Synthesis and Antifungal Properties of 1,2,4-Triazole Schiff Base Agents Based on a 3D-QSAR Model

Based on our previous research, a 3D-QSAR model (q2=0.51, ONC=5, r2=0.982, F=271.887, SEE=0.052) was established to predict the inhibitory effects of triazole Schiff base compounds on Fusarium graminearum, and its predictive ability was also confirmed through the statistical parameters. According to the results of the model design, 30 compounds with superior bioactivity compared to the template molecule 4 were obtained. Seven of these compounds (DES2-6, DES9-10) with improved biological activity and readily available raw materials were successfully synthesized. Their structures were confirmed through HRMS, NMR, and single crystal X-ray diffraction analysis (DES-5). The bioactivity of the final products was investigated through an in vitro antifungal assay. There was little difference in the EC50 values between the experimental and predicted values of the model, demonstrating the reliability of the model. Especially, DES-3 (EC50=9.915 mg/L) and DES-5 (EC50=9.384 mg/L) exhibited better inhibitory effects on Fusarium graminearum compared to the standard drug (SD) triadimenol (EC50=10.820 mg/L). These compounds could serve as potential new fungicides for future research. The interaction between the final products and isocitrate lyase (ICL) was investigated through molecular docking. Compounds with R groups that have a higher electron-donating capacity were found to be biologically active.

The Alzheimer's Knowledge Base: A Knowledge Graph for Alzheimer Disease Research

BACKGROUND

As global populations age and become susceptible to neurodegenerative illnesses, new therapies for Alzheimer disease (AD) are urgently needed. Existing data resources for drug discovery and repurposing fail to capture relationships central to the disease's etiology and response to drugs.

OBJECTIVE

We designed the Alzheimer's Knowledge Base (AlzKB) to alleviate this need by providing a comprehensive knowledge representation of AD etiology and candidate therapeutics.

METHODS

We designed the AlzKB as a large, heterogeneous graph knowledge base assembled using 22 diverse external data sources describing biological and pharmaceutical entities at different levels of organization (eg, chemicals, genes, anatomy, and diseases). AlzKB uses a Web Ontology Language 2 ontology to enforce semantic consistency and allow for ontological inference. We provide a public version of AlzKB and allow users to run and modify local versions of the knowledge base.

RESULTS

AlzKB is freely available on the web and currently contains 118,902 entities with 1,309,527 relationships between those entities. To demonstrate its value, we used graph data science and machine learning to (1) propose new therapeutic targets based on similarities of AD to Parkinson disease and (2) repurpose existing drugs that may treat AD. For each use case, AlzKB recovers known therapeutic associations while proposing biologically plausible new ones.

CONCLUSIONS

AlzKB is a new, publicly available knowledge resource that enables researchers to discover complex translational associations for AD drug discovery. Through 2 use cases, we show that it is a valuable tool for proposing novel therapeutic hypotheses based on public biomedical knowledge.

Deep Learning Sequence Models for Transcriptional Regulation

Deciphering the regulatory code of gene expression and interpreting the transcriptional effects of genome variation are critical challenges in human genetics. Modern experimental technologies have resulted in an abundance of data, enabling the development of sequence-based deep learning models that link patterns embedded in DNA to the biochemical and regulatory properties contributing to transcriptional regulation, including modeling epigenetic marks, 3D genome organization, and gene expression, with tissue and cell-type specificity. Such methods can predict the functional consequences of any noncoding variant in the human genome, even rare or never-before-observed variants, and systematically characterize their consequences beyond what is tractable from experiments or quantitative genetics studies alone. Recently, the development and application of interpretability approaches have led to the identification of key sequence patterns contributing to the predicted tasks, providing insights into the underlying biological mechanisms learned and revealing opportunities for improvement in future models.

[A survey on the current situation of serum vitamin A and vitamin D levels among children aged 2-<7 years of 20 cities in China]

Objective: To investigate serum vitamin A and vitamin D status in children aged 2-<7 years in 20 cities in China. Methods: A cross-sectional study was conducted. A total of 2 924 healthy children aged 2-<7 years were recruited from September 2018 to September 2019 from 20 cities in China, categorized by age groups of 2-<3 years, 3-<5 years, and 5-<7 years. The demographic and economic characteristics and health-related information of the enrolled children were investigated. Body weight and height were measured by professional staff members. The serum vitamin A and vitamin D levels were detected by high-performance liquid chromatography-tandem mass spectrometry. Chi-square test and Logistic regression were applied to analyze the association between vitamin A and vitamin D deficiency and insufficiency as well as their underlying impact factors. Results: The age of the 2 924 enrolled children was 4.33 (3.42, 5.17) years. There were 1 726 males (59.03%) and 1 198 females (40.97%). The prevalences of vitamin A and vitamin D deficiency in enrolled children were 2.19% (64/2 924) and 3.52% (103/2 924), respectively, and the insufficiency rates were 29.27% (856/2 924) and 22.20% (649/2 924), respectively. Children with both vitamin A and vitamin D deficiencies or insufficiencies were found in 10.50% (307/2 924) of cases. Both vitamin A (χ2=7.91 and 8.06, both P=0.005) and vitamin D (χ2=71.35 and 115.10, both P<0.001) insufficiency rates were higher in children aged 3-<5 and 5-<7 years than those in children aged 2-<3 years. Vitamin A and vitamin D supplementation in the last 3 months was a protective factor for vitamin A and D deficiency and insufficiency, respectively (OR=0.68 and 0.22, 95%CI 0.49-0.95 and 0.13-0.40, both P<0.05). The rates of vitamin A and D insufficiency was higher in children with annual household incomes <60 000 RMB than in those with annual household incomes ≥60 000 RMB (χ2=34.11 and 10.43, both P<0.01). Northwest and Southwest had the highest rates of vitamin A and vitamin D insufficiency in children aged 2-<7 yeas, respectively (χ2=93.22 and 202.54, both P<0.001). Conclusions: Among 20 cities in China, children aged 2-<7 years experience high rates of vitamin A and vitamin D insufficiency, which are affected by age, family economic level, vitamin A and vitamin D supplementation, and regional economic level. The current results suggest that high level of attention should be paid to vitamin A and vitamin D nutritional status of preschool children.

Staphylococcus aureus lysate induces an IgE response via memory B cells in nasal polyps

BACKGROUND

Locally increased IgE levels plays a pathologic role in chronic rhinosinusitis with nasal polyps (CRSwNP).

OBJECTIVE

This study aimed to investigate whether Staphylococcus aureus could induce aberrant IgE synthesis in CRSwNP and the potential mechanisms involved.

METHODS

Total IgE, IL-4, IL-5, and IL-13 concentrations in the supernatants of the cultures stimulated with S aureus lysate were assessed by ELISA. S aureus-induced cellular responses were investigated by single-cell RNA sequencing. Flow cytometry and quantitative reverse transcription PCR were used to analyze B-cell subsets and stimulated cell ε-germline transcript expression, respectively. IgE-positive B-cell and germinal center localization were assessed by immunohistochemistry and immunofluorescence.

RESULTS

S aureus lysate induced IgE production in the supernatants of nasal polyp (NP) tissues but not in those of healthy nasal mucosa. Moreover, IgE levels increased from days 2 to 4 after stimulation, paralleling the enhanced ε-germline transcript, IL-5, and IL-13 expression. Single-cell RNA sequencing revealed that there were increased IL-5 and IL-13 in group 2 innate lymphoid cells and identified a clonal overlap between unstimulated memory B cells and S aureus-stimulated plasma cells. The enriched IgE within NPs was mainly produced by IgE-negative memory B cells. Cellular evidence indicated that the IgE memory response to S aureus might also exist in the peripheral blood of CRSwNP patients. The S aureus-induced IgE memory response was associated with elevated IgE levels in NPs, asthma, and postoperative CRSwNP recurrence.

CONCLUSIONS

S aureus induced an IgE response via IgE-negative memory B cells in CRSwNP patients, possibly contributing to CRSwNP development.

An early warning model for predicting major adverse kidney events within 30 days in sepsis patients

Background

In sepsis patients, kidney damage is among the most dangerous complications, with a high mortality rate. In addition, major adverse kidney events within 30 days (MAKE30) served as a comprehensive and unbiased clinical outcome measure for sepsis patients due to the recent shift toward targeting patient-centered renal outcomes in clinical research. However, the underlying predictive model for the prediction of MAKE30 in sepsis patients has not been reported in any study.

Methods

A cohort of 2,849 sepsis patients from the Medical Information Mart for Intensive Care (MIMIC)-IV database was selected and subsequently allocated into a training set (n = 2,137, 75%) and a validation set (n = 712, 25%) through randomization. In addition, 142 sepsis patients from the Xi'An No. 3 Hospital as an external validation group. Univariate and multivariate logistic regression analyses were conducted to ascertain the independent predictors of MAKE30. Subsequently, a nomogram was developed utilizing these predictors, with an area under curve (AUC) above 0.6. The performance of nomogram was assessed through calibration curve, receiver operating characteristics (ROC) curve, and decision curve analysis (DCA). The secondary outcome was 30-day mortality, persistent renal dysfunction (PRD), and new renal replacement therapy (RRT). MAKE30 were a composite of death, PRD, new RRT.

Results

The construction of the nomogram was based on several independent predictors (AUC above 0.6), including age, respiratory rate (RR), PaO2, lactate, and blood urea nitrogen (BUN). The predictive model demonstrated satisfactory discrimination for MAKE30, with an AUC of 0.740, 0.753, and 0.821 in the training, internal validation, and external validation cohorts, respectively. Furthermore, the simple prediction model exhibited superior predictive value compared to the SOFA model in both the training (AUC = 0.710) and validation (AUC = 0.692) cohorts. The nomogram demonstrated satisfactory calibration and clinical utility as evidenced by the calibration curve and DCA. Additionally, the predictive model exhibited excellent accuracy in forecasting 30-day mortality (AUC = 0.737), PRD (AUC = 0.639), and new RRT (AUC = 0.846) within the training dataset. Additionally, the model displayed predictive power for 30-day mortality (AUC = 0.765), PRD (AUC = 0.667), and new RRT (AUC = 0.783) in the validation set.

