Epidemiology, distribution and identification of ticks on livestock in Pakistan

Background: Ticks are ectoparasites that transmit a variety of pathogens that cause many diseases in livestock which can result in skin damage, weight loss, anemia, reduced production of meat and milk, and mortality. Aim: The aim of this study was to identify tick species and the distribution on livestock hosts (sheep, goat, dairy cattle, and buffalo) of Punjab, Khyber Pakhtunkhwa Province and Islamabad from October 2019 to November 2020. Materials and Methods: Surveillance was performed to calculate the prevalence of ticks on livestock. Tick prevalence data (area, host, breed, gender, age, and seasonal infestation rate) was recorded and analyzed. Results: A total of 2080 animals were examined from selected farms, and, of these, 1129 animals were tick-infested. A total of 1010 male tick samples were identified to species using published keys. Haemaphysalis punctata, Haemaphysalis sulcata, Hyalomma anatolicum, Hyalomma detritum, Hyalomma dromedarii, Hyalomma excavatum, Hyalomma marginatum, Hyalomma rufipes, Rhipicephalus decoloratus Rhipicephalus microplus, and Rhipicephalus sanguineus were collected from goats, sheep, buffalo, and cattle. The overall rates of tick infestation on livestock were 34.83% (buffalo), 57.11% (cattle), 51.97% (sheep) and 46.94% (goats). Within each species, different breeds demonstrated different proportions of infestation. For cattle breeds, infestation proportions were as follows: Dhanni (98.73%), Jersey (70.84%) and the Australian breed of cattle (81.81%). The Neeli Ravi breed (40%) of buffalo and the Beetal breed (57.35%) of goats were the most highly infested for these species. Seasonally, the highest prevalence of infestation (76.78%) was observed in summer followed by 70.76% in spring, 45.29% in autumn, and 20% in winter. The prevalence of tick infestation in animals also varied by animal age. In goats, animals aged 4−6 years showed the highest prevalence (90%), but in cattle, the prevalence of ticks was highest (68.75%) in 6 months−1-year-old animals. 1−3 years old buffalo (41.07%) and 6 months−1 year sheep (65.78%) had the highest prevalence rate. Females had significantly higher infestation rates (61.12%, 55.56% and 49.26%, respectively) in cattle, sheep, and goats. In buffalo, males showed a higher prevalence (38.46%) rate. Conclusions: This study showed tick diversity, infestation rate, and numerous factors (season, age, and gender of host) influencing tick infestation rate in different breeds of cattle, sheep, goats, and buffalo in Punjab Province, Khyber Pakhtunkhwa Province, and Islamabad, Pakistan. Higher tick burdens and rates of tick-borne disease reduce production and productivity in animals. Understanding tick species’ prevalence and distribution will help to develop informed control measures

Evaluating predictive pharmacogenetic signatures of adverse events in colorectal cancer patients treated with fluoropyrimidines

The potential clinical utility of genetic markers associated with response to fluoropyrimidine treatment in colorectal cancer patients remains controversial despite extensive study. Our aim was to test the clinical validity of both novel and previously identified markers of adverse events in a broad clinical setting. We have conducted an observational pharmacogenetic study of early adverse events in a cohort study of 254 colorectal cancer patients treated with 5-fluorouracil or capecitabine. Sixteen variants of nine key folate (pharmacodynamic) and drug metabolising (pharmacokinetic) enzymes have been analysed as individual markers and/or signatures of markers. We found a significant association between TYMP S471L (rs11479) and early dose modifications and/or severe adverse events (adjusted OR = 2.02 [1.03; 4.00], p = 0.042, adjusted OR = 2.70 [1.23; 5.92], p = 0.01 respectively). There was also a significant association between these phenotypes and a signature of DPYD mutations (Adjusted OR = 3.96 [1.17; 13.33], p = 0.03, adjusted OR = 6.76 [1.99; 22.96], p = 0.002 respectively). We did not identify any significant associations between the individual candidate pharmacodynamic markers and toxicity. If a predictive test for early adverse events analysed the TYMP and DPYD variants as a signature, the sensitivity would be 45.5 %, with a positive predictive value of just 33.9 % and thus poor clinical validity. Most studies to date have been under-powered to consider multiple pharmacokinetic and pharmacodynamic variants simultaneously but this and similar individualised data sets could be pooled in meta-analyses to resolve uncertainties about the potential clinical utility of these markers

