Explore the vast range of titles available.

Purpose: Radiotherapy is a crucial treatment approach for many types of cancer. Radiation pneumonitis (RP) is one of the major complications in chest irradiation. Fucoidan is a sulfated polysaccharide found mainly in various species of brown seaweed. Recent studies have demonstrated the anti-inflammatory effects of fucoidan. However, no study has reported a well-established prophylactic agent for RP. Therefore, we investigated the effects of fucoidan on RP and radiotherapy (RT)-induced lung fibrosis. Materials and Methods: We compared RP and RT-induced fibrosis in lung tissue specimens obtained from irradiated (10 Gy/shot) C57BL/6 mice with or without fucoidan administration (200 mg/kg/day, oral gavage for 14 days). The expression patterns of cytokines in the pleural fluid were determined using a cytokine array and confirmed through enzyme immunoassays. Results: Fucoidan administration attenuated RP and RT-induced fibrosis in lung tissues. Decreased neutrophil and macrophage accumulation was observed in irradiated lung tissues, and radiation-induced lung fibrosis, as demonstrated by Masson trichrome staining, was attenuated. We investigated the expression patterns of inflammatory cytokines in the irradiated lung pleural fluid through the protein array; results revealed that fucoidan administration changed the expression patterns of inflammatory cytokines in irradiated lung tissues. Furthermore, the expression levels of TIMP-1, CXCL1, MCP-1, MIP-2, and interleukin-1Ra were substantially enhanced in the pleural fluid, but fucoidan administration significantly reduced their expression. Conclusions: Fucoidan changes the expression patterns of inflammatory cytokines, which may consequently attenuate RP and RT-induced lung fibrosis.

Coronavirus Disease-2019 (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus. Various studies exist about the molecular mechanisms of viral infection. However, such information is spread across many publications and it is very time-consuming to integrate, and exploit. We develop CoVex, an interactive online platform for SARS-CoV-2 host interactome exploration and drug (target) identification. CoVex integrates virus-human protein interactions, human protein-protein interactions, and drug-target interactions. It allows visual exploration of the virus-host interactome and implements systems medicine algorithms for network-based prediction of drug candidates. Thus, CoVex is a resource to understand molecular mechanisms of pathogenicity and to prioritize candidate therapeutics. We investigate recent hypotheses on a systems biology level to explore mechanistic virus life cycle drivers, and to extract drug repurposing candidates. CoVex renders COVID-19 drug research systems-medicine-ready by giving the scientific community direct access to network medicine algorithms. It is available at https://exbio.wzw.tum.de/covex/ . Information developed to understand the molecular mechanisms of SARS-CoV-2 infection for predicting drug repurposing candidates is time-consuming to integrate and explore. Here, the authors develop an interactive online platform for virus-host interactome exploration and drug (target) identification.

A potentiometric enzyme biosensor is a convenient detector for quantification of urea concentrations in industrial processes, or for monitoring patients with diabetes, kidney damage or liver malfunction. In this work, poly(3-hexylthiophene-co-3-thiopheneacetic acid) (P(3HT-co-3TAA)) was chemically synthesized, characterized and spin-coated onto conductive indium tin oxide (ITO) glass electrodes. Urease (Urs) was covalently attached to the smooth surface of this copolymer via carbodiimide coupling. The electrochemical behavior and stability of the modified Urs/P(3HT-co-3TAA)/ITO glass electrode were investigated by cyclic voltammetry, and the bound enzyme activity was confirmed by spectrophotometry. Potentiometric response studies indicated that this electrode could determine the concentration of urea in aqueous solutions, with a quasi-Nernstian response up to about 5 mM. No attempt was made to optimize the response speed; full equilibration occurred after 10 min, but the half-time for response was typically <1 min.

Glioblastoma (GBM) is the most common malignant primary brain tumor, with a median survival rate of less than two years. Currently, there is no cure for GBM, underscoring the urgent need for innovative treatment approaches. Vaccine design emerges as a crucial strategy, offering a safe and effective means for both preventive and therapeutic interventions against GBM. In this study, we targeted four GBM-associated mutated surface proteins—urokinase plasminogen activator surface receptor (PLAUR), integrin beta-3 (ITGB3), and the B-41 alpha chain (HLA-B) and A-24 alpha chain (HLA-A) of the HLA class I histocompatibility antigens—to design a peptide-based vaccine. The vaccine construct includes cytotoxic T lymphocyte (CTL) and T helper cell (Th cell) epitopes, and was meticulously evaluated for antigenicity, allergenicity, and toxicity. The results indicate that the vaccine is antigenic and non-allergenic, making it a promising candidate. Additionally, the physicochemical properties of the vaccine suggest stability and suitability for further development. Immune simulation studies predict a strong immune response upon vaccine administration. Our vaccine shows promise as a potential tool in the fight against GBM, offering new hope for patients facing this devastating disease.

