Antenatal rescue corticosteroids and perinatal outcome

Background: Antenatal corticosteroids (ACS) is one of the most effective intervention for prevention of neonatal complications in preterm babies. However, due to its transient effects, single repeat course is recommended. This rescue course of ACS is believed to improve feto-maternal outcome in women with preterm labor and was the subject matter of this study.Methods: Total 200 antenatal women who were admitted for threatened preterm labor, between 28 to 34 weeks of gestation, who had already received a single course of ACS within 7-14 days were allocated into group A and group B. Group A included 100 women, who were given rescue course of ACS. Group B included 100 women who rescue course was not given.Results: Out of 115 babies in group A and 114 babies in group B, 18 babies (16%) in group A and 30 babies (26%) in group B had NICU admission (p<0.05). Eight babies (6%) in group A and 23 babies (20%) in group B were diagnosed with respiratory distress syndrome (RDS) where the difference was statistically highly significant (p<0.001). Maternal outcome was similar among both the groups.Conclusions: A single repeat rescue course of ACS helps to improve neonatal outcome in preterm babies

Career Preferences and its influencing factors among medical graduates and undergraduates

Objective: To determine the career preferences of medical students and young doctors and the associated influencing factors. Methodology: A descriptive cross-sectional study was conducted on 267 graduates and undergraduates of various medical institutes and hospitals of Islamabad., selected through convenient non-probability sampling technique.&nbsp; Data was collected through a self-designed pre-tested questionnaire and processed in SPSS software version 20. Comparison was done among male and female students as well as graduates and undergraduates. For categorical variables frequency and percentages were calculated. χ² test was used to find association between influencing factors, career choices and socio demographic variables.&nbsp; Results: There was significant difference of specialty preferences between males and females (p= 0.017) as the most preferred specialty in males was General Medicine (23.8%) whereas in females it was Gynaecology (21.7%).&nbsp; Graduates and undergraduates also had significant difference in their specialty preference (p=0.008). The students showed overall equally little interest in the subjects such as Anaesthesia, Oncology, Family Medicine, Public Health and Research. Lack of specialists in a particular field was the most common reason for preference of specialty among males. Females were more influenced by advice from family members in pursuing a career as compared to males (p=0.04). Maximum participants (95.5%) thought that there is a need of career counselling in medical field. Conclusion: It was observed that majority prefer to choose the most established disciplines. Various factors influence the specialty choices of medical students which should be kept in mind to avoid mismatching of the personality with selection of choice

A critical review on charging technologies of electric vehicles

The enormous number of automobiles across the world has caused a significant increase in emissions of greenhouse gases, which pose a grave and mounting threat to modern life by escalating global warming and polluting air quality. These adverse effects of climate change have motivated the automotive sector to reform and have pushed the drive towards the transformation to fully electric. Charging time has been identified as one of the key barriers in large-scale applications of Electric Vehicles (EVs). In addition, various challenges are associated with the formulation of a safe charging scheme, which is concerned with appropriate charging converter architecture, with the aim of ensuring a safe charging protocol within a range of 5–10 min. This paper provides a systematic review of thharging technologies and their impacts on battery systems, including charger converter design and associated limitations. Furthermore, the knowledge gap and research directions are provided with regard to the challenges associated with the charger converter architecture design at the systems level

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

Career Preferences and its influencing factors among medical graduates and undergraduates

Objective: To determine the career preferences of medical students and young doctors and the associated influencing factors. Methodology: A descriptive cross-sectional study was conducted on 267 graduates and undergraduates of various medical institutes and hospitals of Islamabad., selected through convenient non-probability sampling technique.&nbsp; Data was collected through a self-designed pre-tested questionnaire and processed in SPSS software version 20. Comparison was done among male and female students as well as graduates and undergraduates. For categorical variables frequency and percentages were calculated. χ² test was used to find association between influencing factors, career choices and socio demographic variables.&nbsp; Results: There was significant difference of specialty preferences between males and females (p= 0.017) as the most preferred specialty in males was General Medicine (23.8%) whereas in females it was Gynaecology (21.7%).&nbsp; Graduates and undergraduates also had significant difference in their specialty preference (p=0.008). The students showed overall equally little interest in the subjects such as Anaesthesia, Oncology, Family Medicine, Public Health and Research. Lack of specialists in a particular field was the most common reason for preference of specialty among males. Females were more influenced by advice from family members in pursuing a career as compared to males (p=0.04). Maximum participants (95.5%) thought that there is a need of career counselling in medical field. Conclusion: It was observed that majority prefer to choose the most established disciplines. Various factors influence the specialty choices of medical students which should be kept in mind to avoid mismatching of the personality with selection of choice

