Effective communication of critical radiology results: The implementation of panic alert mechanism

Objective: To establish an effective channel of timely communication of life-threatening emergencies to primary physicians by radiology team.Methods: The observational study was conducted at Aga Khan Hospital for Women and Children, Kharadar, Karachi. Data was collected from the log book from July 2012 to June 2013.Amultidisciplinary Panic Alert protocol was formulated and implemented in the Radiology unit. All radiological examinations were screened as soon as possible and panic alerts [provisional findings] were communicated to their primary care taker/relevant nursing staff, attendants within 30 minutes from the time of completion of examination. Complete log was maintained. Data was analysed on SPSS 13.Results: A total of 22,474 patients were seen, and 77(0.34%) had panic provisional findings. The mean time for communicating the panic reporting was 19.5±8 minutes. Implementation of the designed protocol, effective communication and proper follow-up resulted in 100% coverage of panic results.CONCLUSIONS: Life-threatening emergencies identified by radiological imaging can be managed effectively if alerts are generated in time

A case series on uterine arteriovenous malformations: A Life-threatening emergency in young women

Uterine arteriovenous malformation (AVM) is a rare condition, with few cases reported in the literature. Despite being rare, it is a potentially life-threatening condition in women of child-bearing age. It should be considered in the differential diagnosis of prolonged or irregular vaginal bleeding, which, otherwise, can lead to critical complications ending up in severe morbidity and mortality. This case series describes four cases of young Asian women aged between 33 and 38 years who presented with irregular vaginal bleeding. Trans-abdominal ultrasound of the pelvis showed increased vascularity with multi-directional blood flow in the uterus. Magnetic resonance imaging (MRI) confirmed an arteriovenous malformation in all cases. All cases remained stable through the diagnostic journey. Embolization of the arteriovenous malformation was performed successfully in three cases and one case was managed conservatively on hormones. Later, two of them conceived within a year and had live births at term. The aim of reporting these cases is to share the common presentation of this condition and our experience in making the diagnosis and treatment of such patients. Although a few cases are reported world over, none was reported earlier from Pakistani Asian women

A neonate with upper GI bleeding

Bleeding in the newborn is often a serious problem because of cardiovascular effects associated with a loss of blood and/or the damaging effects of bleeding on neonatal tissues, especially the brain. Gastric polyps are described as abnormal lesions that originate in the gastric epithelium or submucosa and protrude into the stomach lumen. Clinical presentation of gastric polyps in children varies widely, from incidental endoscopic finding to massive gastrointestinal bleeding. However, acute gastrointestinal bleeding in association with hyperplastic gastric polyps has been reported very rarely. We report a case of unusual upper gastrointestinal bleeding in newborn baby on 2nd day of life, secondary to gastric polyp, which was diagnosed and resected through endoscopy

Mechanical and comfort properties of Hydroentangled nonwovens from comber noil

Cotton fibre is one of the most important commodity fibre and is widely employed in apparels. At present, the share of natural fibres in production of nonwoven fabrics is low and employed in opt applications. The cotton fibre is conventionally converted into woven and knitted fabrics by short staple spinning methods. The comber noil is short fibre waste during production of combed cotton yarns. The aims of the current study were to employ comber noil for preparation of Hydroentangled cotton nonwovens at varying water jet pressures and conveyor speeds. The effect of these parameters is studied with respect to mechanical and comfort properties of prepared fabrics. The results showed that these variables can help to manufacture fibrous assemblies with engineered properties according to required application area

Internet of Things (IoT) Based Indoor Air Quality Sensing and Predictive Analytic—A COVID-19 Perspective

Indoor air quality typically encompasses the ambient conditions inside buildings and public facilities that may affect both the mental and respiratory health of an individual. Until the COVID-19 outbreak, indoor air quality monitoring was not a focus area for public facilities such as shopping complexes, hospitals, banks, restaurants, educational institutes, and so forth. However, the rapid spread of this virus and its consequent detrimental impacts have brought indoor air quality into the spotlight. In contrast to outdoor air, indoor air is recycled constantly causing it to trap and build up pollutants, which may facilitate the transmission of virus. There are several monitoring solutions which are available commercially, a typical system monitors the air quality using gas and particle sensors. These sensor readings are compared against well known thresholds, subsequently generating alarms when thresholds are violated. However, these systems do not predict the quality of air for future instances, which holds paramount importance for taking timely preemptive actions, especially for COVID-19 actual and potential patients as well as people suffering from acute pulmonary disorders and other health problems. In this regard, we have proposed an indoor air quality monitoring and prediction solution based on the latest Internet of Things (IoT) sensors and machine learning capabilities, providing a platform to measure numerous indoor contaminants. For this purpose, an IoT node consisting of several sensors for 8 pollutants including NH3, CO, NO2, CH4, CO2, PM 2.5 along with the ambient temperature & air humidity is developed. For proof of concept and research purposes, the IoT node is deployed inside a research lab to acquire indoor air data. The proposed system has the capability of reporting the air conditions in real-time to a web portal and mobile app through GSM/WiFi technology and generates alerts after detecting anomalies in the air quality. In order to classify the indoor air quality, several machine learning algorithms have been applied to the recorded data, where the Neural Network (NN) model outperformed all others with an accuracy of 99.1%. For predicting the concentration of each air pollutant and thereafter predicting the overall quality of an indoor environment, Long and Short Term Memory (LSTM) model is applied. This model has shown promising results for predicting the air pollutants’ concentration as well as the overall air quality with an accuracy of 99.37%, precision of 99%, recall of 98%, and F1-score of 99%. The proposed solution offers several advantages including remote monitoring, ease of scalability, real-time status of ambient conditions, and portable hardware, and so forth

