Quantitative estimation of protein in sprouts of 'vigna radiate' (mung beans), 'lens culinaris' (lentils), and 'cicer arietinum' (chickpeas) by Kjeldahl and Lowry methods

Protein scarcity is the most vital cause of long-lasting diseases and even untimely deaths in some developing nations. The application of protein in food is advantageous from the point of view of non-toxicity, biocompatibility, and dietary benefits. This study aimed to determine the protein contents of the sprouts of Vigna radiates (mung beans), Lens culinaris (lentils), and Cicer arietinum (chickpeas) using the Kjeldahl and Lowry methods. The results obtained from the Kjeldahl method identified protein concentrations of 2.54, 2.63, and 2.19%, whereas the Lowry method results identified protein concentrations of 2.96%, 4.10%, and 1.6% in mung beans, lentils, and chickpeas, respectively. In both the methods, lentils were found to have the highest amount of protein followed by mung beans and chickpeas. Both the Kjeldahl and Lowry methods demonstrated good protein values and low variation in the protein amount in the analyzed samples. Furthermore, the methods had greater sensitivity and comparable experimental variability. The outcomes revealed that assays can be applied for protein analysis in legumes. In the context of a lack of suitable standard procedures for evaluating legumes’ compositions, the present study is suitable for food control laboratories. In addition, the studied samples represent a significant source of protein and can be used to fulfil the daily requirements for protein intake and other food applications

Effect of early tranexamic acid administration on mortality, hysterectomy, and other morbidities in women with post-partum haemorrhage (WOMAN): an international, randomised, double-blind, placebo-controlled trial

Background Post-partum haemorrhage is the leading cause of maternal death worldwide. Early administration of tranexamic acid reduces deaths due to bleeding in trauma patients. We aimed to assess the effects of early administration of tranexamic acid on death, hysterectomy, and other relevant outcomes in women with post-partum haemorrhage. Methods In this randomised, double-blind, placebo-controlled trial, we recruited women aged 16 years and older with a clinical diagnosis of post-partum haemorrhage after a vaginal birth or caesarean section from 193 hospitals in 21 countries. We randomly assigned women to receive either 1 g intravenous tranexamic acid or matching placebo in addition to usual care. If bleeding continued after 30 min, or stopped and restarted within 24 h of the first dose, a second dose of 1 g of tranexamic acid or placebo could be given. Patients were assigned by selection of a numbered treatment pack from a box containing eight numbered packs that were identical apart from the pack number. Participants, care givers, and those assessing outcomes were masked to allocation. We originally planned to enrol 15 000 women with a composite primary endpoint of death from all-causes or hysterectomy within 42 days of giving birth. However, during the trial it became apparent that the decision to conduct a hysterectomy was often made at the same time as randomisation. Although tranexamic acid could influence the risk of death in these cases, it could not affect the risk of hysterectomy. We therefore increased the sample size from 15 000 to 20 000 women in order to estimate the effect of tranexamic acid on the risk of death from post-partum haemorrhage. All analyses were done on an intention-to-treat basis. This trial is registered with ISRCTN76912190 (Dec 8, 2008); ClinicalTrials.gov, number NCT00872469; and PACTR201007000192283. Findings Between March, 2010, and April, 2016, 20 060 women were enrolled and randomly assigned to receive tranexamic acid (n=10 051) or placebo (n=10 009), of whom 10 036 and 9985, respectively, were included in the analysis. Death due to bleeding was significantly reduced in women given tranexamic acid (155 [1·5%] of 10 036 patients vs 191 [1·9%] of 9985 in the placebo group, risk ratio [RR] 0·81, 95% CI 0·65–1·00; p=0·045), especially in women given treatment within 3 h of giving birth (89 [1·2%] in the tranexamic acid group vs 127 [1·7%] in the placebo group, RR 0·69, 95% CI 0·52–0·91; p=0·008). All other causes of death did not differ significantly by group. Hysterectomy was not reduced with tranexamic acid (358 [3·6%] patients in the tranexamic acid group vs 351 [3·5%] in the placebo group, RR 1·02, 95% CI 0·88–1·07; p=0·84). The composite primary endpoint of death from all causes or hysterectomy was not reduced with tranexamic acid (534 [5·3%] deaths or hysterectomies in the tranexamic acid group vs 546 [5·5%] in the placebo group, RR 0·97, 95% CI 0·87-1·09; p=0·65). Adverse events (including thromboembolic events) did not differ significantly in the tranexamic acid versus placebo group. Interpretation Tranexamic acid reduces death due to bleeding in women with post-partum haemorrhage with no adverse effects. When used as a treatment for postpartum haemorrhage, tranexamic acid should be given as soon as possible after bleeding onset. Funding London School of Hygiene & Tropical Medicine, Pfizer, UK Department of Health, Wellcome Trust, and Bill & Melinda Gates Foundation

