Uric Acid Inhibits Mice Pancreatic Steatosis via the Glycerophospholipid Pathway.

Background: despite evidence for mutually reinforcing effects of serum uric acid (SUA) and lipids, the effects of uric levels on pancreatic steatosis are not well-established. In this study, the relationship between low concentrations of uric acid and pancreatic steatosis was evaluated. Methods: forty C57BL/6J mice were fed a diet of high uric acid (HU), high fat (HF), high uric acid and high fat (HUHF), and normal control (NC) (10 mice in each group). Weight was measured weekly. Ultrasonography was performed to observe the pancreatic echo intensity of all mice before the end of feeding. Subsequently, peripheral blood was taken for biochemical examination. Intact pancreatic tissues were taken, part of which was used for pathological examination, part of which was used for PCR experiments and Western Blot experiments to obtain glycerophospholipid-associated mRNA data and protein levels. Results: body weight was significantly higher in the HF group than in the other three groups. Higher uric acid matched lower total cholesterol and triglyceride, matched higher low-density lipoprotein, and matched equal high-density lipoprotein. Ultrasound images and HE staining of pancreatic tissues of mice showed that higher uric acid matched lower fat content. The mRNA levels of phospholipase A2 group IB were highest in high uric acid group, while relative protein expression levels were lowest in high uric acid and control groups. Phospholipase A2 group IIA showed the opposite patterns. Conclusions: elevated serum uric acid at low concentrations can inhibit pancreatic steatosis, which is modulated via the glycerophospholipid metabolic pathway.

Multimodal PA/US imaging in Rheumatoid Arthritis: Enhanced correlation with clinical scores.

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.

Incidence of chemotherapy-related cardiac dysfunction in cancer patients.

BACKGROUND: Cancer patients are increasingly affected by chemotherapy-related cardiac dysfunction. The reported incidence of this condition vary significantly across different studies. HYPOTHESIS: A better comprehensive understanding of chemotherapy-related cardiac dysfunction incidence in cancer patients is imperative. Therefore, we performed a meta-analysis to establish the overall incidence of chemotherapy-related cardiac dysfunction in cancer patients. METHODS: We searched articles in PubMed and EMBASE from database inception to May 1, 2023. Studies that reported the incidence of chemotherapy-related cardiac dysfunction in cancer patients were included. RESULTS: A total of 53 studies involving 35 651 individuals were finally included in the meta-analysis. The overall pooled incidence of chemotherapy-related cardiac dysfunction in cancer patients was 63.21 per 1000 person-years (95% CI: 57.28-69.14). The chemotherapy-related cardiac dysfunction incidence increased steeply within half a year of cancer chemotherapy. Also, the trend of chemotherapy-related cardiac dysfunction incidence appeared to have plateaued after a longer duration of follow-up. In addition, chemotherapy-related cardiac dysfunction incidence rates are significantly higher among patients with age ≥50 years versus patients with age <50 years (99.96 vs. 34.48 per 1000 person-years). The incidence rate of cardiac dysfunction was higher among breast cancer patients (72.97 per 1000 person-years), leukemia patients (65.21 per 1000 person-years), and lymphoma patients (55.43 per 1000 person-years). CONCLUSION: Our meta-analysis unveiled a definitive overall incidence rate of chemotherapy-related cardiac dysfunction in cancer patients. In addition, it was found that the risk of developing this condition escalates within the initial 6 months postchemotherapy, subsequently tapering off to become statistically insignificant after a duration of 6 years.

Trialkoxysilane-Induced Iridium-Catalyzed para-Selective C-H Bond Borylation of Arenes.

