Avian leukosis virus usurps the cellular SERBP1 protein to enhance its transcription and promote productive infections in avian cells.

Avian leukosis virus subgroup K (ALV-K) is composed of newly emerging isolates, which cluster separately from the well-characterized subgroups A, B, C, D, E, and J in sequence analysis, and exhibits a specific host range and a unique pattern of superinfection interference. Avian leukosis virus subgroup K replicate more slowly in avian cells than other ALV strains, leading to escaped detection during ALV eradication, but the underlying mechanism are largely unknown. In our previous study, we have reported that JS11C1 and most of other suspected ALV-K strains possessed unique mutations in the U3 region. Here, we selected 5 mutations in some important transcriptional regulation elements to explore the possible factor contributing for the lower activity of LTR, including CA-TG mutation in the CAAT box, 21 nt deletion in the CAAT box, A-G and A-T mutations in the CArG boxes, 11 nt insertion in the PRE boxes, and C-T mutation in the TATA box. On the basis of infectious clone of JS11C1, we demonstrated that the 11 nt fragment in the PRE boxes was associated with the transcription activity of LTR, the enhancer ability of U3, and the replication capacity of the virus. Notably, we determined the differential U3-protein interaction profile of ALVs and found that the 11 nt fragment specifically binds to cellular SERPINE1 mRNA binding protein 1 (SERBP1) to increase the LTR activity and enhance virus replication. Collectively, these findings reveal that a 11 nt fragment in the U3 gene contributed to its binding ability to the cellular SERBP1 to enhance its transcription and the infectious virus productions in avian cells. This study highlighted the vital role of host factor in retrovirus replication and thus provides a new perspective to elucidate the interaction between retrovirus and its host and a molecular basis to develop efficient strategies against retroviruses.

Molecular Mechanisms of Ferroptosis and Their Involvement in Acute Kidney Injury.

Ferroptosis is a novel way of regulating cell death, which occurs in a process that is closely linked to intracellular iron metabolism, lipid metabolism, amino acid metabolism, and multiple signaling pathways. The latest research shows that ferroptosis plays a key role in the pathogenesis of acute kidney injury (AKI). Ferroptosis may be an important target for treating AKI caused by various reasons, such as ischemia-reperfusion injury, rhabdomyolysis syndrome, sepsis, and nephrotoxic drugs. This paper provides a review on the regulatory mechanisms of ferroptosis and its role in AKI, which may help to provide new research ideas for the treatment of AKI and future research.

SERS-based biosensor for detection of f-PSA%: Implications for the diagnosis of prostate cancer.

In diagnosing prostate cancer and distinguishing it from other prostate diseases, the ratio of the concentration of free prostate-specific antigen (f-PSA) to total prostate-specific antigen (t-PSA), i.e., (f-PSA%) is more accurate than the concentration of t-PSA alone. Immunoassay based on surface-enhanced Raman scattering (SERS) frequency shift has been proven to be particularly suitable for detecting large biomolecules with high reproducibility. Along similar lines, the present study developed a SERS-based biosensor that simultaneously detects t-PSA and f-PSA. The 4-mercaptobenzoic acid (MBA) on the immunocapture substrate is coupled to the t-PSA antibody through the carboxyl group, and the combination of t-PSA induces the Raman frequency shifts of MBA. The immunocolloidal gold attached with f-PSA antibodies selectively capture the f-PSA that immobilized on the MBA-modified SERS substrates, allowing for f-PSA quantification according to the SERS intensities of the 5, 5'-Dithiobis (succinimidyl-2-nitrobenzoate) (DSNB) probe. The results show that f-PSA and t-PSA have good linear response in the concentration scale of 0.1-20 ng/mL, and 1-200 ng/mL, respectively. The biosensor combines Raman frequency shifts and intensities, which greatly simplifies traditional procedures for f-PSA% detection. All the results demonstrated the great potential of the proposed biosensor in highly reproducible and accurate diagnosis of prostate cancers.

A robust performance evaluation method based on interval evidential reasoning approach under uncertainty.