Background Serial measurements of C-reactive protein (CRP) are often taken in hospitals to assess recovery from infection, but their utility remains debated. Previous studies, including our development of CRP centile reference charts for suspected bloodstream infections (BSI), suggest variability in CRP responses across infection types. Here we investigated the association between serial CRP percentile changes, antibiotic prescribing patterns, and patient outcomes in a large cohort with suspected infection, acknowledging that CRP is one of multiple factors in clinical decision-making. Methods We analysed 51,544 suspected infection episodes (defined by blood culture collection) from 36,578 patients in Oxfordshire, UK (2016–2021). Episodes were categorised by blood culture results: Gram-positive, Gram-negative, polymicrobial, contaminants, or culture-negative (having previously shown that 51% culture-negatives have CRP responses indistinguishable from culture-positives). The spectrum of antibiotic prescriptions and their changes over time were tracked. Multinomial logistic regression, adjusted for clinical covariates, assessed the association between CRP percentile changes and subsequent prescribing decisions. Linear mixed models evaluated CRP trajectories post-prescribing, and logistic regression associations between early CRP changes (days 1–4) and 5–30-day mortality. Results Broad-spectrum antibiotics were predominantly used within the first three days after blood culture collection, followed by a notable shift to narrow-spectrum antibiotics for Gram-positive infections, but with slower de-escalation for Gram-negative and polymicrobial infections. CRP percentile changes were modestly associated with subsequent antibiotic adjustments; in particular, suboptimal recovery, indicated by an increase in CRP centiles, was associated with a higher rate of antibiotic escalation (16.5% vs. 10.7% in expected recovery) and, conversely, faster than expected recovery in CRP was associated with de-escalation (23.6% vs. 17.2%). However, 61.8% of decisions were unchanged despite CRP trends. The relationship between various prescribing decisions and subsequent CRP percentile changes was complex and challenging to estimate, likely due to testing bias. CRP percentile changes during the 4 days post blood culture collection were strongly associated with 5–30-day mortality, highlighting their potential utility as a prognostic indicator. Conclusions While CRP monitoring can inform antibiotic stewardship, its association with prescribing decisions is probably only modest, underscoring the need to integrate a range of clinical factors to optimise infection management.

There is currently no system to predict 90-day morality among patients with locally advanced head and neck squamous cell carcinoma (HNSCC) after the completion of concurrent chemoradiotherapy (CCRT). To validate the accuracy of a predictive scoring system for 90-day mortality among patients with locally advanced HNSCC who have completed CCRT. This prognostic study included 16 029 patients with HNSCC who completed CCRT between January 2006 and December 2015. Data were extracted from the Taiwan Cancer Registry Database. A risk scoring system was developed based on significant risk factors and corresponding risk coefficients. Data analysis was conducted from June 2018 to February 2019. Mortality within 90 days of completion of definitive CCRT. The 90-day mortality rate after completion of CCRT and the accuracy of the scoring system, based on a comparison of mortality rates between training and test data sets. Among 16 029 patients with locally advanced HNSCC, 1068 (6.66%; 1016 [95.1%] men; mean [SD] age, 55.11 [11.45] years) died before reaching the 90-day threshold, and 14 961 (93.4%; 14 080 [94.1%] men; mean [SD] age, 52.07 [9.99] years) survived. Multivariable analysis revealed that being aged 50 years or older (adjusted hazard ratio [aHR], 1.263; 95% CI, 1.104-1.445; P < .001), being aged 70 years or older (aHR, 2.183; 95% CI, 1.801-2.645; P < .001), having pneumonia (aHR, 1.946; 95% CI, 1.636-2.314; P < .001), having sepsis (aHR, 3.005; 95% CI, 2.503-3.607; P < .001), having hemiplegia (aHR, 1.430; 95% CI, 1.085-1.884; P = .01), having moderate or severe renal disease (aHR, 2.054; 95% CI, 1.643-2.568; P < .001), having leukemia (aHR, 4.541; 95% CI, 1.132-8.207; P = .03), and having non-HNSCC metastatic solid cancers (aHR, 1.457; 95% CI, 1.292-1.644; P < .001) were significant risk factors for 90-day mortality. Risk scores were categorized as very low risk (score of 0), low risk (score 1-3), moderate risk (score 4-6), and high risk (score ≥7), with 90-day mortality rates of 3.37%, 5.00% to 10.98%, 16.15% to 29.13%, and 33.93% to 37.50%, respectively. Mortality rates for patients with the same risk score in the training and test data sets were similar (score of 0, 3.27% vs 3.66%; score of 6, 27.42% vs 25.00%). In this prognostic study, a 90-day mortality scoring system accurately predicted 90-day mortality among patients with locally advanced HNSCC who completed CCRT.

