Efficacy and safety of different chemotherapy regimens concurrent with radiotherapy in the treatment of locally advanced cervical cancer.

BACKGROUND: Evaluate the efficacy and safety of different chemotherapy regimens concurrent with radiotherapy in treating locally advanced cervical cancer (LACC). METHODS: Retrospective data was collected from LACC patients who were treated at our institution. These patients were categorized into three groups: the single-agent cisplatin (DDP) chemoradiotherapy group, the paclitaxel plus cisplatin (TP) chemoradiotherapy group, and the nanoparticle albumin-bound (nab-) paclitaxel combined with cisplatin (nPP) chemoradiotherapy group. The primary endpoints were overall survival (OS) and progression-free survival (PFS) and the secondary endpoints were objective response rate (ORR) and incidence of adverse events (AEs). RESULTS: A total of 124 patients were enrolled (32 in the DDP group, 41 in the TP group, and 51 in the nPP group). There were differences in OS (P = 0.041, HR 0.527, 95% CI 0.314-0.884) and PFS (P = 0.003, HR 0.517, 95% CI 0.343-0.779) between the three groups. Notably, the 2-year OS rate was significantly higher in the nPP group compared to the DDP group (92.2% vs. 85.4%, P = 0.012). The 2-year PFS rates showed a marked increase in the TP group (78.0% vs. 59.4%, P = 0.048) and the nPP group (88.2% vs. 59.4%, P = 0.001) relative to the DPP group, with multiple comparisons indicating that the 2-year PFS rate was significantly superior in the nPP group versus the DDP group (88.2% vs. 59.4%, P = 0.001). Moreover, the ORR was also significantly higher in the nPP group than in the DDP group (P = 0.013); and no statistically significant differences were found in the incidence of AEs among the groups (P > 0.05). CONCLUSIONS: In LACC treatment, the two cisplatin-based doublet chemotherapy regimens are associated with better outcomes, with the nab-paclitaxel plus cisplatin regimen showing better efficacy than the paclitaxel plus cisplatin regimen. Furthermore, the AEs associated with these regimens were deemed tolerable. These findings could provide a reference for the clinical treatment of LACC. However, further prospective studies are needed to verify it.

Clinical Implementation of Total-Body PET in China.

Total-body (TB) PET/CT is a groundbreaking tool that has brought about a revolution in both clinical application and scientific research. The transformative impact of TB PET/CT in the realms of clinical practice and scientific exploration has been steadily unfolding since its introduction in 2018, with implications for its implementation within the health care landscape of China. TB PET/CT's exceptional sensitivity enables the acquisition of high-quality images in significantly reduced time frames. Clinical applications have underscored its effectiveness across various scenarios, emphasizing the capacity to personalize dosage, scan duration, and image quality to optimize patient outcomes. TB PET/CT's ability to perform dynamic scans with high temporal and spatial resolution and to perform parametric imaging facilitates the exploration of radiotracer biodistribution and kinetic parameters throughout the body. The comprehensive TB coverage offers opportunities to study interconnections among organs, enhancing our understanding of human physiology and pathology. These insights have the potential to benefit applications requiring holistic TB assessments. The standard topics outlined in The Journal of Nuclear Medicine were used to categorized the reviewed articles into 3 sections: current clinical applications, scan protocol design, and advanced topics. This article delves into the bottleneck that impedes the full use of TB PET in China, accompanied by suggested solutions.

Radiomics analysis of intratumoral and different peritumoral regions from multiparametric MRI for evaluating HER2 status of breast cancer: A comparative study.

