ENDOLUMINAL RADIOFREQUENCY ABLATION WITH STENTING VS STENTING ONLY IN PATIENTS WITH MALIGNANT BILIARY OBSTRUCTION: A META-ANALYSIS OF RANDOMISED TRIALS.

INTRODUCTION: Endoluminal radiofrequency ablation (RFA) is a palliative treatment for patients suffering from malignant biliary obstruction. We aimed to conduct a meta-analysis to evaluate the impact of RFA on stent patency, patient survival, and adverse events. METHODS: Major databases were searched through November 2023 for patients who underwent stenting with or without RFA for extra-hepatic malignant biliary obstruction. A random effects model was employed for analysis and results conveyed using relative risk ratio with 95% confidence interval. RESULTS: Nine RCTs involving 750 subjects (n=374 RFA plus stent vs. n=376 stent only) with malignant biliary obstruction were included. Meta-analysis revealed similar risks of stent patency at 3 months (RR = 1.01; 95% CI [0.92 - 1.11], I2=4% for RFA plus stenting vs. stent only). Meta-analysis showed improved survival at 6 months (RR = 0.84; 95% CI [0.73 - 0.96], I2=21%, P=0.01 for RFA plus stenting vs. stent only). Subgroup analysis comparing plastic vs uncovered metal stents showed that stent patency was unaffected at 3 months (RR = 1.06; 95% CI [0.91 - 1.23]; I2=17%). Subgroup analysis showed that patients with cholangiocarcinoma experienced an overall survival benefit with RFA plus stenting vs. stent only (P<0.001), however, stent patency remained unaffected (P=0.08). An increased incidence of cholecystitis was noted with RFA plus stent vs. stent only (5.1%; 95% CI [3.1% - 7.8%] vs 0.3%; 95% CI [0.01% - 1.5%], respectively). CONCLUSION: Combining endoluminal RFA and stenting may improve overall survival in patients with malignant biliary obstruction. RFA did not impact stent patency significantly.

MAMS: matrix and analysis metadata standards to facilitate harmonization and reproducibility of single-cell data.

Many datasets are being produced by consortia that seek to characterize healthy and disease tissues at single-cell resolution. While biospecimen and experimental information is often captured, detailed metadata standards related to data matrices and analysis workflows are currently lacking. To address this, we develop the matrix and analysis metadata standards (MAMS) to serve as a resource for data centers, repositories, and tool developers. We define metadata fields for matrices and parameters commonly utilized in analytical workflows and developed the rmams package to extract MAMS from single-cell objects. Overall, MAMS promotes the harmonization, integration, and reproducibility of single-cell data across platforms.

Nutritional Partitioning among Sympatric Ungulates in Eastern Tibet.

Wild ungulates play crucial roles in maintaining the structure and function of local ecosystems. The alpine musk deer (Moschus chrysogaste), white-lipped deer (Przewalskium albirostris), and red serow (Capricornis rubidus) are widely distributed throughout the Nyenchen Tanglha Mountains of Tibet. However, research on the mechanisms underlying their coexistence in the same habitat remains lacking. This study aimed to investigate the mechanisms underlying the coexistence of these species based on their dietary preferences through DNA barcoding using the fecal samples of these animals collected from the study area. These species consume a wide variety of food types. Alpine musk deer, white-lipped deer, and red serow consume plants belonging to 74 families and 114 genera, 62 families and 122 genera, and 63 families and 113 genera, respectively. Furthermore, significant differences were observed in the nutritional ecological niche among these species, primarily manifested in the differentiation of food types and selection of food at the genus level. Owing to differences in social behavior, body size, and habitat selection, these three species further expand their differentiation in resource selection, thereby making more efficient use of environmental resources. Our findings indicate these factors are the primary reasons for the stable coexistence of these species.

Effects of regulating gut microbiota by electroacupuncture in the chronic unpredictable mild stress rat model.

