Citations

Abstract Objective Human Papillomavirus (HPV) vaccine is an effective measure to prevent and control the diseases caused by HPV. However, widespread misinformation and vaccine hesitancy remain significant barriers to its uptake. This study focuses on the development of VaxBot-HPV, a chatbot aimed at improving health literacy and promoting vaccination uptake by providing information and answering questions about the HPV vaccine. Methods We constructed the knowledge base (KB) for VaxBot-HPV, which consists of 451 documents from biomedical literature and web sources on the HPV vaccine. We extracted 202 question-answer pairs from the KB and 39 questions generated by GPT-4 for training and testing purposes. To comprehensively understand the capabilities and potential of GPT-based chatbots, 3 models were involved in this study: GPT-3.5, VaxBot-HPV, and GPT-4. The evaluation criteria included answer relevancy and faithfulness. Results VaxBot-HPV demonstrated superior performance in answer relevancy and faithfulness compared to baselines. For test questions in KB, it achieved an answer relevancy score of 0.85 and a faithfulness score of 0.97. Similarly, it attained scores of 0.85 for answer relevancy and 0.96 for faithfulness on GPT-generated questions. Discussion VaxBot-HPV demonstrates the effectiveness of fine-tuned large language models in healthcare, outperforming generic GPT models in accuracy and relevance. Fine-tuning mitigates hallucinations and misinformation, ensuring reliable information on HPV vaccination while allowing dynamic and tailored responses. The specific fine-tuning, which includes context in addition to question-answer pairs, enables VaxBot-HPV to provide explanations and reasoning behind its answers, enhancing transparency and user trust. Conclusions This study underscores the importance of leveraging large language models and fine-tuning techniques in the development of chatbots for healthcare applications, with implications for improving medical education and public health communication.

Severe COVID-19 is a multisystem condition with thromboinflammation as a significant driver of morbidity and mortality. Cellular components involved in inflammatory and coagulation responses include platelets, endothelium, monocytes, and neutrophils. Thrombotic manifestations, such as arterial thrombosis, venous thromboembolism, and tissue microthrombosis, occur in at least 20% of ICU COVID-19 patients, possibly more based on postmortem studies. This study investigates the presence of prothrombotic antibodies similar to those found in heparin-induced thrombocytopenia (HIT), a condition caused by platelet-activating antibodies targeting platelet factor 4 (PF4) when complexed with heparin (PF4/H). In a study of samples from 130 hospitalized patients collected on average 3.6 days after COVID-19 diagnosis, 80% were found to have IgG antibodies recognizing PF4/H. This percentage is significantly lower than in 22 HIT patients (100%) but higher than in 51 non-COVID-19 patients with acute respiratory symptoms (ARS) (25%) and 12 healthy subjects (0%). Additionally, 41% of the 130 patients had antibodies inducing PF4-dependent P-selectin expression in CpG-treated normal platelets, a rate significantly lower than in 12 HIT patients (100%) but higher than in 51 non-COVID-19 ARS patients (20%) and 12 healthy subjects (0%). Significantly, platelet-activating antibodies in COVID-19 patients were associated with a specific elevation of platelet α-granule proteins in the plasma and correlated with inflammation and tissue damage markers, suggesting these antibodies' functionality in patients. Significantly, unlike HIT, both PF4/H-reactive and platelet-activating antibodies were found in COVID-19 patients regardless of recent heparin exposure, indicating different antigenic stimuli for these antibodies in COVID-19. Notably, certain antibodies against the receptor-binding domain (RBD) of the spike protein of SARS-CoV-2 possessed sequence motifs, RKH and Y5, in the heavy-chain complementarity-determining region 3 (HCDR3) resembling those in pathogenic HIT antibodies identified in our previous studies, suggesting that these antibodies can activate platelets. Introducing exogenous RBD to COVID-19 plasma or IgG purified from COVID-19 plasma significantly reduced their ability to activate platelets. Furthermore, immunodepleting RBD-reactive antibodies from COVID-19 plasma or IgG purified from COVID-19 plasma using RBD-coated beads significantly reduced their ability to activate platelets. These findings demonstrate that some RBD-specific plasma IgG antibodies can activate platelets. To demonstrate the presence of RBD-specific, platelet-activating antibodies at the clonal level, we produced recombinant antibodies from 42 RBD-binding IgG+ B cells, tested their ability to activate platelets, and identified four that could do so. Interestingly, three antibodies possess HCDR3 sequences resembling RKH or Y5 motifs. Additionally, we identified RKH or Y5 motifs in RBD-specific antibodies reported by other groups, produced 15 such antibodies recombinantly, tested their ability to activate platelets, and identified four more that could do so. IgG+ B cells with these HCDR3 motifs were markedly expanded in severe COVID-19 patients, suggesting an expansion of B cells producing platelet-activating antibodies. The demonstration of functional and structural similarities between certain RBD-specific antibodies in COVID-19 patients and pathogenic HIT antibodies suggests a novel mechanism by which RBD-specific antibodies might contribute to thrombosis in COVID-19.

