Shock Induced Damage Mechanism Of Perineuronal Net

ECM components, such as the Perineuronal net (PNN), one of the most prevalent parts surrounding the neuronal cell. PNN is a protective net-like structure regulating neuronal activity such as neurotransmission, charge balance and generates an action potential. Shock induced damage of this essential component may cause neuronal cell death and potentially leads to CTE, AD diseases, PTSD, etc. The shock generated possibly during an accident, improvised devie explosion or collision between NFL players may lead to damage to this safety net. The goal is to investigate the mechanics of PNN under shock wave. To understand the mechanics of PNN, mechanical properties of different PNN components such as glycan, GAG, and protein need to be evaluated. In this study, we evaluated the mechanical strength of PNN molecules and the interfacial strength between the components of PNN. Afterward, we have assessed the PNN molecules' damage efficiency at various conditions such as shock speed, preexisting bubble, and boundary conditions. The secondary structure altercation of the protein molecules of the PNN has been analyzed to evaluate damage intensity under varying shock loading. At higher shock speed, damage intensity is more elevated, and hyaluronan is most likely to break at the rigid junction. The primary structure of the protein molecules is most unlikely to fail. Instead, the molecules' secondary bonds will be altered. Our study suggests that the number of hydrogen bonds during the shock wave propagation decreased.Comment: 2

Tropical Indian Ocean Mediates ENSO Influence Over Central Southwest Asia During the Wet Season

AbstractEl Niño–Southern Oscillation (ENSO) modulates wet season (November–April) precipitation over Central Southwest Asia (CSWA), however, intraseasonal characteristics of its influence are largely unknown, which can be important for its subseasonal to seasonal hydroclimate predictability. Here we show that the ENSO‐CSWA teleconnection varies intraseasonally and is a combination of direct and indirect positive influences. The direct influence is through a Rossby wave‐like pattern in the tail months. The indirect influence is through an atmospheric dipole of diabatic heating anomalies in the tropical Indian Ocean (TIO) as a result of ENSO‐forced response, which also generates a Rossby wave‐like forcing and persists throughout the wet season. ENSO exerts its strongest influence when both direct and indirect modes are in phase, while the relationship breaks down when the two modes are out of phase. The atmospheric teleconnection through the atmospheric diabatic heating anomalies in the TIO is reproducible in numerical simulations

Prevalence of Diabetic Retinopathy and Correlation with HbA1c in Patients Admitted in Khyber Teaching Hospital Peshawar

Objective: To determine the prevalence of diabetic retinopathy in patients admitted in Khyber Teaching Hospital Peshawar and to correlate different stages of diabetic retinopathy with HbA1C levels. Methodology: This cross sectional study was conducted at Department of Ophthalmology, Khyber Teaching Hospital, MTI, Peshawar from December 2019 to May 2020. All patients over the age of 15 years who were diagnosed with diabetes mellitus were included in the study while patients with cataract or retinopathy due to other pathologies were excluded. All diabetic patients were admitted through outpatient department. In the ward their blood pressures were recorded and HbA1c levels were also measured. Visual acuity (VA) was checked. Screening for diabetic retinopathy was done by a consultant ophthalmologist by Optos Ultrawide Field Imaging of retina and Optical Coherence Tomography (OCT) of macula to establish stages of diabetic retinopathy and presence of diabetic macular edema respectively. Results: A total of 103 diabetic patients were included. Their retina was photographed, viewed and analyzed. Diabetic retinopathy, irrespective of the type, was found in 69 patients with a prevalence of 66.9%. Patients with lower ranges of HbA1c (below 6%) showed no evidence of DR. The clustering of majority of patients with diabetic retinopathy with HbA1c levels of 8 to 12 %, showed a significant relationship between high blood sugar levels and severity. Conclusion: In our study the higher frequency of retinopathy is alarming by considering it one of the leading causes of blindness in working class. It is highly recommended that routine ophthalmologic examination may be carried out along with optimal diabetic control

Genetic Diversity and Screening of Rice Germplasm Lines against Grain Discoloration Disease