Targeted knock-down of miR21 primary transcripts using snoMEN vectors induces apoptosis in human cancer cell lines

We have previously reported an antisense technology, 'snoMEN vectors', for targeted knock-down of protein coding mRNAs using human snoRNAs manipulated to contain short regions of sequence complementarity with the mRNA target. Here we characterise the use of snoMEN vectors to target the knock-down of micro RNA primary transcripts. We document the specific knock-down of miR21 in HeLa cells using plasmid vectors expressing miR21-targeted snoMEN RNAs and show this induces apoptosis. Knock-down is dependent on the presence of complementary sequences in the snoMEN vector and the induction of apoptosis can be suppressed by over-expression of miR21. Furthermore, we have also developed lentiviral vectors for delivery of snoMEN RNAs and show this increases the efficiency of vector transduction in many human cell lines that are difficult to transfect with plasmid vectors. Transduction of lentiviral vectors expressing snoMEN targeted to pri-miR21 induces apoptosis in human lung adenocarcinoma cells, which express high levels of miR21, but not in human primary cells. We show that snoMEN-mediated suppression of miRNA expression is prevented by siRNA knock-down of Ago2, but not by knock-down of Ago1 or Upf1. snoMEN RNAs colocalise with Ago2 in cell nuclei and nucleoli and can be co-immunoprecipitated from nuclear extracts by antibodies specific for Ago2

Investigation of flexural properties of epoxy composite by utilizing graphene nanofillers and natural hemp fibre reinforcement

This study aims to determine the optimum reinforcement required to attain the best combination of flexural strength of modified green composites (graphene oxide + hemp fibre reinforced epoxy composites) for potential use in structural applications. An attempt was also made for the combination of graphene and hemp fibres to enhance load-bearing ability. The infusion of hemp and graphene was made by the weight of the base matrix (epoxy composite). Results showed that graphene reinforcement at 0.4 wt.% of matrix showed load-sustaining capacity of 0.76 kN or 760 MPa. In the case of hemp fibre reinforcement at 0.2 wt.% of the matrix, infusion showed enhanced load-bearing ability (0.79 kN or 790 MPa). However, the combination of graphene (0.1 wt.% graphene nanofillers) and hemp (5 wt.% hemp fibre) indicated a load-sustaining ability of 0.425 kN or 425 MPa, whereas maximum deflection was observed for specimen with hemp 7.5 % + graphene 0.2 % with 1.9 mm. Graphene addition to the modified composites in combination with natural fibres showed promising results in enhancing the mechanical properties under study. Moreover, graphene-modified composites exhibited higher thermal resistance compared to natural fibre reinforced composites. However, when nanofiller reinforcement exceeded a threshold value, the composites exhibited reduced flexural strength as a result of nanofiller agglomeration

Financial crises and the attainment of the SDGs: an adjusted multidimensional poverty approach

This paper analyses the impact of financial crises on the Sustainable Development Goal of eradicating poverty. To do so, we develop an adjusted Multidimensional Poverty Framework (MPF) that includes 15 indicators that span across key poverty aspects related to income, basic needs, health, education and the environment. We then use an econometric model that allows us to examine the impact of financial crises on these indicators in 150 countries over the period 1980–2015. Our analysis produces new estimates on the impact of financial crises on poverty’s multiple social, economic and environmental aspects and equally important captures dynamic linkages between these aspects. Thus, we offer a better understanding of the potential impact of current debt dynamics on Multidimensional Poverty and demonstrate the need to move beyond the boundaries of SDG1, if we are to meet the target of eradicating poverty. Our results indicate that the current financial distress experienced by many low-income countries may reverse the progress that has been made hitherto in reducing poverty. We find that financial crises are associated with an approximately 10% increase of extreme poor in low-income countries. The impact is even stronger in some other poverty aspects. For instance, crises are associated with an average decrease of government spending in education by 17.72% in low-income countries. The dynamic linkages between most of the Multidimensional Poverty indicators, warn of a negative domino effect on a number of SDGs related to poverty, if there is a financial crisis shock. To pre-empt such a domino effect, the specific SDG target 17.4 on attaining long-term debt sustainability through coordinated policies plays a key role and requires urgent attention by the international community