Performance evaluation (PE) is an important part of equipment health management. If the monitoring information of the equipment is interfered, the evaluation results may be erroneous. A robust performance evaluation (RPE) method is proposed to solve this problem. The performance evaluation results are obtained by distinguishing the cases of single evidence with interference and two evidence with interference, and a robustness measurement based on interval similarity is proposed. To improve the accuracy of the evaluation results, the referential values in the IER evaluation model are optimized. The robustness thresholds of the input indexes are obtained under the satisfaction of the robustness constraints. If the interference value of the input index is within the thresholds, the deviation between the evaluation results using monitoring information with interference and those using monitoring information without interference is small. Finally, the proposed method is applied to a type of electric servo mechanism performance evaluation, and the case shows the validity of the RPE method.

Fault Diagnosis for Complex Equipment Based on Belief Rule Base with Adaptive Nonlinear Membership Function.

Fault diagnosis of complex equipment has become a hot field in recent years. Due to excellent uncertainty processing capability and small sample problem modeling capability, belief rule base (BRB) has been widely used in the fault diagnosis. However, previous BRB models almost did not consider the diverse distributions of observation data which may reduce diagnostic accuracy. In this paper, a new fault diagnosis model based on BRB is proposed. Considering that the previous triangular membership function cannot address the diverse distribution of observation data, a new nonlinear membership function is proposed to transform the input information. Then, since the model parameters initially determined by experts are inaccurate, a new parameter optimization model with the parameters of the nonlinear membership function is proposed and driven by the gradient descent method to prevent the expert knowledge from being destroyed. A fault diagnosis case of laser gyro is used to verify the validity of the proposed model. In the case study, the diagnosis accuracy of the new BRB-based fault diagnosis model reached 95.56%, which shows better fault diagnosis performance than other methods.

Co-Immobilization of GOD & HRP on Y-Shaped DNA Scaffold and the Regulation of Inter-Enzyme Distance.

In multienzymes cascade reaction, the inter-enzyme spacing is supposed to be a factor affecting the cascade activity. Here, a simple and efficient Y-shaped DNA scaffold is assembled using two partially complementary DNA single strands on magnetic microspheres, which is used to coimmobilize glucose oxidase (GOD) and horseradish peroxidase (HRP). As a result, on poly(vinyl acetate) magnetic microspheres (PVAC), GOD/HRP-DNA@PVAC multienzyme system is obtained, which can locate GOD and HRP accurately and control the inter-enzyme distance precisely. The distance between GOD and HRP is regulated by changing the length of DNA strand. It showed that the cascade activity is significantly distance-dependent. Moreover, the inter-enzyme spacing is not the closer the better, and too short distance would generate steric hindrance between enzymes. The cascade activity reached the maximum value of 967 U mg-1 at 13.6 nm, which is 3.5 times higher than that of free enzymes. This is ascribed to the formation of substrate channeling.

Effects of starters with different NDF/starch ratio on rumen fermentation parameters and rumen microorganisms in lambs.

Starch and NDF are the main components in the diets of ruminants worldwide and are the main energy source for rumen microorganisms and hosts. The purpose of this study was to investigate the effects of different NDF/starch ratios on rumen fermentation parameters, rumen development and rumen microbes in lambs and to predict the function of rumen microbes by metagenomic techniques. In this study, 30 lambs with birth weights of (3.0 ± 0.5) kg were selected. The lambs of Hu sheep were randomly divided into two groups, fed starter with an NDF/starch ratio of 0.5 (group A) or 1.0 (group C). Samples of the rumen tissue and contents were collected after slaughter. The results showed that the ADG and ADFI of group A were significantly higher than those of group C (P < 0.05), but there was no significant difference in the FCR (P > 0.05). Therefore, from the perspective of feed-related economic benefits, group C showed greater economic value; the A/P of group C was significantly lower than that of group A (0.05 < P < 0.1), and the TVFA showed no significant difference (P > 0.05); The lengths of the rumen papillae of group C was significantly higher than that of group A (0.05 < P < 0.1). There was no significant difference in the abundance of the top 10 species at the phylum level and genus level (P > 0.05). CAZymes gene enrichment was observed in the rumen microbial community of lambs in group C (P < 0.05). In conclusion, group C, fed with starter with a higher NDF/starch ratio, had a higher feeding value. This study provides comprehensive insights into the composition of NDF and starch in lamb starter.

