A comparison of different methods to maximise signal extraction when using central venous pressure to optimise atrioventricular delay after cardiac surgery.

Our group has shown that central venous pressure (CVP) can optimise atrioventricular (AV) delay in temporary pacing (TP) after cardiac surgery. However, the signal-to-noise ratio (SNR) is influenced both by the methods used to mitigate the pressure effects of respiration and the number of heartbeats analysed. This paper systematically studies the effect of different analysis methods on SNR to maximise the accuracy of this technique. We optimised AV delay in 16 patients with TP after cardiac surgery. Transitioning rapidly and repeatedly from a reference AV delay to different tested AV delays, we measured pressure differences before and after each transition. We analysed the resultant signals in different ways with the aim of maximising the SNR: (1) adjusting averaging window location (around versus after transition), (2) modifying window length (heartbeats analysed), and (3) applying different signal filtering methods to correct respiratory artefact. (1) The SNR was 27 % higher for averaging windows around the transition versus post-transition windows. (2) The optimal window length for CVP analysis was two respiratory cycle lengths versus one respiratory cycle length for optimising SNR for arterial blood pressure (ABP) signals. (3) Filtering with discrete wavelet transform improved SNR by 62 % for CVP measurements. When applying the optimal window length and filtering techniques, the correlation between ABP and CVP peak optima exceeded that of a single cycle length (R = 0.71 vs. R = 0.50, p < 0.001). We demonstrated that utilising a specific set of techniques maximises the signal-to-noise ratio and hence the utility of this technique. [Abstract copyright: © 2024 The Author(s).

Benchmarking a foundation LLM on its ability to re-label structure names in accordance with the AAPM TG-263 report

Purpose: To introduce the concept of using large language models (LLMs) to re-label structure names in accordance with the American Association of Physicists in Medicine (AAPM) Task Group (TG)-263 standard, and to establish a benchmark for future studies to reference. Methods and Materials: The Generative Pre-trained Transformer (GPT)-4 application programming interface (API) was implemented as a Digital Imaging and Communications in Medicine (DICOM) storage server, which upon receiving a structure set DICOM file, prompts GPT-4 to re-label the structure names of both target volumes and normal tissues according to the AAPM TG-263. Three disease sites, prostate, head and neck, and thorax were selected for evaluation. For each disease site category, 150 patients were randomly selected for manually tuning the instructions prompt (in batches of 50) and 50 patients were randomly selected for evaluation. Structure names that were considered were those that were most likely to be relevant for studies utilizing structure contours for many patients. Results: The overall re-labeling accuracy of both target volumes and normal tissues for prostate, head and neck, and thorax cases was 96.0%, 98.5%, and 96.9% respectively. Re-labeling of target volumes was less accurate on average except for prostate - 100%, 93.1%, and 91.1% respectively. Conclusions: Given the accuracy of GPT-4 in re-labeling structure names of both target volumes and normal tissues as presented in this work, LLMs are poised to be the preferred method for standardizing structure names in radiation oncology, especially considering the rapid advancements in LLM capabilities that are likely to continue.Comment: 20 pages, 5 figures, 1 tabl

Deep-Learning-based Fast and Accurate 3D CT Deformable Image Registration in Lung Cancer

Purpose: In some proton therapy facilities, patient alignment relies on two 2D orthogonal kV images, taken at fixed, oblique angles, as no 3D on-the-bed imaging is available. The visibility of the tumor in kV images is limited since the patient's 3D anatomy is projected onto a 2D plane, especially when the tumor is behind high-density structures such as bones. This can lead to large patient setup errors. A solution is to reconstruct the 3D CT image from the kV images obtained at the treatment isocenter in the treatment position. Methods: An asymmetric autoencoder-like network built with vision-transformer blocks was developed. The data was collected from 1 head and neck patient: 2 orthogonal kV images (1024x1024 voxels), 1 3D CT with padding (512x512x512) acquired from the in-room CT-on-rails before kVs were taken and 2 digitally-reconstructed-radiograph (DRR) images (512x512) based on the CT. We resampled kV images every 8 voxels and DRR and CT every 4 voxels, thus formed a dataset consisting of 262,144 samples, in which the images have a dimension of 128 for each direction. In training, both kV and DRR images were utilized, and the encoder was encouraged to learn the jointed feature map from both kV and DRR images. In testing, only independent kV images were used. The full-size synthetic CT (sCT) was achieved by concatenating the sCTs generated by the model according to their spatial information. The image quality of the synthetic CT (sCT) was evaluated using mean absolute error (MAE) and per-voxel-absolute-CT-number-difference volume histogram (CDVH). Results: The model achieved a speed of 2.1s and a MAE of <40HU. The CDVH showed that <5% of the voxels had a per-voxel-absolute-CT-number-difference larger than 185 HU. Conclusion: A patient-specific vision-transformer-based network was developed and shown to be accurate and efficient to reconstruct 3D CT images from kV images.Comment: 9 figure

