Comparison of measured and Monte Carlo-calculated electron depth dose distributions in aluminium

Depth dose profiles in aluminium have been measured using the cellulose triacetate dosimeter against different electron energies (4, 4.5 and 5 MeV) at a recently upgraded 15 kW industrial electron beam accelerator facility. The study also includes comparison of these profiles against Monte Carlo calculations. The measured and simulated depth dose profiles are similar in shape. For all electron energies, at initial depths, the measured doses are higher than the simulated ones. The simulated and measured normalized surface dose values are 0.58 and 0.66, respectively, independent of electron energy. The difference in the surface dose between Monte Carlo and experiment could be attributed to possible presence of low energy electrons in the measurements whereas the Monte Carlo calculations are based on monoenergetic electrons. Between the region of dose maximum and the tail portion of the depth dose curve, the measured dose is smaller than the simulated values (about 17% to 40% at 5 MeV). Using the depth dose profiles, electron beam parameters such as depth at which maximum dose occurs, dmax, practical range, Rp and half-value depth, R50 have been determined. Using the measured parameters Rp and R50, the incident kinetic energy of the electron beam has been determined. The estimated electron energies while using Rp are 4.02, 4.41 and 4.75 MeV. When using R50, the corresponding values are 3.83, 4.21 and 4.64 MeV. The measured RP/R50 ratios are slightly larger than the Monte Carlo-calculated values, which suggest that the electron beam may not be monoenergetic

Therapeutic implications of current Janus kinase inhibitors as anti-COVID agents: A review

Severe cases of COVID-19 are characterized by hyperinflammation induced by cytokine storm, ARDS leading to multiorgan failure and death. JAK-STAT signaling has been implicated in immunopathogenesis of COVID-19 infection under different stages such as viral entry, escaping innate immunity, replication, and subsequent inflammatory processes. Prompted by this fact and prior utilization as an immunomodulatory agent for several autoimmune, allergic, and inflammatory conditions, Jakinibs have been recognized as validated small molecules targeting the rapid release of proinflammatory cytokines, primarily IL-6, and GM-CSF. Various clinical trials are under investigation to evaluate Jakinibs as potential candidates for treating COVID-19. Till date, there is only one small molecule Jakinib known as baricitinib has received FDA-approval as a standalone immunomodulatory agent in treating critical COVID-19 patients. Though various meta-analyses have confirmed and validated the safety and efficacy of Jakinibs, further studies are required to understand the elaborated pathogenesis of COVID-19, duration of Jakinib treatment, and assess the combination therapeutic strategies. In this review, we highlighted JAK-STAT signalling in the pathogenesis of COVID-19 and clinically approved Jakinibs. Moreover, this review described substantially the promising use of Jakinibs and discussed their limitations in the context of COVID-19 therapy. Hence, this review article provides a concise, yet significant insight into the therapeutic implications of Jakinibs as potential anti-COVID agents which opens up a new horizon in the treatment of COVID-19, effectively

Monte Carlo modeling of NRC\u2019s primary standard

The BEAMnrc/EGSnrc Monte Carlo code system is employed to develop a model of the National Research Council of Canada primary standard of absorbed dose to tissue in a beta radiation field, comprising an extrapolation chamber and Sr 90 /Y 90 beta source. We benchmark the model against the measured response of the chamber in terms of absorbed dose to air, for three different experimental setups when irradiated by the Sr 90 /Y 90 source. For the first setup, the chamber cavity depth is fixed at 0.2cm and the source-to-chamber distance varied between 11 and 60cm . In the other two cases, the source-to-chamber distance is fixed at 30cm . In one case the response for different chamber depths is studied, while in the other case the chamber depth is fixed at 0.2cm as different thicknesses of Mylar\u2122 are added to the front surface of the extrapolation chamber.Peer reviewed: YesNRC publication: Ye

Role of melatonin in the management of substance addiction: a systematic review.

