COVID-19 disease is a major health calamity in twentieth century, in which the infection is spreading at the global level. Developing countries like Bangladesh, India, and others are still facing a ...delay in recognizing COVID-19 cases. Hence, there is a need for immediate recognition with perfect identification of infection. This clear visualization helps to save the life of suspected COVID-19 patients. With the help of traditional RT-PCR testing, the combination of medical images and deep learning classifiers delivers more hopeful results with high accuracy in the prediction and recognition of COVID-19 cases. COVID-19 disease is recently researched through sample chest X-ray images, which have already proven its efficiency in lung diseases. To emphasize corona virus testing methods and to control the community spreading, the automatic detection process of COVID-19 is processed through the detailed medication reports from medical images. Although there are numerous challenges in the manual understanding of traces in COVID-19 infection from X-ray, the subtle differences among normal and infected X-rays can be traced by the data patterns of Convolutional Neural Network (CNN). To improve the detection performance of CNN, this paper plans to develop an Ensemble Learning with CNN-based Deep Features (EL-CNN-DF). In the initial phase, image scaling and median filtering perform the pre-processing of the chest X-ray images gathered from the benchmark source. The second phase is lung segmentation, which is the significant step for COVID detection. It is accomplished by the Adaptive Activation Function-based U-Net (AAF-U-Net). Once the lungs are segmented, it is subjected to novel EL-CNN-DF, in which the deep features are extracted from the pooling layer of CNN, and the fully connected layer of CNN are replaced with the three classifiers termed “Support Vector Machine (SVM), Autoencoder, Naive Bayes (NB)”. The final detection of COVID-19 is done by these classifiers, in which high ranking strategy is utilized. As a modification, a Self Adaptive-Tunicate Swarm Algorithm (SA-TSA) is adopted as a boosting algorithm to enhance the performance of segmentation and detection. The overall analysis has shown that the precision of the enhanced CNN by using SA-TSA was 1.02%, 4.63%, 3.38%, 1.62%, 1.51% and 1.04% better than SVM, autoencoder, NB, Ensemble, RNN and LSTM respectively. The comparative performance analysis on existing model proves that the proposed algorithm is better than other algorithms in terms of segmentation and classification of COVID-19 detection.
Acute cerebellitis with obstructive hydrocephalus post-Tetralogy of Fallot surgery is extremely rare but can present aggressively in pediatric cases. Early diagnosis is critical for prompt medical ...and surgical intervention. We report a fatal case in a 7-year-old boy post-surgery, where neurological symptoms rapidly progressed, leading to drowsiness and intermittent response to commands. Despite initial computed tomography scans showing no abnormality, subsequent scans revealed cerebellitis and hydrocephalus. Treatment with steroids, antibiotics, and cerebrospinal fluid drainage was unsuccessful, and the condition’s etiology remained unclear despite negative serological tests and cultures. This highlights the challenge of diagnosing and treating acute cerebellitis, especially when no specific cause is found and when deterioration is swift. The role of opioids in pediatric patients and their potential association with neurosurgical complications is also discussed, prompting further inquiry into postoperative symptoms and opioid-related risks in susceptible individuals.
We study the logical complexity of proofs in cyclic arithmetic ($\mathsf{CA}$), as introduced in Simpson '17, in terms of quantifier alternations of formulae occurring. Writing $C\Sigma_n$ for (the ...logical consequences of) cyclic proofs containing only $\Sigma_n$ formulae, our main result is that $I\Sigma_{n+1}$ and $C\Sigma_n$ prove the same $\Pi_{n+1}$ theorems, for all $n\geq 0$. Furthermore, due to the 'uniformity' of our method, we also show that $\mathsf{CA}$ and Peano Arithmetic ($\mathsf{PA}$) proofs of the same theorem differ only exponentially in size. The inclusion $I\Sigma_{n+1} \subseteq C\Sigma_n$ is obtained by proof theoretic techniques, relying on normal forms and structural manipulations of $\mathsf{PA}$ proofs. It improves upon the natural result that $I\Sigma_n$ is contained in $C\Sigma_n$. The converse inclusion, $C\Sigma_n \subseteq I\Sigma_{n+1}$, is obtained by calibrating the approach of Simpson '17 with recent results on the reverse mathematics of B\"uchi's theorem in Ko{\l}odziejczyk, Michalewski, Pradic & Skrzypczak '16 (KMPS'16), and specialising to the case of cyclic proofs. These results improve upon the bounds on proof complexity and logical complexity implicit in Simpson '17 and also an alternative approach due to Berardi & Tatsuta '17. The uniformity of our method also allows us to recover a metamathematical account of fragments of $\mathsf{CA}$; in particular we show that, for $n\geq 0$, the consistency of $C\Sigma_n$ is provable in $I\Sigma_{n+2}$ but not $I\Sigma_{n+1}$. As a result, we show that certain versions of McNaughton's theorem (the determinisation of $\omega$-word automata) are not provable in $\mathsf{RCA}_0$, partially resolving an open problem from KMPS '16.
