Exploring fetal brain tumor glioblastoma symptom verification with self organizing maps and vulnerability data analysis.

Brain tumor glioblastoma is a disease that is caused for a child who has abnormal cells in the brain, which is found using MRI "Magnetic Resonance Imaging" brain image using a powerful magnetic field, radio waves, and a computer to produce detailed images of the body's internal structures it is a standard diagnostic tool for a wide range of medical conditions, from detecting brain and spinal cord injuries to identifying tumors and also in evaluating joint problems. This is treatable, and by enabling the factor for happening, the factor for dissolving the dead tissues. If the brain tumor glioblastoma is untreated, the child will go to death; to avoid this, the child has to treat the brain problem using the scan of MRI images. Using the neural network, brain-related difficulties have to be resolved. It is identified to make the diagnosis of glioblastoma. This research deals with the techniques of max rationalizing and min rationalizing images, and the method of boosted division time attribute extraction has been involved in diagnosing glioblastoma. The process of maximum and min rationalization is used to recognize the Brain tumor glioblastoma in the brain images for treatment efficiency. The image segment is created for image recognition. The method of boosted division time attribute extraction is used in image recognition with the help of MRI for image extraction. The proposed boosted division time attribute extraction method helps to recognize the fetal images and find Brain tumor glioblastoma with feasible accuracy using image rationalization against the brain tumor glioblastoma diagnosis. In addition, 45% of adults are affected by the tumor, 40% of children and 5% are in death situations. To reduce this ratio, in this study, the Brain tumor glioblastoma is identified and segmented to recognize the fetal images and find the Brain tumor glioblastoma diagnosis. Then the tumor grades were analyzed using the efficient method for the imaging MRI with the diagnosis result of partially high. The accuracy of the proposed TAE-PIS system is 98.12% which is higher when compared to other methods like Genetic algorithm, Convolution neural network, fuzzy-based minimum and maximum neural network and kernel-based support vector machine respectively. Experimental results show that the proposed method archives rate of 98.12% accuracy with low response time and compared with the Genetic algorithm (GA), Convolutional Neural Network (CNN), fuzzy-based minimum and maximum neural network (Fuzzy min-max NN), and kernel-based support vector machine. Specifically, the proposed method achieves a substantial improvement of 80.82%, 82.13%, 85.61%, and 87.03% compared to GA, CNN, Fuzzy min-max NN, and kernel-based support vector machine, respectively.

Optimized machine learning model for air quality index prediction in major cities in India.

Industrial advancements and utilization of large amount of fossil fuels, vehicle pollution, and other calamities increases the Air Quality Index (AQI) of major cities in a drastic manner. Major cities AQI analysis is essential so that the government can take proper preventive, proactive measures to reduce air pollution. This research incorporates artificial intelligence in AQI prediction based on air pollution data. An optimized machine learning model which combines Grey Wolf Optimization (GWO) with the Decision Tree (DT) algorithm for accurate prediction of AQI in major cities of India. Air quality data available in the Kaggle repository is used for experimentation, and major cities like Delhi, Hyderabad, Kolkata, Bangalore, Visakhapatnam, and Chennai are considered for analysis. The proposed model performance is experimentally verified through metrics like R-Square, RMSE, MSE, MAE, and accuracy. Existing machine learning models, like k-nearest Neighbor, Random Forest regressor, and Support vector regressor, are compared with the proposed model. The proposed model attains better prediction performance compared to traditional machine learning algorithms with maximum accuracy of 88.98% for New Delhi city, 91.49% for Bangalore city, 94.48% for Kolkata, 97.66% for Hyderabad, 95.22% for Chennai and 97.68% for Visakhapatnam city.

Sex-specific differences in systemic immune responses in MIS-C children.

