UID-Dual Transcriptome Sequencing Analysis of the Molecular Interactions between Streptococcus agalactiae ATCC 27956 and Mammary Epithelial Cells.

Streptococcus agalactiae ATCC 27956 is a highly contagious Gram-positive bacterium that causes mastitis, has a high infectivity for mammary epithelial cells, and becomes challenging to treat. However, the molecular interactions between it and mammary epithelial cells remain poorly understood. This study analyzed differential gene expression in mammary epithelial cells with varying levels of S. agalactiae infection using UID-Dual transcriptome sequencing and bioinformatics tools. This study identified 211 differentially expressed mRNAs (DEmRNAs) and 452 differentially expressed lncRNAs (DElncRNAs) in host cells, primarily enriched in anti-inflammatory responses, immune responses, and cancer-related processes. Additionally, 854 pathogen differentially expressed mRNAs (pDEmRNAs) were identified, mainly enriched in protein metabolism, gene expression, and biosynthesis processes. Mammary epithelial cells activate pathways, such as the ERK1/2 pathway, to produce reactive oxygen species (ROS) to eliminate bacteria. The bacteria disrupt the host's innate immune mechanisms by interfering with the alternative splicing processes of mammary epithelial cells. Specifically, the bacterial genes of tsf, prfB, and infC can interfere with lncRNAs targeting RUNX1 and BCL2L11 in mammary epithelial cells, affecting the alternative splicing of target genes and altering normal molecular regulation.

Integrated Metabolomics and Metagenomics Unveiled Biomarkers of Antioxidant Potential in Fermented Brewer's Grains.

About one-third of the global food supply is wasted. Brewers' spent grain (BSG), being produced in enormous amounts by the brewery industry, possesses an eminence nutritional profile, yet its recycling is often neglected for multiple reasons. We employed integrated metagenomics and metabolomics techniques to assess the effects of enzyme treatments and Lactobacillus fermentation on the antioxidant capacity of BSG. The biotreated BSG revealed improved antioxidant capability, as evidenced by significantly increased (p < 0.05) radical scavenging activity and flavonoid and polyphenol content. Untargeted metabolomics revealed that Lactobacillus fermentation led to the prominent synthesis (p < 0.05) of 15 novel antioxidant peptides, as well as significantly higher (p < 0.05) enrichment of isoflavonoid and phenylpropanoid biosynthesis pathways. The correlation analysis demonstrated that Lactiplantibacillus plantarum exhibited strong correlation (p < 0.05) with aucubin and carbohydrate-active enzymes, namely, glycoside hydrolases 25, glycosyl transferases 5, and carbohydrate esterases 9. The fermented BSG has potential applications in the food industry as a culture medium, a functional food component for human consumption, and a bioactive feed ingredient for animals.

Yolov8n-FADS: A Study for Enhancing Miners' Helmet Detection Accuracy in Complex Underground Environments.

A new algorithm, Yolov8n-FADS, has been proposed with the aim of improving the accuracy of miners' helmet detection algorithms in complex underground environments. By replacing the head part with Attentional Sequence Fusion (ASF) and introducing the P2 detection layer, the ASF-P2 structure is able to comprehensively extract the global and local feature information of the image, and the improvement in the backbone part is able to capture the spatially sparsely distributed features more efficiently, which improves the model's ability to perceive complex patterns. The improved detection head, SEAMHead by the SEAM module, can handle occlusion more effectively. The Focal Loss module can improve the model's ability to detect rare target categories by adjusting the weights of positive and negative samples. This study shows that compared with the original model, the improved model has 29% memory compression, a 36.7% reduction in the amount of parameters, and a 4.9% improvement in the detection accuracy, which can effectively improve the detection accuracy of underground helmet wearers, reduce the workload of underground video surveillance personnel, and improve the monitoring efficiency.

Hypervirulent Klebsiella pneumoniae Mediated Hepatic Infarction Septic Shock After Rectal Cancer Surgery: A Case Report.