To Study the Histomorphological Changes in Cerebellar Purkinje Cells after Exposure to Fine Particulate Matter in C57BL/6J Mice

Objective: To study the histomorphological changes in cerebellar Purkinje cells after exposure to fine particulate matter in C57BL/6J mice. Study Design: Laboratory based experimental study. Place and Duration of Study: The study was conducted in the Anatomy department of the Army Medical College, Rawalpindi, from 15 June to 15 September 2020, in coordination with the Military Hospital, Rawalpindi, and the National Institute of Health (NIH), Islamabad. Materials and Methods: Thirty male and female C57BL/6 mice, 8 weeks of age, weighing 37± 2 gm were obtained from NIH, Islamabad. The animals were divided in two groups, 15 mice in each group (8 male and 7 female) Group A were marked as control, received regular diet and water ad libitum. Group B (experimental group) received dynamic inhalation of 3mg/m³ fine particles (soot) through air circulation for 6h/d for 12 weeks, in plastic cabin measuring 2x2x2 feet fitted with two small fans for evenly distribution of Particulate Matter. After exposure period, the animals were sacrificed. After sectioning the tissue and staining, the microscopic analysis was carried out. Purkinje cell margins were evaluated. Number of Purkinje cells and changes in Purkinje cell size were noted. Data was collected, analyzed with the statistical package for social sciences version 23. A p value ≤ 0.05 was considered significant. Result: The Purkinje cell margins were observed to become irregular and corrugated in the experimental groups B when compared with control group A. The number and size of Purkinje cells also showed difference when compared to the control group A. Conclusion: The present study concluded that fine particulate matter induces changes in histomorphological features of mice cerebellar tissue including Purkinje cells

Assessment of Available Manganese in Milk by Using fodders Grown in Long-Term Wastewater Irrigated Soil

Heavy metals are considered as most important contaminations due to industrialization of countries and an influence on its existence in soil, plant and milk. A study was carried out to check manganese content in soil, forage and milk at three sites of city Jhang, Punjab, Pakistan. All samples (milk, soil, water, fodder plants and ground water) were analyzed for manganese by Atomic Absorption Spectrophotometer. Different health indices were also studied to check Mn flow in food chain. Level of Mn in samples was found within acceptable limits. Manganese level was higher in soil samples collected from Site-III than other sites. Manganese showed higher value (2.595 to 10.402 mg/kg) in soil than other samples. Fodders were found to accumulate manganese from 0.008 to 0.022 mg/kg. Manganese concentration was found to be 0.1482 to 1.241 mg/L, 0.164 to 0.9708 mg/L in water and milk, respectively. BCF and PLI values for manganese were also found to be less than 1. Estimated daily intake (EDI) and THQ of manganese are found within permissible limits in milk of cows feeding on fodders irrigated with wastewater and ground water. So, use of wastewater for irrigation purpose should be properly checked due to possible toxic effects

Utility of iRat as a Tool to Identify Low Academic Performers in 1st Year MBBS with High Scores in Pre-Medical Examination

Objective: To identify low performers by utilizing individual readiness assurance test (i-RAT) scores in first year MBBS students using Team-based learning (TBL) strategy. Study Design: Cross sectional observational study. Place and Duration of Study: Study was conducted in Federal Medical College Islamabad from 10 January to 31 March 2022. Materials and Methods: TBL were introduced in 1 year MBBS. Six TBL activities were practiced by Anatomy Department during the 12-week respiratory and CVS course program. Premedical examination scores, first week individual readiness assurance scores and average i-RAT scores of 6 weeks were gathered. Mean and standard deviation were calculated. Difference in the first week i-RAT scores of three groups based on their premedical examination scores i.e., upper percentile group (A), middle percentile group (B) and lower percentile group (C). Each group comprised of 37 students, was calculated using One Way ANOVA Method. Pearson correlation coefficient (r) was used to access strength and direction of linear association between premedical examination scores and i-RAT scores. The data was analyzed in the statistical package for social sciences (SPSS) version 21 for analysis. Results: High scorers in premedical examination (Group A) showed lowest scores in first week iRAT (i-RAT 1) and Average i-RAT when compared with group B and C with significant p value < 0.05. Significant increase was seen in progressive i-RAT scores in all 3 groups. Negative linear association (r= -0.2) was found between premedical examination scores and i-RAT 1 scores. A strong positive linear association with r= 0.54 was found between first i-RAT and average i-RAT scores. Conclusion: High achievers in premedical examinations struggled the most in 1 year of medicine

Urdu Handwritten Characters Data Visualization and Recognition Using Distributed Stochastic Neighborhood Embedding and Deep Network

This study was supported by the China University of Petroleum-Beijing and Fundamental Research Funds for Central Universities under Grant no. 2462020YJRC001.Peer reviewedPublisher PD