Multisystem Inflammatory Syndrome in Children (MIS-C) is a rare manifestation of Severe Acute Respiratory Syndrome-CoronaVirus-2 (SARS-CoV-2) infection that can result in increased morbidity and mortality. Mounting evidence describes sex disparities in the clinical outcomes of coronavirus disease 2019 (COVID-19). However, there is a lack of information on sex-specific differences in immune responses in MIS-C. This study is an observational and cross-sectional study and we wanted to examine immune parameters such as cytokines, chemokines, acute phase proteins (APPs), growth factors, microbial translocation markers (MTMs), complement components and matrix metalloproteinases (MMPs) in MIS-C children, based on sex. Male children were associated with heightened levels of pro-inflammatory cytokines-IFNγ, IL-2, TNFα, IL-1α, IL-1ß, IL-6, IL-12, G-CSF and GM-CSF, chemokines-CCL2, CCL11, CXCL1, CXCL8 and CXCL10, acute phase proteins-α-2M, CRP, growth factors VEGF and TGFα, microbial translocation markers- iFABP, LBP, EndoCAb, complement components-C1q, MBL and C3 and matrix metalloproteinases MMP-8 and MMP-9 compared to female children with MIS-C. These results indicate that the heightened immune response in males is a characteristic feature of MIS-C. These findings might explain the differential disease pathogenesis in males compared to females with MIS-C and facilitate a deeper understanding of this disease.

Other Causes of Chronic Diarrhea in Children.

Chronic diarrhea is still an important cause of morbidity and mortality in children. There are several causes of chronic diarrhea which may be due to intestinal, extra-intestinal or underlying systemic diseases. The etiology varies depending on the age of onset and may include both common and uncommon disorders. In this article some of the uncommon disorders such as immune deficiencies, intestinal lymphangiectasias, drug induced diarrhea, eosinophilic gastrointestinal disorders, endocrinopathies, neuroendocrine secretory tumors, malignancy and factitious diarrhea have been included. Though these disorders are uncommon it is essential that they are considered in select situations as detailed below and evaluated so that definitive therapy may be offered.

Multisystem inflammatory syndrome in children characterized by enhanced antigen-specific T-cell expression of cytokines and its reversal following recovery.

Background: Multisystem inflammatory syndrome (MIS) in children is considered to be a post-infectious complication of COVID-19. T-cell responses in children with this condition have not been well-studied. Methods: We aimed to study the immune responses in children with MIS in comparison to children with acute COVID-19 and children with other infections. Whole blood was stimulated with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)-specific antigens and flow cytometry was performed to examine CD4+ and CD8+ T-cell responses. Results: Children with MIS had higher frequencies of CD4+ and CD8+ T cells expressing cytokines at baseline and upon SARS-CoV-2 antigen-specific stimulation in comparison to children with COVID-19 and/or other infections. Children with COVID-19 also exhibited higher frequencies of CD4+ and CD8+ T cells expressing cytokines at baseline and upon SARS-CoV-2 antigen-specific stimulation in comparison to children with other infections. At 6-9 months following treatment and recovery, this enhanced response against SARS-CoV-2 antigens was down modulated in children with MIS. Conclusion: Our study, therefore, provides evidence of enhanced activation of CD4+ and CD8+ T-cell responses in children with MIS and reversal following recovery.

Role of matrix metalloproteinases in multi-system inflammatory syndrome and acute COVID-19 in children.

Introduction: Multisystem Inflammatory Syndrome in children (MIS-C) is a serious inflammatory sequela of SARS-CoV2 infection. The pathogenesis of MIS-C is vague and matrix metalloproteinases (MMPs) may have an important role. Matrix metalloproteinases (MMPs) are known drivers of lung pathology in many diseases. Methods: To elucidate the role of MMPs in pathogenesis of pediatric COVID-19, we examined their plasma levels in MIS-C and acute COVID-19 children and compared them to convalescent COVID-19 and children with other common tropical diseases (with overlapping clinical manifestations). Results: Children with MIS-C had elevated levels of MMPs (P < 0.005 statistically significant) in comparison to acute COVID-19, other tropical diseases (Dengue fever, typhoid fever, and scrub typhus fever) and convalescent COVID-19 children. PCA and ROC analysis (sensitivity 84-100% and specificity 80-100%) showed that MMP-8, 12, 13 could help distinguish MIS-C from acute COVID-19 and other tropical diseases with high sensitivity and specificity. Among MIS-C children, elevated levels of MMPs were seen in children requiring intensive care unit admission as compared to children not needing intensive care. Similar findings were noted when children with severe/moderate COVID-19 were compared to children with mild COVID-19. Finally, MMP levels exhibited significant correlation with laboratory parameters, including lymphocyte counts, CRP, D-dimer, Ferritin and Sodium levels. Discussion: Our findings suggest that MMPs play a pivotal role in the pathogenesis of MIS-C and COVID-19 in children and may help distinguish MIS-C from other conditions with overlapping clinical presentation.