The liver receives blood from both the hepatic artery and portal vein. Hepatic infarction is rare in clinical practice as both the hepatic artery and portal vein can supply blood to the liver. Here, we reported a case of a 75-year-old man who underwent radical laparoscopic surgery for rectal cancer and subsequently developed hepatic infarction. The patient experienced severe infection, as well as circulatory and respiratory failure on the third day after surgery. The patient presented with high fever, chest tightness, shortness of breath, decreased blood oxygen saturation and blood pressure. The leukocyte count decreased from 8.10 × 10^9/L to 1.75 × 10^9/L. Procalcitonin (PCT) levels increased from 1.02 ng/mL to 67.14 ng/mL, and eventually reaching levels over 200 ng/mL. Enhanced abdominal computed tomography (CT) confirmed the presence of hepatic infarction, but no thrombosis was observed in the hepatic artery or portal vein. Metagenomic next-generation sequencing (mNGS) identified hypervirulent Klebsiella pneumoniae (hvKp) in the patient's blood and ascites, one day earlier than the detection results using traditional culture methods. The patient was diagnosed with hepatic infarction combined with septic shock caused by hvKp. This case emphasizes that in the high-risk group of thrombosis, infection can trigger exacerbated hepatic infarction events, particularly in cases after surgical procedures. For severely ill patients with infectious diseases who are admitted to the ICU with worsening symptoms, it is important to collect appropriate samples and send them for pathogen detection using mNGS in a timely manner. This may aid in early intervention and improve clinical outcomes.

Unmasking the sky: high-resolution PM2.5 prediction in Texas using machine learning techniques.

BACKGROUND: Although PM2.5 (fine particulate matter with an aerodynamic diameter less than 2.5 µm) is an air pollutant of great concern in Texas, limited regulatory monitors pose a significant challenge for decision-making and environmental studies. OBJECTIVE: This study aimed to predict PM2.5 concentrations at a fine spatial scale on a daily basis by using novel machine learning approaches and incorporating satellite-derived Aerosol Optical Depth (AOD) and a variety of weather and land use variables. METHODS: We compiled a comprehensive dataset in Texas from 2013 to 2017, including ground-level PM2.5 concentrations from regulatory monitors; AOD values at 1-km resolution based on images retrieved from the MODIS satellite; and weather, land-use, population density, among others. We built predictive models for each year separately to estimate PM2.5 concentrations using two machine learning approaches called gradient boosted trees and random forest. We evaluated the model prediction performance using in-sample and out-of-sample validations. RESULTS: Our predictive models demonstrate excellent in-sample model performance, as indicated by high R2 values generated from the gradient boosting models (0.94-0.97) and random forest models (0.81-0.90). However, the out-of-sample R2 values fall within a range of 0.52-0.75 for gradient boosting models and 0.44-0.69 for random forest models. Model performance varies slightly across years. A generally decreasing trend in predicted PM2.5 concentrations over time is observed in Eastern Texas. IMPACT STATEMENT: We utilized machine learning approaches to predict PM2.5 levels in Texas. Both gradient boosting and random forest models perform well. Gradient boosting models perform slightly better than random forest models. Our models showed excellent in-sample prediction performance (R2 > 0.9).

Magnolol-driven microbiota modulation elicits changes in tryptophan metabolism resulting in reduced skatole formation in pigs.

Skatole of gut origin has garnered significant attention as a malodorous pollutant due to its escalating emissions, recalcitrance to biodegradation and harm to animal and human health. Magnolol is a health-promoting polyphenol with potential to considerably mitigate the skatole production in the intestines. To investigate the impact of magnolol and its underlying mechanism on the skatole formation, in vivo and in vitro experiments were conducted in pigs. Our results revealed that skatole concentrations in the cecum, colon, and faeces decreased by 58.24% (P = 0.088), 44.98% (P < 0.05) and 43.52% (P < 0.05), respectively, following magnolol supplementation. Magnolol supplementation significantly decreased the abundance of Lachnospira, Faecalibacterium, Paramuribaculum, Faecalimonas, Desulfovibrio, Bariatricus, and Mogibacterium within the colon (P < 0.05). Moreover, a strong positive correlation (P < 0.05) between skatole concentration and Desulfovibrio abundance was observed. Subsequent in silico studies showed that magnolol could dock well with indolepyruvate decarboxylase (IPDC) within Desulfovibrio. Further in vitro investigation unveiled that magnolol addition led to less indole-3-pyruvate diverted towards the oxidative skatole pathway by the potential docking of magnolol towards IPDC, thereby diminishing the conversion of substrate into skatole. Our findings offer novel targets and strategies for mitigating skatole emission from the source.

