Therapeutic effect of Interleukin-4 and Interleukin-1 Receptor Antagonist in Actinobacillus pleuropneumoniae challenged pigs

Immunological stressors, in the form of clinical and sub-clinical disease are currently controlled using both prophylactic antibiotics in-feed, and therapeutic antibiotic treatment. Respiratory disease, primarily Actinobacillus pleuropneumoniae (App) infection, is recognised as a major factor causing reduced productivity in pigs. This thesis reports investigations into the use of novel immunomodulators in particular Interleukin 4 (IL-4) and Interleukin 1 receptor antagonist (IL-1ra) as alternatives to antibiotics to treat App infection. Immunological and molecular biological assays were used to investigate and accumulate data. An in vitro study undertaken to find potential anti-inflammatory substances, revealed that Interleukin 8 (IL-8) mRNA production stimulated by PMA or LPS in whole pigs' blood was suppressed by IL-4. IL-1ra also suppressed stimulated IL-8 mRNA production by heat killed App bacteria (KB) in vitro. An acute LPS challenge in pigs in vivo however, showed no variation in illness or weight loss between pigs treated prophylactically with anti-inflammatory substance (IL-4 and IL-1ra) and saline treated pigs. The use of plasmids as a delivery system for anti-inflammatory substance did not show promise since it did not enhance growth or prolong the expression of the substances in the pigs. However, in the chronic App challenge model IL-4 and IL-1ra administered prophylactically in vivo showed an ability to improve growth. The therapeutic administration of IL-4 and IL-1ra to App challenged pigs showed no difference in pigs' growth, regardless of the treatment or control administered. To conclude, IL-4 and IL-1ra showed promise when administered prophylactically and improved growth and abrogated disease under conditions of App challenge. However when IL-4 and IL-1ra where administered therapeutically they did not perform as well. Moreover these compounds have potential as a commercial application to reduce the growth reduction caused by disease such as App

The Corporate Social Responsibility and Firms' Financial Performance: Evidence from Financial Sector of Pakistan

Competitiveness of financial sector has increased manifold and the issue of corporate social responsibility (CSR) has become an indispensable concern parallel to concentrating on profitability enhancement. Businesses are consider as social units, they have to serve stakeholders, and tend to execute CSR on priority basis and subsequent disclosure as well. Unhealthy CSR policies may cause externalities and eventual relinquished customers. The main purpose of study is to shed light on the impact of corporate social responsibility on financial performance of banking sector of Pakistan, using a sample of 30 commercial banks listed with Pakistan stock exchange (PSX) for the period of 10 years from 2006 to 2015, selected based upon market capitalization. We applied pooled regression models to investigate the impact of CSR on financial performance. Empirical findings signify the robustness of pooled model that documented a positive and significant impact of CSR on ROA, ROE and EPS. This premise holds that CSR has positive and significant impact on FP of selected commercial banks of Pakistan. Based upon key findings, this study postulates CSR phenomenon is consider as an essential growth element and financial performance-boosting tool by banking industry of Pakistan. Eventually, mainstream of the studies on CSR are in context of well-established companies and nations, however, developing nations are least emphasized, thus the findings of this study greatly contribute in body of knowledge as well as offer pivotal implications for policy makers and governance of financial sector. Keywords: Corporate social responsibility (CSR), financial performance, financial sector, Pooled regression JEL Classifications: M14; L25; O1

The Impact of Stock Market Performance on Foreign Portfolio Investment in China

The research is aimed at investigating the impact of stock market performance and inflation on foreign portfolio investment (FPI) in China. For this purpose, time series quarterly data from 2007Q1 to 2015Q4 is used. On the basis of stationarity results, ARDL model is used to examine the impact of the stock market prices and inflation on FPI. The results show that there is significant positive impact of stock market performance on the FPI, whereas inflation is found to be negatively associated with the FPI. The study also reveals that some historical events like Asian financial crisis of 2008, and the Shanghai Composite Stock Index crash of 2015, significantly affected the foreign portfolio investment in China. The investors should consider these two factors while investing in foreign financial markets. Keywords: Stock Market Performance, Inflation, FPI, China JEL Classifications: F21, G11, O16, P4

Maternal anaemia and the risk of postpartum haemorrhage: a cohort analysis of data from the WOMAN-2 trial

