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101.
Prediction of the in vivo performance of the drug product from the in vitro studies is the major challenging job for the pharmaceutical industries. From the current regulatory perspective, biorelevant dissolution media should now be considered as quality control media in order to avoid the risk associated. Physiological based pharmacokinetic models (PBPK) coupled with biorelevant dissolution medium is widely used in simulation and prediction of the plasma drug concentration and in vivo drug performance. The present investigation deals with the evaluation of biorelevant dissolution media as well as in vivo drug performance by PBPK modelling using STELLA® simulation software. The PBPK model was developed using STELLA® using dissolution kinetics, solubility, standard gastrointestinal parameters and post-absorptive disposition parameters. The drug product selected for the present study includes Linezolid film-coated immediate-release tablets (Zyvox), Tacrolimus prolonged-release capsules (Advagraf), Valganciclovir tablets (Valcyte) and Mesalamine controlled-release capsules (Pentasa) each belonging to different biopharmaceutics classification system (BCS). The simulated plasma drug concentration was analyzed and pharmacokinetic parameters were calculated and compared with the reported values. The result from the present investigation indicates that STELLA® when coupled with biorelevant dissolution media can predict the in vivo performance of the drug product with prediction error less than 20% irrespective of the dosage form (immediate release versus modified release) and BCS Classification. Thus, STELLA® can be used for in vivo drug prediction which will be helpful in generic drug development. 相似文献
102.
103.
A generalized method of combining non identical parameters like series and shunt resistance dependent photocurrents under open circuit conditions (Iphoa) and the loaded conditions (Ipha) have been deduced. It is found that in the case of series array, only Ipha is dependent upon shunt resistance, while in the case of parallel array both are dependent upon shunt resistance. 相似文献
104.
105.
Manik Dautta Luis Fernando Ayala-Cardona Noelle Davis Ashwin Aggarwal Jonghwa Park Shu Wang Liam Gillan Elina Jansson Mikko Hietala Hyunhyub Ko Jussi Hiltunen Ali Javey 《Advanced Materials Technologies》2023,8(6):2201187
Monitoring sweat secretion rate is essential for uncovering underlying physical conditions like hyperhidrosis, mental stress, and neural disorders. Often, flexible microfluidic sweat rate monitoring devices use tape as a means of attachment to the skin to tightly seal the collection area. While these single-use, adhesive-backed devices have lightweight and thin interfaces for mounting on the skin, their form factor complicates their potential integration with available commercial wearables, such as smartwatches. Here, a tape-free device, consisting of a 3D-printed sweat collector with a concave surface that is strapped onto the skin to form an effective seal, is presented. The materials, structure, and dimensions of the sweat collector are optimized for conformal device-to-skin contact and efficient capture of sweat. The collector is interfaced with a fluidic microchannel with embedded electrodes for continuous digital monitoring of sweat rate. Long-term exercise-induced local sweat rate from multiple body locations in both multi-subject and longitudinal studies is measured, depicting the correlation between the measured sweat profile and total body fluid loss. The simple installation procedure and reusability of this tape-free device make it a good candidate for integration with the band of a watch. 相似文献
106.
Prashant Bisht;Branson D Belle;Pallavi Aggarwal;Abhishek Ghosh;Wen Xing;Narinder Kaur;J. P. Singh;B. R. Mehta; 《Small (Weinheim an der Bergstrasse, Germany)》2024,20(23):2307037
This study employs novel growth methodologies and surface sensitization with metal nanoparticles to enhance and manipulate gas sensing behavior of two-dimensional (2D)SnS film. Growth of SnS films is optimized by varying substrate temperature and laser pulses during pulsed laser deposition (PLD). Thereafter, palladium (Pd), gold (Au), and silver (Ag) nanoparticles are decorated on as-grown film using gas-phase synthesis techniques. X-ray diffraction (XRD), Raman spectroscopy, and Field-emission scanning electron microscopy (FESEM) elucidate the growth evolution of SnS and the effect of nanoparticle decoration. X-ray photoelectron spectroscopy (XPS) analyses the chemical state and composition. Pristine SnS, Ag, and Au decorated SnS films are sensitive and selective toward NO2 at room temperature (RT). Ag nanoparticle increases the response of pristine SnS from 48 to 138% toward 2 ppm NO2, which indicates electronic and chemical sensitization effect of Ag. Pd decoration on SnS tunes its selectivity toward H2 gas with a response of 55% toward 70 ppm H2 and limit of detection (LOD) < 1 ppm. In situ Kelvin probe force microscopy (KPFM) maps the work function changes, revealing catalytic effect of Ag toward NO2 in Ag-decorated SnS and direct charge transfer between Pd and SnS during H2 exposure in Pd-decorated SnS. 相似文献
107.
