Improving immunogenicity and safety of flagellin as vaccine carrier by high-density display on virus-like particle surface

Flagellin is a protein-based adjuvant that activates toll-like receptor (TLR) 5. Flagellin has been actively explored as vaccine adjuvants and carriers. Preclinical and clinical studies find flagellin-based vaccines have a risk to induce systemic adverse reactions potentially due to its overt activation of TLR5. To improve safety and immunogenicity of flagellin as vaccine carriers, FljB was displayed at high densities on hepatitis b core (HBc) virus-like particle (VLP) surface upon c/e1 loop insertion. FljB-HBc (FH) VLPs showed significantly reduced ability to activate TLR5 or induce systemic interleukin-6 release as compared to FljB. FH VLPs also failed to significantly increase rectal temperature of mice, while FljB could significantly increase rectal temperature of mice. These data indicated systemic safety of FljB could be significantly improved by high-density display on HBc VLP surface. Besides improved safety, FH VLPs and FljB similarly boosted co-administered ovalbumin immunization and FH VLPs were found to induce two-fold higher anti-FljB antibody titer than FljB. These data indicated preserved adjuvant potency and improved immunogenicity after high-density display of FljB on HBc VLP surface. Consistent with the high immunogenicity, FH VLPs were found to be more efficiently taken up by bone marrow-derived dendritic cells and stimulate more potent dendritic cell maturation than FljB. Lastly, FH VLPs were found to be a more immunogenic carrier than FljB, HBc VLPs, or the widely used keyhole limpet hemocyanin for nicotine vaccine development with a good local and systemic safety. Our data support FH VLPs to be a potentially safer and more immunogenic carrier than FljB for vaccine development

Laser facilitates week-long sustained transdermal drug delivery at high doses

Traditional patches are most successful in transdermal delivery of low-dose hydrophobic drugs. Week-long transdermal delivery of high-dose hydrophilic drugs remains a big challenge. This study explored ablative fractional laser (AFL) to assist 3-day to week-long sustained transdermal delivery of powder hydrophilic drugs in murine models. Bulk drug powder was coated into reservoir patches followed by topical application onto AFL-treated skin. Water evaporated from AFL-generated skin microchannels (MCs) gradually dissolve topical drug powder to elicit multi-day sustained drug delivery. Using sulforhodamine b, zidovudine, and bovine serum albumin as model hydrophilic drugs, we found tapped coating could coat 10–20 mg drug per 0.5 cm2 reservoir patch to elicit 3-day sustained delivery, while compression coating could coat ~35–70 mg drug per 0.5 cm2 reservoir patch to elicit week-long sustained delivery. Besides sustained drug delivery, AFL-assisted powder reservoir patch delivery showed a good safety. AFL-generated skin MCs resealed in 1–2 days and completely recovered in 3 days after the week-long sustained delivery. AFL-assisted powder reservoir patch delivery involves no complex powder formulation and only requires incorporation of highly water-soluble mannitol or a similar excipient to elicit the high-efficient delivery. Enlarging reservoir patch size to 10 cm2 can conveniently expand the delivery capacity to gram scale. To our knowledge, this is the first time that high-dose week-long sustained transdermal delivery of hydrophilic drugs was achieved via a simple laser-based powder delivery platform

Unbiased Directed Object Attention Graph for Object Navigation

Object navigation tasks require agents to locate specific objects in unknown environments based on visual information. Previously, graph convolutions were used to implicitly explore the relationships between objects. However, due to differences in visibility among objects, it is easy to generate biases in object attention. Thus, in this paper, we propose a directed object attention (DOA) graph to guide the agent in explicitly learning the attention relationships between objects, thereby reducing the object attention bias. In particular, we use the DOA graph to perform unbiased adaptive object attention (UAOA) on the object features and unbiased adaptive image attention (UAIA) on the raw images, respectively. To distinguish features in different branches, a concise adaptive branch energy distribution (ABED) method is proposed. We assess our methods on the AI2-Thor dataset. Compared with the state-of-the-art (SOTA) method, our method reports 7.4%, 8.1% and 17.6% increase in success rate (SR), success weighted by path length (SPL) and success weighted by action efficiency (SAE), respectively.Comment: 13 pages, ready to ACM Mutimedia, under revie

A practical guide to promote informatics-driven efficient biotopographic material development

Micro/nano topographic structures have shown great utility in many biomedical areas including cell therapies, tissue engineering, and implantable devices. Computer-assisted informatics methods hold great promise for the design of topographic structures with targeted properties for a specific medical application. To benefit from these methods, researchers and engineers require a highly reusable “one structural parameter – one set of cell responses” database. However, existing confounding factors in topographic cell culture devices seriously impede the acquisition of this kind of data. Through carefully dissecting the confounding factors and their possible reasons for emergence, we developed corresponding guideline requirements for topographic cell culture device development to remove or control the influence of such factors. Based on these requirements, we then suggested potential strategies to meet them. In this work, we also experimentally demonstrated a topographic cell culture device with controlled confounding factors based on these guideline requirements and corresponding strategies. A “guideline for the development of topographic cell culture devices” was summarized to instruct researchers to develop topographic cell culture devices with the confounding factors removed or well controlled. This guideline aims to promote the establishment of a highly reusable “one structural parameter – one set of cell responses” database that could facilitate the application of informatics methods, such as artificial intelligence, in the rational design of future biotopographic structures with high efficacy

