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Automated assessment of open responses in K–12 science education poses significant challenges due to the multimodal nature of student work, which often integrates textual explanations, drawings, and handwritten elements. Traditional evaluation methods that focus solely on textual analysis fail to capture the full breadth of student reasoning and are susceptible to biases such as handwriting neatness or answer length. In this paper, we propose a novel LLM-augmented multimodal evaluation framework that addresses these limitations through a comprehensive, bias-corrected grading system. Our approach leverages LLMs to generate causal knowledge graphs that encapsulate the essential conceptual relationships in student responses, comparing these graphs with those derived automatically from the rubrics and submissions. Experimental results demonstrate that our framework improves grading accuracy and consistency over deep supervised learning and few-shot LLM baselines. 

Short answer assessment is a vital component of science education, allowing evaluation of students' complex three-dimensional understanding. Large language models (LLMs) that possess human-like ability in linguistic tasks are increasingly popular in assisting human graders to reduce their workload. However, LLMs' limitations in domain knowledge restrict their understanding in task-specific requirements and hinder their ability to achieve satisfactory performance. Retrieval-augmented generation (RAG) emerges as a promising solution by enabling LLMs to access relevant domain-specific knowledge during assessment. In this work, we propose an adaptive RAG framework for automated grading that dynamically retrieves and incorporates domain-specific knowledge based on the question and student answer context. Our approach combines semantic search and curated educational sources to retrieve valuable reference materials. Experimental results in a science education dataset demonstrate that our system achieves an improvement in grading accuracy compared to baseline LLM approaches. The findings suggest that RAG-enhanced grading systems can serve as reliable support with efficient performance gains. 

Abstract SARS-CoV-2 receptor binding domains (RBDs) interact with both the ACE2 receptor and heparan sulfate on the surface of host cells to enhance SARS-CoV-2 infection. We show that suramin, a polysulfated synthetic drug, binds to the ACE2 receptor and heparan sulfate binding sites on the RBDs of wild-type, Delta, and Omicron variants. Specifically, heparan sulfate and suramin had enhanced preferential binding for Omicron RBD, and suramin is most potent against the live SARS-CoV-2 Omicron variant (B.1.1.529) when compared to wild type and Delta (B.1.617.2) variants in vitro. These results suggest that inhibition of live virus infection occurs through dual SARS-CoV-2 targets of S-protein binding and previously reported RNA-dependent RNA polymerase inhibition and offers the possibility for this and other polysulfated molecules to be used as potential therapeutic and prophylactic options against COVID-19. 

Introduction:The unexpected surge of respiratory syncytial virus (RSV) cases following pandemic phase of COVID-19 has drawn much public attention. Drawing on the latest antiviral research, revisiting this heightened annual outbreak of respiratory disease could lead to new treatments. The ability of sulfated polysaccharides to compete for a variety of viruses binding to cell surface heparan sulfate, suggests several drugs that might have therapeutic potential for targeting RSV–glycosaminoglycan interactions. Methods:In the current study, the binding affinity and kinetics of two RSV glycoproteins (RSV-G protein and RSV-F protein) to heparin were investigated by surface plasmon resonance. Furthermore, solution competition studies using heparin oligosaccharides of different lengths indicated that the binding of RSV-G protein to heparin is size-dependent, whereas RSV-F protein did not show any chain length preference. Results and discussion:The two RSV glycoproteins have slightly different preferences for heparin sulfation patterns, but theN-sulfo group in heparin was most critical for the binding of heparin to both RSV-G protein and RSV-F protein. Finally, pentosan polysulfate and mucopolysaccharide polysulfate were evaluated for their inhibition of the RSV-G protein and RSV-F protein–heparin interaction, and both highly negative compounds showed strong inhibition. 

Sulfated glycans from marine organisms are excellent sources of naturally occurring glycosaminoglycan (GAG) mimetics that demonstrate therapeutic activities, such as antiviral/microbial infection, anticoagulant, anticancer, and anti-inflammation activities. Many viruses use the heparan sulfate (HS) GAG on the surface of host cells as co-receptors for attachment and initiating cell entry. Therefore, virion–HS interactions have been targeted to develop broad-spectrum antiviral therapeutics. Here we report the potential anti-monkeypox virus (MPXV) activities of eight defined marine sulfated glycans, three fucosylated chondroitin sulfates, and three sulfated fucans extracted from the sea cucumber species Isostichopus badionotus, Holothuria floridana, and Pentacta pygmaea, and the sea urchin Lytechinus variegatus, as well as two chemically desulfated derivatives. The inhibitions of these marine sulfated glycans on MPXV A29 and A35 protein–heparin interactions were evaluated using surface plasmon resonance (SPR). These results demonstrated that the viral surface proteins of MPXV A29 and A35 bound to heparin, which is a highly sulfated HS, and sulfated glycans from sea cucumbers showed strong inhibition of MPXV A29 and A35 interactions. The study of molecular interactions between viral proteins and host cell GAGs is important in developing therapeutics for the prevention and treatment of MPXV. 

The now prevalent Omicron variant and its subvariants/sub-lineages have led to a significant increase in COVID-19 cases and raised serious concerns about increased risk of infectivity, immune evasion, and reinfection. Heparan sulfate (HS), located on the surface of host cells, plays an important role as a co-receptor for virus–host cell interaction. The ability of heparin and HS to compete for binding of the SARS-CoV-2 spike (S) protein to cell surface HS illustrates the therapeutic potential of agents targeting protein–glycan interactions. In the current study, phylogenetic tree of variants and mutations in S protein receptor-binding domain (RBD) of Omicron BA.2.12.1, BA.4 and BA.5 were described. The binding affinity of Omicron S protein RBD to heparin was further investigated by surface plasmon resonance (SPR). Solution competition studies on the inhibitory activity of heparin oligosaccharides and desulfated heparins at different sites on S protein RBD–heparin interactions revealed that different sub-lineages tend to bind heparin with different chain lengths and sulfation patterns. Furthermore, blind docking experiments showed the contribution of basic amino acid residues in RBD and sulfo groups and carboxyl groups on heparin to the interaction. Finally, pentosan polysulfate and mucopolysaccharide polysulfate were evaluated for inhibition on the interaction of heparin and S protein RBD of Omicron BA.2.12.1, BA.4/BA.5, and both showed much stronger inhibition than heparin.