Prediction of TKI response in EGFR-mutant lung cancer patients-derived organoids using malignant pleural effusion.

Patient-derived organoids (PDOs) are valuable in predicting response to cancer therapy. PDOs are ideal models for precision oncologists. However, their practical application in guiding timely clinical decisions remains challenging. This study focused on patients with advanced EGFR-mutated non-small cell lung cancer and employed a cancer organoid-based diagnosis reactivity prediction (CODRP)-based precision oncology platform to assess the efficacy of EGFR inhibitor treatments. CODRP was employed to evaluate EGFR-tyrosine kinase inhibitors (TKI) drug sensitivity. The results were compared to those obtained using area under the curve index. This study validated this index by testing lung cancer-derived organoids in 14 patients with lung cancer. The CODRP index-based drug sensitivity test reliably classified patient responses to EGFR-TKI treatment within a clinically suitable 10-day timeline, which aligned with clinical drug treatment responses. This approach is promising for predicting and analyzing the efficacy of anticancer, ultimately contributing to the development of a precision medicine platform.

High-Performance Ammonia Electrosynthesis from Nitrate in a NaOH-KOH-H2O Ternary Electrolyte.

A glut of dinitrogen-derived ammonia (NH3) over the past century has resulted in a heavily imbalanced nitrogen cycle and consequently, the large-scale accumulation of reactive nitrogen such as nitrates in our ecosystems has led to detrimental environmental issues. Electrocatalytic upcycling of waste nitrogen back into NH3 holds promise in mitigating these environmental impacts and reducing reliance on the energy-intensive Haber-Bosch process. Herein, we report a high-performance electrolyzer using an ultrahigh alkalinity electrolyte, NaOH-KOH-H2O, for low-cost NH3 electrosynthesis. At 3,000 mA/cm2, the device with a Fe-Cu-Ni ternary catalyst achieves an unprecedented faradaic efficiency (FE) of 92.5±1.5 % under a low cell voltage of 3.83 V; whereas at 1,000 mA/cm2, an FE of 96.5±4.8 % under a cell voltage of only 2.40 V was achieved. Techno-economic analysis revealed that our device cuts the levelized cost of ammonia electrosynthesis by ~40 % ($30.68 for Fe-Cu-Ni vs. $48.53 for Ni foam per kmol-NH3). The NaOH-KOH-H2O electrolyte together with the Fe-Cu-Ni ternary catalyst can enable the high-throughput nitrate-to-ammonia applications for affordable and scalable real-world wastewater treatments.

CT109-SN-38, a Novel Antibody-drug Conjugate with Dual Specificity for CEACAM5 and 6, Elicits Potent Killing of Pancreatic Cancer Cells.

BACKGROUND: CEACAM5 and CEACAM6 are glycosylphosphatidylinositol (GPI)- linked members of the carcinoembryonic antigen-related cell adhesion molecule (CEACAM) family, which are frequently upregulated in epithelial cancers where they contribute to invasion, metastasis, immune evasion, and resistance to anoikis. CT109 is a novel antibody with dual specificity to both CEACAM5 and 6. OBJECTIVE: In this study, we aimed to perform the preclinical characterization of CT109 and antibody- drug conjugate (ADCs) derivatives of CT109, focusing on CT109-SN-38. METHODS: CT109's cognate epitope was characterized by scanning mutagenesis. CT109 specificity and internalization kinetics were assessed by immunoblot and flow cytometry, respectively. Cognate antigen expression prevalence in colorectal cancer and normal tissue arrays was determined by immunohistochemistry. CT109 conjugations were generated by the reaction of reduced CT109 cysteines with maleimide-functionalized payload linkers. In vitro cytotoxic activity of CT109 ADCs was characterized on antigen-positive and negative pancreatic ductal adenocarcinoma cell (PDAC) lines using a luminometric viability assay. In vivo efficacy of CT109-SN-38 was assessed on a PDAC tumor xenograft model at 10 and 25 mg/kg concentrations. RESULTS: CT109 showed to bind a glycoepitope centered on N309. CT109 is internalized in the CEACAM5+/CEACAM6+ double-positive PDAC line, BxPC-3, with a t1/2 of 2.3 hours. CT109 ADCs elicit a dose and antigen-dependent cytotoxic effect, with CT109-SN-38 exhibiting an IC50 value of 21 nM in BxPC-3 cells. In a BxPC-3 tumor xenograft model, CT109-SN-38 reduced tumor growth and induced regression in 3/10 mice at 25 mg/kg concentration. CONCLUSIONS: These data suggest that further preclinical and clinical development of CT109-SN-38 is warranted.

