Little Flower Hospital & Research Centre

Artificial Intelligence (AI) has rapidly evolved from a helpful tool to a highly autonomous decision-making system. It can impact critical infrastructures, social systems, and economic processes. While advanced AI agents offer efficiency and innovation, they also bring significant security risks. This research examines the dual nature of AI, which acts as both an assistant and a potential adversary. We explore key vulnerabilities such as data poisoning, adversarial attacks, and system manipulation that can turn AI systems into security threats. We also examine ethical issues related to autonomy, accountability, and transparency. By showcasing real-world case studies and theoretical models, this work stresses the urgent need for strong safeguards, responsible governance, and security-aware AI design. The findings highlight that without proactive steps, AI could change from a trusted assistant to a powerful adversary, threatening the integrity of digital ecosystems.

Castleman disease is a rare, benign, clinicopathological entity associated with lymphoproliferation. Orbital Castleman disease is an even rarer condition, with multicentric involvement of the orbit being exceptionally uncommon. We report the case of a 61-year-old male who presented with swelling in the right infraorbital region. However, upon detailed evaluation, a bilateral mass clinically suggestive of lymphoma was diagnosed, which, on biopsy, was revealed to be Castleman disease. In this report, we highlight the importance of histology in the definitive diagnosis of Castleman disease and its distinctiveness from lymphoma. Additionally, we provide new insights (through a review of the medical literature) into the clinical features, diagnosis, and treatment of this rare and relatively benign disorder.

ABSTRACTIntroduction:The use of “Platelet-Rich Fibrin (PRF)” has gained significant attention in maxillofacial surgery for its potential to accelerate healing. This trial aims to evaluate the effectiveness of PRF in improving postoperative recovery in subjects undergoing maxillofacial surgery.Methods:In this double-blind trial, subjects were randomly assigned to either the PRF batch or the control batch. Key parameters assessed included wound healing, pain levels, soft tissue regeneration, and postoperative complications. Statistical analysis was conducted to evaluate the effectiveness of PRF using appropriate tests, with significance set at P < 0.05.Results:Subjects in the PRF batch demonstrated faster wound healing (P = 0.03) and reduced pain levels compared to the control batch. Complications such as dry socket and infection were also significantly lower in the PRF batch (P < 0.01). The analysis indicated that PRF significantly enhances tissue regeneration and reduces postoperative complications.Conclusion:Platelet-rich fibrin is effective in accelerating healing post-maxillofacial surgery, with improved clinical outcomes and lower complication rates compared to conventional treatment methods.

Humans evolved in the realm of nature. During evolution, anthropogenic activities led to an imbalance of natural ecosystems thereby causing environmental disasters. An increase in population, rapid industrialization, urban development, and changes in food consumption patterns are major drivers of environmental degradation. Though these are inevitable as a part of development, the nexus of environmental degradation and economic growth are directly linked with the conservation of various environmental compartments including soil, water, air, and biodiversity. Hence, sustainable development is considered the ultimate goal of the interrelationship of Man and the environment. In this context, environmental education is the need of the hour in educating society about the rational use of natural resources and the importance of Sustainable Development. To build a responsible society, the idea of including environmental education in the broader scope of education for development is imperative. Therefore, to assess the importance of environmental education for sustainable development, a perspective on Sustainable Development Goals (SDGs) from college students is attempted. The major objective of the paper was to assess the sensitization and dissemination of skills, attitudes, and behavior of the students with respect to Sustainable Development of Goals in Environmental Education. Methods of environmental education for sustainable development were imparted to the experimental and control group of students. Results indicated a significant difference between the groups in terms of environmental education, perception, and skills of the students from both groups. Further, students who imparted the knowledge on SDGs in Environmental Education showed more sensitization and perception with respect to SDGs, especially on water, biodiversity, climate change, poverty &amp; hunger when compared to the students who were exposed to the conventional teaching methods of environmental education. Outcomes of the study contribute to the development of new methods of environmental education for sustainable development among college students.