An ideal approach for the construction of aryl boron compounds is to selectively replace a C-H bond in arenes with a C-B bond, and controlling regioselectivity is one of the most challenging aspects of these transformations. Herein, we report an iridium-catalyzed trialkoxysilane protecting group-assisted regioselective C-H borylation of arenes, including derivatives of benzaldehydes, acetophenones, benzoic acids, benzyl alcohols, phenols, aryl silanes, benzyl silanes, and multi-functionalized aromatic rings are all well tolerated and gave the para -selective C-H borylation products in a short time without the requirement of inert gases atmosphere. The site-selective C-H borylation can be adjustable by installing the developed trialkoxysilane protecting group on different functional groups on one aromatic ring. Importantly, the preparation process of the trialkoxychlorosilane is efficient and scalable. Mechanistic and computational studies reveal that the steric hindrance of the trialkoxysilane protecting group plays a key role in dictating the para-selectivity.

Predictive value of anthropometric and biochemical indices in non-alcoholic fatty pancreas disease: a cross-sectional study.

OBJECTIVES: Triglyceride (TG), triglyceride-glucose index (TyG), body mass index (BMI), TyG-BMI and triglyceride to high-density lipoprotein ratio (TG/HDL) have been reported to be reliable predictors of non-alcoholic fatty liver disease. However, there are few studies on potential predictors of non-alcoholic fatty pancreas disease (NAFPD). Our aim was to evaluate these and other parameters for predicting NAFPD. DESIGN: Cross-sectional study design. SETTING: Physical examination centre of a tertiary hospital in China. PARTICIPANTS: This study involved 1774 subjects who underwent physical examinations from January 2016 to September 2016. PRIMARY AND SECONDARY OUTCOME MEASURES: From each subject, data were collected for 13 basic physical examination and blood biochemical parameters: age, weight, height, BMI, TyG, TyG-BMI, high-density lipoprotein (HDL), low-density lipoprotein, total cholesterol, TG, fasting plasma glucose, TG/HDL and uric acid. NAFPD was diagnosed by abdominal ultrasonography. A logistic regression model with a restricted cubic spline was used to evaluate the relationship between each parameter and NAFPD. The receiver operating characteristic (ROC) curve was used to calculate the area under the curve for each parameter. RESULTS: HDL was negatively correlated with NAFPD, height was almost uncorrelated with NAFPD and the remaining 11 parameters were positively correlated with NAFPD. ROC curve showed that weight-related parameters (weight, BMI and TyG-BMI) and TG-related parameters (TyG, TG and TG/HDL) had high predictive values for the identification of NAFPD. The combinations of multiple parameters had a better prediction effect than a single parameter. All the predictive effects did not differ by sex. CONCLUSIONS: Weight-related and TG-related parameters are good predictors of NAFPD in all populations. BMI showed the greatest predictive potential. Multiparameter combinations appear to be a good way to predict NAFPD.

Role of RB1 in neurodegenerative diseases: inhibition of post-mitotic neuronal apoptosis via Kmt5b.

During the development of the vertebrate nervous system, 50% of the nerve cells undergo apoptosis shortly after formation. This process is important for sculpting tissue during morphogenesis and removing transiently functional cells that are no longer needed, ensuring the appropriate number of neurons in each region. Dysregulation of neuronal apoptosis can lead to neurodegenerative diseases. However, the molecular events involved in activating and regulating the neuronal apoptosis program are not fully understood. In this study, we identified several RB1 mutations in patients with neurodegenerative diseases. Then, we used a zebrafish model to investigate the role of Rb1 in neuronal apoptosis. We showed that Rb1-deficient mutants exhibit a significant hindbrain neuronal apoptosis, resulting in increased microglia infiltration. We further revealed that the apoptotic neurons in Rb1-deficient zebrafish were post-mitotic neurons, and Rb1 inhibits the apoptosis of these neurons by regulating bcl2/caspase through binding to Kmt5b. Moreover, using this zebrafish mutant, we verified the pathogenicity of the R621S and L819V mutations of human RB1 in neuronal apoptosis. Collectively, our data indicate that the Rb1-Kmt5b-caspase/bcl2 axis is crucial for protecting post-mitotic neurons from apoptosis and provides an explanation for the pathogenesis of clinically relevant mutations.

Optimizing breast cancer diagnosis with photoacoustic imaging: An analysis of intratumoral and peritumoral radiomics.

