Bacterial prediction using internet of things (IoT) and machine learning.

Water is a basic and primary resource which is required for sustenance of life on the Earth. The importance of water quality is increasing with the ascending water pollution owing to industrialization and depletion of fresh water sources. The countries having low control on reducing water pollution are likely to retain poor public health. Additionally, the methods being used in most developing countries are not effective and are based more on human intervention than on technological and automated solutions. Typically, most of the water samples and related data are monitored and tested in laboratories, which eventually consumes time and effort at the expense of producing fewer reliable results. In view of the above, there is an imperative need to devise a proper and systematic system to regularly monitor and manage the quality of water resources to arrest the related issues. Towards such ends, Internet of Things (IoT) is a great alternative to such traditional approaches which are complex and ineffective and it allows taking remote measurements in real-time with minimal human involvement. The proposed system consists of various water quality measuring nodes encompassing various sensors including dissolved oxygen, turbidity, pH level, water temperature, and total dissolved solids. These sensors nodes deployed at various sites of the study area transmit data to the server for processing and analysis using GSM modules. The data collected over months is used for water quality classification using water quality indices and for bacterial prediction by employing machine learning algorithms. For data visualization, a Web portal is developed which consists of a dashboard of Web services to display the heat maps and other related info-graphics. The real-time water quality data is collected using IoT nodes and the historic data is acquired from the Rawal Lake Filtration Plant. Several machine learning algorithms including neural networks (NN), convolutional neural networks (CNN), ridge regression (RR), support vector machines (SVM), decision tree regression (DTR), Bayesian regression (BR), and an ensemble of all models are trained for fecal coliform bacterial prediction, where SVM and Bayesian regression models have shown the optimal performance with mean squared error (MSE) of 0.35575 and 0.39566 respectively. The proposed system provides an alternative and more convenient solution for bacterial prediction, which otherwise is done manually in labs and is an expensive and time-consuming approach. In addition to this, it offers several other advantages including remote monitoring, ease of scalability, real-time status of water quality, and a portable hardware.

Assessment of Knowledge, Perceptions and Perceived Risk Concerning COVID-19 in Pakistan.

The COVID-19 pandemic is one of unmatched scale and severity. A continued state of crisis has been met with poor public adherence to preventive measures and difficulty implementing public health policy. This study aims to identify and evaluate the factors underlying such a response. Thus, it assesses the knowledge, perceived risk, and trust in the sources of information in relation to the novel coronavirus disease at the outset of the COVID-19 pandemic. An online questionnaire was completed between March 20 and 27, 2020. Knowledge, perceptions, and perceived risk (Likert scale) were assessed for 737 literate participants of a representative sample in an urban setting. We found that respondents' risk perception for novel coronavirus disease was high. The perceived risk score for both cognitive and affective domains was raised at 2.24 ± 1.3 (eight items) and 3.01 ± 1 (seven items) respectively. Misconceptions and gaps in knowledge regarding COVID-19 were noted. Religious leadership was the least trusted (10%) while health authorities were the most trusted (35%) sources of information. Our findings suggest that there was a deficiency in knowledge and high concern about the pandemic, leading to a higher risk perception, especially in the affective domain. Thus, we recommend comprehensive education programs, planned intensive risk communication, and a concerted effort by all stakeholders to mitigate the spread of disease. The first of its kind in the region, this study will be critical to response efforts against current and future outbreaks.

Comparing the preventive behavior of medical students and physicians in the era of COVID-19: Novel medical problems demand novel curricular interventions.