Background: Parkinson’s patients experience non-motor symptoms along with motor symptoms that include autonomic deregulation, insomnia, decline in cognition, and psychological distress. Although it is known that mantra chanting offers multiple beneficial effects, the scientific studies related to these are limited. Aims and Objectives: The present study aimed to observe the effectiveness of listening to the Gayatri Mantra in managing non-motor symptoms in patients with Parkinson’s disease. Materials and Methods: The present pilot study recruited 20 patients with Parkinson’s disease. The patients acted as self-controls. After recording the baseline values, the participants were asked to listen to the Gayatri Mantra 108 chanting twice a day for 12 weeks. After 12 weeks of listening, post-intervention values were recorded and analyzed. Sleep quality was assessed using the insomnia severity index. Stress levels were assessed using the perceived stress scale. Spatial and verbal memory tests were used to assess the memory scores. Blood pressure was recorded using the Diamond Original Mercurial Regular BP Monitor (Multicolor). The pulse rate was recorded manually in the radial artery. Results: There was a significant decrease in the perceived stress scores followed by the intervention (P&lt;0.01). Sleep quality was improved in the participants followed by listening to the Gayatri Mantra chanting. There was an improvement in the spatial and verbal memory scores. Systolic and diastolic pressure was decreased and remained within normal limits followed by the intervention. The pulse rate was significantly decreased followed by the intervention. Conclusion: The study results provide preliminary evidence that listening to the Gayatri Mantra has positive effects on the management of the non-motor symptoms of Parkinson’s disease patients. However, there is a need for more studies with higher sample sizes to recommend the implementation of the Gayatri Mantra in the management of Parkinson’s disease.

The sleep-wake cycle, which is regulated by the endogenous circadian rhythm, is disrupted by night-shift work. Altered sleep patterns owing to shift work have been associated with irritability, depressed mood, anxiety, and nervousness. The objective of the study was to evaluate the effect of sleep quality on stress in night shift workers and non-night shift workers. A crosssectional study was conducted in 30night shift and 30 non-night shift workers of Railway Mail Service and Postal Department, Thrissur, Kerala. Sleep quality was assessed using Pittsburg Sleep Quality Index and stress was assessed using Perceived Stress Scale. The findings revealed that a majority of night shift workers reported poor sleep quality, with a significant correlation observed between sleep quality and shift work. Furthermore, stress levels were markedly higher among night workers with poor sleep quality. Regression analysis indicated a positive association between impaired sleep quality and elevated stress levels.

PurposeTo study the role of artificial intelligence (AI) in developing diabetic macular edema (DME) management recommendations by creating and comparing responses to clinicians in hypothetical AI-generated case scenarios. The study also examined whether its joint recommendations followed national DME management guidelines.MethodsThe AI hypothetically generated 50 ocular case scenarios from 25 patients using keywords like age, gender, type, duration and control of diabetes, visual acuity, lens status, retinopathy stage, coexisting ocular and systemic co-morbidities, and DME-related retinal imaging findings. For DME and ocular co-morbidity management, we calculated inter-rater agreements (kappa analysis) separately for clinician responses, AI-platforms, and the “majority clinician response” (the maximum number of identical clinician responses) and “majority AI-platform” (the maximum number of identical AI responses). Treatment recommendations for various situations were compared to the Indian national guidelines.ResultsFor DME management, clinicians (ĸ=0.6), AI platforms (ĸ=0.58), and the ‘majority clinician response’ and ‘majority AI response’ (ĸ=0.69) had moderate to substantial inter-rate agreement. The study showed fair to substantial agreement for ocular co-morbidity management between clinicians (ĸ=0.8), AI platforms (ĸ=0.36), and the ‘majority clinician response’ and ‘majority AI response’ (ĸ=0.49). Many of the current study’s recommendations and national clinical guidelines agreed and disagreed. When treating center-involving DME with very good visual acuity, lattice degeneration, renal disease, anaemia, and a recent history of cardiovascular disease, there were clear disagreements.ConclusionFor the first time, this study recommends DME management using large language model-based generative AI. The study’s findings could guide in revising the global DME management guidelines.

Consider the geometric Linnik distribution GL(α, λ) with characteristic function and type II Generalized Geometric Linnik distribution with characteristic function , [9] used empirical characteristic function to estimate the parameters of a stable law. [1]used characteristic function technique to estimate the parameters of geometric stable law (see also, [2]). Here we estimate the parameters of geometric Linnik distribution and Generalized Geometric Linnik distribution using empirical characteristic function.

Tailed distributions have found applications in various fields. In this paper, we study tailed generalized geometric Linnik distribution. Relation between stable laws and tailed geometric Linnik distribution is established. Tailed generalized geometric asymmetric Linnik distribution is introduced and studied.