Facilitated Release of Doxorubicin from Biodegradable Mesoporous Silica Nanoparticles

Cervical cancer is one of the most common causes of cancer death for women in the United States. The current treatment with chemotherapy drugs has significant side effects and may cause harm to healthy cells rather than cancer cells. In order to combat the potential side effects, nanoparticles composed of mesoporous silica were created to house the chemotherapy drug doxorubicin (DOX). The silica network contains the drug, and a pH study was conducted to determine the conditions for the nanoparticle to disperse the drug. The introduction of disulfide bonds within the nanoparticle created a framework to efficiently release 97% of DOX in acidic environments and 40% release in neutral environments. The denotation of acidic versus neutral environments was important as cancer cells are typically acidic. The chemistry was proved with the incubation of the loaded nanoparticle into HeLa cells for a cytotoxicity report and confocal imaging. The use of the framework for the anticancer drug was shown to be effective for the killing of cancerous cells

How Demographics Influence Self-Image

When creating psychological research surveys, demographics are typically recorded at the end of the main survey. The reasoning behind psychologists placing demographic questions at the end can be to omit any biases from the participants (Hughes et al., 2016). However, does the placement of these types of questions influence people without them knowing? This research project will answer these questions to find the effects of demographic question placement on participants. Specifically, can demographic question placement prime individuals and their self-rating of attractiveness and the overall impact of demographic placement on survey results? To test this question, this project will conduct two versions of the study to compare self-ratings of overall attractiveness. In version one, individuals will first answer demographic questions, rate the attractiveness of celebrities, and then rate their own attractiveness. In version two, participants will first rate the attractiveness of celebrities, rate their attractiveness, and then answer demographic questions. All ratings will be on a scale of 1-10. After gathering the data, we will compare the overall attractiveness ratings between the two groups to see if there is a meaningful difference. So far, a preliminary study has been done on 120 individuals, mainly Chapman students. Participants primed with their demographics at the beginning rated their attractiveness lower than participants who answered them at the end. In the future, we plan on conducting this study on Prolific to see if this finding applies to the general population. Overall, this research will further our understanding of the impacts of demographic question placement. This is important since many testing formats currently place demographic questions at the beginning. Thus, this research will influence not only how psychologists conduct research, but also how proctors execute standardized testing in classroom settings

Linking Representations with Multimodal Contrastive Learning

Many applications require grouping instances contained in diverse document datasets into classes. Most widely used methods do not employ deep learning and do not exploit the inherently multimodal nature of documents. Notably, record linkage is typically conceptualized as a string-matching problem. This study develops CLIPPINGS, (Contrastively Linking Pooled Pre-trained Embeddings), a multimodal framework for record linkage. CLIPPINGS employs end-to-end training of symmetric vision and language bi-encoders, aligned through contrastive language-image pre-training, to learn a metric space where the pooled image-text representation for a given instance is close to representations in the same class and distant from representations in different classes. At inference time, instances can be linked by retrieving their nearest neighbor from an offline exemplar embedding index or by clustering their representations. The study examines two challenging applications: constructing comprehensive supply chains for mid-20th century Japan through linking firm level financial records - with each firm name represented by its crop in the document image and the corresponding OCR - and detecting which image-caption pairs in a massive corpus of historical U.S. newspapers came from the same underlying photo wire source. CLIPPINGS outperforms widely used string matching methods by a wide margin and also outperforms unimodal methods. Moreover, a purely self-supervised model trained on only image-OCR pairs also outperforms popular string-matching methods without requiring any labels

Activation of Dendritic Cells by Soypeptide Lunasin: Implication in Vaccine Adjuvant

