Analysis of Growing Tumor on the Flow Velocity of Cerebrospinal Fluid in Human Brain Using Computational Modeling and Fluid-Structure Interaction

Cerebrospinal fluid (CSF) plays a pivotal role in normal functioning of Brain. Intracranial compartments such as blood, brain and CSF are incompressible in nature. Therefore, if a volume imbalance in one of the aforenoted compartments is observed, the other reaches out to maintain net change to zero. Whereas, CSF has higher compliance over long term. However, if the CSF flow is obstructed in the ventricles, this compliance may get exhausted early. Brain tumor on the other hand poses a similar challenge towards destabilization of CSF flow by compressing any section of ventricles thereby ensuing obstruction. To avoid invasive procedures to study effects of tumor on CSF flow, numerical-based methods such as Finite element modeling (FEM) are used which provide excellent description of underlying pathological interaction. A 3D fluid-structure interaction (FSI) model is developed to study the effect of tumor growth on the flow of cerebrospinal fluid in ventricle system. The FSI model encapsulates all the physiological parameters which may be necessary in analyzing intraventricular CSF flow behavior. Findings of the model show that brain tumor affects CSF flow parameters by deforming the walls of ventricles in this case accompanied by a mean rise of 74.23% in CSF flow velocity and considerable deformation on the walls of ventricles

To Compare the Effectiveness of Platelet Rich Plasma vs Steroid Injection in the Management of Planter Fasciitis

Objective: The study was done to compare the effectiveness of Platelet Rich Plasma (PRP) vs steroid injections in the management of planter fasciitis. Study Design: It was a comparative study. Place and Duration of Study: This study was conducted for the duration of one year from October 2021 to September 2022 in Pakistan Railway General Hospital, Rawalpindi. Materials and Methods: The study was conducted on 500 patients that visited tertiary care unit for a period of one year. Two groups were made based on random sampling technique and type of treatment given for plantar fasciitis (Platelet Rich Plasma and steroid). After the preparation of platelet rich plasma by centrifugation method that separates the red blood cells from plasma and obtain the final volume of plasma with high concentration of platelets. A total of 3ml of platelet rich plasma was injected after all aseptic measures around the area of maximal tenderness in group A patients. 40 mg injection of triamcinolone acetonide was given to the all the participants in group B patients after doing all aseptic measures around the area of maximal tenderness after clinical examination Results: There were 250 patients in each group including both male and females. The average age of patients in our study was 45.9 ± 5.6 years and 45.9±4.5 years in both groups respectively. Patient in group A had more effective pain relief in long term follow up than patients in group B. The Visual Analog Scale (VAS) score values gradually decreased as the duration of treatment increased with the lowest value obtained as 0.68 ± 0.65* and 0.60 ± 0.69* for steroid and PRP group respectively. There was no post injection problem in either group. Conclusion: Our study concludes that PRP administration for the treatment of plantar fasciitis can be more effective as compared to steroid as it gives positive results even after 12 months of follow-up

Exploring the better genetic options from indigenous material to cultivate tomato under high temperature regime

Screening test was conducted on 54genotypes of tomato to analyze the effect of heat stress and categorize them as heat tolerant or heat susceptible ones. Seedlings were grown at temperatures of 28/22oC day/night. Four weeks after sowing, plants were exposed to high temperatures of 40/32oC day/night for one week. Data for various morphological (root and shoot length, root and shoot fresh and dry weight, number of leaves) and physiological parameters (chlorophyll contents, sub-stomatal CO2, transpiration rate, stomatal conductance, photosynthetic rate, water use efficiency and leaf temperature) were recorded. Heat stress had a negative effect on all physiological and morphological processes of the genotypes. However, “Parter Improved”, “Legend” and “Roma” were the most tolerant genotypes whereas “Grus Chovka”, “Nepoli”, “Tima France”, “Kaldera” and “Cold Set” were susceptible to heat stress

Green photosensitisers for the degradation of selected pesticides of high risk in most susceptible food: a safer approach

Pesticides are the leading defence against pests, but their unsafe use reciprocates the pesticide residues in highly susceptible food and is becoming a serious risk for human health. In this study, mint extract and riboflavin were tested as photosensitisers in combination with light irradiation of different frequencies, employed for various time intervals to improve the photo-degradation of deltamethrin (DM) and lambda cyhalothrin (λ-CHT) in cauliflower. Different source of light was studied, either in ultraviolet range (UV-C, 254 nm or UV-A, 320–380 nm) or sunlight simulator (> 380–800 nm). The degradation of the pesticides varied depending on the type of photosensitiser and light source. Photo-degradation of the DM and λ-CHT was enhanced by applying the mint extracts and riboflavin and a more significant degradation was achieved with UV-C than with either UV-A or sunlight, reaching a maximum decrement of the concentration by 67–76%. The light treatments did not significantly affect the in-vitro antioxidant activity of the natural antioxidants in cauliflower. A calculated dietary risk assessment revealed that obvious dietary health hazards of DM and λ-CHT pesticides when sprayed on cauliflower for pest control. The use of green chemical photosensitisers (mint extract and riboflavin) in combination with UV light irradiation represents a novel, sustainable, and safe approach to pesticide reduction in produce

