Expression of short chain fatty acid receptors and pro-inflammatory cytokines in utero-placental tissues is altered in cows developing retention of fetal membranes

Introduction

Retention of fetal membranes (RFM) is an economically important condition in dairy cattle disturbing the health and production in affected animals. In spite of extensive research, pathogenesis for RFM and identification of a predictive marker for the condition still remains elusive. Since expulsion of fetal membranes in an inflammatory process, studying the expression of inflammatory molecules is expected to give an idea about the pathogenesis of RFM.

Methods

Expression of pro-inflammatory cytokines, short chain fatty acid (SCFA) receptors and adhesion molecules was studied using qRT-PCR in the utero-placental tissues obtained from the cows that expelled fetal membranes normally (n = 12) and from the cows that developed RFM (n = 12). Concentrations of SCFAs were estimated in the utero-placental tissues using Gas Chromatography.

Results

The concentration of butyrate in the utero-placental tissue extract was 3–4 times lower, and GPR41 and GPR43 mRNA expression was 7.7–10.0 and 3.4–4.4 folds lower (p < 0.05) in cows that developed RFM compared to those that expelled the fetal membranes normally. The expression of IL-1, IL-6, IL-8, TNF-α, ICAM and PECAM was higher (p < 0.05) in the cows that normally expelled the fetal membranes compared to those that developed RFM.

Discussion

Since a clear association of butyrate levels, expression of pro-inflammatory cytokines, adhesion molecules and SCFAs receptors was observed with expulsion of fetal membranes, modulating the levels of these molecules prior to parturition might help in reducing the incidence of RFM in cows.

Conclusion

Inflammatory response is essential for normal expulsion of fetal membranes and that inadequate or altered expression of pro-inflammatory cytokines, adhesion molecules and SCFA receptors is associated with RFM in cows.     

Protective effect of curcumin on cypermethrin-induced oxidative stress in Wistar rats

The aim of present study was to investigate the protective effect of curcumin on cypermethrin-induced changes in blood biochemical markers and tissue antioxidant enzyme in rats. Rats were divided into six groups of six each: group I used as control and II and III groups were used as vehicle control. While, groups IV, V and VI were orally treated with curcumin (100 mg/kg body weight), cypermethrin (25 mg/kg body weight) and cypermethrin plus curcumin, respectively for 28 days. Serum biochemical markers were measured in the serum, and the levels of lipid peroxidation and antioxidant enzyme activity were determined in the liver, kidney and brain. Cypermethrin administration caused elevated level of blood biochemical markers in serum and lipid peroxidation in liver, kidney and brain. While the activities of non-enzymatic and enzymatic antioxidants levels were decreased except superoxide dismutase in liver, kidney and brain tissues. The presence of curcumin with cypermethrin significantly decreased the blood biochemical markers and lipid peroxidation but significantly increased the reduced glutathione, catalase and glutathione peroxidase level and preserved the normal histological architecture of the liver, kidney and brain. Our results indicate that curcumin can be potent protective agent against cypermethrin-induced biochemical alterations and oxidative damage in rats.     

Repeated preexposure or coexposure to arsenic differentially alters acetaminophen‐induced oxidative stress in rat kidney

Acetaminophen (AP) is a widely used, cheap, and over‐the‐counter nonsteroidal anti‐inflammatory drug. Its toxicity depends on the cytochrome P‐450 (CYP)‐mediated oxidation to the toxic metabolite N‐acetyl‐p‐benzoquinoneimine. On the other hand, arsenic, a global groundwater and environmental contaminant of major public health concern, decreases hepatic CYP content and its dependent monoxygenase activities. We hypothesized that arsenic exposure would reduce the AP toxicity. Our aim was to evaluate the effects of repeated preexposure or coexposure to arsenic on the oxidative stress induced by a single or repeated oral administration of AP in rat kidney and its possible relationship with the effects of arsenic on certain antioxidants. Rats were exposed to arsenic through drinking water at 25 ppm for 28 days. The dosages of AP used for a single administration after arsenic preexposure for 28 days were 420 and 1000 mg kg^?1, while for daily concurrent administration with arsenic for 28 days were 105 and 420 mg kg^?1 body weight. AP increased lipid peroxidation (LPO) in rat kidney where its acute administration caused more LPO than its subacute dosing. Repeated arsenic exposure differentially altered the AP‐induced LPO. Arsenic preexposure antagonized LPO induced by the acute AP administration; in contrast, arsenic coexposure aggravated the repeated dose (AP)‐mediated LPO. Arsenic‐mediated alterations in renal sensitivity to LPO did not appear to be linked to the antioxidants such as reduced glutathione, superoxide dismutase, catalase, glutathione peroxidase, and glutathione reductase; nor could it be related to glutathione‐S‐transferase activity. The results indicated that repeated arsenic preexposure decreased susceptibility of rat kidney to acute AP‐mediated oxidative stress; on the contrary, its coexposure rendered the rat kidney more vulnerable to oxidative stress induced by the repeated dosing of AP. © 2009 Wiley Periodicals, Inc. Environ Toxicol, 2011.     