Purpose: To investigate the potential of radiomics signatures (RSs) from intratumoral and peritumoral regions on multiparametric magnetic resonance imaging (MRI) to noninvasively evaluate HER2 status in breast cancer. Method: In this retrospective study, 992 patients with pathologically confirmed breast cancers who underwent preoperative MRI were enrolled. The breast cancer lesions were segmented manually, and the intratumor region of interest (ROIIntra) was dilated by 2, 4, 6 and 8 mm (ROIPeri2mm, ROIPeri4mm, ROIPeri6mm, and ROIPeri8mm, respectively). Quantitative radiomics features were extracted from dynamic contrast-enhanced T1-weighted imaging (DCE-T1), fat-saturated T2-weighted imaging (T2) and diffusion-weighted imaging (DWI). A three-step procedure was performed for feature selection, and RSs were constructed using a support vector machine (SVM) to predict HER2 status. Result: The best single-area RSs for predicting HER2 status were DCE_Peri4mm-RS, T2_Peri4mm-RS, and DWI_Peri4mm-RS, yielding areas under the curve (AUCs) of 0.716 (95% confidence interval (CI), 0.648-0.778), 0.706 (95% CI, 0.637-0.768), and 0.719 (95% CI, 0.651-0.780), respectively, in the test set. The optimal RSs combining intratumoral and peritumoral regions for evaluating HER2 status were DCE-T1_Intra + DCE_Peri4mm-RS, T2_Intra + T2_Peri6mm-RS and DWI_Intra + DWI_Peri4mm-RS, with AUCs of 0.752 (95% CI, 0.686-0.810), 0.754 (95% CI, 0.688-0.812) and 0.725 (95% CI, 0.657-0.786), respectively, in the test set. Combining three sequences in the ROIIntra, ROIPeri2mm, ROIPeri4mm, ROIPeri6mm and ROIPeri8mm areas, the optimal RS was DCE-T1_Peri4mm + T2_Peri4mm + DWI_Peri4mm-RS, achieving an AUC of 0.795 (95% CI, 0.733-0.849) in the test set. Conclusion: This study systematically explored the influence of the intratumoral region, different peritumoral sizes and their combination in radiomics analysis for predicting HER2 status in breast cancer based on multiparametric MRI and found the optimal RS.

Phase-Dependent Magnetic Proximity Modulations on Valley Polarization and Splitting.

Proximate-induced magnetic interactions present a promising strategy for precise manipulation of valley degrees of freedom. Taking advantage of the splendid valleytronic platform of transition metal dichalcogenides, magnetic two-dimensional VSe2 with different phases are introduced to intervene in the spin of electrons and modulate their valleytronic properties. When constructing the heterostructures, 1T-VSe2/WX2 (X = S and Se) showcases significant improvement in the valley polarizations at room temperature, while 2H-VSe2/WX2 exhibits superior performance at low temperatures and demonstrates heightened sensitivity to the external magnetic field. Simultaneously, considerable valley splitting with a large geff factor up to -29.0 is observed in 2H-VSe2/WS2, while it is negligible in 1T-VSe2/WX2. First-principles calculations reveal a phase-dependent magnetic proximity mechanism on the valleytronic modulations, which is dominated by interfacial charge transfer in 1T-VSe2/WX2 and the proximity exchange field in 2H-VSe2/WX2 heterostructures. The effective control over valley degrees of freedom will bridge the valleytronic physics and devices, rendering enormous potential in the field of valley quantum applications.

Clinical study on the prediction of ALN metastasis based on intratumoral and peritumoral DCE-MRI radiomics and clinico-radiological characteristics in breast cancer.

Objective: To investigate the value of predicting axillary lymph node (ALN) metastasis based on intratumoral and peritumoral dynamic contrast-enhanced MRI (DCE-MRI) radiomics and clinico-radiological characteristics in breast cancer. Methods: A total of 473 breast cancer patients who underwent preoperative DCE-MRI from Jan 2017 to Dec 2020 were enrolled. These patients were randomly divided into training (n=378) and testing sets (n=95) at 8:2 ratio. Intratumoral regions (ITRs) of interest were manually delineated, and peritumoral regions of 3 mm (3 mmPTRs) were automatically obtained by morphologically dilating the ITR. Radiomics features were extracted, and ALN metastasis-related radiomics features were selected by the Mann-Whitney U test, Z score normalization, variance thresholding, K-best algorithm and least absolute shrinkage and selection operator (LASSO) algorithm. Clinico-radiological risk factors were selected by logistic regression and were also used to construct predictive models combined with radiomics features. Then, 5 models were constructed, including ITR, 3 mmPTR, ITR+3 mmPTR, clinico-radiological and combined (ITR+3 mmPTR+ clinico-radiological) models. The performance of models was assessed by sensitivity, specificity, accuracy, F1 score and area under the curve (AUC) of receiver operating characteristic (ROC), calibration curves and decision curve analysis (DCA). Results: A total of 2264 radiomics features were extracted from each region of interest (ROI), 3 and 10 radiomics features were selected for the ITR and 3 mmPTR, respectively. 5 clinico-radiological risk factors were selected, including lesion size, human epidermal growth factor receptor 2 (HER2) expression, vascular cancer thrombus status, MR-reported ALN status, and time-signal intensity curve (TIC) type. In the testing set, the combined model showed the highest AUC (0.839), specificity (74.2%), accuracy (75.8%) and F1 Score (69.3%) among the 5 models. DCA showed that it had the greatest net clinical benefit compared to the other models. Conclusion: The intra- and peritumoral radiomics models based on DCE-MRI could be used to predict ALN metastasis in breast cancer, especially for the combined model with clinico-radiological characteristics showing promising clinical application value.