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.

A role for Retinoblastoma 1 in hindbrain morphogenesis by regulating GBX family.

The hindbrain, which develops from the anterior end of the neural tube expansion, can differentiate into the metencephalon and myelencephalon, with varying sizes and functions. The midbrain-hindbrain boundary (MHB) and hindbrain myelencephalon/ventral midline (HMVM) are known to be the source of the progenitors for the anterior hindbrain and myelencephalon, respectively. However, the molecular networks regulating hindbrain morphogenesis in these structures remain unclear. In this study, we show that retinoblastoma 1 (rb1) is highly expressed at the MHB and HMVM in zebrafish. Knocking out rb1 in mice and zebrafish results in an enlarged hindbrain due to hindbrain neuronal hyperproliferation. Further study reveals that Rb1 controls the hindbrain morphogenesis by suppressing the expression of Gbx1/Gbx2, essential transcription factors for hindbrain development, through its binding to E2f3/Hdac1, respectively. Interestingly, we find that Gbx1 and Gbx2 are expressed in different types of hindbrain neurons, suggesting distinct roles in hindbrain morphogenesis. In summary, our study clarifies the specific role of RB1 in hindbrain neural cell proliferation and morphogenesis by regulating the E2f3-Gbx1 axis and the Hdac1-Gbx2 axis. These findings provide a research paradigm for exploring the differential proliferation of neurons in various brain regions.

Photoacoustic Imaging Radiomics to Identify Breast Cancer in BI-RADS 4 or 5 Lesions.

OBJECTIVES: To develop a nomogram based on photoacoustic imaging (PAI) radiomics and BI-RADs to identify breast cancer (BC) in BI-RADS 4 or 5 lesions detected by ultrasound (US). METHODS: In this retrospective study, 119 females with 119 breast lesions at US and PAI examination were included (January 2022 to December 2022). Patients were divided into the training set (n = 83) or testing set (n = 36) to develop a nomogram to identify BC in BI-RADS 4 or 5 lesions. Relevant factors at clinic, BI-RADS category, and PAI were reviewed. Univariate and multivariate regression was used to evaluate factors for associations with BC. To evaluate the diagnostic performance of nomogram, the area under the curve (AUC) of receiver operating characteristic curve, accuracy, specificity and sensitivity was employed. RESULTS: The nomogram that included BI-RADS category and PAI radiomics score demonstrated a high AUC of 0.925 (95%CI: 0.8467-0.9712) in the training set and 0.926 (95%CI: 0.846-1.000) in the test set. The nomogram also showed significantly better discrimination than the radiomics score (P = .048) or BI-RADS category (P = .009) in the training set. These significant differences were demonstrated in the testing set, outperform the radiomics score (P = .038) and BI-RADS category (P = .013). CONCLUSIONS: The nomogram developed with BI-RADS and PAI radiomics score can effectively identify BC in BI-RADS 4 or 5 lesions. This technique has the potential to further improve early diagnostic accuracy for BC.

Targeting TNF/IL-17/MAPK pathway in hE2A-PBX1 leukemia: effects of OUL35, KJ-Pyr-9, and CID44216842.

t(1;19)(q23;p13) is one of the most common translocation genes in childhood acute lymphoblastic leukemia (ALL) and is also present in acute myeloid leukemia (AML) and mixed-phenotype acute leukemia (MPAL). This translocation results in the formation of the oncogenic E2A-PBX1 fusion protein, which contains a trans-activating domain from E2A and a DNA-binding homologous domain from PBX1. Despite its clear oncogenic potential, the pathogenesis of E2A-PBX1 fusion protein is not fully understood (especially in leukemias other than ALL), and effective targeted clinical therapies have not been developed. To address this, we established a stable and heritable zebrafish line expressing human E2A-PBX1 (hE2APBX1) for high-throughput drug screening. Blood phenotype analysis showed that hE2APBX1 expression induced myeloid hyperplasia by increasing myeloid differentiation propensity of hematopoietic stem cells (HSPCs) and myeloid proliferation in larvae, and progressed to AML in adults. Mechanistic studies revealed that hE2A-PBX1 activated the TNF/IL-17/MAPK signaling pathway in blood cells and induced myeloid hyperplasia by upregulating the expression of the runx1. Interestingly, through high-throughput drug screening, three small molecules targeting the TNF/IL-17/MAPK signaling pathway were identified, including OUL35, KJ-Pyr-9, and CID44216842, which not only alleviated the hE2A-PBX1- induced myeloid hyperplasia in zebrafish but also inhibited the growth and oncogenicity of human pre-B ALL cells with E2A-PBX1. Overall, this study provides a novel hE2A-PBX1 transgenic zebrafish leukemia model and identifies potential targeted therapeutic drugs, which may offer new insights into the treatment of E2A-PBX1 leukemia.