Pathoscope: Species identification and strain attribution with unassembled sequencing data

Emerging next-generation sequencing technologies have revolutionized the collection of genomic data for applications in bioforensics, biosurveillance, and for use in clinical settings. However, to make the most of these new data, new methodology needs to be developed that can accommodate large volumes of genetic data in a computationally efficient manner. We present a statistical framework to analyze raw next-generation sequence reads from purified or mixed environmental or targeted infected tissue samples for rapid species identification and strain attribution against a robust database of known biological agents. Our method, Pathoscope, capitalizes on a Bayesian statistical framework that accommodates information on sequence quality, mapping quality, and provides posterior probabilities of matches to a known database of target genomes. Importantly, our approach also incorporates the possibility that multiple species can be present in the sample and considers cases when the sample species/strain is not in the reference database. Furthermore, our approach can accurately discriminate between very closely related strains of the same species with very little coverage of the genome and without the need for multiple alignment steps, extensive homology searches, or genome assembly—which are time-consuming and labor-intensive steps. We demonstrate the utility of our approach on genomic data from purified and in silico “environmental” samples from known bacterial agents impacting human health for accuracy assessment and comparison with other approaches.The accurate and rapid identification of species and strains of pathogens is an essential component of biosurveillance from both human health and biodefense perspectives (Vaidyanathan 2011). For example, misidentification was among the issues that resulted in a 3-wk delay in accurate diagnosis of the recent outbreak of hemorrhagic Escherichia coli being due to strain O104:H4, resulting in over 3800 infections across 13 countries in Europe with 54 deaths (Frank et al. 2011). The most accurate diagnostic information, necessary for species identification and strain attribution, comes from the most refined level of biological data—genomic DNA sequences (Eppinger et al. 2011). Advances in DNA-sequencing technologies allows for the rapid collection of extraordinary amounts of genomic data, yet robust approaches to analyze this volume of data are just developing, from both statistical and algorithmic perspectives.Next-generation sequencing approaches have revolutionized the way we collect DNA sequence data, including for applications in pathology, bioforensics, and biosurveillance. Given a particular clinical or metagenomic sample, our goal is to identify the specific species, strains, or substrains present in the sample, as well as accurately estimate the proportions of DNA originating from each source genome in the sample. Current approaches for next-gen sequencing usually have read lengths between 25 and 1000 bp; however, these sequencing technologies include error rates that vary by approach and by samples. Such variation is typically less important for species identification given the relatively larger genetic divergences among species than among individuals within species. But for strain attribution, sequencing error has the potential to swamp out discriminatory signal in a data set, necessitating highly sensitive and refined computational models and a robust database for both species identification and strain attribution.Current methods for classifying metagenomic samples rely on one or more of three general approaches: composition or pattern matching (McHardy et al. 2007; Brady and Salzberg 2009; Segata et al. 2012), taxonomic mapping (Huson et al. 2007; Meyer et al. 2008; Monzoorul Haque et al. 2009; Gerlach and Stoye 2011; Patil et al. 2012; Segata et al. 2012), and whole-genome assembly (Kostic et al. 2011; Bhaduri et al. 2012). Composition and pattern-matching algorithms use predetermined patterns in the data, such as taxonomic clade markers (Segata et al. 2012), k-mer frequency, or GC content, often coupled with sophisticated classification algorithms such as support vector machines (McHardy et al. 2007; Patil et al. 2012) or interpolated Markov Models (Brady and Salzberg 2009) to classify reads to the species of interest. These approaches require intensive preprocessing of the genomic database before application. In addition, the classification rule and results can often change dramatically depending on the size and composition of the genome database.Taxonomy-based approaches typically rely on a “lowest common ancestor” approach (Huson et al. 2007), meaning that they identify the most specific taxonomic group for each read. If a read originates from a genomic region that shares homology with other organisms in the database, the read is assigned to the lowest taxonomic group that contains all of the genomes that share the homologous region. These methods are typically highly accurate for higher-level taxonomic levels (e.g., phylum and family), but experience reduced accuracy at lower levels (e.g., species and strain) (Gerlach and Stoye 2011). Furthermore, these approaches are not informative when the reads originate from one or more species or strains that are closely related to each other or different organisms in the database. In these cases, all of the reads can be reassigned to higher-level taxonomies, thus failing to identify the specific species or strains contained in the sample.Assembly-based algorithms can often lead to the most accurate strain identification. However, these methods also require the assembly of a whole genome from a sample, which is a computationally difficult and time-consuming process that requires large numbers of reads to achieve an adequate accuracy—often on the order of 50–100× coverage of the target genome (Schatz et al. 2010). Given current sequencing depths, obtaining this level of coverage is usually possible for purified samples, but coverage levels may not be sufficient for mixed samples or in multiplexed sequencing runs. Assembly approaches are further complicated by the fact that data collection at a crime scene or hospital might include additional environmental components in the biological sample (host genome or naturally occurring bacterial and viral species), thus requiring multiple filtering and alignment steps in order to obtain reads specific to the pathogen of interest.Here we describe an accurate and efficient approach to analyze next-generation sequence data for species identification and strain attribution that capitalizes on a Bayesian statistical framework implemented in the new software package Pathoscope v1.0. Our approach accommodates information on sequence quality, mapping quality, and provides posterior probabilities of matches to a known database of reference genomes. Importantly, our approach incorporates the possibility that multiple species can be present in the sample or that the target strain is not even contained within the reference database. It also accurately discriminates between very closely related strains of the same species with much less than 1× coverage of the genome and without the need for sequence assembly or complex preprocessing of the database or taxonomy. No other method in the literature can identify species or substrains in such a direct and automatic manner and without the need for large numbers of reads. We demonstrate our approach through application to next-generation DNA sequence data from a recent outbreak of the hemorrhagic E. coli (O104:H4) strain in Europe (Frank et al. 2011; Rohde et al. 2011; Turner 2011) and on purified and in silico mixed samples from several other known bacterial agents that impact human health. Software and data examples for our approach are freely available for download at https://sourceforge.net/projects/pathoscope/.     