Conclusion

The proposed nomogram holds the potential to estimate the risk of MAKE30 promptly and efficiently in sepsis patients within the initial 24 h of admission, thereby equipping healthcare professionals with valuable insights to facilitate personalized interventions.

High-intensity interval training versus moderate-intensity continuous training for localized prostate cancer under active surveillance: a systematic review and network meta-analysis

BACKGROUND

High-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) have been increasingly adopted for localized prostate cancer (PCa) under active surveillance (AS). However, it is unclear which training modality is the most favorable in terms of cardiorespiratory fitness and biochemical progression.

METHODS

We searched PubMed, Cochrane and Embase for relevant RCTs. PRISMA guideline was adopted to ensure optimal conduct of this study. Serum prostate specific antigen (PSA) and peak VO2 were selected as primary outcomes and PSA doubling time (PSADT) and testosterone were selected as secondary outcomes. Only articles written in English were included. Cochrane risk-of-bias tool was used for risk of bias evaluation.

RESULTS

A total of 501 studies were selected. Six RCTs with 222 patients were included for data extraction and analysis. High-intensity interval training (HIIT) group demonstrated significantly lower PSA compared with usual care (UC) (MD = -1.4; 95%CI = -2.77 to -0.03) and moderate-intensity continuous training (MICT) group (MD = -1.67; 95%CI = -3.30 to -0.05). Both HIIT and MICT showed significantly improved peak VO2 compared with UC. No significant difference was observed in PSADT and testosterone among different training modalities and UC. Regarding peak VO2, MICT had the highest surface under cumulative ranking curve (SUCRA) scores (98.1%). For serum PSA, HIIT had the highest probability (97.8%) to be the training with the highest efficacy. The potential source of bias mainly came from poorly performed allocation concealment and blinding strategies.

CONCLUSIONS

The present study indicated that HIIT and MICT showed considerable cardiorespiratory benefits for localized PCa. HIIT was preferred over MICT in biochemical progression control in terms of decreasing serum PSA levels. However, MICT was favored over HIIT regarding cardiorespiratory benefits. The findings of this study may facilitate future lifestyle intervention, particularly in the form of physical training, for individuals diagnosed with localized PCa under AS.

Intravesical chemotherapy synergize with an immune adjuvant by a thermo-sensitive hydrogel system for bladder cancer

Surgical resection remains the prefer option for bladder cancer treatment. However, the effectiveness of surgery is usually limited for the high recurrence rate and poor prognosis. Consequently, intravesical chemotherapy synergize with immunotherapy in situ is an attractive way to improve therapeutic effect. Herein, a combined strategy based on thermo-sensitive PLEL hydrogel drug delivery system was developed. GEM loaded PLEL hydrogel was intravesical instilled to kill tumor cells directly, then PLEL hydrogel incorporated with CpG was injected into both groins subcutaneously to promote immune responses synergize with GEM. The results demonstrated that drug loaded PLEL hydrogel had a sol-gel phase transition behavior in response to physiological temperature and presented sustained drug release, and the PLEL-assisted combination therapy could have better tumor suppression effect and stronger immunostimulating effect in vivo. Hence, this combined treatment with PLEL hydrogel system has great potential and suggests a clinically-relevant and valuable option for bladder cancer.

[Comparison of BCR::ABL (P210) mRNA levels detected by dPCR and qPCR methods in patients with chronic myeloid leukemia]

Objective: To compare digital polymerase chain reaction (dPCR) and real-time quantitative PCR (qPCR) measurements of BCR::ABL (P210) mRNA expression in patients with chronic myeloid leukemia (CML) . Methods: In this non-interventional, cross-sectional study, BCR::ABL (P210) mRNA was simultaneously measured by dPCR and qPCR in peripheral blood samples collected from patients with CML who underwent tyrosine kinase inhibitor therapy and who achieved at least a complete cytogenetic response from September 2021 to February 2023 at Peking University People's Hospital. The difference, correlation, and agreement between the two methods were evaluated using the Wilcoxon signed-rank test, Spearman's correlation, and Bland-Altman analysis, respectively. Results: In total, 459 data pairs for BCR::ABL mRNA expression measured by dPCR and qPCR from 356 patients with CML were analyzed. There was a significant difference in BCR::ABL mRNA expression between the two methods (P<0.001). When analyzed by the depth of the molecular response (MR), a significant difference only existed for patients with ≥MR4.5 (P<0.001). No significant difference was observed for those who did not achieve a major MR (no MMR; P=0.922) or for those who achieved a major MR (MMR; P=0.723) or MR4 (P=0.099). There was a moderate correlation between the BCR::ABL mRNA expression between the two methods (r=0.761, P<0.001). However, the correlation gradually weakened or disappeared as the depth of the MR increased (no MMR: r=0.929, P<0.001; MMR: r=0.815, P<0.001; MR4: r=0.408, P<0.001; MR4.5: r=0.176, P=0.176). In addition, the agreement in BCR::ABL mRNA expression between the two methods in those with MR4.5 was weaker than other groups (no MMR: ▉= 0.042, P=0.846; MMR:▉=0.054, P=0.229; MR4:▉=-0.020, P=0.399; MR4.5:▉=-0.219, P<0.001) . Conclusions: dPCR is more accurate than qPCR for measuring BCR::ABL (P210) mRNA expression in patients with CML who achieve a stable deep MR.

[Evaluation of the application value of seven tumor-associated autoantibodies in non-small cell lung cancer based on machine learning algorithms]

Objective: Based on the diagnostic model established and validated by the machine learning algorithm, to investigate the value of seven tumor-associated autoantibodies (TAABs), namely anti-p53, PGP9.5, SOX2, GAGE7, GBU4-5, MAGEA1 and CAGE antibodies in the diagnosis of non-small cell lung cancer (NSCLC) and to differentiate between NSCLC and benign lung nodules. Methods: This was a retrospective study of clinical cases. Model building queue: a total of 227 primary patients who underwent radical lung cancer surgery in the Department of Thoracic Surgery, Shengjing Hospital of China Medical University, from November 2018 to June 2021 were collected as the NSCLC group, and 120 cases of benign lung nodules, 122 cases of pneumonia and 120 healthy individuals were selected as the control groups. External validation queue: a total of 100 primary patients who underwent radical lung cancer surgery in the Department of Thoracic Surgery, Shengjing Hospital of China Medical University, from May 2022 to December 2022 were collected as the NSCLC group, and 36 cases of benign lung nodules, 32 cases of pneumonia and 44 healthy individuals were selected as the control groups. In addition, NSCLC was divided into early (stage 0-ⅠB) and mid-to-late (stage ⅡA-ⅢB) subgroups. The levels of 7-TAABs were detected by enzyme immunoassay, and serum concentrations of CEA and CYFRA21-1 were detected by electrochemiluminescence. Four machine learning algorithms, XGBoost, Lasso logistic regression, Naïve Bayes, and Support Vector Machine are used to establish classification models. And the best performance model was chosen based on evaluation metrics and a multi-indicator combination model was established. In addition, an online risk evaluation tool was generated to assist clinical applications. Results: Except for p53, the levels of rest six TAABs, CEA and CYFRA21-1 were significantly higher in the NSCLC group (P<0.05). Serum levels of anti-SOX2 [1.50 (0.60, 10.85) U/ml vs. 0.8 (0.20, 2.10) U/ml, Z=2.630, P<0.05] and MAGEA1 antibodies [0.20 (0.10, 0.43) U/ml vs. 0.10 (0.10, 0.20) U/ml, Z=2.289, P<0.05], CEA [3.13 (2.12, 5.64) ng/ml vs. 2.11 (1.25, 3.09) ng/ml, Z=3.970, P<0.05] and CYFRA21-1 [4.31(2.37, 7.14) ng/ml vs. 2.53(1.92, 3.48) ng/ml, Z=3.959, P<0.05] were significantly higher in patients with mid-to late-stage NSCLC than in early stages. XGBoost model was used to establish a multi-indicator combined detection model (after removing p53). 6-TAABs combined with CYFRA21-1 was the best combination model for the diagnosis of NSCLC and early NSCLC. The optimal diagnostic thresholds were 0.410, 0.701 and 0.744, and the AUC was 0.828, 0.757 and 0.741, respectively (NSCLC vs. control, NSCLC vs. benign lung nodules, early NSCLC vs. benign lung nodules) in model building queue, and the AUC was 0.760, 0.710 and 0.660, respectively (NSCLC vs. control, NSCLC vs. benign lung nodules, early NSCLC vs. benign lung nodules) in external validation queue. Conclusion: In the diagnosis of NSCLC, 6-TAABs is superior to that of traditional tumor markers CEA and CYFRA21-1, and can compensate for the shortcomings of traditional tumor markers. For the differential diagnosis of NSCLC and benign lung nodule, "6-TAABs+CYFRA21-1" is the most cost-effective combination, and plays an important role in prevention and screening for early lung cancer.

Engineering of antimicrobial peptide fibrils with feedback degradation of bacterial-secreted enzymes

Proteins and peptides can assemble into functional amyloid fibrils with distinct architectures. These amyloid fibrils can fulfil various biological functions in living organisms, and then be degraded. By incorporating an amyloidogenic segment and enzyme-cleavage segment together, we designed a peptide (enzyme-cleavage amyloid peptides (EAP))-based functional fibril which could be degraded specifically by gelatinase. To gain molecular insights into the assembly and degradation of EAP fibrils, we determined the atomic structure of the EAP fibril using cryo-electron microscopy. The amyloidogenic segment of EAP adopted a β-strand conformation and mediated EAP-fibril formation mainly via steric zipper-like interactions. The enzyme-cleavage segment was partially involved in self-assembly, but also exhibited high flexibility in the fibril structure, with accessibility to gelatinase binding and degradation. Moreover, we applied the EAP fibril as a tunable scaffold for developing degradable self-assembled antimicrobial fibrils (SANs) by integrating melittin and EAP together. SANs exhibited superior activity for killing bacteria, and significantly improved the stability and biocompatibility of melittin. SANs were eliminated automatically by the gelatinase secreted from targeted bacteria. Our work provides a new strategy for rational design of functional fibrils with a feedback regulatory loop for optimizing the biocompatibility and biosafety of designed fibrils. Our work may aid further developments of "smart" peptide-based biomaterials for biomedical applications.

