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Immune checkpoint blockade is the exciting breakthrough in cancer, but how immune checkpoints are activated is unknown. We have earlier reported that cell-free chromatin particles (cfChPs) that circulate in blood of cancer patients, or those that are released locally from dying cancer cells, are readily internalized by healthy cells with biological consequences. Here we report that treatment of human lymphocytes with cfChPs isolated from sera of cancer patients led to marked activation of the immune checkpoints PD-1, CTLA-4, LAG-3, NKG2A, and TIM-3. This finding was corroborated in vivo in splenocytes of mice when cfChPs were injected intravenously. Significant upregulation of immune checkpoint was also observed when isolated lymphocytes were exposed to conditioned medium containing cfChPs released from hypoxia-induced dying HeLa cells. Immune checkpoint activation could be down-regulated by pre-treating the conditioned media with three different cfChPs deactivating agents. Down-regulation of immune checkpoints by cfChPs deactivating agents may herald a novel form of immunotherapy of cancer.

Despite having a higher burden of health problems, transgender persons face challenges in accessing healthcare in India. Most studies on healthcare access of transgender persons in India focus only on HIV related care, mental healthcare, gender affirmative services or on the ethno-cultural communities or transgender women. This study fills this gap by focusing on diverse gender identities within the transgender community with a specific focus on experiences in accessing general or routine healthcare services. A qualitative descriptive approach was used in this study. 23 in-depth interviews and 6 focus group discussions were conducted virtually and in-person with a total of 63 transgender persons in different regions of India between May and September 2021. The study used a community-based participatory research approach and was informed by the intersectionality approach. Thematic analysis was conducted to analyze the data. Four key themes emerged: (i) intersectional challenges in accessing healthcare start outside of the health system, continue through cisgender-binary-normative health systems that exclude transgender persons; and at the interface with individuals such as health professionals, support staff and bystanders; (ii) the experiences negatively impact transgender persons at an individual level; (iii) in response, transgender persons navigate these challenges across each of the levels: individual, health system level and from outside of the health system. This is a first of its kind qualitative participatory study focusing on routine healthcare services of transgender persons in India. The findings indicate the need to move conversations on trans-inclusion in healthcare from HIV and gender affirmative services to routine comprehensive healthcare services considering the higher burden of health problems in the community and the impact of poor access on their lives and well-being.

Metastatic dissemination following successful treatment of the primary tumour remains a common cause of death. There is mounting evidence that therapeutic interventions themselves may promote development of metastatic disease. We earlier reported that cell-free chromatin particles (cfChPs) released from dying cancer cells are potentially oncogenic. Based on this observation we hypothesized that therapeutic interventions may lead to the release of cfChPs from therapy induced dying cancer cells which could be carried via the blood stream to distant organs to transform healthy cells into new cancers that would masquerade as metastasis. To test this hypothesis, we generated xenografts of MDA-MB-231 human breast cancer cells in severe combined immune-deficient mice, and using immuno-fluorescence and FISH analysis looked for cfChPs in their brain cells. We detected multiple human DNA signals representing cfChPs in nuclei of brain cells of mice which co-localized with eight human onco-proteins. No intact MDA-MB-231 cells were detected. The number of co-localizing human DNA and human c-Myc signals increased dramatically following treatment with chemotherapy, localized radiotherapy or surgery, which could be prevented by concurrent treatment with three different cfChPs deactivating agents. These results suggest that therapeutic interventions lead to the release cfChPs from therapy induced dying cancer cells carrying oncogenes and are transported via the blood stream to brain cells to potentially transform them to generate new cancers that would appear as metastases. cfChPs induced metastatic spread of cancer is preventable by concurrent treatment with agents that deactivate cfChPs.

Ischemic optic neuropathy is one of the major causes of severe impairment of vision often leading to blindness. It has varied etiopathogenesis with limited management options and very often result in poor outcome. Perioperative ischemic optic neuropathy is rare and particularly seen in elderly patients with multiple comorbidities undergoing cardiac or spine surgery. We present a case of young patient who developed ischemic optic neuropathy following craniotomy for recurrent meningioma. Keywords: Ischemic optic neuropathy; optic nerve vasculature; painless vision loss; perioperative complications; perioperative optic nerve ischemia

The health services research network is showing a lot of interest in the Internet of Medical Things (IoMT). In IoMT, the Internet is used to help compile important health-related data. A brain tumor is caused by a mass of random cells inside the brain, which is dangerous and harmful to the brain. Today, it is difficult to accurately recognise brain images. In order to find and correctly categorize malignant cells in recognizing brain pictures, this research offers a support value-based deep neural network (SDNN) in e-Health care administration utilizing the IoMT innovation. As a starting point, a database of investigation is created using picture data based on IoT innovation and clinical images. The input brain picture is subjected to skull stripping during the preprocessing stage in order to isolate the desired brain area. The preprocessed output pictures are then used to extract the useful characteristics, such as entropy, geometric, and texture features. Finally, based on the collected characteristics, the proposed support value based adaptive deep neural network (SDNN) identification classifies the brain pictures as normal or abnormal. The results of the experiments are examined to show how the suggested recognition approach outperforms the ones already in use.

