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In order to investigate the pharmacokinetic characteristics of technetium [99Tc] methylenediphosphonate injection (99TC-MDP) in the blood of rats，the content of 99Tc-MDP in the blood of rats at different time points was directly determined by inductively coupled plasma-mass spectrometry (ICP-MS)，and the drug-time curve was fitted with DAS 2.1.1 software. The main pharmacokinetic parameters were obtained. The results showed that the pharmacokinetic properties of 99Tc-MDP in the blood of rats were consistent with the characteristics of the three-chamber model，and the half-life of the distribution phase T1/2α was 0.047 h，indicating that the drug was rapidly distributed in the body after entering the blood through the tail vein. The elimination phase half-life T1/2β and T1/2γ were 0.113 h and 37.349 h respectively，indicating that the drug was cleared slowly from the body. The results can provide reference for the study of 99Tc-MDP pharmacokinetics in human

Abstract The deep learning (DL)-based prediction of accurate lymph node (LN) clinical target volumes (CTVs) for nasopharyngeal carcinoma (NPC) radiotherapy (RT) remains challenging. One of the main reasons is the variability of contours despite standardization processes by expert guidelines in combination with scarce data sharing in the community. Therefore, we retrospectively generated a 262-subjects dataset from four centers to develop the DL models for LN CTVs delineation. This dataset included 440 computed tomography images from different scanning phases, disease stages and treatment strategies. Three clinical expert boards, each comprising two experts (totalling six experts), manually delineated six basic LN CTVs on separate cohorts as the ground truth according to LN involvement and clinical requirements. Several state-of-the-art segmentation algorithms were evaluated on this benchmark, showing promising results for LN CTV segmentation. In conclusion, this work built a multicenter LN CTV segmentation dataset, which may be the first dataset for automatic LN CTV delineation development and evaluation, serving as a benchmark for future research.

Abstract Background Nonspecific Orbital Inflammation (NSOI) represents a persistent and idiopathic proliferative inflammatory disorder, characterized by polymorphous lymphoid infiltration within the orbit. The transcription factor Interferon Regulatory Factor 8 (IRF8), integral to the IRF protein family, was initially identified as a pivotal element for the commitment and differentiation of myeloid cell lineage. Serving as a central regulator of innate immune receptor signaling, IRF8 orchestrates a myriad of functions in hematopoietic cell development. However, the intricate mechanisms underlying IRF8 production remain to be elucidated, and its potential role as a biomarker for NSOI is yet to be resolved. Methods IRF8 was extracted from the intersection analysis of common DEGs of GSE58331 and GSE105149 from the GEO and immune- related gene lists in the ImmPort database using The Lasso regression and SVM-RFE analysis. We performed GSEA and GSVA with gene sets coexpressed with IRF8, and observed that gene sets positively related to IRF8 were enriched in immune-related pathways. To further explore the correlation between IRF8 and immune-related biological process, the CIBERSORT algorithm and ESTIMATE method were employed to evaluate TME characteristics of each sample and confirmed that high IRF8 expression might give rise to high immune cell infiltration. Finally, the GSE58331 was utilized to confirm the levels of expression of IRF8. Results Among the 314 differentially expressed genes (DEGs), some DEGs were found to be significantly different. With LASSO and SVM-RFE algorithms, we obtained 15 hub genes. For biological function analysis in IRF8, leukocyte mediated immunity, leukocyte cell-cell adhesion, negative regulation of immune system process were emphasized. B cells naive, Macrophages M0, Macrophages M1, T cells CD4 memory activated, T cells CD4 memory resting, T cells CD4 naive, and T cells gamma delta were shown to be positively associated with IRF8. While, Mast cells resting, Monocytes, NK cells activated, Plasma cells, T cells CD8, and T cells regulatory (Tregs) were shown to be negatively linked with IRF8. The diagnostic ability of the IRF8 in differentiating NSOI exhibited a good value. Conclusions This study discovered IRF8 that are linked to NSOI. IRF8 shed light on potential new biomarkers for NSOI and tracking its progression.

Abstract Background Intrahepatic cholestasis of pregnancy (ICP) is associated with an increased risk of adverse fetal outcomes, yet its influence on offspring growth remains unclear. Our study dynamically tracks growth rates in children from ICP and healthy mothers and investigates the link between maternal liver function and developmental abnormalities in offspring. Method Our case‒control study involved 97 women with ICP and 152 with uncomplicated pregnancies nested in a cohort of their offspring, including 50 from the ICP group and 87 from the uncomplicated pregnancy group. We collected pediatric growth and development data, with a maximum follow-up duration of 36 months. Stratified analyses of children's height, weight, and head circumference were conducted, and Spearman's rank correlation was applied to examine the relationships between maternal serological markers and pediatric growth metrics. Result Maternal liver and renal functions, along with serum lipid profiles, significantly differed between the ICP and normal groups. In the ICP group, the offspring showed elevated alanine aminotransferase (ALT), direct bilirubin (DBIT), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and apolipoprotein B (APOB) levels. Notably, the length-for-age z score (LAZ), weight-for-age z score (WAZ), and head circumference-for-age z score (HCZ) were lower in ICP offspring compared with those from normal pregnancies within the 1- to 12-month age range (P

Summary: Artificial intelligence (AI) is rarely directly used in patent foramen ovale (PFO) diagnosis. In this study, an AI model was developed to detect the presence of PFO automatically in both contrast transthoracic echocardiography (cTTE) images and videos. The whole intelligent diagnosis neural network framework consists of two functional modules of image segmentation (Unet, n = 1866) and image classification (ResNet 101, n = 9152). Finally, another test databases, including 20 cTTE videos (4609 cTTE images), was used to compare the RLS classification model accuracy between AI model and different levels of physicians. The Dice similarity coefficient of left chamber segmentation model of cTTE images was 91.41%, the accuracy of PFO-RLS classification model of cTTE images was 83.55%, the accuracy of PFO-RLS classification model of cTTE videos was 90%. Besides, the AI diagnosis time was significantly shorter than doctors (at only 1.3 s).

Two-component room temperature vulcanizing silicone adhesive RTV566 with a lower elastic modulus has been widely used in precision optomechanical products such as remote sensors and aerospace infrared cameras. However, the silicone adhesive is of poor manufacturability due to its extremely high viscosity, and the bonded joint usually exhibits low bonding strength and requires a long curing time. This paper investigates a way to improve both the adhesion strength and curing efficiency of Invar alloy and optical glass with RTV566 through single-lap experiments. It is found that adding small amounts of acetone and water can significantly reduce the viscosity, enhance the bonding strength, and shorten the curing time. The viscosity can be reduced by 63.4 % and the bonding strength can be improved by 136.4 % with the weight ratio of adhesive to acetone being 20:2. Moreover, a little amount of water in the weight ratio of 100:10:0.1 (adhesive: acetone: water) can shorten the curing time from 7 days to 4 days without harms to the bonding strength and elastic modulus. As to the mechanism, the silicone adhesive can be dissolved by acetone and its sulfuration reaction can be enhanced by water, resulting in good manufacturability and high curing efficiency. This work contributes a novel and easy-to-use method to greatly improve the performances of the bonding process of precision optical structures.

