Lung Cancer Classification Using Modified Squeezenet

Lung cancer is the primary cause of mortality in individuals diagnosed with cancer. Detecting and diagnosing lung cancer early significantly reduces the mortality rate. The early diagnosis of lung cancer is greatly facilitated by medical imaging. The recommendation is to undergo a CT scan, as it has a higher probability of detecting lung cancer during its initial phases. The detection of lung cancer greatly depends on the utilization of advanced deep learning technology, specifically convolutional neural networks, which assist in accurately classifying the CT image. This paper proposed a Modified light weight SqueezeNet architecture that mixes bottleneck residual network and fully connected layer along with global average pooling in the original network. This modification enhances the classification performance with a slight rise in computational complexity.  CT images of 330 patients are used as a data set for testing the proposed technique, which is executed in MATLAB 2022a platform. The proposed method can identify lung cancer and categorize it as either malignant or normal with test Accuracy of 95.76%, Recall-92.94%, Precision of 98.75%, Specificity-98.75%, and AUC-0.9977. The Modified SqueezeNet gives better classification performance against the base SqueezeNet model. The proposed method outperforms traditional deep learning networks like AlexNet, ShuffleNet, ResNet-50, and GoogleNet

Self-repairing composites for corrosion protection: A review on recent strategies and evaluation methods

The use of self-healing coatings to protect metal substrates, such as aluminum alloys, stainless steel, carbon steel, and Mg alloys from corrosion is an important aspect for protecting metals and for the economy. During the past decade, extensive transformations on self-healing strategies were introduced in protective coatings, including the use of green components. Scientists used extracts of henna leaves, aloe vera, tobacco, etc. as corrosion inhibitors, and cellulose nanofibers, hallyosite nanotubes, etc. as healing agent containers. This review gives a concise description on the need for self-healing protective coatings for metal parts, the latest extrinsic self-healing strategies, and the techniques used to follow-up the self-healing process to control the corrosion of metal substrates. Common techniques, such as accelerated salt immersion test and electrochemical impedance spectroscopy (EIS), for evaluating the self-healing process in protective coatings are explained. We also show recent advancements procedures, such as scanning vibrating electrode technique (SVET) and scanning electrochemical microscopy (SECM), as successful techniques in evaluating the self-healing process in protective coatings.Qatar UniversityScopu

COVID-19-associated acute kidney injury: Consensus report of the 25th Acute Disease Quality Initiative (ADQI) workgroup

Kidney involvement in patients with coronavirus disease 2019 (COVID-19) is common, and can range from the presence of proteinuria and haematuria to acute kidney injury (AKI) requiring renal replacement therapy (RRT; also known as kidney replacement therapy). COVID-19-associated AKI (COVID-19 AKI) is associated with high mortality and serves as an independent risk factor for all-cause in-hospital death in patients with COVID-19. The pathophysiology and mechanisms of AKI in patients with COVID-19 have not been fully elucidated and seem to be multifactorial, in keeping with the pathophysiology of AKI in other patients who are critically ill. Little is known about the prevention and management of COVID-19 AKI. The emergence of regional \u27surges\u27 in COVID-19 cases can limit hospital resources, including dialysis availability and supplies; thus, careful daily assessment of available resources is needed. In this Consensus Statement, the Acute Disease Quality Initiative provides recommendations for the diagnosis, prevention and management of COVID-19 AKI based on current literature. We also make recommendations for areas of future research, which are aimed at improving understanding of the underlying processes and improving outcomes for patients with COVID-19 AKI

Muscle fiber conduction velocity is more affected after eccentric than concentric exercise

