Investigating the Reactive Reinforcement Ability of Maleic Anhydride-Modified Cellulose Nanocrystals via In-Situ Emulsion Polymerization.

CNC-based nanocomposites have gained substantial interest because of their enhanced thermomechanical properties for high-end engineering applications. The chemical modification of CNCs expands their applicability, making them suitable for use in hydrophobic polymer matrices. The current study investigates the reactive reinforcing ability of maleic anhydride-modified cellulose nanocrystals during the in situ polymerization of a vinyl monomer, i.e., styrene. Highly crystalline nanocellulose (CNCBG) was isolated from Lagenaria siceraria (Bottle gourd) peels via Hydrochloric acid, which was further modified to synthesize maleic anhydride-modified cellulose nanocrystals (MACNCBG) and characterized employing various techniques. MACNCBG exhibited higher suspension stability than CNCBG due to the introduction of carboxyl groups. Furthermore, polystyrene-based nanocomposites of 3 and 5 wt % filler loading were prepared, respectively. While PSMACNCBG (5 wt %) displayed a premature failure, PSMACNCBG (3 wt %) demonstrated enhanced mechanical properties compared to PSCNCBG (3 wt %) and PS. At the same filler loading, MACNCBG demonstrated a more remarkable reinforcing ability than CNCBG, owing to its reactive tendency. The appearance of a new peak between 3000-2800 cm-1 corresponds to the C-H stretching of the formed C-C bond (between C=C of MACNCBG and benzal carbon of PS) in the FTIR spectra, confirming the reactive nature of MACNCBG.

Development of a New Positron Emission Tomography Imaging Radioligand Targeting RIPK1 in the Brain and Characterization in Alzheimer's Disease.

Targeting receptor-interacting protein kinase 1 (RIPK1) has emerged as a promising therapeutic stratagem for neurodegenerative disorders, particularly Alzheimer's disease (AD). A positron emission tomography (PET) probe enabling brain RIPK1 imaging can provide a powerful tool to unveil the neuropathology associated with RIPK1. Herein, the development of a new PET radioligand, [11C]CNY-10 is reported, which may enable brain RIPK1 imaging. [11C]CNY-10 is radiosynthesized with a high radiochemical yield (41.8%) and molar activity (305 GBq/µmol). [11C]CNY-10 is characterized by PET imaging in rodents and a non-human primate, demonstrating good brain penetration, binding specificity, and a suitable clearance kinetic profile. It is performed autoradiography of [11C]CNY-10 in human AD and healthy control postmortem brain tissues, which shows strong radiosignal in AD brains higher than healthy controls. Subsequently, it is conducted further characterization of RIPK1 in AD using [11C]CNY-10-based PET studies in combination with immunohistochemistry leveraging the 5xFAD mouse model. It is found that AD mice revealed RIPK1 brain signal significantly higher than WT control mice and that RIPK1 is closely related to amyloid plaques in the brain. The studies enable further translational studies of [11C]CNY-10 for AD and potentially other RIPK1-related human studies.

Predictive modeling of plastic pyrolysis process for the evaluation of activation energy: Explainable artificial intelligence based comprehensive insights.

Pyrolysis, a thermochemical conversion approach of transforming plastic waste to energy has tremendous potential to manage the exponentially increasing plastic waste. However, understanding the process kinetics is fundamental to engineering a sustainable process. Conventional analysis techniques do not provide insights into the influence of characteristics of feedstock on the process kinetics. Present study exemplifies the efficacy of using machine learning for predictive modeling of pyrolysis of waste plastics to understand the complexities of the interrelations of predictor variables and their influence on activation energy. The activation energy for pyrolysis of waste plastics was evaluated using machine learning models namely Random Forest, XGBoost, CatBoost, and AdaBoost regression models. Feature selection based on the multicollinearity of data and hyperparameter tuning of the models utilizing RandomizedSearchCV was conducted. Random forest model outperformed the other models with coefficient of determination (R2) value of 0.941, root mean square error (RMSE) value of 14.69 and mean absolute error (MAE) value of 8.66 for the testing dataset. The explainable artificial intelligence-based feature importance plot and the summary plot of the shapely additive explanations projected fixed carbon content, ash content, conversion value, and carbon content as significant parameters of the model in the order; fixed carbon > carbon > ash content > degree of conversion. Present study highlighted the potential of machine learning as a powerful tool to understand the influence of the characteristics of plastic waste and the degree of conversion on the activation energy of a process that is essential for designing the large-scale operations and future scale-up of the process.

A handheld luminometer with sub-attomole limit of detection for distributed applications in global health.

Luminescence is ubiquitous in biology research and medicine. Conceptually simple, the detection of luminescence nonetheless faces technical challenges because relevant signals can exhibit exceptionally low radiant power densities. Although low light detection is well-established in centralized laboratory settings, the cost, size, and environmental requirements of high-performance benchtop luminometers are not compatible with geographically-distributed global health studies or resource-constrained settings. Here we present the design and application of a ~$700 US handheld, battery-powered luminometer with performance on par with high-end benchtop instruments. By pairing robust and inexpensive Silicon Photomultiplier (SiPM) sensors with a low-profile shutter system, our design compensates for sensor non-idealities and thermal drift, achieving a limit of detection of 1.6E-19 moles of firefly luciferase. Using these devices, we performed two pilot cross-sectional serology studies to assess sars-cov-2 antibody levels: a cohort in the United States, as well as a field study in Bangladesh. Results from both studies were consistent with previous work and demonstrate the device's suitability for distributed applications in global health.