poster abstractAdjuvants enhance the immunogenicity of vaccines and improve the immune responses. Although many adjuvants are currently used in research, FDA approved aluminum salt (Alum) remains the most often used in human vaccines. Alum is known to promote the Th2 immune response and enhance antibody production, but is less efficient on eliciting Th1 and CTL cellular responses. Thus, it is prudent to improve the effectiveness of current adjuvants or to develop a novel alternative adjuvant. We have recently identified lunasin, a seed peptide from soybeans, as a novel immune modulator. The objective is to define the effectiveness of lunasin peptide as an adjuvant that can enhance the protective immunity of vaccines. Our studies have revealed stimulatory effects of lunasin on dendritic cells (DCs) by regulating expression of a number of genes that are important for immune responses. Lunasin-treated human conventional DCs (cDCs) not only expressed elevated levels of co-stimulatory molecules (CD86) but also exhibited up-regulation of chemokines (CCL2, CCL3, CCL4) and cytokine (IL-1β). To determine the function of lunasin-treated cDCs, these cells were co-cultured with allogeneic human peripheral blood CD4+ T cells for 7 days in the mixed lymphocyte reaction. Lunasin-treated cDCs induced almost 2-fold higher proliferation of allogeneic CD4+ T cells when comparing with a sham treatment. To verify the in vivo effects, lunasin was administered into mice. Increased CD86 expression was found in cDCs from spleens of mice treated with lunasin. Furthermore, mice vaccinated with lunasin-adjuvanted ovalbumin (OVA) had reduced tumor growth following challenging with OVA-expressing A20 B-lymphoma cells. Taken together, our data suggest that lunasin may act as a vaccine adjuvant by targeting DCs to enhance and modulate the immune responses to antigens

Pre-diagnostic and Diagnostic Stages of Autism Spectrum Disorder: A Parent Perspective

This study examined the experiences of parents receiving an autism spectrum disorder (ASD) diagnosis for their child. Mixed methods were used to give a detailed account of the sequence of events, parents’ experiences and actions associated with the ASD diagnosis. Parents waited nearly two and a half years (mean = 28.72 months) before receiving the ASD diagnosis. Parents with lower general and autism-specific social support, poorer physical health functioning and children with more severe communication problems reported longer wait times. Surprisingly, parents reported more positive than negative experiences from receiving the diagnosis. Paediatricians and psychologists were consulted most frequently; paediatricians and general physicians were rated most likely to neglect early ASD symptoms and least likely to make appropriate referrals. Qualitative analyses revealed seven themes describing the parent experience during the diagnostic process: “heightened awareness”, “initial search”, “dissatisfaction with medical or associated processionals”, “long process/delay”, “feeling uninformed”, “parent psychological and relational experiences” and “diagnosis goals”. A set of commonly experienced stages characterising the process of obtaining a diagnosis were identified and formulated into a six-stage model of diagnostic delay adapted from the patients’ health-seeking model

Autophagy and oxidative stress in cardiovascular diseases

AbstractAutophagy is a highly conserved degradation process by which intracellular components, including soluble macromolecules (e.g. nucleic acids, proteins, carbohydrates, and lipids) and dysfunctional organelles (e.g. mitochondria, ribosomes, peroxisomes, and endoplasmic reticulum) are degraded by the lysosome. Autophagy is orchestrated by the autophagy related protein (Atg) composed protein complexes to form autophagosomes, which fuse with lysosomes to generate autolysosomes where the contents are degraded to provide energy for cell survival in response to environmental and cellular stress. Autophagy is an important player in cardiovascular disease development such as atherosclerosis, cardiac ischemia/reperfusion, cardiomyopathy, heart failure and hypertension. Autophagy in particular contributes to cardiac ischemia, hypertension and diabetes by interaction with reactive oxygen species generated in endoplasmic reticulum and mitochondria. This review highlights the dual role of autophagy in cardiovascular disease development. Full recognition of autophagy as an adaptive or maladaptive response would provide potential new strategies for cardiovascular disease prevention and management. This article is part of a Special Issue entitled: Autophagy and protein quality control in cardiometabolic diseases

frances : cloud-based historical text mining with deep learning and parallel processing

frances is an advanced cloud-based text mining digital platform that leverages information extraction, knowledge graphs, natural language processing (NLP), deep learning, and parallel processing techniques. It has been specifically designed to unlock the full potential of historical digital textual collections, such as those from the National Library of Scotland, offering cloud-based capabilities and extended support for complex NLP analyses and data visualizations. frances enables realtime recurrent operational text mining and provides robust capabilities for temporal analysis, accompanied by automatic visualizations for easy result inspection. In this paper, we present the motivation behind the development of frances, emphasizing its innovative design and novel implementation aspects. We also outline future development directions. Additionally, we evaluate the platform through two comprehensive case studies in history and publishing history. Feedback from participants in these studies demonstrates that frances accelerates their work and facilitates rapid testing and dissemination of ideas.Postprin