Notes

Validation protocols with regard to blood vessels pressure-measuring units: status quo and also development requires.
Numerous studies have concentrated on high-dose radiation exposed accidentally or through therapy, and few involve low-dose occupational exposure, to investigate the correlation between low-dose ionizing radiation and changing hematological parameters among medical workers.

Using a prospective cohort study design, we collected health examination reports and personal dose monitoring data from medical workers and used Poisson regression and restricted cubic spline models to assess the correlation between changing hematological parameters and cumulative radiation dose and determine the dose-response relationship.

We observed that changing platelet of 1265 medical workers followed up was statistically different among the cumulative dose groups (P = 0.010). Although the linear trend tested was not statistically significant (P
= 0.258), the non-linear trend tested was statistically significant (P
= 0.007). Overall, there was a correlation between changing platelets and cumulative radiation dose (a change ation for a short period of time might have increased first and then decreased platelets, and there was a dose-response relationship between the cumulative radiation dose and platelets changing.
Due to continued advances in sequencing technology, the limitation in understanding biological systems through an "-omics" lens is no longer the generation of data, but the ability to analyze it. Importantly, much of this rich -omics data is publicly available waiting to be further investigated. Although many code-based pipelines exist, there is a lack of user-friendly and accessible applications that enable rapid analysis or visualization of data.

GECO (Gene Expression Clustering Optimization; http//www.theGECOapp.com ) is a minimalistic GUI app that utilizes non-linear reduction techniques to rapidly visualize expression trends in many types of biological data matrices (such as bulk RNA-seq or proteomics). The required input is a data matrix with samples and any type of expression level of genes/protein/other with a unique ID. The output is an interactive t-SNE or UMAP analysis that clusters genes (or proteins/other unique IDs) based on their expression patterns across the multiple samples enabling visueb browser app enables investigation of any -omic data matrix in a rapid and code-independent manner. click here With the continued growth of available -omic data, the ability to quickly evaluate a dataset, including specific genes of interest, is more important than ever. GECO is intended to supplement traditional statistical analysis methods and is particularly useful when visualizing clusters of genes with similar trajectories across many samples (ex multiple cell types, time course, dose response). Users will be empowered to investigate -omic data with a new lens of visualization and analysis that has the potential to uncover genes of interest, cohorts of co-regulated genes programs, and previously undetected patterns of expression.
Radiotherapy is used as one of the most effective regimens for cancer treatment, while radioresistance is a major drawback in cancer treatment.

The aim of this study was to evaluate the sensitizing effect of olanzapine (OLA) with X-ray on glioblastoma (U-87 MG) cells death.

The synergistic killing effect of OLA with ionizing radiation (IR) on glioma was evaluated by colony formation assay. The generations of reactive oxygen species (ROS) and protein carbonyl (PC) as oxidized protein were determined in OLA and irradiated cells.

The results of this study showed that OLA reduced the number of colonies in irradiated glioma cells. OLA elevated ROS and PC levels in irradiated cells. The synergistic killing effect of OLA with IR in U-87 MG cell was observed at concentrations 1 µM and 20 µM of OLA. The maximum radiosensitizing effect of OLA was observed at concentration of 20 µM.

The present study demonstrates that OLA has radiosensitizing effect on cell death induced by IR in glioma cells.
The present study demonstrates that OLA has radiosensitizing effect on cell death induced by IR in glioma cells.
Olanzapine belongs to a new class of dual spectrum antipsychotic agents. It is known to show promise in managing both the positive and negative symptoms of schizophrenia. Drug delivery systems based on nanostructured lipid carriers (NLC) are expected to provide rapid nose-to-brain transport of this drug and improved distribution into and within the brain.

The present study deals with the preparation and evaluation of olanzapine loaded NLC via the intranasal route for schizophrenia.

Olanzapine-NLC were formulated through the solvent injection method using isopropyl alcohol as the solvent, stearic acid as solid lipid, and oleic acid as liquid lipid, chitosan as a coating agent, and Poloxamer 407 as a surfactant. NLC were characterized for particle size, polydispersity index, entrapment efficiency, pH, viscosity, X-ray diffraction studies, in-vitro mucoadhesion study, in- vitro release and ex-vivo permeation studies. The shape and surface morphology of the prepared NLC was determined through transmission electron microscopy. To detect the interaction of the drug with carriers, compatibility studies were also carried out.

Average size and polydispersity index of developed formulation S6 was 227.0±6.3 nm and 0.460 respectively. The encapsulation efficiency of formulation S6 was found to be 87.25 %. The pH, viscosity, in-vitro mucoadhesion study, and in- vitro release of optimized olanzapine loaded NLC were recorded as 5.7 ± 0.05, 78 centipoise, 15±2 min, and 91.96 % respectively. In ex-vivo permeation studies, the percent drug permeated after 210 min was found to be 84.03%.

These results reveal potential application of novel olanzapine-NLC in intranasal drug delivery system for treatment of schizophrenia.
These results reveal potential application of novel olanzapine-NLC in intranasal drug delivery system for treatment of schizophrenia.Hypoxia is an integral part of tumor microenvironment, caused primarily due to rapidly multiplying tumor cells and a lack of proper blood supply. Among the major hypoxic pathways, HIF-1 transcription factor activation is one of the widely investigated pathways in the hypoxic tumor microenvironment (TME). HIF-1 is known to activate several adaptive reactions in response to oxygen deficiency in tumor cells. HIF-1 has two subunits, HIF-1β (constitutive) and HIF-1α (inducible). The HIF-1α expression is largely regulated via various cytokines (through PI3K-ACT-mTOR signals), which involves the cascading of several growth factors and oncogenic cascades. These events lead to the loss of cellular tumor suppressant activity through changes in the level of oxygen via oxygen-dependent and oxygen-independent pathways. The significant and crucial role of HIF in cancer progression and its underlying mechanisms have gained much attention lately among the translational researchers in the fields of cancer and biological sciences, which have enabled them to correlate these mchanisms with various other disease modalities.
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