A novel BiOBr/rGO photocatalysts for degradation of organic and antibiotic pollutants under visible light irradiation: Tetracycline degradation pathways, kinetics, and mechanism insight.

In this study, the BiOBr/rGO nanocomposite photocatalysts are fabricated by a facile solvothermal method. The BiOBr growth on reduced graphene oxide (rGO) sheet could improve BiOBr's photocatalytic activity by increasing its adsorption ability, surface area, and charge carriers' separation efficiency. The prepared nanocomposites were characterized by XRD, Raman, FESEM, EDS, XPS, and UV-visible DRS. The BiOBr/rGO (BRG) nanocomposites showed improved photocatalytic activity for the photodegradation of Rhodamine B (RhB) dye and Tetracycline (TC) under visible light irradiation. Rhodamine B and tetracycline degradation efficiency were about 96% and 73% within 120 min under visible light irradiation. The PL analysis indicates that BiOBr/rGO nanocomposite exhibited maximum separation efficiency of photoinduced charge carriers. The trapping test confirmed that O2- and h+ are significant active photodegradation species. The GC-MS spectra detected the two plausible transformation routes of tetracycline degradation. The current work presented a low-cost and facile approach for fabricating Bi-based composites.

Numerical simulation of a fractional stochastic delay differential equations using spectral scheme: a comprehensive stability analysis.

The fractional stochastic delay differential equation (FSDDE) is a powerful mathematical tool for modeling complex systems that exhibit both fractional order dynamics and stochasticity with time delays. The purpose of this study is to explore the stability analysis of a system of FSDDEs. Our study emphasizes the interaction between fractional calculus, stochasticity, and time delays in understanding the stability of such systems. Analyzing the moments of the system's solutions, we investigate stochasticity's influence on FSDDS. The article provides practical insight into solving FSDDS efficiently using various numerical techniques. Additionally, this research focuses both on asymptotic as well as Lyapunov stability of FSDDS. The local stability conditions are clearly presented and also the effects of a fractional orders with delay on the stability properties are examine. Through a comprehensive test of a stability criteria, practical examples and numerical simulations we demonstrate the complexity and challenges concern with the analyzing FSDDEs.

NTRK Therapy among Different Types of Cancers, Review and Future Perspectives.

Neurotrophic tyrosine receptor kinase (NTRK) has been a remarkable therapeutic target for treating different malignancies, playing an essential role in oncogenic signaling pathways. Groundbreaking trials like NAVIGATE led to the approval of NTRK inhibitors by the Food and Drug Administration (FDA) to treat different malignancies, significantly impacting current oncology treatment. Accurate detection of NTRK gene fusion becomes very important for possible targeted therapy. Various methods to detect NTRK gene fusion have been applied widely based on sensitivity, specificity, and accessibility. The utility of different tests in clinical practice is discussed in this study by providing insights into their effectiveness in targeting patients who may benefit from therapy. Widespread use of NTRK inhibitors in different malignancies could remain limited due to resistance mechanisms that cause challenges to medication efficacy in addition to common side effects of the medications. This review provides a succinct overview of the application of NTRK inhibitors in various types of cancer by emphasizing the critical clinical significance of NTRK fusion gene detection. The discussion also provides a solid foundation for understanding the current challenges and potential changes for improving the efficacy of NTRK inhibitor therapy to treat different malignancies.

Enhancement in the dielectric and magnetic properties of Ni2+-Cu2+ co-doped BaFe11Cu1-xNixO19 hexaferrites (0.0 ≤ x ≤ 1.0).