[Research progress of novel functional materials in extraction of algal toxins].

Algal toxins are secondary metabolites produced by harmful algae; these metabolites are characterized with strong toxicity, diverse structure and bioaccumulation. Aquatic organisms that feed on harmful algae can accumulate algal toxins in their bodies, and the consumption of these organisms by humans can cause symptoms of paralysis, diarrhea, and even death. The onset of poisoning can occur within as little as 30 min; in many cases, no suitable antidote for algal toxins is available. Thus, algal toxins present significant threats to human health, the aquaculture industry, and aquatic ecosystems. Because the potential risks of algal toxins are a critical issue, these toxins have become a research hotspot. The water environment and various types of aquatic products should be monitored and analyzed to ensure their safety. However, because of possible matrix effects and the low content of algal toxins in actual samples, an efficient pretreatment method is necessary prior to instrumental analyses. Efficient sample pretreatment techniques can not only reduce or eliminate interferences from the sample matrix during analysis but also enrich the target analytes to meet the detection limit of the analytical instrument, thereby ensuring the sensitivity and accuracy of the detection method. In recent years, sample pretreatment techniques such as solid-phase extraction (SPE), solid-phase microextraction (SPME), magnetic SPE (MSPE), dispersive SPE (DSPE), and pipette tip-based SPE (PT-SPE) have gained wide attention in the field of algal-toxin separation and analysis. The performance of these pretreatment techniques largely depends on the characteristics of the extraction materials. Given the diverse physicochemical properties of algal toxins, including their different molecular sizes, hydrophobicity/hydrophilicity, and charges, the design and preparation of materials suitable for algal-toxin extraction is an essential undertaking. The optimal extraction material should be capable of reversible algal-toxin adsorption and preferably possess a porous structure with a large surface area to allow for high recovery rates and good interfacial contact with the toxins. Additionally, the extraction material should exhibit good chemical stability in the sample solution and elution solvent within the working pH range; otherwise, it may dissolve or lose its functional groups. Many research efforts have sought to develop novel adsorbent materials with these properties in the separation and analysis of algal toxins, focusing on carbon-based materials, metal organic frameworks (MOFs), covalent organic frameworks (COFs), molecularly imprinted polymers (MIPs), and their functionalized counterparts. Carbon-based materials, MOFs, and COFs have advantages such as large surface areas and abundant adsorption sites. These extraction materials are widely used in the separation and analysis of target substances in complex environmental, biological, and food samples owing to their excellent performance and unique microstructure. They are also the main adsorbents used for the extraction of algal toxins. These extraction materials play an essential role in the extraction of algal toxins, but they also present a number of limitations: (1) Carbon-based materials, MOFs, and COFs have relatively poor selective-adsorption ability towards target substances; (2) Most MOFs are unstable in aqueous solutions and challenging to apply during extraction from water-based sample solutions; (3) COFs mainly consist of lightweight elements, rendering them difficult to completely separate from sample solutions using centrifugal force, which limits their application range; (4) Although MIPs have good selectivity, issues such as template-molecule loss, slow mass-transfer rates, and low adsorption capacity must be addressed. Therefore, the design and preparation of novel functionalized extraction materials specifically tailored for algal toxins and studies on new composite extraction materials are highly desirable. This article collects representative literature from domestic and international research on algal-toxin analysis over the past decade, summarizes the relevant findings, categorizes the applications of novel functional materials in algal-toxin-extraction processes, and provides an outlook on their future development prospects.