Purpose To assess whether gray-scale ultrasound (US) based radiomic features can help distinguish HER2 expressions (ie, HER2-overexpressing, HER2-low-expressing, and HER2-zero-expressing) in breast cancer. Materials and Methods This retrospective study encompassed female breast cancer patients who underwent US examinations at two distinct centers from February 2021 to July 2023. Tumor segmentation and radiomic feature extraction were performed on grayscale US images. Decision Tree analysis was employed to simultaneously evaluate feature importance, and the Least Absolute Shrinkage and Selection Operator technique was utilized for feature selection to construct the radiomic signature. The Area Under the Curve (AUC) of the Receiver Operating Characteristic curve was employed to assess the performance of the radiomic features. Multivariate logistic regression was used to identify independent predictors for distinguishing HER2 expression in the dataset. Results The training set comprised 292 patients from Center 1 (median, 51 years; interquartile range [IQR]: 45-61), while the external validation set included 131 patients from Center 2 (median, 51 years; IQR: 45-62). In the external validation dataset, the radiomic features achieved AUC of 0.76 for distinguishing between HER2-low and positive tumors versus HER2-zero tumors. The AUC for differentiating HER2-low (1+) from HER2-zero tumors was 0.74, and for distinguishing HER2-low (2+) from HER2-zero tumors, the AUC was 0.77. In the multivariate analysis assessing HER2-low and HER2-positive versus HER2-zero tumors, internal echoes (P = .029) and margins (P

Purpose: This study explored whether a free-breathing mean heart dose (FB-MHD) of 4 Gy is a reliable dose threshold for selecting left breast cancer patients after modified radical mastectomy suitable for deep inspiration breath-hold (DIBH) and developed anatomical indicators to predict FB-MHD for rapid selection. Materials and methods: Twenty-three patients with left breast cancer treated with DIBH were included to compare FB and DIBH plans. The patients were divided into the high-risk (FB-MHD ≥ 4 Gy) and low-risk (FB-MHD

According to the convergence confinement theory, it is an effective measure to control the large deformation of high ground stress in fractured soft rock tunnels by using yielding support. The yielding support can be classified as either radial or circumferential yielding support. Circumferential yielding support is achieved by transforming radial displacement into circumferential tangential closure without compromising the support capacity of the primary lining support structure. Based on this, and inspired by the design principle of dampers, a yielding support structure system with spring damping elements as its core was developed, based on the connection characteristics of steel arches in highway tunnel, which can provide increasing support resistance in the yielding deformation section. Then the mechanical properties of spring damping elements were obtained through indoor axial pressure and flexural tests. In addition, according to these results with numerical calculations, the yielding support structure system with embedded spring damping elements can reduce the internal force of the support structure by approximately 10% and increase the area of the plastic zone of the surrounding rock by 11.23%, which can fully utilize the self-bearing capacity of surrounding rock and verify the effectiveness of circumferential yielding support. Finally, the spring damping support structure system was designed with reference to the construction process of the tunnel excavated by drilling and blasting method, and the transformation of the spring damping element to spring damping support structure was achieved. Based on field test results, surrounding ground pressure for the yielding support optimization scheme was reduced by 40% and more evenly distributed, resulting in the successful application and a reduction in the construction cost of large deformation tunnels in soft rock.

Purpose: This study aimed to evaluate a radiomics model using Photoacoustic/ultrasound (PA/US) imaging at intra and peri-tumoral area to differentiate Luminal and non-Luminal breast cancer (BC) and to determine the optimal peritumoral area for accurate classification. Materials and methods: From February 2022 to April 2024, this study continuously collected 322 patients at Shenzhen People’s Hospital, using standardized conditions for PA/US imaging of BC. Regions of interest were delineated using ITK-SNAP, with peritumoral regions of 2 mm, 4 mm, and 6 mm automatically expanded using code from the Pyradiomic package. Feature extraction was subsequently performed using Pyradiomics. The study employed Z-score normalization, Spearman correlation for feature correlation, and LASSO regression for feature selection, validated through 10-fold cross-validation. The radiomics model integrated intra and peri-tumoral area, evaluated by receiver operating characteristic curve(ROC), Calibration and Decision Curve Analysis(DCA). Results: We extracted and selected features from intratumoral and peritumoral PA/US images regions at 2 mm, 4 mm, and 6 mm. The comprehensive radiomics model, integrating these regions, demonstrated enhanced diagnostic performance, especially the 4 mm model which showed the highest area under the curve(AUC):0.898(0.78–1.00) and comparably high accuracy (0.900) and sensitivity (0.937). This model outperformed the standalone clinical model and combined clinical-radiomics model in distinguishing between Luminal and non-Luminal BC, as evidenced in the test set results. Conclusion: This study developed a radiomics model integrating intratumoral and peritumoral at 4 mm region PA/US model, enhancing the differentiation of Luminal from non-Luminal BC. It demonstrated the diagnostic utility of peritumoral characteristics, reducing the need for invasive biopsies and aiding chemotherapy planning, while emphasizing the importance of optimizing tumor surrounding size for improved model accuracy.

Canine adenovirus (CAdV) had a high prevalence in fox populations and induced fox encephalitis. No ELISA kits specifically for CAdV-1 antigen had been commercialized for foxes in China. It is crucial to develop a rapid and accurate ELISA method for detecting of CAdV-1. The monoclonal antibodies (mAbs, IgG1A) and HRP-labeled polyclonal antibodies (pAbs) were used to establish the ELISA method in this experiment. The results showed that the optimal concentration and coating time for the mAbs (IgG1A) were 2.15 μg/mL and overnight at 4°C, respectively. The dilution ratio of the HRP-labeled pAbs was 1:2000. Five percent skimmed milk was selected as the blocking agent. The optimal incubation times for blocking, CAdV-1, and HRP-labeled pAbs were all 1 h. The cut-off value for negative rectal swab was determined to be 0.366 ± 0.032. The maximum dilution ratio was 100 TCID50/mL. The ELISA method was positive to CAdV-1, and that was negative to CAdV-2, Canine Parvovirus (CPV) and Canine Distempervirus (CDV). The ELISA method showed good repeatability, sensitivity, and specificity. Compared with RT-PCR, the sensitivity, specificity, and coincidence rates of the ELISA method were 93.75, 90.9, and 92.86%, respectively. These results indicate that the established ELISA method can be used for the large-scale screening and epidemiology surveillance of CAdV-1 in foxes.

ObjectiveTo assess the effect of intravenous immunoglobulin (IVIG) therapy on unexplained recurrent spontaneous abortion (URSA).MethodsWe retrieved all randomized controlled trials (RCTs) related to the effect of IVIG therapy on URSA in the following databases: PubMed, Embase, Web of Science, and Cochrane Central Register of Controlled Trials before April 30, 2023, according to the PRISMA statement. The therapeutic effect of IVIG was measured by live birth rates. Quality assessment was conducted independently by two reviewers, based on the Newcastle‐Ottawa scale. For the meta-analysis, we used odds ratios (random effects model and fixed effects model). The between-study heterogeneity was assessed by the Q test. Publication bias was assessed by funnel plots.ResultsA total of 12 studies with 751 participants were included in this meta-analysis. There was no statistical significance [OR = 1.07, 95%CI (0.65, 1.75), P=0.80] between the IVIG group and the non-IVIG group, including low molecular weight heparin (LMWH) plus low-dose aspirin (LDA), intralipid, multivitamins, albumin, and normal saline. A subgroup analysis was conducted according to the different treatment regimens of the non-IVIG group. Compared to the placebo group, including multivitamins, albumin, and saline, the live birth rate of the IVIG group is superior, but there was no statistical significance [OR =1.43, 95%CI (0.99, 2.07), P=0.05]. Another subgroup analysis was performed according to URSA with positive for antiphospholipid antibodies (aPLs). Results showed the live birth rate of IVIG on URSA with positive for aPLs is inferior to that of LMWH plus LDA [OR = 0.25, 95%CI (0.11, 0.55), P=0.0007].ConclusionsIVIG didn’t increase the live birth rate of URSA compared to placebo. Conversely, compared with the IVIG, the LMWH plus LDA treatment schedule can increase the live birth rate of URSA with positive for aPLs.

Background: The differentiation between benign and malignant breast tumors extends beyond morphological structures to encompass functional alterations within the nodules. The combination of photoacoustic (PA) imaging and radiomics unveils functional insights and intricate details that are imperceptible to the naked eye. Purpose: This study aims to assess the efficacy of PA imaging in breast cancer radiomics, focusing on the impact of peritumoral region size on radiomic model accuracy. Materials and methods: From January 2022 to November 2023, data were collected from 358 patients with breast nodules, diagnosed via PA/US examination and classified as BI-RADS 3–5. The study used the largest lesion dimension in PA images to define the region of interest, expanded by 2 mm, 5 mm, and 8 mm, for extracting radiomic features. Techniques from statistics and machine learning were applied for feature selection, and logistic regression classifiers were used to build radiomic models. These models integrated both intratumoral and peritumoral data, with logistic regressions identifying key predictive features. Results: The developed nomogram, combining 5 mm peritumoral data with intratumoral and clinical features, showed superior diagnostic performance, achieving an AUC of 0.950 in the training cohort and 0.899 in validation. This model outperformed those based solely on clinical features or other radiomic methods, with the 5 mm peritumoral region proving most effective in identifying malignant nodules. Conclusion: This research demonstrates the significant potential of PA imaging in breast cancer radiomics, especially the advantage of integrating 5 mm peritumoral with intratumoral features. This approach not only surpasses models based on clinical data but also underscores the importance of comprehensive radiomic analysis in accurately characterizing breast nodules.