Sulfite altered permanganate effects on acetate-enriched short-chain fatty acids production during sludge anaerobic fermentation.

Anaerobic fermentation is a promising method for waste activated sludge (WAS) treatment, but ineffective solubilization and hydrolysis limit its application. The current study examined the function of sodium sulfite (SDS) in potassium permanganate (PP)-conditioned WAS fermentation for short-chain fatty acids (SCFAs) biosynthesis. The presence of SDS in the PP system (PP/SDS) reduced the positive effects of PP on total SCFAs yield (2755 versus 3471 mg COD/L), while effectively increasing the proportion of acetate (from 41 to 81 %). Not only did SDS decrease the promoting effects of PP on WAS solubilization and hydrolysis efficiency by 5-42 %, it also shifted microbial metabolic pathways to favor acetate production. In addition, the amino acid metabolism with acetate as end product was enhanced. Moreover, PP/SDS inhibited methanogenesis, resulting in an accumulation of acetate in high quantities. Thus, the current study a provided insight and direction for effective WAS treatment with acetate-enriched SCFAs production.

A novel optimization method for belief rule base expert system with activation rate.

Although the belief rule base (BRB) expert system has many advantages, such as the effective use of semi-quantitative information, objective description of uncertainty, and efficient nonlinear modeling capability, it is always limited by the problem of combinatorial explosion. The main reason is that the optimization of a BRB with many rules will consume many computing resources, which makes it unable to meet the real-time requirements in some complex systems. Another reason is that the optimization process will destroy the interpretability of those parameters that belong to the inadequately activated rules given by experts. To solve these problems, a novel optimization method for BRB is proposed in this paper. Through the activation rate, the rules that have never been activated or inadequately activated are pruned during the optimization process. Furthermore, even if there is a complete data set and all rules are activated, the activation rate can also be used in the parallel optimization process of the BRB expert system, where the training data set is divided into some subprocesses. The proposed method effectively solves the combinatorial explosion problem of BRB and can make full use of quantitative data without destroying the original interpretability provided by experts. Case studies prove the advantages and effectiveness of the proposed method, which greatly expands the application fields of the BRB expert system.

A New Evidential Reasoning Rule Considering Interval Uncertainty and Perturbation.

The evidential reasoning (ER) rule has been widely applied in the multiple attribute decision making (MADM), which makes the decision-making process transparent and credible by using a belief structure. To improve the ability of the ER rule in dealing with the interval uncertainty, a new interval ER (IER) rule is proposed in this article. The interval uncertainty is described as the interval grade in the new frame of discernment (FoD) to model the local ignorance. It is proved that the IER rule is a generalization of the ER rule. To study the influence of perturbation on the IER rule, the perturbation is first introduced to the belief structure, and the perturbation analysis (PA) is conducted for the IER rule. An optimization model is established to estimate the perturbation threshold, which can measure the effectiveness of the inference result under perturbation. Two numerical examples and a case study are carried out, respectively, to show the implementation process of the proposed IER rule and validate its effectiveness in different decision-making scenarios.

Performance Evaluation of Complex Equipment Considering Resume Information.

It is of great significance to obtain the performance state of complex equipment to protect equipment and maintain its normal operation. The majority of the performance evaluation methods are based on test data, but resume information is not considered. With its wide applicability and completeness, the resume information can be used in the comprehensive evaluation of equipment in various non-testing situations. By incorporating resume information into the performance evaluation of complex equipment, the flexible use of test data and resume information can result in a more comprehensive and accurate evaluation. Therefore, this paper focuses on the evaluation method of complex equipment performance based on evidential reasoning (ER) considering resume information. In order to unify the test data and resume information in the same framework, a novel method is proposed to transform them into the ER-based performance evaluation. On this basis, according to the index types, different reliability calculation methods are put forward, with one being based on the first-order fitting coefficient of variation, and the other being based on average time to failure; the index weight is analyzed based on the method of expert weight construction. Then, the transformed information with reliability and weight are fused by the ER rule. Finally, a performance evaluation case of a certain inertial measurement unit (IMU) is conducted to verify the effectiveness of the proposed method.

