Extracellular vesicle surface display enhances the therapeutic efficacy and safety profile of cancer immunotherapy.

Immunotherapy has emerged as a mainstay in cancer therapy, yet its efficacy is constrained by the risk of immune-related adverse events. In this study, we present a nanoparticle-based delivery system that enhances the therapeutic efficacy of immunomodulatory ligands while concurrently limiting systemic toxicity. We demonstrate that extracellular vesicles (EVs), lipid bilayer enclosed particles released by cells, can be efficiently engineered via inverse electron demand Diels-Alder (iEDDA)-mediated conjugation to display multiple immunomodulatory ligands on their surface. Display of immunomodulatory ligands on the EV surface conferred substantial enhancements in signaling efficacy, particularly for tumor necrosis factor receptor superfamily (TNFRSF) agonists, where the EV surface display served as an alternative FcγR-independent approach to induce ligand multimerization and efficient receptor crosslinking. EVs displaying a complementary combination of immunotherapeutic ligands were able to shift the tumor immune milieu toward an anti-tumorigenic phenotype and significantly suppress tumor burden and increase survival in multiple models of metastatic cancer to a greater extent than an equivalent dose of free ligands. In summary, we present an EV-based delivery platform for cancer immunotherapeutic ligands that facilitates superior anti-tumor responses at significantly lower doses with fewer side effects than is possible with conventional delivery approaches.

Focus to an attribute with verbal or numerical quantifiers affects the attribute framing effect.

People find positive attribute frames (e.g., 75% lean) more persuasive than negative ones (e.g., 25% fat). In three pre-registered experiments, we tested whether this effect would be magnified by using verbal quantifiers instead of numerical ones (e.g., 'high % lean' vs. '75% lean'). This moderating effect of quantifier format was predicted based on previous empirical work and two non-exclusive accounts of framing effects. First, verbal quantifiers are presumed to be a more intuitive format than numerical quantifiers, so might predispose people more to judgement biases such as the framing effect. Second, verbal quantifiers draw a greater focus to the attributes they describe. This could provide a linguistic signal that the positive frame is better than the negative one. In three experiments, we manipulated the attribute frame (positive or negative) and the quantifier format (verbal or numerical) between-subjects, and quantity pairs (e.g., 5% fat and 95% lean or 25% fat and 75% lean) within-subjects. We also tested if participants focused more on the attributes in the frame, by measuring whether participants selected causal sentence completions about the beef that focused on why it had fat meat or lean meat. Results showed a robust framing effect, which was partially mediated by the focus of the sentence completions. However, the verbal format did not increase the magnitude of the framing effect. These results suggest that a focus on the attribute contributes to the framing effect, but contrary to past work, this focus is not different between verbal and numerical quantifiers.

The intuitive use of contextual information in decisions made with verbal and numerical quantifiers.

Verbal and numerical formats (e.g., verbal: "low fat," or numerical: "20% fat") are used interchangeably to communicate nutritional information. However, prior research implies that verbal quantifiers are processed more intuitively than numerical ones. We tested this hypothesis in two pre-registered experiments measuring four indicators of processing style: (a) response time, (b) decision performance, (c) reliance on irrelevant contextual information, which we inferred from participants' decision patterns, and (d) the level of interference from a concurrent memory task. Participants imagined they had consumed a given amount of a nutrient (represented in a pie chart) and decided whether a new quantity (either verbal or numerical) could be eaten within their guideline daily amount (GDA). The experiments used a mixed design varying format (verbal or numerical), concurrent memory load (no load, easy, and hard load in Experiment 1; no load and hard load in Experiment 2), nutrient (fat and minerals), quantity (low, medium, and high in Experiment 1; low and high in Experiment 2), and the assigned correct response for a trial (within and exceeding limits). Participants were faster and made fewer correct decisions with verbal quantifiers, and they relied more on contextual information (i.e., the identity of the nutrient involved). However, memory load did not impair decisions with verbal or numerical quantifiers. Altogether, these results suggest that verbal quantifiers are processed intuitively, slightly more so than numerical quantifiers, but that numerical quantifiers do not require much analytical processing to reach simple decisions.

The Validation of the VereBeef™ Detection Kit.