Ginsenoside Rg3: A Review of its Anticancer Mechanisms and Potential Therapeutic Applications.

BACKGROUND: Traditional Chinese Medicine (TCM) has a long history of treating various diseases and is increasingly being recognized as a complementary therapy for cancer. A promising natural compound extracted from the Chinese herb ginseng is ginsenoside Rg3, which has demonstrated significant anticancer effects. It has been tested in a variety of cancers and tumors and has proven to be effective in suppressing cancer. OBJECTIVE: This work covers various aspects of the role of ginsenoside Rg3 in cancer treatment, including its biological functions, key pathways, epigenetics, and potential for combination therapies, all of which have been extensively researched and elucidated. The study aims to provide a reference for future research on ginsenoside Rg3 as an anticancer agent and a support for the potential application of ginsenoside Rg3 in cancer treatment.

Amide proton transfer-weighted imaging and stretch-exponential model DWI based 18F-FDG PET/MRI for differentiation of benign and malignant solitary pulmonary lesions.

OBJECTIVES: To differentiate benign and malignant solitary pulmonary lesions (SPLs) by amide proton transfer-weighted imaging (APTWI), mono-exponential model DWI (MEM-DWI), stretched exponential model DWI (SEM-DWI), and 18F-FDG PET-derived parameters. METHODS: A total of 120 SPLs patients underwent chest 18F-FDG PET/MRI were enrolled, including 84 in the training set (28 benign and 56 malignant) and 36 in the test set (13 benign and 23 malignant). MTRasym(3.5 ppm), ADC, DDC, α, SUVmax, MTV, and TLG were compared. The area under receiver-operator characteristic curve (AUC) was used to assess diagnostic efficacy. The Logistic regression analysis was used to identify independent predictors and establish prediction model. RESULTS: SUVmax, MTV, TLG, α, and MTRasym(3.5 ppm) values were significantly lower and ADC, DDC values were significantly higher in benign SPLs than malignant SPLs (all P < 0.01). SUVmax, ADC, and MTRasym(3.5 ppm) were independent predictors. Within the training set, the prediction model based on these independent predictors demonstrated optimal diagnostic efficacy (AUC, 0.976; sensitivity, 94.64%; specificity, 92.86%), surpassing any single parameter with statistical significance. Similarly, within the test set, the prediction model exhibited optimal diagnostic efficacy. The calibration curves and DCA revealed that the prediction model not only had good consistency but was also able to provide a significant benefit to the related patients, both in the training and test sets. CONCLUSION: The SUVmax, ADC, and MTRasym(3.5 ppm) were independent predictors for differentiation of benign and malignant SPLs, and the prediction model based on them had an optimal diagnostic efficacy.

Short-term responses of temperate and subarctic marine diatoms to Irgarol 1051 and UV radiation: Insights into temperature interactions.

Phytoplankton face numerous pressures resulting from chemical and physical stressors, primarily induced by human activities. This study focuses on investigating the interactive effects of widely used antifouling agent Irgarol 1051 and UV radiation on the photo-physiology of marine diatoms from diverse latitudes, within the context of global warming. Our findings clearly shown that both Irgarol and UV radiation have a significant inhibitory impact on the photochemical performance of the three diatoms examined, with Irgarol treatment exhibiting more pronounced effects. In the case of the two temperate zone diatoms, we observed a decrease in the inhibition induced by Irgarol 1051 and UVR as the temperature increased up to 25°C. Similarly, for the subarctic species, an increase in temperature resulted in a reduction in the inhibition caused by Irgarol and UVR. These results suggest that elevated temperatures can mitigate the short-term inhibitory effects of both Irgarol and UVR on diatoms. Furthermore, our data indicate that increased temperature could significantly interact with UVR or Irgarol for temperate diatoms, while this was not the case for cold water diatoms, indicating temperate and subarctic diatoms may respond differentially under global warming.

Joint Exposure to Ambient Air Pollutants, Genetic Risk, and Ischemic Stroke: A Prospective Analysis in UK Biobank.

