Omega-3 polyunsaturated fatty acids and the psychiatric post-acute sequelae of COVID-19: A one-year retrospective cohort analysis of 33,908 patients.

BACKGROUND: Early prevention and management of psychiatric symptoms in long COVID (or post-COVID-19 conditions) are crucial for reducing long-term disability. Existing clinical guidelines recommend the use of omega-3 polyunsaturated fatty acids (PUFAs) as a promising therapeutic approach for various common psychiatric disorders due to their anti-inflammatory and neuroprotective characteristics. This study aims to investigate the potential efficacy of omega-3 PUFAs in alleviating the psychiatric sequelae following COVID-19. METHODS: This 1-year retrospective cohort study used the TriNetX electronic health records network to examine the effects of omega-3 PUFAs supplements on psychiatric sequelae in adults diagnosed with COVID-19. Using propensity-score matching, the study compared those who used omega-3 PUFAs supplements with those who did not, assessing outcomes including depression, anxiety disorders, insomnia, and other somatic conditions up to a year after COVID-19 diagnosis. RESULTS: In 16,962 patients who received omega-3 PUFAs supplements and 2,248,803 who did not, omega-3 supplementation significantly reduced the risk of developing psychiatric sequelae post-COVID-19 diagnosis (HR, 0.804; 95% CI, 0.729 to 0.888). Specifically, the risks for depression (HR, 0.828; 95% CI, 0.714 to 0.960), anxiety disorders (HR, 0.833; 95% CI, 0.743 to 0.933), and insomnia (HR, 0.679; 95% CI, 0.531 to 0.869) were reduced in the omega-3 group. This effect was consistent across sex, race, 18-59 age group, and patients with less than two doses of the COVID-19 vaccine. The omega-3 group also had a lower risk of cough and myalgia, but no significant difference was noted for other symptoms like chest pain, abnormal breathing, abdominal issues, fatigue, headache, and cognitive symptoms. CONCLUSION: Omega-3 PUFAs may require re-evaluation as a preventive strategy against adverse mental health outcomes post-COVID-19 in placebo-controlled clinical trials.

Reaction-Diffusion Modeling of E. coli Colony Growth Based on Nutrient Distribution and Agar Dehydration.

The bacterial colony is a powerful experimental platform for broad biological research, and reaction-diffusion models are widely used to study the mechanisms of its formation process. However, there are still some crucial factors that drastically affect the colony growth but are not considered in the current models, such as the non-homogeneously distributed nutrient within the colony and the substantially decreasing expansion rate caused by agar dehydration. In our study, we propose two plausible reaction-diffusion models (the VN and MVN models) based on the above two factors and validate them against experimental data. Both models provide a plausible description of the non-homogeneously distributed nutrient within the colony and outperform the classical Fisher-Kolmogorov equation and its variation in better describing experimental data. Moreover, by accounting for agar dehydration, the MVN model captures how a colony's expansion slows down and the change of a colony's height profile over time. Furthermore, we demonstrate the existence of a traveling wave solution for the VN model.

The emergence of a virus variant: dynamics of a competition model with cross-immunity time-delay validated by wastewater surveillance data for COVID-19.

We consider the dynamics of a virus spreading through a population that produces a mutant strain with the ability to infect individuals that were infected with the established strain. Temporary cross-immunity is included using a time delay, but is found to be a harmless delay. We provide some sufficient conditions that guarantee local and global asymptotic stability of the disease-free equilibrium and the two boundary equilibria when the two strains outcompete one another. It is shown that, due to the immune evasion of the emerging strain, the reproduction number of the emerging strain must be significantly lower than that of the established strain for the local stability of the established-strain-only boundary equilibrium. To analyze the unique coexistence equilibrium we apply a quasi steady-state argument to reduce the full model to a two-dimensional one that exhibits a global asymptotically stable established-strain-only equilibrium or global asymptotically stable coexistence equilibrium. Our results indicate that the basic reproduction numbers of both strains govern the overall dynamics, but in nontrivial ways due to the inclusion of cross-immunity. The model is applied to study the emergence of the SARS-CoV-2 Delta variant in the presence of the Alpha variant using wastewater surveillance data from the Deer Island Treatment Plant in Massachusetts, USA.