Label-Free Surface-Enhanced Raman Spectroscopic Analysis of Proteins: Advances and Applications.

Surface-enhanced Raman spectroscopy (SERS) is powerful for structural characterization of biomolecules under physiological condition. Owing to its high sensitivity and selectivity, SERS is useful for probing intrinsic structural information of proteins and is attracting increasing attention in biophysics, bioanalytical chemistry, and biomedicine. This review starts with a brief introduction of SERS theories and SERS methodology of protein structural characterization. SERS-active materials, related synthetic approaches, and strategies for protein-material assemblies are outlined and discussed, followed by detailed discussion of SERS spectroscopy of proteins with and without cofactors. Recent applications and advances of protein SERS in biomarker detection, cell analysis, and pathogen discrimination are then highlighted, and the spectral reproducibility and limitations are critically discussed. The review ends with a conclusion and a discussion of current challenges and perspectives of promising directions.

Effect of Cocaine on Potassium-Evoked Release of Glutamate From Fetal Rat Brain Synaptosomes.

Introduction Cocaine use during pregnancy can affect fetal brain development. A fetal brain injury could happen from the direct effect of cocaine on the developing brain or from the reduction of placental perfusion from vasoconstriction, which may lead to hypoxia-ischemia. A potential mechanism for brain injury could be due to a neurotransmitter imbalance within the brain, especially glutamate. In an immature rat brain synaptosome model, we explored the additive effect of cocaine alone on glutamate release and the effect of cocaine combined with simulated hypoxic depolarization using potassium as a surrogate. Method Rat pups' brains were dissected and placed on a chilled petri dish. They then entered the experimental protocol. The suspended synaptosomes were divided equally into four experimental groups (control, high potassium "surrogate to hypoxic stimulation," cocaine, and cocaine + high K). Reversed-phase high-performance liquid chromatography analyzed glutamate with fluorescent detection Results The glutamate level was lowest in the cocaine-only group, with a level of 1.96 × 104, compared to the control and high potassium group. However, combining cocaine with high potassium seemed to generate a synergistic effect, achieving the highest glutamate level of all groups with a value of 5.31 × 104. Post hoc Conover's test for multiple pairwise-comparison between groups was done. In comparing various solutions to control, we did not find a statistically significant difference with the cocaine-only solution with a p-value of 0.074. Also, on comparing various other solutions to each other, there was no statistically significant difference between cocaine vs. cocaine + high potassium a p-value of 0.074. Conclusion Our data support the conclusion that cocaine alone does not induce glutamate release from fetal rat brain synaptosomes. Exposure to high potassium does lead to glutamate release. However, cocaine greatly enhances glutamate release in the presence of high potassium levels. This could explain how cocaine affects brain maturation during pregnancy with a low oxygen tension environment in the placenta. This hypothesis should be tested in vivo.

Design on intermittent ventilation strategy for radon removal in underground space.

Ventilation to reduce radon was one of the most widely used, important, and effective means to reduce radon concentration in underground engineering. The largest energy consumption of underground buildings was the building ventilation system. Taking the radon migration process in a room as an example, this paper built a numerical model that accounted for the mechanism of radon production, exhalation, and diffusion process, by proposing a novel intermittent ventilation strategy to mitigate radon concentration in underground space. Three ventilation strategies (no ventilation, continuous ventilation, and intermittent ventilation) were compared under various wind speeds and fresh air ratios. Under the same safe duration of radon concentration, when intermittent ventilation was operated with the same wind speed, the startup time was reduced by 79.4%, 86.0%, 90.8%, 92.8%, 91.25%, with compared with continuous ventilation. The higher the fresh air ratio, the lower the radon concentration limit, and the faster the dynamic equilibrium state of radon concentration will be reached. During intermittent ventilation, reducing the fresh air ratio can greatly increase the recovery and utilization of the return air heat, thereby reducing the power of the air conditioning unit. Considering the comprehensive energy-saving benefits of the ventilation system, the appropriate intermittent ventilation plan should be made to meet radon reduction requirements in the range of low wind speed. If low wind speed was selected, there existed advantages of low ventilation noise and more comfortable, as well.

