Background: Meningiomas are the most common intracranial tumor with surgery, dural margin treatment, and radiotherapy as cornerstones of therapy. Response to treatment continues to be highly heterogeneous even across tumors of the same grade. Methods: Using a cohort of 2490 meningiomas in addition to 100 cases from the prospective RTOG-0539 phase II clinical trial, we define molecular biomarkers of response across multiple different, recently defined molecular classifications and use propensity score matching to mimic a randomized controlled trial to evaluate the role of extent of resection, dural marginal resection, and adjuvant radiotherapy on clinical outcome. Results: Gross tumor resection led to improved progression-free-survival (PFS) across all molecular groups (MG) and improved overall survival in proliferative meningiomas (HR 0.52, 95%CI 0.30-0.93). Dural margin treatment (Simpson grade 1/2) improved PFS versus complete tumor removal alone (Simpson 3). MG reliably predicted response to radiotherapy, including in the RTOG-0539 cohort. A molecular model developed using clinical trial cases discriminated response to radiotherapy better than standard of care grading in multiple cohorts (ΔAUC 0.12, 95%CI 0.10-0.14). Conclusions: We elucidate biological and molecular classifications of meningioma that influence response to surgery and radiotherapy in addition to introducing a novel molecular-based prediction model of response to radiation to guide treatment decisions.

Background: Liquid biopsy represents a major development in cancer research, with significant translational potential. Similarly, the integration of multiple molecular platforms has yielded novel insights into disease biology and heterogeneity. We hypothesise that applying contemporary multi-omic approaches to liquid biopsies will improve the power of current models. Methods: We have compiled a cohort of 51 patients with glioblastoma, brain metastasis, and primary CNS lymphoma who underwent CSF sampling as part of clinical care. Cell free methylated DNA and shotgun proteomic profiling was obtained from the CSF of each patient and used to build tumour-specific classifiers. Integrated classifiers were compared with single platform classifiers using multiple approaches. Results: In this study, we show that the DNA methylation and protein profiles of cerebrospinal fluid can be combined to fully discriminate lymphomas from their major diagnostic counterparts with perfect AUCs of 1 (95% confidence interval 1-1) and 100% specificity. Each integrated lymphoma classifier significantly outperforms single-platform classifiers, suggesting synergistic biology is obtained using multiple molecular platforms. Conclusions: We present the most specific and accurate CNS lymphoma classifier to date by integrating the methylome and proteome of CSF. This has important implications for the future of cancer diagnostics and generates immediate utility for patients with CNS lymphoma.

Background: Meningiomas have significant heterogeneity between patients, making prognostication challenging. For this study, we prospectively validate the prognostic capabilities of a DNA methylation-based predictor and multiomic molecular groups (MG) of meningiomas. Methods: DNA methylation profiles were generated using the Illumina EPICarray. MG were assigned as previously published. Performance of our methylation-based predictor and MG were compared with WHO grade using generalized boosted regression modeling by generating time-dependent receiver operating characteristic (ROC) curves and computing area under the ROC curves (AUCs) along with their 95% confidence interval using bootstrap resampling. Results: 295 meningiomas treated from 2018-2021 were included. Methylation-defined high-risk meningiomas had significantly poorer PFS and OS compared to low-risk cases (p<0.0001). Methylation risk increased with higher WHO grade and MG. Higher methylome risk (HR 4.89, 95%CI 2.02-11.82) and proliferative MG (HR 4.11, 95%CI 1.29-13.06) were associated with significantly worse PFS independent of WHO grade, extent of resection, and adjuvant RT. Both methylome-risk and MG classification predicted 3- and 5-year PFS and OS more accurately than WHO grade alone (ΔAUC=0.10-0.23). 42 cases were prescribed adjuvant RT prospectively although RT did not significantly improve PFS in high-risk cases (p=0.41). Conclusions: Molecular profiling outperforms conventional WHO grading for prognostication in an independent, prospectively collected cohort of meningiomas.