It has been shown that mean muscle fiber conduction velocity (CV) can be acutely impaired after eccentric exercise. However, it is not known whether this applies to other exercise modes. Therefore, the purpose of this experiment was to compare the effects of eccentric and concentric exercises on CV, and amplitude and frequency content of surface electromyography (sEMG) signals up to 24 h post-exercise. Multichannel sEMG signals were recorded from biceps brachii muscle of the exercised arm during isometric maximal voluntary contraction (MVC) and electrically evoked contractions induced by motor-point stimulation before, immediately after and 2 h after maximal eccentric (ECC group, N = 12) and concentric (CON group, N = 12) elbow flexor exercises. Isometric MVC decreased in CON by 21.7 ± 12.0% (± SD, p < 0.01) and by 30.0 ± 17.7% (p < 0.001) in ECC immediately post-exercise when compared to baseline. At 2 h post-exercise, ECC showed a reduction in isometric MVC by 24.7 ± 13.7% (p < 0.01) when compared to baseline, while no significant reduction (by 8.0 ± 17.0%, ns) was observed in CON. Similarly, reduction in CV was observed only in ECC both during the isometric MVC (from baseline of 4.16 ± 0.3 to 3.43 ± 0.4 m/s, p < 0.001) and the electrically evoked contractions (from baseline of 4.33 ± 0.4 to 3.82 ± 0.3 m/s, p < 0.001). In conclusion, eccentric exercise can induce a greater and more prolonged reduction in muscle force production capability and CV than concentric exercis

TiO2 nanotubes and mesoporous silica as containers in self-healing epoxy coatings

The potential of inorganic nanomaterials as reservoirs for healing agents is presented here. Mesoporous silica (SBA-15) and TiO2 nanotubes (TNTs) were synthesized. Both epoxy-encapsulated TiO2 nanotubes and amine-immobilized mesoporous silica were incorporated into epoxy and subsequently coated on a carbon steel substrate. The encapsulated TiO2 nanotubes was quantitatively estimated using a ‘dead pore ratio’ calculation. The morphology of the composite coating was studied in detail using transmission electron microscopic (TEM) analysis. The self-healing ability of the coating was monitored using electrochemical impedance spectroscopy (EIS); the coating recovered 57% of its anticorrosive property in 5 days. The self-healing of the scratch on the coating was monitored using Scanning Electron Microscopy (SEM). The results confirmed that the epoxy pre-polymer was slowly released into the crack. The released epoxy pre-polymer came into contact with the amine immobilized in mesoporous silica and cross-linked to heal the scratch.This paper was made possible by PDRA grant # PDRA1-1216-13014 from the Qatar National Research Fund (a member of Qatar Foundation)

Structural insights into the polypharmacological activity of quercetin on serine/threonine kinases

Polypharmacology, the discovery or design of drug molecules that can simultaneously interact with multiple targets, is gaining interest in contemporary drug discovery. Serine/threonine kinases are attractive targets for therapeutic intervention in oncology due to their role in cellular phosphorylation and altered expression in cancer. Quercetin, a naturally occurring flavonoid, inhibits multiple cancer cell lines and is used as an anticancer drug in Phase I clinical trial. Quercetin glycosides have also received some attention due to their high bioavailability and activity against various diseases including cancer. However, these have been studied to a lesser extent. In this study, the structural basis of the multitarget inhibitory activity of quercetin and isoquercitrin, a glycoside derivative, on serine/threonine kinases using molecular modeling was explored. Structural analysis showed that both quercetin and isoquercitrin exhibited good binding energies and interacted with aspartate in the highly conserved Asp–Phe–Gly motif. The results indicate that isoquercitrin could be a more potent inhibitor of several members of the serine/threonine kinase family. In summary, the current structural evaluation highlights the multitarget inhibitory property of quercetin and its potential to be a chemical platform for oncological polypharmacology