Background: Although advanced stage cHL typically has excellent disease outcomes, 20-30% of patients (pts) experience treatment failure. In addition, decision-making is challenging given varying treatment options and incomplete prognostic data across the disease course. Pre-treatment factors, such as those incorporated into the Advanced Stage Hodgkin Lymphoma International Prognostication Index (A-HIPI), predict 5 year (y) overall survival (OS) and progression-free survival (PFS) (Rodday JCO 2023). Other than interim PET (iPET) results, it is unknown what factors influence cHL disease states mid-therapy. Using multistate modeling (MSM) and individual pt data from the HoLISTIC Consortium, we refined prognostication across the cHL disease course, specifically assessing the relationships between A-HIPI, iPET and end of treatment (EOT) response, and whether the A-HIPI and iPET provide independent prognostic information. Methods: We analyzed 1240 pts aged 18-65y with newly diagnosed Stage IIB, III or IV cHL treated on 2 advanced stage PET-adapted trials (RATHL, SWOG0816). All pts first received 2 cycles of ABVD; those with a negative iPET (Deauville score (DS) ≤3) received ABVD or AVD, and those with a positive iPET (DS >3) received BEACOPP. In contrast to other methods, MSMs incorporate multiple disease states into one model, account for censoring and competing risks, and estimate transitions between disease states using different covariates. Our MSM had 6 states: diagnosis, negative iPET, positive iPET, EOT non-progression (e.g., DS ≤ 3), treatment failure, and death. Treatment failure included progression or relapse. All pts start at the diagnosis state and can transition to other states without return to prior states. Transition states with <5 events were excluded. The MSM was estimated using a multivariable Cox model with censoring at 5y. Covariates were the 5y PFS A-HIPI (comprised of stage and continuous age, lymphocyte count and albumin), which was included for all transitions, and iPET, which was included for transitions from EOT non-progression and from treatment failure. Higher scores on the 5y PFS A-HIPI indicate lower risk of progression or death; the A-HIPI was modeled for a 1 standard deviation (SD) increase. We calculated probabilities of 5y treatment failure for 4 sample pts based on low (70) and high (85) A-HIPI scores, positive and negative iPET, and EOT non-progression. Results: Median age was 33y (Q1=25, Q3=45), 56% were male, 23% were stage IIB, 40% III and 37% IV, and mean A-HIPI was 77 (SD=7). Median follow-up was 75 months (Q1=53, Q3=92). At iPET, 80% (95% CI 78%, 83%) were negative and 16% (95% CI 14%, 18%) were positive. At EOT, 90% (95% CI 89%, 92%) were in the non-progression state. At 5y, 75% (95% CI 73%, 78%) were in the non-progression state, 16% (95% CI 14%, 19%) had experienced treatment failure, and 9% (7%, 11%) had died. Better A-HIPI scores (per SD) were associated with lower rates of transitioning from diagnosis to positive iPET (HR=0.80, p<0.01) and from positive iPET to treatment failure (HR=0.58, p=0.04). Better A-HIPI scores (per SD) were also associated with lower rates of transitioning from EOT non-progression to treatment failure (HR=0.78, p<0.01) and from treatment failure to death (HR=0.64, p<0.01), adjusting for iPET. Positive iPET was associated with an increased rate of transitioning from EOT non-progression to treatment failure (HR=1.90, p<0.01), adjusting for A-HIPI. The probability of 5y treatment failure for 4 sample pts was: 25% for low A-HIPI and positive iPET; 20% for high A-HIPI and positive iPET; 13% for low A-HIPI and negative iPET; and 12% for high A-HIPI and negative iPET. Conclusions: We created a novel MSM that refines prognostication across the cHL disease course by incorporating pre- and post-treatment factors (e.g., iPET) to estimate transitions to future disease states. Although the A-HIPI was developed using pre-treatment factors to predict 5y OS and PFS, we found that it was also associated with transitions to interim disease states, including iPET and EOT response. The A-HIPI and iPET each provided independent prognostic information, supporting the use of both in estimating cHL outcomes. Future analyses will develop clinical prediction models using MSMs that also incorporate varying frontline and salvage treatments and treatment-specific late effects, with the goal of providing individualized information across the disease course.