Background: Accurate assessment of Rheumatoid Arthritis (RA) activity remains a challenge. Multimodal photoacoustic/ultrasound (PA/US) joint imaging emerges as a novel imaging modality capable of depicting microvascularization and oxygenation levels in inflamed joints associated with RA. However, the scarcity of large-scale studies limits the exploration of correlating joint oxygenation status with disease activity. Objective: This study aimed to explore the correlation between multimodal PA/US imaging scores and RA disease activity, assessing its clinical applicability in managing RA. Methods: In this study, we recruited 111 patients diagnosed with RA and conducted examinations of seven small joints on their clinically dominant side using a PA/US imaging system. The PA and power Doppler ultrasound (PDUS) signals were semi-quantitatively assessed using a 0–3 grading system. The cumulative scores for PA and PDUS across these seven joints (PA-sum and PDUS-sum) were calculated. Relative oxygen saturation (So2) values of inflamed joints on the clinically dominant side were measured, and categorized into four distinct PA+So2 patterns. The correlation between PA/US imaging scores and disease activity indices was systematically evaluated. Results: Analysis of 777 small joints in 111 patients revealed that the PA-sum scores exhibited a strong positive correlation with standard clinical scores for RA, including DAS28 [ESR] (ρ = 0.682), DAS28 [CRP] (ρ = 0.683), CDAI (ρ = 0.738), and SDAI (ρ = 0.739), all with p < 0.001. These correlations were superior to those of the PDUS-sum scores (DAS28 [ESR] ρ = 0.559, DAS28 [CRP] ρ = 0.555, CDAI ρ = 0.575, SDAI ρ = 0.581, p < 0.001). Significantly, in patients with higher PA-sum scores, notable differences were observed in the erythrocyte sedimentation rate (ESR) (p < 0.01) and swollen joint count 28 (SJC28) (p < 0.01) between hypoxia and intermediate groups. Notably, RA patients in the hypoxia group exhibited higher clinical scores in certain clinical indices. Conclusion: Multi-modal PA/US imaging introduces potential advancements in RA assessment, especially regarding So2 evaluations in synovial tissues and associated PA scores. However, further studies are warranted, particularly with more substantial sample sizes and in multi-center settings. Summary: This study utilized multi-modal PA/US imaging to analyze Rheumatoid Arthritis (RA) patients' synovial tissues and affected joints. When juxtaposed with traditional PDUS imaging, the PA approach demonstrated enhanced sensitivity, especially concerning detecting small vessels in thickened synovium and inflamed tendon sheaths. Furthermore, correlations between the derived PA scores, PA+So2 patterns, and standard clinical RA scores were observed. These findings suggest that multi-modal PA/US imaging could be a valuable tool in the comprehensive assessment of RA, offering insights not only into disease activity but also into the oxygenation status of synovial tissues. However, as promising as these results are, further investigations, especially in larger and diverse patient populations, are imperative. Key points: ⸸ Multi-modal PA/US Imaging in RA: This novel technique was used to assess the So2 values in synovial tissues and determine PA scores of affected RA joints.⸸ Correlation significantly with Clinical RA Scores: Correlations significantly were noted between PA scores, PA+So2 patterns, and standard clinical RA metrics, hinting at the potential clinical applicability of the technique.

Abstract Purpose To assess the diagnostic performance of Ultrasound Attenuation Analysis (USAT) in the diagnosis and grading of hepatic steatosis in patients with non-alcoholic fatty liver disease (NAFLD) using Controlled Attenuation Parameters (CAP) as a reference. Materials and methods From February 13, 2023, to September 26, 2023, participants underwent CAP and USAT examinations on the same day. We used manufacturer-recommended CAP thresholds to categorize the stages of hepatic steatosis: stage 1 (mild) − 240 dB/m, stage 2 (moderate) − 265 dB/m, stage 3 (severe) − 295 dB/m. Receiver Operating Characteristic curves were employed to evaluate the diagnostic accuracy of USAT and determine the thresholds for different levels of hepatic steatosis. Results Using CAP as the reference, we observed that the average USAT value increased with the severity of hepatic steatosis, and the differences in USAT values among the different hepatic steatosis groups were statistically significant (p

Abstract Purpose Breast density has consistently been shown to be an independent risk factor for breast cancer in Western populations; however, few studies have evaluated this topic in Chinese women and there is not yet a unified view. This study investigated the association between mammographic density (MD) and breast cancer risk in Chinese women. Methods The PubMed, Cochrane Library, Embase, and Wanfang databases were systematically searched in June 2023 to include all studies on the association between MD and breast cancer risk in Chinese women. A total of 13,977 breast cancer cases from 14 studies were chosen, including 10 case-control/cross-sectional studies, and 4 case-only studies. For case-control/cross-sectional studies, the odds ratios (ORs) of MD were combined using random effects models, and for case-only studies, relative odds ratios (RORs) were combinations of premenopausal versus postmenopausal breast cancer cases. Results Women with BI-RADS density category II-IV in case-control/cross-sectional studies had a 0.93-fold (95% confidence interval [CI] 0.55, 1.57), 1.08-fold (95% CI 0.40, 2.94), and 1.24-fold (95% CI 0.42, 3.69) higher risk compared to women with the lowest density category. Combined RORs for premenopausal versus postmenopausal women in case-only studies were 3.84 (95% CI 2.92, 5.05), 22.65 (95% CI 7.21, 71.13), and 42.06 (95% CI 4.22, 419.52), respectively, for BI-RADS density category II-IV versus I. Conclusions For Chinese women, breast cancer risk is weakly associated with MD; however, breast cancer risk is more strongly correlated with mammographic density in premenopausal women than postmenopausal women. Further research on the factors influencing MD in premenopausal women may provide meaningful insights into breast cancer prevention in China.

Abstract Background The application of artificial intelligence (AI) in the ultrasound (US) diagnosis of breast cancer (BCa) is increasingly prevalent. However, the impact of US-probe frequencies on the diagnostic efficacy of AI models has not been clearly established. Objectives To explore the impact of using US-video of variable frequencies on the diagnostic efficacy of AI in breast US screening. Methods This study utilized different frequency US-probes (L14: frequency range: 3.0-14.0 MHz, central frequency 9 MHz, L9: frequency range: 2.5-9.0 MHz, central frequency 6.5 MHz and L13: frequency range: 3.6-13.5 MHz, central frequency 8 MHz, L7: frequency range: 3-7 MHz, central frequency 4.0 MHz, linear arrays) to collect breast-video and applied an entropy-based deep learning approach for evaluation. We analyzed the average two-dimensional image entropy (2-DIE) of these videos and the performance of AI models in processing videos from these different frequencies to assess how probe frequency affects AI diagnostic performance. Results The study found that in testing set 1, L9 was higher than L14 in average 2-DIE; in testing set 2, L13 was higher in average 2-DIE than L7. The diagnostic efficacy of US-data, utilized in AI model analysis, varied across different frequencies (AUC: L9 > L14: 0.849 vs. 0.784; L13 > L7: 0.920 vs. 0.887). Conclusion This study indicate that US-data acquired using probes with varying frequencies exhibit diverse average 2-DIE values, and datasets characterized by higher average 2-DIE demonstrate enhanced diagnostic outcomes in AI-driven BCa diagnosis. Unlike other studies, our research emphasizes the importance of US-probe frequency selection on AI model diagnostic performance, rather than focusing solely on the AI algorithms themselves. These insights offer a new perspective for early BCa screening and diagnosis and are of significant for future choices of US equipment and optimization of AI algorithms.