Innovative Application of SERS in Food Quality and Safety: A Brief Review of Recent Trends.

Innovative application of surface-enhanced Raman scattering (SERS) for rapid and nondestructive analyses has been gaining increasing attention for food safety and quality. SERS is based on inelastic scattering enhancement from molecules located near nanostructured metallic surfaces and has many advantages, including ultrasensitive detection and simple protocols. Current SERS-based quality analysis contains composition and structural information that can be used to establish an electronic file of the food samples for subsequent reference and traceability. SERS is a promising technique for the detection of chemical, biological, and harmful metal contaminants, as well as for food poisoning, and allergen identification using label-free or label-based methods, based on metals and semiconductors as substrates. Recognition elements, including immunosensors, aptasensors, or molecularly imprinted polymers, can be linked to SERS tags to specifically identify targeted contaminants and perform authenticity analysis. Herein, we highlight recent studies on SERS-based quality and safety analysis for different foods categories spanning the whole food chain, 'from farm to table' and processing, genetically modified food, and novel foods. Moreover, SERS detection is a potential tool that ensures food safety in an easy, rapid, reliable, and nondestructive manner during the COVID-19 pandemic.

Spammer detection using multi-classifier information fusion based on evidential reasoning rule.

Spammer detection is essentially a process of judging the authenticity of users, and thus can be regarded as a classification problem. In order to improve the classification performance, multi-classifier information fusion is usually used to realize the automatic detection of spammers by utilizing the information from multiple classifiers. However, the existing fusion strategies do not reasonably take the uncertainty from the results of different classifiers (views) into account, and the relative importance and reliability of each classifier are not strictly distinguished. Therefore, in order to detect spammers effectively, this paper develops a novel multi-classifier information fusion model based on the evidential reasoning (ER) rule. Firstly, according to the user's characterization strategy, the base classifiers are constructed through the profile-based, content-based and behavior-based. Then, the idea of multi-classifier fusion is combined with the ER rule, and the results of base classifiers are aggregated by considering their weights and reliabilities. Extensive experimental results on the real-world dataset verify the effectiveness of the proposed model.

Identification of novel biomarkers differentially expressed between African-American and Caucasian-American prostate cancer patients.

Prostate cancer (PCa) incidence and mortality rate vary among racial and ethnic groups with the highest occurrence in African American (AA) men who have mortality rates twice that of Caucasians (CA). In this study, we focused on differential expression of proteins in AA prostate cancer compared to CA using Protein Pathway Array Analysis (PPAA), in order to identify protein biomarkers associated with PCa racial disparity. Fresh frozen prostate samples (n=90) obtained from radical prostatectomy specimens with PCa, including 25 AA tumor, 21 AA benign, 23 CA tumor, 21 CA benign samples were analyzed. A total of 286 proteins and phosphoproteins were assessed using PPAA. By PPAA analysis, 33 proteins were found to be significantly differentially expressed in tumor tissue (n=48, including both CA and AA) in comparison to benign tissue (n=42). We further compared protein expression levels between AA and CA tumor groups and found that 3 proteins were differentially expressed (P<0.05 and q<5%). Aurora was found to be significantly increased in AA tumors, while Cyclin D1 and HNF-3a proteins were downregulated in AA tumors. Predicted risk score was significantly different between AA and CA ethnic groups using logistic regression analysis. In conclusion, we identified Aurora, Cyclin D1 and HNF-3a proteins as being differentially expressed between AA and CA in PCa tissue. Our study suggests that these proteins might be involved in different pathways that lead to aggressive PCa behavior in AA patients, potentially serving as biomarkers for the PCa racial disparity.