Global stability and parameter analysis reinforce therapeutic targets of PD-L1-PD-1 and MDSCs for glioblastoma.

Glioblastoma (GBM) is an aggressive primary brain cancer that currently has minimally effective treatments. Like other cancers, immunosuppression by the PD-L1-PD-1 immune checkpoint complex is a prominent axis by which glioma cells evade the immune system. Myeloid-derived suppressor cells (MDSCs), which are recruited to the glioma microenviroment, also contribute to the immunosuppressed GBM microenvironment by suppressing T cell functions. In this paper, we propose a GBM-specific tumor-immune ordinary differential equations model of glioma cells, T cells, and MDSCs to provide theoretical insights into the interactions between these cells. Equilibrium and stability analysis indicates that there are unique tumorous and tumor-free equilibria which are locally stable under certain conditions. Further, the tumor-free equilibrium is globally stable when T cell activation and the tumor kill rate by T cells overcome tumor growth, T cell inhibition by PD-L1-PD-1 and MDSCs, and the T cell death rate. Bifurcation analysis suggests that a treatment plan that includes surgical resection and therapeutics targeting immune suppression caused by the PD-L1-PD1 complex and MDSCs results in the system tending to the tumor-free equilibrium. Using a set of preclinical experimental data, we implement the approximate Bayesian computation (ABC) rejection method to construct probability density distributions that estimate model parameters. These distributions inform an appropriate search curve for global sensitivity analysis using the extended fourier amplitude sensitivity test. Sensitivity results combined with the ABC method suggest that parameter interaction is occurring between the drivers of tumor burden, which are the tumor growth rate and carrying capacity as well as the tumor kill rate by T cells, and the two modeled forms of immunosuppression, PD-L1-PD-1 immune checkpoint and MDSC suppression of T cells. Thus, treatment with an immune checkpoint inhibitor in combination with a therapeutic targeting the inhibitory mechanisms of MDSCs should be explored.

Coptisine Inhibits Influenza Virus Replication by Upregulating p21.

The activation of innate antiviral immunity is a promising approach for combatting viral infections. In this study, we screened Chinese herbs that activated human immunity and identified coptisine as a potent inhibitor of the influenza virus with an EC50 of 10.7 µM in MDCK cells. The time of an addition assay revealed that pre-treatment with coptisine was more effective at reducing viral replication than co-treatment or post-treatment. Our bulk RNA-sequencing data showed that coptisine upregulated the p21 signaling pathway in MDCK cells, which was responsible for its antiviral effects. Specifically, coptisine increased the expression of p21 and FOXO1 in a dose-dependent manner while leaving the MELK expression unchanged. Docking analysis revealed that coptisine likely inhibited MELK activity directly by forming hydrogen bonds with ASP-150 and GLU-87 in the catalytic pocket. These findings suggest that coptisine may be a promising antiviral agent that regulates the p21 signaling pathway to inhibit viral replication.

Traveling wave speed and profile of a "go or grow" glioblastoma multiforme model.

Glioblastoma multiforme (GBM) is a fast-growing and deadly brain tumor due to its ability to aggressively invade the nearby brain tissue. A host of mathematical models in the form of reaction-diffusion equations have been formulated and studied in order to assist clinical assessment of GBM growth and its treatment prediction. To better understand the speed of GBM growth and form, we propose a two population reaction-diffusion GBM model based on the 'go or grow' hypothesis. Our model is validated by in vitro data and assumes that tumor cells are more likely to leave and search for better locations when resources are more limited at their current positions. Our findings indicate that the tumor progresses slower than the simpler Fisher model, which is known to overestimate GBM progression. Moreover, we obtain accurate estimations of the traveling wave solution profiles under several plausible GBM cell switching scenarios by applying the approximation method introduced by Canosa.

Revisiting the growth rate hypothesis: Towards a holistic stoichiometric understanding of growth.