Abstract Thromboembolic complication is common in severe coronavirus disease 2019 (COVID-19), leading to an investigation into the presence of prothrombotic antibodies akin to those found in heparin-induced thrombocytopenia (HIT). In a study of samples from 130 hospitalized patients, collected 3.6 days after COVID-19 diagnosis, 80% had immunoglobulin G (IgG) antibodies recognizing complexes of heparin and platelet factor 4 (PF4; PF4/H), and 41% had antibodies inducing PF4-dependent P-selectin expression in CpG oligodeoxynucleotide–treated normal platelets. Unlike HIT, both PF4/H-reactive and platelet-activating antibodies were found in patients with COVID-19 regardless of recent heparin exposure. Notably, PF4/H-reactive IgG antibodies correlated with those targeting the receptor-binding domain (RBD) of the severe acute respiratory syndrome coronavirus 2 spike protein. Moreover, introducing exogenous RBD to or removing RBD-reactive IgG from COVID-19 plasma or IgG purified from COVID-19 plasma significantly reduced their ability to activate platelets. RBD-specific antibodies capable of platelet activation were cloned from peripheral blood B cells of patients with COVID-19. These antibodies possessed sequence motifs in the heavy-chain complementarity-determining region 3 (HCDR3), resembling those identified in pathogenic HIT antibodies. Furthermore, IgG+ B cells having these HCDR3 signatures were markedly expanded in patients with severe COVID-19. Importantly, platelet-activating antibodies present in patients with COVID-19 were associated with a specific elevation of platelet α-granule proteins in the plasma and showed a positive correlation with markers for inflammation and tissue damage, suggesting a functionality of these antibodies in patients. The demonstration of functional and structural similarities between certain RBD-specific antibodies in patients with COVID-19 and pathogenic antibodies typical of HIT suggests a novel mechanism by which RBD-specific antibodies might contribute to thrombosis in COVID-19.

AbstractLiver fibrosis is a pathological process resulting from prolonged exposure to various injury factors. It is characterized by the abnormal proliferation and activation of hepatic stellate cells and excessive deposition of extracellular matrix. If left untreated, it can progress to cirrhosis, liver failure, and even liver cancer. There is currently no efficient and accurate clinical diagnostic method for early liver fibrosis. Therefore, there is an urgent need to address the challenge of accurate staging and early diagnosis of liver fibrosis in clinical practice. Recently, nanomaterials have demonstrated significant potential for enhancing the diagnosis of liver fibrosis. Nanomaterials possess the ability to precisely identify and target the microenvironment associated with liver fibrosis. By enhancing their enrichment in the target area, nanomaterials can improve imaging contrast of fibrosis lesions in the liver, thereby enabling accurate diagnosis of liver fibrosis. Accordingly, this review delves into the latest research and advancements concerning nanomaterials in liver fibrosis diagnosis.

Abstract Objective SNOMED CT provides a standardized terminology for clinical concepts, allowing cohort queries over heterogeneous clinical data including Electronic Health Records (EHRs). While it is intuitive that missing and inaccurate subtype (or is-a) relations in SNOMED CT reduce the recall and precision of cohort queries, the extent of these impacts has not been formally assessed. This study fills this gap by developing quantitative metrics to measure these impacts and performing statistical analysis on their significance. Material and Methods We used the Optum de-identified COVID-19 Electronic Health Record dataset. We defined micro-averaged and macro-averaged recall and precision metrics to assess the impact of missing and inaccurate is-a relations on cohort queries. Both practical and simulated analyses were performed. Practical analyses involved 407 missing and 48 inaccurate is-a relations confirmed by domain experts, with statistical testing using Wilcoxon signed-rank tests. Simulated analyses used two random sets of 400 is-a relations to simulate missing and inaccurate is-a relations. Results Wilcoxon signed-rank tests from both practical and simulated analyses (P-values < .001) showed that missing is-a relations significantly reduced the micro- and macro-averaged recall, and inaccurate is-a relations significantly reduced the micro- and macro-averaged precision. Discussion The introduced impact metrics can assist SNOMED CT maintainers in prioritizing critical hierarchical defects for quality enhancement. These metrics are generally applicable for assessing the quality impact of a terminology’s subtype hierarchy on its cohort query applications. Conclusion Our results indicate a significant impact of missing and inaccurate is-a relations in SNOMED CT on the recall and precision of cohort queries. Our work highlights the importance of high-quality terminology hierarchy for cohort queries over EHR data and provides valuable insights for prioritizing quality improvements of SNOMED CT's hierarchy.

