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One of the artificial intelligence applications in the biomedical field is knowledge-intensive question-answering. As domain expertise is particularly crucial in this field, we propose a method for efficiently infusing biomedical knowledge into pretrained language models, ultimately targeting biomedical question-answering. Transferring all semantics of a large knowledge graph into the entire model requires too many parameters, increasing computational cost and time. We investigate an efficient approach that leverages adapters to inject Unified Medical Language System knowledge into pretrained language models, and we question the need to use all semantics in the knowledge graph. This study focuses on strategies of partitioning knowledge graph and either discarding or merging some for more efficient pretraining. According to the results of three biomedical question answering finetuning datasets, the adapters pretrained on semantically partitioned group showed more efficient performance in terms of evaluation metrics, required parameters, and time. The results also show that discarding groups with fewer concepts is a better direction for small datasets, and merging these groups is better for large dataset. Furthermore, the metric results show a slight improvement, demonstrating that the adapter methodology is rather insensitive to the group formulation.

This study explores the progression of intracerebral hemorrhage (ICH) in patients with mild to moderate traumatic brain injury (TBI). It aims to predict the risk of ICH progression using initial CT scans and identify clinical factors associated with this progression. A retrospective analysis of TBI patients between January 2010 and December 2021 was performed, focusing on initial CT evaluations and demographic, comorbid, and medical history data. ICH was categorized into intraparenchymal hemorrhage (IPH), petechial hemorrhage (PH), and subarachnoid hemorrhage (SAH). Within our study cohort, we identified a 22.2% progression rate of ICH among 650 TBI patients. The Random Forest algorithm identified variables such as petechial hemorrhage (PH) and countercoup injury as significant predictors of ICH progression. The XGBoost algorithm, incorporating key variables identified through SHAP values, demonstrated robust performance, achieving an AUC of 0.9. Additionally, an individual risk assessment diagram, utilizing significant SHAP values, visually represented the impact of each variable on the risk of ICH progression, providing personalized risk profiles. This approach, highlighted by an AUC of 0.913, underscores the model’s precision in predicting ICH progression, marking a significant step towards enhancing TBI patient management through early identification of ICH progression risks.

The paper describes guidelines for the planning, organization, and successful execution of virtual, global scientific conferences for global audiences. The guidelines are based on experience and lessons learned during the organization of the 3‐day 2020 Virtual Systems Chemistry Symposium hosted on Zoom webinar and Twitter, held on May 2020 with over 1000 registered participants from 46 different countries. This planning guide outlines ten steps that academic organizers can follow to successfully organize and execute virtual, global scientific symposia for global audiences. The authors have also included instructional guides, videos, and PowerPoint slides that can be used as templates or inspiration for hosting virtual symposia with oral presentations on Zoom webinar and poster presentations on Twitter.

Matrix metalloproteinase (MMP)-responsive materials have been investigated since the late 1990’s as scaffolds for tissue engineering and since then, have evolved into sophisticated nanomaterials for cancer-targeting therapy. In this thesis titled, “Design and Application of Matrix Metalloproteinase-9-Responsive Peptide Nanostructures,” we aim to answer the following key questions: can MMP-responsive nanomaterials improve the efficacy of anti-cancer treatments? How can we achieve specificity towards MMPs using nanomaterials? Finally, what are the advantages in using peptides as building blocks to create MMP-responsive nanostructures? Each chapter in the thesis will address one or more of the key questions and draw conclusions at the end.

In the rapidly evolving field of healthcare, the integration of artificial intelligence (AI) has become a pivotal component in the automation of clinical workflows, ushering in a new era of efficiency and accuracy. This study focuses on the transformative capabilities of the fine-tuned KoELECTRA model in comparison to the GPT-4 model, aiming to facilitate automated information extraction from thyroid operation narratives. The current research landscape is dominated by traditional methods heavily reliant on regular expressions, which often face challenges in processing free-style text formats containing critical details of operation records, including frozen biopsy reports. Addressing this, the study leverages advanced natural language processing (NLP) techniques to foster a paradigm shift towards more sophisticated data processing systems. Through this comparative study, we aspire to unveil a more streamlined, precise, and efficient approach to document processing in the healthcare domain, potentially revolutionizing the way medical data is handled and analyzed.