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Thermophoresis and Brownian Model of Pseudo-Plastic Nanofluid Flow over a Vertical Slender Cylinder

This study focuses on the industrial and engineering interest quantities, such as drag force and rate of transmission of heat, for pseudo-plastic nanofluid flow. The attributes of natural convection of the pseudo-plastic nanofluid flow model over a vertical slender cylinder are explored. The pseudo-plastic flow is studied under the influence of concentration of nanoparticles, rate of heat transmission, and drag force. For the first time, the pseudo-plastic nanofluid flow model has been implemented over a vertical slender cylinder which is not yet investigated. The acquired model is based on thermophoresis and Brownian motion mechanisms. The governing equations of pseudo-plastic nanofluid in cylindrical coordinates are modelled. The developed system of nonlinear equations is tackled by boundary layer assumptions and similarity transformations. Moreover, the solution of the acquired system exhibited by using a new powerful numerical technique. A comprehensive debate on drag force and transmission of heat under the influence of various emerging parameters is illustrated in the table. Furthermore, the effects of dimensionless parameters over the velocity profile, temperature profile, and concentration of nanoparticle profile have been exhibited graphically

Augmented Reality Based Spelling Assistance to Dysgraphia Students

Dysgraphia, a learning disability associated with writing skills, hinders students to put their thought on paper and write correctly. Writing problems hit students most frequently that one third students become failed to acquire writing skill. Different IT based assistance solutions available for dysgraphia students but most of them are accommodations based or provides writing alternatives rather than developing writing skills of a dysgraphia student. Handwriting is an essential skill for academic life and developed handwriting skill helps student to protect their self-esteem and build student’s confidence to participate in other activities during class. Most of available writing assistance solutions do not provide interesting ways to acquire writing skills. To handle this problem, augmented reality (AR) based dysgraphia assistance solution has presented in this work. This study utilized AR to develop dysgraphia student’s interest in writing and used it to assist in writing activity by providing help in spellings. AR based dysgraphia assistance writing environment (AR-DAWE) modal use Google cloud API of speech-to-text and addressed one of the important issues of dysgraphia student that is associated with spelling mistakes

Derivatization/chromophore introduction of tranexamic acid and its HPLC determination in pharmaceutical formulations

A viable cost-effective and isocratic approach employing C-18 column (250 mm × 4.6 mm, 5 μm) based HPLC has been utilized to separate and estimate the drug, tranexamic acid in pharmaceutical formulations. Tranexamic acid contains no π-electrons to act as fluorophore or chromophore hence pre-column derivatization was performed with benzene sulfonyl chloride in aqueous medium at room temperature. The derivatized drug was then estimated using C-18 column by exploiting a 25:75 (v/v) solvent mixture of acetonitrile and 0.1 M ammonium acetate (pH 5.0) as the mobile phase. The flow rate of mobile phase was 1 mL/min and detection was performed at a wavelength of 232 nm using UV detector. Retention time of tranexamic acid was 4.42 min. The method followed linear regression equation in the concentration range of 1–100 μg/mL with co-efficient of determination equal to 0.9994. The limit of detection and limit of quantitation were 0.3 and 1 μg/mL, respectively. The relative standard deviation and recovery ranges for tranexamic acid were found to be 0.11–2.47% and 97.60–103.25%, respectively. The suggested method is very sensitive and may have the potential to be used for tranexamic acid detection in medicinal formulations

Evolutionary Model for Brain Cancer-Grading and Classification

Brain cancer is a dangerous disease and affects millions of people life in worldwide. Approximately 70% of patients diagnosed with this disease do not survive. Machine learning is a promising and recent development in this area. However, very limited research is performed in this direction. Therefore, in this research, we propose an evolutionary lightweight model aimed at detecting brain cancer and classification, starting from the analysis of magnetic resonance images. The proposed model named lightweight ensemble combines (weighted average and lightweight combines multiple XGBoost decision trees) is the modified version of the recent Multimodal Lightweight XGBoost. Herein, we provide prediction explain ability by considering the preprocessing of Magnetic Resonance Imaging (MRI) data and the feature extraction (Intensity, texture, and shape). The process in the evolutionary model involves a various step - first, prepare the data, extract important features, and finally, merge together using a special kind of classification called ensemble classification. We evaluate our proposed model using BraTS 2020 dataset. The dataset consists of 285 MRI scans of patients diagnosed with gliomas. The simulation results showed that our proposed model achieved 93.0% accuracy, 0.94 precision, 0.93 recall, 0.94 F1 score, and an area under Receiver Operating Characteristic Curve (AUC-ROC) value of 0.984. The efficient results demonstrate the effectiveness of our proposed model for brain tumor grading and classification using four grades. The efficient results show the potential of our proposed approach as a valuable tool for early diagnosis and effective treatment planning of brain tumors. Finally, the proposed model holds promise for aiding in early cancer diagnosis and treatment