The privilege of working from home and health disparities during the covid-19 pandemic in major American cities.

Working from home (WFH) has been adopted as a key mitigation strategy in the COVID-19 pandemic; yet few research has studied its impact on pandemic outcomes. Using multiple sources of data including cellphone data and online survey during the pandemic, this study investigates the effect of WFH on intra-city health disparities during the COVID-19 pandemic in American cities. Pandemic data for zip code tabulation areas and cellphone mobility data for census block groups in New York City (NYC), Chicago, and Philadelphia are converted to census tract level, which are then merged with 2019 census data. WFH is measured with the proportion of workers who potentially can telework based on employment composition in census tracts and percentages of jobs in each industry that actually WFH during the pandemic. Results show that while infection and death rates are higher in NYC, intra-city disparities in pandemic outcomes are more pronounced in Philadelphia. Poisson regressions show a negative association between WFH and COVID-19 infection and death rates in NYC and Chicago, which is weakened by increased time spent at home during the pandemic and in minority neighborhoods (in NYC). In Philadelphia, WFH is barely relevant for infection rates but has a marginally positive association with death rates, which is also moderated by the time spent at home. This study demonstrates the relative effectiveness of WFH in mitigating pandemic outcomes and underscores the intersectionality between WFH and race/ethnicity and resident behaviors. It provides important policy implications for future pandemic mitigation.

Association of peritumoral region features assessed on breast MRI and prognosis of breast cancer: a systematic review and meta-analysis.

BACKGROUND: Increasing attention has been given to the peritumoral region. However, conflicting findings have been reported regarding the relationship between peritumoral region features on MRI and the prognosis of breast cancer. PURPOSE: To evaluate the relationship between peritumoral region features on MRI and prognosis of breast cancer. MATERIALS AND METHODS: A retrospective meta-analysis of observational studies comparing either qualitative or quantitative assessments of peritumoral MRI features on breast cancer with poor prognosis and control subjects was performed for studies published till October 2022. Pooled odds ratios (ORs) or standardized mean differences and 95% confidence intervals (CIs) were estimated by using random-effects models. The heterogeneity across the studies was measured using the statistic I2. Sensitivity analyses were conducted to test this association according to different study characteristics. RESULTS: Twenty-four studies comprising 1853 breast cancers of poor prognosis and 2590 control participants were included in the analysis. Peritumoral edema was associated with non-luminal breast cancers (OR=3.56; 95%CI: 2.17, 5.83; p=.000), high expression of the Ki-67 index (OR=3.70; 95%CI: 2.41, 5.70; p =.000), high histological grade (OR=5.85; 95%CI: 3.89, 8.80; p=.000), lymph node metastasis (OR=2.83; 95%CI: 1.71, 4.67; p=.000), negative expression of HR (OR=3.15; 95%CI: 2.03, 4.88; p=.000), and lymphovascular invasion (OR=1.72; 95%CI: 1.28, 2.30; p=.000). The adjacent vessel sign was associated with greater odds of breast cancer with poor prognosis (OR=2.02; 95%CI: 1.68, 2.44; p=.000). Additionally, breast cancers with poor prognosis had higher peritumor-tumor ADC ratio (SMD=0.67; 95%CI: 0.54, 0.79; p=.000) and peritumoral ADCmean (SMD=0.29; 95%CI: 0.15, 0.42; p=.000). A peritumoral region of 2-20 mm away from the margin of the tumor is recommended. CONCLUSION: The presence of peritumoral edema and adjacent vessel signs, higher peritumor-tumor ADC ratio, and peritumoral ADCmean were significantly correlated with poor prognosis of breast cancer. CLINICAL RELEVANCE STATEMENT: MRI features of the peritumoral region can be used as a non-invasive index for the prognostic evaluation of invasive breast cancer. KEY POINTS: • Peritumoral edema was positively associated with non-luminal breast cancer, high expression of the Ki-67 index, high histological grade, lymph node metastasis, negative expression of HR, and lymphovascular invasion. • The adjacent vessel sign was associated with greater odds of breast cancers with poor prognosis. • Breast cancers with poor prognosis had higher peritumor-tumor ADC ratio and peritumoral ADCmean.