In Situ Infrared Spectroscopic Evidence of Enhanced Electrochemical CO2 Reduction and C-C Coupling on Oxide-Derived Copper.

The reaction mechanism of CO2 electroreduction on oxide-derived copper has not yet been unraveled even though high C2+ Faradaic efficiencies are commonly observed on these surfaces. In this study, we aim to explore the effects of copper anodization on the adsorption of various CO2RR intermediates using in situ surface-enhanced infrared absorption spectroscopy (SEIRAS) on metallic and mildly anodized copper thin films. The in situ SEIRAS results show that the preoxidation process can significantly improve the overall CO2 reduction activity by (1) enhancing CO2 activation, (2) increasing CO uptake, and (3) promoting C-C coupling. First, the strong *COO- redshift indicates that the preoxidation process significantly enhances the first elementary step of CO2 adsorption and activation. The rapid uptake of adsorbed *COatop also illustrates how a high *CO coverage can be achieved in oxide-derived copper electrocatalysts. Finally, for the first time, we observed the formation of the *COCHO dimer on the anodized copper thin film. Using DFT calculations, we show how the presence of subsurface oxygen within the Cu lattice can improve the thermodynamics of C2 product formation via the coupling of adsorbed *CO and *CHO intermediates. This study advances our understanding of the role of surface and subsurface conditions in improving the catalytic reaction kinetics and product selectivity of CO2 reduction.

Revealing invisible cell phenotypes with conditional generative modeling.

Biological sciences, drug discovery and medicine rely heavily on cell phenotype perturbation and microscope observation. However, most cellular phenotypic changes are subtle and thus hidden from us by natural cell variability: two cells in the same condition already look different. In this study, we show that conditional generative models can be used to transform an image of cells from any one condition to another, thus canceling cell variability. We visually and quantitatively validate that the principle of synthetic cell perturbation works on discernible cases. We then illustrate its effectiveness in displaying otherwise invisible cell phenotypes triggered by blood cells under parasite infection, or by the presence of a disease-causing pathological mutation in differentiated neurons derived from iPSCs, or by low concentration drug treatments. The proposed approach, easy to use and robust, opens the door to more accessible discovery of biological and disease biomarkers.

Observation of Hidden Polar Phases and Flux Closure Domain Topology in Bi2WO6 Thin Films.

Topological textures of ferroelectric polarizations have promise as alternative devices for future information technology. A polarization rotation inevitably deviates from the stable orientation in axial ferroelectrics, but local energy losses compromise the global symmetry, resulting in a distorted shape of the topological vortex or inhibiting the vortex. Easy planar isotropy helps to promote rotating structures and, accordingly, to facilitate access to nontrivial textures. Here, we investigate the domain structure of an epitaxial thin film of bismuth tungsten oxide (Bi2WO6) grown on a (001) SrTiO3 substrate. By using angle-resolved piezoresponse force microscopy and scanning transmission electron microscopy, we find the existence of a hidden phase with ⟨100⟩-oriented ferroelectric polarizations in the middle of the four variant ⟨110⟩-oriented polarization domains, which assists in the formation of flux closure domains. The results suggest that this material is one step closer to becoming an isotropic two-dimensional polar material.

Pharmacogenomic profiling reveals molecular features of chemotherapy resistance in IDH wild-type primary glioblastoma.