COVID-19 and dermatology Das, Anupam
Indian journal of dermatology,
05/2021, Letnik:
66, Številka:
3
Journal Article
Recenzirano
Odprti dostop
The skin is believed to act as a mirror of the underlying systemic pathologies. A gamut of cutaneous manifestations in the background of COVID-19 have been described, some of which have been ...“claimed” to be highly indicative of the disease. However, many of the reported manifestations could be explained by the “Baader–Meinhof phenomenon.” Also known as frequency illusion, Baader-Meinhof phenomenon is a cognitive bias in which, after noticing something for the first time, there is a tendency to notice it more often, leading someone to believe that it has a high frequency (a form of selection bias). COVID toes (presence of purple or bluish lesions on the patient's feet and toes) were reported from different parts of the globe as a specific sign of COVID-19 disease. However, in the subsequent months, this phenomenon or “epiphenomenon” has been reported from many other centers. I believe that it is difficult to qualify COVID toes as a direct manifestation of the disease because the rate of the COVID-19 antigen test positivity among the affected patients has been found to be low.3 Akin to other viral infections, some of the frequently reported cutaneous manifestations include morbilliform rash, urticaria, erythema multiforme like lesions, and others. In the pediatric population, one interesting condition (multisystem inflammatory syndrome in children) is being increasingly reported; wherein the cutaneous manifestations have been found to simulate Kawasaki disease.4
Cancer incidence and mortality have both increased in the last decade and are predicted to continue to rise. Diagnosis and treatment of cancers are often hampered by the inability to specifically ...target neoplastic cells. Bioimprinting is a promising new approach to overcome shortfalls in cancer targeting. Highly specific recognition cavities can be made into polymer matrices to mimic lock-and-key actions seen in in vivo biological systems. Early studies concentrated on molecules and were inhibited by template size complexity. Surface imprinting allows the capture of increasingly complex motifs from polypeptides to single cell organisms and mammalian cells. Highly specific cell shape recognition can also be achieved by cell interaction with imprints that can be made into polymer matrices to mimic biological systems at a molecular level. Bioimprinting has also been used to achieve nanometre scale resolution imaging of cancer cells. Studies of bioimprint-based drug delivery on cancer cells have been recently trialled in vitro and show that this approach can potentially improve existing chemotherapeutic approaches. This review focuses on the possible applications of bioimprinting with particular regards to cancer understanding, diagnosis and therapy. Cell imprints, incorporated into biosensors can allow the limits of detection to be improved or negate the need for extensive patient sample processing. Similar cell imprinting platforms can be used for nanoscale imaging of cancer morphology, as well as to investigate topographical signalling of cancer cells in vitro. Lastly, bioimprints also have applications as selective drug delivery vehicles to tumours with the potential to decrease chemotherapy-related side effects.
Multidrug‐resistant bacterial infections can kill 700,000 individuals globally each year and is considered among the top 10 global health threats faced by humanity as the arsenal of antibiotics is ...becoming dry and alternate antibacterial molecule is in demand. Nanoparticles of curcumin exhibit appreciable broad‐spectrum antibacterial activity using unique and novel mechanisms and thus the process deserves to be reviewed and further researched to clearly understand the mechanisms. Based on the antibiotic resistance, infection, and virulence potential, a list of clinically important bacteria was prepared after extensive literature survey and all recent reports on the antibacterial activity of curcumin and its nanoformulations as well as their mechanism of antibacterial action have been reviewed. Curcumin, nanocurcumin, and its nanocomposites with improved aqueous solubility and bioavailability are very potential, reliable, safe, and sustainable antibacterial molecule against clinically important bacterial species that uses multitarget mechanism such as inactivation of antioxidant enzyme, reactive oxygen species‐mediated cellular damage, and inhibition of acyl‐homoserine‐lactone synthase necessary for quorum sensing and biofilm formation, thereby bypassing the mechanisms of bacterial antibiotic resistance. Nanoformulations of curcumin can thus be considered as a potential and sustainable antibacterial drug candidate to address the issue of antibiotic resistance.