VereBeef™ Detection Kit, incorporating both multiplex PCR and microarray technologies on a lab-on-chip platform, is intended for qualitative detection and differentiation of Escherichia coli O157:H7, E. coli O26, E. coli O45, E. coli O103, E. coli O111, E. coli O121, E. coli O145, Shiga toxin-producing E. coli (STEC) virulence factors (stx1A, stx2A, eae), and Salmonella species in one test using raw beef trim samples. This product underwent extensive evaluations, including inclusivity-exclusivity, method comparison, robustness, lot-to-lot variability, and stability studies. The inclusivity/exclusivity study demonstrated that VereBeef Detection Kit specifically detects and identifies target analytes without occurrence of false-positive and false-negative detection. In the method comparison study, the performance of the VereBeef Detection Kit was compared with U.S. Department of Agriculture Food Safety and Inspection Service Microbiology Laboratory Guidebook's methods for target organism detection in raw beef trim using E. coli O157:H7 single inoculation and Salmonella and non-O157 STEC dual inoculation. Data demonstrated equivalence in both methods. The robustness study showed that changes in the test parameters do not impact assay performance. Collectively, VereBeef Detection Kit is able to detect target pathogens in raw beef trim with a minimum enrichment time of 8 h for E. coli O157:H7 detection and 10 h for Salmonella and non-O157 STEC detection.

Conceptual understanding and quantity inferences: a new framework for examining consumer understanding of food energy.

OBJECTIVE: The study examined two components of consumer understanding of food energy information: understanding the concept of energy and its quantity. Using this new framework, we investigated whether activity-equivalent labels facilitated interpretations of food energy compared with calorie labels and whether an image format would strengthen this facilitative effect compared with text. DESIGN: We assessed the effect of energy representation and format in a 2 (activity v. calories)×2 (image v. text) between-subjects design. Conceptual understanding of energy was measured in terms of level of understanding and personal engagement. Quantitative understanding was measured in terms of participants' estimations of a food's contribution to their recommended daily intake and perceptions of energy values as precise or single-bound interval estimates. SETTING: The experiment was conducted online through Qualtrics. SUBJECTS: Eight hundred and twelve participants (55 % female, age range 18-74 years) were recruited through a national survey panel in the UK. RESULTS: Participants were twice more likely to have a stronger conceptual understanding of energy and four times more likely to personally engage with activity labels v. calorie labels. Participants did not differ across labels in their estimations of energy quantities; however, they inferred quantities to mean exactly the stated number of calories, but at least the stated activity duration. There were no added benefits in presenting an image over the text format. CONCLUSIONS: Activity labels can facilitate conceptual understanding of energy, but may be subject to quantitative misinterpretations. Nutrition communication should consider what people infer from quantities represented on labels.

A pilot study of urine cytokines in ketamine-associated lower urinary tract symptoms.

INTRODUCTION AND HYPOTHESIS: The aim of this study was to investigate urine cytokine and chemokine levels in symptomatic ketamine abusers compared with age-matched controls. METHODS: Midstream urine specimens were collected in a prospective study of 23 ketamine abusers and 27 controls who had never used ketamine. Their basic demographic and urinary symptoms were compared. The urine was analyzed by a multiplex panel screen for 19 cytokines/chemokines: EGF, GM-CSF, GRO, IL-1Ra, IL-5, IL-6, IL-7, IL-8, IL-10, IL-12p40, IL-12p70, IP-10, MCP-1, MIP-1b, sCD40L, sIL-2Ra, VEGF, MCP-4, and TARC using Luminex™ xMAP® technology. Protein concentration values were normalized to urine creatinine concentrations. RESULTS: Mean age of the control group was 21.1 ± 4.3 years (n = 27) and of the ketamine group was 20.6 ± 3.7 years (n = 23). All participants were women. The urine cytokine analysis showed a significant elevation in EGF levels in the ketamine group with lower urinary tract symptoms (LUTS) compared with the control group (p < 0.005). Levels of the remaining 18 proteins tested were not different from control values. CONCLUSIONS: Urinary EGF levels were increased among symptomatic ketamine abusers. This suggests inflammation and epithelial repair may play a role in ketamine-associated LUTS, and this may in turn help in understanding the pathophysiology of this disease entity, leading to better treatment options.