Seroprevalence of <em>Lawsonia intracellularis</em> antibodies in intensive pig farms in China

BACKGROUND: Porcine proliferative enteropathy caused by Lawsonia intracellularis (L. intracellularis) is a major concern to the pig industry worldwide. Although 8.3 billion pigs are produced each year in China, few reports on the prevalence of L.intracellularis infection are available. The aim of the current study was to estimate the seroprevalence of L. intracellularis antibodies in intensive pig farms in China. RESULTS: A total of 1060 serum samples were collected from 14 commercial pig farms located throughout China. Animals from all age groups were sampled including pre-weaning piglets, weaners, fattening pigs, adult sows and boars. Antibodies against L. intracellularis were detected using a specific blocking ELISA. Of the 1060 serum samples, 602 were identified as positive using the ELISA test. The apparent seroprevalence of L. intracellularis seropositivity was 57% (95% CI 50 to 64%). The true prevalence (that is, prevalence corrected for the imperfect sensitivity and specificity of the testing method) was 77% (95% CI 70 to 83%). CONCLUSIONS: The highest true prevalence was observed in sows and boars, suggesting that within a herd these stock classes are a reservoir for infection. The prevalence of L. intracellularis seropositivity in local breed pigs was significantly less than that in imported breeds. A higher seroprevalence was found in pigs in herds in Central and Northern China, which may correspond to the greater use of the intensive production systems in these areas. We conclude that L. intracellularis is widely prevalent in commercial pigs in China

Priorization of River Restoration by Coupling Soil and Water Assessment Tool (SWAT) and Support Vector Machine (SVM) Models in the Taizi River Basin, Northern China

Identifying priority zones for river restoration is important for biodiversity conservation and catchment management. However, limited data due to the difficulty of field collection has led to research to better understand the ecological status within a catchment and develop a targeted planning strategy for river restoration. To address this need, coupling hydrological and machine learning models were constructed to identify priority zones for river restoration based on a dataset of aquatic organisms (i.e., algae, macroinvertebrates, and fish) and physicochemical indicators that were collected from 130 sites in September 2014 in the Taizi River, northern China. A process-based model soil and water assessment tool (SWAT) was developed to model the temporal-spatial variations in environmental indicators. A support vector machine (SVM) model was applied to explore the relationships between aquatic organisms and environmental indicators. Biological indices among different hydrological periods were simulated by coupling SWAT and SVM models. Results indicated that aquatic biological indices and physicochemical indicators exhibited apparent temporal and spatial patterns, and those patterns were more evident in the upper reaches compared to the lower reaches. The ecological status of the Taizi River was better in the flood season than that in the dry season. Priority zones were identified for different hydrological seasons by setting the target values for ecological restoration based on biota organisms, and the results suggest that hydrological conditions significantly influenced restoration prioritization over other environmental parameters. Our approach could be applied in other seasonal river ecosystems to provide important preferences for river restoration

Protocatechuic acid, a novel active substance against avian influenza virus H9N2 infection.

Influenza virus H9N2 subtype has triggered co-infection with other infectious agents, resulting in huge economical losses in the poultry industry. Our current study aims to evaluate the antiviral activity of protocatechuic acid (PCA) against a virulent H9N2 strain in a mouse model. 120 BALB/c mice were divided into one control group, one untreated group, one 50 mg/kg amantadine hydrochloride-treated group and three PCA groups treated 12 hours post-inoculation with 40, 20 or 10 mg/kg PCA for 7 days. All the infected animals were inoculated intranasally with 0.2 ml of a A/Chicken/Hebei/4/2008(H9N2) inoculum. A significant body weight loss was found in the 20 mg/kg and 40 mg/kg PCA-treated and amantadine groups as compared to the control group. The 14 day survivals were 94.4%, 100% and 95% in the PCA-treated groups and 94.4% in the amantadine hydrochloride group, compared to less than 60% in the untreated group. Virus loads were less in the PCA-treated groups compared to the amantadine-treated or the untreated groups. Neutrophil cells in BALF were significantly decreased while IFN-γ, IL-2, TNF-α and IL-6 decreased significantly at days 7 in the PCA-treated groups compared to the untreated group. Furthermore, a significantly decreased CD4+/CD8+ ratio and an increased proportion of CD19 cells were observed in the PCA-treated groups and amantadine-treated group compared to the untreated group. Mice administered with PCA exhibited a higher survival rate and greater viral clearance associated with an inhibition of inflammatory cytokines and activation of CD8+ T cell subsets. PCA is a promising novel agent against bird flu infection in the poultry industry

Associations of metabolic heterogeneity of obesity with frailty progression: Results from two prospective cohorts