Explainable Multimodal Emotion Reasoning

Multimodal emotion recognition is an active research topic in artificial intelligence. Its primary objective is to integrate multi-modalities (such as acoustic, visual, and lexical clues) to identify human emotional states. Current works generally assume accurate emotion labels for benchmark datasets and focus on developing more effective architectures. But due to the inherent subjectivity of emotions, existing datasets often lack high annotation consistency, resulting in potentially inaccurate labels. Consequently, models built on these datasets may struggle to meet the demands of practical applications. To address this issue, it is crucial to enhance the reliability of emotion annotations. In this paper, we propose a novel task called ``\textbf{Explainable Multimodal Emotion Reasoning (EMER)}''. In contrast to previous works that primarily focus on predicting emotions, EMER takes a step further by providing explanations for these predictions. The prediction is considered correct as long as the reasoning process behind the predicted emotion is plausible. This paper presents our initial efforts on EMER, where we introduce a benchmark dataset, establish baseline models, and define evaluation metrics. Meanwhile, we observe the necessity of integrating multi-faceted capabilities to deal with EMER. Therefore, we propose the first multimodal large language model (LLM) in affective computing, called \textbf{AffectGPT}. We aim to tackle the long-standing challenge of label ambiguity and chart a path toward more reliable techniques. Furthermore, EMER offers an opportunity to evaluate the audio-video-text understanding capabilities of recent multimodal LLM. To facilitate further research, we make the code and data available at: https://github.com/zeroQiaoba/AffectGPT

The association of periodontal diseases and Sjogren’s syndrome: A systematic review and meta-analysis

BackgroundThe relationship between periodontal diseases and Sjogren’s syndrome were found inconsistent in current studies. Our objective is to clarify the relationship between periodontal diseases and Sjogren’s syndrome.MethodsA systematic review was performed and reported according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Electronic databases (EMBASE, PubMed, Web of Science, and Cochrane Library, from inceptions until 24 November 2021) were searched. The Newcastle-Ottawa Scale (NOS) and Agency for Healthcare Research and Quality (AHRQ) were applied to evaluate the quality of studies. Quality assessment of the certainty of evidence was performed based on the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) guidelines. When the output is the ratio, Odds ratio (OR) of periodontal diseases with Sjogren’s syndrome were calculated. When the output is the mean, weighted mean difference (WMD) of periodontal diseases with Sjogren’s syndrome was calculated. We conducted meta-analysis and estimated the pool sensitivity. Begg’s test was used to test the possibility of publication bias. We also carried out meta-regression to clarify the source of heterogeneity (I2 > 50%). Finally, we performed a trial sequential analysis (TSA) to identify the false positive or false negative outcomes that might occur during repeated updates.Results21 studies were included in this systematic review, with a total of 11435 subjects. Meta-analysis of 5 studies showed that there is a positive correlation between periodontitis and Sjogren’s syndrome (OR = 2.12, 95% CI = 1.43–3.17; 5 studies, 6927 participants; low certainty of evidence). Meta-analysis of 16 studies showed that the periodontal condition of patients with Sjogren’s syndrome was worse compared with the control group, and the scores of clinical periodontal parameters were relatively high.ConclusionSjogren’s syndrome patients seem to be more likely to be diagnosed with periodontal diseases. However, our results should be interpreted with caution considering the high heterogeneity.Systematic review registration[https://www.crd.york.ac.uk/prospero/], identifier [CRD42021261322]

Aspects of human saliva chemistry: hydroxyapatite Solubility and anionic composition

published_or_final_versionDentistryDoctoralDoctor of Philosoph

Comparative tissue proteomics reveals unique action mechanisms of vaccine adjuvants

Summary: Radiofrequency adjuvant (RFA) was recently developed to boost influenza vaccination without the safety concerns of chemical adjuvants due to their physical nature. Yet, the action mechanisms of RFA remain largely unknown. Omics techniques offer new opportunities to identify molecular mechanisms of RFA. This study utilized comparative tissue proteomics to explore molecular mechanisms of the physical RFA. Comparison of RFA and chemical adjuvant (Alum, AddaVax, MPL, MPL/Alum)-induced tissue proteome changes identified 14 exclusively induced proteins by RFA, among which heat shock protein (HSP) 70 was selected for further analysis due to its known immune-modulating functions. RFA showed much weakened ability to boost ovalbumin and pandemic influenza vaccination in HSP70 knockout than wild-type mice, hinting crucial roles of HSP70 in RFA effects. This study supports comparative tissue proteomics to be an effective tool to study molecular mechanisms of vaccine adjuvants

Effect of content and spin state of iron on electronic properties and floatability of iron-bearing sphalerite: A DFT+U study

Iron is an impurity widely occurred in sphalerite, and its effect on sphalerite flotation is complex. In this work, the effects of iron content and spin state on electronic properties and floatability of iron-bearing sphalerite are comprehensively studied using density functional theory Hubbard U (DFT+U) calculations combined with coordination chemistry flotation. The band gap of ideal sphalerite is 3.723 eV, and thus electron transition is difficult to occur, resulting in poor floatability. The results suggest the band gap of sphalerite decreases with increasing iron content. For low iron content, the decreased band gap facilitates electron transition; at this case, Fe2+ in a high-spin state possesses one π electron pair, which can form a weak π-backbonding with xanthate, causing increasing floatability. However, for medium and high iron-bearing sphalerite, with the further decrease of band gap, Fe2+ is oxidized to Fe3+ due to electrochemical interaction, and hence π-backbonding is eliminated, leading to lower floatability of iron-bearing sphalerite, which is consistent with the flotation experimental results. This work could give a deeper understanding of how sphalerite flotation behaviors are affected by iron content