An overview of the genus Dioscorea L. (Dioscoreaceae) in India

The present paper depicts an overview and elucidated assessment of published data and herbarium records on the diversity, distribution pattern, endemism and threat status of Dioscorea spp. to get availed with extant stature and design strategies for its effective conservation. Dioscorea nested under family Dioscoreceae is a pantropical genus comprising about 682 species. In India, the genus is known to possess 42 taxa (41 species and one variety). Dioscorea L. is highly regarded for its nutritional and medicinal values having a significant role in pharmaceutical and nutraceutical industries. Several species of Dioscorea contain various biologically active molecules that show anti-arthritic, anti-inflammatory and anti-fertility effects and thereby known for alleviating medicinal curses

Use of folk remedies among patients in Karachi, Pakistan

BACKGROUND: The concept that food is medicine is being practiced in certain parts of the world, with positive outcomes on health of the population. We have such practice in Pakistan but it needs to be brought in line with the available scientific evidence. METHODS: The study was conducted on 270 patients, visiting the Family Practice Center, the Aga Khan University, Karachi. A questionnaire was used to collect information on the demographic profile, and the use of folk remedies for medicinal uses. RESULTS: Substantial use of folk remedies for different medical conditions has been documented. The remedies included cinnamon, ginger, cloves, cordimon, sesame oil, poppy seeds, honey, lemon, table salt, eggs and curd. The medical conditions in which folk remedies are used in respondents\u27 view, include conditions such as common cold, cough and flu to more serious conditions such as asthma, jaundice and heat stroke.CONCLUSIONS: We have found a substantial use of folk remedies for treatment of medical conditions. There is a need to organize their use on scientific lines

PREVELANCE OF OVARIAN CANCER AND ITS CORELATION WITH AGE IN PAKISTAN

Introduction: group of diseases that is originated from the different parts of ovaries and cause production of abnormal cells that divide uncontrolled themselves in the ovaries is known as ovarian cancer. OC is mainly classified into majorly three types on the base of three components of ovaries known as epithelium, stroma and germinal cells. Approximately, 7000 women develop OC and 4200 of them die every year in UK. In Pakistan the incidence of OC is increasing at the rate of around 13.6%. Approximately 70% cases are diagnosed at later stages. Methodology: The blood sample was collected by Layyah region. The CA125 identification through Elisa technique for their better identification on the basis of antibodies. Normal values of CA125 were considered less than 35 U/ml. the other tumor marker was also measured such as fibrinogen, prolactin, CA15.3, PT, APTT, INR, D Dimer, and CA19.9. Results: The mean age of patients was 59.0 ± 8.1while the minimum and maximum age at which the tumor marker detection was 22 and 74 years. The no of patient was found in order of 25 >24 > 10 in 1st, 2nd and 3rd age groups, respectively. The clinical histopathological test in the ovarian cancer patients show that the tumor size 5.21 ± 3.42, fibrinogen 5.09 ± 1.29, CA-199 (U/mL) 121.17 ± 59.76, and D-dimer 0.61 ± 0.31. The CA-125 level increase in ovarian cancer patients it indication as a tumor marker

Neurodegenerative diseases and effective drug delivery: A review of challenges and novel therapeutics

The central nervous system (CNS) encompasses the brain and spinal cord and is considered the processing center and the most vital part of human body. The central nervous system (CNS) barriers are crucial interfaces between the CNS and the periphery. Among all these biological barriers, the blood-brain barrier (BBB) strongly impede hurdle for drug transport to brain. It is a semi-permeable diffusion barrier against the noxious chemicals and harmful substances present in the blood stream and regulates the nutrients delivery to the brain for its proper functioning. Neurological diseases owing to the existence of the BBB and the blood-spinal cord barrier have been terrible and threatening challenges all over the world and can rarely be directly mediated. In fact, drug delivery to brain remained a challenge in the treatment of neurodegenerative (ND) disorders, for these different approaches have been proposed. Nano-fabricated smart drug delivery systems and implantable drug loaded biomaterials for brain repair are among some of these latest approaches. In current review, modern approaches developed to deal with the challenges associated with transporting drugs to the CNS are included. Recent studies on neural drug discovery and injectable hydrogels provide a potential new treatment option for neurological disorders. Moreover, induced pluripotent stem cells used to model ND diseases are discussed to evaluate drug efficacy. These protocols and recent developments will enable discovery of more effective drug delivery systems for brain

Performance evaluation of convolutional neural network for hand gesture recognition using EMG

peer reviewedElectromyography (EMG) is a measure of electrical activity generated by the contraction of muscles. Non-invasive surface EMG (sEMG)-based pattern recognition methods have shown the potential for upper limb prosthesis control. However, it is still insufficient for natural control. Recent advancements in deep learning have shown tremendous progress in biosignal processing. Multiple architectures have been proposed yielding high accuracies (>95%) for offline analysis, yet the delay caused due to optimization of the system remains a challenge for its real-time application. From this arises a need for optimized deep learning architecture based on fine-tuned hyper-parameters. Although the chance of achieving convergence is random, however, it is important to observe that the performance gain made is significant enough to justify extra computation. In this study, the convolutional neural network (CNN) was implemented to decode hand gestures from the sEMG data recorded from 18 subjects to investigate the effect of hyper-parameters on each hand gesture. Results showed that the learning rate set to either 0.0001 or 0.001 with 80-100 epochs significantly outperformed (p < 0.05) other considerations. In addition, it was observed that regardless of network configuration some motions (close hand, flex hand, extend the hand and fine grip) performed better (83.7% ± 13.5%, 71.2% ± 20.2%, 82.6% ± 13.9% and 74.6% ± 15%, respectively) throughout the course of study. So, a robust and stable myoelectric control can be designed on the basis of the best performing hand motions. With improved recognition and uniform gain in performance, the deep learning-based approach has the potential to be a more robust alternative to traditional machine learning algorithms

Hepatitis C virus to hepatocellular carcinoma

Hepatitis C virus causes acute and chronic hepatitis and can lead to permanent liver damage and hepatocellular carcinoma (HCC) in a significant number of patients via oxidative stress, insulin resistance (IR), fibrosis, liver cirrhosis and HCV induced steatosis. HCV induced steatosis and oxidative stress causes steato-hepatitis and these pathways lead to liver injury or HCC in chronic HCV infection. Steatosis and oxidative stress crosstalk play an important role in liver damage in HCV infection. This Review illustrates viral and host factors which induce Oxidative stress, steatosis and leads toward HCC. It also expresses Molecular cascade which leads oxidative stress and steatosis to HCC

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Background: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. Methods: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. Findings: In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]). Interpretation: Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions