3D-CEUS/MRI-CEUS fusion imaging vs 2D-CEUS after locoregional therapies for hepatocellular carcinoma: a multicenter prospective study of therapeutic response evaluation.

OBJECTIVES: To compare the diagnostic accuracy of 3D contrast-enhanced ultrasound (CEUS)/MRI-CEUS fusion imaging with 2D-CEUS in assessing the response of hepatocellular carcinoma (HCC) to locoregional therapies in a multicenter prospective study. MATERIALS AND METHODS: A consecutive series of patients with HCC scheduled for locoregional treatment were enrolled between April 2021 and March 2023. Patients were randomly divided into 3D-CEUS/MRI-CEUS fusion imaging group (3D/fusion group) or 2D-CEUS group (2D group). CEUS was performed 1 week before and 4-6 weeks after locoregional treatment. Contrast-enhanced MRI (CE-MRI) 4-6 weeks after treatment was set as the reference standard. CEUS images were evaluated for the presence or absence of viable tumors. Diagnostic performance criteria, including sensitivity, specificity, accuracy, and area under the curve (AUC), were determined for each modality. RESULTS: A total of 140 patients were included, 70 patients in the 2D group (mean age, 60.2 ± 10.4 years) and 70 patients in the 3D/fusion group (mean age, 59.8 ± 10.6 years). The sensitivity of the 3D/fusion group was 100.0% (95% CI: 75.9, 100.0), higher than that of the 2D group (55.6%, 95% CI: 22.7, 84.7; p = 0.019). The specificity of the 3D/fusion group was 96.3% (95% CI: 86.2, 99.4), which was comparable to that of the 2D group (98.4%, 95% CI: 90.0, 99.9; p = 0.915). The AUC of the 3D/fusion group was 0.98 (95% CI: 0.95, 1.00), higher than that of the 2D group (0.77, 95% CI: 0.56, 0.98; p = 0.020). CONCLUSION: 3D-CEUS/MRI-CEUS fusion imaging exhibits superior diagnostic accuracy in evaluating the treatment response to locoregional therapies for HCC. CLINICAL RELEVANCE STATEMENT: 3D-CEUS/MRI-CEUS fusion imaging can be applied for post-treatment assessment of residual tumors in HCC undergoing locoregional treatment, offering potential benefits in terms of accurate diagnosis and clinical management. KEY POINTS: Evaluating for HCC recurrence following locoregional therapy is important. 3D-CEUS/MRI-CEUS fusion imaging achieved a higher sensitivity than 2D-CEUS in assessing residual tumors after locoregional therapies. 3D-CEUS/MRI-CEUS fusion imaging can help clinicians intervene early in residual HCC lesions after locoregional treatment.

Controlled Twill Surface Structure Endowing Nanofiber Composite Membrane Excellent Electromagnetic Interference Shielding.

Inspired by the Chinese Knotting weave structure, an electromagnetic interference (EMI) nanofiber composite membrane with a twill surface was prepared. Poly(vinyl alcohol-co-ethylene) (Pva-co-PE) nanofibers and twill nylon fabric were used as the matrix and filter templates, respectively. A Pva-co-PE-MXene/silver nanowire (Pva-co-PE-MXene/AgNW, PMxAg) membrane was successfully prepared using a template method. When the MXene/AgNW content was only 7.4 wt% (PM7.4Ag), the EMI shielding efficiency (SE) of the composite membrane with the oblique twill structure on the surface was 103.9 dB and the surface twill structure improved the EMI by 38.5%. This result was attributed to the pre-interference of the oblique twill structure in the direction of the incident EM wave, which enhanced the probability of the electromagnetic waves randomly colliding with the MXene nanosheets. Simultaneously, the internal reflection and ohmic and resonance losses were enhanced. The PM7.4Ag membrane with the twill structure exhibited both an outstanding tensile strength of 22.8 MPa and EMI SE/t of 3925.2 dB cm-1. Moreover, the PMxAg nanocomposite membranes demonstrated an excellent thermal management performance, hydrophobicity, non-flammability, and performance stability, which was demonstrated by an EMI SE of 97.3% in a high-temperature environment of 140 °C. The successful preparation of surface-twill composite membranes makes it difficult to achieve both a low filler content and a high EMI SE in electromagnetic shielding materials. This strategy provides a new approach for preparing thin membranes with excellent EMI properties.