BACKGROUND: Although temozolomide (TMZ) has been used as a standard adjuvant chemotherapeutic agent for primary glioblastoma (GBM), treating isocitrate dehydrogenase wild-type (IDH-wt) cases remains challenging due to intrinsic and acquired drug resistance. Therefore, elucidation of the molecular mechanisms of TMZ resistance is critical for its precision application. METHODS: We stratified 69 primary IDH-wt GBM patients into TMZ-resistant (n = 29) and sensitive (n = 40) groups, using TMZ screening of the corresponding patient-derived glioma stem-like cells (GSCs). Genomic and transcriptomic features were then examined to identify TMZ-associated molecular alterations. Subsequently, we developed a machine learning (ML) model to predict TMZ response from combined signatures. Moreover, TMZ response in multisector samples (52 tumor sectors from 18 cases) was evaluated to validate findings and investigate the impact of intra-tumoral heterogeneity on TMZ efficacy. RESULTS: In vitro TMZ sensitivity of patient-derived GSCs classified patients into groups with different survival outcomes (P = 1.12e-4 for progression-free survival (PFS) and 3.63e-4 for overall survival (OS)). Moreover, we found that elevated gene expression of EGR4, PAPPA, LRRC3, and ANXA3 was associated to intrinsic TMZ resistance. In addition, other features such as 5-aminolevulinic acid negative, mesenchymal/proneural expression subtypes, and hypermutation phenomena were prone to promote TMZ resistance. In contrast, concurrent copy-number-alteration in PTEN, EGFR, and CDKN2A/B was more frequent in TMZ-sensitive samples (Fisher's exact P = 0.0102), subsequently consolidated by multi-sector sequencing analyses. Integrating all features, we trained a ML tool to segregate TMZ-resistant and sensitive groups. Notably, our method segregated IDH-wt GBM patients from The Cancer Genome Atlas (TCGA) into two groups with divergent survival outcomes (P = 4.58e-4 for PFS and 3.66e-4 for OS). Furthermore, we showed a highly heterogeneous TMZ-response pattern within each GBM patient using in vitro TMZ screening and genomic characterization of multisector GSCs. Lastly, the prediction model that evaluates the TMZ efficacy for primary IDH-wt GBMs was developed into a webserver for public usage ( http://www.wang-lab-hkust.com:3838/TMZEP ). CONCLUSIONS: We identified molecular characteristics associated to TMZ sensitivity, and illustrate the potential clinical value of a ML model trained from pharmacogenomic profiling of patient-derived GSC against IDH-wt GBMs.

High-content phenotyping of Parkinson's disease patient stem cell-derived midbrain dopaminergic neurons using machine learning classification.

Combining multiple Parkinson's disease (PD) relevant cellular phenotypes might increase the accuracy of midbrain dopaminergic neuron (mDAN) in vitro models. We differentiated patient-derived induced pluripotent stem cells (iPSCs) with a LRRK2 G2019S mutation, isogenic control, and genetically unrelated iPSCs into mDANs. Using automated fluorescence microscopy in 384-well-plate format, we identified elevated levels of α-synuclein (αSyn) and serine 129 phosphorylation, reduced dendritic complexity, and mitochondrial dysfunction. Next, we measured additional image-based phenotypes and used machine learning (ML) to accurately classify mDANs according to their genotype. Additionally, we show that chemical compound treatments, targeting LRRK2 kinase activity or αSyn levels, are detectable when using ML classification based on multiple image-based phenotypes. We validated our approach using a second isogenic patient-derived SNCA gene triplication mDAN model which overexpresses αSyn. This phenotyping and classification strategy improves the practical exploitability of mDANs for disease modeling and the identification of novel LRRK2-associated drug targets.

Simple Saliva Sample Collection for the Detection of SARS-CoV-2 Variants Compared With Nasopharyngeal Swab Sample.

CONTEXT.­: The use of saliva samples for diagnosis of SARS-CoV-2 infection offers several advantages, including ease of sample collection, feasibility of self-collection, and minimization of medical staff exposure to infection. The emergence of new SARS-CoV-2 variants has had an impact on the viral load of specimens and the results of real-time reverse transcription-polymerase chain reaction (rRT-PCR). OBJECTIVE.­: To compare nasopharyngeal swab and saliva samples for the diagnosis of SARS-CoV-2 using rRT-PCR. DESIGN.­: In this study, participants were recruited prospectively, and paired nasopharyngeal swab and saliva samples were collected simultaneously from each participant. After adding universal transport medium, RNA was extracted in an identical manner for both sample types, and samples were tested using rRT-PCR. In addition, samples with positive results were tested for SARS-CoV-2 variants. RESULTS.­: Of the 338 paired samples, 100 nasopharyngeal swab and 101 saliva samples tested positive for SARS-CoV-2. The rRT-PCR results of the saliva and nasopharyngeal swab samples showed a positive percent agreement of 95.0% (95% CI, 88.7%-98.4%), a negative percent agreement of 97.9% (95% CI, 95.2%-99.3%), and an overall percent agreement of 96.8% (95% CI, 94.3%-98.4%). SARS-CoV-2 was detected in the saliva samples of 6 participants with negative nasopharyngeal sample results. In addition, the sensitivity of saliva samples was similar to that of nasopharyngeal samples for detecting various SARS-CoV-2 variants, including the Omicron variant. CONCLUSIONS.­: Saliva samples can be used as an alternative to nasopharyngeal samples for convenient and effective detection of various SARS-CoV-2 variants.