Modelling small block aperture in an in-house developed GPU-accelerated Monte Carlo-based dose engine for pencil beam scanning proton therapy

Purpose: To enhance an in-house graphic-processing-unit (GPU) accelerated virtual particle (VP)-based Monte Carlo (MC) proton dose engine (VPMC) to model aperture blocks in both dose calculation and optimization for pencil beam scanning proton therapy (PBSPT)-based stereotactic radiosurgery (SRS). Methods and Materials: A block aperture module was integrated into VPMC. VPMC was validated by an opensource code, MCsquare, in eight water phantom simulations with 3cm thick brass apertures: four were with aperture openings of 1, 2, 3, and 4cm without a range shifter, while the other four were with same aperture opening configurations with a range shifter of 45mm water equivalent thickness. VPMC was benchmarked with MCsquare and RayStation MC for 10 patients with small targets (average volume 8.4 cc). Finally, 3 patients were selected for robust optimization with aperture blocks using VPMC. Results: In the water phantoms, 3D gamma passing rate (2%/2mm/10%) between VPMC and MCsquare were 99.71$\pm$0.23%. In the patient geometries, 3D gamma passing rates (3%/2mm/10%) between VPMC/MCsquare and RayStation MC were 97.79$\pm$2.21%/97.78$\pm$1.97%, respectively. The calculation time was greatly decreased from 112.45$\pm$114.08 seconds (MCsquare) to 8.20$\pm$6.42 seconds (VPMC), both having statistical uncertainties of about 0.5%. The robustly optimized plans met all the dose-volume-constraints (DVCs) for the targets and OARs per our institutional protocols. The mean calculation time for 13 influence matrices in robust optimization by VPMC was 41.6 seconds. Conclusion: VPMC has been successfully enhanced to model aperture blocks in dose calculation and optimization for the PBSPT-based SRS.Comment: 3 tables, 3 figure

Hormonal regulation of ovarian bursa fluid in mice and involvement of aquaporins.

In rodent species, the ovary and the end of oviduct are encapsulated by a thin membrane called ovarian bursa. The biological functions of ovarian bursa remain unexplored despite its structural arrangement in facilitating oocytes transport into oviduct. In the present study, we observed a rapid fluid accumulation and reabsorption within the ovarian bursa after ovarian stimulation (PMSG-primed hCG injection), suggesting that the ovarian bursa might play an active role in regulating local fluid homeostasis around the timing of ovulation. We hypothesized that the aquaporin proteins, which are specialized channels for water transport, might be involved in this process. By screening the expression of aquaporin family members (Aqp1-9) in the ovarian tissue and isolated ovarian bursa (0, 1, 2 and 5 h after hCG injection), we found that AQP2 and AQP5 mRNA showed dynamic changes after hCG treatment, showing upregulation at 1-2 h followed by gradually decrease at 5 h, which is closely related with the intra-bursa fluid dynamics. Further immunofluorescence examinations of AQP2 and AQP5 in the ovarian bursa revealed that AQP2 is specifically localized in the outer layer (peritoneal side) while AQP5 localized in the inner layer (ovarian side) of the bursa, such cell type specific and spatial-temporal expressions of AQP2 and 5 support our hypothesis that they might be involved in efficient water transport through ovarian bursa under ovulation related hormonal regulation. The physiological significance of aquaporin-mediated water transport in the context of ovarian bursa still awaits further clarification

Climate warming and decreasing total column ozone over the Tibetan Plateau during winter and spring