External fistula internalization - Endoscopic ultrasound guided stent implantation between stomach and fistula in the treatment of refractory pancreatic cutaneous fistula.

Pancreatic cutaneous fistula is a complex condition, making it challenging to achieve favorable outcomes with conservative medical treatment. Surgical interventions often entail surgical risks and postoperative complications. Here, we present a case involving endoscopically guided stent placement between the stomach and the fistula. By internalizing the fistula, patients can potentially remove the external drainage tube, offering a novel endoscopic treatment approach for such cases.

Unexpected finding: a patient with choledocholithiasis found mass at the lower end of common bile duct.

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Study on the value of Inhibin B in the diagnosis of nasopharyngeal carcinoma and its correlation with traditional Chinese medicine syndromes: An observational study.

To investigate the expression of Inhibin B between various clinical stages, Chinese medicine dialectic typing, and in nasopharyngeal carcinoma (NPC) tissues and serum, and to evaluate the potential of Inhibin B as a new biomarker for NPC. Paraffin specimens of pathologically confirmed NPC tissues and paracancerous tissues were retrospectively collected, and the expression of Inhibin α (INHA) and Inhibin ßB (INHBB) was detected by SP method, and their relationship with clinicopathological indexes was analyzed; in addition, patients with NPC who had received radiotherapy were included as the study subjects, and Epstein-Barr virus DNA (EBV-DNA), INHA, and INHBB in patients were detected by using the fluorescence quantitative polymerase chain reaction, enzyme-linked immunosorbent assay, and chemiluminescent immuno-sandwiching method, respectively. EBV-DNA, EBV-viral capsid antigen-immunoglobulin A (VCA IgA), INHA, and INHBB were detected in the patients, respectively, and their relationships with traditional Chinese medicine (TCM) patterns were also analyzed. The expression of INHA and INHBB in NPC tissues was lower than that in paracancerous tissues, and the expression of INHA in NPC patients was correlated with lymphatic metastasis, clinical staging, and TCM staging; the levels of EBV-DNA and VCA IgA were higher than that of healthy populations in NPC patients and were higher than that of patients with stage III + IV than that of patients with stage I + II, and the levels of INHA and INHBB were lower than those of healthy populations and were lower than those of patients with stage III + IV than that of patients with stage I + II. The levels of INHA and INHBB in nasopharyngeal cancer patients were lower than those in healthy people, and the levels in stage III + IV patients were lower than those in stage I + II patients. The levels of EBV-DNA and VCA IgA in nasopharyngeal cancer patients were correlated with the Chinese medicine patterns, and had different patterns. The expression of Inhibin B may be related to the progression of NPC, and it has certain typing significance for different TCM syndromes of NPC, which is helpful for TCM typing diagnosis.

Multimode Ultrasound Model for Predicting the Early Treatment Response of Anti-VEGF Agents Plus Anti-PD-1 Antibody in Patients with Unresectable Hepatocellular Carcinoma.