Performance of Adaptive Deep Learning Models for Dose Predictions on High-Quality Cone-Beam Computed Tomography Images

PURPOSE/OBJECTIVE(S)

Online plan generation remains a patient-specific and time-consuming process that can place a significant burden on clinics strained with staffing shortages. As previous research show that dose-volume histogram (DVH) prediction plays a crucial role in automatic treatment planning, the objective of this study is to assess the capability of adaptive deep learning models in predicting dose information in volumetric modulation radiotherapy plans using the high-quality CBCT images and contour information of organs-at-risk (OARs).

MATERIALS/METHODS

The relationship between dose-volume histograms (DVHs) in radiotherapy plans and the geometric information of organs-at-risk (OAR) and planning target volume (PTV) has been well established. To evaluate the performance of the current state-of-the-art convolutional neural network (CNN) models including VIT3D and Unet3D, and intuitive machine learning methods (i.e., SVM and MLP), we implemented those models for dose prediction and conducted a comprehensive analysis with treatment plans created from images acquired from patients who consented to participate an IRB-approved imaging study designed to evaluate the imaging performance of the system. In total, 20 plans created by certified medical dosimetrists were employed in this study, with 15 used for training the machine-learning models and the remaining 5 used for performance testing. Two evaluation metrics were used: 1) root mean square error (RMSE) of the predicted dose and true dose and 2) time spent on dose prediction.

RESULTS

The results of the analysis showed that the ViT-3D (Transformer) model had the lowest RMSE of 3.682 ±0.010, followed by the Unet-3D (CNN) model with an RMSE of. 3.973 ±0.021 The MLP model had an RMSE of 8.007 ±0.019 while the SVM model had the highest RMSE of 9.156 ±0.032. For a fair comparison, we use 4-fold cross validation (each has 15 training plans and 5 testing plans), and report the mean value with standard deviation. All models are optimized with Adam optimizer of a learning rate 0.01, and the training process is stopped after 100 epochs. These findings indicate that the ViT-3D (Transformer) model performed the best in terms of predicting the dose information in volumetric modulation radiotherapy plans based on the CBCT images and contour information of OARs. For tested plan which contains 81 CT images (512 × 512 resolution), the inference time to predict dose information with a general CPU machine (6-Core Intel Core i7) is about 1.5 minutes. With GPU resources, such as NVIDIA A100, the inference process can be finished within seconds.

CONCLUSION

The study demonstrated that current state-of-the-art machine-learning models can achieve promising accuracy in dose prediction using high-quality CBCT images. A well-trained machine-learning model could offer clinicians a quick and reliable prediction of the true dose to patients in the case of significant anatomical changes or provide patient-specific optimization objectives if replanning is warranted.

Accuracy of Electron Density and Planning Dosimetry in a Novel High-Quality CBCT Imaging System

PURPOSE/OBJECTIVE(S)

A high-quality Cone-Beam Computed Tomography (CBCT) imaging system has been FDA approved for imaging guidance and dose calculation in radiotherapy. This study aims to evaluate the accuracy of the relative electron density in CBCT images acquired in this CBCT imaging system in a phantom study and its dosimetric impact on treatment planning in a patient study.

MATERIALS/METHODS

Astoichiometric CT calibration was performed with a CIRS phantom (SunNuclear, Model 062M) to generate the HU-electron density curve for two tube voltages, 125kVp and 140 kVp, respectively. The phantom has a longitudinal length of 26.5 cm and is equipped with interchangeable inserts of various compositions, supplied by the vendor. Measurements were taken with solid water plates added to both ends of the phantom to allow adequate scattering and repeated for various clinical protocols with different combinations of tube voltages and exposures. The accuracy of the relative electron density of the CBCT imaging system was verified by comparing the calculated electron density from the Hounsfield Units (HU) measurements obtained from a Gammex phantom to the relative electron densities provided in vendor's specifications. To benchmark the relative electron density of the CBCT imaging system against a standard helical CT simulator, ten clinical plans that were created on CT simulation images were copied and recalculated on the CBCT images acquired immediately after the CT simulation, the latter of which was a standard procedure in current radiotherapy care for all patients who had given their consent to participate in the IRB-approved imaging study. The dose grids used in these calculations were 2.5mm x 2.5mm x 3mm. The Gamma passing rate was calculated using a standard 3mm/3% criterion with a 10% threshold.

RESULTS

Ourresults showed the difference between the averaged CBCT calibration curves acquired at tube voltages of 125 kVP and 140 kVp was less than 2%. The mean discrepancy of the relative electron densities from vendor's specification was 0.0045 with a range between -0.02 and 0.04. Relative electron densities in all inserts were within 2% from the vendor's specifications except the cortical bone insert. Gamma passing rate was between 96.02% and 98.49% with mean value of 97.4% and a standard deviation of 0.95%. We consider this reflects the fact that the CT simulation and CBCT imaging were performed in separated rooms, which resulted in slight anatomical deformation that could negatively impact the Gamma passing rate.

CONCLUSION

The CBCT imaging system provides sufficient accuracy of electron density for dose calculation, and the dose distribution calculated on the CBCT images is clinically equivalent to those calculated on helical CT images. The enhanced imaging quality of CBCT could further extend the role of imaging guidance to planning for adaptive radiotherapy, potentially reducing the need for re-simulation and interruptions in the radiotherapy course.

An In Silico study of a One-Day One-Machine Workflow for Definitive Radiotherapy Cases on a Novel Simulation and Treatment Platform

PURPOSE/OBJECTIVE(S)

The workflow in Radiotherapy (RT) has largely unchanged for the past three decades, despite increasing evidence suggesting that delayed access to RT, including the wait time between consultation, simulation, and treatment appointments, can negatively impact clinical outcomes. In this pilot study, we present preliminary results of an in silico study that demonstrate the feasibility of a novel RT platform, which integrates simulation into the treatment process and enables patients to receive immediate RT after their initial RT consultation.

MATERIALS/METHODS

A prospective clinical study has been approved to assess the capabilities of a novel RT platform with a high quality CBCT system for imaging guidance as well as planning. This new platform enables a novel clinical workflow that allows clinicians to review contours and plans created on diagnostic CT images prior to the initial RT consultation and allow them to approve new plans adapted on the actual simulation dataset acquired on the first treatment fraction. Four patients receiving standard of care RT (three abdomen and one thorax) consented for this study and underwent additional experimental CBCT simulation on the new platform in addition to their standard CT simulation. The CBCT simulation was taken in two setups: with a specific mold on a flat couch and without a mold on a curved couch. To demonstrate the equivalence of the new workflow to the current standard of care, the plan created on the most recent diagnostic CT images was compared to the plans adapted on the experimental simulation images and the standard CT simulation images, using a knowledge-based model. Contours were propagated from approved datasets to the new datasets through deformable image registration.

RESULTS

All experimental simulations were completed between 14 and 21 minutes with the assistance of two therapists. The contouring, editing, and replanning process took less than one hour in all cases, in line with our experience and peer-reviewed literature. Despite notable anatomical changes observed, the dose-volume histograms (DVH) were consistent, as shown in Table 1.

CONCLUSION

The novel workflow presented herein was feasible and demonstrates that the integration of simulation with image-guided RT on one single platform may unlock the potential of accelerating the RT workflow and reducing the wait time for treatment from weeks to hours.

Proton Online Adaptation Using Novel Cone-Beam Computed Tomography System

PURPOSE/OBJECTIVE(S)

Cone beam computed tomography (CBCT) has been used in clinic frequently to provide quick, online, and handy three-dimensional images. However, due to its significant artifacts and inaccurate Hounsfield values (HU), CBCT based online proton adaptation is infeasible. Recently, a novel in-room imaging solution was developed to allow larger images, better contrast and faster CBCT imaging acquisition. Our work demonstrated for the first time the feasibility of using this novel CBCT images for direct intensity modulated proton planning.

MATERIALS/METHODS

Three patients and three CIRS phantoms were scanned using novel imaging technique (CBCTp) for this work. CT curves were acquired by scanning a CIRS electron density phantom. Stopping power ratio was computed using the stoichiometric method. Proton plans were made on treatment simulation CT and further evaluated on CBCTp to compare the differences.

RESULTS

The table below shows three patients and three phantoms plan comparisons. Multiple sites and dose levels were studied. The planning target volume (PTV) coverage (D95%) and mean dose difference between simulation CT and CBCTp are 0.8% and 0.3%, correspondingly. Dosimetrically, phantom and patient plans are almost identical between two imaging techniques. Lung patient plan show the largest variation due to patient tumor change and the quality of breathing.

CONCLUSION

The novel and high quality of CBCT is feasible for direct proton planning with accurate CT calibration. It provides a reliable alternative solution for proton online adaptive therapy.

[Association between different obesity measurement indexes and serum C-reactive protein in adult women]

Objective: To explore the association of different obesity measurement indexes on serum C-reactive protein (CRP) in Chinese adult women. Methods: The data were obtained from baseline and follow-up surveys of the urban Breast Cancer Screening Program in Shuangliu District, Chengdu. A total of 441 adult women were included in the study. A questionnaire survey, physical examination, and laboratory testing were conducted on the subjects. Multivariate logistic regression model, two-level mixed effects logistic regression model, and restricted cubic spline method were used to investigate the linear and nonlinear correlation between different obesity measurement indexes and serum CRP in adult women. Results: For every 1 unit increase in BMI, waist circumference (WC), and adiposity, the risk of elevated serum CRP or exacerbation of chronic low-grade inflammation in adult women increased by 16.5%, 5.0%, and 11.1% (P<0.05), respectively. Both BMI and adiposity were nonlinear correlated with serum CRP. Using BMI=24.0 kg/m2 as the reference point, serum CRP level increased with the increase of BMI when BMI >24.0 kg/m2. Using adiposity=30% as the reference point, serum CRP level increased with the increase of adiposity when adiposity >30%. Conclusions: Overall, obesity reflected by BMI had the strongest association with serum CRP in adult women, followed by body fat content reflected by adiposity, and central obesity reflected by WC had the weakest association with CRP. Adult women with BMI >24.0 kg/m2 or adiposity >30% are at high risk for obesity-related inflammatory manifestations.