Patient-Derived Tumor Organoids for Guidance of Personalized Drug Therapies in Recurrent Glioblastoma.

An obstacle to effective uniform treatment of glioblastoma, especially at recurrence, is genetic and cellular intertumoral heterogeneity. Hence, personalized strategies are necessary, as are means to stratify potential targeted therapies in a clinically relevant timeframe. Functional profiling of drug candidates against patient-derived glioblastoma organoids (PD-GBO) holds promise as an empirical method to preclinically discover potentially effective treatments of individual tumors. Here, we describe our establishment of a PD-GBO-based functional profiling platform and the results of its application to four patient tumors. We show that our PD-GBO model system preserves key features of individual patient glioblastomas in vivo. As proof of concept, we tested a panel of 41 FDA-approved drugs and were able to identify potential treatment options for three out of four patients; the turnaround from tumor resection to discovery of treatment option was 13, 14, and 15 days, respectively. These results demonstrate that this approach is a complement and, potentially, an alternative to current molecular profiling efforts in the pursuit of effective personalized treatment discovery in a clinically relevant time period. Furthermore, these results warrant the use of PD-GBO platforms for preclinical identification of new drugs against defined morphological glioblastoma features.

Personalized functional profiling using ex-vivo patient-derived spheroids points out the potential of an antiangiogenic treatment in a patient with a metastatic lung atypical carcinoid.

Lung carcinoids are neuroendocrine tumors representing 1 to 2% of lung cancers. This study outlines the case of a patient with a metastatic lung atypical carcinoid who presented with a pleural effusion and progression of liver metastases after developing resistance to conventional treatments. Personalized functional profiling (PFP), i.e. drug screening, was performed in ex-vivo spheroids obtained from the patient's liver metastasis to identify potential therapeutic options. The drug screening results revealed cediranib, an antiangiogenic drug, as a hit drug for this patient, from a library of 66 Food and Drug Administration (FDA)-approved and investigational drugs. Based on the PFP results and the reported evidence of clinical efficacy of bevacizumab and capecitabine combination in gastro-intestinal neuroendocrine tumors, this combination was given to the patient. Four months later, the pleural effusion and pleura carcinosis regressed and the liver metastasis did not progress. The patient experienced 2 years of a stable disease under the PFP-guided personalized treatment.

Gene-corrected p.A30P SNCA patient-derived isogenic neurons rescue neuronal branching and function.

Parkinson's disease (PD) is characterised by the degeneration of A9 dopaminergic neurons and the pathological accumulation of alpha-synuclein. The p.A30P SNCA mutation generates the pathogenic form of the alpha-synuclein protein causing an autosomal-dominant form of PD. There are limited studies assessing pathogenic SNCA mutations in patient-derived isogenic cell models. Here we provide a functional assessment of dopaminergic neurons derived from a patient harbouring the p.A30P SNCA mutation. Using two clonal gene-corrected isogenic cell lines we identified image-based phenotypes showing impaired neuritic processes. The pathological neurons displayed impaired neuronal activity, reduced mitochondrial respiration, an energy deficit, vulnerability to rotenone, and transcriptional alterations in lipid metabolism. Our data describes for the first time the mutation-only effect of the p.A30P SNCA mutation on neuronal function, supporting the use of isogenic cell lines in identifying image-based pathological phenotypes that can serve as an entry point for future disease-modifying compound screenings and drug discovery strategies.

CXCL10 Is an Agonist of the CC Family Chemokine Scavenger Receptor ACKR2/D6.

Atypical chemokine receptors (ACKRs) are important regulators of chemokine functions. Among them, the atypical chemokine receptor ACKR2 (also known as D6) has long been considered as a scavenger of inflammatory chemokines exclusively from the CC family. In this study, by using highly sensitive ß-arrestin recruitment assays based on NanoBiT and NanoBRET technologies, we identified the inflammatory CXC chemokine CXCL10 as a new strong agonist ligand for ACKR2. CXCL10 is known to play an important role in the infiltration of immune cells into the tumour bed and was previously reported to bind to CXCR3 only. We demonstrated that ACKR2 is able to internalize and reduce the availability of CXCL10 in the extracellular space. Moreover, we found that, in contrast to CC chemokines, CXCL10 activity towards ACKR2 was drastically reduced by the dipeptidyl peptidase 4 (DPP4 or CD26) N-terminal processing, pointing to a different receptor binding pocket occupancy by CC and CXC chemokines. Overall, our study sheds new light on the complexity of the chemokine network and the potential role of CXCL10 regulation by ACKR2 in many physiological and pathological processes, including tumour immunology. Our data also testify that systematic reassessment of chemokine-receptor pairing is critically needed as important interactions may remain unexplored.