OBJECTIVE: This study aims to investigate the effect of electroacupuncture (EA) treatment on depression, and the potential molecular mechanism of EA in depression-like behaviors rats. METHODS: A total of 40 male Sprague Dawley rats were divided into three groups: normal control, chronic unpredictable mild stress (CUMS), and EA (CUMS + EA). The rats in CUMS and EA groups underwent chronic stress for 10 weeks, and EA group rats received EA treatment for 4 weeks starting from week 7. Body weight and behavioral tests, including the sucrose preference test (SPT), the forced swimming test (FST), and the open field test (OFT) were monitored. Gut microbiota composition was assessed via 16S rDNA sequencing, and lipid metabolism was analyzed by using UPLC-Q-TOF/MS technology. RESULTS: In comparison to CUMS group, EA could improve the behavior including bodyweight, immovability time, sucrose preference index, crossing piece index and rearing times index. After 4 weeks of EA treatment, 5-HT in hippocampus, serum and colon of depressive rats were simultaneously increased, indicating a potential alleviation of depression-like behaviors. In future studies revealed that EA could regulate the distribution and functions of gut microbiota, and improve the intestinal barrier function of CUMS rats. The regulation of intestinal microbial homeostasis by EA may further affect lipid metabolism in CUMS rats, and thus play an antidepressant role. CONCLUSION: This study suggested that EA has potential antidepressant effects by regulating gut microbiota composition and abundance, subsequently affecting lipid metabolism.

A Strategy of Killing Two Birds With One Stone for Blocking Drug Resistance Spread With Engineered Bdellovibrio bacteriovorus.

Drug-resistant pathogens significantly threaten human health and life. Simply killing drug-resistant pathogens cannot effectively eliminate their threat since the drug-resistant genes (DRGs) released from dead drug-resistant pathogens are difficult to eliminate and can further spread via horizontal gene transfer, leading to the spread of drug resistance. The development of antibacterial materials with sterilization and DRGs cleavage activities is highly crucial. Herein, a living system, Ce-PEA@Bdello, is fabricated with bacterial killing and DRGs cleavage activities for blocking bacterial drug resistance dissemination by engineered Bdellovibrio bacteriovorus (Bdello). Ce-PEA@Bdello is obtained by engineering Bdello with dopamine and a multinuclear cerium (IV) complex. Ce-PEA@Bdello can penetrate and eliminate kanamycin-resistant P. aeruginosa (KanR) biofilms via the synergistic effect of predatory Bdello and photothermal polydopamine under near-infrared light. Additionally, the DNase-mimicking ability of Ce-PEA@Bdello endows it with genome and plasmid DNA cleavage ability. An in vivo study reveals that Ce-PEA@Bdello can eliminate P. aeruginosa (KanR) and cleave DRGs in scald/burn infected wounds to block the spread of drug resistance and accelerate wound healing. This bioactive system constructed from natural living materials offers a promising means for blocking the spread of drug resistance.

Prospective Comparison of 2D and 3D T2-Weighted Imaging in Multiparametric MRI for Assessing Muscle Invasion Accuracy Using VI-RADS in Bladder Cancer.

RATIONALE AND OBJECTIVES: T2-weighted imaging (T2WI) is an essential sequence for assessing the staging of bladder cancer. This study aimed to compare the image quality and diagnostic performance of three-dimensional (3D) and two-dimensional (2D) T2WI in diagnosing muscle invasion of bladder cancer using Vesical Imaging Reporting and Data System (VI-RADS). MATERIALS AND METHODS: Between August 2022 and May 2023, 101 participants with bladder cancer underwent multiparametric MRI including 3D and 2D T2WI. Two radiologists independently reviewed 2D and 3D T2WI, evaluating image quality and muscle invasion based on VI-RADS scoring. The paired Wilcoxon signed-rank test assessed the differences between 2D and 3D T2WI. The areas under the receiver operating characteristic curve (AUCs) were utilized to compare the diagnostic performance. RESULTS: 3D T2WI demonstrated significantly superior overall image quality scores with less artifacts than 2D T2WI. Compared to 2D T2WI, 3D T2WI categories had significantly higher AUC for both readers (reader 1: 0.937 vs. 0.909, p = .02; reader 2: 0.923 vs.0.884, p = .04). The VI-RADS score of 3D MR protocol had higher accuracy than 2D MR protocol (reader 1: 0.931 vs. 0.921, p = .02; reader 2: 0.931 vs. 0.911, p = .02). However, there were no significant differences in AUC values of VI-RADS categories between 2D and 3D MR protocol (all p > 0.05). CONCLUSION: In assessing muscle invasion of bladder cancer, 3D T2WI exhibited superior overall image quality and diagnostic performance than 2D T2WI. However, 3D T2WI did not significantly improve the diagnostic performance of VI-RADS.