Background: The research was conducted to screen out the diverse rice germplasm lines against grain discoloration disease by using 10 SSR primer pairs and on the basis of various morphological characters to evaluate the diversity of the genotypes at Faculty of Agricultural sciences, University of the Punjab, Lahore. Methods: Seed morphological traits were measured and recorded under Randomized Complete Block Design (RCBD) experiment. DNA extraction and PCR analysis was done to measure the genotypic characteristics of rice. Genotypic and phenotypic variability was measured by using ANOVA and correlation. Microsatellite markers, also called simple sequence repeats (SSR) were used for screening and to check the genetic diversity of rice.Results: The PIC values ranged from 0.204 of RM-07 to 0.640 of primer RM-22 along with other genetic characters i.e., number of alleles, percentage of polymorphism chromosomal location etc. The higher PIC (polymorphism information content) value showed the greatest genetic diversity among the genotypes. The polymorphic SSRs produced 3-5 alleles with an average unit of 3.3. The PIC values ranged from 0.204 to 0.640 with an average mean of 0.51. All the genotypes showed significant differences in all the studied traits which gave the significant results and non-significant results at significance level of p<0.05= *; p<0.01=** respectively.  A significant association was also observed between seed length with length width ratio, 1000 grain weight (r= 0.1251*; r= 0.1922**) and seed thickness with 1000 grain weight (r=0.1205*). All these traits showed higher variations for different rice lines.Conclusions:  From the study it was concluded that some rice found to be highly resistant (Blue Nile, IR 50, Line 9 (4×15) and Line 12 (4×23) against grain discoloration that could be more useful for the production new rice lines with diverse genetic characteristics.Keywords: Oryza sativa; DNA; SSR; Germplasm; Traits; Diversity   

Mechanistic Insight into the role of Vitamin D and Zinc in Modulating Immunity Against COVID-19: A View from an Immunological Standpoint

The pathophysiology of coronavirus disease-19 (COVID-19) is characterized by worsened inflammation because of weakened immunity, causing the infiltration of immune cells, followed by necrosis. Consequently, these pathophysiological changes may lead to a life-threatening decline in perfusion due to hyperplasia of the lungs, instigating severe pneumonia, and causing fatalities. Additionally, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can cause mortality due to viral septic shock, resulting from unrestrained and backfiring immune reactions to the pathogen. Sepsis can cause premature organ failure in COVID-19 patients, as well. Notably, vitamin D and its derivatives and minerals, such as zinc and magnesium, have been reported to improve the immune system against respiratory illnesses. This comprehensive review aims to provide updated mechanistic details of vitamin D and zinc as immunomodulators. Additionally, this review also focuses on their role in respiratory illnesses, while specifically delineating the plausibility of employing them as a preventive and therapeutic agent against current and future pandemics from an immunological perspective. Furthermore, this comprehensive review will attract the attention of health professionals, nutritionists, pharmaceuticals, and scientific communities, as it encourages the use of such micronutrients for therapeutic purposes, as well as promoting their health benefits for a healthy lifestyle and wellbeing

Modelling the nexus of carbon dioxide emissions, economic growth, electricity production and consumption: assessing the evidence from Pakistan

The economy of Pakistan has constantly been plunged due to its severe electricity shortages over the last 2 decades and persistently faces challenges in revamping its electricity supply network. The purpose of this research was to assess the causal relationship between carbon dioxide emissions (CO2), combustible renewable and waste (CRW), electric power consumption (EC), electricity production from coal (EPC), hydroelectric (EPH) and natural gas (EPN) sources, energy use (EU) and gross domestic product (GDP). The scope of this research included Pakistan’s annual time series data from 1971 to 2014. This study employed Autoregressive Distributed Lag (ARDL) bound testing analysis to determine the long-term and short-term correlations among all research parameters. This research also conducted Augmented Dickey-Fuller (ADF), Phillips-Perron (PP) and Kwiatkowski-Phillips-Schmidt-Shin (KPSS) tests to evaluate the stationarity existence among dependent variable and independent variables. The outcomes of the fully modified least squares (FMOLS), dynamic ordinary least square (DOLS) and canonical co-integrating regression (CCR) estimators showed that coefficients of EC, EPH and GDP all were a significantly positive relationship with CO2 emissions, while the coefficients of CRW, EPC and EU were negatively significant, respectively. Furthermore, the outcomes from the short-run analysis revealed that the error correction term value was -0.8668, which indicates that from short-run to long-run equilibrium, the adjustment of the deviation of CO2 emission is by 86.68 percent annually. Moreover, the diagnostic results also demonstrated that the model employed in this research is stable and reliable. Pakistan was selected in this research work because of the deficit of power and if environmental degradation continues unchecked, it will eventually affect the state’s economic growth and CO2 emissions. The study’s primary policy recommendation is that government energy policymakers in Pakistan who create the environment framework in should pursue conservative energy measures as such measures will not negatively impact economic growth