ABSTRACT Background The optimal exercise regimen for alleviating sarcopenia remains uncertain. This study aimed to investigate the efficacy of high‐intensity interval training (HIIT) over moderate‐intensity continuous training (MICT) in ameliorating sarcopenia. Methods We conducted a randomized crossover trial to evaluate plasma proteomic reactions to acute HIIT (four 4‐min high‐intensity intervals at 70% maximal capacity alternating with 4 min at 30%) versus MICT (constant 50% maximal capacity) in inactive adults. We explored the relationship between a HIIT‐specific protein relative to MICT, identified via comparative proteomic analysis, eukaryotic translation elongation factor 1 epsilon 1 (EEF1E1) and sarcopenia in a paired case–control study of elderly individuals (aged over 65). Young (3 months old) and aged (20 months old) mice were randomized to sedentary, HIIT and MICT groups (five sessions/week for 4 weeks; n = 8 for each group). Measurements included skeletal muscle index, hand grip strength, expression of atrophic markers Atrogin1 and MuRF1 and differentiation markers MyoD, myogenin and MyHC‐II via western blotting. We examined the impact of EEF1E1 siRNA and recombinant protein on D‐galactose‐induced myoblast senescence, measuring senescence‐associated β‐galactosidase and markers like p21 and p53. Results The crossover trial, including 10 sedentary adults (32 years old, IQR 31–32) demonstrated significant alterations in the abundance of 21 plasma proteins after HIIT compared with MICT. In the paired case–control study of 84 older adults (84 years old, IQR 69–81; 52% female), EEF1E1 was significantly increased in those with sarcopenia compared to those without (14.68 [95%CI, 2.02–27.34] pg/mL, p = 0.03) and was associated with skeletal muscle index ( R 2 = 0.51, p < 0.001) and hand grip strength ( R 2 = 0.54, p < 0.001). In the preclinical study, aged mice exhibited higher EEF1E1 mRNA and protein levels in skeletal muscle compared to young mice, accompanied by a lower muscle mass and strength, increased cellular senescence and protein degradation markers and reduced muscle differentiation efficiency (all p < 0.05). HIIT reduced EEF1E1 expression and mitigated age‐related muscle decline and atrophy in aged mice more effectively than MICT. Notably, EEF1E1 downregulation via siRNA significantly counteracted D‐galactose‐induced myoblast senescence as evidenced by reduced markers of muscle protein degradation and improved muscle differentiation efficiency (all p < 0.05). Conversely, treatments that increased EEF1E1 levels accelerated the senescence process ( p < 0.05). Further exploration indicated that the decrease in EEF1E1 was associated with increased SIRT1 level and enhanced autophagy. Conclusions This study highlights the potential of HIIT as a promising approach to prevent and treat sarcopenia while also highlighting EEF1E1 as a potential intervention target.

Abstract Background: HPV vaccine is an effective measure to prevent and control the diseases caused by Human Papillomavirus (HPV). This study addresses the development of VaxBot-HPV, a chatbot aimed at improving health literacy and promoting vaccination uptake by providing information and answering questions about the HPV vaccine; Methods: We constructed the knowledge base (KB) for VaxBot-HPV, which consists of 451 documents from biomedical literature and web sources on the HPV vaccine. We extracted 202 question-answer pairs from the KB and 39 questions generated by GPT-4 for training and testing purposes. To comprehensively understand the capabilities and potential of GPT-based chatbots, three models were involved in this study : GPT-3.5, VaxBot-HPV, and GPT-4. The evaluation criteria included answer relevancy and faithfulness; Results: VaxBot-HPV demonstrated superior performance in answer relevancy and faithfulness compared to baselines (Answer relevancy: 0.85; Faithfulness: 0.97) for the test questions in KB, (Answer relevancy: 0.85; Faithfulness: 0.96) for GPT generated questions; Conclusions: This study underscores the importance of leveraging advanced language models and fine-tuning techniques in the development of chatbots for healthcare applications, with implications for improving medical education and public health communication.