Comparative study of ultrasound attenuation analysis and controlled attenuation parameter in the diagnosis and grading of liver steatosis in non-alcoholic fatty liver disease patients.

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 < 0.05). There was a strong positive correlation between USAT and CAP (r = 0.674, p < 0.0001). When using CAP as the reference, the optimal cut-off values for diagnosing and predicting different levels of hepatic steatosis with USAT were as follows: the cut-off value for excluding the presence of hepatic steatosis was 0.54 dB/cm/MHz (AUC 0.96); for mild hepatic steatosis, it was 0.59 dB/cm/MHz (AUC 0.86); for moderate hepatic steatosis, it was 0.73 dB/cm/MHz (AUC 0.81); and for severe hepatic steatosis, it was 0.87 dB/cm/MHz (AUC 0.87). CONCLUSION: USAT exhibits strong diagnostic performance for hepatic steatosis and shows a high correlation with CAP values.

Diagnostic Performance of Deep Learning in Video-Based Ultrasonography for Breast Cancer: A Retrospective Multicentre Study.

OBJECTIVE: Although ultrasound is a common tool for breast cancer screening, its accuracy is often operator-dependent. In this study, we proposed a new automated deep-learning framework that extracts video-based ultrasound data for breast cancer screening. METHODS: Our framework incorporates DenseNet121, MobileNet, and Xception as backbones for both video- and image-based models. We used data from 3907 patients to train and evaluate the models, which were tested using video- and image-based methods, as well as reader studies with human experts. RESULTS: This study evaluated 3907 female patients aged 22 to 86 years. The results indicated that the MobileNet video model achieved an AUROC of 0.961 in prospective data testing, surpassing the DenseNet121 video model. In real-world data testing, it demonstrated an accuracy of 92.59%, outperforming both the DenseNet121 and Xception video models, and exceeding the 76.00% to 85.60% accuracy range of human experts. Additionally, the MobileNet video model exceeded the performance of image models and other video models across all evaluation metrics, including accuracy, sensitivity, specificity, F1 score, and AUC. Its exceptional performance, particularly suitable for resource-limited clinical settings, demonstrates its potential for clinical application in breast cancer screening. CONCLUSIONS: The level of expertise reached by the video models was greater than that achieved by image-based models. We have developed an artificial intelligence framework based on videos that may be able to aid breast cancer diagnosis and alleviate the shortage of experienced experts.

Assessment of Oxygen Saturation in Breast Lesions Using Photoacoustic Imaging: Correlation With Benign and Malignant Disease.