Unique cellular immune signatures of multisystem inflammatory syndrome in children.

The clinical presentation of MIS-C overlaps with other infectious/non-infectious diseases such as acute COVID-19, Kawasaki disease, acute dengue, enteric fever, and systemic lupus erythematosus. We examined the ex-vivo cellular parameters with the aim of distinguishing MIS-C from other syndromes with overlapping clinical presentations. MIS-C children differed from children with non-MIS-C conditions by having increased numbers of naïve CD8+ T cells, naïve, immature and atypical memory B cells and diminished numbers of transitional memory, stem cell memory, central and effector memory CD4+ and CD8+ T cells, classical, activated memory B and plasma cells and monocyte (intermediate and non-classical) and dendritic cell (plasmacytoid and myeloid) subsets. All of the above alterations were significantly reversed at 6-9 months post-recovery in MIS-C. Thus, MIS-C is characterized by a distinct cellular signature that distinguishes it from other syndromes with overlapping clinical presentations. Trial Registration: ClinicalTrials.gov clinicaltrial.gov. No: NCT04844242.

Enhanced Severe Acute Respiratory Syndrome Coronavirus 2 Antigen-Specific Systemic Immune Responses in Multisystem Inflammatory Syndrome in Children and Reversal After Recovery.

BACKGROUND: Multisystem inflammatory syndrome in children (MIS-C) presents with inflammation and pathology of multiple organs in the pediatric population in the weeks following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. METHODS: We characterized the SARS-CoV-2 antigen-specific cytokine and chemokine responses in children with MIS-C, coronavirus disease 2019 (COVID-19), and other infectious diseases. RESULTS: MIS-C is characterized by elevated levels of type 1 (interferon-γ, interleukin [IL] 2), type 2 (IL-4, IL-13), type 17 (IL-17), and other proinflammatory cytokines (IL-1α, IL-6, IL-12p70, IL-18, and granulocyte-macrophage colony-stimulating factor) in comparison to COVID-19 and other infectious diseases following stimulation with SARS-CoV-2-specific antigens. Similarly, upon SARS-CoV-2 antigen stimulation, CCL2, CCL3, and CXCL10 chemokines were significantly elevated in children with MIS-C in comparison to the other 2 groups. Principal component analysis based on these cytokines and chemokines could clearly distinguish MIS-C from both COVID-19 and other infections. In addition, these responses were significantly diminished and normalized 6-9 months after recovery. CONCLUSIONS: Our data suggest that MIS-C is characterized by an enhanced production of cytokines and chemokines that may be associated with disease pathogenesis.

Control of the Cu morphology on Ru-passivated and Ru-doped TaN surfaces - promoting growth of 2D conducting copper for CMOS interconnects.

Prolonging the lifetime of Cu as a level 1 and level 2 interconnect metal in future nanoelectronic devices is a significant challenge as device dimensions continue to shrink and device structures become more complex. At nanoscale dimensions Cu exhibits high resistivity which prevents its functioning as a conducting wire and prefers to form non-conducting 3D islands. Given that changing from Cu to an alternative metal is challenging, we are investigating new materials that combine properties of diffusion barriers and seed liners to reduce the thickness of this layer and to promote successful electroplating of Cu to facilitate the coating of high-aspect ratio interconnect vias and to allow for optimal electrical conductance. In this study we propose new combined barrier/liner materials based on modifying the surface layer of the TaN barrier through Ru incorporation. Simulating a model Cu29 structure at 0 K and through finite temperature ab initio molecular dynamics on these surfaces allows us to demonstrate how the Ru content can control copper wetting, adhesion and thermal stability properties. Activation energies for atom migrations onto a nucleating copper island allow insight into the growth mechanism of a Cu thin-film. Using this understanding allows us to tailor the Ru content on TaN to control the final morphology of the Cu film. These Ru-modified TaN films can be deposited by atomic layer deposition, allowing for fine control over the film thickness and composition.