This study presents the design and development of a high-resolution convex grating dispersion hyperspectral imaging system tailored for unmanned aerial vehicle (UAV) remote sensing applications. The system operates within a spectral range of 400 to 1000 nm, encompassing over 150 channels, and achieves an average spectral resolution of less than 4 nm. It features a field of view of 30°, a focal length of 20 mm, a compact volume of only 200 mm × 167 mm × 78 mm, and a total weight of less than 1.5 kg. Based on the design specifications, the system was meticulously adjusted, calibrated, and tested. Additionally, custom software for the hyperspectral system was independently developed to facilitate functions such as control parameter adjustments, real-time display, and data preprocessing of the hyperspectral camera. Subsequently, the prototype was integrated onto a drone for remote sensing observations of Spartina alterniflora at Yangkou Beach in Shouguang City, Shandong Province. Various algorithms were employed for data classification and comparison, with support vector machine (SVM) and neural network algorithms demonstrating superior classification accuracy. The experimental results indicate that the UAV-based hyperspectral imaging system exhibits high imaging quality, minimal distortion, excellent resolution, an expansive camera field of view, a broad detection range, high experimental efficiency, and remarkable capabilities for remote sensing detection.

Summary: We evaluated the diagnostic performance of a multimodal deep-learning (DL) model for ovarian mass differential diagnosis. This single-center retrospective study included 1,054 ultrasound (US)-detected ovarian tumors (699 benign and 355 malignant). Patients were randomly divided into training (n = 675), validation (n = 169), and testing (n = 210) sets. The model was developed using ResNet-50. Three DL-based models were proposed for benign-malignant classification of these lesions: single-modality model that only utilized US images; dual-modality model that used US images and menopausal status as inputs; and multi-modality model that integrated US images, menopausal status, and serum indicators. After 5-fold cross-validation, 210 lesions were tested. We evaluated the three models using the area under the curve (AUC), accuracy, sensitivity, and specificity. The multimodal model outperformed the single- and dual-modality models with 93.80% accuracy and 0.983 AUC. The Multimodal ResNet-50 DL model outperformed the single- and dual-modality models in identifying benign and malignant ovarian tumors.

The gene therapy attracted more and more attention for the tumor therapy. To obtain a safe gene therapy system, the new gene vectors beyond the virus were developed for a high gene therapy efficiency. The ultrasound mediated gene therapy was safer and the plasmid DNA could be delivered by the microbubbles and combined with the ultrasound to increase the gene transfection efficiency. In this work, the cationic microbubbles decorated with Cyclo(Cys-Arg-Gly-Asp-Lys-Gly-Pro-AspCys) (iRGD peptides) and magnetic Fe3O4 nanoparticles (MBiM) was designed for targeted ultrasound contrast imaging guided gene therapy of tumors. The ultrasound image intensity was dramatically enhanced at the tumor site that received MBiM with the magnet applied, compared to those administrated the non-targeted microbubbles (MBb) or the microbubbles with only one target material on the surface (MBM and MBbi). The pGPU6/GFP/Neo-shAKT2 was used as a sample gene, which down regulate the AKT2 protein expression for the cancer therapy. It illustrated that MBiM/AKT2 had the highest gene transfection efficiency in the studied microbubbles mediated by the ultrasound, leading to the AKT2 protein expression downregulation and the strongest tumor killing effect in vitro and in vivo. In summary, a novel and biocompatible gene delivery platform via MBiM with both the endogenous and external targeting effects for breast cancer theranostics was developed.

Abstract Background This retrospective study aims to validate the effectiveness of artificial intelligence (AI) to detect and classify non-mass breast lesions (NMLs) on ultrasound (US) images. Methods A total of 228 patients with NMLs and 596 volunteers without breast lesions on US images were enrolled in the study from January 2020 to December 2022. The pathological results served as the gold standard for NMLs. Two AI models were developed to accurately detect and classify NMLs on US images, including DenseNet121_448 and MobileNet_448. To evaluate and compare the diagnostic performance of AI models, the area under the curve (AUC), accuracy, specificity and sensitivity was employed. Results A total of 228 NMLs patients confirmed by postoperative pathology with 870 US images and 596 volunteers with 1003 US images were enrolled. In the detection experiment, the MobileNet_448 achieved the good performance in the testing set, with the AUC, accuracy, sensitivity, and specificity were 0.999 (95%CI: 0.997-1.000),96.5%,96.9% and 96.1%, respectively. It was no statistically significant compared to DenseNet121_448. In the classification experiment, the MobileNet_448 model achieved the highest diagnostic performance in the testing set, with the AUC, accuracy, sensitivity, and specificity were 0.837 (95%CI: 0.990-1.000), 70.5%, 80.3% and 74.6%, respectively. Conclusions This study suggests that the AI models, particularly MobileNet_448, can effectively detect and classify NMLs in US images. This technique has the potential to improve early diagnostic accuracy for NMLs.

Coronavirus infectious disease 2019 (COVID-19), caused by severe acute respiratory virus type 2 (SARS-CoV-2), has caused a global public health crisis. As an RNA virus, the high gene mutability of SARS-CoV-2 poses significant challenges to the development of broad-spectrum vaccines and antiviral therapeutics. There remains a lack of specific therapeutics directly targeting SARS-CoV-2. With the ability to efficiently inhibit the expression of target genes in a sequence-specific way, small interfering RNA (siRNA) therapy has exhibited significant potential in antiviral and other disease treatments. In this work, we presented a highly effective self-assembled siRNA nanoparticle targeting multiple highly conserved regions of SARS-CoV-2. The siRNA sequences targeting viral conserved regions were first screened and evaluated by their thermodynamic features, off-target effects, and secondary structure toxicities. RNA motifs including siRNA sequences were then designed and self-assembled into siRNA nanoparticles. These siRNA nanoparticles demonstrated remarkable uniformity and stability and efficiently entered cells directly through cellular endocytic pathways. Moreover, these nanoparticles effectively inhibited the replication of SARS-CoV-2, exhibiting a superior inhibitory effect compared to free siRNA. These results demonstrated that these self-assembled siRNA nanoparticles targeting highly conserved regions of SARS-CoV-2 represent highly effective antiviral candidates for the treatment of infections, and are promisingly effective against current and future viral variants.

Objective(s): Existing Brucella vaccines are attenuated and can cause vaccine-associated brucellosis; and these safety concerns have affected their application. Although subunit vaccines have the advantages of safety, efficacy, low cost, and rapid production, they are usually poorly immunogenic and insufficient to trigger persistent immunity. Therefore, we added layered double hydroxide (LDH) as an adjuvant to Brucella subunit vaccine formulations to enhance the immune response to the antigen.Materials and Methods: LDH and Freund’s adjuvant were combined with Brucella outer-membrane vesicles (OMVs) and OMV-associated proteins to form a subunit vaccine, respectively. The immunogenicity of LDH as an adjuvant was assessed in BALB/c mice. We examined levels of immunoglobulin G, G1, and G2a (IgG, IgG1, and IgG2a) antibodies (aBs); percentages of Cluster of Differentiation 4-positive (CD4+) and CD8+ T cells in peripheral-blood lymphocytes; and secretion of cytokines in mouse spleen lymphocytes. Finally, splenic index and splenic bacterial load were assessed via Brucella challenge experiments on mice.Results: The LDH subunit vaccine also produced high levels of specific aBs in mice compared with Freund’s adjuvant subunit vaccine and induced mainly T-helper 1 cell (Th1)-type immune responses. In addition, mice in the LDH subunit vaccine group had significantly lower bacterial loads in their spleens than those in the Freund’s adjuvant subunit vaccine group, and the LDH-OMV vaccine offered a higher level of protection against Brucella attack.Conclusion: LDH as an adjuvant-paired vaccine provided a high level of protection against Brucella infection.