BACKGROUND: Hypoxia is a hallmark of breast cancer (BC). Photoacoustic (PA) imaging, based on the use of laser-generated ultrasound (US), can detect oxygen saturation (So2) in the tissues of breast lesion patients. PURPOSE: To measure the oxygenation status of tissue in and on both sides of the lesion in breast lesion participants using a multimodal Photoacoustic/ultrasound (PA/US) imaging system and to determine the correlation between So2 measured by PA imaging and benign or malignant disease. MATERIALS AND METHODS: Multimodal PA/US imaging and gray-scale US (GSUS) of breast lesion was performed in consecutive breast lesion participants imaged in the US Outpatient Clinic between 2022 and 2023. Dual-wavelength PA imaging was used to measure the So2 value inside the lesion and on both sides of the tissue, and to distinguish benign from malignant lesions based on the So2 value. The ability of So2 to distinguish benign from malignant breast lesions was evaluated by the receiver operating characteristic curve (ROC) and the De-Long test. RESULTS: A total of 120 breast lesion participants (median age, 42.5 years) were included in the study. The malignant lesions exhibited lower So2 levels compared to benign lesions (malignant: 71.30%; benign: 83.81%; P < .01). Moreover, PA/US imaging demonstrates superior diagnostic results compared to GSUS, with an area under the curve (AUC) of 0.89 versus 0.70, sensitivity of 89.58% versus 85.42%, and specificity of 86.11% versus 55.56% at the So2 cut-off value of 78.85 (P < .001). The false positive rate in GSUS reduced by 30.75%, and the false negative rate diminished by 4.16% with PA /US diagnosis. Finally, the So2 on both sides tissues of malignant lesions are lower than that of benign lesions (P < .01). CONCLUSION: PA imaging allows for the assessment of So2 within the lesions of breast lesion patients, thereby facilitating a superior distinction between benign and malignant lesions.

Cebp1 and Cebpß transcriptional axis controls eosinophilopoiesis in zebrafish.

Eosinophils are a group of granulocytes well known for their capacity to protect the host from parasites and regulate immune function. Diverse biological roles for eosinophils have been increasingly identified, but the developmental pattern and regulation of the eosinophil lineage remain largely unknown. Herein, we utilize the zebrafish model to analyze eosinophilic cell differentiation, distribution, and regulation. By identifying eslec as an eosinophil lineage-specific marker, we establish a Tg(eslec:eGFP) reporter line, which specifically labeled cells of the eosinophil lineage from early life through adulthood. Spatial-temporal analysis of eslec+ cells demonstrates their organ distribution from larval stage to adulthood. By single-cell RNA-Seq analysis, we decipher the eosinophil lineage cells from lineage-committed progenitors to mature eosinophils. Through further genetic analysis, we demonstrate the role of Cebp1 in balancing neutrophil and eosinophil lineages, and a Cebp1-Cebpß transcriptional axis that regulates the commitment and differentiation of the eosinophil lineage. Cross-species functional comparisons reveals that zebrafish Cebp1 is the functional orthologue of human C/EBPεP27 in suppressing eosinophilopoiesis. Our study characterizes eosinophil development in multiple dimensions including spatial-temporal patterns, expression profiles, and genetic regulators, providing for a better understanding of eosinophilopoiesis.

Correlation between oxygenation status of extra-synovial tissue of wrist and disease activity in rheumatoid arthritis: a photoacoustic imaging study.

OBJECTIVES: Rheumatoid arthritis (RA) is characterized by hypoxia in the synovial tissue. While photoacoustic imaging (PA) offers a method to evaluate tissue oxygenation in RA patients, studies exploring the link between extra-synovial tissue of wrist oxygenation and disease activity remain scarce. We aimed to assess synovial oxygenation in RA patients using a multimodal photoacoustic-ultrasound (PA/US) imaging system and establish its correlation with disease activity. METHODS: A retrospective study was conducted on 111 patients with RA and 72 healthy controls from 2022 to 2023. Dual-wavelength PA imaging quantified oxygen saturation (So2) levels in the synovial membrane and peri-wrist region. Oxygenation states were categorised as hyperoxia, intermediate oxygenation, and hypoxia based on So2 values. The association between oxygenation levels and the clinical disease activity index was evaluated using a one-way analysis of variance, complemented by the Kruskal-Wallis test with Bonferroni adjustment. RESULTS: Of the patients with RA, 39 exhibited hyperoxia, 24 had intermediate oxygenation, and 48 had hypoxia in the wrist extra-synovial tissue. All of the control participants exhibited the hyperoxia status. Oxygenation levels in patients with RA correlated with clinical metrics. Patients with intermediate oxygenation had a lower disease activity index compared with those with hypoxia and hyperoxia. CONCLUSION: A significant correlation exists between wrist extra-synovial tissue oxygenation and disease activity in patients with RA.

