Open fractures with bone loss are a common occurrence following high energy trauma. But usually the bone fragments are lost on the roadside and are not usable. We report a patient who was involved in a head-on collision between two wheelers and presented with a bone fragment embedded in his thigh. Radiological survey revealed no bony injury in that patient. Another patient, who presented at the same time, sustained a segmental fracture of shaft femur and was found to have lost a bone fragment that was similar to the one found in previous patient. CT scan with 3D reconstruction revealed this missing fragment to be the same as that found in previous patient. Both patients had a history of head-on collision while travelling on a two-wheeler. Present case report throws some highlights on the probable mechanism of injury.
Accidents, Traffic ; Bone and Bones ; injuries ; Foreign Bodies ; Thigh ; injuries

OBJECTIVES: Aedes mosquitoes are responsible for transmitting the dengue virus. The mosquito lifecycle is known to be influenced by temperature, rainfall, and relative humidity. This retrospective study was planned to investigate whether climatic factors could be used to predict the occurrence of dengue in East Delhi. METHODS: The number of monthly dengue cases reported over 19 years was obtained from the laboratory records of our institution. Monthly data of rainfall, temperature, and humidity collected from a local weather station were correlated with the number of monthly reported dengue cases. One-way analysis of variance was used to analyse whether the climatic parameters differed significantly among seasons. Four models were developed using negative binomial generalized linear model analysis. Monthly rainfall, temperature, humidity, were used as independent variables, and the number of dengue cases reported monthly was used as the dependent variable. The first model considered data from the same month, while the other three models involved incorporating data with a lag phase of 1, 2, and 3 months, respectively. RESULTS: The greatest number of cases was reported during the post-monsoon period each year. Temperature, rainfall, and humidity varied significantly across the pre-monsoon, monsoon, and post-monsoon periods. The best correlation between these three climatic factors and dengue occurrence was at a time lag of 2 months. CONCLUSIONS: This study found that temperature, rainfall, and relative humidity significantly affected dengue occurrence in East Delhi. This weather-based dengue empirical model can forecast potential outbreaks 2-month in advance, providing an early warning system for intensifying dengue control measures.
Aedes ; Culicidae ; Dengue Virus ; Dengue* ; Disease Outbreaks ; Humidity* ; Incidence* ; Linear Models ; Retrospective Studies* ; Seasons ; Weather

Cardiovascular disease (CVD) related mortality and morbidity heavily strain society. The relationship between external risk factors and our genetics have not been well established.It is widely acknowledged that environmental influence and individual behaviours play a significant role in CVD vulnerability, leading to the development of polygenic risk scores (PRS). We employed the PRISMA search method to locate pertinent research and literature to extensively review artificial intelligence (AI)-based PRS models for CVD risk prediction.Furthermore, we analyzed and compared conventional vs. AI-based solutions for PRS. We summarized the recent advances in our understanding of the use of AI-based PRS for risk prediction of CVD. Our study proposes three hypotheses: i) Multiple genetic variations and risk factors can be incorporated into AI-based PRS to improve the accuracy of CVD risk predicting. ii) AI-based PRS for CVD circumvents the drawbacks of conventional PRS calculators by incorporating a larger variety of genetic and non-genetic components, allowing for more precise and individualised risk estimations. iii) Using AI approaches, it is possible to significantly reduce the dimensionality of huge genomic datasets, resulting in more accurate and effective disease risk prediction models. Our study highlighted that the AI-PRS model outperformed traditional PRS calculators in predicting CVD risk. Furthermore, using AI-based methods to calculate PRS may increase the precision of risk predictions for CVD and have significant ramifications for individualized prevention and treatment plans.

Tephrosia purpurea (L.) Pers. is popularly known as 'Sarapunkha' in classical Ayurvedic texts. It is a perennial plant belonging to the family Fabaceae, and occurs throughout the Indian subcontinent. T. purpurea is traditionally used to treat splenomegaly, cirrhosis, cough and cold, abdominal swelling and as an antidote in the Ayurvedic system of medicine. Phytochemical investigations indicate the presence of semiglabrin, pongamole, lanceolatins A and B, rutin, lupeol, and β-sitosterol. Flavonoids including (+)-tephrorin A and B, (+)-tephrosone, an isoflavone, 7, 4'-dihydroxy-3', 5'-dimethoxyisoflavone and a chalcone, (+)-tephropurpurin were isolated from the whole plant. Pharmacological activities of different parts of the plant reported include anti-inflammatory, antiulcer, antimicrobial, antioxidant, antiallergic, antidiabetic, hepatoprotective, antitumor and insect repellent activity. In the present review, the literature on the phytochemical and pharmacological investigations of Tephrosia purpurea (L.) Pers. are summarized to August, 2012.
Animals ; Humans ; India ; Medicine, Ayurvedic ; Plant Extracts ; chemistry ; pharmacology ; Tephrosia ; chemistry