Background: Meningiomas are the most common intracranial tumor, graded from 1 (benign) to 3 (malignant). The aim of this study was to identify clinical features associated with overall survival (OS), progression-free survival (PFS) and functional status for malignant meningiomas. Methods: Demographic, clinical and histopathological data from grade 3 intracranial meningioma cases were identified in the clinical databases from seven sites in North America and Europe from 1991-2022. Summary statistics and Kaplan-Meier OS and PFS curves were generated. Results: We identified 108 patients, with a median age 65 years (IQR: 52, 72) and 53.7% were female. Median OS was 109 months (95% CIs: 88, 227), and 5-year OS rate was 65% (95% CIs: 56, 76). Median PFS was 38 months (95% CIs: 24, 56) and 5-year PFS rate was 37% (95% CIs: 28, 49). OS and PFS were significantly lower in patients aged ≥65 years. Median preoperative KPS score was 80 (IQR: 70, 90), postoperatively KPS was 90 (IQR: 70, 98) and 1-year follow-up KPS was 70 (IQR: 50, 80). Conclusions: This study provides robust survival, recurrence and functional data for grade 3 meningiomas in North America and Europe over a 30-year period.

OBJECTIVES/GOALS: The goal of this study was to develop a clinically applicable technique to increase the precision of in vivo dose monitoring during radiation therapy by mapping the dose deposition and resolving the temporal dose accumulation while the treatment is being delivered in real time. METHODS/STUDY POPULATION: Ironizing radiation acoustic imaging (iRAI) is a novel imaging concept with the potential to map the delivered radiation dose on anatomic structure in real time during external beam radiation therapy without interrupting the clinical workflow. The iRAI system consisted of a custom-designed two-dimensional (2D) matrix transducer array with integrated preamplifier array, driven by a clinic-ready ultrasound imaging platform. The feasibility of iRAI volumetric imaging in mapping dose delivery and real-time monitoring of temporal dose accumulation in a clinical treatment plan were investigated with a phantom, a rabbit model, and a cancer patient. RESULTS/ANTICIPATED RESULTS: The total dose deposition and temporal dose accumulation in 3D space of a clinical C-shape treatment plan in a targeted region were first imaged and optimized in a phantom. Then, semi-quantitative iRAI measurements were achieved in an in vivo rabbit model. Finally, for the first time, real-time visualization of radiation dose delivered deep in a patient with liver metastases was performed with a clinical linear accelerator. These studies demonstrate the potential of iRAI to monitor and quantify the radiation dose deposition during treatment. DISCUSSION/SIGNIFICANCE: Described here is the pioneering role of an iRAI system in mapping the 3D radiation dose deposition of a complex clinical radiotherapy treatment plan. iRAI offers a cost-effective and practical solution for real-time visualization of 3D radiation dose delivery, potentially leading to personalized radiotherapy with optimal efficacy and safety.

We present the Widefield ASKAP L-band Legacy All-sky Blind surveY (WALLABY) Pilot Phase I Hi kinematic models. This first data release consists of Hi observations of three fields in the direction of the Hydra and Norma clusters, and the NGC 4636 galaxy group. In this paper, we describe how we generate and publicly release flat-disk tilted-ring kinematic models for 109/592 unique Hi detections in these fields. The modelling method adopted here—which we call the WALLABY Kinematic Analysis Proto-Pipeline (WKAPP) and for which the corresponding scripts are also publicly available—consists of combining results from the homogeneous application of the FAT and 3DBarolo algorithms to the subset of 209 detections with sufficient resolution and $S/N$ in order to generate optimised model parameters and uncertainties. The 109 models presented here tend to be gas rich detections resolved by at least 3–4 synthesised beams across their major axes, but there is no obvious environmental bias in the modelling. The data release described here is the first step towards the derivation of similar products for thousands of spatially resolved WALLABY detections via a dedicated kinematic pipeline. Such a large publicly available and homogeneously analysed dataset will be a powerful legacy product that that will enable a wide range of scientific studies.