Proprotein Convertase Subtilisin/Kexin Type 9 Inhibitor Improves the Vascular Function of Arteriovenous Fistula in Rats with Hyperglycemia.

Objectives: Few evidence-based medications to improve the primary patency of arteriovenous fistulas in patients with diabetes who require hemodialysis are available. We investigated whether proprotein convertase subtilisin/kexin type 9 inhibitors (PCSK9i) could improve arteriovenous fistula function through pleiotropic effects in a rat model of hyperglycemia. Methods: Ex vivo effects of PCSK9i on the aorta of Sprague-Dawley (SD) rats were investigated using an organ bath system. For in vivo experiments, an abdominal aortocaval (AC) fistula was generated in SD rats (200-250 g) after inducing hyperglycemia through streptozotocin administration (80 mg/kg, intraperitoneal). Alirocumab (50 mg/kg/week, subcutaneous) was administered on the day of fistula surgery and day 7. Echocardiography, blood flow through the aorta-limb, vasomotor reactivity, and serum biochemistry were examined on D14. Furthermore, enzyme-linked immunosorbent assay and immunoblotting were performed. Results: PCSK9i induced aorta relaxation ex vivo through a potassium channel-associated mechanism. PCSK9i significantly improved blood flow and preserved endothelial function without changes in cardiac function and serum lipid levels in rats with hyperglycemia. The levels of lectin-like oxidized low-density lipoprotein receptor-1, superoxide dismutase, cyclooxygenase-2, caspase-1, and interleukin-1ß were significantly reduced in the treatment group. PCSK9i decreased the ratio of phosphorylated to total p38 mitogen-activated protein kinase and extracellular signal-regulated kinase in the aorta of rats with hyperglycemia. Conclusions: Short-term treatment with PCSK9i preserved endothelial function, induced vascular dilatation, and increased blood flow in the AC fistula of rats with hyperglycemia. The pleiotropic mechanisms were associated with the suppression of oxidative stress and tissue inflammation during hyperglycemia.

Esophageal cancer mortality disparities between Black and White adults in the United States, 1999-2020: insights from CDC-WONDER.

BACKGROUND AND AIM: Esophageal cancer significantly contributes to US cancer mortality, with notable racial disparities. This study aims to provide updated esophageal cancer mortality trends among Black and White adults from 1999 to 2020. METHODS: CDC-WONDER was used to identify Black and White adults in the United States from 1999 to 2020. We calculated age-standardized mortality rates, absolute rate differences, and rate ratios to compare the mortality differences between these populations. RESULTS: From 1999 to 2020 in the United States, there were 303 267 esophageal cancer deaths, with significant racial disparities. The age-adjusted mortality rate for Black adults fell from 6.52 to 2.62 per 100 000, while for White adults, it declined from 4.19 to 3.97 per 100 000, narrowing the racial mortality gap. Gender-wise, the study showed a decrease in the mortality rate from 3.31 to 2.29 per 100 000 in Black women, but an increase from 1.52 to 1.99 per 100 000 in White women. Among young men, the rate dropped in Black men from 12.82 to 6.26 per 100 000 but rose in White men from 9.90 to 10.57 per 100 000. Regionally, Black adults in the Midwest and South initially had higher mortality rates than Whites, but this gap reduced over time. By 2020, Black men had lower mortality rates across all regions. CONCLUSIONS: Over the last two decades, age-adjusted esophageal cancer mortality decreased in Black adults but stabilized in White adults, reflecting distinct cancer trends and risk factors. The study highlights the importance of tailored public health strategies for healthcare access and risk factor management.