Background: Worldwide, more than half a billion women of reproductive age are anaemic. Each year, about 70 000 women who give birth die from postpartum haemorrhage. Almost all deaths are in low-income or middle-income countries. We examined the association between anaemia and the risk of postpartum haemorrhage. Methods: We did a prospective cohort analysis of data from the World Maternal Antifibrinolytic-2 (WOMAN-2) trial. This trial enrols women with moderate or severe anaemia giving birth vaginally in hospitals in Pakistan, Nigeria, Tanzania, and Zambia. Hospitals in each country where anaemia in pregnancy is common were identified from a network established during previous obstetric trials. Women who were younger than 18 years without permission provided by a guardian, had a known tranexamic acid allergy, or developed postpartum haemorrhage before the umbilical cord was cut or clamped were excluded from the study. Prebirth haemoglobin, the exposure, was measured after hospital arrival and just before giving birth. Postpartum haemorrhage, the outcome, was defined in three ways: (1) clinical postpartum haemorrhage (estimated blood loss ≥500 mL or any blood loss sufficient to compromise haemodynamic stability); (2) WHO-defined postpartum haemorrhage (estimated blood loss of at least 500 mL); and (3) calculated postpartum haemorrhage (calculated estimated blood loss of ≥1000 mL). Calculated postpartum haemorrhage was estimated from the peripartum change in haemoglobin concentration and bodyweight. We used multivariable logistic regression to examine the association between haemoglobin and postpartum haemorrhage, adjusting for confounding factors. Findings: Of the 10 620 women recruited to the WOMAN-2 trial between Aug 24, 2019, and Nov 1, 2022, 10 561 (99·4%) had complete outcome data. 8751 (82·9%) of 10 561 women were recruited from hospitals in Pakistan, 837 (7·9%) from hospitals in Nigeria, 525 (5·0%) from hospitals in Tanzania, and 448 (4·2%) from hospitals in Zambia. The mean age was 27·1 years (SD 5·5) and mean prebirth haemoglobin was 80·7 g/L (11·8). Mean estimated blood loss was 301 mL (SD 183) for the 8791 (83·2%) women with moderate anaemia and 340 mL (288) for the 1770 (16·8%) women with severe anaemia. 742 (7·0%) women had clinical postpartum haemorrhage. The risk of clinical postpartum haemorrhage was 6·2% in women with moderate anaemia and 11·2% in women with severe anaemia. A 10 g/L reduction in prebirth haemoglobin increased the odds of clinical postpartum haemorrhage (adjusted odds ratio [aOR] 1·29 [95% CI 1·21–1·38]), WHO-defined postpartum haemorrhage (aOR 1·25 [1·16–1·36]), and calculated postpartum haemorrhage (aOR 1·23 [1·14–1·32]). 14 women died and 68 either died or had a near miss. Severe anaemia was associated with seven times higher odds of death or near miss (OR 7·25 [95% CI 4·45–11·80]) than was moderate anaemia. Interpretation: Anaemia is strongly associated with postpartum haemorrhage and the risk of death or near miss. Attention should be given to the prevention and treatment of anaemia in women of reproductive age. Funding: The WOMAN-2 trial is funded by Wellcome and the Bill & Melinda Gates Foundation

Service Quality of Higher Education in Pakistan

This paper attempts to evaluate the perceptions and expectations of students in higher education students with regard to service quality. Forming the basis of the empirical investigation, the data was collected from five focus groups using two different service quality measurement instruments: service quality (SERVQUAL), and service performance (SERVPERF). 160 questionnaires were returned out of 200. Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM) were used to analyze the data. The results indicated that SERVQUAL and SERVPERF were both valid and reliable indicators of university service quality in Pakistan and SERVPERF was only significant to student satisfaction

