Design and Production of a Novel Anti-PD-1 Nanobody by CDR Grafting and Site-Directed Mutagenesis Approach.

Programmed cell death protein-1 (PD-1) is a membrane protein expressed on the surface of activated T-cells, B-cells, natural killer cells, dendritic cells, macrophages, and monocytes. Inhibition of the PD-1/PD-L1 interaction by monoclonal antibodies (mAbs) has many therapeutic benefits and has led to a major advance in the treatment of various types of tumors. Due to the large size and immunogenicity of the antibodies (Abs), using small molecules such as nanobodies (nanobodies or VHH) is more appropriate for this purpose. In this research, the complementarity determining regions (CDR) grafting method was used to produce anti-PD-1 nanobody. For producing the grafted anti-PD-1 nanobody, CDRs from the tislelizumab mAb were grafted into the frameworks of a nanobody whose sequence is similar to the tislelizumab mAb. Also, the site-directed mutagenesis method was used to produce two mutated anti-PD-1 nanobodies which increased the affinity of grafted anti-PD-1 nanobodies. Two amino acid substitutions (Tyr97Arg and Tyr102Arg) in the VHH-CDR3 were used to improve grafted nanobody affinity and the binding capacity of the mutated nanobodies. The binding of the anti-PD-1 nanobodies and PD-1 antigen (Ag) was confirmed by Dot blot, western blot, and indirect ELISA analysis. According to the results of these in silico and in vitro studies, the binding between grafted and mutated nanobodies with PD-1 was confirmed. Also, our findings show that site-directed mutagenesis can increase the affinity of nanobodies.

Employing Supervised Algorithms for the Prediction of Nanomaterial's Antioxidant Efficiency.

Reactive oxygen species (ROS) are compounds that readily transform into free radicals. Excessive exposure to ROS depletes antioxidant enzymes that protect cells, leading to oxidative stress and cellular damage. Nanomaterials (NMs) exhibit free radical scavenging efficiency representing a potential solution for oxidative stress-induced disorders. This study aims to demonstrate the application of machine learning (ML) algorithms for predicting the antioxidant efficiency of NMs. We manually compiled a comprehensive dataset based on a literature review of 62 in vitro studies. We extracted NMs' physico-chemical (P-chem) properties, the NMs' synthesis technique and various experimental conditions as input features to predict the antioxidant efficiency measured by a 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay. Following data pre-processing, various regression models were trained and validated. The random forest model showed the highest predictive performance reaching an R2 = 0.83. The attribute importance analysis revealed that the NM's type, core-size and dosage are the most important attributes influencing the prediction. Our findings corroborate with those of the prior research landscape regarding the importance of P-chem characteristics. This study expands the application of ML in the nano-domain beyond safety-related outcomes by capturing the functional performance. Accordingly, this study has two objectives: (1) to develop a model to forecast the antioxidant efficiency of NMs to complement conventional in vitro assays and (2) to underline the lack of a comprehensive database and the scarcity of relevant data and/or data management practices in the nanotechnology field, especially with regards to functionality assessments.

Synthesis, characterization, and dye degradation photocatalytic activity of the nano-size copper iron binary oxide.

Magnetic nano-size copper iron binary oxide is synthesized via a sol-gel method using copper and iron nitrates as precursors and citric acid, chicken egg white, and starch as stabilizers followed by annealing at 400 °C and 800 °C in air. The TG-DTG, XRD, FESEM, EDX, VSM, and FT-IR and UV-Vis DRS spectroscopy methods are used for thermal, structural, magnetic, and optoelectronic characterizations. Depending on the stabilizer and annealing temperature, pure CuFe2O4, (CuFe2O4,CuO) or (CuFe2O4,CuO,Fe2O3) phases are formed with nano-size particles of 20-65 nm, having optical band gaps in the range of 2.15-2.60 eV (577-477 nm). Photocatalytic activities of the synthesized nano-size copper iron binary oxide samples are examined for degradation of Nile Blue textile dye displayed first-cycle removal (from water solution) efficiencies of 86.7-93.3%. Considering usage of non-toxic metals and low-cost green stabilizers, good degradation performances, and easy/efficient (magnetic) recyclability, this nano-size catalyst is suggested for further optimization studies for industrial applications.