We present WALLABY pilot data release 1, the first public release of H i pilot survey data from the Wide-field ASKAP L-band Legacy All-sky Blind Survey (WALLABY) on the Australian Square Kilometre Array Pathfinder. Phase 1 of the WALLABY pilot survey targeted three $60\,\mathrm{deg}^{2}$ regions on the sky in the direction of the Hydra and Norma galaxy clusters and the NGC 4636 galaxy group, covering the redshift range of $z \lesssim 0.08$ . The source catalogue, images and spectra of nearly 600 extragalactic H i detections and kinematic models for 109 spatially resolved galaxies are available. As the pilot survey targeted regions containing nearby group and cluster environments, the median redshift of the sample of $z \approx 0.014$ is relatively low compared to the full WALLABY survey. The median galaxy H i mass is $2.3 \times 10^{9}\,{\rm M}_{{\odot}}$ . The target noise level of $1.6\,\mathrm{mJy}$ per 30′′ beam and $18.5\,\mathrm{kHz}$ channel translates into a $5 \sigma$ H i mass sensitivity for point sources of about $5.2 \times 10^{8} \, (D_{\rm L} / \mathrm{100\,Mpc})^{2} \, {\rm M}_{{\odot}}$ across 50 spectral channels ( ${\approx} 200\,\mathrm{km \, s}^{-1}$ ) and a $5 \sigma$ H i column density sensitivity of about $8.6 \times 10^{19} \, (1 + z)^{4}\,\mathrm{cm}^{-2}$ across 5 channels ( ${\approx} 20\,\mathrm{km \, s}^{-1}$ ) for emission filling the 30′′ beam. As expected for a pilot survey, several technical issues and artefacts are still affecting the data quality. Most notably, there are systematic flux errors of up to several 10% caused by uncertainties about the exact size and shape of each of the primary beams as well as the presence of sidelobes due to the finite deconvolution threshold. In addition, artefacts such as residual continuum emission and bandpass ripples have affected some of the data. The pilot survey has been highly successful in uncovering such technical problems, most of which are expected to be addressed and rectified before the start of the full WALLABY survey.

The great demographic pressure brings tremendous volume of beef demand. The key to solve this problem is the growth and development of Chinese cattle. In order to find molecular markers conducive to the growth and development of Chinese cattle, sequencing was used to determine the position of copy number variations (CNVs), bioinformatics analysis was used to predict the function of ZNF146 gene, real-time fluorescent quantitative polymerase chain reaction (qPCR) was used for CNV genotyping and one-way analysis of variance was used for association analysis. The results showed that there exists CNV in Chr 18: 47225201-47229600 (5.0.1 version) of ZNF146 gene through the early sequencing results in the laboratory and predicted ZNF146 gene was expressed in liver, skeletal muscle and breast cells, and was amplified or overexpressed in pancreatic cancer, which promoted the development of tumour through bioinformatics. Therefore, it is predicted that ZNF146 gene affects the proliferation of muscle cells, and then affects the growth and development of cattle. Furthermore, CNV genotyping of ZNF146 gene was three types (deletion type, normal type and duplication type) by Real-time fluorescent quantitative PCR (qPCR). The association analysis results showed that ZNF146-CNV was significantly correlated with rump length of Qinchuan cattle, hucklebone width of Jiaxian red cattle and heart girth of Yunling cattle. From the above results, ZNF146-CNV had a significant effect on growth traits, which provided an important candidate molecular marker for growth and development of Chinese cattle.

This work investigates the role of flexibility and resonant excitation on the deformation mechanism and aerodynamic performance of flapping wings. A hummingbird-inspired wing (HIW) is considered and designed to have a bone-like stiffener made of carbon fibre/epoxy (CF/E) composite attached to a membrane made of carbon nanotubes/polypropylene (CNTs/PP) nanocomposite representing the flexible part of the natural wing. The designed HIW model is analysed through fluid-structure interaction simulations performed at frequencies near and at resonant frequency. It is found that HIW generates desired bending and twisting deformations that are coupled. These deformation mechanisms are studied in detail with the help of time-varying deflections and bending-twisting angles. Further, the simultaneous effect of these parameters on the aerodynamic performance of the wing is also investigated. It is observed that the coupled nature of bending and twisting deformations is critical in enhancing the aerodynamic performance of flapping wings. In addition to that, the resonance generates higher amplitude of desired structural deformations that further enhances thrust as well as lift generation capability of the wing. The underlying mechanism for this is also explained by studying the flow around the deflected surface of the wing. Compared to off-resonant frequencies, vorticity and pressures are substantially higher for the wing at resonance. A physical model of HIW is realised using CNTs/PP and CF/E composites to perform experimental wing motion analysis and to validate the computational results. In conclusion, the present study provides a basis to design efficient biomimetic flapping wings for micro aerial vehicles (MAVs) by exploring flexibility and resonant excitation.

In this retrospective cohort study, we assessed central-line–associated bloodstream infections (CLABSIs) and blood-culture contamination frequency during the first pandemic wave. Coronavirus disease 2019 (COVID-19) was significantly associated with CLABSI and blood-culture contamination. In the COVID-19 cohort, malignancy was associated with CLABSI. Black race, end-stage renal disease, and obesity were associated with blood-culture contamination.