Knowledge graph aids comprehensive explanation of drug and chemical toxicity

In computational toxicology, prediction of complex endpoints has always been challenging, as they often involve multiple distinct mechanisms. State-of-the-art models are either limited by low accuracy, or lack of interpretability due to their black-box nature. Here, we introduce AIDTox, an interpretable deep learning model which incorporates curated knowledge of chemical-gene connections, gene-pathway annotations, and pathway hierarchy. AIDTox accurately predicts cytotoxicity outcomes in HepG2 and HEK293 cells. It also provides comprehensive explanations of cytotoxicity covering multiple aspects of drug activity, including target interaction, metabolism, and elimination. In summary, AIDTox provides a computational framework for unveiling cellular mechanisms for complex toxicity endpoints.

[Identification and 3D architecture analysis of the LIPC gene mutation in a pedigree with familial hypercholesterolemia-like phenotype]

Objective: To identify and analyze 3D architecture of the mutational sites of susceptible genes in a pedigree with familial hypercholesterolemia-like phenotype (FHLP). Methods: This is a case series study. A pedigree with suspected familial hypercholesterolemia was surveyed. The proband admitted in Beijing Anzhen Hospital in April 2019. Whole-exome sequencing was performed to determine the mutational sites of susceptible genes in the proband. Polymerase chain reaction (PCR) sequencing was used to verify the pathogenic variant on proband's relatives. The structural and functional changes of the proteins were analyzed and predicted by Discovery Studio 4.0 and PyMol 2.0. Results: The patients in the pedigree showed abnormal lipid profiles, especially elevated levels of total cholesterol(TC). The genetic screening detected the c.1330C>T SNP in the exon 8 of lipase C (LIPC) gene, this mutation leads to an amino acid substitution from arginine to cysteine at position 444 (Arg444Cys), in the proband and proband's father and brother. In this family, members with this mutation exhibited elevated TC, whereas lipid profile was normal from the proband's mother without this mutation. This finding indicated that LIPC: c.1330C>T mutation might be the mutational sites of susceptible genes. The analysis showed that Arg444Cys predominantly affected the ligand-binding property of the protein, but had a limited impact on catalytic function. Conclusion: LIPC: c.1330C>T is a new mutational site of susceptible genes in this FHLP pedigree.

Molecular characterization and protective efficacy of vacuolar protein sorting 29 from Eimeria tenella

Introduction

Vacuolar protein sorting 29 (VPS29) is a core component of the retromer-retriever complex and is essential for recycling numerous cell-surface cargoes from endosomes. However, there are no reports yet on VPS29 of Eimeria spp.

Methods

Here, we cloned and prokaryotically expressed a partial sequence of Eimeria tenella VPS29 (EtVPS29) with RT-PCR and engineered strain of Escherichia coli respectively. The localization of the VPS29 protein in E. tenella sporozoites was investigated with immunofluorescence (IFA) and overexpression assays. And its protective efficacy against E. tenella infection was investigated in chickens with the animal protection test.

Results

An EtVPS29 gene fragment with an ORF reading frame of 549 bp was cloned. The band size of the expressed recombinant protein, rEtVPS29, was approximately 39 kDa and was recognized by the chicken anti-E. tenella positive serum. EtVPS29 protein was observed widely distributing in the cytoplasm of E. tenella sporozoites in the IFA and overexpression assays. rEtVPS29 significantly increased average body weight gain and decreased mean lesion score and oocyst output in chickens. The relative weight gain rate in the rEtVPS29-immunized group was 62.9%, which was significantly higher than that in the unimmunized and challenged group (P < 0.05). The percentage of reduced oocyst output in the rEtVPS29 immunized group was 32.2%. The anticoccidial index of the rEtVPS29-immunized group was 144.2. Serum ELISA also showed that rEtVPS29 immunization induced high levels of specific antibodies in chickens.

Discussion

These results suggest that rEtVPS29 can induce a specific immune response and is a potential candidate for the development of novel vaccines against E. tenella infections in chickens.

Methionine restriction promotes cGAS activation and chromatin untethering through demethylation to enhance antitumor immunity

Cyclic GMP-AMP synthase (cGAS) is the major sensor for cytosolic DNA and activates type I interferon signaling and plays an essential role in antitumor immunity. However, it remains unclear whether the cGAS-mediated antitumor activity is affected by nutrient status. Here, our study reports that methionine deprivation enhances cGAS activity by blocking its methylation, which is catalyzed by methyltransferase SUV39H1. We further show that methylation enhances the chromatin sequestration of cGAS in a UHRF1-dependent manner. Blocking cGAS methylation enhances cGAS-mediated antitumor immunity and suppresses colorectal tumorigenesis. Clinically, cGAS methylation in human cancers correlates with poor prognosis. Thus, our results indicate that nutrient stress promotes cGAS activation via reversible methylation, and suggest a potential therapeutic strategy for targeting cGAS methylation in cancer treatment.

[Comparison of diagnostic performance of Clear Cell Likelihood Score v1.0 and v2.0 for clear renal cell carcinoma]

OBJECTIVE

To compare the performance of Clear Cell Likelihood Score (ccLS) v1.0 and v2.0 in diagnosing clear cell renal cell carcinoma (ccRCC) from small renal masses (SRM).

METHODS

We retrospectively analyzed the clinical data and MR images of patients with pathologically confirmed solid SRM from the First Medical Center of the Chinese PLA General Hospital between January 1, 2018, and December 31, 2021, and from Beijing Friendship Hospital of Capital Medical University and Peking University First Hospital between January 1, 2019 and May 17, 2021. Six abdominal radiologists were trained for use of the ccLS algorithm and scored independently using ccLS v1.0 and ccLS v2.0. Random- effects logistic regression modeling was used to generate plot receiver operating characteristic curves (ROC) to evaluate the diagnostic performance of ccLS v1.0 and ccLS v2.0 for ccRCC, and the area under curve (AUC) of these two scoring systems were compared using the DeLong's test. Weighted Kappa test was used to evaluate the interobserver agreement of the ccLS score, and differences in the weighted Kappa coefficients was compared using the Gwet consistency coefficient.

RESULTS

In total, 691 patients (491 males, 200 females; mean age, 54 ± 12 years) with 700 renal masses were included in this study. The pooled accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of ccLS v1.0 for diagnosing ccRCC were 77.1%, 76.8%, 77.7%, 90.2%, and 55.7%, as compared with 80.9%, 79.3%, 85.1%, 93.4%, 60.6% with ccLS v2.0, respectively. The AUC of ccLS v2.0 was significantly higher than that of ccLS v1.0 for diagnosis of ccRCC (0.897 vs 0.859; P < 0.01). The interobserver agreement did not differ significantly between ccLS v1.0 and ccLS v2.0 (0.56 vs 0.60; P > 0.05).

CONCLUSION

ccLS v2.0 has better performance for diagnosing ccRCC than ccLS v1.0 and can be considered for use to assist radiologists with their routine diagnostic tasks.

Toward discovering a novel family of peptides targeting neuroinflammatory states of brain microglia and astrocytes

Microglia are immune-derived cells critical to the development and healthy function of the brain and spinal cord, yet are implicated in the active pathology of many neuropsychiatric disorders. A range of functional phenotypes associated with the healthy brain or disease states has been suggested from in vivo work and were modeled in vitro as surveying, reactive, and primed sub-types of primary rat microglia and mixed microglia/astrocytes. It was hypothesized that the biomolecular profile of these cells undergoes a phenotypical change as well, and these functional phenotypes were explored for potential novel peptide binders using a custom 7 amino acid-presenting M13 phage library (SX7) to identify unique peptides that bind differentially to these respective cell types. Surveying glia were untreated, reactive were induced with a lipopolysaccharide treatment, recovery was modeled with a potent anti-inflammatory treatment dexamethasone, and priming was determined by subsequently challenging the cells with interferon gamma. Microglial function was profiled by determining the secretion of cytokines and nitric oxide, and expression of inducible nitric oxide synthase. After incubation with the SX7 phage library, populations of SX7-positive microglia and/or astrocytes were collected using fluorescence-activated cell sorting, SX7 phage was amplified in Escherichia coli culture, and phage DNA was sequenced via next-generation sequencing. Binding validation was done with synthesized peptides via in-cell westerns. Fifty-eight unique peptides were discovered, and their potential functions were assessed using a basic local alignment search tool. Peptides potentially originated from proteins ranging in function from a variety of supportive glial roles, including synapse support and pruning, to inflammatory incitement including cytokine and interleukin activation, and potential regulation in neurodegenerative and neuropsychiatric disorders.

Global Visual-Inertial Localization for Autonomous Vehicles with Pre-Built Map

Accurate, robust and drift-free global pose estimation is a fundamental problem for autonomous vehicles. In this work, we propose a global drift-free map-based localization method for estimating the global poses of autonomous vehicles that integrates visual-inertial odometry and global localization with respect to a pre-built map. In contrast to previous work on visual-inertial localization, the global pre-built map provides global information to eliminate drift and assists in obtaining the global pose. Additionally, in order to ensure the local odometry frame and the global map frame can be aligned accurately, we augment the transformation between these two frames into the state vector and use a global pose-graph optimization for online estimation. Extensive evaluations on public datasets and real-world experiments demonstrate the effectiveness of the proposed method. The proposed method can provide accurate global pose-estimation results in different scenarios. The experimental results are compared against the mainstream map-based localization method, revealing that the proposed approach is more accurate and consistent than other methods.