Nanoparticle-enhanced radiotherapy synergizes with PD-L1 blockade to limit post-surgical cancer recurrence and metastasis.

Cancer recurrence after surgical resection (SR) is a considerable challenge, and the biological effect of SR on the tumor microenvironment (TME) that is pivotal in determining postsurgical treatment efficacy remains poorly understood. Here, with an experimental model, we demonstrate that the genomic landscape shaped by SR creates an immunosuppressive milieu characterized by hypoxia and high-influx of myeloid cells, fostering cancer progression and hindering PD-L1 blockade therapy. To address this issue, we engineer a radio-immunostimulant nanomedicine (IPI549@HMP) capable of targeting myeloid cells, and catalyzing endogenous H2O2 into O2 to achieve hypoxia-relieved radiotherapy (RT). The enhanced RT-mediated immunogenic effect results in postsurgical TME reprogramming and increased susceptibility to anti-PD-L1 therapy, which can suppress/eradicate locally residual and distant tumors, and elicits strong immune memory effects to resist tumor rechallenge. Our radioimmunotherapy points to a simple and effective therapeutic intervention against postsurgical cancer recurrence and metastasis.

The Burnout Epidemic Within A Viral Pandemic: Impact of a Wellness Initiative.

Background: Anesthesiologists are at high risk of developing burnout, a condition which can lead to many deleterious effects for the physician, and far-reaching effects on their patients and hospital systems. The COVID-19 pandemic has presented new challenges that have further exacerbated the risk of burnout in anesthesiologists. It is critical to develop effective strategies to promote well-being and decrease burnout for physicians in this specialty. The purpose of this observational study was to evaluate the impact of a Physician Well-Being Initiative on distress and well-being in anesthesiologists. It was hypothesized that the wellness intervention would promote an improvement in well-being scores. Methods: The Physician Well-Being Initiative was launched in August 2019 in the Department of Anesthesiology, Pain Management and Perioperative Medicine at Henry Ford Hospital in Detroit, Michigan. The Physician Well-Being Initiative was designed to address several of the key factors that improve physician wellness, including 1) a sense of autonomy; 2) positive view of leadership; and 3) flexible schedule opportunities. To assess the impact of the Physician Well-Being Initiative on the well-being and distress scores of participating anesthesiologists, the physicians were emailed the validated Well-Being Index survey at baseline and 3, 6 and 12 months. The Well-Being Index evaluates multiple items of distress in the healthcare setting. The sample size was limited to the 54 anesthesiologists at Henry Ford Hospital. Results: Forty-four of the 54 anesthesiologists completed the baseline questionnaire. A total of 44 physicians answered the questionnaire at baseline, with more male than female physicians (35 males and 7 females) and the majority (17/44) in practice for 5-10 years. Thirty-two physicians completed the survey at 3 and 6 months, and 31 physicians at 12 months after the launch of the Physician Well-Being Initiative. Twenty-one physicians completed the questionnaire at all 4 time points. Although the COVID-19 pandemic started shortly after the 6-month surveys were submitted, results indicated that there was a 0.05 decrease in the Well-Being Index sum score for every 1-month of time (coefficient -0.05, 95% CI -0.01, -0.08, P = 0.013). This study shows that, with the wellness initiative in place, the department was able to maintain and potentially even reduce physician distress despite the concurrent onset of the pandemic. Conclusions: Following the launch of a sustained wellness initiative, this study demonstrates that physician wellness improved with time. This suggests that it takes time for a wellness initiative to have an effect on well-being and distress in anesthesiologists.

The Relationship Between Work Engagement and Job Performance: Psychological Capital as a Moderating Factor.

Based on the job demands-resources model, this study explored the relationships of work engagement, job performance and psychological capital in industry employees. A total of 399 IT programmers were recruited and completed the work engagement scale, knowledge employee job performance scale and psychological capital questionnaire. The results showed that: (1) There is a relationship between work engagement and job performance, which may not be linear but inverted U-shaped, and (2) psychological capital plays a moderating role in the inverted U-shaped relationship between work engagement and job performance.