OBJECTIVE: The purpose of the study described was to establish prediction models to initially screen the beneficiary patients with unresectable hepatocellular carcinoma (HCC) in the treatment of anti-vascular endothelial growth factor (VEGF) agents plus anti-programmed cell death-1 (PD-1) antibody. METHODS: A total of 62 patients were enrolled in this study. All patients underwent ultrasound (US), color ddoppler flowing imaging (CDFI), contrast-enhanced ultrasound (CEUS) and laboratory examinations within 2 wk before the treatment. Tumor response was assessed according to mRECIST criteria. Univariate and multivariate analyses were used to select the independent predictors. US + CDFI, CEUS and FULL models were established. Three models were displayed by nomography. Receiver operating characteristic (ROC) and calibration curves were drawn to evaluate the predictive ability of models. Decision curve analysis (DCA) was used to assess the clinical utility of models. RESULTS: On univariate and multivariate analysis, the US boundary (p = 0.037), halo (p = 0.002) and CDFI (p = 0.024) were included in the US + CDFI model. CEUS boundary (p = 0.001) and washout time (p < 0.001) were included in the CEUS model. The number of lesions (p = 0.104), halo on US (p = 0.014), CDFI (p = 0.057) and washout time on CEUS (p = 0.015) were incorporated into the FULL model. The C indices of the US + CDFI, CEUS and FULL models were 0.918, 0.920 and 0.973. CEUS and FULL models yielded a good net benefit for almost all threshold probabilities. CONCLUSION: Nomograms based on US, CDFI, CEUS and clinical characteristics could help to non-invasively predict the response to treatment with anti-PD-1 antibodies plus anti-VEGF agents.

The lethal K18-hACE2 knock-in mouse model mimicking the severe pneumonia of COVID-19 is practicable for antiviral development.

Animal models of COVID-19 facilitate the development of vaccines and antivirals against SARS-CoV-2. The efficacy of antivirals or vaccines may differ in different animal models with varied degrees of disease. Here, we introduce a mouse model expressing human angiotensin-converting enzyme 2 (ACE2). In this model, ACE2 with the human cytokeratin 18 promoter was knocked into the Hipp11 locus of C57BL/6J mouse by CRISPR - Cas9 (K18-hACE2 KI). Upon intranasal inoculation with high (3 × 105 PFU) or low (2.5 × 102 PFU) dose of SARS-CoV-2 wildtype (WT), Delta, Omicron BA.1, or Omicron BA.2 variants, all mice showed obvious infection symptoms, including weight loss, high viral loads in the lung, and interstitial pneumonia. 100% lethality was observed in K18-hACE2 KI mice infected by variants with a delay of endpoint for Delta and BA.1, and a significantly attenuated pathogenicity was observed for BA.2. The pneumonia of infected mice was accompanied by the infiltration of neutrophils and pulmonary fibrosis in the lung. Compared with K18-hACE2 Tg mice and HFH4-hACE2 Tg mice, K18-hACE2 KI mice are more susceptible to SARS-CoV-2. In the antivirals test, REGN10933 and Remdesivir had limited antiviral efficacies in K18-hACE2 KI mice upon the challenge of SARS-CoV-2 infections, while Nirmatrelvir, monoclonal antibody 4G4, and mRNA vaccines potently protected the mice from death. Our results suggest that the K18-hACE2 KI mouse model is lethal and stable for SARS-CoV-2 infection, and is practicable and stringent to antiviral development.

[A multicenter study of neonatal stroke in Shenzhen, China]. / 深圳市新生儿脑卒中多中心现况调查.