Antifungal Activity, Structure-Activity Relationship and Molecular Docking Studies of 1,2,4-Triazole Schiff Base Derivatives

Fourteen novel Schiff base compounds (AS-1∼AS-14) containing 5-amino-1H-1,2,4-triazole-3-carboxylic acid and substituted benzaldehyde were successfully synthesized, and their structures were verified by melting point, elemental analysis (EA) and spectroscopic techniques (Fourier Transform Infra-Red (FT-IR) and Nuclear Magnetic Resonance (NMR)). In vitro hyphal measurements were used to investigate the antifungal activities of the synthesised compounds against Wheat gibberellic, Maize rough dwarf and Glomerella cingulate. The preliminary studies indicated that all compounds had good inhibitory effect on Wheat gibberellic and Maize rough dwarf, among which the compounds of AS-1 (7.44 mg/L, 7.27 mg/L), AS-4 (6.80 mg/L, 9.57 mg/L) and AS-14 (5.33 mg/L, 6.53 mg/L) showed better antifungal activity than that of the standard drug fluconazole (7.66 mg/L, 6.72 mg/L); while inhibitory effect against Glomerella cingulate was poor, only AS-14 (5.67 mg/L) was superior to that of fluconazole (6.27 mg/L). The research of structure-activity relationship exhibited that the introduction of halogen elements on the benzene ring and electron withdrawing groups at the 2,4,5 positions on the benzene ring was beneficial to the improvement of the activity against Wheat gibberellic, while the large steric hindrance was not conducive to the improvement of the activity. Additionally, except for AS-1, AS-3 and AS-10, the other compounds had one or several ratio systems to achieve synergistic effect after recombination with pyrimethamine, among which AS-7 had significant synergistic effect and was expected to be a combinated agent with application prospects. Finally, the molecular docking results of isocitrate lyase with Wheat gibberellic displayed that the presence of hydrogen bonds enabled stable binding of compounds to receptor proteins, and the residues of ARG A: 252, ASN A: 432, CYS A: 215, SER A: 436 and SER A: 434 were the key residues for their binding. Comparing the docking binding energy and biological activity results, it was revealed that the lower the docking binding energy was, the stronger the inhibitory ability of the Wheat gibberellic, when the same position on the benzene ring was substituted.

Endotypes of chronic rhinosinusitis based on inflammatory and remodeling factors

BACKGROUND

Previous studies on the endotyping of chronic rhinosinusitis (CRS) that were based on inflammatory factors have broadened our understanding of the disease. However, the endotype of CRS combined with inflammatory and remodeling features has not yet been clearly elucidated.

OBJECTIVE

We sought to identify the endotypes of patients with CRS according to inflammatory and remodeling factors.

METHODS

Forty-eight inflammatory and remodeling factors in the nasal mucosal tissues of 128 CRS patients and 24 control subjects from northern China were analyzed by Luminex, ELISA, and ImmunoCAP. Sixteen factors were used to perform the cluster analysis. The characteristics of each cluster were analyzed using correlation analysis and validated by immunofluorescence staining.

RESULTS

Patients were classified into 5 clusters. Clusters 1 and 2 showed non-type 2 signatures with low biomarker concentrations, except for IL-19 and IL-27. Cluster 3 involved a low type 2 endotype with the highest expression of neutrophil factors, such as granulocyte colony-stimulating factor, IL-8, and myeloperoxidase, and remodeling factors, such as matrix metalloproteinases and fibronectin. Cluster 4 exhibited moderate type 2 inflammation. Cluster 5 exhibited high type 2 inflammation, which was associated with relatively higher levels of neutrophil and remodeling factors. The proportion of CRS with nasal polyps, asthma, allergies, anosmia, aspirin sensitivity, and the recurrence of CRS increased from clusters 1 to 5.

CONCLUSION

Diverse inflammatory mechanisms result in distinct CRS endotypes and remodeling profiles. The explicit differentiation and accurate description of these endotypes will guide targeted treatment decisions.

[Preliminary study on the effect of fecal microbiota transplantation on neurobehavior and gut microbiota of offspring rats exposed to arsenic]

Objective: To explore the effects of fecal microbiota transplantation (FMT) on neurobehavior and gut microbiota of arsenic-exposed offspring rats. Methods: In April 2021, Thirty-six SPF SD rats aged 8 weeks were seleted, rats were ranked by weight and divided into four groups according to randomized block design, namely control group, arsenic exposure group (As group) , arsenic+normal saline group (As+NaCl group) and As+FMT group, 6 females and 3 males in each group. Fecal microbiota fluid were provided by feces of rats in control group. Rats drank tap water containing 75 mg/L sodium arsenite for one week and then were caged together. The arsenic exposure was terminated until the pups were born. Female rats with vaginal plug were treated with fecal microbiota fluid via gavage during neurodevelopmental teratogenic window period. The volume of gavage was 1 ml/100 g with once every two days, for a total of three times. Weight alterations of offspring rats were recorded every week after weaning, and when offspring rats grew up for 6 weeks, Morris test and open field experiment was used to observe learning and memory abilities, as well as neurobehavioral performance of autonomous exploration and tension, respectively. 16S rDNA sequencing technology was used to detect microbiota diversities in fecal samples of rats in As group and As+FMT group. Results: Compared with the control group, the ratio of swimming distance and staying time in the target quadrant and the times of crossing the platform of rats in As group decreased significantly, and the motor distance, times entering central zone and the number of grid crossing of rats decreased significantly (P<0.05) . Compared with As group, the ratio of swimming distance in target quadrant, the motor distance in central zone and times entering central zone of rats in As+FMT group were evidently increased (P<0.05) . The analysis of fecal microbiota diversities showed that, at the phyla level, the relative abundance of Bacteroidetes in feces of rats in As+FMT group was higher than that in As group (68.34% vs 60.55%) , while the relative abundance of Firmicutes was lower than that in As group (28.02% vs 33.48%) . At the genus level, the relative abundance of Prevotella in As+FMT group was significantly higher than that in As group, becoming the dominant genus (42.08% vs 21.78%) . Additionally, compared with As group, a total of 22 genus were increased with 21 decreased genus in As+FMT group (P<0.05) . LEfSe analysis showed that dominant genuses in As+FMT group were Prevotella and UCG_005, and their relative abundance was significantly higher than that of As group (P<0.05) . Conclusion: FMT may alleviate the impaired learning and memory ability and anxiety like behavior of the offspring rats exposed to arsenic, and improve the disrupted gut microbiota.

Hetnet connectivity search provides rapid insights into how two biomedical entities are related

Hetnets, short for "heterogeneous networks", contain multiple node and relationship types and offer a way to encode biomedical knowledge. One such example, Hetionet connects 11 types of nodes - including genes, diseases, drugs, pathways, and anatomical structures - with over 2 million edges of 24 types. Previous work has demonstrated that supervised machine learning methods applied to such networks can identify drug repurposing opportunities. However, a training set of known relationships does not exist for many types of node pairs, even when it would be useful to examine how nodes of those types are meaningfully connected. For example, users may be curious not only how metformin is related to breast cancer, but also how the GJA1 gene might be involved in insomnia. We developed a new procedure, termed hetnet connectivity search, that proposes important paths between any two nodes without requiring a supervised gold standard. The algorithm behind connectivity search identifies types of paths that occur more frequently than would be expected by chance (based on node degree alone). We find that predictions are broadly similar to those from previously described supervised approaches for certain node type pairs. Scoring of individual paths is based on the most specific paths of a given type. Several optimizations were required to precompute significant instances of node connectivity at the scale of large knowledge graphs. We implemented the method on Hetionet and provide an online interface at https://het.io/search . We provide an open source implementation of these methods in our new Python package named hetmatpy .

Dynapenic Abdominal Obesity and Risk of Heart Disease among Middle-Aged and Older Adults: A Prospective Cohort Study

OBJECTIVES

The vicious cycle of dynapenia and abdominal obesity may have synergistic detrimental impacts on health. We aim to investigate the prospective association between dynapenic abdominal obesity and the risk of heart disease among middle-aged and older adults.

DESIGN

A prospective cohort study.

SETTING

English Longitudinal Study of Ageing, 2002-2019.

PARTICIPANTS

A total of 4734 participants aged 50 years and older were included.

MEASUREMENTS

Individuals were divided into non-dynapenia/non-abdominal obesity (ND/NAO), non-dynapenia/abdominal obesity (ND/AO), dynapenia/non-abdominal obesity (D/NAO), and dynapenia/abdominal obesity (D/AO) according to grip strength and waist circumference at baseline. The Cox proportional hazards models were used to obtain the hazard ratios (HRs) of incident heart disease associated with dynapenia and abdominal obesity after adjusting for potential confounding factors.

RESULTS

During a median follow-up of 9.5 years, 1040 cases of heart disease were recorded. Compared with ND/NAO group, the multivariable HRs were 1.05 (0.92, 1.21) for ND/AO group, 1.31 (0.96, 1.81) for D/NAO group, and 1.39 (1.03, 1.88) for D/AO group. The significant association of D/AO with incident heart disease was detected in women but not in men [HR = 1.55 (1.07, 2.24) and 1.06 (0.60, 1.88), respectively]. Among middle-aged adults, significant associations of D/NAO and D/AO with incident heart disease were observed [HR = 2.46 (1.42, 4.29) and 1.74 (1.02, 2.97), respectively].

CONCLUSION

Both D/NAO and D/AO might increase the risk of developing heart disease, highlighting the importance of dynapenia and obesity early screening for heart disease prevention.

Hetnet connectivity search provides rapid insights into how biomedical entities are related

BACKGROUND

Hetnets, short for "heterogeneous networks," contain multiple node and relationship types and offer a way to encode biomedical knowledge. One such example, Hetionet, connects 11 types of nodes-including genes, diseases, drugs, pathways, and anatomical structures-with over 2 million edges of 24 types. Previous work has demonstrated that supervised machine learning methods applied to such networks can identify drug repurposing opportunities. However, a training set of known relationships does not exist for many types of node pairs, even when it would be useful to examine how nodes of those types are meaningfully connected. For example, users may be curious about not only how metformin is related to breast cancer but also how a given gene might be involved in insomnia.

FINDINGS

We developed a new procedure, termed hetnet connectivity search, that proposes important paths between any 2 nodes without requiring a supervised gold standard. The algorithm behind connectivity search identifies types of paths that occur more frequently than would be expected by chance (based on node degree alone). Several optimizations were required to precompute significant instances of node connectivity at the scale of large knowledge graphs.

CONCLUSION

We implemented the method on Hetionet and provide an online interface at https://het.io/search. We provide an open-source implementation of these methods in our new Python package named hetmatpy.