The Effectiveness of On-Demand Health Education Systems in Assisting the Nursing Workload.

This article explores the "On-Demand Health Education System" in healthcare, highlighting its role in enhancing nursing efficiency and quality. Using a database, it allows nurses to provide tailored education via QR codes for patients and families. Key findings show its positive impact on education quality and efficiency, though improvements are needed in user interface and accessibility for certain groups like the elderly. Future enhancements should focus on user experience and expanding accessibility, acknowledging the potential of such systems in medical education with technological advancement.

Effectiveness of Using Clinical Decision Support System in Nursing Records.

This study evaluates the impact of Clinical Decision Support System (CDSS) integration into the Nursing Information System 2.0 on nursing records and nurse satisfaction. Longitudinal data collection employs questionnaires and nursing records audits. Findings show improved electronic signature integration and nursing problem identification, benefiting real-time patient information access and record completeness. Younger, less experienced, highly educated nurses exhibit higher CDSS usage and acceptance. Overall, 80.2% agreement rate confirms CDSS's positive impact, highlighting the importance of user effectiveness evaluation in system implementation for nursing innovation.

Clinical trial of two-step photodynamic therapy for reduced pain in the treatment of precancerous squamous lesions (actinic keratoses).

BACKGROUND: Pain associated with aminolevulinic acid photodynamic therapy (ALA-PDT) for the treatment of facial dermatoses results in low patient compliance. Two-step photodynamic therapy (two-step PDT) may improve comfort by optimizing light amplitude and exposure time. OBJECTIVE: To investigate the efficacy of two-step PDT in reducing the pain generated during the treatment of facial skin disorders. METHODS: Twenty-six patients with AK were randomly divided into two groups; the experimental group was treated with two-step photodynamic therapy and the control group was treated with conventional photodynamic therapy. The pain intensity of the patients at different times was assessed using the pain numerical rating scale (NRS). RESULTS: A total of 26 patients completed three ALA-PDT treatments, 13 and 13 patients in each group, respectively. The mean NRS scores of patients in the experimental group (3.28±1.41, 3.33±1.43, 3.42±1.78) were lower than those of the control group (5.00±1.94, 5.09±1.86, 4.86±1.64) on each occasion. The incidence of certain adverse reactions was lower in the experimental group than in the control group. There was no difference between the two groups in terms of clinical outcome, recurrence rate and patient satisfaction. CONCLUSION: Two-step photodynamic therapy can reduce pain and the incidence of some adverse reactions, but does not affect clinical efficacy, recurrence rate and patient satisfaction.

Super-resolution diffractive neural network for all-optical direction of arrival estimation beyond diffraction limits.

Wireless sensing of the wave propagation direction from radio sources lays the foundation for communication, radar, navigation, etc. However, the existing signal processing paradigm for the direction of arrival estimation requires the radio frequency electronic circuit to demodulate and sample the multichannel baseband signals followed by a complicated computing process, which places the fundamental limit on its sensing speed and energy efficiency. Here, we propose the super-resolution diffractive neural networks (S-DNN) to process electromagnetic (EM) waves directly for the DOA estimation at the speed of light. The multilayer meta-structures of S-DNN generate super-oscillatory angular responses in local angular regions that can perform the all-optical DOA estimation with angular resolutions beyond the diffraction limit. The spatial-temporal multiplexing of passive and reconfigurable S-DNNs is utilized to achieve high-resolution DOA estimation over a wide field of view. The S-DNN is validated for the DOA estimation of multiple radio sources over 5 GHz frequency bandwidth with estimation latency over two to four orders of magnitude lower than the state-of-the-art commercial devices in principle. The results achieve the angular resolution over an order of magnitude, experimentally demonstrated with four times, higher than diffraction-limited resolution. We also apply S-DNN's edge computing capability, assisted by reconfigurable intelligent surfaces, for extremely low-latency integrated sensing and communication with low power consumption. Our work is a significant step towards utilizing photonic computing processors to facilitate various wireless sensing and communication tasks with advantages in both computing paradigms and performance over electronic computing.