Electrochromism has emerged as a pivotal technology in the pursuit of energy efficiency and environmental sustainability, spurring significant research efforts aimed at the creation of advanced electrochromic devices. Most electrochromic materials are used for smart window applications. However, current electrochromic materials have been applied to new energy vehicles, cell phone back covers, AR glasses, and so on. More application scenarios put forward more requirements for the color of the colored states. Choosing the right color change in the application will be the trend in the future. In this work, tungsten trioxide (WO3) thin films were prepared by adjusting the in situ heating temperature. WO3 with a crystalline structure showed excellent cyclic stability (5000 cycles), electrochromic performance (ΔT = 77.7% at 633 nm, CE = 37.1 cm2/C), relatively fast bleaching/coloring speed (20.0 s/19.4 s), and the darkest coloring effect (L* = 29.32, a* = 7.41, b* = −22.12 for the colored state). These findings offer valuable insights into the manipulation of smart materials and devices, contributing to the advancement of electrochromic technology.

Mountainous forests are pivotal in the global carbon cycle, serving as substantial reservoirs and sinks of carbon. However, generating a reliable estimate remains a considerable challenge, primarily due to the lack of representative in situ measurements and proper methods capable of addressing their complex spatial variation. Here, we proposed a deep learning-based method that combines Residual convolutional neural networks (ResNet) with in situ measurements, microwave (Sentinel-1 and VOD), and optical data (Sentinel-2 and Landsat) to estimate forest biomass and track its change over the mountainous regions. Our approach, integrating in situ measurements across representative elevations with multi-source remote sensing images, significantly improves the accuracy of biomass estimation in Tibet’s complex mountainous forests (R2 = 0.80, root mean squared error = 15.8 MgC ha−1). Moreover, ResNet, which addresses the vanishing gradient problem in deep neural networks by introducing skip connections, enables the extraction of complex spatial patterns from limited datasets, outperforming traditional optical-based or pixel-based methods. The mean value of forest biomass was estimated as 162.8 ± 21.3 MgC ha−1, notably higher than that of forests at comparable latitudes or flat regions in China. Additionally, our findings revealed a substantial forest biomass carbon sink of 3.35 TgC year−1 during 2015–2020, which is largely underestimated by previous estimates, mainly due to the underestimation of mountainous carbon stock. The significant carbon density, combined with the underestimated carbon sink in mountainous regions, emphasizes the urgent need to reassess mountain forests to better approximate the global carbon budget.

The current use of elastography ultrasound faces challenges, including vulnerability to subjective manipulation, echo signal attenuation, unknown risks of elastic pressure and high imaging hardware cost. Here, the author shows a virtual elastography to empower low-end ultrasound devices with state-of-art elastography function.

Objective(s): Hyperinsulinemia, secondary to insulin resistance, may lead to vascular smooth muscle cell dysfunction. In the present research, we aimed to investigate the effect of Chemokine receptor 8 (CCR8) on angiotensin II (Ang II)-induced dysfunction of vascular smooth muscle cells (VSMCs) and to explore the underlying molecular mechanism. Materials and Methods: The expression of CCR8 was analyzed in diabetics and normal people by RT-PCR and ELISA. CCK-8 assay and transwell were used to explore cell proliferation and migration, and ELISA was used to measure the content of IL-6 and TNF-α. Reactive oxygen species (ROS) kit was employed to measure ROS generation. Results: The results revealed that CCR8 was highly expressed in diabetics and Ang Ⅱ-induced VSMCs. Further studies found that interfering with the expression of CCR8 significantly reduced the production of ROS and the levels of inflammatory factors in AngⅡ-induced VSMCs. Interfering with CCR8 increased the glucose uptake induced by AngⅡ+IR. More importantly, inhibition of CCR8 alleviated Ang II-induced dysfunction of VSMCs. Inhibition of CCR8 inactivated the MAPK/NF-κB signaling pathway.Conclusion: Inhibition of CCR8 attenuates Ang II-induced VSMCs injury by inhibiting the MAPK/NF-κB pathway. CCR8 may be a new biomarker related to hypertension and insulin resistance and is a new target for the treatment of human cardiovascular diseases.

Purpose: The objective of this research was to investigate the efficacy of various parameter combinations of Convolutional Neural Networks (CNNs) models, namely MobileNet and DenseNet121, and different input image resolutions (REZs) ranging from 64×64 to 512×512 pixels, for diagnosing breast cancer. Materials and methods: During the period of June 2015 to November 2020, two hospitals were involved in the collection of two-dimensional ultrasound breast images for this retrospective multicenter study. The diagnostic performance of the computer models MobileNet and DenseNet 121 was compared at different resolutions. Results: The results showed that MobileNet had the best breast cancer diagnosis performance at 320×320pixel REZ and DenseNet121 had the best breast cancer diagnosis performance at 448×448pixel REZ. Conclusion: Our study reveals a significant correlation between image resolution and breast cancer diagnosis accuracy. Through the comparison of MobileNet and DenseNet121, it is highlighted that lightweight neural networks (LW-CNNs) can achieve model performance similar to or even slightly better than large neural networks models (HW-CNNs) in ultrasound images, and LW-CNNs' prediction time per image is lower.

IntroductionAnimal trade favors the spreading of emerging canine adenovirus 1 (CAdV-1) in mink. Because the 100K protein is not exposed to the viral surface at any stage, it can be used to differentiate the vaccine from wild virus infection. However, no related research has been conducted. This study aimed to find evidence of CAdV-1 in mink and predict the character of the 100K protein in the current circulating CAdV-1 strain of mink.MethodIn this experiment, the identification of CAdV-1, the phylogenetic tree, homology, and bioinformatics analysis of 100K were conducted.ResultsThe results showed that the CAdV-1 was identified in the mink and that its Fiber was located in a separate branch. It was closely related to strains isolated from Norwegian Arctic fox and Red fox. 100K was located in a separate branch, which had the closest genetic relationship with skunks, porcupines, raccoons, and hedgehogs and a far genetic relationship with the strains in dogs. 100K protein is an unstable and hydrophobic protein. It had evidence of selective pressure and recombination, 1 glycosylation site, 48 phosphorylation sites, 60 dominant B cell epitopes, and 9 peptides of MHC-I and MHC-II. Its subcellular localization was mainly in the endoplasmic reticulum and mitochondria. The binding sites of 100K proteins were DBP proteins and 33K proteins.DiscussionThe stains in the mink were different from fox. The exploration of its genomic characteristics will provide us with a deeper understanding of the prevention of canine adenovirus.

Abstract Background In the past decade, the field of tumour immunotherapy has made a great progress. However, the efficacy of immune checkpoint blocking (ICB) in the treatment of hepatocellular carcinoma (HCC) remains limited. Cytotoxic lymphocyte trafficking into tumours is critical for the success of ICB. Therefore, additional strategies that increase cytotoxic lymphocyte trafficking into tumours are urgently needed to improve patient immune responses. Methods Paired adjacent tissue and cancerous lesions with HBV‐associated HCC were subjected to RNA‐seq analysis. Bone morphogenetic protein (BMP9), which reflects vessel normalisation, was identified through Cytoscape software, clinical specimens and Gene Expression Omnibus (GEO) datasets for HCC. The functional effects and mechanism of BMP9 on the tumour vasculature were evaluated in cells and animals. An ultrasound‐targeted microbubble destruction (UTMD)‐mediated BMP9 delivery strategy was used to normalise the vasculature and evaluate therapeutic efficacy mediated by cytotoxic lymphocytes (NK cells) in combination with a PD‐L1 antibody in human cancer xenografts of immune‐deficient mice. Results We discovered that hepatitis B virus (HBV) infection‐induced downregulation of BMP9 expression correlated with a poor prognosis and pathological vascular abnormalities in patients with HCC. BMP9 overexpression in HBV‐infected HCC cells promoted intra‐tumoural cytotoxic lymphocyte infiltration via vascular normalisation by inhibiting the Rho‐ROCK‐myosin light chain (MLC) signalling cascade, resulting in enhanced efficacy of immunotherapy. Furthermore, UTMD‐mediated BMP9 delivery restored the anti‐tumour function of cytotoxic lymphocytes (NK cells) and showed therapeutic efficacy in combination with a PD‐L1 antibody in human cancer xenografts of immune‐deficient mice. Conclusions HBV‐induced BMP9 downregulation causes vascular abnormalities that inhibit intra‐tumoural cytotoxic lymphocyte infiltration, providing a rationale for developing and combining immunotherapy with BMP9‐based therapy to treat HBV‐associated HCC.