Modelling the nexus of carbon dioxide emissions, economic growth, electricity production and consumption: Assessing the evidence from Pakistan

The economy of Pakistan has constantly been plunged due to its severe electricity shortages over the last 2 decades and persistently faces challenges in revamping its electricity supply network. The purpose of this research was to assess the causal relationship between carbon dioxide emissions (CO2), combustible renewable and waste (CRW), electric power consumption (EC), electricity production from coal (EPC), hydroelectric (EPH) and natural gas (EPN) sources, energy use (EU) and gross domestic product (GDP). The scope of this research included Pakistan’s annual time series data from 1971 to 2014. This study employed Autoregressive Distributed Lag (ARDL) bound testing analysis to determine the long-term and short-term correlations among all research parameters. This research also conducted Augmented Dickey-Fuller (ADF), Phillips-Perron (PP) and Kwiatkowski-Phillips-Schmidt-Shin (KPSS) tests to evaluate the stationarity existence among dependent variable and independent variables. The outcomes of the fully modified least squares (FMOLS), dynamic ordinary least square (DOLS) and canonical co-integrating regression (CCR) estimators showed that coefficients of EC, EPH and GDP all were a significantly positive relationship with CO2 emissions, while the coefficients of CRW, EPC and EU were negatively significant, respectively. Furthermore, the outcomes from the short-run analysis revealed that the error correction term value was -0.8668, which indicates that from short-run to long-run equilibrium, the adjustment of the deviation of CO2 emission is by 86.68 percent annually. Moreover, the diagnostic results also demonstrated that the model employed in this research is stable and reliable. Pakistan was selected in this research work because of the deficit of power and if environmental degradation continues unchecked, it will eventually affect the state’s economic growth and CO2 emissions. The study’s primary policy recommendation is that government energy policymakers in Pakistan who create the environment framework in should pursue conservative energy measures as such measures will not negatively impact economic growth

Corneal nerve and brain imaging in mild cognitive impairment and dementia

Background: Visual rating of medial temporal lobe atrophy (MTA) is an accepted structural neuroimaging marker of Alzheimer's disease. Corneal confocal microscopy (CCM) is a non-invasive ophthalmic technique that detects neuronal loss in peripheral and central neurodegenerative disorders. Objective: To determine the diagnostic accuracy of CCM for mild cognitive impairment (MCI) and dementia compared to medial temporal lobe atrophy (MTA) rating on MRI. Methods: Subjects aged 60-85 with no cognitive impairment (NCI), MCI, and dementia based on the ICD-10 criteria were recruited. Subjects underwent cognitive screening, CCM, and MTA rating on MRI. Results: 182 subjects with NCI (n = 36), MCI (n = 80), and dementia (n = 66), including AD (n = 19, 28.8%), VaD (n = 13, 19.7%), and mixed AD (n = 34, 51.5%) were studied. CCM showed a progressive reduction in corneal nerve fiber density (CNFD, fibers/mm2) (32.0±7.5 versus 24.5±9.6 and 20.8±9.3, p < 0.0001), branch density (CNBD, branches/mm2) (90.9±46.5 versus 59.3±35.7 and 53.9±38.7, p < 0.0001), and fiber length (CNFL, mm/mm2) (22.9±6.1 versus 17.2±6.5 and 15.8±7.4, p < 0.0001) in subjects with MCI and dementia compared to NCI. The area under the ROC curve (95% CI) for the diagnostic accuracy of CNFD, CNBD, CNFL compared to MTA-right and MTA-left for MCI was 78% (67-90%), 82% (72-92%), 86% (77-95%) versus 53% (36-69%) and 40% (25-55%), respectively, and for dementia it was 85% (76-94%), 84% (75-93%), 85% (76-94%) versus 86% (76-96%) and 82% (72-92%), respectively. Conclusion: The diagnostic accuracy of CCM, a non-invasive ophthalmic biomarker of neurodegeneration, was high and comparable with MTA rating for dementia but was superior to MTA rating for MCI