The global challenge presented by COVID-19 is unparalleled. Shortages in healthcare staff and manpower bring the practical skills of medical students under the spotlight. However, before they can be placed on hospital frontlines, it is crucial to assess their preparedness for patient interaction. This can be achieved by comparing their behavioral dynamics to those of physicians. An online questionnaire was administered between March 20, 2020 and March 27, 2020. The preventive strategies adopted by medical students and physicians at different ages and levels of education were compared by using chi-square test where a p value of <0.05 was considered statistically significant. We report that the demonstration of preventive behaviors increased with educational attainment and age. Older age groups avoided crowded areas, wore more masks, used disinfectants and did not touch their faces as compared to the younger participants (p < 0.001). Similarly, postgraduate doctors used more masks and disinfectants as compared to graduate doctors and medical students (p < 0.001). Based on our results, the lack of preventive behavior shown by medical students has implications for policy makers. We recommend short- and long-term changes to medical programs and admissions policies to equip medical students with the personal and professional skills to better contribute to the healthcare system in the present pandemic and beyond.

Structure-based design of guanosine analogue inhibitors targeting GTP cyclohydrolase IB towards a new class of antibiotics.

GTP cyclohydrolase (GCYH-I) is an enzyme in the folate biosynthesis pathway that has not been previously exploited as an antibiotic target, although several pathogens including N. gonorrhoeae use a form of the enzyme GCYH-IB that is structurally distinct from the human homologue GCYH-IA. A comparison of the crystal structures of GCYH-IA and -IB with the nM inhibitor 8-oxo-GTP bound shows that the active site of GCYH-IB is larger and differently shaped. Based on this structural information, we designed and synthesized a small set of 8-oxo-G derivatives with ether linkages at O6 and O8 expected to displace water molecules from the expanded active site of GCYH-IB. The most potent of these compounds, G3, is selective for GCYH-IB, supporting the premise that potent and selective inhibitors of GCYH-IB could constitute a new class of small molecule antibiotics.

Quantitative volumetric analysis of a retinoic acid induced hypoplastic model of chick thymus, using Image-J.

OBJECTIVE: To assess the total volume change in a retinoic acid-induced, hypoplastic model of a chick thymus using Image-J. METHODS: This experimental study was carried out at the anatomy department of College of Physicians and Surgeons, Islamabad, Pakistan, from February 2009 to February 2010, and comprised fertilised chicken eggs. The eggs were divided into experimental group A and control group C. Group A was injected with 0.3µg of retinoic acid via yolk sac to induce a defective model of a thymus with hypoplasia. The chicks were sacrificed on embryonic day 15 and at hatching. The thymus of each animal was processed, serially sectioned and stained. The total area of each section of thymus was calculated using Image-J. This total area was summed and multiplied with the thickness of each section to obtain volume. RESULTS: Of the 120 eggs, there were 60(50%) in each group. Image analysis revealed a highly significant decrease in the volume of the chick thymus in the experimental group A than its matched control at the time of hatching (p=0.001). Moreover, volumetric depletion progressed with time, being substantially pronounced at hatching compared to the embryonic stage. CONCLUSIONS: The volume changes were significant and were effectively quantified using Image-J.

Does folinic acid ameliorates retinoic acid induced teratogenicity in chick embryo?

OBJECTIVE: To investigate the protective effect of folinic acid on the hatching ability and developmental defects in a retinoic acid-induced teratogenic model of chick embryo. METHODS: The experimental study was conducted at the Department of Anatomy, Regional Centre of the College of Physicians and Surgeons Pakistan, Islamabad, from February 2009 to February 2010. Chicken eggs were divided into two experimental groups and a control group. The first experimental group was injected with retinoic acid to induce a defective model, while the second experimental group was concomitantly injected folinic acid to observe its protective effects on retinoic acid-induced defects in the development and hatching process. Both groups were compared with the age-matched control group. RESULTS: A total of 90 fertilised eggs were divided into three groups. The experimental groups had significantly more delayed and assisted hatchings compared to the control group (p<0.05) but the difference between the experimental groups regarding the mode and day of hatching was insignificant (p>0.05). CONCLUSIONS: Irrespective of the presence of folinic acid, prenatal retinoic acid exposure significantly altered the hatchability characteristics in the experimental groups compared to the control.