Self-Explainable Graph Neural Network for Alzheimer Disease and Related Dementias Risk Prediction: Algorithm Development and Validation Study.

BACKGROUND: Alzheimer disease and related dementias (ADRD) rank as the sixth leading cause of death in the United States, underlining the importance of accurate ADRD risk prediction. While recent advancements in ADRD risk prediction have primarily relied on imaging analysis, not all patients undergo medical imaging before an ADRD diagnosis. Merging machine learning with claims data can reveal additional risk factors and uncover interconnections among diverse medical codes. OBJECTIVE: The study aims to use graph neural networks (GNNs) with claim data for ADRD risk prediction. Addressing the lack of human-interpretable reasons behind these predictions, we introduce an innovative, self-explainable method to evaluate relationship importance and its influence on ADRD risk prediction. METHODS: We used a variationally regularized encoder-decoder GNN (variational GNN [VGNN]) integrated with our proposed relation importance method for estimating ADRD likelihood. This self-explainable method can provide a feature-important explanation in the context of ADRD risk prediction, leveraging relational information within a graph. Three scenarios with 1-year, 2-year, and 3-year prediction windows were created to assess the model's efficiency, respectively. Random forest (RF) and light gradient boost machine (LGBM) were used as baselines. By using this method, we further clarify the key relationships for ADRD risk prediction. RESULTS: In scenario 1, the VGNN model showed area under the receiver operating characteristic (AUROC) scores of 0.7272 and 0.7480 for the small subset and the matched cohort data set. It outperforms RF and LGBM by 10.6% and 9.1%, respectively, on average. In scenario 2, it achieved AUROC scores of 0.7125 and 0.7281, surpassing the other models by 10.5% and 8.9%, respectively. Similarly, in scenario 3, AUROC scores of 0.7001 and 0.7187 were obtained, exceeding 10.1% and 8.5% than the baseline models, respectively. These results clearly demonstrate the significant superiority of the graph-based approach over the tree-based models (RF and LGBM) in predicting ADRD. Furthermore, the integration of the VGNN model and our relation importance interpretation could provide valuable insight into paired factors that may contribute to or delay ADRD progression. CONCLUSIONS: Using our innovative self-explainable method with claims data enhances ADRD risk prediction and provides insights into the impact of interconnected medical code relationships. This methodology not only enables ADRD risk modeling but also shows potential for other image analysis predictions using claims data.

Pancreatic stellate cells and the interleukin family: Linking fibrosis and immunity to pancreatic ductal adenocarcinoma (Review).

Pancreatic ductal adenocarcinoma (PDAC) is an extremely aggressive form of cancer with a low survival rate. A successful treatment strategy should not be limited to targeting cancer cells alone, but should adopt a more comprehensive approach, taking into account other influential factors. These include the extracellular matrix (ECM) and immune microenvironment, both of which are integral components of the tumor microenvironment. The present review describes the roles of pancreatic stellate cells, differentiated cancer­associated fibroblasts and the interleukin family, either independently or in combination, in the progression of precursor lesions in pancreatic intraepithelial neoplasia and PDAC. These elements contribute to ECM deposition and immunosuppression in PDAC. Therapeutic strategies that integrate interleukin and/or stromal blockade for PDAC immunomodulation and fibrogenesis have yielded inconsistent results. A deeper comprehension of the intricate interplay between fibrosis, and immune responses could pave the way for more effective treatment targets, by elucidating the mechanisms and causes of ECM fibrosis during PDAC progression.

Mechanistic investigation of wogonin in delaying the progression of endothelial mesenchymal transition by targeting the TGF-ß1 pathway in pulmonary hypertension.