Recent evidence links melatonin hormone and its receptor to the etiology and behavioral manifestation of addiction. The role of exogenous melatonin in addiction treatment is still inconsistent and unclear. The present study aimed to review the literature on randomized clinical trials that evaluated the role of melatonin supplementation, compared to placebo, in the treatment of various substance addictions. The literature searches of relevant articles published in the English language in MEDLINE and Google Scholar databases were performed from inception up to May 2021. We included only randomized clinical trials investigating the effect of melatonin treatment, compared to placebo, on substance addiction-related parameters. Non-randomized clinical trials, observation studies, and animal studies were excluded. The risk of bias-2 was used to assess the quality of the studies. Of 537 articles, 12 randomized control trials (RCT) met our inclusion criteria. Studies have been conducted on substances of addiction including benzodiazepine (BZD), alcohol, nicotine, and opioids. Our results indicated that melatonin treatment had mixed results in improving sleep quality and was not found beneficial in BDZ cessation/discontinuation rate among patients with BDZ dependence. Sleep quality and mental health had improved by melatonin supplements in opioid addiction. In nicotine addiction, melatonin treatment showed effectiveness only on mood changes but not in performance tests. In patients with alcohol use disorder (AUD), melatonin treatment did not show any improvement in sleep quality. We found that the use of exogenous melatonin in substance addiction has mixed results which do not provide sufficient evidence, relative to randomized clinical trials, to establish its role

Evaluating Interference of Lipemia on Routine Clinical Biochemical Tests

Objective Lipemia is an important cause of preanalytical errors in laboratory results. They affect the specimen integrity and trustworthiness of laboratory results. The present study was to assess the impact of lipemia on routine clinical chemistry analytes. Methods Anonymous leftover serum samples with normal levels of routine biochemical parameters were pooled. Twenty such pooled serum samples were used for the study. The samples were spiked with commercially available intralipid solution (20%) to produce lipemic concentrations of 0, 400 (mild, 20 μL), 1,000 (moderate, 50 μL), and 2,000 mg/dL (severe, 100 μL). Glucose, renal function test, electrolytes, and liver function test were estimated in all the samples. Baseline data without the effect of interference was considered as true value and percentage bias for the spiked samples was calculated. Interference was considered significant if the interference bias percentage exceeded 10%. Result Parameters like glucose, urea, creatinine, direct bilirubin, sodium, potassium, and chloride showed negative interference at mild and moderate lipemic concentration and positive interference at severe lipemic concentration. Parameters like aspartate transaminase (AST) and alanine transaminase (ALT) showed negative interference at mild and positive interference at moderate and severe lipemic concentration. Whereas uric acid, total protein, albumin, total bilirubin, alkaline phosphatase, gamma-glutamyl transferase, calcium, magnesium, and phosphorous showed positive interference at all concentrations. Significant interference (> 10%) was shown for magnesium (mild lipemia), albumin, direct bilirubin, ALT, and AST at moderate lipemic concentration. All parameters showed significant interference at severe lipemic concentration. Conclusion All the study parameters are affected by lipemic interference at varying levels. Laboratory-specific data regarding lipemic interference at various concentrations on the clinical biochemistry parameters is needed

Comparison of measured and Monte Carlo-calculated electron depth dose distributions in aluminium

48-52Depth dose profiles in aluminium have been measured using the cellulose triacetate dosimeter against different electron energies (4, 4.5 and 5 MeV) at a recently upgraded 15 kW industrial electron beam accelerator facility. The study also includes comparison of these profiles against Monte Carlo calculations. The measured and simulated depth dose profiles are similar in shape. For all electron energies, at initial depths, the measured doses are higher than the simulated ones. The simulated and measured normalized surface dose values are 0.58 and 0.66, respectively, independent of electron energy. The difference in the surface dose between Monte Carlo and experiment could be attributed to possible presence of low energy electrons in the measurements whereas the Monte Carlo calculations are based on monoenergetic electrons. Between the region of dose maximum and the tail portion of the depth dose curve, the measured dose is smaller than the simulated values (about 17% to 40% at 5 MeV). Using the depth dose profiles, electron beam parameters such as depth at which maximum dose occurs, dmax, practical range, Rp and half-value depth, R50 have been determined. Using the measured parameters Rp and R50, the incident kinetic energy of the electron beam has been determined. The estimated electron energies while using Rp are 4.02, 4.41 and 4.75 MeV. When using R50, the corresponding values are 3.83, 4.21 and 4.64 MeV. The measured RP/R50 ratios are slightly larger than the Monte Carlo-calculated values, which suggest that the electron beam may not be monoenergetic