BACKGROUND: Our primary objective was to assess the association between joint exposure to various air pollutants and the risk of ischemic stroke (IS) and the modification of the genetic susceptibility. METHODS: This observational cohort study included 307 304 British participants from the United Kingdom Biobank, who were stroke-free and possessed comprehensive baseline data on genetics, air pollutant exposure, alcohol consumption, and dietary habits. All participants were initially enrolled between 2006 and 2010 and were followed up until 2022. An air pollution score was calculated to assess joint exposure to 5 ambient air pollutants, namely particulate matter with diameters equal to or <2.5 µm, ranging from 2.5 to 10 µm, equal to or <10 µm, as well as nitrogen oxide and nitrogen dioxide. To evaluate individual genetic risk, a polygenic risk score for IS was calculated for each participant. We adjusted for demographic, social, economic, and health covariates. Cox regression models were utilized to estimate the associations between air pollution exposure, polygenic risk score, and the incidence of IS. RESULTS: Over a median follow-up duration of 13.67 years, a total of 2476 initial IS events were detected. The hazard ratios (95% CI) of IS for per 10 µg/m3 increase in particulate matter with diameters equal to or <2.5 µm, ranging from 2.5 to 10 µm, equal to or <10 µm, nitrogen dioxide, and nitrogen oxide were 1.73 (1.33-2.14), 1.24 (0.88-1.70), 1.13 (0.89-1.33), 1.03 (0.98-1.08), and 1.04 (1.02-1.07), respectively. Furthermore, individuals in the highest quintile of the air pollution score exhibited a 29% to 66% higher risk of IS compared with those in the lowest quintile. Notably, participants with both high polygenic risk score and air pollution score had a 131% (95% CI, 85%-189%) greater risk of IS than participants with low polygenic risk score and air pollution score. CONCLUSIONS: Our findings suggested that prolonged joint exposure to air pollutants may contribute to an increased risk of IS, particularly among individuals with elevated genetic susceptibility to IS.

Salvianolic Acid B Ameliorated Chemotherapeutic Injury of Cardiac Myocytes through the Nrf2/ARE Signaling Pathway.

BACKGROUND: Cardiotoxicity has been corroborated to be the toxic influence of cisplatin (CDDP). Oxidative stress and cardiomyocyte apoptosis play a vital part in cardiotoxicity induced by CDDP. Salvianolic acid Salvianolic acid B (SalB) is a monomeric component of Salvia miltiorrhiza, which has antioxidant and anti-inflammatory influences. In this research, we explored the mechanism of SalB in cardiotoxicity induced by CDDP. METHOD: 36 Wistar rats were separated into sham subgroup, CDDP (10 mg/kg) subgroup, CDDP (10 mg/kg) + SalB (1 µM) subgroup at random, CDDP (10 mg/kg) + SalB (5 µM) subgroup and CDDP (10 mg/kg) + SalB (10 µM) subgroup, Nicotinic Acid Riboside (NAR, 5 µM), with 6 rats in each subgroup. The cardiac function of rats in each subgroup was estimated by echocardiography, and hematoxylin-eosin (HE) staining and Masson staining corroborated the pathological changes of cardiac tissue. Biochemical kits were utilized for detecting the lactate dehydrogenase (LDH), creatine kinase (CK), interleukin-1ß (IL-1ß), IL-18, and caspase-1 concentrations in serum, superoxide dismutase (SOD), and malondialdehyde (MDA) in myocardial tissue, TdT-mediated dUTP Nick-End Labeling (TUNEL) staining, and flow cytometry were utilized for estimating the apoptosis level in myocardial tissue, western blot was used for estimating caspase-3, Bcl2-Associated X (Bax) levels in myocardial tissue and proteins levels related to Nuclear factor E2 related factor 2 (Nrf2) signal pathway. RESULTS: CDDP-induced cardiac dysfunction, myocardial injury, boosted LDH and CK levels in serum (p < 0.05), memorably increased oxidative stress level in myocardial tissue (p < 0.05), boosted inflammatory response (p < 0.05), boosted apoptosis rate of cardiomyocytes (p < 0.05), and declined the Nrf2, NAD(P)H quinone oxidoreductase 1 (NQO1), heme oxygenase 1 (HO-1) protein levels (p < 0.05). Interestingly, SalB remedy could alleviate the changes caused by CDDP in the above parameters, significantly decrease the level of myocardial oxidative stress and apoptosis (p < 0.05). CONCLUSIONS: SalB ameliorates the injury of cardiomyocytes induced by chemotherapy through oxidative stress mediated by the Nrf2/antioxidant response element (ARE) signal pathway.