Pulmonary hypertension (PH) is characterized by pulmonary vascular remodeling, which endothelial-to-mesenchymal transition (EndMT) being its main progressive phase. Wogonin, a flavonoid extracted from the root of Scutellaria baicalensis Georgi, hinders the abnormal proliferation of cells and has been employed in the treatment of several cardiopulmonary diseases. This study was designed to investigate how wogonin affected EndMT during PH. Monocrotaline (MCT) was used to induce PH in rats. Binding capacity of TGF-ß1 receptor to wogonin detected by molecular docking and molecular dynamics. EndMT model was established in pulmonary microvascular endothelial cells (PMVECs) by transforming growth factor beta-1 (TGF-ß1). The result demonstrated that wogonin (20 mg/kg/day) attenuated right ventricular systolic pressure (RVSP), right ventricular hypertrophy and pulmonary vascular thickness in PH rats. EndMT in the pulmonary vascular was inhibited after wogonin treatment as evidenced by the restored expression of CD31 and decreased expression of α-SMA. Wogonin has strong affinity for both TGFBRI and TGFBRII, and has a better binding stability for TGFBRI. In TGF-ß1-treated PMVECs, wogonin (0.3, 1, and 3 µM) exhibited significant inhibitory effects on this transformation process via down-regulating the expression of p-Smad2 and Snail, while up-regulating the expression of p-Smad1/5. Additionally, results of Western blot and fluorescence shown that the expression of α-SMA were decrease with increasing level of CD31 in PMVECs. In conclusion, our research showed that wogonin suppressed EndMT via the TGF-ß1/Smad pathway which may lead to its alleviated effect on PH. Wogonin may be a promising drug against PH.

Vaginal microbial profile of cervical cancer patients receiving chemoradiotherapy: the potential involvement of Lactobacillus iners in recurrence.

The vaginal microbiome is an immune defense against reproductive diseases and can serve as an important biomarker for cervical cancer. However, the intrinsic relationship between the recurrence and the vaginal microbiome in patients with cervical cancer before and after concurrent chemoradiotherapy is poorly understood. Here, we analyzed 125 vaginal microbial profiles from a patient cohort of stage IB-IVB cervical cancer using 16S metagenomic sequencing and deciphered the microbial composition and functional characteristics of the recurrent and non-recurrent both before and after chemoradiotherapy. We demonstrated that the abundance of beneficial bacteria and stability of the microbial community in the vagina decreased in the recurrence group, implying the unique characteristics of the vaginal microbiome for recurrent cervical cancer. Moreover, using machine learning, we identified Lactobacillus iners as the most important biomarker, combined with age and other biomarkers (such as Ndongobacter massiliensis, Corynebacterium pyruviciproducens ATCC BAA-1742, and Prevotella buccalis), and could predict cancer recurrence phenotype before chemoradiotherapy. This study prospectively employed rigorous bioinformatics analysis and highlights the critical role of vaginal microbiota in post-treatment cervical cancer recurrence, identifying promising biomarkers with prognostic significance in the context of concurrent chemoradiotherapy for cervical cancer. The role of L. iners in determining chemoradiation resistance in cervical cancer warrants further detailed investigation. Our results expand our understanding of cervical cancer recurrence and help develop better strategies for prognosis prediction and personalized therapy.

Host-defence caerin 1.1 and 1.9 peptides suppress glioblastoma U87 and U118 cell proliferation through the modulation of mitochondrial respiration and induce the downregulation of CHI3L1.

Glioblastoma, the most aggressive form of brain cancer, poses a significant global health challenge with a considerable mortality rate. With the predicted increase in glioblastoma incidence, there is an urgent need for more effective treatment strategies. In this study, we explore the potential of caerin 1.1 and 1.9, host defence peptides derived from an Australian tree frog, in inhibiting glioblastoma U87 and U118 cell growth. Our findings demonstrate the inhibitory impact of caerin 1.1 and 1.9 on cell growth through CCK8 assays. Additionally, these peptides effectively curtail the migration of glioblastoma cells in a cell scratch assay, exhibiting varying inhibitory effects among different cell lines. Notably, the peptides hinder the G0/S phase replication in both U87 and U118 cells, pointing to their impact on the cell cycle. Furthermore, caerin 1.1 and 1.9 show the ability to enter the cytoplasm of glioblastoma cells, influencing the morphology of mitochondria. Proteomics experiments reveal intriguing insights, with a decrease in CHI3L1 expression and an increase in PZP and JUNB expression after peptide treatment. These proteins play roles in cell energy metabolism and inflammatory response, suggesting a multifaceted impact on glioblastoma cells. In conclusion, our study underscores the substantial anticancer potential of caerin 1.1 and 1.9 against glioblastoma cells. These findings propose the peptides as promising candidates for further exploration in the realm of glioblastoma management, offering new avenues for developing effective treatment strategies.

