Evolutionary trajectory of TRPM2 channel activation by adenosine diphosphate ribose and calcium.

Ion channel activation upon ligand gating triggers a myriad of biological events and, therefore, evolution of ligand gating mechanism is of fundamental importance. TRPM2, a typical ancient ion channel, is activated by adenosine diphosphate ribose (ADPR) and calcium and its activation has evolved from a simple mode in invertebrates to a more complex one in vertebrates, but the evolutionary process is still unknown. Molecular evolutionary analysis of TRPM2s from more than 280 different animal species has revealed that, the C-terminal NUDT9-H domain has evolved from an enzyme to a ligand binding site for activation, while the N-terminal MHR domain maintains a conserved ligand binding site. Calcium gating pattern has also evolved, from one Ca2+-binding site as in sea anemones to three sites as in human. Importantly, we identified a new group represented by olTRPM2, which has a novel gating mode and fills the missing link of the channel gating evolution. We conclude that the TRPM2 ligand binding or activation mode evolved through at least three identifiable stages in the past billion years from simple to complicated and coordinated. Such findings benefit the evolutionary investigations of other channels and proteins.

Early diagnosis of oral cancer using a hybrid arrangement of deep belief networkand combined group teaching algorithm.

Oral cancer can occur in different parts of the mouth, including the lips, palate, gums, and inside the cheeks. If not treated in time, it can be life-threatening. Incidentally, using CAD-based diagnosis systems can be so helpful for early detection of this disease and curing it. In this study, a new deep learning-based methodology has been proposed for optimal oral cancer diagnosis from the images. In this method, after some preprocessing steps, a new deep belief network (DBN) has been proposed as the main part of the diagnosis system. The main contribution of the proposed DBN is its combination with a developed version of a metaheuristic technique, known as the Combined Group Teaching Optimization algorithm to provide an efficient system of diagnosis. The presented method is then implemented in the "Oral Cancer (Lips and Tongue) images dataset" and a comparison is done between the results and other methods, including ANN, Bayesian, CNN, GSO-NN, and End-to-End NN to show the efficacy of the techniques. The results showed that the DBN-CGTO method achieved a precision rate of 97.71%, sensitivity rate of 92.37%, the Matthews Correlation Coefficient of 94.65%, and 94.65% F1 score, which signifies its ability as the highest efficiency among the others to accurately classify positive samples while remaining the independent correct classification of negative samples.

Establishment of a Seven-Gene Signature Associated with CD8+ T Cells through the Utilization of Both Single-Cell and Bulk RNA-Sequencing Techniques in Clear Cell Renal Cell Carcinoma.

Tumor immune microenvironment constituents, such as CD8+ T cells, have emerged as crucial focal points for cancer immunotherapy. Given the absence of reliable biomarkers for clear cell renal cell carcinoma (ccRCC), we aimed to ascertain a molecular signature that could potentially be linked to CD8+ T cells. The differentially expressed genes (DEGs) linked to CD8+ T cells were identified through an analysis of single-cell RNA sequencing (scRNA-seq) data obtained from the Gene Expression Omnibus (GEO) database. Subsequently, immune-associated genes were obtained from the InnateDB and ImmPort datasets and were cross-referenced with CD8+ T-cell-associated DEGs to generate a series of DEGs linked to immune response and CD8+ T cells. Patients with ccRCC from the Cancer Genome Atlas (TCGA) were randomly allocated into testing and training groups. A gene signature was established by conducting LASSO-Cox analysis and subsequently confirmed using both the testing and complete groups. The efficacy of this signature in evaluating immunotherapy response was assessed on the IMvigor210 cohort. Finally, we employed various techniques, including CIBERSORT, ESTIMATE, ssGSEA, and qRT-PCR, to examine the immunological characteristics, drug responses, and expression of the signature genes in ccRCC. Our findings revealed 206 DEGs linked to immune response and CD8+ T cells, among which 65 genes were correlated with overall survival (OS) in ccRCC. A risk assessment was created utilizing a set of seven genes: RARRES2, SOCS3, TNFSF14, XCL1, GRN, CLDN4, and RBP7. The group with a lower risk showed increased expression of CD274 (PD-L1), suggesting a more favorable response to anti-PD-L1 treatment. The seven-gene signature demonstrated accurate prognostic prediction for ccRCC and holds potential as a clinical reference for treatment decisions.