Meenakshi Aggarwal;Vikas Khullar;Nitin Goyal;Rashi Rastogi;Aman Singh;Vanessa Yelamos Torres;Marwan Ali Albahar; 《International journal of imaging systems and technology》2024,34(2):e22994
Correct identification of tumor in brain images is critical for treatment. In the medical domain, class distributions of recorded data could differ with locations and require high levels of privacy while collaboratively training the deep learning (DL) models for classifications. The main aim of this paper is to propose a privacy-preserving collaborative model for the classification of brain tumor in heterogeneously distributed magnetic resonance imaging (MRI) images. In this paper, initially, an open-source dataset has been acquired and analyzed as per the required competencies. The acquired dataset has four types of MRI images: pituitary tumor, meningioma tumor, glioma tumor, and no tumor. First, the acquired dataset was analyzed using DL and transfer learning algorithms. By applying implementations of basic algorithms, better algorithms were identified for further implementations in a federated learning ecosystem. DenseNet201-based transfer learning was identified as a better neural network and further utilized for collaborative transfer learning implementations. Here, the paper also focused on developing a suitable system for a heterogeneous distributed tumor database. Heterogeneous data were converted from the available data by applying nonidentical data distribution. The study discovered that the federated DL models, involving multiple clients, exhibited superior performance compared to conventional pretrained models. The proposed framework possesses distinctive characteristics that distinguish it from existing classification methods for brain tumor identification, particularly in terms of ensuring data privacy for edge devices with limited resources. Due to these additional features, the framework stands as the optimal alternative solution for early diagnosis of brain tumor. 相似文献
108.
The crucial part of the software development cycle is software maintenance. The demands included in the software management are fault fixes and request to change or bring a new feature. If priority is not given to these demands, then it may lead to customer dissatisfaction, inefficient planning, and software failure as well. Therefore, it is important to study the severity of the bug reports to maintain the efficiency of the software. Various research has been conducted in the past to predict the severity of the paper using text mining focusing only on the content of the bug reports. The sentiment of the user while reporting a bug also plays a vital role. In this study, we will be focusing on two aspects, that is, sentiment and content to improve the prediction. We propose a prediction model based on LDA to study the content aspect and emotion analysis to study the sentiment aspect. The model is validated on the datasets collected from the Eclipse project using Convolutional Neural Network (CNN). The results show that the CNN model effectively utilizes the content and sentiment aspect of the data to handle the severity prediction. CNN has weight sharing feature that decreases the number of parameters used for training. It also improves generalization and overfitting is avoided The Accuracy, Precision, Recall, and F-measure are improved when both aspects are taken into account rather than considering only content. 相似文献
109.
Pooja Sarotra Gayatri Sharma Shevali Kansal Anjana Kumari Negi Ritu Aggarwal Rajat Sandhir Navneet Agnihotri 《Lipids》2010,45(9):785-798
n-3 Polyunsaturated fatty acids (PUFA) have a chemopreventive effect while n-6 PUFA promote carcinogenesis. The effect of
these essential fatty acids may be related to oxidative stress. Therefore, the study was designed to evaluate the effect of
different ratios of fish oil (FO) and corn oil (CO) in the prevention of colon cancer. Male Wistar rats were divided into
control, dimethylhydrazine dihydrochloride (DMH) treated, FO + CO (1:1) and FO + CO (2.5:1). All the groups, except the control
received a weekly injection of DMH for 4 weeks. The animals were sacrificed either 48 h later (initiation phase) or kept for
16 weeks (post initiation phase). DMH treatment in the initiation phase animals showed mild to moderate inflammation, decreased
ROS and TrxR activity, increased antioxidants, apoptosis and ACF multiplicity. The post initiation study showed severe inflammation
with hyperplasia, increased ACF multiplicity and ROS levels, a decrease in antioxidants and apoptosis. The FO + CO (1:1) treated
animals showed severe inflammation, a decrease in ROS, an increase in antioxidants and apoptosis in the initiation phase.
FO + CO (1:1) in the post initiation phase and FO + CO (2.5:1) in the initiation showed mild inflammation, increased ROS,
apoptosis and decreased antioxidants. There was a decrease in ACF multiplicity and ROS levels, increased antioxidants and
apoptosis in the post initiation phase study. The present study suggests that FO has a dose- and time-dependent chemopreventive
effect in colon cancer mediated through oxidative stress and apoptosis. 相似文献
110.
Tso Yee Fan Ripin D.J. Aggarwal R.L. Ochoa J.R. Bien Chann Tilleman M. Spitzberg J. 《IEEE journal of selected topics in quantum electronics》2007,13(3):448-459
Cryogenically cooled solid-state lasers promise a revolution in power scalability while maintaining a good beam quality because of significant improvements in efficiency and thermo-optic properties. This is particularly true for Yb lasers because of their relatively low quantum defect and relatively broadband absorption even at cryogenic temperatures. Thermo-optic properties of host materials, including thermal conductivity, thermal expansion, and refractive index at low temperature, are reviewed and data presented for YAG (ceramic and single crystal), GGG, GdVO4, and Y2O3. Spectroscopic properties of Yb:YAG and Yb:LiYF4 (YLF) including absorption cross sections, emission cross sections, and fluorescence lifetimes at cryogenic temperatures are characterized. Recent experiments have pushed the power from an end-pumped cryogenically cooled Yb:YAG laser to 455-W continuous-wave output power from 640-W incident pump power at an of M2 1.4. 相似文献