Sodium oligomannate alters gut microbiota, reduces cerebral amyloidosis and reactive microglia in a sex-specific manner.

It has recently become well-established that there is a connection between Alzheimer's disease pathology and gut microbiome dysbiosis. We have previously demonstrated that antibiotic-mediated gut microbiota perturbations lead to attenuation of Aß deposition, phosphorylated tau accumulation, and disease-associated glial cell phenotypes in a sex-dependent manner. In this regard, we were intrigued by the finding that a marine-derived oligosaccharide, GV-971, was reported to alter gut microbiota and reduce Aß amyloidosis in the 5XFAD mouse model that were treated at a point when Aß burden was near plateau levels. Utilizing comparable methodologies, but with distinct technical and temporal features, we now report on the impact of GV-971 on gut microbiota, Aß amyloidosis and microglial phenotypes in the APPPS1-21 model, studies performed at the University of Chicago, and independently in the 5X FAD model, studies performed at Washington University, St. Louis.Methods To comprehensively characterize the effects of GV-971 on the microbiota-microglia-amyloid axis, we conducted two separate investigations at independent institutions. There was no coordination of the experimental design or execution between the two laboratories. Indeed, the two laboratories were not aware of each other's experiments until the studies were completed. Male and female APPPS1-21 mice were treated daily with 40, 80, or 160 mg/kg of GV-971 from 8, when Aß burden was detectable upto 12 weeks of age when Aß burden was near maximal levels. In parallel, and to corroborate existing published studies and further investigate sex-related differences, male and female 5XFAD mice were treated daily with 100 mg/kg of GV-971 from 7 to 9 months of age when Aß burden was near peak levels. Subsequently, the two laboratories independently assessed amyloid-ß deposition, metagenomic, and neuroinflammatory profiles. Finally, studies were initiated at the University of Chicago to evaluate the metabolites in cecal tissue from vehicle and GV-971-treated 5XFAD mice.Results These studies showed that independent of the procedural differences (dosage, timing and duration of treatment) between the two laboratories, cerebral amyloidosis was reduced primarily in male mice, independent of strain. We also observed sex-specific microbiota differences following GV-971 treatment. Interestingly, GV-971 significantly altered multiple overlapping bacterial species at both institutions. Moreover, we discovered that GV-971 significantly impacted microbiome metabolism, particularly by elevating amino acid production and influencing the tryptophan pathway. The metagenomics and metabolomics changes correspond with notable reductions in peripheral pro-inflammatory cytokine and chemokine profiles. Furthermore, GV-971 treatment dampened astrocyte and microglia activation, significantly decreasing plaque-associated reactive microglia while concurrently increasing homeostatic microglia only in male mice. Bulk RNAseq analysis unveiled sex-specific changes in cerebral cortex transcriptome profiles, but most importantly, the transcriptome changes in the GV-971-treated male group revealed the involvement of microglia and inflammatory responses.Conclusions In conclusion, these studies demonstrate the connection between the gut microbiome, neuroinflammation, and Alzheimer's disease pathology while highlighting the potential therapeutic effect of GV-971. GV-971 targets the microbiota-microglia-amyloid axis, leading to the lowering of plaque pathology and neuroinflammatory signatures in a sex-dependent manner when given at the onset of Aß deposition or when given after Aß deposition is already at higher levels.

Designed novel nuclear localizing anticancer peptide targets p53 negative regulator MDM2 protein.

Intracellular protein-protein interactions provide a major therapeutic target for the development of peptide-based anticancer therapeutic agents. MDM2 is the 491-residue protein encoded by the MDM2 oncogene. Being a ubiquitin-protein ligase, MDM2 represses the transcription ability of the tumor suppressor p53 by proteasome-mediated degradation. Under typical cellular circumstances, a sustained p53 expression level is maintained by negative regulation of MDM2, whereas under stress conditions, this is alleviated to increase the p53 level. Modulation of MDM2-p53 interaction via fabrication of an MDM2-interacting peptide could be a useful strategy to inhibit subsequent proteasomal degradation of p53 and initiation of p53 signaling leading to the initiation of p53-mediated apoptosis of tumor cells. Here, in this research work, a novel anticancer peptide mPNC-NLS targeting the nucleus and the MDM2 protein (p53 negative regulator) was designed to promote the p53 protein activity for the prevention of cancer. It induces effective apoptosis in both A549 and U87 cells and remains non-cytotoxic to normal lung fibroblast cells (WI38). Further, immunocytochemistry and Western blot results confirm that the designed mPNC-NLS peptide induces the apoptotic death of lung cancer cells via activation of p53 and p21 proteins and remarkably stifled the in vitro growth of 3D multicellular spheroids composed of A549 cells.