Matrigel coated polydimethylsiloxane based microfluidic devices for studying metastatic and non-metastatic cancer cell invasion and migration

Three-dimensional (3-D) extracellular matrices (ECM) allow complex biochemical and biophysical interactions between cells and matrices. Unlike 2-D systems, 3-D models provide a better representation of the micro and local environments in living tissues for facilitating the physiological study of cell migration. Here, we report a microfluidic device based on polydimethylsiloxane (PDMS) for monitoring 3-D cell migration across ECM-coated microgaps with real-time light microscopy. We tracked the migration of the invasive MDA-MB-231 (mammary carcinoma) cells and mapped out their migration paths. It enabled us to quantify the percentage of migrated cells as well as migration information of individual cells. This wide spectrum of data acquisition is vital for elucidating the migration capabilities of different type of cells and to understand the basic mechanism involved in cancer metastasis.     

Tumor Preventive Efficacy of Emodin in 7,12-Dimethylbenz[a]Anthracene-Induced Oral Carcinogenesis: a Histopathological and Biochemical Approach

The aim of the present study is to focus the chemopreventive potential of Emodin during 7,12-dimethylbenz[a]anthracene (DMBA) induced hamster buccal pouch carcinogenesis. Tumors were developed in the buccal pouches of golden Syrian hamsters by painting with 0.5% DMBA thrice a week for 14 weeks. The status of lipid peroxidation, antioxidants and detoxification agents were utilized as biochemical endpoints and the expression pattern of apoptotic proteins was employed as molecular endpoints in addition to the histopathological studies, to substantiate the anticancer potential of Emodin. Hamsters treated with DMBA + Emodin revealed mild to moderate precancerous lesions such as hyperplasia and dysplasia whereas 100% tumor formation was noticed in hamsters treated with DMBA alone. Also, Emodin treatment modulated the status of lipid peroxidation, antioxidants, phase I and II detoxification agents and apoptotic proteins in favor of the inhibition/reversal/suppression of the oral tumorigenesis in DMBA treated hamsters. The present study thus concludes that the chemopreventive potential of Emodin relies on its pro-apoptotic and antioxidant efficacy during DMBA induced hamster buccal pouch carcinogenesis.     