OBJECTIVES: To investigate the incidence rate, clinical characteristics, and prognosis of neonatal stroke in Shenzhen, China. METHODS: Led by Shenzhen Children's Hospital, the Shenzhen Neonatal Data Collaboration Network organized 21 institutions to collect 36 cases of neonatal stroke from January 2020 to December 2022. The incidence, clinical characteristics, treatment, and prognosis of neonatal stroke in Shenzhen were analyzed. RESULTS: The incidence rate of neonatal stroke in 21 hospitals from 2020 to 2022 was 1/15 137, 1/6 060, and 1/7 704, respectively. Ischemic stroke accounted for 75% (27/36); boys accounted for 64% (23/36). Among the 36 neonates, 31 (86%) had disease onset within 3 days after birth, and 19 (53%) had convulsion as the initial presentation. Cerebral MRI showed that 22 neonates (61%) had left cerebral infarction and 13 (36%) had basal ganglia infarction. Magnetic resonance angiography was performed for 12 neonates, among whom 9 (75%) had involvement of the middle cerebral artery. Electroencephalography was performed for 29 neonates, with sharp waves in 21 neonates (72%) and seizures in 10 neonates (34%). Symptomatic/supportive treatment varied across different hospitals. Neonatal Behavioral Neurological Assessment was performed for 12 neonates (33%, 12/36), with a mean score of (32±4) points. The prognosis of 27 neonates was followed up to around 12 months of age, with 44% (12/27) of the neonates having a good prognosis. CONCLUSIONS: Ischemic stroke is the main type of neonatal stroke, often with convulsions as the initial presentation, involvement of the middle cerebral artery, sharp waves on electroencephalography, and a relatively low neurodevelopment score. Symptomatic/supportive treatment is the main treatment method, and some neonates tend to have a poor prognosis.

Striatal Functional Alterations Link to Distinct Symptomatology Across Mood States in Bipolar Disorder.

BACKGROUND: As a central hub in cognitive and emotional brain circuits, the striatum is considered likely to be integrally involved in the psychopathology of bipolar disorder (BD). However, it remains unclear how alterations in striatal function contribute to distinct symptomatology of BD during different mood states. METHODS: Behavioral assessment (i.e., emotional symptoms and cognitive performance) and neuroimaging data were collected from 125 participants comprising 31 (hypo)manic, 31 depressive, and 31 euthymic patients with BD, and 32 healthy control participants. We compared the functional connectivity (FC) of striatal subregions across BD mood states with healthy control participants and then used a multivariate data-driven approach to explore dimensional associations between striatal connectivity and behavioral performance. Finally, we compared the FC and behavioral composite scores, which reflect the individual weighted representation of the associations, among different mood states. RESULTS: Patients in all mood states exhibited increased FC between the bilateral ventral rostral putamen and ventrolateral thalamus. Bipolar (hypo)mania uniquely exhibited increased ventral rostral putamen connectivity and superior ventral striatum connectivity. One latent component was identified, whereby increased FCs of striatal subregions were associated with distinct psychopathological symptomatology (more manic symptoms, elevated positive mood, less depressive symptoms, and worse cognitive performance). Patients with bipolar (hypo)mania had the highest FC and behavioral composite scores while bipolar patients with depression had the lowest scores. CONCLUSIONS: Our data demonstrated both trait features of BD and state features specific to bipolar (hypo)mania. The findings underscored the fundamental role of the striatum in the pathophysiological processes underlying specific symptomatology across all mood states.

Transcriptomic and neuroimaging data integration enhances machine learning classification of schizophrenia.

Background: Schizophrenia is a polygenic disorder associated with changes in brain structure and function. Integrating macroscale brain features with microscale genetic data may provide a more complete overview of the disease etiology and may serve as potential diagnostic markers for schizophrenia. Objective: We aim to systematically evaluate the impact of multi-scale neuroimaging and transcriptomic data fusion in schizophrenia classification models. Methods: We collected brain imaging data and blood RNA sequencing data from 43 patients with schizophrenia and 60 age- and gender-matched healthy controls, and we extracted multi-omics features of macroscale brain morphology, brain structural and functional connectivity, and gene transcription of schizophrenia risk genes. Multi-scale data fusion was performed using a machine learning integration framework, together with several conventional machine learning methods and neural networks for patient classification. Results: We found that multi-omics data fusion in conventional machine learning models achieved the highest accuracy (AUC ~0.76-0.92) in contrast to the single-modality models, with AUC improvements of 8.88 to 22.64%. Similar findings were observed for the neural network, showing an increase of 16.57% for the multimodal classification model (accuracy 71.43%) compared to the single-modal average. In addition, we identified several brain regions in the left posterior cingulate and right frontal pole that made a major contribution to disease classification. Conclusion: We provide empirical evidence for the increased accuracy achieved by imaging genetic data integration in schizophrenia classification. Multi-scale data fusion holds promise for enhancing diagnostic precision, facilitating early detection and personalizing treatment regimens in schizophrenia.