The growth rate hypothesis (GRH) posits that variation in organismal stoichiometry (C:P and N:P ratios) is driven by growth-dependent allocation of P to ribosomal RNA. The GRH has found broad but not uniform support in studies across diverse biota and habitats. We synthesise information on how and why the tripartite growth-RNA-P relationship predicted by the GRH may be uncoupled and outline paths for both theoretical and empirical work needed to broaden the working domain of the GRH. We found strong support for growth to RNA (r2  = 0.59) and RNA-P to P (r2  = 0.63) relationships across taxa, but growth to P relationships were relatively weaker (r2  = 0.09). Together, the GRH was supported in ~50% of studies. Mechanisms behind GRH uncoupling were diverse but could generally be attributed to physiological (P accumulation in non-RNA pools, inactive ribosomes, translation elongation rates and protein turnover rates), ecological (limitation by resources other than P), and evolutionary (adaptation to different nutrient supply regimes) causes. These factors should be accounted for in empirical tests of the GRH and formalised mathematically to facilitate a predictive understanding of growth.

Learning Biological Dynamics From Spatio-Temporal Data by Gaussian Processes.

Model discovery methods offer a promising way to understand biology from data. We propose a method to learn biological dynamics from spatio-temporal data by Gaussian processes. This approach is essentially "equation free" and hence avoids model derivation, which is often difficult due to high complexity of biological processes. By exploiting the local nature of biological processes, dynamics can be learned with data sparse in time. When the length scales (hyperparameters) of the squared exponential covariance function are tuned, they reveal key insights of the underlying process. The squared exponential covariance function also simplifies propagation of uncertainty in multi-step forecasting. After evaluating the performance of the method on synthetic data, we demonstrate a case study on real image data of E. coli colony.

[Economic burden of Down syndrome patients and psychological and social discrimination to female caregivers in Changsha, China].

OBJECTIVE: To estimate the social and economic burden of Downs syndrome for patients and their families residing in Changsha, China. METHODS: An 160-item self-administered questionnaire was designed and distributed to the primary caregivers of the patients in March 2020. A total of 81 eligible participants had completed the questionnaire, among which 20 were excluded for incomplete data. A patient perspective was taken to estimate the economic burden of the disease. The social impact of the disease on the patient's family was evaluated through questions adapted from the Stanford Psychological Wellbeing (PWB) Scale. RESULTS: The estimated life-course cost of a Downs syndrome patient in Changsha is 4 985 659 RMB, with the patient and caregiver's loss of income taking the greater proportion. In addition, as the majority of the patients' primary caregivers, female caregivers experienced not only considerable financial hardship caused by the care provision, but also a significant amount of psychological pressure and social discrimination. CONCLUSION: Increased level of social welfare for the patients and social support for their female caregivers are essential for reducing economic burden and improving their quality of life in the area. In addition, prenatal screening and diagnosis for Downs syndrome are important for reducing both the social and economic burden of the disease by preventing its occurrence.

[Health economic evaluation of four prenatal screening strategies for Down syndrome in Changsha, China].

OBJECTIVE: To compare the clinical application and health economic values of non-invasive prenatal testing (NIPT) and second trimester serum screening (STSS). METHODS: A retrospective analysis was carried out on 54 026 singleton pregnant women undergoing NIPT and STSS from March 1, 2018 to December 31, 2019 in Changsha Maternal and Child Health Care Hospital. For pregnant women with high-risk results of NIPT, prenatal diagnosis and follow-up of pregnancy outcomes were conducted. The data was grouped to 4 screening models, and their cost-benefit was analyzed. RESULTS: The sensitivity, specificity and positive predictive value of NIPT were all higher than STSS. Screening models 1 to 4 have prevented the birth of 71, 29, 52 and 54 patients with Down syndrome, respectively. The safety index of screening models 1 to 4 were 0.0036, 0.3944, 02215 and 0.1281, respectively. When the price of NIPT was decreased to 600 RMB, the cost-benefit of the screening models 1 to 4 was 0.46, 0.65, 0.44 and 0.40 million RMB, respectively. CONCLUSION: NIPT has a better detection performance than STSS. When the price of NIPT is 600 RMB, screening model 1 has the best screening effect and the highest accuracy, safety index and health economical value.