Herein, Ni2+-Cu2+ co-doped barium hexaferrites (BaFe11Cu1-xNixO19, 0.0 ≤ x≤ 1.0 with an interval of 0.25) were successfully synthesized using a co-precipitation method. The formation of a magnetoplumbite structure with the P63/mmc space group was confirmed by Rietveld refinement of the obtained X-ray diffraction patterns. Microstructural investigations revealed grains in the shape of hexagonal plates, while co-doping resulted in a variation in the grain sizes of the prepared samples. X-ray photoelectron spectroscopy was performed to determine the valence state of iron in the prepared hexaferrites. Impedance spectroscopy analysis revealed that dielectric permittivity initially decreased with an increase in the co-dopant content up to x = 0.5 and then increased by two orders of magnitude for x = 1.0. Alternatively, resistive properties showed microstructural resistance values in the range 105-108 Ω, with the highest value obtained for the sample with x = 0.5. Furthermore, magnetic measurements indicated that all the prepared samples exhibited ferrimagnetic behaviour. Saturation magnetization and magnetic anisotropy values were found to be the highest for the sample with x = 1.0, which also had the lowest coercivity among the prepared samples. Herein, the observed variations in the obtained results can be explained by the variations in grain sizes and the Fe2+/Fe3+ ratio associated with the preferential occupation of co-dopants at octahedral sites. Based on our findings, the BaFe11Ni1O19 (x = 1.0) composition appears to be the most promising choice as a microwave absorption material among the prepared samples owing to the coexistence of high dielectric permittivity (>103 at 107 Hz) and saturation magnetization (73 emu g-1).

Up-regulation of GINS1 highlighted a good diagnostic and prognostic potential of survival in three different subtypes of human cancer

Abstract Cancer is a fatal malignancy and its increasing worldwide prevalence demands the discovery of more sensitive and reliable molecular biomarkers. To investigate the GINS1 expression level and its prognostic value in distinct human cancers using a series of multi-layered in silico approach may help to establish it as a potential shared diagnostic and prognostic biomarker of different cancer subtypes. The GINS1 mRNA, protein expression, and promoter methylation were analyzed using UALCAN and Human Protein Atlas (HPA), while mRNA expression was further validated via GENT2. The potential prognostic values of GINS1 were evaluated through KM plotter. Then, cBioPortal was utilized to examine the GINS1-related genetic mutations and copy number variations (CNVs), while pathway enrichment analysis was performed using DAVID. Moreover, a correlational analysis between GINS1 expression and CD8+ T immune cells and a the construction of gene-drug interaction network was performed using TIMER, CDT, and Cytoscape. The GINS1 was found down-regulated in a single subtypes of human cancer while commonly up-regulated in 23 different other subtypes. The up-regulation of GINS1 was significantly correlated with the poor overall survival (OS) of Liver Hepatocellular Carcinoma (LIHC), Lung Adenocarcinoma (LUAD), and Kidney renal clear cell carcinoma (KIRC). The GINS1 was also found up-regulated in LIHC, LUAD, and KIRC patients of different clinicopathological features. Pathways enrichment analysis revealed the involvement of GINS1 in two diverse pathways, while few interesting correlations were also documented between GINS1 expression and its promoter methylation level, CD8+ T immune cells level, and CNVs. Moreover, we also predicted few drugs that could be used in the treatment of LIHC, LUAD, and KIRC by regulating the GINS1 expression. The expression profiling of GINS1 in the current study has suggested it a novel shared diagnostic and prognostic biomarker of LIHC, LUAD, and KIRC.