Longitudinal ultrasound-based AI model predicts axillary lymph node response to neoadjuvant chemotherapy in breast cancer: a multicenter study.

OBJECTIVES: Developing a deep learning radiomics model from longitudinal breast ultrasound and sonographer's axillary ultrasound diagnosis for predicting axillary lymph node (ALN) response to neoadjuvant chemotherapy (NAC) in breast cancer. METHODS: Breast cancer patients undergoing NAC followed by surgery were recruited from three centers between November 2016 and December 2022. We collected ultrasound images for extracting tumor-derived radiomics and deep learning features, selecting quantitative features through various methods. Two machine learning models based on random forest were developed using pre-NAC and post-NAC features. A support vector machine integrated these data into a fusion model, evaluated via the area under the curve (AUC), decision curve analysis, and calibration curves. We compared the fusion model's performance against sonographer's diagnosis from pre-NAC and post-NAC axillary ultrasonography, referencing histological outcomes from sentinel lymph node biopsy or axillary lymph node dissection. RESULTS: In the validation cohort, the fusion model outperformed both pre-NAC (AUC: 0.899 vs. 0.786, p < 0.001) and post-NAC models (AUC: 0.899 vs. 0.853, p = 0.014), as well as the sonographer's diagnosis of ALN status on pre-NAC and post-NAC axillary ultrasonography (AUC: 0.899 vs. 0.719, p < 0.001). Decision curve analysis revealed patient benefits from the fusion model across threshold probabilities from 0.02 to 0.98. The model also enhanced sonographer's diagnostic ability, increasing accuracy from 71.9% to 79.2%. CONCLUSION: The deep learning radiomics model accurately predicted the ALN response to NAC in breast cancer. Furthermore, the model will assist sonographers to improve their diagnostic ability on ALN status before surgery. CLINICAL RELEVANCE STATEMENT: Our AI model based on pre- and post-neoadjuvant chemotherapy ultrasound can accurately predict axillary lymph node metastasis and assist sonographer's axillary diagnosis. KEY POINTS: Axillary lymph node metastasis status affects the choice of surgical treatment, and currently relies on subjective ultrasound. Our AI model outperformed sonographer's visual diagnosis on axillary ultrasound. Our deep learning radiomics model can improve sonographers' diagnosis and might assist in surgical decision-making.

Exploring the transformative impact of traditional Chinese medicine on depression: Insights from animal models.

Depression, a prevalent and complex mental health condition, presents a significant global health burden. Depression is one of the most frequent mental disorders; deaths from it account for 14.3% of people worldwide. In recent years, the integration of complementary and alternative medicine, including traditional Chinese medicine (TCM), has gained attention as a potential avenue for addressing depression. This comprehensive review critically assesses the efficacy of TCM interventions in alleviating depressive symptoms. An in-depth look at different research studies, clinical trials, and meta-analyses is used in this review to look into how TCM practices like herbal formulations, acupuncture, and mind-body practices work. The review looks at the quality of the evidence, the rigor of the methods, and any possible flaws in the current studies. This gives us an idea of where TCM stands right now in terms of treating depression. This comprehensive review aims to assess the efficacy of TCM interventions in alleviating depressive symptoms. In order to learn more about their possible healing effects, the study also looks into how different types of TCM work, such as herbal formulas, acupuncture, and mind-body practices.

Sinomenine protects against atherosclerosis in apolipoprotein E-knockout mice by inhibiting of inflammatory pathway.