Preterm birth (PTB), a leading cause of neonatal morbidity and mortality, is frequently associated with premature cervical remodeling and vaginal microbiome dysbiosis. Cervical shortening in mid-pregnancy is a well-established risk factor for spontaneous PTB (sPTB), yet the microbial signatures underlying this condition remain underexplored, especially in Asian populations. In this study, we conducted shotgun metagenomic analysis of vaginal samples from 35 East Asian pregnant women with a short cervix and 12 with normal cervical length. Species-level taxonomic profiling and functional pathway analysis revealed reduced Lactobacillus dominance, increased microbial diversity, and enrichment of non-optimal CST IV species, such as Fannyhessea vaginae , Bifidobacterium breve , and Mycobacterium canetti in the short cervix group. Functional profiling showed group differences in pathways related to folate biosynthesis, carbohydrate metabolism, and epithelial barrier regulation. Among women with a short cervix, those who delivered preterm had vaginal microbiomes enriched in opportunistic pathogens, including Peptoniphilus equinus , Treponema spp. , and Staphylococcus hominis . Conversely, B. breve , Lactobacillus gasseri , and Lactobacillus paragasseri were associated with full-term delivery. Functions related to glycosylation, structural stability, and degradation of cervical mucin were enriched in the sPTB group. Network analysis identified distinct microbial interactions between Lactobacillus-dominated clusters and CST IV-associated taxa, providing ecological insights that may reflect competitive dynamics and potential influences on cervicovaginal barrier integrity. These findings enhance our understanding of the taxonomic and functional profiles of the vaginal microbiome linked to cervical shortening and sPTB, contributing to improved risk stratification and management strategies for PTB, particularly in women with cervical shortening.

Osteoarthritis—the most common form of age-related degenerative whole-joint disease 1 —is primarily characterized by cartilage destruction, as well as by synovial inflammation, osteophyte formation and subchondral bone remodelling 2 , 3 . However, the molecular mechanisms that underlie the pathogenesis of osteoarthritis are largely unknown. Although osteoarthritis is currently considered to be associated with metabolic disorders, direct evidence for this is lacking, and the role of cholesterol metabolism in the pathogenesis of osteoarthritis has not been fully investigated 4 – 6 . Various types of cholesterol hydroxylases contribute to cholesterol metabolism in extrahepatic tissues by converting cellular cholesterol to circulating oxysterols, which regulate diverse biological processes 7 , 8 . Here we show that the CH25H–CYP7B1–RORα axis of cholesterol metabolism in chondrocytes is a crucial catabolic regulator of the pathogenesis of osteoarthritis. Osteoarthritic chondrocytes had increased levels of cholesterol because of enhanced uptake, upregulation of cholesterol hydroxylases (CH25H and CYP7B1) and increased production of oxysterol metabolites. Adenoviral overexpression of CH25H or CYP7B1 in mouse joint tissues caused experimental osteoarthritis, whereas knockout or knockdown of these hydroxylases abrogated the pathogenesis of osteoarthritis. Moreover, retinoic acid-related orphan receptor alpha (RORα) was found to mediate the induction of osteoarthritis by alterations in cholesterol metabolism. These results indicate that osteoarthritis is a disease associated with metabolic disorders and suggest that targeting the CH25H–CYP7B1–RORα axis of cholesterol metabolism may provide a therapeutic avenue for treating osteoarthritis. In experimentally induced osteoarthritis, chondrocytes show increased uptake and metabolism of cholesterol, implicating the CH25H–CYP7B1–RORα axis in the pathogenesis of osteoarthritis.

Background Metabolic engineering of cyanobacteria has enabled photosynthetic conversion of CO2 to value-added chemicals as bio-solar cell factories. However, the production levels of isoprenoids in engineered cyanobacteria were quite low, compared to other microbial hosts. Therefore, modular optimization of multiple gene expressions for metabolic engineering of cyanobacteria is required for the production of farnesyl diphosphate-derived isoprenoids from CO2. Results Here, we engineered Synechococcus elongatus PCC 7942 with modular metabolic pathways consisting of the methylerythritol phosphate pathway enzymes and the amorphadiene synthase for production of amorpha-4,11-diene, resulting in significantly increased levels (23-fold) of amorpha-4,11-diene (19.8 mg/L) in the best strain relative to a parental strain. Replacing amorphadiene synthase with squalene synthase led to the synthesis of a high amount of squalene (4.98 mg/L/OD730). Overexpression of farnesyl diphosphate synthase is the most critical factor for the significant production, whereas overexpression of 1-deoxy-d-xylulose 5-phosphate reductase is detrimental to the cell growth and the production. Additionally, the cyanobacterial growth inhibition was alleviated by expressing a terpene synthase in S. elongatus PCC 7942 strain with the optimized MEP pathway only (SeHL33). Conclusions This is the first demonstration of photosynthetic production of amorpha-4,11-diene from CO2 in cyanobacteria and production of squalene in S. elongatus PCC 7942. Our optimized modular OverMEP strain (SeHL33) with either co-expression of ADS or SQS demonstrated the highest production levels of amorpha-4,11-diene and squalene, which could expand the list of farnesyl diphosphate-derived isoprenoids from CO2 as bio-solar cell factories.