Resumo O câncer é uma doença maligna fatal e sua crescente prevalência mundial exige a descoberta de biomarcadores moleculares mais sensíveis e confiáveis. Investigar o nível de expressão de GINS1 e seu valor prognóstico em cânceres humanos distintos, usando uma série de abordagens in silico em várias camadas, pode ajudar a estabelecê-lo como um potencial biomarcador de diagnóstico e prognóstico compartilhado de diferentes subtipos de câncer. O mRNA de GINS1, a expressão da proteína e a metilação do promotor foram analisados usando UALCAN e Human Protein Atlas (HPA), enquanto a expressão de mRNA foi posteriormente validada via GENT2. Os valores prognósticos potenciais de GINS1 foram avaliados por meio do plotter KM. Em seguida, o cBioPortal foi utilizado para examinar as mutações genéticas relacionadas ao GINS1 e as variações do número de cópias (CNVs), enquanto a análise de enriquecimento da via foi realizada usando DAVID. Além disso, uma análise correlacional entre a expressão de GINS1 e células imunes T CD8 + e a construção de uma rede de interação gene-droga foi realizada usando TIMER, CDT e Cytoscape. O GINS1 foi encontrado regulado negativamente em um único subtipo de câncer humano, enquanto comumente regulado positivamente em 23 outros subtipos diferentes. A regulação positiva de GINS1 foi significativamente correlacionada com a sobrevida global pobre (OS) de Carcinoma Hepatocelular de Fígado (LIHC), Adenocarcinoma de Pulmão (LUAD) e Carcinoma de Células Claras Renais de Rim (KIRC). O GINS1 também foi encontrado regulado positivamente em pacientes LIHC, LUAD e KIRC de diferentes características clínico-patológicas. A análise de enriquecimento de vias revelou o envolvimento de GINS1 em duas vias diversas, enquanto poucas correlações interessantes também foram documentadas entre a expressão de GINS1 e seu nível de metilação do promotor, nível de células imunes T CD8 + e CNVs. Além disso, também previmos poucos medicamentos que poderiam ser usados no tratamento de LIHC, LUAD e KIRC, regulando a expressão de GINS1. O perfil de expressão de GINS1 no estudo atual sugeriu que é um novo biomarcador de diagnóstico e prognóstico compartilhado de LIHC, LUAD e KIRC.

Up-regulation of GINS1 highlighted a good diagnostic and prognostic potential of survival in three different subtypes of human cancer / A regulação positiva de GINS1 destacou um bom potencial diagnóstico e prognóstico de sobrevivência em três subtipos diferentes de câncer humano

Abstract Cancer is a fatal malignancy and its increasing worldwide prevalence demands the discovery of more sensitive and reliable molecular biomarkers. To investigate the GINS1 expression level and its prognostic value in distinct human cancers using a series of multi-layered in silico approach may help to establish it as a potential shared diagnostic and prognostic biomarker of different cancer subtypes. The GINS1 mRNA, protein expression, and promoter methylation were analyzed using UALCAN and Human Protein Atlas (HPA), while mRNA expression was further validated via GENT2. The potential prognostic values of GINS1 were evaluated through KM plotter. Then, cBioPortal was utilized to examine the GINS1-related genetic mutations and copy number variations (CNVs), while pathway enrichment analysis was performed using DAVID. Moreover, a correlational analysis between GINS1 expression and CD8+ T immune cells and a the construction of gene-drug interaction network was performed using TIMER, CDT, and Cytoscape. The GINS1 was found down-regulated in a single subtypes of human cancer while commonly up-regulated in 23 different other subtypes. The up-regulation of GINS1 was significantly correlated with the poor overall survival (OS) of Liver Hepatocellular Carcinoma (LIHC), Lung Adenocarcinoma (LUAD), and Kidney renal clear cell carcinoma (KIRC). The GINS1 was also found up-regulated in LIHC, LUAD, and KIRC patients of different clinicopathological features. Pathways enrichment analysis revealed the involvement of GINS1 in two diverse pathways, while few interesting correlations were also documented between GINS1 expression and its promoter methylation level, CD8+ T immune cells level, and CNVs. Moreover, we also predicted few drugs that could be used in the treatment of LIHC, LUAD, and KIRC by regulating the GINS1 expression. The expression profiling of GINS1 in the current study has suggested it a novel shared diagnostic and prognostic biomarker of LIHC, LUAD, and KIRC.