Ferroptosis is a form of regulated cell death characterized by iron overload, overwhelming lipid peroxidation, and disruption of antioxidant systems. Emerging evidence suggests that ferroptosis is associated with pregnancy related diseases, such as spontaneous abortion, pre-eclampsia, gestational diabetes mellitus, intrahepatic cholestasis of pregnancy, and spontaneous preterm birth. According to these findings, inhibiting ferroptosis might be a potential option to treat pregnancy related diseases. This review summarizes the mechanisms and advances of ferroptosis, the pathogenic role of ferroptosis in pregnancy related diseases and the potential medicines for its treatment.

Ultrasound (US) is considered as a secure external stimulation for different biomedical applications because it is non-invasive, non-toxic and it brings no radiation pollution. Compared with traditional ultrasonography application, US has now attracted more and more attention for cancer therapy. It treats cancer in deeper tissues because it penetrates far than light does. New types of nanomaterials have been developed for US triggered cancer therapy. The study on emerging cancer therapeutic modality triggered by US is also increasing, e.g., high intensity-focused ultrasound (HIFU) therapy, sonodynamic therapy (SDT), and US-mediated drug delivery. The research on current advances in nanomaterials-based and US-triggered cancer treatments have been discussed in detail in this review, especially the underlying mechanisms for better therapeutic effectiveness. Furthermore, challenges and prospective in the evolution of nanomaterials for the US-based cancer therapy fields were also explained. It is anticipated that our manifestation in this expanding discipline will aid in the advancement of US-based basic research and therapeutic applications.

Abstract Background To assess the stiffness of benign breast masses in ultrasound images with posterior acoustic shadowing (PAS) and malignant lesions, and explore the significance of differential diagnosis using ultrasound real time shear wave elastography. Material and methods All 117 mammary masses (98 patients) with PAS were assessed by using routine ultrasound examination, and elastic modulus values were obtained with the real time shear wave elastography mode. All breast lesions were confirmed by surgery or biopsy. The significance of differences in ultrasound elastography values between breast benign and malignant masses with posterior acoustic shadowing was assessed, and the ROC curves of elasticity modulus values were analyzed. Results Among the 117 masses, 72 were benign and 45 were malignant. The two types of breast masses showed significant differences in size, margin, internal echo, calcification, and blood flow characteristics (P 0.05). Emean, Emax and Esd obtained with real time shear wave elastography showed statistically significant differences between benign masses with posterior acoustic shadowing and breast cancer (P

This study addresses the analysis of complex multivariate survival data, where each individual may experience multiple events and a wide range of relevant covariates are available. We propose an advanced modeling approach that extends the classical shared frailty framework to account for within-subject dependence. Our model incorporates a flexible frailty distribution, encompassing well-known distributions, such as gamma, log-normal, and inverse Gaussian. To ensure accurate estimation and effective model selection, we utilize innovative regularization techniques. The proposed methodology exhibits desirable theoretical properties and has been validated through comprehensive simulation studies. Additionally, we apply the approach to real-world data from the Medical Information Mart for Intensive Care (MIMIC-III) dataset, demonstrating its practical utility in analyzing complex survival data structures.

Abstract Background A noninvasive left ventricular (LV) pressure-strain loop (PSL) provides a new method to quantify myocardial work (MW) by combining global longitudinal strain (GLS) and LV pressure, which exerts potential advantages over traditional GLS. We studied the LV PSL and MW in patients with type 2 diabetes mellitus (T2DM). Methods This cross-sectional study included 201 subjects (54 healthy controls and 147 T2DM patients) who underwent complete two-dimensional echocardiography (2DE), including 2D speckle-tracking echocardiography (STE), as well as brachial artery pulse pressure measurement. The PSL was used to determine the global myocardial work index (GWI), global constructive work (GCW), global wasted work (GWW), and global work efficiency (GWE) of all study participants. The association between T2DM and LV function was evaluated according to these MW indices. Results The GLS was significantly lower in the T2DM group than in the control group (P

Summary: The research of AI-assisted breast diagnosis has primarily been based on static images. It is unclear whether it represents the best diagnosis image.To explore the method of capturing complementary responsible frames from breast ultrasound screening by using artificial intelligence. We used feature entropy breast network (FEBrNet) to select responsible frames from breast ultrasound screenings and compared the diagnostic performance of AI models based on FEBrNet-recommended frames, physician-selected frames, 5-frame interval-selected frames, all frames of video, as well as that of ultrasound and mammography specialists. The AUROC of AI model based on FEBrNet-recommended frames outperformed other frame set based AI models, as well as ultrasound and mammography physicians, indicating that FEBrNet can reach level of medical specialists in frame selection.FEBrNet model can extract video responsible frames for breast nodule diagnosis, whose performance is equivalent to the doctors selected responsible frames.

IntroductionControversies surround the issue if chronic consumption of a high-sugar diet is detrimental to health or not. This study investigates whether lifelong consumption of a higher sucrose diet will induce overeating, and obesity, and cause metabolic dysfunctions such as hyperglycemia and dyslipidaemia in C57BL/6N mice, compared to a lower sucrose diet.MethodsMale C57BL/6N mice at 3 weeks of age were randomized into consuming a diet with 25 or 10% kcal from sucrose for the rest of their lives. Body weight, food and water intake, fasting blood glucose, insulin, and lipid levels were measured at regular intervals. At the end of the study, organs and tissues were collected and gene expression was measured.ResultsThere was no discernible difference in the impact on food intake, body composition, glucose and lipid homeostasis, liver triglyceride content, life expectancy, as well as gene expression related to intermediary metabolism between mice fed a diet with 10 vs. 25% kcal as sucrose over their lifespan. We also showed that switching from a 25% kcal diet to a 10% kcal diet at different life stages, or vice versa, did not appear to affect these outcomes of interest.DiscussionThe results from our study suggest that lifelong consumption of a higher sugar diet generally did not induce overeating and obesity, disrupt carbohydrate metabolism and lipid homeostasis, and reduce life expectancy compared with a lower sugar diet. Our unorthodox findings disagreed with the popular belief that higher sugar consumption is detrimental to health, which should be confirmed in future studies.

Purpose The aim of this study was to evaluate the value of elastography in the differential diagnosis of benign versus malignant testicular lesions. Methods The PubMed, Cochrane Library, and Embase databases were searched for relevant studies. The diagnostic accuracy of elastography was evaluated using pooled sensitivity, specificity, likelihood ratio, post-test probability, diagnostic odds ratio, and by summarizing the area under the hierarchical summary receiver operating characteristic (HSROC) curve. Results Seven studies with 568 lesions were included. The pooled sensitivity and specificity were 87% (95% confidence interval [CI], 81% to 92%) and 81% (95% CI, 65% to 90%), respectively. The pooled estimates of the positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were 4.48 (95% CI, 2.37 to 8.47), 0.16 (95% CI, 0.10 to 0.25), and 28.11 (95% CI, 11.39 to 69.36), respectively. The area under the HSROC curve was 90% (95% CI, 88% to 93%). Conclusion Elastography is useful for assessing the stiffness of testicular lesions and for differentiating benign from malignant lesions. Elastography can be an effective supplement to conventional ultrasonography.

Abstract Background Plant miRNAs are involved in the response to biotic and abiotic stresses by altering their expression levels, and they play an important role in the regulation of plant resistance to stress. However, the molecular mechanism that regulates the expression levels of miRNAs in plants with biotic and abiotic stress still needs to be explored. Previously, we found that the expression of the miR482 family was changed in tomato infected by Botrytis cinerea. In this study, we investigated and uncovered the mechanism underlying the response of miR482 to B. cinerea infection in tomato. Results First, RT-qPCR was employed to detect the expression patterns of miR482b in tomato infected by B. cinerea, and results showed that miR482b primary transcripts (pri-miR482b) were up-regulated in B. cinerea-infected leaves, but the mature miR482b was down-regulated. Subsequently, we used rapid amplification cDNA end method to amplify the full-length of pri-miR482b. Result showed that the pri-miR482b had two isoforms, with the longer one (consisting 300 bp) having an extra fragment of 53 bp in the 3’-end compared with the shorter one. In vitro Dicer assay indicated that the longer isoform pri-miR482b-x1 had higher efficiency in the post-transcriptional splicing of miRNA than the shorter isoform pri-miR482b-x2. In addition, the transcription level of mature miR482b was much higher in transgenic Arabidopsis overexpressing pri-miR482b-x1 than that in OE pri-miR482b-x2 Arabidopsis. These results confirmed that this extra 53 bp in pri-miR482b-x1 might play a key role in the miR482b biogenesis of post-transcription processing. Conclusions Extra 53 bp in pri-miR482b-x1 enhanced miR482b biogenesis, which elevated the transcription level of miR482b. This study clarified the response of miR482 to B. cinerea infection in tomato, thereby helping us further understand the molecular mechanisms that regulate the expression levels of other miRNAs.