Background India has been implementing active case-finding (ACF) for TB among marginalised and vulnerable (high-risk) populations since 2017. The effectiveness of ACF cycle(s) is dependent on the use of appropriate screening and diagnostic tools and meeting quality indicators. Objectives To determine the number of ACF cycles implemented in 2021 at national, state (n = 36) and district (n = 768) level and quality indicators for the first ACF cycle. Methods In this descriptive study, aggregate TB program data for each ACF activity that was extracted was further aggregated against each ACF cycle at the district level in 2021. One ACF cycle was the period identified to cover all the high-risk populations in the district. Three TB ACF quality indicators were calculated: percentage population screened (≥10%), percentage tested among screened (≥4.8%) and percentage diagnosed among tested (≥5%). We also calculated the number needed to screen (NNS) for diagnosing one person with TB (≤1538). Results Of 768 TB districts, ACF data for 111 were not available. Of the remaining 657 districts, 642 (98%) implemented one, and 15 implemented two to three ACF cycles. None of the districts or states met all three TB ACF quality indicators’ cut-offs. At the national level, for the first ACF cycle, 9.3% of the population were screened, 1% of the screened were tested and 3.7% of the tested were diagnosed. The NNS was 2824: acceptable (≤1538) in institutional facilities and poor for population-based groups. Data were not consistently available to calculate the percentage of i) high-risk population covered, ii) presumptive TB among screened and iii) tested among presumptive. Conclusion In 2021, India implemented one ACF cycle with sub-optimal ACF quality indicators. Reducing the losses between screening and testing, improving data quality and sensitising stakeholders regarding the importance of meeting all ACF quality indicators are recommended.

Background: Adipokines have an important role in the pathophysiology of overweight and obesity and associated inflammatory diseases. Objective: The present review aims to evaluate the role of Yoga on adipokines among people with overweight and obesity. Methods: Authors performed a systematic search for relevant research studies as per the PRISMA guidelines in Google Scholar, Medline/Pubmed, Scopus, Web of Science, PsychInfo electronic databases.Two independent authors conducted the selection of articles, data extraction, assessment of the risk of bias for individual studies. Any disagreements were resolved by discussion with the third author. Results: Eight randomized trials and four uncontrolled trials involving a total of 1054 participants were included. Yoga with varying frequencies was administered for different durations. The studied adipokines among overweight and obese were leptin, adiponectin, interleukin-6 (IL-6), Tumor necrosis factor-alpha (TNF-α), chemerin, visfatin, plasminogen activator inhibitor-1 (PAI-1), and transforming growth factor-beta (TGF-β). The methodological quality of the included studies was low to moderate on the Cochrane risk of bias tool and Newcastle-Ottawa Quality Assessment Scale. The higher the frequency and duration of Yoga practice, the more significant changes in the adipokine levels were seen. Conclusion: The present review indicates that Yoga practices positively impacts adipokines among people with overweight and obesity. However, the present study precludes the generalizability of results due to the methodological heterogeneity, the type of Yoga intervention, and settings.

Images of the retina are widely used for diagnosing fundus disease. Low-quality retinal photos make it hard for computer-aided diagnosis systems and ophthalmologists to make a clinical diagnosis. In ophthalmology, precision medicine is based partly on the quality of retinal images. Diabetic Retinopathy (DR) is a common complication of diabetes mellitus that causes iris damage. It is difficult to detect and, if not detected early, can result in blindness. Convolutional neural networks are gaining popularity as an effective deep learning (DL) approach for medical image analysis. This study suggests using deep learning approaches at various stages of the fundus image-based diagnostic pipeline for diabetic retinopathy (DR). Many fields, including medical image classification, have adopted DL representations. Using retinal fundus images, we propose a bi-directional extended short-term memory-based diabetic retinopathy detection model. By examining images of the retinal fundus, the Bi-directional Long Short-Term Memory (LSTM) method can detect and classify various grades of DR. As a preprocessing step, the proposed model uses the Multiscale Retinex with Chromaticity Preservation (MSRCP) method to increase the difference of fundus pictures and progress the short difference of medicinal views. To prepare satisfactory results for image processing, multiscale retinex with chromaticity preservation is used. However, choosing the parameters’ values, such as the Gaussian scales, gain, offset, etc., is the main difficulty with the retinex algorithm. To achieve a practical effect, these parameters must be adjusted. The main goal of the suggested method is to obtain the ideal values for the parameters used in the MSRCP algorithm. Also, photos that have already been processed are used to make feature vectors with the help of an efficient net-based feature extractor that uses deep learning. Many experiments use the benchmark Methods to Evaluate Segmentation and Indexing Techniques in the Field of Retinal Ophthalmology (MESSIDOR) dataset. The results are analyzed in terms of various evaluation factors. The results show that the Bi-LSTM-MSRCP technique is better at diagnosing DR than more modern methods.