Resumo O câncer é uma doença maligna fatal e sua crescente prevalência mundial exige a descoberta de biomarcadores moleculares mais sensíveis e confiáveis. Investigar o nível de expressão de GINS1 e seu valor prognóstico em cânceres humanos distintos, usando uma série de abordagens in silico em várias camadas, pode ajudar a estabelecê-lo como um potencial biomarcador de diagnóstico e prognóstico compartilhado de diferentes subtipos de câncer. O mRNA de GINS1, a expressão da proteína e a metilação do promotor foram analisados ​​usando UALCAN e Human Protein Atlas (HPA), enquanto a expressão de mRNA foi posteriormente validada via GENT2. Os valores prognósticos potenciais de GINS1 foram avaliados por meio do plotter KM. Em seguida, o cBioPortal foi utilizado para examinar as mutações genéticas relacionadas ao GINS1 e as variações do número de cópias (CNVs), enquanto a análise de enriquecimento da via foi realizada usando DAVID. Além disso, uma análise correlacional entre a expressão de GINS1 e células imunes T CD8 + e a construção de uma rede de interação gene-droga foi realizada usando TIMER, CDT e Cytoscape. O GINS1 foi encontrado regulado negativamente em um único subtipo de câncer humano, enquanto comumente regulado positivamente em 23 outros subtipos diferentes. A regulação positiva de GINS1 foi significativamente correlacionada com a sobrevida global pobre (OS) de Carcinoma Hepatocelular de Fígado (LIHC), Adenocarcinoma de Pulmão (LUAD) e Carcinoma de Células Claras Renais de Rim (KIRC). O GINS1 também foi encontrado regulado positivamente em pacientes LIHC, LUAD e KIRC de diferentes características clínico-patológicas. A análise de enriquecimento de vias revelou o envolvimento de GINS1 em duas vias diversas, enquanto poucas correlações interessantes também foram documentadas entre a expressão de GINS1 e seu nível de metilação do promotor, nível de células imunes T CD8 + e CNVs. Além disso, também previmos poucos medicamentos que poderiam ser usados ​​no tratamento de LIHC, LUAD e KIRC, regulando a expressão de GINS1. O perfil de expressão de GINS1 no estudo atual sugeriu que é um novo biomarcador de diagnóstico e prognóstico compartilhado de LIHC, LUAD e KIRC.

Fabrication of La3+ doped Ba1-x La x TiO3 ceramics with improved dielectric and ferroelectric properties using a composite-hydroxide-mediated method.

Lanthanum (La3+) doped Ba1-x La x TiO3 (x = 0.0, 0.0025, 0.005, 0.0075) ceramics were synthesized by the composite-hydroxide-mediated method. Rietveld refinement of the XRD patterns confirmed the formation of a perovskite crystal structure that transforms from tetragonal to pseudo-cubic with La3+ doping content (x). Scanning electron microscopy displayed a dense and homogeneous microstructure with reduced grain size on La3+ doping. The frequency and temperature-dependent dielectric measurements showed an improvement in the dielectric permittivity, a decrease in the ferroelectric-paraelectric transition temperature, and an increase in the dielectric diffusivity with increasing La3+ doping content. Complex impedance analysis indicated the semiconducting behavior with a positive temperature coefficient of resistance effect, which could be explained in terms of a charge compensation mechanism in the donor doped BaTiO3. The ferroelectric hysteresis loops revealed that these ceramics are ferroelectric in nature, while an improvement in the energy storage density and energy storage efficiency was observed for the doped samples due to reduced grain size on La3+ doping. Here, the sample with x = 0.005 has a high dielectric permittivity, a low dielectric tangent loss, and the highest energy storage efficiency. This makes this composition interesting for energy storage applications.

Oxygen saturation and blood volume analysis by photoacoustic imaging to identify pre and post-PDT vascular changes.