Hyperspectral imaging with machine learning for non-destructive classification of Astragalus membranaceus var. mongholicus, Astragalus membranaceus, and similar seeds

The roots of Astragalus membranaceus var. mongholicus (AMM) and A. membranaceus (AM) are widely used in traditional Chinese medicine. Although AMM has higher yields and accounts for a larger market share, its cultivation is fraught with challenges, including mixed germplasm resources and widespread adulteration of commercial seeds. Current methods for distinguishing Astragalus seeds from similar (SM) seeds are time-consuming, laborious, and destructive. To establish a non-destructive method, AMM, AM, and SM seeds were collected from various production areas. Machine vision and hyperspectral imaging (HSI) were used to collect morphological data and spectral data of each seed batch, which was used to establish discriminant models through various algorithms. Several preprocessing methods based on hyperspectral data were compared, including multiplicative scatter correction (MSC), standard normal variable (SNV), and first derivative (FD). Then selection methods for identifying informative features in the above data were compared, including successive projections algorithm (SPA), uninformative variable elimination (UVE), and competitive adaptive reweighted sampling (CARS). The results showed that support vector machine (SVM) modeling of machine vision data could distinguish Astragalus seeds from SM with >99% accuracy, but could not satisfactorily distinguish AMM seeds from AM. The FD-UVE-SVM model based on hyperspectral data reached 100.0% accuracy in the validation set. Another 90 seeds were tested, and the recognition accuracy was 100.0%, supporting the stability of the model. In summary, HSI data can be applied to discriminate among the seeds of AMM, AM, and SM non-destructively and with high accuracy, which can drive standardization in the Astragalus production industry.

The characterization of tumor microenvironment infiltration and the construction of predictive index based on cuproptosis-related gene in primary lung adenocarcinoma

Objective

We aimed to use the cancer genome atlas and gene expression omnibus databases to explore the characterization of tumor microenvironment (TME) infiltration and construct a predictive index of prognosis and treatment effect based on cuproptosis-related genes (CRGs) in primary lung adenocarcinoma (LUAD).

Methods

We described the alterations of CRGs in 954 LUAD samples from genetic and transcriptional fields and evaluated their expression patterns from three independent datasets. We identified two distinct molecular subtypes and found that multi-layer CRG alterations were correlated with patient clinicopathological features, prognosis, and TME cell infiltrating characteristics. Then, a cuproptosis scoring system (CSS) for predicting the prognosis was constructed, and its predictive capability in LUAD patients was validated.

Results

Two molecular subtypes of cuproptosis (Copper Genes cluster A and cluster B) in LUAD were identified. Copper Genes cluster B had better survival than those with Copper Genes cluster A (p <0.01). Besides, we found that the infiltration of activated CD4⁺ T cells, natural killer T cells, and neutrophils was stronger in cluster A than in cluster B. Then, we constructed a highly accurate CSS to predict the prognosis, targeted therapy effect, and immune response. Compared with the low-CSS subgroup, the mutations of the TP53, MUC16, and TTN genes were more common in the high-CSS subgroup, while the mutation of TP53, TTN, and CSMD3 genes were more common in the low-CSS subgroup than in high-CSS subgroup. The low-score CSS group had an inferior survival than high-score CSS group (p <0.01). In addition, CSS presented good ability to predict the immune response (area under curve [AUC], 0.726). Moreover, AZD5363 and AZD8186 were the inhibitors of AKT and PI3K, respectively, and had lower IC50 and AUC in the low-score CSS group than it in the high-score CSS group.

Conclusions

CRGs are associated with the development, TME, and prognosis of LUAD. Besides, a scoring system based on CRGs can predict the efficacy of targeted drugs and immune response. These findings may improve our understanding of CRGs in LUAD and pave a new path for the assessment of prognosis and the development of more effective targeted therapy and immunotherapy strategies.

Extracellular vesicles derived from mesenchymal stem cells confer protection against intervertebral disc degeneration through a microRNA-217-dependent mechanism

OBJECTIVE

Extracellular vesicles released by mesenchymal stem cells (MSC-EVs) can be applied to alleviate intervertebral disc degeneration (IVDD) by curbing apoptosis of nucleus pulposus cells (NPCs). The current study aims to evaluate the effect of MSC-EVs on NPC apoptosis and IVDD and the related regulatory mechanisms involving microRNA (miR)-217.

METHOD

Expression of miR-217 was examined in tumor necrosis factor-α (TNF-α)-induced NPCs and MSC-EVs, followed by identification in the relationship between miR-217, enhancer of zeste homolog 2 (EZH2) and forkhead box O-3 (FOXO3). After isolation of EVs from MSCs and subsequent co-culture with NPCs, we assessed effects of miR-217 on NPC viability, autophagy, senescence and apoptosis along with extracellular matrix (ECM) degradation. Further in vivo experiments were conducted in rat models of IVDD to substantiate the effect of miR-217 on IVDD.

RESULTS

Poor miR-217 expression was found in TNF-α-induced NPCs, while high miR-217 expression was identified in MSC-EVs (P < 0.05). MSC-EVs transferred miR-217 to NPCs and increased its expression, thus attenuating NPC apoptosis and ECM degradation (elevated collagen II and aggrecan but reduced MMP13 and ADAMTS5) (P < 0.05). miR-217 targeted EZH2, and EZH2 bound to the FOXO3 promoter and consequently downregulated its expression. FOXO3 restrained NPC apoptosis and ECM degradation by stimulating cell autophagy (P < 0.05). Furthermore, in vivo experimental results confirmed the suppressive role of miR-217 shuttled by MSC-EVs in IVDD.

CONCLUSION

Overall, the delivery of miR-217 may be a novel mechanism underlying the effect of MSC-EVs on NPC apoptosis and ECM degradation following IVDD.

Knowledge-guided deep learning models of drug toxicity improve interpretation

In drug development, a major reason for attrition is the lack of understanding of cellular mechanisms governing drug toxicity. The black-box nature of conventional classification models has limited their utility in identifying toxicity pathways. Here we developed DTox (deep learning for toxicology), an interpretation framework for knowledge-guided neural networks, which can predict compound response to toxicity assays and infer toxicity pathways of individual compounds. We demonstrate that DTox can achieve the same level of predictive performance as conventional models with a significant improvement in interpretability. Using DTox, we were able to rediscover mechanisms of transcription activation by three nuclear receptors, recapitulate cellular activities induced by aromatase inhibitors and pregnane X receptor (PXR) agonists, and differentiate distinctive mechanisms leading to HepG2 cytotoxicity. Virtual screening by DTox revealed that compounds with predicted cytotoxicity are at higher risk for clinical hepatic phenotypes. In summary, DTox provides a framework for deciphering cellular mechanisms of toxicity in silico.

Automating Predictive Toxicology Using ComptoxAI

ComptoxAI is a new data infrastructure for computational and artificial intelligence research in predictive toxicology. Here, we describe and showcase ComptoxAI's graph-structured knowledge base in the context of three real-world use-cases, demonstrating that it can rapidly answer complex questions about toxicology that are infeasible using previous technologies and data resources. These use-cases each demonstrate a tool for information retrieval from the knowledge base being used to solve a specific task: The "shortest path" module is used to identify mechanistic links between perfluorooctanoic acid (PFOA) exposure and nonalcoholic fatty liver disease; the "expand network" module identifies communities that are linked to dioxin toxicity; and the quantitative structure-activity relationship (QSAR) dataset generator predicts pregnane X receptor agonism in a set of 4,021 pesticide ingredients. The contents of ComptoxAI's source data are rigorously aggregated from a diverse array of public third-party databases, and ComptoxAI is designed as a free, public, and open-source toolkit to enable diverse classes of users including biomedical researchers, public health and regulatory officials, and the general public to predict toxicology of unknowns and modes of action.

Effects of the Chinese herbal medicine Hong Huang decoction, on myocardial injury in breast cancer patients who underwent anthracycline-based chemotherapy

Objective

To assess the effects of Hong Huang Decoction (HHD), a Chinese herbal medicine, on myocardial injury in breast cancer patients who underwent anthracycline (ANT)-based chemotherapy.

Methods

A total of 51 patients with breast cancer who underwent an ANT-based chemotherapy program and met the inclusion/exclusion criteria were allocated to the treatment or placebo groups using a random number generation process. Patients in the treatment group received liquid HHD twice a day. Treatment was given from 1 day prior to chemotherapy up to the end of chemotherapy (after 6 months). Participants in the placebo group received a placebo over the same schedule. Left ventricular ejection fraction (LVEF), global longitudinal strain (GLS), diagnostic markers of acute myocardial infarction [e.g., lactate dehydrogenase (LDH), creatine kinase-MB (CK-MB), and B-type natriuretic peptide (BNP)], nitric oxide (NO), superoxide dismutase (SOD), as well as pro-inflammatory cytokines [e.g., tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), and human C-reactive protein (CRP)], and anti-inflammatory cytokine interleukin-10 (IL-10), were outcome measures assessed before chemotherapy, 3 and 6 months after chemotherapy.

Results

Compared to the placebo group, the GLS value was significantly higher in the treatment group (19.95 ± 1.16 vs. 19.06 ± 1.64, P ≤ 0.001). Significant differences were also noted for levels of SOD (689.71 ± 203.60 vs. 807.88 ± 182.10, P < 0.05), IL-6 (58.04 ± 22.06 vs. 194.20 ± 40.14, P ≤ 0.001), IL-10 (237.90 ± 94.98 vs. 68.81 ± 32.92, P ≤ 0.001), NO (75.05 ± 26.39 vs. 55.83 ± 19.37, P ≤ 0.005), and TNF-α (301.80 ± 134.20 vs. 680.30 ± 199.60, P ≤ 0.001) in the patients before chemotherapy compared to 6 months after initiating chemotherapy.

Conclusion

HHD regulated the levels of IL-6, IL-10, SOD, NO, and TNF-α. The results demonstrated that GLS is a better indicator of early myocardial injury compared to LVEF, and HHD could modulate oxidative stress to protect against ANT cardio toxicity.

Clinical trial registration

Chinese Clinical Trial Registry, identifier ChiCTR1900022394. Date of registration: 2019-04-09.