Direct observations of the products of binary interactions are sparse, yet they provide important insights on the outcome of the interaction and the physics at play. Young and intermediate-age star clusters are the ideal tool to search for, and characterize such interaction products and allow for a detailed comparison to theoretical predictions. We here report on integral field spectroscopy obtained with MUSE for several such clusters in the Magellanic Clouds.

The incidence of scarlet fever has increased dramatically in recent years in Chongqing, China, but there has no effective method to forecast it. This study aimed to develop a forecasting model of the incidence of scarlet fever using a seasonal autoregressive integrated moving average (SARIMA) model. Monthly scarlet fever data between 2011 and 2019 in Chongqing, China were retrieved from the Notifiable Infectious Disease Surveillance System. From 2011 to 2019, a total of 5073 scarlet fever cases were reported in Chongqing, the male-to-female ratio was 1.44:1, children aged 3–9 years old accounted for 81.86% of the cases, while 42.70 and 42.58% of the reported cases were students and kindergarten children, respectively. The data from 2011 to 2018 were used to fit a SARIMA model and data in 2019 were used to validate the model. The normalised Bayesian information criterion (BIC), the coefficient of determination (R2) and the root mean squared error (RMSE) were used to evaluate the goodness-of-fit of the fitted model. The optimal SARIMA model was identified as (3, 1, 3) (3, 1, 0)12. The RMSE and mean absolute per cent error (MAPE) were used to assess the accuracy of the model. The RMSE and MAPE of the predicted values were 19.40 and 0.25 respectively, indicating that the predicted values matched the observed values reasonably well. Taken together, the SARIMA model could be employed to forecast scarlet fever incidence trend, providing support for scarlet fever control and prevention.

Frequent freezing injury greatly influences winter wheat production; thus, effective prevention and a command of agricultural production are vital. The freezing injury monitoring method integrated with ‘3S’ (geographic information systems (GIS), global positioning system (GPS) and remote sensing (RS)) technology has an unparalleled advantage. Using HuanJing (HJ)-1A/1B satellite images of a winter wheat field in Shanxi Province, China plus a field survey, crop types and winter wheat planting area were identified through repeated visual interpretations of image information and spatial analyses conducted in GIS. Six vegetation indices were extracted from processed HJ-1A/1B satellite images to determine whether the winter wheat suffered from freezing injury and its degree of severity and recovery, using change vector analysis (CVA), the freeze injury representative vegetation index and the combination of the two methods, respectively. Accuracy of the freezing damage classification results was verified by determining the impact of freezing damage on yield and quantitative analysis. The CVA and the change of normalized difference vegetation index (ΔNDVI) monitoring results were different so a comprehensive analysis of the combination of CVA and ΔNDVI was performed. The area with serious freezing injury covered 0.9% of the total study area, followed by the area of no freezing injury (3.5%), moderate freezing injury (10.2%) and light freezing injury (85.4%). Of the moderate and serious freezing injury areas, 0.2% did not recover; 1.2% of the no freezing injury and light freezing injury areas showed optimal recovery, 15.6% of the light freezing injury and moderate freezing injury areas showed poor recovery, and the remaining areas exhibited general recovery.

Although biological evidence suggests that tea consumption may protect against non-Hodgkin lymphoma (NHL), epidemiological evidence has been unclear. The aim of this study was to examine the association between tea-drinking habits and the risk of NHL in a large nationwide prospective cohort of postmenopausal US women. 68 854 women who were enrolled from 1993 through 1998 in the Women’s Health Initiative Observational Study and responded to year 3 annual follow-up questionnaire comprised the analytic cohort. Newly diagnosed NHL cases after the year 3 visit were confirmed by medical and pathology reports. Multivariable-adjusted Cox proportional hazards models were performed to assess the associations of tea-drinking habits (specifically, the amounts of caffeinated/herbal/decaffeinated tea intake) with the overall risk of NHL and three major subtypes (diffuse large B-cell lymphoma (n 195, 0·3 %), follicular lymphoma (n 128, 0·2 %) and chronic lymphocytic leukaemia/small lymphocytic lymphoma (n 51, 0·1 %)). Among 62 622 participants, a total of 663 (1·1 %) women developed NHL during a median follow-up of 16·51 (sd 6·20) years. Overall, different amounts of type-specific tea intake were not associated with the risk of NHL regardless of its histologic subtypes after adjustment for confounders. Our findings suggest that tea intake at the current consumption level does not influence the risk of NHL, regardless of its histologic types.