In this study, the blood volume and oxygen saturation of tumors were measured after photoacoustic imaging (PAI) under conditions of pre-photodynamic therapy (PDT), post-PDT, and 4 hrs, and 24 hrs post-PDT. PDTs with aminolevulinic acid (ALA) and low and high doses of benzoporphyrin derivative (BPD) were conducted to observe oxygen saturation changes, and the rapid oxygen consumption in the blood detected due to the action of BPD at the vascular level resulted in the recovery of PDT completion. Likewise, blood volume changes followed by ALA-PDT and BPD-PDT at low and high doses depicted a fast expansion of the blood volume after treatment. The tumor subjected to a high dose of ALA-PDT showed a partial alteration of Hb-pO2 in the first 24 hrs, as did the tumors treated with two ALA- and BPD-mediated PDTs. The Hb-pO2 started reducing immediately post-PDT and was less than 30% after 4 hrs until 24 hrs post-PDT. Reduced vascular demand was possibly due to tumor necrosis, as shown by the permanent damage in the cancer cells' bioluminescence signal. The ALA-mediated PDT-subjected tumor showed a 50% drop in BV at 24 hrs post-PDT, which is suggestive of vascular pruning. The studied data of blood volume against BLI showed the blood volume and oxygenation variations validating the cells' metabolic activity, including cell death.

Unusual semiconductor-metal-semiconductor transitions in magnetite Fe3O4 nanoparticles.

Magnetite (Fe3O4) nanoparticles were successfully prepared by a co-precipitation method. Rietveld refinement on the X-ray diffraction pattern confirmed the development of a single-phase cubic spinel structure with space group Fd3̄m. However, 57Fe Mössbauer spectroscopy suggested the presence of Fe3+ and Fe2.5+ (mixed Fe3+ and Fe2+) ions at the tetrahedral and octahedral sites of the inverse spinel structure, respectively. Impedance spectroscopy measurements showed a discontinues variation in the temperature dependence of the sample's resistive behavior, indicating the appearance of semiconductor-metal-semiconductor like transitions between the temperature range of 293 and 373 K. A similar dual transition was also observed from the dielectric and conductivity measurements around the same temperature regions. The observed unusual transition is explained in term of the competitive effects among the hopping of localized/delocalized and short-range/long-range charge carriers present in the sample. Moreover, the prepared sample exhibits colossal dielectric permittivity (∼106), reduced tangent loss (∼0.2) and moderate conductivity (>10-6 S cm-1) values, making Fe3O4 nanoparticles a potential candidate for electromagnetic absorbing materials.

Up-regulation of GINS1 highlighted a good diagnostic and prognostic potential of survival in three different subtypes of human cancer.

Cancer is a fatal malignancy and its increasing worldwide prevalence demands the discovery of more sensitive and reliable molecular biomarkers. To investigate the GINS1 expression level and its prognostic value in distinct human cancers using a series of multi-layered in silico approach may help to establish it as a potential shared diagnostic and prognostic biomarker of different cancer subtypes. The GINS1 mRNA, protein expression, and promoter methylation were analyzed using UALCAN and Human Protein Atlas (HPA), while mRNA expression was further validated via GENT2. The potential prognostic values of GINS1 were evaluated through KM plotter. Then, cBioPortal was utilized to examine the GINS1-related genetic mutations and copy number variations (CNVs), while pathway enrichment analysis was performed using DAVID. Moreover, a correlational analysis between GINS1 expression and CD8+ T immune cells and a the construction of gene-drug interaction network was performed using TIMER, CDT, and Cytoscape. The GINS1 was found down-regulated in a single subtypes of human cancer while commonly up-regulated in 23 different other subtypes. The up-regulation of GINS1 was significantly correlated with the poor overall survival (OS) of Liver Hepatocellular Carcinoma (LIHC), Lung Adenocarcinoma (LUAD), and Kidney renal clear cell carcinoma (KIRC). The GINS1 was also found up-regulated in LIHC, LUAD, and KIRC patients of different clinicopathological features. Pathways enrichment analysis revealed the involvement of GINS1 in two diverse pathways, while few interesting correlations were also documented between GINS1 expression and its promoter methylation level, CD8+ T immune cells level, and CNVs. Moreover, we also predicted few drugs that could be used in the treatment of LIHC, LUAD, and KIRC by regulating the GINS1 expression. The expression profiling of GINS1 in the current study has suggested it a novel shared diagnostic and prognostic biomarker of LIHC, LUAD, and KIRC.