Modeling the synergistic properties of drugs in hormonal treatment for prostate cancer.

Prostate cancer is one of the most prevalent cancers in men, with increasing incidence worldwide. This public health concern has inspired considerable effort to study various aspects of prostate cancer treatment using dynamical models, especially in clinical settings. The standard of care for metastatic prostate cancer is hormonal therapy, which reduces the production of androgen that fuels the growth of prostate tumor cells prior to treatment resistance. Existing population models often use patients' prostate-specific antigen levels as a biomarker for model validation and for finding optimal treatment schedules; however, the synergistic effects of drugs used in hormonal therapy have not been well-examined. This paper describes the first mathematical model that explicitly incorporates the synergistic effects of two drugs used to inhibit androgen production in hormonal therapy. The drugs are cyproterone acetate, representing the drug family of anti-androgens that affect luteinizing hormones, and leuprolide acetate, representing the drug family of gonadotropin-releasing hormone analogs. By fitting the model to clinical data, we show that the proposed model can capture the dynamics of serum androgen levels during intermittent hormonal therapy better than previously published models. Our results highlight the importance of considering the synergistic effects of drugs in cancer treatment, thus suggesting that the dynamics of the drugs should be taken into account in optimal treatment studies, particularly for adaptive therapy. Otherwise, an unrealistic treatment schedule may be prescribed and render the treatment less effective. Furthermore, the drug dynamics allow our model to explain the delay in the relapse of androgen the moment a patient is taken off treatment, which supports that this delay is due to the residual effects of the drugs.

Effect of catechin and commercial preparation of green tea essence on the pharmacokinetics of l-dopa in rabbits.

The aim of this study was to investigate drug interactions of L-dopa/carbidopa with catechin and green tea essence in rabbits following the simultaneous administration via an intramuscular injection of catechin or via an intragastric route for green tea essence with L-dopa/carbidopa. The results indicated that catechin at doses of 10, 20 and 50 mg/kg increased the area under the plasma concentration-time curve from time zero to the time of the last quantifiable concentration (AUC0-t ) of L-dopa by about 69, 78 and 42%, respectively. The metabolic ratios of the AUC0-t for 3-O-methyldopa (3-OMD)/L-dopa significantly decreased by about 56, 68 and 76% (P < 0.05), respectively. In addition, a single dose of 5/1.25 mg/kg L-dopa/carbidopa was co-administrated with 150 mg/kg green tea essence via an intragastric route with an oral-gastric tube. Comparing the related pharmacokinetic parameters of L-dopa, the clearance and metabolic ratio of L-dopa decreased by 20 and 19% (P < 0.05), respectively. In conclusion, catechin and green tea essence can significantly affect the metabolism of L-dopa by the catechol-O-methyltransferase (COMT) metabolic pathway. Catechin can enhance L-dopa bioavailability, and both catechin and green tea essence decreased 3-OMD formation. Therefore, catechin and green tea essence may increase L-dopa efficacy for Parkinson's disease treatment.

Analysis of tumor-immune dynamics in a delayed dendritic cell therapy model.

We formulate a tumor-immune interaction model with a constant delay to capture the behavior following application of a dendritic cell therapy. The model is validated using experimental data from melanoma-induced mice. Through theoretical and numerical analyses, the model is shown to produce rich dynamics, such as a Hopf bifurcation and bistability. We provide thresholds for tumor existence and, in a special case, tumor elimination. Our work indicates a sensitivity in model outcomes to the immune response time. We provide a stability analysis for the high tumor equilibrium. For small delays in response, the tumor and immune system coexist at a low level. Large delays give rise to fatally high tumor levels. Our computational and theoretical work reveals that there exists an intermediate region of delay that generates complex oscillatory, even chaotic, behavior. The model then reflects uncertainty in treatment outcomes for varying initial tumor burdens, as well as tumor dormancy followed by uncontrolled growth to a lethal size, a phenomenon seen in vivo. Theoretical and computational analyses suggest efficacious treatments to use in conjunction with the dendritic cell vaccine. Additional analysis of a highly aggressive tumor additionally confirms the importance of representation with a time delay, as periodic solutions are strictly able to be generated when a delay is present.

