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Background: The quadriceps tendon (QT) autograft is a commonly used and effective graft option for anterior cruciate ligament reconstruction (ACLR). Surgical techniques vary, and there is no current standard of care for management of the QT autograft harvest site. Purpose: To examine the literature on patient-reported outcomes and complications after ACLR with a QT autograft and to further clarify the frequency with which the harvest site is closed and potential biomechanical implications. Study Design: Systematic review; Level of evidence, 4. Methods: A systematic review according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines was performed using multiple medical databases. Level 1 to 4 studies on patients undergoing ACLR with a QT autograft were included. There were 2 independent reviewers who analyzed all studies. Study quality was analyzed using the methodological index for non-randomized studies checklist. Results: Overall, 13 studies with a total of 650 patients were included. The mean patient age for all studies was 31 years (range, 14-59 years) with a mean follow-up of 21.2 months (range, 6-84 months). Of the 13 studies, 12 studies (92%) documented patient sex, comprising 331 female patients (55%) and 274 male patients (45%). There were 8 studies (62%) that reported the use of a bony QT autograft in 273 patients, and 5 studies (38%) reported the use of a soft tissue QT autograft in 377 patients. The graft length harvested was most commonly 7 to 8 cm, while the tendon width harvested was 10 mm. Moreover, 5 studies (38%) did not discuss closure of the harvest site, while 2 studies (15%) only closed the harvest site if a capsular rent was present. The surgical technique for harvest-site closure varied when reported in 7 studies (54%). Good to excellent clinical outcomes were reported in 80% of patients when the harvest site was closed. Conclusion: Based on the results of this study, there is no consensus on whether the QT defect should be closed after harvesting the graft for ACLR. It has been reported that closure of the harvest site is performed if there is a capsular rent present. Several techniques are utilized to close the QT autograft harvest site; however, it is unclear if there is a difference in outcomes based on the technique used. Future studies should further clarify whether there are any biomechanical and clinical advantages to closing the QT autograft harvest site.

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As we are familiar that there are many languages around the world, which many of us might even not be aware of but due to globalization and digitalization we have got to see and learn many languages. During those days of colonization, English became an integral part of many people’s language and still continues to be in dominance. Hence, inarguably English is one of the prominent languages that is spoken worldwide. But we also cannot deny the fact that there are still many people across the world who aren’t familiar with this language and face difficulties when most of the texts are written in this particular language. For instance, Indian being one of the countries where there are more than 121 languages and every state has its own dialects. So, it becomes difficult for the people who are less familiar with English or any other language that they aren’t familiar with. To overcome these issues and help people who are from vernacular medium or whose native language is other than English, there are already many applications and systems around the world which is appreciable. Most of the existing systems that are present currently have built separate application for each and every step which could be little overwhelming for someone who is not very mobile friendly specifically people with age group above 60. So, the applications are divided according to the steps like capturing text image through camera, then another application for translation which could be done through any translation API and lastly for scanning we have Optical Character Recognition (OCR) scanner for text. But problem is that people expect that the application that they are using should be easy to use, simple to reach and does everything in one go. So, the application that we have proposed makes it easy for people and provides them with a new idea to translate the unfamiliar language (specifically English) into their native language or the languages that are known to them. So, this mobile application captures images which are text based and has important messages or any documents from real world that is important to be translated, and once capturing of image is done then the text is extracted and at the same time identification of language is done of extracted text, and then using Google translation (we have used this translation api) language is translated into their chosen language( we have more than 50 languages to choose) and then the result is displayed on the screen. Keywords: Text recognition, Text Translation, Language Identification, Natural Language Processing, Android, ML kit