Diabetes risk among US adults with different socioeconomic status and behavioral lifestyles: evidence from the National Health and Nutrition Examination Survey.

Background: Diabetes disproportionately affects minorities and those with low socioeconomic status (SES) in the United States, and differences in behavioral lifestyles are largely responsible for the unequal distribution of diabetes among different groups. Methods: With data of 9,969 participants collected in the 2007-2008 and 2009-2010 cycles of the US National Health and Nutrition Examination Survey (NHANES), this study examined several mediators and their mediating effects in the connection between SES and the risk of diabetes. The SES is assessed by the income-to-poverty ratio (IPR), education level, and employment status. For the mediation analysis, we used health-related behaviors as mediators (smoking, alcohol use, consumption of green vegetables and fruits, physical activity and sedentary time, health insurance, and healthcare). In this study, the structural equation model was utilized to evaluate the mediating effects of behavioral lifestyle as a mediator in the relationship between SES and diabetes. Results: A total of 9,969 participants were included in this study. We found a negative nonlinear association between IPR and diabetes risk (Poverall < 0.001; Pnon-linear = 0.46), which was independent of the majority of known or suspected risk factors and confounding variables (gender, age, race). Participants with lower SES had higher risk of diabetes compared with those with higher SES. In mediating analysis, we found alcohol intake (OR = 0.996), physical activity (OR = 0.993), health insurance (OR = 0.998), and healthcare (OR = 1.002) mediated the IPR-diabetes association. But in the relationship between education status and diabetes, the mediation effect of alcohol intake (OR = 0.995), physical activity (OR = 0.991), and health care (OR = 1.008) were obvious. Likewise, alcohol intake (OR = 0.996), fruit intake (OR = 0.998), and health care (OR = 0.975) were important mediators in the association between employment status and diabetes. Conclusion: This study provides critical insights on the link between SES and diabetes. Our results highlight that poor health-related behaviors and limited access to healthcare are important pathways for increased diabetes risk related to those with low SES, particularly among Mexican Americans and males. They should be top priorities for agencies and healthcare providers to develop behavior-related interventions to reduce inequalities in diabetes risk.

The growth or decay estimates for nonlinear wave equations with damping and source terms.

The spatial decay or growth behavior of a coupled nonlinear wave equation with damping and source terms is considered. By defining the wave equations in a cylinder or an exterior region, the spatial growth and decay estimates for the solutions are obtained by assuming that the boundary conditions satisfy certain conditions. We also show that the growth or decay rates are faster than those obtained by relevant literature. This kind of spatial behavior can be extended to a nonlinear system of viscoelastic type. In the case of decay, we also prove that the total energy can be bounded by known data.

Magnolol Supplementation Alters Serum Parameters, Immune Homeostasis, Amino Acid Profiles, and Gene Expression of Amino Acid Transporters in Growing Pigs.

This study investigated whether dietary supplementation with magnolol affects growth performance, anti-inflammatory abilities, serum and muscle amino acid profiles, and metabolisms in growing pigs. A total of 42 seventy-days-old growing barrows (Duroc × Landrace × Yorkshire) were randomly allocated into two dietary groups: Con, control group (basal diet); and Mag, magnolol group (basal diet supplemented with 400 mg/kg of magnolol). The results revealed that dietary supplementation with magnolol had no effect (p > 0.05) on growth performance. However, magnolol supplementation remarkably increased (p < 0.05) the serum content of albumin, total protein, immunoglobulin G, immunoglobulin M, and interleukin-22. In addition, dietary magnolol supplementation altered the amino acid (AA) profiles in serum and dorsal muscle and particularly increased (p < 0.05) the serum content of arginine and muscle glutamate. Simultaneously, the mRNA expression of genes associated with AA transport in jejunum (SLC38A2, SLC1A5, and SLC7A1) and ileum (SLC1A5 and SLC7A1) was higher (p < 0.05) in the Mag group than in the Con group. Additionally, the serum metabolomics analysis showed that the addition of magnolol significantly enhanced (p < 0.05) arginine biosynthesis, as well as D-glutamine and D-glutamate metabolism. Overall, these results suggested that dietary supplementation with magnolol has the potential to improve the accumulation of AAs, protein synthesis, immunity, and body health in growing pigs by increasing intestinal absorption and the transport of AAs.