Targeting anticancer immunity in oral cancer: Drugs, products, and nanoparticles.

Oral cavity carcinomas are the most frequent malignancies among head and neck malignancies. Oral tumors include not only oral cancer cells with different potency and stemness but also consist of diverse cells, containing anticancer immune cells, stromal and also immunosuppressive cells that influence the immune system reactions. The infiltrated T and natural killer (NK) cells are the substantial tumor-suppressive immune compartments in the tumor. The infiltration of these cells has substantial impacts on the response of tumors to immunotherapy, chemotherapy, and radiotherapy. Nevertheless, cancer cells, stromal cells, and some other compartments like regulatory T cells (Tregs), macrophages, and myeloid-derived suppressor cells (MDSCs) can repress the immune responses against malignant cells. Boosting anticancer immunity by inducing the immune system or repressing the tumor-promoting cells is one of the intriguing approaches for the eradication of malignant cells such as oral cancers. This review aims to concentrate on the secretions and interactions in the oral tumor immune microenvironment. We review targeting tumor stroma, immune system and immunosuppressive interactions in oral tumors. This review will also focus on therapeutic targets and therapeutic agents such as nanoparticles and products with anti-tumor potency that can boost anticancer immunity in oral tumors. We also explain possible future perspectives including delivery of various cells, natural products and drugs by nanoparticles for boosting anticancer immunity in oral tumors.

Evaluation of the Yield of DNA Double-Strand Breaks for Carbon Ions Using Monte Carlo Simulation and DNA Fragment Distribution.

PURPOSE: The aim of this work was to provide a method to evaluate the yield of DNA double-strand breaks (DSBs) for carbon ions, overcoming the bias in existing methods due to the nonrandom distribution of DSBs. METHODS AND MATERIALS: A previously established biophysical program based on the radiation track structure and a multilevel chromosome model was used to simulate DNA damage induced by x-rays and carbon ions. The fraction of activity retained (FAR) as a function of absorbed dose or particle fluence was obtained by counting the fraction of DNA fragments larger than 6 Mbp. Simulated FAR curves for the 250 kV x-rays and carbon ions at various energies were compared with measurements using constant-field gel electrophoresis. The doses or fluences at the FAR of 0.7 based on linear interpolation were used to estimate the simulation error for the production of DSBs. RESULTS: The relative difference of doses at the FAR of 0.7 between simulation and experiment was -8.5% for the 250 kV x-rays. The relative differences of fluences at the FAR of 0.7 between simulations and experiments were -17.5%, -42.2%, -18.2%, -3.1%, 10.8%, and -14.5% for the 34, 65, 130, 217, 2232, and 3132 MeV carbon ions, respectively. In comparison, the measurement uncertainty was about 20%. Carbon ions produced remarkably more DSBs and DSB clusters per unit dose than x-rays. The yield of DSBs for carbon ions, ranging from 10 to 16 Gbp-1Gy-1, increased with linear energy transfer (LET) but plateaued in the high-LET end. The yield of DSB clusters first increased and then decreased with LET. This pattern was similar to the relative biological effectiveness for cell survival for heavy ions. CONCLUSIONS: The estimated yields of DSBs for carbon ions increased from 10 Gbp-1Gy-1 in the low-LET end to 16 Gbp-1Gy-1 in the high-LET end with 20% uncertainty.

Monte Carlo simulation of physical dose enhancement in core-shell magnetic gold nanoparticles with TOPAS.