How ticks keep ticking in the adversity of host immune reactions.

Ixodid ticks are acknowledged as one of the most important hematophagous arthropods because of their ability in transmitting a variety of tick-borne diseases. Mathematical models have been developed, based on emerging knowledge about tick ecology, pathogen epidemiology and their interface, to understand tick population dynamics and tick-borne diseases spread patterns. However, no serious effort has been made to model and assess the impact of host immunity triggered by tick feeding on the distribution of the tick population according to tick stages and on tick population extinction and persistence. Here, we construct a novel mathematical model taking into account the effect of host immunity status on tick population dynamics, and analyze the long-term behaviours of the model solutions. Two threshold values, [Formula: see text] and [Formula: see text], are introduced to measure the reproduction ratios for the tick-host interaction in the absence and presence of host immunity. We then show that these two thresholds (sometimes under additional conditions) can be used to predict whether the tick population goes extinct ([Formula: see text]) and the tick population grows without bound ([Formula: see text]). We also prove tick permanence (persistence and boundedness of the tick population) and the existence of a tick persistence equilibrium if [Formula: see text]. As the host species adjust their immunity to tick infestation levels, they form for the tick population an environment with a carrying capacity very much like that in logistic growth. Numerical results show that the host immune reactions decrease the size of the tick population at equilibrium and apparently reduce the tick-borne infection risk.

Oscillatory dynamics of an intravenous glucose tolerance test model with delay interval.

Type 2 diabetes mellitus (T2DM) has become prevalent pandemic disease in view of the modern life style. Both diabetic population and health expenses grow rapidly according to American Diabetes Association. Detecting the potential onset of T2DM is an essential focal point in the research of diabetes mellitus. The intravenous glucose tolerance test (IVGTT) is an effective protocol to determine the insulin sensitivity, glucose effectiveness, and pancreatic ß-cell functionality, through the analysis and parameter estimation of a proper differential equation model. Delay differential equations have been used to study the complex physiological phenomena including the glucose and insulin regulations. In this paper, we propose a novel approach to model the time delay in IVGTT modeling. This novel approach uses two parameters to simulate not only both discrete time delay and distributed time delay in the past interval, but also the time delay distributed in a past sub-interval. Normally, larger time delay, either a discrete or a distributed delay, will destabilize the system. However, we find that time delay over a sub-interval might not. We present analytically some basic model properties, which are desirable biologically and mathematically. We show that this relatively simple model provides good fit to fluctuating patient data sets and reveals some intriguing dynamics. Moreover, our numerical simulation results indicate that our model may remove the defect in well known Minimal Model, which often overestimates the glucose effectiveness index.

Cognitive Dysfunction in Asian Patients with Depression (CogDAD): A Cross-Sectional Study.

BACKGROUND: Cognitive dysfunction is a predominant symptom of Major Depressive Disorder (MDD), contributing to functional impairment. OBJECTIVE: The primary objective of this study was to assess and describe perceived cognitive dysfunction amongst Asian patients diagnosed with MDD. The secondary objective was to explore the associations between depression severity, perceived cognitive dysfunction and functional disability. METHODS: This was a multi-country, multi-centre, cross-sectional study. Adults with a current episode of MDD were recruited from 9 university/general hospital clinics in Asia. During a single study visit, psychiatrists assessed depression severity (Clinical Global Impression-Severity, CGI-S); patients completed questionnaires assessing depression severity (Patient Health Questionnaire-9 items, PHQ-9), perceived cognitive dysfunction (Perceived Deficit Questionnaire-Depression, PDQ-D) and functional disability (Sheehan Disability Scale, SDS). RESULTS: Patients (n=664), predominantly women (66.3%), were aged 46.5±12.5 years, lived in urban areas (81.3%) and were employed (84.6%). 51.5% of patients were having their first depressive episode; 86.7% were receiving treatment; 82.2% had a current episode duration >8 weeks. Patients had mild-to-moderate depression (CGI-S=3.3±1.0; PHQ-9=11.3±6.9). Patients reported perceived cognitive dysfunction (PDQ-D=22.6±16.2) and functional disability (SDS=11.3±7.9). PHQ-9, PDQ-D and SDS were moderately-to-highly correlated (PHQ-9 and SDS: r=0.72; PHQ-9 and PDQ-D: r=0.69; PDQ-D and SDS, r=0.63). ANCOVA showed that after controlling for patient-reported depression severity (PHQ-9), perceived cognitive dysfunction (PDQ-D) was significantly associated with functional disability (SDS) (p<0.001). CONCLUSIONS: Asian patients with MDD reported perceived cognitive dysfunction. There is a need for physicians to evaluate cognitive dysfunction in the clinical setting in order to reach treatment goals, including functional recovery beyond remission of mood symptoms.