Development of a novel senescence-related gene signature to predict clinical outcomes, immune landscape, and chemotherapeutic sensitivity in oral squamous cell carcinoma.

BACKGROUND: Cellular senescence significantly associates with tumor initiation, progression, and therapeutic response across multiple cancers. Here, we sought to develop a novel senescence-related genes (SRGs)-derived signature for oral squamous cell carcinoma (OSCC) prognostication and therapeutic response prediction. METHODS: OSCC-specific SRG prognostic signature was established with univariate Cox regression, Kaplan-Meier survival, and LASSO-penalized multivariate Cox regression analyses. A SRG nomogram integrating this signature and selected clinicopathological parameters were constructed by multivariate Cox regression. SiRNA-mediated gene knockdown was exploited to validate its function in vitro. The utilities of SRG signature in predicting immune status and chemotherapeutic sensitivities were analyzed. RESULTS: The prognostic performance of SRG signature/nomogram was satisfactory in multiple independent cohorts. CDK1 knockdown induced senescence phenotype in vitro. Moreover, SRG signature scores negatively correlated with tumor-infiltrating immune cells and associated with multiple chemotherapeutic drug sensitivities. CONCLUSIONS: Our results established SRG-derived signature/nomogram as powerful predictors for prognosis and chemotherapeutic response for OSCC.

An Efficient and Fast Method for Labeling and Analyzing Mouse Glomeruli.

The glomeruli are fundamental units in the kidney; hence, studying the glomeruli is pivotal for understanding renal function and pathology. Biological imaging provides intuitive information; thus, it is of great significance to label and observe the glomeruli. However, the glomeruli observation methods currently in use require complicated operations, and the results may lose label details or three-dimensional (3D) information. The clear, unobstructed brain imaging cocktails and computational analysis (CUBIC) tissue clearing technology has been widely used in renal research, allowing for more accurate detection and deeper detection depth. We found that mouse glomeruli can be rapidly and effectively labeled by tail vein injection of medium molecular weight FITC-Dextran followed by the CUBIC clearing method. The cleared mouse kidney could be scanned by a light-sheet microscope (or a confocal microscope when sliced) to obtain three-dimensional image stacks of all the glomeruli in the entire kidney. Processed with appropriate software, the glomeruli signals could be easily digitized and further analyzed to measure the number, volume, and frequency of the glomeruli.

Synthesis of gadolinium-enhanced glioma images on multisequence magnetic resonance images using contrastive learning.

BACKGROUND: Gadolinium-based contrast agents are commonly used in brain magnetic resonance imaging (MRI), however, they cannot be used by patients with allergic reactions or poor renal function. For long-term follow-up patients, gadolinium deposition in the body can cause nephrogenic systemic fibrosis and other potential risks. PURPOSE: Developing a new method of enhanced image synthesis based on the advantages of multisequence MRI has important clinical value for these patients. In this paper, an end-to-end synthesis model structure similarity index measure (SSIM)-based Dual Constrastive Learning with Attention (SDACL) based on contrastive learning is proposed to synthesize contrast-enhanced T1 (T1ce) using three unenhanced MRI images of T1, T2, and Flair in patients with glioma. METHODS: The model uses the attention-dilation generator to enlarge the receptive field by expanding the residual blocks and to strengthen the feature representation and context learning of multisequence MRI. To enhance the detail and texture performance of the imaged tumor area, a comprehensive loss function combining patch-level contrast loss and structural similarity loss is created, which can effectively suppress noise and ensure the consistency of synthesized images and real images. RESULTS: The normalized root-mean-square error (NRMSE), peak signal-to-noise ratio (PSNR), and SSIM of the model on the independent test set are 0.307  ± $\pm$  0.12, 23.337  ± $\pm$  3.21, and 0.881  ± $\pm$  0.05, respectively. CONCLUSIONS: Results show this method can be used for the multisequence synthesis of T1ce images, which can provide valuable information for clinical diagnosis.

Non-invasive quantification of the brain [18F]FDG-PET using inferred blood input function learned from total-body data with physical constraint.