Click Chemistry-Mediated Polymannose Surface-Engineering of Natural Killer Cells for Immunotherapy of Triple-Negative Breast Cancer.

Natural killer (NK) cells, serve as the frontline defense of the immune system, and are capable of surveilling and eliminating tumor cells. Their significance in tumor immunotherapy has garnered considerable attention in recent years. However, the absence of specific receptor-ligand interactions between NK cells and tumor cells hampers their selectivity, thereby limiting the therapeutic effectiveness of NK cell-based tumor immunotherapy. Herein, this work constructs polymannose-engineered NK (pM-NK) cells via metabolic glycoengineering and copper-free click chemistry. Polymannose containing dibenzocyclooctyne terminal groups (pM-DBCO) is synthesized and covalently modified on the surface of azido-labeled NK cells. Compared to the untreated NK cells, the interactions between pM-NK cells and MDA-MB-231 cells, a breast tumor cell line with overexpression of mannose receptors (MRs), are significantly increased, and lead to significantly enhanced killing efficacy. Consequently, intravenous administration of pM-NK cells will effectively inhibit the tumor growth and will prolong the survival of mice bearing MDA-MB-231 tumors. Thus, this work presents a novel strategy for tumor-targeting NK cell-based tumor immunotherapy.

Reduced field-of-view DWI based on deep learning reconstruction improving diagnostic accuracy of VI-RADS for evaluating muscle invasion.

OBJECTIVES: To investigate whether reduced field-of-view (rFOV) diffusion-weighted imaging (DWI) with deep learning reconstruction (DLR) can improve the accuracy of evaluating muscle invasion using VI-RADS. METHODS: Eighty-six bladder cancer participants who were evaluated by conventional full field-of-view (fFOV) DWI, standard rFOV (rFOVSTA) DWI, and fast rFOV with DLR (rFOVDLR) DWI were included in this prospective study. Tumors were categorized according to the vesical imaging reporting and data system (VI-RADS). Qualitative image quality scoring, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and ADC value were evaluated. Friedman test with post hoc test revealed the difference across the three DWIs. Receiver operating characteristic analysis was performed to calculate the areas under the curve (AUCs). RESULTS: The AUC of the rFOVSTA DWI and rFOVDLR DWI were higher than that of fFOV DWI. rFOVDLR DWI reduced the acquisition time from 5:02 min to 3:25 min, and showed higher scores in overall image quality with higher CNR and SNR, compared to rFOVSTA DWI (p < 0.05). The mean ADC of all cases of rFOVSTA DWI and rFOVDLR DWI was significantly lower than that of fFOV DWI (all p < 0.05). There was no difference in mean ADC value and the AUC for evaluating muscle invasion between rFOVSTA DWI and rFOVDLR DWI (p > 0.05). CONCLUSIONS: rFOV DWI with DLR can improve the diagnostic accuracy of fFOV DWI for evaluating muscle invasion. Applying DLR to rFOV DWI reduced the acquisition time and improved overall image quality while maintaining ADC value and diagnostic accuracy. CRITICAL RELEVANCE STATEMENT: The diagnostic performance and image quality of full field-of-view DWI, reduced field-of-view (rFOV) DWI with and without DLR were compared. DLR would benefit the wide clinical application of rFOV DWI by reducing the acquisition time and improving the image quality. KEY POINTS: Deep learning reconstruction (DLR) can reduce scan time and improve image quality. Reduced field-of-view (rFOV) diffusion-weighted imaging (DWI) with DLR showed better diagnostic performances than full field-of-view DWI. There was no difference of diagnostic accuracy between rFOV DWI with DLR and standard rFOV DWI.