Bacterial and fungal co-infection is a major barrier in COVID-19 patients: A specific management and therapeutic strategy is required

Microbial co-infections are another primary concern in patients with coronavirus disease 2019 (COVID-19), yet it is an untouched area among researchers. Preliminary data and systematic reviews only show the type of pathogens responsible for that, but its pathophysiology is still unknown. Studies show that these microbial co-infections are hospital-acquired/nosocomial infections, and patients admitted to intensive care units with invasive mechanical ventilation are highly susceptible to it. Patients with COVID-19 had elevated inflammatory cytokines and a weakened cell-mediated immune response, with lower CD4⁺ T and CD8⁺ T cell counts, indicating vulnerability to various co-infections. Despite this, there are only a few studies that recommend the management of co-infections.     

Clinicopathological Profile of Myelomatous Pleural Effusion: Single-center Real-world Experience and Review of Literature

Background

Multiple myeloma (MM) is a hematologic malignancy of plasma cell origin. MM primarily affects bone marrow, but extramedullary sites can also be involved. Myelomatous pleural effusion (MPE) is an atypical and rare complication of MM. We aimed to systematically study the incidence and clinicopathologic profile of patients with MPE in a real-world setting.

Temperature-controlled power modulation compensates for heterogeneous nanoparticle distributions: a computational optimization analysis for magnetic hyperthermia

Purpose: To study, with computational models, the utility of power modulation to reduce tissue temperature heterogeneity for variable nanoparticle distributions in magnetic nanoparticle hyperthermia.

Methods: Tumour and surrounding tissue were modeled by elliptical two- and three-dimensional computational phantoms having six different nanoparticle distributions. Nanoparticles were modeled as point heat sources having amplitude-dependent loss power. The total number of nanoparticles was fixed, and their spatial distribution and heat output were varied. Heat transfer was computed by solving the Pennes’ bioheat equation using finite element methods (FEM) with temperature-dependent blood perfusion. Local temperature was regulated using a proportional-integral-derivative (PID) controller. Tissue temperature, thermal dose and tissue damage were calculated. The required minimum thermal dose delivered to the tumor was kept constant, and heating power was adjusted for comparison of both the heating methods.

Results: Modulated power heating produced lower and more homogeneous temperature distributions than did constant power heating for all studied nanoparticle distributions. For a concentrated nanoparticle distribution, located off-center within the tumor, the maximum temperatures inside the tumor were 16% lower for modulated power heating when compared to constant power heating. This resulted in less damage to surrounding normal tissue. Modulated power heating reached target thermal doses up to nine-fold more rapidly when compared to constant power heating.

Conclusions: Controlling the temperature at the tumor-healthy tissue boundary by modulating the heating power of magnetic nanoparticles demonstrably compensates for a variable nanoparticle distribution to deliver effective treatment.     

The Clinical and Prognostic Implications of Pluripotent Stem Cell Markers Expression and Their Correlation with the WNT signal pathway in Hepatocellular Carcinoma

Objectives: This study aimed to investigate the expression of SOX2, SOX9, p53, and β-catenin in hepatocellular carcinoma (HCC) and their correlation with clinicopathological parameters of prognostic importance. Materials and Methods: Seventy-five patients were enrolled in this study. All patients had full clinical and follow-up data and available paraffin blocks. Immunohistochemical analysis was performed and correlated with clinicopathological factors and patient survival. Results: We detected the positive expression of SOX2, SOX9, p53, and β-catenin in 76%, 50.7%, 50.7%, and 77.9% of HCC specimens respectively. All studied markers showed a significant increase in the expression in tumor tissue specimens compared to non-tumor tissue. Both SOX2 and SOX9 expressions were significantly associated with adverse prognostic factors in HCC. Significant positive correlations were found between SOX2 and SOX9 and both p53 and β-catenin expression (r= 0.528, 0.485 and; r = 0.253, 0.327, respectively; p < 0.0001 for both of them). Regarding survival, we found that HCC patients with positive SOX2 and SOX9 expressions had significantly shorter overall survival (p=0.0001, each). Additionally, larger tumor size, tumor grade, high stage, tumor multiplicity, presence of cirrhosis, tumor necrosis, high p53 expression, and positive β-catenin expression were independent predictors of worse survival. A multivariate Cox analysis revealed that tumor grade, stage, p53, and SOX2 expression were independent predictors of unfavorable prognosis in overall survival (p=0.0001, p=0.0001,p=0.033; and p=0.003, respectively). Conclusions: Our findings might provide an insight into SOX2 and SOX9’s role in HCC and suggest that SOX2 might be targeted for HCC therapy.     

Extended Kalman smoother with differential evolution technique for denoising of ECG signal

Electrocardiogram (ECG) signal gives a lot of information on the physiology of heart. In reality, noise from various sources interfere with the ECG signal. To get the correct information on physiology of the heart, noise cancellation of the ECG signal is required. In this paper, the effectiveness of extended Kalman smoother (EKS) with the differential evolution (DE) technique for noise cancellation of the ECG signal is investigated. DE is used as an automatic parameter selection method for the selection of ten optimized components of the ECG signal, and those are used to create the ECG signal according to the real ECG signal. These parameters are used by the EKS for the development of the state equation and also for initialization of the parameters of EKS. EKS framework is used for denoising the ECG signal from the single channel. The effectiveness of proposed noise cancellation technique has been evaluated by adding white, colored Gaussian noise and real muscle artifact noise at different SNR to some visually clean ECG signals from the MIT-BIH arrhythmia database. The proposed noise cancellation technique of ECG signal shows better signal to noise ratio (SNR) improvement, lesser mean square error (MSE) and percent of distortion (PRD) compared to other well-known methods.