Automated image classification of chest X-rays of COVID-19 using deep transfer learning.

INTRODUCTION: In December 2019, the city of Wuhan, located in the Hubei province of China became the epicentre of an outbreak of a pandemic called COVID-19 by the World Health Organisation. The detection of this virus by rRTPCR (Real-Time Reverse Transcription-Polymerase Chain Reaction) tests reported high false negative rate. The manifestations of CXR (Chest X-Ray) images contained salient features of the virus. The objective of this paper is to establish the application of an early automated screening model that uses low computational power coupled with raw radiology images to assist the physicians and radiologists in the early detection and isolation of potential positive COVID-19 patients, to stop the rapid spread of the virus in vulnerable countries with limited hospital capacities and low doctor to patient ratio in order to prevent the escalating death rates. MATERIALS AND METHODS: Our database consists of 447 and 447 CXR images of COVID-19 and Nofindings respectively, a total of 894 CXR images. They were then divided into 4 parts namely training, validation, testing and local/Aligarh dataset. The 4th (local/Aligarh) folder of the dataset was created to retest the diagnostics efficacy of our model on a developing nation such as India (Images from J.N.M.C., Aligarh, Uttar Pradesh, India). We used an Artificial Intelligence technique called CNN (Convolutional Neural Network). The architecture based on CNN used was MobileNet. MobileNet makes it faster than the ordinary convolutional model, while substantially decreasing the computational cost. RESULTS: The experimental results of our model show an accuracy of 96.33%. The F1-score is 93% and 96% for the 1st testing and 2nd testing (local/Aligarh) datasets (Tables 3.3 and 3.4). The false negative (FN) value, for the validation dataset is 6 (Fig. 3.6), for the testing dataset is 0 (Fig. 3.7) and that for the local/Aligarh dataset is 2 . The recall/sensitivity of the classifier is 93% and 96% for the 1st testing and 2nd testing (local/Aligarh) datasets (Tables 3.3 and 3.4). The recall/sensitivity for the detection of specifically COVID-19 (+) for the testing dataset is 88% and for the locally acquired dataset from India is 100%. The False Negative Rate (FNR) is 12% for the testing dataset and 0% for the locally acquired dataset (local/Aligarh). The execution time for the model to predict the input images and classify them is less than 0.1 s. DISCUSSION AND CONCLUSION: The false negative rate is much lower than the standard rRT-PCR tests and even 0% on the locally acquired dataset. This suggests that the established model with end-to-end structure and deep learning technique can be employed to assist radiologists in validating their initial screenings of Chest X-Ray images of COVID-19 in developed and developing nations. Further research is needed to test the model to make it more robust, employ it on multiclass classification and also try sensitise it to identify new strains of COVID-19. This model might help cultivate tele-radiology.

A novel mathematical model for COVID-19 with remedial strategies.

Coronavirus (COVID-19) outbreak from Wuhan, Hubei province in China and spread out all over the World. In this work, a new mathematical model is proposed. The model consists the system of ODEs. The developed model describes the transmission pathways by employing non constant transmission rates with respect to the conditions of environment and epidemiology. There are many mathematical models purposed by many scientists. In this model, " α E " and " α I ", transmission coefficients of the exposed cases to susceptible and infectious cases to susceptible respectively, are included. " δ " as a governmental action and restriction against the spread of coronavirus is also introduced. The RK method of order four (RK4) is employed to solve the model equations. The results are presented for four countries i.e., Pakistan, Italy, Japan, and Spain etc. The parametric study is also performed to validate the proposed model.