PurposeThe risk of cardiotoxicity induced by adjuvant anthracycline-based chemotherapy (CT) and radiotherapy (RT) is yet to be investigated in a large-scale randomized controlled trial with an adequate sample size of young and old women with breast cancer.Patients and methodsTo compare the occurrence of major heart events (heart failure and coronary artery disease) in patients with breast cancer, 3489 women who underwent surgical resection of the breast tumor were retrospectively selected from the Taiwan National Health Insurance Research Database. The patients were categorized into the following groups based on their treatment modalities: group 1 (n = 1113), no treatment; group 2 (n = 646), adjuvant RT alone; group 3 (n = 705), adjuvant anthracycline-based CT alone; and group 4 (n = 1025), combined adjuvant RT and anthracycline-based CT.ResultsThe mean patient age was 50.35 years. Subsequent coronary artery disease and heart failure were identified in 244 (7.0%) and 206 (5.9%) patients, respectively. All three adjuvant therapies were significant independent prognostic factors of major heart events (adjusted hazard ratio [95% confidence interval]: 1.47 [1.24–1.73]; 1.48 [1.25–1.75], and 1.92 [1.65–2.23] in groups 2, 3, and 4, respectively). In patients aged ≥50 years with breast cancer who underwent surgery, the log-rank p values of groups 2 and 3 after adjustment were 0.537 and 0.001, respectively.ConclusionAdjuvant RT can increase cardiotoxicity in patients with breast cancer, particularly when used in combination with anthracycline-based CT. Therefore, it should be offered with optimal heart-sparing techniques, particularly in younger patients with good prognosis and long life expectancy.

We examined the overall survival rates of a national cohort to determine optimal treatments and prognostic factors for patients with metachronous second primary head and neck squamous cell carcinomas (mspHNSCCs) at different stages and sites. We analyzed data of mspHNSCC patients collected from the Taiwan Cancer Registry database. The patients were categorized into four groups based on the treatment modality: Group 1 (control arm; chemotherapy [CT] alone), Group 2 (reirradiation [re‐RT] alone with intensity‐modulated radiotherapy [IMRT]), Group 3 (concurrent chemoradiotherapy alone [irradiation with IMRT]), and Group 4 (salvage surgery with or without RT or CT). We enrolled 1741 mspHNSCC patients without distant metastasis. Multivariate Cox regression analyses revealed that Charlson comorbidity index (CCI) ≥6, stage of second HNSCC, stage of first HNSCC, and duration from first primary HNSCC of <3 years were significant poor independent prognostic risk factors for overall survival. After adjustment, adjusted hazard ratios and 95% confidence intervals for the overall all‐cause mortality risk at mspHNSCC clinical stages III and IV were 0.72 (0.40–1.82), 0.52 (0.35–0.75), and 0.32 (0.22–0.45) in Groups 2, 3, and 4, respectively. A Cox regression analysis indicated that a re‐RT dose of ≥6000 cGy was an independent protective prognostic factor for treatment modalities. CCI ≥ 6, stage of second HNSCC, stage of first HNSCC, and duration from first primary HNSCC of <3 years were significant poor independent prognostic risk factors for overall survival. A re‐RT dose of ≥6000 cGy may be necessary for mspHNSCCs. Metachronous second primary head and neck squamous cell carcinoma are rare and optimal therapeutic decisions for metachronous second primary head and neck squamous cell carcinomas (HNSCCs) are unclear. Suitable treatments and prognostic factors for the population were analyzed. This study is the first to estimate the prognostic factors of metachronous second primary HNSCCs.