Full quantification of brain PET requires the blood input function (IF), which is traditionally achieved through an invasive and time-consuming arterial catheter procedure, making it unfeasible for clinical routine. This study presents a deep learning based method to estimate the input function (DLIF) for a dynamic brain FDG scan. A long short-term memory combined with a fully connected network was used. The dataset for training was generated from 85 total-body dynamic scans obtained on a uEXPLORER scanner. Time-activity curves from 8 brain regions and the carotid served as the input of the model, and labelled IF was generated from the ascending aorta defined on CT image. We emphasize the goodness-of-fitting of kinetic modeling as an additional physical loss to reduce the bias and the need for large training samples. DLIF was evaluated together with existing methods in terms of RMSE, area under the curve, regional and parametric image quantifications. The results revealed that the proposed model can generate IFs that closer to the reference ones in terms of shape and amplitude compared with the IFs generated using existing methods. All regional kinetic parameters calculated using DLIF agreed with reference values, with the correlation coefficient being 0.961 (0.913) and relative bias being 1.68±8.74% (0.37±4.93%) for Ki (K1). In terms of the visual appearance and quantification, parametric images were also highly identical to the reference images. In conclusion, our experiments indicate that a trained model can infer an image-derived IF from dynamic brain PET data, which enables subsequent reliable kinetic modeling.

Simultaneously Regulated Highly Polarized and Long-Lived Valley Excitons in WSe2/GaN Heterostructures.

Interlayer excitons, with prolonged lifetimes and tunability, hold potential for advanced optoelectronics. Previous research on the interlayer excitons has been dominated by two-dimensional heterostructures. Here, we construct WSe2/GaN composite heterostructures, in which the doping concentration of GaN and the twist angle of bilayer WSe2 are employed as two ingredients for the manipulation of exciton behaviors and polarizations. The exciton energies in monolayer WSe2/GaN can be regulated continuously by the doping levels of the GaN substrate, and a remarkable increase in the valley polarizations is achieved. Especially in a heterostructure with 4°-twisted bilayer WSe2, a maximum polarization of 38.9% with a long lifetime is achieved for the interlayer exciton. Theoretical calculations reveal that the large polarization and long lifetime are attributed to the high exciton binding energy and large spin flipping energy during depolarization in bilayer WSe2/GaN. This work introduces a distinctive member of the interlayer exciton with a high degree of polarization and a long lifetime.

Quad-Net: Quad-Domain Network for CT Metal Artifact Reduction.

Metal implants and other high-density objects in patients introduce severe streaking artifacts in CT images, compromising image quality and diagnostic performance. Although various methods were developed for CT metal artifact reduction over the past decades, including the latest dual-domain deep networks, remaining metal artifacts are still clinically challenging in many cases. Here we extend the state-of-the-art dual-domain deep network approach into a quad-domain counterpart so that all the features in the sinogram, image, and their corresponding Fourier domains are synergized to eliminate metal artifacts optimally without compromising structural subtleties. Our proposed quad-domain network for MAR, referred to as Quad-Net, takes little additional computational cost since the Fourier transform is highly efficient, and works across the four receptive fields to learn both global and local features as well as their relations. Specifically, we first design a Sinogram-Fourier Restoration Network (SFR-Net) in the sinogram domain and its Fourier space to faithfully inpaint metal-corrupted traces. Then, we couple SFR-Net with an Image-Fourier Refinement Network (IFR-Net) which takes both an image and its Fourier spectrum to improve a CT image reconstructed from the SFR-Net output using cross-domain contextual information. Quad-Net is trained on clinical datasets to minimize a composite loss function. Quad-Net does not require precise metal masks, which is of great importance in clinical practice. Our experimental results demonstrate the superiority of Quad-Net over the state-of-the-art MAR methods quantitatively, visually, and statistically. The Quad-Net code is publicly available at https://github.com/longzilicart/Quad-Net.

The role of dynamic, static, and delayed total-body PET imaging in the detection and differential diagnosis of oncological lesions.