A validation of an entropy-based artificial intelligence for ultrasound data in breast tumors.

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.

The research on artificial intelligence-assisted breast diagnosis often relies on static images or dynamic videos obtained from ultrasound probes with different frequencies. However, the effect of frequency-induced image variations on the diagnostic performance of artificial intelligence models remains unclear. In this study, we aimed to explore the impact of using ultrasound images with variable frequencies on AI's diagnostic efficacy in breast ultrasound screening. Our approach involved employing a video and entropy-based feature breast network to compare the diagnostic efficiency and average two-dimensional image entropy of the 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) linear array probe and L13 (frequency range: 3.6-13.5 MHz, central frequency 8 MHz), and L7 (frequency range: 3-7 MHz, central frequency 4.0 MHz) linear array probes. The results revealed that the diagnostic efficiency of AI models differed based on the frequency of the ultrasound probe. It is noteworthy that ultrasound images acquired with different frequency probes exhibit different average two-dimensional image entropy, while higher average two-dimensional image entropy positively affect the diagnostic performance of the AI model. We concluded that a dataset with higher average two-dimensional image entropy is associated with superior diagnostic efficacy for AI-based breast diagnosis. These findings contribute to a better understanding of how ultrasound image variations impact AI-assisted breast diagnosis, potentially leading to improved breast cancer screening outcomes.

Development and validation of nomograms using photoacoustic imaging and 2D ultrasound to predict breast nodule benignity and malignancy.

BACKGROUND: The application of photoacoustic imaging (PAI), utilizing laser-induced ultrasound, shows potential in assessing blood oxygenation in breast nodules. However, its effectiveness in distinguishing between malignant and benign nodules remains insufficiently explored. PURPOSE: This study aims to develop nomogram models for predicting the benign or malignant nature of breast nodules using PAI. METHOD: A prospective cohort study enrolled 369 breast nodules, subjecting them to PAI and ultrasound examination. The training and testing cohorts were randomly divided into two cohorts in a ratio of 3:1. Based on the source of the variables, three models were developed, Model 1: photoacoustic-BIRADS+BMI + blood oxygenation, Model 2: BIRADS+Shape+Intranodal blood (Doppler) + BMI, Model 3: photoacoustic-BIRADS+BIRADS+ Shape+Intranodal blood (Doppler) + BMI + blood oxygenation. Risk factors were identified through logistic regression, resulting in the creation of three predictive models. These models were evaluated using calibration curves, subject receiver operating characteristic (ROC), and decision curve analysis. RESULTS: The area under the ROC curve for the training cohort was 0.91 (95% confidence interval, 95% CI: 0.88-0.95), 0.92 (95% CI: 0.89-0.95), and 0.97 (95% CI: 0.96-0.99) for Models 1-3, and the ROC curve for the testing cohort was 0.95 (95% CI: 0.91-0.98), 0.89 (95% CI: 0.83-0.96), and 0.97 (95% CI: 0.95-0.99) for Models 1-3. CONCLUSIONS: The calibration curves demonstrate that the model's predictions agree with the actual values. Decision curve analysis suggests a good clinical application.

Sonography-based multimodal information platform for identifying the surgical pathology of ductal carcinoma in situ.