Atherosclerosis, a multifaceted and persistent inflammatory condition, significantly contributes to the progression of cardiocerebrovascular disorders, such as myocardial infarctions and cerebrovascular accidents. It involves the accumulation of cholesterol, fatty deposits, calcium and cellular debris in the walls of arteries, leading to the formation of plaques. Our aim is to investigate the potential of sinomenine to counteract atherosclerosis in mice lacking Apolipoprotein E (ApoE-/-) Mice. We employed the high-fat diet-induced method to induce atherosclerosis in ApoE-/- mice, and the mice were treated with sinomenine (5, 10, and 15 mg/kg) and simvastatin (0.5 mg/kg) for 12 weeks. Body weight, water intake, and food intake were assessed. Lipid parameters, oxidative stress, inflammatory cytokines, and mRNA levels were estimated. Sinomenine treatment remarkably (P < 0.001) suppressed body weight, along with food and water intake. Sinomenine altered the levels of total cholesterol (TC), high-density lipoprotein (HDL), triglyceride (TG), low-density lipoprotein (LDL), and very low-density lipoprotein (VLDL), which were modulated in the atherosclerosis group. Sinomenine treatment also altered the levels of oxidative stress parameters such as glutathione peroxidase (GPx), catalase (CAT), malonaldehyde (MDA), superoxide dismutase (SOD) and glutathione (GSH). In addition, it modulated cardiac parameters like C-reactive protein (CRP), endothelin-1 (ET-1), thromboxane B2 (TXB2), nitric oxide (NO), cardiac troponin I (cTnI), lactate dehydrogenase (LDH), and creatinine kinase isoenzymes (CK-MB). Inflammatory cytokines interleukin (IL)-1α, IL-1ß, TNF-α, IL-6, and IL-10 were also affected. Sinomenine further suppressed the mRNA expression of IL-6, IL-17, IL-10, tumor necrosis factor-α (TNF-α), Il-1ß, monocyte chemoattractant protein-1 (MCP-1), MCP-2, MCP-3, transforming Growth Factor-1ß (TGF-1ß), vascular cell adhesion molecule 1 (VCAM-1), and intercellular adhesion molecule-1 (ICAM-1). The results suggest that sinomenine remarkably suppressed the development of atherosclerosis in the early stage.

Circ_0020460 drives tumorigenesis in cervical cancer through miR-485-3p sponging.

Deregulation of circular RNAs (circRNAs) is widely recognized in cancer progression. Our study aims to investigate the role of circ_0020460 in the development of cervical cancer (CC) and its potential mechanism of action. Quantitative real-time polymerase chain reaction (qRT-PCR) and western blot assays were used to detect the expression levels of circ_0020460, miR-485-3p and C-X-C motif chemokine ligand 1 (CXCL1). The roles of circ_0020460 on cell proliferation, cell migration, cell invasion, cell apoptosis, and angiogenesis were investigated using cell counting kit-8 (CCK-8) and Ethynyl deoxyuridine (Edu) assay, wound healing assay, transwell assay, flow cytometry assay, and tube formation assay, respectively. The putative relationship predicted by bioinformatics analysis was verified by dual-luciferase reporter assay and RNA immunoprecipitation (RIP) assay. Xenograft models were constructed to explore the role of circ_0020460 in vivo. The expression of circ_0020460 and CXCL1 expression were increased, while miR-485-3p expression was declined in CC tissues and cells. Circ_0020460 knockdown suppressed CC cell proliferation, cell migration, cell invasion, angiogenesis, and promoted cell apoptosis. Circ_0020460 functioned as a miR-485-3p sponge to inhibit miR-485-3p level, and the anti-cancer effects mediated by circ_0020460 knockdown were reversed by miR-485-3p inhibitor. MiR-485-3p bound to CXCL1 3' untranslated region (3'UTR) to degrade CXCL1 expression, and the anti-cancer effects of miR-485-3p restoration were impaired by CXCL1 overexpression. Circ_0020460 downregulation inhibited CC xenograft tumor growth. These results suggest that circ_0020460 promoted the malignant behavior of CC cells by modulating the miR-485-3p/CXCL1 axis.

A distinctive subcortical functional connectivity pattern linking negative affect and treatment outcome in major depressive disorder.