Abstract Background Placenta previa and accreta are serious obstetric conditions that are associated with a high risk of intraoperative massive hemorrhage, the prophylactic intravascular balloon occlusion technique is increasingly used in managing uncontrolled hemorrhage in cesarean section (CS). We aim to examine the clinical effectiveness of prophylactic balloon occlusion of the internal iliac artery (PBOIIA) during CS in improving maternal outcomes for patients with placenta previa and accreta. Methods A total of 420 women with placenta previa and accreta who underwent CS from January 2014 to December 2018 were included retrospectively. Patients were divided into balloon group in which patients had PBOIIA (n = 248) and the control group in which patients did not have PBOIIA (n = 172). Meanwhile, we performed a subgroup analysis in whether taking parallel transverse uterine incision (PTUI) surgery. Information on conditions of patients and newborns, perioperative blood indicators, surgical outcomes were collected. Results Median estimated blood loss (mEBL) was 2200 mL in the balloon group and 2150 mL in the control group respectively, there was no significant difference between two-groups comparison (P > 0.05), and the rate of patients with hysterectomy was also has no difference between the two groups (36.3% verus 35.5%, P > 0.05), while there is a significant difference between two groups in the amount of PRBCs transfused [3 (0–31.5) verus 3 (0–39), P 8 units in the balloon group is significantly lower than that in control group (11.29% verus 23.26%, P 0.05), but it could significantly decrease hysterectomy rates (P

The global surface temperature has witnessed a warming hiatus in the first decade of this century, but how this slowing down of warming will impact spring phenology over Pan-Third Pole remains unclear. Here, we combined multiple satellite-derived vegetation indices with eddy covariance datasets to evaluate the spatiotemporal changes in spring phenological changes over the Pan-Third Pole. We found that the spring phenology over Pan-Third Pole continues to advance at the rate of 4.8 days decade-1 during the warming hiatus period, which is contrasted to a non-significant change over the northern hemisphere. Such a significant and continued advance in spring phenology was mainly attributed to an increase in preseason minimum temperature and water availability. Moreover, there is an overall increasing importance of precipitation on changes in spring phenology during the last four decades. We further demonstrated that this increasingly negative correlation was also found across more than two-thirds of the dryland region, tentatively suggesting that spring phenological changes might shift from temperature to precipitation-controlled over the Pan-Third Pole in a warmer world.

ObjectivesTo investigate the feasibility of the vector flow imaging (V Flow) technique to measure peripheral arterial hemodynamic parameters, including wall shear stress (WSS) and turbulence index (Tur) in healthy adults, and compare the results in different arteries.Materials and methodsFifty-two healthy adult volunteers were recruited in this study. The maximum and mean values of WSS, and the Tur values at early-systole, mid-systole, late-systole, and early diastole for total 156 normal peripheral arteries [common carotid arteries (CCA), subclavian arteries (SCA), and common femoral arteries (CFA)] were assessed using the V Flow technique.ResultsThe mean WSS values for CCA, SCA, and CFA were (1.66 ± 0.68) Pa, (0.62 ± 0.30) Pa, and (0.56 ± 0.27) Pa, respectively. The mean Tur values for CCA, SCA, and CFA were (0.46 ± 1.09%), (20.7 ± 9.06%), and (24.63 ± 17.66%), respectively. The CCA and SCA, as well as the CCA and CFA, showed statistically significant differences in the mean WSS and the mean Tur (P < 0.01). The mean Tur values had a negative correlation with the mean WSS; the correlation coefficient between log(Tur) and WSS is −0.69 (P < 0.05).ConclusionV Flow technique is a simple, practical, and feasible quantitative imaging approach for assessing WSS and Tur in peripheral arteries. It has the potential to be a useful tool for evaluating atherosclerotic plaques in peripheral arteries. The results provide a new quantitative foundation for future investigations into diverse arterial hemodynamic parameters.

Objective: We aim to establish a deep learning model called multimodal ultrasound fusion network (MUF-Net) based on gray-scale and contrast-enhanced ultrasound (CEUS) images for classifying benign and malignant solid renal tumors automatically and to compare the model’s performance with the assessments by radiologists with different levels of experience.Methods: A retrospective study included the CEUS videos of 181 patients with solid renal tumors (81 benign and 100 malignant tumors) from June 2012 to June 2021. A total of 9794 B-mode and CEUS-mode images were cropped from the CEUS videos. The MUF-Net was proposed to combine gray-scale and CEUS images to differentiate benign and malignant solid renal tumors. In this network, two independent branches were designed to extract features from each of the two modalities, and the features were fused using adaptive weights. Finally, the network output a classification score based on the fused features. The model’s performance was evaluated using five-fold cross-validation and compared with the assessments of the two groups of radiologists with different levels of experience.Results: For the discrimination between benign and malignant solid renal tumors, the junior radiologist group, senior radiologist group, and MUF-Net achieved accuracy of 70.6%, 75.7%, and 80.0%, sensitivity of 89.3%, 95.9%, and 80.4%, specificity of 58.7%, 62.9%, and 79.1%, and area under the receiver operating characteristic curve of 0.740 (95% confidence internal (CI): 0.70–0.75), 0.794 (95% CI: 0.72–0.83), and 0.877 (95% CI: 0.83–0.93), respectively.Conclusion: The MUF-Net model can accurately classify benign and malignant solid renal tumors and achieve better performance than senior radiologists.Key points: The CEUS video data contain the entire tumor microcirculation perfusion characteristics. The proposed MUF-Net based on B-mode and CEUS-mode images can accurately distinguish between benign and malignant solid renal tumors with an area under the receiver operating characteristic curve of 0.877, which surpasses senior radiologists’ assessments by a large margin.

ObjectivesThe goal of this work is to determine the clinical value of the transverse carpal ligament (TCL) in carpal tunnel syndrome (CTS) for guiding subsequent treatment.MethodsThis study analyzed patients who underwent median nerve (MN) ultrasound (US) examination of the wrist from April 2020 to April 2021. The cross-sectional area and anteroposterior diameter of the MN, as well as the TCL thickness and stiffness, were measured from images. The intra-group and intra-patient subgroup differences were compared using a t-test and a rank test. We also utilized receiver operating characteristic (ROC) curves to diagnose CTS and evaluate the severity.ResultsThe final cohort consisted of 120 wrists (bilateral) from 60 samples, evenly balanced across the patient and control groups according to their CTS diagnosis. In the unilateral positive patient subgroup, the MN and TCL of the positive hand were significantly thicker and stiffer than the negative counterparts (both, p < 0.05). The values from the right were also thicker and stiffer than the left (both, p < 0.05) in patients with bilateral CTS. The MN and TCL of the patient group were also significantly thicker and stiffer than those of the control group (both, p < 0.001). For diagnosing CTS, the area under the curve (AUC) of TCL thickness and stiffness at the distal carpal tunnel (DCT) ranged between 0.925 and 0.967. For evaluating CTS severity, we found that the optimal TCL stiffness is sufficient for diagnosing mild and non-mild patient cases (AUC: Emean = 0.757, Emax = 0.779).ConclusionsShear wave elastography is therefore an effective method for CTS diagnosis and management.