BACKGROUND: The risk of ductal carcinoma in situ (DCIS) identified by biopsy often increases during surgery. Therefore, confirming the DCIS grade preoperatively is necessary for clinical decision-making. PURPOSE: To train a three-classification deep learning (DL) model based on ultrasound (US), combining clinical data, mammography (MG), US, and core needle biopsy (CNB) pathology to predict low-grade DCIS, intermediate-to-high-grade DCIS, and upstaged DCIS. MATERIALS AND METHODS: Data of 733 patients with 754 DCIS cases confirmed by biopsy were retrospectively collected from May 2013 to June 2022 (N1), and other data (N2) were confirmed by biopsy as low-grade DCIS. The lesions were randomly divided into training (n=471), validation (n=142), and test (n = 141) sets to establish the DCIS-Net. Information on the DCIS-Net, clinical (age and sign), US (size, calcifications, type, breast imaging reporting and data system [BI-RADS]), MG (microcalcifications, BI-RADS), and CNB pathology (nuclear grade, architectural features, and immunohistochemistry) were collected. Logistic regression and random forest analyses were conducted to develop Multimodal DCIS-Net to calculate the specificity, sensitivity, accuracy, receiver operating characteristic curve, and area under the curve (AUC). RESULTS: In the test set of N1, the accuracy and AUC of the multimodal DCIS-Net were 0.752-0.766 and 0.859-0.907 in the three-classification task, respectively. The accuracy and AUC for discriminating DCIS from upstaged DCIS were 0.751-0.780 and 0.829-0.861, respectively. In the test set of N2, the accuracy and AUC of discriminating low-grade DCIS from upstaged low-grade DCIS were 0.769-0.987 and 0.818-0.939, respectively. DL was ranked from one to five in the importance of features in the multimodal-DCIS-Net. CONCLUSION: By developing the DCIS-Net and integrating it with multimodal information, diagnosing low-grade DCIS, intermediate-to high-grade DCIS, and upstaged DCIS is possible. It can also be used to distinguish DCIS from upstaged DCIS and low-grade DCIS from upstaged low-grade DCIS, which could pave the way for the DCIS clinical workflow.

Dexmedetomidine alleviates cognitive impairment by promoting hippocampal neurogenesis via BDNF/TrkB/CREB signaling pathway in hypoxic-ischemic neonatal rats.

AIMS: Dexmedetomidine (DEX) has been reported to alleviate hypoxic-ischemic brain damage (HIBD) in neonates. This study aimed to investigate whether DEX improves cognitive impairment by promoting hippocampal neurogenesis via the BDNF/TrkB/CREB signaling pathway in neonatal rats with HIBD. METHODS: HIBD was induced in postnatal day 7 rats using the Rice-Vannucci method, and DEX (25 µg/kg) was administered intraperitoneally immediately after the HIBD induction. The BDNF/TrkB/CREB pathway was regulated by administering the TrkB receptor antagonist ANA-12 through intraperitoneal injection or by delivering adeno-associated virus (AAV)-shRNA-BDNF via intrahippocampal injection. Western blot was performed to measure the levels of BDNF, TrkB, and CREB. Immunofluorescence staining was utilized to identify the polarization of astrocytes and evaluate the levels of neurogenesis in the dentate gyrus of the hippocampus. Nissl and TTC staining were performed to evaluate the extent of neuronal damage. The MWM test was conducted to evaluate spatial learning and memory ability. RESULTS: The levels of BDNF and neurogenesis exhibited a notable decrease in the hippocampus of neonatal rats after HIBD, as determined by RNA-sequencing technology. Our results demonstrated that treatment with DEX effectively increased the protein expression of BDNF and the phosphorylation of TrkB and CREB, promoting neurogenesis in the dentate gyrus of the hippocampus in neonatal rats with HIBD. Specifically, DEX treatment significantly augmented the expression of BDNF in hippocampal astrocytes, while decreasing the proportion of detrimental A1 astrocytes and increasing the proportion of beneficial A2 astrocytes in neonatal rats with HIBD. Furthermore, inhibiting the BDNF/TrkB/CREB pathway using either ANA-12 or AAV-shRNA-BDNF significantly counteracted the advantageous outcomes of DEX on hippocampal neurogenesis, neuronal survival, and cognitive improvement. CONCLUSIONS: DEX promoted neurogenesis in the hippocampus by activating the BDNF/TrkB/CREB pathway through the induction of polarization of A1 astrocytes toward A2 astrocytes, subsequently mitigating neuronal damage and cognitive impairment in neonates with HIBD.