Abstract Background Previous studies indicated that obesity would accelerate frailty progression. However, obesity is heterogeneous by different metabolic status. The associations of metabolic heterogeneity of obesity with frailty progression remain unclear. Methods A total of 6730 participants from the China Health and Retirement Longitudinal Study (CHARLS) and 4713 from the English Longitudinal Study of Ageing (ELSA) were included at baseline. Metabolic heterogeneity of obesity was evaluated based on four obesity and metabolic phenotypes as metabolically healthy normal weight (MHNW), metabolically unhealthy normal weight (MUNW), metabolically healthy overweight/obesity (MHOO), and metabolically unhealthy overweight/obesity (MUOO). Frailty status was assessed by the frailty index (FI) ranging from 0 to 100 and frailty was defined as FI ≥ 25. Linear mixed‐effect models were used to analyse the associations of metabolic heterogeneity of obesity with frailty progression. Results In the CHARLS, MUOO and MUNW presented the accelerated FI progression with additional annual increases of 0.284 (95% CI: 0.155 to 0.413, P < 0.001) and 0.169 (95% CI: 0.035 to 0.303, P = 0.013) as compared with MHNW. MHOO presented no accelerated FI progression (β: ‐0.011, 95% CI: −0.196 to 0.173, P = 0.904) as compared with MHNW. In the ELSA, the accelerated FI progression was marginally significant for MUOO (β: 0.103, 95% CI: −0.005 to 0.210, P = 0.061) and MUNW (β: 0.157, 95% CI: −0.011 to 0.324, P = 0.066), but not for MHOO (β: ‐0.047, 95% CI: −0.157 to 0.062, P = 0.396) in comparison with MHNW. The associations of MUOO and MUNW with the accelerated FI progression were stronger after excluding the baseline frail participants in both cohorts. The metabolic status changed over time. When compared with stable MHNW, participants who changed from MHNW to MUNW presented the accelerated FI progression with additional annual increases of 0.356 (95% CI: 0.113 to 0.599, P = 0.004) and 0.255 (95% CI: 0.033 to 0.477, P = 0.024) in the CHARLS and ELSA, respectively. The accelerated FI progression was also found in MHOO participants who transitioned to MUOO (CHARLS, β: 0.358, 95% CI: 0.053 to 0.663, P = 0.022; ELSA, β: 0.210, 95% CI: 0.049 to 0.370, P = 0.011). Conclusions Metabolically unhealthy overweight/obesity and normal weight, but not metabolically healthy overweight/obesity, accelerated frailty progression as compared with metabolically healthy normal weight. Regardless of obesity status, transitions from healthy metabolic status to unhealthy metabolic status accelerated frailty progression as compared with stable metabolically healthy normal weight. Our findings highlight the important role of metabolic status in frailty progression and recommend the stratified management of obesity based on metabolic status

The effect of PCA on the percentage of monocytes (A), neutrophils (B) and lymphocytes (C) in bronchial alveolar fluid (BALF) on day 7 following infection.

<p>A. ^## Indicates a statistically significant difference (P<0.01) in monocytes percentage when the untreated group was compared with the PCA- or amantadine-treated groups on day 7. ** Indicates a statistically significant difference (P<0.01) in monocytes percentage when the control group was compared with the virus-treated groups on day 7. B. ^## Indicates a statistically significant difference (P<0.01) in neutrophils percentage when the untreated control group was compared with the PCA- or amantadine-treated groups on day 7. ** Indicates a statistically significant difference (P<0.01) in neutrophils percentage when the control group was compared with the virus-treated groups on day 7. C. ^## Indicates a statistically significant difference (P<0.01) in lymphocytes percentage when the untreated group was compared with 10 mg/kg PCA-treated group on day 7. ** Indicates a statistically significant difference (P<0.01) in lymphocytes percentage when the control group was compared with the 10 or 20 mg/kg PCA-treated groups on day 7. *or^# Indicates a statistically significant difference (P<0.05) in lymphocytes or neutrophils percentage when the untreated group was compared with the control group on day 7.</p

The effect of PCA on T cell subsets and B cell in peripheral blood cells on days 7 and 14 of mice infected with influenza virus.

<p>A. ** Indicates a statistically significant difference (P<0.01) in the ratio of CD4+/CD8+ cells between the untreated group and all other groups on day 7, and a significant difference between PCA treated groups and the untreated group on day 14 (##, P<0.01; #, P<0.05). B. ** Indicates a statistically significant difference (P<0.01) in the proportions of CD19+ B cell subset between the untreated group and all other groups on day 7. The proportion of CD19+ B cell subset between PCA-treated groups and the untreated group on day 14 (##, P<0.01; #, P<0.05). C. *Indicates a statistical difference (P<0.05) in the proportions of CD3+ T cells between the treated or healthy groups and the untreated group on day 7. ##Indicates a statistically significant difference (P<0.01) in the proportions of CD3+ T cells when the 40 mg/kg PCA-treated group were compared to the untreated group on day 14.</p

The effects of PCA on lung index (A) and virus load post infection with influenza virus A/Chicken/Hebei/4/2008(H9N2) (B).

<p>A.*^# Indicates a statistically significant differences (P<0.05) in lung index between the untreated group and all other groups on day 7 (*) or day 14 (^#). ** Indicates a statistically significant differences (P<0.01) in lung index between the untreated group and all other groups on day 7 (**). B. * Indicates a statistically significant difference (P<0.05) in virus load when the amantadine-treated group was compared with PCA-treated group on day 7. ** Indicates a statistically significant difference (P<0.01) in virus load when the untreated group was compared with the PCA- or amantadine-treated groups on day 7.</p

Therapeutic efficacy of protocatechuic acid (PCA) in mice infected with influenza virus A/Chicken/Hebei/4/2008(H9N2).

<p>(A) The assessment of mouse body weight post administration with PCA or amantadine hydrochloride as compared to the untreated or control animals; (B) The mice survival rate post administration with 10, 20 and 40 mg/kg of PCA or 50 mg/kg of amantadine hydrochloride twice daily by oral gavages at 12 h intervals for 7 days. The untreated group was inoculated with H9N2 virus without any medication.</p