Background Free-text data is abundant in electronic health records, but challenges in accurate and scalable information extraction mean less specific clinical codes are often used instead. Methods We evaluated the efficacy of feature extraction using modern natural language processing methods (NLP) and large language models (LLMs) on 938,150 hospital antibiotic prescriptions from Oxfordshire, UK. Specifically, we investigated inferring the type(s) of infection from a free-text “indication” field, where clinicians state the reason for prescribing antibiotics. Clinical researchers labelled a subset of the 4000 most frequent unique indications (representing 692,310 prescriptions) into 11 categories describing the infection source or clinical syndrome. Various models were then trained to determine the binary presence/absence of these infection types and also any uncertainty expressed by clinicians. Results We show on separate internal ( n  = 2000 prescriptions) and external test datasets (n = 2000 prescriptions), a fine-tuned domain-specific Bio+Clinical BERT model performs best across the 11 categories (average F1 score 0.97 and 0.98 respectively) and outperforms traditional regular expression (F1 = 0.71 and 0.74) and n-grams/XGBoost (F1 = 0.86 and 0.84) models. A zero-shot OpenAI GPT4 model matches the performance of traditional NLP models without the need for labelled training data (F1 = 0.71 and 0.86) and a fine-tuned GPT3.5 model achieves similar performance to the fine-tuned BERT-based model (F1 = 0.95 and 0.97). Infection sources obtained from free-text indications reveal specific infection sources 31% more often than ICD-10 codes. Conclusions Modern transformer-based models have the potential to be used widely throughout medicine to extract information from structured free-text records, to facilitate better research and patient care. Plain language summary Electronic health records often contain detailed information on clinical decisions and patient histories that are written as free text and otherwise not recorded in a structured format in a specific section of the record. Extracting specific information from this unstructured text is challenging, leading to researchers often using less detailed clinical information. This study evaluated whether computational methods, including large language models, could be used to extract detailed information from unstructured sections of medical records. As an example task, we attempted to identify which type of infection was being treated from free-text justifying antibiotic prescriptions. We could categorise infection types more often and more accurately than previous methods. This method of extracting detailed information from medical records could potentially improve research and patient care. Yuan, Yoon, Gu et al. use modern natural language processing (NLP) methods and large language models (LLMs) to extract features from medical records. Transformer-based models provide high performance on antibiotic prescriptions, demonstrating their potential to be used to extract information from free-text medical records.

Abstract BACKGROUND: Although the majority of patients with cerebral venous sinus thrombosis (CVST) obtain an optimistic clinical outcome after heparin or warfarin treatment, there remains a subgroup of patients who do not respond to conventional anticoagulation treatment. These patients, especially younger people, as documented by hospital-based studies, have a high morbidity and mortality rate. OBJECTIVE: To verify the safety and efficacy of a dual mechanical thrombectomy with thrombolysis treatment modality option in patients with severe CVST. METHODS: Fifty-two patients diagnosed with CVST were enrolled and treated with mechanical thrombectomy combined with thrombolysis. Patients underwent urokinase 100 to 1500 × 103 IU intravenous sinus injection via a jugular catheter after confirming diagnoses of CVST by using either magnetic resonance imaging/magnetic resonance venography or digital subtract angiography. Information obtained on the patients included recanalization status of venous sinuses as evaluated by magnetic resonance venography or digital subtract angiography at admission, during operation, and at 3- and 6-month follow-up after treatment. RESULTS: The percentage of patients that showed complete and partial recanalization were 87% and 6%, respectively, after mechanical thrombectomy combined with thrombolysis treatment; 8% of the patients showed no recanalization. The modified Rankin Scale scores were 1.0 ± 0.9, 0.85 ± 0.63, and 0.37 ± 0.53 for discharge, and 3- and 6-month follow-up, respectively. A total of 6 patients died despite receiving aggressive treatment. No cases of relapse occurred after 3 to 6 months of follow-up. CONCLUSION: Thrombectomy combined with thrombolysis is a safe and valid treatment modality to use in severe CVST cases or in intractable patients that have shown no adequate response to antithrombotic drugs.