Impact of Population Recruitment on the HIV Epidemics and the Effectiveness of HIV Prevention Interventions.

Mechanistic mathematical models are increasingly used to evaluate the effectiveness of different interventions for HIV prevention and to inform public health decisions. By focusing exclusively on the impact of the interventions, the importance of the demographic processes in these studies is often underestimated. In this paper, we use simple deterministic models to assess the effectiveness of pre-exposure prophylaxis in reducing the HIV transmission and to explore the influence of the recruitment mechanisms on the epidemic and effectiveness projections. We employ three commonly used formulas that correspond to constant, proportional and logistic recruitment and compare the dynamical properties of the resulting models. Our analysis exposes substantial differences in the transient and asymptotic behavior of the models which result in 47 % variation in population size and more than 6 percentage points variation in HIV prevalence over 40 years between models using different recruitment mechanisms. We outline the strong influence of recruitment assumptions on the impact of HIV prevention interventions and conclude that detailed demographic data should be used to inform the integration of recruitment processes in the models before HIV prevention is considered.

Transperitoneal versus retroperitoneal approach for elective open abdominal aortic aneurysm repair.

BACKGROUND: There has been extensive debate in the surgical literature regarding the optimum surgical access approach to the infrarenal abdominal aorta during an operation to repair an abdominal aortic aneurysm. The published trials comparing retroperitoneal (RP) and transperitoneal (TP) aortic surgery show conflicting results. OBJECTIVES: To assess the effectiveness and safety of the transperitoneal versus retroperitoneal approach for elective open abdominal aortic aneurysm repair on mortality, complications, hospital stay and blood loss. SEARCH METHODS: The Cochrane Vascular Trials Search Co-ordinator searched the Cochrane Vascular Specialised Register (last searched May 2015) and CENTRAL (2015, Issue 4) and trials databases (May 2015). The review authors searched the Chinese Biomedical Literature Database and other resources including clinical trials registers. SELECTION CRITERIA: We included randomized controlled trials (RCTs) that assessed the TP approach versus the RP approach for elective open abdominal aortic aneurysm (AAA) repair. We evaluated the outcomes of mortality, complications, intensive care unit (ICU) stay, hospital stay, blood loss, aortic cross-clamp time and operating time. Two review authors independently selected RCTs against the inclusion criteria. We resolved any disagreements by discussion with a third review author. DATA COLLECTION AND ANALYSIS: Two review authors independently extracted data from the included trials. We resolved any disagreements by discussion with a third review author. Two review authors independently assessed the risk of bias according to a standard quality checklist provided by Cochrane Vascular. MAIN RESULTS: We included four RCTs, with a combined total of 129 participants, that assessed the TP approach versus the RP approach for elective open AAA repair. The overall quality of the evidence was low to very low because of the low methodological quality of the included trials (unclear random sequence generation method and allocation concealment, and no blinding of outcome assessors), small sample sizes, small number of events, high heterogeneity and inconsistency between the included trials, no power calculations and relatively short follow-up. There were no differences between the RP approach and the TP approach regarding mortality (odds ratio (OR) 0.32, 95% CI 0.01 to 8.25; 110 participants; four trials; P = 0.49; I² statistic = 0%; very low quality evidence). However, the RP approach may increase complications, such as hematoma (OR 0.90, 95% CI 0.13 to 6.48; 75 participants; two trials; P = 0.92; very low