and evolutionarily. Here, we examine how spiteful bacteriocin production in the insect-pathogenic bacterium Xenorhabdus nematophila is evolutionarily linked to its virulence. We expected a negative correlation between virulence and spite owing to their inverse correlations with growth. We examined bacteriocin production and growth across 14 experimentally evolved lineages that show faster host-killing relative to their ancestral population. Consistent with expectations, these more virulent lineages showed reduced bacteriocin production and faster growth relative to the ancestor. Further, bacteriocin production was negatively correlated with growth across the examined lineages. These results strongly support an evolutionary trade-off between virulence and bacteriocin production and lend credence to the view that disease management can be improved by exploiting pathogen social interactions.

Potential Moderating Effects of Psychiatric Diagnosis and Symptom Severity on Subjective and Behavioral Responses to Reduced Nicotine Content Cigarettes.

INTRODUCTION: Given FDA's authority to implement a cigarette nicotine reduction policy, possible outcomes of this regulation must be examined, especially among those who may be most affected, such as those with comorbid psychiatric disorders. METHODS: In this secondary analysis of a multisite, randomized, clinical laboratory study, we used analyses of variance to examine the effects of nicotine dose (0.4, 2.4, 5.2, and 15.8 mg/g of tobacco), depressive and anxiety diagnoses (depression only, anxiety only, both, or neither), and depressive and anxiety symptom severity on cigarette choice, smoke exposure, craving, and withdrawal across three vulnerable populations: socioeconomically disadvantaged women of reproductive age, opioid-dependent individuals, and those with affective disorders (n = 169). RESULTS: Diagnosis and symptom severity largely had no effects on smoking choice, total puff volume, or CO boost. Significant main effects on craving and withdrawal were observed, with higher scores in those with both anxiety and depression diagnoses compared with depression alone or no diagnosis, and in those with more severe depressive symptoms (p's < .001). These factors did not interact with nicotine dose. Cigarettes with <15.8 mg/g nicotine were less reinforcing, decreased total puff volume, and produced significant but lower magnitude and shorter duration reductions in craving and withdrawal than higher doses (p's < .01). CONCLUSIONS: Reducing nicotine dose reduced measures of cigarette addiction potential, with little evidence of moderation by either psychiatric diagnosis or symptom severity, providing evidence that those with comorbid psychiatric disorders would respond to a nicotine reduction policy similarly to other smokers. IMPLICATIONS: Thus far, controlled studies in healthy populations of smokers have demonstrated that use of very low nicotine content cigarettes reduces cigarette use and dependence without resulting in compensatory smoking. These analyses extend those findings to a vulnerable population of interest, those with comorbid psychiatric disorders. Cigarettes with very low nicotine content were less reinforcing, decreased total puff volume, and produced significant but lower magnitude and shorter duration reductions in craving and withdrawal than higher doses. These nicotine dose effects did not interact with psychiatric diagnosis or mood symptom severity suggesting that smokers in this vulnerable population would respond to a nicotine reduction strategy similarly to other smokers.

On-farm NIR sensor for milk analysis: Exploitation of bias monitoring and bias correction.

Long-term studies have shown a bias drift over time in the prediction performance of near-infrared spectroscopy measurement systems. This bias drift generally requires extra laboratory reference measurements to detect and correct for this bias. Since these reference measurements are expensive and time consuming, there is a need for advanced methodologies for bias drift monitoring and correction without the need for taking extra samples. In this study, we propose and validate a method to monitor the bias drift and two methods to tackle it. The first method requires no extra measurements and uses a modified version of Partial Least Squares Regression to estimate and correct the bias. This method is based on the assumption that the mean concentration of the predicted component remains constant over time. The second method uses regular bulk milk measurements as a reference for bias correction. This method compares the measured concentrations of the bulk milk to the volume-weighted average concentrations of individual milk samples predicted by the sensor. Any difference between the actual and calculated bulk milk composition is then used to perform a bias correction on the predictions by the sensor system. The effectiveness of these methods to improve the component prediction was evaluated on data originating from a custom-built sensor that automatically measures the NIR reflectance and transmittance spectra of raw milk on the farm. We evaluate the practical use case where models for predicting the milk composition are trained upon installation of the sensor at the farm, and later used to predict the composition of subsequent samples over a period of more than 6 months. The effectiveness of the fully unsupervised method was confirmed when the mean concentration of the milk samples remained constant, while the effectiveness reduced when this was not the case. The bulk milk correction method was effective when all relevant samples for the component were measured by the sensor and included in the analyzed bulk milk, but is less effective when samples included in the bulk which are not measured by the sensor system. When the necessary conditions are met, these methods can be used to extend the lifetime of deployed prediction models by significantly reducing the bias on the predicted values.

Near-infrared spectra dataset of milk composition in transmittance mode.

Monitoring of milk composition can support several dimensions of dairy management such as identification of the health status of individual dairy cows and the safeguarding of dairy quality. The quantification of milk composition has been traditionally executed employing destructive chemical or laboratory Fourier-transform infrared (FTIR) spectroscopy analyses which can incur high costs and prolonged waiting times for continuous monitoring. Therefore, modern technology for milk composition quantification relies on non-destructive near-infrared (NIR) spectroscopy which is not invasive and can be performed on-farm, in real-time. The current dataset contains NIR spectral measurements in transmittance mode in the wavelength range from 960 nm to 1690 nm of 1224 individual raw milk samples, collected on-farm over an eight-week span in 2017, at the experimental dairy farm of the province of Antwerp, 'Hooibeekhoeve' (Geel, Belgium). For these spectral measurements, laboratory reference values corresponding to the three main components of raw milk (fat, protein and lactose), urea and somatic cell count (SCC) are included. This data has been used to build multivariate calibration models to predict the three milk compounds, as well as develop strategies to monitor the prediction performance of the calibration models.