Integrated, automated maintenance, expansion and differentiation of 2D and 3D patient-derived cellular models for high throughput drug screening.

Patient-derived cellular models become an increasingly powerful tool to model human diseases for precision medicine approaches. The identification of robust cellular disease phenotypes in these models paved the way towards high throughput screenings (HTS) including the implementation of laboratory advanced automation. However, maintenance and expansion of cells for HTS remains largely manual work. Here, we describe an integrated, complex automated platform for HTS in a translational research setting also designed for maintenance and expansion of different cell types. The comprehensive design allows automation of all cultivation steps and is flexible for development of methods for variable cell types. We demonstrate protocols for controlled cell seeding, splitting and expansion of human fibroblasts, induced pluripotent stem cells (iPSC), and neural progenitor cells (NPC) that allow for subsequent differentiation into different cell types and image-based multiparametric screening. Furthermore, we provide automated protocols for neuronal differentiation of NPC in 2D culture and 3D midbrain organoids for HTS. The flexibility of this multitask platform makes it an ideal solution for translational research settings involving experiments on different patient-derived cellular models for precision medicine.

Patient-derived organoids and orthotopic xenografts of primary and recurrent gliomas represent relevant patient avatars for precision oncology.

Patient-based cancer models are essential tools for studying tumor biology and for the assessment of drug responses in a translational context. We report the establishment a large cohort of unique organoids and patient-derived orthotopic xenografts (PDOX) of various glioma subtypes, including gliomas with mutations in IDH1, and paired longitudinal PDOX from primary and recurrent tumors of the same patient. We show that glioma PDOXs enable long-term propagation of patient tumors and represent clinically relevant patient avatars that retain histopathological, genetic, epigenetic, and transcriptomic features of parental tumors. We find no evidence of mouse-specific clonal evolution in glioma PDOXs. Our cohort captures individual molecular genotypes for precision medicine including mutations in IDH1, ATRX, TP53, MDM2/4, amplification of EGFR, PDGFRA, MET, CDK4/6, MDM2/4, and deletion of CDKN2A/B, PTCH, and PTEN. Matched longitudinal PDOX recapitulate the limited genetic evolution of gliomas observed in patients following treatment. At the histological level, we observe increased vascularization in the rat host as compared to mice. PDOX-derived standardized glioma organoids are amenable to high-throughput drug screens that can be validated in mice. We show clinically relevant responses to temozolomide (TMZ) and to targeted treatments, such as EGFR and CDK4/6 inhibitors in (epi)genetically defined subgroups, according to MGMT promoter and EGFR/CDK status, respectively. Dianhydrogalactitol (VAL-083), a promising bifunctional alkylating agent in the current clinical trial, displayed high therapeutic efficacy, and was able to overcome TMZ resistance in glioblastoma. Our work underscores the clinical relevance of glioma organoids and PDOX models for translational research and personalized treatment studies and represents a unique publicly available resource for precision oncology.

Effects of 1,2-dioleoyl-sn-glycero-3-phosphocholine on moisture content and oxidative stability in soybean oil-water system at different interfaces.

Effects of 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC) on the oxidative stability were determined in soybean oil-water system at different locations including at the interface of air-oil, in the middle of oil, and at the interface of oil-water. Also, profile changes of tocopherols were determined during UV irradiation for 18 days. Although no significant changes in tocopherol profiles were observed at three different locations irrespective of DOPC from 0 to 1250 µmol/kg oil, addition of DOPC increased total tocopherols, α-tocopherol, and δ-tocopherol whereas content of ß + γ tocopherols did not increase at any locations. Moisture content in water-oil interface was higher than other locations while those were not consistent at different DOPC concentration. Added DOPC significantly decreased oxidative stability from 250 to 830 µmol/kg oil compared to controls (p < 0.05) whereas 1250 µmol/kg oil DOPC increased oxidative stability. Stabilities of tocopherols especially α-tocopherol were lower in oil-water system than those in bulk oil at UV irradiation.

RNAi Screening-based Identification of USP10 as a Novel Regulator of Paraptosis.