OBJECTIVES: Commercialized total-body PET scanners can provide high-quality images due to its ultra-high sensitivity. We compared the dynamic, regular static, and delayed 18F-fluorodeoxyglucose (FDG) scans to detect lesions in oncologic patients on a total-body PET/CT scanner. MATERIALS & METHODS: In all, 45 patients were scanned continuously for the first 60 min, followed by a delayed acquisition. FDG metabolic rate was calculated from dynamic data using full compartmental modeling, whereas regular static and delayed SUV images were obtained approximately 60- and 145-min post-injection, respectively. The retention index was computed from static and delayed measures for all lesions. Pearson's correlation and Kruskal-Wallis tests were used to compare parameters. RESULTS: The number of lesions was largely identical between the three protocols, except MRFDG and delayed images on total-body PET only detected 4 and 2 more lesions, respectively (85 total). FDG metabolic rate (MRFDG) image-derived contrast-to-noise ratio and target-to-background ratio were significantly higher than those from static standardized uptake value (SUV) images (P < 0.01), but this is not the case for the delayed images (P > 0.05). Dynamic protocol did not significantly differentiate between benign and malignant lesions just like regular SUV, delayed SUV, and retention index. CONCLUSION: The potential quantitative advantages of dynamic imaging may not improve lesion detection and differential diagnosis significantly on a total-body PET/CT scanner. The same conclusion applied to delayed imaging. This suggested the added benefits of complex imaging protocols must be weighed against the complex implementation in the future. CLINICAL RELEVANCE: Total-body PET/CT was known to significantly improve the PET image quality due to its ultra-high sensitivity. However, whether the dynamic and delay imaging on total-body scanner could show additional clinical benefits is largely unknown. Head-to-head comparison between two protocols is relevant to oncological management.

Manipulations of Electronic and Spin States in Co-Quantum Dot/WS2 Heterostructure on a Metal-Dielectric Composite Substrate by Controlling Interfacial Carriers.

Charge and spin are two intrinsic attributes of carriers governing almost all of the physical processes and operation principles in materials. Here, we demonstrate the manipulation of electronic and spin states in designed Co-quantum dot/WS2 (Co-QDs/WS2) heterostructures by employing a metal-dielectric composite substrate and via scanning tunneling microscope. By repeatedly scanning under a unipolar bias, switching the bias polarity, or applying a pulse through nonmagnetic or magnetic tips, the Co-QDs morphologies exhibit a regular and reproducible transformation between bright and dark dots. First-principles calculations reveal that these tunable characters are attributed to the variation of density of states and the transition of magnetic anisotropy energy induced by carrier accumulation. It also suggests that the metal-dielectric composite substrate is successful in creating the interfacial potential for carrier accumulation and realizes the electrically controllable modulations. These results will promote the exploration of electron-matter interactions in quantum systems and provide an innovative way to facilitate the development of spintronics.

Performance of node reporting and data system (node-RADS): a preliminary study in cervical cancer.

BACKGROUND: Node Reporting and Data System (Node-RADS) was proposed and can be applied to lymph nodes (LNs) across all anatomical sites. This study aimed to investigate the diagnostic performance of Node-RADS in cervical cancer patients. METHODS: A total of 81 cervical cancer patients treated with radical hysterectomy and LN dissection were retrospectively enrolled. Node-RADS evaluations were performed by two radiologists on preoperative MRI scans for all patients, both at the LN level and patient level. Chi-square and Fisher's exact tests were employed to evaluate the distribution differences in size and configuration between patients with and without LN metastasis (LNM) in various regions. The receiver operating characteristic (ROC) and the area under the curve (AUC) were used to explore the diagnostic performance of the Node-RADS score for LNM. RESULTS: The rates of LNM in the para-aortic, common iliac, internal iliac, external iliac, and inguinal regions were 7.4%, 9.3%, 19.8%, 21.0%, and 2.5%, respectively. At the patient level, as the NODE-RADS score increased, the rate of LNM also increased, with rates of 26.1%, 29.2%, 42.9%, 80.0%, and 90.9% for Node-RADS scores 1, 2, 3, 4, and 5, respectively. At the patient level, the AUCs for Node-RADS scores > 1, >2, > 3, and > 4 were 0.632, 0.752, 0.763, and 0.726, respectively. Both at the patient level and LN level, a Node-RADS score > 3 could be considered the optimal cut-off value with the best AUC and accuracy. CONCLUSIONS: Node-RADS is effective in predicting LNM for scores 4 to 5. However, the proportions of LNM were more than 25% at the patient level for scores 1 and 2, which does not align with the expected very low and low probability of LNM for these scores.