The long-term trends of the total column ozone (TCO) over the Tibetan Plateau (TP) and factors responsible for the trends are analysed in this study using various observations and a chemistry–climate model (CCM). The results indicate that the total column ozone low (TOL) over the TP during winter and spring is deepening over the recent decade, which is opposite to the recovery signal in annual mean TCO over the TP after mid-1990s. The TOL intensity is increasing at a rate of 1.4 DU/decade and the TOL area is extending with 50,000 km2/decade during winter for the period 1979–2009. The enhanced transport of ozone-poor air into the stratosphere and elevated tropopause due to the rapid and significant warming over the TP during winter reduce ozone concentrations in the upper troposphere and lower stratosphere and hence lead to the deepening of the TOL. Based on the analysis of the multiple regression model, the thermal dynamical processes associated with the TP warming accounts for more than 50% of TCO decline during winter for the period 1979–2009. The solar variations during 1995–2009 further enlarge ozone decreases over the TP in the past decade. According to the CCM simulations, the increases in NOx emissions in East Asia and global tropospheric N2O mixing ratio for the period 1979–2009 contribute to no more than 20% reductions in TCO during this period

PI3Kγ is a molecular switch that controls immune suppression

Macrophages play critical, but opposite, roles in acute and chronic inflammation and cancer1,2,3,4,5. In response to pathogens or injury, inflammatory macrophages express cytokines that stimulate cytotoxic T cells, whereas macrophages in neoplastic and parasitic diseases express anti-inflammatory cytokines that induce immune suppression and may promote resistance to T cell checkpoint inhibitors1,2,3,4,5,6,7. Here we show that macrophage PI 3-kinase γ controls a critical switch between immune stimulation and suppression during inflammation and cancer. PI3Kγ signalling through Akt and mTor inhibits NFκB activation while stimulating C/EBPβ activation, thereby inducing a transcriptional program that promotes immune suppression during inflammation and tumour growth. By contrast, selective inactivation of macrophage PI3Kγ stimulates and prolongs NFκB activation and inhibits C/EBPβ activation, thus promoting an immunostimulatory transcriptional program that restores CD8+ T cell activation and cytotoxicity. PI3Kγ synergizes with checkpoint inhibitor therapy to promote tumour regression and increased survival in mouse models of cancer. In addition, PI3Kγ-directed, anti-inflammatory gene expression can predict survival probability in cancer patients. Our work thus demonstrates that therapeutic targeting of intracellular signalling pathways that regulate the switch between macrophage polarization states can control immune suppression in cancer and other disorders

Overexpression of a Common Wheat Gene TaSnRK2.8 Enhances Tolerance to Drought, Salt and Low Temperature in Arabidopsis

Drought, salinity and low temperatures are major factors limiting crop productivity and quality. Sucrose non-fermenting1-related protein kinase 2 (SnRK2) plays a key role in abiotic stress signaling in plants. In this study, TaSnRK2.8, a SnRK2 member in wheat, was cloned and its functions under multi-stress conditions were characterized. Subcellular localization showed the presence of TaSnRK2.8 in the cell membrane, cytoplasm and nucleus. Expression pattern analyses in wheat revealed that TaSnRK2.8 was involved in response to PEG, NaCl and cold stresses, and possibly participates in ABA-dependent signal transduction pathways. To investigate its role under various environmental stresses, TaSnRK2.8 was transferred to Arabidopsis under control of the CaMV-35S promoter. Overexpression of TaSnRK2.8 resulted in enhanced tolerance to drought, salt and cold stresses, further confirmed by longer primary roots and various physiological characteristics, including higher relative water content, strengthened cell membrane stability, significantly lower osmotic potential, more chlorophyll content, and enhanced PSII activity. Meanwhile, TaSnRK2.8 plants had significantly lower total soluble sugar levels under normal growing conditions, suggesting that TaSnRK2.8 might be involved in carbohydrate metabolism. Moreover, the transcript levels of ABA biosynthesis (ABA1, ABA2), ABA signaling (ABI3, ABI4, ABI5), stress-responsive genes, including two ABA-dependent genes (RD20A, RD29B) and three ABA-independent genes (CBF1, CBF2, CBF3), were generally higher in TaSnRK2.8 plants than in WT/GFP controls under normal/stress conditions. Our results suggest that TaSnRK2.8 may act as a regulatory factor involved in a multiple stress response pathways