quality evidence), chronic wound pain (OR 2.20, 95% CI 0.36 to 13.34; 48 participants; one trial; P = 0.39; very low quality evidence) and abdominal wall hernia (OR 10.76, 95% CI 0.55 to 211.78; 48 participants; one trial; P = 0.12; very low quality evidence) compared with the TP approach in the patients for elective open AAA repair, but the confidence intervals (CIs) were wide. The RP approach reduced the blood loss (mean difference (MD) -504.87 mL, 95% CI -779.19 to -230.56; 129 participants; four trials; P = 0.003; very low quality evidence), ICU stay (MD -19.00 hours, 95% CI -31.41 to -6.59; 83 participants; two trials; P = 0.003; low quality evidence) and hospital stay (MD -3.14 days, 95% CI -4.82 to -1.45; 129 participants; four trials; P = 0.0003; low quality evidence). There were no differences between the RP approach and the TP approach regarding aortic cross-clamp time (MD 0.69 mins, 95% CI -7.23 to 8.60; 129 participants; four trials; P = 0.86; very low quality evidence) and operating time (MD -15.94 mins, 95% CI -34.76 to 2.88; 129 participants; four trials; P = 0.10; very low quality evidence). AUTHORS' CONCLUSIONS: Very low quality evidence from four small RCTs indicates that the RP approach did not have advantages over the TP approach for elective open AAA repair in terms of mortality. Moreover, the RP approach may increase the risk of postoperative wound complications although the CIs were wide.Low quality evidence shows that the RP approach could reduce blood loss, hospital stay and ICU stay compared with the TP approach. Very low quality evidence shows no differences between the RP approach and TP approaches in aortic cross-clamp time and operating time.Further large-scale RCTs of the RP approach versus TP approach for elective open AAA repair are required.

Dynamics of a producer-grazer model incorporating the effects of excess food nutrient content on grazer's growth.

Modeling under the framework of ecological stoichiometric allows the investigation of the effects of food quality on food web population dynamics. Recent discoveries in ecological stoichiometry suggest that grazer dynamics are affected by insufficient food nutrient content (low phosphorus (P)/carbon (C) ratio) as well as excess food nutrient content (high P:C). This phenomenon is known as the "stoichiometric knife edge." While previous models have captured this phenomenon, they do not explicitly track P in the producer or in the media that supports the producer, which brings questions to the validity of their predictions. Here, we extend a Lotka-Volterra-type stoichiometric model by mechanistically deriving and tracking P in the producer and free P in the environment in order to investigate the growth response of Daphnia to algae of varying P:C ratios. Bifurcation analysis and numerical simulations of the full model, that explicitly tracks phosphorus, lead to quantitative different predictions than previous models that neglect to track free nutrients. The full model shows that the fate of the grazer population can be very sensitive to excess nutrient concentrations. Dynamical free nutrient pool seems to induce extreme grazer population density changes when total nutrient is in an intermediate range.

Pharmacokinetics of fexofenadine in healthy Taiwanese volunteers.

The aim of presented study was to assess pharmacokinetic properties of fexofenadine in Taiwanese volunteers. Thirty-three healthy male subjects received 180mg fexofenadine. Blood samples were drawn at appropriate times. Drug concentrations of fexofenadine were measured by a LC/MS/MS method. Non-compartmental models were applied to describe the pharmacokinetic characters of fexofenadine. After oral administration of fexofenadine, the Tmax was 1.90 ± 0.81h. The Cmax was 703.76 ± 298.94ng/mL and AUC0-oo was 4582.52 ± 1812.59h´ng/mL. The elimination half-life of fexofenadine was 12.18 ± 3.61h. One of the most important determinants was to prove the similar results in the pharmacokinetics of fexofenadine in Taiwan subjects compared with the reported data of other ethnic origin.