Personality of Mirza Adeeb Through His Letters

Letter writing is an old tradition in Urdu language. Mirza Adeeb'swriting style is conversational which reveal many secret parts of his life. This tradition is still in practice. A very short number of his letters were available after his death which were given away to "GCUL". There are few letters not onely reflects many aspects of his personality,but also his deep relations with renowned scholars of his time.Bano Quddsiya and Tabish Delhvi wrote letters to Mirza in which they paid tribute to him on his services for the revival of Urdu literature. He was high decent fellow with whom people like to share their suffering and affairs. His letters are also important from historical point of view. He also wrote letters to his daughter "Naghma Adeeb" which highilghts his personal life as a loving and caring father. We also find literary information from his letters. No doubt his letters to his predecessors are very important from literary as well as historical point of view

Personality of Mirza Adeeb Through His Letters

Letter writing is an old tradition in Urdu language. Mirza Adeeb'swriting style is conversational which reveal many secret parts of his life. This tradition is still in practice. A very short number of his letters were available after his death which were given away to "GCUL". There are few letters not onely reflects many aspects of his personality,but also his deep relations with renowned scholars of his time.Bano Quddsiya and Tabish Delhvi wrote letters to Mirza in which they paid tribute to him on his services for the revival of Urdu literature. He was high decent fellow with whom people like to share their suffering and affairs. His letters are also important from historical point of view. He also wrote letters to his daughter "Naghma Adeeb" which highilghts his personal life as a loving and caring father. We also find literary information from his letters. No doubt his letters to his predecessors are very important from literary as well as historical point of view

Personality of Mirza Adeeb Through His Letters

Letter writing is an old tradition in Urdu language. Mirza Adeeb'swriting style is conversational which reveal many secret parts of his life. This tradition is still in practice. A very short number of his letters were available after his death which were given away to "GCUL". There are few letters not onely reflects many aspects of his personality,but also his deep relations with renowned scholars of his time.Bano Quddsiya and Tabish Delhvi wrote letters to Mirza in which they paid tribute to him on his services for the revival of Urdu literature. He was high decent fellow with whom people like to share their suffering and affairs. His letters are also important from historical point of view. He also wrote letters to his daughter "Naghma Adeeb" which highilghts his personal life as a loving and caring father. We also find literary information from his letters. No doubt his letters to his predecessors are very important from literary as well as historical point of view

Social Inclusion of Persons with Disabilities into Mainstream Society: Using the Community Care Context

Social Inclusion is an important and extremely desirable phenomenon for persons with disabilities(PWDs). It is the gateway to creating the sense and opportunities for PWDs by recognizing being as integral and potential human resources and a responsible segment of society.  In addition to the lack of research and policies that have been formulated from time to time to emphasize the concept and importance of the Social Inclusion of PWDs’, the traditional response of the community towards PWDs has deterred the social inclusion of PWDs.  The basic theme of this research study was to explore the efforts made by community members for the social inclusion of PWDs in the Community Care context.  A qualitative research method was used to conduct the study. At first, the document -analysis of previous research studies was made to explore the efforts made by the Government and policymakers for the social inclusion of PWDs in the COVID-19 endemic scenario. The open-ended interviews were conducted with the 20 professionals related to special education and social welfare fields to explore the efforts made by the community stakeholders as an element of community care to deal with social restrictions for PWDs and foster their social inclusion to make them productive members of society. The content -analysis reflected that no significant effort has been made at the governmental level for the social inclusion of PWDs d. Finally, the study suggested two Social Inclusion models; 1) Personal Social Services Model (PSSM) and 2) the Social-Ecological Model (SEM) of Social Inclusion which deals with the Individual, Interpersonal, Organizational, Community, and Socio-Political Factors of Society

Machine Learning Algorithms for Depression: Diagnosis, Insights, and Research Directions

Over the years, stress, anxiety, and modern-day fast-paced lifestyles have had immense psychological effects on people’s minds worldwide. The global technological development in healthcare digitizes the scopious data, enabling the map of the various forms of human biology more accurately than traditional measuring techniques. Machine learning (ML) has been accredited as an efficient approach for analyzing the massive amount of data in the healthcare domain. ML methodologies are being utilized in mental health to predict the probabilities of mental disorders and, therefore, execute potential treatment outcomes. This review paper enlists different machine learning algorithms used to detect and diagnose depression. The ML-based depression detection algorithms are categorized into three classes, classification, deep learning, and ensemble. A general model for depression diagnosis involving data extraction, pre-processing, training ML classifier, detection classification, and performance evaluation is presented. Moreover, it presents an overview to identify the objectives and limitations of different research studies presented in the domain of depression detection. Furthermore, it discussed future research possibilities in the field of depression diagnosis