Materials for developing future flexible electronic device

Achieving mobility, flexibility, biocompatibility, and functional security while lowering the expense and environmental effects are the main objectives for the next generation of wearable electronics. Flexible electronics (FE) is a promising concept which makes it possible to incorporate many technologies into daily life and promote the development of ground-breaking applications. For physically FE, mechanical properties like the bending radius and the overall thickness are crucial. This study's fundamental goal is to provide a thorough summary of the development, advancement, and applications of FE in diverse fields. The article begins by listing the flexible materials employed during the last few decades in a chronological order. The distinct structural design of flexural electronics is briefly introduced and the processing techniques for producing FE are taken into consideration. The recent developments in flexible electronic are then discussed in relation to the development of materials, such as inorganic and organic substances. The application of materials in the field of flexible electronic is finally discussed, along with potential challenges and future prospects

Development in materials for manufacturing electronics with 3D printing

Three-dimensional (3D) printing or additive manufacturing (AM) appears to be one of the promising technologies with numerous advantages and innovative usages as it diminishes worldwide energy utilization and CO2 releases related to manufacturing processes in industries. It is a manufacturing process utilized for fabricating a 3D product by adding layers from a 3Dmodel as required. The adoption of 3D printing (3DP) techniques and technologies, particularly for printed electronics, has the potential to revolutionize flexible electronics industry, and other fields. From a fundamental standpoint, every application must take into account the materials that are available, the speed of creation, and the resolution of 3DP techniques. This chapter offers a fundamental overview of 3DP techniques as well as the applications and classifications associated with this advanced technology. The most recent advancements in unique 3DP materials for fabricating electronic products have also been presented. Most importantly, this chapter emphasizes the significant role of 3DP in current research advancements, directing readers to concentrate on the current challenges faced by this technology and afterwards outlining future research outlooks to advance 3DP technology

Role of fine needle aspiration, imprint and scrape cytology in the evaluation of intraoral lesions

Aim: The primary goal of our study was to evaluate the value and accuracy of fine needle aspiration cytology (FNAC) in the diagnosis of various intraoral lesions and to correlate the cytological diagnosis with final histopathological findings. Materials and Methods: Fine needle aspiration was performed in 229 patients presented with different lesions of the oral cavity at our institution. Cytological findings were then compared with final histopathological diagnosis. Results: With a male to female ratio of 1.79:1, 229 patients presented with different lesions of the oral cavity were aspirated. Histopathological correlation was available in 86.9% of cases while inadequate material was obtained in 13.1% cases. The diagnostic accuracy of fine needle aspiration in diagnosing benign, pre-malignant and malignant lesions were 95.8%, 84.6% and 97% respectively. Overall the diagnostic accuracy of FNAC in diagnosing intraoral lesions was 94.9% with sensitivity and specificity of 93.2% and 96.8% respectively. Conclusion: FNAC of intraoral lesion is recommended as a valuable procedure for the initial evaluation of all intraoral lesions as it is simple, inexpensive, convenient and comfortable to the patient. Moreover, it can offer a rapid and accurate diagnosis for further management of the patient

Improving Cardiovascular Disease Prediction through Comparative Analysis of Machine Learning Models

Cardiovascular diseases, including myocardial infarction, present significant challenges in modern healthcare, necessitating accurate prediction models for early intervention. This study explores the efficacy of machine learning algorithms in predicting myocardial infarction, leveraging a dataset comprising various clinical attributes sourced from patients with heart failure. Six machine learning models, including Logistic Regression, Support Vector Machine, XGBoost, LightGBM, Decision Tree, and Bagging, are evaluated based on key performance metrics such as accuracy, precision, recall, F1 Score, and AUC. The results reveal XGBoost as the top performer, achieving an accuracy of 94.80% and an AUC of 90.0%. LightGBM closely follows with an accuracy of 92.50% and an AUC of 92.00%. Logistic Regression emerges as a reliable option with an accuracy of 85.0%. The study underscores the potential of machine learning in enhancing myocardial infarction prediction, offering valuable insights for clinical decision-making and healthcare intervention strategies