Green Crop Yam-Derived Carbons: Off-Plane Active Sites for Oxygen Electroreduction Identified by First-Principles

Plant-derived nonprecious metal catalysts are considered one of the promising candidates of platinum for oxygen reduction reaction (ORR). In this work, the typical microscopic morphology of fresh green crop yam is first detected by cryoscanning electronic microscopy. Using the green and widely sourced yam with spherical starch in nature as a precursor, well-defined spherical carbons are prepared via hypersaline-assisted hydrothermal carbonization and NH₃activation, featuring a high heteroatom doping level and a hierarchical porous structure. Experimental results and density functional theory (DFT) calculations reveal that diverse off-plane Fe-N_x-C_y ensembles on the spherical carbons trigger the high performance that exceeds state-of-art Pt/C and most reported carbon catalysts toward ORR in a KOH solution. The increased charge density and the bond length of Fe coordinated in the sites should be responsible for the significantly improved property. The easily editing of off-plane active sites from the simple carbon morphology may shed light on optimizing nonprecious carbons as next-generation catalysts for ORR.

POS0720 LOW-DOSE GLUCOCORTICOIDS WITHDRAWN IN SYSTEMIC LUPUS ERYTHEMATOSUS: A DESIRABLE AND ATTAINABLE GOAL

Background

Prolonged use of GC may cause irreversible organ damage, leading to impaired quality of life and even increased mortality. However, many physicians are worried about severe flares after GC withdrawal in daily practice.

Objectives

To assess the risk of flare in systemic lupus erythematosus (SLE) patients after low dose glucocorticoids (GC) discontinuation and evaluate the risk factors of flare.

Methods

SLE patients who ever discontinued GC were identified from PKUFHS cohort. The disease flare profile after GC discontinuation were analyzed. Flare rate was analyzed using Kaplan-Meier analysis. COX regression was used to determine the effect of variables on SLE flare. A prognostic nomogram using Cox proportional hazards regression modeling were developed.

Results

132 SLE patients were eligible for the final analysis. They were followed up for a median (IQR) period of 21.8 (9.01, 36.7) months. The cumulative probability of flare after GC discontinuation was 8.3 % at 6 months, 16.8% at year 1 and 27.5% at year 2 (Figure 1A). In multivariate COX analysis, hypocomplementemia and serologically active clinically quiescent (SACQ) were independent risk factors of flare [HR 2.53, 95% CI (1.32, 4.88); HR 3.17, 95% CI (1.44, 6.97), respectively]. Age ≥ 40y at GC withdrawal and hydroxychloroquine usage were independent protective factors of flare [HR 0.53, 95% CI (0.29, 0.99); HR 0.32, 95% CI (0.17, 0.62), respectively] (Table 1). The protective effect of hydroxychloroquine was dosage related. From the prospective of different tapering strategies embodied as duration from prednisone 5mg/d to complete discontinuation, slower tapering strategy (12-24 months) significantly reduced the risk of flare compared to faster tapering strategy (< 3 months) [HR 0.30, 95% CI (0.11, 0.82), p=0.019]. The prognostic nomogram including aforementioned factors effectively predicted 1- and 2-year probability of flare-free (Figure 1B).

Table 1.

Predictors of flare by univariate and multivariate COX analysis.

UnivariatepMultivariatepMultivariatepModel 1Model 2age≥40y at GC withdrawal0.59 (0.33,1.07)0.0840.53 (0.29, 0.99)0.0490.63 (0.33, 1.18)0.147Age at onset ≥18y2.03 (0.62, 6.66)0.2442.75 (0.77, 9.85)0.1212.88 (0.81, 10.2)0.103Remission duration≥60 months since the last flare0.66 (0.35, 1.27)0.2170.81 (0.41, 1.57)0.5260.73 (0.38, 1.41)0.346history of thrombocytopenia1.73 (0.94, 3.18)0.0771.36 (0.70, 2.65)0.3591.45 (0.74, 2.83)0.278history of lupus nephritis0.86 (0.47, 1.55)0.610////Hypocomplementemia1.97 (1.06, 3.66)0.0312.53 (1.32, 4.88)0.005//anti-dsDNA positive1.25 (0.70, 2.23)0.456////SACQ (both)2.91 (1.38, 6.15)0.005//3.17 (1.44, 6.97)0.004SACQ (or)1.29 (0.73, 2.30)0.380////Hydroxychloroquine or not0.29 (0.16, 0.53)<0.0010.29 (0.15, 0.56)<0.0010.32 (0.17, 0.62)0.001Immunosuppressant or not0.77 (0.40, 1.48)0.426////

There was strong collinearity between hypocomplementemia and SACQ, so the two parameters were separated into two models. SACQ (both): anti-dsDNA positive and hypocomplementemia; SACQ (or): anti-dsDNA positive or hypocomplementemia; GC: glucocorticoids. Data were shown as HR (95% CI).

Figure 1.

Conclusion

Low-dose GC is feasibly discontinued with infrequent flare in real-life setting. SACQ and younger age are potential risk factors of SLE flare, while hydroxychloroquine usage and slow GC tapering to withdrawal can reduce relapse. The visualized model we developed may help to predict risk of flare among SLE patients who discontinued GC.

Disclosure of Interests

None declared

The Prembion® pre-biotic improves the impact of anti-CTLA4 immune checkpoint inhibitor in a murine model of malignant pleural mesothelioma

Objective

Immune checkpoint inhibition (ICI) therapy has revolutionized the outcome of certain cancers such as malignant pleural mesothelioma (MPM). However, patient responsiveness to this treatment remains unpredictable. Recently, a role for the gut microbiota composition has emerged for patients to generate a robust immune response against their tumors, following immunotherapy. Here, we studied the impact of Prembion®, a pre-biotic and modulator of the gut microbiota, on tumor control and lymphocyte infiltration in a murine MPM model treated by ICI.

Methods

Prembion® (diluted into drinking water) was administrated to BALBc mice for 14 days. These animals were then inoculated orthotopically with a syngeneic MPM cell line (AB12-luc cells injected in the pleura) and followed by bioluminescence imaging. We determined the tumor growth and mouse survival in different groups: untreated control, Prembion®, IgG control, anti-PDL-1, anti-CTLA4, Prembion®+anti-PDL-1 and Prembion®+anti-CTLA4. A correlation between tumor response/animal survival and MPM infiltration with CD8+ lymphocytes was also performed by immunohistochemistry.

Results

Prembion® was well tolerated and did not affect animal weight or activity. Interestingly, Prembion® was as effective as anti-PDL1 and anti-CTLA4 monotherapy on tumor control, prolonging survival by 4.0 ± 1.1 days compared to controls (p&lt;0.05). Moreover Prembion® potentiated anti-CTLA4 efficacy with a significant improvement in mouse survival of the Prembion®+anti-CTLA4 compared to controls (3.6 ± 1.1 days, p&lt;0.05). Additionally, this finding correlated with enhanced MPM infiltration by CD8+ lymphocytes compared to controls (p&lt;0.05).

Conclusion

Prembion® positively regulated the adaptive immune response against MPM and helped to improve the impact of anti-CTLA4 ICI on MPM. Further work focusing on the gut microbiome changes induced by Prembion® are ongoing to better understand the mechanisms involved.

OP0142 COMPARISON OF ATTAINMENT AND PROTECTIVE EFFECTS OF THE LUPUS LOW DISEASE ACTIVITY STATE IN PATIENTS WITH NEWLY DIAGNOSED VERSUS ESTABLISHED SLE - A MULTICENTRE PROSPECTIVE STUDY

Background

Lupus low disease activity state (LLDAS) attainment has been reported to be associated with reduced damage accrual, flare, and mortality, as well as improved quality of life, in cohorts of SLE patients with established disease. Whether these associations are present in recent-onset disease is less well known.

Objectives

To evaluate the associations of LLDAS attainment with outcomes in patients with recent onset SLE.

Methods

Data from a 13-country longitudinal SLE cohort (ACR/SLICC criteria) were collected prospectively between 2013 and 2020 using standard templates. Organ damage and flare were captured using SLICC Damage Index and SELENA-SLEDAI Flare Index, respectively. LLDAS was defined as Golder et al., 2019 [1]. An inception cohort was defined based on duration since SLE diagnosis<1 year at enrolment. Patient characteristics between inception and non-inception cohorts were compared using Wilcoxon rank-sum (continuous variables) or Pearson’s Chi-squared tests (categorical variables). Survival analyses were performed to examine the association between LLDAS attainment and damage accrual and flare.

Results

The study cohort included 4,106 patients of whom 680 (16%) were recruited within 1 year of SLE diagnosis (inception cohort). Compared to the non-inception cohort, inception cohort patients were significantly younger, had higher disease activity (SLEDAI-2K and physician global assessment), used more glucocorticoids and immunosuppressants but had less organ damage at enrolment and only 88 (13.6%) patients accrued damage during a median 2.2 years follow-up (Table 1).

Table 1.Non-inception cohortInception cohortp-valuen=3426n=680Age at enrolment (years), median [IQR]40 [31, 51]33 [25, 44]<0.001Age at diagnosis (years), median [IQR]28 [21, 38]33 [25, 43]<0.001SLE duration at enrolment (years), median [IQR]10 [5, 16]1 [0, 1]<0.001Study duration (years), median [IQR]2.5 [1.0, 5.4]2.2 [0.9, 3.7]<0.001Females, n (%)3155 (92.1%)623 (91.6%)0.68Asian ethnicity, n (%)3037 (89.1%)595 (88.1%)0.49Prednisolone (PNL) use - ever, n (%)2865 (83.6%)620 (91.2%)<0.001Time adjusted mean (TAM)-PNL, median [IQR]5.0 [2.2, 8.6]6.2 [3.2, 10.3]<0.001Cumulative PNL (g), median [IQR]3.4 [0.5, 9.7]3.8 [1.1, 8.5]0.26Anti-Malarial use - ever, n (%)2669 (77.9%)569 (83.7%)<0.001Immunosupressant use -ever, n (%)2367 (69.1%)521 (76.6%)<0.001AMS (TAM-SLEDAI-2K), median [IQR]2.8 [1.2, 4.6]3.1 [1.6, 5.0]0.002TAM-PGA, median [IQR]0.4 [0.2, 0.7]0.4 [0.3, 0.8]<0.001Mild/moderate/severe flare ever, n (%)1789 (52.2%)391 (57.5%)0.012Organ damage accrual, n (%)629 (20.8%)88 (13.6%)<0.001LLDAS at baseline, n (%)1730 (50.5%)195 (28.7%)<0.001LLDAS-ever (at least once), n (%)2637 (78.2%)492 (73.9%)0.014≥50% time in LLDAS (LLDAS-5), n (%)1612 (50.6%)256 (41.1%)<0.001

Significantly fewer inception cohort patients were in LLDAS at enrolment than the non-inception cohort (29% vs. 51%, p<0.001). However, 74% of inception and 78% of non-inception cohort patients achieved LLDAS at least once during follow-up. Limiting analysis only to patients not in LLDAS at enrolment, time to first LLDAS attainment was assessed: inception cohort patients were 60% more likely to attain their first LLDAS (HR = 1.60 (95%CI: 1.40, 1.82), p<0.001) than non-inception cohort patients. LLDAS attainment was significantly protective against flare in the inception (HR, 95% CI) and non-inception (HR, 95% CI) cohorts. Trends towards protection against damage accrual in association with LLDAS in the inception cohort were not significant.