Routine ophthalmoscopic screening for retinopathy of prematurity (ROP) from the age of 2 weeks is necessary to detect and treat fulminate ROP.

Nitrogen (N) is an essential but generally limiting nutrient for biological systems. Development of the Haber-Bosch industrial process for ammonia synthesis helped to relieve N limitation of agricultural production, fueling the Green Revolution and reducing hunger. However, the massive use of industrial N fertilizer has doubled the N moving through the global N cycle with dramatic environmental consequences that threaten planetary health. Thus, there is an urgent need to reduce losses of reactive N from agriculture, while ensuring sufficient N inputs for food security. Here we review current knowledge related to N use efficiency (NUE) in agriculture and identify research opportunities in the areas of agronomy, plant breeding, biological N fixation (BNF), soil N cycling, and modeling to achieve responsible, sustainable use of N in agriculture. Amongst these opportunities, improved agricultural practices that synchronize crop N demand with soil N availability are low-hanging fruit. Crop breeding that targets root and shoot physiological processes will likely increase N uptake and utilization of soil N, while breeding for BNF effectiveness in legumes will enhance overall system NUE. Likewise, engineering of novel N-fixing symbioses in non-legumes could reduce the need for chemical fertilizers in agroecosystems but is a much longer-term goal. The use of simulation modeling to conceptualize the complex, interwoven processes that affect agroecosystem NUE, along with multi-objective optimization, will also accelerate NUE gains.

In the last six decades, the consumption of reactive nitrogen (Nr) in the form of fertilizer in India has been growing rapidly, whilst the nitrogen use efficiency (NUE) of cropping systems has been decreasing. These trends have led to increasing environmental losses of Nr, threatening the quality of air, soils, and fresh waters, and thereby endangering climate-stability, ecosystems, and human-health. Since it has been suggested that the fertilizer consumption of India may double by 2050, there is an urgent need for scientific research to support better nitrogen management in Indian agriculture. In order to share knowledge and to develop a joint vision, experts from the UK and India came together for a conference and workshop on “Challenges and Opportunities for Agricultural Nitrogen Science in India.” The meeting concluded with three core messages: (1) Soil stewardship is essential and legumes need to be planted in rotation with cereals to increase nitrogen fixation in areas of limited Nr availability. Synthetic symbioses and plastidic nitrogen fixation are possibly disruptive technologies, but their potential and implications must be considered. (2) Genetic diversity of crops and new technologies need to be shared and exploited to reduce N losses and support productive, sustainable agriculture livelihoods. (3) The use of leaf color sensing shows great potential to reduce nitrogen fertilizer use (by 10–15%). This, together with the usage of urease inhibitors in neem-coated urea, and better management of manure, urine, and crop residues, could result in a 20–25% improvement in NUE of India by 2030.

The outward migration of skilled migrants has disproportionally affected the Global South, particularly in countries in Africa, producing what is commonly referred to as 'brain drain'. Within this literature, there has been considerable focus on the future migration intentions of international students, who symbolise skilled migration. However, much previous literature assumes international education must be obtained through physical mobility, despite the growing provision of internationalisation at a distance, whereby students remain 'at home' while studying online or distantly from an institution based 'abroad'. This study has unravelled the future migration intentions of students studying through online distance education, using a questionnaire of 607 South African, Namibian, and Zimbabwean students in relation to four sets of factors: academic and social adjustment, educational and work experience, socio-economic variables, and individual demographic characteristics. Our findings indicate a complex picture of international distance students' future migration intentions and significant differences between students based on country of origin, socioeconomic status, and demographic variables. These findings have particular relevance following the increasing shifts to online distance learning following the COVID-19 pandemic.