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1.
Front Nutr ; 10: 1233070, 2023.
Artigo em Inglês | MEDLINE | ID: mdl-37789898

RESUMO

Micronutrient deficiency also known as "hidden hunger" refers to a condition that occurs when the body lacks essential vitamins and minerals that are required in small amounts for proper growth, development and overall health. These deficiencies are particularly common in developing countries, where a lack of access to a varied and nutritious diet makes it difficult for people to get the micronutrients they need. Micronutrient supplementation has been a topic of interest, especially during the Covid-19 pandemic, due to its potential role in supporting immune function and overall health. Iron (Fe), zinc (Zn), iodine (I), and selenium (Se) deficiency in humans are significant food-related issues worldwide. Biofortification is a sustainable strategy that has been developed to address micronutrient deficiencies by increasing the levels of essential vitamins and minerals in staple crops that are widely consumed by people in affected communities. There are a number of agricultural techniques for biofortification, including selective breeding of crops to have higher levels of specific nutrients, agronomic approach using fertilizers and other inputs to increase nutrient uptake by crops and transgenic approach. The agronomic approach offers a temporary but speedy solution while the genetic approach (breeding and transgenic) is the long-term solution but requires time to develop a nutrient-rich variety.

2.
Prateek Singh; Rajat Ujjainiya; Satyartha Prakash; Salwa Naushin; Viren Sardana; Nitin Bhatheja; Ajay Pratap Singh; Joydeb Barman; Kartik Kumar; Raju Khan; Karthik Bharadwaj Tallapaka; Mahesh Anumalla; Amit Lahiri; Susanta Kar; Vivek Bhosale; Mrigank Srivastava; Madhav Nilakanth Mugale; C.P Pandey; Shaziya Khan; Shivani Katiyar; Desh Raj; Sharmeen Ishteyaque; Sonu Khanka; Ankita Rani; Promila; Jyotsna Sharma; Anuradha Seth; Mukul Dutta; Nishant Saurabh; Murugan Veerapandian; Ganesh Venkatachalam; Deepak Bansal; Dinesh Gupta; Prakash M Halami; Muthukumar Serva Peddha; Gopinath M Sundaram; Ravindra P Veeranna; Anirban Pal; Ranvijay Kumar Singh; Suresh Kumar Anandasadagopan; Parimala Karuppanan; Syed Nasar Rahman; Gopika Selvakumar; Subramanian Venkatesan; MalayKumar Karmakar; Harish Kumar Sardana; Animika Kothari; DevendraSingh Parihar; Anupma Thakur; Anas Saifi; Naman Gupta; Yogita Singh; Ritu Reddu; Rizul Gautam; Anuj Mishra; Avinash Mishra; Iranna Gogeri; Geethavani Rayasam; Yogendra Padwad; Vikram Patial; Vipin Hallan; Damanpreet Singh; Narendra Tirpude; Partha Chakrabarti; Sujay Krishna Maity; Dipyaman Ganguly; Ramakrishna Sistla; Narender Kumar Balthu; Kiran Kumar A; Siva Ranjith; Vijay B Kumar; Piyush Singh Jamwal; Anshu Wali; Sajad Ahmed; Rekha Chouhan; Sumit G Gandhi; Nancy Sharma; Garima Rai; Faisal Irshad; Vijay Lakshmi Jamwal; MasroorAhmad Paddar; Sameer Ullah Khan; Fayaz Malik; Debashish Ghosh; Ghanshyam Thakkar; Saroj K Barik; Prabhanshu Tripathi; Yatendra Kumar Satija; Sneha Mohanty; Md. Tauseef Khan; Umakanta Subudhi; Pradip Sen; Rashmi Kumar; Anshu Bhardwaj; Pawan Gupta; Deepak Sharma; Amit Tuli; Saumya Ray Chaudhuri; Srinivasan Krishnamurthi; Prakash L; Ch V Rao; B N Singh; Arvindkumar Chaurasiya; Meera Chaurasiyar; Mayuri Bhadange; Bhagyashree Likhitkar; Sharada Mohite; Yogita Patil; Mahesh Kulkarni; Rakesh Joshi; Vaibhav Pandya; Amita Patil; Rachel Samson; Tejas Vare; Mahesh Dharne; Ashok Giri; Shilpa Paranjape; G. Narahari Sastry; Jatin Kalita; Tridip Phukan; Prasenjit Manna; Wahengbam Romi; Pankaj Bharali; Dibyajyoti Ozah; Ravi Kumar Sahu; Prachurjya Dutta; Moirangthem Goutam Singh; Gayatri Gogoi; Yasmin Begam Tapadar; Elapavalooru VSSK Babu; Rajeev K Sukumaran; Aishwarya R Nair; Anoop Puthiyamadam; PrajeeshKooloth Valappil; Adrash Velayudhan Pillai Prasannakumari; Kalpana Chodankar; Samir Damare; Ved Varun Agrawal; Kumardeep Chaudhary; Anurag Agrawal; Shantanu Sengupta; Debasis Dash.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-21267889