Major depressive disorder (MDD) is associated with functional disturbances in subcortical regions. In this naturalistic prospective study (NCT03294525), we aimed to investigate relationships among subcortical functional connectivity (FC), mood symptom profiles and treatment outcome in MDD using multivariate methods. Medication-free participants with MDD (n = 135) underwent a functional magnetic resonance imaging scan at baseline and completed posttreatment clinical assessment after 8 weeks of antidepressant monotherapy. We used partial least squares (PLS) correlation analysis to explore the association between subcortical FC and mood symptom profiles. FC score, reflecting the weighted representation of each individual in this association, was computed. Replication analysis was undertaken in an independent sample (n = 74). We also investigated the relationship between FC score and treatment outcome in the main sample. A distinctive subcortical connectivity pattern was found to be associated with negative affect. In general, higher FC between the caudate, putamen and thalamus was associated with greater negative affect. This association was partly replicated in the independent sample (similarity between the two samples: r = 0.66 for subcortical connectivity, r = 0.75 for mood symptom profile). Lower FC score predicted both remission and response to treatment after 8 weeks of antidepressant monotherapy. The emphasis here on the role of dorsal striatum and thalamus consolidates prior work of subcortical connectivity in MDD. The findings provide insight into the pathogenesis of MDD, linking subcortical FC with negative affect. However, while the FC score significantly predicted treatment outcome, the low odds ratio suggests that finding predictive biomarkers for depression remains an aspiration.

Time-varying gain extended state observer-based adaptive optimal control for disturbed unmanned helicopter.

In this paper, the robust adaptive optimal tracking control problem is addressed for the disturbed unmanned helicopter based on the time-varying gain extended state observer (TVGESO) and adaptive dynamic programming (ADP) methods. Firstly, a novel TVGESO is developed to tackle the unknown disturbance, which can overcome the drawback of initial peaking phenomenon in the traditional linear ESO method. Meanwhile, compared with the nonlinear ESO, the proposed TVGESO possesses easier and rigorous stability analysis process. Subsequently, the optimal tracking control issue for the original unmanned helicopter system is transformed into an optimization stabilization problem. By means of the ADP and neural network techniques, the feedforward controller and optimal feedback controller are skillfully designed. Compared with the conventional backstepping approach, the designed anti-disturbance optimal controller can make the unmanned helicopter accomplish the tracking task with less energy. Finally, simulation comparisons demonstrate the validity of the developed control scheme.

Predictive nomograms of repeat intrahepatic recurrence and overall survival after radiofrequency ablation of recurrent colorectal liver metastases.

OBJECTIVES: This study was conducted to develop nomograms for predicting repeat intrahepatic recurrence (rIHR) and overall survival (OS), after radiofrequency ablation (RFA), treatment in patients with recurrent colorectal liver metastases (CLMs) after hepatectomy based on clinicopathologic features. METHODS: A total of 160 consecutive patients with recurrent CLMs after hepatectomy who were treated with ultrasound-guided percutaneous RFA from 2012 to 2022 were retrospectively included. Patients were randomly divided into a training cohort and a validation cohort, with a ratio of 8:2. Potential prognostic factors associated with rIHR and OS, after RFA, were identified by using the competing-risks and Cox proportional hazard models, respectively, and were used to construct the nomogram. The nomogram was evaluated by Harrell's C-index and a calibration curve. RESULTS: The 1-, 2-, and 3-year rIHR rates after RFA were 58.8%, 70.2%, and 74.2%, respectively. The 1-, 3- and 5-year OS rates were 96.3%, 60.4%, and 38.5%, respectively. In the multivariate analysis, mutant RAS, interval from hepatectomy to intrahepatic recurrence ≤ 12 months, CEA level >5 ng/ml, and ablation margin <5 mm were the independent predictive factors for rIHR. Mutant RAS, largest CLM at hepatectomy >3 cm, CEA level >5 ng/ml, and extrahepatic disease were independent predictors of poor OS. Two nomograms for rIHR and OS were constructed using the respective significant variables. In both cohorts, the nomogram demonstrated good discrimination and calibration. CONCLUSIONS: The established nomograms can predict individual risk of rIHR and OS after RFA for recurrent CLMs and contribute to improving individualized management.