Inorganic Porous Materials Based Epoxy Self-Healing Coatings

The long-term stability of protective coating for metal is critically important for structural applications [1, 2]. Self-healing ability extend the service life of protective coatings leading to a significant reduction in maintenance cost for oil and gas pipe lines and structural parts in civil and construction industry. Recently, the self-healing technology based on healing agent loaded containers has been receiving attention [3, 4]. The incorporation of self- healing agent loaded containers into polymer matrix can be carried out using existing blending techniques. Hence, this technology facilitate large-scale application of self-healing materials [5]. Different micro or nano containers has been used for the storage and release of self-healing agents upon specific corrosion triggering conditions (e.g. on pH change) or upon mechanical damage [6]. Polymer capsules, polymer nanofibers, hollow glass bubbles, hollow glass fibers etc. were used by the researchers to load the healing agent inside their cavity. The inorganic particles with nano cavity offers large surface area, high pore volume and good stability favorable for the storage of the healing agents. Moreover, the usage of inorganic nanomaterials as reservoirs for healing agent can eliminate the tedious encapsulation process. The present study aims to use inorganic nanotubes and mesoporous silica as containers for healing agents in epoxy coating. The ability of Halloysite nanotubes (HNT), titanium dioxide (TiO2) nanotube and mesoporous silica to load and release the healing agents are investigated and compared their performance. Among them, Halloysite nanotubes are naturally occurring clay mineral. Meanwhile, TiO2 nanotube and mesoporous silica are synthesised in laboratory and characterised using scanning electron microscopic (SEM), transmission electron microscopic (TEM) techniques and Brunauer-Emmett-Teller (BET) surface area analysis. The morphology of the nanotubes and mesoporous silica are shown in Fig. 1 (in supporting file). In this study, the epoxy pre-polymer and hardener are used as healing agents. Containers loaded with epoxy and hardener can provide a repair system with matching chemical entity with host epoxy coating. Both epoxy encapsulated nanotubes (either Halloysite or TiO2 nanotubes) and amine immobilized mesoporous silica are incorporated into epoxy, followed by the addition of diethylenetriamine curing agent. The mixture is coated on the metal with an average thickness of 300 ?m. The controlled epoxy coatings are also prepared without nanotube and mesoporous silica. Epoxy coating loaded with encapsulated Halloysite nanotubes and immobilized mesoporous silica is abbreviated as 'EP/HNT/SiO2' and the one loaded with encapsulated TiO2 nanotubes and immobilized mesoporous silica is abbreviated as 'EP/ TiO2/SiO2'. The self-healing ability of the scratched coatings is monitored by electrochemical impedance spectroscopy (EIS) in definite time intervals for 5 days. Both EIS bode plots and tafel polarization curves are analysed to observe the self-healing ability of the coatings. For the scratched controlled epoxy coating, after an immersion time of 24 hours, the impedance curve drop to its minimum value over the entire frequency range and on further immersion period the impedance curve remains its minimum value. However, in the case of self-healing coatings, the initially declined impedance value recovers in successive days. The recovery in low frequency impedance values (at 0.01 Hz), which is a direct reflection of the recovery of corrosion resistance of the coating are evaluated. While EP/TiO2/SiO2 coating recovered 57% of its anticorrosive property, the EP/HNT/SiO2 coating recovered only 0.026%. This results suggest that the nature of the nanotubes affect the amount and rate of healing agent released into the scratched area from the tube lumen which itself affect the self-healing ability of the coating. SEM is also used to observe the healed scratches on the coatings. After 96 hours of immersion in 3.5 wt% NaCl solution, the scratches in EP/TiO2/SiO2 self-healing coatings are found to be almost covered. The results confirm the effective self-healing ability of the EP/TiO2/SiO2 coating in which the released epoxy pre-polymer from nanotube lumen get contact with the amine hardener immobilized in mesoporous silica and cross-link to cover the scratch. Acknowledgment: This abstract was made possible by PDRA grant # PDRA1-1216-13014 from the Qatar national research fund (a member of Qatar foundation).qscienc

An atlas of healthy and injured cell states and niches in the human kidney

Understanding kidney disease relies on defining the complexity of cell types and states, their associated molecular profiles and interactions within tissue neighbourhood

Integrins as therapeutic targets: lessons and opportunities.

The integrins are a large family of cell adhesion molecules that are essential for the regulation of cell growth and function. The identification of key roles for integrins in a diverse range of diseases, including cancer, infection, thrombosis and autoimmune disorders, has revealed their substantial potential as therapeutic targets. However, so far, pharmacological inhibitors for only three integrins have received marketing approval. This article discusses the structure and function of integrins, their roles in disease and the chequered history of the approved integrin antagonists. Recent advances in the understanding of integrin function, ligand interaction and signalling pathways suggest novel strategies for inhibiting integrin function that could help harness their full potential as therapeutic targets

A survey on artificial intelligence techniques for various wastewater treatment processes

Pollutant removal percentage is a key parameter for every WWTPs, and it is crucial to predict pollutant removal efficiency. The efficiency of pollutant removal processes can be increased with the help of modeling and its optimization. Statistical models are not practical enough for wastewater treatments due to complicated relationship among input and output parameters. AI models are generally more flexible while modeling complex datasets with missing data and nonlinearities. Many AI techniques are available, and the aim is to sort out the best AI technique to design predictive models for WWTPs. Deep Learning and Ensemble are the main techniques reviewed in this work. The Ensemble Learning models showing the most successful performance among other techniques by generally showed their accuracy and efficiency