A short report on epidemiological investigation of dog bite cases in association with temperature rise as a part of climate change

Background: Rabies is a neglected disease that claims more than 5000 human’s deaths in Pakistan that account for 10% global load of rabies related deaths annually. Dogs are major carriers for this zoonotic ailment in the country. Global climatic changes, especially rise in temperature, is altering ecological niche of reservoir of infectious diseases. Pakistan is among those countries which are most effected by the temperature rise. This rise has a relation in increase in dog bites and subsequent rabies cases to develop.Methods: Passive data of dog bite cases is acquired from Institute of Public health and were examined for 12 consecutive months. Data analyzed by SPSS software for frequency distribution of dog bite cases in comparison with different months of the year.Results: Data analysis indicate a positive correlation between temperature rise and dog bites rates. This study found prevalence of 2.56% dog bite cases and seasonality in dog bites.Conclusion: These finding recommend further study to investigate other factors involved in increase of dog bite cases in high temperature months of years.  In order to develop understanding the reasons of subsequent rabies cases associated with dog bites. Bats are the most sensitive mammals to high temperature and they migrate and even dye due to hike in temperature, which later may become source of various zoonotic diseases including rabies. Carnivorous bats are believed to be primary reservoir for rabies worldwide but Pakistan do not have this bat specie (Desmodus rotundus). However, increase in dog bite and rabies cases with every year suggest to monitor Indian fruit bat (Pteropus giganteus) which are prevalent in Pakistan.  Ecological Niche Model (ENM) should be used for bats to determine their role in rabies ecology in Pakistan.Keywords: Rabies; Dog bites; Climate shift; Disease ecology; Pteropus giganteu

In vitro evaluation of antimicrobial and anticancer potential of Artemisia absinthium growing in Kashmir Himalayas

Herbal medicines are an important and growing part of International pharmacopeia. Research and testing enhance our understanding of their medical properties, making them a safer alternative or preferable option to allopathic medication. Plant-derived pharmaceuticals are gaining popularity due to the belief that "green medicine" is safer and more trustworthy than expensive synthetic drugs. This study aimed to evaluate the antimicrobial and anticancer potential of the methanolic leaf extract of Artemisia absinthium against human lung cancer A549 cell line by well diffusion method and MTT assay, respectively. The A. absinthium leaf extract showed the highest activity against Enterococcus faecalis (20 ± 0.7 mm), and Escherichia coli (18 ± 0.8 mm), followed by Pseudomonas aeruginosa (16 ± 0.6 mm), Candida albicans (14 ± 0.9 mm) and Staphylococcus aureus (13 ± 0.8 mm), with MIC values 128, 128, 128, 256 and 256 µg/mL respectively. The methanolic extract of A. absinthium showed significant (p ≤ 0.05) cytotoxicity against the A549 cancer cell line with an IC50 value of 36.8 µg/mL. The present study's findings give strong evidence for using the methanolic leaf extract of A. absinthium as an effective ethnomedicinal agent and a possible candidate for treating various human diseases and a potent bioactive agent in anticancer medications

Predicting COVID-19 Incidence Using Data Mining Techniques: A case study of Pakistan

The Outbreak of Coronavirus (COVID-19) came to the world in early December 2019. The early cases of coronavirus were reported in Wuhan City, Hubei Province, China. Till May 18, 2020, 198 countries have been affected by this life-threatening disease. The most common and known traits of COVID-19 are tiredness, fever, and dry cough. In this paper, we have discussed the Predictive data mining approach for COVID-19 predictions. In Predictive data mining, a model is developed and trained using supervised learning and then it predicts the behavior of provided data.  Predictive data mining is a renowned technique known to many health organizations for the classification and prediction of diseases such as Heart disease and various types of cancers etc. There are several factors for comparing the model's accuracy, scalability, and interpretability. This predictive model is compared to the basics of its accuracy. In this proposed approach, we have used WEKA as it provides a vast collection of many machine learning algorithms. The main objective of this paper is to forecast the possible future incidence of corona cases in Pakistan. This study concludes that the number of corona cases will increase swiftly. If the government take proactive steps and strictly implement precautionary measures, then Pakistan may be able to overcome this pandemic.</em

Exploring Emotional and Psychological Impacts of Mammography in Women

Introduction: Mammography is a diagnostic tool that is routinely used to test women for breast cancer. While it has been shown to be beneficial in detecting early-stage malignancies, it can also have emotional and psychological consequences for patients. The goal of this study is to dive into the emotional and psychological experiences of mammography patients. We hope to obtain a better understanding of the potential complications and problems faced by women during the screening process by investigating these elements. Materials and Methods: The Psychological Consequences Questionnaire (PCQ) and a self-administered questionnaire were used to collect data. SPSS was used for statistical analysis. All participants were given information about mammography technology and safety, and their participation was based on informed consent. Results: The study included 60 women ranging in age from 40 to 67 years old, with a mean age of 50.22. The PCQ results revealed a high prevalence of symptoms such as difficulty sleeping, changes in appetite, depression or unhappy feelings, fear and panic, nervousness or tension, feeling under pressure, withholding items, venting frustrations on others, withdrawal from relationships, difficulty with daily tasks, and difficulties fulfilling obligations. These findings shed light on the psychological repercussions that people face and point to the necessity for support networks or therapy to address these concerns. Conclusion:&nbsp; This research focuses on the emotional and psychological effects of mammography on women. The data suggest that anxiety is a common feeling for women undergoing mammography, which could be exacerbated by previous negative experiences or fear of breast cancer. In order to provide holistic and comprehensive care, healthcare providers must recognize and meet patients\u27 emotional and psychological needs