Microstructure and Mechanical Behavior of Quaternary Eutectic α+θ+Q+Si Clusters in As-Cast Al-Mg-Si-Cu Alloys.

Cu additions notably strengthen Al-Mg-Si and Al-Si-Mg alloys due to the dense precipitation of quaternary nano precipitates during ageing. However, the chemical evolution and mechanical behaviors of the quaternary micro-scale Q constituent phase occurring in cast and homogenized states have rarely been studied. Meanwhile, there exists a type of AlCuMgSi cluster in the cast state, which has been regarded as Q particles. The accurate identification of phase constituents is the basis for the future design of alloys with better performance. In our work, this type of cluster was revealed to consist of α-Al, θ-Al2Cu, Q, and Si phases through micro-to-atomic scale studies using scanning and transmission electron microscopes. The skeleton of the dendrite was θ phase. The second phases in the dendritic eutectic cluster dissolved quickly during a 4 h homogenization at 550 °C. The Q phase was found to effectively absorb the Fe impurities during casting and homogenization. As a result, the formation of other harmful Fe-rich intermetallics was suppressed. These Q constituent particles were observed to break into separate pieces in an intermediately brittle manner when compressed in situ in a scanning electron microscope. These findings provide insights into the thermodynamic modeling of the Al-Mg-Si-Cu system and alloy design.

Historical redlining and park use during the COVID-19 pandemic: Evidence from big mobility data.

BACKGROUND: Despite the health benefits of urban green space, disparities in its access and use have long existed. Emerging evidence suggests an adverse impact of redlining, a discriminatory practice decades ago, on multiple health outcomes. However, whether and to what degree redlining contributes to these disparities remains unknown particularly during a pandemic. With newly available mobility data tracking the locations of large numbers of mobile devices, this study links historical redlining with changes in green space use during the COVID-19 pandemic. OBJECTIVE: This study examines how changes in park visits during the lockdown period (3/23/2020-8/2/2020) are associated with redlining across census tracts in three large U.S. cities. METHODS: HOLC neighborhood redlining grade data were merged with SafeGraph mobility data at census tract level for New York City, Chicago, and Philadelphia. Ordinary Least Square regressions were conducted to assess the association between dominant redlining grade and relative change in park visits in census tracts by comparing the lockdown period to the reference period. Spatial error and lag models were also used to account for potential spatial autocorrelation. RESULTS: Park visits during the lockdown period in 2020 decreased by at least one-third in the three cities. The influence of redlining varied across neighborhoods and cities. In New York City, neighborhoods with more redlined areas experienced the largest drop, sharper decreases concentrated in neighborhoods previously graded as "best" or "still desirable" in Philadelphia, but the effect was barely present in Chicago. In addition, changes in park visits are positively correlated between neighborhoods in New York City and Chicago, but it's not observed in Philadelphia. IMPACT STATEMENT: Using emerging big mobility data, our study revealed large drops in park visits, a better measure than commonly-used access measures in capturing green space exposure, during the lockdown period. We found that historical redlining has a lasting impact on current green space use. More decreases in park visits were observed in the redlined areas in New York City, but patterns vary by neighborhood and city due to local-specific neighborhood dynamics. And changes in park visits were spatially, positively correlated across places.

Dietary Supplementation with Rutin Alters Meat Quality, Fatty Acid Profile, Antioxidant Capacity, and Expression Levels of Genes Associated with Lipid Metabolism in Breast Muscle of Qingyuan Partridge Chickens.