A Machine Learning Tool to Predict the Antibacterial Capacity of Nanoparticles.

The emergence and rapid spread of multidrug-resistant bacteria strains are a public health concern. This emergence is caused by the overuse and misuse of antibiotics leading to the evolution of antibiotic-resistant strains. Nanoparticles (NPs) are objects with all three external dimensions in the nanoscale that varies from 1 to 100 nm. Research on NPs with enhanced antimicrobial activity as alternatives to antibiotics has grown due to the increased incidence of nosocomial and community acquired infections caused by pathogens. Machine learning (ML) tools have been used in the field of nanoinformatics with promising results. As a consequence of evident achievements on a wide range of predictive tasks, ML techniques are attracting significant interest across a variety of stakeholders. In this article, we present an ML tool that successfully predicts the antibacterial capacity of NPs while the model's validation demonstrates encouraging results (R2 = 0.78). The data were compiled after a literature review of 60 articles and consist of key physico-chemical (p-chem) properties and experimental conditions (exposure variables and bacterial clustering) from in vitro studies. Following data homogenization and pre-processing, we trained various regression algorithms and we validated them using diverse performance metrics. Finally, an important attribute evaluation, which ranks the attributes that are most important in predicting the outcome, was performed. The attribute importance revealed that NP core size, the exposure dose, and the species of bacterium are key variables in predicting the antibacterial effect of NPs. This tool assists various stakeholders and scientists in predicting the antibacterial effects of NPs based on their p-chem properties and diverse exposure settings. This concept also aids the safe-by-design paradigm by incorporating functionality tools.

The Effects of Medicago Sativa and Allium Porrum on Iron Overload in Rats.

PURPOSE: Iron overload may occur due to regular blood transfusions and high intestinal iron absorption. Currently, there is no effective drug without side effects for the treatment of iron excess in thalassemia and other iron storage diseases, except chelation therapy, which is the only safe method for iron excretion. Thus, scientists are more focused on medicinal plants rich in phytochemical compounds for the removal of iron in thalassemia. Therefore this study was managed to discover the therapeutic potential of hydro-alcoholic extract of Allium porrum and Medicago sativa for iron chelating potential. METHODS: Aerial parts of Allium porrum and Medicago sativa were collected in Yasuj Iran. Rats were divided into seven groups each containing six. Extracts were administrated in four groups (two groups for each extract) by single doses of each plant with 200 and 400 mg/kg body weight by (i.p.) route every other day for 28 days. Group 1 as negative control received saline (0.5 ml/kg) by (i.p.) route. Positive control received iron dextran 200 mg/kg body weight. Experimental groups 1 and 2 for each plant extract were fed with 200 and 400 mg/kg, hydro-alcoholic extract respectively via (i.p.) route, 1 h after the injection of iron dextran. Standard group was treated with deferoxamine (DF) 50 mg/kg by (i.p.) route 1 h after the injection of iron dextran. Serum iron (SI) and serum total iron binding capacity (TIBC) were determined .The serum ferritin was then measured using enzyme immunoassay ELISA kit for rat. For Analysis of data ANOVA test was used. RESULTS: Hydro-alcoholic extract of Medicago sativa and Allium porrum at 400 mg/kg showed significant (p<0.05) iron chelating activity compared to control. The plant extracts with dose 200 mg/kg also reduced the iron and ferritin content but the effect was lower level compared to higher doses. The plant extract effects were similar to that of standard drug deferoxamine. Iron and ferritin levels were significantly reduced in experimental groups when compared to positive group especially in Medicago sativap<0.05. There was no difference between standard drugs and last concentration of plant extracts. CONCLUSION: Protective effect of M. sativa and A. Porrum against iron overload in rat model was reported. Significant decrease in serum ferritin and iron concentration was reported in iron overload rats which induced by iron dextran.