Automated highway pavement crack recognition under complex environment.

The pavement is vulnerable to damage from natural disasters, accidents and other human factors, resulting in the formation of cracks. Periodic pavement monitoring can facilitate prompt detection and repair the pavement diseases, thereby minimizing casualties and property losses. Due to the presence of numerous interferences, recognizing highway pavement cracks in complex environments poses a significant challenge. Nevertheless, several computer vision approaches have demonstrated notable success in tackling this issue. We have employed a novel approach for crack recognition utilizing the ResNet34 model with a convolutional block attention module (CBAM), which not only saves parameters and computing power but also ensures seamless integration of the module as a plug-in. Initially, ResNet18, ResNet34, and ResNet50 models were trained by employing transfer learning techniques, with the ResNet34 network being selected as a fundamental model. Subsequently, CBAM was integrated into ResBlock and further training was conducted. Finally, we calculated the precision, average recall on the test set, and the recall of each class. The results demonstrate that by integrating CBAM into the ResNet34 network, the model exhibited improved test accuracy and average recall compared to its previous state. Moreover, our proposed model outperformed all other models in terms of performance. The recall rates for transverse crack, longitudinal crack, map crack, repairing, and pavement marking were 88.8%, 86.8%, 88.5%, 98.3%, and 99.9%, respectively. Our model achieves the highest precision of 92.9% and the highest average recall of 92.5%. However, the effectiveness in detecting mesh cracks was found to be unsatisfactory, despite their significant prevalence. In summary, the proposed model exhibits great potential for crack identification and serves as a crucial foundation for highway maintenance.

A novel nomogram for prediction of intrahepatic recurrence-free survival in patients with HCC followed by radiofrequency ablation.

OBJECTIVE: Although radiofrequency ablation (RFA) has been considered as the favourable treatment option for hepatocellular carcinoma (HCC), there still exist some challenges for new recurrence after RFA. The present study aims to determine the factors affecting recurrence and develop an effective model to predict intrahepatic recurrence-free survival (RFS). METHODS: Patients with HCC followed by RFA between 2000 and 2021 were included in this study. Multivariable Cox regression analysis was used to determine the independent prognostic factors and establish the nomogram predicting intrahepatic RFS after RFA. The predictive performance of the nomogram was assessed according to the C-index, calibration plots, and Kaplan-Meier curves stratified by the tertiles. RESULTS: A total of 801 sessions in 660 patients (including 1155 lesions) were enrolled into this study. Intrahepatic new recurrence was observed in all patients during the follow-up, and the mean intrahepatic RFS was 21.9 months in the present cohort. According to multivariate COX regression analysis, five independent prognostic factors affecting intrahepatic RFS were determined, including age, Child-Pugh class, tumour distribution, number of tumours, and a-fetoprotein (AFP). Based on all independent prognostic factors, the nomogram model was developed and evaluated, which achieved favourable discrimination and calibration. CONCLUSION: This study established five independent prognostic factors and constructed a nomogram model to predict intrahepatic RFS for HCC patients followed by RFA. It could better help clinicians select RFA candidates, as well as offering the important information about whether patients need receive comprehensive treatment to prevent new recurrence after RFA. ADVANCES IN KNOWLEDGE: (1) In this study, 5 preoperative clinic-pathological variables were determined as the independent prognostic factors affecting RFS after RFA in the current largest sample size. (2) Based on these independent prognostic factors, a prognostic nomogram predicting RFS after RFA was established, which may be used to select patients who benefit from RFA and could help both surgeons and patients provide useful information for choosing the personalized treatment.