Consumer demand for tasty and quality meat has been quickly increasing. This study investigated how dietary supplemented rutin affects meat quality, muscle fatty acid profile, and antioxidant capacity in the Chinese indigenous Qingyuan partridge chicken. A cohort of 180 healthy 119-day-old chickens was subjected to a randomized assignment into three groups, identified as the control, R200, and R400 groups, with respective supplementation of 0, 200, and 400 mg/kg of rutin. The results revealed insignificance in growth performance, namely, average daily gain, average daily feed intake, and feed-to-gain ratio, across the various treatment groups (p > 0.05). Nevertheless, dietary rutin supplementation increased (p < 0.05) breast muscle yield and intramuscular fat content in breast muscle and decreased (p < 0.05) drip loss in breast muscle. Rutin supplementation increased (p < 0.05) the content of high-density lipoprotein but decreased (p < 0.05) the contents of glucose, triglyceride, and total cholesterol in serum. Rutin supplementation increased (p < 0.05) the levels of DHA (C22:6n-3), total polyunsaturated fatty acids (PUFAs), n-3 PUFAs, decanoic acid (C10:0), the activity of Δ5 + Δ6 (22:6 (n - 3)/18:3 (n - 3)), and the ratio of PUFA/SFA in breast muscle but decreased (p < 0.05) the level of palmitoleic acid (C16:1n-7), the ratio of n-6/n-3 PUFAs, and the activity of Δ9 (16:1 (n - 7)/16:0). Rutin treatment also reduced (p < 0.05) the contents of malondialdehyde in serum and breast muscle, and increased (p < 0.05) the catalase activity and total antioxidant capacity in serum and breast muscle and the activity of total superoxide dismutase in serum. Additionally, rutin supplementation downregulated the expression of AMPKα and upregulated the expression of PPARG, FADS1, FAS, ELOVL7, NRF2, and CAT in breast muscle (p < 0.05). Convincingly, the results revealed that rutin supplementation improved meat quality, fatty acid profiles, especially n-3 PUFAs, and the antioxidant capacity of Qingyuan partridge chickens.

Air Pollution, Built Environment, and Early Cardiovascular Disease.

As the world's population becomes increasingly urbanized, there is growing concern about the impact of urban environments on cardiovascular health. Urban residents are exposed to a variety of adverse environmental exposures throughout their lives, including air pollution, built environment, and lack of green space, which may contribute to the development of early cardiovascular disease and related risk factors. While epidemiological studies have examined the role of a few environmental factors with early cardiovascular disease, the relationship with the broader environment remains poorly defined. In this article, we provide a brief overview of studies that have examined the impact of the environment including the built physical environment, discuss current challenges in the field, and suggest potential directions for future research. Additionally, we highlight the clinical implications of these findings and propose multilevel interventions to promote cardiovascular health among children and young adults.

The development of prediction model on irradiation embitterment for low Cu RPV steels.

The development of prediction model on irradiation embitterment (PMIE) of reactor pressure vessel (RPV) is an important method for nuclear reactor long term operation. Based on the physical mechanism of RPV irradiation embrittlement, a preliminary model is determined and the critical threshold of Cu content of 0.072% is obtained according to this preliminary model. Then a prediction model named PMIE-2020 for low Cu RPV steels is developed. At last the residual, standard deviation and predicted values and test values distribution analysis are given. Simultaneously, a comparison between PMIE-2020 and other prediction model and irradiation data is provided. Results indicate that the predicted results of PMIE-2020 has no tendency with influence factors such as neutron fluence, flux, irradiation temperature, chemical elements Cu, P, Mn, Ni, Si. The residual standard deviation is 10.76 °C, which is lower than present prediction model. The distribution between predicted values of PMIE-2020 and test values are located the area near the 45° line. These results prove that the PMIE-2020 have high accuracy on irradiation embrittlement prediction.

Predicting Drug-Target Affinity by Learning Protein Knowledge From Biological Networks.