The application of metal nanoparticles (MNPs) as sensitization materials is a common strategy that is used to study dose enhancement in radiotherapy. Recent in vitro tests have revealed that magnetic gold nanoparticles (NPs) can be used in cancer therapy under a magnetic field to enhance the synergistic efficiency in radiotherapy and photothermal therapy. However, magnetic gold NPs have rarely been studied as sensitization materials. In this study, we obtained further results of the sensitization properties of the magnetic gold NPs (Fe3O4@AuNPs) with or without magnetic field using the TOPAS-nBio Monte Carlo (MC) toolkit. We analyzed the properties of Fe3O4@AuNP in a single NP model and in a cell model under monoenergetic photons and brachytherapy, and we investigated whether the magnetic field contributes to the physical sensitization process. Our results revealed that the dose enhancement factor (DEF) of Fe3O4@AuNPs was lower than that of gold nanoparticles (AuNPs) in a single NP and in a cell irradiated by monoenergetic photons. But it's worth mentioning that under a magnetic field, the DEF of targeted Fe3O4@AuNPs in a cell model with a clinical brachytherapy source was 22.17% (cytoplasm) and 6.89% (nucleus) higher than those of AuNPs (50 mg/mL). The Fe3O4@AuNPs were proved as an effective sensitization materials when combined with the magnetic field in MC simulation for the first time, which contributes to the research on in vitro tests on radiosensitization as well as clinical research in future.

Investigating beam range uncertainty in proton prostate treatment using pelvic-like biological phantoms.

This study aims to develop a method for verifying site-specific and/or beam path specific proton beam range, which could reduce range uncertainty margins and the associated treatment complications. It investigates the range uncertainties from both CT HU to relative stopping power conversion and patient positioning errors for prostate treatment using pelvic-like biological phantoms. Three 25 × 14 × 12 cm3phantoms, made of fresh animal tissues mimicking the pelvic anatomies of prostate patients, were scanned with a general electric CT simulator. A 22 cm circular passive scattering beam with 29 cm range and 8 cm modulation width was used to measure the water equivalent path lengths (WEPL) through the phantoms at multiple points using the dose extinction method with a MatriXXPT detector. The measured WEPLs were compared to those predicted by TOPAS simulations and ray-tracing WEPL calculations. For the three phantoms, the WEPL differences between measured and theoretical prediction (WDMT) are below 1.8% for TOPAS, and 2.5% for ray-tracing. WDMT varies with phantom anatomies by about 0.5% for both TOPAS and ray-tracing. WDMT also correlates with the tissue types of a specific treated region. For the regions where the proton beam path is parallel to sharp bone edges, the WDMTs of TOPAS and ray-tracing respectively reach up to 1.8% and 2.5%. For the region where proton beams pass through just soft tissues, the WDMT is mostly less than 1% for both TOPAS and ray-tracing. For prostate treatments, range uncertainty depends on the tissue types within a specific treated region, patient anatomies and the range calculation methods in the planning algorithms. Our study indicates range uncertainty is less than 2.5% for the whole treated region with both ray-tracing and TOPAS, which suggests the potential to reduce the current 3.5% range uncertainty margin used in the clinics by at least 1% even for single-energy CT data.

Monte Carlo study of TG-43 dosimetry parameters of GammaMed Plus high dose rate 192 Ir brachytherapy source using TOPAS.

PURPOSE: To develop a simulation model for GammaMed Plus high dose rate 192 Ir brachytherapy source in TOPAS Monte Carlo software and validate it by calculating the TG-43 dosimetry parameters and comparing them with published data. METHODS: We built a model for GammaMed Plus high dose rate brachytherapy source in TOPAS. The TG-43 dosimetry parameters including air-kerma strength SK , dose-rate constant Λ, radial dose function gL (r), and 2D anisotropy function F(r,θ) were calculated using Monte Carlo simulation with Geant4 physics models and NNDC 192 Ir spectrum. Calculations using an old 192 Ir spectrum were also carried out to evaluate the impact of incident spectrum and cross sections. The results were compared with published data. RESULTS: For calculations using the NNDC spectrum, the air-kerma strength per unit source activity SK /A and Λ were 1.0139 × 10-7 U/Bq and 1.1101 cGy.h-1 .U-1 , which were 3.56% higher and 0.62% lower than the reference values, respectively. The gL (r) agreed with reference values within 1% for radial distances from 2 mm to 20 cm. For radial distances of 1, 3, 5, and 10 cm, the agreements between F(r,θ) from this work and the reference data were within 1.5% for 15° < Î¸ < 165°, and within 4% for all θ values. The discrepancies were attributed to the updated source spectrum and cross sections. They caused deviations of the SK /A of 2.90% and 0.64%, respectively. As for gL (r), they caused average deviations of -0.22% and 0.48%, respectively. Their impact on F(r,θ) was not quantified for the relatively high statistical uncertainties, but basically they did not result in significant discrepancies. CONCLUSION: A model for GammaMed Plus high dose rate 192 Ir brachytherapy source was developed in TOPAS and validated following TG-43 protocols, which can be used for future studies. The impact of updated incident spectrum and cross sections on the dosimetry parameters was quantified.