PurposeThe purpose of this study was to explore the performance of different parameter combinations of deep learning (DL) models (Xception, DenseNet121, MobileNet, ResNet50 and EfficientNetB0) and input image resolutions (REZs) (224 × 224, 320 × 320 and 488 × 488 pixels) for breast cancer diagnosis.MethodsThis multicenter study retrospectively studied gray-scale ultrasound breast images enrolled from two Chinese hospitals. The data are divided into training, validation, internal testing and external testing set. Three-hundreds images were randomly selected for the physician-AI comparison. The Wilcoxon test was used to compare the diagnose error of physicians and models under P=0.05 and 0.10 significance level. The specificity, sensitivity, accuracy, area under the curve (AUC) were used as primary evaluation metrics.ResultsA total of 13,684 images of 3447 female patients are finally included. In external test the 224 and 320 REZ achieve the best performance in MobileNet and EfficientNetB0 respectively (AUC: 0.893 and 0.907). Meanwhile, 448 REZ achieve the best performance in Xception, DenseNet121 and ResNet50 (AUC: 0.900, 0.883 and 0.871 respectively). In physician-AI test set, the 320 REZ for EfficientNetB0 (AUC: 0.896, P < 0.1) is better than senior physicians. Besides, the 224 REZ for MobileNet (AUC: 0.878, P < 0.1), 448 REZ for Xception (AUC: 0.895, P < 0.1) are better than junior physicians. While the 448 REZ for DenseNet121 (AUC: 0.880, P < 0.05) and ResNet50 (AUC: 0.838, P < 0.05) are only better than entry physicians.ConclusionBased on the gray-scale ultrasound breast images, we obtained the best DL combination which was better than the physicians.

Canine adenovirus type 1 (CAdV-1) is a double-stranded DNA virus, which is the causative agent of fox encephalitis. The Fiber protein is one of the structural proteins in CAdV-1, which mediates virion binding to the coxsackievirus and adenovirus receptor on host cells. The suspected virus was cultured in the MDCK cells, and it was determined through the cytopathic effects, sequencing and electron microscopy. The informatics analysis of the Fiber was done using online bioinformatics servers. The CAdV-1-JL2021 strain was isolated successfully, and were most similar to the CAdV-1 strain circulating in Italy. The occurrence of negative selection and recombination were found in the CAdV-1-JL2021 and CAdV-2-AC_000020.1. Host cell membrane was its subcellular localization. The CAdV-1-JL2021 Fiber (ON164651) had 6 glycosylation sites and 107 phosphorylation sites, exerted adhesion receptor-mediated virion attachment to host cell, which was the same as CAdV-2-AC_000020.1 Fiber. The Fiber tertiary structure of the CAdV-1-JL2021 and CAdV-2-AC_000020.1 was different, but they had the same coxsackievirus and adenovirus receptor. “VATTSPTLTFAYPLIKNNNH” were predicted to be the potential CAdV-1 B cell linear epitope. The MHC-I binding peptide “KLGVKPTTY” were both presented in the CAdV-1-JL2021 and CAdV-2-AC_000020.1 Fiber and it is useful to design the canine adenovirus vaccine.

Fetal heart rate (FHR) is an essential indicator of fetal well-being. The ultrasonic Doppler FHR detector is widely used to monitor the fetus’s health due to its advantages of non-invasion, high sensitivity, and good directivity. However, the existing commercial Doppler FHR detector primarily uses an analog multiplier for demodulation, which has limited functions and insufficient sensitivity. The analog demodulation is performed only on a single-sideband signal(in-phase or quadrature) (IQ), which is impossible to derive the fetal heart movement’s vector velocity. Moreover, repetitive recognition of the mitral valve’s positive and negative motion easily causes the measured FHR twice the actual one (FHR doubling). Although the traditional digital demodulation FHR detector can obtain in-phase and quadrature demodulation signals, it needs a high-level field-programmable gate array chip and therefore cannot meet low-power consumption requirements in battery-powered situations. Herein we proposed a novel digital demodulation FHR algorithm using time-domain windowing. Then, we applied the algorithm into a low-power complex programmable logic device to achieve low-cost acquisition of vector velocity and suppress FHR doubling and finally designed a hand-held, noninvasive digital Doppler FHR detection system for continuous perinatal detection. In this work, the comparison curve between the TREND curve generated by the simulator and the measured curve of our FHR detector was obtained. The comparative experiment between the commercial FM-3A FHR detector and our proposed FHR detector was performed, and the relative error and standard error of the obtained FHR data were used to evaluate the two FHR detectors’ detection accuracy. The results showed that our FHR detector showed excellent detection accuracy at an accuracy rate of 98%, which was much higher than the average accuracy of the FM-3A FHR detector and indicated our proposed digital FHR detector showed excellent detection performance. It means that the proposed digital windowed FHR demodulation algorithm is practical, the multi-FHR monitoring system is feasible, and our proposed FHR detector has high detection accuracy, effectively suppresses FHR doubling, and meets the requirements of Chinese national standards. It provides an alternative scheme towards the low-cost hand-held digital demodulation FHR detection application.

Introduction: We compare the differences in the diagnostic results of S-thyroid, a computer-aided diagnosis (CAD) software, based on two mutually perpendicular planes.Methods: Initially, 149 thyroid nodules confirmed by surgical pathology were enrolled in our study. CAD in our study was based on the ACR TI-RADS lexicon. t test, rank-sum test, and Chi-square test were used. The interclass correlation coefficient and Cohen’s kappa were used to explore the correlation between CAD features. Receiver operating characteristic was plotted for different combinations of CAD features.Results: The patient’s age, transverse diameter, longitudinal diameter, shape, margin, echogenicity, echogenic foci, composition, TI-RADS classification, and risk probability of nodules in the transverse and longitudinal planes were related to thyroid cancer (p < 0.05). The AUC (95%CI) of TI-RADS classification in the transverse plane of CAD is better than that of the longitudinal plane [0.90 (0.84–0.95) vs. 0.83 (0.77–0.90), p = 0.04]. The AUC (95%CI) of risk probability of nodules in the transverse planes shows no difference from that in the longitudinal plane statistically [0.90 (0.85–0.95) vs. 0.88 (0.82–0.94), p = 0.52]. The AUC (95% CI), specificity, sensitivity, and accuracy [TI-RADS classification (transverse plane) + TI-RADS classification (longitudinal plane) + risk (transverse plane) + risk (longitudinal plane)] are 0.93 (0.89–0.97), 86.15%, 90.48%, and 88.59%, respectively.Conclusion: The diagnosis of thyroid cancer in the CAD transverse plane was superior to that in the CAD longitudinal plane when using the TI-RADS classification, but there was no difference in the diagnosis between the two planes when using risk. However, the combination of CAD transverse and longitudinal planes had the best diagnostic ability.

PurposeTo develop a risk stratification system that can predict axillary lymph node (LN) metastasis in invasive breast cancer based on the combination of shear wave elastography (SWE) and conventional ultrasound.Materials and MethodsA total of 619 participants pathologically diagnosed with invasive breast cancer underwent breast ultrasound examinations were recruited from a multicenter of 17 hospitals in China from August 2016 to August 2017. Conventional ultrasound and SWE features were compared between positive and negative LN metastasis groups. The regression equation, the weighting, and the counting methods were used to predict axillary LN metastasis. The sensitivity, specificity, and the areas under the receiver operating characteristic curve (AUC) were calculated.ResultsA significant difference was found in the Breast Imaging Reporting and Data System (BI-RADS) category, the “stiff rim” sign, minimum elastic modulusof the internal tumor and peritumor region of 3 mm between positive and negative LN groups (p < 0.05 for all). There was no significant difference in the diagnostic performance of the regression equation, the weighting, and the counting methods (p > 0.05 for all). Using the counting method, a 0–4 grade risk stratification system based on the four characteristics was established, which yielded an AUC of 0.656 (95% CI, 0.617–0.693, p < 0.001), a sensitivity of 54.60% (95% CI, 46.9%–62.1%), and a specificity of 68.99% (95% CI, 64.5%–73.3%) in predicting axillary LN metastasis.ConclusionA 0–4 grade risk stratification system was developed based on SWE characteristics and BI-RADS categories, and this system has the potential to predict axillary LN metastases in invasive breast cancer.