TH‐C‐T‐617‐08: Monte Carlo Modelling of the Response of NRC's 90Sr/90Y Primary Beta Standard

Purpose: To benchmark an EGSnrc Monte Carlo calculated response against the high quality measured response of an extrapolation chamber used as NRC's primary standard of absorbed dose to tissue in a [formula omitted] beta field. Method and Materials: The BEAMnrc code was used to model the NRC's beta source and indigenously developed extrapolation chamber. The calculated response was compared to the measured response in 3 different series of measurements. An overall scale factor was determined by a global fit. It was used to scale the calculated values to the measured values and was compared to the known activity of the source. A single measurement configuration (30 cm distance, 0.2015 cm chamber depth) was common to all 3 sets of experimental data. Results: The scale factor led to an estimated source activity of 1.237±0.08% GBq which is consistent with the nominal value of 1.2±0.1 GBq. As the source‐detector distance was varied from 11 cm to 60 cm, values of calculated and measured responses agreed within 0.37% for a variation in response by a factor of 29. As chamber depth was varied from 0.05 cm to 0.25 cm the values agreed within 0.4%. As Mylar thicknesses up to 11 mg/cm2 were added to the face of the chamber, the values agreed within 0.2%, and agreed within 1.2% up to 150 mg/cm2. Conclusion: This project demonstrates EGSnrc's ability to calculate the response of extrapolation chamber with a remarkable degree of accuracy. Such high precision comparisons with experimental data are rare. This benchmarking of the Monte Carlo model will allow it to be used to calculate correction factors needed for the NRC's primary standard

Monte Carlo-based revised values of dose rate constants at discrete photon energies

Absorbed dose rate to water at 0.2 cm and 1 cm due to a point isotropic photon source as a function of photon energy is calculated using the EDKnrc user-code of the EGSnrc Monte Carlo system. This code system utilized widely used XCOM photon cross-section dataset for the calculation of absorbed dose to water. Using the above dose rates, dose rate constants are calculated. Air-kerma strength S k needed for deriving dose rate constant is based on the mass-energy absorption coefficient compilations of Hubbell and Seltzer published in the year 1995. A comparison of absorbed dose rates in water at the above distances to the published values reflects the differences in photon cross-section dataset in the low-energy region (difference is up to 2% in dose rate values at 1 cm in the energy range 30-50 keV and up to 4% at 0.2 cm at 30 keV). A maximum difference of about 8% is observed in the dose rate value at 0.2 cm at 1.75 MeV when compared to the published value. S k calculations based on the compilation of Hubbell and Seltzer show a difference of up to 2.5% in the low-energy region (20-50 keV) when compared to the published values. The deviations observed in the values of dose rate and S k affect the values of dose rate constants up to 3%

A multi-stage machine learning algorithm for estimating personal dose equivalent using thermoluminescent dosimeter

In the present age, marked by data-driven advancements in various fields, the importance of machine learning (ML) holds a prominent position. The ability of ML algorithms to resolve complex patterns and extract insights from large datasets has solidified its transformative potential in various scientific domains. This paper introduces an innovative application of ML techniques in the domain of radiation dosimetry. Specifically, it shows the applicability of ML in estimating the radiation dose received by occupational workers. This estimation is expressed in terms of personal dose equivalent, and it involves the utilization of thermoluminescence signals emitted by CaSO _4 :Dy-based personnel monitoring badges. To estimate personal dose equivalent, three-stage algorithm driven by ML models is proposed. This algorithm systematically identifies the photon energy ranges, calculates the average photon energy, and determines personal dose equivalent. By implementing this approach to the conventional three-element dosimeter, the study overcomes existing limitations and enhances accuracy in dose estimation. The algorithm demonstrates 97.8% classification accuracy in discerning photon energy ranges and achieves a coefficient of determination of 0.988 for estimating average photon energy. Importantly, it also reduces the coefficient of variation of relative deviations by up to 6% for estimated personal dose equivalent, compared to existing algorithms. The study improves accuracy and establishes a new methodology for evaluating radiation exposure to occupational workers using conventional thermoluminescent dosimeter badge