Synthesis, Characterization of Liposomes Modified with Biosurfactant MEL-A Loading Betulinic Acid and Its Anticancer Effect in HepG2 Cell.

As a novel natural compound delivery system, liposomes are capable of incorporating lipophilic bioactive compounds with enhanced compound solubility, stability and bioavailability, and have been successfully translated into real-time clinical applications. To construct the soy phosphatidylcholine (SPC)-cholesterol (Chol) liposome system, the optimal formulation was investigated as 3:1 of SPC to Chol, 10% mannosylerythritol lipid-A (MEL-A) and 1% betulinic acid. Results show that liposomes with or without betulinic acid or MEL-A are able to inhibit the proliferation of HepG2 cells with a dose-effect relation remarkably. In addition, the modification of MEL-A in liposomes can significantly promote cell apoptosis and strengthen the destruction of mitochondrial membrane potential in HepG2 cells. Liposomes containing MEL-A and betulinic acid have exhibited excellent anticancer activity, which provide factual basis for the development of MEL-A in the anti-cancer applications. These results provide a design thought to develop delivery liposome systems carrying betulinic acid with enhanced functional and pharmaceutical attributes.

Production and characterization of a new glycolipid, mannosylerythritol lipid, from waste cooking oil biotransformation by Pseudozyma aphidis ZJUDM34.

Mannosylerythritol lipids (MELs) are glycolipids possessing unique biosurfactant properties. However, the prices of substrates currently used for MEL formation caused its unsustainable commercial development. Waste cooking oil poses significant ecological and economical problems. Thus, the production of MELs from used waste cooking oil using the biotransformation route is one of the better alternatives to utilize it efficiently and economically. This work aims at the production of MELs using waste cooking oil instead of soybean oil and evaluating the major characteristics and compositions of MELs. The titers reached 61.50 g/L by the optimization of culture medium, higher than the counterpart (10.25 ± 0.32 g/L) of the nonoptimized medium. MELs exhibited good surface activity and better performance in contrast to MELs grown on soybean oil. The water phase behavior of MEL-A was also evaluated. The process showed higher productivity of MELs with better surface activity and application stability than the conventional process using soybean oil. The findings of this study imply that the use of inexpensive fermentation substrates associated with straightforward downstream processing is expected to have a great impact on the economy of MEL production.

White Pitaya (Hylocereus undatus) Juice Attenuates Insulin Resistance and Hepatic Steatosis in Diet-Induced Obese Mice.

Insulin resistance and hepatic steatosis are the most common complications of obesity. Pitaya is an important source of phytochemicals such as polyphenols, flavonoid and vitamin C which are related to its antioxidant activity. The present study was conducted to evaluate the influence of white pitaya juice (WPJ) on obesity-related metabolic disorders (e.g. insulin resistance and hepatic steatosis) in high-fat diet-fed mice. Forty-eight male C57BL/6J mice were assigned into four groups and fed low-fat diet with free access to water or WPJ, or fed high-fat diet with free access to water or WPJ for 14 weeks. Our results showed that administration of WPJ improved high-fat diet-induced insulin resistance, hepatic steatosis and adipose hypertrophy, but it exerted no influence on body weight gain in mice. Hepatic gene expression analysis indicated that WPJ supplement not only changed the expression profile of genes involved in lipid and cholesterol metabolism (Srebp1, HMGCoR, Cpt1b, HL, Insig1 and Insig2) but also significantly increased the expression levels of FGF21-related genes (Klb, FGFR2, Egr1 and cFos). In conclusion, WPJ protected from diet-induced hepatic steatosis and insulin resistance, which was associated with the improved FGF21 resistance and lipid metabolism.