RESUMO

Data science has been an invaluable part of the COVID-19 pandemic response with multiple applications, ranging from tracking viral evolution to understanding the effectiveness of interventions. Asymptomatic breakthrough infections have been a major problem during the ongoing surge of Delta variant globally. Serological discrimination of vaccine response from infection has so far been limited to Spike protein vaccines used in the higher-income regions. Here, we show for the first time how statistical and machine learning (ML) approaches can discriminate SARS-CoV-2 infection from immune response to an inactivated whole virion vaccine (BBV152, Covaxin, India), thereby permitting real-world vaccine effectiveness assessments from cohort-based serosurveys in Asia and Africa where such vaccines are commonly used. Briefly, we accessed serial data on Anti-S and Anti-NC antibody concentration values, along with age, sex, number of doses, and number of days since the last vaccine dose for 1823 Covaxin recipients. An ensemble ML model, incorporating a consensus clustering approach alongside the support vector machine (SVM) model, was built on 1063 samples where reliable qualifying data existed, and then applied to the entire dataset. Of 1448 self-reported negative subjects, 724 were classified as infected. Since the vaccine contains wild-type virus and the antibodies induced will neutralize wild type much better than Delta variant, we determined the relative ability of a random subset of such samples to neutralize Delta versus wild type strain. In 100 of 156 samples, where ML prediction differed from self-reported uninfected status, Delta variant, was neutralized more effectively than the wild type, which cannot happen without infection. The fraction rose to 71.8% (28 of 39) in subjects predicted to be infected during the surge, which is concordant with the percentage of sequences classified as Delta (75.6%-80.2%) over the same period.

3.
J Clin Diagn Res ; 10(9): RC13-RC16, 2016 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-27790533

RESUMO

INTRODUCTION: Open fractures of shaft of humerus have been treated conservatively as well as operatively. Plate osteosynthesis has been considered as the gold standard treatment. Intramedullary nailing also has same success rate in closed fractures. The results of 30 open fractures of shaft humerus fixed with locked unreamed antegrade intramedullary nailing were evaluated. AIM: The purpose of the study was to evaluate the role of locked intramedullary nailing in open fractures of shaft humerus in terms of bone union, secondary procedure required, complication, shoulder dysfunction and infection. MATERIALS AND METHODS: Of consecutive 365 humeral shaft fractures, 63 fractures were open. Thirty-two patients were operated with plate osteosynthesis, while 31 patients who were treated with locked unreamed intramedullary nails fulfilling the inclusion criteria entered the study. RESULTS: Twenty eight of thirty patients united in mean duration of 10.5 weeks. There were two non-unions both of them united with bone grafting and plate osteosynthesis. Seven patients had superficial infection which healed with antibiotic course, while two patients had deep infection, which healed with repeat debridement. Eleven patients had preoperative radial nerve palsy, nine of which healed completely in average of six months. Twenty eight patients had excellent functional outcome at final follow-up while two patients had good outcome. CONCLUSION: Antegrade nailing is associated with good union rates and low infection rates and is a good option in open fractures and in polytrauma patients.

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