Comparative study of the physico-chemical properties of rice and corn starches grown in Indian temperate climate

Starches isolated from the rice (Jhelum and Kohsar) and corn (PS-43 and Shalimar-maize) cultivars were studied for their physico-chemical and morphological properties. Physico-chemical properties such as composition, water and oil absorption capacity, swelling power, syneresis, freeze–thaw stability and light transmittance showed significant differences among the starches. Amylose contents of starches separated from the Jhelum and Kohsar rice cultivars and PS-43 and Shalimar-maize corn cultivars were 6.33%, 4.90%, 7.52% and 8.09%, respectively. The granular size varied from 5.2 to 5.9 μm for rice starches and 11.4–12.0 μm for corn starches. Transmittance value of gelatinized pastes from all starches progressively decreased up to the 2nd day during refrigerated storage, except Kohsar rice starch which lost its clarity significantly up to 3rd day of storage. The pasting property revealed peak, breakdown and setback viscosity which were in the range of 2479–3021 cP, 962–1713 cP and 1293–2003 cP respectively

Future directions for One Health research: Regional and sectoral gaps

Implementation of a One Health approach varies considerably between different geographical regions and remains challenging to implement without greater inclusivity of different disciplinary capacity and expertise. We performed comparative analyses of abstracts presented at the 1st World One Health Congress (WOHC 2011) and 6th WOHC (2020) to explore and describe the evolving demographics and disciplinary scope of One Health research. We classified abstracts into six One Health research categories and twenty-three subcategories. We also recorded corresponding authors' country and regional affiliation as well as study country (i.e., the country in which the research was conducted) to explore potential asymmetries between funding recipients and study subjects. The WOHC has seen a significant expansion in participation over the last 10 years. The numbers of abstracts accepted to the Congress increased threefold over the last decade (i.e., 302 abstracts in 2010, and 932 abstracts in 2020). At both Congresses, “Disease Surveillance” accounted for the largest proportion (105/302 (35%) and 335/932 (36%) in 2010 and 2020, respectively) of all abstracts accepted. However, “Environmental and Ecological Issues” (33/302 (10%) and 94/932 (11%)), and “Sustainable Food Systems” (19/302 (6%) and 44/932 (4%)) were less well-represented categories of One Health research in both 1st and 6th WOHC respectively. In contrast, “Antimicrobial Resistance” related research increased substantially over time (4/302 (1%) in 2011) and (119/932 (13%) in 2020). There were also differences in the type of research by authors based in “Very High Human Development” index countries compared to “Medium and Low Human Development. “Public Policy” dominated the former, whereas “Disease Surveillance” dominated the latter, suggesting potential regional differences regarding One Health research priorities. The results of the study highlight potential regional gaps and differences in One Health research priorities, with respect to emphasis on operational (surveillance) versus strategic (policy) One Health activities

Microfinance Facility for Rural Women Entrepreneurs in Pakistan: An Empirical Analysis

Since 1990, microfinance has gained universal recognition as an essential and useful tool to address the economically productive poor and provide them with a way to come out of the vicious circle of poverty, by delivering loans and credit on flexible terms in contrast to commercial banks. Many studies from different parts of the world have shown significant economic and social uplift of recipients (both men and women) of microfinance programs. However, in recent years, some studies argue against the positive influence of microfinance and stresses that microfinance is commercialized, and it has become more of a profit generation activity than uplifting of the economically productive poor, which is one of many core objective of microfinance organizations. Many empirical studies have been done to know the effects of microfinance on the welfare of households. They are well documented, e.g., in Bangladesh and India, but only a few studies assess the microfinance effect on rural female entrepreneurs of Pakistan. The present study was carried out to empirically analyze the outcome of microfinance on Pakistan&rsquo;s female entrepreneurs. Women&rsquo;s empowerment is gauged using income and consumption as welfare indicators. The difference in difference method is applied to investigate the effects of microfinance on its recipients, which is considered a useful tool to tackle the selection bias problem. Our study result shows that microfinance programs that target women not just only increase income and consumption of female borrowers, making them financially stable, but in fact, many local stakeholders also get benefited from it, and in turn, it creates opportunities for the whole local community. However, our results also show that it does not reach to the poorest of poor women (extremely poor) and thus does not serve the purpose of many of its core objectives, i.e., poverty reduction of extremely poor and henceforth should not be relied upon in this perspective