Hemosuccus pancreatitis due to a ruptured splenic artery pseudoaneurysm - diagnosis and endovascular management.

Hemosuccus pancreatitis is a rare and potentially fatal cause of upper gastrointestinal bleeding characterized by hemorrhage from the ampulla of Vater via the pancreatic duct. In this case, a patient with chronic pancreatitis on a background of chronic alcoholism is found to have a splenic artery pseudoaneurysm that was bleeding into the pancreatic duct. This was identified on contrast-enhanced computed tomography imaging and successfully managed via microcoil embolization.

Mechanism of Thermal Atomic Layer Etch of W Metal Using Sequential Oxidation and Chlorination: A First-Principles Study.

Thermal atomic layer etch (ALE) of W metal can be achieved by sequential self-limiting oxidation and chlorination reactions at elevated temperatures. In this paper, we analyze the reaction mechanisms of W ALE using the first-principles simulation. We show that oxidizing agents such as O2, O3, and N2O can be used to produce a WOx surface layer in the first step of an ALE process with ozone being the most reactive. While the oxidation pulse on clean W is very exergonic, our study suggests that runaway oxidation of W is not thermodynamically favorable. In the second ALE pulse, WCl6 and Cl2 remove the oxidized surface W atoms by the formation of volatile tungsten oxychloride (WxOyClz) species. In this pulse, each adsorbed WCl6 molecule was found to remove one surface W atom with a moderate energy cost. Our calculations further show that the desorption of the additional etch products is endothermic by up to 4.7 eV. Our findings are consistent with the high temperatures needed to produce ALE in experiments. In total, our quantum chemical calculations have identified the lowest energy pathways for ALE of tungsten metal along with the most likely etch products, and these findings may help guide the development of improved etch reagents.

The role of Ru passivation and doping on the barrier and seed layer properties of Ru-modified TaN for copper interconnects.

Size reduction of the barrier and liner stack for copper interconnects is a major bottleneck in further down-scaling of transistor devices. The role of the barrier is to prevent diffusion of Cu atoms into the surrounding dielectric, while the liner (also referred to as a seed layer) ensures that a smooth Cu film can be electroplated. Therefore, a combined barrier + liner material that restricts the diffusion of Cu into the dielectric and allows for copper electro-deposition is needed. In this paper, we have explored barrier + liner materials composed of 1 and 2 monolayers (MLs) of Ru-passivated ϵ-TaN and Ru doped ϵ-TaN and focused on their interactions with Cu through the adsorption of small Cu clusters with 1-4 atoms. Moreover, different doping patterns for Ru doping in TaN are investigated to understand how selective doping of the ϵ-TaN surface influences surface stability. We found that an increased concentration of Ru atoms in the outermost Ta layer improves the adhesion of Cu. The strongest binding of the Cu atoms was found on the 100% Ru doped surface followed by the 1 ML Ru passivated surface. These two surfaces are recommended for the combined barrier + liner for Cu interconnects. The closely packed arrangements of Cu were found to exhibit weak Cu-slab and strong Cu-Cu interactions, whereas the sparse arrangements of Cu exhibit strong Cu-slab and weak Cu-Cu interactions. The Cu atoms seem to bind more favorably when they are buried in the doped or passivated surface layer due to the increase in their coordination number. This is facilitated by the surface distortion arising from the ionic radius mismatch between Ta and Ru. We also show that the strong Cu-Cu interaction alone cannot predict the association of Cu atoms as a few 2D Cu clusters showed stronger Cu-Cu interaction than the 3D clusters, highlighting the importance of Cu-surface interactions.

The Complex Relationship between Mesenteric Panniculitis and Malignancy - A Holistic Approach is Still Needed to Understand the Diagnostic Uncertainties.

Mesenteric panniculitis is an idiopathic, localized inflammation involving the adipose tissue of the small bowel mesentery. The association of mesenteric panniculitis with malignancy, predominantly lymphomas, has been widely reported in the medical literature. In this review article, we will discuss the clinical guidelines in the diagnosis and management of mesenteric panniculitis and the clinical association between mesenteric panniculitis and malignancies.