We demonstrate that stimulus-responsive capillary-structured materials can be formed from hydrophobized calcium carbonate particles suspended in a non-polar phase (silicone oil) and bridged by very ...small amounts of a hydrogel as the secondary aqueous phase. Inclusion of thermally responsive polymers into the aqueous phase yielded a capillary-structured suspension whose rheology is controlled by a change in temperature and can increase its complex modulus by several orders of magnitude because of the gelation of the capillary bridges between the solid particles. We demonstrate that the rheology of the capillary suspension and its response upon temperature changes can be controlled by the gelling properties as little as 0.1 w/w % of the secondary aqueous phase containing 2 wt % of the gelling carbohydrate. Doping the secondary (aqueous) phase with methyl cellulose, which gels at elevated temperatures, gave capillary-structured materials whose viscosity and structural strength can increase by several orders of magnitude as the temperature is increased past the gelling temperature of the methyl cellulose solution. Increasing the methyl cellulose concentration from 0 to 2 w/w % in the secondary (aqueous) phase increases the complex modulus and the yield stress of the capillary suspension of 10 w/w % hydrophobized calcium carbonate in silicone oil by 2 orders of magnitude at a fixed temperature. By using an aqueous solution of a low melting point agarose as a secondary liquid phase, which melts as the temperature is raised, we produced capillary-structured materials whose viscosity and structural strength can decrease by several orders of magnitude as the temperature is increased past the melting temperature of the agarose solution. The development of thermally responsive capillary suspensions can find potential applications in structuring of smart home and personal care products as well as in temperature-triggered change in rheology and release of flavors in foods and actives in pharmaceutical formulations.
The article highlights the Development of a Process Monitoring Strategy for a multi-stage manufacturing facility laden with non-normal data. A multi-block variant of the modified independent ...component analysis (MICA)-based technique has been proposed for building of the said monitoring strategy. For validation of the monitoring strategy thus developed, a case study pertaining to a Copper Cathode Manufacturing Unit (CCMU) has been taking into account. The multi-block MICA (MBMICA)-based monitoring strategy provided a means for hierarchical monitoring and effectively negotiating with non-normal data for the chosen multi-stage CCMU. The detection of faults were achieved by employment of MBMICA score-based Hotelling T2 control chart whose control limit was estimated via application of bootstrap procedure. The fault detection was succeeded by fault diagnosis which was performed via application of appropriate fault diagnosis statistic. The said process monitoring strategy thus developed was able to detect and diagnose the detected fault(s) with appreciable accuracy for a multi-stage CCMU laden with non-normal data.
The conventional drug delivery systems made from organic- or inorganic-based materials suffer from some problems associated with uncontrolled drug release, biocompatibility, cytotoxicity, and so ...forth. To overcome these problems, zeolitic imidazole framework (ZIF) hybrid materials can be one of the solutions. Here, we report a very easy and successful encapsulation of an anticancer drug doxorubicin inside two ZIFs, namely, ZIF-7 and ZIF-8, which are little explored as drug delivery systems, and we studied the controlled release of the drug from these two ZIFs under external stimuli such as change in pH and upon contact with biomimetic systems. Experimental results demonstrate that ZIF-7 remains intact when the pH changes from physiological condition to acidic condition, whereas ZIF-8 successfully releases drug under acidic condition. Interestingly, both the ZIFs are excellent for drug release when they come in contact with micelles or liposomes. In the case of ZIF-8, the drug delivery can be controlled for 3 h, whereas its analogue ZIF-7 delivers the drug for a time span of 10 h. We explained the reluctance of ZIF-7 toward drug release in terms of rigidity. This study highlights that by using different ZIFs and liposomes, the drug release rate can be easily modulated, which implies ample possibility for ZIFs as a good drug delivery system. The study shows a novel strategy for easy drug encapsulation and its release in a controlled manner, which will help future development of the drug delivery system.
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