Accumulating reports demonstrate that apoptosis does not explain all the effects of cancer therapy due to the innate and acquired apoptotic resistance of malignant cancer cells. Recently, paraptosis, a type of programmed cell death accompanied by dilation of mitochondria and/or the endoplasmic reticulum (ER), has garnered interest in cancer research as an alternative way to kill apoptosis-resistant cancers. We describe here the adaptation and validation of a high-content cell-based assay to screen and identify novel paraptotic regulators employing the malignant breast cancer cells undergoing curcumin-induced paraptosis. We used YFP-Mito cells, which express fluorescence selectively in mitochondria, to select paraptosis-related genes whose corresponding siRNAs appeared to modulate mitochondrial dilation, a morphological feature of paraptosis. From the selected 38 candidate genes, we chose ubiquitin specific peptidase 10 (USP10), a ubiquitin specific protease, as a strongly active candidate that warranted further evaluation of its involvement in paraptosis. We found that both siRNA-mediated knockdown of USP10 and treatment with the USP10 inhibitor, spautin-1, effectively attenuated curcumin-induced paraptosis. This systematic assay, in which a siRNA library is screened for the ability to ameliorate paraptotic changes in mitochondria, may enable researchers to identify potent regulators of paraptosis and new candidate genes/drugs to combat malignant breast cancer.

Drug Efficacy Comparison of 3D Forming and Preforming Sphere Models with a Micropillar and Microwell Chip Platform.

Hepatocellular carcinoma (HCC), a major histological subtype of liver cancer, is the third most common cause of cancer-related death worldwide. Currently, many curative standard treatments using target-specific chemotherapeutic agents are being developed. However, drug efficacy tests based on the 2D monolayer cell culture model do not effectively screen the best drug candidates because they do not accurately reflect in vivo tumor microenvironments. Thus, to select the best drug candidates or repositioning drugs, we developed new 3D in vitro hepatic tumor models, including 3D forming and preformed sphere models. A micropillar and microwell chip platform was used for the 3D in vitro liver cell-based model for high-throughput screening. We measured the efficacy of 60 drugs and sorted the most efficacious drugs by comparing the drug response of the 2D monolayer model with the 3D forming and preformed sphere models. Among the 60 drugs, 17 drugs (28.3%) showed a significant high efficacy in the 3D preformed sphere model, while 45 drugs (75%) showed an efficacy in the 2D model. We also calculated the IC50 values of the 17 drugs and found that 7 drugs exhibited a high sensitivity in HCC, which was in agreement with previous studies.

Pharmacogenomic landscape of patient-derived tumor cells informs precision oncology therapy.

Outcomes of anticancer therapy vary dramatically among patients due to diverse genetic and molecular backgrounds, highlighting extensive intertumoral heterogeneity. The fundamental tenet of precision oncology defines molecular characterization of tumors to guide optimal patient-tailored therapy. Towards this goal, we have established a compilation of pharmacological landscapes of 462 patient-derived tumor cells (PDCs) across 14 cancer types, together with genomic and transcriptomic profiling in 385 of these tumors. Compared with the traditional long-term cultured cancer cell line models, PDCs recapitulate the molecular properties and biology of the diseases more precisely. Here, we provide insights into dynamic pharmacogenomic associations, including molecular determinants that elicit therapeutic resistance to EGFR inhibitors, and the potential repurposing of ibrutinib (currently used in hematological malignancies) for EGFR-specific therapy in gliomas. Lastly, we present a potential implementation of PDC-derived drug sensitivities for the prediction of clinical response to targeted therapeutics using retrospective clinical studies.

Effects of chitosan and collagen containing α-tocopherol on the oxidative stability in bulk oil and oil-in-water emulsion.

To provide efficient antioxidant capacities, proper carriers are needed to protect antioxidants against oxidative stress. Collagen mesh structure or chitosan gel was loaded with α-tocopherol and their effects were evaluated in bulk corn oil or oil-in-water (O/W) emulsion at 60 °C. Added collagen and chitosan enhanced oxidative stability in corn oil and O/W emulsions at 60 °C compared to corn oils without carriers or with addition of α-tocopherol (p < 0.05). Stability of α-tocopherol in corn oil loaded in collagen or chitosan was significantly enhanced compared to that in oils without carriers (p < 0.05). In O/W emulsions, α-tocopherol loaded collagen showed higher antioxidant properties than α-tocopherol loaded chitosan (p < 0.05). Collagen mesh structure and chitosan gel retarded the rates of lipid oxidation efficiently in both food matrices when α-tocopherol was not loaded. Collagen mesh structure and chitosan gel can be useful carriers for α-tocopherol in bulk oil or O/W emulsion.