Effect of low temperature and high humidity stress on physiology of cucumber at different leaf stages.

Low temperature (LT) and high humidity (HH) are important environmental factors in greenhouses and plastic tunnels during the cold season, as they hamper plant growth and development. Here, we studied the effect of LT (day/night: 9/5 °C, 25/18 °C as control) and HH (95%, 80% as control) on young cucumber plants at the 2, 4 or 6 leaf stages. LT+HH stress resulted in a decline in shoot, root and total fresh and dry weights, and decreased Pn , gs , Tr , Fv /Fm , qP, ETR and chlorophyll, and increased MDA, H2 O2 , O2 - , NPQ and Ci as compared to the control at the 2 leaf stage. SOD, POD, CAT, APX and GR were upregulated under LT+HH stress as compared to the control at the 6 leaf stage. ABA and JA increased under LT+HH stress as compared to the control at the 6 leaf stage, while IAA and GA decreased under LT+HH stress as compared to the control at the 2 leaf stage. Our results show that LT+HH stress affects young cucumber plant photosynthetic efficiency, PSII activity, antioxidant defence system, ROS and hormone profile. Plants at the 6 leaf stage were more tolerant than at the 2 and 4 leaf stages under stress conditions.

Mathematical modeling and experimental analysis of the efficacy of photodynamic therapy in conjunction with photo thermal therapy and PEG-coated Au-doped TiO2 nanostructures to target MCF-7 cancerous cells.

Some nanoscale morphologies of titanium oxide nanostructures blend with gold nanoparticles and act as satellites and targeted weapon methodologies in biomedical applications. Simultaneously, titanium oxide can play an important role when combined with gold after blending with polyethylene glycol (PEG). Our experimental approach is novel with respect to the plasmonic role of metal nanoparticles as an efficient PDT drug. The current experimental strategy floats the comprehensive and facile way of experimental strategy on the critical influence that titanium with gold nanoparticles used as novel photosensitizing agents after significant biodistribution of proposed nanostructures toward targeted site. In addition, different morphologies of PEG-coated Au-doped titanium nanostructures were shown to provide various therapeutic effects due to a wide range of electromagnetic field development. This confirms a significantly amplified population of hot electron generation adjacent to the interface between Au and TiO2 nanostructures, leading to maximum cancerous cell injury in the MCF-7 cell line. The experimental results were confirmed by applying a least squares fit math model which verified our results with 99% goodness of fit. These results can pave the way for comprehensive rational designs for satisfactory response of performance phototherapeutic model mechanisms along with new horizons of photothermal therapy (HET) and photodynamic therapy (HET) operating under visible and near-infrared (NIR) light.

Manganese-doped cerium oxide nanocomposite as a therapeutic agent for MCF-7 adenocarcinoma cell line.

The preparation of a manganese-doped cerium oxide (Mn:CeO2) nanocomposite via hydrothermal route is described. Cubic fluorite structure of single phase was exhibited by studying structural analysis through x-ray diffraction (XRD) technique and morphological analysis was conducted by scanning electron microscope. Surface analytic technique of energy dispersive x-ray spectroscopy (EDX) was conducted to analyze the relative amount of any impurity and doping. Structural changes due to manganese doping such as increment in production of vacancies of oxygen within crystal of cerium oxide, and reduction in size of crystallite and constant of lattice was observed in our research study. Moreover, the Mn:CeO2 nanocomposite demonstrates differential cytotoxicity against MCF-7 adenocarcinoma cell line, which renders it a promising candidate for targeted cancer therapy. The anti-tumorous activity of the cerium oxide nanocomposite was significantly enhanced with doping of manganese, which is directly linked with the generation of highly reactive oxygen facets. The experimental results are supported by a mathematical model that confirms a confidence level of 95%. This research has paved the way for many utilities in therapeutics and magnetic resonance imaging diagnostics through new observations, and hence verified their math model.