Unsupervised dynamic orthogonal projection. An efficient approach to calibration transfer without standard samples.

Calibration transfer has been traditionally performed in the context of transferring models between instruments using standard samples. Recently, new methodologies and applications have shown that transfer techniques can be adopted to achieve calibration transfer between other types of domains, such as product form, variant or seasonality. In addition, to achieving a higher efficiency for calibration transfer, it is desirable to perform the transfer without the need for standard samples or new reference analyses. Therefore, we propose a method for unsupervised calibration transfer based on the orthogonalization for structural differences between domains. The method has been successfully applied to one simulated dataset and two real datasets. In the studied cases, the proposed methodology allowed to achieve a successful transfer of calibration models and enabled the interpretation of the interferences responsible for the degradation of the original calibration models when transferred to the new domain.

Postoperative morbidity and mortality in total joint arthroplasty: Exploring the limits of early discharge.

INTRODUCTION: In order to enhance cost-effectiveness, shorter hospital stays have been adopted following hip or knee replacement surgery. This study seeks to describe the incidence of morbidity and mortality, five days after patients were taken to surgery with an expected hospital stay of four days. METHODS: Utilizing an Institutional Joint Replacement database, a descriptive study was carried out using a retrospective cohort of 1233 procedures in 1100 patients between 2012 and 2016. These were followed up for three months to evaluate morbidity and mortality in the postoperative period. RESULTS: Complications were classified as minor or major (these were defined as any adverse event that can threaten a patient's life or had the potential to result in readmission). Of the cohort, 18 (1.5%) patient procedures presented one or more major complications. On the first postoperative day 3 major complications occurred (including one death). On the second and third day, 4 major complications were registered each day. On the fourth day after surgery, there were no major complications. On the fifth day 1 major complication was identified. After patient discharge there were 6 major complications reported. DISCUSSION: The balance between early discharge and out-of-hospital morbidity as well as the frequency of hospital readmission must be the basis to determine whether a patient's hospital stay should be reduced. According to our results, it seems to be safe to shorten hospital stay in young and healthy patients. Furthermore, only orthopedic teams that have minimal rates of outpatient complications and adhere to high standards of care should consider reducing hospital stay.

The effect of national protest in Ecuador on PM pollution.

Particulate matter (PM) accounts for millions of premature deaths in the human population every year. Due to social and economic inequality, growing human dissatisfaction manifests in waves of strikes and protests all over the world, causing paralysis of institutions, services and circulation of transport. In this study, we aim to investigate air quality in Ecuador during the national protest of 2019, by studying the evolution of PM2.5 (PM ≤ 2.5 µm) concentrations in Ecuador and its capital city Quito using ground based and satellite data. Apart from analyzing the PM2.5 evolution over time to trace the pollution changes, we employ machine learning techniques to estimate these changes relative to the business-as-usual pollution scenario. In addition, we present a chemical analysis of plant samples from an urban park housing the strike. Positive impact on regional air quality was detected for Ecuador, and an overall - 10.75 ± 17.74% reduction of particulate pollution in the capital during the protest. However, barricade burning PM peaks may contribute to a release of harmful heavy metals (tire manufacture components such as Co, Cr, Zn, Al, Fe, Pb, Mg, Ba and Cu), which might be of short- and long-term health concerns.

Response to Reduced Nicotine Content in Vulnerable Populations: Effect of Menthol Status.

OBJECTIVES: In this study, we investigated potential effects of being a menthol smoker on response to reduced nicotine content (RNC) cigarettes in smokers especially vulnerable to smoking. METHOD: Participants were 169 smokers (61 menthol and 108 non-menthol smokers) with comorbid mental illness, substance use disorder, or socioeconomic disadvantage. Participants completed a double-blind study assessing addiction potential, withdrawal/craving, and compensatory smoking across 4 research cigarettes varying in nicotine content from very low levels to commercial levels (0.4, 2.4, 5.2, 15.8mg/g of tobacco). Repeated measures analysis of variance was used to examine potential moderating effects of menthol status. RESULTS: Statistically significant effects of nicotine dose were noted across measures, with higher doses producing greater economic demand and relief from withdrawal/craving. The relationships between nicotine dose and response to RNC cigarettes do not differ by menthol status. CONCLUSIONS: Results of this study suggest menthol does not have a differential impact on response to RNC cigarettes across measures of economic demand, withdrawal/craving, or smoking topography. These results suggest that any potential beneficial effects of RNC cigarettes should extend to menthol smokers including those especially vulnerable to smoking.

Particulate matter air pollution from the city of Quito, Ecuador, activates inflammatory signaling pathways in vitro.

Automobile traffic, industrial processes and natural phenomena cause notable air pollution, including gaseous and particulate contaminants, in urban centers. Exposure to particulate matter (PM) air pollution affects human health, and has been linked to respiratory, cardiovascular and neurological diseases. The mechanisms underlying inflammation in these diverse diseases, and to what extent health effects are different for PM obtained from different sources or locations, are still unclear. This study investigated the in vitro toxicity of ambient course (PM10) and fine (PM2.5) particulate matter collected at seven sites in the urban and periurban zones of Quito, Ecuador. Material from all sites was capable of activating TLR2 and TLR4 signaling pathways, with differences in the activation related to particle size. Additionally, airborne particulate matter from Quito is an effective activator of the NLRP3 inflammasome.