Neural network molecular dynamics simulations of solid-liquid interfaces: water at low-index copper surfaces.

Solid-liquid interfaces have received considerable attention in recent years due to their central role in many technologically relevant fields like electrochemistry, heterogeneous catalysis and corrosion. As the chemical processes in these examples take place primarily at the interface, understanding the structural and dynamical properties of the interfacial water molecules is of vital importance. Here, we use a first-principles quality high-dimensional neural network potential built from dispersion-corrected density functional theory data in molecular dynamics simulations to investigate water-copper interfaces as a prototypical case. After performing convergence tests concerning the required supercell size and water film diameter, we investigate numerous properties of the interfacial water molecules at the low-index copper (111), (100) and (110) surfaces. These include density profiles, hydrogen bond properties, lateral mean squared displacements and residence times of the water molecules at the surface. We find that in general the copper-water interaction is rather weak with the strongest interactions observed at the Cu(110) surface, followed by the Cu(100) and Cu(111) surfaces. The distribution of the water molecules in the first hydration layer exhibits a double peak structure. In all cases, the molecules closest to the surface are predominantly allocated on top of the metal sites and are aligned nearly parallel with the oxygen pointing slightly to the surface. The more distant molecules in the first hydration layer at the Cu(111) and Cu(100) surfaces are mainly found in between the top sites, whereas at the Cu(110) surface most of these water molecules are found above the trenches of the close packed atom rows at the surface.

Nasopharyngeal aspirate & blood cytokine profile in infants hospitalized for respiratory syncytial virus bronchiolitis: A pilot study from south India.

BACKGROUND & OBJECTIVES: Following a respiratory syncytial virus (RSV) bronchiolitis, only some infants develop serious illness, and a proportion of them develop recurrent wheeze subsequently. Studies have revealed that cytokine expression following RSV infection may influence the severity and also the risk for subsequent reactive airway disease. This present study was conducted to determine the blood, and nasopharyngeal aspirate (NPA) cytokine profile among infants admitted for RSV bronchiolitis. METHODS: In this prospective pilot study, a sample size of 15 cases and 15 controls was included. Detailed history, physical examination, blood sample and NPA collection were done. Cytokines (IFNγ and IL-4) estimation was done in the blood and NPA samples of cases and blood samples of controls. RESULTS: The mean levels of interferon gamma in controls (blood) and cases (NPA and blood) were 5.95, 9.54 and 32.02 pg/ml, respectively. The mean levels of interleukin-4 in controls (blood), and cases (NPA and blood) were 1280.77, 956.08 and 692.37 pg/ml, respectively (P<0.05). INTERPRETATION & CONCLUSIONS: Our study showed that infants with RSV bronchiolitis evoked a Th1 response in both blood and NPA. Large multicentre studies are needed to validate our findings.

Representing the potential-energy surface of protonated water clusters by high-dimensional neural network potentials.

Investigating the properties of protons in water is essential for understanding many chemical processes in aqueous solution. While important insights can in principle be gained by accurate and well-established methods like ab initio molecular dynamics simulations, the computational costs of these techniques are often very high. This prevents studying large systems on long time scales, which is severely limiting the applicability of computer simulations to address a wide range of interesting phenomena. Developing more efficient potentials enabling the simulation of water including dissociation and recombination events with first-principles accuracy is a very challenging task. In particular protonated water clusters have become important model systems to assess the reliability of such potentials, as the presence of the excess proton induces substantial changes in the local hydrogen bond patterns and many energetically similar isomers exist, which are extremely difficult to describe. In recent years it has been demonstrated for a number of systems including neutral water clusters of varying size that neural networks (NNs) can be used to construct potentials with close to first-principles accuracy. Based on density-functional theory (DFT) calculations, here we present a reactive full-dimensional NN potential for protonated water clusters up to the octamer. A detailed investigation of this potential shows that the energetic, structural, and vibrational properties are in excellent agreement with DFT results making the NN approach a very promising candidate for developing a high-quality potential for water. This finding is further supported by first preliminary but very encouraging NN-based simulations of the bulk liquid.