Background It is crucial that the safety profiles of biosimilars are similar to those of the original biologics. A better understanding of biosimilars and their relative safety and immunogenicity profiles are required for healthcare providers to prescribe them to patients with life-threatening cancer diseases who receive chemotherapies with potentially serious adverse events (AEs). Objectives The purpose of this study was to collate and analyze currently available safety and immunogenicity outcomes of biosimilars used in oncology and compare their safety information with those of the original biologics. Methods The MEDLINE and Cochrane Library databases were searched as at 28 February 2022. Four anti-cancer biosimilar molecules were considered: bevacizumab, trastuzumab, rituximab, and (peg)filgrastim. Through a systematic review, we selected the randomized controlled trials (RCTs) comparing safety outcomes between the biosimilars and original biologics of the four molecules. As safety outcomes, various treatment-emergent adverse events (TEAEs) were collated, such as any TEAE, serious AE, and TEAE higher than grade 3. A risk ratio (RR) per category of TEAE was estimated through a meta-analysis. A network meta-analysis (NMA) was also conducted to compare the safety among the biosimilar brands for TEAEs over 25% with higher variability in addition to the serious AE cases. Results Forty-nine RCTs were identified. The results from the meta-analysis showed that the safety and immunogenicity profiles of all four biosimilar molecules are comparable with that of the original biologics at the TEAE level without statistically significant differences, except for diarrhea for (peg)filgrastim. The incidence of diarrhea with (peg)filgrastim was less than that with the original biologic (RR 0.66, 95% confidence interval 0.50–0.89). The NMA results showed similar safety profiles among the biosimilar brands for all four biosimilar molecules, except for the serious adverse event of a trastuzumab biosimilar (RR 0.296, 95% credible interval 0.109–0.840). Conclusion The meta-analysis and NMA for all four biosimilars showed that the safety and immunogenicity profiles of biosimilar products in oncology are generally comparable with that of the original biologics at the TEAE level. However, additional evidence needs to be collected since several TEAEs of specific biosimilars were out of the equivalent range. The results of this study provide comparative safety information and a better understanding of oncology biosimilars for healthcare providers to prescribe them to patients.

Osteoarthritis--the most common form of age-related degenerative whole-joint disease.sup.1--is primarily characterized by cartilage destruction, as well as by synovial inflammation, osteophyte formation and subchondral bone remodelling.sup.2,3. However, the molecular mechanisms that underlie the pathogenesis of osteoarthritis are largely unknown. Although osteoarthritis is currently considered to be associated with metabolic disorders, direct evidence for this is lacking, and the role of cholesterol metabolism in the pathogenesis of osteoarthritis has not been fully investigated.sup.4-6. Various types of cholesterol hydroxylases contribute to cholesterol metabolism in extrahepatic tissues by converting cellular cholesterol to circulating oxysterols, which regulate diverse biological processes.sup.7,8. Here we show that the CH25H-CYP7B1-ROR[alpha] axis of cholesterol metabolism in chondrocytes is a crucial catabolic regulator of the pathogenesis of osteoarthritis. Osteoarthritic chondrocytes had increased levels of cholesterol because of enhanced uptake, upregulation of cholesterol hydroxylases (CH25H and CYP7B1) and increased production of oxysterol metabolites. Adenoviral overexpression of CH25H or CYP7B1 in mouse joint tissues caused experimental osteoarthritis, whereas knockout or knockdown of these hydroxylases abrogated the pathogenesis of osteoarthritis. Moreover, retinoic acid-related orphan receptor alpha (ROR[alpha]) was found to mediate the induction of osteoarthritis by alterations in cholesterol metabolism. These results indicate that osteoarthritis is a disease associated with metabolic disorders and suggest that targeting the CH25H-CYP7B1-ROR[alpha] axis of cholesterol metabolism may provide a therapeutic avenue for treating osteoarthritis.