Enhanced snoMEN Vectors Facilitate Establishment of GFP–HIF-1α Protein Replacement Human Cell Lines

The snoMEN (snoRNA Modulator of gene ExpressioN) vector technology was developed from a human box C/D snoRNA, HBII-180C, which contains an internal sequence that can be manipulated to make it complementary to RNA targets, allowing knock-down of targeted genes. Here we have screened additional human nucleolar snoRNAs and assessed their application for gene specific knock-downs to improve the efficiency of snoMEN vectors. We identify and characterise a new snoMEN vector, termed 47snoMEN, that is derived from box C/D snoRNA U47, demonstrating its use for knock-down of both endogenous cellular proteins and G/YFP-fusion proteins. Using multiplex 47snoMEM vectors that co-express multiple 47snoMEN in a single transcript, each of which can target different sites in the same mRNA, we document >3-fold increase in knock-down efficiency when compared with the original HBII-180C based snoMEN. The multiplex 47snoMEM vector allowed the construction of human protein replacement cell lines with improved efficiency, including the establishment of novel GFP–HIF-1α replacement cells. Quantitative mass spectrometry analysis confirmed the enhanced efficiency and specificity of protein replacement using the 47snoMEN-PR vectors. The 47snoMEN vectors expand the potential applications for snoMEN technology in gene expression studies, target validation and gene therapy

Effect of Kohl-Chikni Dawa – a compound ophthalmic formulation of Unani medicine on naphthalene-induced cataracts in rats

BACKGROUND: Cataracts are the leading cause of blindness worldwide, accounting for 13-27% of cases. Kohl-Chikni Dawa (KCD) is reputed for its beneficial effects in the treatment of premature cataracts. However, its efficacy is yet to be tested. To investigate the rationality of the therapeutic use of Kohl-Chikni Dawa (KCD) in Unani medicine. METHODS: The effect of Kohl-Chikni Dawa eye drops on naphthalene-induced cataracts in rats was investigated by slit-lamp biomicroscopic analysis. The normal group of experimental animals was administered with mineral oil (orally), while other groups were given naphthalene (orally) along with local application of KCD eye drops (once and twice daily), placebo and distilled water (twice daily). Initial morphological changes of the lenses were observed twice a week for two weeks, and thereafter once a week for four weeks. RESULTS: Local application of KCD (twice daily) caused significant reduction in the lens opacification after 2 to 4 weeks of naphthalene administration. CONCLUSION: KCD eye drops may have the potential to delay progression of naphthalene-induced cataracts in rats

Application of deep learning in detecting neurological disorders from magnetic resonance images: a survey on the detection of Alzheimer’s disease, Parkinson's disease and schizophrenia

Neuroimaging, in particular magnetic resonance imaging (MRI), has been playing an important role in understanding brain functionalities and its disorders during the last couple of decades. These cutting-edge MRI scans, supported by high-performance computational tools and novel ML techniques, have opened up possibilities to unprecedentedly identify neurological disorders. However, similarities in disease phenotypes make it very difficult to detect such disorders accurately from the acquired neuroimaging data. This article critically examines and compares performances of the existing deep learning (DL)-based methods to detect neurological disorders—focusing on Alzheimer’s disease, Parkinson’s disease and schizophrenia—from MRI data acquired using different modalities including functional and structural MRI. The comparative performance analysis of various DL architectures across different disorders and imaging modalities suggests that the Convolutional Neural Network outperforms other methods in detecting neurological disorders. Towards the end, a number of current research challenges are indicated and some possible future research directions are provided