Exploring genetic mechanisms of Staphylococcus aureus keratitis

Staphylococcus aureus or “golden-staph” is the leading cause of hospital acquired infections, medical device related infections and diabetic foot ulcers. Multi-drug resistant strains and methicillin-resistant-S. aureus (MRSA) are a particular problem in hospital. Staphylococcus aureus is a leading cause of microbial keratitis, characterized by severe pain, blurred vision, an epithelial defect, infiltration and an anterior chamber reaction and can result in blindnes. Treatment of S. aureus corneal infections is extremely labour-intensive and usually involves the application of antibiotic drops every half-hour for 48 hours. As the prevalence of antibiotic resistance is increasing in S. aureus isolated from nosocomial and community-acquired infections such as MK the development of new therapies is paramount. The aim of this study was to identify virulence factors contribute to the pathology of S. aureus keratitis by comparing two different isolates of Staphylococcus aureus, a virulent clinical corneal ulcer isolate (Staph 38) and a less virulent laboratory strain (S. aureus 8325-4). Initially, we identified an increase in the expression of thirteen extracellular proteins and eight cell-associated proteins was increased 3-fold or greater in the clinical isolate Staph 38 compared to the laboratory strain 8325-4. Four of these proteins were homologous to known S. aureus virulence factors; fibronectin binding protein (FnBP), staphopain, glyceraldehyde-3-phosphate dehydrogenase A2 and extracellular adherence protein. In addition, two putative proteins which have been tentatively identified as cell wall surface anchor protein and S. aureus surface protein G were found in abundance in Staph 38. Alterations in the expression of the four known virulence factors were confirmed by the use of binding assays to specific ligands. The clinical isolate demonstrated an increase in the ability to bind all ligands. Further investigation on these factors suggested some unique mechanisms by which S. aureus may promote its colonisation of the cornea such as the effects of staphopain on the levels of surface FnBP. While virulence factors such as GAPDH do not appear to offer useful points for therapeutic interventions and others such as SasG, Q6G7Y, Eap, FNBP and staphopain do. This knowledge has contributed to our understanding function of bacterial factors of S. aureus during corneal infection with the serious and potentially blinding S. aureus. Overall, from the results obtained in this study, several virulence factors were identified in abundance in the clinical isolate Staph 38 and their effect on the outcome of S. aureus keratitis infection was established

New ferrocene integrated amphiphilic guanidines: Synthesis, spectroscopic elucidation, DFT calculation and in vitro α-amylase and α-glucosidase inhibition combined with molecular docking approach

Three N, N’, N″-trisubstituted ferrocenyl guanidines (MG-10, MG-12 and MG-14) were synthesized, characterized by several analytical methods such as FT-IR, 1H and 13C NMR, elemental analysis and UV–visible spectroscopy. These compounds have long chain aliphatic groups therefore their aliphatic nature has been evaluated by determining their critical micelle concentration (CMC). CMC point decreases from 0.036 mM to 0.013 mM with increase in the aliphatic chain length. The quantum mechanical parameters such as the energy of frontier molecular orbitals (EHOMO and ELUMO) and the Mulliken charge distribution on the optimized structures were determined using a DFT/B3LYP method combined with the 6-31G (d,p) basis set in the gas phase. The in vitro antidiabetic activity of synthesized compounds showed that MG-12 has IC50value 23.10 μg/mL against α-amylase while MG-10 has IC50value 27.32 μg/mL against α-glucosidase with the respective standard Acarbose (IC50value 20.12 μg/mL). Theoretical docking analysis demonstrated that MG-10 and MG-12 interacted with α-amylase by 3 types of interaction, including hydrogen bonds, hydrophobic interactions and electrostatic interactions

Improving Mispronunciation Detection of Arabic Words for Non-Native Learners Using Deep Convolutional Neural Network Features

Computer-Aided Language Learning (CALL) is growing nowadays because learning new languages is essential for communication with people of different linguistic backgrounds. Mispronunciation detection is an integral part of CALL, which is used for automatic pointing of errors for the non-native speaker. In this paper, we investigated the mispronunciation detection of Arabic words using deep Convolution Neural Network (CNN). For automated pronunciation error detection, we proposed CNN features-based model and extracted features from different layers of Alex Net (layers 6, 7, and 8) to train three machine learning classifiers; K-nearest neighbor (KNN), Support Vector Machine (SVM) and Random Forest (RF). We also used a transfer learning-based model in which feature extraction and classification are performed automatically. To evaluate the performance of the proposed method, a comprehensive evaluation is provided on these methods with a traditional machine learning-based method using Mel Frequency Cepstral Coefficients (MFCC) features. We used the same three classifiers KNN, SVM, and RF in the baseline method for mispronunciation detection. Experimental results show that with handcrafted features, transfer learning-based method and classification based on deep features extracted from Alex Net achieved an average accuracy of 73.67, 85 and 93.20 on Arabic words, respectively. Moreover, these results reveal that the proposed method with feature selection achieved the best average accuracy of 93.20% than all other methods