Predicting drug-target affinity (DTA) is a crucial step in the process of drug discovery. Efficient and accurate prediction of DTA would greatly reduce the time and economic cost of new drug development, which has encouraged the emergence of a large number of deep learning-based DTA prediction methods. In terms of the representation of target proteins, current methods can be classified into 1D sequence- and 2D-protein graph-based methods. However, both two approaches focused only on the inherent properties of the target protein, but neglected the broad prior knowledge regarding protein interactions that have been clearly elucidated in past decades. Aiming at the above issue, this work presents an end-to-end DTA prediction method named MSF-DTA (Multi-Source Feature Fusion-based Drug-Target Affinity). The contributions can be summarized as follows. First, MSF-DTA adopts a novel "neighboring feature"-based protein representation. Instead of utilizing only the inherent features of a target protein, MSF-DTA gathers additional information for the target protein from its biologically related "neighboring" proteins in PPI (i.e., protein-protein interaction) and SSN (i.e., sequence similarity) networks to get prior knowledge. Second, the representation was learned using an advanced graph pre-training framework, VGAE, which could not only gather node features but also learn topological connections, therefore contributing to a richer protein representation and benefiting the downstream DTA prediction task. This study provides new perspective for the DTA prediction task, and evaluation results demonstrated that MSF-DTA obtained superior performances compared to current state-of-the-art methods.

Spatial decay bound and structural stability for the double-diffusion perturbation equations.

In this paper, we study the double-diffusion perturbation equations when the flow is through a porous medium. If the initial conditions satisfy some constraint conditions, the Saint-Venant type spatial decay of solutions for double-diffusion perturbation equations is obtained. Based on the spatial decay bound, the structural stability for the double-diffusion perturbation equations is also established.

Flammulina velutipes Mycorrhizae Attenuate High Fat Diet-Induced Lipid Disorder, Oxidative Stress and Inflammation in the Liver and Perirenal Adipose Tissue of Mice.

Flammulina velutipes (FV) is edible mushroom that has nutritional and medicinal values. FV mycorrhizae, the by-products of FV, are an abundant source and receive less attention. The objective of this study was to investigate the composition of FV mycorrhizae, and its effects on high fat diet (HFD)-induced lipid disorder, oxidative stress, and inflammatory cytokines, both in the liver and perirenal adipose tissue (PAT) of mice. The results showed that FV mycorrhizae contain abundant trace elements, polysaccharide, amino acids and derivatives, and organic compounds. It was found that 4% FV mycorrhizae (HFDFV) supplementation decreased HFD-induced liver weight and triglyceride (TG) in the plasma, liver and PAT, altered plasma and hepatic fatty acids profiles, promoted gene expression involved in lipid hydrolysis, fatty acid transportation and ß-oxidation in the liver and reduced lipid synthesis in the liver and PAT. HFDFV attenuated HFD-induced oxidative stress and pro-inflammatory cytokine by increasing GSH/GSSG, and decreasing levels of MDA and IL6 both in the liver and PAT, while it differentially regulated gene expression of IL1ß, IL6, and CCL2 in liver and PAT. The results indicated that FV mycorrhizae are effective to attenuate HFD-induced lipid disorder, oxidative stress and inflammation in the liver and PAT, indicating their promising constituents for functional foods and herbal medicine.

Mechanistic Insights Into Inflammation-Induced Arrhythmias: A Simulation Study.

Cardiovascular diseases are the primary cause of death of humans, and among these, ventricular arrhythmias are the most common cause of death. There is plausible evidence implicating inflammation in the etiology of ventricular fibrillation (VF). In the case of systemic inflammation caused by an overactive immune response, the induced inflammatory cytokines directly affect the function of ion channels in cardiomyocytes, leading to a prolonged action potential duration (APD). However, the mechanistic links between inflammatory cytokine-induced molecular and cellular influences and inflammation-associated ventricular arrhythmias need to be elucidated. The present study aimed to determine the potential impact of systemic inflammation on ventricular electrophysiology by means of multiscale virtual heart models. The experimental data on the ionic current of three major cytokines [i.e., tumor necrosis factor-α (TNF-α), interleukin-1 (IL-1ß), and interleukin-6 (IL-6)] were incorporated into the cell model, and the effects of each cytokine and their combined effect on the cell action potential (AP) were evaluated. Moreover, the integral effect of these cytokines on the conduction of excitation waves was also investigated in a tissue model. The simulation results suggested that inflammatory cytokines significantly prolonged APD, enhanced the transmural and regional repolarization heterogeneities that predispose to arrhythmias, and reduced the adaptability of ventricular tissue to fast heart rates. In addition, simulated pseudo-ECGs showed a prolonged QT interval-a manifestation consistent with clinical observations. In summary, the present study provides new insights into ventricular arrhythmias associated with inflammation.