Two new flavonoids from Centella asiatica (Linn.)

Two new flavonoids named castilliferol 1 and castillicetin 2, as well as a known compound, isochlorogenic acid 3, were isolated from the whole plant of Centella asiatica. Isolates 1 and 2 exhibited good antioxidant activity using 2,2-diphenyl-1-picryl hydrazyl radical solution with IC₅₀ values of 23.10 and 13.30, respectively. The structures of these isolates were determined by analytical and spectral data, including 1-D and 2-D NMR spectra.     

Effects of piperine on testis of albino rats.

Piperine was administered to mature male albino rats at doses of 5 and 10 mg/kg body weight, p.o., respectively, for 30 days. Only a 10 mg dose of piperine treatment caused a significant reduction in the weights of testis and accessory sex organs. Histological studies revealed that piperine at a 5 mg dose caused partial degeneration of germ cell types, whereas at a 10 mg dose, it caused severe damage to the seminiferous tubule, decrease in seminiferous tubular and Leydig cell nuclear diameter and desquamation of spermatocytes and spermatids. Correlated to the structural changes, a fall in caput and cauda epididymal sperm concentrations was also evident. A 10 mg dose of piperine also caused a marked increase in serum gonadotropins and a decrease in intratesticular testosterone concentration, despite normal serum testosterone titres.     

Flexible Laryngoscopy in Management of Congenital Stridor

The incidence of congenital stridor is on rise due to improved neonate and infant survival rate. The gold standard investigation for evaluation of stridor is rigid laryngotracheobronchoscopy, but this is invasive and requires general anesthesia. Flexible fibreoptic laryngoscopy, a relatively simple and less invasive procedure can be done under topical anaesthesia for evaluation of stridor. In this study, we have presented our experience of flexible laryngoscopy in children with congenital stridor, their results and management. Laryngomalacia was the commonest cause of stridor accounting for 80% of cases. 15% (6) patients required tracheostomy for relieving airway obstruction and 22.5% (9) patients required a definitive surgical procedure for correcting the cause. Flexible laryngoscopy is safe and gives a comprehensive analysis of airway including its dynamic functions. We also recommend flexible laryngoscopy as a frontline investigation for evaluation of stridor.     

Effects of acetaminophen on reactive oxygen species and nitric oxide redox signaling in kidney of arsenic-exposed rats

We examined whether acetaminophen could alter renal oxidative stress induced by arsenic; also whether withdrawal of acetaminophen treatment can increase susceptibility of kidney to arsenic toxicity. Acetaminophen (400 and 1600 mg/kg) was co-administered orally to rats for 3 days after preexposure to arsenic (25 ppm) for 28 days (Phase-I) and thereafter, acetaminophen was withdrawn, but arsenic exposure was continued for another 28 days (Phase-II). Acetaminophen enhanced arsenic-induced lipid peroxidation, GSH depletion and ROS production and further decreased superoxide dismutase, catalase, glutathione peroxidase and glutathione reductase activities. Increased peroxidation did not alter kidney weight, but increased serum urea nitrogen and creatinine. Arsenic did not alter basal, iNOS-mediated NO production or iNOS expression. Arsenic decreased cNOS-mediated NO release and eNOS expression in Phase-II. Acetaminophen increased their expressions and NO production in Phase-I. In Phase-II, arsenic-mediated effects on NO remained mostly unaffected with acetaminophen. Results reveal that acetaminophen enhanced the risk of arsenic-mediated oxidative stress in kidney. Discontinuation of acetaminophen administration also increased the susceptibility of kidney to nephrotoxic effect of arsenic. It appeared ROS were primarily responsible for oxidative stress in both the phases. NO may have a minor role in Phase-I, but does not contribute to redox signaling mechanism in Phase-II.