Conclusion

LLDAS attainment is protective from flare in recent onset SLE. Significant protection from damage accrual was not observed, due to low rates of damage accrual in the first years after SLE diagnosis.

References

[1]Golder, V., et al., Lupus low disease activity state as a treatment endpoint for systemic lupus erythematosus: a prospective validation study. The Lancet Rheumatology, 2019. 1(2): p. e95-e102.

Acknowledgements

We thank all patients participating in the Asia Pacific Lupus Collaboration (APLC) cohort, and all data collectors for their ongoing support for APLC research activities.

The APLC has received unrestricted project grants from AstraZeneca, BMS, Eli Lily, Janssen, Merck Serono, and UCB to support data collection contributing to this work.

Disclosure of Interests

Vera Golder: None declared, Rangi Kandane-Rathnayake: None declared, Worawit Louthrenoo: None declared, Yi-Hsing Chen Speakers bureau: Pfizer, Novartis, Abbvie, Johnson & Johnson, BMS, Roche, Lilly, GSK, Astra& Zeneca, Sanofi, MSD, Guigai, Astellas, Inova Diagnostics, UCB, Agnitio Science Technology, United Biopharma, Thermo Fisher, Consultant of: Pfizer, Novartis, Abbvie, Johnson & Johnson, BMS, Roche, Lilly, GSK, Astra and Zeneca, Sanofi, Guigai, Astellas, Inova Diagnostics, UCB, Agnitio Science Technology, United Biopharma, Thermo Fisher, Gilead, Grant/research support from: Yes. Clinical trials and/or research grants from Pfizer, Norvatis, BMS, Abbevie, Johnson & Johnson, Roche,Sanofi, Guigai, Roche, Boehringer Ingelheim, UCB, MSD, Astra-Zeneca,Astellas, Gilead, Jiacai Cho: None declared, Aisha Lateef: None declared, Laniyati Hamijoyo Speakers bureau: Pfizer, Novartis, Abbot, Shue Fen Luo: None declared, Yeong-Jian Jan Wu Speakers bureau: Pfizer, Lilly, Novartis, Abbvie, Sandra Navarra Speakers bureau: Pfizer, Johnson & Johnson, Novartis, Astellas, Grant/research support from: Astellas, Johnson & Johnson, Leonid Zamora: None declared, Zhanguo Li Speakers bureau: Eli, Lilly, Novartis, GSK, AbbVie, Paid instructor for: Pfizer, Roche, Johnson, Consultant of: Lilly, Pfizer, Grant/research support from: Pfizer, Yuan An: None declared, Sargunan Sockalingam Speakers bureau: Yes. Pfizer, Roche, Novartis, Grant/research support from: Roche and Novartis, Yasuhiro Katsumata Speakers bureau: Chugai Pharmaceutical Co., Ltd., Glaxo-Smithkline K.K., and Sanofi K.K., Masayoshi Harigai Speakers bureau: MH has received speaker’s fee from AbbVie Japan GK, Ayumi Pharmaceutical Co., Boehringer Ingelheim Japan, Inc.,Bristol Myers Squibb Co., Ltd., Chugai Pharmaceutical Co., Ltd., Eisai Co., Ltd., Eli Lilly Japan K.K., GlaxoSmithKline K.K., Kissei Pharmaceutical Co., Ltd., Pfizer Japan Inc., Takeda Pharmaceutical Co., Ltd., and Teijin Pharma Ltd, Consultant of: MH is a consultant for AbbVie, Boehringer-ingelheim, Bristol Myers Squibb Co., Kissei Pharmaceutical Co.,Ltd. and Teijin Pharma., Grant/research support from: MH has received research grants from AbbVie Japan GK, Asahi Kasei Corp., Astellas Pharma Inc., Ayumi Pharmaceutical Co., Bristol Myers Squibb Co., Ltd., Chugai Pharmaceutical Co., Daiichi-Sankyo, Inc.,Eisai Co., Ltd., Kissei Pharmaceutical Co., Ltd., Mitsubishi Tanabe Pharma Co., Nippon Kayaku Co., Ltd., Sekiui Medical, Shionogi & Co., Ltd., Taisho Pharmaceutical Co., Ltd., Takeda Pharmaceutical Co., Ltd., and Teijin Pharma Ltd., Yanjie Hao: None declared, Zhuoli Zhang Speakers bureau: Norvatis, GSK, Pfizer, BMDB Basnayake: None declared, Madelynn Chan Speakers bureau: AbbVie, Novartis, Consultant of: Advisory Board member for Pfizer, Eli-Lilly, Jun Kikuchi: None declared, Tsutomu Takeuchi Speakers bureau: AbbVie AYUMI Pharmaceutical Corp. Bristol-Myers Squibb Chugai Pharmaceutical Co, Ltd. Daiichi Sankyo Co., Ltd. Eisai Co., Ltd. Eli Lilly Japan, Gilead Sciences, Inc. Mitsubishi-Tanabe Pharma Corp. Pfizer Japan Inc. Sanofi K.K., Consultant of: Astellas Pharma, Inc. Chugai Pharmaceutical Co, Ltd. Eli Lilly Japan, Mitsubishi-Tanabe Pharma Corp., Grant/research support from: AbbVie Asahikasei Pharma Corp. Chugai Pharmaceutical Co, Ltd. Mitsubishi-Tanabe Pharma Corp. Sanofi K.K, Sang-Cheol Bae: None declared, Sean O’Neill Paid instructor for: Advisory board member for GSK, Fiona Goldblatt: None declared, Shereen Oon: None declared, Kathryn Gibson Speakers bureau: UCB, Consultant of: Novartis – co-chair for NSW and steering committee member for ARISE meeting Feb 2021

Janssen Pharmaceuticals – advisory board, Grant/research support from: Novartis, Employee of: Eli Lilly, Kristine Ng Speakers bureau: speaker fees and advisory board (Abbvie, Novartis, Janssen), Annie Law: None declared, Nicola Tugnet: None declared, Sunil Kumar: None declared, Cherica Tee: None declared, Michael Tee: None declared, Yoshiya Tanaka Speakers bureau: Daiichi-Sankyo, Eli Lilly, Novartis, YL Biologics, Bristol-Myers, Eisai, Chugai, Abbvie, Astellas, Pfizer, Sanofi, Asahi-kasei, GSK, Mitsubishi-Tanabe, Gilead, Janssen, Grant/research support from: Daiichi-Sankyo, Eli Lilly, Novartis, YL Biologics, Bristol-Myers, Eisai, Chugai, Abbvie, Astellas, Pfizer, Sanofi, Asahi-kasei, GSK, Mitsubishi-Tanabe, Gilead, Janssen, C.S. Lau Shareholder of: Pfizer, Sanofi and Janssen, Mandana Nikpour Speakers bureau: Actelion, GSK, Janssen, Pfizer, UCB, Paid instructor for: UCB, Consultant of: Actelion, Boehringer Ingelheim, Certa Therapeutics, Eli Lilly, GSK, Janssen, Pfizer, UCB, Grant/research support from: Actelion, Astra Zeneca, BMS, GSK, Janssen, UCB, Alberta Hoi Consultant of: AH is on the advisory board for Abbvie and GSK, Grant/research support from: AH has received research support from AstraZeneca, GSK, BMS, Janssen, and Merck Serono, Eric F. Morand Speakers bureau: AstraZeneca, Paid instructor for: Eli Lilly, Consultant of: AstraZeneca, Amgen, Biogen, BristolMyersSquibb, Eli Lilly, EMD Serono, Genentech, Janssen, Grant/research support from: AstraZeneca, BristolMyersSquibb, Eli Lilly, EMD Serono, Janssen

Photodynamique therapy relieves tumor vascular anergy and promotes immune cell trafficking in an orthotopic mouse model of malignant pleural mesothelioma

Objective

Malignant pleural mesothelioma (MPM) is a deadly disease with limited treatment options. Recently, dual immune checkpoint inhibition therapy (ICI) showed improved patient survival. However, only a fraction of patients were responsive to immunotherapy. One potential mechanism of MPM resistance to ICIs could be their endothelial anergy that hampers leukocyte trafficking to the tumor bulk. Here, we hypothesized that vascular-targeted low dose photodynamic therapy (L-PDT), treatment of MPM could relieve tumor endothelial anergy and improve immunotherapy efficacy.

Methods

Using an orthotopic syngeneic MPM murine model (AB12 cells injected in the pleura of BALB/c mice), we determined the impact of L-PDT on the endothelial expression of E-Selectin, a key molecule involved in leukocyte diapedesis by immunohistochemistry. Furthermore, to confirm the role of E-selectin, we determined the extravasation of effector T cells (CD8+/CD4+) by immunostaining in L-PDT treated tumors in the presence or absence of an E-selectin blocking antibody. Finally, we assessed tumor growth/survival of our MPM murine model treated with L-PDT alone or combined to ICIs.

Results

L-PDT pre-treatment enhanced MPM endothelial E-Selectin expression in vivo. The latter was associated with increased CD4+ and CD8+ lymphocyte infiltration of MPM following L-PDT which did not occur after E-Selectin blockade. Also, L-PDT pre-treatment of MPM influenced favorably tumor control, mouse survival and the impact of ICIs compared to controls.

Conclusion

L-PDT pre-treatment relieves endothelial anergy in MPM which improves antitumor immunity and response to ICI. This approach could constitute a promising pre-treatment option, in combination with ICIs, for the management of this deadly disease.